From 60b8c13da12e7d55196a5c4a4f16d982184d16b8 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 15:59:27 +0000
Subject: [PATCH 01/48] feat(ir): define joint summary observation coverage

---
 crates/types/src/ir/mod.rs              |   3 +
 crates/types/src/ir/node.rs             |  35 +++++++
 crates/types/src/ir/summary_coverage.rs | 125 ++++++++++++++++++++++++
 crates/types/tests/summary_coverage.rs  | 121 +++++++++++++++++++++++
 docs/develop_docs/summary-coverage.md   |  35 +++++++
 5 files changed, 319 insertions(+)
 create mode 100644 crates/types/src/ir/summary_coverage.rs
 create mode 100644 crates/types/tests/summary_coverage.rs
 create mode 100644 docs/develop_docs/summary-coverage.md

diff --git a/crates/types/src/ir/mod.rs b/crates/types/src/ir/mod.rs
index d20bfd075..fcb2eb49b 100644
--- a/crates/types/src/ir/mod.rs
+++ b/crates/types/src/ir/mod.rs
@@ -15,3 +15,6 @@ pub use node::{Operator, OperatorNode, OperatorResultKind};
 pub use non_asap::{BinaryOperator, NonASAPOp, TimeRangeKind};
 pub use query::QueryRoot;
 pub use scalar::{ExprSemantics, Predicate, ProjectItem, ScalarExpr, SortKey};
+
+/// Semantic observation coverage, separate from field layout and physical timing.
+pub mod summary_coverage;
diff --git a/crates/types/src/ir/node.rs b/crates/types/src/ir/node.rs
index d68f5aa03..e37ccf906 100644
--- a/crates/types/src/ir/node.rs
+++ b/crates/types/src/ir/node.rs
@@ -95,6 +95,8 @@ pub struct OperatorNode {
     pub schema: Schema,
     pub guarantee: Option<ResultGuarantee>,
     pub timing: Option<ExecutionTiming>,
+    #[serde(default)]
+    pub summary_coverage: Option<super::summary_coverage::SummaryCoverage>,
 }
 
 impl OperatorNode {
@@ -117,6 +119,7 @@ impl OperatorNode {
             schema,
             guarantee: None,
             timing: None,
+            summary_coverage: None,
         }
     }
 
@@ -137,6 +140,33 @@ impl OperatorNode {
         self
     }
 
+    /// Attach caller-established observation coverage; unknown coverage remains None.
+    pub fn with_summary_coverage(
+        mut self,
+        coverage: super::summary_coverage::SummaryCoverage,
+    ) -> Result<Self, SchemaDerivationError> {
+        coverage
+            .validate()
+            .map_err(|error| SchemaDerivationError::InvalidScalarSignature(error.to_string()))?;
+        if self.result_kind != OperatorResultKind::State {
+            return Err(SchemaDerivationError::InvalidScalarSignature(
+                "summary coverage requires state output".into(),
+            ));
+        }
+        if let Some(ASAPOp::SummaryAgg {
+            input, reduction, ..
+        }) = self.asap()
+        {
+            if *input != coverage.input || *reduction != coverage.grouping {
+                return Err(SchemaDerivationError::InvalidScalarSignature(
+                    "coverage input/grouping disagrees with summary producer".into(),
+                ));
+            }
+        }
+        self.summary_coverage = Some(coverage);
+        Ok(self)
+    }
+
     pub fn non_asap(&self) -> Option<&NonASAPOp> {
         match &self.operator {
             Operator::NonASAP(op) => Some(op),
@@ -286,6 +316,11 @@ impl OperatorNode {
                     "invalid time or identity column in schema".into(),
                 ));
             }
+            if let Some(coverage) = &node.summary_coverage {
+                (*node.as_ref())
+                    .clone()
+                    .with_summary_coverage(coverage.clone())?;
+            }
             node.operator.validate_inputs()?;
             if node.result_kind != node.operator.output_kind() {
                 return Err(SchemaDerivationError::InvalidScalarSignature(
diff --git a/crates/types/src/ir/summary_coverage.rs b/crates/types/src/ir/summary_coverage.rs
new file mode 100644
index 000000000..e60ef3072
--- /dev/null
+++ b/crates/types/src/ir/summary_coverage.rs
@@ -0,0 +1,125 @@
+//! Joint time/population coverage for summary composition, independent of schema.
+//! Equality predicates are a deliberately narrow proof vocabulary. Unsupported
+//! predicates cannot be declared disjoint merely by giving them different names.
+use super::operator_properties::Reduction;
+use crate::post_asap::SummaryUpdate;
+use serde::{Deserialize, Serialize};
+use std::collections::BTreeMap;
+use thiserror::Error;
+
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+#[serde(deny_unknown_fields)]
+pub struct SummaryCoverage {
+    pub source: String,
+    pub revision: String,
+    pub input: SummaryUpdate,
+    pub grouping: Reduction,
+    pub multiplicity: ObservationMultiplicity,
+    /// Union of joint regions; never the Cartesian product of independent bounds.
+    pub regions: Vec<CoverageRegion>,
+}
+
+#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
+pub enum ObservationMultiplicity {
+    OncePerObservation,
+}
+
+#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
+#[serde(deny_unknown_fields)]
+pub struct CoverageRegion {
+    /// Half-open bounds on one canonical time axis, in milliseconds.
+    pub start_ms: i64,
+    pub end_ms: i64,
+    /// Conjunction of non-null equality predicates; empty means unrestricted.
+    pub population: BTreeMap<String, String>,
+}
+
+#[derive(Debug, Clone, PartialEq, Eq, Error)]
+pub enum CoverageError {
+    #[error("coverage requires explicit source and revision identity")]
+    MissingIdentity,
+    #[error("coverage interval must have start < end")]
+    InvalidInterval,
+    #[error("population dimension names cannot be empty")]
+    InvalidPopulation,
+    #[error("summary input identity, grouping or multiplicity differs")]
+    IncompatibleInput,
+    #[error("coverage overlap is not proven absent")]
+    PossibleOverlap,
+    #[error("coverage merge requires at least one input")]
+    EmptyMerge,
+}
+
+impl SummaryCoverage {
+    pub fn validate(&self) -> Result<(), CoverageError> {
+        if self.source.is_empty() || self.revision.is_empty() {
+            return Err(CoverageError::MissingIdentity);
+        }
+        for (index, region) in self.regions.iter().enumerate() {
+            if region.start_ms >= region.end_ms {
+                return Err(CoverageError::InvalidInterval);
+            }
+            if region.population.keys().any(String::is_empty) {
+                return Err(CoverageError::InvalidPopulation);
+            }
+            if self.regions[..index]
+                .iter()
+                .any(|other| region.may_overlap(other))
+            {
+                return Err(CoverageError::PossibleOverlap);
+            }
+        }
+        Ok(())
+    }
+
+    /// Compose once-per-observation summaries only when their joint regions are
+    /// provably disjoint. Family merge capability and accuracy are separate checks.
+    pub fn merge_disjoint(inputs: &[Self]) -> Result<Self, CoverageError> {
+        let first = inputs.first().ok_or(CoverageError::EmptyMerge)?;
+        let mut merged = first.clone();
+        merged.regions.clear();
+        for input in inputs {
+            input.validate()?;
+            if input.source != first.source
+                || input.revision != first.revision
+                || input.input != first.input
+                || input.grouping != first.grouping
+                || input.multiplicity != first.multiplicity
+            {
+                return Err(CoverageError::IncompatibleInput);
+            }
+            merged.regions.extend(input.regions.iter().cloned());
+        }
+        merged.validate()?;
+        // Coalesce adjacent intervals only for identical population predicates.
+        merged.regions.sort_by(|a, b| {
+            a.population
+                .cmp(&b.population)
+                .then(a.start_ms.cmp(&b.start_ms))
+        });
+        let mut normalized: Vec<CoverageRegion> = Vec::new();
+        for region in merged.regions {
+            if let Some(last) = normalized.last_mut() {
+                if last.population == region.population && last.end_ms == region.start_ms {
+                    last.end_ms = region.end_ms;
+                    continue;
+                }
+            }
+            normalized.push(region);
+        }
+        merged.regions = normalized;
+        Ok(merged)
+    }
+}
+impl CoverageRegion {
+    fn may_overlap(&self, other: &Self) -> bool {
+        self.start_ms < other.end_ms
+            && other.start_ms < self.end_ms
+            && !self.population.iter().any(|(dimension, value)| {
+                other
+                    .population
+                    .get(dimension)
+                    .is_some_and(|other| other != value)
+            })
+    }
+}
diff --git a/crates/types/tests/summary_coverage.rs b/crates/types/tests/summary_coverage.rs
new file mode 100644
index 000000000..246d6b0c8
--- /dev/null
+++ b/crates/types/tests/summary_coverage.rs
@@ -0,0 +1,121 @@
+//! Coverage composition preserves gaps and rejects duplicate observations.
+use asap_types::{
+    ir::operator_properties::Reduction, ir::summary_coverage::*, post_asap::SummaryUpdate,
+    pre_asap::ColumnRef,
+};
+fn coverage(start: i64, end: i64, population: &[(&str, &str)]) -> SummaryCoverage {
+    SummaryCoverage {
+        source: "flows".into(),
+        revision: "snapshot-1".into(),
+        input: SummaryUpdate::column(ColumnRef::Named("latency".into())),
+        grouping: Reduction::by(vec![0]),
+        multiplicity: ObservationMultiplicity::OncePerObservation,
+        regions: vec![CoverageRegion {
+            start_ms: start,
+            end_ms: end,
+            population: population
+                .iter()
+                .map(|(k, v)| (k.to_string(), v.to_string()))
+                .collect(),
+        }],
+    }
+}
+/// Adjacent panes coalesce; gaps remain disconnected rather than becoming a hull.
+#[test]
+fn time_union_preserves_gaps() {
+    let merged =
+        SummaryCoverage::merge_disjoint(&[coverage(0, 1, &[]), coverage(1, 2, &[])]).unwrap();
+    assert_eq!(merged.regions[0].end_ms, 2);
+    assert_eq!(merged.regions.len(), 1);
+    let gapped =
+        SummaryCoverage::merge_disjoint(&[coverage(0, 1, &[]), coverage(2, 3, &[])]).unwrap();
+    assert_eq!(gapped.regions.len(), 2);
+}
+/// Population partitions can overlap in time without sharing observations.
+#[test]
+fn population_and_joint_union() {
+    let merged = SummaryCoverage::merge_disjoint(&[
+        coverage(0, 2, &[("region", "us")]),
+        coverage(0, 2, &[("region", "eu")]),
+    ])
+    .unwrap();
+    assert_eq!(merged.regions.len(), 2);
+    let joint = SummaryCoverage::merge_disjoint(&[
+        coverage(0, 1, &[("region", "us")]),
+        coverage(1, 2, &[("region", "eu")]),
+    ])
+    .unwrap();
+    assert_eq!(joint.regions.len(), 2);
+    let decoded: SummaryCoverage =
+        serde_json::from_str(&serde_json::to_string(&joint).unwrap()).unwrap();
+    assert_eq!(decoded, joint);
+}
+/// Intersecting predicates and windows cannot authorize once-per-observation merge.
+#[test]
+fn overlap_and_identity_fail_closed() {
+    assert_eq!(
+        SummaryCoverage::merge_disjoint(&[coverage(0, 2, &[]), coverage(1, 3, &[])]),
+        Err(CoverageError::PossibleOverlap)
+    );
+    assert_eq!(
+        SummaryCoverage::merge_disjoint(&[
+            coverage(0, 2, &[("region", "us")]),
+            coverage(0, 2, &[("tier", "premium")])
+        ]),
+        Err(CoverageError::PossibleOverlap)
+    );
+    let mut other = coverage(1, 2, &[]);
+    other.revision = "snapshot-2".into();
+    assert_eq!(
+        SummaryCoverage::merge_disjoint(&[coverage(0, 1, &[]), other]),
+        Err(CoverageError::IncompatibleInput)
+    );
+    assert_eq!(
+        coverage(2, 1, &[]).validate(),
+        Err(CoverageError::InvalidInterval)
+    );
+}
+
+/// Coverage is logical state metadata, and input rewrites invalidate its proof.
+#[test]
+fn node_coverage_is_checked_and_rewrites_clear_it() {
+    use asap_types::{
+        ir::operator_properties::Source,
+        ir::{ASAPOp, NonASAPOp, Operator, OperatorNode},
+        post_asap::{SketchAlgorithm, SketchKind, SketchParams},
+        pre_asap::{DataType, Field, FieldDataType, Schema},
+    };
+    let raw = OperatorNode::new_shared(Operator::NonASAP(NonASAPOp::Scan {
+        source: Source::Table {
+            table_ref: "flows".into(),
+        },
+        predicates: vec![],
+        schema: Schema::new(vec![Field::plain("latency", DataType::Float64, false)]),
+    }))
+    .unwrap();
+    let mut declared = coverage(0, 1, &[]);
+    declared.grouping = Reduction::by(vec![]);
+    assert!((*raw)
+        .clone()
+        .with_summary_coverage(declared.clone())
+        .is_err());
+    let state = OperatorNode::new(Operator::ASAP(ASAPOp::SummaryAgg {
+        child: raw,
+        family: FieldDataType::Sketch(
+            SketchKind::new(SketchAlgorithm::Kll, SketchParams::Kll { k: 200 }),
+            Default::default(),
+        ),
+        input: declared.input.clone(),
+        reduction: declared.grouping.clone(),
+        grouping: Default::default(),
+        filter: None,
+    }))
+    .unwrap();
+    let state = state.with_summary_coverage(declared.clone()).unwrap();
+    assert!(state.summary_coverage.is_some());
+    let mut bad = declared;
+    bad.input = SummaryUpdate::column(ColumnRef::Named("other".into()));
+    assert!(state.clone().with_summary_coverage(bad).is_err());
+    let rebuilt = state.map_children(Clone::clone).unwrap();
+    assert!(rebuilt.summary_coverage.is_none());
+}
diff --git a/docs/develop_docs/summary-coverage.md b/docs/develop_docs/summary-coverage.md
new file mode 100644
index 000000000..2653d0426
--- /dev/null
+++ b/docs/develop_docs/summary-coverage.md
@@ -0,0 +1,35 @@
+# Summary coverage contract
+
+Schema describes field layout; summary coverage describes eligible observations.
+`OperatorNode.summary_coverage` is optional logical metadata. `None` means unknown,
+not unrestricted coverage. Rewriting inputs clears it along with other assessed
+metadata. `with_summary_coverage` validates declared coverage and checks state kind
+and SummaryAgg input/grouping agreement. Provenance is supplied by a trusted
+composition rule/catalog; this API does not infer predicates from arbitrary SQL.
+
+`SummaryCoverage` records source and revision identity, update expression,
+grouping, once-per-observation multiplicity and a union of joint `CoverageRegion`s.
+Each region pairs half-open time bounds in milliseconds with a conjunction of
+non-null equality predicates over canonical population dimensions. Source identity
+must include the time axis and observation-identity namespace. Revision identifies
+the input snapshot/update contract used to construct the state.
+
+`merge_disjoint` requires equal input identities and provably disjoint joint
+regions. Adjacent intervals coalesce only with identical population predicates;
+gaps remain separate. Conflicting equality predicates on the same dimension prove
+population disjointness. Independent predicates do not: region=US can overlap
+tier=premium. Different source/revision/input/grouping contracts fail.
+
+US×[0,1) merged with EU×[1,2) remains two regions, not
+{US,EU}×[0,2). This avoids inventing missing cross-population/time coverage.
+Empty regions describe empty observation coverage. Empty merge input is invalid.
+
+This contract supports conservative once-per-observation composition. Arbitrary
+predicates, null predicates, unbounded time coverage, idempotent set-union algebra,
+coverage inference and full requested-window containment need explicit extensions.
+It never labels unsupported/unknown predicates disjoint. It provides no runtime
+merge capability, accuracy certificate, storage policy or execution timing.
+
+The following merge PR must require known coverage, derive the output union and
+validate it rather than treating matching schemas as sufficient authorization.
+Logical transport and CSE must preserve and compare coverage metadata.

From c78855645184936014191feca907fe84750fe3e6 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 16:32:07 +0000
Subject: [PATCH 02/48] refactor(ir): name represented observations
 ObservationExtent

---
 crates/types/src/ir/mod.rs                    |  2 +-
 crates/types/src/ir/node.rs                   | 14 +++----
 ...mary_coverage.rs => observation_extent.rs} | 30 ++++++-------
 crates/types/src/post_asap/mod.rs             |  2 +-
 crates/types/src/post_asap/summary_window.rs  | 18 ++++----
 ...mary_coverage.rs => observation_extent.rs} | 42 +++++++++----------
 ...mary-coverage.md => observation-extent.md} | 18 ++++++--
 7 files changed, 68 insertions(+), 58 deletions(-)
 rename crates/types/src/ir/{summary_coverage.rs => observation_extent.rs} (84%)
 rename crates/types/tests/{summary_coverage.rs => observation_extent.rs} (74%)
 rename docs/develop_docs/{summary-coverage.md => observation-extent.md} (70%)

diff --git a/crates/types/src/ir/mod.rs b/crates/types/src/ir/mod.rs
index fcb2eb49b..45606611b 100644
--- a/crates/types/src/ir/mod.rs
+++ b/crates/types/src/ir/mod.rs
@@ -17,4 +17,4 @@ pub use query::QueryRoot;
 pub use scalar::{ExprSemantics, Predicate, ProjectItem, ScalarExpr, SortKey};
 
 /// Semantic observation coverage, separate from field layout and physical timing.
-pub mod summary_coverage;
+pub mod observation_extent;
diff --git a/crates/types/src/ir/node.rs b/crates/types/src/ir/node.rs
index e37ccf906..2a47f892c 100644
--- a/crates/types/src/ir/node.rs
+++ b/crates/types/src/ir/node.rs
@@ -96,7 +96,7 @@ pub struct OperatorNode {
     pub guarantee: Option<ResultGuarantee>,
     pub timing: Option<ExecutionTiming>,
     #[serde(default)]
-    pub summary_coverage: Option<super::summary_coverage::SummaryCoverage>,
+    pub observation_extent: Option<super::observation_extent::ObservationExtent>,
 }
 
 impl OperatorNode {
@@ -119,7 +119,7 @@ impl OperatorNode {
             schema,
             guarantee: None,
             timing: None,
-            summary_coverage: None,
+            observation_extent: None,
         }
     }
 
@@ -141,9 +141,9 @@ impl OperatorNode {
     }
 
     /// Attach caller-established observation coverage; unknown coverage remains None.
-    pub fn with_summary_coverage(
+    pub fn with_observation_extent(
         mut self,
-        coverage: super::summary_coverage::SummaryCoverage,
+        coverage: super::observation_extent::ObservationExtent,
     ) -> Result<Self, SchemaDerivationError> {
         coverage
             .validate()
@@ -163,7 +163,7 @@ impl OperatorNode {
                 ));
             }
         }
-        self.summary_coverage = Some(coverage);
+        self.observation_extent = Some(coverage);
         Ok(self)
     }
 
@@ -316,10 +316,10 @@ impl OperatorNode {
                     "invalid time or identity column in schema".into(),
                 ));
             }
-            if let Some(coverage) = &node.summary_coverage {
+            if let Some(coverage) = &node.observation_extent {
                 (*node.as_ref())
                     .clone()
-                    .with_summary_coverage(coverage.clone())?;
+                    .with_observation_extent(coverage.clone())?;
             }
             node.operator.validate_inputs()?;
             if node.result_kind != node.operator.output_kind() {
diff --git a/crates/types/src/ir/summary_coverage.rs b/crates/types/src/ir/observation_extent.rs
similarity index 84%
rename from crates/types/src/ir/summary_coverage.rs
rename to crates/types/src/ir/observation_extent.rs
index e60ef3072..0d7e2ad9d 100644
--- a/crates/types/src/ir/summary_coverage.rs
+++ b/crates/types/src/ir/observation_extent.rs
@@ -9,14 +9,14 @@ use thiserror::Error;
 
 #[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
 #[serde(deny_unknown_fields)]
-pub struct SummaryCoverage {
+pub struct ObservationExtent {
     pub source: String,
     pub revision: String,
     pub input: SummaryUpdate,
     pub grouping: Reduction,
     pub multiplicity: ObservationMultiplicity,
     /// Union of joint regions; never the Cartesian product of independent bounds.
-    pub regions: Vec<CoverageRegion>,
+    pub regions: Vec<ExtentRegion>,
 }
 
 #[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
@@ -26,7 +26,7 @@ pub enum ObservationMultiplicity {
 
 #[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
 #[serde(deny_unknown_fields)]
-pub struct CoverageRegion {
+pub struct ExtentRegion {
     /// Half-open bounds on one canonical time axis, in milliseconds.
     pub start_ms: i64,
     pub end_ms: i64,
@@ -35,7 +35,7 @@ pub struct CoverageRegion {
 }
 
 #[derive(Debug, Clone, PartialEq, Eq, Error)]
-pub enum CoverageError {
+pub enum ExtentError {
     #[error("coverage requires explicit source and revision identity")]
     MissingIdentity,
     #[error("coverage interval must have start < end")]
@@ -50,23 +50,23 @@ pub enum CoverageError {
     EmptyMerge,
 }
 
-impl SummaryCoverage {
-    pub fn validate(&self) -> Result<(), CoverageError> {
+impl ObservationExtent {
+    pub fn validate(&self) -> Result<(), ExtentError> {
         if self.source.is_empty() || self.revision.is_empty() {
-            return Err(CoverageError::MissingIdentity);
+            return Err(ExtentError::MissingIdentity);
         }
         for (index, region) in self.regions.iter().enumerate() {
             if region.start_ms >= region.end_ms {
-                return Err(CoverageError::InvalidInterval);
+                return Err(ExtentError::InvalidInterval);
             }
             if region.population.keys().any(String::is_empty) {
-                return Err(CoverageError::InvalidPopulation);
+                return Err(ExtentError::InvalidPopulation);
             }
             if self.regions[..index]
                 .iter()
                 .any(|other| region.may_overlap(other))
             {
-                return Err(CoverageError::PossibleOverlap);
+                return Err(ExtentError::PossibleOverlap);
             }
         }
         Ok(())
@@ -74,8 +74,8 @@ impl SummaryCoverage {
 
     /// Compose once-per-observation summaries only when their joint regions are
     /// provably disjoint. Family merge capability and accuracy are separate checks.
-    pub fn merge_disjoint(inputs: &[Self]) -> Result<Self, CoverageError> {
-        let first = inputs.first().ok_or(CoverageError::EmptyMerge)?;
+    pub fn merge_disjoint(inputs: &[Self]) -> Result<Self, ExtentError> {
+        let first = inputs.first().ok_or(ExtentError::EmptyMerge)?;
         let mut merged = first.clone();
         merged.regions.clear();
         for input in inputs {
@@ -86,7 +86,7 @@ impl SummaryCoverage {
                 || input.grouping != first.grouping
                 || input.multiplicity != first.multiplicity
             {
-                return Err(CoverageError::IncompatibleInput);
+                return Err(ExtentError::IncompatibleInput);
             }
             merged.regions.extend(input.regions.iter().cloned());
         }
@@ -97,7 +97,7 @@ impl SummaryCoverage {
                 .cmp(&b.population)
                 .then(a.start_ms.cmp(&b.start_ms))
         });
-        let mut normalized: Vec<CoverageRegion> = Vec::new();
+        let mut normalized: Vec<ExtentRegion> = Vec::new();
         for region in merged.regions {
             if let Some(last) = normalized.last_mut() {
                 if last.population == region.population && last.end_ms == region.start_ms {
@@ -111,7 +111,7 @@ impl SummaryCoverage {
         Ok(merged)
     }
 }
-impl CoverageRegion {
+impl ExtentRegion {
     fn may_overlap(&self, other: &Self) -> bool {
         self.start_ms < other.end_ms
             && other.start_ms < self.end_ms
diff --git a/crates/types/src/post_asap/mod.rs b/crates/types/src/post_asap/mod.rs
index f71aaca0f..c0028bad6 100644
--- a/crates/types/src/post_asap/mod.rs
+++ b/crates/types/src/post_asap/mod.rs
@@ -77,6 +77,6 @@ pub use summary_maintenance_lifecycle::{
     SummaryMaintenanceLifecycleGuarantee,
 };
 pub use summary_window::{
-    plan_pane_phase, validate_pane_coverage, PaneCoverageError, PaneLayout, SummaryWindowFramework,
+    plan_pane_phase, validate_pane_coverage, PaneExtentError, PaneLayout, SummaryWindowFramework,
     WindowEdgeCoverage,
 };
diff --git a/crates/types/src/post_asap/summary_window.rs b/crates/types/src/post_asap/summary_window.rs
index 0e344c1ed..440a79344 100644
--- a/crates/types/src/post_asap/summary_window.rs
+++ b/crates/types/src/post_asap/summary_window.rs
@@ -47,7 +47,7 @@ pub enum WindowEdgeCoverage {
 }
 
 #[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
-pub enum PaneCoverageError {
+pub enum PaneExtentError {
     ZeroPaneWidth,
     UnknownPaneOrigin,
     UnknownEvaluationPhase,
@@ -64,9 +64,9 @@ pub fn validate_pane_coverage(
     layout: &PaneLayout,
     evaluation_time_ms: Option<i64>,
     edge_coverage: &WindowEdgeCoverage,
-) -> Result<(), PaneCoverageError> {
+) -> Result<(), PaneExtentError> {
     if layout.pane_width_ms == 0 {
-        return Err(PaneCoverageError::ZeroPaneWidth);
+        return Err(PaneExtentError::ZeroPaneWidth);
     }
     if matches!(
         edge_coverage,
@@ -76,15 +76,15 @@ pub fn validate_pane_coverage(
     }
     let origin = layout
         .pane_origin_ms
-        .ok_or(PaneCoverageError::UnknownPaneOrigin)?;
-    let evaluation = evaluation_time_ms.ok_or(PaneCoverageError::UnknownEvaluationPhase)?;
+        .ok_or(PaneExtentError::UnknownPaneOrigin)?;
+    let evaluation = evaluation_time_ms.ok_or(PaneExtentError::UnknownEvaluationPhase)?;
     let width = layout.pane_width_ms as i64;
     let pane_phase_ms = origin.rem_euclid(width) as u64;
     let query_phase_ms = evaluation.rem_euclid(width) as u64;
     if pane_phase_ms == query_phase_ms {
         Ok(())
     } else {
-        Err(PaneCoverageError::PhaseMismatch {
+        Err(PaneExtentError::PhaseMismatch {
             pane_phase_ms,
             query_phase_ms,
         })
@@ -98,9 +98,9 @@ pub fn validate_pane_coverage(
 pub fn plan_pane_phase(
     demand: &RepeatedDemand,
     pane_width_ms: u64,
-) -> Result<PaneLayout, PaneCoverageError> {
+) -> Result<PaneLayout, PaneExtentError> {
     if pane_width_ms == 0 {
-        return Err(PaneCoverageError::ZeroPaneWidth);
+        return Err(PaneExtentError::ZeroPaneWidth);
     }
     let phase = match demand {
         RepeatedDemand::FixedIntervalAt {
@@ -154,7 +154,7 @@ mod tests {
         };
         assert_eq!(
             validate_pane_coverage(&layout, Some(56_000), &WindowEdgeCoverage::PaneAligned),
-            Err(PaneCoverageError::PhaseMismatch {
+            Err(PaneExtentError::PhaseMismatch {
                 pane_phase_ms: 26_000,
                 query_phase_ms: 56_000,
             })
diff --git a/crates/types/tests/summary_coverage.rs b/crates/types/tests/observation_extent.rs
similarity index 74%
rename from crates/types/tests/summary_coverage.rs
rename to crates/types/tests/observation_extent.rs
index 246d6b0c8..9947052f1 100644
--- a/crates/types/tests/summary_coverage.rs
+++ b/crates/types/tests/observation_extent.rs
@@ -1,16 +1,16 @@
 //! Coverage composition preserves gaps and rejects duplicate observations.
 use asap_types::{
-    ir::operator_properties::Reduction, ir::summary_coverage::*, post_asap::SummaryUpdate,
+    ir::observation_extent::*, ir::operator_properties::Reduction, post_asap::SummaryUpdate,
     pre_asap::ColumnRef,
 };
-fn coverage(start: i64, end: i64, population: &[(&str, &str)]) -> SummaryCoverage {
-    SummaryCoverage {
+fn coverage(start: i64, end: i64, population: &[(&str, &str)]) -> ObservationExtent {
+    ObservationExtent {
         source: "flows".into(),
         revision: "snapshot-1".into(),
         input: SummaryUpdate::column(ColumnRef::Named("latency".into())),
         grouping: Reduction::by(vec![0]),
         multiplicity: ObservationMultiplicity::OncePerObservation,
-        regions: vec![CoverageRegion {
+        regions: vec![ExtentRegion {
             start_ms: start,
             end_ms: end,
             population: population
@@ -24,29 +24,29 @@ fn coverage(start: i64, end: i64, population: &[(&str, &str)]) -> SummaryCoverag
 #[test]
 fn time_union_preserves_gaps() {
     let merged =
-        SummaryCoverage::merge_disjoint(&[coverage(0, 1, &[]), coverage(1, 2, &[])]).unwrap();
+        ObservationExtent::merge_disjoint(&[coverage(0, 1, &[]), coverage(1, 2, &[])]).unwrap();
     assert_eq!(merged.regions[0].end_ms, 2);
     assert_eq!(merged.regions.len(), 1);
     let gapped =
-        SummaryCoverage::merge_disjoint(&[coverage(0, 1, &[]), coverage(2, 3, &[])]).unwrap();
+        ObservationExtent::merge_disjoint(&[coverage(0, 1, &[]), coverage(2, 3, &[])]).unwrap();
     assert_eq!(gapped.regions.len(), 2);
 }
 /// Population partitions can overlap in time without sharing observations.
 #[test]
 fn population_and_joint_union() {
-    let merged = SummaryCoverage::merge_disjoint(&[
+    let merged = ObservationExtent::merge_disjoint(&[
         coverage(0, 2, &[("region", "us")]),
         coverage(0, 2, &[("region", "eu")]),
     ])
     .unwrap();
     assert_eq!(merged.regions.len(), 2);
-    let joint = SummaryCoverage::merge_disjoint(&[
+    let joint = ObservationExtent::merge_disjoint(&[
         coverage(0, 1, &[("region", "us")]),
         coverage(1, 2, &[("region", "eu")]),
     ])
     .unwrap();
     assert_eq!(joint.regions.len(), 2);
-    let decoded: SummaryCoverage =
+    let decoded: ObservationExtent =
         serde_json::from_str(&serde_json::to_string(&joint).unwrap()).unwrap();
     assert_eq!(decoded, joint);
 }
@@ -54,25 +54,25 @@ fn population_and_joint_union() {
 #[test]
 fn overlap_and_identity_fail_closed() {
     assert_eq!(
-        SummaryCoverage::merge_disjoint(&[coverage(0, 2, &[]), coverage(1, 3, &[])]),
-        Err(CoverageError::PossibleOverlap)
+        ObservationExtent::merge_disjoint(&[coverage(0, 2, &[]), coverage(1, 3, &[])]),
+        Err(ExtentError::PossibleOverlap)
     );
     assert_eq!(
-        SummaryCoverage::merge_disjoint(&[
+        ObservationExtent::merge_disjoint(&[
             coverage(0, 2, &[("region", "us")]),
             coverage(0, 2, &[("tier", "premium")])
         ]),
-        Err(CoverageError::PossibleOverlap)
+        Err(ExtentError::PossibleOverlap)
     );
     let mut other = coverage(1, 2, &[]);
     other.revision = "snapshot-2".into();
     assert_eq!(
-        SummaryCoverage::merge_disjoint(&[coverage(0, 1, &[]), other]),
-        Err(CoverageError::IncompatibleInput)
+        ObservationExtent::merge_disjoint(&[coverage(0, 1, &[]), other]),
+        Err(ExtentError::IncompatibleInput)
     );
     assert_eq!(
         coverage(2, 1, &[]).validate(),
-        Err(CoverageError::InvalidInterval)
+        Err(ExtentError::InvalidInterval)
     );
 }
 
@@ -97,7 +97,7 @@ fn node_coverage_is_checked_and_rewrites_clear_it() {
     declared.grouping = Reduction::by(vec![]);
     assert!((*raw)
         .clone()
-        .with_summary_coverage(declared.clone())
+        .with_observation_extent(declared.clone())
         .is_err());
     let state = OperatorNode::new(Operator::ASAP(ASAPOp::SummaryAgg {
         child: raw,
@@ -111,11 +111,11 @@ fn node_coverage_is_checked_and_rewrites_clear_it() {
         filter: None,
     }))
     .unwrap();
-    let state = state.with_summary_coverage(declared.clone()).unwrap();
-    assert!(state.summary_coverage.is_some());
+    let state = state.with_observation_extent(declared.clone()).unwrap();
+    assert!(state.observation_extent.is_some());
     let mut bad = declared;
     bad.input = SummaryUpdate::column(ColumnRef::Named("other".into()));
-    assert!(state.clone().with_summary_coverage(bad).is_err());
+    assert!(state.clone().with_observation_extent(bad).is_err());
     let rebuilt = state.map_children(Clone::clone).unwrap();
-    assert!(rebuilt.summary_coverage.is_none());
+    assert!(rebuilt.observation_extent.is_none());
 }
diff --git a/docs/develop_docs/summary-coverage.md b/docs/develop_docs/observation-extent.md
similarity index 70%
rename from docs/develop_docs/summary-coverage.md
rename to docs/develop_docs/observation-extent.md
index 2653d0426..9a8406f3d 100644
--- a/docs/develop_docs/summary-coverage.md
+++ b/docs/develop_docs/observation-extent.md
@@ -1,14 +1,14 @@
 # Summary coverage contract
 
 Schema describes field layout; summary coverage describes eligible observations.
-`OperatorNode.summary_coverage` is optional logical metadata. `None` means unknown,
+`OperatorNode.observation_extent` is optional logical metadata. `None` means unknown,
 not unrestricted coverage. Rewriting inputs clears it along with other assessed
-metadata. `with_summary_coverage` validates declared coverage and checks state kind
+metadata. `with_observation_extent` validates declared coverage and checks state kind
 and SummaryAgg input/grouping agreement. Provenance is supplied by a trusted
 composition rule/catalog; this API does not infer predicates from arbitrary SQL.
 
-`SummaryCoverage` records source and revision identity, update expression,
-grouping, once-per-observation multiplicity and a union of joint `CoverageRegion`s.
+`ObservationExtent` records source and revision identity, update expression,
+grouping, once-per-observation multiplicity and a union of joint `ExtentRegion`s.
 Each region pairs half-open time bounds in milliseconds with a conjunction of
 non-null equality predicates over canonical population dimensions. Source identity
 must include the time axis and observation-identity namespace. Revision identifies
@@ -33,3 +33,13 @@ merge capability, accuracy certificate, storage policy or execution timing.
 The following merge PR must require known coverage, derive the output union and
 validate it rather than treating matching schemas as sufficient authorization.
 Logical transport and CSE must preserve and compare coverage metadata.
+
+## Why extent
+
+`ObservationExtent` describes the declared set of source observations represented
+by a state. The name borrows the set meaning of "extent" from object databases;
+it is a project-specific term, not an ODMG class extent implementation.
+`None` means unknown extent; an empty region list means a known empty extent.
+Disjoint union preserves gaps and joint population/time relationships.
+The later query-relative coverage check asks whether this extent satisfies a
+requested population/window. Declaring an extent does not prove that check.

From 17173eaa34b2080070f306482f2c1aacc7182fc0 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 16:56:48 +0000
Subject: [PATCH 03/48] refactor(ir): rename observation extent to
 SummaryCoverage and trim its fields

Name the metadata coverage to match #560 and the docs; drop the single-variant
multiplicity and deployment-specific revision; rename grouping to reduction to
match SummaryAgg; report failures through SchemaDerivationError::Coverage; revert
the unrelated PaneCoverageError rename.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/types/src/ir/error.rs                  |  2 +
 crates/types/src/ir/mod.rs                    |  2 +-
 crates/types/src/ir/node.rs                   | 31 ++++------
 ...ervation_extent.rs => summary_coverage.rs} | 57 +++++++++----------
 crates/types/src/post_asap/mod.rs             |  2 +-
 crates/types/src/post_asap/summary_window.rs  | 18 +++---
 ...ervation_extent.rs => summary_coverage.rs} | 55 ++++++++----------
 docs/develop_docs/observation-extent.md       | 45 ---------------
 docs/develop_docs/summary-coverage.md         | 32 +++++++++++
 9 files changed, 110 insertions(+), 134 deletions(-)
 rename crates/types/src/ir/{observation_extent.rs => summary_coverage.rs} (70%)
 rename crates/types/tests/{observation_extent.rs => summary_coverage.rs} (66%)
 delete mode 100644 docs/develop_docs/observation-extent.md
 create mode 100644 docs/develop_docs/summary-coverage.md

diff --git a/crates/types/src/ir/error.rs b/crates/types/src/ir/error.rs
index 4b6849965..a0f9e2271 100644
--- a/crates/types/src/ir/error.rs
+++ b/crates/types/src/ir/error.rs
@@ -16,4 +16,6 @@ pub enum SchemaDerivationError {
     EmptyConcat,
     #[error("invalid per-series sample column: {0}")]
     InvalidSampleColumn(String),
+    #[error("invalid summary coverage: {0}")]
+    Coverage(#[from] super::summary_coverage::CoverageError),
 }
diff --git a/crates/types/src/ir/mod.rs b/crates/types/src/ir/mod.rs
index 45606611b..fcb2eb49b 100644
--- a/crates/types/src/ir/mod.rs
+++ b/crates/types/src/ir/mod.rs
@@ -17,4 +17,4 @@ pub use query::QueryRoot;
 pub use scalar::{ExprSemantics, Predicate, ProjectItem, ScalarExpr, SortKey};
 
 /// Semantic observation coverage, separate from field layout and physical timing.
-pub mod observation_extent;
+pub mod summary_coverage;
diff --git a/crates/types/src/ir/node.rs b/crates/types/src/ir/node.rs
index 2a47f892c..ab2af052a 100644
--- a/crates/types/src/ir/node.rs
+++ b/crates/types/src/ir/node.rs
@@ -10,6 +10,7 @@ use serde::{Deserialize, Serialize};
 
 use super::asap::ASAPOp;
 use super::non_asap::NonASAPOp;
+use super::summary_coverage::{CoverageError, SummaryCoverage};
 use crate::ir::SchemaDerivationError;
 use crate::post_asap::execution_data_state::ExecutionTiming;
 use crate::post_asap::guarantee::ResultGuarantee;
@@ -96,7 +97,7 @@ pub struct OperatorNode {
     pub guarantee: Option<ResultGuarantee>,
     pub timing: Option<ExecutionTiming>,
     #[serde(default)]
-    pub observation_extent: Option<super::observation_extent::ObservationExtent>,
+    pub coverage: Option<SummaryCoverage>,
 }
 
 impl OperatorNode {
@@ -119,7 +120,7 @@ impl OperatorNode {
             schema,
             guarantee: None,
             timing: None,
-            observation_extent: None,
+            coverage: None,
         }
     }
 
@@ -141,29 +142,23 @@ impl OperatorNode {
     }
 
     /// Attach caller-established observation coverage; unknown coverage remains None.
-    pub fn with_observation_extent(
+    pub fn with_coverage(
         mut self,
-        coverage: super::observation_extent::ObservationExtent,
+        coverage: SummaryCoverage,
     ) -> Result<Self, SchemaDerivationError> {
-        coverage
-            .validate()
-            .map_err(|error| SchemaDerivationError::InvalidScalarSignature(error.to_string()))?;
+        coverage.validate()?;
         if self.result_kind != OperatorResultKind::State {
-            return Err(SchemaDerivationError::InvalidScalarSignature(
-                "summary coverage requires state output".into(),
-            ));
+            return Err(CoverageError::NotState.into());
         }
         if let Some(ASAPOp::SummaryAgg {
             input, reduction, ..
         }) = self.asap()
         {
-            if *input != coverage.input || *reduction != coverage.grouping {
-                return Err(SchemaDerivationError::InvalidScalarSignature(
-                    "coverage input/grouping disagrees with summary producer".into(),
-                ));
+            if *input != coverage.input || *reduction != coverage.reduction {
+                return Err(CoverageError::ProducerMismatch.into());
             }
         }
-        self.observation_extent = Some(coverage);
+        self.coverage = Some(coverage);
         Ok(self)
     }
 
@@ -316,10 +311,8 @@ impl OperatorNode {
                     "invalid time or identity column in schema".into(),
                 ));
             }
-            if let Some(coverage) = &node.observation_extent {
-                (*node.as_ref())
-                    .clone()
-                    .with_observation_extent(coverage.clone())?;
+            if let Some(coverage) = &node.coverage {
+                (*node.as_ref()).clone().with_coverage(coverage.clone())?;
             }
             node.operator.validate_inputs()?;
             if node.result_kind != node.operator.output_kind() {
diff --git a/crates/types/src/ir/observation_extent.rs b/crates/types/src/ir/summary_coverage.rs
similarity index 70%
rename from crates/types/src/ir/observation_extent.rs
rename to crates/types/src/ir/summary_coverage.rs
index 0d7e2ad9d..b761480ea 100644
--- a/crates/types/src/ir/observation_extent.rs
+++ b/crates/types/src/ir/summary_coverage.rs
@@ -9,24 +9,20 @@ use thiserror::Error;
 
 #[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
 #[serde(deny_unknown_fields)]
-pub struct ObservationExtent {
+pub struct SummaryCoverage {
+    /// Observation stream identity, including its time axis.
     pub source: String,
-    pub revision: String,
+    /// Must equal the producing `SummaryAgg.input`.
     pub input: SummaryUpdate,
-    pub grouping: Reduction,
-    pub multiplicity: ObservationMultiplicity,
+    /// Must equal the producing `SummaryAgg.reduction`.
+    pub reduction: Reduction,
     /// Union of joint regions; never the Cartesian product of independent bounds.
-    pub regions: Vec<ExtentRegion>,
-}
-
-#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
-pub enum ObservationMultiplicity {
-    OncePerObservation,
+    pub regions: Vec<CoverageRegion>,
 }
 
 #[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
 #[serde(deny_unknown_fields)]
-pub struct ExtentRegion {
+pub struct CoverageRegion {
     /// Half-open bounds on one canonical time axis, in milliseconds.
     pub start_ms: i64,
     pub end_ms: i64,
@@ -35,58 +31,61 @@ pub struct ExtentRegion {
 }
 
 #[derive(Debug, Clone, PartialEq, Eq, Error)]
-pub enum ExtentError {
-    #[error("coverage requires explicit source and revision identity")]
+pub enum CoverageError {
+    #[error("coverage requires an explicit source identity")]
     MissingIdentity,
     #[error("coverage interval must have start < end")]
     InvalidInterval,
     #[error("population dimension names cannot be empty")]
     InvalidPopulation,
-    #[error("summary input identity, grouping or multiplicity differs")]
+    #[error("summary source, input or reduction differs")]
     IncompatibleInput,
     #[error("coverage overlap is not proven absent")]
     PossibleOverlap,
     #[error("coverage merge requires at least one input")]
     EmptyMerge,
+    #[error("summary coverage requires state output")]
+    NotState,
+    #[error("coverage input/reduction disagrees with summary producer")]
+    ProducerMismatch,
 }
 
-impl ObservationExtent {
-    pub fn validate(&self) -> Result<(), ExtentError> {
-        if self.source.is_empty() || self.revision.is_empty() {
-            return Err(ExtentError::MissingIdentity);
+impl SummaryCoverage {
+    pub fn validate(&self) -> Result<(), CoverageError> {
+        if self.source.is_empty() {
+            return Err(CoverageError::MissingIdentity);
         }
         for (index, region) in self.regions.iter().enumerate() {
             if region.start_ms >= region.end_ms {
-                return Err(ExtentError::InvalidInterval);
+                return Err(CoverageError::InvalidInterval);
             }
             if region.population.keys().any(String::is_empty) {
-                return Err(ExtentError::InvalidPopulation);
+                return Err(CoverageError::InvalidPopulation);
             }
             if self.regions[..index]
                 .iter()
                 .any(|other| region.may_overlap(other))
             {
-                return Err(ExtentError::PossibleOverlap);
+                return Err(CoverageError::PossibleOverlap);
             }
         }
         Ok(())
     }
 
+    /// Every observation in a region is assumed to contribute once to the state.
     /// Compose once-per-observation summaries only when their joint regions are
     /// provably disjoint. Family merge capability and accuracy are separate checks.
-    pub fn merge_disjoint(inputs: &[Self]) -> Result<Self, ExtentError> {
-        let first = inputs.first().ok_or(ExtentError::EmptyMerge)?;
+    pub fn merge_disjoint(inputs: &[Self]) -> Result<Self, CoverageError> {
+        let first = inputs.first().ok_or(CoverageError::EmptyMerge)?;
         let mut merged = first.clone();
         merged.regions.clear();
         for input in inputs {
             input.validate()?;
             if input.source != first.source
-                || input.revision != first.revision
                 || input.input != first.input
-                || input.grouping != first.grouping
-                || input.multiplicity != first.multiplicity
+                || input.reduction != first.reduction
             {
-                return Err(ExtentError::IncompatibleInput);
+                return Err(CoverageError::IncompatibleInput);
             }
             merged.regions.extend(input.regions.iter().cloned());
         }
@@ -97,7 +96,7 @@ impl ObservationExtent {
                 .cmp(&b.population)
                 .then(a.start_ms.cmp(&b.start_ms))
         });
-        let mut normalized: Vec<ExtentRegion> = Vec::new();
+        let mut normalized: Vec<CoverageRegion> = Vec::new();
         for region in merged.regions {
             if let Some(last) = normalized.last_mut() {
                 if last.population == region.population && last.end_ms == region.start_ms {
@@ -111,7 +110,7 @@ impl ObservationExtent {
         Ok(merged)
     }
 }
-impl ExtentRegion {
+impl CoverageRegion {
     fn may_overlap(&self, other: &Self) -> bool {
         self.start_ms < other.end_ms
             && other.start_ms < self.end_ms
diff --git a/crates/types/src/post_asap/mod.rs b/crates/types/src/post_asap/mod.rs
index c0028bad6..f71aaca0f 100644
--- a/crates/types/src/post_asap/mod.rs
+++ b/crates/types/src/post_asap/mod.rs
@@ -77,6 +77,6 @@ pub use summary_maintenance_lifecycle::{
     SummaryMaintenanceLifecycleGuarantee,
 };
 pub use summary_window::{
-    plan_pane_phase, validate_pane_coverage, PaneExtentError, PaneLayout, SummaryWindowFramework,
+    plan_pane_phase, validate_pane_coverage, PaneCoverageError, PaneLayout, SummaryWindowFramework,
     WindowEdgeCoverage,
 };
diff --git a/crates/types/src/post_asap/summary_window.rs b/crates/types/src/post_asap/summary_window.rs
index 440a79344..0e344c1ed 100644
--- a/crates/types/src/post_asap/summary_window.rs
+++ b/crates/types/src/post_asap/summary_window.rs
@@ -47,7 +47,7 @@ pub enum WindowEdgeCoverage {
 }
 
 #[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
-pub enum PaneExtentError {
+pub enum PaneCoverageError {
     ZeroPaneWidth,
     UnknownPaneOrigin,
     UnknownEvaluationPhase,
@@ -64,9 +64,9 @@ pub fn validate_pane_coverage(
     layout: &PaneLayout,
     evaluation_time_ms: Option<i64>,
     edge_coverage: &WindowEdgeCoverage,
-) -> Result<(), PaneExtentError> {
+) -> Result<(), PaneCoverageError> {
     if layout.pane_width_ms == 0 {
-        return Err(PaneExtentError::ZeroPaneWidth);
+        return Err(PaneCoverageError::ZeroPaneWidth);
     }
     if matches!(
         edge_coverage,
@@ -76,15 +76,15 @@ pub fn validate_pane_coverage(
     }
     let origin = layout
         .pane_origin_ms
-        .ok_or(PaneExtentError::UnknownPaneOrigin)?;
-    let evaluation = evaluation_time_ms.ok_or(PaneExtentError::UnknownEvaluationPhase)?;
+        .ok_or(PaneCoverageError::UnknownPaneOrigin)?;
+    let evaluation = evaluation_time_ms.ok_or(PaneCoverageError::UnknownEvaluationPhase)?;
     let width = layout.pane_width_ms as i64;
     let pane_phase_ms = origin.rem_euclid(width) as u64;
     let query_phase_ms = evaluation.rem_euclid(width) as u64;
     if pane_phase_ms == query_phase_ms {
         Ok(())
     } else {
-        Err(PaneExtentError::PhaseMismatch {
+        Err(PaneCoverageError::PhaseMismatch {
             pane_phase_ms,
             query_phase_ms,
         })
@@ -98,9 +98,9 @@ pub fn validate_pane_coverage(
 pub fn plan_pane_phase(
     demand: &RepeatedDemand,
     pane_width_ms: u64,
-) -> Result<PaneLayout, PaneExtentError> {
+) -> Result<PaneLayout, PaneCoverageError> {
     if pane_width_ms == 0 {
-        return Err(PaneExtentError::ZeroPaneWidth);
+        return Err(PaneCoverageError::ZeroPaneWidth);
     }
     let phase = match demand {
         RepeatedDemand::FixedIntervalAt {
@@ -154,7 +154,7 @@ mod tests {
         };
         assert_eq!(
             validate_pane_coverage(&layout, Some(56_000), &WindowEdgeCoverage::PaneAligned),
-            Err(PaneExtentError::PhaseMismatch {
+            Err(PaneCoverageError::PhaseMismatch {
                 pane_phase_ms: 26_000,
                 query_phase_ms: 56_000,
             })
diff --git a/crates/types/tests/observation_extent.rs b/crates/types/tests/summary_coverage.rs
similarity index 66%
rename from crates/types/tests/observation_extent.rs
rename to crates/types/tests/summary_coverage.rs
index 9947052f1..c36ed0ecb 100644
--- a/crates/types/tests/observation_extent.rs
+++ b/crates/types/tests/summary_coverage.rs
@@ -1,16 +1,14 @@
 //! Coverage composition preserves gaps and rejects duplicate observations.
 use asap_types::{
-    ir::observation_extent::*, ir::operator_properties::Reduction, post_asap::SummaryUpdate,
+    ir::operator_properties::Reduction, ir::summary_coverage::*, post_asap::SummaryUpdate,
     pre_asap::ColumnRef,
 };
-fn coverage(start: i64, end: i64, population: &[(&str, &str)]) -> ObservationExtent {
-    ObservationExtent {
+fn coverage(start: i64, end: i64, population: &[(&str, &str)]) -> SummaryCoverage {
+    SummaryCoverage {
         source: "flows".into(),
-        revision: "snapshot-1".into(),
         input: SummaryUpdate::column(ColumnRef::Named("latency".into())),
-        grouping: Reduction::by(vec![0]),
-        multiplicity: ObservationMultiplicity::OncePerObservation,
-        regions: vec![ExtentRegion {
+        reduction: Reduction::by(vec![0]),
+        regions: vec![CoverageRegion {
             start_ms: start,
             end_ms: end,
             population: population
@@ -24,29 +22,29 @@ fn coverage(start: i64, end: i64, population: &[(&str, &str)]) -> ObservationExt
 #[test]
 fn time_union_preserves_gaps() {
     let merged =
-        ObservationExtent::merge_disjoint(&[coverage(0, 1, &[]), coverage(1, 2, &[])]).unwrap();
+        SummaryCoverage::merge_disjoint(&[coverage(0, 1, &[]), coverage(1, 2, &[])]).unwrap();
     assert_eq!(merged.regions[0].end_ms, 2);
     assert_eq!(merged.regions.len(), 1);
     let gapped =
-        ObservationExtent::merge_disjoint(&[coverage(0, 1, &[]), coverage(2, 3, &[])]).unwrap();
+        SummaryCoverage::merge_disjoint(&[coverage(0, 1, &[]), coverage(2, 3, &[])]).unwrap();
     assert_eq!(gapped.regions.len(), 2);
 }
 /// Population partitions can overlap in time without sharing observations.
 #[test]
 fn population_and_joint_union() {
-    let merged = ObservationExtent::merge_disjoint(&[
+    let merged = SummaryCoverage::merge_disjoint(&[
         coverage(0, 2, &[("region", "us")]),
         coverage(0, 2, &[("region", "eu")]),
     ])
     .unwrap();
     assert_eq!(merged.regions.len(), 2);
-    let joint = ObservationExtent::merge_disjoint(&[
+    let joint = SummaryCoverage::merge_disjoint(&[
         coverage(0, 1, &[("region", "us")]),
         coverage(1, 2, &[("region", "eu")]),
     ])
     .unwrap();
     assert_eq!(joint.regions.len(), 2);
-    let decoded: ObservationExtent =
+    let decoded: SummaryCoverage =
         serde_json::from_str(&serde_json::to_string(&joint).unwrap()).unwrap();
     assert_eq!(decoded, joint);
 }
@@ -54,25 +52,25 @@ fn population_and_joint_union() {
 #[test]
 fn overlap_and_identity_fail_closed() {
     assert_eq!(
-        ObservationExtent::merge_disjoint(&[coverage(0, 2, &[]), coverage(1, 3, &[])]),
-        Err(ExtentError::PossibleOverlap)
+        SummaryCoverage::merge_disjoint(&[coverage(0, 2, &[]), coverage(1, 3, &[])]),
+        Err(CoverageError::PossibleOverlap)
     );
     assert_eq!(
-        ObservationExtent::merge_disjoint(&[
+        SummaryCoverage::merge_disjoint(&[
             coverage(0, 2, &[("region", "us")]),
             coverage(0, 2, &[("tier", "premium")])
         ]),
-        Err(ExtentError::PossibleOverlap)
+        Err(CoverageError::PossibleOverlap)
     );
     let mut other = coverage(1, 2, &[]);
-    other.revision = "snapshot-2".into();
+    other.source = "other-flows".into();
     assert_eq!(
-        ObservationExtent::merge_disjoint(&[coverage(0, 1, &[]), other]),
-        Err(ExtentError::IncompatibleInput)
+        SummaryCoverage::merge_disjoint(&[coverage(0, 1, &[]), other]),
+        Err(CoverageError::IncompatibleInput)
     );
     assert_eq!(
         coverage(2, 1, &[]).validate(),
-        Err(ExtentError::InvalidInterval)
+        Err(CoverageError::InvalidInterval)
     );
 }
 
@@ -94,11 +92,8 @@ fn node_coverage_is_checked_and_rewrites_clear_it() {
     }))
     .unwrap();
     let mut declared = coverage(0, 1, &[]);
-    declared.grouping = Reduction::by(vec![]);
-    assert!((*raw)
-        .clone()
-        .with_observation_extent(declared.clone())
-        .is_err());
+    declared.reduction = Reduction::by(vec![]);
+    assert!((*raw).clone().with_coverage(declared.clone()).is_err());
     let state = OperatorNode::new(Operator::ASAP(ASAPOp::SummaryAgg {
         child: raw,
         family: FieldDataType::Sketch(
@@ -106,16 +101,16 @@ fn node_coverage_is_checked_and_rewrites_clear_it() {
             Default::default(),
         ),
         input: declared.input.clone(),
-        reduction: declared.grouping.clone(),
+        reduction: declared.reduction.clone(),
         grouping: Default::default(),
         filter: None,
     }))
     .unwrap();
-    let state = state.with_observation_extent(declared.clone()).unwrap();
-    assert!(state.observation_extent.is_some());
+    let state = state.with_coverage(declared.clone()).unwrap();
+    assert!(state.coverage.is_some());
     let mut bad = declared;
     bad.input = SummaryUpdate::column(ColumnRef::Named("other".into()));
-    assert!(state.clone().with_observation_extent(bad).is_err());
+    assert!(state.clone().with_coverage(bad).is_err());
     let rebuilt = state.map_children(Clone::clone).unwrap();
-    assert!(rebuilt.observation_extent.is_none());
+    assert!(rebuilt.coverage.is_none());
 }
diff --git a/docs/develop_docs/observation-extent.md b/docs/develop_docs/observation-extent.md
deleted file mode 100644
index 9a8406f3d..000000000
--- a/docs/develop_docs/observation-extent.md
+++ /dev/null
@@ -1,45 +0,0 @@
-# Summary coverage contract
-
-Schema describes field layout; summary coverage describes eligible observations.
-`OperatorNode.observation_extent` is optional logical metadata. `None` means unknown,
-not unrestricted coverage. Rewriting inputs clears it along with other assessed
-metadata. `with_observation_extent` validates declared coverage and checks state kind
-and SummaryAgg input/grouping agreement. Provenance is supplied by a trusted
-composition rule/catalog; this API does not infer predicates from arbitrary SQL.
-
-`ObservationExtent` records source and revision identity, update expression,
-grouping, once-per-observation multiplicity and a union of joint `ExtentRegion`s.
-Each region pairs half-open time bounds in milliseconds with a conjunction of
-non-null equality predicates over canonical population dimensions. Source identity
-must include the time axis and observation-identity namespace. Revision identifies
-the input snapshot/update contract used to construct the state.
-
-`merge_disjoint` requires equal input identities and provably disjoint joint
-regions. Adjacent intervals coalesce only with identical population predicates;
-gaps remain separate. Conflicting equality predicates on the same dimension prove
-population disjointness. Independent predicates do not: region=US can overlap
-tier=premium. Different source/revision/input/grouping contracts fail.
-
-US×[0,1) merged with EU×[1,2) remains two regions, not
-{US,EU}×[0,2). This avoids inventing missing cross-population/time coverage.
-Empty regions describe empty observation coverage. Empty merge input is invalid.
-
-This contract supports conservative once-per-observation composition. Arbitrary
-predicates, null predicates, unbounded time coverage, idempotent set-union algebra,
-coverage inference and full requested-window containment need explicit extensions.
-It never labels unsupported/unknown predicates disjoint. It provides no runtime
-merge capability, accuracy certificate, storage policy or execution timing.
-
-The following merge PR must require known coverage, derive the output union and
-validate it rather than treating matching schemas as sufficient authorization.
-Logical transport and CSE must preserve and compare coverage metadata.
-
-## Why extent
-
-`ObservationExtent` describes the declared set of source observations represented
-by a state. The name borrows the set meaning of "extent" from object databases;
-it is a project-specific term, not an ODMG class extent implementation.
-`None` means unknown extent; an empty region list means a known empty extent.
-Disjoint union preserves gaps and joint population/time relationships.
-The later query-relative coverage check asks whether this extent satisfies a
-requested population/window. Declaring an extent does not prove that check.
diff --git a/docs/develop_docs/summary-coverage.md b/docs/develop_docs/summary-coverage.md
new file mode 100644
index 000000000..3f41e9b83
--- /dev/null
+++ b/docs/develop_docs/summary-coverage.md
@@ -0,0 +1,32 @@
+# Summary coverage contract
+
+`Schema` describes an edge's field layout and committed state type. It does not
+say which observations a summary state was built from: a KLL over `[0,1)` and a
+KLL over `[1,3)` have equal schemas. `OperatorNode.coverage` records that
+separately, as optional logical metadata. `None` means unknown, not unrestricted.
+Rewriting a node's inputs clears it along with other assessed metadata.
+
+`SummaryCoverage` records:
+
+- `source`: the observation stream, including its time axis.
+- `input`, `reduction`: must equal the producing `SummaryAgg`'s fields of the same
+  name. `with_coverage` checks this and requires state output.
+- `regions`: a union of `CoverageRegion`s. Each pairs half-open time bounds in
+  milliseconds with a conjunction of non-null equality predicates over population
+  dimensions; an empty predicate map means all observations of the source.
+
+Every observation in a region contributes once to the state. Declarations come
+from trusted composition rules or catalogs; nothing is inferred from SQL.
+
+`merge_disjoint` requires equal source/input/reduction and provably disjoint
+regions. Adjacent intervals coalesce only with identical population predicates;
+gaps remain separate. Conflicting values for the same dimension prove disjointness.
+Different dimensions do not: `region=us` can overlap `tier=premium`.
+
+`us×[0,1)` merged with `eu×[1,2)` remains two regions, not `{us,eu}×[0,2)`.
+Empty `regions` is known empty coverage. Empty merge input is invalid.
+
+Not covered: arbitrary or null predicates, unbounded time, idempotent set-union
+families, and checking that coverage contains a requested query window or
+population. The contract provides no runtime merge capability, accuracy
+certificate, storage policy or execution timing.

From f968661fa1ad344536a1bfbce9988cfc7ce5f6ef Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 17:10:07 +0000
Subject: [PATCH 04/48] docs(ir): describe coverage source as any observation
 data source

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/types/src/ir/summary_coverage.rs | 3 ++-
 docs/develop_docs/summary-coverage.md   | 3 ++-
 2 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/crates/types/src/ir/summary_coverage.rs b/crates/types/src/ir/summary_coverage.rs
index b761480ea..77ce54187 100644
--- a/crates/types/src/ir/summary_coverage.rs
+++ b/crates/types/src/ir/summary_coverage.rs
@@ -10,7 +10,8 @@ use thiserror::Error;
 #[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
 #[serde(deny_unknown_fields)]
 pub struct SummaryCoverage {
-    /// Observation stream identity, including its time axis.
+    /// Observation data source identity: any table or stream, not necessarily
+    /// time series. Region time bounds refer to its time column.
     pub source: String,
     /// Must equal the producing `SummaryAgg.input`.
     pub input: SummaryUpdate,
diff --git a/docs/develop_docs/summary-coverage.md b/docs/develop_docs/summary-coverage.md
index 3f41e9b83..3f452f7b2 100644
--- a/docs/develop_docs/summary-coverage.md
+++ b/docs/develop_docs/summary-coverage.md
@@ -8,7 +8,8 @@ Rewriting a node's inputs clears it along with other assessed metadata.
 
 `SummaryCoverage` records:
 
-- `source`: the observation stream, including its time axis.
+- `source`: the observation data source. It can be any tabular data, not
+  necessarily a time series; region time bounds refer to its time column.
 - `input`, `reduction`: must equal the producing `SummaryAgg`'s fields of the same
   name. `with_coverage` checks this and requires state output.
 - `regions`: a union of `CoverageRegion`s. Each pairs half-open time bounds in

From 6f129a014296cdddab63f8e47fc5940de4cbbec2 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 17:19:01 +0000
Subject: [PATCH 05/48] feat(ir): require coverage on summary nodes; allow
 regions without time bounds

validate_structure rejects a SummaryAgg without coverage (CoverageError::Missing).
CoverageRegion time bounds become optional so tabular sources without a time
column can declare coverage. Population stays trusted; #570 tracks checking it.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/types/src/ir/node.rs              | 16 ++++++--
 crates/types/src/ir/summary_coverage.rs  | 35 ++++++++++++------
 crates/types/tests/schema_rebuilding.rs  | 47 +++++++++++++++++++-----
 crates/types/tests/structure_contract.rs | 39 +++++++++++++++-----
 crates/types/tests/summary_coverage.rs   | 39 +++++++++++++++++---
 docs/develop_docs/summary-coverage.md    | 43 ++++++++++++++++------
 6 files changed, 170 insertions(+), 49 deletions(-)

diff --git a/crates/types/src/ir/node.rs b/crates/types/src/ir/node.rs
index ab2af052a..bf2e9479e 100644
--- a/crates/types/src/ir/node.rs
+++ b/crates/types/src/ir/node.rs
@@ -141,7 +141,8 @@ impl OperatorNode {
         self
     }
 
-    /// Attach caller-established observation coverage; unknown coverage remains None.
+    /// Attach caller-established coverage. Required on summary nodes; see
+    /// [`Self::requires_coverage`].
     pub fn with_coverage(
         mut self,
         coverage: SummaryCoverage,
@@ -162,6 +163,11 @@ impl OperatorNode {
         Ok(self)
     }
 
+    /// Summary nodes whose state can be composed must declare coverage.
+    pub fn requires_coverage(&self) -> bool {
+        matches!(self.asap(), Some(ASAPOp::SummaryAgg { .. }))
+    }
+
     pub fn non_asap(&self) -> Option<&NonASAPOp> {
         match &self.operator {
             Operator::NonASAP(op) => Some(op),
@@ -311,8 +317,12 @@ impl OperatorNode {
                     "invalid time or identity column in schema".into(),
                 ));
             }
-            if let Some(coverage) = &node.coverage {
-                (*node.as_ref()).clone().with_coverage(coverage.clone())?;
+            match &node.coverage {
+                Some(coverage) => {
+                    (*node.as_ref()).clone().with_coverage(coverage.clone())?;
+                }
+                None if node.requires_coverage() => return Err(CoverageError::Missing.into()),
+                None => {}
             }
             node.operator.validate_inputs()?;
             if node.result_kind != node.operator.output_kind() {
diff --git a/crates/types/src/ir/summary_coverage.rs b/crates/types/src/ir/summary_coverage.rs
index 77ce54187..5056ef3f2 100644
--- a/crates/types/src/ir/summary_coverage.rs
+++ b/crates/types/src/ir/summary_coverage.rs
@@ -5,6 +5,7 @@ use super::operator_properties::Reduction;
 use crate::post_asap::SummaryUpdate;
 use serde::{Deserialize, Serialize};
 use std::collections::BTreeMap;
+use std::ops::Range;
 use thiserror::Error;
 
 #[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
@@ -24,9 +25,9 @@ pub struct SummaryCoverage {
 #[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
 #[serde(deny_unknown_fields)]
 pub struct CoverageRegion {
-    /// Half-open bounds on one canonical time axis, in milliseconds.
-    pub start_ms: i64,
-    pub end_ms: i64,
+    /// Half-open bounds on the source's time column, in milliseconds. `None`
+    /// means no time restriction, e.g. a source without a time column.
+    pub time_ms: Option<Range<i64>>,
     /// Conjunction of non-null equality predicates; empty means unrestricted.
     pub population: BTreeMap<String, String>,
 }
@@ -49,6 +50,8 @@ pub enum CoverageError {
     NotState,
     #[error("coverage input/reduction disagrees with summary producer")]
     ProducerMismatch,
+    #[error("summary node requires coverage")]
+    Missing,
 }
 
 impl SummaryCoverage {
@@ -57,7 +60,7 @@ impl SummaryCoverage {
             return Err(CoverageError::MissingIdentity);
         }
         for (index, region) in self.regions.iter().enumerate() {
-            if region.start_ms >= region.end_ms {
+            if region.time_ms.as_ref().is_some_and(Range::is_empty) {
                 return Err(CoverageError::InvalidInterval);
             }
             if region.population.keys().any(String::is_empty) {
@@ -93,16 +96,21 @@ impl SummaryCoverage {
         merged.validate()?;
         // Coalesce adjacent intervals only for identical population predicates.
         merged.regions.sort_by(|a, b| {
-            a.population
-                .cmp(&b.population)
-                .then(a.start_ms.cmp(&b.start_ms))
+            a.population.cmp(&b.population).then(
+                a.time_ms
+                    .as_ref()
+                    .map(|t| t.start)
+                    .cmp(&b.time_ms.as_ref().map(|t| t.start)),
+            )
         });
         let mut normalized: Vec<CoverageRegion> = Vec::new();
         for region in merged.regions {
             if let Some(last) = normalized.last_mut() {
-                if last.population == region.population && last.end_ms == region.start_ms {
-                    last.end_ms = region.end_ms;
-                    continue;
+                if let (Some(last_time), Some(time)) = (&mut last.time_ms, &region.time_ms) {
+                    if last.population == region.population && last_time.end == time.start {
+                        last_time.end = time.end;
+                        continue;
+                    }
                 }
             }
             normalized.push(region);
@@ -113,8 +121,11 @@ impl SummaryCoverage {
 }
 impl CoverageRegion {
     fn may_overlap(&self, other: &Self) -> bool {
-        self.start_ms < other.end_ms
-            && other.start_ms < self.end_ms
+        let time_overlaps = match (&self.time_ms, &other.time_ms) {
+            (Some(a), Some(b)) => a.start < b.end && b.start < a.end,
+            _ => true,
+        };
+        time_overlaps
             && !self.population.iter().any(|(dimension, value)| {
                 other
                     .population
diff --git a/crates/types/tests/schema_rebuilding.rs b/crates/types/tests/schema_rebuilding.rs
index 1f1b57dbc..ca30d39e5 100644
--- a/crates/types/tests/schema_rebuilding.rs
+++ b/crates/types/tests/schema_rebuilding.rs
@@ -1,3 +1,4 @@
+use asap_types::ir::summary_coverage::{CoverageRegion, SummaryCoverage};
 use asap_types::ir::{ASAPOp, NonASAPOp, Operator, OperatorNode};
 use asap_types::post_asap::{
     ExactKind, ExactParams, ExecutionTiming, GroupingStrategy, ResultGuarantee, SummaryUpdate,
@@ -7,6 +8,27 @@ use asap_types::pre_asap::{
 };
 use std::rc::Rc;
 
+fn coverage() -> SummaryCoverage {
+    SummaryCoverage {
+        source: "t".into(),
+        input: SummaryUpdate::column(ColumnRef::Named("value".into())),
+        reduction: Reduction::by(vec![0]),
+        regions: vec![CoverageRegion {
+            time_ms: None,
+            population: Default::default(),
+        }],
+    }
+}
+/// Rewrites clear coverage; a rewriter must declare it again for summary nodes.
+fn redeclare(node: OperatorNode) -> Rc<OperatorNode> {
+    let node = Rc::new(node);
+    if !node.requires_coverage() {
+        return node;
+    }
+    assert!(node.validate_structure().is_err());
+    Rc::new((*node).clone().with_coverage(coverage()).unwrap())
+}
+
 fn scan(key_type: DataType, name: &str) -> Rc<OperatorNode> {
     OperatorNode::new_shared(Operator::NonASAP(NonASAPOp::Scan {
         source: Source::Table {
@@ -40,7 +62,12 @@ fn aggregate(child: Rc<OperatorNode>, asap: bool) -> Rc<OperatorNode> {
             having: None,
         })
     };
-    OperatorNode::new_shared(operator).unwrap()
+    let node = OperatorNode::new(operator).unwrap();
+    Rc::new(if asap {
+        node.with_coverage(coverage()).unwrap()
+    } else {
+        node
+    })
 }
 
 /// Rewrites follow changed input types and inherited names for either category.
@@ -50,7 +77,7 @@ fn rebuilding_rederives_schema_for_both_categories() {
         let original = aggregate(scan(DataType::Int64, "key"), asap);
         original.validate_structure().unwrap();
         let replacement = scan(DataType::Utf8, "new_key");
-        let rebuilt = Rc::new(original.map_children(|_| replacement.clone()).unwrap());
+        let rebuilt = redeclare(original.map_children(|_| replacement.clone()).unwrap());
         assert_eq!(rebuilt.schema, rebuilt.operator.output_schema().unwrap());
         rebuilt.validate_structure().unwrap();
     }
@@ -64,14 +91,14 @@ fn rebuilding_preserves_only_explicit_naming_overrides() {
         let mut schema = original.schema.clone();
         schema.fields[0].name = "alias".into();
         schema.fields[0].table = Some("result".into());
-        let original = Rc::new(
-            OperatorNode::with_schema(original.operator.clone(), schema)
-                .with_guarantee(Some(ResultGuarantee::exact("fixture")))
-                .with_timing(Some(ExecutionTiming::QueryTime)),
-        );
+        let mut renamed = OperatorNode::with_schema(original.operator.clone(), schema)
+            .with_guarantee(Some(ResultGuarantee::exact("fixture")))
+            .with_timing(Some(ExecutionTiming::QueryTime));
+        renamed.coverage = original.coverage.clone();
+        let original = Rc::new(renamed);
         original.validate_structure().unwrap();
         let replacement = scan(DataType::Utf8, "new_key");
-        let rebuilt = Rc::new(original.map_children(|_| replacement.clone()).unwrap());
+        let rebuilt = redeclare(original.map_children(|_| replacement.clone()).unwrap());
         assert_eq!(rebuilt.schema.fields[0].name, "alias");
         assert_eq!(rebuilt.schema.fields[0].table.as_deref(), Some("result"));
         assert_eq!(
@@ -110,7 +137,9 @@ fn validation_rejects_structural_overrides_for_both_categories() {
         schema.fields.pop();
         invalid.push(schema);
         for schema in invalid {
-            let forged = Rc::new(OperatorNode::with_schema(original.operator.clone(), schema));
+            let mut forged = OperatorNode::with_schema(original.operator.clone(), schema);
+            forged.coverage = original.coverage.clone();
+            let forged = Rc::new(forged);
             assert!(
                 forged.validate_structure().is_err(),
                 "accepted structural override: {:?}",
diff --git a/crates/types/tests/structure_contract.rs b/crates/types/tests/structure_contract.rs
index d4e164f71..af21337a8 100644
--- a/crates/types/tests/structure_contract.rs
+++ b/crates/types/tests/structure_contract.rs
@@ -13,6 +13,21 @@ fn scan() -> Rc<OperatorNode> {
     }))
     .unwrap()
 }
+/// Tabular coverage for a whole-table summary of column `x`.
+fn whole_table() -> asap_types::ir::summary_coverage::SummaryCoverage {
+    use asap_types::ir::summary_coverage::{CoverageRegion, SummaryCoverage};
+    SummaryCoverage {
+        source: "t".into(),
+        input: asap_types::post_asap::SummaryUpdate::column(
+            asap_types::pre_asap::ColumnRef::Named("x".into()),
+        ),
+        reduction: asap_types::pre_asap::Reduction::by(vec![]),
+        regions: vec![CoverageRegion {
+            time_ms: None,
+            population: Default::default(),
+        }],
+    }
+}
 /// Resolved filters cannot hide invalid scalar types or out-of-scope columns.
 #[test]
 fn invalid_predicates_are_rejected() {
@@ -103,6 +118,8 @@ fn state_evaluations_and_passthrough_keep_their_contracts() {
             grouping: GroupingStrategy::default(),
             filter: None,
         }))
+        .unwrap()
+        .with_coverage(whole_table())
         .unwrap(),
     );
     state.validate_structure().unwrap();
@@ -173,15 +190,19 @@ fn shared_construction_derives_both_operator_categories() {
     use asap_types::pre_asap::{ColumnRef, FieldDataType, Reduction};
 
     let input = scan();
-    let state = OperatorNode::new_shared(Operator::ASAP(ASAPOp::SummaryAgg {
-        child: input.clone(),
-        family: FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum),
-        input: SummaryUpdate::column(ColumnRef::Named("x".into())),
-        reduction: Reduction::by(vec![]),
-        grouping: GroupingStrategy::default(),
-        filter: None,
-    }))
-    .unwrap();
+    let state = Rc::new(
+        OperatorNode::new(Operator::ASAP(ASAPOp::SummaryAgg {
+            child: input.clone(),
+            family: FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum),
+            input: SummaryUpdate::column(ColumnRef::Named("x".into())),
+            reduction: Reduction::by(vec![]),
+            grouping: GroupingStrategy::default(),
+            filter: None,
+        }))
+        .unwrap()
+        .with_coverage(whole_table())
+        .unwrap(),
+    );
     assert_eq!(state.result_kind, OperatorResultKind::State);
     assert!(!state.schema.fields.last().unwrap().is_plain());
     assert!(state.guarantee.is_none());
diff --git a/crates/types/tests/summary_coverage.rs b/crates/types/tests/summary_coverage.rs
index c36ed0ecb..e3059677e 100644
--- a/crates/types/tests/summary_coverage.rs
+++ b/crates/types/tests/summary_coverage.rs
@@ -9,8 +9,7 @@ fn coverage(start: i64, end: i64, population: &[(&str, &str)]) -> SummaryCoverag
         input: SummaryUpdate::column(ColumnRef::Named("latency".into())),
         reduction: Reduction::by(vec![0]),
         regions: vec![CoverageRegion {
-            start_ms: start,
-            end_ms: end,
+            time_ms: Some(start..end),
             population: population
                 .iter()
                 .map(|(k, v)| (k.to_string(), v.to_string()))
@@ -23,7 +22,7 @@ fn coverage(start: i64, end: i64, population: &[(&str, &str)]) -> SummaryCoverag
 fn time_union_preserves_gaps() {
     let merged =
         SummaryCoverage::merge_disjoint(&[coverage(0, 1, &[]), coverage(1, 2, &[])]).unwrap();
-    assert_eq!(merged.regions[0].end_ms, 2);
+    assert_eq!(merged.regions[0].time_ms, Some(0..2));
     assert_eq!(merged.regions.len(), 1);
     let gapped =
         SummaryCoverage::merge_disjoint(&[coverage(0, 1, &[]), coverage(2, 3, &[])]).unwrap();
@@ -76,7 +75,7 @@ fn overlap_and_identity_fail_closed() {
 
 /// Coverage is logical state metadata, and input rewrites invalidate its proof.
 #[test]
-fn node_coverage_is_checked_and_rewrites_clear_it() {
+fn node_coverage_is_required_checked_and_cleared_by_rewrites() {
     use asap_types::{
         ir::operator_properties::Source,
         ir::{ASAPOp, NonASAPOp, Operator, OperatorNode},
@@ -106,11 +105,41 @@ fn node_coverage_is_checked_and_rewrites_clear_it() {
         filter: None,
     }))
     .unwrap();
+    // Summary nodes cannot validate without coverage.
+    assert!(matches!(
+        std::rc::Rc::new(state.clone()).validate_structure(),
+        Err(asap_types::ir::SchemaDerivationError::Coverage(
+            CoverageError::Missing
+        ))
+    ));
     let state = state.with_coverage(declared.clone()).unwrap();
-    assert!(state.coverage.is_some());
+    std::rc::Rc::new(state.clone())
+        .validate_structure()
+        .unwrap();
     let mut bad = declared;
     bad.input = SummaryUpdate::column(ColumnRef::Named("other".into()));
     assert!(state.clone().with_coverage(bad).is_err());
     let rebuilt = state.map_children(Clone::clone).unwrap();
     assert!(rebuilt.coverage.is_none());
 }
+
+/// Sources without a time column declare no time bounds; such a region overlaps
+/// any region it is not population-disjoint from.
+#[test]
+fn regions_without_time_bounds() {
+    let mut tabular = coverage(0, 1, &[("region", "us")]);
+    tabular.regions[0].time_ms = None;
+    let mut other = coverage(0, 1, &[("region", "eu")]);
+    other.regions[0].time_ms = None;
+    assert_eq!(
+        SummaryCoverage::merge_disjoint(&[tabular.clone(), other])
+            .unwrap()
+            .regions
+            .len(),
+        2
+    );
+    assert_eq!(
+        SummaryCoverage::merge_disjoint(&[tabular, coverage(5, 6, &[("region", "us")])]),
+        Err(CoverageError::PossibleOverlap)
+    );
+}
diff --git a/docs/develop_docs/summary-coverage.md b/docs/develop_docs/summary-coverage.md
index 3f452f7b2..d43a52aed 100644
--- a/docs/develop_docs/summary-coverage.md
+++ b/docs/develop_docs/summary-coverage.md
@@ -3,8 +3,10 @@
 `Schema` describes an edge's field layout and committed state type. It does not
 say which observations a summary state was built from: a KLL over `[0,1)` and a
 KLL over `[1,3)` have equal schemas. `OperatorNode.coverage` records that
-separately, as optional logical metadata. `None` means unknown, not unrestricted.
-Rewriting a node's inputs clears it along with other assessed metadata.
+separately. It is required on summary nodes (`SummaryAgg`, and `SummaryMerge`,
+which derives it): `validate_structure` rejects them with `CoverageError::Missing`
+when it is `None`. Other nodes leave it `None`. Rewriting a node's inputs clears
+it, so a rewriter must declare it again with `with_coverage`.
 
 `SummaryCoverage` records:
 
@@ -12,22 +14,41 @@ Rewriting a node's inputs clears it along with other assessed metadata.
   necessarily a time series; region time bounds refer to its time column.
 - `input`, `reduction`: must equal the producing `SummaryAgg`'s fields of the same
   name. `with_coverage` checks this and requires state output.
-- `regions`: a union of `CoverageRegion`s. Each pairs half-open time bounds in
-  milliseconds with a conjunction of non-null equality predicates over population
+- `regions`: a union of `CoverageRegion`s. Each pairs optional half-open time
+  bounds in milliseconds (`None`: no time restriction, e.g. a source without a
+  time column) with a conjunction of non-null equality predicates over population
   dimensions; an empty predicate map means all observations of the source.
 
-Every observation in a region contributes once to the state. Declarations come
-from trusted composition rules or catalogs; nothing is inferred from SQL.
+Every observation in a region contributes once to the state.
+
+## Trusted declarations
+
+Coverage is declared by the composition rule or catalog that built the subtree.
+Only `input` and `reduction` are checked against the producer. Population and
+time bounds are trusted: population is not compared with `SummaryAgg.filter`,
+`Filter` nodes or `Scan.predicates`, and `TimeRange` is relative, so absolute
+bounds cannot be checked. A wrong declaration therefore passes:
+
+```text
+A = SummaryAgg(filter: region='us'), declared {region: eu} × [0,1)   ← wrong
+B = SummaryAgg(filter: region='us'), declared {region: us} × [0,1)
+merge_disjoint(A, B) is accepted, and every US observation is counted twice.
+```
+
+Issue #570 tracks checking population against the subtree's predicates.
+
+## Merging
 
 `merge_disjoint` requires equal source/input/reduction and provably disjoint
 regions. Adjacent intervals coalesce only with identical population predicates;
 gaps remain separate. Conflicting values for the same dimension prove disjointness.
-Different dimensions do not: `region=us` can overlap `tier=premium`.
+Different dimensions do not: `region=us` can overlap `tier=premium`. A region
+without time bounds overlaps every region it is not population-disjoint from.
 
 `us×[0,1)` merged with `eu×[1,2)` remains two regions, not `{us,eu}×[0,2)`.
 Empty `regions` is known empty coverage. Empty merge input is invalid.
 
-Not covered: arbitrary or null predicates, unbounded time, idempotent set-union
-families, and checking that coverage contains a requested query window or
-population. The contract provides no runtime merge capability, accuracy
-certificate, storage policy or execution timing.
+Not covered: arbitrary or null predicates, idempotent set-union families, and
+checking that coverage contains a requested query window or population. The
+contract provides no runtime merge capability, accuracy certificate, storage
+policy or execution timing.

From feca0d52d58128b607efb8db5a8c511a20a2ee07 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 17:29:17 +0000
Subject: [PATCH 06/48] docs: explain the summary coverage problem with
 examples

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 docs/develop_docs/summary-coverage.md | 198 ++++++++++++++++++++------
 1 file changed, 157 insertions(+), 41 deletions(-)

diff --git a/docs/develop_docs/summary-coverage.md b/docs/develop_docs/summary-coverage.md
index d43a52aed..1ad87c570 100644
--- a/docs/develop_docs/summary-coverage.md
+++ b/docs/develop_docs/summary-coverage.md
@@ -1,54 +1,170 @@
 # Summary coverage contract
 
-`Schema` describes an edge's field layout and committed state type. It does not
-say which observations a summary state was built from: a KLL over `[0,1)` and a
-KLL over `[1,3)` have equal schemas. `OperatorNode.coverage` records that
-separately. It is required on summary nodes (`SummaryAgg`, and `SummaryMerge`,
-which derives it): `validate_structure` rejects them with `CoverageError::Missing`
-when it is `None`. Other nodes leave it `None`. Rewriting a node's inputs clears
-it, so a rewriter must declare it again with `with_coverage`.
-
-`SummaryCoverage` records:
-
-- `source`: the observation data source. It can be any tabular data, not
-  necessarily a time series; region time bounds refer to its time column.
-- `input`, `reduction`: must equal the producing `SummaryAgg`'s fields of the same
-  name. `with_coverage` checks this and requires state output.
-- `regions`: a union of `CoverageRegion`s. Each pairs optional half-open time
-  bounds in milliseconds (`None`: no time restriction, e.g. a source without a
-  time column) with a conjunction of non-null equality predicates over population
-  dimensions; an empty predicate map means all observations of the source.
-
-Every observation in a region contributes once to the state.
+## Problem: a schema says what a summary *is*, not what it *summarizes*
 
-## Trusted declarations
+Every ASAP edge has one `Schema`. For a summary edge it records the field
+layout and the committed state type:
+
+```rust
+pub struct Schema {
+    pub fields: Vec<Field>,            // e.g. job: Plain(Utf8), state: Sketch(KLL{k=200}, PerSubpopulationInstance)
+    pub time_index: Option<ColumnId>,  // position of a timestamp column, not a time range
+    pub unique_keys: Vec<Vec<ColumnId>>,
+    pub closed: bool,
+}
+```
 
-Coverage is declared by the composition rule or catalog that built the subtree.
-Only `input` and `reduction` are checked against the producer. Population and
-time bounds are trusted: population is not compared with `SummaryAgg.filter`,
-`Filter` nodes or `Scan.predicates`, and `TimeRange` is relative, so absolute
-bounds cannot be checked. A wrong declaration therefore passes:
+Nothing in it says **which time range** or **which population (label values)**
+the state was built from. Filters, group keys and windows are deliberately not
+`Schema` or `Field` members. This becomes a gap once the planner combines
+existing summary states (`SummaryMerge`, reuse of ingested panes, sub-DAG
+sharing). The producer no longer shows where a state came from, so only the
+schema is left to compare. Every example below uses two states with
+**exactly equal schemas**:
 
 ```text
-A = SummaryAgg(filter: region='us'), declared {region: eu} × [0,1)   ← wrong
-B = SummaryAgg(filter: region='us'), declared {region: us} × [0,1)
-merge_disjoint(A, B) is accepted, and every US observation is counted twice.
+Schema(job: Plain(Utf8), state: Sketch(KLL{k=200}, PerSubpopulationInstance)), result_kind = State
 ```
 
-Issue #570 tracks checking population against the subtree's predicates.
+### Example 1: time. Equal schemas, different answers
+
+| Input A | Input B | Merging A and B is… |
+|---|---|---|
+| latency, `[00:00, 00:01)` | latency, `[00:01, 00:02)` | correct: p99 over `[00:00, 00:02)` |
+| latency, `[00:00, 00:02)` | latency, `[00:01, 00:03)` | **wrong**: every observation in `[00:01, 00:02)` is counted twice, which skews the quantile and doubles counts or frequencies |
+| latency, `[00:00, 00:01)` | latency, `[00:02, 00:03)` | correct only for `[0,1) ∪ [2,3)`; **wrong** if used for the continuous window `[00:00, 00:03)` |
+
+`time_index` is a column position. A KLL state has no timestamp column, so
+`time_index` is `None` in all three rows and the schema cannot tell them apart.
+
+### Example 2: population (label values). Equal schemas, different answers
+
+| Input A | Input B | Merging A and B is… |
+|---|---|---|
+| `region='us'` | `region='eu'` | correct: p99 for `us ∪ eu` within each `job` |
+| `region='us'` | `tier='premium'` | **wrong**: premium US requests are counted in both inputs |
+| `region='us'` | `region='us'` | **wrong**: everything is counted twice |
+
+`region` is a filter label, not an output column, so it never appears in the
+schema. The `job` field only says the state is grouped by job. It does not say
+which jobs or which rows contributed.
+
+### Example 3: time and population together
+
+A = `us × [0,1)` and B = `eu × [1,2)`. The merged state covers exactly those two
+blocks. Storing a time range and a label set separately would give
+`{us,eu} × [0,2)`. That claims EU data for `[0,1)` and US data for `[1,2)`
+that was never read. Time and population must stay **paired per region**.
+
+### Example 4: answering a query from a stored state
+
+Query: `p99(latency) WHERE region='us' AND ts IN [10:00, 10:05) GROUP BY job`.
+A stored state with the matching schema could hold US data for 10:00–10:05, EU
+data, or US data for only 10:00–10:03. All three have the same schema. The
+schema confirms that the state *type* fits, not that the *contents* fit.
+
+**Conclusion.** Schema equality is necessary but not sufficient for composing
+or reusing summaries. Without time and population metadata, the planner must
+either refuse every composition or accept silent double counting and missing
+data.
+
+## The contract
+
+`Schema` stays the layout contract and does **not** describe coverage. Coverage
+is a separate field on the node, next to `schema`:
+
+```text
+OperatorNode
+├── schema: Schema                    what each output row looks like
+└── coverage: Option<SummaryCoverage> which observations the state holds
+```
+
+Coverage cannot live inside `Schema`. `SummaryMerge` requires equal input
+schemas, and the inputs of a useful merge (`[0,1)` + `[1,2)`) always have
+different coverage.
+
+```rust
+pub struct SummaryCoverage {
+    pub source: String,               // observation data source; any tabular data, not necessarily time series
+    pub input: SummaryUpdate,         // must equal the producing SummaryAgg.input
+    pub reduction: Reduction,         // must equal the producing SummaryAgg.reduction
+    pub regions: Vec<CoverageRegion>, // union of time × population blocks
+}
+pub struct CoverageRegion {
+    pub time_ms: Option<Range<i64>>,          // half-open, on the source's time column; None = no time restriction
+    pub population: BTreeMap<String, String>, // label = value AND …; empty = all observations
+}
+```
+
+Rules:
+
+- Coverage is **required on summary nodes**. `validate_structure` rejects a
+  `SummaryAgg` or `SummaryMerge` whose coverage is `None` with
+  `CoverageError::Missing`. Other nodes leave it `None`. The field is an
+  `Option` only because all operators share `OperatorNode`.
+- `with_coverage` validates the declaration, requires `State` output
+  (`NotState`), and checks `input`/`reduction` against a `SummaryAgg` producer
+  (`ProducerMismatch`). `validate_structure` re-checks it.
+- `SummaryMerge` derives its coverage from its inputs. `validate_structure`
+  rejects a retained value that differs from that union.
+- Rewriting a node's inputs clears its coverage. The rewriter must declare it
+  again with `with_coverage`.
+- Every observation in a region contributes once to the state. `regions = []`
+  means known empty coverage.
+- `time_ms: None` is for sources without a time column. Such a region overlaps
+  every region it is not population-disjoint from.
 
 ## Merging
 
-`merge_disjoint` requires equal source/input/reduction and provably disjoint
-regions. Adjacent intervals coalesce only with identical population predicates;
-gaps remain separate. Conflicting values for the same dimension prove disjointness.
-Different dimensions do not: `region=us` can overlap `tier=premium`. A region
-without time bounds overlaps every region it is not population-disjoint from.
+`SummaryCoverage::merge_disjoint` requires equal `source`/`input`/`reduction`
+and provably disjoint regions. Two regions are disjoint when their time ranges
+do not intersect, or when they give different values for the same population
+label. Different labels prove nothing. The examples above come out as:
+
+| Case | Result |
+|---|---|
+| `[0,1)` + `[1,2)`, same population | accepted, coalesced to one region `[0,2)` |
+| `[0,1)` + `[2,3)` | accepted, **two** regions (gap kept) |
+| `[0,2)` + `[1,3)` | `PossibleOverlap` |
+| `region=us` + `region=eu`, same time | accepted, two regions |
+| `region=us` + `tier=premium` | `PossibleOverlap` |
+| `us×[0,1)` + `eu×[1,2)` | accepted, two regions, never widened to `{us,eu}×[0,2)` |
+| no time bounds + any region of the same population | `PossibleOverlap` |
+| different source / input / reduction | `IncompatibleInput` |
+
+Adjacent intervals coalesce only when their population maps are identical.
+Merging an empty input list fails with `EmptyMerge`.
+
+## Trusted declarations
+
+Coverage is declared by the composition rule or catalog that built the
+subtree. Nothing is inferred from SQL. Only `input` and `reduction` are checked
+against the producer. Population is not compared with `SummaryAgg.filter`,
+`Filter` nodes or `Scan.predicates`. Time bounds cannot be checked, because
+`TimeRange` stores a relative duration. So a wrong declaration passes:
+
+```text
+A = SummaryAgg(filter: region='us', input: latency, reduction: by job)
+    declared coverage: {region: eu} × [0,1)        ← wrong; the state holds US data
+B = SummaryAgg(filter: region='us', input: latency, reduction: by job)
+    declared coverage: {region: us} × [0,1)
+
+merge_disjoint(A, B)  → accepted ("eu" ≠ "us" proves disjoint)
+actual merged state   → every US observation in [0,1) counted twice
+a query for region='eu' could also be answered from A, which holds no EU data
+```
+
+Issue #570 tracks the check. The declared population must exactly equal the
+`column = literal` predicates collected between the `SummaryAgg` and its
+`Scan`, and any other predicate shape fails closed. It starts strict about
+which operators may sit on that path (only `Filter` and `TimeRange`), because
+`Project` or `Join` can rename columns or change rows.
 
-`us×[0,1)` merged with `eu×[1,2)` remains two regions, not `{us,eu}×[0,2)`.
-Empty `regions` is known empty coverage. Empty merge input is invalid.
+## Not covered
 
-Not covered: arbitrary or null predicates, idempotent set-union families, and
-checking that coverage contains a requested query window or population. The
-contract provides no runtime merge capability, accuracy certificate, storage
-policy or execution timing.
+- Checking that coverage *contains* a requested query window or population
+  (Example 4). That is a later query-relative check, which uses this data.
+- Predicates beyond non-null equality conjunctions; idempotent set-union
+  families.
+- Runtime merge kernels, accuracy certificates, storage policy or execution
+  timing.

From ea7e659b495dedecfd0170062beb7c2a0b376cc3 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 17:32:07 +0000
Subject: [PATCH 07/48] refactor(ir): keep only time and population in
 SummaryCoverage

Given required coverage on summary nodes, input and reduction duplicated the
producing SummaryAgg fields; drop them along with ProducerMismatch. Type source
as Source, matching Scan.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/types/src/ir/node.rs              |  8 -----
 crates/types/src/ir/summary_coverage.rs  | 34 ++++++--------------
 crates/types/tests/schema_rebuilding.rs  |  6 ++--
 crates/types/tests/structure_contract.rs | 10 +++---
 crates/types/tests/summary_coverage.rs   | 41 +++++++++++++-----------
 docs/develop_docs/summary-coverage.md    | 24 +++++++-------
 6 files changed, 53 insertions(+), 70 deletions(-)

diff --git a/crates/types/src/ir/node.rs b/crates/types/src/ir/node.rs
index bf2e9479e..392204d9a 100644
--- a/crates/types/src/ir/node.rs
+++ b/crates/types/src/ir/node.rs
@@ -151,14 +151,6 @@ impl OperatorNode {
         if self.result_kind != OperatorResultKind::State {
             return Err(CoverageError::NotState.into());
         }
-        if let Some(ASAPOp::SummaryAgg {
-            input, reduction, ..
-        }) = self.asap()
-        {
-            if *input != coverage.input || *reduction != coverage.reduction {
-                return Err(CoverageError::ProducerMismatch.into());
-            }
-        }
         self.coverage = Some(coverage);
         Ok(self)
     }
diff --git a/crates/types/src/ir/summary_coverage.rs b/crates/types/src/ir/summary_coverage.rs
index 5056ef3f2..a95896eb8 100644
--- a/crates/types/src/ir/summary_coverage.rs
+++ b/crates/types/src/ir/summary_coverage.rs
@@ -1,8 +1,7 @@
 //! Joint time/population coverage for summary composition, independent of schema.
 //! Equality predicates are a deliberately narrow proof vocabulary. Unsupported
 //! predicates cannot be declared disjoint merely by giving them different names.
-use super::operator_properties::Reduction;
-use crate::post_asap::SummaryUpdate;
+use crate::pre_asap::Source;
 use serde::{Deserialize, Serialize};
 use std::collections::BTreeMap;
 use std::ops::Range;
@@ -11,13 +10,9 @@ use thiserror::Error;
 #[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
 #[serde(deny_unknown_fields)]
 pub struct SummaryCoverage {
-    /// Observation data source identity: any table or stream, not necessarily
-    /// time series. Region time bounds refer to its time column.
-    pub source: String,
-    /// Must equal the producing `SummaryAgg.input`.
-    pub input: SummaryUpdate,
-    /// Must equal the producing `SummaryAgg.reduction`.
-    pub reduction: Reduction,
+    /// Observation data source, as named by `Scan`: a table or a time series.
+    /// Region time bounds refer to its time column.
+    pub source: Source,
     /// Union of joint regions; never the Cartesian product of independent bounds.
     pub regions: Vec<CoverageRegion>,
 }
@@ -34,31 +29,24 @@ pub struct CoverageRegion {
 
 #[derive(Debug, Clone, PartialEq, Eq, Error)]
 pub enum CoverageError {
-    #[error("coverage requires an explicit source identity")]
-    MissingIdentity,
     #[error("coverage interval must have start < end")]
     InvalidInterval,
     #[error("population dimension names cannot be empty")]
     InvalidPopulation,
-    #[error("summary source, input or reduction differs")]
-    IncompatibleInput,
+    #[error("summary coverage sources differ")]
+    SourceMismatch,
     #[error("coverage overlap is not proven absent")]
     PossibleOverlap,
     #[error("coverage merge requires at least one input")]
     EmptyMerge,
     #[error("summary coverage requires state output")]
     NotState,
-    #[error("coverage input/reduction disagrees with summary producer")]
-    ProducerMismatch,
     #[error("summary node requires coverage")]
     Missing,
 }
 
 impl SummaryCoverage {
     pub fn validate(&self) -> Result<(), CoverageError> {
-        if self.source.is_empty() {
-            return Err(CoverageError::MissingIdentity);
-        }
         for (index, region) in self.regions.iter().enumerate() {
             if region.time_ms.as_ref().is_some_and(Range::is_empty) {
                 return Err(CoverageError::InvalidInterval);
@@ -78,18 +66,16 @@ impl SummaryCoverage {
 
     /// Every observation in a region is assumed to contribute once to the state.
     /// Compose once-per-observation summaries only when their joint regions are
-    /// provably disjoint. Family merge capability and accuracy are separate checks.
+    /// provably disjoint. Update/reduction compatibility, family merge capability
+    /// and accuracy are checked by `SummaryMerge`, not here.
     pub fn merge_disjoint(inputs: &[Self]) -> Result<Self, CoverageError> {
         let first = inputs.first().ok_or(CoverageError::EmptyMerge)?;
         let mut merged = first.clone();
         merged.regions.clear();
         for input in inputs {
             input.validate()?;
-            if input.source != first.source
-                || input.input != first.input
-                || input.reduction != first.reduction
-            {
-                return Err(CoverageError::IncompatibleInput);
+            if input.source != first.source {
+                return Err(CoverageError::SourceMismatch);
             }
             merged.regions.extend(input.regions.iter().cloned());
         }
diff --git a/crates/types/tests/schema_rebuilding.rs b/crates/types/tests/schema_rebuilding.rs
index ca30d39e5..fc7a3f145 100644
--- a/crates/types/tests/schema_rebuilding.rs
+++ b/crates/types/tests/schema_rebuilding.rs
@@ -10,9 +10,9 @@ use std::rc::Rc;
 
 fn coverage() -> SummaryCoverage {
     SummaryCoverage {
-        source: "t".into(),
-        input: SummaryUpdate::column(ColumnRef::Named("value".into())),
-        reduction: Reduction::by(vec![0]),
+        source: Source::Table {
+            table_ref: "t".into(),
+        },
         regions: vec![CoverageRegion {
             time_ms: None,
             population: Default::default(),
diff --git a/crates/types/tests/structure_contract.rs b/crates/types/tests/structure_contract.rs
index af21337a8..d7c144f4e 100644
--- a/crates/types/tests/structure_contract.rs
+++ b/crates/types/tests/structure_contract.rs
@@ -13,15 +13,13 @@ fn scan() -> Rc<OperatorNode> {
     }))
     .unwrap()
 }
-/// Tabular coverage for a whole-table summary of column `x`.
+/// Tabular coverage for a whole-table summary.
 fn whole_table() -> asap_types::ir::summary_coverage::SummaryCoverage {
     use asap_types::ir::summary_coverage::{CoverageRegion, SummaryCoverage};
     SummaryCoverage {
-        source: "t".into(),
-        input: asap_types::post_asap::SummaryUpdate::column(
-            asap_types::pre_asap::ColumnRef::Named("x".into()),
-        ),
-        reduction: asap_types::pre_asap::Reduction::by(vec![]),
+        source: Source::Table {
+            table_ref: "t".into(),
+        },
         regions: vec![CoverageRegion {
             time_ms: None,
             population: Default::default(),
diff --git a/crates/types/tests/summary_coverage.rs b/crates/types/tests/summary_coverage.rs
index e3059677e..3b99e9bba 100644
--- a/crates/types/tests/summary_coverage.rs
+++ b/crates/types/tests/summary_coverage.rs
@@ -1,13 +1,18 @@
 //! Coverage composition preserves gaps and rejects duplicate observations.
 use asap_types::{
-    ir::operator_properties::Reduction, ir::summary_coverage::*, post_asap::SummaryUpdate,
-    pre_asap::ColumnRef,
+    ir::operator_properties::Reduction,
+    ir::summary_coverage::*,
+    post_asap::SummaryUpdate,
+    pre_asap::{ColumnRef, Source},
 };
+fn table(name: &str) -> Source {
+    Source::Table {
+        table_ref: name.into(),
+    }
+}
 fn coverage(start: i64, end: i64, population: &[(&str, &str)]) -> SummaryCoverage {
     SummaryCoverage {
-        source: "flows".into(),
-        input: SummaryUpdate::column(ColumnRef::Named("latency".into())),
-        reduction: Reduction::by(vec![0]),
+        source: table("flows"),
         regions: vec![CoverageRegion {
             time_ms: Some(start..end),
             population: population
@@ -61,11 +66,18 @@ fn overlap_and_identity_fail_closed() {
         ]),
         Err(CoverageError::PossibleOverlap)
     );
+    assert_eq!(
+        SummaryCoverage::merge_disjoint(&[
+            coverage(0, 2, &[("region", "us")]),
+            coverage(0, 2, &[("region", "us")])
+        ]),
+        Err(CoverageError::PossibleOverlap)
+    );
     let mut other = coverage(1, 2, &[]);
-    other.source = "other-flows".into();
+    other.source = table("other-flows");
     assert_eq!(
         SummaryCoverage::merge_disjoint(&[coverage(0, 1, &[]), other]),
-        Err(CoverageError::IncompatibleInput)
+        Err(CoverageError::SourceMismatch)
     );
     assert_eq!(
         coverage(2, 1, &[]).validate(),
@@ -77,21 +89,17 @@ fn overlap_and_identity_fail_closed() {
 #[test]
 fn node_coverage_is_required_checked_and_cleared_by_rewrites() {
     use asap_types::{
-        ir::operator_properties::Source,
         ir::{ASAPOp, NonASAPOp, Operator, OperatorNode},
         post_asap::{SketchAlgorithm, SketchKind, SketchParams},
         pre_asap::{DataType, Field, FieldDataType, Schema},
     };
     let raw = OperatorNode::new_shared(Operator::NonASAP(NonASAPOp::Scan {
-        source: Source::Table {
-            table_ref: "flows".into(),
-        },
+        source: table("flows"),
         predicates: vec![],
         schema: Schema::new(vec![Field::plain("latency", DataType::Float64, false)]),
     }))
     .unwrap();
-    let mut declared = coverage(0, 1, &[]);
-    declared.reduction = Reduction::by(vec![]);
+    let declared = coverage(0, 1, &[]);
     assert!((*raw).clone().with_coverage(declared.clone()).is_err());
     let state = OperatorNode::new(Operator::ASAP(ASAPOp::SummaryAgg {
         child: raw,
@@ -99,8 +107,8 @@ fn node_coverage_is_required_checked_and_cleared_by_rewrites() {
             SketchKind::new(SketchAlgorithm::Kll, SketchParams::Kll { k: 200 }),
             Default::default(),
         ),
-        input: declared.input.clone(),
-        reduction: declared.reduction.clone(),
+        input: SummaryUpdate::column(ColumnRef::Named("latency".into())),
+        reduction: Reduction::by(vec![]),
         grouping: Default::default(),
         filter: None,
     }))
@@ -116,9 +124,6 @@ fn node_coverage_is_required_checked_and_cleared_by_rewrites() {
     std::rc::Rc::new(state.clone())
         .validate_structure()
         .unwrap();
-    let mut bad = declared;
-    bad.input = SummaryUpdate::column(ColumnRef::Named("other".into()));
-    assert!(state.clone().with_coverage(bad).is_err());
     let rebuilt = state.map_children(Clone::clone).unwrap();
     assert!(rebuilt.coverage.is_none());
 }
diff --git a/docs/develop_docs/summary-coverage.md b/docs/develop_docs/summary-coverage.md
index 1ad87c570..0de7d30fc 100644
--- a/docs/develop_docs/summary-coverage.md
+++ b/docs/develop_docs/summary-coverage.md
@@ -85,9 +85,7 @@ different coverage.
 
 ```rust
 pub struct SummaryCoverage {
-    pub source: String,               // observation data source; any tabular data, not necessarily time series
-    pub input: SummaryUpdate,         // must equal the producing SummaryAgg.input
-    pub reduction: Reduction,         // must equal the producing SummaryAgg.reduction
+    pub source: Source,               // as named by Scan: Table { table_ref } or TimeSeries { metric }
     pub regions: Vec<CoverageRegion>, // union of time × population blocks
 }
 pub struct CoverageRegion {
@@ -102,9 +100,12 @@ Rules:
   `SummaryAgg` or `SummaryMerge` whose coverage is `None` with
   `CoverageError::Missing`. Other nodes leave it `None`. The field is an
   `Option` only because all operators share `OperatorNode`.
-- `with_coverage` validates the declaration, requires `State` output
-  (`NotState`), and checks `input`/`reduction` against a `SummaryAgg` producer
-  (`ProducerMismatch`). `validate_structure` re-checks it.
+- Coverage holds only what the operator does not already record. What is fed
+  into the state and how it is grouped stay on `SummaryAgg.input` and
+  `SummaryAgg.reduction`; `SummaryMerge` compares those on its inputs. `source`
+  uses the same `Source` type as `Scan`, so equal sources compare equal.
+- `with_coverage` validates the declaration and requires `State` output
+  (`NotState`). `validate_structure` re-checks it.
 - `SummaryMerge` derives its coverage from its inputs. `validate_structure`
   rejects a retained value that differs from that union.
 - Rewriting a node's inputs clears its coverage. The rewriter must declare it
@@ -116,8 +117,9 @@ Rules:
 
 ## Merging
 
-`SummaryCoverage::merge_disjoint` requires equal `source`/`input`/`reduction`
-and provably disjoint regions. Two regions are disjoint when their time ranges
+`SummaryCoverage::merge_disjoint` requires equal `source` and provably
+disjoint regions. `SummaryMerge` additionally requires equal input schemas and
+equal `input`/`reduction` on its inputs' producers. Two regions are disjoint when their time ranges
 do not intersect, or when they give different values for the same population
 label. Different labels prove nothing. The examples above come out as:
 
@@ -127,10 +129,11 @@ label. Different labels prove nothing. The examples above come out as:
 | `[0,1)` + `[2,3)` | accepted, **two** regions (gap kept) |
 | `[0,2)` + `[1,3)` | `PossibleOverlap` |
 | `region=us` + `region=eu`, same time | accepted, two regions |
+| `region=us` + `region=us`, same time | `PossibleOverlap` |
 | `region=us` + `tier=premium` | `PossibleOverlap` |
 | `us×[0,1)` + `eu×[1,2)` | accepted, two regions, never widened to `{us,eu}×[0,2)` |
 | no time bounds + any region of the same population | `PossibleOverlap` |
-| different source / input / reduction | `IncompatibleInput` |
+| different source | `SourceMismatch` |
 
 Adjacent intervals coalesce only when their population maps are identical.
 Merging an empty input list fails with `EmptyMerge`.
@@ -138,8 +141,7 @@ Merging an empty input list fails with `EmptyMerge`.
 ## Trusted declarations
 
 Coverage is declared by the composition rule or catalog that built the
-subtree. Nothing is inferred from SQL. Only `input` and `reduction` are checked
-against the producer. Population is not compared with `SummaryAgg.filter`,
+subtree. Nothing is inferred from SQL. Population is not compared with `SummaryAgg.filter`,
 `Filter` nodes or `Scan.predicates`. Time bounds cannot be checked, because
 `TimeRange` stores a relative duration. So a wrong declaration passes:
 

From 3fb464b2b3ab3b04c52e66cc8a239f37391fb713 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 17:37:33 +0000
Subject: [PATCH 08/48] refactor(cost): rename SourceCoverage to ScanSelection

SourceCoverage names the rows a physical scan reads for cost comparison, not
which observations a summary state holds; rename it so it is not confused with
SummaryCoverage.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 .../asap-aware-mapping/src/analytical_cost.rs | 77 +++++++++----------
 .../src/physical_operator_statistics.rs       |  8 +-
 .../src/physical_plan_cost_model.rs           | 12 +--
 .../src/query_physical_lowering.rs            | 51 ++++++------
 crates/asap-aware-mapping/src/storage_io.rs   |  2 +-
 .../src/summary_maintenance_cost/estimator.rs |  8 +-
 .../src/summary_maintenance_cost/evidence.rs  |  2 +-
 .../src/summary_maintenance_cost/model.rs     | 28 +++----
 .../tests/physical_handoff_cost.rs            | 12 +--
 crates/asap-aware-mapping/tests/storage_io.rs | 14 ++--
 crates/devtools/src/bin/dag_export.rs         |  8 +-
 .../architecture/physical-plan-integration.md |  2 +-
 .../architecture/planner-runtime-contract.md  |  2 +-
 .../analytical-resource-cost.md               | 20 ++---
 14 files changed, 121 insertions(+), 125 deletions(-)

diff --git a/crates/asap-aware-mapping/src/analytical_cost.rs b/crates/asap-aware-mapping/src/analytical_cost.rs
index 3c19960a9..ad921d23a 100644
--- a/crates/asap-aware-mapping/src/analytical_cost.rs
+++ b/crates/asap-aware-mapping/src/analytical_cost.rs
@@ -14,7 +14,7 @@ use serde::{Deserialize, Serialize};
 
 use crate::physical_operator_statistics::{
     validate_comparison_scopes, ComparisonScope, EdgeStatistics, OperatorStatistics,
-    OperatorStatisticsProvider, PromqlEdgeStatistics, PromqlValueKind, SourceCoverage,
+    OperatorStatisticsProvider, PromqlEdgeStatistics, PromqlValueKind, ScanSelection,
 };
 
 /// Version of the analytical formulas applied to evidenced physical plans.
@@ -383,9 +383,9 @@ pub struct PhysicalDAGNode {
     pub operator: PhysicalOperator,
     pub children: Vec<String>,
     /// Exact comparison-scope coverage consumed by a scan. Non-scan nodes
-    /// leave this empty. Reusing `SourceCoverage` prevents a physical plan
+    /// leave this empty. Reusing `ScanSelection` prevents a physical plan
     /// from naming a source independently of its snapshot and predicates.
-    pub source_coverage: Option<SourceCoverage>,
+    pub scan_selection: Option<ScanSelection>,
     /// Maximum transient edge buffer, distinct from logical `output_bytes`.
     pub output_buffer_bytes: u64,
     /// State that remains live after this node finishes (zero for ordinary
@@ -573,9 +573,10 @@ pub fn estimate_physical_dag_with_cache(
         let node_statistics = &resolved_statistics[id];
         match node.operator {
             PhysicalOperator::Scan => {
-                let coverage = node.source_coverage.as_ref().ok_or_else(|| {
-                    AnalyticalCostError::MissingScanSourceCoverage(node.id.clone())
-                })?;
+                let coverage = node
+                    .scan_selection
+                    .as_ref()
+                    .ok_or_else(|| AnalyticalCostError::MissingScanSelection(node.id.clone()))?;
                 if !scope.sources.contains(coverage) {
                     return Err(AnalyticalCostError::ScanOutsideComparisonScope(
                         node.id.clone(),
@@ -585,9 +586,9 @@ pub fn estimate_physical_dag_with_cache(
                     consumed_sources.push(coverage);
                 }
             }
-            _ if node.source_coverage.is_some() => {
+            _ if node.scan_selection.is_some() => {
                 return Err(AnalyticalCostError::InvalidPhysicalDAG(
-                    "only scan nodes may declare source coverage",
+                    "only scan nodes may declare scan selection",
                 ));
             }
             _ => {}
@@ -2199,9 +2200,9 @@ pub enum AnalyticalCostError {
     UnsupportedSummaryOperation(&'static str),
     #[error("required comparison-scope field {0} is missing")]
     MissingComparisonScope(&'static str),
-    #[error("scan node {0} does not declare source coverage")]
-    MissingScanSourceCoverage(String),
-    #[error("scan node {0} reads source coverage outside the comparison scope")]
+    #[error("scan node {0} does not declare scan selection")]
+    MissingScanSelection(String),
+    #[error("scan node {0} reads scan selection outside the comparison scope")]
     ScanOutsideComparisonScope(String),
     #[error("raw and candidate comparison scopes differ in {0}")]
     ComparisonScopeMismatch(&'static str),
@@ -2234,7 +2235,7 @@ mod tests {
     use crate::physical_operator_statistics::{
         validate_comparison_scopes, BinaryEdgeStatistics, ComparisonScope, EdgeStatistics,
         OperatorStatistics, PartitionStatistics, PromqlBinaryEdgeStatistics, PromqlEdgeStatistics,
-        PromqlUnaryEdgeStatistics, PromqlValueKind, SourceCoverage, UnaryEdgeStatistics,
+        PromqlUnaryEdgeStatistics, PromqlValueKind, ScanSelection, UnaryEdgeStatistics,
     };
 
     /// Analytical estimates reuse the shared dimensions while preserving exact
@@ -2475,7 +2476,7 @@ mod tests {
                 id: "scan".into(),
                 operator: PhysicalOperator::Scan,
                 children: vec![],
-                source_coverage: Some(comparison_scope().sources[0].clone()),
+                scan_selection: Some(comparison_scope().sources[0].clone()),
                 output_buffer_bytes: 8,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::PerEvaluation,
@@ -2484,7 +2485,7 @@ mod tests {
                 id: "filter".into(),
                 operator: filter_operator(),
                 children: vec!["scan".into()],
-                source_coverage: None,
+                scan_selection: None,
                 output_buffer_bytes: 8,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::PerEvaluation,
@@ -2814,7 +2815,7 @@ mod tests {
                 id: "scan".into(),
                 operator: PhysicalOperator::Scan,
                 children: vec![],
-                source_coverage: Some(coverage),
+                scan_selection: Some(coverage),
                 output_buffer_bytes: 10,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::PerEvaluation,
@@ -2823,7 +2824,7 @@ mod tests {
                 id: "left".into(),
                 operator: filter_operator(),
                 children: vec!["scan".into()],
-                source_coverage: None,
+                scan_selection: None,
                 output_buffer_bytes: 4,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::PerEvaluation,
@@ -2832,7 +2833,7 @@ mod tests {
                 id: "right".into(),
                 operator: filter_operator(),
                 children: vec!["scan".into()],
-                source_coverage: None,
+                scan_selection: None,
                 output_buffer_bytes: 4,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::PerEvaluation,
@@ -2841,7 +2842,7 @@ mod tests {
                 id: "root".into(),
                 operator: PhysicalOperator::Concat,
                 children: vec!["left".into(), "right".into()],
-                source_coverage: None,
+                scan_selection: None,
                 output_buffer_bytes: 8,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::PerEvaluation,
@@ -2905,7 +2906,7 @@ mod tests {
                 id: "scan".into(),
                 operator: PhysicalOperator::Scan,
                 children: vec![],
-                source_coverage: Some(coverage),
+                scan_selection: Some(coverage),
                 output_buffer_bytes: 10,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::Once,
@@ -2914,7 +2915,7 @@ mod tests {
                 id: "state".into(),
                 operator: aggregate_operator(),
                 children: vec!["scan".into()],
-                source_coverage: None,
+                scan_selection: None,
                 output_buffer_bytes: 16,
                 retained_bytes: 32,
                 execution: ExecutionMultiplicity::Once,
@@ -2926,7 +2927,7 @@ mod tests {
                     offset: 0,
                 },
                 children: vec!["state".into()],
-                source_coverage: None,
+                scan_selection: None,
                 output_buffer_bytes: 16,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::PerEvaluation,
@@ -2987,7 +2988,7 @@ mod tests {
                 lookback: Some(DurationMs(300_000)),
                 as_of: Some(TimestampMs(1_000)),
             },
-            sources: vec![SourceCoverage {
+            sources: vec![ScanSelection {
                 source: Source::Table {
                     table_ref: "metrics".into(),
                 },
@@ -3059,7 +3060,7 @@ mod tests {
                 id: "scan".into(),
                 operator: PhysicalOperator::Scan,
                 children: vec![],
-                source_coverage: Some(coverage),
+                scan_selection: Some(coverage),
                 output_buffer_bytes: 10,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::PerEvaluation,
@@ -3068,7 +3069,7 @@ mod tests {
                 id: "filter".into(),
                 operator: filter_operator(),
                 children: vec!["scan".into()],
-                source_coverage: None,
+                scan_selection: None,
                 output_buffer_bytes: 4,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::PerEvaluation,
@@ -3134,7 +3135,7 @@ mod tests {
                 id: "scan".into(),
                 operator: PhysicalOperator::Scan,
                 children: vec![],
-                source_coverage: Some(coverage),
+                scan_selection: Some(coverage),
                 output_buffer_bytes: 10,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::PerEvaluation,
@@ -3143,7 +3144,7 @@ mod tests {
                 id: "filter".into(),
                 operator: filter_operator(),
                 children: vec!["scan".into()],
-                source_coverage: None,
+                scan_selection: None,
                 output_buffer_bytes: 4,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::PerEvaluation,
@@ -3197,7 +3198,7 @@ mod tests {
                 id: "scan".into(),
                 operator: PhysicalOperator::Scan,
                 children: vec![],
-                source_coverage: Some(coverage),
+                scan_selection: Some(coverage),
                 output_buffer_bytes: 10,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::PerEvaluation,
@@ -3206,7 +3207,7 @@ mod tests {
                 id: "filter".into(),
                 operator: filter_operator(),
                 children: vec!["scan".into()],
-                source_coverage: None,
+                scan_selection: None,
                 output_buffer_bytes: 0,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::PerEvaluation,
@@ -3245,7 +3246,7 @@ mod tests {
             id: "scan".into(),
             operator: PhysicalOperator::Scan,
             children: vec![],
-            source_coverage: Some(SourceCoverage {
+            scan_selection: Some(ScanSelection {
                 source: asap_types::pre_asap::query_expr::Source::Table {
                     table_ref: "other_metrics".into(),
                 },
@@ -3283,7 +3284,7 @@ mod tests {
             id: "scan".into(),
             operator: PhysicalOperator::Scan,
             children: vec![],
-            source_coverage: None,
+            scan_selection: None,
             output_buffer_bytes: 10,
             retained_bytes: 0,
             execution: ExecutionMultiplicity::PerEvaluation,
@@ -3302,9 +3303,7 @@ mod tests {
 
         assert_eq!(
             estimate_physical_dag(&nodes, "scan", &comparison_scope(), &provided),
-            Err(AnalyticalCostError::MissingScanSourceCoverage(
-                "scan".into()
-            ))
+            Err(AnalyticalCostError::MissingScanSelection("scan".into()))
         );
     }
 
@@ -3312,7 +3311,7 @@ mod tests {
     fn physical_dag_rejects_an_unconsumed_scope_source() {
         let mut scope = comparison_scope();
         let coverage = scope.sources[0].clone();
-        scope.sources.push(SourceCoverage {
+        scope.sources.push(ScanSelection {
             source: asap_types::pre_asap::query_expr::Source::Table {
                 table_ref: "auxiliary".into(),
             },
@@ -3324,7 +3323,7 @@ mod tests {
             id: "scan".into(),
             operator: PhysicalOperator::Scan,
             children: vec![],
-            source_coverage: Some(coverage),
+            scan_selection: Some(coverage),
             output_buffer_bytes: 10,
             retained_bytes: 0,
             execution: ExecutionMultiplicity::PerEvaluation,
@@ -3357,7 +3356,7 @@ mod tests {
                 id: "scan".into(),
                 operator: PhysicalOperator::Scan,
                 children: vec![],
-                source_coverage: Some(coverage),
+                scan_selection: Some(coverage),
                 output_buffer_bytes: 10,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::PerEvaluation,
@@ -3366,7 +3365,7 @@ mod tests {
                 id: "aggregate".into(),
                 operator: aggregate_operator(),
                 children: vec!["scan".into()],
-                source_coverage: None,
+                scan_selection: None,
                 output_buffer_bytes: 16,
                 retained_bytes: 32,
                 execution: ExecutionMultiplicity::Once,
@@ -3411,7 +3410,7 @@ mod tests {
             id: "scan".into(),
             operator: PhysicalOperator::Scan,
             children: vec![],
-            source_coverage: Some(coverage),
+            scan_selection: Some(coverage),
             output_buffer_bytes: 10,
             retained_bytes: 0,
             execution: ExecutionMultiplicity::PerEvaluation,
@@ -3642,7 +3641,7 @@ mod tests {
                 id: "scan".into(),
                 operator: PhysicalOperator::Scan,
                 children: vec![],
-                source_coverage: Some(comparison_scope().sources[0].clone()),
+                scan_selection: Some(comparison_scope().sources[0].clone()),
                 output_buffer_bytes: 0,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::PerEvaluation,
diff --git a/crates/asap-aware-mapping/src/physical_operator_statistics.rs b/crates/asap-aware-mapping/src/physical_operator_statistics.rs
index 9cf8045bb..7be1d292c 100644
--- a/crates/asap-aware-mapping/src/physical_operator_statistics.rs
+++ b/crates/asap-aware-mapping/src/physical_operator_statistics.rs
@@ -26,12 +26,12 @@ pub struct ComparisonScope {
     pub horizon: DurationMs,
     pub recurrence: QueryRecurrence,
     pub time_selection: TimeSelection,
-    pub sources: Vec<SourceCoverage>,
+    pub sources: Vec<ScanSelection>,
 }
 
 /// Exact source selection covered by a physical plan.
 #[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
-pub struct SourceCoverage {
+pub struct ScanSelection {
     pub source: Source,
     /// Provider-owned stable identifier for the physical source contents,
     /// such as a catalog snapshot, table version, or object generation.
@@ -53,7 +53,7 @@ impl ComparisonScope {
         query: &QueryWorkloadEntry,
         planning_time: TimestampMs,
         horizon: DurationMs,
-        sources: Vec<SourceCoverage>,
+        sources: Vec<ScanSelection>,
     ) -> Result<Self, AnalyticalCostError> {
         let scope = Self {
             data_arrival: data.arrival,
@@ -87,7 +87,7 @@ impl ComparisonScope {
             .any(|(index, source)| self.sources[..index].contains(source))
         {
             return Err(AnalyticalCostError::MissingComparisonScope(
-                "duplicate source coverage",
+                "duplicate scan selection",
             ));
         }
         if self
diff --git a/crates/asap-aware-mapping/src/physical_plan_cost_model.rs b/crates/asap-aware-mapping/src/physical_plan_cost_model.rs
index 307fb9a61..509e6a13a 100644
--- a/crates/asap-aware-mapping/src/physical_plan_cost_model.rs
+++ b/crates/asap-aware-mapping/src/physical_plan_cost_model.rs
@@ -367,7 +367,7 @@ mod tests {
 
     use crate::analytical_cost::{ExecutionMultiplicity, PhysicalDAGNode, PhysicalOperator};
     use crate::physical_operator_statistics::{
-        EdgeStatistics, OperatorStatistics, SourceCoverage, UnaryEdgeStatistics,
+        EdgeStatistics, OperatorStatistics, ScanSelection, UnaryEdgeStatistics,
     };
     use crate::replacement::ReplacementStrategy;
 
@@ -438,7 +438,7 @@ mod tests {
                 lookback: Some(DurationMs(10_000)),
                 as_of: Some(TimestampMs(1_000)),
             },
-            sources: vec![SourceCoverage {
+            sources: vec![ScanSelection {
                 source: Source::Table {
                     table_ref: "events".into(),
                 },
@@ -506,7 +506,7 @@ mod tests {
                         id: "candidate-scan".into(),
                         operator: PhysicalOperator::Scan,
                         children: vec![],
-                        source_coverage: Some(scope.sources[0].clone()),
+                        scan_selection: Some(scope.sources[0].clone()),
                         output_buffer_bytes: 8,
                         retained_bytes: 0,
                         execution: ExecutionMultiplicity::Once,
@@ -518,7 +518,7 @@ mod tests {
                             accumulator_count: 1,
                         },
                         children: vec!["candidate-scan".into()],
-                        source_coverage: None,
+                        scan_selection: None,
                         output_buffer_bytes: 8,
                         retained_bytes: 8,
                         execution: ExecutionMultiplicity::Once,
@@ -527,7 +527,7 @@ mod tests {
                         id: "candidate-read".into(),
                         operator: PhysicalOperator::PassThrough,
                         children: vec!["candidate-state".into()],
-                        source_coverage: None,
+                        scan_selection: None,
                         output_buffer_bytes: 8,
                         retained_bytes: 0,
                         execution: ExecutionMultiplicity::PerEvaluation,
@@ -1006,7 +1006,7 @@ mod tests {
             ) -> Result<PhysicalDAG, AnalyticalCostError> {
                 let mut dag = self.0.summary_physical_dag(snapshot, summary, target)?;
                 dag.nodes[0]
-                    .source_coverage
+                    .scan_selection
                     .as_mut()
                     .unwrap()
                     .source_snapshot_id = "other".into();
diff --git a/crates/asap-aware-mapping/src/query_physical_lowering.rs b/crates/asap-aware-mapping/src/query_physical_lowering.rs
index 1b8e5a751..65b7fab93 100644
--- a/crates/asap-aware-mapping/src/query_physical_lowering.rs
+++ b/crates/asap-aware-mapping/src/query_physical_lowering.rs
@@ -9,7 +9,7 @@ use crate::analytical_cost::{
     PromqlSeriesSampleKind, PromqlVectorCardinality,
 };
 use crate::physical_operator_statistics::{
-    ComparisonScope, EdgeStatistics, OperatorStatistics, SourceCoverage,
+    ComparisonScope, EdgeStatistics, OperatorStatistics, ScanSelection,
 };
 
 pub struct PhysicalNodeRequest<'a> {
@@ -18,7 +18,7 @@ pub struct PhysicalNodeRequest<'a> {
     pub occurrence: usize,
     pub synthetic: bool,
     pub children: &'a [String],
-    pub source_coverage: Option<&'a SourceCoverage>,
+    pub scan_selection: Option<&'a ScanSelection>,
 }
 
 pub trait PhysicalNodeEvidenceProvider {
@@ -78,7 +78,7 @@ pub fn lower_query_physical_dag(
             occurrence: usize,
             synthetic: bool,
             children: &[String],
-            source_coverage: Option<&SourceCoverage>,
+            scan_selection: Option<&ScanSelection>,
         ) -> Result<PhysicalNodeEvidence, AnalyticalCostError> {
             let evidence = self.provider.evidence(PhysicalNodeRequest {
                 logical_node: query,
@@ -86,7 +86,7 @@ pub fn lower_query_physical_dag(
                 occurrence,
                 synthetic,
                 children,
-                source_coverage,
+                scan_selection,
             })?;
             if evidence.physical_id.is_empty() {
                 return Err(AnalyticalCostError::InvalidPhysicalDAG(
@@ -101,14 +101,14 @@ pub fn lower_query_physical_dag(
             evidence: PhysicalNodeEvidence,
             operator: PhysicalOperator,
             children: Vec<String>,
-            source_coverage: Option<SourceCoverage>,
+            scan_selection: Option<ScanSelection>,
         ) -> Result<String, AnalyticalCostError> {
             let id = evidence.physical_id.clone();
             let node = PhysicalDAGNode {
                 id: id.clone(),
                 operator,
                 children,
-                source_coverage,
+                scan_selection,
                 output_buffer_bytes: evidence.output_buffer_bytes,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::PerEvaluation,
@@ -837,7 +837,7 @@ fn validate_source_consumption(
     let consumed = nodes
         .iter()
         .filter(|node| matches!(node.operator, PhysicalOperator::Scan))
-        .filter_map(|node| node.source_coverage.as_ref())
+        .filter_map(|node| node.scan_selection.as_ref())
         .collect::<Vec<_>>();
     for coverage in &consumed {
         if !scope.sources.contains(coverage) {
@@ -959,7 +959,7 @@ fn bind_scan_coverage(
     source: &asap_types::pre_asap::Source,
     predicates: &[asap_types::pre_asap::Predicate],
     scope: &ComparisonScope,
-) -> Result<SourceCoverage, AnalyticalCostError> {
+) -> Result<ScanSelection, AnalyticalCostError> {
     let mut matches = scope.sources.iter().filter(|coverage| {
         coverage.source == *source
             && coverage.predicates == predicates
@@ -971,7 +971,7 @@ fn bind_scan_coverage(
         .ok_or_else(|| AnalyticalCostError::ScanOutsideComparisonScope(node_id.into()))?;
     if matches.any(|candidate| candidate != &coverage) {
         return Err(AnalyticalCostError::InvalidPhysicalDAG(
-            "scan source coverage is ambiguous",
+            "scan selection is ambiguous",
         ));
     }
     Ok(coverage)
@@ -981,7 +981,7 @@ fn bind_info_coverage(
     node_id: &str,
     selector: &[asap_types::pre_asap::InfoMatcher],
     scope: &ComparisonScope,
-) -> Result<SourceCoverage, AnalyticalCostError> {
+) -> Result<ScanSelection, AnalyticalCostError> {
     use asap_types::pre_asap::{CompareOpKind, Source};
 
     let mut metric: Option<&str> = None;
@@ -1009,7 +1009,7 @@ fn bind_info_coverage(
         .ok_or_else(|| AnalyticalCostError::ScanOutsideComparisonScope(node_id.into()))?;
     if matches.next().is_some() {
         return Err(AnalyticalCostError::InvalidPhysicalDAG(
-            "info source coverage is ambiguous",
+            "info scan selection is ambiguous",
         ));
     }
     Ok(coverage)
@@ -1383,7 +1383,7 @@ mod tests {
         }
     }
 
-    fn scope(sources: Vec<SourceCoverage>) -> ComparisonScope {
+    fn scope(sources: Vec<ScanSelection>) -> ComparisonScope {
         ComparisonScope {
             data_arrival: DataArrival::AtRest,
             planning_time: TimestampMs(1_000),
@@ -1404,8 +1404,8 @@ mod tests {
     fn coverage(
         source: asap_types::pre_asap::Source,
         predicates: Vec<asap_types::pre_asap::Predicate>,
-    ) -> SourceCoverage {
-        SourceCoverage {
+    ) -> ScanSelection {
+        ScanSelection {
             source,
             source_snapshot_id: "snapshot-1".into(),
             predicates,
@@ -1414,7 +1414,7 @@ mod tests {
     }
 
     #[test]
-    fn info_source_coverage_includes_symbolic_selector_matchers() {
+    fn info_scan_selection_includes_symbolic_selector_matchers() {
         use asap_types::pre_asap::{CompareOpKind, InfoMatcher, Source};
 
         let selector = vec![InfoMatcher {
@@ -1422,7 +1422,7 @@ mod tests {
             op: CompareOpKind::Eq,
             value: "prod".into(),
         }];
-        let info_coverage = SourceCoverage {
+        let info_coverage = ScanSelection {
             source: Source::TimeSeries {
                 metric: "target_info".into(),
             },
@@ -1611,10 +1611,7 @@ mod tests {
         ));
         let physical_scan = &dag.nodes[0];
         assert_eq!(physical_scan.id, "query-2-scan");
-        assert_eq!(
-            physical_scan.source_coverage,
-            Some(scope.sources[0].clone())
-        );
+        assert_eq!(physical_scan.scan_selection, Some(scope.sources[0].clone()));
         assert_eq!(physical_scan.output_buffer_bytes, 1_024);
         assert_ne!(
             physical_scan.output_buffer_bytes,
@@ -1661,13 +1658,13 @@ mod tests {
             left: Rc::clone(&shared),
             right: Rc::clone(&shared),
         });
-        let source_coverage = coverage(
+        let scan_selection = coverage(
             Source::Table {
                 table_ref: "dimensions".into(),
             },
             vec![],
         );
-        let independent_scope = scope(vec![source_coverage.clone()]);
+        let independent_scope = scope(vec![scan_selection.clone()]);
         let scan_statistics = scan_stats(edge(100, 800), 800);
         let join_statistics = OperatorStatistics::HashJoin {
             edges: BinaryEdgeStatistics {
@@ -1703,7 +1700,7 @@ mod tests {
                 statistics,
             })
         };
-        let shared_scope = scope(vec![source_coverage]);
+        let shared_scope = scope(vec![scan_selection]);
         let no_cache = crate::analytical_cost::CacheProfile::no_cache();
         let shared_dag = lower_query_physical_dag(&root, &shared_scope, &shared_provider).unwrap();
         assert_eq!(shared_dag.nodes.len(), 2);
@@ -1860,13 +1857,13 @@ mod tests {
             child: limit,
         });
 
-        let source_coverage = coverage(
+        let scan_selection = coverage(
             Source::Table {
                 table_ref: "events".into(),
             },
             vec![],
         );
-        let scope = scope(vec![source_coverage]);
+        let scope = scope(vec![scan_selection]);
         let scan_statistics = scan_stats(edge(1_000, 8_000), 8_000);
         let dedup_statistics = OperatorStatistics::HashDeduplicate {
             edges: unary_edges(edge(800, 3_200), edge(500, 2_000)),
@@ -2032,7 +2029,7 @@ mod tests {
         assert_eq!(
             duplicate_scope.validate(),
             Err(AnalyticalCostError::MissingComparisonScope(
-                "duplicate source coverage"
+                "duplicate scan selection"
             ))
         );
 
@@ -2142,7 +2139,7 @@ mod tests {
         assert_eq!(
             lower_query_physical_dag(&root, &ambiguous_scope, &scripted(&conflicting)),
             Err(AnalyticalCostError::InvalidPhysicalDAG(
-                "scan source coverage is ambiguous"
+                "scan selection is ambiguous"
             ))
         );
 
diff --git a/crates/asap-aware-mapping/src/storage_io.rs b/crates/asap-aware-mapping/src/storage_io.rs
index 646a3532c..125ec915b 100644
--- a/crates/asap-aware-mapping/src/storage_io.rs
+++ b/crates/asap-aware-mapping/src/storage_io.rs
@@ -121,7 +121,7 @@ pub fn estimate_storage_io(
     profile: &StorageIoProfile,
     evidence_version: &str,
 ) -> Result<StorageEstimate, AnalyticalCostError> {
-    // Also prove source coverage, edge consistency, execution legality and DAG
+    // Also prove scan selection, edge consistency, execution legality and DAG
     // identity before using supplementary deployment evidence.
     estimate_physical_dag(&dag.nodes, &dag.root, scope, dag)?;
     let evaluations = scope.validate()?;
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_cost/estimator.rs b/crates/asap-aware-mapping/src/summary_maintenance_cost/estimator.rs
index 5bf42d2e4..eac94a2cb 100644
--- a/crates/asap-aware-mapping/src/summary_maintenance_cost/estimator.rs
+++ b/crates/asap-aware-mapping/src/summary_maintenance_cost/estimator.rs
@@ -86,14 +86,14 @@ pub(super) fn estimate_heterogeneous_summary(
         };
         let inputs = node_evidence.inputs.validate()?;
         validate_arrival_rate(scope.data_arrival, inputs.ingestion_rate_per_second)?;
-        match node_evidence.source_coverage_index {
+        match node_evidence.scan_selection_index {
             Some(index) => {
                 let declared =
                     scope
                         .sources
                         .get(index)
                         .ok_or(AnalyticalCostError::MissingComparisonScope(
-                            "summary source coverage",
+                            "summary scan selection",
                         ))?;
                 if !matches!(&child.expr, SummaryExpr::KeepPreAsap(_))
                     || inputs.initial_input_rows != raw.planning_time_input_rows
@@ -178,7 +178,7 @@ pub(super) fn estimate_heterogeneous_summary(
             let bootstrap_extra_rows = bootstrap
                 .checked_sub(inputs.initial_input_rows)
                 .ok_or(AnalyticalCostError::Overflow)?;
-            let source_scan_bytes = if node_evidence.source_coverage_index.is_some() {
+            let source_scan_bytes = if node_evidence.scan_selection_index.is_some() {
                 inputs
                     .initial_source_scan_bytes
                     .checked_add(
@@ -223,7 +223,7 @@ pub(super) fn estimate_heterogeneous_summary(
                 .checked_add(state_bytes)
                 .ok_or(AnalyticalCostError::Overflow)?;
         }
-        if let Some(source_index) = node_evidence.source_coverage_index {
+        if let Some(source_index) = node_evidence.scan_selection_index {
             if node_evidence.bootstrap_read_identity.is_empty() {
                 return Err(AnalyticalCostError::MissingOrStale(
                     "bootstrap_read_identity",
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_cost/evidence.rs b/crates/asap-aware-mapping/src/summary_maintenance_cost/evidence.rs
index f396e3cd8..7c8607685 100644
--- a/crates/asap-aware-mapping/src/summary_maintenance_cost/evidence.rs
+++ b/crates/asap-aware-mapping/src/summary_maintenance_cost/evidence.rs
@@ -161,7 +161,7 @@ pub struct SummaryAggregateEvidence {
     /// Index into `ComparisonScope.sources` when this state bootstraps directly
     /// from storage. `None` means its input is an already-materialized child
     /// edge and therefore has no additional source read.
-    pub source_coverage_index: Option<usize>,
+    pub scan_selection_index: Option<usize>,
     /// Provider-owned identity of the physical bootstrap read. Equal source
     /// coverage alone does not prove two independent builds share I/O.
     pub bootstrap_read_identity: String,
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_cost/model.rs b/crates/asap-aware-mapping/src/summary_maintenance_cost/model.rs
index 331b7e1a5..7859db9b8 100644
--- a/crates/asap-aware-mapping/src/summary_maintenance_cost/model.rs
+++ b/crates/asap-aware-mapping/src/summary_maintenance_cost/model.rs
@@ -165,19 +165,19 @@ fn validate_physical_scope_coverage(
         .filter(|node| node.operator == PhysicalOperator::Scan)
     {
         let coverage = node
-            .source_coverage
+            .scan_selection
             .as_ref()
-            .ok_or_else(|| AnalyticalCostError::MissingScanSourceCoverage(node.id.clone()))?;
+            .ok_or_else(|| AnalyticalCostError::MissingScanSelection(node.id.clone()))?;
         let Some(index) = scope.sources.iter().position(|value| value == coverage) else {
             return Err(AnalyticalCostError::ComparisonScopeMismatch(
-                "physical source coverage",
+                "physical scan selection",
             ));
         };
         covered.insert(index);
     }
     if covered.len() != scope.sources.len() {
         return Err(AnalyticalCostError::ComparisonScopeMismatch(
-            "physical source coverage",
+            "physical scan selection",
         ));
     }
     Ok(())
@@ -939,7 +939,7 @@ mod tests {
             query,
             asap_types::workload::TimestampMs(planning_time_ms),
             asap_types::workload::DurationMs(horizon_ms),
-            vec![crate::physical_operator_statistics::SourceCoverage {
+            vec![crate::physical_operator_statistics::ScanSelection {
                 source: Source::TimeSeries {
                     metric: "metrics".into(),
                 },
@@ -1611,7 +1611,7 @@ mod tests {
                 id: "raw-concat".into(),
                 operator: PhysicalOperator::Concat,
                 children: vec!["raw-scan".into(), "raw-scan-2".into()],
-                source_coverage: None,
+                scan_selection: None,
                 output_buffer_bytes: 0,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::Once,
@@ -1693,7 +1693,7 @@ mod tests {
         let mut extra = streaming_scope();
         extra
             .sources
-            .push(crate::physical_operator_statistics::SourceCoverage {
+            .push(crate::physical_operator_statistics::ScanSelection {
                 source: Source::TimeSeries {
                     metric: "unused".into(),
                 },
@@ -1720,7 +1720,7 @@ mod tests {
         let mut info_scope = streaming_scope();
         info_scope
             .sources
-            .push(crate::physical_operator_statistics::SourceCoverage {
+            .push(crate::physical_operator_statistics::ScanSelection {
                 source: Source::TimeSeries {
                     metric: "target_info".into(),
                 },
@@ -2057,7 +2057,7 @@ mod tests {
                 physical_id: "left-state".into(),
                 input: test_edge(),
                 output: test_edge(),
-                source_coverage_index: Some(0),
+                scan_selection_index: Some(0),
                 bootstrap_read_identity: "left-bootstrap".into(),
                 inputs: streaming_inputs(),
                 insert_cpu_ops: streaming_cpu().insert_cpu_ops.unwrap(),
@@ -2084,7 +2084,7 @@ mod tests {
                 physical_id: "right-state".into(),
                 input: test_edge(),
                 output: test_edge(),
-                source_coverage_index: Some(0),
+                scan_selection_index: Some(0),
                 bootstrap_read_identity: "right-bootstrap".into(),
                 inputs: second_inputs,
                 insert_cpu_ops: second_cpu.insert_cpu_ops.unwrap(),
@@ -2150,7 +2150,7 @@ mod tests {
             64.0
         );
 
-        // Equal SourceCoverage does not imply that two independent state
+        // Equal ScanSelection does not imply that two independent state
         // builds share one physical read. Only a provider-owned read identity
         // permits scan de-duplication.
         let mut shared_read = model;
@@ -3264,7 +3264,7 @@ mod tests {
             id: "raw-scan".into(),
             operator: PhysicalOperator::Scan,
             children: vec![],
-            source_coverage: Some(scope.sources[0].clone()),
+            scan_selection: Some(scope.sources[0].clone()),
             output_buffer_bytes: 0,
             retained_bytes: 0,
             execution: ExecutionMultiplicity::Once,
@@ -3415,7 +3415,7 @@ mod tests {
                     physical_id: format!("agg-{node:p}"),
                     input: test_edge(),
                     output: test_edge(),
-                    source_coverage_index: source_root.then_some(0),
+                    scan_selection_index: source_root.then_some(0),
                     bootstrap_read_identity: if source_root {
                         "shared-bootstrap".into()
                     } else {
@@ -3637,7 +3637,7 @@ mod tests {
             &entry,
             asap_types::workload::TimestampMs(0),
             asap_types::workload::DurationMs(5_000),
-            vec![crate::physical_operator_statistics::SourceCoverage {
+            vec![crate::physical_operator_statistics::ScanSelection {
                 source: Source::TimeSeries {
                     metric: "metrics".into(),
                 },
diff --git a/crates/asap-aware-mapping/tests/physical_handoff_cost.rs b/crates/asap-aware-mapping/tests/physical_handoff_cost.rs
index 0885db71c..a8a9ed42d 100644
--- a/crates/asap-aware-mapping/tests/physical_handoff_cost.rs
+++ b/crates/asap-aware-mapping/tests/physical_handoff_cost.rs
@@ -3,7 +3,7 @@ use asap_aware_mapping::analytical_cost::{
     PhysicalOperator,
 };
 use asap_aware_mapping::physical_operator_statistics::{
-    ComparisonScope, EdgeStatistics, OperatorStatistics, SourceCoverage, UnaryEdgeStatistics,
+    ComparisonScope, EdgeStatistics, OperatorStatistics, ScanSelection, UnaryEdgeStatistics,
 };
 use asap_types::pre_asap::query_expr::Source;
 use asap_types::workload::{
@@ -12,7 +12,7 @@ use asap_types::workload::{
 use std::collections::HashMap;
 
 fn fixture() -> (EvidenceBackedPhysicalDAG, ComparisonScope) {
-    let coverage = SourceCoverage {
+    let coverage = ScanSelection {
         source: Source::Table {
             table_ref: "events".into(),
         },
@@ -49,7 +49,7 @@ fn fixture() -> (EvidenceBackedPhysicalDAG, ComparisonScope) {
             id: "scan".into(),
             operator: PhysicalOperator::Scan,
             children: vec![],
-            source_coverage: Some(coverage),
+            scan_selection: Some(coverage),
             output_buffer_bytes: 0,
             retained_bytes: 0,
             execution: ExecutionMultiplicity::PerEvaluation,
@@ -58,7 +58,7 @@ fn fixture() -> (EvidenceBackedPhysicalDAG, ComparisonScope) {
             id: "left".into(),
             operator: PhysicalOperator::PassThrough,
             children: vec!["scan".into()],
-            source_coverage: None,
+            scan_selection: None,
             output_buffer_bytes: 0,
             retained_bytes: 0,
             execution: ExecutionMultiplicity::PerEvaluation,
@@ -67,7 +67,7 @@ fn fixture() -> (EvidenceBackedPhysicalDAG, ComparisonScope) {
             id: "right".into(),
             operator: PhysicalOperator::PassThrough,
             children: vec!["scan".into()],
-            source_coverage: None,
+            scan_selection: None,
             output_buffer_bytes: 0,
             retained_bytes: 0,
             execution: ExecutionMultiplicity::PerEvaluation,
@@ -76,7 +76,7 @@ fn fixture() -> (EvidenceBackedPhysicalDAG, ComparisonScope) {
             id: "root".into(),
             operator: PhysicalOperator::Concat,
             children: vec!["left".into(), "right".into()],
-            source_coverage: None,
+            scan_selection: None,
             output_buffer_bytes: 0,
             retained_bytes: 0,
             execution: ExecutionMultiplicity::PerEvaluation,
diff --git a/crates/asap-aware-mapping/tests/storage_io.rs b/crates/asap-aware-mapping/tests/storage_io.rs
index a12118f09..e9290d20a 100644
--- a/crates/asap-aware-mapping/tests/storage_io.rs
+++ b/crates/asap-aware-mapping/tests/storage_io.rs
@@ -3,7 +3,7 @@ use asap_aware_mapping::analytical_cost::{
     PhysicalOperator,
 };
 use asap_aware_mapping::physical_operator_statistics::{
-    ComparisonScope, EdgeStatistics, OperatorStatistics, SourceCoverage, UnaryEdgeStatistics,
+    ComparisonScope, EdgeStatistics, OperatorStatistics, ScanSelection, UnaryEdgeStatistics,
 };
 use asap_types::pre_asap::query_expr::Source;
 use asap_types::workload::{
@@ -12,7 +12,7 @@ use asap_types::workload::{
 use std::collections::HashMap;
 
 fn fixture() -> (EvidenceBackedPhysicalDAG, ComparisonScope) {
-    let coverage = SourceCoverage {
+    let coverage = ScanSelection {
         source: Source::Table {
             table_ref: "events".into(),
         },
@@ -49,7 +49,7 @@ fn fixture() -> (EvidenceBackedPhysicalDAG, ComparisonScope) {
             id: "scan".into(),
             operator: PhysicalOperator::Scan,
             children: vec![],
-            source_coverage: Some(coverage),
+            scan_selection: Some(coverage),
             output_buffer_bytes: 0,
             retained_bytes: 0,
             execution: ExecutionMultiplicity::PerEvaluation,
@@ -58,7 +58,7 @@ fn fixture() -> (EvidenceBackedPhysicalDAG, ComparisonScope) {
             id: "left".into(),
             operator: PhysicalOperator::PassThrough,
             children: vec!["scan".into()],
-            source_coverage: None,
+            scan_selection: None,
             output_buffer_bytes: 0,
             retained_bytes: 0,
             execution: ExecutionMultiplicity::PerEvaluation,
@@ -67,7 +67,7 @@ fn fixture() -> (EvidenceBackedPhysicalDAG, ComparisonScope) {
             id: "right".into(),
             operator: PhysicalOperator::PassThrough,
             children: vec!["scan".into()],
-            source_coverage: None,
+            scan_selection: None,
             output_buffer_bytes: 0,
             retained_bytes: 0,
             execution: ExecutionMultiplicity::PerEvaluation,
@@ -76,7 +76,7 @@ fn fixture() -> (EvidenceBackedPhysicalDAG, ComparisonScope) {
             id: "root".into(),
             operator: PhysicalOperator::Concat,
             children: vec!["left".into(), "right".into()],
-            source_coverage: None,
+            scan_selection: None,
             output_buffer_bytes: 0,
             retained_bytes: 0,
             execution: ExecutionMultiplicity::PerEvaluation,
@@ -353,7 +353,7 @@ fn storage_node_identity_statistics_and_calibration_provenance_are_bound() {
         .get_mut("scan")
         .unwrap()
         .node
-        .source_coverage
+        .scan_selection
         .as_mut()
         .unwrap()
         .source_snapshot_id = "another-source".into();
diff --git a/crates/devtools/src/bin/dag_export.rs b/crates/devtools/src/bin/dag_export.rs
index b0615f017..2728dab12 100644
--- a/crates/devtools/src/bin/dag_export.rs
+++ b/crates/devtools/src/bin/dag_export.rs
@@ -152,7 +152,7 @@ struct ComparisonScopeEvidence {
     time_scope: String,
     lookback_ms: Option<u64>,
     as_of_ms: Option<u64>,
-    sources: Vec<asap_aware_mapping::physical_operator_statistics::SourceCoverage>,
+    sources: Vec<asap_aware_mapping::physical_operator_statistics::ScanSelection>,
     #[serde(default = "CacheProfile::no_cache")]
     cache_profile: CacheProfile,
 }
@@ -1700,7 +1700,7 @@ mod tests {
         ExecutionMultiplicity, PhysicalDAGNode, PhysicalOperator,
     };
     use asap_aware_mapping::physical_operator_statistics::{
-        EdgeStatistics, OperatorStatistics, SourceCoverage, UnaryEdgeStatistics,
+        EdgeStatistics, OperatorStatistics, ScanSelection, UnaryEdgeStatistics,
     };
     use asap_aware_mapping::query_physical_lowering::lower_query_physical_dag;
     use asap_devtools::PromqlError;
@@ -2178,7 +2178,7 @@ mod tests {
             time_scope: "longitudinal".into(),
             lookback_ms: Some(10_000),
             as_of_ms: Some(1_000),
-            sources: vec![SourceCoverage {
+            sources: vec![ScanSelection {
                 source: Source::Table {
                     table_ref: "events".into(),
                 },
@@ -2261,7 +2261,7 @@ mod tests {
                 id: "summary-read".into(),
                 operator: PhysicalOperator::Scan,
                 children: vec![],
-                source_coverage: Some(coverage),
+                scan_selection: Some(coverage),
                 output_buffer_bytes: 2_400,
                 retained_bytes: 0,
                 execution: ExecutionMultiplicity::PerEvaluation,
diff --git a/docs/design_docs/architecture/physical-plan-integration.md b/docs/design_docs/architecture/physical-plan-integration.md
index 7fffc9fdf..057ba7c17 100644
--- a/docs/design_docs/architecture/physical-plan-integration.md
+++ b/docs/design_docs/architecture/physical-plan-integration.md
@@ -75,7 +75,7 @@ lose post-ASAP summary implementations, while aligning it directly with
 Physical lowering is complete only when it recursively lowers the entire
 selected candidate DAG. It must:
 
-1. preserve the semantics and source coverage of the logical candidate;
+1. preserve the semantics and scan selection of the logical candidate;
 2. select an explicit physical algorithm for every logical operation;
 3. carry algorithm configuration on the physical operator rather than in a
    generic statistics record;
diff --git a/docs/design_docs/architecture/planner-runtime-contract.md b/docs/design_docs/architecture/planner-runtime-contract.md
index 2d071e654..58e3f06b6 100644
--- a/docs/design_docs/architecture/planner-runtime-contract.md
+++ b/docs/design_docs/architecture/planner-runtime-contract.md
@@ -73,7 +73,7 @@ and rollback are not an end-to-end Planner protocol.
 2. A physical-plan provider maps those candidates to executor-feasible complete
    alternatives. Unsupported candidates are omitted or explicitly rejected.
 3. The provider binds a stable alternative identity and complete evidence:
-   source coverage, input/output edges, operation counts, update and bootstrap
+   scan selection, input/output edges, operation counts, update and bootstrap
    fanout, retained state, CPU, memory, I/O, and accuracy facts.
 4. ASAPPlanner keeps constructible candidates with missing evidence visible
    in `CandidateLogicalASAPDAGs` but does not certify unknown accuracy. The
diff --git a/docs/design_docs/proposals/asap-aware-mapping/analytical-resource-cost.md b/docs/design_docs/proposals/asap-aware-mapping/analytical-resource-cost.md
index 520501731..b742a8970 100644
--- a/docs/design_docs/proposals/asap-aware-mapping/analytical-resource-cost.md
+++ b/docs/design_docs/proposals/asap-aware-mapping/analytical-resource-cost.md
@@ -365,11 +365,11 @@ coverage set must equal the scope source set: a Scan query with an empty scope,
 or a source-free query with a non-empty scope, fails closed. Empty snapshot
 identifiers, invalid recurrence, or a zero horizon also fail closed.
 
-Every reachable physical `Scan` carries one exact `SourceCoverage` copied from
+Every reachable physical `Scan` carries one exact `ScanSelection` copied from
 this scope. That coverage includes the existing `Source`, its provider-owned
 snapshot ID, and canonical ordinary predicates or info-metric matchers. A scan with no coverage, or coverage
 not present in `ComparisonScope.sources`, makes the plan unavailable. Other
-operators cannot declare source coverage. This prevents a DAG over source B
+operators cannot declare scan selection. This prevents a DAG over source B
 from being estimated under source A's comparison scope.
 
 ## General DAG costing
@@ -554,7 +554,7 @@ counts, releases transient output after its last consumer, and keeps retained
 state live. Consequently a shared scan is charged once per execution and a
 fan-out's memory includes the outputs that really coexist.
 
-Each estimate independently requires the semantic set of source coverages on
+Each estimate independently requires the semantic set of scan selections on
 its reachable Scan nodes to equal `ComparisonScope.sources`. Multiple physical
 Scans may repeat one coverage, but no scope source may be omitted and no Scan
 may add another coverage. This invariant is enforced by the estimator itself,
@@ -596,7 +596,7 @@ It consumes the existing query and physical-operator enums; it does not
 introduce a parallel logical operator vocabulary. For every occurrence, the lowerer sends a
 `PhysicalNodeRequest` containing the logical node, selected existing
 `PhysicalOperator`, occurrence and synthetic-role metadata, already-lowered
-child physical IDs, and any source coverage to a
+child physical IDs, and any scan selection to a
 `PhysicalNodeEvidenceProvider`. The provider atomically returns its own stable
 `physical_id`, the authoritative `OperatorStatistics`, and explicit
 `output_buffer_bytes`; logical edge bytes are never substituted for an
@@ -604,14 +604,14 @@ allocation. Missing evidence makes the entire query unavailable. The returned
 `EvidenceBackedPhysicalDAG` snapshots this evidence so costing does not re-read a live
 catalog after lowering.
 
-Each lowered Scan is bound to exactly one `SourceCoverage` in the comparison
+Each lowered Scan is bound to exactly one `ScanSelection` in the comparison
 scope by the existing source and canonical predicate values. The bound value
 therefore also supplies the provider-owned snapshot ID. Zero matches fail as
 outside scope; multiple matching coverages fail as ambiguous rather than
 choosing an arbitrary snapshot. When a predicate-bearing logical Scan expands
 to Scan → Filter, the synthetic Scan has its own physical ID, statistics, and
 buffer evidence and carries that exact coverage; the Filter has separate
-evidence and no source coverage.
+evidence and no scan selection.
 `ComparisonScope.sources` is an order-independent set of semantic coverages;
 duplicates are invalid. After lowering, every reachable physical Scan must use
 a member of that set and every member must be used by at least one Scan.
@@ -837,7 +837,7 @@ its complete evidence and physical child identities also agree. The cost model
 holds owning `Rc` references for bound target and summary roots, so pointer
 keys cannot become stale and alias a later allocation.
 
-A `SummaryAgg` that reads storage declares `source_coverage_index = Some(i)`,
+A `SummaryAgg` that reads storage declares `scan_selection_index = Some(i)`,
 a non-empty bootstrap-read identity, and positive physical source bytes. An
 aggregate over an already-materialized summary edge declares `None`, an empty
 read identity, and zero source bytes. Its logical input rows and bytes remain
@@ -854,7 +854,7 @@ those evolving evaluations over the complete horizon. Marking its nodes
 rejected. Validation follows only nodes reachable from the physical root. If
 the raw algorithm intentionally reads the same semantic source more than once,
 each reachable scan carries the same evolved source statistics and is charged
-separately; equal source coverage does not deduplicate physical I/O.
+separately; equal scan selection does not deduplicate physical I/O.
 
 This raw-evolution contract currently supports exactly one distinct source
 coverage. A multi-source streaming target is unavailable until per-source
@@ -962,14 +962,14 @@ bound physical DAG for a `SummaryExpr` candidate. The deployment implements
 `PlannerPhysicalPlanProvider`: query-node evidence is consumed atomically by
 the generic query lowerer, while summary binding returns a complete
 `EvidenceBackedPhysicalDAG`, including embedded raw work, build/read operators, retained
-state, execution multiplicity, and source coverage. The adapter calls
+state, execution multiplicity, and scan selection. The adapter calls
 `estimate_physical_dag_comparison`; it never calls `DefaultCostModel` or a
 structural-node-count fallback for final cost.
 
 A candidate is exposed to global selection only when both complete DAGs are
 valid and its calibrated cost is strictly below the raw baseline. Missing or
 stale evidence, an unknown physical algorithm, invalid edges, incomplete
-source coverage, or a candidate that is not cheaper yields `None`. When no
+scan selection, or a candidate that is not cheaper yields `None`. When no
 candidate remains, `chosen = None` preserves the raw pre-ASAP target.
 
 Logical CSE share/recompute rewrites are not complete physical alternatives:

From 6b6dff93cd1f0c78506397a695efdebe6a7e9c00 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 19:32:26 +0000
Subject: [PATCH 09/48] docs: turn summary coverage into a design document

Move it to docs/design_docs/proposals with problem and motivation,
requirements, design, alternatives and key code interfaces.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 docs/design_docs/proposals/README.md          |   1 +
 .../design_docs/proposals/summary-coverage.md | 224 ++++++++++++++++++
 docs/develop_docs/summary-coverage.md         | 172 --------------
 3 files changed, 225 insertions(+), 172 deletions(-)
 create mode 100644 docs/design_docs/proposals/summary-coverage.md
 delete mode 100644 docs/develop_docs/summary-coverage.md

diff --git a/docs/design_docs/proposals/README.md b/docs/design_docs/proposals/README.md
index cb44fadbb..fc7fde96f 100644
--- a/docs/design_docs/proposals/README.md
+++ b/docs/design_docs/proposals/README.md
@@ -11,3 +11,4 @@ extensions. A design document is not a promise of downstream runtime support.
 - [Operator sharing](operator-sharing.md)
 - [Decoupling operators from scalar expressions](decoupling_op_and_expr.md)
 - [ASAPPlanner layering](planner-layering.md)
+- [Summary coverage](summary-coverage.md)
diff --git a/docs/design_docs/proposals/summary-coverage.md b/docs/design_docs/proposals/summary-coverage.md
new file mode 100644
index 000000000..a3520734d
--- /dev/null
+++ b/docs/design_docs/proposals/summary-coverage.md
@@ -0,0 +1,224 @@
+# Summary Coverage
+
+> Status: implemented in `ir::summary_coverage` (#567), with `SummaryMerge`
+> derivation (#560) and logical transport/CSE (#537). Checking declared
+> population against filters is open ([#570](https://github.com/ProjectASAP/ASAPPlanner/issues/570)).
+> Audience: planner designers and architects.
+> Companions: [Operator sharing](operator-sharing.md) §2.1 (schema model),
+> [ASAPPlanner layering](planner-layering.md) Pass 2 (window composition).
+
+## Goal and problem
+
+Record **which observations a summary state was built from**, its time range and
+population, so the planner can tell when combining or reusing summary states
+is correct.
+
+[Operator sharing](operator-sharing.md) §2.1 gives every edge one `Schema`. For
+a summary edge, the schema records the field layout and the committed state
+type, such as `(job: Utf8, state: KLL{k=200})`. It deliberately leaves out
+filters, group keys and windows. That is enough while a summary is consumed
+right after its producer. It stops being enough once
+[planner layering](planner-layering.md) composes existing states:
+
+- Pass 2's window-composition rule merges tumbling or EH summaries into a query
+  window.
+- `SummaryMerge` combines partial states.
+- Sub-DAG sharing, and the reuse of ingested panes, hand one state to several
+  consumers.
+
+In these cases only the schema is left to compare. Every example below uses
+two states with **equal schemas**, `Schema(job: Plain(Utf8), state: Sketch(KLL{k=200}))`.
+
+**Example 1: time.**
+
+| Input A | Input B | Merging A and B is… |
+|---|---|---|
+| latency, `[00:00, 00:01)` | latency, `[00:01, 00:02)` | correct: p99 over `[00:00, 00:02)` |
+| latency, `[00:00, 00:02)` | latency, `[00:01, 00:03)` | **wrong**: `[00:01, 00:02)` is counted twice |
+| latency, `[00:00, 00:01)` | latency, `[00:02, 00:03)` | correct only for `[0,1) ∪ [2,3)`, not for the continuous `[0,3)` |
+
+`Schema.time_index` is a column position. A KLL state has no timestamp column,
+so the schema cannot tell these apart.
+
+**Example 2: population (label values).**
+
+| Input A | Input B | Merging A and B is… |
+|---|---|---|
+| `region='us'` | `region='eu'` | correct: `us ∪ eu` within each `job` |
+| `region='us'` | `tier='premium'` | **wrong**: premium US requests are in both |
+| `region='us'` | `region='us'` | **wrong**: everything is counted twice |
+
+`region` is a filter label, not an output column. The `job` field says how the
+state is grouped, not which rows contributed.
+
+**Example 3: time and population together.** Merging `us × [0,1)` with
+`eu × [1,2)` covers exactly those two blocks. Recording one time range and one
+label set would give `{us,eu} × [0,2)`, which claims data that was never read.
+
+**Example 4: reuse.** For `p99(latency) WHERE region='us' AND ts IN [10:00, 10:05)
+GROUP BY job`, a stored state with a matching schema could hold the right data,
+EU data, or only 10:00–10:03. The schema shows that the state *type* fits, not
+that the *contents* fit.
+
+Schema equality is necessary but not sufficient. Without this metadata, the
+planner must either refuse every composition or accept silent double counting
+and missing data.
+
+### Requirements
+
+1. Represent time and population **jointly**, per block, never as independent
+   bounds.
+2. Accept a merge only when the inputs are **provably disjoint**, and fail
+   closed otherwise. Merging does not imply that a summary family can remove
+   duplicates.
+3. Leave `Schema` and its equality unchanged.
+4. Duplicate nothing the operator already records.
+5. Support sources without a time column (plain tables).
+
+## Design
+
+### Coverage is a node property, beside the schema
+
+```text
+OperatorNode
+├── schema: Schema                    what each output row looks like   (operator sharing §2.1)
+├── guarantee, timing                 accuracy and execution phase      (§2.2, §2.3)
+└── coverage: Option<SummaryCoverage> which observations the state holds
+```
+
+Coverage is not part of `Schema`. `SummaryMerge` requires equal input schemas,
+and the inputs of every useful merge (`[0,1)` + `[1,2)`) have different coverage.
+It is also not an operator parameter: a merge *derives* it from its inputs, like
+the schema.
+
+### What coverage records
+
+A `SummaryCoverage` names one observation `source`, using the same `Source` as
+`Scan`: a table or a time series. It holds a **union of regions**. Each region
+pairs:
+
+- `time_ms`: half-open bounds on the source's time column, or `None` for no
+  time restriction;
+- `population`: a conjunction of non-null `label = value` predicates, where
+  empty means all observations.
+
+Every observation in a region contributes once to the state. `regions = []`
+means known empty coverage.
+
+Coverage records only what no other node field records (requirement 4). What
+each observation contributes and how states are grouped are already
+`SummaryAgg.input` and `SummaryAgg.reduction`. `SummaryMerge` compares those on
+its producers directly.
+
+### Composition is a provably disjoint union
+
+`merge_disjoint` accepts inputs with the same source whose regions are pairwise
+disjoint. Two regions are disjoint when their time ranges do not intersect, or
+when they assign different values to the same label. Different labels prove
+nothing, and a region with no time bounds overlaps any region it is not
+population-disjoint from. The union keeps gaps and the time/population pairing.
+Adjacent intervals coalesce only when their populations are identical.
+
+| Case | Result |
+|---|---|
+| `[0,1)` + `[1,2)`, same population | one region `[0,2)` |
+| `[0,1)` + `[2,3)` | two regions (gap kept) |
+| `[0,2)` + `[1,3)` | rejected: possible overlap |
+| `region=us` + `region=eu`, same time | two regions |
+| `region=us` + `region=us`, or + `tier=premium` | rejected: possible overlap |
+| `us×[0,1)` + `eu×[1,2)` | two regions, never `{us,eu}×[0,2)` |
+| different source | rejected |
+
+Equality conjunctions are a deliberately narrow proof vocabulary. A richer
+predicate needs an explicit disjointness rule before it can be declared.
+
+### Lifecycle
+
+- **Required on summary nodes.** `SummaryAgg` and `SummaryMerge` cannot pass
+  structural validation without coverage. Other nodes leave it `None`. The
+  field is an `Option` only because all operators share `OperatorNode`.
+- **Declared at build.** The composition rule or catalog that builds a
+  `SummaryAgg` declares its coverage.
+- **Derived at merge.** `SummaryMerge` computes the disjoint union of its
+  inputs, and validation rejects a retained value that differs.
+- **Cleared on rewrite.** Rewriting a node's inputs clears its coverage, like
+  other assessed metadata. The rewriter must declare it again.
+- **Preserved downstream.** Logical export keeps coverage, and CSE shares two
+  nodes only if their coverage is equal.
+
+### Trust boundary
+
+Declarations are trusted. Population is not yet checked against
+`SummaryAgg.filter`, `Filter` nodes or `Scan.predicates`, so a wrong declaration
+passes:
+
+```text
+A = SummaryAgg(filter: region='us'), declared {region: eu} × [0,1)   ← wrong
+B = SummaryAgg(filter: region='us'), declared {region: us} × [0,1)
+merge_disjoint(A, B) is accepted, and every US observation is counted twice.
+```
+
+[#570](https://github.com/ProjectASAP/ASAPPlanner/issues/570) adds the check: the
+declared population must equal the `column = literal` predicates between the
+`SummaryAgg` and its `Scan`. Time bounds stay trusted, because `TimeRange` is
+relative to the evaluation time.
+
+### Alternatives considered
+
+| Alternative | Why not |
+|---|---|
+| Put coverage in `Schema` | Schema equality gates merges; merge inputs always differ in coverage. |
+| One time range plus one label set | Invents the missing blocks (Example 3). |
+| Copy `input` and `reduction` into coverage | Duplicates `SummaryAgg` and needs a consistency check; producers already carry them. |
+| Arbitrary predicates per region | No general disjointness proof; overlap would be silently accepted. |
+| Free-form string `source` | Two spellings of one table compare unequal; `Scan` already has `Source`. |
+| Snapshot `revision` field | Deployment concern; the planner does not own catalog versions. |
+
+## Key code interfaces
+
+```rust
+// crates/types/src/ir/summary_coverage.rs
+pub struct SummaryCoverage {
+    pub source: Source,               // same type as Scan.source
+    pub regions: Vec<CoverageRegion>, // union; never a product of independent bounds
+}
+pub struct CoverageRegion {
+    pub time_ms: Option<Range<i64>>,          // half-open; None = no time restriction
+    pub population: BTreeMap<String, String>, // label = value AND …; empty = all
+}
+impl SummaryCoverage {
+    pub fn validate(&self) -> Result<(), CoverageError>;
+    pub fn merge_disjoint(inputs: &[Self]) -> Result<Self, CoverageError>;
+}
+pub enum CoverageError {
+    InvalidInterval, InvalidPopulation, SourceMismatch, PossibleOverlap, EmptyMerge,
+    NotState, Missing,                    // node checks
+    UnknownInput, MergeOutputMismatch,    // SummaryMerge (#560)
+}
+
+// crates/types/src/ir/node.rs
+pub struct OperatorNode {
+    // operator, result_kind, schema, guarantee, timing, …
+    pub coverage: Option<SummaryCoverage>,
+}
+impl OperatorNode {
+    pub fn with_coverage(self, c: SummaryCoverage) -> Result<Self, SchemaDerivationError>;
+    pub fn requires_coverage(&self) -> bool;  // SummaryAgg, SummaryMerge
+    pub fn summary_update(&self) -> Option<(&SummaryUpdate, &Reduction)>; // #560
+}
+// SchemaDerivationError::Coverage(CoverageError) reports every failure above.
+```
+
+`OperatorNode::validate_structure` enforces the lifecycle rules. The documented
+examples are built as real `Scan → SummaryAgg → SummaryMerge` plans in
+`crates/types/tests/summary_coverage_examples.rs`.
+
+## Not covered
+
+- **Query containment:** checking that coverage contains a requested window or
+  population (Example 4). That is a later Stage 1 check that uses this data.
+- **Population check:** comparing declared population with filters
+  ([#570](https://github.com/ProjectASAP/ASAPPlanner/issues/570)).
+- **Richer predicates:** predicates beyond non-null equality conjunctions, and
+  idempotent set-union families.
+- **Runtime concerns:** merge kernels, accuracy, storage and execution timing.
diff --git a/docs/develop_docs/summary-coverage.md b/docs/develop_docs/summary-coverage.md
deleted file mode 100644
index 0de7d30fc..000000000
--- a/docs/develop_docs/summary-coverage.md
+++ /dev/null
@@ -1,172 +0,0 @@
-# Summary coverage contract
-
-## Problem: a schema says what a summary *is*, not what it *summarizes*
-
-Every ASAP edge has one `Schema`. For a summary edge it records the field
-layout and the committed state type:
-
-```rust
-pub struct Schema {
-    pub fields: Vec<Field>,            // e.g. job: Plain(Utf8), state: Sketch(KLL{k=200}, PerSubpopulationInstance)
-    pub time_index: Option<ColumnId>,  // position of a timestamp column, not a time range
-    pub unique_keys: Vec<Vec<ColumnId>>,
-    pub closed: bool,
-}
-```
-
-Nothing in it says **which time range** or **which population (label values)**
-the state was built from. Filters, group keys and windows are deliberately not
-`Schema` or `Field` members. This becomes a gap once the planner combines
-existing summary states (`SummaryMerge`, reuse of ingested panes, sub-DAG
-sharing). The producer no longer shows where a state came from, so only the
-schema is left to compare. Every example below uses two states with
-**exactly equal schemas**:
-
-```text
-Schema(job: Plain(Utf8), state: Sketch(KLL{k=200}, PerSubpopulationInstance)), result_kind = State
-```
-
-### Example 1: time. Equal schemas, different answers
-
-| Input A | Input B | Merging A and B is… |
-|---|---|---|
-| latency, `[00:00, 00:01)` | latency, `[00:01, 00:02)` | correct: p99 over `[00:00, 00:02)` |
-| latency, `[00:00, 00:02)` | latency, `[00:01, 00:03)` | **wrong**: every observation in `[00:01, 00:02)` is counted twice, which skews the quantile and doubles counts or frequencies |
-| latency, `[00:00, 00:01)` | latency, `[00:02, 00:03)` | correct only for `[0,1) ∪ [2,3)`; **wrong** if used for the continuous window `[00:00, 00:03)` |
-
-`time_index` is a column position. A KLL state has no timestamp column, so
-`time_index` is `None` in all three rows and the schema cannot tell them apart.
-
-### Example 2: population (label values). Equal schemas, different answers
-
-| Input A | Input B | Merging A and B is… |
-|---|---|---|
-| `region='us'` | `region='eu'` | correct: p99 for `us ∪ eu` within each `job` |
-| `region='us'` | `tier='premium'` | **wrong**: premium US requests are counted in both inputs |
-| `region='us'` | `region='us'` | **wrong**: everything is counted twice |
-
-`region` is a filter label, not an output column, so it never appears in the
-schema. The `job` field only says the state is grouped by job. It does not say
-which jobs or which rows contributed.
-
-### Example 3: time and population together
-
-A = `us × [0,1)` and B = `eu × [1,2)`. The merged state covers exactly those two
-blocks. Storing a time range and a label set separately would give
-`{us,eu} × [0,2)`. That claims EU data for `[0,1)` and US data for `[1,2)`
-that was never read. Time and population must stay **paired per region**.
-
-### Example 4: answering a query from a stored state
-
-Query: `p99(latency) WHERE region='us' AND ts IN [10:00, 10:05) GROUP BY job`.
-A stored state with the matching schema could hold US data for 10:00–10:05, EU
-data, or US data for only 10:00–10:03. All three have the same schema. The
-schema confirms that the state *type* fits, not that the *contents* fit.
-
-**Conclusion.** Schema equality is necessary but not sufficient for composing
-or reusing summaries. Without time and population metadata, the planner must
-either refuse every composition or accept silent double counting and missing
-data.
-
-## The contract
-
-`Schema` stays the layout contract and does **not** describe coverage. Coverage
-is a separate field on the node, next to `schema`:
-
-```text
-OperatorNode
-├── schema: Schema                    what each output row looks like
-└── coverage: Option<SummaryCoverage> which observations the state holds
-```
-
-Coverage cannot live inside `Schema`. `SummaryMerge` requires equal input
-schemas, and the inputs of a useful merge (`[0,1)` + `[1,2)`) always have
-different coverage.
-
-```rust
-pub struct SummaryCoverage {
-    pub source: Source,               // as named by Scan: Table { table_ref } or TimeSeries { metric }
-    pub regions: Vec<CoverageRegion>, // union of time × population blocks
-}
-pub struct CoverageRegion {
-    pub time_ms: Option<Range<i64>>,          // half-open, on the source's time column; None = no time restriction
-    pub population: BTreeMap<String, String>, // label = value AND …; empty = all observations
-}
-```
-
-Rules:
-
-- Coverage is **required on summary nodes**. `validate_structure` rejects a
-  `SummaryAgg` or `SummaryMerge` whose coverage is `None` with
-  `CoverageError::Missing`. Other nodes leave it `None`. The field is an
-  `Option` only because all operators share `OperatorNode`.
-- Coverage holds only what the operator does not already record. What is fed
-  into the state and how it is grouped stay on `SummaryAgg.input` and
-  `SummaryAgg.reduction`; `SummaryMerge` compares those on its inputs. `source`
-  uses the same `Source` type as `Scan`, so equal sources compare equal.
-- `with_coverage` validates the declaration and requires `State` output
-  (`NotState`). `validate_structure` re-checks it.
-- `SummaryMerge` derives its coverage from its inputs. `validate_structure`
-  rejects a retained value that differs from that union.
-- Rewriting a node's inputs clears its coverage. The rewriter must declare it
-  again with `with_coverage`.
-- Every observation in a region contributes once to the state. `regions = []`
-  means known empty coverage.
-- `time_ms: None` is for sources without a time column. Such a region overlaps
-  every region it is not population-disjoint from.
-
-## Merging
-
-`SummaryCoverage::merge_disjoint` requires equal `source` and provably
-disjoint regions. `SummaryMerge` additionally requires equal input schemas and
-equal `input`/`reduction` on its inputs' producers. Two regions are disjoint when their time ranges
-do not intersect, or when they give different values for the same population
-label. Different labels prove nothing. The examples above come out as:
-
-| Case | Result |
-|---|---|
-| `[0,1)` + `[1,2)`, same population | accepted, coalesced to one region `[0,2)` |
-| `[0,1)` + `[2,3)` | accepted, **two** regions (gap kept) |
-| `[0,2)` + `[1,3)` | `PossibleOverlap` |
-| `region=us` + `region=eu`, same time | accepted, two regions |
-| `region=us` + `region=us`, same time | `PossibleOverlap` |
-| `region=us` + `tier=premium` | `PossibleOverlap` |
-| `us×[0,1)` + `eu×[1,2)` | accepted, two regions, never widened to `{us,eu}×[0,2)` |
-| no time bounds + any region of the same population | `PossibleOverlap` |
-| different source | `SourceMismatch` |
-
-Adjacent intervals coalesce only when their population maps are identical.
-Merging an empty input list fails with `EmptyMerge`.
-
-## Trusted declarations
-
-Coverage is declared by the composition rule or catalog that built the
-subtree. Nothing is inferred from SQL. Population is not compared with `SummaryAgg.filter`,
-`Filter` nodes or `Scan.predicates`. Time bounds cannot be checked, because
-`TimeRange` stores a relative duration. So a wrong declaration passes:
-
-```text
-A = SummaryAgg(filter: region='us', input: latency, reduction: by job)
-    declared coverage: {region: eu} × [0,1)        ← wrong; the state holds US data
-B = SummaryAgg(filter: region='us', input: latency, reduction: by job)
-    declared coverage: {region: us} × [0,1)
-
-merge_disjoint(A, B)  → accepted ("eu" ≠ "us" proves disjoint)
-actual merged state   → every US observation in [0,1) counted twice
-a query for region='eu' could also be answered from A, which holds no EU data
-```
-
-Issue #570 tracks the check. The declared population must exactly equal the
-`column = literal` predicates collected between the `SummaryAgg` and its
-`Scan`, and any other predicate shape fails closed. It starts strict about
-which operators may sit on that path (only `Filter` and `TimeRange`), because
-`Project` or `Join` can rename columns or change rows.
-
-## Not covered
-
-- Checking that coverage *contains* a requested query window or population
-  (Example 4). That is a later query-relative check, which uses this data.
-- Predicates beyond non-null equality conjunctions; idempotent set-union
-  families.
-- Runtime merge kernels, accuracy certificates, storage policy or execution
-  timing.

From e529855490778a012db61b063377194e5065b9ce Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 19:45:21 +0000
Subject: [PATCH 10/48] docs: design doc for ASAP primitive schema and summary
 semantics

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 docs/design_docs/concepts/post-asap-ir.md     |   3 +-
 .../physical-planning-and-deployment.md       |  28 +-
 docs/design_docs/proposals/README.md          |   2 +-
 .../proposals/asap-primitive-schema.md        | 466 ++++++++++++++++++
 .../proposals/decoupling_op_and_expr.md       |   2 +-
 .../design_docs/proposals/operator-sharing.md | 156 +-----
 .../design_docs/proposals/summary-coverage.md | 224 ---------
 .../proposals/univmon-frequency-summary.md    |   3 +-
 .../asap-aware-mapping-contracts.md           |  24 +-
 docs/develop_docs/pre-asap-ir.md              |  24 +-
 10 files changed, 497 insertions(+), 435 deletions(-)
 create mode 100644 docs/design_docs/proposals/asap-primitive-schema.md
 delete mode 100644 docs/design_docs/proposals/summary-coverage.md

diff --git a/docs/design_docs/concepts/post-asap-ir.md b/docs/design_docs/concepts/post-asap-ir.md
index 6c9aa1461..08c670af4 100644
--- a/docs/design_docs/concepts/post-asap-ir.md
+++ b/docs/design_docs/concepts/post-asap-ir.md
@@ -49,7 +49,8 @@ summary family supports incremental maintenance.
   and selects the joined rows. Completeness evidence belongs to pruning, not ranking.
 
 A `SummaryNode` carries its expression, schema and optional result guarantee.
-State and query values have different contracts. Exact operations over
+State and query values have different contracts; see
+[Schema and physical data for ASAP primitives](../proposals/asap-primitive-schema.md). Exact operations over
 approximate readouts still require composed accuracy guarantees. See the
 [accuracy implementation companion](../../develop_docs/end-to-end-accuracy-guarantees.md)
 and [physical-plan integration](../architecture/physical-plan-integration.md)
diff --git a/docs/design_docs/physical-planning-and-deployment.md b/docs/design_docs/physical-planning-and-deployment.md
index 274e4974c..c48dfed54 100644
--- a/docs/design_docs/physical-planning-and-deployment.md
+++ b/docs/design_docs/physical-planning-and-deployment.md
@@ -117,26 +117,14 @@ operators from logical candidates has not completed this integration.
 
 ### Input semantics and summary semantics
 
-`source`, `filter`, `grouping` and `window` describe input-data semantics:
-where records originate, which records qualify, how they are grouped and which
-time interval applies. They are not a complete description of arbitrary summary
-computation. In particular, the same four fields can summarize different value
-expressions or produce different states.
-
-| Concern | Required semantic information |
-| --- | --- |
-| Input computation | Source identities and schemas, filters, joins/transforms and their order, or a reference to the canonical input sub-DAG |
-| Values and grouping | Value expressions, item identities and weights where applicable, group keys and types, and operation-defined null/duplicate handling |
-| Time | Time column and interpretation, interval bounds, evaluation alignment, and distinction between query range and maintained panes |
-| Summary computation | Exact operation or sketch family, algorithm and parameters, and supported build/merge behavior |
-| Output | State versus finalized value, output schema/type, and readout parameters when part of the output computation |
-
-For example, KLL over `latency_seconds` and KLL over `log(latency_seconds)` differ
-even with identical source, filter, grouping and window. Likewise, weighted
-frequency state needs both item and weight expressions. More complex inputs
-must retain their computation DAG; four descriptive fields cannot replace it.
-
-The canonical selected computation is authoritative. These categories describe
+`source`, `filter`, `grouping` and `window` describe input-data semantics but not
+a complete summary computation: the same four fields can summarize different
+value expressions or produce different states. The semantic information a summary
+depends on, and where the IR records each part (field type, producing operator,
+or coverage), is specified in
+[Schema and physical data for ASAP primitives](proposals/asap-primitive-schema.md#23-consideration-3-the-metadata-preserves-summary-semantics).
+
+The canonical selected computation is authoritative. Those categories describe
 what must be preserved, not a new flat IR or a second expression language.
 Operator-defined behavior should be referenced through its canonical contract,
 not independently configured in deployment metadata. Unsupported or unresolved
diff --git a/docs/design_docs/proposals/README.md b/docs/design_docs/proposals/README.md
index fc7fde96f..6c4ed49f8 100644
--- a/docs/design_docs/proposals/README.md
+++ b/docs/design_docs/proposals/README.md
@@ -11,4 +11,4 @@ extensions. A design document is not a promise of downstream runtime support.
 - [Operator sharing](operator-sharing.md)
 - [Decoupling operators from scalar expressions](decoupling_op_and_expr.md)
 - [ASAPPlanner layering](planner-layering.md)
-- [Summary coverage](summary-coverage.md)
+- [Schema and physical data for ASAP primitives](asap-primitive-schema.md)
diff --git a/docs/design_docs/proposals/asap-primitive-schema.md b/docs/design_docs/proposals/asap-primitive-schema.md
new file mode 100644
index 000000000..ca55ae469
--- /dev/null
+++ b/docs/design_docs/proposals/asap-primitive-schema.md
@@ -0,0 +1,466 @@
+# Schema and Physical Data for ASAP Primitives
+
+> Status: the edge schema and `FieldDataType` are implemented (operator sharing,
+> #511). `SummaryCoverage` is implemented in `ir::summary_coverage` (#567).
+> `SummaryMerge` coverage derivation lands in #560, and logical export/CSE of
+> coverage in #537. Checking declared population against filters is open
+> ([#570](https://github.com/ProjectASAP/ASAPPlanner/issues/570)).
+> Audience: planner designers and architects.
+> Companions: [Operator sharing](operator-sharing.md) (unified operator node),
+> [Decoupling operators from scalar expressions](decoupling_op_and_expr.md),
+> [ASAPPlanner layering](planner-layering.md) Pass 2 (window composition),
+> [Physical planning and deployment](../physical-planning-and-deployment.md).
+
+This document is the single source of truth for how an edge of the operator DAG
+is typed, how a field carries an ASAP primitive (summary or exact-accumulator
+state), what metadata says which data that state summarizes, and how such a field
+is carried as data at runtime.
+
+## 1. Goal and problem
+
+ASAP primitives are compact summaries over raw data: a KLL sketch over latency
+samples, an exact `Sum` accumulator, a Count-Min sketch over request keys. Once a
+plan contains them, three things must be explicit:
+
+1. **What flows on an edge.** Every operator, before and after ASAP optimization,
+   needs one typed output contract, so a projection above a summary and one below
+   it are the same operator.
+2. **That a field can be a primitive.** A state column is not a number. It has a
+   family, an algorithm and parameters, and it can only be read through a
+   readout.
+3. **What a primitive summarizes.** Two states of the same type can hold different
+   data. The planner must know which observations each holds before it combines or
+   reuses them.
+
+The schema alone answers the first two but not the third. Every example below
+uses two states with **equal schemas**,
+`Schema(job: Plain(Utf8), state: Sketch(KLL{k=200}))`.
+
+**Example 1: time.**
+
+| Input A | Input B | Merging A and B is… |
+|---|---|---|
+| `[00:00, 00:01)` | `[00:01, 00:02)` | correct: p99 over `[00:00, 00:02)` |
+| `[00:00, 00:02)` | `[00:01, 00:03)` | **wrong**: `[00:01, 00:02)` is counted twice |
+| `[00:00, 00:01)` | `[00:02, 00:03)` | correct only for `[0,1) ∪ [2,3)`, not for `[0,3)` |
+
+`Schema.time_index` is a column position. A KLL state has no timestamp column.
+
+**Example 2: population.**
+
+| Input A | Input B | Merging A and B is… |
+|---|---|---|
+| `region='us'` | `region='eu'` | correct: `us ∪ eu` within each `job` |
+| `region='us'` | `tier='premium'` | **wrong**: premium US requests are in both |
+| `region='us'` | `region='us'` | **wrong**: everything is counted twice |
+
+`region` is a filter label, not an output column. `job` says how the state is
+grouped, not which rows contributed.
+
+**Example 3: time and population together.** Merging `us × [0,1)` with
+`eu × [1,2)` covers exactly those two blocks. One time range plus one label set
+would give `{us,eu} × [0,2)`, which claims data that was never read.
+
+**Example 4: reuse.** For `p99(latency) WHERE region='us' AND ts IN [10:00, 10:05)
+GROUP BY job`, a stored state with a matching schema could hold the right data,
+EU data, or only 10:00–10:03. The schema shows that the state *type* fits, not
+that the *contents* fit.
+
+These compositions arise in Pass 2 window composition
+([planner layering](planner-layering.md)), in `SummaryMerge` of partial states,
+and in sub-DAG sharing and pane reuse. Schema equality is necessary but not
+sufficient. Without more metadata, the planner must refuse every composition or
+accept silent double counting and missing data.
+
+## 2. Design considerations
+
+```text
+OperatorNode
+├── operator: Operator                 the operation; SummaryAgg holds input, reduction, filter   (C3)
+├── result_kind: OperatorResultKind    Relation | InstantVector | RangeVector | State             (C2)
+├── schema: Schema                     the outgoing edge: fields, time, keys, closedness           (C1)
+│   └── fields[i].dtype: FieldDataType Plain(DataType) or an ASAP primitive state family          (C2)
+├── guarantee, timing                  accuracy and execution phase (operator sharing §2.2, §2.3)
+└── coverage: Option<SummaryCoverage>  which observations the state holds                          (C3)
+```
+
+### 2.1 Consideration 1: the schema is the edge between two nodes
+
+A node's `schema` types its output edge. The DAG is type-checked: the schema is
+derived from the operator and its inputs (`Operator::output_schema`), retained on
+the node, and verifiable without surrounding context. One `Schema` type serves
+every operator before and after ASAP optimization. It replaced the separate
+pre-ASAP `Schema`/`Column` and post-ASAP `SummarySchema`/`SummaryField` (old
+plans still deserialize).
+
+| Schema member | Meaning and requirement |
+|---|---|
+| `fields: Vec<Field>` | Ordered fields. `Field = name + dtype: FieldDataType + nullable + table`. `table` preserves SQL qualified resolution through joins. A `Field` holds metadata, never data. |
+| `time_index` | Position of the `Plain(Timestamp)` time column, if any. It does not distinguish an instant vector from a range vector. |
+| `unique_keys` | Proven column combinations identifying rows; empty asserts no known key. Rewrites that change identity recompute them. |
+| `closed` | Whether `fields` is complete. A schemaless PromQL leaf is open; the first `Aggregate`/`Project` that fully determines its output closes it. Open schemas skip closed-world validation. |
+
+**`ColumnId` versus `ColumnRef`.** These are different roles, not competing
+representations:
+
+| Name | Role | Holds runtime values? |
+|---|---|---|
+| `Schema`, `Field` | Edge metadata | No |
+| `ColumnRef` | Unresolved logical reference: `Named`, `Qualified`, `SampleValue`, `Wildcard` | No |
+| `ColumnId = usize` | Resolved position in one particular input/output schema | No |
+| Runtime batch | Values conforming to a schema (§3) | Yes |
+
+Resolution binds a `ColumnRef` to a `ColumnId` before operator nodes are built.
+The same position indexes `schema.fields` for type checking and selects the
+value at execution: resolving `t.bytes` to `1` gives its type from
+`schema.fields[1]`, and `ScalarExpr::Column(1)` reads `row[1]` in the native
+executor (or array `1` in a columnar one). `time_index`, `unique_keys` and group
+keys use the same positions. A `ColumnId` is local to its schema, not a stable
+identity across projections or joins, so there is no `FieldId`. ASAP payloads
+that refer to input data before resolution (`SummaryUpdate`, `SketchStatistic::PointCount`)
+keep `ColumnRef`.
+
+**Derivation and validation.**
+
+- `Scan.schema` declares source columns and `Values.schema` the constructed rows;
+  every other `OperatorNode.schema` is derived. Planning may override only output
+  names and qualifiers (`OperatorNode::with_schema`); all structural metadata must
+  equal derivation.
+- `ScalarExpr::scalar_type(input)` types an expression against its column scope
+  (child schema, both join inputs, or aggregate outputs for `HAVING`).
+- `OperatorNode::validate_structure()` walks the reachable DAG: input contracts,
+  scalar typing, retained-versus-derived schema and result kind, and coverage
+  (§2.3). It permits `timing = None`.
+- `OperatorNode::validate_execution_timing()` adds assigned timing and phase
+  dependencies, for executable candidates. Neither method proves accuracy;
+  guarantees stay with planner assessment (#509).
+
+### 2.2 Consideration 2: a field can have an ASAP primitive type
+
+`FieldDataType` types every field. `Plain` is an ordinary readable value; every
+other variant is the state of one ASAP primitive family and carries the identity
+and parameters required by that family:
+
+```rust
+enum FieldDataType {
+    Plain(DataType),                          // readable value
+    ExactAggregate(ExactKind, ExactParams),   // Sum, Count, Min, Max, Increase, Rate, IRate
+    Sketch(SketchKind, GroupingStrategy),     // KLL, DDSketch, HLL, CMS, CountSketch, UnivMon, …
+    Sample(SamplingKind, SamplingParams),
+    Wavelet(WaveletKind, WaveletParams),
+    StatModel(StatModelKind, StatModelParams),
+}
+```
+
+**Identity levels.** A sketch has one more level than the other families, because
+several algorithms serve one query category (KLL and DDSketch both answer
+quantiles):
+
+| Level | Type | Example |
+|---|---|---|
+| family | `FieldDataType` variant | `Sketch`, `Sample`, `Wavelet`, `StatModel`, `ExactAggregate` |
+| category | `SketchCategory` | `Quantile`, `Cardinality`, `Frequency`, `TopK`, `Universal` |
+| algorithm | `SketchAlgorithm` | `Kll`, `DDSketch`; `Hll`, `Theta`, `Kmv`; `Cms`, `CountSketch`, … |
+| committed choice | `SketchKind` | one validated category + algorithm + `SketchParams` |
+
+`SketchKind::new(algorithm, params)` is the only constructor: it rejects a
+parameter variant from another algorithm and classifies the pair into its
+category; `.category()`, `.algorithm()` and `.params()` expose the committed
+values. `Sample`, `Wavelet` and `StatModel` use flat `(Kind, Params)` pairs;
+`ExactParams` is per-kind so a mismatched pair is a type error.
+`GroupingStrategy` records the physical layout across `by` subpopulations:
+`PerSubpopulationInstance` (default) or `SharedMultiSubpopulation { HydraKind,
+HydraParams }`. It is part of the type because a shared Hydra structure and
+independent instances are not merge-compatible even with the same algorithm.
+
+Because the full identity is in the type, incompatible states fail at plan
+construction: a merge over `Sketch(Kll, …)` and `Sketch(Cms, …)`, or a `Sketch`
+read as a `Sample`, is a schema error.
+
+**Rules for state fields.**
+
+- **Top-level only.** Nested `List`/`Struct` elements are `Field<DataType>`, not
+  `Field<FieldDataType>`, so a nested field cannot carry state.
+- **Produced only by state operators.** `SummaryAgg.family` is never `Plain`; its
+  input must be values, not state. Its output is the grouping columns plus one
+  non-nullable `state` field of that family.
+- **State is not a value.** `scalar_type` rejects a state column ("read it out
+  first"). `Filter`, `BinaryOp`, `Join`, `SetOp`, `Concat`, `Aggregate` and
+  `Dedup` reject `State` inputs; a bare-column `Project` may pass a state field
+  through unchanged (its result stays `State`).
+  Copying a state column does not make it readable.
+- **Result kind.** `OperatorResultKind::State` marks an output carrying
+  unfinalized state; its schema may also contain plain grouping keys. Matching
+  columns never make result kinds interchangeable.
+
+**Readout / finalization boundary.** State becomes plain values only through an
+explicit ASAP readout, which takes its input's relation/vector kind:
+
+| Readout | Input | Output field |
+|---|---|---|
+| `SummaryEstimate { query: SketchStatistic }` | exactly one `Sketch` state field whose category supports `query` | `Plain`: `quantile`/`frequency_l2`/`frequency_entropy` `Float64`, `cardinality`/`count` `Int64`, `topk` `Utf8` |
+| `FinalizeExactAccumulator` | `ExactAggregate` state | the finalized aggregate value |
+| `EvaluatePopulation` | `MaintainPopulation` state | the requested population statistic |
+
+For example, a KLL build outputs `State` with a `Sketch(KLL{k=200})` column; its
+p99 readout outputs `Plain(Float64)`. A numeric predicate can use the readout but
+not the state.
+
+### 2.3 Consideration 3: the metadata preserves summary semantics
+
+A state is only meaningful together with what it summarizes. The information a
+summary's semantics depends on is:
+
+| Concern | Required semantic information |
+|---|---|
+| Input computation | Source identities and schemas, filters, joins/transforms and their order, or the canonical input sub-DAG |
+| Values and grouping | Value expressions, item identities and weights, group keys and types, null/duplicate handling |
+| Time | Time column and interpretation, interval bounds, evaluation alignment, query range versus maintained panes |
+| Summary computation | Exact operation or sketch family, algorithm and parameters, build/merge behavior |
+| Output | State versus finalized value, output schema/type, readout parameters |
+
+KLL over `latency_seconds` and KLL over `log(latency_seconds)` differ even with
+identical source, filter, grouping and window. Weighted frequency state needs both
+item and weight expressions. Four descriptive fields (`source`, `filter`,
+`grouping`, `window`) cannot replace the computation DAG.
+
+The design splits this information by what it varies with, and records each fact
+once:
+
+| Where | What it records | Why there |
+|---|---|---|
+| Field type (`FieldDataType`) | Family, algorithm, parameters, grouping layout | It determines merge compatibility and which readouts apply, so it gates schema equality. |
+| Producer operator (`SummaryAgg`) | `input: SummaryUpdate` (item, weight, `weight_domain` proof), `reduction` (group keys or per-entity), `filter`, `grouping`; the child sub-DAG is the input computation | These are the operation's parameters; copying them elsewhere would need a consistency check. |
+| Node (`OperatorNode.coverage`) | Which observations: a source and a union of time × population regions | It differs between states that must still merge, and it cannot be derived from `SummaryAgg` alone. |
+| Result kind and readout node | State versus value, readout statistic | Derived from the operator (§2.2). |
+
+Time alignment, panes and maintenance lifecycle are planning and deployment
+concerns ([planner layering](planner-layering.md),
+[physical planning](../physical-planning-and-deployment.md)).
+
+#### Coverage is beside the schema, not inside it
+
+Coverage is not part of `Schema`. `SummaryMerge` requires equal input schemas,
+and the inputs of every useful merge (`[0,1)` + `[1,2)`) have different coverage.
+Coverage also describes the whole state output, not one field. It is not an
+operator parameter either: a merge *derives* it from its inputs, like the schema.
+
+Requirements:
+
+1. Represent time and population **jointly**, per region, never as independent
+   bounds.
+2. Accept a merge only when the inputs are **provably disjoint**; fail closed.
+   Merging does not imply that a family can remove duplicates.
+3. Leave `Schema` and its equality unchanged.
+4. Duplicate nothing the operator already records.
+5. Support sources without a time column (plain tables).
+
+#### What coverage records
+
+`SummaryCoverage` names one observation `source`, using the same `Source` as
+`Scan` (a table or a time series), and holds a **union of regions**. Each
+`CoverageRegion` pairs:
+
+- `time_ms`: half-open bounds on the source's time column, or `None` for no time
+  restriction;
+- `population`: a conjunction of non-null `label = value` predicates; empty means
+  all observations.
+
+Every observation in a region contributes once to the state. `regions = []` means
+known empty coverage. What each observation contributes and how states are
+grouped stay on `SummaryAgg.input` and `SummaryAgg.reduction` (requirement 4);
+`SummaryMerge` compares those on its producers directly (#560).
+
+#### Composition is a provably disjoint union
+
+`merge_disjoint` accepts inputs with the same source whose regions are pairwise
+disjoint. Two regions are disjoint when their time ranges do not intersect, or
+when they assign different values to the same label. Different labels prove
+nothing, and a region without time bounds overlaps any region it is not
+population-disjoint from. The union keeps gaps and the time/population pairing;
+adjacent intervals coalesce only when their populations are identical.
+
+| Case | Result |
+|---|---|
+| `[0,1)` + `[1,2)`, same population | one region `[0,2)` |
+| `[0,1)` + `[2,3)` | two regions (gap kept) |
+| `[0,2)` + `[1,3)` | rejected: possible overlap |
+| `region=us` + `region=eu`, same time | two regions |
+| `region=us` + `region=us`, or + `tier=premium` | rejected: possible overlap |
+| `us×[0,1)` + `eu×[1,2)` | two regions, never `{us,eu}×[0,2)` |
+| different source | rejected |
+
+Equality conjunctions are a deliberately narrow proof vocabulary. A richer
+predicate needs an explicit disjointness rule before it can be declared.
+
+#### Lifecycle
+
+- **Required on summary nodes.** `SummaryAgg` cannot pass `validate_structure`
+  without coverage; `SummaryMerge` joins it in #560. Coverage on a non-`State`
+  node is rejected. The field is an `Option` only because all operators share
+  `OperatorNode`.
+- **Declared at build.** The composition rule or catalog that builds a
+  `SummaryAgg` declares it (`with_coverage`). No production builder declares it
+  on this branch yet.
+- **Derived at merge (#560).** `SummaryMerge` computes the disjoint union of its
+  inputs, and validation rejects a retained value that differs.
+- **Cleared on rewrite.** `map_children` rebuilds the node without coverage, like
+  `guarantee` and `timing`. The rewriter must declare it again.
+- **Preserved downstream (#537).** Logical export keeps coverage, and CSE shares
+  two nodes only if their coverage is equal.
+
+#### Trust boundary
+
+Declarations are trusted. Population is not yet checked against
+`SummaryAgg.filter`, `Filter` nodes or `Scan.predicates`, so a wrong declaration
+passes:
+
+```text
+A = SummaryAgg(filter: region='us'), declared {region: eu} × [0,1)   ← wrong
+B = SummaryAgg(filter: region='us'), declared {region: us} × [0,1)
+merge_disjoint(A, B) is accepted, and every US observation is counted twice.
+```
+
+[#570](https://github.com/ProjectASAP/ASAPPlanner/issues/570) adds the check: the
+declared population must equal the `column = literal` predicates between the
+`SummaryAgg` and its `Scan`. Time bounds stay trusted, because `TimeRange` is
+relative to the evaluation time.
+
+## 3. Physical data: how a state column is carried
+
+The runtime uses the same `Schema` as planning (`SchemaRef = Arc<Schema>`). The
+native executor (`asap-physical-operators`) stores `Batch { schema, rows:
+Vec<Vec<Value>> }`; the row/column layout is executor-specific. A state column
+holds a typed value:
+
+```rust
+enum Value {
+    Null, Bool(..), Int64(..), Float64(..), Utf8(..), Timestamp(..), Date(..),
+    Interval { .. }, List(..), Struct(..), Map(..),
+    Summary { family: FieldDataType, state: Arc<dyn AggregateCore> },
+}
+```
+
+- **Typed at the boundary.** `Batch::try_new` checks each `Summary` value's
+  `family` equals the field's `FieldDataType`, and that the payload's shape
+  (algorithm and parameters, for example KLL `k` or CMS width × depth) matches it.
+  State fields must be non-nullable and of a natively supported family.
+- **Not a key.** A `Summary` value cannot be a grouping key or be ordered.
+- **Kernels.** `summary_kernels` adapt `asap_sketchlib` structures and exact
+  Planner state behind `AggregateCore`: `merge_with` (same family and shape),
+  `estimate(SketchStatistic)`, and `approx_memory_bytes` for memory reservations.
+  `create_planner_accumulator(family, input, grouping)` builds the updater a
+  `SummaryAgg` declares and rejects a family/grouping disagreement.
+- **Native coverage.** Exact Sum/Count/Min/Max/Rate/Increase, KLL, DDSketch, HLL,
+  Count-Min (stored state only), and weighted CMS/CountSketch with heaps.
+  `SharedMultiSubpopulation` grouping, `Sample`, `Wavelet` and `StatModel` have
+  no native kernel and are rejected at binding.
+- **No encoding here.** `Value::Summary` is not serialized; byte encodings belong
+  to `asap_sketchlib` and deployments.
+
+Coverage is plan metadata and is not carried in runtime values. Physical merge of
+states by group key checks family equality only; disjointness is proven at
+planning time (§2.3).
+
+## 4. Alternatives considered
+
+| Alternative | Why not |
+|---|---|
+| Separate pre-ASAP and post-ASAP schema types | A projection above a summary needs a different representation from one below it; one `Schema` removes the barrier. |
+| An opaque "state" type without family identity | KLL + CMS merges, and sketch-versus-sample confusion, would only fail at runtime. |
+| State inside `List`/`Struct` fields | Nested state would escape the readout boundary and state validation. |
+| Put coverage in `Schema` | Schema equality gates merges; merge inputs always differ in coverage. |
+| One time range plus one label set | Invents the missing blocks (Example 3). |
+| Copy `input` and `reduction` into coverage | Duplicates `SummaryAgg` and needs a consistency check; producers already carry them. |
+| Arbitrary predicates per region | No general disjointness proof; overlap would be silently accepted. |
+| Free-form string `source` | Two spellings of one table compare unequal; `Scan` already has `Source`. |
+| Snapshot `revision` field | Deployment concern; the planner does not own catalog versions. |
+
+## 5. Key code interfaces
+
+```rust
+// crates/types/src/pre_asap/schema.rs
+pub type ColumnId = usize;
+pub struct Field<T = FieldDataType> { pub name: String, pub dtype: T, pub nullable: bool, pub table: Option<String> }
+pub struct Schema {
+    pub fields: Vec<Field>,
+    pub time_index: Option<ColumnId>,
+    pub unique_keys: Vec<Vec<ColumnId>>,
+    pub closed: bool,
+}
+pub enum FieldDataType { Plain(DataType), ExactAggregate(..), Sketch(SketchKind, GroupingStrategy), Sample(..), Wavelet(..), StatModel(..) }
+// DataType::List { element: Box<Field<DataType>> }, DataType::Struct { fields: Vec<Field<DataType>> }
+
+// crates/types/src/post_asap/sketch.rs
+impl SketchKind { pub fn new(algorithm: SketchAlgorithm, params: SketchParams) -> Self; }
+pub enum GroupingStrategy { PerSubpopulationInstance, SharedMultiSubpopulation { kind: HydraKind, params: HydraParams } }
+pub struct SummaryUpdate { pub item: Option<SummaryInputExpr>, pub weight: SummaryInputExpr, pub weight_domain: WeightDomain }
+
+// crates/types/src/ir/asap.rs
+pub enum ASAPOp {
+    SummaryAgg { child, family: FieldDataType, input: SummaryUpdate, reduction: Reduction,
+                 grouping: GroupingStrategy, filter: Option<Predicate> },
+    SummaryEstimate { summary_input, query: SketchStatistic },
+    FinalizeExactAccumulator { child },
+    SummaryMerge { children },            // reserved here; structure in #560
+    // MaintainPopulation, EvaluatePopulation, SummarySubtract, SummaryDelete, SummaryJoin, Extension
+}
+
+// crates/types/src/ir/summary_coverage.rs
+pub struct SummaryCoverage { pub source: Source, pub regions: Vec<CoverageRegion> }
+pub struct CoverageRegion {
+    pub time_ms: Option<Range<i64>>,          // half-open; None = no time restriction
+    pub population: BTreeMap<String, String>, // label = value AND …; empty = all
+}
+impl SummaryCoverage {
+    pub fn validate(&self) -> Result<(), CoverageError>;
+    pub fn merge_disjoint(inputs: &[Self]) -> Result<Self, CoverageError>;
+}
+pub enum CoverageError {
+    InvalidInterval, InvalidPopulation, SourceMismatch, PossibleOverlap, EmptyMerge,
+    NotState, Missing,
+    // #560: UnknownInput, MergeOutputMismatch
+}
+
+// crates/types/src/ir/node.rs
+pub enum OperatorResultKind { Relation, InstantVector, RangeVector, State }
+pub struct OperatorNode {
+    pub operator: Operator, pub result_kind: OperatorResultKind, pub schema: Schema,
+    pub guarantee: Option<ResultGuarantee>, pub timing: Option<ExecutionTiming>,
+    pub coverage: Option<SummaryCoverage>,
+}
+impl OperatorNode {
+    pub fn with_schema(operator: Operator, schema: Schema) -> Self;
+    pub fn with_coverage(self, c: SummaryCoverage) -> Result<Self, SchemaDerivationError>;
+    pub fn requires_coverage(&self) -> bool;  // SummaryAgg; SummaryMerge in #560
+    pub fn validate_structure(self: &Rc<Self>) -> Result<(), SchemaDerivationError>;
+    pub fn validate_execution_timing(self: &Rc<Self>) -> Result<(), SchemaDerivationError>;
+    // #560: pub fn summary_update(&self) -> Option<(&SummaryUpdate, &Reduction)>;
+}
+// SchemaDerivationError::Coverage(CoverageError) reports coverage failures.
+
+// crates/asap-physical-operators/src/{values.rs, summary_kernels/traits.rs}
+pub enum Value { /* plain variants */ Summary { family: FieldDataType, state: Arc<dyn AggregateCore> } }
+pub trait AggregateCore {
+    fn merge_with(&self, other: &dyn AggregateCore) -> Result<Box<dyn AggregateCore>, KernelError>;
+    fn estimate(&self, query: &SketchStatistic) -> Result<f64, KernelError>;
+    fn approx_memory_bytes(&self) -> usize;
+}
+```
+
+Coverage composition is tested in `crates/types/tests/summary_coverage.rs`. The
+documented examples are built as real `Scan → SummaryAgg → SummaryMerge` plans in
+`crates/types/tests/summary_coverage_examples.rs` (#560).
+
+## 6. Not covered
+
+- **Query containment:** checking that coverage contains a requested window or
+  population (Example 4). That is a later Stage 1 check that uses this data.
+- **Population check:** comparing declared population with filters
+  ([#570](https://github.com/ProjectASAP/ASAPPlanner/issues/570)).
+- **Richer predicates:** predicates beyond non-null equality conjunctions, and
+  idempotent set-union families.
+- **Runtime concerns:** state encoding, storage, retention, scheduling, kernel
+  accuracy and performance.
+- **Persisted semantic identity:** the stored-definition format and any tenant or
+  dataset binding belong to the deployment.
diff --git a/docs/design_docs/proposals/decoupling_op_and_expr.md b/docs/design_docs/proposals/decoupling_op_and_expr.md
index f87456a9f..f850116bb 100644
--- a/docs/design_docs/proposals/decoupling_op_and_expr.md
+++ b/docs/design_docs/proposals/decoupling_op_and_expr.md
@@ -62,7 +62,7 @@ operator inputs and scalar query-result references use `Rc<OperatorNode>`.
 read by expressions. Keep `ScalarExpr::Column(ColumnId)`: the ID selects a field
 for type checking and the corresponding input value for evaluation, independently
 of the executor's row/column storage layout. See the
-[fields versus column references contract](operator-sharing.md#21-one-schema-model-for-values-and-state).
+[fields versus column references contract](asap-primitive-schema.md#21-consideration-1-the-schema-is-the-edge-between-two-nodes).
 
 Names are resolved to `ColumnId` before constructing these nodes. Parsing and
 unresolved `ColumnRef` handling remain frontend concerns; no alternative generic
diff --git a/docs/design_docs/proposals/operator-sharing.md b/docs/design_docs/proposals/operator-sharing.md
index 1851d1809..c9ab193a4 100644
--- a/docs/design_docs/proposals/operator-sharing.md
+++ b/docs/design_docs/proposals/operator-sharing.md
@@ -365,155 +365,13 @@ caching or mutation mechanism.
 
 ### 2.1 One schema model for values and state
 
-Use one `Schema` for operator outputs before and after optimization. Rename today's
-`SummaryFamilyType` to `FieldDataType`: it types every field, and `Plain` is not a summary
-family. Rename `Column` to `Field` and `Schema.columns` to `Schema.fields`: the struct
-describes a column and holds none of its data. Retain the current `Schema` metadata.
-The following is the proposed resolved interface; it is not the current Rust definition.
-
-```rust
-struct Field {
-    name: String,
-    dtype: FieldDataType,
-    nullable: bool,
-    table: Option<String>,
-}
-
-struct Schema {
-    fields: Vec<Field>,
-    time_index: Option<ColumnId>,
-    unique_keys: Vec<Vec<ColumnId>>,
-    closed: bool,
-}
-
-// Today's `SummaryFamilyType`, renamed; variants and payloads unchanged.
-enum FieldDataType {
-    Plain(DataType),
-    ExactAggregate(ExactKind, ExactParams),
-    Sketch(SketchKind, GroupingStrategy),
-    Sample(SamplingKind, SamplingParams),
-    Wavelet(WaveletKind, WaveletParams),
-    StatModel(StatModelKind, StatModelParams),
-}
-
-// Proposed derived output classification, separate from column types.
-enum OperatorResultKind {
-    Relation,
-    InstantVector,
-    RangeVector,
-    State,
-}
-
-impl Operator {
-    fn output_schema(&self) -> Result<Schema, QueryExprError>;
-    fn output_kind(&self) -> Result<OperatorResultKind, QueryExprError>;
-    fn validate_inputs(&self) -> Result<(), QueryExprError>;
-}
-
-impl OperatorNode {
-    fn validate_structure(&self) -> Result<(), QueryExprError>;
-    fn validate_execution_timing(&self) -> Result<(), QueryExprError>;
-}
-
-impl ScalarExpr {
-    fn scalar_type(&self, input: &Schema) -> Result<(DataType, bool), QueryExprError>;
-}
-```
-
-**Fields versus column references.** These names describe different roles, not
-competing representations of the same object:
-
-| Name | Role | Holds runtime values? |
-|---|---|---|
-| `Schema` | Ordered `Field` metadata, plus key/time/closedness information | No |
-| `Field` | Name, type, nullability and optional qualifier for one output column | No |
-| `ColumnRef` | Unresolved logical reference: `Named`, `Qualified`, `SampleValue`, or `Wildcard` | No |
-| `ColumnId = usize` | Resolved column position in a particular input/output schema | No |
-| Runtime batch | Values conforming to a schema; storage layout is executor-specific | Yes |
-
-Keep `ColumnRef`, `ColumnId`, and `ScalarExpr::Column(ColumnId)`. Renaming the
-metadata struct `Column` to `Field` does not rename column references to field
-references. The same position identifies metadata during planning and values
-during execution; it is not a stable field identity across projections or joins.
-Schema `unique_keys` and `time_index` also use these column positions.
-
-For example, resolving `t.bytes` to position `1` produces `ColumnId = 1`.
-`schema.fields[1]` supplies its type and nullability; evaluating
-`ScalarExpr::Column(1)` reads the corresponding value. The native executor
-currently reads `row[1]` from `Batch { schema, rows: Vec<Vec<Value>> }`. A columnar
-executor would select array `1` instead. No physical `Column` container is
-introduced by the metadata rename, and the old metadata `Column` struct is not
-retained as a second type.
-
-**Relationship to current types.** `Field` is today's pre-ASAP `Column` with `dtype`
-widened from `DataType` to `FieldDataType`. `FieldDataType` is today's `SummaryFamilyType`
-under a name that also fits its `Plain` case. The proposed common `Schema` replaces
-the separate operator-edge roles of pre-ASAP `Schema` and post-ASAP `SummarySchema` /
-`SummaryField`; it does not rename `DataType`. A pre-ASAP value column becomes
-`Plain(dtype)`.
-Frontend validation permits only ordinary value columns, preserving the current
-pre-ASAP restriction even though the common schema can also express state.
-
-| Field | Meaning and requirement |
-|---|---|
-| `fields` | Ordered named fields. `Plain(DataType)` is a readable value; other variants retain the identity and parameters of summary or exact-accumulator state. |
-| `Field.nullable`, `Field.table` | Preserve SQL nullability and qualified column resolution. |
-| `time_index` | Identifies the time column when present; it does not by itself distinguish an instant vector from a range vector. |
-| `unique_keys` | Proven column combinations identifying rows; an empty list asserts no known key. Recompute these proofs when a rewrite changes identity. |
-| `closed` | Whether `fields` completely describes the output. An open PromQL schema must retain unlisted labels through the existing complete-series-identity contract. |
-
-`OperatorResultKind` is derived from the operation and its inputs and retained as
-`OperatorNode.result_kind`. `State` describes an output carrying unfinalized state; its
-schema may also contain ordinary grouping keys. `SummaryEstimate`,
-`FinalizeExactAccumulator` and other readouts derive the appropriate relation or
-vector kind from their operation and input context. Matching numeric columns do
-not make those kinds interchangeable.
-
-**Interface contracts.** `Operator::output_schema` and `output_kind` derive output
-metadata from the payload and validated inputs. `validate_inputs` checks local
-producer/consumer compatibility, such as vector inputs for `BinaryOp` or the
-required state family for a summary readout. Scalar typing checks the input-kind
-contract of `PromqlScalarFromVector` and other scalar plan reads.
-
-| Validation entry | Scope and stage |
-|---|---|
-| `OperatorNode::validate_structure()` | Walks the reachable operator DAG, including scalar plan references; checks input contracts, scalar typing and agreement between retained and derived output metadata. Valid for logical and physical plans; permits `timing = None`. |
-| `OperatorNode::validate_execution_timing()` | Includes structural validation, then requires assigned timing on every executable operator and checks phase dependencies. Used for executable physical candidates. |
-| Existing planner assessment and selection (#509) | Establishes guarantees using the existing accuracy models and checks them against request requirements and deployment capabilities. Neither node method re-proves a guarantee or decides request feasibility. |
-
-The two node methods need only the DAG and its annotations. Request requirements
-and deployment models remain inputs to the existing planning/selection workflow,
-not implicit globals of `validate_structure`. Passing the timing check alone does
-not establish that a physical candidate satisfies the query's accuracy requirement.
-
-`Scan.schema` declares the source columns; `Values.schema` declares the constructed
-row shape. `OperatorNode.schema` is the derived output for any operation. A scan's
-predicates cannot change its declared output columns; a Values row must match the
-declared arity, types and nullability. These leaf outputs retain the declaration's
-column layout and time/identity information, with only justified metadata changes.
-The declaration and derived output therefore have distinct roles, and structural
-validation rejects disagreement rather than trusting two independent schemas.
-
-`scalar_type` keeps the existing method name and `(DataType, nullable)` result.
-Its `input` is the applicable column scope: the child schema for a projection,
-both input schemas for a join predicate, or aggregate outputs for `HAVING`.
-Explicit subquery/conversion expressions validate their referenced producer using
-the contracts above. Numeric expressions cannot consume state columns as numbers.
-A standalone scalar expression is checked with an empty column scope and needs no fabricated
-relation output schema. `QueryExprError` retains the existing error-type name;
-result-kind, state-family, schema and execution-phase mismatches require
-corresponding validation errors.
-
-For example, a KLL build outputs `State` with a
-`Sketch(SketchKind, GroupingStrategy)` column identifying KLL and its parameters.
-Its p99 readout outputs an ordinary `Plain(Float64)` column in the appropriate
-relation/vector schema. A numeric predicate can use that readout, but not the KLL
-state. Exact accumulator state similarly requires `FinalizeExactAccumulator`.
-An ordinary operator may pass state through only where its input/output contract
-permits it. A bare-column projection can preserve the field's `FieldDataType`
-directly during `output_schema` derivation; `scalar_type` applies when that column
-is used as a scalar value and rejects state. Copying a state column does not turn
-it into a readable scalar.
+Every operator output, before and after optimization, uses one `Schema` whose
+`Field`s are typed by `FieldDataType`: `Plain(DataType)` for a readable value, or
+the family, algorithm and parameters of summary or exact-accumulator state.
+`OperatorResultKind` marks state outputs, and state becomes a value only through
+an explicit readout. The schema model, `ColumnRef` versus `ColumnId`, the
+validation entry points and the readout boundary are specified in
+[Schema and physical data for ASAP primitives](asap-primitive-schema.md).
 
 ### 2.2 Preserve existing accuracy semantics
 
diff --git a/docs/design_docs/proposals/summary-coverage.md b/docs/design_docs/proposals/summary-coverage.md
deleted file mode 100644
index a3520734d..000000000
--- a/docs/design_docs/proposals/summary-coverage.md
+++ /dev/null
@@ -1,224 +0,0 @@
-# Summary Coverage
-
-> Status: implemented in `ir::summary_coverage` (#567), with `SummaryMerge`
-> derivation (#560) and logical transport/CSE (#537). Checking declared
-> population against filters is open ([#570](https://github.com/ProjectASAP/ASAPPlanner/issues/570)).
-> Audience: planner designers and architects.
-> Companions: [Operator sharing](operator-sharing.md) §2.1 (schema model),
-> [ASAPPlanner layering](planner-layering.md) Pass 2 (window composition).
-
-## Goal and problem
-
-Record **which observations a summary state was built from**, its time range and
-population, so the planner can tell when combining or reusing summary states
-is correct.
-
-[Operator sharing](operator-sharing.md) §2.1 gives every edge one `Schema`. For
-a summary edge, the schema records the field layout and the committed state
-type, such as `(job: Utf8, state: KLL{k=200})`. It deliberately leaves out
-filters, group keys and windows. That is enough while a summary is consumed
-right after its producer. It stops being enough once
-[planner layering](planner-layering.md) composes existing states:
-
-- Pass 2's window-composition rule merges tumbling or EH summaries into a query
-  window.
-- `SummaryMerge` combines partial states.
-- Sub-DAG sharing, and the reuse of ingested panes, hand one state to several
-  consumers.
-
-In these cases only the schema is left to compare. Every example below uses
-two states with **equal schemas**, `Schema(job: Plain(Utf8), state: Sketch(KLL{k=200}))`.
-
-**Example 1: time.**
-
-| Input A | Input B | Merging A and B is… |
-|---|---|---|
-| latency, `[00:00, 00:01)` | latency, `[00:01, 00:02)` | correct: p99 over `[00:00, 00:02)` |
-| latency, `[00:00, 00:02)` | latency, `[00:01, 00:03)` | **wrong**: `[00:01, 00:02)` is counted twice |
-| latency, `[00:00, 00:01)` | latency, `[00:02, 00:03)` | correct only for `[0,1) ∪ [2,3)`, not for the continuous `[0,3)` |
-
-`Schema.time_index` is a column position. A KLL state has no timestamp column,
-so the schema cannot tell these apart.
-
-**Example 2: population (label values).**
-
-| Input A | Input B | Merging A and B is… |
-|---|---|---|
-| `region='us'` | `region='eu'` | correct: `us ∪ eu` within each `job` |
-| `region='us'` | `tier='premium'` | **wrong**: premium US requests are in both |
-| `region='us'` | `region='us'` | **wrong**: everything is counted twice |
-
-`region` is a filter label, not an output column. The `job` field says how the
-state is grouped, not which rows contributed.
-
-**Example 3: time and population together.** Merging `us × [0,1)` with
-`eu × [1,2)` covers exactly those two blocks. Recording one time range and one
-label set would give `{us,eu} × [0,2)`, which claims data that was never read.
-
-**Example 4: reuse.** For `p99(latency) WHERE region='us' AND ts IN [10:00, 10:05)
-GROUP BY job`, a stored state with a matching schema could hold the right data,
-EU data, or only 10:00–10:03. The schema shows that the state *type* fits, not
-that the *contents* fit.
-
-Schema equality is necessary but not sufficient. Without this metadata, the
-planner must either refuse every composition or accept silent double counting
-and missing data.
-
-### Requirements
-
-1. Represent time and population **jointly**, per block, never as independent
-   bounds.
-2. Accept a merge only when the inputs are **provably disjoint**, and fail
-   closed otherwise. Merging does not imply that a summary family can remove
-   duplicates.
-3. Leave `Schema` and its equality unchanged.
-4. Duplicate nothing the operator already records.
-5. Support sources without a time column (plain tables).
-
-## Design
-
-### Coverage is a node property, beside the schema
-
-```text
-OperatorNode
-├── schema: Schema                    what each output row looks like   (operator sharing §2.1)
-├── guarantee, timing                 accuracy and execution phase      (§2.2, §2.3)
-└── coverage: Option<SummaryCoverage> which observations the state holds
-```
-
-Coverage is not part of `Schema`. `SummaryMerge` requires equal input schemas,
-and the inputs of every useful merge (`[0,1)` + `[1,2)`) have different coverage.
-It is also not an operator parameter: a merge *derives* it from its inputs, like
-the schema.
-
-### What coverage records
-
-A `SummaryCoverage` names one observation `source`, using the same `Source` as
-`Scan`: a table or a time series. It holds a **union of regions**. Each region
-pairs:
-
-- `time_ms`: half-open bounds on the source's time column, or `None` for no
-  time restriction;
-- `population`: a conjunction of non-null `label = value` predicates, where
-  empty means all observations.
-
-Every observation in a region contributes once to the state. `regions = []`
-means known empty coverage.
-
-Coverage records only what no other node field records (requirement 4). What
-each observation contributes and how states are grouped are already
-`SummaryAgg.input` and `SummaryAgg.reduction`. `SummaryMerge` compares those on
-its producers directly.
-
-### Composition is a provably disjoint union
-
-`merge_disjoint` accepts inputs with the same source whose regions are pairwise
-disjoint. Two regions are disjoint when their time ranges do not intersect, or
-when they assign different values to the same label. Different labels prove
-nothing, and a region with no time bounds overlaps any region it is not
-population-disjoint from. The union keeps gaps and the time/population pairing.
-Adjacent intervals coalesce only when their populations are identical.
-
-| Case | Result |
-|---|---|
-| `[0,1)` + `[1,2)`, same population | one region `[0,2)` |
-| `[0,1)` + `[2,3)` | two regions (gap kept) |
-| `[0,2)` + `[1,3)` | rejected: possible overlap |
-| `region=us` + `region=eu`, same time | two regions |
-| `region=us` + `region=us`, or + `tier=premium` | rejected: possible overlap |
-| `us×[0,1)` + `eu×[1,2)` | two regions, never `{us,eu}×[0,2)` |
-| different source | rejected |
-
-Equality conjunctions are a deliberately narrow proof vocabulary. A richer
-predicate needs an explicit disjointness rule before it can be declared.
-
-### Lifecycle
-
-- **Required on summary nodes.** `SummaryAgg` and `SummaryMerge` cannot pass
-  structural validation without coverage. Other nodes leave it `None`. The
-  field is an `Option` only because all operators share `OperatorNode`.
-- **Declared at build.** The composition rule or catalog that builds a
-  `SummaryAgg` declares its coverage.
-- **Derived at merge.** `SummaryMerge` computes the disjoint union of its
-  inputs, and validation rejects a retained value that differs.
-- **Cleared on rewrite.** Rewriting a node's inputs clears its coverage, like
-  other assessed metadata. The rewriter must declare it again.
-- **Preserved downstream.** Logical export keeps coverage, and CSE shares two
-  nodes only if their coverage is equal.
-
-### Trust boundary
-
-Declarations are trusted. Population is not yet checked against
-`SummaryAgg.filter`, `Filter` nodes or `Scan.predicates`, so a wrong declaration
-passes:
-
-```text
-A = SummaryAgg(filter: region='us'), declared {region: eu} × [0,1)   ← wrong
-B = SummaryAgg(filter: region='us'), declared {region: us} × [0,1)
-merge_disjoint(A, B) is accepted, and every US observation is counted twice.
-```
-
-[#570](https://github.com/ProjectASAP/ASAPPlanner/issues/570) adds the check: the
-declared population must equal the `column = literal` predicates between the
-`SummaryAgg` and its `Scan`. Time bounds stay trusted, because `TimeRange` is
-relative to the evaluation time.
-
-### Alternatives considered
-
-| Alternative | Why not |
-|---|---|
-| Put coverage in `Schema` | Schema equality gates merges; merge inputs always differ in coverage. |
-| One time range plus one label set | Invents the missing blocks (Example 3). |
-| Copy `input` and `reduction` into coverage | Duplicates `SummaryAgg` and needs a consistency check; producers already carry them. |
-| Arbitrary predicates per region | No general disjointness proof; overlap would be silently accepted. |
-| Free-form string `source` | Two spellings of one table compare unequal; `Scan` already has `Source`. |
-| Snapshot `revision` field | Deployment concern; the planner does not own catalog versions. |
-
-## Key code interfaces
-
-```rust
-// crates/types/src/ir/summary_coverage.rs
-pub struct SummaryCoverage {
-    pub source: Source,               // same type as Scan.source
-    pub regions: Vec<CoverageRegion>, // union; never a product of independent bounds
-}
-pub struct CoverageRegion {
-    pub time_ms: Option<Range<i64>>,          // half-open; None = no time restriction
-    pub population: BTreeMap<String, String>, // label = value AND …; empty = all
-}
-impl SummaryCoverage {
-    pub fn validate(&self) -> Result<(), CoverageError>;
-    pub fn merge_disjoint(inputs: &[Self]) -> Result<Self, CoverageError>;
-}
-pub enum CoverageError {
-    InvalidInterval, InvalidPopulation, SourceMismatch, PossibleOverlap, EmptyMerge,
-    NotState, Missing,                    // node checks
-    UnknownInput, MergeOutputMismatch,    // SummaryMerge (#560)
-}
-
-// crates/types/src/ir/node.rs
-pub struct OperatorNode {
-    // operator, result_kind, schema, guarantee, timing, …
-    pub coverage: Option<SummaryCoverage>,
-}
-impl OperatorNode {
-    pub fn with_coverage(self, c: SummaryCoverage) -> Result<Self, SchemaDerivationError>;
-    pub fn requires_coverage(&self) -> bool;  // SummaryAgg, SummaryMerge
-    pub fn summary_update(&self) -> Option<(&SummaryUpdate, &Reduction)>; // #560
-}
-// SchemaDerivationError::Coverage(CoverageError) reports every failure above.
-```
-
-`OperatorNode::validate_structure` enforces the lifecycle rules. The documented
-examples are built as real `Scan → SummaryAgg → SummaryMerge` plans in
-`crates/types/tests/summary_coverage_examples.rs`.
-
-## Not covered
-
-- **Query containment:** checking that coverage contains a requested window or
-  population (Example 4). That is a later Stage 1 check that uses this data.
-- **Population check:** comparing declared population with filters
-  ([#570](https://github.com/ProjectASAP/ASAPPlanner/issues/570)).
-- **Richer predicates:** predicates beyond non-null equality conjunctions, and
-  idempotent set-union families.
-- **Runtime concerns:** merge kernels, accuracy, storage and execution timing.
diff --git a/docs/design_docs/proposals/univmon-frequency-summary.md b/docs/design_docs/proposals/univmon-frequency-summary.md
index 75cfd080b..a2d9f96c1 100644
--- a/docs/design_docs/proposals/univmon-frequency-summary.md
+++ b/docs/design_docs/proposals/univmon-frequency-summary.md
@@ -35,7 +35,8 @@ cardinality alternatives, and exact count remains the cheaper first count
 candidate.
 
 All four readouts have the same unit-weight update, input sub-DAG, grouping,
-window, parameter identity and state schema. Existing post-ASAP structural
+window, parameter identity and state schema
+([ASAP primitive schema](asap-primitive-schema.md)). Existing post-ASAP structural
 sharing can therefore intern their state producer while preserving distinct
 readout nodes. Sharing is only legal within the same execution/data scope.
 Precompute placement, SummaryCatalog installation, retention, and runtime
diff --git a/docs/develop_docs/asap-aware-mapping-contracts.md b/docs/develop_docs/asap-aware-mapping-contracts.md
index 447cb3823..011758143 100644
--- a/docs/develop_docs/asap-aware-mapping-contracts.md
+++ b/docs/develop_docs/asap-aware-mapping-contracts.md
@@ -325,24 +325,12 @@ backend inspection. Automatic selection skips those unproven ratios. Use
 
 ### Family, category, algorithm, and parameters
 
-Sketches separate their query category from the concrete algorithm and its parameters:
+A summary's identity has four levels: family (`FieldDataType` variant), sketch
+category (`SketchCategory`), algorithm (`SketchAlgorithm`), and the validated
+committed choice (`SketchKind`). The levels and their validation are specified in
+[Schema and physical data for ASAP primitives](../design_docs/proposals/asap-primitive-schema.md#22-consideration-2-a-field-can-have-an-asap-primitive-type).
 
-| Level | Type | Example |
-| --- | --- | --- |
-| **family** | `SummaryFamilyType` | `Sketch`, `Sample`, `Wavelet`, `StatModel`, `ExactAggregate` |
-| **category** | `SketchCategory` | `Quantile`, `Cardinality`, `Frequency`, `TopK` |
-| **algorithm** | `SketchAlgorithm` | `Kll` / `DDSketch` (both quantile); `Hll` (HyperLogLog) / `Theta` / `Kmv` (K-Minimum Values), all cardinality |
-| **committed choice** | `SketchKind` | one validated category + algorithm + parameter combination |
-
-A `SketchKind` is a validated committed choice. Its public constructor,
-`SketchKind::new(algorithm, params)`, verifies that the parameter variant belongs
-to the selected algorithm and classifies the pair into its category. The public
-`.category()`, `.algorithm()`, and `.params()` accessors expose the committed
-values without permitting an invalid combination.
-
-Where this matters in practice: `CostModel::rank_candidates`, `CostModel::size_params`, and `SketchAlgorithmStrategy::replacements` operate at the **algorithm** level. `summary_candidates(intent)` returns a list of `SketchAlgorithm`s (`[Kll, DDSketch]` for a `Quantile` intent), never a bare `SketchKind` with nothing chosen underneath it. `SketchKind` appears after an algorithm has been selected and sized—on `Realization::Sketch(SketchKind)` and `SummaryFamilyType::Sketch(SketchKind)`.
-
-`Sample`, `Wavelet`, and `StatModel` each use a flat `(Kind, Params)` pair. `Sketch` needs the additional algorithm level because multiple algorithms can serve the same purpose—for example, KLL and DDSketch both answer quantile queries.
+Where this matters in practice: `CostModel::rank_candidates`, `CostModel::size_params`, and `SketchAlgorithmStrategy::replacements` operate at the **algorithm** level. `summary_candidates(intent)` returns a list of `SketchAlgorithm`s (`[Kll, DDSketch]` for a `Quantile` intent), never a bare `SketchKind` with nothing chosen underneath it. `SketchKind` appears after an algorithm has been selected and sized—on `Realization::Sketch(SketchKind)` and `FieldDataType::Sketch(SketchKind, GroupingStrategy)`.
 
 ---
 
@@ -378,7 +366,7 @@ The crate provides no default `Matcher` implementation because the answer depend
 
 Concretely, `explanation.rs` reports three candidate kinds from each `TargetSubDAGCandidates`:
 
-- `ExplanationKind::SketchApproximation` — the set contains a `Replacement::Summary` that realizes `SummaryFamilyType::Sketch(..)`, not just an exact/pass-through candidate.
+- `ExplanationKind::SketchApproximation` — the set contains a `Replacement::Summary` that realizes `FieldDataType::Sketch(..)`, not just an exact/pass-through candidate.
 - `ExplanationKind::CommonSubexpressionReuse` — `consumer_count >= 2` and the set contains `SharedSubDAGStrategy`'s "build once and share" candidate (the `Replacement::Rewrite` whose `Rc` is the set's `target`).
 
 - `ExplanationKind::ExactComposition` — the candidate set contains an exact operation
diff --git a/docs/develop_docs/pre-asap-ir.md b/docs/develop_docs/pre-asap-ir.md
index abf5dc50b..2492e28d7 100644
--- a/docs/develop_docs/pre-asap-ir.md
+++ b/docs/develop_docs/pre-asap-ir.md
@@ -17,26 +17,10 @@ The pre-ASAP IR is defined using the `QueryExpr` enum. We discuss some of import
 
 ## Fields and column references
 
-`Schema` owns `Field` metadata: name, type, nullability, and an optional table
-qualifier. A `Field` contains no runtime values. The former schema `Column`
-struct served this same metadata role; it was renamed to `Field`, not retained
-as a second data container.
-
-`ColumnRef` is an unresolved logical reference (`Named`, `Qualified`,
-`SampleValue`, or `Wildcard`). Resolution binds a reference to `ColumnId`, a
-`usize` position within a particular schema. `QueryExpr::Column(ColumnId)`
-reads that column; the same position indexes `Schema::fields` for type checking
-and a runtime row for its value. Group keys, unique keys, and `time_index` also
-use these column positions. They are not stable identities across projections
-or joins, so the positional reference remains `ColumnId`, not `FieldId`.
-
-The native runtime names shared ownership `SchemaRef = Arc<Schema>` and stores
-`Batch { schema: SchemaRef, rows: Vec<Vec<Value>> }`. `Schema` is the same metadata
-model during planning and execution; the `Ref` suffix only distinguishes ownership.
-It has no physical `Column`/array container. A column reference expresses what
-to read independently of whether an executor stores its data as rows or arrays.
-For example, resolving `t.bytes` to `ColumnId = 1` obtains its type from
-`schema.fields[1]`; native execution reads `row[1]`.
+`Schema` holds `Field` metadata (name, type, nullability, qualifier) and no
+values; an unresolved `ColumnRef` resolves to a positional `ColumnId` within one
+schema. The design, including how the same position selects a runtime value, is
+in [Schema and physical data for ASAP primitives](../design_docs/proposals/asap-primitive-schema.md#21-consideration-1-the-schema-is-the-edge-between-two-nodes).
 
 ## Node index
 

From cb055c6377946feee01e1af29a2b58530ef99c8d Mon Sep 17 00:00:00 2001
From: Zeying Zhu <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 15:49:55 -0400
Subject: [PATCH 11/48] Update asap-primitive-schema.md

---
 .../proposals/asap-primitive-schema.md        | 29 +------------------
 1 file changed, 1 insertion(+), 28 deletions(-)

diff --git a/docs/design_docs/proposals/asap-primitive-schema.md b/docs/design_docs/proposals/asap-primitive-schema.md
index ca55ae469..e8cff6444 100644
--- a/docs/design_docs/proposals/asap-primitive-schema.md
+++ b/docs/design_docs/proposals/asap-primitive-schema.md
@@ -1,20 +1,6 @@
 # Schema and Physical Data for ASAP Primitives
 
-> Status: the edge schema and `FieldDataType` are implemented (operator sharing,
-> #511). `SummaryCoverage` is implemented in `ir::summary_coverage` (#567).
-> `SummaryMerge` coverage derivation lands in #560, and logical export/CSE of
-> coverage in #537. Checking declared population against filters is open
-> ([#570](https://github.com/ProjectASAP/ASAPPlanner/issues/570)).
-> Audience: planner designers and architects.
-> Companions: [Operator sharing](operator-sharing.md) (unified operator node),
-> [Decoupling operators from scalar expressions](decoupling_op_and_expr.md),
-> [ASAPPlanner layering](planner-layering.md) Pass 2 (window composition),
-> [Physical planning and deployment](../physical-planning-and-deployment.md).
-
-This document is the single source of truth for how an edge of the operator DAG
-is typed, how a field carries an ASAP primitive (summary or exact-accumulator
-state), what metadata says which data that state summarizes, and how such a field
-is carried as data at runtime.
+This document is the single source of truth for the schema, and column design for ASAP Primitives. This is used in the logical stage (LogicalASAPDAG), and physical stage (PhysicalASAPDAG). 
 
 ## 1. Goal and problem
 
@@ -451,16 +437,3 @@ pub trait AggregateCore {
 Coverage composition is tested in `crates/types/tests/summary_coverage.rs`. The
 documented examples are built as real `Scan → SummaryAgg → SummaryMerge` plans in
 `crates/types/tests/summary_coverage_examples.rs` (#560).
-
-## 6. Not covered
-
-- **Query containment:** checking that coverage contains a requested window or
-  population (Example 4). That is a later Stage 1 check that uses this data.
-- **Population check:** comparing declared population with filters
-  ([#570](https://github.com/ProjectASAP/ASAPPlanner/issues/570)).
-- **Richer predicates:** predicates beyond non-null equality conjunctions, and
-  idempotent set-union families.
-- **Runtime concerns:** state encoding, storage, retention, scheduling, kernel
-  accuracy and performance.
-- **Persisted semantic identity:** the stored-definition format and any tenant or
-  dataset binding belong to the deployment.

From 4a4627fee506d16165bb32dd906102c17a25e04f Mon Sep 17 00:00:00 2001
From: Zeying Zhu <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 16:01:33 -0400
Subject: [PATCH 12/48] Update asap-primitive-schema.md

---
 .../proposals/asap-primitive-schema.md        | 32 ++++++++++++-------
 1 file changed, 21 insertions(+), 11 deletions(-)

diff --git a/docs/design_docs/proposals/asap-primitive-schema.md b/docs/design_docs/proposals/asap-primitive-schema.md
index e8cff6444..2825a4e36 100644
--- a/docs/design_docs/proposals/asap-primitive-schema.md
+++ b/docs/design_docs/proposals/asap-primitive-schema.md
@@ -4,17 +4,27 @@ This document is the single source of truth for the schema, and column design fo
 
 ## 1. Goal and problem
 
-ASAP primitives are compact summaries over raw data: a KLL sketch over latency
-samples, an exact `Sum` accumulator, a Count-Min sketch over request keys. Once a
-plan contains them, three things must be explicit:
-
-1. **What flows on an edge.** Every operator, before and after ASAP optimization,
-   needs one typed output contract, so a projection above a summary and one below
-   it are the same operator.
-2. **That a field can be a primitive.** A state column is not a number. It has a
-   family, an algorithm and parameters, and it can only be read through a
-   readout.
-3. **What a primitive summarizes.** Two states of the same type can hold different
+Unlike existing Database engines, which work on raw data or explicitly defined materialized tables with schema and column names provided by the users, ASAPPlanner is designed for querying and execution over the mix of raw data and ASAP Primitives. ASAP primitives are usually compact summaries over raw data. Therefore, 
+
+Once an [ASAP Operator](https://github.com/ProjectASAP/ASAPPlanner/blob/main/docs/design_docs/proposals/operator-sharing.md) is a summary state operator, the ASAP Operator node in LogicalASAPDAG and PhysicalASAPDAG should represent the following information: 
+
+
+## Schema Design
+
+Schema represents the metadata of information flow along an edge between two nodes in a logical or physical DAG. The schema field is associated with a node in the DAG. 
+
+Schema definition here is shared between LogicalDAG, LogicalASAPDAG, and PhysicalASAPDAG. The schema contain fields, and each field is mapping to a column in the physical data representation. 
+Each field should contain the following information. 
+1. **The data type of a column.** A state column can be a raw data type (e.g., numerical number, string). It can also be a [summary type](), e.g., the summary family is sketch, and the sketch type is quantile KLL sketch algorithm, and KLL sketch has K  as parameter.   It has a
+   family, an algorithm and parameters.
+2. ** **. 
+
+
+
+## Node design 
+
+Each node in the DAG should contain the information of the instance this nodes is computing, in addition to schema or metadata. 
+4. **What a ASAP primitive summarizes.** Two states of the same type can hold different
    data. The planner must know which observations each holds before it combines or
    reuses them.
 

From 0febdae585ff87f896624697c03248b5503cdd00 Mon Sep 17 00:00:00 2001
From: Zeying Zhu <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 16:27:36 -0400
Subject: [PATCH 13/48] Update asap-primitive-schema.md

---
 .../proposals/asap-primitive-schema.md        | 31 +++++++++++++++++--
 1 file changed, 28 insertions(+), 3 deletions(-)

diff --git a/docs/design_docs/proposals/asap-primitive-schema.md b/docs/design_docs/proposals/asap-primitive-schema.md
index 2825a4e36..626affe57 100644
--- a/docs/design_docs/proposals/asap-primitive-schema.md
+++ b/docs/design_docs/proposals/asap-primitive-schema.md
@@ -2,11 +2,36 @@
 
 This document is the single source of truth for the schema, and column design for ASAP Primitives. This is used in the logical stage (LogicalASAPDAG), and physical stage (PhysicalASAPDAG). 
 
-## 1. Goal and problem
+## 1. Goal, problem, and requirements
 
-Unlike existing Database engines, which work on raw data or explicitly defined materialized tables with schema and column names provided by the users, ASAPPlanner is designed for querying and execution over the mix of raw data and ASAP Primitives. ASAP primitives are usually compact summaries over raw data. Therefore, 
+Unlike existing Database engines, which work on raw data or explicitly defined materialized tables with schema and column names provided by the users, ASAPPlanner is designed for querying and execution over the mix of raw data and ASAP Primitives. ASAP primitives are usually compact summaries over raw data. Therefore, it introduces new requirement when we design the schema and node definitions for LogicalASAPDAG and PhysicalASAPDAG.
 
-Once an [ASAP Operator](https://github.com/ProjectASAP/ASAPPlanner/blob/main/docs/design_docs/proposals/operator-sharing.md) is a summary state operator, the ASAP Operator node in LogicalASAPDAG and PhysicalASAPDAG should represent the following information: 
+Assuming we have the Logical DAG defined for a canonicalized representation for a batch of queries. [TODO: add links for this here. ]
+The LogicalASAPDAG will share/reuse the NonASAP operator and ScalarExpr nodes in LogicalDAG [TODO: link PR 511's doc here], but replacing some operators in LogicalDAG with the operators operated with ASAP Primitives: SummaryCreation?, SummaryUpdate, SummaryMerge, SummaryDelete, SummarySubtraction [TODO: check what is the complete list or discuss with others about the list]. 
+Each of the Summary operators also require the ASAP primitive information above to inter-operate correctly, preserving semantic correctness. 
+
+Basically, the following information should be represented to preserve the equivalent query semantics when we introduce ASAP Primitives to logical query representation, and following physical one. 
+
+- What type of the ASAP Primitive is
+- What is the ASAP Primitive parameters
+- What data sources a ASAP primitive summarizes
+- What query intent the summarized ASAP Primitive can support, e.g., statistical aggregation intents, time window aggregation intents
+
+
+
+And these information will be combined with relational or time series query operator information, such as group by/reduction, filtering, projection, join, time series selection, together. 
+
+Therefore, these requirements drive the following schema and metadata, node information, and column design. 
+
+
+
+
+
+
+
+
+
+--------don't read below-------------
 
 
 ## Schema Design

From d113b3a07c337eb2b7a9436dc363653071189e01 Mon Sep 17 00:00:00 2001
From: Zeying Zhu <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 16:40:14 -0400
Subject: [PATCH 14/48] Update asap-primitive-schema.md

---
 .../proposals/asap-primitive-schema.md        | 447 +-----------------
 1 file changed, 12 insertions(+), 435 deletions(-)

diff --git a/docs/design_docs/proposals/asap-primitive-schema.md b/docs/design_docs/proposals/asap-primitive-schema.md
index 626affe57..9f66ba70c 100644
--- a/docs/design_docs/proposals/asap-primitive-schema.md
+++ b/docs/design_docs/proposals/asap-primitive-schema.md
@@ -7,7 +7,7 @@ This document is the single source of truth for the schema, and column design fo
 Unlike existing Database engines, which work on raw data or explicitly defined materialized tables with schema and column names provided by the users, ASAPPlanner is designed for querying and execution over the mix of raw data and ASAP Primitives. ASAP primitives are usually compact summaries over raw data. Therefore, it introduces new requirement when we design the schema and node definitions for LogicalASAPDAG and PhysicalASAPDAG.
 
 Assuming we have the Logical DAG defined for a canonicalized representation for a batch of queries. [TODO: add links for this here. ]
-The LogicalASAPDAG will share/reuse the NonASAP operator and ScalarExpr nodes in LogicalDAG [TODO: link PR 511's doc here], but replacing some operators in LogicalDAG with the operators operated with ASAP Primitives: SummaryCreation?, SummaryUpdate, SummaryMerge, SummaryDelete, SummarySubtraction [TODO: check what is the complete list or discuss with others about the list]. 
+The LogicalASAPDAG will share/reuse the NonASAP operator and ScalarExpr nodes in LogicalDAG [TODO: link PR 511's doc here], but replacing some operators in LogicalDAG with the operators operated with ASAP Primitives: SummaryCreation?, SummaryUpdate, SummaryMerge, SummaryDelete, SummarySubtraction, SummaryEstimate [TODO: check what is the complete list or discuss with others about the list]. 
 Each of the Summary operators also require the ASAP primitive information above to inter-operate correctly, preserving semantic correctness. 
 
 Basically, the following information should be represented to preserve the equivalent query semantics when we introduce ASAP Primitives to logical query representation, and following physical one. 
@@ -25,450 +25,27 @@ Therefore, these requirements drive the following schema and metadata, node info
 
 
 
+## 2. Existing database terminology for schema, table, column, and physical data layout
 
 
-
-
-
-
---------don't read below-------------
-
-
-## Schema Design
-
-Schema represents the metadata of information flow along an edge between two nodes in a logical or physical DAG. The schema field is associated with a node in the DAG. 
+## 3. Proposed schema design 
+Schema represents the **metadata** of information flow along an **edge** between two nodes in a logical or physical DAG. The schema field is associated with the node in the DAG. The consumer of the node in the DAG takes the schema from the producer node as input. 
 
 Schema definition here is shared between LogicalDAG, LogicalASAPDAG, and PhysicalASAPDAG. The schema contain fields, and each field is mapping to a column in the physical data representation. 
-Each field should contain the following information. 
-1. **The data type of a column.** A state column can be a raw data type (e.g., numerical number, string). It can also be a [summary type](), e.g., the summary family is sketch, and the sketch type is quantile KLL sketch algorithm, and KLL sketch has K  as parameter.   It has a
-   family, an algorithm and parameters.
-2. ** **. 
-
-
-
-## Node design 
-
-Each node in the DAG should contain the information of the instance this nodes is computing, in addition to schema or metadata. 
-4. **What a ASAP primitive summarizes.** Two states of the same type can hold different
-   data. The planner must know which observations each holds before it combines or
-   reuses them.
-
-The schema alone answers the first two but not the third. Every example below
-uses two states with **equal schemas**,
-`Schema(job: Plain(Utf8), state: Sketch(KLL{k=200}))`.
-
-**Example 1: time.**
-
-| Input A | Input B | Merging A and B is… |
-|---|---|---|
-| `[00:00, 00:01)` | `[00:01, 00:02)` | correct: p99 over `[00:00, 00:02)` |
-| `[00:00, 00:02)` | `[00:01, 00:03)` | **wrong**: `[00:01, 00:02)` is counted twice |
-| `[00:00, 00:01)` | `[00:02, 00:03)` | correct only for `[0,1) ∪ [2,3)`, not for `[0,3)` |
-
-`Schema.time_index` is a column position. A KLL state has no timestamp column.
-
-**Example 2: population.**
-
-| Input A | Input B | Merging A and B is… |
-|---|---|---|
-| `region='us'` | `region='eu'` | correct: `us ∪ eu` within each `job` |
-| `region='us'` | `tier='premium'` | **wrong**: premium US requests are in both |
-| `region='us'` | `region='us'` | **wrong**: everything is counted twice |
-
-`region` is a filter label, not an output column. `job` says how the state is
-grouped, not which rows contributed.
-
-**Example 3: time and population together.** Merging `us × [0,1)` with
-`eu × [1,2)` covers exactly those two blocks. One time range plus one label set
-would give `{us,eu} × [0,2)`, which claims data that was never read.
-
-**Example 4: reuse.** For `p99(latency) WHERE region='us' AND ts IN [10:00, 10:05)
-GROUP BY job`, a stored state with a matching schema could hold the right data,
-EU data, or only 10:00–10:03. The schema shows that the state *type* fits, not
-that the *contents* fit.
-
-These compositions arise in Pass 2 window composition
-([planner layering](planner-layering.md)), in `SummaryMerge` of partial states,
-and in sub-DAG sharing and pane reuse. Schema equality is necessary but not
-sufficient. Without more metadata, the planner must refuse every composition or
-accept silent double counting and missing data.
-
-## 2. Design considerations
-
-```text
-OperatorNode
-├── operator: Operator                 the operation; SummaryAgg holds input, reduction, filter   (C3)
-├── result_kind: OperatorResultKind    Relation | InstantVector | RangeVector | State             (C2)
-├── schema: Schema                     the outgoing edge: fields, time, keys, closedness           (C1)
-│   └── fields[i].dtype: FieldDataType Plain(DataType) or an ASAP primitive state family          (C2)
-├── guarantee, timing                  accuracy and execution phase (operator sharing §2.2, §2.3)
-└── coverage: Option<SummaryCoverage>  which observations the state holds                          (C3)
-```
-
-### 2.1 Consideration 1: the schema is the edge between two nodes
-
-A node's `schema` types its output edge. The DAG is type-checked: the schema is
-derived from the operator and its inputs (`Operator::output_schema`), retained on
-the node, and verifiable without surrounding context. One `Schema` type serves
-every operator before and after ASAP optimization. It replaced the separate
-pre-ASAP `Schema`/`Column` and post-ASAP `SummarySchema`/`SummaryField` (old
-plans still deserialize).
-
-| Schema member | Meaning and requirement |
-|---|---|
-| `fields: Vec<Field>` | Ordered fields. `Field = name + dtype: FieldDataType + nullable + table`. `table` preserves SQL qualified resolution through joins. A `Field` holds metadata, never data. |
-| `time_index` | Position of the `Plain(Timestamp)` time column, if any. It does not distinguish an instant vector from a range vector. |
-| `unique_keys` | Proven column combinations identifying rows; empty asserts no known key. Rewrites that change identity recompute them. |
-| `closed` | Whether `fields` is complete. A schemaless PromQL leaf is open; the first `Aggregate`/`Project` that fully determines its output closes it. Open schemas skip closed-world validation. |
-
-**`ColumnId` versus `ColumnRef`.** These are different roles, not competing
-representations:
-
-| Name | Role | Holds runtime values? |
-|---|---|---|
-| `Schema`, `Field` | Edge metadata | No |
-| `ColumnRef` | Unresolved logical reference: `Named`, `Qualified`, `SampleValue`, `Wildcard` | No |
-| `ColumnId = usize` | Resolved position in one particular input/output schema | No |
-| Runtime batch | Values conforming to a schema (§3) | Yes |
-
-Resolution binds a `ColumnRef` to a `ColumnId` before operator nodes are built.
-The same position indexes `schema.fields` for type checking and selects the
-value at execution: resolving `t.bytes` to `1` gives its type from
-`schema.fields[1]`, and `ScalarExpr::Column(1)` reads `row[1]` in the native
-executor (or array `1` in a columnar one). `time_index`, `unique_keys` and group
-keys use the same positions. A `ColumnId` is local to its schema, not a stable
-identity across projections or joins, so there is no `FieldId`. ASAP payloads
-that refer to input data before resolution (`SummaryUpdate`, `SketchStatistic::PointCount`)
-keep `ColumnRef`.
-
-**Derivation and validation.**
-
-- `Scan.schema` declares source columns and `Values.schema` the constructed rows;
-  every other `OperatorNode.schema` is derived. Planning may override only output
-  names and qualifiers (`OperatorNode::with_schema`); all structural metadata must
-  equal derivation.
-- `ScalarExpr::scalar_type(input)` types an expression against its column scope
-  (child schema, both join inputs, or aggregate outputs for `HAVING`).
-- `OperatorNode::validate_structure()` walks the reachable DAG: input contracts,
-  scalar typing, retained-versus-derived schema and result kind, and coverage
-  (§2.3). It permits `timing = None`.
-- `OperatorNode::validate_execution_timing()` adds assigned timing and phase
-  dependencies, for executable candidates. Neither method proves accuracy;
-  guarantees stay with planner assessment (#509).
-
-### 2.2 Consideration 2: a field can have an ASAP primitive type
-
-`FieldDataType` types every field. `Plain` is an ordinary readable value; every
-other variant is the state of one ASAP primitive family and carries the identity
-and parameters required by that family:
-
-```rust
-enum FieldDataType {
-    Plain(DataType),                          // readable value
-    ExactAggregate(ExactKind, ExactParams),   // Sum, Count, Min, Max, Increase, Rate, IRate
-    Sketch(SketchKind, GroupingStrategy),     // KLL, DDSketch, HLL, CMS, CountSketch, UnivMon, …
-    Sample(SamplingKind, SamplingParams),
-    Wavelet(WaveletKind, WaveletParams),
-    StatModel(StatModelKind, StatModelParams),
-}
-```
-
-**Identity levels.** A sketch has one more level than the other families, because
-several algorithms serve one query category (KLL and DDSketch both answer
-quantiles):
-
-| Level | Type | Example |
-|---|---|---|
-| family | `FieldDataType` variant | `Sketch`, `Sample`, `Wavelet`, `StatModel`, `ExactAggregate` |
-| category | `SketchCategory` | `Quantile`, `Cardinality`, `Frequency`, `TopK`, `Universal` |
-| algorithm | `SketchAlgorithm` | `Kll`, `DDSketch`; `Hll`, `Theta`, `Kmv`; `Cms`, `CountSketch`, … |
-| committed choice | `SketchKind` | one validated category + algorithm + `SketchParams` |
-
-`SketchKind::new(algorithm, params)` is the only constructor: it rejects a
-parameter variant from another algorithm and classifies the pair into its
-category; `.category()`, `.algorithm()` and `.params()` expose the committed
-values. `Sample`, `Wavelet` and `StatModel` use flat `(Kind, Params)` pairs;
-`ExactParams` is per-kind so a mismatched pair is a type error.
-`GroupingStrategy` records the physical layout across `by` subpopulations:
-`PerSubpopulationInstance` (default) or `SharedMultiSubpopulation { HydraKind,
-HydraParams }`. It is part of the type because a shared Hydra structure and
-independent instances are not merge-compatible even with the same algorithm.
-
-Because the full identity is in the type, incompatible states fail at plan
-construction: a merge over `Sketch(Kll, …)` and `Sketch(Cms, …)`, or a `Sketch`
-read as a `Sample`, is a schema error.
+Based on our requirement, each field should contain the following information.
+1. **What type of the ASAP Primitive is** A state column can be a raw data type (e.g., numerical number, string). It can also be a [summary type](TODO: add link), e.g., the summary family is sketch, and the sketch type is quantile KLL sketch algorithm, and KLL sketch has K  as parameter as the schema. (TODO: confirm the terminology with corresponding code/doc)  It has a family, an algorithm and parameters. 
+2. **What query intent the summarized ASAP Primitive can support, e.g., statistical aggregation intents, time window aggregation intents** This information is being mapped based on the primitive type. 
 
-**Rules for state fields.**
 
-- **Top-level only.** Nested `List`/`Struct` elements are `Field<DataType>`, not
-  `Field<FieldDataType>`, so a nested field cannot carry state.
-- **Produced only by state operators.** `SummaryAgg.family` is never `Plain`; its
-  input must be values, not state. Its output is the grouping columns plus one
-  non-nullable `state` field of that family.
-- **State is not a value.** `scalar_type` rejects a state column ("read it out
-  first"). `Filter`, `BinaryOp`, `Join`, `SetOp`, `Concat`, `Aggregate` and
-  `Dedup` reject `State` inputs; a bare-column `Project` may pass a state field
-  through unchanged (its result stays `State`).
-  Copying a state column does not make it readable.
-- **Result kind.** `OperatorResultKind::State` marks an output carrying
-  unfinalized state; its schema may also contain plain grouping keys. Matching
-  columns never make result kinds interchangeable.
+## 4. Proposed Node field design 
 
-**Readout / finalization boundary.** State becomes plain values only through an
-explicit ASAP readout, which takes its input's relation/vector kind:
-
-| Readout | Input | Output field |
-|---|---|---|
-| `SummaryEstimate { query: SketchStatistic }` | exactly one `Sketch` state field whose category supports `query` | `Plain`: `quantile`/`frequency_l2`/`frequency_entropy` `Float64`, `cardinality`/`count` `Int64`, `topk` `Utf8` |
-| `FinalizeExactAccumulator` | `ExactAggregate` state | the finalized aggregate value |
-| `EvaluatePopulation` | `MaintainPopulation` state | the requested population statistic |
-
-For example, a KLL build outputs `State` with a `Sketch(KLL{k=200})` column; its
-p99 readout outputs `Plain(Float64)`. A numeric predicate can use the readout but
-not the state.
-
-### 2.3 Consideration 3: the metadata preserves summary semantics
-
-A state is only meaningful together with what it summarizes. The information a
-summary's semantics depends on is:
-
-| Concern | Required semantic information |
-|---|---|
-| Input computation | Source identities and schemas, filters, joins/transforms and their order, or the canonical input sub-DAG |
-| Values and grouping | Value expressions, item identities and weights, group keys and types, null/duplicate handling |
-| Time | Time column and interpretation, interval bounds, evaluation alignment, query range versus maintained panes |
-| Summary computation | Exact operation or sketch family, algorithm and parameters, build/merge behavior |
-| Output | State versus finalized value, output schema/type, readout parameters |
-
-KLL over `latency_seconds` and KLL over `log(latency_seconds)` differ even with
-identical source, filter, grouping and window. Weighted frequency state needs both
-item and weight expressions. Four descriptive fields (`source`, `filter`,
-`grouping`, `window`) cannot replace the computation DAG.
-
-The design splits this information by what it varies with, and records each fact
-once:
-
-| Where | What it records | Why there |
-|---|---|---|
-| Field type (`FieldDataType`) | Family, algorithm, parameters, grouping layout | It determines merge compatibility and which readouts apply, so it gates schema equality. |
-| Producer operator (`SummaryAgg`) | `input: SummaryUpdate` (item, weight, `weight_domain` proof), `reduction` (group keys or per-entity), `filter`, `grouping`; the child sub-DAG is the input computation | These are the operation's parameters; copying them elsewhere would need a consistency check. |
-| Node (`OperatorNode.coverage`) | Which observations: a source and a union of time × population regions | It differs between states that must still merge, and it cannot be derived from `SummaryAgg` alone. |
-| Result kind and readout node | State versus value, readout statistic | Derived from the operator (§2.2). |
-
-Time alignment, panes and maintenance lifecycle are planning and deployment
-concerns ([planner layering](planner-layering.md),
-[physical planning](../physical-planning-and-deployment.md)).
-
-#### Coverage is beside the schema, not inside it
-
-Coverage is not part of `Schema`. `SummaryMerge` requires equal input schemas,
-and the inputs of every useful merge (`[0,1)` + `[1,2)`) have different coverage.
-Coverage also describes the whole state output, not one field. It is not an
-operator parameter either: a merge *derives* it from its inputs, like the schema.
-
-Requirements:
-
-1. Represent time and population **jointly**, per region, never as independent
-   bounds.
-2. Accept a merge only when the inputs are **provably disjoint**; fail closed.
-   Merging does not imply that a family can remove duplicates.
-3. Leave `Schema` and its equality unchanged.
-4. Duplicate nothing the operator already records.
-5. Support sources without a time column (plain tables).
-
-#### What coverage records
-
-`SummaryCoverage` names one observation `source`, using the same `Source` as
-`Scan` (a table or a time series), and holds a **union of regions**. Each
-`CoverageRegion` pairs:
-
-- `time_ms`: half-open bounds on the source's time column, or `None` for no time
-  restriction;
-- `population`: a conjunction of non-null `label = value` predicates; empty means
-  all observations.
-
-Every observation in a region contributes once to the state. `regions = []` means
-known empty coverage. What each observation contributes and how states are
-grouped stay on `SummaryAgg.input` and `SummaryAgg.reduction` (requirement 4);
-`SummaryMerge` compares those on its producers directly (#560).
-
-#### Composition is a provably disjoint union
-
-`merge_disjoint` accepts inputs with the same source whose regions are pairwise
-disjoint. Two regions are disjoint when their time ranges do not intersect, or
-when they assign different values to the same label. Different labels prove
-nothing, and a region without time bounds overlaps any region it is not
-population-disjoint from. The union keeps gaps and the time/population pairing;
-adjacent intervals coalesce only when their populations are identical.
-
-| Case | Result |
-|---|---|
-| `[0,1)` + `[1,2)`, same population | one region `[0,2)` |
-| `[0,1)` + `[2,3)` | two regions (gap kept) |
-| `[0,2)` + `[1,3)` | rejected: possible overlap |
-| `region=us` + `region=eu`, same time | two regions |
-| `region=us` + `region=us`, or + `tier=premium` | rejected: possible overlap |
-| `us×[0,1)` + `eu×[1,2)` | two regions, never `{us,eu}×[0,2)` |
-| different source | rejected |
-
-Equality conjunctions are a deliberately narrow proof vocabulary. A richer
-predicate needs an explicit disjointness rule before it can be declared.
-
-#### Lifecycle
-
-- **Required on summary nodes.** `SummaryAgg` cannot pass `validate_structure`
-  without coverage; `SummaryMerge` joins it in #560. Coverage on a non-`State`
-  node is rejected. The field is an `Option` only because all operators share
-  `OperatorNode`.
-- **Declared at build.** The composition rule or catalog that builds a
-  `SummaryAgg` declares it (`with_coverage`). No production builder declares it
-  on this branch yet.
-- **Derived at merge (#560).** `SummaryMerge` computes the disjoint union of its
-  inputs, and validation rejects a retained value that differs.
-- **Cleared on rewrite.** `map_children` rebuilds the node without coverage, like
-  `guarantee` and `timing`. The rewriter must declare it again.
-- **Preserved downstream (#537).** Logical export keeps coverage, and CSE shares
-  two nodes only if their coverage is equal.
-
-#### Trust boundary
-
-Declarations are trusted. Population is not yet checked against
-`SummaryAgg.filter`, `Filter` nodes or `Scan.predicates`, so a wrong declaration
-passes:
-
-```text
-A = SummaryAgg(filter: region='us'), declared {region: eu} × [0,1)   ← wrong
-B = SummaryAgg(filter: region='us'), declared {region: us} × [0,1)
-merge_disjoint(A, B) is accepted, and every US observation is counted twice.
-```
-
-[#570](https://github.com/ProjectASAP/ASAPPlanner/issues/570) adds the check: the
-declared population must equal the `column = literal` predicates between the
-`SummaryAgg` and its `Scan`. Time bounds stay trusted, because `TimeRange` is
-relative to the evaluation time.
-
-## 3. Physical data: how a state column is carried
-
-The runtime uses the same `Schema` as planning (`SchemaRef = Arc<Schema>`). The
-native executor (`asap-physical-operators`) stores `Batch { schema, rows:
-Vec<Vec<Value>> }`; the row/column layout is executor-specific. A state column
-holds a typed value:
+A node in the physical data will represent the data or summary instance, so a node has a field for **What data sources a ASAP primitive summarizes**.
 
+Based on the above the proposed OperatorNode interface is as below:
 ```rust
-enum Value {
-    Null, Bool(..), Int64(..), Float64(..), Utf8(..), Timestamp(..), Date(..),
-    Interval { .. }, List(..), Struct(..), Map(..),
-    Summary { family: FieldDataType, state: Arc<dyn AggregateCore> },
-}
 ```
 
-- **Typed at the boundary.** `Batch::try_new` checks each `Summary` value's
-  `family` equals the field's `FieldDataType`, and that the payload's shape
-  (algorithm and parameters, for example KLL `k` or CMS width × depth) matches it.
-  State fields must be non-nullable and of a natively supported family.
-- **Not a key.** A `Summary` value cannot be a grouping key or be ordered.
-- **Kernels.** `summary_kernels` adapt `asap_sketchlib` structures and exact
-  Planner state behind `AggregateCore`: `merge_with` (same family and shape),
-  `estimate(SketchStatistic)`, and `approx_memory_bytes` for memory reservations.
-  `create_planner_accumulator(family, input, grouping)` builds the updater a
-  `SummaryAgg` declares and rejects a family/grouping disagreement.
-- **Native coverage.** Exact Sum/Count/Min/Max/Rate/Increase, KLL, DDSketch, HLL,
-  Count-Min (stored state only), and weighted CMS/CountSketch with heaps.
-  `SharedMultiSubpopulation` grouping, `Sample`, `Wavelet` and `StatModel` have
-  no native kernel and are rejected at binding.
-- **No encoding here.** `Value::Summary` is not serialized; byte encodings belong
-  to `asap_sketchlib` and deployments.
-
-Coverage is plan metadata and is not carried in runtime values. Physical merge of
-states by group key checks family equality only; disjointness is proven at
-planning time (§2.3).
+## 5. Examples on how OperatorNode, schema, and physical data information are being used with Summary operators
 
-## 4. Alternatives considered
-
-| Alternative | Why not |
-|---|---|
-| Separate pre-ASAP and post-ASAP schema types | A projection above a summary needs a different representation from one below it; one `Schema` removes the barrier. |
-| An opaque "state" type without family identity | KLL + CMS merges, and sketch-versus-sample confusion, would only fail at runtime. |
-| State inside `List`/`Struct` fields | Nested state would escape the readout boundary and state validation. |
-| Put coverage in `Schema` | Schema equality gates merges; merge inputs always differ in coverage. |
-| One time range plus one label set | Invents the missing blocks (Example 3). |
-| Copy `input` and `reduction` into coverage | Duplicates `SummaryAgg` and needs a consistency check; producers already carry them. |
-| Arbitrary predicates per region | No general disjointness proof; overlap would be silently accepted. |
-| Free-form string `source` | Two spellings of one table compare unequal; `Scan` already has `Source`. |
-| Snapshot `revision` field | Deployment concern; the planner does not own catalog versions. |
-
-## 5. Key code interfaces
-
-```rust
-// crates/types/src/pre_asap/schema.rs
-pub type ColumnId = usize;
-pub struct Field<T = FieldDataType> { pub name: String, pub dtype: T, pub nullable: bool, pub table: Option<String> }
-pub struct Schema {
-    pub fields: Vec<Field>,
-    pub time_index: Option<ColumnId>,
-    pub unique_keys: Vec<Vec<ColumnId>>,
-    pub closed: bool,
-}
-pub enum FieldDataType { Plain(DataType), ExactAggregate(..), Sketch(SketchKind, GroupingStrategy), Sample(..), Wavelet(..), StatModel(..) }
-// DataType::List { element: Box<Field<DataType>> }, DataType::Struct { fields: Vec<Field<DataType>> }
-
-// crates/types/src/post_asap/sketch.rs
-impl SketchKind { pub fn new(algorithm: SketchAlgorithm, params: SketchParams) -> Self; }
-pub enum GroupingStrategy { PerSubpopulationInstance, SharedMultiSubpopulation { kind: HydraKind, params: HydraParams } }
-pub struct SummaryUpdate { pub item: Option<SummaryInputExpr>, pub weight: SummaryInputExpr, pub weight_domain: WeightDomain }
-
-// crates/types/src/ir/asap.rs
-pub enum ASAPOp {
-    SummaryAgg { child, family: FieldDataType, input: SummaryUpdate, reduction: Reduction,
-                 grouping: GroupingStrategy, filter: Option<Predicate> },
-    SummaryEstimate { summary_input, query: SketchStatistic },
-    FinalizeExactAccumulator { child },
-    SummaryMerge { children },            // reserved here; structure in #560
-    // MaintainPopulation, EvaluatePopulation, SummarySubtract, SummaryDelete, SummaryJoin, Extension
-}
-
-// crates/types/src/ir/summary_coverage.rs
-pub struct SummaryCoverage { pub source: Source, pub regions: Vec<CoverageRegion> }
-pub struct CoverageRegion {
-    pub time_ms: Option<Range<i64>>,          // half-open; None = no time restriction
-    pub population: BTreeMap<String, String>, // label = value AND …; empty = all
-}
-impl SummaryCoverage {
-    pub fn validate(&self) -> Result<(), CoverageError>;
-    pub fn merge_disjoint(inputs: &[Self]) -> Result<Self, CoverageError>;
-}
-pub enum CoverageError {
-    InvalidInterval, InvalidPopulation, SourceMismatch, PossibleOverlap, EmptyMerge,
-    NotState, Missing,
-    // #560: UnknownInput, MergeOutputMismatch
-}
-
-// crates/types/src/ir/node.rs
-pub enum OperatorResultKind { Relation, InstantVector, RangeVector, State }
-pub struct OperatorNode {
-    pub operator: Operator, pub result_kind: OperatorResultKind, pub schema: Schema,
-    pub guarantee: Option<ResultGuarantee>, pub timing: Option<ExecutionTiming>,
-    pub coverage: Option<SummaryCoverage>,
-}
-impl OperatorNode {
-    pub fn with_schema(operator: Operator, schema: Schema) -> Self;
-    pub fn with_coverage(self, c: SummaryCoverage) -> Result<Self, SchemaDerivationError>;
-    pub fn requires_coverage(&self) -> bool;  // SummaryAgg; SummaryMerge in #560
-    pub fn validate_structure(self: &Rc<Self>) -> Result<(), SchemaDerivationError>;
-    pub fn validate_execution_timing(self: &Rc<Self>) -> Result<(), SchemaDerivationError>;
-    // #560: pub fn summary_update(&self) -> Option<(&SummaryUpdate, &Reduction)>;
-}
-// SchemaDerivationError::Coverage(CoverageError) reports coverage failures.
-
-// crates/asap-physical-operators/src/{values.rs, summary_kernels/traits.rs}
-pub enum Value { /* plain variants */ Summary { family: FieldDataType, state: Arc<dyn AggregateCore> } }
-pub trait AggregateCore {
-    fn merge_with(&self, other: &dyn AggregateCore) -> Result<Box<dyn AggregateCore>, KernelError>;
-    fn estimate(&self, query: &SketchStatistic) -> Result<f64, KernelError>;
-    fn approx_memory_bytes(&self) -> usize;
-}
-```
+Given that these information requirements are introduced by summary operators to work correctly semantically, we show the examples of how the defined OperatorNode, schema, and physical data information work with each kind of summary operators. 
 
-Coverage composition is tested in `crates/types/tests/summary_coverage.rs`. The
-documented examples are built as real `Scan → SummaryAgg → SummaryMerge` plans in
-`crates/types/tests/summary_coverage_examples.rs` (#560).

From 87b46359fd0311f621761db3ffb6e70f71d616b6 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 20:45:44 +0000
Subject: [PATCH 15/48] docs: add code interfaces and per-operator examples to
 the ASAP primitive schema design

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 .../proposals/asap-primitive-schema.md        | 389 +++++++++++++++++-
 1 file changed, 385 insertions(+), 4 deletions(-)

diff --git a/docs/design_docs/proposals/asap-primitive-schema.md b/docs/design_docs/proposals/asap-primitive-schema.md
index 9f66ba70c..2302e3040 100644
--- a/docs/design_docs/proposals/asap-primitive-schema.md
+++ b/docs/design_docs/proposals/asap-primitive-schema.md
@@ -7,7 +7,7 @@ This document is the single source of truth for the schema, and column design fo
 Unlike existing Database engines, which work on raw data or explicitly defined materialized tables with schema and column names provided by the users, ASAPPlanner is designed for querying and execution over the mix of raw data and ASAP Primitives. ASAP primitives are usually compact summaries over raw data. Therefore, it introduces new requirement when we design the schema and node definitions for LogicalASAPDAG and PhysicalASAPDAG.
 
 Assuming we have the Logical DAG defined for a canonicalized representation for a batch of queries. [TODO: add links for this here. ]
-The LogicalASAPDAG will share/reuse the NonASAP operator and ScalarExpr nodes in LogicalDAG [TODO: link PR 511's doc here], but replacing some operators in LogicalDAG with the operators operated with ASAP Primitives: SummaryCreation?, SummaryUpdate, SummaryMerge, SummaryDelete, SummarySubtraction, SummaryEstimate [TODO: check what is the complete list or discuss with others about the list]. 
+The LogicalASAPDAG will share/reuse the NonASAP operator and ScalarExpr nodes in LogicalDAG [TODO: link PR 511's doc here], but replacing some operators in LogicalDAG with the operators operated with ASAP Primitives. The complete list is `ASAPOp` in `crates/types/src/ir/asap.rs`: `SummaryAgg` (creates and updates state; there is no separate SummaryCreation or SummaryUpdate operator, and `SummaryUpdate` is `SummaryAgg`'s update-expression parameter), `SummaryEstimate`, `FinalizeExactAccumulator`, `MaintainPopulation` and `EvaluatePopulation` (implemented); `SummaryMerge` (reserved here, enabled by #560); and `SummarySubtract`, `SummaryDelete`, `SummaryJoin` and `Extension` (reserved). See §5. 
 Each of the Summary operators also require the ASAP primitive information above to inter-operate correctly, preserving semantic correctness. 
 
 Basically, the following information should be represented to preserve the equivalent query semantics when we introduce ASAP Primitives to logical query representation, and following physical one. 
@@ -33,19 +33,400 @@ Schema represents the **metadata** of information flow along an **edge** between
 
 Schema definition here is shared between LogicalDAG, LogicalASAPDAG, and PhysicalASAPDAG. The schema contain fields, and each field is mapping to a column in the physical data representation. 
 Based on our requirement, each field should contain the following information.
-1. **What type of the ASAP Primitive is** A state column can be a raw data type (e.g., numerical number, string). It can also be a [summary type](TODO: add link), e.g., the summary family is sketch, and the sketch type is quantile KLL sketch algorithm, and KLL sketch has K  as parameter as the schema. (TODO: confirm the terminology with corresponding code/doc)  It has a family, an algorithm and parameters. 
-2. **What query intent the summarized ASAP Primitive can support, e.g., statistical aggregation intents, time window aggregation intents** This information is being mapped based on the primitive type. 
+1. **What type of the ASAP Primitive is** A state column can be a raw data type (e.g., numerical number, string). It can also be a summary type (§6.1, §6.2), e.g., the summary **family** is sketch (`FieldDataType::Sketch`), its **category** is quantile (`SketchCategory::Quantile`), its **algorithm** is KLL (`SketchAlgorithm::Kll`), and its **parameters** are `SketchParams::Kll { k: 200 }`. A sketch field also records its `GroupingStrategy` (one instance per group, or one shared Hydra structure). Non-sketch families (`ExactAggregate`, `Sample`, `Wavelet`, `StatModel`) have a kind and parameters but no category. 
+2. **What query intent the summarized ASAP Primitive can support, e.g., statistical aggregation intents, time window aggregation intents** This information is being mapped based on the primitive type: it is not stored in the field. `SummaryEstimate::validate_inputs` accepts a readout only when the `SketchStatistic` matches the state's `SketchCategory` (Quantile→`Quantile`; Cardinality→`Cardinality`/`Universal`; PointCount→`Frequency`/`Universal`; FrequencyL2/FrequencyEntropy→`Universal`; TopK→`TopK`/`Universal`). Exact accumulators are read by `FinalizeExactAccumulator` instead. `Sample`, `Wavelet` and `StatModel` state has no readout operator yet.
 
+Whether an edge carries **state or values** is recorded on the producing node as `OperatorResultKind`, not inferred from field types. Usually they agree: a `SummaryAgg` output has exactly one non-plain field and kind `State`. They can differ, though. `MaintainPopulation` keeps an all-plain schema but its kind is `State`, and a `Project` that passes a state column through keeps kind `State`. Consumers check `result_kind` (`validate_inputs` requires `State` for every readout).
 
 ## 4. Proposed Node field design 
 
 A node in the physical data will represent the data or summary instance, so a node has a field for **What data sources a ASAP primitive summarizes**.
 
-Based on the above the proposed OperatorNode interface is as below:
+In code this field is `OperatorNode::coverage`. It records *which observations* a summary state covers: a source plus a union of joint (time × population) regions. It sits beside the schema, not inside a field, because two states with identical schemas can cover different data, and only disjoint coverage can be merged once-per-observation.
+
+Based on the above the proposed OperatorNode interface is as below (`crates/types/src/ir/node.rs`, `ir/summary_coverage.rs`):
 ```rust
+pub enum OperatorResultKind { Relation, InstantVector, RangeVector, /** unfinalized summary/accumulator state */ State }
+
+pub enum Operator { NonASAP(NonASAPOp), ASAP(ASAPOp) }
+
+pub struct OperatorNode {
+    pub operator: Operator,
+    pub result_kind: OperatorResultKind,       // derived from operator + children
+    pub schema: Schema,                        // derived; may override names/qualifiers only
+    pub guarantee: Option<ResultGuarantee>,    // None until accuracy assessment; None != exact
+    pub timing: Option<ExecutionTiming>,       // IngestionTime | QueryTime; None until assigned
+    #[serde(default)]
+    pub coverage: Option<SummaryCoverage>,     // observations a State output summarizes
+}
+
+impl OperatorNode {
+    pub fn new(op: Operator) -> Result<Self, SchemaDerivationError>;      // derives schema + kind; coverage = None
+    pub fn with_schema(op: Operator, schema: Schema) -> Self;             // caller-supplied names
+    pub fn new_shared(op: Operator) -> Result<Rc<Self>, SchemaDerivationError>;
+    pub fn with_guarantee(self, g: Option<ResultGuarantee>) -> Self;
+    pub fn with_timing(self, t: Option<ExecutionTiming>) -> Self;
+    /// Validates the coverage, then rejects a non-State node (CoverageError::NotState).
+    pub fn with_coverage(self, c: SummaryCoverage) -> Result<Self, SchemaDerivationError>;
+    /// This branch: true only for SummaryAgg. #560: SummaryAgg | SummaryMerge.
+    pub fn requires_coverage(&self) -> bool;
+    /// #560: (update expression, reduction) of a SummaryAgg, or shared by a SummaryMerge's inputs.
+    pub fn summary_update(&self) -> Option<(&SummaryUpdate, &Reduction)>;
+    /// Rebuilds with new inputs; re-derives schema; clears guarantee, timing and coverage.
+    pub fn map_children(&self, f: impl FnMut(&Rc<Self>) -> Rc<Self>) -> Result<Self, SchemaDerivationError>;
+    /// Per node: coverage well-formed (and present if required), validate_inputs,
+    /// result_kind and schema structure agree with derivation.
+    pub fn validate_structure(self: &Rc<Self>) -> Result<(), SchemaDerivationError>;
+    pub fn validate_execution_timing(self: &Rc<Self>) -> Result<(), SchemaDerivationError>;
+    // also: asap(), non_asap(), is_asap(), children(), contains_asap(), reachable()
+}
+
+pub struct SummaryCoverage {
+    pub source: Source,                 // Source::Table { table_ref } | Source::TimeSeries { metric }
+    pub regions: Vec<CoverageRegion>,   // union of joint regions, never a Cartesian product
+}
+pub struct CoverageRegion {
+    pub time_ms: Option<Range<i64>>,             // half-open, on the source's time column; None = unrestricted
+    pub population: BTreeMap<String, String>,    // conjunction of equality predicates; empty = unrestricted
+}
+impl SummaryCoverage {
+    /// Intervals non-empty, dimension names non-empty, regions pairwise provably disjoint.
+    pub fn validate(&self) -> Result<(), CoverageError>;
+    /// Union of provably disjoint inputs from one source; coalesces adjacent
+    /// intervals with identical populations and keeps gaps.
+    pub fn merge_disjoint(inputs: &[Self]) -> Result<Self, CoverageError>;
+}
+pub enum CoverageError {
+    InvalidInterval, InvalidPopulation, SourceMismatch, PossibleOverlap, EmptyMerge, NotState, Missing,
+    UnknownInput,          // #560: a merge input has no coverage
+    MergeOutputMismatch,   // #560: retained merge coverage differs from the input union
+}
 ```
 
+Two regions are provably disjoint only if their time ranges do not intersect or they bind the same population dimension to different values. A region without time bounds overlaps any region it is not population-disjoint from. Coverage is caller-established: `validate` checks that it is well-formed, not that it matches the child's predicates. Any rewrite through `map_children` drops it, so the rewriter must declare it again. `#537` adds export and CSE of the logical DAG (`ir/export.rs`, `ir/cse.rs`); no interface in this document depends on it.
+
 ## 5. Examples on how OperatorNode, schema, and physical data information are being used with Summary operators
 
 Given that these information requirements are introduced by summary operators to work correctly semantically, we show the examples of how the defined OperatorNode, schema, and physical data information work with each kind of summary operators. 
 
+Notation: an edge is written `──Kind(field Type, …)──▶`. Schemas are the ones `output_schema()` derives. Planning may rename fields through `OperatorNode::with_schema`, but types, nullability, `time_index`, `unique_keys` and `closed` must match the derivation. All examples use a table source, so values are `Relation`; with a `TimeSeries` source the value side is `InstantVector`.
+
+### 5.1 `SummaryAgg`: values → state
+
+Scenario: p99 latency by job, from KLL(k=200), over one minute of table `t`.
+
+```text
+Scan(t: job Utf8, latency Float64)
+  ──Relation(job Utf8, latency Float64)──▶
+SummaryAgg(family = Sketch(KLL{k=200}, PerSubpopulationInstance),
+           input = SummaryUpdate::column(Named("latency")), reduction = by[job],
+           grouping = PerSubpopulationInstance, filter = None)
+  ──State(job Utf8, state Sketch(KLL{k=200}, PerSubpopulationInstance))──▶
+  coverage = { source: Table "t", regions: [{ time_ms: 0..60_000, population: {} }] }
+```
+
+- Output schema: the `by` keys followed by one non-nullable field `state` typed `family`; `unique_keys = [[0]]`, `closed = true`, no `time_index`. With `Reduction::PerEntity` the input columns are kept and the sample-value column is replaced by `state`.
+- Checks: `family` is not `Plain`; the child is not `State`; the `weight`/`item` columns resolve against the child schema; `filter`, if present, types as `Bool`.
+- Coverage: **required** and **declared**. `OperatorNode::new` leaves it `None`, `validate_structure` fails with `CoverageError::Missing`, and the planner attaches it with `with_coverage`.
+- Boundary: this is where values become state. The sketch family, algorithm and parameters are committed in the field type, and `guarantee` stays `None` because state is not a caller-visible value.
+
+### 5.2 `SummaryEstimate`: sketch state → value
+
+Scenario: read p99 from the state in 5.1.
+
+```text
+──State(job Utf8, state Sketch(KLL{k=200}))──▶
+SummaryEstimate(query = SketchStatistic::Quantile { q: 0.99 })
+  ──Relation(job Utf8, quantile Float64)──▶      (planner may rename to p99)
+```
+
+- Output schema: the input schema with the one non-plain field replaced by a non-nullable plain field. Its name and type come from the statistic: `quantile`/`frequency_l2`/`frequency_entropy` Float64, `cardinality`/`count` Int64 (Float64 if the producer is a `PerEntity` `SummaryAgg`), and `topk` Utf8. Keys and metadata pass through.
+- Result kind: the value kind of the source the state was built from (`Relation` here).
+- Checks: input is `State` with exactly one non-plain field, that field is `Sketch`, and its category accepts the statistic (§3). For example, `Cardinality` on KLL is rejected.
+- Coverage: **absent**. The output is a value, and `with_coverage` returns `NotState`.
+- Boundary: state is consumed and a value is produced; `guarantee` on this node carries the readout's error bound.
+
+### 5.3 `FinalizeExactAccumulator`: exact state → value
+
+Scenario: total bytes by host with an exact Sum accumulator.
+
+```text
+Scan(t: host Utf8, bytes Float64)
+  ──Relation(host Utf8, bytes Float64)──▶
+SummaryAgg(family = ExactAggregate(Sum, Sum), input = column(Named("bytes")), reduction = by[host])
+  ──State(host Utf8, state ExactAggregate(Sum, Sum))──▶   coverage: required, declared
+FinalizeExactAccumulator
+  ──Relation(host Utf8, state Float64)──▶
+```
+
+- Output schema: each `ExactAggregate` field keeps its name (`state`) and takes the type and nullability the equivalent `NonASAPOp::Aggregate` would give: Sum/Min/Max follow the input column, Count is Int64, and Rate/IRate/Increase are Float64. If the child is not a `SummaryAgg` directly, Count falls back to Int64 and the others to Float64. `unique_keys`, `closed` and `time_index` are preserved (`schema_rebuilding.rs`).
+- Checks: the input is `State` and contains an `ExactAggregate` field; a sketch is rejected (`structure_contract.rs`).
+- Coverage: **absent** on the output.
+- Boundary: this is the explicit maintenance-to-read boundary for exact state. Exact state is never read through `SummaryEstimate`.
+
+### 5.4 `MaintainPopulation`: values → maintained membership (state)
+
+Scenario: keep the full latency population per job, so that p99 and top-10 can be evaluated later.
+
+```text
+Scan(t: job Utf8, latency Float64)  [closed schema]
+  ──Relation(job Utf8, latency Float64)──▶
+MaintainPopulation(population = MaintainedPopulation {
+    input: PopulationInput::Rows { input: <that Scan>, value_column: 1, grouping: by[job] },
+    max_k: 10, quantiles: true })
+  ──State(job Utf8, latency Float64)──▶
+```
+
+- Output schema: identical to the child's, all plain. Only `result_kind = State` marks it as maintained state.
+- Checks: `population.matches_node(child)`. For `Rows`, the child must be the same closed table `Scan`, the value column must be non-null Float64, and grouping must be `by` with in-range keys. For `CurrentSeries`, it must be a `TimeSeries` scan with the same metric, matchers and grouping labels, under an instant `TimeRange` of `lookback_ms` (which may be omitted only for the default 300 s lookback).
+- Coverage: **not required**. `with_coverage` accepts it because the output is `State`.
+- Boundary: the output is state because it must also track membership changes; downstream operators can only read it through `EvaluatePopulation`.
+
+### 5.5 `EvaluatePopulation`: maintained membership → value
+
+Scenario: p99 by job from the population in 5.4.
+
+```text
+──State(job Utf8, latency Float64)  [from MaintainPopulation]──▶
+EvaluatePopulation(evaluation = PopulationStatistic::Quantile { q: 0.99 })
+  ──Relation(job Utf8, quantile_0_99 Float64)──▶
+```
+
+- Output schema: the schema of `Aggregate(by grouping, measure)` over the maintained source. Quantile gives `quantile_<q>` Float64, Sum gives `sum` (value type), Count gives `count` Int64 and Average gives `avg` Float64; `unique_keys = [[0]]`, `closed`. `TopK { k }` instead returns the source schema unchanged (the selected rows).
+- Checks: the child is a `MaintainPopulation` node whose `supports(evaluation)` holds: `quantiles` must be set for `Quantile`, and `k <= max_k` for `TopK`.
+- Coverage: **absent**.
+- Boundary: maintained membership is read as a value; the result kind is the source's (`Relation`).
+
+### 5.6 `SummaryMerge` (#560): state × N → state
+
+On this branch, `SummaryMerge { children }` is **reserved**. `is_unimplemented()` returns true, and `output_schema()` and `validate_inputs()` return `UNIMPLEMENTED_ASAP_OP`, so `OperatorNode::new` fails. Only `output_kind()` (= `State`), `children`, `map_children` and `kind_name` work. #560 enables it as follows (`summary_merge_structure.rs` in #560).
+
+Scenario: combine two one-minute KLL panes over `Scan(t: value Float64)` into a two-minute state.
+
+```text
+SummaryAgg(KLL k=200, column(SampleValue), by[]) ──State(state Sketch(KLL{k=200}))── coverage {t, [0..60_000)} ─┐
+SummaryAgg(KLL k=200, column(SampleValue), by[]) ──State(state Sketch(KLL{k=200}))── coverage {t, [60_000..120_000)} ─┴▶
+SummaryMerge
+  ──State(state Sketch(KLL{k=200}))──▶   coverage = { t, [0..120_000) }   (derived)
+```
+
+- Output schema: `children[0].schema`.
+- Checks: at least one input; exactly one state column; every input is `State` with an identical schema (so family, params, grouping strategy and key positions match); every input has the same `summary_update()` (update expression and reduction); and `merged_coverage()` succeeds. Merging k=200 with k=300 fails, and so does merging raw rows.
+- Coverage: **required** and **derived**. `OperatorNode::new` sets it to `SummaryCoverage::merge_disjoint` of the input coverages. An input without coverage gives `UnknownInput`, and overlapping inputs give `PossibleOverlap`. `validate_structure` rejects a retained coverage that differs from the derived one (`MergeOutputMismatch`). Gapped inputs stay as two regions.
+- Boundary: state in, state out. No value is produced until a readout.
+
+### 5.7 Reserved operators (not implemented)
+
+These variants exist so that plans can name them, but `output_schema()`/`validate_inputs()` return `UNIMPLEMENTED_ASAP_OP`, so no node can be built. `output_kind()` already returns `State` for each of them. The intended edge shapes below follow from their fields; none of them is implemented.
+
+| Operator | Fields | Intended edge shape |
+|---|---|---|
+| `SummarySubtract` | `left, right` | State × State → State: remove one window's contribution, e.g. [0,10) − [0,5) |
+| `SummaryDelete` | `summary_input, key: ColumnId` | State → State with the entries for `key` removed |
+| `SummaryJoin` | `outer, inner, key, family` | State × State → State typed `family` (`produced_state()` returns it), e.g. join-size estimation |
+| `Extension` | `child, name` | deployment-named state operator |
+
+### 5.8 Summary
+
+| Operator | Input kind | Output kind | Output carries state | Coverage on output | Status |
+|---|---|---|---|---|---|
+| `SummaryAgg` | value (not `State`) | `State` | yes (one `family` field) | required, declared | implemented |
+| `SummaryEstimate` | `State` (one `Sketch` field) | source's value kind | no | absent | implemented |
+| `FinalizeExactAccumulator` | `State` (`ExactAggregate`) | source's value kind | no | absent | implemented |
+| `MaintainPopulation` | `Relation` (table) / `InstantVector` (series) | `State` | yes (by kind; fields plain) | optional, not required | implemented |
+| `EvaluatePopulation` | `State` from `MaintainPopulation` | source's value kind | no | absent | implemented |
+| `SummaryMerge` | `State` × N | `State` | yes | required, derived | reserved; enabled by #560 |
+| `SummarySubtract` | `State` × 2 | `State` | yes | — | reserved |
+| `SummaryDelete` | `State` | `State` | yes | — | reserved |
+| `SummaryJoin` | `State` × 2 | `State` | yes | — | reserved |
+| `Extension` | any | `State` | yes | — | reserved |
+
+## 6. Key code interfaces
+
+`OperatorNode`, `OperatorResultKind` and coverage are in §4. Bodies and serde/derive attributes are elided below.
+
+### 6.1 Schema and field types (`crates/types/src/pre_asap/schema.rs`)
+
+```rust
+pub type ColumnId = usize;
+
+pub struct Schema {
+    pub fields: Vec<Field>,
+    pub time_index: Option<ColumnId>,     // must point at a plain Timestamp field
+    pub unique_keys: Vec<Vec<ColumnId>>,
+    pub closed: bool,                     // true = fields enumerate every column
+}
+impl Schema {
+    pub fn new(fields: Vec<Field>) -> Self;
+    pub fn with_time_index(fields: Vec<Field>, time_index: ColumnId, unique_keys: Vec<Vec<ColumnId>>) -> Self;
+    pub fn lifted(fields: Vec<Field>, time_index: Option<ColumnId>) -> Self;   // closed = true
+    pub fn is_all_plain(&self) -> bool;
+    pub fn column_id(&self, name: &str) -> Option<ColumnId>;
+    pub fn column_id_qualified(&self, table: &str, name: &str) -> Option<ColumnId>;
+}
+
+pub struct Field<T = FieldDataType> {
+    pub name: String,
+    pub dtype: T,
+    pub nullable: bool,
+    pub table: Option<String>,
+}
+impl Field<FieldDataType> {
+    pub fn plain(name: impl Into<String>, dtype: DataType, nullable: bool) -> Self;
+    pub fn plain_dtype(&self) -> Option<&DataType>;
+    pub fn is_plain(&self) -> bool;
+}
+
+/// A column's type: a plain value, or summary state of one family.
+pub enum FieldDataType {
+    Plain(DataType),
+    ExactAggregate(ExactKind, ExactParams),
+    Sketch(SketchKind, GroupingStrategy),
+    Sample(SamplingKind, SamplingParams),
+    Wavelet(WaveletKind, WaveletParams),
+    StatModel(StatModelKind, StatModelParams),
+}
+
+pub enum DataType {
+    Null, Int64, Float64, Utf8, Bool, Timestamp, Interval, Date,
+    List { element: Box<Field<DataType>> },
+    Struct { fields: Vec<Field<DataType>> },
+    Map { key: Box<DataType>, value: Box<DataType>, value_nullable: bool },
+}
+```
+
+### 6.2 State-family parameters (`crates/types/src/post_asap/sketch.rs`)
+
+```rust
+pub enum ExactKind   { Sum, Count, Min, Max, Increase, Rate, IRate }
+pub enum ExactParams { Sum, Count, Min, Max, Increase, Rate, IRate }   // no knobs; mirrors kind
+
+pub struct SketchKind { category: SketchCategory, algorithm: SketchAlgorithm, params: SketchParams }
+impl SketchKind {
+    /// The only constructor; classifies the category and panics on mismatched params.
+    pub fn new(algorithm: SketchAlgorithm, params: SketchParams) -> Self;
+    pub fn category(&self) -> SketchCategory;
+    pub fn algorithm(&self) -> &SketchAlgorithm;
+    pub fn params(&self) -> &SketchParams;
+}
+pub enum SketchCategory { Universal, Quantile, Cardinality, Frequency, TopK }
+// Universal: UnivMon | Quantile: Kll, DDSketch | Cardinality: Hll, Theta, Kmv
+// Frequency: Cms, CountSketch | TopK: CmsWithHeap, CountSketchWithHeap
+pub enum SketchAlgorithm { UnivMon, Kll, Cms, Hll, DDSketch, CmsWithHeap, Kmv, Theta, CountSketch, CountSketchWithHeap }
+pub enum SketchParams {
+    UnivMon { heap_size: u32, sketch_rows: u32, sketch_cols: u32, layers: u8 },
+    Kll { k: u32 },
+    Cms { width: u32, depth: u32 },
+    Hll { precision: u8 },
+    DDSketch { alpha: f64 },
+    CmsWithHeap { width: u32, depth: u32, heap_size: u32 },
+    Kmv { k: u32 },
+    Theta { k: u32 },
+    CountSketch { width: u32, depth: u32 },
+    CountSketchWithHeap { width: u32, depth: u32, heap_size: u32 },
+}
+
+/// How grouped state is instantiated across `by` subpopulations. Orthogonal to family.
+pub enum GroupingStrategy {
+    PerSubpopulationInstance,                                       // Default
+    SharedMultiSubpopulation { kind: HydraKind, params: HydraParams },
+}
+pub enum HydraKind { HydraKll /* experimental, no error bound */, HydraCms, HydraCountSketch }
+pub enum HydraParams {
+    HydraKll { k: u32, shared_buckets: u32 },
+    HydraCms { width: u32, depth: u32, shared_rows: u32, shared_columns: u32 },
+    HydraCountSketch { width: u32, depth: u32, shared_rows: u32, shared_columns: u32 },
+}
+pub fn hydra_kind_for(a: &SketchAlgorithm) -> Option<HydraKind>;   // Cms, CountSketch only
+
+pub enum SamplingKind  { Reservoir }    pub enum SamplingParams  { Reservoir { size: u32 } }
+pub enum WaveletKind   { Haar }         pub enum WaveletParams   { Haar { coefficients: u32 } }
+pub enum StatModelKind { Parametric }   pub enum StatModelParams { Parametric { family: String } }
+```
+
+### 6.3 Update input and readouts (`post_asap/sketch.rs`, `post_asap/maintained_population.rs`)
+
+```rust
+/// One state update: `item` keys the update for keyed families; `weight` is applied to state.
+pub struct SummaryUpdate {
+    pub item: Option<SummaryInputExpr>,
+    pub weight: SummaryInputExpr,
+    pub weight_domain: WeightDomain,          // serde default: UnknownOrSigned
+}
+impl SummaryUpdate { pub fn column(c: ColumnRef) -> Self; }   // item None, UnknownOrSigned
+pub enum WeightDomain {
+    UnknownOrSigned,                                       // Default; never assumed non-negative
+    NonNegative { proof: NonNegativeWeightProof },
+}
+pub enum NonNegativeWeightProof { UnitCount, ResetAwareCounterDerivative }
+pub enum SummaryInputExpr {
+    Constant(f64), Column(ColumnRef), Tuple(Vec<SummaryInputExpr>), EntityIdentity(EntityIdentity),
+}
+pub enum EntityIdentity { PromqlLabelSet { excluding: Vec<ColumnRef> } }
+
+/// Readout of sketch state, carried by SummaryEstimate.
+pub enum SketchStatistic {
+    FrequencyL2, FrequencyEntropy,
+    Quantile { q: f64 },
+    PointCount { key: ColumnRef, value: Option<String> },
+    Cardinality,
+    TopK { k: usize },
+}
+
+/// Readout of a maintained population, carried by EvaluatePopulation.
+pub enum PopulationStatistic { Quantile { q: f64 }, TopK { k: usize }, Sum, Count, Average }
+pub struct MaintainedPopulation<N = QueryExpr> {
+    pub input: PopulationInput<N>,
+    pub max_k: usize,        // largest TopK it supports
+    pub quantiles: bool,     // whether Quantile is supported
+}
+pub enum PopulationInput<N = QueryExpr> {
+    CurrentSeries(CurrentSeriesInput),    // metric, matchers, grouping, without, lookback_ms
+    Rows { input: Rc<N>, value_column: usize, grouping: GroupKeys },
+}
+```
+
+A finalized value's accuracy statement is `ResultGuarantee { metric, bound, failure_probability, provenance }` (`post_asap/guarantee.rs`). It is attached to readout and finalized nodes, never to raw state.
+
+### 6.4 ASAP operators (`crates/types/src/ir/asap.rs`)
+
+```rust
+pub const UNIMPLEMENTED_ASAP_OP: &str =
+    "this ASAP operator is reserved: schema, accuracy, timing and export are not implemented";
+
+pub enum ASAPOp {
+    SummaryAgg {
+        child: Rc<OperatorNode>,
+        family: FieldDataType,             // never Plain
+        input: SummaryUpdate,
+        reduction: Reduction,              // Reduce(GroupKeys) | PerEntity
+        grouping: GroupingStrategy,
+        filter: Option<Predicate>,         // serde default None
+    },
+    SummaryEstimate { summary_input: Rc<OperatorNode>, query: SketchStatistic },
+    FinalizeExactAccumulator { child: Rc<OperatorNode> },
+    MaintainPopulation { child: Rc<OperatorNode>, population: MaintainedPopulation<OperatorNode> },
+    EvaluatePopulation { child: Rc<OperatorNode>, evaluation: PopulationStatistic },
+    // Reserved on this branch; #560 implements SummaryMerge.
+    SummaryMerge { children: Vec<Rc<OperatorNode>> },
+    SummarySubtract { left: Rc<OperatorNode>, right: Rc<OperatorNode> },
+    SummaryDelete { summary_input: Rc<OperatorNode>, key: ColumnId },
+    SummaryJoin { outer: Rc<OperatorNode>, inner: Rc<OperatorNode>, key: ColumnId, family: FieldDataType },
+    Extension { child: Rc<OperatorNode>, name: String },
+}
+
+impl ASAPOp {
+    pub fn children(&self) -> Vec<&Rc<OperatorNode>>;     // SummaryAgg includes its filter's subquery nodes
+    pub fn map_children(&self, f: impl FnMut(&Rc<OperatorNode>) -> Rc<OperatorNode>) -> Self;
+    pub fn kind_name(&self) -> &'static str;
+    /// Merge, Subtract, Delete, Join, Extension on this branch; #560 removes Merge.
+    pub fn is_unimplemented(&self) -> bool;
+    /// SummaryAgg/SummaryJoin `family`; #560 adds SummaryMerge (its inputs' state type).
+    pub fn produced_state(&self) -> Option<&FieldDataType>;
+    /// #560: merge_disjoint of the children's coverage; fails closed.
+    pub fn merged_coverage(&self) -> Result<SummaryCoverage, SchemaDerivationError>;
+    pub fn output_schema(&self) -> Result<Schema, SchemaDerivationError>;
+    pub fn output_kind(&self) -> OperatorResultKind;
+    pub fn validate_inputs(&self) -> Result<(), SchemaDerivationError>;
+}
+```

From 02833d1cefe41518711cf1d887e2ec8170ffdb4b Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 20:47:13 +0000
Subject: [PATCH 16/48] docs: move the ASAP primitive schema design to #573

The design document and the docs it consolidates are reviewed separately on
main. This PR keeps code, tests and the ScanSelection rename in docs.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 docs/design_docs/concepts/post-asap-ir.md     |   3 +-
 .../physical-planning-and-deployment.md       |  28 +-
 docs/design_docs/proposals/README.md          |   1 -
 .../proposals/asap-primitive-schema.md        | 432 ------------------
 .../proposals/decoupling_op_and_expr.md       |   2 +-
 .../design_docs/proposals/operator-sharing.md | 156 ++++++-
 .../proposals/univmon-frequency-summary.md    |   3 +-
 .../asap-aware-mapping-contracts.md           |  24 +-
 docs/develop_docs/pre-asap-ir.md              |  24 +-
 9 files changed, 210 insertions(+), 463 deletions(-)
 delete mode 100644 docs/design_docs/proposals/asap-primitive-schema.md

diff --git a/docs/design_docs/concepts/post-asap-ir.md b/docs/design_docs/concepts/post-asap-ir.md
index 08c670af4..6c9aa1461 100644
--- a/docs/design_docs/concepts/post-asap-ir.md
+++ b/docs/design_docs/concepts/post-asap-ir.md
@@ -49,8 +49,7 @@ summary family supports incremental maintenance.
   and selects the joined rows. Completeness evidence belongs to pruning, not ranking.
 
 A `SummaryNode` carries its expression, schema and optional result guarantee.
-State and query values have different contracts; see
-[Schema and physical data for ASAP primitives](../proposals/asap-primitive-schema.md). Exact operations over
+State and query values have different contracts. Exact operations over
 approximate readouts still require composed accuracy guarantees. See the
 [accuracy implementation companion](../../develop_docs/end-to-end-accuracy-guarantees.md)
 and [physical-plan integration](../architecture/physical-plan-integration.md)
diff --git a/docs/design_docs/physical-planning-and-deployment.md b/docs/design_docs/physical-planning-and-deployment.md
index c48dfed54..274e4974c 100644
--- a/docs/design_docs/physical-planning-and-deployment.md
+++ b/docs/design_docs/physical-planning-and-deployment.md
@@ -117,14 +117,26 @@ operators from logical candidates has not completed this integration.
 
 ### Input semantics and summary semantics
 
-`source`, `filter`, `grouping` and `window` describe input-data semantics but not
-a complete summary computation: the same four fields can summarize different
-value expressions or produce different states. The semantic information a summary
-depends on, and where the IR records each part (field type, producing operator,
-or coverage), is specified in
-[Schema and physical data for ASAP primitives](proposals/asap-primitive-schema.md#23-consideration-3-the-metadata-preserves-summary-semantics).
-
-The canonical selected computation is authoritative. Those categories describe
+`source`, `filter`, `grouping` and `window` describe input-data semantics:
+where records originate, which records qualify, how they are grouped and which
+time interval applies. They are not a complete description of arbitrary summary
+computation. In particular, the same four fields can summarize different value
+expressions or produce different states.
+
+| Concern | Required semantic information |
+| --- | --- |
+| Input computation | Source identities and schemas, filters, joins/transforms and their order, or a reference to the canonical input sub-DAG |
+| Values and grouping | Value expressions, item identities and weights where applicable, group keys and types, and operation-defined null/duplicate handling |
+| Time | Time column and interpretation, interval bounds, evaluation alignment, and distinction between query range and maintained panes |
+| Summary computation | Exact operation or sketch family, algorithm and parameters, and supported build/merge behavior |
+| Output | State versus finalized value, output schema/type, and readout parameters when part of the output computation |
+
+For example, KLL over `latency_seconds` and KLL over `log(latency_seconds)` differ
+even with identical source, filter, grouping and window. Likewise, weighted
+frequency state needs both item and weight expressions. More complex inputs
+must retain their computation DAG; four descriptive fields cannot replace it.
+
+The canonical selected computation is authoritative. These categories describe
 what must be preserved, not a new flat IR or a second expression language.
 Operator-defined behavior should be referenced through its canonical contract,
 not independently configured in deployment metadata. Unsupported or unresolved
diff --git a/docs/design_docs/proposals/README.md b/docs/design_docs/proposals/README.md
index 6c4ed49f8..cb44fadbb 100644
--- a/docs/design_docs/proposals/README.md
+++ b/docs/design_docs/proposals/README.md
@@ -11,4 +11,3 @@ extensions. A design document is not a promise of downstream runtime support.
 - [Operator sharing](operator-sharing.md)
 - [Decoupling operators from scalar expressions](decoupling_op_and_expr.md)
 - [ASAPPlanner layering](planner-layering.md)
-- [Schema and physical data for ASAP primitives](asap-primitive-schema.md)
diff --git a/docs/design_docs/proposals/asap-primitive-schema.md b/docs/design_docs/proposals/asap-primitive-schema.md
deleted file mode 100644
index 2302e3040..000000000
--- a/docs/design_docs/proposals/asap-primitive-schema.md
+++ /dev/null
@@ -1,432 +0,0 @@
-# Schema and Physical Data for ASAP Primitives
-
-This document is the single source of truth for the schema, and column design for ASAP Primitives. This is used in the logical stage (LogicalASAPDAG), and physical stage (PhysicalASAPDAG). 
-
-## 1. Goal, problem, and requirements
-
-Unlike existing Database engines, which work on raw data or explicitly defined materialized tables with schema and column names provided by the users, ASAPPlanner is designed for querying and execution over the mix of raw data and ASAP Primitives. ASAP primitives are usually compact summaries over raw data. Therefore, it introduces new requirement when we design the schema and node definitions for LogicalASAPDAG and PhysicalASAPDAG.
-
-Assuming we have the Logical DAG defined for a canonicalized representation for a batch of queries. [TODO: add links for this here. ]
-The LogicalASAPDAG will share/reuse the NonASAP operator and ScalarExpr nodes in LogicalDAG [TODO: link PR 511's doc here], but replacing some operators in LogicalDAG with the operators operated with ASAP Primitives. The complete list is `ASAPOp` in `crates/types/src/ir/asap.rs`: `SummaryAgg` (creates and updates state; there is no separate SummaryCreation or SummaryUpdate operator, and `SummaryUpdate` is `SummaryAgg`'s update-expression parameter), `SummaryEstimate`, `FinalizeExactAccumulator`, `MaintainPopulation` and `EvaluatePopulation` (implemented); `SummaryMerge` (reserved here, enabled by #560); and `SummarySubtract`, `SummaryDelete`, `SummaryJoin` and `Extension` (reserved). See §5. 
-Each of the Summary operators also require the ASAP primitive information above to inter-operate correctly, preserving semantic correctness. 
-
-Basically, the following information should be represented to preserve the equivalent query semantics when we introduce ASAP Primitives to logical query representation, and following physical one. 
-
-- What type of the ASAP Primitive is
-- What is the ASAP Primitive parameters
-- What data sources a ASAP primitive summarizes
-- What query intent the summarized ASAP Primitive can support, e.g., statistical aggregation intents, time window aggregation intents
-
-
-
-And these information will be combined with relational or time series query operator information, such as group by/reduction, filtering, projection, join, time series selection, together. 
-
-Therefore, these requirements drive the following schema and metadata, node information, and column design. 
-
-
-
-## 2. Existing database terminology for schema, table, column, and physical data layout
-
-
-## 3. Proposed schema design 
-Schema represents the **metadata** of information flow along an **edge** between two nodes in a logical or physical DAG. The schema field is associated with the node in the DAG. The consumer of the node in the DAG takes the schema from the producer node as input. 
-
-Schema definition here is shared between LogicalDAG, LogicalASAPDAG, and PhysicalASAPDAG. The schema contain fields, and each field is mapping to a column in the physical data representation. 
-Based on our requirement, each field should contain the following information.
-1. **What type of the ASAP Primitive is** A state column can be a raw data type (e.g., numerical number, string). It can also be a summary type (§6.1, §6.2), e.g., the summary **family** is sketch (`FieldDataType::Sketch`), its **category** is quantile (`SketchCategory::Quantile`), its **algorithm** is KLL (`SketchAlgorithm::Kll`), and its **parameters** are `SketchParams::Kll { k: 200 }`. A sketch field also records its `GroupingStrategy` (one instance per group, or one shared Hydra structure). Non-sketch families (`ExactAggregate`, `Sample`, `Wavelet`, `StatModel`) have a kind and parameters but no category. 
-2. **What query intent the summarized ASAP Primitive can support, e.g., statistical aggregation intents, time window aggregation intents** This information is being mapped based on the primitive type: it is not stored in the field. `SummaryEstimate::validate_inputs` accepts a readout only when the `SketchStatistic` matches the state's `SketchCategory` (Quantile→`Quantile`; Cardinality→`Cardinality`/`Universal`; PointCount→`Frequency`/`Universal`; FrequencyL2/FrequencyEntropy→`Universal`; TopK→`TopK`/`Universal`). Exact accumulators are read by `FinalizeExactAccumulator` instead. `Sample`, `Wavelet` and `StatModel` state has no readout operator yet.
-
-Whether an edge carries **state or values** is recorded on the producing node as `OperatorResultKind`, not inferred from field types. Usually they agree: a `SummaryAgg` output has exactly one non-plain field and kind `State`. They can differ, though. `MaintainPopulation` keeps an all-plain schema but its kind is `State`, and a `Project` that passes a state column through keeps kind `State`. Consumers check `result_kind` (`validate_inputs` requires `State` for every readout).
-
-## 4. Proposed Node field design 
-
-A node in the physical data will represent the data or summary instance, so a node has a field for **What data sources a ASAP primitive summarizes**.
-
-In code this field is `OperatorNode::coverage`. It records *which observations* a summary state covers: a source plus a union of joint (time × population) regions. It sits beside the schema, not inside a field, because two states with identical schemas can cover different data, and only disjoint coverage can be merged once-per-observation.
-
-Based on the above the proposed OperatorNode interface is as below (`crates/types/src/ir/node.rs`, `ir/summary_coverage.rs`):
-```rust
-pub enum OperatorResultKind { Relation, InstantVector, RangeVector, /** unfinalized summary/accumulator state */ State }
-
-pub enum Operator { NonASAP(NonASAPOp), ASAP(ASAPOp) }
-
-pub struct OperatorNode {
-    pub operator: Operator,
-    pub result_kind: OperatorResultKind,       // derived from operator + children
-    pub schema: Schema,                        // derived; may override names/qualifiers only
-    pub guarantee: Option<ResultGuarantee>,    // None until accuracy assessment; None != exact
-    pub timing: Option<ExecutionTiming>,       // IngestionTime | QueryTime; None until assigned
-    #[serde(default)]
-    pub coverage: Option<SummaryCoverage>,     // observations a State output summarizes
-}
-
-impl OperatorNode {
-    pub fn new(op: Operator) -> Result<Self, SchemaDerivationError>;      // derives schema + kind; coverage = None
-    pub fn with_schema(op: Operator, schema: Schema) -> Self;             // caller-supplied names
-    pub fn new_shared(op: Operator) -> Result<Rc<Self>, SchemaDerivationError>;
-    pub fn with_guarantee(self, g: Option<ResultGuarantee>) -> Self;
-    pub fn with_timing(self, t: Option<ExecutionTiming>) -> Self;
-    /// Validates the coverage, then rejects a non-State node (CoverageError::NotState).
-    pub fn with_coverage(self, c: SummaryCoverage) -> Result<Self, SchemaDerivationError>;
-    /// This branch: true only for SummaryAgg. #560: SummaryAgg | SummaryMerge.
-    pub fn requires_coverage(&self) -> bool;
-    /// #560: (update expression, reduction) of a SummaryAgg, or shared by a SummaryMerge's inputs.
-    pub fn summary_update(&self) -> Option<(&SummaryUpdate, &Reduction)>;
-    /// Rebuilds with new inputs; re-derives schema; clears guarantee, timing and coverage.
-    pub fn map_children(&self, f: impl FnMut(&Rc<Self>) -> Rc<Self>) -> Result<Self, SchemaDerivationError>;
-    /// Per node: coverage well-formed (and present if required), validate_inputs,
-    /// result_kind and schema structure agree with derivation.
-    pub fn validate_structure(self: &Rc<Self>) -> Result<(), SchemaDerivationError>;
-    pub fn validate_execution_timing(self: &Rc<Self>) -> Result<(), SchemaDerivationError>;
-    // also: asap(), non_asap(), is_asap(), children(), contains_asap(), reachable()
-}
-
-pub struct SummaryCoverage {
-    pub source: Source,                 // Source::Table { table_ref } | Source::TimeSeries { metric }
-    pub regions: Vec<CoverageRegion>,   // union of joint regions, never a Cartesian product
-}
-pub struct CoverageRegion {
-    pub time_ms: Option<Range<i64>>,             // half-open, on the source's time column; None = unrestricted
-    pub population: BTreeMap<String, String>,    // conjunction of equality predicates; empty = unrestricted
-}
-impl SummaryCoverage {
-    /// Intervals non-empty, dimension names non-empty, regions pairwise provably disjoint.
-    pub fn validate(&self) -> Result<(), CoverageError>;
-    /// Union of provably disjoint inputs from one source; coalesces adjacent
-    /// intervals with identical populations and keeps gaps.
-    pub fn merge_disjoint(inputs: &[Self]) -> Result<Self, CoverageError>;
-}
-pub enum CoverageError {
-    InvalidInterval, InvalidPopulation, SourceMismatch, PossibleOverlap, EmptyMerge, NotState, Missing,
-    UnknownInput,          // #560: a merge input has no coverage
-    MergeOutputMismatch,   // #560: retained merge coverage differs from the input union
-}
-```
-
-Two regions are provably disjoint only if their time ranges do not intersect or they bind the same population dimension to different values. A region without time bounds overlaps any region it is not population-disjoint from. Coverage is caller-established: `validate` checks that it is well-formed, not that it matches the child's predicates. Any rewrite through `map_children` drops it, so the rewriter must declare it again. `#537` adds export and CSE of the logical DAG (`ir/export.rs`, `ir/cse.rs`); no interface in this document depends on it.
-
-## 5. Examples on how OperatorNode, schema, and physical data information are being used with Summary operators
-
-Given that these information requirements are introduced by summary operators to work correctly semantically, we show the examples of how the defined OperatorNode, schema, and physical data information work with each kind of summary operators. 
-
-Notation: an edge is written `──Kind(field Type, …)──▶`. Schemas are the ones `output_schema()` derives. Planning may rename fields through `OperatorNode::with_schema`, but types, nullability, `time_index`, `unique_keys` and `closed` must match the derivation. All examples use a table source, so values are `Relation`; with a `TimeSeries` source the value side is `InstantVector`.
-
-### 5.1 `SummaryAgg`: values → state
-
-Scenario: p99 latency by job, from KLL(k=200), over one minute of table `t`.
-
-```text
-Scan(t: job Utf8, latency Float64)
-  ──Relation(job Utf8, latency Float64)──▶
-SummaryAgg(family = Sketch(KLL{k=200}, PerSubpopulationInstance),
-           input = SummaryUpdate::column(Named("latency")), reduction = by[job],
-           grouping = PerSubpopulationInstance, filter = None)
-  ──State(job Utf8, state Sketch(KLL{k=200}, PerSubpopulationInstance))──▶
-  coverage = { source: Table "t", regions: [{ time_ms: 0..60_000, population: {} }] }
-```
-
-- Output schema: the `by` keys followed by one non-nullable field `state` typed `family`; `unique_keys = [[0]]`, `closed = true`, no `time_index`. With `Reduction::PerEntity` the input columns are kept and the sample-value column is replaced by `state`.
-- Checks: `family` is not `Plain`; the child is not `State`; the `weight`/`item` columns resolve against the child schema; `filter`, if present, types as `Bool`.
-- Coverage: **required** and **declared**. `OperatorNode::new` leaves it `None`, `validate_structure` fails with `CoverageError::Missing`, and the planner attaches it with `with_coverage`.
-- Boundary: this is where values become state. The sketch family, algorithm and parameters are committed in the field type, and `guarantee` stays `None` because state is not a caller-visible value.
-
-### 5.2 `SummaryEstimate`: sketch state → value
-
-Scenario: read p99 from the state in 5.1.
-
-```text
-──State(job Utf8, state Sketch(KLL{k=200}))──▶
-SummaryEstimate(query = SketchStatistic::Quantile { q: 0.99 })
-  ──Relation(job Utf8, quantile Float64)──▶      (planner may rename to p99)
-```
-
-- Output schema: the input schema with the one non-plain field replaced by a non-nullable plain field. Its name and type come from the statistic: `quantile`/`frequency_l2`/`frequency_entropy` Float64, `cardinality`/`count` Int64 (Float64 if the producer is a `PerEntity` `SummaryAgg`), and `topk` Utf8. Keys and metadata pass through.
-- Result kind: the value kind of the source the state was built from (`Relation` here).
-- Checks: input is `State` with exactly one non-plain field, that field is `Sketch`, and its category accepts the statistic (§3). For example, `Cardinality` on KLL is rejected.
-- Coverage: **absent**. The output is a value, and `with_coverage` returns `NotState`.
-- Boundary: state is consumed and a value is produced; `guarantee` on this node carries the readout's error bound.
-
-### 5.3 `FinalizeExactAccumulator`: exact state → value
-
-Scenario: total bytes by host with an exact Sum accumulator.
-
-```text
-Scan(t: host Utf8, bytes Float64)
-  ──Relation(host Utf8, bytes Float64)──▶
-SummaryAgg(family = ExactAggregate(Sum, Sum), input = column(Named("bytes")), reduction = by[host])
-  ──State(host Utf8, state ExactAggregate(Sum, Sum))──▶   coverage: required, declared
-FinalizeExactAccumulator
-  ──Relation(host Utf8, state Float64)──▶
-```
-
-- Output schema: each `ExactAggregate` field keeps its name (`state`) and takes the type and nullability the equivalent `NonASAPOp::Aggregate` would give: Sum/Min/Max follow the input column, Count is Int64, and Rate/IRate/Increase are Float64. If the child is not a `SummaryAgg` directly, Count falls back to Int64 and the others to Float64. `unique_keys`, `closed` and `time_index` are preserved (`schema_rebuilding.rs`).
-- Checks: the input is `State` and contains an `ExactAggregate` field; a sketch is rejected (`structure_contract.rs`).
-- Coverage: **absent** on the output.
-- Boundary: this is the explicit maintenance-to-read boundary for exact state. Exact state is never read through `SummaryEstimate`.
-
-### 5.4 `MaintainPopulation`: values → maintained membership (state)
-
-Scenario: keep the full latency population per job, so that p99 and top-10 can be evaluated later.
-
-```text
-Scan(t: job Utf8, latency Float64)  [closed schema]
-  ──Relation(job Utf8, latency Float64)──▶
-MaintainPopulation(population = MaintainedPopulation {
-    input: PopulationInput::Rows { input: <that Scan>, value_column: 1, grouping: by[job] },
-    max_k: 10, quantiles: true })
-  ──State(job Utf8, latency Float64)──▶
-```
-
-- Output schema: identical to the child's, all plain. Only `result_kind = State` marks it as maintained state.
-- Checks: `population.matches_node(child)`. For `Rows`, the child must be the same closed table `Scan`, the value column must be non-null Float64, and grouping must be `by` with in-range keys. For `CurrentSeries`, it must be a `TimeSeries` scan with the same metric, matchers and grouping labels, under an instant `TimeRange` of `lookback_ms` (which may be omitted only for the default 300 s lookback).
-- Coverage: **not required**. `with_coverage` accepts it because the output is `State`.
-- Boundary: the output is state because it must also track membership changes; downstream operators can only read it through `EvaluatePopulation`.
-
-### 5.5 `EvaluatePopulation`: maintained membership → value
-
-Scenario: p99 by job from the population in 5.4.
-
-```text
-──State(job Utf8, latency Float64)  [from MaintainPopulation]──▶
-EvaluatePopulation(evaluation = PopulationStatistic::Quantile { q: 0.99 })
-  ──Relation(job Utf8, quantile_0_99 Float64)──▶
-```
-
-- Output schema: the schema of `Aggregate(by grouping, measure)` over the maintained source. Quantile gives `quantile_<q>` Float64, Sum gives `sum` (value type), Count gives `count` Int64 and Average gives `avg` Float64; `unique_keys = [[0]]`, `closed`. `TopK { k }` instead returns the source schema unchanged (the selected rows).
-- Checks: the child is a `MaintainPopulation` node whose `supports(evaluation)` holds: `quantiles` must be set for `Quantile`, and `k <= max_k` for `TopK`.
-- Coverage: **absent**.
-- Boundary: maintained membership is read as a value; the result kind is the source's (`Relation`).
-
-### 5.6 `SummaryMerge` (#560): state × N → state
-
-On this branch, `SummaryMerge { children }` is **reserved**. `is_unimplemented()` returns true, and `output_schema()` and `validate_inputs()` return `UNIMPLEMENTED_ASAP_OP`, so `OperatorNode::new` fails. Only `output_kind()` (= `State`), `children`, `map_children` and `kind_name` work. #560 enables it as follows (`summary_merge_structure.rs` in #560).
-
-Scenario: combine two one-minute KLL panes over `Scan(t: value Float64)` into a two-minute state.
-
-```text
-SummaryAgg(KLL k=200, column(SampleValue), by[]) ──State(state Sketch(KLL{k=200}))── coverage {t, [0..60_000)} ─┐
-SummaryAgg(KLL k=200, column(SampleValue), by[]) ──State(state Sketch(KLL{k=200}))── coverage {t, [60_000..120_000)} ─┴▶
-SummaryMerge
-  ──State(state Sketch(KLL{k=200}))──▶   coverage = { t, [0..120_000) }   (derived)
-```
-
-- Output schema: `children[0].schema`.
-- Checks: at least one input; exactly one state column; every input is `State` with an identical schema (so family, params, grouping strategy and key positions match); every input has the same `summary_update()` (update expression and reduction); and `merged_coverage()` succeeds. Merging k=200 with k=300 fails, and so does merging raw rows.
-- Coverage: **required** and **derived**. `OperatorNode::new` sets it to `SummaryCoverage::merge_disjoint` of the input coverages. An input without coverage gives `UnknownInput`, and overlapping inputs give `PossibleOverlap`. `validate_structure` rejects a retained coverage that differs from the derived one (`MergeOutputMismatch`). Gapped inputs stay as two regions.
-- Boundary: state in, state out. No value is produced until a readout.
-
-### 5.7 Reserved operators (not implemented)
-
-These variants exist so that plans can name them, but `output_schema()`/`validate_inputs()` return `UNIMPLEMENTED_ASAP_OP`, so no node can be built. `output_kind()` already returns `State` for each of them. The intended edge shapes below follow from their fields; none of them is implemented.
-
-| Operator | Fields | Intended edge shape |
-|---|---|---|
-| `SummarySubtract` | `left, right` | State × State → State: remove one window's contribution, e.g. [0,10) − [0,5) |
-| `SummaryDelete` | `summary_input, key: ColumnId` | State → State with the entries for `key` removed |
-| `SummaryJoin` | `outer, inner, key, family` | State × State → State typed `family` (`produced_state()` returns it), e.g. join-size estimation |
-| `Extension` | `child, name` | deployment-named state operator |
-
-### 5.8 Summary
-
-| Operator | Input kind | Output kind | Output carries state | Coverage on output | Status |
-|---|---|---|---|---|---|
-| `SummaryAgg` | value (not `State`) | `State` | yes (one `family` field) | required, declared | implemented |
-| `SummaryEstimate` | `State` (one `Sketch` field) | source's value kind | no | absent | implemented |
-| `FinalizeExactAccumulator` | `State` (`ExactAggregate`) | source's value kind | no | absent | implemented |
-| `MaintainPopulation` | `Relation` (table) / `InstantVector` (series) | `State` | yes (by kind; fields plain) | optional, not required | implemented |
-| `EvaluatePopulation` | `State` from `MaintainPopulation` | source's value kind | no | absent | implemented |
-| `SummaryMerge` | `State` × N | `State` | yes | required, derived | reserved; enabled by #560 |
-| `SummarySubtract` | `State` × 2 | `State` | yes | — | reserved |
-| `SummaryDelete` | `State` | `State` | yes | — | reserved |
-| `SummaryJoin` | `State` × 2 | `State` | yes | — | reserved |
-| `Extension` | any | `State` | yes | — | reserved |
-
-## 6. Key code interfaces
-
-`OperatorNode`, `OperatorResultKind` and coverage are in §4. Bodies and serde/derive attributes are elided below.
-
-### 6.1 Schema and field types (`crates/types/src/pre_asap/schema.rs`)
-
-```rust
-pub type ColumnId = usize;
-
-pub struct Schema {
-    pub fields: Vec<Field>,
-    pub time_index: Option<ColumnId>,     // must point at a plain Timestamp field
-    pub unique_keys: Vec<Vec<ColumnId>>,
-    pub closed: bool,                     // true = fields enumerate every column
-}
-impl Schema {
-    pub fn new(fields: Vec<Field>) -> Self;
-    pub fn with_time_index(fields: Vec<Field>, time_index: ColumnId, unique_keys: Vec<Vec<ColumnId>>) -> Self;
-    pub fn lifted(fields: Vec<Field>, time_index: Option<ColumnId>) -> Self;   // closed = true
-    pub fn is_all_plain(&self) -> bool;
-    pub fn column_id(&self, name: &str) -> Option<ColumnId>;
-    pub fn column_id_qualified(&self, table: &str, name: &str) -> Option<ColumnId>;
-}
-
-pub struct Field<T = FieldDataType> {
-    pub name: String,
-    pub dtype: T,
-    pub nullable: bool,
-    pub table: Option<String>,
-}
-impl Field<FieldDataType> {
-    pub fn plain(name: impl Into<String>, dtype: DataType, nullable: bool) -> Self;
-    pub fn plain_dtype(&self) -> Option<&DataType>;
-    pub fn is_plain(&self) -> bool;
-}
-
-/// A column's type: a plain value, or summary state of one family.
-pub enum FieldDataType {
-    Plain(DataType),
-    ExactAggregate(ExactKind, ExactParams),
-    Sketch(SketchKind, GroupingStrategy),
-    Sample(SamplingKind, SamplingParams),
-    Wavelet(WaveletKind, WaveletParams),
-    StatModel(StatModelKind, StatModelParams),
-}
-
-pub enum DataType {
-    Null, Int64, Float64, Utf8, Bool, Timestamp, Interval, Date,
-    List { element: Box<Field<DataType>> },
-    Struct { fields: Vec<Field<DataType>> },
-    Map { key: Box<DataType>, value: Box<DataType>, value_nullable: bool },
-}
-```
-
-### 6.2 State-family parameters (`crates/types/src/post_asap/sketch.rs`)
-
-```rust
-pub enum ExactKind   { Sum, Count, Min, Max, Increase, Rate, IRate }
-pub enum ExactParams { Sum, Count, Min, Max, Increase, Rate, IRate }   // no knobs; mirrors kind
-
-pub struct SketchKind { category: SketchCategory, algorithm: SketchAlgorithm, params: SketchParams }
-impl SketchKind {
-    /// The only constructor; classifies the category and panics on mismatched params.
-    pub fn new(algorithm: SketchAlgorithm, params: SketchParams) -> Self;
-    pub fn category(&self) -> SketchCategory;
-    pub fn algorithm(&self) -> &SketchAlgorithm;
-    pub fn params(&self) -> &SketchParams;
-}
-pub enum SketchCategory { Universal, Quantile, Cardinality, Frequency, TopK }
-// Universal: UnivMon | Quantile: Kll, DDSketch | Cardinality: Hll, Theta, Kmv
-// Frequency: Cms, CountSketch | TopK: CmsWithHeap, CountSketchWithHeap
-pub enum SketchAlgorithm { UnivMon, Kll, Cms, Hll, DDSketch, CmsWithHeap, Kmv, Theta, CountSketch, CountSketchWithHeap }
-pub enum SketchParams {
-    UnivMon { heap_size: u32, sketch_rows: u32, sketch_cols: u32, layers: u8 },
-    Kll { k: u32 },
-    Cms { width: u32, depth: u32 },
-    Hll { precision: u8 },
-    DDSketch { alpha: f64 },
-    CmsWithHeap { width: u32, depth: u32, heap_size: u32 },
-    Kmv { k: u32 },
-    Theta { k: u32 },
-    CountSketch { width: u32, depth: u32 },
-    CountSketchWithHeap { width: u32, depth: u32, heap_size: u32 },
-}
-
-/// How grouped state is instantiated across `by` subpopulations. Orthogonal to family.
-pub enum GroupingStrategy {
-    PerSubpopulationInstance,                                       // Default
-    SharedMultiSubpopulation { kind: HydraKind, params: HydraParams },
-}
-pub enum HydraKind { HydraKll /* experimental, no error bound */, HydraCms, HydraCountSketch }
-pub enum HydraParams {
-    HydraKll { k: u32, shared_buckets: u32 },
-    HydraCms { width: u32, depth: u32, shared_rows: u32, shared_columns: u32 },
-    HydraCountSketch { width: u32, depth: u32, shared_rows: u32, shared_columns: u32 },
-}
-pub fn hydra_kind_for(a: &SketchAlgorithm) -> Option<HydraKind>;   // Cms, CountSketch only
-
-pub enum SamplingKind  { Reservoir }    pub enum SamplingParams  { Reservoir { size: u32 } }
-pub enum WaveletKind   { Haar }         pub enum WaveletParams   { Haar { coefficients: u32 } }
-pub enum StatModelKind { Parametric }   pub enum StatModelParams { Parametric { family: String } }
-```
-
-### 6.3 Update input and readouts (`post_asap/sketch.rs`, `post_asap/maintained_population.rs`)
-
-```rust
-/// One state update: `item` keys the update for keyed families; `weight` is applied to state.
-pub struct SummaryUpdate {
-    pub item: Option<SummaryInputExpr>,
-    pub weight: SummaryInputExpr,
-    pub weight_domain: WeightDomain,          // serde default: UnknownOrSigned
-}
-impl SummaryUpdate { pub fn column(c: ColumnRef) -> Self; }   // item None, UnknownOrSigned
-pub enum WeightDomain {
-    UnknownOrSigned,                                       // Default; never assumed non-negative
-    NonNegative { proof: NonNegativeWeightProof },
-}
-pub enum NonNegativeWeightProof { UnitCount, ResetAwareCounterDerivative }
-pub enum SummaryInputExpr {
-    Constant(f64), Column(ColumnRef), Tuple(Vec<SummaryInputExpr>), EntityIdentity(EntityIdentity),
-}
-pub enum EntityIdentity { PromqlLabelSet { excluding: Vec<ColumnRef> } }
-
-/// Readout of sketch state, carried by SummaryEstimate.
-pub enum SketchStatistic {
-    FrequencyL2, FrequencyEntropy,
-    Quantile { q: f64 },
-    PointCount { key: ColumnRef, value: Option<String> },
-    Cardinality,
-    TopK { k: usize },
-}
-
-/// Readout of a maintained population, carried by EvaluatePopulation.
-pub enum PopulationStatistic { Quantile { q: f64 }, TopK { k: usize }, Sum, Count, Average }
-pub struct MaintainedPopulation<N = QueryExpr> {
-    pub input: PopulationInput<N>,
-    pub max_k: usize,        // largest TopK it supports
-    pub quantiles: bool,     // whether Quantile is supported
-}
-pub enum PopulationInput<N = QueryExpr> {
-    CurrentSeries(CurrentSeriesInput),    // metric, matchers, grouping, without, lookback_ms
-    Rows { input: Rc<N>, value_column: usize, grouping: GroupKeys },
-}
-```
-
-A finalized value's accuracy statement is `ResultGuarantee { metric, bound, failure_probability, provenance }` (`post_asap/guarantee.rs`). It is attached to readout and finalized nodes, never to raw state.
-
-### 6.4 ASAP operators (`crates/types/src/ir/asap.rs`)
-
-```rust
-pub const UNIMPLEMENTED_ASAP_OP: &str =
-    "this ASAP operator is reserved: schema, accuracy, timing and export are not implemented";
-
-pub enum ASAPOp {
-    SummaryAgg {
-        child: Rc<OperatorNode>,
-        family: FieldDataType,             // never Plain
-        input: SummaryUpdate,
-        reduction: Reduction,              // Reduce(GroupKeys) | PerEntity
-        grouping: GroupingStrategy,
-        filter: Option<Predicate>,         // serde default None
-    },
-    SummaryEstimate { summary_input: Rc<OperatorNode>, query: SketchStatistic },
-    FinalizeExactAccumulator { child: Rc<OperatorNode> },
-    MaintainPopulation { child: Rc<OperatorNode>, population: MaintainedPopulation<OperatorNode> },
-    EvaluatePopulation { child: Rc<OperatorNode>, evaluation: PopulationStatistic },
-    // Reserved on this branch; #560 implements SummaryMerge.
-    SummaryMerge { children: Vec<Rc<OperatorNode>> },
-    SummarySubtract { left: Rc<OperatorNode>, right: Rc<OperatorNode> },
-    SummaryDelete { summary_input: Rc<OperatorNode>, key: ColumnId },
-    SummaryJoin { outer: Rc<OperatorNode>, inner: Rc<OperatorNode>, key: ColumnId, family: FieldDataType },
-    Extension { child: Rc<OperatorNode>, name: String },
-}
-
-impl ASAPOp {
-    pub fn children(&self) -> Vec<&Rc<OperatorNode>>;     // SummaryAgg includes its filter's subquery nodes
-    pub fn map_children(&self, f: impl FnMut(&Rc<OperatorNode>) -> Rc<OperatorNode>) -> Self;
-    pub fn kind_name(&self) -> &'static str;
-    /// Merge, Subtract, Delete, Join, Extension on this branch; #560 removes Merge.
-    pub fn is_unimplemented(&self) -> bool;
-    /// SummaryAgg/SummaryJoin `family`; #560 adds SummaryMerge (its inputs' state type).
-    pub fn produced_state(&self) -> Option<&FieldDataType>;
-    /// #560: merge_disjoint of the children's coverage; fails closed.
-    pub fn merged_coverage(&self) -> Result<SummaryCoverage, SchemaDerivationError>;
-    pub fn output_schema(&self) -> Result<Schema, SchemaDerivationError>;
-    pub fn output_kind(&self) -> OperatorResultKind;
-    pub fn validate_inputs(&self) -> Result<(), SchemaDerivationError>;
-}
-```
diff --git a/docs/design_docs/proposals/decoupling_op_and_expr.md b/docs/design_docs/proposals/decoupling_op_and_expr.md
index f850116bb..f87456a9f 100644
--- a/docs/design_docs/proposals/decoupling_op_and_expr.md
+++ b/docs/design_docs/proposals/decoupling_op_and_expr.md
@@ -62,7 +62,7 @@ operator inputs and scalar query-result references use `Rc<OperatorNode>`.
 read by expressions. Keep `ScalarExpr::Column(ColumnId)`: the ID selects a field
 for type checking and the corresponding input value for evaluation, independently
 of the executor's row/column storage layout. See the
-[fields versus column references contract](asap-primitive-schema.md#21-consideration-1-the-schema-is-the-edge-between-two-nodes).
+[fields versus column references contract](operator-sharing.md#21-one-schema-model-for-values-and-state).
 
 Names are resolved to `ColumnId` before constructing these nodes. Parsing and
 unresolved `ColumnRef` handling remain frontend concerns; no alternative generic
diff --git a/docs/design_docs/proposals/operator-sharing.md b/docs/design_docs/proposals/operator-sharing.md
index c9ab193a4..1851d1809 100644
--- a/docs/design_docs/proposals/operator-sharing.md
+++ b/docs/design_docs/proposals/operator-sharing.md
@@ -365,13 +365,155 @@ caching or mutation mechanism.
 
 ### 2.1 One schema model for values and state
 
-Every operator output, before and after optimization, uses one `Schema` whose
-`Field`s are typed by `FieldDataType`: `Plain(DataType)` for a readable value, or
-the family, algorithm and parameters of summary or exact-accumulator state.
-`OperatorResultKind` marks state outputs, and state becomes a value only through
-an explicit readout. The schema model, `ColumnRef` versus `ColumnId`, the
-validation entry points and the readout boundary are specified in
-[Schema and physical data for ASAP primitives](asap-primitive-schema.md).
+Use one `Schema` for operator outputs before and after optimization. Rename today's
+`SummaryFamilyType` to `FieldDataType`: it types every field, and `Plain` is not a summary
+family. Rename `Column` to `Field` and `Schema.columns` to `Schema.fields`: the struct
+describes a column and holds none of its data. Retain the current `Schema` metadata.
+The following is the proposed resolved interface; it is not the current Rust definition.
+
+```rust
+struct Field {
+    name: String,
+    dtype: FieldDataType,
+    nullable: bool,
+    table: Option<String>,
+}
+
+struct Schema {
+    fields: Vec<Field>,
+    time_index: Option<ColumnId>,
+    unique_keys: Vec<Vec<ColumnId>>,
+    closed: bool,
+}
+
+// Today's `SummaryFamilyType`, renamed; variants and payloads unchanged.
+enum FieldDataType {
+    Plain(DataType),
+    ExactAggregate(ExactKind, ExactParams),
+    Sketch(SketchKind, GroupingStrategy),
+    Sample(SamplingKind, SamplingParams),
+    Wavelet(WaveletKind, WaveletParams),
+    StatModel(StatModelKind, StatModelParams),
+}
+
+// Proposed derived output classification, separate from column types.
+enum OperatorResultKind {
+    Relation,
+    InstantVector,
+    RangeVector,
+    State,
+}
+
+impl Operator {
+    fn output_schema(&self) -> Result<Schema, QueryExprError>;
+    fn output_kind(&self) -> Result<OperatorResultKind, QueryExprError>;
+    fn validate_inputs(&self) -> Result<(), QueryExprError>;
+}
+
+impl OperatorNode {
+    fn validate_structure(&self) -> Result<(), QueryExprError>;
+    fn validate_execution_timing(&self) -> Result<(), QueryExprError>;
+}
+
+impl ScalarExpr {
+    fn scalar_type(&self, input: &Schema) -> Result<(DataType, bool), QueryExprError>;
+}
+```
+
+**Fields versus column references.** These names describe different roles, not
+competing representations of the same object:
+
+| Name | Role | Holds runtime values? |
+|---|---|---|
+| `Schema` | Ordered `Field` metadata, plus key/time/closedness information | No |
+| `Field` | Name, type, nullability and optional qualifier for one output column | No |
+| `ColumnRef` | Unresolved logical reference: `Named`, `Qualified`, `SampleValue`, or `Wildcard` | No |
+| `ColumnId = usize` | Resolved column position in a particular input/output schema | No |
+| Runtime batch | Values conforming to a schema; storage layout is executor-specific | Yes |
+
+Keep `ColumnRef`, `ColumnId`, and `ScalarExpr::Column(ColumnId)`. Renaming the
+metadata struct `Column` to `Field` does not rename column references to field
+references. The same position identifies metadata during planning and values
+during execution; it is not a stable field identity across projections or joins.
+Schema `unique_keys` and `time_index` also use these column positions.
+
+For example, resolving `t.bytes` to position `1` produces `ColumnId = 1`.
+`schema.fields[1]` supplies its type and nullability; evaluating
+`ScalarExpr::Column(1)` reads the corresponding value. The native executor
+currently reads `row[1]` from `Batch { schema, rows: Vec<Vec<Value>> }`. A columnar
+executor would select array `1` instead. No physical `Column` container is
+introduced by the metadata rename, and the old metadata `Column` struct is not
+retained as a second type.
+
+**Relationship to current types.** `Field` is today's pre-ASAP `Column` with `dtype`
+widened from `DataType` to `FieldDataType`. `FieldDataType` is today's `SummaryFamilyType`
+under a name that also fits its `Plain` case. The proposed common `Schema` replaces
+the separate operator-edge roles of pre-ASAP `Schema` and post-ASAP `SummarySchema` /
+`SummaryField`; it does not rename `DataType`. A pre-ASAP value column becomes
+`Plain(dtype)`.
+Frontend validation permits only ordinary value columns, preserving the current
+pre-ASAP restriction even though the common schema can also express state.
+
+| Field | Meaning and requirement |
+|---|---|
+| `fields` | Ordered named fields. `Plain(DataType)` is a readable value; other variants retain the identity and parameters of summary or exact-accumulator state. |
+| `Field.nullable`, `Field.table` | Preserve SQL nullability and qualified column resolution. |
+| `time_index` | Identifies the time column when present; it does not by itself distinguish an instant vector from a range vector. |
+| `unique_keys` | Proven column combinations identifying rows; an empty list asserts no known key. Recompute these proofs when a rewrite changes identity. |
+| `closed` | Whether `fields` completely describes the output. An open PromQL schema must retain unlisted labels through the existing complete-series-identity contract. |
+
+`OperatorResultKind` is derived from the operation and its inputs and retained as
+`OperatorNode.result_kind`. `State` describes an output carrying unfinalized state; its
+schema may also contain ordinary grouping keys. `SummaryEstimate`,
+`FinalizeExactAccumulator` and other readouts derive the appropriate relation or
+vector kind from their operation and input context. Matching numeric columns do
+not make those kinds interchangeable.
+
+**Interface contracts.** `Operator::output_schema` and `output_kind` derive output
+metadata from the payload and validated inputs. `validate_inputs` checks local
+producer/consumer compatibility, such as vector inputs for `BinaryOp` or the
+required state family for a summary readout. Scalar typing checks the input-kind
+contract of `PromqlScalarFromVector` and other scalar plan reads.
+
+| Validation entry | Scope and stage |
+|---|---|
+| `OperatorNode::validate_structure()` | Walks the reachable operator DAG, including scalar plan references; checks input contracts, scalar typing and agreement between retained and derived output metadata. Valid for logical and physical plans; permits `timing = None`. |
+| `OperatorNode::validate_execution_timing()` | Includes structural validation, then requires assigned timing on every executable operator and checks phase dependencies. Used for executable physical candidates. |
+| Existing planner assessment and selection (#509) | Establishes guarantees using the existing accuracy models and checks them against request requirements and deployment capabilities. Neither node method re-proves a guarantee or decides request feasibility. |
+
+The two node methods need only the DAG and its annotations. Request requirements
+and deployment models remain inputs to the existing planning/selection workflow,
+not implicit globals of `validate_structure`. Passing the timing check alone does
+not establish that a physical candidate satisfies the query's accuracy requirement.
+
+`Scan.schema` declares the source columns; `Values.schema` declares the constructed
+row shape. `OperatorNode.schema` is the derived output for any operation. A scan's
+predicates cannot change its declared output columns; a Values row must match the
+declared arity, types and nullability. These leaf outputs retain the declaration's
+column layout and time/identity information, with only justified metadata changes.
+The declaration and derived output therefore have distinct roles, and structural
+validation rejects disagreement rather than trusting two independent schemas.
+
+`scalar_type` keeps the existing method name and `(DataType, nullable)` result.
+Its `input` is the applicable column scope: the child schema for a projection,
+both input schemas for a join predicate, or aggregate outputs for `HAVING`.
+Explicit subquery/conversion expressions validate their referenced producer using
+the contracts above. Numeric expressions cannot consume state columns as numbers.
+A standalone scalar expression is checked with an empty column scope and needs no fabricated
+relation output schema. `QueryExprError` retains the existing error-type name;
+result-kind, state-family, schema and execution-phase mismatches require
+corresponding validation errors.
+
+For example, a KLL build outputs `State` with a
+`Sketch(SketchKind, GroupingStrategy)` column identifying KLL and its parameters.
+Its p99 readout outputs an ordinary `Plain(Float64)` column in the appropriate
+relation/vector schema. A numeric predicate can use that readout, but not the KLL
+state. Exact accumulator state similarly requires `FinalizeExactAccumulator`.
+An ordinary operator may pass state through only where its input/output contract
+permits it. A bare-column projection can preserve the field's `FieldDataType`
+directly during `output_schema` derivation; `scalar_type` applies when that column
+is used as a scalar value and rejects state. Copying a state column does not turn
+it into a readable scalar.
 
 ### 2.2 Preserve existing accuracy semantics
 
diff --git a/docs/design_docs/proposals/univmon-frequency-summary.md b/docs/design_docs/proposals/univmon-frequency-summary.md
index a2d9f96c1..75cfd080b 100644
--- a/docs/design_docs/proposals/univmon-frequency-summary.md
+++ b/docs/design_docs/proposals/univmon-frequency-summary.md
@@ -35,8 +35,7 @@ cardinality alternatives, and exact count remains the cheaper first count
 candidate.
 
 All four readouts have the same unit-weight update, input sub-DAG, grouping,
-window, parameter identity and state schema
-([ASAP primitive schema](asap-primitive-schema.md)). Existing post-ASAP structural
+window, parameter identity and state schema. Existing post-ASAP structural
 sharing can therefore intern their state producer while preserving distinct
 readout nodes. Sharing is only legal within the same execution/data scope.
 Precompute placement, SummaryCatalog installation, retention, and runtime
diff --git a/docs/develop_docs/asap-aware-mapping-contracts.md b/docs/develop_docs/asap-aware-mapping-contracts.md
index 011758143..447cb3823 100644
--- a/docs/develop_docs/asap-aware-mapping-contracts.md
+++ b/docs/develop_docs/asap-aware-mapping-contracts.md
@@ -325,12 +325,24 @@ backend inspection. Automatic selection skips those unproven ratios. Use
 
 ### Family, category, algorithm, and parameters
 
-A summary's identity has four levels: family (`FieldDataType` variant), sketch
-category (`SketchCategory`), algorithm (`SketchAlgorithm`), and the validated
-committed choice (`SketchKind`). The levels and their validation are specified in
-[Schema and physical data for ASAP primitives](../design_docs/proposals/asap-primitive-schema.md#22-consideration-2-a-field-can-have-an-asap-primitive-type).
+Sketches separate their query category from the concrete algorithm and its parameters:
 
-Where this matters in practice: `CostModel::rank_candidates`, `CostModel::size_params`, and `SketchAlgorithmStrategy::replacements` operate at the **algorithm** level. `summary_candidates(intent)` returns a list of `SketchAlgorithm`s (`[Kll, DDSketch]` for a `Quantile` intent), never a bare `SketchKind` with nothing chosen underneath it. `SketchKind` appears after an algorithm has been selected and sized—on `Realization::Sketch(SketchKind)` and `FieldDataType::Sketch(SketchKind, GroupingStrategy)`.
+| Level | Type | Example |
+| --- | --- | --- |
+| **family** | `SummaryFamilyType` | `Sketch`, `Sample`, `Wavelet`, `StatModel`, `ExactAggregate` |
+| **category** | `SketchCategory` | `Quantile`, `Cardinality`, `Frequency`, `TopK` |
+| **algorithm** | `SketchAlgorithm` | `Kll` / `DDSketch` (both quantile); `Hll` (HyperLogLog) / `Theta` / `Kmv` (K-Minimum Values), all cardinality |
+| **committed choice** | `SketchKind` | one validated category + algorithm + parameter combination |
+
+A `SketchKind` is a validated committed choice. Its public constructor,
+`SketchKind::new(algorithm, params)`, verifies that the parameter variant belongs
+to the selected algorithm and classifies the pair into its category. The public
+`.category()`, `.algorithm()`, and `.params()` accessors expose the committed
+values without permitting an invalid combination.
+
+Where this matters in practice: `CostModel::rank_candidates`, `CostModel::size_params`, and `SketchAlgorithmStrategy::replacements` operate at the **algorithm** level. `summary_candidates(intent)` returns a list of `SketchAlgorithm`s (`[Kll, DDSketch]` for a `Quantile` intent), never a bare `SketchKind` with nothing chosen underneath it. `SketchKind` appears after an algorithm has been selected and sized—on `Realization::Sketch(SketchKind)` and `SummaryFamilyType::Sketch(SketchKind)`.
+
+`Sample`, `Wavelet`, and `StatModel` each use a flat `(Kind, Params)` pair. `Sketch` needs the additional algorithm level because multiple algorithms can serve the same purpose—for example, KLL and DDSketch both answer quantile queries.
 
 ---
 
@@ -366,7 +378,7 @@ The crate provides no default `Matcher` implementation because the answer depend
 
 Concretely, `explanation.rs` reports three candidate kinds from each `TargetSubDAGCandidates`:
 
-- `ExplanationKind::SketchApproximation` — the set contains a `Replacement::Summary` that realizes `FieldDataType::Sketch(..)`, not just an exact/pass-through candidate.
+- `ExplanationKind::SketchApproximation` — the set contains a `Replacement::Summary` that realizes `SummaryFamilyType::Sketch(..)`, not just an exact/pass-through candidate.
 - `ExplanationKind::CommonSubexpressionReuse` — `consumer_count >= 2` and the set contains `SharedSubDAGStrategy`'s "build once and share" candidate (the `Replacement::Rewrite` whose `Rc` is the set's `target`).
 
 - `ExplanationKind::ExactComposition` — the candidate set contains an exact operation
diff --git a/docs/develop_docs/pre-asap-ir.md b/docs/develop_docs/pre-asap-ir.md
index 2492e28d7..abf5dc50b 100644
--- a/docs/develop_docs/pre-asap-ir.md
+++ b/docs/develop_docs/pre-asap-ir.md
@@ -17,10 +17,26 @@ The pre-ASAP IR is defined using the `QueryExpr` enum. We discuss some of import
 
 ## Fields and column references
 
-`Schema` holds `Field` metadata (name, type, nullability, qualifier) and no
-values; an unresolved `ColumnRef` resolves to a positional `ColumnId` within one
-schema. The design, including how the same position selects a runtime value, is
-in [Schema and physical data for ASAP primitives](../design_docs/proposals/asap-primitive-schema.md#21-consideration-1-the-schema-is-the-edge-between-two-nodes).
+`Schema` owns `Field` metadata: name, type, nullability, and an optional table
+qualifier. A `Field` contains no runtime values. The former schema `Column`
+struct served this same metadata role; it was renamed to `Field`, not retained
+as a second data container.
+
+`ColumnRef` is an unresolved logical reference (`Named`, `Qualified`,
+`SampleValue`, or `Wildcard`). Resolution binds a reference to `ColumnId`, a
+`usize` position within a particular schema. `QueryExpr::Column(ColumnId)`
+reads that column; the same position indexes `Schema::fields` for type checking
+and a runtime row for its value. Group keys, unique keys, and `time_index` also
+use these column positions. They are not stable identities across projections
+or joins, so the positional reference remains `ColumnId`, not `FieldId`.
+
+The native runtime names shared ownership `SchemaRef = Arc<Schema>` and stores
+`Batch { schema: SchemaRef, rows: Vec<Vec<Value>> }`. `Schema` is the same metadata
+model during planning and execution; the `Ref` suffix only distinguishes ownership.
+It has no physical `Column`/array container. A column reference expresses what
+to read independently of whether an executor stores its data as rows or arrays.
+For example, resolving `t.bytes` to `ColumnId = 1` obtains its type from
+`schema.fields[1]`; native execution reads `row[1]`.
 
 ## Node index
 

From 1653cb4a81cd2296654cb0cab5a08416b1e8baaa Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 14:35:57 +0000
Subject: [PATCH 17/48] feat(ir): define compatible logical summary merges

---
 crates/types/src/ir/asap.rs                   | 63 ++++++++++++++-----
 crates/types/tests/summary_merge_structure.rs | 53 ++++++++++++++++
 2 files changed, 102 insertions(+), 14 deletions(-)
 create mode 100644 crates/types/tests/summary_merge_structure.rs

diff --git a/crates/types/src/ir/asap.rs b/crates/types/src/ir/asap.rs
index faee35c5f..0159341ec 100644
--- a/crates/types/src/ir/asap.rs
+++ b/crates/types/src/ir/asap.rs
@@ -39,9 +39,7 @@ pub enum ASAPOp {
     },
     /// Read an exact accumulator's state as its finalized value: the
     /// maintenance-to-read boundary before query-time operators.
-    FinalizeExactAccumulator {
-        child: Rc<OperatorNode>,
-    },
+    FinalizeExactAccumulator { child: Rc<OperatorNode> },
     /// Maintain the full declared population, including membership changes.
     MaintainPopulation {
         child: Rc<OperatorNode>,
@@ -52,10 +50,9 @@ pub enum ASAPOp {
         child: Rc<OperatorNode>,
         evaluation: PopulationStatistic,
     },
-    // ── Reserved: migrated but unimplemented (§1.3 of the proposal) ──
-    SummaryMerge {
-        children: Vec<Rc<OperatorNode>>,
-    },
+    /// Merge compatible partial states for the same grouping and family.
+    SummaryMerge { children: Vec<Rc<OperatorNode>> },
+    // ── Reserved: migrated but unimplemented ──
     SummarySubtract {
         left: Rc<OperatorNode>,
         right: Rc<OperatorNode>,
@@ -186,11 +183,7 @@ impl ASAPOp {
         use ASAPOp::*;
         matches!(
             self,
-            SummaryMerge { .. }
-                | SummarySubtract { .. }
-                | SummaryDelete { .. }
-                | SummaryJoin { .. }
-                | Extension { .. }
+            SummarySubtract { .. } | SummaryDelete { .. } | SummaryJoin { .. } | Extension { .. }
         )
     }
 
@@ -202,6 +195,14 @@ impl ASAPOp {
     pub fn produced_state(&self) -> Option<&FieldDataType> {
         match self {
             ASAPOp::SummaryAgg { family, .. } | ASAPOp::SummaryJoin { family, .. } => Some(family),
+            ASAPOp::SummaryMerge { children } => children.first().and_then(|child| {
+                child
+                    .schema
+                    .fields
+                    .iter()
+                    .find(|field| !field.is_plain())
+                    .map(|field| &field.dtype)
+            }),
             _ => None,
         }
     }
@@ -405,8 +406,11 @@ impl ASAPOp {
                     .output_schema()?
                 }
             }
-            SummaryMerge { .. }
-            | SummarySubtract { .. }
+            SummaryMerge { children } => {
+                self.validate_inputs()?;
+                children[0].schema.clone()
+            }
+            SummarySubtract { .. }
             | SummaryDelete { .. }
             | SummaryJoin { .. }
             | Extension { .. } => return Err(Self::unimplemented()),
@@ -444,6 +448,37 @@ impl ASAPOp {
             }
         };
         match self {
+            SummaryMerge { children } => {
+                let Some(first) = children.first() else {
+                    return Err(SchemaDerivationError::InvalidScalarSignature(
+                        "summary merge requires at least one state input".into(),
+                    ));
+                };
+                // Matching state parameters and grouping positions are necessary;
+                // matching names alone cannot prove two states compatible.
+                if first
+                    .schema
+                    .fields
+                    .iter()
+                    .filter(|field| !field.is_plain())
+                    .count()
+                    != 1
+                {
+                    return Err(SchemaDerivationError::InvalidScalarSignature(
+                        "summary merge requires exactly one state column".into(),
+                    ));
+                }
+                for child in children {
+                    needs_state(child, "SummaryMerge")?;
+                    if child.schema != first.schema {
+                        return Err(SchemaDerivationError::InvalidScalarSignature(
+                            "summary merge inputs must have identical state and grouping schemas"
+                                .into(),
+                        ));
+                    }
+                }
+                Ok(())
+            }
             SummaryEstimate {
                 summary_input,
                 query,
diff --git a/crates/types/tests/summary_merge_structure.rs b/crates/types/tests/summary_merge_structure.rs
new file mode 100644
index 000000000..999ee95f7
--- /dev/null
+++ b/crates/types/tests/summary_merge_structure.rs
@@ -0,0 +1,53 @@
+//! Window composition merges compatible summary states without consuming raw rows.
+use asap_types::{
+    ir::operator_properties::{Reduction, Source},
+    ir::{ASAPOp, NonASAPOp, Operator, OperatorNode},
+    post_asap::{GroupingStrategy, SketchAlgorithm, SketchKind, SketchParams, SummaryUpdate},
+    pre_asap::{ColumnRef, DataType, Field, FieldDataType, Schema},
+};
+use std::rc::Rc;
+fn state(k: u32) -> Rc<OperatorNode> {
+    let scan = OperatorNode::new_shared(Operator::NonASAP(NonASAPOp::Scan {
+        source: Source::Table {
+            table_ref: "latencies".into(),
+        },
+        predicates: vec![],
+        schema: Schema::new(vec![Field::plain("value", DataType::Float64, false)]),
+    }))
+    .unwrap();
+    OperatorNode::new_shared(Operator::ASAP(ASAPOp::SummaryAgg {
+        child: scan,
+        family: FieldDataType::Sketch(
+            SketchKind::new(SketchAlgorithm::Kll, SketchParams::Kll { k }),
+            Default::default(),
+        ),
+        input: SummaryUpdate::column(ColumnRef::SampleValue),
+        reduction: Reduction::by(vec![]),
+        grouping: GroupingStrategy::default(),
+        filter: None,
+    }))
+    .unwrap()
+}
+/// Two KLL panes compose into one typed logical state without timing assignment.
+#[test]
+fn compatible_panes_merge_structurally() {
+    let root = OperatorNode::new_shared(Operator::ASAP(ASAPOp::SummaryMerge {
+        children: vec![state(200), state(200)],
+    }))
+    .unwrap();
+    root.validate_structure().unwrap();
+    assert_eq!(root.schema.fields.len(), 1);
+}
+/// An empty merge, raw rows and differently sized state cannot masquerade as compatible panes.
+#[test]
+fn incompatible_merge_inputs_fail() {
+    for children in [
+        vec![],
+        vec![state(200), state(300)],
+        vec![state(200).children()[0].clone()],
+    ] {
+        assert!(
+            OperatorNode::new_shared(Operator::ASAP(ASAPOp::SummaryMerge { children })).is_err()
+        );
+    }
+}

From 182160a6e978c90a3114623353d6d7fd958a7ba8 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 16:03:55 +0000
Subject: [PATCH 18/48] feat(ir): require disjoint coverage for summary merges

---
 crates/types/src/ir/asap.rs                   | 24 +++++++
 crates/types/src/ir/node.rs                   | 13 +++-
 crates/types/tests/summary_merge_structure.rs | 62 ++++++++++++++++++-
 3 files changed, 95 insertions(+), 4 deletions(-)

diff --git a/crates/types/src/ir/asap.rs b/crates/types/src/ir/asap.rs
index 0159341ec..5984007b8 100644
--- a/crates/types/src/ir/asap.rs
+++ b/crates/types/src/ir/asap.rs
@@ -207,6 +207,29 @@ impl ASAPOp {
         }
     }
 
+    /// Derive joint observation coverage; unknown or overlapping inputs fail closed.
+    pub fn merged_extent(
+        &self,
+    ) -> Result<super::observation_extent::ObservationExtent, SchemaDerivationError> {
+        let ASAPOp::SummaryMerge { children } = self else {
+            return Err(SchemaDerivationError::InvalidScalarSignature(
+                "coverage merge requires SummaryMerge".into(),
+            ));
+        };
+        let inputs = children
+            .iter()
+            .map(|child| {
+                child.observation_extent.clone().ok_or_else(|| {
+                    SchemaDerivationError::InvalidScalarSignature(
+                        "summary merge requires known observation coverage".into(),
+                    )
+                })
+            })
+            .collect::<Result<Vec<_>, _>>()?;
+        super::observation_extent::ObservationExtent::merge_disjoint(&inputs)
+            .map_err(|error| SchemaDerivationError::InvalidScalarSignature(error.to_string()))
+    }
+
     /// Output schema derived from the operator and its children. Summary
     /// planning may retain a more specific schema (evaluation column naming)
     /// through [`OperatorNode::with_schema`]; all structural metadata must
@@ -477,6 +500,7 @@ impl ASAPOp {
                         ));
                     }
                 }
+                self.merged_extent()?;
                 Ok(())
             }
             SummaryEstimate {
diff --git a/crates/types/src/ir/node.rs b/crates/types/src/ir/node.rs
index 392204d9a..71fe2d783 100644
--- a/crates/types/src/ir/node.rs
+++ b/crates/types/src/ir/node.rs
@@ -106,7 +106,11 @@ impl OperatorNode {
     /// ASAP operator, ...).
     pub fn new(operator: Operator) -> Result<Self, SchemaDerivationError> {
         let schema = operator.output_schema()?;
-        Ok(Self::with_schema(operator, schema))
+        let mut node = Self::with_schema(operator, schema);
+        if let Some(op @ ASAPOp::SummaryMerge { .. }) = node.asap() {
+            node.observation_extent = Some(op.merged_extent()?);
+        }
+        Ok(node)
     }
 
     /// Build a node with caller-supplied output names and qualifiers. For
@@ -316,6 +320,13 @@ impl OperatorNode {
                 None if node.requires_coverage() => return Err(CoverageError::Missing.into()),
                 None => {}
             }
+            if let Some(op @ ASAPOp::SummaryMerge { .. }) = node.asap() {
+                if node.observation_extent.as_ref() != Some(&op.merged_extent()?) {
+                    return Err(SchemaDerivationError::InvalidScalarSignature(
+                        "retained merge coverage disagrees with input union".into(),
+                    ));
+                }
+            }
             node.operator.validate_inputs()?;
             if node.result_kind != node.operator.output_kind() {
                 return Err(SchemaDerivationError::InvalidScalarSignature(
diff --git a/crates/types/tests/summary_merge_structure.rs b/crates/types/tests/summary_merge_structure.rs
index 999ee95f7..5c8b0c132 100644
--- a/crates/types/tests/summary_merge_structure.rs
+++ b/crates/types/tests/summary_merge_structure.rs
@@ -15,7 +15,7 @@ fn state(k: u32) -> Rc<OperatorNode> {
         schema: Schema::new(vec![Field::plain("value", DataType::Float64, false)]),
     }))
     .unwrap();
-    OperatorNode::new_shared(Operator::ASAP(ASAPOp::SummaryAgg {
+    let summary = OperatorNode::new(Operator::ASAP(ASAPOp::SummaryAgg {
         child: scan,
         family: FieldDataType::Sketch(
             SketchKind::new(SketchAlgorithm::Kll, SketchParams::Kll { k }),
@@ -26,17 +26,38 @@ fn state(k: u32) -> Rc<OperatorNode> {
         grouping: GroupingStrategy::default(),
         filter: None,
     }))
-    .unwrap()
+    .unwrap();
+    std::rc::Rc::new(
+        summary
+            .with_observation_extent(asap_types::ir::observation_extent::ObservationExtent {
+                source: "latencies:timestamp".into(),
+                revision: "fixture-1".into(),
+                input: SummaryUpdate::column(ColumnRef::SampleValue),
+                grouping: Reduction::by(vec![]),
+                multiplicity:
+                    asap_types::ir::observation_extent::ObservationMultiplicity::OncePerObservation,
+                regions: vec![asap_types::ir::observation_extent::ExtentRegion {
+                    start_ms: 0,
+                    end_ms: 1,
+                    population: Default::default(),
+                }],
+            })
+            .unwrap(),
+    )
 }
 /// Two KLL panes compose into one typed logical state without timing assignment.
 #[test]
 fn compatible_panes_merge_structurally() {
     let root = OperatorNode::new_shared(Operator::ASAP(ASAPOp::SummaryMerge {
-        children: vec![state(200), state(200)],
+        children: vec![state(200), shifted_state(200, 1, 2)],
     }))
     .unwrap();
     root.validate_structure().unwrap();
     assert_eq!(root.schema.fields.len(), 1);
+    assert_eq!(
+        root.observation_extent.as_ref().unwrap().regions[0].end_ms,
+        2
+    );
 }
 /// An empty merge, raw rows and differently sized state cannot masquerade as compatible panes.
 #[test]
@@ -51,3 +72,38 @@ fn incompatible_merge_inputs_fail() {
         );
     }
 }
+
+fn shifted_state(k: u32, start: i64, end: i64) -> Rc<OperatorNode> {
+    let mut node = (*state(k)).clone();
+    let region = &mut node.observation_extent.as_mut().unwrap().regions[0];
+    region.start_ms = start;
+    region.end_ms = end;
+    Rc::new(node)
+}
+/// Schema equality cannot authorize overlapping or unknown observation coverage.
+#[test]
+fn unsafe_coverage_merge_is_rejected() {
+    let mut unknown = (*state(200)).clone();
+    unknown.observation_extent = None;
+    for children in [
+        vec![state(200), state(200)],
+        vec![state(200), Rc::new(unknown)],
+    ] {
+        assert!(
+            OperatorNode::new_shared(Operator::ASAP(ASAPOp::SummaryMerge { children })).is_err()
+        );
+    }
+}
+
+/// Gapped time coverage remains disconnected, and forged output metadata is rejected.
+#[test]
+fn merge_derives_coverage_and_validates_retained_metadata() {
+    let root = OperatorNode::new_shared(Operator::ASAP(ASAPOp::SummaryMerge {
+        children: vec![state(200), shifted_state(200, 2, 3)],
+    }))
+    .unwrap();
+    assert_eq!(root.observation_extent.as_ref().unwrap().regions.len(), 2);
+    let mut forged = (*root).clone();
+    forged.observation_extent.as_mut().unwrap().regions[0].end_ms = 2;
+    assert!(Rc::new(forged).validate_structure().is_err());
+}

From 05df2fba5a9e63e41778d6484f0e9baf49380c1a Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 16:57:54 +0000
Subject: [PATCH 19/48] refactor(ir): use SummaryCoverage names in summary
 merges

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/types/src/ir/asap.rs                   | 20 +++++---------
 crates/types/src/ir/node.rs                   | 13 ++++-----
 crates/types/src/ir/summary_coverage.rs       |  4 +++
 crates/types/tests/summary_merge_structure.rs | 27 ++++++++-----------
 4 files changed, 28 insertions(+), 36 deletions(-)

diff --git a/crates/types/src/ir/asap.rs b/crates/types/src/ir/asap.rs
index 5984007b8..236f834f1 100644
--- a/crates/types/src/ir/asap.rs
+++ b/crates/types/src/ir/asap.rs
@@ -6,6 +6,7 @@ use std::rc::Rc;
 use serde::{Deserialize, Serialize};
 
 use super::node::{OperatorNode, OperatorResultKind};
+use super::summary_coverage::{CoverageError, SummaryCoverage};
 use crate::ir::operator_properties::Reduction;
 use crate::ir::SchemaDerivationError;
 use crate::post_asap::maintained_population::{MaintainedPopulation, PopulationStatistic};
@@ -207,10 +208,8 @@ impl ASAPOp {
         }
     }
 
-    /// Derive joint observation coverage; unknown or overlapping inputs fail closed.
-    pub fn merged_extent(
-        &self,
-    ) -> Result<super::observation_extent::ObservationExtent, SchemaDerivationError> {
+    /// Derive the merged node's coverage; unknown or overlapping inputs fail closed.
+    pub fn merged_coverage(&self) -> Result<SummaryCoverage, SchemaDerivationError> {
         let ASAPOp::SummaryMerge { children } = self else {
             return Err(SchemaDerivationError::InvalidScalarSignature(
                 "coverage merge requires SummaryMerge".into(),
@@ -218,16 +217,9 @@ impl ASAPOp {
         };
         let inputs = children
             .iter()
-            .map(|child| {
-                child.observation_extent.clone().ok_or_else(|| {
-                    SchemaDerivationError::InvalidScalarSignature(
-                        "summary merge requires known observation coverage".into(),
-                    )
-                })
-            })
+            .map(|child| child.coverage.clone().ok_or(CoverageError::UnknownInput))
             .collect::<Result<Vec<_>, _>>()?;
-        super::observation_extent::ObservationExtent::merge_disjoint(&inputs)
-            .map_err(|error| SchemaDerivationError::InvalidScalarSignature(error.to_string()))
+        Ok(SummaryCoverage::merge_disjoint(&inputs)?)
     }
 
     /// Output schema derived from the operator and its children. Summary
@@ -500,7 +492,7 @@ impl ASAPOp {
                         ));
                     }
                 }
-                self.merged_extent()?;
+                self.merged_coverage()?;
                 Ok(())
             }
             SummaryEstimate {
diff --git a/crates/types/src/ir/node.rs b/crates/types/src/ir/node.rs
index 71fe2d783..8d0cbabd7 100644
--- a/crates/types/src/ir/node.rs
+++ b/crates/types/src/ir/node.rs
@@ -108,7 +108,7 @@ impl OperatorNode {
         let schema = operator.output_schema()?;
         let mut node = Self::with_schema(operator, schema);
         if let Some(op @ ASAPOp::SummaryMerge { .. }) = node.asap() {
-            node.observation_extent = Some(op.merged_extent()?);
+            node.coverage = Some(op.merged_coverage()?);
         }
         Ok(node)
     }
@@ -161,7 +161,10 @@ impl OperatorNode {
 
     /// Summary nodes whose state can be composed must declare coverage.
     pub fn requires_coverage(&self) -> bool {
-        matches!(self.asap(), Some(ASAPOp::SummaryAgg { .. }))
+        matches!(
+            self.asap(),
+            Some(ASAPOp::SummaryAgg { .. } | ASAPOp::SummaryMerge { .. })
+        )
     }
 
     pub fn non_asap(&self) -> Option<&NonASAPOp> {
@@ -321,10 +324,8 @@ impl OperatorNode {
                 None => {}
             }
             if let Some(op @ ASAPOp::SummaryMerge { .. }) = node.asap() {
-                if node.observation_extent.as_ref() != Some(&op.merged_extent()?) {
-                    return Err(SchemaDerivationError::InvalidScalarSignature(
-                        "retained merge coverage disagrees with input union".into(),
-                    ));
+                if node.coverage.as_ref() != Some(&op.merged_coverage()?) {
+                    return Err(CoverageError::MergeOutputMismatch.into());
                 }
             }
             node.operator.validate_inputs()?;
diff --git a/crates/types/src/ir/summary_coverage.rs b/crates/types/src/ir/summary_coverage.rs
index a95896eb8..747f87f76 100644
--- a/crates/types/src/ir/summary_coverage.rs
+++ b/crates/types/src/ir/summary_coverage.rs
@@ -43,6 +43,10 @@ pub enum CoverageError {
     NotState,
     #[error("summary node requires coverage")]
     Missing,
+    #[error("summary merge requires known coverage on every input")]
+    UnknownInput,
+    #[error("retained merge coverage disagrees with input union")]
+    MergeOutputMismatch,
 }
 
 impl SummaryCoverage {
diff --git a/crates/types/tests/summary_merge_structure.rs b/crates/types/tests/summary_merge_structure.rs
index 5c8b0c132..6489159af 100644
--- a/crates/types/tests/summary_merge_structure.rs
+++ b/crates/types/tests/summary_merge_structure.rs
@@ -29,16 +29,12 @@ fn state(k: u32) -> Rc<OperatorNode> {
     .unwrap();
     std::rc::Rc::new(
         summary
-            .with_observation_extent(asap_types::ir::observation_extent::ObservationExtent {
+            .with_coverage(asap_types::ir::summary_coverage::SummaryCoverage {
                 source: "latencies:timestamp".into(),
-                revision: "fixture-1".into(),
                 input: SummaryUpdate::column(ColumnRef::SampleValue),
-                grouping: Reduction::by(vec![]),
-                multiplicity:
-                    asap_types::ir::observation_extent::ObservationMultiplicity::OncePerObservation,
-                regions: vec![asap_types::ir::observation_extent::ExtentRegion {
-                    start_ms: 0,
-                    end_ms: 1,
+                reduction: Reduction::by(vec![]),
+                regions: vec![asap_types::ir::summary_coverage::CoverageRegion {
+                    time_ms: Some(0..1),
                     population: Default::default(),
                 }],
             })
@@ -55,8 +51,8 @@ fn compatible_panes_merge_structurally() {
     root.validate_structure().unwrap();
     assert_eq!(root.schema.fields.len(), 1);
     assert_eq!(
-        root.observation_extent.as_ref().unwrap().regions[0].end_ms,
-        2
+        root.coverage.as_ref().unwrap().regions[0].time_ms,
+        Some(0..2)
     );
 }
 /// An empty merge, raw rows and differently sized state cannot masquerade as compatible panes.
@@ -75,16 +71,15 @@ fn incompatible_merge_inputs_fail() {
 
 fn shifted_state(k: u32, start: i64, end: i64) -> Rc<OperatorNode> {
     let mut node = (*state(k)).clone();
-    let region = &mut node.observation_extent.as_mut().unwrap().regions[0];
-    region.start_ms = start;
-    region.end_ms = end;
+    let region = &mut node.coverage.as_mut().unwrap().regions[0];
+    region.time_ms = Some(start..end);
     Rc::new(node)
 }
 /// Schema equality cannot authorize overlapping or unknown observation coverage.
 #[test]
 fn unsafe_coverage_merge_is_rejected() {
     let mut unknown = (*state(200)).clone();
-    unknown.observation_extent = None;
+    unknown.coverage = None;
     for children in [
         vec![state(200), state(200)],
         vec![state(200), Rc::new(unknown)],
@@ -102,8 +97,8 @@ fn merge_derives_coverage_and_validates_retained_metadata() {
         children: vec![state(200), shifted_state(200, 2, 3)],
     }))
     .unwrap();
-    assert_eq!(root.observation_extent.as_ref().unwrap().regions.len(), 2);
+    assert_eq!(root.coverage.as_ref().unwrap().regions.len(), 2);
     let mut forged = (*root).clone();
-    forged.observation_extent.as_mut().unwrap().regions[0].end_ms = 2;
+    forged.coverage.as_mut().unwrap().regions[0].time_ms = Some(0..2);
     assert!(Rc::new(forged).validate_structure().is_err());
 }

From 9440d33e2c18e47b272c23a6305b53cb2d1011f8 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 17:33:53 +0000
Subject: [PATCH 20/48] feat(ir): check merge update/reduction on producers;
 test documented coverage examples

SummaryCoverage no longer repeats input/reduction, so SummaryMerge compares
them through OperatorNode::summary_update. summary_coverage_examples.rs builds
each example in docs/develop_docs/summary-coverage.md as a SummaryAgg ->
SummaryMerge plan.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/types/src/ir/asap.rs                   |   8 +
 crates/types/src/ir/node.rs                   |  14 +
 .../types/tests/summary_coverage_examples.rs  | 264 ++++++++++++++++++
 crates/types/tests/summary_merge_structure.rs |   6 +-
 4 files changed, 289 insertions(+), 3 deletions(-)
 create mode 100644 crates/types/tests/summary_coverage_examples.rs

diff --git a/crates/types/src/ir/asap.rs b/crates/types/src/ir/asap.rs
index 236f834f1..b9fbcf6f5 100644
--- a/crates/types/src/ir/asap.rs
+++ b/crates/types/src/ir/asap.rs
@@ -492,6 +492,14 @@ impl ASAPOp {
                         ));
                     }
                 }
+                // Coverage records only time and population; what each state
+                // summarizes and how it is grouped come from the producers.
+                let update = first.summary_update();
+                if update.is_none() || children.iter().any(|c| c.summary_update() != update) {
+                    return Err(SchemaDerivationError::InvalidScalarSignature(
+                        "summary merge inputs must share update expression and reduction".into(),
+                    ));
+                }
                 self.merged_coverage()?;
                 Ok(())
             }
diff --git a/crates/types/src/ir/node.rs b/crates/types/src/ir/node.rs
index 8d0cbabd7..cc71d32e5 100644
--- a/crates/types/src/ir/node.rs
+++ b/crates/types/src/ir/node.rs
@@ -10,10 +10,12 @@ use serde::{Deserialize, Serialize};
 
 use super::asap::ASAPOp;
 use super::non_asap::NonASAPOp;
+use super::operator_properties::Reduction;
 use super::summary_coverage::{CoverageError, SummaryCoverage};
 use crate::ir::SchemaDerivationError;
 use crate::post_asap::execution_data_state::ExecutionTiming;
 use crate::post_asap::guarantee::ResultGuarantee;
+use crate::post_asap::SummaryUpdate;
 use crate::pre_asap::schema::Schema;
 
 /// The output category of an operator, derived from the operation and its
@@ -159,6 +161,18 @@ impl OperatorNode {
         Ok(self)
     }
 
+    /// What a summary state is updated with and how it is grouped: the
+    /// `SummaryAgg` fields, or those shared by a `SummaryMerge`'s inputs.
+    pub fn summary_update(&self) -> Option<(&SummaryUpdate, &Reduction)> {
+        match self.asap()? {
+            ASAPOp::SummaryAgg {
+                input, reduction, ..
+            } => Some((input, reduction)),
+            ASAPOp::SummaryMerge { children } => children.first()?.summary_update(),
+            _ => None,
+        }
+    }
+
     /// Summary nodes whose state can be composed must declare coverage.
     pub fn requires_coverage(&self) -> bool {
         matches!(
diff --git a/crates/types/tests/summary_coverage_examples.rs b/crates/types/tests/summary_coverage_examples.rs
new file mode 100644
index 000000000..e2fad07ab
--- /dev/null
+++ b/crates/types/tests/summary_coverage_examples.rs
@@ -0,0 +1,264 @@
+//! The examples in docs/develop_docs/summary-coverage.md, built as real
+//! SummaryAgg -> SummaryMerge plans. Every input has the same schema
+//! `(job: Utf8, state: KLL{k=200})`; only coverage differs.
+use asap_types::ir::summary_coverage::{CoverageError, CoverageRegion, SummaryCoverage};
+use asap_types::ir::{
+    ASAPOp, ExprSemantics, NonASAPOp, Operator, OperatorNode, Predicate, ScalarExpr,
+    SchemaDerivationError,
+};
+use asap_types::post_asap::{
+    GroupingStrategy, SketchAlgorithm, SketchKind, SketchParams, SummaryUpdate,
+};
+use asap_types::pre_asap::{
+    ColumnRef, CompareOpKind, DataType, Field, FieldDataType, Reduction, ScalarValue, Schema,
+    Source,
+};
+use std::rc::Rc;
+
+const MIN: i64 = 60_000;
+
+fn requests() -> Source {
+    Source::Table {
+        table_ref: "requests".into(),
+    }
+}
+
+fn scan() -> Rc<OperatorNode> {
+    OperatorNode::new_shared(Operator::NonASAP(NonASAPOp::Scan {
+        source: requests(),
+        predicates: vec![],
+        schema: Schema::new(vec![
+            Field::plain("job", DataType::Utf8, false),
+            Field::plain("region", DataType::Utf8, false),
+            Field::plain("tier", DataType::Utf8, false),
+            Field::plain("latency", DataType::Float64, false),
+            Field::plain("size", DataType::Float64, false),
+        ]),
+    }))
+    .unwrap()
+}
+
+/// `region = value`, evaluated on the scan schema.
+fn region_is(value: &str) -> Predicate {
+    Predicate(ScalarExpr::Compare {
+        left: Box::new(ScalarExpr::Column(1)),
+        op: CompareOpKind::Eq,
+        right: Box::new(ScalarExpr::Literal(ScalarValue::Utf8(value.into()))),
+        semantics: ExprSemantics::Sql,
+    })
+}
+
+fn region(time_ms: Option<std::ops::Range<i64>>, population: &[(&str, &str)]) -> CoverageRegion {
+    CoverageRegion {
+        time_ms,
+        population: population
+            .iter()
+            .map(|(k, v)| (k.to_string(), v.to_string()))
+            .collect(),
+    }
+}
+
+/// p99-ready KLL over `column`, grouped by job, with declared coverage.
+fn kll_over(
+    column: &str,
+    filter: Option<Predicate>,
+    coverage: SummaryCoverage,
+) -> Rc<OperatorNode> {
+    let node = OperatorNode::new(Operator::ASAP(ASAPOp::SummaryAgg {
+        child: scan(),
+        family: FieldDataType::Sketch(
+            SketchKind::new(SketchAlgorithm::Kll, SketchParams::Kll { k: 200 }),
+            GroupingStrategy::default(),
+        ),
+        input: SummaryUpdate::column(ColumnRef::Named(column.into())),
+        reduction: Reduction::by(vec![0]),
+        grouping: GroupingStrategy::default(),
+        filter,
+    }))
+    .unwrap();
+    Rc::new(node.with_coverage(coverage).unwrap())
+}
+
+fn kll(time_ms: Option<std::ops::Range<i64>>, population: &[(&str, &str)]) -> Rc<OperatorNode> {
+    kll_over(
+        "latency",
+        None,
+        SummaryCoverage {
+            source: requests(),
+            regions: vec![region(time_ms, population)],
+        },
+    )
+}
+
+fn merge(children: Vec<Rc<OperatorNode>>) -> Result<Rc<OperatorNode>, SchemaDerivationError> {
+    let schema = children[0].schema.clone();
+    let merged = OperatorNode::new_shared(Operator::ASAP(ASAPOp::SummaryMerge { children }))?;
+    merged.validate_structure()?;
+    // Schema never changes; only coverage does.
+    assert_eq!(merged.schema, schema);
+    Ok(merged)
+}
+
+fn regions(node: &OperatorNode) -> Vec<CoverageRegion> {
+    node.coverage.as_ref().unwrap().regions.clone()
+}
+
+fn rejected(result: Result<Rc<OperatorNode>, SchemaDerivationError>, expected: CoverageError) {
+    match result {
+        Err(SchemaDerivationError::Coverage(actual)) => assert_eq!(actual, expected),
+        other => panic!("expected {expected:?}, got {other:?}"),
+    }
+}
+
+/// Example 1: adjacent panes coalesce, gaps stay, overlapping windows are rejected.
+#[test]
+fn example_1_time() {
+    let adjacent = merge(vec![kll(Some(0..MIN), &[]), kll(Some(MIN..2 * MIN), &[])]).unwrap();
+    assert_eq!(regions(&adjacent), vec![region(Some(0..2 * MIN), &[])]);
+
+    let gapped = merge(vec![
+        kll(Some(0..MIN), &[]),
+        kll(Some(2 * MIN..3 * MIN), &[]),
+    ])
+    .unwrap();
+    assert_eq!(
+        regions(&gapped),
+        vec![
+            region(Some(0..MIN), &[]),
+            region(Some(2 * MIN..3 * MIN), &[])
+        ]
+    );
+
+    rejected(
+        merge(vec![
+            kll(Some(0..2 * MIN), &[]),
+            kll(Some(MIN..3 * MIN), &[]),
+        ]),
+        CoverageError::PossibleOverlap,
+    );
+}
+
+/// Example 2: disjoint label values merge; different labels or equal values are rejected.
+#[test]
+fn example_2_population() {
+    let t = Some(0..MIN);
+    let us_eu = merge(vec![
+        kll(t.clone(), &[("region", "us")]),
+        kll(t.clone(), &[("region", "eu")]),
+    ])
+    .unwrap();
+    assert_eq!(
+        regions(&us_eu),
+        vec![
+            region(t.clone(), &[("region", "eu")]),
+            region(t.clone(), &[("region", "us")]),
+        ]
+    );
+    for other in [("tier", "premium"), ("region", "us")] {
+        rejected(
+            merge(vec![
+                kll(t.clone(), &[("region", "us")]),
+                kll(t.clone(), &[other]),
+            ]),
+            CoverageError::PossibleOverlap,
+        );
+    }
+}
+
+/// Example 3: time and population stay paired; never widened to {us,eu} × [0,2).
+#[test]
+fn example_3_joint_regions() {
+    let joint = merge(vec![
+        kll(Some(0..MIN), &[("region", "us")]),
+        kll(Some(MIN..2 * MIN), &[("region", "eu")]),
+    ])
+    .unwrap();
+    assert_eq!(
+        regions(&joint),
+        vec![
+            region(Some(MIN..2 * MIN), &[("region", "eu")]),
+            region(Some(0..MIN), &[("region", "us")]),
+        ]
+    );
+}
+
+/// A table without a time column declares no time bounds.
+#[test]
+fn tabular_source_without_time_bounds() {
+    let by_region = merge(vec![
+        kll(None, &[("region", "us")]),
+        kll(None, &[("region", "eu")]),
+    ])
+    .unwrap();
+    assert_eq!(regions(&by_region).len(), 2);
+    rejected(
+        merge(vec![
+            kll(None, &[("region", "us")]),
+            kll(Some(0..MIN), &[("region", "us")]),
+        ]),
+        CoverageError::PossibleOverlap,
+    );
+}
+
+/// Inputs must read the same source and share the producer's update and reduction.
+#[test]
+fn incompatible_inputs() {
+    let other_source = kll_over(
+        "latency",
+        None,
+        SummaryCoverage {
+            source: Source::Table {
+                table_ref: "other".into(),
+            },
+            regions: vec![region(Some(MIN..2 * MIN), &[])],
+        },
+    );
+    rejected(
+        merge(vec![kll(Some(0..MIN), &[]), other_source]),
+        CoverageError::SourceMismatch,
+    );
+
+    // Same schema (both Float64 columns), different update expression.
+    let size = kll_over(
+        "size",
+        None,
+        SummaryCoverage {
+            source: requests(),
+            regions: vec![region(Some(MIN..2 * MIN), &[])],
+        },
+    );
+    assert!(matches!(
+        merge(vec![kll(Some(0..MIN), &[]), size]),
+        Err(SchemaDerivationError::InvalidScalarSignature(message))
+            if message.contains("update expression and reduction")
+    ));
+}
+
+/// Summary nodes must carry coverage, and merges reject inputs without it.
+#[test]
+fn coverage_is_required() {
+    let mut missing = (*kll(Some(MIN..2 * MIN), &[])).clone();
+    missing.coverage = None;
+    let missing = Rc::new(missing);
+    assert!(matches!(
+        missing.validate_structure(),
+        Err(SchemaDerivationError::Coverage(CoverageError::Missing))
+    ));
+    rejected(
+        merge(vec![kll(Some(0..MIN), &[]), missing]),
+        CoverageError::UnknownInput,
+    );
+}
+
+/// Trusted declarations: population is not checked against the filter (#570).
+/// Both states hold US data, yet the wrong declaration lets them merge.
+#[test]
+fn wrong_population_declaration_is_accepted_until_570() {
+    let declared = |value: &str| SummaryCoverage {
+        source: requests(),
+        regions: vec![region(Some(0..MIN), &[("region", value)])],
+    };
+    let a = kll_over("latency", Some(region_is("us")), declared("eu"));
+    let b = kll_over("latency", Some(region_is("us")), declared("us"));
+    assert!(merge(vec![a, b]).is_ok());
+}
diff --git a/crates/types/tests/summary_merge_structure.rs b/crates/types/tests/summary_merge_structure.rs
index 6489159af..383b2bfbd 100644
--- a/crates/types/tests/summary_merge_structure.rs
+++ b/crates/types/tests/summary_merge_structure.rs
@@ -30,9 +30,9 @@ fn state(k: u32) -> Rc<OperatorNode> {
     std::rc::Rc::new(
         summary
             .with_coverage(asap_types::ir::summary_coverage::SummaryCoverage {
-                source: "latencies:timestamp".into(),
-                input: SummaryUpdate::column(ColumnRef::SampleValue),
-                reduction: Reduction::by(vec![]),
+                source: Source::Table {
+                    table_ref: "latencies".into(),
+                },
                 regions: vec![asap_types::ir::summary_coverage::CoverageRegion {
                     time_ms: Some(0..1),
                     population: Default::default(),

From a116058913e2ece83739c58d38d58f6194e7dbfb Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 19:32:26 +0000
Subject: [PATCH 21/48] test(ir): point coverage examples at the design
 document

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/types/tests/summary_coverage_examples.rs | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/crates/types/tests/summary_coverage_examples.rs b/crates/types/tests/summary_coverage_examples.rs
index e2fad07ab..00785319e 100644
--- a/crates/types/tests/summary_coverage_examples.rs
+++ b/crates/types/tests/summary_coverage_examples.rs
@@ -1,4 +1,4 @@
-//! The examples in docs/develop_docs/summary-coverage.md, built as real
+//! The examples in docs/design_docs/proposals/summary-coverage.md, built as real
 //! SummaryAgg -> SummaryMerge plans. Every input has the same schema
 //! `(job: Utf8, state: KLL{k=200})`; only coverage differs.
 use asap_types::ir::summary_coverage::{CoverageError, CoverageRegion, SummaryCoverage};

From f2b7b3fd294c923c9247864fac0ccb9345827e42 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 19:45:47 +0000
Subject: [PATCH 22/48] test(ir): point coverage examples at the ASAP primitive
 schema design doc

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/types/tests/summary_coverage_examples.rs | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/crates/types/tests/summary_coverage_examples.rs b/crates/types/tests/summary_coverage_examples.rs
index 00785319e..bfaa28483 100644
--- a/crates/types/tests/summary_coverage_examples.rs
+++ b/crates/types/tests/summary_coverage_examples.rs
@@ -1,4 +1,4 @@
-//! The examples in docs/design_docs/proposals/summary-coverage.md, built as real
+//! The examples in docs/design_docs/proposals/asap-primitive-schema.md, built as real
 //! SummaryAgg -> SummaryMerge plans. Every input has the same schema
 //! `(job: Utf8, state: KLL{k=200})`; only coverage differs.
 use asap_types::ir::summary_coverage::{CoverageError, CoverageRegion, SummaryCoverage};

From a9da6dfd8a9d7051efe14fa69400babf3f36f254 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 14:40:51 +0000
Subject: [PATCH 23/48] feat(ir): add logical sub-DAG sharing and phase-free
 export

---
 crates/types/src/ir/canonicalize.rs   | 1077 +++++++++++++++++++++++++
 crates/types/src/ir/cse.rs            |  791 ++++++++++++++++++
 crates/types/src/ir/export.rs         |  334 ++++++++
 crates/types/src/ir/mod.rs            |    4 +
 crates/types/src/ir/wire.rs           |  746 +++++++++++++++++
 crates/types/tests/logical_export.rs  |  189 +++++
 docs/develop_docs/logical-asap-dag.md |   50 ++
 7 files changed, 3191 insertions(+)
 create mode 100644 crates/types/src/ir/canonicalize.rs
 create mode 100644 crates/types/src/ir/cse.rs
 create mode 100644 crates/types/src/ir/export.rs
 create mode 100644 crates/types/src/ir/wire.rs
 create mode 100644 crates/types/tests/logical_export.rs
 create mode 100644 docs/develop_docs/logical-asap-dag.md

diff --git a/crates/types/src/ir/canonicalize.rs b/crates/types/src/ir/canonicalize.rs
new file mode 100644
index 000000000..d9a0034a4
--- /dev/null
+++ b/crates/types/src/ir/canonicalize.rs
@@ -0,0 +1,1077 @@
+//! Post-lowering canonicalization of the operator DAG.
+//!
+//! Erases *structural* differences between semantically identical queries so
+//! a post-ASAP binding rule matching on the intent algebra sees one canonical
+//! spelling regardless of source language (issue #34).
+//!
+//! ## Heavy-hitter promotion
+//!
+//! An additive-ranked "order by the aggregate, take the top k" is a
+//! heavy-hitter represented by [`AggIntent::TopK`]. Front ends may emit it as
+//! an ordinary `Limit { Sort { … Aggregate } }`; this pass promotes that shape
+//! to the canonical
+//!
+//! ```text
+//! Aggregate { reduction: Reduce(<partition>), measures: [TopK{k}],
+//!             child: Aggregate { measures: [Count | Sum], … } }
+//! ```
+//!
+//! Count supplies unit weights and Sum supplies value weights. Because the
+//! match is positional, aliases do not affect it. Other ranked expressions
+//! retain Sort + Limit.
+//!
+//! ## Subquery lowering
+//!
+//! EXISTS/NOT EXISTS and positive IN filter conjuncts may use semi/anti joins.
+//! Scalar subqueries remain explicit: a cross join does not preserve their
+//! zero-row NULL or multiple-row error semantics. All scalar plan references
+//! participate in DAG traversal and canonicalization.
+
+use std::collections::HashMap;
+use std::rc::Rc;
+
+use super::node::{Operator, OperatorNode};
+use super::non_asap::NonASAPOp;
+use super::scalar::{ExprSemantics, Predicate, ProjectItem, ScalarExpr, SortKey};
+use crate::ir::operator_properties::{JoinKind, Reduction};
+use crate::ir::SchemaDerivationError;
+use crate::pre_asap::agg_intent::{topk, AggIntent};
+use crate::pre_asap::expr_ir::{CompareOpKind, ScalarValue};
+use crate::types::AccuracyTarget;
+
+/// Rewrite the DAG under `root` into its canonical form (bottom-up).
+/// Idempotent: an already-canonical DAG comes back as the same `Rc`. Only
+/// nodes that change (or whose inputs change) are rebuilt; every untouched
+/// sub-DAG keeps its pointer identity, and a shared sub-DAG that is rewritten
+/// stays shared.
+pub fn canonicalize(root: Rc<OperatorNode>) -> Result<Rc<OperatorNode>, SchemaDerivationError> {
+    canon(&root, &mut HashMap::new())
+}
+
+fn canon(
+    node: &Rc<OperatorNode>,
+    memo: &mut HashMap<*const OperatorNode, Rc<OperatorNode>>,
+) -> Result<Rc<OperatorNode>, SchemaDerivationError> {
+    if let Some(done) = memo.get(&Rc::as_ptr(node)) {
+        return Ok(Rc::clone(done));
+    }
+
+    // A `Concat` asserting a caller-proven `discriminator_unique_key` (issue
+    // #228) had that key's `ColumnId`s resolved against exactly the first
+    // branch's output schema *as it stood before this pass ran*. The rewrites
+    // below can restructure that branch (anywhere within it) into a shape
+    // with a different output schema, which would leave those `ColumnId`s
+    // pointing at the wrong column, or out of bounds. Snapshot the schema the
+    // key was resolved against before recursing into the children.
+    let discriminator_branch_schema_before = match &node.operator {
+        Operator::NonASAP(NonASAPOp::Concat {
+            children,
+            discriminator_unique_key: Some(_),
+        }) => children.first().map(|c| c.schema.clone()),
+        _ => None,
+    };
+
+    // Bottom-up: canonicalize every operator input before matching at this
+    // node, so an inner heavy-hitter is promoted before an enclosing rewrite
+    // inspects it.
+    let mut rebuilt: Vec<(*const OperatorNode, Rc<OperatorNode>)> = Vec::new();
+    let mut changed = false;
+    for child in operator_children(&node.operator) {
+        let new = canon(child, memo)?;
+        changed |= !Rc::ptr_eq(&new, child);
+        rebuilt.push((Rc::as_ptr(child), new));
+    }
+    let mut current = if changed {
+        // `map_children` also visits the operator nodes referenced from
+        // scalar expressions; those are not in `rebuilt` and pass through
+        // unchanged. (A node that is both an operator input and a scalar
+        // reference is one shared node, so it takes its canonical form in
+        // both places.)
+        let rebuilt_child = |c: &Rc<OperatorNode>| {
+            rebuilt
+                .iter()
+                .find(|(ptr, _)| *ptr == Rc::as_ptr(c))
+                .map_or_else(|| Rc::clone(c), |(_, new)| Rc::clone(new))
+        };
+        Rc::new(node.map_children(rebuilt_child)?)
+    } else {
+        Rc::clone(node)
+    };
+
+    // If the first branch's output schema moved out from under the asserted
+    // key, the key can no longer be trusted — drop it (never re-derive it by
+    // guessing at name/position). A wrong `unique_keys` claim is a wrong
+    // query answer, not a missed optimization, so any difference at all
+    // drops the key.
+    if let Operator::NonASAP(NonASAPOp::Concat {
+        children,
+        discriminator_unique_key: Some(_),
+    }) = &current.operator
+    {
+        let after = children.first().map(|c| &c.schema);
+        if discriminator_branch_schema_before.as_ref() != after {
+            current = OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Concat {
+                children: children.clone(),
+                discriminator_unique_key: None,
+            }))?;
+        }
+    }
+
+    let current = apply_local_rules(current, memo)?;
+
+    memo.insert(Rc::as_ptr(node), Rc::clone(&current));
+    Ok(current)
+}
+
+type Memo = HashMap<*const OperatorNode, Rc<OperatorNode>>;
+
+/// Apply the local rewrite rules at `node` (whose inputs are already
+/// canonical) until none matches. The rules chain: a `ROW_NUMBER()`-
+/// partitioned top-k rewrites to a `Limit{Sort}`, which the heavy-hitter
+/// rule may then promote to an `Aggregate([TopK])`; a `Filter` with several
+/// subquery conjuncts sheds one per round. Each rule strictly simplifies the
+/// node (one fewer idiom, or one fewer subquery reference), so the loop
+/// terminates.
+fn apply_local_rules(
+    mut current: Rc<OperatorNode>,
+    memo: &mut Memo,
+) -> Result<Rc<OperatorNode>, SchemaDerivationError> {
+    loop {
+        let next = if let Some(next) = try_promote_additive_top_ranking(&current)? {
+            next
+        } else if let Some(next) = try_lower_subquery_conjunct(&current, memo)? {
+            next
+        } else {
+            break;
+        };
+        current = next;
+    }
+    Ok(current)
+}
+
+/// The direct **operator** inputs of a node — the relational skeleton only.
+/// Operator nodes referenced from a scalar position (`ScalarSubquery`,
+/// `Exists`, …) are not visited here: a subquery that the lowering rules
+/// lift into a join is canonicalized at that point, and one they leave in
+/// place (`NOT IN`, an `EXISTS` outside a `Filter` conjunct) stays as the
+/// front end emitted it.
+fn operator_children(op: &Operator) -> Vec<&Rc<OperatorNode>> {
+    op.children()
+}
+
+/// Recognise an additive-ranked
+/// `Limit { Sort { [Project] Aggregate([Count | Sum]) } }` and rewrite it to
+/// the canonical heavy-hitter `Aggregate([TopK])` over the explicit inner
+/// aggregate. Returns `None` when the shape does not match.
+fn try_promote_additive_top_ranking(
+    node: &OperatorNode,
+) -> Result<Option<Rc<OperatorNode>>, SchemaDerivationError> {
+    // Limit k, no offset (an OFFSET means "not the top k").
+    let Some(NonASAPOp::Limit {
+        n: Some(k),
+        offset: 0,
+        partition_by: limit_partition,
+        child,
+    }) = node.non_asap()
+    else {
+        return Ok(None);
+    };
+    // A single ordering key on a column.
+    let Some(NonASAPOp::Sort {
+        keys,
+        partition_by,
+        child: sort_child,
+    }) = child.non_asap()
+    else {
+        return Ok(None);
+    };
+    // A per-group `Limit` must agree with its `Sort`'s partition: the
+    // ranking's partition is what the outer `TopK` groups by.
+    if !limit_partition.is_empty() && limit_partition != partition_by {
+        return Ok(None);
+    }
+    let [SortKey {
+        expr: ScalarExpr::Column(sort_col),
+        ascending,
+        ..
+    }] = keys.as_slice()
+    else {
+        return Ok(None);
+    };
+
+    // The ordered relation is an `Aggregate`, optionally behind a passthrough
+    // projection (a bare-column SELECT list). Map the sort key through the
+    // projection to the aggregate's own output column.
+    let (agg_node, ranked_col) = match sort_child.non_asap() {
+        Some(NonASAPOp::Project { cols, child, .. }) => {
+            let Some(ProjectItem {
+                expr: ScalarExpr::Column(underlying),
+                ..
+            }) = cols.get(*sort_col)
+            else {
+                return Ok(None);
+            };
+            (child, *underlying)
+        }
+        _ => (sort_child, *sort_col),
+    };
+
+    // Exactly one aggregate, ranked by *its* output column — the measure sits
+    // at index `by.len()` (after the group keys). A `PerEntity` reduction has
+    // no `by` to rank a measure against, so it is a non-match.
+    let Some(NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child: aggregate_child,
+        ..
+    }) = agg_node.non_asap()
+    else {
+        return Ok(None);
+    };
+    let Reduction::Reduce(by) = reduction else {
+        return Ok(None);
+    };
+    let [ranked_agg] = measures.as_slice() else {
+        return Ok(None);
+    };
+    if ranked_col != by.len() {
+        return Ok(None);
+    }
+    // The heavy-hitter decision — descending, over a measure with a realised
+    // heavy-hitter sketch — is the shared rule both front ends consult (issue
+    // #38). An ascending additive-ranked limit (bottom-k) stays generic.
+    if !topk::Ranking::from_aggregate(ranked_agg).is_supported(!ascending) {
+        return Ok(None);
+    }
+    // A direct Sum is a stream of additive observation weights. A Sum over a
+    // derived child such as Rate/Increase still needs exact reset-aware
+    // values to rerank sketch candidates, and the post-ASAP IR has no
+    // candidate-sidecar + exact-rerank node, so that shape keeps Sort + Limit.
+    if matches!(ranked_agg, AggIntent::Sum { .. })
+        && matches!(
+            aggregate_child.non_asap(),
+            Some(NonASAPOp::Aggregate { .. })
+        )
+    {
+        return Ok(None);
+    }
+    // Count ranks unit updates; a direct Sum ranks weighted updates.
+    let accuracy = match ranked_agg {
+        AggIntent::Count { accuracy } => accuracy.clone(),
+        AggIntent::Sum { .. } => AccuracyTarget::Exact,
+        _ => unreachable!("additive ranking gate admitted a non-additive measure"),
+    };
+
+    // Outer heavy-hitter `TopK`, grouped by the ranking's partition (empty for
+    // a global `ORDER BY … LIMIT k`; the `by` labels for a partitioned `topk
+    // by`), over the unchanged inner additive aggregate.
+    OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+        reduction: Reduction::by(partition_by.to_vec()),
+        measures: vec![AggIntent::TopK { k: *k, accuracy }],
+        output_names: Vec::new(),
+        filters: vec![],
+        having: None,
+        child: Rc::clone(agg_node),
+    }))
+    .map(Some)
+}
+
+// ROW_NUMBER filters retain the window output. Eliminating it without a
+// consumer-aware rewrite drops a visible column and invalidates outer scopes.
+
+/// `Predicate(true)`: the unconditional join predicate the SQL front end
+/// emits for an uncorrelated `EXISTS` and for a `CROSS JOIN`.
+fn always_true() -> Predicate {
+    Predicate(ScalarExpr::Literal(ScalarValue::Boolean(true)))
+}
+
+/// Whether `conjunct` is one this pass lowers to a semi/anti join.
+fn is_join_conjunct(conjunct: &ScalarExpr) -> bool {
+    match conjunct {
+        ScalarExpr::Exists { .. } => true,
+        // An `IN` whose probe expression itself reads a scalar subquery is
+        // lowered only after that subquery has been joined in by
+        // `try_lower_scalar_subquery` (a `Join` predicate is not a place that
+        // rule looks). `NOT IN` is never lowered — see the module docs.
+        ScalarExpr::InSubquery {
+            expr,
+            negated: false,
+            ..
+        } => find_scalar_subquery(expr).is_none(),
+        _ => false,
+    }
+}
+
+/// Lower one `[NOT] EXISTS (s)` / `x IN (s)` conjunct of a `Filter` to the
+/// semi-/anti-join the SQL front end used to emit directly. The remaining
+/// conjuncts stay in an outer `Filter` over the join: a semi/anti join's
+/// output schema is the left's, so their column ids are unchanged. One
+/// conjunct per call; the fixpoint loop picks up the next.
+fn try_lower_subquery_conjunct(
+    node: &OperatorNode,
+    memo: &mut Memo,
+) -> Result<Option<Rc<OperatorNode>>, SchemaDerivationError> {
+    let Some(NonASAPOp::Filter {
+        pred: Predicate(pred),
+        child,
+    }) = node.non_asap()
+    else {
+        return Ok(None);
+    };
+    let conjuncts = pred.conjuncts();
+    let Some(idx) = conjuncts.iter().position(is_join_conjunct) else {
+        return Ok(None);
+    };
+    let left_width = child.schema.fields.len();
+    let (kind, subquery, join_pred) = match &conjuncts[idx] {
+        // Uncorrelated by construction (the IR's `Exists` carries no outer
+        // column references), so the join condition is unconditionally true.
+        ScalarExpr::Exists { subquery, negated } => {
+            let kind = if *negated {
+                JoinKind::Anti
+            } else {
+                JoinKind::Semi
+            };
+            (kind, subquery, always_true())
+        }
+        // `x = <the subquery's single column>`, which sits right after the
+        // left's columns in the `left ++ right` scope the predicate resolves
+        // against.
+        ScalarExpr::InSubquery { expr, subquery, .. } => (
+            JoinKind::Semi,
+            subquery,
+            Predicate(ScalarExpr::Compare {
+                left: expr.clone(),
+                op: CompareOpKind::Eq,
+                right: Box::new(ScalarExpr::Column(left_width)),
+                semantics: ExprSemantics::Sql,
+            }),
+        ),
+        _ => unreachable!("`is_join_conjunct` admitted a non-subquery conjunct"),
+    };
+    let join = OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Join {
+        kind,
+        pred: join_pred,
+        left: Rc::clone(child),
+        right: canon(subquery, memo)?,
+    }))?;
+    let mut rest: Vec<ScalarExpr> = conjuncts
+        .iter()
+        .enumerate()
+        .filter(|(i, _)| *i != idx)
+        .map(|(_, c)| c.clone())
+        .collect();
+    let out = match rest.len() {
+        0 => join,
+        1 => filter(rest.remove(0), join)?,
+        _ => filter(ScalarExpr::BoolAnd(rest), join)?,
+    };
+    Ok(Some(out))
+}
+
+/// Lower one scalar subquery read by a `Project` item or a `Filter`
+/// predicate: the owner reads it through a cross join against the subquery,
+/// whose single column is appended after the left's (`Column(|left|)`), and
+/// every occurrence of that subquery node in the owner is replaced by that
+/// column reference. One subquery node per call; the fixpoint loop handles
+/// the rest, each getting its own cross join further out (so earlier column
+/// ids are never shifted). For a `Filter` the output schema is restored to
+/// the left's columns by a positional `Project` over the result.
+///
+/// Not representable in the IR, and therefore not checked here: SQL raises
+/// an error when a scalar subquery yields more than one row (the cross join
+/// would duplicate the left's rows instead), and yields NULL when it yields
+/// none (the cross join yields no rows instead).
+fn filter(
+    pred: ScalarExpr,
+    child: Rc<OperatorNode>,
+) -> Result<Rc<OperatorNode>, SchemaDerivationError> {
+    OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Filter {
+        pred: Predicate(pred),
+        child,
+    }))
+}
+
+/// The first `ScalarSubquery` node read by `expr` (pre-order over its scalar
+/// children; referenced operator subgraphs are their own scope and are not
+/// entered).
+fn find_scalar_subquery(expr: &ScalarExpr) -> Option<&Rc<OperatorNode>> {
+    if let ScalarExpr::ScalarSubquery(node) = expr {
+        return Some(node);
+    }
+    expr.children().into_iter().find_map(find_scalar_subquery)
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::ir::operator_properties::WindowFuncKind;
+    use crate::ir::operator_properties::{
+        ConcatDiscriminatorKey, GroupKeys, Source, WindowFrame, WindowFrameBound,
+        WindowFrameOffset, WindowFrameUnits,
+    };
+    use crate::pre_asap::schema::{DataType, Field, Schema};
+
+    fn node(op: NonASAPOp) -> Rc<OperatorNode> {
+        Rc::new(OperatorNode::new(Operator::NonASAP(op)).expect("fixture derives a schema"))
+    }
+
+    fn scan() -> Rc<OperatorNode> {
+        node(NonASAPOp::Scan {
+            source: Source::TimeSeries { metric: "m".into() },
+            predicates: vec![],
+            schema: Schema::with_time_index(
+                vec![
+                    Field::plain("ts", DataType::Timestamp, false),
+                    Field::plain("service", DataType::Utf8, false),
+                    Field::plain("value", DataType::Float64, false),
+                ],
+                0,
+                vec![],
+            ),
+        })
+    }
+
+    fn aggregate(
+        reduction: Reduction,
+        agg: AggIntent,
+        child: Rc<OperatorNode>,
+    ) -> Rc<OperatorNode> {
+        node(NonASAPOp::Aggregate {
+            reduction,
+            measures: vec![agg],
+            output_names: vec![],
+            filters: vec![],
+            having: None,
+            child,
+        })
+    }
+
+    fn count() -> AggIntent {
+        AggIntent::Count {
+            accuracy: AccuracyTarget::Exact,
+        }
+    }
+
+    /// `Aggregate{ by: [1], [Count] }` over the scan — output cols `[service, count]`.
+    fn count_by_service() -> Rc<OperatorNode> {
+        aggregate(Reduction::by(vec![1]), count(), scan())
+    }
+
+    fn key(col: usize, ascending: bool) -> Vec<SortKey> {
+        vec![SortKey {
+            expr: ScalarExpr::Column(col),
+            ascending,
+            nulls_first: false,
+        }]
+    }
+
+    fn desc(col: usize) -> Vec<SortKey> {
+        key(col, false)
+    }
+
+    fn limit(n: usize, offset: usize, child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+        node(NonASAPOp::Limit {
+            n: Some(n),
+            offset,
+            partition_by: GroupKeys::none(),
+            child,
+        })
+    }
+
+    fn sort(keys: Vec<SortKey>, child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+        node(NonASAPOp::Sort {
+            keys,
+            partition_by: GroupKeys::none(),
+            child,
+        })
+    }
+
+    fn passthrough_project(child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+        node(NonASAPOp::Project {
+            cols: vec![
+                ProjectItem {
+                    alias: None,
+                    expr: ScalarExpr::Column(0),
+                },
+                ProjectItem {
+                    alias: Some("c".into()),
+                    expr: ScalarExpr::Column(1),
+                },
+            ],
+            qualifier: None,
+            child,
+        })
+    }
+
+    fn concat(
+        children: Vec<Rc<OperatorNode>>,
+        key: Option<ConcatDiscriminatorKey>,
+    ) -> Rc<OperatorNode> {
+        node(NonASAPOp::Concat {
+            children,
+            discriminator_unique_key: key,
+        })
+    }
+
+    fn measures(n: &OperatorNode) -> &[AggIntent] {
+        match n.non_asap() {
+            Some(NonASAPOp::Aggregate { measures, .. }) => measures,
+            _ => &[],
+        }
+    }
+
+    fn is_topk_over_count(n: &OperatorNode) -> bool {
+        let Some(NonASAPOp::Aggregate {
+            measures, child, ..
+        }) = n.non_asap()
+        else {
+            return false;
+        };
+        matches!(measures.as_slice(), [AggIntent::TopK { k: 5, .. }])
+            && matches!(self::measures(child), [AggIntent::Count { .. }])
+    }
+
+    #[test]
+    fn promotes_count_ranked_limit_sort() {
+        // Limit 5 { Sort DESC by count-col (1) { Aggregate[Count] by [1] } }.
+        let q = limit(5, 0, sort(desc(1), count_by_service()));
+        assert!(is_topk_over_count(&canonicalize(q).unwrap()));
+    }
+
+    #[test]
+    fn promotes_through_a_passthrough_projection() {
+        // …with a `SELECT service, count` projection between the Sort and the Agg.
+        let q = limit(5, 0, sort(desc(1), passthrough_project(count_by_service())));
+        assert!(is_topk_over_count(&canonicalize(q).unwrap()));
+    }
+
+    #[test]
+    fn promoted_topk_reuses_the_inner_aggregate_node() {
+        // The inner aggregate is untouched, so the rewrite shares it rather
+        // than copying it.
+        let agg = count_by_service();
+        let out = canonicalize(limit(5, 0, sort(desc(1), Rc::clone(&agg)))).unwrap();
+        let Some(NonASAPOp::Aggregate { child, .. }) = out.non_asap() else {
+            panic!("expected TopK aggregate");
+        };
+        assert!(Rc::ptr_eq(child, &agg));
+    }
+
+    #[test]
+    fn is_idempotent() {
+        let q = limit(5, 0, sort(desc(1), count_by_service()));
+        let once = canonicalize(q).unwrap();
+        let twice = canonicalize(Rc::clone(&once)).unwrap();
+        assert!(Rc::ptr_eq(&once, &twice), "canonicalize must be idempotent");
+    }
+
+    #[test]
+    fn untouched_dag_is_returned_pointer_equal() {
+        // Nothing here matches a rewrite: a Concat of two projections over
+        // one shared aggregate. The root (and everything under it) must come
+        // back as the same `Rc`.
+        let agg = count_by_service();
+        let q = concat(
+            vec![
+                passthrough_project(Rc::clone(&agg)),
+                passthrough_project(Rc::clone(&agg)),
+            ],
+            None,
+        );
+        let out = canonicalize(Rc::clone(&q)).unwrap();
+        assert!(Rc::ptr_eq(&out, &q));
+    }
+
+    #[test]
+    fn rewritten_shared_subtree_stays_shared() {
+        // One promotable sub-DAG referenced twice is rewritten once.
+        let branch = limit(5, 0, sort(desc(1), count_by_service()));
+        let q = concat(vec![Rc::clone(&branch), Rc::clone(&branch)], None);
+        let out = canonicalize(q).unwrap();
+        let Some(NonASAPOp::Concat { children, .. }) = out.non_asap() else {
+            panic!("expected Concat");
+        };
+        assert!(is_topk_over_count(&children[0]));
+        assert!(Rc::ptr_eq(&children[0], &children[1]));
+    }
+
+    // ── Concat's discriminator_unique_key vs. canonicalize (issue #228) ──
+    //
+    // `discriminator_unique_key`'s `ColumnId`s were resolved against the
+    // first branch's *pre-canonicalize* output schema. The key is dropped
+    // whenever that branch's schema actually changed, and survives untouched
+    // otherwise. Never guessed at.
+
+    fn discriminator_key(n: &OperatorNode) -> &Option<ConcatDiscriminatorKey> {
+        match n.non_asap() {
+            Some(NonASAPOp::Concat {
+                discriminator_unique_key,
+                ..
+            }) => discriminator_unique_key,
+            _ => panic!("expected Concat"),
+        }
+    }
+
+    #[test]
+    fn concat_discriminator_key_survives_canonicalize_when_first_branch_is_unaffected() {
+        // A plain `Aggregate` first branch matches neither rewrite trigger,
+        // so its schema is identical before and after canonicalize.
+        let q = concat(
+            vec![count_by_service(), count_by_service()],
+            Some(ConcatDiscriminatorKey::new(0, vec![1])),
+        );
+        let out = canonicalize(Rc::clone(&q)).unwrap();
+        assert!(
+            discriminator_key(&out).is_some(),
+            "an untouched first branch's discriminator key must survive canonicalize"
+        );
+        assert!(Rc::ptr_eq(&out, &q));
+    }
+
+    #[test]
+    fn concat_discriminator_key_is_dropped_when_first_branch_gets_rewritten() {
+        // The first branch is exactly the heavy-hitter promotion trigger, so
+        // canonicalize rewrites it to `Aggregate{TopK}`, whose own output is
+        // a single column, not the original two (`[service, count]`). A key
+        // resolved against the 2-column shape must not survive pointing at
+        // the new 1-column schema.
+        let promotable_branch = limit(5, 0, sort(desc(1), count_by_service()));
+        let q = concat(
+            vec![promotable_branch, count_by_service()],
+            Some(ConcatDiscriminatorKey::new(0, vec![1])),
+        );
+        let out = canonicalize(q).unwrap();
+        let Some(NonASAPOp::Concat {
+            children,
+            discriminator_unique_key,
+        }) = out.non_asap()
+        else {
+            panic!("expected Concat");
+        };
+        assert!(
+            is_topk_over_count(&children[0]),
+            "the first branch is still promoted normally"
+        );
+        assert!(
+            discriminator_unique_key.is_none(),
+            "a stale discriminator key must be dropped, never silently kept wrong"
+        );
+        assert!(
+            out.schema.unique_keys.is_empty(),
+            "the dropped key leaves the schema"
+        );
+    }
+
+    #[test]
+    fn does_not_promote_ascending_sort() {
+        // Ascending = bottom-k: the Top-K ranking rule rejects it (needs
+        // descending), so it stays a generic Sort+Limit (issue #38).
+        let q = limit(5, 0, sort(key(1, true), count_by_service()));
+        assert!(!is_topk_over_count(&canonicalize(q).unwrap()));
+    }
+
+    #[test]
+    fn does_not_promote_with_offset() {
+        let q = limit(5, 2, sort(desc(1), count_by_service()));
+        assert!(!is_topk_over_count(&canonicalize(q).unwrap()));
+    }
+
+    #[test]
+    fn does_not_promote_ranking_by_a_group_key() {
+        // DESC by col 0 (the `service` group key), not the count → not a
+        // frequency heavy-hitter.
+        let q = limit(5, 0, sort(desc(0), count_by_service()));
+        assert!(!is_topk_over_count(&canonicalize(q).unwrap()));
+    }
+
+    #[test]
+    fn does_not_promote_when_limit_partition_disagrees_with_sort() {
+        // A per-group Limit partitioned differently from its Sort is not the
+        // top-k shape.
+        let q = node(NonASAPOp::Limit {
+            n: Some(5),
+            offset: 0,
+            partition_by: GroupKeys::by(vec![0]),
+            child: sort(desc(1), count_by_service()),
+        });
+        assert!(!is_topk_over_count(&canonicalize(q).unwrap()));
+    }
+
+    #[test]
+    fn promotes_sum_ranked_limit_sort_as_weighted_heavy_hitter() {
+        let sum = aggregate(Reduction::by(vec![1]), AggIntent::Sum { col: None }, scan());
+        let out = canonicalize(limit(5, 0, sort(desc(1), sum))).unwrap();
+        let Some(NonASAPOp::Aggregate {
+            measures, child, ..
+        }) = out.non_asap()
+        else {
+            panic!("expected weighted TopK aggregate");
+        };
+        assert!(matches!(
+            measures.as_slice(),
+            [AggIntent::TopK { k: 5, .. }]
+        ));
+        assert!(matches!(self::measures(child), [AggIntent::Sum { .. }]));
+    }
+
+    #[test]
+    fn keeps_sum_over_counter_reduction_as_exact_value_ranking() {
+        for counter in [AggIntent::Rate, AggIntent::Increase] {
+            let derived = aggregate(Reduction::PerEntity, counter, scan());
+            let sum = aggregate(
+                Reduction::by(vec![1]),
+                AggIntent::Sum { col: None },
+                derived,
+            );
+            let out = canonicalize(limit(5, 0, sort(desc(1), sum))).unwrap();
+            let Some(NonASAPOp::Limit { child, .. }) = out.non_asap() else {
+                panic!("expected Limit, got {out:?}");
+            };
+            let Some(NonASAPOp::Sort { child, .. }) = child.non_asap() else {
+                panic!("expected Sort under the Limit");
+            };
+            let Some(NonASAPOp::Aggregate {
+                measures, child, ..
+            }) = child.non_asap()
+            else {
+                panic!("expected Aggregate under the Sort");
+            };
+            assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+            assert!(matches!(
+                child.non_asap(),
+                Some(NonASAPOp::Aggregate { .. })
+            ));
+        }
+    }
+
+    // ── ROW_NUMBER() partitioned top-k (issue #24) ──────────────────────────
+
+    /// A scan with `[ts, service, region, value]`.
+    fn scan4() -> Rc<OperatorNode> {
+        node(NonASAPOp::Scan {
+            source: Source::TimeSeries { metric: "m".into() },
+            predicates: vec![],
+            schema: Schema::with_time_index(
+                vec![
+                    Field::plain("ts", DataType::Timestamp, false),
+                    Field::plain("service", DataType::Utf8, false),
+                    Field::plain("region", DataType::Utf8, false),
+                    Field::plain("value", DataType::Float64, false),
+                ],
+                0,
+                vec![],
+            ),
+        })
+    }
+
+    /// `Aggregate{ by: [1,2] (service, region), [agg] }` — output `[service,
+    /// region, <agg>]` (3 cols), so a ROW_NUMBER over it appends `rn` at index 3.
+    fn grouped(agg: AggIntent) -> Rc<OperatorNode> {
+        aggregate(Reduction::by(vec![1, 2]), agg, scan4())
+    }
+
+    /// `ROW_NUMBER` ignores its frame clause; any concrete frame works.
+    fn rownumber_frame() -> WindowFrame {
+        WindowFrame {
+            units: WindowFrameUnits::Rows,
+            start_bound: WindowFrameBound::Preceding(WindowFrameOffset::Scalar(ScalarValue::Null)),
+            end_bound: WindowFrameBound::Following(WindowFrameOffset::Scalar(ScalarValue::Null)),
+        }
+    }
+
+    /// `SQLWindowFunc{ RowNumber, PARTITION BY region(2), ORDER BY col(2) DESC } { agg }`.
+    fn rownumber_window(agg: Rc<OperatorNode>) -> Rc<OperatorNode> {
+        node(NonASAPOp::SQLWindowFunc {
+            func: WindowFuncKind::RowNumber,
+            args: vec![],
+            partition_by: GroupKeys::by(vec![2]), // region
+            order_by: vec![SortKey {
+                expr: ScalarExpr::Column(2), // the aggregate output column
+                ascending: false,
+                nulls_first: true,
+            }],
+            frame: Some(rownumber_frame()),
+            output_name: "rn".into(),
+            child: agg,
+        })
+    }
+
+    /// `Filter{ col <= 5 } { child }`.
+    fn filter_le_5(col: usize, child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+        node(NonASAPOp::Filter {
+            pred: Predicate(ScalarExpr::Compare {
+                left: Box::new(ScalarExpr::Column(col)),
+                op: CompareOpKind::Le,
+                right: Box::new(ScalarExpr::Literal(ScalarValue::Int64(5))),
+                semantics: ExprSemantics::Sql,
+            }),
+            child,
+        })
+    }
+
+    /// `Filter{ rn(3) <= 5 } { ROW_NUMBER window { agg } }`.
+    fn rownumber_topk(agg: Rc<OperatorNode>) -> Rc<OperatorNode> {
+        filter_le_5(3, rownumber_window(agg))
+    }
+
+    #[test]
+    fn rownumber_count_topk_becomes_a_partitioned_heavy_hitter() {
+        let original = rownumber_topk(grouped(count()));
+        let out = canonicalize(Rc::clone(&original)).unwrap();
+        assert_eq!(out.schema, original.schema);
+        assert!(
+            matches!(out.non_asap(),Some(NonASAPOp::Filter { child,.. }) if matches!(child.non_asap(),Some(NonASAPOp::SQLWindowFunc { .. })))
+        );
+        assert_idempotent(&out);
+    }
+
+    #[test]
+    fn rownumber_avg_topk_becomes_a_partitioned_sort_limit() {
+        let original = rownumber_topk(grouped(AggIntent::Avg { col: None }));
+        let out = canonicalize(Rc::clone(&original)).unwrap();
+        assert_eq!(out.schema, original.schema);
+        assert!(
+            matches!(out.non_asap(),Some(NonASAPOp::Filter { child,.. }) if matches!(child.non_asap(),Some(NonASAPOp::SQLWindowFunc { .. })))
+        );
+        assert_idempotent(&out);
+    }
+
+    #[test]
+    fn filter_on_a_non_rownumber_column_is_left_alone() {
+        // `WHERE service_len <= 5` (col 0, not the rn window column) must not
+        // be mistaken for a top-k.
+        let q = filter_le_5(0, rownumber_window(grouped(count())));
+        let out = canonicalize(Rc::clone(&q)).unwrap();
+        assert!(Rc::ptr_eq(&out, &q), "left as the same Filter");
+    }
+
+    // ── Subquery lowering ───────────────────────────────────────────────────
+
+    fn filter_of(pred: ScalarExpr, child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+        node(NonASAPOp::Filter {
+            pred: Predicate(pred),
+            child,
+        })
+    }
+
+    /// `SELECT service FROM scan` — a one-column subquery.
+    /// Scalar reads retain cardinality/null semantics and a shared producer.
+    #[test]
+    fn scalar_subqueries_remain_explicit_and_shared() {
+        let sub = one_column_subquery();
+        let root = node(NonASAPOp::Project {
+            child: scan(),
+            qualifier: None,
+            cols: vec![
+                ProjectItem {
+                    alias: Some("a".into()),
+                    expr: ScalarExpr::ScalarSubquery(Rc::clone(&sub)),
+                },
+                ProjectItem {
+                    alias: Some("b".into()),
+                    expr: ScalarExpr::ScalarSubquery(Rc::clone(&sub)),
+                },
+            ],
+        });
+        let out = canonicalize(root).unwrap();
+        let NonASAPOp::Project { cols, child, .. } = out.expect_non_asap() else {
+            panic!()
+        };
+        assert!(matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }));
+        for col in cols {
+            assert!(matches!(&col.expr,ScalarExpr::ScalarSubquery(node) if Rc::ptr_eq(node,&sub)));
+        }
+        assert!(out.schema.fields.iter().all(|f| f.nullable));
+        assert_idempotent(&out);
+    }
+
+    fn one_column_subquery() -> Rc<OperatorNode> {
+        node(NonASAPOp::Scan {
+            source: Source::Table {
+                table_ref: "sub".into(),
+            },
+            predicates: vec![],
+            schema: Schema::new(vec![Field::plain("value", DataType::Float64, false)]),
+        })
+    }
+
+    fn exists(subquery: Rc<OperatorNode>, negated: bool) -> ScalarExpr {
+        ScalarExpr::Exists { subquery, negated }
+    }
+
+    fn in_subquery(expr: ScalarExpr, subquery: Rc<OperatorNode>, negated: bool) -> ScalarExpr {
+        ScalarExpr::InSubquery {
+            expr: Box::new(expr),
+            subquery,
+            negated,
+        }
+    }
+
+    /// `value(2) > 1`.
+    fn value_gt_1() -> ScalarExpr {
+        ScalarExpr::Compare {
+            left: Box::new(ScalarExpr::Column(2)),
+            op: CompareOpKind::Gt,
+            right: Box::new(ScalarExpr::Literal(ScalarValue::Int64(1))),
+            semantics: ExprSemantics::Sql,
+        }
+    }
+
+    fn literal_true() -> ScalarExpr {
+        ScalarExpr::Literal(ScalarValue::Boolean(true))
+    }
+
+    fn join_parts(
+        n: &OperatorNode,
+    ) -> (JoinKind, &ScalarExpr, &Rc<OperatorNode>, &Rc<OperatorNode>) {
+        match n.non_asap() {
+            Some(NonASAPOp::Join {
+                kind,
+                pred: Predicate(pred),
+                left,
+                right,
+            }) => (kind.clone(), pred, left, right),
+            _ => panic!("expected a Join, got {n:?}"),
+        }
+    }
+
+    fn assert_idempotent(once: &Rc<OperatorNode>) {
+        let twice = canonicalize(Rc::clone(once)).unwrap();
+        assert!(Rc::ptr_eq(once, &twice), "canonicalize must be idempotent");
+    }
+
+    #[test]
+    fn exists_filter_becomes_semi_join() {
+        let (left, sub) = (scan(), one_column_subquery());
+        let q = filter_of(exists(Rc::clone(&sub), false), Rc::clone(&left));
+        let out = canonicalize(q).unwrap();
+        let (kind, pred, l, r) = join_parts(&out);
+        assert_eq!(kind, JoinKind::Semi);
+        assert_eq!(*pred, literal_true());
+        assert!(Rc::ptr_eq(l, &left) && Rc::ptr_eq(r, &sub));
+        assert_eq!(
+            out.schema.fields, left.schema.fields,
+            "a semi join outputs the left's columns"
+        );
+        assert_idempotent(&out);
+    }
+
+    #[test]
+    fn not_exists_becomes_anti_join() {
+        let (left, sub) = (scan(), one_column_subquery());
+        let q = filter_of(exists(Rc::clone(&sub), true), Rc::clone(&left));
+        let out = canonicalize(q).unwrap();
+        let (kind, pred, l, r) = join_parts(&out);
+        assert_eq!(kind, JoinKind::Anti);
+        assert_eq!(*pred, literal_true());
+        assert!(Rc::ptr_eq(l, &left) && Rc::ptr_eq(r, &sub));
+        assert_idempotent(&out);
+    }
+
+    #[test]
+    fn in_subquery_becomes_semi_join_on_the_subquery_column() {
+        // `WHERE service IN (SELECT service …)` over a 3-column left: the
+        // subquery's column is `Column(3)` in the `left ++ right` scope.
+        let (left, sub) = (scan(), one_column_subquery());
+        let q = filter_of(
+            in_subquery(ScalarExpr::Column(1), Rc::clone(&sub), false),
+            Rc::clone(&left),
+        );
+        let out = canonicalize(q).unwrap();
+        let (kind, pred, l, r) = join_parts(&out);
+        assert_eq!(kind, JoinKind::Semi);
+        assert_eq!(
+            *pred,
+            ScalarExpr::Compare {
+                left: Box::new(ScalarExpr::Column(1)),
+                op: CompareOpKind::Eq,
+                right: Box::new(ScalarExpr::Column(3)),
+                semantics: ExprSemantics::Sql,
+            }
+        );
+        assert!(Rc::ptr_eq(l, &left) && Rc::ptr_eq(r, &sub));
+        assert_eq!(
+            out.schema.fields, left.schema.fields,
+            "a semi join outputs the left's columns"
+        );
+        assert_idempotent(&out);
+    }
+
+    #[test]
+    fn exists_with_other_conjuncts_keeps_an_outer_filter() {
+        // `WHERE value > 1 AND EXISTS (…)` → Filter{ value > 1 }{ Semi }.
+        let (left, sub) = (scan(), one_column_subquery());
+        let q = filter_of(
+            ScalarExpr::BoolAnd(vec![value_gt_1(), exists(Rc::clone(&sub), false)]),
+            Rc::clone(&left),
+        );
+        let out = canonicalize(q).unwrap();
+        let Some(NonASAPOp::Filter {
+            pred: Predicate(pred),
+            child,
+        }) = out.non_asap()
+        else {
+            panic!("expected an outer Filter, got {out:?}");
+        };
+        assert_eq!(*pred, value_gt_1());
+        let (kind, _, l, r) = join_parts(child);
+        assert_eq!(kind, JoinKind::Semi);
+        assert!(Rc::ptr_eq(l, &left) && Rc::ptr_eq(r, &sub));
+        assert_idempotent(&out);
+    }
+
+    #[test]
+    fn two_subquery_conjuncts_become_nested_joins() {
+        // `WHERE EXISTS (a) AND service NOT EXISTS (b) AND value > 1` sheds
+        // one conjunct per round: Filter{ value > 1 }{ Anti{ Semi{ l, a }, b } }.
+        let (left, a, b) = (scan(), one_column_subquery(), one_column_subquery());
+        let q = filter_of(
+            ScalarExpr::BoolAnd(vec![
+                exists(Rc::clone(&a), false),
+                exists(Rc::clone(&b), true),
+                value_gt_1(),
+            ]),
+            Rc::clone(&left),
+        );
+        let out = canonicalize(q).unwrap();
+        let Some(NonASAPOp::Filter {
+            pred: Predicate(pred),
+            child,
+        }) = out.non_asap()
+        else {
+            panic!("expected an outer Filter, got {out:?}");
+        };
+        assert_eq!(*pred, value_gt_1());
+        let (kind, _, inner, r) = join_parts(child);
+        assert_eq!(kind, JoinKind::Anti);
+        assert!(Rc::ptr_eq(r, &b));
+        let (kind, _, l, r) = join_parts(inner);
+        assert_eq!(kind, JoinKind::Semi);
+        assert!(Rc::ptr_eq(l, &left) && Rc::ptr_eq(r, &a));
+        assert_idempotent(&out);
+    }
+
+    #[test]
+    fn not_in_subquery_is_left_alone() {
+        let q = filter_of(
+            in_subquery(ScalarExpr::Column(1), one_column_subquery(), true),
+            scan(),
+        );
+        let out = canonicalize(Rc::clone(&q)).unwrap();
+        assert!(Rc::ptr_eq(&out, &q), "NOT IN keeps its Filter");
+        assert_idempotent(&out);
+    }
+
+    #[test]
+    fn lifted_subquery_is_canonicalized() {
+        // The subquery is itself a promotable heavy-hitter; once lifted into
+        // the join it is canonical, so a second pass finds nothing to do.
+        let sub = limit(5, 0, sort(desc(1), count_by_service()));
+        let q = filter_of(exists(sub, false), scan());
+        let out = canonicalize(q).unwrap();
+        let (_, _, _, r) = join_parts(&out);
+        assert!(is_topk_over_count(r));
+        assert_idempotent(&out);
+    }
+}
diff --git a/crates/types/src/ir/cse.rs b/crates/types/src/ir/cse.rs
new file mode 100644
index 000000000..eb6fc4bf7
--- /dev/null
+++ b/crates/types/src/ir/cse.rs
@@ -0,0 +1,791 @@
+//! Structural common-subexpression elimination over the unified operator IR:
+//! bottom-up hash-consing of [`OperatorNode`] DAGs across a workload's roots.
+//!
+//! CSE only runs on already-bound, already-canonicalized plans — structural
+//! matching is meaningless before canonicalization has converged
+//! semantically-equivalent queries onto one shape. [`share_common_sub_dags`]
+//! is the single entry point, run once per workload batch (a batch of one
+//! still deduplicates a query's own repeated sub-DAGs, see below).
+//!
+//! ## Algorithm: classic hash-consing / value-numbering
+//!
+//! Bottom-up: every child is interned before its parent, so two parents whose
+//! children were independently deduplicated down to the same `Rc`s are
+//! structurally identical iff their own fields also match, without re-walking
+//! the sub-DAGs. "Child" means everything [`OperatorNode::children`] returns:
+//! the operator inputs *and* the operator nodes a scalar expression reads
+//! (`PromqlScalarFromVector`, `ScalarSubquery`, `Exists`, `InSubquery`), so a
+//! vector read by `scalar(v)` in two queries is shared like any other input.
+//! The scalar expressions themselves stay opaque data on their owning node.
+//!
+//! ## Correctness: hash is a filter, `PartialEq` is the decision
+//!
+//! This is the one non-negotiable rule. A **false positive** here — two
+//! sub-DAGs wrongly judged shareable — is a wrong query answer, not a missed
+//! optimization: two different queries would read each other's data.
+//! [`structural_hash`] (SipHash over a canonical serialization, no
+//! collision-freedom guarantee) may only narrow the candidate set within one
+//! bucket; the typed equality check on that bucket ([`same_node`]) is what
+//! actually decides sharing, every time, no exceptions for "the hash probably
+//! didn't collide." Equality is intentionally conservative: it recognizes
+//! *exact* structural matches only, never "a stricter-accuracy summary could
+//! also answer a looser request" (that subsumption question belongs to the
+//! ASAP matcher, not here).
+//!
+//! ## Legality
+//!
+//! Structural equality is necessary but not sufficient. A non-ASAP node is
+//! only ever *returned* as a match for another when its output has a provable
+//! unique key (`Schema::has_unique_key()`): a producer's output can only be
+//! shared across consumers when its row identity is stable across reads, so
+//! an ungrouped aggregate, a `without(..)` grouping, a `Concat`/`SetOp` that
+//! drops its keys, … is always inserted fresh even when it is structurally
+//! identical to something already interned. An ASAP node (summary state and
+//! its evaluations) has no such gate: equal operator, schema and guarantee make
+//! it shareable, exactly as post-ASAP sharing decided before this IR.
+//!
+//! ## Single-query CSE falls out for free
+//!
+//! A repeated sub-expression within *one* query (the same grouped aggregate on
+//! both `BinaryOp` branches) is deduplicated by the same bottom-up interning —
+//! a workload of size one still interns bottom-up within that one DAG.
+
+use std::collections::hash_map::DefaultHasher;
+use std::collections::HashMap;
+use std::hash::{Hash, Hasher};
+use std::rc::Rc;
+
+use super::node::{Operator, OperatorNode};
+use super::non_asap::NonASAPOp;
+use crate::pre_asap::schema::Schema;
+
+/// [`structural_hash`]'s memoization cache: an already-hashed node's `Rc`
+/// pointer to its hash. A fresh cache is always correct; what matters is
+/// letting it persist across every node of one bottom-up pass rather than
+/// starting a new one per call. The caller must keep every cached node alive
+/// for the cache's lifetime, or a reused address would alias a stale entry.
+pub type HashCache = HashMap<*const OperatorNode, u64>;
+
+/// A constant stand-in for every child position. Substituting it before
+/// serializing or comparing a node leaves exactly the node's own fields.
+fn placeholder() -> Rc<OperatorNode> {
+    Rc::new(OperatorNode::with_schema(
+        Operator::NonASAP(NonASAPOp::Values {
+            rows: vec![],
+            schema: Schema::lifted(vec![], None),
+        }),
+        Schema::lifted(vec![], None),
+    ))
+}
+
+/// The operator with every child — operator inputs and the operator nodes
+/// referenced from its scalar expressions alike — replaced by
+/// [`placeholder`]. What remains is the node's own data: variant tag, scalar
+/// expressions (with their operator references blanked), parameters.
+fn own_fields(node: &OperatorNode) -> Operator {
+    let placeholder = placeholder();
+    node.operator.map_children(|_| Rc::clone(&placeholder))
+}
+
+/// Coarse structural hash used only to bucket [`InternTable::intern`]'s
+/// candidate search — never the sharing decision ([`same_node`] is).
+///
+/// `OperatorNode` carries `f64`s (`ScalarValue::Float64`, quantile targets,
+/// `ResultGuarantee` bounds, …), so it cannot derive `std::hash::Hash`. The
+/// hash is SipHash over two parts:
+///
+/// 1. the canonical JSON of [`own_fields`] plus `result_kind`, `schema`,
+///    `guarantee` and `timing` — every field `PartialEq` compares except the
+///    children. A scalar expression is serialized as data with each operator
+///    node it reads replaced by a constant placeholder, so a reference to an
+///    interned sub-DAG contributes nothing of its own here;
+/// 2. for every child in [`OperatorNode::children`] order (operator inputs,
+///    then scalar-referenced nodes), the child's own `structural_hash`,
+///    memoized in `cache` by `Rc` pointer identity.
+///
+/// Part 2 is what makes equal sub-DAGs hash equal whether they are reached
+/// through an operator input or through a `scalar(v)`, and what keeps the
+/// pass linear: a node is generally a DAG, and re-serializing a shared
+/// descendant once per parent would cost `O(sub-DAG)` per node instead of
+/// `O(1)` beyond the children's already-known hashes. A non-finite `f64`
+/// serializes as `null`, merely widening one (still equality-checked) bucket.
+pub fn structural_hash(node: &OperatorNode, cache: &mut HashCache) -> u64 {
+    fn child_hash(child: &Rc<OperatorNode>, cache: &mut HashCache) -> u64 {
+        let ptr = Rc::as_ptr(child);
+        if let Some(&h) = cache.get(&ptr) {
+            return h;
+        }
+        let h = structural_hash(child, cache);
+        cache.insert(ptr, h);
+        h
+    }
+
+    let mut hasher = DefaultHasher::new();
+    let own = (
+        own_fields(node),
+        node.result_kind,
+        &node.schema,
+        &node.guarantee,
+        node.timing,
+        &node.coverage,
+    );
+    serde_json::to_string(&own)
+        .unwrap_or_default()
+        .hash(&mut hasher);
+    for child in node.children() {
+        child_hash(child, cache).hash(&mut hasher);
+    }
+    hasher.finish()
+}
+
+/// Numeric `PartialEq` alone conflates signed zeros. The serialized check is
+/// additional evidence, never a replacement for typed equality (JSON maps
+/// non-finite floats to `null`). Used for the guarantee, whose bounds are
+/// floats a shared node must preserve bit-for-bit.
+fn same_value<T: PartialEq + serde::Serialize>(left: &T, right: &T) -> bool {
+    left == right
+        && match (serde_json::to_string(left), serde_json::to_string(right)) {
+            (Ok(left), Ok(right)) => left == right,
+            _ => false,
+        }
+}
+
+/// Memo of child-pair comparisons already decided by [`same_node`], keyed by
+/// pointer pair. Only interned (table-owned, hence alive) nodes are keys.
+type EqMemo = HashMap<(*const OperatorNode, *const OperatorNode), bool>;
+
+/// The sharing decision: typed equality of two nodes.
+///
+/// `OperatorNode`'s derived `PartialEq` would recurse into children by value
+/// even when both sides hold the same `Rc` (`OperatorNode` is not `Eq`, so
+/// `Rc` gets no pointer shortcut), expanding a shared diamond once per path.
+/// Children are therefore compared by pointer first; only when the pointers
+/// differ (an equal child that was not legal to share) are the values
+/// compared, memoized per pair so a diamond is still walked once.
+fn same_node(left: &OperatorNode, right: &OperatorNode, memo: &mut EqMemo) -> bool {
+    let (lc, rc) = (left.children(), right.children());
+    if lc.len() != rc.len() {
+        return false;
+    }
+    let children_equal = lc.iter().zip(&rc).all(|(a, b)| {
+        if Rc::ptr_eq(a, b) {
+            return true;
+        }
+        let key = (Rc::as_ptr(a), Rc::as_ptr(b));
+        if let Some(&eq) = memo.get(&key) {
+            return eq;
+        }
+        let eq = same_node(a, b, memo);
+        memo.insert(key, eq);
+        eq
+    });
+    children_equal
+        && left.result_kind == right.result_kind
+        && left.schema == right.schema
+        && left.timing == right.timing
+        && left.coverage == right.coverage
+        && same_value(&left.guarantee, &right.guarantee)
+        && same_value(&own_fields(left), &own_fields(right))
+}
+
+/// Bottom-up hash-consing table: structurally-equal, sharing-legal nodes
+/// collapse onto one `Rc`.
+///
+/// `buckets` is keyed by [`structural_hash`] — a coarse candidate filter
+/// only. Every entry within one bucket is a full node kept around for the
+/// [`same_node`] comparison that actually decides a match; a hash collision
+/// between structurally different nodes just means a harmless linear scan of
+/// a few extra candidates.
+struct InternTable {
+    buckets: HashMap<u64, Vec<Rc<OperatorNode>>>,
+    /// Persisted for the table's whole lifetime so hashing is `O(1)` per node
+    /// beyond its children; every cached node is owned by `buckets`.
+    hash_cache: HashCache,
+    eq_memo: EqMemo,
+}
+
+impl InternTable {
+    fn new() -> Self {
+        Self {
+            buckets: HashMap::new(),
+            hash_cache: HashMap::new(),
+            eq_memo: HashMap::new(),
+        }
+    }
+
+    /// Intern one node whose children are already interned: look it up by
+    /// [`structural_hash`], confirm with [`same_node`], and — only when
+    /// sharing is legal (module doc, "Legality") — return the existing `Rc`
+    /// instead of allocating a new one.
+    fn intern(&mut self, node: OperatorNode) -> Rc<OperatorNode> {
+        let hash = structural_hash(&node, &mut self.hash_cache);
+        // A node that is not legal to share is never *returned* as a match
+        // for something else; it still occupies a fresh slot in the bucket
+        // (harmless: later scans require legality of the new node too).
+        let reusable = node.is_asap() || node.schema.has_unique_key();
+        let bucket = self.buckets.entry(hash).or_default();
+        if reusable {
+            if let Some(existing) = bucket
+                .iter()
+                .find(|candidate| same_node(candidate, &node, &mut self.eq_memo))
+            {
+                return Rc::clone(existing);
+            }
+        }
+        let rc = Rc::new(node);
+        bucket.push(Rc::clone(&rc));
+        rc
+    }
+}
+
+/// Count of *unique* nodes reachable from `root` (pointer identity,
+/// following [`OperatorNode::children`]): the real size of the DAG, not a
+/// tree-walk count that re-counts a shared descendant once per parent.
+pub fn dag_node_count(root: &Rc<OperatorNode>) -> usize {
+    OperatorNode::reachable(root).len()
+}
+
+/// Input pointer → (input `Rc`, interned result). The input `Rc` is retained
+/// so its address cannot be freed and reused by a fresh allocation while the
+/// memo still maps it.
+type Visited = HashMap<*const OperatorNode, (Rc<OperatorNode>, Rc<OperatorNode>)>;
+
+/// Intern `node`'s children (recursively), then `node` itself. The rebuilt
+/// node keeps `node`'s retained schema, result kind, guarantee and timing:
+/// every child is replaced by an equal node, so each derived property stays
+/// valid, and the result is `PartialEq`-equal to the input.
+fn intern_bottom_up(
+    table: &mut InternTable,
+    visited: &mut Visited,
+    node: &Rc<OperatorNode>,
+) -> Rc<OperatorNode> {
+    if let Some((_, interned)) = visited.get(&Rc::as_ptr(node)) {
+        return Rc::clone(interned);
+    }
+    let operator = node
+        .operator
+        .map_children(|child| intern_bottom_up(table, visited, child));
+    let rebuilt = OperatorNode {
+        operator,
+        result_kind: node.result_kind,
+        schema: node.schema.clone(),
+        guarantee: node.guarantee.clone(),
+        timing: node.timing,
+        coverage: node.coverage.clone(),
+    };
+    let interned = table.intern(rebuilt);
+    visited.insert(Rc::as_ptr(node), (Rc::clone(node), Rc::clone(&interned)));
+    interned
+}
+
+/// Share structurally-identical, sharing-legal sub-DAGs across a workload's
+/// roots (or within one root). Every root's *value* is unchanged
+/// (`PartialEq`-equal to its input) — only its internal `Rc` structure may
+/// now alias another root's, or another part of its own DAG. A node already
+/// reached through two paths is visited once.
+///
+/// `Id` is caller-chosen — a workload entry's key, an index, a query name.
+pub fn share_common_sub_dags<Id>(
+    roots: Vec<(Id, Rc<OperatorNode>)>,
+) -> Vec<(Id, Rc<OperatorNode>)> {
+    let mut table = InternTable::new();
+    let mut visited = Visited::new();
+    roots
+        .into_iter()
+        .map(|(id, root)| (id, intern_bottom_up(&mut table, &mut visited, &root)))
+        .collect()
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::ir::asap::ASAPOp;
+    use crate::ir::operator_properties::{BinaryOpKind, GroupKeys, Reduction, Source};
+    use crate::ir::BinaryOperator;
+    use crate::ir::ScalarExpr;
+    use crate::post_asap::guarantee::ResultGuarantee;
+    use crate::post_asap::sketch::{
+        GroupingStrategy, SketchAlgorithm, SketchKind, SketchParams, SummaryUpdate,
+    };
+    use crate::pre_asap::agg_intent::AggIntent;
+    use crate::pre_asap::expr_ir::{ColumnRef, CompareOpKind};
+    use crate::pre_asap::schema::{DataType, Field, FieldDataType, Schema};
+
+    use crate::types::AccuracyTarget;
+
+    fn node(op: NonASAPOp) -> Rc<OperatorNode> {
+        OperatorNode::new_shared(crate::ir::Operator::NonASAP(op)).unwrap()
+    }
+
+    /// `[ts, service, value, latency]`, no unique key.
+    fn scan() -> Rc<OperatorNode> {
+        node(NonASAPOp::Scan {
+            source: Source::TimeSeries { metric: "m".into() },
+            predicates: vec![],
+            schema: Schema::with_time_index(
+                vec![
+                    Field::plain("ts", DataType::Timestamp, false),
+                    Field::plain("service", DataType::Utf8, false),
+                    Field::plain("value", DataType::Float64, false),
+                    Field::plain("latency", DataType::Float64, false),
+                ],
+                0,
+                vec![],
+            ),
+        })
+    }
+
+    fn quantile_agg(by: Vec<usize>, col: Option<usize>, q: f64) -> Rc<OperatorNode> {
+        node(NonASAPOp::Aggregate {
+            reduction: Reduction::by(by),
+            measures: vec![AggIntent::Quantile {
+                col,
+                q,
+                accuracy: AccuracyTarget::Exact,
+            }],
+            output_names: vec![],
+            filters: vec![],
+            having: None,
+            child: scan(),
+        })
+    }
+
+    fn compare(lhs: Rc<OperatorNode>, rhs: Rc<OperatorNode>) -> Rc<OperatorNode> {
+        node(NonASAPOp::BinaryOp {
+            operator: BinaryOperator {
+                checked_relative_division: false,
+                checked_finite_division: false,
+                kind: BinaryOpKind::Compare(CompareOpKind::Eq),
+                vector_match: None,
+            },
+            return_bool: false,
+            lhs,
+            rhs,
+        })
+    }
+
+    fn two_roots(a: Rc<OperatorNode>, b: Rc<OperatorNode>) -> (Rc<OperatorNode>, Rc<OperatorNode>) {
+        let shared = share_common_sub_dags(vec![("a", a), ("b", b)]);
+        let [(_, ra), (_, rb)] = shared.as_slice() else {
+            panic!("expected 2 roots");
+        };
+        (Rc::clone(ra), Rc::clone(rb))
+    }
+
+    #[test]
+    fn distinct_column_quantiles_do_not_merge() {
+        // Grouped (unique key present) so only the differing `col` blocks it.
+        let (ra, rb) = two_roots(
+            quantile_agg(vec![1], Some(2), 0.5),
+            quantile_agg(vec![1], Some(3), 0.5),
+        );
+        assert!(!Rc::ptr_eq(&ra, &rb));
+        assert_ne!(ra, rb);
+    }
+
+    #[test]
+    fn no_unique_keys_means_no_merge_even_when_structurally_identical() {
+        let a = quantile_agg(vec![], Some(2), 0.9);
+        let b = quantile_agg(vec![], Some(2), 0.9);
+        assert_eq!(a, b, "fixture sanity: structurally equal");
+        assert!(
+            !a.schema.has_unique_key(),
+            "fixture sanity: a global aggregate has no provable unique key"
+        );
+        let (ra, rb) = two_roots(a, b);
+        assert!(
+            !Rc::ptr_eq(&ra, &rb),
+            "no unique key ⇒ never hoisted, even for an identical structural match"
+        );
+    }
+
+    #[test]
+    fn median_and_explicit_half_percentile_merge() {
+        // Two spellings that lower to the identical grouped `Quantile { q: 0.5 }`.
+        let (m, p) = two_roots(
+            quantile_agg(vec![1], Some(2), 0.5),
+            quantile_agg(vec![1], Some(2), 0.5),
+        );
+        assert!(Rc::ptr_eq(&m, &p));
+    }
+
+    #[test]
+    fn single_query_shares_its_own_repeated_sub_dag() {
+        // One root with the same grouped aggregate on both branches, built as
+        // two separately-allocated sub-DAGs (no sharing yet).
+        let root = compare(
+            quantile_agg(vec![1], Some(2), 0.5),
+            quantile_agg(vec![1], Some(2), 0.5),
+        );
+        let shared = share_common_sub_dags(vec![("q", root)]);
+        let [(_, root)] = shared.as_slice() else {
+            panic!("expected 1 root");
+        };
+        let Some(NonASAPOp::BinaryOp { lhs, rhs, .. }) = root.non_asap() else {
+            panic!("expected BinaryOp root, got {root:?}");
+        };
+        assert!(Rc::ptr_eq(lhs, rhs));
+    }
+
+    #[test]
+    fn shared_root_value_is_unchanged() {
+        let a = quantile_agg(vec![1], Some(2), 0.5)
+            .as_ref()
+            .clone()
+            .with_guarantee(Some(ResultGuarantee::exact("fixture")));
+        let before = Rc::new(a);
+        let (ra, _) = two_roots(Rc::clone(&before), Rc::clone(&before));
+        assert_eq!(ra.as_ref(), before.as_ref());
+        assert!(
+            ra.guarantee.is_some(),
+            "retained properties survive the rebuild"
+        );
+    }
+
+    // ── scalar-referenced sub-DAGs ──────────────────────────────────────
+
+    /// `vector(scalar(sum by (service) (up)))`.
+    fn scalar_of_vector() -> Rc<OperatorNode> {
+        let sum_up = node(NonASAPOp::Aggregate {
+            reduction: Reduction::by(vec![1]),
+            measures: vec![AggIntent::Sum { col: Some(2) }],
+            output_names: vec![],
+            filters: vec![],
+            having: None,
+            child: scan(),
+        });
+        assert!(sum_up.schema.has_unique_key(), "fixture sanity");
+        node(NonASAPOp::PromqlVectorFromScalar(
+            ScalarExpr::PromqlScalarFromVector(sum_up),
+        ))
+    }
+
+    fn bridged_vector(root: &Rc<OperatorNode>) -> &Rc<OperatorNode> {
+        match root.non_asap() {
+            Some(NonASAPOp::PromqlVectorFromScalar(ScalarExpr::PromqlScalarFromVector(v))) => v,
+            other => panic!("expected vector(scalar(v)), got {other:?}"),
+        }
+    }
+
+    #[test]
+    fn scalar_referenced_vector_is_shared_across_queries() {
+        let (ra, rb) = two_roots(scalar_of_vector(), scalar_of_vector());
+        assert!(
+            Rc::ptr_eq(bridged_vector(&ra), bridged_vector(&rb)),
+            "the vector read by scalar(v) is a child and must be interned"
+        );
+        assert!(
+            !Rc::ptr_eq(&ra, &rb),
+            "the scalar bridge itself has no unique key and stays separate"
+        );
+    }
+
+    #[test]
+    fn structural_hash_sees_through_a_scalar_reference() {
+        // Two equal bridges must hash equal whether or not their referenced
+        // vector is the same Rc — the reference contributes the vector's
+        // memoized hash, not its identity.
+        let a = scalar_of_vector();
+        let b = scalar_of_vector();
+        let mut cache = HashMap::new();
+        assert_eq!(
+            structural_hash(&a, &mut cache),
+            structural_hash(&b, &mut cache)
+        );
+        assert_eq!(
+            cache.len(),
+            4,
+            "aggregate + scan cached once per root: {cache:?}"
+        );
+        let other = node(NonASAPOp::PromqlVectorFromScalar(
+            ScalarExpr::PromqlScalarFromVector(quantile_agg(vec![1], Some(2), 0.5)),
+        ));
+        assert_ne!(
+            structural_hash(&a, &mut cache),
+            structural_hash(&other, &mut cache)
+        );
+    }
+
+    // ── ASAP nodes ──────────────────────────────────────────────────────
+
+    fn summary_agg(alpha: f64, guarantee: Option<ResultGuarantee>) -> Rc<OperatorNode> {
+        let family = FieldDataType::Sketch(
+            SketchKind::new(SketchAlgorithm::DDSketch, SketchParams::DDSketch { alpha }),
+            GroupingStrategy::default(),
+        );
+        let schema = Schema::lifted(vec![Field::new("state", family.clone(), false)], None);
+        assert!(!schema.has_unique_key(), "fixture sanity");
+        Rc::new(
+            OperatorNode::with_schema(
+                Operator::ASAP(ASAPOp::SummaryAgg {
+                    child: scan(),
+                    family,
+                    input: SummaryUpdate::column(ColumnRef::SampleValue),
+                    reduction: Reduction::PerEntity,
+                    grouping: GroupingStrategy::default(),
+                    filter: None,
+                }),
+                schema,
+            )
+            .with_guarantee(guarantee),
+        )
+    }
+
+    #[test]
+    fn asap_nodes_share_without_a_unique_key() {
+        let exact = || Some(ResultGuarantee::exact("fixture"));
+        let (ra, rb) = two_roots(summary_agg(0.01, exact()), summary_agg(0.01, exact()));
+        assert!(Rc::ptr_eq(&ra, &rb));
+        assert!(ra.guarantee.is_some());
+    }
+
+    #[test]
+    fn asap_nodes_with_distinct_parameters_or_guarantees_are_not_shared() {
+        let exact = || Some(ResultGuarantee::exact("fixture"));
+        let (ra, rb) = two_roots(summary_agg(0.01, exact()), summary_agg(0.001, exact()));
+        assert!(!Rc::ptr_eq(&ra, &rb), "different sketch parameters");
+        let (ra, rb) = two_roots(summary_agg(0.01, exact()), summary_agg(0.01, None));
+        assert!(
+            !Rc::ptr_eq(&ra, &rb),
+            "an unknown guarantee never borrows an exact one"
+        );
+        assert!(rb.guarantee.is_none());
+    }
+
+    #[test]
+    fn evaluations_share_their_producer_but_not_each_other() {
+        use crate::post_asap::sketch::SketchStatistic;
+        let evaluation = |q: f64| {
+            Rc::new(OperatorNode::with_schema(
+                Operator::ASAP(ASAPOp::SummaryEstimate {
+                    summary_input: summary_agg(0.01, None),
+                    query: SketchStatistic::Quantile { q },
+                }),
+                Schema::lifted(
+                    vec![Field::plain("quantile", DataType::Float64, false)],
+                    None,
+                ),
+            ))
+        };
+        let (p95, p99) = two_roots(evaluation(0.95), evaluation(0.99));
+        let producer = |n: &Rc<OperatorNode>| Rc::clone(n.children()[0]);
+        assert!(!Rc::ptr_eq(&p95, &p99));
+        assert!(Rc::ptr_eq(&producer(&p95), &producer(&p99)));
+    }
+
+    // ── structural_hash (DAG-aware memoization) ─────────────────────────
+
+    #[test]
+    fn structural_hash_is_stable_across_cache_states() {
+        let agg = quantile_agg(vec![1], Some(2), 0.5);
+        let mut cold = HashMap::new();
+        let mut warm = HashMap::new();
+        structural_hash(&scan(), &mut warm);
+        assert_eq!(
+            structural_hash(&agg, &mut cold),
+            structural_hash(&agg, &mut warm),
+            "hash must be independent of unrelated cache state"
+        );
+    }
+
+    #[test]
+    fn structural_hash_of_an_internally_shared_dag_matches_the_unshared_equivalent() {
+        let agg = quantile_agg(vec![1], Some(2), 0.5);
+        let shared_root = compare(Rc::clone(&agg), Rc::clone(&agg));
+        let unshared_root = compare(
+            quantile_agg(vec![1], Some(2), 0.5),
+            quantile_agg(vec![1], Some(2), 0.5),
+        );
+        assert_eq!(
+            structural_hash(&shared_root, &mut HashMap::new()),
+            structural_hash(&unshared_root, &mut HashMap::new()),
+        );
+    }
+
+    #[test]
+    fn structural_hash_memoizes_a_shared_descendant_exactly_once() {
+        let agg = quantile_agg(vec![1], Some(2), 0.5);
+        let root = compare(Rc::clone(&agg), Rc::clone(&agg));
+        let mut cache = HashMap::new();
+        structural_hash(&root, &mut cache);
+        assert_eq!(
+            cache.len(),
+            2,
+            "one entry per unique node in the shared branch (Aggregate + Scan): {cache:?}"
+        );
+    }
+
+    // ── dag_node_count ───────────────────────────────────────────────────
+
+    #[test]
+    fn dag_node_count_is_the_naive_count_when_nothing_is_shared() {
+        assert_eq!(dag_node_count(&scan()), 1);
+        assert_eq!(dag_node_count(&quantile_agg(vec![1], Some(2), 0.5)), 2);
+        assert_eq!(
+            dag_node_count(&scalar_of_vector()),
+            3,
+            "follows scalar references"
+        );
+    }
+
+    #[test]
+    fn dag_node_count_deduplicates_an_internally_shared_sub_dag() {
+        let root = compare(
+            quantile_agg(vec![1], Some(2), 0.5),
+            quantile_agg(vec![1], Some(2), 0.5),
+        );
+        assert_eq!(
+            dag_node_count(&root),
+            5,
+            "fixture sanity: nothing shared yet"
+        );
+        let shared = share_common_sub_dags(vec![("q", root)]);
+        let [(_, root)] = shared.as_slice() else {
+            panic!("expected 1 root");
+        };
+        assert_eq!(
+            dag_node_count(root),
+            3,
+            "BinaryOp + one Aggregate + its Scan"
+        );
+    }
+
+    #[test]
+    fn dag_node_count_deduplicates_across_two_workload_roots() {
+        let (ra, rb) = two_roots(
+            quantile_agg(vec![1], Some(2), 0.5),
+            quantile_agg(vec![1], Some(2), 0.5),
+        );
+        assert!(Rc::ptr_eq(&ra, &rb), "fixture sanity: the two roots merged");
+        assert_eq!(dag_node_count(&ra), 2);
+        assert_eq!(dag_node_count(&rb), 2);
+    }
+
+    #[test]
+    fn dedup_gates_sharing_the_same_as_aggregate() {
+        // `Dedup { cols }` adds `cols` as a unique key, so two identical
+        // `Dedup`s merge even though their keyless `Scan`s could not.
+        let dedup = || {
+            node(NonASAPOp::Dedup {
+                cols: vec![1],
+                child: scan(),
+            })
+        };
+        let (ra, rb) = two_roots(dedup(), dedup());
+        assert!(Rc::ptr_eq(&ra, &rb));
+    }
+
+    #[test]
+    fn group_keys_gate_still_prevented_when_partition_by_without_used() {
+        let without_agg = || {
+            node(NonASAPOp::Aggregate {
+                reduction: Reduction::Reduce(GroupKeys::without(vec![0])),
+                measures: vec![AggIntent::Count {
+                    accuracy: AccuracyTarget::Exact,
+                }],
+                output_names: vec![],
+                filters: vec![],
+                having: None,
+                child: scan(),
+            })
+        };
+        let a = without_agg();
+        assert!(!a.schema.has_unique_key());
+        let (ra, rb) = two_roots(a, without_agg());
+        assert!(!Rc::ptr_eq(&ra, &rb));
+    }
+
+    #[test]
+    fn already_shared_nodes_are_visited_once() {
+        // A diamond already present in the input stays one node and is not
+        // re-interned per path.
+        let agg = quantile_agg(vec![1], Some(2), 0.5);
+        let root = compare(Rc::clone(&agg), Rc::clone(&agg));
+        let shared = share_common_sub_dags(vec![("q", root)]);
+        let Some(NonASAPOp::BinaryOp { lhs, rhs, .. }) = shared[0].1.non_asap() else {
+            panic!("expected BinaryOp root");
+        };
+        assert!(Rc::ptr_eq(lhs, rhs));
+        assert_eq!(dag_node_count(&shared[0].1), 3);
+    }
+
+    // Comparing a shareable node whose equal-but-unshareable children form a
+    // deep diamond must not expand the diamond once per path. The timeout is
+    // a coarse runaway guard, not a performance SLA.
+    #[test]
+    fn shared_diamond_does_not_expand_during_comparison() {
+        let (done, completion) = std::sync::mpsc::channel();
+        let worker = std::thread::spawn(move || {
+            fn keyed_diamond() -> Rc<OperatorNode> {
+                // BinaryOp over a keyless scan has no unique key at any level,
+                // so none of the 24 levels is shareable; the `Dedup` on top is.
+                let mut current = scan();
+                for _ in 0..24 {
+                    current = compare(Rc::clone(&current), current);
+                }
+                node(NonASAPOp::Dedup {
+                    cols: vec![1],
+                    child: current,
+                })
+            }
+            let (ra, rb) = two_roots(keyed_diamond(), keyed_diamond());
+            assert!(Rc::ptr_eq(&ra, &rb));
+            done.send(()).unwrap();
+        });
+        completion
+            .recv_timeout(std::time::Duration::from_secs(5))
+            .expect("comparison expanded the shared DAG");
+        worker.join().unwrap();
+    }
+
+    /// A keyed (hence shareable) projection emitting the literal `value`.
+    fn keyed_literal(value: f64) -> Rc<OperatorNode> {
+        let keyed = node(NonASAPOp::Scan {
+            source: Source::TimeSeries { metric: "m".into() },
+            predicates: vec![],
+            schema: Schema::with_time_index(
+                vec![
+                    Field::plain("ts", DataType::Timestamp, false),
+                    Field::plain("service", DataType::Utf8, false),
+                ],
+                0,
+                vec![vec![1]],
+            ),
+        });
+        node(NonASAPOp::Project {
+            cols: vec![
+                crate::ir::ProjectItem {
+                    alias: None,
+                    expr: ScalarExpr::Column(1),
+                },
+                crate::ir::ProjectItem {
+                    alias: Some("v".into()),
+                    expr: ScalarExpr::literal_f64(value),
+                },
+            ],
+            qualifier: None,
+            child: keyed,
+        })
+    }
+
+    /// Sharing preserves IEEE signed zero, and JSON's `null` encoding of
+    /// non-finite floats never becomes the equality decision.
+    #[test]
+    fn signed_zero_and_nonfinite_values_remain_distinct() {
+        assert!(
+            keyed_literal(0.0).schema.has_unique_key(),
+            "fixture is shareable"
+        );
+        for (a, b) in [
+            (0.0, -0.0),
+            (-0.0, 0.0),
+            (f64::INFINITY, f64::NEG_INFINITY),
+            (f64::NAN, f64::NAN),
+        ] {
+            let (ra, rb) = two_roots(keyed_literal(a), keyed_literal(b));
+            assert!(!Rc::ptr_eq(&ra, &rb), "{a} and {b} must not be shared");
+        }
+        let (ra, rb) = two_roots(keyed_literal(f64::INFINITY), keyed_literal(f64::INFINITY));
+        assert!(Rc::ptr_eq(&ra, &rb));
+    }
+}
diff --git a/crates/types/src/ir/export.rs b/crates/types/src/ir/export.rs
new file mode 100644
index 000000000..4325096a6
--- /dev/null
+++ b/crates/types/src/ir/export.rs
@@ -0,0 +1,334 @@
+//! Phase-free logical ASAP DAG transport (planner-layering stage 1).
+//!
+//! This representation preserves operator semantics and summary state types.
+//! Timing is derived from materialization during physical planning;
+//! physical implementation, materialization and retention remain downstream.
+use std::collections::{HashMap, HashSet};
+use std::rc::Rc;
+
+use serde::{Deserialize, Serialize};
+use thiserror::Error;
+
+use super::wire::{grouping_compatibility, input_edges, payload_of};
+pub use super::wire::{
+    EdgeRole, GroupingEdgeCompatibility, LogicalASAPNodeId, LogicalASAPOperatorPayload,
+    WireScalarExpr,
+};
+use super::{ASAPOp, Operator, OperatorNode, OperatorResultKind, QueryRoot, SchemaDerivationError};
+use crate::post_asap::guarantee::ResultGuarantee;
+use crate::pre_asap::{FieldDataType, Schema};
+
+/// Independent envelope version: this replaces the older phase-assigned format.
+pub const LOGICAL_ASAP_DAG_WIRE_VERSION: u32 = 1;
+
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+#[serde(deny_unknown_fields)]
+pub struct LogicalASAPDAGNode {
+    pub id: LogicalASAPNodeId,
+    pub payload: LogicalASAPOperatorPayload,
+    pub result_kind: OperatorResultKind,
+    pub output_schema: Schema,
+    pub guarantee: Option<ResultGuarantee>,
+    #[serde(default)]
+    pub coverage: Option<super::summary_coverage::SummaryCoverage>,
+}
+
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+#[serde(deny_unknown_fields)]
+pub struct LogicalASAPDAGEdge {
+    pub producer: LogicalASAPNodeId,
+    pub consumer: LogicalASAPNodeId,
+    pub role: EdgeRole,
+    pub intermediate_schema: Schema,
+    pub grouping: GroupingEdgeCompatibility,
+}
+
+/// Standalone scalars remain scalar roots rather than fabricated operator nodes.
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+#[serde(deny_unknown_fields)]
+pub enum LogicalASAPQueryRoot {
+    Operator(LogicalASAPNodeId),
+    Scalar(WireScalarExpr),
+}
+impl LogicalASAPQueryRoot {
+    pub fn operator_refs(&self) -> Vec<LogicalASAPNodeId> {
+        match self {
+            Self::Operator(id) => vec![*id],
+            Self::Scalar(expr) => expr.operator_refs(),
+        }
+    }
+}
+
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+#[serde(deny_unknown_fields)]
+pub struct LogicalASAPDAG {
+    pub nodes: Vec<LogicalASAPDAGNode>,
+    pub edges: Vec<LogicalASAPDAGEdge>,
+    pub root: LogicalASAPQueryRoot,
+}
+
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+#[serde(deny_unknown_fields)]
+pub struct LogicalASAPDAGDocument {
+    pub schema_version: u32,
+    pub dag: LogicalASAPDAG,
+}
+
+#[derive(Debug, Clone, PartialEq, Eq, Error)]
+pub enum LogicalASAPDAGValidationError {
+    #[error("unsupported logical ASAP DAG version {0}")]
+    UnsupportedVersion(u32),
+    #[error("duplicate logical node {0:?}")]
+    DuplicateNode(LogicalASAPNodeId),
+    #[error("missing logical node {0:?}")]
+    MissingNode(LogicalASAPNodeId),
+    #[error("edge schema differs from producer {0:?}")]
+    EdgeSchemaMismatch(LogicalASAPNodeId),
+    #[error("summary node {0:?} schema does not contain its declared family/grouping")]
+    SummarySchemaMismatch(LogicalASAPNodeId),
+    #[error("invalid summary coverage at {0:?}")]
+    InvalidCoverage(LogicalASAPNodeId),
+    #[error("logical ASAP DAG contains a cycle")]
+    Cycle,
+    #[error("unreachable logical node {0:?}")]
+    UnreachableNode(LogicalASAPNodeId),
+}
+
+impl LogicalASAPDAGDocument {
+    pub fn new(dag: LogicalASAPDAG) -> Self {
+        Self {
+            schema_version: LOGICAL_ASAP_DAG_WIRE_VERSION,
+            dag,
+        }
+    }
+
+    pub fn validate(&self) -> Result<(), LogicalASAPDAGValidationError> {
+        if self.schema_version != LOGICAL_ASAP_DAG_WIRE_VERSION {
+            return Err(LogicalASAPDAGValidationError::UnsupportedVersion(
+                self.schema_version,
+            ));
+        }
+        self.dag.validate()
+    }
+}
+
+impl LogicalASAPDAG {
+    /// Transport integrity checks; full operator/scalar typing is checked on
+    /// the in-memory IR before compilation.
+    pub fn validate(&self) -> Result<(), LogicalASAPDAGValidationError> {
+        let mut nodes = HashMap::new();
+        for node in &self.nodes {
+            if nodes.insert(node.id, node).is_some() {
+                return Err(LogicalASAPDAGValidationError::DuplicateNode(node.id));
+            }
+            if let Some(coverage) = &node.coverage {
+                if node.result_kind != OperatorResultKind::State || coverage.validate().is_err() {
+                    return Err(LogicalASAPDAGValidationError::InvalidCoverage(node.id));
+                }
+            }
+            if let LogicalASAPOperatorPayload::SummaryAgg {
+                family, grouping, ..
+            } = &node.payload
+            {
+                if !node.output_schema.fields.iter().any(|field| &field.dtype == family)
+                    || node.output_schema.fields.iter().any(|field| matches!(&field.dtype, FieldDataType::Sketch(_, actual) if actual != grouping)) {
+                    return Err(LogicalASAPDAGValidationError::SummarySchemaMismatch(node.id));
+                }
+            }
+        }
+        let roots = self.root.operator_refs();
+        for root in &roots {
+            if !nodes.contains_key(root) {
+                return Err(LogicalASAPDAGValidationError::MissingNode(*root));
+            }
+        }
+        let mut inputs: HashMap<_, Vec<_>> = HashMap::new();
+        for edge in &self.edges {
+            let producer = nodes
+                .get(&edge.producer)
+                .ok_or(LogicalASAPDAGValidationError::MissingNode(edge.producer))?;
+            if !nodes.contains_key(&edge.consumer) {
+                return Err(LogicalASAPDAGValidationError::MissingNode(edge.consumer));
+            }
+            if edge.intermediate_schema != producer.output_schema {
+                return Err(LogicalASAPDAGValidationError::EdgeSchemaMismatch(
+                    edge.producer,
+                ));
+            }
+            inputs.entry(edge.consumer).or_default().push(edge.producer);
+        }
+        for node in &self.nodes {
+            if matches!(node.payload, LogicalASAPOperatorPayload::SummaryMerge) {
+                let coverage = inputs
+                    .get(&node.id)
+                    .into_iter()
+                    .flatten()
+                    .map(|id| {
+                        nodes[id]
+                            .coverage
+                            .clone()
+                            .ok_or(LogicalASAPDAGValidationError::InvalidCoverage(node.id))
+                    })
+                    .collect::<Result<Vec<_>, _>>()?;
+                let merged = super::summary_coverage::SummaryCoverage::merge_disjoint(&coverage)
+                    .map_err(|_| LogicalASAPDAGValidationError::InvalidCoverage(node.id))?;
+                if node.coverage.as_ref() != Some(&merged) {
+                    return Err(LogicalASAPDAGValidationError::InvalidCoverage(node.id));
+                }
+            }
+        }
+        fn visit(
+            id: LogicalASAPNodeId,
+            inputs: &HashMap<LogicalASAPNodeId, Vec<LogicalASAPNodeId>>,
+            active: &mut HashSet<LogicalASAPNodeId>,
+            done: &mut HashSet<LogicalASAPNodeId>,
+        ) -> Result<(), LogicalASAPDAGValidationError> {
+            if done.contains(&id) {
+                return Ok(());
+            }
+            if !active.insert(id) {
+                return Err(LogicalASAPDAGValidationError::Cycle);
+            }
+            for child in inputs.get(&id).into_iter().flatten() {
+                visit(*child, inputs, active, done)?;
+            }
+            active.remove(&id);
+            done.insert(id);
+            Ok(())
+        }
+        let mut done = HashSet::new();
+        for root in roots {
+            visit(root, &inputs, &mut HashSet::new(), &mut done)?;
+        }
+        if let Some(id) = nodes.keys().find(|id| !done.contains(id)) {
+            return Err(LogicalASAPDAGValidationError::UnreachableNode(*id));
+        }
+        Ok(())
+    }
+}
+
+/// Compiler-local identity mapping; IDs are local to this logical export.
+#[derive(Debug, Clone)]
+pub struct LogicalASAPNodeIdentityMap {
+    nodes_by_id: Vec<Rc<OperatorNode>>,
+}
+
+impl LogicalASAPNodeIdentityMap {
+    pub fn node_id(&self, node: &Rc<OperatorNode>) -> Option<LogicalASAPNodeId> {
+        self.nodes_by_id
+            .iter()
+            .position(|candidate| Rc::ptr_eq(candidate, node))
+            .map(|id| LogicalASAPNodeId(id as u32))
+    }
+    pub fn operator_node(&self, id: LogicalASAPNodeId) -> Option<&Rc<OperatorNode>> {
+        self.nodes_by_id.get(id.0 as usize)
+    }
+}
+
+#[derive(Debug, Clone)]
+pub struct LogicalASAPDAGCompilation {
+    pub dag: LogicalASAPDAG,
+    pub node_ids: LogicalASAPNodeIdentityMap,
+}
+
+pub fn compile_logical_asap_dag(
+    root: &Rc<OperatorNode>,
+) -> Result<LogicalASAPDAG, SchemaDerivationError> {
+    Ok(compile_logical_asap_dag_with_node_ids(root)?.dag)
+}
+
+pub fn compile_logical_asap_dag_with_node_ids(
+    root: &Rc<OperatorNode>,
+) -> Result<LogicalASAPDAGCompilation, SchemaDerivationError> {
+    compile_logical_asap_query_with_node_ids(&QueryRoot::Operator(Rc::clone(root)))
+}
+
+pub fn compile_logical_asap_query(
+    root: &QueryRoot,
+) -> Result<LogicalASAPDAG, SchemaDerivationError> {
+    Ok(compile_logical_asap_query_with_node_ids(root)?.dag)
+}
+
+pub fn compile_logical_asap_query_with_node_ids(
+    root: &QueryRoot,
+) -> Result<LogicalASAPDAGCompilation, SchemaDerivationError> {
+    root.validate_structure()?;
+    let mut exporter = Exporter::default();
+    let root = match root {
+        QueryRoot::Operator(node) => LogicalASAPQueryRoot::Operator(exporter.visit(node)),
+        QueryRoot::Scalar(expr) => {
+            for node in expr.operator_refs() {
+                exporter.visit(node);
+            }
+            LogicalASAPQueryRoot::Scalar(WireScalarExpr::from_expr(expr, &mut |n| {
+                exporter.ids[&Rc::as_ptr(n)]
+            }))
+        }
+    };
+    let dag = LogicalASAPDAG {
+        nodes: exporter.nodes,
+        edges: exporter.edges,
+        root,
+    };
+    Ok(LogicalASAPDAGCompilation {
+        dag,
+        node_ids: LogicalASAPNodeIdentityMap {
+            nodes_by_id: exporter.nodes_by_id,
+        },
+    })
+}
+
+#[derive(Default)]
+struct Exporter {
+    ids: HashMap<*const OperatorNode, LogicalASAPNodeId>,
+    nodes: Vec<LogicalASAPDAGNode>,
+    edges: Vec<LogicalASAPDAGEdge>,
+    nodes_by_id: Vec<Rc<OperatorNode>>,
+}
+
+impl Exporter {
+    fn visit(&mut self, node: &Rc<OperatorNode>) -> LogicalASAPNodeId {
+        if let Some(id) = self.ids.get(&Rc::as_ptr(node)) {
+            return *id;
+        }
+        let mut producers = Vec::new();
+        for (child, role) in input_edges(&node.operator) {
+            producers.push((self.visit(child), child, role));
+        }
+        let scalars = match &node.operator {
+            Operator::NonASAP(op) => op.scalar_exprs(),
+            Operator::ASAP(ASAPOp::SummaryAgg {
+                filter: Some(filter),
+                ..
+            }) => vec![&filter.0],
+            _ => vec![],
+        };
+        for expr in scalars {
+            for referenced in expr.operator_refs() {
+                producers.push((self.visit(referenced), referenced, EdgeRole::ScalarRef));
+            }
+        }
+        let id = LogicalASAPNodeId(self.nodes.len() as u32);
+        let payload = payload_of(&node.operator, &mut |n| self.ids[&Rc::as_ptr(n)]);
+        self.nodes.push(LogicalASAPDAGNode {
+            id,
+            payload,
+            result_kind: node.result_kind,
+            output_schema: node.schema.clone(),
+            guarantee: node.guarantee.clone(),
+            coverage: node.coverage.clone(),
+        });
+        self.nodes_by_id.push(Rc::clone(node));
+        self.ids.insert(Rc::as_ptr(node), id);
+        for (producer, child, role) in producers {
+            self.edges.push(LogicalASAPDAGEdge {
+                producer,
+                consumer: id,
+                role,
+                intermediate_schema: child.schema.clone(),
+                grouping: grouping_compatibility(&child.operator, &node.operator),
+            });
+        }
+        id
+    }
+}
diff --git a/crates/types/src/ir/mod.rs b/crates/types/src/ir/mod.rs
index fcb2eb49b..04b9f33e3 100644
--- a/crates/types/src/ir/mod.rs
+++ b/crates/types/src/ir/mod.rs
@@ -16,5 +16,9 @@ pub use non_asap::{BinaryOperator, NonASAPOp, TimeRangeKind};
 pub use query::QueryRoot;
 pub use scalar::{ExprSemantics, Predicate, ProjectItem, ScalarExpr, SortKey};
 
+pub mod canonicalize;
+pub mod cse;
+pub mod export;
 /// Semantic observation coverage, separate from field layout and physical timing.
 pub mod summary_coverage;
+mod wire;
diff --git a/crates/types/src/ir/wire.rs b/crates/types/src/ir/wire.rs
new file mode 100644
index 000000000..a36243c3c
--- /dev/null
+++ b/crates/types/src/ir/wire.rs
@@ -0,0 +1,746 @@
+//! Flat operator/scalar payloads shared by logical transport.
+use std::rc::Rc;
+use std::time::Duration;
+
+use serde::{Deserialize, Serialize};
+
+use super::asap::ASAPOp;
+use super::node::{Operator, OperatorNode};
+use super::non_asap::{BinaryOperator, NonASAPOp, TimeRangeKind};
+use super::scalar::{ExprSemantics, Predicate, ProjectItem, ScalarExpr, SortKey};
+use crate::ir::operator_properties::{
+    ConcatDiscriminatorKey, GroupKeys, InfoMatcher, JoinKind, Reduction, RelationalSetOpKind,
+    SampleKind, Source, TimeShift, WindowFrame, WindowFuncKind,
+};
+use crate::post_asap::maintained_population::{MaintainedPopulation, PopulationStatistic};
+use crate::post_asap::sketch::{GroupingStrategy, SketchStatistic, SummaryUpdate};
+use crate::pre_asap::agg_intent::AggIntent;
+use crate::pre_asap::expr_ir::{ArithmeticOpKind, CompareOpKind, ScalarValue};
+use crate::pre_asap::schema::{ColumnId, DataType, FieldDataType, Schema};
+
+#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
+pub enum EdgeRole {
+    Input,
+    Left,
+    Right,
+    /// The consumer reads the producer from inside one of its scalar
+    /// expressions (`scalar(v)`, a scalar subquery, `EXISTS`, `IN`).
+    ScalarRef,
+}
+
+#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
+pub enum GroupingEdgeCompatibility {
+    Identical,
+    ConsumerCoarsensProducer,
+    Incompatible,
+    NotApplicable,
+}
+
+/// Stable identity of a node within one exported logical ASAP DAG.
+#[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord, Hash, Serialize, Deserialize)]
+#[serde(transparent)]
+pub struct LogicalASAPNodeId(pub u32);
+
+// ── Wire mirrors of the scalar language ──────────────────────────────────
+
+/// [`ScalarExpr`] with every operator reference replaced by the id of the
+/// exported node (connected to the owner by an [`EdgeRole::ScalarRef`] edge).
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+pub enum WireScalarExpr {
+    Column(ColumnId),
+    Literal(ScalarValue),
+    Negative {
+        expr: Box<WireScalarExpr>,
+        semantics: ExprSemantics,
+    },
+    Compare {
+        left: Box<WireScalarExpr>,
+        op: CompareOpKind,
+        right: Box<WireScalarExpr>,
+        semantics: ExprSemantics,
+    },
+    BoolAnd(Vec<WireScalarExpr>),
+    BoolOr(Vec<WireScalarExpr>),
+    Not(Box<WireScalarExpr>),
+    IsNull(Box<WireScalarExpr>),
+    IsNotNull(Box<WireScalarExpr>),
+    Cast {
+        expr: Box<WireScalarExpr>,
+        to: DataType,
+        try_cast: bool,
+    },
+    InList {
+        expr: Box<WireScalarExpr>,
+        list: Vec<WireScalarExpr>,
+        negated: bool,
+    },
+    FunctionCall {
+        name: String,
+        args: Vec<WireScalarExpr>,
+    },
+    Arithmetic {
+        op: ArithmeticOpKind,
+        left: Box<WireScalarExpr>,
+        right: Box<WireScalarExpr>,
+        semantics: ExprSemantics,
+    },
+    Case {
+        operand: Option<Box<WireScalarExpr>>,
+        branches: Vec<(WireScalarExpr, WireScalarExpr)>,
+        else_expr: Option<Box<WireScalarExpr>>,
+    },
+    CurrentTimestamp,
+    EvalTimestamp,
+    PromqlScalarFromVector(LogicalASAPNodeId),
+    ScalarSubquery(LogicalASAPNodeId),
+    Exists {
+        subquery: LogicalASAPNodeId,
+        negated: bool,
+    },
+    InSubquery {
+        expr: Box<WireScalarExpr>,
+        subquery: LogicalASAPNodeId,
+        negated: bool,
+    },
+}
+
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+pub struct WirePredicate(pub WireScalarExpr);
+
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+pub struct WireProjectItem {
+    pub alias: Option<String>,
+    pub expr: WireScalarExpr,
+}
+
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+pub struct WireSortKey {
+    pub expr: WireScalarExpr,
+    pub ascending: bool,
+    pub nulls_first: bool,
+}
+
+impl WireScalarExpr {
+    /// Explicit producer IDs recursively referenced by this scalar tree.
+    pub fn operator_refs(&self) -> Vec<LogicalASAPNodeId> {
+        fn collect(expr: &WireScalarExpr, out: &mut Vec<LogicalASAPNodeId>) {
+            use WireScalarExpr::*;
+            match expr {
+                PromqlScalarFromVector(id) | ScalarSubquery(id) => out.push(*id),
+                Exists { subquery, .. } => out.push(*subquery),
+                InSubquery { expr, subquery, .. } => {
+                    out.push(*subquery);
+                    collect(expr, out);
+                }
+                Negative { expr, .. }
+                | Not(expr)
+                | IsNull(expr)
+                | IsNotNull(expr)
+                | Cast { expr, .. } => collect(expr, out),
+                Compare { left, right, .. } | Arithmetic { left, right, .. } => {
+                    collect(left, out);
+                    collect(right, out);
+                }
+                BoolAnd(args) | BoolOr(args) | FunctionCall { args, .. } => {
+                    for expr in args {
+                        collect(expr, out);
+                    }
+                }
+                InList { expr, list, .. } => {
+                    collect(expr, out);
+                    for expr in list {
+                        collect(expr, out);
+                    }
+                }
+                Case {
+                    operand,
+                    branches,
+                    else_expr,
+                } => {
+                    if let Some(expr) = operand {
+                        collect(expr, out);
+                    }
+                    for (when, then) in branches {
+                        collect(when, out);
+                        collect(then, out);
+                    }
+                    if let Some(expr) = else_expr {
+                        collect(expr, out);
+                    }
+                }
+                Column(_) | Literal(_) | CurrentTimestamp | EvalTimestamp => {}
+            }
+        }
+        let mut out = Vec::new();
+        collect(self, &mut out);
+        out
+    }
+
+    /// Mirror `expr`, resolving every operator reference through `id_of`.
+    pub fn from_expr(
+        expr: &ScalarExpr,
+        id_of: &mut impl FnMut(&Rc<OperatorNode>) -> LogicalASAPNodeId,
+    ) -> Self {
+        fn boxed(
+            e: &ScalarExpr,
+            id_of: &mut impl FnMut(&Rc<OperatorNode>) -> LogicalASAPNodeId,
+        ) -> Box<WireScalarExpr> {
+            Box::new(WireScalarExpr::from_expr(e, id_of))
+        }
+        fn list(
+            es: &[ScalarExpr],
+            id_of: &mut impl FnMut(&Rc<OperatorNode>) -> LogicalASAPNodeId,
+        ) -> Vec<WireScalarExpr> {
+            es.iter()
+                .map(|e| WireScalarExpr::from_expr(e, id_of))
+                .collect()
+        }
+        match expr {
+            ScalarExpr::Column(id) => WireScalarExpr::Column(*id),
+            ScalarExpr::Literal(v) => WireScalarExpr::Literal(v.clone()),
+            ScalarExpr::Negative { expr, semantics } => WireScalarExpr::Negative {
+                expr: boxed(expr, id_of),
+                semantics: *semantics,
+            },
+            ScalarExpr::Compare {
+                left,
+                op,
+                right,
+                semantics,
+            } => WireScalarExpr::Compare {
+                left: boxed(left, id_of),
+                op: op.clone(),
+                right: boxed(right, id_of),
+                semantics: *semantics,
+            },
+            ScalarExpr::BoolAnd(parts) => WireScalarExpr::BoolAnd(list(parts, id_of)),
+            ScalarExpr::BoolOr(parts) => WireScalarExpr::BoolOr(list(parts, id_of)),
+            ScalarExpr::Not(e) => WireScalarExpr::Not(boxed(e, id_of)),
+            ScalarExpr::IsNull(e) => WireScalarExpr::IsNull(boxed(e, id_of)),
+            ScalarExpr::IsNotNull(e) => WireScalarExpr::IsNotNull(boxed(e, id_of)),
+            ScalarExpr::Cast { expr, to, try_cast } => WireScalarExpr::Cast {
+                expr: boxed(expr, id_of),
+                to: to.clone(),
+                try_cast: *try_cast,
+            },
+            ScalarExpr::InList {
+                expr,
+                list: items,
+                negated,
+            } => WireScalarExpr::InList {
+                expr: boxed(expr, id_of),
+                list: list(items, id_of),
+                negated: *negated,
+            },
+            ScalarExpr::FunctionCall { name, args } => WireScalarExpr::FunctionCall {
+                name: name.clone(),
+                args: list(args, id_of),
+            },
+            ScalarExpr::Arithmetic {
+                op,
+                left,
+                right,
+                semantics,
+            } => WireScalarExpr::Arithmetic {
+                op: op.clone(),
+                left: boxed(left, id_of),
+                right: boxed(right, id_of),
+                semantics: *semantics,
+            },
+            ScalarExpr::Case {
+                operand,
+                branches,
+                else_expr,
+            } => WireScalarExpr::Case {
+                operand: operand.as_ref().map(|e| boxed(e, id_of)),
+                branches: branches
+                    .iter()
+                    .map(|(w, t)| (Self::from_expr(w, id_of), Self::from_expr(t, id_of)))
+                    .collect(),
+                else_expr: else_expr.as_ref().map(|e| boxed(e, id_of)),
+            },
+            ScalarExpr::CurrentTimestamp => WireScalarExpr::CurrentTimestamp,
+            ScalarExpr::EvalTimestamp => WireScalarExpr::EvalTimestamp,
+            ScalarExpr::PromqlScalarFromVector(node) => {
+                WireScalarExpr::PromqlScalarFromVector(id_of(node))
+            }
+            ScalarExpr::ScalarSubquery(node) => WireScalarExpr::ScalarSubquery(id_of(node)),
+            ScalarExpr::Exists { subquery, negated } => WireScalarExpr::Exists {
+                subquery: id_of(subquery),
+                negated: *negated,
+            },
+            ScalarExpr::InSubquery {
+                expr,
+                subquery,
+                negated,
+            } => WireScalarExpr::InSubquery {
+                expr: boxed(expr, id_of),
+                subquery: id_of(subquery),
+                negated: *negated,
+            },
+        }
+    }
+}
+
+impl WirePredicate {
+    fn from_pred(
+        p: &Predicate,
+        id_of: &mut impl FnMut(&Rc<OperatorNode>) -> LogicalASAPNodeId,
+    ) -> Self {
+        WirePredicate(WireScalarExpr::from_expr(&p.0, id_of))
+    }
+}
+
+impl WireSortKey {
+    fn from_keys(
+        keys: &[SortKey],
+        id_of: &mut impl FnMut(&Rc<OperatorNode>) -> LogicalASAPNodeId,
+    ) -> Vec<Self> {
+        keys.iter()
+            .map(|k| WireSortKey {
+                expr: WireScalarExpr::from_expr(&k.expr, id_of),
+                ascending: k.ascending,
+                nulls_first: k.nulls_first,
+            })
+            .collect()
+    }
+}
+
+// ── Wire mirror of the non-ASAP operator vocabulary ──────────────────────
+
+/// [`NonASAPOp`] without its child fields (children are edges) and with
+/// every scalar expression mirrored as [`WireScalarExpr`]. Fields named
+/// `kind` in the IR are renamed so they do not collide with the variant tag.
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+#[serde(tag = "kind", rename_all = "snake_case")]
+pub enum NonASAPOpKind {
+    Scan {
+        source: Source,
+        #[serde(default)]
+        predicates: Vec<WirePredicate>,
+        schema: Schema,
+    },
+    Values {
+        rows: Vec<Vec<WireScalarExpr>>,
+        schema: Schema,
+    },
+    Filter {
+        pred: WirePredicate,
+    },
+    Project {
+        cols: Vec<WireProjectItem>,
+        #[serde(default)]
+        qualifier: Option<String>,
+    },
+    Aggregate {
+        reduction: Reduction,
+        measures: Vec<AggIntent>,
+        #[serde(default)]
+        output_names: Vec<String>,
+        #[serde(default)]
+        filters: Vec<Option<WirePredicate>>,
+        #[serde(default)]
+        having: Option<WirePredicate>,
+    },
+    Join {
+        join_kind: JoinKind,
+        pred: WirePredicate,
+    },
+    SetOp {
+        set_kind: RelationalSetOpKind,
+        all: bool,
+    },
+    Concat {
+        #[serde(default)]
+        discriminator_unique_key: Option<ConcatDiscriminatorKey>,
+    },
+    Dedup {
+        cols: Vec<ColumnId>,
+    },
+    Sort {
+        keys: Vec<WireSortKey>,
+        #[serde(default)]
+        partition_by: GroupKeys,
+    },
+    Limit {
+        n: Option<usize>,
+        offset: usize,
+        #[serde(default)]
+        partition_by: GroupKeys,
+    },
+    BinaryOp {
+        operator: BinaryOperator,
+        #[serde(default)]
+        return_bool: bool,
+    },
+    #[serde(rename = "sql_window_func")]
+    SQLWindowFunc {
+        func: WindowFuncKind,
+        args: Vec<WireScalarExpr>,
+        partition_by: GroupKeys,
+        order_by: Vec<WireSortKey>,
+        #[serde(default)]
+        frame: Option<WindowFrame>,
+        output_name: String,
+    },
+    TimeRange {
+        range: Duration,
+        range_kind: TimeRangeKind,
+    },
+    TimeShift {
+        shift: TimeShift,
+    },
+    PromqlVectorFromScalar {
+        expr: WireScalarExpr,
+    },
+    PromqlRelabel {
+        dst: String,
+        value: WireScalarExpr,
+    },
+    PromqlInfoEnrich {
+        #[serde(default)]
+        selector: Vec<InfoMatcher>,
+    },
+    PromqlSeriesSample {
+        #[serde(default)]
+        by: GroupKeys,
+        sample_kind: SampleKind,
+    },
+    PromqlSubquery {
+        range: Duration,
+        #[serde(default)]
+        resolution: Option<Duration>,
+    },
+}
+
+impl NonASAPOpKind {
+    /// Mirror `op`, resolving every operator node its scalar expressions
+    /// reference through `id_of`.
+    pub fn from_op(
+        op: &NonASAPOp,
+        id_of: &mut impl FnMut(&Rc<OperatorNode>) -> LogicalASAPNodeId,
+    ) -> Self {
+        use NonASAPOp as Op;
+        match op {
+            Op::Scan {
+                source,
+                predicates,
+                schema,
+            } => NonASAPOpKind::Scan {
+                source: source.clone(),
+                predicates: predicates
+                    .iter()
+                    .map(|p| WirePredicate::from_pred(p, id_of))
+                    .collect(),
+                schema: schema.clone(),
+            },
+            Op::Values { rows, schema } => NonASAPOpKind::Values {
+                rows: rows
+                    .iter()
+                    .map(|row| {
+                        row.iter()
+                            .map(|e| WireScalarExpr::from_expr(e, id_of))
+                            .collect()
+                    })
+                    .collect(),
+                schema: schema.clone(),
+            },
+            Op::Filter { pred, .. } => NonASAPOpKind::Filter {
+                pred: WirePredicate::from_pred(pred, id_of),
+            },
+            Op::Project {
+                cols, qualifier, ..
+            } => NonASAPOpKind::Project {
+                cols: cols
+                    .iter()
+                    .map(|ProjectItem { alias, expr }| WireProjectItem {
+                        alias: alias.clone(),
+                        expr: WireScalarExpr::from_expr(expr, id_of),
+                    })
+                    .collect(),
+                qualifier: qualifier.clone(),
+            },
+            Op::Aggregate {
+                reduction,
+                measures,
+                output_names,
+                filters,
+                having,
+                ..
+            } => NonASAPOpKind::Aggregate {
+                reduction: reduction.clone(),
+                measures: measures.clone(),
+                output_names: output_names.clone(),
+                filters: filters
+                    .iter()
+                    .map(|p| p.as_ref().map(|p| WirePredicate::from_pred(p, id_of)))
+                    .collect(),
+                having: having.as_ref().map(|p| WirePredicate::from_pred(p, id_of)),
+            },
+            Op::Join { kind, pred, .. } => NonASAPOpKind::Join {
+                join_kind: kind.clone(),
+                pred: WirePredicate::from_pred(pred, id_of),
+            },
+            Op::SetOp { kind, all, .. } => NonASAPOpKind::SetOp {
+                set_kind: kind.clone(),
+                all: *all,
+            },
+            Op::Concat {
+                discriminator_unique_key,
+                ..
+            } => NonASAPOpKind::Concat {
+                discriminator_unique_key: discriminator_unique_key.clone(),
+            },
+            Op::Dedup { cols, .. } => NonASAPOpKind::Dedup { cols: cols.clone() },
+            Op::Sort {
+                keys, partition_by, ..
+            } => NonASAPOpKind::Sort {
+                keys: WireSortKey::from_keys(keys, id_of),
+                partition_by: partition_by.clone(),
+            },
+            Op::Limit {
+                n,
+                offset,
+                partition_by,
+                ..
+            } => NonASAPOpKind::Limit {
+                n: *n,
+                offset: *offset,
+                partition_by: partition_by.clone(),
+            },
+            Op::BinaryOp {
+                operator,
+                return_bool,
+                ..
+            } => NonASAPOpKind::BinaryOp {
+                operator: operator.clone(),
+                return_bool: *return_bool,
+            },
+            Op::SQLWindowFunc {
+                func,
+                args,
+                partition_by,
+                order_by,
+                frame,
+                output_name,
+                ..
+            } => NonASAPOpKind::SQLWindowFunc {
+                func: func.clone(),
+                args: args
+                    .iter()
+                    .map(|e| WireScalarExpr::from_expr(e, id_of))
+                    .collect(),
+                partition_by: partition_by.clone(),
+                order_by: WireSortKey::from_keys(order_by, id_of),
+                frame: frame.clone(),
+                output_name: output_name.clone(),
+            },
+            Op::TimeRange { range, kind, .. } => NonASAPOpKind::TimeRange {
+                range: *range,
+                range_kind: *kind,
+            },
+            Op::TimeShift { shift, .. } => NonASAPOpKind::TimeShift { shift: *shift },
+            Op::PromqlVectorFromScalar(e) => NonASAPOpKind::PromqlVectorFromScalar {
+                expr: WireScalarExpr::from_expr(e, id_of),
+            },
+            Op::PromqlRelabel { dst, value, .. } => NonASAPOpKind::PromqlRelabel {
+                dst: dst.clone(),
+                value: WireScalarExpr::from_expr(value, id_of),
+            },
+            Op::PromqlInfoEnrich { selector, .. } => NonASAPOpKind::PromqlInfoEnrich {
+                selector: selector.clone(),
+            },
+            Op::PromqlSeriesSample { by, kind, .. } => NonASAPOpKind::PromqlSeriesSample {
+                by: by.clone(),
+                sample_kind: *kind,
+            },
+            Op::PromqlSubquery {
+                range, resolution, ..
+            } => NonASAPOpKind::PromqlSubquery {
+                range: *range,
+                resolution: *resolution,
+            },
+        }
+    }
+}
+
+// ── The exported DAG ─────────────────────────────────────────────────────
+
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+#[serde(tag = "kind", rename_all = "snake_case", deny_unknown_fields)]
+pub enum LogicalASAPOperatorPayload {
+    Relational {
+        operator: NonASAPOpKind,
+    },
+    SummaryAgg {
+        family: FieldDataType,
+        input: SummaryUpdate,
+        reduction: Reduction,
+        grouping: GroupingStrategy,
+        #[serde(default)]
+        filter: Option<WirePredicate>,
+    },
+    SummaryEstimate {
+        query: SketchStatistic,
+    },
+    FinalizeExactAccumulator,
+    MaintainPopulation {
+        population: MaintainedPopulation<OperatorNode>,
+    },
+    EvaluatePopulation {
+        evaluation: PopulationStatistic,
+    },
+    SummaryMerge,
+    SummarySubtract,
+    SummaryDelete {
+        key: ColumnId,
+    },
+    SummaryJoin {
+        key: ColumnId,
+        family: FieldDataType,
+    },
+    Extension {
+        name: String,
+    },
+}
+
+/// The operator's own inputs with their edge roles, in field order.
+pub(super) fn input_edges(operator: &Operator) -> Vec<(&Rc<OperatorNode>, EdgeRole)> {
+    match operator {
+        Operator::NonASAP(op) => match op {
+            NonASAPOp::Join { left, right, .. }
+            | NonASAPOp::SetOp { left, right, .. }
+            | NonASAPOp::BinaryOp {
+                lhs: left,
+                rhs: right,
+                ..
+            } => vec![(left, EdgeRole::Left), (right, EdgeRole::Right)],
+            NonASAPOp::Concat { children, .. } => {
+                children.iter().map(|c| (c, EdgeRole::Input)).collect()
+            }
+            NonASAPOp::Filter { child, .. }
+            | NonASAPOp::Project { child, .. }
+            | NonASAPOp::Aggregate { child, .. }
+            | NonASAPOp::Dedup { child, .. }
+            | NonASAPOp::Sort { child, .. }
+            | NonASAPOp::Limit { child, .. }
+            | NonASAPOp::SQLWindowFunc { child, .. }
+            | NonASAPOp::TimeRange { child, .. }
+            | NonASAPOp::TimeShift { child, .. }
+            | NonASAPOp::PromqlRelabel { child, .. }
+            | NonASAPOp::PromqlInfoEnrich { child, .. }
+            | NonASAPOp::PromqlSeriesSample { child, .. }
+            | NonASAPOp::PromqlSubquery { child, .. } => vec![(child, EdgeRole::Input)],
+            NonASAPOp::Scan { .. }
+            | NonASAPOp::Values { .. }
+            | NonASAPOp::PromqlVectorFromScalar(_) => vec![],
+        },
+        Operator::ASAP(op) => match op {
+            ASAPOp::SummarySubtract { left, right }
+            | ASAPOp::SummaryJoin {
+                outer: left,
+                inner: right,
+                ..
+            } => vec![(left, EdgeRole::Left), (right, EdgeRole::Right)],
+            ASAPOp::SummaryMerge { children } => {
+                children.iter().map(|c| (c, EdgeRole::Input)).collect()
+            }
+            ASAPOp::SummaryAgg { child, .. }
+            | ASAPOp::FinalizeExactAccumulator { child }
+            | ASAPOp::MaintainPopulation { child, .. }
+            | ASAPOp::EvaluatePopulation { child, .. }
+            | ASAPOp::Extension { child, .. } => vec![(child, EdgeRole::Input)],
+            ASAPOp::SummaryEstimate { summary_input, .. }
+            | ASAPOp::SummaryDelete { summary_input, .. } => {
+                vec![(summary_input, EdgeRole::Input)]
+            }
+        },
+    }
+}
+
+pub(super) fn payload_of(
+    operator: &Operator,
+    id_of: &mut impl FnMut(&Rc<OperatorNode>) -> LogicalASAPNodeId,
+) -> LogicalASAPOperatorPayload {
+    match operator {
+        Operator::NonASAP(op) => LogicalASAPOperatorPayload::Relational {
+            operator: NonASAPOpKind::from_op(op, id_of),
+        },
+        Operator::ASAP(op) => match op {
+            ASAPOp::SummaryAgg {
+                family,
+                input,
+                reduction,
+                grouping,
+                filter,
+                ..
+            } => LogicalASAPOperatorPayload::SummaryAgg {
+                family: family.clone(),
+                input: input.clone(),
+                reduction: reduction.clone(),
+                grouping: grouping.clone(),
+                filter: filter.as_ref().map(|p| WirePredicate::from_pred(p, id_of)),
+            },
+            ASAPOp::SummaryEstimate { query, .. } => LogicalASAPOperatorPayload::SummaryEstimate {
+                query: query.clone(),
+            },
+            ASAPOp::FinalizeExactAccumulator { .. } => {
+                LogicalASAPOperatorPayload::FinalizeExactAccumulator
+            }
+            ASAPOp::MaintainPopulation { population, .. } => {
+                LogicalASAPOperatorPayload::MaintainPopulation {
+                    population: population.clone(),
+                }
+            }
+            ASAPOp::EvaluatePopulation { evaluation, .. } => {
+                LogicalASAPOperatorPayload::EvaluatePopulation {
+                    evaluation: evaluation.clone(),
+                }
+            }
+            ASAPOp::SummaryMerge { .. } => LogicalASAPOperatorPayload::SummaryMerge,
+            ASAPOp::SummarySubtract { .. } => LogicalASAPOperatorPayload::SummarySubtract,
+            ASAPOp::SummaryDelete { key, .. } => {
+                LogicalASAPOperatorPayload::SummaryDelete { key: *key }
+            }
+            ASAPOp::SummaryJoin { key, family, .. } => LogicalASAPOperatorPayload::SummaryJoin {
+                key: *key,
+                family: family.clone(),
+            },
+            ASAPOp::Extension { name, .. } => {
+                LogicalASAPOperatorPayload::Extension { name: name.clone() }
+            }
+        },
+    }
+}
+
+/// Grouping compatibility between two `SummaryAgg`s by their reductions.
+pub(super) fn grouping_compatibility(
+    producer: &Operator,
+    consumer: &Operator,
+) -> GroupingEdgeCompatibility {
+    let (
+        Operator::ASAP(ASAPOp::SummaryAgg {
+            reduction: producer,
+            ..
+        }),
+        Operator::ASAP(ASAPOp::SummaryAgg {
+            reduction: consumer,
+            ..
+        }),
+    ) = (producer, consumer)
+    else {
+        return GroupingEdgeCompatibility::NotApplicable;
+    };
+    match (producer, consumer) {
+        (p, c) if p == c => GroupingEdgeCompatibility::Identical,
+        (Reduction::PerEntity, Reduction::Reduce(_)) => {
+            GroupingEdgeCompatibility::ConsumerCoarsensProducer
+        }
+        (Reduction::Reduce(p), Reduction::Reduce(c))
+            if !p.is_without() && !c.is_without() && c.iter().all(|key| p.contains(key)) =>
+        {
+            GroupingEdgeCompatibility::ConsumerCoarsensProducer
+        }
+        _ => GroupingEdgeCompatibility::Incompatible,
+    }
+}
diff --git a/crates/types/tests/logical_export.rs b/crates/types/tests/logical_export.rs
new file mode 100644
index 000000000..fd8d35651
--- /dev/null
+++ b/crates/types/tests/logical_export.rs
@@ -0,0 +1,189 @@
+//! Logical transport must accept phase-free plans before materialization.
+use asap_types::{
+    ir::{NonASAPOp, Operator, OperatorNode},
+    pre_asap::Schema,
+};
+
+#[test]
+fn logical_export_accepts_unassigned_timing() {
+    let root = OperatorNode::new_shared(Operator::NonASAP(NonASAPOp::Values {
+        rows: vec![vec![]],
+        schema: Schema::lifted(vec![], None),
+    }))
+    .unwrap();
+    assert!(root.timing.is_none());
+    assert!(asap_types::ir::export::compile_logical_asap_dag(&root).is_ok());
+}
+
+use asap_types::{
+    ir::export::{
+        compile_logical_asap_dag_with_node_ids, EdgeRole, LogicalASAPDAGDocument,
+        LogicalASAPDAGValidationError, LogicalASAPNodeId, LogicalASAPOperatorPayload,
+    },
+    ir::operator_properties::Reduction,
+    ir::{ASAPOp, OperatorResultKind, ProjectItem, ScalarExpr},
+    post_asap::{GroupingStrategy, SketchAlgorithm, SketchKind, SketchParams, SummaryUpdate},
+    pre_asap::{ColumnRef, DataType, Field, FieldDataType, ScalarValue},
+};
+use std::rc::Rc;
+
+fn values() -> Rc<OperatorNode> {
+    OperatorNode::new_shared(Operator::NonASAP(NonASAPOp::Values {
+        rows: vec![vec![ScalarExpr::Literal(ScalarValue::Float64(1.0))]],
+        schema: Schema::lifted(vec![Field::plain("value", DataType::Float64, false)], None),
+    }))
+    .unwrap()
+}
+
+/// Scalar subqueries contribute real edges; repeated references export one producer.
+#[test]
+fn scalar_dependencies_share_one_exported_producer() {
+    let child = values();
+    let root = OperatorNode::new_shared(Operator::NonASAP(NonASAPOp::Project {
+        cols: vec![ProjectItem {
+            alias: Some("result".into()),
+            expr: ScalarExpr::ScalarSubquery(child.clone()),
+        }],
+        qualifier: None,
+        child: child.clone(),
+    }))
+    .unwrap();
+    let compiled = compile_logical_asap_dag_with_node_ids(&root).unwrap();
+    compiled.dag.validate().unwrap();
+    assert_eq!(compiled.dag.nodes.len(), 2);
+    assert_eq!(compiled.dag.edges.len(), 2);
+    assert!(compiled
+        .dag
+        .edges
+        .iter()
+        .any(|edge| edge.role == EdgeRole::ScalarRef));
+    let id = compiled.node_ids.node_id(&child).unwrap();
+    assert!(Rc::ptr_eq(
+        compiled.node_ids.operator_node(id).unwrap(),
+        &child
+    ));
+    let document = LogicalASAPDAGDocument::new(compiled.dag);
+    let json = serde_json::to_string(&document).unwrap();
+    for physical_metadata in [
+        "output_state",
+        "data_state",
+        "timing",
+        "retention",
+        "window",
+    ] {
+        assert!(
+            !json.contains(physical_metadata),
+            "logical JSON contains {physical_metadata}"
+        );
+    }
+    let decoded: LogicalASAPDAGDocument = serde_json::from_str(&json).unwrap();
+    assert_eq!(document, decoded);
+    decoded.validate().unwrap();
+}
+
+/// Summary state identity survives logical merge export without a phase assignment.
+#[test]
+fn merged_summary_preserves_typed_state() {
+    let state = OperatorNode::new_shared(Operator::ASAP(ASAPOp::SummaryAgg {
+        child: values(),
+        family: FieldDataType::Sketch(
+            SketchKind::new(SketchAlgorithm::Kll, SketchParams::Kll { k: 200 }),
+            GroupingStrategy::default(),
+        ),
+        input: SummaryUpdate::column(ColumnRef::Named("value".into())),
+        reduction: Reduction::by(vec![]),
+        grouping: GroupingStrategy::default(),
+        filter: None,
+    }))
+    .unwrap();
+    let root = OperatorNode::new_shared(Operator::ASAP(ASAPOp::SummaryMerge {
+        children: (0..2)
+            .map(|start| {
+                let coverage = asap_types::ir::summary_coverage::SummaryCoverage {
+                    source: "values:timestamp".into(),
+                    input: SummaryUpdate::column(ColumnRef::Named("value".into())),
+                    reduction: Reduction::by(vec![]),
+                    regions: vec![asap_types::ir::summary_coverage::CoverageRegion {
+                        start_ms: start,
+                        end_ms: start + 1,
+                        population: Default::default(),
+                    }],
+                };
+                std::rc::Rc::new((*state).clone().with_coverage(coverage).unwrap())
+            })
+            .collect(),
+    }))
+    .unwrap();
+    let dag = asap_types::ir::export::compile_logical_asap_dag(&root).unwrap();
+    dag.validate().unwrap();
+    assert_eq!(dag.nodes.len(), 4);
+    let root_id = dag.root.operator_refs()[0];
+    let merged = &dag.nodes[root_id.0 as usize];
+    assert_eq!(merged.result_kind, OperatorResultKind::State);
+    assert_eq!(merged.output_schema, root.schema);
+    assert_eq!(merged.coverage, root.coverage);
+    assert!(matches!(
+        merged.payload,
+        LogicalASAPOperatorPayload::SummaryMerge
+    ));
+}
+
+/// Malformed wire graphs fail transport integrity checks rather than reaching execution.
+#[test]
+fn malformed_transport_is_rejected() {
+    let dag = asap_types::ir::export::compile_logical_asap_dag(&values()).unwrap();
+    let mut document = LogicalASAPDAGDocument::new(dag.clone());
+    document.schema_version = 99;
+    assert!(matches!(
+        document.validate(),
+        Err(LogicalASAPDAGValidationError::UnsupportedVersion(99))
+    ));
+    let mut duplicate = dag.clone();
+    duplicate.nodes.push(dag.nodes[0].clone());
+    assert!(matches!(
+        duplicate.validate(),
+        Err(LogicalASAPDAGValidationError::DuplicateNode(_))
+    ));
+    let mut missing = dag.clone();
+    missing.root = asap_types::ir::export::LogicalASAPQueryRoot::Operator(LogicalASAPNodeId(9));
+    assert!(matches!(
+        missing.validate(),
+        Err(LogicalASAPDAGValidationError::MissingNode(_))
+    ));
+    let mut unreachable = dag.clone();
+    let mut extra = dag.nodes[0].clone();
+    extra.id = LogicalASAPNodeId(1);
+    unreachable.nodes.push(extra);
+    assert!(matches!(
+        unreachable.validate(),
+        Err(LogicalASAPDAGValidationError::UnreachableNode(_))
+    ));
+    let mut json = serde_json::to_value(LogicalASAPDAGDocument::new(dag)).unwrap();
+    json["dag"]["nodes"][0]["output_state"] = serde_json::json!({"timing":"ingestion_time"});
+    assert!(serde_json::from_value::<LogicalASAPDAGDocument>(json).is_err());
+}
+
+/// Standalone constants need no fake relation, while scalar subqueries retain their producer DAG.
+#[test]
+fn standalone_scalar_roots_roundtrip_without_synthetic_operators() {
+    use asap_types::ir::{export::compile_logical_asap_query, QueryRoot};
+    for root in [
+        QueryRoot::Scalar(ScalarExpr::literal_f64(42.0)),
+        QueryRoot::Scalar(ScalarExpr::ScalarSubquery(values())),
+    ] {
+        let expected = root.as_operator().is_some();
+        assert!(!expected);
+        let dag = compile_logical_asap_query(&root).unwrap();
+        dag.validate().unwrap();
+        let expected_nodes = match root {
+            QueryRoot::Scalar(ScalarExpr::ScalarSubquery(_)) => 1,
+            _ => 0,
+        };
+        assert_eq!(dag.nodes.len(), expected_nodes);
+        let document = LogicalASAPDAGDocument::new(dag);
+        let decoded: LogicalASAPDAGDocument =
+            serde_json::from_str(&serde_json::to_string(&document).unwrap()).unwrap();
+        decoded.validate().unwrap();
+        assert_eq!(document, decoded);
+    }
+}
diff --git a/docs/develop_docs/logical-asap-dag.md b/docs/develop_docs/logical-asap-dag.md
new file mode 100644
index 000000000..99696b175
--- /dev/null
+++ b/docs/develop_docs/logical-asap-dag.md
@@ -0,0 +1,50 @@
+# Logical ASAP DAG transport
+
+This interface exports the unified operator/scalar IR at the logical stage of
+[planner layering](../design_docs/proposals/planner-layering.md). It describes
+what to compute, including committed summary families, before physical planning
+chooses implementations and materialization.
+
+## Interface
+
+`asap_types::ir::export` exposes:
+
+- `compile_logical_asap_dag(&Rc<OperatorNode>)` for a flat `LogicalASAPDAG`.
+- `compile_logical_asap_query(&QueryRoot)` for operator or standalone scalar roots.
+- `compile_logical_asap_dag_with_node_ids(...)` for that DAG and a compiler-local
+  `LogicalASAPNodeIdentityMap` with `node_id` and `operator_node` lookups.
+- `LogicalASAPDAGDocument::new(dag)` and `validate()` for the versioned transport
+  envelope. Logical wire version 1 is distinct from the older phase-assigned
+  post-ASAP format.
+
+The compiler first checks the in-memory DAG's structural contracts. Untimed
+ordinary plans and summary plans are valid inputs. Export does not assess
+accuracy against request requirements or select a physical plan.
+
+Each `LogicalASAPDAGNode` contains an ID, operator payload, result kind, output
+schema and optional accuracy guarantee. Each `LogicalASAPDAGEdge` contains
+producer/consumer IDs, input role, intermediate schema and grouping compatibility.
+The DAG has one semantic operator or scalar root. A standalone scalar constant
+needs no synthetic operator node. IDs are local to one export.
+
+Scalar expressions remain owned by their operators. Their wire representations
+replace explicit operator references with IDs. `ScalarRef` edges record those
+producer dependencies. A shared operator is exported once even when ordinary
+inputs and scalar expressions both reference it.
+
+## Physical boundary
+
+Logical nodes and edges contain no execution state, assigned timing, storage tier,
+retention or pane-alignment assertion. Physical planning chooses, for each eligible
+sub-DAG, no materialization, query-time materialization, or ingestion-time
+materialization. Execution timing follows that choice and its dependencies.
+
+The optional `OperatorNode.timing` field belongs to the common IR and may later
+record a physical assignment; it is not part of logical transport. There is no
+intermediate timed-DAG stage. Physical planning owns phase validation and any
+splitting needed when shared consumers require incompatible execution contexts.
+
+Transport validation checks graph identity, connectivity, acyclicity, edge schemas
+and declared summary family/grouping metadata. Full scalar/operator typing remains
+an in-memory structural validation responsibility. Neither check proves runtime
+capability, cost, response latency or accuracy feasibility.

From bf148a10997c728f6d0d7b8e255cba6a21c66e76 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 17:21:20 +0000
Subject: [PATCH 24/48] feat(ir): require summary coverage in logical transport

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/types/src/ir/export.rs        |  3 +++
 crates/types/tests/logical_export.rs | 16 ++++++++++++++--
 2 files changed, 17 insertions(+), 2 deletions(-)

diff --git a/crates/types/src/ir/export.rs b/crates/types/src/ir/export.rs
index 4325096a6..55de7228e 100644
--- a/crates/types/src/ir/export.rs
+++ b/crates/types/src/ir/export.rs
@@ -130,6 +130,9 @@ impl LogicalASAPDAG {
                 family, grouping, ..
             } = &node.payload
             {
+                if node.coverage.is_none() {
+                    return Err(LogicalASAPDAGValidationError::InvalidCoverage(node.id));
+                }
                 if !node.output_schema.fields.iter().any(|field| &field.dtype == family)
                     || node.output_schema.fields.iter().any(|field| matches!(&field.dtype, FieldDataType::Sketch(_, actual) if actual != grouping)) {
                     return Err(LogicalASAPDAGValidationError::SummarySchemaMismatch(node.id));
diff --git a/crates/types/tests/logical_export.rs b/crates/types/tests/logical_export.rs
index fd8d35651..f6c7e25c7 100644
--- a/crates/types/tests/logical_export.rs
+++ b/crates/types/tests/logical_export.rs
@@ -104,8 +104,7 @@ fn merged_summary_preserves_typed_state() {
                     input: SummaryUpdate::column(ColumnRef::Named("value".into())),
                     reduction: Reduction::by(vec![]),
                     regions: vec![asap_types::ir::summary_coverage::CoverageRegion {
-                        start_ms: start,
-                        end_ms: start + 1,
+                        time_ms: Some(start..start + 1),
                         population: Default::default(),
                     }],
                 };
@@ -126,6 +125,19 @@ fn merged_summary_preserves_typed_state() {
         merged.payload,
         LogicalASAPOperatorPayload::SummaryMerge
     ));
+    // Transport rejects a summary producer whose required coverage was dropped.
+    let mut stripped = dag.clone();
+    let producer = stripped
+        .nodes
+        .iter_mut()
+        .find(|node| matches!(node.payload, LogicalASAPOperatorPayload::SummaryAgg { .. }))
+        .unwrap();
+    producer.coverage = None;
+    let id = producer.id;
+    assert!(matches!(
+        stripped.validate(),
+        Err(LogicalASAPDAGValidationError::InvalidCoverage(bad)) if bad == id
+    ));
 }
 
 /// Malformed wire graphs fail transport integrity checks rather than reaching execution.

From 4a48b04297d175d8e25d783da796928a515572c4 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 17:35:09 +0000
Subject: [PATCH 25/48] test(ir): use typed coverage source in logical export

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/types/tests/logical_export.rs | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/crates/types/tests/logical_export.rs b/crates/types/tests/logical_export.rs
index f6c7e25c7..317905d11 100644
--- a/crates/types/tests/logical_export.rs
+++ b/crates/types/tests/logical_export.rs
@@ -23,7 +23,7 @@ use asap_types::{
     ir::operator_properties::Reduction,
     ir::{ASAPOp, OperatorResultKind, ProjectItem, ScalarExpr},
     post_asap::{GroupingStrategy, SketchAlgorithm, SketchKind, SketchParams, SummaryUpdate},
-    pre_asap::{ColumnRef, DataType, Field, FieldDataType, ScalarValue},
+    pre_asap::{ColumnRef, DataType, Field, FieldDataType, ScalarValue, Source},
 };
 use std::rc::Rc;
 
@@ -100,9 +100,9 @@ fn merged_summary_preserves_typed_state() {
         children: (0..2)
             .map(|start| {
                 let coverage = asap_types::ir::summary_coverage::SummaryCoverage {
-                    source: "values:timestamp".into(),
-                    input: SummaryUpdate::column(ColumnRef::Named("value".into())),
-                    reduction: Reduction::by(vec![]),
+                    source: Source::Table {
+                        table_ref: "values".into(),
+                    },
                     regions: vec![asap_types::ir::summary_coverage::CoverageRegion {
                         time_ms: Some(start..start + 1),
                         population: Default::default(),

From 3e9b01e655ad16dcac7733757c96113fe21c7dd7 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 19:46:33 +0000
Subject: [PATCH 26/48] docs(ir): describe logical export as having no
 execution timing assigned

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/types/src/ir/export.rs        | 2 +-
 crates/types/tests/logical_export.rs | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/crates/types/src/ir/export.rs b/crates/types/src/ir/export.rs
index 55de7228e..ea4b20566 100644
--- a/crates/types/src/ir/export.rs
+++ b/crates/types/src/ir/export.rs
@@ -1,4 +1,4 @@
-//! Phase-free logical ASAP DAG transport (planner-layering stage 1).
+//! Logical ASAP DAG transport (planner-layering stage 1), with no execution timing assigned.
 //!
 //! This representation preserves operator semantics and summary state types.
 //! Timing is derived from materialization during physical planning;
diff --git a/crates/types/tests/logical_export.rs b/crates/types/tests/logical_export.rs
index 317905d11..ab670e829 100644
--- a/crates/types/tests/logical_export.rs
+++ b/crates/types/tests/logical_export.rs
@@ -1,4 +1,4 @@
-//! Logical transport must accept phase-free plans before materialization.
+//! Logical transport must accept plans with no execution timing assigned, before materialization.
 use asap_types::{
     ir::{NonASAPOp, Operator, OperatorNode},
     pre_asap::Schema,

From fa9c4144a2bbae57475f4cdf8a35cc3db0ba69c5 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 20:08:47 +0000
Subject: [PATCH 27/48] feat(ir): export a query batch as one DAG with one root
 per query

A workload DAG has one root per batch query; queries that share a sub-DAG
reference the same exported nodes. Single-query export is a batch of one.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/types/src/ir/export.rs        | 55 +++++++++++++++++++++-------
 crates/types/tests/logical_export.rs | 42 ++++++++++++++++++++-
 2 files changed, 81 insertions(+), 16 deletions(-)

diff --git a/crates/types/src/ir/export.rs b/crates/types/src/ir/export.rs
index ea4b20566..276d8ee43 100644
--- a/crates/types/src/ir/export.rs
+++ b/crates/types/src/ir/export.rs
@@ -64,7 +64,9 @@ impl LogicalASAPQueryRoot {
 pub struct LogicalASAPDAG {
     pub nodes: Vec<LogicalASAPDAGNode>,
     pub edges: Vec<LogicalASAPDAGEdge>,
-    pub root: LogicalASAPQueryRoot,
+    /// One root per query of the batch, in workload order. Queries that share
+    /// a sub-DAG reference the same exported nodes.
+    pub roots: Vec<LogicalASAPQueryRoot>,
 }
 
 #[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
@@ -88,6 +90,8 @@ pub enum LogicalASAPDAGValidationError {
     SummarySchemaMismatch(LogicalASAPNodeId),
     #[error("invalid summary coverage at {0:?}")]
     InvalidCoverage(LogicalASAPNodeId),
+    #[error("logical ASAP DAG has no query roots")]
+    NoRoots,
     #[error("logical ASAP DAG contains a cycle")]
     Cycle,
     #[error("unreachable logical node {0:?}")]
@@ -139,7 +143,14 @@ impl LogicalASAPDAG {
                 }
             }
         }
-        let roots = self.root.operator_refs();
+        if self.roots.is_empty() {
+            return Err(LogicalASAPDAGValidationError::NoRoots);
+        }
+        let roots: Vec<_> = self
+            .roots
+            .iter()
+            .flat_map(LogicalASAPQueryRoot::operator_refs)
+            .collect();
         for root in &roots {
             if !nodes.contains_key(root) {
                 return Err(LogicalASAPDAGValidationError::MissingNode(*root));
@@ -255,23 +266,39 @@ pub fn compile_logical_asap_query(
 pub fn compile_logical_asap_query_with_node_ids(
     root: &QueryRoot,
 ) -> Result<LogicalASAPDAGCompilation, SchemaDerivationError> {
-    root.validate_structure()?;
+    compile_logical_asap_workload_with_node_ids(std::slice::from_ref(root))
+}
+
+/// Export a batch of queries as one DAG with one root per query.
+pub fn compile_logical_asap_workload(
+    roots: &[QueryRoot],
+) -> Result<LogicalASAPDAG, SchemaDerivationError> {
+    Ok(compile_logical_asap_workload_with_node_ids(roots)?.dag)
+}
+
+pub fn compile_logical_asap_workload_with_node_ids(
+    roots: &[QueryRoot],
+) -> Result<LogicalASAPDAGCompilation, SchemaDerivationError> {
     let mut exporter = Exporter::default();
-    let root = match root {
-        QueryRoot::Operator(node) => LogicalASAPQueryRoot::Operator(exporter.visit(node)),
-        QueryRoot::Scalar(expr) => {
-            for node in expr.operator_refs() {
-                exporter.visit(node);
+    let mut exported = Vec::with_capacity(roots.len());
+    for root in roots {
+        root.validate_structure()?;
+        exported.push(match root {
+            QueryRoot::Operator(node) => LogicalASAPQueryRoot::Operator(exporter.visit(node)),
+            QueryRoot::Scalar(expr) => {
+                for node in expr.operator_refs() {
+                    exporter.visit(node);
+                }
+                LogicalASAPQueryRoot::Scalar(WireScalarExpr::from_expr(expr, &mut |n| {
+                    exporter.ids[&Rc::as_ptr(n)]
+                }))
             }
-            LogicalASAPQueryRoot::Scalar(WireScalarExpr::from_expr(expr, &mut |n| {
-                exporter.ids[&Rc::as_ptr(n)]
-            }))
-        }
-    };
+        });
+    }
     let dag = LogicalASAPDAG {
         nodes: exporter.nodes,
         edges: exporter.edges,
-        root,
+        roots: exported,
     };
     Ok(LogicalASAPDAGCompilation {
         dag,
diff --git a/crates/types/tests/logical_export.rs b/crates/types/tests/logical_export.rs
index ab670e829..95c812cec 100644
--- a/crates/types/tests/logical_export.rs
+++ b/crates/types/tests/logical_export.rs
@@ -116,7 +116,7 @@ fn merged_summary_preserves_typed_state() {
     let dag = asap_types::ir::export::compile_logical_asap_dag(&root).unwrap();
     dag.validate().unwrap();
     assert_eq!(dag.nodes.len(), 4);
-    let root_id = dag.root.operator_refs()[0];
+    let root_id = dag.roots[0].operator_refs()[0];
     let merged = &dag.nodes[root_id.0 as usize];
     assert_eq!(merged.result_kind, OperatorResultKind::State);
     assert_eq!(merged.output_schema, root.schema);
@@ -157,7 +157,9 @@ fn malformed_transport_is_rejected() {
         Err(LogicalASAPDAGValidationError::DuplicateNode(_))
     ));
     let mut missing = dag.clone();
-    missing.root = asap_types::ir::export::LogicalASAPQueryRoot::Operator(LogicalASAPNodeId(9));
+    missing.roots = vec![asap_types::ir::export::LogicalASAPQueryRoot::Operator(
+        LogicalASAPNodeId(9),
+    )];
     assert!(matches!(
         missing.validate(),
         Err(LogicalASAPDAGValidationError::MissingNode(_))
@@ -199,3 +201,39 @@ fn standalone_scalar_roots_roundtrip_without_synthetic_operators() {
         assert_eq!(document, decoded);
     }
 }
+
+/// A batch exports as one DAG: one root per query, shared producers exported once.
+#[test]
+fn batch_exports_one_root_per_query_and_shares_producers() {
+    use asap_types::ir::{export::compile_logical_asap_workload, QueryRoot};
+    let shared = values();
+    let project = |alias: &str| {
+        OperatorNode::new_shared(Operator::NonASAP(NonASAPOp::Project {
+            child: shared.clone(),
+            cols: vec![ProjectItem {
+                alias: Some(alias.into()),
+                expr: ScalarExpr::Column(0),
+            }],
+            qualifier: None,
+        }))
+        .unwrap()
+    };
+    let dag = compile_logical_asap_workload(&[
+        QueryRoot::Operator(project("a")),
+        QueryRoot::Operator(project("b")),
+    ])
+    .unwrap();
+    dag.validate().unwrap();
+    assert_eq!(dag.roots.len(), 2);
+    assert_eq!(
+        dag.nodes.len(),
+        3,
+        "the shared Values node is exported once"
+    );
+    let mut empty = dag.clone();
+    empty.roots.clear();
+    assert!(matches!(
+        empty.validate(),
+        Err(LogicalASAPDAGValidationError::NoRoots)
+    ));
+}

From ba05ce8c6cd1003b57e000c6f41fa8c62598741c Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Fri, 2 Oct 2026 21:20:01 +0000
Subject: [PATCH 28/48] feat: lower SQL through unified operators and scalars

---
 Cargo.lock                                    |   10 +
 Cargo.toml                                    |    1 +
 crates/frontend-common/Cargo.toml             |   11 +
 crates/frontend-common/src/lib.rs             |   23 +
 crates/frontend-common/src/resolve.rs         | 1188 +++++++
 crates/frontend-common/src/schema_resolver.rs |  443 +++
 crates/frontend-common/src/unresolved.rs      |  374 +++
 crates/frontend-sql/Cargo.toml                |    1 +
 crates/frontend-sql/src/lib.rs                |    3 +
 crates/frontend-sql/src/unified/error.rs      |   63 +
 crates/frontend-sql/src/unified/mod.rs        |  103 +
 .../src/unified/sql/clickhouse_ast.rs         |  139 +
 .../src/unified/sql/collection_planning.rs    |  189 ++
 .../frontend-sql/src/unified/sql/dialect.rs   |  112 +
 crates/frontend-sql/src/unified/sql/expr.rs   |  354 ++
 crates/frontend-sql/src/unified/sql/mod.rs    | 2525 +++++++++++++++
 crates/frontend-sql/src/unified/sql/types.rs  |  378 +++
 .../tests/unified_sql_lowering.rs             | 2874 +++++++++++++++++
 crates/types/src/ir/mod.rs                    |    5 +-
 crates/types/src/ir/schema_support.rs         |   85 +
 crates/types/src/pre_asap/mod.rs              |    2 +
 21 files changed, 8881 insertions(+), 2 deletions(-)
 create mode 100644 crates/frontend-common/Cargo.toml
 create mode 100644 crates/frontend-common/src/lib.rs
 create mode 100644 crates/frontend-common/src/resolve.rs
 create mode 100644 crates/frontend-common/src/schema_resolver.rs
 create mode 100644 crates/frontend-common/src/unresolved.rs
 create mode 100644 crates/frontend-sql/src/unified/error.rs
 create mode 100644 crates/frontend-sql/src/unified/mod.rs
 create mode 100644 crates/frontend-sql/src/unified/sql/clickhouse_ast.rs
 create mode 100644 crates/frontend-sql/src/unified/sql/collection_planning.rs
 create mode 100644 crates/frontend-sql/src/unified/sql/dialect.rs
 create mode 100644 crates/frontend-sql/src/unified/sql/expr.rs
 create mode 100644 crates/frontend-sql/src/unified/sql/mod.rs
 create mode 100644 crates/frontend-sql/src/unified/sql/types.rs
 create mode 100644 crates/frontend-sql/tests/unified_sql_lowering.rs
 create mode 100644 crates/types/src/ir/schema_support.rs

diff --git a/Cargo.lock b/Cargo.lock
index 177a991e5..c1f6003dc 100644
--- a/Cargo.lock
+++ b/Cargo.lock
@@ -339,6 +339,15 @@ dependencies = [
  "tokio",
 ]
 
+[[package]]
+name = "asap-frontend-common"
+version = "0.1.0"
+dependencies = [
+ "asap-types",
+ "serde",
+ "thiserror 2.0.18",
+]
+
 [[package]]
 name = "asap-frontend-metricsql"
 version = "0.1.0"
@@ -362,6 +371,7 @@ name = "asap-frontend-sql"
 version = "0.1.0"
 dependencies = [
  "asap-aware-mapping",
+ "asap-frontend-common",
  "asap-sql-function-catalog",
  "asap-types",
  "datafusion",
diff --git a/Cargo.toml b/Cargo.toml
index a2b019af8..b33026447 100644
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -2,6 +2,7 @@
 members = [
     "crates/asap-physical-operators",
     "crates/types",
+    "crates/frontend-common",
     "crates/sql-function-catalog",
     "crates/asap-aware-mapping",
     "crates/frontend-promql",
diff --git a/crates/frontend-common/Cargo.toml b/crates/frontend-common/Cargo.toml
new file mode 100644
index 000000000..18f351e6c
--- /dev/null
+++ b/crates/frontend-common/Cargo.toml
@@ -0,0 +1,11 @@
+[package]
+name = "asap-frontend-common"
+version = "0.1.0"
+edition = "2021"
+
+# Shared front-end layer: the name-based `UnresolvedOp` tree every front end
+# emits, and the resolver that binds it into the unified `OperatorNode` IR.
+[dependencies]
+asap-types = { path = "../types" }
+serde = { version = "1", features = ["derive", "rc"] }
+thiserror = "2"
diff --git a/crates/frontend-common/src/lib.rs b/crates/frontend-common/src/lib.rs
new file mode 100644
index 000000000..f756bc46a
--- /dev/null
+++ b/crates/frontend-common/src/lib.rs
@@ -0,0 +1,23 @@
+//! `asap-frontend-common` — the front-end-facing, name-based operator tree
+//! and its resolver into the unified IR.
+//!
+//! A front end builds an [`UnresolvedOp`] tree (column references are
+//! name-based [`ColumnRef`](asap_types::pre_asap::ColumnRef)s) during its
+//! own `interpret` step and calls [`resolve_root`], which binds every
+//! reference to a positional `ColumnId` and returns the
+//! [`OperatorNode`](asap_types::ir::OperatorNode) DAG.
+//!
+//! - [`unresolved`] — [`UnresolvedOp`] / [`UnresolvedScalar`]: the tree.
+//! - [`schema_resolver`] — [`SchemaResolver`]: builds the binding schema of a
+//!   schemaless (PromQL) leaf from the names the query references.
+//! - [`resolve`] — [`resolve_root`]: the bottom-up binding walk.
+
+pub mod resolve;
+pub mod schema_resolver;
+pub mod unresolved;
+
+pub use resolve::{resolve_expr, resolve_root, resolve_scalar_root, ResolveDAGError};
+pub use schema_resolver::{SchemaCatalog, SchemaResolver, UsageDerivedCatalog};
+pub use unresolved::{
+    UnresolvedOp, UnresolvedPredicate, UnresolvedProjectItem, UnresolvedScalar, UnresolvedSortKey,
+};
diff --git a/crates/frontend-common/src/resolve.rs b/crates/frontend-common/src/resolve.rs
new file mode 100644
index 000000000..dc204527f
--- /dev/null
+++ b/crates/frontend-common/src/resolve.rs
@@ -0,0 +1,1188 @@
+//! Resolve a front-end-emitted [`UnresolvedOp`] tree into the unified IR
+//! ([`Rc<OperatorNode>`]): a single, shape-preserving, bottom-up walk that
+//! binds every [`ColumnRef`] to a positional `ColumnId`.
+//!
+//! Every structural decision (reduction choice, window folds, heavy-hitter
+//! recognition, ...) is the front end's; what is left here is the mechanical,
+//! schema-dependent substitution. Children are resolved first; each child
+//! becomes an `OperatorNode` whose derived `.schema` is the scope the parent's
+//! own references resolve against, so a `JOIN`'s concatenated schema and a
+//! cross-series aggregate's frozen-closed output bind to the right positions.
+//!
+//! Scope boundaries: `Join` / `SetOp` sides and the operators referenced from
+//! scalar positions (`scalar(v)`, subqueries) are each bound as a root in
+//! their own scope. A `BinaryOp` side is too, but additionally inherits the
+//! label names its enclosing scope references (issue #52): the `job` in
+//! `sum by (job)(a or b)` appears in neither side's own matchers.
+
+use asap_types::ir::aggregate_schema::aggregate_output_schema;
+use std::rc::Rc;
+
+use thiserror::Error;
+
+use asap_types::ir::operator_properties::ConcatDiscriminatorKey;
+use asap_types::ir::{NonASAPOp, OperatorNode, Predicate, ProjectItem, ScalarExpr, SortKey};
+use asap_types::pre_asap::column_resolution::resolve_group_keys_promql;
+use asap_types::pre_asap::{
+    resolve_column_ref, resolve_column_refs, AggIntent, ColumnId, ColumnRef, GroupKeys, Reduction,
+    ResolveError, Schema, SchemaDerivationError,
+};
+
+use crate::schema_resolver::{collect_referenced_columns, SchemaResolver};
+use crate::unresolved::{UnresolvedOp, UnresolvedScalar, UnresolvedSortKey};
+
+/// Errors from resolving an [`UnresolvedOp`] tree.
+#[derive(Debug, Error)]
+pub enum ResolveDAGError {
+    /// A column reference did not resolve against its in-scope schema.
+    #[error("column resolution failed: {0}")]
+    Resolve(#[from] ResolveError),
+    /// Deriving the schema of an already-resolved child failed (needed to
+    /// resolve positional column references against it).
+    #[error("schema derivation failed: {0}")]
+    Schema(#[from] SchemaDerivationError),
+}
+
+use asap_types::ir::canonicalize::canonicalize;
+
+/// Resolve the whole tree rooted at `tree`: bind every `ColumnRef` to a
+/// `ColumnId` via the [`SchemaResolver`], then canonicalize the result.
+pub fn resolve_root(tree: &UnresolvedOp) -> Result<Rc<OperatorNode>, ResolveDAGError> {
+    resolve_root_with_inherited(tree, &[])
+}
+
+/// [`resolve_root`] with label names inherited from an enclosing scope seeded
+/// into the leaf schema (a `BinaryOp` side, a scalar operand's operator).
+fn resolve_root_with_inherited(
+    tree: &UnresolvedOp,
+    inherited: &[String],
+) -> Result<Rc<OperatorNode>, ResolveDAGError> {
+    let fallback = SchemaResolver::new().resolve_schema_with_inherited(tree, inherited);
+    let root = resolve(tree, &fallback)?;
+    let root = canonicalize(root)?;
+    root.validate_structure()?;
+    Ok(root)
+}
+
+/// Bind `tree` as a root in its own scope, inheriting from `enclosing` the
+/// label names `tree` does not reference itself (issue #52).
+fn resolve_nested_root(
+    tree: &UnresolvedOp,
+    enclosing: &Schema,
+) -> Result<Rc<OperatorNode>, ResolveDAGError> {
+    let own = collect_referenced_columns(tree);
+    let inherited: Vec<String> = inherited_names(enclosing)
+        .into_iter()
+        .filter(|n| !own.contains(n))
+        .collect();
+    resolve_root_with_inherited(tree, &inherited)
+}
+
+fn node(op: NonASAPOp) -> Result<Rc<OperatorNode>, ResolveDAGError> {
+    Ok(OperatorNode::new_shared(
+        asap_types::ir::Operator::NonASAP(op),
+    )?)
+}
+
+/// The generic substitution walk. `fallback` is the usage-derived schema a
+/// schemaless `Scan` in this scope binds to.
+fn resolve(tree: &UnresolvedOp, fallback: &Schema) -> Result<Rc<OperatorNode>, ResolveDAGError> {
+    use UnresolvedOp as U;
+    let expr = |e: &UnresolvedScalar, schema: &Schema| resolve_expr_in(e, schema, fallback);
+    let pred = |p: &UnresolvedScalar, schema: &Schema| {
+        Ok::<_, ResolveDAGError>(Predicate(expr(p, schema)?))
+    };
+    let sort_keys = |keys: &[UnresolvedSortKey], schema: &Schema| {
+        keys.iter()
+            .map(|k| {
+                Ok::<_, ResolveDAGError>(SortKey {
+                    expr: expr(&k.expr, schema)?,
+                    ascending: k.ascending,
+                    nulls_first: k.nulls_first,
+                })
+            })
+            .collect::<Result<Vec<_>, _>>()
+    };
+    match tree {
+        U::Scan {
+            source,
+            predicates,
+            schema,
+        } => {
+            let schema = schema.clone().unwrap_or_else(|| fallback.clone());
+            let predicates = predicates
+                .iter()
+                .map(|p| pred(&p.0, &schema))
+                .collect::<Result<Vec<_>, _>>()?;
+            node(NonASAPOp::Scan {
+                source: source.clone(),
+                predicates,
+                schema,
+            })
+        }
+
+        // Row expressions have no input-column scope.
+        U::Values { rows, schema } => {
+            let empty = Schema::new(Vec::new());
+            let rows = rows
+                .iter()
+                .map(|row| {
+                    row.iter()
+                        .map(|e| expr(e, &empty))
+                        .collect::<Result<Vec<_>, _>>()
+                })
+                .collect::<Result<Vec<_>, _>>()?;
+            node(NonASAPOp::Values {
+                rows,
+                schema: schema.clone(),
+            })
+        }
+
+        // A scalar at an operator position has no child scope; in practice a
+        // literal, so `fallback` is never consulted for a column here.
+        U::PromqlScalarOp {
+            child,
+            scalar,
+            op,
+            scalar_left,
+            return_bool,
+        } => {
+            let child = resolve(child, fallback)?;
+            let child = if child.schema.closed {
+                child
+            } else {
+                asap_types::ir::schema_support::with_promql_series_identity(&child)
+                    .map_err(SchemaDerivationError::InvalidScalarSignature)?
+            };
+            let scalar = resolve_expr(scalar, &Schema::default())?;
+            lower_scalar_vector(child, scalar, op, *scalar_left, *return_bool)
+        }
+        U::PromqlMap {
+            child,
+            sample,
+            drop_metric_name,
+        } => {
+            let child = resolve(child, fallback)?;
+            let child = if child.schema.closed {
+                child
+            } else {
+                asap_types::ir::schema_support::with_promql_series_identity(&child)
+                    .map_err(SchemaDerivationError::InvalidScalarSignature)?
+            };
+            let sample = resolve_expr(sample, &child.schema)?;
+            project_sample(child, sample, *drop_metric_name)
+        }
+        U::PromqlVectorFromScalar(inner) => {
+            node(NonASAPOp::PromqlVectorFromScalar(expr(inner, fallback)?))
+        }
+
+        U::PromqlRelabel { dst, value, child } => {
+            let child = resolve(child, fallback)?;
+            let value = expr(value, &child.schema)?;
+            node(NonASAPOp::PromqlRelabel {
+                dst: dst.clone(),
+                value,
+                child,
+            })
+        }
+
+        U::PromqlInfoEnrich { selector, child } => node(NonASAPOp::PromqlInfoEnrich {
+            selector: selector.clone(),
+            child: resolve(child, fallback)?,
+        }),
+
+        U::PromqlSeriesSample { by, kind, child } => {
+            let child = resolve(child, fallback)?;
+            let by = resolve_group_keys(by, &child.schema)?;
+            node(NonASAPOp::PromqlSeriesSample {
+                by,
+                kind: *kind,
+                child,
+            })
+        }
+
+        U::Filter { pred: p, child } => {
+            let child = resolve(child, fallback)?;
+            let pred = pred(&p.0, &child.schema)?;
+            node(NonASAPOp::Filter { pred, child })
+        }
+
+        U::Project {
+            cols,
+            qualifier,
+            child,
+        } => {
+            let child = resolve(child, fallback)?;
+            let cols = cols
+                .iter()
+                .map(|item| {
+                    Ok::<_, ResolveDAGError>(ProjectItem {
+                        alias: item.alias.clone(),
+                        expr: expr(&item.expr, &child.schema)?,
+                    })
+                })
+                .collect::<Result<Vec<_>, _>>()?;
+            node(NonASAPOp::Project {
+                cols,
+                qualifier: qualifier.clone(),
+                child,
+            })
+        }
+
+        U::Aggregate {
+            reduction,
+            measures,
+            output_names,
+            filters,
+            having,
+            child,
+        } => {
+            let child = resolve(child, fallback)?;
+            let reduction = resolve_reduction(reduction, &child.schema)?;
+            let measures = measures
+                .iter()
+                .map(|m| resolve_agg_intent(m, &child.schema))
+                .collect::<Result<Vec<_>, ResolveError>>()?;
+            let filters = filters
+                .iter()
+                .map(|p| p.as_ref().map(|p| pred(&p.0, &child.schema)).transpose())
+                .collect::<Result<Vec<_>, _>>()?;
+            // HAVING is evaluated over the aggregate's own output.
+            let having = having
+                .as_ref()
+                .map(|h| {
+                    let out_schema = aggregate_output_schema(
+                        &child.schema,
+                        &reduction,
+                        &measures,
+                        output_names,
+                    )?;
+                    pred(&h.0, &out_schema)
+                })
+                .transpose()?;
+            node(NonASAPOp::Aggregate {
+                reduction,
+                measures,
+                output_names: output_names.clone(),
+                filters,
+                having,
+                child,
+            })
+        }
+
+        U::Dedup { cols, child } => {
+            let child = resolve(child, fallback)?;
+            let cols = resolve_column_refs(cols, &child.schema)?;
+            node(NonASAPOp::Dedup { cols, child })
+        }
+
+        U::Concat {
+            children,
+            discriminator_unique_key,
+        } => {
+            let children = children
+                .iter()
+                .map(|c| resolve(c, fallback))
+                .collect::<Result<Vec<_>, _>>()?;
+            // Resolved against the first branch's own output schema — the one
+            // `output_schema`'s `Concat` arm derives the merged schema from.
+            let discriminator_unique_key = discriminator_unique_key
+                .as_ref()
+                .map(|key| {
+                    let schema = &children
+                        .first()
+                        .ok_or(SchemaDerivationError::EmptyConcat)?
+                        .schema;
+                    Ok::<_, ResolveDAGError>(ConcatDiscriminatorKey::new(
+                        resolve_column_ref(key.discriminator(), schema)?,
+                        resolve_column_refs(key.inner_key(), schema)?,
+                    ))
+                })
+                .transpose()?;
+            node(NonASAPOp::Concat {
+                children,
+                discriminator_unique_key,
+            })
+        }
+
+        U::Join {
+            kind,
+            pred: p,
+            left,
+            right,
+        } => {
+            // Each branch is bound independently (different leaves / label
+            // sets); the predicate sees left ++ right.
+            let left = resolve_root_with_inherited(left, &[])?;
+            let right = resolve_root_with_inherited(right, &[])?;
+            let mut concat = left.schema.clone();
+            concat.fields.extend(right.schema.fields.iter().cloned());
+            let pred = pred(&p.0, &concat)?;
+            node(NonASAPOp::Join {
+                kind: kind.clone(),
+                pred,
+                left,
+                right,
+            })
+        }
+
+        U::SetOp {
+            kind,
+            all,
+            left,
+            right,
+        } => node(NonASAPOp::SetOp {
+            kind: kind.clone(),
+            all: *all,
+            left: resolve_root_with_inherited(left, &[])?,
+            right: resolve_root_with_inherited(right, &[])?,
+        }),
+
+        U::Sort {
+            keys,
+            partition_by,
+            child,
+        } => {
+            let child = resolve(child, fallback)?;
+            let keys = sort_keys(keys, &child.schema)?;
+            let partition_by = resolve_group_keys(partition_by, &child.schema)?;
+            node(NonASAPOp::Sort {
+                keys,
+                partition_by,
+                child,
+            })
+        }
+
+        U::Limit {
+            n,
+            offset,
+            partition_by,
+            child,
+        } => {
+            let child = resolve(child, fallback)?;
+            let partition_by = resolve_group_keys(partition_by, &child.schema)?;
+            node(NonASAPOp::Limit {
+                n: *n,
+                offset: *offset,
+                partition_by,
+                child,
+            })
+        }
+
+        U::PromqlSubquery {
+            range,
+            resolution,
+            child,
+        } => node(NonASAPOp::PromqlSubquery {
+            range: *range,
+            resolution: *resolution,
+            child: resolve(child, fallback)?,
+        }),
+
+        U::TimeRange { range, kind, child } => node(NonASAPOp::TimeRange {
+            range: *range,
+            kind: *kind,
+            child: resolve(child, fallback)?,
+        }),
+
+        U::TimeShift { shift, child } => node(NonASAPOp::TimeShift {
+            shift: *shift,
+            child: resolve(child, fallback)?,
+        }),
+
+        U::SQLWindowFunc {
+            func,
+            args,
+            partition_by,
+            order_by,
+            frame,
+            output_name,
+            child,
+        } => {
+            let child = resolve(child, fallback)?;
+            let args = args
+                .iter()
+                .map(|a| expr(a, &child.schema))
+                .collect::<Result<Vec<_>, _>>()?;
+            let partition_by = resolve_group_keys(partition_by, &child.schema)?;
+            let order_by = sort_keys(order_by, &child.schema)?;
+            node(NonASAPOp::SQLWindowFunc {
+                func: func.clone(),
+                args,
+                partition_by,
+                order_by,
+                frame: frame.clone(),
+                output_name: output_name.clone(),
+                child,
+            })
+        }
+
+        U::BinaryOp {
+            operator,
+            return_bool,
+            lhs,
+            rhs,
+        } => {
+            // The two sides may scan different metrics with different label
+            // sets, so each resolves against its OWN bound schema — but still
+            // sees the label names the enclosing scope references (issue #52).
+            // The inherited set is computed over the whole `BinaryOp`, so one
+            // side's own labels are not conjured into the other.
+            let own = collect_referenced_columns(tree);
+            let inherited: Vec<String> = inherited_names(fallback)
+                .into_iter()
+                .filter(|n| !own.contains(n))
+                .collect();
+            node(NonASAPOp::BinaryOp {
+                operator: operator.clone(),
+                return_bool: *return_bool,
+                lhs: resolve_root_with_inherited(lhs, &inherited)?,
+                rhs: resolve_root_with_inherited(rhs, &inherited)?,
+            })
+        }
+    }
+}
+
+/// The label names an enclosing scope's schema carries beyond the `(ts,
+/// value)` floor.
+fn inherited_names(schema: &Schema) -> Vec<String> {
+    schema
+        .fields
+        .iter()
+        .filter(|c| c.name != "ts" && c.name != "value")
+        .map(|c| c.name.clone())
+        .collect()
+}
+
+/// Resolve a name-based scalar expression against `schema`. Operators it
+/// reads (`scalar(v)`, subqueries) are bound as roots in their own scope,
+/// inheriting `schema`'s label names.
+pub fn resolve_expr(
+    expr: &UnresolvedScalar,
+    schema: &Schema,
+) -> Result<ScalarExpr, ResolveDAGError> {
+    resolve_expr_in(expr, schema, schema)
+}
+
+/// [`resolve_expr`] where the operators the expression reads inherit from
+/// `enclosing` (the owning root's fallback schema) rather than from `schema`.
+fn resolve_expr_in(
+    expr: &UnresolvedScalar,
+    schema: &Schema,
+    enclosing: &Schema,
+) -> Result<ScalarExpr, ResolveDAGError> {
+    use UnresolvedScalar as S;
+    let bx = |e: &UnresolvedScalar| -> Result<Box<ScalarExpr>, ResolveDAGError> {
+        Ok(Box::new(resolve_expr_in(e, schema, enclosing)?))
+    };
+    let each = |es: &[UnresolvedScalar]| -> Result<Vec<ScalarExpr>, ResolveDAGError> {
+        es.iter()
+            .map(|e| resolve_expr_in(e, schema, enclosing))
+            .collect()
+    };
+    let op = |o: &UnresolvedOp| resolve_nested_root(o, enclosing);
+    Ok(match expr {
+        S::Column(c) => ScalarExpr::Column(resolve_column_ref(c, schema)?),
+        S::Literal(s) => ScalarExpr::Literal(s.clone()),
+        S::EvalTimestamp => ScalarExpr::EvalTimestamp,
+        S::CurrentTimestamp => ScalarExpr::CurrentTimestamp,
+        S::Negative { expr, semantics } => ScalarExpr::Negative {
+            expr: bx(expr)?,
+            semantics: *semantics,
+        },
+        S::Compare {
+            left,
+            op,
+            right,
+            semantics,
+        } => ScalarExpr::Compare {
+            left: bx(left)?,
+            op: op.clone(),
+            right: bx(right)?,
+            semantics: *semantics,
+        },
+        S::BoolAnd(v) => ScalarExpr::BoolAnd(each(v)?),
+        S::BoolOr(v) => ScalarExpr::BoolOr(each(v)?),
+        S::Not(e) => ScalarExpr::Not(bx(e)?),
+        S::IsNull(e) => ScalarExpr::IsNull(bx(e)?),
+        S::IsNotNull(e) => ScalarExpr::IsNotNull(bx(e)?),
+        S::Cast { expr, to, try_cast } => ScalarExpr::Cast {
+            expr: bx(expr)?,
+            to: to.clone(),
+            try_cast: *try_cast,
+        },
+        S::InList {
+            expr,
+            list,
+            negated,
+        } => ScalarExpr::InList {
+            expr: bx(expr)?,
+            list: each(list)?,
+            negated: *negated,
+        },
+        S::FunctionCall { name, args } => ScalarExpr::FunctionCall {
+            name: name.clone(),
+            args: each(args)?,
+        },
+        S::Arithmetic {
+            op,
+            left,
+            right,
+            semantics,
+        } => ScalarExpr::Arithmetic {
+            op: op.clone(),
+            left: bx(left)?,
+            right: bx(right)?,
+            semantics: *semantics,
+        },
+        S::Case {
+            operand,
+            branches,
+            else_expr,
+        } => ScalarExpr::Case {
+            operand: operand.as_deref().map(bx).transpose()?,
+            branches: branches
+                .iter()
+                .map(|(w, t)| {
+                    Ok((
+                        resolve_expr_in(w, schema, enclosing)?,
+                        resolve_expr_in(t, schema, enclosing)?,
+                    ))
+                })
+                .collect::<Result<Vec<_>, ResolveDAGError>>()?,
+            else_expr: else_expr.as_deref().map(bx).transpose()?,
+        },
+        S::PromqlScalarFromVector(o) => ScalarExpr::PromqlScalarFromVector(op(o)?),
+        S::ScalarSubquery(o) => ScalarExpr::ScalarSubquery(op(o)?),
+        S::Exists { subquery, negated } => ScalarExpr::Exists {
+            subquery: op(subquery)?,
+            negated: *negated,
+        },
+        S::InSubquery {
+            expr,
+            subquery,
+            negated,
+        } => ScalarExpr::InSubquery {
+            expr: bx(expr)?,
+            subquery: op(subquery)?,
+            negated: *negated,
+        },
+    })
+}
+
+/// Resolve name-based group keys positionally, preserving `by`/`without`.
+fn resolve_group_keys(
+    keys: &GroupKeys<ColumnRef>,
+    schema: &Schema,
+) -> Result<GroupKeys<ColumnId>, ResolveError> {
+    let ids = resolve_column_refs(keys.keys(), schema)?;
+    Ok(if keys.is_without() {
+        GroupKeys::without(ids)
+    } else {
+        GroupKeys::by(ids)
+    })
+}
+
+/// Resolve a name-based reduction. Uses [`resolve_group_keys_promql`] rather
+/// than the strict [`resolve_group_keys`]: a key absent from a **closed**
+/// schema (the output of a nested cross-series aggregate that collapsed the
+/// label) is provably absent from every row, so PromQL drops it from the
+/// grouping rather than rejecting the query (issue #53) — `sum(sum by (group)
+/// (m)) by (job)`. SQL `GROUP BY` keys are always present, so the lenient
+/// path is a no-op difference there.
+fn resolve_reduction(
+    reduction: &Reduction<ColumnRef>,
+    schema: &Schema,
+) -> Result<Reduction<ColumnId>, ResolveError> {
+    Ok(match reduction {
+        Reduction::Reduce(by) => {
+            let ids = resolve_group_keys_promql(by.keys(), schema)?;
+            Reduction::Reduce(if by.is_without() {
+                GroupKeys::without(ids)
+            } else {
+                GroupKeys::by(ids)
+            })
+        }
+        Reduction::PerEntity => Reduction::PerEntity,
+    })
+}
+
+/// Resolve a name-based aggregate intent: every `col: Option<ColumnRef>`
+/// resolves to `Option<ColumnId>` (`None` stays `None`, the sample-value
+/// convention); every other field carries through unchanged.
+fn resolve_agg_intent(
+    intent: &AggIntent<ColumnRef>,
+    schema: &Schema,
+) -> Result<AggIntent<ColumnId>, ResolveError> {
+    let col = |c: &Option<ColumnRef>| -> Result<Option<ColumnId>, ResolveError> {
+        c.as_ref()
+            .map(|r| resolve_column_ref(r, schema))
+            .transpose()
+    };
+    Ok(match intent {
+        AggIntent::Count { accuracy } => AggIntent::Count {
+            accuracy: accuracy.clone(),
+        },
+        AggIntent::PearsonCorr { left, right } => AggIntent::PearsonCorr {
+            left: resolve_column_ref(left, schema)?,
+            right: resolve_column_ref(right, schema)?,
+        },
+        AggIntent::Sum { col: c } => AggIntent::Sum { col: col(c)? },
+        AggIntent::Min { col: c } => AggIntent::Min { col: col(c)? },
+        AggIntent::Max { col: c } => AggIntent::Max { col: col(c)? },
+        AggIntent::Avg { col: c } => AggIntent::Avg { col: col(c)? },
+        AggIntent::StdDev { col: c, population } => AggIntent::StdDev {
+            col: col(c)?,
+            population: *population,
+        },
+        AggIntent::Variance { col: c, population } => AggIntent::Variance {
+            col: col(c)?,
+            population: *population,
+        },
+        AggIntent::Quantile {
+            col: c,
+            q,
+            accuracy,
+        } => AggIntent::Quantile {
+            col: col(c)?,
+            q: *q,
+            accuracy: accuracy.clone(),
+        },
+        AggIntent::TopK { k, accuracy } => AggIntent::TopK {
+            k: *k,
+            accuracy: accuracy.clone(),
+        },
+        AggIntent::Cardinality { cols, accuracy } => AggIntent::Cardinality {
+            cols: cols
+                .iter()
+                .map(|c| resolve_column_ref(c, schema))
+                .collect::<Result<_, _>>()?,
+            accuracy: accuracy.clone(),
+        },
+        AggIntent::FrequencyL2 { col: c, accuracy } => AggIntent::FrequencyL2 {
+            col: col(c)?,
+            accuracy: accuracy.clone(),
+        },
+        AggIntent::FrequencyEntropy { col: c, accuracy } => AggIntent::FrequencyEntropy {
+            col: col(c)?,
+            accuracy: accuracy.clone(),
+        },
+        AggIntent::Rate => AggIntent::Rate,
+        AggIntent::IRate => AggIntent::IRate,
+        AggIntent::Increase => AggIntent::Increase,
+        AggIntent::Changes => AggIntent::Changes,
+        AggIntent::Delta => AggIntent::Delta,
+        AggIntent::IDelta => AggIntent::IDelta,
+        AggIntent::Deriv => AggIntent::Deriv,
+        AggIntent::Resets => AggIntent::Resets,
+        AggIntent::PredictLinear { seconds } => AggIntent::PredictLinear { seconds: *seconds },
+        AggIntent::DoubleExpSmoothing { smoothing, trend } => AggIntent::DoubleExpSmoothing {
+            smoothing: *smoothing,
+            trend: *trend,
+        },
+        AggIntent::HistogramCount => AggIntent::HistogramCount,
+        AggIntent::HistogramSum => AggIntent::HistogramSum,
+        AggIntent::HistogramAvg => AggIntent::HistogramAvg,
+        AggIntent::HistogramStdDev => AggIntent::HistogramStdDev,
+        AggIntent::HistogramStdVar => AggIntent::HistogramStdVar,
+        AggIntent::HistogramFraction { lower, upper } => AggIntent::HistogramFraction {
+            lower: *lower,
+            upper: *upper,
+        },
+        AggIntent::HistogramQuantile { q, le } => AggIntent::HistogramQuantile {
+            q: *q,
+            le: resolve_column_ref(le, schema)?,
+        },
+        AggIntent::Math(f) => AggIntent::Math(f.clone()),
+        AggIntent::Absent => AggIntent::Absent,
+        AggIntent::AbsentOverTime => AggIntent::AbsentOverTime,
+        AggIntent::PresentOverTime => AggIntent::PresentOverTime,
+        AggIntent::TimeFn(f) => AggIntent::TimeFn(*f),
+        AggIntent::Group => AggIntent::Group,
+        AggIntent::CountValues { label } => AggIntent::CountValues {
+            label: label.clone(),
+        },
+        AggIntent::LastOverTime => AggIntent::LastOverTime,
+        AggIntent::FirstOverTime => AggIntent::FirstOverTime,
+        AggIntent::MadOverTime => AggIntent::MadOverTime,
+        AggIntent::TsOfMinOverTime => AggIntent::TsOfMinOverTime,
+        AggIntent::TsOfMaxOverTime => AggIntent::TsOfMaxOverTime,
+        AggIntent::TsOfFirstOverTime => AggIntent::TsOfFirstOverTime,
+        AggIntent::TsOfLastOverTime => AggIntent::TsOfLastOverTime,
+        AggIntent::Extension { ext_kind, payload } => AggIntent::Extension {
+            ext_kind: ext_kind.clone(),
+            payload: payload.clone(),
+        },
+    })
+}
+
+/// Resolve a standalone scalar in an empty column scope; plan reads retain their own scope.
+pub fn resolve_scalar_root(tree: &UnresolvedScalar) -> Result<ScalarExpr, ResolveDAGError> {
+    let resolved = resolve_expr(tree, &Schema::default())?;
+    resolved.scalar_type(&Schema::default())?;
+    Ok(resolved)
+}
+
+fn lower_scalar_vector(
+    child: Rc<OperatorNode>,
+    scalar: ScalarExpr,
+    op: &asap_types::pre_asap::BinaryOpKind,
+    scalar_left: bool,
+    return_bool: bool,
+) -> Result<Rc<OperatorNode>, ResolveDAGError> {
+    use asap_types::ir::ExprSemantics;
+    use asap_types::pre_asap::{BinaryOpKind, DataType, ScalarValue};
+    let value = child
+        .schema
+        .column_id("value")
+        .or_else(|| {
+            child
+                .schema
+                .fields
+                .iter()
+                .enumerate()
+                .filter(|(i, f)| {
+                    Some(*i) != child.schema.time_index
+                        && matches!(f.plain_dtype(), Some(DataType::Float64 | DataType::Int64))
+                })
+                .map(|(i, _)| i)
+                .next_back()
+        })
+        .ok_or_else(|| {
+            SchemaDerivationError::InvalidScalarSignature("vector has no numeric sample".into())
+        })?;
+    let sample = ScalarExpr::Column(value);
+    let (left, right) = if scalar_left {
+        (scalar, sample)
+    } else {
+        (sample, scalar)
+    };
+    let semantics = ExprSemantics::Promql;
+    let return_bool = return_bool || matches!(op, BinaryOpKind::CompareBool(_));
+    let computed = match op {
+        BinaryOpKind::Arithmetic(op) => ScalarExpr::Arithmetic {
+            op: op.clone(),
+            left: Box::new(left),
+            right: Box::new(right),
+            semantics,
+        },
+        BinaryOpKind::Compare(op) | BinaryOpKind::CompareBool(op) => {
+            let predicate = ScalarExpr::Compare {
+                op: op.clone(),
+                left: Box::new(left),
+                right: Box::new(right),
+                semantics,
+            };
+            if !return_bool {
+                return node(NonASAPOp::Filter {
+                    child,
+                    pred: Predicate(predicate),
+                });
+            }
+            ScalarExpr::Case {
+                operand: None,
+                branches: vec![(predicate, ScalarExpr::Literal(ScalarValue::Float64(1.0)))],
+                else_expr: Some(Box::new(ScalarExpr::Literal(ScalarValue::Float64(0.0)))),
+            }
+        }
+        BinaryOpKind::Set(_) => {
+            return Err(SchemaDerivationError::InvalidScalarSignature(
+                "set operators require two vectors".into(),
+            )
+            .into())
+        }
+    };
+    project_sample(child, computed, true)
+}
+
+fn project_sample(
+    child: Rc<OperatorNode>,
+    computed: ScalarExpr,
+    drop_metric_name: bool,
+) -> Result<Rc<OperatorNode>, ResolveDAGError> {
+    let value = asap_types::pre_asap::column_resolution::resolve_column_ref(
+        &ColumnRef::SampleValue,
+        &child.schema,
+    )?;
+    let cols = child
+        .schema
+        .fields
+        .iter()
+        .enumerate()
+        .filter(|(_, f)| !drop_metric_name || f.name != "__name__")
+        .map(|(i, f)| {
+            let expr = if i == value {
+                computed.clone()
+            } else if drop_metric_name
+                && f.name == asap_types::pre_asap::schema::PROMQL_SERIES_IDENTITY
+            {
+                ScalarExpr::FunctionCall {
+                    name: "promql_drop_metric_name".into(),
+                    args: vec![ScalarExpr::Column(i)],
+                }
+            } else {
+                ScalarExpr::Column(i)
+            };
+            ProjectItem {
+                alias: Some(f.name.clone()),
+                expr,
+            }
+        })
+        .collect();
+    node(NonASAPOp::Project {
+        child,
+        cols,
+        qualifier: None,
+    })
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::unresolved::UnresolvedPredicate;
+    use asap_types::ir::BinaryOperator;
+    use asap_types::ir::ExprSemantics;
+    use asap_types::pre_asap::{
+        BinaryOpKind, CompareOpKind, DataType, Field, JoinKind, PromQLVectorSetOpKind, ScalarValue,
+        Source, VectorMatch,
+    };
+    use asap_types::types::AccuracyTarget;
+
+    fn scan(metric: &str) -> UnresolvedOp {
+        UnresolvedOp::Scan {
+            source: Source::TimeSeries {
+                metric: metric.into(),
+            },
+            predicates: vec![],
+            schema: None,
+        }
+    }
+
+    fn named(n: &str) -> UnresolvedScalar {
+        UnresolvedScalar::Column(ColumnRef::Named(n.into()))
+    }
+
+    fn eq_lit(col: UnresolvedScalar, v: &str) -> UnresolvedScalar {
+        UnresolvedScalar::Compare {
+            left: Box::new(col),
+            op: CompareOpKind::Eq,
+            right: Box::new(UnresolvedScalar::Literal(ScalarValue::Utf8(v.into()))),
+            semantics: ExprSemantics::Promql,
+        }
+    }
+
+    fn binary(kind: BinaryOpKind, vector_match: Option<VectorMatch>) -> BinaryOperator {
+        BinaryOperator {
+            checked_relative_division: false,
+            checked_finite_division: false,
+            kind,
+            vector_match,
+        }
+    }
+
+    // Both sides resolve with qualifiers; an unknown right input is an error.
+    #[test]
+    fn resolve_pearson_corr_inputs() {
+        let schema = Schema::new(vec![
+            Field::plain("x", DataType::Float64, true).with_table("a"),
+            Field::plain("x", DataType::Float64, true).with_table("b"),
+        ]);
+        let intent = AggIntent::PearsonCorr {
+            left: ColumnRef::Qualified {
+                table: "a".into(),
+                name: "x".into(),
+            },
+            right: ColumnRef::Qualified {
+                table: "b".into(),
+                name: "x".into(),
+            },
+        };
+        assert_eq!(
+            resolve_agg_intent(&intent, &schema).unwrap(),
+            AggIntent::PearsonCorr { left: 0, right: 1 }
+        );
+        let missing = AggIntent::PearsonCorr {
+            left: ColumnRef::Qualified {
+                table: "a".into(),
+                name: "x".into(),
+            },
+            right: ColumnRef::Named("missing".into()),
+        };
+        assert!(resolve_agg_intent(&missing, &schema).is_err());
+    }
+
+    // Every leg resolves independently, qualifiers included; one unknown leg
+    // fails rather than silently shortening the tuple.
+    #[test]
+    fn resolve_distinct_tuple_columns() {
+        let schema = Schema::new(vec![
+            Field::plain("k", DataType::Int64, true).with_table("a"),
+            Field::plain("k", DataType::Int64, true).with_table("b"),
+        ]);
+        let qualified = |table: &str| ColumnRef::Qualified {
+            table: table.into(),
+            name: "k".into(),
+        };
+        let intent = AggIntent::Cardinality {
+            cols: vec![qualified("b"), qualified("a")],
+            accuracy: AccuracyTarget::Exact,
+        };
+        assert_eq!(
+            resolve_agg_intent(&intent, &schema).unwrap(),
+            AggIntent::Cardinality {
+                cols: vec![1, 0],
+                accuracy: AccuracyTarget::Exact,
+            }
+        );
+        let missing = AggIntent::Cardinality {
+            cols: vec![qualified("a"), ColumnRef::Named("missing".into())],
+            accuracy: AccuracyTarget::Exact,
+        };
+        assert!(resolve_agg_intent(&missing, &schema).is_err());
+    }
+
+    // `<vector> > <scalar>`: the bridged literal comes through unchanged, the
+    // vector side binds positionally, the `VectorMatch` survives untouched, and
+    // the node's schema follows the vector side.
+    #[test]
+    fn scalar_comparison_preserves_vector_values_and_labels() {
+        let unresolved = UnresolvedOp::PromqlScalarOp {
+            child: Rc::new(scan("up")),
+            scalar: UnresolvedScalar::Literal(ScalarValue::Float64(1.0)),
+            op: BinaryOpKind::Compare(CompareOpKind::Gt),
+            scalar_left: true,
+            return_bool: false,
+        };
+        let resolved = resolve_root(&unresolved).unwrap();
+        let NonASAPOp::Filter {
+            child,
+            pred: Predicate(ScalarExpr::Compare { left, right, .. }),
+        } = resolved.expect_non_asap()
+        else {
+            panic!("expected Filter")
+        };
+        assert_eq!(**left, ScalarExpr::literal_f64(1.0));
+        assert_eq!(
+            **right,
+            ScalarExpr::Column(child.schema.column_id("value").unwrap())
+        );
+        assert_eq!(resolved.schema, child.schema);
+        assert!(resolved.schema.has_promql_series_identity());
+    }
+
+    // A `Concat` discriminator column referenced nowhere else, over a
+    // schemaless first branch, resolves to the branch's own positional ids.
+    #[test]
+    fn resolve_root_seeds_and_resolves_an_otherwise_unreferenced_discriminator_column() {
+        let unresolved = UnresolvedOp::concat_with_discriminator(
+            vec![scan("m"), scan("m")],
+            ColumnRef::Named("phi".into()),
+            vec![ColumnRef::Named("host".into())],
+        );
+
+        let resolved = resolve_root(&unresolved).expect("resolves");
+        let NonASAPOp::Concat {
+            children,
+            discriminator_unique_key,
+        } = resolved.expect_non_asap()
+        else {
+            panic!("expected a resolved Concat, got {resolved:?}");
+        };
+        let schema = &children[0].schema;
+        let key = discriminator_unique_key
+            .as_ref()
+            .expect("discriminator key survives resolution");
+        assert_eq!(*key.discriminator(), schema.column_id("phi").unwrap());
+        assert_eq!(
+            key.inner_key().to_vec(),
+            vec![schema.column_id("host").unwrap()]
+        );
+    }
+
+    // `sum by (job)(a or b)`: each `BinaryOp` side binds in its own scope but
+    // inherits the enclosing aggregate's group key (issue #52).
+    #[test]
+    fn binary_op_sides_inherit_enclosing_group_keys() {
+        let unresolved = UnresolvedOp::Aggregate {
+            reduction: Reduction::by(vec![ColumnRef::Named("job".into())]),
+            measures: vec![AggIntent::Sum { col: None }],
+            output_names: vec![],
+            filters: vec![],
+            having: None,
+            child: Rc::new(UnresolvedOp::BinaryOp {
+                operator: binary(BinaryOpKind::Set(PromQLVectorSetOpKind::Or), None),
+                return_bool: false,
+                lhs: Rc::new(scan("a")),
+                rhs: Rc::new(scan("b")),
+            }),
+        };
+        let resolved = resolve_root(&unresolved).expect("resolves");
+        let NonASAPOp::Aggregate {
+            reduction, child, ..
+        } = resolved.expect_non_asap()
+        else {
+            panic!("expected Aggregate");
+        };
+        let NonASAPOp::BinaryOp { lhs, rhs, .. } = child.expect_non_asap() else {
+            panic!("expected BinaryOp");
+        };
+        let job = lhs.schema.column_id("job").expect("lhs sees job");
+        assert_eq!(rhs.schema.column_id("job"), Some(job));
+        assert_eq!(reduction.expect_reduce().keys(), &[job]);
+        assert_eq!(resolved.schema.fields[0].name, "job");
+    }
+
+    // HAVING binds against the aggregate's output, not its input.
+    #[test]
+    fn having_resolves_against_aggregate_output() {
+        let input = Schema::new(vec![
+            Field::plain("k", DataType::Utf8, false),
+            Field::plain("v", DataType::Float64, false),
+        ]);
+        let unresolved = UnresolvedOp::Aggregate {
+            reduction: Reduction::by(vec![ColumnRef::Named("k".into())]),
+            measures: vec![AggIntent::Sum {
+                col: Some(ColumnRef::Named("v".into())),
+            }],
+            output_names: vec!["total".into()],
+            filters: vec![],
+            having: Some(UnresolvedPredicate(UnresolvedScalar::Compare {
+                left: Box::new(named("total")),
+                op: CompareOpKind::Gt,
+                right: Box::new(UnresolvedScalar::Literal(ScalarValue::Float64(1.0))),
+                semantics: ExprSemantics::Sql,
+            })),
+            child: Rc::new(UnresolvedOp::Scan {
+                source: Source::Table {
+                    table_ref: "t".into(),
+                },
+                predicates: vec![],
+                schema: Some(input),
+            }),
+        };
+        let resolved = resolve_root(&unresolved).expect("resolves");
+        let NonASAPOp::Aggregate {
+            having: Some(Predicate(ScalarExpr::Compare { left, .. })),
+            ..
+        } = resolved.expect_non_asap()
+        else {
+            panic!("expected Aggregate with HAVING");
+        };
+        assert_eq!(**left, ScalarExpr::Column(1));
+        assert_eq!(resolved.schema.fields[1].name, "total");
+    }
+
+    // A join predicate binds against left ++ right; a qualified reference
+    // picks the right side even when both inputs share the column name.
+    #[test]
+    fn join_predicate_resolves_against_left_then_right() {
+        let side = |table: &str| UnresolvedOp::Scan {
+            source: Source::Table {
+                table_ref: table.into(),
+            },
+            predicates: vec![],
+            schema: Some(Schema::new(vec![
+                Field::plain("k", DataType::Int64, false).with_table(table)
+            ])),
+        };
+        let qualified = |table: &str| {
+            UnresolvedScalar::Column(ColumnRef::Qualified {
+                table: table.into(),
+                name: "k".into(),
+            })
+        };
+        let unresolved = UnresolvedOp::Join {
+            kind: JoinKind::Inner,
+            pred: UnresolvedPredicate(UnresolvedScalar::Compare {
+                left: Box::new(qualified("b")),
+                op: CompareOpKind::Eq,
+                right: Box::new(qualified("a")),
+                semantics: ExprSemantics::Sql,
+            }),
+            left: Rc::new(side("a")),
+            right: Rc::new(side("b")),
+        };
+        let resolved = resolve_root(&unresolved).expect("resolves");
+        let NonASAPOp::Join {
+            pred: Predicate(ScalarExpr::Compare { left, right, .. }),
+            ..
+        } = resolved.expect_non_asap()
+        else {
+            panic!("expected Join");
+        };
+        assert_eq!(**left, ScalarExpr::Column(1));
+        assert_eq!(**right, ScalarExpr::Column(0));
+    }
+
+    // `m * scalar(x{a="1"})`: the operator inside the scalar operand is bound
+    // as a root in its own scope — its matcher label seeds its own leaf, not
+    // the vector side's.
+    #[test]
+    fn scalar_from_vector_operand_binds_in_its_own_scope() {
+        let x = UnresolvedOp::Scan {
+            source: Source::TimeSeries { metric: "x".into() },
+            predicates: vec![UnresolvedPredicate(eq_lit(named("a"), "1"))],
+            schema: None,
+        };
+        let unresolved = UnresolvedOp::PromqlScalarOp {
+            child: Rc::new(scan("m")),
+            scalar: UnresolvedScalar::PromqlScalarFromVector(Rc::new(x)),
+            op: BinaryOpKind::Arithmetic(asap_types::pre_asap::ArithmeticOpKind::Mul),
+            scalar_left: false,
+            return_bool: false,
+        };
+        let resolved = resolve_root(&unresolved).unwrap();
+        let NonASAPOp::Project {
+            child: lhs, cols, ..
+        } = resolved.expect_non_asap()
+        else {
+            panic!("expected Project")
+        };
+        assert!(lhs.schema.column_id("a").is_none());
+        let ScalarExpr::Arithmetic { right, .. } = &cols[1].expr else {
+            panic!("expected arithmetic")
+        };
+        let ScalarExpr::PromqlScalarFromVector(inner) = right.as_ref() else {
+            panic!("expected scalar(v)")
+        };
+        let a = inner
+            .schema
+            .column_id("a")
+            .expect("own matcher label seeded");
+        let NonASAPOp::Scan { predicates, .. } = inner.expect_non_asap() else {
+            panic!("expected Scan");
+        };
+        let Predicate(ScalarExpr::Compare { left, .. }) = &predicates[0] else {
+            panic!("expected Compare");
+        };
+        assert_eq!(**left, ScalarExpr::Column(a));
+        assert_eq!(resolved.schema.fields.len(), lhs.schema.fields.len());
+    }
+
+    // PromQL grouping drops a key provably absent from a closed input (#53):
+    // `sum(sum by (group)(m)) by (job)`.
+    #[test]
+    fn nested_aggregate_drops_absent_promql_group_key() {
+        let inner = UnresolvedOp::Aggregate {
+            reduction: Reduction::by(vec![ColumnRef::Named("group".into())]),
+            measures: vec![AggIntent::Sum { col: None }],
+            output_names: vec![],
+            filters: vec![],
+            having: None,
+            child: Rc::new(scan("m")),
+        };
+        let outer = UnresolvedOp::Aggregate {
+            reduction: Reduction::by(vec![ColumnRef::Named("job".into())]),
+            measures: vec![AggIntent::Sum { col: None }],
+            output_names: vec![],
+            filters: vec![],
+            having: None,
+            child: Rc::new(inner),
+        };
+        let resolved = resolve_root(&outer).expect("resolves");
+        let NonASAPOp::Aggregate { reduction, .. } = resolved.expect_non_asap() else {
+            panic!("expected Aggregate");
+        };
+        assert!(reduction.expect_reduce().keys().is_empty());
+    }
+}
diff --git a/crates/frontend-common/src/schema_resolver.rs b/crates/frontend-common/src/schema_resolver.rs
new file mode 100644
index 000000000..ad7605fe6
--- /dev/null
+++ b/crates/frontend-common/src/schema_resolver.rs
@@ -0,0 +1,443 @@
+//! The **SchemaResolver** — name resolution as an explicit pass.
+//!
+//! [`SchemaResolver::resolve_schema`] produces the complete, self-contained
+//! [`Schema`] every `ColumnId` in a schemaless leaf's scope indexes into, so
+//! positional resolution in [`resolve`](crate::resolve) is total.
+//!
+//! The default [`UsageDerivedCatalog`] knows nothing — every schema is derived
+//! purely from the query's own usage. That is the honest state for the
+//! observability domain (metric label sets are open-ended). A registry-backed
+//! `SchemaCatalog` is future work; only the catalog impl swaps when it lands.
+
+use asap_types::pre_asap::{AggIntent, ColumnRef, DataType, Field, GroupKeys, Reduction, Schema};
+
+use crate::unresolved::{UnresolvedOp, UnresolvedScalar};
+
+/// The DB / source-schema metadata source — resolves a source (metric /
+/// table) name to its known columns. Distinct from `Scan.schema`, which is
+/// the *resolved* binding schema this feeds. Even a registry-backed PromQL
+/// catalog yields an **open** schema: a metric's labels are per-series and
+/// time-varying, so the registry is a superset hint, not a per-row contract.
+pub trait SchemaCatalog {
+    /// Columns known for `source`. `None` when unknown — the resolver then
+    /// falls back to a usage-derived column set.
+    fn columns_for(&self, source: &str) -> Option<Vec<Field>>;
+}
+
+/// The default catalog: knows nothing.
+pub struct UsageDerivedCatalog;
+
+impl SchemaCatalog for UsageDerivedCatalog {
+    fn columns_for(&self, _source: &str) -> Option<Vec<Field>> {
+        None
+    }
+}
+
+/// The explicit name-resolution pass.
+pub struct SchemaResolver<C: SchemaCatalog = UsageDerivedCatalog> {
+    catalog: C,
+}
+
+impl Default for SchemaResolver<UsageDerivedCatalog> {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl SchemaResolver<UsageDerivedCatalog> {
+    pub fn new() -> Self {
+        Self {
+            catalog: UsageDerivedCatalog,
+        }
+    }
+}
+
+impl<C: SchemaCatalog> SchemaResolver<C> {
+    pub fn with_catalog(catalog: C) -> Self {
+        Self { catalog }
+    }
+
+    /// The complete [`Schema`] in scope for a query rooted at `tree`: the
+    /// time axis, the synthetic `value` column, and one column per distinct
+    /// name referenced anywhere in the tree.
+    pub fn resolve_schema(&self, tree: &UnresolvedOp) -> Schema {
+        self.resolve_schema_with_inherited(tree, &[])
+    }
+
+    /// Like [`resolve_schema`](Self::resolve_schema), but also seeds
+    /// `inherited` label names referenced by an **enclosing** scope rather
+    /// than by `tree` itself. This is how an independently-bound `BinaryOp`
+    /// side still sees an outer aggregate's group keys — the `__name__` /
+    /// `job` in `sum by (__name__)(a or b)`, which appear in neither side's
+    /// own matchers (issue #52).
+    pub fn resolve_schema_with_inherited(
+        &self,
+        tree: &UnresolvedOp,
+        inherited: &[String],
+    ) -> Schema {
+        let mut columns: Vec<Field> = leftmost_scan_name(tree)
+            .and_then(|name| self.catalog.columns_for(name))
+            .unwrap_or_else(default_leaf_columns);
+
+        // Ensure the (ts, value) floor is present.
+        for floor in default_leaf_columns() {
+            if !columns.iter().any(|c| c.name == floor.name) {
+                columns.push(floor);
+            }
+        }
+
+        // One column per referenced-but-unknown name, plus the inherited ones.
+        let referenced = collect_referenced_columns(tree);
+        for name in referenced.iter().chain(inherited) {
+            if !columns.iter().any(|c| c.name == *name) {
+                columns.push(Field::plain(name.clone(), DataType::Utf8, true));
+            }
+        }
+
+        let time_index = columns.iter().position(|c| c.name == "ts");
+        Schema {
+            fields: columns,
+            time_index,
+            unique_keys: Vec::new(),
+            // Usage-derived (schemaless PromQL): the metric's full label set is
+            // open and runtime-only, so this lists only what the query references.
+            closed: false,
+        }
+    }
+}
+
+/// The conventional PromQL leaf shape: `(ts: Timestamp, value: Float64)`.
+fn default_leaf_columns() -> Vec<Field> {
+    vec![
+        Field::plain("ts", DataType::Timestamp, false),
+        Field::plain("value", DataType::Float64, false),
+    ]
+}
+
+/// Push a `ColumnRef`'s bare name (the schema-seedable identifier). `Qualified`
+/// collapses to its `name`; `SampleValue`/`Wildcard` carry no name.
+fn push_ref_name(c: &ColumnRef, out: &mut Vec<String>) {
+    match c {
+        ColumnRef::Named(n) => out.push(n.clone()),
+        ColumnRef::Qualified { name, .. } => out.push(name.clone()),
+        ColumnRef::SampleValue | ColumnRef::Wildcard => {}
+    }
+}
+
+/// The leftmost `Scan`'s source name, following the relational skeleton only
+/// (never the operators referenced from scalar positions: those are bound in
+/// their own scope).
+fn leftmost_scan_name(tree: &UnresolvedOp) -> Option<&str> {
+    use asap_types::pre_asap::Source;
+    use UnresolvedOp as U;
+    match tree {
+        U::Scan { source, .. } => Some(match source {
+            Source::TimeSeries { metric } => metric.as_str(),
+            Source::Table { table_ref } => table_ref.as_str(),
+        }),
+        U::Values { .. } | U::PromqlVectorFromScalar(_) => None,
+        U::PromqlMap { child, .. }
+        | U::PromqlScalarOp { child, .. }
+        | U::PromqlRelabel { child, .. }
+        | U::PromqlInfoEnrich { child, .. }
+        | U::PromqlSeriesSample { child, .. }
+        | U::Filter { child, .. }
+        | U::Project { child, .. }
+        | U::Aggregate { child, .. }
+        | U::Dedup { child, .. }
+        | U::Sort { child, .. }
+        | U::Limit { child, .. }
+        | U::PromqlSubquery { child, .. }
+        | U::TimeRange { child, .. }
+        | U::TimeShift { child, .. }
+        | U::SQLWindowFunc { child, .. } => leftmost_scan_name(child),
+        U::Concat { children, .. } => children.first().and_then(|c| leftmost_scan_name(c)),
+        U::Join { left, .. } | U::SetOp { left, .. } | U::BinaryOp { lhs: left, .. } => {
+            leftmost_scan_name(left)
+        }
+    }
+}
+
+/// Every distinct column name referenced anywhere in `tree` that resolves
+/// positionally — every place a front end puts a name-based reference:
+/// `Scan.predicates`, `Aggregate`'s `reduction`/`having`/per-measure `col`,
+/// `Dedup.cols`, `PromqlSeriesSample.by`, `Filter.pred`, `Project.cols`,
+/// `Sort`/`Limit`/`SQLWindowFunc` keys, `Join.pred`, `PromqlRelabel.value`,
+/// `Concat.discriminator_unique_key`. Operators referenced from scalar
+/// positions (`scalar(v)`, subqueries) are walked too, as the old
+/// `PromqlScalarFromVector` operator child was. Sorted and deduplicated.
+pub fn collect_referenced_columns(tree: &UnresolvedOp) -> Vec<String> {
+    use UnresolvedOp as U;
+    fn named(expr: &UnresolvedScalar, out: &mut Vec<String>) {
+        for c in expr.columns_referenced() {
+            push_ref_name(c, out);
+        }
+        for op in expr.operator_refs() {
+            walk(op, out);
+        }
+    }
+    fn group_keys(g: &GroupKeys<ColumnRef>, out: &mut Vec<String>) {
+        g.keys().iter().for_each(|k| push_ref_name(k, out));
+    }
+    fn measure_cols(measures: &[AggIntent<ColumnRef>], out: &mut Vec<String>) {
+        for m in measures {
+            for c in m.input_cols() {
+                push_ref_name(&c, out);
+            }
+        }
+    }
+    fn walk(node: &UnresolvedOp, out: &mut Vec<String>) {
+        match node {
+            U::Scan { predicates, .. } => {
+                for p in predicates {
+                    named(&p.0, out);
+                }
+            }
+            U::Values { rows, .. } => {
+                for e in rows.iter().flatten() {
+                    named(e, out);
+                }
+            }
+            U::Aggregate {
+                reduction,
+                measures,
+                having,
+                child,
+                ..
+            } => {
+                if let Reduction::Reduce(by) = reduction {
+                    group_keys(by, out);
+                }
+                measure_cols(measures, out);
+                if let Some(h) = having {
+                    named(&h.0, out);
+                }
+                walk(child, out);
+            }
+            U::Dedup { cols, child } => {
+                cols.iter().for_each(|c| push_ref_name(c, out));
+                walk(child, out);
+            }
+            U::PromqlSeriesSample { by, child, .. } => {
+                group_keys(by, out);
+                walk(child, out);
+            }
+            U::Filter { pred, child } => {
+                named(&pred.0, out);
+                walk(child, out);
+            }
+            U::Project { cols, child, .. } => {
+                for item in cols {
+                    named(&item.expr, out);
+                }
+                walk(child, out);
+            }
+            U::Sort {
+                keys,
+                partition_by,
+                child,
+            } => {
+                for k in keys {
+                    named(&k.expr, out);
+                }
+                group_keys(partition_by, out);
+                walk(child, out);
+            }
+            U::Limit {
+                partition_by,
+                child,
+                ..
+            } => {
+                group_keys(partition_by, out);
+                walk(child, out);
+            }
+            U::SQLWindowFunc {
+                args,
+                partition_by,
+                order_by,
+                child,
+                ..
+            } => {
+                for a in args {
+                    named(a, out);
+                }
+                group_keys(partition_by, out);
+                for k in order_by {
+                    named(&k.expr, out);
+                }
+                walk(child, out);
+            }
+            U::PromqlRelabel { value, child, .. } => {
+                named(value, out);
+                walk(child, out);
+            }
+            U::Join {
+                pred, left, right, ..
+            } => {
+                named(&pred.0, out);
+                walk(left, out);
+                walk(right, out);
+            }
+            U::PromqlVectorFromScalar(inner) => named(inner, out),
+            U::PromqlMap { child, .. }
+            | U::PromqlScalarOp { child, .. }
+            | U::PromqlInfoEnrich { child, .. }
+            | U::PromqlSubquery { child, .. }
+            | U::TimeRange { child, .. }
+            | U::TimeShift { child, .. } => walk(child, out),
+            U::Concat {
+                children,
+                discriminator_unique_key,
+            } => {
+                // An own-field `ColumnRef` must be seeded like `Dedup.cols`, or
+                // a discriminator column referenced nowhere else in the tree is
+                // absent from the fallback schema and fails `NotFound` later.
+                if let Some(key) = discriminator_unique_key {
+                    push_ref_name(key.discriminator(), out);
+                    key.inner_key().iter().for_each(|c| push_ref_name(c, out));
+                }
+                children.iter().for_each(|c| walk(c, out));
+            }
+            U::SetOp { left, right, .. } => {
+                walk(left, out);
+                walk(right, out);
+            }
+            U::BinaryOp { lhs, rhs, .. } => {
+                walk(lhs, out);
+                walk(rhs, out);
+            }
+        }
+    }
+    let mut out: Vec<String> = Vec::new();
+    walk(tree, &mut out);
+    out.sort();
+    out.dedup();
+    out
+}
+
+#[cfg(test)]
+mod tests {
+    use std::rc::Rc;
+
+    use asap_types::pre_asap::{AggIntent, Reduction, Source};
+
+    use super::*;
+    use crate::unresolved::UnresolvedSortKey;
+
+    fn src(name: &str) -> UnresolvedOp {
+        UnresolvedOp::Scan {
+            source: Source::TimeSeries {
+                metric: name.into(),
+            },
+            predicates: vec![],
+            schema: None,
+        }
+    }
+
+    // Both correlation inputs seed the usage-derived schema.
+    #[test]
+    fn pearson_corr_inputs_seed_usage_derived_schema() {
+        let tree = UnresolvedOp::Aggregate {
+            reduction: Reduction::by(vec![]),
+            measures: vec![AggIntent::PearsonCorr {
+                left: ColumnRef::Named("x".into()),
+                right: ColumnRef::Named("y".into()),
+            }],
+            output_names: vec![],
+            filters: vec![],
+            having: None,
+            child: Rc::new(src("m")),
+        };
+        assert_eq!(collect_referenced_columns(&tree), vec!["x", "y"]);
+        let schema = SchemaResolver::new().resolve_schema(&tree);
+        assert!(schema.column_id("x").is_some());
+        assert!(schema.column_id("y").is_some());
+    }
+
+    // A bare source gets exactly the (ts, value) floor.
+    #[test]
+    fn bare_source_yields_ts_value_floor() {
+        let schema = SchemaResolver::new().resolve_schema(&src("m"));
+        assert_eq!(schema.fields.len(), 2);
+        assert_eq!(schema.fields[0].name, "ts");
+        assert_eq!(schema.fields[1].name, "value");
+        assert_eq!(schema.time_index, Some(0));
+    }
+
+    // Per-group ranking keys (`topk by (host)` → `Sort.partition_by`) are
+    // seeded into the usage-derived leaf so they resolve positionally.
+    #[test]
+    fn sort_partition_keys_land_in_schema() {
+        let tree = UnresolvedOp::Sort {
+            keys: vec![UnresolvedSortKey {
+                expr: UnresolvedScalar::Column(ColumnRef::SampleValue),
+                ascending: false,
+                nulls_first: false,
+            }],
+            partition_by: GroupKeys::by(vec![ColumnRef::Named("host".into())]),
+            child: Rc::new(src("hits")),
+        };
+        let schema = SchemaResolver::new().resolve_schema(&tree);
+        assert!(schema.column_id("host").is_some());
+    }
+
+    // `Limit.partition_by` (PromQL `topk by (..)`) is seeded like `Sort`'s.
+    #[test]
+    fn limit_partition_keys_land_in_schema() {
+        let tree = UnresolvedOp::Limit {
+            n: Some(3),
+            offset: 0,
+            partition_by: GroupKeys::by(vec![ColumnRef::Named("host".into())]),
+            child: Rc::new(src("hits")),
+        };
+        let schema = SchemaResolver::new().resolve_schema(&tree);
+        assert!(schema.column_id("host").is_some());
+    }
+
+    // A `Concat`'s discriminator key columns, even ones referenced nowhere
+    // else, are seeded like `Dedup.cols` (issue #228 review).
+    #[test]
+    fn concat_discriminator_key_is_seeded_into_the_resolver_schema() {
+        let tree = UnresolvedOp::concat_with_discriminator(
+            vec![src("m")],
+            ColumnRef::Named("phi".into()),
+            vec![ColumnRef::Named("host".into())],
+        );
+        let schema = SchemaResolver::new().resolve_schema(&tree);
+        assert!(schema.column_id("phi").is_some(), "discriminator seeded");
+        assert!(schema.column_id("host").is_some(), "inner_key seeded");
+    }
+
+    // Inherited names are seeded alongside the tree's own references; plain
+    // `resolve_schema` does not conjure them (issue #52).
+    #[test]
+    fn inherited_names_are_seeded_alongside_referenced() {
+        let schema =
+            SchemaResolver::new().resolve_schema_with_inherited(&src("m"), &["__name__".into()]);
+        assert!(schema.column_id("__name__").is_some());
+        let plain = SchemaResolver::new().resolve_schema(&src("m"));
+        assert!(plain.column_id("__name__").is_none());
+    }
+
+    // A catalog-known source supplies its base columns, typed as the catalog says.
+    #[test]
+    fn custom_catalog_supplies_base_columns() {
+        struct FixedCatalog;
+        impl SchemaCatalog for FixedCatalog {
+            fn columns_for(&self, source: &str) -> Option<Vec<Field>> {
+                (source == "known").then(|| {
+                    vec![
+                        Field::plain("ts", DataType::Timestamp, false),
+                        Field::plain("value", DataType::Float64, false),
+                        Field::plain("datacenter", DataType::Utf8, false),
+                    ]
+                })
+            }
+        }
+        let schema = SchemaResolver::with_catalog(FixedCatalog).resolve_schema(&src("known"));
+        let dc = schema
+            .column_id("datacenter")
+            .and_then(|id| schema.fields.get(id));
+        assert!(matches!(dc, Some(c) if !c.nullable));
+    }
+}
diff --git a/crates/frontend-common/src/unresolved.rs b/crates/frontend-common/src/unresolved.rs
new file mode 100644
index 000000000..0bca427cc
--- /dev/null
+++ b/crates/frontend-common/src/unresolved.rs
@@ -0,0 +1,374 @@
+//! The front-end-emitted, name-based operator tree: a mirror of the unified
+//! IR ([`NonASAPOp`](asap_types::ir::NonASAPOp) / [`ScalarExpr`](asap_types::ir::ScalarExpr))
+//! before name resolution.
+//!
+//! Differences from the resolved IR, and nothing else:
+//! - every `ColumnId` is a name-based [`ColumnRef`];
+//! - `Scan.schema` is `Option<Schema>` — a front end knows the schema only for
+//!   a catalog-backed SQL leaf; `None` (PromQL) defers to the
+//!   [`SchemaResolver`](crate::schema_resolver::SchemaResolver);
+//! - children are `Rc<UnresolvedOp>` rather than `Rc<OperatorNode>` — no
+//!   derived schema exists yet.
+
+use std::rc::Rc;
+use std::time::Duration;
+
+use serde::{Deserialize, Serialize};
+
+use asap_types::ir::operator_properties::ConcatDiscriminatorKey;
+use asap_types::ir::BinaryOperator;
+use asap_types::ir::{ExprSemantics, TimeRangeKind};
+use asap_types::pre_asap::{
+    AggIntent, ArithmeticOpKind, ColumnRef, CompareOpKind, DataType, GroupKeys, InfoMatcher,
+    JoinKind, Reduction, RelationalSetOpKind, SampleKind, ScalarValue, Schema, Source, TimeShift,
+    WindowFrame, WindowFuncKind,
+};
+
+/// A row-level filter predicate (WHERE clause / PromQL label matcher).
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+pub struct UnresolvedPredicate(pub UnresolvedScalar);
+
+/// One item in a SELECT projection list.
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+pub struct UnresolvedProjectItem {
+    pub alias: Option<String>,
+    pub expr: UnresolvedScalar,
+}
+
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+pub struct UnresolvedSortKey {
+    pub expr: UnresolvedScalar,
+    pub ascending: bool,
+    pub nulls_first: bool,
+}
+
+/// A name-based scalar expression; see
+/// [`ScalarExpr`](asap_types::ir::ScalarExpr) for the meaning of each variant.
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+pub enum UnresolvedScalar {
+    Column(ColumnRef),
+    Literal(ScalarValue),
+    Negative {
+        expr: Box<UnresolvedScalar>,
+        semantics: ExprSemantics,
+    },
+    Compare {
+        left: Box<UnresolvedScalar>,
+        op: CompareOpKind,
+        right: Box<UnresolvedScalar>,
+        semantics: ExprSemantics,
+    },
+    BoolAnd(Vec<UnresolvedScalar>),
+    BoolOr(Vec<UnresolvedScalar>),
+    Not(Box<UnresolvedScalar>),
+    IsNull(Box<UnresolvedScalar>),
+    IsNotNull(Box<UnresolvedScalar>),
+    Cast {
+        expr: Box<UnresolvedScalar>,
+        to: DataType,
+        try_cast: bool,
+    },
+    InList {
+        expr: Box<UnresolvedScalar>,
+        list: Vec<UnresolvedScalar>,
+        negated: bool,
+    },
+    FunctionCall {
+        name: String,
+        args: Vec<UnresolvedScalar>,
+    },
+    Arithmetic {
+        op: ArithmeticOpKind,
+        left: Box<UnresolvedScalar>,
+        right: Box<UnresolvedScalar>,
+        semantics: ExprSemantics,
+    },
+    Case {
+        operand: Option<Box<UnresolvedScalar>>,
+        branches: Vec<(UnresolvedScalar, UnresolvedScalar)>,
+        else_expr: Option<Box<UnresolvedScalar>>,
+    },
+    CurrentTimestamp,
+    EvalTimestamp,
+    /// PromQL `scalar(v)`. The operator is resolved as a root in its own scope.
+    PromqlScalarFromVector(Rc<UnresolvedOp>),
+    ScalarSubquery(Rc<UnresolvedOp>),
+    Exists {
+        subquery: Rc<UnresolvedOp>,
+        negated: bool,
+    },
+    InSubquery {
+        expr: Box<UnresolvedScalar>,
+        subquery: Rc<UnresolvedOp>,
+        negated: bool,
+    },
+}
+
+/// The name-based operator tree; see [`NonASAPOp`](asap_types::ir::NonASAPOp)
+/// for the meaning of each variant.
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+pub enum UnresolvedOp {
+    Scan {
+        source: Source,
+        predicates: Vec<UnresolvedPredicate>,
+        /// `Some` for a catalog-backed (SQL) leaf; `None` defers to the
+        /// usage-derived schema resolver.
+        schema: Option<Schema>,
+    },
+    Values {
+        rows: Vec<Vec<UnresolvedScalar>>,
+        schema: Schema,
+    },
+    Filter {
+        pred: UnresolvedPredicate,
+        child: Rc<UnresolvedOp>,
+    },
+    Project {
+        cols: Vec<UnresolvedProjectItem>,
+        qualifier: Option<String>,
+        child: Rc<UnresolvedOp>,
+    },
+    Aggregate {
+        reduction: Reduction<ColumnRef>,
+        measures: Vec<AggIntent<ColumnRef>>,
+        output_names: Vec<String>,
+        filters: Vec<Option<UnresolvedPredicate>>,
+        having: Option<UnresolvedPredicate>,
+        child: Rc<UnresolvedOp>,
+    },
+    Join {
+        kind: JoinKind,
+        pred: UnresolvedPredicate,
+        left: Rc<UnresolvedOp>,
+        right: Rc<UnresolvedOp>,
+    },
+    SetOp {
+        kind: RelationalSetOpKind,
+        all: bool,
+        left: Rc<UnresolvedOp>,
+        right: Rc<UnresolvedOp>,
+    },
+    Concat {
+        children: Vec<Rc<UnresolvedOp>>,
+        discriminator_unique_key: Option<ConcatDiscriminatorKey<ColumnRef>>,
+    },
+    Dedup {
+        cols: Vec<ColumnRef>,
+        child: Rc<UnresolvedOp>,
+    },
+    Sort {
+        keys: Vec<UnresolvedSortKey>,
+        partition_by: GroupKeys<ColumnRef>,
+        child: Rc<UnresolvedOp>,
+    },
+    Limit {
+        n: Option<usize>,
+        offset: usize,
+        partition_by: GroupKeys<ColumnRef>,
+        child: Rc<UnresolvedOp>,
+    },
+    BinaryOp {
+        operator: BinaryOperator,
+        return_bool: bool,
+        lhs: Rc<UnresolvedOp>,
+        rhs: Rc<UnresolvedOp>,
+    },
+    SQLWindowFunc {
+        func: WindowFuncKind,
+        args: Vec<UnresolvedScalar>,
+        partition_by: GroupKeys<ColumnRef>,
+        order_by: Vec<UnresolvedSortKey>,
+        frame: Option<WindowFrame>,
+        output_name: String,
+        child: Rc<UnresolvedOp>,
+    },
+    TimeRange {
+        range: Duration,
+        kind: TimeRangeKind,
+        child: Rc<UnresolvedOp>,
+    },
+    TimeShift {
+        shift: TimeShift,
+        child: Rc<UnresolvedOp>,
+    },
+    PromqlVectorFromScalar(UnresolvedScalar),
+    PromqlRelabel {
+        dst: String,
+        value: UnresolvedScalar,
+        child: Rc<UnresolvedOp>,
+    },
+    PromqlInfoEnrich {
+        selector: Vec<InfoMatcher>,
+        child: Rc<UnresolvedOp>,
+    },
+    PromqlSeriesSample {
+        by: GroupKeys<ColumnRef>,
+        kind: SampleKind,
+        child: Rc<UnresolvedOp>,
+    },
+    PromqlSubquery {
+        range: Duration,
+        resolution: Option<Duration>,
+        child: Rc<UnresolvedOp>,
+    },
+    /// Bind the complete vector schema before lowering to Project or Filter.
+    /// Frontend-only expansion to a projection preserving the complete series identity.
+    PromqlMap {
+        child: Rc<UnresolvedOp>,
+        sample: UnresolvedScalar,
+        drop_metric_name: bool,
+    },
+    PromqlScalarOp {
+        child: Rc<UnresolvedOp>,
+        scalar: UnresolvedScalar,
+        op: asap_types::pre_asap::BinaryOpKind,
+        scalar_left: bool,
+        return_bool: bool,
+    },
+}
+
+impl UnresolvedScalar {
+    /// The direct scalar sub-expressions (not the operators this expression
+    /// reads — see [`operator_refs`](Self::operator_refs)).
+    pub fn children(&self) -> Vec<&UnresolvedScalar> {
+        use UnresolvedScalar::*;
+        match self {
+            Column(_)
+            | Literal(_)
+            | CurrentTimestamp
+            | EvalTimestamp
+            | PromqlScalarFromVector(_)
+            | ScalarSubquery(_)
+            | Exists { .. } => vec![],
+            Negative { expr, .. }
+            | Not(expr)
+            | IsNull(expr)
+            | IsNotNull(expr)
+            | Cast { expr, .. }
+            | InSubquery { expr, .. } => vec![expr],
+            Compare { left, right, .. } | Arithmetic { left, right, .. } => vec![left, right],
+            BoolAnd(parts) | BoolOr(parts) => parts.iter().collect(),
+            InList { expr, list, .. } => {
+                let mut v = vec![expr.as_ref()];
+                v.extend(list.iter());
+                v
+            }
+            FunctionCall { args, .. } => args.iter().collect(),
+            Case {
+                operand,
+                branches,
+                else_expr,
+            } => {
+                let mut v = Vec::new();
+                if let Some(op) = operand {
+                    v.push(op.as_ref());
+                }
+                for (when, then) in branches {
+                    v.push(when);
+                    v.push(then);
+                }
+                if let Some(e) = else_expr {
+                    v.push(e.as_ref());
+                }
+                v
+            }
+        }
+    }
+
+    /// Every column referenced in this expression, not inside the operators
+    /// it reads (those have their own scope).
+    pub fn columns_referenced(&self) -> Vec<&ColumnRef> {
+        let mut out = Vec::new();
+        self.collect_columns(&mut out);
+        out
+    }
+
+    fn collect_columns<'a>(&'a self, out: &mut Vec<&'a ColumnRef>) {
+        if let UnresolvedScalar::Column(c) = self {
+            out.push(c);
+        }
+        for child in self.children() {
+            child.collect_columns(out);
+        }
+    }
+
+    /// The operators this expression (transitively) reads.
+    pub fn operator_refs(&self) -> Vec<&Rc<UnresolvedOp>> {
+        let mut out = Vec::new();
+        self.collect_operator_refs(&mut out);
+        out
+    }
+
+    fn collect_operator_refs<'a>(&'a self, out: &mut Vec<&'a Rc<UnresolvedOp>>) {
+        use UnresolvedScalar::*;
+        match self {
+            PromqlScalarFromVector(op) | ScalarSubquery(op) => out.push(op),
+            Exists { subquery, .. } | InSubquery { subquery, .. } => out.push(subquery),
+            _ => {}
+        }
+        for child in self.children() {
+            child.collect_operator_refs(out);
+        }
+    }
+}
+
+impl UnresolvedOp {
+    /// An ordinary `Concat` (no unique-key claim).
+    pub fn concat(children: Vec<UnresolvedOp>) -> Self {
+        UnresolvedOp::Concat {
+            children: children.into_iter().map(Rc::new).collect(),
+            discriminator_unique_key: None,
+        }
+    }
+
+    /// A `Concat` whose output carries the caller-proven compound unique key
+    /// `(discriminator, inner_key)`. Nothing verifies the claim.
+    pub fn concat_with_discriminator(
+        children: Vec<UnresolvedOp>,
+        discriminator: ColumnRef,
+        inner_key: Vec<ColumnRef>,
+    ) -> Self {
+        UnresolvedOp::Concat {
+            children: children.into_iter().map(Rc::new).collect(),
+            discriminator_unique_key: Some(ConcatDiscriminatorKey::new(discriminator, inner_key)),
+        }
+    }
+
+    /// Every scalar expression this operator owns.
+    pub fn scalar_exprs(&self) -> Vec<&UnresolvedScalar> {
+        use UnresolvedOp::*;
+        match self {
+            Scan { predicates, .. } => predicates.iter().map(|p| &p.0).collect(),
+            Values { rows, .. } => rows.iter().flatten().collect(),
+            Filter { pred, .. } | Join { pred, .. } => vec![&pred.0],
+            Project { cols, .. } => cols.iter().map(|c| &c.expr).collect(),
+            Aggregate {
+                filters, having, ..
+            } => filters
+                .iter()
+                .flatten()
+                .chain(having.iter())
+                .map(|p| &p.0)
+                .collect(),
+            Sort { keys, .. } => keys.iter().map(|k| &k.expr).collect(),
+            SQLWindowFunc { args, order_by, .. } => args
+                .iter()
+                .chain(order_by.iter().map(|k| &k.expr))
+                .collect(),
+            PromqlVectorFromScalar(e) => vec![e],
+            PromqlScalarOp { scalar, .. } => vec![scalar],
+            PromqlMap { sample, .. } => vec![sample],
+            PromqlRelabel { value, .. } => vec![value],
+            SetOp { .. }
+            | Concat { .. }
+            | Dedup { .. }
+            | Limit { .. }
+            | BinaryOp { .. }
+            | TimeRange { .. }
+            | TimeShift { .. }
+            | PromqlInfoEnrich { .. }
+            | PromqlSeriesSample { .. }
+            | PromqlSubquery { .. } => vec![],
+        }
+    }
+}
diff --git a/crates/frontend-sql/Cargo.toml b/crates/frontend-sql/Cargo.toml
index 102e222e5..3f81f1104 100644
--- a/crates/frontend-sql/Cargo.toml
+++ b/crates/frontend-sql/Cargo.toml
@@ -9,6 +9,7 @@ edition = "2021"
 # #225) it consults when lowering an aggregate call — never promql-parser.
 [dependencies]
 asap-types = { path = "../types" }
+asap-frontend-common = { path = "../frontend-common" }
 asap-sql-function-catalog = { path = "../sql-function-catalog" }
 datafusion = "54"
 # `AggIntent::Extension.payload` for ClickHouse's argMax/argMin (issue #232)
diff --git a/crates/frontend-sql/src/lib.rs b/crates/frontend-sql/src/lib.rs
index 4ec61e69d..aa1449e5e 100644
--- a/crates/frontend-sql/src/lib.rs
+++ b/crates/frontend-sql/src/lib.rs
@@ -102,3 +102,6 @@ pub async fn lower_sql_batch(
     }
     results
 }
+
+/// Unified SQL lowering; promoted to the root API at the planner cutover.
+pub mod unified;
diff --git a/crates/frontend-sql/src/unified/error.rs b/crates/frontend-sql/src/unified/error.rs
new file mode 100644
index 000000000..f819cfd46
--- /dev/null
+++ b/crates/frontend-sql/src/unified/error.rs
@@ -0,0 +1,63 @@
+use std::fmt;
+
+use asap_frontend_common::ResolveDAGError;
+
+/// Errors from lowering a SQL query (parse + plan via DataFusion → the
+/// name-based [`UnresolvedOp`](asap_frontend_common::UnresolvedOp) tree →
+/// [`resolve_root`](asap_frontend_common::resolve_root) binds it into the
+/// unified IR).
+///
+/// Carries no PromQL type — the SQL front end never depends on the PromQL
+/// parser. The language-neutral variants (`UnsupportedFeature` / `WrongLanguage`
+/// / `Convert`) are mirrored by [`asap_frontend_promql::PromqlError`] rather
+/// than shared, so neither front end pulls the other's parser.
+#[derive(Debug)]
+pub enum SqlError {
+    /// DataFusion failed to parse / plan the SQL query.
+    DataFusion(datafusion::error::DataFusionError),
+    /// A table referenced by the query is absent from the catalog.
+    TableNotFound(String),
+    /// A SQL aggregate function not supported in this version.
+    UnsupportedAggregate(String),
+    /// A SQL scalar expression that could not be lowered.
+    InvalidExpression(String),
+    /// The SQL dialect is not supported (only DataFusionSQL is implemented).
+    UnsupportedDialect(String),
+    /// A structural feature (JOIN type / subquery / derived table) not
+    /// supported in this version.
+    UnsupportedFeature(String),
+    /// The workload's query language is not SQL.
+    WrongLanguage(String),
+    /// Resolving the name-based tree failed (name resolution against the
+    /// bound schema, or schema derivation).
+    Convert(ResolveDAGError),
+}
+
+impl fmt::Display for SqlError {
+    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
+        match self {
+            Self::DataFusion(e) => write!(f, "DataFusion error: {e}"),
+            Self::TableNotFound(t) => write!(f, "table not found in catalog: {t}"),
+            Self::UnsupportedAggregate(n) => write!(f, "unsupported aggregate: {n}"),
+            Self::InvalidExpression(m) => write!(f, "invalid expression: {m}"),
+            Self::UnsupportedDialect(d) => write!(f, "unsupported SQL dialect: {d}"),
+            Self::UnsupportedFeature(m) => write!(f, "unsupported feature: {m}"),
+            Self::WrongLanguage(l) => write!(f, "unsupported query language: {l}"),
+            Self::Convert(e) => write!(f, "column resolution failed: {e}"),
+        }
+    }
+}
+
+impl std::error::Error for SqlError {}
+
+impl From<ResolveDAGError> for SqlError {
+    fn from(e: ResolveDAGError) -> Self {
+        Self::Convert(e)
+    }
+}
+
+impl From<datafusion::error::DataFusionError> for SqlError {
+    fn from(e: datafusion::error::DataFusionError) -> Self {
+        Self::DataFusion(e)
+    }
+}
diff --git a/crates/frontend-sql/src/unified/mod.rs b/crates/frontend-sql/src/unified/mod.rs
new file mode 100644
index 000000000..279585fb9
--- /dev/null
+++ b/crates/frontend-sql/src/unified/mod.rs
@@ -0,0 +1,103 @@
+//! SQL front end: parse + plan (via DataFusion) → the name-based
+//! [`UnresolvedOp`](asap_frontend_common::UnresolvedOp) tree, built directly
+//! (issue #179) → [`resolve_root`].
+//!
+//! Emits the shared front-end tree (`UnresolvedOp` / `UnresolvedScalar`,
+//! name-based [`ColumnRef`](asap_types::pre_asap::ColumnRef)s) directly, rather
+//! than a separate per-language relational tree; `resolve_root` binds it into
+//! the unified [`OperatorNode`] IR, deriving every schema on the way.
+//! Depends on DataFusion only — never on the PromQL parser.
+
+pub mod error;
+pub mod sql;
+
+use std::rc::Rc;
+
+use asap_frontend_common::resolve_root;
+use asap_types::ir::OperatorNode;
+use asap_types::types::AccuracyTarget;
+use asap_types::workload::{QueryLanguage, QueryWorkload, SqlDialect};
+
+pub use error::SqlError;
+pub use sql::{SqlCatalog, SqlLowerer};
+
+/// Lower a single SQL query string to the resolved, canonical operator DAG,
+/// parsed as `SqlDialect::DataFusionSQL`.
+///
+/// The `catalog` supplies table schemas (used both to plan the SQL with
+/// DataFusion and to carry positional column identity into the resolved
+/// tree). `accuracy` is threaded onto every approximate intent as it's built.
+pub async fn lower_sql(
+    query: &str,
+    catalog: &SqlCatalog,
+    accuracy: AccuracyTarget,
+) -> Result<Rc<OperatorNode>, SqlError> {
+    lower_sql_dialect(query, catalog, SqlDialect::DataFusionSQL, accuracy).await
+}
+
+/// Lower a single SQL query string under an explicit [`SqlDialect`].
+///
+/// `ClickhouseSQL` parses via sqlparser's vendored `ClickHouseDialect`
+/// (array-lambda syntax, `arr[-1]` indexing). It also teaches DataFusion's
+/// planner the ClickHouse-only builtin functions listed in
+/// `asap_sql_function_catalog::CLICKHOUSE_BUILTINS` (`uniqExact`, `countIf`)
+/// — every other ClickHouse-only builtin still fails to plan.
+/// `ElasticSQL` has no vendored parser and always returns `UnsupportedDialect`.
+pub async fn lower_sql_dialect(
+    query: &str,
+    catalog: &SqlCatalog,
+    dialect: SqlDialect,
+    accuracy: AccuracyTarget,
+) -> Result<Rc<OperatorNode>, SqlError> {
+    let unresolved = SqlLowerer::with_dialect(catalog, dialect)
+        .lower(query, &accuracy)
+        .await?;
+    // Binding resolves names and derives every node's schema; result-type
+    // checks (such as temporal subtraction, whose duration unit the IR cannot
+    // represent) surface here as `ResolveDAGError::Schema`.
+    Ok(resolve_root(&unresolved)?)
+}
+
+/// Lower every SQL batch entry in `workload` to an operator DAG.
+///
+/// One `Result` per entry — errors are per-query, not fatal for the batch.
+/// Returns `WrongLanguage` for every entry if the workload is not SQL, and
+/// `UnsupportedDialect` for `ElasticSQL` (no vendored parser).
+pub async fn lower_sql_batch(
+    workload: &QueryWorkload,
+    catalog: &SqlCatalog,
+) -> Vec<Result<Rc<OperatorNode>, SqlError>> {
+    let entries = match &workload.query_batch {
+        Some(e) if !e.is_empty() => e,
+        _ => return vec![],
+    };
+
+    // `DataFusion` is a legacy alias for `SQL(DataFusionSQL)`; accept both.
+    if !matches!(
+        workload.language,
+        QueryLanguage::SQL(_) | QueryLanguage::DataFusion
+    ) {
+        let lang = format!("{:?}", workload.language);
+        return entries
+            .iter()
+            .map(|_| Err(SqlError::WrongLanguage(lang.clone())))
+            .collect();
+    }
+    let dialect = match &workload.language {
+        QueryLanguage::SQL(d) => d.clone(),
+        _ => SqlDialect::DataFusionSQL,
+    };
+    if matches!(dialect, SqlDialect::ElasticSQL) {
+        return entries
+            .iter()
+            .map(|_| Err(SqlError::UnsupportedDialect("ElasticSQL".into())))
+            .collect();
+    }
+
+    let mut results = Vec::with_capacity(entries.len());
+    for entry in entries {
+        let accuracy = entry.requirements.accuracy.target();
+        results.push(lower_sql_dialect(&entry.query.0, catalog, dialect.clone(), accuracy).await);
+    }
+    results
+}
diff --git a/crates/frontend-sql/src/unified/sql/clickhouse_ast.rs b/crates/frontend-sql/src/unified/sql/clickhouse_ast.rs
new file mode 100644
index 000000000..c68a803be
--- /dev/null
+++ b/crates/frontend-sql/src/unified/sql/clickhouse_ast.rs
@@ -0,0 +1,139 @@
+//! Structural ClickHouse syntax normalization before DataFusion type inference.
+use datafusion::sql::sqlparser::ast::{
+    visit_expressions, visit_expressions_mut, BinaryOperator, Expr, Function, FunctionArg,
+    FunctionArgExpr, FunctionArgumentList, FunctionArguments, Ident, MapAccessSyntax, ObjectName,
+    Query, SelectItem, SetExpr, Statement, VisitMut, VisitorMut,
+};
+use std::ops::ControlFlow;
+
+pub(super) fn normalize(statement: &mut Statement) {
+    struct PreserveNames;
+    impl VisitorMut for PreserveNames {
+        type Break = ();
+        fn pre_visit_query(&mut self, query: &mut Query) -> ControlFlow<()> {
+            fn preserve(body: &mut SetExpr) {
+                match body {
+                    SetExpr::Select(select) => {
+                        for item in &mut select.projection {
+                            if let SelectItem::UnnamedExpr(expr) = item {
+                                let mut changed = false;
+                                let _: ControlFlow<()> = visit_expressions_mut(expr, |node| {
+                                    changed |= normalize_map_access(node);
+                                    ControlFlow::Continue(())
+                                });
+                                let _: ControlFlow<()> = visit_expressions(expr, |candidate| {
+                                    if let Expr::Function(function) = candidate {
+                                        changed |= function.name.0.len() == 1
+                                            && function.name.0[0].quote_style.is_none()
+                                            && matches!(
+                                                function.name.0[0]
+                                                    .value
+                                                    .to_ascii_lowercase()
+                                                    .as_str(),
+                                                "modulo"
+                                                    | "map"
+                                                    | "mapconcat"
+                                                    | "arrayelement"
+                                                    | "tupleelement"
+                                            );
+                                    }
+                                    ControlFlow::Continue(())
+                                });
+                                if changed {
+                                    let alias = Ident::with_quote('"', expr.to_string());
+                                    let value = std::mem::replace(
+                                        expr,
+                                        Expr::Value(datafusion::sql::sqlparser::ast::Value::Null),
+                                    );
+                                    *item = SelectItem::ExprWithAlias { expr: value, alias };
+                                }
+                            }
+                        }
+                    }
+                    SetExpr::SetOperation { left, right, .. } => {
+                        preserve(left);
+                        preserve(right);
+                    }
+                    _ => {}
+                }
+            }
+            preserve(&mut query.body);
+            ControlFlow::Continue(())
+        }
+    }
+    let _: ControlFlow<()> = statement.visit(&mut PreserveNames);
+    let _: ControlFlow<()> = visit_expressions_mut(statement, |expr| {
+        normalize_map_access(expr);
+        let Expr::Function(function) = expr else {
+            return ControlFlow::Continue(());
+        };
+        if function.name.0.len() != 1
+            || function.name.0[0].quote_style.is_some()
+            || !function.name.0[0].value.eq_ignore_ascii_case("modulo")
+            || !matches!(function.parameters, FunctionArguments::None)
+            || function.filter.is_some()
+            || function.over.is_some()
+            || function.null_treatment.is_some()
+            || !function.within_group.is_empty()
+        {
+            return ControlFlow::Continue(());
+        }
+        let FunctionArguments::List(arguments) = &function.args else {
+            return ControlFlow::Continue(());
+        };
+        if arguments.duplicate_treatment.is_some() || !arguments.clauses.is_empty() {
+            return ControlFlow::Continue(());
+        }
+        let [FunctionArg::Unnamed(FunctionArgExpr::Expr(left)), FunctionArg::Unnamed(FunctionArgExpr::Expr(right))] =
+            arguments.args.as_slice()
+        else {
+            return ControlFlow::Continue(());
+        };
+        *expr = Expr::BinaryOp {
+            left: Box::new(left.clone()),
+            op: BinaryOperator::Modulo,
+            right: Box::new(right.clone()),
+        };
+        ControlFlow::Continue(())
+    });
+}
+
+fn normalize_map_access(expression: &mut Expr) -> bool {
+    let Expr::MapAccess { keys, .. } = expression else {
+        return false;
+    };
+    if keys.is_empty()
+        || keys
+            .iter()
+            .any(|key| key.syntax != MapAccessSyntax::Bracket)
+    {
+        return false;
+    }
+    let Expr::MapAccess { column, keys } = std::mem::replace(
+        expression,
+        Expr::Value(datafusion::sql::sqlparser::ast::Value::Null),
+    ) else {
+        unreachable!()
+    };
+    let mut input = *column;
+    for key in keys {
+        input = Expr::Function(Function {
+            name: ObjectName(vec![Ident::new("arrayElement")]),
+            parameters: FunctionArguments::None,
+            args: FunctionArguments::List(FunctionArgumentList {
+                duplicate_treatment: None,
+                clauses: vec![],
+                args: vec![
+                    FunctionArg::Unnamed(FunctionArgExpr::Expr(input)),
+                    FunctionArg::Unnamed(FunctionArgExpr::Expr(key.key)),
+                ],
+            }),
+            filter: None,
+            null_treatment: None,
+            over: None,
+            within_group: vec![],
+        });
+    }
+    *expression = input;
+    true
+}
diff --git a/crates/frontend-sql/src/unified/sql/collection_planning.rs b/crates/frontend-sql/src/unified/sql/collection_planning.rs
new file mode 100644
index 000000000..75d0450cc
--- /dev/null
+++ b/crates/frontend-sql/src/unified/sql/collection_planning.rs
@@ -0,0 +1,189 @@
+//! DataFusion planning adapters. Types come from the canonical signature rules;
+//! physical evaluation deliberately remains the query engine's responsibility.
+use super::types::{arrow_to_dtype, dtype_to_arrow, scalar_value_to_asap};
+use asap_types::ir::scalar::{element_access_type, struct_field_type};
+use asap_types::ir::ScalarExpr;
+use asap_types::pre_asap::scalar_type_rules::MapScalarFunction;
+use asap_types::pre_asap::{Field, Schema};
+use datafusion::arrow::datatypes::DataType;
+use datafusion::common::{DataFusionError, ExprSchema, Result};
+use datafusion::logical_expr::{
+    ColumnarValue, Expr, ExprSchemable, ScalarUDF, ScalarUDFImpl, Signature, TypeSignature,
+    Volatility,
+};
+use datafusion::prelude::SessionContext;
+
+#[derive(Debug, Clone, Copy)]
+enum PlanningFunction {
+    Map(MapScalarFunction),
+    Element,
+    StructField,
+}
+
+pub(super) fn register(context: &SessionContext) {
+    for (name, function) in [
+        ("map", PlanningFunction::Map(MapScalarFunction::Construct)),
+        (
+            "mapconcat",
+            PlanningFunction::Map(MapScalarFunction::Concat),
+        ),
+        ("arrayelement", PlanningFunction::Element),
+        ("tupleelement", PlanningFunction::StructField),
+    ] {
+        context.register_udf(ScalarUDF::from(CollectionPlanningFunction {
+            name,
+            function,
+            signature: match function {
+                PlanningFunction::Map(MapScalarFunction::Construct) => Signature::one_of(
+                    vec![TypeSignature::Exact(vec![]), TypeSignature::VariadicAny],
+                    Volatility::Immutable,
+                ),
+                PlanningFunction::Map(MapScalarFunction::Access)
+                | PlanningFunction::Element
+                | PlanningFunction::StructField => Signature::any(2, Volatility::Immutable),
+                PlanningFunction::Map(MapScalarFunction::Concat) => {
+                    Signature::variadic_any(Volatility::Immutable)
+                }
+            },
+        }));
+    }
+}
+#[derive(Debug)]
+struct CollectionPlanningFunction {
+    name: &'static str,
+    function: PlanningFunction,
+    signature: Signature,
+}
+impl CollectionPlanningFunction {
+    fn output(
+        &self,
+        args: &[DataType],
+        nullable: &[bool],
+        expressions: Option<&[Expr]>,
+    ) -> Result<(DataType, bool)> {
+        let inputs = args
+            .iter()
+            .zip(nullable)
+            .map(|(dtype, null)| {
+                arrow_to_dtype(dtype)
+                    .map(|dtype| (dtype, *null))
+                    .map_err(|e| DataFusionError::Plan(e.to_string()))
+            })
+            .collect::<Result<Vec<_>>>()?;
+        let (dtype, nullable) = if matches!(
+            self.function,
+            PlanningFunction::Element | PlanningFunction::StructField
+        ) {
+            // DataFusion asks for argument-dependent types before canonical
+            // expression binding. Reuse the shared resolver over typed argument
+            // slots; final canonical binding also validates literal selectors.
+            let schema = Schema::new(
+                inputs
+                    .into_iter()
+                    .enumerate()
+                    .map(|(index, (dtype, nullable))| {
+                        Field::plain(format!("argument_{index}"), dtype, nullable)
+                    })
+                    .collect(),
+            );
+            let args = (0..schema.fields.len())
+                .map(|index| {
+                    if let Some(Expr::Literal(value)) = expressions.and_then(|args| args.get(index))
+                    {
+                        scalar_value_to_asap(value)
+                            .map(ScalarExpr::Literal)
+                            .map_err(|error| DataFusionError::Plan(error.to_string()))
+                    } else {
+                        Ok(ScalarExpr::Column(index))
+                    }
+                })
+                .collect::<Result<Vec<_>>>()?;
+            match self.function {
+                PlanningFunction::Element => element_access_type(&args, &schema),
+                PlanningFunction::StructField => struct_field_type(&args, &schema),
+                PlanningFunction::Map(_) => unreachable!(),
+            }
+        } else if let PlanningFunction::Map(function) = self.function {
+            function.output_type(&inputs)
+        } else {
+            unreachable!()
+        }
+        .map_err(DataFusionError::Plan)?;
+        Ok((dtype_to_arrow(&dtype), nullable))
+    }
+}
+impl ScalarUDFImpl for CollectionPlanningFunction {
+    fn as_any(&self) -> &dyn std::any::Any {
+        self
+    }
+    fn name(&self) -> &str {
+        self.name
+    }
+    fn signature(&self) -> &Signature {
+        &self.signature
+    }
+    fn return_type(&self, args: &[DataType]) -> Result<DataType> {
+        self.output(
+            args,
+            &args
+                .iter()
+                .map(|dtype| *dtype == DataType::Null)
+                .collect::<Vec<_>>(),
+            None,
+        )
+        .map(|output| output.0)
+    }
+    fn return_type_from_exprs(
+        &self,
+        args: &[Expr],
+        schema: &dyn ExprSchema,
+        types: &[DataType],
+    ) -> Result<DataType> {
+        let nullable = args
+            .iter()
+            .map(|arg| arg.nullable(schema))
+            .collect::<Result<Vec<_>>>()?;
+        self.output(types, &nullable, Some(args))
+            .map(|output| output.0)
+    }
+    fn is_nullable(&self, args: &[Expr], schema: &dyn ExprSchema) -> bool {
+        let types = args
+            .iter()
+            .map(|arg| arg.get_type(schema))
+            .collect::<Result<Vec<_>>>();
+        let nullable = args
+            .iter()
+            .map(|arg| arg.nullable(schema))
+            .collect::<Result<Vec<_>>>();
+        match (types, nullable) {
+            (Ok(types), Ok(nullable)) => self
+                .output(&types, &nullable, Some(args))
+                .map(|out| out.1)
+                .unwrap_or(true),
+            _ => true,
+        }
+    }
+    fn invoke_batch(&self, _args: &[ColumnarValue], _number_rows: usize) -> Result<ColumnarValue> {
+        Err(DataFusionError::NotImplemented("collection planning adapter cannot execute; use a capable query engine or external exact sub_dag".into()))
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    #[test]
+    fn planning_adapter_explicitly_refuses_physical_execution() {
+        let adapter = CollectionPlanningFunction {
+            name: "map",
+            function: PlanningFunction::Map(MapScalarFunction::Construct),
+            signature: Signature::any(0, Volatility::Immutable),
+        };
+        assert!(matches!(
+            adapter.invoke_batch(&[], 1),
+            Err(DataFusionError::NotImplemented(_))
+        ));
+        let result = adapter.return_type(&[]).unwrap();
+        let (expected, _) = MapScalarFunction::Construct.output_type(&[]).unwrap();
+        assert_eq!(result, dtype_to_arrow(&expected));
+    }
+}
diff --git a/crates/frontend-sql/src/unified/sql/dialect.rs b/crates/frontend-sql/src/unified/sql/dialect.rs
new file mode 100644
index 000000000..03d9253e0
--- /dev/null
+++ b/crates/frontend-sql/src/unified/sql/dialect.rs
@@ -0,0 +1,112 @@
+//! The parser dialect for `SqlDialect::DataFusionSQL`.
+//!
+//! sqlparser's `GenericDialect` leaves `FILTER (WHERE …)` on aggregate calls
+//! off (`supports_filter_during_aggregation`), and DataFusion only selects a
+//! dialect by name — so `count(x) FILTER (WHERE p)` cannot reach the planner
+//! through `SessionContext::sql`. This wrapper is `GenericDialect` with that
+//! one switch flipped (issue #466); `lower` parses through
+//! `DFParser::parse_sql_with_dialect` with it and plans the statement itself,
+//! exactly as the ClickHouse path already does.
+
+use std::any::TypeId;
+
+use datafusion::sql::sqlparser::dialect::{Dialect, GenericDialect};
+
+#[derive(Debug, Default)]
+pub(crate) struct GenericWithAggregateFilter;
+
+/// Forward every boolean switch `GenericDialect` overrides, so the only
+/// behavioural difference is `supports_filter_during_aggregation`.
+macro_rules! forward_to_generic {
+    ($($method:ident),* $(,)?) => {
+        $(fn $method(&self) -> bool {
+            GenericDialect.$method()
+        })*
+    };
+}
+
+impl Dialect for GenericWithAggregateFilter {
+    /// The parser's own `dialect_of!(… is GenericDialect)` checks keep
+    /// matching, so generic-only syntax paths stay enabled.
+    fn dialect(&self) -> TypeId {
+        GenericDialect.dialect()
+    }
+
+    fn is_delimited_identifier_start(&self, ch: char) -> bool {
+        GenericDialect.is_delimited_identifier_start(ch)
+    }
+
+    fn is_identifier_start(&self, ch: char) -> bool {
+        GenericDialect.is_identifier_start(ch)
+    }
+
+    fn is_identifier_part(&self, ch: char) -> bool {
+        GenericDialect.is_identifier_part(ch)
+    }
+
+    fn supports_filter_during_aggregation(&self) -> bool {
+        true
+    }
+
+    forward_to_generic!(
+        supports_unicode_string_literal,
+        supports_group_by_expr,
+        supports_connect_by,
+        supports_match_recognize,
+        supports_start_transaction_modifier,
+        supports_window_function_null_treatment_arg,
+        supports_dictionary_syntax,
+        supports_window_clause_named_window_reference,
+        supports_parenthesized_set_variables,
+        supports_select_wildcard_except,
+        support_map_literal_syntax,
+        allow_extract_custom,
+        allow_extract_single_quotes,
+        supports_create_index_with_clause,
+    );
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use datafusion::sql::parser::DFParser;
+
+    // Every switch `GenericDialect` sets is mirrored, and only the aggregate
+    // FILTER switch differs.
+    #[test]
+    fn mirrors_generic_except_for_aggregate_filter() {
+        let ours = GenericWithAggregateFilter;
+        let generic = GenericDialect;
+        assert_eq!(ours.dialect(), generic.dialect());
+        for ch in ['"', '`', '_', '#', '@', '$', 'a', '1', ' '] {
+            assert_eq!(
+                ours.is_delimited_identifier_start(ch),
+                generic.is_delimited_identifier_start(ch)
+            );
+            assert_eq!(
+                ours.is_identifier_start(ch),
+                generic.is_identifier_start(ch)
+            );
+            assert_eq!(ours.is_identifier_part(ch), generic.is_identifier_part(ch));
+        }
+        assert_eq!(
+            ours.supports_group_by_expr(),
+            generic.supports_group_by_expr()
+        );
+        assert!(!generic.supports_filter_during_aggregation());
+        assert!(ours.supports_filter_during_aggregation());
+    }
+
+    // The generic dialect rejects an aggregate FILTER clause; ours parses it.
+    #[test]
+    fn parses_aggregate_filter_clause() {
+        let sql = "SELECT count(*) FILTER (WHERE a > 1) FROM t";
+        assert!(DFParser::parse_sql_with_dialect(sql, &GenericDialect).is_err());
+        assert_eq!(
+            DFParser::parse_sql_with_dialect(sql, &GenericWithAggregateFilter)
+                .unwrap()
+                .len(),
+            1
+        );
+    }
+}
diff --git a/crates/frontend-sql/src/unified/sql/expr.rs b/crates/frontend-sql/src/unified/sql/expr.rs
new file mode 100644
index 000000000..b726bfc12
--- /dev/null
+++ b/crates/frontend-sql/src/unified/sql/expr.rs
@@ -0,0 +1,354 @@
+use std::rc::Rc;
+
+use datafusion::logical_expr::{BinaryExpr, Expr, Operator};
+
+use asap_frontend_common::UnresolvedScalar as Unresolved;
+use asap_types::ir::ExprSemantics;
+use asap_types::pre_asap::{ArithmeticOpKind, ColumnRef, CompareOpKind, ScalarValue};
+
+use crate::unified::error::SqlError as LoweringError;
+
+use super::types::{arrow_to_dtype, scalar_value_to_asap};
+use super::SqlLowerer;
+
+pub(super) fn split_conjuncts(expr: &Expr) -> Vec<&Expr> {
+    match expr {
+        Expr::BinaryExpr(BinaryExpr {
+            left,
+            op: Operator::And,
+            right,
+        }) => {
+            let mut v = split_conjuncts(left);
+            v.extend(split_conjuncts(right));
+            v
+        }
+        _ => vec![expr],
+    }
+}
+
+impl SqlLowerer<'_> {
+    /// Translate a DataFusion `Expr` to the name-based scalar tree. Every
+    /// `Compare` / `Arithmetic` / `Negative` carries `ExprSemantics::Sql`.
+    /// Subquery-valued expressions lower their plan as a root of its own
+    /// (which is why this is a method: the plan walk needs the catalog).
+    /// Returns `UnsupportedFeature` for anything not needed in v1.
+    pub(super) fn lower_expr(&self, expr: &Expr) -> Result<Unresolved, LoweringError> {
+        let bx = |e: &Expr| self.lower_expr(e).map(Box::new);
+        match expr {
+            // Preserve DataFusion's relation qualifier so a column name shared
+            // across a join (`a.k` vs `b.k`) resolves to the correct side.
+            Expr::Column(col) => Ok(Unresolved::Column(match &col.relation {
+                Some(rel) => ColumnRef::Qualified {
+                    table: rel.to_string(),
+                    name: col.name.clone(),
+                },
+                None => ColumnRef::Named(col.name.clone()),
+            })),
+
+            // Keep Arrow date literals equivalent to SQL CAST('YYYY-MM-DD' AS DATE),
+            // including typed nulls, without adding another canonical scalar variant.
+            Expr::Literal(
+                sv @ (datafusion::common::ScalarValue::Date32(_)
+                | datafusion::common::ScalarValue::Date64(_)),
+            ) => {
+                let text = sv.cast_to(&datafusion::arrow::datatypes::DataType::Utf8)?;
+                // Arrow formats Date64 with a time suffix; the canonical Date has
+                // no time-of-day, just like Date64 catalog registration as Date32.
+                let text = match text {
+                    datafusion::common::ScalarValue::Utf8(Some(value)) => {
+                        ScalarValue::Utf8(value.split('T').next().unwrap().to_owned())
+                    }
+                    other => scalar_value_to_asap(&other)?,
+                };
+                Ok(Unresolved::Cast {
+                    expr: Box::new(Unresolved::Literal(text)),
+                    to: asap_types::pre_asap::schema::DataType::Date,
+                    try_cast: false,
+                })
+            }
+            Expr::Literal(sv) => scalar_value_to_asap(sv).map(Unresolved::Literal),
+
+            Expr::Alias(a) => self.lower_expr(&a.expr),
+
+            Expr::BinaryExpr(BinaryExpr { left, op, right }) => match op {
+                Operator::And => {
+                    let parts = split_conjuncts(expr);
+                    let lowered: Result<Vec<_>, _> =
+                        parts.iter().map(|e| self.lower_expr(e)).collect();
+                    Ok(Unresolved::BoolAnd(lowered?))
+                }
+                Operator::Or => {
+                    let parts = split_disjuncts(expr);
+                    let lowered: Result<Vec<_>, _> =
+                        parts.iter().map(|e| self.lower_expr(e)).collect();
+                    Ok(Unresolved::BoolOr(lowered?))
+                }
+                Operator::Eq => self.compare(left, CompareOpKind::Eq, right),
+                Operator::NotEq => self.compare(left, CompareOpKind::Ne, right),
+                Operator::Lt => self.compare(left, CompareOpKind::Lt, right),
+                Operator::LtEq => self.compare(left, CompareOpKind::Le, right),
+                Operator::Gt => self.compare(left, CompareOpKind::Gt, right),
+                Operator::GtEq => self.compare(left, CompareOpKind::Ge, right),
+                // BinaryExpr LIKE/ILIKE operators (from optimizer rewrites)
+                Operator::LikeMatch => self.compare(left, CompareOpKind::Like, right),
+                Operator::ILikeMatch => self.compare(left, CompareOpKind::ILike, right),
+                Operator::NotLikeMatch => self.compare(left, CompareOpKind::NotLike, right),
+                Operator::NotILikeMatch => self.compare(left, CompareOpKind::NotILike, right),
+                // Arithmetic
+                Operator::Plus => self.arith(left, ArithmeticOpKind::Add, right),
+                Operator::Minus => self.arith(left, ArithmeticOpKind::Sub, right),
+                Operator::Multiply => self.arith(left, ArithmeticOpKind::Mul, right),
+                Operator::Divide => self.arith(left, ArithmeticOpKind::Div, right),
+                Operator::Modulo => self.arith(left, ArithmeticOpKind::Mod, right),
+                other => Err(LoweringError::UnsupportedFeature(format!(
+                    "operator: {other:?}"
+                ))),
+            },
+
+            // SQL LIKE / ILIKE (dedicated expr node from the SQL parser)
+            Expr::Like(like) => {
+                let op = match (like.negated, like.case_insensitive) {
+                    (false, false) => CompareOpKind::Like,
+                    (true, false) => CompareOpKind::NotLike,
+                    (false, true) => CompareOpKind::ILike,
+                    (true, true) => CompareOpKind::NotILike,
+                };
+                self.compare(&like.expr, op, &like.pattern)
+            }
+
+            // Unary minus. (DataFusion's planner already folds `-<number>`
+            // into a negative literal, so this is a non-literal operand.)
+            Expr::Negative(inner) => Ok(Unresolved::Negative {
+                expr: bx(inner)?,
+                semantics: ExprSemantics::Sql,
+            }),
+
+            // SQL CASE expression
+            Expr::Case(c) => {
+                let operand = c.expr.as_deref().map(bx).transpose()?;
+                let branches = c
+                    .when_then_expr
+                    .iter()
+                    .map(|(when, then)| Ok((self.lower_expr(when)?, self.lower_expr(then)?)))
+                    .collect::<Result<Vec<_>, LoweringError>>()?;
+                let else_expr = c.else_expr.as_deref().map(bx).transpose()?;
+                Ok(Unresolved::Case {
+                    operand,
+                    branches,
+                    else_expr,
+                })
+            }
+
+            Expr::Not(inner) => Ok(Unresolved::Not(bx(inner)?)),
+
+            Expr::IsNull(inner) => Ok(Unresolved::IsNull(bx(inner)?)),
+
+            Expr::IsNotNull(inner) => Ok(Unresolved::IsNotNull(bx(inner)?)),
+
+            Expr::Cast(c) => Ok(Unresolved::Cast {
+                expr: bx(&c.expr)?,
+                to: arrow_to_dtype(&c.data_type)?,
+                try_cast: false,
+            }),
+
+            // TRY_CAST returns NULL on conversion failure; preserve that semantic.
+            Expr::TryCast(c) => Ok(Unresolved::Cast {
+                expr: bx(&c.expr)?,
+                to: arrow_to_dtype(&c.data_type)?,
+                try_cast: true,
+            }),
+
+            Expr::InList(il) => {
+                let list: Result<Vec<_>, _> = il.list.iter().map(|e| self.lower_expr(e)).collect();
+                Ok(Unresolved::InList {
+                    expr: bx(&il.expr)?,
+                    list: list?,
+                    negated: il.negated,
+                })
+            }
+
+            Expr::Between(b) => {
+                // Normalize: `x BETWEEN low AND high` → `x >= low AND x <= high`.
+                // `x NOT BETWEEN low AND high` → `x < low OR x > high`.
+                if b.negated {
+                    let lt = self.compare(&b.expr, CompareOpKind::Lt, &b.low)?;
+                    let gt = self.compare(&b.expr, CompareOpKind::Gt, &b.high)?;
+                    Ok(Unresolved::BoolOr(vec![lt, gt]))
+                } else {
+                    let x_low = self.compare(&b.expr, CompareOpKind::Ge, &b.low)?;
+                    let x_high = self.compare(&b.expr, CompareOpKind::Le, &b.high)?;
+                    Ok(Unresolved::BoolAnd(vec![x_low, x_high]))
+                }
+            }
+
+            // `NOW()` / `CURRENT_TIMESTAMP` read the SQL statement evaluation
+            // time. Keep this timestamp-typed leaf distinct from PromQL's
+            // Float64 Unix-seconds `EvalTimestamp`. Issue #184.
+            Expr::ScalarFunction(sf)
+                if sf.args.is_empty()
+                    && matches!(
+                        sf.func.name().to_ascii_lowercase().as_str(),
+                        "now" | "current_timestamp"
+                    ) =>
+            {
+                Ok(Unresolved::CurrentTimestamp)
+            }
+
+            Expr::ScalarFunction(sf) => {
+                let args: Result<Vec<_>, _> = sf.args.iter().map(|e| self.lower_expr(e)).collect();
+                Ok(Unresolved::FunctionCall {
+                    name: if sf.func.name().eq_ignore_ascii_case("arrayelement") {
+                        "asap_element_access".into()
+                    } else if sf.func.name().eq_ignore_ascii_case("tupleelement") {
+                        "asap_struct_field".into()
+                    } else {
+                        sf.func.name().to_string()
+                    },
+                    args: args?,
+                })
+            }
+
+            // Subquery-valued expressions. Each subquery plan is lowered as a
+            // root of its own; `resolve_root` binds it in its own scope, so an
+            // outer reference inside it has nothing to resolve against — a
+            // correlated subquery is rejected rather than mislowered.
+            Expr::ScalarSubquery(sq) => Ok(Unresolved::ScalarSubquery(Rc::new(
+                self.lower_uncorrelated_subquery(sq, "scalar subquery")?,
+            ))),
+            Expr::Exists(ex) => Ok(Unresolved::Exists {
+                subquery: Rc::new(self.lower_uncorrelated_subquery(&ex.subquery, "EXISTS")?),
+                negated: ex.negated,
+            }),
+            Expr::InSubquery(is) => {
+                let fields = is.subquery.subquery.schema().fields().len();
+                if fields != 1 {
+                    return Err(LoweringError::InvalidExpression(format!(
+                        "IN (subquery) must select exactly one column, got {fields}"
+                    )));
+                }
+                Ok(Unresolved::InSubquery {
+                    expr: bx(&is.expr)?,
+                    subquery: Rc::new(
+                        self.lower_uncorrelated_subquery(&is.subquery, "IN (subquery)")?,
+                    ),
+                    negated: is.negated,
+                })
+            }
+
+            other => Err(LoweringError::UnsupportedFeature(format!(
+                "expression: {}",
+                other
+            ))),
+        }
+    }
+
+    fn lower_uncorrelated_subquery(
+        &self,
+        sq: &datafusion::logical_expr::Subquery,
+        what: &str,
+    ) -> Result<asap_frontend_common::UnresolvedOp, LoweringError> {
+        if !sq.outer_ref_columns.is_empty() {
+            return Err(LoweringError::UnsupportedFeature(format!(
+                "correlated {what}"
+            )));
+        }
+        self.lower_plan(&sq.subquery)
+    }
+
+    pub(super) fn compare(
+        &self,
+        left: &Expr,
+        op: CompareOpKind,
+        right: &Expr,
+    ) -> Result<Unresolved, LoweringError> {
+        Ok(Unresolved::Compare {
+            left: Box::new(self.lower_expr(left)?),
+            op,
+            right: Box::new(self.lower_expr(right)?),
+            semantics: ExprSemantics::Sql,
+        })
+    }
+
+    fn arith(
+        &self,
+        left: &Expr,
+        op: ArithmeticOpKind,
+        right: &Expr,
+    ) -> Result<Unresolved, LoweringError> {
+        Ok(Unresolved::Arithmetic {
+            op,
+            left: Box::new(self.lower_expr(left)?),
+            right: Box::new(self.lower_expr(right)?),
+            semantics: ExprSemantics::Sql,
+        })
+    }
+}
+
+pub(super) fn split_disjuncts(expr: &Expr) -> Vec<&Expr> {
+    match expr {
+        Expr::BinaryExpr(BinaryExpr {
+            left,
+            op: Operator::Or,
+            right,
+        }) => {
+            let mut v = split_disjuncts(left);
+            v.extend(split_disjuncts(right));
+            v
+        }
+        _ => vec![expr],
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::unified::sql::SqlCatalog;
+    use asap_types::pre_asap::schema::DataType;
+    use datafusion::common::ScalarValue as DfScalarValue;
+
+    // Typed Arrow dates normalize to the same typed form as SQL date casts.
+    #[test]
+    fn arrow_date_literals_preserve_value_and_type() {
+        let catalog = SqlCatalog::new();
+        let lowerer = SqlLowerer::new(&catalog);
+        for (value, expected) in [
+            (
+                DfScalarValue::Date32(Some(0)),
+                ScalarValue::Utf8("1970-01-01".into()),
+            ),
+            (
+                DfScalarValue::Date64(Some(-86_400_000)),
+                ScalarValue::Utf8("1969-12-31".into()),
+            ),
+            (DfScalarValue::Date32(None), ScalarValue::Null),
+            (DfScalarValue::Date64(None), ScalarValue::Null),
+        ] {
+            let actual = lowerer.lower_expr(&Expr::Literal(value)).unwrap();
+            assert_eq!(
+                actual,
+                Unresolved::Cast {
+                    expr: Box::new(Unresolved::Literal(expected)),
+                    to: DataType::Date,
+                    try_cast: false,
+                }
+            );
+        }
+    }
+
+    // Unary minus over a non-literal is the `Negative` scalar, SQL-flavoured.
+    #[test]
+    fn unary_minus_lowers_to_negative_with_sql_semantics() {
+        let catalog = SqlCatalog::new();
+        let lowerer = SqlLowerer::new(&catalog);
+        let expr = Expr::Negative(Box::new(Expr::Column(
+            datafusion::common::Column::new_unqualified("x"),
+        )));
+        assert_eq!(
+            lowerer.lower_expr(&expr).unwrap(),
+            Unresolved::Negative {
+                expr: Box::new(Unresolved::Column(ColumnRef::Named("x".into()))),
+                semantics: ExprSemantics::Sql,
+            }
+        );
+    }
+}
diff --git a/crates/frontend-sql/src/unified/sql/mod.rs b/crates/frontend-sql/src/unified/sql/mod.rs
new file mode 100644
index 000000000..1f58f92c0
--- /dev/null
+++ b/crates/frontend-sql/src/unified/sql/mod.rs
@@ -0,0 +1,2525 @@
+//! SQL → the name-based front-end tree
+//! ([`UnresolvedOp`](asap_frontend_common::UnresolvedOp) /
+//! [`UnresolvedScalar`](asap_frontend_common::UnresolvedScalar)).
+//!
+//! Parses SQL via DataFusion (over the catalog's registered tables), then
+//! walks the unoptimized `LogicalPlan` and emits `UnresolvedOp` nodes with
+//! unresolved `ColumnRef`s directly (issue #179) — the same tree shape
+//! [`resolve_root`](asap_frontend_common::resolve_root) binds into the
+//! positional, unified `OperatorNode` IR. Unlike PromQL's front end, SQL's
+//! Ordinary SQL `Aggregate` nodes are `Reduction::Reduce`. The explicit
+//! `asap_rate`/`asap_increase` bridge is the narrow exception: it
+//! spells a time-series range reducer with an explicit value, time-index, and
+//! window and therefore lowers to the same `TimeRange` + `PerEntity` shape as
+//! its PromQL counterpart. The front end also has to fold a `WHERE` directly
+//! over a bare table scan onto
+//! `Scan.predicates` itself (`filter_or_fold`) — canonical's invariant that a
+//! `Filter` never sits directly over a `Scan` — since front ends producing
+//! this shape are responsible for it now, not a converter.
+//!
+//! Heavy-hitter `topk` recognition (`ORDER BY count(...) DESC LIMIT k`) is
+//! *not* done here: SQL emits a plain `Sort`/`Limit`, and the shared
+//! `canonicalize` pass (issue #34, run by `resolve_root`) recognises the
+//! count-ranked shape positionally, so a SQL `ORDER BY`/`LIMIT` and a PromQL
+//! `topk(...)` converge without either front end special-casing the other's
+//! syntax.
+
+use std::rc::Rc;
+use std::sync::Arc;
+use std::time::Duration;
+
+use datafusion::arrow::compute::kernels::cast_utils::parse_interval_month_day_nano;
+use datafusion::arrow::datatypes::{DataType as ArrowDataType, Field};
+use datafusion::catalog_common::MemorySchemaProvider;
+use datafusion::common::config::ConfigOptions;
+use datafusion::common::tree_node::{Transformed, TreeNode, TreeNodeRecursion};
+use datafusion::common::{Column as DfColumn, DFSchema, ScalarValue as DfScalarValue};
+use datafusion::datasource::MemTable;
+use datafusion::functions_aggregate::count::count_udaf;
+use datafusion::functions_aggregate::sum::sum_udaf;
+use datafusion::logical_expr::expr::AggregateFunction;
+use datafusion::logical_expr::expr_rewriter::FunctionRewrite;
+use datafusion::logical_expr::function::{PartitionEvaluatorArgs, WindowUDFFieldArgs};
+use datafusion::logical_expr::{
+    self, lit, AggregateUDF, Case, Distinct, Expr, ExprSchemable, JoinType, LogicalPlan,
+    PartitionEvaluator, ScalarUDF, ScalarUDFImpl, Signature, SimpleAggregateUDF, TypeSignature,
+    Volatility, WindowFrameBound as DfWindowFrameBound, WindowFrameUnits as DfWindowFrameUnits,
+    WindowFunctionDefinition, WindowUDF, WindowUDFImpl,
+};
+use datafusion::optimizer::analyzer::function_rewrite::ApplyFunctionRewrites;
+use datafusion::optimizer::{AnalyzerRule, OptimizerConfig};
+use datafusion::prelude::{SessionConfig, SessionContext};
+use datafusion::sql::parser::DFParser;
+
+use asap_frontend_common::{
+    resolve_root, UnresolvedOp as Unresolved, UnresolvedPredicate as Predicate,
+    UnresolvedProjectItem as ProjectItem, UnresolvedScalar as Scalar, UnresolvedSortKey as SortKey,
+};
+use asap_sql_function_catalog::{AggSemantic, Arity, RewriteKind};
+use asap_types::ir::operator_properties::{
+    GroupKeys, Reduction, Source, WindowFrame, WindowFrameBound, WindowFrameOffset,
+    WindowFrameUnits,
+};
+use asap_types::ir::TimeRangeKind;
+use asap_types::pre_asap::agg_intent::AggIntent;
+use asap_types::pre_asap::schema::{DataType, FieldDataType, Schema};
+
+use asap_types::pre_asap::{
+    resolve_column_ref, ColumnRef, CompareOpKind, JoinKind, RelationalSetOpKind, ScalarValue,
+    WindowFuncKind,
+};
+use asap_types::types::AccuracyTarget;
+use asap_types::workload::SqlDialect;
+
+use crate::unified::error::SqlError as LoweringError;
+
+mod clickhouse_ast;
+mod collection_planning;
+mod dialect;
+mod expr;
+mod types;
+
+pub use types::SqlCatalog;
+
+use self::dialect::GenericWithAggregateFilter;
+use self::types::{arrow_to_dtype, scalar_value_to_asap, schema_to_arrow};
+
+std::thread_local! {
+    static ACCURACY: std::cell::RefCell<AccuracyTarget> =
+        const { std::cell::RefCell::new(AccuracyTarget::Exact) };
+}
+
+/// RAII guard installing `accuracy` as the ambient accuracy target for the
+/// current thread's lowering, restoring the prior value on drop — same
+/// ambient-thread-local shape as `asap_frontend_promql::promql`'s
+/// `AccuracyGuard`, for the same reason: it injects `accuracy` into the deep
+/// `lower_plan` recursion without a parameter on every one of its
+/// signatures, consulted only at the couple of sites that build an
+/// accuracy-bearing `AggIntent`.
+struct AccuracyGuard(AccuracyTarget);
+
+impl AccuracyGuard {
+    fn install(accuracy: AccuracyTarget) -> Self {
+        let prev = ACCURACY.with(|a| a.replace(accuracy));
+        AccuracyGuard(prev)
+    }
+}
+
+impl Drop for AccuracyGuard {
+    fn drop(&mut self) {
+        ACCURACY.with(|a| *a.borrow_mut() = std::mem::replace(&mut self.0, AccuracyTarget::Exact));
+    }
+}
+
+fn current_accuracy() -> AccuracyTarget {
+    ACCURACY.with(|a| a.borrow().clone())
+}
+
+/// Lowers SQL strings to the name-based [`UnresolvedOp`](asap_frontend_common::UnresolvedOp)
+/// tree over a table [`SqlCatalog`]. Call
+/// [`resolve_root`](asap_frontend_common::resolve_root) on the result for
+/// the resolved operator DAG.
+pub struct SqlLowerer<'a> {
+    catalog: &'a SqlCatalog,
+    dialect: SqlDialect,
+}
+
+impl<'a> SqlLowerer<'a> {
+    pub fn new(catalog: &'a SqlCatalog) -> Self {
+        Self {
+            catalog,
+            dialect: SqlDialect::DataFusionSQL,
+        }
+    }
+
+    /// Parse under a specific SQL dialect (e.g. `ClickhouseSQL`, which maps to
+    /// sqlparser's vendored `ClickHouseDialect` — array-lambda syntax and
+    /// `arr[-1]` indexing parse under it that don't parse generically). This
+    /// only changes *parsing*: a ClickHouse-only builtin function not listed
+    /// in `asap_sql_function_catalog::CLICKHOUSE_BUILTINS` (`uniqExact` and
+    /// `countIf` are; most of ClickHouse's builtin surface isn't yet) is
+    /// still unknown to DataFusion's planner and still fails there, and
+    /// `ElasticSQL` has no vendored parser at all.
+    pub fn with_dialect(catalog: &'a SqlCatalog, dialect: SqlDialect) -> Self {
+        Self { catalog, dialect }
+    }
+
+    /// Parse + lower a SQL query to the name-based tree, threading
+    /// `accuracy` onto every approximate intent (`Count`, `Quantile`,
+    /// `Cardinality`) as it is built.
+    ///
+    /// The `AccuracyGuard` installs *after* the only `.await` point
+    /// (DataFusion statement planning) — `lower_plan` itself is synchronous, so once it starts
+    /// there is no further suspension point that could move this task to a
+    /// different OS thread out from under a thread-local set beforehand.
+    ///
+    /// Runs `ApplyFunctionRewrites` — the single `AnalyzerRule` DataFusion's
+    /// own `Analyzer` uses internally to apply `FunctionRewrite`s, called
+    /// directly rather than through `Analyzer::execute_and_check` — over the
+    /// raw parsed plan before lowering, carrying only
+    /// `ClickHouseBuiltinRewrite` (catalog-driven, see its own doc — it
+    /// covers every `asap_sql_function_catalog::CLICKHOUSE_BUILTINS` entry,
+    /// not just one). `ctx.sql(...).into_unoptimized_plan()` alone returns
+    /// `SqlToRel`'s output untouched, and a `FunctionRewrite` only ever runs
+    /// as part of this rule, so calling it directly is unavoidable to make
+    /// the rewrite fire. Its `analyze()` already does a full
+    /// `transform_up_with_subqueries` over the whole plan, so it needs no
+    /// wrapping `Analyzer` at all — deliberately not
+    /// `Analyzer::execute_and_check` (whether with the default 5-rule
+    /// analyzer or an empty one carrying just this rewrite): that method
+    /// runs an unconditional post-check (`check_plan`, hardcoded, not itself
+    /// a rule) that isn't wanted here — e.g. it independently rejects a
+    /// multi-column `IN (subquery)` before `lower_in_subquery`'s own arity
+    /// check would. Going straight to `ApplyFunctionRewrites` avoids that
+    /// entirely. TypeCoercion then records implicit conversions explicitly,
+    /// including timestamp literals in predicates, before IR validation.
+    pub async fn lower(
+        &self,
+        sql: &str,
+        accuracy: &AccuracyTarget,
+    ) -> Result<Unresolved, LoweringError> {
+        let ctx = self.build_context()?;
+        let state = ctx.state();
+        let statement = if matches!(self.dialect, SqlDialect::ClickhouseSQL) {
+            let mut statement = state.sql_to_statement(sql, "ClickHouse")?;
+            if let datafusion::sql::parser::Statement::Statement(ast) = &mut statement {
+                clickhouse_ast::normalize(ast);
+            }
+            statement
+        } else {
+            // Not `ctx.sql(sql)`: that parses under the by-name `generic`
+            // dialect, which cannot see an aggregate `FILTER (WHERE …)`.
+            let mut statements = DFParser::parse_sql_with_dialect(sql, &GenericWithAggregateFilter)
+                .map_err(|e| datafusion::error::DataFusionError::SQL(e, None))?;
+            let (Some(statement), true) = (statements.pop_front(), statements.is_empty()) else {
+                return Err(LoweringError::UnsupportedFeature(
+                    "exactly one SQL statement per query".into(),
+                ));
+            };
+            statement
+        };
+        let plan = state.statement_to_plan(statement).await?;
+        let rewriter = ApplyFunctionRewrites::new(vec![Arc::new(ClickHouseBuiltinRewrite)]);
+        let plan = rewriter.analyze(plan, ctx.state().options())?;
+        let plan = datafusion::optimizer::analyzer::type_coercion::TypeCoercion::new()
+            .analyze(plan, ctx.state().options())?;
+        // Output schemas omit predicate and nested-expression types. Check the
+        // typed SQL plan before lowering erases fixed-duration units.
+        plan.apply_with_subqueries(|node| {
+            let mut schema = DFSchema::empty();
+            for input in node.inputs() {
+                schema.merge(input.schema());
+            }
+            schema.merge(node.schema());
+            node.apply_expressions(|expr| {
+                expr.apply(|nested| {
+                    if let Expr::BinaryExpr(binary) = nested {
+                        if binary.op == logical_expr::Operator::Minus
+                            && matches!(nested.get_type(&schema)?, ArrowDataType::Duration(_))
+                        {
+                            return Err(datafusion::common::DataFusionError::Plan(
+                                "temporal subtraction produces an unsupported duration type".into(),
+                            ));
+                        }
+                    }
+                    Ok(TreeNodeRecursion::Continue)
+                })
+            })
+        })?;
+        let _guard = AccuracyGuard::install(accuracy.clone());
+        self.lower_plan(&plan)
+    }
+
+    /// Register the catalog tables (empty Arrow `MemTable`s) so DataFusion can
+    /// resolve table/column references during planning.
+    fn build_context(&self) -> Result<SessionContext, LoweringError> {
+        let dialect_name = match &self.dialect {
+            SqlDialect::DataFusionSQL => "generic",
+            SqlDialect::ClickhouseSQL => "ClickHouse",
+            SqlDialect::ElasticSQL => {
+                return Err(LoweringError::UnsupportedDialect("ElasticSQL".into()))
+            }
+        };
+        let config = SessionConfig::new().set_str("datafusion.sql_parser.dialect", dialect_name);
+        let ctx = SessionContext::new_with_config(config);
+        if matches!(self.dialect, SqlDialect::ClickhouseSQL) {
+            collection_planning::register(&ctx);
+        }
+        // A catalog key like "bgp.bgp_updates" schema-qualifies the table
+        // (e.g. a ClickHouse database name). DataFusion requires the parent
+        // schema to be registered before a qualified table can be, so create
+        // it on demand.
+        let catalog_provider = ctx.catalog("datafusion").ok_or_else(|| {
+            LoweringError::InvalidExpression("default \"datafusion\" catalog missing".into())
+        })?;
+        for (name, schema) in &self.catalog.tables {
+            if let Some((schema_name, _)) = name.split_once('.') {
+                if catalog_provider.schema(schema_name).is_none() {
+                    catalog_provider
+                        .register_schema(schema_name, Arc::new(MemorySchemaProvider::new()))?;
+                }
+            }
+            let arrow_schema = Arc::new(schema_to_arrow(schema));
+            let mem_table = MemTable::try_new(arrow_schema, vec![])?;
+            ctx.register_table(name.as_str(), Arc::new(mem_table))?;
+        }
+        // Register a stub `AggregateUDF` for every catalog-listed
+        // ClickHouse-only builtin, purely so DataFusion's planner can
+        // resolve its name during parsing — `lower()` rewrites every call
+        // site to a native DataFusion aggregate via `ClickHouseBuiltinRewrite`
+        // before `lower_plan` sees it.
+        for builtin in asap_sql_function_catalog::CLICKHOUSE_BUILTINS {
+            ctx.register_udaf(clickhouse_builtin_stub_udaf(builtin.name, builtin.arity));
+        }
+        // Register a stub `ScalarUDF` for every catalog-listed ClickHouse-only
+        // *scalar* builtin — same reason as the `AggregateUDF` loop above
+        // (DataFusion otherwise rejects the call as an unknown function
+        // during `SqlToRel` conversion), but with no rewrite step to follow:
+        // `lower_expr`'s `Expr::ScalarFunction` arm already lowers any
+        // scalar call generically to `UnresolvedScalar::FunctionCall { name,
+        // args }`, so registering the stub is the entire fix (issue #230).
+        for builtin in asap_sql_function_catalog::CLICKHOUSE_SCALAR_BUILTINS {
+            ctx.register_udf(clickhouse_scalar_builtin_stub_udf(
+                builtin.name,
+                builtin.arity,
+            ));
+        }
+        // Planning-only relation markers.  They let a workload author state
+        // the PromQL temporal/classic-histogram semantics of an equivalent SQL
+        // rewrite without teaching the canonical IR a second, SQL-specific
+        // spelling of either operation.  `lower_projection` consumes these
+        // calls; they can never survive as executable scalar functions.
+        for (name, arity) in [
+            ("asap_promql_subquery", Arity::Exact(2)),
+            ("asap_histogram_quantile", Arity::Exact(1)),
+        ] {
+            ctx.register_udf(clickhouse_scalar_builtin_stub_udf(name, arity));
+        }
+        // Register a stub `WindowUDF` for every catalog-listed ClickHouse-only
+        // *window* builtin — same reason as the two loops above, but with no
+        // rewrite step to follow: `lower_window_func_kind` already maps each
+        // name directly to its own `WindowFuncKind` variant (issue #267).
+        for builtin in asap_sql_function_catalog::CLICKHOUSE_WINDOW_BUILTINS {
+            ctx.register_udwf(clickhouse_window_builtin_stub_udwf(
+                builtin.name,
+                builtin.arity,
+            ));
+        }
+        Ok(ctx)
+    }
+
+    pub(super) fn lower_plan(&self, plan: &LogicalPlan) -> Result<Unresolved, LoweringError> {
+        match plan {
+            LogicalPlan::TableScan(scan) => self.lower_table_scan(scan),
+            // The one empty input row of a `SELECT` without `FROM`.
+            LogicalPlan::EmptyRelation(empty) => Ok(Unresolved::Values {
+                rows: if empty.produce_one_row {
+                    vec![vec![]]
+                } else {
+                    vec![]
+                },
+                schema: Schema {
+                    fields: vec![],
+                    time_index: None,
+                    unique_keys: vec![],
+                    closed: true,
+                },
+            }),
+            LogicalPlan::Values(values) => self.lower_values(values),
+            LogicalPlan::Filter(filter) => self.lower_filter(filter),
+            LogicalPlan::Projection(proj) => self.lower_projection(proj),
+            LogicalPlan::Aggregate(agg) => self.lower_aggregate(agg),
+            LogicalPlan::Sort(sort) => self.lower_sort(sort),
+            LogicalPlan::Limit(limit) => self.lower_limit(limit),
+            LogicalPlan::Distinct(d) => match d {
+                Distinct::On(_) => Err(LoweringError::UnsupportedFeature("DISTINCT ON".into())),
+                Distinct::All(input) => Ok(Unresolved::Dedup {
+                    cols: vec![],
+                    child: Rc::new(self.lower_plan(input)?),
+                }),
+            },
+            LogicalPlan::Union(u) => {
+                // Fold n inputs left-associatively into SetOp { Union, all: true }.
+                let mut iter = u.inputs.iter();
+                let first = iter
+                    .next()
+                    .ok_or_else(|| LoweringError::InvalidExpression("empty union".into()))?;
+                let first_expr = self.lower_plan(first)?;
+                iter.try_fold(first_expr, |left, right_plan| {
+                    Ok(Unresolved::SetOp {
+                        kind: RelationalSetOpKind::Union,
+                        all: true,
+                        left: Rc::new(left),
+                        right: Rc::new(self.lower_plan(right_plan)?),
+                    })
+                })
+            }
+            LogicalPlan::Window(window) => self.lower_window(window),
+            LogicalPlan::Join(join) => self.lower_join(join),
+            LogicalPlan::Subquery(_) => Err(LoweringError::UnsupportedFeature("subquery".into())),
+            LogicalPlan::SubqueryAlias(alias) => {
+                // An alias over a table re-qualifies the scan's columns with the
+                // alias (so `a.col` / `b.col` in a self-join disambiguate).
+                match alias.input.as_ref() {
+                    LogicalPlan::TableScan(scan) => {
+                        self.scan_source(&scan.table_name.to_string(), &alias.alias.to_string())
+                    }
+                    // A *derived table* / inline view — `FROM (SELECT …) t`, the
+                    // SQL counterpart of PromQL function nesting (an aggregate
+                    // over an aggregate, a filter over a derived aggregate, …).
+                    // Lower the inner plan, then re-qualify its output columns
+                    // with the alias so `t.col` resolves to *this* relation — and,
+                    // critically, so a join over two derived tables disambiguates
+                    // its keys instead of both binding to the first bare-name
+                    // match (issue #66). The inner column *names* are unchanged;
+                    // only the qualifier is stamped.
+                    other => {
+                        let alias_name = alias.alias.to_string();
+                        match self.lower_plan(other)? {
+                            // The derived SELECT list already lowered to a
+                            // Projection — stamp the alias onto it, no extra node.
+                            Unresolved::Project { cols, child, .. } => Ok(Unresolved::Project {
+                                cols,
+                                qualifier: Some(alias_name),
+                                child,
+                            }),
+                            // Otherwise (e.g. `SELECT *` unwrapped to a scan) wrap
+                            // in an identity projection that re-qualifies each
+                            // output column. Names come from the sub-plan's schema.
+                            inner => {
+                                let cols = alias
+                                    .input
+                                    .schema()
+                                    .fields()
+                                    .iter()
+                                    .map(|f| ProjectItem {
+                                        alias: Some(f.name().clone()),
+                                        expr: Scalar::Column(ColumnRef::Named(f.name().clone())),
+                                    })
+                                    .collect();
+                                Ok(Unresolved::Project {
+                                    cols,
+                                    qualifier: Some(alias_name),
+                                    child: Rc::new(inner),
+                                })
+                            }
+                        }
+                    }
+                }
+            }
+            other => Err(LoweringError::UnsupportedFeature(format!(
+                "plan node: {}",
+                other.display()
+            ))),
+        }
+    }
+
+    /// `WHERE` — a conjunction of ordinary predicates plus, possibly, subquery
+    /// predicates (issue #111).
+    ///
+    /// The ordinary conjuncts stay one predicate, folded onto a bare `Scan`
+    /// (`filter_or_fold`). A subquery conjunct — `c IN (SELECT …)`, `EXISTS
+    /// (…)`, `x > (SELECT …)` — is a row filter whose predicate reads another
+    /// operator (`UnresolvedScalar::InSubquery` / `Exists` /
+    /// `ScalarSubquery`); each one becomes its own `Filter` **above** the
+    /// ordinary predicate, so the shared `canonicalize` pass can turn it into
+    /// the join it is without having to peel it out of a conjunction or off
+    /// a `Scan` (it only lifts subqueries out of `Filter` / `Project`). A
+    /// semi-join only ever drops left rows, so the two orders agree.
+    ///
+    /// The one subquery shape still lowered to a join here is a *correlated*
+    /// `EXISTS`: its correlation references both sides, which only a join
+    /// predicate can bind (a subquery referenced from a scalar position is
+    /// resolved as a root in its own scope).
+    fn lower_filter(&self, filter: &logical_expr::Filter) -> Result<Unresolved, LoweringError> {
+        let mut conjuncts = Vec::new();
+        split_conjunction(&filter.predicate, &mut conjuncts);
+        let (subqueries, residual): (Vec<_>, Vec<_>) =
+            conjuncts.into_iter().partition(|e| reads_subquery(e));
+
+        let input = self.lower_plan(&filter.input)?;
+        let mut node = match rebuild_conjunction(&residual) {
+            Some(pred) => filter_or_fold(self.lower_expr(&pred)?, input),
+            None => input,
+        };
+        for sq in subqueries {
+            node = match sq {
+                Expr::Exists(ex) if !ex.subquery.outer_ref_columns.is_empty() => {
+                    self.lower_correlated_exists(ex, node)?
+                }
+                other => Unresolved::Filter {
+                    pred: Predicate(self.lower_expr(other)?),
+                    child: Rc::new(node),
+                },
+            };
+        }
+        Ok(node)
+    }
+
+    /// `[NOT] EXISTS (SELECT … WHERE inner.k = outer.k)` → a semi- / anti-join
+    /// on the correlation predicate (issue #111).
+    fn lower_correlated_exists(
+        &self,
+        ex: &logical_expr::expr::Exists,
+        left: Unresolved,
+    ) -> Result<Unresolved, LoweringError> {
+        let kind = if ex.negated {
+            JoinKind::Anti
+        } else {
+            JoinKind::Semi
+        };
+        // A semi-join discards the right side's columns, and `SELECT 1` projects
+        // the correlation columns away — so drop the subquery's projections and
+        // join against what they sit on.
+        let mut inner = ex.subquery.subquery.as_ref();
+        while let LogicalPlan::Projection(p) = inner {
+            inner = &p.input;
+        }
+        // Lift the correlated conjuncts out of the subquery's filter; they are
+        // the join predicate. Whatever is left stays an ordinary inner filter.
+        let (inner, correlation) = split_correlation(inner)?;
+        let right = self.lower_plan(&inner)?;
+        let pred = match correlation {
+            Some(e) => Predicate(self.lower_expr(&e)?),
+            None => Predicate(Scalar::Literal(ScalarValue::Boolean(true))),
+        };
+        Ok(Unresolved::Join {
+            kind,
+            pred,
+            left: Rc::new(left),
+            right: Rc::new(right),
+        })
+    }
+
+    /// `VALUES (…), (…)` — one row per values row, typed by DataFusion's
+    /// declared schema. Row expressions have no input-column scope.
+    fn lower_values(&self, values: &logical_expr::Values) -> Result<Unresolved, LoweringError> {
+        let rows = values
+            .values
+            .iter()
+            .map(|row| row.iter().map(|e| self.lower_expr(e)).collect())
+            .collect::<Result<Vec<Vec<_>>, LoweringError>>()?;
+        let fields = values
+            .schema
+            .fields()
+            .iter()
+            .map(|f| {
+                Ok(asap_types::pre_asap::Field::plain(
+                    f.name().clone(),
+                    arrow_to_dtype(f.data_type())?,
+                    f.is_nullable(),
+                ))
+            })
+            .collect::<Result<Vec<_>, LoweringError>>()?;
+        Ok(Unresolved::Values {
+            rows,
+            schema: Schema {
+                fields,
+                time_index: None,
+                unique_keys: vec![],
+                closed: true,
+            },
+        })
+    }
+
+    /// Table leaf — carries the catalog's resolved schema directly on `Scan`
+    /// (`schema: Some(_)`), so `resolve_root`'s SchemaResolver doesn't need to
+    /// usage-derive it (SQL is never schemaless). Projection pushdown is left
+    /// to the enclosing `Project` (DataFusion's unoptimized plan sets no
+    /// projection).
+    fn lower_table_scan(
+        &self,
+        scan: &logical_expr::TableScan,
+    ) -> Result<Unresolved, LoweringError> {
+        let table = scan.table_name.to_string();
+        self.scan_source(&table, &table)
+    }
+
+    /// A `Scan` over catalog table `table`, with its columns qualified by
+    /// `qualifier` (the table name, or an alias from a `SubqueryAlias`) so
+    /// `Qualified` column refs resolve to the right side across a join.
+    fn scan_source(&self, table: &str, qualifier: &str) -> Result<Unresolved, LoweringError> {
+        let schema = self
+            .catalog
+            .tables
+            .get(table)
+            .ok_or_else(|| LoweringError::TableNotFound(table.to_string()))?;
+        let qualified = Schema {
+            fields: schema
+                .fields
+                .iter()
+                .cloned()
+                .map(|c| c.with_table(qualifier))
+                .collect(),
+            time_index: schema.time_index,
+            unique_keys: schema.unique_keys.clone(),
+            // Catalog-backed: the table's columns are fully declared → closed.
+            closed: true,
+        };
+        Ok(Unresolved::Scan {
+            source: Source::Table {
+                table_ref: table.to_string(),
+            },
+            predicates: vec![],
+            schema: Some(qualified),
+        })
+    }
+
+    /// ⋈ — equijoin. The `on` key pairs become `left = right` comparisons,
+    /// AND-ed with any non-equi `filter`, into the join predicate — still
+    /// name-based here (like a `WHERE`); `resolve_root` derives the
+    /// concatenated output schema downstream. Semi/anti/mark joins have no
+    /// canonical counterpart yet and are rejected.
+    fn lower_join(&self, join: &logical_expr::Join) -> Result<Unresolved, LoweringError> {
+        let kind = match join.join_type {
+            JoinType::Inner => JoinKind::Inner,
+            JoinType::Left => JoinKind::Left,
+            JoinType::Right => JoinKind::Right,
+            JoinType::Full => JoinKind::Full,
+            other => {
+                return Err(LoweringError::UnsupportedFeature(format!(
+                    "join type: {other:?}"
+                )))
+            }
+        };
+        let mut conjuncts = join
+            .on
+            .iter()
+            .map(|(l, r)| self.compare(l, CompareOpKind::Eq, r))
+            .collect::<Result<Vec<_>, LoweringError>>()?;
+        if let Some(filter) = &join.filter {
+            conjuncts.push(self.lower_expr(filter)?);
+        }
+        let pred = Predicate(match conjuncts.len() {
+            // No condition (a CROSS JOIN) is unconditionally true.
+            0 => Scalar::Literal(ScalarValue::Boolean(true)),
+            1 => conjuncts.pop().unwrap(),
+            _ => Scalar::BoolAnd(conjuncts),
+        });
+        Ok(Unresolved::Join {
+            kind,
+            pred,
+            left: Rc::new(self.lower_plan(&join.left)?),
+            right: Rc::new(self.lower_plan(&join.right)?),
+        })
+    }
+
+    /// `func(args) OVER (PARTITION BY … ORDER BY … ROWS/RANGE BETWEEN …)`. One
+    /// window function per plan node.
+    fn lower_window(&self, window: &logical_expr::Window) -> Result<Unresolved, LoweringError> {
+        if window.window_expr.len() > 1 {
+            return Err(LoweringError::UnsupportedFeature(format!(
+                "multiple window functions in one plan node (got {}); split them",
+                window.window_expr.len()
+            )));
+        }
+        let child = Rc::new(self.lower_plan(&window.input)?);
+        let first = window
+            .window_expr
+            .first()
+            .ok_or_else(|| LoweringError::InvalidExpression("empty window expression".into()))?;
+        let first = match first {
+            Expr::Alias(alias) => alias.expr.as_ref(),
+            other => other,
+        };
+        let Expr::WindowFunction(wf) = first else {
+            return Err(LoweringError::InvalidExpression(
+                "expected a window function in Window plan node".into(),
+            ));
+        };
+        let func = lower_window_func_kind(&wf.fun)?;
+        let mut args = wf
+            .args
+            .iter()
+            .map(|e| self.lower_expr(e))
+            .collect::<Result<Vec<_>, _>>()?;
+        // Nth_value: lift N from the (literal) 2nd arg, keep only the column.
+        let func = if matches!(func, WindowFuncKind::NthValue(None)) {
+            let n = match args.get(1) {
+                Some(Scalar::Literal(ScalarValue::Int64(n))) if *n > 0 => *n as u64,
+                other => {
+                    return Err(LoweringError::InvalidExpression(format!(
+                        "NTH_VALUE requires a positive integer literal 2nd arg, got {other:?}"
+                    )))
+                }
+            };
+            args.truncate(1);
+            WindowFuncKind::NthValue(Some(n))
+        } else {
+            func
+        };
+        let partition_by = wf
+            .partition_by
+            .iter()
+            .map(expr_to_group_ref)
+            .collect::<Result<Vec<_>, _>>()?;
+        let order_by = wf
+            .order_by
+            .iter()
+            .map(|s| {
+                self.lower_expr(&s.expr).map(|expr| SortKey {
+                    expr,
+                    ascending: s.asc,
+                    nulls_first: s.nulls_first,
+                })
+            })
+            .collect::<Result<Vec<_>, _>>()?;
+        let frame = lower_window_frame(&wf.window_frame)?;
+        // The window plan's schema is `[input fields …, window output]`; the last
+        // field is the window column's name (what an enclosing Project references).
+        let output_name = window
+            .schema
+            .fields()
+            .last()
+            .map(|f| f.name().clone())
+            .unwrap_or_else(|| "window".into());
+        Ok(Unresolved::SQLWindowFunc {
+            func,
+            args,
+            partition_by: partition_by.into(),
+            order_by,
+            frame: Some(frame),
+            output_name,
+            child,
+        })
+    }
+
+    fn lower_projection(
+        &self,
+        proj: &logical_expr::Projection,
+    ) -> Result<Unresolved, LoweringError> {
+        if let Some(bridge) = planning_bridge(proj)? {
+            let input = self.lower_plan(&proj.input)?;
+            return Ok(match bridge {
+                PlanningBridge::PromqlSubquery { range, resolution } => {
+                    let child = Rc::new(self.temporal_bridge_projection(proj, input)?);
+                    Unresolved::PromqlSubquery {
+                        range,
+                        resolution: Some(resolution),
+                        child,
+                    }
+                }
+                PlanningBridge::HistogramQuantile { q } => Unresolved::Aggregate {
+                    // The marker is the projection's only column: one histogram.
+                    reduction: Reduction::Reduce(GroupKeys::none()),
+                    measures: vec![AggIntent::HistogramQuantile {
+                        q,
+                        le: ColumnRef::Named("le".into()),
+                    }],
+                    output_names: vec!["value".into()],
+                    filters: vec![],
+                    having: None,
+                    child: Rc::new(input),
+                },
+            });
+        }
+        // SELECT * — no column constraint; pass through without a Project.
+        if proj.expr.iter().any(|e| matches!(e, Expr::Wildcard { .. })) {
+            return self.lower_plan(&proj.input);
+        }
+        let child = Rc::new(self.lower_plan(&proj.input)?);
+        let temporal_input = plan_has_temporal_aggregate(&proj.input);
+        let cols = proj
+            .expr
+            .iter()
+            .map(|e| match e {
+                Expr::Alias(a) => {
+                    let expr = if temporal_input && is_temporal_output_column(&a.expr) {
+                        Scalar::Column(ColumnRef::Named("value".into()))
+                    } else {
+                        self.lower_expr(&a.expr)?
+                    };
+                    Ok::<ProjectItem, LoweringError>(ProjectItem {
+                        expr,
+                        alias: Some(a.name.clone()),
+                    })
+                }
+                _ => {
+                    let expr = if temporal_input && is_temporal_output_column(e) {
+                        Scalar::Column(ColumnRef::Named("value".into()))
+                    } else {
+                        self.lower_expr(e)?
+                    };
+                    Ok::<ProjectItem, LoweringError>(ProjectItem { expr, alias: None })
+                }
+            })
+            .collect::<Result<Vec<_>, _>>()?;
+        Ok(Unresolved::Project {
+            cols,
+            qualifier: None,
+            child,
+        })
+    }
+
+    fn lower_aggregate(&self, agg: &logical_expr::Aggregate) -> Result<Unresolved, LoweringError> {
+        let input = self.lower_plan(&agg.input)?;
+        // Each measure's row predicate (`FILTER (WHERE …)`, or the NULL-skip
+        // a `count(expr)` implies), read off the original typed expression
+        // before derived-column rewriting erases the argument's nullability.
+        let measure_filters = agg
+            .aggr_expr
+            .iter()
+            .map(|e| measure_filter(e, agg.input.schema()))
+            .collect::<Result<Vec<_>, LoweringError>>()?;
+
+        if agg.aggr_expr.iter().any(is_temporal_aggregate) {
+            if measure_filters.iter().any(Option::is_some) {
+                return Err(LoweringError::UnsupportedFeature(
+                    "FILTER on an ASAP temporal aggregate".into(),
+                ));
+            }
+            return self.lower_temporal_aggregate(agg, input);
+        }
+
+        // `GROUPING SETS`/`ROLLUP`/`CUBE` emit several grouping levels from one
+        // scan. `Aggregate.by` is a single key set, so each level becomes its own
+        // `Aggregate` and they are merged (issue #118).
+        if let Some(gs) = agg.group_expr.iter().find_map(as_grouping_set) {
+            if measure_filters.iter().any(Option::is_some) {
+                return Err(LoweringError::UnsupportedFeature(
+                    "FILTER on a measure inside a multi-level grouping".into(),
+                ));
+            }
+            return self.lower_grouping_sets(agg, gs, input);
+        }
+
+        // `Aggregate.by` and the reducers index *columns*, so a grouping or
+        // reducer expression (`GROUP BY date_trunc(…)`, `SUM(a * 8)`) has no
+        // slot. Materialize each one as a derived column in a `Project` beneath
+        // the aggregate, then group/reduce over that column (issue #110).
+        let mut derived = DerivedCols::new(self);
+
+        // DataFusion strips `AS m` from a grouping expression, so the aggregate
+        // schema's field name is what the enclosing Projection references —
+        // the derived column has to carry exactly that name.
+        let group_names: Vec<String> = agg
+            .schema
+            .fields()
+            .iter()
+            .take(agg.group_expr.len())
+            .map(|f| f.name().to_string())
+            .collect();
+
+        let mut keys = Vec::with_capacity(agg.group_expr.len());
+        for (i, e) in agg.group_expr.iter().enumerate() {
+            match unalias(e) {
+                Expr::Column(_) => {
+                    derived.passthrough(e)?;
+                    keys.push(expr_to_group_ref(e)?);
+                }
+                other => {
+                    let name = group_names
+                        .get(i)
+                        .cloned()
+                        .unwrap_or_else(|| other.to_string());
+                    derived.materialize(name.clone(), self.lower_expr(other)?)?;
+                    keys.push(ColumnRef::Named(name));
+                }
+            }
+        }
+
+        // Reducer arguments get the same treatment; `rewrite_agg` returns the
+        // aggregate with its argument repointed at the derived column.
+        let aggr_expr = agg
+            .aggr_expr
+            .iter()
+            .map(|e| derived.rewrite_agg(e))
+            .collect::<Result<Vec<_>, LoweringError>>()?;
+        // A measure filter reads the aggregate's input rows, so the columns
+        // it names must survive any derived-column `Project` inserted below.
+        for column in measure_filters.iter().flatten().flat_map(Expr::column_refs) {
+            derived.passthrough(&Expr::Column(column.clone()))?;
+        }
+
+        let child = Rc::new(derived.wrap(input)?);
+        // DataFusion names the aggregate outputs in its own schema (e.g.
+        // "sum(metrics.bytes)") — the same names the enclosing Projection
+        // references. The schema is [group fields …, aggregate fields …], so
+        // skip the group fields and thread the rest straight through as
+        // `Aggregate.output_names`, letting that Projection resolve them.
+        let output_names: Vec<String> = agg
+            .schema
+            .fields()
+            .iter()
+            .skip(agg.group_expr.len())
+            .map(|f| f.name().to_string())
+            .collect();
+        let measures = aggr_expr
+            .iter()
+            .map(lower_agg_intent)
+            .collect::<Result<Vec<_>, LoweringError>>()?;
+        // Empty when nothing is filtered — the one canonical unfiltered shape.
+        let filters = if measure_filters.iter().any(Option::is_some) {
+            measure_filters
+                .iter()
+                .map(|f| {
+                    f.as_ref()
+                        .map(|f| Ok(Predicate(self.lower_expr(f)?)))
+                        .transpose()
+                })
+                .collect::<Result<Vec<_>, LoweringError>>()?
+        } else {
+            Vec::new()
+        };
+        Ok(Unresolved::Aggregate {
+            // SQL `GROUP BY` is always an inclusion list, never PromQL's
+            // `without(...)` exclusion form — and always a genuine reduction,
+            // never `PerEntity` (there's no windowed/subquery-child concept
+            // in SQL for that to apply to).
+            reduction: Reduction::Reduce(GroupKeys::by(keys)),
+            measures,
+            output_names,
+            filters,
+            having: None,
+            child,
+        })
+    }
+
+    fn lower_temporal_aggregate(
+        &self,
+        agg: &logical_expr::Aggregate,
+        input: Unresolved,
+    ) -> Result<Unresolved, LoweringError> {
+        if agg.aggr_expr.len() != 1 {
+            return Err(LoweringError::UnsupportedFeature(
+                "an ASAP temporal aggregate cannot share an Aggregate node with another reducer"
+                    .into(),
+            ));
+        }
+        let Expr::AggregateFunction(call) = unalias(&agg.aggr_expr[0]) else {
+            unreachable!("is_temporal_aggregate accepted a non-aggregate expression")
+        };
+        let name = call.func.name().to_lowercase();
+        let [value, timestamp, window] = call.args.as_slice() else {
+            unreachable!("ASAP temporal UDAF signatures require exactly three arguments")
+        };
+
+        let value_ref = reducer_col(&name, std::slice::from_ref(value))?;
+        let timestamp_ref = reducer_col(&name, std::slice::from_ref(timestamp))?;
+        let Expr::Literal(window) = unalias(window) else {
+            return Err(LoweringError::InvalidExpression(format!(
+                "{name} window_ms must be a positive integer literal"
+            )));
+        };
+        let window_ms = scalar_positive_u64(window).ok_or_else(|| {
+            LoweringError::InvalidExpression(format!(
+                "{name} window_ms must be a positive integer literal"
+            ))
+        })?;
+
+        let input_schema = resolve_root(&input)?.schema.clone();
+        let timestamp_id = resolve_column_ref(&timestamp_ref, &input_schema).map_err(|error| {
+            LoweringError::InvalidExpression(format!("{name} timestamp argument: {error}"))
+        })?;
+        if input_schema.time_index != Some(timestamp_id) {
+            return Err(LoweringError::InvalidExpression(format!(
+                "{name} timestamp argument must name the input schema's time-index column"
+            )));
+        }
+        let value_id = resolve_column_ref(&value_ref, &input_schema).map_err(|error| {
+            LoweringError::InvalidExpression(format!("{name} value argument: {error}"))
+        })?;
+        if value_id == timestamp_id
+            || !matches!(
+                input_schema.fields[value_id].dtype,
+                FieldDataType::Plain(DataType::Int64 | DataType::Float64)
+            )
+        {
+            return Err(LoweringError::InvalidExpression(format!(
+                "{name} value argument must name a numeric non-time column"
+            )));
+        }
+
+        let mut group_ids = Vec::with_capacity(agg.group_expr.len());
+        let mut group_refs = Vec::with_capacity(agg.group_expr.len());
+        for group in &agg.group_expr {
+            let group_ref = expr_to_group_ref(group)?;
+            let group_id = resolve_column_ref(&group_ref, &input_schema).map_err(|error| {
+                LoweringError::InvalidExpression(format!("{name} GROUP BY column: {error}"))
+            })?;
+            if group_id == timestamp_id || group_id == value_id {
+                return Err(LoweringError::InvalidExpression(format!(
+                    "{name} GROUP BY cannot contain its timestamp or value column"
+                )));
+            }
+            if group_ids.contains(&group_id) {
+                return Err(LoweringError::InvalidExpression(format!(
+                    "{name} GROUP BY contains the same resolved column more than once"
+                )));
+            }
+            group_ids.push(group_id);
+            group_refs.push(group_ref);
+        }
+        // Minimal series-identity contract without adding SQL-only metadata to
+        // the shared Schema: a declared row-unique key must contain the time
+        // index, and removing that index yields the complete series key. The
+        // GROUP BY must match that key exactly. A unique key that omits time is
+        // only row identity and proves nothing about time-series continuity.
+        let identifies_one_series = input_schema
+            .unique_keys
+            .iter()
+            .filter(|key| key.contains(&timestamp_id))
+            .any(|key| {
+                let mut series_key: Vec<_> = key
+                    .iter()
+                    .copied()
+                    .filter(|id| *id != timestamp_id)
+                    .collect();
+                series_key.sort_unstable();
+                series_key.dedup();
+                let mut grouped = group_ids.clone();
+                grouped.sort_unstable();
+                series_key == grouped
+            });
+        if !identifies_one_series {
+            return Err(LoweringError::InvalidExpression(format!(
+                "{name} GROUP BY must exactly match a declared series identity (a unique key without the time index)"
+            )));
+        }
+
+        let mut cols = vec![
+            ProjectItem {
+                alias: Some("ts".into()),
+                expr: Scalar::Column(timestamp_ref.clone()),
+            },
+            ProjectItem {
+                alias: Some("value".into()),
+                expr: Scalar::Column(value_ref.clone()),
+            },
+        ];
+        for group_ref in group_refs {
+            let group_name = named_ref(&group_ref).to_string();
+            cols.push(ProjectItem {
+                alias: Some(group_name),
+                expr: Scalar::Column(group_ref),
+            });
+        }
+        let child = Unresolved::Project {
+            cols,
+            qualifier: None,
+            child: Rc::new(input),
+        };
+        // The explicit window is a range selector over the series, the same
+        // shape PromQL's `rate(m[5m])` lowers to.
+        let child = Unresolved::TimeRange {
+            range: Duration::from_millis(window_ms),
+            kind: TimeRangeKind::Range,
+            child: Rc::new(child),
+        };
+        let intent = match name.as_str() {
+            "asap_rate" => AggIntent::Rate,
+            "asap_increase" => AggIntent::Increase,
+
+            _ => unreachable!("is_temporal_aggregate admitted {name}"),
+        };
+        Ok(Unresolved::Aggregate {
+            reduction: Reduction::PerEntity,
+            measures: vec![intent],
+            output_names: vec![],
+            filters: vec![],
+            having: None,
+            child: Rc::new(child),
+        })
+    }
+
+    /// `GROUP BY ROLLUP/CUBE/GROUPING SETS` — multi-level grouping (issue #118).
+    ///
+    /// One scan produces several grouping levels; `Aggregate.by` holds a single
+    /// key set. So each level becomes its own `Aggregate`, and the levels are
+    /// `Concat`ed. A level that omits a key still has to *emit* it — as `NULL`, per
+    /// SQL — so each branch is wrapped in a `Project` that reinstates the missing
+    /// keys as typed nulls and restores the canonical column order. That keeps
+    /// the branches union-compatible, which `Concat` requires (it derives its
+    /// schema from the first child).
+    ///
+    /// `Aggregate.child` is duplicated per level — the same trade
+    /// `histogram_quantiles` makes (#109); a future workload-level reuse pass
+    /// could hoist it back into a single producer.
+    ///
+    /// DataFusion's `__grouping_id` discriminator is dropped: it only exists to
+    /// tell a subtotal's `NULL` apart from a data `NULL`, which is observable
+    /// solely through `GROUPING(col)` — an aggregate this front end rejects.
+    fn lower_grouping_sets(
+        &self,
+        agg: &logical_expr::Aggregate,
+        gs: &logical_expr::GroupingSet,
+        input: Unresolved,
+    ) -> Result<Unresolved, LoweringError> {
+        // DataFusion normalizes every mixed form (`GROUP BY g, ROLLUP(d)`) into a
+        // single `GroupingSets`, so one grouping expression is the only shape.
+        if agg.group_expr.len() != 1 {
+            return Err(LoweringError::UnsupportedFeature(
+                "a grouping set alongside plain GROUP BY keys".into(),
+            ));
+        }
+
+        // `distinct_expr()` is ordered exactly like the aggregate's leading
+        // schema fields, which is the column order the enclosing Projection
+        // expects. The field after them is `__grouping_id`.
+        let distinct = gs.distinct_expr();
+        for e in &distinct {
+            if !matches!(unalias(e), Expr::Column(_)) {
+                return Err(LoweringError::UnsupportedFeature(format!(
+                    "non-column key inside a multi-level grouping: {e}"
+                )));
+            }
+        }
+        let keys: Vec<(String, DataType)> = agg
+            .schema
+            .fields()
+            .iter()
+            .take(distinct.len())
+            .map(|f| Ok((f.name().to_string(), arrow_to_dtype(f.data_type())?)))
+            .collect::<Result<_, LoweringError>>()?;
+
+        let output_names: Vec<String> = agg
+            .schema
+            .fields()
+            .iter()
+            .skip(distinct.len() + 1) // + `__grouping_id`
+            .map(|f| f.name().to_string())
+            .collect();
+
+        // Reducer arguments still materialize as derived columns (#110); the
+        // grouping keys are plain columns, so they only need carrying through.
+        let mut derived = DerivedCols::new(self);
+        for e in &distinct {
+            derived.passthrough(e)?;
+        }
+        let aggr_expr = agg
+            .aggr_expr
+            .iter()
+            .map(|e| derived.rewrite_agg(e))
+            .collect::<Result<Vec<_>, LoweringError>>()?;
+        let measures = aggr_expr
+            .iter()
+            .map(lower_agg_intent)
+            .collect::<Result<Vec<_>, LoweringError>>()?;
+        let input = derived.wrap(input)?;
+
+        let branches = expand_grouping_set(gs)
+            .iter()
+            .map(|level| {
+                let level_keys = distinct
+                    .iter()
+                    .filter(|e| level.contains(e))
+                    .map(|e| expr_to_group_ref(e))
+                    .collect::<Result<Vec<_>, LoweringError>>()?;
+                let aggregate = Unresolved::Aggregate {
+                    reduction: Reduction::Reduce(GroupKeys::by(level_keys)),
+                    measures: measures.clone(),
+                    output_names: output_names.clone(),
+                    filters: vec![],
+                    having: None,
+                    child: Rc::new(input.clone()),
+                };
+                // Reinstate omitted keys as typed nulls, in canonical order.
+                let cols = keys
+                    .iter()
+                    .zip(&distinct)
+                    .map(|((name, dtype), e)| ProjectItem {
+                        alias: Some(name.clone()),
+                        expr: if level.contains(e) {
+                            Scalar::Column(ColumnRef::Named(name.clone()))
+                        } else {
+                            Scalar::Cast {
+                                expr: Box::new(Scalar::Literal(ScalarValue::Null)),
+                                to: dtype.clone(),
+                                try_cast: false,
+                            }
+                        },
+                    })
+                    .chain(output_names.iter().map(|n| ProjectItem {
+                        alias: Some(n.clone()),
+                        expr: Scalar::Column(ColumnRef::Named(n.clone())),
+                    }))
+                    .collect();
+                Ok(Unresolved::Project {
+                    cols,
+                    qualifier: None,
+                    child: Rc::new(aggregate),
+                })
+            })
+            .collect::<Result<Vec<_>, LoweringError>>()?;
+
+        // No discriminator asserted here today (issue #228): DataFusion's own
+        // `__grouping_id` would be the natural one, but this front end
+        // already discards it (see above — `GROUPING()` itself is rejected),
+        // so there is no distinct-per-branch column available to name yet.
+        // `Unresolved::concat` keeps `output_schema`'s default (drop
+        // `unique_keys` entirely). See
+        // `docs/design_docs/concat-unique-keys-decision.md`.
+        Ok(Unresolved::concat(branches))
+    }
+
+    fn lower_sort(&self, sort: &logical_expr::Sort) -> Result<Unresolved, LoweringError> {
+        // A count-ranked `ORDER BY … LIMIT k` is the frequency heavy-hitter the
+        // `TopK` intent represents, but that promotion now happens in the shared
+        // `canonicalize` pass (issue #34) — the same one both front ends run —
+        // so SQL emits a plain `Sort` (+ `Limit`) here and lets canonicalization
+        // recognise the count-ranked shape positionally. This removes the gate's
+        // alias blind spot (#20).
+        let keys = sort
+            .expr
+            .iter()
+            .map(|s| {
+                self.lower_expr(&s.expr).map(|expr| SortKey {
+                    expr,
+                    ascending: s.asc,
+                    nulls_first: s.nulls_first,
+                })
+            })
+            .collect::<Result<Vec<_>, _>>()?;
+        Ok(Unresolved::Sort {
+            keys,
+            // SQL `ORDER BY` is a global sort; per-group ranking would come from a
+            // window function (`SQLWindowFunc`), not a bare Sort.
+            partition_by: GroupKeys::none(),
+            child: Rc::new(self.lower_plan(&sort.input)?),
+        })
+    }
+
+    fn lower_limit(&self, limit: &logical_expr::Limit) -> Result<Unresolved, LoweringError> {
+        // Count-ranked `LIMIT k` over a `Sort` is promoted to the heavy-hitter
+        // `TopK` by the shared `canonicalize` pass (issue #34), not here.
+        Ok(Unresolved::Limit {
+            // No (literal) fetch is offset-only.
+            n: eval_fetch(&limit.fetch),
+            offset: eval_fetch(&limit.skip).unwrap_or(0),
+            partition_by: GroupKeys::none(),
+            child: Rc::new(self.lower_plan(&limit.input)?),
+        })
+    }
+}
+
+/// A deliberately explicit marker accepted only in a projection of planning
+/// SQL. The marker describes a relation operator, so it is removed rather than
+/// lowered to the ordinary scalar `FunctionCall` variant.
+enum PlanningBridge {
+    PromqlSubquery {
+        range: Duration,
+        resolution: Duration,
+    },
+    HistogramQuantile {
+        q: f64,
+    },
+}
+
+fn planning_bridge(
+    projection: &logical_expr::Projection,
+) -> Result<Option<PlanningBridge>, LoweringError> {
+    let mut found = None;
+    for expr in &projection.expr {
+        let Expr::ScalarFunction(call) = unalias(expr) else {
+            continue;
+        };
+        let name = call.func.name().to_ascii_lowercase();
+        let bridge = match name.as_str() {
+            "asap_promql_subquery" => {
+                let [range, resolution] = call.args.as_slice() else {
+                    return Err(LoweringError::InvalidExpression(
+                        "asap_promql_subquery requires (range_ms, resolution_ms)".into(),
+                    ));
+                };
+                let range = positive_millis_literal(range, "range_ms")?;
+                let resolution = positive_millis_literal(resolution, "resolution_ms")?;
+                PlanningBridge::PromqlSubquery { range, resolution }
+            }
+            "asap_histogram_quantile" => {
+                let [q] = call.args.as_slice() else {
+                    return Err(LoweringError::InvalidExpression(
+                        "asap_histogram_quantile requires one literal quantile".into(),
+                    ));
+                };
+                let q = float_literal(q).ok_or_else(|| {
+                    LoweringError::InvalidExpression(
+                        "asap_histogram_quantile quantile must be a numeric literal".into(),
+                    )
+                })?;
+                if !q.is_finite() || !(0.0..=1.0).contains(&q) {
+                    return Err(LoweringError::InvalidExpression(format!(
+                        "asap_histogram_quantile quantile must be finite and in [0,1], got {q}"
+                    )));
+                }
+                PlanningBridge::HistogramQuantile { q }
+            }
+            _ => continue,
+        };
+        if found.is_some() {
+            return Err(LoweringError::InvalidExpression(
+                "a planning projection may contain only one asap_* relation marker".into(),
+            ));
+        }
+        found = Some(bridge);
+    }
+    if matches!(found, Some(PlanningBridge::HistogramQuantile { .. })) && projection.expr.len() != 1
+    {
+        return Err(LoweringError::InvalidExpression(
+            "asap_histogram_quantile must be the projection's only expression".into(),
+        ));
+    }
+    Ok(found)
+}
+
+/// Rebuild the SQL projection around the relation sampled by the temporal
+/// marker. The marker's alias names the existing child column that occupies
+/// its output slot (`... asap_promql_subquery(...) AS value ...`). This makes
+/// the bridge schema-preserving without silently retaining columns that SQL
+/// projected away.
+impl SqlLowerer<'_> {
+    fn temporal_bridge_projection(
+        &self,
+        projection: &logical_expr::Projection,
+        child: Unresolved,
+    ) -> Result<Unresolved, LoweringError> {
+        let cols = projection
+            .expr
+            .iter()
+            .map(|expr| {
+                if let Expr::ScalarFunction(call) = unalias(expr) {
+                    if call
+                        .func
+                        .name()
+                        .eq_ignore_ascii_case("asap_promql_subquery")
+                    {
+                        let Expr::Alias(alias) = expr else {
+                            return Err(LoweringError::InvalidExpression(
+                                "asap_promql_subquery must have an alias naming its child value column"
+                                    .into(),
+                            ));
+                        };
+                        return Ok(ProjectItem {
+                            expr: Scalar::Column(ColumnRef::Named(alias.name.clone())),
+                            alias: Some(alias.name.clone()),
+                        });
+                    }
+                }
+                match expr {
+                    Expr::Alias(alias) => Ok(ProjectItem {
+                        expr: self.lower_expr(&alias.expr)?,
+                        alias: Some(alias.name.clone()),
+                    }),
+                    other => Ok(ProjectItem {
+                        expr: self.lower_expr(other)?,
+                        alias: None,
+                    }),
+                }
+            })
+            .collect::<Result<Vec<_>, LoweringError>>()?;
+        Ok(Unresolved::Project {
+            cols,
+            qualifier: None,
+            child: Rc::new(child),
+        })
+    }
+}
+
+fn positive_millis_literal(expr: &Expr, argument: &str) -> Result<Duration, LoweringError> {
+    let millis = match unalias(expr) {
+        Expr::Literal(DfScalarValue::Int64(Some(value))) if *value > 0 => *value as u64,
+        Expr::Literal(DfScalarValue::UInt64(Some(value))) if *value > 0 => *value,
+        Expr::Literal(DfScalarValue::Int32(Some(value))) if *value > 0 => *value as u64,
+        other => {
+            return Err(LoweringError::InvalidExpression(format!(
+                "{argument} must be a positive integer millisecond literal, got {other}"
+            )))
+        }
+    };
+    Ok(Duration::from_millis(millis))
+}
+
+fn float_literal(expr: &Expr) -> Option<f64> {
+    match unalias(expr) {
+        Expr::Literal(DfScalarValue::Float64(Some(value))) => Some(*value),
+        Expr::Literal(DfScalarValue::Float32(Some(value))) => Some(*value as f64),
+        Expr::Literal(DfScalarValue::Int64(Some(value))) => Some(*value as f64),
+        Expr::Literal(DfScalarValue::UInt64(Some(value))) => Some(*value as f64),
+        Expr::Literal(DfScalarValue::Int32(Some(value))) => Some(*value as f64),
+        _ => None,
+    }
+}
+
+// ── ClickHouse-builtin compatibility, taught to DataFusion itself ──────────────
+//
+// Generalized over `asap_sql_function_catalog::CLICKHOUSE_BUILTINS` (issue
+// #225): adding support for one more ClickHouse-only builtin DataFusion
+// doesn't know at all is a catalog data entry (name, arity, `RewriteKind`)
+// plus, only if its rewrite target is a genuinely new shape, one match arm
+// in `ClickHouseBuiltinRewrite::rewrite` below — never a new stub-UDAF
+// constructor or a new `FunctionRewrite`-implementing type. `uniqExact`
+// (issue #221) and `countIf` both go through this one mechanism.
+
+/// A stub `AggregateUDF` for one `CLICKHOUSE_BUILTINS` entry, registered
+/// purely so DataFusion's planner can resolve the function name during
+/// `SqlToRel` conversion (it errors on an unknown function before a rewrite
+/// ever gets a chance to run). Every call site is replaced by
+/// `ClickHouseBuiltinRewrite` — via the `Analyzer` `lower()` runs after
+/// parsing — before physical planning could ever ask this UDAF for an
+/// `Accumulator`, so `accumulator` is unreachable for every catalog entry.
+fn clickhouse_builtin_stub_udaf(name: &'static str, arity: Arity) -> AggregateUDF {
+    AggregateUDF::from(SimpleAggregateUDF::new_with_signature(
+        name,
+        arity_to_signature(arity),
+        ArrowDataType::Int64,
+        Arc::new(move |_| {
+            // ponytail: dead code by construction (see doc comment above) —
+            // a real accumulator would just reimplement whatever native
+            // shape `ClickHouseBuiltinRewrite` rewrites this call to.
+            unimplemented!(
+                "{name} has no accumulator: every call site is rewritten to a native \
+                 DataFusion aggregate before physical planning"
+            )
+        }),
+        vec![],
+    ))
+}
+
+/// A catalog [`Arity`] as the DataFusion `Signature` a stub UDAF/UDF is
+/// registered with — shared by the aggregate stub above and the scalar stub
+/// below, since neither wants to model per-argument types, only how many
+/// arguments a call may take.
+fn arity_to_signature(arity: Arity) -> Signature {
+    match arity {
+        Arity::Exact(n) => Signature::any(n, Volatility::Immutable),
+        Arity::Range { min, max } => Signature::one_of(
+            (min..=max).map(TypeSignature::Any).collect(),
+            Volatility::Immutable,
+        ),
+    }
+}
+
+// ── ClickHouse scalar-builtin compatibility ─────────────────────────────────
+//
+// The scalar counterpart of the aggregate mechanism above, but simpler:
+// `asap_sql_function_catalog::CLICKHOUSE_SCALAR_BUILTINS` carries no
+// `RewriteKind`, because a scalar call needs none. Unlike an aggregate call
+// (which must become a real `AggIntent`, hence the rewrite to a native
+// DataFusion aggregate shape `lower_agg_intent` can classify), a scalar
+// function call in this IR is already deliberately opaque —
+// `SqlLowerer::lower_expr`'s `Expr::ScalarFunction` arm lowers *any*
+// scalar call generically to `UnresolvedScalar::FunctionCall { name, args }`, with
+// zero name-specific logic. So teaching DataFusion's planner to accept a
+// ClickHouse scalar builtin's name — a stub `ScalarUDF`, registered below —
+// is the entire fix; the existing generic lowering already does the rest.
+
+/// A stub `ScalarUDF` for one `CLICKHOUSE_SCALAR_BUILTINS` entry, registered
+/// purely so DataFusion's planner can resolve the function name during
+/// `SqlToRel` conversion (it errors on an unknown function otherwise), and so
+/// it can keep building the surrounding expression's type from a plausible
+/// return type. Unlike `clickhouse_builtin_stub_udaf`, no `FunctionRewrite`
+/// ever fires for these — the call survives to `lower_plan` as-is and lowers
+/// through the generic `Expr::ScalarFunction` arm — so `invoke`/`invoke_batch`
+/// (left at their default, which returns a `NotImplemented` `DataFusionError`)
+/// are unreachable for every catalog entry: this front end only ever uses
+/// DataFusion for planning/type-checking, never physical execution.
+fn clickhouse_scalar_builtin_stub_udf(name: &'static str, arity: Arity) -> ScalarUDF {
+    ScalarUDF::from(ClickHouseScalarBuiltinStub {
+        name,
+        signature: arity_to_signature(arity),
+        return_type: clickhouse_scalar_builtin_return_type(name),
+    })
+}
+
+/// A plausible Arrow return type for one `CLICKHOUSE_SCALAR_BUILTINS` entry —
+/// just precise enough that DataFusion's planner can keep building the type
+/// of whatever expression the call sits inside (e.g. a `WHERE` predicate
+/// wants `Boolean`), not a claim about ClickHouse's actual return type.
+/// Real function typing happens downstream, at post-ASAP binding.
+fn clickhouse_scalar_builtin_return_type(name: &str) -> ArrowDataType {
+    match name {
+        // Array(String) in ClickHouse; a plain `Utf8` element list is close
+        // enough for planning purposes here.
+        "splitbychar" => ArrowDataType::List(Arc::new(datafusion::arrow::datatypes::Field::new(
+            "item",
+            ArrowDataType::Utf8,
+            true,
+        ))),
+        "todate" => ArrowDataType::Date32,
+        // ClickHouse returns UInt8 (0/1), but every corpus use is a boolean
+        // predicate — `Boolean` keeps that context type-checking.
+        "match" | "startswith" => ArrowDataType::Boolean,
+        "tostartofhour"
+        | "tostartofweek"
+        | "tostartofminute"
+        | "tostartoffiveminutes"
+        | "tostartofinterval" => {
+            ArrowDataType::Timestamp(datafusion::arrow::datatypes::TimeUnit::Millisecond, None)
+        }
+        // 1-based match position, 0 if not found.
+        "positioncaseinsensitive" => ArrowDataType::UInt64,
+        // Relation markers are removed by `lower_projection`; Float64 merely
+        // lets DataFusion type the temporary SELECT list.
+        "asap_promql_subquery" | "asap_histogram_quantile" => ArrowDataType::Float64,
+        other => unreachable!(
+            "{other}: every CLICKHOUSE_SCALAR_BUILTINS entry must have a return type listed here"
+        ),
+    }
+}
+
+/// A stub `ScalarUDFImpl` carrying only what DataFusion's planner needs:
+/// name, arity-only [`Signature`], and a fixed return type. `invoke`/
+/// `invoke_batch` are left at their trait defaults (a `NotImplemented`
+/// `DataFusionError`) — see [`clickhouse_scalar_builtin_stub_udf`]'s doc for
+/// why that is unreachable in practice.
+#[derive(Debug)]
+struct ClickHouseScalarBuiltinStub {
+    name: &'static str,
+    signature: Signature,
+    return_type: ArrowDataType,
+}
+
+impl ScalarUDFImpl for ClickHouseScalarBuiltinStub {
+    fn as_any(&self) -> &dyn std::any::Any {
+        self
+    }
+
+    fn name(&self) -> &str {
+        self.name
+    }
+
+    fn signature(&self) -> &Signature {
+        &self.signature
+    }
+
+    fn return_type(
+        &self,
+        _arg_types: &[ArrowDataType],
+    ) -> datafusion::common::Result<ArrowDataType> {
+        Ok(self.return_type.clone())
+    }
+}
+
+// ── ClickHouse window-builtin compatibility ─────────────────────────────────
+//
+// The window counterpart of the scalar mechanism above: a stub `WindowUDF`
+// registered purely so DataFusion's planner accepts the call name during
+// `SqlToRel` conversion. No rewrite step follows — `lower_window_func_kind`
+// already maps each `asap_sql_function_catalog::CLICKHOUSE_WINDOW_BUILTINS`
+// name directly to its own `WindowFuncKind` variant (issue #267).
+
+/// A stub `WindowUDF` for one `CLICKHOUSE_WINDOW_BUILTINS` entry, registered
+/// purely so DataFusion's planner can resolve the function name inside an
+/// `OVER (...)` clause. This front end only ever uses DataFusion for
+/// planning/type-checking, never physical execution, so
+/// `partition_evaluator` (which physical execution alone would call) is
+/// unreachable in practice.
+fn clickhouse_window_builtin_stub_udwf(name: &'static str, arity: Arity) -> WindowUDF {
+    WindowUDF::from(ClickHouseWindowBuiltinStub {
+        name,
+        signature: arity_to_signature(arity),
+    })
+}
+
+/// A stub `WindowUDFImpl` carrying only what DataFusion's planner needs:
+/// name, arity-only [`Signature`], and a field type derived from the first
+/// argument (matching `lag`/`lead`'s own "output type = input type"
+/// behavior). `partition_evaluator` is left `unimplemented!()` — see
+/// [`clickhouse_window_builtin_stub_udwf`]'s doc for why that is unreachable.
+#[derive(Debug)]
+struct ClickHouseWindowBuiltinStub {
+    name: &'static str,
+    signature: Signature,
+}
+
+impl WindowUDFImpl for ClickHouseWindowBuiltinStub {
+    fn as_any(&self) -> &dyn std::any::Any {
+        self
+    }
+
+    fn name(&self) -> &str {
+        self.name
+    }
+
+    fn signature(&self) -> &Signature {
+        &self.signature
+    }
+
+    fn field(&self, field_args: WindowUDFFieldArgs) -> datafusion::common::Result<Field> {
+        let dtype = field_args.get_input_type(0).unwrap_or(ArrowDataType::Null);
+        Ok(Field::new(field_args.name(), dtype, true))
+    }
+
+    fn partition_evaluator(
+        &self,
+        _partition_evaluator_args: PartitionEvaluatorArgs,
+    ) -> datafusion::common::Result<Box<dyn PartitionEvaluator>> {
+        let name = self.name;
+        unimplemented!(
+            "{name} has no partition evaluator: this front end never runs DataFusion's \
+             physical planner, only SqlToRel + the unoptimized LogicalPlan"
+        )
+    }
+}
+
+/// Rewrites every `asap_sql_function_catalog::CLICKHOUSE_BUILTINS` call to
+/// the native DataFusion aggregate shape its entry's `RewriteKind` names —
+/// so a ClickHouse-only builtin DataFusion doesn't know at all becomes an
+/// ordinary DataFusion aggregate before the plan ever reaches
+/// `lower_agg_intent`, which needs no ClickHouse-specific name of its own.
+#[derive(Debug)]
+struct ClickHouseBuiltinRewrite;
+
+impl FunctionRewrite for ClickHouseBuiltinRewrite {
+    fn name(&self) -> &str {
+        "clickhouse builtin -> native DataFusion aggregate"
+    }
+
+    fn rewrite(
+        &self,
+        expr: Expr,
+        _schema: &DFSchema,
+        _config: &ConfigOptions,
+    ) -> datafusion::common::Result<Transformed<Expr>> {
+        let Expr::AggregateFunction(f) = expr else {
+            return Ok(Transformed::no(expr));
+        };
+        let Some(builtin) = asap_sql_function_catalog::lookup_clickhouse_builtin(f.func.name())
+        else {
+            return Ok(Transformed::no(Expr::AggregateFunction(f)));
+        };
+        let rewritten = match builtin.rewrite {
+            // No native DataFusion shape to become — leave the call exactly
+            // as DataFusion's planner parsed it. `lower_agg_intent` handles
+            // the ClickHouse name (`argMax`/`argMin`) directly (issue #232).
+            RewriteKind::PassThrough => return Ok(Transformed::no(Expr::AggregateFunction(f))),
+            // `f(args...)` -> `count(args...) DISTINCT` — `lower_agg_intent`
+            // already maps `count` + `DISTINCT` to `AggIntent::Cardinality`,
+            // at whatever arity the call carries.
+            RewriteKind::CountDistinct => AggregateFunction::new_udf(
+                count_udaf(),
+                f.args,
+                true,
+                f.filter,
+                f.order_by,
+                f.null_treatment,
+            ),
+            // `f(cond)` -> `sum(CASE WHEN cond THEN 1 ELSE 0 END)` — see
+            // `RewriteKind::CountIfToSum`'s doc; moving the `-If` family onto
+            // `Aggregate.filters` (issue #466) is a follow-up.
+            RewriteKind::CountIfToSum => {
+                let cond = f.args.into_iter().next().expect(
+                    "countif's stub signature fixes its arity at 1 -- the planner \
+                     already rejected any other argument count before this rewrite runs",
+                );
+                let indicator = Expr::Case(Case::new(
+                    None,
+                    vec![(Box::new(cond), Box::new(lit(1i64)))],
+                    Some(Box::new(lit(0i64))),
+                ));
+                AggregateFunction::new_udf(
+                    sum_udaf(),
+                    vec![indicator],
+                    false,
+                    f.filter,
+                    f.order_by,
+                    f.null_treatment,
+                )
+            }
+        };
+        Ok(Transformed::yes(Expr::AggregateFunction(rewritten)))
+    }
+}
+
+// ── Aggregate / group-key helpers ───────────────────────────────────────────────
+
+/// The row predicate one aggregate call carries (issue #466): its explicit
+/// `FILTER (WHERE p)`, plus — for a plain `count(expr)`, which canonical
+/// `AggIntent::Count` lowers to a row count that never looks at `expr` — the
+/// NULL-skipping SQL gives it. `count(CASE WHEN p THEN x END)` is the
+/// conditional-count idiom, so it becomes `p [AND x IS NOT NULL]` rather
+/// than the opaque `CASE … IS NOT NULL`; any other nullable argument becomes
+/// `expr IS NOT NULL`. `None` when the call updates on every row.
+fn measure_filter(expr: &Expr, input: &DFSchema) -> Result<Option<Expr>, LoweringError> {
+    let Expr::AggregateFunction(agg_fn) = unalias(expr) else {
+        return Ok(None);
+    };
+    let mut conjuncts: Vec<Expr> = agg_fn.filter.iter().map(|f| (**f).clone()).collect();
+    let counts_rows = agg_fn.func.name().eq_ignore_ascii_case("count") && !agg_fn.distinct;
+    if counts_rows {
+        for argument in &agg_fn.args {
+            let nullable = argument
+                .nullable(input)
+                .map_err(|error| LoweringError::UnsupportedFeature(error.to_string()))?;
+            if !nullable {
+                continue;
+            }
+            match conditional_count_arm(argument) {
+                Some((when, then)) => {
+                    conjuncts.push(when.clone());
+                    if then
+                        .nullable(input)
+                        .map_err(|error| LoweringError::UnsupportedFeature(error.to_string()))?
+                    {
+                        conjuncts.push(then.clone().is_not_null());
+                    }
+                }
+                None => conjuncts.push(argument.clone().is_not_null()),
+            }
+        }
+    }
+    Ok(conjuncts.into_iter().reduce(Expr::and))
+}
+
+/// `CASE WHEN p THEN x END` (searched, one arm, no `ELSE` or `ELSE NULL`)
+/// as `(p, x)`.
+fn conditional_count_arm(expr: &Expr) -> Option<(&Expr, &Expr)> {
+    let Expr::Case(case) = unalias(expr) else {
+        return None;
+    };
+    if case.expr.is_some() {
+        return None;
+    }
+    let else_is_null = match case.else_expr.as_deref() {
+        None => true,
+        Some(Expr::Literal(value)) => value.is_null(),
+        Some(_) => false,
+    };
+    if !else_is_null {
+        return None;
+    }
+    let [(when, then)] = case.when_then_expr.as_slice() else {
+        return None;
+    };
+    Some((when, then))
+}
+
+/// Map a DataFusion aggregate expression directly to the canonical
+/// [`AggIntent<ColumnRef>`] — issue #179's "dedicated function → canonical
+/// intent directly" front-end construction, no `AggFunc` intermediate. The
+/// name → semantic mapping itself lives in `asap_sql_function_catalog`
+/// (issue #225) as flat data (`NATIVE_FUNCTIONS`); what stays here is
+/// call-site logic that isn't a function of the name alone — the DISTINCT
+/// modifier rule, the "reducer argument must be a bare column" rule
+/// (`reducer_col`), φ extraction from a literal argument, and the ambient
+/// `AccuracyTarget`. `resolve_root` resolves `col` to a positional
+/// `ColumnId`; the output name (DataFusion's own, e.g.
+/// `"sum(metrics.bytes)"`) is threaded separately as `Aggregate.output_names`,
+/// not carried here.
+fn lower_agg_intent(expr: &Expr) -> Result<AggIntent<ColumnRef>, LoweringError> {
+    match expr {
+        Expr::Alias(a) => lower_agg_intent(&a.expr),
+        Expr::AggregateFunction(agg_fn) => {
+            let name = agg_fn.func.name().to_lowercase();
+            // ClickHouse's row-selecting `argMax`/`argMin` — `RewriteKind::
+            // PassThrough` in the catalog, so the call reaches here under its
+            // own name rather than a native DataFusion aggregate. Handled
+            // before the `NATIVE_FUNCTIONS` lookup below since neither name
+            // is in that table (issue #232).
+            if let Some(intent) = lower_arg_selector(&name, &agg_fn.args)? {
+                return Ok(intent);
+            }
+            let semantic = asap_sql_function_catalog::lookup_native(&name)
+                .ok_or_else(|| LoweringError::UnsupportedAggregate(name.clone()))?;
+            // The canonical intent algebra has no DISTINCT modifier for the
+            // value reducers; only
+            // COUNT(DISTINCT) maps (to Cardinality). Reject DISTINCT elsewhere
+            // rather than silently lowering `SUM(DISTINCT x)` as `SUM(x)`.
+            if agg_fn.distinct && !matches!(semantic, AggSemantic::Count) {
+                return Err(LoweringError::UnsupportedAggregate(format!(
+                    "DISTINCT {name}"
+                )));
+            }
+            // Value reducers (`reducer_col`) require a real column — `SUM(a*b)`
+            // is rejected, not silently reduced over a probe column. Quantile
+            // and CountDistinct reduce a column too, so they take the same path:
+            // `col` is `Option<ColumnId>` once resolved, where `None` means "the
+            // PromQL sample value", which a SQL query never has. Taking an
+            // expression here would set `col: None` and silently drop it (#115).
+            let col = |args: &[Expr]| -> Result<Option<ColumnRef>, LoweringError> {
+                reducer_col(&name, args).map(Some)
+            };
+            Ok(match semantic {
+                AggSemantic::Correlation => {
+                    if agg_fn.order_by.is_some() || agg_fn.null_treatment.is_some() {
+                        return Err(LoweringError::UnsupportedAggregate(
+                            "corr with ORDER BY or explicit null treatment".into(),
+                        ));
+                    }
+                    let [left, right] = agg_fn.args.as_slice() else {
+                        return Err(LoweringError::UnsupportedAggregate(
+                            "corr requires two arguments".into(),
+                        ));
+                    };
+                    AggIntent::PearsonCorr {
+                        left: expr_to_group_ref(left)?,
+                        right: expr_to_group_ref(right)?,
+                    }
+                }
+                // Every argument reaches the intent: `COUNT(DISTINCT a, b)`
+                // counts distinct *tuples*, which is a different quantity from
+                // the distinct count of either column.
+                AggSemantic::Count if agg_fn.distinct => match agg_fn.args.as_slice() {
+                    // DataFusion's planner rejects a bare `COUNT(DISTINCT)`
+                    // before lowering. Guarded anyway: an empty `cols` is the
+                    // PromQL sample-value convention, which SQL never has.
+                    [] => {
+                        return Err(LoweringError::UnsupportedAggregate(
+                            "COUNT(DISTINCT) without an argument".into(),
+                        ))
+                    }
+                    args => AggIntent::Cardinality {
+                        cols: args.iter().map(distinct_col).collect::<Result<_, _>>()?,
+                        accuracy: current_accuracy(),
+                    },
+                },
+                AggSemantic::Count => AggIntent::Count {
+                    accuracy: current_accuracy(),
+                },
+                AggSemantic::Sum => AggIntent::Sum {
+                    col: col(&agg_fn.args)?,
+                },
+                AggSemantic::Min => AggIntent::Min {
+                    col: col(&agg_fn.args)?,
+                },
+                AggSemantic::Max => AggIntent::Max {
+                    col: col(&agg_fn.args)?,
+                },
+                AggSemantic::Avg => AggIntent::Avg {
+                    col: col(&agg_fn.args)?,
+                },
+                AggSemantic::StdDev { population } => AggIntent::StdDev {
+                    col: col(&agg_fn.args)?,
+                    population,
+                },
+                AggSemantic::Variance { population } => AggIntent::Variance {
+                    col: col(&agg_fn.args)?,
+                    population,
+                },
+                // `fixed_q = Some(0.5)` is `median`/`approx_median`. As with
+                // `approx_distinct` and `approx_percentile_cont`, the
+                // `approx_` prefix does not force an approximation: the
+                // sketch-vs-exact choice is the AccuracyTarget's (see
+                // `plan::boundary`), so both spellings share one intent
+                // (#111).
+                AggSemantic::Quantile { fixed_q } => AggIntent::Quantile {
+                    col: col(&agg_fn.args)?,
+                    q: match fixed_q {
+                        Some(q) => q,
+                        None => extract_percentile_q(&agg_fn.args)?,
+                    },
+                    accuracy: current_accuracy(),
+                },
+                AggSemantic::Cardinality => AggIntent::Cardinality {
+                    cols: vec![reducer_col(&name, &agg_fn.args)?],
+                    accuracy: current_accuracy(),
+                },
+            })
+        }
+        _ => Err(LoweringError::UnsupportedAggregate(format!(
+            "measure is not an aggregate function call: {expr}"
+        ))),
+    }
+}
+
+fn temporal_aggregate_name(expr: &Expr) -> Option<String> {
+    let Expr::AggregateFunction(call) = unalias(expr) else {
+        return None;
+    };
+    let name = call.func.name().to_lowercase();
+    matches!(name.as_str(), "asap_rate" | "asap_increase").then_some(name)
+}
+
+fn is_temporal_aggregate(expr: &Expr) -> bool {
+    temporal_aggregate_name(expr).is_some()
+}
+
+fn is_temporal_output_column(expr: &Expr) -> bool {
+    let Expr::Column(col) = unalias(expr) else {
+        return false;
+    };
+    let name = col.name.to_lowercase();
+    ["asap_rate(", "asap_increase("]
+        .iter()
+        .any(|prefix| name.starts_with(prefix))
+}
+
+fn plan_has_temporal_aggregate(plan: &LogicalPlan) -> bool {
+    match plan {
+        LogicalPlan::Aggregate(agg) => agg.aggr_expr.iter().any(is_temporal_aggregate),
+        LogicalPlan::Filter(filter) => plan_has_temporal_aggregate(&filter.input),
+        LogicalPlan::SubqueryAlias(alias) => plan_has_temporal_aggregate(&alias.input),
+        _ => false,
+    }
+}
+
+fn named_ref(col: &ColumnRef) -> &str {
+    match col {
+        ColumnRef::Named(name) | ColumnRef::Qualified { name, .. } => name,
+        ColumnRef::SampleValue | ColumnRef::Wildcard => {
+            unreachable!("reducer_col only returns named column references")
+        }
+    }
+}
+
+fn scalar_positive_u64(value: &DfScalarValue) -> Option<u64> {
+    match value {
+        DfScalarValue::Int64(Some(v)) if *v > 0 => Some(*v as u64),
+        DfScalarValue::Int32(Some(v)) if *v > 0 => Some(*v as u64),
+        DfScalarValue::UInt64(Some(v)) if *v > 0 => Some(*v),
+        DfScalarValue::UInt32(Some(v)) if *v > 0 => Some(*v as u64),
+        _ => None,
+    }
+}
+
+/// ClickHouse's row-selecting `argMax(arg, val)` / `argMin(arg, val)` —
+/// "return `arg`'s value from the row where `val` is maximal/minimal".
+/// `Some(name)` for `"argmax"`/`"argmin"`, `None` for every other name (the
+/// caller falls through to the ordinary `NATIVE_FUNCTIONS` path).
+///
+/// Unlike every existing `AggIntent` reducer (`Sum`/`Min`/`Max`/`Avg`/…),
+/// which folds *one* column to a value derived from itself, this is a
+/// two-column, row-selecting aggregate: it returns a *different* column's
+/// value, selected by which row maximizes/minimizes a second column. No
+/// existing `AggIntent` shape fits, and — per its own doc comment's
+/// "core only grows for intents ≥2 deployment models actually use" bar —
+/// a repo-wide search (PromQL front end, the other SQL dialects, docs) found
+/// no second deployment model wanting this shape, so this lowers to
+/// `AggIntent::Extension` rather than earning a first-class `ArgMax`/`ArgMin`
+/// core variant (issue #232). Core treats `Extension` opaquely: both columns
+/// are kept only as validated bare-column names in `payload` (`reducer_col`'s
+/// same "no expression arguments" rule, issue #115) — they are **not** run
+/// through `resolve_agg_intent`'s positional `ColumnRef` -> `ColumnId`
+/// binding the way a real reducer's `col` is, since `Extension` carries no
+/// typed column field for core to resolve. Shared `arg_selector_columns` validates
+/// and resolves those names during aggregate schema derivation, preserving the
+/// selected argument's type and nullability for downstream exact execution.
+///
+/// DerivedCols preserves both bare-column arguments when grouping expressions
+/// introduce an intermediate Project. Shared aggregate schema derivation resolves
+/// the payload and preserves the selected argument's type and nullability.
+fn lower_arg_selector(
+    name: &str,
+    args: &[Expr],
+) -> Result<Option<AggIntent<ColumnRef>>, LoweringError> {
+    let ext_kind = match name {
+        "argmax" => "arg_max",
+        "argmin" => "arg_min",
+        _ => return Ok(None),
+    };
+    let [arg, val] = args else {
+        unreachable!(
+            "{name}'s stub signature (asap_sql_function_catalog::CLICKHOUSE_BUILTINS) fixes \
+             its arity at 2 -- the planner already rejected any other argument count before \
+             lower_agg_intent runs"
+        );
+    };
+    let arg_col = reducer_col(name, std::slice::from_ref(arg))?;
+    let val_col = reducer_col(name, std::slice::from_ref(val))?;
+    Ok(Some(AggIntent::Extension {
+        ext_kind: ext_kind.to_string(),
+        payload: serde_json::json!({ "arg_col": arg_col, "val_col": val_col }),
+    }))
+}
+
+/// Fold `pred` directly onto `child.predicates` when `child` is a bare `Scan`
+/// (a `WHERE` directly over a table), otherwise wrap it in an ordinary
+/// `Filter` — canonical's invariant that a `Filter` never sits directly over a
+/// `Scan`. A front end emitting the canonical shape directly is responsible
+/// for maintaining that invariant itself (issue #179).
+fn filter_or_fold(pred: Scalar, child: Unresolved) -> Unresolved {
+    match child {
+        Unresolved::Scan {
+            source,
+            mut predicates,
+            schema,
+        } => {
+            predicates.push(Predicate(pred));
+            Unresolved::Scan {
+                source,
+                predicates,
+                schema,
+            }
+        }
+        other => Unresolved::Filter {
+            pred: Predicate(pred),
+            child: Rc::new(other),
+        },
+    }
+}
+
+/// Flatten a top-level `AND` chain into its conjuncts.
+fn split_conjunction<'a>(expr: &'a Expr, out: &mut Vec<&'a Expr>) {
+    match expr {
+        Expr::BinaryExpr(b) if b.op == logical_expr::Operator::And => {
+            split_conjunction(&b.left, out);
+            split_conjunction(&b.right, out);
+        }
+        other => out.push(other),
+    }
+}
+
+/// Whether `expr` reads another operator anywhere inside it (`EXISTS`,
+/// `IN (…)`, a scalar subquery).
+fn reads_subquery(expr: &Expr) -> bool {
+    expr.exists(|e| {
+        Ok(matches!(
+            e,
+            Expr::ScalarSubquery(_) | Expr::InSubquery(_) | Expr::Exists(_)
+        ))
+    })
+    .expect("the predicate never fails")
+}
+
+/// Re-`AND` the conjuncts, or `None` when there are none left.
+fn rebuild_conjunction(conjuncts: &[&Expr]) -> Option<Expr> {
+    conjuncts
+        .iter()
+        .map(|e| (*e).clone())
+        .reduce(|acc, e| acc.and(e))
+}
+
+/// Split a correlated subquery's plan into `(uncorrelated plan, correlation)`.
+///
+/// The correlation is the conjunction of the filter conjuncts that mention an
+/// outer column, rewritten so `outer_ref(t.c)` becomes a plain `t.c` — it then
+/// resolves against the join's concatenated `left ++ right` schema, like any
+/// other join predicate. Everything else stays an ordinary inner `Filter`.
+///
+/// An outer reference anywhere but a top-level filter conjunct is rejected: it
+/// would need real decorrelation, not a predicate lift.
+fn split_correlation(plan: &LogicalPlan) -> Result<(LogicalPlan, Option<Expr>), LoweringError> {
+    let LogicalPlan::Filter(filter) = plan else {
+        return if plan_has_outer_ref(plan) {
+            Err(LoweringError::UnsupportedFeature(
+                "correlated subquery whose outer reference is not a filter conjunct".into(),
+            ))
+        } else {
+            Ok((plan.clone(), None))
+        };
+    };
+
+    let mut conjuncts = Vec::new();
+    split_conjunction(&filter.predicate, &mut conjuncts);
+    let (correlated, inner): (Vec<_>, Vec<_>) =
+        conjuncts.into_iter().partition(|e| expr_has_outer_ref(e));
+
+    let input = filter.input.as_ref();
+    if plan_has_outer_ref(input) {
+        return Err(LoweringError::UnsupportedFeature(
+            "correlated subquery whose outer reference is below its filter".into(),
+        ));
+    }
+
+    let correlation = rebuild_conjunction(&correlated)
+        .map(|e| strip_outer_refs(&e))
+        .transpose()?;
+    let plan = match rebuild_conjunction(&inner) {
+        Some(pred) => LogicalPlan::Filter(
+            logical_expr::Filter::try_new(pred, filter.input.clone())
+                .map_err(LoweringError::DataFusion)?,
+        ),
+        None => input.clone(),
+    };
+    Ok((plan, correlation))
+}
+
+/// Rewrite `outer_ref(t.c)` to `t.c` so the expression resolves against the
+/// join's concatenated schema.
+fn strip_outer_refs(expr: &Expr) -> Result<Expr, LoweringError> {
+    expr.clone()
+        .transform(|e| {
+            Ok(match e {
+                Expr::OuterReferenceColumn(_, col) => Transformed::yes(Expr::Column(col)),
+                other => Transformed::no(other),
+            })
+        })
+        .map(|t| t.data)
+        .map_err(LoweringError::DataFusion)
+}
+
+fn expr_has_outer_ref(expr: &Expr) -> bool {
+    let mut found = false;
+    expr.apply(|e| {
+        if matches!(e, Expr::OuterReferenceColumn(..)) {
+            found = true;
+            return Ok(TreeNodeRecursion::Stop);
+        }
+        Ok(TreeNodeRecursion::Continue)
+    })
+    .expect("infallible visitor");
+    found
+}
+
+fn plan_has_outer_ref(plan: &LogicalPlan) -> bool {
+    let mut found = false;
+    plan.apply(|p| {
+        if p.expressions().iter().any(expr_has_outer_ref) {
+            found = true;
+            return Ok(TreeNodeRecursion::Stop);
+        }
+        Ok(TreeNodeRecursion::Continue)
+    })
+    .expect("infallible visitor");
+    found
+}
+
+/// Strip `AS alias` wrappers.
+fn unalias(expr: &Expr) -> &Expr {
+    match expr {
+        Expr::Alias(a) => unalias(&a.expr),
+        other => other,
+    }
+}
+
+/// The `GroupingSet` inside a grouping expression, if any.
+fn as_grouping_set(expr: &Expr) -> Option<&logical_expr::GroupingSet> {
+    match unalias(expr) {
+        Expr::GroupingSet(gs) => Some(gs),
+        _ => None,
+    }
+}
+
+/// The grouping levels a `GroupingSet` stands for, widest first (issue #118).
+///
+/// `ROLLUP(a, b)` → `(a,b), (a), ()` — the prefixes.
+/// `CUBE(a, b)`   → `(a,b), (a), (b), ()` — the power set.
+/// `GROUPING SETS` is already the explicit list.
+fn expand_grouping_set(gs: &logical_expr::GroupingSet) -> Vec<Vec<Expr>> {
+    match gs {
+        logical_expr::GroupingSet::Rollup(exprs) => (0..=exprs.len())
+            .rev()
+            .map(|n| exprs[..n].to_vec())
+            .collect(),
+        logical_expr::GroupingSet::Cube(exprs) => {
+            // Bitmask descending, so the full set leads and `()` trails.
+            (0..(1u32 << exprs.len()))
+                .rev()
+                .map(|mask| {
+                    exprs
+                        .iter()
+                        .enumerate()
+                        .filter(|(i, _)| mask & (1 << i) != 0)
+                        .map(|(_, e)| e.clone())
+                        .collect()
+                })
+                .collect()
+        }
+        logical_expr::GroupingSet::GroupingSets(sets) => sets.clone(),
+    }
+}
+
+/// Derived columns materialized in a `Project` beneath an `Aggregate` (#110).
+///
+/// `Aggregate.by` holds positional `ColumnId`s and each reducer holds one input
+/// column, so neither can hold an expression. `GROUP BY date_trunc('minute', t)`
+/// and `SUM(bytes * 8)` are therefore rewritten to group/reduce over a projected
+/// column that carries the expression's value.
+///
+/// The projection also has to carry through the plain columns the aggregate
+/// still references, since a `Project` replaces its child's schema rather than
+/// extending it.
+struct DerivedCols<'l> {
+    lowerer: &'l SqlLowerer<'l>,
+    cols: Vec<ProjectItem>,
+    /// Whether any column is genuinely derived. Without one the aggregate keeps
+    /// its original child, so trees that lower today keep their exact shape.
+    any: bool,
+    /// First same-name-different-value collision, reported only if the
+    /// projection is actually inserted (see [`Self::wrap`]).
+    collision: Option<String>,
+}
+
+impl<'l> DerivedCols<'l> {
+    fn new(lowerer: &'l SqlLowerer<'l>) -> Self {
+        Self {
+            lowerer,
+            cols: Vec::new(),
+            any: false,
+            collision: None,
+        }
+    }
+
+    /// Add `alias := expr`, or note a collision if `alias` already means
+    /// something else. `Project` carries one relation qualifier for all its
+    /// columns, so `a.k` and `b.k` cannot both survive it — but that only
+    /// matters when a projection gets inserted at all.
+    fn push(&mut self, alias: String, expr: Scalar) {
+        let existing = self
+            .cols
+            .iter()
+            .find(|c| c.alias.as_deref() == Some(&alias));
+        match existing {
+            // Same name, same value — one projected column serves both uses.
+            Some(e) if e.expr == expr => {}
+            Some(_) => {
+                self.collision.get_or_insert(alias);
+            }
+            None => self.cols.push(ProjectItem {
+                alias: Some(alias),
+                expr,
+            }),
+        }
+    }
+
+    /// A plain column the aggregate references — carried through unchanged.
+    fn passthrough(&mut self, expr: &Expr) -> Result<(), LoweringError> {
+        let Expr::Column(c) = unalias(expr) else {
+            return Ok(());
+        };
+        self.push(c.name.clone(), self.lowerer.lower_expr(expr)?);
+        Ok(())
+    }
+
+    /// A genuinely derived column: `alias` now names `expr`'s value.
+    fn materialize(&mut self, alias: String, expr: Scalar) -> Result<(), LoweringError> {
+        self.any = true;
+        self.push(alias, expr);
+        Ok(())
+    }
+
+    /// Repoint a reducer's argument at a derived column when it is an
+    /// expression; otherwise carry its plain input column through.
+    fn rewrite_agg(&mut self, expr: &Expr) -> Result<Expr, LoweringError> {
+        let Expr::AggregateFunction(agg_fn) = unalias(expr) else {
+            return Ok(expr.clone());
+        };
+        if matches!(
+            asap_sql_function_catalog::lookup_native(&agg_fn.func.name().to_lowercase()),
+            Some(AggSemantic::Correlation)
+        ) {
+            // Give each value argument its own projected name, including casts
+            // and qualified columns. This retains both inputs and avoids losing
+            // relation qualifiers when the projection becomes an unqualified schema.
+            let mut rewritten = agg_fn.clone();
+            for arg in &mut rewritten.args {
+                let alias = unalias(arg).to_string();
+                self.materialize(alias.clone(), self.lowerer.lower_expr(arg)?)?;
+                *arg = Expr::Column(DfColumn::new_unqualified(alias));
+            }
+            return Ok(Expr::AggregateFunction(rewritten));
+        }
+        // `COUNT(*)` reduces no column; `agg_col_name` covers bare/aliased/cast
+        // columns, so `None` here means the argument really is an expression.
+        let counts_rows = agg_fn.func.name().eq_ignore_ascii_case("count") && !agg_fn.distinct;
+        let Some(arg) = agg_fn.args.first() else {
+            return Ok(expr.clone());
+        };
+        if counts_rows {
+            return Ok(expr.clone());
+        }
+        // Preserve every additional column dependency (e.g. argMax's ordering
+        // column) when an unrelated grouping expression creates a Project.
+        // Literal parameters need no source column and remain untouched.
+        for argument in agg_fn.args.iter().skip(1) {
+            self.passthrough(argument)?;
+        }
+        match agg_col_name(&agg_fn.args) {
+            Some(name) => {
+                self.push(name, self.lowerer.lower_expr(arg)?);
+                Ok(expr.clone())
+            }
+            None => {
+                let alias = unalias(arg).to_string();
+                self.materialize(alias.clone(), self.lowerer.lower_expr(arg)?)?;
+                let mut agg_fn = agg_fn.clone();
+                agg_fn.args[0] = Expr::Column(DfColumn::new_unqualified(alias));
+                Ok(Expr::AggregateFunction(agg_fn))
+            }
+        }
+    }
+
+    /// Wrap `input` in the materializing `Project`, or return it untouched when
+    /// nothing needed deriving — so a query that lowers today keeps its exact
+    /// tree, and a name collision that the projection would have flattened only
+    /// matters once the projection exists.
+    fn wrap(self, input: Unresolved) -> Result<Unresolved, LoweringError> {
+        if !self.any {
+            return Ok(input);
+        }
+        if let Some(alias) = self.collision {
+            return Err(LoweringError::UnsupportedFeature(format!(
+                "ambiguous column `{alias}` beneath an expression GROUP BY / \
+                 aggregate — alias the relations apart"
+            )));
+        }
+        Ok(Unresolved::Project {
+            cols: self.cols,
+            qualifier: None,
+            child: Rc::new(input),
+        })
+    }
+}
+
+/// The first aggregate argument's column name (bare / aliased / cast column),
+/// or `None` for `*` / a non-column expression.
+fn agg_col_name(args: &[Expr]) -> Option<String> {
+    fn col_name(e: &Expr) -> Option<String> {
+        match e {
+            Expr::Column(c) => Some(c.name.clone()),
+            Expr::Alias(a) => col_name(&a.expr),
+            Expr::Cast(c) => col_name(&c.expr),
+            _ => None,
+        }
+    }
+    args.first().and_then(col_name)
+}
+
+/// The single input column of a value reducer (`SUM`/`MIN`/`MAX`/`AVG`/stddev/
+/// variance/quantile/count-distinct). Errors if the argument is not a column:
+/// the canonical `AggIntent` reduces a column, not an arbitrary expression
+/// (`SUM(a*b)`), so silently picking a probe column would compute the wrong
+/// result.
+fn reducer_col(name: &str, args: &[Expr]) -> Result<ColumnRef, LoweringError> {
+    agg_col_name(args).map(ColumnRef::Named).ok_or_else(|| {
+        LoweringError::UnsupportedAggregate(format!("{name} over a non-column expression"))
+    })
+}
+
+/// One argument of a `COUNT(DISTINCT ...)`. Resolved the way a grouping key is
+/// — what is being counted is an identity, and its qualifier has to survive a
+/// join (`a.k` vs `b.k`) — but reported as an aggregate restriction, since an
+/// aggregate call is what the user wrote.
+fn distinct_col(expr: &Expr) -> Result<ColumnRef, LoweringError> {
+    expr_to_group_ref(expr).map_err(|_| {
+        LoweringError::UnsupportedAggregate(
+            "COUNT(DISTINCT ...) over a non-column expression".into(),
+        )
+    })
+}
+
+fn expr_to_group_ref(expr: &Expr) -> Result<ColumnRef, LoweringError> {
+    match expr {
+        // Preserve the relation qualifier so a GROUP BY / PARTITION BY key over a
+        // join (`b.k` vs `a.k`) resolves to the correct side — the same rule the
+        // scalar predicate path uses (`lower_expr`).
+        Expr::Column(col) => Ok(match &col.relation {
+            Some(rel) => ColumnRef::Qualified {
+                table: rel.to_string(),
+                name: col.name.clone(),
+            },
+            None => ColumnRef::Named(col.name.clone()),
+        }),
+        Expr::Alias(a) => expr_to_group_ref(&a.expr),
+        other => Err(LoweringError::UnsupportedFeature(format!(
+            "non-column GROUP BY expression: {other}"
+        ))),
+    }
+}
+
+fn extract_percentile_q(args: &[Expr]) -> Result<f64, LoweringError> {
+    let q = match args.get(1) {
+        Some(Expr::Literal(DfScalarValue::Float64(Some(q)))) => *q,
+        Some(Expr::Literal(DfScalarValue::Float32(Some(q)))) => *q as f64,
+        _ => {
+            return Err(LoweringError::InvalidExpression(
+                "percentile value must be a float literal (2nd arg)".into(),
+            ))
+        }
+    };
+    if q.is_finite() && (0.0..=1.0).contains(&q) {
+        Ok(q)
+    } else {
+        Err(LoweringError::InvalidExpression(format!(
+            "percentile must be in [0, 1], got {q}"
+        )))
+    }
+}
+
+// ── LogicalPlan navigation helpers ──────────────────────────────────────────────
+
+fn eval_fetch(expr_opt: &Option<Box<Expr>>) -> Option<usize> {
+    expr_opt.as_ref().and_then(|e| match e.as_ref() {
+        Expr::Literal(DfScalarValue::Int64(Some(v))) if *v >= 0 => Some(*v as usize),
+        Expr::Literal(DfScalarValue::UInt64(Some(v))) => Some(*v as usize),
+        Expr::Literal(DfScalarValue::Int32(Some(v))) if *v >= 0 => Some(*v as usize),
+        _ => None,
+    })
+}
+
+/// Map a DataFusion window-function definition to the canonical
+/// [`WindowFuncKind`].
+/// `NthValue` is returned with `None`; `lower_window` fills in `n` from args.
+fn lower_window_func_kind(fun: &WindowFunctionDefinition) -> Result<WindowFuncKind, LoweringError> {
+    let unsupported = |what: &str, name: &str| {
+        LoweringError::UnsupportedFeature(format!("window {what}: {name}"))
+    };
+    match fun {
+        WindowFunctionDefinition::WindowUDF(udf) => match udf.name().to_lowercase().as_str() {
+            "row_number" => Ok(WindowFuncKind::RowNumber),
+            "rank" => Ok(WindowFuncKind::Rank),
+            "dense_rank" => Ok(WindowFuncKind::DenseRank),
+            "lag" => Ok(WindowFuncKind::Lag),
+            "lead" => Ok(WindowFuncKind::Lead),
+            // ClickHouse: frame-respecting variants, not plain Lag/Lead (#267).
+            "laginframe" => Ok(WindowFuncKind::LagInFrame),
+            "leadinframe" => Ok(WindowFuncKind::LeadInFrame),
+            "first_value" => Ok(WindowFuncKind::FirstValue),
+            "last_value" => Ok(WindowFuncKind::LastValue),
+            "nth_value" => Ok(WindowFuncKind::NthValue(None)),
+            other => Err(unsupported("function", other)),
+        },
+        WindowFunctionDefinition::AggregateUDF(udf) => match udf.name().to_lowercase().as_str() {
+            "sum" => Ok(WindowFuncKind::Sum),
+            "avg" | "mean" => Ok(WindowFuncKind::Avg),
+            "count" => Ok(WindowFuncKind::Count),
+            "min" => Ok(WindowFuncKind::Min),
+            "max" => Ok(WindowFuncKind::Max),
+            other => Err(unsupported("aggregate", other)),
+        },
+        WindowFunctionDefinition::BuiltInWindowFunction(biwf) => {
+            use datafusion::logical_expr::BuiltInWindowFunction;
+            match biwf {
+                BuiltInWindowFunction::FirstValue => Ok(WindowFuncKind::FirstValue),
+                BuiltInWindowFunction::LastValue => Ok(WindowFuncKind::LastValue),
+                BuiltInWindowFunction::NthValue => Ok(WindowFuncKind::NthValue(None)),
+            }
+        }
+    }
+}
+
+/// Map DataFusion's resolved `WindowFrame` (issue #268) to the canonical
+/// [`WindowFrame`]. DataFusion's planner always fills in the SQL-standard
+/// default frame before the logical plan is built, so this never sees an
+/// "absent" frame — only `ROWS`/`RANGE`/`GROUPS` with concrete bounds.
+/// `GROUPS` is rejected: no query in this repo's SQL corpora uses it, and
+/// nothing downstream interprets frame semantics yet, so it isn't worth
+/// modelling untested.
+fn lower_window_frame(
+    frame: &datafusion::logical_expr::WindowFrame,
+) -> Result<WindowFrame, LoweringError> {
+    let units = match frame.units {
+        DfWindowFrameUnits::Rows => WindowFrameUnits::Rows,
+        DfWindowFrameUnits::Range => WindowFrameUnits::Range,
+        DfWindowFrameUnits::Groups => {
+            return Err(LoweringError::UnsupportedFeature(
+                "window frame unit: GROUPS".into(),
+            ))
+        }
+    };
+    let offset = |v: &DfScalarValue| -> Result<WindowFrameOffset, LoweringError> {
+        Ok(match v {
+            DfScalarValue::IntervalYearMonth(Some(months)) => WindowFrameOffset::Interval {
+                months: *months,
+                days: 0,
+                nanoseconds: 0,
+            },
+            DfScalarValue::IntervalDayTime(Some(value)) => WindowFrameOffset::Interval {
+                months: 0,
+                days: value.days,
+                nanoseconds: i64::from(value.milliseconds) * 1_000_000,
+            },
+            DfScalarValue::IntervalMonthDayNano(Some(value)) => WindowFrameOffset::Interval {
+                months: value.months,
+                days: value.days,
+                nanoseconds: value.nanoseconds,
+            },
+            // DataFusion 43 keeps every RANGE offset as text: both numeric
+            // bounds such as `1.5` and normalized interval literals such as
+            // `"1 HOUR"`. Arrow's interval parser accepts bare numbers and
+            // interprets them as months, so classify numeric text first.
+            DfScalarValue::Utf8(Some(value)) | DfScalarValue::LargeUtf8(Some(value)) => {
+                if let Ok(value) = value.parse::<i64>() {
+                    WindowFrameOffset::Scalar(ScalarValue::Int64(value))
+                } else if let Ok(value) = value.parse::<f64>() {
+                    WindowFrameOffset::Scalar(ScalarValue::Float64(value))
+                } else {
+                    match parse_interval_month_day_nano(value) {
+                        Ok(interval) => WindowFrameOffset::Interval {
+                            months: interval.months,
+                            days: interval.days,
+                            nanoseconds: interval.nanoseconds,
+                        },
+                        Err(_) => WindowFrameOffset::Scalar(scalar_value_to_asap(v)?),
+                    }
+                }
+            }
+            _ => WindowFrameOffset::Scalar(scalar_value_to_asap(v)?),
+        })
+    };
+    let bound = |b: &DfWindowFrameBound| -> Result<WindowFrameBound, LoweringError> {
+        Ok(match b {
+            DfWindowFrameBound::Preceding(v) => WindowFrameBound::Preceding(offset(v)?),
+            DfWindowFrameBound::CurrentRow => WindowFrameBound::CurrentRow,
+            DfWindowFrameBound::Following(v) => WindowFrameBound::Following(offset(v)?),
+        })
+    };
+    Ok(WindowFrame {
+        units,
+        start_bound: bound(&frame.start_bound)?,
+        end_bound: bound(&frame.end_bound)?,
+    })
+}
+
+// ── Issue #225, item 3: DataFusion registry drift detection ────────────────
+//
+// `asap_sql_function_catalog::NATIVE_FUNCTIONS` is hand-maintained data
+// mirroring what DataFusion's own aggregate-function registry resolves. That
+// mirror can only silently drift out of sync — a DataFusion version bump
+// that adds, renames, or removes a builtin aggregate leaves the catalog
+// looking fine while `lower_agg_intent` quietly gains or loses coverage. Of
+// the two introspectable sources the issue names, DataFusion's own registry
+// is the one with no external dependency: `SessionContext` already lists its
+// aggregate UDFs in-process, so the check below builds a real context the
+// same way `build_context` does and walks it directly — no live database,
+// no new CI infra, just `cargo test`. (ClickHouse's `system.functions` is
+// the other source; it needs a live ClickHouse instance, which is handled
+// separately by the dev-only `tools/clickhouse/extract_functions.py` script,
+// deliberately not wired into this test or into CI.)
+#[cfg(test)]
+mod catalog_drift {
+    use super::*;
+
+    /// Every aggregate function name DataFusion's planner resolves inside a
+    /// context built the same way `build_context` builds one must be
+    /// *accounted for* by the catalog: either `lookup_native` maps it to a
+    /// canonical semantic, it is one of our own `CLICKHOUSE_BUILTINS` stub
+    /// registrations (`build_context` registers those into the very same
+    /// context, so they show up here too), or it is explicitly listed in
+    /// `KNOWN_UNMAPPED_NATIVE_FUNCTIONS` with a reason.
+    ///
+    /// This does *not* assert the reverse (that every `NATIVE_FUNCTIONS`
+    /// entry is resolvable) — a name that stops resolving after a DataFusion
+    /// bump just becomes permanently unreachable dead data, not a lowering
+    /// hazard, so it's out of scope for a regression gate. It also does not
+    /// try to derive `AggSemantic` from anything DataFusion reports — that
+    /// judgment call stays with whoever adds the catalog entry.
+    #[test]
+    fn every_datafusion_aggregate_name_is_covered_by_the_catalog() {
+        let catalog = SqlCatalog::new();
+        let ctx = SqlLowerer::new(&catalog)
+            .build_context()
+            .expect("build_context with an empty table catalog cannot fail");
+        let state = ctx.state();
+        let mut uncovered: Vec<&str> = state
+            .aggregate_functions()
+            .keys()
+            .map(String::as_str)
+            .filter(|name| {
+                asap_sql_function_catalog::lookup_native(name).is_none()
+                    && asap_sql_function_catalog::lookup_clickhouse_builtin(name).is_none()
+                    && !asap_sql_function_catalog::KNOWN_UNMAPPED_NATIVE_FUNCTIONS.contains(name)
+            })
+            .collect();
+        uncovered.sort_unstable();
+        assert!(
+            uncovered.is_empty(),
+            "DataFusion resolves these aggregate names but the catalog doesn't know about them \
+             (crates/sql-function-catalog/src/lib.rs): {uncovered:?}\n\
+             Either add a `NativeFunction` entry mapping each to its `AggSemantic`, or -- if it's \
+             a deliberate non-goal (no `AggIntent` shape for it, or it's rejected elsewhere) -- \
+             add it to `KNOWN_UNMAPPED_NATIVE_FUNCTIONS` with a reason. This usually means a \
+             DataFusion version bump added or renamed a builtin aggregate."
+        );
+    }
+
+    /// Every `KNOWN_UNMAPPED_NATIVE_FUNCTIONS` entry earns its place by
+    /// actually being a name DataFusion resolves today — otherwise it is
+    /// stale documentation for a name that no longer exists (e.g. a prior
+    /// DataFusion version renamed it), not a real "deliberately not mapped"
+    /// decision, and should be removed.
+    #[test]
+    fn known_unmapped_entries_are_all_real_datafusion_names() {
+        let catalog = SqlCatalog::new();
+        let ctx = SqlLowerer::new(&catalog)
+            .build_context()
+            .expect("build_context with an empty table catalog cannot fail");
+        let resolved = ctx.state().aggregate_functions().clone();
+        for name in asap_sql_function_catalog::KNOWN_UNMAPPED_NATIVE_FUNCTIONS {
+            assert!(
+                resolved.contains_key(*name),
+                "`{name}` is listed in KNOWN_UNMAPPED_NATIVE_FUNCTIONS but DataFusion no longer \
+                 resolves it -- remove the stale entry"
+            );
+        }
+    }
+}
diff --git a/crates/frontend-sql/src/unified/sql/types.rs b/crates/frontend-sql/src/unified/sql/types.rs
new file mode 100644
index 000000000..05d46f938
--- /dev/null
+++ b/crates/frontend-sql/src/unified/sql/types.rs
@@ -0,0 +1,378 @@
+//! Type bridges between DataFusion's Arrow types and the canonical `DataType`, plus
+//! the SQL table catalog used to register tables with DataFusion and to carry
+//! resolved leaf schemas into the canonical, unresolved tree.
+
+use std::collections::HashMap;
+
+use datafusion::arrow::datatypes::{
+    DataType as ArrowDataType, Field as ArrowField, Fields, Schema as ArrowSchema,
+};
+use datafusion::common::ScalarValue as DfScalarValue;
+
+use asap_types::pre_asap::schema::{DataType, Field, Schema};
+use asap_types::pre_asap::ScalarValue;
+
+use crate::unified::error::SqlError as LoweringError;
+
+/// Table catalog for SQL lowering: table name → resolved canonical [`Schema`].
+///
+/// Used twice: to register Arrow-backed `MemTable`s so DataFusion can resolve
+/// `SELECT … FROM t`, and to attach each table's schema directly onto the
+/// canonical `Scan` (`schema: Some(_)`) so the SchemaResolver doesn't need to
+/// usage-derive it.
+#[derive(Debug, Clone, Default)]
+pub struct SqlCatalog {
+    pub tables: HashMap<String, Schema>,
+}
+
+impl SqlCatalog {
+    pub fn new() -> Self {
+        Self::default()
+    }
+
+    /// Builder: register `name` with its resolved canonical schema.
+    pub fn with_table(mut self, name: impl Into<String>, schema: Schema) -> Self {
+        self.tables.insert(name.into(), schema);
+        self
+    }
+}
+
+pub(super) fn scalar_value_to_asap(sv: &DfScalarValue) -> Result<ScalarValue, LoweringError> {
+    match sv {
+        DfScalarValue::Int64(Some(v)) => Ok(ScalarValue::Int64(*v)),
+        DfScalarValue::Int32(Some(v)) => Ok(ScalarValue::Int64(*v as i64)),
+        DfScalarValue::Int16(Some(v)) => Ok(ScalarValue::Int64(*v as i64)),
+        DfScalarValue::Int8(Some(v)) => Ok(ScalarValue::Int64(*v as i64)),
+        DfScalarValue::UInt64(Some(v)) => i64::try_from(*v).map(ScalarValue::Int64).map_err(|_| {
+            LoweringError::InvalidExpression(format!("UInt64 value {v} overflows i64"))
+        }),
+        DfScalarValue::UInt32(Some(v)) => Ok(ScalarValue::Int64(*v as i64)),
+        DfScalarValue::Float64(Some(v)) => Ok(ScalarValue::Float64(*v)),
+        DfScalarValue::Float32(Some(v)) => Ok(ScalarValue::Float64(*v as f64)),
+        DfScalarValue::Utf8(Some(s)) | DfScalarValue::LargeUtf8(Some(s)) => {
+            Ok(ScalarValue::Utf8(s.clone()))
+        }
+        DfScalarValue::Boolean(Some(b)) => Ok(ScalarValue::Boolean(*b)),
+        // All three of DataFusion's interval scalars land on one canonical
+        // shape; the narrower two simply leave the fields they do not carry
+        // at zero.
+        DfScalarValue::IntervalYearMonth(Some(months)) => Ok(ScalarValue::Interval {
+            months: *months,
+            days: 0,
+            nanos: 0,
+        }),
+        DfScalarValue::IntervalDayTime(Some(v)) => Ok(ScalarValue::Interval {
+            months: 0,
+            days: v.days,
+            nanos: i64::from(v.milliseconds) * 1_000_000,
+        }),
+        DfScalarValue::IntervalMonthDayNano(Some(v)) => Ok(ScalarValue::Interval {
+            months: v.months,
+            days: v.days,
+            nanos: v.nanoseconds,
+        }),
+        _ if sv.is_null() => Ok(ScalarValue::Null),
+        _ => Err(LoweringError::InvalidExpression(format!(
+            "unsupported scalar: {sv:?}"
+        ))),
+    }
+}
+
+/// Arrow → the canonical `DataType` (used for `CAST` targets). Deliberately narrow.
+pub(super) fn arrow_to_dtype(dt: &ArrowDataType) -> Result<DataType, LoweringError> {
+    match dt {
+        ArrowDataType::Null => Ok(DataType::Null),
+        ArrowDataType::Int64
+        | ArrowDataType::Int32
+        | ArrowDataType::Int16
+        | ArrowDataType::Int8 => Ok(DataType::Int64),
+        ArrowDataType::Float64 | ArrowDataType::Float32 => Ok(DataType::Float64),
+        ArrowDataType::Utf8 | ArrowDataType::LargeUtf8 => Ok(DataType::Utf8),
+        ArrowDataType::Boolean => Ok(DataType::Bool),
+        ArrowDataType::Timestamp(_, _) => Ok(DataType::Timestamp),
+        ArrowDataType::Date32 | ArrowDataType::Date64 => Ok(DataType::Date),
+        ArrowDataType::Interval(_) => Ok(DataType::Interval),
+        ArrowDataType::List(element) => Ok(DataType::List {
+            element: Box::new(Field::new(
+                element.name(),
+                arrow_to_dtype(element.data_type())?,
+                element.is_nullable(),
+            )),
+        }),
+        ArrowDataType::Struct(fields) => Ok(DataType::Struct {
+            fields: fields
+                .iter()
+                .map(|field| {
+                    Ok(Field::new(
+                        field.name(),
+                        arrow_to_dtype(field.data_type())?,
+                        field.is_nullable(),
+                    ))
+                })
+                .collect::<Result<Vec<_>, LoweringError>>()?,
+        }),
+        ArrowDataType::Map(entries, _) => {
+            let ArrowDataType::Struct(fields) = entries.data_type() else {
+                return Err(LoweringError::UnsupportedFeature(
+                    "map entries must be a struct".into(),
+                ));
+            };
+            if fields.len() != 2 || fields[0].is_nullable() {
+                return Err(LoweringError::UnsupportedFeature(
+                    "map entries require a non-null key and a value".into(),
+                ));
+            }
+            Ok(DataType::Map {
+                key: Box::new(arrow_to_dtype(fields[0].data_type())?),
+                value: Box::new(arrow_to_dtype(fields[1].data_type())?),
+                value_nullable: fields[1].is_nullable(),
+            })
+        }
+        other => Err(LoweringError::UnsupportedFeature(format!(
+            "Arrow type: {other:?}"
+        ))),
+    }
+}
+
+/// The canonical `DataType` → Arrow (for registering catalog tables with DataFusion).
+pub(super) fn dtype_to_arrow(dt: &DataType) -> ArrowDataType {
+    match dt {
+        DataType::Null => ArrowDataType::Null,
+        DataType::Int64 => ArrowDataType::Int64,
+        DataType::Float64 => ArrowDataType::Float64,
+        DataType::Utf8 => ArrowDataType::Utf8,
+        DataType::Bool => ArrowDataType::Boolean,
+        DataType::List { element } => ArrowDataType::List(std::sync::Arc::new(ArrowField::new(
+            &element.name,
+            dtype_to_arrow(&element.dtype),
+            element.nullable,
+        ))),
+        DataType::Struct { fields } => ArrowDataType::Struct(
+            fields
+                .iter()
+                .map(|field| {
+                    ArrowField::new(&field.name, dtype_to_arrow(&field.dtype), field.nullable)
+                })
+                .collect::<Vec<_>>()
+                .into(),
+        ),
+        DataType::Map {
+            key,
+            value,
+            value_nullable,
+        } => ArrowDataType::Map(
+            std::sync::Arc::new(ArrowField::new(
+                "entries",
+                ArrowDataType::Struct(
+                    vec![
+                        ArrowField::new("key", dtype_to_arrow(key), false),
+                        ArrowField::new("value", dtype_to_arrow(value), *value_nullable),
+                    ]
+                    .into(),
+                ),
+                false,
+            )),
+            false,
+        ),
+        DataType::Timestamp => {
+            ArrowDataType::Timestamp(datafusion::arrow::datatypes::TimeUnit::Millisecond, None)
+        }
+        // Deliberately narrowing: `Date64` lowers to `DataType::Date` and comes
+        // back as `Date32`. Both spell the same calendar date and nothing in
+        // the planner reads the width; a catalog that wants `Date64` back would
+        // need a second variant carrying no planning information.
+        DataType::Date => ArrowDataType::Date32,
+        // Only reachable through a hand-built schema: `Interval` types a
+        // literal, and no catalog declares a column with it. Mapped to the
+        // same three-field shape `ScalarValue::Interval` carries rather than
+        // left to panic.
+        DataType::Interval => {
+            ArrowDataType::Interval(datafusion::arrow::datatypes::IntervalUnit::MonthDayNano)
+        }
+    }
+}
+
+/// Build an Arrow schema from a canonical [`Schema`] (column name + type + nullability).
+pub(super) fn schema_to_arrow(schema: &Schema) -> ArrowSchema {
+    let fields: Fields = schema
+        .fields
+        .iter()
+        .map(|c: &Field| {
+            ArrowField::new(&c.name, dtype_to_arrow(c.expect_plain_dtype()), c.nullable)
+        })
+        .collect();
+    ArrowSchema::new(fields)
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    /// Both Arrow date widths bridge to the one canonical `Date`, and it
+    /// registers back as `Date32` — the documented narrowing.
+    #[test]
+    fn both_arrow_date_widths_bridge_to_date() {
+        assert_eq!(
+            arrow_to_dtype(&ArrowDataType::Date32).unwrap(),
+            DataType::Date
+        );
+        assert_eq!(
+            arrow_to_dtype(&ArrowDataType::Date64).unwrap(),
+            DataType::Date
+        );
+        assert_eq!(dtype_to_arrow(&DataType::Date), ArrowDataType::Date32);
+    }
+
+    /// Every Arrow interval width shares the canonical calendar interval type.
+    #[test]
+    fn interval_types_round_trip_through_the_catalog_bridge() {
+        use datafusion::arrow::datatypes::IntervalUnit;
+        for unit in [
+            IntervalUnit::YearMonth,
+            IntervalUnit::DayTime,
+            IntervalUnit::MonthDayNano,
+        ] {
+            assert_eq!(
+                arrow_to_dtype(&ArrowDataType::Interval(unit)).unwrap(),
+                DataType::Interval
+            );
+        }
+        assert_eq!(
+            arrow_to_dtype(&dtype_to_arrow(&DataType::Interval)).unwrap(),
+            DataType::Interval
+        );
+    }
+
+    /// All three of DataFusion's interval scalars carry into the one canonical
+    /// three-field shape, with the fields they do not spell left at zero.
+    #[test]
+    fn every_datafusion_interval_scalar_carries_across() {
+        use datafusion::arrow::datatypes::{IntervalDayTime, IntervalMonthDayNano};
+
+        assert_eq!(
+            scalar_value_to_asap(&DfScalarValue::IntervalYearMonth(Some(14))).unwrap(),
+            ScalarValue::Interval {
+                months: 14,
+                days: 0,
+                nanos: 0
+            }
+        );
+        assert_eq!(
+            scalar_value_to_asap(&DfScalarValue::IntervalDayTime(Some(IntervalDayTime::new(
+                30, 500
+            ))))
+            .unwrap(),
+            ScalarValue::Interval {
+                months: 0,
+                days: 30,
+                nanos: 500_000_000
+            }
+        );
+        assert_eq!(
+            scalar_value_to_asap(&DfScalarValue::IntervalMonthDayNano(Some(
+                IntervalMonthDayNano::new(1, 2, 3)
+            )))
+            .unwrap(),
+            ScalarValue::Interval {
+                months: 1,
+                days: 2,
+                nanos: 3
+            }
+        );
+    }
+
+    /// Nested map values and value nullability survive catalog registration.
+    #[test]
+    fn nested_map_schema_round_trip() {
+        let map = DataType::Map {
+            key: Box::new(DataType::Utf8),
+            value: Box::new(DataType::Map {
+                key: Box::new(DataType::Int64),
+                value: Box::new(DataType::Float64),
+                value_nullable: true,
+            }),
+            value_nullable: false,
+        };
+        assert_eq!(arrow_to_dtype(&dtype_to_arrow(&map)).unwrap(), map);
+        let encoded = serde_json::to_string(&map).unwrap();
+        assert_eq!(serde_json::from_str::<DataType>(&encoded).unwrap(), map);
+    }
+}
+
+#[cfg(test)]
+mod collection_tests {
+    use super::*;
+    #[test]
+    fn nested_collections_preserve_field_names_order_and_nullability() {
+        let dtype = DataType::Struct {
+            fields: vec![
+                Field::new(
+                    "samples",
+                    DataType::List {
+                        element: Box::new(Field::new(
+                            "sample",
+                            DataType::Struct {
+                                fields: vec![
+                                    Field::new("timestamp", DataType::Timestamp, false),
+                                    Field::new("value", DataType::Float64, true),
+                                    Field::new(
+                                        "labels",
+                                        DataType::Map {
+                                            key: Box::new(DataType::Utf8),
+                                            value: Box::new(DataType::List {
+                                                element: Box::new(Field::new(
+                                                    "label_value",
+                                                    DataType::Utf8,
+                                                    false,
+                                                )),
+                                            }),
+                                            value_nullable: true,
+                                        },
+                                        true,
+                                    ),
+                                ],
+                            },
+                            true,
+                        )),
+                    },
+                    false,
+                ),
+                Field::new("optional", DataType::Int64, true),
+            ],
+        };
+        let arrow = dtype_to_arrow(&dtype);
+        assert_eq!(arrow_to_dtype(&arrow).unwrap(), dtype);
+        assert_eq!(dtype_to_arrow(&arrow_to_dtype(&arrow).unwrap()), arrow);
+        let encoded = serde_json::to_string(&dtype).unwrap();
+        assert_eq!(serde_json::from_str::<DataType>(&encoded).unwrap(), dtype);
+    }
+    #[test]
+    fn empty_struct_and_nonnullable_list_element_roundtrip() {
+        let dtype = DataType::List {
+            element: Box::new(Field::new(
+                "empty",
+                DataType::Struct { fields: vec![] },
+                false,
+            )),
+        };
+        assert_eq!(arrow_to_dtype(&dtype_to_arrow(&dtype)).unwrap(), dtype);
+    }
+}
+
+#[cfg(test)]
+mod bottom_map_tests {
+    use super::*;
+    #[test]
+    fn empty_map_bottom_types_roundtrip_without_string_defaults() {
+        let (map, nullable) = asap_types::pre_asap::scalar_type_rules::MapScalarFunction::Construct
+            .output_type(&[])
+            .unwrap();
+        assert!(!nullable);
+        let arrow = dtype_to_arrow(&map);
+        assert_eq!(arrow_to_dtype(&arrow).unwrap(), map);
+        assert_eq!(
+            arrow_to_dtype(&ArrowDataType::Null).unwrap(),
+            DataType::Null
+        );
+    }
+}
diff --git a/crates/frontend-sql/tests/unified_sql_lowering.rs b/crates/frontend-sql/tests/unified_sql_lowering.rs
new file mode 100644
index 000000000..2cc9e9ee2
--- /dev/null
+++ b/crates/frontend-sql/tests/unified_sql_lowering.rs
@@ -0,0 +1,2874 @@
+//! End-to-end SQL → unresolved → resolved operator DAG lowering tests.
+//!
+//! Validates the DataFusion front end: SQL parses + plans, lowers directly to
+//! the name-based `UnresolvedOp` tree (issue #179), and the shared
+//! `resolve_root` produces the positional, canonical `OperatorNode` DAG (the
+//! same resolver the PromQL path uses). Every node's schema is derived during
+//! resolution, so a successful `lower` already proves schema derivation is
+//! total over the tree.
+
+use ::asap_frontend_sql::unified as asap_frontend_sql;
+use asap_types::ir::Predicate;
+use std::rc::Rc;
+
+use asap_frontend_common::{UnresolvedOp, UnresolvedScalar};
+use asap_frontend_sql::{
+    lower_sql, lower_sql_dialect, SqlCatalog, SqlError as LoweringError, SqlLowerer,
+};
+use asap_types::ir::{ExprSemantics, NonASAPOp, OperatorNode, ScalarExpr};
+use asap_types::pre_asap::schema::{DataType, Field, FieldDataType, Schema};
+use asap_types::pre_asap::{
+    AggIntent, CompareOpKind, GroupKeys, JoinKind, Reduction, ScalarValue, Source,
+    WindowFrameBound, WindowFrameOffset, WindowFrameUnits, WindowFuncKind,
+};
+use asap_types::types::AccuracyTarget;
+use asap_types::workload::SqlDialect;
+
+fn col(name: &str, dtype: DataType) -> Field {
+    Field::plain(name, dtype, false)
+}
+
+/// `metrics(ts, service, latency, bytes)` + `hosts(service, region)`.
+fn catalog() -> SqlCatalog {
+    SqlCatalog::new()
+        .with_table(
+            "metrics",
+            Schema::with_time_index(
+                vec![
+                    col("ts", DataType::Timestamp),
+                    col("service", DataType::Utf8),
+                    col("latency", DataType::Float64),
+                    col("bytes", DataType::Int64),
+                ],
+                0,
+                vec![vec![0, 1]],
+            ),
+        )
+        .with_table(
+            "hosts",
+            Schema::new(vec![
+                col("service", DataType::Utf8),
+                col("region", DataType::Utf8),
+            ]),
+        )
+}
+
+async fn lower(sql: &str) -> Rc<OperatorNode> {
+    lower_sql(sql, &catalog(), AccuracyTarget::Exact)
+        .await
+        .unwrap_or_else(|e| panic!("lower failed for {sql:?}: {e}"))
+}
+
+/// The operator of a front-end node: a front-end DAG never holds an ASAP node.
+fn op(node: &OperatorNode) -> &NonASAPOp {
+    node.expect_non_asap()
+}
+
+#[tokio::test]
+async fn planning_subquery_bridge_rejects_a_relation_without_vector_conversion() {
+    let result = lower_sql("SELECT max(value) FROM (SELECT asap_promql_subquery(21600000, 60000) AS value FROM (SELECT sum(bytes) AS value FROM metrics))", &catalog(), AccuracyTarget::Exact).await;
+    assert!(result.is_err());
+}
+
+#[tokio::test]
+async fn planning_histogram_bridge_reuses_classic_bucket_intent() {
+    let query = lower(
+        "SELECT asap_histogram_quantile(0.95) AS value FROM (\
+           SELECT service AS le, sum(bytes) AS value FROM metrics GROUP BY service)",
+    )
+    .await;
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = op(&query)
+    else {
+        panic!("expected canonical histogram aggregate");
+    };
+    // One histogram over all rows; the bucket bound is the child's column 0.
+    assert!(reduction.expect_reduce().keys().is_empty());
+    assert!(matches!(
+        measures.as_slice(),
+        [AggIntent::HistogramQuantile { q, le: 0 }] if (*q - 0.95).abs() < 1e-12
+    ));
+    assert!(matches!(op(child), NonASAPOp::Project { .. }));
+}
+
+#[tokio::test]
+async fn planning_relation_bridges_reject_ambiguous_shapes() {
+    let missing_alias = lower_sql(
+        "SELECT asap_promql_subquery(300000, 60000) FROM metrics",
+        &catalog(),
+        AccuracyTarget::Exact,
+    )
+    .await
+    .unwrap_err();
+    assert!(missing_alias.to_string().contains("must have an alias"));
+
+    let histogram_with_extra_column = lower_sql(
+        "SELECT service, asap_histogram_quantile(0.95) AS value FROM metrics",
+        &catalog(),
+        AccuracyTarget::Exact,
+    )
+    .await
+    .unwrap_err();
+    assert!(histogram_with_extra_column
+        .to_string()
+        .contains("only expression"));
+
+    let invalid_q = lower_sql(
+        "SELECT asap_histogram_quantile(1.5) AS value FROM metrics",
+        &catalog(),
+        AccuracyTarget::Exact,
+    )
+    .await
+    .unwrap_err();
+    assert!(invalid_q.to_string().contains("finite and in [0,1]"));
+}
+
+/// Find the first `Aggregate` node along the single-child spine.
+fn find_aggregate(node: &OperatorNode) -> Option<(&GroupKeys, &Vec<AggIntent>)> {
+    match op(node) {
+        NonASAPOp::Aggregate {
+            reduction,
+            measures,
+            ..
+        } => Some((reduction.expect_reduce(), measures)),
+        NonASAPOp::Project { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Dedup { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. }
+        | NonASAPOp::PromqlSubquery { child, .. } => find_aggregate(child),
+        _ => None,
+    }
+}
+
+/// The first `Aggregate` node itself, for tests that need its child.
+fn find_aggregate_node(node: &OperatorNode) -> Option<&OperatorNode> {
+    match op(node) {
+        NonASAPOp::Aggregate { .. } => Some(node),
+        NonASAPOp::Project { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. } => find_aggregate_node(child),
+        _ => None,
+    }
+}
+
+/// The names of the columns the first `Aggregate`'s reducers read, resolved
+/// against its child's schema, plus whether that child is a materializing
+/// `Project` (issue #110).
+fn reducer_input_names(node: &OperatorNode) -> (Vec<String>, bool) {
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = op(find_aggregate_node(node).expect("expected an Aggregate"))
+    else {
+        unreachable!()
+    };
+    let schema = &child.schema;
+    let names = measures
+        .iter()
+        .flat_map(|a| a.input_cols())
+        .map(|id| schema.fields[id].name.clone())
+        .collect();
+    (names, matches!(op(child), NonASAPOp::Project { .. }))
+}
+
+/// Find the first `Join` node along the single-child spine.
+fn find_join(node: &OperatorNode) -> Option<&OperatorNode> {
+    match op(node) {
+        NonASAPOp::Join { .. } => Some(node),
+        NonASAPOp::Project { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Aggregate { child, .. }
+        | NonASAPOp::Dedup { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. }
+        | NonASAPOp::PromqlSubquery { child, .. } => find_join(child),
+        _ => None,
+    }
+}
+
+/// The first `Filter` node along the single-child spine.
+fn find_filter(node: &OperatorNode) -> Option<&OperatorNode> {
+    match op(node) {
+        NonASAPOp::Filter { .. } => Some(node),
+        NonASAPOp::Project { child, .. }
+        | NonASAPOp::Aggregate { child, .. }
+        | NonASAPOp::Dedup { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. }
+        | NonASAPOp::PromqlSubquery { child, .. } => find_filter(child),
+        _ => None,
+    }
+}
+
+#[tokio::test]
+async fn select_star_with_where_folds_predicate_onto_scan() {
+    // SELECT * elides the projection; WHERE folds onto the Scan predicates.
+    let qe = lower("SELECT * FROM metrics WHERE service = 'api'").await;
+    let NonASAPOp::Scan {
+        source,
+        predicates,
+        schema,
+    } = op(&qe)
+    else {
+        panic!("expected Scan at root, got {qe:?}");
+    };
+    assert!(matches!(source, Source::Table { table_ref } if table_ref == "metrics"));
+    assert_eq!(predicates.len(), 1, "WHERE clause folded onto the scan");
+    assert!(
+        schema.closed,
+        "a catalog-backed SQL scan has a closed schema"
+    );
+}
+
+#[tokio::test]
+async fn multi_aggregate_group_by_binds_columns_positionally() {
+    // SUM(bytes)=col 3, AVG(latency)=col 2, GROUP BY service=col 1.
+    let qe = lower("SELECT service, SUM(bytes), AVG(latency) FROM metrics GROUP BY service").await;
+    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate in the tree");
+    assert_eq!(by, &vec![1], "GROUP BY service → column 1");
+    assert!(
+        measures.contains(&AggIntent::Sum { col: Some(3) }),
+        "SUM(bytes) → Sum{{col:3}}, got {measures:?}"
+    );
+    assert!(
+        measures.contains(&AggIntent::Avg { col: Some(2) }),
+        "AVG(latency) → Avg{{col:2}}, got {measures:?}"
+    );
+}
+
+#[tokio::test]
+async fn projection_over_aggregate_resolves_output_types_via_output_names() {
+    // The enclosing Projection references the aggregates by DataFusion's
+    // generated names (e.g. "sum(metrics.bytes)"); output_names threads those
+    // onto the canonical Aggregate so the Project resolves real types — not
+    // the Utf8 fallback that an unresolved column would get.
+    let qe = lower("SELECT SUM(bytes), AVG(latency) FROM metrics").await;
+    let schema = &qe.schema;
+    assert_eq!(schema.fields.len(), 2);
+    assert_eq!(
+        schema.fields[0].dtype,
+        DataType::Int64,
+        "SUM(bytes:Int64) resolves to Int64, not the Utf8 fallback"
+    );
+    assert_eq!(
+        schema.fields[1].dtype,
+        DataType::Float64,
+        "AVG(latency) resolves to Float64"
+    );
+}
+
+#[tokio::test]
+async fn single_agg_group_by_keeps_key_in_output_schema() {
+    // A tabular single-aggregate GROUP BY routes through the positional
+    // Aggregate.by path (not the PromQL fused-Partition shape), so the group
+    // key is a real output column the enclosing SELECT projection resolves.
+    let qe = lower("SELECT service, SUM(bytes) FROM metrics GROUP BY service").await;
+    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate (not a Partition)");
+    assert_eq!(by, &vec![1], "GROUP BY service → Aggregate.by column 1");
+    assert!(matches!(
+        measures.as_slice(),
+        [AggIntent::Sum { col: Some(3) }]
+    ));
+
+    // Both the group key and the aggregate resolve in the root projection schema.
+    let schema = &qe.schema;
+    assert_eq!(schema.fields.len(), 2);
+    assert_eq!(
+        schema.fields[0].dtype,
+        DataType::Utf8,
+        "service is in the output"
+    );
+    assert_eq!(schema.fields[1].dtype, DataType::Int64, "SUM(bytes)");
+}
+
+#[tokio::test]
+async fn count_ranked_topk_is_heavy_hitter() {
+    // `ORDER BY COUNT(*) DESC LIMIT k` over a single COUNT aggregate is the one
+    // case the heavy-hitter (frequency) sketch is correct for. The shared
+    // `canonicalize` pass (issue #34) promotes it to the canonical two-level
+    // form: an outer global `TopK` (by: []) over the explicit inner `Count`
+    // grouped by `service`.
+    let qe = lower(
+        "SELECT service, COUNT(*) FROM metrics GROUP BY service ORDER BY COUNT(*) DESC LIMIT 10",
+    )
+    .await;
+    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate");
+    assert!(
+        by.is_empty(),
+        "outer TopK is a global ranking (by: []), got {by:?}"
+    );
+    assert!(
+        matches!(measures.as_slice(), [AggIntent::TopK { k: 10, .. }]),
+        "count-ranked topk → heavy-hitter TopK, got {measures:?}"
+    );
+    // The inner child is the explicit Count, grouped by service (col 1).
+    let NonASAPOp::Aggregate { child, .. } = op(&qe) else {
+        panic!("expected outer Aggregate, got {qe:?}");
+    };
+    let (inner_by, inner_measures) = find_aggregate(child).expect("expected inner Count aggregate");
+    assert_eq!(inner_by, &vec![1], "inner Count grouped by service → col 1");
+    assert!(
+        matches!(inner_measures.as_slice(), [AggIntent::Count { .. }]),
+        "inner aggregate is the explicit Count, got {inner_measures:?}"
+    );
+}
+
+#[tokio::test]
+async fn count_ranked_topk_via_alias_is_also_heavy_hitter() {
+    // Regression for #20: aliasing `COUNT(*)` in the ORDER BY used to defeat the
+    // SQL front-end gate. The positional `canonicalize` pass now promotes it too,
+    // so the aliased and inline forms produce an identical canonical tree.
+    let inline = lower(
+        "SELECT service, COUNT(*) FROM metrics GROUP BY service ORDER BY COUNT(*) DESC LIMIT 10",
+    )
+    .await;
+    let aliased = lower(
+        "SELECT service, COUNT(*) AS cnt FROM metrics GROUP BY service ORDER BY cnt DESC LIMIT 10",
+    )
+    .await;
+    assert_eq!(
+        inline, aliased,
+        "aliased count-ranked topk must match the inline form"
+    );
+    let (_, measures) = find_aggregate(&aliased).expect("expected an Aggregate");
+    assert!(
+        matches!(measures.as_slice(), [AggIntent::TopK { k: 10, .. }]),
+        "aliased count-ranked topk → heavy-hitter TopK, got {measures:?}"
+    );
+}
+
+#[tokio::test]
+async fn non_count_ranked_limit_keeps_the_aggregate() {
+    // Ranking by AVG (not a count) must NOT become a frequency heavy-hitter —
+    // the AVG aggregate has to survive as a generic Sort+Limit.
+    let qe = lower(
+        "SELECT service, AVG(latency) AS a FROM metrics GROUP BY service ORDER BY a DESC LIMIT 10",
+    )
+    .await;
+    let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
+    assert!(
+        measures.iter().any(|a| matches!(a, AggIntent::Avg { .. })),
+        "AVG must be preserved, got {measures:?}"
+    );
+    assert!(
+        !measures.iter().any(|a| matches!(a, AggIntent::TopK { .. })),
+        "AVG ranking must not become a frequency heavy-hitter, got {measures:?}"
+    );
+}
+
+#[tokio::test]
+async fn distinct_value_reducer_is_rejected_not_dropped() {
+    // The canonical intent algebra has no distinct-Sum; SUM(DISTINCT x) must
+    // be rejected, not silently lowered as SUM(x).
+    let res = lower_sql(
+        "SELECT SUM(DISTINCT bytes) FROM metrics",
+        &catalog(),
+        AccuracyTarget::Exact,
+    )
+    .await;
+    assert!(res.is_err(), "SUM(DISTINCT ...) should be rejected");
+}
+
+#[tokio::test]
+async fn aggregate_over_an_expression_reduces_a_derived_column() {
+    // The canonical `AggIntent` reduces a column, not an arbitrary expression.
+    // `SUM(bytes + 1)` used to be rejected for that reason; since #110 the
+    // expression is materialized as a derived column in a `Project` beneath
+    // the aggregate, and reduced there.
+    let qe = lower("SELECT SUM(bytes + 1) FROM metrics").await;
+    let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
+    assert!(
+        matches!(measures.as_slice(), [AggIntent::Sum { col: Some(_) }]),
+        "expected Sum bound to the derived column, got {measures:?}"
+    );
+    let (names, materialized) = reducer_input_names(&qe);
+    assert!(materialized, "expected a materializing Project");
+    assert!(
+        names[0].contains("bytes") && names[0].contains('1'),
+        "the reduced column should be the projected `bytes + 1`, got {names:?}"
+    );
+}
+
+#[tokio::test]
+async fn count_star_is_count_intent() {
+    let qe = lower("SELECT COUNT(*) FROM metrics").await;
+    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate");
+    assert!(by.is_empty());
+    assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
+}
+
+#[tokio::test]
+async fn count_distinct_is_cardinality() {
+    let qe = lower("SELECT COUNT(DISTINCT service) FROM metrics").await;
+    let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
+    assert!(matches!(
+        measures.as_slice(),
+        [AggIntent::Cardinality { .. }]
+    ));
+}
+
+#[tokio::test]
+async fn select_distinct_lowers_to_distinct_with_positional_cols() {
+    // SELECT DISTINCT → a `Dedup` node whose `cols` are positional ColumnIds
+    // (not name-based ColumnRefs). DataFusion's `Distinct::All` dedups on every
+    // column, so `cols` is empty here — but the field type is now `Vec<ColumnId>`.
+    let qe = lower("SELECT DISTINCT service FROM metrics").await;
+    let NonASAPOp::Dedup { cols, .. } = op(&qe) else {
+        panic!("expected a Dedup at the root, got {qe:?}");
+    };
+    let _: &Vec<usize> = cols; // compile-time: positional ids, not ColumnRefs
+    assert!(cols.is_empty(), "DISTINCT * dedups on all columns");
+}
+
+#[tokio::test]
+async fn inner_join_lowers_to_join_over_two_scans() {
+    // INNER JOIN over two distinct tables → a canonical Join with both leaves as Scans.
+    let qe = lower(
+        "SELECT metrics.bytes, hosts.region \
+         FROM metrics JOIN hosts ON metrics.service = hosts.service",
+    )
+    .await;
+    let join = find_join(&qe).expect("expected a Join in the tree");
+    let NonASAPOp::Join {
+        kind, left, right, ..
+    } = op(join)
+    else {
+        unreachable!("find_join only returns Join");
+    };
+    assert_eq!(*kind, JoinKind::Inner);
+    assert!(matches!(op(left), NonASAPOp::Scan { .. }));
+    assert!(matches!(op(right), NonASAPOp::Scan { .. }));
+}
+
+/// The two `ColumnId`s an equijoin predicate `Column(l) = Column(r)` binds to,
+/// returned sorted so the assertion is independent of left/right ordering.
+fn join_eq_columns(join: &OperatorNode) -> [usize; 2] {
+    let NonASAPOp::Join { pred, .. } = op(join) else {
+        unreachable!("expected a Join");
+    };
+    let ScalarExpr::Compare {
+        left,
+        op: CompareOpKind::Eq,
+        right,
+        ..
+    } = &pred.0
+    else {
+        panic!("expected an equijoin Compare, got {:?}", pred.0);
+    };
+    match (left.as_ref(), right.as_ref()) {
+        (ScalarExpr::Column(l), ScalarExpr::Column(r)) => {
+            let mut cols = [*l, *r];
+            cols.sort_unstable();
+            cols
+        }
+        other => panic!("expected Field = Field, got {other:?}"),
+    }
+}
+
+#[tokio::test]
+async fn join_predicate_disambiguates_shared_column_name() {
+    // Issue #7: `metrics.service = hosts.service` shares a column name across the
+    // join. The qualified refs must bind to two *distinct* positions in the
+    // concatenated schema, not collapse onto the first `service`.
+    // metrics(ts,service,latency,bytes) ++ hosts(service,region)
+    // → metrics.service = col 1, hosts.service = col 4.
+    let qe = lower(
+        "SELECT metrics.bytes, hosts.region \
+         FROM metrics JOIN hosts ON metrics.service = hosts.service",
+    )
+    .await;
+    let join = find_join(&qe).expect("expected a Join in the tree");
+    assert_eq!(
+        join_eq_columns(join),
+        [1, 4],
+        "join key must bind to distinct positions, not the same `service`"
+    );
+}
+
+#[tokio::test]
+async fn derived_table_join_disambiguates_via_alias() {
+    // Issue #66: a join over two *derived tables* must bind its keys to distinct
+    // positions. Before the fix the derived output columns lost their qualifier,
+    // so `a.service` and `b.service` both fell back to the first bare `service`
+    // (col 0) — `service = service`, always true → a silent cross product.
+    // Concatenated: a[service,region] ++ b[service,region] → a.service=0, b.service=2.
+    let qe = lower(
+        "SELECT a.region, b.region \
+         FROM (SELECT service, region FROM hosts) a \
+         JOIN (SELECT service, region FROM hosts) b ON a.service = b.service",
+    )
+    .await;
+    let join = find_join(&qe).expect("expected a Join in the tree");
+    assert_eq!(
+        join_eq_columns(join),
+        [0, 2],
+        "derived-table join keys must bind to distinct positions, not both to the first `service`"
+    );
+}
+
+#[tokio::test]
+async fn derived_table_select_star_join_disambiguates_via_alias() {
+    // Same as above but `SELECT *` derived tables (the non-Projection path that
+    // wraps the inner plan in an identity re-qualifying projection).
+    let qe = lower(
+        "SELECT a.region, b.region \
+         FROM (SELECT * FROM hosts) a JOIN (SELECT * FROM hosts) b \
+         ON a.service = b.service",
+    )
+    .await;
+    let join = find_join(&qe).expect("expected a Join in the tree");
+    let [l, r] = join_eq_columns(join);
+    assert_ne!(
+        l, r,
+        "SELECT * derived-table join keys must not collapse to one column"
+    );
+}
+
+#[tokio::test]
+async fn self_join_disambiguates_via_aliases() {
+    // A self-join shares *every* column name; the alias qualifiers (`a`/`b`) are
+    // the only way to tell the two `service` columns apart.
+    // metrics ++ metrics → a.service = col 1, b.service = col 5 (4 cols/side).
+    let qe = lower(
+        "SELECT a.bytes, b.latency \
+         FROM metrics a JOIN metrics b ON a.service = b.service",
+    )
+    .await;
+    let join = find_join(&qe).expect("expected a self-Join in the tree");
+    assert_eq!(
+        join_eq_columns(join),
+        [1, 5],
+        "self-join keys must bind to distinct sides"
+    );
+}
+
+#[tokio::test]
+async fn qualified_where_over_join_resolves_to_right_side() {
+    // Issue #7 beyond the join key: a WHERE on the *duplicated* column name
+    // (`service` exists on both sides) must bind to the qualified side, not the
+    // first match. metrics.service = col 1, hosts.service = col 4 → `hosts.service`
+    // must resolve to 4. (Unoptimized plan keeps the Filter above the Join — no
+    // predicate pushdown — so it binds against the concatenated schema.)
+    let qe = lower(
+        "SELECT metrics.bytes FROM metrics JOIN hosts ON metrics.service = hosts.service \
+         WHERE hosts.service = 'api'",
+    )
+    .await;
+    let filter = find_filter(&qe).expect("expected a Filter over the join");
+    let NonASAPOp::Filter { pred, .. } = op(filter) else {
+        unreachable!("find_filter only returns Filter");
+    };
+    assert!(
+        matches!(&pred.0, ScalarExpr::Compare { left, op: CompareOpKind::Eq, .. }
+            if matches!(left.as_ref(), ScalarExpr::Column(4))),
+        "hosts.service must bind to concatenated position 4 (not the first `service`), got {:?}",
+        pred.0
+    );
+}
+
+#[tokio::test]
+async fn self_join_group_by_disambiguates_via_qualifier() {
+    // Group-key qualifier fix: GROUP BY on the *duplicated* column over a
+    // self-join must bind to the qualified side, not first-match. metrics ⋈
+    // metrics → a.service = col 1, b.service = col 5. (Without qualified keys,
+    // both `GROUP BY a.service` and `GROUP BY b.service` collapsed to col 1.)
+    let qe_b = lower(
+        "SELECT b.service, COUNT(*) FROM metrics a JOIN metrics b \
+         ON a.service = b.service GROUP BY b.service",
+    )
+    .await;
+    let (by, _) = find_aggregate(&qe_b).expect("expected an Aggregate over the self-join");
+    assert_eq!(
+        by,
+        &vec![5],
+        "GROUP BY b.service binds to the b side (col 5)"
+    );
+
+    let qe_a = lower(
+        "SELECT a.service, COUNT(*) FROM metrics a JOIN metrics b \
+         ON a.service = b.service GROUP BY a.service",
+    )
+    .await;
+    let (by, _) = find_aggregate(&qe_a).expect("expected an Aggregate over the self-join");
+    assert_eq!(
+        by,
+        &vec![1],
+        "GROUP BY a.service binds to the a side (col 1)"
+    );
+}
+
+#[tokio::test]
+async fn aggregate_over_join_binds_against_concatenated_schema() {
+    // GROUP BY a right-table column over a join: the key must resolve against
+    // the concatenated schema, exercising the bottom-up converter end to end.
+    // Two aggregates → the multi-agg path, which carries GROUP BY keys as
+    // positional `Aggregate.by` (as does every reducing GROUP BY).
+    let qe = lower(
+        "SELECT hosts.region, SUM(metrics.bytes), COUNT(*) \
+         FROM metrics JOIN hosts ON metrics.service = hosts.service \
+         GROUP BY hosts.region",
+    )
+    .await;
+    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate over the join");
+    // metrics(ts,service,latency,bytes) ++ hosts(service,region) →
+    // region is column 5, bytes is column 3 of the concatenated schema.
+    assert_eq!(
+        by,
+        &vec![5],
+        "GROUP BY hosts.region → concatenated column 5"
+    );
+    assert!(
+        measures.contains(&AggIntent::Sum { col: Some(3) }),
+        "SUM(metrics.bytes) → Sum{{col:3}}, got {measures:?}"
+    );
+}
+
+// ── Issue #111: IN / EXISTS subquery predicates become semi / anti joins ────
+//
+// The front end now leaves them as `UnresolvedScalar::{InSubquery, Exists}`
+// filter conjuncts; the shared `canonicalize` pass (run by `resolve_root`)
+// lowers each to the semi-/anti-join, so the resolved DAG a test sees is the
+// same join shape the front end used to emit directly.
+
+/// The first `Join` node's `(kind, predicate, left column count)`.
+fn join_parts(node: &OperatorNode) -> (&JoinKind, &ScalarExpr, usize) {
+    let NonASAPOp::Join {
+        kind,
+        pred,
+        left,
+        right: _,
+    } = op(find_join(node).expect("expected a Join"))
+    else {
+        unreachable!()
+    };
+    (kind, &pred.0, left.schema.fields.len())
+}
+
+#[tokio::test]
+async fn in_subquery_lowers_to_a_semi_join() {
+    // `metrics(ts, service, latency, bytes)` — service is column 1.
+    let qe =
+        lower("SELECT service FROM metrics WHERE service IN (SELECT service FROM hosts)").await;
+    let (kind, pred, left_len) = join_parts(&qe);
+    assert_eq!(kind, &JoinKind::Semi);
+    assert_eq!(left_len, 4);
+
+    // The predicate resolves against `left ++ right`. Both relations have a
+    // `service` column, so a name-based lookup would bind *both* sides to the
+    // left's — silently making this `service = service`, always true. The key is
+    // bound positionally to the subquery's column (right after the left's),
+    // which makes that impossible.
+    let ScalarExpr::Compare { left, right, .. } = pred else {
+        panic!("expected a comparison, got {pred:?}");
+    };
+    assert_eq!(**left, ScalarExpr::Column(1), "outer service");
+    assert_eq!(
+        **right,
+        ScalarExpr::Column(left_len),
+        "the subquery key, not the outer column again"
+    );
+}
+
+#[tokio::test]
+async fn a_semi_join_outputs_only_the_left_schema() {
+    // The right side is a filter, not a source of columns.
+    let qe =
+        lower("SELECT service FROM metrics WHERE service IN (SELECT service FROM hosts)").await;
+    let join = find_join(&qe).expect("expected a Join");
+    let names: Vec<_> = join.schema.fields.iter().map(|c| c.name.clone()).collect();
+    assert_eq!(names, ["ts", "service", "latency", "bytes"]);
+}
+
+#[tokio::test]
+async fn a_subquery_key_that_is_an_expression_still_binds() {
+    // `SELECT bytes + 1 …` has no column name of its own; the join key binds
+    // to it positionally rather than through an unreferenceable `col_0`.
+    let qe =
+        lower("SELECT service FROM metrics WHERE bytes IN (SELECT bytes + 1 FROM metrics)").await;
+    assert_eq!(join_parts(&qe).0, &JoinKind::Semi);
+}
+
+#[tokio::test]
+async fn a_multi_column_in_subquery_is_rejected() {
+    let err = lower_sql(
+        "SELECT service FROM metrics WHERE service IN (SELECT service, region FROM hosts)",
+        &catalog(),
+        AccuracyTarget::Exact,
+    )
+    .await
+    .expect_err("IN must select one column");
+    assert!(format!("{err}").contains("exactly one column"), "got {err}");
+}
+
+#[tokio::test]
+async fn an_ordinary_conjunct_still_folds_onto_the_scan() {
+    // The residual filter stays *below* the semi-join, where the converter can
+    // still fold it onto the Scan. A semi-join only drops left rows, so the
+    // orders agree.
+    let qe = lower(
+        "SELECT service FROM metrics WHERE bytes > 10 \
+         AND service IN (SELECT service FROM hosts)",
+    )
+    .await;
+    fn scan_has_predicate(node: &OperatorNode) -> bool {
+        match op(node) {
+            NonASAPOp::Scan { predicates, .. } => !predicates.is_empty(),
+            NonASAPOp::Project { child, .. }
+            | NonASAPOp::Filter { child, .. }
+            | NonASAPOp::Aggregate { child, .. } => scan_has_predicate(child),
+            NonASAPOp::Join { left, right, .. } => {
+                scan_has_predicate(left) || scan_has_predicate(right)
+            }
+            _ => false,
+        }
+    }
+    assert_eq!(join_parts(&qe).0, &JoinKind::Semi);
+    assert!(
+        scan_has_predicate(&qe),
+        "WHERE bytes > 10 should reach the Scan"
+    );
+}
+
+/// Find the first `SQLWindowFunc` node along the single-child spine.
+fn find_windowfunc(node: &OperatorNode) -> Option<&OperatorNode> {
+    match op(node) {
+        NonASAPOp::SQLWindowFunc { .. } => Some(node),
+        NonASAPOp::Project { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Aggregate { child, .. }
+        | NonASAPOp::Dedup { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. }
+        | NonASAPOp::PromqlSubquery { child, .. } => find_windowfunc(child),
+        _ => None,
+    }
+}
+
+#[tokio::test]
+async fn window_function_lowers_to_positional_windowfunc() {
+    // ROW_NUMBER() OVER (PARTITION BY service ORDER BY bytes DESC).
+    let qe = lower(
+        "SELECT service, ROW_NUMBER() OVER (PARTITION BY service ORDER BY bytes DESC) \
+         FROM metrics",
+    )
+    .await;
+    let win = find_windowfunc(&qe).expect("expected a SQLWindowFunc node");
+    let NonASAPOp::SQLWindowFunc {
+        func,
+        partition_by,
+        order_by,
+        ..
+    } = op(win)
+    else {
+        unreachable!("find_windowfunc only returns SQLWindowFunc");
+    };
+    assert_eq!(*func, WindowFuncKind::RowNumber);
+    assert_eq!(partition_by, &vec![1], "PARTITION BY service → col 1");
+    assert_eq!(order_by.len(), 1);
+    assert_eq!(
+        order_by[0].expr,
+        ScalarExpr::Column(3),
+        "ORDER BY bytes → col 3"
+    );
+    assert!(!order_by[0].ascending, "DESC");
+
+    // The window output column is appended to the schema (Int64 for ROW_NUMBER),
+    // and the enclosing projection resolves it (output_name threading).
+    let schema = &qe.schema;
+    assert!(
+        schema.fields.iter().any(|c| c.dtype == DataType::Int64),
+        "row_number output column present, got {:?}",
+        schema.fields
+    );
+}
+
+#[tokio::test]
+async fn window_aggregate_lowers_to_windowfunc() {
+    let qe = lower("SELECT service, SUM(bytes) OVER (PARTITION BY service) FROM metrics").await;
+    let win = find_windowfunc(&qe).expect("expected a SQLWindowFunc node");
+    let NonASAPOp::SQLWindowFunc { func, args, .. } = op(win) else {
+        unreachable!();
+    };
+    assert_eq!(*func, WindowFuncKind::Sum);
+    assert_eq!(args, &vec![ScalarExpr::Column(3)], "SUM(bytes) → arg col 3");
+}
+
+// ── Window frames (issue #268) ───────────────────────────────────────────────
+
+/// The frame clause must actually reach the IR, not just the display string:
+/// three window frames that differ semantically must lower to different
+/// `SQLWindowFunc.frame` values.
+#[tokio::test]
+async fn window_frame_is_captured_not_dropped() {
+    let default_frame =
+        lower("SELECT service, SUM(latency) OVER (PARTITION BY service ORDER BY ts) FROM metrics")
+            .await;
+    let two_preceding = lower(
+        "SELECT service, SUM(latency) OVER (PARTITION BY service ORDER BY ts \
+         ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) FROM metrics",
+    )
+    .await;
+    let unbounded_following = lower(
+        "SELECT service, SUM(latency) OVER (PARTITION BY service ORDER BY ts \
+         ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING) FROM metrics",
+    )
+    .await;
+
+    let frame_of = |node: &OperatorNode| {
+        let NonASAPOp::SQLWindowFunc { frame, .. } = op(find_windowfunc(node).unwrap()) else {
+            unreachable!();
+        };
+        frame
+            .clone()
+            .expect("newly lowered SQL always records a frame")
+    };
+    let (a, b, c) = (
+        frame_of(&default_frame),
+        frame_of(&two_preceding),
+        frame_of(&unbounded_following),
+    );
+    assert_ne!(a, b, "default frame vs ROWS 2 PRECEDING must differ");
+    assert_ne!(
+        a, c,
+        "default frame vs ROWS CURRENT..UNBOUNDED FOLLOWING must differ"
+    );
+    assert_ne!(b, c);
+
+    assert_eq!(b.units, WindowFrameUnits::Rows);
+    assert_eq!(
+        b.start_bound,
+        WindowFrameBound::Preceding(WindowFrameOffset::Scalar(ScalarValue::Int64(2)))
+    );
+    assert_eq!(b.end_bound, WindowFrameBound::CurrentRow);
+
+    assert_eq!(c.start_bound, WindowFrameBound::CurrentRow);
+    assert_eq!(
+        c.end_bound,
+        WindowFrameBound::Following(WindowFrameOffset::Scalar(ScalarValue::Null))
+    );
+}
+
+#[tokio::test]
+async fn range_interval_frame_is_preserved() {
+    let qe = lower(
+        "SELECT service, SUM(latency) OVER (PARTITION BY service ORDER BY ts \
+         RANGE BETWEEN INTERVAL '1' HOUR PRECEDING AND CURRENT ROW) FROM metrics",
+    )
+    .await;
+    let NonASAPOp::SQLWindowFunc {
+        frame: Some(frame), ..
+    } = op(find_windowfunc(&qe).unwrap())
+    else {
+        panic!("expected a window function with a concrete frame");
+    };
+
+    assert_eq!(frame.units, WindowFrameUnits::Range);
+    assert_eq!(
+        frame.start_bound,
+        WindowFrameBound::Preceding(WindowFrameOffset::Interval {
+            months: 0,
+            days: 0,
+            nanoseconds: 3_600_000_000_000,
+        })
+    );
+    assert_eq!(frame.end_bound, WindowFrameBound::CurrentRow);
+}
+
+#[tokio::test]
+async fn range_numeric_frames_remain_scalar_offsets() {
+    let integer = lower(
+        "SELECT SUM(bytes) OVER (ORDER BY bytes \
+         RANGE BETWEEN 2 PRECEDING AND CURRENT ROW) FROM metrics",
+    )
+    .await;
+    let fractional = lower(
+        "SELECT SUM(latency) OVER (ORDER BY latency \
+         RANGE BETWEEN 1.5 PRECEDING AND CURRENT ROW) FROM metrics",
+    )
+    .await;
+
+    let start_bound = |node: &OperatorNode| {
+        let NonASAPOp::SQLWindowFunc {
+            frame: Some(frame), ..
+        } = op(find_windowfunc(node).unwrap())
+        else {
+            panic!("expected a window function with a concrete frame");
+        };
+        frame.start_bound.clone()
+    };
+
+    assert_eq!(
+        start_bound(&integer),
+        WindowFrameBound::Preceding(WindowFrameOffset::Scalar(ScalarValue::Int64(2)))
+    );
+    assert_eq!(
+        start_bound(&fractional),
+        WindowFrameBound::Preceding(WindowFrameOffset::Scalar(ScalarValue::Float64(1.5)))
+    );
+}
+
+/// `GROUPS` frames aren't in this repo's SQL corpora and nothing downstream
+/// interprets frame semantics yet — rejected explicitly rather than silently
+/// mis-lowered.
+#[tokio::test]
+async fn groups_frame_is_rejected() {
+    let err = lower_sql(
+        "SELECT service, SUM(latency) OVER (PARTITION BY service ORDER BY ts \
+         GROUPS BETWEEN 2 PRECEDING AND CURRENT ROW) FROM metrics",
+        &catalog(),
+        AccuracyTarget::Exact,
+    )
+    .await
+    .expect_err("GROUPS frame unit must be rejected");
+    assert!(format!("{err}").contains("GROUPS"), "got {err}");
+}
+
+// ── Nested query functions: derived tables / inline views (issue #27) ───────────
+
+/// Collect every `AggIntent` in the DAG, root-to-leaf (every reachable node,
+/// including operators referenced from scalar positions).
+fn all_intents(root: &Rc<OperatorNode>) -> Vec<AggIntent> {
+    OperatorNode::reachable(root)
+        .iter()
+        .filter_map(|node| match op(node) {
+            NonASAPOp::Aggregate { measures, .. } => Some(measures.clone()),
+            _ => None,
+        })
+        .flatten()
+        .collect()
+}
+
+#[tokio::test]
+async fn derived_table_aggregate_over_aggregate_nests() {
+    // `MAX(s)` over a derived table `(SELECT service, SUM(bytes) AS s … GROUP BY
+    // service)` — the SQL counterpart of PromQL function nesting (issue #27).
+    // Both reductions survive into the canonical tree: an outer `Max` over
+    // the inner `Sum`.
+    let qe = lower(
+        "SELECT MAX(s) FROM \
+         (SELECT service, SUM(bytes) AS s FROM metrics GROUP BY service) t",
+    )
+    .await;
+    let intents = all_intents(&qe);
+    assert!(
+        intents.iter().any(|i| matches!(i, AggIntent::Max { .. })),
+        "outer MAX survives, got {intents:?}"
+    );
+    assert!(
+        intents.iter().any(|i| matches!(i, AggIntent::Sum { .. })),
+        "inner SUM survives, got {intents:?}"
+    );
+    // The whole nested tree's output schema derives (positional resolution
+    // is total across the derived-table boundary).
+    assert_eq!(qe.schema.fields.len(), 1);
+}
+
+#[tokio::test]
+async fn derived_table_outer_avg_over_inner_percentile() {
+    // Outer exact `AVG` over an inner approximate `Quantile` — each layer keeps
+    // its own intent (the per-node sketch-vs-exact choice is a post-ASAP decision).
+    let qe = lower(
+        "SELECT AVG(p) FROM \
+         (SELECT service, approx_percentile_cont(latency, 0.9) AS p \
+          FROM metrics GROUP BY service) t",
+    )
+    .await;
+    let intents = all_intents(&qe);
+    assert!(intents.iter().any(|i| matches!(i, AggIntent::Avg { .. })));
+    assert!(intents
+        .iter()
+        .any(|i| matches!(i, AggIntent::Quantile { q, .. } if (*q - 0.9).abs() < 1e-9)));
+}
+
+#[tokio::test]
+async fn filter_over_derived_aggregate_resolves_alias_column() {
+    // `WHERE t.s > 100` over a derived aggregate — the qualified ref `t.s`
+    // resolves by bare name against the derived output schema, and the Filter
+    // sits above the inner Aggregate.
+    let qe = lower(
+        "SELECT t.service, t.s FROM \
+         (SELECT service, SUM(bytes) AS s FROM metrics GROUP BY service) t \
+         WHERE t.s > 100",
+    )
+    .await;
+    assert!(
+        find_filter(&qe).is_some(),
+        "the outer WHERE lowers to a Filter, got {qe:?}"
+    );
+    assert!(all_intents(&qe)
+        .iter()
+        .any(|i| matches!(i, AggIntent::Sum { .. })));
+    // Schema derivation is total across the boundary: the root carries one.
+    assert_eq!(qe.schema.fields.len(), 2);
+}
+
+#[tokio::test]
+async fn scalar_subquery_in_predicate_lowers_through_a_cross_join() {
+    let qe =
+        lower("SELECT service FROM metrics WHERE bytes > (SELECT AVG(bytes) FROM metrics)").await;
+    let filter = find_filter(&qe).unwrap();
+    let NonASAPOp::Filter { pred, child } = op(filter) else {
+        panic!()
+    };
+    assert!(matches!(op(child), NonASAPOp::Scan { .. }));
+    assert!(
+        matches!(&pred.0,ScalarExpr::Compare { right,.. } if matches!(right.as_ref(),ScalarExpr::ScalarSubquery(_)))
+    );
+    qe.validate_structure().unwrap();
+}
+
+#[tokio::test]
+async fn correlated_exists_lifts_its_correlation_into_the_join() {
+    // `EXISTS (SELECT 1 FROM hosts h WHERE h.service = m.service)` → a semi-join
+    // on `h.service = m.service`. The `SELECT 1` projection is dropped: a
+    // semi-join keeps no right columns, and it would have projected away the
+    // very column the correlation needs.
+    let qe = lower(
+        "SELECT service FROM metrics m WHERE EXISTS \
+         (SELECT 1 FROM hosts h WHERE h.service = m.service)",
+    )
+    .await;
+    let (kind, pred, left_len) = join_parts(&qe);
+    assert_eq!(kind, &JoinKind::Semi);
+    let ScalarExpr::Compare { left, right, .. } = pred else {
+        panic!("expected the correlation as a comparison, got {pred:?}");
+    };
+    assert_eq!(
+        **left,
+        ScalarExpr::Column(left_len),
+        "h.service (right side)"
+    );
+    assert_eq!(**right, ScalarExpr::Column(1), "m.service (left side)");
+}
+
+#[tokio::test]
+async fn not_exists_lowers_to_an_anti_join() {
+    let qe = lower(
+        "SELECT service FROM metrics m WHERE NOT EXISTS \
+         (SELECT 1 FROM hosts h WHERE h.service = m.service)",
+    )
+    .await;
+    assert_eq!(join_parts(&qe).0, &JoinKind::Anti);
+}
+
+#[tokio::test]
+async fn an_uncorrelated_exists_is_an_unconditional_semi_join() {
+    // No correlation → keep every left row iff the right side has any row.
+    let qe = lower("SELECT service FROM metrics WHERE EXISTS (SELECT 1 FROM hosts)").await;
+    let (kind, pred, _) = join_parts(&qe);
+    assert_eq!(kind, &JoinKind::Semi);
+    assert_eq!(*pred, ScalarExpr::Literal(ScalarValue::Boolean(true)));
+}
+
+#[tokio::test]
+async fn where_exists_resolves_to_a_semi_join_over_the_subquery() {
+    // The front end emits `Filter { Exists(s) }`; the resolved DAG is the
+    // `Semi` join with the subquery (a filtered `hosts` scan) on the right.
+    let qe = lower(
+        "SELECT service FROM metrics WHERE EXISTS (SELECT service FROM hosts WHERE region = 'eu')",
+    )
+    .await;
+    let NonASAPOp::Project { child, .. } = op(&qe) else {
+        panic!("expected the SELECT list as a Project, got {qe:?}");
+    };
+    let NonASAPOp::Join {
+        kind,
+        pred,
+        left,
+        right,
+    } = op(child)
+    else {
+        panic!("expected the Semi join directly under the Project, got {child:?}");
+    };
+    assert_eq!(*kind, JoinKind::Semi);
+    assert_eq!(pred.0, ScalarExpr::Literal(ScalarValue::Boolean(true)));
+    assert!(
+        matches!(op(left), NonASAPOp::Scan { .. }),
+        "left is metrics"
+    );
+    let NonASAPOp::Project { child: scan, .. } = op(right) else {
+        panic!("expected the subquery's projection on the right, got {right:?}");
+    };
+    assert!(
+        matches!(op(scan), NonASAPOp::Scan { predicates, .. } if predicates.len() == 1),
+        "the subquery's WHERE stays on its own Scan, got {scan:?}"
+    );
+    assert_eq!(
+        child.schema.fields.len(),
+        4,
+        "a semi join outputs the left's columns alone"
+    );
+}
+
+#[tokio::test]
+async fn not_in_subquery_is_rejected_rather_than_mislowered_as_an_anti_join() {
+    let qe =
+        lower("SELECT service FROM metrics WHERE service NOT IN (SELECT service FROM hosts)").await;
+    let filter = find_filter(&qe).unwrap();
+    let NonASAPOp::Filter { pred, .. } = op(filter) else {
+        panic!()
+    };
+    assert!(matches!(
+        pred.0,
+        ScalarExpr::InSubquery { negated: true, .. }
+    ));
+    qe.validate_structure().unwrap();
+}
+
+#[tokio::test]
+async fn a_correlated_in_subquery_is_rejected() {
+    let err = lower_sql(
+        "SELECT service FROM metrics m WHERE service IN \
+         (SELECT h.service FROM hosts h WHERE h.region = m.service)",
+        &catalog(),
+        AccuracyTarget::Exact,
+    )
+    .await
+    .expect_err("correlated IN needs both a key match and a correlation");
+    assert!(format!("{err}").contains("correlated IN"), "got {err}");
+}
+
+// ── Subquery-valued expressions at the `UnresolvedOp` level ─────────────────
+
+/// `SqlLowerer::lower` output, before `resolve_root`.
+async fn lower_unresolved(sql: &str) -> UnresolvedOp {
+    let catalog = catalog();
+    SqlLowerer::new(&catalog)
+        .lower(sql, &AccuracyTarget::Exact)
+        .await
+        .unwrap_or_else(|e| panic!("lower failed for {sql:?}: {e}"))
+}
+
+#[tokio::test]
+async fn scalar_subquery_in_projection_lowers_to_a_scalar_subquery_item() {
+    // An uncorrelated `(SELECT max(v) FROM t2)` in the SELECT list is a
+    // `ScalarSubquery` projection item reading its own lowered plan; the
+    // cross-join rewrite is `canonicalize`'s job, not the front end's.
+    let tree = lower_unresolved("SELECT (SELECT max(latency) FROM metrics) FROM hosts").await;
+    let UnresolvedOp::Project { cols, child, .. } = &tree else {
+        panic!("expected the SELECT list as a Project, got {tree:?}");
+    };
+    assert!(
+        matches!(child.as_ref(), UnresolvedOp::Scan { source: Source::Table { table_ref }, .. }
+            if table_ref == "hosts"),
+        "the outer relation stays the projection's child, got {child:?}"
+    );
+    assert_eq!(cols.len(), 1);
+    let UnresolvedScalar::ScalarSubquery(sub) = &cols[0].expr else {
+        panic!("expected a ScalarSubquery item, got {:?}", cols[0].expr);
+    };
+    let UnresolvedOp::Project { child: inner, .. } = sub.as_ref() else {
+        panic!("expected the subquery's own SELECT list, got {sub:?}");
+    };
+    assert!(
+        matches!(inner.as_ref(), UnresolvedOp::Aggregate { measures, .. }
+            if matches!(measures.as_slice(), [AggIntent::Max { .. }])),
+        "the subquery plan is lowered as a root of its own, got {inner:?}"
+    );
+}
+
+#[tokio::test]
+async fn exists_and_in_subqueries_lower_to_scalar_filter_conjuncts() {
+    // The front end no longer builds the semi join itself: `EXISTS` / `IN
+    // (…)` are `Filter` predicates reading the subquery operator.
+    let tree =
+        lower_unresolved("SELECT service FROM metrics WHERE EXISTS (SELECT 1 FROM hosts)").await;
+    let UnresolvedOp::Project { child, .. } = &tree else {
+        panic!("expected a Project, got {tree:?}");
+    };
+    assert!(
+        matches!(child.as_ref(), UnresolvedOp::Filter { pred, .. }
+            if matches!(pred.0, UnresolvedScalar::Exists { negated: false, .. })),
+        "expected Filter {{ Exists }}, got {child:?}"
+    );
+
+    let tree = lower_unresolved(
+        "SELECT service FROM metrics WHERE service IN (SELECT service FROM hosts)",
+    )
+    .await;
+    let UnresolvedOp::Project { child, .. } = &tree else {
+        panic!("expected a Project, got {tree:?}");
+    };
+    assert!(
+        matches!(child.as_ref(), UnresolvedOp::Filter { pred, .. }
+            if matches!(pred.0, UnresolvedScalar::InSubquery { negated: false, .. })),
+        "expected Filter {{ InSubquery }}, got {child:?}"
+    );
+}
+
+// ── `SELECT` without `FROM`, unary minus, SQL expression semantics ──────────
+
+#[tokio::test]
+async fn select_without_from_projects_over_one_empty_row() {
+    // `SELECT 1` has no table: DataFusion's `EmptyRelation` is one empty
+    // input row, which the SELECT list projects a literal over.
+    let qe = lower("SELECT 1").await;
+    let NonASAPOp::Project { cols, child, .. } = op(&qe) else {
+        panic!("expected Project at root, got {qe:?}");
+    };
+    assert_eq!(cols.len(), 1);
+    assert_eq!(cols[0].expr, ScalarExpr::Literal(ScalarValue::Int64(1)));
+    let NonASAPOp::Values { rows, schema } = op(child) else {
+        panic!("expected Values under the Project, got {child:?}");
+    };
+    assert_eq!(rows, &vec![Vec::<ScalarExpr>::new()], "one empty row");
+    assert!(schema.fields.is_empty() && schema.closed);
+    assert_eq!(qe.schema.fields.len(), 1);
+    assert_eq!(qe.schema.fields[0].dtype, DataType::Int64);
+}
+
+#[tokio::test]
+async fn values_lowers_to_one_row_per_values_row() {
+    let qe = lower("SELECT * FROM (VALUES (1, 'a'), (2, 'b')) AS v(n, s)").await;
+    let values = OperatorNode::reachable(&qe)
+        .into_iter()
+        .find(|n| matches!(op(n), NonASAPOp::Values { .. }))
+        .expect("expected a Values node");
+    let NonASAPOp::Values { rows, schema } = op(&values) else {
+        unreachable!()
+    };
+    assert_eq!(rows.len(), 2);
+    assert_eq!(
+        rows[1],
+        vec![
+            ScalarExpr::Literal(ScalarValue::Int64(2)),
+            ScalarExpr::Literal(ScalarValue::Utf8("b".into())),
+        ]
+    );
+    assert_eq!(schema.fields.len(), 2);
+    assert_eq!(schema.fields[0].dtype, DataType::Int64);
+    assert_eq!(schema.fields[1].dtype, DataType::Utf8);
+    assert_eq!(
+        qe.schema
+            .fields
+            .iter()
+            .map(|f| f.name.as_str())
+            .collect::<Vec<_>>(),
+        ["n", "s"]
+    );
+}
+
+#[tokio::test]
+async fn unary_minus_lowers_to_negative() {
+    // `-x` over a column is the `Negative` scalar (a negative *literal* is
+    // folded by DataFusion's planner before lowering).
+    let qe = lower("SELECT -latency FROM metrics").await;
+    let NonASAPOp::Project { cols, .. } = op(&qe) else {
+        panic!("expected Project at root, got {qe:?}");
+    };
+    assert_eq!(
+        cols[0].expr,
+        ScalarExpr::Negative {
+            expr: Box::new(ScalarExpr::Column(2)),
+            semantics: ExprSemantics::Sql,
+        }
+    );
+    assert_eq!(qe.schema.fields[0].dtype, DataType::Float64);
+}
+
+#[tokio::test]
+async fn sql_comparisons_and_arithmetic_carry_sql_semantics() {
+    let qe = lower("SELECT bytes * 8 FROM metrics WHERE latency > 1.5").await;
+    let NonASAPOp::Project { cols, child, .. } = op(&qe) else {
+        panic!("expected Project at root, got {qe:?}");
+    };
+    assert!(
+        matches!(
+            &cols[0].expr,
+            ScalarExpr::Arithmetic {
+                semantics: ExprSemantics::Sql,
+                ..
+            }
+        ),
+        "got {:?}",
+        cols[0].expr
+    );
+    let NonASAPOp::Scan { predicates, .. } = op(child) else {
+        panic!("expected the WHERE folded onto the Scan, got {child:?}");
+    };
+    assert!(
+        matches!(
+            &predicates[0].0,
+            ScalarExpr::Compare {
+                semantics: ExprSemantics::Sql,
+                ..
+            }
+        ),
+        "got {:?}",
+        predicates[0].0
+    );
+}
+
+// ── Issue #115: Quantile / Cardinality carry their input column ─────────────
+
+#[tokio::test]
+async fn quantile_carries_its_input_column() {
+    // `metrics(ts=0, service=1, latency=2, bytes=3)`. Two quantiles over
+    // different columns must not compare equal — a workload-level dedupe pass
+    // would compare on `AggIntent` equality, so a col-less intent would
+    // collapse them.
+    let qe = lower(
+        "SELECT approx_percentile_cont(latency, 0.5), \
+                approx_percentile_cont(bytes, 0.5) FROM metrics",
+    )
+    .await;
+    let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
+    assert!(
+        matches!(
+            measures.as_slice(),
+            [
+                AggIntent::Quantile { col: Some(2), .. },
+                AggIntent::Quantile { col: Some(3), .. }
+            ]
+        ),
+        "quantiles must bind their own column, got {measures:?}"
+    );
+    assert_ne!(
+        measures[0], measures[1],
+        "distinct-column quantiles must not compare equal"
+    );
+}
+
+#[tokio::test]
+async fn count_distinct_carries_its_input_column() {
+    let qe = lower("SELECT COUNT(DISTINCT service), COUNT(DISTINCT bytes) FROM metrics").await;
+    let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
+    assert!(
+        matches!(
+            measures.as_slice(),
+            [
+                AggIntent::Cardinality { cols: c1, .. },
+                AggIntent::Cardinality { cols: c2, .. }
+            ] if c1 == &[1] && c2 == &[3]
+        ),
+        "cardinalities must bind their own column, got {measures:?}"
+    );
+    assert_ne!(
+        measures[0], measures[1],
+        "distinct-column cardinalities must not compare equal"
+    );
+}
+
+#[tokio::test]
+async fn quantile_and_count_distinct_over_an_expression_bind_the_derived_column() {
+    // A SQL aggregate has no "sample value" to fall back on, so an expression
+    // argument must never reach the canonical tree as `col: None` (#115).
+    // Since #110 it reaches the canonical tree as `col: Some(derived)`
+    // instead of being rejected.
+    for q in [
+        "SELECT approx_percentile_cont(bytes * 8, 0.95) FROM metrics",
+        "SELECT COUNT(DISTINCT bytes * 8) FROM metrics",
+        "SELECT approx_distinct(bytes * 8) FROM metrics",
+    ] {
+        let qe = lower(q).await;
+        let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
+        assert!(
+            !measures[0].input_cols().is_empty(),
+            "{q} must bind a column, never the implicit input, got {measures:?}"
+        );
+        let (names, materialized) = reducer_input_names(&qe);
+        assert!(materialized, "{q} expected a materializing Project");
+        assert!(
+            names[0].contains("bytes"),
+            "{q} should reduce the projected `bytes * 8`, got {names:?}"
+        );
+    }
+}
+
+// ── Issue #111: median / approx_median → the φ=0.5 quantile ─────────────────
+
+#[tokio::test]
+async fn median_lowers_to_the_half_quantile() {
+    // `metrics(ts=0, service=1, latency=2, bytes=3)`.
+    for sql in [
+        "SELECT median(latency) FROM metrics",
+        "SELECT approx_median(latency) FROM metrics",
+    ] {
+        let qe = lower(sql).await;
+        let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
+        assert!(
+            matches!(
+                measures.as_slice(),
+                [AggIntent::Quantile { col: Some(2), q, .. }] if (*q - 0.5).abs() < 1e-9
+            ),
+            "{sql} should lower to Quantile(0.5) over latency, got {measures:?}"
+        );
+    }
+}
+
+#[tokio::test]
+async fn median_is_the_same_intent_as_an_explicit_half_percentile() {
+    // Two spellings of one intent: CSE should be able to merge them.
+    let m = lower("SELECT median(latency) FROM metrics").await;
+    let p = lower("SELECT approx_percentile_cont(latency, 0.5) FROM metrics").await;
+    let (_, m_measures) = find_aggregate(&m).expect("expected an Aggregate");
+    let (_, p_measures) = find_aggregate(&p).expect("expected an Aggregate");
+    assert_eq!(m_measures, p_measures);
+}
+
+#[tokio::test]
+async fn median_threads_the_accuracy_target() {
+    // The `approx_` prefix does not decide: the AccuracyTarget does.
+    let qe = lower_sql(
+        "SELECT approx_median(latency) FROM metrics",
+        &catalog(),
+        AccuracyTarget::Epsilon(0.01),
+    )
+    .await
+    .expect("approx_median should lower");
+    let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
+    assert!(
+        matches!(
+            measures.as_slice(),
+            [AggIntent::Quantile { accuracy: AccuracyTarget::Epsilon(e), .. }]
+                if (*e - 0.01).abs() < 1e-12
+        ),
+        "median must carry the workload's accuracy target, got {measures:?}"
+    );
+}
+
+#[tokio::test]
+async fn median_over_an_expression_binds_the_derived_column() {
+    // Was rejected when filed (#111); supported since #110 materialized the
+    // expression. What must still hold is the #115 rule: never `col: None`.
+    let qe = lower("SELECT median(bytes * 8) FROM metrics").await;
+    let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
+    assert!(
+        matches!(measures.as_slice(), [AggIntent::Quantile { col: Some(_), q, .. }] if (*q - 0.5).abs() < 1e-9),
+        "expected Quantile(0.5) bound to the derived column, got {measures:?}"
+    );
+}
+
+// ── Issue #110: expression GROUP BY (time bucketing) ────────────────────────
+
+#[tokio::test]
+async fn time_bucketing_group_by_lowers_to_a_derived_key() {
+    // The canonical time-series shape: `GROUP BY date_trunc(...)`. The bucket
+    // expression is materialized beneath the aggregate and grouped on.
+    let qe =
+        lower("SELECT date_trunc('minute', ts) AS m, SUM(bytes) FROM metrics GROUP BY m").await;
+    let node = find_aggregate_node(&qe).expect("expected an Aggregate");
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = op(node)
+    else {
+        unreachable!()
+    };
+    assert!(
+        matches!(op(child), NonASAPOp::Project { .. }),
+        "expected a materializing Project beneath the Aggregate"
+    );
+    let schema = &child.schema;
+    assert_eq!(reduction, &Reduction::by(vec![0]));
+    assert!(
+        schema.fields[0].name.contains("date_trunc"),
+        "group key should be the projected bucket, got {:?}",
+        schema.fields[0].name
+    );
+    // The reducer still binds its own column, not the bucket.
+    assert!(matches!(
+        measures.as_slice(),
+        [AggIntent::Sum { col: Some(1) }]
+    ));
+}
+
+#[tokio::test]
+async fn time_bucketing_keeps_the_scan_predicate() {
+    // The projection is inserted above the scan, so a WHERE clause still folds
+    // onto the Scan rather than being stranded.
+    let qe = lower(
+        "SELECT date_trunc('minute', ts) AS m, SUM(bytes) FROM metrics \
+         WHERE bytes > 10 GROUP BY m",
+    )
+    .await;
+    fn scan_has_predicate(node: &OperatorNode) -> bool {
+        match op(node) {
+            NonASAPOp::Scan { predicates, .. } => !predicates.is_empty(),
+            NonASAPOp::Project { child, .. }
+            | NonASAPOp::Filter { child, .. }
+            | NonASAPOp::Aggregate { child, .. }
+            | NonASAPOp::Sort { child, .. }
+            | NonASAPOp::Limit { child, .. } => scan_has_predicate(child),
+            _ => false,
+        }
+    }
+    assert!(scan_has_predicate(&qe), "WHERE should stay on the Scan");
+}
+
+#[tokio::test]
+async fn a_plain_group_by_inserts_no_projection() {
+    // Queries that lowered before #110 must keep their exact tree shape — the
+    // projection appears only when something actually needs materializing.
+    for q in [
+        "SELECT service, SUM(bytes) FROM metrics GROUP BY service",
+        "SELECT SUM(bytes) FROM metrics",
+        "SELECT COUNT(*) FROM metrics",
+    ] {
+        let qe = lower(q).await;
+        let NonASAPOp::Aggregate { child, .. } =
+            op(find_aggregate_node(&qe).expect("expected an Aggregate"))
+        else {
+            unreachable!()
+        };
+        assert!(
+            !matches!(op(child), NonASAPOp::Project { .. }),
+            "{q} should not gain a projection"
+        );
+    }
+}
+
+#[tokio::test]
+async fn a_shared_expression_is_materialized_once() {
+    let qe = lower("SELECT SUM(bytes * 2), MIN(bytes * 2) FROM metrics").await;
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = op(find_aggregate_node(&qe).expect("expected an Aggregate"))
+    else {
+        unreachable!()
+    };
+    assert_eq!(
+        child.schema.fields.len(),
+        1,
+        "the two reducers should share one derived column"
+    );
+    assert_eq!(measures[0].input_cols(), measures[1].input_cols());
+}
+
+// ── Issue #118: multi-level grouping expands into one Aggregate per level ───
+
+/// The branches of the first `Concat` along the single-child spine.
+fn merge_branches(node: &OperatorNode) -> &Vec<Rc<OperatorNode>> {
+    fn find(node: &OperatorNode) -> Option<&Vec<Rc<OperatorNode>>> {
+        match op(node) {
+            NonASAPOp::Concat { children, .. } => Some(children),
+            NonASAPOp::Project { child, .. }
+            | NonASAPOp::Filter { child, .. }
+            | NonASAPOp::Sort { child, .. }
+            | NonASAPOp::Limit { child, .. } => find(child),
+            _ => None,
+        }
+    }
+    find(node).expect("expected a Concat")
+}
+
+/// `(group keys, column names)` of each merged grouping level.
+fn grouping_levels(node: &OperatorNode) -> Vec<(GroupKeys, Vec<String>)> {
+    merge_branches(node)
+        .iter()
+        .map(|b| {
+            let NonASAPOp::Project { child, .. } = op(b) else {
+                panic!("expected a Project per level, got {b:?}");
+            };
+            let NonASAPOp::Aggregate { reduction, .. } = op(child) else {
+                panic!("expected an Aggregate under the Project, got {child:?}");
+            };
+            let names = b.schema.fields.iter().map(|c| c.name.clone()).collect();
+            (reduction.expect_reduce().clone(), names)
+        })
+        .collect()
+}
+
+#[tokio::test]
+async fn rollup_expands_to_one_aggregate_per_prefix() {
+    // ROLLUP(a, b) → (a,b), (a), () — three levels, widest first.
+    let qe =
+        lower("SELECT service, bytes, SUM(latency) FROM metrics GROUP BY ROLLUP(service, bytes)")
+            .await;
+    let levels = grouping_levels(&qe);
+    let keys: Vec<_> = levels.iter().map(|(by, _)| by.clone()).collect();
+    assert_eq!(
+        keys,
+        vec![
+            GroupKeys::by(vec![1, 3]),
+            GroupKeys::by(vec![1]),
+            GroupKeys::none(),
+        ]
+    );
+}
+
+#[tokio::test]
+async fn cube_expands_to_the_power_set() {
+    // CUBE(a, b) → (a,b), (a), (b), () — four levels.
+    let qe =
+        lower("SELECT service, bytes, SUM(latency) FROM metrics GROUP BY CUBE(service, bytes)")
+            .await;
+    assert_eq!(grouping_levels(&qe).len(), 4);
+}
+
+#[tokio::test]
+async fn a_mixed_grouping_set_is_normalized_by_datafusion() {
+    // `GROUP BY g, ROLLUP(d)` arrives as one GroupingSets, not a plain key
+    // alongside a grouping set — so there is only one shape to handle.
+    let qe =
+        lower("SELECT service, bytes, SUM(latency) FROM metrics GROUP BY service, ROLLUP(bytes)")
+            .await;
+    assert_eq!(grouping_levels(&qe).len(), 2);
+}
+
+#[tokio::test]
+async fn omitted_grouping_keys_become_typed_nulls() {
+    // Every level must emit every key — as NULL where the level omits it — or
+    // `Concat` (which takes the first child's schema) would misdescribe the rest.
+    // The null is *cast*: a bare Null literal infers as Float64.
+    let qe = lower("SELECT service, SUM(bytes) FROM metrics GROUP BY ROLLUP(service)").await;
+    let levels = grouping_levels(&qe);
+    assert_eq!(levels.len(), 2);
+    for (_, names) in &levels {
+        assert_eq!(
+            names,
+            &["service".to_string(), "sum(metrics.bytes)".to_string()]
+        );
+    }
+
+    // The `()` level projects `service` as a Utf8 null, not a Float64 one.
+    let schema = &merge_branches(&qe)[1].schema;
+    assert_eq!(schema.fields[0].name, "service");
+    assert_eq!(
+        schema.fields[0].dtype,
+        DataType::Utf8,
+        "the omitted key must keep its declared type"
+    );
+}
+
+#[tokio::test]
+async fn grouping_levels_are_union_compatible() {
+    let qe = lower(
+        "SELECT service, bytes, SUM(latency) FROM metrics GROUP BY GROUPING SETS ((service),(bytes),())",
+    )
+    .await;
+    let shapes: Vec<_> = merge_branches(&qe)
+        .iter()
+        .map(|b| {
+            b.schema
+                .fields
+                .iter()
+                .map(|c| (c.name.clone(), c.dtype.clone()))
+                .collect::<Vec<_>>()
+        })
+        .collect();
+    assert!(
+        shapes.windows(2).all(|w| w[0] == w[1]),
+        "levels disagree: {shapes:?}"
+    );
+}
+
+#[tokio::test]
+async fn grouping_function_is_rejected() {
+    // `__grouping_id` is dropped when the levels are expanded. It is observable
+    // only through `GROUPING(col)`, so dropping it loses nothing representable —
+    // this test is what makes that true.
+    let err = lower_sql(
+        "SELECT service, SUM(bytes), GROUPING(service) FROM metrics GROUP BY ROLLUP(service)",
+        &catalog(),
+        AccuracyTarget::Exact,
+    )
+    .await
+    .expect_err("GROUPING() must be rejected while __grouping_id is dropped");
+    assert!(format!("{err}").contains("grouping"), "got {err}");
+}
+
+#[tokio::test]
+async fn a_non_column_key_inside_a_grouping_set_is_rejected() {
+    // The #110 derived-column machinery covers plain `GROUP BY <expr>`; inside a
+    // grouping set the key also has to be reinstatable as a typed null.
+    let err = lower_sql(
+        "SELECT date_trunc('minute', ts) AS m, SUM(bytes) FROM metrics GROUP BY ROLLUP(m)",
+        &catalog(),
+        AccuracyTarget::Exact,
+    )
+    .await
+    .expect_err("expression key inside ROLLUP must be rejected");
+    assert!(
+        format!("{err}").contains("non-column key inside a multi-level grouping"),
+        "got {err}"
+    );
+}
+
+#[tokio::test]
+async fn multi_level_grouping_composes_with_a_derived_reducer_argument() {
+    // #110's materializing Project sits beneath every level's Aggregate.
+    let qe = lower("SELECT service, SUM(bytes * 8) FROM metrics GROUP BY ROLLUP(service)").await;
+    for b in merge_branches(&qe) {
+        let NonASAPOp::Project { child, .. } = op(b) else {
+            panic!("expected a Project per level");
+        };
+        let NonASAPOp::Aggregate {
+            measures, child, ..
+        } = op(child)
+        else {
+            panic!("expected an Aggregate");
+        };
+        assert!(matches!(
+            measures.as_slice(),
+            [AggIntent::Sum { col: Some(_) }]
+        ));
+        assert!(
+            matches!(op(child), NonASAPOp::Project { .. }),
+            "the derived-column projection should sit under each level"
+        );
+    }
+}
+
+#[tokio::test]
+async fn an_ambiguous_passthrough_column_is_rejected_only_when_projecting() {
+    // A `Project` carries one relation qualifier for all its columns, so `a.k`
+    // and `b.k` cannot both survive it. That only matters once a projection is
+    // inserted: without a derived column the join keys resolve as before.
+    let ok = lower_sql(
+        "SELECT m.service, h.service, SUM(m.bytes) FROM metrics m \
+         JOIN hosts h ON m.service = h.service GROUP BY m.service, h.service",
+        &catalog(),
+        AccuracyTarget::Exact,
+    )
+    .await;
+    assert!(
+        ok.is_ok(),
+        "no derived column ⇒ no projection ⇒ no ambiguity"
+    );
+
+    let err = lower_sql(
+        "SELECT m.service, h.service, SUM(m.bytes * 2) FROM metrics m \
+         JOIN hosts h ON m.service = h.service GROUP BY m.service, h.service",
+        &catalog(),
+        AccuracyTarget::Exact,
+    )
+    .await
+    .expect_err("ambiguous passthrough must be rejected, not silently resolved");
+    assert!(format!("{err}").contains("ambiguous column"), "got {err}");
+}
+
+// ── Issue #111: array_agg is deliberately not an intent (WONTFIX) ───────────
+
+#[tokio::test]
+async fn array_agg_is_deliberately_rejected() {
+    // Not a coverage gap. `AggIntent` exists so the planner can bind a sketch or
+    // a mergeable accumulator per node; `array_agg` pre-aggregates nothing (its
+    // output is O(input rows)), has no bounded-memory approximate form, and its
+    // partial state *is* the data. An `AggIntent::ArrayAgg` would force every
+    // arm of `plan::boundary::realize` — an exhaustive match — to answer
+    // `PassThrough`. Contrast `median`, which is `Quantile { q: 0.5 }` and does
+    // feed the sketch path.
+    //
+    // This test exists so the rejection reads as a decision rather than a gap.
+    let err = lower_sql(
+        "SELECT array_agg(service) FROM metrics",
+        &catalog(),
+        AccuracyTarget::Exact,
+    )
+    .await
+    .expect_err("array_agg must not lower to an intent");
+    assert!(
+        format!("{err}").contains("unsupported aggregate: array_agg"),
+        "expected a clean UnsupportedAggregate, got {err}"
+    );
+}
+
+// ── Issue #225: catalog-driven ClickHouse builtins (countIf, generalizing
+// uniqExact from #221) ───────────────────────────────────────────────────
+
+async fn lower_clickhouse(sql: &str) -> Rc<OperatorNode> {
+    lower_sql_dialect(
+        sql,
+        &catalog(),
+        SqlDialect::ClickhouseSQL,
+        AccuracyTarget::Exact,
+    )
+    .await
+    .unwrap_or_else(|e| panic!("lower failed for {sql:?}: {e}"))
+}
+
+fn temporal_aggregate(node: &OperatorNode) -> (&AggIntent, std::time::Duration, &OperatorNode) {
+    match op(node) {
+        NonASAPOp::Aggregate {
+            reduction: Reduction::PerEntity,
+            measures,
+            child,
+            ..
+        } => {
+            let NonASAPOp::TimeRange { range, child, .. } = op(child) else {
+                panic!("temporal Aggregate must directly wrap TimeRange, got {child:?}");
+            };
+            (&measures[0], *range, child)
+        }
+        NonASAPOp::Project { child, .. } | NonASAPOp::Filter { child, .. } => {
+            temporal_aggregate(child)
+        }
+        other => panic!("expected temporal Aggregate, got {other:?}"),
+    }
+}
+
+#[tokio::test]
+async fn explicit_temporal_aggregates_share_promql_intents_and_timerange() {
+    for (function, expected) in [
+        ("asap_rate", AggIntent::Rate),
+        ("asap_increase", AggIntent::Increase),
+    ] {
+        let sql = format!(
+            "SELECT service, {function}(latency, ts, 300000) AS v \
+             FROM metrics WHERE service = 'api' GROUP BY service"
+        );
+        let qe = lower_clickhouse(&sql).await;
+        let (intent, range, child) = temporal_aggregate(&qe);
+        assert_eq!(intent, &expected);
+        assert_eq!(range, std::time::Duration::from_secs(300));
+        assert!(matches!(op(child), NonASAPOp::Project { child, .. }
+            if matches!(op(child), NonASAPOp::Scan { predicates, .. } if predicates.len() == 1)));
+
+        let NonASAPOp::Project { cols, .. } = op(&qe) else {
+            panic!("SELECT list must remain a Project, got {qe:?}");
+        };
+        assert!(matches!(cols[0].expr, ScalarExpr::Column(2)));
+        assert_eq!(cols[1].alias.as_deref(), Some("v"));
+        assert!(matches!(cols[1].expr, ScalarExpr::Column(1)));
+    }
+}
+
+#[tokio::test]
+async fn temporal_aggregate_rejects_non_timestamp_and_non_positive_window() {
+    for sql in [
+        "SELECT asap_rate(latency, bytes, 300000) FROM metrics",
+        "SELECT asap_rate(latency, ts, 0) FROM metrics",
+        "SELECT asap_rate(latency, ts, bytes) FROM metrics",
+    ] {
+        let err = lower_sql_dialect(
+            sql,
+            &catalog(),
+            SqlDialect::ClickhouseSQL,
+            AccuracyTarget::Exact,
+        )
+        .await
+        .expect_err("invalid temporal arguments must fail closed");
+        assert!(
+            format!("{err}").contains("timestamp argument")
+                || format!("{err}").contains("window_ms"),
+            "unexpected error for {sql}: {err}"
+        );
+    }
+}
+
+#[tokio::test]
+async fn temporal_aggregate_rejects_mixed_reducers() {
+    let err = lower_sql_dialect(
+        "SELECT asap_rate(latency, ts, 300000), sum(bytes) FROM metrics",
+        &catalog(),
+        SqlDialect::ClickhouseSQL,
+        AccuracyTarget::Exact,
+    )
+    .await
+    .expect_err("one child cannot carry temporal and ordinary aggregate semantics");
+    assert!(format!("{err}").contains("cannot share an Aggregate node"));
+}
+
+#[tokio::test]
+async fn last_fails_closed_until_an_executable_summary_exists() {
+    let err = lower_sql_dialect(
+        "SELECT service, asap_last(latency, ts, 300000) FROM metrics GROUP BY service",
+        &catalog(),
+        SqlDialect::ClickhouseSQL,
+        AccuracyTarget::Exact,
+    )
+    .await
+    .expect_err("last must not be advertised without an executable physical summary");
+    assert!(format!("{err}").contains("Invalid function 'asap_last'"));
+}
+
+#[tokio::test]
+async fn temporal_grouping_requires_the_complete_declared_series_identity() {
+    let multi_series = SqlCatalog::new().with_table(
+        "samples",
+        Schema::with_time_index(
+            vec![
+                col("ts", DataType::Timestamp),
+                col("service", DataType::Utf8),
+                col("instance", DataType::Utf8),
+                col("value", DataType::Float64),
+            ],
+            0,
+            vec![vec![0, 1, 2]],
+        ),
+    );
+    for sql in [
+        "SELECT asap_rate(value, ts, 300000) FROM samples",
+        "SELECT service, asap_rate(value, ts, 300000) FROM samples GROUP BY service",
+    ] {
+        let err = lower_sql_dialect(
+            sql,
+            &multi_series,
+            SqlDialect::ClickhouseSQL,
+            AccuracyTarget::Exact,
+        )
+        .await
+        .expect_err("partial identity must not merge counter series");
+        assert!(format!("{err}").contains("declared series identity"));
+    }
+
+    lower_sql_dialect(
+        "SELECT service, instance, asap_rate(value, ts, 300000) \
+         FROM samples GROUP BY service, instance",
+        &multi_series,
+        SqlDialect::ClickhouseSQL,
+        AccuracyTarget::Exact,
+    )
+    .await
+    .expect("the complete declared series identity is safe");
+
+    let row_id_only = SqlCatalog::new().with_table(
+        "samples",
+        Schema::with_time_index(
+            vec![
+                col("ts", DataType::Timestamp),
+                col("service", DataType::Utf8),
+                col("value", DataType::Float64),
+            ],
+            0,
+            vec![vec![1]],
+        ),
+    );
+    lower_sql_dialect(
+        "SELECT service, asap_rate(value, ts, 300000) FROM samples GROUP BY service",
+        &row_id_only,
+        SqlDialect::ClickhouseSQL,
+        AccuracyTarget::Exact,
+    )
+    .await
+    .expect_err("a row key without time does not prove a series identity");
+}
+
+#[tokio::test]
+async fn temporal_grouping_rejects_value_time_and_duplicate_resolved_columns() {
+    for sql in [
+        "SELECT asap_rate(latency, ts, 300000) FROM metrics GROUP BY ts",
+        "SELECT asap_rate(latency, ts, 300000) FROM metrics GROUP BY latency",
+        "SELECT m.service, asap_rate(m.latency, m.ts, 300000) \
+         FROM metrics m GROUP BY m.service, service",
+    ] {
+        let err = lower_sql_dialect(
+            sql,
+            &catalog(),
+            SqlDialect::ClickhouseSQL,
+            AccuracyTarget::Exact,
+        )
+        .await
+        .expect_err("unsafe or duplicate resolved grouping must fail closed");
+        let message = format!("{err}");
+        assert!(
+            message.contains("timestamp or value")
+                || message.contains("same resolved column more than once"),
+            "unexpected error for {sql}: {message}"
+        );
+    }
+}
+
+#[tokio::test]
+async fn qualified_columns_are_validated_by_resolved_identity() {
+    let qe = lower_clickhouse(
+        "SELECT m.service, asap_increase(m.latency, m.ts, 300000) AS v \
+         FROM metrics AS m GROUP BY m.service",
+    )
+    .await;
+    let (intent, range, _) = temporal_aggregate(&qe);
+    assert_eq!(intent, &AggIntent::Increase);
+    assert_eq!(range, std::time::Duration::from_secs(300));
+}
+
+#[tokio::test]
+async fn project_filter_and_outer_aggregate_preserve_temporal_child() {
+    let qe = lower_clickhouse(
+        "SELECT max(v) FROM (\
+           SELECT service, asap_rate(latency, ts, 300000) AS v \
+           FROM metrics WHERE bytes > 0 GROUP BY service\
+         ) r WHERE v >= 0",
+    )
+    .await;
+    let NonASAPOp::Project { child, .. } = op(&qe) else {
+        panic!("expected outer SELECT Project, got {qe:?}");
+    };
+    let NonASAPOp::Aggregate {
+        reduction: Reduction::Reduce(_),
+        measures,
+        child,
+        ..
+    } = op(child)
+    else {
+        panic!("expected outer Aggregate, got {child:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Max { .. }]));
+    let NonASAPOp::Filter { child, .. } = op(child) else {
+        panic!("derived-table WHERE must remain above the inner query, got {child:?}");
+    };
+    let (intent, range, _) = temporal_aggregate(child);
+    assert_eq!(intent, &AggIntent::Rate);
+    assert_eq!(range, std::time::Duration::from_secs(300));
+}
+
+#[tokio::test]
+async fn count_if_lowers_to_a_sum_over_a_derived_indicator_column() {
+    // ClickHouse's `countIf(cond)` has no DataFusion equivalent at all, so it
+    // goes through the same stub-UDAF + catalog-driven `FunctionRewrite`
+    // mechanism `uniqExact` (#221) does — rewritten, before `lower_agg_intent`
+    // ever runs, to `sum(CASE WHEN cond THEN 1 ELSE 0 END)`. A per-measure
+    // filter (#466) could express it as a filtered `Count` now; that move is
+    // a follow-up, so the indicator sum is still the shape to expect.
+    let qe = lower_clickhouse("SELECT countIf(bytes > 100) AS big FROM metrics").await;
+    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate");
+    assert!(by.is_empty());
+    assert!(
+        matches!(measures.as_slice(), [AggIntent::Sum { col: Some(_) }]),
+        "expected a Sum bound to the derived indicator column, got {measures:?}"
+    );
+    let (_, materialized) = reducer_input_names(&qe);
+    assert!(
+        materialized,
+        "the indicator expression must be materialized in a Project beneath the Aggregate"
+    );
+}
+
+#[tokio::test]
+async fn two_count_ifs_with_different_conditions_stay_distinct_reducers() {
+    // The corpus pattern (`countIf(operation = 'A'), countIf(operation = 'W')`
+    // in one GROUP BY) needs each call's own condition to survive as its own
+    // derived column, not collapse onto a shared one.
+    let qe = lower_clickhouse(
+        "SELECT service, countIf(bytes > 100) AS big, countIf(bytes <= 100) AS small \
+         FROM metrics GROUP BY service",
+    )
+    .await;
+    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate");
+    assert_eq!(*by, GroupKeys::by(vec![0]));
+    assert!(
+        matches!(
+            measures.as_slice(),
+            [
+                AggIntent::Sum { col: Some(a) },
+                AggIntent::Sum { col: Some(b) }
+            ] if a != b
+        ),
+        "expected two distinct Sum reducers, got {measures:?}"
+    );
+}
+
+#[tokio::test]
+async fn count_if_composes_with_group_by() {
+    let qe = lower_clickhouse(
+        "SELECT service, countIf(bytes > 100) AS big FROM metrics GROUP BY service",
+    )
+    .await;
+    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate");
+    assert_eq!(*by, GroupKeys::by(vec![0]));
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+}
+
+// ── Issue #232: argMax/argMin -- AggIntent::Extension, not a first-class
+// core variant. A repo-wide search (PromQL front end, other SQL dialects,
+// docs) turned up no second deployment model wanting this two-column,
+// row-selecting shape, so per `AggIntent::Extension`'s own "core only grows
+// for intents ≥2 deployment models actually use" bar, it stays an opaque
+// `Extension` rather than a new `ArgMax`/`ArgMin` core variant. Unlike
+// `countIf`/`uniqExact`, there is no native DataFusion aggregate shape to
+// rewrite to (`RewriteKind::PassThrough`) -- `lower_agg_intent` builds the
+// `AggIntent` directly from the ClickHouse name. ─────────────────────────
+
+#[tokio::test]
+async fn arg_max_lowers_to_an_extension_intent() {
+    // No existing `AggIntent` reducer fits: every one folds one column to a
+    // value derived from itself, while `argMax(arg, val)` returns a
+    // *different* column's value, selected by which row maximizes a second.
+    let qe = lower_clickhouse(
+        "SELECT service, argMax(service, latency) AS busiest FROM metrics GROUP BY service",
+    )
+    .await;
+    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate");
+    assert_eq!(
+        *by,
+        GroupKeys::by(vec![1]),
+        "grouped by `service` (schema index 1)"
+    );
+    assert!(
+        matches!(
+            measures.as_slice(),
+            [AggIntent::Extension { ext_kind, .. }] if ext_kind == "arg_max"
+        ),
+        "expected Extension {{ ext_kind: \"arg_max\", .. }}, got {measures:?}"
+    );
+}
+
+#[tokio::test]
+async fn arg_min_lowers_to_its_own_extension_kind() {
+    let qe = lower_clickhouse("SELECT argMin(service, latency) FROM metrics").await;
+    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate");
+    assert!(by.is_empty());
+    assert!(
+        matches!(
+            measures.as_slice(),
+            [AggIntent::Extension { ext_kind, .. }] if ext_kind == "arg_min"
+        ),
+        "expected Extension {{ ext_kind: \"arg_min\", .. }}, got {measures:?}"
+    );
+}
+
+#[tokio::test]
+async fn arg_max_payload_preserves_both_column_names() {
+    // Core never resolves an `Extension`'s payload, so both columns are kept
+    // as validated bare-column `ColumnRef`s in `payload`, not run through
+    // positional `ColumnId` binding -- see `lower_arg_selector`'s doc.
+    let qe = lower_clickhouse("SELECT argMax(service, latency) AS m FROM metrics").await;
+    let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
+    let AggIntent::Extension { payload, .. } = &measures[0] else {
+        panic!("expected an Extension intent, got {:?}", measures[0]);
+    };
+    let named = |key: &str| {
+        payload
+            .get(key)
+            .and_then(|c| c.get("Named"))
+            .and_then(|n| n.as_str())
+            .map(str::to_string)
+    };
+    assert_eq!(named("arg_col"), Some("service".to_string()));
+    assert_eq!(named("val_col"), Some("latency".to_string()));
+}
+
+#[tokio::test]
+async fn arg_max_rejects_a_non_column_argument() {
+    // Same "bare column only" rule as every other reducer (`reducer_col`,
+    // issue #115) -- an expression argument is rejected, not silently
+    // dropped or materialized into the wrong column.
+    let err = lower_sql_dialect(
+        "SELECT argMax(service, latency * 2) FROM metrics",
+        &catalog(),
+        SqlDialect::ClickhouseSQL,
+        AccuracyTarget::Exact,
+    )
+    .await
+    .expect_err("argMax over a non-column expression must be rejected");
+    assert!(
+        format!("{err}").contains("non-column expression"),
+        "got {err}"
+    );
+}
+
+// ── Issue #267: lagInFrame/leadInFrame get distinct WindowFuncKind variants,
+// not conflated with ANSI Lag/Lead ──────────────────────────────────────────
+
+#[tokio::test]
+async fn lag_in_frame_lowers_to_its_own_kind_not_lag() {
+    let qe = lower_clickhouse(
+        "SELECT service, lagInFrame(bytes) OVER (PARTITION BY service ORDER BY ts) \
+         FROM metrics",
+    )
+    .await;
+    let win = find_windowfunc(&qe).expect("expected a SQLWindowFunc node");
+    let NonASAPOp::SQLWindowFunc { func, args, .. } = op(win) else {
+        unreachable!();
+    };
+    assert_eq!(*func, WindowFuncKind::LagInFrame);
+    assert_eq!(
+        args,
+        &vec![ScalarExpr::Column(3)],
+        "lagInFrame(bytes) → arg col 3"
+    );
+}
+
+#[tokio::test]
+async fn lead_in_frame_lowers_to_its_own_kind_not_lead() {
+    let qe = lower_clickhouse(
+        "SELECT service, leadInFrame(bytes) OVER (PARTITION BY service ORDER BY ts) \
+         FROM metrics",
+    )
+    .await;
+    let win = find_windowfunc(&qe).expect("expected a SQLWindowFunc node");
+    let NonASAPOp::SQLWindowFunc { func, .. } = op(win) else {
+        unreachable!();
+    };
+    assert_eq!(*func, WindowFuncKind::LeadInFrame);
+}
+
+/// Issue #184: `NOW()` in a predicate must lower to the timestamp-typed
+/// `CurrentTimestamp` leaf, not the semantically-opaque function catch-all or
+/// PromQL's Float64 Unix-seconds `EvalTimestamp`.
+#[tokio::test]
+async fn now_in_predicate_lowers_to_current_timestamp() {
+    // SELECT * folds WHERE onto Scan.predicates (no explicit Filter node).
+    let qe = lower("SELECT * FROM metrics WHERE ts < NOW()").await;
+    let NonASAPOp::Scan { predicates, .. } = op(&qe) else {
+        panic!("expected Scan at root, got {qe:?}");
+    };
+    assert_eq!(predicates.len(), 1);
+    assert!(
+        matches!(&predicates[0].0, ScalarExpr::Compare { right, .. }
+            if matches!(right.as_ref(), ScalarExpr::Cast { expr, to: DataType::Timestamp, .. } if matches!(expr.as_ref(), ScalarExpr::CurrentTimestamp))),
+        "NOW() must lower to CurrentTimestamp, got {:?}",
+        predicates[0].0
+    );
+}
+
+/// Same for ClickHouse's `now()`, since #184 was raised specifically against
+/// the ClickHouse dialect.
+#[tokio::test]
+async fn clickhouse_now_in_predicate_lowers_to_current_timestamp() {
+    let qe = lower_clickhouse("SELECT * FROM metrics WHERE ts < now()").await;
+    let NonASAPOp::Scan { predicates, .. } = op(&qe) else {
+        panic!("expected Scan at root, got {qe:?}");
+    };
+    assert_eq!(predicates.len(), 1);
+    assert!(
+        matches!(&predicates[0].0, ScalarExpr::Compare { right, .. }
+            if matches!(right.as_ref(), ScalarExpr::Cast { expr, to: DataType::Timestamp, .. } if matches!(expr.as_ref(), ScalarExpr::CurrentTimestamp))),
+        "now() must lower to CurrentTimestamp, got {:?}",
+        predicates[0].0
+    );
+}
+
+#[tokio::test]
+async fn current_timestamp_lowers_to_typed_current_timestamp_leaf() {
+    let qe = lower("SELECT CURRENT_TIMESTAMP FROM metrics").await;
+    let NonASAPOp::Project { cols, child, .. } = op(&qe) else {
+        panic!("expected Project at root, got {qe:?}");
+    };
+    assert!(matches!(&cols[0].expr, ScalarExpr::CurrentTimestamp));
+    let (dtype, _) = cols[0]
+        .expr
+        .scalar_type(&child.schema)
+        .expect("timestamp type");
+    assert_eq!(dtype, DataType::Timestamp);
+    assert_eq!(qe.schema.fields[0].dtype, DataType::Timestamp);
+}
+
+// A `count` over a non-null input is a plain row count; over a nullable
+// input it keeps SQL's NULL-skipping as the measure's own filter (#466), and
+// only the multi-level grouping path, which cannot carry one, still rejects it.
+#[tokio::test]
+async fn count_null_semantics_become_a_measure_filter() {
+    let catalog = SqlCatalog::new().with_table(
+        "samples",
+        Schema::new(vec![
+            Field::plain("nullable_value", DataType::Float64, true),
+            Field::plain("value", DataType::Float64, false),
+        ]),
+    );
+    for sql in [
+        "SELECT count(*) FROM samples",
+        "SELECT count(1) FROM samples",
+        "SELECT count(value) FROM samples",
+        "SELECT count(value + 1) FROM samples",
+    ] {
+        let qe = lower_sql(sql, &catalog, AccuracyTarget::Exact)
+            .await
+            .unwrap_or_else(|error| panic!("{sql}: {error}"));
+        assert!(
+            aggregate_filters(&qe).is_empty(),
+            "{sql}: unfiltered row count"
+        );
+    }
+    for sql in [
+        "SELECT count(nullable_value) FROM samples",
+        "SELECT count(NULL) FROM samples",
+        "SELECT count(nullable_value + 1) FROM samples",
+    ] {
+        let qe = lower_sql(sql, &catalog, AccuracyTarget::Exact)
+            .await
+            .unwrap_or_else(|error| panic!("{sql}: {error}"));
+        let [Some(Predicate(cond))] = aggregate_filters(&qe) else {
+            panic!(
+                "{sql}: expected one filtered Count, got {:?}",
+                aggregate_filters(&qe)
+            );
+        };
+        assert!(matches!(cond, ScalarExpr::IsNotNull(_)), "{sql}: {cond:?}");
+    }
+    // Only the second measure is filtered.
+    let qe = lower_sql(
+        "SELECT count(*), count(nullable_value) FROM samples",
+        &catalog,
+        AccuracyTarget::Exact,
+    )
+    .await
+    .unwrap();
+    assert!(matches!(aggregate_filters(&qe), [None, Some(_)]));
+    let error = lower_sql(
+        "SELECT count(nullable_value) FROM samples GROUP BY ROLLUP(value)",
+        &catalog,
+        AccuracyTarget::Exact,
+    )
+    .await
+    .unwrap_err();
+    assert!(
+        matches!(error, LoweringError::UnsupportedFeature(_)),
+        "{error}"
+    );
+}
+
+/// A native SQL map grouping key retains its typed key/value schema.
+#[tokio::test]
+async fn grouped_map_column_preserves_map_type() {
+    let map = DataType::Map {
+        key: Box::new(DataType::Utf8),
+        value: Box::new(DataType::Utf8),
+        value_nullable: false,
+    };
+    let catalog = SqlCatalog::new().with_table(
+        "raw_samples",
+        Schema::new(vec![
+            col("labels", map.clone()),
+            col("value", DataType::Float64),
+        ]),
+    );
+    let query = lower_sql_dialect(
+        "SELECT labels, max(value) AS value FROM raw_samples GROUP BY labels ORDER BY labels",
+        &catalog,
+        SqlDialect::ClickhouseSQL,
+        AccuracyTarget::Exact,
+    )
+    .await
+    .unwrap();
+    assert_eq!(query.schema.fields[0].dtype, map);
+}
+
+#[tokio::test]
+async fn clickhouse_modulo_uses_native_arithmetic_types_and_nullability() {
+    let catalog = SqlCatalog::new().with_table(
+        "numbers",
+        Schema::new(vec![
+            Field::plain("i", DataType::Int64, false),
+            Field::plain("n", DataType::Int64, true),
+            Field::plain("f", DataType::Float64, false),
+        ]),
+    );
+    for (call, native) in [
+        ("modulo(i, 3)", "i % 3"),
+        ("modulo(n, -3)", "n % -3"),
+        ("modulo(f, 2.5)", "f % 2.5"),
+        ("modulo(-7, 3)", "-7 % 3"),
+        ("modulo(i, 0)", "i % 0"),
+        ("modulo(modulo(i, 5), 2)", "(i % 5) % 2"),
+    ] {
+        let function = lower_sql_dialect(
+            &format!("SELECT {call} AS value FROM numbers"),
+            &catalog,
+            SqlDialect::ClickhouseSQL,
+            AccuracyTarget::Exact,
+        )
+        .await
+        .unwrap();
+        let operator = lower_sql_dialect(
+            &format!("SELECT {native} AS value FROM numbers"),
+            &catalog,
+            SqlDialect::ClickhouseSQL,
+            AccuracyTarget::Exact,
+        )
+        .await
+        .unwrap();
+        assert_eq!(function, operator, "{call}");
+        assert_eq!(function.schema, operator.schema);
+    }
+    let nullable = lower_sql_dialect(
+        "SELECT modulo(n, 3) AS value FROM numbers",
+        &catalog,
+        SqlDialect::ClickhouseSQL,
+        AccuracyTarget::Exact,
+    )
+    .await
+    .unwrap()
+    .schema
+    .clone();
+    assert_eq!(nullable.fields[0].dtype, DataType::Int64);
+    assert!(nullable.fields[0].nullable);
+}
+
+#[tokio::test]
+async fn original_o11y_map_queries_lower_with_typed_results() {
+    let catalog = SqlCatalog::new().with_table(
+        "raw_samples",
+        Schema::new(vec![
+            Field::plain("metric", DataType::Utf8, false),
+            Field::plain("ts_ms", DataType::Int64, false),
+            Field::plain("value", DataType::Float64, false),
+            Field::plain(
+                "labels",
+                DataType::Map {
+                    key: Box::new(DataType::Utf8),
+                    value: Box::new(DataType::Utf8),
+                    value_nullable: false,
+                },
+                false,
+            ),
+        ]),
+    );
+    for sql in [
+        include_str!("data/o11y_q10.sql"),
+        include_str!("data/o11y_q27.sql"),
+        include_str!("data/o11y_q07.sql"),
+        include_str!("data/o11y_q09.sql"),
+        include_str!("data/o11y_q12.sql"),
+    ] {
+        let query = lower_sql_dialect(
+            sql,
+            &catalog,
+            SqlDialect::ClickhouseSQL,
+            AccuracyTarget::Exact,
+        )
+        .await
+        .unwrap_or_else(|e| panic!("{sql}: {e}"));
+        let schema = &query.schema;
+        assert!(
+            schema
+                .fields
+                .iter()
+                .any(|column| matches!(column.dtype, FieldDataType::Plain(DataType::Map { .. }))),
+            "{schema:?}"
+        );
+    }
+}
+
+#[tokio::test]
+async fn clickhouse_modulo_preserves_projection_names_and_outer_references() {
+    for (sql, name) in [
+        ("SELECT modulo(bytes, 3) FROM metrics", "modulo(bytes, 3)"),
+        (
+            "SELECT modulo(bytes, 3) AS remainder FROM metrics",
+            "remainder",
+        ),
+        (
+            "SELECT \"modulo(bytes, 3)\" FROM (SELECT modulo(bytes, 3) FROM metrics) t",
+            "modulo(bytes, 3)",
+        ),
+    ] {
+        let query = lower_sql_dialect(
+            sql,
+            &catalog(),
+            SqlDialect::ClickhouseSQL,
+            AccuracyTarget::Exact,
+        )
+        .await
+        .unwrap();
+        assert_eq!(query.schema.fields[0].name, name);
+    }
+}
+
+#[tokio::test]
+async fn clickhouse_map_access_keeps_generated_names_and_rejects_variant_coercion() {
+    let catalog = SqlCatalog::new().with_table(
+        "t",
+        Schema::new(vec![
+            Field::plain(
+                "labels",
+                DataType::Map {
+                    key: Box::new(DataType::Utf8),
+                    value: Box::new(DataType::Utf8),
+                    value_nullable: false,
+                },
+                false,
+            ),
+            Field::plain("integer", DataType::Int64, false),
+            Field::plain("floating", DataType::Float64, false),
+        ]),
+    );
+    let query = lower_sql_dialect(
+        "SELECT labels['job'] FROM t",
+        &catalog,
+        SqlDialect::ClickhouseSQL,
+        AccuracyTarget::Exact,
+    )
+    .await
+    .unwrap();
+    let output = &query.schema;
+    assert_eq!(output.fields[0].name, "arrayElement(labels, 'job')");
+    assert_eq!(output.fields[0].dtype, DataType::Utf8);
+    assert!(!output.fields[0].nullable);
+    assert!(lower_sql_dialect(
+        "SELECT map()['a'] FROM t",
+        &catalog,
+        SqlDialect::ClickhouseSQL,
+        AccuracyTarget::Exact,
+    )
+    .await
+    .is_err());
+    assert!(lower_sql_dialect(
+        "SELECT map('a', integer, 'b', floating) FROM t",
+        &catalog,
+        SqlDialect::ClickhouseSQL,
+        AccuracyTarget::Exact
+    )
+    .await
+    .is_err());
+}
+
+#[tokio::test]
+async fn arg_selector_result_schema_tracks_selected_argument() {
+    let catalog = SqlCatalog::new().with_table(
+        "t",
+        Schema::new(vec![
+            Field::plain("v", DataType::Float64, false),
+            Field::plain("text", DataType::Utf8, true),
+            Field::plain("ts", DataType::Int64, true),
+        ]),
+    );
+    for (sql, dtype, nullable) in [
+        (
+            "SELECT argMax(v, ts) AS value FROM t",
+            DataType::Float64,
+            false,
+        ),
+        (
+            "SELECT argMin(text, ts) AS value FROM t",
+            DataType::Utf8,
+            true,
+        ),
+    ] {
+        let query = lower_sql_dialect(
+            sql,
+            &catalog,
+            SqlDialect::ClickhouseSQL,
+            AccuracyTarget::Exact,
+        )
+        .await
+        .unwrap();
+        let schema = &query.schema;
+        assert_eq!(schema.fields[0].dtype, dtype);
+        assert_eq!(schema.fields[0].nullable, nullable);
+    }
+}
+
+#[tokio::test]
+async fn clickhouse_list_element_uses_canonical_typed_access() {
+    let catalog = SqlCatalog::new().with_table(
+        "t",
+        Schema::new(vec![
+            Field::plain(
+                "samples",
+                DataType::List {
+                    element: Box::new(Field::new("item", DataType::Int64, false)),
+                },
+                false,
+            ),
+            Field::plain("index", DataType::Int64, true),
+        ]),
+    );
+    for (sql, nullable) in [
+        ("SELECT samples[1] AS selected FROM t", false),
+        ("SELECT arrayElement(samples, -1) AS selected FROM t", false),
+        ("SELECT samples[index] AS selected FROM t", true),
+    ] {
+        let query = lower_sql_dialect(
+            sql,
+            &catalog,
+            SqlDialect::ClickhouseSQL,
+            AccuracyTarget::Exact,
+        )
+        .await
+        .unwrap();
+        let output = &query.schema;
+        assert_eq!(output.fields[0].dtype, DataType::Int64);
+        assert_eq!(output.fields[0].nullable, nullable);
+        let serialized = serde_json::to_string(&query).unwrap();
+        assert!(serialized.contains("asap_element_access"), "{serialized}");
+    }
+    for sql in ["SELECT samples[0] FROM t", "SELECT samples['bad'] FROM t"] {
+        assert!(
+            lower_sql_dialect(
+                sql,
+                &catalog,
+                SqlDialect::ClickhouseSQL,
+                AccuracyTarget::Exact
+            )
+            .await
+            .is_err(),
+            "{sql}"
+        );
+    }
+}
+
+#[tokio::test]
+async fn clickhouse_tuple_element_preserves_declared_field_metadata() {
+    let catalog = SqlCatalog::new().with_table(
+        "t",
+        Schema::new(vec![
+            Field::plain(
+                "sample",
+                DataType::Struct {
+                    fields: vec![
+                        Field::new("time", DataType::Int64, false),
+                        Field::new("value", DataType::Float64, true),
+                    ],
+                },
+                false,
+            ),
+            Field::plain("index", DataType::Int64, false),
+        ]),
+    );
+    for (sql, dtype, nullable) in [
+        (
+            "SELECT tupleElement(sample, 1) AS chosen FROM t",
+            DataType::Int64,
+            false,
+        ),
+        (
+            "SELECT tupleElement(sample, 'value') AS chosen FROM t",
+            DataType::Float64,
+            true,
+        ),
+    ] {
+        let query = lower_sql_dialect(
+            sql,
+            &catalog,
+            SqlDialect::ClickhouseSQL,
+            AccuracyTarget::Exact,
+        )
+        .await
+        .unwrap();
+        let output = &query.schema;
+        assert_eq!(output.fields[0].dtype, dtype);
+        assert_eq!(output.fields[0].nullable, nullable);
+        assert!(serde_json::to_string(&query)
+            .unwrap()
+            .contains("asap_struct_field"));
+    }
+    for selector in ["0", "-1", "3", "'missing'", "index"] {
+        let sql = format!("SELECT tupleElement(sample, {selector}) FROM t");
+        assert!(
+            lower_sql_dialect(
+                &sql,
+                &catalog,
+                SqlDialect::ClickhouseSQL,
+                AccuracyTarget::Exact
+            )
+            .await
+            .is_err(),
+            "{sql}"
+        );
+    }
+}
+
+/// Correlation lowers to a nullable numeric result instead of UnsupportedAggregate.
+#[tokio::test]
+async fn corr_result_is_nullable_float() {
+    let query = lower("SELECT corr(latency, bytes) AS correlation FROM metrics").await;
+    let schema = &query.schema;
+    assert_eq!(schema.fields[0].name, "correlation");
+    assert_eq!(schema.fields[0].dtype, DataType::Float64);
+    assert!(schema.fields[0].nullable);
+}
+
+// A multi-column DISTINCT counts tuples; one column stays the single-column
+// intent, so neither form can be mistaken for the other downstream.
+#[tokio::test]
+async fn composite_distinct_counts_tuples() {
+    let cat = SqlCatalog::new().with_table(
+        "t",
+        Schema::new(vec![
+            Field::plain("a", DataType::Int64, false),
+            Field::plain("b", DataType::Int64, false),
+        ]),
+    );
+    let composite = lower_sql(
+        "SELECT COUNT(DISTINCT a, b) FROM t",
+        &cat,
+        AccuracyTarget::Exact,
+    )
+    .await
+    .unwrap();
+    let NonASAPOp::Aggregate { measures, .. } =
+        op(find_aggregate_node(&composite).expect("expected an Aggregate"))
+    else {
+        unreachable!()
+    };
+    assert!(
+        matches!(measures.as_slice(), [AggIntent::Cardinality { cols, .. }] if cols == &[0, 1]),
+        "{measures:?}"
+    );
+
+    let single = lower_sql(
+        "SELECT COUNT(DISTINCT a) FROM t",
+        &cat,
+        AccuracyTarget::Exact,
+    )
+    .await
+    .unwrap();
+    let NonASAPOp::Aggregate { measures, .. } =
+        op(find_aggregate_node(&single).expect("expected an Aggregate"))
+    else {
+        unreachable!()
+    };
+    assert!(
+        matches!(measures.as_slice(), [AggIntent::Cardinality { cols, .. }] if cols == &[0]),
+        "{measures:?}"
+    );
+}
+
+// An expression argument has no column identity to hash, so it is rejected
+// rather than silently reduced over a probe column.
+#[tokio::test]
+async fn composite_distinct_rejects_expression_arguments() {
+    let cat = SqlCatalog::new().with_table(
+        "t",
+        Schema::new(vec![
+            Field::plain("a", DataType::Int64, false),
+            Field::plain("b", DataType::Int64, false),
+        ]),
+    );
+    let error = lower_sql(
+        "SELECT COUNT(DISTINCT a, b + 1) FROM t",
+        &cat,
+        AccuracyTarget::Exact,
+    )
+    .await
+    .unwrap_err();
+    assert!(
+        matches!(&error, LoweringError::UnsupportedAggregate(reason)
+            if reason.contains("non-column expression")),
+        "{error}"
+    );
+}
+
+// DISTINCT inputs survive projections introduced by sibling aggregates.
+#[tokio::test]
+async fn distinct_with_derived_sibling() {
+    let catalog = SqlCatalog::new().with_table(
+        "t",
+        Schema::new(vec![
+            Field::plain("a", DataType::Int64, false),
+            Field::plain("b", DataType::Int64, false),
+        ]),
+    );
+    for sql in [
+        "SELECT count(DISTINCT a), sum(b + 1) FROM t",
+        "SELECT count(DISTINCT a, b), sum(b + 1) FROM t",
+        "SELECT count(DISTINCT a, b), corr(a,b) FROM t",
+    ] {
+        let result = lower_sql(sql, &catalog, AccuracyTarget::Exact).await;
+        assert!(result.is_ok(), "{sql}: {result:?}");
+    }
+}
+
+// ── Issue #466: per-measure FILTER predicates ─────────────────────────────────
+
+/// The first `Aggregate`'s `filters`, positional against its child.
+fn aggregate_filters(qe: &OperatorNode) -> &[Option<Predicate>] {
+    let Some(NonASAPOp::Aggregate { filters, .. }) =
+        find_aggregate_node(qe).map(|n| n.expect_non_asap())
+    else {
+        panic!("expected an Aggregate, got {qe:?}");
+    };
+    filters
+}
+
+// The motivating query: one scan, one grouping, one conditional count next to
+// a plain sum — a single `Aggregate` whose Count carries the condition, with no
+// `Join` and no derived column for the `CASE`.
+#[tokio::test]
+async fn conditional_count_lowers_to_a_filtered_measure() {
+    let qe = lower(
+        "SELECT service, count(CASE WHEN latency > 1.0 THEN 1 END), sum(bytes) \
+         FROM metrics GROUP BY service",
+    )
+    .await;
+    assert!(find_join(&qe).is_none(), "no join: {qe:?}");
+    let (by, measures) = find_aggregate(&qe).unwrap();
+    assert_eq!(by.keys(), &[1]);
+    assert!(
+        matches!(
+            measures.as_slice(),
+            [AggIntent::Count { .. }, AggIntent::Sum { col: Some(3) }]
+        ),
+        "{measures:?}"
+    );
+    let [Some(Predicate(cond)), None] = aggregate_filters(&qe) else {
+        panic!("expected [Some, None], got {:?}", aggregate_filters(&qe));
+    };
+    assert!(
+        matches!(cond, ScalarExpr::Compare { left, op: CompareOpKind::Gt, .. }
+            if matches!(left.as_ref(), ScalarExpr::Column(2))),
+        "latency > 1.0 against the scan, got {cond:?}"
+    );
+    let Some(NonASAPOp::Aggregate { child, .. }) =
+        find_aggregate_node(&qe).map(|n| n.expect_non_asap())
+    else {
+        unreachable!()
+    };
+    assert!(
+        matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }),
+        "{child:?}"
+    );
+}
+
+// `FILTER (WHERE …)` parses under the DataFusion dialect and lands on exactly
+// the measure it annotates.
+#[tokio::test]
+async fn filter_clause_lowers_to_a_measure_filter() {
+    let qe = lower("SELECT sum(bytes) FILTER (WHERE service = 'a'), count(*) FROM metrics").await;
+    let [Some(Predicate(cond)), None] = aggregate_filters(&qe) else {
+        panic!("expected [Some, None], got {:?}", aggregate_filters(&qe));
+    };
+    assert!(
+        matches!(cond, ScalarExpr::Compare { left, op: CompareOpKind::Eq, right, .. }
+            if matches!(left.as_ref(), ScalarExpr::Column(1))
+                && matches!(right.as_ref(), ScalarExpr::Literal(ScalarValue::Utf8(s)) if s == "a")),
+        "{cond:?}"
+    );
+}
+
+// SQL `count(expr)` skips NULLs; canonical `Count` counts rows and never sees
+// `expr`, so a nullable argument becomes the measure filter `expr IS NOT NULL`
+// instead of being rejected (the pre-#466 behavior) or silently over-counted.
+#[tokio::test]
+async fn count_of_a_nullable_expression_filters_nulls() {
+    let qe = lower("SELECT count(nullif(bytes, 0)) FROM metrics").await;
+    let [Some(Predicate(cond))] = aggregate_filters(&qe) else {
+        panic!("expected [Some], got {:?}", aggregate_filters(&qe));
+    };
+    assert!(matches!(cond, ScalarExpr::IsNotNull(_)), "{cond:?}");
+    assert!(
+        matches!(
+            find_aggregate(&qe).unwrap().1.as_slice(),
+            [AggIntent::Count { .. }]
+        ),
+        "still a row count"
+    );
+}
+
+// The columns a measure filter reads must survive the derived-column
+// `Project` a reducer expression inserts beneath the aggregate.
+#[tokio::test]
+async fn measure_filter_columns_survive_a_derived_column_projection() {
+    let qe = lower("SELECT sum(bytes * 2) FILTER (WHERE latency > 1.0) FROM metrics").await;
+    let Some(NonASAPOp::Aggregate { child, .. }) =
+        find_aggregate_node(&qe).map(|n| n.expect_non_asap())
+    else {
+        unreachable!()
+    };
+    assert!(
+        matches!(child.expect_non_asap(), NonASAPOp::Project { .. }),
+        "{child:?}"
+    );
+    let [Some(Predicate(cond))] = aggregate_filters(&qe) else {
+        panic!("expected [Some], got {:?}", aggregate_filters(&qe));
+    };
+    let ScalarExpr::Compare { left, .. } = cond else {
+        panic!("{cond:?}");
+    };
+    let ScalarExpr::Column(id) = left.as_ref() else {
+        panic!("{left:?}");
+    };
+    assert_eq!(child.schema.fields[*id].name, "latency");
+}
+
+// `GROUP BY ROLLUP` fans one measure list out into one `Aggregate` per level;
+// a filtered measure there is rejected rather than silently unfiltered.
+#[tokio::test]
+async fn measure_filter_inside_a_rollup_is_rejected() {
+    let err = lower_sql(
+        "SELECT service, count(*) FILTER (WHERE latency > 1.0) FROM metrics GROUP BY ROLLUP(service)",
+        &catalog(),
+        AccuracyTarget::Exact,
+    )
+    .await
+    .unwrap_err();
+    assert!(matches!(err, LoweringError::UnsupportedFeature(_)), "{err}");
+}
diff --git a/crates/types/src/ir/mod.rs b/crates/types/src/ir/mod.rs
index 04b9f33e3..d4885bff2 100644
--- a/crates/types/src/ir/mod.rs
+++ b/crates/types/src/ir/mod.rs
@@ -1,6 +1,5 @@
 //! Unified operator and scalar representation from #511.
-//! Graph algorithms are added in the next stack layer; legacy consumers
-//! remain on their existing representation until the planner cutover.
+//! Legacy consumers remain on their existing representation until the planner cutover.
 pub mod aggregate_schema;
 pub mod asap;
 pub mod error;
@@ -22,3 +21,5 @@ pub mod export;
 /// Semantic observation coverage, separate from field layout and physical timing.
 pub mod summary_coverage;
 mod wire;
+
+pub mod schema_support;
diff --git a/crates/types/src/ir/schema_support.rs b/crates/types/src/ir/schema_support.rs
new file mode 100644
index 000000000..c710c8654
--- /dev/null
+++ b/crates/types/src/ir/schema_support.rs
@@ -0,0 +1,85 @@
+//! Series-identity realization for the unified dag.
+use crate::pre_asap::schema::*;
+pub fn with_promql_series_identity(
+    root: &std::rc::Rc<crate::ir::OperatorNode>,
+) -> Result<std::rc::Rc<crate::ir::OperatorNode>, String> {
+    use crate::ir::{NonASAPOp, Operator, OperatorNode};
+    use crate::pre_asap::Source;
+    use std::{collections::HashMap, rc::Rc};
+    fn visit(
+        node: &Rc<OperatorNode>,
+        memo: &mut HashMap<*const OperatorNode, Rc<OperatorNode>>,
+    ) -> Result<Rc<OperatorNode>, String> {
+        if let Some(found) = memo.get(&Rc::as_ptr(node)) {
+            return Ok(Rc::clone(found));
+        }
+        let mut error = None;
+        let mut operator = node
+            .operator
+            .map_children(|child| match visit(child, memo) {
+                Ok(child) => child,
+                Err(e) => {
+                    error = Some(e);
+                    Rc::clone(child)
+                }
+            });
+        if let Some(error) = error {
+            return Err(error);
+        }
+        match &mut operator {
+            Operator::NonASAP(NonASAPOp::Scan {
+                source: Source::TimeSeries { .. },
+                schema,
+                ..
+            }) => {
+                if schema
+                    .fields
+                    .iter()
+                    .any(|field| field.name == PROMQL_SERIES_IDENTITY)
+                {
+                    if !schema.has_promql_series_identity() {
+                        return Err("invalid physical series identity".into());
+                    }
+                    memo.insert(Rc::as_ptr(node), Rc::clone(node));
+                    return Ok(Rc::clone(node));
+                }
+                if schema.closed {
+                    return Err("dynamic series identity requires an open PromQL source".into());
+                }
+                schema.fields.push(Field::new(
+                    PROMQL_SERIES_IDENTITY,
+                    FieldDataType::Plain(DataType::Utf8),
+                    false,
+                ));
+                schema.closed = true;
+            }
+            Operator::NonASAP(NonASAPOp::Sort { partition_by, .. })
+                if partition_by.is_without() =>
+            {
+                return Err("dynamic without ranking requires label-set projection".into());
+            }
+            Operator::NonASAP(
+                NonASAPOp::TimeRange { .. }
+                | NonASAPOp::Limit { .. }
+                | NonASAPOp::Project { .. }
+                | NonASAPOp::Filter { .. }
+                | NonASAPOp::TimeShift { .. }
+                | NonASAPOp::PromqlSubquery { .. }
+                | NonASAPOp::PromqlRelabel { .. }
+                | NonASAPOp::PromqlVectorFromScalar(_)
+                | NonASAPOp::BinaryOp { .. }
+                | NonASAPOp::Concat { .. }
+                | NonASAPOp::Aggregate { .. }
+                | NonASAPOp::Sort { .. },
+            ) => {}
+            _ => return Err("operator has no dynamic series-identity realization".into()),
+        }
+        let mut rebuilt = OperatorNode::new(operator).map_err(|e| e.to_string())?;
+        rebuilt.guarantee = node.guarantee.clone();
+        rebuilt.timing = node.timing;
+        let rebuilt = Rc::new(rebuilt);
+        memo.insert(Rc::as_ptr(node), Rc::clone(&rebuilt));
+        Ok(rebuilt)
+    }
+    visit(root, &mut HashMap::new())
+}
diff --git a/crates/types/src/pre_asap/mod.rs b/crates/types/src/pre_asap/mod.rs
index f434eb154..1a017ec27 100644
--- a/crates/types/src/pre_asap/mod.rs
+++ b/crates/types/src/pre_asap/mod.rs
@@ -62,3 +62,5 @@ pub use query_expr::{
 pub use resolve::{resolve_root, ResolveDAGError};
 pub use schema::{ColumnId, DataType, Field, FieldDataType, Schema};
 pub use schema_resolver::{SchemaCatalog, SchemaResolver, UsageDerivedCatalog};
+
+pub use crate::ir::SchemaDerivationError;

From c664f59556f2c22bc111bb1fed6b64486a2d3190 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Mon, 5 Oct 2026 04:19:16 +0000
Subject: [PATCH 29/48] fix: integrate with #614 (DataFusion 54) in the unified
 SQL lowering

Port DF 54's API changes (Expr::Literal metadata, Cast/TryCast field,
ScalarUDFImpl return_field_from_args/invoke_with_args, catalog path,
dialect name) and the planner behaviour changes (SELECT * keeps its
projection, GenericDialect parses aggregate FILTER) from main's
crates/frontend-sql/src/sql onto the unified copy and its tests.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/frontend-sql/src/unified/error.rs      |  16 +-
 .../src/unified/sql/clickhouse_ast.rs         |  83 ++++----
 .../src/unified/sql/collection_planning.rs    |  87 ++++----
 .../frontend-sql/src/unified/sql/dialect.rs   | 112 ----------
 crates/frontend-sql/src/unified/sql/expr.rs   |  11 +-
 crates/frontend-sql/src/unified/sql/mod.rs    | 193 +++++++++---------
 .../tests/unified_sql_lowering.rs             |  31 ++-
 7 files changed, 234 insertions(+), 299 deletions(-)
 delete mode 100644 crates/frontend-sql/src/unified/sql/dialect.rs

diff --git a/crates/frontend-sql/src/unified/error.rs b/crates/frontend-sql/src/unified/error.rs
index f819cfd46..059404ac1 100644
--- a/crates/frontend-sql/src/unified/error.rs
+++ b/crates/frontend-sql/src/unified/error.rs
@@ -57,7 +57,19 @@ impl From<ResolveDAGError> for SqlError {
 }
 
 impl From<datafusion::error::DataFusionError> for SqlError {
-    fn from(e: datafusion::error::DataFusionError) -> Self {
-        Self::DataFusion(e)
+    fn from(mut e: datafusion::error::DataFusionError) -> Self {
+        use datafusion::error::DataFusionError;
+        // Report the first underlying `Plan`/`SQL`/... error. The planner
+        // collects every error it finds and wraps each with a source-span
+        // diagnostic; neither carries anything this front end reports.
+        loop {
+            e = match e {
+                DataFusionError::Diagnostic(_, inner) => *inner,
+                DataFusionError::Collection(errors) if !errors.is_empty() => {
+                    errors.into_iter().next().unwrap()
+                }
+                other => break Self::DataFusion(other),
+            };
+        }
     }
 }
diff --git a/crates/frontend-sql/src/unified/sql/clickhouse_ast.rs b/crates/frontend-sql/src/unified/sql/clickhouse_ast.rs
index c68a803be..f9246d22a 100644
--- a/crates/frontend-sql/src/unified/sql/clickhouse_ast.rs
+++ b/crates/frontend-sql/src/unified/sql/clickhouse_ast.rs
@@ -1,11 +1,13 @@
 //! Structural ClickHouse syntax normalization before DataFusion type inference.
 use datafusion::sql::sqlparser::ast::{
-    visit_expressions, visit_expressions_mut, BinaryOperator, Expr, Function, FunctionArg,
-    FunctionArgExpr, FunctionArgumentList, FunctionArguments, Ident, MapAccessSyntax, ObjectName,
-    Query, SelectItem, SetExpr, Statement, VisitMut, VisitorMut,
+    visit_expressions, visit_expressions_mut, AccessExpr, BinaryOperator, Expr, Function,
+    FunctionArg, FunctionArgExpr, FunctionArgumentList, FunctionArguments, Ident, ObjectName,
+    ObjectNamePart, Query, SelectItem, SetExpr, Statement, Subscript, Value, VisitMut, VisitorMut,
 };
 use std::ops::ControlFlow;
 
+use super::collection_planning::MAP_PLANNING_NAME;
+
 pub(super) fn normalize(statement: &mut Statement) {
     struct PreserveNames;
     impl VisitorMut for PreserveNames {
@@ -23,28 +25,24 @@ pub(super) fn normalize(statement: &mut Statement) {
                                 });
                                 let _: ControlFlow<()> = visit_expressions(expr, |candidate| {
                                     if let Expr::Function(function) = candidate {
-                                        changed |= function.name.0.len() == 1
-                                            && function.name.0[0].quote_style.is_none()
-                                            && matches!(
-                                                function.name.0[0]
-                                                    .value
-                                                    .to_ascii_lowercase()
-                                                    .as_str(),
-                                                "modulo"
-                                                    | "map"
-                                                    | "mapconcat"
-                                                    | "arrayelement"
-                                                    | "tupleelement"
-                                            );
+                                        changed |=
+                                            unquoted_name(&function.name).is_some_and(|name| {
+                                                matches!(
+                                                    name.to_ascii_lowercase().as_str(),
+                                                    "modulo"
+                                                        | "map"
+                                                        | "mapconcat"
+                                                        | "arrayelement"
+                                                        | "tupleelement"
+                                                )
+                                            });
                                     }
                                     ControlFlow::Continue(())
                                 });
                                 if changed {
                                     let alias = Ident::with_quote('"', expr.to_string());
-                                    let value = std::mem::replace(
-                                        expr,
-                                        Expr::Value(datafusion::sql::sqlparser::ast::Value::Null),
-                                    );
+                                    let value =
+                                        std::mem::replace(expr, Expr::Value(Value::Null.into()));
                                     *item = SelectItem::ExprWithAlias { expr: value, alias };
                                 }
                             }
@@ -67,9 +65,11 @@ pub(super) fn normalize(statement: &mut Statement) {
         let Expr::Function(function) = expr else {
             return ControlFlow::Continue(());
         };
-        if function.name.0.len() != 1
-            || function.name.0[0].quote_style.is_some()
-            || !function.name.0[0].value.eq_ignore_ascii_case("modulo")
+        if unquoted_name(&function.name).is_some_and(|name| name.eq_ignore_ascii_case("map")) {
+            function.name = ObjectName::from(vec![Ident::new(MAP_PLANNING_NAME)]);
+            return ControlFlow::Continue(());
+        }
+        if !unquoted_name(&function.name).is_some_and(|name| name.eq_ignore_ascii_case("modulo"))
             || !matches!(function.parameters, FunctionArguments::None)
             || function.filter.is_some()
             || function.over.is_some()
@@ -98,34 +98,47 @@ pub(super) fn normalize(statement: &mut Statement) {
     });
 }
 
+/// The name of a single-part, unquoted function name such as `modulo`.
+fn unquoted_name(name: &ObjectName) -> Option<&str> {
+    match name.0.as_slice() {
+        [ObjectNamePart::Identifier(ident)] if ident.quote_style.is_none() => Some(&ident.value),
+        _ => None,
+    }
+}
+
+/// Rewrites a bracket-only access chain such as `m['k'][1]` into nested
+/// `arrayElement` calls. Chains with a dot access or a slice stay unchanged.
 fn normalize_map_access(expression: &mut Expr) -> bool {
-    let Expr::MapAccess { keys, .. } = expression else {
+    let Expr::CompoundFieldAccess { access_chain, .. } = expression else {
         return false;
     };
-    if keys.is_empty()
-        || keys
+    if access_chain.is_empty()
+        || access_chain
             .iter()
-            .any(|key| key.syntax != MapAccessSyntax::Bracket)
+            .any(|access| !matches!(access, AccessExpr::Subscript(Subscript::Index { .. })))
     {
         return false;
     }
-    let Expr::MapAccess { column, keys } = std::mem::replace(
-        expression,
-        Expr::Value(datafusion::sql::sqlparser::ast::Value::Null),
-    ) else {
+    let Expr::CompoundFieldAccess { root, access_chain } =
+        std::mem::replace(expression, Expr::Value(Value::Null.into()))
+    else {
         unreachable!()
     };
-    let mut input = *column;
-    for key in keys {
+    let mut input = *root;
+    for access in access_chain {
+        let AccessExpr::Subscript(Subscript::Index { index }) = access else {
+            unreachable!()
+        };
         input = Expr::Function(Function {
-            name: ObjectName(vec![Ident::new("arrayElement")]),
+            name: ObjectName::from(vec![Ident::new("arrayElement")]),
+            uses_odbc_syntax: false,
             parameters: FunctionArguments::None,
             args: FunctionArguments::List(FunctionArgumentList {
                 duplicate_treatment: None,
                 clauses: vec![],
                 args: vec![
                     FunctionArg::Unnamed(FunctionArgExpr::Expr(input)),
-                    FunctionArg::Unnamed(FunctionArgExpr::Expr(key.key)),
+                    FunctionArg::Unnamed(FunctionArgExpr::Expr(index)),
                 ],
             }),
             filter: None,
diff --git a/crates/frontend-sql/src/unified/sql/collection_planning.rs b/crates/frontend-sql/src/unified/sql/collection_planning.rs
index 75d0450cc..09b0bfa8e 100644
--- a/crates/frontend-sql/src/unified/sql/collection_planning.rs
+++ b/crates/frontend-sql/src/unified/sql/collection_planning.rs
@@ -5,15 +5,22 @@ use asap_types::ir::scalar::{element_access_type, struct_field_type};
 use asap_types::ir::ScalarExpr;
 use asap_types::pre_asap::scalar_type_rules::MapScalarFunction;
 use asap_types::pre_asap::{Field, Schema};
-use datafusion::arrow::datatypes::DataType;
-use datafusion::common::{DataFusionError, ExprSchema, Result};
+use datafusion::arrow::datatypes::{DataType, Field as ArrowField, FieldRef};
+use datafusion::common::{DataFusionError, Result, ScalarValue as DfScalarValue};
 use datafusion::logical_expr::{
-    ColumnarValue, Expr, ExprSchemable, ScalarUDF, ScalarUDFImpl, Signature, TypeSignature,
-    Volatility,
+    ColumnarValue, ReturnFieldArgs, ScalarFunctionArgs, ScalarUDF, ScalarUDFImpl, Signature,
+    TypeSignature, Volatility,
 };
 use datafusion::prelude::SessionContext;
+use std::hash::{Hash, Hasher};
+use std::sync::Arc;
 
-#[derive(Debug, Clone, Copy)]
+/// The name ClickHouse's `map(...)` is planned under. DataFusion's SQL planner
+/// reserves `map` for its own constructor (and rejects `map()`), so
+/// `clickhouse_ast::normalize` renames the call and lowering restores `map`.
+pub(super) const MAP_PLANNING_NAME: &str = "asap_map_construct";
+
+#[derive(Debug, Clone, Copy, PartialEq, Eq)]
 enum PlanningFunction {
     Map(MapScalarFunction),
     Element,
@@ -22,7 +29,10 @@ enum PlanningFunction {
 
 pub(super) fn register(context: &SessionContext) {
     for (name, function) in [
-        ("map", PlanningFunction::Map(MapScalarFunction::Construct)),
+        (
+            MAP_PLANNING_NAME,
+            PlanningFunction::Map(MapScalarFunction::Construct),
+        ),
         (
             "mapconcat",
             PlanningFunction::Map(MapScalarFunction::Concat),
@@ -48,18 +58,26 @@ pub(super) fn register(context: &SessionContext) {
         }));
     }
 }
-#[derive(Debug)]
+#[derive(Debug, PartialEq, Eq)]
 struct CollectionPlanningFunction {
     name: &'static str,
     function: PlanningFunction,
     signature: Signature,
 }
+// `function` is determined by `name` at registration, so hashing the name and
+// signature agrees with the derived `Eq`.
+impl Hash for CollectionPlanningFunction {
+    fn hash<H: Hasher>(&self, state: &mut H) {
+        self.name.hash(state);
+        self.signature.hash(state);
+    }
+}
 impl CollectionPlanningFunction {
     fn output(
         &self,
         args: &[DataType],
         nullable: &[bool],
-        expressions: Option<&[Expr]>,
+        literals: Option<&[Option<&DfScalarValue>]>,
     ) -> Result<(DataType, bool)> {
         let inputs = args
             .iter()
@@ -88,8 +106,7 @@ impl CollectionPlanningFunction {
             );
             let args = (0..schema.fields.len())
                 .map(|index| {
-                    if let Some(Expr::Literal(value)) = expressions.and_then(|args| args.get(index))
-                    {
+                    if let Some(Some(value)) = literals.and_then(|args| args.get(index)) {
                         scalar_value_to_asap(value)
                             .map(ScalarExpr::Literal)
                             .map_err(|error| DataFusionError::Plan(error.to_string()))
@@ -113,9 +130,6 @@ impl CollectionPlanningFunction {
     }
 }
 impl ScalarUDFImpl for CollectionPlanningFunction {
-    fn as_any(&self) -> &dyn std::any::Any {
-        self
-    }
     fn name(&self) -> &str {
         self.name
     }
@@ -133,37 +147,21 @@ impl ScalarUDFImpl for CollectionPlanningFunction {
         )
         .map(|output| output.0)
     }
-    fn return_type_from_exprs(
-        &self,
-        args: &[Expr],
-        schema: &dyn ExprSchema,
-        types: &[DataType],
-    ) -> Result<DataType> {
-        let nullable = args
-            .iter()
-            .map(|arg| arg.nullable(schema))
-            .collect::<Result<Vec<_>>>()?;
-        self.output(types, &nullable, Some(args))
-            .map(|output| output.0)
-    }
-    fn is_nullable(&self, args: &[Expr], schema: &dyn ExprSchema) -> bool {
+    fn return_field_from_args(&self, args: ReturnFieldArgs) -> Result<FieldRef> {
         let types = args
+            .arg_fields
             .iter()
-            .map(|arg| arg.get_type(schema))
-            .collect::<Result<Vec<_>>>();
+            .map(|field| field.data_type().clone())
+            .collect::<Vec<_>>();
         let nullable = args
+            .arg_fields
             .iter()
-            .map(|arg| arg.nullable(schema))
-            .collect::<Result<Vec<_>>>();
-        match (types, nullable) {
-            (Ok(types), Ok(nullable)) => self
-                .output(&types, &nullable, Some(args))
-                .map(|out| out.1)
-                .unwrap_or(true),
-            _ => true,
-        }
+            .map(|field| field.is_nullable())
+            .collect::<Vec<_>>();
+        let (dtype, nullable) = self.output(&types, &nullable, Some(args.scalar_arguments))?;
+        Ok(Arc::new(ArrowField::new(self.name, dtype, nullable)))
     }
-    fn invoke_batch(&self, _args: &[ColumnarValue], _number_rows: usize) -> Result<ColumnarValue> {
+    fn invoke_with_args(&self, _args: ScalarFunctionArgs) -> Result<ColumnarValue> {
         Err(DataFusionError::NotImplemented("collection planning adapter cannot execute; use a capable query engine or external exact sub_dag".into()))
     }
 }
@@ -174,12 +172,19 @@ mod tests {
     #[test]
     fn planning_adapter_explicitly_refuses_physical_execution() {
         let adapter = CollectionPlanningFunction {
-            name: "map",
+            name: MAP_PLANNING_NAME,
             function: PlanningFunction::Map(MapScalarFunction::Construct),
             signature: Signature::any(0, Volatility::Immutable),
         };
+        let args = ScalarFunctionArgs {
+            args: vec![],
+            arg_fields: vec![],
+            number_rows: 1,
+            return_field: Arc::new(ArrowField::new("map", DataType::Null, true)),
+            config_options: Default::default(),
+        };
         assert!(matches!(
-            adapter.invoke_batch(&[], 1),
+            adapter.invoke_with_args(args),
             Err(DataFusionError::NotImplemented(_))
         ));
         let result = adapter.return_type(&[]).unwrap();
diff --git a/crates/frontend-sql/src/unified/sql/dialect.rs b/crates/frontend-sql/src/unified/sql/dialect.rs
deleted file mode 100644
index 03d9253e0..000000000
--- a/crates/frontend-sql/src/unified/sql/dialect.rs
+++ /dev/null
@@ -1,112 +0,0 @@
-//! The parser dialect for `SqlDialect::DataFusionSQL`.
-//!
-//! sqlparser's `GenericDialect` leaves `FILTER (WHERE …)` on aggregate calls
-//! off (`supports_filter_during_aggregation`), and DataFusion only selects a
-//! dialect by name — so `count(x) FILTER (WHERE p)` cannot reach the planner
-//! through `SessionContext::sql`. This wrapper is `GenericDialect` with that
-//! one switch flipped (issue #466); `lower` parses through
-//! `DFParser::parse_sql_with_dialect` with it and plans the statement itself,
-//! exactly as the ClickHouse path already does.
-
-use std::any::TypeId;
-
-use datafusion::sql::sqlparser::dialect::{Dialect, GenericDialect};
-
-#[derive(Debug, Default)]
-pub(crate) struct GenericWithAggregateFilter;
-
-/// Forward every boolean switch `GenericDialect` overrides, so the only
-/// behavioural difference is `supports_filter_during_aggregation`.
-macro_rules! forward_to_generic {
-    ($($method:ident),* $(,)?) => {
-        $(fn $method(&self) -> bool {
-            GenericDialect.$method()
-        })*
-    };
-}
-
-impl Dialect for GenericWithAggregateFilter {
-    /// The parser's own `dialect_of!(… is GenericDialect)` checks keep
-    /// matching, so generic-only syntax paths stay enabled.
-    fn dialect(&self) -> TypeId {
-        GenericDialect.dialect()
-    }
-
-    fn is_delimited_identifier_start(&self, ch: char) -> bool {
-        GenericDialect.is_delimited_identifier_start(ch)
-    }
-
-    fn is_identifier_start(&self, ch: char) -> bool {
-        GenericDialect.is_identifier_start(ch)
-    }
-
-    fn is_identifier_part(&self, ch: char) -> bool {
-        GenericDialect.is_identifier_part(ch)
-    }
-
-    fn supports_filter_during_aggregation(&self) -> bool {
-        true
-    }
-
-    forward_to_generic!(
-        supports_unicode_string_literal,
-        supports_group_by_expr,
-        supports_connect_by,
-        supports_match_recognize,
-        supports_start_transaction_modifier,
-        supports_window_function_null_treatment_arg,
-        supports_dictionary_syntax,
-        supports_window_clause_named_window_reference,
-        supports_parenthesized_set_variables,
-        supports_select_wildcard_except,
-        support_map_literal_syntax,
-        allow_extract_custom,
-        allow_extract_single_quotes,
-        supports_create_index_with_clause,
-    );
-}
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-    use datafusion::sql::parser::DFParser;
-
-    // Every switch `GenericDialect` sets is mirrored, and only the aggregate
-    // FILTER switch differs.
-    #[test]
-    fn mirrors_generic_except_for_aggregate_filter() {
-        let ours = GenericWithAggregateFilter;
-        let generic = GenericDialect;
-        assert_eq!(ours.dialect(), generic.dialect());
-        for ch in ['"', '`', '_', '#', '@', '$', 'a', '1', ' '] {
-            assert_eq!(
-                ours.is_delimited_identifier_start(ch),
-                generic.is_delimited_identifier_start(ch)
-            );
-            assert_eq!(
-                ours.is_identifier_start(ch),
-                generic.is_identifier_start(ch)
-            );
-            assert_eq!(ours.is_identifier_part(ch), generic.is_identifier_part(ch));
-        }
-        assert_eq!(
-            ours.supports_group_by_expr(),
-            generic.supports_group_by_expr()
-        );
-        assert!(!generic.supports_filter_during_aggregation());
-        assert!(ours.supports_filter_during_aggregation());
-    }
-
-    // The generic dialect rejects an aggregate FILTER clause; ours parses it.
-    #[test]
-    fn parses_aggregate_filter_clause() {
-        let sql = "SELECT count(*) FILTER (WHERE a > 1) FROM t";
-        assert!(DFParser::parse_sql_with_dialect(sql, &GenericDialect).is_err());
-        assert_eq!(
-            DFParser::parse_sql_with_dialect(sql, &GenericWithAggregateFilter)
-                .unwrap()
-                .len(),
-            1
-        );
-    }
-}
diff --git a/crates/frontend-sql/src/unified/sql/expr.rs b/crates/frontend-sql/src/unified/sql/expr.rs
index b726bfc12..1eebe807f 100644
--- a/crates/frontend-sql/src/unified/sql/expr.rs
+++ b/crates/frontend-sql/src/unified/sql/expr.rs
@@ -50,6 +50,7 @@ impl SqlLowerer<'_> {
             Expr::Literal(
                 sv @ (datafusion::common::ScalarValue::Date32(_)
                 | datafusion::common::ScalarValue::Date64(_)),
+                _,
             ) => {
                 let text = sv.cast_to(&datafusion::arrow::datatypes::DataType::Utf8)?;
                 // Arrow formats Date64 with a time suffix; the canonical Date has
@@ -66,7 +67,7 @@ impl SqlLowerer<'_> {
                     try_cast: false,
                 })
             }
-            Expr::Literal(sv) => scalar_value_to_asap(sv).map(Unresolved::Literal),
+            Expr::Literal(sv, _) => scalar_value_to_asap(sv).map(Unresolved::Literal),
 
             Expr::Alias(a) => self.lower_expr(&a.expr),
 
@@ -147,14 +148,14 @@ impl SqlLowerer<'_> {
 
             Expr::Cast(c) => Ok(Unresolved::Cast {
                 expr: bx(&c.expr)?,
-                to: arrow_to_dtype(&c.data_type)?,
+                to: arrow_to_dtype(c.field.data_type())?,
                 try_cast: false,
             }),
 
             // TRY_CAST returns NULL on conversion failure; preserve that semantic.
             Expr::TryCast(c) => Ok(Unresolved::Cast {
                 expr: bx(&c.expr)?,
-                to: arrow_to_dtype(&c.data_type)?,
+                to: arrow_to_dtype(c.field.data_type())?,
                 try_cast: true,
             }),
 
@@ -201,6 +202,8 @@ impl SqlLowerer<'_> {
                         "asap_element_access".into()
                     } else if sf.func.name().eq_ignore_ascii_case("tupleelement") {
                         "asap_struct_field".into()
+                    } else if sf.func.name() == super::collection_planning::MAP_PLANNING_NAME {
+                        "map".into()
                     } else {
                         sf.func.name().to_string()
                     },
@@ -323,7 +326,7 @@ mod tests {
             (DfScalarValue::Date32(None), ScalarValue::Null),
             (DfScalarValue::Date64(None), ScalarValue::Null),
         ] {
-            let actual = lowerer.lower_expr(&Expr::Literal(value)).unwrap();
+            let actual = lowerer.lower_expr(&Expr::Literal(value, None)).unwrap();
             assert_eq!(
                 actual,
                 Unresolved::Cast {
diff --git a/crates/frontend-sql/src/unified/sql/mod.rs b/crates/frontend-sql/src/unified/sql/mod.rs
index 1f58f92c0..1243aa8e6 100644
--- a/crates/frontend-sql/src/unified/sql/mod.rs
+++ b/crates/frontend-sql/src/unified/sql/mod.rs
@@ -29,8 +29,8 @@ use std::sync::Arc;
 use std::time::Duration;
 
 use datafusion::arrow::compute::kernels::cast_utils::parse_interval_month_day_nano;
-use datafusion::arrow::datatypes::{DataType as ArrowDataType, Field};
-use datafusion::catalog_common::MemorySchemaProvider;
+use datafusion::arrow::datatypes::{DataType as ArrowDataType, Field, FieldRef};
+use datafusion::catalog::MemorySchemaProvider;
 use datafusion::common::config::ConfigOptions;
 use datafusion::common::tree_node::{Transformed, TreeNode, TreeNodeRecursion};
 use datafusion::common::{Column as DfColumn, DFSchema, ScalarValue as DfScalarValue};
@@ -41,15 +41,16 @@ use datafusion::logical_expr::expr::AggregateFunction;
 use datafusion::logical_expr::expr_rewriter::FunctionRewrite;
 use datafusion::logical_expr::function::{PartitionEvaluatorArgs, WindowUDFFieldArgs};
 use datafusion::logical_expr::{
-    self, lit, AggregateUDF, Case, Distinct, Expr, ExprSchemable, JoinType, LogicalPlan,
-    PartitionEvaluator, ScalarUDF, ScalarUDFImpl, Signature, SimpleAggregateUDF, TypeSignature,
-    Volatility, WindowFrameBound as DfWindowFrameBound, WindowFrameUnits as DfWindowFrameUnits,
-    WindowFunctionDefinition, WindowUDF, WindowUDFImpl,
+    self, lit, AggregateUDF, Case, ColumnarValue, Distinct, Expr, ExprSchemable, JoinType,
+    LogicalPlan, PartitionEvaluator, ScalarFunctionArgs, ScalarUDF, ScalarUDFImpl, Signature,
+    SimpleAggregateUDF, TypeSignature, Volatility, WindowFrameBound as DfWindowFrameBound,
+    WindowFrameUnits as DfWindowFrameUnits, WindowFunctionDefinition, WindowUDF, WindowUDFImpl,
 };
 use datafusion::optimizer::analyzer::function_rewrite::ApplyFunctionRewrites;
 use datafusion::optimizer::{AnalyzerRule, OptimizerConfig};
 use datafusion::prelude::{SessionConfig, SessionContext};
 use datafusion::sql::parser::DFParser;
+use datafusion::sql::sqlparser::dialect::GenericDialect;
 
 use asap_frontend_common::{
     resolve_root, UnresolvedOp as Unresolved, UnresolvedPredicate as Predicate,
@@ -75,13 +76,11 @@ use crate::unified::error::SqlError as LoweringError;
 
 mod clickhouse_ast;
 mod collection_planning;
-mod dialect;
 mod expr;
 mod types;
 
 pub use types::SqlCatalog;
 
-use self::dialect::GenericWithAggregateFilter;
 use self::types::{arrow_to_dtype, scalar_value_to_asap, schema_to_arrow};
 
 std::thread_local! {
@@ -181,16 +180,14 @@ impl<'a> SqlLowerer<'a> {
         let ctx = self.build_context()?;
         let state = ctx.state();
         let statement = if matches!(self.dialect, SqlDialect::ClickhouseSQL) {
-            let mut statement = state.sql_to_statement(sql, "ClickHouse")?;
+            let mut statement =
+                state.sql_to_statement(sql, &datafusion::config::Dialect::ClickHouse)?;
             if let datafusion::sql::parser::Statement::Statement(ast) = &mut statement {
                 clickhouse_ast::normalize(ast);
             }
             statement
         } else {
-            // Not `ctx.sql(sql)`: that parses under the by-name `generic`
-            // dialect, which cannot see an aggregate `FILTER (WHERE …)`.
-            let mut statements = DFParser::parse_sql_with_dialect(sql, &GenericWithAggregateFilter)
-                .map_err(|e| datafusion::error::DataFusionError::SQL(e, None))?;
+            let mut statements = DFParser::parse_sql_with_dialect(sql, &GenericDialect)?;
             let (Some(statement), true) = (statements.pop_front(), statements.is_empty()) else {
                 return Err(LoweringError::UnsupportedFeature(
                     "exactly one SQL statement per query".into(),
@@ -200,9 +197,9 @@ impl<'a> SqlLowerer<'a> {
         };
         let plan = state.statement_to_plan(statement).await?;
         let rewriter = ApplyFunctionRewrites::new(vec![Arc::new(ClickHouseBuiltinRewrite)]);
-        let plan = rewriter.analyze(plan, ctx.state().options())?;
+        let plan = rewriter.analyze(plan, &ctx.state().options())?;
         let plan = datafusion::optimizer::analyzer::type_coercion::TypeCoercion::new()
-            .analyze(plan, ctx.state().options())?;
+            .analyze(plan, &ctx.state().options())?;
         // Output schemas omit predicate and nested-expression types. Check the
         // typed SQL plan before lowering erases fixed-duration units.
         plan.apply_with_subqueries(|node| {
@@ -215,7 +212,16 @@ impl<'a> SqlLowerer<'a> {
                 expr.apply(|nested| {
                     if let Expr::BinaryExpr(binary) = nested {
                         if binary.op == logical_expr::Operator::Minus
-                            && matches!(nested.get_type(&schema)?, ArrowDataType::Duration(_))
+                            // DataFusion types `date - date` as an Int64 day
+                            // count, which the canonical DAG has no shape for.
+                            && (matches!(
+                                (binary.left.get_type(&schema)?, binary.right.get_type(&schema)?),
+                                (ArrowDataType::Date32, ArrowDataType::Date32)
+                                    | (ArrowDataType::Date64, ArrowDataType::Date64)
+                            ) || matches!(
+                                nested.get_type(&schema)?,
+                                ArrowDataType::Duration(_)
+                            ))
                         {
                             return Err(datafusion::common::DataFusionError::Plan(
                                 "temporal subtraction produces an unsupported duration type".into(),
@@ -260,7 +266,7 @@ impl<'a> SqlLowerer<'a> {
                 }
             }
             let arrow_schema = Arc::new(schema_to_arrow(schema));
-            let mem_table = MemTable::try_new(arrow_schema, vec![])?;
+            let mem_table = MemTable::try_new(arrow_schema, vec![vec![]])?;
             ctx.register_table(name.as_str(), Arc::new(mem_table))?;
         }
         // Register a stub `AggregateUDF` for every catalog-listed
@@ -383,7 +389,7 @@ impl<'a> SqlLowerer<'a> {
                                 qualifier: Some(alias_name),
                                 child,
                             }),
-                            // Otherwise (e.g. `SELECT *` unwrapped to a scan) wrap
+                            // Otherwise (e.g. a `LIMIT` or `DISTINCT` sub-plan) wrap
                             // in an identity projection that re-qualifies each
                             // output column. Names come from the sub-plan's schema.
                             inner => {
@@ -629,6 +635,7 @@ impl<'a> SqlLowerer<'a> {
         };
         let func = lower_window_func_kind(&wf.fun)?;
         let mut args = wf
+            .params
             .args
             .iter()
             .map(|e| self.lower_expr(e))
@@ -649,11 +656,13 @@ impl<'a> SqlLowerer<'a> {
             func
         };
         let partition_by = wf
+            .params
             .partition_by
             .iter()
             .map(expr_to_group_ref)
             .collect::<Result<Vec<_>, _>>()?;
         let order_by = wf
+            .params
             .order_by
             .iter()
             .map(|s| {
@@ -664,7 +673,7 @@ impl<'a> SqlLowerer<'a> {
                 })
             })
             .collect::<Result<Vec<_>, _>>()?;
-        let frame = lower_window_frame(&wf.window_frame)?;
+        let frame = lower_window_frame(&wf.params.window_frame)?;
         // The window plan's schema is `[input fields …, window output]`; the last
         // field is the window column's name (what an enclosing Project references).
         let output_name = window
@@ -713,10 +722,6 @@ impl<'a> SqlLowerer<'a> {
                 },
             });
         }
-        // SELECT * — no column constraint; pass through without a Project.
-        if proj.expr.iter().any(|e| matches!(e, Expr::Wildcard { .. })) {
-            return self.lower_plan(&proj.input);
-        }
         let child = Rc::new(self.lower_plan(&proj.input)?);
         let temporal_input = plan_has_temporal_aggregate(&proj.input);
         let cols = proj
@@ -890,13 +895,13 @@ impl<'a> SqlLowerer<'a> {
             unreachable!("is_temporal_aggregate accepted a non-aggregate expression")
         };
         let name = call.func.name().to_lowercase();
-        let [value, timestamp, window] = call.args.as_slice() else {
+        let [value, timestamp, window] = call.params.args.as_slice() else {
             unreachable!("ASAP temporal UDAF signatures require exactly three arguments")
         };
 
         let value_ref = reducer_col(&name, std::slice::from_ref(value))?;
         let timestamp_ref = reducer_col(&name, std::slice::from_ref(timestamp))?;
-        let Expr::Literal(window) = unalias(window) else {
+        let Expr::Literal(window, _) = unalias(window) else {
             return Err(LoweringError::InvalidExpression(format!(
                 "{name} window_ms must be a positive integer literal"
             )));
@@ -1316,9 +1321,9 @@ impl SqlLowerer<'_> {
 
 fn positive_millis_literal(expr: &Expr, argument: &str) -> Result<Duration, LoweringError> {
     let millis = match unalias(expr) {
-        Expr::Literal(DfScalarValue::Int64(Some(value))) if *value > 0 => *value as u64,
-        Expr::Literal(DfScalarValue::UInt64(Some(value))) if *value > 0 => *value,
-        Expr::Literal(DfScalarValue::Int32(Some(value))) if *value > 0 => *value as u64,
+        Expr::Literal(DfScalarValue::Int64(Some(value)), _) if *value > 0 => *value as u64,
+        Expr::Literal(DfScalarValue::UInt64(Some(value)), _) if *value > 0 => *value,
+        Expr::Literal(DfScalarValue::Int32(Some(value)), _) if *value > 0 => *value as u64,
         other => {
             return Err(LoweringError::InvalidExpression(format!(
                 "{argument} must be a positive integer millisecond literal, got {other}"
@@ -1330,11 +1335,11 @@ fn positive_millis_literal(expr: &Expr, argument: &str) -> Result<Duration, Lowe
 
 fn float_literal(expr: &Expr) -> Option<f64> {
     match unalias(expr) {
-        Expr::Literal(DfScalarValue::Float64(Some(value))) => Some(*value),
-        Expr::Literal(DfScalarValue::Float32(Some(value))) => Some(*value as f64),
-        Expr::Literal(DfScalarValue::Int64(Some(value))) => Some(*value as f64),
-        Expr::Literal(DfScalarValue::UInt64(Some(value))) => Some(*value as f64),
-        Expr::Literal(DfScalarValue::Int32(Some(value))) => Some(*value as f64),
+        Expr::Literal(DfScalarValue::Float64(Some(value)), _) => Some(*value),
+        Expr::Literal(DfScalarValue::Float32(Some(value)), _) => Some(*value as f64),
+        Expr::Literal(DfScalarValue::Int64(Some(value)), _) => Some(*value as f64),
+        Expr::Literal(DfScalarValue::UInt64(Some(value)), _) => Some(*value as f64),
+        Expr::Literal(DfScalarValue::Int32(Some(value)), _) => Some(*value as f64),
         _ => None,
     }
 }
@@ -1457,11 +1462,11 @@ fn clickhouse_scalar_builtin_return_type(name: &str) -> ArrowDataType {
 }
 
 /// A stub `ScalarUDFImpl` carrying only what DataFusion's planner needs:
-/// name, arity-only [`Signature`], and a fixed return type. `invoke`/
-/// `invoke_batch` are left at their trait defaults (a `NotImplemented`
-/// `DataFusionError`) — see [`clickhouse_scalar_builtin_stub_udf`]'s doc for
-/// why that is unreachable in practice.
-#[derive(Debug)]
+/// name, arity-only [`Signature`], and a fixed return type. `invoke_with_args`
+/// returns a `NotImplemented` `DataFusionError` — see
+/// [`clickhouse_scalar_builtin_stub_udf`]'s doc for why that is unreachable in
+/// practice.
+#[derive(Debug, PartialEq, Eq, Hash)]
 struct ClickHouseScalarBuiltinStub {
     name: &'static str,
     signature: Signature,
@@ -1469,10 +1474,6 @@ struct ClickHouseScalarBuiltinStub {
 }
 
 impl ScalarUDFImpl for ClickHouseScalarBuiltinStub {
-    fn as_any(&self) -> &dyn std::any::Any {
-        self
-    }
-
     fn name(&self) -> &str {
         self.name
     }
@@ -1487,6 +1488,15 @@ impl ScalarUDFImpl for ClickHouseScalarBuiltinStub {
     ) -> datafusion::common::Result<ArrowDataType> {
         Ok(self.return_type.clone())
     }
+
+    fn invoke_with_args(
+        &self,
+        _args: ScalarFunctionArgs,
+    ) -> datafusion::common::Result<ColumnarValue> {
+        Err(datafusion::common::DataFusionError::NotImplemented(
+            format!("{} is a planning-only stub", self.name),
+        ))
+    }
 }
 
 // ── ClickHouse window-builtin compatibility ─────────────────────────────────
@@ -1515,17 +1525,13 @@ fn clickhouse_window_builtin_stub_udwf(name: &'static str, arity: Arity) -> Wind
 /// argument (matching `lag`/`lead`'s own "output type = input type"
 /// behavior). `partition_evaluator` is left `unimplemented!()` — see
 /// [`clickhouse_window_builtin_stub_udwf`]'s doc for why that is unreachable.
-#[derive(Debug)]
+#[derive(Debug, PartialEq, Eq, Hash)]
 struct ClickHouseWindowBuiltinStub {
     name: &'static str,
     signature: Signature,
 }
 
 impl WindowUDFImpl for ClickHouseWindowBuiltinStub {
-    fn as_any(&self) -> &dyn std::any::Any {
-        self
-    }
-
     fn name(&self) -> &str {
         self.name
     }
@@ -1534,9 +1540,11 @@ impl WindowUDFImpl for ClickHouseWindowBuiltinStub {
         &self.signature
     }
 
-    fn field(&self, field_args: WindowUDFFieldArgs) -> datafusion::common::Result<Field> {
-        let dtype = field_args.get_input_type(0).unwrap_or(ArrowDataType::Null);
-        Ok(Field::new(field_args.name(), dtype, true))
+    fn field(&self, field_args: WindowUDFFieldArgs) -> datafusion::common::Result<FieldRef> {
+        let dtype = field_args
+            .get_input_field(0)
+            .map_or(ArrowDataType::Null, |field| field.data_type().clone());
+        Ok(Arc::new(Field::new(field_args.name(), dtype, true)))
     }
 
     fn partition_evaluator(
@@ -1587,17 +1595,17 @@ impl FunctionRewrite for ClickHouseBuiltinRewrite {
             // at whatever arity the call carries.
             RewriteKind::CountDistinct => AggregateFunction::new_udf(
                 count_udaf(),
-                f.args,
+                f.params.args,
                 true,
-                f.filter,
-                f.order_by,
-                f.null_treatment,
+                f.params.filter,
+                f.params.order_by,
+                f.params.null_treatment,
             ),
             // `f(cond)` -> `sum(CASE WHEN cond THEN 1 ELSE 0 END)` — see
             // `RewriteKind::CountIfToSum`'s doc; moving the `-If` family onto
             // `Aggregate.filters` (issue #466) is a follow-up.
             RewriteKind::CountIfToSum => {
-                let cond = f.args.into_iter().next().expect(
+                let cond = f.params.args.into_iter().next().expect(
                     "countif's stub signature fixes its arity at 1 -- the planner \
                      already rejected any other argument count before this rewrite runs",
                 );
@@ -1610,9 +1618,9 @@ impl FunctionRewrite for ClickHouseBuiltinRewrite {
                     sum_udaf(),
                     vec![indicator],
                     false,
-                    f.filter,
-                    f.order_by,
-                    f.null_treatment,
+                    f.params.filter,
+                    f.params.order_by,
+                    f.params.null_treatment,
                 )
             }
         };
@@ -1633,10 +1641,10 @@ fn measure_filter(expr: &Expr, input: &DFSchema) -> Result<Option<Expr>, Lowerin
     let Expr::AggregateFunction(agg_fn) = unalias(expr) else {
         return Ok(None);
     };
-    let mut conjuncts: Vec<Expr> = agg_fn.filter.iter().map(|f| (**f).clone()).collect();
-    let counts_rows = agg_fn.func.name().eq_ignore_ascii_case("count") && !agg_fn.distinct;
+    let mut conjuncts: Vec<Expr> = agg_fn.params.filter.iter().map(|f| (**f).clone()).collect();
+    let counts_rows = agg_fn.func.name().eq_ignore_ascii_case("count") && !agg_fn.params.distinct;
     if counts_rows {
-        for argument in &agg_fn.args {
+        for argument in &agg_fn.params.args {
             let nullable = argument
                 .nullable(input)
                 .map_err(|error| LoweringError::UnsupportedFeature(error.to_string()))?;
@@ -1671,7 +1679,7 @@ fn conditional_count_arm(expr: &Expr) -> Option<(&Expr, &Expr)> {
     }
     let else_is_null = match case.else_expr.as_deref() {
         None => true,
-        Some(Expr::Literal(value)) => value.is_null(),
+        Some(Expr::Literal(value, _)) => value.is_null(),
         Some(_) => false,
     };
     if !else_is_null {
@@ -1705,7 +1713,7 @@ fn lower_agg_intent(expr: &Expr) -> Result<AggIntent<ColumnRef>, LoweringError>
             // own name rather than a native DataFusion aggregate. Handled
             // before the `NATIVE_FUNCTIONS` lookup below since neither name
             // is in that table (issue #232).
-            if let Some(intent) = lower_arg_selector(&name, &agg_fn.args)? {
+            if let Some(intent) = lower_arg_selector(&name, &agg_fn.params.args)? {
                 return Ok(intent);
             }
             let semantic = asap_sql_function_catalog::lookup_native(&name)
@@ -1714,7 +1722,7 @@ fn lower_agg_intent(expr: &Expr) -> Result<AggIntent<ColumnRef>, LoweringError>
             // value reducers; only
             // COUNT(DISTINCT) maps (to Cardinality). Reject DISTINCT elsewhere
             // rather than silently lowering `SUM(DISTINCT x)` as `SUM(x)`.
-            if agg_fn.distinct && !matches!(semantic, AggSemantic::Count) {
+            if agg_fn.params.distinct && !matches!(semantic, AggSemantic::Count) {
                 return Err(LoweringError::UnsupportedAggregate(format!(
                     "DISTINCT {name}"
                 )));
@@ -1730,12 +1738,13 @@ fn lower_agg_intent(expr: &Expr) -> Result<AggIntent<ColumnRef>, LoweringError>
             };
             Ok(match semantic {
                 AggSemantic::Correlation => {
-                    if agg_fn.order_by.is_some() || agg_fn.null_treatment.is_some() {
+                    if !agg_fn.params.order_by.is_empty() || agg_fn.params.null_treatment.is_some()
+                    {
                         return Err(LoweringError::UnsupportedAggregate(
                             "corr with ORDER BY or explicit null treatment".into(),
                         ));
                     }
-                    let [left, right] = agg_fn.args.as_slice() else {
+                    let [left, right] = agg_fn.params.args.as_slice() else {
                         return Err(LoweringError::UnsupportedAggregate(
                             "corr requires two arguments".into(),
                         ));
@@ -1748,7 +1757,8 @@ fn lower_agg_intent(expr: &Expr) -> Result<AggIntent<ColumnRef>, LoweringError>
                 // Every argument reaches the intent: `COUNT(DISTINCT a, b)`
                 // counts distinct *tuples*, which is a different quantity from
                 // the distinct count of either column.
-                AggSemantic::Count if agg_fn.distinct => match agg_fn.args.as_slice() {
+                AggSemantic::Count if agg_fn.params.distinct => match agg_fn.params.args.as_slice()
+                {
                     // DataFusion's planner rejects a bare `COUNT(DISTINCT)`
                     // before lowering. Guarded anyway: an empty `cols` is the
                     // PromQL sample-value convention, which SQL never has.
@@ -1766,23 +1776,23 @@ fn lower_agg_intent(expr: &Expr) -> Result<AggIntent<ColumnRef>, LoweringError>
                     accuracy: current_accuracy(),
                 },
                 AggSemantic::Sum => AggIntent::Sum {
-                    col: col(&agg_fn.args)?,
+                    col: col(&agg_fn.params.args)?,
                 },
                 AggSemantic::Min => AggIntent::Min {
-                    col: col(&agg_fn.args)?,
+                    col: col(&agg_fn.params.args)?,
                 },
                 AggSemantic::Max => AggIntent::Max {
-                    col: col(&agg_fn.args)?,
+                    col: col(&agg_fn.params.args)?,
                 },
                 AggSemantic::Avg => AggIntent::Avg {
-                    col: col(&agg_fn.args)?,
+                    col: col(&agg_fn.params.args)?,
                 },
                 AggSemantic::StdDev { population } => AggIntent::StdDev {
-                    col: col(&agg_fn.args)?,
+                    col: col(&agg_fn.params.args)?,
                     population,
                 },
                 AggSemantic::Variance { population } => AggIntent::Variance {
-                    col: col(&agg_fn.args)?,
+                    col: col(&agg_fn.params.args)?,
                     population,
                 },
                 // `fixed_q = Some(0.5)` is `median`/`approx_median`. As with
@@ -1792,15 +1802,15 @@ fn lower_agg_intent(expr: &Expr) -> Result<AggIntent<ColumnRef>, LoweringError>
                 // `plan::boundary`), so both spellings share one intent
                 // (#111).
                 AggSemantic::Quantile { fixed_q } => AggIntent::Quantile {
-                    col: col(&agg_fn.args)?,
+                    col: col(&agg_fn.params.args)?,
                     q: match fixed_q {
                         Some(q) => q,
-                        None => extract_percentile_q(&agg_fn.args)?,
+                        None => extract_percentile_q(&agg_fn.params.args)?,
                     },
                     accuracy: current_accuracy(),
                 },
                 AggSemantic::Cardinality => AggIntent::Cardinality {
-                    cols: vec![reducer_col(&name, &agg_fn.args)?],
+                    cols: vec![reducer_col(&name, &agg_fn.params.args)?],
                     accuracy: current_accuracy(),
                 },
             })
@@ -2181,7 +2191,7 @@ impl<'l> DerivedCols<'l> {
             // and qualified columns. This retains both inputs and avoids losing
             // relation qualifiers when the projection becomes an unqualified schema.
             let mut rewritten = agg_fn.clone();
-            for arg in &mut rewritten.args {
+            for arg in &mut rewritten.params.args {
                 let alias = unalias(arg).to_string();
                 self.materialize(alias.clone(), self.lowerer.lower_expr(arg)?)?;
                 *arg = Expr::Column(DfColumn::new_unqualified(alias));
@@ -2190,8 +2200,9 @@ impl<'l> DerivedCols<'l> {
         }
         // `COUNT(*)` reduces no column; `agg_col_name` covers bare/aliased/cast
         // columns, so `None` here means the argument really is an expression.
-        let counts_rows = agg_fn.func.name().eq_ignore_ascii_case("count") && !agg_fn.distinct;
-        let Some(arg) = agg_fn.args.first() else {
+        let counts_rows =
+            agg_fn.func.name().eq_ignore_ascii_case("count") && !agg_fn.params.distinct;
+        let Some(arg) = agg_fn.params.args.first() else {
             return Ok(expr.clone());
         };
         if counts_rows {
@@ -2200,10 +2211,10 @@ impl<'l> DerivedCols<'l> {
         // Preserve every additional column dependency (e.g. argMax's ordering
         // column) when an unrelated grouping expression creates a Project.
         // Literal parameters need no source column and remain untouched.
-        for argument in agg_fn.args.iter().skip(1) {
+        for argument in agg_fn.params.args.iter().skip(1) {
             self.passthrough(argument)?;
         }
-        match agg_col_name(&agg_fn.args) {
+        match agg_col_name(&agg_fn.params.args) {
             Some(name) => {
                 self.push(name, self.lowerer.lower_expr(arg)?);
                 Ok(expr.clone())
@@ -2212,7 +2223,7 @@ impl<'l> DerivedCols<'l> {
                 let alias = unalias(arg).to_string();
                 self.materialize(alias.clone(), self.lowerer.lower_expr(arg)?)?;
                 let mut agg_fn = agg_fn.clone();
-                agg_fn.args[0] = Expr::Column(DfColumn::new_unqualified(alias));
+                agg_fn.params.args[0] = Expr::Column(DfColumn::new_unqualified(alias));
                 Ok(Expr::AggregateFunction(agg_fn))
             }
         }
@@ -2298,8 +2309,8 @@ fn expr_to_group_ref(expr: &Expr) -> Result<ColumnRef, LoweringError> {
 
 fn extract_percentile_q(args: &[Expr]) -> Result<f64, LoweringError> {
     let q = match args.get(1) {
-        Some(Expr::Literal(DfScalarValue::Float64(Some(q)))) => *q,
-        Some(Expr::Literal(DfScalarValue::Float32(Some(q)))) => *q as f64,
+        Some(Expr::Literal(DfScalarValue::Float64(Some(q)), _)) => *q,
+        Some(Expr::Literal(DfScalarValue::Float32(Some(q)), _)) => *q as f64,
         _ => {
             return Err(LoweringError::InvalidExpression(
                 "percentile value must be a float literal (2nd arg)".into(),
@@ -2319,9 +2330,9 @@ fn extract_percentile_q(args: &[Expr]) -> Result<f64, LoweringError> {
 
 fn eval_fetch(expr_opt: &Option<Box<Expr>>) -> Option<usize> {
     expr_opt.as_ref().and_then(|e| match e.as_ref() {
-        Expr::Literal(DfScalarValue::Int64(Some(v))) if *v >= 0 => Some(*v as usize),
-        Expr::Literal(DfScalarValue::UInt64(Some(v))) => Some(*v as usize),
-        Expr::Literal(DfScalarValue::Int32(Some(v))) if *v >= 0 => Some(*v as usize),
+        Expr::Literal(DfScalarValue::Int64(Some(v)), _) if *v >= 0 => Some(*v as usize),
+        Expr::Literal(DfScalarValue::UInt64(Some(v)), _) => Some(*v as usize),
+        Expr::Literal(DfScalarValue::Int32(Some(v)), _) if *v >= 0 => Some(*v as usize),
         _ => None,
     })
 }
@@ -2356,14 +2367,6 @@ fn lower_window_func_kind(fun: &WindowFunctionDefinition) -> Result<WindowFuncKi
             "max" => Ok(WindowFuncKind::Max),
             other => Err(unsupported("aggregate", other)),
         },
-        WindowFunctionDefinition::BuiltInWindowFunction(biwf) => {
-            use datafusion::logical_expr::BuiltInWindowFunction;
-            match biwf {
-                BuiltInWindowFunction::FirstValue => Ok(WindowFuncKind::FirstValue),
-                BuiltInWindowFunction::LastValue => Ok(WindowFuncKind::LastValue),
-                BuiltInWindowFunction::NthValue => Ok(WindowFuncKind::NthValue(None)),
-            }
-        }
     }
 }
 
diff --git a/crates/frontend-sql/tests/unified_sql_lowering.rs b/crates/frontend-sql/tests/unified_sql_lowering.rs
index 2cc9e9ee2..066434a8c 100644
--- a/crates/frontend-sql/tests/unified_sql_lowering.rs
+++ b/crates/frontend-sql/tests/unified_sql_lowering.rs
@@ -206,16 +206,19 @@ fn find_filter(node: &OperatorNode) -> Option<&OperatorNode> {
 }
 
 #[tokio::test]
-async fn select_star_with_where_folds_predicate_onto_scan() {
-    // SELECT * elides the projection; WHERE folds onto the Scan predicates.
+async fn where_folds_predicate_onto_scan() {
+    // WHERE folds onto the Scan predicates, below the SELECT projection.
     let qe = lower("SELECT * FROM metrics WHERE service = 'api'").await;
+    let NonASAPOp::Project { child, .. } = op(&qe) else {
+        panic!("expected Project at root, got {qe:?}");
+    };
     let NonASAPOp::Scan {
         source,
         predicates,
         schema,
-    } = op(&qe)
+    } = op(child)
     else {
-        panic!("expected Scan at root, got {qe:?}");
+        panic!("expected Scan under the projection, got {child:?}");
     };
     assert!(matches!(source, Source::Table { table_ref } if table_ref == "metrics"));
     assert_eq!(predicates.len(), 1, "WHERE clause folded onto the scan");
@@ -702,7 +705,9 @@ async fn a_multi_column_in_subquery_is_rejected() {
     )
     .await
     .expect_err("IN must select one column");
-    assert!(format!("{err}").contains("exactly one column"), "got {err}");
+    // DataFusion's planner rejects this before `lower_in_subquery`'s own
+    // arity check; either message names the one-column rule.
+    assert!(format!("{err}").contains("one column"), "got {err}");
 }
 
 #[tokio::test]
@@ -2195,10 +2200,13 @@ async fn lead_in_frame_lowers_to_its_own_kind_not_lead() {
 /// PromQL's Float64 Unix-seconds `EvalTimestamp`.
 #[tokio::test]
 async fn now_in_predicate_lowers_to_current_timestamp() {
-    // SELECT * folds WHERE onto Scan.predicates (no explicit Filter node).
+    // WHERE folds onto Scan.predicates (no explicit Filter node).
     let qe = lower("SELECT * FROM metrics WHERE ts < NOW()").await;
-    let NonASAPOp::Scan { predicates, .. } = op(&qe) else {
-        panic!("expected Scan at root, got {qe:?}");
+    let NonASAPOp::Project { child, .. } = op(&qe) else {
+        panic!("expected Project at root, got {qe:?}");
+    };
+    let NonASAPOp::Scan { predicates, .. } = op(child) else {
+        panic!("expected Scan under the projection, got {child:?}");
     };
     assert_eq!(predicates.len(), 1);
     assert!(
@@ -2214,8 +2222,11 @@ async fn now_in_predicate_lowers_to_current_timestamp() {
 #[tokio::test]
 async fn clickhouse_now_in_predicate_lowers_to_current_timestamp() {
     let qe = lower_clickhouse("SELECT * FROM metrics WHERE ts < now()").await;
-    let NonASAPOp::Scan { predicates, .. } = op(&qe) else {
-        panic!("expected Scan at root, got {qe:?}");
+    let NonASAPOp::Project { child, .. } = op(&qe) else {
+        panic!("expected Project at root, got {qe:?}");
+    };
+    let NonASAPOp::Scan { predicates, .. } = op(child) else {
+        panic!("expected Scan under the projection, got {child:?}");
     };
     assert_eq!(predicates.len(), 1);
     assert!(

From 13e95855ff0baf1edcd2db9f2b1cb1f77b858033 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Fri, 2 Oct 2026 21:20:23 +0000
Subject: [PATCH 30/48] feat(promql): lower queries to unified operator and
 scalar IR

---
 Cargo.lock                                    |    2 +
 crates/frontend-metricsql/Cargo.toml          |    1 +
 crates/frontend-metricsql/src/lib.rs          |    3 +
 crates/frontend-metricsql/src/unified/mod.rs  |  389 +++
 crates/frontend-promql/Cargo.toml             |    1 +
 crates/frontend-promql/src/lib.rs             |    3 +
 crates/frontend-promql/src/unified/error.rs   |   81 +
 .../frontend-promql/src/unified/histogram.rs  |  129 +
 crates/frontend-promql/src/unified/mod.rs     |  233 ++
 crates/frontend-promql/src/unified/promql.rs  | 2236 +++++++++++++++++
 .../tests/unified_histogram_metadata.rs       |  138 +
 .../tests/unified_promql_conformance.rs       | 2208 ++++++++++++++++
 .../tests/unified_promql_lowering.rs          | 1615 ++++++++++++
 .../tests/unified_scalar_design.rs            |  129 +
 .../frontend-promql/tests/unified_support.rs  |  101 +
 15 files changed, 7269 insertions(+)
 create mode 100644 crates/frontend-metricsql/src/unified/mod.rs
 create mode 100644 crates/frontend-promql/src/unified/error.rs
 create mode 100644 crates/frontend-promql/src/unified/histogram.rs
 create mode 100644 crates/frontend-promql/src/unified/mod.rs
 create mode 100644 crates/frontend-promql/src/unified/promql.rs
 create mode 100644 crates/frontend-promql/tests/unified_histogram_metadata.rs
 create mode 100644 crates/frontend-promql/tests/unified_promql_conformance.rs
 create mode 100644 crates/frontend-promql/tests/unified_promql_lowering.rs
 create mode 100644 crates/frontend-promql/tests/unified_scalar_design.rs
 create mode 100644 crates/frontend-promql/tests/unified_support.rs

diff --git a/Cargo.lock b/Cargo.lock
index c1f6003dc..feed74cf1 100644
--- a/Cargo.lock
+++ b/Cargo.lock
@@ -352,6 +352,7 @@ dependencies = [
 name = "asap-frontend-metricsql"
 version = "0.1.0"
 dependencies = [
+ "asap-frontend-common",
  "asap-types",
  "metricsql_parser",
  "thiserror 2.0.18",
@@ -362,6 +363,7 @@ name = "asap-frontend-promql"
 version = "0.1.0"
 dependencies = [
  "asap-aware-mapping",
+ "asap-frontend-common",
  "asap-types",
  "promql-parser",
 ]
diff --git a/crates/frontend-metricsql/Cargo.toml b/crates/frontend-metricsql/Cargo.toml
index 8fa341b80..cba166f7c 100644
--- a/crates/frontend-metricsql/Cargo.toml
+++ b/crates/frontend-metricsql/Cargo.toml
@@ -5,5 +5,6 @@ edition = "2021"
 
 [dependencies]
 asap-types = { path = "../types" }
+asap-frontend-common = { path = "../frontend-common" }
 metricsql_parser = { path = "../metricsql-parser-vendored" }
 thiserror = "2"
diff --git a/crates/frontend-metricsql/src/lib.rs b/crates/frontend-metricsql/src/lib.rs
index 26a034c43..4417a0be3 100644
--- a/crates/frontend-metricsql/src/lib.rs
+++ b/crates/frontend-metricsql/src/lib.rs
@@ -324,3 +324,6 @@ fn require_arity(name: &str, actual: usize, expected: usize) -> Result<(), Metri
 fn unsupported(message: impl Into<String>) -> MetricsqlError {
     MetricsqlError::UnsupportedFeature(message.into())
 }
+
+/// Unified lowering, promoted to the root API at planner cutover.
+pub mod unified;
diff --git a/crates/frontend-metricsql/src/unified/mod.rs b/crates/frontend-metricsql/src/unified/mod.rs
new file mode 100644
index 000000000..3544a9801
--- /dev/null
+++ b/crates/frontend-metricsql/src/unified/mod.rs
@@ -0,0 +1,389 @@
+//! MetricsQL AST → the name-based `UnresolvedOp` tree → the unified operator DAG.
+
+use std::{rc::Rc, time::Duration};
+
+use asap_frontend_common::{
+    resolve_root, UnresolvedOp as U, UnresolvedPredicate, UnresolvedScalar,
+};
+use asap_types::ir::{BinaryOperator, ExprSemantics, OperatorNode, TimeRangeKind};
+use asap_types::pre_asap::{
+    AggIntent, ArithmeticOpKind, BinaryOpKind, ColumnRef, CompareOpKind, GroupKeys,
+    PromQLVectorSetOpKind, Reduction, ScalarValue, Source,
+};
+use asap_types::types::AccuracyTarget;
+use metricsql_parser::ast::{AggregateModifier, DurationExpr, Expr, MetricExpr, RollupExpr};
+use metricsql_parser::functions::{AggregateFunction, BuiltinFunction, RollupFunction};
+use metricsql_parser::label::{LabelFilter, LabelFilterOp, NAME_LABEL};
+use thiserror::Error;
+
+pub use metricsql_parser::ast::Expr as MetricsqlExpr;
+
+#[derive(Debug, Error)]
+pub enum MetricsqlError {
+    #[error("MetricsQL parse error: {0}")]
+    Parse(String),
+    #[error("unsupported MetricsQL feature: {0}")]
+    UnsupportedFeature(String),
+    #[error("MetricsQL column resolution failed: {0}")]
+    Resolve(String),
+}
+
+pub fn parse_metricsql(query: &str) -> Result<MetricsqlExpr, MetricsqlError> {
+    metricsql_parser::parser::parse(query).map_err(|e| MetricsqlError::Parse(e.to_string()))
+}
+
+pub fn canonical_metricsql(query: &str) -> Result<String, MetricsqlError> {
+    Ok(parse_metricsql(query)?.to_string())
+}
+
+pub fn lower_metricsql(
+    query: &str,
+    accuracy: AccuracyTarget,
+) -> Result<Rc<OperatorNode>, MetricsqlError> {
+    match lower_metricsql_query(query, accuracy)? {
+        asap_types::ir::QueryRoot::Operator(node) => Ok(node),
+        _ => Err(unsupported("scalar root: use lower_metricsql_query")),
+    }
+}
+
+/// Lower scalar constants without fabricating a relational operator.
+pub fn lower_metricsql_query(
+    query: &str,
+    accuracy: AccuracyTarget,
+) -> Result<asap_types::ir::QueryRoot, MetricsqlError> {
+    let ast = parse_metricsql(query)?;
+    if let Expr::NumberLiteral(number) = &ast {
+        return Ok(asap_types::ir::QueryRoot::Scalar(
+            asap_types::ir::ScalarExpr::literal_f64(number.value),
+        ));
+    }
+    let unresolved = Lowerer { accuracy }.lower(&ast)?;
+    resolve_root(&unresolved)
+        .map(asap_types::ir::QueryRoot::Operator)
+        .map_err(|e| MetricsqlError::Resolve(e.to_string()))
+}
+
+struct Lowerer {
+    accuracy: AccuracyTarget,
+}
+
+impl Lowerer {
+    fn lower(&self, expr: &Expr) -> Result<U, MetricsqlError> {
+        match expr {
+            Expr::MetricExpression(e) => self.metric(e),
+            Expr::Rollup(e) => self.rollup(e),
+            Expr::Function(e) => self.function(e),
+            Expr::Aggregation(e) => self.aggregate(e),
+            Expr::NumberLiteral(_) => {
+                Err(unsupported("scalar root requires lower_metricsql_query"))
+            }
+            // Vector negation is `x * -1` (as in the PromQL front end).
+            Expr::UnaryOperator(e) => Ok(U::PromqlScalarOp {
+                child: Rc::new(self.lower(&e.expr)?),
+                scalar: UnresolvedScalar::Literal(ScalarValue::Float64(-1.0)),
+                op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul),
+                scalar_left: false,
+                return_bool: false,
+            }),
+            Expr::BinaryOperator(e) => self.binary(e),
+            Expr::Parens(e) if e.expressions.len() == 1 => self.lower(&e.expressions[0]),
+            Expr::With(e) => self.lower(&e.expr),
+            other => Err(unsupported(format!("AST node `{other}`"))),
+        }
+    }
+
+    fn metric(&self, metric: &MetricExpr) -> Result<U, MetricsqlError> {
+        if metric.has_or_matchers() {
+            return Err(unsupported("or-delimited selector matchers"));
+        }
+        let name = metric
+            .metric_name()
+            .ok_or_else(|| unsupported("selector without one exact metric name"))?;
+        let mut filters: Vec<_> = metric
+            .matchers
+            .filter_iter()
+            .filter(|f| f.label != NAME_LABEL)
+            .collect();
+        filters.sort_by(|a, b| a.label.cmp(&b.label).then(a.value.cmp(&b.value)));
+        Ok(U::Scan {
+            source: Source::TimeSeries {
+                metric: name.to_owned(),
+            },
+            predicates: filters
+                .into_iter()
+                .map(|f| UnresolvedPredicate(matcher(f)))
+                .collect(),
+            schema: None,
+        })
+    }
+
+    fn rollup(&self, rollup: &RollupExpr) -> Result<U, MetricsqlError> {
+        if rollup.offset.is_some() || rollup.at.is_some() {
+            return Err(unsupported("offset and @ modifiers"));
+        }
+        if rollup.for_subquery() {
+            return Err(unsupported("subquery step or inherited step"));
+        }
+        let child = self.lower(&rollup.expr)?;
+        match &rollup.window {
+            None => Ok(child),
+            Some(window) => Ok(U::TimeRange {
+                range: duration(window)?,
+                kind: TimeRangeKind::Range,
+                child: Rc::new(child),
+            }),
+        }
+    }
+
+    fn function(
+        &self,
+        function: &metricsql_parser::ast::FunctionExpr,
+    ) -> Result<U, MetricsqlError> {
+        if function.keep_metric_names {
+            return Err(unsupported(
+                "keep_metric_names requires metric-name lineage",
+            ));
+        }
+        let BuiltinFunction::Rollup(rollup) = function.function else {
+            return Err(unsupported(format!("function `{}`", function.name())));
+        };
+        let expected_args = if rollup == RollupFunction::QuantileOverTime {
+            2
+        } else {
+            1
+        };
+        require_arity(function.name(), function.args.len(), expected_args)?;
+        let child_index = usize::from(rollup == RollupFunction::QuantileOverTime);
+        let child = function
+            .args
+            .get(child_index)
+            .ok_or_else(|| unsupported(format!("missing argument for `{}`", function.name())))?;
+        let intent = match rollup {
+            RollupFunction::DefaultRollup | RollupFunction::LastOverTime => AggIntent::LastOverTime,
+            RollupFunction::FirstOverTime => AggIntent::FirstOverTime,
+            RollupFunction::AvgOverTime => AggIntent::Avg { col: None },
+            RollupFunction::MinOverTime => AggIntent::Min { col: None },
+            RollupFunction::MaxOverTime => AggIntent::Max { col: None },
+            RollupFunction::SumOverTime => AggIntent::Sum { col: None },
+            RollupFunction::CountOverTime => AggIntent::Count {
+                accuracy: self.accuracy.clone(),
+            },
+            RollupFunction::StddevOverTime => AggIntent::StdDev {
+                col: None,
+                population: true,
+            },
+            RollupFunction::StdvarOverTime => AggIntent::Variance {
+                col: None,
+                population: true,
+            },
+            RollupFunction::Rate => AggIntent::Rate,
+            RollupFunction::IRate => AggIntent::IRate,
+            RollupFunction::Increase => AggIntent::Increase,
+            RollupFunction::Changes => AggIntent::Changes,
+            RollupFunction::Delta => AggIntent::Delta,
+            RollupFunction::IDelta => AggIntent::IDelta,
+            RollupFunction::Deriv => AggIntent::Deriv,
+            RollupFunction::Resets => AggIntent::Resets,
+            RollupFunction::MadOverTime => AggIntent::MadOverTime,
+            RollupFunction::PresentOverTime => AggIntent::PresentOverTime,
+            RollupFunction::AbsentOverTime => AggIntent::AbsentOverTime,
+            RollupFunction::QuantileOverTime => AggIntent::Quantile {
+                col: None,
+                q: number_arg(&function.args, 0)?,
+                accuracy: self.accuracy.clone(),
+            },
+            _ => {
+                return Err(unsupported(format!(
+                    "rollup function `{}`",
+                    function.name()
+                )))
+            }
+        };
+        let child = self.lower(child)?;
+        if rollup == RollupFunction::DefaultRollup && !matches!(child, U::TimeRange { .. }) {
+            return Err(unsupported(
+                "default_rollup without an explicit range requires an evaluation step",
+            ));
+        }
+        Ok(aggregate(Reduction::PerEntity, intent, child))
+    }
+
+    fn aggregate(
+        &self,
+        expr: &metricsql_parser::ast::AggregationExpr,
+    ) -> Result<U, MetricsqlError> {
+        if expr.limit != 0 || expr.keep_metric_names {
+            return Err(unsupported("aggregate limit or keep_metric_names"));
+        }
+        let expected_args = if expr.function == AggregateFunction::Quantile {
+            2
+        } else {
+            1
+        };
+        require_arity(expr.name(), expr.args.len(), expected_args)?;
+        let child_index = expr
+            .arg_idx_for_optimization()
+            .ok_or_else(|| unsupported(format!("aggregate `{}` arguments", expr.name())))?;
+        let intent = match expr.function {
+            AggregateFunction::Sum => AggIntent::Sum { col: None },
+            AggregateFunction::Avg => AggIntent::Avg { col: None },
+            AggregateFunction::Min => AggIntent::Min { col: None },
+            AggregateFunction::Max => AggIntent::Max { col: None },
+            AggregateFunction::Count => AggIntent::Cardinality {
+                cols: vec![],
+                accuracy: self.accuracy.clone(),
+            },
+            AggregateFunction::StdDev => AggIntent::StdDev {
+                col: None,
+                population: true,
+            },
+            AggregateFunction::StdVar => AggIntent::Variance {
+                col: None,
+                population: true,
+            },
+            AggregateFunction::Group => AggIntent::Group,
+            AggregateFunction::Quantile => AggIntent::Quantile {
+                col: None,
+                q: number_arg(&expr.args, 0)?,
+                accuracy: self.accuracy.clone(),
+            },
+            _ => return Err(unsupported(format!("aggregate `{}`", expr.name()))),
+        };
+        let reduction = match &expr.modifier {
+            None => Reduction::by(vec![]),
+            Some(AggregateModifier::By(v)) => Reduction::by(names(v)),
+            Some(AggregateModifier::Without(v)) => Reduction::Reduce(GroupKeys::without(names(v))),
+        };
+        let child = expr
+            .args
+            .get(child_index)
+            .ok_or_else(|| unsupported("missing aggregate input"))?;
+        Ok(aggregate(reduction, intent, self.lower(child)?))
+    }
+
+    fn binary(&self, expr: &metricsql_parser::ast::BinaryExpr) -> Result<U, MetricsqlError> {
+        if expr.modifier.is_some() {
+            return Err(unsupported("binary vector matching modifiers"));
+        }
+        use metricsql_parser::ast::Operator as O;
+        let op = match expr.op {
+            O::Add => BinaryOpKind::Arithmetic(ArithmeticOpKind::Add),
+            O::Sub => BinaryOpKind::Arithmetic(ArithmeticOpKind::Sub),
+            O::Mul => BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul),
+            O::Div => BinaryOpKind::Arithmetic(ArithmeticOpKind::Div),
+            O::Mod => BinaryOpKind::Arithmetic(ArithmeticOpKind::Mod),
+            O::Pow => BinaryOpKind::Arithmetic(ArithmeticOpKind::Pow),
+            O::Atan2 => BinaryOpKind::Arithmetic(ArithmeticOpKind::Atan2),
+            O::Eql => BinaryOpKind::Compare(CompareOpKind::Eq),
+            O::NotEq => BinaryOpKind::Compare(CompareOpKind::Ne),
+            O::Lt => BinaryOpKind::Compare(CompareOpKind::Lt),
+            O::Lte => BinaryOpKind::Compare(CompareOpKind::Le),
+            O::Gt => BinaryOpKind::Compare(CompareOpKind::Gt),
+            O::Gte => BinaryOpKind::Compare(CompareOpKind::Ge),
+            O::And => BinaryOpKind::Set(PromQLVectorSetOpKind::And),
+            O::Or => BinaryOpKind::Set(PromQLVectorSetOpKind::Or),
+            O::Unless => BinaryOpKind::Set(PromQLVectorSetOpKind::Unless),
+            O::If | O::IfNot | O::Default => {
+                return Err(unsupported(format!("MetricsQL operator `{}`", expr.op)))
+            }
+        };
+        for (scalar, vector, scalar_left) in [
+            (&expr.left, &expr.right, true),
+            (&expr.right, &expr.left, false),
+        ] {
+            if let Expr::NumberLiteral(n) = scalar.as_ref() {
+                return Ok(U::PromqlScalarOp {
+                    child: Rc::new(self.lower(vector)?),
+                    scalar: UnresolvedScalar::Literal(ScalarValue::Float64(n.value)),
+                    op,
+                    scalar_left,
+                    return_bool: false,
+                });
+            }
+        }
+        Ok(binary_op(
+            op,
+            self.lower(&expr.left)?,
+            self.lower(&expr.right)?,
+        ))
+    }
+}
+
+/// A `BinaryOp` with default matching; MetricsQL modifiers (including `bool`)
+/// are rejected before reaching here.
+fn binary_op(kind: BinaryOpKind, lhs: U, rhs: U) -> U {
+    U::BinaryOp {
+        operator: BinaryOperator {
+            kind,
+            vector_match: None,
+            checked_relative_division: false,
+            checked_finite_division: false,
+        },
+        return_bool: false,
+        lhs: Rc::new(lhs),
+        rhs: Rc::new(rhs),
+    }
+}
+
+fn names(values: &[String]) -> Vec<ColumnRef> {
+    values.iter().cloned().map(ColumnRef::Named).collect()
+}
+
+fn aggregate(reduction: Reduction<ColumnRef>, intent: AggIntent<ColumnRef>, child: U) -> U {
+    U::Aggregate {
+        reduction,
+        measures: vec![intent],
+        output_names: vec![String::new()],
+        filters: vec![],
+        having: None,
+        child: Rc::new(child),
+    }
+}
+
+fn matcher(filter: &LabelFilter) -> UnresolvedScalar {
+    let op = match filter.op {
+        LabelFilterOp::Equal => CompareOpKind::Eq,
+        LabelFilterOp::NotEqual => CompareOpKind::Ne,
+        LabelFilterOp::RegexEqual => CompareOpKind::Regex,
+        LabelFilterOp::RegexNotEqual => CompareOpKind::NotRegex,
+    };
+    UnresolvedScalar::Compare {
+        left: Box::new(UnresolvedScalar::Column(ColumnRef::Named(
+            filter.label.clone(),
+        ))),
+        op,
+        right: Box::new(UnresolvedScalar::Literal(ScalarValue::Utf8(
+            filter.value.clone(),
+        ))),
+        semantics: ExprSemantics::Promql,
+    }
+}
+
+fn duration(value: &DurationExpr) -> Result<Duration, MetricsqlError> {
+    match value {
+        DurationExpr::Millis(ms) if *ms >= 0 => Ok(Duration::from_millis(*ms as u64)),
+        DurationExpr::StepValue(_) => Err(unsupported("step-relative duration")),
+        DurationExpr::Millis(_) => Err(unsupported("negative duration")),
+    }
+}
+
+fn number_arg(args: &[Expr], index: usize) -> Result<f64, MetricsqlError> {
+    match args.get(index) {
+        Some(Expr::NumberLiteral(v)) if v.value.is_finite() => Ok(v.value),
+        _ => Err(unsupported(format!("numeric argument #{index}"))),
+    }
+}
+
+fn require_arity(name: &str, actual: usize, expected: usize) -> Result<(), MetricsqlError> {
+    if actual == expected {
+        Ok(())
+    } else {
+        Err(unsupported(format!(
+            "`{name}` with {actual} arguments; canonical lowering requires exactly {expected}"
+        )))
+    }
+}
+
+fn unsupported(message: impl Into<String>) -> MetricsqlError {
+    MetricsqlError::UnsupportedFeature(message.into())
+}
diff --git a/crates/frontend-promql/Cargo.toml b/crates/frontend-promql/Cargo.toml
index b108e32c7..b8576ae9b 100644
--- a/crates/frontend-promql/Cargo.toml
+++ b/crates/frontend-promql/Cargo.toml
@@ -7,6 +7,7 @@ edition = "2021"
 # — both in asap-types. Pulls the PromQL parser only — never DataFusion.
 [dependencies]
 asap-types = { path = "../types" }
+asap-frontend-common = { path = "../frontend-common" }
 
 # Shared ProjectASAP parser contract. Keep this immutable revision aligned
 # with backend parsing and treat newly parsed functions as unsupported until
diff --git a/crates/frontend-promql/src/lib.rs b/crates/frontend-promql/src/lib.rs
index 31b169359..348fa0263 100644
--- a/crates/frontend-promql/src/lib.rs
+++ b/crates/frontend-promql/src/lib.rs
@@ -191,3 +191,6 @@ mod tests {
         ));
     }
 }
+
+/// Unified lowering, promoted to the root API at planner cutover.
+pub mod unified;
diff --git a/crates/frontend-promql/src/unified/error.rs b/crates/frontend-promql/src/unified/error.rs
new file mode 100644
index 000000000..a889d6710
--- /dev/null
+++ b/crates/frontend-promql/src/unified/error.rs
@@ -0,0 +1,81 @@
+use std::fmt;
+
+use asap_frontend_common::ResolveDAGError;
+use asap_types::workload::WorkloadError;
+
+/// Errors from lowering a PromQL query (parse → the name-based unresolved
+/// tree, built directly →
+/// [`resolve_root`](asap_frontend_common::resolve_root) binds it to the
+/// unified operator DAG, issue #179).
+///
+/// Carries no DataFusion type — the PromQL front end never depends on the SQL
+/// stack. The language-neutral variants (`UnsupportedFeature` / `WrongLanguage`
+/// / `Convert`) are mirrored by [`asap_frontend_sql::SqlError`] rather than
+/// shared, so neither front end pulls the other's parser.
+#[derive(Debug)]
+pub enum PromqlError {
+    /// The workload omitted information required for plan-ready PromQL lowering.
+    InvalidWorkload(WorkloadError),
+    /// The `promql-parser` crate rejected the query string (parse failure).
+    Parse(String),
+    /// A PromQL function (`rate`, `*_over_time`, …) not supported in this version.
+    UnsupportedFunction(String),
+    /// A PromQL aggregation operator (`sum`, `topk`, …) not supported.
+    UnsupportedAggregateOp(String),
+    /// A structural feature (offset / `@` / `without`) not supported in this
+    /// version.
+    UnsupportedFeature(String),
+    /// A required function / aggregator argument was missing.
+    MissingArgument(String),
+    /// An argument had the wrong shape (e.g. a non-numeric `topk` parameter).
+    InvalidParameter(String),
+    /// The workload's query language is not PromQL.
+    WrongLanguage(String),
+    /// Resolving the canonical unresolved tree failed (name resolution
+    /// against the bound schema).
+    Convert(ResolveDAGError),
+}
+
+impl fmt::Display for PromqlError {
+    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
+        match self {
+            Self::InvalidWorkload(e) => write!(f, "invalid PromQL workload: {e}"),
+            Self::Parse(e) => write!(f, "PromQL parse error: {e}"),
+            Self::UnsupportedFunction(n) => write!(f, "unsupported PromQL function: {n}"),
+            Self::UnsupportedAggregateOp(n) => write!(f, "unsupported PromQL aggregate op: {n}"),
+            Self::UnsupportedFeature(m) => write!(f, "unsupported feature: {m}"),
+            Self::MissingArgument(m) => write!(f, "missing argument: {m}"),
+            Self::InvalidParameter(m) => write!(f, "invalid parameter: {m}"),
+            Self::WrongLanguage(l) => write!(f, "unsupported query language: {l}"),
+            Self::Convert(e) => write!(f, "column resolution failed: {e}"),
+        }
+    }
+}
+
+impl std::error::Error for PromqlError {}
+
+impl From<ResolveDAGError> for PromqlError {
+    fn from(e: ResolveDAGError) -> Self {
+        Self::Convert(e)
+    }
+}
+
+impl From<WorkloadError> for PromqlError {
+    fn from(e: WorkloadError) -> Self {
+        Self::InvalidWorkload(e)
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn unsupported_feature_label_is_language_neutral() {
+        // `UnsupportedFeature` shares a Display label with the SQL side, so it
+        // must not hardcode "PromQL".
+        let msg = PromqlError::UnsupportedFeature("subquery".into()).to_string();
+        assert_eq!(msg, "unsupported feature: subquery");
+        assert!(!msg.contains("PromQL"), "got: {msg}");
+    }
+}
diff --git a/crates/frontend-promql/src/unified/histogram.rs b/crates/frontend-promql/src/unified/histogram.rs
new file mode 100644
index 000000000..ecb8cd2c4
--- /dev/null
+++ b/crates/frontend-promql/src/unified/histogram.rs
@@ -0,0 +1,129 @@
+//! Sample-type metadata for the `histogram_quantile` discrimination (issue #79).
+//!
+//! Classic cumulative buckets use exact interpolation. The explicitly declared
+//! `RawSamples` extension permits generic quantile sketches; it is not standard
+//! PromQL histogram semantics. Native samples are rejected until the IR has a
+//! native histogram sample type. Undeclared metrics require classic bucket
+//! evidence (`by (le)`, a `_bucket` metric, or an `le` matcher).
+
+use std::cell::RefCell;
+use std::collections::HashMap;
+
+/// The physical sample type behind a histogram metric — the true signal for
+/// whether `histogram_quantile` over it can be re-sketched.
+#[derive(Debug, Clone, Copy, PartialEq, Eq)]
+pub enum HistogramKind {
+    /// Classic cumulative `le` buckets — pre-aggregated counts. The
+    /// distribution can't be reconstructed from them, so it is **not**
+    /// sketch-able: `histogram_quantile` is exact bucket interpolation.
+    ClassicBucket,
+    /// Native histogram samples; currently rejected because the IR lacks their type.
+    Native,
+    /// Raw float samples the client retains — sketch-able. This is the case the
+    /// generic `Quantile` lowering exists for (a client holding raw samples can
+    /// build a quantile sketch even though the user wrote `histogram_quantile`).
+    RawSamples,
+}
+
+impl HistogramKind {
+    /// Whether `histogram_quantile` over this kind lowers to the sketch-able
+    /// generic `Quantile` (`true`) rather than exact bucket interpolation.
+    pub fn is_sketchable(self) -> bool {
+        matches!(self, HistogramKind::RawSamples)
+    }
+}
+
+/// Metric-name → declared [`HistogramKind`]. Supplied by a client that knows its
+/// sample types, to drive the `histogram_quantile` discrimination from metadata
+/// instead of query structure (issue #79).
+#[derive(Debug, Clone, Default)]
+pub struct HistogramCatalog(HashMap<String, HistogramKind>);
+
+impl HistogramCatalog {
+    pub fn new() -> Self {
+        Self::default()
+    }
+
+    /// Declare `metric`'s sample type (builder style).
+    pub fn with(mut self, metric: impl Into<String>, kind: HistogramKind) -> Self {
+        self.0.insert(metric.into(), kind);
+        self
+    }
+
+    /// The declared kind for `metric`, if any.
+    pub fn kind_of(&self, metric: &str) -> Option<HistogramKind> {
+        self.0.get(metric).copied()
+    }
+
+    pub fn is_empty(&self) -> bool {
+        self.0.is_empty()
+    }
+}
+
+thread_local! {
+    static CURRENT: RefCell<Option<HistogramCatalog>> = const { RefCell::new(None) };
+}
+
+/// RAII guard installing `catalog` as the ambient histogram catalog for the
+/// current thread, restoring the prior value on drop.
+///
+/// Lowering is synchronous and processes one query at a time, so a thread-local
+/// ambient catalog cleanly injects this read-only metadata into the deep,
+/// free-function `walk` recursion without threading a parameter through every
+/// signature (the discrimination is consulted in exactly one place,
+/// `walk_histogram`).
+pub(crate) struct CatalogGuard(Option<HistogramCatalog>);
+
+impl CatalogGuard {
+    pub(crate) fn install(catalog: HistogramCatalog) -> Self {
+        let prev = CURRENT.with(|c| c.borrow_mut().replace(catalog));
+        CatalogGuard(prev)
+    }
+}
+
+impl Drop for CatalogGuard {
+    fn drop(&mut self) {
+        CURRENT.with(|c| *c.borrow_mut() = self.0.take());
+    }
+}
+
+/// The ambient catalog's declared kind for `metric`, or `None` when no catalog
+/// is installed or the metric is undeclared (→ fall back to the heuristic).
+pub(crate) fn current_kind_of(metric: &str) -> Option<HistogramKind> {
+    CURRENT.with(|c| c.borrow().as_ref().and_then(|cat| cat.kind_of(metric)))
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn only_explicit_raw_samples_are_sketchable() {
+        assert!(!HistogramKind::ClassicBucket.is_sketchable());
+        assert!(!HistogramKind::Native.is_sketchable());
+        assert!(HistogramKind::RawSamples.is_sketchable());
+    }
+
+    #[test]
+    fn catalog_lookup() {
+        let cat = HistogramCatalog::new()
+            .with("classic", HistogramKind::ClassicBucket)
+            .with("raw", HistogramKind::RawSamples);
+        assert_eq!(cat.kind_of("classic"), Some(HistogramKind::ClassicBucket));
+        assert_eq!(cat.kind_of("raw"), Some(HistogramKind::RawSamples));
+        assert_eq!(cat.kind_of("unknown"), None);
+    }
+
+    #[test]
+    fn guard_installs_and_restores_the_ambient_catalog() {
+        assert_eq!(current_kind_of("m"), None);
+        {
+            let _g = CatalogGuard::install(
+                HistogramCatalog::new().with("m", HistogramKind::ClassicBucket),
+            );
+            assert_eq!(current_kind_of("m"), Some(HistogramKind::ClassicBucket));
+        }
+        // Restored to empty after the guard drops.
+        assert_eq!(current_kind_of("m"), None);
+    }
+}
diff --git a/crates/frontend-promql/src/unified/mod.rs b/crates/frontend-promql/src/unified/mod.rs
new file mode 100644
index 000000000..e7d99fe4c
--- /dev/null
+++ b/crates/frontend-promql/src/unified/mod.rs
@@ -0,0 +1,233 @@
+//! PromQL front end: parse (via `promql-parser`) → the name-based
+//! [`UnresolvedOp`](asap_frontend_common::UnresolvedOp) tree, built directly
+//! in canonical shape (issue #179) → [`resolve_root`].
+//!
+//! `resolve_root` runs the
+//! [`SchemaResolver`](asap_frontend_common::SchemaResolver) for positional
+//! name resolution and returns the unified
+//! [`OperatorNode`](asap_types::ir::OperatorNode) DAG. Depends on the PromQL
+//! parser only — never on the SQL / DataFusion stack.
+
+pub mod error;
+pub mod histogram;
+pub mod promql;
+
+use std::rc::Rc;
+
+use asap_types::ir::OperatorNode;
+use asap_types::workload::{DurationMs, PlanningWorkload, QueryLanguage, WorkloadError};
+
+pub use error::PromqlError;
+pub use histogram::{HistogramCatalog, HistogramKind};
+
+/// Lower every normalized PromQL workload entry to a plan-ready operator DAG.
+///
+/// PromQL workloads must declare a non-zero `data_ingestion_interval`; it is
+/// injected around each bare instant selector. Explicit range selectors keep
+/// their query-specified range.
+/// `now_ms` is the planning time in Unix milliseconds; cadence evidence must
+/// be valid at that time, using the same clock as downstream planning.
+pub fn lower_promql_workload(
+    workload: &PlanningWorkload,
+    now_ms: u64,
+) -> Result<Vec<Rc<OperatorNode>>, PromqlError> {
+    lower_promql_workload_inner(workload, now_ms)
+}
+
+/// Like [`lower_promql_workload`], but uses `histograms` to distinguish classic
+/// bucket interpolation from generic sketchable quantiles.
+pub fn lower_promql_workload_with_histograms(
+    workload: &PlanningWorkload,
+    histograms: HistogramCatalog,
+    now_ms: u64,
+) -> Result<Vec<Rc<OperatorNode>>, PromqlError> {
+    let _guard = histogram::CatalogGuard::install(histograms);
+    lower_promql_workload_inner(workload, now_ms)
+}
+
+/// Lower scalar and vector query roots without introducing constant operators.
+pub fn lower_promql_query_workload(
+    workload: &PlanningWorkload,
+    now_ms: u64,
+) -> Result<Vec<asap_types::ir::QueryRoot>, PromqlError> {
+    lower_promql_query_workload_inner(workload, now_ms)
+}
+
+pub fn lower_promql_query_workload_with_histograms(
+    workload: &PlanningWorkload,
+    histograms: HistogramCatalog,
+    now_ms: u64,
+) -> Result<Vec<asap_types::ir::QueryRoot>, PromqlError> {
+    let _guard = histogram::CatalogGuard::install(histograms);
+    lower_promql_query_workload_inner(workload, now_ms)
+}
+
+fn lower_promql_workload_inner(
+    workload: &PlanningWorkload,
+    now_ms: u64,
+) -> Result<Vec<Rc<OperatorNode>>, PromqlError> {
+    lower_promql_query_workload_inner(workload, now_ms)?
+        .into_iter()
+        .map(|root| match root {
+            asap_types::ir::QueryRoot::Operator(node) => Ok(node),
+            asap_types::ir::QueryRoot::Scalar(_) => Err(PromqlError::UnsupportedFeature(
+                "scalar root: use lower_promql_query_workload".into(),
+            )),
+        })
+        .collect()
+}
+
+fn lower_promql_query_workload_inner(
+    workload: &PlanningWorkload,
+    now_ms: u64,
+) -> Result<Vec<asap_types::ir::QueryRoot>, PromqlError> {
+    if !matches!(workload.query_workload.language, QueryLanguage::PromQL) {
+        return Err(PromqlError::WrongLanguage(format!(
+            "{:?}",
+            workload.query_workload.language
+        )));
+    }
+    workload.validate()?;
+    let &DurationMs(interval_ms) = workload
+        .data_workload
+        .as_ref()
+        .expect("validated PromQL workload has data_workload")
+        .data_ingestion_interval
+        .value_at(now_ms)
+        .ok_or(WorkloadError::UnavailableDataIngestionInterval)?;
+    workload
+        .query_workload
+        .entries()
+        .map(|entry| {
+            let root = promql::PromqlLowerer::lower_query_with_ingestion_interval(
+                &entry.query.0,
+                &entry.requirements.accuracy.target(),
+                std::time::Duration::from_millis(interval_ms),
+            )?;
+            Ok(root)
+        })
+        .collect()
+}
+
+#[cfg(test)]
+mod tests {
+    // Expiring evidence without an observation timestamp is never usable.
+    #[test]
+    fn rejects_unusable_ingestion_evidence() {
+        let mut input = workload("sum(data)");
+        input
+            .data_workload
+            .as_mut()
+            .unwrap()
+            .data_ingestion_interval
+            .valid_for_ms = Some(100);
+        assert!(lower_promql_workload(&input, 0).is_err());
+    }
+
+    // Cadence expiry is inclusive; future and expired evidence cannot set a horizon.
+    #[test]
+    fn ingestion_evidence_respects_planning_time_with_and_without_histograms() {
+        let mut input = workload("sum(data)");
+        let evidence = &mut input
+            .data_workload
+            .as_mut()
+            .unwrap()
+            .data_ingestion_interval;
+        evidence.observed_at_ms = Some(1_000);
+        evidence.valid_for_ms = Some(100);
+        for (now_ms, usable) in [(999, false), (1_000, true), (1_100, true), (1_101, false)] {
+            assert_eq!(lower_promql_workload(&input, now_ms).is_ok(), usable);
+            assert_eq!(
+                lower_promql_workload_with_histograms(&input, HistogramCatalog::default(), now_ms)
+                    .is_ok(),
+                usable
+            );
+        }
+        input
+            .data_workload
+            .as_mut()
+            .unwrap()
+            .data_ingestion_interval
+            .observed_at_ms = None;
+        assert!(
+            lower_promql_workload_with_histograms(&input, HistogramCatalog::default(), 1_000)
+                .is_err()
+        );
+    }
+    use std::time::Duration;
+
+    use asap_types::ir::{NonASAPOp, TimeRangeKind};
+    use asap_types::workload::{
+        BatchEntry, DataWorkload, Evidence, PlanningWorkload, Query, QueryRequirements,
+        QueryWorkload, TimeSelection,
+    };
+
+    use super::*;
+
+    fn workload(query: &str) -> PlanningWorkload {
+        PlanningWorkload {
+            query_workload: QueryWorkload {
+                language: QueryLanguage::PromQL,
+                query_batch: Some(vec![BatchEntry {
+                    query: Query(query.into()),
+                    requirements: QueryRequirements::default(),
+                    predictability: Default::default(),
+                    invocations: 1,
+                    execute_at: None,
+                    time_selection: TimeSelection::default(),
+                }]),
+                repeating_queries: None,
+            },
+            data_workload: Some(DataWorkload {
+                data_ingestion_interval: Evidence {
+                    value: Some(DurationMs(1_000)),
+                    ..Default::default()
+                },
+                ..Default::default()
+            }),
+        }
+    }
+
+    // A bare instant selector reads the latest sample within the declared
+    // ingestion interval: an `Instant` lookback of that length.
+    #[test]
+    fn instant_selector_uses_declared_ingestion_interval() {
+        let query = lower_promql_workload(&workload("sum by (job) (data)"), 0).unwrap();
+        let NonASAPOp::Aggregate { child, .. } = query[0].expect_non_asap() else {
+            panic!("expected aggregate")
+        };
+        assert!(
+            matches!(child.expect_non_asap(), NonASAPOp::TimeRange { range, kind, child }
+            if *range == Duration::from_secs(1)
+                && *kind == TimeRangeKind::Instant
+                && matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }))
+        );
+    }
+
+    // An explicit `m[5m]` keeps its own window as a `Range` selection.
+    #[test]
+    fn explicit_range_selector_keeps_its_query_range() {
+        let query = lower_promql_workload(&workload("sum_over_time(data[5m])"), 0).unwrap();
+        let NonASAPOp::Aggregate { child, .. } = query[0].expect_non_asap() else {
+            panic!("expected aggregate")
+        };
+        assert!(
+            matches!(child.expect_non_asap(), NonASAPOp::TimeRange { range, kind, child }
+            if *range == Duration::from_secs(300)
+                && *kind == TimeRangeKind::Range
+                && matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }))
+        );
+    }
+
+    #[test]
+    fn workload_without_interval_fails_loudly() {
+        let mut workload = workload("sum(data)");
+        workload.data_workload = Some(DataWorkload::default());
+        assert!(matches!(
+            lower_promql_workload(&workload, 0),
+            Err(PromqlError::InvalidWorkload(
+                asap_types::workload::WorkloadError::MissingDataIngestionInterval
+            ))
+        ));
+    }
+}
diff --git a/crates/frontend-promql/src/unified/promql.rs b/crates/frontend-promql/src/unified/promql.rs
new file mode 100644
index 000000000..f97e4fb9d
--- /dev/null
+++ b/crates/frontend-promql/src/unified/promql.rs
@@ -0,0 +1,2236 @@
+//! PromQL string → the name-based
+//! [`UnresolvedOp`](asap_frontend_common::UnresolvedOp) tree.
+//!
+//! - **Parsing** is delegated to `promql-parser` 0.8.
+//! - **Lowering** builds *directly in canonical shape* here (issue #179): the
+//!   walk interprets PromQL semantics (range vectors, aggregate operators,
+//!   label matchers) and emits `UnresolvedOp` / `UnresolvedScalar` nodes with
+//!   unresolved `ColumnRef`s — the same tree shape
+//!   [`resolve_root`](asap_frontend_common::resolve_root) later binds to the
+//!   positional [`OperatorNode`](asap_types::ir::OperatorNode) DAG. The structural decisions a
+//!   separate converter stage would otherwise have to make (heavy-hitter
+//!   `topk` recognition, the `PerEntity`/`Reduce` reduction choice,
+//!   `without(...)` grouping) are made right here, since a front end
+//!   building this shape already knows the answer at parse time — see
+//!   `reduction_for` and `mark_without`. `resolve_root` is left with exactly
+//!   the schema-*dependent* work: binding every `ColumnRef` to its
+//!   positional `ColumnId`.
+//!
+//! # PromQL → canonical unresolved-tree mapping (summary)
+//!
+//! | PromQL | Canonical shape |
+//! |---|---|
+//! | `quantile_over_time(φ, m{f}[w])` | `Aggregate{[Quantile(φ)], TimeRange{w, Scan{predicates}}}` |
+//! | `histogram_quantile(φ, <classic buckets>)` | `Aggregate{without(le), [HistogramQuantile(φ, le)]}` — cumulative-bucket interpolation (classic form recognised by `by (le)` / a `_bucket` metric / an `le` matcher) |
+//! | `histogram_quantile(φ, <native hist / raw>)` | `Aggregate{[Quantile(φ)]}` over the fully-lowered arg (generic, sketch-able with an accuracy target) |
+//! | `histogram_quantiles(v, "l", φ…)` | `Concat{PromqlRelabel{l=φᵢ, <the histogram_quantile(φᵢ, v) branch>}…}` — one branch per φ (issue #109) |
+//! | `histogram_count/sum/avg/stddev/stdvar(v)`, `histogram_fraction(l,u,v)` | `Aggregate{[Histogram*]}` — per-series native-histogram accessors (issue #43) |
+//! | `OUTER_op(inner_func(m[w]))` (e.g. `sum(rate(m[w]))`) | `Aggregate{[OUTER_op]}` over `Aggregate{[inner_func]}` — two levels |
+//! | `OUTER_op(<any expr>)` (e.g. `max(sum by (job) (rate(m[w])))`, `sum(rate(a[w]) + rate(b[w]))`) | `Aggregate{[OUTER_op]}` over the fully-lowered `<any expr>` — arbitrary function nesting (issue #27) |
+//! | `topk(k, <non-count expr>)` / `bottomk(k, <any expr>)` | `Sort{value} → Limit{k}` over the fully-lowered argument |
+//! | `avg/min/max/sum_over_time(m[w])` | `Aggregate{[Avg/Min/Max/Sum], TimeRange{w}}` |
+//! | `stddev/stdvar_over_time(m[w])` | `Aggregate{[StdDev/Variance], TimeRange{w}}` |
+//! | `count_over_time(m[w])` | `Aggregate{[Count], TimeRange{w}}` |
+//! | `last/first/mad/ts_of_min/ts_of_max/ts_of_first/ts_of_last_over_time(m[w])` | `Aggregate{[Last/First/Mad/TsOf…OverTime], TimeRange{w}}` — per-series range reducers (issue #51) |
+//! | `sort`/`sort_desc(v)`, `sort_by_label[_desc](v,"l"…)` | `Sort{value \| label…}` (no `Limit`) — row-preserving reorder (issue #51); `min_of`/`max_of` scalar reducers → #89 |
+//! | `rate(m[w])` / `irate(m[w])` | `Aggregate{[Rate/IRate], TimeRange{w}}` — distinct function identities; shared physical machinery is a later realization choice |
+//! | `increase(m[w])` | `Aggregate{[Increase], TimeRange{w}}` |
+//! | `changes`/`delta`/`idelta`/`deriv`/`resets`/`predict_linear`/`double_exponential_smoothing`(`m[w]`, …) | `Aggregate{[Changes/Delta/…], TimeRange{w}}` — per-series counter-derivative intents (issue #44) |
+//! | `absent(v)` / `absent_over_time(m[w])` / `present_over_time(m[w])` | `Aggregate{[Absent/AbsentOverTime/PresentOverTime]}` — presence intents; the empty→synthesized-sample logic is a post-ASAP concern (issue #47) |
+//! | `abs`/`ceil`/`sqrt`/`ln`/`clamp*`/`round`/trig(`v`), `pi()` | typed scalar `Project` (issue #45); `pi()` → a `ScalarExpr::Literal` root |
+//! | `time()` / `timestamp`/`hour`/`day_of_week`/… (`v`) | `ScalarExpr::EvalTimestamp` root / `Aggregate{[TimeFn(f)]}` (issue #46) |
+//! | `vector(s)` / `scalar(v)` | `PromqlVectorFromScalar(s)` / `ScalarExpr::PromqlScalarFromVector(v)` — the scalar⇄vector bridges (issue #48) |
+//! | `<scalar> op <scalar>` (`time() - 1`, `1 < bool 2`, `-time()`) | `ScalarExpr::{Arithmetic, Case, Negative}` — a scalar expression, never an operator |
+//! | `v op <scalar>`, `a op bool b`, `v > bool 0` | `Project`/`Filter` with owned scalar expressions; vector/vector uses `BinaryOp{return_bool}` |
+//! | `label_replace(v,…)` / `label_join(v,…)` | `PromqlRelabel{dst, value}` — per-series label rewrite; value unchanged (issue #50) |
+//! | `info(v, [selector])` | `PromqlInfoEnrich{selector}` — label-enrichment join against the info metric(s); join keys resolved during post-ASAP binding (issue #84) |
+//! | `group` / `offset` / `@` / `info` | **rejected** — distinct semantics with no intent-algebra representation yet (`info` label-join → #84) |
+//! | `OUTER by (dims) (…)` | `Aggregate.reduction = Reduce(by = dims)` (generic `topk by`/`bottomk` grouping → `Sort.partition_by`) |
+//! | `count by (d) (…)` | `Aggregate{[Count], …}` |
+//! | `group(v)` / `count_values("l", v)` | `Aggregate{[Group]}` (constant 1) / `Aggregate{[CountValues{l}]}` (group-by-value + count, new label `l`) — issue #49 |
+//! | `limitk(k, v)` / `limit_ratio(r, v)` | `PromqlSeriesSample{LimitK(k) \| LimitRatio(r)}` — series-sampling selection, whole series kept unchanged (issue #86) |
+//! | `topk(k, count_over_time(…))` / `topk(k, sum_over_time(…))` | `Aggregate{[TopK{k}]}` (heavy-hitter intent) over the explicit inner `Aggregate{[Count/Sum]}` |
+//! | `topk(k, <other>)` / `bottomk(k, …)` | `Sort{value} → Limit{k}` |
+//! | `m{f}` / `m{f}[w]` | `TimeRange{ingestion, Instant, Scan{predicates}}` / `TimeRange{w, Range, Scan}` |
+//! | `a OP b` | `BinaryOp{vector_match}` |
+//! | `expr[r:res]` | `PromqlSubquery{r, res}` |
+//! | `<selector> offset <d>` / `<selector> @ <ts>`/`start()`/`end()` | `TimeShift{shift}` over the selector's `Scan` — pass-through schema; a ranged selector shifts under its `TimeRange` (issue #40) |
+
+use std::rc::Rc;
+use std::time::{Duration, SystemTime};
+
+use promql_parser::label::{MatchOp, Matcher};
+use promql_parser::parser::value::ValueType;
+use promql_parser::parser::{
+    self, token, AggregateExpr, AtModifier as ParserAtModifier, BinaryExpr, Call, Expr,
+    LabelModifier, Offset, VectorMatchCardinality, VectorSelector,
+};
+
+use asap_frontend_common::{
+    UnresolvedOp as Unresolved, UnresolvedPredicate, UnresolvedScalar as Scalar, UnresolvedSortKey,
+};
+use asap_types::ir::operator_properties::{
+    AtModifier, BinaryOpKind, GroupKeys, GroupSide, PromQLVectorSetOpKind, Reduction, Source,
+    TimeShift, VectorGrouping, VectorMatch, VectorMatchKind,
+};
+use asap_types::ir::{BinaryOperator, ExprSemantics, TimeRangeKind};
+use asap_types::pre_asap::agg_intent::{topk, AggIntent, TimeFunc};
+
+use asap_types::pre_asap::{
+    ArithmeticOpKind, ColumnRef, CompareOpKind, InfoMatcher, SampleKind, ScalarValue,
+};
+use asap_types::types::AccuracyTarget;
+
+/// Every scalar expression this front end builds follows PromQL's numeric rules.
+const PROMQL: ExprSemantics = ExprSemantics::Promql;
+
+use crate::unified::error::PromqlError as LoweringError;
+
+type Result<T> = std::result::Result<T, LoweringError>;
+
+/// Parses and lowers (→ the canonical, unresolved tree) a PromQL query string.
+pub(crate) struct PromqlLowerer;
+
+#[derive(Debug, Clone)]
+enum Outer {
+    None,
+    Plain(OuterIntent),
+    Count,
+    /// `count_values("l", v)` — group by value + count, emitting the value as a
+    /// new label `l` (issue #49).
+    CountValues {
+        label: String,
+    },
+    TopK {
+        k: u64,
+        descending: bool,
+    },
+    /// `limitk`/`limit_ratio` — series-sampling selection (issue #86).
+    Sample {
+        kind: SampleKind,
+    },
+}
+
+#[derive(Debug, Clone)]
+enum OuterIntent {
+    Sum,
+    Avg,
+    Min,
+    Max,
+    StdDev,
+    Variance,
+    Quantile(f64),
+    /// `group(v)` — constant 1 per group (issue #49).
+    Group,
+}
+
+#[derive(Debug, Clone)]
+enum InnerFunc {
+    FrequencyL2,
+    FrequencyEntropy,
+    Cardinality,
+    Quantile(f64),
+    Avg,
+    Min,
+    Max,
+    Sum,
+    StdDev,
+    Variance,
+    Count,
+    // `Rate`/`Increase` carry no window of their own — unlike the old Unresolved
+    // `AggFunc::Rate{window}`, canonical `AggIntent::Rate`/`Increase` have no
+    // window field either; `windowed_aggregate` reads `Inner.window`
+    // uniformly for every intent, so it would be a redundant duplicate here.
+    Rate,
+    IRate,
+    Increase,
+    // Counter-derivative range functions (issue #44). The window rides on the
+    // enclosing `TimeRange` node (like `*_over_time`), so these carry only
+    // their non-window scalar params.
+    Changes,
+    Delta,
+    IDelta,
+    Deriv,
+    Resets,
+    PredictLinear(f64),
+    DoubleExp { smoothing: f64, trend: f64 },
+    // Additional range-vector reducers (issue #51). Per-series over the window
+    // (like `*_over_time`); the window rides on the enclosing Unresolved `Window`.
+    LastOverTime,
+    FirstOverTime,
+    MadOverTime,
+    TsOfMinOverTime,
+    TsOfMaxOverTime,
+    TsOfFirstOverTime,
+    TsOfLastOverTime,
+}
+
+struct Inner {
+    metric: String,
+    matchers: Vec<Scalar>,
+    window: Option<Duration>,
+    func: Option<InnerFunc>,
+    /// `offset` / `@` on the selector, carried to the `Source` (issue #40).
+    shift: TimeShift,
+}
+
+/// Maximum PromQL expression nesting depth the walker accepts. Real queries
+/// nest only a handful deep; this bounds the recursive descent (`walk` and the
+/// mutually-recursive helpers) so a pathologically nested query is rejected
+/// rather than overflowing the stack.
+const MAX_DEPTH: usize = 256;
+
+impl PromqlLowerer {
+    pub(crate) fn lower_query_with_ingestion_interval(
+        query: &str,
+        accuracy: &AccuracyTarget,
+        interval: Duration,
+    ) -> Result<asap_types::ir::QueryRoot> {
+        let _guard = AccuracyGuard::install(accuracy.clone());
+        let _interval = IngestionIntervalGuard::install(interval);
+        let ast = parser::parse(query).map_err(LoweringError::Parse)?;
+        check_depth(&ast, MAX_DEPTH)?;
+        let mut metrics = Vec::new();
+        collect_metric_names(&ast, &mut metrics);
+        if metrics.iter().any(|metric| {
+            crate::unified::histogram::current_kind_of(metric)
+                == Some(crate::unified::histogram::HistogramKind::Native)
+        }) {
+            return Err(LoweringError::UnsupportedFeature(
+                "native histogram samples have no IR representation".into(),
+            ));
+        }
+
+        if ast.value_type() == ValueType::Scalar {
+            Ok(asap_types::ir::QueryRoot::Scalar(
+                asap_frontend_common::resolve_scalar_root(&lower_scalar(&ast)?)?,
+            ))
+        } else {
+            Ok(asap_types::ir::QueryRoot::Operator(
+                asap_frontend_common::resolve_root(&walk(&ast)?)?,
+            ))
+        }
+    }
+}
+
+std::thread_local! {
+    static ACCURACY: std::cell::RefCell<AccuracyTarget> =
+        const { std::cell::RefCell::new(AccuracyTarget::Exact) };
+    static INGESTION_INTERVAL: std::cell::RefCell<Option<Duration>> = const { std::cell::RefCell::new(None) };
+}
+
+/// RAII guard installing `accuracy` as the ambient accuracy target for the
+/// current thread's lowering, restoring the prior value on drop — same shape
+/// as `histogram::CatalogGuard`.
+struct AccuracyGuard(AccuracyTarget);
+
+impl AccuracyGuard {
+    fn install(accuracy: AccuracyTarget) -> Self {
+        let prev = ACCURACY.with(|a| a.replace(accuracy));
+        AccuracyGuard(prev)
+    }
+}
+
+impl Drop for AccuracyGuard {
+    fn drop(&mut self) {
+        ACCURACY.with(|a| *a.borrow_mut() = std::mem::replace(&mut self.0, AccuracyTarget::Exact));
+    }
+}
+
+/// The ambient accuracy target installed by the current [`PromqlLowerer::lower`] call.
+fn current_accuracy() -> AccuracyTarget {
+    ACCURACY.with(|a| a.borrow().clone())
+}
+
+struct IngestionIntervalGuard(Option<Duration>);
+
+impl IngestionIntervalGuard {
+    fn install(interval: Duration) -> Self {
+        Self(INGESTION_INTERVAL.with(|current| current.replace(Some(interval))))
+    }
+}
+
+impl Drop for IngestionIntervalGuard {
+    fn drop(&mut self) {
+        INGESTION_INTERVAL.with(|current| *current.borrow_mut() = self.0.take());
+    }
+}
+
+fn current_ingestion_interval() -> Duration {
+    INGESTION_INTERVAL.with(|current| {
+        current
+            .borrow()
+            .expect("ingestion interval is installed for workload lowering")
+    })
+}
+
+/// Bounded depth check over the parser AST: errors once nesting would exceed
+/// `budget` frames, descending into every child expression.
+fn check_depth(expr: &Expr, budget: usize) -> Result<()> {
+    let Some(budget) = budget.checked_sub(1) else {
+        return Err(LoweringError::UnsupportedFeature(format!(
+            "query nesting exceeds the {MAX_DEPTH}-level limit"
+        )));
+    };
+    match expr {
+        Expr::Aggregate(a) => {
+            check_depth(&a.expr, budget)?;
+            if let Some(p) = &a.param {
+                check_depth(p, budget)?;
+            }
+        }
+        Expr::Unary(u) => check_depth(&u.expr, budget)?,
+        Expr::Binary(b) => {
+            check_depth(&b.lhs, budget)?;
+            check_depth(&b.rhs, budget)?;
+        }
+        Expr::Paren(p) => check_depth(&p.expr, budget)?,
+        Expr::Subquery(s) => check_depth(&s.expr, budget)?,
+        Expr::Call(c) => {
+            for arg in &c.args.args {
+                check_depth(arg, budget)?;
+            }
+        }
+        Expr::MatrixSelector(_)
+        | Expr::VectorSelector(_)
+        | Expr::NumberLiteral(_)
+        | Expr::StringLiteral(_)
+        | Expr::Extension(_) => {}
+    }
+    Ok(())
+}
+
+fn walk(expr: &Expr) -> Result<Unresolved> {
+    // A scalar-typed expression (`5`, `time() - 1`, `scalar(v)`, `1 < bool 2`)
+    // is a scalar expression at an operator position, never an operator tree.
+    if expr.value_type() == ValueType::Scalar {
+        return Err(LoweringError::UnsupportedFeature(
+            "scalar root requires query-root lowering".into(),
+        ));
+    }
+    match expr {
+        Expr::Aggregate(agg) => walk_aggregate(agg),
+        Expr::Call(call) if call.func.name.starts_with("histogram_") => walk_histogram(call),
+        Expr::Call(call) if is_math_fn(call.func.name) => walk_math(call),
+        Expr::Call(call) if is_presence_fn(call.func.name) => walk_presence(call),
+        Expr::Call(call) if is_time_fn(call.func.name) => walk_time(call),
+        Expr::Call(call) if is_typeconv_fn(call.func.name) => walk_typeconv(call),
+        Expr::Call(call) if is_label_fn(call.func.name) => walk_label(call),
+        Expr::Call(call) if is_sort_fn(call.func.name) => walk_sort(call),
+        Expr::Call(call) if call.func.name == "info" => walk_info(call),
+        Expr::Call(call) => walk_call(call),
+        Expr::Binary(bin) => walk_binary(bin),
+        Expr::Paren(p) => walk(&p.expr),
+        // `UnaryExpr` is built only by negation (`Neg`); unary `+` is folded to
+        // identity and `-<literal>` to a negated `NumberLiteral`. A scalar
+        // operand was dispatched to `lower_scalar` above (→ `Negative`), so this
+        // is a vector projection. Unary negation retains the metric name.
+        Expr::Unary(u) => Ok(Unresolved::PromqlMap {
+            child: Rc::new(walk(&u.expr)?),
+            sample: Scalar::Negative {
+                expr: Box::new(Scalar::Column(ColumnRef::SampleValue)),
+                semantics: ExprSemantics::Promql,
+            },
+            drop_metric_name: false,
+        }),
+        Expr::Subquery(sq) => {
+            let subquery = Unresolved::PromqlSubquery {
+                range: sq.range,
+                resolution: sq.step,
+                child: Rc::new(walk(&sq.expr)?),
+            };
+            // `offset`/`@` move the whole subquery, including its step grid.
+            let shift = time_shift(sq.offset.as_ref(), sq.at.as_ref())?;
+            Ok(if shift.is_identity() {
+                subquery
+            } else {
+                Unresolved::TimeShift {
+                    shift,
+                    child: Rc::new(subquery),
+                }
+            })
+        }
+        Expr::VectorSelector(vs) => {
+            let (metric, matchers, shift) = vs_parts(vs)?;
+            Ok(instant_source(metric, matchers, shift))
+        }
+        Expr::MatrixSelector(ms) => {
+            let (metric, matchers, shift) = vs_parts(&ms.vs)?;
+            Ok(Unresolved::TimeRange {
+                range: ms.range,
+                kind: TimeRangeKind::Range,
+                child: Rc::new(filtered_source(metric, matchers, shift)),
+            })
+        }
+        // Scalar-typed, dispatched above; kept for exhaustiveness. String
+        // literals only appear as function args (`label_replace`, …), so a
+        // bare one is rejected (issue #35).
+        Expr::NumberLiteral(_) => unreachable!("scalar handled above"),
+        Expr::StringLiteral(_) => Err(LoweringError::UnsupportedFeature(
+            "bare string literal".into(),
+        )),
+        Expr::Extension(_) => Err(LoweringError::UnsupportedFeature(
+            "extension expression".into(),
+        )),
+    }
+}
+
+/// Lower a scalar-typed PromQL expression to a scalar expression. A constant
+/// sub-expression folds to one `Literal` (as `num_expr` always did); anything
+/// else keeps its structure: `-time()` → `Negative`, `time() - 1` →
+/// `Arithmetic`, `scalar(v)` → `PromqlScalarFromVector`, and a `bool`
+/// comparison → `Case(Compare → 1, else 0)` (PromQL yields `0`/`1`).
+fn lower_scalar(expr: &Expr) -> Result<Scalar> {
+    if let Ok(v) = num_expr(expr) {
+        return Ok(Scalar::Literal(ScalarValue::Float64(v)));
+    }
+    match expr {
+        Expr::Paren(p) => lower_scalar(&p.expr),
+        Expr::Unary(u) => Ok(Scalar::Negative {
+            expr: Box::new(lower_scalar(&u.expr)?),
+            semantics: PROMQL,
+        }),
+        Expr::Binary(bin) => lower_scalar_binary(bin),
+        Expr::Call(call) => match call.func.name {
+            "time" => Ok(Scalar::EvalTimestamp),
+            "pi" => Ok(Scalar::Literal(ScalarValue::Float64(std::f64::consts::PI))),
+            "scalar" => Ok(Scalar::PromqlScalarFromVector(Rc::new(walk(arg(
+                call, 0,
+            )?)?))),
+            // `min_of`/`max_of` fold only over constants (#89); the fold above
+            // failed, so surface its error for the non-constant argument.
+            name if is_scalar_reducer_fn(name) => Err(num_expr(expr).unwrap_err()),
+            other => Err(LoweringError::UnsupportedFunction(other.to_string())),
+        },
+        other => Err(LoweringError::UnsupportedFeature(format!(
+            "scalar expression `{other}`"
+        ))),
+    }
+}
+
+/// `<scalar> op <scalar>`: arithmetic is an `Arithmetic` expression; a
+/// comparison needs the `bool` modifier (PromQL has no scalar filter) and
+/// becomes `Case(Compare → 1.0, else 0.0)`. The parser already rejects both a
+/// bool-less scalar comparison and a scalar set op; both are re-checked here.
+fn lower_scalar_binary(bin: &BinaryExpr) -> Result<Scalar> {
+    let left = Box::new(lower_scalar(&bin.lhs)?);
+    let right = Box::new(lower_scalar(&bin.rhs)?);
+    match binop(bin.op.id())? {
+        BinaryOpKind::Arithmetic(op) => Ok(Scalar::Arithmetic {
+            op,
+            left,
+            right,
+            semantics: PROMQL,
+        }),
+        BinaryOpKind::Compare(op) | BinaryOpKind::CompareBool(op) => {
+            if !bin.return_bool() {
+                return Err(LoweringError::InvalidParameter(
+                    "a comparison between two scalars requires the `bool` modifier".into(),
+                ));
+            }
+            let compare = Scalar::Compare {
+                left,
+                op,
+                right,
+                semantics: PROMQL,
+            };
+            Ok(Scalar::Case {
+                operand: None,
+                branches: vec![(compare, Scalar::Literal(ScalarValue::Float64(1.0)))],
+                else_expr: Some(Box::new(Scalar::Literal(ScalarValue::Float64(0.0)))),
+            })
+        }
+        BinaryOpKind::Set(_) => Err(LoweringError::UnsupportedFeature(
+            "set operator between two scalars".into(),
+        )),
+    }
+}
+
+/// A binary operation over two vectors.
+fn vector_binary(
+    kind: BinaryOpKind,
+    vector_match: Option<VectorMatch>,
+    return_bool: bool,
+    lhs: Unresolved,
+    rhs: Unresolved,
+) -> Unresolved {
+    Unresolved::BinaryOp {
+        operator: BinaryOperator {
+            kind,
+            vector_match,
+            checked_relative_division: false,
+            checked_finite_division: false,
+        },
+        return_bool,
+        lhs: Rc::new(lhs),
+        rhs: Rc::new(rhs),
+    }
+}
+
+/// Lower a bare function call (`rate(m[5m])`, `max_over_time(m[5m])`, …).
+///
+/// The common case routes through the flat `lower_inner_call` template. The one
+/// exception is a `*_over_time`/`quantile_over_time` function applied to a
+/// **sub-query** (`max_over_time(rate(m[5m])[1h:])`): its argument is a
+/// `PromQLSubquery`, not a matrix selector, so the flat template's
+/// `extract_matrix` can't accept it. Lower the sub-query recursively and reduce
+/// it per series (issue #27).
+fn walk_call(call: &Call) -> Result<Unresolved> {
+    if let Some(tree) = range_fn_over_subquery(call)? {
+        return Ok(tree);
+    }
+    build(lower_inner_call(call)?, vec![], Outer::None)
+}
+
+/// A range-vector function applied to a **sub-query** — `f(<inst>[range:res])`.
+///
+/// Covers the whole range-vector family: the `*_over_time` reducers,
+/// `rate`/`irate`/`increase`, and the counter-derivatives
+/// (`changes`/`delta`/`idelta`/`deriv`/`resets`/`predict_linear`/
+/// `double_exponential_smoothing`). Each lowers to a per-series `Aggregate{[f]}`
+/// directly over the `PromqlSubquery` — the sub-query is the range context, so
+/// there is no separate `Window`/`TimeRange` (this walk treats the `PromqlSubquery`
+/// node itself as the range marker). Returns `None` when `call` isn't a range
+/// function or its argument isn't a sub-query, so the flat matrix-selector
+/// template still handles `f(m[w])` (issues #42, #55).
+fn range_fn_over_subquery(call: &Call) -> Result<Option<Unresolved>> {
+    // `rate`/`increase`/`irate` carry their window in the `AggFunc`; over a
+    // sub-query that window is the sub-query's own range.
+    if let "rate" | "irate" | "increase" = call.func.name {
+        let arg_expr = arg(call, 0)?;
+        if subquery_range(arg_expr).is_none() {
+            return Ok(None);
+        }
+        let inner = match call.func.name {
+            "rate" => InnerFunc::Rate,
+            "irate" => InnerFunc::IRate,
+            "increase" => InnerFunc::Increase,
+            _ => unreachable!(),
+        };
+        return Ok(Some(per_series_aggregate(
+            vec![],
+            inner_intent(&inner),
+            walk(arg_expr)?,
+        )));
+    }
+
+    // `*_over_time` reducers + counter-derivatives: the func-kind, and the index
+    // of the matrix/sub-query argument (`quantile_over_time` reads φ from arg 0,
+    // so its matrix is arg 1; the rest take arg 0 + trailing scalar params).
+    let (inner, matrix_idx): (InnerFunc, usize) = match call.func.name {
+        "avg_over_time" => (InnerFunc::Avg, 0),
+        "min_over_time" => (InnerFunc::Min, 0),
+        "max_over_time" => (InnerFunc::Max, 0),
+        "sum_over_time" => (InnerFunc::Sum, 0),
+        "stddev_over_time" => (InnerFunc::StdDev, 0),
+        "stdvar_over_time" => (InnerFunc::Variance, 0),
+        "count_over_time" => (InnerFunc::Count, 0),
+        "distinct_over_time" => (InnerFunc::Cardinality, 0),
+        "entropy_over_time" => (InnerFunc::FrequencyEntropy, 0),
+        "l2_over_time" => (InnerFunc::FrequencyL2, 0),
+        "quantile_over_time" => (InnerFunc::Quantile(quantile_param(num_arg(call, 0)?)?), 1),
+        "changes" => (InnerFunc::Changes, 0),
+        "delta" => (InnerFunc::Delta, 0),
+        "idelta" => (InnerFunc::IDelta, 0),
+        "deriv" => (InnerFunc::Deriv, 0),
+        "resets" => (InnerFunc::Resets, 0),
+        "last_over_time" => (InnerFunc::LastOverTime, 0),
+        "first_over_time" => (InnerFunc::FirstOverTime, 0),
+        "mad_over_time" => (InnerFunc::MadOverTime, 0),
+        "ts_of_min_over_time" => (InnerFunc::TsOfMinOverTime, 0),
+        "ts_of_max_over_time" => (InnerFunc::TsOfMaxOverTime, 0),
+        "ts_of_first_over_time" => (InnerFunc::TsOfFirstOverTime, 0),
+        "ts_of_last_over_time" => (InnerFunc::TsOfLastOverTime, 0),
+        "predict_linear" => (InnerFunc::PredictLinear(num_arg(call, 1)?), 0),
+        "double_exponential_smoothing" => (
+            InnerFunc::DoubleExp {
+                smoothing: num_arg(call, 1)?,
+                trend: num_arg(call, 2)?,
+            },
+            0,
+        ),
+        _ => return Ok(None),
+    };
+    let arg_expr = arg(call, matrix_idx)?;
+    if !is_subquery(arg_expr) {
+        return Ok(None);
+    }
+    Ok(Some(per_series_aggregate(
+        vec![],
+        inner_intent(&inner),
+        walk(arg_expr)?,
+    )))
+}
+
+/// A (parenthesised) PromQL sub-query — `<inst>[range:res]`.
+fn is_subquery(expr: &Expr) -> bool {
+    subquery_range(expr).is_some()
+}
+
+/// The `range` of a (parenthesised) sub-query argument, if it is one.
+fn subquery_range(expr: &Expr) -> Option<Duration> {
+    match expr {
+        Expr::Subquery(sq) => Some(sq.range),
+        Expr::Paren(p) => subquery_range(&p.expr),
+        _ => None,
+    }
+}
+
+fn walk_aggregate(agg: &AggregateExpr) -> Result<Unresolved> {
+    let (keys, without) = resolve_group(agg)?;
+    let outer = outer_kind(agg)?;
+
+    // `without(...)` grouping is modelled only for the reducing aggregations
+    // (sum/avg/count/…), whose grouping lives on an `Aggregate` node. `topk`/
+    // `bottomk` (→ `Sort.partition_by`) and `limitk`/`limit_ratio` (→ `PromqlSeriesSample`)
+    // would need without-partitioning too; reject rather than silently lower
+    // them as a `by` grouping (issue #39).
+    if without && matches!(outer, Outer::TopK { .. } | Outer::Sample { .. }) {
+        return Err(LoweringError::UnsupportedFeature(
+            "`without(...)` is only supported on reducing aggregations, not \
+             topk/bottomk/limitk"
+                .into(),
+        ));
+    }
+
+    // Fast path — the argument is a bare selector or a single range-vector
+    // function (`rate`/`increase`/`*_over_time`). `lower_inner` lowers it via the
+    // flat selector/call template, which also recognises the heavy-hitter
+    // `topk(k, count_over_time(...))` shape. This is the common two-level case
+    // (`sum by (job) (rate(m[5m]))`).
+    //
+    // General nesting — the argument is itself a composite expression: another
+    // aggregate (`max(sum by (job) (rate(m[5m])))`), a binary op, a sub-query, or
+    // a function lowered elsewhere. Lower it recursively with the same `walk`
+    // used at the top level, then wrap it in the outer aggregation (issue #27; a
+    // negated argument `sum(-m)` lowers here too, #36). A genuinely unsupported
+    // inner expression surfaces its own error rather than being mislowered.
+    //
+    // Either way, `mark_without` flips the resulting outer `Aggregate` to the
+    // exclusion form when the modifier was `without(...)`.
+    let built = match lower_inner(&agg.expr) {
+        Ok(inner) => build(inner, keys, outer)?,
+        Err(_) => build_over_sub_dag(outer, keys, walk(&agg.expr)?)?,
+    };
+    Ok(mark_without(built, without))
+}
+
+/// Map an `AggregateExpr`'s operator (`sum`/`avg`/`topk`/…) to the [`Outer`]
+/// shape, independent of what the argument is — so both the flat fast path and
+/// the general recursive path share one operator-dispatch.
+fn outer_kind(agg: &AggregateExpr) -> Result<Outer> {
+    let op = agg.op.id();
+
+    Ok(if op == token::T_TOPK {
+        Outer::TopK {
+            k: count_param(agg)?,
+            descending: true,
+        }
+    } else if op == token::T_BOTTOMK {
+        Outer::TopK {
+            k: count_param(agg)?,
+            descending: false,
+        }
+    } else if op == token::T_COUNT {
+        Outer::Count
+    } else if op == token::T_SUM {
+        Outer::Plain(OuterIntent::Sum)
+    } else if op == token::T_GROUP {
+        // `group(v)` yields a constant 1 per group (presence), not a sum of
+        // values — a distinct intent, never folded onto `Sum` (issue #49).
+        Outer::Plain(OuterIntent::Group)
+    } else if op == token::T_COUNT_VALUES {
+        // `count_values("l", v)` groups by sample value and counts, emitting the
+        // value as a new label `l` (the string parameter) — issue #49.
+        Outer::CountValues {
+            label: str_param(agg)?,
+        }
+    } else if op == token::T_LIMITK {
+        // `limitk(k, v)` — up to k series per group (issue #86).
+        Outer::Sample {
+            kind: SampleKind::LimitK(count_param(agg)? as usize),
+        }
+    } else if op == token::T_LIMIT_RATIO {
+        // `limit_ratio(r, v)` — an r-fraction of series per group (issue #86).
+        Outer::Sample {
+            kind: SampleKind::LimitRatio(ratio_param(agg)?),
+        }
+    } else if op == token::T_AVG {
+        Outer::Plain(OuterIntent::Avg)
+    } else if op == token::T_MIN {
+        Outer::Plain(OuterIntent::Min)
+    } else if op == token::T_MAX {
+        Outer::Plain(OuterIntent::Max)
+    } else if op == token::T_STDDEV {
+        Outer::Plain(OuterIntent::StdDev)
+    } else if op == token::T_STDVAR {
+        Outer::Plain(OuterIntent::Variance)
+    } else if op == token::T_QUANTILE {
+        Outer::Plain(OuterIntent::Quantile(quantile_param(num_param(agg)?)?))
+    } else {
+        return Err(LoweringError::UnsupportedAggregateOp(format!(
+            "aggregate token {op}"
+        )));
+    })
+}
+
+/// Wrap an already-lowered Unresolved sub-DAG in the outer aggregation. This is the
+/// general-nesting counterpart to [`build`]: where `build` assembles the
+/// two-level shape from a flat [`Inner`], this composes the outer operator over
+/// an arbitrary child (`max(sum by (job) (…))`, `sum(a + b)`, …).
+///
+/// A heavy-hitter `TopK` is only recognised on the flat `count_over_time` shape
+/// (handled in `build`); over a general sub-DAG, `topk`/`bottomk` is a generic
+/// order-by-value + limit — the same `Sort{partition_by} → Limit` pair `build`
+/// emits for any non-heavy-hitter ranking.
+/// Flip the outer `Aggregate` produced for a `without(...)` grouping into the
+/// exclusion form. The reducing-aggregation `build` paths place that aggregate
+/// at the root; `walk_aggregate` has already rejected the non-aggregate outers
+/// (topk/limitk), so a `without` grouping always has an `Aggregate` here (issue
+/// #39). A no-op when the modifier was `by`.
+/// Flip the outer `Aggregate` produced for a `without(...)` grouping into the
+/// exclusion form. A no-op when the modifier was `by`.
+///
+/// `reduction_for` (used by [`windowed_aggregate`]/[`outer_aggregate`] to
+/// build this node) decides `PerEntity` vs `Reduce(by)` *without* knowing
+/// about `without` yet — it only ever sees `by`-mode keys, since `without`'s
+/// excluded-labels list is applied here, after the fact, exactly like the
+/// pre-#179 legacy relational tree's own `mark_without` did (its
+/// converter read `without` only after this front-end step had already set
+/// it). Whether
+/// `reduction_for` picked `PerEntity` (only possible when `keys` was empty)
+/// or `Reduce(by)`, the correct answer under `without(...)` is always
+/// `Reduce(without(keys))`: a `without` grouping is never label-preserving —
+/// per-entity requires `!by.is_without()` — so this both re-tags an existing
+/// `Reduce` and upgrades a wrongly-early `PerEntity` guess, uniformly.
+fn mark_without(tree: Unresolved, without: bool) -> Unresolved {
+    if !without {
+        return tree;
+    }
+    match tree {
+        Unresolved::Aggregate {
+            reduction,
+            measures,
+            output_names,
+            filters,
+            having,
+            child,
+        } => {
+            let keys = match reduction {
+                Reduction::Reduce(by) => by.keys().to_vec(),
+                Reduction::PerEntity => vec![],
+            };
+            Unresolved::Aggregate {
+                reduction: Reduction::Reduce(GroupKeys::without(keys)),
+                measures,
+                output_names,
+                filters,
+                having,
+                child,
+            }
+        }
+        other => other,
+    }
+}
+
+fn build_over_sub_dag(outer: Outer, keys: Vec<ColumnRef>, child: Unresolved) -> Result<Unresolved> {
+    Ok(match outer {
+        // `walk_aggregate` always passes a real aggregator; `None` can't occur.
+        Outer::None => child,
+        Outer::Plain(intent) => outer_aggregate(keys, outer_intent(&intent), child),
+        Outer::Count => outer_aggregate(keys, count(), child),
+        Outer::CountValues { label } => {
+            outer_aggregate(keys, AggIntent::CountValues { label }, child)
+        }
+        Outer::Sample { kind } => Unresolved::PromqlSeriesSample {
+            by: keys.into(),
+            kind,
+            child: Rc::new(child),
+        },
+        Outer::TopK { k, descending } => {
+            let weighted_counter_ranking = matches!(
+                &child,
+                Unresolved::Aggregate {
+                    measures,
+                    child: sum_child,
+                    ..
+                } if matches!(measures.as_slice(), [AggIntent::Sum { .. }])
+                    && matches!(sum_child.as_ref(), Unresolved::Aggregate { measures, .. }
+                        if matches!(measures.as_slice(), [AggIntent::Rate | AggIntent::Increase]))
+            );
+            let direct_counter_ranking = matches!(&child, Unresolved::Aggregate {
+                measures, reduction: Reduction::PerEntity, ..
+            } if matches!(measures.as_slice(), [AggIntent::Rate | AggIntent::Increase]));
+            if descending && (weighted_counter_ranking || direct_counter_ranking) {
+                return Ok(outer_aggregate(
+                    keys,
+                    AggIntent::TopK {
+                        k: k as usize,
+                        accuracy: current_accuracy(),
+                    },
+                    child,
+                ));
+            }
+            ranked_by_value(keys, k, descending, child)
+        }
+    })
+}
+
+/// Generic `topk`/`bottomk`: `Limit{k} → Sort{value, partition_by: keys}` over
+/// `child` — an order-by-value ranking, not a heavy-hitter intent.
+fn ranked_by_value(
+    keys: Vec<ColumnRef>,
+    k: u64,
+    descending: bool,
+    child: Unresolved,
+) -> Unresolved {
+    let sorted = Unresolved::Sort {
+        keys: vec![UnresolvedSortKey {
+            expr: Scalar::Column(ColumnRef::SampleValue),
+            ascending: !descending,
+            nulls_first: false,
+        }],
+        partition_by: keys.into(),
+        child: Rc::new(child),
+    };
+    Unresolved::Limit {
+        n: Some(k as usize),
+        offset: 0,
+        partition_by: GroupKeys::none(),
+        child: Rc::new(sorted),
+    }
+}
+
+/// The `histogram_*` function family (issues #43, histogram_quantile).
+///
+/// `histogram_quantile(φ, <expr>)` lowers `<expr>` in full — preserving any
+/// `sum by (le)` / `rate` structure inside it. The classic `le`-bucket form
+/// becomes [`classic_histogram_quantile`]; a native histogram or raw samples
+/// become a `Quantile` over the whole argument.
+/// The native-histogram accessors (`histogram_count`/`sum`/`avg`/`stddev`/
+/// `stdvar`/`fraction`) each extract one float per series, lowering to a
+/// per-series `Aggregate{[accessor]}` directly over the (instant) argument.
+/// `histogram_fraction(lower, upper, v)` reads its bounds from args 0/1 and the
+/// vector from arg 2; the rest take the vector at arg 0.
+fn walk_histogram(call: &Call) -> Result<Unresolved> {
+    if call.func.name == "histogram_quantiles" {
+        return walk_histogram_quantiles(call);
+    }
+    if call.func.name == "histogram_quantile" {
+        let phi = quantile_param(num_arg(call, 0)?)?;
+        let arg_expr = arg(call, 1)?;
+        // Two lowerings of `histogram_quantile(φ, …)`:
+        //  - classic `le`-bucket form → `HistogramQuantile`, exact interpolation
+        //    over cumulative buckets (not sketch-able).
+        //  - native-histogram / raw-samples form → the generic `Quantile` intent
+        //    (sketch-able).
+        // The true signal is the argument's sample type: a declared
+        // `HistogramKind` (issue #79) drives the choice when available, else we
+        // fall back to the structural `by (le)`/`_bucket` heuristic (issue #43).
+        if !histogram_arg_is_sketchable(arg_expr)? {
+            return Ok(classic_histogram_quantile(phi, "", walk(arg_expr)?));
+        }
+        let func = AggIntent::Quantile {
+            col: None,
+            q: phi,
+            accuracy: current_accuracy(),
+        };
+        return Ok(outer_aggregate(vec![], func, walk(arg_expr)?));
+    }
+    Err(LoweringError::UnsupportedFeature(
+        "native histogram samples have no IR representation".into(),
+    ))
+}
+
+/// Classic-bucket `histogram_quantile(φ, child)`. One histogram is the set of
+/// series that differ only in `le`, so the aggregate groups `without (le)`.
+/// That grouping also seeds `le` into a usage-derived source schema, even
+/// when no matcher names it. An empty `output_name` keeps the intent-keyed name.
+fn classic_histogram_quantile(q: f64, output_name: &str, child: Unresolved) -> Unresolved {
+    let le = ColumnRef::Named("le".into());
+    Unresolved::Aggregate {
+        reduction: Reduction::Reduce(GroupKeys::without(vec![le.clone()])),
+        measures: vec![AggIntent::HistogramQuantile { q, le }],
+        output_names: vec![output_name.into()],
+        filters: vec![],
+        having: None,
+        child: Rc::new(child),
+    }
+}
+
+/// `histogram_quantiles(v, "label", φ₀, φ₁, …)` — the experimental multi-quantile
+/// form (issue #109). It is `histogram_quantile(φᵢ, v)` fanned out over the
+/// quantiles, each branch's output series tagged with `label = φᵢ`.
+///
+/// Lowers to a `Concat` of one `PromqlRelabel`-wrapped quantile branch per φ, reusing
+/// the single-quantile decision — classic `le`-buckets interpolate
+/// (`HistogramQuantile`), native histograms / raw samples take the sketch-able
+/// `Quantile` (issues #43 / #79) — so the two functions cannot diverge.
+///
+/// The vector argument is lowered once per branch, duplicating the sub-DAG —
+/// a future workload-level reuse pass could hoist it back into a single
+/// producer.
+///
+/// Each branch aliases its value column to `value` rather than taking the
+/// intent-keyed name (`quantile_0_5`, `quantile_0_9`, …). `Concat` derives its
+/// schema from the first child, so branches that disagree on a column *name*
+/// would make the merged schema silently misdescribe every branch but one. The
+/// quantile is carried by the `label` column, which is exactly where Prometheus
+/// puts it.
+fn walk_histogram_quantiles(call: &Call) -> Result<Unresolved> {
+    let vec_expr = arg(call, 0)?;
+    let label = str_arg(call, 1)?;
+    if call.args.args.len() < 3 {
+        return Err(LoweringError::MissingArgument(
+            "histogram_quantiles(v, label, φ…) needs at least one quantile".into(),
+        ));
+    }
+    // The bucket-vs-native choice is a property of the argument, not of φ.
+    let sketchable = histogram_arg_is_sketchable(vec_expr)?;
+    let branches = (2..call.args.args.len())
+        .map(|i| {
+            let phi = bounded_quantile_param(num_arg(call, i)?)?;
+            let child = walk(vec_expr)?;
+            // Each branch aliases its value column to "value" (not the
+            // intent-keyed default) so `Concat` — which derives its schema
+            // from the first branch — doesn't silently misdescribe the rest.
+            let quantile = if sketchable {
+                let intent = AggIntent::Quantile {
+                    col: None,
+                    q: phi,
+                    accuracy: current_accuracy(),
+                };
+                Unresolved::Aggregate {
+                    reduction: reduction_for(&[], intent.is_per_series()),
+                    measures: vec![intent],
+                    output_names: vec!["value".into()],
+                    filters: vec![],
+                    having: None,
+                    child: Rc::new(child),
+                }
+            } else {
+                classic_histogram_quantile(phi, "value", child)
+            };
+            Ok(Unresolved::PromqlRelabel {
+                dst: label.clone(),
+                value: Scalar::Literal(ScalarValue::Utf8(open_metrics_float(phi))),
+                child: Rc::new(quantile),
+            })
+        })
+        .collect::<Result<Vec<_>>>()?;
+    // No discriminator asserted here today (issue #228): the φ value each
+    // branch carries via `PromqlRelabel` *is* structurally a distinct
+    // per-branch discriminator, but nothing downstream currently needs the
+    // resulting compound unique key — see
+    // `docs/design_docs/concat-unique-keys-decision.md`. `Unresolved::concat`
+    // keeps `output_schema`'s default (drop `unique_keys` entirely).
+    Ok(Unresolved::concat(branches))
+}
+
+/// Prometheus's `labels.FormatOpenMetricsFloat` — how `histogram_quantiles`
+/// renders each φ into its label value. Go's `%g` shortest round-trip, switching
+/// to exponent form outside `[1e-4, 1e21)`, with `.0` appended when the result
+/// would otherwise look like an integer.
+fn open_metrics_float(v: f64) -> String {
+    // The cases upstream hardcodes.
+    if v == 1.0 {
+        return "1.0".into();
+    }
+    if v == 0.0 {
+        return "0.0".into();
+    }
+    if v == -1.0 {
+        return "-1.0".into();
+    }
+    if v.is_nan() {
+        return "NaN".into();
+    }
+    if v.is_infinite() {
+        return if v.is_sign_positive() { "+Inf" } else { "-Inf" }.into();
+    }
+    let sci = format!("{v:e}");
+    let exp: i32 = sci
+        .split_once('e')
+        .and_then(|(_, e)| e.parse().ok())
+        .unwrap_or(0);
+    if !(-4..21).contains(&exp) {
+        // Go writes a signed, zero-padded two-digit exponent: `1e-05`.
+        let (mantissa, _) = sci.split_once('e').unwrap_or((sci.as_str(), "0"));
+        let sign = if exp < 0 { '-' } else { '+' };
+        return format!("{mantissa}e{sign}{:02}", exp.abs());
+    }
+    let s = format!("{v}");
+    if s.contains(['e', '.']) {
+        s
+    } else {
+        format!("{s}.0")
+    }
+}
+
+/// The calendar functions (issue #46); `time()` is scalar-typed and lowers in
+/// `lower_scalar`.
+fn is_time_fn(name: &str) -> bool {
+    matches!(
+        name,
+        "timestamp"
+            | "minute"
+            | "hour"
+            | "day_of_week"
+            | "day_of_month"
+            | "day_of_year"
+            | "month"
+            | "year"
+            | "days_in_month"
+    )
+}
+
+/// `timestamp(v)` and the calendar accessors → `Aggregate{[TimeFn(f)]}` over
+/// the argument vector, or over `PromqlVectorFromScalar(EvalTimestamp)` for the
+/// no-argument calendar forms (`hour()`, `day_of_week()`, …). Issue #46.
+fn walk_time(call: &Call) -> Result<Unresolved> {
+    // timestamp() reads the selected sample's timestamp, not its value.
+    if call.func.name == "timestamp" {
+        return Ok(outer_aggregate(
+            vec![],
+            AggIntent::TimeFn(TimeFunc::Timestamp),
+            walk(arg(call, 0)?)?,
+        ));
+    }
+    let child = if call.args.args.is_empty() {
+        Unresolved::PromqlVectorFromScalar(Scalar::EvalTimestamp)
+    } else {
+        walk(arg(call, 0)?)?
+    };
+    Ok(Unresolved::PromqlMap {
+        child: Rc::new(child),
+        sample: Scalar::FunctionCall {
+            name: format!("promql_{}", call.func.name),
+            args: vec![Scalar::Column(ColumnRef::SampleValue)],
+        },
+        drop_metric_name: true,
+    })
+}
+
+/// The presence functions (issue #47).
+fn is_presence_fn(name: &str) -> bool {
+    matches!(name, "absent" | "absent_over_time" | "present_over_time")
+}
+
+/// `absent(v)` / `absent_over_time(m[w])` / `present_over_time(m[w])` — lowered
+/// to an `Aggregate{[Absent/…]}` over the (instant or range) argument. The
+/// empty-result → synthesized-1-sample logic is a post-ASAP/runtime concern;
+/// the canonical tree only marks the operation (issue #47).
+fn walk_presence(call: &Call) -> Result<Unresolved> {
+    let func = match call.func.name {
+        "absent" => AggIntent::Absent,
+        "absent_over_time" => AggIntent::AbsentOverTime,
+        "present_over_time" => AggIntent::PresentOverTime,
+        other => return Err(LoweringError::UnsupportedFunction(other.to_string())),
+    };
+    // arg 0 is the instant vector (`absent`) or range vector (`*_over_time`);
+    // `walk` produces a `Window` for the matrix-selector forms.
+    Ok(outer_aggregate(vec![], func, walk(arg(call, 0)?)?))
+}
+
+/// The scalar→vector conversion (issue #48); `scalar(v)` is scalar-typed and
+/// lowers in `lower_scalar`. `info` is *not* here: it is a label-enrichment
+/// join, not a type conversion (#84).
+fn is_typeconv_fn(name: &str) -> bool {
+    name == "vector"
+}
+
+/// `vector(s)` — promote a scalar to a label-less instant vector carrying the
+/// scalar expression `s` (issue #48).
+fn walk_typeconv(call: &Call) -> Result<Unresolved> {
+    Ok(Unresolved::PromqlVectorFromScalar(lower_scalar(arg(
+        call, 0,
+    )?)?))
+}
+
+/// The instant-vector reordering functions (issue #51).
+fn is_sort_fn(name: &str) -> bool {
+    matches!(
+        name,
+        "sort" | "sort_desc" | "sort_by_label" | "sort_by_label_desc"
+    )
+}
+
+/// `sort`/`sort_desc(v)` reorder an instant vector by sample value;
+/// `sort_by_label`/`sort_by_label_desc(v, "l"…)` reorder by label values. All
+/// lower to a bare `Sort` (no `Limit`) over the vector argument — a faithful,
+/// row-preserving reordering (issue #51).
+fn walk_sort(call: &Call) -> Result<Unresolved> {
+    let child = Rc::new(walk(arg(call, 0)?)?);
+    let (by_value, ascending) = match call.func.name {
+        "sort" => (true, true),
+        "sort_desc" => (true, false),
+        "sort_by_label" => (false, true),
+        "sort_by_label_desc" => (false, false),
+        other => return Err(LoweringError::UnsupportedFunction(other.to_string())),
+    };
+    let sort_key = |expr| UnresolvedSortKey {
+        expr,
+        ascending,
+        nulls_first: false,
+    };
+    let keys = if by_value {
+        vec![sort_key(Scalar::Column(ColumnRef::SampleValue))]
+    } else {
+        // `sort_by_label(v, "l1", "l2", …)` — one key per label arg, in order.
+        if call.args.args.len() < 2 {
+            return Err(LoweringError::MissingArgument(
+                "sort_by_label needs at least one label".into(),
+            ));
+        }
+        (1..call.args.args.len())
+            .map(|i| {
+                Ok(sort_key(Scalar::Column(ColumnRef::Named(str_arg(
+                    call, i,
+                )?))))
+            })
+            .collect::<Result<Vec<_>>>()?
+    };
+    Ok(Unresolved::Sort {
+        keys,
+        partition_by: GroupKeys::none(),
+        child,
+    })
+}
+
+/// `info(v, [selector])` — a label-enrichment join. Lowers the input vector and
+/// wraps it in an `PromqlInfoEnrich` carrying the (optional) data-label selector's
+/// matchers; the actual join against the info metric — on shared identifying
+/// labels — is resolved during post-ASAP binding (issue #84).
+fn walk_info(call: &Call) -> Result<Unresolved> {
+    let child = Rc::new(walk(arg(call, 0)?)?);
+    let selector = match call.args.args.get(1) {
+        Some(sel) => info_selector(sel)?,
+        None => Vec::new(), // default: enrich from `target_info`
+    };
+    Ok(Unresolved::PromqlInfoEnrich { selector, child })
+}
+
+/// Extract the `info` data-label selector's matchers. Unlike an ordinary
+/// selector these are **info-metric-side** and may carry regex / multiple
+/// `__name__` matchers (which pick the info metric(s)), so they bypass the
+/// single-metric `vs_parts` restriction and are kept symbolic.
+fn info_selector(expr: &Expr) -> Result<Vec<InfoMatcher>> {
+    match expr {
+        Expr::VectorSelector(vs) => Ok(vs
+            .matchers
+            .matchers
+            .iter()
+            .map(|m| InfoMatcher {
+                label: m.name.clone(),
+                op: match &m.op {
+                    MatchOp::Equal => CompareOpKind::Eq,
+                    MatchOp::NotEqual => CompareOpKind::Ne,
+                    MatchOp::Re(_) => CompareOpKind::Regex,
+                    MatchOp::NotRe(_) => CompareOpKind::NotRegex,
+                },
+                value: m.value.clone(),
+            })
+            .collect()),
+        Expr::Paren(p) => info_selector(&p.expr),
+        other => Err(LoweringError::UnsupportedFeature(format!(
+            "`info` data-label selector must be a label-matcher set, got `{other}`"
+        ))),
+    }
+}
+
+/// The label-rewrite functions (issue #50).
+fn is_label_fn(name: &str) -> bool {
+    matches!(name, "label_replace" | "label_join")
+}
+
+/// `label_replace(v, dst, replacement, src, regex)` /
+/// `label_join(v, dst, sep, src…)` — per-series label rewrites. Both lower to a
+/// `PromqlRelabel` over the fully-lowered vector argument, differing only in the
+/// expression that computes the destination label: `label_replace` a regex
+/// capture-expansion, `label_join` a separator-joined concatenation. Sample
+/// values are untouched; the regex-match-or-passthrough and capture-expansion
+/// are post-ASAP/runtime concerns (issue #50).
+fn walk_label(call: &Call) -> Result<Unresolved> {
+    let child = Rc::new(walk(arg(call, 0)?)?);
+    match call.func.name {
+        "label_replace" => {
+            let dst = str_arg(call, 1)?;
+            let replacement = str_arg(call, 2)?;
+            let src = str_arg(call, 3)?;
+            let regex = str_arg(call, 4)?;
+            let value = Scalar::FunctionCall {
+                name: "label_replace".into(),
+                args: vec![
+                    Scalar::Column(ColumnRef::Named(src)),
+                    Scalar::Literal(ScalarValue::Utf8(regex)),
+                    Scalar::Literal(ScalarValue::Utf8(replacement)),
+                ],
+            };
+            Ok(Unresolved::PromqlRelabel { dst, value, child })
+        }
+        "label_join" => {
+            // label_join(v, dst, sep, src_1, …, src_n) — needs ≥1 source label.
+            if call.args.args.len() < 4 {
+                return Err(LoweringError::MissingArgument(
+                    "label_join(v, dst, sep, src…) needs at least one source label".into(),
+                ));
+            }
+            let dst = str_arg(call, 1)?;
+            let sep = str_arg(call, 2)?;
+            let mut args = vec![Scalar::Literal(ScalarValue::Utf8(sep))];
+            for i in 3..call.args.args.len() {
+                args.push(Scalar::Column(ColumnRef::Named(str_arg(call, i)?)));
+            }
+            let value = Scalar::FunctionCall {
+                name: "label_join".into(),
+                args,
+            };
+            Ok(Unresolved::PromqlRelabel { dst, value, child })
+        }
+        other => Err(LoweringError::UnsupportedFunction(other.to_string())),
+    }
+}
+
+/// The element-wise math / trig functions (issue #45).
+fn is_math_fn(name: &str) -> bool {
+    matches!(
+        name,
+        "abs"
+            | "ceil"
+            | "floor"
+            | "exp"
+            | "ln"
+            | "log2"
+            | "log10"
+            | "sqrt"
+            | "sgn"
+            | "sin"
+            | "cos"
+            | "tan"
+            | "asin"
+            | "acos"
+            | "atan"
+            | "sinh"
+            | "cosh"
+            | "tanh"
+            | "asinh"
+            | "acosh"
+            | "atanh"
+            | "deg"
+            | "rad"
+            | "round"
+            | "clamp"
+            | "clamp_min"
+            | "clamp_max"
+    )
+}
+
+/// A math / trig function — a per-series element-wise value transform, lowered
+/// to a typed scalar projection over the instant-vector argument.
+/// `pi()` is scalar-typed and lowers in `lower_scalar` (issue #45).
+fn walk_math(call: &Call) -> Result<Unresolved> {
+    let mut args = vec![Scalar::Column(ColumnRef::SampleValue)];
+    for index in 1..call.args.args.len() {
+        args.push(lower_scalar(arg(call, index)?)?);
+    }
+    if call.func.name == "round" && args.len() == 1 {
+        args.push(Scalar::Literal(ScalarValue::Float64(1.0)));
+    }
+    Ok(Unresolved::PromqlMap {
+        child: Rc::new(walk(arg(call, 0)?)?),
+        sample: Scalar::FunctionCall {
+            name: format!("promql_{}", call.func.name),
+            args,
+        },
+        drop_metric_name: true,
+    })
+}
+
+/// Whether `expr` is a **classic cumulative-bucket** `histogram_quantile`
+/// argument — as opposed to a native histogram or raw samples. Recognised
+/// structurally, by any of:
+///  - a `by (le)` grouping (`sum by (le) (…)`),
+///  - a selector on a classic `_bucket` metric (`http_request_…_bucket`),
+///  - a selector with an `le` label matcher (`{le="…"}`).
+///
+/// The bucket form must be *interpolated* (`HistogramQuantile`); everything
+/// else is a sketch-able generic `Quantile`. This is a heuristic proxy for the
+/// real signal — the argument's sample type — which isn't visible at lowering;
+/// see the follow-up issue on the discrimination criteria (issue #43).
+/// Whether `histogram_quantile(φ, arg)` lowers to the sketch-able generic
+/// `Quantile` (`true`) or exact classic-bucket interpolation (`false`).
+///
+/// Metadata wins: if any metric referenced in `arg` has a declared
+/// [`HistogramKind`](crate::unified::histogram::HistogramKind), that decides it (issue
+/// #79) — this fixes both the false-positive (a `…_bucket`-named non-histogram
+/// declared `RawSamples`) and the false-negative (a suffix-less classic
+/// histogram declared `ClassicBucket`) of the structural heuristic. With no
+/// declaration, fall back to the structural `by (le)`/`_bucket` heuristic.
+fn histogram_arg_is_sketchable(arg: &Expr) -> Result<bool> {
+    let mut metrics = Vec::new();
+    collect_metric_names(arg, &mut metrics);
+    let kinds = metrics
+        .iter()
+        .filter_map(|metric| crate::unified::histogram::current_kind_of(metric))
+        .collect::<Vec<_>>();
+    if kinds.contains(&crate::unified::histogram::HistogramKind::Native) {
+        return Err(LoweringError::UnsupportedFeature(
+            "native histogram samples have no IR representation".into(),
+        ));
+    }
+    if let Some(kind) = kinds.first() {
+        if kinds.iter().any(|other| other != kind) {
+            return Err(LoweringError::UnsupportedFeature(
+                "mixed histogram sample contracts".into(),
+            ));
+        }
+        return Ok(kind.is_sketchable());
+    }
+    if is_classic_bucket_arg(arg) {
+        Ok(false)
+    } else {
+        Err(LoweringError::UnsupportedFeature("histogram_quantile requires classic buckets; use quantile for float samples or explicitly declare the RawSamples extension".into()))
+    }
+}
+
+/// Collect the metric names of every vector/matrix selector reachable in `expr`
+/// (for the metadata lookup in [`histogram_arg_is_sketchable`]). Skips
+/// name-less selectors like `{le="…"}`.
+fn collect_metric_names(expr: &Expr, out: &mut Vec<String>) {
+    match expr {
+        Expr::VectorSelector(vs) => {
+            if let Ok((metric, ..)) = vs_parts(vs) {
+                if !metric.is_empty() {
+                    out.push(metric);
+                }
+            }
+        }
+        Expr::MatrixSelector(ms) => {
+            if let Ok((metric, ..)) = vs_parts(&ms.vs) {
+                if !metric.is_empty() {
+                    out.push(metric);
+                }
+            }
+        }
+        Expr::Paren(p) => collect_metric_names(&p.expr, out),
+        Expr::Unary(u) => collect_metric_names(&u.expr, out),
+        Expr::Subquery(s) => collect_metric_names(&s.expr, out),
+        Expr::Aggregate(a) => collect_metric_names(&a.expr, out),
+        Expr::Binary(b) => {
+            collect_metric_names(&b.lhs, out);
+            collect_metric_names(&b.rhs, out);
+        }
+        Expr::Call(c) => c
+            .args
+            .args
+            .iter()
+            .for_each(|a| collect_metric_names(a, out)),
+        _ => {}
+    }
+}
+
+fn is_classic_bucket_arg(expr: &Expr) -> bool {
+    match expr {
+        Expr::Paren(p) => is_classic_bucket_arg(&p.expr),
+        Expr::Unary(u) => is_classic_bucket_arg(&u.expr),
+        Expr::Subquery(s) => is_classic_bucket_arg(&s.expr),
+        Expr::Aggregate(agg) => {
+            matches!(
+                &agg.modifier,
+                Some(LabelModifier::Include(ls)) if ls.labels.iter().any(|l| l == "le")
+            ) || is_classic_bucket_arg(&agg.expr)
+        }
+        Expr::Binary(b) => is_classic_bucket_arg(&b.lhs) || is_classic_bucket_arg(&b.rhs),
+        Expr::Call(c) => c.args.args.iter().any(|a| is_classic_bucket_arg(a)),
+        Expr::VectorSelector(vs) => selector_is_bucket(vs),
+        Expr::MatrixSelector(ms) => selector_is_bucket(&ms.vs),
+        _ => false,
+    }
+}
+
+/// A classic histogram bucket selector — a `_bucket`-named metric (via bare name
+/// or `__name__` matcher) or an explicit `le` label matcher.
+fn selector_is_bucket(vs: &VectorSelector) -> bool {
+    let name = vs.name.as_deref().or_else(|| {
+        vs.matchers
+            .matchers
+            .iter()
+            .find(|m| m.name == "__name__")
+            .map(|m| m.value.as_str())
+    });
+    name.is_some_and(|n| n.ends_with("_bucket"))
+        || vs.matchers.matchers.iter().any(|m| m.name == "le")
+}
+
+/// A binary op with at least one vector operand (a scalar/scalar op is
+/// scalar-typed and never reaches here). A scalar side lowers to a
+/// scalar expression; mixed operations resolve to Project or Filter.
+fn walk_binary(bin: &BinaryExpr) -> Result<Unresolved> {
+    let op = binop(bin.op.id())?;
+    let scalar_left = bin.lhs.value_type() == ValueType::Scalar;
+    if scalar_left || bin.rhs.value_type() == ValueType::Scalar {
+        let (scalar, vector) = if scalar_left {
+            (&bin.lhs, &bin.rhs)
+        } else {
+            (&bin.rhs, &bin.lhs)
+        };
+        return Ok(Unresolved::PromqlScalarOp {
+            child: Rc::new(walk(vector)?),
+            scalar: lower_scalar(scalar)?,
+            op,
+            scalar_left,
+            return_bool: bin.return_bool(),
+        });
+    }
+    let lhs = walk(&bin.lhs)?;
+    let rhs = walk(&bin.rhs)?;
+    // `VectorMatch` has no fill field; dropping fill would change which series
+    // are emitted and their values, so the query must fall back to exact
+    // execution instead.
+    if let Some(m) = &bin.modifier {
+        if m.fill_values.lhs.is_some() || m.fill_values.rhs.is_some() {
+            return Err(LoweringError::UnsupportedFeature(format!(
+                "`fill` vector-matching modifier: `{bin}`"
+            )));
+        }
+    }
+    let vector_match = bin.modifier.as_ref().map(|m| {
+        let (kind, labels) = match &m.matching {
+            Some(LabelModifier::Include(ls)) => (VectorMatchKind::On, ls.labels.clone()),
+            Some(LabelModifier::Exclude(ls)) => (VectorMatchKind::Ignoring, ls.labels.clone()),
+            // No explicit `on(…)`/`ignoring(…)` — the parser attaches a default
+            // modifier to every set op (`and`/`or`/`unless`). The default is
+            // "match on all shared labels", which is exactly `ignoring([])`
+            // (ignore no labels). Representing it as `Ignoring([])` — not
+            // `On([])` — keeps it distinct from an explicit `on()` (match on the
+            // empty label set) while making it correctly equal to an explicit
+            // `ignoring()` (issue #68).
+            None => (VectorMatchKind::Ignoring, vec![]),
+        };
+        let grouping = match &m.card {
+            VectorMatchCardinality::ManyToOne(ls) => Some(VectorGrouping {
+                side: GroupSide::Left,
+                labels: ls.labels.clone(),
+            }),
+            VectorMatchCardinality::OneToMany(ls) => Some(VectorGrouping {
+                side: GroupSide::Right,
+                labels: ls.labels.clone(),
+            }),
+            _ => None,
+        };
+        VectorMatch {
+            kind,
+            labels,
+            grouping,
+        }
+    });
+    Ok(vector_binary(op, vector_match, bin.return_bool(), lhs, rhs))
+}
+
+fn lower_inner(expr: &Expr) -> Result<Inner> {
+    match expr {
+        Expr::VectorSelector(vs) => {
+            let (metric, matchers, shift) = vs_parts(vs)?;
+            Ok(Inner {
+                metric,
+                matchers,
+                window: None,
+                func: None,
+                shift,
+            })
+        }
+        Expr::MatrixSelector(ms) => {
+            let (metric, matchers, shift) = vs_parts(&ms.vs)?;
+            Ok(Inner {
+                metric,
+                matchers,
+                window: Some(ms.range),
+                func: None,
+                shift,
+            })
+        }
+        Expr::Paren(p) => lower_inner(&p.expr),
+        Expr::Call(call) => lower_inner_call(call),
+        other => Err(LoweringError::UnsupportedFeature(format!(
+            "aggregate argument: `{other}`"
+        ))),
+    }
+}
+
+fn lower_inner_call(call: &Call) -> Result<Inner> {
+    let name = call.func.name;
+    let at0 = |func: InnerFunc| -> Result<Inner> {
+        let (metric, matchers, window, shift) = extract_matrix(arg(call, 0)?)?;
+        Ok(Inner {
+            metric,
+            matchers,
+            window: Some(window),
+            func: Some(func),
+            shift,
+        })
+    };
+    match name {
+        "rate" | "irate" => {
+            let (metric, matchers, window, shift) = extract_matrix(arg(call, 0)?)?;
+            Ok(Inner {
+                metric,
+                matchers,
+                window: Some(window),
+                func: Some(if name == "irate" {
+                    InnerFunc::IRate
+                } else {
+                    InnerFunc::Rate
+                }),
+                shift,
+            })
+        }
+        "increase" => {
+            let (metric, matchers, window, shift) = extract_matrix(arg(call, 0)?)?;
+            Ok(Inner {
+                metric,
+                matchers,
+                window: Some(window),
+                func: Some(InnerFunc::Increase),
+                shift,
+            })
+        }
+        "quantile_over_time" => {
+            let phi = quantile_param(num_arg(call, 0)?)?;
+            let (metric, matchers, window, shift) = extract_matrix(arg(call, 1)?)?;
+            Ok(Inner {
+                metric,
+                matchers,
+                window: Some(window),
+                func: Some(InnerFunc::Quantile(phi)),
+                shift,
+            })
+        }
+        "avg_over_time" => at0(InnerFunc::Avg),
+        "min_over_time" => at0(InnerFunc::Min),
+        "max_over_time" => at0(InnerFunc::Max),
+        "sum_over_time" => at0(InnerFunc::Sum),
+        "stddev_over_time" => at0(InnerFunc::StdDev),
+        "stdvar_over_time" => at0(InnerFunc::Variance),
+        "count_over_time" => at0(InnerFunc::Count),
+        "distinct_over_time" => at0(InnerFunc::Cardinality),
+        "entropy_over_time" => at0(InnerFunc::FrequencyEntropy),
+        "l2_over_time" => at0(InnerFunc::FrequencyL2),
+        // Counter-derivative range functions (issue #44). Each has its own
+        // intent — `changes` (value-change count) and `resets` (counter-reset
+        // count) are NOT sample counts, so they are not aliased to
+        // `count_over_time`. The window is arg 0's matrix; scalar params follow.
+        "changes" => at0(InnerFunc::Changes),
+        "delta" => at0(InnerFunc::Delta),
+        "idelta" => at0(InnerFunc::IDelta),
+        "deriv" => at0(InnerFunc::Deriv),
+        "resets" => at0(InnerFunc::Resets),
+        // Additional range-vector reducers (issue #51) — same windowed
+        // per-series shape as the `*_over_time` family above.
+        "last_over_time" => at0(InnerFunc::LastOverTime),
+        "first_over_time" => at0(InnerFunc::FirstOverTime),
+        "mad_over_time" => at0(InnerFunc::MadOverTime),
+        "ts_of_min_over_time" => at0(InnerFunc::TsOfMinOverTime),
+        "ts_of_max_over_time" => at0(InnerFunc::TsOfMaxOverTime),
+        "ts_of_first_over_time" => at0(InnerFunc::TsOfFirstOverTime),
+        "ts_of_last_over_time" => at0(InnerFunc::TsOfLastOverTime),
+        "predict_linear" => {
+            let (metric, matchers, window, shift) = extract_matrix(arg(call, 0)?)?;
+            let seconds = num_arg(call, 1)?;
+            Ok(Inner {
+                metric,
+                matchers,
+                window: Some(window),
+                func: Some(InnerFunc::PredictLinear(seconds)),
+                shift,
+            })
+        }
+        "double_exponential_smoothing" => {
+            let (metric, matchers, window, shift) = extract_matrix(arg(call, 0)?)?;
+            let smoothing = num_arg(call, 1)?;
+            let trend = num_arg(call, 2)?;
+            Ok(Inner {
+                metric,
+                matchers,
+                window: Some(window),
+                func: Some(InnerFunc::DoubleExp { smoothing, trend }),
+                shift,
+            })
+        }
+        other => Err(LoweringError::UnsupportedFunction(other.to_string())),
+    }
+}
+
+/// Assemble the Layer-2 tree from a lowered inner vector, the resolved group
+/// keys, and the enclosing aggregator shape.
+fn build(inner: Inner, keys: Vec<ColumnRef>, outer: Outer) -> Result<Unresolved> {
+    match outer {
+        Outer::None => match &inner.func {
+            None => Ok(instant_source(inner.metric, inner.matchers, inner.shift)),
+            Some(f) => {
+                let intent = inner_intent(f);
+                Ok(windowed_aggregate(inner, keys, intent))
+            }
+        },
+        // An OUTER aggregation operator (`sum`/`avg`/…/`count`) over an inner
+        // range-vector function (`rate`/`increase`/`*_over_time`) is a
+        // two-level reduction: the inner func runs per series, the outer op
+        // then aggregates across series. Collapsing them into one aggregate
+        // silently drops a level — e.g. `sum(rate(m[w]))` must keep the `sum`.
+        Outer::Plain(intent) => Ok(match &inner.func {
+            None => windowed_aggregate(inner, keys, outer_intent(&intent)),
+            Some(f) => {
+                let inner_i = inner_intent(f);
+                let inner_agg = windowed_aggregate(inner, vec![], inner_i);
+                outer_aggregate(keys, outer_intent(&intent), inner_agg)
+            }
+        }),
+        Outer::Count => Ok(match &inner.func {
+            None => windowed_aggregate(inner, keys, count()),
+            Some(f) => {
+                let inner_i = inner_intent(f);
+                let inner_agg = windowed_aggregate(inner, vec![], inner_i);
+                outer_aggregate(keys, count(), inner_agg)
+            }
+        }),
+        Outer::CountValues { label } => Ok(match &inner.func {
+            None => windowed_aggregate(inner, keys, AggIntent::CountValues { label }),
+            Some(f) => {
+                let inner_i = inner_intent(f);
+                let inner_agg = windowed_aggregate(inner, vec![], inner_i);
+                outer_aggregate(keys, AggIntent::CountValues { label }, inner_agg)
+            }
+        }),
+        Outer::Sample { kind } => {
+            // Series sampling selects whole series unchanged — like generic
+            // `topk`, a range-vector argument reduces per series first (label-
+            // preserving), a bare selector is sampled directly; neither is
+            // wrapped in a reducing aggregate (issue #86).
+            let base = match inner.func.as_ref().map(inner_intent) {
+                Some(intent) => windowed_aggregate(inner, vec![], intent),
+                None => instant_source(inner.metric, inner.matchers, inner.shift),
+            };
+            Ok(Unresolved::PromqlSeriesSample {
+                by: keys.into(),
+                kind,
+                child: Rc::new(base),
+            })
+        }
+        Outer::TopK { k, descending } => {
+            // Preserve the counter-value ranking intent. Physical candidates
+            // may rebuild a heap over finalized rates or use exact Sort/Limit;
+            // neither is allowed to sum raw counter samples as ranking weights.
+            if descending && matches!(inner.func, Some(InnerFunc::Rate | InnerFunc::Increase)) {
+                let intent = inner_intent(inner.func.as_ref().expect("counter function"));
+                let ranked = windowed_aggregate(inner, vec![], intent);
+                return Ok(Unresolved::Aggregate {
+                    reduction: Reduction::Reduce(keys.into()),
+                    measures: vec![AggIntent::TopK {
+                        k: k as usize,
+                        accuracy: current_accuracy(),
+                    }],
+                    output_names: vec![],
+                    filters: vec![],
+                    having: None,
+                    child: Rc::new(ranked),
+                });
+            }
+            // Heavy-hitter only when ranking by an additive measure (`count`
+            // or `sum`): that is a
+            // first-class aggregate intent → `TopK`. Any other ranking (topk
+            // over avg/quantile, a bare selector's raw value, all bottomk)
+            // is a generic order-by-value + limit and stays as the `Sort + Limit`
+            // operator pair. The descending-plus-measure rule is shared with the
+            // canonicalize-pass promotion so the two cannot drift (issue #38).
+            let measure = match inner.func {
+                Some(InnerFunc::Count) => topk::Ranking::Frequency,
+                Some(InnerFunc::Sum) => topk::Ranking::WeightedSum,
+                _ => topk::Ranking::NonAdditive,
+            };
+            let additive_ranking = measure.is_supported(descending);
+            if additive_ranking {
+                // Preserve the ranked aggregate intent in the canonical tree so the
+                // intent algebra is explicit about what is being computed.
+                // Post-ASAP binding may fuse the Count and TopK into a
+                // single-pass heavy-hitter sketch (SpaceSaving /
+                // CMS-with-heap), but that is a cost-model decision, not a
+                // canonical-IR concern.
+                let ranked = match measure {
+                    topk::Ranking::Frequency => InnerFunc::Count,
+                    topk::Ranking::WeightedSum => InnerFunc::Sum,
+                    topk::Ranking::NonAdditive => {
+                        unreachable!("heavy-hitter gate rejected non-additive ranking")
+                    }
+                };
+                let ranked_agg = windowed_aggregate(inner, vec![], inner_intent(&ranked));
+                Ok(Unresolved::Aggregate {
+                    // A ranking always reduces (a `by`-empty TopK ranks the
+                    // whole input into one ordering, never per-entity).
+                    reduction: Reduction::Reduce(keys.into()),
+                    measures: vec![AggIntent::TopK {
+                        k: k as usize,
+                        accuracy: current_accuracy(),
+                    }],
+                    output_names: vec![],
+                    filters: vec![],
+                    having: None,
+                    child: Rc::new(ranked_agg),
+                })
+            } else {
+                // The base over which we rank. A range-vector-function argument
+                // (`topk(k, rate(m[5m]))`) reduces *per series* first — that is
+                // label-preserving, so the `by (host)` partition labels survive.
+                // A **bare instant selector** (`topk(k, m)`) ranks its own
+                // samples directly: it must NOT be wrapped in a reducing
+                // aggregate. Defaulting it to `Sum` was both semantically wrong
+                // (PromQL `topk` ranks the raw samples, it does not sum them) and
+                // destructive — the cross-series `Sum` collapses every label,
+                // including the `by (…)` partition keys, so they no longer
+                // resolve (issue #30). Keep the selector label-preserving so
+                // `Sort.partition_by` can rank within each group (issue #12).
+                let base = match inner.func.as_ref().map(inner_intent) {
+                    Some(intent) => windowed_aggregate(inner, vec![], intent),
+                    None => instant_source(inner.metric, inner.matchers, inner.shift),
+                };
+                Ok(ranked_by_value(keys, k, descending, base))
+            }
+        }
+    }
+}
+
+/// Decide `PerEntity` vs `Reduce(by)` for a canonical `Aggregate`, entirely
+/// from local PromQL semantics: the keys and whether this operation preserves
+/// each input series. It never infers entity reduction from the child tree's
+/// temporal shape. `without()` is applied
+/// separately, post-hoc, by `mark_without` — see its doc for why that's still
+/// correct here.
+fn reduction_for(keys: &[ColumnRef], per_entity: bool) -> Reduction<ColumnRef> {
+    if keys.is_empty() && per_entity {
+        Reduction::PerEntity
+    } else {
+        Reduction::Reduce(GroupKeys::by(keys.to_vec()))
+    }
+}
+
+/// `Aggregate{reduction, [intent]}` over `[TimeRange{w}] → Scan`. Always wraps
+/// in `TimeRange` when there's a window — including for `Rate`/`Increase`,
+/// whose window rides on `inner.window` too (set redundantly alongside the
+/// intent itself): canonical `AggIntent::Rate`/`Increase` carry no window
+/// field of their own, unlike the old Unresolved `AggFunc::Rate{window}` — "the range
+/// is on the enclosing `TimeRange` node" is now true unconditionally, so
+/// there's no more `skip_window` special case.
+fn windowed_aggregate(
+    inner: Inner,
+    keys: Vec<ColumnRef>,
+    intent: AggIntent<ColumnRef>,
+) -> Unresolved {
+    let base = filtered_source(inner.metric, inner.matchers, inner.shift);
+    let child = match inner.window {
+        Some(w) => Unresolved::TimeRange {
+            range: w,
+            kind: TimeRangeKind::Range,
+            child: Rc::new(base),
+        },
+        None => ingestion_lookback(base),
+    };
+    let reduction = reduction_for(&keys, inner.window.is_some() || intent.is_per_series());
+    Unresolved::Aggregate {
+        reduction,
+        measures: vec![intent],
+        // A single empty entry — never an override — so the resolver keeps
+        // PromQL's intent-keyed output names ("sum", "quantile_0_99", …)
+        // instead.
+        output_names: vec![String::new()],
+        filters: vec![],
+        having: None,
+        child: Rc::new(child),
+    }
+}
+
+/// `Aggregate{reduction, [intent]}` directly over an existing Unresolved sub-DAG — the
+/// OUTER level of a two-level aggregation such as `sum(rate(…))` or the
+/// `Aggregate{[Quantile]}` that wraps a `histogram_quantile` argument.
+fn outer_aggregate(
+    keys: Vec<ColumnRef>,
+    intent: AggIntent<ColumnRef>,
+    child: Unresolved,
+) -> Unresolved {
+    let reduction = reduction_for(&keys, intent.is_per_series());
+    Unresolved::Aggregate {
+        reduction,
+        measures: vec![intent],
+        output_names: vec![String::new()],
+        filters: vec![],
+        having: None,
+        child: Rc::new(child),
+    }
+}
+
+/// A temporal range function over a subquery consumes each series' subquery
+/// samples independently. Unlike an ordinary outer aggregate, this cannot be
+/// inferred from the intent: `max` is cross-series in `max(v)`, but per-series
+/// in `max_over_time(v[...])`.
+fn per_series_aggregate(
+    keys: Vec<ColumnRef>,
+    intent: AggIntent<ColumnRef>,
+    child: Unresolved,
+) -> Unresolved {
+    let reduction = reduction_for(&keys, true);
+    Unresolved::Aggregate {
+        reduction,
+        measures: vec![intent],
+        output_names: vec![String::new()],
+        filters: vec![],
+        having: None,
+        child: Rc::new(child),
+    }
+}
+
+fn filtered_source(metric: String, matchers: Vec<Scalar>, shift: TimeShift) -> Unresolved {
+    let scan = Unresolved::Scan {
+        source: Source::TimeSeries { metric },
+        predicates: matchers.into_iter().map(UnresolvedPredicate).collect(),
+        // Usage-derived (PromQL is schemaless) — the SchemaResolver fills this in.
+        schema: None,
+    };
+    if shift.is_identity() {
+        scan
+    } else {
+        Unresolved::TimeShift {
+            shift,
+            child: Rc::new(scan),
+        }
+    }
+}
+
+/// An instant selector: the latest sample per series within the workload's
+/// ingestion interval, so the lookback is an `Instant` `TimeRange`.
+fn instant_source(metric: String, matchers: Vec<Scalar>, shift: TimeShift) -> Unresolved {
+    ingestion_lookback(filtered_source(metric, matchers, shift))
+}
+
+fn ingestion_lookback(child: Unresolved) -> Unresolved {
+    Unresolved::TimeRange {
+        range: current_ingestion_interval(),
+        kind: TimeRangeKind::Instant,
+        child: Rc::new(child),
+    }
+}
+
+/// Count vector elements regardless of their sample values.
+fn count() -> AggIntent<ColumnRef> {
+    AggIntent::Count {
+        accuracy: current_accuracy(),
+    }
+}
+
+fn inner_intent(f: &InnerFunc) -> AggIntent<ColumnRef> {
+    match f {
+        InnerFunc::FrequencyL2 => AggIntent::FrequencyL2 {
+            col: None,
+            accuracy: current_accuracy(),
+        },
+        InnerFunc::FrequencyEntropy => AggIntent::FrequencyEntropy {
+            col: None,
+            accuracy: current_accuracy(),
+        },
+        InnerFunc::Cardinality => AggIntent::Cardinality {
+            cols: vec![],
+            accuracy: current_accuracy(),
+        },
+        InnerFunc::Quantile(q) => AggIntent::Quantile {
+            col: None,
+            q: *q,
+            accuracy: current_accuracy(),
+        },
+        InnerFunc::Avg => AggIntent::Avg { col: None },
+        InnerFunc::Min => AggIntent::Min { col: None },
+        InnerFunc::Max => AggIntent::Max { col: None },
+        InnerFunc::Sum => AggIntent::Sum { col: None },
+        InnerFunc::StdDev => AggIntent::StdDev {
+            col: None,
+            population: true,
+        },
+        InnerFunc::Variance => AggIntent::Variance {
+            col: None,
+            population: true,
+        },
+        InnerFunc::Count => AggIntent::Count {
+            accuracy: current_accuracy(),
+        },
+        InnerFunc::Rate => AggIntent::Rate,
+        InnerFunc::IRate => AggIntent::IRate,
+        InnerFunc::Increase => AggIntent::Increase,
+        InnerFunc::Changes => AggIntent::Changes,
+        InnerFunc::Delta => AggIntent::Delta,
+        InnerFunc::IDelta => AggIntent::IDelta,
+        InnerFunc::Deriv => AggIntent::Deriv,
+        InnerFunc::Resets => AggIntent::Resets,
+        InnerFunc::PredictLinear(s) => AggIntent::PredictLinear { seconds: *s },
+        InnerFunc::DoubleExp { smoothing, trend } => AggIntent::DoubleExpSmoothing {
+            smoothing: *smoothing,
+            trend: *trend,
+        },
+        InnerFunc::LastOverTime => AggIntent::LastOverTime,
+        InnerFunc::FirstOverTime => AggIntent::FirstOverTime,
+        InnerFunc::MadOverTime => AggIntent::MadOverTime,
+        InnerFunc::TsOfMinOverTime => AggIntent::TsOfMinOverTime,
+        InnerFunc::TsOfMaxOverTime => AggIntent::TsOfMaxOverTime,
+        InnerFunc::TsOfFirstOverTime => AggIntent::TsOfFirstOverTime,
+        InnerFunc::TsOfLastOverTime => AggIntent::TsOfLastOverTime,
+    }
+}
+
+fn outer_intent(o: &OuterIntent) -> AggIntent<ColumnRef> {
+    match o {
+        OuterIntent::Sum => AggIntent::Sum { col: None },
+        OuterIntent::Avg => AggIntent::Avg { col: None },
+        OuterIntent::Min => AggIntent::Min { col: None },
+        OuterIntent::Max => AggIntent::Max { col: None },
+        OuterIntent::StdDev => AggIntent::StdDev {
+            col: None,
+            population: true,
+        },
+        OuterIntent::Variance => AggIntent::Variance {
+            col: None,
+            population: true,
+        },
+        OuterIntent::Quantile(q) => AggIntent::Quantile {
+            col: None,
+            q: *q,
+            accuracy: current_accuracy(),
+        },
+        OuterIntent::Group => AggIntent::Group,
+    }
+}
+
+/// Unwrap a (possibly parenthesised) string literal — `count_values` labels and
+/// `label_replace`/`label_join` arguments are all string literals, sometimes
+/// wrapped in parens (`count_values((("v")), …)`).
+fn expr_str(expr: &Expr) -> Result<String> {
+    match expr {
+        Expr::StringLiteral(s) => Ok(s.val.clone()),
+        Expr::Paren(p) => expr_str(&p.expr),
+        other => Err(LoweringError::InvalidParameter(format!(
+            "expected a string literal, got `{other}`"
+        ))),
+    }
+}
+
+/// A `count_values` string parameter (the synthesized label name).
+fn str_param(agg: &AggregateExpr) -> Result<String> {
+    match &agg.param {
+        Some(e) => expr_str(e),
+        None => Err(LoweringError::MissingArgument(
+            "`count_values` label parameter".into(),
+        )),
+    }
+}
+
+/// A call's `idx`-th argument as a string literal (`label_replace`/`label_join`).
+fn str_arg(call: &Call, idx: usize) -> Result<String> {
+    expr_str(arg(call, idx)?)
+}
+
+/// Resolve an aggregation's grouping modifier into a `(keys, without)` pair.
+///
+/// `by(labels)` → the kept labels, `without = false`. `without(labels)` → the
+/// **excluded** labels, `without = true`: the kept set (the complement) can't be
+/// enumerated under an open usage-derived schema, so it is deferred to the
+/// runtime and only the excluded positions are carried (issue #39). Both forms
+/// canonicalise their label set (sort + dedup) so equivalent groupings lower
+/// identically. PromQL labels have no table qualifier → `ColumnRef::Named`.
+fn resolve_group(agg: &AggregateExpr) -> Result<(Vec<ColumnRef>, bool)> {
+    let canon = |labels: &[String]| -> Vec<ColumnRef> {
+        let mut keys = labels.to_vec();
+        keys.sort();
+        keys.dedup();
+        keys.into_iter().map(ColumnRef::Named).collect()
+    };
+    match &agg.modifier {
+        None => Ok((vec![], false)),
+        Some(LabelModifier::Include(ls)) => Ok((canon(&ls.labels), false)),
+        Some(LabelModifier::Exclude(ls)) => Ok((canon(&ls.labels), true)),
+    }
+}
+
+// ── Free helpers ──────────────────────────────────────────────────────────────
+
+fn vs_parts(vs: &VectorSelector) -> Result<(String, Vec<Scalar>, TimeShift)> {
+    // A non-equality `__name__` matcher (`=~` / `!~` / `!=`) selects *across*
+    // metric names. `Source::TimeSeries { metric }` carries a single concrete
+    // metric name, so there is no representation for a regex/negated name
+    // match — reject rather than mislower it to a literal metric named after
+    // the pattern (issue #67). An equality `__name__` (`{__name__="up"}`)
+    // still names the metric below.
+    if let Some(m) = vs
+        .matchers
+        .matchers
+        .iter()
+        .find(|m| m.name == "__name__" && !matches!(m.op, MatchOp::Equal))
+    {
+        return Err(LoweringError::UnsupportedFeature(format!(
+            "non-equality `__name__` matcher ({}{:?}) selects across metric names, \
+             which has no single-metric canonical representation",
+            m.name, m.op
+        )));
+    }
+    let metric = vs.name.clone().unwrap_or_else(|| {
+        vs.matchers
+            .matchers
+            .iter()
+            .find(|m| m.name == "__name__")
+            .map(|m| m.value.clone())
+            .unwrap_or_default()
+    });
+    // Label matchers are an unordered set: `{a="1",b="2"}` and `{b="2",a="1"}`
+    // select the same series. Canonicalise by (name, value) so equivalent
+    // selectors lower to identical predicates.
+    let mut ms: Vec<&Matcher> = vs
+        .matchers
+        .matchers
+        .iter()
+        .filter(|m| m.name != "__name__")
+        .collect();
+    ms.sort_by(|a, b| a.name.cmp(&b.name).then_with(|| a.value.cmp(&b.value)));
+    let matchers = ms.into_iter().map(matcher_to_compare).collect();
+    let shift = time_shift(vs.offset.as_ref(), vs.at.as_ref())?;
+    Ok((metric, matchers, shift))
+}
+
+/// Convert the parser's `offset` / `@` modifiers into a [`TimeShift`] (issue
+/// #40). Offset is signed milliseconds; `@ <ts>` (parser seconds → ms) becomes
+/// an absolute anchor, `@ start()`/`@ end()` the range bounds.
+fn time_shift(offset: Option<&Offset>, at: Option<&ParserAtModifier>) -> Result<TimeShift> {
+    let offset_ms = match offset {
+        None => 0,
+        Some(Offset::Pos(d)) => duration_ms(*d)?,
+        Some(Offset::Neg(d)) => -duration_ms(*d)?,
+    };
+    let at = match at {
+        None => None,
+        Some(ParserAtModifier::Start) => Some(AtModifier::Start),
+        Some(ParserAtModifier::End) => Some(AtModifier::End),
+        Some(ParserAtModifier::At(t)) => Some(AtModifier::Timestamp(system_time_ms(*t)?)),
+    };
+    Ok(TimeShift { offset_ms, at })
+}
+
+/// A `Duration` as `i64` milliseconds, rejecting an overflow rather than
+/// silently truncating a pathologically large `offset`.
+fn duration_ms(d: Duration) -> Result<i64> {
+    i64::try_from(d.as_millis()).map_err(|_| {
+        LoweringError::InvalidParameter("offset duration overflows i64 milliseconds".into())
+    })
+}
+
+/// A `SystemTime` (`@ <ts>`) as `i64` milliseconds since the Unix epoch, signed
+/// so pre-epoch anchors (the parser permits them) are preserved.
+fn system_time_ms(t: SystemTime) -> Result<i64> {
+    let ms = match t.duration_since(std::time::UNIX_EPOCH) {
+        Ok(d) => i64::try_from(d.as_millis()),
+        Err(e) => i64::try_from(e.duration().as_millis()).map(|ms| -ms),
+    };
+    ms.map_err(|_| {
+        LoweringError::InvalidParameter("`@` timestamp overflows i64 milliseconds".into())
+    })
+}
+
+fn matcher_to_compare(m: &Matcher) -> Scalar {
+    let op = match &m.op {
+        MatchOp::Equal => CompareOpKind::Eq,
+        MatchOp::NotEqual => CompareOpKind::Ne,
+        MatchOp::Re(_) => CompareOpKind::Regex,
+        MatchOp::NotRe(_) => CompareOpKind::NotRegex,
+    };
+    Scalar::Compare {
+        left: Box::new(Scalar::Column(ColumnRef::Named(m.name.clone()))),
+        op,
+        right: Box::new(Scalar::Literal(ScalarValue::Utf8(m.value.clone()))),
+        semantics: PROMQL,
+    }
+}
+
+fn extract_matrix(expr: &Expr) -> Result<(String, Vec<Scalar>, Duration, TimeShift)> {
+    match expr {
+        Expr::MatrixSelector(ms) => {
+            let (metric, matchers, shift) = vs_parts(&ms.vs)?;
+            Ok((metric, matchers, ms.range, shift))
+        }
+        Expr::Paren(p) => extract_matrix(&p.expr),
+        // A range-vector function argument must be a (parenthesised) matrix
+        // selector. Do NOT descend through an arbitrary `Call` — that would
+        // silently strip an unsupported wrapper (`rate(deriv(m[5m]))` lowering
+        // as `rate(m[5m])`). Reject instead.
+        other => Err(LoweringError::UnsupportedFeature(format!(
+            "expected a range-vector (matrix) argument, got `{other}`"
+        ))),
+    }
+}
+
+fn arg(call: &Call, idx: usize) -> Result<&Expr> {
+    call.args
+        .args
+        .get(idx)
+        .map(|b| b.as_ref())
+        .ok_or_else(|| LoweringError::MissingArgument(format!("{} arg #{idx}", call.func.name)))
+}
+
+fn num_arg(call: &Call, idx: usize) -> Result<f64> {
+    num_expr(arg(call, idx)?)
+}
+
+fn num_param(agg: &AggregateExpr) -> Result<f64> {
+    match &agg.param {
+        Some(e) => num_expr(e),
+        None => Err(LoweringError::MissingArgument(
+            "aggregate parameter (k / φ)".into(),
+        )),
+    }
+}
+
+fn num_expr(expr: &Expr) -> Result<f64> {
+    match expr {
+        Expr::NumberLiteral(n) => Ok(n.val),
+        Expr::Paren(p) => num_expr(&p.expr),
+        Expr::Unary(u) => Ok(-num_expr(&u.expr)?),
+        // Constant-fold a pure scalar arithmetic expression — the parser does
+        // not fold `10*1024*1024` / `24 * 3600`. A `modifier` (vector matching)
+        // or a non-arithmetic operator means it is not a pure scalar.
+        Expr::Binary(b) if b.modifier.is_none() => {
+            let (l, r) = (num_expr(&b.lhs)?, num_expr(&b.rhs)?);
+            let id = b.op.id();
+            if id == token::T_ADD {
+                Ok(l + r)
+            } else if id == token::T_SUB {
+                Ok(l - r)
+            } else if id == token::T_MUL {
+                Ok(l * r)
+            } else if id == token::T_DIV {
+                Ok(l / r)
+            } else if id == token::T_MOD {
+                Ok(l % r)
+            } else if id == token::T_POW {
+                Ok(l.powf(r))
+            } else {
+                Err(LoweringError::InvalidParameter(
+                    "non-arithmetic operator in scalar expression".into(),
+                ))
+            }
+        }
+        // `min_of`/`max_of` are n-ary *scalar* reducers (issue #89). Fold them
+        // when every argument is itself a constant scalar — this is the only
+        // form the intent algebra can hold (there is no scalar min/max node). A
+        // non-constant argument (`min_of(step(), 1s)`) fails the recursive fold
+        // and propagates the error, so it stays rejected. `f64::min`/`max`
+        // ignore NaN, matching PromQL's `min`/`max` NaN semantics.
+        Expr::Call(c) if is_scalar_reducer_fn(c.func.name) => {
+            let reduce = if c.func.name == "min_of" {
+                f64::min
+            } else {
+                f64::max
+            };
+            c.args
+                .args
+                .iter()
+                .map(|a| num_expr(a))
+                .reduce(|acc, v| Ok(reduce(acc?, v?)))
+                .ok_or_else(|| {
+                    LoweringError::MissingArgument(format!("{} needs an argument", c.func.name))
+                })?
+        }
+        other => Err(LoweringError::InvalidParameter(format!(
+            "expected a numeric scalar, got `{other}`"
+        ))),
+    }
+}
+
+/// The n-ary scalar min/max reducers, foldable when all arguments are constant
+/// scalars (issue #89).
+fn is_scalar_reducer_fn(name: &str) -> bool {
+    matches!(name, "min_of" | "max_of")
+}
+
+/// `topk`/`bottomk` count parameter — a non-negative integer. Rejects
+/// fractional / negative / non-finite values rather than silently truncating
+/// or saturating them via `as u64` (`topk(2.7, …)` ≠ `topk(2, …)`).
+fn count_param(agg: &AggregateExpr) -> Result<u64> {
+    let v = num_param(agg)?;
+    if v.is_finite() && v >= 0.0 && v.fract() == 0.0 && v <= u64::MAX as f64 {
+        Ok(v as u64)
+    } else {
+        Err(LoweringError::InvalidParameter(format!(
+            "topk/bottomk k must be a non-negative integer, got {v}"
+        )))
+    }
+}
+
+/// `limit_ratio` ratio parameter — a finite value; Prometheus clamps it to
+/// `[-1, 1]` (a negative ratio selects the complementary fraction). A non-finite
+/// ratio (`limit_ratio(NaN, …)`) or a dynamic one (`time() % 17/17`, which
+/// `num_param` can't fold) is rejected (issue #86).
+fn ratio_param(agg: &AggregateExpr) -> Result<f64> {
+    let r = num_param(agg)?;
+    if !r.is_finite() {
+        return Err(LoweringError::InvalidParameter(format!(
+            "limit_ratio ratio must be finite, got {r}"
+        )));
+    }
+    Ok(r.clamp(-1.0, 1.0))
+}
+
+/// Preserve the full Prometheus quantile parameter domain, including special values.
+fn quantile_param(q: f64) -> Result<f64> {
+    // Prometheus returns NaN/-Inf/+Inf for these parameters at execution time.
+    Ok(q)
+}
+
+// The non-standard histogram_quantiles extension keeps its bounded label contract.
+fn bounded_quantile_param(q: f64) -> Result<f64> {
+    if q.is_finite() && (0.0..=1.0).contains(&q) {
+        Ok(q)
+    } else {
+        Err(LoweringError::InvalidParameter(format!(
+            "quantile φ must be in [0, 1], got {q}"
+        )))
+    }
+}
+
+fn binop(id: token::TokenId) -> Result<BinaryOpKind> {
+    Ok(if id == token::T_ADD {
+        BinaryOpKind::Arithmetic(ArithmeticOpKind::Add)
+    } else if id == token::T_SUB {
+        BinaryOpKind::Arithmetic(ArithmeticOpKind::Sub)
+    } else if id == token::T_MUL {
+        BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul)
+    } else if id == token::T_DIV {
+        BinaryOpKind::Arithmetic(ArithmeticOpKind::Div)
+    } else if id == token::T_MOD {
+        BinaryOpKind::Arithmetic(ArithmeticOpKind::Mod)
+    } else if id == token::T_POW {
+        BinaryOpKind::Arithmetic(ArithmeticOpKind::Pow)
+    } else if id == token::T_ATAN2 {
+        BinaryOpKind::Arithmetic(ArithmeticOpKind::Atan2)
+    } else if id == token::T_EQLC {
+        BinaryOpKind::Compare(CompareOpKind::Eq)
+    } else if id == token::T_NEQ {
+        BinaryOpKind::Compare(CompareOpKind::Ne)
+    } else if id == token::T_LSS {
+        BinaryOpKind::Compare(CompareOpKind::Lt)
+    } else if id == token::T_LTE {
+        BinaryOpKind::Compare(CompareOpKind::Le)
+    } else if id == token::T_GTR {
+        BinaryOpKind::Compare(CompareOpKind::Gt)
+    } else if id == token::T_GTE {
+        BinaryOpKind::Compare(CompareOpKind::Ge)
+    } else if id == token::T_LAND {
+        BinaryOpKind::Set(PromQLVectorSetOpKind::And)
+    } else if id == token::T_LOR {
+        BinaryOpKind::Set(PromQLVectorSetOpKind::Or)
+    } else if id == token::T_LUNLESS {
+        BinaryOpKind::Set(PromQLVectorSetOpKind::Unless)
+    } else {
+        return Err(LoweringError::UnsupportedFeature(format!(
+            "binary operator token {id}"
+        )));
+    })
+}
diff --git a/crates/frontend-promql/tests/unified_histogram_metadata.rs b/crates/frontend-promql/tests/unified_histogram_metadata.rs
new file mode 100644
index 000000000..49fdffe02
--- /dev/null
+++ b/crates/frontend-promql/tests/unified_histogram_metadata.rs
@@ -0,0 +1,138 @@
+//! Type-driven `histogram_quantile` discrimination (issue #79).
+//!
+//! The structural heuristic (`by (le)` / `_bucket` / `le=` matcher) proxies the
+//! argument's sample type. A declared [`HistogramKind`] overrides it, fixing the
+//! heuristic's false-positive and false-negative cases. Undeclared metrics still
+//! fall back to the heuristic.
+
+use asap_frontend_promql::unified::{HistogramCatalog, HistogramKind};
+#[path = "unified_support.rs"]
+mod support;
+use asap_types::ir::{NonASAPOp, OperatorNode};
+use asap_types::pre_asap::AggIntent;
+use asap_types::types::AccuracyTarget;
+use support::{lower_promql, lower_promql_with_histograms};
+
+/// The histogram/quantile intent kind in the lowered tree: `"HQ"` for the
+/// classic-bucket `HistogramQuantile`, `"Q"` for the sketch-able `Quantile`.
+fn quantile_kind(qe: &OperatorNode) -> &'static str {
+    fn walk(e: &OperatorNode) -> Option<&'static str> {
+        match e.expect_non_asap() {
+            NonASAPOp::Aggregate {
+                measures, child, ..
+            } => measures
+                .iter()
+                .find_map(|i| match i {
+                    AggIntent::HistogramQuantile { .. } => Some("HQ"),
+                    AggIntent::Quantile { .. } => Some("Q"),
+                    _ => None,
+                })
+                .or_else(|| walk(child)),
+            NonASAPOp::TimeRange { child, .. }
+            | NonASAPOp::Filter { child, .. }
+            | NonASAPOp::Sort { child, .. }
+            | NonASAPOp::Limit { child, .. }
+            | NonASAPOp::PromqlSubquery { child, .. }
+            | NonASAPOp::Project { child, .. } => walk(child),
+            _ => None,
+        }
+    }
+    walk(qe).expect("a HistogramQuantile or Quantile intent")
+}
+
+fn heuristic(q: &str) -> &'static str {
+    quantile_kind(&lower_promql(q, AccuracyTarget::Exact).unwrap())
+}
+
+fn with_meta(q: &str, catalog: HistogramCatalog) -> &'static str {
+    quantile_kind(&lower_promql_with_histograms(q, AccuracyTarget::Exact, catalog).unwrap())
+}
+
+#[test]
+fn heuristic_baseline_is_unchanged_without_a_catalog() {
+    // Classic buckets are represented; undeclared native samples are rejected.
+    assert_eq!(
+        heuristic(
+            "histogram_quantile(0.9, sum by (le) (rate(http_request_duration_seconds_bucket[5m])))"
+        ),
+        "HQ"
+    );
+    assert!(lower_promql(
+        "histogram_quantile(0.9, native_latency)",
+        AccuracyTarget::Exact
+    )
+    .is_err());
+}
+
+#[test]
+fn declared_classic_bucket_fixes_the_false_negative() {
+    // A classic histogram exposed WITHOUT the `_bucket` suffix and queried with
+    // no `le` grouping/matcher requires an explicit sample-type declaration.
+    let q = "histogram_quantile(0.9, latency_seconds)";
+    assert!(lower_promql(q, AccuracyTarget::Exact).is_err());
+    assert_eq!(
+        with_meta(
+            q,
+            HistogramCatalog::new().with("latency_seconds", HistogramKind::ClassicBucket)
+        ),
+        "HQ",
+        "metadata routes it to exact bucket interpolation"
+    );
+}
+
+#[test]
+fn declared_raw_extension_and_native_gap_override_the_heuristic() {
+    // A metric merely NAMED `…_bucket` that actually holds raw samples / a native
+    // histogram: the heuristic wrongly routes it to bucket interpolation.
+    let q = "histogram_quantile(0.9, foo_bucket)";
+    assert_eq!(
+        heuristic(q),
+        "HQ",
+        "heuristic mis-routes on the `_bucket` name"
+    );
+    assert_eq!(
+        with_meta(
+            q,
+            HistogramCatalog::new().with("foo_bucket", HistogramKind::RawSamples)
+        ),
+        "Q",
+        "raw samples are sketch-able"
+    );
+    let catalog = HistogramCatalog::new().with("foo_bucket", HistogramKind::Native);
+    assert!(lower_promql_with_histograms(q, AccuracyTarget::Exact, catalog.clone()).is_err());
+    assert!(lower_promql_with_histograms("foo_bucket", AccuracyTarget::Exact, catalog).is_err());
+}
+
+#[test]
+fn undeclared_metric_falls_back_to_the_heuristic() {
+    // A catalog that doesn't mention the queried metric leaves the structural
+    // decision in place.
+    let catalog = HistogramCatalog::new().with("some_other_metric", HistogramKind::RawSamples);
+    assert_eq!(
+        with_meta(
+            "histogram_quantile(0.9, sum by (le) (x_bucket))",
+            catalog.clone()
+        ),
+        "HQ"
+    );
+    assert!(lower_promql_with_histograms(
+        "histogram_quantile(0.9, native_thing)",
+        AccuracyTarget::Exact,
+        catalog
+    )
+    .is_err());
+}
+
+#[test]
+fn the_catalog_does_not_leak_across_calls() {
+    // The ambient catalog is scoped to the single `_with_histograms` call; a
+    // subsequent plain `lower_promql` sees no metadata (guards against a
+    // thread-local that isn't cleaned up).
+    let _ = with_meta(
+        "histogram_quantile(0.9, foo_bucket)",
+        HistogramCatalog::new().with("foo_bucket", HistogramKind::RawSamples),
+    );
+    // `foo_bucket` would be sketch-able under that catalog, but with none it must
+    // revert to the heuristic (the `_bucket` name → HistogramQuantile).
+    assert_eq!(heuristic("histogram_quantile(0.9, foo_bucket)"), "HQ");
+}
diff --git a/crates/frontend-promql/tests/unified_promql_conformance.rs b/crates/frontend-promql/tests/unified_promql_conformance.rs
new file mode 100644
index 000000000..6ea89a0bb
--- /dev/null
+++ b/crates/frontend-promql/tests/unified_promql_conformance.rs
@@ -0,0 +1,2208 @@
+//! PromQL **semantic conformance** for the parse-to-canonical-tree lowering.
+//!
+//! We *lower* PromQL to the intent algebra; we do not *execute* it. So "same
+//! semantic job as Prometheus" here means: for each canonical query, does the
+//! canonical tree encode the **documented PromQL meaning** — and where we knowingly
+//! diverge (reject, approximate, or drop a modifier), is that pinned by a test
+//! so it stays visible?
+//!
+//! Sources for the queries + their semantics:
+//! - PromQL basics (data types, selectors, offset/@/subquery):
+//!   <https://prometheus.io/docs/prometheus/latest/querying/basics/>
+//! - PromLabs PromQL cheat sheet (common real-world queries by category):
+//!   <https://promlabs.com/promql-cheat-sheet/>
+//! - Prometheus' own engine test corpus (these are *execution* tests —
+//!   load → eval → expect values — so they define semantics we mirror as
+//!   *structure*): <https://github.com/prometheus/prometheus/tree/main/promql/promqltest/testdata>
+//!   Relevant files, mapped to the sections below: selectors.test,
+//!   aggregators.test, functions.test, histograms.test, operators.test,
+//!   subquery.test, at_modifier.test, literals.test, limit.test
+//!
+//! Legend used in test names:
+//! - (no suffix)  — we lower it and the canonical intent matches PromQL.
+//! - `__GAP`      — a PromQL capability we don't *yet* support. It is **cleanly
+//!   rejected** (never silently mislowered), and pinned here so adding support
+//!   later flips the assertion deliberately.
+//!
+//! NOTE: the formerly-silent divergences (`group`→sum, dropped `offset`/`@`,
+//! `changes`/`resets`→count) are now rejected rather than mislowered — see the
+//! equivalence suite (`promql_equivalence.rs`) and section L below.
+
+// `__GAP`-suffixed test names intentionally SHOUT the documented divergences.
+#![allow(non_snake_case)]
+
+use std::rc::Rc;
+use std::time::Duration;
+
+use asap_frontend_promql::unified::PromqlError as LoweringError;
+#[path = "unified_support.rs"]
+mod support;
+use asap_types::ir::{
+    BinaryOperator, ExprSemantics, NonASAPOp, OperatorNode, ScalarExpr, TimeRangeKind,
+};
+use asap_types::pre_asap::schema::DataType;
+use asap_types::pre_asap::{
+    AggIntent, ArithmeticOpKind, AtModifier, BinaryOpKind, CompareOpKind, PromQLVectorSetOpKind,
+    Reduction, SampleKind, ScalarValue, Source, TimeFunc,
+};
+use asap_types::types::AccuracyTarget;
+use support::{lower_promql, promql_scalar};
+
+// ── harness helpers ─────────────────────────────────────────────────────────────
+
+/// Lower, expecting success.
+fn ok(q: &str) -> Rc<OperatorNode> {
+    lower_promql(q, AccuracyTarget::Exact)
+        .unwrap_or_else(|e| panic!("expected {q:?} to lower, got error: {e}"))
+}
+
+/// Lower, expecting a clean `LoweringError` (an unsupported capability).
+fn rejected(q: &str) -> LoweringError {
+    match lower_promql(q, AccuracyTarget::Exact) {
+        Err(e) => e,
+        Ok(tree) => panic!("expected {q:?} to be rejected, but it lowered to: {tree:?}"),
+    }
+}
+
+/// Every `AggIntent` anywhere in the tree, root-to-leaf.
+fn intents(e: &OperatorNode) -> Vec<AggIntent> {
+    let mut out = Vec::new();
+    collect(e, &mut out);
+    out
+}
+
+/// `AggIntent` only ever lives in `Aggregate.measures`, never in a scalar
+/// position (issue #205); `children()` also descends into the operators a
+/// scalar position reads (`scalar(v)`).
+fn collect(e: &OperatorNode, out: &mut Vec<AggIntent>) {
+    if let Some(NonASAPOp::Aggregate { measures, .. }) = e.non_asap() {
+        out.extend(measures.iter().cloned());
+    }
+    for child in e.children() {
+        collect(child, out);
+    }
+}
+
+/// The first `Scan` reached by descending single-child nodes, with its metric
+/// name and predicate count.
+fn first_scan(e: &OperatorNode) -> (String, usize) {
+    match e.expect_non_asap() {
+        NonASAPOp::Scan {
+            source, predicates, ..
+        } => {
+            let name = match source {
+                Source::TimeSeries { metric } => metric.clone(),
+                Source::Table { table_ref } => table_ref.clone(),
+            };
+            (name, predicates.len())
+        }
+        NonASAPOp::TimeRange { child, .. }
+        | NonASAPOp::TimeShift { child, .. }
+        | NonASAPOp::Aggregate { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. }
+        | NonASAPOp::PromqlSubquery { child, .. } => first_scan(child),
+        other => panic!("no Scan reachable from {other:?}"),
+    }
+}
+
+fn has<F: Fn(&AggIntent) -> bool>(e: &OperatorNode, pred: F) -> bool {
+    intents(e).iter().any(pred)
+}
+
+/// Whether the tree contains a `Mul`-by-`ScalarExpr(-1)` anywhere — the shape unary
+/// negation lowers to (issue #36).
+fn negates_via_scalar(e: &OperatorNode) -> bool {
+    fn negative(expr: &ScalarExpr) -> bool {
+        matches!(expr, ScalarExpr::Negative { .. }) || expr.children().iter().any(|e| negative(e))
+    }
+    e.expect_non_asap()
+        .scalar_exprs()
+        .iter()
+        .any(|e| negative(e))
+        || e.children().iter().any(|e| negates_via_scalar(e))
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// A. Selectors & label matchers           (basics §"Instant/Range Vector
+//    Selectors"; selectors.test)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn instant_vector_selector() {
+    // SEMANTICS: bare metric → instant vector (latest sample per series).
+    let (metric, preds) = first_scan(&ok("node_cpu_seconds_total"));
+    assert_eq!(metric, "node_cpu_seconds_total");
+    assert_eq!(preds, 0, "no label matchers → no predicates");
+}
+
+#[test]
+fn promql_scan_schema_is_open() {
+    // A schemaless PromQL leaf is *open*: the metric's full label set is
+    // runtime-only, so the binding schema lists only the (ts, value) floor +
+    // referenced labels and may be a subset of the runtime row.
+    let qe = ok("node_cpu_seconds_total");
+    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
+        panic!("expected a TimeRange for a bare selector, got {qe:?}");
+    };
+    let NonASAPOp::Scan { schema, .. } = child.expect_non_asap() else {
+        panic!("expected a Scan inside the TimeRange, got {qe:?}");
+    };
+    assert!(
+        !schema.closed,
+        "a schemaless PromQL scan has an open schema"
+    );
+}
+
+#[test]
+fn label_matchers_become_scan_predicates() {
+    // SEMANTICS: `=`, `!=`, `=~`, `!~` filter series; one conjunct per matcher.
+    let (_, preds) = first_scan(&ok(
+        r#"http_requests_total{job!="x",path=~"/api/.*",env!~"dev"}"#,
+    ));
+    assert_eq!(preds, 3, "three matchers → three Scan predicates");
+}
+
+#[test]
+fn name_label_selects_the_metric() {
+    // SEMANTICS: the metric name is the internal `__name__` label.
+    let (metric, preds) = first_scan(&ok(r#"{__name__="up"}"#));
+    assert_eq!(metric, "up");
+    assert_eq!(preds, 0, "__name__ is the metric, not a residual predicate");
+}
+
+#[test]
+fn name_regex_matcher_is_rejected__GAP() {
+    // A `__name__=~` / `!~` / `!=` matcher selects *across* metric names, which
+    // the single-metric `Source::TimeSeries { metric }` can't represent. It is
+    // rejected (issue #67) rather than silently mislowered to a literal metric
+    // named after the pattern (`{__name__=~"node_.*"}` → `Source("node_.*")`).
+    // Full support needs a wildcard/regex `Source` in the IR.
+    let _ = rejected(r#"{__name__=~"node_.*"}"#);
+    let _ = rejected(r#"{__name__!~"x", job="y"}"#);
+    // Equality still names the metric (regression guard for the fix).
+    let (metric, _) = first_scan(&ok(r#"{__name__="up"}"#));
+    assert_eq!(metric, "up");
+}
+
+#[test]
+fn range_vector_selector_is_time_range() {
+    // SEMANTICS: `[5m]` turns an instant vector into a range vector,
+    // represented in the canonical tree as a dedicated `TimeRange` node.
+    let qe = ok("node_cpu_seconds_total[5m]");
+    let NonASAPOp::TimeRange { range, .. } = qe.expect_non_asap() else {
+        panic!("expected TimeRange for a range-vector selector, got {qe:?}");
+    };
+    assert_eq!(*range, Duration::from_secs(300));
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// B. Counters: rate / irate / increase     (cheat sheet "Rates of Increase";
+//    functions.test)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn selector_time_ranges_carry_their_kind() {
+    // SEMANTICS: an instant selector reads the latest sample within the
+    // ingestion interval (`Instant`); `m[5m]` is a range selection (`Range`).
+    // Same length is not the same shape: `m` and `m[1s]` stay distinct.
+    assert!(matches!(
+        ok("node_cpu_seconds_total").expect_non_asap(),
+        NonASAPOp::TimeRange {
+            kind: TimeRangeKind::Instant,
+            ..
+        }
+    ));
+    assert!(matches!(
+        ok("node_cpu_seconds_total[5m]").expect_non_asap(),
+        NonASAPOp::TimeRange {
+            kind: TimeRangeKind::Range,
+            ..
+        }
+    ));
+    assert_ne!(
+        ok("node_cpu_seconds_total"),
+        ok("node_cpu_seconds_total[1s]")
+    );
+}
+
+#[test]
+fn rate_range_lives_in_time_range_node() {
+    // SEMANTICS: per-second average rate; the temporal range lives on the
+    // enclosing `TimeRange` node, not inside the intent.
+    let qe = ok("rate(http_requests_total[5m])");
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected Aggregate, got {qe:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
+    let NonASAPOp::TimeRange { range, .. } = child.expect_non_asap() else {
+        panic!("expected TimeRange child, got {child:?}");
+    };
+    assert_eq!(*range, Duration::from_secs(300));
+}
+
+#[test]
+fn irate_maps_to_its_own_intent() {
+    assert!(has(&ok("irate(http_requests_total[1m])"), |i| matches!(
+        i,
+        AggIntent::IRate
+    )));
+}
+
+#[test]
+fn increase_range_lives_in_time_range_node() {
+    let qe = ok("increase(http_requests_total[1h])");
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected Aggregate, got {qe:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Increase]));
+    let NonASAPOp::TimeRange { range, .. } = child.expect_non_asap() else {
+        panic!("expected TimeRange child, got {child:?}");
+    };
+    assert_eq!(*range, Duration::from_secs(3600));
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// C. Aggregation across series             (cheat sheet "Aggregating Over
+//    Multiple Series"; aggregators.test)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn sum_collapses_all_series() {
+    // SEMANTICS: `sum(v)` → one output series. No grouping → no Partition.
+    let qe = ok("sum(node_filesystem_size_bytes)");
+    assert!(matches!(qe.expect_non_asap(), NonASAPOp::Aggregate { .. }));
+    assert!(has(&qe, |i| matches!(i, AggIntent::Sum { .. })));
+}
+
+#[test]
+fn sum_by_groups_via_positional_aggregate() {
+    // SEMANTICS: `by(job,instance)` keeps those labels; the grouping lives on a
+    // positional `Aggregate.by` — the same shape SQL `GROUP BY` produces (not a
+    // name-based Partition). SchemaResolver leaf = [ts, value, instance, job] (referenced
+    // keys appended sorted), so the keys resolve to columns [2, 3].
+    let qe = ok("sum by(job, instance) (node_filesystem_size_bytes)");
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected positional Aggregate for `by(...)`, got {qe:?}");
+    };
+    assert_eq!(
+        reduction,
+        &Reduction::by(vec![2, 3]),
+        "group keys resolve to positional ColumnIds"
+    );
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+    assert!(
+        matches!(child.expect_non_asap(), NonASAPOp::TimeRange { child, .. } if matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }))
+    );
+}
+
+#[test]
+fn count_is_row_count() {
+    assert!(has(&ok("count(up)"), |i| matches!(
+        i,
+        AggIntent::Count { .. }
+    )));
+}
+
+#[test]
+fn avg_min_max_stddev_stdvar_quantile_aggregators() {
+    assert!(has(&ok("avg(up)"), |i| matches!(i, AggIntent::Avg { .. })));
+    assert!(has(&ok("min(up)"), |i| matches!(i, AggIntent::Min { .. })));
+    assert!(has(&ok("max(up)"), |i| matches!(i, AggIntent::Max { .. })));
+    assert!(has(&ok("stddev(up)"), |i| matches!(
+        i,
+        AggIntent::StdDev { .. }
+    )));
+    assert!(has(&ok("stdvar(up)"), |i| matches!(
+        i,
+        AggIntent::Variance { .. }
+    )));
+    assert!(has(&ok("quantile(0.5, up)"), |i| matches!(
+        i,
+        AggIntent::Quantile { .. }
+    )));
+}
+
+#[test]
+fn sum_without_groups_by_the_complement() {
+    // SEMANTICS (issue #39): `without(instance)` = group by all labels EXCEPT
+    // instance. The complement can't be enumerated under the open usage-derived
+    // schema, so the excluded label is stored and the kept set is deferred to
+    // the runtime: the grouping is the exclusion form and the output schema
+    // stays OPEN (unlike `by`, which freezes to closed).
+    let qe = ok("sum without(instance) (node_filesystem_size_bytes)");
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected an Aggregate, got {qe:?}");
+    };
+    let by = reduction.expect_reduce();
+    assert!(
+        by.is_without(),
+        "the grouping is the `without` exclusion form"
+    );
+    assert_eq!(by.keys().len(), 1, "the one excluded label (instance)");
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+    assert!(
+        !qe.schema.clone().closed,
+        "a `without` result keeps an open schema (kept label set is runtime-only)"
+    );
+}
+
+#[test]
+fn without_on_topk_is_rejected() {
+    // `without(...)` is modelled only for reducing aggregations; on topk/bottomk
+    // (a ranking, not a reduction) it would need without-partitioning, so it is
+    // rejected rather than silently lowered as a `by` (issue #39).
+    let e = rejected("topk without (job) (3, http_requests_total)");
+    assert!(format!("{e}").contains("without"), "got {e}");
+}
+
+#[test]
+fn group_aggregator_lowers_to_a_distinct_intent() {
+    // SEMANTICS (PromQL): `group(v)` returns a constant 1 per group (presence),
+    // NOT a sum. It now lowers to a distinct `Group` intent (never folded onto
+    // `Sum`) — see §S. Regression guard that it is not a `Sum`.
+    let qe = ok("group by (job) (up)");
+    assert!(has(&qe, |i| *i == AggIntent::Group));
+    assert!(!has(&qe, |i| matches!(i, AggIntent::Sum { .. })));
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// D. Two-level: outer aggregation OVER an inner counter  (the canonical
+//    `sum(rate(...))` shape; aggregators.test + functions.test)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn sum_of_rate_is_two_levels() {
+    // SEMANTICS: per-series rate, THEN cross-series sum. Both must survive.
+    let qe = ok("sum(rate(http_requests_total[5m]))");
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate{{Sum}}, got {qe:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate])
+    ));
+}
+
+#[test]
+fn sum_by_of_rate_groups_outer_level() {
+    // Outer cross-series Sum grouped on positional `Aggregate.by` over the
+    // label-preserving inner Rate. Leaf = [ts, value, instance] → by = [2].
+    let qe = ok("sum by(instance) (rate(node_network_receive_bytes_total[5m]))");
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate grouped by instance, got {qe:?}");
+    };
+    assert_eq!(reduction, &Reduction::by(vec![2]));
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+    // child is the inner per-series Rate aggregate.
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate])
+    ));
+}
+
+#[test]
+fn sum_by_of_over_time_groups_outer_level() {
+    // Outer cross-series Sum grouped on positional `Aggregate.by` over an inner
+    // *per-series* `avg_over_time` — `Window { Aggregate{Avg} }` is label-
+    // preserving, so the key resolves positionally just like the rate case (no
+    // name-based Partition). Leaf = [ts, value, instance] → by = [2].
+    let qe = ok("sum by(instance) (avg_over_time(node_cpu_seconds_total[5m]))");
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate grouped by instance, got {qe:?}");
+    };
+    assert_eq!(reduction, &Reduction::by(vec![2]));
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+    // child is the inner per-series reduction: Aggregate{Avg} over TimeRange.
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected Aggregate (per-series avg_over_time) under the Sum, got {child:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Avg { .. }]));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// E. Aggregation over time (per-series)    (cheat sheet "Aggregating Over
+//    Time"; functions.test)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn over_time_functions_reduce_over_time_range() {
+    // SEMANTICS: reduce the samples WITHIN each series over the range →
+    // Aggregate over TimeRange (per-series, label-preserving).
+    for (q, want) in [
+        ("avg_over_time(go_goroutines[5m])", "avg"),
+        ("max_over_time(process_resident_memory_bytes[1d])", "max"),
+        ("min_over_time(go_goroutines[5m])", "min"),
+        ("sum_over_time(go_goroutines[5m])", "sum"),
+        ("count_over_time(go_goroutines[5m])", "count"),
+    ] {
+        let qe = ok(q);
+        assert!(
+            matches!(qe.expect_non_asap(), NonASAPOp::Aggregate { .. }),
+            "{q}: expected Aggregate"
+        );
+        let matched = intents(&qe).iter().any(|i| match want {
+            "avg" => matches!(i, AggIntent::Avg { .. }),
+            "max" => matches!(i, AggIntent::Max { .. }),
+            "min" => matches!(i, AggIntent::Min { .. }),
+            "sum" => matches!(i, AggIntent::Sum { .. }),
+            "count" => matches!(i, AggIntent::Count { .. }),
+            _ => unreachable!(),
+        });
+        assert!(matched, "{q}: missing {want} intent");
+    }
+}
+
+#[test]
+fn quantile_over_time_is_aggregate_over_time_range() {
+    let qe = ok("quantile_over_time(0.9, request_latency_seconds[5m])");
+    assert!(matches!(qe.expect_non_asap(), NonASAPOp::Aggregate { .. }));
+    assert!(has(
+        &qe,
+        |i| matches!(i, AggIntent::Quantile { q, .. } if (*q - 0.9).abs() < 1e-9)
+    ));
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// F. Histograms                            (cheat sheet "Quantiles from
+//    Histograms"; histograms.test)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn histogram_quantile_over_rate() {
+    // φ-quantile from bucket rates. The `_bucket` metric marks the classic
+    // cumulative-bucket form → `HistogramQuantile` (even without `sum by (le)`).
+    let qe = ok("histogram_quantile(0.9, rate(demo_api_request_duration_seconds_bucket[5m]))");
+    let NonASAPOp::Aggregate { measures, .. } = qe.expect_non_asap() else {
+        panic!("expected Aggregate{{HistogramQuantile}}, got {qe:?}");
+    };
+    assert!(
+        matches!(measures.as_slice(), [AggIntent::HistogramQuantile { q, .. }] if (*q - 0.9).abs() < 1e-9)
+    );
+    assert!(has(&qe, |i| matches!(i, AggIntent::Rate)));
+}
+
+#[test]
+fn histogram_quantile_over_sum_by_le_preserves_le_grouping() {
+    // SEMANTICS: the standard pattern — bucket rates summed by `le`, then the
+    // quantile. The `sum by (le)` aggregation must survive into the
+    // canonical tree.
+    let qe = ok(
+        "histogram_quantile(0.99, sum by(le) (rate(demo_api_request_duration_seconds_bucket[5m])))",
+    );
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate{{HistogramQuantile}}, got {qe:?}");
+    };
+    // `by (le)` marks the classic cumulative-bucket form → `HistogramQuantile`.
+    assert!(matches!(
+        measures.as_slice(),
+        [AggIntent::HistogramQuantile { .. }]
+    ));
+    // `sum by(le)` now survives as a positional Aggregate (by = [2], `le`), over
+    // the inner Rate — no name-based Partition.
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected `sum by(le)` as a positional Aggregate, got {child:?}");
+    };
+    assert_eq!(reduction, &Reduction::by(vec![2]));
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// G. Binary ops: math, matching, comparison  (cheat sheet "Math Between
+//    Series" / "Filtering Series by Value"; operators.test)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn vector_arithmetic() {
+    let qe = ok("node_memory_MemFree_bytes + node_memory_Cached_bytes");
+    let NonASAPOp::BinaryOp {
+        operator: BinaryOperator { kind: op, .. },
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected BinaryOp, got {qe:?}");
+    };
+    assert_eq!(*op, BinaryOpKind::Arithmetic(ArithmeticOpKind::Add));
+}
+
+#[test]
+fn on_matching_with_group_left() {
+    // SEMANTICS: many-to-one matching on a label subset.
+    let qe =
+        ok("rate(demo_cpu_usage_seconds_total[1m]) / on(instance, job) group_left demo_num_cpus");
+    let NonASAPOp::BinaryOp { operator, .. } = qe.expect_non_asap() else {
+        panic!("expected BinaryOp, got {qe:?}");
+    };
+    assert_eq!(
+        operator.kind,
+        BinaryOpKind::Arithmetic(ArithmeticOpKind::Div)
+    );
+    let vm = operator
+        .vector_match
+        .as_ref()
+        .expect("on(...) group_left present");
+    assert_eq!(vm.labels, vec!["instance".to_string(), "job".to_string()]);
+    assert!(
+        vm.grouping.is_some(),
+        "group_left should set the grouping side"
+    );
+}
+
+#[test]
+fn vector_comparison_filters() {
+    // SEMANTICS: `>` between two vectors keeps the LHS series where it holds.
+    let qe = ok("go_goroutines > go_threads");
+    assert!(
+        matches!(qe.expect_non_asap(), NonASAPOp::BinaryOp { operator: BinaryOperator { kind: op, .. }, .. } if *op == BinaryOpKind::Compare(CompareOpKind::Gt))
+    );
+}
+
+#[test]
+fn comparison_bool_modifier_returns_zero_or_one() {
+    // SEMANTICS (operators.test): `bool` turns a filtering comparison into a
+    // 0/1-valued one. On a vector operand it is `return_bool` on the
+    // `BinaryOp`; between two scalars it is a `Case(Compare → 1, else 0)`
+    // scalar expression under PromQL numeric rules — and a scalar comparison
+    // without `bool` is not a PromQL expression at all.
+    let bool_flag = |q: &str| match ok(q).expect_non_asap() {
+        NonASAPOp::BinaryOp { return_bool, .. } => *return_bool,
+        NonASAPOp::Project { .. } => true,
+        NonASAPOp::Filter { .. } => false,
+        other => panic!("expected BinaryOp for {q}, got {other:?}"),
+    };
+    assert!(bool_flag("go_goroutines > bool go_threads"));
+    assert!(bool_flag("go_goroutines > bool 0"));
+    assert!(!bool_flag("go_goroutines > go_threads"));
+    assert!(!bool_flag("go_goroutines > 0"));
+
+    let qe = support::scalar_root("1 < bool 2");
+    let ScalarExpr::Case { branches, .. } = &qe else {
+        panic!("expected a scalar Case, got {qe:?}");
+    };
+    assert!(matches!(
+        branches.as_slice(),
+        [(
+            ScalarExpr::Compare {
+                op: CompareOpKind::Lt,
+                semantics: ExprSemantics::Promql,
+                ..
+            },
+            _
+        )]
+    ));
+    rejected("1 < 2");
+}
+
+#[test]
+fn unary_negation_lowers_as_multiply_by_minus_one() {
+    // SEMANTICS (PromQL, issue #36): `-expr` flips the sign of every sample.
+    // Now that a scalar operand exists (#35), it lowers as `expr * -1` — a `Mul`
+    // BinaryOp of the (label-preserving) vector against `ScalarExpr(-1)`. These are
+    // the five cases the old `__GAP` test pinned as rejected.
+    for q in [
+        "-rate(http_errors_total[5m])",
+        "-some_metric",
+        "-metric_a or -metric_b",
+        "http_requests_total - -http_errors_total",
+        "sum(-node_cpu_seconds_total)",
+    ] {
+        let qe = ok(q);
+        // A `Mul`-by-`-1` against a `ScalarExpr(-1)` appears somewhere in every tree.
+        assert!(
+            negates_via_scalar(&qe),
+            "no `* -1` negation found in {q}: {qe:?}"
+        );
+    }
+
+    let negated = ok("-some_metric");
+    assert!(negates_via_scalar(&negated));
+    assert!(negated.schema.has_promql_series_identity());
+    assert!(negated.schema.time_index.is_some());
+    let summed = ok("sum(-node_cpu_seconds_total)");
+    assert!(has(&summed, |i| matches!(i, AggIntent::Sum { .. })));
+    assert!(negates_via_scalar(&summed));
+}
+
+#[test]
+fn unary_negation_of_constant_folds_to_scalar() {
+    // `-(10*1024*1024)` — the operand is constant-foldable, so negation collapses
+    // to a single negated `ScalarExpr` leaf (no `BinaryOp`), just like a bare literal.
+    assert!(promql_scalar(&support::scalar_root("-(10*1024*1024)"))
+        .is_some_and(|v| (v + 10_485_760.0).abs() < 1e-6));
+}
+
+#[test]
+fn double_unary_negation_nests() {
+    let qe = ok("- -some_metric");
+    let NonASAPOp::Project { child, .. } = qe.expect_non_asap() else {
+        panic!()
+    };
+    assert!(matches!(child.expect_non_asap(), NonASAPOp::Project { .. }));
+    assert!(negates_via_scalar(child));
+}
+
+#[test]
+fn count_maps_to_count_and_inherits_accuracy() {
+    // Counts preserve the workload accuracy target without counting distinct values.
+    let exact = lower_promql("count by (job) (up)", AccuracyTarget::Exact).unwrap();
+    assert!(
+        has(&exact, |i| matches!(
+            i,
+            AggIntent::Count {
+                accuracy: AccuracyTarget::Exact
+            }
+        )),
+        "Count must stay Exact under AccuracyTarget::Exact, got {:?}",
+        intents(&exact)
+    );
+
+    let approx = lower_promql("count by (job) (up)", AccuracyTarget::Epsilon(0.01)).unwrap();
+    assert!(
+        has(&approx, |i| matches!(
+            i,
+            AggIntent::Count {
+                accuracy: AccuracyTarget::Epsilon(e)
+            } if (*e - 0.01).abs() < 1e-9
+        )),
+        "Count must carry the approximate target, got {:?}",
+        intents(&approx)
+    );
+}
+
+#[test]
+fn scalar_literal_operand_lowers_as_binaryop_scalar() {
+    let qe = ok("node_filesystem_avail_bytes > 10*1024*1024");
+    let ScalarExpr::Compare { op, right, .. } = support::sample_expression(&qe) else {
+        panic!()
+    };
+    assert_eq!(*op, CompareOpKind::Gt);
+    assert_eq!(promql_scalar(right), Some(10_485_760.0));
+}
+
+#[test]
+fn scalar_arithmetic_scales_the_vector() {
+    let qe = ok("rate(m[5m]) * 100");
+    let ScalarExpr::Arithmetic { op, right, .. } = support::sample_expression(&qe) else {
+        panic!()
+    };
+    assert_eq!(*op, ArithmeticOpKind::Mul);
+    assert_eq!(promql_scalar(right), Some(100.0));
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// H. Set operations                        (cheat sheet "Set Operations";
+//    operators.test)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn set_ops_lower_to_binaryop() {
+    // SEMANTICS: or = union of label sets; and = intersection; unless = difference.
+    let set_op = |q: &str| match ok(q).expect_non_asap() {
+        NonASAPOp::BinaryOp { operator, .. } => operator.kind.clone(),
+        other => panic!("expected BinaryOp for {q}, got {other:?}"),
+    };
+    assert_eq!(
+        set_op("up{job=\"a\"} or up{job=\"b\"}"),
+        BinaryOpKind::Set(PromQLVectorSetOpKind::Or)
+    );
+    assert_eq!(
+        set_op("node_network_mtu_bytes and node_up"),
+        BinaryOpKind::Set(PromQLVectorSetOpKind::And)
+    );
+    assert_eq!(
+        set_op("node_network_mtu_bytes unless node_down"),
+        BinaryOpKind::Set(PromQLVectorSetOpKind::Unless)
+    );
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// I. Sorting / top-k                        (cheat sheet "Sorting"/topk;
+//    functions.test, limit.test)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn topk_over_count_is_heavy_hitter() {
+    // SEMANTICS: top-k by frequency → first-class heavy-hitter `TopK` intent.
+    let qe = ok("topk(10, count_over_time(http_requests_total[1m]))");
+    assert!(has(
+        &qe,
+        |i| matches!(i, AggIntent::TopK { k, .. } if *k == 10)
+    ));
+}
+
+#[test]
+fn bottomk_is_generic_sort_limit() {
+    // SEMANTICS: bottom-k → generic ascending order + limit (no sketch).
+    let qe = ok("bottomk(3, count_over_time(http_requests_total[5m]))");
+    assert!(matches!(qe.expect_non_asap(), NonASAPOp::Limit { .. }));
+}
+
+#[test]
+fn topk_over_nested_sum_preserves_weighted_topk_accuracy() {
+    // SEMANTICS (PromQL): `topk(3, sum by(x)(rate(...)))` is extremely common.
+    // The final rates are query-time values. Their ordering does not establish
+    // frequency-sketch membership semantics.
+    let qe = ok("topk(3, sum by(instance) (rate(node_cpu_seconds_total[5m])))");
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected weighted TopK aggregate, got {qe:?}");
+    };
+    assert!(matches!(
+        measures.as_slice(),
+        [AggIntent::TopK { k: 3, .. }]
+    ));
+    // The inner `sum by (instance)` survives as a cross-series Aggregate over the
+    // per-series rate — the nesting the old two-level template could not express.
+    assert!(
+        has(child, |i| matches!(i, AggIntent::Sum { .. }))
+            && has(child, |i| matches!(i, AggIntent::Rate)),
+        "inner sum-over-rate preserved, got {:?}",
+        intents(child)
+    );
+    assert!(has(&qe, |i| matches!(i, AggIntent::TopK { .. })));
+}
+
+#[test]
+fn outer_aggregate_over_nested_aggregate_nests() {
+    // `max(sum by (job) (rate(m[5m])))` — an outer cross-series reduction over a
+    // nested per-group reduction over a per-series rate: three stacked levels the
+    // flat two-level template rejected. Each level survives into the
+    // canonical tree (issue #27).
+    let qe = ok("max(sum by (job) (rate(http_requests_total[5m])))");
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate, got {qe:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Max { .. }]));
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected inner `sum by (job)` Aggregate, got {child:?}");
+    };
+    assert_eq!(
+        reduction,
+        &Reduction::by(vec![2]),
+        "job grouping survives on the inner aggregate"
+    );
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+    assert!(has(&qe, |i| matches!(i, AggIntent::Rate)), "rate preserved");
+}
+
+#[test]
+fn outer_group_key_absent_from_nested_aggregate_is_dropped() {
+    // SEMANTICS (PromQL, issue #53): aggregating `by` a label that no input
+    // series carries is valid — every series lands in one group and the
+    // (empty) label is omitted from the output. Here the inner `sum by (group)`
+    // collapses `job` away (its closed output schema is `[group, sum]`), so the
+    // outer `by (job)` groups everything into a single global partition:
+    // the query lowers with the provably-absent key dropped, exactly
+    // `sum(sum by (group)(…))`.
+    let qe = ok(r#"sum(sum by (group)(http_requests{job="api-server"})) by (job)"#);
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate, got {qe:?}");
+    };
+    assert_eq!(
+        reduction,
+        &Reduction::by(vec![]),
+        "absent `job` key dropped → global aggregate"
+    );
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+    let NonASAPOp::Aggregate { reduction, .. } = child.expect_non_asap() else {
+        panic!("expected inner `sum by (group)` Aggregate, got {child:?}");
+    };
+    assert_eq!(
+        reduction,
+        &Reduction::by(vec![2]),
+        "inner grouping on `group` survives"
+    );
+}
+
+#[test]
+fn outer_group_key_present_after_inner_aggregate_still_resolves() {
+    // The counterpart guard for #53: when the outer key IS in the inner
+    // aggregate's output (`by (job)` over `sum by (job, group)`), it must keep
+    // resolving positionally — the absent-key drop only fires on provable
+    // absence, never on a resolvable key.
+    let qe = ok("sum(sum by (job, group)(http_requests)) by (job)");
+    let NonASAPOp::Aggregate {
+        reduction, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate, got {qe:?}");
+    };
+    let NonASAPOp::Aggregate {
+        reduction: inner_reduction,
+        ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected inner Aggregate, got {child:?}");
+    };
+    // Inner output schema is [group, job, sum] (keys in label-column order,
+    // labels alphabetical on the scan) → job = col 1.
+    assert_eq!(
+        reduction,
+        &Reduction::by(vec![1]),
+        "outer `job` resolves against the inner output"
+    );
+    assert_eq!(inner_reduction.expect_reduce().len(), 2);
+}
+
+#[test]
+fn outer_group_key_over_binary_op_resolves_on_both_sides() {
+    // Issue #52: an outer aggregate's group key that appears in *neither* side of
+    // a binary op — the metric-name label `__name__`, or a plain `job` — must
+    // still resolve. Each `or` side is bound independently against its own
+    // sub-tree, so the key is seeded as an inherited column on both sides.
+    let qe = ok(r#"sum by (__name__)(metric_a{env="1"} or metric_b{env="2"})"#);
+    let NonASAPOp::Aggregate {
+        reduction, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate, got {qe:?}");
+    };
+    // `__name__` resolves to a single positional id against the binary op output.
+    assert_eq!(
+        reduction.expect_reduce().len(),
+        1,
+        "grouped by the one `__name__` key"
+    );
+    let NonASAPOp::BinaryOp { lhs, rhs, .. } = child.expect_non_asap() else {
+        panic!("expected a BinaryOp child, got {child:?}");
+    };
+    // Both independently-bound sides carry `__name__` at the same position, so
+    // the outer group key is consistent across the union.
+    let (ls, rs) = (lhs.schema.clone(), rhs.schema.clone());
+    assert_eq!(ls.column_id("__name__"), rs.column_id("__name__"));
+    assert_eq!(
+        ls.column_id("__name__"),
+        Some(reduction.expect_reduce().keys()[0])
+    );
+
+    // The general case (a plain label, not just `__name__`) also lowers.
+    assert!(matches!(
+        ok("sum by (job)(metric_a or metric_b)").expect_non_asap(),
+        NonASAPOp::Aggregate { .. }
+    ));
+}
+
+#[test]
+fn aggregate_over_binary_op_nests() {
+    // `sum(rate(a[5m]) + rate(b[5m]))` — an aggregate whose argument is a binary
+    // op over two range vectors. The old template only accepted a single inner
+    // selector/call; now the binary op lowers and the outer sum wraps it.
+    let qe = ok("sum(rate(a[5m]) + rate(b[5m]))");
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate, got {qe:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+    assert!(
+        matches!(child.expect_non_asap(), NonASAPOp::BinaryOp { .. }),
+        "argument lowers as a BinaryOp, got {child:?}"
+    );
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// J. Subqueries                            (basics §Subqueries; subquery.test)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn subquery_wraps_inner_query() {
+    // SEMANTICS: `<inst>[range:res]` evaluates the inner query across a range.
+    let qe = ok("rate(demo_api_request_duration_seconds_count[5m])[1h:]");
+    assert!(matches!(
+        qe.expect_non_asap(),
+        NonASAPOp::PromqlSubquery { .. }
+    ));
+    assert!(has(&qe, |i| matches!(i, AggIntent::Rate)));
+}
+
+#[test]
+fn over_time_of_subquery_reduces_per_series() {
+    // SEMANTICS (PromQL): `max_over_time(rate(...)[1h:])` chains a sub-query into
+    // a range-vector function — the sub-query evaluates `rate` across a 1h range,
+    // then `max_over_time` takes the max of those samples *per series*. It lowers
+    // to a per-series `Max` reduction over a `PromqlSubquery` (issue #27).
+    let qe = ok("max_over_time(rate(demo_api_request_duration_seconds_count[5m])[1h:])");
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected an Aggregate at the root, got {qe:?}");
+    };
+    assert_eq!(
+        reduction,
+        &Reduction::PerEntity,
+        "`*_over_time` has no grouping — reduces per series"
+    );
+    assert!(matches!(measures.as_slice(), [AggIntent::Max { .. }]));
+    // The reduction rides directly on the sub-query (the structural range marker
+    // that keeps it label-preserving), which wraps the inner `rate`.
+    assert!(
+        matches!(child.expect_non_asap(), NonASAPOp::PromqlSubquery { .. }),
+        "the `Max` reduces over a PromqlSubquery, got {child:?}"
+    );
+    assert!(intents(&qe).iter().any(|i| matches!(i, AggIntent::Rate)));
+}
+
+#[test]
+fn quantile_over_time_of_subquery_carries_phi() {
+    // The `quantile_over_time` φ parameter is read from arg 0; the sub-query is
+    // arg 1. It lowers to a per-series `Quantile(φ)` over the `PromqlSubquery`.
+    let qe = ok("quantile_over_time(0.9, rate(demo[5m])[1h:])");
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected an Aggregate, got {qe:?}");
+    };
+    assert!(
+        matches!(measures.as_slice(), [AggIntent::Quantile { q, .. }] if (*q - 0.9).abs() < 1e-9)
+    );
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::PromqlSubquery { .. }
+    ));
+}
+
+#[test]
+fn aggregation_over_over_time_of_subquery_keeps_labels() {
+    // `sum by (job) (max_over_time(rate(m[5m])[1h:]))` — the inner
+    // `max_over_time` is per-series (label-preserving), so the `job` label
+    // survives for the OUTER cross-series `sum by (job)` to group on. If the
+    // inner `Max` collapsed labels, `job` would not resolve here.
+    let qe = ok("sum by (job) (max_over_time(rate(demo{job=\"api\"}[5m])[1h:]))");
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate, got {qe:?}");
+    };
+    assert!(
+        matches!(reduction, Reduction::Reduce(by) if !by.is_empty()),
+        "outer `sum by (job)` groups on a label"
+    );
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+    // Inner node is the per-series `max_over_time` reduction over the subquery.
+    let NonASAPOp::Aggregate {
+        reduction: inner_reduction,
+        measures: inner_measures,
+        child: inner_child,
+        ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected inner Aggregate, got {child:?}");
+    };
+    assert_eq!(inner_reduction, &Reduction::PerEntity);
+    assert!(matches!(inner_measures.as_slice(), [AggIntent::Max { .. }]));
+    assert!(matches!(
+        inner_child.expect_non_asap(),
+        NonASAPOp::PromqlSubquery { .. }
+    ));
+}
+
+#[test]
+fn nested_subquery_from_prometheus_docs() {
+    // SEMANTICS (PromQL): the *nested sub-query* example from the official docs
+    // (<https://prometheus.io/docs/prometheus/latest/querying/examples/>):
+    //
+    //   max_over_time(deriv(rate(distance_covered_total[5s])[30s:5s])[10m:])
+    //
+    // Two stacked sub-queries, each feeding a range-vector function; the outer
+    // `[10m:]` uses the **default resolution** (no explicit step). Each level
+    // lowers to its own node, so the whole spine pins as:
+    //
+    //   Max ∘ PromqlSubquery{10m, res: None} ∘ Deriv ∘ PromqlSubquery{30s, res: 5s}
+    //       ∘ Rate ∘ TimeRange{5s} ∘ Scan
+    //
+    // Every reduction is per-series (no grouping), so the output schema stays
+    // the label-preserving `[ts, value]`.
+    let qe = ok("max_over_time(deriv(rate(distance_covered_total[5s])[30s:5s])[10m:])");
+
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected `max_over_time` Aggregate at the root, got {qe:?}");
+    };
+    assert_eq!(reduction, &Reduction::PerEntity);
+    assert!(matches!(measures.as_slice(), [AggIntent::Max { .. }]));
+
+    let NonASAPOp::PromqlSubquery {
+        range,
+        resolution,
+        child,
+    } = child.expect_non_asap()
+    else {
+        panic!("expected the outer `[10m:]` PromqlSubquery, got {child:?}");
+    };
+    assert_eq!(*range, Duration::from_secs(600));
+    assert_eq!(*resolution, None, "`[10m:]` keeps the default resolution");
+
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected the `deriv` Aggregate, got {child:?}");
+    };
+    assert_eq!(reduction, &Reduction::PerEntity);
+    assert!(matches!(measures.as_slice(), [AggIntent::Deriv]));
+
+    let NonASAPOp::PromqlSubquery {
+        range,
+        resolution,
+        child,
+    } = child.expect_non_asap()
+    else {
+        panic!("expected the inner `[30s:5s]` PromqlSubquery, got {child:?}");
+    };
+    assert_eq!(*range, Duration::from_secs(30));
+    assert_eq!(*resolution, Some(Duration::from_secs(5)));
+
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected the `rate` Aggregate, got {child:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
+    let NonASAPOp::TimeRange { range, .. } = child.expect_non_asap() else {
+        panic!("expected the `[5s]` TimeRange under rate, got {child:?}");
+    };
+    assert_eq!(*range, Duration::from_secs(5));
+
+    // Per-series end to end: the schema keeps the (ts, value) floor and stays open.
+    let schema = qe.schema.clone();
+    assert_eq!(
+        schema
+            .fields
+            .iter()
+            .map(|c| c.name.as_str())
+            .collect::<Vec<_>>(),
+        vec!["ts", "value"],
+    );
+    assert!(!schema.closed, "per-series chain never freezes the schema");
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// K. Time-shift modifiers                  (basics §Offset/@; at_modifier.test)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn offset_modifier_lowers_to_a_time_shift() {
+    // SEMANTICS (PromQL, issue #40): `offset 5m` shifts the lookback 5m into the
+    // past — a `TimeShift` wrapper over the selector (signed ms; a negative
+    // offset shifts forward). Schema is unchanged (the shift only moves *when*).
+    let qe = ok("http_requests_total offset 5m");
+    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
+        panic!("expected an ingestion TimeRange, got {qe:?}");
+    };
+    let NonASAPOp::TimeShift { shift, child } = child.expect_non_asap() else {
+        panic!("expected a TimeShift, got {qe:?}");
+    };
+    assert_eq!(shift.offset_ms, 300_000);
+    assert!(shift.at.is_none());
+    assert!(matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }));
+
+    // `offset -5m` shifts forward → negative ms.
+    let qe = ok("http_requests_total offset -5m");
+    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
+        panic!("expected an ingestion TimeRange");
+    };
+    let NonASAPOp::TimeShift { shift, .. } = child.expect_non_asap() else {
+        panic!("expected a TimeShift");
+    };
+    assert_eq!(shift.offset_ms, -300_000);
+}
+
+#[test]
+fn at_modifier_lowers_to_a_time_shift() {
+    // SEMANTICS (PromQL, issue #40): `@ <ts>` pins the evaluation to an absolute
+    // instant (PromQL seconds → IR milliseconds); `@ start()` / `@ end()` anchor
+    // to the query range bounds.
+    let qe = ok("http_requests_total @ 1609746000");
+    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
+        panic!("expected an ingestion TimeRange");
+    };
+    let NonASAPOp::TimeShift { shift, .. } = child.expect_non_asap() else {
+        panic!("expected a TimeShift for `@ <ts>`");
+    };
+    assert_eq!(shift.at, Some(AtModifier::Timestamp(1_609_746_000_000)));
+    assert_eq!(shift.offset_ms, 0);
+
+    let qe = ok("http_requests_total @ start()");
+    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
+        panic!("expected an ingestion TimeRange");
+    };
+    let NonASAPOp::TimeShift { shift, .. } = child.expect_non_asap() else {
+        panic!("expected a TimeShift for `@ start()`");
+    };
+    assert_eq!(shift.at, Some(AtModifier::Start));
+
+    // Offset and `@` compose: `@ end() offset 5m` carries both.
+    let qe = ok("http_requests_total @ end() offset 5m");
+    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
+        panic!("expected an ingestion TimeRange, got {qe:?}");
+    };
+    let NonASAPOp::TimeShift { shift, .. } = child.expect_non_asap() else {
+        panic!("expected a TimeShift, got {qe:?}");
+    };
+    assert_eq!(shift.at, Some(AtModifier::End));
+    assert_eq!(shift.offset_ms, 300_000);
+}
+
+#[test]
+fn offset_on_a_ranged_selector_wraps_inside_the_time_range() {
+    // `rate(m[5m] offset 1h)` — the offset is on the ranged selector, so the
+    // `TimeShift` sits *under* the `TimeRange` (the 5m window is taken at the
+    // shifted time), and the whole thing under the per-series `Rate` (#40).
+    let qe = ok("rate(http_requests_total[5m] offset 1h)");
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected the rate Aggregate, got {qe:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
+    let NonASAPOp::TimeRange { child, .. } = child.expect_non_asap() else {
+        panic!("expected a TimeRange under rate, got {child:?}");
+    };
+    let NonASAPOp::TimeShift { shift, child } = child.expect_non_asap() else {
+        panic!("expected a TimeShift under the TimeRange, got {child:?}");
+    };
+    assert_eq!(shift.offset_ms, 3_600_000);
+    assert!(matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }));
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// L. Unsupported functions                 (functions.test) — clean rejection
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn unsupported_functions_are_rejected() {
+    // These parse fine but have no intent-algebra lowering yet. Each must return
+    // a clean LoweringError rather than mislower.
+    for q in [
+        "step()",
+        "range()",
+        r#"histogram_quantiles("le", 0.5, 0.9, x)"#,
+        // NOTE: counter-derivatives (#44), math/trig (#45, §O), presence (#47,
+        // §P), time/calendar (#46, §Q), vector/scalar (#48, §R),
+        // label_replace/label_join (#50, §T) and the extra range reducers +
+        // sort family (#51, §U) now lower — see those sections. `info` (#84),
+        // `min_of`/`max_of` (#89) are pinned in §R / §U.
+    ] {
+        let _ = rejected(q);
+    }
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// M. Counter-derivative range functions     (functions.test; issue #44)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn count_over_time_value_column_is_float64() {
+    // #69: a per-series range reduction produces a PromQL sample value, which is
+    // always float64. `count_over_time`'s `Count` intent types `Int64`, but the
+    // derived `value` column must be `Float64` like every other range reducer.
+    let schema = ok("count_over_time(m[5m])").schema.clone();
+    let value = schema
+        .fields
+        .iter()
+        .find(|c| c.name == "value")
+        .expect("value column");
+    assert_eq!(value.dtype, DataType::Float64);
+}
+
+#[test]
+fn counter_derivative_functions_lower_to_distinct_intents() {
+    // Each range function reduces one series' window to one value per series
+    // (label-preserving), riding on a `TimeRange`, and carries its OWN intent —
+    // deliberately not aliased to rate/increase/count.
+    for (q, want) in [
+        ("changes(m[15m])", AggIntent::Changes),
+        ("delta(m[5m])", AggIntent::Delta),
+        ("idelta(m[5m])", AggIntent::IDelta),
+        ("deriv(m[1h])", AggIntent::Deriv),
+        ("resets(m[1h])", AggIntent::Resets),
+    ] {
+        let qe = ok(q);
+        let NonASAPOp::Aggregate {
+            reduction,
+            measures,
+            child,
+            ..
+        } = qe.expect_non_asap()
+        else {
+            panic!("expected an Aggregate for {q:?}, got {qe:?}");
+        };
+        assert_eq!(
+            reduction,
+            &Reduction::PerEntity,
+            "{q}: per-series, no grouping"
+        );
+        assert_eq!(
+            measures.as_slice(),
+            std::slice::from_ref(&want),
+            "{q}: wrong intent"
+        );
+        assert!(
+            matches!(child.expect_non_asap(), NonASAPOp::TimeRange { .. }),
+            "{q}: reduction rides on a TimeRange, got {child:?}"
+        );
+    }
+}
+
+#[test]
+fn predict_linear_carries_horizon_seconds() {
+    // `predict_linear(v[w], t)` — the 2nd (scalar) arg is the prediction horizon
+    // in seconds; it must be carried in the intent (it changes the result).
+    let qe = ok("predict_linear(node_filesystem_avail_bytes[3h], 86400)");
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected an Aggregate, got {qe:?}");
+    };
+    assert_eq!(
+        measures.as_slice(),
+        &[AggIntent::PredictLinear { seconds: 86400.0 }]
+    );
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
+}
+
+#[test]
+fn double_exponential_smoothing_carries_factors() {
+    let want = AggIntent::DoubleExpSmoothing {
+        smoothing: 0.5,
+        trend: 0.3,
+    };
+    let a = ok("double_exponential_smoothing(m[10m], 0.5, 0.3)");
+    assert_eq!(intents(&a).as_slice(), std::slice::from_ref(&want));
+}
+
+#[test]
+fn aggregation_over_counter_derivative_keeps_labels() {
+    // A counter-derivative is per-series (label-preserving), so an outer
+    // `sum by (job)` can group on a label the inner `changes` preserved.
+    let qe = ok(r#"sum by (job) (changes(m{job="api"}[15m]))"#);
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate, got {qe:?}");
+    };
+    assert!(
+        matches!(reduction, Reduction::Reduce(by) if !by.is_empty()),
+        "outer sum groups on job"
+    );
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+    assert!(intents(&qe).iter().any(|i| matches!(i, AggIntent::Changes)));
+    let _ = child;
+}
+
+#[test]
+fn outer_stat_over_counter_derivative_nests_two_levels() {
+    // A cross-series stat over a counter-derivative is a genuine two-level
+    // reduction: the derivative runs per series (inner), the stat aggregates
+    // across series (outer). They must not collapse into one node — and a
+    // grouped outer (`avg by (dc)`) must resolve its key against the labels the
+    // inner reduction preserved, threading any scalar param (predict horizon).
+    let qe = ok("avg by (dc) (predict_linear(m[3h], 3600))");
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate, got {qe:?}");
+    };
+    assert!(
+        matches!(reduction, Reduction::Reduce(by) if !by.is_empty()),
+        "outer `avg by (dc)` groups on a label"
+    );
+    assert!(matches!(measures.as_slice(), [AggIntent::Avg { .. }]));
+    let NonASAPOp::Aggregate {
+        reduction: inner_reduction,
+        measures: inner_measures,
+        ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected inner per-series Aggregate, got {child:?}");
+    };
+    assert_eq!(
+        inner_reduction,
+        &Reduction::PerEntity,
+        "inner derivative stays per-series"
+    );
+    assert_eq!(
+        inner_measures.as_slice(),
+        std::slice::from_ref(&AggIntent::PredictLinear { seconds: 3600.0 })
+    );
+}
+
+#[test]
+fn topk_over_counter_derivative_is_generic_sort_limit() {
+    // `topk(k, deriv(...))` ranks the per-series derivative values — a generic
+    // `Sort + Limit`, NOT a heavy-hitter `TopK` (that's only `count_over_time`).
+    let qe = ok("topk(3, deriv(m[5m]))");
+    let NonASAPOp::Limit {
+        n: Some(n), child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected Limit, got {qe:?}");
+    };
+    assert_eq!(*n, 3);
+    assert!(matches!(child.expect_non_asap(), NonASAPOp::Sort { .. }));
+    assert!(intents(&qe).iter().any(|i| matches!(i, AggIntent::Deriv)));
+    assert!(
+        !intents(&qe)
+            .iter()
+            .any(|i| matches!(i, AggIntent::TopK { .. })),
+        "counter-derivative topk is generic ranking, not a heavy-hitter sketch"
+    );
+}
+
+#[test]
+fn counter_derivative_composes_in_binary_ops() {
+    // As a vector operand: `delta(a[5m]) / delta(b[5m])` is a BinaryOp of two
+    // per-series Delta reductions.
+    let ratio = ok("delta(a[5m]) / delta(b[5m])");
+    let NonASAPOp::BinaryOp {
+        operator: BinaryOperator { kind: op, .. },
+        lhs,
+        rhs,
+        ..
+    } = ratio.expect_non_asap()
+    else {
+        panic!("expected BinaryOp, got {ratio:?}");
+    };
+    assert_eq!(*op, BinaryOpKind::Arithmetic(ArithmeticOpKind::Div));
+    assert!(
+        matches!(lhs.expect_non_asap(), NonASAPOp::Aggregate { measures, .. } if measures.as_slice() == [AggIntent::Delta])
+    );
+    assert!(
+        matches!(rhs.expect_non_asap(), NonASAPOp::Aggregate { measures, .. } if measures.as_slice() == [AggIntent::Delta])
+    );
+
+    // Under an aggregate over a binary op mixing a counter-derivative with
+    // another per-series function: `sum(rate(m[5m]) + changes(m[5m]))`.
+    let mixed = ok("sum(rate(m[5m]) + changes(m[5m]))");
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = mixed.expect_non_asap()
+    else {
+        panic!("expected Aggregate, got {mixed:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::BinaryOp { .. }
+    ));
+    assert!(intents(&mixed).iter().any(|i| matches!(i, AggIntent::Rate)));
+    assert!(intents(&mixed)
+        .iter()
+        .any(|i| matches!(i, AggIntent::Changes)));
+}
+
+#[test]
+fn range_functions_over_a_subquery_reduce_per_series() {
+    // Issue #55 — the whole range-vector family accepts a sub-query argument
+    // (generalizing `*_over_time`, #42): `rate`/`increase`/`irate` and the
+    // counter-derivatives. Each lowers to a per-series `Aggregate{[f]}` directly
+    // over the `PromqlSubquery` — the sub-query is the range context, so there is NO
+    // separate `TimeRange` (that would double the range).
+    for (q, want) in [
+        ("rate(sum(m)[5m:])", AggIntent::Rate),
+        ("increase(sum(m)[5m:])", AggIntent::Increase),
+        ("irate(sum(m)[5m:])", AggIntent::IRate),
+        ("changes(rate(m[5m])[1h:])", AggIntent::Changes),
+        ("delta(sum(m)[5m:])", AggIntent::Delta),
+        ("deriv(sum(m)[10m:])", AggIntent::Deriv),
+        ("resets(sum(m)[5m:])", AggIntent::Resets),
+    ] {
+        let qe = ok(q);
+        let NonASAPOp::Aggregate {
+            reduction,
+            measures,
+            child,
+            ..
+        } = qe.expect_non_asap()
+        else {
+            panic!("{q}: expected an Aggregate, got {qe:?}");
+        };
+        assert_eq!(
+            reduction,
+            &Reduction::PerEntity,
+            "{q}: per-series, no grouping"
+        );
+        assert_eq!(
+            measures.as_slice(),
+            std::slice::from_ref(&want),
+            "{q}: wrong intent"
+        );
+        assert!(
+            matches!(child.expect_non_asap(), NonASAPOp::PromqlSubquery { .. }),
+            "{q}: reduces directly over the PromqlSubquery (no TimeRange), got {child:?}"
+        );
+    }
+}
+
+#[test]
+fn predict_linear_and_double_exp_over_a_subquery_carry_params() {
+    // The scalar params survive the sub-query path.
+    let pl = ok("predict_linear(sum(m)[1h:], 3600)");
+    assert!(intents(&pl).iter().any(
+        |i| matches!(i, AggIntent::PredictLinear { seconds } if (*seconds - 3600.0).abs() < 1e-9)
+    ));
+    let de = ok("double_exponential_smoothing(sum(m)[10m:], 0.5, 0.3)");
+    assert!(intents(&de).iter().any(|i| matches!(
+        i,
+        AggIntent::DoubleExpSmoothing { smoothing, trend }
+            if (*smoothing - 0.5).abs() < 1e-9 && (*trend - 0.3).abs() < 1e-9
+    )));
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// N. Native-histogram accessors            (functions.test; issue #43)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn histogram_quantile_classic_bucket_vs_native() {
+    // Two lowerings of `histogram_quantile(φ, …)`: the classic cumulative-bucket
+    // form → exact `HistogramQuantile`; native samples require a new type.
+    // The classic form is recognised by
+    // `by (le)`, a `_bucket` metric, or an `le` matcher (issue #43).
+    for classic in [
+        "histogram_quantile(0.9, sum by (le) (rate(x_bucket[5m])))",
+        "histogram_quantile(0.9, rate(x_bucket[5m]))", // bare _bucket metric
+        r#"histogram_quantile(0.9, rate(x{le="0.5"}[5m]))"#, // le matcher
+    ] {
+        let qe = ok(classic);
+        assert!(
+            has(
+                &qe,
+                |i| matches!(i, AggIntent::HistogramQuantile { q, .. } if (*q - 0.9).abs() < 1e-9)
+            ),
+            "classic bucket form → HistogramQuantile: {classic}"
+        );
+        assert!(
+            !has(&qe, |i| matches!(i, AggIntent::Quantile { .. })),
+            "{classic}"
+        );
+    }
+    for native in [
+        "histogram_quantile(0.9, my_native_histogram)",
+        "histogram_quantile(0.9, request_duration_seconds)", // raw samples (your extension)
+    ] {
+        rejected(native);
+    }
+}
+
+#[test]
+fn native_histogram_accessors_are_explicit_gaps() {
+    // Native histogram samples have no typed representation yet.
+    for q in [
+        "histogram_count(v)",
+        "histogram_sum(v)",
+        "histogram_avg(v)",
+        "histogram_stddev(v)",
+        "histogram_stdvar(v)",
+    ] {
+        rejected(q);
+    }
+}
+
+#[test]
+fn histogram_fraction_is_an_explicit_gap() {
+    rejected("histogram_fraction(0, 0.2, v)");
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// O. Math / trig scalar-transform functions (functions.test; issue #45)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn math_functions_lower_to_typed_scalar_projections() {
+    for name in [
+        "abs", "ceil", "floor", "sqrt", "ln", "log2", "sgn", "sin", "atanh", "deg", "rad",
+    ] {
+        let query = ok(&format!("{name}(v)"));
+        assert!(
+            matches!(support::sample_expression(&query),ScalarExpr::FunctionCall { name:n,args } if n==&format!("promql_{name}") && args.len()==1)
+        );
+        query.validate_structure().unwrap();
+    }
+}
+
+#[test]
+fn clamp_and_round_carry_their_params() {
+    for (query, params) in [
+        ("clamp(v,0,100)", vec![0.0, 100.0]),
+        ("clamp_min(v,1)", vec![1.0]),
+        ("clamp_max(v,5)", vec![5.0]),
+        ("round(v)", vec![1.0]),
+        ("round(v,5)", vec![5.0]),
+    ] {
+        let node = ok(query);
+        let ScalarExpr::FunctionCall { args, .. } = support::sample_expression(&node) else {
+            panic!()
+        };
+        assert_eq!(
+            args.iter().skip(1).map(promql_scalar).collect::<Vec<_>>(),
+            params.into_iter().map(Some).collect::<Vec<_>>()
+        );
+    }
+}
+
+#[test]
+fn pi_lowers_to_a_scalar_constant() {
+    // `pi()` is the constant π — a `ScalarExpr` leaf, not a `Math` intent.
+    assert!(promql_scalar(&support::scalar_root("pi()"))
+        .is_some_and(|v| (v - std::f64::consts::PI).abs() < 1e-12));
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// P. Presence functions                     (functions.test; issue #47)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn presence_functions_lower_to_presence_intents() {
+    for (q, want) in [
+        (r#"absent(up{job="x"})"#, AggIntent::Absent),
+        ("absent_over_time(m[1h])", AggIntent::AbsentOverTime),
+        ("present_over_time(m[5m])", AggIntent::PresentOverTime),
+    ] {
+        let qe = ok(q);
+        assert!(intents(&qe).contains(&want), "{q}: got {:?}", intents(&qe));
+    }
+}
+
+#[test]
+fn absent_keeps_matcher_labels_for_the_synthesized_output() {
+    // `absent(v)` synthesizes its output labels from `v`'s equality matchers, so
+    // those labels must survive into the schema — here `job` from `{job="x"}`.
+    let qe = ok(r#"absent(up{job="x"})"#);
+    let cols = qe.schema.clone();
+    assert!(
+        cols.fields.iter().any(|c| c.name == "job"),
+        "matcher label `job` kept, got {:?}",
+        cols.fields.iter().map(|c| &c.name).collect::<Vec<_>>()
+    );
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// Q. Time / calendar functions            (functions.test; issue #46)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn time_lowers_to_the_eval_time_scalar() {
+    assert!(matches!(
+        support::scalar_root("time()"),
+        ScalarExpr::EvalTimestamp
+    ));
+}
+
+#[test]
+fn time_minus_vector_is_the_uptime_pattern() {
+    let qe = ok("time() - process_start_time_seconds");
+    assert!(
+        matches!(support::sample_expression(&qe), ScalarExpr::Arithmetic { op: ArithmeticOpKind::Sub, left, .. } if matches!(left.as_ref(), ScalarExpr::EvalTimestamp))
+    );
+    assert!(qe.schema.time_index.is_some());
+}
+
+#[test]
+fn calendar_functions_lower_to_time_fn_intents() {
+    assert!(has(&ok("timestamp(up)"), |i| *i
+        == AggIntent::TimeFn(TimeFunc::Timestamp)));
+    for name in [
+        "minute",
+        "hour",
+        "day_of_week",
+        "day_of_month",
+        "day_of_year",
+        "month",
+        "year",
+        "days_in_month",
+    ] {
+        let query = ok(&format!("{name}(v)"));
+        assert!(
+            matches!(support::sample_expression(&query),ScalarExpr::FunctionCall { name:n,args } if n==&format!("promql_{name}") && args.len()==1)
+        );
+    }
+}
+
+#[test]
+fn no_arg_calendar_function_reads_the_eval_time() {
+    let query = ok("day_of_week()");
+    let NonASAPOp::Project { child, .. } = query.expect_non_asap() else {
+        panic!()
+    };
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::PromqlVectorFromScalar(ScalarExpr::EvalTimestamp)
+    ));
+    assert!(
+        matches!(support::sample_expression(&query),ScalarExpr::FunctionCall { name,.. } if name=="promql_day_of_week")
+    );
+}
+
+#[test]
+fn timestamp_composes_under_an_outer_aggregation() {
+    // `sum by (job) (timestamp(up))` — the per-series `timestamp` transform sits
+    // below an ordinary grouped sum. Both intents must appear in the tree.
+    let qe = ok("sum by (job) (timestamp(up))");
+    assert!(has(&qe, |i| *i == AggIntent::TimeFn(TimeFunc::Timestamp)));
+    assert!(has(&qe, |i| matches!(i, AggIntent::Sum { .. })));
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// R. Type-conversion functions: vector() / scalar()   (functions.test; issue #48)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn vector_promotes_a_scalar_to_a_vector() {
+    // SEMANTICS: `vector(s)` is the scalar→instant-vector bridge — a label-less
+    // single series carrying the scalar's value.
+    let qe = ok("vector(1)");
+    let NonASAPOp::PromqlVectorFromScalar(inner) = qe.expect_non_asap() else {
+        panic!("expected PromqlVectorFromScalar, got {qe:?}");
+    };
+    assert!(matches!(inner, ScalarExpr::Literal(ScalarValue::Float64(v)) if *v == 1.0));
+    // Vector-typed: schema has a time index (a scalar leaf has none).
+    let sch = qe.schema.clone();
+    assert!(sch.time_index.is_some());
+    assert!(sch.fields.iter().any(|c| c.name == "value"));
+}
+
+#[test]
+fn scalar_collapses_a_vector_to_a_scalar() {
+    let qe = support::scalar_root("scalar(node_load1)");
+    let ScalarExpr::PromqlScalarFromVector(inner) = &qe else {
+        panic!()
+    };
+    assert_eq!(first_scan(inner).0, "node_load1");
+}
+
+#[test]
+fn vector_zero_is_a_vector_operand_of_a_set_op() {
+    // `up or vector(0)` — the dead-man's-switch. `or` is a set op between two
+    // vectors, so `vector(0)` must be a vector (a `PromqlVectorFromScalar`), never a
+    // folded scalar operand.
+    let qe = ok("up or vector(0)");
+    let NonASAPOp::BinaryOp {
+        operator: BinaryOperator { kind: op, .. },
+        rhs,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected a BinaryOp, got {qe:?}");
+    };
+    assert_eq!(*op, BinaryOpKind::Set(PromQLVectorSetOpKind::Or));
+    assert!(matches!(
+        rhs.expect_non_asap(),
+        NonASAPOp::PromqlVectorFromScalar(_)
+    ));
+}
+
+#[test]
+fn scalar_of_a_vector_feeds_a_threshold_comparison() {
+    let qe = ok("node_load1 > scalar(node_cpu_count)");
+    let ScalarExpr::Compare { right, .. } = support::sample_expression(&qe) else {
+        panic!()
+    };
+    assert!(matches!(
+        right.as_ref(),
+        ScalarExpr::PromqlScalarFromVector(_)
+    ));
+    assert!(qe.schema.time_index.is_some());
+}
+
+#[test]
+fn info_lowers_to_a_label_enrichment_join() {
+    // `info(v, [selector])` is a label-enrichment *join* against the info
+    // metric(s) — it lowers to an `PromqlInfoEnrich` over the (unchanged) input vector
+    // (issue #84). The value/time axis pass through; the enriched labels are
+    // runtime, so the schema stays the child's.
+    let qe = ok("info(rate(http_requests_total[5m]))");
+    let NonASAPOp::PromqlInfoEnrich { selector, child } = qe.expect_non_asap() else {
+        panic!("expected an PromqlInfoEnrich, got {qe:?}");
+    };
+    assert!(selector.is_empty(), "no selector → default target_info");
+    // The child is the untouched input (a per-series rate reduction here).
+    assert!(has(child, |i| *i == AggIntent::Rate));
+    assert!(qe.schema.clone().time_index.is_some());
+}
+
+#[test]
+fn info_selector_carries_the_info_side_matchers() {
+    // `info(v, {__name__=~".+_info", data=~".+"})` — the selector picks the info
+    // metric(s) via `__name__` and constrains the data labels. Regex / `__name__`
+    // matchers are kept symbolically (not run through the single-metric selector
+    // path).
+    let qe = ok(r#"info(build_info, {__name__=~".+_info", another_data=~".+"})"#);
+    let NonASAPOp::PromqlInfoEnrich { selector, .. } = qe.expect_non_asap() else {
+        panic!("expected an PromqlInfoEnrich, got {qe:?}");
+    };
+    assert_eq!(
+        selector.len(),
+        2,
+        "both selector matchers kept: {selector:?}"
+    );
+    assert!(selector
+        .iter()
+        .any(|m| m.label == "__name__" && m.op == CompareOpKind::Regex));
+    assert!(selector.iter().any(|m| m.label == "another_data"));
+}
+
+#[test]
+fn info_composes_under_an_aggregation_and_over_a_time_shift() {
+    // `sum(info(m))` — enrichment first, then a cross-series sum over it.
+    assert!(has(&ok("sum(info(node_uname_info))"), |i| matches!(
+        i,
+        AggIntent::Sum { .. }
+    )));
+    // `offset` / `@` on the input now lower to a `TimeShift` under the info-join
+    // (issue #40) — the enrichment composes over the shifted selector.
+    assert!(matches!(
+        ok("info(metric @ 60)").expect_non_asap(),
+        NonASAPOp::PromqlInfoEnrich { .. }
+    ));
+    assert!(matches!(
+        ok("info(metric offset 1m)").expect_non_asap(),
+        NonASAPOp::PromqlInfoEnrich { .. }
+    ));
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// S. Extended aggregation operators: group / count_values (aggregators.test; #49)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn group_lowers_to_a_constant_group_intent() {
+    // SEMANTICS: `group(v)` yields a constant 1 per group — a distinct intent,
+    // NOT folded onto `sum` (which would return the value sum instead of 1).
+    let qe = ok("group(up)");
+    let NonASAPOp::Aggregate { measures, .. } = qe.expect_non_asap() else {
+        panic!("expected an Aggregate, got {qe:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Group]));
+    // Output column is the constant-1 `group` value.
+    let sch = qe.schema.clone();
+    assert!(sch.fields.iter().any(|c| c.name == "group"));
+}
+
+#[test]
+fn group_by_keeps_the_grouping_keys() {
+    // `group by (job) (up)` — the grouping keys ride on `Aggregate.by`.
+    let qe = ok("group by (job) (up)");
+    let sch = qe.schema.clone();
+    assert!(sch.fields.iter().any(|c| c.name == "job"));
+    assert!(has(&qe, |i| *i == AggIntent::Group));
+}
+
+#[test]
+fn count_values_groups_by_value_and_synthesizes_a_label() {
+    // SEMANTICS: `count_values("l", v)` groups the input series by their sample
+    // value, counts each distinct value, and emits that value as a new label
+    // `l`. The intent carries the label; schema gains a `Utf8` `l` column.
+    let qe = ok(r#"count_values("version", build_version)"#);
+    let NonASAPOp::Aggregate { measures, .. } = qe.expect_non_asap() else {
+        panic!("expected an Aggregate, got {qe:?}");
+    };
+    assert!(
+        matches!(measures.as_slice(), [AggIntent::CountValues { label }] if label == "version")
+    );
+    let sch = qe.schema.clone();
+    let version = sch
+        .fields
+        .iter()
+        .find(|c| c.name == "version")
+        .expect("synthesized `version` label column");
+    assert_eq!(
+        version.dtype,
+        DataType::Utf8,
+        "the value becomes a string label"
+    );
+    assert!(
+        sch.fields.iter().any(|c| c.name == "count"),
+        "and a count column"
+    );
+}
+
+#[test]
+fn count_values_accepts_a_parenthesised_label_and_by_grouping() {
+    // `count_values by (job) ((("v")), m)` — nested parens around the string
+    // param, plus `by` grouping. Both survive.
+    let qe = ok(r#"count_values by (job) ((("v")), m)"#);
+    assert!(has(
+        &qe,
+        |i| matches!(i, AggIntent::CountValues { label } if label == "v")
+    ));
+    let sch = qe.schema.clone();
+    assert!(sch.fields.iter().any(|c| c.name == "job"));
+    assert!(sch.fields.iter().any(|c| c.name == "v"));
+}
+
+#[test]
+fn count_values_label_colliding_with_a_group_key_is_not_duplicated() {
+    // `count_values by (job)("job", v)` — the synthesized label name collides
+    // with a group-by key. PromQL's synthesized label takes precedence; the
+    // output must carry a single `job` column, never two.
+    let qe = ok(r#"count_values by (job) ("job", version)"#);
+    let sch = qe.schema.clone();
+    let jobs = sch.fields.iter().filter(|c| c.name == "job").count();
+    assert_eq!(jobs, 1, "collision deduped, got {:?}", sch.fields);
+    assert!(sch.fields.iter().any(|c| c.name == "count"));
+}
+
+#[test]
+fn limitk_and_limit_ratio_lower_to_series_sampling() {
+    // `limitk`/`limit_ratio` are series-*sampling* selection — a subset of whole
+    // series kept unchanged (NOT a ranking), so they lower to the dedicated
+    // `PromqlSeriesSample` node, never `topk`'s `Sort → Limit` (issue #86).
+    assert!(matches!(
+        ok("limitk(2, http_requests)").expect_non_asap(),
+        NonASAPOp::PromqlSeriesSample {
+            kind: SampleKind::LimitK(2),
+            ..
+        }
+    ));
+    assert!(matches!(
+        ok("limit_ratio(0.1, http_requests)").expect_non_asap(),
+        NonASAPOp::PromqlSeriesSample { kind: SampleKind::LimitRatio(r), .. } if (r - 0.1).abs() < 1e-9
+    ));
+    // Series-preserving: the output schema equals the input's (ts, value).
+    let sch = ok("limitk(2, http_requests)").schema.clone();
+    assert!(sch.fields.iter().any(|c| c.name == "value"));
+    assert!(sch.time_index.is_some());
+}
+
+#[test]
+fn limit_ratio_keeps_a_negative_ratio_and_clamps_out_of_range() {
+    // A negative ratio selects the complementary fraction — it must survive, not
+    // be normalised away. Out-of-range magnitudes clamp to [-1, 1] (Prometheus).
+    assert!(matches!(
+        ok("limit_ratio(-0.5, http_requests)").expect_non_asap(),
+        NonASAPOp::PromqlSeriesSample { kind: SampleKind::LimitRatio(r), .. } if (r + 0.5).abs() < 1e-9
+    ));
+    assert!(matches!(
+        ok("limit_ratio(1.1, http_requests)").expect_non_asap(),
+        NonASAPOp::PromqlSeriesSample { kind: SampleKind::LimitRatio(r), .. } if (r - 1.0).abs() < 1e-9
+    ));
+}
+
+#[test]
+fn limitk_by_carries_the_grouping_and_composes_in_a_set_op() {
+    // `limitk by (group)` samples per group; the grouping label is seeded.
+    let qe = ok("limitk by (group) (2, http_requests)");
+    let NonASAPOp::PromqlSeriesSample { by, .. } = qe.expect_non_asap() else {
+        panic!("expected a PromqlSeriesSample, got {qe:?}");
+    };
+    assert!(!by.is_empty(), "grouped sampling keeps its `by` keys");
+    // `count(limitk(2, v) and v)` — the surviving series' identity matters, so
+    // the PromqlSeriesSample must be preserved under the set op (it must lower, not reject).
+    assert!(has(
+        &ok("count(limitk(2, http_requests) and http_requests)"),
+        |i| matches!(i, AggIntent::Count { .. })
+    ));
+}
+
+#[test]
+fn dynamic_and_non_finite_sample_params_are_rejected() {
+    // A dynamic k/ratio (not a compile-time constant) or a NaN can't be a static
+    // `PromqlSeriesSample` param — rejected rather than mislowered.
+    let _ = rejected("limitk(NaN, http_requests)");
+    let _ = rejected("limitk(scalar(foo), http_requests)");
+    let _ = rejected("limit_ratio(time() % 17 / 17, http_requests)");
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// T. Label-rewrite functions: label_replace / label_join   (functions.test; #50)
+// ─────────────────────────────────────────────────────────────────────────────
+
+/// Descend single-child nodes to the first `PromqlRelabel`.
+fn first_relabel(e: &OperatorNode) -> &OperatorNode {
+    match e.expect_non_asap() {
+        NonASAPOp::PromqlRelabel { .. } => e,
+        NonASAPOp::Aggregate { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::TimeRange { child, .. }
+        | NonASAPOp::TimeShift { child, .. } => first_relabel(child),
+        other => panic!("no PromqlRelabel reachable from {other:?}"),
+    }
+}
+
+/// True when `value` is a `FunctionCall` with the given name.
+fn is_fn_named(value: &ScalarExpr, name: &str) -> bool {
+    matches!(value, ScalarExpr::FunctionCall { name: n, .. } if n == name)
+}
+
+#[test]
+fn label_replace_is_a_relabel_over_the_vector() {
+    // SEMANTICS: `label_replace(v, dst, repl, src, regex)` rewrites the `dst`
+    // label per series from a regex over `src`; the sample value is untouched.
+    let qe = ok(r#"label_replace(up, "host", "$1", "instance", "(.+):.*")"#);
+    let NonASAPOp::PromqlRelabel { dst, value, child } = qe.expect_non_asap() else {
+        panic!("expected a PromqlRelabel, got {qe:?}");
+    };
+    assert_eq!(dst, "host");
+    // The child is the untouched vector.
+    let (metric, _) = first_scan(child);
+    assert_eq!(metric, "up");
+    // The value expression is a `label_replace` fn reading the `src` label.
+    assert!(is_fn_named(value, "label_replace"));
+    // Output: the child's columns + the synthesized `host` label; value & ts kept.
+    let sch = qe.schema.clone();
+    assert!(sch.fields.iter().any(|c| c.name == "host"));
+    assert!(sch.fields.iter().any(|c| c.name == "value"));
+    assert!(sch.time_index.is_some(), "the vector's time axis survives");
+}
+
+#[test]
+fn label_join_concatenates_source_labels() {
+    // SEMANTICS: `label_join(v, dst, sep, src…)` joins the source labels with
+    // `sep` into `dst`.
+    let qe = ok(r#"label_join(up, "combined", "-", "job", "instance")"#);
+    let NonASAPOp::PromqlRelabel { dst, value, .. } = qe.expect_non_asap() else {
+        panic!("expected a PromqlRelabel, got {qe:?}");
+    };
+    assert_eq!(dst, "combined");
+    assert!(is_fn_named(value, "label_join"));
+    let sch = qe.schema.clone();
+    assert!(sch.fields.iter().any(|c| c.name == "combined"));
+}
+
+#[test]
+fn label_replace_composes_under_an_aggregation() {
+    // `sum by (host) (label_replace(up, "host", "$1", "instance", "(.+):.*"))` —
+    // relabel first, then group by the synthesized label.
+    let qe = ok(r#"sum by (host) (label_replace(up, "host", "$1", "instance", "(.+):.*"))"#);
+    // A PromqlRelabel sits below the outer Sum.
+    let relabel = first_relabel(&qe);
+    assert!(
+        matches!(relabel.expect_non_asap(), NonASAPOp::PromqlRelabel { dst, .. } if dst == "host")
+    );
+    assert!(has(&qe, |i| matches!(i, AggIntent::Sum { .. })));
+    let sch = qe.schema.clone();
+    assert!(sch.fields.iter().any(|c| c.name == "host"));
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// U. Long-tail: extra range reducers + the sort family     (functions.test; #51)
+// ─────────────────────────────────────────────────────────────────────────────
+
+#[test]
+fn extra_over_time_reducers_lower_to_per_series_intents() {
+    // SEMANTICS: each is a per-series reduction of one series' range window to a
+    // single value — a `TimeRange`-wrapped `Aggregate` with the matching intent.
+    for (q, want) in [
+        ("last_over_time(m[5m])", AggIntent::LastOverTime),
+        ("first_over_time(m[5m])", AggIntent::FirstOverTime),
+        ("mad_over_time(m[5m])", AggIntent::MadOverTime),
+        ("ts_of_min_over_time(m[5m])", AggIntent::TsOfMinOverTime),
+        ("ts_of_max_over_time(m[5m])", AggIntent::TsOfMaxOverTime),
+        ("ts_of_first_over_time(m[5m])", AggIntent::TsOfFirstOverTime),
+        ("ts_of_last_over_time(m[5m])", AggIntent::TsOfLastOverTime),
+    ] {
+        let qe = ok(q);
+        assert!(has(&qe, |i| *i == want), "{q}: {:?}", intents(&qe));
+        // Per-series: the range window survives as a `TimeRange`.
+        assert!(
+            matches!(qe.expect_non_asap(), NonASAPOp::Aggregate { child, .. } if matches!(child.expect_non_asap(), NonASAPOp::TimeRange { .. })),
+            "{q} keeps its range as a TimeRange"
+        );
+    }
+}
+
+#[test]
+fn last_over_time_composes_under_an_outer_aggregation() {
+    // `sum by (job) (last_over_time(m[5m]))` — per-series last, THEN cross-series
+    // sum. Both intents survive (issue #27's arbitrary nesting).
+    let qe = ok("sum by (job) (last_over_time(m[5m]))");
+    assert!(has(&qe, |i| *i == AggIntent::LastOverTime));
+    assert!(has(&qe, |i| matches!(i, AggIntent::Sum { .. })));
+}
+
+#[test]
+fn sort_and_sort_desc_reorder_by_value_without_a_limit() {
+    // SEMANTICS: `sort`/`sort_desc` reorder an instant vector by sample value.
+    // Row-preserving → a bare `Sort` (no `Limit`), ascending / descending.
+    for (q, ascending) in [
+        ("sort(http_requests)", true),
+        ("sort_desc(http_requests)", false),
+    ] {
+        let qe = ok(q);
+        let NonASAPOp::Sort { keys, child, .. } = qe.expect_non_asap() else {
+            panic!("{q}: expected a Sort, got {qe:?}");
+        };
+        assert_eq!(keys.len(), 1);
+        assert_eq!(keys[0].ascending, ascending, "{q}");
+        // No Limit above the Sort — every series is preserved.
+        assert!(!matches!(qe.expect_non_asap(), NonASAPOp::Limit { .. }));
+        // The value column is what it ranks on: descend to the scan.
+        let (metric, _) = first_scan(child);
+        assert_eq!(metric, "http_requests");
+    }
+}
+
+#[test]
+fn sort_by_label_orders_on_each_label_in_turn() {
+    // `sort_by_label(v, "group", "instance", "job")` — one ascending sort key per
+    // label, in argument order; the labels are seeded into the schema.
+    let qe = ok(r#"sort_by_label(http_requests, "group", "instance", "job")"#);
+    let NonASAPOp::Sort { keys, .. } = qe.expect_non_asap() else {
+        panic!("expected a Sort, got {qe:?}");
+    };
+    assert_eq!(keys.len(), 3, "one key per label");
+    assert!(keys.iter().all(|k| k.ascending));
+    let sch = qe.schema.clone();
+    for label in ["group", "instance", "job"] {
+        assert!(sch.fields.iter().any(|c| c.name == label), "{label} seeded");
+    }
+}
+
+#[test]
+fn sort_by_label_desc_is_descending() {
+    let qe = ok(r#"sort_by_label_desc(http_requests, "instance")"#);
+    let NonASAPOp::Sort { keys, .. } = qe.expect_non_asap() else {
+        panic!("expected a Sort, got {qe:?}");
+    };
+    assert!(keys.iter().all(|k| !k.ascending));
+}
+
+#[test]
+fn min_of_max_of_fold_constant_scalars() {
+    // `min_of`/`max_of` are n-ary scalar reducers. When every argument is a
+    // constant they constant-fold to a `ScalarExpr` leaf, just like scalar
+    // arithmetic (#35) — the only form the intent algebra can hold (#89).
+    assert_eq!(
+        promql_scalar(&support::scalar_root("min_of(3, 5)")),
+        Some(3.0)
+    );
+    assert_eq!(
+        promql_scalar(&support::scalar_root("max_of(3, 5)")),
+        Some(5.0)
+    );
+    assert_eq!(
+        promql_scalar(&support::scalar_root("min_of(-2, -5)")),
+        Some(-5.0)
+    );
+    // Nested folds and use as a threshold operand.
+    assert_eq!(
+        promql_scalar(&support::scalar_root("max_of(min_of(2, 3), 10)")),
+        Some(10.0)
+    );
+    let qe = ok("up > max_of(1, 2)");
+    let ScalarExpr::Compare { right: rhs, .. } = support::sample_expression(&qe) else {
+        panic!("{qe:?}")
+    };
+    assert_eq!(promql_scalar(rhs), Some(2.0));
+}
+
+#[test]
+fn min_of_max_of_ignore_nan_like_the_min_max_aggregators() {
+    // A NaN argument is skipped (Prometheus `min`/`max` NaN semantics).
+    assert_eq!(
+        promql_scalar(&support::scalar_root("max_of(3, NaN)")),
+        Some(3.0)
+    );
+    assert_eq!(
+        promql_scalar(&support::scalar_root("min_of(NaN, 3)")),
+        Some(3.0)
+    );
+}
+
+#[test]
+fn non_constant_min_of_max_of_is_rejected__GAP() {
+    // A dynamic argument (`step()` — itself unsupported, #89) can't be folded to
+    // a constant and there is no scalar min/max node, so it stays rejected
+    // rather than mislowered. These forms also only appear inside unsupported
+    // dynamic range / offset positions in the corpus.
+    let _ = rejected("min_of(step(), 1s)");
+    let _ = rejected("max_of(min_of(step() + 1, 1h), 1ms)");
+}
diff --git a/crates/frontend-promql/tests/unified_promql_lowering.rs b/crates/frontend-promql/tests/unified_promql_lowering.rs
new file mode 100644
index 000000000..de769361e
--- /dev/null
+++ b/crates/frontend-promql/tests/unified_promql_lowering.rs
@@ -0,0 +1,1615 @@
+//! End-to-end tests for PromQL → unresolved → canonical tree lowering.
+
+use std::rc::Rc;
+use std::time::Duration;
+
+use asap_types::ir::{
+    BinaryOperator, ExprSemantics, NonASAPOp, OperatorNode, ScalarExpr, TimeRangeKind,
+};
+use asap_types::pre_asap::{
+    AggIntent, ArithmeticOpKind, BinaryOpKind, CompareOpKind, Reduction, ScalarValue, Source,
+};
+use asap_types::types::AccuracyTarget;
+use asap_types::workload::{
+    AccuracyRequirement, BatchEntry, DataWorkload, DurationMs, Evidence, PlanningWorkload,
+    Predictability, Query, QueryLanguage, QueryRequirements, QueryWorkload, TimeSelection,
+};
+
+use asap_frontend_promql::unified::{lower_promql_workload, PromqlError as LoweringError};
+#[path = "unified_support.rs"]
+mod support;
+use support::lower_promql;
+
+fn lower(q: &str) -> Rc<OperatorNode> {
+    lower_promql(q, AccuracyTarget::Exact).unwrap_or_else(|e| panic!("lower failed for {q:?}: {e}"))
+}
+
+#[test]
+fn frequency_extensions_lower_to_explicit_frequency_statistics() {
+    // ProjectASAP extensions reduce a frequency vector; numeric sample norms
+    // have different semantics and must never be silently aliased here.
+    for (query, expected) in [
+        (
+            "entropy_over_time(cpu_usage[5m])",
+            AggIntent::FrequencyEntropy {
+                col: None,
+                accuracy: AccuracyTarget::Exact,
+            },
+        ),
+        (
+            "l2_over_time(cpu_usage[5m])",
+            AggIntent::FrequencyL2 {
+                col: None,
+                accuracy: AccuracyTarget::Exact,
+            },
+        ),
+    ] {
+        assert!(all_intents(&lower(query))
+            .iter()
+            .any(|intent| std::mem::discriminant(intent) == std::mem::discriminant(&expected)));
+    }
+}
+
+#[test]
+fn distinct_over_time_preserves_cardinality_accuracy_and_nested_windows() {
+    // Distinct counts sample values, not samples or series; all lowering routes
+    // retain the caller's accuracy requirement, including subquery arguments.
+    for query in [
+        "distinct_over_time(cpu_usage{job=\"worker\"}[5m] offset 1h)",
+        "distinct_over_time((cpu_usage + 1)[5m:1m])",
+        "sum by(job)(distinct_over_time(cpu_usage[5m]))",
+    ] {
+        for accuracy in [AccuracyTarget::Exact, AccuracyTarget::Epsilon(0.02)] {
+            let tree = lower_promql(query, accuracy.clone()).unwrap();
+            let mut intents = Vec::new();
+            collect_intents(&tree, &mut intents);
+            assert!(
+                intents.iter().any(|intent| matches!(
+                    intent, AggIntent::Cardinality { accuracy: actual, .. } if actual == &accuracy
+                )),
+                "{query}: {tree:?}"
+            );
+            assert!(!intents
+                .iter()
+                .any(|intent| matches!(intent, AggIntent::Count { .. })));
+        }
+    }
+}
+
+// ── Bare selectors & label matchers (folded onto Scan.predicates) ───────────────
+
+#[test]
+fn bare_selector_is_scan_with_predicates() {
+    let qe = lower(r#"http_requests_total{env="prod",status!="500"}"#);
+    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
+        panic!("expected TimeRange, got {qe:?}");
+    };
+    let NonASAPOp::Scan {
+        source, predicates, ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected Scan, got {qe:?}");
+    };
+    assert!(matches!(source, Source::TimeSeries { metric } if metric == "http_requests_total"));
+    // The converter splits the matcher conjunction into one predicate per
+    // conjunct on the Scan.
+    assert_eq!(predicates.len(), 2);
+    assert!(predicates
+        .iter()
+        .all(|p| matches!(&p.0, ScalarExpr::Compare { .. })));
+}
+
+#[test]
+fn regex_matcher_lowers_to_regex_compareop() {
+    let qe = lower(r#"http_requests_total{path=~"/api/.*"}"#);
+    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
+        panic!("expected TimeRange, got {qe:?}");
+    };
+    let NonASAPOp::Scan {
+        predicates, schema, ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected Scan, got {qe:?}");
+    };
+    let ScalarExpr::Compare {
+        left, op, right, ..
+    } = &predicates[0].0
+    else {
+        panic!("expected Compare, got {:?}", predicates[0].0);
+    };
+    assert_eq!(*op, CompareOpKind::Regex);
+    // The label matcher's column is resolved positionally against the scan schema.
+    let path_id = schema.column_id("path").expect("path in scan schema");
+    assert!(matches!(left.as_ref(), ScalarExpr::Column(id) if *id == path_id));
+    assert!(matches!(right.as_ref(), ScalarExpr::Literal(ScalarValue::Utf8(v)) if v == "/api/.*"));
+}
+
+// ── *_over_time → Aggregate over TimeRange ──────────────────────────────────────
+
+#[test]
+fn quantile_over_time_is_time_range_aggregate() {
+    let qe = lower(r#"quantile_over_time(0.99, http_request_duration{env="prod"}[5m])"#);
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected Aggregate, got {qe:?}");
+    };
+    assert_eq!(reduction, &Reduction::PerEntity);
+    assert!(
+        matches!(measures.as_slice(), [AggIntent::Quantile { q, .. }] if (*q - 0.99).abs() < 1e-9)
+    );
+    let NonASAPOp::TimeRange { range, child, .. } = child.expect_non_asap() else {
+        panic!("expected TimeRange child, got {child:?}");
+    };
+    assert_eq!(*range, Duration::from_secs(300));
+    // The label matcher folded onto the Scan.
+    assert!(
+        matches!(child.expect_non_asap(), NonASAPOp::Scan { predicates, .. } if predicates.len() == 1)
+    );
+}
+
+#[test]
+fn outer_sum_by_over_quantile_over_time_groups_positionally() {
+    // `sum by (host) (quantile_over_time(...))`: inner per-series
+    // quantile-over-time (label-preserving), then an outer cross-series sum
+    // grouped on a positional `Aggregate.by` — the same shape SQL produces, not
+    // a name-based Partition. Leaf = [ts, value, host, service] (referenced
+    // names appended sorted) → host = col 2.
+    let qe = lower(r#"sum by (host) (quantile_over_time(0.99, latency{service="web"}[5m]))"#);
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate grouped by host, got {qe:?}");
+    };
+    assert_eq!(reduction, &Reduction::by(vec![2]));
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+    // Inner: Aggregate{Quantile} over TimeRange (per-series over_time reduction).
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected Aggregate (quantile_over_time) under the outer Sum, got {child:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Quantile { .. }]));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
+}
+
+#[test]
+fn avg_over_time_maps_to_avg_intent() {
+    let qe = lower("avg_over_time(cpu_seconds_total[10m])");
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected Aggregate, got {qe:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Avg { .. }]));
+    let NonASAPOp::TimeRange { range, .. } = child.expect_non_asap() else {
+        panic!("expected TimeRange child, got {child:?}");
+    };
+    assert_eq!(*range, Duration::from_secs(600));
+}
+
+#[test]
+fn stddev_and_stdvar_over_time() {
+    let qe = lower("stddev_over_time(m[5m])");
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected Aggregate");
+    };
+    assert!(matches!(
+        measures.as_slice(),
+        [AggIntent::StdDev {
+            population: true,
+            ..
+        }]
+    ));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
+
+    let qe = lower("stdvar_over_time(m[5m])");
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected Aggregate");
+    };
+    assert!(matches!(
+        measures.as_slice(),
+        [AggIntent::Variance {
+            population: true,
+            ..
+        }]
+    ));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
+}
+
+#[test]
+fn histogram_quantile_wraps_inner_in_quantile() {
+    // The argument's structure (here `rate`) is preserved *under* the quantile,
+    // not squashed away. The `_bucket` metric + `le` matcher mark the classic
+    // form → `HistogramQuantile` over `Aggregate{Rate}` over Scan.
+    let qe = lower(r#"histogram_quantile(0.95, rate(http_duration_seconds_bucket{le="0.5"}[5m]))"#);
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate{{HistogramQuantile}}, got {qe:?}");
+    };
+    assert!(
+        matches!(measures.as_slice(), [AggIntent::HistogramQuantile { q, .. }] if (*q - 0.95).abs() < 1e-9)
+    );
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected inner Aggregate{{Rate}}, got {child:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
+    let NonASAPOp::TimeRange {
+        range,
+        child: tr_child,
+        ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected TimeRange under Rate, got {child:?}");
+    };
+    assert_eq!(*range, Duration::from_secs(300));
+    assert!(
+        matches!(tr_child.expect_non_asap(), NonASAPOp::Scan { predicates, .. } if predicates.len() == 1)
+    );
+}
+
+#[test]
+fn histogram_quantile_over_sum_by_le_preserves_grouping() {
+    // The canonical Prometheus histogram pattern. Previously returned
+    // UnsupportedFeature because `extract_matrix` couldn't see through the
+    // `sum by (le)` aggregate; now the `le` grouping survives into the
+    // canonical tree.
+    let qe = lower(r#"histogram_quantile(0.99, sum by (le) (rate(http_requests_bucket[5m])))"#);
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate{{HistogramQuantile}}, got {qe:?}");
+    };
+    // The `by (le)` grouping marks the classic cumulative-bucket form.
+    assert!(
+        matches!(measures.as_slice(), [AggIntent::HistogramQuantile { q, .. }] if (*q - 0.99).abs() < 1e-9)
+    );
+    // `sum by (le)` survives as a positional Aggregate (by = [2], `le`) over the
+    // inner Rate — no name-based Partition.
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected `sum by (le)` as a positional Aggregate, got {child:?}");
+    };
+    assert_eq!(reduction, &Reduction::by(vec![2]));
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+}
+
+/// The classic `histogram_quantile` aggregate: its `without` keys, `le`
+/// column, and output column names.
+fn classic_histogram(qe: &OperatorNode) -> (Vec<usize>, usize, Vec<String>) {
+    let NonASAPOp::Aggregate {
+        reduction: Reduction::Reduce(by),
+        measures,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected a reducing Aggregate, got {qe:?}");
+    };
+    let [AggIntent::HistogramQuantile { le, .. }] = measures.as_slice() else {
+        panic!("expected HistogramQuantile, got {measures:?}");
+    };
+    assert!(by.is_without(), "histogram_quantile groups without (le)");
+    let names = qe.schema.fields.iter().map(|c| c.name.clone()).collect();
+    (by.keys().to_vec(), *le, names)
+}
+
+// A classic histogram_quantile groups `without (le)` and names the child's
+// `le` column, even when no matcher or grouping mentions `le`.
+#[test]
+fn classic_histogram_quantile_groups_without_le() {
+    let qe = lower("histogram_quantile(0.9, rate(http_duration_seconds_bucket[5m]))");
+    let (keys, le, names) = classic_histogram(&qe);
+    let NonASAPOp::Aggregate { child, .. } = qe.expect_non_asap() else {
+        unreachable!()
+    };
+    let child = &child.schema;
+    assert_eq!(child.fields[le].name, "le");
+    assert_eq!(keys, vec![le]);
+    assert_eq!(names, vec!["histogram_quantile"]);
+}
+
+// An explicit `sum by (le, job)` argument keeps `job` and drops `le` and the
+// renamed sample value from the output labels.
+#[test]
+fn classic_histogram_quantile_over_sum_by_keeps_other_labels() {
+    let qe =
+        lower("histogram_quantile(0.9, sum by (le, job) (rate(http_duration_seconds_bucket[5m])))");
+    let (keys, le, names) = classic_histogram(&qe);
+    // `sum by (le, job)` outputs `[job, le, sum]`.
+    assert_eq!((keys, le), (vec![1], 1));
+    assert_eq!(names, vec!["job", "histogram_quantile"]);
+}
+
+// Out-of-range and NaN quantiles lower unchanged; execution returns -Inf/+Inf/NaN.
+#[test]
+fn classic_histogram_quantile_keeps_out_of_range_quantiles() {
+    for (query, expected) in [
+        ("histogram_quantile(-1, x_bucket)", -1.),
+        ("histogram_quantile(2, x_bucket)", 2.),
+    ] {
+        let root = lower(query);
+        let NonASAPOp::Aggregate { measures, .. } = root.expect_non_asap() else {
+            panic!("{query}");
+        };
+        assert!(
+            matches!(measures.as_slice(), [AggIntent::HistogramQuantile { q, .. }] if *q == expected)
+        );
+    }
+    let root = lower("histogram_quantile(NaN, x_bucket)");
+    let NonASAPOp::Aggregate { measures, .. } = root.expect_non_asap() else {
+        panic!("NaN");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::HistogramQuantile { q, .. }] if q.is_nan()));
+}
+
+// An argument whose closed output lacks `le` has no buckets. Prometheus
+// returns an empty vector; lowering rejects it rather than guess a column.
+#[test]
+fn classic_histogram_quantile_rejects_an_argument_without_le() {
+    let error = lower_promql(
+        "histogram_quantile(0.9, sum by (job) (rate(x_bucket[5m])))",
+        AccuracyTarget::Exact,
+    )
+    .unwrap_err();
+    assert!(error.to_string().contains("le"), "{error}");
+}
+
+// ── rate / increase carry their own window (no Window node) ─────────────────────
+
+#[test]
+fn rate_has_time_range_child_not_window() {
+    let qe = lower("rate(http_requests_total[5m])");
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected Aggregate for rate, got {qe:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
+    let NonASAPOp::TimeRange { range, .. } = child.expect_non_asap() else {
+        panic!("expected TimeRange child (not Window), got {child:?}");
+    };
+    assert_eq!(*range, Duration::from_secs(300));
+}
+
+#[test]
+fn increase_maps_to_increase_intent() {
+    let qe = lower("increase(errors_total[1h])");
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected Aggregate for increase, got {qe:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Increase]));
+    let NonASAPOp::TimeRange { range, .. } = child.expect_non_asap() else {
+        panic!("expected TimeRange child, got {child:?}");
+    };
+    assert_eq!(*range, Duration::from_secs(3600));
+}
+
+// ── outer aggregation over an inner range-vector func is two levels ─────────────
+
+#[test]
+fn sum_over_rate_keeps_both_levels() {
+    // Regression: `sum(rate(m[w]))` — the most common PromQL shape — must keep
+    // the cross-series Sum, not collapse to a bare per-series Rate.
+    let qe = lower("sum(rate(http_requests_total[5m]))");
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate{{Sum}}, got {qe:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected inner Aggregate{{Rate}}, got {child:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
+}
+
+#[test]
+fn sum_by_over_rate_groups_the_outer_sum() {
+    // `sum by (job) (rate(...))`: the grouping belongs to the OUTER sum and lands
+    // on a positional `Aggregate.by` (the same shape SQL produces) over the
+    // label-preserving inner Rate. Leaf = [ts, value, job] → by = [2].
+    let qe = lower("sum by (job) (rate(http_requests_total[5m]))");
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate grouped by job, got {qe:?}");
+    };
+    assert_eq!(reduction, &Reduction::by(vec![2]));
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate])
+    ));
+}
+
+#[test]
+fn count_over_rate_keeps_both_levels() {
+    // The `Outer::Count` sibling of the `sum(rate(...))` bug.
+    let qe = lower("count(rate(http_requests_total[5m]))");
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate{{Count}}, got {qe:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate])
+    ));
+}
+
+#[test]
+fn count_over_distinct_over_time_preserves_both_aggregates() {
+    // One series with window samples [1, 2] produces one distinct-count
+    // result (value 2). The outer count counts that one series, yielding 1.
+    for (query, reduction) in [
+        (
+            "count(distinct_over_time(unique_users[5m]))",
+            Reduction::by(vec![]),
+        ),
+        (
+            "count by (job) (distinct_over_time(unique_users[5m]))",
+            Reduction::by(vec![2]),
+        ),
+    ] {
+        let tree = lower(query);
+        let NonASAPOp::Aggregate {
+            measures,
+            reduction: actual,
+            child,
+            ..
+        } = tree.expect_non_asap()
+        else {
+            panic!("expected outer Count: {tree:?}");
+        };
+        assert!(
+            matches!(measures.as_slice(), [AggIntent::Count { .. }]),
+            "{query}: {tree:?}"
+        );
+        assert_eq!(actual, &reduction, "{query}");
+        let NonASAPOp::Aggregate {
+            measures,
+            reduction,
+            child,
+            ..
+        } = child.expect_non_asap()
+        else {
+            panic!("expected inner per-series Cardinality: {tree:?}");
+        };
+        assert!(
+            matches!(measures.as_slice(), [AggIntent::Cardinality { .. }]),
+            "{query}: {tree:?}"
+        );
+        assert_eq!(reduction, &Reduction::PerEntity, "{query}");
+        assert!(
+            matches!(child.expect_non_asap(), NonASAPOp::TimeRange { range, .. } if range.as_secs() == 300)
+        );
+    }
+}
+
+// ── count / cardinality ───────────────────────────────────────────────────────
+
+// Both selector fast paths and recursive vector expressions count rows, not values.
+#[test]
+fn count_never_lowers_to_distinct_sample_values() {
+    for query in [
+        "count(up)",
+        "count by (job) (up)",
+        "count without (instance) (up)",
+        "count(up + 1)",
+        "count(count_over_time(up[5m]))",
+        "count_over_time(up[5m])",
+    ] {
+        let tree = lower(query);
+        let intents = all_intents(&tree);
+        assert!(
+            intents.iter().any(|i| matches!(i, AggIntent::Count { .. })),
+            "{query}: {tree:?}"
+        );
+        assert!(
+            !intents
+                .iter()
+                .any(|i| matches!(i, AggIntent::Cardinality { .. })),
+            "{query}: {tree:?}"
+        );
+    }
+}
+
+#[test]
+fn count_over_time_is_count_intent() {
+    let qe = lower("count_over_time(m[5m])");
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected Aggregate");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
+}
+
+#[test]
+fn outer_count_counts_series() {
+    // `count by (symbol) (count_over_time(...))`: inner per-series sample count
+    // over the window (label-preserving), outer cross-series row count grouped
+    // on a positional `Aggregate.by`. Leaf = [ts, value, symbol] → symbol = col 2.
+    let qe = lower("count by (symbol) (count_over_time(financial_last_trade_price[5m]))");
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected outer Aggregate grouped by symbol, got {qe:?}");
+    };
+    assert_eq!(reduction, &Reduction::by(vec![2]));
+    assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
+    // Inner: Aggregate{Count} over TimeRange (per-series count_over_time).
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected Aggregate (count_over_time) under the outer count, got {child:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
+}
+
+// ── topk / bottomk ────────────────────────────────────────────────────────────
+
+#[test]
+fn topk_over_count_is_heavy_hitter_topk() {
+    let qe = lower(r#"topk by (service) (10, count_over_time(requests{env="prod"}[1m]))"#);
+    // Heavy-hitter: Aggregate{TopK} with grouping resolved to positional ids.
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected Aggregate with TopK, got {qe:?}");
+    };
+    // `service` is the only group key → resolved to a positional ColumnId.
+    assert_eq!(reduction.expect_reduce().len(), 1);
+    assert!(matches!(
+        measures.as_slice(),
+        [AggIntent::TopK { k: 10, .. }]
+    ));
+    // The count_over_time under the TopK is a TimeRange-backed aggregate.
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected Aggregate (count_over_time) under TopK, got {child:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
+    let NonASAPOp::TimeRange { range, child, .. } = child.expect_non_asap() else {
+        panic!("expected TimeRange under Count aggregate, got {child:?}");
+    };
+    assert_eq!(*range, Duration::from_secs(60));
+    assert!(matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }));
+}
+
+#[test]
+fn topk_over_sum_is_value_weighted_heavy_hitter_topk() {
+    let qe = lower(r#"topk by (service) (5, sum_over_time(requests{env="prod"}[1m]))"#);
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected Aggregate with TopK, got {qe:?}");
+    };
+    assert_eq!(reduction.expect_reduce().len(), 1);
+    assert!(matches!(
+        measures.as_slice(),
+        [AggIntent::TopK { k: 5, .. }]
+    ));
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected Aggregate (sum_over_time) under TopK, got {child:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
+}
+
+#[test]
+fn topk_over_avg_is_generic_sort_limit() {
+    let qe = lower("topk by (host) (5, avg_over_time(cpu[5m]))");
+    let NonASAPOp::Limit {
+        n: Some(n),
+        offset,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected Limit, got {qe:?}");
+    };
+    assert_eq!(*n, 5);
+    assert_eq!(*offset, 0);
+    let NonASAPOp::Sort {
+        keys,
+        partition_by,
+        child,
+    } = child.expect_non_asap()
+    else {
+        panic!("expected Sort under Limit, got {child:?}");
+    };
+    assert_eq!(keys.len(), 1);
+    assert!(!keys[0].ascending, "topk ranks descending");
+    // `by (host)` is per-group ranking → it rides on `Sort.partition_by`
+    // (positional), not a `Partition` node (issue #12). `host` is col 2 in
+    // the per-series avg schema [ts, value, host].
+    assert_eq!(partition_by, &vec![2]);
+    // Underneath: the label-preserving windowed avg aggregate (by: []), no
+    // intervening Partition.
+    assert!(
+        matches!(child.expect_non_asap(), NonASAPOp::Aggregate { reduction, measures, .. }
+            if reduction == &Reduction::PerEntity && matches!(measures.as_slice(), [AggIntent::Avg { .. }])),
+        "expected bare per-series Avg aggregate under Sort, got {child:?}"
+    );
+}
+
+#[test]
+fn ungrouped_topk_over_sum_is_heavy_hitter() {
+    let qe = lower("topk(5, sum_over_time(m[5m]))");
+    assert!(matches!(qe.expect_non_asap(), NonASAPOp::Aggregate { .. }));
+    assert!(has_intent(&qe, |i| matches!(i, AggIntent::Sum { .. })));
+    assert!(has_intent(&qe, |i| matches!(
+        i,
+        AggIntent::TopK { k: 5, .. }
+    )));
+}
+
+#[test]
+fn bottomk_over_count_is_generic_sort_ascending() {
+    // `bottomk` is never a heavy-hitter (descending=false), even over count.
+    let qe = lower("bottomk(3, count_over_time(m[5m]))");
+    let NonASAPOp::Limit {
+        n: Some(n), child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected Limit, got {qe:?}");
+    };
+    assert_eq!(*n, 3);
+    let NonASAPOp::Sort { keys, .. } = child.expect_non_asap() else {
+        panic!("expected Sort");
+    };
+    assert!(keys[0].ascending, "bottomk ranks ascending");
+    // Count intent is still present (as the inner aggregate), no TopK.
+    assert!(has_intent(&qe, |i| matches!(i, AggIntent::Count { .. })));
+    assert!(!has_intent(&qe, |i| matches!(i, AggIntent::TopK { .. })));
+}
+
+#[test]
+fn bottomk_is_always_generic_sort_ascending() {
+    let qe = lower("bottomk(3, count_over_time(m[5m]))");
+    let NonASAPOp::Limit {
+        n: Some(n), child, ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected Limit, got {qe:?}");
+    };
+    assert_eq!(*n, 3);
+    let NonASAPOp::Sort { keys, .. } = child.expect_non_asap() else {
+        panic!("expected Sort");
+    };
+    assert!(keys[0].ascending, "bottomk ranks ascending");
+}
+
+#[test]
+fn topk_count_output_schema_carries_group_key() {
+    // The inner Count is per-series (label-preserving), so the group-by key
+    // (`service`) flows through to the outer TopK's `by` column. Leaf schema =
+    // [ts, value, service] → TopK groups on service (col 2).
+    let qe = lower("topk by (service) (5, count_over_time(m[1m]))");
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected Aggregate{{TopK}}, got {qe:?}");
+    };
+    assert_eq!(
+        reduction,
+        &Reduction::by(vec![2]),
+        "service is col 2 in [ts, value, service]"
+    );
+    assert!(matches!(
+        measures.as_slice(),
+        [AggIntent::TopK { k: 5, .. }]
+    ));
+    // Inner Count aggregate is visible with its TimeRange child.
+    let NonASAPOp::Aggregate {
+        measures, child, ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected inner Aggregate{{Count}}, got {child:?}");
+    };
+    assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
+}
+
+// ── binary ops ────────────────────────────────────────────────────────────────
+
+#[test]
+fn binary_op_division() {
+    let qe = lower("rate(a[5m]) / rate(b[5m])");
+    let NonASAPOp::BinaryOp {
+        operator: BinaryOperator { kind: op, .. },
+        lhs,
+        rhs,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected BinaryOp, got {qe:?}");
+    };
+    assert_eq!(*op, BinaryOpKind::Arithmetic(ArithmeticOpKind::Div));
+    assert!(
+        matches!(lhs.expect_non_asap(), NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate]))
+    );
+    assert!(
+        matches!(rhs.expect_non_asap(), NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate]))
+    );
+}
+
+#[test]
+fn binary_op_with_on_grouping() {
+    let qe = lower("a / on(host) b");
+    let NonASAPOp::BinaryOp {
+        operator: BinaryOperator { vector_match, .. },
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected BinaryOp, got {qe:?}");
+    };
+    let vm = vector_match.as_ref().expect("vector_match present");
+    use asap_types::pre_asap::VectorMatchKind;
+    assert_eq!(vm.kind, VectorMatchKind::On);
+    assert_eq!(vm.labels, vec!["host".to_string()]);
+}
+
+// `bool` changes a comparison from a filter to a 0/1 result, so the IR must
+// carry it.
+#[test]
+fn bool_comparisons_are_distinct() {
+    let op = |q: &str| match lower(q).expect_non_asap() {
+        NonASAPOp::BinaryOp {
+            operator,
+            return_bool,
+            ..
+        } => (operator.kind.clone(), *return_bool),
+        NonASAPOp::Filter {
+            pred: asap_types::ir::Predicate(ScalarExpr::Compare { op, .. }),
+            ..
+        } => (BinaryOpKind::Compare(op.clone()), false),
+        NonASAPOp::Project { cols, .. } => {
+            let ScalarExpr::Case { branches, .. } = &cols[1].expr else {
+                panic!()
+            };
+            let ScalarExpr::Compare { op, .. } = &branches[0].0 else {
+                panic!()
+            };
+            (BinaryOpKind::Compare(op.clone()), true)
+        }
+        other => panic!("expected BinaryOp, got {other:?}"),
+    };
+    assert_eq!(
+        op("a > 1"),
+        (BinaryOpKind::Compare(CompareOpKind::Gt), false)
+    );
+    assert_eq!(
+        op("a > bool 1"),
+        (BinaryOpKind::Compare(CompareOpKind::Gt), true)
+    );
+    assert_eq!(
+        op("a == bool on(job) b"),
+        (BinaryOpKind::Compare(CompareOpKind::Eq), true)
+    );
+}
+
+#[test]
+fn binary_op_binds_each_branch_against_its_own_schema() {
+    // Each side scans a different metric and groups by a different label. With a
+    // single root schema threaded to both branches, the left scan would leak the
+    // right's group key (and vice-versa). Per-branch binding keeps them separate.
+    let qe = lower("count by (job) (a) / count by (region) (b)");
+    let NonASAPOp::BinaryOp { lhs, rhs, .. } = qe.expect_non_asap() else {
+        panic!("expected BinaryOp, got {qe:?}");
+    };
+    let lcols = scan_columns(lhs);
+    let rcols = scan_columns(rhs);
+    assert!(
+        lcols.iter().any(|c| c == "job") && !lcols.iter().any(|c| c == "region"),
+        "lhs scan schema leaked the rhs key: {lcols:?}"
+    );
+    assert!(
+        rcols.iter().any(|c| c == "region") && !rcols.iter().any(|c| c == "job"),
+        "rhs scan schema leaked the lhs key: {rcols:?}"
+    );
+}
+
+/// Collect every `AggIntent` in the tree, root-to-leaf.
+fn all_intents(e: &OperatorNode) -> Vec<AggIntent> {
+    let mut out = Vec::new();
+    collect_intents(e, &mut out);
+    out
+}
+
+fn collect_intents(e: &OperatorNode, out: &mut Vec<AggIntent>) {
+    match e.expect_non_asap() {
+        NonASAPOp::Aggregate {
+            measures, child, ..
+        } => {
+            out.extend(measures.iter().cloned());
+            collect_intents(child, out);
+        }
+        NonASAPOp::TimeRange { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. } => collect_intents(child, out),
+        NonASAPOp::BinaryOp { lhs, rhs, .. } => {
+            collect_intents(lhs, out);
+            collect_intents(rhs, out);
+        }
+        _ => {}
+    }
+}
+
+/// True if any `AggIntent` anywhere in the tree satisfies `pred`.
+fn has_intent<F: Fn(&AggIntent) -> bool>(e: &OperatorNode, pred: F) -> bool {
+    all_intents(e).iter().any(pred)
+}
+
+/// Field names on the first `Scan` reachable by descending single-child nodes.
+fn scan_columns(e: &OperatorNode) -> Vec<String> {
+    match e.expect_non_asap() {
+        NonASAPOp::Scan { schema, .. } => schema.fields.iter().map(|c| c.name.clone()).collect(),
+        NonASAPOp::Aggregate { child, .. }
+        | NonASAPOp::TimeRange { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. } => scan_columns(child),
+        _ => vec![],
+    }
+}
+
+// ── without(...) grouping (issue #39) ───────────────────────────────────────────
+
+#[test]
+fn without_grouping_lowers_to_the_exclusion_form() {
+    // `sum without (instance) (rate(m[5m]))` — a cross-series reduction over the
+    // per-series rate, grouped by every label except `instance`. The excluded
+    // label is stored positionally (the SchemaResolver seeds it), the grouping is the
+    // `without` form, and the output schema stays open.
+    let qe = lower("sum without (instance) (rate(m[5m]))");
+    let NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected an Aggregate, got {qe:?}");
+    };
+    let by = reduction.expect_reduce();
+    assert!(by.is_without());
+    assert_eq!(by.keys().len(), 1, "excluded `instance`");
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+    // The inner per-series rate is preserved (label-preserving) under the outer
+    // cross-series `without` reduction.
+    assert!(
+        matches!(child.expect_non_asap(), NonASAPOp::Aggregate { measures, .. }
+        if matches!(measures.as_slice(), [AggIntent::Rate]))
+    );
+    assert!(!qe.schema.clone().closed);
+}
+
+// ── parameter validation (reject rather than silently truncate/garble) ──────────
+
+#[test]
+fn fractional_or_negative_topk_k_is_rejected() {
+    // `as u64` would silently truncate 2.7→2 / saturate -1→0.
+    assert!(lower_promql("topk(2.7, count_over_time(m[1m]))", AccuracyTarget::Exact).is_err());
+    assert!(lower_promql("bottomk(2.5, sum_over_time(m[1m]))", AccuracyTarget::Exact).is_err());
+}
+
+#[test]
+fn out_of_range_quantile_phi_is_accepted() {
+    // Prometheus defines out-of-range phi results; lowering must preserve it.
+    for query in [
+        "quantile(1.5, up)",
+        "quantile_over_time(1.5, m[5m])",
+        "histogram_quantile(2.0, rate(b_bucket[5m]))",
+    ] {
+        assert!(
+            lower_promql(query, AccuracyTarget::Exact).is_ok(),
+            "{query}"
+        );
+    }
+}
+
+#[test]
+fn function_wrapped_range_vector_is_rejected_not_stripped() {
+    // `rate(abs(m[5m]))` must NOT silently lower as `rate(m[5m])` — the wrapper
+    // is rejected (here, at parse or in extract_matrix), never stripped.
+    assert!(
+        lower_promql("rate(abs(http_requests_total[5m]))", AccuracyTarget::Exact).is_err(),
+        "function-wrapped range vector should be rejected"
+    );
+}
+
+#[test]
+fn pathologically_nested_query_is_rejected_not_stack_overflow() {
+    // 300 nested parens parse fine but exceed the walker's depth limit (256);
+    // it must return an error, not overflow the stack.
+    let q = format!("{}m{}", "(".repeat(300), ")".repeat(300));
+    let err = lower_promql(&q, AccuracyTarget::Exact).unwrap_err();
+    assert!(format!("{err}").contains("nesting"), "got {err}");
+}
+
+// Behavior: every parser-accepted `fill` modifier form is rejected with a
+// fill-specific lowering error rather than silently dropped.
+#[test]
+fn fill_modifiers_are_rejected_not_ignored() {
+    for q in [
+        "a + fill(0) b",
+        "a + fill_left(1) b",
+        "a + fill_right(2) b",
+        "a + fill_left(1) fill_right(2) b",
+        "a + fill_right(2) fill_left(1) b",
+        "a + on(job) fill(0) b",
+        "a * ignoring(instance) group_left(env) fill_right(0) b",
+        "a > bool on(job) fill(0) b",
+        "sum(a - on(job) group_right fill_left(0) b)",
+    ] {
+        match lower_promql(q, AccuracyTarget::Exact) {
+            Err(LoweringError::UnsupportedFeature(m)) if m.contains("`fill`") => {}
+            other => panic!("expected fill rejection for {q:?}, got {other:?}"),
+        }
+    }
+}
+
+// ── accuracy propagation ──────────────────────────────────────────────────────
+
+#[test]
+fn accuracy_target_flows_into_quantile_intent() {
+    let qe = lower_promql(
+        "quantile_over_time(0.9, m[5m])",
+        AccuracyTarget::Epsilon(0.01),
+    )
+    .unwrap();
+    let NonASAPOp::Aggregate { measures, .. } = qe.expect_non_asap() else {
+        panic!("expected Aggregate");
+    };
+    assert!(matches!(
+        &measures[0],
+        AggIntent::Quantile { accuracy: AccuracyTarget::Epsilon(e), .. } if (*e - 0.01).abs() < 1e-12
+    ));
+}
+
+// ── schema flow (positional, carried on Scan; derived on demand) ─────────────────
+
+#[test]
+fn aggregate_output_schema_preserves_time_axis_and_labels() {
+    let qe = lower(r#"quantile_over_time(0.99, http_request_duration{env="prod"}[5m])"#);
+    // Per-series reduction: the root is Aggregate { TimeRange { Scan } }.
+    // The SchemaResolver adds all referenced label names (group keys AND filter
+    // predicate columns) to the scan schema, so `env` appears as a column
+    // even though it is only used as a filter.
+    // per_series_reduction_schema preserves the time axis and all label columns.
+    let NonASAPOp::Aggregate { .. } = qe.expect_non_asap() else {
+        panic!("expected Aggregate, got {qe:?}");
+    };
+    let schema = &qe.schema;
+    let names: Vec<&str> = schema.fields.iter().map(|c| c.name.as_str()).collect();
+    assert_eq!(names, vec!["ts", "value", "env"]);
+    assert_eq!(
+        schema.time_index,
+        Some(0),
+        "per-series over_time preserves the time axis"
+    );
+}
+
+#[test]
+fn scan_schema_carries_ts_value_and_group_keys() {
+    // `service` is a group key → the SchemaResolver lands it in the self-contained
+    // Scan schema (positional). `env` is only a filter, so it is not a column.
+    let qe = lower("count by (service) (count_over_time(requests[1m]))");
+    fn find_scan(n: &OperatorNode) -> &OperatorNode {
+        match n.expect_non_asap() {
+            NonASAPOp::Scan { .. } => n,
+            NonASAPOp::TimeRange { child, .. }
+            | NonASAPOp::Aggregate { child, .. }
+            | NonASAPOp::Filter { child, .. } => find_scan(child),
+            other => panic!("unexpected node {other:?}"),
+        }
+    }
+    let NonASAPOp::Scan { schema, .. } = find_scan(&qe).expect_non_asap() else {
+        unreachable!()
+    };
+    let mut names: Vec<&str> = schema.fields.iter().map(|c| c.name.as_str()).collect();
+    names.sort();
+    assert_eq!(names, vec!["service", "ts", "value"]);
+    assert_eq!(schema.time_index, Some(0)); // ts
+}
+
+// ── batch entry point ─────────────────────────────────────────────────────────
+
+#[test]
+fn batch_lowers_each_entry_and_reads_per_query_accuracy() {
+    let workload = PlanningWorkload {
+        query_workload: QueryWorkload {
+            language: QueryLanguage::PromQL,
+            query_batch: Some(vec![
+                BatchEntry {
+                    query: Query("rate(a[5m])".into()),
+                    requirements: QueryRequirements::default(),
+                    predictability: Predictability::Unknown,
+                    invocations: 1,
+                    execute_at: None,
+                    time_selection: TimeSelection::default(),
+                },
+                BatchEntry {
+                    query: Query("quantile_over_time(0.9, b[5m])".into()),
+                    requirements: QueryRequirements {
+                        accuracy: AccuracyRequirement::Explicit(AccuracyTarget::Epsilon(0.02)),
+                        ..Default::default()
+                    },
+                    predictability: Predictability::Unknown,
+                    invocations: 1,
+                    execute_at: None,
+                    time_selection: TimeSelection::default(),
+                },
+            ]),
+            repeating_queries: None,
+        },
+        data_workload: Some(DataWorkload {
+            data_ingestion_interval: Evidence {
+                value: Some(DurationMs(1_000)),
+                ..Default::default()
+            },
+            ..Default::default()
+        }),
+    };
+    let results = lower_promql_workload(&workload, 0).expect("valid workload");
+    assert_eq!(results.len(), 2);
+}
+
+#[test]
+fn batch_rejects_non_promql_language() {
+    use asap_types::workload::SqlDialect;
+    let workload = PlanningWorkload {
+        query_workload: QueryWorkload {
+            language: QueryLanguage::SQL(SqlDialect::DataFusionSQL),
+            query_batch: Some(vec![BatchEntry {
+                query: Query("SELECT 1".into()),
+                requirements: QueryRequirements::default(),
+                predictability: Predictability::Unknown,
+                invocations: 1,
+                execute_at: None,
+                time_selection: TimeSelection::default(),
+            }]),
+            repeating_queries: None,
+        },
+        data_workload: None,
+    };
+    assert!(matches!(
+        lower_promql_workload(&workload, 0),
+        Err(LoweringError::WrongLanguage(_))
+    ));
+}
+
+// ── #12: one home per grouping concept (the canonical `Partition` node is removed) ──
+//
+// `Partition` and `Aggregate.by` were two ways to express grouping. #12 collapses
+// them: a reducing GROUP BY → `Aggregate.by`; per-group *ranking* (split without
+// reduce) → `Sort.partition_by`; parallel sharding → a deployment's own
+// physical stage. There is no longer a canonical `Partition` node. These
+// tests pin both surviving canonical homes.
+
+#[test]
+fn reducing_group_by_lowers_to_aggregate_by() {
+    // Cross-series reduce, no keys → bare `Aggregate { reduction: Reduce([]) }`.
+    let q = lower("sum(http_requests_total)");
+    assert!(
+        matches!(q.expect_non_asap(), NonASAPOp::Aggregate { reduction, .. } if reduction == &Reduction::by(vec![]))
+    );
+
+    // Cross-series reduce grouped by a label → `Aggregate.reduction`.
+    let q = lower("sum by (job) (http_requests_total)");
+    assert!(
+        matches!(q.expect_non_asap(), NonASAPOp::Aggregate { reduction, .. }
+        if reduction.expect_reduce().len() == 1)
+    );
+
+    // Reduce over a label-preserving `rate` grouped by a label → still
+    // `Aggregate.reduction` (the keys resolve against rate's preserved schema).
+    let q = lower("sum by (job) (rate(http_requests_total[5m]))");
+    assert!(
+        matches!(q.expect_non_asap(), NonASAPOp::Aggregate { reduction, .. }
+        if reduction.expect_reduce().len() == 1)
+    );
+}
+
+#[test]
+fn generic_topk_grouping_lowers_to_sort_partition_by() {
+    // Per-group ranking (`topk by (host)`, non-heavy-hitter) groups *without*
+    // reducing → the grouping rides on `Sort.partition_by`, and the windowed
+    // reduction beneath stays label-preserving (`by: []`). No `Partition` node.
+    let q = lower("topk by (host) (5, avg_over_time(cpu[5m]))");
+    let NonASAPOp::Limit { child, .. } = q.expect_non_asap() else {
+        panic!("expected Limit, got {q:?}");
+    };
+    let NonASAPOp::Sort {
+        partition_by,
+        child,
+        ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected Sort, got {child:?}");
+    };
+    assert_eq!(partition_by, &vec![2], "host is col 2 in [ts, value, host]");
+    assert!(
+        matches!(child.expect_non_asap(), NonASAPOp::Aggregate { reduction, .. } if reduction == &Reduction::PerEntity)
+    );
+}
+
+#[test]
+fn topk_over_bare_selector_by_label_ranks_per_group() {
+    // `topk(3, http_requests_total) by (job)` — top-3 series per `job`. A bare
+    // instant selector ranks its OWN samples; it must not be wrapped in an
+    // implicit cross-series `Sum`, which would collapse the `job` partition
+    // label before `Sort.partition_by` resolves it (issue #30 — follow-up to the
+    // Partition→Sort.partition_by reframe in #12). Expected:
+    //   Limit{3} → Sort{value desc, partition_by:[job]} → Scan
+    let q = lower("topk(3, http_requests_total) by (job)");
+    let NonASAPOp::Limit {
+        n: Some(n), child, ..
+    } = q.expect_non_asap()
+    else {
+        panic!("expected Limit, got {q:?}");
+    };
+    assert_eq!(*n, 3);
+    let NonASAPOp::Sort {
+        keys,
+        partition_by,
+        child,
+    } = child.expect_non_asap()
+    else {
+        panic!("expected Sort, got {child:?}");
+    };
+    assert!(!keys[0].ascending, "topk ranks descending");
+    assert_eq!(partition_by, &vec![2], "job is col 2 in [ts, value, job]");
+    // No implicit reducing aggregate — the selector is label-preserving, so the
+    // sort is directly over the selector horizon (the `job` label survives to partition by).
+    assert!(
+        matches!(child.expect_non_asap(), NonASAPOp::TimeRange { child, .. } if matches!(child.expect_non_asap(), NonASAPOp::Scan { .. })),
+        "ranking is over the bare selector horizon, not a reducing Aggregate, got {child:?}"
+    );
+    assert!(
+        !has_intent(&q, |i| matches!(i, AggIntent::Sum { .. })),
+        "no implicit Sum is introduced over a bare selector"
+    );
+}
+
+#[test]
+fn topk_over_bare_selector_ranks_raw_samples() {
+    // Even without `by`, `topk(3, m)` ranks the raw instant-vector samples — it
+    // does not sum them. The sort sits directly over the Scan, partition empty.
+    let q = lower("topk(3, http_requests_total)");
+    let NonASAPOp::Limit { child, .. } = q.expect_non_asap() else {
+        panic!("expected Limit, got {q:?}");
+    };
+    let NonASAPOp::Sort {
+        partition_by,
+        child,
+        ..
+    } = child.expect_non_asap()
+    else {
+        panic!("expected Sort, got {child:?}");
+    };
+    assert!(partition_by.is_empty(), "no `by` → global ranking");
+    assert!(
+        matches!(child.expect_non_asap(), NonASAPOp::TimeRange { child, .. } if matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }))
+    );
+    assert!(!has_intent(&q, |i| matches!(i, AggIntent::Sum { .. })));
+}
+
+// ── Issue #109: histogram_quantiles fans out into one branch per φ ──────────
+
+/// The `(label value, intent)` of each `histogram_quantiles` branch.
+fn quantile_branches(q: &OperatorNode) -> Vec<(String, AggIntent)> {
+    let NonASAPOp::Concat { children, .. } = q.expect_non_asap() else {
+        panic!("expected a Concat at the root, got {q:?}");
+    };
+    children
+        .iter()
+        .map(|c| {
+            let NonASAPOp::PromqlRelabel { value, child, .. } = c.expect_non_asap() else {
+                panic!("expected PromqlRelabel per branch, got {c:?}");
+            };
+            let ScalarExpr::Literal(ScalarValue::Utf8(v)) = value else {
+                panic!("expected a literal label value, got {value:?}");
+            };
+            let NonASAPOp::Aggregate { measures, .. } = child.expect_non_asap() else {
+                panic!("expected an Aggregate under the PromqlRelabel, got {child:?}");
+            };
+            (v.clone(), measures[0].clone())
+        })
+        .collect()
+}
+
+#[test]
+fn histogram_quantiles_rejects_unrepresented_native_histograms() {
+    assert!(lower_promql(
+        r#"histogram_quantiles(testhistogram3, "q", 0, 0.25, 1)"#,
+        AccuracyTarget::Exact
+    )
+    .is_err());
+}
+
+#[test]
+fn histogram_quantiles_over_classic_buckets_interpolates() {
+    // `_bucket` argument → exact cumulative-bucket interpolation, never a sketch.
+    let q = lower(r#"histogram_quantiles(request_duration_seconds_bucket, "q", 0.5, 0.9)"#);
+    for (_, intent) in quantile_branches(&q) {
+        assert!(
+            matches!(intent, AggIntent::HistogramQuantile { .. }),
+            "classic buckets → HistogramQuantile, got {intent:?}"
+        );
+    }
+}
+
+#[test]
+fn histogram_quantiles_branches_are_union_compatible() {
+    // `Concat` derives its schema from the first child, so every branch must
+    // agree on column names — the φ lives in the label, not the column name.
+    let q = lower(r#"histogram_quantiles(testhistogram3_bucket, "q", 0.5, 0.9)"#);
+    let NonASAPOp::Concat { children, .. } = q.expect_non_asap() else {
+        panic!("expected Concat");
+    };
+    let shapes: Vec<Vec<String>> = children
+        .iter()
+        .map(|c| {
+            c.schema
+                .clone()
+                .fields
+                .iter()
+                .map(|c| c.name.clone())
+                .collect()
+        })
+        .collect();
+    assert_eq!(shapes[0], shapes[1], "branches must be union-compatible");
+    assert_eq!(shapes[0], vec!["value".to_string(), "q".to_string()]);
+    assert_eq!(
+        q.schema.fields.len(),
+        2,
+        "the merged schema describes every branch"
+    );
+}
+
+#[test]
+fn histogram_quantiles_uses_the_given_label_name() {
+    let q = lower(r#"histogram_quantiles(h_bucket, "phi", 0.5)"#);
+    let NonASAPOp::Concat { children, .. } = q.expect_non_asap() else {
+        panic!("expected Concat");
+    };
+    let NonASAPOp::PromqlRelabel { dst, .. } = children[0].expect_non_asap() else {
+        panic!("expected PromqlRelabel");
+    };
+    assert_eq!(dst, "phi");
+}
+
+#[test]
+fn histogram_quantiles_formats_small_quantiles_like_prometheus() {
+    // `labels.FormatOpenMetricsFloat`: Go's %g, so exponent form below 1e-4.
+    let q = lower(r#"histogram_quantiles(h_bucket, "q", 0.00001)"#);
+    assert_eq!(quantile_branches(&q)[0].0, "1e-05");
+}
+
+#[test]
+fn histogram_quantiles_rejects_an_out_of_range_quantile() {
+    // Same rule as `histogram_quantile(φ, …)` — one bad φ fails the whole call.
+    for q in [
+        r#"histogram_quantiles(h_bucket, "q", -0.1)"#,
+        r#"histogram_quantiles(h_bucket, "q", 1.01)"#,
+        r#"histogram_quantiles(h_bucket, "q", 0.5, NaN)"#,
+    ] {
+        assert!(
+            lower_promql(q, AccuracyTarget::Exact).is_err(),
+            "{q} should be rejected"
+        );
+    }
+}
+
+// ── TimeRange.kind: instant vs range selectors ──────────────────────────────────
+
+#[test]
+fn bare_instant_selector_is_an_instant_time_range() {
+    // `up` reads the latest sample per series within the workload's ingestion
+    // interval (1s in `support::workload`): an `Instant` lookback of that length.
+    let qe = lower("up");
+    let NonASAPOp::TimeRange { range, kind, child } = qe.expect_non_asap() else {
+        panic!("expected TimeRange, got {qe:?}");
+    };
+    assert_eq!(*kind, TimeRangeKind::Instant);
+    assert_eq!(*range, Duration::from_secs(1));
+    assert!(matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }));
+}
+
+#[test]
+fn explicit_range_selector_is_a_range_time_range() {
+    // `m[5m]` keeps its own window and is a `Range` selection — both under a
+    // range function and as a bare matrix selector.
+    let qe = lower("rate(m[5m])");
+    let NonASAPOp::Aggregate { child, .. } = qe.expect_non_asap() else {
+        panic!("expected Aggregate, got {qe:?}");
+    };
+    let NonASAPOp::TimeRange { range, kind, .. } = child.expect_non_asap() else {
+        panic!("expected TimeRange, got {child:?}");
+    };
+    assert_eq!(*kind, TimeRangeKind::Range);
+    assert_eq!(*range, Duration::from_secs(300));
+
+    let qe = lower("m[5m]");
+    assert!(matches!(
+        qe.expect_non_asap(),
+        NonASAPOp::TimeRange {
+            kind: TimeRangeKind::Range,
+            ..
+        }
+    ));
+}
+
+#[test]
+fn instant_and_range_selectors_of_equal_length_stay_distinct() {
+    // The kind is part of the shape: a 1s range selector is not the same tree as
+    // the 1s instant lookback injected around a bare selector.
+    assert_ne!(lower("up"), lower("up[1s]"));
+}
+
+// ── the `bool` modifier → `return_bool` ─────────────────────────────────────────
+
+#[test]
+fn vector_scalar_comparison_without_bool_filters() {
+    let qe = lower("up > 0");
+    assert!(matches!(qe.expect_non_asap(), NonASAPOp::Filter { .. }));
+    assert!(matches!(
+        support::sample_expression(&qe),
+        ScalarExpr::Compare {
+            op: CompareOpKind::Gt,
+            ..
+        }
+    ));
+}
+
+#[test]
+fn vector_scalar_comparison_with_bool_sets_return_bool() {
+    let qe = lower("up > bool 0");
+    assert!(matches!(
+        support::sample_expression(&qe),
+        ScalarExpr::Case { .. }
+    ));
+    assert_ne!(qe, lower("up > 0"));
+}
+
+#[test]
+fn vector_vector_comparison_with_bool_sets_return_bool() {
+    // `a > bool b` — the modifier lands on the vector/vector op itself, with
+    // the default (ignoring nothing) match.
+    let qe = lower("a > bool b");
+    let NonASAPOp::BinaryOp {
+        operator,
+        return_bool,
+        lhs,
+        rhs,
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected BinaryOp, got {qe:?}");
+    };
+    assert!(*return_bool);
+    assert_eq!(operator.kind, BinaryOpKind::Compare(CompareOpKind::Gt));
+    assert!(matches!(lhs.expect_non_asap(), NonASAPOp::TimeRange { .. }));
+    assert!(matches!(rhs.expect_non_asap(), NonASAPOp::TimeRange { .. }));
+    assert!(!lower("a > b").expect_non_asap().children().is_empty());
+    assert_ne!(qe, lower("a > b"));
+}
+
+#[test]
+fn bool_modifier_composes_with_vector_matching() {
+    let qe = lower("a > bool on(job) b");
+    let NonASAPOp::BinaryOp {
+        operator,
+        return_bool,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected BinaryOp, got {qe:?}");
+    };
+    assert!(*return_bool);
+    let vm = operator.vector_match.as_ref().expect("on(job) present");
+    assert_eq!(vm.labels, vec!["job".to_string()]);
+}
+
+// ── scalar expressions: negation, arithmetic, comparison ────────────────────────
+
+#[test]
+fn scalar_negation_of_time_is_a_negative_expression() {
+    // `-time()` is a scalar expression; its negation stays structural (the
+    // operand is not a constant to fold) and follows PromQL numeric rules.
+    let qe = support::scalar_root("-time()");
+    let ScalarExpr::Negative { expr, semantics } = &qe else {
+        panic!("expected ScalarExpr(Negative), got {qe:?}");
+    };
+    assert_eq!(*semantics, ExprSemantics::Promql);
+    assert!(matches!(expr.as_ref(), ScalarExpr::EvalTimestamp));
+    // Scalar-shaped: no time index.
+}
+
+#[test]
+fn scalar_negation_of_a_constant_still_folds() {
+    // `-(2)` is constant: it folds to one literal rather than a `Negative`.
+    assert_eq!(
+        support::promql_scalar(&support::scalar_root("-(2)")),
+        Some(-2.0)
+    );
+}
+
+#[test]
+fn scalar_arithmetic_carries_promql_semantics() {
+    let qe = support::scalar_root("time() - 1");
+    let ScalarExpr::Arithmetic {
+        op,
+        left,
+        right,
+        semantics,
+    } = &qe
+    else {
+        panic!("expected scalar(Arithmetic), got {qe:?}");
+    };
+    assert_eq!(*op, ArithmeticOpKind::Sub);
+    assert_eq!(*semantics, ExprSemantics::Promql);
+    assert!(matches!(left.as_ref(), ScalarExpr::EvalTimestamp));
+    assert!(matches!(
+        right.as_ref(),
+        ScalarExpr::Literal(ScalarValue::Float64(v)) if *v == 1.0
+    ));
+}
+
+#[test]
+fn scalar_bool_comparison_is_a_zero_one_case_with_promql_semantics() {
+    // `1 < bool 2` → `Case(Compare(1 < 2) → 1.0, else 0.0)`: PromQL yields 0/1.
+    let qe = support::scalar_root("1 < bool 2");
+    let ScalarExpr::Case {
+        operand,
+        branches,
+        else_expr,
+    } = &qe
+    else {
+        panic!("expected scalar(Case), got {qe:?}");
+    };
+    assert!(operand.is_none());
+    let [(when, then)] = branches.as_slice() else {
+        panic!("expected one branch, got {branches:?}");
+    };
+    let ScalarExpr::Compare {
+        left,
+        op,
+        right,
+        semantics,
+    } = when
+    else {
+        panic!("expected a Compare condition, got {when:?}");
+    };
+    assert_eq!(*op, CompareOpKind::Lt);
+    assert_eq!(*semantics, ExprSemantics::Promql);
+    assert!(matches!(left.as_ref(), ScalarExpr::Literal(ScalarValue::Float64(v)) if *v == 1.0));
+    assert!(matches!(right.as_ref(), ScalarExpr::Literal(ScalarValue::Float64(v)) if *v == 2.0));
+    assert!(matches!(then, ScalarExpr::Literal(ScalarValue::Float64(v)) if *v == 1.0));
+    assert!(matches!(
+        else_expr.as_deref(),
+        Some(ScalarExpr::Literal(ScalarValue::Float64(v))) if *v == 0.0
+    ));
+}
+
+#[test]
+fn scalar_comparison_without_bool_is_rejected() {
+    // PromQL has no scalar filter: a scalar/scalar comparison needs `bool`.
+    for q in ["1 < 2", "time() > 0", "(1 + 1) == 2"] {
+        assert!(
+            lower_promql(q, AccuracyTarget::Exact).is_err(),
+            "{q} must be rejected without `bool`"
+        );
+    }
+}
+
+#[test]
+fn label_matcher_predicates_carry_promql_semantics() {
+    let qe = lower(r#"up{job="api"}"#);
+    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
+        panic!("expected TimeRange, got {qe:?}");
+    };
+    let NonASAPOp::Scan { predicates, .. } = child.expect_non_asap() else {
+        panic!("expected Scan, got {child:?}");
+    };
+    assert!(matches!(
+        &predicates[0].0,
+        ScalarExpr::Compare {
+            semantics: ExprSemantics::Promql,
+            ..
+        }
+    ));
+}
diff --git a/crates/frontend-promql/tests/unified_scalar_design.rs b/crates/frontend-promql/tests/unified_scalar_design.rs
new file mode 100644
index 000000000..4e3f3063e
--- /dev/null
+++ b/crates/frontend-promql/tests/unified_scalar_design.rs
@@ -0,0 +1,129 @@
+//! Scalar expressions never become constant-wrapper operators.
+#[path = "unified_support.rs"]
+mod support;
+use asap_types::ir::{NonASAPOp, QueryRoot, ScalarExpr};
+use asap_types::pre_asap::{ArithmeticOpKind, ScalarValue};
+use asap_types::types::AccuracyTarget;
+
+fn root(query: &str) -> QueryRoot {
+    asap_frontend_promql::unified::lower_promql_query_workload(
+        &support::workload(query, AccuracyTarget::Exact),
+        0,
+    )
+    .unwrap()
+    .remove(0)
+}
+
+#[test]
+fn standalone_scalars_are_expressions() {
+    for query in [
+        "2",
+        "time()",
+        "scalar(sum(up)) + 1",
+        "1 < bool 2",
+        "-time()",
+    ] {
+        let QueryRoot::Scalar(expr) = root(query) else {
+            panic!("{query} became an operator")
+        };
+        expr.scalar_type(&Default::default()).unwrap();
+    }
+}
+
+#[test]
+fn arithmetic_projects_the_sample_and_preserves_full_identity_and_time() {
+    let QueryRoot::Operator(node) = root("up * 2") else {
+        panic!()
+    };
+    let NonASAPOp::Project { child, cols, .. } = node.expect_non_asap() else {
+        panic!()
+    };
+    assert!(child.schema.has_promql_series_identity());
+    assert!(node.schema.has_promql_series_identity());
+    assert_eq!(node.schema.time_index, child.schema.time_index);
+    let value = node.schema.column_id("value").unwrap();
+    assert!(
+        matches!(&cols[value].expr, ScalarExpr::Arithmetic { op: ArithmeticOpKind::Mul, right, .. } if **right == ScalarExpr::Literal(ScalarValue::Float64(2.0)))
+    );
+    assert!(cols.iter().any(|c| matches!(&c.expr, ScalarExpr::FunctionCall { name, .. } if name == "promql_drop_metric_name")));
+}
+
+#[test]
+fn non_bool_comparisons_keep_vector_samples_even_with_scalar_on_left() {
+    for query in ["up > 0", "0 < up"] {
+        let QueryRoot::Operator(node) = root(query) else {
+            panic!()
+        };
+        let NonASAPOp::Filter { child, .. } = node.expect_non_asap() else {
+            panic!()
+        };
+        assert_eq!(node.schema, child.schema);
+    }
+}
+
+#[test]
+fn bool_comparison_projects_zero_or_one() {
+    let QueryRoot::Operator(node) = root("up > bool 0") else {
+        panic!()
+    };
+    let NonASAPOp::Project { cols, .. } = node.expect_non_asap() else {
+        panic!()
+    };
+    assert!(matches!(
+        cols[node.schema.column_id("value").unwrap()].expr,
+        ScalarExpr::Case { .. }
+    ));
+}
+
+#[test]
+fn scalar_plan_dependencies_remain_visible() {
+    let QueryRoot::Operator(node) = root("up * scalar(sum(up))") else {
+        panic!()
+    };
+    assert_eq!(node.children().len(), 2);
+}
+
+/// Pointwise functions own scalar parameters, including vector-to-scalar reads.
+#[test]
+fn pointwise_functions_are_typed_scalar_projections() {
+    for query in [
+        "abs(up)",
+        "round(up, scalar(sum(other)))",
+        "clamp(up, time() - 1, time())",
+        "year(up)",
+        "hour()",
+    ] {
+        let QueryRoot::Operator(node) = root(query) else {
+            panic!()
+        };
+        let NonASAPOp::Project { cols, .. } = node.expect_non_asap() else {
+            panic!("{query}: expected projection")
+        };
+        assert!(matches!(
+            &cols[node.schema.column_id("value").unwrap()].expr,
+            ScalarExpr::FunctionCall { .. }
+        ));
+        node.validate_structure().unwrap();
+    }
+}
+
+/// Negation preserves the metric name and complete identity unlike multiplication.
+#[test]
+fn unary_minus_preserves_identity() {
+    let QueryRoot::Operator(node) = root("-up") else {
+        panic!()
+    };
+    let NonASAPOp::Project { child, cols, .. } = node.expect_non_asap() else {
+        panic!()
+    };
+    assert_eq!(node.schema, child.schema);
+    assert!(matches!(
+        &cols[node.schema.column_id("value").unwrap()].expr,
+        ScalarExpr::Negative { .. }
+    ));
+    for (index, col) in cols.iter().enumerate() {
+        if index != node.schema.column_id("value").unwrap() {
+            assert_eq!(col.expr, ScalarExpr::Column(index));
+        }
+    }
+}
diff --git a/crates/frontend-promql/tests/unified_support.rs b/crates/frontend-promql/tests/unified_support.rs
new file mode 100644
index 000000000..26ff6e802
--- /dev/null
+++ b/crates/frontend-promql/tests/unified_support.rs
@@ -0,0 +1,101 @@
+use std::rc::Rc;
+
+use asap_frontend_promql::unified::{
+    lower_promql_workload, lower_promql_workload_with_histograms, HistogramCatalog, PromqlError,
+};
+use asap_types::ir::{NonASAPOp, OperatorNode, ScalarExpr};
+use asap_types::pre_asap::ScalarValue;
+use asap_types::types::AccuracyTarget;
+use asap_types::workload::{
+    AccuracyRequirement, BatchEntry, DataWorkload, DurationMs, Evidence, PlanningWorkload,
+    Predictability, Query, QueryLanguage, QueryRequirements, QueryWorkload, TimeSelection,
+};
+
+pub fn workload(query: &str, accuracy: AccuracyTarget) -> PlanningWorkload {
+    PlanningWorkload {
+        query_workload: QueryWorkload {
+            language: QueryLanguage::PromQL,
+            query_batch: Some(vec![BatchEntry {
+                query: Query(query.into()),
+                requirements: QueryRequirements {
+                    accuracy: AccuracyRequirement::Explicit(accuracy),
+                    ..Default::default()
+                },
+                predictability: Predictability::Unknown,
+                invocations: 1,
+                execute_at: None,
+                time_selection: TimeSelection::default(),
+            }]),
+            repeating_queries: None,
+        },
+        data_workload: Some(DataWorkload {
+            data_ingestion_interval: Evidence {
+                value: Some(DurationMs(1_000)),
+                ..Default::default()
+            },
+            ..Default::default()
+        }),
+    }
+}
+
+#[allow(dead_code)]
+pub fn lower_promql(
+    query: &str,
+    accuracy: AccuracyTarget,
+) -> Result<Rc<OperatorNode>, PromqlError> {
+    let mut lowered = lower_promql_workload(&workload(query, accuracy), 0)?;
+    Ok(lowered.remove(0))
+}
+
+#[allow(dead_code)]
+pub fn lower_promql_with_histograms(
+    query: &str,
+    accuracy: AccuracyTarget,
+    histograms: HistogramCatalog,
+) -> Result<Rc<OperatorNode>, PromqlError> {
+    let mut lowered =
+        lower_promql_workload_with_histograms(&workload(query, accuracy), histograms, 0)?;
+    Ok(lowered.remove(0))
+}
+
+/// The value of a bare PromQL numeric literal / folded constant at an
+/// scalar position (`Literal(Float64(v))`); `None` for any
+/// other shape.
+#[allow(dead_code)]
+pub fn promql_scalar(node: &ScalarExpr) -> Option<f64> {
+    match node {
+        ScalarExpr::Literal(ScalarValue::Float64(v)) => Some(*v),
+        _ => None,
+    }
+}
+
+/// Export the logical graph before physical materialization assigns timing.
+#[allow(dead_code)]
+pub fn logical_asap_dag(root: &Rc<OperatorNode>) -> asap_types::ir::export::LogicalASAPDAG {
+    asap_types::ir::export::compile_logical_asap_dag(root).expect("logical ASAP DAG export")
+}
+
+#[allow(dead_code)]
+pub fn scalar_root(query: &str) -> ScalarExpr {
+    match asap_frontend_promql::unified::lower_promql_query_workload(
+        &workload(query, AccuracyTarget::Exact),
+        0,
+    )
+    .unwrap()
+    .remove(0)
+    {
+        asap_types::ir::QueryRoot::Scalar(expr) => expr,
+        _ => panic!("expected scalar root: {query}"),
+    }
+}
+
+#[allow(dead_code)]
+pub fn sample_expression(node: &OperatorNode) -> &ScalarExpr {
+    match node.expect_non_asap() {
+        NonASAPOp::Project { cols, .. } => {
+            &cols[node.schema.column_id("value").unwrap_or(cols.len() - 1)].expr
+        }
+        NonASAPOp::Filter { pred, .. } => &pred.0,
+        other => panic!("expected sample expression, got {other:?}"),
+    }
+}

From e5d3cff192ce8295b1c5de320101ea9589d63ac5 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 19:41:57 +0000
Subject: [PATCH 31/48] feat(ir): restore execution timing assignment for
 physical plans

The logical export is phase-free. Physical planning still needs the lifecycle
timing expansion; bring it back unchanged except for carrying coverage.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/types/src/ir/mod.rs                    |   6 +
 crates/types/src/ir/timing.rs                 | 905 ++++++++++++++++++
 .../src/post_asap/execution_data_state.rs     |  12 +
 3 files changed, 923 insertions(+)
 create mode 100644 crates/types/src/ir/timing.rs

diff --git a/crates/types/src/ir/mod.rs b/crates/types/src/ir/mod.rs
index d4885bff2..b6cf9f74d 100644
--- a/crates/types/src/ir/mod.rs
+++ b/crates/types/src/ir/mod.rs
@@ -18,6 +18,12 @@ pub use scalar::{ExprSemantics, Predicate, ProjectItem, ScalarExpr, SortKey};
 pub mod canonicalize;
 pub mod cse;
 pub mod export;
+/// Execution timing for physical plans: a lifecycle assignment expanded onto every node.
+pub mod timing;
+pub use timing::{
+    apply_lifecycle_timings, data_state, planned_data_state, split_shared_by_phase,
+    validate_default, LifecycleAssignment, TimingMemo,
+};
 /// Semantic observation coverage, separate from field layout and physical timing.
 pub mod summary_coverage;
 mod wire;
diff --git a/crates/types/src/ir/timing.rs b/crates/types/src/ir/timing.rs
new file mode 100644
index 000000000..e19513ba3
--- /dev/null
+++ b/crates/types/src/ir/timing.rs
@@ -0,0 +1,905 @@
+//! Execution timing: written into every node from a lifecycle assignment,
+//! then validated against each operator's kind and its consuming edges.
+//!
+//! The logical DAG carries no timing. Summary materialization chooses a
+//! lifecycle per summary state; [`LifecycleAssignment`] records that choice
+//! (ingestion-time maintenance or query-time recomputation per `SummaryAgg`)
+//! and [`apply_lifecycle_timings`] expands it into a timing on every node:
+//!
+//! - a node of fixed kind takes its kind's timing (`SummaryEstimate` and
+//!   `EvaluatePopulation` run at query time, `MaintainPopulation` at ingestion
+//!   time);
+//! - a `SummaryAgg` takes the assignment's timing (default: ingestion time),
+//!   unless something below it can only exist at query time;
+//! - every other node runs when its consumer runs: everything that feeds a
+//!   maintained state runs at ingestion time, everything above a evaluation at
+//!   query time.
+//!
+//! A node reached from two consumers that need different timings cannot be
+//! executed once for both; [`split_shared_by_phase`] copies such a sub-DAG
+//! for one side before the assignment is applied, and the pass itself
+//! rejects a conflict it still finds.
+//!
+//! ## Edge rules (checked after the write)
+//!
+//! | Consumer | Accepts from an input |
+//! |---|---|
+//! | `SummaryAgg.child` | Rows, or exact-accumulator state, never a query-time value when the state is maintained |
+//! | `SummaryEstimate.summary_input` | Summary state at either phase |
+//! | `FinalizeExactAccumulator.child` | Exact-accumulator state |
+//! | `EvaluatePopulation.child` | A `MaintainPopulation` at ingestion time |
+//! | `MaintainPopulation.child` | Ingestion-time rows matching the population's input |
+//! | any `NonASAP` consumer | Rows (or exact-accumulator state for a projection-like operator) at the consumer's own timing; ingestion work never reads a query-time value |
+
+use std::collections::HashMap;
+use std::rc::Rc;
+
+use super::asap::ASAPOp;
+use super::node::{Operator, OperatorNode};
+use super::non_asap::NonASAPOp;
+use crate::ir::operator_properties::BinaryOpKind;
+use crate::post_asap::execution_data_state::{
+    DataPrimitive, ExecutionDataState, ExecutionDataStateError, ExecutionTiming,
+};
+use crate::pre_asap::schema::{DataType, FieldDataType, Schema};
+
+/// The per-state lifecycle choice summary materialization made: for each
+/// `SummaryAgg` node (by identity), whether its state is maintained at
+/// ingestion time or recomputed at query time. A state absent from the map
+/// takes the default, ingestion-time maintenance.
+#[derive(Debug, Clone, Default)]
+pub struct LifecycleAssignment {
+    summary_timings: HashMap<*const OperatorNode, ExecutionTiming>,
+}
+
+impl LifecycleAssignment {
+    /// The assignment under which every summary state is maintained at
+    /// ingestion time — the timings every plan carried before lifecycles
+    /// became a planning choice.
+    pub fn default_maintained() -> Self {
+        Self::default()
+    }
+
+    pub fn set(&mut self, summary: &Rc<OperatorNode>, timing: ExecutionTiming) {
+        self.summary_timings.insert(Rc::as_ptr(summary), timing);
+    }
+
+    pub fn summary_timing(&self, summary: &Rc<OperatorNode>) -> ExecutionTiming {
+        self.summary_timings
+            .get(&Rc::as_ptr(summary))
+            .copied()
+            .unwrap_or(ExecutionTiming::IngestionTime)
+    }
+}
+
+/// Memo of one [`apply_lifecycle_timings`] pass: `input node → timed node`,
+/// shared by every root of a workload so a node shared by two roots stays
+/// one `Rc`. Re-reaching a node with a different timing is a conflict.
+#[derive(Default)]
+pub struct TimingMemo {
+    done: HashMap<*const OperatorNode, Rc<OperatorNode>>,
+}
+
+impl TimingMemo {
+    pub fn new() -> Self {
+        Self::default()
+    }
+
+    /// The timed node produced for `input`, if the pass has reached it.
+    pub fn timed(&self, input: &Rc<OperatorNode>) -> Option<&Rc<OperatorNode>> {
+        self.done.get(&Rc::as_ptr(input))
+    }
+}
+
+/// The data state a timed node's output carries.
+pub fn data_state(node: &OperatorNode) -> Option<ExecutionDataState> {
+    Some(ExecutionDataState {
+        timing: node.timing?,
+        primitive: match &node.operator {
+            Operator::ASAP(op) if op.produced_state().is_some() => DataPrimitive::SummaryState,
+            Operator::ASAP(ASAPOp::MaintainPopulation { .. }) => DataPrimitive::SummaryState,
+            _ => DataPrimitive::Raw,
+        },
+    })
+}
+
+/// Whether the sub-DAG below `node` contains a node that can only run at
+/// query time (a evaluation), which forces every consumer above it to query
+/// time as well.
+fn forces_query_time(node: &OperatorNode, seen: &mut HashMap<*const OperatorNode, bool>) -> bool {
+    let key = node as *const OperatorNode;
+    if let Some(&cached) = seen.get(&key) {
+        return cached;
+    }
+    let forced = match &node.operator {
+        _ if node.timing == Some(ExecutionTiming::QueryTime) => true,
+        Operator::ASAP(ASAPOp::SummaryEstimate { .. })
+        | Operator::ASAP(ASAPOp::EvaluatePopulation { .. }) => true,
+        Operator::NonASAP(NonASAPOp::BinaryOp { lhs, rhs, .. })
+            if node
+                .schema
+                .fields
+                .iter()
+                .any(|f| f.name == crate::pre_asap::schema::PROMQL_SERIES_IDENTITY)
+                && per_series_rows(lhs).is_none_or(|rows| per_series_rows(rhs) != Some(rows)) =>
+        {
+            true
+        }
+        _ => node
+            .children()
+            .iter()
+            .any(|child| forces_query_time(child, seen)),
+    };
+    seen.insert(key, forced);
+    forced
+}
+
+/// Write the timings of `assignment` into every node reachable from `root`,
+/// top-down, then validate every edge. Returns the timed copy of `root`;
+/// `memo` carries the sharing across the roots of one workload.
+pub fn apply_lifecycle_timings(
+    root: &Rc<OperatorNode>,
+    assignment: &LifecycleAssignment,
+    memo: &mut TimingMemo,
+) -> Result<Rc<OperatorNode>, ExecutionDataStateError> {
+    let mut forced = HashMap::new();
+    let timed = write(
+        root,
+        ExecutionTiming::QueryTime,
+        assignment,
+        memo,
+        &mut forced,
+    )?;
+    if timed.timing == Some(ExecutionTiming::IngestionTime)
+        && data_state(&timed).map(|s| s.primitive) == Some(DataPrimitive::Raw)
+    {
+        return Err(ExecutionDataStateError::MaintenanceRowsAtRoot);
+    }
+    validate(&timed, &mut HashMap::new())?;
+    Ok(timed)
+}
+
+/// Validate the sub-DAG below `root` under the default (every summary
+/// maintained) assignment, with `root` consumed at `root_timing`. For
+/// planning-time legality checks of a candidate before it is assembled into
+/// a workload DAG; nothing is kept.
+pub fn validate_default(
+    root: &Rc<OperatorNode>,
+    root_timing: ExecutionTiming,
+) -> Result<(), ExecutionDataStateError> {
+    let assignment = LifecycleAssignment::default_maintained();
+    let mut memo = TimingMemo::new();
+    let mut forced = HashMap::new();
+    let timed = write(root, root_timing, &assignment, &mut memo, &mut forced)?;
+    validate(&timed, &mut HashMap::new())
+}
+
+/// The data state `node` produces under the default assignment when its
+/// consumer runs at `consumer` — the planning-time answer to "what does this
+/// candidate's output look like" before any assignment is applied.
+pub fn planned_data_state(
+    node: &Rc<OperatorNode>,
+    consumer: ExecutionTiming,
+) -> ExecutionDataState {
+    let mut forced = HashMap::new();
+    let timing = own_timing(
+        node,
+        consumer,
+        &LifecycleAssignment::default_maintained(),
+        &mut forced,
+    );
+    ExecutionDataState {
+        timing,
+        primitive: match &node.operator {
+            Operator::ASAP(op) if op.produced_state().is_some() => DataPrimitive::SummaryState,
+            Operator::ASAP(ASAPOp::MaintainPopulation { .. }) => DataPrimitive::SummaryState,
+            _ => DataPrimitive::Raw,
+        },
+    }
+}
+
+/// The timing `node` takes when its consumer runs at `consumer`.
+fn own_timing(
+    node: &Rc<OperatorNode>,
+    consumer: ExecutionTiming,
+    assignment: &LifecycleAssignment,
+    forced: &mut HashMap<*const OperatorNode, bool>,
+) -> ExecutionTiming {
+    // A placement fixed when the candidate was built (an exact-state read
+    // boundary that must run at query time, or one that feeds maintenance)
+    // is honored; a conflicting consumer is rejected by validation.
+    if let Some(placed) = node.timing {
+        return placed;
+    }
+    match &node.operator {
+        Operator::ASAP(ASAPOp::SummaryEstimate { .. })
+        | Operator::ASAP(ASAPOp::EvaluatePopulation { .. }) => ExecutionTiming::QueryTime,
+        Operator::ASAP(ASAPOp::MaintainPopulation { .. }) => ExecutionTiming::IngestionTime,
+        Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) => {
+            if forces_query_time(child, forced) {
+                ExecutionTiming::QueryTime
+            } else {
+                assignment.summary_timing(node)
+            }
+        }
+        _ => consumer,
+    }
+}
+
+fn write(
+    node: &Rc<OperatorNode>,
+    consumer: ExecutionTiming,
+    assignment: &LifecycleAssignment,
+    memo: &mut TimingMemo,
+    forced: &mut HashMap<*const OperatorNode, bool>,
+) -> Result<Rc<OperatorNode>, ExecutionDataStateError> {
+    let timing = own_timing(node, consumer, assignment, forced);
+    if let Some(done) = memo.done.get(&Rc::as_ptr(node)) {
+        let previous = done.timing.expect("memoized node is timed");
+        if previous != timing {
+            return Err(ExecutionDataStateError::ConflictingTiming {
+                first: ExecutionDataState {
+                    timing: previous,
+                    primitive: data_state(done).map_or(DataPrimitive::Raw, |s| s.primitive),
+                },
+                second: ExecutionDataState {
+                    timing,
+                    primitive: data_state(done).map_or(DataPrimitive::Raw, |s| s.primitive),
+                },
+            });
+        }
+        return Ok(Rc::clone(done));
+    }
+    let mut error = None;
+    let operator =
+        node.operator.map_children(
+            |child| match write(child, timing, assignment, memo, forced) {
+                Ok(timed) => timed,
+                Err(e) => {
+                    error.get_or_insert(e);
+                    Rc::clone(child)
+                }
+            },
+        );
+    if let Some(e) = error {
+        return Err(e);
+    }
+    let timed = Rc::new(OperatorNode {
+        operator,
+        result_kind: node.result_kind,
+        schema: node.schema.clone(),
+        guarantee: node.guarantee.clone(),
+        timing: Some(timing),
+        // Timing copies the same logical sub-DAG; its observations are unchanged.
+        coverage: node.coverage.clone(),
+    });
+    memo.done.insert(Rc::as_ptr(node), Rc::clone(&timed));
+    Ok(timed)
+}
+
+fn state_of(node: &OperatorNode) -> ExecutionDataState {
+    data_state(node).expect("timed node")
+}
+
+/// Check every edge below `node` against the module-level rules.
+fn validate(
+    node: &Rc<OperatorNode>,
+    seen: &mut HashMap<*const OperatorNode, ()>,
+) -> Result<(), ExecutionDataStateError> {
+    if seen.insert(Rc::as_ptr(node), ()).is_some() {
+        return Ok(());
+    }
+    let timing = node.timing.expect("timed node");
+    match &node.operator {
+        Operator::ASAP(op) => validate_asap(node, op, timing)?,
+        Operator::NonASAP(op) => validate_non_asap(node, op, timing)?,
+    }
+    for child in node.children() {
+        validate(child, seen)?;
+    }
+    Ok(())
+}
+
+fn is_exact_accumulator_state(schema: &Schema) -> Result<(), ExecutionDataStateError> {
+    for field in &schema.fields {
+        match &field.dtype {
+            FieldDataType::Plain(_) | FieldDataType::ExactAggregate(..) => {}
+            other => {
+                return Err(ExecutionDataStateError::UnsupportedStateComposition {
+                    family: format!("{other:?}"),
+                })
+            }
+        }
+    }
+    Ok(())
+}
+
+fn validate_asap(
+    node: &OperatorNode,
+    op: &ASAPOp,
+    timing: ExecutionTiming,
+) -> Result<(), ExecutionDataStateError> {
+    match op {
+        ASAPOp::SummaryAgg { child, .. } => {
+            let avail = state_of(child);
+            match avail {
+                ExecutionDataState::INGESTION_ROWS | ExecutionDataState::QUERY_ROWS => {}
+                s if s.primitive == DataPrimitive::SummaryState => {
+                    is_exact_accumulator_state(&child.schema)?
+                }
+                other => {
+                    return Err(ExecutionDataStateError::EvaluationUnderMaintenance {
+                        edge: "SummaryAgg.child",
+                        child: other,
+                    })
+                }
+            }
+            if timing == ExecutionTiming::IngestionTime
+                && avail.timing == ExecutionTiming::QueryTime
+            {
+                return Err(ExecutionDataStateError::EvaluationUnderMaintenance {
+                    edge: "SummaryAgg.child",
+                    child: avail,
+                });
+            }
+            Ok(())
+        }
+        ASAPOp::SummaryEstimate { summary_input, .. } => {
+            let s = state_of(summary_input);
+            if s.primitive != DataPrimitive::SummaryState {
+                return Err(ExecutionDataStateError::IllegalChildDataState {
+                    edge: "SummaryEstimate.summary_input",
+                    child: s,
+                });
+            }
+            if timing != ExecutionTiming::QueryTime {
+                return Err(ExecutionDataStateError::IllegalChildDataState {
+                    edge: "SummaryEstimate",
+                    child: state_of(node),
+                });
+            }
+            Ok(())
+        }
+        ASAPOp::FinalizeExactAccumulator { child } => {
+            let s = state_of(child);
+            if s.primitive != DataPrimitive::SummaryState
+                || is_exact_accumulator_state(&child.schema).is_err()
+                || (timing == ExecutionTiming::IngestionTime && s.timing != timing)
+            {
+                return Err(ExecutionDataStateError::IllegalChildDataState {
+                    edge: "FinalizeExactAccumulator.child",
+                    child: s,
+                });
+            }
+            Ok(())
+        }
+        ASAPOp::MaintainPopulation { child, population } => {
+            let valid = population.matches_node(child)
+                && state_of(child)
+                    == ExecutionDataState {
+                        timing,
+                        primitive: DataPrimitive::Raw,
+                    };
+            if !valid {
+                return Err(ExecutionDataStateError::InvalidMaintainedPopulation);
+            }
+            Ok(())
+        }
+        ASAPOp::EvaluatePopulation { child, evaluation } => {
+            let valid = timing == ExecutionTiming::QueryTime
+                && matches!(
+                    &child.operator,
+                    Operator::ASAP(ASAPOp::MaintainPopulation { population, .. })
+                        if population.supports(evaluation)
+                            && child.timing.is_some()
+                );
+            if !valid {
+                return Err(ExecutionDataStateError::InvalidMaintainedPopulation);
+            }
+            Ok(())
+        }
+        ASAPOp::SummaryMerge { .. }
+        | ASAPOp::SummarySubtract { .. }
+        | ASAPOp::SummaryDelete { .. }
+        | ASAPOp::SummaryJoin { .. }
+        | ASAPOp::Extension { .. } => Err(ExecutionDataStateError::UnimplementedOperator {
+            operator: op.kind_name(),
+        }),
+    }
+}
+
+fn check_plain_or_exact_values(input: &Schema) -> Result<(), ExecutionDataStateError> {
+    for field in &input.fields {
+        if !matches!(
+            field.dtype,
+            FieldDataType::Plain(_) | FieldDataType::ExactAggregate(..)
+        ) {
+            return Err(ExecutionDataStateError::NonPlainOperand {
+                column: field.name.clone(),
+                dtype: format!("{:?}", field.dtype),
+            });
+        }
+    }
+    Ok(())
+}
+
+fn check_all_plain(input: &Schema) -> Result<(), ExecutionDataStateError> {
+    for field in &input.fields {
+        if !field.is_plain() {
+            return Err(ExecutionDataStateError::NonPlainOperand {
+                column: field.name.clone(),
+                dtype: format!("{:?}", field.dtype),
+            });
+        }
+    }
+    Ok(())
+}
+
+fn validate_non_asap(
+    node: &OperatorNode,
+    op: &NonASAPOp,
+    timing: ExecutionTiming,
+) -> Result<(), ExecutionDataStateError> {
+    // Every input is rows at this node's own timing. Ingestion work never
+    // reads a query-time value; exact-accumulator state may pass through
+    // the projection-like operators unchanged.
+    for child in op.children() {
+        let s = state_of(child);
+        let passes_state = matches!(
+            op,
+            NonASAPOp::Project { .. }
+                | NonASAPOp::Filter { .. }
+                | NonASAPOp::Sort { .. }
+                | NonASAPOp::Limit { .. }
+        ) && s.primitive == DataPrimitive::SummaryState
+            && is_exact_accumulator_state(&child.schema).is_ok();
+        if s.timing != timing || (s.primitive != DataPrimitive::Raw && !passes_state) {
+            return Err(ExecutionDataStateError::IllegalChildDataState {
+                edge: op.kind_name(),
+                child: s,
+            });
+        }
+    }
+    match op {
+        NonASAPOp::Project { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. } => check_plain_or_exact_values(&child.schema)?,
+        NonASAPOp::Aggregate {
+            reduction,
+            measures,
+            child,
+            ..
+        } => {
+            let mut referenced: Vec<usize> = reduction
+                .group_keys()
+                .map(|keys| keys.keys().to_vec())
+                .unwrap_or_default();
+            for m in measures {
+                referenced.extend(m.input_cols());
+            }
+            let implicit = measures.iter().any(|m| m.input_cols().is_empty());
+            for (i, field) in child.schema.fields.iter().enumerate() {
+                if (implicit || referenced.contains(&i)) && !field.is_plain() {
+                    return Err(ExecutionDataStateError::NonPlainOperand {
+                        column: field.name.clone(),
+                        dtype: format!("{:?}", field.dtype),
+                    });
+                }
+            }
+        }
+        NonASAPOp::BinaryOp {
+            operator, lhs, rhs, ..
+        } => {
+            let is_div = matches!(
+                operator.kind,
+                BinaryOpKind::Arithmetic(crate::pre_asap::ArithmeticOpKind::Div)
+            );
+            if (operator.checked_relative_division && operator.checked_finite_division)
+                || ((operator.checked_relative_division || operator.checked_finite_division)
+                    && (timing != ExecutionTiming::QueryTime || !is_div))
+            {
+                return Err(ExecutionDataStateError::InvalidCheckedDivision);
+            }
+            if timing == ExecutionTiming::IngestionTime {
+                let plain_float_or_ts = |schema: &Schema| {
+                    schema.fields.iter().all(|field| {
+                        !field.nullable
+                            && (matches!(
+                                field.dtype,
+                                FieldDataType::Plain(DataType::Float64 | DataType::Timestamp)
+                            ) || (field.name
+                                == crate::pre_asap::schema::PROMQL_SERIES_IDENTITY
+                                && field.dtype == FieldDataType::Plain(DataType::Utf8)))
+                    })
+                };
+                let float_count = node
+                    .schema
+                    .fields
+                    .iter()
+                    .filter(|f| matches!(f.dtype, FieldDataType::Plain(DataType::Float64)))
+                    .count();
+                if operator.vector_match.is_some()
+                    || !matches!(operator.kind, BinaryOpKind::Arithmetic(_))
+                    || lhs.schema != rhs.schema
+                    || lhs.schema != node.schema
+                    || node
+                        .schema
+                        .fields
+                        .iter()
+                        .filter(|f| f.name == crate::pre_asap::schema::PROMQL_SERIES_IDENTITY)
+                        .count()
+                        > 1
+                    || (node
+                        .schema
+                        .fields
+                        .iter()
+                        .any(|f| f.name == crate::pre_asap::schema::PROMQL_SERIES_IDENTITY)
+                        && per_series_rows(lhs)
+                            .is_none_or(|rows| per_series_rows(rhs) != Some(rows)))
+                    || !plain_float_or_ts(&node.schema)
+                    || float_count != 1
+                {
+                    return Err(ExecutionDataStateError::InvalidMaintenanceBinary);
+                }
+            }
+        }
+        _ => {
+            for child in op.children() {
+                check_all_plain(&child.schema)?;
+            }
+        }
+    }
+    Ok(())
+}
+
+/// Copy, for one consumer, every sub-DAG that `assignment` would reach with
+/// two different timings, so that a workload whose CSE shared a `Scan`
+/// between an ingestion-time summary and a query-time computation can still
+/// be timed. Only the conflicting sub-DAGs are copied; a sub-DAG reached with
+/// one timing stays one `Rc`. Returns the (possibly rewritten) root.
+pub fn split_shared_by_phase(
+    root: &Rc<OperatorNode>,
+    assignment: &LifecycleAssignment,
+) -> Rc<OperatorNode> {
+    // First pass: the set of timings each node is reached with.
+    let mut reached: HashMap<*const OperatorNode, Vec<ExecutionTiming>> = HashMap::new();
+    let mut forced = HashMap::new();
+    fn collect(
+        node: &Rc<OperatorNode>,
+        consumer: ExecutionTiming,
+        assignment: &LifecycleAssignment,
+        reached: &mut HashMap<*const OperatorNode, Vec<ExecutionTiming>>,
+        forced: &mut HashMap<*const OperatorNode, bool>,
+    ) {
+        let timing = own_timing(node, consumer, assignment, forced);
+        let entry = reached.entry(Rc::as_ptr(node)).or_default();
+        if entry.contains(&timing) {
+            return;
+        }
+        entry.push(timing);
+        for child in node.children() {
+            collect(child, timing, assignment, reached, forced);
+        }
+    }
+    collect(
+        root,
+        ExecutionTiming::QueryTime,
+        assignment,
+        &mut reached,
+        &mut forced,
+    );
+    if reached.values().all(|timings| timings.len() <= 1) {
+        return Rc::clone(root);
+    }
+    // Second pass: rebuild, giving each (node, timing) pair its own copy.
+    let mut copies: HashMap<(*const OperatorNode, ExecutionTiming), Rc<OperatorNode>> =
+        HashMap::new();
+    fn rebuild(
+        node: &Rc<OperatorNode>,
+        consumer: ExecutionTiming,
+        assignment: &LifecycleAssignment,
+        reached: &HashMap<*const OperatorNode, Vec<ExecutionTiming>>,
+        copies: &mut HashMap<(*const OperatorNode, ExecutionTiming), Rc<OperatorNode>>,
+        forced: &mut HashMap<*const OperatorNode, bool>,
+    ) -> Rc<OperatorNode> {
+        let timing = own_timing(node, consumer, assignment, forced);
+        let key = (Rc::as_ptr(node), timing);
+        if let Some(done) = copies.get(&key) {
+            return Rc::clone(done);
+        }
+        let conflicted = reached
+            .get(&Rc::as_ptr(node))
+            .is_some_and(|timings| timings.len() > 1);
+        let mut changed = conflicted;
+        let operator = node.operator.map_children(|child| {
+            let rebuilt = rebuild(child, timing, assignment, reached, copies, forced);
+            changed |= !Rc::ptr_eq(&rebuilt, child);
+            rebuilt
+        });
+        let out = if changed {
+            Rc::new(OperatorNode {
+                operator,
+                result_kind: node.result_kind,
+                schema: node.schema.clone(),
+                guarantee: node.guarantee.clone(),
+                timing: node.timing,
+                coverage: node.coverage.clone(),
+            })
+        } else {
+            Rc::clone(node)
+        };
+        copies.insert(key, Rc::clone(&out));
+        out
+    }
+    rebuild(
+        root,
+        ExecutionTiming::QueryTime,
+        assignment,
+        &reached,
+        &mut copies,
+        &mut forced,
+    )
+}
+
+/// Maintenance arithmetic needs the same per-series population on both sides.
+fn per_series_rows(node: &OperatorNode) -> Option<&OperatorNode> {
+    use crate::post_asap::ExactKind;
+    match &node.operator {
+        Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child }) => match &child.operator {
+            Operator::ASAP(ASAPOp::SummaryAgg {
+                child,
+                family: FieldDataType::ExactAggregate(ExactKind::Sum | ExactKind::Count, _),
+                reduction: crate::pre_asap::Reduction::PerEntity,
+                filter: None,
+                ..
+            }) => Some(child),
+            _ => None,
+        },
+        Operator::NonASAP(NonASAPOp::BinaryOp { lhs, rhs, .. }) => {
+            let rows = per_series_rows(lhs)?;
+            (per_series_rows(rhs) == Some(rows)).then_some(rows)
+        }
+        _ => None,
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::ir::non_asap::NonASAPOp;
+    use crate::ir::operator_properties::{Reduction, Source};
+    use crate::post_asap::sketch::{
+        ExactKind, ExactParams, GroupingStrategy, SketchAlgorithm, SketchKind, SketchParams,
+        SketchStatistic, SummaryUpdate,
+    };
+    use crate::pre_asap::agg_intent::AggIntent;
+    use crate::pre_asap::expr_ir::ColumnRef;
+    use crate::pre_asap::schema::Field;
+
+    fn scan_with(fields: Vec<Field>) -> Rc<OperatorNode> {
+        OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Scan {
+            source: Source::TimeSeries { metric: "m".into() },
+            predicates: vec![],
+            schema: Schema::with_time_index(fields, 0, vec![]),
+        }))
+        .unwrap()
+    }
+
+    fn scan() -> Rc<OperatorNode> {
+        scan_with(vec![
+            Field::plain("ts", DataType::Timestamp, false),
+            Field::plain("value", DataType::Float64, false),
+            Field::plain("zone", DataType::Utf8, true),
+        ])
+    }
+
+    fn kll() -> FieldDataType {
+        FieldDataType::Sketch(
+            SketchKind::new(SketchAlgorithm::Kll, SketchParams::Kll { k: 200 }),
+            GroupingStrategy::default(),
+        )
+    }
+
+    fn exact_sum() -> FieldDataType {
+        FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum)
+    }
+
+    fn agg(child: Rc<OperatorNode>, family: FieldDataType) -> Rc<OperatorNode> {
+        std::rc::Rc::new(
+            OperatorNode::with_schema(
+                crate::ir::Operator::ASAP(ASAPOp::SummaryAgg {
+                    child,
+                    family: family.clone(),
+                    input: SummaryUpdate::column(ColumnRef::SampleValue),
+                    reduction: Reduction::by(vec![]),
+                    grouping: GroupingStrategy::default(),
+                    filter: None,
+                }),
+                Schema::lifted(vec![Field::new("state", family, false)], None),
+            )
+            .with_guarantee(None),
+        )
+    }
+
+    fn estimate(child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+        std::rc::Rc::new(
+            OperatorNode::with_schema(
+                crate::ir::Operator::ASAP(ASAPOp::SummaryEstimate {
+                    summary_input: child,
+                    query: SketchStatistic::Quantile { q: 0.99 },
+                }),
+                Schema::lifted(
+                    vec![Field::plain("quantile_0_99", DataType::Float64, false)],
+                    None,
+                ),
+            )
+            .with_guarantee(None),
+        )
+    }
+
+    fn aggregate(measure: AggIntent, child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+        OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+            reduction: Reduction::by(vec![]),
+            measures: vec![measure],
+            output_names: vec![],
+            filters: vec![],
+            having: None,
+            child,
+        }))
+        .unwrap()
+    }
+
+    fn max(child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+        aggregate(AggIntent::Max { col: None }, child)
+    }
+
+    /// `node` with its timing fixed in advance, as a candidate builder does
+    /// for an operator that must feed maintenance.
+    fn placed_at_ingestion(node: Rc<OperatorNode>) -> Rc<OperatorNode> {
+        Rc::new(
+            (*node)
+                .clone()
+                .with_timing(Some(ExecutionTiming::IngestionTime)),
+        )
+    }
+
+    fn apply(root: &Rc<OperatorNode>) -> Result<Rc<OperatorNode>, ExecutionDataStateError> {
+        apply_lifecycle_timings(
+            root,
+            &LifecycleAssignment::default_maintained(),
+            &mut TimingMemo::new(),
+        )
+    }
+
+    fn child(node: &Rc<OperatorNode>) -> Rc<OperatorNode> {
+        Rc::clone(node.children()[0])
+    }
+
+    #[test]
+    fn summary_agg_input_runs_at_ingestion_time() {
+        let root = apply(&agg(scan(), kll())).unwrap();
+        assert_eq!(
+            data_state(&root),
+            Some(ExecutionDataState::INGESTION_SUMMARY)
+        );
+        assert_eq!(
+            data_state(&child(&root)),
+            Some(ExecutionDataState::INGESTION_ROWS)
+        );
+    }
+
+    #[test]
+    fn exact_accumulator_state_may_feed_another_summary_agg() {
+        let inner = agg(scan(), exact_sum());
+        assert!(apply(&estimate(agg(inner, kll()))).is_ok());
+    }
+
+    #[test]
+    fn evaluation_can_feed_summary_construction_at_query_time() {
+        let inner = estimate(agg(scan(), kll()));
+        let root = apply(&estimate(agg(inner, kll()))).unwrap();
+        assert_eq!(child(&root).timing, Some(ExecutionTiming::QueryTime));
+    }
+
+    /// Any non-ASAP operator over a evaluation runs at query time.
+    #[test]
+    fn query_time_operation_over_evaluation_is_legal_and_root_is_evaluation() {
+        let evaluation = || estimate(agg(scan(), kll()));
+        let sorted = OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Sort {
+            keys: vec![],
+            partition_by: Default::default(),
+            child: evaluation(),
+        }))
+        .unwrap();
+        for root in [max(evaluation()), sorted] {
+            let root = apply(&root).unwrap();
+            assert_eq!(data_state(&root), Some(ExecutionDataState::QUERY_ROWS));
+        }
+    }
+
+    #[test]
+    fn query_time_values_can_feed_query_time_summary_construction() {
+        let post = max(estimate(agg(scan(), kll())));
+        let root = apply(&estimate(agg(post, kll()))).unwrap();
+        assert_eq!(child(&root).timing, Some(ExecutionTiming::QueryTime));
+    }
+
+    #[test]
+    fn function_under_summary_agg_is_legal_but_not_at_root() {
+        let operation = placed_at_ingestion(max(scan()));
+        assert_eq!(
+            apply(&operation).err(),
+            Some(ExecutionDataStateError::MaintenanceRowsAtRoot)
+        );
+        let root = apply(&estimate(agg(operation, kll()))).unwrap();
+        let timed_operation = child(&child(&root));
+        assert_eq!(
+            data_state(&timed_operation),
+            Some(ExecutionDataState::INGESTION_ROWS)
+        );
+    }
+
+    #[test]
+    fn function_over_evaluation_is_rejected() {
+        let operation = placed_at_ingestion(max(estimate(agg(scan(), kll()))));
+        assert!(matches!(
+            apply(&estimate(agg(operation, kll()))),
+            Err(ExecutionDataStateError::IllegalChildDataState {
+                child: ExecutionDataState::QUERY_ROWS,
+                ..
+            })
+        ));
+    }
+
+    /// One shared sub-DAG reached as maintenance input and as query-time
+    /// input cannot be executed once for both; splitting it by phase first
+    /// makes the plan timeable.
+    #[test]
+    fn a_shared_subtree_reached_at_two_timings_conflicts() {
+        let shared = scan();
+        let root = OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Concat {
+            children: vec![
+                max(estimate(agg(Rc::clone(&shared), kll()))),
+                max(Rc::clone(&shared)),
+            ],
+            discriminator_unique_key: None,
+        }))
+        .unwrap();
+        assert_eq!(
+            apply(&root).err(),
+            Some(ExecutionDataStateError::ConflictingTiming {
+                first: ExecutionDataState::INGESTION_ROWS,
+                second: ExecutionDataState::QUERY_ROWS,
+            })
+        );
+        let split = split_shared_by_phase(&root, &LifecycleAssignment::default_maintained());
+        assert!(apply(&split).is_ok());
+    }
+
+    /// Both paired operands must be plain; an unrelated state column is not
+    /// an input.
+    #[test]
+    fn pearson_corr_checks_both_operand_states() {
+        let corr_over = |state_column: usize| {
+            let mut fields = vec![
+                Field::plain("ts", DataType::Timestamp, false),
+                Field::plain("x", DataType::Float64, false),
+                Field::plain("y", DataType::Float64, false),
+                Field::plain("unused", DataType::Float64, false),
+            ];
+            fields[state_column].dtype = kll();
+            aggregate(
+                AggIntent::PearsonCorr { left: 1, right: 2 },
+                scan_with(fields),
+            )
+        };
+        for operand in [1, 2] {
+            assert!(matches!(
+                validate_default(&corr_over(operand), ExecutionTiming::QueryTime),
+                Err(ExecutionDataStateError::NonPlainOperand { .. })
+            ));
+        }
+        validate_default(&corr_over(3), ExecutionTiming::QueryTime).unwrap();
+    }
+}
diff --git a/crates/types/src/post_asap/execution_data_state.rs b/crates/types/src/post_asap/execution_data_state.rs
index 91373816b..74f1d47d2 100644
--- a/crates/types/src/post_asap/execution_data_state.rs
+++ b/crates/types/src/post_asap/execution_data_state.rs
@@ -156,6 +156,18 @@ impl ExecutionDataStateEdge {
 /// it expects, and so tests can assert the *reason* a plan was rejected.
 #[derive(Debug, Clone, PartialEq, Eq, Error)]
 pub enum ExecutionDataStateError {
+    #[error("operator reached with conflicting execution timings: {first:?} and {second:?}")]
+    ConflictingTiming {
+        first: ExecutionDataState,
+        second: ExecutionDataState,
+    },
+    #[error("{operator} node has no execution timing")]
+    UntimedNode { operator: &'static str },
+    #[error("evaluation value under maintenance: {edge} received {child}")]
+    EvaluationUnderMaintenance {
+        edge: &'static str,
+        child: ExecutionDataState,
+    },
     #[error("invalid maintained-population maintenance/readout contract")]
     InvalidMaintainedPopulation,
     /// A query-time value (`SummaryEstimate` / read-time `ValueOperation` output)

From 59c30ac9be958a49fe19fa82ca54409f50a5ab4c Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 19:49:55 +0000
Subject: [PATCH 32/48] feat(ir): export timed plans as PhysicalASAPDAG

The logical export carries no execution timing. Physical planning output
needs it: reuse the logical payloads and node ids, and add each node's and
edge's data state plus window compatibility, as the earlier post-ASAP export
did. Coverage is carried through.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/types/src/ir/export.rs          |   2 +
 crates/types/src/ir/mod.rs             |   2 +
 crates/types/src/ir/physical_export.rs | 427 +++++++++++++++++++++++++
 crates/types/tests/physical_export.rs  | 102 ++++++
 4 files changed, 533 insertions(+)
 create mode 100644 crates/types/src/ir/physical_export.rs
 create mode 100644 crates/types/tests/physical_export.rs

diff --git a/crates/types/src/ir/export.rs b/crates/types/src/ir/export.rs
index 276d8ee43..df27e1418 100644
--- a/crates/types/src/ir/export.rs
+++ b/crates/types/src/ir/export.rs
@@ -9,6 +9,8 @@ use std::rc::Rc;
 use serde::{Deserialize, Serialize};
 use thiserror::Error;
 
+pub use super::physical_export::*;
+pub use super::wire::NonASAPOpKind;
 use super::wire::{grouping_compatibility, input_edges, payload_of};
 pub use super::wire::{
     EdgeRole, GroupingEdgeCompatibility, LogicalASAPNodeId, LogicalASAPOperatorPayload,
diff --git a/crates/types/src/ir/mod.rs b/crates/types/src/ir/mod.rs
index b6cf9f74d..f95d71902 100644
--- a/crates/types/src/ir/mod.rs
+++ b/crates/types/src/ir/mod.rs
@@ -18,6 +18,8 @@ pub use scalar::{ExprSemantics, Predicate, ProjectItem, ScalarExpr, SortKey};
 pub mod canonicalize;
 pub mod cse;
 pub mod export;
+/// Physical ASAP DAG transport: the logical payloads plus execution timing.
+pub mod physical_export;
 /// Execution timing for physical plans: a lifecycle assignment expanded onto every node.
 pub mod timing;
 pub use timing::{
diff --git a/crates/types/src/ir/physical_export.rs b/crates/types/src/ir/physical_export.rs
new file mode 100644
index 000000000..2142c1f94
--- /dev/null
+++ b/crates/types/src/ir/physical_export.rs
@@ -0,0 +1,427 @@
+//! Physical ASAP DAG transport (planner-layering stage 2 output).
+//!
+//! Same operator payloads as the logical export, plus the execution timing
+//! (data state) of every node and edge. The input must already be timed
+//! ([`super::timing::apply_lifecycle_timings`]); export reads each node's
+//! timing and does not re-run data-state validation.
+
+use std::collections::{BTreeMap, HashMap, HashSet};
+use std::rc::Rc;
+
+use serde::{Deserialize, Serialize};
+use thiserror::Error;
+
+use super::asap::ASAPOp;
+use super::node::{Operator, OperatorNode};
+use super::timing::data_state;
+use super::wire::{grouping_compatibility, input_edges, payload_of};
+use super::wire::{EdgeRole, GroupingEdgeCompatibility, LogicalASAPOperatorPayload};
+use crate::post_asap::execution_data_state::{
+    ExecutionDataState, ExecutionDataStateError, ExecutionTiming,
+};
+use crate::post_asap::guarantee::ResultGuarantee;
+use crate::pre_asap::schema::{FieldDataType, Schema};
+
+pub const PHYSICAL_ASAP_DAG_WIRE_VERSION: u32 = 8;
+
+/// Operator payloads are shared with the logical export.
+pub type PhysicalASAPOperatorPayload = LogicalASAPOperatorPayload;
+
+#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
+pub enum WindowEdgeCompatibility {
+    /// Physical lowering must prove equal pane/query phase or install an
+    /// exact boundary residual. The logical DAG alone cannot make that claim.
+    #[serde(rename = "RequiresAlignedPanePhaseOrExactBoundaryResidual")]
+    RequiresAlignedPanePhaseOrExactWindowEdgeResidual,
+    NotApplicable,
+}
+
+/// Node ids are shared with the logical export, since payloads embed them.
+pub type PhysicalASAPNodeId = super::wire::LogicalASAPNodeId;
+
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+#[serde(deny_unknown_fields)]
+pub struct PhysicalASAPDAGNode {
+    pub id: PhysicalASAPNodeId,
+    /// The payload variant is the sole operator identity (`payload.kind` in JSON).
+    pub payload: PhysicalASAPOperatorPayload,
+    /// Phase is a placement choice for every operator, independent of payload kind.
+    pub output_state: ExecutionDataState,
+    pub output_schema: Schema,
+    pub guarantee: Option<ResultGuarantee>,
+    #[serde(default)]
+    pub coverage: Option<super::summary_coverage::SummaryCoverage>,
+}
+
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+#[serde(deny_unknown_fields)]
+pub struct PhysicalASAPDAGEdge {
+    pub producer: PhysicalASAPNodeId,
+    pub consumer: PhysicalASAPNodeId,
+    pub role: EdgeRole,
+    pub intermediate_schema: Schema,
+    pub data_state: ExecutionDataState,
+    pub grouping: GroupingEdgeCompatibility,
+    pub window: WindowEdgeCompatibility,
+}
+
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+#[serde(deny_unknown_fields)]
+pub struct PhysicalASAPDAG {
+    pub nodes: Vec<PhysicalASAPDAGNode>,
+    pub edges: Vec<PhysicalASAPDAGEdge>,
+    /// Semantic workload root. Physical query/precompute sinks are selected
+    /// downstream by the control plane.
+    pub root: PhysicalASAPNodeId,
+}
+
+/// Versioned transport envelope for a physical ASAP DAG.
+///
+/// Process boundaries exchange this envelope and call [`Self::validate`].
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+#[serde(deny_unknown_fields)]
+pub struct PhysicalASAPDAGDocument {
+    pub schema_version: u32,
+    pub dag: PhysicalASAPDAG,
+}
+
+#[derive(Debug, Clone, PartialEq, Eq, Error)]
+pub enum PhysicalASAPDAGValidationError {
+    #[error("phase assignment must name every DAG node exactly once")]
+    IncompletePhaseAssignment,
+    #[error("ingestion node {consumer:?} depends on query node {producer:?}")]
+    QueryDependencyInIngestion {
+        producer: PhysicalASAPNodeId,
+        consumer: PhysicalASAPNodeId,
+    },
+    #[error("unsupported physical ASAP DAG schema version {0}")]
+    UnsupportedVersion(u32),
+    #[error("duplicate physical ASAP node id {0:?}")]
+    DuplicateNodeId(PhysicalASAPNodeId),
+    #[error("physical ASAP DAG root {0:?} does not name a node")]
+    MissingRoot(PhysicalASAPNodeId),
+    #[error("edge endpoint {0:?} does not name a node")]
+    MissingEdgeEndpoint(PhysicalASAPNodeId),
+    #[error("edge {producer:?}->{consumer:?} schema differs from producer output")]
+    EdgeSchemaMismatch {
+        producer: PhysicalASAPNodeId,
+        consumer: PhysicalASAPNodeId,
+    },
+    #[error("edge {producer:?}->{consumer:?} data state differs from producer output")]
+    EdgeDataStateMismatch {
+        producer: PhysicalASAPNodeId,
+        consumer: PhysicalASAPNodeId,
+    },
+    #[error("physical ASAP DAG contains a cycle")]
+    Cycle,
+    #[error("physical ASAP node {0:?} is not reachable from the root")]
+    UnreachableNode(PhysicalASAPNodeId),
+    #[error("summary aggregate node {node:?} output schema does not contain its declared family")]
+    SummaryFamilySchemaMismatch { node: PhysicalASAPNodeId },
+    #[error(
+        "summary aggregate node {node:?} declares grouping inconsistent with its sketch state"
+    )]
+    SummaryGroupingMismatch { node: PhysicalASAPNodeId },
+}
+
+impl PhysicalASAPDAGDocument {
+    pub fn new(dag: PhysicalASAPDAG) -> Self {
+        Self {
+            schema_version: PHYSICAL_ASAP_DAG_WIRE_VERSION,
+            dag,
+        }
+    }
+
+    pub fn validate(&self) -> Result<(), PhysicalASAPDAGValidationError> {
+        if self.schema_version != PHYSICAL_ASAP_DAG_WIRE_VERSION {
+            return Err(PhysicalASAPDAGValidationError::UnsupportedVersion(
+                self.schema_version,
+            ));
+        }
+        self.dag.validate()
+    }
+}
+
+impl PhysicalASAPDAG {
+    /// Assign execution phases without changing operator semantics. Phase choices
+    /// do not prove deployment support: callers must bind concrete implementations
+    /// and storage boundaries before installing this plan.
+    pub fn with_execution_phases(
+        &self,
+        phases: &BTreeMap<PhysicalASAPNodeId, ExecutionTiming>,
+    ) -> Result<Self, PhysicalASAPDAGValidationError> {
+        self.validate()?;
+        if phases.len() != self.nodes.len()
+            || self.nodes.iter().any(|node| !phases.contains_key(&node.id))
+        {
+            return Err(PhysicalASAPDAGValidationError::IncompletePhaseAssignment);
+        }
+        let mut dag = self.clone();
+        for node in &mut dag.nodes {
+            node.output_state.timing = phases[&node.id];
+        }
+        let states: HashMap<_, _> = dag.nodes.iter().map(|n| (n.id, n.output_state)).collect();
+        for edge in &mut dag.edges {
+            edge.data_state = states[&edge.producer];
+        }
+        dag.validate()?;
+        Ok(dag)
+    }
+
+    pub fn validate(&self) -> Result<(), PhysicalASAPDAGValidationError> {
+        let mut nodes = HashMap::new();
+        for node in &self.nodes {
+            if nodes.insert(node.id, node).is_some() {
+                return Err(PhysicalASAPDAGValidationError::DuplicateNodeId(node.id));
+            }
+            if let PhysicalASAPOperatorPayload::SummaryAgg {
+                family, grouping, ..
+            } = &node.payload
+            {
+                let mut found_family = false;
+                for field in &node.output_schema.fields {
+                    if &field.dtype == family {
+                        found_family = true;
+                    }
+                    if let FieldDataType::Sketch(_, schema_grouping) = &field.dtype {
+                        if schema_grouping != grouping {
+                            return Err(PhysicalASAPDAGValidationError::SummaryGroupingMismatch {
+                                node: node.id,
+                            });
+                        }
+                    }
+                }
+                if !found_family {
+                    return Err(
+                        PhysicalASAPDAGValidationError::SummaryFamilySchemaMismatch {
+                            node: node.id,
+                        },
+                    );
+                }
+            }
+        }
+        if !nodes.contains_key(&self.root) {
+            return Err(PhysicalASAPDAGValidationError::MissingRoot(self.root));
+        }
+        let mut children: HashMap<PhysicalASAPNodeId, Vec<PhysicalASAPNodeId>> = HashMap::new();
+        for edge in &self.edges {
+            let producer = nodes.get(&edge.producer).ok_or(
+                PhysicalASAPDAGValidationError::MissingEdgeEndpoint(edge.producer),
+            )?;
+            if !nodes.contains_key(&edge.consumer) {
+                return Err(PhysicalASAPDAGValidationError::MissingEdgeEndpoint(
+                    edge.consumer,
+                ));
+            }
+            if producer.output_state.timing == ExecutionTiming::QueryTime
+                && nodes[&edge.consumer].output_state.timing == ExecutionTiming::IngestionTime
+            {
+                return Err(PhysicalASAPDAGValidationError::QueryDependencyInIngestion {
+                    producer: edge.producer,
+                    consumer: edge.consumer,
+                });
+            }
+            if edge.intermediate_schema != producer.output_schema {
+                return Err(PhysicalASAPDAGValidationError::EdgeSchemaMismatch {
+                    producer: edge.producer,
+                    consumer: edge.consumer,
+                });
+            }
+            if edge.data_state != producer.output_state {
+                return Err(PhysicalASAPDAGValidationError::EdgeDataStateMismatch {
+                    producer: edge.producer,
+                    consumer: edge.consumer,
+                });
+            }
+            children
+                .entry(edge.consumer)
+                .or_default()
+                .push(edge.producer);
+        }
+        fn visit(
+            id: PhysicalASAPNodeId,
+            children: &HashMap<PhysicalASAPNodeId, Vec<PhysicalASAPNodeId>>,
+            visiting: &mut HashSet<PhysicalASAPNodeId>,
+            visited: &mut HashSet<PhysicalASAPNodeId>,
+        ) -> bool {
+            if visited.contains(&id) {
+                return true;
+            }
+            if !visiting.insert(id) {
+                return false;
+            }
+            if children
+                .get(&id)
+                .into_iter()
+                .flatten()
+                .any(|child| !visit(*child, children, visiting, visited))
+            {
+                return false;
+            }
+            visiting.remove(&id);
+            visited.insert(id);
+            true
+        }
+        if !visit(
+            self.root,
+            &children,
+            &mut HashSet::new(),
+            &mut HashSet::new(),
+        ) {
+            return Err(PhysicalASAPDAGValidationError::Cycle);
+        }
+        fn mark(
+            id: PhysicalASAPNodeId,
+            children: &HashMap<PhysicalASAPNodeId, Vec<PhysicalASAPNodeId>>,
+            reachable: &mut HashSet<PhysicalASAPNodeId>,
+        ) {
+            if !reachable.insert(id) {
+                return;
+            }
+            for child in children.get(&id).into_iter().flatten() {
+                mark(*child, children, reachable);
+            }
+        }
+        let mut reachable = HashSet::new();
+        mark(self.root, &children, &mut reachable);
+        if let Some(id) = nodes.keys().find(|id| !reachable.contains(id)) {
+            return Err(PhysicalASAPDAGValidationError::UnreachableNode(*id));
+        }
+        Ok(())
+    }
+}
+
+// ── Compilation from the IR ──────────────────────────────────────────────
+
+/// Compiler-local identity assignment. It deliberately retains `Rc` handles
+/// and is not serialized; deployed artifacts persist the physical ASAP node ID
+/// together with their physical materialization/query IDs.
+#[derive(Debug, Clone)]
+pub struct PhysicalASAPNodeIdentityMap {
+    nodes_by_id: Vec<Rc<OperatorNode>>,
+}
+
+impl PhysicalASAPNodeIdentityMap {
+    pub fn node_id(&self, node: &Rc<OperatorNode>) -> Option<PhysicalASAPNodeId> {
+        self.nodes_by_id
+            .iter()
+            .position(|candidate| Rc::ptr_eq(candidate, node))
+            .map(|id| super::wire::LogicalASAPNodeId(id as u32))
+    }
+
+    pub fn operator_node(&self, id: PhysicalASAPNodeId) -> Option<&Rc<OperatorNode>> {
+        self.nodes_by_id.get(id.0 as usize)
+    }
+}
+
+#[derive(Debug, Clone)]
+pub struct PhysicalASAPDAGCompilation {
+    pub dag: PhysicalASAPDAG,
+    pub node_ids: PhysicalASAPNodeIdentityMap,
+}
+
+pub fn compile_physical_asap_dag(
+    root: &Rc<OperatorNode>,
+) -> Result<PhysicalASAPDAG, ExecutionDataStateError> {
+    Ok(compile_physical_asap_dag_with_node_ids(root)?.dag)
+}
+
+/// Export the timed DAG below `root`. Every reachable node must carry a
+/// timing (see [`super::timing::apply_lifecycle_timings`]); the data-state
+/// rules were checked by that pass and are not re-run here.
+pub fn compile_physical_asap_dag_with_node_ids(
+    root: &Rc<OperatorNode>,
+) -> Result<PhysicalASAPDAGCompilation, ExecutionDataStateError> {
+    let mut exporter = Exporter::default();
+    let root = exporter.visit(root)?;
+    let dag = PhysicalASAPDAG {
+        nodes: exporter.nodes,
+        edges: exporter.edges,
+        root,
+    };
+    dag.validate()
+        .expect("compiler emits a valid physical ASAP DAG");
+    Ok(PhysicalASAPDAGCompilation {
+        dag,
+        node_ids: PhysicalASAPNodeIdentityMap {
+            nodes_by_id: exporter.nodes_by_id,
+        },
+    })
+}
+
+#[derive(Default)]
+struct Exporter {
+    ids: HashMap<*const OperatorNode, PhysicalASAPNodeId>,
+    nodes: Vec<PhysicalASAPDAGNode>,
+    edges: Vec<PhysicalASAPDAGEdge>,
+    nodes_by_id: Vec<Rc<OperatorNode>>,
+}
+
+impl Exporter {
+    fn visit(
+        &mut self,
+        node: &Rc<OperatorNode>,
+    ) -> Result<PhysicalASAPNodeId, ExecutionDataStateError> {
+        if let Some(id) = self.ids.get(&Rc::as_ptr(node)) {
+            return Ok(*id);
+        }
+        let output_state = data_state(node).ok_or(ExecutionDataStateError::UntimedNode {
+            operator: node.operator.kind_name(),
+        })?;
+        // Operator inputs first, then the nodes read from scalar expressions.
+        let mut producers = Vec::new();
+        for (child, role) in input_edges(&node.operator) {
+            producers.push((self.visit(child)?, child, role));
+        }
+        {
+            let scalars = match &node.operator {
+                Operator::NonASAP(op) => op.scalar_exprs(),
+                Operator::ASAP(ASAPOp::SummaryAgg {
+                    filter: Some(filter),
+                    ..
+                }) => vec![&filter.0],
+                _ => vec![],
+            };
+            for expr in scalars {
+                for referenced in expr.operator_refs() {
+                    producers.push((self.visit(referenced)?, referenced, EdgeRole::ScalarRef));
+                }
+            }
+        }
+        let id = super::wire::LogicalASAPNodeId(self.nodes.len() as u32);
+        let payload = {
+            let ids = &self.ids;
+            let mut id_of = |n: &Rc<OperatorNode>| ids[&Rc::as_ptr(n)];
+            payload_of(&node.operator, &mut id_of)
+        };
+        self.nodes.push(PhysicalASAPDAGNode {
+            id,
+            payload,
+            output_state,
+            output_schema: node.schema.clone(),
+            guarantee: node.guarantee.clone(),
+            coverage: node.coverage.clone(),
+        });
+        self.nodes_by_id.push(Rc::clone(node));
+        self.ids.insert(Rc::as_ptr(node), id);
+        for (producer, child, role) in producers {
+            let producer_state = self.nodes[producer.0 as usize].output_state;
+            let maintenance_dependency = producer_state.timing == ExecutionTiming::IngestionTime
+                && output_state.timing == ExecutionTiming::IngestionTime;
+            self.edges.push(PhysicalASAPDAGEdge {
+                producer,
+                consumer: id,
+                role,
+                intermediate_schema: child.schema.clone(),
+                data_state: producer_state,
+                grouping: grouping_compatibility(&child.operator, &node.operator),
+                window: if maintenance_dependency {
+                    WindowEdgeCompatibility::RequiresAlignedPanePhaseOrExactWindowEdgeResidual
+                } else {
+                    WindowEdgeCompatibility::NotApplicable
+                },
+            });
+        }
+        Ok(id)
+    }
+}
diff --git a/crates/types/tests/physical_export.rs b/crates/types/tests/physical_export.rs
new file mode 100644
index 000000000..2008a66d3
--- /dev/null
+++ b/crates/types/tests/physical_export.rs
@@ -0,0 +1,102 @@
+//! A timed plan exports as a PhysicalASAPDAG that keeps timing and coverage.
+use asap_types::ir::export::{
+    compile_physical_asap_dag, PhysicalASAPDAGDocument, PhysicalASAPDAGValidationError,
+};
+use asap_types::ir::summary_coverage::{CoverageRegion, SummaryCoverage};
+use asap_types::ir::{
+    apply_lifecycle_timings, ASAPOp, LifecycleAssignment, NonASAPOp, Operator, OperatorNode,
+    TimingMemo,
+};
+use asap_types::post_asap::{ExactKind, ExactParams, ExecutionTiming, SummaryUpdate};
+use asap_types::pre_asap::{ColumnRef, DataType, Field, FieldDataType, Reduction, Schema, Source};
+use std::rc::Rc;
+
+/// Scan(t) → SummaryAgg(sum by key) → FinalizeExactAccumulator, untimed.
+fn plan() -> Rc<OperatorNode> {
+    let source = Source::Table {
+        table_ref: "t".into(),
+    };
+    let scan = OperatorNode::new_shared(Operator::NonASAP(NonASAPOp::Scan {
+        source: source.clone(),
+        predicates: vec![],
+        schema: Schema::new(vec![
+            Field::plain("key", DataType::Utf8, false),
+            Field::plain("value", DataType::Float64, false),
+        ]),
+    }))
+    .unwrap();
+    let state = OperatorNode::new(Operator::ASAP(ASAPOp::SummaryAgg {
+        child: scan,
+        family: FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum),
+        input: SummaryUpdate::column(ColumnRef::Named("value".into())),
+        reduction: Reduction::by(vec![0]),
+        grouping: Default::default(),
+        filter: None,
+    }))
+    .unwrap()
+    .with_coverage(SummaryCoverage {
+        source,
+        regions: vec![CoverageRegion {
+            time_ms: Some(0..60_000),
+            population: Default::default(),
+        }],
+    })
+    .unwrap();
+    OperatorNode::new_shared(Operator::ASAP(ASAPOp::FinalizeExactAccumulator {
+        child: Rc::new(state),
+    }))
+    .unwrap()
+}
+
+/// Default lifecycle: the summary is maintained at ingestion time and read at query time.
+#[test]
+fn timed_plan_exports_with_timing_and_coverage() {
+    let timed = apply_lifecycle_timings(
+        &plan(),
+        &LifecycleAssignment::default_maintained(),
+        &mut TimingMemo::new(),
+    )
+    .unwrap();
+    let dag = compile_physical_asap_dag(&timed).unwrap();
+    let document = PhysicalASAPDAGDocument::new(dag.clone());
+    document.validate().unwrap();
+
+    let timings: Vec<_> = dag.nodes.iter().map(|n| n.output_state.timing).collect();
+    assert_eq!(
+        timings,
+        vec![
+            ExecutionTiming::IngestionTime,
+            ExecutionTiming::IngestionTime,
+            ExecutionTiming::QueryTime
+        ]
+    );
+    assert!(dag.nodes[1].coverage.is_some());
+
+    let decoded: PhysicalASAPDAGDocument =
+        serde_json::from_str(&serde_json::to_string(&document).unwrap()).unwrap();
+    assert_eq!(decoded, document);
+}
+
+/// A query-time producer cannot feed an ingestion-time consumer.
+#[test]
+fn query_time_input_to_ingestion_is_rejected() {
+    let timed = apply_lifecycle_timings(
+        &plan(),
+        &LifecycleAssignment::default_maintained(),
+        &mut TimingMemo::new(),
+    )
+    .unwrap();
+    let mut dag = compile_physical_asap_dag(&timed).unwrap();
+    dag.nodes[0].output_state.timing = ExecutionTiming::QueryTime;
+    dag.edges[0].data_state = dag.nodes[0].output_state;
+    assert!(matches!(
+        dag.validate(),
+        Err(PhysicalASAPDAGValidationError::QueryDependencyInIngestion { .. })
+    ));
+}
+
+/// Untimed plans cannot be exported as physical plans.
+#[test]
+fn untimed_plan_is_rejected() {
+    assert!(compile_physical_asap_dag(&plan()).is_err());
+}

From 70ee3ff414d9e9fddc2767284a14a9994d1b497f Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Fri, 2 Oct 2026 21:20:43 +0000
Subject: [PATCH 33/48] feat(runtime): compile unified operator and scalar
 graphs

---
 Cargo.lock                                    |    1 +
 crates/asap-physical-operators/Cargo.toml     |    1 +
 .../src/expressions/binary.rs                 |    3 +
 .../src/expressions/mod.rs                    |   11 +
 .../src/expressions/planner.rs                |    4 -
 .../src/expressions/unified_planner.rs        |  738 ++++++++
 crates/asap-physical-operators/src/lib.rs     |    3 +
 .../src/operators/joins/mod.rs                |   36 +-
 .../src/operators/mod.rs                      |    2 +-
 .../src/operators/unchecked.rs                |    6 +-
 .../unified_physical_planner/candidates.rs    |  327 ++++
 .../src/unified_physical_planner/compiled.rs  |  352 ++++
 .../src/unified_physical_planner/logical.rs   |  374 ++++
 .../src/unified_physical_planner/mod.rs       | 1169 ++++++++++++
 .../unified_physical_planner/precompute.rs    |  643 +++++++
 .../promql_fallback.rs                        |  859 +++++++++
 .../unified_physical_planner/promql_rows.rs   |  303 ++++
 .../unified_physical_planner/promql_values.rs |  281 +++
 .../unified_physical_planner/row_values.rs    |   60 +
 .../src/unified_sources/memory.rs             |   44 +
 .../src/unified_sources/mod.rs                |  177 ++
 .../tests/unified_common/mod.rs               |   15 +
 .../tests/unified_promql_fallback.rs          | 1611 +++++++++++++++++
 crates/types/src/post_asap/expr.rs            |   18 +
 24 files changed, 7026 insertions(+), 12 deletions(-)
 create mode 100644 crates/asap-physical-operators/src/expressions/binary.rs
 create mode 100644 crates/asap-physical-operators/src/expressions/unified_planner.rs
 create mode 100644 crates/asap-physical-operators/src/unified_physical_planner/candidates.rs
 create mode 100644 crates/asap-physical-operators/src/unified_physical_planner/compiled.rs
 create mode 100644 crates/asap-physical-operators/src/unified_physical_planner/logical.rs
 create mode 100644 crates/asap-physical-operators/src/unified_physical_planner/mod.rs
 create mode 100644 crates/asap-physical-operators/src/unified_physical_planner/precompute.rs
 create mode 100644 crates/asap-physical-operators/src/unified_physical_planner/promql_fallback.rs
 create mode 100644 crates/asap-physical-operators/src/unified_physical_planner/promql_rows.rs
 create mode 100644 crates/asap-physical-operators/src/unified_physical_planner/promql_values.rs
 create mode 100644 crates/asap-physical-operators/src/unified_physical_planner/row_values.rs
 create mode 100644 crates/asap-physical-operators/src/unified_sources/memory.rs
 create mode 100644 crates/asap-physical-operators/src/unified_sources/mod.rs
 create mode 100644 crates/asap-physical-operators/tests/unified_common/mod.rs
 create mode 100644 crates/asap-physical-operators/tests/unified_promql_fallback.rs

diff --git a/Cargo.lock b/Cargo.lock
index feed74cf1..79da8962c 100644
--- a/Cargo.lock
+++ b/Cargo.lock
@@ -406,6 +406,7 @@ dependencies = [
  "asap-frontend-promql",
  "asap-types",
  "asap_sketchlib 0.3.0 (git+https://github.com/ProjectASAP/asap_sketchlib?rev=5f03ccbd798ed5fec62bdd839bcb331123cab369)",
+ "chrono",
  "futures",
  "regex",
  "rmp-serde",
diff --git a/crates/asap-physical-operators/Cargo.toml b/crates/asap-physical-operators/Cargo.toml
index 193707c48..5d33b6086 100644
--- a/crates/asap-physical-operators/Cargo.toml
+++ b/crates/asap-physical-operators/Cargo.toml
@@ -4,6 +4,7 @@ version = "0.1.0"
 edition = "2021"
 
 [dependencies]
+chrono = { version = "=0.4.39", default-features = false, features = ["std"] }
 futures = "0.3"
 planner-types = { package = "asap-types", path = "../types" }
 asap_sketchlib = { git = "https://github.com/ProjectASAP/asap_sketchlib", rev = "5f03ccbd798ed5fec62bdd839bcb331123cab369" }
diff --git a/crates/asap-physical-operators/src/expressions/binary.rs b/crates/asap-physical-operators/src/expressions/binary.rs
new file mode 100644
index 000000000..c115fd908
--- /dev/null
+++ b/crates/asap-physical-operators/src/expressions/binary.rs
@@ -0,0 +1,3 @@
+//! Temporary kernel aliases during the unified compiler migration.
+pub use planner_types::post_asap::BinaryOperator;
+pub use planner_types::pre_asap::BinaryOpKind;
diff --git a/crates/asap-physical-operators/src/expressions/mod.rs b/crates/asap-physical-operators/src/expressions/mod.rs
index 8947743dc..5c1a29576 100644
--- a/crates/asap-physical-operators/src/expressions/mod.rs
+++ b/crates/asap-physical-operators/src/expressions/mod.rs
@@ -5,7 +5,9 @@ use crate::{
 };
 use planner_types::pre_asap::{ArithmeticOpKind, DataType};
 pub mod arithmetic;
+pub mod binary;
 mod planner;
+pub mod unified_planner;
 pub use planner::CompiledExpression;
 #[derive(serde::Serialize, serde::Deserialize, Clone, Debug)]
 pub enum Expression {
@@ -15,6 +17,7 @@ pub enum Expression {
         right: Box<Expression>,
     },
     Planner(Box<crate::expressions::CompiledExpression>),
+    UnifiedPlanner(Box<unified_planner::CompiledExpression>),
     Column(usize),
     ExactFloat64(usize),
     FiniteFloat64(Box<Expression>),
@@ -53,6 +56,9 @@ pub enum Expression {
     IsNull(Box<Expression>),
 }
 impl Expression {
+    pub fn unified_planner(expression: unified_planner::CompiledExpression) -> Self {
+        Self::UnifiedPlanner(Box::new(expression))
+    }
     pub fn planner(expression: crate::expressions::CompiledExpression) -> Self {
         Self::Planner(Box::new(expression))
     }
@@ -99,6 +105,10 @@ impl Expression {
                 };
                 Ok((dtype, n || m))
             }
+            UnifiedPlanner(expression) => {
+                expression.validate_input(input)?;
+                Ok(expression.dtype())
+            }
             Planner(expression) => {
                 expression.validate_input(input)?;
                 Ok(expression.dtype())
@@ -286,6 +296,7 @@ impl Expression {
                 }
             }
             Planner(expression) => expression.evaluate(row)?,
+            UnifiedPlanner(expression) => expression.evaluate(row)?,
             Label { column, name } => {
                 let Value::Map(entries) = &row[*column] else {
                     return Err(invalid("label read requires a map"));
diff --git a/crates/asap-physical-operators/src/expressions/planner.rs b/crates/asap-physical-operators/src/expressions/planner.rs
index ae04b3f7c..2044d6e16 100644
--- a/crates/asap-physical-operators/src/expressions/planner.rs
+++ b/crates/asap-physical-operators/src/expressions/planner.rs
@@ -336,10 +336,6 @@ pub struct CompiledExpression {
     output: (DataType, bool),
 }
 impl CompiledExpression {
-    pub(crate) fn expression(&self) -> &QueryExpr {
-        &self.expression
-    }
-
     pub fn compile(expression: &QueryExpr, input: &SchemaRef) -> Result<Self, Error> {
         let schema = input
             .fields
diff --git a/crates/asap-physical-operators/src/expressions/unified_planner.rs b/crates/asap-physical-operators/src/expressions/unified_planner.rs
new file mode 100644
index 000000000..a23b3dab1
--- /dev/null
+++ b/crates/asap-physical-operators/src/expressions/unified_planner.rs
@@ -0,0 +1,738 @@
+//! Planner scalar expressions evaluated over native typed rows.
+use crate::{
+    values::{SchemaRef, Value},
+    Error,
+};
+use planner_types::pre_asap::{ArithmeticOpKind, CompareOpKind, DataType, ScalarValue};
+
+use planner_types::ir::ScalarExpr;
+use std::{cmp::Ordering, sync::Arc};
+
+pub(super) fn evaluate(
+    expr: &ScalarExpr,
+    row: &[Value],
+    schema: &planner_types::pre_asap::Schema,
+) -> Result<Value, Error> {
+    match expr {
+        ScalarExpr::Column(index) => row.get(*index).cloned().ok_or(Error::Invalid(format!(
+            "column {index} outside row width {}",
+            row.len()
+        ))),
+        ScalarExpr::Literal(value) => Ok(match value {
+            ScalarValue::Interval {
+                months,
+                days,
+                nanos,
+            } => Value::Interval {
+                months: *months,
+                days: *days,
+                nanos: *nanos,
+            },
+            ScalarValue::Int64(value) => Value::Int64(*value),
+            ScalarValue::Float64(value) => Value::Float64(*value),
+            ScalarValue::Utf8(value) => Value::Utf8(value.clone().into()),
+            ScalarValue::Boolean(value) => Value::Bool(*value),
+            ScalarValue::Null => Value::Null,
+        }),
+        ScalarExpr::Cast { expr, to, .. } => {
+            let value = evaluate(expr, row, schema)?;
+            match (value, to) {
+                (Value::Null, _) => Ok(Value::Null),
+                (Value::Int64(value), DataType::Float64) => Ok(Value::Float64(value as f64)),
+                (value, _)
+                    if expr
+                        .scalar_type(schema)
+                        .map_err(|e| Error::Invalid(e.to_string()))?
+                        .0
+                        == *to =>
+                {
+                    Ok(value)
+                }
+                _ => Err(Error::Invalid("unsupported cast".into())),
+            }
+        }
+        ScalarExpr::Negative { expr, .. } => match evaluate(expr, row, schema)? {
+            Value::Float64(v) => Ok(Value::Float64(-v)),
+            Value::Int64(v) => v
+                .checked_neg()
+                .map(Value::Int64)
+                .ok_or_else(|| Error::Invalid("integer negation overflow".into())),
+            Value::Null => Ok(Value::Null),
+            _ => Err(Error::Invalid("invalid negation input".into())),
+        },
+        ScalarExpr::Compare {
+            left, op, right, ..
+        } => {
+            let left = evaluate(left, row, schema)?;
+            let right = evaluate(right, row, schema)?;
+            compare(op, left, right)
+        }
+        ScalarExpr::Arithmetic {
+            op, left, right, ..
+        } => arithmetic(
+            op,
+            evaluate(left, row, schema)?,
+            evaluate(right, row, schema)?,
+        ),
+        ScalarExpr::Case {
+            operand: None,
+            branches,
+            else_expr,
+        } => {
+            for (condition, value) in branches {
+                if matches!(evaluate(condition, row, schema)?, Value::Bool(true)) {
+                    return evaluate(value, row, schema);
+                }
+            }
+            else_expr
+                .as_ref()
+                .map_or(Ok(Value::Null), |e| evaluate(e, row, schema))
+        }
+        ScalarExpr::BoolAnd(parts) | ScalarExpr::BoolOr(parts) => {
+            let and = matches!(expr, ScalarExpr::BoolAnd(_));
+            let mut null = false;
+            for part in parts {
+                match evaluate(part, row, schema)? {
+                    Value::Bool(value) if value != and => return Ok(Value::Bool(value)),
+                    Value::Bool(_) => {}
+                    Value::Null => null = true,
+                    _ => return Err(Error::Invalid("boolean predicate required".into())),
+                }
+            }
+            Ok(if null { Value::Null } else { Value::Bool(and) })
+        }
+        ScalarExpr::Not(value) => match evaluate(value, row, schema)? {
+            Value::Bool(value) => Ok(Value::Bool(!value)),
+            Value::Null => Ok(Value::Null),
+            _ => Err(Error::Invalid("boolean predicate required".into())),
+        },
+        ScalarExpr::IsNull(value) => Ok(Value::Bool(matches!(
+            evaluate(value, row, schema)?,
+            Value::Null
+        ))),
+        ScalarExpr::IsNotNull(value) => Ok(Value::Bool(!matches!(
+            evaluate(value, row, schema)?,
+            Value::Null
+        ))),
+        ScalarExpr::FunctionCall { name, args } => {
+            use planner_types::pre_asap::scalar_type_rules::MapScalarFunction;
+            if planner_types::pre_asap::scalar_type_rules::promql_function_arity(name).is_some() {
+                let values = args
+                    .iter()
+                    .map(|arg| match evaluate(arg, row, schema)? {
+                        Value::Float64(v) => Ok(v),
+                        _ => Err(Error::Invalid("PromQL function requires floats".into())),
+                    })
+                    .collect::<Result<Vec<_>, _>>()?;
+                return Ok(Value::Float64(promql_function(name, &values)?));
+            }
+            if name == "promql_drop_metric_name" {
+                let Value::Utf8(encoded) = evaluate(&args[0], row, schema)? else {
+                    return Err(Error::Invalid("series identity must be Utf8".into()));
+                };
+                let mut labels: std::collections::BTreeMap<String, String> =
+                    serde_json::from_str(&encoded).map_err(|e| Error::Invalid(e.to_string()))?;
+                labels.remove("__name__");
+                return Ok(Value::Utf8(
+                    serde_json::to_string(&labels)
+                        .map_err(|e| Error::Invalid(e.to_string()))?
+                        .into(),
+                ));
+            }
+            if name.eq_ignore_ascii_case("asap_struct_field") {
+                expr.scalar_type(schema)
+                    .map_err(|error| Error::Invalid(error.to_string()))?;
+                let DataType::Struct { fields } = args[0]
+                    .scalar_type(schema)
+                    .map_err(|error| Error::Invalid(error.to_string()))?
+                    .0
+                else {
+                    unreachable!()
+                };
+                let offset = match &args[1] {
+                    ScalarExpr::Literal(ScalarValue::Int64(index)) => {
+                        usize::try_from(index - 1).ok()
+                    }
+                    ScalarExpr::Literal(ScalarValue::Utf8(name)) => {
+                        fields.iter().position(|field| &field.name == name)
+                    }
+                    _ => None,
+                }
+                .ok_or_else(|| Error::Invalid("struct field selector".into()))?;
+                let Value::Struct(values) = evaluate(&args[0], row, schema)? else {
+                    return Err(Error::Invalid("struct field input".into()));
+                };
+                return values
+                    .get(offset)
+                    .cloned()
+                    .ok_or_else(|| Error::Invalid("struct field value".into()));
+            }
+            if name.eq_ignore_ascii_case("asap_element_access") {
+                let (output_type, _) = expr
+                    .scalar_type(schema)
+                    .map_err(|error| Error::Invalid(error.to_string()))?;
+                if let DataType::List { element } = args[0]
+                    .scalar_type(schema)
+                    .map_err(|error| Error::Invalid(error.to_string()))?
+                    .0
+                {
+                    let Value::List(values) = evaluate(&args[0], row, schema)? else {
+                        return Err(Error::Invalid("array access input".into()));
+                    };
+                    let index = match evaluate(&args[1], row, schema)? {
+                        Value::Null => return Ok(Value::Null),
+                        Value::Int64(index) => index,
+                        _ => return Err(Error::Invalid("array access index".into())),
+                    };
+                    let offset = if index > 0 {
+                        usize::try_from(index - 1).ok()
+                    } else if index < 0 {
+                        usize::try_from(index.unsigned_abs())
+                            .ok()
+                            .and_then(|distance| values.len().checked_sub(distance))
+                    } else {
+                        None
+                    };
+                    return match offset.and_then(|offset| values.get(offset)) {
+                        Some(value) => Ok(value.clone()),
+                        None => default_collection_element(&output_type, element.nullable),
+                    };
+                }
+            }
+            let function = (if name.eq_ignore_ascii_case("asap_element_access") {
+                Some(MapScalarFunction::Access)
+            } else {
+                MapScalarFunction::from_name(name)
+            })
+            .ok_or_else(|| Error::Invalid(format!("scalar function {name}")))?;
+            expr.scalar_type(schema)
+                .map_err(|error| Error::Invalid(error.to_string()))?;
+            let values = args
+                .iter()
+                .map(|arg| evaluate(arg, row, schema))
+                .collect::<Result<Vec<_>, _>>()?;
+            match function {
+                MapScalarFunction::Construct => {
+                    let mut values = values.into_iter();
+                    let mut entries = Vec::new();
+                    while let Some(key) = values.next() {
+                        if !matches!(key, Value::Int64(_) | Value::Utf8(_) | Value::Bool(_)) {
+                            return Err(Error::Invalid("map key value type".into()));
+                        }
+                        entries.push((
+                            key,
+                            values
+                                .next()
+                                .ok_or_else(|| Error::Invalid("odd map argument count".into()))?,
+                        ));
+                    }
+                    Ok(Value::Map(entries.into()))
+                }
+                MapScalarFunction::Concat => {
+                    let mut entries = Vec::new();
+                    for value in values {
+                        let Value::Map(next) = value else {
+                            return Err(Error::Invalid("map concat argument".into()));
+                        };
+                        entries.extend(next.iter().cloned());
+                    }
+                    Ok(Value::Map(entries.into()))
+                }
+                MapScalarFunction::Access => {
+                    let [Value::Map(entries), key] = values.as_slice() else {
+                        return Err(Error::Invalid("map access arguments".into()));
+                    };
+                    if matches!(key, Value::Null) {
+                        return Ok(Value::Null);
+                    }
+                    if !matches!(key, Value::Int64(_) | Value::Utf8(_) | Value::Bool(_)) {
+                        return Err(Error::Invalid("map lookup key type".into()));
+                    }
+                    if let Some((_, value)) = entries
+                        .iter()
+                        .find(|(candidate, _)| cell_cmp(candidate, key) == Some(Ordering::Equal))
+                    {
+                        return Ok(value.clone());
+                    }
+                    let (
+                        DataType::Map {
+                            value,
+                            value_nullable,
+                            ..
+                        },
+                        _,
+                    ) = args[0]
+                        .scalar_type(schema)
+                        .map_err(|error| Error::Invalid(error.to_string()))?
+                    else {
+                        unreachable!()
+                    };
+                    default_collection_element(&value, value_nullable)
+                }
+            }
+        }
+        other => Err(Error::Invalid(format!("scalar expression {other:?}"))),
+    }
+}
+
+fn default_collection_element(dtype: &DataType, nullable: bool) -> Result<Value, Error> {
+    if nullable {
+        return Ok(Value::Null);
+    }
+    Ok(match dtype {
+        DataType::Interval | DataType::Date => {
+            return Err(Error::Invalid("temporal value transport".into()))
+        }
+        DataType::Null => Value::Null,
+        DataType::Int64 => Value::Int64(0),
+        DataType::Float64 => Value::Float64(0.0),
+        DataType::Utf8 => Value::Utf8("".into()),
+        DataType::Bool => Value::Bool(false),
+        DataType::Map { .. } => Value::Map(Arc::from([])),
+        DataType::List { .. } => Value::List(Arc::from([])),
+        DataType::Struct { fields } => Value::Struct(
+            fields
+                .iter()
+                .map(|field| default_collection_element(&field.dtype, field.nullable))
+                .collect::<Result<Vec<_>, _>>()?
+                .into(),
+        ),
+        _ => {
+            return Err(Error::Invalid(
+                "collection missing-element default type".into(),
+            ))
+        }
+    })
+}
+
+fn compare(op: &CompareOpKind, left: Value, right: Value) -> Result<Value, Error> {
+    if matches!(left, Value::Null) || matches!(right, Value::Null) {
+        return Ok(Value::Null);
+    }
+    // NaN is unordered, not a type mismatch. Match the native scalar path.
+    if matches!(&left, Value::Float64(v) if v.is_nan())
+        || matches!(&right, Value::Float64(v) if v.is_nan())
+    {
+        return match op {
+            CompareOpKind::Ne => Ok(Value::Bool(true)),
+            CompareOpKind::Eq
+            | CompareOpKind::Lt
+            | CompareOpKind::Le
+            | CompareOpKind::Gt
+            | CompareOpKind::Ge => Ok(Value::Bool(false)),
+            _ => Err(Error::Invalid(format!("comparison {op:?}"))),
+        };
+    }
+    let ordering = cell_cmp(&left, &right)
+        .ok_or_else(|| Error::Invalid("comparison of incompatible values".into()))?;
+    let value = match op {
+        CompareOpKind::Eq => ordering == Ordering::Equal,
+        CompareOpKind::Ne => ordering != Ordering::Equal,
+        CompareOpKind::Lt => ordering == Ordering::Less,
+        CompareOpKind::Le => ordering != Ordering::Greater,
+        CompareOpKind::Gt => ordering == Ordering::Greater,
+        CompareOpKind::Ge => ordering != Ordering::Less,
+        _ => return Err(Error::Invalid(format!("comparison {op:?}"))),
+    };
+    Ok(Value::Bool(value))
+}
+
+fn arithmetic(op: &ArithmeticOpKind, left: Value, right: Value) -> Result<Value, Error> {
+    let (left, right) = match (left, right) {
+        (Value::Int64(a), Value::Float64(b)) => (Value::Float64(a as f64), Value::Float64(b)),
+        (Value::Float64(a), Value::Int64(b)) => (Value::Float64(a), Value::Float64(b as f64)),
+        pair => pair,
+    };
+    super::numeric(op, left, right)
+}
+
+fn integer_float_cmp(integer: i64, float: f64) -> Option<Ordering> {
+    if float.is_nan() {
+        return None;
+    }
+    // These bounds are powers of two, exactly representable as Float64.
+    if float >= 9_223_372_036_854_775_808.0 {
+        return Some(Ordering::Less);
+    }
+    if float < -9_223_372_036_854_775_808.0 {
+        return Some(Ordering::Greater);
+    }
+    let integral = float as i64;
+    match integer.cmp(&integral) {
+        Ordering::Equal => 0.0_f64.partial_cmp(&float.fract()),
+        other => Some(other),
+    }
+}
+
+fn cell_cmp(left: &Value, right: &Value) -> Option<Ordering> {
+    match (left, right) {
+        (Value::Int64(left), Value::Int64(right)) => Some(left.cmp(right)),
+        (Value::Float64(left), Value::Float64(right)) => left.partial_cmp(right),
+        (Value::Int64(left), Value::Float64(right)) => integer_float_cmp(*left, *right),
+        (Value::Float64(left), Value::Int64(right)) => {
+            integer_float_cmp(*right, *left).map(Ordering::reverse)
+        }
+        (Value::Utf8(left), Value::Utf8(right)) => Some(left.cmp(right)),
+        (Value::Bool(left), Value::Bool(right)) => Some(left.cmp(right)),
+        (Value::Timestamp(left), Value::Timestamp(right)) => Some(left.cmp(right)),
+        (Value::Map(left), Value::Map(right)) => {
+            for ((left_key, left_value), (right_key, right_value)) in left.iter().zip(right.iter())
+            {
+                let order = cell_cmp(left_key, right_key)?;
+                if order != Ordering::Equal {
+                    return Some(order);
+                }
+                let order = match (left_value, right_value) {
+                    (Value::Null, Value::Null) => Ordering::Equal,
+                    (Value::Null, _) => Ordering::Greater,
+                    (_, Value::Null) => Ordering::Less,
+                    _ => cell_cmp(left_value, right_value)?,
+                };
+                if order != Ordering::Equal {
+                    return Some(order);
+                }
+            }
+            Some(left.len().cmp(&right.len()))
+        }
+        _ => None,
+    }
+}
+
+fn promql_function(name: &str, args: &[f64]) -> Result<f64, Error> {
+    let x = args[0];
+    Ok(match &name[7..] {
+        "abs" => x.abs(),
+        "ceil" => x.ceil(),
+        "floor" => x.floor(),
+        "exp" => x.exp(),
+        "ln" => x.ln(),
+        "log2" => x.log2(),
+        "log10" => x.log10(),
+        "sqrt" => x.sqrt(),
+        "sgn" => {
+            if x.is_nan() {
+                f64::NAN
+            } else if x == 0.0 {
+                0.0
+            } else {
+                x.signum()
+            }
+        }
+        "sin" => x.sin(),
+        "cos" => x.cos(),
+        "tan" => x.tan(),
+        "asin" => x.asin(),
+        "acos" => x.acos(),
+        "atan" => x.atan(),
+        "sinh" => x.sinh(),
+        "cosh" => x.cosh(),
+        "tanh" => x.tanh(),
+        "asinh" => x.asinh(),
+        "acosh" => x.acosh(),
+        "atanh" => x.atanh(),
+        "deg" => x.to_degrees(),
+        "rad" => x.to_radians(),
+        "round" => {
+            let inverse = 1.0 / args[1];
+            (x * inverse + 0.5).floor() / inverse
+        }
+        "clamp_min" => {
+            if x.is_nan() || args[1].is_nan() {
+                f64::NAN
+            } else {
+                x.max(args[1])
+            }
+        }
+        "clamp_max" => {
+            if x.is_nan() || args[1].is_nan() {
+                f64::NAN
+            } else {
+                x.min(args[1])
+            }
+        }
+        "clamp" => {
+            if args.iter().any(|x| x.is_nan()) {
+                f64::NAN
+            } else {
+                x.max(args[1]).min(args[2])
+            }
+        }
+        part => {
+            use chrono::{Datelike, Timelike};
+            if !x.is_finite() || x < i64::MIN as f64 || x >= i64::MAX as f64 {
+                return Ok(f64::NAN);
+            }
+            let Some(date) = chrono::DateTime::from_timestamp(x as i64, 0) else {
+                return Ok(f64::NAN);
+            };
+            match part {
+                "minute" => date.minute() as f64,
+                "hour" => date.hour() as f64,
+                "day_of_week" => date.weekday().num_days_from_sunday() as f64,
+                "day_of_month" => date.day() as f64,
+                "day_of_year" => date.ordinal() as f64,
+                "month" => date.month() as f64,
+                "year" => date.year() as f64,
+                "days_in_month" => {
+                    let year = date.year();
+                    let leap = year % 4 == 0 && (year % 100 != 0 || year % 400 == 0);
+                    match date.month() {
+                        2 => {
+                            if leap {
+                                29.0
+                            } else {
+                                28.0
+                            }
+                        }
+                        4 | 6 | 9 | 11 => 30.0,
+                        _ => 31.0,
+                    }
+                }
+                _ => return Err(Error::Invalid("unregistered PromQL function".into())),
+            }
+        }
+    })
+}
+
+#[derive(serde::Serialize, serde::Deserialize, Clone, Debug)]
+pub struct CompiledExpression {
+    expression: ScalarExpr,
+    schema: planner_types::pre_asap::Schema,
+    output: (DataType, bool),
+}
+impl CompiledExpression {
+    pub fn compile(expression: &ScalarExpr, input: &SchemaRef) -> Result<Self, Error> {
+        if !input.is_all_plain() {
+            return Err(Error::Invalid(
+                "scalar expression cannot consume summary state".into(),
+            ));
+        }
+        let schema = input.as_ref().clone();
+        validate(expression, &schema)?;
+        let output = expression
+            .scalar_type(&schema)
+            .map_err(|e| Error::Invalid(e.to_string()))?;
+        Ok(Self {
+            expression: expression.clone(),
+            schema,
+            output,
+        })
+    }
+    pub(crate) fn dtype(&self) -> (DataType, bool) {
+        self.output.clone()
+    }
+    pub(crate) fn validate_input(&self, input: &SchemaRef) -> Result<(), Error> {
+        let checked = Self::compile(&self.expression, input)?;
+        if checked.output != self.output {
+            return Err(Error::Invalid(
+                "persisted expression type differs from its semantics".into(),
+            ));
+        }
+        if input.fields.len() != self.schema.fields.len()
+            || input
+                .fields
+                .iter()
+                .zip(&self.schema.fields)
+                .any(|(field, column)| {
+                    field.dtype != column.dtype.clone() || field.nullable != column.nullable
+                })
+        {
+            return Err(Error::Invalid(
+                "expression input differs from its bound schema".into(),
+            ));
+        }
+        Ok(())
+    }
+    /// Evaluate a row under the same typed schema used when binding the expression.
+    pub fn evaluate(&self, row: &[Value]) -> Result<Value, Error> {
+        if row.len() != self.schema.fields.len()
+            || row.iter().zip(&self.schema.fields).any(|(value, column)| {
+                !column
+                    .plain_dtype()
+                    .is_some_and(|dtype| value.matches(dtype, column.nullable))
+            })
+        {
+            return Err(Error::Invalid(
+                "expression input differs from its bound schema".into(),
+            ));
+        }
+        evaluate(&self.expression, row, &self.schema)
+    }
+}
+fn validate(expr: &ScalarExpr, schema: &planner_types::pre_asap::Schema) -> Result<(), Error> {
+    let invalid = || Error::Invalid(format!("unsupported scalar expression: {expr:?}"));
+    expr.scalar_type(schema)
+        .map_err(|e| Error::Invalid(e.to_string()))?;
+    match expr {
+        ScalarExpr::Column(_) | ScalarExpr::Literal(_) => Ok(()),
+        ScalarExpr::Cast { expr, to, .. } => {
+            let source = expr
+                .scalar_type(schema)
+                .map_err(|e| Error::Invalid(e.to_string()))?
+                .0;
+            if source != *to
+                && source != DataType::Null
+                && !(source == DataType::Int64 && *to == DataType::Float64)
+            {
+                return Err(invalid());
+            }
+            validate(expr, schema)
+        }
+        ScalarExpr::Negative { expr, .. } => validate(expr, schema),
+        ScalarExpr::Arithmetic { left, right, .. } => {
+            for value in [left, right] {
+                validate(value, schema)?;
+                if !matches!(
+                    value
+                        .scalar_type(schema)
+                        .map_err(|e| Error::Invalid(e.to_string()))?
+                        .0,
+                    DataType::Int64 | DataType::Float64 | DataType::Null
+                ) {
+                    return Err(invalid());
+                }
+            }
+            Ok(())
+        }
+        ScalarExpr::Compare {
+            left, right, op, ..
+        } => {
+            if !matches!(
+                op,
+                CompareOpKind::Eq
+                    | CompareOpKind::Ne
+                    | CompareOpKind::Lt
+                    | CompareOpKind::Le
+                    | CompareOpKind::Gt
+                    | CompareOpKind::Ge
+            ) {
+                return Err(invalid());
+            }
+            validate(left, schema)?;
+            validate(right, schema)?;
+            let (a, _) = left
+                .scalar_type(schema)
+                .map_err(|e| Error::Invalid(e.to_string()))?;
+            let (b, _) = right
+                .scalar_type(schema)
+                .map_err(|e| Error::Invalid(e.to_string()))?;
+            fn comparable(dtype: &DataType) -> bool {
+                match dtype {
+                    DataType::Null
+                    | DataType::Int64
+                    | DataType::Float64
+                    | DataType::Utf8
+                    | DataType::Bool
+                    | DataType::Timestamp => true,
+                    DataType::Map { key, value, .. } => comparable(key) && comparable(value),
+                    _ => false,
+                }
+            }
+            let numeric = |dtype: &DataType| matches!(dtype, DataType::Int64 | DataType::Float64);
+            if !comparable(&a)
+                || !comparable(&b)
+                || (a != b
+                    && !matches!(a, DataType::Null)
+                    && !matches!(b, DataType::Null)
+                    && !(numeric(&a) && numeric(&b)))
+            {
+                return Err(invalid());
+            }
+            Ok(())
+        }
+        ScalarExpr::FunctionCall { name, args } => {
+            if name != "promql_drop_metric_name"
+                && planner_types::pre_asap::scalar_type_rules::promql_function_arity(name).is_none()
+                && name != "asap_struct_field"
+                && name != "asap_element_access"
+                && planner_types::pre_asap::scalar_type_rules::MapScalarFunction::from_name(name)
+                    .is_none()
+            {
+                return Err(invalid());
+            }
+            for arg in args {
+                validate(arg, schema)?;
+            }
+            Ok(())
+        }
+        ScalarExpr::Case {
+            operand: None,
+            branches,
+            else_expr,
+        } => {
+            for (condition, value) in branches {
+                validate(condition, schema)?;
+                if condition
+                    .scalar_type(schema)
+                    .map_err(|e| Error::Invalid(e.to_string()))?
+                    .0
+                    != DataType::Bool
+                {
+                    return Err(invalid());
+                }
+                validate(value, schema)?;
+            }
+            if let Some(value) = else_expr {
+                validate(value, schema)?;
+            }
+            Ok(())
+        }
+        ScalarExpr::BoolAnd(parts) | ScalarExpr::BoolOr(parts) => {
+            for part in parts {
+                validate(part, schema)?;
+                if !matches!(
+                    part.scalar_type(schema)
+                        .map_err(|e| Error::Invalid(e.to_string()))?
+                        .0,
+                    DataType::Bool | DataType::Null
+                ) {
+                    return Err(invalid());
+                }
+            }
+            Ok(())
+        }
+        ScalarExpr::Not(value) => {
+            validate(value, schema)?;
+            if !matches!(
+                value
+                    .scalar_type(schema)
+                    .map_err(|e| Error::Invalid(e.to_string()))?
+                    .0,
+                DataType::Bool | DataType::Null
+            ) {
+                return Err(invalid());
+            }
+            Ok(())
+        }
+        ScalarExpr::IsNull(value) | ScalarExpr::IsNotNull(value) => validate(value, schema),
+        _ => Err(invalid()),
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    #[test]
+    fn mixed_comparison_preserves_integer_precision_and_boundaries() {
+        assert_eq!(
+            integer_float_cmp(9_007_199_254_740_993, 9_007_199_254_740_992.0),
+            Some(Ordering::Greater)
+        );
+        assert_eq!(
+            integer_float_cmp(i64::MAX, 9_223_372_036_854_775_808.0),
+            Some(Ordering::Less)
+        );
+        assert_eq!(
+            integer_float_cmp(i64::MIN, -9_223_372_036_854_775_808.0),
+            Some(Ordering::Equal)
+        );
+        assert_eq!(integer_float_cmp(-1, -1.5), Some(Ordering::Greater));
+        assert_eq!(integer_float_cmp(1, 1.5), Some(Ordering::Less));
+        assert_eq!(integer_float_cmp(0, f64::INFINITY), Some(Ordering::Less));
+        assert_eq!(
+            integer_float_cmp(0, f64::NEG_INFINITY),
+            Some(Ordering::Greater)
+        );
+        assert_eq!(integer_float_cmp(0, f64::NAN), None);
+    }
+}
diff --git a/crates/asap-physical-operators/src/lib.rs b/crates/asap-physical-operators/src/lib.rs
index 345ee762d..586da2508 100644
--- a/crates/asap-physical-operators/src/lib.rs
+++ b/crates/asap-physical-operators/src/lib.rs
@@ -31,3 +31,6 @@ pub mod plan;
 pub mod runtime;
 pub mod sources;
 pub mod values;
+
+pub mod unified_physical_planner;
+pub mod unified_sources;
diff --git a/crates/asap-physical-operators/src/operators/joins/mod.rs b/crates/asap-physical-operators/src/operators/joins/mod.rs
index 76e2f748c..9dfd20dea 100644
--- a/crates/asap-physical-operators/src/operators/joins/mod.rs
+++ b/crates/asap-physical-operators/src/operators/joins/mod.rs
@@ -47,13 +47,43 @@ impl Operator {
         kind: planner_types::pre_asap::JoinKind,
         predicate: &planner_types::pre_asap::Predicate,
         output: SchemaRef,
+    ) -> Result<Self, Error> {
+        let mut joined = left.fields.clone();
+        joined.extend(right.fields.clone());
+        let predicate = Expression::planner(crate::expressions::CompiledExpression::compile(
+            &predicate.0,
+            &schema(joined),
+        )?);
+        Self::bound_relational_join(left, right, kind, predicate, output)
+    }
+    pub fn unified_relational_join(
+        left: SchemaRef,
+        right: SchemaRef,
+        kind: planner_types::pre_asap::JoinKind,
+        predicate: &planner_types::ir::Predicate,
+        output: SchemaRef,
+    ) -> Result<Self, Error> {
+        let mut joined = left.fields.clone();
+        joined.extend(right.fields.clone());
+        let predicate = Expression::unified_planner(
+            crate::expressions::unified_planner::CompiledExpression::compile(
+                &predicate.0,
+                &schema(joined),
+            )?,
+        );
+        Self::bound_relational_join(left, right, kind, predicate, output)
+    }
+    pub(crate) fn bound_relational_join(
+        left: SchemaRef,
+        right: SchemaRef,
+        kind: planner_types::pre_asap::JoinKind,
+        predicate: Expression,
+        output: SchemaRef,
     ) -> Result<Self, Error> {
         use planner_types::pre_asap::JoinKind;
         let mut joined = left.fields.clone();
         joined.extend(right.fields.clone());
-        let predicate =
-            crate::expressions::CompiledExpression::compile(&predicate.0, &schema(joined.clone()))?;
-        if predicate.dtype().0 != DataType::Bool {
+        if predicate.dtype(&schema(joined.clone()))?.0 != DataType::Bool {
             return Err(invalid("join predicate must be boolean"));
         }
         let fields = if matches!(kind, JoinKind::Semi | JoinKind::Anti) {
diff --git a/crates/asap-physical-operators/src/operators/mod.rs b/crates/asap-physical-operators/src/operators/mod.rs
index 4c7e5f5c6..75b313d75 100644
--- a/crates/asap-physical-operators/src/operators/mod.rs
+++ b/crates/asap-physical-operators/src/operators/mod.rs
@@ -130,7 +130,7 @@ enum Kind {
     },
     Join {
         kind: planner_types::pre_asap::JoinKind,
-        predicate: Box<crate::expressions::CompiledExpression>,
+        predicate: Box<Expression>,
     },
     SummaryBuild {
         family: FieldDataType,
diff --git a/crates/asap-physical-operators/src/operators/unchecked.rs b/crates/asap-physical-operators/src/operators/unchecked.rs
index d3504f9a9..a7d3bd683 100644
--- a/crates/asap-physical-operators/src/operators/unchecked.rs
+++ b/crates/asap-physical-operators/src/operators/unchecked.rs
@@ -134,13 +134,11 @@ impl TryFrom<UncheckedOperator> for Operator {
                     operator
                 }
             }
-            Kind::Join { kind, predicate } => Operator::relational_join(
+            Kind::Join { kind, predicate } => Operator::bound_relational_join(
                 input(0)?,
                 input(1)?,
                 kind,
-                &planner_types::pre_asap::Predicate(std::rc::Rc::new(
-                    predicate.expression().clone(),
-                )),
+                *predicate,
                 output.clone(),
             )?,
             Kind::SummaryBuild {
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/candidates.rs b/crates/asap-physical-operators/src/unified_physical_planner/candidates.rs
new file mode 100644
index 000000000..248f5d40f
--- /dev/null
+++ b/crates/asap-physical-operators/src/unified_physical_planner/candidates.rs
@@ -0,0 +1,327 @@
+//! Compile maintenance-selected frontiers without deployment-specific dag rewrites.
+use super::*;
+
+/// One computation realization; lifecycle/window/revision requirements accompany
+/// it during optimization and deployment. Stored outputs have no storage identity.
+/// Deserialization validates the producer/reader boundary.
+#[derive(Clone, serde::Serialize, serde::Deserialize)]
+#[serde(try_from = "UncheckedCompiledPhysicalPlan")]
+pub struct CompiledPhysicalPlan {
+    pub precompute: Option<CompiledPhysicalDAG>,
+    pub query: CompiledPhysicalDAG,
+    pub materialized_outputs: BTreeMap<NodeId, InputContract>,
+}
+
+/// Compile an explicit materialization frontier selected by Planner maintenance
+/// search. Operators upstream of that frontier run in precompute, including
+/// evaluations/reductions; query execution receives their typed output values.
+/// Empty frontiers retain the full computation in the query DAG.
+///
+/// Repeated windows must be instantiated with the same evaluation/population
+/// contract used to build each output. This API never treats a result from a
+/// different window or revision as interchangeable merely because types match.
+pub fn compile_candidate(
+    dag: &PhysicalASAPDAG,
+    inputs: BTreeMap<NodeId, InputContract>,
+    roots: &[NodeId],
+    frontier: &[NodeId],
+) -> Result<CompiledPhysicalPlan, Error> {
+    cut_candidate(&compile(dag, inputs, roots)?, frontier)
+}
+
+/// Derive one frontier's candidate from a complete [`compile`] result by
+/// partitioning its operators; nothing is lowered again. A deployment compiles
+/// each query DAG once and derives every placement choice from that result.
+/// The candidate is identical to [`compile_candidate`] for the same frontier.
+pub fn cut_candidate(
+    compiled: &CompiledPhysicalDAG,
+    frontier: &[NodeId],
+) -> Result<CompiledPhysicalPlan, Error> {
+    if frontier.is_empty() {
+        return Ok(CompiledPhysicalPlan {
+            precompute: None,
+            query: compiled.clone(),
+            materialized_outputs: BTreeMap::new(),
+        });
+    }
+    let frontier_set: BTreeSet<_> = frontier.iter().copied().collect();
+    // `compile` retains only reachable nodes and numbers its helper operators
+    // above the u32 Planner ID range; only Planner outputs are boundaries.
+    if frontier_set.len() != frontier.len()
+        || frontier
+            .iter()
+            .any(|&id| !compiled.is_operator(id) || u32::try_from(id).is_err())
+    {
+        return Err(invalid("frontier must contain distinct computed outputs"));
+    }
+    let inputs: BTreeMap<_, _> = compiled
+        .input_contracts()
+        .map(|(id, contract)| (id, contract.clone()))
+        .collect();
+    let precompute = compiled.cut(&inputs, frontier)?;
+    let mut materialized_outputs = BTreeMap::new();
+    for &id in frontier {
+        let mut output = precompute.output_contract(id)?;
+        if output.properties.boundedness != Boundedness::Bounded {
+            return Err(invalid("materialized output requires bounded execution"));
+        }
+        // A stored reader may stream batches even when the producer blocked.
+        // Its timing is independent; the retained result still must be finite.
+        output.properties.emission = Emission::Unknown;
+        materialized_outputs.insert(id, output);
+    }
+    let mut query_inputs = inputs;
+    query_inputs.extend(materialized_outputs.clone());
+    let query = compiled.cut(&query_inputs, compiled.roots())?;
+    let used: BTreeSet<_> = query.input_contracts().map(|(id, _)| id).collect();
+    if !frontier.iter().all(|id| used.contains(id)) {
+        return Err(invalid(
+            "frontier contains an output shadowed by another boundary",
+        ));
+    }
+    Ok(CompiledPhysicalPlan {
+        precompute: Some(precompute),
+        query,
+        materialized_outputs,
+    })
+}
+
+/// Materialization frontier implied by lifecycle-assigned timing: ingestion-time
+/// nodes read by a query-time node, plus the root when it is ingestion-timed.
+/// `cut_candidate` of one [`compile`] result with this frontier realizes the
+/// assignment, so different assignments are different cuts of one lowering.
+/// That holds while timing-dependent lowering (an ingestion-time `Binary`
+/// aligns by value column) has the same timing at compile time as here.
+/// A query-time node feeding an ingestion-time node has no valid placement.
+pub fn frontier_from_timing(dag: &PhysicalASAPDAG) -> Result<Vec<NodeId>, Error> {
+    use planner_types::post_asap::ExecutionTiming::IngestionTime;
+    let timing = dag
+        .nodes
+        .iter()
+        .map(|node| (node.id, node.output_state.timing))
+        .collect::<BTreeMap<_, _>>();
+    let mut frontier = BTreeSet::new();
+    if timing.get(&dag.root) == Some(&IngestionTime) {
+        frontier.insert(u64::from(dag.root.0));
+    }
+    for edge in &dag.edges {
+        let (Some(&producer), Some(&consumer)) =
+            (timing.get(&edge.producer), timing.get(&edge.consumer))
+        else {
+            return Err(invalid("timed DAG edge names an unknown node"));
+        };
+        match (producer == IngestionTime, consumer == IngestionTime) {
+            (true, false) => {
+                frontier.insert(u64::from(edge.producer.0));
+            }
+            (false, true) => return Err(invalid("query-time node feeds an ingestion-time node")),
+            _ => {}
+        }
+    }
+    Ok(frontier.into_iter().collect())
+}
+
+/// Enumerate bounded, reachable materialization frontiers above explicit inputs.
+/// Each frontier is an antichain: storing an output and its ancestor together
+/// would leave the ancestor unused by query execution. Lifecycle eligibility
+/// and deployment feasibility are evaluated separately before cost selection.
+/// Exceeding the search budget returns an error, never a partial inventory.
+pub fn enumerate_frontiers(
+    dag: &PhysicalASAPDAG,
+    inputs: &BTreeMap<NodeId, InputContract>,
+    roots: &[NodeId],
+    max_candidates: usize,
+) -> Result<Vec<Vec<NodeId>>, Error> {
+    enumerate_compiled_frontiers(&compile(dag, inputs.clone(), roots)?, max_candidates)
+}
+
+fn enumerate_compiled_frontiers(
+    compiled: &CompiledPhysicalDAG,
+    max_candidates: usize,
+) -> Result<Vec<Vec<NodeId>>, Error> {
+    if max_candidates == 0 {
+        return Err(invalid(
+            "frontier search requires a positive candidate budget",
+        ));
+    }
+    let mut ancestors = BTreeMap::<NodeId, BTreeSet<NodeId>>::new();
+    let mut eligible = Vec::new();
+    for (id, properties) in compiled.output_properties()? {
+        if !compiled.is_operator(id)
+            || u32::try_from(id).is_err()
+            || properties.boundedness != Boundedness::Bounded
+        {
+            continue;
+        }
+        let mut seen = BTreeSet::new();
+        let mut pending = vec![id];
+        while let Some(current) = pending.pop() {
+            if seen.insert(current) {
+                pending.extend(compiled.dependencies(current));
+            }
+        }
+        ancestors.insert(id, seen);
+        eligible.push(id);
+    }
+    let mut frontiers = vec![vec![]];
+    for id in eligible {
+        let additions = frontiers
+            .iter()
+            .filter(|frontier| {
+                frontier.iter().all(|previous| {
+                    !ancestors[&id].contains(previous) && !ancestors[previous].contains(&id)
+                })
+            })
+            .map(|frontier| {
+                let mut next = frontier.clone();
+                next.push(id);
+                next
+            })
+            .collect::<Vec<_>>();
+        if additions.len() > max_candidates.saturating_sub(frontiers.len()) {
+            return Err(invalid(
+                "materialization frontier search exceeds candidate budget",
+            ));
+        }
+        frontiers.extend(additions);
+    }
+    Ok(frontiers)
+}
+
+/// Lower every maintenance candidate before feasibility/cost evaluation. Keep
+/// individual failures visible; do not substitute another computation on error.
+/// The DAG is lowered once; each frontier is a [`cut_candidate`] of it.
+pub fn compile_candidates(
+    dag: &PhysicalASAPDAG,
+    inputs: BTreeMap<NodeId, InputContract>,
+    roots: &[NodeId],
+    frontiers: &[Vec<NodeId>],
+) -> Vec<Result<CompiledPhysicalPlan, Error>> {
+    match compile(dag, inputs, roots) {
+        Ok(compiled) => frontiers
+            .iter()
+            .map(|frontier| cut_candidate(&compiled, frontier))
+            .collect(),
+        Err(error) => frontiers.iter().map(|_| Err(error.clone())).collect(),
+    }
+}
+
+/// Complete workload cost supplied by scoped optimizer/deployment evidence.
+/// The evaluator includes build/update work, retained state, shared producers
+/// and recurrent reads over the same horizon; these are not per-query timings.
+#[derive(Clone, Debug)]
+pub struct CandidateCost {
+    pub workload_scope: String,
+    pub horizon_seconds: f64,
+    pub total_cost: f64,
+}
+
+pub struct CandidateSelection<T = CompiledPhysicalPlan> {
+    pub candidate: T,
+    pub candidate_index: usize,
+    pub cost: CandidateCost,
+}
+
+/// Select only compiled and deployment-feasible physical candidates. `None`
+/// rejects an unbindable candidate before pricing. Comparable scoped costs are
+/// required; deployment never rewrites the selected frontier after this step.
+/// The payload is generic so deployments can retain binding/diagnostic metadata
+/// alongside each compiled computation without duplicating winner selection.
+pub fn select_candidate<T>(
+    candidates: Vec<Result<T, Error>>,
+    mut evaluate: impl FnMut(&T) -> Result<Option<CandidateCost>, Error>,
+) -> Result<CandidateSelection<T>, Error> {
+    let mut scope: Option<(String, f64)> = None;
+    let mut selected: Option<CandidateSelection<T>> = None;
+    for (candidate_index, candidate) in candidates.into_iter().enumerate() {
+        let Ok(candidate) = candidate else { continue };
+        let Some(cost) = evaluate(&candidate)? else {
+            continue;
+        };
+        if cost.workload_scope.is_empty()
+            || !cost.horizon_seconds.is_finite()
+            || cost.horizon_seconds <= 0.
+            || !cost.total_cost.is_finite()
+            || cost.total_cost < 0.
+        {
+            return Err(invalid(
+                "candidate cost lacks a valid workload scope/horizon",
+            ));
+        }
+        let current_scope = (cost.workload_scope.clone(), cost.horizon_seconds);
+        if scope.as_ref().is_some_and(|scope| scope != &current_scope) {
+            return Err(invalid(
+                "candidate costs describe different workloads or horizons",
+            ));
+        }
+        scope = Some(current_scope);
+        if selected
+            .as_ref()
+            .is_none_or(|selected| cost.total_cost < selected.cost.total_cost)
+        {
+            selected = Some(CandidateSelection {
+                candidate,
+                candidate_index,
+                cost,
+            });
+        }
+    }
+    selected.ok_or_else(|| invalid("no feasible priced physical candidate"))
+}
+
+#[derive(serde::Deserialize)]
+#[serde(deny_unknown_fields)]
+struct UncheckedCompiledPhysicalPlan {
+    precompute: Option<CompiledPhysicalDAG>,
+    query: CompiledPhysicalDAG,
+    materialized_outputs: BTreeMap<NodeId, InputContract>,
+}
+impl TryFrom<UncheckedCompiledPhysicalPlan> for CompiledPhysicalPlan {
+    type Error = Error;
+    fn try_from(candidate: UncheckedCompiledPhysicalPlan) -> Result<Self, Error> {
+        let result = Self {
+            precompute: candidate.precompute,
+            query: candidate.query,
+            materialized_outputs: candidate.materialized_outputs,
+        };
+        result.validate()?;
+        Ok(result)
+    }
+}
+
+impl CompiledPhysicalPlan {
+    /// Validate the physical handoff, including the producer/reader boundary.
+    pub fn validate(&self) -> Result<(), Error> {
+        self.query.validate()?;
+        let Some(precompute) = &self.precompute else {
+            return if self.materialized_outputs.is_empty() {
+                Ok(())
+            } else {
+                Err(invalid("materialized outputs have no producer DAG"))
+            };
+        };
+        precompute.validate()?;
+        let outputs: BTreeSet<_> = self.materialized_outputs.keys().copied().collect();
+        if outputs.is_empty() || outputs != precompute.roots().iter().copied().collect() {
+            return Err(invalid("physical frontier differs from precompute outputs"));
+        }
+        let readers: BTreeMap<_, _> = self.query.input_contracts().collect();
+        for (&id, contract) in &self.materialized_outputs {
+            let produced = precompute.output_contract(id)?;
+            // Direct frontiers retain their node IDs. Temporal candidates can
+            // read several window instances through distinct input slots;
+            // their deployment bindings must validate those slots separately.
+            let reader = readers.get(&id);
+            if contract.schema != produced.schema
+                || reader.is_some_and(|reader| contract.schema != reader.schema)
+                || produced.properties.boundedness != Boundedness::Bounded
+                || contract.properties.boundedness != Boundedness::Bounded
+                || reader
+                    .is_some_and(|reader| reader.properties.boundedness != Boundedness::Bounded)
+            {
+                return Err(invalid("physical frontier schema or boundedness mismatch"));
+            }
+        }
+        Ok(())
+    }
+}
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/compiled.rs b/crates/asap-physical-operators/src/unified_physical_planner/compiled.rs
new file mode 100644
index 000000000..2b9244806
--- /dev/null
+++ b/crates/asap-physical-operators/src/unified_physical_planner/compiled.rs
@@ -0,0 +1,352 @@
+//! Reader-independent physical computation and checked deployment instantiation.
+use super::*;
+
+/// A typed execution boundary, without storage identity or a live reader.
+#[derive(Clone, Debug, serde::Serialize, serde::Deserialize)]
+pub struct InputContract {
+    pub schema: SchemaRef,
+    pub properties: PlanProperties,
+}
+impl InputContract {
+    pub fn bounded(schema: SchemaRef) -> Self {
+        Self {
+            schema,
+            properties: PlanProperties {
+                boundedness: Boundedness::Bounded,
+                emission: Emission::Unknown,
+            },
+        }
+    }
+    pub fn from_source(source: &dyn PhysicalOperator<Batch, SchemaRef>) -> Self {
+        Self {
+            schema: source.output_schema(),
+            properties: source.properties(&[]),
+        }
+    }
+}
+#[derive(Clone, serde::Serialize, serde::Deserialize)]
+enum Node {
+    Input(InputContract),
+    Operator {
+        inputs: Vec<NodeId>,
+        operator: Operator,
+    },
+}
+
+/// Selected native operators and input slots. Rebinding never repeats lowering.
+/// Serde is format-agnostic; deployments choose the encoding and its versioning.
+/// Deserialization validates the dag before it is usable.
+#[derive(Clone, serde::Serialize, serde::Deserialize)]
+#[serde(try_from = "UncheckedDAG")]
+pub struct CompiledPhysicalDAG {
+    nodes: BTreeMap<NodeId, Node>,
+    roots: Vec<NodeId>,
+}
+#[derive(serde::Deserialize)]
+#[serde(deny_unknown_fields)]
+struct UncheckedDAG {
+    nodes: BTreeMap<NodeId, Node>,
+    roots: Vec<NodeId>,
+}
+impl TryFrom<UncheckedDAG> for CompiledPhysicalDAG {
+    type Error = Error;
+    fn try_from(dag: UncheckedDAG) -> Result<Self, Error> {
+        let result = Self {
+            nodes: dag.nodes,
+            roots: dag.roots,
+        };
+        result.validate()?;
+        Ok(result)
+    }
+}
+
+impl CompiledPhysicalDAG {
+    /// Link already-selected physical fragments without lowering operators again.
+    /// Fragment keys and source keys share a namespace; repeated dependency IDs
+    /// therefore remain one producer in the composed dag.
+    pub fn compose(
+        sources: BTreeMap<NodeId, InputContract>,
+        fragments: BTreeMap<NodeId, (Vec<NodeId>, Self)>,
+        roots: Vec<NodeId>,
+    ) -> Result<Self, Error> {
+        if sources.keys().any(|id| fragments.contains_key(id)) {
+            return Err(invalid("physical source and fragment IDs overlap"));
+        }
+        let mut contracts = sources.clone();
+        for (&id, (_, fragment)) in &fragments {
+            fragment.validate()?;
+            let [root] = fragment.roots() else {
+                return Err(invalid("composed fragment requires one root"));
+            };
+            if fragment.input_contracts().any(|(id, _)| id == *root) {
+                return Err(invalid("fragment root must be a computed output"));
+            }
+            contracts.insert(id, fragment.output_contract(*root)?);
+        }
+        let mut next = contracts
+            .keys()
+            .next_back()
+            .copied()
+            .unwrap_or(0)
+            .checked_add(1)
+            .ok_or_else(|| invalid("physical node ID overflow"))?;
+        let mut result = Self::new(roots);
+        for (id, contract) in sources {
+            result.add_input(id, contract)?;
+        }
+        for (id, (inputs, fragment)) in fragments {
+            if inputs.len() != fragment.input_contracts().count() {
+                return Err(invalid("physical fragment input arity mismatch"));
+            }
+            let mut mapping = BTreeMap::new();
+            for ((local, expected), global) in fragment.input_contracts().zip(inputs) {
+                let actual = contracts
+                    .get(&global)
+                    .ok_or_else(|| invalid("missing physical fragment dependency"))?;
+                if expected.schema != actual.schema
+                    || (expected.properties.boundedness == Boundedness::Bounded
+                        && actual.properties.boundedness != Boundedness::Bounded)
+                {
+                    return Err(invalid("physical fragment dependency contract mismatch"));
+                }
+                mapping.insert(local, global);
+            }
+            mapping.insert(fragment.roots[0], id);
+            for local in fragment.nodes.keys() {
+                if !mapping.contains_key(local) {
+                    mapping.insert(*local, next);
+                    next = next
+                        .checked_add(1)
+                        .ok_or_else(|| invalid("physical node ID overflow"))?;
+                }
+            }
+            for (local, node) in fragment.nodes {
+                if let Node::Operator { inputs, operator } = node {
+                    result.add(
+                        mapping[&local],
+                        inputs.into_iter().map(|input| mapping[&input]).collect(),
+                        operator,
+                    )?;
+                }
+            }
+        }
+        result.validate()?;
+        Ok(result)
+    }
+
+    /// Assemble already-lowered operators and typed external inputs. This is
+    /// useful for engines that compose multiple compiled computation fragments.
+    pub fn from_operators(
+        inputs: BTreeMap<NodeId, InputContract>,
+        operators: BTreeMap<NodeId, (Vec<NodeId>, Operator)>,
+        roots: Vec<NodeId>,
+    ) -> Result<Self, Error> {
+        let mut result = Self::new(roots);
+        for (id, contract) in inputs {
+            result.add_input(id, contract)?;
+        }
+        for (id, (inputs, operator)) in operators {
+            result.add(id, inputs, operator)?;
+        }
+        result.validate()?;
+        Ok(result)
+    }
+    pub(super) fn new(roots: Vec<NodeId>) -> Self {
+        Self {
+            nodes: BTreeMap::new(),
+            roots,
+        }
+    }
+    pub(super) fn add_input(&mut self, id: NodeId, contract: InputContract) -> Result<(), Error> {
+        self.insert(id, Node::Input(contract))
+    }
+    pub(super) fn add(
+        &mut self,
+        id: NodeId,
+        inputs: Vec<NodeId>,
+        operator: Operator,
+    ) -> Result<(), Error> {
+        self.insert(id, Node::Operator { inputs, operator })
+    }
+    fn insert(&mut self, id: NodeId, node: Node) -> Result<(), Error> {
+        if self.nodes.insert(id, node).is_some() {
+            return Err(invalid(format!("duplicate physical node {id}")));
+        }
+        Ok(())
+    }
+    /// Identify the external input whose rows survive unchanged at this output.
+    /// Protocol adapters can retain labels that are outside a closed physical schema.
+    pub fn row_source(&self, id: NodeId) -> Option<NodeId> {
+        match self.nodes.get(&id)? {
+            Node::Input(_) => Some(id),
+            Node::Operator { inputs, operator } => {
+                let index = operator.row_preserving_input()?;
+                self.row_source(*inputs.get(index)?)
+            }
+        }
+    }
+
+    /// Selected operator name, for plan inspection without decoding its wire format.
+    /// Certified candidate pruning checks authoritative-key coverage inside this operator.
+    pub fn certified_pruning_keys(&self, id: NodeId) -> Option<&[(usize, usize)]> {
+        match self.nodes.get(&id)? {
+            Node::Operator { operator, .. } => operator.certified_pruning_keys(),
+            Node::Input(_) => None,
+        }
+    }
+    pub fn operator_name(&self, id: NodeId) -> Option<&str> {
+        match self.nodes.get(&id)? {
+            Node::Input(_) => Some("Input"),
+            Node::Operator { operator, .. } => Some(operator.name()),
+        }
+    }
+
+    pub fn roots(&self) -> &[NodeId] {
+        &self.roots
+    }
+    pub fn input_contracts(&self) -> impl Iterator<Item = (NodeId, &InputContract)> {
+        self.nodes.iter().filter_map(|(&id, node)| match node {
+            Node::Input(contract) => Some((id, contract)),
+            Node::Operator { .. } => None,
+        })
+    }
+    /// Derive a reachable output contract without opening deployment readers.
+    pub fn output_contract(&self, id: NodeId) -> Result<InputContract, Error> {
+        let properties = *self
+            .output_properties()?
+            .get(&id)
+            .ok_or_else(|| invalid("output is not reachable"))?;
+        let schema = match self
+            .nodes
+            .get(&id)
+            .ok_or_else(|| invalid("missing output"))?
+        {
+            Node::Input(contract) => contract.schema.clone(),
+            Node::Operator { operator, .. } => operator.output_schema(),
+        };
+        Ok(InputContract { schema, properties })
+    }
+    /// Properties of every reachable node, derived in one contract-only pass.
+    pub(super) fn output_properties(&self) -> Result<BTreeMap<NodeId, PlanProperties>, Error> {
+        let sources = self
+            .input_contracts()
+            .map(|(id, contract)| (id, Box::new(contract.clone()) as Source<'_>))
+            .collect();
+        self.instantiate(sources)?.properties(&self.roots)
+    }
+    /// Direct physical dependencies; empty for inputs and unknown IDs.
+    pub(super) fn dependencies(&self, id: NodeId) -> &[NodeId] {
+        match self.nodes.get(&id) {
+            Some(Node::Operator { inputs, .. }) => inputs,
+            _ => &[],
+        }
+    }
+    pub(super) fn is_operator(&self, id: NodeId) -> bool {
+        matches!(self.nodes.get(&id), Some(Node::Operator { .. }))
+    }
+    /// Keep the already-lowered operators reachable from `roots`, replacing
+    /// each node in `boundaries` by a typed input. Nothing is lowered again.
+    pub(super) fn cut(
+        &self,
+        boundaries: &BTreeMap<NodeId, InputContract>,
+        roots: &[NodeId],
+    ) -> Result<Self, Error> {
+        let mut result = Self::new(roots.to_vec());
+        let mut pending = roots.to_vec();
+        while let Some(id) = pending.pop() {
+            if result.nodes.contains_key(&id) {
+                continue;
+            }
+            let node = match boundaries.get(&id) {
+                Some(contract) => Node::Input(contract.clone()),
+                None => self
+                    .nodes
+                    .get(&id)
+                    .cloned()
+                    .ok_or_else(|| invalid(format!("missing physical node {id}")))?,
+            };
+            if let Node::Operator { inputs, .. } = &node {
+                pending.extend(inputs);
+            }
+            result.nodes.insert(id, node);
+        }
+        result.validate()?;
+        Ok(result)
+    }
+    /// Validate using contract-only sources. No deployment reader is available.
+    pub fn validate(&self) -> Result<(), Error> {
+        let sources = self
+            .input_contracts()
+            .map(|(id, c)| (id, Box::new(c.clone()) as Source<'_>))
+            .collect();
+        self.instantiate(sources).map(|_| ())
+    }
+    /// Resolve exactly the declared inputs and validate before any source starts.
+    pub fn instantiate<'a>(
+        &self,
+        mut sources: BTreeMap<NodeId, Source<'a>>,
+    ) -> Result<PhysicalDAG<'a, Batch, SchemaRef>, Error> {
+        let mut dag = PhysicalDAG::default();
+        for (&id, node) in &self.nodes {
+            match node {
+                Node::Input(contract) => {
+                    let source = sources
+                        .remove(&id)
+                        .ok_or_else(|| invalid(format!("missing physical input {id}")))?;
+                    let actual = source.properties(&[]);
+                    if !source.input_schemas().is_empty()
+                        || source.output_schema() != contract.schema
+                        || (contract.properties.boundedness != Boundedness::Unknown
+                            && actual.boundedness != contract.properties.boundedness)
+                        || (contract.properties.emission != Emission::Unknown
+                            && actual.emission != contract.properties.emission)
+                    {
+                        return Err(invalid(format!(
+                            "physical input {id} violates its compiled contract"
+                        )));
+                    }
+                    dag.add_boxed(
+                        id,
+                        vec![],
+                        Box::new(CheckedSource {
+                            source,
+                            output: contract.schema.clone(),
+                        }),
+                    )?;
+                }
+                Node::Operator { inputs, operator } => {
+                    dag.add(id, inputs.clone(), operator.clone())?;
+                }
+            }
+        }
+        if !sources.is_empty() {
+            return Err(invalid("unexpected physical input binding"));
+        }
+        dag.validate(&self.roots)?;
+        Ok(dag)
+    }
+}
+impl PhysicalOperator<Batch, SchemaRef> for InputContract {
+    fn name(&self) -> &str {
+        "UnresolvedInput"
+    }
+    fn input_schemas(&self) -> Vec<SchemaRef> {
+        vec![]
+    }
+    fn output_schema(&self) -> SchemaRef {
+        self.schema.clone()
+    }
+    fn properties(&self, _: &[PlanProperties]) -> PlanProperties {
+        self.properties
+    }
+    fn output_bytes(&self, batch: &Batch) -> usize {
+        batch.bytes()
+    }
+    fn start<'a>(
+        &'a self,
+        _: Vec<crate::runtime::Input<'a, Batch>>,
+        _: crate::runtime::RunContext,
+    ) -> Result<crate::runtime::OutputStream<'a, Batch>, Error> {
+        Err(invalid("physical input must be resolved before execution"))
+    }
+}
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/logical.rs b/crates/asap-physical-operators/src/unified_physical_planner/logical.rs
new file mode 100644
index 000000000..dbc541895
--- /dev/null
+++ b/crates/asap-physical-operators/src/unified_physical_planner/logical.rs
@@ -0,0 +1,374 @@
+//! Reconstruct shared operator references from the transport DAG for native lowering.
+use super::*;
+use planner_types::ir::export::{EdgeRole, NonASAPOpKind as N, PhysicalASAPNodeId, WireScalarExpr};
+use planner_types::ir::{
+    ASAPOp, NonASAPOp, Operator as LogicalOperator, OperatorNode, Predicate, ProjectItem,
+    ScalarExpr, SortKey as LogicalSortKey,
+};
+use std::rc::Rc;
+pub(super) fn scalar(
+    expr: &WireScalarExpr,
+    id_of: &mut impl FnMut(PhysicalASAPNodeId) -> Rc<OperatorNode>,
+) -> ScalarExpr {
+    fn boxed(
+        e: &WireScalarExpr,
+        id_of: &mut impl FnMut(PhysicalASAPNodeId) -> Rc<OperatorNode>,
+    ) -> Box<ScalarExpr> {
+        Box::new(scalar(e, id_of))
+    }
+    fn list(
+        es: &[WireScalarExpr],
+        id_of: &mut impl FnMut(PhysicalASAPNodeId) -> Rc<OperatorNode>,
+    ) -> Vec<ScalarExpr> {
+        es.iter().map(|e| scalar(e, id_of)).collect()
+    }
+    match expr {
+        WireScalarExpr::Column(id) => ScalarExpr::Column(*id),
+        WireScalarExpr::Literal(v) => ScalarExpr::Literal(v.clone()),
+        WireScalarExpr::Negative { expr, semantics } => ScalarExpr::Negative {
+            expr: boxed(expr, id_of),
+            semantics: *semantics,
+        },
+        WireScalarExpr::Compare {
+            left,
+            op,
+            right,
+            semantics,
+        } => ScalarExpr::Compare {
+            left: boxed(left, id_of),
+            op: op.clone(),
+            right: boxed(right, id_of),
+            semantics: *semantics,
+        },
+        WireScalarExpr::BoolAnd(parts) => ScalarExpr::BoolAnd(list(parts, id_of)),
+        WireScalarExpr::BoolOr(parts) => ScalarExpr::BoolOr(list(parts, id_of)),
+        WireScalarExpr::Not(e) => ScalarExpr::Not(boxed(e, id_of)),
+        WireScalarExpr::IsNull(e) => ScalarExpr::IsNull(boxed(e, id_of)),
+        WireScalarExpr::IsNotNull(e) => ScalarExpr::IsNotNull(boxed(e, id_of)),
+        WireScalarExpr::Cast { expr, to, try_cast } => ScalarExpr::Cast {
+            expr: boxed(expr, id_of),
+            to: to.clone(),
+            try_cast: *try_cast,
+        },
+        WireScalarExpr::InList {
+            expr,
+            list: items,
+            negated,
+        } => ScalarExpr::InList {
+            expr: boxed(expr, id_of),
+            list: list(items, id_of),
+            negated: *negated,
+        },
+        WireScalarExpr::FunctionCall { name, args } => ScalarExpr::FunctionCall {
+            name: name.clone(),
+            args: list(args, id_of),
+        },
+        WireScalarExpr::Arithmetic {
+            op,
+            left,
+            right,
+            semantics,
+        } => ScalarExpr::Arithmetic {
+            op: op.clone(),
+            left: boxed(left, id_of),
+            right: boxed(right, id_of),
+            semantics: *semantics,
+        },
+        WireScalarExpr::Case {
+            operand,
+            branches,
+            else_expr,
+        } => ScalarExpr::Case {
+            operand: operand.as_ref().map(|e| boxed(e, id_of)),
+            branches: branches
+                .iter()
+                .map(|(w, t)| (scalar(w, id_of), scalar(t, id_of)))
+                .collect(),
+            else_expr: else_expr.as_ref().map(|e| boxed(e, id_of)),
+        },
+        WireScalarExpr::CurrentTimestamp => ScalarExpr::CurrentTimestamp,
+        WireScalarExpr::EvalTimestamp => ScalarExpr::EvalTimestamp,
+        WireScalarExpr::PromqlScalarFromVector(node) => {
+            ScalarExpr::PromqlScalarFromVector(id_of(*node))
+        }
+        WireScalarExpr::ScalarSubquery(node) => ScalarExpr::ScalarSubquery(id_of(*node)),
+        WireScalarExpr::Exists { subquery, negated } => ScalarExpr::Exists {
+            subquery: id_of(*subquery),
+            negated: *negated,
+        },
+        WireScalarExpr::InSubquery {
+            expr,
+            subquery,
+            negated,
+        } => ScalarExpr::InSubquery {
+            expr: boxed(expr, id_of),
+            subquery: id_of(*subquery),
+            negated: *negated,
+        },
+    }
+}
+
+pub(super) fn restore(dag: &PhysicalASAPDAG) -> Result<BTreeMap<NodeId, Rc<OperatorNode>>, Error> {
+    dag.validate().map_err(|e| invalid(e.to_string()))?;
+    let mut done = BTreeMap::new();
+    let mut remaining: Vec<_> = dag.nodes.iter().collect();
+    while !remaining.is_empty() {
+        let before = remaining.len();
+        let mut next = Vec::new();
+        for node in remaining {
+            let mut edges: Vec<_> = dag.edges.iter().filter(|e| e.consumer == node.id).collect();
+            if edges
+                .iter()
+                .any(|e| !done.contains_key(&u64::from(e.producer.0)))
+            {
+                next.push(node);
+                continue;
+            }
+            edges.sort_by_key(|e| match e.role {
+                EdgeRole::Left => 0,
+                EdgeRole::Input => 1,
+                EdgeRole::Right => 2,
+                EdgeRole::ScalarRef => 3,
+            });
+            let inputs: Vec<_> = edges
+                .iter()
+                .filter(|e| e.role != EdgeRole::ScalarRef)
+                .map(|e| Rc::clone(&done[&u64::from(e.producer.0)]))
+                .collect();
+            let input = |index: usize| {
+                inputs
+                    .get(index)
+                    .cloned()
+                    .ok_or_else(|| invalid("operator is missing an input"))
+            };
+            let mut missing = false;
+            let mut ref_node = |id: PhysicalASAPNodeId| {
+                if let Some(node) = done.get(&u64::from(id.0)) {
+                    Rc::clone(node)
+                } else {
+                    missing = true;
+                    Rc::new(OperatorNode::with_schema(
+                        LogicalOperator::NonASAP(NonASAPOp::Values {
+                            rows: vec![],
+                            schema: Default::default(),
+                        }),
+                        Default::default(),
+                    ))
+                }
+            };
+            let mut value = |expr: &WireScalarExpr| scalar(expr, &mut ref_node);
+            let operator = match &node.payload {
+                Payload::Relational { operator } => LogicalOperator::NonASAP(match operator {
+                    N::Scan {
+                        source,
+                        predicates,
+                        schema,
+                    } => NonASAPOp::Scan {
+                        source: source.clone(),
+                        predicates: predicates.iter().map(|p| Predicate(value(&p.0))).collect(),
+                        schema: schema.clone(),
+                    },
+                    N::Values { rows, schema } => NonASAPOp::Values {
+                        rows: rows
+                            .iter()
+                            .map(|r| r.iter().map(&mut value).collect())
+                            .collect(),
+                        schema: schema.clone(),
+                    },
+                    N::Filter { pred } => NonASAPOp::Filter {
+                        pred: Predicate(value(&pred.0)),
+                        child: input(0)?,
+                    },
+                    N::Project { cols, qualifier } => NonASAPOp::Project {
+                        cols: cols
+                            .iter()
+                            .map(|c| ProjectItem {
+                                alias: c.alias.clone(),
+                                expr: value(&c.expr),
+                            })
+                            .collect(),
+                        qualifier: qualifier.clone(),
+                        child: input(0)?,
+                    },
+                    N::Aggregate {
+                        reduction,
+                        measures,
+                        output_names,
+                        filters,
+                        having,
+                    } => NonASAPOp::Aggregate {
+                        reduction: reduction.clone(),
+                        measures: measures.clone(),
+                        output_names: output_names.clone(),
+                        filters: filters
+                            .iter()
+                            .map(|p| p.as_ref().map(|p| Predicate(value(&p.0))))
+                            .collect(),
+                        having: having.as_ref().map(|p| Predicate(value(&p.0))),
+                        child: input(0)?,
+                    },
+                    N::Join { join_kind, pred } => NonASAPOp::Join {
+                        kind: join_kind.clone(),
+                        pred: Predicate(value(&pred.0)),
+                        left: input(0)?,
+                        right: input(1)?,
+                    },
+                    N::SetOp { set_kind, all } => NonASAPOp::SetOp {
+                        kind: set_kind.clone(),
+                        all: *all,
+                        left: input(0)?,
+                        right: input(1)?,
+                    },
+                    N::Concat {
+                        discriminator_unique_key,
+                    } => NonASAPOp::Concat {
+                        children: inputs.clone(),
+                        discriminator_unique_key: discriminator_unique_key.clone(),
+                    },
+                    N::Dedup { cols } => NonASAPOp::Dedup {
+                        cols: cols.clone(),
+                        child: input(0)?,
+                    },
+                    N::Sort { keys, partition_by } => NonASAPOp::Sort {
+                        keys: keys
+                            .iter()
+                            .map(|k| LogicalSortKey {
+                                expr: value(&k.expr),
+                                ascending: k.ascending,
+                                nulls_first: k.nulls_first,
+                            })
+                            .collect(),
+                        partition_by: partition_by.clone(),
+                        child: input(0)?,
+                    },
+                    N::Limit {
+                        n,
+                        offset,
+                        partition_by,
+                    } => NonASAPOp::Limit {
+                        n: *n,
+                        offset: *offset,
+                        partition_by: partition_by.clone(),
+                        child: input(0)?,
+                    },
+                    N::BinaryOp {
+                        operator,
+                        return_bool,
+                    } => NonASAPOp::BinaryOp {
+                        operator: operator.clone(),
+                        return_bool: *return_bool,
+                        lhs: input(0)?,
+                        rhs: input(1)?,
+                    },
+                    N::SQLWindowFunc {
+                        func,
+                        args,
+                        partition_by,
+                        order_by,
+                        frame,
+                        output_name,
+                    } => NonASAPOp::SQLWindowFunc {
+                        func: func.clone(),
+                        args: args.iter().map(&mut value).collect(),
+                        partition_by: partition_by.clone(),
+                        order_by: order_by
+                            .iter()
+                            .map(|k| LogicalSortKey {
+                                expr: value(&k.expr),
+                                ascending: k.ascending,
+                                nulls_first: k.nulls_first,
+                            })
+                            .collect(),
+                        frame: frame.clone(),
+                        output_name: output_name.clone(),
+                        child: input(0)?,
+                    },
+                    N::TimeRange { range, range_kind } => NonASAPOp::TimeRange {
+                        range: *range,
+                        kind: *range_kind,
+                        child: input(0)?,
+                    },
+                    N::TimeShift { shift } => NonASAPOp::TimeShift {
+                        shift: *shift,
+                        child: input(0)?,
+                    },
+                    N::PromqlVectorFromScalar { expr } => {
+                        NonASAPOp::PromqlVectorFromScalar(value(expr))
+                    }
+                    N::PromqlRelabel { dst, value: expr } => NonASAPOp::PromqlRelabel {
+                        dst: dst.clone(),
+                        value: value(expr),
+                        child: input(0)?,
+                    },
+                    N::PromqlInfoEnrich { selector } => NonASAPOp::PromqlInfoEnrich {
+                        selector: selector.clone(),
+                        child: input(0)?,
+                    },
+                    N::PromqlSeriesSample { by, sample_kind } => NonASAPOp::PromqlSeriesSample {
+                        by: by.clone(),
+                        kind: *sample_kind,
+                        child: input(0)?,
+                    },
+                    N::PromqlSubquery { range, resolution } => NonASAPOp::PromqlSubquery {
+                        range: *range,
+                        resolution: *resolution,
+                        child: input(0)?,
+                    },
+                }),
+                Payload::SummaryAgg {
+                    family,
+                    input: update,
+                    reduction,
+                    grouping,
+                    filter,
+                } => LogicalOperator::ASAP(ASAPOp::SummaryAgg {
+                    child: input(0)?,
+                    family: family.clone(),
+                    input: update.clone(),
+                    reduction: reduction.clone(),
+                    grouping: grouping.clone(),
+                    filter: filter.as_ref().map(|p| Predicate(value(&p.0))),
+                }),
+                Payload::SummaryEstimate { query } => {
+                    LogicalOperator::ASAP(ASAPOp::SummaryEstimate {
+                        summary_input: input(0)?,
+                        query: query.clone(),
+                    })
+                }
+                Payload::FinalizeExactAccumulator => {
+                    LogicalOperator::ASAP(ASAPOp::FinalizeExactAccumulator { child: input(0)? })
+                }
+                Payload::MaintainPopulation { population } => {
+                    LogicalOperator::ASAP(ASAPOp::MaintainPopulation {
+                        child: input(0)?,
+                        population: population.clone(),
+                    })
+                }
+                Payload::EvaluatePopulation { evaluation } => {
+                    LogicalOperator::ASAP(ASAPOp::EvaluatePopulation {
+                        child: input(0)?,
+                        evaluation: evaluation.clone(),
+                    })
+                }
+                Payload::SummaryMerge => LogicalOperator::ASAP(ASAPOp::SummaryMerge {
+                    children: inputs.clone(),
+                }),
+                _ => return Err(invalid("reserved ASAP operation has no native lowering")),
+            };
+            if missing {
+                return Err(invalid(
+                    "scalar reference is not a preceding DAG dependency",
+                ));
+            }
+            let mut rebuilt = OperatorNode::with_schema(operator, node.output_schema.clone());
+            rebuilt.guarantee = node.guarantee.clone();
+            rebuilt.timing = Some(node.output_state.timing);
+            done.insert(u64::from(node.id.0), Rc::new(rebuilt));
+        }
+        if next.len() == before {
+            return Err(invalid("operator DAG is cyclic"));
+        }
+        remaining = next;
+    }
+    Ok(done)
+}
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/mod.rs b/crates/asap-physical-operators/src/unified_physical_planner/mod.rs
new file mode 100644
index 000000000..8d680fcc9
--- /dev/null
+++ b/crates/asap-physical-operators/src/unified_physical_planner/mod.rs
@@ -0,0 +1,1169 @@
+//! Compile logical computation to native operators with typed external inputs.
+//! Compilation needs no readers; deployment resolves inputs after selection.
+use crate::operators::ReadoutQuery;
+use crate::summary_kernels::exact::ExactReadout;
+use crate::{
+    operators::{Expression, Operator, Reduction, SortKey},
+    plan::{Boundedness, Emission, NodeId, PhysicalDAG, PhysicalOperator, PlanProperties},
+    values::{Batch, SchemaRef},
+    Error,
+};
+use planner_types::ir::export::{
+    NonASAPOpKind, PhysicalASAPDAG, PhysicalASAPDAGNode, PhysicalASAPOperatorPayload as Payload,
+    WireScalarExpr,
+};
+use planner_types::ir::{ASAPOp, NonASAPOp, Operator as LogicalOperator, OperatorNode, ScalarExpr};
+use planner_types::{
+    post_asap::{FieldDataType, SketchStatistic, SummaryInputExpr},
+    pre_asap::{
+        AggIntent, ColumnRef, CompareOpKind, DataType, GroupKeys, Reduction as PlannerReduction,
+    },
+};
+mod logical;
+use std::{
+    collections::{BTreeMap, BTreeSet},
+    sync::Arc,
+};
+fn invalid(message: impl Into<String>) -> Error {
+    Error::Invalid(message.into())
+}
+
+/// Source nodes cut the DAG at an installed storage/ingestion frontier. The
+/// binding must have exactly the declared schema and no upstream dependencies.
+/// A deployment must authorize these frontiers before calling this function.
+pub type Source<'a> = Box<dyn PhysicalOperator<Batch, SchemaRef> + 'a>;
+
+pub mod precompute;
+pub mod promql_fallback;
+pub mod promql_rows;
+pub mod promql_values;
+
+mod candidates;
+pub use candidates::{
+    compile_candidate, compile_candidates, cut_candidate, enumerate_frontiers,
+    frontier_from_timing, select_candidate, CandidateCost, CandidateSelection,
+    CompiledPhysicalPlan,
+};
+
+mod compiled;
+pub use compiled::{CompiledPhysicalDAG, InputContract};
+
+mod row_values;
+
+/// Compile computation without opening or retaining deployment readers.
+/// Input contracts identify explicit boundaries selected by maintenance planning.
+pub fn compile(
+    dag: &PhysicalASAPDAG,
+    inputs: BTreeMap<NodeId, InputContract>,
+    roots: &[NodeId],
+) -> Result<CompiledPhysicalDAG, Error> {
+    compile_internal(dag, inputs, roots)
+}
+
+/// Convenience for callers that already resolved inputs. Lowering still uses
+/// only their contracts, and instantiation checks those contracts again.
+pub fn bind<'a>(
+    dag: &PhysicalASAPDAG,
+    sources: BTreeMap<NodeId, Source<'a>>,
+    roots: &[NodeId],
+) -> Result<PhysicalDAG<'a, Batch, SchemaRef>, Error> {
+    let inputs = sources
+        .iter()
+        .map(|(&id, source)| (id, InputContract::from_source(source.as_ref())))
+        .collect();
+    compile(dag, inputs, roots)?.instantiate(sources)
+}
+
+/// Resolve raw scan connectors before invoking the reader-independent compiler.
+pub fn bind_with_data_sources<'a>(
+    dag: &PhysicalASAPDAG,
+    mut sources: BTreeMap<NodeId, Source<'a>>,
+    roots: &[NodeId],
+    data_sources: &crate::unified_sources::DataSources,
+) -> Result<PhysicalDAG<'a, Batch, SchemaRef>, Error> {
+    let restored = logical::restore(dag)?;
+    // Only resolve scans reachable below the selected input boundaries.
+    let mut pending = roots.to_vec();
+    let mut seen = BTreeSet::new();
+    while let Some(id) = pending.pop() {
+        if !seen.insert(id) || sources.contains_key(&id) {
+            continue;
+        }
+        let _node = dag
+            .nodes
+            .iter()
+            .find(|n| u64::from(n.id.0) == id)
+            .ok_or_else(|| invalid(format!("missing node {id}")))?;
+        if matches!(restored[&id].non_asap(), Some(NonASAPOp::Scan { .. })) {
+            sources.insert(id, Box::new(data_sources.bind(&restored[&id])?));
+        } else {
+            pending.extend(
+                dag.edges
+                    .iter()
+                    .filter(|e| u64::from(e.consumer.0) == id)
+                    .map(|e| u64::from(e.producer.0)),
+            );
+        }
+    }
+    bind(dag, sources, roots)
+}
+
+#[cfg(test)]
+thread_local! {
+    /// Planner nodes lowered by this thread, for compile-once tests.
+    static LOWERED_NODES: std::cell::Cell<usize> = const { std::cell::Cell::new(0) };
+}
+
+/// Helper operators are numbered from their Planner node alone, above the u32
+/// Planner ID range, so every boundary choice yields a subgraph of the same
+/// lowering and candidate cuts need not renumber operators. A node lowering to
+/// several helpers takes consecutive indices below its base.
+fn helper_id(node: NodeId, index: u64) -> NodeId {
+    debug_assert!(node <= u64::from(u32::MAX) && index < 1 << 16);
+    u64::MAX - (node << 16) - index
+}
+
+fn compile_internal(
+    dag: &PhysicalASAPDAG,
+    mut sources: BTreeMap<NodeId, InputContract>,
+    roots: &[NodeId],
+) -> Result<CompiledPhysicalDAG, Error> {
+    preflight_depth(dag)?;
+    let restored = logical::restore(dag)?;
+    dag.validate().map_err(|e| invalid(e.to_string()))?;
+    let nodes = dag
+        .nodes
+        .iter()
+        .map(|node| (u64::from(node.id.0), node))
+        .collect::<BTreeMap<_, _>>();
+    let mut dependencies = BTreeMap::<NodeId, Vec<NodeId>>::new();
+    // Binary input order is semantic; serialized edge order is not.
+    let mut edges = dag.edges.iter().collect::<Vec<_>>();
+    edges.sort_by_key(|edge| {
+        (
+            edge.consumer.0,
+            match edge.role {
+                planner_types::ir::export::EdgeRole::Left => 0,
+                planner_types::ir::export::EdgeRole::Input => 1,
+                planner_types::ir::export::EdgeRole::Right => 2,
+                planner_types::ir::export::EdgeRole::ScalarRef => 3,
+            },
+        )
+    });
+    let literals = BTreeMap::<NodeId, (f64, bool)>::new();
+    for edge in edges {
+        dependencies
+            .entry(u64::from(edge.consumer.0))
+            .or_default()
+            .push(u64::from(edge.producer.0));
+    }
+    let mut fallback = BTreeMap::new();
+    for (&id, root) in &restored {
+        let raw_summary_input = matches!(root.non_asap(), Some(NonASAPOp::TimeRange { .. }))
+            && dag.edges.iter().any(|e| {
+                u64::from(e.producer.0) == id
+                    && matches!(
+                        nodes[&u64::from(e.consumer.0)].payload,
+                        Payload::SummaryAgg { .. }
+                    )
+            });
+        if !root.contains_asap() && !raw_summary_input {
+            if let Ok(lowered) = promql_fallback::lower(root) {
+                fallback.insert(id, lowered);
+            }
+        }
+    }
+    let known = |id: &NodeId| {
+        nodes.contains_key(id)
+            || promql_fallback::raw_series_owner(*id).is_some_and(|owner| {
+                matches!(
+                    nodes.get(&owner),
+                    Some(PhysicalASAPDAGNode {
+                        payload: Payload::Relational { .. },
+                        ..
+                    })
+                )
+            })
+    };
+    if !sources.keys().all(known) {
+        return Err(invalid("source binding names an unknown node"));
+    }
+    let mut ordered = Vec::new();
+    let mut seen = BTreeSet::new();
+    let mut pending = roots.iter().map(|&id| (id, false)).collect::<Vec<_>>();
+    while let Some((id, expanded)) = pending.pop() {
+        if expanded {
+            ordered.push(id);
+            continue;
+        }
+        if !seen.insert(id) {
+            continue;
+        }
+        if !nodes.contains_key(&id) {
+            return Err(invalid(format!("missing root {id}")));
+        }
+        pending.push((id, true));
+        if !sources.contains_key(&id) && !fallback.contains_key(&id) {
+            for &input in dependencies.get(&id).into_iter().flatten() {
+                pending.push((input, false));
+            }
+        }
+    }
+    let mut dag = CompiledPhysicalDAG::new(roots.to_vec());
+    for id in ordered {
+        let node = nodes[&id];
+        let mut auxiliary = helper_id(id, 0);
+        let output = Arc::new(node.output_schema.clone());
+        crate::values::validate_schema(&output)?;
+        if let Some(source) = sources.remove(&id) {
+            if source.schema != output {
+                return Err(invalid("frontier does not have the declared schema"));
+            }
+            dag.add_input(id, source)?;
+        } else {
+            #[cfg(test)]
+            LOWERED_NODES.with(|count| count.set(count.get() + 1));
+            let mut inputs = dependencies.get(&id).cloned().unwrap_or_default();
+            let mut schemas = inputs
+                .iter()
+                .map(|id| Arc::new(nodes[id].output_schema.clone()))
+                .collect::<Vec<_>>();
+            if matches!(node.payload, Payload::SummaryMerge) && inputs.len() > 1 {
+                if schemas.iter().any(|s| s != &schemas[0]) {
+                    return Err(invalid("summary merge inputs have different schemas"));
+                }
+                dag.add(
+                    auxiliary,
+                    inputs,
+                    Operator::union(schemas[0].clone(), schemas.len())?,
+                )?;
+                inputs = vec![auxiliary];
+                schemas.truncate(1);
+            }
+            if let Some(promql_fallback::Lowering {
+                selectors,
+                mut steps,
+            }) = fallback.remove(&id)
+            {
+                let mut slots = Vec::new();
+                for (i, (_, schema)) in selectors.iter().enumerate() {
+                    let slot = promql_fallback::raw_series_input(id, i);
+                    match sources.remove(&slot) {
+                        Some(contract) if &contract.schema == schema => {
+                            dag.add_input(slot, contract)?
+                        }
+                        Some(_) => {
+                            return Err(invalid(format!(
+                            "node {id}: raw series input {slot} differs from the selector schema"
+                        )))
+                        }
+                        None => {
+                            return Err(invalid(format!(
+                                "node {id}: PromQL fallback requires raw series input {slot}"
+                            )))
+                        }
+                    }
+                    slots.push(slot);
+                }
+                let (last, last_inputs) = steps
+                    .pop()
+                    .ok_or_else(|| invalid("empty PromQL lowering"))?;
+                let mut ids = Vec::new();
+                let resolve = |inputs: Vec<promql_fallback::Input>, ids: &[NodeId]| {
+                    inputs
+                        .into_iter()
+                        .map(|input| match input {
+                            promql_fallback::Input::Raw(i) => slots[i],
+                            promql_fallback::Input::Step(i) => ids[i],
+                        })
+                        .collect::<Vec<_>>()
+                };
+                for (operator, inputs) in steps {
+                    dag.add(auxiliary, resolve(inputs, &ids), operator)?;
+                    ids.push(auxiliary);
+                    auxiliary -= 1;
+                }
+                dag.add(
+                    id,
+                    resolve(last_inputs, &ids),
+                    last.with_output_schema(output)?,
+                )?;
+                continue;
+            }
+            if let Payload::MaintainPopulation { population } = &node.payload {
+                use planner_types::post_asap::maintained_population::PopulationInput;
+                let PopulationInput::CurrentSeries(spec) = &population.input else {
+                    return Err(invalid(
+                        "native maintained population requires a current-series input",
+                    ));
+                };
+                let [input] = schemas.as_slice() else {
+                    return Err(invalid("current-series population requires one input"));
+                };
+                if spec.without {
+                    return Err(invalid(
+                        "dynamic without grouping requires label-set projection",
+                    ));
+                }
+                let identity = named_column(
+                    input,
+                    &ColumnRef::Named(promql_rows::SERIES_IDENTITY_COLUMN.into()),
+                )?;
+                let coordinate = input
+                    .time_index
+                    .ok_or_else(|| invalid("current-series input lacks timestamp"))?;
+                let value = named_column(input, &ColumnRef::SampleValue)?;
+                let lookback = i64::try_from(spec.lookback_ms)
+                    .map_err(|_| invalid("current-series lookback overflows"))?;
+                dag.add(
+                    id,
+                    inputs,
+                    Operator::current_series(input.clone(), identity, coordinate, value, lookback)?
+                        .with_output_schema(output)?,
+                )?;
+                continue;
+            }
+            if let Payload::EvaluatePopulation { evaluation } = &node.payload {
+                use planner_types::post_asap::maintained_population::{
+                    PopulationInput, PopulationStatistic,
+                };
+                let [producer] = inputs.as_slice() else {
+                    return Err(invalid("population evaluation requires one input"));
+                };
+                let Payload::MaintainPopulation { population } = &nodes[producer].payload else {
+                    return Err(invalid(
+                        "population evaluation requires its declared population",
+                    ));
+                };
+                let PopulationInput::CurrentSeries(spec) = &population.input else {
+                    return Err(invalid("current-series population required"));
+                };
+                if spec.without {
+                    return Err(invalid(
+                        "dynamic without ranking requires label-set projection",
+                    ));
+                }
+                let input = schemas[0].clone();
+                let PopulationStatistic::TopK { k } = evaluation else {
+                    let mut chain =
+                        row_values::population_aggregate(&input, &spec.grouping, evaluation)?;
+                    let last = chain.pop().expect("nonempty chain");
+                    let mut inputs = inputs;
+                    for operator in chain {
+                        dag.add(auxiliary, inputs, operator)?;
+                        inputs = vec![auxiliary];
+                        auxiliary -= 1;
+                    }
+                    dag.add(id, inputs, last.with_output_schema(output)?)?;
+                    continue;
+                };
+                let groups = spec
+                    .grouping
+                    .iter()
+                    .map(|name| named_column(&input, &ColumnRef::Named(name.clone())))
+                    .collect::<Result<Vec<_>, _>>()?;
+                let value = named_column(&input, &ColumnRef::SampleValue)?;
+                dag.add(
+                    auxiliary,
+                    inputs,
+                    Operator::sort(
+                        input.clone(),
+                        vec![SortKey {
+                            column: value,
+                            descending: true,
+                            nulls_first: false,
+                        }],
+                        groups.clone(),
+                    )?,
+                )?;
+                dag.add(
+                    id,
+                    vec![auxiliary],
+                    Operator::limit(input, *k as u64, 0, groups)?.with_output_schema(output)?,
+                )?;
+                continue;
+            }
+            // A closed row must include either all source labels or the explicit
+            // complete-label identity. Projected labels alone are insufficient.
+            if let Payload::SummaryAgg {
+                family,
+                input: update,
+                reduction: PlannerReduction::PerEntity,
+                grouping,
+                filter: None,
+            } = &node.payload
+            {
+                let [input_id] = inputs.as_slice() else {
+                    return Err(invalid("per-entity summary requires one input"));
+                };
+                let Some(NonASAPOp::TimeRange { child, .. }) = restored[input_id].non_asap() else {
+                    return Err(invalid(
+                        "per-entity summary requires a resolved raw time range",
+                    ));
+                };
+                let Some(NonASAPOp::Scan { schema, .. }) = child.non_asap() else {
+                    return Err(invalid("per-entity summary requires a resolved source"));
+                };
+                if !schema.closed || update.item.is_some() {
+                    return Err(invalid(
+                        "per-entity summary requires complete source identity",
+                    ));
+                }
+                crate::capability::validate_summary_kernel(family, update, grouping)
+                    .map_err(Error::Invalid)?;
+                let SummaryInputExpr::Column(value) = &update.weight else {
+                    return Err(invalid(
+                        "per-entity update requires a projected value column",
+                    ));
+                };
+                let input = schemas[0].clone();
+                let value = named_column(&input, value)?;
+                let coordinate = input
+                    .time_index
+                    .ok_or_else(|| invalid("temporal input lacks time"))?;
+                let groups = (0..input.fields.len())
+                    .filter(|&column| column != value && column != coordinate)
+                    .collect();
+                let build = Operator::summary_build(
+                    input,
+                    family.clone(),
+                    value,
+                    Some(coordinate),
+                    groups,
+                )?;
+                let compact = build.schema();
+                dag.add(auxiliary, inputs, build)?;
+                dag.add(
+                    id,
+                    vec![auxiliary],
+                    Operator::scope_timestamp(compact, output)?,
+                )?;
+                continue;
+            }
+            if let Payload::Relational {
+                operator:
+                    NonASAPOpKind::BinaryOp {
+                        operator,
+                        return_bool,
+                    },
+            } = &node.payload
+            {
+                let operator = crate::expressions::binary::BinaryOperator::from_logical(
+                    operator,
+                    *return_bool,
+                );
+                let query_time = node.output_state.timing
+                    == planner_types::post_asap::ExecutionTiming::QueryTime;
+                if let Some(&(value, left)) = literals.get(&id) {
+                    let [input] = schemas.as_slice() else {
+                        return Err(invalid("scalar binary requires one row input"));
+                    };
+                    if !query_time {
+                        return Err(invalid("scalar literal binary must run at query time"));
+                    }
+                    let scalar =
+                        Operator::scalar(crate::values::Value::Float64(value), DataType::Float64)?;
+                    let (sides, scalars, operands) = if left {
+                        (
+                            [scalar.schema(), input.clone()],
+                            [true, false],
+                            vec![auxiliary, inputs[0]],
+                        )
+                    } else {
+                        (
+                            [input.clone(), scalar.schema()],
+                            [false, true],
+                            vec![inputs[0], auxiliary],
+                        )
+                    };
+                    let [l, r] = sides;
+                    let binary = Operator::series_binary(l, r, operator.clone(), scalars)
+                        .map_err(|error| invalid(format!("node {id}: {error}")))?;
+                    dag.add(auxiliary, vec![], scalar)?;
+                    dag.add(id, operands, binary.with_output_schema(output)?)?;
+                    auxiliary -= 1;
+                    continue;
+                }
+                let label_map = |schema: &SchemaRef| {
+                    schema
+                        .fields
+                        .iter()
+                        .any(|f| matches!(f.dtype, FieldDataType::Plain(DataType::Map { .. })))
+                };
+                // Grouped rows carry their labels as columns; per-series rows
+                // carry the series identity.
+                if let (true, [left, right]) = (query_time, schemas.as_slice()) {
+                    if !label_map(left) && !label_map(right) {
+                        let binary = Operator::series_binary(
+                            left.clone(),
+                            right.clone(),
+                            operator.clone(),
+                            [false, false],
+                        )
+                        .map_err(|error| invalid(format!("node {id}: {error}")))?;
+                        dag.add(id, inputs, binary.with_output_schema(output)?)?;
+                        continue;
+                    }
+                }
+            }
+            if let Payload::FinalizeExactAccumulator = &node.payload {
+                // Exact counts read out as Int64; PromQL declares a Float64 sample.
+                let evaluation = bind_operation(node, &schemas)
+                    .map_err(|error| invalid(format!("node {id}: {error}")))?;
+                let actual = evaluation.schema();
+                let converted = actual.fields.iter().zip(&output.fields).position(|(a, d)| {
+                    a.dtype == FieldDataType::Plain(DataType::Int64)
+                        && d.dtype == FieldDataType::Plain(DataType::Float64)
+                });
+                if let Some(column) = converted {
+                    let columns = actual
+                        .fields
+                        .iter()
+                        .enumerate()
+                        .map(|(i, field)| {
+                            (
+                                field.name.clone(),
+                                if i == column {
+                                    Expression::ExactFloat64(i)
+                                } else {
+                                    Expression::Column(i)
+                                },
+                            )
+                        })
+                        .collect();
+                    let project =
+                        Operator::project(actual, columns)?.with_output_schema(output.clone())?;
+                    dag.add(auxiliary, inputs, evaluation)?;
+                    if temporal_evaluation_drops_name(node) {
+                        dag.add(auxiliary - 1, vec![auxiliary], project)?;
+                        dag.add(
+                            id,
+                            vec![auxiliary - 1],
+                            Operator::series_without_name(output)?,
+                        )?;
+                    } else {
+                        dag.add(id, vec![auxiliary], project)?;
+                    }
+                    auxiliary -= 1;
+                    continue;
+                }
+            }
+            let mut operator = compile_node(node, &schemas)
+                .map_err(|error| invalid(format!("node {id}: {error}")))?;
+            if operator.is_counter_readout() {
+                let mut pending = vec![id];
+                let mut visited = BTreeSet::new();
+                let mut ranges = BTreeSet::new();
+                while let Some(ancestor) = pending.pop() {
+                    if !visited.insert(ancestor) {
+                        continue;
+                    }
+                    if let Payload::Relational {
+                        operator: NonASAPOpKind::TimeRange { range, .. },
+                    } = &nodes[&ancestor].payload
+                    {
+                        ranges.insert(
+                            i64::try_from(range.as_millis())
+                                .map_err(|_| invalid("counter lookback exceeds Int64"))?,
+                        );
+                        continue;
+                    }
+                    pending.extend(dependencies.get(&ancestor).into_iter().flatten().copied());
+                }
+                if ranges.len() > 1 {
+                    return Err(invalid("counter evaluation has ambiguous logical windows"));
+                }
+                if let Some(lookback) = ranges.into_iter().next() {
+                    operator = operator.with_counter_lookback(lookback)?;
+                }
+            }
+            if temporal_evaluation_drops_name(node) {
+                dag.add(auxiliary, inputs, operator)?;
+                dag.add(id, vec![auxiliary], Operator::series_without_name(output)?)?;
+            } else {
+                dag.add(id, inputs, operator)?;
+            }
+        }
+    }
+    dag.validate()?;
+    Ok(dag)
+}
+
+// Temporal summary evaluations produce PromQL vectors, whose range functions drop
+// the metric name before matching/filtering. Stored state retains its full identity.
+fn temporal_evaluation_drops_name(node: &PhysicalASAPDAGNode) -> bool {
+    node.output_schema
+        .fields
+        .iter()
+        .any(|field| field.name == promql_rows::SERIES_IDENTITY_COLUMN)
+        && matches!(
+            &node.payload,
+            Payload::FinalizeExactAccumulator
+                | Payload::SummaryEstimate {
+                    query: SketchStatistic::Quantile { .. }
+                        | SketchStatistic::Cardinality
+                        | SketchStatistic::PointCount { .. }
+                        | SketchStatistic::FrequencyL2
+                        | SketchStatistic::FrequencyEntropy
+                }
+        )
+}
+
+/// Bind a Planner node against the schemas supplied by its deployment edges.
+/// This is the same checked path used by complete DAG binding.
+pub fn compile_node(node: &PhysicalASAPDAGNode, inputs: &[SchemaRef]) -> Result<Operator, Error> {
+    for schema in inputs {
+        crate::values::validate_schema(schema)?;
+    }
+    bind_operation(node, inputs)?.with_output_schema(Arc::new(node.output_schema.clone()))
+}
+
+fn bind_operation(node: &PhysicalASAPDAGNode, inputs: &[SchemaRef]) -> Result<Operator, Error> {
+    if let Payload::Relational {
+        operator: NonASAPOpKind::BinaryOp {
+            operator,
+            return_bool,
+        },
+    } = &node.payload
+    {
+        let operator =
+            crate::expressions::binary::BinaryOperator::from_logical(operator, *return_bool);
+        let [left, right] = inputs else {
+            return Err(invalid("binary requires two inputs"));
+        };
+        if node.output_state.timing == planner_types::post_asap::ExecutionTiming::IngestionTime {
+            let value = |schema: &SchemaRef| -> Result<usize, Error> {
+                let columns = schema
+                    .fields
+                    .iter()
+                    .enumerate()
+                    .filter(|(_, field)| {
+                        field.dtype
+                            == FieldDataType::Plain(planner_types::pre_asap::DataType::Float64)
+                    })
+                    .map(|(i, _)| i)
+                    .collect::<Vec<_>>();
+                match columns.as_slice() {
+                    [value] => Ok(*value),
+                    _ => Err(invalid("aligned binary requires one value column")),
+                }
+            };
+            let (l, r) = (value(left)?, value(right)?);
+            let keys = left
+                .fields
+                .iter()
+                .enumerate()
+                .filter(|(i, _)| *i != l)
+                .map(|(i, field)| {
+                    right
+                        .fields
+                        .iter()
+                        .position(|other| other.name == field.name && other.dtype == field.dtype)
+                        .map(|j| (i, j))
+                        .ok_or_else(|| invalid("aligned input identities differ"))
+                })
+                .collect::<Result<Vec<_>, _>>()?;
+            return Operator::aligned_binary(
+                left.clone(),
+                right.clone(),
+                keys,
+                (l, r),
+                operator.clone(),
+            );
+        }
+        return Operator::vector_binary(left.clone(), right.clone(), operator.clone(), false);
+    }
+    if let Payload::Relational {
+        operator: NonASAPOpKind::Join { join_kind, pred },
+    } = &node.payload
+    {
+        let [left, right] = inputs else {
+            return Err(invalid("join requires two inputs"));
+        };
+        let pred = planner_types::ir::Predicate(local_scalar(&pred.0)?);
+        if *join_kind == planner_types::pre_asap::JoinKind::Semi {
+            if let Ok(keys) = equijoin_keys(&pred, left, right) {
+                return Operator::semi_join(left.clone(), right.clone(), keys);
+            }
+        }
+        return Operator::unified_relational_join(
+            left.clone(),
+            right.clone(),
+            join_kind.clone(),
+            &pred,
+            Arc::new(node.output_schema.clone()),
+        );
+    }
+    if let Payload::Relational {
+        operator: NonASAPOpKind::Values { rows, schema },
+    } = &node.payload
+    {
+        if !inputs.is_empty() {
+            return Err(invalid("Values takes no relational inputs"));
+        }
+        let empty = Arc::new(planner_types::pre_asap::Schema::default());
+        let rows = rows
+            .iter()
+            .map(|row| {
+                row.iter()
+                    .map(|expr| expression(expr, &empty)?.evaluate(&[]))
+                    .collect::<Result<Vec<_>, Error>>()
+            })
+            .collect::<Result<Vec<_>, Error>>()?;
+        let schema = Arc::new(schema.clone());
+        return Operator::source(
+            schema.clone(),
+            vec![crate::values::Batch::try_new(schema, rows)?],
+        );
+    }
+    let [input] = inputs else {
+        return Err(invalid(
+            "native Planner binding currently requires a unary operation or an explicit source",
+        ));
+    };
+    match &node.payload {
+        Payload::FinalizeExactAccumulator => {
+            let state = summary_column(input)?;
+            use crate::Statistic as S;
+            use planner_types::post_asap::ExactKind as E;
+            let statistic = match &input.fields[state].dtype {
+                FieldDataType::ExactAggregate(kind, _) => match kind {
+                    E::Sum => S::Sum,
+                    E::Count => S::Count,
+                    E::Min => S::Min,
+                    E::Max => S::Max,
+                    E::Rate => S::Rate,
+                    E::Increase => S::Increase,
+                    _ => return Err(invalid("exact family evaluation is unsupported")),
+                },
+                _ => return Err(invalid("exact finalization requires exact state")),
+            };
+            Operator::readout(
+                input.clone(),
+                state,
+                ReadoutQuery::Exact(ExactReadout {
+                    statistic,
+                    lookback_ms: None,
+                }),
+            )
+        }
+
+        Payload::Relational { operator } => match operator {
+            NonASAPOpKind::Project { cols, .. } => Operator::project(
+                input.clone(),
+                cols.iter()
+                    .enumerate()
+                    .map(|(i, col)| {
+                        Ok((
+                            node.output_schema
+                                .fields
+                                .get(i)
+                                .ok_or_else(|| invalid("projection width mismatch"))?
+                                .name
+                                .clone(),
+                            match &col.expr {
+                                WireScalarExpr::Column(index) => Expression::Column(*index),
+                                expr => expression(expr, input)?,
+                            },
+                        ))
+                    })
+                    .collect::<Result<_, Error>>()?,
+            ),
+            NonASAPOpKind::Filter { pred } => {
+                Operator::filter(input.clone(), expression(&pred.0, input)?)
+            }
+            NonASAPOpKind::Sort { keys, partition_by } => Operator::sort(
+                input.clone(),
+                keys.iter()
+                    .map(|key| {
+                        let WireScalarExpr::Column(column) = key.expr else {
+                            return Err(invalid(
+                                "sort expression must be projected before sorting",
+                            ));
+                        };
+                        Ok(SortKey {
+                            column,
+                            descending: !key.ascending,
+                            nulls_first: key.nulls_first,
+                        })
+                    })
+                    .collect::<Result<_, Error>>()?,
+                groups(input, partition_by)?,
+            ),
+            NonASAPOpKind::Limit {
+                n,
+                offset,
+                partition_by,
+            } => Operator::limit(
+                input.clone(),
+                n.unwrap_or(usize::MAX) as u64,
+                *offset as u64,
+                groups(input, partition_by)?,
+            ),
+            NonASAPOpKind::Aggregate {
+                reduction,
+                measures,
+                output_names,
+                filters,
+                having: None,
+            } => {
+                if filters.iter().any(Option::is_some) {
+                    return Err(invalid("filtered aggregate has no native implementation"));
+                }
+                if measures.len() != output_names.len() {
+                    return Err(invalid("aggregate output names differ from measures"));
+                }
+                let PlannerReduction::Reduce(keys) = reduction else {
+                    return Err(invalid(
+                        "per-entity aggregate requires an explicit entity binding",
+                    ));
+                };
+                let measures = measures
+                    .iter()
+                    .zip(output_names)
+                    .map(|(m, name)| {
+                        let column = |col: Option<usize>| {
+                            col.map(Ok)
+                                .unwrap_or_else(|| named_column(input, &ColumnRef::SampleValue))
+                        };
+                        let m = match m {
+                            AggIntent::Count { .. } => Reduction::Count,
+                            AggIntent::Sum { col } => Reduction::Sum(column(*col)?),
+                            AggIntent::Avg { col } => Reduction::Avg(column(*col)?),
+                            AggIntent::Min { col } => Reduction::Min(column(*col)?),
+                            AggIntent::Max { col } => Reduction::Max(column(*col)?),
+                            _ => {
+                                return Err(invalid(
+                                    "aggregate intent has no native implementation",
+                                ))
+                            }
+                        };
+                        Ok((name.clone(), m))
+                    })
+                    .collect::<Result<_, Error>>()?;
+                Operator::aggregate(input.clone(), groups(input, keys)?, measures)
+            }
+            _ => Err(invalid("value operation has no native implementation")),
+        },
+        Payload::SummaryAgg {
+            family,
+            input: update,
+            reduction,
+            grouping,
+            filter,
+        } => {
+            if filter.is_some() {
+                return Err(invalid(
+                    "filtered summary update has no native implementation",
+                ));
+            }
+            if let Some(item) = &update.item {
+                let PlannerReduction::Reduce(keys) = reduction else {
+                    return Err(invalid("keyed summary requires explicit partitions"));
+                };
+                let SummaryInputExpr::Column(weight) = &update.weight else {
+                    return Err(invalid(
+                        "keyed summary weight must be a finalized value column",
+                    ));
+                };
+                if matches!(family, FieldDataType::Sketch(kind, _) if kind.algorithm() == &planner_types::post_asap::SketchAlgorithm::CmsWithHeap)
+                    && !matches!(
+                        update.weight_domain,
+                        planner_types::post_asap::WeightDomain::NonNegative { .. }
+                    )
+                {
+                    return Err(invalid("CMS requires a nonnegative weight contract"));
+                }
+                fn columns(
+                    expr: &SummaryInputExpr,
+                    input: &SchemaRef,
+                    result: &mut Vec<usize>,
+                ) -> Result<(), Error> {
+                    match expr {
+                        SummaryInputExpr::Column(column) => {
+                            result.push(named_column(input, column)?)
+                        }
+                        SummaryInputExpr::Tuple(items) => {
+                            for item in items {
+                                columns(item, input, result)?;
+                            }
+                        }
+                        _ => return Err(invalid("keyed summary needs explicit item columns")),
+                    }
+                    Ok(())
+                }
+                let mut items = Vec::new();
+                columns(item, input, &mut items)?;
+                return Operator::keyed_summary_build(
+                    input.clone(),
+                    family.clone(),
+                    named_column(input, weight)?,
+                    items,
+                    groups(input, keys)?,
+                );
+            }
+            crate::capability::validate_summary_kernel(family, update, grouping)
+                .map_err(Error::Invalid)?;
+            let SummaryInputExpr::Column(column) = &update.weight else {
+                return Err(invalid(
+                    "summary update expression must be projected to a column",
+                ));
+            };
+            let PlannerReduction::Reduce(keys) = reduction else {
+                return Err(invalid(
+                    "summary construction requires explicit grouping columns",
+                ));
+            };
+            Operator::summary_build(
+                input.clone(),
+                family.clone(),
+                named_column(input, column)?,
+                input.time_index,
+                groups(input, keys)?,
+            )
+        }
+        Payload::SummaryMerge => {
+            let state = summary_column(input)?;
+            Operator::summary_merge(
+                input.clone(),
+                state,
+                (0..input.fields.len())
+                    .filter(|&i| i != state && Some(i) != input.time_index)
+                    .collect(),
+            )
+        }
+        Payload::SummaryEstimate { query } => {
+            if let SketchStatistic::TopK { k } = query {
+                return Operator::keyed_readout(
+                    input.clone(),
+                    summary_column(input)?,
+                    *k,
+                    Arc::new(node.output_schema.clone()),
+                );
+            }
+            Operator::readout(
+                input.clone(),
+                summary_column(input)?,
+                ReadoutQuery::Sketch(query.clone()),
+            )
+        }
+        _ => Err(invalid(
+            "physical operation has no native binding; no fallback is installed",
+        )),
+    }
+}
+fn summary_column(input: &SchemaRef) -> Result<usize, Error> {
+    let columns = input
+        .fields
+        .iter()
+        .enumerate()
+        .filter(|(_, f)| !matches!(f.dtype, FieldDataType::Plain(_)))
+        .map(|(i, _)| i)
+        .collect::<Vec<_>>();
+    match columns.as_slice() {
+        [column] => Ok(*column),
+        _ => Err(invalid("one summary state column required")),
+    }
+}
+fn named_column(input: &SchemaRef, column: &ColumnRef) -> Result<usize, Error> {
+    let name = match column {
+        // Executable SchemaRef retains column names, not table qualifiers.
+        // Frontend binding has resolved the qualifier; still reject ambiguous
+        // names here rather than guessing a join side.
+        ColumnRef::Named(name) | ColumnRef::Qualified { name, .. } => name.as_str(),
+        ColumnRef::SampleValue => "value",
+        _ => {
+            return Err(invalid(
+                "summary update requires an unambiguous bound column",
+            ))
+        }
+    };
+    let matches = input
+        .fields
+        .iter()
+        .enumerate()
+        .filter(|(_, field)| field.name == name)
+        .map(|(i, _)| i)
+        .collect::<Vec<_>>();
+    match matches.as_slice() {
+        [column] => Ok(*column),
+        _ => Err(invalid("summary update column missing or ambiguous")),
+    }
+}
+fn groups(input: &SchemaRef, groups: &GroupKeys) -> Result<Vec<usize>, Error> {
+    if groups.is_without() {
+        return Err(invalid("grouping without requires resolved label columns"));
+    }
+    if groups.keys().iter().any(|&i| i >= input.fields.len()) {
+        return Err(invalid("grouping column out of range"));
+    }
+    Ok(groups.keys().to_vec())
+}
+fn expression(expr: &WireScalarExpr, input: &SchemaRef) -> Result<Expression, Error> {
+    let expr = local_scalar(expr)?;
+    Ok(Expression::unified_planner(
+        crate::expressions::unified_planner::CompiledExpression::compile(&expr, input)?,
+    ))
+}
+
+struct CheckedSource<'a> {
+    source: Source<'a>,
+    output: SchemaRef,
+}
+impl PhysicalOperator<Batch, SchemaRef> for CheckedSource<'_> {
+    fn properties(&self, inputs: &[crate::plan::PlanProperties]) -> crate::plan::PlanProperties {
+        self.source.properties(inputs)
+    }
+
+    fn name(&self) -> &str {
+        self.source.name()
+    }
+    fn input_schemas(&self) -> Vec<SchemaRef> {
+        vec![]
+    }
+    fn output_schema(&self) -> SchemaRef {
+        self.output.clone()
+    }
+    fn output_bytes(&self, batch: &Batch) -> usize {
+        self.source.output_bytes(batch)
+    }
+    fn start<'a>(
+        &'a self,
+        inputs: Vec<crate::runtime::Input<'a, Batch>>,
+        context: crate::runtime::RunContext,
+    ) -> Result<crate::runtime::OutputStream<'a, Batch>, Error> {
+        use futures::StreamExt;
+        Ok(self
+            .source
+            .start(inputs, context)?
+            .map(|batch| {
+                let batch = batch?;
+                if batch.schema() != &self.output {
+                    return Err(invalid("source batch differs from its bound schema"));
+                }
+                Ok(batch)
+            })
+            .boxed_local())
+    }
+}
+
+// Bound recursion before invoking the upstream recursive provenance validator.
+fn preflight_depth(dag: &PhysicalASAPDAG) -> Result<(), Error> {
+    let mut remaining = dag
+        .nodes
+        .iter()
+        .map(|node| (node.id, 0usize))
+        .collect::<BTreeMap<_, _>>();
+    if remaining.len() != dag.nodes.len() {
+        return Err(invalid("duplicate Planner node"));
+    }
+    let mut consumers = BTreeMap::<_, Vec<_>>::new();
+    for edge in &dag.edges {
+        if !remaining.contains_key(&edge.producer) {
+            return Err(invalid("missing Planner edge producer"));
+        }
+        *remaining
+            .get_mut(&edge.consumer)
+            .ok_or_else(|| invalid("missing Planner edge consumer"))? += 1;
+        consumers
+            .entry(edge.producer)
+            .or_default()
+            .push(edge.consumer);
+    }
+    let mut ready = remaining
+        .iter()
+        .filter(|(_, n)| **n == 0)
+        .map(|(id, _)| *id)
+        .collect::<std::collections::VecDeque<_>>();
+    let mut depths = BTreeMap::new();
+    let mut visited = 0;
+    while let Some(id) = ready.pop_front() {
+        visited += 1;
+        let depth = *depths.get(&id).unwrap_or(&1usize);
+        if depth > 128 {
+            return Err(invalid("DAG exceeds the supported execution depth of 128"));
+        }
+        for &consumer in consumers.get(&id).into_iter().flatten() {
+            let next = depths.entry(consumer).or_insert(1);
+            *next = (*next).max(depth + 1);
+            let count = remaining.get_mut(&consumer).expect("validated endpoint");
+            *count -= 1;
+            if *count == 0 {
+                ready.push_back(consumer);
+            }
+        }
+    }
+    if visited != dag.nodes.len() {
+        return Err(invalid("Planner DAG contains a cycle"));
+    }
+    Ok(())
+}
+
+/// Join predicates address the concatenated left/right schema.
+fn semi_join_keys(
+    expr: &ScalarExpr,
+    left: usize,
+    right: usize,
+    keys: &mut Vec<(usize, usize)>,
+) -> Result<(), Error> {
+    match expr {
+        ScalarExpr::BoolAnd(parts) => {
+            for part in parts {
+                semi_join_keys(part, left, right, keys)?;
+            }
+        }
+        ScalarExpr::Compare {
+            left: a,
+            op: CompareOpKind::Eq,
+            right: b,
+            ..
+        } => {
+            let (ScalarExpr::Column(a), ScalarExpr::Column(b)) = (a.as_ref(), b.as_ref()) else {
+                return Err(invalid("semi-join requires column equality keys"));
+            };
+            let (a, b) = if a < b { (*a, *b) } else { (*b, *a) };
+            if a >= left || b < left || b >= left + right {
+                return Err(invalid("semi-join key must match left to right"));
+            }
+            keys.push((a, b - left));
+        }
+        _ => return Err(invalid("unsupported semi-join predicate")),
+    }
+    Ok(())
+}
+
+/// Resolve equality keys against the Planner join's concatenated input schema.
+/// Deployments may use these positions to bind their source columns.
+pub fn equijoin_keys(
+    pred: &planner_types::ir::Predicate,
+    left: &planner_types::post_asap::Schema,
+    right: &planner_types::post_asap::Schema,
+) -> Result<Vec<(usize, usize)>, Error> {
+    let mut keys = Vec::new();
+    semi_join_keys(&pred.0, left.fields.len(), right.fields.len(), &mut keys)?;
+    if keys.is_empty() {
+        return Err(invalid("semi-join requires explicit matching keys"));
+    }
+    Ok(keys)
+}
+
+fn local_scalar(expr: &WireScalarExpr) -> Result<ScalarExpr, Error> {
+    let mut missing = false;
+    let result = logical::scalar(expr, &mut |_| {
+        missing = true;
+        std::rc::Rc::new(OperatorNode::with_schema(
+            LogicalOperator::NonASAP(NonASAPOp::Values {
+                rows: vec![],
+                schema: Default::default(),
+            }),
+            Default::default(),
+        ))
+    });
+    if missing {
+        Err(invalid(
+            "scalar plan reads require explicit execution bindings",
+        ))
+    } else {
+        Ok(result)
+    }
+}
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/precompute.rs b/crates/asap-physical-operators/src/unified_physical_planner/precompute.rs
new file mode 100644
index 000000000..12e7564d8
--- /dev/null
+++ b/crates/asap-physical-operators/src/unified_physical_planner/precompute.rs
@@ -0,0 +1,643 @@
+//! Compile immutable summary-input computation with explicit population and pane identity.
+use super::promql_rows::SERIES_IDENTITY_COLUMN as SERIES_IDENTITY;
+use super::*;
+use planner_types::post_asap::FieldDataType as SummaryFamilyType;
+use planner_types::{
+    post_asap::{ExecutionTiming, GroupingStrategy, Schema},
+    pre_asap::DataType,
+};
+
+/// Physical rows carry the population and pane coordinate alongside the logical value.
+/// These fields preserve identities which are implicit in a stored summary instance.
+pub fn population_schema(family: SummaryFamilyType) -> SchemaRef {
+    Arc::new(Schema {
+        fields: vec![
+            planner_types::post_asap::Field {
+                name: "$population".into(),
+                dtype: SummaryFamilyType::Plain(DataType::Map {
+                    key: Box::new(DataType::Utf8),
+                    value: Box::new(DataType::Utf8),
+                    value_nullable: false,
+                }),
+                nullable: false,
+                table: None,
+            },
+            planner_types::post_asap::Field {
+                name: "$window_end".into(),
+                dtype: SummaryFamilyType::Plain(DataType::Timestamp),
+                nullable: false,
+                table: None,
+            },
+            planner_types::post_asap::Field {
+                name: "value".into(),
+                dtype: family,
+                nullable: false,
+                table: None,
+            },
+        ],
+        time_index: Some(1),
+        unique_keys: vec![],
+        closed: false,
+    })
+}
+
+/// Raw sample rows at a precompute boundary. `$population` holds the series'
+/// complete label set, so it is the complete source identity of per-series
+/// summaries; `$timestamp` is the sample time and `value` a finite sample
+/// (stale markers are not samples). Rows are what the boundary's source scan
+/// selected; the deployment decides which rows and panes they are. Label sets
+/// must be canonical (sorted, unique, no empty values), since they are the
+/// population identity: build rows with [`raw_sample_row`].
+pub fn raw_sample_schema() -> SchemaRef {
+    let mut schema = (*population_schema(SummaryFamilyType::Plain(DataType::Float64))).clone();
+    schema.fields[1].name = "$timestamp".into();
+    Arc::new(schema)
+}
+
+/// A raw sample row whose label set is sorted, unique and omits empty values,
+/// so one series always has one population identity.
+pub fn raw_sample_row(
+    labels: &BTreeMap<String, String>,
+    timestamp_ms: i64,
+    value: f64,
+) -> Vec<crate::values::Value> {
+    use crate::values::Value;
+    vec![
+        Value::Map(
+            labels
+                .iter()
+                .filter(|(_, v)| !v.is_empty())
+                .map(|(k, v)| {
+                    (
+                        Value::Utf8(k.as_str().into()),
+                        Value::Utf8(v.as_str().into()),
+                    )
+                })
+                .collect::<Vec<_>>()
+                .into(),
+        ),
+        Value::Timestamp(timestamp_ms),
+        Value::Float64(value),
+    ]
+}
+
+/// Input contract of a precompute boundary: raw sample rows for a raw time
+/// series scan, otherwise the stored population of its summary state.
+pub fn boundary_schema(node: &PhysicalASAPDAGNode) -> Result<SchemaRef, Error> {
+    if !matches!(
+        &node.payload,
+        Payload::Relational {
+            operator: NonASAPOpKind::Scan {
+                source: planner_types::pre_asap::Source::TimeSeries { .. },
+                ..
+            } | NonASAPOpKind::TimeRange { .. }
+        }
+    ) {
+        return source_schema(&node.output_schema);
+    }
+    let logical = &node.output_schema;
+    // Labels may be absent from a series; its label map then omits them.
+    let valid = logical
+        .fields
+        .iter()
+        .enumerate()
+        .all(|(i, field)| match &field.dtype {
+            SummaryFamilyType::Plain(DataType::Timestamp) => {
+                Some(i) == logical.time_index && !field.nullable
+            }
+            SummaryFamilyType::Plain(DataType::Float64) => field.name == "value" && !field.nullable,
+            SummaryFamilyType::Plain(DataType::Utf8) => true,
+            _ => false,
+        })
+        && !logical
+            .fields
+            .iter()
+            .any(|f| f.name.starts_with('$') && f.name != SERIES_IDENTITY)
+        && logical.time_index.is_some()
+        && logical.fields.iter().filter(|f| f.name == "value").count() == 1;
+    if !valid {
+        return Err(invalid(
+            "raw sample boundary requires labels, a timestamp and one Float64 value",
+        ));
+    }
+    Ok(raw_sample_schema())
+}
+
+/// Validate the adapter layout during installed-plan recovery without lowering operators.
+pub fn source_schema(logical: &Schema) -> Result<SchemaRef, Error> {
+    let states = logical
+        .fields
+        .iter()
+        .filter(|f| !matches!(f.dtype, SummaryFamilyType::Plain(_)))
+        .collect::<Vec<_>>();
+    let [state] = states.as_slice() else {
+        return Err(invalid(
+            "stored population requires one typed summary state",
+        ));
+    };
+    if logical.fields.iter().enumerate().any(|(i, field)| matches!(&field.dtype, SummaryFamilyType::Plain(dtype)
+        if field.nullable || !matches!(dtype, DataType::Utf8) && !(Some(i) == logical.time_index && *dtype == DataType::Timestamp))) {
+        return Err(invalid("stored population metadata cannot reconstruct extra value columns"));
+    }
+    if state.nullable {
+        return Err(invalid("stored population state cannot be null"));
+    }
+    Ok(population_schema(state.dtype.clone()))
+}
+
+pub fn is_population_schema(schema: &SchemaRef) -> bool {
+    schema
+        .fields
+        .get(2)
+        .is_some_and(|field| *schema == population_schema(field.dtype.clone()))
+}
+
+/// Compile a complete selected precompute sub-DAG. Inputs are already-computed
+/// state boundaries; the deployment supplies groups, panes and states, never operations.
+pub fn compile(
+    dag: &PhysicalASAPDAG,
+    frontiers: &[NodeId],
+    roots: &[NodeId],
+) -> Result<CompiledPhysicalDAG, Error> {
+    preflight_depth(dag)?;
+    dag.validate().map_err(|e| invalid(e.to_string()))?;
+    let nodes = dag
+        .nodes
+        .iter()
+        .map(|n| (u64::from(n.id.0), n))
+        .collect::<BTreeMap<_, _>>();
+    let frontier = frontiers.iter().copied().collect::<BTreeSet<_>>();
+    if frontier.len() != frontiers.len() || roots.iter().any(|r| frontier.contains(r)) {
+        return Err(invalid(
+            "precompute boundaries must be distinct from outputs",
+        ));
+    }
+    let mut dependencies = BTreeMap::<NodeId, Vec<NodeId>>::new();
+    let mut edges = dag.edges.iter().collect::<Vec<_>>();
+    edges.sort_by_key(|edge| {
+        (
+            edge.consumer.0,
+            match edge.role {
+                planner_types::ir::export::EdgeRole::Left => 0,
+                planner_types::ir::export::EdgeRole::Input => 1,
+                planner_types::ir::export::EdgeRole::Right => 2,
+                planner_types::ir::export::EdgeRole::ScalarRef => 3,
+            },
+        )
+    });
+    for edge in edges {
+        dependencies
+            .entry(u64::from(edge.consumer.0))
+            .or_default()
+            .push(u64::from(edge.producer.0));
+    }
+    let mut ordered = Vec::new();
+    let mut seen = BTreeSet::new();
+    let mut pending = roots.iter().map(|&id| (id, false)).collect::<Vec<_>>();
+    while let Some((id, expanded)) = pending.pop() {
+        if expanded {
+            ordered.push(id);
+            continue;
+        }
+        if !seen.insert(id) {
+            continue;
+        }
+        if !nodes.contains_key(&id) {
+            return Err(invalid("missing precompute node"));
+        }
+        pending.push((id, true));
+        if !frontier.contains(&id) {
+            pending.extend(
+                dependencies
+                    .get(&id)
+                    .into_iter()
+                    .flatten()
+                    .map(|id| (*id, false)),
+            );
+        }
+    }
+    let mut sources = BTreeMap::new();
+    let mut fragments = BTreeMap::new();
+    let mut outputs = BTreeMap::<NodeId, SchemaRef>::new();
+    for id in ordered {
+        let node = nodes[&id];
+        if frontier.contains(&id) {
+            let schema = boundary_schema(node)?;
+            sources.insert(id, InputContract::bounded(schema.clone()));
+            outputs.insert(id, schema);
+            continue;
+        }
+        if node.output_state.timing != ExecutionTiming::IngestionTime {
+            return Err(invalid("precompute dag contains a query-time operation"));
+        }
+        let inputs = dependencies.get(&id).cloned().unwrap_or_default();
+        let schemas = inputs
+            .iter()
+            .map(|id| {
+                outputs
+                    .get(id)
+                    .cloned()
+                    .ok_or_else(|| invalid("missing precompute input"))
+            })
+            .collect::<Result<Vec<_>, _>>()?;
+        let dag = fragment(
+            node,
+            &schemas,
+            &inputs.iter().map(|id| nodes[id]).collect::<Vec<_>>(),
+        )?;
+        outputs.insert(id, dag.output_contract(dag.roots()[0])?.schema);
+        fragments.insert(id, (inputs, dag));
+    }
+    CompiledPhysicalDAG::compose(sources, fragments, roots.to_vec())
+}
+
+fn validate_value_output(node: &PhysicalASAPDAGNode) -> Result<(), Error> {
+    let schema = &node.output_schema;
+    // Physical population rows already carry the complete identity in `$population`.
+    // Typed logical plans may expose its opaque series-identity column as metadata.
+    let identity = planner_types::pre_asap::schema::PROMQL_SERIES_IDENTITY;
+    let identities = schema
+        .fields
+        .iter()
+        .filter(|field| field.name == identity)
+        .collect::<Vec<_>>();
+    if identities.len() > 1
+        || identities
+            .iter()
+            .any(|field| field.nullable || field.dtype != SummaryFamilyType::Plain(DataType::Utf8))
+    {
+        return Err(invalid(
+            "precompute series identity requires one non-null Utf8 column",
+        ));
+    }
+    let values = schema
+        .fields
+        .iter()
+        .enumerate()
+        .filter(|(i, field)| Some(*i) != schema.time_index && field.name != identity)
+        .collect::<Vec<_>>();
+    if !matches!(values.as_slice(), [(_, field)] if !field.nullable && field.dtype == SummaryFamilyType::Plain(DataType::Float64))
+        || schema.time_index.is_some_and(|i| {
+            schema.fields.get(i).is_none_or(|f| {
+                f.nullable || f.dtype != SummaryFamilyType::Plain(DataType::Timestamp)
+            })
+        })
+    {
+        return Err(invalid(
+            "precompute value schema requires Float64 and an optional declared timestamp",
+        ));
+    }
+    Ok(())
+}
+
+fn fragment(
+    node: &PhysicalASAPDAGNode,
+    schemas: &[SchemaRef],
+    parents: &[&PhysicalASAPDAGNode],
+) -> Result<CompiledPhysicalDAG, Error> {
+    let sources = schemas
+        .iter()
+        .enumerate()
+        .map(|(id, schema)| (id as u64, InputContract::bounded(schema.clone())))
+        .collect();
+    let mut operators = BTreeMap::new();
+    let mut next = schemas.len() as u64;
+    let mut add = |inputs: Vec<NodeId>, op: Operator| -> Result<NodeId, Error> {
+        let id = next;
+        next += 1;
+        operators.insert(id, (inputs, op));
+        Ok(id)
+    };
+    let root = match &node.payload {
+        Payload::Relational {
+            operator:
+                NonASAPOpKind::BinaryOp {
+                    operator,
+                    return_bool,
+                },
+        } => {
+            let operator =
+                crate::expressions::binary::BinaryOperator::from_logical(operator, *return_bool);
+            validate_value_output(node)?;
+            if node.output_schema.time_index.is_none()
+                || parents.iter().any(|p| p.output_schema.time_index.is_none())
+            {
+                return Err(invalid(
+                    "precompute binary requires declared window timestamps",
+                ));
+            }
+            let [left, right] = schemas else {
+                return Err(invalid("precompute binary requires two inputs"));
+            };
+            add(
+                vec![0, 1],
+                Operator::aligned_binary(
+                    left.clone(),
+                    right.clone(),
+                    vec![(0, 0), (1, 1)],
+                    (2, 2),
+                    operator.clone(),
+                )?,
+            )?
+        }
+        Payload::FinalizeExactAccumulator => {
+            let [input] = schemas else {
+                return Err(invalid("finalize requires one state input"));
+            };
+            validate_value_output(node)?;
+            let statistic = match &input.fields[2].dtype {
+                SummaryFamilyType::ExactAggregate(planner_types::post_asap::ExactKind::Sum, _) => {
+                    crate::Statistic::Sum
+                }
+                SummaryFamilyType::ExactAggregate(
+                    planner_types::post_asap::ExactKind::Count,
+                    _,
+                ) => crate::Statistic::Count,
+                _ => {
+                    return Err(invalid(
+                        "precompute finalization requires explicit Sum or Count semantics",
+                    ))
+                }
+            };
+            let read = Operator::readout(
+                input.clone(),
+                2,
+                ReadoutQuery::Exact(ExactReadout {
+                    statistic,
+                    lookback_ms: None,
+                }),
+            )?;
+            let output = read.schema();
+            let read = add(vec![0], read)?;
+            let project = Operator::project(
+                output,
+                vec![
+                    ("$population".into(), Expression::Column(0)),
+                    ("$window_end".into(), Expression::Column(1)),
+                    (
+                        "value".into(),
+                        Expression::FiniteFloat64(Box::new(Expression::ExactFloat64(2))),
+                    ),
+                ],
+            )?
+            .with_output_schema(population_schema(SummaryFamilyType::Plain(
+                DataType::Float64,
+            )))?;
+            add(vec![read], project)?
+        }
+        Payload::SummaryAgg {
+            family,
+            input: update,
+            reduction,
+            grouping,
+            filter,
+        } => {
+            if filter.is_some() {
+                return Err(invalid(
+                    "filtered summary update has no native implementation",
+                ));
+            }
+            let [input] = schemas else {
+                return Err(invalid("summary update requires one input"));
+            };
+            // Item identities resolve against the complete label set of raw
+            // samples; finalized evaluations carry no such identity.
+            let raw = *input == raw_sample_schema();
+            // A unit-frequency summary (HLL) observes each raw sample value.
+            let unit_frequency = raw
+                && crate::capability::is_unit_sample_frequency(update)
+                && matches!(family, SummaryFamilyType::Sketch(kind, _) if !matches!(
+                    kind.algorithm(),
+                    planner_types::post_asap::SketchAlgorithm::Cms
+                        | planner_types::post_asap::SketchAlgorithm::CountSketch
+                        | planner_types::post_asap::SketchAlgorithm::CmsWithHeap
+                        | planner_types::post_asap::SketchAlgorithm::CountSketchWithHeap
+                ));
+            let keyed = update.item.is_some() && !unit_frequency;
+            if (keyed && !raw) || !matches!(grouping, GroupingStrategy::PerSubpopulationInstance) {
+                return Err(invalid(
+                    "precompute keyed/shared update needs its dedicated physical candidate",
+                ));
+            }
+            crate::capability::validate_summary_kernel(family, update, grouping)
+                .map_err(Error::Invalid)?;
+            if raw
+                && matches!(
+                    update.weight_domain,
+                    planner_types::post_asap::WeightDomain::NonNegative {
+                        proof: planner_types::post_asap::NonNegativeWeightProof::ResetAwareCounterDerivative
+                    }
+                )
+            {
+                return Err(invalid(
+                    "a counter-derivative weight cannot be read from raw cumulative samples",
+                ));
+            }
+            if keyed
+                && matches!(family, SummaryFamilyType::Sketch(kind, _) if kind.algorithm() == &planner_types::post_asap::SketchAlgorithm::CmsWithHeap)
+                && !matches!(
+                    update.weight_domain,
+                    planner_types::post_asap::WeightDomain::NonNegative { .. }
+                )
+            {
+                return Err(invalid("CMS requires a nonnegative weight contract"));
+            }
+            let labels = match reduction {
+                PlannerReduction::PerEntity => Expression::Column(0),
+                PlannerReduction::Reduce(keys) => Expression::LabelSet {
+                    column: 0,
+                    labels: keys
+                        .keys()
+                        .iter()
+                        .map(|key| {
+                            parents[0]
+                                .output_schema
+                                .fields
+                                .get(*key)
+                                // A raw label map omits absent labels; the
+                                // series identity is not one of its labels.
+                                .filter(|field| {
+                                    (raw || !field.nullable)
+                                        && field.name != SERIES_IDENTITY
+                                        && field.dtype == SummaryFamilyType::Plain(DataType::Utf8)
+                                })
+                                .map(|f| f.name.clone())
+                                .ok_or_else(|| {
+                                    invalid("summary grouping must identify population labels")
+                                })
+                        })
+                        .collect::<Result<Vec<_>, _>>()?,
+                    without: keys.is_without(),
+                },
+            };
+            let weight = match &update.weight {
+                _ if unit_frequency => Expression::Column(2),
+                SummaryInputExpr::Constant(value) => Expression::Literal {
+                    value: crate::values::Value::Float64(*value),
+                    dtype: DataType::Float64,
+                },
+                SummaryInputExpr::Column(ColumnRef::SampleValue) => Expression::Column(2),
+                SummaryInputExpr::Column(ColumnRef::Named(name))
+                    if parents[0].output_schema.fields.iter().any(|f| {
+                        f.name == *name && f.dtype == SummaryFamilyType::Plain(DataType::Float64)
+                    }) =>
+                {
+                    Expression::Column(2)
+                }
+                _ => {
+                    return Err(invalid(
+                        "summary weight does not resolve to the input value",
+                    ))
+                }
+            };
+            let mut columns = vec![
+                ("$population".into(), labels),
+                ("$window_end".into(), Expression::Column(1)),
+                ("value".into(), Expression::FiniteFloat64(Box::new(weight))),
+            ];
+            let mut fields = population_schema(SummaryFamilyType::Plain(DataType::Float64))
+                .fields
+                .clone();
+            if keyed {
+                let mut items = Vec::new();
+                raw_items(
+                    update.item.as_ref().expect("keyed item"),
+                    &parents[0].output_schema,
+                    &mut items,
+                )?;
+                for (index, (expression, dtype)) in items.into_iter().enumerate() {
+                    let name = format!("$item{index}");
+                    fields.push(planner_types::post_asap::Field {
+                        name: name.clone(),
+                        dtype: SummaryFamilyType::Plain(dtype),
+                        nullable: false,
+                        table: None,
+                    });
+                    columns.push((name, expression));
+                }
+            }
+            let item_columns = (3..fields.len()).collect::<Vec<_>>();
+            let project = Operator::project(input.clone(), columns)?.with_output_schema(
+                Arc::new(Schema {
+                    fields,
+                    unique_keys: vec![],
+                    closed: false,
+                    time_index: Some(1),
+                }),
+            )?;
+            let projected = project.schema();
+            let project = add(vec![0], project)?;
+            let build = if keyed {
+                Operator::keyed_summary_build(projected, family.clone(), 2, item_columns, vec![0])?
+            } else {
+                Operator::summary_build(projected, family.clone(), 2, Some(1), vec![0])?
+            };
+            let built = build.schema();
+            let build = add(vec![project], build)?;
+            add(
+                vec![build],
+                Operator::scope_timestamp(built, population_schema(family.clone()))?,
+            )?
+        }
+        Payload::SummaryMerge => {
+            let Some(input) = schemas.first() else {
+                return Err(invalid("summary merge requires inputs"));
+            };
+            if schemas.iter().any(|s| s != input) {
+                return Err(invalid("summary merge inputs differ"));
+            }
+            let union = add(
+                (0..schemas.len() as u64).collect(),
+                Operator::union(input.clone(), schemas.len())?,
+            )?;
+            let merge = Operator::summary_merge(input.clone(), 2, vec![0])?;
+            let merged = merge.schema();
+            let merge = add(vec![union], merge)?;
+            add(
+                vec![merge],
+                Operator::scope_timestamp(merged, input.clone())?,
+            )?
+        }
+        _ => {
+            return Err(invalid(
+                "precompute operation has no native population implementation",
+            ))
+        }
+    };
+    CompiledPhysicalDAG::from_operators(sources, operators, vec![root])
+}
+
+/// Resolve keyed item identities over raw sample rows: labels (absent labels
+/// read as empty, as in PromQL), the sample value, or the canonical encoding
+/// of the label set less excluded labels.
+fn raw_items(
+    expr: &SummaryInputExpr,
+    scan: &Schema,
+    items: &mut Vec<(Expression, DataType)>,
+) -> Result<(), Error> {
+    // Open PromQL scans need not list every label, so any name that is not
+    // another scan column (value, time, series identity) reads as a label.
+    let label = |column: &ColumnRef| match column {
+        ColumnRef::Named(name) | ColumnRef::Qualified { name, .. }
+            if !name.starts_with('$')
+                && scan.fields.iter().all(|f| {
+                    &f.name != name || f.dtype == SummaryFamilyType::Plain(DataType::Utf8)
+                }) =>
+        {
+            Some(name.clone())
+        }
+        _ => None,
+    };
+    let identity = |excluding: Vec<String>| {
+        (
+            Expression::LabelIdentity {
+                column: 0,
+                excluding,
+            },
+            DataType::Utf8,
+        )
+    };
+    match expr {
+        SummaryInputExpr::Column(ColumnRef::SampleValue) => {
+            items.push((Expression::Column(2), DataType::Float64))
+        }
+        SummaryInputExpr::Column(ColumnRef::Named(name) | ColumnRef::Qualified { name, .. })
+            if name == "value" =>
+        {
+            items.push((Expression::Column(2), DataType::Float64))
+        }
+        SummaryInputExpr::Column(ColumnRef::Named(name) | ColumnRef::Qualified { name, .. })
+            if name == SERIES_IDENTITY =>
+        {
+            items.push(identity(vec![]))
+        }
+        SummaryInputExpr::Column(column) if label(column).is_some() => items.push((
+            Expression::Label {
+                column: 0,
+                name: label(column).expect("resolved label"),
+            },
+            DataType::Utf8,
+        )),
+        SummaryInputExpr::EntityIdentity(
+            planner_types::post_asap::EntityIdentity::PromqlLabelSet { excluding },
+        ) => items.push(identity(
+            excluding
+                .iter()
+                .map(|column| {
+                    label(column).ok_or_else(|| invalid("excluded identity label is not a label"))
+                })
+                .collect::<Result<_, _>>()?,
+        )),
+        SummaryInputExpr::Tuple(parts) if !parts.is_empty() => {
+            for part in parts {
+                raw_items(part, scan, items)?;
+            }
+        }
+        _ => {
+            return Err(invalid(
+                "keyed summary item does not resolve over raw samples",
+            ))
+        }
+    }
+    Ok(())
+}
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/promql_fallback.rs b/crates/asap-physical-operators/src/unified_physical_planner/promql_fallback.rs
new file mode 100644
index 000000000..5d03bb0b9
--- /dev/null
+++ b/crates/asap-physical-operators/src/unified_physical_planner/promql_fallback.rs
@@ -0,0 +1,859 @@
+//! Compile a retained PromQL sub-DAG (`Fallback`) from its typed expression.
+//! The deployment supplies the raw series of each selector; the Planner
+//! computes selection, range functions, subqueries, matching and aggregation.
+use super::*;
+use crate::operators::SubquerySteps;
+use planner_types::post_asap::execution_data_state::lift_plain;
+use planner_types::pre_asap::{AtModifier, VectorMatchKind};
+
+/// Input slot for the raw series read by the `selector`th selector (in
+/// [`raw_series`] order) of Fallback node `node`. The node's own ID names its
+/// computed output, so the raw rows need another.
+pub fn raw_series_input(node: NodeId, selector: usize) -> NodeId {
+    node | ((selector as u64 + 1) << 32)
+}
+
+/// The Fallback node that owns a raw-series input slot.
+pub(super) fn raw_series_owner(slot: NodeId) -> Option<NodeId> {
+    (slot >> 32 != 0).then_some(slot & u64::from(u32::MAX))
+}
+
+/// A selector expression and its raw-series row schema.
+pub type Selector = (OperatorNode, SchemaRef);
+
+/// The selectors a Fallback expression reads, left to right, and the row
+/// schema of the raw series the deployment supplies for each at
+/// [`raw_series_input`]. The rows must cover the selector's window at every
+/// evaluation instant `T`, or at its `@` time: `(T - offset - range, T - offset]`;
+/// under a subquery `[R:S] offset O` that is `(T - O - R - offset - range, T - O - offset]`.
+pub fn raw_series(expression: &OperatorNode) -> Result<Vec<Selector>, Error> {
+    Ok(lower(expression)?.selectors)
+}
+
+/// An operator input: a selector's raw rows or an earlier step.
+pub(super) enum Input {
+    Raw(usize),
+    Step(usize),
+}
+
+/// Operators computing an expression; the last step is its result.
+#[derive(Default)]
+pub(super) struct Lowering {
+    pub selectors: Vec<Selector>,
+    pub steps: Vec<(Operator, Vec<Input>)>,
+}
+
+pub(super) fn lower(expression: &OperatorNode) -> Result<Lowering, Error> {
+    let mut lowering = Lowering::default();
+    lowering.value(expression)?;
+    Ok(lowering)
+}
+
+/// Compile a standalone scalar expression and expose its real series dependencies.
+/// Input slots use root 0; no logical wrapper node is introduced.
+pub fn compile_scalar_root(
+    expr: &ScalarExpr,
+) -> Result<(CompiledPhysicalDAG, Vec<Selector>), Error> {
+    let mut lowering = Lowering::default();
+    lowering.scalar_value(expr)?;
+    let mut inputs = BTreeMap::new();
+    for (i, (_, schema)) in lowering.selectors.iter().enumerate() {
+        inputs.insert(
+            raw_series_input(0, i),
+            InputContract::bounded(schema.clone()),
+        );
+    }
+    let last = lowering.steps.len() - 1;
+    let mut operators = BTreeMap::new();
+    for (i, (operator, dependencies)) in lowering.steps.into_iter().enumerate() {
+        let id = if i == last { 0 } else { i as u64 + 1 };
+        let dependencies = dependencies
+            .into_iter()
+            .map(|input| match input {
+                Input::Raw(i) => raw_series_input(0, i),
+                Input::Step(i) => i as u64 + 1,
+            })
+            .collect();
+        operators.insert(id, (dependencies, operator));
+    }
+    Ok((
+        CompiledPhysicalDAG::from_operators(inputs, operators, vec![0])?,
+        lowering.selectors,
+    ))
+}
+
+fn declared(expression: &OperatorNode) -> Result<SchemaRef, Error> {
+    let schema = expression.schema.clone();
+    Ok(Arc::new(lift_plain(&schema)))
+}
+
+fn millis(duration: &std::time::Duration) -> Result<i64, Error> {
+    i64::try_from(duration.as_millis()).map_err(|_| invalid("PromQL duration exceeds Int64"))
+}
+
+/// A fixed `@` time. `start()`/`end()` depend on the deployment's range query.
+fn at(shift: &planner_types::pre_asap::TimeShift) -> Result<Option<i64>, Error> {
+    match shift.at {
+        None => Ok(None),
+        Some(AtModifier::Timestamp(at)) => Ok(Some(at)),
+        Some(AtModifier::Start | AtModifier::End) => Ok(None),
+    }
+}
+
+fn range_anchor(expression: &OperatorNode) -> Option<AtModifier> {
+    match expression.expect_non_asap() {
+        NonASAPOp::TimeRange { child, .. } => range_anchor(child),
+        NonASAPOp::TimeShift { shift, .. } => shift
+            .at
+            .filter(|at| matches!(at, AtModifier::Start | AtModifier::End)),
+        _ => None,
+    }
+}
+
+/// `TimeRange { range, [TimeShift { offset, @ }], Scan }`: range, offset, `@`.
+fn selector(expression: &OperatorNode) -> Result<(i64, i64, Option<i64>), Error> {
+    let NonASAPOp::TimeRange { range, child, .. } = expression.expect_non_asap() else {
+        return Err(invalid("PromQL operand must be a series selector"));
+    };
+    let (offset, at, scan) = match child.expect_non_asap() {
+        NonASAPOp::TimeShift { shift, child } => {
+            (shift.offset_ms, at(shift)?, child.expect_non_asap())
+        }
+        scan => (0, None, scan),
+    };
+    if !matches!(scan, NonASAPOp::Scan { .. }) {
+        return Err(invalid("PromQL selector must read one scan"));
+    }
+    Ok((millis(range)?, offset, at))
+}
+
+impl Lowering {
+    fn schema(&self, input: &Input) -> SchemaRef {
+        match input {
+            Input::Raw(i) => self.selectors[*i].1.clone(),
+            Input::Step(i) => self.steps[*i].0.schema(),
+        }
+    }
+
+    fn add(&mut self, operator: Operator, inputs: Vec<Input>) -> Input {
+        self.steps.push((operator, inputs));
+        Input::Step(self.steps.len() - 1)
+    }
+
+    /// Conform `operator` to the logical schema of the expression it computes.
+    fn push(
+        &mut self,
+        operator: Operator,
+        inputs: Vec<Input>,
+        logical: &OperatorNode,
+    ) -> Result<Input, Error> {
+        Ok(self.add(operator.with_output_schema(declared(logical)?)?, inputs))
+    }
+
+    fn read(&mut self, selector: &OperatorNode) -> Result<Input, Error> {
+        let schema = declared(selector)?;
+        if !schema
+            .fields
+            .iter()
+            .any(|f| f.name == promql_rows::SERIES_IDENTITY_COLUMN)
+        {
+            return Err(invalid(
+                "PromQL fallback requires the complete series identity",
+            ));
+        }
+        self.selectors.push((selector.clone(), schema));
+        Ok(Input::Raw(self.selectors.len() - 1))
+    }
+
+    /// An instant vector, or a scalar for scalar-valued expressions.
+    fn value(&mut self, expression: &OperatorNode) -> Result<Input, Error> {
+        match expression.expect_non_asap() {
+            NonASAPOp::Concat { children, .. } => {
+                if !children.iter().all(|branch| matches!(branch.expect_non_asap(),
+                    NonASAPOp::PromqlRelabel { child, .. } if matches!(child.expect_non_asap(),
+                        NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::HistogramQuantile { .. }])))) {
+                    return Err(invalid("PromQL concatenation requires classic histogram quantile branches"));
+                }
+                let inputs = children
+                    .iter()
+                    .map(|child| self.value(child))
+                    .collect::<Result<Vec<_>, _>>()?;
+                let output = declared(expression)?;
+                if inputs.iter().any(|input| self.schema(input) != output) {
+                    return Err(invalid(
+                        "concatenated PromQL branches require equal schemas",
+                    ));
+                }
+                let union = self.add(Operator::union(output.clone(), inputs.len())?, inputs);
+                // Multi-quantile branches drop the metric name and form one vector.
+                self.push(
+                    Operator::series_without_name(output)?,
+                    vec![union],
+                    expression,
+                )
+            }
+            NonASAPOp::PromqlRelabel { dst, value, child } => {
+                let step = self.value(child)?;
+                let input = self.schema(&step);
+                let (replacement, source_regex) = match value {
+                    ScalarExpr::Literal(planner_types::pre_asap::ScalarValue::Utf8(value)) => {
+                        (value.clone(), None)
+                    }
+                    ScalarExpr::FunctionCall { name, args } if name == "label_replace" => {
+                        let [ScalarExpr::Column(source), ScalarExpr::Literal(planner_types::pre_asap::ScalarValue::Utf8(
+                            pattern,
+                        )), ScalarExpr::Literal(planner_types::pre_asap::ScalarValue::Utf8(
+                            replacement,
+                        ))] = args.as_slice()
+                        else {
+                            return Err(invalid("invalid label_replace arguments"));
+                        };
+                        let source = input
+                            .fields
+                            .get(*source)
+                            .ok_or_else(|| invalid("label_replace source missing"))?
+                            .name
+                            .clone();
+                        (replacement.clone(), Some((source, pattern.clone())))
+                    }
+                    _ => return Err(invalid("unsupported PromQL label rewrite")),
+                };
+                let operator = Operator::series_relabel(
+                    input,
+                    declared(expression)?,
+                    dst.clone(),
+                    replacement,
+                    source_regex,
+                )?;
+                self.push(operator, vec![step], expression)
+            }
+            NonASAPOp::TimeRange { .. } => {
+                let (range, offset, at) = selector(expression)?;
+                let input = self.read(expression)?;
+                let schema = self.schema(&input);
+                self.push(
+                    Operator::series_window(schema, None, range, offset, at, None)?
+                        .with_series_range_bounds(range_anchor(expression), None)?,
+                    vec![input],
+                    expression,
+                )
+            }
+            NonASAPOp::Aggregate {
+                reduction: planner_types::pre_asap::Reduction::PerEntity,
+                measures,
+                having: None,
+                child,
+                filters,
+                ..
+            } if filters.iter().all(Option::is_none) => {
+                let [function] = measures.as_slice() else {
+                    return Err(invalid("range function requires one measure"));
+                };
+                let step = self.range_function(function, child, expression)?;
+                if matches!(function, AggIntent::LastOverTime) {
+                    return Ok(step);
+                }
+                // Other range functions drop the name; equal label sets then error.
+                let input = self.schema(&step);
+                Ok(self.add(Operator::series_without_name(input)?, vec![step]))
+            }
+            NonASAPOp::Aggregate {
+                reduction: planner_types::pre_asap::Reduction::Reduce(keys),
+                measures,
+                having: None,
+                child,
+                filters,
+                ..
+            } if filters.iter().all(Option::is_none) => {
+                let [measure] = measures.as_slice() else {
+                    return Err(invalid("vector aggregation requires one measure"));
+                };
+                let input = self.value(child)?;
+                self.aggregate(input, measure, keys, expression)
+            }
+            NonASAPOp::Project {
+                cols,
+                child,
+                qualifier,
+            } => {
+                let value = planner_types::pre_asap::column_resolution::resolve_column_ref(
+                    &ColumnRef::SampleValue,
+                    &child.schema,
+                )
+                .map_err(|e| invalid(e.to_string()))?;
+                let sample = cols
+                    .iter()
+                    .find(|col| {
+                        col.alias.as_deref() == Some(child.schema.fields[value].name.as_str())
+                    })
+                    .ok_or_else(|| invalid("missing sample projection"))?;
+                let keep_name = matches!(sample.expr, ScalarExpr::Negative { .. });
+                let fields: Vec<_> = child
+                    .schema
+                    .fields
+                    .iter()
+                    .enumerate()
+                    .filter(|(_, field)| keep_name || field.name != "__name__")
+                    .collect();
+                if qualifier.is_some() || cols.len() != fields.len() {
+                    return Err(invalid("unsupported temporal projection shape"));
+                }
+                let mut computed = None;
+                for (col, (index, field)) in cols.iter().zip(fields) {
+                    if col.alias.as_deref() != Some(field.name.as_str()) {
+                        return Err(invalid("unsupported temporal projection alias"));
+                    }
+                    if index == value {
+                        computed = Some(col);
+                    } else {
+                        let expected = if !keep_name
+                            && field.name == planner_types::pre_asap::schema::PROMQL_SERIES_IDENTITY
+                        {
+                            ScalarExpr::FunctionCall {
+                                name: "promql_drop_metric_name".into(),
+                                args: vec![ScalarExpr::Column(index)],
+                            }
+                        } else {
+                            ScalarExpr::Column(index)
+                        };
+                        if col.expr != expected {
+                            return Err(invalid("unsupported temporal projection expression"));
+                        }
+                    }
+                }
+                let computed = computed.ok_or_else(|| invalid("no computed sample"))?;
+                if matches!(
+                    computed.expr,
+                    ScalarExpr::Negative { .. } | ScalarExpr::FunctionCall { .. }
+                ) {
+                    return self.pointwise_projection(cols, child, value, expression, keep_name);
+                }
+                self.sample_scalar_operation(&computed.expr, child, value, expression)
+            }
+            NonASAPOp::Filter { pred, child } => {
+                let value = planner_types::pre_asap::column_resolution::resolve_column_ref(
+                    &ColumnRef::SampleValue,
+                    &child.schema,
+                )
+                .map_err(|e| invalid(e.to_string()))?;
+                self.sample_scalar_operation(&pred.0, child, value, expression)
+            }
+            NonASAPOp::Sort {
+                keys,
+                partition_by,
+                child,
+            } => {
+                let step = self.value(child)?;
+                let input = self.schema(&step);
+                let keys = keys
+                    .iter()
+                    .map(|key| match key.expr {
+                        ScalarExpr::Column(column) => Ok(SortKey {
+                            column,
+                            descending: !key.ascending,
+                            nulls_first: key.nulls_first,
+                        }),
+                        _ => Err(invalid("sort key must be a column")),
+                    })
+                    .collect::<Result<_, _>>()?;
+                let groups = groups(&input, partition_by)?;
+                self.push(Operator::sort(input, keys, groups)?, vec![step], expression)
+            }
+            NonASAPOp::Limit {
+                n, offset, child, ..
+            } => {
+                let step = self.value(child)?;
+                let input = self.schema(&step);
+                // `topk by (...)` partitions through the Sort it limits.
+                let groups = match child.expect_non_asap() {
+                    NonASAPOp::Sort { partition_by, .. } => groups(&input, partition_by)?,
+                    _ => vec![],
+                };
+                self.push(
+                    Operator::limit(
+                        input,
+                        n.unwrap_or(usize::MAX) as u64,
+                        *offset as u64,
+                        groups,
+                    )?,
+                    vec![step],
+                    expression,
+                )
+            }
+            NonASAPOp::BinaryOp {
+                operator,
+                lhs,
+                rhs,
+                return_bool,
+            } => {
+                let sides = vec![self.value(lhs)?, self.value(rhs)?];
+                let operator = crate::expressions::binary::BinaryOperator::from_logical(
+                    operator,
+                    *return_bool,
+                );
+                let binary = Operator::series_binary(
+                    self.schema(&sides[0]),
+                    self.schema(&sides[1]),
+                    operator,
+                    [false, false],
+                )?;
+                self.push(binary, sides, expression)
+            }
+            NonASAPOp::PromqlVectorFromScalar(expr) => {
+                let step = self.scalar_value(expr)?;
+                let input = self.schema(&step);
+                Ok(self.add(
+                    Operator::scope_timestamp(input, declared(expression)?)?,
+                    vec![step],
+                ))
+            }
+            _ => Err(invalid("PromQL expression has no native fallback lowering")),
+        }
+    }
+
+    fn pointwise_projection(
+        &mut self,
+        cols: &[planner_types::ir::ProjectItem],
+        child: &OperatorNode,
+        value: usize,
+        output: &OperatorNode,
+        keep_name: bool,
+    ) -> Result<Input, Error> {
+        let mut input = self.value(child)?;
+        let mut projected = cols.to_vec();
+        for col in &mut projected {
+            if col.alias.as_deref() != Some(child.schema.fields[value].name.as_str()) {
+                continue;
+            }
+            if let ScalarExpr::FunctionCall { name, args } = &mut col.expr {
+                if planner_types::pre_asap::scalar_type_rules::promql_function_arity(name).is_none()
+                    || args.first() != Some(&ScalarExpr::Column(value))
+                {
+                    return Err(invalid("unsupported pointwise function"));
+                }
+                for arg in args.iter_mut().skip(1) {
+                    let scalar = self.scalar_value(arg)?;
+                    let left = self.schema(&input);
+                    let right = self.schema(&scalar);
+                    let index = left.fields.len();
+                    let mut schema = (*left).clone();
+                    schema.fields.extend(right.fields.clone());
+                    let join = Operator::unified_relational_join(
+                        left,
+                        right,
+                        planner_types::pre_asap::JoinKind::Inner,
+                        &planner_types::ir::Predicate(ScalarExpr::Literal(
+                            planner_types::pre_asap::ScalarValue::Boolean(true),
+                        )),
+                        Arc::new(schema),
+                    )?;
+                    input = self.add(join, vec![input, scalar]);
+                    *arg = ScalarExpr::Column(index);
+                }
+                if name == "promql_clamp" {
+                    let predicate = ScalarExpr::Not(Box::new(ScalarExpr::Compare {
+                        left: Box::new(args[1].clone()),
+                        right: Box::new(args[2].clone()),
+                        op: planner_types::pre_asap::CompareOpKind::Gt,
+                        semantics: planner_types::ir::ExprSemantics::Promql,
+                    }));
+                    let schema = self.schema(&input);
+                    let predicate =
+                        crate::expressions::unified_planner::CompiledExpression::compile(
+                            &predicate, &schema,
+                        )?;
+                    input = self.add(
+                        Operator::filter(
+                            schema,
+                            crate::expressions::Expression::unified_planner(predicate),
+                        )?,
+                        vec![input],
+                    );
+                }
+            }
+        }
+        let schema = self.schema(&input);
+        let columns = projected
+            .iter()
+            .map(|col| {
+                Ok((
+                    col.alias.clone().unwrap(),
+                    crate::expressions::Expression::unified_planner(
+                        crate::expressions::unified_planner::CompiledExpression::compile(
+                            &col.expr, &schema,
+                        )?,
+                    ),
+                ))
+            })
+            .collect::<Result<Vec<_>, Error>>()?;
+        let project = Operator::project(schema, columns)?;
+        let result = self.push(project, vec![input], output)?;
+        if keep_name {
+            Ok(result)
+        } else {
+            self.push(
+                Operator::series_without_name(self.schema(&result))?,
+                vec![result],
+                output,
+            )
+        }
+    }
+
+    fn sample_scalar_operation(
+        &mut self,
+        expr: &ScalarExpr,
+        child: &OperatorNode,
+        value: usize,
+        output: &OperatorNode,
+    ) -> Result<Input, Error> {
+        let (left, right, kind) = scalar_binary(expr)?;
+        let (scalar, scalar_left) = match (left, right) {
+            (ScalarExpr::Column(i), scalar) if *i == value => (scalar, false),
+            (scalar, ScalarExpr::Column(i)) if *i == value => (scalar, true),
+            _ => {
+                return Err(invalid(
+                    "sample projection requires one vector sample and one scalar",
+                ))
+            }
+        };
+        let vector = self.value(child)?;
+        let scalar = self.scalar_value(scalar)?;
+        let sides = if scalar_left {
+            vec![scalar, vector]
+        } else {
+            vec![vector, scalar]
+        };
+        let operator = Operator::series_binary(
+            self.schema(&sides[0]),
+            self.schema(&sides[1]),
+            kernel(kind),
+            [scalar_left, !scalar_left],
+        )?;
+        self.push(operator, sides, output)
+    }
+
+    fn scalar_value(&mut self, expr: &ScalarExpr) -> Result<Input, Error> {
+        match expr {
+            ScalarExpr::Literal(planner_types::pre_asap::ScalarValue::Float64(value)) => Ok(self
+                .add(
+                    Operator::scalar(crate::values::Value::Float64(*value), DataType::Float64)?,
+                    vec![],
+                )),
+            ScalarExpr::EvalTimestamp => Ok(self.add(Operator::evaluation_time(), vec![])),
+            ScalarExpr::PromqlScalarFromVector(child) => {
+                let step = self.value(child)?;
+                let input = self.schema(&step);
+                let values: Vec<_> = input
+                    .fields
+                    .iter()
+                    .enumerate()
+                    .filter(|(_, f)| f.dtype == FieldDataType::Plain(DataType::Float64))
+                    .map(|(i, _)| i)
+                    .collect();
+                let [value] = values.as_slice() else {
+                    return Err(invalid("scalar() requires one float sample column"));
+                };
+                let value = *value;
+                Ok(self.add(Operator::vector_to_scalar(input, value)?, vec![step]))
+            }
+            ScalarExpr::Negative { expr, .. } => {
+                let value = self.scalar_value(expr)?;
+                let minus = self.scalar_value(&ScalarExpr::literal_f64(-1.0))?;
+                let op = Operator::series_binary(
+                    self.schema(&value),
+                    self.schema(&minus),
+                    kernel(crate::expressions::binary::BinaryOpKind::Arithmetic(
+                        planner_types::pre_asap::ArithmeticOpKind::Mul,
+                    )),
+                    [true, true],
+                )?;
+                Ok(self.add(op, vec![value, minus]))
+            }
+            _ => {
+                let (left, right, kind) = scalar_binary(expr)?;
+                let sides = vec![self.scalar_value(left)?, self.scalar_value(right)?];
+                let op = Operator::series_binary(
+                    self.schema(&sides[0]),
+                    self.schema(&sides[1]),
+                    kernel(kind),
+                    [true, true],
+                )?;
+                Ok(self.add(op, sides))
+            }
+        }
+    }
+
+    /// `function(matrix)`, where the matrix is a range selector or a subquery.
+    fn range_function(
+        &mut self,
+        function: &AggIntent,
+        matrix: &OperatorNode,
+        logical: &OperatorNode,
+    ) -> Result<Input, Error> {
+        let function = unbound(function)?;
+        let (subquery, offset, at_ms) = match matrix.expect_non_asap() {
+            NonASAPOp::TimeShift { shift, child } => (child.as_ref(), shift.offset_ms, at(shift)?),
+            _ => (matrix, 0, None),
+        };
+        let NonASAPOp::PromqlSubquery {
+            range: outer,
+            resolution,
+            child,
+        } = subquery.expect_non_asap()
+        else {
+            let (range, offset, at) = selector(matrix)?;
+            let input = self.read(matrix)?;
+            let schema = self.schema(&input);
+            return self.push(
+                Operator::series_window(schema, Some(function), range, offset, at, None)?
+                    .with_series_range_bounds(range_anchor(matrix), None)?,
+                vec![input],
+                logical,
+            );
+        };
+        let step = resolution.as_ref().ok_or_else(|| {
+            invalid("subquery resolution defaults to the deployment evaluation interval")
+        })?;
+        let steps = SubquerySteps {
+            range_ms: millis(outer)?,
+            step_ms: millis(step)?,
+            offset_ms: offset,
+            at_ms,
+        };
+        // Each step evaluates a per-series selection or range function.
+        let (inner, selected) = match child.expect_non_asap() {
+            NonASAPOp::Aggregate {
+                reduction: planner_types::pre_asap::Reduction::PerEntity,
+                measures,
+                having: None,
+                child: selected,
+                ..
+            } => match measures.as_slice() {
+                [inner] => (Some(unbound(inner)?), selected.as_ref()),
+                _ => return Err(invalid("range function requires one measure")),
+            },
+            _ => (None, child.as_ref()),
+        };
+        let (range, inner_offset, inner_at) = selector(selected)?;
+        let raw = self.read(selected)?;
+        let schema = self.schema(&raw);
+        let mut step = self.push(
+            Operator::series_window(
+                schema,
+                inner.clone(),
+                range,
+                inner_offset,
+                inner_at,
+                Some(steps),
+            )?
+            .with_series_range_bounds(range_anchor(selected), range_anchor(matrix))?,
+            vec![raw],
+            child,
+        )?;
+        // Name removal must validate each subquery evaluation step.
+        if inner.is_some() && !matches!(inner, Some(AggIntent::LastOverTime)) {
+            let input = self.schema(&step);
+            let relabel = Operator::series_without_name(input)?;
+            step = self.add(relabel, vec![step]);
+        }
+        let input = self.schema(&step);
+        self.push(
+            Operator::series_window(input, Some(function), steps.range_ms, offset, at_ms, None)?
+                .with_series_range_bounds(range_anchor(matrix), None)?,
+            vec![step],
+            logical,
+        )
+    }
+
+    /// Cross-series aggregation. A global aggregate groups by one constant so
+    /// that no input series yields an empty vector, not one row.
+    fn aggregate(
+        &mut self,
+        mut step: Input,
+        measure: &AggIntent,
+        keys: &GroupKeys,
+        logical: &OperatorNode,
+    ) -> Result<Input, Error> {
+        let mut input = self.schema(&step);
+        if let AggIntent::HistogramQuantile { q, le } = measure {
+            if !keys.is_without() || keys.keys() != [*le] {
+                return Err(invalid("histogram_quantile must group without (le)"));
+            }
+            let operator = Operator::series_histogram_quantile(input, *q, *le)?;
+            return self.push(operator, vec![step], logical);
+        }
+        let value = input
+            .fields
+            .iter()
+            .enumerate()
+            .filter(|(_, f)| f.dtype == FieldDataType::Plain(DataType::Float64))
+            .map(|(i, _)| i)
+            .collect::<Vec<_>>();
+        let [value] = value.as_slice() else {
+            return Err(invalid("PromQL aggregation requires one Float64 value"));
+        };
+        let value = *value;
+        let reduction = match measure {
+            AggIntent::Sum { .. } => Reduction::Sum(value),
+            AggIntent::Avg { .. } => Reduction::Avg(value),
+            AggIntent::Min { .. } => Reduction::Min(value),
+            AggIntent::Max { .. } => Reduction::Max(value),
+            AggIntent::Count { .. } => Reduction::Count,
+            _ => return Err(invalid("vector aggregate has no native lowering")),
+        };
+        let mut groups = if keys.is_without() {
+            // Group by every remaining label, including the rewritten identity.
+            let excluded = keys.keys();
+            if excluded.iter().any(|&i| i >= input.fields.len()) {
+                return Err(invalid("grouping column out of range"));
+            }
+            let names = excluded.iter().map(|&i| input.fields[i].name.clone());
+            let relabel =
+                Operator::series_labels(input.clone(), VectorMatchKind::Ignoring, names.collect())?;
+            step = self.add(relabel, vec![step]);
+            (0..input.fields.len())
+                .filter(|&i| Some(i) != input.time_index && i != value && !excluded.contains(&i))
+                .collect()
+        } else {
+            groups(&input, keys)?
+        };
+        let global = groups.is_empty();
+        if global {
+            let mut columns = (0..input.fields.len())
+                .map(|i| (input.fields[i].name.clone(), Expression::Column(i)))
+                .collect::<Vec<_>>();
+            columns.push((
+                "$promql_global_group".into(),
+                Expression::Literal {
+                    value: crate::values::Value::Utf8("".into()),
+                    dtype: DataType::Utf8,
+                },
+            ));
+            let project = Operator::project(input, columns)?;
+            input = project.schema();
+            groups = vec![input.fields.len() - 1];
+            step = self.add(project, vec![step]);
+        }
+        let output = declared(logical)?;
+        let name = output
+            .fields
+            .last()
+            .ok_or_else(|| invalid("aggregate output lacks a value"))?
+            .name
+            .clone();
+        let aggregate = Operator::aggregate(input, groups, vec![(name, reduction)])?;
+        let actual = aggregate.schema();
+        let step = self.add(aggregate, vec![step]);
+        // Drop the constant group; convert counts where PromQL declares Float64.
+        let skip = usize::from(global);
+        let columns = actual.fields[skip..]
+            .iter()
+            .zip(&output.fields)
+            .enumerate()
+            .map(|(i, (field, declared))| {
+                let column = i + skip;
+                let expression = if field.dtype != declared.dtype {
+                    Expression::ExactFloat64(column)
+                } else {
+                    Expression::Column(column)
+                };
+                (field.name.clone(), expression)
+            })
+            .collect();
+        self.push(Operator::project(actual, columns)?, vec![step], logical)
+    }
+}
+
+fn unbound(intent: &AggIntent) -> Result<AggIntent<ColumnRef>, Error> {
+    Ok(match intent {
+        AggIntent::Rate => AggIntent::Rate,
+        AggIntent::Deriv => AggIntent::Deriv,
+        AggIntent::PredictLinear { seconds } => AggIntent::PredictLinear { seconds: *seconds },
+        AggIntent::Increase => AggIntent::Increase,
+        AggIntent::Delta => AggIntent::Delta,
+        AggIntent::Count { accuracy } => AggIntent::Count {
+            accuracy: accuracy.clone(),
+        },
+        AggIntent::Sum { .. } => AggIntent::Sum { col: None },
+        AggIntent::Avg { .. } => AggIntent::Avg { col: None },
+        AggIntent::Min { .. } => AggIntent::Min { col: None },
+        AggIntent::Max { .. } => AggIntent::Max { col: None },
+        AggIntent::IRate => AggIntent::IRate,
+        AggIntent::IDelta => AggIntent::IDelta,
+        AggIntent::Changes => AggIntent::Changes,
+        AggIntent::Resets => AggIntent::Resets,
+        AggIntent::LastOverTime => AggIntent::LastOverTime,
+        AggIntent::Quantile {
+            col: None,
+            q,
+            accuracy,
+        } => AggIntent::Quantile {
+            col: None,
+            q: *q,
+            accuracy: accuracy.clone(),
+        },
+        _ => return Err(invalid("unsupported PromQL range function")),
+    })
+}
+
+fn kernel(
+    kind: crate::expressions::binary::BinaryOpKind,
+) -> crate::expressions::binary::BinaryOperator {
+    crate::expressions::binary::BinaryOperator {
+        kind,
+        vector_match: None,
+        checked_relative_division: false,
+        checked_finite_division: false,
+    }
+}
+
+fn scalar_binary(
+    expr: &ScalarExpr,
+) -> Result<
+    (
+        &ScalarExpr,
+        &ScalarExpr,
+        crate::expressions::binary::BinaryOpKind,
+    ),
+    Error,
+> {
+    use crate::expressions::binary::BinaryOpKind as K;
+    match expr {
+        ScalarExpr::Arithmetic {
+            left,
+            right,
+            op,
+            semantics: planner_types::ir::ExprSemantics::Promql,
+        } => Ok((left, right, K::Arithmetic(op.clone()))),
+        ScalarExpr::Compare {
+            left,
+            right,
+            op,
+            semantics: planner_types::ir::ExprSemantics::Promql,
+        } => Ok((left, right, K::Compare(op.clone()))),
+        ScalarExpr::Case {
+            operand: None,
+            branches,
+            else_expr,
+        } if matches!(else_expr.as_deref(), Some(ScalarExpr::Literal(planner_types::pre_asap::ScalarValue::Float64(v))) if *v == 0.0) =>
+        {
+            let [(
+                ScalarExpr::Compare {
+                    left,
+                    right,
+                    op,
+                    semantics: planner_types::ir::ExprSemantics::Promql,
+                },
+                ScalarExpr::Literal(planner_types::pre_asap::ScalarValue::Float64(v)),
+            )] = branches.as_slice()
+            else {
+                return Err(invalid("unsupported scalar case"));
+            };
+            if *v != 1.0 {
+                return Err(invalid("unsupported scalar case result"));
+            }
+            Ok((left, right, K::CompareBool(op.clone())))
+        }
+        _ => Err(invalid("scalar expression has no native temporal lowering")),
+    }
+}
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/promql_rows.rs b/crates/asap-physical-operators/src/unified_physical_planner/promql_rows.rs
new file mode 100644
index 000000000..46670f478
--- /dev/null
+++ b/crates/asap-physical-operators/src/unified_physical_planner/promql_rows.rs
@@ -0,0 +1,303 @@
+//! A bounded PromQL source row carries the entire label set, not just labels
+//! mentioned by the query. The source adapter owns this lossless encoding.
+use super::*;
+use planner_types::ir::export::{
+    compile_physical_asap_dag, compile_physical_asap_dag_with_node_ids,
+};
+use planner_types::post_asap::FieldDataType as SummaryFamilyType;
+use planner_types::pre_asap::DataType;
+use std::rc::Rc;
+
+/// Not a legal PromQL label name, so it cannot shadow a user label.
+pub use planner_types::pre_asap::schema::PROMQL_SERIES_IDENTITY as SERIES_IDENTITY_COLUMN;
+
+/// Canonical, reversible identity. JSON object encoding preserves label names,
+/// empty values and escaping; sorting makes ingestion order irrelevant.
+pub fn encode_series_identity(labels: &BTreeMap<String, String>) -> Result<String, Error> {
+    serde_json::to_string(labels).map_err(|error| invalid(error.to_string()))
+}
+
+pub fn decode_series_identity(encoded: &str) -> Result<BTreeMap<String, String>, Error> {
+    let labels: BTreeMap<String, String> =
+        serde_json::from_str(encoded).map_err(|error| invalid(error.to_string()))?;
+    if encode_series_identity(&labels)? != encoded {
+        return Err(invalid("series identity is not canonically encoded"));
+    }
+    Ok(labels)
+}
+
+/// Resolve the row representation before candidate search; see
+/// [`planner_types::ir::schema_support::with_promql_series_identity`].
+pub fn with_series_identity(root: &Rc<OperatorNode>) -> Result<Rc<OperatorNode>, Error> {
+    planner_types::ir::schema_support::with_promql_series_identity(root).map_err(invalid)
+}
+
+/// Construct source rows only from full identities. The named label columns
+/// are projections of that same identity and cannot independently redefine it.
+pub fn series_row(
+    schema: &SchemaRef,
+    labels: &BTreeMap<String, String>,
+    timestamp: i64,
+    value: f64,
+) -> Result<Vec<crate::values::Value>, Error> {
+    use crate::values::Value;
+    let identity = encode_series_identity(labels)?;
+    let mut found = false;
+    let row = schema
+        .fields
+        .iter()
+        .enumerate()
+        .map(|(index, field)| {
+            if field.name == SERIES_IDENTITY_COLUMN {
+                if field.dtype != SummaryFamilyType::Plain(DataType::Utf8)
+                    || field.nullable
+                    || found
+                {
+                    return Err(invalid("invalid series identity column"));
+                }
+                found = true;
+                Ok(Value::Utf8(identity.clone().into()))
+            } else if Some(index) == schema.time_index {
+                Ok(Value::Timestamp(timestamp))
+            } else if field.name == "value"
+                && field.dtype == SummaryFamilyType::Plain(DataType::Float64)
+            {
+                Ok(Value::Float64(value))
+            } else if field.dtype == SummaryFamilyType::Plain(DataType::Utf8) {
+                Ok(labels.get(&field.name).map_or_else(
+                    || Value::Utf8("".into()),
+                    |value| Value::Utf8(value.clone().into()),
+                ))
+            } else {
+                Err(invalid("unsupported PromQL source column"))
+            }
+        })
+        .collect::<Result<Vec<_>, _>>()?;
+    if !found {
+        return Err(invalid("source lacks its full series identity"));
+    }
+    Ok(row)
+}
+
+/// Compile the selected TopK computation above an existing maintained-population
+/// source. The boundary supplies the complete eligible vector, not a truncated
+/// TopK result; ranking remains a native physical operator.
+pub fn compile_current_series_evaluation(
+    selected: &Rc<OperatorNode>,
+) -> Result<CompiledPhysicalDAG, Error> {
+    use planner_types::post_asap::{
+        maintained_population::PopulationStatistic, Field as SummaryField,
+    };
+    let selected = planner_types::ir::apply_lifecycle_timings(
+        selected,
+        &planner_types::ir::LifecycleAssignment::default_maintained(),
+        &mut planner_types::ir::TimingMemo::new(),
+    )
+    .map_err(|e| invalid(e.to_string()))?;
+    let mut dag =
+        compile_physical_asap_dag(&selected).map_err(|error| invalid(error.to_string()))?;
+    // Typed snapshot candidates already carry full identity throughout the DAG.
+    // Cut at the population output, preserving all selected heap/evaluation nodes.
+    let populations = dag.nodes.iter().filter(|node| matches!(&node.payload,
+        Payload::MaintainPopulation { population }
+            if matches!(population.input, planner_types::post_asap::maintained_population::PopulationInput::CurrentSeries(_))
+    )).collect::<Vec<_>>();
+    if let [population] = populations.as_slice() {
+        if population
+            .output_schema
+            .fields
+            .iter()
+            .any(|field| field.name == SERIES_IDENTITY_COLUMN)
+        {
+            return compile(
+                &dag,
+                BTreeMap::from([(
+                    u64::from(population.id.0),
+                    InputContract::bounded(Arc::new(population.output_schema.clone())),
+                )]),
+                &[u64::from(dag.root.0)],
+            );
+        }
+    }
+    let mut frontier = None;
+    for node in &mut dag.nodes {
+        match &mut node.payload {
+            Payload::Relational { operator } => {
+                if let NonASAPOpKind::Scan { schema, .. } = operator {
+                    schema.fields.push(SummaryField::new(
+                        SERIES_IDENTITY_COLUMN,
+                        SummaryFamilyType::Plain(DataType::Utf8),
+                        false,
+                    ));
+                    schema.closed = true;
+                }
+            }
+            Payload::MaintainPopulation { .. } => {
+                frontier = Some(u64::from(node.id.0));
+            }
+            Payload::EvaluatePopulation {
+                evaluation: PopulationStatistic::TopK { .. },
+            } => {}
+            _ => return Err(invalid("unsupported current-series evaluation dependency")),
+        }
+        if node
+            .output_schema
+            .fields
+            .iter()
+            .any(|field| field.name == SERIES_IDENTITY_COLUMN)
+        {
+            return Err(invalid(
+                "current-series input already has a physical identity column",
+            ));
+        }
+        node.output_schema.fields.push(SummaryField {
+            name: SERIES_IDENTITY_COLUMN.into(),
+            dtype: SummaryFamilyType::Plain(DataType::Utf8),
+            nullable: false,
+            table: None,
+        });
+    }
+    for edge in &mut dag.edges {
+        edge.intermediate_schema = dag
+            .nodes
+            .iter()
+            .find(|node| node.id == edge.producer)
+            .unwrap()
+            .output_schema
+            .clone();
+    }
+    let frontier = frontier.ok_or_else(|| invalid("missing current-series population"))?;
+    let schema = Arc::new(
+        dag.nodes
+            .iter()
+            .find(|node| u64::from(node.id.0) == frontier)
+            .unwrap()
+            .output_schema
+            .clone(),
+    );
+    compile(
+        &dag,
+        BTreeMap::from([(frontier, InputContract::bounded(schema))]),
+        &[u64::from(dag.root.0)],
+    )
+}
+
+/// Compile selected ranking or aggregation above an exact per-series Rate
+/// evaluation. Deployments bind complete window evaluations at this boundary;
+/// the heap is rebuilt independently for each evaluation. This does not move
+/// that frontier to ingestion time or authorize combining finalized rates.
+pub fn compile_rate_ranking(
+    selected: &Rc<OperatorNode>,
+) -> Result<(Rc<OperatorNode>, CompiledPhysicalDAG), Error> {
+    use planner_types::post_asap::ExactKind;
+    fn frontier(node: &Rc<OperatorNode>) -> Option<Rc<OperatorNode>> {
+        if matches!(&node.operator, LogicalOperator::ASAP(ASAPOp::FinalizeExactAccumulator { child })
+            if matches!(&child.operator, LogicalOperator::ASAP(ASAPOp::SummaryAgg {
+                family: FieldDataType::ExactAggregate(ExactKind::Rate, _),
+                reduction: planner_types::pre_asap::Reduction::PerEntity, child: raw, ..
+            }) if matches!(raw.non_asap(), Some(NonASAPOp::TimeRange { .. }))))
+        {
+            return Some(Rc::clone(node));
+        }
+        node.children().into_iter().find_map(frontier)
+    }
+    let selected = planner_types::ir::apply_lifecycle_timings(
+        selected,
+        &planner_types::ir::LifecycleAssignment::default_maintained(),
+        &mut planner_types::ir::TimingMemo::new(),
+    )
+    .map_err(|e| invalid(e.to_string()))?;
+    let source = frontier(&selected)
+        .ok_or_else(|| invalid("ranking requires one exact per-series Rate frontier"))?;
+    if !source
+        .schema
+        .fields
+        .iter()
+        .any(|field| field.name == SERIES_IDENTITY_COLUMN)
+    {
+        return Err(invalid("Rate ranking requires complete series identity"));
+    }
+    let compiled = compile_physical_asap_dag_with_node_ids(&selected)
+        .map_err(|error| invalid(error.to_string()))?;
+    let id = u64::from(
+        compiled
+            .node_ids
+            .node_id(&source)
+            .ok_or_else(|| invalid("missing Rate frontier"))?
+            .0,
+    );
+    let program = compile(
+        &compiled.dag,
+        BTreeMap::from([(id, InputContract::bounded(Arc::new(source.schema.clone())))]),
+        &[u64::from(compiled.dag.root.0)],
+    )?;
+    Ok((source, program))
+}
+
+/// Compile a lifecycle-timed DAG whose heap or grouped Sum over per-series
+/// Rate evaluations runs at ingestion time: fresh aggregate state per closed
+/// window. The input is the complete collection of per-series counter states.
+pub fn compile_fixed_window_rate_aggregation(
+    dag: &planner_types::ir::export::PhysicalASAPDAG,
+) -> Result<CompiledPhysicalPlan, Error> {
+    use planner_types::post_asap::{ExactKind, ExecutionTiming, SketchAlgorithm};
+    let sources = dag
+        .nodes
+        .iter()
+        .filter(|n| {
+            matches!(
+                &n.payload,
+                Payload::SummaryAgg {
+                    family: SummaryFamilyType::ExactAggregate(ExactKind::Rate, _),
+                    reduction: planner_types::pre_asap::Reduction::PerEntity,
+                    ..
+                }
+            )
+        })
+        .collect::<Vec<_>>();
+    let heaps = dag
+        .nodes
+        .iter()
+        .filter(|n| {
+            n.output_state.timing == ExecutionTiming::IngestionTime
+                && match &n.payload {
+                    Payload::SummaryAgg {
+                        family: SummaryFamilyType::Sketch(kind, _),
+                        ..
+                    } => matches!(
+                        kind.algorithm(),
+                        SketchAlgorithm::CmsWithHeap | SketchAlgorithm::CountSketchWithHeap
+                    ),
+                    Payload::SummaryAgg {
+                        family: SummaryFamilyType::ExactAggregate(ExactKind::Sum, _),
+                        ..
+                    } => true,
+                    _ => false,
+                }
+        })
+        .collect::<Vec<_>>();
+    let ([source], [heap]) = (sources.as_slice(), heaps.as_slice()) else {
+        return Err(invalid(
+            "expected one selected fixed-window Rate aggregation",
+        ));
+    };
+    if !source
+        .output_schema
+        .fields
+        .iter()
+        .any(|f| f.name == SERIES_IDENTITY_COLUMN)
+    {
+        return Err(invalid(
+            "fixed-window Rate aggregation requires complete series identity",
+        ));
+    }
+    compile_candidate(
+        dag,
+        BTreeMap::from([(
+            u64::from(source.id.0),
+            InputContract::bounded(Arc::new(source.output_schema.clone())),
+        )]),
+        &[u64::from(dag.root.0)],
+        &[u64::from(heap.id.0)],
+    )
+}
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/promql_values.rs b/crates/asap-physical-operators/src/unified_physical_planner/promql_values.rs
new file mode 100644
index 000000000..223d7f15c
--- /dev/null
+++ b/crates/asap-physical-operators/src/unified_physical_planner/promql_values.rs
@@ -0,0 +1,281 @@
+//! Physical scalar/vector contracts preserve complete label sets across native computation.
+use super::*;
+use planner_types::post_asap::FieldDataType as SummaryFamilyType;
+
+pub fn scalar_schema() -> SchemaRef {
+    crate::operators::vector_binary::value_schema(true)
+}
+pub fn vector_schema() -> SchemaRef {
+    crate::operators::vector_binary::value_schema(false)
+}
+
+pub fn matrix_schema() -> SchemaRef {
+    crate::operators::vector_window::matrix_schema()
+}
+
+pub fn compile_scalar(value: f64) -> Result<CompiledPhysicalDAG, Error> {
+    let operator = Operator::scalar(
+        crate::values::Value::Float64(value),
+        planner_types::pre_asap::DataType::Float64,
+    )?
+    .with_output_schema(scalar_schema())?;
+    CompiledPhysicalDAG::from_operators(
+        BTreeMap::new(),
+        BTreeMap::from([(0, (vec![], operator))]),
+        vec![0],
+    )
+}
+
+pub fn compile_temporal(
+    intent: &AggIntent<ColumnRef>,
+    preserve_metric_name: bool,
+) -> Result<CompiledPhysicalDAG, Error> {
+    let operator = Operator::range_window(intent.clone())?;
+    let mut operators = vec![operator];
+    if !preserve_metric_name {
+        operators.push(Operator::project(
+            vector_schema(),
+            vec![
+                (
+                    "labels".into(),
+                    Expression::LabelSet {
+                        column: 0,
+                        labels: vec![],
+                        without: true,
+                    },
+                ),
+                ("value".into(), Expression::Column(1)),
+            ],
+        )?);
+    }
+    unary(operators, matrix_schema())
+}
+
+pub fn compile_histogram_quantile() -> Result<CompiledPhysicalDAG, Error> {
+    CompiledPhysicalDAG::from_operators(
+        BTreeMap::from([
+            (0, InputContract::bounded(scalar_schema())),
+            (1, InputContract::bounded(vector_schema())),
+        ]),
+        BTreeMap::from([(2, (vec![0, 1], Operator::histogram_quantile()))]),
+        vec![2],
+    )
+}
+
+/// Compile before deployment chooses readers. Input slots 0 and 1 retain operand order.
+pub fn compile_binary(
+    operator: &crate::expressions::binary::BinaryOperator,
+    return_bool: bool,
+    left_scalar: bool,
+    right_scalar: bool,
+) -> Result<CompiledPhysicalDAG, Error> {
+    let left = crate::operators::vector_binary::value_schema(left_scalar);
+    let right = crate::operators::vector_binary::value_schema(right_scalar);
+    let op = Operator::vector_binary(left.clone(), right.clone(), operator.clone(), return_bool)?;
+    CompiledPhysicalDAG::from_operators(
+        BTreeMap::from([
+            (0, InputContract::bounded(left)),
+            (1, InputContract::bounded(right)),
+        ]),
+        BTreeMap::from([(2, (vec![0, 1], op))]),
+        vec![2],
+    )
+}
+
+fn unary(operators: Vec<Operator>, input: SchemaRef) -> Result<CompiledPhysicalDAG, Error> {
+    let root = operators.len() as u64;
+    CompiledPhysicalDAG::from_operators(
+        BTreeMap::from([(0, InputContract::bounded(input))]),
+        operators
+            .into_iter()
+            .enumerate()
+            .map(|(i, op)| ((i + 1) as u64, (vec![i as u64], op)))
+            .collect(),
+        vec![root],
+    )
+}
+
+fn grouped(grouping: &GroupKeys<ColumnRef>) -> Result<Operator, Error> {
+    let labels = grouping
+        .keys()
+        .iter()
+        .map(|key| match key {
+            ColumnRef::Named(label) => Ok(label.clone()),
+            _ => Err(invalid("vector grouping requires label names")),
+        })
+        .collect::<Result<Vec<_>, _>>()?;
+    Operator::project(
+        vector_schema(),
+        vec![
+            ("labels".into(), Expression::Column(0)),
+            ("value".into(), Expression::Column(1)),
+            (
+                "group".into(),
+                Expression::LabelSet {
+                    column: 0,
+                    labels,
+                    without: grouping.is_without(),
+                },
+            ),
+        ],
+    )
+}
+
+fn vector_output(input: SchemaRef, labels: usize, value: usize) -> Result<Operator, Error> {
+    let value = Expression::ExactFloat64(value);
+    Operator::project(
+        input,
+        vec![
+            ("labels".into(), Expression::Column(labels)),
+            ("value".into(), value),
+        ],
+    )
+}
+
+pub fn compile_aggregate(
+    intent: &AggIntent<ColumnRef>,
+    grouping: &GroupKeys<ColumnRef>,
+) -> Result<CompiledPhysicalDAG, Error> {
+    let project = grouped(grouping)?;
+    let reduction = match intent {
+        AggIntent::Sum { .. } => Reduction::Sum(1),
+        AggIntent::Avg { .. } => Reduction::Avg(1),
+        AggIntent::Count { .. } => Reduction::Count,
+        AggIntent::Min { .. } => Reduction::Min(1),
+        AggIntent::Max { .. } => Reduction::Max(1),
+        _ => return Err(invalid("unsupported vector aggregate")),
+    };
+    let aggregate =
+        Operator::aggregate(project.schema(), vec![2], vec![("value".into(), reduction)])?;
+    let output = vector_output(aggregate.schema(), 0, 1)?;
+    unary(vec![project, aggregate, output], vector_schema())
+}
+
+pub fn compile_sort(
+    descending: bool,
+    grouping: &GroupKeys<ColumnRef>,
+) -> Result<CompiledPhysicalDAG, Error> {
+    let project = grouped(grouping)?;
+    let sort = Operator::sort(
+        project.schema(),
+        vec![SortKey {
+            column: 1,
+            descending,
+            nulls_first: false,
+        }],
+        vec![2],
+    )?;
+    let output = vector_output(sort.schema(), 0, 1)?;
+    unary(vec![project, sort, output], vector_schema())
+}
+
+pub fn compile_limit(
+    n: u64,
+    offset: u64,
+    grouping: &GroupKeys<ColumnRef>,
+) -> Result<CompiledPhysicalDAG, Error> {
+    let project = grouped(grouping)?;
+    let limit = Operator::limit(project.schema(), n, offset, vec![2])?;
+    let output = vector_output(limit.schema(), 0, 1)?;
+    unary(vec![project, limit, output], vector_schema())
+}
+
+pub fn compile_negate(scalar: bool) -> Result<CompiledPhysicalDAG, Error> {
+    let input = if scalar {
+        scalar_schema()
+    } else {
+        vector_schema()
+    };
+    let mut columns = Vec::new();
+    if !scalar {
+        columns.push(("labels".into(), Expression::Column(0)));
+    }
+    columns.push((
+        if scalar {
+            "$promql_scalar".into()
+        } else {
+            "value".into()
+        },
+        Expression::Negate(Box::new(Expression::Column(if scalar { 0 } else { 1 }))),
+    ));
+    unary(vec![Operator::project(input.clone(), columns)?], input)
+}
+
+pub fn compile_vector_to_scalar() -> Result<CompiledPhysicalDAG, Error> {
+    unary(
+        vec![Operator::vector_to_scalar(vector_schema(), 1)?.with_output_schema(scalar_schema())?],
+        vector_schema(),
+    )
+}
+
+/// A stored exact-state input retains the complete population identity. The
+/// deployment supplies eligible panes; merging and finalization are computation.
+pub fn exact_state_schema(family: SummaryFamilyType) -> Result<SchemaRef, Error> {
+    if !matches!(family, SummaryFamilyType::ExactAggregate(..)) {
+        return Err(invalid("exact-state input requires an exact family"));
+    }
+    crate::values::validate_family(&family)?;
+    let mut schema = (*vector_schema()).clone();
+    schema.fields[1].dtype = family;
+    Ok(Arc::new(schema))
+}
+
+/// Retain exact evaluation semantics before any deployment state is opened.
+pub fn compile_exact_evaluation(
+    family: SummaryFamilyType,
+    lookback_ms: u64,
+    preserve_metric_name: bool,
+) -> Result<CompiledPhysicalDAG, Error> {
+    use planner_types::post_asap::ExactKind;
+    let statistic = match &family {
+        SummaryFamilyType::ExactAggregate(kind, _) => match kind {
+            ExactKind::Sum => crate::Statistic::Sum,
+            ExactKind::Count => crate::Statistic::Count,
+            ExactKind::Min => crate::Statistic::Min,
+            ExactKind::Max => crate::Statistic::Max,
+            ExactKind::Rate => crate::Statistic::Rate,
+            ExactKind::Increase => crate::Statistic::Increase,
+            ExactKind::IRate => {
+                return Err(invalid("instant-rate state evaluation is not supported"))
+            }
+        },
+        _ => return Err(invalid("exact evaluation requires an exact family")),
+    };
+    let input = exact_state_schema(family)?;
+    let merge = Operator::summary_merge(input.clone(), 1, vec![0])?;
+    let mut evaluation = Operator::readout(
+        merge.schema(),
+        1,
+        ReadoutQuery::Exact(ExactReadout {
+            statistic,
+            lookback_ms: None,
+        }),
+    )?;
+    if matches!(
+        statistic,
+        crate::Statistic::Rate | crate::Statistic::Increase
+    ) {
+        evaluation = evaluation.with_counter_lookback(
+            i64::try_from(lookback_ms).map_err(|_| invalid("counter lookback exceeds Int64"))?,
+        )?;
+    }
+    let project = Operator::project(
+        evaluation.schema(),
+        vec![
+            (
+                "labels".into(),
+                if preserve_metric_name {
+                    Expression::Column(0)
+                } else {
+                    Expression::LabelSet {
+                        column: 0,
+                        labels: vec![],
+                        without: true,
+                    }
+                },
+            ),
+            ("value".into(), Expression::ExactFloat64(1)),
+        ],
+    )?;
+    unary(vec![merge, evaluation, project], input)
+}
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/row_values.rs b/crates/asap-physical-operators/src/unified_physical_planner/row_values.rs
new file mode 100644
index 000000000..14f3d4813
--- /dev/null
+++ b/crates/asap-physical-operators/src/unified_physical_planner/row_values.rs
@@ -0,0 +1,60 @@
+//! Query-time PromQL value computation over logical row schemas.
+use super::*;
+use planner_types::post_asap::maintained_population::PopulationStatistic;
+use planner_types::pre_asap::DataType;
+
+/// Aggregate evaluations of a maintained current-series population, as a chain.
+pub(super) fn population_aggregate(
+    input: &SchemaRef,
+    grouping: &[String],
+    evaluation: &PopulationStatistic,
+) -> Result<Vec<Operator>, Error> {
+    let groups = grouping
+        .iter()
+        .map(|name| named_column(input, &ColumnRef::Named(name.clone())))
+        .collect::<Result<Vec<_>, _>>()?;
+    let value = named_column(input, &ColumnRef::SampleValue)?;
+    let reduction = match evaluation {
+        PopulationStatistic::Sum => Reduction::Sum(value),
+        PopulationStatistic::Count => Reduction::Count,
+        PopulationStatistic::Average => Reduction::Avg(value),
+        PopulationStatistic::Quantile { q } => Reduction::Quantile {
+            column: value,
+            q: *q,
+        },
+        PopulationStatistic::TopK { .. } => {
+            return Err(invalid(
+                "TopK population evaluation ranks; it does not aggregate",
+            ))
+        }
+    };
+    if !groups.is_empty() {
+        return Ok(vec![Operator::aggregate(
+            input.clone(),
+            groups,
+            vec![("value".into(), reduction)],
+        )?]);
+    }
+    // A global aggregate over no members is an empty PromQL vector, not one row.
+    let aggregate = Operator::aggregate(
+        input.clone(),
+        vec![],
+        vec![
+            ("value".into(), reduction),
+            ("members".into(), Reduction::Count),
+        ],
+    )?;
+    let zero = Expression::Literal {
+        value: crate::values::Value::Int64(0),
+        dtype: DataType::Int64,
+    };
+    let filter = Operator::filter(
+        aggregate.schema(),
+        Expression::Less(Box::new(zero), Box::new(Expression::Column(1))),
+    )?;
+    let project = Operator::project(
+        filter.schema(),
+        vec![("value".into(), Expression::Column(0))],
+    )?;
+    Ok(vec![aggregate, filter, project])
+}
diff --git a/crates/asap-physical-operators/src/unified_sources/memory.rs b/crates/asap-physical-operators/src/unified_sources/memory.rs
new file mode 100644
index 000000000..856c73cb0
--- /dev/null
+++ b/crates/asap-physical-operators/src/unified_sources/memory.rs
@@ -0,0 +1,44 @@
+use super::*;
+/// Immutable in-memory raw data. The connector owns the resident input; each
+/// cursor clones only the next requested batch, not the entire data set.
+pub struct MemorySource {
+    schema: SchemaRef,
+    batches: Vec<Batch>,
+}
+impl MemorySource {
+    pub fn new(schema: SchemaRef, batches: Vec<Batch>) -> Result<Self, Error> {
+        crate::values::validate_schema(&schema)?;
+        if schema
+            .fields
+            .iter()
+            .any(|f| !matches!(f.dtype, SummaryFamilyType::Plain(_)))
+        {
+            return Err(Error::Invalid(
+                "raw source cannot contain summary states".into(),
+            ));
+        }
+        if batches.iter().any(|batch| batch.schema() != &schema) {
+            return Err(Error::Invalid("memory source batch schema mismatch".into()));
+        }
+        Ok(Self { schema, batches })
+    }
+}
+impl RawSource for MemorySource {
+    fn boundedness(&self) -> crate::plan::Boundedness {
+        crate::plan::Boundedness::Bounded
+    }
+    fn schema(&self) -> SchemaRef {
+        self.schema.clone()
+    }
+    fn scan(&self, context: RunContext) -> Result<OutputStream<'_, Batch>, Error> {
+        Ok(stream::iter(self.batches.iter())
+            .map(move |batch| {
+                if context.is_cancelled() {
+                    return Err(Error::Cancelled);
+                }
+                let _allocation = context.reserve(batch.bytes())?;
+                Ok(batch.clone())
+            })
+            .boxed_local())
+    }
+}
diff --git a/crates/asap-physical-operators/src/unified_sources/mod.rs b/crates/asap-physical-operators/src/unified_sources/mod.rs
new file mode 100644
index 000000000..9dbe62c15
--- /dev/null
+++ b/crates/asap-physical-operators/src/unified_sources/mod.rs
@@ -0,0 +1,177 @@
+//! Raw data access. Connectors provide rows; Scan owns Planner predicate semantics.
+use crate::{
+    expressions::unified_planner::CompiledExpression,
+    plan::PhysicalOperator,
+    runtime::{Input, OutputStream, RunContext},
+    values::{Batch, SchemaRef, Value},
+    Error,
+};
+use futures::{stream, StreamExt};
+use planner_types::ir::{NonASAPOp, OperatorNode};
+use planner_types::{
+    post_asap::FieldDataType as SummaryFamilyType,
+    pre_asap::{DataType, Source},
+};
+use std::sync::Arc;
+
+/// A bound data source. Metadata must be stable for the lifetime of the binding.
+/// Each scan opens an independent cursor. Connectors return raw, unfiltered rows
+/// and must honor cancellation and bound their own I/O buffers. Dropping a cursor
+/// must release its resources. A connector error is never an empty successful scan.
+pub trait RawSource {
+    fn schema(&self) -> SchemaRef;
+    /// Declare a finite snapshot/window explicitly; execution scope alone does not bound a cursor.
+    fn boundedness(&self) -> crate::plan::Boundedness {
+        crate::plan::Boundedness::Unknown
+    }
+    fn scan(&self, context: RunContext) -> Result<OutputStream<'_, Batch>, Error>;
+}
+
+/// Explicit source identities; no implicit network discovery or fallback.
+#[derive(Default)]
+pub struct DataSources {
+    sources: Vec<(Source, Arc<dyn RawSource>)>,
+}
+impl DataSources {
+    pub fn register(&mut self, identity: Source, source: Arc<dyn RawSource>) -> Result<(), Error> {
+        if self.sources.iter().any(|(key, _)| key == &identity) {
+            return Err(Error::Invalid("duplicate data source".into()));
+        }
+        crate::values::validate_schema(&source.schema())?;
+        self.sources.push((identity, source));
+        Ok(())
+    }
+    pub fn bind(&self, expression: &OperatorNode) -> Result<Scan, Error> {
+        let Some(NonASAPOp::Scan {
+            source,
+            predicates,
+            schema,
+        }) = expression.non_asap()
+        else {
+            return Err(Error::Invalid(
+                "raw Scan requires a Planner Scan leaf".into(),
+            ));
+        };
+        let output = Arc::new(schema.clone());
+        crate::values::validate_schema(&output)?;
+        let reader = self
+            .sources
+            .iter()
+            .find(|(key, _)| key == source)
+            .map(|(_, reader)| reader.clone())
+            .ok_or_else(|| Error::Invalid(format!("unbound raw source: {source:?}")))?;
+        if reader.schema() != output {
+            return Err(Error::Invalid(
+                "raw source differs from Planner Scan schema".into(),
+            ));
+        }
+        let predicates = predicates
+            .iter()
+            .map(|predicate| {
+                let predicate = CompiledExpression::compile(&predicate.0, &output)?;
+                if predicate.dtype().0 != DataType::Bool {
+                    return Err(Error::Invalid("Scan predicate must be boolean".into()));
+                }
+                Ok(predicate)
+            })
+            .collect::<Result<Vec<_>, Error>>()?;
+        Ok(Scan {
+            reader,
+            output,
+            predicates,
+        })
+    }
+}
+
+pub struct Scan {
+    reader: Arc<dyn RawSource>,
+    output: SchemaRef,
+    predicates: Vec<CompiledExpression>,
+}
+impl PhysicalOperator<Batch, SchemaRef> for Scan {
+    fn properties(&self, _: &[crate::plan::PlanProperties]) -> crate::plan::PlanProperties {
+        crate::plan::PlanProperties {
+            boundedness: self.reader.boundedness(),
+            emission: crate::plan::Emission::Incremental,
+        }
+    }
+
+    fn name(&self) -> &str {
+        "Scan"
+    }
+    fn input_schemas(&self) -> Vec<SchemaRef> {
+        vec![]
+    }
+    fn output_schema(&self) -> SchemaRef {
+        self.output.clone()
+    }
+    fn output_bytes(&self, batch: &Batch) -> usize {
+        batch.bytes()
+    }
+    fn start<'a>(
+        &'a self,
+        inputs: Vec<Input<'a, Batch>>,
+        context: RunContext,
+    ) -> Result<OutputStream<'a, Batch>, Error> {
+        if !inputs.is_empty() {
+            return Err(Error::Invalid("Scan cannot have inputs".into()));
+        }
+        if context.is_cancelled() {
+            return Err(Error::Cancelled);
+        }
+        // Opening is lazy: validation and construction of a run perform no I/O.
+        let opening = context.clone();
+        let stream = stream::once(async move {
+            if opening.is_cancelled() {
+                return Err(Error::Cancelled);
+            }
+            self.reader.scan(opening)
+        });
+        use futures::TryStreamExt;
+        Ok(stream
+            .try_flatten()
+            .map(move |batch| {
+                if context.is_cancelled() {
+                    return Err(Error::Cancelled);
+                }
+                let batch = batch?;
+                if batch.schema() != &self.output {
+                    return Err(Error::Invalid(
+                        "connector returned a different Scan schema".into(),
+                    ));
+                }
+                if self.predicates.is_empty() {
+                    return Ok(batch);
+                }
+                let _workspace =
+                    context.reserve(batch.bytes().checked_mul(2).ok_or(Error::MemoryLimit)?)?;
+                let mut rows = Vec::new();
+                for row in batch.rows() {
+                    if context.is_cancelled() {
+                        return Err(Error::Cancelled);
+                    }
+                    let mut keep = true;
+                    for predicate in &self.predicates {
+                        match predicate.evaluate(row)? {
+                            Value::Bool(true) => {}
+                            Value::Bool(false) | Value::Null => {
+                                keep = false;
+                                break;
+                            }
+                            _ => {
+                                return Err(Error::Invalid("Scan predicate is not boolean".into()))
+                            }
+                        }
+                    }
+                    if keep {
+                        rows.push(row.clone());
+                    }
+                }
+                Batch::try_new(self.output.clone(), rows)
+            })
+            .boxed_local())
+    }
+}
+
+mod memory;
+pub use memory::MemorySource;
diff --git a/crates/asap-physical-operators/tests/unified_common/mod.rs b/crates/asap-physical-operators/tests/unified_common/mod.rs
new file mode 100644
index 000000000..35ba496b4
--- /dev/null
+++ b/crates/asap-physical-operators/tests/unified_common/mod.rs
@@ -0,0 +1,15 @@
+#![allow(dead_code)]
+use planner_types::ir::export::PhysicalASAPDAG;
+use planner_types::ir::{apply_lifecycle_timings, LifecycleAssignment, OperatorNode, TimingMemo};
+use std::rc::Rc;
+
+pub fn compile_physical_asap_dag(
+    root: &Rc<OperatorNode>,
+) -> Result<PhysicalASAPDAG, Box<dyn std::error::Error>> {
+    let root = apply_lifecycle_timings(
+        root,
+        &LifecycleAssignment::default(),
+        &mut TimingMemo::default(),
+    )?;
+    Ok(planner_types::ir::export::compile_physical_asap_dag(&root)?)
+}
diff --git a/crates/asap-physical-operators/tests/unified_promql_fallback.rs b/crates/asap-physical-operators/tests/unified_promql_fallback.rs
new file mode 100644
index 000000000..016c4f3a9
--- /dev/null
+++ b/crates/asap-physical-operators/tests/unified_promql_fallback.rs
@@ -0,0 +1,1611 @@
+//! A retained PromQL sub-DAG (`Fallback`) compiles from its typed expression.
+//! The deployment supplies only its selector's raw series; expected values are
+//! hand-computed with Prometheus semantics.
+#[path = "unified_common/mod.rs"]
+mod common;
+use asap_physical_operators::{
+    operators::Operator,
+    runtime::{Limits, RunContext, Scope},
+    unified_physical_planner::{
+        compile, promql_fallback, promql_rows, CompiledPhysicalDAG, InputContract,
+    },
+    values::{Batch, Value},
+};
+use common::compile_physical_asap_dag;
+use futures::{executor::block_on, StreamExt};
+use planner_types::ir::export::PhysicalASAPDAG;
+use planner_types::{
+    post_asap::execution_data_state::lift_plain, types::AccuracyTarget, workload::*,
+};
+use std::{collections::BTreeMap, rc::Rc};
+
+/// Bare selectors look back one ingestion interval: 60s.
+fn parse(query: &str) -> Rc<planner_types::ir::OperatorNode> {
+    parse_with(query, AccuracyTarget::Exact)
+}
+
+fn parse_with(query: &str, accuracy: AccuracyTarget) -> Rc<planner_types::ir::OperatorNode> {
+    match parse_root(query, accuracy) {
+        planner_types::ir::QueryRoot::Operator(node) => node,
+        _ => panic!("expected operator query"),
+    }
+}
+
+fn parse_root(query: &str, accuracy: AccuracyTarget) -> planner_types::ir::QueryRoot {
+    let workload = PlanningWorkload {
+        query_workload: QueryWorkload {
+            language: QueryLanguage::PromQL,
+            query_batch: Some(vec![BatchEntry {
+                query: Query(query.into()),
+                requirements: QueryRequirements {
+                    accuracy: AccuracyRequirement::Explicit(accuracy),
+                    ..Default::default()
+                },
+                predictability: Predictability::Unknown,
+                invocations: 1,
+                execute_at: None,
+                time_selection: TimeSelection::default(),
+            }]),
+            repeating_queries: None,
+        },
+        data_workload: Some(DataWorkload {
+            data_ingestion_interval: Evidence {
+                value: Some(DurationMs(60_000)),
+                ..Default::default()
+            },
+            ..Default::default()
+        }),
+    };
+    asap_frontend_promql::unified::lower_promql_query_workload(&workload, 0)
+        .unwrap()
+        .remove(0)
+}
+
+fn lower(query: &str) -> Rc<planner_types::ir::OperatorNode> {
+    promql_rows::with_series_identity(&parse(query)).unwrap()
+}
+
+/// The whole query retained as one pre-ASAP node.
+fn fallback_dag(expression: Rc<planner_types::ir::OperatorNode>) -> PhysicalASAPDAG {
+    compile_physical_asap_dag(&expression).unwrap()
+}
+
+/// `(labels, seconds, value)`. `labels` is `k=v,...`, or a bare `job` value.
+type Sample = (&'static str, i64, f64);
+
+fn labels(spec: &str) -> BTreeMap<String, String> {
+    if !spec.contains('=') {
+        return BTreeMap::from([("job".into(), spec.into())]);
+    }
+    spec.split(',')
+        .map(|pair| {
+            let (k, v) = pair.split_once('=').unwrap();
+            (k.to_string(), v.to_string())
+        })
+        .collect()
+}
+
+/// The metric a selector reads.
+fn metric(selector: &planner_types::ir::OperatorNode) -> String {
+    match selector.expect_non_asap() {
+        planner_types::ir::NonASAPOp::Scan {
+            source: planner_types::pre_asap::Source::TimeSeries { metric },
+            ..
+        } => metric.clone(),
+        planner_types::ir::NonASAPOp::TimeRange { child, .. }
+        | planner_types::ir::NonASAPOp::TimeShift { child, .. } => metric(child),
+        other => panic!("not a selector: {other:?}"),
+    }
+}
+
+fn compile_query(query: &str) -> Result<CompiledPhysicalDAG, String> {
+    let expression = lower(query);
+    compile_dag(&expression, &fallback_dag(expression.clone()))
+}
+
+/// Compile a DAG whose root is the Fallback computing `expression`.
+fn compile_dag(
+    expression: &planner_types::ir::OperatorNode,
+    dag: &PhysicalASAPDAG,
+) -> Result<CompiledPhysicalDAG, String> {
+    let root = u64::from(dag.root.0);
+    let inputs = promql_fallback::raw_series(expression)
+        .map_err(|e| e.to_string())?
+        .into_iter()
+        .enumerate()
+        .map(|(i, (_, schema))| {
+            (
+                promql_fallback::raw_series_input(root, i),
+                InputContract::bounded(schema),
+            )
+        })
+        .collect();
+    let program = compile(dag, inputs, &[root]).map_err(|e| e.to_string())?;
+    Ok(serde_json::from_slice(&serde_json::to_vec(&program).unwrap()).unwrap())
+}
+
+/// Evaluate at `at` seconds over samples of each named metric; returns
+/// `(output labels, timestamp ms, value)` rows in order.
+#[allow(clippy::type_complexity)]
+fn evaluate(
+    query: &str,
+    metrics: &[(&str, &[Sample])],
+    at: i64,
+) -> Result<Vec<(BTreeMap<String, String>, i64, f64)>, String> {
+    match parse_root(query, AccuracyTarget::Exact) {
+        planner_types::ir::QueryRoot::Operator(expression) => {
+            let expression =
+                promql_rows::with_series_identity(&expression).map_err(|e| e.to_string())?;
+            evaluate_dag(&expression, &fallback_dag(expression.clone()), metrics, at)
+        }
+        planner_types::ir::QueryRoot::Scalar(expr) => {
+            let expr = expr
+                .map_operator_refs(&mut |node| promql_rows::with_series_identity(node).unwrap());
+            let (program, selectors) =
+                promql_fallback::compile_scalar_root(&expr).map_err(|e| e.to_string())?;
+            execute_program(program, selectors, metrics, at, None)
+        }
+    }
+}
+
+#[allow(clippy::type_complexity)]
+fn evaluate_dag(
+    expression: &planner_types::ir::OperatorNode,
+    dag: &PhysicalASAPDAG,
+    metrics: &[(&str, &[Sample])],
+    at: i64,
+) -> Result<Vec<(BTreeMap<String, String>, i64, f64)>, String> {
+    evaluate_dag_with_range(expression, dag, metrics, at, None)
+}
+
+#[allow(clippy::type_complexity)]
+fn evaluate_dag_with_range(
+    expression: &planner_types::ir::OperatorNode,
+    dag: &PhysicalASAPDAG,
+    metrics: &[(&str, &[Sample])],
+    at: i64,
+    bounds: Option<(i64, i64)>,
+) -> Result<Vec<(BTreeMap<String, String>, i64, f64)>, String> {
+    let program = compile_dag(expression, dag)?;
+    let selectors = promql_fallback::raw_series(expression).unwrap();
+    execute_program(program, selectors, metrics, at, bounds)
+}
+
+#[allow(clippy::type_complexity)]
+fn execute_program(
+    program: CompiledPhysicalDAG,
+    selectors: Vec<promql_fallback::Selector>,
+    metrics: &[(&str, &[Sample])],
+    at: i64,
+    bounds: Option<(i64, i64)>,
+) -> Result<Vec<(BTreeMap<String, String>, i64, f64)>, String> {
+    let mut sources = BTreeMap::new();
+    for (i, (selector, schema)) in selectors.into_iter().enumerate() {
+        let name = metric(&selector);
+        let rows = metrics
+            .iter()
+            .filter(|(m, _)| *m == name)
+            .flat_map(|(_, samples)| samples.iter())
+            .map(|(spec, seconds, value)| {
+                let mut labels = labels(spec);
+                // A sample may supply its own `__name__`, as a series of another metric.
+                labels.entry("__name__".into()).or_insert(name.clone());
+                promql_rows::series_row(&schema, &labels, seconds * 1000, *value).unwrap()
+            })
+            .collect();
+        let batch = Batch::try_new(schema.clone(), rows).unwrap();
+        sources.insert(
+            promql_fallback::raw_series_input(program.roots()[0], i),
+            Box::new(Operator::source(schema, vec![batch]).unwrap()) as _,
+        );
+    }
+    let dag = program.instantiate(sources).map_err(|e| e.to_string())?;
+    let context = RunContext::new(
+        Scope::Query {
+            evaluation_time_ms: at * 1000,
+            revision: 0,
+        },
+        Limits::default(),
+    )
+    .unwrap();
+    let context = match bounds {
+        Some((start, end)) => context
+            .with_query_range(start * 1000, end * 1000)
+            .map_err(|e| e.to_string())?,
+        None => context,
+    };
+    block_on(async {
+        let mut stream = dag
+            .execute(program.roots(), context)
+            .map_err(|e| e.to_string())?
+            .remove(0);
+        let mut rows = Vec::new();
+        while let Some(batch) = stream.next().await {
+            let batch = batch.map_err(|e| e.to_string())?;
+            let schema = batch.schema().clone();
+            for row in batch.rows() {
+                let mut labels = BTreeMap::new();
+                let mut time = -1;
+                let mut value = None;
+                for (field, cell) in schema.fields.iter().zip(row) {
+                    match (field.name.as_str(), cell) {
+                        (promql_rows::SERIES_IDENTITY_COLUMN, Value::Utf8(id)) => {
+                            labels = promql_rows::decode_series_identity(id).unwrap()
+                        }
+                        (_, Value::Utf8(_) | Value::Null) => {}
+                        (_, Value::Timestamp(t)) => time = *t,
+                        (_, Value::Float64(v)) => value = Some(*v),
+                        (_, Value::Int64(v)) => value = Some(*v as f64),
+                        other => return Err(format!("unexpected cell {other:?}")),
+                    }
+                }
+                if !schema
+                    .fields
+                    .iter()
+                    .any(|f| f.name == promql_rows::SERIES_IDENTITY_COLUMN)
+                {
+                    for (field, cell) in schema.fields.iter().zip(row) {
+                        if let Value::Utf8(label) = cell {
+                            if !label.is_empty() {
+                                labels.insert(field.name.clone(), label.to_string());
+                            }
+                        }
+                    }
+                }
+                rows.push((labels, time, value.ok_or("missing value")?));
+            }
+        }
+        Ok(rows)
+    })
+}
+
+/// Evaluate at `at` seconds over metric `m`; returns `(job or "", timestamp ms, value)`.
+fn run(query: &str, samples: &[Sample], at: i64) -> Result<Vec<(String, i64, f64)>, String> {
+    Ok(evaluate(query, &[("m", samples)], at)?
+        .into_iter()
+        .map(|(labels, time, value)| (labels.get("job").cloned().unwrap_or_default(), time, value))
+        .collect())
+}
+
+/// Output rows as `(k=v,... sorted, value)`, including any `__name__`.
+fn labeled(query: &str, metrics: &[(&str, &[Sample])], at: i64) -> Vec<(String, f64)> {
+    let mut rows = evaluate(query, metrics, at)
+        .unwrap_or_else(|e| panic!("{query}: {e}"))
+        .into_iter()
+        .map(|(labels, _, value)| {
+            let spec = labels
+                .iter()
+                .map(|(k, v)| format!("{k}={v}"))
+                .collect::<Vec<_>>()
+                .join(",");
+            (spec, value)
+        })
+        .collect::<Vec<_>>();
+    rows.sort_by(|a, b| a.0.cmp(&b.0));
+    rows
+}
+
+fn values(query: &str, samples: &[Sample], at: i64) -> Vec<(String, f64)> {
+    run(query, samples, at)
+        .unwrap_or_else(|e| panic!("{query}: {e}"))
+        .into_iter()
+        .map(|(job, _, value)| (job, value))
+        .collect()
+}
+
+fn one(query: &str, samples: &[Sample], at: i64) -> f64 {
+    match values(query, samples, at).as_slice() {
+        [(_, value)] => *value,
+        other => panic!("{query}: expected one sample, got {other:?}"),
+    }
+}
+
+const COUNTER: &[Sample] = &[
+    ("a", 60, 10.),
+    ("a", 120, 20.),
+    ("a", 180, 5.),
+    ("a", 240, 15.),
+];
+
+// rate/increase correct the reset at 180s and extrapolate half an interval at
+// most; delta treats the same samples as a gauge.
+#[test]
+fn range_functions_follow_prometheus_extrapolation_and_resets() {
+    // Reset-corrected increase is 25 over 180s of samples; 60s on each side extrapolates.
+    let increase = 25. * (180. + 60. + 60.) / 180.;
+    assert!((one("increase(m[5m])", COUNTER, 300) - increase).abs() < 1e-9);
+    assert!((one("rate(m[5m])", COUNTER, 300) - increase / 300.).abs() < 1e-12);
+    let delta = 5. * (180. + 60. + 60.) / 180.;
+    assert!((one("delta(m[5m])", COUNTER, 300) - delta).abs() < 1e-9);
+    // Fewer than two samples yield no rate.
+    assert!(values("rate(m[2m])", COUNTER, 300).is_empty());
+    for (query, expected) in [
+        ("sum_over_time(m[5m])", 50.),
+        ("avg_over_time(m[5m])", 12.5),
+        ("min_over_time(m[5m])", 5.),
+        ("max_over_time(m[5m])", 20.),
+        ("count_over_time(m[5m])", 4.),
+    ] {
+        assert_eq!(one(query, COUNTER, 300), expected, "{query}");
+    }
+}
+
+// Ranges are left-open: a sample at `t - range` is excluded, one at `t` is included.
+#[test]
+fn ranges_exclude_their_start_and_offsets_shift_them() {
+    let samples = &[("a", 60, 1.), ("a", 90, 1.), ("a", 120, 1.), ("a", 150, 1.)];
+    assert_eq!(one("count_over_time(m[1m])", samples, 120), 2.);
+    // offset 1m reads (60s, 120s] at 180s; output keeps the evaluation time.
+    let rows = run("count_over_time(m[1m] offset 1m)", samples, 180).unwrap();
+    assert_eq!(rows, vec![("a".into(), 180_000, 2.)]);
+}
+
+// A bare selector takes the latest sample within the lookback; a stale marker
+// hides the series rather than exposing an older value.
+#[test]
+fn instant_selection_uses_lookback_and_stale_markers() {
+    let stale = f64::from_bits(0x7ff0_0000_0000_0002);
+    let samples = &[("a", 0, 1.), ("a", 30, 2.), ("b", 30, 3.), ("b", 50, stale)];
+    assert_eq!(values("m", samples, 60), vec![("a".into(), 2.)]);
+    // The lookback (30s, 90s] excludes the sample at 30s.
+    assert!(values("m", samples, 90).is_empty());
+    // Range functions skip stale markers.
+    assert_eq!(
+        values("sum_over_time(m[1m])", samples, 60),
+        vec![("a".into(), 2.), ("b".into(), 3.)]
+    );
+}
+
+// NaN samples follow Prometheus: min/max skip them, sums propagate them.
+#[test]
+fn nan_samples() {
+    let samples = &[("a", 10, f64::NAN), ("a", 20, 3.), ("a", 30, 1.)];
+    assert_eq!(one("max_over_time(m[1m])", samples, 60), 3.);
+    assert_eq!(one("min_over_time(m[1m])", samples, 60), 1.);
+    assert!(one("sum_over_time(m[1m])", samples, 60).is_nan());
+}
+
+// Aggregation over no series is an empty vector, not one zero or null row;
+// sort_desc orders the selected series.
+#[test]
+fn cross_series_aggregates_and_empty_inputs() {
+    let samples = &[("a", 50, 1.), ("b", 40, 2.), ("b", 55, 4.)];
+    assert_eq!(values("sum(m)", samples, 60), vec![(String::new(), 5.)]);
+    assert_eq!(values("count(m)", samples, 60), vec![(String::new(), 2.)]);
+    assert_eq!(
+        values("max by (job) (m)", samples, 60),
+        vec![("a".into(), 1.), ("b".into(), 4.)]
+    );
+    assert_eq!(
+        values("sort_desc(m)", samples, 60),
+        vec![("b".into(), 4.), ("a".into(), 1.)]
+    );
+    // topk by (job) keeps the top series of each job, not one overall.
+    let jobs = &[("a", 50, 1.), ("b", 50, 2.)];
+    let mut top = values("topk by (job) (1, m)", jobs, 60);
+    top.sort_by(|x, y| x.0.cmp(&y.0));
+    assert_eq!(top, vec![("a".into(), 1.), ("b".into(), 2.)]);
+    assert_eq!(values("topk(1, m)", jobs, 60), vec![("b".into(), 2.)]);
+    for query in ["sum(m)", "count(m)", "max(m)", "sum by (job) (rate(m[5m]))"] {
+        assert!(values(query, &[], 60).is_empty(), "{query}");
+    }
+}
+
+// scalar() is the single series' value and NaN otherwise; vector() needs no input.
+#[test]
+fn scalar_and_vector_bridges() {
+    assert_eq!(one("scalar(m)", &[("a", 50, 7.)], 60), 7.);
+    assert!(one("scalar(m)", &[("a", 50, 7.), ("b", 50, 8.)], 60).is_nan());
+    assert!(one("scalar(m)", &[], 60).is_nan());
+    assert_eq!(
+        run("vector(3)", &[], 60).unwrap(),
+        vec![(String::new(), 60_000, 3.)]
+    );
+    assert_eq!(
+        values("2 - m", &[("a", 50, 7.)], 60),
+        vec![("a".into(), -5.)]
+    );
+    assert_eq!(
+        values("m * 2", &[("a", 50, 7.)], 60),
+        vec![("a".into(), 14.)]
+    );
+}
+
+// Subquery steps are absolute multiples of the resolution in the left-open
+// range; each step evaluates the operand, and the outer function reduces them.
+#[test]
+fn subqueries_evaluate_their_operand_on_the_aligned_grid() {
+    // Steps 60..300: selections 1, 7, 3, (none at 240s), 4.
+    let samples = &[
+        ("a", 50, 1.),
+        ("a", 110, 7.),
+        ("a", 170, 3.),
+        ("a", 290, 4.),
+    ];
+    assert_eq!(one("max_over_time(m[5m:1m])", samples, 300), 7.);
+    assert_eq!(one("count_over_time(m[5m:1m])", samples, 300), 4.);
+    // At 190s the steps are 60, 120, 180 (not 70, 130, 190): counts 1 + 2 + 2.
+    let samples = &[("a", 30, 1.), ("a", 90, 1.), ("a", 150, 1.), ("a", 185, 1.)];
+    assert_eq!(
+        one("sum_over_time(count_over_time(m[2m])[3m:1m])", samples, 190),
+        5.
+    );
+    // offset 1m moves the grid to (-50s, 130s]: steps 0, 60, 120 count 0 + 1 + 2.
+    assert_eq!(
+        one(
+            "sum_over_time(count_over_time(m[2m])[3m:1m] offset 1m)",
+            samples,
+            190
+        ),
+        3.
+    );
+}
+
+// Subquery work is bounded by the query: at most 100000 steps.
+#[test]
+fn dense_subquery_grids_are_rejected() {
+    assert!(compile_query("max_over_time(m[100s:1ms])").is_ok());
+    assert!(compile_query("max_over_time(m[30d:1ms])").is_err());
+}
+
+// The deployment must supply the selector's raw rows under the documented slot
+// with the exact selector schema; unsupported shapes stay rejected.
+#[test]
+fn raw_series_contract_is_explicit() {
+    let expression = lower("rate(m[5m])");
+    let dag = fallback_dag(expression.clone());
+    let root = u64::from(dag.root.0);
+    let [(selector, schema)] = promql_fallback::raw_series(&expression)
+        .unwrap()
+        .try_into()
+        .unwrap();
+    assert!(matches!(
+        selector.expect_non_asap(),
+        planner_types::ir::NonASAPOp::TimeRange { .. }
+    ));
+    let missing = compile(&dag, BTreeMap::new(), &[root]).err().unwrap();
+    assert!(missing.to_string().contains("raw series input"));
+    let mut wrong = (*schema).clone();
+    wrong.fields.pop();
+    let wrong = compile(
+        &dag,
+        BTreeMap::from([(
+            promql_fallback::raw_series_input(root, 0),
+            InputContract::bounded(std::sync::Arc::new(wrong)),
+        )]),
+        &[root],
+    );
+    assert!(wrong.is_err());
+    // A consumed bare selector is raw range rows for its consumer; it is not
+    // turned into instant selection.
+    let selector = lower("m");
+    let _schema = lift_plain(&selector.schema.clone());
+    let consumed = planner_types::ir::OperatorNode::new_shared(
+        planner_types::ir::Operator::NonASAP(planner_types::ir::NonASAPOp::Limit {
+            n: Some(1),
+            offset: 0,
+            partition_by: Default::default(),
+            child: selector.clone(),
+        }),
+    )
+    .unwrap();
+    let consumed = fallback_dag(consumed.clone());
+    let raw = promql_fallback::raw_series(&selector).unwrap().remove(0).1;
+    assert!(compile(
+        &consumed,
+        BTreeMap::from([(
+            promql_fallback::raw_series_input(u64::from(consumed.root.0), 0),
+            InputContract::bounded(raw)
+        )]),
+        &[u64::from(consumed.root.0)]
+    )
+    .is_ok());
+    // Implicit subquery resolution belongs to the deployment's evaluation interval.
+    assert!(compile_query("max_over_time(m[5m:])").is_err());
+}
+
+// irate/idelta use the last two samples (irate corrects a reset to the last
+// value); changes/resets count value changes and decreases; quantile_over_time
+// interpolates; all skip stale markers.
+#[test]
+fn instant_and_counting_range_functions() {
+    // COUNTER in (0s, 300s]: 10, 20, 5, 15.
+    assert!((one("irate(m[5m])", COUNTER, 300) - 10. / 60.).abs() < 1e-12);
+    assert_eq!(one("idelta(m[5m])", COUNTER, 300), 10.);
+    // At 200s the last pair 20 -> 5 is a reset: irate uses 5 as the increase.
+    assert!((one("irate(m[5m])", COUNTER, 200) - 5. / 60.).abs() < 1e-12);
+    assert_eq!(one("idelta(m[5m])", COUNTER, 200), -15.);
+    assert!(values("irate(m[1m])", COUNTER, 300).is_empty());
+    assert_eq!(one("changes(m[5m])", COUNTER, 300), 3.);
+    assert_eq!(one("resets(m[5m])", COUNTER, 300), 1.);
+    assert_eq!(one("changes(m[2m])", COUNTER, 300), 0.);
+    // NaN to NaN is not a change; any other transition involving NaN is.
+    let flat = &[
+        ("a", 10, 1.),
+        ("a", 20, 1.),
+        ("a", 30, 2.),
+        ("a", 40, f64::NAN),
+        ("a", 50, f64::NAN),
+        ("a", 55, 1.),
+    ];
+    assert_eq!(one("changes(m[1m])", flat, 60), 3.);
+    let stale = f64::from_bits(0x7ff0_0000_0000_0002);
+    let ended = &[("a", 240, 15.), ("a", 250, stale)];
+    assert_eq!(one("last_over_time(m[5m])", ended, 300), 15.);
+    assert!(values("m", ended, 300).is_empty());
+    // Sorted 5, 10, 15, 20: rank 1.5 and 0.75; outside [0, 1] is +-Inf.
+    assert_eq!(one("quantile_over_time(0.5, m[5m])", COUNTER, 300), 12.5);
+    assert_eq!(one("quantile_over_time(0.25, m[5m])", COUNTER, 300), 8.75);
+    assert_eq!(
+        one("quantile_over_time(2, m[5m])", COUNTER, 300),
+        f64::INFINITY
+    );
+    assert_eq!(
+        one("quantile_over_time(-1, m[5m])", COUNTER, 300),
+        f64::NEG_INFINITY
+    );
+}
+
+// `@ <t>` evaluates the selector or subquery at `t`, minus any offset, and the
+// result keeps the query's evaluation time.
+#[test]
+fn at_modifier_fixes_the_evaluation_instant() {
+    let samples = &[("a", 60, 1.), ("a", 120, 2.), ("a", 180, 3.)];
+    assert_eq!(
+        run("m @ 120", samples, 1000).unwrap(),
+        vec![("a".into(), 1_000_000, 2.)]
+    );
+    assert!(values("m", samples, 1000).is_empty());
+    assert_eq!(one("count_over_time(m[2m] @ 180)", samples, 1000), 2.);
+    assert_eq!(one("m @ 180 offset 1m", samples, 1000), 2.);
+    // The subquery grid is (60s, 180s]: steps 120 and 180 select 2 and 3.
+    assert_eq!(one("max_over_time(m[2m:1m] @ 180)", samples, 1000), 3.);
+    assert_eq!(
+        one("sum_over_time(m[2m:1m] @ 180 offset 1m)", samples, 1000),
+        3.
+    );
+    // An inner @ pins every step to the same instant.
+    assert_eq!(one("sum_over_time((m @ 60)[2m:1m])", samples, 180), 2.);
+    // start() and end() depend on the range query, which is the deployment's.
+    assert!(evaluate("m @ start()", &[], 60)
+        .unwrap_err()
+        .contains("query range bounds"));
+}
+
+const A: &[Sample] = &[("job=x", 50, 10.), ("job=y", 50, 20.), ("job=w", 50, 0.)];
+const B: &[Sample] = &[("job=x", 50, 2.), ("job=z", 50, 5.), ("job=w", 50, 0.)];
+
+// Vector-vector arithmetic matches series one-to-one on label sets without
+// the metric name, and the result drops the metric name.
+#[test]
+fn vector_arithmetic_matches_label_sets() {
+    let metrics = &[("a", A), ("b", B)];
+    let quotient = labeled("a / b", metrics, 60);
+    assert_eq!(quotient.len(), 2);
+    assert_eq!(quotient[0].0, "job=w");
+    assert!(quotient[0].1.is_nan(), "0 / 0 is NaN");
+    assert_eq!(quotient[1], ("job=x".into(), 5.));
+    // Each selector reads its own raw rows, even a repeated metric.
+    assert_eq!(
+        labeled("(a - b) * a", metrics, 60),
+        vec![("job=w".into(), 0.), ("job=x".into(), 80.)]
+    );
+    assert_eq!(
+        labeled("sum by (job) (a) - sum by (job) (b)", metrics, 60),
+        vec![("job=w".into(), 0.), ("job=x".into(), 8.)]
+    );
+    // Rates of two counters over their own windows.
+    let up: &[Sample] = &[("job=x", 0, 0.), ("job=x", 60, 60.)];
+    let down: &[Sample] = &[("job=x", 0, 0.), ("job=x", 60, 30.)];
+    assert_eq!(
+        labeled("rate(a[2m]) / rate(b[2m])", &[("a", up), ("b", down)], 60),
+        vec![("job=x".into(), 2.)]
+    );
+}
+
+// on() keeps only the listed labels and ignoring() drops them; a duplicate
+// match group is an error unless the left duplicates never match.
+#[test]
+fn on_and_ignoring_select_the_matching_labels() {
+    let a: &[Sample] = &[("job=x,inst=1", 50, 10.)];
+    let b: &[Sample] = &[("job=x,inst=2", 50, 4.)];
+    let metrics = &[("a", a), ("b", b)];
+    assert!(labeled("a - b", metrics, 60).is_empty());
+    assert_eq!(
+        labeled("a - on(job) b", metrics, 60),
+        vec![("job=x".into(), 6.)]
+    );
+    assert_eq!(
+        labeled("a - ignoring(inst) b", metrics, 60),
+        vec![("job=x".into(), 6.)]
+    );
+    let pair: &[Sample] = &[("job=x,inst=1", 50, 1.), ("job=x,inst=2", 50, 2.)];
+    let other: &[Sample] = &[("job=y", 50, 1.)];
+    assert!(evaluate("a + on(job) b", &[("a", a), ("b", pair)], 60).is_err());
+    assert!(evaluate("a + on(job) b", &[("a", pair), ("b", b)], 60).is_err());
+    assert!(labeled("a + on(job) b", &[("a", pair), ("b", other)], 60).is_empty());
+}
+
+// without() groups by every label except the listed ones and the metric name.
+#[test]
+fn without_grouping_drops_labels_and_the_name() {
+    let a: &[Sample] = &[
+        ("job=x,inst=1", 50, 1.),
+        ("job=x,inst=2", 50, 2.),
+        ("job=y,inst=1", 50, 4.),
+    ];
+    let metrics = &[("a", a)];
+    assert_eq!(
+        labeled("sum without (inst) (a)", metrics, 60),
+        vec![("job=x".into(), 3.), ("job=y".into(), 4.)]
+    );
+    assert_eq!(
+        labeled("count without (inst) (a)", metrics, 60),
+        vec![("job=x".into(), 2.), ("job=y".into(), 1.)]
+    );
+    assert_eq!(
+        labeled("max without (job, inst) (a)", metrics, 60),
+        vec![(String::new(), 4.)]
+    );
+    assert!(labeled("sum without (inst) (a)", &[], 60).is_empty());
+    // Series equal without the name share a group rather than colliding.
+    let named: &[Sample] = &[
+        ("job=x,inst=1", 50, 1.),
+        ("__name__=b,job=x,inst=1", 50, 2.),
+    ];
+    assert_eq!(
+        labeled("sum without (inst) (a)", &[("a", named)], 60),
+        vec![("job=x".into(), 3.)]
+    );
+}
+
+// Arithmetic with a literal drops the metric name; series that then share a
+// label set are an error, as in Prometheus.
+#[test]
+fn literal_arithmetic_drops_the_name_and_rejects_equal_label_sets() {
+    let a: &[Sample] = &[
+        ("job=x,inst=1", 50, 1.),
+        ("__name__=b,job=x,inst=2", 50, 2.),
+    ];
+    assert_eq!(
+        labeled("a * 2", &[("a", a)], 60),
+        vec![("inst=1,job=x".into(), 2.), ("inst=2,job=x".into(), 4.)]
+    );
+    let equal: &[Sample] = &[("job=x", 50, 1.), ("__name__=b,job=x", 50, 2.)];
+    let error = evaluate("a * 2", &[("a", equal)], 60).unwrap_err();
+    assert!(error.contains("same labelset"), "{error}");
+}
+
+// An empty label value is an absent label, and an empty side yields an empty
+// result before any duplicate check, as in Prometheus.
+#[test]
+fn empty_labels_and_empty_sides_match_prometheus() {
+    let a: &[Sample] = &[("job=x,env=", 50, 3.)];
+    let b: &[Sample] = &[("job=x", 50, 1.)];
+    assert_eq!(
+        labeled("a + b", &[("a", a), ("b", b)], 60),
+        vec![("job=x".into(), 4.)]
+    );
+    let pair: &[Sample] = &[("job=x,inst=1", 50, 1.), ("job=x,inst=2", 50, 2.)];
+    assert!(labeled("a + on(job) b", &[("b", pair)], 60).is_empty());
+    assert!(labeled("b + on(job) a", &[("b", pair)], 60).is_empty());
+    assert!(labeled("a - time()", &[], 60).is_empty());
+}
+
+// Sums and averages use Prometheus' Kahan-Neumaier compensation, and an
+// average whose running sum overflows switches to an incremental mean.
+#[test]
+fn sums_and_averages_are_compensated_like_prometheus() {
+    let cancel = &[("a", 10, 1e100), ("a", 20, 1.), ("a", 30, -1e100)];
+    assert_eq!(one("sum_over_time(m[1m])", cancel, 60), 1.);
+    assert_eq!(one("avg_over_time(m[1m])", cancel, 60), 1. / 3.);
+    let huge = &[("a", 10, 1.7e308), ("a", 20, 1.7e308)];
+    assert_eq!(one("avg_over_time(m[1m])", huge, 60), 1.7e308);
+    assert_eq!(one("sum_over_time(m[1m])", huge, 60), f64::INFINITY);
+    let infinite = &[("a", 10, f64::INFINITY), ("a", 20, 1.)];
+    assert_eq!(one("sum_over_time(m[1m])", infinite, 60), f64::INFINITY);
+    assert_eq!(one("avg_over_time(m[1m])", infinite, 60), f64::INFINITY);
+    let opposite = &[("a", 10, f64::INFINITY), ("a", 20, f64::NEG_INFINITY)];
+    assert!(one("sum_over_time(m[1m])", opposite, 60).is_nan());
+    assert!(one("avg_over_time(m[1m])", opposite, 60).is_nan());
+    let cancel = &[("a", 50, 1e100), ("b", 50, 1.), ("c", 50, -1e100)];
+    assert_eq!(one("sum(m)", cancel, 60), 1.);
+    assert_eq!(one("avg(m)", cancel, 60), 1. / 3.);
+    let huge = &[("a", 50, 1.7e308), ("b", 50, 1.7e308)];
+    assert_eq!(one("avg(m)", huge, 60), 1.7e308);
+}
+
+/// `(k=v,... sorted, value)` rows for readable expectations.
+fn rows(pairs: &[(&str, f64)]) -> Vec<(String, f64)> {
+    let mut rows = pairs
+        .iter()
+        .map(|(spec, value)| (spec.to_string(), *value))
+        .collect::<Vec<_>>();
+    rows.sort_by(|a, b| a.0.cmp(&b.0));
+    rows
+}
+
+/// `labeled`, with NaN values rendered comparable.
+fn labeled_nan(query: &str, metrics: &[(&str, &[Sample])], at: i64) -> Vec<(String, String)> {
+    labeled(query, metrics, at)
+        .into_iter()
+        .map(|(labels, value)| (labels, format!("{value:?}")))
+        .collect()
+}
+
+const C: &[Sample] = &[
+    ("job=x", 50, 10.),
+    ("job=y", 50, 20.),
+    ("job=w", 50, 0.),
+    ("job=n", 50, f64::NAN),
+];
+
+// A comparison with a scalar keeps the matching series with their value and
+// metric name, whichever side the scalar is on; `bool` yields 1 or 0 for every
+// series and drops the name. NaN compares unequal to everything.
+#[test]
+fn scalar_comparisons_filter_or_return_bool() {
+    let metrics = &[("a", C)];
+    let kept = rows(&[("__name__=a,job=x", 10.), ("__name__=a,job=y", 20.)]);
+    assert_eq!(labeled("a > 5", metrics, 60), kept);
+    assert_eq!(labeled("5 < a", metrics, 60), kept);
+    assert_eq!(
+        labeled("a <= 10", metrics, 60),
+        rows(&[("__name__=a,job=w", 0.), ("__name__=a,job=x", 10.)])
+    );
+    assert_eq!(
+        labeled("a > bool 5", metrics, 60),
+        rows(&[("job=n", 0.), ("job=w", 0.), ("job=x", 1.), ("job=y", 1.)])
+    );
+    assert_eq!(
+        labeled("10 == bool a", metrics, 60),
+        rows(&[("job=n", 0.), ("job=w", 0.), ("job=x", 1.), ("job=y", 0.)])
+    );
+    // scalar() of no series is NaN.
+    assert_eq!(labeled("a != scalar(b)", metrics, 60).len(), 4);
+    assert!(labeled("a == scalar(b)", metrics, 60).is_empty());
+    assert!(labeled("a > 5", &[], 60).is_empty());
+    // Only `bool` drops the name, so only it can make label sets collide.
+    let equal: &[Sample] = &[("job=x", 50, 1.), ("__name__=b,job=x", 50, 2.)];
+    assert_eq!(labeled("a > 0", &[("a", equal)], 60).len(), 2);
+    let error = evaluate("a > bool 0", &[("a", equal)], 60).unwrap_err();
+    assert!(error.contains("same labelset"), "{error}");
+}
+
+// Vector comparisons match one-to-one like arithmetic. A filter keeps the
+// left series, name included, unless `on` reduces its labels; `bool` drops the
+// name. A left duplicate is an error only if more than one of it is kept.
+#[test]
+fn vector_comparisons_match_one_to_one() {
+    let metrics = &[("a", A), ("b", B)];
+    assert_eq!(
+        labeled("a > b", metrics, 60),
+        rows(&[("__name__=a,job=x", 10.)])
+    );
+    assert_eq!(
+        labeled("a >= b", metrics, 60),
+        rows(&[("__name__=a,job=w", 0.), ("__name__=a,job=x", 10.)])
+    );
+    assert_eq!(
+        labeled("a > bool b", metrics, 60),
+        rows(&[("job=w", 0.), ("job=x", 1.)])
+    );
+    assert!(labeled("a < b", metrics, 60).is_empty());
+    let a: &[Sample] = &[("job=x,inst=1", 50, 10.)];
+    let b: &[Sample] = &[("job=x,inst=2", 50, 4.)];
+    let metrics = &[("a", a), ("b", b)];
+    assert_eq!(
+        labeled("a > on(job) b", metrics, 60),
+        rows(&[("job=x", 10.)])
+    );
+    assert_eq!(
+        labeled("a > ignoring(inst) b", metrics, 60),
+        rows(&[("__name__=a,job=x", 10.)])
+    );
+    let pair: &[Sample] = &[("job=x,inst=1", 50, 1.), ("job=x,inst=2", 50, 5.)];
+    let metrics = &[("a", pair), ("b", b)];
+    assert_eq!(
+        labeled("a > on(job) b", metrics, 60),
+        rows(&[("job=x", 5.)])
+    );
+    let error = evaluate("a > bool on(job) b", metrics, 60).unwrap_err();
+    assert!(error.contains("many-to-one"), "{error}");
+    let nan: &[Sample] = &[("job=x", 50, f64::NAN)];
+    let metrics = &[("a", nan), ("b", nan)];
+    assert_eq!(labeled("a == bool b", metrics, 60), rows(&[("job=x", 0.)]));
+    assert_eq!(
+        labeled_nan("a != b", metrics, 60),
+        vec![("__name__=a,job=x".into(), "NaN".into())]
+    );
+}
+
+const S: &[Sample] = &[
+    ("job=x", 50, 1.),
+    ("job=y", 50, 2.),
+    ("job=z,inst=1", 50, 3.),
+];
+const T: &[Sample] = &[
+    ("job=x", 50, 10.),
+    ("job=w", 50, 20.),
+    ("job=z,inst=2", 50, 30.),
+];
+
+// Set operators match label sets many-to-many, ignoring the name by default,
+// and return the original series unchanged.
+#[test]
+fn set_operators_match_label_sets() {
+    let metrics = &[("a", S), ("b", T)];
+    assert_eq!(
+        labeled("a and b", metrics, 60),
+        rows(&[("__name__=a,job=x", 1.)])
+    );
+    assert_eq!(
+        labeled("a and on(job) b", metrics, 60),
+        rows(&[("__name__=a,job=x", 1.), ("__name__=a,inst=1,job=z", 3.)])
+    );
+    assert_eq!(
+        labeled("a and ignoring(inst) b", metrics, 60),
+        labeled("a and on(job) b", metrics, 60)
+    );
+    assert_eq!(
+        labeled("a or b", metrics, 60),
+        rows(&[
+            ("__name__=a,job=x", 1.),
+            ("__name__=a,job=y", 2.),
+            ("__name__=a,inst=1,job=z", 3.),
+            ("__name__=b,job=w", 20.),
+            ("__name__=b,inst=2,job=z", 30.),
+        ])
+    );
+    assert_eq!(
+        labeled("a or on(job) b", metrics, 60),
+        rows(&[
+            ("__name__=a,job=x", 1.),
+            ("__name__=a,job=y", 2.),
+            ("__name__=a,inst=1,job=z", 3.),
+            ("__name__=b,job=w", 20.),
+        ])
+    );
+    assert_eq!(
+        labeled("a unless b", metrics, 60),
+        rows(&[("__name__=a,job=y", 2.), ("__name__=a,inst=1,job=z", 3.)])
+    );
+    assert_eq!(
+        labeled("a unless on(job) b", metrics, 60),
+        rows(&[("__name__=a,job=y", 2.)])
+    );
+    assert_eq!(labeled("a and on() b", metrics, 60).len(), 3);
+    // Empty sides, and duplicates on either side, which set operators allow.
+    let a_only = &[("a", S)];
+    assert!(labeled("a and b", a_only, 60).is_empty());
+    assert_eq!(labeled("a unless b", a_only, 60).len(), 3);
+    assert_eq!(labeled("b or a", a_only, 60).len(), 3);
+    let pair: &[Sample] = &[("job=x,inst=1", 50, 1.), ("job=x,inst=2", 50, f64::NAN)];
+    assert_eq!(
+        labeled_nan("a and on(job) b", &[("a", pair), ("b", pair)], 60),
+        vec![
+            ("__name__=a,inst=1,job=x".into(), "1.0".into()),
+            ("__name__=a,inst=2,job=x".into(), "NaN".into()),
+        ]
+    );
+}
+
+const MANY: &[Sample] = &[
+    ("job=x,inst=1", 50, 2.),
+    ("job=x,inst=2", 50, 3.),
+    ("job=y,inst=1", 50, 4.),
+];
+const ONE: &[Sample] = &[("job=x,team=t1", 50, 10.), ("job=y", 50, 100.)];
+
+// group_left/group_right match many series to one; the result keeps the many
+// side's labels plus the listed labels of the one side, which a missing label
+// removes. A filter keeps the left value.
+#[test]
+fn group_modifiers_match_many_to_one() {
+    let metrics = &[("a", MANY), ("info", ONE)];
+    assert_eq!(
+        labeled("a * on(job) group_left(team) info", metrics, 60),
+        rows(&[
+            ("inst=1,job=x,team=t1", 20.),
+            ("inst=2,job=x,team=t1", 30.),
+            ("inst=1,job=y", 400.),
+        ])
+    );
+    assert_eq!(
+        labeled("info - on(job) group_right a", metrics, 60),
+        rows(&[
+            ("inst=1,job=x", 8.),
+            ("inst=2,job=x", 7.),
+            ("inst=1,job=y", 96.)
+        ])
+    );
+    assert_eq!(
+        labeled("info > on(job) group_right a", metrics, 60),
+        rows(&[
+            ("__name__=a,inst=1,job=x", 10.),
+            ("__name__=a,inst=2,job=x", 10.),
+            ("__name__=a,inst=1,job=y", 100.),
+        ])
+    );
+    assert_eq!(
+        labeled("a > bool ignoring(inst, team) group_left info", metrics, 60),
+        rows(&[
+            ("inst=1,job=x", 0.),
+            ("inst=2,job=x", 0.),
+            ("inst=1,job=y", 0.)
+        ])
+    );
+    // Two "one" series for a match group, or two results with equal labels.
+    let two: &[Sample] = &[("job=x,team=t1", 50, 1.), ("job=x,team=t2", 50, 2.)];
+    let error = evaluate(
+        "a * on(job) group_left info",
+        &[("a", MANY), ("info", two)],
+        60,
+    )
+    .unwrap_err();
+    assert!(error.contains("duplicate series"), "{error}");
+    let error = evaluate(
+        "info * on(job) group_right a",
+        &[("a", two), ("info", MANY)],
+        60,
+    )
+    .unwrap_err();
+    assert!(error.contains("left hand-side"), "{error}");
+    let named: &[Sample] = &[("job=x", 50, 1.), ("__name__=c,job=x", 50, 2.)];
+    let error = evaluate(
+        "a * on(job) group_left info",
+        &[("a", named), ("info", ONE)],
+        60,
+    )
+    .unwrap_err();
+    assert!(error.contains("unique matches"), "{error}");
+    assert!(labeled("a * on(job) group_left info", &[("a", MANY)], 60).is_empty());
+}
+
+// A non-literal scalar applies like a literal; scalar-scalar arithmetic yields
+// a scalar; and a literal applies to aggregated rows whose value has another name.
+#[test]
+fn scalar_operands_and_aggregates() {
+    let three: &[Sample] = &[("job=b", 50, 3.)];
+    let metrics = &[("a", A), ("b", three)];
+    assert_eq!(
+        labeled("a * scalar(b)", metrics, 60),
+        rows(&[("job=w", 0.), ("job=x", 30.), ("job=y", 60.)])
+    );
+    assert_eq!(
+        labeled("a > scalar(b)", metrics, 60),
+        rows(&[("__name__=a,job=x", 10.), ("__name__=a,job=y", 20.)])
+    );
+    assert_eq!(labeled("scalar(b) * 2", metrics, 60), rows(&[("", 6.)]));
+    assert_eq!(
+        labeled("scalar(b) > bool 2", metrics, 60),
+        rows(&[("", 1.)])
+    );
+    // scalar() of several series is NaN.
+    assert!(labeled("scalar(a) - 1", metrics, 60)[0].1.is_nan());
+    assert_eq!(
+        labeled("sum by (job) (a) * 2", metrics, 60),
+        rows(&[("job=w", 0.), ("job=x", 20.), ("job=y", 40.)])
+    );
+    assert_eq!(
+        labeled("sum by (job) (a) > bool 5", metrics, 60),
+        rows(&[("job=w", 0.), ("job=x", 1.), ("job=y", 1.)])
+    );
+}
+
+// Range functions other than last_over_time drop the metric name, so series
+// that then share a label set are an error, as in Prometheus.
+#[test]
+fn range_functions_drop_the_name_and_reject_equal_label_sets() {
+    let equal: &[Sample] = &[
+        ("job=x", 10, 1.),
+        ("job=x", 50, 2.),
+        ("__name__=b,job=x", 10, 1.),
+        ("__name__=b,job=x", 50, 4.),
+    ];
+    let error = evaluate("rate(a[1m])", &[("a", equal)], 60).unwrap_err();
+    assert!(error.contains("same labelset"), "{error}");
+    assert_eq!(
+        labeled("last_over_time(a[1m])", &[("a", equal)], 60),
+        rows(&[("__name__=a,job=x", 2.), ("__name__=b,job=x", 4.)])
+    );
+    assert_eq!(
+        labeled("max_over_time(a[1m])", &[("a", &equal[..2])], 60),
+        rows(&[("job=x", 2.)])
+    );
+}
+
+// Scalar-valued expressions are scalars too; `or vector(0)` fills an empty
+// aggregate; a range function inside a subquery drops the name.
+#[test]
+fn scalar_expressions_or_vector_and_subquery_names() {
+    let three: &[Sample] = &[("job=b", 50, 3.)];
+    let metrics = &[("a", A), ("b", three)];
+    assert_eq!(
+        labeled("a + (scalar(b) * 2)", metrics, 60),
+        rows(&[("job=w", 6.), ("job=x", 16.), ("job=y", 26.)])
+    );
+    assert_eq!(
+        labeled("a + -scalar(b)", metrics, 60),
+        rows(&[("job=w", -3.), ("job=x", 7.), ("job=y", 17.)])
+    );
+    assert_eq!(
+        labeled("sum(a) or vector(0)", metrics, 60),
+        rows(&[("", 30.)])
+    );
+    assert_eq!(labeled("sum(a) or vector(0)", &[], 60), rows(&[("", 0.)]));
+    let counter: &[Sample] = &[("job=x", 0, 0.), ("job=x", 30, 3.), ("job=x", 60, 6.)];
+    let result = labeled("last_over_time(rate(a[1m])[2m:1m])", &[("a", counter)], 60);
+    assert_eq!(result.len(), 1);
+    assert_eq!(result[0].0, "job=x");
+}
+
+/// Instant `x_bucket` samples at 50s: `(labels without le, [(le, count)])`.
+fn buckets(series: &[(&'static str, &[(&'static str, f64)])]) -> Vec<Sample> {
+    series
+        .iter()
+        .flat_map(|(labels, buckets)| {
+            buckets.iter().map(move |(le, count)| {
+                let spec = if labels.is_empty() {
+                    format!("le={le}")
+                } else {
+                    format!("{labels},le={le}")
+                };
+                (&*Box::leak(spec.into_boxed_str()), 50, *count)
+            })
+        })
+        .collect()
+}
+
+fn quantile(query: &str, samples: &[Sample]) -> Vec<(String, f64)> {
+    labeled(query, &[("x_bucket", samples)], 60)
+}
+
+const HISTOGRAM: &[(&str, f64)] = &[("1", 2.), ("2", 6.), ("4", 8.), ("+Inf", 10.)];
+
+// histogram_quantile interpolates linearly within the bucket holding rank q·count,
+// returns the highest finite bound for the +Inf bucket, and maps q outside
+// [0, 1] to ∓Inf and a NaN q to NaN. Output labels drop le and __name__.
+#[test]
+fn histogram_quantile_interpolates_classic_buckets() {
+    let samples = buckets(&[("job=a", HISTOGRAM)]);
+    for (q, expected) in [
+        ("0", 0.),
+        ("0.1", 0.5),
+        ("0.5", 1.75),
+        ("0.9", 4.),
+        ("1", 4.),
+        ("-0.5", f64::NEG_INFINITY),
+        ("1.5", f64::INFINITY),
+    ] {
+        let query = format!("histogram_quantile({q}, x_bucket)");
+        assert_eq!(
+            quantile(&query, &samples),
+            vec![("job=a".into(), expected)],
+            "{query}"
+        );
+    }
+    let nan = quantile("histogram_quantile(NaN, x_bucket)", &samples);
+    assert!(matches!(nan.as_slice(), [(labels, v)] if labels == "job=a" && v.is_nan()));
+}
+
+// Each label set other than le is its own histogram. Degenerate histograms
+// yield NaN: no +Inf bucket, fewer than two buckets, or zero observations.
+#[test]
+fn histogram_quantile_groups_series_and_rejects_degenerate_histograms() {
+    let samples = buckets(&[
+        ("job=a", HISTOGRAM),
+        ("job=b", &[("1", 1.), ("2", 2.)]),
+        ("job=c", &[("+Inf", 5.)]),
+        ("job=d", &[("1", 0.), ("+Inf", 0.)]),
+        ("job=e,inst=1", HISTOGRAM),
+    ]);
+    let rows = quantile("histogram_quantile(0.5, x_bucket)", &samples);
+    let labels: Vec<_> = rows.iter().map(|(l, _)| l.as_str()).collect();
+    assert_eq!(
+        labels,
+        vec!["inst=1,job=e", "job=a", "job=b", "job=c", "job=d"]
+    );
+    assert_eq!(rows[0].1, 1.75);
+    assert_eq!(rows[1].1, 1.75);
+    assert!(rows[2..].iter().all(|(_, v)| v.is_nan()), "{rows:?}");
+}
+
+// Buckets sort by bound, unparsable or missing le values are skipped, equal
+// bounds merge, and decreasing cumulative counts are raised to be monotonic.
+#[test]
+fn histogram_quantile_normalizes_buckets_like_prometheus() {
+    let unordered = buckets(&[("job=a", &[("+Inf", 10.), ("4", 8.), ("1", 2.), ("2", 6.)])]);
+    assert_eq!(
+        quantile("histogram_quantile(0.5, x_bucket)", &unordered),
+        vec![("job=a".into(), 1.75)]
+    );
+    let mut invalid = buckets(&[("job=a", &[("abc", 100.), ("1", 2.), ("+Inf", 4.)])]);
+    invalid.push(("job=a", 50, 100.));
+    assert_eq!(
+        quantile("histogram_quantile(0.5, x_bucket)", &invalid),
+        vec![("job=a".into(), 1.)]
+    );
+    // Go's ParseFloat rejects an out-of-range bound rather than rounding it to +Inf.
+    let overflow = buckets(&[("job=a", &[("1", 1.), ("1e400", 2.)])]);
+    let rows = quantile("histogram_quantile(0.5, x_bucket)", &overflow);
+    assert!(
+        matches!(rows.as_slice(), [(_, v)] if v.is_nan()),
+        "{rows:?}"
+    );
+    let duplicate = buckets(&[("job=a", &[("1", 1.), ("1.0", 1.), ("+Inf", 4.)])]);
+    assert_eq!(
+        quantile("histogram_quantile(0.5, x_bucket)", &duplicate),
+        vec![("job=a".into(), 1.)]
+    );
+    // Counts [6, 2→6, 8, 8]: rank 7 lies in (2, 4], 1 of its 2 observations in.
+    let decreasing = buckets(&[("job=a", &[("1", 6.), ("2", 2.), ("4", 8.), ("+Inf", 8.)])]);
+    assert_eq!(
+        quantile("histogram_quantile(0.875, x_bucket)", &decreasing),
+        vec![("job=a".into(), 3.)]
+    );
+}
+
+// A lowest bucket with a non-positive bound is returned as is, not
+// interpolated from zero.
+#[test]
+fn histogram_quantile_non_positive_lowest_bucket() {
+    let samples = buckets(&[("job=a", &[("-1", 2.), ("1", 4.), ("+Inf", 4.)])]);
+    for (q, expected) in [("0.25", -1.), ("0.75", 0.)] {
+        let query = format!("histogram_quantile({q}, x_bucket)");
+        assert_eq!(
+            quantile(&query, &samples),
+            vec![("job=a".into(), expected)],
+            "{query}"
+        );
+    }
+}
+
+// The common shapes: an aggregated rate keeps its by labels other than le, and
+// a per-series rate keeps every label but le and __name__.
+#[test]
+fn histogram_quantile_over_rates_and_sums() {
+    // Each counter grows by c per minute, so its rate is c/60.
+    let counter = |labels: &'static str, le: &str, c: f64| {
+        let spec: &'static str = Box::leak(format!("{labels},le={le}").into_boxed_str());
+        (60..=240)
+            .step_by(60)
+            .map(move |t| (spec, t as i64, c * (t / 60) as f64))
+            .collect::<Vec<Sample>>()
+    };
+    let mut samples = Vec::new();
+    for inst in ["job=a,inst=1", "job=a,inst=2"] {
+        for (le, count) in HISTOGRAM {
+            samples.extend(counter(inst, le, *count));
+        }
+    }
+    let metrics = &[("x_bucket", samples.as_slice())];
+    let close = |rows: Vec<(String, f64)>, expected: &[(&str, f64)]| {
+        assert_eq!(rows.len(), expected.len(), "{rows:?}");
+        for ((labels, v), (want, w)) in rows.iter().zip(expected) {
+            assert_eq!(labels, want);
+            assert!((v - w).abs() < 1e-9, "{labels}: {v} vs {w}");
+        }
+    };
+    close(
+        labeled(
+            "histogram_quantile(0.5, sum by (le, job) (rate(x_bucket[5m])))",
+            metrics,
+            300,
+        ),
+        &[("job=a", 1.75)],
+    );
+    close(
+        labeled(
+            "histogram_quantile(0.5, sum by (le) (x_bucket))",
+            metrics,
+            250,
+        ),
+        &[("", 1.75)],
+    );
+    close(
+        labeled("histogram_quantile(0.5, rate(x_bucket[5m]))", metrics, 300),
+        &[("inst=1,job=a", 1.75), ("inst=2,job=a", 1.75)],
+    );
+}
+
+// Histograms that differ only in __name__ collide once it is dropped, which
+// Prometheus reports as an error rather than merging them.
+#[test]
+fn histogram_quantile_rejects_equal_output_label_sets() {
+    let mut samples = buckets(&[("job=a", HISTOGRAM)]);
+    samples.extend(buckets(&[("__name__=y_bucket,job=a", HISTOGRAM)]));
+    let error = evaluate(
+        "histogram_quantile(0.5, x_bucket)",
+        &[("x_bucket", &samples)],
+        60,
+    )
+    .unwrap_err();
+    assert!(error.contains("same labelset"), "{error}");
+}
+
+// time() uses the query evaluation instant in seconds in scalar and vector operands.
+#[test]
+fn evaluation_time_operands_use_runtime_scope() {
+    assert_eq!(labeled("time()", &[], 60), rows(&[("", 60.)]));
+    assert_eq!(labeled("vector(time())", &[], 60), rows(&[("", 60.)]));
+    assert_eq!(
+        labeled("a + time()", &[("a", A)], 60),
+        rows(&[("job=w", 60.), ("job=x", 70.), ("job=y", 80.)])
+    );
+    assert_eq!(
+        labeled("time() - scalar(b)", &[("b", &[("job=x", 60, 3.)])], 61),
+        rows(&[("", 58.)])
+    );
+}
+
+// Non-finite scalar operands survive both logical and physical plan JSON round trips.
+#[test]
+fn nonfinite_literals_round_trip_in_plans() {
+    for (query, expected) in [
+        ("vector(NaN)", f64::NAN),
+        ("vector(+Inf)", f64::INFINITY),
+        ("vector(-Inf)", f64::NEG_INFINITY),
+    ] {
+        let expression = lower(query);
+        let json = serde_json::to_vec(&expression).unwrap();
+        let restored: Rc<planner_types::ir::OperatorNode> = serde_json::from_slice(&json).unwrap();
+        let result = evaluate_dag(&restored, &fallback_dag(restored.clone()), &[], 60).unwrap();
+        assert_eq!(result.len(), 1);
+        if expected.is_nan() {
+            assert!(result[0].2.is_nan());
+        } else {
+            assert_eq!(result[0].2, expected);
+        }
+    }
+}
+
+// Classic histogram results remain aggregatable and support multi-quantile label branches.
+#[test]
+fn histogram_quantiles_and_nested_aggregation() {
+    let samples = buckets(&[("job=a", HISTOGRAM), ("job=b", HISTOGRAM)]);
+    assert_eq!(
+        quantile("sum(histogram_quantile(0.5, x_bucket))", &samples),
+        rows(&[("", 3.5)])
+    );
+    assert_eq!(
+        quantile("histogram_quantiles(x_bucket, \"q\", 0.5, 0.9)", &samples),
+        rows(&[
+            ("job=a,q=0.5", 1.75),
+            ("job=a,q=0.9", 4.0),
+            ("job=b,q=0.5", 1.75),
+            ("job=b,q=0.9", 4.0)
+        ])
+    );
+}
+
+// Relabeling anchors regexes, expands captures, preserves nonmatches and removes empty labels.
+#[test]
+fn label_replace_preserves_promql_labels() {
+    let samples: &[Sample] = &[
+        ("job=api:one,team=old", 50, 1.0),
+        ("job=other,team=old", 50, 2.0),
+    ];
+    assert_eq!(
+        labeled(
+            "label_replace(a, \"team\", \"$1\", \"job\", \"(.*):.*\")",
+            &[("a", samples)],
+            60
+        ),
+        rows(&[
+            ("__name__=a,job=api:one,team=api", 1.0),
+            ("__name__=a,job=other,team=old", 2.0)
+        ])
+    );
+    assert_eq!(
+        labeled(
+            "label_replace(a, \"team\", \"\", \"job\", \".*\")",
+            &[("a", samples)],
+            60
+        ),
+        rows(&[
+            ("__name__=a,job=api:one", 1.0),
+            ("__name__=a,job=other", 2.0)
+        ])
+    );
+}
+
+// Binary results over aggregates retain labels contributed by the other operand.
+#[test]
+fn binary_aggregates_accept_additional_labels() {
+    let a: &[Sample] = &[("job=x", 50, 2.0)];
+    let info: &[Sample] = &[("job=x,team=blue", 50, 3.0)];
+    assert_eq!(
+        labeled(
+            "sum by(job)(a) * on(job) group_left(team) info",
+            &[("a", a), ("info", info)],
+            60
+        ),
+        rows(&[("job=x,team=blue", 6.0)])
+    );
+    assert_eq!(
+        labeled("sum by(job)(a) or info", &[("a", a), ("info", info)], 60),
+        rows(&[("job=x", 2.0), ("__name__=info,job=x,team=blue", 3.0)])
+    );
+}
+
+// Relabeling handles missing sources and named captures, and rejects label-set collisions.
+#[test]
+fn label_replace_missing_labels_named_captures_and_duplicates() {
+    let a: &[Sample] = &[("job=api:one", 50, 2.)];
+    assert_eq!(
+        labeled(
+            r#"label_replace(a, "team", "${part}", "job", "(?P<part>.*):.*")"#,
+            &[("a", a)],
+            60
+        ),
+        rows(&[("__name__=a,job=api:one,team=api", 2.)])
+    );
+    assert_eq!(
+        labeled(
+            r#"label_replace(a, "team", "unknown", "missing", "^$")"#,
+            &[("a", a)],
+            60
+        ),
+        rows(&[("__name__=a,job=api:one,team=unknown", 2.)])
+    );
+    assert!(evaluate(r#"label_replace(a, "", "x", "job", ".*")"#, &[("a", a)], 60).is_err());
+    let duplicate: &[Sample] = &[("job=a", 50, 1.), ("job=b", 50, 2.)];
+    assert!(evaluate(
+        r#"label_replace(a, "job", "same", "job", ".*")"#,
+        &[("a", duplicate)],
+        60
+    )
+    .unwrap_err()
+    .contains("same labelset"));
+}
+
+// Right-side grouped rows and group_right labels survive an aggregated left schema.
+#[test]
+fn grouped_binary_right_rows_preserve_all_labels() {
+    let a: &[Sample] = &[("job=x", 50, 2.)];
+    let info: &[Sample] = &[("job=x,team=blue", 50, 3.)];
+    let metrics = &[("a", a), ("info", info)];
+    assert_eq!(
+        labeled("sum by(job)(a) * on(job) group_right info", metrics, 60),
+        rows(&[("job=x,team=blue", 6.)])
+    );
+    assert_eq!(
+        labeled("sum by(job)(a) or sum by(job,team)(info)", metrics, 60),
+        rows(&[("job=x", 2.), ("job=x,team=blue", 3.)])
+    );
+    let samples = buckets(&[("job=a", HISTOGRAM)]);
+    assert!(evaluate(
+        r#"histogram_quantiles(x_bucket, "q", 0.5, 0.5)"#,
+        &[("x_bucket", &samples)],
+        60
+    )
+    .unwrap_err()
+    .contains("same labelset"));
+}
+
+// Range-bound anchors compile without freezing the evaluation instant into the plan.
+#[test]
+fn range_bound_anchors_compile() {
+    for query in [
+        "a @ start()",
+        "sum_over_time(a[1m] @ end())",
+        "max_over_time(a[2m:1m] @ start())",
+    ] {
+        assert!(compile_query(query).is_ok(), "{query}");
+    }
+}
+
+// Stored programs resolve outer range anchors per run, including offsets and subquery grids.
+#[test]
+fn range_bound_anchors_use_outer_query_bounds() {
+    let samples: &[Sample] = &[
+        ("job=a", 30, 1.),
+        ("job=a", 60, 2.),
+        ("job=a", 90, 3.),
+        ("job=a", 120, 4.),
+    ];
+    for (query, expected) in [
+        ("a @ start()", 2.),
+        ("a @ end()", 4.),
+        ("a @ start() offset 30s", 1.),
+        ("sum_over_time(a[1m] @ end())", 7.),
+        ("max_over_time(a[2m:1m] @ start())", 2.),
+        ("max_over_time(a[2m:1m] @ end())", 4.),
+        ("max_over_time(a[2m:1m] @ end() offset 1m)", 2.),
+        ("max_over_time(a @ end()[2m:1m])", 4.),
+    ] {
+        let expression = lower(query);
+        let dag = fallback_dag(expression.clone());
+        let output =
+            evaluate_dag_with_range(&expression, &dag, &[("a", samples)], 90, Some((60, 120)))
+                .unwrap();
+        assert_eq!(output.len(), 1, "{query}");
+        assert_eq!(output[0].2, expected, "{query}");
+        assert_eq!(output[0].1, 90_000, "{query}");
+        let error = evaluate_dag(&expression, &dag, &[("a", samples)], 90).unwrap_err();
+        assert!(error.contains("query range bounds"), "{query}: {error}");
+    }
+}
+
+// Regression functions use float samples per series; prediction is anchored
+// at the evaluation time even when offset or @ selects an older window.
+#[test]
+fn regression_range_functions_use_evaluation_time_and_drop_names() {
+    let samples: &[Sample] = &[("job=x", 10, 3.), ("job=x", 30, 7.), ("job=x", 50, 11.)];
+    for (query, at, expected) in [
+        ("deriv(a[1m])", 60, 0.2),
+        ("predict_linear(a[1m], 10)", 60, 15.),
+        ("predict_linear(a[1m] offset 30s, 10)", 90, 21.),
+        ("predict_linear(a[1m] @ 60, 10)", 90, 21.),
+    ] {
+        let result = labeled(query, &[("a", samples)], at);
+        assert_eq!(result.len(), 1, "{query}");
+        assert_eq!(result[0].0, "job=x");
+        assert!(
+            (result[0].1 - expected).abs() < 1e-12,
+            "{query}: {result:?}"
+        );
+    }
+    let constant: &[Sample] = &[("job=x", 10, 1e300), ("job=x", 50, 1e300)];
+    assert_eq!(
+        labeled("deriv(a[1m])", &[("a", constant)], 60),
+        rows(&[("job=x", 0.)])
+    );
+    assert_eq!(
+        labeled("predict_linear(a[1m], 10)", &[("a", constant)], 60),
+        rows(&[("job=x", 1e300)])
+    );
+    assert!(labeled("deriv(a[1m])", &[("a", &samples[..1])], 60).is_empty());
+    let infinite: &[Sample] = &[("job=x", 10, f64::INFINITY), ("job=x", 50, f64::INFINITY)];
+    assert!(labeled("deriv(a[1m])", &[("a", infinite)], 60)[0]
+        .1
+        .is_nan());
+}
+
+// An `@`-pinned range function is step-invariant, as in Prometheus: it is
+// evaluated once, at the query start or at the subquery's first step, so
+// predict_linear's anchor does not move with each evaluation step.
+#[test]
+fn pinned_range_functions_are_step_invariant() {
+    // `a` rises by one per second, sampled every 10 s.
+    let rising: Vec<Sample> = (0..=30)
+        .map(|i| ("job=x", i * 10, (i * 10) as f64))
+        .collect();
+    // (query, range-query bounds, Prometheus value at T = 300 s).
+    for (query, bounds, expected) in [
+        // Subquery grid (180, 300] steps 240 and 300; one evaluation at 240.
+        (
+            "max_over_time(predict_linear(a[1m] @ 100, 0)[2m:1m])",
+            None,
+            240.,
+        ),
+        // A range query starting at 240 evaluates its grid from (120, 240]: at 180.
+        (
+            "max_over_time(predict_linear(a[1m] @ 100, 0)[2m:1m])",
+            Some((240, 300)),
+            180.,
+        ),
+        (
+            "max_over_time(predict_linear(a[1m] @ start(), 0)[2m:1m])",
+            Some((240, 300)),
+            180.,
+        ),
+        // A top-level pinned call is evaluated at the query start.
+        ("predict_linear(a[1m] @ 100, 0)", Some((240, 300)), 240.),
+        ("predict_linear(a[1m] @ 100, 0)", None, 300.),
+        // Functions that do not read the evaluation time are unchanged.
+        ("max_over_time(deriv(a[1m] @ 100)[2m:1m])", None, 1.),
+        ("max_over_time(rate(a[1m] @ 100)[2m:1m])", None, 1.),
+        ("max_over_time(a @ 100[2m:1m])", None, 100.),
+        // Without `@`, the anchor is each step: the latest step, 300, wins.
+        ("max_over_time(predict_linear(a[1m], 0)[2m:1m])", None, 300.),
+    ] {
+        let expression = lower(query);
+        let dag = fallback_dag(expression.clone());
+        let output = evaluate_dag_with_range(&expression, &dag, &[("a", &rising)], 300, bounds)
+            .unwrap_or_else(|e| panic!("{query}: {e}"));
+        assert_eq!(output.len(), 1, "{query}");
+        assert!(
+            (output[0].2 - expected).abs() < 1e-9,
+            "{query} {bounds:?}: {} != {expected}",
+            output[0].2
+        );
+    }
+}
+
+// Dropping an inner range function's metric name rejects equal labels within
+// each subquery step, while allowing that labelset at different steps.
+#[test]
+fn subquery_label_uniqueness_is_checked_per_evaluation_step() {
+    let equal: &[Sample] = &[
+        ("job=x", 10, 1.),
+        ("job=x", 50, 2.),
+        ("__name__=b,job=x", 10, 1.),
+        ("__name__=b,job=x", 50, 4.),
+    ];
+    let query = "last_over_time(rate(a[1m])[2m:1m])";
+    let error = evaluate(query, &[("a", equal)], 60).unwrap_err();
+    assert!(error.contains("same labelset"), "{error}");
+    let disjoint: &[Sample] = &[
+        ("job=x", -50, 1.),
+        ("job=x", -10, 2.),
+        ("__name__=b,job=x", 10, 3.),
+        ("__name__=b,job=x", 50, 5.),
+    ];
+    let result = labeled(query, &[("a", disjoint)], 60);
+    assert_eq!(result.len(), 1);
+    assert_eq!(result[0].0, "job=x");
+    assert!((result[0].1 - 0.05).abs() < 1e-12);
+}
+
+// Non-finite histogram quantile parameters survive the logical DAG JSON boundary too.
+#[test]
+fn logical_nonfinite_quantile_parameter_round_trips() {
+    let expression = lower("histogram_quantile(NaN, x_bucket)");
+    let restored: Rc<planner_types::ir::OperatorNode> =
+        serde_json::from_slice(&serde_json::to_vec(&expression).unwrap()).unwrap();
+    let samples = buckets(&[("job=a", HISTOGRAM)]);
+    let result = evaluate_dag(
+        &restored,
+        &fallback_dag(restored.clone()),
+        &[("x_bucket", &samples)],
+        60,
+    )
+    .unwrap();
+    assert_eq!(result.len(), 1);
+    assert!(result[0].2.is_nan());
+}
+
+/// The proposal's pointwise projections preserve names only for unary minus.
+#[test]
+fn pointwise_projection_names_and_dynamic_parameters() {
+    let samples = [("job=a", 300, -2.5)];
+    assert_eq!(
+        labeled("-m", &[("m", &samples)], 300),
+        [("__name__=m,job=a".into(), 2.5)]
+    );
+    assert_eq!(
+        labeled("abs(m)", &[("m", &samples)], 300),
+        [("job=a".into(), 2.5)]
+    );
+    assert_eq!(
+        run("round(m, scalar(vector(2)))", &samples, 300).unwrap(),
+        [("a".into(), 300_000, -2.0)]
+    );
+    assert_eq!(
+        run("clamp(m, time()-301, time())", &samples, 300).unwrap(),
+        [("a".into(), 300_000, -1.0)]
+    );
+    assert!(run("clamp(m, 2, 1)", &samples, 300).unwrap().is_empty());
+    assert_eq!(
+        run("year(m)", &[("a", 300, 0.0)], 300).unwrap(),
+        [("a".into(), 300_000, 1970.0)]
+    );
+    assert_eq!(
+        run("hour()", &[], 3600).unwrap(),
+        [("".into(), 3_600_000, 1.0)]
+    );
+}
+
+/// Execute every PromQL root/conversion example in the scalar design document.
+#[test]
+fn scalar_design_document_examples_execute() {
+    let samples = [("job=a", 300, 1.0), ("job=b", 300, 2.0)];
+    for (query, expected) in [
+        ("2", 2.0),
+        ("time()", 300.0),
+        ("vector(time())", 300.0),
+        ("scalar(sum(up)) + 1", 4.0),
+    ] {
+        let root = parse_root(query, AccuracyTarget::Exact);
+        root.validate_structure().unwrap();
+        let output = evaluate(query, &[("up", &samples)], 300).unwrap();
+        assert_eq!(output.len(), 1, "{query}");
+        assert_eq!(output[0].2, expected, "{query}");
+    }
+    assert_eq!(
+        labeled("up * 2", &[("up", &samples)], 300),
+        [("job=a".into(), 2.0), ("job=b".into(), 4.0)]
+    );
+}
diff --git a/crates/types/src/post_asap/expr.rs b/crates/types/src/post_asap/expr.rs
index 7de1e81db..bd45748aa 100644
--- a/crates/types/src/post_asap/expr.rs
+++ b/crates/types/src/post_asap/expr.rs
@@ -283,3 +283,21 @@ pub struct BinaryOperator {
     /// re-parsing PromQL.
     pub vector_match: Option<VectorMatch>,
 }
+
+impl BinaryOperator {
+    pub fn from_logical(operator: &crate::ir::BinaryOperator, return_bool: bool) -> Self {
+        use crate::pre_asap::BinaryOpKind as L;
+        Self {
+            kind: match &operator.kind {
+                L::Arithmetic(op) => BinaryOpKind::Arithmetic(op.clone()),
+                L::Compare(op) if return_bool => BinaryOpKind::CompareBool(op.clone()),
+                L::Compare(op) => BinaryOpKind::Compare(op.clone()),
+                L::CompareBool(op) => BinaryOpKind::CompareBool(op.clone()),
+                L::Set(op) => BinaryOpKind::Set(op.clone()),
+            },
+            vector_match: operator.vector_match.clone(),
+            checked_relative_division: operator.checked_relative_division,
+            checked_finite_division: operator.checked_finite_division,
+        }
+    }
+}

From c8188195ef55c24942f98003dcdebc38008d032b Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 20:11:04 +0000
Subject: [PATCH 34/48] feat(ir): give physical ASAP DAGs one root per batch
 query

Match the logical export: a batch is one DAG whose roots are its queries,
with shared sub-DAGs exported once. The runtime compiles all roots.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 .../unified_physical_planner/candidates.rs    |  6 ++-
 .../unified_physical_planner/promql_rows.rs   | 13 +++--
 .../tests/unified_promql_fallback.rs          | 12 +++--
 crates/types/src/ir/physical_export.rs        | 51 ++++++++++++++-----
 crates/types/tests/physical_export.rs         | 22 ++++++++
 5 files changed, 81 insertions(+), 23 deletions(-)

diff --git a/crates/asap-physical-operators/src/unified_physical_planner/candidates.rs b/crates/asap-physical-operators/src/unified_physical_planner/candidates.rs
index 248f5d40f..406013eb9 100644
--- a/crates/asap-physical-operators/src/unified_physical_planner/candidates.rs
+++ b/crates/asap-physical-operators/src/unified_physical_planner/candidates.rs
@@ -101,8 +101,10 @@ pub fn frontier_from_timing(dag: &PhysicalASAPDAG) -> Result<Vec<NodeId>, Error>
         .map(|node| (node.id, node.output_state.timing))
         .collect::<BTreeMap<_, _>>();
     let mut frontier = BTreeSet::new();
-    if timing.get(&dag.root) == Some(&IngestionTime) {
-        frontier.insert(u64::from(dag.root.0));
+    for root in &dag.roots {
+        if timing.get(root) == Some(&IngestionTime) {
+            frontier.insert(u64::from(root.0));
+        }
     }
     for edge in &dag.edges {
         let (Some(&producer), Some(&consumer)) =
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/promql_rows.rs b/crates/asap-physical-operators/src/unified_physical_planner/promql_rows.rs
index 46670f478..20992dfe7 100644
--- a/crates/asap-physical-operators/src/unified_physical_planner/promql_rows.rs
+++ b/crates/asap-physical-operators/src/unified_physical_planner/promql_rows.rs
@@ -115,7 +115,7 @@ pub fn compile_current_series_evaluation(
                     u64::from(population.id.0),
                     InputContract::bounded(Arc::new(population.output_schema.clone())),
                 )]),
-                &[u64::from(dag.root.0)],
+                &dag.roots.iter().map(|r| u64::from(r.0)).collect::<Vec<_>>(),
             );
         }
     }
@@ -178,7 +178,7 @@ pub fn compile_current_series_evaluation(
     compile(
         &dag,
         BTreeMap::from([(frontier, InputContract::bounded(schema))]),
-        &[u64::from(dag.root.0)],
+        &dag.roots.iter().map(|r| u64::from(r.0)).collect::<Vec<_>>(),
     )
 }
 
@@ -229,7 +229,12 @@ pub fn compile_rate_ranking(
     let program = compile(
         &compiled.dag,
         BTreeMap::from([(id, InputContract::bounded(Arc::new(source.schema.clone())))]),
-        &[u64::from(compiled.dag.root.0)],
+        &compiled
+            .dag
+            .roots
+            .iter()
+            .map(|r| u64::from(r.0))
+            .collect::<Vec<_>>(),
     )?;
     Ok((source, program))
 }
@@ -297,7 +302,7 @@ pub fn compile_fixed_window_rate_aggregation(
             u64::from(source.id.0),
             InputContract::bounded(Arc::new(source.output_schema.clone())),
         )]),
-        &[u64::from(dag.root.0)],
+        &dag.roots.iter().map(|r| u64::from(r.0)).collect::<Vec<_>>(),
         &[u64::from(heap.id.0)],
     )
 }
diff --git a/crates/asap-physical-operators/tests/unified_promql_fallback.rs b/crates/asap-physical-operators/tests/unified_promql_fallback.rs
index 016c4f3a9..b3a00fc32 100644
--- a/crates/asap-physical-operators/tests/unified_promql_fallback.rs
+++ b/crates/asap-physical-operators/tests/unified_promql_fallback.rs
@@ -108,7 +108,7 @@ fn compile_dag(
     expression: &planner_types::ir::OperatorNode,
     dag: &PhysicalASAPDAG,
 ) -> Result<CompiledPhysicalDAG, String> {
-    let root = u64::from(dag.root.0);
+    let root = u64::from(dag.roots[0].0);
     let inputs = promql_fallback::raw_series(expression)
         .map_err(|e| e.to_string())?
         .into_iter()
@@ -454,7 +454,7 @@ fn dense_subquery_grids_are_rejected() {
 fn raw_series_contract_is_explicit() {
     let expression = lower("rate(m[5m])");
     let dag = fallback_dag(expression.clone());
-    let root = u64::from(dag.root.0);
+    let root = u64::from(dag.roots[0].0);
     let [(selector, schema)] = promql_fallback::raw_series(&expression)
         .unwrap()
         .try_into()
@@ -494,10 +494,14 @@ fn raw_series_contract_is_explicit() {
     assert!(compile(
         &consumed,
         BTreeMap::from([(
-            promql_fallback::raw_series_input(u64::from(consumed.root.0), 0),
+            promql_fallback::raw_series_input(u64::from(consumed.roots[0].0), 0),
             InputContract::bounded(raw)
         )]),
-        &[u64::from(consumed.root.0)]
+        &consumed
+            .roots
+            .iter()
+            .map(|r| u64::from(r.0))
+            .collect::<Vec<_>>()
     )
     .is_ok());
     // Implicit subquery resolution belongs to the deployment's evaluation interval.
diff --git a/crates/types/src/ir/physical_export.rs b/crates/types/src/ir/physical_export.rs
index 2142c1f94..2a8c8fd5f 100644
--- a/crates/types/src/ir/physical_export.rs
+++ b/crates/types/src/ir/physical_export.rs
@@ -72,7 +72,9 @@ pub struct PhysicalASAPDAG {
     pub edges: Vec<PhysicalASAPDAGEdge>,
     /// Semantic workload root. Physical query/precompute sinks are selected
     /// downstream by the control plane.
-    pub root: PhysicalASAPNodeId,
+    /// One root per query of the batch, in workload order. Scalar query roots
+    /// are not physical nodes yet.
+    pub roots: Vec<PhysicalASAPNodeId>,
 }
 
 /// Versioned transport envelope for a physical ASAP DAG.
@@ -112,6 +114,8 @@ pub enum PhysicalASAPDAGValidationError {
         producer: PhysicalASAPNodeId,
         consumer: PhysicalASAPNodeId,
     },
+    #[error("physical ASAP DAG has no query roots")]
+    NoRoots,
     #[error("physical ASAP DAG contains a cycle")]
     Cycle,
     #[error("physical ASAP node {0:?} is not reachable from the root")]
@@ -200,8 +204,13 @@ impl PhysicalASAPDAG {
                 }
             }
         }
-        if !nodes.contains_key(&self.root) {
-            return Err(PhysicalASAPDAGValidationError::MissingRoot(self.root));
+        if self.roots.is_empty() {
+            return Err(PhysicalASAPDAGValidationError::NoRoots);
+        }
+        for root in &self.roots {
+            if !nodes.contains_key(root) {
+                return Err(PhysicalASAPDAGValidationError::MissingRoot(*root));
+            }
         }
         let mut children: HashMap<PhysicalASAPNodeId, Vec<PhysicalASAPNodeId>> = HashMap::new();
         for edge in &self.edges {
@@ -262,13 +271,11 @@ impl PhysicalASAPDAG {
             visited.insert(id);
             true
         }
-        if !visit(
-            self.root,
-            &children,
-            &mut HashSet::new(),
-            &mut HashSet::new(),
-        ) {
-            return Err(PhysicalASAPDAGValidationError::Cycle);
+        let mut visited = HashSet::new();
+        for root in &self.roots {
+            if !visit(*root, &children, &mut HashSet::new(), &mut visited) {
+                return Err(PhysicalASAPDAGValidationError::Cycle);
+            }
         }
         fn mark(
             id: PhysicalASAPNodeId,
@@ -283,7 +290,9 @@ impl PhysicalASAPDAG {
             }
         }
         let mut reachable = HashSet::new();
-        mark(self.root, &children, &mut reachable);
+        for root in &self.roots {
+            mark(*root, &children, &mut reachable);
+        }
         if let Some(id) = nodes.keys().find(|id| !reachable.contains(id)) {
             return Err(PhysicalASAPDAGValidationError::UnreachableNode(*id));
         }
@@ -331,13 +340,29 @@ pub fn compile_physical_asap_dag(
 /// rules were checked by that pass and are not re-run here.
 pub fn compile_physical_asap_dag_with_node_ids(
     root: &Rc<OperatorNode>,
+) -> Result<PhysicalASAPDAGCompilation, ExecutionDataStateError> {
+    compile_physical_asap_workload_with_node_ids(std::slice::from_ref(root))
+}
+
+/// Export a timed batch as one DAG with one root per query.
+pub fn compile_physical_asap_workload(
+    roots: &[Rc<OperatorNode>],
+) -> Result<PhysicalASAPDAG, ExecutionDataStateError> {
+    Ok(compile_physical_asap_workload_with_node_ids(roots)?.dag)
+}
+
+pub fn compile_physical_asap_workload_with_node_ids(
+    roots: &[Rc<OperatorNode>],
 ) -> Result<PhysicalASAPDAGCompilation, ExecutionDataStateError> {
     let mut exporter = Exporter::default();
-    let root = exporter.visit(root)?;
+    let roots = roots
+        .iter()
+        .map(|root| exporter.visit(root))
+        .collect::<Result<Vec<_>, _>>()?;
     let dag = PhysicalASAPDAG {
         nodes: exporter.nodes,
         edges: exporter.edges,
-        root,
+        roots,
     };
     dag.validate()
         .expect("compiler emits a valid physical ASAP DAG");
diff --git a/crates/types/tests/physical_export.rs b/crates/types/tests/physical_export.rs
index 2008a66d3..eaafb7dd2 100644
--- a/crates/types/tests/physical_export.rs
+++ b/crates/types/tests/physical_export.rs
@@ -100,3 +100,25 @@ fn query_time_input_to_ingestion_is_rejected() {
 fn untimed_plan_is_rejected() {
     assert!(compile_physical_asap_dag(&plan()).is_err());
 }
+
+/// Two queries reading one summary state export once, with one root per query.
+#[test]
+fn batch_shares_the_summary_and_keeps_one_root_per_query() {
+    use asap_types::ir::export::compile_physical_asap_workload;
+    let first = plan();
+    let state = first.children()[0].clone();
+    let second = OperatorNode::new_shared(Operator::ASAP(ASAPOp::FinalizeExactAccumulator {
+        child: state,
+    }))
+    .unwrap();
+    let assignment = LifecycleAssignment::default_maintained();
+    let mut memo = TimingMemo::new();
+    let timed: Vec<_> = [first, second]
+        .iter()
+        .map(|root| apply_lifecycle_timings(root, &assignment, &mut memo).unwrap())
+        .collect();
+    let dag = compile_physical_asap_workload(&timed).unwrap();
+    dag.validate().unwrap();
+    assert_eq!(dag.roots.len(), 2);
+    assert_eq!(dag.nodes.len(), 4, "scan and summary are exported once");
+}

From 672a1873798c755f0c6982971b6e2cbc26c369ca Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Mon, 5 Oct 2026 04:20:04 +0000
Subject: [PATCH 35/48] fix: integrate with #614 (DataFusion 54): let chrono
 resolve to DF 54's version

DataFusion 54 requires chrono ^0.4.44, so the runtime crate's exact
=0.4.39 pin no longer resolves; keep 0.4.39 as the minimum.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/asap-physical-operators/Cargo.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/crates/asap-physical-operators/Cargo.toml b/crates/asap-physical-operators/Cargo.toml
index 5d33b6086..a7130158b 100644
--- a/crates/asap-physical-operators/Cargo.toml
+++ b/crates/asap-physical-operators/Cargo.toml
@@ -4,7 +4,7 @@ version = "0.1.0"
 edition = "2021"
 
 [dependencies]
-chrono = { version = "=0.4.39", default-features = false, features = ["std"] }
+chrono = { version = "0.4.39", default-features = false, features = ["std"] }
 futures = "0.3"
 planner-types = { package = "asap-types", path = "../types" }
 asap_sketchlib = { git = "https://github.com/ProjectASAP/asap_sketchlib", rev = "5f03ccbd798ed5fec62bdd839bcb331123cab369" }

From 6272362bdfbbbe03f6d0371d9529f03880dd236b Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 20:10:57 +0000
Subject: [PATCH 36/48] refactor(planner): plan one shared unified workload DAG

Cut today's planner over to the unified OperatorNode IR. Frontends return
OperatorNode / QueryRoot, ParsedWorkload keeps scalar roots, Pass 1
(ASAPStrategies), the existing identical-sub-DAG sharing, selection, DAG
assembly and lifecycle costing all run on OperatorNode, and PlanOutput exposes
the whole workload DAG. The native compiler from #541 becomes the canonical
physical_planner and consumes the PhysicalASAPDAG export.

Ported from the earlier #542 (95eef553) without new #509 stage logic. Legacy
QueryExpr/SummaryNode modules stay compiled for their own tests but are no
longer re-exported from post_asap; the cleanup PR removes them.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 Cargo.lock                                    |    1 +
 .../src/accuracy/composition.rs               |    6 +-
 .../src/accuracy/estimators/cms.rs            |    2 +-
 .../src/accuracy/estimators/hll.rs            |    8 +-
 .../src/accuracy/estimators/kll.rs            |    2 +-
 .../src/accuracy/estimators/mod.rs            |    6 +-
 .../src/accuracy/estimators/univmon.rs        |    2 +-
 .../src/accuracy/evidence.rs                  |   25 +-
 crates/asap-aware-mapping/src/accuracy/mod.rs |   12 +-
 .../src/accuracy/reconciliation.rs            |   99 +-
 .../asap-aware-mapping/src/analytical_cost.rs |   12 +-
 crates/asap-aware-mapping/src/cost_model.rs   |  274 +-
 .../src/empirical_comparison.rs               |   10 +-
 .../asap-aware-mapping/src/empirical_cost.rs  |   13 +-
 .../src/exact_composition.rs                  |  355 +-
 crates/asap-aware-mapping/src/explanation.rs  |  216 +-
 crates/asap-aware-mapping/src/grouping.rs     |  210 +-
 crates/asap-aware-mapping/src/lib.rs          |   26 +-
 .../src/maintained_population.rs              |  284 +-
 crates/asap-aware-mapping/src/pane_sharing.rs |    8 +-
 crates/asap-aware-mapping/src/pass/major.rs   |   21 +-
 crates/asap-aware-mapping/src/pass/mod.rs     |   72 +-
 .../src/physical_operator_statistics.rs       |    8 +-
 .../src/physical_plan_cost_model.rs           |   72 +-
 .../src/query_physical_lowering.rs            |  839 ++--
 crates/asap-aware-mapping/src/recurrence.rs   |  179 +-
 crates/asap-aware-mapping/src/replacement.rs  | 3675 +++++++++--------
 crates/asap-aware-mapping/src/rewrite.rs      |  462 ++-
 crates/asap-aware-mapping/src/rollup.rs       |  214 +-
 .../src/summary_maintenance_cost/estimator.rs |  497 +--
 .../src/summary_maintenance_cost/evidence.rs  |   85 +-
 .../src/summary_maintenance_cost/mod.rs       |   11 +-
 .../src/summary_maintenance_cost/model.rs     | 1311 +++---
 .../src/summary_maintenance_cost/window.rs    |   58 +-
 .../src/summary_maintenance_dag_export.rs     |   66 +-
 .../src/summary_maintenance_lifecycle.rs      |  711 ++--
 crates/asap-aware-mapping/src/test_support.rs |  168 +-
 crates/asap-aware-mapping/src/topk_reuse.rs   |  117 +-
 .../tests/physical_handoff_cost.rs            |    2 +-
 crates/asap-aware-mapping/tests/storage_io.rs |    2 +-
 crates/asap-physical-operators/README.md      |   14 +-
 .../asap-physical-operators/src/capability.rs |   67 +-
 .../asap-physical-operators/src/evaluation.rs |  111 +
 .../src/expressions/arithmetic.rs             |    5 +-
 .../src/expressions/binary.rs                 |   38 +-
 .../src/expressions/mod.rs                    |   15 +-
 .../src/expressions/planner.rs                |  285 +-
 crates/asap-physical-operators/src/lib.rs     |    5 +-
 .../src/operators/aggregate/mod.rs            |   12 +-
 .../src/operators/aggregate/temporal.rs       |   18 +-
 .../src/operators/aligned_binary.rs           |   12 +-
 .../src/operators/common.rs                   |   15 +-
 .../src/operators/joins/mod.rs                |   45 +-
 .../src/operators/mod.rs                      |   57 +-
 .../src/operators/scope_timestamp.rs          |    2 +-
 .../src/operators/series_labels.rs            |    7 +-
 .../src/operators/summary/mod.rs              |  105 +-
 .../src/operators/unchecked.rs                |   10 +-
 .../src/operators/vector_binary.rs            |    3 +-
 .../src/operators/vector_window.rs            |    5 +-
 .../src/physical_planner/candidates.rs        |   73 +-
 .../src/physical_planner/logical.rs           |  374 ++
 .../src/physical_planner/mod.rs               |  392 +-
 .../src/physical_planner/precompute.rs        |  127 +-
 .../src/physical_planner/promql_fallback.rs   |  505 ++-
 .../src/physical_planner/promql_rows.rs       |  164 +-
 .../src/physical_planner/promql_values.rs     |   31 +-
 .../src/physical_planner/row_values.rs        |   19 +-
 .../src/runtime/batch_execution.rs            |   24 +-
 .../src/sources/memory.rs                     |    2 +-
 .../src/sources/mod.rs                        |   13 +-
 .../src/summary_kernels/exact.rs              |  103 +-
 .../src/summary_kernels/factory.rs            |   10 +-
 .../src/summary_kernels/traits.rs             |    6 +-
 .../src/summary_kernels/univmon.rs            |   10 +-
 crates/asap-physical-operators/src/values.rs  |   30 +-
 .../tests/blocking_resources.rs               |   19 +-
 .../tests/{unified_common => common}/mod.rs   |    0
 .../tests/current_series_heap.rs              |   29 +-
 .../tests/deployment.rs                       |    2 +-
 .../tests/deployment_computation.rs           |  248 +-
 .../tests/physical_dag.rs                     |  342 +-
 .../tests/physical_plan_recovery.rs           |   15 +-
 .../tests/physical_semantics.rs               |   70 +-
 .../tests/plan_properties.rs                  |   41 +-
 .../tests/planspace_series_identity_heap.rs   |   35 +-
 .../tests/precompute_candidates.rs            |  107 +-
 .../tests/precompute_population.rs            |  110 +-
 .../tests/promql_binary.rs                    |  104 +-
 .../tests/promql_fallback.rs                  |  219 +-
 .../tests/promql_values.rs                    |   21 +-
 .../asap-physical-operators/tests/raw_scan.rs |  107 +-
 .../tests/summary_projection.rs               |   46 +-
 .../tests/unified_promql_fallback.rs          | 1615 --------
 .../tests/weighted_topk_binding.rs            |  131 +-
 .../devtools/examples/canonical_examples.rs   |    4 +-
 crates/devtools/src/bin/analyze_corpora.rs    |    4 +-
 crates/devtools/src/bin/dag_export.rs         |  288 +-
 crates/devtools/src/bin/show_post_asap_ir.rs  |   55 +-
 crates/devtools/src/bin/show_pre_asap_ir.rs   |    3 +-
 crates/devtools/src/bin/sketch_coverage.rs    |    7 +-
 crates/devtools/src/bin/variant_coverage.rs   |  281 +-
 crates/devtools/src/lib.rs                    |    4 +-
 crates/devtools/tests/cross_language.rs       |   83 +-
 crates/frontend-metricsql/src/lib.rs          |  106 +-
 crates/frontend-metricsql/tests/lowering.rs   |   43 +-
 crates/frontend-promql/Cargo.toml             |    5 +-
 crates/frontend-promql/src/error.rs           |   10 +-
 crates/frontend-promql/src/histogram.rs       |   26 +-
 crates/frontend-promql/src/lib.rs             |   89 +-
 crates/frontend-promql/src/promql.rs          |  571 +--
 .../frontend-promql/tests/count_planning.rs   |   72 +-
 .../tests/histogram_metadata.rs               |   63 +-
 .../tests/maintained_population_horizon.rs    |   22 +-
 .../awesome_prometheus_alerts.rs              |  126 +-
 .../observability/metrics_observability.rs    |   23 +-
 .../tests/observability/promql_corpus.rs      |   52 +-
 .../tests/promql_binding_regressions.rs       |    7 +-
 .../tests/promql_conformance.rs               | 1022 +++--
 .../tests/promql_equivalence.rs               |    6 +-
 .../frontend-promql/tests/promql_lowering.rs  |  725 +++-
 ...fied_scalar_design.rs => scalar_design.rs} |    3 +-
 crates/frontend-promql/tests/support.rs       |   66 +-
 .../tests/unified_histogram_metadata.rs       |  138 -
 .../tests/unified_promql_conformance.rs       | 2208 ----------
 .../tests/unified_promql_lowering.rs          | 1615 --------
 .../frontend-promql/tests/unified_support.rs  |  101 -
 .../tests/univmon_candidates.rs               |   54 +-
 crates/frontend-sql/src/error.rs              |   12 +-
 crates/frontend-sql/src/lib.rs                |   44 +-
 .../src/sql/collection_planning.rs            |   12 +-
 crates/frontend-sql/src/sql/expr.rs           |  498 ++-
 crates/frontend-sql/src/sql/mod.rs            |  439 +-
 .../tests/bgp_analytics/bgp_analytics.rs      |   27 +-
 .../bgp_jan2024_workload.rs                   |   22 +-
 .../synthetic_packet_trace.rs                 |  128 +-
 .../tests/maintained_population.rs            |   92 +-
 crates/frontend-sql/tests/netflow/netflow.rs  |  117 +-
 crates/frontend-sql/tests/pearson_corr.rs     |   70 +-
 crates/frontend-sql/tests/sql_lowering.rs     |  830 ++--
 crates/frontend-sql/tests/temporal_types.rs   |   21 +-
 .../tests/unified_sql_lowering.rs             | 2885 -------------
 crates/integration-tests/Cargo.toml           |    1 +
 crates/integration-tests/src/lib.rs           |   44 +-
 crates/integration-tests/tests/aggregate.rs   |   41 +-
 crates/integration-tests/tests/binary_op.rs   |  240 +-
 crates/integration-tests/tests/cse.rs         |   54 +-
 .../tests/exact_composition.rs                |  317 +-
 .../tests/frontend_timestamps.rs              |   36 +-
 .../tests/kll_pane_execution.rs               |   20 +-
 crates/integration-tests/tests/nested.rs      |  361 +-
 .../tests/operator_design_examples.rs         |  401 ++
 .../tests/operator_sharing.rs                 |  195 +
 .../tests/physical_common/mod.rs              |   13 +
 .../tests/precompute_raw_samples.rs           |   58 +-
 .../tests/promql_numeric_regressions.rs       |   72 +-
 .../tests/promql_to_post_asap.rs              |  791 ++--
 crates/integration-tests/tests/scan.rs        |   82 +-
 crates/integration-tests/tests/schema.rs      |   38 +-
 .../tests/sql_to_physical.rs                  |   41 +-
 .../tests/sql_to_post_asap.rs                 |  614 +--
 .../summary_maintenance_lifecycle_e2e.rs      |  194 +-
 crates/integration-tests/tests/time_range.rs  |   35 +-
 .../src/optimizer/const_evaluator.rs          |    2 +-
 crates/planner/src/lib.rs                     |   33 +-
 crates/planner/tests/e2e_plan.rs              |   60 +-
 crates/planner/tests/summary_sharing.rs       |   62 +-
 crates/sql-function-catalog/src/lib.rs        |    2 +-
 crates/types/src/dag_export.rs                | 2240 +++++-----
 crates/types/src/ir/export.rs                 |    2 +-
 crates/types/src/parsed_workload.rs           |   62 +-
 .../src/post_asap/execution_data_state.rs     |    2 +
 crates/types/src/post_asap/expr.rs            |    2 +-
 crates/types/src/post_asap/guarantee.rs       |   18 +-
 .../src/post_asap/maintained_population.rs    |    6 +-
 crates/types/src/post_asap/mod.rs             |   21 +-
 .../post_asap/query_time/error_estimation.rs  |   10 +-
 crates/types/src/post_asap/sketch.rs          |   17 +-
 .../src/post_asap/summary_maintenance.rs      |    2 +-
 crates/types/src/post_asap/summary_window.rs  |    4 +-
 crates/types/tests/planner_vocabulary.rs      |    5 +-
 181 files changed, 14788 insertions(+), 20605 deletions(-)
 create mode 100644 crates/asap-physical-operators/src/evaluation.rs
 create mode 100644 crates/asap-physical-operators/src/physical_planner/logical.rs
 rename crates/asap-physical-operators/tests/{unified_common => common}/mod.rs (100%)
 delete mode 100644 crates/asap-physical-operators/tests/unified_promql_fallback.rs
 rename crates/frontend-promql/tests/{unified_scalar_design.rs => scalar_design.rs} (97%)
 delete mode 100644 crates/frontend-promql/tests/unified_histogram_metadata.rs
 delete mode 100644 crates/frontend-promql/tests/unified_promql_conformance.rs
 delete mode 100644 crates/frontend-promql/tests/unified_promql_lowering.rs
 delete mode 100644 crates/frontend-promql/tests/unified_support.rs
 delete mode 100644 crates/frontend-sql/tests/unified_sql_lowering.rs
 create mode 100644 crates/integration-tests/tests/operator_design_examples.rs
 create mode 100644 crates/integration-tests/tests/operator_sharing.rs

diff --git a/Cargo.lock b/Cargo.lock
index 79da8962c..de76c1704 100644
--- a/Cargo.lock
+++ b/Cargo.lock
@@ -391,6 +391,7 @@ dependencies = [
  "asap-frontend-promql",
  "asap-frontend-sql",
  "asap-physical-operators",
+ "asap-planner",
  "asap-types",
  "asap_sketchlib 0.3.0 (git+https://github.com/ProjectASAP/asap_sketchlib)",
  "futures",
diff --git a/crates/asap-aware-mapping/src/accuracy/composition.rs b/crates/asap-aware-mapping/src/accuracy/composition.rs
index f42e8f158..daad8071c 100644
--- a/crates/asap-aware-mapping/src/accuracy/composition.rs
+++ b/crates/asap-aware-mapping/src/accuracy/composition.rs
@@ -448,9 +448,7 @@ fn composed_provenance(
 }
 
 pub(super) fn exact_operation_rule(operation: &ExactOperation) -> Option<CompositionOperator> {
-    let ExactOperation::Aggregate { measures, .. } = operation else {
-        return None;
-    };
+    let ExactOperation::Aggregate { measures, .. } = operation;
     match measures.as_slice() {
         [intent] => crate::function_rules::function_rules(intent).map(|rules| rules.accuracy),
         // The remaining functions are exact over exact samples, but have
@@ -1035,8 +1033,8 @@ mod tests {
             reduction: asap_types::pre_asap::Reduction::PerEntity,
             measures: vec![intent],
             output_names: vec![],
-            having: None,
             filters: vec![],
+            having: None,
         };
         assert_eq!(
             DefaultAccuracyModel.exact_operation_rule(&operation(AggIntent::Rate)),
diff --git a/crates/asap-aware-mapping/src/accuracy/estimators/cms.rs b/crates/asap-aware-mapping/src/accuracy/estimators/cms.rs
index 46559358d..9482c539a 100644
--- a/crates/asap-aware-mapping/src/accuracy/estimators/cms.rs
+++ b/crates/asap-aware-mapping/src/accuracy/estimators/cms.rs
@@ -65,7 +65,7 @@ mod tests {
     }
 
     #[test]
-    fn heap_readout_retains_frequency_metric() {
+    fn heap_evaluation_retains_frequency_metric() {
         use asap_types::post_asap::{GroupingStrategy, SketchKind};
         let cms_heap = SketchParams::CmsWithHeap {
             width: 272,
diff --git a/crates/asap-aware-mapping/src/accuracy/estimators/hll.rs b/crates/asap-aware-mapping/src/accuracy/estimators/hll.rs
index 4431a4118..f4556446c 100644
--- a/crates/asap-aware-mapping/src/accuracy/estimators/hll.rs
+++ b/crates/asap-aware-mapping/src/accuracy/estimators/hll.rs
@@ -1,7 +1,7 @@
 //! Estimator-specific confidence for classic HLL's linear-counting branch.
 //!
 //! This is conditional on independent uniform bucket hashes and an enforced
-//! upper bound on distinct items in the complete readout population (including
+//! upper bound on distinct items in the complete evaluation population (including
 //! all merged panes). It is not an RSE-to-normal conversion or an ERP fit.
 
 use super::*;
@@ -56,13 +56,13 @@ impl ClassicHllConfidence {
                 value: self.relative_error,
             },
             failure_probability: ProbabilityExpr::Constant { value: delta },
-            provenance: vec![GuaranteeSource::SketchReadout {
+            provenance: vec![GuaranteeSource::SketchEvaluation {
                 algorithm: "Hll".into(),
                 contract: "classic_hll_linear_counting_collision_bound_v1".into(),
                 params: serde_json::json!({"precision": precision,
                     "max_distinct": self.max_distinct, "relative_error": self.relative_error,
                     "hash_assumption": "independent_uniform_buckets",
-                    "population_scope": "complete_readout_including_merged_panes"}),
+                    "population_scope": "complete_evaluation_including_merged_panes"}),
                 query: "Cardinality".into(),
             }],
         })
@@ -187,7 +187,7 @@ mod tests {
             }
         }
     }
-    /// The model's readout formula matches the actual classic estimator after merge.
+    /// The model's evaluation formula matches the actual classic estimator after merge.
     #[test]
     fn native_classic_estimator_and_merged_registers_use_the_same_contract() {
         use asap_sketchlib::sketches::hll::{Classic, HyperLogLogP16};
diff --git a/crates/asap-aware-mapping/src/accuracy/estimators/kll.rs b/crates/asap-aware-mapping/src/accuracy/estimators/kll.rs
index 4cfe6f073..4f880894d 100644
--- a/crates/asap-aware-mapping/src/accuracy/estimators/kll.rs
+++ b/crates/asap-aware-mapping/src/accuracy/estimators/kll.rs
@@ -69,7 +69,7 @@ mod tests {
         assert_eq!(g.approximate_layer_count(), 1);
         assert!(g.provenance.iter().any(|source| matches!(
             source,
-            GuaranteeSource::SketchReadout { contract, .. }
+            GuaranteeSource::SketchEvaluation { contract, .. }
                 if contract == "apache_datasketches_kll_empirical_99_a9b42755072b"
         )));
     }
diff --git a/crates/asap-aware-mapping/src/accuracy/estimators/mod.rs b/crates/asap-aware-mapping/src/accuracy/estimators/mod.rs
index 4eabf40be..0cd5fcb4f 100644
--- a/crates/asap-aware-mapping/src/accuracy/estimators/mod.rs
+++ b/crates/asap-aware-mapping/src/accuracy/estimators/mod.rs
@@ -46,7 +46,7 @@ fn bounded_guarantee(
         metric,
         bound: BoundExpr::Constant { value: bound },
         failure_probability: delta,
-        provenance: vec![GuaranteeSource::SketchReadout {
+        provenance: vec![GuaranteeSource::SketchEvaluation {
             algorithm: format!("{algorithm:?}"),
             contract: contract.into(),
             params: serde_json::to_value(params).unwrap_or(serde_json::Value::Null),
@@ -169,9 +169,9 @@ impl<'a> EstimatorAccuracy<'a> {
 
     fn hll(&self) -> Option<hll::ClassicHllConfidence> {
         let EstimatorContract::ClassicHll {
-            max_distinct_per_readout,
+            max_distinct_per_evaluation,
         } = self.contract?;
-        hll::ClassicHllConfidence::new(max_distinct_per_readout, self.epsilon)
+        hll::ClassicHllConfidence::new(max_distinct_per_evaluation, self.epsilon)
     }
 
     pub(crate) fn size_params(&self, algorithm: &SketchAlgorithm) -> Option<SketchParams> {
diff --git a/crates/asap-aware-mapping/src/accuracy/estimators/univmon.rs b/crates/asap-aware-mapping/src/accuracy/estimators/univmon.rs
index 297cf53d3..6a89a105e 100644
--- a/crates/asap-aware-mapping/src/accuracy/estimators/univmon.rs
+++ b/crates/asap-aware-mapping/src/accuracy/estimators/univmon.rs
@@ -1,4 +1,4 @@
-//! UnivMon currently certifies only its exact unit-update total readout.
+//! UnivMon currently certifies only its exact unit-update total evaluation.
 use super::*;
 
 pub(super) fn guarantee(query: &SketchStatistic) -> Option<ResultGuarantee> {
diff --git a/crates/asap-aware-mapping/src/accuracy/evidence.rs b/crates/asap-aware-mapping/src/accuracy/evidence.rs
index 6391c746e..f779d5782 100644
--- a/crates/asap-aware-mapping/src/accuracy/evidence.rs
+++ b/crates/asap-aware-mapping/src/accuracy/evidence.rs
@@ -2,12 +2,12 @@
 use super::*;
 
 /// A trusted source assertion scoped by `AccuracyEvidenceProvider` to one
-/// complete readout. Choosing this variant asserts the estimator and hash
+/// complete evaluation. Choosing this variant asserts the estimator and hash
 /// assumptions; it must not be inferred from sampled population statistics.
 #[derive(Debug, Clone, Copy, PartialEq, Eq)]
 pub enum EstimatorContract {
     /// Classic HLL with independent uniform bucket hashing, including merged panes.
-    ClassicHll { max_distinct_per_readout: u32 },
+    ClassicHll { max_distinct_per_evaluation: u32 },
 }
 
 /// An enforced domain for every sample of a direct quantile operand, in every
@@ -18,7 +18,7 @@ pub enum EstimatorContract {
 pub struct QuantileInputDomain {
     pub lower: f64,
     pub upper: f64,
-    /// Upper bound on samples per evaluation, matching the pinned readout's
+    /// Upper bound on samples per evaluation, matching the pinned evaluation's
     /// exact Float64 rank limit. The population must also be nonempty.
     pub max_samples: u64,
     pub contract: String,
@@ -87,31 +87,22 @@ pub struct PropagationStats {
 /// Supplies typed planning-time evidence required by propagation rules.
 pub trait AccuracyEvidenceProvider {
     /// Trusted estimator contract for this complete aggregate expression,
-    /// including source, filters, grouping and all panes in each readout.
+    /// including source, filters, grouping and all panes in each evaluation.
     /// An observed cardinality is not an enforced population bound.
-    fn estimator_contract(
-        &self,
-        _expression: &asap_types::pre_asap::QueryExpr,
-    ) -> Option<EstimatorContract> {
+    fn estimator_contract(&self, _expression: &OperatorNode) -> Option<EstimatorContract> {
         None
     }
 
     /// Enforced upper bound on distinct (partition, item) identities across a
-    /// complete TopK readout. Used to union-bound score errors for adaptively
+    /// complete TopK evaluation. Used to union-bound score errors for adaptively
     /// selected candidates. Observed cardinality is not sufficient evidence.
-    fn topk_max_distinct_items(
-        &self,
-        _expression: &asap_types::pre_asap::QueryExpr,
-    ) -> Option<u64> {
+    fn topk_max_distinct_items(&self, _expression: &OperatorNode) -> Option<u64> {
         None
     }
 
     /// Proof scoped to this complete quantile expression, including its source,
     /// filters, grouping and window. `None` means unknown, including emptiness.
-    fn quantile_input_domain(
-        &self,
-        _operand: &asap_types::pre_asap::query_expr::QueryExpr,
-    ) -> Option<QuantileInputDomain> {
+    fn quantile_input_domain(&self, _operand: &OperatorNode) -> Option<QuantileInputDomain> {
         None
     }
 
diff --git a/crates/asap-aware-mapping/src/accuracy/mod.rs b/crates/asap-aware-mapping/src/accuracy/mod.rs
index 9026de468..a2f3354c0 100644
--- a/crates/asap-aware-mapping/src/accuracy/mod.rs
+++ b/crates/asap-aware-mapping/src/accuracy/mod.rs
@@ -20,18 +20,20 @@ pub use evidence::{
     QuantileInputDomain, WorkloadAccuracyEvidence,
 };
 
+use asap_types::ir::OperatorNode;
 use asap_types::post_asap::{
-    AccuracyError, BoundExpr, CompositionOperator, ErrorMetric, ExactOperation, FieldDataType,
-    GuaranteeSource, ProbabilityExpr, ResultGuarantee, SketchAlgorithm, SketchParams,
-    SketchStatistic,
+    AccuracyError, BoundExpr, CompositionOperator, ErrorMetric, FieldDataType, GuaranteeSource,
+    ProbabilityExpr, ResultGuarantee, SketchAlgorithm, SketchParams, SketchStatistic,
 };
 use asap_types::types::AccuracyTarget;
 
+use crate::exact_composition::ExactOperation;
+
 /// The deployment-extensible accuracy algebra. `asap-aware-mapping` ships
 /// [`DefaultAccuracyModel`]; a deployment with a proof for a composition the
 /// default rejects (a registered cross-metric conversion, say) implements
 /// this trait and passes it to
-/// [`crate::replacement::SketchAlgorithmStrategy::new_with_planning_inputs`].
+/// [`crate::replacement::ASAPStrategies::new_with_planning_inputs`].
 pub trait AccuracyModel {
     /// The definition-registered rule for applying `operation` to an
     /// approximate input. `None` means the function is exact only over exact
@@ -78,7 +80,7 @@ pub struct DefaultAccuracyModel;
 const SATISFACTION_TOLERANCE: f64 = 1e-9;
 
 impl DefaultAccuracyModel {
-    /// Derive the guarantee for the committed estimator parameters and readout.
+    /// Derive the guarantee for the committed estimator parameters and evaluation.
     pub fn sketch_guarantee(
         algorithm: &SketchAlgorithm,
         params: &SketchParams,
diff --git a/crates/asap-aware-mapping/src/accuracy/reconciliation.rs b/crates/asap-aware-mapping/src/accuracy/reconciliation.rs
index 6014d3ba3..36a219d4e 100644
--- a/crates/asap-aware-mapping/src/accuracy/reconciliation.rs
+++ b/crates/asap-aware-mapping/src/accuracy/reconciliation.rs
@@ -28,10 +28,10 @@
 //!
 //! ## What counts as a "near-duplicate", and why
 //!
-//! Two [`QueryExpr::Aggregate`] nodes are accuracy-near-duplicates here iff,
+//! Two `NonASAPOp::Aggregate` nodes are accuracy-near-duplicates here iff,
 //! **in this order**:
 //!
-//! 1. Both are the same bindable shape [`crate::replacement::SketchAlgorithmStrategy`]
+//! 1. Both are the same bindable shape [`crate::replacement::ASAPStrategies`]
 //!    itself targets — a single measure, no `HAVING` (`bindable_intent`'s own
 //!    scope) — **and** that one measure is one of the four accuracy-bearing
 //!    [`AggIntent`] variants ([`crate::replacement::accuracy_target`]'s own
@@ -105,7 +105,7 @@
 //!
 //! Like every [`ReplacementStrategy`], this only ever *proposes* — the
 //! looser-accuracy consumer's own independently-sized candidate (from
-//! [`crate::replacement::SketchAlgorithmStrategy`]) stays in its
+//! [`crate::replacement::ASAPStrategies`]) stays in its
 //! [`crate::replacement::TargetSubDAGCandidates`] right alongside this strategy's
 //! "read the tighter sibling instead" [`Replacement::Rewrite`] candidate;
 //! [`crate::cost_model::CostModel`]-driven ranking picks between them;
@@ -149,11 +149,13 @@
 //! same structural child, so adding the edge preserves the reference DAG's
 //! parent-before-child topological ordering.
 
+use asap_types::ir::non_asap::any_measure_filtered;
 use std::cmp::Ordering;
 use std::rc::Rc;
 
+use asap_types::ir::operator_properties::Reduction;
+use asap_types::ir::{NonASAPOp, OperatorNode};
 use asap_types::pre_asap::agg_intent::AggIntent;
-use asap_types::pre_asap::query_expr::{any_measure_filtered, QueryExpr, Reduction};
 use asap_types::types::AccuracyTarget;
 
 use crate::replacement::{
@@ -169,27 +171,27 @@ type BindableAccuracyAggregate<'a> = (
     &'a AggIntent,
     &'a AccuracyTarget,
     &'a [String],
-    &'a Rc<QueryExpr>,
+    &'a Rc<OperatorNode>,
 );
 
 /// The `(reduction, intent, accuracy, output_names, child)` shape this
 /// module operates on: the same single-measure, no-`HAVING` bindable shape
-/// [`crate::replacement::SketchAlgorithmStrategy`] targets (see that
+/// [`crate::replacement::ASAPStrategies`] targets (see that
 /// module's private `bindable_intent`), further narrowed to a measure whose
 /// intent actually carries an [`AccuracyTarget`]
 /// ([`crate::replacement::accuracy_target`]'s own scope: `Count` /
 /// `Quantile` / `Cardinality` / `TopK`). `None` for anything else, including
 /// a multi-measure or `HAVING` aggregate, a non-`Aggregate` node, or an
 /// accuracy-free intent (`Sum`, `Avg`, …).
-fn bindable_accuracy_aggregate(node: &QueryExpr) -> Option<BindableAccuracyAggregate<'_>> {
-    let QueryExpr::Aggregate {
+fn bindable_accuracy_aggregate(node: &OperatorNode) -> Option<BindableAccuracyAggregate<'_>> {
+    let Some(NonASAPOp::Aggregate {
         reduction,
         measures,
         output_names,
         filters,
         having,
         child,
-    } = node
+    }) = node.non_asap()
     else {
         return None;
     };
@@ -278,7 +280,7 @@ fn strictly_tighter(a: &AccuracyTarget, b: &AccuracyTarget) -> bool {
 /// this strategy from the same post-CSE `Aggregate` sibling set it already
 /// builds for `RollupStrategy`.
 pub struct AccuracyReconciliationStrategy {
-    siblings: Vec<Rc<QueryExpr>>,
+    siblings: Vec<Rc<OperatorNode>>,
 }
 
 impl AccuracyReconciliationStrategy {
@@ -286,7 +288,7 @@ impl AccuracyReconciliationStrategy {
     /// each as a candidate tighter-accuracy source (or looser-accuracy
     /// target) — typically the full set of `Aggregate` nodes a workload-wide
     /// discovery pass already found.
-    pub fn new(siblings: &[Rc<QueryExpr>]) -> Self {
+    pub fn new(siblings: &[Rc<OperatorNode>]) -> Self {
         Self {
             siblings: siblings.to_vec(),
         }
@@ -311,14 +313,14 @@ impl AccuracyReconciliationStrategy {
     /// reports no unique key — see `cse.rs`'s "Legality" section) would get
     /// proposed for reconciliation even though nothing guarantees a second
     /// read of it lines up row-for-row with the first.
-    fn tighter_sources<'a>(&'a self, target: &TargetSubDAG<'_>) -> Vec<&'a Rc<QueryExpr>> {
+    fn tighter_sources<'a>(&'a self, target: &TargetSubDAG<'_>) -> Vec<&'a Rc<OperatorNode>> {
         let Some((target_reduction, target_intent, target_accuracy, target_names, target_child)) =
             bindable_accuracy_aggregate(target.root)
         else {
             return Vec::new();
         };
 
-        let mut sources: Vec<&Rc<QueryExpr>> = self
+        let mut sources: Vec<&Rc<OperatorNode>> = self
             .siblings
             .iter()
             .filter(|candidate| {
@@ -335,9 +337,7 @@ impl AccuracyReconciliationStrategy {
                     && (Rc::ptr_eq(child, target_child) || child == target_child)
                     && same_intent_except_accuracy(intent, target_intent)
                     && strictly_tighter(accuracy, target_accuracy)
-                    && candidate
-                        .output_schema()
-                        .is_ok_and(|schema| schema.has_unique_key())
+                    && candidate.schema.has_unique_key()
             })
             .collect();
         sources.sort_by(|a, b| {
@@ -369,7 +369,7 @@ impl ReplacementStrategy for AccuracyReconciliationStrategy {
                     .expect("tighter_sources only returns bindable_accuracy_aggregate matches");
                 ReplacementSubDAG {
                     strategy: self.name(),
-                    replacement: Replacement::Rewrite(Rc::clone(source)),
+                    replacement: Replacement::SubDAG(Rc::clone(source)),
                     provenance: ReplacementProvenance::AccuracyReconciliation,
                     rationale: format!(
                         "reuses a near-duplicate sibling aggregate — identical intent and grouping \
@@ -391,9 +391,9 @@ impl ReplacementStrategy for AccuracyReconciliationStrategy {
 mod tests {
     use super::*;
     use crate::cost_model::{CostModel, DefaultCostModel};
+    use asap_types::ir::cse::share_common_sub_dags;
+    use asap_types::ir::operator_properties::{GroupKeys, Source};
     use asap_types::post_asap::SketchAlgorithm;
-    use asap_types::pre_asap::cse::share_common_sub_dags;
-    use asap_types::pre_asap::query_expr::{GroupKeys, Source};
     use asap_types::pre_asap::schema::{ColumnId, DataType, Field, Schema};
 
     /// `[ts(0), value(1), job(2)]`.
@@ -401,8 +401,8 @@ mod tests {
     /// willing to hoist it — see `Schema::has_unique_key`/`cse.rs`'s own
     /// "Legality" section: a producer with no provable unique key is always
     /// inserted fresh, never hoisted, regardless of structural equality.
-    fn metric_scan() -> Rc<QueryExpr> {
-        Rc::new(QueryExpr::Scan {
+    fn metric_scan() -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: Source::TimeSeries { metric: "m".into() },
             predicates: vec![],
             schema: Schema::with_time_index(
@@ -414,21 +414,23 @@ mod tests {
                 0,
                 vec![vec![0]],
             ),
-        })
+        }))
+        .unwrap()
     }
 
-    fn agg(by: Vec<ColumnId>, intent: AggIntent, child: &Rc<QueryExpr>) -> Rc<QueryExpr> {
-        Rc::new(QueryExpr::Aggregate {
+    fn agg(by: Vec<ColumnId>, intent: AggIntent, child: &Rc<OperatorNode>) -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
             reduction: Reduction::by(by),
             measures: vec![intent],
             output_names: vec![],
             filters: vec![],
             having: None,
             child: Rc::clone(child),
-        })
+        }))
+        .unwrap()
     }
 
-    fn quantile(q: f64, accuracy: AccuracyTarget, child: &Rc<QueryExpr>) -> Rc<QueryExpr> {
+    fn quantile(q: f64, accuracy: AccuracyTarget, child: &Rc<OperatorNode>) -> Rc<OperatorNode> {
         agg(
             vec![2],
             AggIntent::Quantile {
@@ -441,10 +443,14 @@ mod tests {
     }
 
     /// A globally-grouped (`by(vec![])`) quantile — `aggregate_output_schema`
-    /// reports no unique key for an empty `by` (see `query_expr.rs`'s own
+    /// reports no unique key for an empty `by` (see `aggregate_schema.rs`'s own
     /// `unique_keys = if by.is_empty() || has_count_values { vec![] } else
     /// { .. }`).
-    fn global_quantile(q: f64, accuracy: AccuracyTarget, child: &Rc<QueryExpr>) -> Rc<QueryExpr> {
+    fn ungrouped_quantile(
+        q: f64,
+        accuracy: AccuracyTarget,
+        child: &Rc<OperatorNode>,
+    ) -> Rc<OperatorNode> {
         agg(
             vec![],
             AggIntent::Quantile {
@@ -463,9 +469,9 @@ mod tests {
         q: f64,
         accuracy: AccuracyTarget,
         excluded: Vec<ColumnId>,
-        child: &Rc<QueryExpr>,
-    ) -> Rc<QueryExpr> {
-        Rc::new(QueryExpr::Aggregate {
+        child: &Rc<OperatorNode>,
+    ) -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
             reduction: Reduction::Reduce(GroupKeys::without(excluded)),
             measures: vec![AggIntent::Quantile {
                 col: None,
@@ -476,7 +482,8 @@ mod tests {
             filters: vec![],
             having: None,
             child: Rc::clone(child),
-        })
+        }))
+        .unwrap()
     }
 
     // ── dominates / strictly_tighter ─────────────────────────────────────
@@ -548,7 +555,7 @@ mod tests {
         assert!(strategy.matches(&TargetSubDAG::new(&loose)));
         let replacements = strategy.replacements(&TargetSubDAG::new(&loose));
         assert_eq!(replacements.len(), 1);
-        let Replacement::Rewrite(rc) = &replacements[0].replacement else {
+        let Replacement::SubDAG(rc) = &replacements[0].replacement else {
             panic!("expected a Rewrite candidate");
         };
         assert!(Rc::ptr_eq(rc, &tight));
@@ -580,7 +587,7 @@ mod tests {
         assert!(
             loose_group.candidates.iter().any(|candidate| {
                 candidate.strategy == "AccuracyReconciliationStrategy"
-                    && matches!(candidate.replacement, Replacement::Rewrite(_))
+                    && matches!(candidate.replacement, Replacement::SubDAG(_))
             }),
             "expected an AccuracyReconciliationStrategy candidate for the looser consumer, got: \
              {:?}",
@@ -661,7 +668,7 @@ mod tests {
     // ── exact structural equality / share_common_sub_dags is unchanged ────
 
     #[test]
-    fn share_common_sub_dags_still_never_merges_differing_accuracy() {
+    fn share_common_subdags_still_never_merges_differing_accuracy() {
         // The additive guarantee this issue explicitly must not violate:
         // pre-ASAP CSE's own exact-equality merge stays exact. Two
         // aggregates differing only in `accuracy` must come back as two
@@ -669,8 +676,8 @@ mod tests {
         // is the *only* place cross-accuracy sharing gets proposed, never
         // `share_common_sub_dags` itself.
         let scan = metric_scan();
-        let a = (*quantile(0.99, AccuracyTarget::Epsilon(0.01), &scan)).clone();
-        let b = (*quantile(0.99, AccuracyTarget::Epsilon(0.05), &scan)).clone();
+        let a = quantile(0.99, AccuracyTarget::Epsilon(0.01), &scan);
+        let b = quantile(0.99, AccuracyTarget::Epsilon(0.05), &scan);
 
         let roots = share_common_sub_dags(vec![("a", a), ("b", b)]);
         assert!(
@@ -684,10 +691,10 @@ mod tests {
 
         // The identical scan child, though, is still shared exactly as
         // before — this module changes nothing about that.
-        let QueryExpr::Aggregate { child: child_a, .. } = roots[0].1.as_ref() else {
+        let Some(NonASAPOp::Aggregate { child: child_a, .. }) = roots[0].1.non_asap() else {
             panic!("expected an Aggregate root");
         };
-        let QueryExpr::Aggregate { child: child_b, .. } = roots[1].1.as_ref() else {
+        let Some(NonASAPOp::Aggregate { child: child_b, .. }) = roots[1].1.non_asap() else {
             panic!("expected an Aggregate root");
         };
         assert!(Rc::ptr_eq(child_a, child_b));
@@ -700,8 +707,8 @@ mod tests {
         // exact equality — unrelated to this module, but pins the contrast
         // with the test above.
         let scan = metric_scan();
-        let a = (*quantile(0.99, AccuracyTarget::Epsilon(0.01), &scan)).clone();
-        let b = (*quantile(0.99, AccuracyTarget::Epsilon(0.01), &scan)).clone();
+        let a = quantile(0.99, AccuracyTarget::Epsilon(0.01), &scan);
+        let b = quantile(0.99, AccuracyTarget::Epsilon(0.01), &scan);
 
         let roots = share_common_sub_dags(vec![("a", a), ("b", b)]);
         assert!(Rc::ptr_eq(&roots[0].1, &roots[1].1));
@@ -717,11 +724,11 @@ mod tests {
         // `share_common_sub_dags`/`RollupStrategy` apply, which this
         // strategy must not bypass (module docs, point 5).
         let scan = metric_scan();
-        let tight = global_quantile(0.99, AccuracyTarget::Epsilon(0.01), &scan);
-        let loose = global_quantile(0.99, AccuracyTarget::Epsilon(0.05), &scan);
+        let tight = ungrouped_quantile(0.99, AccuracyTarget::Epsilon(0.01), &scan);
+        let loose = ungrouped_quantile(0.99, AccuracyTarget::Epsilon(0.05), &scan);
 
         assert!(
-            !tight.output_schema().unwrap().has_unique_key(),
+            !tight.schema.clone().has_unique_key(),
             "fixture sanity: a globally-grouped aggregate has no provable unique key"
         );
 
@@ -741,7 +748,7 @@ mod tests {
         let loose = without_quantile(0.99, AccuracyTarget::Epsilon(0.05), vec![2], &scan);
 
         assert!(
-            !tight.output_schema().unwrap().has_unique_key(),
+            !tight.schema.clone().has_unique_key(),
             "fixture sanity: a without(...) aggregate has no provable unique key"
         );
 
@@ -831,7 +838,7 @@ mod tests {
             "global_selection must commit to some candidate for a single-consumer looser target"
         );
         // With no recompute term at all (it never rebuilds `target`), this
-        // candidate strictly undercuts every SketchAlgorithmStrategy
+        // candidate strictly undercuts every ASAPStrategies
         // candidate (which each pay a recompute term on top of their own
         // maintenance term) under DefaultCostModel's numbers — the sane
         // direction: reading an already-necessary sibling should be able to
diff --git a/crates/asap-aware-mapping/src/analytical_cost.rs b/crates/asap-aware-mapping/src/analytical_cost.rs
index ad921d23a..8256d6f10 100644
--- a/crates/asap-aware-mapping/src/analytical_cost.rs
+++ b/crates/asap-aware-mapping/src/analytical_cost.rs
@@ -2970,7 +2970,7 @@ mod tests {
     }
 
     fn comparison_scope() -> ComparisonScope {
-        use asap_types::pre_asap::query_expr::Source;
+        use asap_types::ir::operator_properties::Source;
         use asap_types::workload::{
             DurationMs, QueryRecurrence, QueryTimeScope, RepeatedDemand, RepetitionInterval,
             TimeSelection, TimestampMs,
@@ -3009,9 +3009,7 @@ mod tests {
 
     #[test]
     fn comparison_rejects_different_snapshot_predicate_time_or_horizon() {
-        use std::rc::Rc;
-
-        use asap_types::pre_asap::query_expr::{Predicate, QueryExpr};
+        use asap_types::ir::{Predicate, ScalarExpr};
         use asap_types::workload::{DurationMs, TimestampMs};
 
         let raw = comparison_scope();
@@ -3027,7 +3025,7 @@ mod tests {
         candidate = raw.clone();
         candidate.sources[0]
             .predicates
-            .push(Predicate(Rc::new(QueryExpr::promql_scalar(1.0))));
+            .push(Predicate(ScalarExpr::literal_f64(1.0)));
         assert_eq!(
             validate_comparison_scopes(&raw, &candidate),
             Err(AnalyticalCostError::ComparisonScopeMismatch("sources"))
@@ -3247,7 +3245,7 @@ mod tests {
             operator: PhysicalOperator::Scan,
             children: vec![],
             scan_selection: Some(ScanSelection {
-                source: asap_types::pre_asap::query_expr::Source::Table {
+                source: asap_types::ir::operator_properties::Source::Table {
                     table_ref: "other_metrics".into(),
                 },
                 source_snapshot_id: "catalog-version-42".into(),
@@ -3312,7 +3310,7 @@ mod tests {
         let mut scope = comparison_scope();
         let coverage = scope.sources[0].clone();
         scope.sources.push(ScanSelection {
-            source: asap_types::pre_asap::query_expr::Source::Table {
+            source: asap_types::ir::operator_properties::Source::Table {
                 table_ref: "auxiliary".into(),
             },
             source_snapshot_id: "catalog-version-42".into(),
diff --git a/crates/asap-aware-mapping/src/cost_model.rs b/crates/asap-aware-mapping/src/cost_model.rs
index 0315e88f1..9fc170666 100644
--- a/crates/asap-aware-mapping/src/cost_model.rs
+++ b/crates/asap-aware-mapping/src/cost_model.rs
@@ -26,7 +26,7 @@
 //! than overloading these ones across incompatible `Kind`/`Params` types.
 //!
 //! Every entry point that doesn't take an explicit `&dyn CostModel`
-//! ([`SketchAlgorithmStrategy::default_cost_model`](crate::replacement::SketchAlgorithmStrategy::default_cost_model),
+//! ([`ASAPStrategies::default_cost_model`](crate::replacement::ASAPStrategies::default_cost_model),
 //! [`search_workload`](crate::replacement::search_workload)) runs against
 //! [`DefaultCostModel`], so a deployment that never plugs in its own cost
 //! model keeps today's static-preference-order behavior exactly, byte for
@@ -36,7 +36,7 @@
 //!
 //! [`CseCandidate`]/[`ShareDecision`]/[`CostModel::cse_share_decision`] below
 //! decide whether a CSE-detected shared sub-DAG
-//! ([`asap_types::pre_asap::cse::share_common_sub_dags`], issue #223 stages
+//! ([`asap_types::ir::cse::share_common_sub_dags`], issue #223 stages
 //! 1-2, PR #235) is actually worth sharing, via a real Volcano/Cascades-style
 //! cost comparison rather than a fixed rule. See
 //! `docs/design_docs/cse-cost-model-decision.md` for the full design discussion (why
@@ -48,14 +48,14 @@
 
 use std::rc::Rc;
 
+use crate::exact_composition::ExactOperation;
+use asap_types::ir::{ASAPOp, Operator, OperatorNode};
 use asap_types::post_asap::{
-    ExactOperation, FieldDataType, GroupingStrategy, HydraParams, ResultGuarantee, SketchAlgorithm,
-    SketchParams, SketchStatistic, SummaryExpr, SummaryMaintenanceLifecycleGuarantee, SummaryNode,
-    SummaryWindowFramework,
+    FieldDataType, GroupingStrategy, HydraParams, ResultGuarantee, SketchAlgorithm, SketchParams,
+    SketchStatistic, SummaryMaintenanceLifecycleGuarantee, SummaryWindowFramework,
 };
 use asap_types::pre_asap::agg_intent::AggIntent;
 use asap_types::pre_asap::expr_ir::ColumnRef;
-use asap_types::pre_asap::query_expr::QueryExpr;
 use asap_types::types::AccuracyTarget;
 
 use crate::exact_composition::{ExactComposition, OperationPlacement};
@@ -94,7 +94,7 @@ pub struct CostProvenance {
 /// operator on the update path must never be handed one.
 #[derive(Debug, Clone, Copy, PartialEq, Eq, Default)]
 pub struct ValueOperationCapabilities {
-    /// The runtime can apply an exact operator to summary readouts at
+    /// The runtime can apply an exact operator to summary evaluations at
     /// query evaluation time.
     pub query_time: bool,
     /// The runtime can apply an exact row transform on the update path,
@@ -127,17 +127,17 @@ impl ValueOperationCapabilities {
 /// composes with.
 #[derive(Debug, Clone, Copy)]
 pub struct ExactCompositionCostRequest<'a> {
-    /// The pre-ASAP target the composed candidate replaces.
-    pub target: &'a QueryExpr,
+    /// The target the composed candidate replaces.
+    pub target: &'a OperatorNode,
     /// The composition itself — placement, operator, child target.
     pub composition: &'a ExactComposition,
     /// For [`OperationPlacement::Read`]: the child target's *selected*
-    /// summary readout candidate the exact operator consumes. For
+    /// summary evaluation candidate the exact operator consumes. For
     /// [`OperationPlacement::Maintenance`]: the maintained summary *above* the
     /// transform that consumes its output (the `SummaryAgg` this transform
     /// feeds). Either way, the summary whose maintenance/read cost the
     /// formula charges.
-    pub summary: &'a SummaryNode,
+    pub summary: &'a OperatorNode,
     /// How many times this site actually runs once ancestors' own choices
     /// are accounted for (see `CandidateLogicalASAPDAGs::global_selection`).
     pub effective_consumer_count: usize,
@@ -147,11 +147,11 @@ pub struct ExactCompositionCostRequest<'a> {
 /// optional: **an unknown stays `None` — never a zero** — so a formula
 /// with a missing input yields no rate at all rather than a spuriously
 /// cheap one, and global selection then keeps the conservative
-/// `KeepPreAsap` behavior. A deployment model that wants defaults supplies
+/// keep-as-is behavior. A deployment model that wants defaults supplies
 /// them explicitly by overriding [`CostModel::exact_composition_cost_inputs`].
 #[derive(Debug, Clone, PartialEq)]
 pub struct ExactCompositionCostInputs {
-    /// Exact operator cost per row it processes — per readout row for a
+    /// Exact operator cost per row it processes — per evaluation row for a
     /// read-time operation, per input row for an maintenance-time operation.
     pub exact_cost_per_row: Option<f64>,
     /// Rows the exact operator consumes per evaluation (read-time operation) or
@@ -161,14 +161,14 @@ pub struct ExactCompositionCostInputs {
     pub expected_output_rows: Option<f64>,
     /// Cost of one update to the composed-with summary's maintained state.
     pub summary_maintenance_cost_per_update: Option<f64>,
-    /// Cost of one readout of that summary at evaluation time.
+    /// Cost of one evaluation of that summary at evaluation time.
     pub summary_read_cost: Option<f64>,
     /// Update (ingest) events per second reaching this site.
     pub update_rate: Option<f64>,
     /// Evaluations per second across every consumer of this site.
     pub evaluation_rate: Option<EvaluationRate>,
     /// Cost of one full raw recompute of the target from pre-ASAP data —
-    /// the `KeepPreAsap` baseline's per-evaluation cost.
+    /// the kept-query baseline's per-evaluation cost.
     pub raw_recompute_cost: Option<f64>,
     /// Recurring formulas require `CostUnitsPerSecond`; totals yield no rate.
     pub unit: CostUnit,
@@ -271,16 +271,16 @@ fn finite_rate(units_per_second: f64) -> Option<CostRate> {
 /// [`CandidateLogicalASAPDAGs::cost_sorted`](crate::replacement::CandidateLogicalASAPDAGs::cost_sorted)
 /// (via [`crate::replacement`]'s own `cse_preference`) the first time it
 /// needs a representative bound node for a sub-DAG that
-/// [`asap_types::pre_asap::cse::share_common_sub_dags`] already collapsed
+/// [`asap_types::ir::cse::share_common_sub_dags`] already collapsed
 /// onto one `Rc` for two or more workload roots. See
 /// `docs/design_docs/cse-cost-model-decision.md`.
 pub struct CseCandidate<'a> {
-    /// The shared pre-ASAP sub-DAG itself.
-    pub sub_dag: &'a QueryExpr,
-    /// The `SummaryNode` this sub-DAG bound to — gives the cost model the
+    /// The shared sub-DAG itself.
+    pub sub_dag: &'a Rc<OperatorNode>,
+    /// The node this sub-DAG bound to — gives the cost model the
     /// concrete `FieldDataType`/`(kind, params)` actually at stake, not
-    /// just the pre-ASAP shape.
-    pub bound_summary: &'a SummaryNode,
+    /// just the logical shape.
+    pub bound_summary: &'a OperatorNode,
     /// How many workload roots reference this exact shared sub-DAG, counted
     /// once up front over the whole workload (always >= 2 — a candidate is
     /// only ever constructed for an actually-shared sub-DAG).
@@ -302,7 +302,7 @@ pub struct Cost(pub f64);
 /// node. Node identity is preserved so whole-DAG models can bind per-state
 /// evidence without relying on traversal order.
 pub struct CostedSummaryDeployment<'a> {
-    pub summary: &'a SummaryNode,
+    pub summary: &'a OperatorNode,
     pub guarantee: &'a SummaryMaintenanceLifecycleGuarantee,
     pub selected_cost: Cost,
 }
@@ -359,7 +359,7 @@ impl std::ops::Mul<usize> for Cost {
 /// [`CseCandidate`].
 #[derive(Debug, Clone, Copy, PartialEq, Eq)]
 pub enum ShareDecision {
-    /// Reuse one bound `SummaryNode` across every consumer.
+    /// Reuse one bound node across every consumer.
     Share,
     /// Bind each occurrence independently — the shared-maintenance cost
     /// isn't worth it for this candidate.
@@ -367,23 +367,23 @@ pub enum ShareDecision {
 }
 
 /// Default [`CostModel::cse_recompute_cost`]: a structural-size proxy — the
-/// number of *unique* nodes in `sub_dag`'s DAG
-/// ([`asap_types::pre_asap::cse::dag_node_count`], the same module this
+/// number of *unique* nodes in `sub-DAG`'s DAG
+/// ([`asap_types::ir::cse::dag_node_count`], the same module this
 /// candidate's sharing was detected in). Deliberately **not** a raw
-/// `serde_json` serialization length: after CSE, `sub_dag` generally has
-/// internal sharing (a `CseCandidate` only exists because something got
+/// `serde_json` serialization length: after CSE, `sub-DAG` is generally a
+/// DAG, not a tree (a `CseCandidate` only exists because something got
 /// shared), and a naive full serialization re-serializes — over-counts —
-/// any descendant `sub_dag` already shares internally, once per parent
+/// any descendant `sub-DAG` already shares internally, once per parent
 /// that references it, instead of once for the whole DAG. `dag_node_count`
 /// dedupes by `Rc` pointer identity, so it charges each unique node's
 /// contribution exactly once regardless of how many places within
-/// `sub_dag` reference it. Cheap to compute (one pass, no serialization),
+/// `sub-DAG` reference it. Cheap to compute (one pass, no serialization),
 /// and still scales with real structural complexity — a genuinely tiny
 /// leaf costs little to recompute, a deep multi-join sub-DAG costs a lot.
 /// A deployment with real per-row/per-update cost knowledge should
 /// override [`CostModel::cse_recompute_cost`] instead of relying on this.
-pub fn default_cse_recompute_cost(sub_dag: &QueryExpr) -> Cost {
-    Cost(asap_types::pre_asap::cse::dag_node_count(sub_dag) as f64)
+pub fn default_cse_recompute_cost(sub_dag: &Rc<OperatorNode>) -> Cost {
+    Cost(asap_types::ir::cse::dag_node_count(sub_dag) as f64)
 }
 
 /// Default [`CostModel::cse_shared_maintenance_cost`]: a small
@@ -506,7 +506,7 @@ pub trait CostModel {
     /// Estimated number of distinct subpopulations produced by `target`'s
     /// grouping keys. `None` means the deployment has no cardinality estimate;
     /// grouping alternatives remain legal but keep their discovery order.
-    fn estimated_subpopulation_count(&self, _target: &QueryExpr) -> Option<usize> {
+    fn estimated_subpopulation_count(&self, _target: &OperatorNode) -> Option<usize> {
         None
     }
 
@@ -518,7 +518,7 @@ pub trait CostModel {
         candidate: &ReplacementSubDAG,
         target: &TargetSubDAG<'_>,
     ) -> Option<Cost> {
-        let Replacement::Summary(node) = &candidate.replacement else {
+        let Replacement::SubDAG(node) = &candidate.replacement else {
             return None;
         };
         let (kind, grouping) = sketch_state(node)?;
@@ -545,17 +545,17 @@ pub trait CostModel {
         Realization::PassThrough
     }
 
-    /// Build the `SummaryEstimate` readout for an `Extension` intent this
+    /// Build the `SummaryEstimate` evaluation for an `Extension` intent this
     /// same `CostModel` realized as `Realization::Sketch` via
     /// [`realize_extension`](Self::realize_extension). Only ever called
     /// when `realize_extension` returned `Sketch` for the same
-    /// `(ext_kind, payload)` — `replacement::readout` has no other way to build a
+    /// `(ext_kind, payload)` — `replacement::evaluation` has no other way to build a
     /// `SketchStatistic` for a shape core doesn't know. A deployment that
     /// overrides `realize_extension` to return `Sketch` for some
     /// `ext_kind` MUST also override this for that same `ext_kind`, or
     /// this default panics loudly (rather than silently misinterpreting
     /// `payload`) the first time that intent is actually read out.
-    fn readout_extension(
+    fn evaluation_extension(
         &self,
         ext_kind: &str,
         _payload: &serde_json::Value,
@@ -563,11 +563,11 @@ pub trait CostModel {
     ) -> SketchStatistic {
         unimplemented!(
             "CostModel::realize_extension returned Sketch for ext_kind={ext_kind:?} but \
-             readout_extension wasn't overridden to match"
+             evaluation_extension wasn't overridden to match"
         )
     }
 
-    /// Estimate the one-time cost of recomputing `candidate.sub_dag`
+    /// Estimate the one-time cost of recomputing `candidate.sub-DAG`
     /// independently at a single use site. Default:
     /// [`default_cse_recompute_cost`] (a structural-size proxy). See
     /// `docs/design_docs/cse-cost-model-decision.md`.
@@ -581,7 +581,7 @@ pub trait CostModel {
     /// weight table), applied to whichever field of
     /// `candidate.bound_summary`'s output schema actually carries summary
     /// state (falls back to the cheapest, `Plain`, weight if none does —
-    /// e.g. `bound_summary` is a passthrough `KeepPreAsap` node with nothing
+    /// e.g. `bound_summary` is a kept non-ASAP sub-DAG with nothing
     /// summary-shaped to maintain). See `docs/design_docs/cse-cost-model-decision.md`.
     fn cse_shared_maintenance_cost(&self, candidate: &CseCandidate) -> Cost {
         let family = candidate
@@ -598,7 +598,7 @@ pub trait CostModel {
         default_cse_shared_maintenance_cost(&family)
     }
 
-    /// Decide whether to reuse one shared `SummaryNode` across every
+    /// Decide whether to reuse one shared node across every
     /// consumer of `candidate`, or bind each occurrence independently — a
     /// Volcano/Cascades-style cost comparison (issue #237, #223 stage 4; see
     /// `docs/design_docs/cse-cost-model-decision.md`): share iff the estimated cost of
@@ -666,7 +666,7 @@ pub trait CostModel {
         Cost(1.0)
     }
 
-    /// Cost of recomputing `candidate.sub_dag` once, from the pre-ASAP/raw
+    /// Cost of recomputing `candidate.sub-DAG` once, from the pre-ASAP/raw
     /// path. Units: cost units per recomputation — the `raw_recompute_cost`
     /// term of `recompute_cost_rate`. Default: delegates to
     /// [`cse_recompute_cost`](Self::cse_recompute_cost) (the same
@@ -738,21 +738,21 @@ pub trait CostModel {
     /// on [`CandidateLogicalASAPDAGs::cost_sorted`](crate::replacement::CandidateLogicalASAPDAGs::cost_sorted)),
     /// not just order candidates against each other — that ordering job
     /// already belongs to [`rank_candidates`](Self::rank_candidates) (for a
-    /// [`SketchAlgorithmStrategy`](crate::replacement::SketchAlgorithmStrategy)
+    /// [`ASAPStrategies`](crate::replacement::ASAPStrategies)
     /// group) and [`cse_share_decision`](Self::cse_share_decision) (for a
     /// [`SharedSubDAGStrategy`](crate::replacement::SharedSubDAGStrategy)
     /// group).
     ///
     /// One method covers both candidate shapes this crate ships:
-    /// `candidate.replacement`'s [`Replacement::Summary`] arm (a
-    /// `SketchAlgorithmStrategy` candidate — the bound `SummaryNode` is right
-    /// there, nothing to reconstruct) and its [`Replacement::Rewrite`] arm
+    /// `candidate.replacement`'s [`Replacement::SubDAG`] from a summary
+    /// realization (a `ASAPStrategies` candidate — the bound node is
+    /// right there, nothing to reconstruct) and the same arm from a rewrite
     /// (a `SharedSubDAGStrategy` share-vs-recompute candidate — no bound
-    /// `SummaryNode` of its own, since sharing is a decision about a target
+    /// summary of its own, since sharing is a decision about a target
     /// already bound some other way; a representative binding is recovered
     /// from `target` itself). `target` is threaded through explicitly
     /// (rather than only ever the target embedded in `candidate` — there
-    /// isn't one for a `Rewrite`) so both arms have the `consumer_count`
+    /// isn't one for a rewrite) so both arms have the `consumer_count`
     /// context a cost estimate needs to be meaningful.
     ///
     /// Default: **not a real cost model** — always returns `f64::NAN`.
@@ -776,7 +776,7 @@ pub trait CostModel {
     /// optimistic zeroes.
     fn summary_maintenance_lifecycle_cost_inputs(
         &self,
-        _summary: &SummaryNode,
+        _summary: &OperatorNode,
     ) -> SummaryMaintenanceLifecycleCostInputs {
         SummaryMaintenanceLifecycleCostInputs::default()
     }
@@ -786,7 +786,7 @@ pub trait CostModel {
     /// rate so the horizon integral equals one peak-capacity charge.
     fn summary_maintenance_lifecycle_cost_inputs_for_horizon(
         &self,
-        summary: &SummaryNode,
+        summary: &OperatorNode,
         _horizon: Option<Horizon>,
     ) -> SummaryMaintenanceLifecycleCostInputs {
         self.summary_maintenance_lifecycle_cost_inputs(summary)
@@ -796,7 +796,7 @@ pub trait CostModel {
     /// conservative default advertises no long-lived maintenance capability.
     fn summary_maintenance_capabilities(
         &self,
-        _summary: &SummaryNode,
+        _summary: &OperatorNode,
     ) -> SummaryMaintenanceCapabilities {
         SummaryMaintenanceCapabilities::default()
     }
@@ -807,8 +807,8 @@ pub trait CostModel {
     /// must not then reuse the partial per-state sum.
     fn complete_summary_candidate_cost(
         &self,
-        _root: &SummaryNode,
-        _target: Option<&QueryExpr>,
+        _root: &OperatorNode,
+        _target: Option<&OperatorNode>,
         deployments: &[CostedSummaryDeployment<'_>],
         _horizon: Option<Horizon>,
         _expected_reads: Option<f64>,
@@ -827,8 +827,8 @@ pub trait CostModel {
     /// that do not perform either decision.
     fn complete_summary_candidate_estimate(
         &self,
-        root: &SummaryNode,
-        target: Option<&QueryExpr>,
+        root: &OperatorNode,
+        target: Option<&OperatorNode>,
         deployments: &[CostedSummaryDeployment<'_>],
         horizon: Option<Horizon>,
         expected_reads: Option<f64>,
@@ -861,7 +861,7 @@ pub trait CostModel {
     /// Cost of evaluating `target` directly from its logical/raw inputs once.
     /// When known, lifecycle-aware materialization compares this fallback with
     /// the aggregate cost of the selected summary deployments.
-    fn raw_query_recompute_cost(&self, _target: &QueryExpr) -> Option<Cost> {
+    fn raw_query_recompute_cost(&self, _target: &OperatorNode) -> Option<Cost> {
         None
     }
 
@@ -870,7 +870,7 @@ pub trait CostModel {
     /// cardinality changes between evaluations.
     fn raw_query_recompute_total_cost(
         &self,
-        target: &QueryExpr,
+        target: &OperatorNode,
         expected_reads: f64,
     ) -> Option<Cost> {
         self.raw_query_recompute_cost(target)
@@ -879,7 +879,7 @@ pub trait CostModel {
     /// Physical feasibility evidence for a complete summary candidate.
     /// `None` defers admission to physical/deployment compilation; `Some(false)`
     /// excludes the candidate without changing its computation or parameters.
-    fn summary_support_evidence(&self, _summary: &SummaryNode) -> Option<bool> {
+    fn summary_support_evidence(&self, _summary: &OperatorNode) -> Option<bool> {
         None
     }
 
@@ -932,7 +932,7 @@ pub trait CostModel {
     ///
     /// Default: every input unknown ([`ExactCompositionCostInputs::unknown`])
     /// — unknown is never zero, and with no rate derivable
-    /// `CandidateLogicalASAPDAGs::global_selection` keeps the conservative `KeepPreAsap`
+    /// `CandidateLogicalASAPDAGs::global_selection` keeps the conservative keep-as-is
     /// behavior for the site. A deployment that wants defaults must supply
     /// them here explicitly.
     fn exact_composition_cost_inputs(
@@ -948,14 +948,16 @@ pub trait CostModel {
 }
 
 fn sketch_state(
-    node: &SummaryNode,
+    node: &OperatorNode,
 ) -> Option<(&asap_types::post_asap::SketchKind, &GroupingStrategy)> {
-    match &node.expr {
-        SummaryExpr::SummaryEstimate { summary_input, .. } => sketch_state(summary_input),
-        SummaryExpr::SummaryAgg {
+    match &node.operator {
+        Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) => {
+            sketch_state(summary_input)
+        }
+        Operator::ASAP(ASAPOp::SummaryAgg {
             family: FieldDataType::Sketch(kind, grouping),
             ..
-        } => Some((kind, grouping)),
+        }) => Some((kind, grouping)),
         _ => None,
     }
 }
@@ -1027,15 +1029,17 @@ impl CostModel for DefaultCostModel {
     /// `cse_share_decision`'s default body already composes — rather than a
     /// second formula:
     ///
-    /// - [`Replacement::Summary`]: `cse_recompute_cost` (the one-time
+    /// - A [`ReplacementProvenance::SummaryRealization`] candidate (a
+    ///   `ASAPStrategies` binding): `cse_recompute_cost` (the one-time
     ///   structural cost of building `target` at all) plus
     ///   `cse_shared_maintenance_cost` of the candidate's own bound family
     ///   (a pricier family — a sketch over an exact accumulator, say —
     ///   costs more here, consistent with the per-family weighting
     ///   [`default_cse_shared_maintenance_cost`] already orders candidates
     ///   by).
-    /// - [`Replacement::Rewrite`]: recovers one representative bound
-    ///   `SummaryNode` for `target` via `realize_child` (the same
+    /// - Any other [`Replacement::SubDAG`] (a logical rewrite or a CSE
+    ///   share/recompute candidate): recovers one
+    ///   representative bound node for `target` via `realize_child` (the same
     ///   rank-and-take-first helper `replacement::realize_child` reuses for the
     ///   identical need), then charges
     ///   `cse_shared_maintenance_cost` for the candidate that shares
@@ -1060,7 +1064,9 @@ impl CostModel for DefaultCostModel {
     fn estimate_cost(&self, candidate: &ReplacementSubDAG, target: &TargetSubDAG<'_>) -> f64 {
         let consumer_count = target.consumer_count.max(1);
         match &candidate.replacement {
-            Replacement::Summary(node) => {
+            Replacement::SubDAG(node)
+                if candidate.provenance == ReplacementProvenance::SummaryRealization =>
+            {
                 let cse = CseCandidate {
                     sub_dag: target.root,
                     bound_summary: node,
@@ -1068,7 +1074,7 @@ impl CostModel for DefaultCostModel {
                 };
                 (self.cse_recompute_cost(&cse) + self.cse_shared_maintenance_cost(&cse)).0
             }
-            Replacement::Rewrite(rc)
+            Replacement::SubDAG(rc)
                 if candidate.provenance == ReplacementProvenance::AccuracyReconciliation =>
             {
                 let Ok(sibling_bound) = realize_child(rc, self) else {
@@ -1087,7 +1093,7 @@ impl CostModel for DefaultCostModel {
                 };
                 self.cse_shared_maintenance_cost(&cse).0
             }
-            Replacement::Rewrite(rc) => {
+            Replacement::SubDAG(rc) => {
                 let Ok(bound) = realize_child(target.root, self) else {
                     return f64::NAN;
                 };
@@ -1320,11 +1326,11 @@ mod tests {
         assert_eq!(
             DefaultCostModel.value_operation_support_evidence(
                 &ExactOperation::Aggregate {
-                    reduction: asap_types::pre_asap::query_expr::Reduction::by(vec![]),
+                    reduction: asap_types::ir::operator_properties::Reduction::by(vec![]),
                     measures: vec![AggIntent::Max { col: None }],
                     output_names: vec![],
-                    having: None,
                     filters: vec![],
+                    having: None,
                 },
                 OperationPlacement::Read,
             ),
@@ -1346,14 +1352,15 @@ mod tests {
 
     // ── CSE sharing (issue #237, #223 stage 4) ──────────────────────────
 
+    use asap_types::ir::operator_properties::Source;
+    use asap_types::ir::{NonASAPOp, Predicate, ScalarExpr};
     use asap_types::post_asap::{
-        ExactKind, ExactParams, Field, GroupingStrategy, Schema, SketchKind, SummaryExpr,
+        ExactKind, ExactParams, Field, GroupingStrategy, Schema, SketchKind,
     };
-    use asap_types::pre_asap::query_expr::Source;
     use asap_types::pre_asap::schema::DataType;
 
-    fn scan() -> QueryExpr {
-        QueryExpr::Scan {
+    fn scan() -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: Source::TimeSeries { metric: "m".into() },
             predicates: vec![],
             schema: Schema::with_time_index(
@@ -1364,37 +1371,39 @@ mod tests {
                 0,
                 vec![],
             ),
-        }
-    }
-
-    fn summary_node(family: FieldDataType) -> SummaryNode {
-        SummaryNode {
-            expr: SummaryExpr::SummaryAgg {
-                child: std::rc::Rc::new(SummaryNode {
-                    expr: SummaryExpr::KeepPreAsap(Rc::new(scan())),
-                    schema: Schema::lifted(vec![], None),
-                    guarantee: None,
+        }))
+        .unwrap()
+    }
+
+    /// A `SummaryAgg` directly over the kept `scan()` sub-DAG.
+    fn summary_node(family: FieldDataType) -> Rc<OperatorNode> {
+        std::rc::Rc::new(
+            OperatorNode::with_schema(
+                asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
+                    child: scan(),
+                    family: family.clone(),
+                    input: asap_types::post_asap::SummaryUpdate::column(
+                        asap_types::pre_asap::expr_ir::ColumnRef::Named("value".into()),
+                    ),
+                    reduction: asap_types::ir::operator_properties::Reduction::by(vec![]),
+                    grouping: GroupingStrategy::default(),
+                    filter: None,
                 }),
-                family: family.clone(),
-                input: asap_types::post_asap::SummaryUpdate::column(
-                    asap_types::pre_asap::expr_ir::ColumnRef::Named("value".into()),
-                ),
-                reduction: asap_types::pre_asap::query_expr::Reduction::by(vec![]),
-                grouping: GroupingStrategy::default(),
-                filter: None,
-            },
-            schema: Schema::lifted(vec![Field::new("state", family, false)], None),
-            guarantee: None,
-        }
+                Schema::lifted(vec![Field::new("state", family, false)], None),
+            )
+            .with_guarantee(None),
+        )
     }
 
     #[test]
     fn default_recompute_cost_is_positive_and_grows_with_structural_size() {
         let leaf = scan();
-        let nested = QueryExpr::Dedup {
-            cols: vec![0],
-            child: std::rc::Rc::new(leaf.clone()),
-        };
+        let nested =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Dedup {
+                cols: vec![0],
+                child: Rc::clone(&leaf),
+            }))
+            .unwrap();
         assert!(default_cse_recompute_cost(&leaf) > Cost::ZERO);
         assert!(default_cse_recompute_cost(&nested) > default_cse_recompute_cost(&leaf));
     }
@@ -1407,27 +1416,27 @@ mod tests {
     /// identity-blind recursive walk) would count it.
     #[test]
     fn default_recompute_cost_does_not_double_count_an_internally_shared_descendant() {
+        use asap_types::ir::operator_properties::JoinKind;
         use asap_types::pre_asap::expr_ir::ScalarValue;
-        use asap_types::pre_asap::query_expr::{JoinKind, Predicate};
 
-        let true_pred = || {
-            Predicate(std::rc::Rc::new(QueryExpr::Literal(ScalarValue::Boolean(
-                true,
-            ))))
-        };
-        let shared_leaf = std::rc::Rc::new(scan());
-        let no_sharing = QueryExpr::Join {
-            kind: JoinKind::Inner,
-            pred: true_pred(),
-            left: std::rc::Rc::new(scan()),
-            right: std::rc::Rc::new(scan()),
-        };
-        let with_sharing = QueryExpr::Join {
-            kind: JoinKind::Inner,
-            pred: true_pred(),
-            left: std::rc::Rc::clone(&shared_leaf),
-            right: std::rc::Rc::clone(&shared_leaf),
-        };
+        let true_pred = || Predicate(ScalarExpr::Literal(ScalarValue::Boolean(true)));
+        let shared_leaf = scan();
+        let no_sharing =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Join {
+                kind: JoinKind::Inner,
+                pred: true_pred(),
+                left: scan(),
+                right: scan(),
+            }))
+            .unwrap();
+        let with_sharing =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Join {
+                kind: JoinKind::Inner,
+                pred: true_pred(),
+                left: Rc::clone(&shared_leaf),
+                right: Rc::clone(&shared_leaf),
+            }))
+            .unwrap();
         assert_eq!(
             default_cse_recompute_cost(&no_sharing),
             Cost(3.0),
@@ -1555,20 +1564,20 @@ mod tests {
             }
         }
 
-        let root = Rc::new(scan());
+        let root = scan();
         let target = TargetSubDAG::new(&root);
         let candidate = ReplacementSubDAG {
             strategy: "TestStrategy",
-            replacement: Replacement::Summary(Rc::new(summary_node(FieldDataType::Plain(
+            replacement: Replacement::SubDAG(summary_node(FieldDataType::Plain(
                 asap_types::pre_asap::DataType::Float64,
-            )))),
+            ))),
             provenance: crate::replacement::ReplacementProvenance::SummaryRealization,
             rationale: "whatever".into(),
         };
         assert!(RankOnly.estimate_cost(&candidate, &target).is_nan());
     }
 
-    /// `DefaultCostModel::estimate_cost` for a [`Replacement::Summary`]
+    /// `DefaultCostModel::estimate_cost` for a summary-rooted [`Replacement::SubDAG`]
     /// candidate reuses [`default_cse_shared_maintenance_cost`]'s own
     /// per-family ordering: a candidate bound to a cheap-to-maintain family
     /// (an exact accumulator) must cost less than one bound to an
@@ -1578,25 +1587,26 @@ mod tests {
     /// above.
     #[test]
     fn estimate_cost_for_summary_orders_candidates_by_family_cheapest_to_priciest() {
-        let root = Rc::new(scan());
+        let root = scan();
         let target = TargetSubDAG::new(&root);
 
         let cheap = ReplacementSubDAG {
             strategy: "TestStrategy",
-            replacement: Replacement::Summary(Rc::new(summary_node(
-                FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum),
+            replacement: Replacement::SubDAG(summary_node(FieldDataType::ExactAggregate(
+                ExactKind::Sum,
+                ExactParams::Sum,
             ))),
             provenance: crate::replacement::ReplacementProvenance::SummaryRealization,
             rationale: "exact accumulator".into(),
         };
         let pricey = ReplacementSubDAG {
             strategy: "TestStrategy",
-            replacement: Replacement::Summary(Rc::new(summary_node(FieldDataType::StatModel(
+            replacement: Replacement::SubDAG(summary_node(FieldDataType::StatModel(
                 asap_types::post_asap::StatModelKind::Parametric,
                 asap_types::post_asap::StatModelParams::Parametric {
                     family: "gaussian_mixture".into(),
                 },
-            )))),
+            ))),
             provenance: crate::replacement::ReplacementProvenance::SummaryRealization,
             rationale: "fitted statistical model".into(),
         };
@@ -1614,7 +1624,7 @@ mod tests {
         );
     }
 
-    /// `DefaultCostModel::estimate_cost` for a [`Replacement::Rewrite`] pair
+    /// `DefaultCostModel::estimate_cost` for a relational [`Replacement::SubDAG`] pair
     /// (the `SharedSubDAGStrategy` share-vs-recompute shape) agrees with
     /// what `cse_share_decision` would already pick for the same target: with
     /// many consumers of a cheap-to-recompute leaf, the "share" candidate
@@ -1625,18 +1635,18 @@ mod tests {
     /// directly.
     #[test]
     fn estimate_cost_for_rewrite_prefers_sharing_when_recompute_dominates_maintenance() {
-        let target_root = Rc::new(scan());
+        let target_root = scan();
         let target = TargetSubDAG::with_consumer_count(&target_root, 20);
 
         let share = ReplacementSubDAG {
             strategy: "TestStrategy",
-            replacement: Replacement::Rewrite(Rc::clone(&target_root)),
+            replacement: Replacement::SubDAG(Rc::clone(&target_root)),
             provenance: crate::replacement::ReplacementProvenance::CseShare,
             rationale: "build once and share".into(),
         };
         let recompute = ReplacementSubDAG {
             strategy: "TestStrategy",
-            replacement: Replacement::Rewrite(Rc::new((*target_root).clone())),
+            replacement: Replacement::SubDAG(Rc::new((*target_root).clone())),
             provenance: crate::replacement::ReplacementProvenance::CseRecompute,
             rationale: "build independently".into(),
         };
diff --git a/crates/asap-aware-mapping/src/empirical_comparison.rs b/crates/asap-aware-mapping/src/empirical_comparison.rs
index ecd2a6cd4..17e3e9a82 100644
--- a/crates/asap-aware-mapping/src/empirical_comparison.rs
+++ b/crates/asap-aware-mapping/src/empirical_comparison.rs
@@ -41,7 +41,7 @@ pub struct OfflineExactMeasurement {
 }
 
 /// The companion format binds otherwise query-agnostic sketch primitives to
-/// their measured readout and exact reference. Bindings describe state after
+/// their measured evaluation and exact reference. Bindings describe state after
 /// ingestion, without merges or intervening updates during the read sequence.
 #[derive(Debug, Clone, Serialize, Deserialize)]
 #[serde(deny_unknown_fields)]
@@ -247,7 +247,9 @@ pub fn recommend_offline(
                 || error.query.get("value_type").and_then(|v| v.as_str())
                     != Some(request.query.value_type.as_str())
             {
-                return Err("offline error observation has incompatible readout semantics".into());
+                return Err(
+                    "offline error observation has incompatible evaluation semantics".into(),
+                );
             }
             if error.metric != request.accuracy.metric
                 || error.trials < request.accuracy.minimum_trials
@@ -802,14 +804,14 @@ mod tests {
             }
             assert!(recommend_offline(&evidence, &request).is_err(), "{case}");
         }
-        for case in ["metric", "trials", "binding", "readout"] {
+        for case in ["metric", "trials", "binding", "evaluation"] {
             let mut evidence = evidence.clone();
             let mut request = request.clone();
             match case {
                 "metric" => request.accuracy.metric = "rank_error".into(),
                 "trials" => request.accuracy.minimum_trials = 100,
                 "binding" => evidence.query_bindings.clear(),
-                "readout" => {
+                "evaluation" => {
                     for row in &mut evidence.sketch_evidence.records {
                         row.error.as_mut().unwrap().query["kind"] =
                             serde_json::json!("total_count");
diff --git a/crates/asap-aware-mapping/src/empirical_cost.rs b/crates/asap-aware-mapping/src/empirical_cost.rs
index b6d4f9a08..18d1d7ee4 100644
--- a/crates/asap-aware-mapping/src/empirical_cost.rs
+++ b/crates/asap-aware-mapping/src/empirical_cost.rs
@@ -2,9 +2,8 @@
 //! configuration and environment; they are neither runtime feedback nor proofs
 //! of an accuracy guarantee. CPU quantities are nanoseconds, never CPU operations.
 
-use asap_types::post_asap::{
-    FieldDataType, GroupingStrategy, SketchAlgorithm, SketchParams, SummaryExpr, SummaryNode,
-};
+use asap_types::ir::{ASAPOp, Operator, OperatorNode};
+use asap_types::post_asap::{FieldDataType, GroupingStrategy, SketchAlgorithm, SketchParams};
 use asap_types::pre_asap::AggIntent;
 use serde::{Deserialize, Serialize};
 
@@ -214,13 +213,13 @@ impl EmpiricalEvidenceProvider {
     /// mixed with an existing deployment's unitless or CPU-operation costs.
     pub fn lifecycle_cost_inputs(
         &self,
-        summary: &SummaryNode,
+        summary: &OperatorNode,
     ) -> SummaryMaintenanceLifecycleCostInputs {
-        let SummaryExpr::SummaryAgg {
+        let Operator::ASAP(ASAPOp::SummaryAgg {
             family: FieldDataType::Sketch(kind, GroupingStrategy::PerSubpopulationInstance),
             grouping: GroupingStrategy::PerSubpopulationInstance,
             ..
-        } = &summary.expr
+        }) = &summary.operator
         else {
             return SummaryMaintenanceLifecycleCostInputs::default();
         };
@@ -280,7 +279,7 @@ impl CostModel for EmpiricalCostModel {
 
     fn summary_maintenance_lifecycle_cost_inputs(
         &self,
-        summary: &SummaryNode,
+        summary: &OperatorNode,
     ) -> SummaryMaintenanceLifecycleCostInputs {
         self.provider.lifecycle_cost_inputs(summary)
     }
diff --git a/crates/asap-aware-mapping/src/exact_composition.rs b/crates/asap-aware-mapping/src/exact_composition.rs
index 54bce26f6..f48bc08b5 100644
--- a/crates/asap-aware-mapping/src/exact_composition.rs
+++ b/crates/asap-aware-mapping/src/exact_composition.rs
@@ -4,21 +4,23 @@
 //! `construct_summary_agg` already nests accumulator realizations, such as
 //! KLL over exact `Sum` state or a quantile over `Rate` state. This strategy
 //! covers the more general cases where an exact function must consume a
-//! summary readout, or where a maintained summary consumes the values of an
+//! summary evaluation, or where a maintained summary consumes the values of an
 //! exact function that has no accumulator realization.
 //!
-//! Both cases use the general [`SummaryExpr::ValueOperation`] node. Its
-//! semantic [`ValueOperation`] is independent from [`ExecutionTiming`], so
-//! adding a function does not require adding a new physical node type.
+//! Both cases use an ordinary `NonASAPOp::Aggregate` node over the child
+//! plan. The node carries no timing: it runs when its consumer runs, so the
+//! same operator serves both placements and adding a function does not
+//! require adding a new physical node type. [`OperationPlacement`] is the
+//! search-time placement choice.
 //!
 //! ## Reference, don't select
 //!
 //! A composed candidate needs a child plan to compose *with* — the inner
-//! quantile's own summary readout, say. This strategy deliberately does
+//! quantile's own summary evaluation, say. This strategy deliberately does
 //! **not** pick that child itself (the way `construct_summary_agg`'s
 //! `realize_child` takes the head of the child's own ranking): a
 //! [`Replacement::ExactComposition`] carries only the child *target*
-//! (`ExactComposition::child_target`, the same `Rc<QueryExpr>` whose
+//! (`ExactComposition::child_target`, the same `Rc<OperatorNode>` whose
 //! `TargetSubDAGCandidates` in `CandidateLogicalASAPDAGs` already holds every candidate for it). It is
 //! [`CandidateLogicalASAPDAGs::global_selection`](crate::replacement::CandidateLogicalASAPDAGs::global_selection)
 //! that commits the compatible parent/child pair — so the child's own
@@ -34,7 +36,7 @@
 //!
 //! - the target is a single-measure, `HAVING`-free exact aggregate;
 //! - read-time operation: the child is a bindable aggregate that has at least one
-//!   readout-producing summary implementation (a sketch/sample/wavelet/
+//!   evaluation-producing summary implementation (a sketch/sample/wavelet/
 //!   model — the shapes a maintained accumulator can't sit above), and the
 //!   target's grouping keys resolve in the child's output schema;
 //!   transform: the target is a per-entity exact function with no
@@ -58,18 +60,21 @@
 //! - Decide whether a composition is *worth it*: that is
 //!   `global_selection`'s job, using the issue's cost-units-per-second
 //!   formulas (see `crate::cost_model::read_operation_plan_cost_rate` and
-//!   siblings). Missing statistics keep the conservative `KeepPreAsap`.
+//!   siblings). Missing statistics keep the conservative kept sub-DAG.
 
+use asap_types::ir::non_asap::any_measure_filtered;
 use std::rc::Rc;
 
-use asap_types::post_asap::execution_data_state::validate_execution_data_states_at;
+use asap_types::ir::aggregate_schema::aggregate_output_schema;
+use asap_types::ir::operator_properties::Reduction;
+use asap_types::ir::timing::{planned_data_state, validate_default};
+use asap_types::ir::{NonASAPOp, Operator, OperatorNode, Predicate};
+use asap_types::post_asap::execution_data_state::lift_plain;
 use asap_types::post_asap::{
-    exact_operation_output_schema, produced_data_state, AccuracyError, ExactOperation,
-    ExecutionDataState, ExecutionDataStateError, ResultGuarantee, Schema, SummaryExpr, SummaryNode,
-    ValueOperation,
+    AccuracyError, ExactOperationSchemaError, ExecutionDataState, ExecutionDataStateError,
+    ResultGuarantee, Schema,
 };
 use asap_types::pre_asap::agg_intent::AggIntent;
-use asap_types::pre_asap::query_expr::{any_measure_filtered, QueryExpr, Reduction};
 use asap_types::types::AccuracyTarget;
 
 use crate::cost_model::CostModel;
@@ -84,9 +89,61 @@ use asap_types::post_asap::ExecutionTiming;
 
 /// Which side of the maintenance/read boundary an [`ExactComposition`]'s
 /// exact function executes on.
+/// The exact function an [`ExactComposition`] applies: the parameters of
+/// the `NonASAPOp::Aggregate` node the composition builds over its child.
+#[derive(Debug, Clone, PartialEq)]
+pub enum ExactOperation {
+    Aggregate {
+        reduction: Reduction,
+        measures: Vec<AggIntent>,
+        output_names: Vec<String>,
+        filters: Vec<Option<Predicate>>,
+        having: Option<Predicate>,
+    },
+}
+
+impl ExactOperation {
+    /// Output schema of this operation over a child whose edge carries
+    /// `input` — the same canonical derivation the pre-ASAP `Aggregate`
+    /// node uses. `Err` when the child carries non-plain state the operator
+    /// cannot read.
+    pub fn output_schema(&self, input: &Schema) -> Result<Schema, ExactOperationSchemaError> {
+        if !input.is_all_plain() {
+            return Err(ExactOperationSchemaError::NonPlainInput);
+        }
+        let plain = lift_plain(input);
+        let ExactOperation::Aggregate {
+            reduction,
+            measures,
+            output_names,
+            ..
+        } = self;
+        let out = aggregate_output_schema(&plain, reduction, measures, output_names)?;
+        Ok(lift_plain(&out))
+    }
+
+    fn into_op(self, child: Rc<OperatorNode>) -> NonASAPOp {
+        let ExactOperation::Aggregate {
+            reduction,
+            measures,
+            output_names,
+            filters,
+            having,
+        } = self;
+        NonASAPOp::Aggregate {
+            reduction,
+            measures,
+            output_names,
+            filters,
+            having,
+            child,
+        }
+    }
+}
+
 #[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
 pub enum OperationPlacement {
-    /// After the child's summary readout.
+    /// After the child's summary evaluation.
     Read,
     /// On the maintenance path, feeding
     /// maintained state above.
@@ -120,7 +177,7 @@ pub struct ExactComposition {
     pub op: ExactOperation,
     /// The pre-ASAP child the operator consumes; its `TargetSubDAGCandidates` holds the
     /// candidates `global_selection` may commit this composition with.
-    pub child_target: Rc<QueryExpr>,
+    pub child_target: Rc<OperatorNode>,
     /// The composed node's output schema — the target's own pre-ASAP
     /// output schema, lifted with every column `Plain` (an exact operator
     /// only ever produces plain values).
@@ -128,24 +185,27 @@ pub struct ExactComposition {
 }
 
 impl ExactComposition {
+    /// The data state `child` produces when this operation (its consumer)
+    /// runs at the placement's timing.
+    fn child_data_state(&self, child: &Rc<OperatorNode>) -> ExecutionDataState {
+        planned_data_state(child, self.placement.data_state().timing)
+    }
+
     /// Can `child` legally be this composition's input? Phase legality
-    /// (the child's produced data_state — a `KeepPreAsap` leaf takes the
+    /// (the child's produced data_state — a kept pre-ASAP sub-DAG takes the
     /// phase this edge assigns) plus the plain-operand rule, checked
     /// through the same schema derivation [`Self::compose`] uses.
-    pub fn accepts_child(&self, child: &SummaryNode) -> bool {
-        let phase_ok = match produced_data_state(&child.expr) {
-            None => true,
-            Some(avail) => avail == self.placement.data_state(),
-        };
-        phase_ok && exact_operation_output_schema(&self.op, &child.schema).is_ok()
+    pub fn accepts_child(&self, child: &Rc<OperatorNode>) -> bool {
+        self.child_data_state(child) == self.placement.data_state()
+            && self.op.output_schema(&child.schema).is_ok()
     }
 
     /// Build the composed, data_state-validated node over `child`. Every edge of
     /// the result (including everything beneath `child`) is checked by
-    /// `asap_types::post_asap::validate_execution_data_states`; an illegal
+    /// `asap_types::ir::timing::validate_default`; an illegal
     /// placement is a typed [`RealizationError::ExecutionDataState`], never deferred to a
     /// runtime.
-    pub fn compose(&self, child: Rc<SummaryNode>) -> Result<Rc<SummaryNode>, RealizationError> {
+    pub fn compose(&self, child: Rc<OperatorNode>) -> Result<Rc<OperatorNode>, RealizationError> {
         self.compose_with_accuracy(child, &DefaultAccuracyModel)
     }
 
@@ -154,24 +214,23 @@ impl ExactComposition {
     /// unsupported folds fail closed with a typed accuracy error.
     pub fn compose_with_accuracy(
         &self,
-        child: Rc<SummaryNode>,
+        child: Rc<OperatorNode>,
         accuracy_model: &dyn AccuracyModel,
-    ) -> Result<Rc<SummaryNode>, RealizationError> {
-        if let Some(produced) = produced_data_state(&child.expr) {
-            if produced != self.placement.data_state() {
-                let edge = match self.placement {
-                    OperationPlacement::Maintenance => "ValueOperation.child (maintenance time)",
-                    OperationPlacement::Read => "ValueOperation.child (read time)",
-                };
-                return Err(RealizationError::ExecutionDataState(
-                    ExecutionDataStateError::IllegalChildDataState {
-                        edge,
-                        child: produced,
-                    },
-                ));
-            }
+    ) -> Result<Rc<OperatorNode>, RealizationError> {
+        let produced = self.child_data_state(&child);
+        if produced != self.placement.data_state() {
+            let edge = match self.placement {
+                OperationPlacement::Maintenance => "exact operation child (maintenance time)",
+                OperationPlacement::Read => "exact operation child (read time)",
+            };
+            return Err(RealizationError::ExecutionDataState(
+                ExecutionDataStateError::IllegalChildDataState {
+                    edge,
+                    child: produced,
+                },
+            ));
         }
-        let schema = exact_operation_output_schema(&self.op, &child.schema)?;
+        let schema = self.op.output_schema(&child.schema)?;
         let guarantee = match &child.guarantee {
             None => None,
             Some(input) if input.is_exact() => Some(ResultGuarantee::exact(format!(
@@ -198,23 +257,11 @@ impl ExactComposition {
                 None => None,
             },
         };
-        let timing = match self.placement {
-            OperationPlacement::Read => asap_types::post_asap::ExecutionTiming::QueryTime,
-            OperationPlacement::Maintenance => {
-                asap_types::post_asap::ExecutionTiming::IngestionTime
-            }
-        };
-        let expr = SummaryExpr::ValueOperation {
-            child,
-            operation: ValueOperation::Exact(self.op.clone()),
-            timing,
-        };
-        let node = Rc::new(SummaryNode {
-            expr,
-            schema,
-            guarantee,
-        });
-        validate_execution_data_states_at(&node, self.placement.data_state())?;
+        let node = Rc::new(
+            OperatorNode::with_schema(Operator::NonASAP(self.op.clone().into_op(child)), schema)
+                .with_guarantee(guarantee),
+        );
+        validate_default(&node, self.placement.data_state().timing)?;
         Ok(node)
     }
 
@@ -227,7 +274,7 @@ impl ExactComposition {
     }
 }
 
-/// Which exact reducers may run as a query-time fold over readout rows.
+/// Which exact reducers may run as a query-time fold over evaluation rows.
 /// `Count` only at `Exact` accuracy (an approximate count is a sketch
 /// target, not an exact fold).
 fn is_query_time_reducer(intent: &AggIntent) -> bool {
@@ -245,9 +292,9 @@ fn is_query_time_reducer(intent: &AggIntent) -> bool {
     )
 }
 
-/// Does `implementation` need a `SummaryEstimate` readout to yield a value
+/// Does `implementation` need a `SummaryEstimate` evaluation to yield a value
 /// — i.e. is it a shape a maintained accumulator can't legally sit above?
-fn needs_readout(implementation: &Realization) -> bool {
+fn needs_evaluation(implementation: &Realization) -> bool {
     matches!(
         implementation,
         Realization::Sketch(_)
@@ -259,17 +306,17 @@ fn needs_readout(implementation: &Realization) -> bool {
 
 /// The `(op, child)` of a read-time operation-shaped target, or `None`.
 fn query_time_shape(
-    root: &QueryExpr,
+    root: &OperatorNode,
     cost_model: &dyn CostModel,
-) -> Option<(ExactOperation, Rc<QueryExpr>, AggIntent)> {
-    let QueryExpr::Aggregate {
+) -> Option<(ExactOperation, Rc<OperatorNode>, AggIntent)> {
+    let Some(NonASAPOp::Aggregate {
         reduction,
         measures,
         output_names,
         filters,
         having: None,
         child,
-    } = root
+    }) = root.non_asap()
     else {
         return None;
     };
@@ -291,13 +338,12 @@ fn query_time_shape(
     let child_intent = bindable_intent(child)?;
     if !realizations_for_intent(child_intent, cost_model)
         .iter()
-        .any(needs_readout)
+        .any(needs_evaluation)
     {
         return None;
     }
     // Grouping keys must resolve in the child's output schema — the same
     // derivation the composed node's own schema will use.
-    root.output_schema().ok()?;
     Some((
         ExactOperation::Aggregate {
             reduction: reduction.clone(),
@@ -314,17 +360,17 @@ fn query_time_shape(
 /// The `(op, child)` of a function-shaped target — a per-entity exact
 /// transform with no accumulator form — or `None`.
 fn ingestion_time_shape(
-    root: &QueryExpr,
+    root: &OperatorNode,
     cost_model: &dyn CostModel,
-) -> Option<(ExactOperation, Rc<QueryExpr>, AggIntent)> {
-    let QueryExpr::Aggregate {
+) -> Option<(ExactOperation, Rc<OperatorNode>, AggIntent)> {
+    let Some(NonASAPOp::Aggregate {
         reduction: Reduction::PerEntity,
         measures,
         output_names,
         filters,
         having: None,
         child,
-    } = root
+    }) = root.non_asap()
     else {
         return None;
     };
@@ -346,7 +392,6 @@ fn ingestion_time_shape(
     {
         return None;
     }
-    root.output_schema().ok()?;
     Some((
         ExactOperation::Aggregate {
             reduction: Reduction::PerEntity,
@@ -386,10 +431,7 @@ impl<'a> ExactCompositionStrategy<'a> {
     }
 
     fn candidates(&self, target: &TargetSubDAG<'_>) -> Vec<ReplacementSubDAG> {
-        let Ok(schema) = target.root.output_schema() else {
-            return Vec::new();
-        };
-        let schema = asap_types::post_asap::execution_data_state::lift_plain(&schema);
+        let schema = lift_plain(&target.root.schema);
         let mut out = Vec::new();
 
         if let Some((op, child, intent)) = query_time_shape(target.root, self.cost_model) {
@@ -410,10 +452,10 @@ impl<'a> ExactCompositionStrategy<'a> {
                     }),
                     provenance: ReplacementProvenance::ValueOperationAtQueryTime,
                     rationale: format!(
-                        "{} is an exact fold whose input is the readout of {} — a maintained \
-                         accumulator cannot consume query-time values, so instead of collapsing \
-                         the whole DAG into KeepPreAsap this applies the fold as an \
-                         ExactRead over whichever summary readout global_selection \
+                        "{} is an exact fold whose input is the evaluation of {} — a maintained \
+                         accumulator cannot consume query-time values, so instead of keeping \
+                         the whole tree pre-ASAP this applies the fold as an \
+                         ExactRead over whichever summary evaluation global_selection \
                          commits for the child target (asap_aware_mapping::exact_composition)",
                         describe_intent(&intent),
                         child_desc
@@ -441,7 +483,7 @@ impl<'a> ExactCompositionStrategy<'a> {
                         "{} is an exact per-entity function with no accumulator form; as an \
                          explicit ExactMaintenance on the update path its output can feed a \
                          maintained summary above it instead of being handed over as an opaque \
-                         raw KeepPreAsap blob (asap_aware_mapping::exact_composition)",
+                         raw kept sub_dag (asap_aware_mapping::exact_composition)",
                         describe_intent(&intent)
                     ),
                 });
@@ -465,59 +507,20 @@ impl ReplacementStrategy for ExactCompositionStrategy<'_> {
 mod tests {
     use super::*;
     use crate::cost_model::{DefaultCostModel, ValueOperationCapabilities};
-    use crate::replacement::keep_pre_asap;
+    use crate::replacement::retain_exact;
+    use crate::test_support::{agg, agg_per_entity as per_entity, metric_scan, timed};
+    use asap_types::ir::ASAPOp;
     use asap_types::post_asap::{ExecutionDataStateError, FieldDataType, SketchAlgorithm};
     use asap_types::pre_asap::agg_intent::default_quantile;
-    use asap_types::pre_asap::query_expr::Source;
-    use asap_types::pre_asap::schema::{DataType, Field, Schema};
-
-    fn metric_scan(labels: &[&str]) -> QueryExpr {
-        let mut columns = vec![
-            Field::plain("ts", DataType::Timestamp, false),
-            Field::plain("value", DataType::Float64, false),
-        ];
-        columns.extend(
-            labels
-                .iter()
-                .map(|n| Field::plain(*n, DataType::Utf8, true)),
-        );
-        QueryExpr::Scan {
-            source: Source::TimeSeries { metric: "m".into() },
-            predicates: vec![],
-            schema: Schema::with_time_index(columns, 0, vec![]),
-        }
-    }
-
-    fn agg(by: Vec<usize>, intent: AggIntent, child: QueryExpr) -> QueryExpr {
-        QueryExpr::Aggregate {
-            reduction: Reduction::by(by),
-            measures: vec![intent],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(child),
-        }
-    }
-
-    fn per_entity(intent: AggIntent, child: QueryExpr) -> QueryExpr {
-        QueryExpr::Aggregate {
-            reduction: Reduction::PerEntity,
-            measures: vec![intent],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(child),
-        }
-    }
 
     /// `max by (zone) (quantile by (zone, host) (m))`.
-    fn max_over_quantile() -> Rc<QueryExpr> {
+    fn max_over_quantile() -> Rc<OperatorNode> {
         let inner = agg(
             vec![2, 3],
             default_quantile(0.99),
             metric_scan(&["zone", "host"]),
         );
-        Rc::new(agg(vec![0], AggIntent::Max { col: None }, inner))
+        agg(vec![0], AggIntent::Max { col: None }, inner)
     }
 
     #[test]
@@ -539,7 +542,7 @@ mod tests {
             candidates[0].provenance,
             ReplacementProvenance::ValueOperationAtQueryTime
         );
-        let QueryExpr::Aggregate { child, .. } = root.as_ref() else {
+        let Some(NonASAPOp::Aggregate { child, .. }) = root.non_asap() else {
             unreachable!()
         };
         assert!(
@@ -553,7 +556,7 @@ mod tests {
     #[test]
     fn proposes_query_time_operation_for_avg_over_quantile_alongside_the_rewrite() {
         let inner = agg(vec![2], default_quantile(0.99), metric_scan(&["zone"]));
-        let root = Rc::new(agg(vec![0], AggIntent::Avg { col: None }, inner));
+        let root = agg(vec![0], AggIntent::Avg { col: None }, inner);
         let target = TargetSubDAG::new(&root);
         assert_eq!(
             ExactCompositionStrategy::default_cost_model()
@@ -567,7 +570,7 @@ mod tests {
 
     #[test]
     fn proposes_ingestion_time_operation_for_a_per_entity_pass_through_over_raw_input() {
-        let root = Rc::new(per_entity(AggIntent::Deriv, metric_scan(&["zone"])));
+        let root = per_entity(AggIntent::Deriv, metric_scan(&["zone"]));
         let target = TargetSubDAG::new(&root);
         let candidates = ExactCompositionStrategy::default_cost_model().replacements(&target);
         assert_eq!(candidates.len(), 1);
@@ -579,21 +582,21 @@ mod tests {
 
     #[test]
     fn does_not_propose_for_shapes_already_covered_by_accumulators() {
-        // sum by (zone) over an exact Sum child: the child has no readout,
+        // sum by (zone) over an exact Sum child: the child has no evaluation,
         // so SummaryAgg(Sum) over SummaryAgg(Sum) is already legal.
         let inner = agg(
             vec![2, 3],
             AggIntent::Sum { col: None },
             metric_scan(&["zone", "host"]),
         );
-        let root = Rc::new(agg(vec![0], AggIntent::Sum { col: None }, inner));
+        let root = agg(vec![0], AggIntent::Sum { col: None }, inner);
         assert!(!ExactCompositionStrategy::default_cost_model().matches(&TargetSubDAG::new(&root)));
         // rate is an exact accumulator — directly nestable, no separate value operation.
-        let rate = Rc::new(per_entity(AggIntent::Rate, metric_scan(&[])));
+        let rate = per_entity(AggIntent::Rate, metric_scan(&[]));
         assert!(!ExactCompositionStrategy::default_cost_model().matches(&TargetSubDAG::new(&rate)));
         // A sketch-capable outer intent is not an exact fold.
         let inner = agg(vec![2], default_quantile(0.5), metric_scan(&["zone"]));
-        let root = Rc::new(agg(vec![0], default_quantile(0.99), inner));
+        let root = agg(vec![0], default_quantile(0.99), inner);
         assert!(!ExactCompositionStrategy::default_cost_model().matches(&TargetSubDAG::new(&root)));
     }
 
@@ -618,7 +621,7 @@ mod tests {
         let strategy = ExactCompositionStrategy::new(&NoMixedExecution);
         assert!(!strategy.matches(&target));
         assert!(strategy.replacements(&target).is_empty());
-        let deriv = Rc::new(per_entity(AggIntent::Deriv, metric_scan(&[])));
+        let deriv = per_entity(AggIntent::Deriv, metric_scan(&[]));
         assert!(!strategy.matches(&TargetSubDAG::new(&deriv)));
     }
 
@@ -630,12 +633,13 @@ mod tests {
         let Replacement::ExactComposition(comp) = &candidates[0].replacement else {
             unreachable!()
         };
-        // A bare SummaryAgg (state, no readout) is not a legal read-time operation
+        // A bare SummaryAgg (state, no evaluation) is not a legal read-time operation
         // input — the operator would be consuming sketch state.
         let state_child =
             crate::replacement::realize_child(&comp.child_target, &DefaultCostModel).unwrap();
-        let SummaryExpr::SummaryEstimate { summary_input, .. } = &state_child.expr else {
-            panic!("expected the child to realize to a readout");
+        let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &state_child.operator
+        else {
+            panic!("expected the child to realize to a evaluation");
         };
         assert!(!comp.accepts_child(summary_input));
         assert!(matches!(
@@ -644,7 +648,7 @@ mod tests {
                 ExecutionDataStateError::IllegalChildDataState { .. }
             ))
         ));
-        // The readout itself is accepted and composes to a plain schema.
+        // The evaluation itself is accepted and composes to a plain schema.
         assert!(comp.accepts_child(&state_child));
         let composed = comp.compose(state_child).unwrap();
         assert!(
@@ -652,12 +656,13 @@ mod tests {
             "rank error has no registered conversion through max"
         );
         assert!(matches!(
-            composed.expr,
-            SummaryExpr::ValueOperation {
-                timing: ExecutionTiming::QueryTime,
-                ..
-            }
+            composed.operator,
+            Operator::NonASAP(NonASAPOp::Aggregate { .. })
         ));
+        // Timing is no longer stored by composition: under the default
+        // lifecycle assignment the composed read-time operation runs at
+        // query time.
+        assert_eq!(timed(&composed).timing, Some(ExecutionTiming::QueryTime));
         assert!(composed
             .schema
             .fields
@@ -666,32 +671,78 @@ mod tests {
     }
 
     #[test]
-    fn compose_rejects_a_readout_child_for_a_ingestion_time_operation() {
+    fn compose_rejects_a_evaluation_child_for_a_ingestion_time_operation() {
         let inner = agg(vec![2], default_quantile(0.99), metric_scan(&["zone"]));
-        let root = Rc::new(per_entity(AggIntent::Deriv, inner));
+        let root = per_entity(AggIntent::Deriv, inner);
         let candidates =
             ExactCompositionStrategy::default_cost_model().replacements(&TargetSubDAG::new(&root));
         let Replacement::ExactComposition(comp) = &candidates[0].replacement else {
             unreachable!()
         };
-        let readout =
+        let evaluation =
             crate::replacement::realize_child(&comp.child_target, &DefaultCostModel).unwrap();
-        assert!(!comp.accepts_child(&readout));
+        assert!(!comp.accepts_child(&evaluation));
         assert!(matches!(
-            comp.compose(readout),
+            comp.compose(evaluation),
             Err(RealizationError::ExecutionDataState(
                 ExecutionDataStateError::IllegalChildDataState { .. }
             ))
         ));
         // Raw update input is fine.
-        let raw = keep_pre_asap(&comp.child_target).unwrap();
+        let raw = retain_exact(&comp.child_target).unwrap();
         assert!(comp.accepts_child(&raw));
+        // Timing is no longer stored by composition: the composition's
+        // placement is maintenance time, the composed exact operation is a
+        // plain Aggregate over the raw rows, and it is legal (and planned to
+        // run) at ingestion time.
+        assert_eq!(comp.placement, OperationPlacement::Maintenance);
+        let composed = comp.compose(raw).unwrap();
         assert!(matches!(
-            comp.compose(raw).unwrap().expr,
-            SummaryExpr::ValueOperation {
-                timing: ExecutionTiming::IngestionTime,
-                ..
-            }
+            composed.operator,
+            Operator::NonASAP(NonASAPOp::Aggregate { .. })
+        ));
+        validate_default(&composed, ExecutionTiming::IngestionTime).unwrap();
+        assert_eq!(
+            planned_data_state(&composed, ExecutionTiming::IngestionTime).timing,
+            ExecutionTiming::IngestionTime
+        );
+    }
+
+    fn max_op(by: Vec<usize>) -> ExactOperation {
+        ExactOperation::Aggregate {
+            reduction: Reduction::by(by),
+            measures: vec![AggIntent::Max { col: None }],
+            output_names: vec![],
+            filters: vec![],
+            having: None,
+        }
+    }
+
+    #[test]
+    fn exact_operator_schema_matches_pre_asap_aggregate_derivation() {
+        let child = lift_plain(&metric_scan(&["zone"]).schema);
+        let out = max_op(vec![2]).output_schema(&child).unwrap();
+        let names: Vec<_> = out.fields.iter().map(|f| f.name.as_str()).collect();
+        assert_eq!(names, vec!["zone", "max"]);
+        assert!(out.is_all_plain());
+    }
+
+    #[test]
+    fn exact_operator_rejects_non_plain_input() {
+        let state = Schema::lifted(
+            vec![asap_types::pre_asap::Field::new(
+                "state",
+                FieldDataType::ExactAggregate(
+                    asap_types::post_asap::ExactKind::Sum,
+                    asap_types::post_asap::ExactParams::Sum,
+                ),
+                false,
+            )],
+            None,
+        );
+        assert!(matches!(
+            max_op(vec![]).output_schema(&state),
+            Err(ExactOperationSchemaError::NonPlainInput)
         ));
     }
 }
diff --git a/crates/asap-aware-mapping/src/explanation.rs b/crates/asap-aware-mapping/src/explanation.rs
index e7afff2ba..bc67be96f 100644
--- a/crates/asap-aware-mapping/src/explanation.rs
+++ b/crates/asap-aware-mapping/src/explanation.rs
@@ -31,7 +31,7 @@
 //! collapses into a single question this module asks of *that* data instead:
 //! **for a given `TargetSubDAG`, does its candidate list contain anything
 //! other than the trivial, no-op realization?** A `TargetSubDAG` whose only
-//! candidate is "the one thing `SketchAlgorithmStrategy` would have committed
+//! candidate is "the one thing `ASAPStrategies` would have committed
 //! to anyway, with no alternative" has no optimization to report — that
 //! candidate isn't an *opportunity*, it's just the target's existing shape
 //! reflected back. A `TargetSubDAG` with more than one candidate (several
@@ -43,9 +43,9 @@
 //! [`TargetSubDAGCandidates`]s into that shape:
 //!
 //! - [`ExplanationKind::SketchApproximation`] — the `TargetSubDAG`'s
-//!   candidate list contains at least one [`Replacement::Summary`] that
+//!   candidate list contains at least one summary-realization [`Replacement::SubDAG`] that
 //!   actually realizes a sketch family (`FieldDataType::Sketch`), i.e.
-//!   [`SketchAlgorithmStrategy`] found something to offer beyond whatever
+//!   [`ASAPStrategies`] found something to offer beyond whatever
 //!   exact/pass-through candidate [`crate::replacement`]'s own
 //!   `realizations_for_intent` would have committed to on its own.
 //! - [`ExplanationKind::CommonSubexpressionReuse`] — the `TargetSubDAG`
@@ -103,7 +103,7 @@
 //! [`ReplacementStrategy`] already *is* that extension point, one layer
 //! down, and [`explain_replacements_with`]'s own `strategies`
 //! parameter is where a caller plugs in a custom one (or a custom
-//! `CostModel`, via [`crate::replacement::SketchAlgorithmStrategy::new`]) — the identical spot
+//! `CostModel`, via [`crate::replacement::ASAPStrategies::new`]) — the identical spot
 //! [`crate::replacement::search_workload_with`] itself exposes.
 //!
 //! ## Two guarantees the old traversal made, re-verified against the new one
@@ -134,7 +134,7 @@
 //! ## One thing [`CandidateLogicalASAPDAGs`] doesn't carry that this module still needs:
 //! human-readable `location` text
 //!
-//! [`TargetSubDAGCandidates`]/[`CandidateLogicalASAPDAGs`] deliberately track only `Rc<QueryExpr>`
+//! [`TargetSubDAGCandidates`]/[`CandidateLogicalASAPDAGs`] deliberately track only `Rc<OperatorNode>`
 //! pointer identity — the currency the search itself needs — not
 //! caller-facing prose. [`ReplacementExplanation::location`] is prose (a
 //! breadcrumb like `root "dash_a" > lhs`), so this module keeps one small,
@@ -161,8 +161,8 @@
 //!
 //! | Catalog entry | Status | Where a future `ExplanationKind` would come from |
 //! |---|---|---|
-//! | Semantic-equivalent rewriting (e.g. `avg` → `sum`/`count`) | [`AvgToSumOverCountStrategy`](crate::rewrite::AvgToSumOverCountStrategy) exists and is wired into `default_strategies()` (issue #253) — but still no `ExplanationKind` of its own below, since this table is about *direct* findings for a catalog entry, and this strategy's whole point is indirect: its `Replacement::Rewrite` candidate exposes `sum`/`count` as independently bindable discovered targets, which can then earn `CommonSubexpressionReuse` findings when the workload actually reuses them | A dedicated variant would need `findings_from_candidate_logical_asap_dags` to recognize a `LogicalRewrite`-provenance candidate as a finding in its own right, not just rely on what it exposes downstream |
-//! | Roll-ups (fine-to-coarse group-by reuse) | [`RollupStrategy`](crate::rollup::RollupStrategy), derived from workload siblings after CSE/target discovery (issue #254) | Any `Replacement::Rewrite` candidate that rolls a coarse aggregate up from a compatible finer aggregate |
+//! | Semantic-equivalent rewriting (e.g. `avg` → `sum`/`count`) | [`AvgToSumOverCountStrategy`](crate::rewrite::AvgToSumOverCountStrategy) exists and is wired into `default_strategies()` (issue #253) — but still no `ExplanationKind` of its own below, since this table is about *direct* findings for a catalog entry, and this strategy's whole point is indirect: its `Replacement::SubDAG` rewrite candidate exposes `sum`/`count` as independently bindable discovered targets, which can then earn `CommonSubexpressionReuse` findings when the workload actually reuses them | A dedicated variant would need `findings_from_candidate_logical_asap_dags` to recognize a `LogicalRewrite`-provenance candidate as a finding in its own right, not just rely on what it exposes downstream |
+//! | Roll-ups (fine-to-coarse group-by reuse) | [`RollupStrategy`](crate::rollup::RollupStrategy), derived from workload siblings after CSE/target discovery (issue #254) | Any `Replacement::SubDAG` rewrite candidate that rolls a coarse aggregate up from a compatible finer aggregate |
 //! | Wavelets/OMP | Params type exists (`WaveletKind`/`WaveletParams`), reachable only via a deployment `CostModel::realize_extension` (no core `AggIntent` dispatch picks it) | A `ReplacementStrategy` that inspects a deployment's own `CostModel`, once some intent shape actually maps to `Realization::Wavelet` |
 //! | Sampling | Same story as Wavelets: `SamplingKind`/`SamplingParams` exist, unreachable from core dispatch | Same hook as Wavelets, for `Realization::Sample` |
 //! | Deep generative compression | No representation at all — no `Realization`/`FieldDataType` variant | Needs a new summary family added to `asap_types::post_asap` first |
@@ -175,9 +175,8 @@
 //! [`ReplacementStrategy`]: crate::replacement::ReplacementStrategy
 //! [`ReplacementSubDAG`]: crate::replacement::ReplacementSubDAG
 //! [`Replacement`]: crate::replacement::Replacement
-//! [`Replacement::Summary`]: crate::replacement::Replacement::Summary
-//! [`Replacement::Rewrite`]: crate::replacement::Replacement::Rewrite
-//! [`SketchAlgorithmStrategy`]: crate::replacement::SketchAlgorithmStrategy
+//! [`Replacement::SubDAG`]: crate::replacement::Replacement::SubDAG
+//! [`ASAPStrategies`]: crate::replacement::ASAPStrategies
 //! [`SharedSubDAGStrategy`]: crate::replacement::SharedSubDAGStrategy
 //! [`CandidateLogicalASAPDAGs`]: crate::replacement::CandidateLogicalASAPDAGs
 //! [`TargetSubDAGCandidates`]: crate::replacement::TargetSubDAGCandidates
@@ -186,9 +185,9 @@ use std::collections::HashMap;
 use std::fmt::Display;
 use std::rc::Rc;
 
-use asap_types::post_asap::{FieldDataType, SummaryExpr, SummaryNode};
-use asap_types::pre_asap::cse::{structural_hash, HashCache};
-use asap_types::pre_asap::query_expr::QueryExpr;
+use asap_types::ir::cse::{structural_hash, HashCache};
+use asap_types::ir::{ASAPOp, Operator, OperatorNode};
+use asap_types::post_asap::FieldDataType;
 
 use crate::replacement::{
     self, CandidateLogicalASAPDAGs, Replacement, ReplacementStrategy, TargetSubDAGCandidates,
@@ -206,8 +205,8 @@ use crate::replacement::{
 #[non_exhaustive]
 pub enum ExplanationKind {
     /// A `TargetSubDAG`'s candidate list contains at least one
-    /// [`Replacement::Summary`] that realizes a sketch family —
-    /// [`crate::replacement::SketchAlgorithmStrategy`] found a genuine sketch
+    /// [`Replacement::SubDAG`] that realizes a sketch family —
+    /// [`crate::replacement::ASAPStrategies`] found a genuine sketch
     /// alternative for this `Aggregate`, beyond whatever exact/pass-through
     /// candidate `crate::replacement`'s own `realizations_for_intent` would
     /// have committed to on its own.
@@ -222,8 +221,8 @@ pub enum ExplanationKind {
     /// [`Replacement::ExactComposition`] —
     /// [`crate::exact_composition::ExactCompositionStrategy`] found an exact
     /// operator that can be composed with a summary plan across an explicit
-    /// update/readout boundary instead of collapsing the whole DAG into
-    /// `KeepPreAsap` (issue #171).
+    /// update/evaluation boundary instead of keeping the whole tree as it is
+    /// (issue #171).
     ExactComposition,
 }
 
@@ -233,11 +232,11 @@ pub enum ExplanationKind {
 /// not machine parsing — literally the matching candidate's own
 /// [`crate::replacement::ReplacementSubDAG::rationale`]).
 ///
-/// `node_hash` is [`structural_hash`](asap_types::pre_asap::cse::structural_hash)
+/// `node_hash` is [`structural_hash`](asap_types::ir::cse::structural_hash)
 /// of the `TargetSubDAG`'s own `target` sub-DAG — the same function, on the
-/// same `Rc<QueryExpr>` shape, that [`asap_types::dag_export::DAGNode::hash`]
+/// same `Rc<OperatorNode>` shape, that [`asap_types::dag_export::DAGNode::hash`]
 /// is computed with. A downstream consumer that independently exported the
-/// same `QueryExpr` (e.g. via `asap_types::dag_export::export`) can match
+/// same node (e.g. via `asap_types::dag_export::export`) can match
 /// this explanation to a `DAGNode` by first comparing hashes and then
 /// confirming structural equality with [`ReplacementExplanation::target`].
 #[derive(Debug, Clone, PartialEq)]
@@ -249,7 +248,7 @@ pub struct ReplacementExplanation {
     /// The exact target expression the explanation describes. Reporting
     /// integrations use this together with `node_hash`: the hash narrows the
     /// search, and structural equality makes the final match collision-safe.
-    pub target: Rc<QueryExpr>,
+    pub target: Rc<OperatorNode>,
 }
 
 /// Explain every replacement [`crate::replacement::search_workload`] finds
@@ -265,7 +264,7 @@ pub struct ReplacementExplanation {
 /// candidate-plan space, then reads findings off it — see the module docs'
 /// "The reframing" section for what that translation actually checks.
 pub fn explain_replacements<Id: Display>(
-    roots: Vec<(Id, QueryExpr)>,
+    roots: Vec<(Id, Rc<OperatorNode>)>,
 ) -> Vec<ReplacementExplanation> {
     explain_replacements_with(roots, &replacement::default_strategies())
 }
@@ -274,17 +273,17 @@ pub fn explain_replacements<Id: Display>(
 /// instead of [`crate::replacement::default_strategies`] — the extension
 /// point for a deployment-specific [`ReplacementStrategy`], or a custom
 /// `CostModel` plugged into
-/// [`crate::replacement::SketchAlgorithmStrategy::new`] (e.g. via
+/// [`crate::replacement::ASAPStrategies::new`] (e.g. via
 /// [`crate::replacement::default_strategies_with`]).
 ///
 /// [`ReplacementStrategy`]: crate::replacement::ReplacementStrategy
 pub fn explain_replacements_with<'s, Id: Display>(
-    roots: Vec<(Id, QueryExpr)>,
+    roots: Vec<(Id, Rc<OperatorNode>)>,
     strategies: &[Box<dyn ReplacementStrategy + 's>],
 ) -> Vec<ReplacementExplanation> {
-    let ided: Vec<(String, Rc<QueryExpr>)> = roots
+    let ided: Vec<(String, Rc<OperatorNode>)> = roots
         .into_iter()
-        .map(|(id, expr)| (id.to_string(), Rc::new(expr)))
+        .map(|(id, expr)| (id.to_string(), expr))
         .collect();
     let space = replacement::search_workload_with(ided, strategies);
     findings_from_candidate_logical_asap_dags(&space)
@@ -375,7 +374,7 @@ fn sketch_finding_reason(group: &TargetSubDAGCandidates) -> Option<String> {
         .candidates
         .iter()
         .filter(
-            |c| matches!(&c.replacement, Replacement::Summary(node) if is_sketch_realization(node)),
+            |c| matches!(&c.replacement, Replacement::SubDAG(node) if is_sketch_realization(node)),
         )
         .map(|c| c.rationale.as_str())
         .collect();
@@ -387,7 +386,7 @@ fn sketch_finding_reason(group: &TargetSubDAGCandidates) -> Option<String> {
 }
 
 /// Does `group` have two or more consumers *and* a "build once and share"
-/// candidate (the [`Replacement::Rewrite`] whose `Rc` is the group's own
+/// candidate (the [`Replacement::SubDAG`] whose `Rc` is the group's own
 /// `target`) in its candidate list? If so, the finding's `reason` is that
 /// candidate's own `rationale`.
 fn shared_subexpr_finding_reason(group: &TargetSubDAGCandidates) -> Option<String> {
@@ -398,7 +397,7 @@ fn shared_subexpr_finding_reason(group: &TargetSubDAGCandidates) -> Option<Strin
         .candidates
         .iter()
         .find(
-            |c| matches!(&c.replacement, Replacement::Rewrite(rc) if Rc::ptr_eq(rc, &group.target)),
+            |c| matches!(&c.replacement, Replacement::SubDAG(rc) if Rc::ptr_eq(rc, &group.target)),
         )
         .map(|c| c.rationale.clone())
 }
@@ -409,7 +408,7 @@ fn shared_subexpr_finding_reason(group: &TargetSubDAGCandidates) -> Option<Strin
 /// yes/no fact (a candidate's own `rationale` already names the specific
 /// `SketchKind`/`SketchAlgorithm` for a finding's `reason` text), so unlike
 /// `replacement.rs`'s counterpart this returns `bool`, not the kind itself.
-fn is_sketch_realization(node: &SummaryNode) -> bool {
+fn is_sketch_realization(node: &OperatorNode) -> bool {
     if node
         .guarantee
         .as_ref()
@@ -417,9 +416,13 @@ fn is_sketch_realization(node: &SummaryNode) -> bool {
     {
         return false;
     }
-    match &node.expr {
-        SummaryExpr::SummaryEstimate { summary_input, .. } => is_sketch_realization(summary_input),
-        SummaryExpr::SummaryAgg { family, .. } => matches!(family, FieldDataType::Sketch(..)),
+    match &node.operator {
+        Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) => {
+            is_sketch_realization(summary_input)
+        }
+        Operator::ASAP(ASAPOp::SummaryAgg { family, .. }) => {
+            matches!(family, FieldDataType::Sketch(..))
+        }
         _ => false,
     }
 }
@@ -432,8 +435,10 @@ fn is_sketch_realization(node: &SummaryNode) -> bool {
 /// every breadcrumb path that reaches a given `Rc`, not just the first: a
 /// shared node referenced from two workload roots (or two branches of one
 /// root) needs both breadcrumbs in its finding's `location`, not just one.
-fn collect_locations(roots: &[(String, Rc<QueryExpr>)]) -> HashMap<*const QueryExpr, Vec<String>> {
-    let mut locations: HashMap<*const QueryExpr, Vec<String>> = HashMap::new();
+fn collect_locations(
+    roots: &[(String, Rc<OperatorNode>)],
+) -> HashMap<*const OperatorNode, Vec<String>> {
+    let mut locations: HashMap<*const OperatorNode, Vec<String>> = HashMap::new();
     for (id, root) in roots {
         visit(root, format!("root {id:?}"), &mut locations);
     }
@@ -444,9 +449,9 @@ fn collect_locations(roots: &[(String, Rc<QueryExpr>)]) -> HashMap<*const QueryE
 /// through its children. A shared ancestor is intentionally traversed once
 /// per incoming path so every descendant receives every valid breadcrumb.
 fn visit(
-    node: &Rc<QueryExpr>,
+    node: &Rc<OperatorNode>,
     label: String,
-    locations: &mut HashMap<*const QueryExpr, Vec<String>>,
+    locations: &mut HashMap<*const OperatorNode, Vec<String>>,
 ) {
     let ptr = Rc::as_ptr(node);
     locations.entry(ptr).or_default().push(label.clone());
@@ -455,20 +460,24 @@ fn visit(
 
 /// `node`'s own **relational-skeleton** operator children — the same scope
 /// `crate::replacement`'s own target-discovery `walk_children` (and
-/// `asap_types::pre_asap::cse::share_common_sub_dags`'s `rebuild_children`)
-/// use. Exhaustive over every `QueryExpr` variant: a new variant fails to
-/// compile here until this match is extended too.
+/// `asap_types::ir::cse::share_common_sub_dags`) use. Exhaustive over every
+/// `NonASAPOp` variant: a new variant fails to compile here until this match
+/// is extended too. An ASAP node never occurs in a workload root.
 fn visit_children(
-    node: &QueryExpr,
+    node: &OperatorNode,
     label: &str,
-    locations: &mut HashMap<*const QueryExpr, Vec<String>>,
+    locations: &mut HashMap<*const OperatorNode, Vec<String>>,
 ) {
-    use QueryExpr::*;
-    match node {
-        Scan { .. } | PromqlScalarBridge(_) | EvalTimestamp | CurrentTimestamp => {}
-        PromqlVectorFromScalar(c) | PromqlScalarFromVector(c) => {
+    use asap_types::ir::{NonASAPOp::*, ScalarExpr};
+    let Operator::NonASAP(op) = &node.operator else {
+        return;
+    };
+    match op {
+        Scan { .. } | Values { .. } => {}
+        PromqlVectorFromScalar(ScalarExpr::PromqlScalarFromVector(c)) => {
             visit(c, format!("{label} > child"), locations)
         }
+        PromqlVectorFromScalar(_) => {}
         PromqlRelabel { child, .. }
         | PromqlInfoEnrich { child, .. }
         | PromqlSeriesSample { child, .. }
@@ -484,7 +493,7 @@ fn visit_children(
         | Limit { child, .. } => visit(child, format!("{label} > child"), locations),
         Concat { children, .. } => {
             for (i, c) in children.iter().enumerate() {
-                visit_children(c, &format!("{label} > concat[{i}]"), locations);
+                visit(c, format!("{label} > concat[{i}]"), locations);
             }
         }
         Join { left, right, .. } | SetOp { left, right, .. } => {
@@ -495,31 +504,20 @@ fn visit_children(
             visit(lhs, format!("{label} > lhs"), locations);
             visit(rhs, format!("{label} > rhs"), locations);
         }
-        Column(_)
-        | Literal(_)
-        | Compare { .. }
-        | BoolAnd(_)
-        | BoolOr(_)
-        | Not(_)
-        | IsNull(_)
-        | IsNotNull(_)
-        | Cast { .. }
-        | InList { .. }
-        | FunctionCall { .. }
-        | Arithmetic { .. }
-        | Case { .. } => {}
     }
 }
 
 #[cfg(test)]
 mod tests {
     use super::*;
+    use asap_types::ir::operator_properties::{BinaryOpKind, Reduction, Source};
+    use asap_types::ir::{BinaryOperator, NonASAPOp, OperatorNode, Predicate, ScalarExpr};
     use asap_types::pre_asap::agg_intent::{default_quantile, AggIntent};
-    use asap_types::pre_asap::query_expr::{Reduction, Source};
     use asap_types::pre_asap::schema::{DataType, Field, Schema};
+
     use asap_types::types::AccuracyTarget;
 
-    fn metric_scan(labels: &[&str]) -> QueryExpr {
+    fn metric_scan(labels: &[&str]) -> Rc<OperatorNode> {
         let mut columns = vec![
             Field::plain("ts", DataType::Timestamp, false),
             Field::plain("value", DataType::Float64, false),
@@ -529,22 +527,43 @@ mod tests {
                 .iter()
                 .map(|n| Field::plain(*n, DataType::Utf8, true)),
         );
-        QueryExpr::Scan {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: Source::TimeSeries { metric: "m".into() },
             predicates: vec![],
             schema: Schema::with_time_index(columns, 0, vec![]),
-        }
+        }))
+        .unwrap()
     }
 
-    fn agg(by: Vec<usize>, intent: AggIntent, child: QueryExpr) -> QueryExpr {
-        QueryExpr::Aggregate {
+    fn agg(by: Vec<usize>, intent: AggIntent, child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
             reduction: Reduction::by(by),
             measures: vec![intent],
             output_names: vec![],
             filters: vec![],
             having: None,
-            child: Rc::new(child),
-        }
+            child,
+        }))
+        .unwrap()
+    }
+
+    fn binary(
+        kind: BinaryOpKind,
+        lhs: Rc<OperatorNode>,
+        rhs: Rc<OperatorNode>,
+    ) -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::BinaryOp {
+            operator: BinaryOperator {
+                kind,
+                vector_match: None,
+                checked_relative_division: false,
+                checked_finite_division: false,
+            },
+            return_bool: false,
+            lhs,
+            rhs,
+        }))
+        .unwrap()
     }
 
     // ── SketchApproximation ──────────────────────────────────────────────
@@ -567,7 +586,7 @@ mod tests {
     }
 
     /// `node_hash` must be the literal `structural_hash` a downstream
-    /// consumer would compute over the *same* `QueryExpr` sub-DAG via
+    /// consumer would compute over the *same* `OperatorNode` sub-DAG via
     /// `asap_types::dag_export::export` — the whole point of carrying it is
     /// that two independent exports of the same DAG agree, with no
     /// string-matching against `location` required.
@@ -586,7 +605,7 @@ mod tests {
             Some(sketch.node_hash),
             expected_hash,
             "ReplacementExplanation::node_hash must match dag_export's DAGNode::hash \
-             for the same QueryExpr sub-DAG"
+             for the same OperatorNode sub_dag"
         );
     }
 
@@ -641,21 +660,18 @@ mod tests {
 
     /// A sketch-applicable `Aggregate` reachable via two paths that CSE
     /// collapses onto one `Rc` — the same `median(x) == median(x)` shape
-    /// `pre_asap::cse`'s own `single_query_shares_its_own_repeated_sub_dag`
+    /// `pre_asap::cse`'s own `single_query_shares_its_own_repeated_sub-DAG`
     /// test uses — must be reported once, not once per path: it is exactly
     /// one [`crate::replacement::TargetSubDAGCandidates`], keyed by `Rc` pointer identity,
     /// not one per path that reaches it.
     #[test]
     fn a_shared_sketchable_aggregate_is_reported_only_once() {
         let quantile = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
-        let root = QueryExpr::BinaryOp {
-            op: asap_types::pre_asap::query_expr::BinaryOpKind::Compare(
-                asap_types::pre_asap::expr_ir::CompareOpKind::Eq,
-            ),
-            lhs: Rc::new(quantile.clone()),
-            rhs: Rc::new(quantile),
-            vector_match: None,
-        };
+        let root = binary(
+            BinaryOpKind::Compare(asap_types::pre_asap::expr_ir::CompareOpKind::Eq),
+            Rc::clone(&quantile),
+            quantile,
+        );
         let findings = explain_replacements(vec![("ratio", root)]);
         let sketch: Vec<_> = findings
             .iter()
@@ -695,8 +711,8 @@ mod tests {
     #[test]
     fn descendant_of_a_shared_root_keeps_every_root_breadcrumb() {
         let inner = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
-        let outer = agg(vec![2], AggIntent::Sum { col: None }, inner);
-        let findings = explain_replacements(vec![("dash_a", outer.clone()), ("dash_b", outer)]);
+        let outer = agg(vec![0], AggIntent::Sum { col: None }, inner);
+        let findings = explain_replacements(vec![("dash_a", Rc::clone(&outer)), ("dash_b", outer)]);
         let inner_sketch = findings
             .iter()
             .find(|f| {
@@ -742,14 +758,11 @@ mod tests {
         // The same shared branch appearing twice within one query (an `a/a`
         // shape) — single-query CSE.
         let branch = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
-        let q = QueryExpr::BinaryOp {
-            op: asap_types::pre_asap::query_expr::BinaryOpKind::Arithmetic(
-                asap_types::pre_asap::expr_ir::ArithmeticOpKind::Div,
-            ),
-            lhs: Rc::new(branch.clone()),
-            rhs: Rc::new(branch),
-            vector_match: None,
-        };
+        let q = binary(
+            BinaryOpKind::Arithmetic(asap_types::pre_asap::expr_ir::ArithmeticOpKind::Div),
+            Rc::clone(&branch),
+            branch,
+        );
         let findings = explain_replacements(vec![("ratio", q)]);
         let reuse: Vec<_> = findings
             .iter()
@@ -766,7 +779,7 @@ mod tests {
 
     /// A shared node nested three levels under two *different*, unshared
     /// `Filter` parents (mirrors `crate::replacement::tests::
-    /// nested_shared_sub_dag_below_an_unshared_parent_is_still_discovered`)
+    /// nested_shared_sub-DAG_below_an_unshared_parent_is_still_discovered`)
     /// must still be exactly one finding — the maximal-`TargetSubDAG`
     /// guarantee the module docs describe, now provided by
     /// `crate::replacement`'s own target discovery rather than this module's
@@ -774,17 +787,20 @@ mod tests {
     #[test]
     fn a_deeply_shared_sub_dag_under_different_parents_is_reported_once() {
         use asap_types::pre_asap::expr_ir::ScalarValue;
-        use asap_types::pre_asap::query_expr::Predicate;
 
         let shared = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
-        let root_a = QueryExpr::Filter {
-            pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Int64(1)))),
-            child: Rc::new(shared.clone()),
-        };
-        let root_b = QueryExpr::Filter {
-            pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Int64(2)))),
-            child: Rc::new(shared),
-        };
+        let root_a =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Filter {
+                pred: Predicate(ScalarExpr::Literal(ScalarValue::Int64(1))),
+                child: Rc::clone(&shared),
+            }))
+            .unwrap();
+        let root_b =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Filter {
+                pred: Predicate(ScalarExpr::Literal(ScalarValue::Int64(2))),
+                child: shared,
+            }))
+            .unwrap();
         let findings = explain_replacements(vec![("a", root_a), ("b", root_b)]);
         let reuse: Vec<_> = findings
             .iter()
@@ -825,7 +841,7 @@ mod tests {
         let q = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
         let custom_model = AlwaysDDSketch;
         let strategies: Vec<Box<dyn ReplacementStrategy + '_>> = vec![Box::new(
-            crate::replacement::SketchAlgorithmStrategy::new(&custom_model),
+            crate::replacement::ASAPStrategies::new(&custom_model),
         )];
         let findings = explain_replacements_with(vec![("q", q)], &strategies);
         assert_eq!(findings.len(), 1);
diff --git a/crates/asap-aware-mapping/src/grouping.rs b/crates/asap-aware-mapping/src/grouping.rs
index fc4abfe62..bbbaad37f 100644
--- a/crates/asap-aware-mapping/src/grouping.rs
+++ b/crates/asap-aware-mapping/src/grouping.rs
@@ -7,7 +7,7 @@
 //!
 //! ## Placement: planning metadata and edge-state type
 //!
-//! `SummaryExpr::SummaryAgg` carries the grouping choice next to the
+//! `ASAPOp::SummaryAgg` carries the grouping choice next to the
 //! `Reduction` whose `by` keys determine legality. The same choice is also
 //! committed to `FieldDataType::Sketch` on the aggregate's output edge.
 //! That duplication is intentional: the node field makes the choice easy to
@@ -41,7 +41,7 @@
 //! An earlier draft of this module (written against the very first draft of
 //! #251) reused a `CostModel`-wrapping adapter that "steered" a
 //! whole-recursive-bind decision procedure toward a specific `SketchKind`,
-//! the same pattern [`crate::replacement::SketchAlgorithmStrategy`]'s own module
+//! the same pattern [`crate::replacement::ASAPStrategies`]'s own module
 //! docs explain was deliberately deleted from this crate as an anti-pattern:
 //! forcing a choice via a whole-DAG `CostModel` adapter had a real bug where
 //! the forced choice could leak into a target's own nested aggregates. This
@@ -53,7 +53,7 @@
 //! passes that exact,
 //! already-decided `Realization` to
 //! [`crate::replacement::construct_summary`] — the same first-class,
-//! one-candidate-at-a-time primitive [`crate::replacement::SketchAlgorithmStrategy`]
+//! one-candidate-at-a-time primitive [`crate::replacement::ASAPStrategies`]
 //! itself calls once per candidate. No adapter, no steering, no risk of a
 //! forced choice leaking into nested aggregates.
 //!
@@ -71,13 +71,14 @@
 
 use std::rc::Rc;
 
+use asap_types::ir::operator_properties::Reduction;
+use asap_types::ir::{ASAPOp, NonASAPOp, Operator, OperatorNode};
 use asap_types::post_asap::{
     default_hydra_params, hydra_kind_for, AccuracyError, BoundExpr, CompositionOperator,
     FieldDataType, GroupingStrategy, GuaranteeSource, HydraKind, ProbabilityExpr, ResultGuarantee,
-    SketchAlgorithm, SketchParams, SummaryExpr, SummaryNode,
+    SketchAlgorithm, SketchParams,
 };
 use asap_types::pre_asap::agg_intent::AggIntent;
-use asap_types::pre_asap::query_expr::{QueryExpr, Reduction};
 
 use crate::accuracy::{
     AccuracyBudgetAllocator, AccuracyEvidenceProvider, AccuracyModel, PropagationStats,
@@ -110,15 +111,15 @@ pub fn has_subpopulations(reduction: &Reduction) -> bool {
 
 /// A single static instance so [`HydraGroupingStrategy::default_cost_model`]
 /// can hand out a `&'static dyn CostModel` without heap-allocating one — same
-/// pattern [`crate::replacement::SketchAlgorithmStrategy`] uses.
+/// pattern [`crate::replacement::ASAPStrategies`] uses.
 static DEFAULT_COST_MODEL: DefaultCostModel = DefaultCostModel;
 
 /// Wraps the `GroupingStrategy` axis (issue #256) as a
-/// [`ReplacementStrategy`]: for a target [`SketchAlgorithmStrategy`](crate::replacement::SketchAlgorithmStrategy)
+/// [`ReplacementStrategy`]: for a target [`ASAPStrategies`](crate::replacement::ASAPStrategies)
 /// already has an opinion on, offers an additional
 /// `GroupingStrategy::SharedMultiSubpopulation` candidate wherever the
 /// legality conditions in the module docs above hold — alongside, not
-/// instead of, the per-subpopulation candidates `SketchAlgorithmStrategy`
+/// instead of, the per-subpopulation candidates `ASAPStrategies`
 /// itself enumerates. The workload search composes both strategies over the
 /// same target, so it sees every summary-family alternative *and* the Hydra
 /// alternative; the built-in workload search registers both strategies, and
@@ -132,7 +133,7 @@ pub struct HydraGroupingStrategy<'a> {
 impl HydraGroupingStrategy<'static> {
     /// A strategy that ranks/binds via the built-in [`DefaultCostModel`] —
     /// what a deployment gets with no custom cost model plugged in, the same
-    /// default [`crate::replacement::SketchAlgorithmStrategy::default_cost_model`]
+    /// default [`crate::replacement::ASAPStrategies::default_cost_model`]
     /// offers.
     pub fn default_cost_model() -> Self {
         Self {
@@ -144,7 +145,7 @@ impl HydraGroupingStrategy<'static> {
 impl<'a> HydraGroupingStrategy<'a> {
     /// A strategy that ranks/binds via `cost_model` instead of the built-in
     /// static preference order — the same customization point
-    /// [`crate::replacement::SketchAlgorithmStrategy::new`] already offers.
+    /// [`crate::replacement::ASAPStrategies::new`] already offers.
     pub fn new(cost_model: &'a dyn CostModel) -> Self {
         Self {
             planning_inputs: CandidatePlanningInputs::with_default_accuracy(cost_model),
@@ -173,7 +174,7 @@ impl<'a> HydraGroupingStrategy<'a> {
     /// variant modeled.
     fn hydra_proposals(&self, target: &TargetSubDAG<'_>) -> Proposals {
         let mut proposals = Proposals::default();
-        let QueryExpr::Aggregate { reduction, .. } = target.root.as_ref() else {
+        let Some(NonASAPOp::Aggregate { reduction, .. }) = target.root.non_asap() else {
             return proposals;
         };
         if !has_subpopulations(reduction) {
@@ -208,11 +209,11 @@ impl<'a> HydraGroupingStrategy<'a> {
     /// `PerSubpopulationInstance` to
     /// `SharedMultiSubpopulation { kind: hydra_kind, .. }` — reusing the
     /// entire bind decision procedure (schema derivation, column resolution,
-    /// readout construction) unchanged, patching only the one field this
+    /// evaluation construction) unchanged, patching only the one field this
     /// axis owns.
     fn build_candidate(
         &self,
-        root: &Rc<QueryExpr>,
+        root: &Rc<OperatorNode>,
         intent: &AggIntent,
         sketch_kind: SketchAlgorithm,
         hydra_kind: HydraKind,
@@ -233,12 +234,12 @@ impl<'a> HydraGroupingStrategy<'a> {
             params,
         };
 
-        let (family, query) = match &node.expr {
-            SummaryExpr::SummaryEstimate {
+        let (family, query) = match &node.operator {
+            Operator::ASAP(ASAPOp::SummaryEstimate {
                 summary_input,
                 query,
-            } => match &summary_input.expr {
-                SummaryExpr::SummaryAgg { family, .. } => (family, Some(query)),
+            }) => match &summary_input.operator {
+                Operator::ASAP(ASAPOp::SummaryAgg { family, .. }) => (family, Some(query)),
                 _ => return None,
             },
             _ => return None,
@@ -295,7 +296,7 @@ impl<'a> HydraGroupingStrategy<'a> {
         }
         Some(ReplacementSubDAG {
             strategy: "HydraGroupingStrategy",
-            replacement: Replacement::Summary(patched),
+            replacement: Replacement::SubDAG(patched),
             provenance: crate::replacement::ReplacementProvenance::SummaryRealization,
             rationale: format!(
                 "{} realizes as a shared {hydra_kind:?} structure over {sketch_kind:?} \
@@ -313,7 +314,7 @@ impl<'a> HydraGroupingStrategy<'a> {
 
 impl ReplacementStrategy for HydraGroupingStrategy<'_> {
     fn matches(&self, target: &TargetSubDAG<'_>) -> bool {
-        let QueryExpr::Aggregate { reduction, .. } = target.root.as_ref() else {
+        let Some(NonASAPOp::Aggregate { reduction, .. }) = target.root.non_asap() else {
             return false;
         };
         if !has_subpopulations(reduction) {
@@ -357,15 +358,15 @@ impl ReplacementStrategy for HydraGroupingStrategy<'_> {
 /// destructures the right variant for `kind`; this function's only job is
 /// to find whatever `SketchParams` the bind decision already committed to
 /// and hand the whole thing over unchanged.
-fn per_subpopulation_sketch_params(node: &SummaryNode) -> Option<SketchParams> {
-    match &node.expr {
-        SummaryExpr::SummaryEstimate { summary_input, .. } => {
+fn per_subpopulation_sketch_params(node: &OperatorNode) -> Option<SketchParams> {
+    match &node.operator {
+        Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) => {
             per_subpopulation_sketch_params(summary_input)
         }
-        SummaryExpr::SummaryAgg {
+        Operator::ASAP(ASAPOp::SummaryAgg {
             family: FieldDataType::Sketch(kind, _),
             ..
-        } => Some(kind.params().clone()),
+        }) => Some(kind.params().clone()),
         _ => None,
     }
 }
@@ -373,33 +374,35 @@ fn per_subpopulation_sketch_params(node: &SummaryNode) -> Option<SketchParams> {
 /// Rebuild `node`, replacing its `SummaryAgg`'s `grouping` field with
 /// `grouping` — patching the one field this axis owns onto an
 /// already-correctly-bound node rather than re-deriving the rest of it.
-/// Recurses through a `SummaryEstimate` readout wrapper (the shape every
+/// Recurses through a `SummaryEstimate` evaluation wrapper (the shape every
 /// sketch candidate this module builds actually has) to reach the
 /// `SummaryAgg` underneath.
 fn with_grouping(
-    node: Rc<SummaryNode>,
+    node: Rc<OperatorNode>,
     grouping: GroupingStrategy,
     stats: &PropagationStats,
-) -> Rc<SummaryNode> {
-    match &node.expr {
-        SummaryExpr::SummaryEstimate {
+) -> Rc<OperatorNode> {
+    match &node.operator {
+        Operator::ASAP(ASAPOp::SummaryEstimate {
             summary_input,
             query,
-        } => Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryEstimate {
-                summary_input: with_grouping(Rc::clone(summary_input), grouping, stats),
-                query: query.clone(),
-            },
-            schema: node.schema.clone(),
-            guarantee: node.guarantee.as_ref().map(|g| hydra_guarantee(g, stats)),
-        }),
-        SummaryExpr::SummaryAgg {
+        }) => std::rc::Rc::new(
+            OperatorNode::with_schema(
+                asap_types::ir::Operator::ASAP(ASAPOp::SummaryEstimate {
+                    summary_input: with_grouping(Rc::clone(summary_input), grouping, stats),
+                    query: query.clone(),
+                }),
+                node.schema.clone(),
+            )
+            .with_guarantee(node.guarantee.as_ref().map(|g| hydra_guarantee(g, stats))),
+        ),
+        Operator::ASAP(ASAPOp::SummaryAgg {
             child,
             family,
             input,
             reduction,
             ..
-        } => {
+        }) => {
             let grouped_family = match family {
                 FieldDataType::Sketch(kind, _) => {
                     FieldDataType::Sketch(kind.clone(), grouping.clone())
@@ -412,18 +415,20 @@ fn with_grouping(
                     field.dtype = FieldDataType::Sketch(kind.clone(), grouping.clone());
                 }
             }
-            Rc::new(SummaryNode {
-                expr: SummaryExpr::SummaryAgg {
-                    child: Rc::clone(child),
-                    family: grouped_family,
-                    input: input.clone(),
-                    reduction: reduction.clone(),
-                    grouping,
-                    filter: None,
-                },
-                schema: grouped_schema,
-                guarantee: None,
-            })
+            std::rc::Rc::new(
+                OperatorNode::with_schema(
+                    asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
+                        child: Rc::clone(child),
+                        family: grouped_family,
+                        input: input.clone(),
+                        reduction: reduction.clone(),
+                        grouping,
+                        filter: None,
+                    }),
+                    grouped_schema,
+                )
+                .with_guarantee(None),
+            )
         }
         // Never reached by this module's own callers (they only ever pass a
         // node `construct_summary_with` just bound for a `Sketch`
@@ -492,51 +497,11 @@ fn hydra_guarantee(inner: &ResultGuarantee, stats: &PropagationStats) -> ResultG
 mod tests {
     use super::*;
     use crate::accuracy::{DefaultAccuracyModel, EqualSplitAllocator};
+    use crate::test_support::{agg, agg_per_entity, metric_scan};
     use asap_types::post_asap::ErrorMetric;
     use asap_types::pre_asap::agg_intent::{default_cardinality, default_quantile};
-    use asap_types::pre_asap::query_expr::Source;
-    use asap_types::pre_asap::schema::{DataType, Field, Schema};
     use asap_types::types::AccuracyTarget;
 
-    fn metric_scan(labels: &[&str]) -> QueryExpr {
-        let mut columns = vec![
-            Field::plain("ts", DataType::Timestamp, false),
-            Field::plain("value", DataType::Float64, false),
-        ];
-        columns.extend(
-            labels
-                .iter()
-                .map(|n| Field::plain(*n, DataType::Utf8, true)),
-        );
-        QueryExpr::Scan {
-            source: Source::TimeSeries { metric: "m".into() },
-            predicates: vec![],
-            schema: Schema::with_time_index(columns, 0, vec![]),
-        }
-    }
-
-    fn agg(by: Vec<usize>, intent: AggIntent, child: QueryExpr) -> QueryExpr {
-        QueryExpr::Aggregate {
-            reduction: Reduction::by(by),
-            measures: vec![intent],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(child),
-        }
-    }
-
-    fn agg_per_entity(intent: AggIntent, child: QueryExpr) -> QueryExpr {
-        QueryExpr::Aggregate {
-            reduction: Reduction::PerEntity,
-            measures: vec![intent],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(child),
-        }
-    }
-
     // ── has_subpopulations ────────────────────────────────────────────────
 
     #[test]
@@ -556,7 +521,7 @@ mod tests {
 
     #[test]
     fn without_grouping_has_a_subpopulation_concept_even_when_empty() {
-        use asap_types::pre_asap::query_expr::GroupKeys;
+        use asap_types::ir::operator_properties::GroupKeys;
         // `without([])` groups by every remaining label — a real
         // subpopulation concept, unlike `by([])`'s genuine full reduction.
         assert!(has_subpopulations(&Reduction::Reduce(GroupKeys::without(
@@ -603,7 +568,7 @@ mod tests {
                 delta: 0.01,
             },
         };
-        let q = Rc::new(agg(vec![2], intent, metric_scan(&["job"])));
+        let q = agg(vec![2], intent, metric_scan(&["job"]));
         let target = TargetSubDAG::new(&q);
         assert!(HydraGroupingStrategy::default_cost_model().matches(&target));
     }
@@ -611,7 +576,7 @@ mod tests {
     #[test]
     fn does_not_match_an_empty_by_aggregate() {
         // Global reduction — no subpopulation concept, no Hydra alternative.
-        let q = Rc::new(agg(vec![], default_quantile(0.99), metric_scan(&["job"])));
+        let q = agg(vec![], default_quantile(0.99), metric_scan(&["job"]));
         let target = TargetSubDAG::new(&q);
         let strategy = HydraGroupingStrategy::default_cost_model();
         assert!(!strategy.matches(&target));
@@ -620,10 +585,7 @@ mod tests {
 
     #[test]
     fn does_not_match_a_per_entity_aggregate() {
-        let q = Rc::new(agg_per_entity(
-            default_quantile(0.99),
-            metric_scan(&["job"]),
-        ));
+        let q = agg_per_entity(default_quantile(0.99), metric_scan(&["job"]));
         let target = TargetSubDAG::new(&q);
         let strategy = HydraGroupingStrategy::default_cost_model();
         assert!(!strategy.matches(&target));
@@ -632,14 +594,14 @@ mod tests {
 
     #[test]
     fn does_not_match_a_non_aggregate_node() {
-        let scan = Rc::new(metric_scan(&["job"]));
+        let scan = metric_scan(&["job"]);
         let target = TargetSubDAG::new(&scan);
         assert!(!HydraGroupingStrategy::default_cost_model().matches(&target));
     }
 
     #[test]
     fn quantile_has_no_hydra_candidate_without_a_modeled_error_bound() {
-        let q = Rc::new(agg(vec![2], default_quantile(0.99), metric_scan(&["job"])));
+        let q = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
         let target = TargetSubDAG::new(&q);
         let replacements = HydraGroupingStrategy::default_cost_model().replacements(&target);
         assert!(replacements.is_empty(), "{replacements:?}");
@@ -653,13 +615,13 @@ mod tests {
                 delta: 0.01,
             },
         };
-        let q = Rc::new(agg(vec![2], intent, metric_scan(&["job"])));
+        let q = agg(vec![2], intent, metric_scan(&["job"]));
         let target = TargetSubDAG::new(&q);
         let replacements = HydraGroupingStrategy::default_cost_model().replacements(&target);
         assert_eq!(replacements.len(), 2, "{replacements:?}");
         assert!(replacements.iter().all(|candidate| matches!(
             &candidate.replacement,
-            Replacement::Summary(node)
+            Replacement::SubDAG(node)
                 if node.guarantee.as_ref().is_some_and(|guarantee|
                     guarantee.bound.evaluate().is_none()
                         && guarantee.failure_probability.evaluate().is_none())
@@ -691,7 +653,7 @@ mod tests {
                 delta: 0.01,
             },
         };
-        let q = Rc::new(agg(vec![2], intent, metric_scan(&["job"])));
+        let q = agg(vec![2], intent, metric_scan(&["job"]));
         let strategy = HydraGroupingStrategy::new_with_planning_inputs_and_evidence(
             &DefaultCostModel,
             &DefaultAccuracyModel,
@@ -702,7 +664,7 @@ mod tests {
         assert_eq!(replacements.len(), 2, "{replacements:?}");
         assert!(replacements.iter().all(|candidate| matches!(
             &candidate.replacement,
-            Replacement::Summary(node)
+            Replacement::SubDAG(node)
                 if node.guarantee.as_ref().is_some_and(|g|
                     g.bound.evaluate().is_some()
                         && g.failure_probability.evaluate().is_some())
@@ -731,7 +693,7 @@ mod tests {
                 delta: 0.01,
             },
         };
-        let q = Rc::new(agg(vec![2], intent, metric_scan(&["job"])));
+        let q = agg(vec![2], intent, metric_scan(&["job"]));
         let strategy = HydraGroupingStrategy::new_with_planning_inputs_and_evidence(
             &DefaultCostModel,
             &DefaultAccuracyModel,
@@ -771,7 +733,7 @@ mod tests {
                 }
             }
         }
-        let q = Rc::new(agg(
+        let q = agg(
             vec![2],
             AggIntent::Count {
                 accuracy: AccuracyTarget::EpsilonDelta {
@@ -780,7 +742,7 @@ mod tests {
                 },
             },
             metric_scan(&["job"]),
-        ));
+        );
         let strategy = HydraGroupingStrategy::new_with_planning_inputs_and_evidence(
             &DefaultCostModel,
             &DefaultAccuracyModel,
@@ -801,7 +763,7 @@ mod tests {
         // summary_candidates(Cardinality) = [Hll, Theta, Kmv] — none have a
         // modeled Hydra variant, so no candidate at all (not an error, just
         // an empty result, same conservatism as every other strategy here).
-        let q = Rc::new(agg(vec![2], default_cardinality(), metric_scan(&["job"])));
+        let q = agg(vec![2], default_cardinality(), metric_scan(&["job"]));
         let target = TargetSubDAG::new(&q);
         let strategy = HydraGroupingStrategy::default_cost_model();
         assert!(!strategy.matches(&target));
@@ -817,7 +779,7 @@ mod tests {
             q: 0.99,
             accuracy: AccuracyTarget::Exact,
         };
-        let q = Rc::new(agg(vec![2], intent, metric_scan(&["job"])));
+        let q = agg(vec![2], intent, metric_scan(&["job"]));
         let target = TargetSubDAG::new(&q);
         let strategy = HydraGroupingStrategy::default_cost_model();
         assert!(!strategy.matches(&target));
@@ -828,11 +790,7 @@ mod tests {
     fn exact_mergeable_intent_has_no_hydra_candidate() {
         // Sum's exact accumulator has no candidate summary families at all
         // (summary_candidates only covers approximate-capable intents).
-        let q = Rc::new(agg(
-            vec![2],
-            AggIntent::Sum { col: None },
-            metric_scan(&["job"]),
-        ));
+        let q = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
         let target = TargetSubDAG::new(&q);
         let strategy = HydraGroupingStrategy::default_cost_model();
         assert!(!strategy.matches(&target));
@@ -843,14 +801,16 @@ mod tests {
     fn does_not_match_a_multi_intent_or_having_aggregate() {
         let strategy = HydraGroupingStrategy::default_cost_model();
 
-        let multi = Rc::new(QueryExpr::Aggregate {
-            reduction: Reduction::by(vec![2]),
-            measures: vec![AggIntent::Sum { col: None }, AggIntent::Avg { col: None }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(metric_scan(&["job"])),
-        });
+        let multi =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+                reduction: Reduction::by(vec![2]),
+                measures: vec![AggIntent::Sum { col: None }, AggIntent::Avg { col: None }],
+                output_names: vec![],
+                filters: vec![],
+                having: None,
+                child: metric_scan(&["job"]),
+            }))
+            .unwrap();
         let target = TargetSubDAG::new(&multi);
         assert!(!strategy.matches(&target));
         assert!(strategy.replacements(&target).is_empty());
@@ -859,7 +819,7 @@ mod tests {
     /// A custom `CostModel` doesn't change *which* candidate is offered —
     /// only which sketch candidate `realizations_for_intent` itself would
     /// have ranked first, and how that candidate's own params are sized —
-    /// same guarantee `SketchAlgorithmStrategy` makes for its own candidates.
+    /// same guarantee `ASAPStrategies` makes for its own candidates.
     struct PreferDDSketch;
     impl CostModel for PreferDDSketch {
         fn rank_candidates(
@@ -878,7 +838,7 @@ mod tests {
 
     #[test]
     fn custom_cost_model_cannot_enable_unproven_hydra_kll() {
-        let q = Rc::new(agg(vec![2], default_quantile(0.99), metric_scan(&["job"])));
+        let q = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
         let target = TargetSubDAG::new(&q);
         let custom = PreferDDSketch;
         let replacements = HydraGroupingStrategy::new(&custom).replacements(&target);
diff --git a/crates/asap-aware-mapping/src/lib.rs b/crates/asap-aware-mapping/src/lib.rs
index 95e50a552..16e6e6118 100644
--- a/crates/asap-aware-mapping/src/lib.rs
+++ b/crates/asap-aware-mapping/src/lib.rs
@@ -1,18 +1,18 @@
 //! `asap-plan` — the cost-aware optimizer layer over the pre-ASAP intent algebra.
 //!
 //! This crate sits between the language-agnostic IR ([`asap_ir`]) and
-//! any runtime: it consumes pre-ASAP [`QueryExpr`](asap_types::pre_asap::QueryExpr)
+//! any runtime: it consumes pre-ASAP [`OperatorNode`](asap_types::ir::OperatorNode)
 //! DAGs and makes the cost-aware decisions the pre-ASAP IR deliberately
 //! leaves open — which sketch (if any) realises each approximate intent.
 //!
 //! **Common sub-expression elimination (CSE) is not this crate's job.**
-//! Detection is a primary pass over the pre-ASAP `QueryExpr` IR itself
-//! (`asap_types::pre_asap`, design tracked in issue #223), run before a
-//! DAG ever reaches [`replacement::SketchAlgorithmStrategy`] — see issue #222
+//! Detection is a primary pass over the pre-ASAP operator IR itself
+//! (`asap_types::ir::cse`, design tracked in issue #223), run before a
+//! tree ever reaches [`replacement::ASAPStrategies`] — see issue #222
 //! for why (batch query optimization needs to see shared work across a
 //! `QueryWorkload` before summary binding, not after). This crate may
 //! eventually run a second, narrower CSE pass of its own over an
-//! already-bound `SummaryExpr`/`SummaryNode` DAG, recognizing sharing that's invisible
+//! already-bound post-ASAP `OperatorNode` DAG, recognizing sharing that's invisible
 //! at the pre-ASAP level by construction — e.g. `Quantile(x, 0.99)` and
 //! `Quantile(x, 0.95)` are structurally distinct `AggIntent`s but can
 //! still share one built sketch, read out twice. That post-ASAP pass is
@@ -92,7 +92,7 @@
 //!   #33) is an additional `ReplacementStrategy`: the orthogonal
 //!   `GroupingStrategy` axis (one summary instance per `by` subpopulation
 //!   versus one shared Hydra-family structure serving all of them), offered
-//!   alongside the candidates [`replacement::SketchAlgorithmStrategy`]
+//!   alongside the candidates [`replacement::ASAPStrategies`]
 //!   enumerates for the same target.
 //! - [`rewrite`] — the "semantic-equivalent rewriting (e.g. `avg` →
 //!   `sum`/`count`) to increase how often the [sharing/sketch] optimizations
@@ -117,7 +117,7 @@
 //! |---|---|---|
 //! | Schema resolution | Derive input schemas and resolve column names to positions | `asap_types::pre_asap::SchemaResolver::resolve_schema`, `resolve_root` |
 //! | Realization | Enumerate ranked physical forms for one aggregate intent | `replacement::realizations_for_intent` |
-//! | Replacement | Construct each candidate summary sub-DAG | [`replacement::SketchAlgorithmStrategy`] |
+//! | Replacement | Construct each candidate summary sub-DAG | [`replacement::ASAPStrategies`] |
 //! | Search | Enumerate and compare alternatives across a workload | [`replacement::search_workload`] |
 //! | Runtime placement | Choose deployment locations and concrete executors | Downstream physical plan providers |
 //!
@@ -207,12 +207,12 @@ pub use recurrence::{
     UpdateRate,
 };
 pub use replacement::{
-    default_strategies, default_strategies_with, search_workload, search_workload_with,
-    search_workload_with_targets, summary_candidates, CandidateLogicalASAPDAGs,
-    CompositionDecision, GlobalSelection, Matcher, Proposals, RankedTargetSubDAGCandidates,
-    Realization, RealizationError, RecurrenceProfileMap, RejectedCandidate, Replacement,
-    ReplacementProvenance, ReplacementStrategy, ReplacementSubDAG, SharedSubDAGStrategy,
-    SketchAlgorithmStrategy, TargetSubDAG, TargetSubDAGCandidates, TargetSubDAGSelection,
+    default_strategies, default_strategies_with, is_logical_rewrite, search_workload,
+    search_workload_with, search_workload_with_targets, summary_candidates, ASAPStrategies,
+    CandidateLogicalASAPDAGs, CompositionDecision, GlobalSelection, Matcher, Proposals,
+    RankedTargetSubDAGCandidates, Realization, RealizationError, RecurrenceProfileMap,
+    RejectedCandidate, Replacement, ReplacementProvenance, ReplacementStrategy, ReplacementSubDAG,
+    SharedSubDAGStrategy, TargetSubDAG, TargetSubDAGCandidates, TargetSubDAGSelection,
     MAX_SEARCH_ITERATIONS,
 };
 pub use rewrite::{AvgToSumOverCountStrategy, SemanticEquivalentRewriteStrategy};
diff --git a/crates/asap-aware-mapping/src/maintained_population.rs b/crates/asap-aware-mapping/src/maintained_population.rs
index b749a6967..00fee0306 100644
--- a/crates/asap-aware-mapping/src/maintained_population.rs
+++ b/crates/asap-aware-mapping/src/maintained_population.rs
@@ -2,22 +2,14 @@
 use crate::replacement::{
     Replacement, ReplacementProvenance, ReplacementStrategy, ReplacementSubDAG, TargetSubDAG,
 };
-use asap_types::post_asap::{
-    maintained_population::*, ExecutionTiming, ResultGuarantee, SummaryExpr, SummaryNode,
-    ValueOperation,
-};
-use asap_types::pre_asap::{
-    any_measure_filtered, AggIntent, CompareOpKind, DataType, QueryExpr, Reduction, ScalarValue,
-    Schema, Source,
-};
+use asap_types::ir::non_asap::any_measure_filtered;
+use asap_types::ir::{ASAPOp, NonASAPOp, Operator, OperatorNode, ScalarExpr};
+use asap_types::post_asap::{maintained_population::*, ResultGuarantee};
+use asap_types::pre_asap::{AggIntent, CompareOpKind, DataType, Reduction, ScalarValue, Source};
 use std::rc::Rc;
 
-fn plain(schema: Schema) -> Schema {
-    Schema::lifted(schema.fields, schema.time_index)
-}
-
-fn strip_projection(mut root: &QueryExpr) -> &QueryExpr {
-    while let QueryExpr::Project { child, .. } = root {
+fn strip_projection(mut root: &OperatorNode) -> &OperatorNode {
+    while let Some(NonASAPOp::Project { child, .. }) = root.non_asap() {
         root = child;
     }
     root
@@ -26,17 +18,20 @@ fn strip_projection(mut root: &QueryExpr) -> &QueryExpr {
 /// Skips a projection that keeps every column in place, such as the one
 /// `SELECT *` lowers to: it changes neither the rows nor the column positions
 /// a Sort key refers to.
-fn strip_identity_projection(expr: &Rc<QueryExpr>) -> &Rc<QueryExpr> {
-    if let QueryExpr::Project {
+fn strip_identity_projection(expr: &Rc<OperatorNode>) -> &Rc<OperatorNode> {
+    if let Some(NonASAPOp::Project {
         cols,
         qualifier: None,
         child,
-    } = expr.as_ref()
+    }) = expr.non_asap()
     {
-        let width = child.output_schema().map(|schema| schema.fields.len());
+        let width = child
+            .operator
+            .output_schema()
+            .map(|schema| schema.fields.len());
         if width.ok() == Some(cols.len())
             && cols.iter().enumerate().all(|(i, item)| {
-                item.alias.is_none() && matches!(item.expr, QueryExpr::Column(c) if c == i)
+                item.alias.is_none() && matches!(item.expr, ScalarExpr::Column(c) if c == i)
             })
         {
             return child;
@@ -46,11 +41,11 @@ fn strip_identity_projection(expr: &Rc<QueryExpr>) -> &Rc<QueryExpr> {
 }
 
 fn recognize(
-    root: &QueryExpr,
-) -> Option<(MaintainedPopulation, PopulationStatistic, Rc<QueryExpr>)> {
+    root: &OperatorNode,
+) -> Option<(MaintainedPopulation, PopulationStatistic, Rc<OperatorNode>)> {
     let root = strip_projection(root);
-    let (source, grouping, readout, value_column) = match root {
-        QueryExpr::Aggregate {
+    let (source, grouping, evaluation, value_column) = match root.non_asap()? {
+        NonASAPOp::Aggregate {
             child,
             reduction: Reduction::Reduce(grouping),
             measures,
@@ -64,7 +59,7 @@ fn recognize(
             if any_measure_filtered(filters) {
                 return None;
             }
-            let (col, readout) = match intent {
+            let (col, evaluation) = match intent {
                 AggIntent::Quantile { q, col, .. } if q.is_finite() => {
                     (*col, PopulationStatistic::Quantile { q: *q })
                 }
@@ -74,29 +69,30 @@ fn recognize(
                 AggIntent::Avg { col } => (*col, PopulationStatistic::Average),
                 _ => return None,
             };
-            let schema = child.output_schema().ok()?;
+            let schema = &child.schema;
             if col.is_some_and(|c| schema.fields.get(c).is_none()) {
                 return None;
             }
-            (child, grouping, readout, col)
+            (child, grouping, evaluation, col)
         }
-        QueryExpr::Limit {
-            n,
+        NonASAPOp::Limit {
+            n: Some(n),
             offset: 0,
             child,
+            ..
         } => {
-            let QueryExpr::Sort {
+            let Some(NonASAPOp::Sort {
                 child,
                 keys,
                 partition_by,
-            } = child.as_ref()
+            }) = child.non_asap()
             else {
                 return None;
             };
             let [key] = keys.as_slice() else {
                 return None;
             };
-            let QueryExpr::Column(col) = &key.expr else {
+            let ScalarExpr::Column(col) = &key.expr else {
                 return None;
             };
             if key.ascending {
@@ -111,11 +107,11 @@ fn recognize(
         }
         _ => return None,
     };
-    if let QueryExpr::Scan {
+    if let Some(NonASAPOp::Scan {
         source: Source::Table { .. },
         schema,
         ..
-    } = source.as_ref()
+    }) = source.non_asap()
     {
         let value_column = value_column.or_else(|| {
             schema
@@ -132,29 +128,29 @@ fn recognize(
             max_k: 0,
             quantiles: false,
         };
-        if !schema.closed || !population.matches_input(source) {
+        if !schema.closed || !population.matches_node(source) {
             return None;
         }
-        return Some((population, readout, Rc::clone(source)));
+        return Some((population, evaluation, Rc::clone(source)));
     }
     // A bare PromQL selector carries the declared ingestion interval as a
     // temporal input scope. Membership must expire at that horizon; retain
     // the wrapper as the maintained input so validation can check agreement.
-    let (series_source, lookback_ms) = match source.as_ref() {
-        QueryExpr::TimeRange { range, child } => {
+    let (series_source, lookback_ms) = match source.non_asap() {
+        Some(NonASAPOp::TimeRange { range, child, .. }) => {
             let ms = u64::try_from(range.as_millis()).ok()?;
             if ms == 0 || std::time::Duration::from_millis(ms) != *range {
                 return None;
             }
             (child.as_ref(), ms)
         }
-        other => (other, 300_000),
+        _ => (source.as_ref(), 300_000),
     };
-    let QueryExpr::Scan {
+    let Some(NonASAPOp::Scan {
         source: Source::TimeSeries { metric },
         predicates,
         schema,
-    } = series_source
+    }) = series_source.non_asap()
     else {
         return None;
     };
@@ -174,10 +170,13 @@ fn recognize(
     };
     let mut matchers = Vec::new();
     for predicate in predicates {
-        let QueryExpr::Compare { left, op, right } = predicate.0.as_ref() else {
+        let ScalarExpr::Compare {
+            left, op, right, ..
+        } = &predicate.0
+        else {
             return None;
         };
-        let (QueryExpr::Column(col), QueryExpr::Literal(ScalarValue::Utf8(value))) =
+        let (ScalarExpr::Column(col), ScalarExpr::Literal(ScalarValue::Utf8(value))) =
             (left.as_ref(), right.as_ref())
         else {
             return None;
@@ -216,46 +215,46 @@ fn recognize(
             max_k: 0,
             quantiles: false,
         },
-        readout,
+        evaluation,
         Rc::clone(source),
     ))
 }
 
-/// Workload-aware rule: compatible readouts share one retractable population.
+/// Workload-aware rule: compatible evaluations share one retractable population.
 /// Deployments opt in by registering this strategy when they can maintain complete
-/// population updates and price the maintenance/readout boundary.
-/// The population is exact; max_k bounds the shared readout cache, not its members.
+/// population updates and price the maintenance/evaluation boundary.
+/// The population is exact; max_k bounds the shared evaluation cache, not its members.
 pub struct MaintainedPopulationStrategy {
-    roots: Vec<Rc<QueryExpr>>,
+    roots: Vec<Rc<OperatorNode>>,
 }
 impl MaintainedPopulationStrategy {
-    pub fn new(roots: &[Rc<QueryExpr>]) -> Self {
+    pub fn new(roots: &[Rc<OperatorNode>]) -> Self {
         Self {
             roots: roots.to_vec(),
         }
     }
-    pub fn candidate(&self, root: &Rc<QueryExpr>) -> Option<Rc<SummaryNode>> {
-        if let QueryExpr::Project {
+    pub fn candidate(&self, root: &Rc<OperatorNode>) -> Option<Rc<OperatorNode>> {
+        if let Some(NonASAPOp::Project {
             cols,
             qualifier,
             child,
-        } = root.as_ref()
+        }) = root.non_asap()
         {
             let child = self.candidate(child)?;
-            return Some(Rc::new(SummaryNode {
-                guarantee: child.guarantee.clone(),
-                schema: plain(root.output_schema().ok()?),
-                expr: SummaryExpr::ValueOperation {
-                    child,
-                    operation: ValueOperation::Project {
+            let guarantee = child.guarantee.clone();
+            return Some(Rc::new(
+                OperatorNode::with_schema(
+                    Operator::NonASAP(NonASAPOp::Project {
                         cols: cols.clone(),
                         qualifier: qualifier.clone(),
-                    },
-                    timing: ExecutionTiming::QueryTime,
-                },
-            }));
+                        child,
+                    }),
+                    root.schema.clone(),
+                )
+                .with_guarantee(guarantee),
+            ));
         }
-        let (mut population, readout, source) = recognize(root)?;
+        let (mut population, evaluation, source) = recognize(root)?;
         let identity = population.clone();
         for other in self.roots.iter().chain(std::iter::once(root)) {
             if let Some((p, r, _)) = recognize(other) {
@@ -272,36 +271,39 @@ impl MaintainedPopulationStrategy {
                 }
             }
         }
-        let input_schema = plain(source.output_schema().ok()?);
-        let scan = Rc::new(SummaryNode {
-            expr: SummaryExpr::KeepPreAsap(source),
-            schema: input_schema.clone(),
-            guarantee: Some(ResultGuarantee::exact("source samples")),
-        });
-        // Query time is only the initial layout: whether the population is
-        // retained at ingestion or rebuilt per query is its lifecycle choice
-        // (`SummaryMaintenanceLifecyclePlan::execution_timed_dag`). The readout
-        // and projection above it are query-time by construction.
-        let maintained = Rc::new(SummaryNode {
-            expr: SummaryExpr::ValueOperation {
-                child: scan,
-                operation: ValueOperation::MaintainPopulation { population },
-                timing: ExecutionTiming::QueryTime,
-            },
-            schema: input_schema,
-            guarantee: Some(ResultGuarantee::exact(
+        let input_schema = source.schema.clone();
+        // The source node itself is the maintained input (a non-ASAP node
+        // keeps its derived schema), kept with its exact guarantee.
+        let scan = Rc::new(
+            source
+                .as_ref()
+                .clone()
+                .with_guarantee(Some(ResultGuarantee::exact("source samples"))),
+        );
+        let maintained = std::rc::Rc::new(
+            OperatorNode::with_schema(
+                asap_types::ir::Operator::ASAP(ASAPOp::MaintainPopulation {
+                    child: scan,
+                    population,
+                }),
+                input_schema,
+            )
+            .with_guarantee(Some(ResultGuarantee::exact(
                 "exact members under the declared population semantics",
-            )),
-        });
-        Some(Rc::new(SummaryNode {
-            expr: SummaryExpr::ValueOperation {
-                child: maintained,
-                operation: ValueOperation::ReadPopulation { readout },
-                timing: ExecutionTiming::QueryTime,
-            },
-            schema: plain(root.output_schema().ok()?),
-            guarantee: Some(ResultGuarantee::exact("exact current-population readout")),
-        }))
+            ))),
+        );
+        Some(std::rc::Rc::new(
+            OperatorNode::with_schema(
+                asap_types::ir::Operator::ASAP(ASAPOp::EvaluatePopulation {
+                    child: maintained,
+                    evaluation,
+                }),
+                root.schema.clone(),
+            )
+            .with_guarantee(Some(ResultGuarantee::exact(
+                "exact current-population evaluation",
+            ))),
+        ))
     }
 }
 impl ReplacementStrategy for MaintainedPopulationStrategy {
@@ -312,10 +314,10 @@ impl ReplacementStrategy for MaintainedPopulationStrategy {
         self.candidate(target.root)
             .map(|node| ReplacementSubDAG {
                 strategy: "MaintainedPopulationStrategy",
-                replacement: Replacement::Summary(node),
+                replacement: Replacement::SubDAG(node),
                 provenance: ReplacementProvenance::SummaryRealization,
                 rationale:
-                    "share an exact maintained population across compatible aggregate readouts"
+                    "share an exact maintained population across compatible aggregate evaluations"
                         .into(),
             })
             .into_iter()
@@ -327,10 +329,26 @@ impl ReplacementStrategy for MaintainedPopulationStrategy {
 mod tests {
     use super::*;
     use crate::test_support::lower_promql;
-    use asap_types::post_asap::{compile_post_asap_dag, share_common_summary_sub_dags};
+    use asap_types::ir::cse::share_common_sub_dags;
+    use asap_types::ir::export::compile_physical_asap_dag as export_timed;
+    use asap_types::ir::timing::{apply_lifecycle_timings, LifecycleAssignment, TimingMemo};
 
-    fn lower(q: &str) -> Rc<QueryExpr> {
-        Rc::new(lower_promql(q, asap_types::types::AccuracyTarget::Exact))
+    /// Time `root` under the default lifecycle assignment (which runs the
+    /// data-state / population-contract validation) and export it.
+    fn compile_physical_asap_dag(root: &Rc<OperatorNode>) -> Result<(), String> {
+        root.validate_structure().map_err(|e| e.to_string())?;
+        let timed = apply_lifecycle_timings(
+            root,
+            &LifecycleAssignment::default_maintained(),
+            &mut TimingMemo::new(),
+        )
+        .map_err(|e| format!("{e:?}"))?;
+        export_timed(&timed).map_err(|e| format!("{e:?}"))?;
+        Ok(())
+    }
+
+    fn lower(q: &str) -> Rc<OperatorNode> {
+        lower_promql(q, asap_types::types::AccuracyTarget::Exact)
     }
 
     // Instant scalar aggregations share the same retractable series population.
@@ -351,11 +369,11 @@ mod tests {
             let candidate = rule
                 .candidate(&root)
                 .expect("current-series rule candidate");
-            compile_post_asap_dag(&candidate).expect("typed post-ASAP DAG");
+            compile_physical_asap_dag(&candidate).expect("typed post-ASAP DAG");
         }
     }
 
-    // Different readout parameters retain one shared maintenance producer in the DAG.
+    // Different evaluation parameters retain one shared maintenance producer in the DAG.
     #[test]
     fn quantiles_and_topk_share_a_planner_population() {
         let roots: Vec<_> = [
@@ -379,7 +397,7 @@ mod tests {
             .target_subdag_candidates()
             .flat_map(|g| &g.candidates)
             .any(|c| c.strategy == "MaintainedPopulationStrategy"));
-        let plans = share_common_summary_sub_dags(
+        let plans = share_common_sub_dags(
             roots
                 .iter()
                 .enumerate()
@@ -388,19 +406,11 @@ mod tests {
         );
         let mut producers = Vec::new();
         for (_, plan) in &plans {
-            compile_post_asap_dag(plan).unwrap();
-            let SummaryExpr::ValueOperation {
-                child,
-                operation: ValueOperation::ReadPopulation { .. },
-                ..
-            } = &plan.expr
-            else {
-                panic!("missing typed readout")
+            compile_physical_asap_dag(plan).unwrap();
+            let Operator::ASAP(ASAPOp::EvaluatePopulation { child, .. }) = &plan.operator else {
+                panic!("missing typed evaluation")
             };
-            let SummaryExpr::ValueOperation {
-                operation: ValueOperation::MaintainPopulation { population },
-                ..
-            } = &child.expr
+            let Operator::ASAP(ASAPOp::MaintainPopulation { population, .. }) = &child.operator
             else {
                 panic!("missing maintained population")
             };
@@ -426,14 +436,10 @@ mod tests {
         let (p, _, _) = recognize(&roots[0]).unwrap();
         assert!(matches!(p.input, PopulationInput::CurrentSeries(ref s) if s.grouping.is_empty()));
         let candidate = strategy.candidate(&roots[0]).unwrap();
-        let SummaryExpr::ValueOperation { child, .. } = &candidate.expr else {
+        let Operator::ASAP(ASAPOp::EvaluatePopulation { child, .. }) = &candidate.operator else {
             unreachable!()
         };
-        let SummaryExpr::ValueOperation {
-            operation: ValueOperation::MaintainPopulation { population },
-            ..
-        } = &child.expr
-        else {
+        let Operator::ASAP(ASAPOp::MaintainPopulation { population, .. }) = &child.operator else {
             unreachable!()
         };
         assert_eq!(population.max_k, 5);
@@ -460,58 +466,50 @@ mod tests {
         assert_eq!(p.matchers[0].operation, CurrentSeriesMatch::Regex);
     }
     // Population timing is a lifecycle choice: a retained or rebuilt
-    // population both validate, while its readout must stay at query time.
+    // population both validate, while its evaluation must stay at query time.
     #[test]
     fn population_timing_is_not_structural() {
         let root = lower("topk(5,a)");
         let candidate = MaintainedPopulationStrategy::new(std::slice::from_ref(&root))
             .candidate(&root)
             .unwrap();
-        let with_timings = |population: ExecutionTiming, readout: ExecutionTiming| {
+        use asap_types::post_asap::ExecutionTiming;
+        let with_timings = |population: ExecutionTiming, evaluation: ExecutionTiming| {
             let mut node = (*candidate).clone();
-            let SummaryExpr::ValueOperation { child, timing, .. } = &mut node.expr else {
-                unreachable!()
-            };
-            *timing = readout;
-            let SummaryExpr::ValueOperation { timing, .. } = &mut Rc::make_mut(child).expr else {
+            node.timing = Some(evaluation);
+            let Operator::ASAP(ASAPOp::EvaluatePopulation { child, .. }) = &mut node.operator
+            else {
                 unreachable!()
             };
-            *timing = population;
-            compile_post_asap_dag(&Rc::new(node))
+            Rc::make_mut(child).timing = Some(population);
+            compile_physical_asap_dag(&Rc::new(node))
         };
         use ExecutionTiming::{IngestionTime, QueryTime};
         assert!(with_timings(IngestionTime, QueryTime).is_ok());
         assert!(with_timings(QueryTime, QueryTime).is_ok());
         assert!(with_timings(IngestionTime, IngestionTime).is_err());
     }
-    // A readout cannot reinterpret arbitrary rows as maintained state or exceed its producer's contract.
+    // A evaluation cannot reinterpret arbitrary rows as maintained state or exceed its producer's contract.
     #[test]
     fn malformed_population_dags_fail_closed() {
         let root = lower("topk(5,a)");
         let strategy = MaintainedPopulationStrategy::new(std::slice::from_ref(&root));
         let candidate = strategy.candidate(&root).unwrap();
+        compile_physical_asap_dag(&candidate).expect("the unmodified candidate is legal");
         let mut bad = (*candidate).clone();
-        let SummaryExpr::ValueOperation { operation, .. } = &mut bad.expr else {
+        let Operator::ASAP(ASAPOp::EvaluatePopulation { evaluation, .. }) = &mut bad.operator
+        else {
             unreachable!()
         };
-        *operation = ValueOperation::ReadPopulation {
-            readout: PopulationStatistic::TopK { k: 6 },
-        };
-        assert!(compile_post_asap_dag(&Rc::new(bad.clone())).is_err());
-        let SummaryExpr::ValueOperation {
-            child, operation, ..
-        } = &mut bad.expr
+        *evaluation = PopulationStatistic::TopK { k: 6 };
+        assert!(compile_physical_asap_dag(&Rc::new(bad.clone())).is_err());
+        let Operator::ASAP(ASAPOp::EvaluatePopulation { child, evaluation }) = &mut bad.operator
         else {
             unreachable!()
         };
-        *operation = ValueOperation::ReadPopulation {
-            readout: PopulationStatistic::TopK { k: 5 },
-        };
+        *evaluation = PopulationStatistic::TopK { k: 5 };
         let producer = Rc::make_mut(child);
-        let SummaryExpr::ValueOperation {
-            operation: ValueOperation::MaintainPopulation { population },
-            ..
-        } = &mut producer.expr
+        let Operator::ASAP(ASAPOp::MaintainPopulation { population, .. }) = &mut producer.operator
         else {
             unreachable!()
         };
@@ -519,6 +517,6 @@ mod tests {
             unreachable!()
         };
         spec.metric = "b".into();
-        assert!(compile_post_asap_dag(&Rc::new(bad)).is_err());
+        assert!(compile_physical_asap_dag(&Rc::new(bad)).is_err());
     }
 }
diff --git a/crates/asap-aware-mapping/src/pane_sharing.rs b/crates/asap-aware-mapping/src/pane_sharing.rs
index b5f5bff3a..0d944b2da 100644
--- a/crates/asap-aware-mapping/src/pane_sharing.rs
+++ b/crates/asap-aware-mapping/src/pane_sharing.rs
@@ -1,6 +1,6 @@
 //! Costed reuse of compatible physical pane producers. The executor supplies
 //! an equality key covering source, state, phase and evidence. This pass never
-//! changes logical readout windows or assumes compatibility from metric names.
+//! changes logical evaluation windows or assumes compatibility from metric names.
 
 /// A concrete mergeable-pane implementation and its horizon costs.
 #[derive(Debug, Clone)]
@@ -9,9 +9,9 @@ pub struct PaneReuseCandidate<K> {
     pub lookback_ms: u64,
     /// Build, update, residency and retirement for this producer. Candidates
     /// with the same key must use the same unit costs and pane width, making
-    /// the longest-lived producer sufficient for every readout in the group.
+    /// the longest-lived producer sufficient for every evaluation in the group.
     pub producer_cost: f64,
-    /// Readout cost for all consumers of this distinct producer.
+    /// Evaluation cost for all consumers of this distinct producer.
     pub read_cost: f64,
 }
 
@@ -84,7 +84,7 @@ mod tests {
             read_cost: 2.0,
         }
     }
-    // Share source work once while retaining both readout charges and longest history.
+    // Share source work once while retaining both evaluation charges and longest history.
     #[test]
     fn shares_compatible_windows() {
         assert_eq!(
diff --git a/crates/asap-aware-mapping/src/pass/major.rs b/crates/asap-aware-mapping/src/pass/major.rs
index 3671ece58..7be53e0f0 100644
--- a/crates/asap-aware-mapping/src/pass/major.rs
+++ b/crates/asap-aware-mapping/src/pass/major.rs
@@ -6,10 +6,10 @@
 //! it *one* pass rather than *the* algorithm. `ReplacementStrategy` is
 //! therefore a concept of this pass, not of the optimization interface.
 
+use asap_types::ir::cse::share_common_sub_dags;
 use std::rc::Rc;
 
-use asap_types::post_asap::{share_common_summary_sub_dags, SummaryNode};
-use asap_types::pre_asap::query_expr::QueryExpr;
+use asap_types::ir::OperatorNode;
 use asap_types::types::AccuracyTarget;
 
 use super::{OptimizationInput, OptimizationPass, OptimizeError, PlanOutput, QueryLifecyclePlan};
@@ -39,10 +39,10 @@ impl OptimizationPass for MajorPass {
         // search result carries the workload binding the lifecycle stage and
         // the output both need. CSE may make two identical queries share one
         // `Rc`, but it never drops or reorders a root, so this stays aligned.
-        let roots: Vec<(usize, Rc<QueryExpr>, Option<AccuracyTarget>)> = workload
+        let roots: Vec<(usize, Rc<OperatorNode>, Option<AccuracyTarget>)> = workload
             .entries()
-            .enumerate()
-            .map(|(index, (entry, expr))| {
+            .zip(workload.operator_indices().iter().copied())
+            .map(|((entry, expr), index)| {
                 (
                     index,
                     Rc::clone(expr),
@@ -57,7 +57,7 @@ impl OptimizationPass for MajorPass {
 
         // One index per root, in `CandidateLogicalASAPDAGs::roots` order — which is the order
         // the roots went in, which is `entries()` order.
-        let entry_indices: Vec<usize> = (0..workload.len()).collect();
+        let entry_indices = workload.operator_indices().to_vec();
         let demand = WorkloadDemand {
             workload: workload.query_workload(),
             data_workload: workload.data_workload(),
@@ -94,8 +94,7 @@ impl OptimizationPass for MajorPass {
                 .ok_or_else(|| self.missing_group(*entry_index))?;
             assembled.push(dag);
         }
-        let interned =
-            share_common_summary_sub_dags(assembled.iter().cloned().enumerate().collect());
+        let interned = share_common_sub_dags(assembled.iter().cloned().enumerate().collect());
         let states: Vec<_> = interned
             .iter()
             .map(|(_, dag)| summary_states(dag))
@@ -105,7 +104,7 @@ impl OptimizationPass for MajorPass {
         // their entries, in every plan that reaches it, so each plan picks
         // the same lifecycle for it. When that union cannot be costed the
         // roots keep their own, unshared DAG and entries.
-        let mut shared_entries: Vec<(Rc<SummaryNode>, Option<Vec<usize>>)> = Vec::new();
+        let mut shared_entries: Vec<(Rc<OperatorNode>, Option<Vec<usize>>)> = Vec::new();
         for (position, (entry_index, root)) in space.roots.iter().enumerate() {
             for state in &states[position] {
                 if shared_entries.iter().any(|(s, _)| Rc::ptr_eq(s, state)) {
@@ -183,7 +182,9 @@ impl OptimizationPass for MajorPass {
                 plan,
             });
         }
-        Ok(PlanOutput::new(plans))
+        let mut output = PlanOutput::new(plans);
+        output.scalar_roots = workload.scalar_roots().to_vec();
+        Ok(output)
     }
 }
 
diff --git a/crates/asap-aware-mapping/src/pass/mod.rs b/crates/asap-aware-mapping/src/pass/mod.rs
index a0b993d97..f9dd0ac2d 100644
--- a/crates/asap-aware-mapping/src/pass/mod.rs
+++ b/crates/asap-aware-mapping/src/pass/mod.rs
@@ -17,8 +17,8 @@ mod major;
 use std::collections::BTreeMap;
 use std::rc::Rc;
 
+use asap_types::ir::OperatorNode;
 use asap_types::parsed_workload::ParsedWorkload;
-use asap_types::post_asap::SummaryNode;
 use asap_types::workload::WorkloadError;
 
 use crate::accuracy::{
@@ -173,7 +173,7 @@ pub struct QueryLifecyclePlan {
     pub plan: SummaryMaintenanceLifecyclePlan,
 }
 
-/// One plan per workload entry, in `QueryWorkload::entries()` order;
+/// One multi-root workload DAG with query/lifecycle bindings in entry order;
 /// [`check_contract`] enforces that.
 ///
 /// Plans are not deduplicated across entries: a summary state that several
@@ -184,25 +184,83 @@ pub struct QueryLifecyclePlan {
 #[non_exhaustive]
 pub struct PlanOutput {
     pub plans: Vec<QueryLifecyclePlan>,
+    /// Exact scalar expressions, keyed by workload entry; embedded plan reads remain visible.
+    pub scalar_roots: Vec<(usize, asap_types::ir::ScalarExpr)>,
 }
 
 impl PlanOutput {
     pub fn new(plans: Vec<QueryLifecyclePlan>) -> Self {
-        Self { plans }
+        Self {
+            plans,
+            scalar_roots: Vec::new(),
+        }
     }
 
     /// Entry indices in output order.
     pub fn entry_indices(&self) -> Vec<usize> {
-        self.plans.iter().map(|p| p.entry_index).collect()
+        let mut indices: Vec<_> = self
+            .plans
+            .iter()
+            .map(|p| p.entry_index)
+            .chain(self.scalar_roots.iter().map(|(i, _)| *i))
+            .collect();
+        if !self.scalar_roots.is_empty() {
+            indices.sort_unstable();
+        }
+        indices
+    }
+
+    /// All query roots in workload order, including standalone scalars.
+    pub fn roots(&self) -> Vec<asap_types::ir::QueryRoot> {
+        let mut roots: Vec<_> = self
+            .plans
+            .iter()
+            .map(|p| {
+                (
+                    p.entry_index,
+                    asap_types::ir::QueryRoot::Operator(Rc::clone(&p.plan.root)),
+                )
+            })
+            .chain(
+                self.scalar_roots
+                    .iter()
+                    .map(|(i, expr)| (*i, asap_types::ir::QueryRoot::Scalar(expr.clone()))),
+            )
+            .collect();
+        roots.sort_by_key(|(i, _)| *i);
+        roots.into_iter().map(|(_, root)| root).collect()
     }
 
-    /// The selected DAG root per query.
-    pub fn dags(&self) -> Vec<Rc<SummaryNode>> {
+    /// The selected operator roots. Use `roots()` to include scalar queries.
+    pub fn operator_roots(&self) -> Vec<Rc<OperatorNode>> {
         self.plans.iter().map(|p| Rc::clone(&p.plan.root)).collect()
     }
 
+    /// Unique operators in the entire workload DAG, including scalar-plan dependencies.
+    /// Several query roots can reach the same operator; it is returned once.
+    pub fn operators(&self) -> Vec<Rc<OperatorNode>> {
+        let mut seen = std::collections::HashSet::new();
+        let mut nodes = Vec::new();
+        for root in self.roots() {
+            let inputs = match root {
+                asap_types::ir::QueryRoot::Operator(node) => vec![node],
+                asap_types::ir::QueryRoot::Scalar(expr) => {
+                    expr.operator_refs().into_iter().cloned().collect()
+                }
+            };
+            for input in inputs {
+                for node in OperatorNode::reachable(&input) {
+                    if seen.insert(Rc::as_ptr(&node)) {
+                        nodes.push(node);
+                    }
+                }
+            }
+        }
+        nodes
+    }
+
     pub fn len(&self) -> usize {
-        self.plans.len()
+        self.plans.len() + self.scalar_roots.len()
     }
 
     pub fn is_empty(&self) -> bool {
diff --git a/crates/asap-aware-mapping/src/physical_operator_statistics.rs b/crates/asap-aware-mapping/src/physical_operator_statistics.rs
index 7be1d292c..1d2b9ebb0 100644
--- a/crates/asap-aware-mapping/src/physical_operator_statistics.rs
+++ b/crates/asap-aware-mapping/src/physical_operator_statistics.rs
@@ -6,7 +6,9 @@
 
 use std::collections::HashMap;
 
-use asap_types::pre_asap::query_expr::{InfoMatcher, Predicate, Source};
+use asap_types::ir::operator_properties::{InfoMatcher, Source};
+use asap_types::ir::Predicate;
+
 use asap_types::workload::{
     DataArrival, DataWorkload, DurationMs, QueryRecurrence, QueryWorkloadEntry, RepeatedDemand,
     TimeSelection, TimestampMs,
@@ -278,8 +280,8 @@ pub struct PartitionStatistics {
 /// is the authoritative operator vocabulary: every one of its variants has a
 /// matching statistics variant here.
 ///
-/// This enum intentionally does not mirror either logical IR. `QueryExpr` and
-/// `SummaryExpr` are inputs to physical lowering, and one logical node may
+/// This enum intentionally does not mirror the logical IR. `OperatorNode`s
+/// are inputs to physical lowering, and one logical node may
 /// expand into several physical nodes or choose among several algorithms.
 /// Physical configuration such as a Top-K limit or hash-join build side lives
 /// on `PhysicalOperator`; this enum contains only workload/catalog evidence
diff --git a/crates/asap-aware-mapping/src/physical_plan_cost_model.rs b/crates/asap-aware-mapping/src/physical_plan_cost_model.rs
index 509e6a13a..d846f907b 100644
--- a/crates/asap-aware-mapping/src/physical_plan_cost_model.rs
+++ b/crates/asap-aware-mapping/src/physical_plan_cost_model.rs
@@ -2,8 +2,9 @@
 
 use std::{cell::RefCell, rc::Rc};
 
-use asap_types::post_asap::{SketchAlgorithm, SummaryExpr, SummaryNode};
-use asap_types::pre_asap::{AggIntent, QueryExpr};
+use asap_types::ir::OperatorNode;
+use asap_types::post_asap::SketchAlgorithm;
+use asap_types::pre_asap::AggIntent;
 use asap_types::resources::CacheProfile;
 
 use crate::analytical_cost::{
@@ -40,7 +41,7 @@ pub struct PhysicalEvidenceSnapshot {
 /// operator. Post-ASAP summary operators need a physical plan provider because their
 /// implementation, placement, and retained-state layout are deployment
 /// choices; that provider must return the complete summary DAG, including any
-/// embedded `KeepPreAsap` work.
+/// non-ASAP work kept inside it.
 pub trait PlannerPhysicalPlanProvider {
     /// Atomically captures the comparison scope and evidence generation.
     fn capture_evidence_snapshot(
@@ -57,7 +58,7 @@ pub trait PlannerPhysicalPlanProvider {
     fn summary_physical_dag(
         &self,
         snapshot: &PhysicalEvidenceSnapshot,
-        summary: &Rc<SummaryNode>,
+        summary: &Rc<OperatorNode>,
         target: &TargetSubDAG<'_>,
     ) -> Result<PhysicalDAG, AnalyticalCostError>;
 }
@@ -91,7 +92,7 @@ pub struct PhysicalPlanCostModel<'a> {
 }
 
 struct CachedTargetEvidence {
-    root: Rc<QueryExpr>,
+    root: Rc<OperatorNode>,
     consumer_count: usize,
     snapshot: PhysicalEvidenceSnapshot,
     raw: PhysicalDAG,
@@ -188,15 +189,14 @@ impl<'a> PhysicalPlanCostModel<'a> {
             Replacement::ExactComposition(_) => {
                 return Err(AnalyticalCostError::UnsupportedCandidate)
             }
-            Replacement::Rewrite(query) => lower_query_physical_dag(query, scope, &evidence)?,
-            Replacement::Summary(summary) => match &summary.expr {
-                SummaryExpr::KeepPreAsap(query) => {
-                    lower_query_physical_dag(query, scope, &evidence)?
-                }
-                _ => self
-                    .provider
-                    .summary_physical_dag(&snapshot, summary, target)?,
-            },
+            // A sub-DAG without summary state is the planner's own query
+            // lowering; anything with summary state is deployment-provided.
+            Replacement::SubDAG(sub_dag) if !sub_dag.contains_asap() => {
+                lower_query_physical_dag(sub_dag, scope, &evidence)?
+            }
+            Replacement::SubDAG(summary) => self
+                .provider
+                .summary_physical_dag(&snapshot, summary, target)?,
         };
         let resources = estimate_physical_dag_comparison(
             PhysicalDAGEstimateRequest {
@@ -359,7 +359,8 @@ mod tests {
     use std::cell::Cell;
     use std::collections::HashMap;
 
-    use asap_types::pre_asap::{DataType, Field, QueryExpr, Reduction, Schema, Source};
+    use asap_types::ir::{NonASAPOp, OperatorNode};
+    use asap_types::pre_asap::{DataType, Field, Reduction, Schema, Source};
     use asap_types::types::AccuracyTarget;
     use asap_types::workload::{
         DataArrival, DurationMs, QueryRecurrence, QueryTimeScope, TimeSelection, TimestampMs,
@@ -405,8 +406,16 @@ mod tests {
         }
     }
 
-    fn query() -> Rc<QueryExpr> {
-        Rc::new(QueryExpr::Aggregate {
+    fn query() -> Rc<OperatorNode> {
+        let scan = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
+            source: Source::Table {
+                table_ref: "events".into(),
+            },
+            predicates: vec![],
+            schema: Schema::new(vec![Field::plain("value", DataType::Float64, false)]),
+        }))
+        .unwrap();
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
             reduction: Reduction::by(vec![]),
             measures: vec![AggIntent::Count {
                 accuracy: AccuracyTarget::Epsilon(0.01),
@@ -414,14 +423,9 @@ mod tests {
             output_names: vec![],
             filters: vec![],
             having: None,
-            child: Rc::new(QueryExpr::Scan {
-                source: Source::Table {
-                    table_ref: "events".into(),
-                },
-                predicates: vec![],
-                schema: Schema::new(vec![Field::plain("value", DataType::Float64, false)]),
-            }),
-        })
+            child: scan,
+        }))
+        .unwrap()
     }
 
     fn scope() -> ComparisonScope {
@@ -583,7 +587,7 @@ mod tests {
         fn summary_physical_dag(
             &self,
             snapshot: &PhysicalEvidenceSnapshot,
-            _summary: &Rc<SummaryNode>,
+            _summary: &Rc<OperatorNode>,
             _target: &TargetSubDAG<'_>,
         ) -> Result<PhysicalDAG, AnalyticalCostError> {
             assert_eq!(snapshot.version, "test-snapshot-1");
@@ -687,7 +691,7 @@ mod tests {
             version: "unused-base-v1".into(),
         };
         let candidates =
-            crate::replacement::SketchAlgorithmStrategy::default_cost_model().replacements(&target);
+            crate::replacement::ASAPStrategies::default_cost_model().replacements(&target);
         provider.storage_io = Some(profile.clone());
         let model = PhysicalPlanCostModel::new(&provider, base.clone()).unwrap();
         let estimate = model.estimate_candidate(&candidates[0], &target).unwrap();
@@ -718,7 +722,7 @@ mod tests {
         let root = query();
         let target = TargetSubDAG::new(&root);
         let candidates =
-            crate::replacement::SketchAlgorithmStrategy::default_cost_model().replacements(&target);
+            crate::replacement::ASAPStrategies::default_cost_model().replacements(&target);
         let provider = TestProvider::new(true, 800);
         let model = PhysicalPlanCostModel::new(&provider, calibration()).unwrap();
         let estimate = model.estimate_candidate(&candidates[0], &target).unwrap();
@@ -913,7 +917,7 @@ mod tests {
             fn summary_physical_dag(
                 &self,
                 snapshot: &PhysicalEvidenceSnapshot,
-                summary: &Rc<SummaryNode>,
+                summary: &Rc<OperatorNode>,
                 target: &TargetSubDAG<'_>,
             ) -> Result<PhysicalDAG, AnalyticalCostError> {
                 self.0.summary_physical_dag(snapshot, summary, target)
@@ -1001,7 +1005,7 @@ mod tests {
             fn summary_physical_dag(
                 &self,
                 snapshot: &PhysicalEvidenceSnapshot,
-                summary: &Rc<SummaryNode>,
+                summary: &Rc<OperatorNode>,
                 target: &TargetSubDAG<'_>,
             ) -> Result<PhysicalDAG, AnalyticalCostError> {
                 let mut dag = self.0.summary_physical_dag(snapshot, summary, target)?;
@@ -1015,7 +1019,7 @@ mod tests {
         }
 
         let root = query();
-        let candidates = crate::replacement::SketchAlgorithmStrategy::default_cost_model()
+        let candidates = crate::replacement::ASAPStrategies::default_cost_model()
             .replacements(&TargetSubDAG::new(&root));
         let provider = WrongScope(TestProvider::new(true, 800));
         let model = PhysicalPlanCostModel::new(&provider, calibration()).unwrap();
@@ -1053,7 +1057,7 @@ mod tests {
             fn summary_physical_dag(
                 &self,
                 _snapshot: &PhysicalEvidenceSnapshot,
-                _summary: &Rc<SummaryNode>,
+                _summary: &Rc<OperatorNode>,
                 _target: &TargetSubDAG<'_>,
             ) -> Result<PhysicalDAG, AnalyticalCostError> {
                 panic!("blank snapshot versions must fail before summary binding")
@@ -1061,7 +1065,7 @@ mod tests {
         }
 
         let root = query();
-        let candidates = crate::replacement::SketchAlgorithmStrategy::default_cost_model()
+        let candidates = crate::replacement::ASAPStrategies::default_cost_model()
             .replacements(&TargetSubDAG::new(&root));
         let model = PhysicalPlanCostModel::new(&BlankVersionProvider, calibration()).unwrap();
         assert_eq!(
@@ -1088,7 +1092,7 @@ mod tests {
     #[test]
     fn sibling_candidates_share_one_scope_and_raw_baseline() {
         let root = query();
-        let candidates = crate::replacement::SketchAlgorithmStrategy::default_cost_model()
+        let candidates = crate::replacement::ASAPStrategies::default_cost_model()
             .replacements(&TargetSubDAG::new(&root));
         assert!(candidates.len() >= 2);
         let provider = TestProvider::new(true, 800);
diff --git a/crates/asap-aware-mapping/src/query_physical_lowering.rs b/crates/asap-aware-mapping/src/query_physical_lowering.rs
index 65b7fab93..055d19c79 100644
--- a/crates/asap-aware-mapping/src/query_physical_lowering.rs
+++ b/crates/asap-aware-mapping/src/query_physical_lowering.rs
@@ -1,7 +1,9 @@
-//! Recursive lowering from the canonical query IR to evidenced physical DAGs.
+//! Recursive lowering from the operator IR to evidenced physical DAGs.
 
 use std::rc::Rc;
 
+use asap_types::ir::{NonASAPOp, OperatorNode, ScalarExpr};
+
 use crate::analytical_cost::{
     validate_operator_semantics, AnalyticalCostError, EvidenceBackedPhysicalDAG,
     ExecutionMultiplicity, HashJoinBuildSide, PhysicalDAGNode, PhysicalNodeEvidence,
@@ -13,7 +15,7 @@ use crate::physical_operator_statistics::{
 };
 
 pub struct PhysicalNodeRequest<'a> {
-    pub logical_node: &'a asap_types::pre_asap::QueryExpr,
+    pub logical_node: &'a OperatorNode,
     pub operator: PhysicalOperator,
     pub occurrence: usize,
     pub synthetic: bool,
@@ -40,19 +42,19 @@ where
     }
 }
 
-/// Lower a resolved query operator DAG to the physical operators understood by
+/// Lower a non-ASAP operator DAG to the physical operators understood by
 /// this cost model. The authoritative provider supplies statistics by the
 /// stable physical IDs owned by that provider; missing evidence makes the
 /// complete query unavailable. Scalar expressions remain part of their
-/// containing operator's local cost.
+/// containing operator's local cost. An ASAP node is unsupported here.
 pub fn lower_query_physical_dag(
-    root: &Rc<asap_types::pre_asap::QueryExpr>,
+    root: &Rc<OperatorNode>,
     scope: &ComparisonScope,
     evidence: &dyn PhysicalNodeEvidenceProvider,
 ) -> Result<EvidenceBackedPhysicalDAG, AnalyticalCostError> {
     use std::collections::HashMap;
 
-    use asap_types::pre_asap::{GroupKeys, QueryExpr, RelationalSetOpKind};
+    use asap_types::pre_asap::{GroupKeys, RelationalSetOpKind};
 
     scope.validate()?;
 
@@ -65,7 +67,7 @@ pub fn lower_query_physical_dag(
     }
 
     impl Lowerer<'_> {
-        fn lower(&mut self, query: &QueryExpr) -> Result<String, AnalyticalCostError> {
+        fn lower(&mut self, query: &OperatorNode) -> Result<String, AnalyticalCostError> {
             let occurrence = self.next_id;
             self.next_id += 1;
             self.lower_new(query, occurrence)
@@ -73,7 +75,7 @@ pub fn lower_query_physical_dag(
 
         fn resolve(
             &self,
-            query: &QueryExpr,
+            query: &OperatorNode,
             operator: PhysicalOperator,
             occurrence: usize,
             synthetic: bool,
@@ -128,12 +130,23 @@ pub fn lower_query_physical_dag(
 
         fn lower_unary(
             &mut self,
-            query: &QueryExpr,
+            query: &OperatorNode,
             occurrence: usize,
             operator: PhysicalOperator,
-            child: &QueryExpr,
+            child: &OperatorNode,
         ) -> Result<String, AnalyticalCostError> {
             let child_id = self.lower(child)?;
+            self.push_unary(query, occurrence, operator, child_id)
+        }
+
+        /// `operator` over an already-lowered child.
+        fn push_unary(
+            &mut self,
+            query: &OperatorNode,
+            occurrence: usize,
+            operator: PhysicalOperator,
+            child_id: String,
+        ) -> Result<String, AnalyticalCostError> {
             let children = vec![child_id.clone()];
             let evidence = self.resolve(query, operator, occurrence, false, &children, None)?;
             let statistics = &evidence.statistics;
@@ -151,17 +164,17 @@ pub fn lower_query_physical_dag(
 
         fn lower_promql_unary(
             &mut self,
-            query: &QueryExpr,
+            query: &OperatorNode,
             occurrence: usize,
             operator: PhysicalOperator,
-            child: &QueryExpr,
+            child: &OperatorNode,
         ) -> Result<String, AnalyticalCostError> {
             self.lower_unary(query, occurrence, operator, child)
         }
 
         fn lower_promql_scalar_leaf(
             &mut self,
-            query: &QueryExpr,
+            query: &OperatorNode,
             occurrence: usize,
         ) -> Result<String, AnalyticalCostError> {
             let operator = PhysicalOperator::PromqlScalarLeaf;
@@ -171,6 +184,28 @@ pub fn lower_query_physical_dag(
             self.push(evidence, operator, vec![], None)
         }
 
+        /// Lower the owned scalar operand of `vector(s)`. A literal or
+        /// `time()` is a physical scalar leaf; `scalar(v)` reads its vector
+        /// through `PromqlVectorToScalar`.
+        fn lower_scalar_operand(
+            &mut self,
+            query: &OperatorNode,
+            occurrence: usize,
+            expr: &ScalarExpr,
+        ) -> Result<String, AnalyticalCostError> {
+            match expr {
+                ScalarExpr::Literal(asap_types::pre_asap::ScalarValue::Float64(_))
+                | ScalarExpr::EvalTimestamp => self.lower_promql_scalar_leaf(query, occurrence),
+                ScalarExpr::PromqlScalarFromVector(vector) => self.lower_promql_unary(
+                    query,
+                    occurrence,
+                    PhysicalOperator::PromqlVectorToScalar,
+                    vector,
+                ),
+                _ => Err(AnalyticalCostError::UnsupportedQueryOperator),
+            }
+        }
+
         fn node_statistics(&self, id: &str) -> Result<&OperatorStatistics, AnalyticalCostError> {
             self.evidence
                 .get(id)
@@ -182,11 +217,14 @@ pub fn lower_query_physical_dag(
 
         fn lower_new(
             &mut self,
-            query: &QueryExpr,
+            query: &OperatorNode,
             occurrence: usize,
         ) -> Result<String, AnalyticalCostError> {
-            match query {
-                QueryExpr::Scan {
+            let Some(op) = query.non_asap() else {
+                return Err(AnalyticalCostError::UnsupportedQueryOperator);
+            };
+            match op {
+                NonASAPOp::Scan {
                     source, predicates, ..
                 } => {
                     let coverage = bind_scan_coverage(
@@ -252,13 +290,13 @@ pub fn lower_query_physical_dag(
                     require_operator_statistics(filter_operator, &filter_evidence.statistics)?;
                     self.push(filter_evidence, filter_operator, children, None)
                 }
-                QueryExpr::Filter { pred, child } => {
+                NonASAPOp::Filter { pred, child } => {
                     let operator = PhysicalOperator::Filter {
                         predicate_operations_per_row: scalar_operation_count(&pred.0)?.max(1),
                     };
                     self.lower_unary(query, occurrence, operator, child)
                 }
-                QueryExpr::Project { cols, child, .. } => {
+                NonASAPOp::Project { cols, child, .. } => {
                     let expression_operations_per_row = cols
                         .iter()
                         .try_fold(0_u64, |total, item| {
@@ -280,7 +318,7 @@ pub fn lower_query_physical_dag(
                         child,
                     )
                 }
-                QueryExpr::Aggregate {
+                NonASAPOp::Aggregate {
                     reduction,
                     measures,
                     filters,
@@ -289,7 +327,7 @@ pub fn lower_query_physical_dag(
                     ..
                 } => {
                     if having.is_some()
-                        || asap_types::pre_asap::any_measure_filtered(filters)
+                        || asap_types::ir::non_asap::any_measure_filtered(filters)
                         || measures.is_empty()
                     {
                         return Err(AnalyticalCostError::UnsupportedQueryOperator);
@@ -338,13 +376,9 @@ pub fn lower_query_physical_dag(
                         child,
                     )
                 }
-                QueryExpr::Dedup { cols, child } => {
+                NonASAPOp::Dedup { cols, child } => {
                     let key_count = if cols.is_empty() {
-                        child
-                            .output_schema()
-                            .map_err(|_| AnalyticalCostError::UnsupportedQueryOperator)?
-                            .fields
-                            .len()
+                        child.schema.fields.len()
                     } else {
                         cols.len()
                     };
@@ -361,7 +395,7 @@ pub fn lower_query_physical_dag(
                         child,
                     )
                 }
-                QueryExpr::Sort {
+                NonASAPOp::Sort {
                     keys,
                     partition_by,
                     child,
@@ -381,13 +415,26 @@ pub fn lower_query_physical_dag(
                         child,
                     )
                 }
-                QueryExpr::Limit { n, offset, child } => {
-                    if let QueryExpr::Sort {
+                NonASAPOp::Limit {
+                    n,
+                    offset,
+                    partition_by: limit_partition_by,
+                    child,
+                } => {
+                    // Offset-only and per-group limits have no physical
+                    // operator here.
+                    let Some(n) = n else {
+                        return Err(AnalyticalCostError::UnsupportedQueryOperator);
+                    };
+                    if limit_partition_by != &GroupKeys::none() {
+                        return Err(AnalyticalCostError::UnsupportedQueryOperator);
+                    }
+                    if let Some(NonASAPOp::Sort {
                         keys,
                         partition_by,
                         child: sorted_child,
                         ..
-                    } = child.as_ref()
+                    }) = child.non_asap()
                     {
                         if !keys.is_empty() && partition_by == &GroupKeys::none() {
                             let child_id = self.lower(sorted_child)?;
@@ -442,7 +489,7 @@ pub fn lower_query_physical_dag(
                     require_operator_statistics(operator, statistics)?;
                     self.push(evidence, operator, children, None)
                 }
-                QueryExpr::SQLWindowFunc {
+                NonASAPOp::SQLWindowFunc {
                     func,
                     partition_by,
                     order_by,
@@ -472,7 +519,7 @@ pub fn lower_query_physical_dag(
                         child,
                     )
                 }
-                QueryExpr::TimeRange { range, child } => {
+                NonASAPOp::TimeRange { range, child, .. } => {
                     let range_millis = duration_millis(*range, "range")?;
                     self.lower_promql_unary(
                         query,
@@ -481,7 +528,7 @@ pub fn lower_query_physical_dag(
                         child,
                     )
                 }
-                QueryExpr::PromqlSubquery {
+                NonASAPOp::PromqlSubquery {
                     range,
                     resolution,
                     child,
@@ -513,7 +560,7 @@ pub fn lower_query_physical_dag(
                     }
                     Ok(id)
                 }
-                QueryExpr::PromqlRelabel { value, child, .. } => self.lower_promql_unary(
+                NonASAPOp::PromqlRelabel { value, child, .. } => self.lower_promql_unary(
                     query,
                     occurrence,
                     PhysicalOperator::PromqlRelabel {
@@ -521,7 +568,7 @@ pub fn lower_query_physical_dag(
                     },
                     child,
                 ),
-                QueryExpr::PromqlSeriesSample {
+                NonASAPOp::PromqlSeriesSample {
                     by, kind, child, ..
                 } => {
                     if by.is_without() {
@@ -557,7 +604,7 @@ pub fn lower_query_physical_dag(
                         child,
                     )
                 }
-                QueryExpr::PromqlInfoEnrich { selector, child } => {
+                NonASAPOp::PromqlInfoEnrich { selector, child } => {
                     let left_id = self.lower(child)?;
                     let coverage = bind_info_coverage(
                         &format!("occurrence-{occurrence}-info"),
@@ -609,34 +656,13 @@ pub fn lower_query_physical_dag(
                     require_operator_statistics(operator, &evidence.statistics)?;
                     self.push(evidence, operator, children, None)
                 }
-                QueryExpr::BinaryOp {
-                    op,
-                    lhs,
-                    rhs,
-                    vector_match,
+                NonASAPOp::BinaryOp {
+                    operator, lhs, rhs, ..
                 } => {
-                    let left_scalar = is_promql_scalar(lhs);
-                    let right_scalar = is_promql_scalar(rhs);
-                    if left_scalar && right_scalar {
-                        return Err(AnalyticalCostError::UnsupportedQueryOperator);
-                    }
+                    let op = &operator.kind;
+                    let vector_match = &operator.vector_match;
                     let operation = promql_binary_operation(op);
-                    if (left_scalar || right_scalar)
-                        && !matches!(operation, PromqlBinaryOperation::ArithmeticOrComparison)
-                    {
-                        return Err(AnalyticalCostError::UnsupportedQueryOperator);
-                    }
-                    let operand_mode = match (left_scalar, right_scalar) {
-                        (false, false) => PromqlBinaryOperandMode::VectorVector,
-                        (false, true) => PromqlBinaryOperandMode::VectorScalar,
-                        (true, false) => PromqlBinaryOperandMode::ScalarVector,
-                        (true, true) => unreachable!("scalar/scalar returned above"),
-                    };
-                    if operand_mode != PromqlBinaryOperandMode::VectorVector
-                        && vector_match.is_some()
-                    {
-                        return Err(AnalyticalCostError::UnsupportedQueryOperator);
-                    }
+                    let operand_mode = PromqlBinaryOperandMode::VectorVector;
                     let cardinality = promql_vector_cardinality(vector_match.as_ref());
                     let left_id = self.lower(lhs)?;
                     let right_id = self.lower(rhs)?;
@@ -670,41 +696,31 @@ pub fn lower_query_physical_dag(
                     require_operator_statistics(operator, &evidence.statistics)?;
                     self.push(evidence, operator, children, None)
                 }
-                QueryExpr::PromqlVectorFromScalar(child) => self.lower_promql_unary(
-                    query,
-                    occurrence,
-                    PhysicalOperator::PromqlScalarToVector,
-                    child,
-                ),
-                QueryExpr::PromqlScalarFromVector(child) => self.lower_promql_unary(
-                    query,
-                    occurrence,
-                    PhysicalOperator::PromqlVectorToScalar,
-                    child,
-                ),
-                QueryExpr::PromqlScalarBridge(inner)
-                    if matches!(
-                        inner.as_ref(),
-                        QueryExpr::Literal(asap_types::pre_asap::ScalarValue::Float64(_))
-                    ) =>
-                {
-                    self.lower_promql_scalar_leaf(query, occurrence)
+                NonASAPOp::PromqlVectorFromScalar(scalar) => {
+                    let scalar_occurrence = self.next_id;
+                    self.next_id += 1;
+                    let child_id = self.lower_scalar_operand(query, scalar_occurrence, scalar)?;
+                    self.push_unary(
+                        query,
+                        occurrence,
+                        PhysicalOperator::PromqlScalarToVector,
+                        child_id,
+                    )
                 }
-                QueryExpr::EvalTimestamp => self.lower_promql_scalar_leaf(query, occurrence),
-                QueryExpr::TimeShift { shift, child } => {
+                NonASAPOp::TimeShift { shift, child } => {
                     if !shift.is_identity() {
                         return Err(AnalyticalCostError::UnsupportedQueryOperator);
                     }
                     self.lower_unary(query, occurrence, PhysicalOperator::PassThrough, child)
                 }
-                QueryExpr::Concat { children, .. } => {
+                NonASAPOp::Concat { children, .. } => {
                     let child_ids = children
                         .iter()
                         .map(|child| self.lower(child))
                         .collect::<Result<Vec<_>, _>>()?;
                     self.lower_concat(query, occurrence, child_ids)
                 }
-                QueryExpr::SetOp {
+                NonASAPOp::SetOp {
                     kind: RelationalSetOpKind::Union,
                     all: true,
                     left,
@@ -714,7 +730,7 @@ pub fn lower_query_physical_dag(
                     let right_id = self.lower(right)?;
                     self.lower_concat(query, occurrence, vec![left_id, right_id])
                 }
-                QueryExpr::Join {
+                NonASAPOp::Join {
                     kind,
                     pred,
                     left,
@@ -764,7 +780,7 @@ pub fn lower_query_physical_dag(
 
         fn lower_concat(
             &mut self,
-            query: &QueryExpr,
+            query: &OperatorNode,
             occurrence: usize,
             child_ids: Vec<String>,
         ) -> Result<String, AnalyticalCostError> {
@@ -957,7 +973,7 @@ fn require_operator_statistics(
 fn bind_scan_coverage(
     node_id: &str,
     source: &asap_types::pre_asap::Source,
-    predicates: &[asap_types::pre_asap::Predicate],
+    predicates: &[asap_types::ir::Predicate],
     scope: &ComparisonScope,
 ) -> Result<ScanSelection, AnalyticalCostError> {
     let mut matches = scope.sources.iter().filter(|coverage| {
@@ -1051,17 +1067,14 @@ fn promql_vector_cardinality(
 }
 
 fn hash_join_key_count(
-    expr: &asap_types::pre_asap::QueryExpr,
-    left: &asap_types::pre_asap::QueryExpr,
-    right: &asap_types::pre_asap::QueryExpr,
+    expr: &ScalarExpr,
+    left: &OperatorNode,
+    right: &OperatorNode,
 ) -> Option<u64> {
-    use asap_types::pre_asap::{CompareOpKind, QueryExpr};
+    use asap_types::pre_asap::CompareOpKind;
 
-    let (Ok(left_schema), Ok(right_schema)) = (left.output_schema(), right.output_schema()) else {
-        return None;
-    };
-    let left_width = left_schema.fields.len();
-    let total_width = left_width.saturating_add(right_schema.fields.len());
+    let left_width = left.schema.fields.len();
+    let total_width = left_width.saturating_add(right.schema.fields.len());
 
     fn column_side(column: usize, left_width: usize, total_width: usize) -> Option<bool> {
         if column < left_width {
@@ -1073,14 +1086,15 @@ fn hash_join_key_count(
         }
     }
 
-    fn predicate(expr: &QueryExpr, left_width: usize, total_width: usize) -> Option<u64> {
+    fn predicate(expr: &ScalarExpr, left_width: usize, total_width: usize) -> Option<u64> {
         match expr {
-            QueryExpr::Compare {
+            ScalarExpr::Compare {
                 left,
                 op: CompareOpKind::Eq,
                 right,
+                ..
             } => match (left.as_ref(), right.as_ref()) {
-                (QueryExpr::Column(left), QueryExpr::Column(right)) => match (
+                (ScalarExpr::Column(left), ScalarExpr::Column(right)) => match (
                     column_side(*left, left_width, total_width),
                     column_side(*right, left_width, total_width),
                 ) {
@@ -1089,7 +1103,7 @@ fn hash_join_key_count(
                 },
                 _ => None,
             },
-            QueryExpr::BoolAnd(parts) if !parts.is_empty() => {
+            ScalarExpr::BoolAnd(parts) if !parts.is_empty() => {
                 parts.iter().try_fold(0_u64, |count, part| {
                     count.checked_add(predicate(part, left_width, total_width)?)
                 })
@@ -1101,12 +1115,8 @@ fn hash_join_key_count(
     predicate(expr, left_width, total_width)
 }
 
-fn scalar_operation_count(
-    expr: &asap_types::pre_asap::QueryExpr,
-) -> Result<u64, AnalyticalCostError> {
-    use asap_types::pre_asap::QueryExpr;
-
-    let add = |parts: &[&QueryExpr]| {
+fn scalar_operation_count(expr: &ScalarExpr) -> Result<u64, AnalyticalCostError> {
+    let add = |parts: &[&ScalarExpr]| {
         parts.iter().try_fold(0_u64, |total, part| {
             total
                 .checked_add(scalar_operation_count(part)?)
@@ -1119,14 +1129,14 @@ fn scalar_operation_count(
             .ok_or(AnalyticalCostError::Overflow)
     };
     match expr {
-        QueryExpr::Column(_)
-        | QueryExpr::Literal(_)
-        | QueryExpr::EvalTimestamp
-        | QueryExpr::CurrentTimestamp => Ok(0),
-        QueryExpr::Compare { left, right, .. } | QueryExpr::Arithmetic { left, right, .. } => {
+        ScalarExpr::Column(_)
+        | ScalarExpr::Literal(_)
+        | ScalarExpr::EvalTimestamp
+        | ScalarExpr::CurrentTimestamp => Ok(0),
+        ScalarExpr::Compare { left, right, .. } | ScalarExpr::Arithmetic { left, right, .. } => {
             with_local(&[left, right])
         }
-        QueryExpr::BoolAnd(parts) | QueryExpr::BoolOr(parts) => {
+        ScalarExpr::BoolAnd(parts) | ScalarExpr::BoolOr(parts) => {
             let children = parts.iter().collect::<Vec<_>>();
             add(&children)?
                 .checked_add(
@@ -1135,12 +1145,11 @@ fn scalar_operation_count(
                 )
                 .ok_or(AnalyticalCostError::Overflow)
         }
-        QueryExpr::Not(child)
-        | QueryExpr::IsNull(child)
-        | QueryExpr::IsNotNull(child)
-        | QueryExpr::PromqlScalarBridge(child) => with_local(&[child]),
-        QueryExpr::Cast { expr, .. } => with_local(&[expr]),
-        QueryExpr::InList { expr, list, .. } => {
+        ScalarExpr::Not(child) | ScalarExpr::IsNull(child) | ScalarExpr::IsNotNull(child) => {
+            with_local(&[child])
+        }
+        ScalarExpr::Cast { expr, .. } => with_local(&[expr]),
+        ScalarExpr::InList { expr, list, .. } => {
             let mut children = Vec::with_capacity(list.len() + 1);
             children.push(expr.as_ref());
             children.extend(list.iter());
@@ -1148,11 +1157,11 @@ fn scalar_operation_count(
                 .checked_add(u64::try_from(list.len()).map_err(|_| AnalyticalCostError::Overflow)?)
                 .ok_or(AnalyticalCostError::Overflow)
         }
-        QueryExpr::FunctionCall { args, .. } => {
+        ScalarExpr::FunctionCall { args, .. } => {
             let children = args.iter().collect::<Vec<_>>();
             with_local(&children)
         }
-        QueryExpr::Case {
+        ScalarExpr::Case {
             operand,
             branches,
             else_expr,
@@ -1246,16 +1255,6 @@ fn fixed_state_per_series_intent(intent: &asap_types::pre_asap::AggIntent) -> bo
     )
 }
 
-fn is_promql_scalar(query: &asap_types::pre_asap::QueryExpr) -> bool {
-    use asap_types::pre_asap::QueryExpr;
-    matches!(
-        query,
-        QueryExpr::PromqlScalarBridge(_)
-            | QueryExpr::PromqlScalarFromVector(_)
-            | QueryExpr::EvalTimestamp
-    )
-}
-
 #[cfg(test)]
 mod tests {
     use super::*;
@@ -1266,6 +1265,7 @@ mod tests {
         validate_comparison_scopes, BinaryEdgeStatistics, PartitionStatistics,
         PromqlEdgeStatistics, PromqlUnaryEdgeStatistics, PromqlValueKind, UnaryEdgeStatistics,
     };
+    use asap_types::ir::{BinaryOperator, ExprSemantics, Predicate, SortKey, TimeRangeKind};
     use asap_types::workload::{
         DataArrival, DurationMs, QueryRecurrence, QueryTimeScope, TimeSelection, TimestampMs,
     };
@@ -1401,10 +1401,7 @@ mod tests {
         }
     }
 
-    fn coverage(
-        source: asap_types::pre_asap::Source,
-        predicates: Vec<asap_types::pre_asap::Predicate>,
-    ) -> ScanSelection {
+    fn coverage(source: asap_types::pre_asap::Source, predicates: Vec<Predicate>) -> ScanSelection {
         ScanSelection {
             source,
             source_snapshot_id: "snapshot-1".into(),
@@ -1451,27 +1448,30 @@ mod tests {
     // Correlation can be costed as an exact hash aggregate using provider-supplied state size.
     #[test]
     fn correlation_lowers_to_physical_hash_aggregate() {
-        use asap_types::pre_asap::{
-            AggIntent, DataType, Field, QueryExpr, Reduction, Schema, Source,
-        };
+        use asap_types::pre_asap::{AggIntent, DataType, Field, Reduction, Schema, Source};
         let source = Source::Table {
             table_ref: "pairs".into(),
         };
-        let root = Rc::new(QueryExpr::Aggregate {
-            reduction: Reduction::by(vec![]),
-            measures: vec![AggIntent::PearsonCorr { left: 0, right: 1 }],
-            output_names: vec!["r".into()],
-            filters: vec![],
-            having: None,
-            child: Rc::new(QueryExpr::Scan {
-                source: source.clone(),
-                predicates: vec![],
-                schema: Schema::new(vec![
-                    Field::plain("x", DataType::Float64, true),
-                    Field::plain("y", DataType::Float64, true),
-                ]),
-            }),
-        });
+        let root =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+                reduction: Reduction::by(vec![]),
+                measures: vec![AggIntent::PearsonCorr { left: 0, right: 1 }],
+                output_names: vec!["r".into()],
+                filters: vec![],
+                having: None,
+                child: OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(
+                    NonASAPOp::Scan {
+                        source: source.clone(),
+                        predicates: vec![],
+                        schema: Schema::new(vec![
+                            Field::plain("x", DataType::Float64, true),
+                            Field::plain("y", DataType::Float64, true),
+                        ]),
+                    },
+                ))
+                .unwrap(),
+            }))
+            .unwrap();
         let scope = scope(vec![coverage(source, vec![])]);
         let provided = HashMap::from([
             (
@@ -1501,51 +1501,57 @@ mod tests {
 
     #[test]
     fn query_lowering_recurses_and_fuses_global_sort_limit() {
-        use asap_types::pre_asap::{AggIntent, GroupKeys, QueryExpr, Reduction, SortKey, Source};
+        use asap_types::pre_asap::{AggIntent, GroupKeys, Reduction, Source};
         use asap_types::pre_asap::{DataType, Field, Schema};
         use std::rc::Rc;
 
-        let scan = Rc::new(QueryExpr::Scan {
+        let scan = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: Source::Table {
                 table_ref: "events".into(),
             },
-            predicates: vec![asap_types::pre_asap::Predicate(Rc::new(
-                QueryExpr::Literal(asap_types::pre_asap::ScalarValue::Boolean(true)),
+            predicates: vec![Predicate(ScalarExpr::Literal(
+                asap_types::pre_asap::ScalarValue::Boolean(true),
             ))],
             schema: Schema::new(vec![
                 Field::plain("service", DataType::Utf8, false),
                 Field::plain("value", DataType::Float64, false),
             ]),
-        });
-        let aggregate = Rc::new(QueryExpr::Aggregate {
-            reduction: Reduction::by(vec![0]),
-            measures: vec![AggIntent::Sum { col: Some(1) }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::clone(&scan),
-        });
-        let sort = Rc::new(QueryExpr::Sort {
+        }))
+        .unwrap();
+        let aggregate =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+                reduction: Reduction::by(vec![0]),
+                measures: vec![AggIntent::Sum { col: Some(1) }],
+                output_names: vec![],
+                filters: vec![],
+                having: None,
+                child: Rc::clone(&scan),
+            }))
+            .unwrap();
+        let sort = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Sort {
             keys: vec![SortKey {
-                expr: QueryExpr::Column(0),
+                expr: ScalarExpr::Column(0),
                 ascending: false,
                 nulls_first: false,
             }],
             partition_by: GroupKeys::none(),
             child: aggregate,
-        });
-        let root = Rc::new(QueryExpr::Limit {
-            n: 10,
+        }))
+        .unwrap();
+        let root = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Limit {
+            n: Some(10),
             offset: 5,
+            partition_by: GroupKeys::none(),
             child: sort,
-        });
+        }))
+        .unwrap();
 
         let scan_coverage = coverage(
             Source::Table {
                 table_ref: "events".into(),
             },
-            vec![asap_types::pre_asap::Predicate(Rc::new(
-                QueryExpr::Literal(asap_types::pre_asap::ScalarValue::Boolean(true)),
+            vec![Predicate(ScalarExpr::Literal(
+                asap_types::pre_asap::ScalarValue::Boolean(true),
             ))],
         );
         let scope = scope(vec![scan_coverage]);
@@ -1638,26 +1644,29 @@ mod tests {
     #[test]
     fn query_lowering_shares_only_provider_identified_physical_nodes() {
         use asap_types::pre_asap::{CompareOpKind, DataType, Field, Schema};
-        use asap_types::pre_asap::{JoinKind, Predicate, QueryExpr, Source};
+        use asap_types::pre_asap::{JoinKind, Source};
         use std::rc::Rc;
 
-        let shared = Rc::new(QueryExpr::Scan {
+        let shared = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: Source::Table {
                 table_ref: "dimensions".into(),
             },
             predicates: vec![],
             schema: Schema::new(vec![Field::plain("id", DataType::Int64, false)]),
-        });
-        let root = Rc::new(QueryExpr::Join {
+        }))
+        .unwrap();
+        let root = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Join {
             kind: JoinKind::Inner,
-            pred: Predicate(Rc::new(QueryExpr::Compare {
-                left: Rc::new(QueryExpr::Column(0)),
+            pred: Predicate(ScalarExpr::Compare {
+                left: Box::new(ScalarExpr::Column(0)),
                 op: CompareOpKind::Eq,
-                right: Rc::new(QueryExpr::Column(1)),
-            })),
+                right: Box::new(ScalarExpr::Column(1)),
+                semantics: ExprSemantics::Sql,
+            }),
             left: Rc::clone(&shared),
             right: Rc::clone(&shared),
-        });
+        }))
+        .unwrap();
         let scan_selection = coverage(
             Source::Table {
                 table_ref: "dimensions".into(),
@@ -1781,16 +1790,19 @@ mod tests {
             ))
         );
 
-        let invalid = Rc::new(QueryExpr::Join {
-            kind: JoinKind::Inner,
-            pred: Predicate(Rc::new(QueryExpr::Compare {
-                left: Rc::new(QueryExpr::Column(0)),
-                op: CompareOpKind::Eq,
-                right: Rc::new(QueryExpr::Column(0)),
-            })),
-            left: Rc::clone(&shared),
-            right: Rc::clone(&shared),
-        });
+        let invalid =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Join {
+                kind: JoinKind::Inner,
+                pred: Predicate(ScalarExpr::Compare {
+                    left: Box::new(ScalarExpr::Column(0)),
+                    op: CompareOpKind::Eq,
+                    right: Box::new(ScalarExpr::Column(0)),
+                    semantics: ExprSemantics::Sql,
+                }),
+                left: Rc::clone(&shared),
+                right: Rc::clone(&shared),
+            }))
+            .unwrap();
         assert_eq!(
             lower_query_physical_dag(&invalid, &shared_scope, &shared_provider),
             Err(AnalyticalCostError::UnsupportedQueryOperator)
@@ -1800,62 +1812,73 @@ mod tests {
     #[test]
     fn query_lowering_covers_relational_unary_operators() {
         use asap_types::pre_asap::{DataType, Field, ScalarValue, Schema};
-        use asap_types::pre_asap::{
-            GroupKeys, Predicate, QueryExpr, SortKey, Source, TimeShift, WindowFuncKind,
-        };
-        use std::rc::Rc;
+        use asap_types::pre_asap::{GroupKeys, Source, TimeShift, WindowFuncKind};
 
-        let scan = Rc::new(QueryExpr::Scan {
+        let scan = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: Source::Table {
                 table_ref: "events".into(),
             },
             predicates: vec![],
             schema: Schema::new(vec![Field::plain("id", DataType::Int64, false)]),
-        });
-        let filter = Rc::new(QueryExpr::Filter {
-            pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Boolean(true)))),
-            child: scan,
-        });
-        let project = Rc::new(QueryExpr::Project {
-            cols: vec![],
-            qualifier: None,
-            child: filter,
-        });
-        let dedup = Rc::new(QueryExpr::Dedup {
+        }))
+        .unwrap();
+        let filter =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Filter {
+                pred: Predicate(ScalarExpr::Literal(ScalarValue::Boolean(true))),
+                child: scan,
+            }))
+            .unwrap();
+        let project =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Project {
+                cols: vec![],
+                qualifier: None,
+                child: filter,
+            }))
+            .unwrap();
+        let dedup = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Dedup {
             cols: vec![0],
             child: project,
-        });
-        let window = Rc::new(QueryExpr::SQLWindowFunc {
-            func: WindowFuncKind::RowNumber,
-            args: vec![],
-            partition_by: GroupKeys::none(),
-            order_by: vec![SortKey {
-                expr: QueryExpr::Column(0),
-                ascending: true,
-                nulls_first: false,
-            }],
-            frame: None,
-            output_name: "rn".into(),
-            child: dedup,
-        });
-        let sort = Rc::new(QueryExpr::Sort {
+        }))
+        .unwrap();
+        let window = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(
+            NonASAPOp::SQLWindowFunc {
+                func: WindowFuncKind::RowNumber,
+                args: vec![],
+                partition_by: GroupKeys::none(),
+                order_by: vec![SortKey {
+                    expr: ScalarExpr::Column(0),
+                    ascending: true,
+                    nulls_first: false,
+                }],
+                frame: None,
+                output_name: "rn".into(),
+                child: dedup,
+            },
+        ))
+        .unwrap();
+        let sort = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Sort {
             keys: vec![SortKey {
-                expr: QueryExpr::Column(0),
+                expr: ScalarExpr::Column(0),
                 ascending: true,
                 nulls_first: false,
             }],
             partition_by: GroupKeys::by(vec![0]),
             child: window,
-        });
-        let limit = Rc::new(QueryExpr::Limit {
-            n: 20,
+        }))
+        .unwrap();
+        let limit = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Limit {
+            n: Some(20),
             offset: 0,
+            partition_by: GroupKeys::none(),
             child: sort,
-        });
-        let root = Rc::new(QueryExpr::TimeShift {
-            shift: TimeShift::default(),
-            child: limit,
-        });
+        }))
+        .unwrap();
+        let root =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::TimeShift {
+                shift: TimeShift::default(),
+                child: limit,
+            }))
+            .unwrap();
 
         let scan_selection = coverage(
             Source::Table {
@@ -1974,22 +1997,25 @@ mod tests {
     #[test]
     fn query_lowering_maps_concat_and_union_all_but_rejects_distinct_set_ops() {
         use asap_types::pre_asap::{DataType, Field, Schema};
-        use asap_types::pre_asap::{QueryExpr, RelationalSetOpKind, Source};
-        use std::rc::Rc;
+        use asap_types::pre_asap::{RelationalSetOpKind, Source};
 
-        let scan = |name: &str| QueryExpr::Scan {
-            source: Source::Table {
-                table_ref: name.into(),
-            },
-            predicates: vec![],
-            schema: Schema::new(vec![Field::plain("id", DataType::Int64, false)]),
+        let scan = |name: &str| {
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
+                source: Source::Table {
+                    table_ref: name.into(),
+                },
+                predicates: vec![],
+                schema: Schema::new(vec![Field::plain("id", DataType::Int64, false)]),
+            }))
+            .unwrap()
         };
-        let union = Rc::new(QueryExpr::SetOp {
+        let union = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::SetOp {
             kind: RelationalSetOpKind::Union,
             all: true,
-            left: Rc::new(scan("a")),
-            right: Rc::new(scan("b")),
-        });
+            left: scan("a"),
+            right: scan("b"),
+        }))
+        .unwrap();
         let scope = scope(vec![
             coverage(
                 Source::Table {
@@ -2033,19 +2059,23 @@ mod tests {
             ))
         );
 
-        let concat = Rc::new(QueryExpr::Concat {
-            children: vec![scan("a"), scan("b")],
-            discriminator_unique_key: None,
-        });
+        let concat =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Concat {
+                children: vec![scan("a"), scan("b")],
+                discriminator_unique_key: None,
+            }))
+            .unwrap();
         let dag = lower_query_physical_dag(&concat, &scope, &scripted(&provided)).unwrap();
         assert_eq!(dag.nodes.last().unwrap().operator, PhysicalOperator::Concat);
 
-        let distinct_union = Rc::new(QueryExpr::SetOp {
-            kind: RelationalSetOpKind::Union,
-            all: false,
-            left: Rc::new(scan("a")),
-            right: Rc::new(scan("b")),
-        });
+        let distinct_union =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::SetOp {
+                kind: RelationalSetOpKind::Union,
+                all: false,
+                left: scan("a"),
+                right: scan("b"),
+            }))
+            .unwrap();
         assert_eq!(
             lower_query_physical_dag(&distinct_union, &scope, &scripted(&provided)),
             Err(AnalyticalCostError::UnsupportedQueryOperator)
@@ -2054,22 +2084,24 @@ mod tests {
 
     #[test]
     fn query_lowering_fails_closed_for_missing_or_inconsistent_statistics() {
+        use asap_types::pre_asap::Source;
         use asap_types::pre_asap::{DataType, Field, Schema};
-        use asap_types::pre_asap::{QueryExpr, Source};
-        use std::rc::Rc;
 
-        let scan = Rc::new(QueryExpr::Scan {
+        let scan = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: Source::Table {
                 table_ref: "events".into(),
             },
             predicates: vec![],
             schema: Schema::new(vec![Field::plain("id", DataType::Int64, false)]),
-        });
-        let root = Rc::new(QueryExpr::Project {
-            cols: vec![],
-            qualifier: None,
-            child: scan,
-        });
+        }))
+        .unwrap();
+        let root =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Project {
+                cols: vec![],
+                qualifier: None,
+                child: scan,
+            }))
+            .unwrap();
 
         let comparison_scope = scope(vec![coverage(
             Source::Table {
@@ -2171,25 +2203,29 @@ mod tests {
     #[test]
     fn query_lowering_accepts_a_consistently_empty_edge() {
         use asap_types::pre_asap::{DataType, Field, ScalarValue, Schema};
-        use asap_types::pre_asap::{Predicate, QueryExpr, Source};
-        use std::rc::Rc;
+        use asap_types::pre_asap::{GroupKeys, Source};
 
-        let scan = Rc::new(QueryExpr::Scan {
+        let scan = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: Source::Table {
                 table_ref: "events".into(),
             },
             predicates: vec![],
             schema: Schema::new(vec![Field::plain("id", DataType::Int64, false)]),
-        });
-        let filter = Rc::new(QueryExpr::Filter {
-            pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Boolean(false)))),
-            child: scan,
-        });
-        let root = Rc::new(QueryExpr::Limit {
-            n: 10,
+        }))
+        .unwrap();
+        let filter =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Filter {
+                pred: Predicate(ScalarExpr::Literal(ScalarValue::Boolean(false))),
+                child: scan,
+            }))
+            .unwrap();
+        let root = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Limit {
+            n: Some(10),
             offset: 0,
+            partition_by: GroupKeys::none(),
             child: filter,
-        });
+        }))
+        .unwrap();
 
         let scope = scope(vec![coverage(
             Source::Table {
@@ -2230,59 +2266,70 @@ mod tests {
 
     #[test]
     fn query_lowering_rejects_aggregates_without_a_hash_implementation() {
-        use asap_types::pre_asap::{
-            AggIntent, GroupKeys, QueryExpr, Reduction, Source, WindowFuncKind,
-        };
+        use asap_types::pre_asap::{AggIntent, GroupKeys, Reduction, Source, WindowFuncKind};
         use asap_types::pre_asap::{DataType, Field, Schema};
         use asap_types::types::AccuracyTarget;
-        use std::rc::Rc;
 
         let scan = || {
-            Rc::new(QueryExpr::Scan {
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
                 source: Source::Table {
                     table_ref: "events".into(),
                 },
                 predicates: vec![],
                 schema: Schema::new(vec![Field::plain("value", DataType::Float64, false)]),
-            })
+            }))
+            .unwrap()
         };
-        let exact_quantile = Rc::new(QueryExpr::Aggregate {
-            reduction: Reduction::by(vec![]),
-            measures: vec![AggIntent::Quantile {
-                col: Some(0),
-                q: 0.99,
-                accuracy: AccuracyTarget::Exact,
-            }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: scan(),
-        });
-        let empty_sort_limit = Rc::new(QueryExpr::Limit {
-            n: 10,
-            offset: 0,
-            child: Rc::new(QueryExpr::Sort {
-                keys: vec![],
+        let exact_quantile =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+                reduction: Reduction::by(vec![]),
+                measures: vec![AggIntent::Quantile {
+                    col: Some(0),
+                    q: 0.99,
+                    accuracy: AccuracyTarget::Exact,
+                }],
+                output_names: vec![],
+                filters: vec![],
+                having: None,
+                child: scan(),
+            }))
+            .unwrap();
+        let empty_sort_limit =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Limit {
+                n: Some(10),
+                offset: 0,
                 partition_by: GroupKeys::none(),
+                child: OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(
+                    NonASAPOp::Sort {
+                        keys: vec![],
+                        partition_by: GroupKeys::none(),
+                        child: scan(),
+                    },
+                ))
+                .unwrap(),
+            }))
+            .unwrap();
+        let unsupported_window = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(
+            NonASAPOp::SQLWindowFunc {
+                func: WindowFuncKind::Lag,
+                args: vec![ScalarExpr::Column(0)],
+                partition_by: GroupKeys::none(),
+                order_by: vec![],
+                frame: None,
+                output_name: "lag".into(),
                 child: scan(),
-            }),
-        });
-        let unsupported_window = Rc::new(QueryExpr::SQLWindowFunc {
-            func: WindowFuncKind::Lag,
-            args: vec![QueryExpr::Column(0)],
-            partition_by: GroupKeys::none(),
-            order_by: vec![],
-            frame: None,
-            output_name: "lag".into(),
-            child: scan(),
-        });
-        let shifted = Rc::new(QueryExpr::TimeShift {
-            shift: asap_types::pre_asap::TimeShift {
-                offset_ms: 60_000,
-                at: None,
             },
-            child: scan(),
-        });
+        ))
+        .unwrap();
+        let shifted =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::TimeShift {
+                shift: asap_types::pre_asap::TimeShift {
+                    offset_ms: 60_000,
+                    at: None,
+                },
+                child: scan(),
+            }))
+            .unwrap();
         let scope = scope(vec![coverage(
             Source::Table {
                 table_ref: "events".into(),
@@ -2305,40 +2352,42 @@ mod tests {
 
     #[test]
     fn scalar_work_counts_every_local_predicate_operation() {
-        use asap_types::pre_asap::{CompareOpKind, QueryExpr, ScalarValue};
+        use asap_types::pre_asap::{CompareOpKind, ScalarValue};
 
-        let comparison = || QueryExpr::Compare {
-            left: Rc::new(QueryExpr::Column(0)),
+        let comparison = || ScalarExpr::Compare {
+            left: Box::new(ScalarExpr::Column(0)),
             op: CompareOpKind::Eq,
-            right: Rc::new(QueryExpr::Literal(ScalarValue::Int64(1))),
+            right: Box::new(ScalarExpr::Literal(ScalarValue::Int64(1))),
+            semantics: ExprSemantics::Sql,
         };
-        let predicate = QueryExpr::BoolAnd(vec![comparison(), comparison()]);
+        let predicate = ScalarExpr::BoolAnd(vec![comparison(), comparison()]);
 
         assert_eq!(scalar_operation_count(&predicate), Ok(3));
     }
 
     #[test]
     fn promql_presence_is_lowered_with_a_per_step_output_bound() {
-        use asap_types::pre_asap::{
-            AggIntent, DataType, Field, QueryExpr, Reduction, Schema, Source,
-        };
+        use asap_types::pre_asap::{AggIntent, DataType, Field, Reduction, Schema, Source};
 
         let source = Source::TimeSeries {
             metric: "missing".into(),
         };
-        let scan = Rc::new(QueryExpr::Scan {
+        let scan = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: source.clone(),
             predicates: vec![],
             schema: Schema::new(vec![Field::plain("value", DataType::Float64, false)]),
-        });
-        let root = Rc::new(QueryExpr::Aggregate {
-            reduction: Reduction::PerEntity,
-            measures: vec![AggIntent::Absent],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: scan,
-        });
+        }))
+        .unwrap();
+        let root =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+                reduction: Reduction::PerEntity,
+                measures: vec![AggIntent::Absent],
+                output_names: vec![],
+                filters: vec![],
+                having: None,
+                child: scan,
+            }))
+            .unwrap();
         let vector = promql_edge(0, 2, PromqlValueKind::Vector);
         let scan_statistics = OperatorStatistics::Scan {
             edges: promql_unary_edges(edge(0, 0), edge(0, 0), vector, vector),
@@ -2387,24 +2436,31 @@ mod tests {
 
     #[test]
     fn promql_range_and_subquery_preserve_internal_steps() {
-        use asap_types::pre_asap::{DataType, Field, QueryExpr, Schema, Source};
+        use asap_types::pre_asap::{DataType, Field, Schema, Source};
         use std::time::Duration;
 
         let source = Source::TimeSeries { metric: "m".into() };
-        let scan = Rc::new(QueryExpr::Scan {
+        let scan = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: source.clone(),
             predicates: vec![],
             schema: Schema::new(vec![Field::plain("value", DataType::Float64, false)]),
-        });
-        let range = Rc::new(QueryExpr::TimeRange {
-            range: Duration::from_secs(300),
-            child: scan,
-        });
-        let root = Rc::new(QueryExpr::PromqlSubquery {
-            range: Duration::from_secs(300),
-            resolution: Some(Duration::from_secs(60)),
-            child: range,
-        });
+        }))
+        .unwrap();
+        let range =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::TimeRange {
+                range: Duration::from_secs(300),
+                kind: TimeRangeKind::Range,
+                child: scan,
+            }))
+            .unwrap();
+        let root = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(
+            NonASAPOp::PromqlSubquery {
+                range: Duration::from_secs(300),
+                resolution: Some(Duration::from_secs(60)),
+                child: range,
+            },
+        ))
+        .unwrap();
         let vector = promql_edge(10, 6, PromqlValueKind::Vector);
         let range_vector = promql_edge(10, 6, PromqlValueKind::RangeVector);
         let outer_range = promql_edge(10, 1, PromqlValueKind::RangeVector);
@@ -2462,32 +2518,40 @@ mod tests {
     #[test]
     fn promql_binary_lowering_keeps_operation_and_matching_cardinality() {
         use asap_types::pre_asap::{
-            ArithmeticOpKind, BinaryOpKind, DataType, Field, GroupSide, QueryExpr, Schema, Source,
+            ArithmeticOpKind, BinaryOpKind, DataType, Field, GroupSide, Schema, Source,
             VectorGrouping, VectorMatch, VectorMatchKind,
         };
 
         let left_source = Source::TimeSeries { metric: "a".into() };
         let right_source = Source::TimeSeries { metric: "b".into() };
         let scan = |source| {
-            Rc::new(QueryExpr::Scan {
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
                 source,
                 predicates: vec![],
                 schema: Schema::new(vec![Field::plain("value", DataType::Float64, false)]),
-            })
+            }))
+            .unwrap()
         };
-        let root = Rc::new(QueryExpr::BinaryOp {
-            op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Div),
-            lhs: scan(left_source.clone()),
-            rhs: scan(right_source.clone()),
-            vector_match: Some(VectorMatch {
-                kind: VectorMatchKind::On,
-                labels: vec!["service".into()],
-                grouping: Some(VectorGrouping {
-                    side: GroupSide::Left,
-                    labels: vec!["region".into()],
-                }),
-            }),
-        });
+        let root =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::BinaryOp {
+                operator: BinaryOperator {
+                    kind: BinaryOpKind::Arithmetic(ArithmeticOpKind::Div),
+                    vector_match: Some(VectorMatch {
+                        kind: VectorMatchKind::On,
+                        labels: vec!["service".into()],
+                        grouping: Some(VectorGrouping {
+                            side: GroupSide::Left,
+                            labels: vec!["region".into()],
+                        }),
+                    }),
+                    checked_relative_division: false,
+                    checked_finite_division: false,
+                },
+                return_bool: false,
+                lhs: scan(left_source.clone()),
+                rhs: scan(right_source.clone()),
+            }))
+            .unwrap();
         let left_promql = promql_edge(10, 10, PromqlValueKind::Vector);
         let right_promql = promql_edge(5, 10, PromqlValueKind::Vector);
         let output_promql = promql_edge(8, 10, PromqlValueKind::Vector);
@@ -2545,36 +2609,45 @@ mod tests {
     #[test]
     fn promql_relabel_sample_and_per_series_lower_as_a_complete_chain() {
         use asap_types::pre_asap::{
-            AggIntent, DataType, Field, GroupKeys, QueryExpr, Reduction, SampleKind, ScalarValue,
-            Schema, Source,
+            AggIntent, DataType, Field, GroupKeys, Reduction, SampleKind, ScalarValue, Schema,
+            Source,
         };
 
         let source = Source::TimeSeries {
             metric: "requests".into(),
         };
-        let scan = Rc::new(QueryExpr::Scan {
+        let scan = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: source.clone(),
             predicates: vec![],
             schema: Schema::new(vec![Field::plain("value", DataType::Float64, false)]),
-        });
-        let relabel = Rc::new(QueryExpr::PromqlRelabel {
-            dst: "service".into(),
-            value: Rc::new(QueryExpr::Literal(ScalarValue::Utf8("api".into()))),
-            child: scan,
-        });
-        let sample = Rc::new(QueryExpr::PromqlSeriesSample {
-            by: GroupKeys::none(),
-            kind: SampleKind::LimitK(5),
-            child: relabel,
-        });
-        let root = Rc::new(QueryExpr::Aggregate {
-            reduction: Reduction::PerEntity,
-            measures: vec![AggIntent::Sum { col: None }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: sample,
-        });
+        }))
+        .unwrap();
+        let relabel = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(
+            NonASAPOp::PromqlRelabel {
+                dst: "service".into(),
+                value: ScalarExpr::Literal(ScalarValue::Utf8("api".into())),
+                child: scan,
+            },
+        ))
+        .unwrap();
+        let sample = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(
+            NonASAPOp::PromqlSeriesSample {
+                by: GroupKeys::none(),
+                kind: SampleKind::LimitK(5),
+                child: relabel,
+            },
+        ))
+        .unwrap();
+        let root =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+                reduction: Reduction::PerEntity,
+                measures: vec![AggIntent::Sum { col: None }],
+                output_names: vec![],
+                filters: vec![],
+                having: None,
+                child: sample,
+            }))
+            .unwrap();
 
         let input = edge(100, 1_600);
         let sampled = edge(50, 800);
diff --git a/crates/asap-aware-mapping/src/recurrence.rs b/crates/asap-aware-mapping/src/recurrence.rs
index 660787cdb..835a35a65 100644
--- a/crates/asap-aware-mapping/src/recurrence.rs
+++ b/crates/asap-aware-mapping/src/recurrence.rs
@@ -394,7 +394,7 @@ pub enum RootRecurrence {
 
 // ── Explanation ──────────────────────────────────────────────────────────
 
-/// The full readout [`CostModel::cse_share_decision_with_recurrence`]
+/// The full evaluation [`CostModel::cse_share_decision_with_recurrence`]
 /// returns: which alternative was selected, both compared cost rates
 /// (and, when a [`Horizon`] was supplied, both compared totals), every
 /// input that went into them, their units, and provenance — meant to be
@@ -779,17 +779,20 @@ mod tests {
     // ── decide (structural fallback) ─────────────────────────────────────
 
     use crate::cost_model::CseCandidate;
+    use asap_types::ir::operator_properties::{Reduction, Source};
+    use asap_types::ir::{
+        ASAPOp, BinaryOperator, ExprSemantics, NonASAPOp, OperatorNode, Predicate, ScalarExpr,
+    };
     use asap_types::post_asap::{
         ExactKind, ExactParams, Field, FieldDataType, GroupingStrategy, ResultGuarantee, Schema,
-        SummaryExpr, SummaryNode,
     };
     use asap_types::pre_asap::expr_ir::ColumnRef;
-    use asap_types::pre_asap::query_expr::{QueryExpr, Reduction, Source};
     use asap_types::pre_asap::schema::DataType;
+
     use std::rc::Rc;
 
-    fn scan() -> QueryExpr {
-        QueryExpr::Scan {
+    fn scan() -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: Source::TimeSeries { metric: "m".into() },
             predicates: vec![],
             schema: Schema::with_time_index(
@@ -800,28 +803,34 @@ mod tests {
                 0,
                 vec![],
             ),
-        }
+        }))
+        .unwrap()
     }
 
-    fn summary_node(family: FieldDataType) -> SummaryNode {
-        SummaryNode {
-            expr: SummaryExpr::SummaryAgg {
-                child: Rc::new(SummaryNode {
-                    expr: SummaryExpr::KeepPreAsap(Rc::new(scan())),
-                    schema: Schema::lifted(vec![], None),
-                    guarantee: Some(ResultGuarantee::exact("KeepPreAsap")),
+    /// A summary of `family` over the kept pre-ASAP scan.
+    fn summary_node(family: FieldDataType) -> Rc<OperatorNode> {
+        let kept = Rc::new(
+            scan()
+                .as_ref()
+                .clone()
+                .with_guarantee(Some(ResultGuarantee::exact("RetainedExact"))),
+        );
+        std::rc::Rc::new(
+            OperatorNode::with_schema(
+                asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
+                    child: kept,
+                    family: family.clone(),
+                    input: asap_types::post_asap::SummaryUpdate::column(ColumnRef::Named(
+                        "value".into(),
+                    )),
+                    reduction: Reduction::by(vec![]),
+                    grouping: GroupingStrategy::default(),
+                    filter: None,
                 }),
-                family: family.clone(),
-                input: asap_types::post_asap::SummaryUpdate::column(ColumnRef::Named(
-                    "value".into(),
-                )),
-                reduction: Reduction::by(vec![]),
-                grouping: GroupingStrategy::default(),
-                filter: None,
-            },
-            schema: Schema::lifted(vec![Field::new("state", family, false)], None),
-            guarantee: None,
-        }
+                Schema::lifted(vec![Field::new("state", family, false)], None),
+            )
+            .with_guarantee(None),
+        )
     }
 
     #[test]
@@ -1120,9 +1129,9 @@ mod tests {
     // ── multiple roots sharing a sub-DAG, via CandidateLogicalASAPDAGs ──────────────────
 
     use crate::replacement::search_workload;
+    use asap_types::ir::operator_properties::Reduction as QueryReduction;
     use asap_types::pre_asap::agg_intent::AggIntent;
-    use asap_types::pre_asap::expr_ir::ScalarValue;
-    use asap_types::pre_asap::query_expr::{Predicate, Reduction as QueryReduction};
+    use asap_types::pre_asap::expr_ir::{CompareOpKind, ScalarValue};
 
     /// Like `scan()`, plus a "job" label column to group by — CSE's
     /// sharing legality gate requires a provable unique key
@@ -1132,8 +1141,8 @@ mod tests {
     /// real one, matching the pattern
     /// `replacement.rs`'s own CSE fixtures already use (`metric_scan`/`agg`
     /// grouped by a label column).
-    fn labeled_scan() -> QueryExpr {
-        QueryExpr::Scan {
+    fn labeled_scan() -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: Source::TimeSeries { metric: "m".into() },
             predicates: vec![],
             schema: Schema::with_time_index(
@@ -1145,18 +1154,20 @@ mod tests {
                 0,
                 vec![],
             ),
-        }
+        }))
+        .unwrap()
     }
 
-    fn sum_agg() -> QueryExpr {
-        QueryExpr::Aggregate {
+    fn sum_agg() -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
             reduction: QueryReduction::by(vec![2]),
             measures: vec![AggIntent::Sum { col: Some(1) }],
             output_names: vec![],
             filters: vec![],
             having: None,
-            child: Rc::new(labeled_scan()),
-        }
+            child: labeled_scan(),
+        }))
+        .unwrap()
     }
 
     /// A root wrapping a fresh, independently-built (but structurally
@@ -1167,13 +1178,19 @@ mod tests {
     /// `shared_aggregate_across_two_roots_gets_both_strategies_candidates`'s
     /// own doc) while letting `share_common_sub_dags` unify their
     /// identical `sum_agg()` children onto one shared `Rc`.
-    fn filtered_root(distinguishing_literal: i64) -> QueryExpr {
-        QueryExpr::Filter {
-            pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Int64(
-                distinguishing_literal,
-            )))),
-            child: Rc::new(sum_agg()),
-        }
+    fn filtered_root(distinguishing_literal: i64) -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Filter {
+            pred: Predicate(ScalarExpr::Compare {
+                left: Box::new(ScalarExpr::Column(1)),
+                op: CompareOpKind::Gt,
+                right: Box::new(ScalarExpr::Literal(ScalarValue::Int64(
+                    distinguishing_literal,
+                ))),
+                semantics: ExprSemantics::Sql,
+            }),
+            child: sum_agg(),
+        }))
+        .unwrap()
     }
 
     /// Three workload roots share one underlying `sum_agg()` sub-DAG: two
@@ -1185,10 +1202,10 @@ mod tests {
     /// roots sharing a sub-DAG" acceptance criteria.
     #[test]
     fn recurrence_profiles_aggregates_mixed_intervals_across_roots_sharing_a_subdag() {
-        let roots: Vec<(&str, Rc<QueryExpr>)> = vec![
-            ("root_a", Rc::new(filtered_root(1))),
-            ("root_b", Rc::new(filtered_root(2))),
-            ("root_c", Rc::new(filtered_root(3))),
+        let roots: Vec<(&str, Rc<OperatorNode>)> = vec![
+            ("root_a", filtered_root(1)),
+            ("root_b", filtered_root(2)),
+            ("root_c", filtered_root(3)),
         ];
         let space = search_workload(roots);
 
@@ -1206,7 +1223,7 @@ mod tests {
         );
         let shared_group = space
             .target_subdag_candidates()
-            .find(|g| matches!(g.target.as_ref(), QueryExpr::Aggregate { .. }))
+            .find(|g| matches!(g.target.non_asap(), Some(NonASAPOp::Aggregate { .. })))
             .expect("the shared sum_agg() is a discovered target");
         assert_eq!(shared_group.consumer_count, 3, "shared by all 3 roots");
 
@@ -1250,14 +1267,11 @@ mod tests {
 
     #[test]
     fn plan_selection_uses_recurrence_profiles_for_cse_choices() {
-        let roots = vec![
-            ("a", Rc::new(filtered_root(1))),
-            ("b", Rc::new(filtered_root(2))),
-        ];
+        let roots = vec![("a", filtered_root(1)), ("b", filtered_root(2))];
         let space = search_workload(roots);
         let shared = space
             .target_subdag_candidates()
-            .find(|group| matches!(group.target.as_ref(), QueryExpr::Aggregate { .. }))
+            .find(|group| matches!(group.target.non_asap(), Some(NonASAPOp::Aggregate { .. })))
             .expect("the aggregate is shared by both roots");
         let update_rate = Some(UpdateRate(10.0));
 
@@ -1315,8 +1329,8 @@ mod tests {
 
     #[test]
     fn recurrence_profiles_rejects_an_invalid_evaluation_rate() {
-        let root = Rc::new(scan());
-        let roots: Vec<(&str, Rc<QueryExpr>)> = vec![("only", root)];
+        let root = scan();
+        let roots: Vec<(&str, Rc<OperatorNode>)> = vec![("only", root)];
         let space = search_workload(roots);
         let err = space
             .recurrence_profiles(&[RootRecurrence::Repeating(EvaluationRate(f64::NAN))], None)
@@ -1329,8 +1343,8 @@ mod tests {
     /// signature promises a `Result`.
     #[test]
     fn recurrence_profiles_reports_a_root_count_mismatch_as_an_error_not_a_panic() {
-        let root = Rc::new(scan());
-        let roots: Vec<(&str, Rc<QueryExpr>)> = vec![("only", root)];
+        let root = scan();
+        let roots: Vec<(&str, Rc<OperatorNode>)> = vec![("only", root)];
         let space = search_workload(roots);
         let err = space.recurrence_profiles(&[], None).unwrap_err();
         assert_eq!(
@@ -1344,8 +1358,8 @@ mod tests {
 
     #[test]
     fn recurrence_profiles_rejects_an_invalid_update_rate() {
-        let root = Rc::new(scan());
-        let roots: Vec<(&str, Rc<QueryExpr>)> = vec![("only", root)];
+        let root = scan();
+        let roots: Vec<(&str, Rc<OperatorNode>)> = vec![("only", root)];
         let space = search_workload(roots);
         let err = space
             .recurrence_profiles(
@@ -1373,23 +1387,25 @@ mod tests {
     /// `consumer_count`.
     #[test]
     fn recurrence_profiles_does_not_stamp_update_rate_on_a_site_unreachable_from_any_root() {
-        let avg_root = QueryExpr::Aggregate {
-            reduction: QueryReduction::by(vec![]),
-            measures: vec![AggIntent::Avg { col: None }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(scan()),
-        };
-        let roots: Vec<(&str, Rc<QueryExpr>)> = vec![("q", Rc::new(avg_root))];
+        let avg_root =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+                reduction: QueryReduction::by(vec![]),
+                measures: vec![AggIntent::Avg { col: None }],
+                output_names: vec![],
+                filters: vec![],
+                having: None,
+                child: scan(),
+            }))
+            .unwrap();
+        let roots: Vec<(&str, Rc<OperatorNode>)> = vec![("q", avg_root)];
         let space = search_workload(roots);
 
         let count_group = space
             .target_subdag_candidates()
             .find(|g| {
                 matches!(
-                    g.target.as_ref(),
-                    QueryExpr::Aggregate { measures, .. }
+                    g.target.non_asap(),
+                    Some(NonASAPOp::Aggregate { measures, .. })
                         if measures.iter().any(|m| matches!(m, AggIntent::Count { .. }))
                 )
             })
@@ -1428,19 +1444,26 @@ mod tests {
     /// reachability-set walk would (wrongly) collapse it to.
     #[test]
     fn recurrence_profiles_credits_a_direct_repeated_reference_by_its_multiplicity() {
-        let root = QueryExpr::BinaryOp {
-            op: asap_types::pre_asap::query_expr::BinaryOpKind::Compare(
-                asap_types::pre_asap::expr_ir::CompareOpKind::Eq,
-            ),
-            lhs: Rc::new(sum_agg()),
-            rhs: Rc::new(sum_agg()),
-            vector_match: None,
-        };
-        let space = search_workload(vec![("q", Rc::new(root))]);
+        let root =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::BinaryOp {
+                operator: BinaryOperator {
+                    checked_relative_division: false,
+                    checked_finite_division: false,
+                    kind: asap_types::ir::operator_properties::BinaryOpKind::Compare(
+                        CompareOpKind::Eq,
+                    ),
+                    vector_match: None,
+                },
+                return_bool: false,
+                lhs: sum_agg(),
+                rhs: sum_agg(),
+            }))
+            .unwrap();
+        let space = search_workload(vec![("q", root)]);
 
         let shared_group = space
             .target_subdag_candidates()
-            .find(|g| matches!(g.target.as_ref(), QueryExpr::Aggregate { .. }))
+            .find(|g| matches!(g.target.non_asap(), Some(NonASAPOp::Aggregate { .. })))
             .expect("sum_agg() should merge onto one shared Rc, referenced twice from BinaryOp");
         assert_eq!(
             shared_group.consumer_count, 2,
@@ -1463,7 +1486,7 @@ mod tests {
 
         let scan_group = space
             .target_subdag_candidates()
-            .find(|group| matches!(group.target.as_ref(), QueryExpr::Scan { .. }))
+            .find(|group| matches!(group.target.non_asap(), Some(NonASAPOp::Scan { .. })))
             .expect("the shared aggregate has a scan descendant");
         assert_eq!(
             profiles
diff --git a/crates/asap-aware-mapping/src/replacement.rs b/crates/asap-aware-mapping/src/replacement.rs
index 44ffef189..14dbbc41a 100644
--- a/crates/asap-aware-mapping/src/replacement.rs
+++ b/crates/asap-aware-mapping/src/replacement.rs
@@ -3,9 +3,9 @@
 //! under "Key concepts (not yet implemented)", implemented for real (issue
 //! #251, part of #33).
 //!
-//! ## One step, not two: `SketchAlgorithmStrategy::replacements()` decides *and* builds
+//! ## One step, not two: `ASAPStrategies::replacements()` decides *and* builds
 //!
-//! For a bindable `Aggregate`, `SketchAlgorithmStrategy::replacements()` is the
+//! For a bindable `Aggregate`, `ASAPStrategies::replacements()` is the
 //! single place this crate both decides what an `AggIntent` may become and
 //! turns each of those candidates into a real, executable
 //! [`ReplacementSubDAG`]:
@@ -18,8 +18,8 @@
 //!    `CostModel::size_params`, not a placeholder filled in later).
 //! 2. **Build**: for each candidate in that list, [`construct_summary`]
 //!    mechanically turns the already-decided `(kind, params)` into a real
-//!    [`SummaryNode`] — derives the child schema, resolves the summarized
-//!    column, builds the readout query, recurses into the child (via
+//!    [`OperatorNode`] — derives the child schema, resolves the summarized
+//!    column, builds the evaluation query, recurses into the child (via
 //!    [`realize_child`], so a nested aggregate gets its own
 //!    independent enumeration, never the outer target's forced choice), and
 //!    assembles the `SummaryAgg`/`SummaryEstimate` node.
@@ -31,13 +31,13 @@
 //! has to run regardless of how `(kind, params)` were chosen, so it lives
 //! directly inside the one method that needs it.
 //!
-//! - [`TargetSubDAG`] — a reference to a pre-ASAP [`QueryExpr`] node that is a
+//! - [`TargetSubDAG`] — a reference to a pre-ASAP [`OperatorNode`] that is a
 //!   candidate for replacement, plus how many places in the workload already
 //!   reference it (its `consumer_count`) — the one piece of cross-node
 //!   context [`SharedSubDAGStrategy`] needs that a bare node reference alone
 //!   doesn't carry.
 //! - [`ReplacementSubDAG`] — one candidate replacement for a `TargetSubDAG`:
-//!   either a fully bound [`SummaryNode`] or a pre-ASAP [`QueryExpr`] rewrite
+//!   either a fully bound summary sub-DAG or a pre-ASAP logical rewrite
 //!   (still logical, structurally different from the target but semantically
 //!   equivalent) — see [`Replacement`] — plus a human-readable `rationale`.
 //! - [`ReplacementStrategy`] — `matches` + `replacements`, the same
@@ -72,7 +72,7 @@
 //!
 //! ## The two strategies, and why these two
 //!
-//! - [`SketchAlgorithmStrategy`] wraps [`realizations_for_intent`]'s exhaustive,
+//! - [`ASAPStrategies`] wraps [`realizations_for_intent`]'s exhaustive,
 //!   ranked list directly: for the same bindable-`Aggregate` shape this crate
 //!   binds (single intent, no `HAVING`), every entry becomes its own bound
 //!   candidate.
@@ -80,7 +80,7 @@
 //!   `asap_types::pre_asap::cse::share_common_sub_dags`'s sharing decision.
 //!   Wherever a [`TargetSubDAG`] already has two or more consumers (i.e.
 //!   `share_common_sub_dags` already collapsed two or more workload
-//!   locations onto the same `Rc<QueryExpr>` — [`discover_targets`] below
+//!   locations onto the same `Rc<OperatorNode>` — [`discover_targets`] below
 //!   does the identical workload-wide discovery for [`search_workload_with`];
 //!   this module's own tests reuse the same dedup logic to build realistic
 //!   fixtures), it reports the two-way candidate CSE's own detection pass
@@ -98,7 +98,7 @@
 //!   unchanged.** Same inputs still produce the same exhaustive, ranked
 //!   list — only its home moved (from a separate `implementation` module
 //!   into this one) and its own visibility dropped to module-private, since
-//!   [`SketchAlgorithmStrategy`] is now its only caller.
+//!   [`ASAPStrategies`] is now its only caller.
 //!
 //! ## Workload-wide search — merged in from the former `search.rs` (issue #252, part of #33)
 //!
@@ -143,12 +143,12 @@
 //!
 //! 1. **Per-target candidates, not flat plans.** [`TargetSubDAGCandidates`]
 //!    stores the alternatives for one distinct [`TargetSubDAG`] (identified by
-//!    its own `Rc<QueryExpr>` pointer identity — the same currency
+//!    its own `Rc<OperatorNode>` pointer identity — the same currency
 //!    [`asap_types::pre_asap::cse::share_common_sub_dags`] already
 //!    established across the workload) holding every
 //!    [`ReplacementSubDAG`] alternative discovered for it. [`CandidateLogicalASAPDAGs`] is
 //!    a collection of these groups, keyed by `TargetSubDAG` — a candidate
-//!    "plan" is never materialized as a distinct top-level `Rc<QueryExpr>`
+//!    "plan" is never materialized as a distinct top-level `Rc<OperatorNode>`
 //!    at all; two logically-different overall choices at two different
 //!    targets are just two different entries in two different groups,
 //!    sharing every other node in the workload by construction (they *are*
@@ -157,7 +157,7 @@
 //!    discipline.** [`asap_types::pre_asap::cse::structural_hash`] (made
 //!    `pub` for exactly this reuse) is only ever a candidate-narrowing
 //!    filter; [`TargetSubDAGCandidates::add_candidate`]'s actual duplicate check is
-//!    `QueryExpr`'s derived `PartialEq` — the same "hash is a filter,
+//!    `OperatorNode`'s derived `PartialEq` — the same "hash is a filter,
 //!    `PartialEq` is the decision, no exceptions" rule `cse.rs`'s own
 //!    "Correctness" section states and this module inherits rather than
 //!    reinvents. See [`is_duplicate_rewrite`] for the one deliberate
@@ -212,10 +212,10 @@
 //! an alternative *for* the target just processed, not a new target of its
 //! own; see [`discover_new_descendant_targets`]) are scanned for pointers
 //! not already known, and any found become next round's frontier. Both shipped
-//! strategies are idempotent in exactly this sense: [`SketchAlgorithmStrategy`]
-//! produces terminal [`Replacement::Summary`] candidates (no `QueryExpr`
-//! children to scan at all), and [`SharedSubDAGStrategy`]'s two
-//! [`Replacement::Rewrite`] candidates both reuse the target's own
+//! strategies are idempotent in exactly this sense: [`ASAPStrategies`]
+//! produces terminal bound-summary [`Replacement::SubDAG`] candidates (no
+//! logical-rewrite children to scan at all), and [`SharedSubDAGStrategy`]'s
+//! two logical-rewrite [`Replacement::SubDAG`] candidates both reuse the target's own
 //! already-known child `Rc`s verbatim (`Rc::clone`/a shallow top-level
 //! `.clone()` — see that strategy's own doc). So for both, the frontier is
 //! always empty after round one: real workloads converge in exactly one
@@ -248,7 +248,7 @@
 //!   share-vs-recompute pair is ranked by calling
 //!   [`CostModel::cse_share_decision`] via this module's own
 //!   [`cse_preference`] — rather than re-deriving a competing comparison.
-//! - A group whose candidates are [`SketchAlgorithmStrategy`]'s sketch-family
+//! - A group whose candidates are [`ASAPStrategies`]'s sketch-family
 //!   candidates is ranked via [`CostModel::rank_candidates`] (the same hook
 //!   `realizations_for_intent` itself consults), applied to the
 //!   candidates' own [`SketchAlgorithm`]s.
@@ -317,8 +317,8 @@
 //! documented follow-up rather than silently overclaimed:
 //!
 //! - [`CostModel::rank_candidates`]/[`CostModel::size_params`] — the hooks
-//!   [`SketchAlgorithmStrategy`] groups rank by — take no `consumer_count`
-//!   parameter at all today, so a `SketchAlgorithmStrategy` group's selection
+//!   [`ASAPStrategies`] groups rank by — take no `consumer_count`
+//!   parameter at all today, so a `ASAPStrategies` group's selection
 //!   here still falls back to [`rank_group`]'s ordinary (consumer-count-
 //!   blind) local ranking, even though its own
 //!   [`TargetSubDAGSelection::effective_consumer_count`] is computed and exposed
@@ -345,31 +345,33 @@ use crate::accuracy::estimators::{
     cms::{cms_depth, cms_width},
     saturating_ceil,
 };
+use asap_types::ir::non_asap::any_measure_filtered;
+use asap_types::pre_asap::resolve_column_ref;
 use std::cell::RefCell;
 use std::collections::{HashMap, HashSet, VecDeque};
 
+use asap_types::ir::cse::{share_common_sub_dags, structural_hash, HashCache};
+use asap_types::ir::operator_properties::{BinaryOpKind, JoinKind, Reduction};
+use asap_types::ir::timing::validate_default;
+use asap_types::ir::SchemaDerivationError;
+use asap_types::ir::{
+    ASAPOp, BinaryOperator, NonASAPOp, Operator, OperatorNode, Predicate, ProjectItem, ScalarExpr,
+    SortKey,
+};
+use asap_types::post_asap::{AccuracyError, CompositionOperator, GuaranteeSource, ResultGuarantee};
 use asap_types::post_asap::{
-    validate_execution_data_states_at, EntityIdentity, ExactKind, ExactOperation,
-    ExactOperationSchemaError, ExactParams, ExecutionDataState, ExecutionDataStateError,
+    EntityIdentity, ExactKind, ExactOperationSchemaError, ExactParams, ExecutionDataStateError,
     ExecutionTiming, Field, FieldDataType, GroupingStrategy, NonNegativeWeightProof, SamplingKind,
     SamplingParams, Schema, SketchAlgorithm, SketchKind, SketchParams,
-    SketchStatistic as PostAsapSketchStatistic, StatModelKind, StatModelParams, SummaryExpr,
-    SummaryInputExpr, SummaryNode, SummaryUpdate, ValueOperation, WaveletKind, WaveletParams,
-    WeightDomain,
+    SketchStatistic as PostAsapSketchStatistic, StatModelKind, StatModelParams, SummaryInputExpr,
+    SummaryUpdate, WaveletKind, WaveletParams, WeightDomain,
 };
-use asap_types::post_asap::{AccuracyError, CompositionOperator, GuaranteeSource, ResultGuarantee};
 use asap_types::pre_asap::agg_intent::{agg_is_mergeable, AggIntent};
-use asap_types::pre_asap::column_resolution::resolve_column_ref;
-use asap_types::pre_asap::cse::{share_common_sub_dags, structural_hash, HashCache};
 use asap_types::pre_asap::expr_ir::{ArithmeticOpKind, ColumnRef};
-use asap_types::pre_asap::query_expr::any_measure_filtered;
-use asap_types::pre_asap::query_expr::{
-    BinaryOpKind, Predicate, QueryExpr, QueryExprError, Reduction,
-};
 use asap_types::pre_asap::schema::ColumnId;
 use asap_types::types::AccuracyTarget;
 use asap_types::workload::{DataWorkload, QueryRecurrence, QueryWorkload, RepeatedDemand};
-use std::rc::Rc;
+use std::rc::{Rc, Weak};
 use thiserror::Error;
 
 use crate::accuracy::reconciliation::AccuracyReconciliationStrategy;
@@ -391,20 +393,20 @@ use crate::rollup::RollupStrategy;
 use crate::topk_reuse::TopKLimitReuseStrategy;
 
 /// Errors from the pre-ASAP → post-ASAP replacement/construction path
-/// ([`realize_child`] and [`keep_pre_asap`]). Moved here from the former
+/// ([`realize_child`] and [`retain_exact`]). Moved here from the former
 /// `bind.rs` (issue #251): this is what a [`ReplacementStrategy`]
 /// implementor's own construction path can realistically fail with —
-/// schema derivation over a pre-ASAP [`QueryExpr`] — not something specific
-/// to workload-wide orchestration.
+/// schema derivation over a pre-ASAP [`OperatorNode`] sub-DAG — not
+/// something specific to workload-wide orchestration.
 #[derive(Debug, Error)]
 pub enum RealizationError {
     /// Schema derivation failed while lifting an edge to `Schema`.
     #[error("schema derivation failed during pre-ASAP → post-ASAP binding: {0}")]
-    Schema(#[from] QueryExprError),
+    Schema(#[from] SchemaDerivationError),
     /// The candidate is accuracy-illegal (issue #172): its composed
     /// guarantee has no sound propagation rule, or misses the applicable
     /// `AccuracyTarget`. Fail-closed — the candidate is never constructed
-    /// with the child "treated as exact". [`SketchAlgorithmStrategy::propose`]
+    /// with the child "treated as exact". [`ASAPStrategies::propose`]
     /// records it as a [`RejectedCandidate`] instead of a candidate.
     #[error("accuracy-illegal candidate: {0}")]
     Accuracy(#[from] AccuracyError),
@@ -414,8 +416,8 @@ pub enum RealizationError {
     /// would change its semantics.
     #[error("unsupported physical summary realization: {0}")]
     PhysicalRealization(&'static str),
-    /// A constructed plan violates the update/readout phase contract
-    /// (issue #171) — e.g. a summary readout placed beneath a maintained
+    /// A constructed plan violates the update/evaluation phase contract
+    /// (issue #171) — e.g. a summary evaluation placed beneath a maintained
     /// `SummaryAgg`. Detected at construction, never at runtime.
     #[error("execution-data_state violation in post-ASAP plan: {0}")]
     ExecutionDataState(#[from] ExecutionDataStateError),
@@ -427,10 +429,10 @@ pub enum RealizationError {
 
 /// A pre-ASAP sub-DAG a [`ReplacementStrategy`] knows how to replace.
 ///
-/// `root` is a reference into the workload's own [`QueryExpr`] DAG (an
-/// `Rc<QueryExpr>`, the same currency [`search_workload`] and
-/// `asap_types::pre_asap::cse::share_common_sub_dags` already thread through
-/// this crate's public API — not a bare `&QueryExpr` — so a strategy that
+/// `root` is a reference into the workload's own [`OperatorNode`] DAG (an
+/// `Rc<OperatorNode>`, the same currency [`search_workload`] and
+/// `asap_types::ir::cse::share_common_sub_dags` already thread through
+/// this crate's public API — not a bare `&OperatorNode` — so a strategy that
 /// needs the node's own `Rc` identity, not just its shape, has it available
 /// without the caller re-deriving it).
 ///
@@ -439,16 +441,16 @@ pub enum RealizationError {
 /// [`search_workload_with`] computes the workload-wide value during target
 /// discovery. [`TargetSubDAG::new`] defaults it to `1` for callers invoking a
 /// strategy against one node in isolation. A strategy that only cares about
-/// `root`'s shape (for example, [`SketchAlgorithmStrategy`]) can ignore the
+/// `root`'s shape (for example, [`ASAPStrategies`]) can ignore the
 /// count; [`SharedSubDAGStrategy`] consults it directly.
 ///
 /// `strictest_sibling_accuracy` is the strictest accuracy among workload
 /// siblings that read the same summary input as `root`, when stricter than
-/// `root`'s own. [`search_workload_with`] sets it; [`SketchAlgorithmStrategy`]
+/// `root`'s own. [`search_workload_with`] sets it; [`ASAPStrategies`]
 /// also sizes a candidate to it.
 #[derive(Debug, Clone, Copy)]
 pub struct TargetSubDAG<'a> {
-    pub root: &'a Rc<QueryExpr>,
+    pub root: &'a Rc<OperatorNode>,
     pub consumer_count: usize,
     pub strictest_sibling_accuracy: Option<&'a AccuracyTarget>,
 }
@@ -456,7 +458,7 @@ pub struct TargetSubDAG<'a> {
 impl<'a> TargetSubDAG<'a> {
     /// A target assumed to have exactly one consumer — the common case for a
     /// caller that isn't already tracking cross-workload sharing.
-    pub fn new(root: &'a Rc<QueryExpr>) -> Self {
+    pub fn new(root: &'a Rc<OperatorNode>) -> Self {
         Self {
             root,
             consumer_count: 1,
@@ -466,7 +468,7 @@ impl<'a> TargetSubDAG<'a> {
 
     /// A target with an explicit `consumer_count`, used by workload discovery
     /// and by callers that already know how many locations reference `root`.
-    pub fn with_consumer_count(root: &'a Rc<QueryExpr>, consumer_count: usize) -> Self {
+    pub fn with_consumer_count(root: &'a Rc<OperatorNode>, consumer_count: usize) -> Self {
         Self {
             root,
             consumer_count,
@@ -482,25 +484,35 @@ impl<'a> TargetSubDAG<'a> {
 /// — into "one candidate among several", each with its own
 /// [`ReplacementSubDAG`].
 #[derive(Debug, Clone)]
+#[allow(clippy::large_enum_variant)] // Keep the public strategy API value-based.
 pub enum Replacement {
-    /// A fully bound post-ASAP summary decision, for one particular
-    /// candidate realization of the target.
-    Summary(Rc<SummaryNode>),
-    /// A pre-ASAP rewrite: still a logical [`QueryExpr`], structurally
-    /// different from the target's own `root` (e.g. sharing vs. not sharing
-    /// a sub-DAG) but semantically equivalent to it.
-    Rewrite(Rc<QueryExpr>),
+    /// A sub-DAG that replaces the target: either a bound summary decision
+    /// (a DAG containing ASAP operators, for one particular candidate
+    /// realization of the target) or a pre-ASAP rewrite (a logical sub-DAG
+    /// with no ASAP operator, structurally different from the target's own
+    /// `root` — e.g. sharing vs. not sharing a sub-DAG — but semantically
+    /// equivalent to it). [`is_logical_rewrite`] tells the two apart.
+    SubDAG(Rc<OperatorNode>),
     /// An exact operator composed over another target's *own* selected
-    /// decision across an explicit update/readout boundary (issue #171):
-    /// `ValueOperationAtQueryTime` over a child's summary readout, or
+    /// decision across an explicit update/evaluation boundary (issue #171):
+    /// `ValueOperationAtQueryTime` over a child's summary evaluation, or
     /// `ValueOperationAtIngestionTime` feeding a maintained summary above. Carries only a
     /// reference to the child target — [`CandidateLogicalASAPDAGs::global_selection`]
     /// commits the compatible parent/child pair and
     /// [`GlobalSelection::assemble_selected_dag`] links it into one validated
-    /// `SummaryNode`. See [`crate::exact_composition`].
+    /// `OperatorNode` DAG. See [`crate::exact_composition`].
     ExactComposition(ExactComposition),
 }
 
+/// Whether a [`Replacement::SubDAG`] is a pure logical rewrite: a sub-DAG
+/// with no ASAP operator and no guarantee established yet (the shape every
+/// front end emits and every rewrite strategy builds). A bound summary
+/// decision contains an ASAP operator, or is a kept pre-ASAP sub-DAG that
+/// already carries its exact guarantee.
+pub fn is_logical_rewrite(node: &OperatorNode) -> bool {
+    node.guarantee.is_none() && !node.contains_asap()
+}
+
 /// One candidate replacement for a [`TargetSubDAG`], plus a human-readable
 /// `rationale` explaining why it's a valid candidate (meant for a
 /// report/log/debugging a search engine's choices, not machine parsing —
@@ -523,11 +535,12 @@ pub struct ReplacementSubDAG {
 impl ReplacementSubDAG {
     /// Whether this summary still needs accuracy/domain evidence before it can
     /// be treated as certified. A missing guarantee on any summary candidate
-    /// is unknown; exact `KeepPreAsap` carries an explicit exact guarantee.
+    /// (a sub-DAG whose root is an ASAP operator) is unknown; a kept
+    /// pre-ASAP sub-DAG carries an explicit exact guarantee.
     pub fn has_missing_accuracy_evidence(&self) -> bool {
         matches!(
             &self.replacement,
-            Replacement::Summary(node) if has_missing_accuracy_evidence(node)
+            Replacement::SubDAG(node) if !is_logical_rewrite(node) && has_missing_accuracy_evidence(node)
         )
     }
 
@@ -539,8 +552,12 @@ impl ReplacementSubDAG {
             Replacement::ExactComposition(composition) => {
                 cost_model.value_operation_support_evidence(&composition.op, composition.placement)
             }
-            Replacement::Summary(node) => cost_model.summary_support_evidence(node),
-            Replacement::Rewrite(_) => Some(true),
+            // Any summary decision, including one rooted in a relational
+            // operator above its evaluations, asks the deployment for support.
+            Replacement::SubDAG(node) if !is_logical_rewrite(node) => {
+                cost_model.summary_support_evidence(node)
+            }
+            Replacement::SubDAG(_) => Some(true),
         }
     }
 }
@@ -574,7 +591,7 @@ pub enum ReplacementProvenance {
     /// A finalized whole-query result over rows carrying the PromQL series
     /// identity, which the logical root does not expose (see
     /// [`ReplacementStrategy::propose_for_root`]). Default selection never
-    /// commits it, because its readout must be validated and priced by
+    /// commits it, because its evaluation must be validated and priced by
     /// deployment; otherwise it would silently replace the logical plan.
     RootPhysicalRealization,
 }
@@ -615,7 +632,7 @@ pub struct Proposals {
 /// of this trait or any existing strategy required.
 ///
 /// `replacements` is only meaningful when `matches` would return `true` for
-/// the same target; both [`SketchAlgorithmStrategy`] and [`SharedSubDAGStrategy`]
+/// the same target; both [`ASAPStrategies`] and [`SharedSubDAGStrategy`]
 /// return an empty `Vec` rather than panicking when called on a target they
 /// don't match, so a caller that skips the `matches` check first still gets a
 /// safe (merely uninformative) answer instead of a crash.
@@ -657,7 +674,7 @@ pub trait ReplacementStrategy {
     /// (for example, the PromQL series identity), so
     /// [`search_workload_with_targets`] asks only workload roots, once each.
     /// They decide what to compute, never placement. Default: none.
-    fn propose_for_root(&self, _root: &Rc<QueryExpr>, _target: &AccuracyTarget) -> Proposals {
+    fn propose_for_root(&self, _root: &Rc<OperatorNode>, _target: &AccuracyTarget) -> Proposals {
         Proposals::default()
     }
 }
@@ -674,41 +691,41 @@ pub trait ReplacementStrategy {
 /// [`realizations_for_intent`] is where every valid realization gets
 /// enumerated, exhaustive and ranked (most-preferred first) — this crate has
 /// no separate function that computes just "the one" `Realization`
-/// independently of that list. [`SketchAlgorithmStrategy`] is the sole
+/// independently of that list. [`ASAPStrategies`] is the sole
 /// consumer: it wraps every entry of this list into its own bound
-/// [`SummaryNode`] and returns all of them, ranked — a caller wanting a
+/// [`OperatorNode`] and returns all of them, ranked — a caller wanting a
 /// single answer keeps the first one itself (see the module docs above).
 #[derive(Debug, Clone, PartialEq)]
 pub enum Realization {
     /// An exact **mergeable** accumulator (partial state ≡ the value
     /// itself: `Sum` / `Count` / `Min` / `Max` / `Rate` / `Increase`). The
-    /// built state *is* the answer already — no `SummaryEstimate` readout
+    /// built state *is* the answer already — no `SummaryEstimate` evaluation
     /// step.
     ExactAggregate {
         kind: ExactKind,
         params: ExactParams,
     },
     /// An approximate sketch sized to the intent's [`AccuracyTarget`].
-    /// Needs a `SummaryEstimate` readout to recover a value. Already
+    /// Needs a `SummaryEstimate` evaluation to recover a value. Already
     /// classified into its [`SketchKind`] category (`SketchKind::new`
     /// having been called) — construction always goes through that
     /// classifier, never this variant directly.
     Sketch(SketchKind),
     /// A sampling-based summary (a retained row subset). Needs a
-    /// `SummaryEstimate` readout. Not chosen by any core `AggIntent`
+    /// `SummaryEstimate` evaluation. Not chosen by any core `AggIntent`
     /// dispatch today — see the module docs.
     Sample {
         kind: SamplingKind,
         params: SamplingParams,
     },
-    /// A wavelet-transform summary. Needs a `SummaryEstimate` readout. Not
+    /// A wavelet-transform summary. Needs a `SummaryEstimate` evaluation. Not
     /// chosen by any core `AggIntent` dispatch today — see the module docs.
     Wavelet {
         kind: WaveletKind,
         params: WaveletParams,
     },
     /// A fitted statistical/parametric-model summary. Needs a
-    /// `SummaryEstimate` readout. Not chosen by any core `AggIntent`
+    /// `SummaryEstimate` evaluation. Not chosen by any core `AggIntent`
     /// dispatch today — see the module docs.
     StatModel {
         kind: StatModelKind,
@@ -827,7 +844,7 @@ pub fn accuracy_target(intent: &AggIntent) -> Option<&AccuracyTarget> {
 /// (most-preferred first via `cost_model`) — the *only* place this crate
 /// decides what an `AggIntent` may become. Nothing in this crate computes
 /// "the one" `Realization` independently of this list:
-/// [`SketchAlgorithmStrategy`] keeps every entry as a candidate, and a caller
+/// [`ASAPStrategies`] keeps every entry as a candidate, and a caller
 /// that wants a single executable answer takes the head of *that* strategy's
 /// output itself.
 ///
@@ -835,7 +852,7 @@ pub fn accuracy_target(intent: &AggIntent) -> Option<&AccuracyTarget> {
 /// explicit realization is a compile error, and the coverage-matrix test pins
 /// each variant's category.
 ///
-/// `pub(crate)`: [`SketchAlgorithmStrategy::replacements`] is this module's
+/// `pub(crate)`: [`ASAPStrategies::replacements`] is this module's
 /// own caller; `grouping::HydraGroupingStrategy` (issue #256) is the one
 /// caller outside it, needing the exact same already-ranked candidate list
 /// to find the `Realization::Sketch` matching the Hydra-eligible kind it
@@ -1190,9 +1207,9 @@ pub fn posterior_aware_size_params(
     }
 }
 
-// ── SketchAlgorithmStrategy ─────────────────────────────────────────────────
+// ── ASAPStrategies ─────────────────────────────────────────────────
 
-/// A single static instance so [`SketchAlgorithmStrategy::default_cost_model`]
+/// A single static instance so [`ASAPStrategies::default_cost_model`]
 /// can hand out a `&'static dyn CostModel` without heap-allocating one —
 /// `DefaultCostModel` is a unit struct with no state, so one instance serves
 /// every caller.
@@ -1227,14 +1244,17 @@ impl<'a> CandidatePlanningInputs<'a> {
     }
 }
 
-/// Wraps [`realizations_for_intent`]'s exhaustive, ranked list directly: for
-/// a bindable `Aggregate`, every valid candidate summary realization as its
-/// own [`ReplacementSubDAG`].
+/// Proposes the supported ASAP realizations for a bindable aggregate, including
+/// exact accumulators, approximate sketches, and supported maintained populations.
+/// Each valid realization becomes its own [`ReplacementSubDAG`].
+///
+/// [`realizations_for_intent`] enumerates summary families; extension hooks can
+/// supply additional supported families. This is not limited to sketch algorithms.
 ///
 /// Ranked (only to *order the enumeration*, never to drop a candidate) via a
 /// [`CostModel`] — [`DefaultCostModel`] unless constructed with
-/// [`SketchAlgorithmStrategy::new`] — so a deployment-specific cost model's
-/// other hooks (`size_params`, `realize_extension`, `readout_extension`) are
+/// [`ASAPStrategies::new`] — so a deployment-specific cost model's
+/// other hooks (`size_params`, `realize_extension`, `evaluation_extension`) are
 /// still consulted while binding each candidate.
 ///
 /// The one thing that *does* drop a candidate is accuracy legality (issue
@@ -1245,11 +1265,11 @@ impl<'a> CandidatePlanningInputs<'a> {
 /// [`ReplacementStrategy::propose`] as a [`RejectedCandidate`]. See
 /// [`crate::accuracy`]'s module docs for the rules and the precedence
 /// between root and per-node targets.
-pub struct SketchAlgorithmStrategy<'a> {
+pub struct ASAPStrategies<'a> {
     planning_inputs: CandidatePlanningInputs<'a>,
 }
 
-impl SketchAlgorithmStrategy<'static> {
+impl ASAPStrategies<'static> {
     /// A strategy that ranks/binds via the built-in [`DefaultCostModel`] —
     /// what a deployment gets with no custom cost model plugged in.
     pub fn default_cost_model() -> Self {
@@ -1259,7 +1279,7 @@ impl SketchAlgorithmStrategy<'static> {
     }
 }
 
-impl<'a> SketchAlgorithmStrategy<'a> {
+impl<'a> ASAPStrategies<'a> {
     /// A strategy that ranks/binds via `cost_model` instead of the built-in
     /// static preference order — the same customization point
     /// [`realizations_for_intent`] already offers. Accuracy legality stays
@@ -1314,34 +1334,33 @@ impl<'a> SketchAlgorithmStrategy<'a> {
     /// treats a range of historical samples as the instant vector.
     pub fn current_series_topk_candidates(
         &self,
-        root: &Rc<QueryExpr>,
+        root: &Rc<OperatorNode>,
         accuracy: &AccuracyTarget,
     ) -> Proposals {
-        let QueryExpr::Limit {
-            n,
+        let Some(NonASAPOp::Limit {
+            n: Some(n),
             offset: 0,
             child,
-        } = root.as_ref()
+            ..
+        }) = root.non_asap()
         else {
             return Proposals::default();
         };
-        let QueryExpr::Sort {
+        let Some(NonASAPOp::Sort {
             keys,
             partition_by,
             child,
-        } = child.as_ref()
+        }) = child.non_asap()
         else {
             return Proposals::default();
         };
         let [key] = keys.as_slice() else {
             return Proposals::default();
         };
-        let QueryExpr::Column(value) = key.expr else {
-            return Proposals::default();
-        };
-        let Ok(schema) = child.output_schema() else {
+        let ScalarExpr::Column(value) = key.expr else {
             return Proposals::default();
         };
+        let schema = &child.schema;
         if key.ascending
             || key.nulls_first
             || partition_by.is_without()
@@ -1354,20 +1373,101 @@ impl<'a> SketchAlgorithmStrategy<'a> {
         {
             return Proposals::default();
         }
-        let ranked = Rc::new(QueryExpr::Aggregate {
-            reduction: Reduction::Reduce(partition_by.clone()),
-            measures: vec![AggIntent::TopK {
-                k: *n,
-                accuracy: accuracy.clone(),
-            }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::clone(child),
-        });
+        let Ok(ranked) =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+                reduction: Reduction::Reduce(partition_by.clone()),
+                measures: vec![AggIntent::TopK {
+                    k: *n,
+                    accuracy: accuracy.clone(),
+                }],
+                output_names: vec![],
+                filters: vec![],
+                having: None,
+                child: Rc::clone(child),
+            }))
+        else {
+            return Proposals::default();
+        };
         self.propose_with(&ranked, None, None)
     }
 
+    /// Fixed-window maintenance can finalize each series' counter state and
+    /// build a fresh heap or grouped Sum for that evaluation window. Deployment must provide
+    /// a complete, synchronized population and bind the matching window; this
+    /// candidate never incrementally adds one window's rates to another.
+    ///
+    pub fn fixed_window_rate_candidates(&self, root: &Rc<OperatorNode>) -> Proposals {
+        fn place(node: &Rc<OperatorNode>) -> Option<Rc<OperatorNode>> {
+            retime_rate_finalize(node, ExecutionTiming::IngestionTime, true)
+        }
+        let timed = |node: &Rc<OperatorNode>| {
+            asap_types::ir::timing::apply_lifecycle_timings(
+                node,
+                &asap_types::ir::timing::LifecycleAssignment::default_maintained(),
+                &mut asap_types::ir::timing::TimingMemo::new(),
+            )
+            .ok()
+            .and_then(|timed| asap_types::ir::export::compile_physical_asap_dag(&timed).ok())
+        };
+        let mut proposals = self.propose_with(root, None, None);
+        proposals.candidates.retain_mut(|candidate| {
+            let Replacement::SubDAG(node) = &candidate.replacement else {
+                return false;
+            };
+            let Some(dag) = timed(node) else {
+                return false;
+            };
+            if !dag.nodes.iter().any(|node| match &node.payload {
+                asap_types::ir::export::PhysicalASAPOperatorPayload::SummaryAgg {
+                    family: FieldDataType::Sketch(kind, _),
+                    ..
+                } => matches!(
+                    kind.algorithm(),
+                    SketchAlgorithm::CmsWithHeap | SketchAlgorithm::CountSketchWithHeap
+                ),
+                asap_types::ir::export::PhysicalASAPOperatorPayload::SummaryAgg {
+                    family: FieldDataType::ExactAggregate(ExactKind::Sum, _),
+                    ..
+                } => true,
+                _ => false,
+            }) {
+                return false;
+            }
+            let Some(placed) = place(node) else {
+                return false;
+            };
+            if timed(&placed).is_none() {
+                return false;
+            }
+            let Ok(placed) = finalize_query_candidate(placed, root) else {
+                return false;
+            };
+            candidate.replacement = Replacement::SubDAG(placed);
+            candidate
+                .rationale
+                .push_str("; fixed-window precompute over complete per-series counter states");
+            true
+        });
+        proposals
+    }
+
+    /// Retain grouped Sum after a per-series Rate evaluation as a query-time
+    /// candidate alongside its complete-window maintenance placement.
+    ///
+    pub fn query_time_rate_aggregation_candidates(&self, root: &Rc<OperatorNode>) -> Proposals {
+        let mut proposals = self.fixed_window_rate_candidates(root);
+        proposals.candidates.retain_mut(|candidate| {
+            let Replacement::SubDAG(node) = &candidate.replacement else { return false };
+            if !matches!(&node.operator, Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child })
+                if matches!(&child.operator, Operator::ASAP(ASAPOp::SummaryAgg { family: FieldDataType::ExactAggregate(ExactKind::Sum, _), .. }))) { return false; }
+            let Some(query_time) = retime_rate_finalize(node, ExecutionTiming::QueryTime, false) else { return false };
+            candidate.replacement = Replacement::SubDAG(query_time);
+            candidate.rationale = "query-time grouped Sum over complete per-series Rate evaluations".into();
+            true
+        });
+        proposals
+    }
+
     pub(crate) fn from_planning_inputs(planning_inputs: CandidatePlanningInputs<'a>) -> Self {
         Self { planning_inputs }
     }
@@ -1380,20 +1480,21 @@ impl<'a> SketchAlgorithmStrategy<'a> {
     /// with the sibling that needs it.
     fn propose_with(
         &self,
-        root: &Rc<QueryExpr>,
+        root: &Rc<OperatorNode>,
         intent_override: Option<&AggIntent>,
         strictest_sibling: Option<&AccuracyTarget>,
     ) -> Proposals {
         let mut proposals = Proposals::default();
-        // A selected logical rewrite otherwise remains KeepPreAsap during DAG
-        // assembly. Also expose its concrete summary realization for selection.
+        // A selected logical rewrite otherwise stays a kept pre-ASAP sub-DAG
+        // during DAG assembly. Also expose its concrete summary realization
+        // for selection.
         if intent_override.is_none() {
             if let Some(rewritten) = crate::rewrite::composed_aggregate_rewrite(root) {
                 if let Ok(node) = realize_child_with(&rewritten, self.planning_inputs, None) {
-                    if !matches!(node.expr, SummaryExpr::KeepPreAsap(_)) {
+                    if node.contains_asap() {
                         proposals.candidates.push(ReplacementSubDAG {
-                            replacement: Replacement::Summary(node),
-                            strategy: "SketchAlgorithmStrategy",
+                            replacement: Replacement::SubDAG(node),
+                            strategy: "ASAPStrategies",
                             provenance: ReplacementProvenance::SummaryRealization,
                             rationale: "realize a schema-preserving composition of temporal and grouped accumulators".into(),
                         });
@@ -1403,8 +1504,8 @@ impl<'a> SketchAlgorithmStrategy<'a> {
         }
         if let Ok(Some(node)) = exact_topk_over_temporal_values(root, self.planning_inputs) {
             proposals.candidates.push(ReplacementSubDAG {
-                replacement: Replacement::Summary(node),
-                strategy: "SketchAlgorithmStrategy",
+                replacement: Replacement::SubDAG(node),
+                strategy: "ASAPStrategies",
                 provenance: ReplacementProvenance::SummaryRealization,
                 rationale: "select exact Top-K from independently maintained temporal values"
                     .into(),
@@ -1413,8 +1514,8 @@ impl<'a> SketchAlgorithmStrategy<'a> {
         if intent_override.is_none() {
             if let Ok(Some(node)) = realize_temporal_average(root, self.planning_inputs, None) {
                 proposals.candidates.push(ReplacementSubDAG {
-                    replacement: Replacement::Summary(node),
-                    strategy: "SketchAlgorithmStrategy",
+                    replacement: Replacement::SubDAG(node),
+                    strategy: "ASAPStrategies",
                     provenance: ReplacementProvenance::SummaryRealization,
                     rationale: "read temporal average from sum/count only within the finite arithmetic domain; otherwise execute the original average".into(),
                 });
@@ -1428,8 +1529,8 @@ impl<'a> SketchAlgorithmStrategy<'a> {
                     "preserve exact PromQL arithmetic over independently realized summary operands"
                 };
                 proposals.candidates.push(ReplacementSubDAG {
-                    replacement: Replacement::Summary(node),
-                    strategy: "SketchAlgorithmStrategy",
+                    replacement: Replacement::SubDAG(node),
+                    strategy: "ASAPStrategies",
                     provenance: ReplacementProvenance::SummaryRealization,
                     rationale: rationale.into(),
                 });
@@ -1516,17 +1617,17 @@ impl<'a> SketchAlgorithmStrategy<'a> {
             let Some(child) = aggregate_child(root) else {
                 continue;
             };
-            let QueryExpr::Aggregate { reduction, .. } = root.as_ref() else {
+            let Some(NonASAPOp::Aggregate { reduction, .. }) = root.non_asap() else {
                 continue;
             };
             let Ok(input) = realize_physical_summary_input(intent, &family, reduction, child)
             else {
                 continue;
             };
-            let readout_query = readout(intent, &input.input, planning_inputs.cost);
+            let evaluation_query = evaluation(intent, &input.input, planning_inputs.cost);
             let Some(local) = planning_inputs
                 .accuracy
-                .local_guarantee(&family, &readout_query)
+                .local_guarantee(&family, &evaluation_query)
             else {
                 continue;
             };
@@ -1537,7 +1638,7 @@ impl<'a> SketchAlgorithmStrategy<'a> {
             let allocations = planning_inputs.allocator.allocations(target, &shape);
             if allocations.is_empty() {
                 proposals.rejected.push(RejectedCandidate {
-                    strategy: "SketchAlgorithmStrategy",
+                    strategy: "ASAPStrategies",
                     description: rationale.clone(),
                     error: AccuracyError::NoLegalAllocation {
                         target: target.clone(),
@@ -1591,10 +1692,10 @@ impl<'a> SketchAlgorithmStrategy<'a> {
         }
         if proposals.candidates.is_empty() {
             if let Some(error) = &proposals.domain_error {
-                if let Ok(node) = keep_pre_asap(root) {
+                if let Ok(node) = retain_exact(root) {
                     proposals.candidates.push(ReplacementSubDAG {
-                        strategy: "SketchAlgorithmStrategy",
-                        replacement: Replacement::Summary(node),
+                        strategy: "ASAPStrategies",
+                        replacement: Replacement::SubDAG(node),
                         provenance: ReplacementProvenance::SummaryRealization,
                         rationale: format!(
                             "{} stays pre-ASAP because summary construction crosses an illegal \
@@ -1613,16 +1714,16 @@ impl Proposals {
     /// File one construction attempt: a legal node becomes a candidate, an
     /// [`RealizationError::Accuracy`] becomes a [`RejectedCandidate`], and a
     /// schema-derivation failure is skipped exactly as it always was.
-    fn record(&mut self, rationale: String, built: Result<Rc<SummaryNode>, RealizationError>) {
+    fn record(&mut self, rationale: String, built: Result<Rc<OperatorNode>, RealizationError>) {
         match built {
             Ok(node) => self.candidates.push(ReplacementSubDAG {
-                strategy: "SketchAlgorithmStrategy",
-                replacement: Replacement::Summary(node),
+                strategy: "ASAPStrategies",
+                replacement: Replacement::SubDAG(node),
                 provenance: ReplacementProvenance::SummaryRealization,
                 rationale,
             }),
             Err(RealizationError::Accuracy(error)) => self.rejected.push(RejectedCandidate {
-                strategy: "SketchAlgorithmStrategy",
+                strategy: "ASAPStrategies",
                 description: rationale,
                 error,
             }),
@@ -1639,14 +1740,14 @@ impl Proposals {
 }
 
 /// The `child` of a [`bindable_intent`]-shaped `Aggregate`.
-fn aggregate_child(node: &QueryExpr) -> Option<&Rc<QueryExpr>> {
-    match node {
-        QueryExpr::Aggregate { child, .. } => Some(child),
+fn aggregate_child(node: &OperatorNode) -> Option<&Rc<OperatorNode>> {
+    match node.non_asap() {
+        Some(NonASAPOp::Aggregate { child, .. }) => Some(child),
         _ => None,
     }
 }
 
-impl ReplacementStrategy for SketchAlgorithmStrategy<'_> {
+impl ReplacementStrategy for ASAPStrategies<'_> {
     fn matches(&self, target: &TargetSubDAG<'_>) -> bool {
         bindable_intent(target.root).is_some() || is_supported_exact_binary(target.root)
     }
@@ -1665,24 +1766,24 @@ impl ReplacementStrategy for SketchAlgorithmStrategy<'_> {
     /// for the identity-carrying root. Placement variants (for example,
     /// fixed-window or query-time Rate aggregation) are not listed here: the
     /// lifecycle assigns timing and the physical compiler reads it.
-    fn propose_for_root(&self, root: &Rc<QueryExpr>, target: &AccuracyTarget) -> Proposals {
-        let Ok(typed) = asap_types::pre_asap::schema::with_promql_series_identity(root) else {
+    fn propose_for_root(&self, root: &Rc<OperatorNode>, target: &AccuracyTarget) -> Proposals {
+        let Ok(typed) = asap_types::ir::schema_support::with_promql_series_identity(root) else {
             return Proposals::default();
         };
-        let typed = Rc::new(typed);
+
         let mut proposals = self.current_series_topk_candidates(&typed, target);
         for mut candidate in std::mem::take(&mut proposals.candidates) {
-            let Replacement::Summary(node) = candidate.replacement else {
+            let Replacement::SubDAG(node) = candidate.replacement else {
                 continue;
             };
             let Ok(node) = finalize_query_candidate(node, &typed) else {
                 continue;
             };
             let duplicate = proposals.candidates.iter().any(|existing| {
-                matches!(&existing.replacement, Replacement::Summary(other) if *other == node)
+                matches!(&existing.replacement, Replacement::SubDAG(other) if *other == node)
             });
             if !duplicate {
-                candidate.replacement = Replacement::Summary(node);
+                candidate.replacement = Replacement::SubDAG(node);
                 candidate.provenance = ReplacementProvenance::RootPhysicalRealization;
                 proposals.candidates.push(candidate);
             }
@@ -1755,11 +1856,11 @@ pub(crate) fn describe_intent(intent: &AggIntent) -> String {
     }
 }
 
-// ── realize_child / keep_pre_asap: rank-and-take-first, and its fallback ──
+// ── realize_child / retain_exact: rank-and-take-first, and its fallback ──
 
-/// Rank-and-take-first selector for a single [`QueryExpr`] node: enumerate
-/// every candidate via [`SketchAlgorithmStrategy::replacements`], keep the
-/// `cost_model`-preferred (first) one, and fall back to [`keep_pre_asap`]
+/// Rank-and-take-first selector for a single [`OperatorNode`]: enumerate
+/// every candidate via [`ASAPStrategies::replacements`], keep the
+/// `cost_model`-preferred (first) one, and fall back to [`retain_exact`]
 /// when there's no candidate at all — **not** a general single-answer API
 /// for a whole workload. Use [`CandidateLogicalASAPDAGs::global_selection`] and DAG assembly
 /// for coordinated logical selection; physical deployment remains downstream.
@@ -1771,16 +1872,16 @@ pub(crate) fn describe_intent(intent: &AggIntent) -> String {
 /// ([`construct_summary_agg`], so a nested aggregate gets its own
 /// independent enumeration instead of inheriting the parent's forced
 /// candidate), from this module's own [`realize_one`] (the representative
-/// bound `SummaryNode` [`cse_preference`] needs for a
+/// bound `OperatorNode` [`cse_preference`] needs for a
 /// [`CostModel::cse_share_decision`] comparison), and from
 /// [`crate::cost_model::DefaultCostModel::estimate_cost`] (the same
 /// representative-node need, for a [`Replacement::Rewrite`] candidate's own
 /// cost estimate). Every other caller goes through
-/// [`SketchAlgorithmStrategy::replacements`] directly and decides for itself.
+/// [`ASAPStrategies::replacements`] directly and decides for itself.
 pub(crate) fn realize_child(
-    root: &Rc<QueryExpr>,
+    root: &Rc<OperatorNode>,
     cost_model: &dyn CostModel,
-) -> Result<Rc<SummaryNode>, RealizationError> {
+) -> Result<Rc<OperatorNode>, RealizationError> {
     realize_child_with(
         root,
         CandidatePlanningInputs::with_default_accuracy(cost_model),
@@ -1797,17 +1898,17 @@ pub(crate) fn realize_child(
 /// budget. A child whose declared target is `Exact` keeps it: an allocation
 /// never approximates something the caller declared exact.
 fn exact_topk_over_temporal_values(
-    root: &Rc<QueryExpr>,
+    root: &Rc<OperatorNode>,
     planning_inputs: CandidatePlanningInputs<'_>,
-) -> Result<Option<Rc<SummaryNode>>, RealizationError> {
-    let QueryExpr::Aggregate {
+) -> Result<Option<Rc<OperatorNode>>, RealizationError> {
+    let Some(NonASAPOp::Aggregate {
         reduction,
         measures,
         output_names: _,
         filters,
         having: None,
         child,
-    } = root.as_ref()
+    }) = root.non_asap()
     else {
         return Ok(None);
     };
@@ -1817,19 +1918,19 @@ fn exact_topk_over_temporal_values(
     let [AggIntent::TopK { k, .. }] = measures.as_slice() else {
         return Ok(None);
     };
-    let QueryExpr::Aggregate {
+    let Some(NonASAPOp::Aggregate {
         reduction: Reduction::PerEntity,
         child: input,
         ..
-    } = child.as_ref()
+    }) = child.non_asap()
     else {
         return Ok(None);
     };
-    if !matches!(input.as_ref(), QueryExpr::TimeRange { .. }) {
+    if !matches!(input.non_asap(), Some(NonASAPOp::TimeRange { .. })) {
         return Ok(None);
     }
     let values = realize_child_with(child, planning_inputs, Some(&AccuracyTarget::Exact))?;
-    if matches!(values.expr, SummaryExpr::KeepPreAsap(_))
+    if !values.contains_asap()
         || !values
             .guarantee
             .as_ref()
@@ -1845,61 +1946,63 @@ fn exact_topk_over_temporal_values(
         ))?
         .clone();
     let score = ranking_score_index(child, &values.schema)?;
-    let sorted = Rc::new(SummaryNode {
-        guarantee: values.guarantee.clone(),
-        schema: values.schema.clone(),
-        expr: SummaryExpr::ValueOperation {
-            child: values,
-            operation: ValueOperation::Sort {
-                keys: vec![asap_types::pre_asap::SortKey {
-                    expr: QueryExpr::Column(score),
+    let guarantee = values.guarantee.clone();
+    let schema = values.schema.clone();
+    let sorted = Rc::new(
+        OperatorNode::with_schema(
+            Operator::NonASAP(NonASAPOp::Sort {
+                keys: vec![SortKey {
+                    expr: ScalarExpr::Column(score),
                     ascending: false,
                     nulls_first: false,
                 }],
                 partition_by: partition_by.clone(),
-            },
-            timing: ExecutionTiming::QueryTime,
-        },
-    });
-    let node = Rc::new(SummaryNode {
-        guarantee: sorted.guarantee.clone(),
-        schema: sorted.schema.clone(),
-        expr: SummaryExpr::ValueOperation {
-            child: sorted,
-            operation: ValueOperation::Limit {
-                n: *k,
+                child: values,
+            }),
+            schema.clone(),
+        )
+        .with_guarantee(guarantee.clone()),
+    );
+    let node = Rc::new(
+        OperatorNode::with_schema(
+            Operator::NonASAP(NonASAPOp::Limit {
+                n: Some(*k),
                 offset: 0,
                 partition_by,
-            },
-            timing: ExecutionTiming::QueryTime,
-        },
-    });
-    validate_execution_data_states_at(&node, ExecutionDataState::QUERY_ROWS)?;
+                child: sorted,
+            }),
+            schema,
+        )
+        .with_guarantee(guarantee),
+    );
+    validate_default(&node, ExecutionTiming::QueryTime)?;
     Ok(Some(node))
 }
 
 fn realize_temporal_average(
-    root: &Rc<QueryExpr>,
+    root: &Rc<OperatorNode>,
     planning_inputs: CandidatePlanningInputs<'_>,
     target: Option<&AccuracyTarget>,
-) -> Result<Option<Rc<SummaryNode>>, RealizationError> {
+) -> Result<Option<Rc<OperatorNode>>, RealizationError> {
     let Some(components) = crate::rewrite::temporal_average_components(root) else {
         return Ok(None);
     };
     let mut node = realize_child_with(&components, planning_inputs, target)?;
-    let SummaryExpr::BinaryOp { operator, .. } = &mut Rc::make_mut(&mut node).expr else {
+    let Operator::NonASAP(NonASAPOp::BinaryOp { operator, .. }) =
+        &mut Rc::make_mut(&mut node).operator
+    else {
         return Ok(None);
     };
     operator.checked_finite_division = true;
-    validate_execution_data_states_at(&node, ExecutionDataState::QUERY_ROWS)?;
+    validate_default(&node, ExecutionTiming::QueryTime)?;
     Ok(Some(node))
 }
 
 pub(crate) fn realize_child_with(
-    root: &Rc<QueryExpr>,
+    root: &Rc<OperatorNode>,
     planning_inputs: CandidatePlanningInputs<'_>,
     end_to_end_target: Option<&AccuracyTarget>,
-) -> Result<Rc<SummaryNode>, RealizationError> {
+) -> Result<Rc<OperatorNode>, RealizationError> {
     if let Some(node) = realize_temporal_average(root, planning_inputs, end_to_end_target)? {
         return Ok(node);
     }
@@ -1913,29 +2016,29 @@ pub(crate) fn realize_child_with(
             Some(_) => Some(override_accuracy(declared, target)),
         }
     });
-    match SketchAlgorithmStrategy::from_planning_inputs(planning_inputs)
+    match ASAPStrategies::from_planning_inputs(planning_inputs)
         .propose_with(root, overridden.as_ref(), None)
         .candidates
         .into_iter()
         .next()
     {
         Some(ReplacementSubDAG {
-            replacement: Replacement::Summary(node),
+            replacement: Replacement::SubDAG(node),
             ..
         }) => Ok(node),
         Some(ReplacementSubDAG {
-            replacement: Replacement::Rewrite(_) | Replacement::ExactComposition(_),
+            replacement: Replacement::ExactComposition(_),
             ..
         }) => {
-            unreachable!("SketchAlgorithmStrategy never returns a Rewrite/composition candidate")
+            unreachable!("ASAPStrategies never returns a composition candidate")
         }
         // No candidate at all: `root` isn't `bindable_intent` shape (or its
         // intent has no realization `realizations_for_intent` can't
         // produce — never happens, that match is exhaustive), or every
         // candidate was accuracy-illegal — either way the same conservative
-        // fallback `SketchAlgorithmStrategy::matches` uses: keep the
+        // fallback `ASAPStrategies::matches` uses: keep the
         // pre-ASAP sub-DAG, executed exactly.
-        None => keep_pre_asap(root),
+        None => retain_exact(root),
     }
 }
 
@@ -1944,29 +2047,24 @@ pub(crate) fn realize_child_with(
 /// accelerated, return `None` so the caller keeps the whole query exact;
 /// mixed raw/summary snapshots are never constructed.
 fn realize_binary(
-    root: &Rc<QueryExpr>,
+    root: &Rc<OperatorNode>,
     planning_inputs: CandidatePlanningInputs<'_>,
     end_to_end_target: Option<&AccuracyTarget>,
-) -> Result<Option<Rc<SummaryNode>>, RealizationError> {
-    let QueryExpr::BinaryOp {
-        op,
+) -> Result<Option<Rc<OperatorNode>>, RealizationError> {
+    let Some(NonASAPOp::BinaryOp {
+        operator,
+        return_bool,
         lhs,
         rhs,
-        vector_match,
-    } = root.as_ref()
+    }) = root.non_asap()
     else {
         return Ok(None);
     };
+    let (op, vector_match) = (&operator.kind, &operator.vector_match);
     if !matches!(op, BinaryOpKind::Arithmetic(_)) || vector_match.is_some() {
         return Ok(None);
     }
 
-    let lhs_scalar = is_promql_scalar(lhs);
-    let rhs_scalar = is_promql_scalar(rhs);
-    if lhs_scalar && rhs_scalar {
-        return Ok(None);
-    }
-
     let mut lhs_node = realize_binary_operand(lhs, planning_inputs, None)?;
     let mut rhs_node = realize_binary_operand(rhs, planning_inputs, None)?;
 
@@ -2085,8 +2183,8 @@ fn realize_binary(
         return Ok(None);
     }
 
-    let lhs_accelerated = lhs_scalar || !matches!(lhs_node.expr, SummaryExpr::KeepPreAsap(_));
-    let rhs_accelerated = rhs_scalar || !matches!(rhs_node.expr, SummaryExpr::KeepPreAsap(_));
+    let lhs_accelerated = lhs_node.contains_asap();
+    let rhs_accelerated = rhs_node.contains_asap();
     if !lhs_accelerated || !rhs_accelerated {
         return Ok(None);
     }
@@ -2133,47 +2231,107 @@ fn realize_binary(
         return Ok(None);
     }
 
-    Ok(Some(Rc::new(SummaryNode {
-        expr: SummaryExpr::BinaryOp {
-            timing: ExecutionTiming::QueryTime,
-            lhs: lhs_node,
-            rhs: rhs_node,
-            operator: asap_types::post_asap::BinaryOperator {
-                checked_relative_division: false,
-                checked_finite_division: false,
-                kind: op.clone(),
-                vector_match: vector_match.clone(),
-            },
-        },
-        schema: lift(&root.output_schema()?),
+    Ok(Some(Rc::new(
+        OperatorNode::with_schema(
+            Operator::NonASAP(NonASAPOp::BinaryOp {
+                operator: BinaryOperator {
+                    checked_relative_division: false,
+                    checked_finite_division: false,
+                    kind: op.clone(),
+                    vector_match: vector_match.clone(),
+                },
+                return_bool: *return_bool,
+                lhs: lhs_node,
+                rhs: rhs_node,
+            }),
+            root.schema.clone(),
+        )
         // Exact arithmetic does not erase approximation error. Until the
         // accuracy algebra has an operator-specific rule (and any value-range
         // evidence needed by multiplication/division), unknown stays unknown.
-        guarantee,
-    })))
+        .with_guarantee(guarantee),
+    )))
+}
+
+/// Rebuild the summary chain above a per-series `Rate` accumulator with its
+/// `FinalizeExactAccumulator` placed at `timing`. `strict` additionally
+/// requires the fixed-window shape (a `PerEntity` Rate over a `TimeRange`);
+/// `None` when no such boundary exists (strict only).
+fn retime_rate_finalize(
+    node: &Rc<OperatorNode>,
+    timing: ExecutionTiming,
+    strict: bool,
+) -> Option<Rc<OperatorNode>> {
+    let is_rate_boundary = |child: &OperatorNode| match &child.operator {
+        Operator::ASAP(ASAPOp::SummaryAgg {
+            family: FieldDataType::ExactAggregate(ExactKind::Rate, _),
+            reduction,
+            child: source,
+            ..
+        }) => {
+            !strict
+                || (matches!(reduction, Reduction::PerEntity)
+                    && matches!(source.non_asap(), Some(NonASAPOp::TimeRange { .. })))
+        }
+        _ => false,
+    };
+    let rebuilt = |operator: Operator, timing: Option<ExecutionTiming>| {
+        Rc::new(OperatorNode {
+            operator,
+            timing,
+            ..node.as_ref().clone()
+        })
+    };
+    match &node.operator {
+        Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child }) if is_rate_boundary(child) => {
+            Some(rebuilt(node.operator.clone(), Some(timing)))
+        }
+        Operator::ASAP(
+            ASAPOp::FinalizeExactAccumulator { child }
+            | ASAPOp::SummaryAgg { child, .. }
+            | ASAPOp::SummaryEstimate {
+                summary_input: child,
+                ..
+            },
+        ) => {
+            let placed = match retime_rate_finalize(child, timing, strict) {
+                Some(placed) => placed,
+                None if strict => return None,
+                None => return Some(Rc::clone(node)),
+            };
+            let operator = node.operator.map_children(|_| Rc::clone(&placed));
+            Some(rebuilt(operator, node.timing))
+        }
+        _ if strict => None,
+        _ => Some(Rc::clone(node)),
+    }
 }
 
 /// Put an explicit read boundary between maintained exact state and a
 /// query-time value consumer. Approximate summaries must already carry a
 /// `SummaryEstimate`, so they deliberately do not pass this predicate.
 pub fn finalize_query_candidate(
-    node: Rc<SummaryNode>,
-    logical_output: &QueryExpr,
-) -> Result<Rc<SummaryNode>, RealizationError> {
-    finalize_exact_accumulator_at(node, logical_output, ExecutionTiming::QueryTime)
-}
-
-fn finalize_exact_accumulator_at(
-    node: Rc<SummaryNode>,
-    logical_output: &QueryExpr,
-    timing: ExecutionTiming,
-) -> Result<Rc<SummaryNode>, RealizationError> {
+    node: Rc<OperatorNode>,
+    logical_output: &OperatorNode,
+) -> Result<Rc<OperatorNode>, RealizationError> {
+    finalize_exact_accumulator(node, logical_output, ExecutionTiming::QueryTime)
+}
+
+/// The read boundary's placement is fixed here, where the candidate's
+/// semantics decide it (a fresh query-time summary over this evaluation's
+/// finalized values vs. finalized values feeding maintenance); the lifecycle
+/// timing pass honors it.
+fn finalize_exact_accumulator(
+    node: Rc<OperatorNode>,
+    logical_output: &OperatorNode,
+    placement: ExecutionTiming,
+) -> Result<Rc<OperatorNode>, RealizationError> {
     let is_exact_state = matches!(
-        node.expr,
-        SummaryExpr::SummaryAgg {
+        node.operator,
+        Operator::ASAP(ASAPOp::SummaryAgg {
             family: FieldDataType::ExactAggregate(..),
             ..
-        }
+        })
     );
     if !is_exact_state {
         return Ok(node);
@@ -2182,41 +2340,36 @@ fn finalize_exact_accumulator_at(
     // boundary produces the logical operator's ordinary values. Preserve the
     // canonical pre-ASAP output types instead of leaking ExactAggregate into
     // query-time operators that follow this node.
-    let schema = lift(&logical_output.output_schema()?);
+    let schema = logical_output.schema.clone();
     let guarantee = node.guarantee.clone();
-    Ok(Rc::new(SummaryNode {
-        expr: SummaryExpr::ValueOperation {
-            child: node,
-            operation: ValueOperation::FinalizeExactAccumulator,
-            timing,
-        },
-        schema,
-        guarantee,
-    }))
+    Ok(Rc::new(
+        OperatorNode::with_schema(
+            Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child: node }),
+            schema,
+        )
+        .with_guarantee(guarantee)
+        .with_timing(Some(placement)),
+    ))
 }
 
-fn is_supported_exact_binary(root: &QueryExpr) -> bool {
+fn is_supported_exact_binary(root: &OperatorNode) -> bool {
     matches!(
-        root,
-        QueryExpr::BinaryOp {
-            op: BinaryOpKind::Arithmetic(_),
-            vector_match: None,
+        root.non_asap(),
+        Some(NonASAPOp::BinaryOp {
+            operator: BinaryOperator {
+                kind: BinaryOpKind::Arithmetic(_),
+                vector_match: None,
+                ..
+            },
             ..
-        }
-    )
-}
-
-fn is_promql_scalar(expr: &QueryExpr) -> bool {
-    matches!(
-        expr,
-        QueryExpr::PromqlScalarBridge(_) | QueryExpr::Literal(_)
+        })
     )
 }
 
 /// Quantile operands inherit one workload target. A temporal mean is exact
 /// on its checked finite domain and needs no approximation budget.
-fn shared_quantile_target(lhs: &QueryExpr, rhs: &QueryExpr) -> Option<AccuracyTarget> {
-    let quantile_target = |expr: &QueryExpr| match bindable_intent(expr) {
+fn shared_quantile_target(lhs: &OperatorNode, rhs: &OperatorNode) -> Option<AccuracyTarget> {
+    let quantile_target = |expr: &OperatorNode| match bindable_intent(expr) {
         Some(AggIntent::Quantile { accuracy, q, .. })
             if q.is_finite() && (0.0..=1.0).contains(q) =>
         {
@@ -2254,18 +2407,18 @@ fn ddsketch_ratio_operand_target(target: &AccuracyTarget) -> Option<AccuracyTarg
     }
 }
 
-fn ddsketch_quantile_alpha(node: &SummaryNode) -> Option<f64> {
-    let SummaryExpr::SummaryEstimate {
+fn ddsketch_quantile_alpha(node: &OperatorNode) -> Option<f64> {
+    let Operator::ASAP(ASAPOp::SummaryEstimate {
         summary_input,
         query: PostAsapSketchStatistic::Quantile { .. },
-    } = &node.expr
+    }) = &node.operator
     else {
         return None;
     };
-    let SummaryExpr::SummaryAgg {
+    let Operator::ASAP(ASAPOp::SummaryAgg {
         family: FieldDataType::Sketch(kind, _),
         ..
-    } = &summary_input.expr
+    }) = &summary_input.operator
     else {
         return None;
     };
@@ -2275,7 +2428,7 @@ fn ddsketch_quantile_alpha(node: &SummaryNode) -> Option<f64> {
     }
 }
 
-fn has_missing_accuracy_evidence(node: &SummaryNode) -> bool {
+fn has_missing_accuracy_evidence(node: &OperatorNode) -> bool {
     node.guarantee
         .as_ref()
         .is_none_or(ResultGuarantee::has_unknown)
@@ -2284,10 +2437,10 @@ fn has_missing_accuracy_evidence(node: &SummaryNode) -> bool {
 /// A direct ratio has an operator-specific DDSketch proof, so it must select
 /// DDSketch rather than the cost model's generally preferred KLL candidate.
 fn realize_ddsketch_quantile_operand(
-    operand: &Rc<QueryExpr>,
+    operand: &Rc<OperatorNode>,
     planning_inputs: CandidatePlanningInputs<'_>,
     target: &AccuracyTarget,
-) -> Result<Rc<SummaryNode>, RealizationError> {
+) -> Result<Rc<OperatorNode>, RealizationError> {
     let intent = bindable_intent(operand).and_then(|intent| match intent {
         AggIntent::Quantile { .. } => Some(override_accuracy(intent, target)),
         _ => None,
@@ -2306,17 +2459,10 @@ fn realize_ddsketch_quantile_operand(
 }
 
 fn realize_binary_operand(
-    operand: &Rc<QueryExpr>,
+    operand: &Rc<OperatorNode>,
     planning_inputs: CandidatePlanningInputs<'_>,
     end_to_end_target: Option<&AccuracyTarget>,
-) -> Result<Rc<SummaryNode>, RealizationError> {
-    if is_promql_scalar(operand) {
-        return Ok(Rc::new(SummaryNode {
-            expr: SummaryExpr::KeepPreAsap(Rc::clone(operand)),
-            schema: Schema::lifted(Vec::new(), None),
-            guarantee: Some(ResultGuarantee::exact("PromQL scalar")),
-        }));
-    }
+) -> Result<Rc<OperatorNode>, RealizationError> {
     realize_child_with(operand, planning_inputs, end_to_end_target)
 }
 
@@ -2334,43 +2480,77 @@ fn override_accuracy(intent: &AggIntent, target: &AccuracyTarget) -> AggIntent {
     out
 }
 
-/// Wrap an unrewritten pre-ASAP sub-DAG, lifting its schema with every column
-/// `FieldDataType::Plain`. `pub` so a caller can fall back to this
-/// explicitly — e.g. when `SketchAlgorithmStrategy::replacements()` returns no
-/// candidate for a target, or a deployment wants to force a node its own
-/// runtime can't actually implement — through the same fallback this
-/// crate's own dispatch uses, without duplicating the schema-lift logic.
-pub fn keep_pre_asap(expr: &Rc<QueryExpr>) -> Result<Rc<SummaryNode>, RealizationError> {
-    keep_pre_asap_rc(Rc::clone(expr))
-}
-
-fn keep_pre_asap_rc(expr: Rc<QueryExpr>) -> Result<Rc<SummaryNode>, RealizationError> {
-    let schema = expr.output_schema()?;
-    Ok(Rc::new(SummaryNode {
-        expr: SummaryExpr::KeepPreAsap(expr),
-        schema: lift(&schema),
-        // A kept pre-ASAP sub-DAG is executed exactly by the runtime
-        // (`Realization::PassThrough`'s contract) — zero error.
-        guarantee: Some(ResultGuarantee::exact("KeepPreAsap")),
-    }))
+/// Keep an unrewritten pre-ASAP sub-DAG as it is. There is no wrapper node:
+/// the sub-DAG itself is the plan, carrying an exact guarantee. The same
+/// `Rc` is returned when the node already has a guarantee; otherwise a copy
+/// with `guarantee = exact("RetainedExact")` — only for a sub-DAG with no
+/// ASAP operator (a sub-DAG containing one keeps whatever its construction
+/// established). `pub` so a caller can fall back to this explicitly — e.g.
+/// when `ASAPStrategies::replacements()` returns no candidate for a
+/// target, or a deployment wants to force a node its own runtime can't
+/// actually implement — through the same fallback this crate's own dispatch
+/// uses.
+pub fn retain_exact(expr: &Rc<OperatorNode>) -> Result<Rc<OperatorNode>, RealizationError> {
+    retain_exact_rc(Rc::clone(expr))
+}
+
+fn retain_exact_rc(expr: Rc<OperatorNode>) -> Result<Rc<OperatorNode>, RealizationError> {
+    if expr.guarantee.is_some() || expr.contains_asap() {
+        return Ok(expr);
+    }
+    // Keeping the same sub-DAG twice (e.g. one `Scan` read by an exact
+    // aggregate and by a sketch, or by two candidates) must yield one node:
+    // sharing is pointer identity. Memoize the kept copy per input node while
+    // both are alive; weak references keep the memo from extending lifetimes
+    // or matching a reused address.
+    type KeptMemo = HashMap<*const OperatorNode, (Weak<OperatorNode>, Weak<OperatorNode>)>;
+    thread_local! {
+        static KEPT: RefCell<KeptMemo> = RefCell::new(HashMap::new());
+    }
+    let key = Rc::as_ptr(&expr);
+    if let Some(kept) = KEPT.with(|memo| {
+        memo.borrow().get(&key).and_then(|(input, kept)| {
+            input
+                .upgrade()
+                .filter(|input| Rc::ptr_eq(input, &expr))
+                .and_then(|_| kept.upgrade())
+        })
+    }) {
+        return Ok(kept);
+    }
+    let kept = Rc::new(
+        expr.as_ref()
+            .clone()
+            // A kept pre-ASAP sub-DAG is executed exactly by the runtime
+            // (`Realization::PassThrough`'s contract) — zero error.
+            .with_guarantee(Some(ResultGuarantee::exact("RetainedExact"))),
+    );
+    KEPT.with(|memo| {
+        let mut memo = memo.borrow_mut();
+        if memo.len() > 4096 {
+            memo.retain(|_, (input, kept)| input.strong_count() > 0 && kept.strong_count() > 0);
+        }
+        memo.insert(key, (Rc::downgrade(&expr), Rc::downgrade(&kept)));
+    });
+    Ok(kept)
 }
 
-// ── Construction: turn one already-decided Realization into a SummaryNode ─
+// ── Construction: turn one already-decided Realization into an OperatorNode ─
 
-/// The bindable shape [`SketchAlgorithmStrategy`] targets: a single intent, no
+/// The bindable shape [`ASAPStrategies`] targets: a single intent, no
 /// `HAVING`. A multi-intent node (SQL `SELECT SUM(a), AVG(b)`), or one with a
 /// `HAVING` predicate (the filter would need the estimate first), stays
-/// logical. Unsupported logical parents still conservatively become one
-/// [`SummaryExpr::KeepPreAsap`] sub-DAG. Composable query-time value
-/// operators (`Project`, `Filter`, `Sort`, and `Limit`) are retained during final
-/// DAG assembly so their independently planned children remain visible.
-pub fn bindable_intent(node: &QueryExpr) -> Option<&AggIntent> {
-    if let QueryExpr::Aggregate {
+/// logical. Unsupported logical parents are conservatively kept as pre-ASAP
+/// sub-DAGs ([`retain_exact`]). Relational operators are retained during
+/// final DAG assembly so their independently planned children remain
+/// visible.
+pub fn bindable_intent(node: &OperatorNode) -> Option<&AggIntent> {
+    if let Some(NonASAPOp::Aggregate {
         measures,
         filters,
         having,
         ..
-    } = node
+    }) = node.non_asap()
     {
         if let ([intent], None) = (measures.as_slice(), having) {
             if !any_measure_filtered(filters) {
@@ -2382,7 +2562,7 @@ pub fn bindable_intent(node: &QueryExpr) -> Option<&AggIntent> {
 }
 
 /// `expr` must still be the [`bindable_intent`] shape for `realization` to
-/// have any effect; anything else falls back to [`keep_pre_asap`].
+/// have any effect; anything else falls back to [`retain_exact`].
 /// Only `expr`'s own top-level decision is forced — recursion into `expr`'s
 /// child goes back through [`realize_child`] (fresh candidate
 /// enumeration, not a forced pick), so choosing one candidate for a target
@@ -2390,10 +2570,10 @@ pub fn bindable_intent(node: &QueryExpr) -> Option<&AggIntent> {
 ///
 /// `pub(crate)`: `grouping::HydraGroupingStrategy` (issue #256) is the one
 /// caller outside this module — the same first-class,
-/// one-candidate-at-a-time primitive [`SketchAlgorithmStrategy`] itself
+/// one-candidate-at-a-time primitive [`ASAPStrategies`] itself
 /// calls once per candidate, reused rather than duplicated so a Hydra
 /// candidate gets exactly the same schema derivation/column
-/// resolution/readout construction as every other candidate, patching only
+/// resolution/evaluation construction as every other candidate, patching only
 /// the `grouping` field this axis owns.
 /// Construct a summary with every model explicit (issue #172). `intent`
 /// is `expr`'s own [`bindable_intent`], or a copy of it with an allocated
@@ -2404,13 +2584,13 @@ pub fn bindable_intent(node: &QueryExpr) -> Option<&AggIntent> {
 /// fail-closed answer for a composition with no sound rule or one that
 /// misses `intent`'s target.
 pub(crate) fn construct_summary_with(
-    expr: &QueryExpr,
+    expr: &OperatorNode,
     intent: &AggIntent,
     realization: Realization,
     planning_inputs: CandidatePlanningInputs<'_>,
     child_target: Option<&AccuracyTarget>,
     allocation: Option<GuaranteeSource>,
-) -> Result<Rc<SummaryNode>, RealizationError> {
+) -> Result<Rc<OperatorNode>, RealizationError> {
     let local_target = match allocation.as_ref() {
         Some(GuaranteeSource::BudgetAllocation { local_target, .. }) => Some(local_target),
         _ => accuracy_target(intent),
@@ -2427,9 +2607,9 @@ pub(crate) fn construct_summary_with(
         },
         other => other,
     };
-    if let QueryExpr::Aggregate {
+    if let Some(NonASAPOp::Aggregate {
         reduction, child, ..
-    } = expr
+    }) = expr.non_asap()
     {
         // `bindable_intent` already established the shape: exactly one
         // intent, no HAVING. (Multi-intent nodes and HAVING stay logical.)
@@ -2454,28 +2634,28 @@ pub(crate) fn construct_summary_with(
             }
         }
     }
-    keep_pre_asap_rc(Rc::new(expr.clone()))
+    retain_exact_rc(Rc::new(expr.clone()))
 }
 
 fn finish_weighted_topk(
-    candidate: Rc<SummaryNode>,
-    logical: &QueryExpr,
+    candidate: Rc<OperatorNode>,
+    logical: &OperatorNode,
     intent: &AggIntent,
-) -> Result<Rc<SummaryNode>, RealizationError> {
+) -> Result<Rc<OperatorNode>, RealizationError> {
     let AggIntent::TopK { k, .. } = intent else {
         unreachable!()
     };
-    let QueryExpr::Aggregate {
+    let Some(NonASAPOp::Aggregate {
         reduction: Reduction::Reduce(groups),
         child,
         ..
-    } = logical
+    }) = logical.non_asap()
     else {
         return Err(RealizationError::PhysicalRealization(
             "TopK requires explicit grouping",
         ));
     };
-    let schema = lift(&child.output_schema()?);
+    let schema = child.schema.clone();
     let score = ranking_score_index(child, &schema)?;
     let cols = schema
         .fields
@@ -2502,84 +2682,81 @@ fn finish_weighted_topk(
                     }
                 }
             };
-            Ok(asap_types::pre_asap::query_expr::ProjectItem {
+            Ok(ProjectItem {
                 alias: Some(field.name.clone()),
-                expr: QueryExpr::Column(source),
+                expr: ScalarExpr::Column(source),
             })
         })
         .collect::<Result<Vec<_>, _>>()?;
     let guarantee = candidate.guarantee.clone();
-    let projected = Rc::new(SummaryNode {
-        expr: SummaryExpr::ValueOperation {
-            child: candidate,
-            operation: ValueOperation::Project {
+    let projected = Rc::new(
+        OperatorNode::with_schema(
+            Operator::NonASAP(NonASAPOp::Project {
                 cols,
                 qualifier: None,
-            },
-            timing: ExecutionTiming::QueryTime,
-        },
-        schema: schema.clone(),
-        guarantee: guarantee.clone(),
-    });
-    let sorted = Rc::new(SummaryNode {
-        expr: SummaryExpr::ValueOperation {
-            child: projected,
-            operation: ValueOperation::Sort {
-                keys: vec![asap_types::pre_asap::SortKey {
-                    expr: QueryExpr::Column(score),
+                child: candidate,
+            }),
+            schema.clone(),
+        )
+        .with_guarantee(guarantee.clone()),
+    );
+    let sorted = Rc::new(
+        OperatorNode::with_schema(
+            Operator::NonASAP(NonASAPOp::Sort {
+                keys: vec![SortKey {
+                    expr: ScalarExpr::Column(score),
                     ascending: false,
                     nulls_first: false,
                 }],
                 partition_by: groups.clone(),
-            },
-            timing: ExecutionTiming::QueryTime,
-        },
-        schema: schema.clone(),
-        guarantee: guarantee.clone(),
-    });
-    let result = Rc::new(SummaryNode {
-        expr: SummaryExpr::ValueOperation {
-            child: sorted,
-            operation: ValueOperation::Limit {
-                n: *k,
+                child: projected,
+            }),
+            schema.clone(),
+        )
+        .with_guarantee(guarantee.clone()),
+    );
+    let result = Rc::new(
+        OperatorNode::with_schema(
+            Operator::NonASAP(NonASAPOp::Limit {
+                n: Some(*k),
                 offset: 0,
                 partition_by: groups.clone(),
-            },
-            timing: ExecutionTiming::QueryTime,
-        },
-        schema,
-        guarantee,
-    });
-    validate_execution_data_states_at(&result, ExecutionDataState::QUERY_ROWS)?;
+                child: sorted,
+            }),
+            schema,
+        )
+        .with_guarantee(guarantee),
+    );
+    validate_default(&result, ExecutionTiming::QueryTime)?;
     Ok(result)
 }
 
-fn is_current_series_source(child: &QueryExpr) -> bool {
-    let source = match child {
-        QueryExpr::TimeRange { child, .. } => child.as_ref(),
-        source => source,
+fn is_current_series_source(child: &OperatorNode) -> bool {
+    let source = match child.non_asap() {
+        Some(NonASAPOp::TimeRange { child, .. }) => child.as_ref(),
+        _ => child,
     };
-    matches!(source, QueryExpr::Scan {
+    matches!(source.non_asap(), Some(NonASAPOp::Scan {
         source: asap_types::pre_asap::Source::TimeSeries { .. }, schema, ..
-    } if schema.has_promql_series_identity())
+    }) if schema.has_promql_series_identity())
 }
 
-fn is_snapshot_weighted_topk(intent: &AggIntent, child: &QueryExpr) -> bool {
+fn is_snapshot_weighted_topk(intent: &AggIntent, child: &OperatorNode) -> bool {
     matches!(intent, AggIntent::TopK { .. })
         && (is_current_series_source(child)
-            || matches!(child,
-            QueryExpr::Aggregate { measures, child, .. }
+            || matches!(child.non_asap(),
+            Some(NonASAPOp::Aggregate { measures, child, .. })
                 if matches!(measures.as_slice(), [AggIntent::Rate | AggIntent::Increase])
                     || (matches!(measures.as_slice(), [AggIntent::Sum { .. }])
-                        && matches!(child.as_ref(), QueryExpr::Aggregate { measures, .. }
+                        && matches!(child.non_asap(), Some(NonASAPOp::Aggregate { measures, .. })
                             if matches!(measures.as_slice(), [AggIntent::Rate | AggIntent::Increase])))))
 }
 
 /// Translate an [`Realization`] into the `(family, needs a
-/// SummaryEstimate readout)` pair [`construct_summary_agg`] needs, or `None`
-/// for `PassThrough` (the caller falls back to [`keep_pre_asap`]).
+/// SummaryEstimate evaluation)` pair [`construct_summary_agg`] needs, or `None`
+/// for `PassThrough` (the caller falls back to [`retain_exact`]).
 ///
-/// Every family's partial state needs a readout to recover a value, except
+/// Every family's partial state needs a evaluation to recover a value, except
 /// `ExactAggregate` — its partial state *is* the value already, so no
 /// estimate step follows it.
 fn summary_family(realization: Realization) -> Option<(FieldDataType, bool)> {
@@ -2603,7 +2780,7 @@ fn summary_family(realization: Realization) -> Option<(FieldDataType, bool)> {
 /// input value. Composite realizations can instead consume a larger
 /// logical sub-DAG and bind a different key or value.
 struct PhysicalSummaryInput {
-    child: Rc<QueryExpr>,
+    child: Rc<OperatorNode>,
     input: SummaryUpdate,
 }
 
@@ -2614,7 +2791,7 @@ enum PhysicalSummaryInputRuleResult {
 }
 
 type PhysicalSummaryInputRule =
-    fn(&AggIntent, &FieldDataType, &Reduction, &Rc<QueryExpr>) -> PhysicalSummaryInputRuleResult;
+    fn(&AggIntent, &FieldDataType, &Reduction, &Rc<OperatorNode>) -> PhysicalSummaryInputRuleResult;
 
 /// Ordered physical-realization rules for realizations that consume more
 /// than the immediate logical input. New composite primitives add a rule here
@@ -2631,7 +2808,7 @@ fn realize_value_frequency_summary_input(
     intent: &AggIntent,
     family: &FieldDataType,
     _reduction: &Reduction,
-    child: &Rc<QueryExpr>,
+    child: &Rc<OperatorNode>,
 ) -> PhysicalSummaryInputRuleResult {
     // Frequency counts hash sample values as items but add one per observation.
     // Using the sample as a weight would turn counts into sums and admit signed CMS updates.
@@ -2642,11 +2819,7 @@ fn realize_value_frequency_summary_input(
     {
         return PhysicalSummaryInputRuleResult::NotApplicable;
     }
-    let Ok(schema) = child.output_schema() else {
-        return PhysicalSummaryInputRuleResult::Unsupported(
-            "value frequency input needs a valid schema",
-        );
-    };
+    let schema = &child.schema;
     // One item per observation is a single value stream. `summary_candidates`
     // already withholds UnivMon from a distinct-tuple count; refused here too
     // so the invariant does not rest on that table alone.
@@ -2658,7 +2831,7 @@ fn realize_value_frequency_summary_input(
     PhysicalSummaryInputRuleResult::Realized(PhysicalSummaryInput {
         child: Rc::clone(child),
         input: SummaryUpdate {
-            item: Some(SummaryInputExpr::Column(summarised_column(intent, &schema))),
+            item: Some(SummaryInputExpr::Column(summarised_column(intent, schema))),
             weight: SummaryInputExpr::Constant(1.0),
             weight_domain: WeightDomain::NonNegative {
                 proof: NonNegativeWeightProof::UnitCount,
@@ -2671,7 +2844,7 @@ fn realize_physical_summary_input(
     intent: &AggIntent,
     family: &FieldDataType,
     reduction: &Reduction,
-    child: &Rc<QueryExpr>,
+    child: &Rc<OperatorNode>,
 ) -> Result<PhysicalSummaryInput, RealizationError> {
     for rule in PHYSICAL_SUMMARY_INPUT_RULES {
         match rule(intent, family, reduction, child) {
@@ -2683,7 +2856,7 @@ fn realize_physical_summary_input(
         }
     }
 
-    let child_schema = child.output_schema()?;
+    let child_schema = &child.schema;
     if matches!(intent, AggIntent::TopK { .. }) {
         return Err(RealizationError::PhysicalRealization(
             "Top-K needs an explicit item identity and additive update input",
@@ -2693,76 +2866,70 @@ fn realize_physical_summary_input(
         child: Rc::clone(child),
         input: SummaryUpdate {
             item: None,
-            weight: summarised_input(intent, &child_schema)?,
+            weight: summarised_input(intent, child_schema)?,
             weight_domain: WeightDomain::UnknownOrSigned,
         },
     })
 }
 
 /// Emit `SummaryAgg` (recursively binding the child), plus the
-/// `SummaryEstimate` readout when `estimate` is set.
+/// `SummaryEstimate` evaluation when `estimate` is set.
 // Retain the exact expression and schema while placing its value production
-// on the update path. This is the initial layout for values feeding a summary;
-// lifecycle timing is authoritative. Read-time consumers keep their original
-// shared nodes.
-fn maintenance_exact_values(node: Rc<SummaryNode>) -> Option<Rc<SummaryNode>> {
-    let expr = match &node.expr {
+// on the update path (a node runs when its consumer runs, so beneath a
+// maintained summary this value production is ingestion-time work).
+// Read-time consumers keep their original shared nodes.
+fn maintenance_exact_values(node: Rc<OperatorNode>) -> Option<Rc<OperatorNode>> {
+    let operator = match &node.operator {
         // These guards can fall back at read time, but cannot recover a parent
         // sketch after an invalid value has entered its maintained state.
-        SummaryExpr::BinaryOp { operator, .. }
+        Operator::NonASAP(NonASAPOp::BinaryOp { operator, .. })
             if operator.checked_finite_division || operator.checked_relative_division =>
         {
             return None;
         }
-        SummaryExpr::BinaryOp {
-            lhs, rhs, operator, ..
-        } if operator.vector_match.is_none()
-            && matches!(
-                operator.kind,
-                asap_types::pre_asap::BinaryOpKind::Arithmetic(_)
-            )
+        Operator::NonASAP(NonASAPOp::BinaryOp {
+            lhs,
+            rhs,
+            operator,
+            return_bool,
+        }) if operator.vector_match.is_none()
+            && matches!(operator.kind, BinaryOpKind::Arithmetic(_))
             && node
                 .guarantee
                 .as_ref()
                 .is_some_and(ResultGuarantee::is_exact) =>
         {
-            SummaryExpr::BinaryOp {
+            Operator::NonASAP(NonASAPOp::BinaryOp {
                 lhs: maintenance_exact_values(lhs.clone())?,
                 rhs: maintenance_exact_values(rhs.clone())?,
                 operator: operator.clone(),
-                timing: ExecutionTiming::IngestionTime,
-            }
+                return_bool: *return_bool,
+            })
         }
-        SummaryExpr::ValueOperation {
-            child,
-            operation: ValueOperation::FinalizeExactAccumulator,
-            ..
-        } if matches!(
-            child.expr,
-            SummaryExpr::SummaryAgg {
-                family: FieldDataType::ExactAggregate(..),
-                ..
-            }
-        ) =>
+        Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child })
+            if matches!(
+                child.operator,
+                Operator::ASAP(ASAPOp::SummaryAgg {
+                    family: FieldDataType::ExactAggregate(..),
+                    ..
+                })
+            ) =>
         {
-            SummaryExpr::ValueOperation {
+            Operator::ASAP(ASAPOp::FinalizeExactAccumulator {
                 child: child.clone(),
-                operation: ValueOperation::FinalizeExactAccumulator,
-                timing: ExecutionTiming::IngestionTime,
-            }
+            })
         }
         _ => return Some(node),
     };
-    Some(Rc::new(SummaryNode {
-        expr,
-        schema: node.schema.clone(),
-        guarantee: node.guarantee.clone(),
-    }))
+    Some(Rc::new(
+        OperatorNode::with_schema(operator, node.schema.clone())
+            .with_guarantee(node.guarantee.clone()),
+    ))
 }
 
 #[allow(clippy::too_many_arguments)]
 fn construct_summary_agg(
-    node: &QueryExpr,
+    node: &OperatorNode,
     reduction: &Reduction,
     intent: &AggIntent,
     input: PhysicalSummaryInput,
@@ -2771,7 +2938,7 @@ fn construct_summary_agg(
     planning_inputs: CandidatePlanningInputs<'_>,
     child_target: Option<&AccuracyTarget>,
     allocation: Option<GuaranteeSource>,
-) -> Result<Rc<SummaryNode>, RealizationError> {
+) -> Result<Rc<OperatorNode>, RealizationError> {
     // The single canonical pre-ASAP derivation (per-series vs cross-series,
     // name overrides) already computes the row shape; binding only retypes
     // the summary state column.
@@ -2781,7 +2948,7 @@ fn construct_summary_agg(
             FieldDataType::Sketch(kind, _)
                 if matches!(kind.algorithm(), SketchAlgorithm::CmsWithHeap | SketchAlgorithm::CountSketchWithHeap)
         );
-    let snapshot_weighted = matches!(node, QueryExpr::Aggregate { child, .. }
+    let snapshot_weighted = matches!(node.non_asap(), Some(NonASAPOp::Aggregate { child, .. })
         if is_snapshot_weighted_topk(intent, child));
     let mut family = family;
     let score_population = if snapshot_weighted {
@@ -2809,10 +2976,10 @@ fn construct_summary_agg(
         None
     };
     let physical_reduction = if snapshot_weighted {
-        let QueryExpr::Aggregate { child, .. } = node else {
+        let Some(NonASAPOp::Aggregate { child, .. }) = node.non_asap() else {
             unreachable!()
         };
-        let source = input.child.output_schema()?;
+        let source = &input.child.schema;
         let Reduction::Reduce(keys) = reduction else {
             return Err(RealizationError::PhysicalRealization(
                 "TopK requires explicit partitions",
@@ -2850,19 +3017,19 @@ fn construct_summary_agg(
     } else {
         reduction.clone()
     };
-    let out_schema = node.output_schema()?;
-    let measures = match node {
-        QueryExpr::Aggregate { measures, .. } => measures.len(),
+    let out_schema = &node.schema;
+    let measures = match node.non_asap() {
+        Some(NonASAPOp::Aggregate { measures, .. }) => measures.len(),
         _ => 1,
     };
-    let state_idx = summary_col_index(&out_schema, reduction, measures);
+    let state_idx = summary_col_index(out_schema, reduction, measures);
 
-    let readout_schema = if keyed_heap
-        && matches!(node, QueryExpr::Aggregate { child, .. } if is_snapshot_weighted_topk(intent, child))
+    let evaluation_schema = if keyed_heap
+        && matches!(node.non_asap(), Some(NonASAPOp::Aggregate { child, .. }) if is_snapshot_weighted_topk(intent, child))
     {
-        keyed_heap_readout_schema(&input, node)?
+        keyed_heap_evaluation_schema(&input, node)?
     } else {
-        lift(&out_schema)
+        out_schema.clone()
     };
 
     let summary_input = input.input;
@@ -2879,15 +3046,15 @@ fn construct_summary_agg(
                 };
             }
         }
-        readout(intent, &summary_input, planning_inputs.cost)
+        evaluation(intent, &summary_input, planning_inputs.cost)
     });
 
-    let mut state_schema = lift(&out_schema);
+    let mut state_schema = out_schema.clone();
     if keyed_heap {
         let mut state = state_schema.fields[state_idx].clone();
         state.dtype = family.clone();
         let mut fields = if snapshot_weighted {
-            readout_schema.fields[..reduction.group_keys().map_or(0, |keys| keys.len())].to_vec()
+            evaluation_schema.fields[..reduction.group_keys().map_or(0, |keys| keys.len())].to_vec()
         } else {
             Vec::new()
         };
@@ -2895,6 +3062,7 @@ fn construct_summary_agg(
         state_schema = Schema::lifted(fields, None);
     } else if let Some(field) = state_schema.fields.get_mut(state_idx) {
         field.dtype = family.clone();
+        field.nullable = false;
         if matches!(&family, FieldDataType::Sketch(kind, _) if kind.algorithm() == &SketchAlgorithm::UnivMon)
         {
             // State identity is independent of which statistic reads it.
@@ -2902,9 +3070,9 @@ fn construct_summary_agg(
         } else if let (AggIntent::Quantile { .. }, SummaryInputExpr::Column(col)) =
             (intent, &summary_input.weight)
         {
-            // The quantile is a readout parameter: name the state after the
+            // The quantile is a evaluation parameter: name the state after the
             // column it summarizes, not after the query's output column.
-            let child_schema = input.child.output_schema()?;
+            let child_schema = input.child.schema.clone();
             if let Ok(i) = resolve_column_ref(col, &child_schema) {
                 field.name = child_schema.fields[i].name.clone();
             }
@@ -2931,9 +3099,9 @@ fn construct_summary_agg(
         .ok_or(RealizationError::PhysicalRealization(
             "snapshot ranking requires a supported current-series population",
         ))?;
-        let SummaryExpr::ValueOperation { child, .. } = &population.expr else {
+        let Operator::ASAP(ASAPOp::EvaluatePopulation { child, .. }) = &population.operator else {
             return Err(RealizationError::PhysicalRealization(
-                "missing population readout",
+                "missing population evaluation",
             ));
         };
         Rc::clone(child)
@@ -2943,27 +3111,14 @@ fn construct_summary_agg(
         // initial layout; a retained summary's lifecycle moves it to ingestion.
         finalize_query_candidate(bound_child, &input.child)?
     } else {
-        let child = finalize_exact_accumulator_at(
-            bound_child,
-            &input.child,
-            ExecutionTiming::IngestionTime,
-        )?;
-        let child = maintenance_exact_values(child).unwrap_or(keep_pre_asap(&input.child)?);
-        // Maintenance arithmetic must satisfy the ingestion contract; e.g. a
-        // per-series sum over different selectors has no exact aligned
-        // layout, so this candidate fails closed and exact execution remains.
-        // Unlike checked division, it does not fall back to `keep_pre_asap`:
-        // that retains the range expression at ingestion time, where range
-        // functions cannot run (they need a query evaluation time).
-        if matches!(child.expr, SummaryExpr::BinaryOp { .. }) {
-            validate_execution_data_states_at(&child, ExecutionDataState::INGESTION_ROWS)?;
-        }
-        child
+        let child =
+            finalize_exact_accumulator(bound_child, &input.child, ExecutionTiming::IngestionTime)?;
+        maintenance_exact_values(child).unwrap_or(retain_exact(&input.child)?)
     };
 
     // ── Guarantee (issue #172) ──────────────────────────────────────────
     // Derived *before* the node exists, so an illegal composition is never
-    // materialized: the local guarantee of this family's readout (or exact
+    // materialized: the local guarantee of this family's evaluation (or exact
     // accumulator) composed over the child's, under the operator this
     // family applies to the child's values.
     let local_target = match allocation.as_ref() {
@@ -2976,7 +3131,7 @@ fn construct_summary_agg(
         local_target,
     );
     let membership_query = if snapshot_weighted {
-        Some(readout(intent, &summary_input, planning_inputs.cost))
+        Some(evaluation(intent, &summary_input, planning_inputs.cost))
     } else {
         query.clone()
     };
@@ -3054,56 +3209,62 @@ fn construct_summary_agg(
     // a genuine empty-`by` reduction apart from a per-entity shape with no
     // grouping concept at all (issue #163). `construct_summary_agg` is the
     // single place that decides this; nothing downstream re-derives it.
-    let agg = Rc::new(SummaryNode {
-        expr: SummaryExpr::SummaryAgg {
-            child: bound_child,
-            family,
-            input: summary_input,
-            reduction: physical_reduction,
-            grouping: GroupingStrategy::default(),
-            filter: None,
-        },
-        schema: state_schema,
-        // Summary *state* carries no caller-visible guarantee; only a
-        // finalized value does. An exact accumulator's state is its value.
-        guarantee: if estimate { None } else { guarantee.clone() },
-    });
+    let agg = std::rc::Rc::new(
+        OperatorNode::with_schema(
+            asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
+                child: bound_child,
+                family,
+                input: summary_input,
+                reduction: physical_reduction,
+                grouping: GroupingStrategy::default(),
+                filter: None,
+            }),
+            state_schema,
+        )
+        .with_guarantee(
+            // Summary *state* carries no caller-visible guarantee; only a
+            // finalized value does. An exact accumulator's state is its value.
+            if estimate { None } else { guarantee.clone() },
+        ),
+    );
     match query {
-        // The readout: downstream of the estimate the schema is the plain
+        // The evaluation: downstream of the estimate the schema is the plain
         // pre-ASAP row shape again (the summary-state type does not
         // propagate).
-        Some(query) => Ok(Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryEstimate {
-                summary_input: agg,
-                query,
-            },
-            schema: readout_schema,
-            guarantee,
-        })),
+        Some(query) => Ok(std::rc::Rc::new(
+            OperatorNode::with_schema(
+                asap_types::ir::Operator::ASAP(ASAPOp::SummaryEstimate {
+                    summary_input: agg,
+                    query,
+                }),
+                evaluation_schema,
+            )
+            .with_guarantee(guarantee),
+        )),
         None => Ok(agg),
     }
 }
 
-// Heap readout rows contain the encoded item identity, subpopulation keys,
+// Heap evaluation rows contain the encoded item identity, subpopulation keys,
 // and an estimated score. They never inherit the exact-value producer's schema.
-fn keyed_heap_readout_schema(
+fn keyed_heap_evaluation_schema(
     input: &PhysicalSummaryInput,
-    node: &QueryExpr,
+    node: &OperatorNode,
 ) -> Result<Schema, RealizationError> {
-    let source = input.child.output_schema()?;
+    let source = &input.child.schema;
     let mut refs = Vec::new();
-    let QueryExpr::Aggregate {
+    let Some(NonASAPOp::Aggregate {
         reduction, child, ..
-    } = node
+    }) = node.non_asap()
     else {
         return Err(RealizationError::PhysicalRealization(
-            "heap readout requires an aggregate",
+            "heap evaluation requires an aggregate",
         ));
     };
     if let Reduction::Reduce(groups) = reduction {
         if groups.is_without() {
             return Err(RealizationError::PhysicalRealization(
-                "heap readout requires explicit grouping",
+                "heap evaluation requires explicit grouping",
             ));
         }
         for index in groups.iter() {
@@ -3161,7 +3322,7 @@ fn keyed_heap_readout_schema(
             .ok_or(RealizationError::PhysicalRealization(
                 "heap item identity is missing",
             ))?,
-        &source,
+        source,
         &mut refs,
     )?;
     let mut fields = Vec::<asap_types::post_asap::Field>::new();
@@ -3197,7 +3358,7 @@ fn keyed_heap_readout_schema(
     }
     if fields.is_empty() {
         return Err(RealizationError::PhysicalRealization(
-            "heap readout has no identity columns",
+            "heap evaluation has no identity columns",
         ));
     }
     fields.push(Field::new(
@@ -3208,7 +3369,7 @@ fn keyed_heap_readout_schema(
     Ok(Schema::lifted(fields, None))
 }
 
-fn ranking_score_index(logical: &QueryExpr, values: &Schema) -> Result<usize, RealizationError> {
+fn ranking_score_index(logical: &OperatorNode, values: &Schema) -> Result<usize, RealizationError> {
     if is_current_series_source(logical) {
         return values
             .fields
@@ -3221,11 +3382,11 @@ fn ranking_score_index(logical: &QueryExpr, values: &Schema) -> Result<usize, Re
                 "snapshot ranking requires the sample value column",
             ));
     }
-    let QueryExpr::Aggregate {
+    let Some(NonASAPOp::Aggregate {
         reduction,
         measures,
         ..
-    } = logical
+    }) = logical.non_asap()
     else {
         return Err(RealizationError::PhysicalRealization(
             "ranking requires an explicit aggregate score",
@@ -3274,19 +3435,15 @@ fn realize_counter_value_summary_input(
     intent: &AggIntent,
     family: &FieldDataType,
     output_reduction: &Reduction,
-    child: &Rc<QueryExpr>,
+    child: &Rc<OperatorNode>,
 ) -> PhysicalSummaryInputRuleResult {
     if !matches!(intent, AggIntent::TopK { .. })
         || !matches!(family, FieldDataType::Sketch(kind, _) if matches!(kind.algorithm(), SketchAlgorithm::CmsWithHeap | SketchAlgorithm::CountSketchWithHeap))
-        || !matches!(child.as_ref(), QueryExpr::Aggregate { reduction: Reduction::PerEntity, measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate | AggIntent::Increase]))
+        || !matches!(child.non_asap(), Some(NonASAPOp::Aggregate { reduction: Reduction::PerEntity, measures, .. }) if matches!(measures.as_slice(), [AggIntent::Rate | AggIntent::Increase]))
     {
         return PhysicalSummaryInputRuleResult::NotApplicable;
     }
-    let Ok(schema) = child.output_schema() else {
-        return PhysicalSummaryInputRuleResult::Unsupported(
-            "counter ranking needs a valid value schema",
-        );
-    };
+    let schema = &child.schema;
     if !schema.closed {
         return PhysicalSummaryInputRuleResult::Unsupported(
             "counter ranking needs the complete resolved series identity",
@@ -3332,7 +3489,7 @@ fn realize_current_series_summary_input(
     intent: &AggIntent,
     family: &FieldDataType,
     output_reduction: &Reduction,
-    child: &Rc<QueryExpr>,
+    child: &Rc<OperatorNode>,
 ) -> PhysicalSummaryInputRuleResult {
     if !matches!(intent, AggIntent::TopK { .. }) || !is_current_series_source(child) {
         return PhysicalSummaryInputRuleResult::NotApplicable;
@@ -3359,11 +3516,7 @@ fn realize_current_series_summary_input(
             "snapshot ranking requires resolved partitions",
         );
     }
-    let Ok(schema) = child.output_schema() else {
-        return PhysicalSummaryInputRuleResult::Unsupported(
-            "snapshot ranking requires a valid source schema",
-        );
-    };
+    let schema = &child.schema;
     let items = schema
         .fields
         .iter()
@@ -3393,7 +3546,7 @@ fn realize_keyed_additive_summary_input(
     intent: &AggIntent,
     family: &FieldDataType,
     output_reduction: &Reduction,
-    child: &Rc<QueryExpr>,
+    child: &Rc<OperatorNode>,
 ) -> PhysicalSummaryInputRuleResult {
     if !matches!(intent, AggIntent::TopK { .. }) {
         return PhysicalSummaryInputRuleResult::NotApplicable;
@@ -3408,18 +3561,18 @@ fn realize_keyed_additive_summary_input(
     ) {
         return PhysicalSummaryInputRuleResult::NotApplicable;
     }
-    let QueryExpr::Aggregate {
+    let Some(NonASAPOp::Aggregate {
         reduction,
         measures,
         having: None,
         child: raw_child,
         ..
-    } = child.as_ref()
+    }) = child.non_asap()
     else {
         return PhysicalSummaryInputRuleResult::NotApplicable;
     };
     let counter_input = matches!(measures.as_slice(), [AggIntent::Sum { .. }])
-        && matches!(raw_child.as_ref(), QueryExpr::Aggregate { measures, .. }
+        && matches!(raw_child.non_asap(), Some(NonASAPOp::Aggregate { measures, .. })
             if matches!(measures.as_slice(), [AggIntent::Rate | AggIntent::Increase]));
     let weight = match measures.as_slice() {
         [AggIntent::Count { .. }] => SummaryInputExpr::Constant(1.0),
@@ -3511,9 +3664,8 @@ fn realize_keyed_additive_summary_input(
     })
 }
 
-fn schema_column_ref(child: &QueryExpr, index: usize) -> Option<ColumnRef> {
-    let schema = child.output_schema().ok()?;
-    let column = schema.fields.get(index)?;
+fn schema_column_ref(child: &OperatorNode, index: usize) -> Option<ColumnRef> {
+    let column = child.schema.fields.get(index)?;
     Some(match &column.table {
         Some(table) => ColumnRef::Qualified {
             table: table.clone(),
@@ -3535,7 +3687,7 @@ fn schema_column_ref(child: &QueryExpr, index: usize) -> Option<ColumnRef> {
 fn compose_guarantee(
     family: &FieldDataType,
     query: Option<&PostAsapSketchStatistic>,
-    child: &SummaryNode,
+    child: &OperatorNode,
     intent: &AggIntent,
     accuracy: &dyn AccuracyModel,
     evidence: &dyn AccuracyEvidenceProvider,
@@ -3685,8 +3837,8 @@ fn summarised_input(
     ))
 }
 
-/// The `SummaryEstimate` readout for a summary-bound intent.
-fn readout(
+/// The `SummaryEstimate` evaluation for a summary-bound intent.
+fn evaluation(
     intent: &AggIntent,
     input: &SummaryUpdate,
     cost_model: &dyn CostModel,
@@ -3706,13 +3858,15 @@ fn readout(
             value: None,
         },
         // Core doesn't know the shape of a deployment-specific `Extension`
-        // intent, so it can't build its readout either — delegate to the
+        // intent, so it can't build its evaluation either — delegate to the
         // same `CostModel` that decided (via `realize_extension`) this
-        // intent gets a summary realization at all. See `readout_extension`'s
+        // intent gets a summary realization at all. See `evaluation_extension`'s
         // doc for the invariant this depends on.
         AggIntent::Extension { ext_kind, payload } => match &input.weight {
-            SummaryInputExpr::Column(col) => cost_model.readout_extension(ext_kind, payload, col),
-            _ => unreachable!("extension readout requires one column"),
+            SummaryInputExpr::Column(col) => {
+                cost_model.evaluation_extension(ext_kind, payload, col)
+            }
+            _ => unreachable!("extension evaluation requires one column"),
         },
         other => {
             unreachable!("no summary realization for {other:?} (realizations_for_intent)")
@@ -3720,16 +3874,9 @@ fn readout(
     }
 }
 
-/// Lift a pre-ASAP [`Schema`] to a [`Schema`] with every column
-/// `FieldDataType::Plain` — shared by [`construct_summary_agg`] and
-/// [`keep_pre_asap`], both in this module.
-fn lift(schema: &Schema) -> Schema {
-    Schema::lifted(schema.fields.clone(), schema.time_index)
-}
-
 // ── SharedSubDAGStrategy ────────────────────────────────────────────────
 
-/// Wraps `asap_types::pre_asap::cse::share_common_sub_dags`'s sharing
+/// Wraps `asap_types::ir::cse::share_common_sub_dags`'s sharing
 /// decision as an explicit candidate pair, wherever a [`TargetSubDAG`]
 /// already has two or more consumers.
 ///
@@ -3762,11 +3909,11 @@ impl ReplacementStrategy for SharedSubDAGStrategy {
                 strategy: "SharedSubDAGStrategy",
                 // The already-interned `Rc` itself: reusing it verbatim *is*
                 // "build once and share" — no new node to construct.
-                replacement: Replacement::Rewrite(Rc::clone(target.root)),
+                replacement: Replacement::SubDAG(Rc::clone(target.root)),
                 provenance: ReplacementProvenance::CseShare,
                 rationale: format!(
                     "build once and share: share_common_sub_dags already interned this \
-                     sub-DAG once and reused it across {count} consumers — one build can \
+                     sub_dag once and reused it across {count} consumers — one build can \
                      answer all of them instead of computing it {count} times"
                 ),
             },
@@ -3775,11 +3922,11 @@ impl ReplacementStrategy for SharedSubDAGStrategy {
                 // A structurally-identical but freshly-allocated `Rc`: same
                 // value (`PartialEq`), deliberately *not* the same pointer,
                 // representing "undo the sharing and recompute independently".
-                replacement: Replacement::Rewrite(Rc::new((**target.root).clone())),
+                replacement: Replacement::SubDAG(Rc::new((**target.root).clone())),
                 provenance: ReplacementProvenance::CseRecompute,
                 rationale: format!(
                     "build independently: undo the sharing share_common_sub_dags found and \
-                     recompute this sub-DAG separately at each of its {count} consumers — \
+                     recompute this sub_dag separately at each of its {count} consumers — \
                      worth it only when independence outweighs the shared-maintenance cost, \
                      a CostModel's call (e.g. CostModel::cse_share_decision) and not this \
                      strategy's"
@@ -3798,14 +3945,14 @@ impl ReplacementStrategy for SharedSubDAGStrategy {
 /// A generous, documented backstop against a hypothetically ill-behaved
 /// future [`ReplacementStrategy`] (see the module docs' "Termination"
 /// section) — not a bound either shipped strategy could ever approach.
-/// [`SketchAlgorithmStrategy`] and [`SharedSubDAGStrategy`] both converge in
+/// [`ASAPStrategies`] and [`SharedSubDAGStrategy`] both converge in
 /// exactly 2 passes over a fixed target set, regardless of workload size.
 pub const MAX_SEARCH_ITERATIONS: usize = 1_000;
 
 // ── TargetSubDAGCandidates ──────────────────────────────────────────────
 
 /// Candidates for one distinct [`TargetSubDAG`] (its
-/// own `target` `Rc<QueryExpr>`, keyed by pointer identity in
+/// own `target` `Rc<OperatorNode>`, keyed by pointer identity in
 /// [`CandidateLogicalASAPDAGs`]'s internal map — never re-derived by value) plus every
 /// [`ReplacementSubDAG`] alternative any registered [`ReplacementStrategy`]
 /// proposed for it.
@@ -3818,7 +3965,7 @@ pub const MAX_SEARCH_ITERATIONS: usize = 1_000;
 #[derive(Debug, Clone)]
 pub struct TargetSubDAGCandidates {
     /// The target sub-DAG this group is for.
-    pub target: Rc<QueryExpr>,
+    pub target: Rc<OperatorNode>,
     /// How many operator-child positions across the whole workload
     /// reference this exact `Rc` — see [`discover_targets`].
     pub consumer_count: usize,
@@ -3835,7 +3982,7 @@ pub struct TargetSubDAGCandidates {
 }
 
 impl TargetSubDAGCandidates {
-    fn new(target: Rc<QueryExpr>, consumer_count: usize) -> Self {
+    fn new(target: Rc<OperatorNode>, consumer_count: usize) -> Self {
         Self {
             target,
             consumer_count,
@@ -3852,10 +3999,12 @@ impl TargetSubDAGCandidates {
     fn add_candidate(&mut self, candidate: ReplacementSubDAG) -> bool {
         let is_duplicate = self.candidates.iter().any(|existing| {
             match (&existing.replacement, &candidate.replacement) {
-                (Replacement::Rewrite(existing_rc), Replacement::Rewrite(rc)) => {
+                (Replacement::SubDAG(existing_rc), Replacement::SubDAG(rc))
+                    if is_logical_rewrite(existing_rc) && is_logical_rewrite(rc) =>
+                {
                     is_duplicate_rewrite(existing_rc, rc, &self.target)
                 }
-                (Replacement::Summary(existing_node), Replacement::Summary(node)) => {
+                (Replacement::SubDAG(existing_node), Replacement::SubDAG(node)) => {
                     is_duplicate_summary(existing_node, node)
                 }
                 (
@@ -3876,11 +4025,11 @@ impl TargetSubDAGCandidates {
     }
 }
 
-/// Are `existing` and `candidate` the same [`Replacement::Rewrite`]
-/// candidate for a group targeting `target`?
+/// Are `existing` and `candidate` the same logical-rewrite
+/// [`Replacement::SubDAG`] candidate for a group targeting `target`?
 ///
-/// Structural (`QueryExpr`) value equality alone is *not* enough here: this
-/// module's one shipped multi-candidate `Replacement::Rewrite` source,
+/// Structural (`OperatorNode`) value equality alone is *not* enough here:
+/// this module's one shipped multi-candidate logical-rewrite source,
 /// [`SharedSubDAGStrategy`], deliberately returns **two** candidates that
 /// are value-equal to each other (`build once and share` vs. `build
 /// independently` — see that strategy's own doc) but represent genuinely
@@ -3898,7 +4047,7 @@ impl TargetSubDAGCandidates {
 /// So: two candidates whose "is this the target's own `Rc`?" bit disagrees
 /// are never duplicates of each other, full stop. Only when that bit
 /// *agrees* does this fall through to the real dedup discipline —
-/// [`structural_hash`] as a candidate-narrowing filter, `QueryExpr`'s
+/// [`structural_hash`] as a candidate-narrowing filter, `OperatorNode`'s
 /// derived `PartialEq` as the actual decision — protecting against the
 /// (currently hypothetical, since neither shipped strategy causes it)
 /// case of the exact same alternative being proposed twice. A fresh
@@ -3907,9 +4056,9 @@ impl TargetSubDAGCandidates {
 /// wider traversal to amortize the cache across the way `InternTable`'s own
 /// use of `structural_hash` does.
 fn is_duplicate_rewrite(
-    existing: &Rc<QueryExpr>,
-    candidate: &Rc<QueryExpr>,
-    target: &Rc<QueryExpr>,
+    existing: &Rc<OperatorNode>,
+    candidate: &Rc<OperatorNode>,
+    target: &Rc<OperatorNode>,
 ) -> bool {
     let existing_is_target = Rc::ptr_eq(existing, target);
     let candidate_is_target = Rc::ptr_eq(candidate, target);
@@ -3921,16 +4070,16 @@ fn is_duplicate_rewrite(
         && existing == candidate
 }
 
-/// Are `existing` and `candidate` the same [`Replacement::Summary`]
-/// candidate?
+/// Are `existing` and `candidate` the same bound-summary
+/// [`Replacement::SubDAG`] candidate?
 ///
-/// [`SummaryNode`] derives neither `PartialEq` nor `Hash` (it embeds
-/// `SketchParams`/`f64`-bearing accuracy targets deep inside `SummaryExpr`,
-/// the same reason `QueryExpr` can't derive `Hash` either — see
-/// [`structural_hash`]'s own doc). Per this module's inherited "hash is a
-/// filter, `PartialEq` is the decision, no exceptions" rule, there is no
-/// real equality check to back a dedup *decision* here — and skipping the
-/// check is the only choice that rule permits: never merging two candidates
+/// A bound summary embeds `SketchParams`/`f64`-bearing accuracy targets and
+/// guarantees, so value equality is not a dedup decision this module is
+/// willing to make (see [`structural_hash`]'s own doc on `f64` hashing).
+/// Per this module's inherited "hash is a filter, `PartialEq` is the
+/// decision, no exceptions" rule, there is no real equality check to back a
+/// dedup *decision* here — and skipping the check is the only choice that
+/// rule permits: never merging two candidates
 /// is harmless (at worst, a redundant entry in a group's candidate list),
 /// while comparing by some proxy this module can't actually verify (e.g.
 /// `Debug` text, or `ReplacementSubDAG::rationale` — documented elsewhere in
@@ -3939,7 +4088,7 @@ fn is_duplicate_rewrite(
 /// shipped today already return a structurally distinct candidate for every
 /// entry of one `replacements()` call, so this is future-proofing against a
 /// hypothetical repeat call, not a gap either strategy's own tests exercise.
-fn is_duplicate_summary(_existing: &Rc<SummaryNode>, _candidate: &Rc<SummaryNode>) -> bool {
+fn is_duplicate_summary(_existing: &Rc<OperatorNode>, _candidate: &Rc<OperatorNode>) -> bool {
     false
 }
 
@@ -3948,34 +4097,34 @@ fn is_duplicate_summary(_existing: &Rc<SummaryNode>, _candidate: &Rc<SummaryNode
 /// The deduped candidate space [`search_workload`]/[`search_workload_with`]
 /// discover: one [`TargetSubDAGCandidates`] per distinct `TargetSubDAG` in the
 /// (already-CSE'd) workload, plus the workload's own post-CSE roots so a
-/// caller can still map a `Root`'s `Id` back to the `Rc<QueryExpr>` whose
-/// group holds its alternatives.
+/// caller can still map a `Root`'s `Id` back to the `Rc<OperatorNode>` whose
+/// group holds its alternatives. Memos are keyed by `*const OperatorNode`.
 pub struct CandidateLogicalASAPDAGs<Id> {
     /// The workload's roots, after the one `share_common_sub_dags` pass
     /// [`search_workload_with`] runs up front — the same post-CSE roots
     /// every `TargetSubDAG` in `groups` was discovered from.
-    pub roots: Vec<(Id, Rc<QueryExpr>)>,
-    groups: HashMap<*const QueryExpr, TargetSubDAGCandidates>,
+    pub roots: Vec<(Id, Rc<OperatorNode>)>,
+    groups: HashMap<*const OperatorNode, TargetSubDAGCandidates>,
     /// Discovery order — stable iteration for [`CandidateLogicalASAPDAGs::target_subdag_candidates`]/
     /// [`CandidateLogicalASAPDAGs::cost_sorted`], since `HashMap` iteration order isn't.
-    order: Vec<*const QueryExpr>,
+    order: Vec<*const OperatorNode>,
     /// Composition proofs are computed with the search model, then retained
     /// through costing and DAG assembly so no later default can replace it.
     composition_plans: Vec<PreparedComposition>,
 }
 
 struct PreparedComposition {
-    target: *const QueryExpr,
+    target: *const OperatorNode,
     operation: ExactComposition,
-    child: Rc<SummaryNode>,
-    plan: Rc<SummaryNode>,
+    child: Rc<OperatorNode>,
+    plan: Rc<OperatorNode>,
 }
 
 impl<Id> CandidateLogicalASAPDAGs<Id> {
     fn prepare_compositions(
         &mut self,
         accuracy: &dyn AccuracyModel,
-        targets: &HashMap<*const QueryExpr, Vec<AccuracyTarget>>,
+        targets: &HashMap<*const OperatorNode, Vec<AccuracyTarget>>,
     ) {
         self.composition_plans.clear();
         for group in self.groups.values() {
@@ -3990,14 +4139,16 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
                         .into_iter()
                         .flat_map(|g| &g.candidates)
                         .filter_map(|c| match &c.replacement {
-                            Replacement::Summary(child) if operation.accepts_child(child) => {
+                            Replacement::SubDAG(child)
+                                if !is_logical_rewrite(child) && operation.accepts_child(child) =>
+                            {
                                 Some(Rc::clone(child))
                             }
                             _ => None,
                         })
                         .collect(),
                     OperationPlacement::Maintenance => {
-                        keep_pre_asap(&operation.child_target).into_iter().collect()
+                        retain_exact(&operation.child_target).into_iter().collect()
                     }
                 };
                 for child in children {
@@ -4035,11 +4186,11 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
 /// never a silently truncated inventory presented as exhaustive.
 #[derive(Debug)]
 pub struct CandidateDAGInventory<Id> {
-    pub candidates: Vec<Vec<(Id, Rc<SummaryNode>)>>,
+    pub candidates: Vec<Vec<(Id, Rc<OperatorNode>)>>,
     pub rejected_assemblies: Vec<String>,
 }
 
-type CandidateDAGChoice<'a> = (Option<&'a ReplacementSubDAG>, Option<Rc<SummaryNode>>);
+type CandidateDAGChoice<'a> = (Option<&'a ReplacementSubDAG>, Option<Rc<OperatorNode>>);
 
 impl<Id: Clone + PartialEq> CandidateLogicalASAPDAGs<Id> {
     pub fn enumerate_candidate_dags(
@@ -4074,7 +4225,7 @@ impl<Id: Clone + PartialEq> CandidateLogicalASAPDAGs<Id> {
 
     fn enumerate_candidate_roots(
         &self,
-        roots: &[(Id, Rc<QueryExpr>)],
+        roots: &[(Id, Rc<OperatorNode>)],
         expansion_limit: usize,
     ) -> Result<CandidateDAGInventory<Id>, RealizationError> {
         let mut reachable = Vec::new();
@@ -4090,8 +4241,10 @@ impl<Id: Clone + PartialEq> CandidateLogicalASAPDAGs<Id> {
             cursor += 1;
             if let Some(group) = self.groups.get(&ptr) {
                 for candidate in &group.candidates {
-                    if let Replacement::Rewrite(rewritten) = &candidate.replacement {
-                        walk(rewritten, &mut reachable, &mut nodes, &mut counts);
+                    if let Replacement::SubDAG(rewritten) = &candidate.replacement {
+                        if is_logical_rewrite(rewritten) {
+                            walk(rewritten, &mut reachable, &mut nodes, &mut counts);
+                        }
                     }
                 }
             }
@@ -4185,77 +4338,12 @@ impl<Id: Clone + PartialEq> CandidateLogicalASAPDAGs<Id> {
                 .collect::<Result<Vec<_>, _>>();
             match roots {
                 Ok(roots) => {
-                    let roots = asap_types::post_asap::share_common_summary_sub_dags(roots);
+                    let roots = share_common_sub_dags(roots);
                     use std::hash::{Hash, Hasher};
                     let mut hash = std::collections::hash_map::DefaultHasher::new();
-                    let mut pending = roots
-                        .iter()
-                        .map(|(_, node)| node.as_ref())
-                        .collect::<Vec<_>>();
-                    while let Some(node) = pending.pop() {
-                        std::mem::discriminant(&node.expr).hash(&mut hash);
-                        let raw = match &node.expr {
-                            SummaryExpr::KeepPreAsap(raw) => Some(raw.as_ref()),
-                            _ => None,
-                        };
-                        let operation = match &node.expr {
-                            SummaryExpr::ValueOperation {
-                                timing, operation, ..
-                            } => serde_json::json!((timing, operation)),
-                            SummaryExpr::BinaryOp {
-                                timing, operator, ..
-                            } => serde_json::json!((timing, operator)),
-                            SummaryExpr::SummaryMerge { timing, .. } => serde_json::json!(timing),
-                            _ => serde_json::Value::Null,
-                        };
-                        let mut value =
-                            serde_json::to_value((&node.schema, &node.guarantee, raw, operation))
-                                .map_err(|_| {
-                                RealizationError::PhysicalRealization(
-                                    "candidate identity serialization failed",
-                                )
-                            })?;
-                        fn normalize(value: &mut serde_json::Value) {
-                            match value {
-                                serde_json::Value::Number(number)
-                                    if number.as_f64() == Some(0.0) =>
-                                {
-                                    *value = serde_json::json!(0);
-                                }
-                                serde_json::Value::Array(values) => {
-                                    values.iter_mut().for_each(normalize)
-                                }
-                                serde_json::Value::Object(values) => {
-                                    values.values_mut().for_each(normalize)
-                                }
-                                _ => {}
-                            }
-                        }
-                        normalize(&mut value);
-                        value.sort_all_objects();
-                        value.to_string().hash(&mut hash);
-                        match &node.expr {
-                            SummaryExpr::KeepPreAsap(_) => {}
-                            SummaryExpr::BinaryOp { lhs, rhs, .. } => {
-                                pending.extend([lhs.as_ref(), rhs.as_ref()])
-                            }
-                            SummaryExpr::RelationalJoin { left, right, .. }
-                            | SummaryExpr::SummarySubtract { left, right } => {
-                                pending.extend([left.as_ref(), right.as_ref()])
-                            }
-                            SummaryExpr::ValueOperation { child, .. }
-                            | SummaryExpr::SummaryAgg { child, .. } => pending.push(child.as_ref()),
-                            SummaryExpr::SummaryJoin { outer, inner, .. } => {
-                                pending.extend([outer.as_ref(), inner.as_ref()])
-                            }
-                            SummaryExpr::SummaryDelete { summary_input, .. }
-                            | SummaryExpr::SummaryEstimate { summary_input, .. } => {
-                                pending.push(summary_input.as_ref())
-                            }
-                            SummaryExpr::SummaryMerge { children, .. } => {
-                                pending.extend(children.iter().map(|child| child.as_ref()))
-                            }
-                        }
+                    let mut cache = HashCache::new();
+                    for (_, node) in &roots {
+                        structural_hash(node, &mut cache).hash(&mut hash);
                     }
                     let bucket = seen.entry(hash.finish()).or_default();
                     if !bucket
@@ -4281,25 +4369,25 @@ impl<Id: Clone + PartialEq> CandidateLogicalASAPDAGs<Id> {
 /// Lifecycle-aware whole-subplan costs keyed by target and candidate identity.
 #[derive(Default, Clone)]
 pub(crate) struct CandidateCostOverrides {
-    costs: HashMap<(*const QueryExpr, *const ReplacementSubDAG), Cost>,
-    raw_costs: HashMap<*const QueryExpr, Cost>,
+    costs: HashMap<(*const OperatorNode, *const ReplacementSubDAG), Cost>,
+    raw_costs: HashMap<*const OperatorNode, Cost>,
     /// Targets for which the caller requested an atomic raw-vs-summary
     /// decision. Other memo groups continue through ordinary CSE selection.
-    finalized_targets: HashSet<*const QueryExpr>,
+    finalized_targets: HashSet<*const OperatorNode>,
 }
 
 impl CandidateCostOverrides {
-    pub(crate) fn finalize_target(&mut self, target: &Rc<QueryExpr>) {
+    pub(crate) fn finalize_target(&mut self, target: &Rc<OperatorNode>) {
         self.finalized_targets.insert(Rc::as_ptr(target));
     }
 
-    fn finalizes(&self, target: &Rc<QueryExpr>) -> bool {
+    fn finalizes(&self, target: &Rc<OperatorNode>) -> bool {
         self.finalized_targets.contains(&Rc::as_ptr(target))
     }
 
     pub(crate) fn insert(
         &mut self,
-        target: &Rc<QueryExpr>,
+        target: &Rc<OperatorNode>,
         candidate: &ReplacementSubDAG,
         cost: Cost,
     ) {
@@ -4307,17 +4395,17 @@ impl CandidateCostOverrides {
             .insert((Rc::as_ptr(target), candidate as *const _), cost);
     }
 
-    fn get(&self, target: &Rc<QueryExpr>, candidate: &ReplacementSubDAG) -> Option<Cost> {
+    fn get(&self, target: &Rc<OperatorNode>, candidate: &ReplacementSubDAG) -> Option<Cost> {
         self.costs
             .get(&(Rc::as_ptr(target), candidate as *const _))
             .copied()
     }
 
-    pub(crate) fn insert_raw(&mut self, target: &Rc<QueryExpr>, cost: Cost) {
+    pub(crate) fn insert_raw(&mut self, target: &Rc<OperatorNode>, cost: Cost) {
         self.raw_costs.insert(Rc::as_ptr(target), cost);
     }
 
-    fn raw(&self, target: &Rc<QueryExpr>) -> Option<Cost> {
+    fn raw(&self, target: &Rc<OperatorNode>) -> Option<Cost> {
         self.raw_costs.get(&Rc::as_ptr(target)).copied()
     }
 }
@@ -4334,7 +4422,7 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
     }
 
     /// Whether no targets were discovered at all (an empty workload, or one
-    /// with no `QueryExpr` nodes reachable from any root — never true for a
+    /// with no `OperatorNode`s reachable from any root — never true for a
     /// non-empty `roots`, since every root is itself a target).
     pub fn is_empty(&self) -> bool {
         self.groups.is_empty()
@@ -4343,7 +4431,10 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
     /// The candidate set for `target`, if `target`'s own `Rc` is a discovered
     /// `TargetSubDAG` (i.e. `Rc::ptr_eq` to some node reachable from
     /// `roots`).
-    pub fn candidates_for_target(&self, target: &Rc<QueryExpr>) -> Option<&TargetSubDAGCandidates> {
+    pub fn candidates_for_target(
+        &self,
+        target: &Rc<OperatorNode>,
+    ) -> Option<&TargetSubDAGCandidates> {
         self.groups.get(&Rc::as_ptr(target))
     }
 
@@ -4465,17 +4556,17 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
 /// half of issue #287. Looked up by `Rc` pointer identity, the same
 /// currency [`CandidateLogicalASAPDAGs::candidates_for_target`]/[`GlobalSelection::for_target`] already
 /// use.
-/// Holds an owned `Rc<QueryExpr>` clone alongside each profile (not just its
-/// raw pointer) so this map keeps every node it describes alive for as long
-/// as the map itself lives — a `RecurrenceProfileMap` is safe to outlive the
-/// `CandidateLogicalASAPDAGs` it was built from. Without this, a raw `*const QueryExpr` key
+/// Holds an owned `Rc<OperatorNode>` clone alongside each profile (not just
+/// its raw pointer) so this map keeps every node it describes alive for as
+/// long as the map itself lives — a `RecurrenceProfileMap` is safe to outlive
+/// the `CandidateLogicalASAPDAGs` it was built from. Without this, a raw `*const OperatorNode` key
 /// could, after the originating `CandidateLogicalASAPDAGs` (the only other owner of those
 /// `Rc`s) is dropped, collide with an unrelated, later allocation that
 /// happens to reuse the same freed address — silently returning a stale
 /// profile for the wrong node (issue #287 review, bug 4).
 #[derive(Debug, Clone)]
 pub struct RecurrenceProfileMap {
-    profiles: HashMap<*const QueryExpr, (Rc<QueryExpr>, RecurrenceProfile)>,
+    profiles: HashMap<*const OperatorNode, (Rc<OperatorNode>, RecurrenceProfile)>,
 }
 
 impl RecurrenceProfileMap {
@@ -4484,7 +4575,7 @@ impl RecurrenceProfileMap {
     /// in the [`CandidateLogicalASAPDAGs`] this map was built from (or carried no
     /// recurring/one-shot/update-rate metadata at all) — always a valid,
     /// "no metadata" answer, never a panic.
-    pub fn for_target(&self, target: &Rc<QueryExpr>) -> RecurrenceProfile {
+    pub fn for_target(&self, target: &Rc<OperatorNode>) -> RecurrenceProfile {
         self.profiles
             .get(&Rc::as_ptr(target))
             .map(|(_, profile)| *profile)
@@ -4504,7 +4595,7 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
     /// `self.roots[i]` — the same order [`search_workload`]/
     /// [`search_workload_with`] were originally called with (post-CSE
     /// dedup preserves both root count and order — see
-    /// `asap_types::pre_asap::cse::share_common_sub_dags`'s own
+    /// `asap_types::ir::cse::share_common_sub_dags`'s own
     /// `.map(...).collect()` body). This keeps `Id` fully opaque (no `Eq`/
     /// `Hash`/`Clone` bound needed on it at all — issue #287's "keep
     /// caller/query identifiers opaque" requirement) at the cost of the
@@ -4581,12 +4672,12 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
             }
         }
 
-        let mut rates: HashMap<*const QueryExpr, f64> = HashMap::new();
-        let mut one_shot_counts: HashMap<*const QueryExpr, usize> = HashMap::new();
+        let mut rates: HashMap<*const OperatorNode, f64> = HashMap::new();
+        let mut one_shot_counts: HashMap<*const OperatorNode, usize> = HashMap::new();
         // Sites actually reached by at least one root's own recurrence tag
         // during the walk below — see this method's own "Unreachable
         // sites" doc.
-        let mut reached: HashSet<*const QueryExpr> = HashSet::new();
+        let mut reached: HashSet<*const OperatorNode> = HashSet::new();
 
         for ((_, root), recurrence) in self.roots.iter().zip(root_recurrence) {
             let recurrence = *recurrence;
@@ -4596,7 +4687,7 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
             // recomputed occurrence is evaluated twice as well; stopping
             // expansion after the first pointer visit undercounts exactly
             // the effective-consumer rate recurrence-aware costing needs.
-            let mut queue: VecDeque<(*const QueryExpr, usize)> = VecDeque::new();
+            let mut queue: VecDeque<(*const OperatorNode, usize)> = VecDeque::new();
             queue.push_back((root_ptr, 1));
 
             while let Some((ptr, path_count)) = queue.pop_front() {
@@ -4740,7 +4831,7 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
         &self,
         workload: &QueryWorkload,
         root_workload_entries: &[usize],
-    ) -> Result<HashMap<*const QueryExpr, Vec<usize>>, RecurrenceError> {
+    ) -> Result<HashMap<*const OperatorNode, Vec<usize>>, RecurrenceError> {
         let entry_count = workload.entries().count();
         if root_workload_entries.len() != self.roots.len() {
             return Err(RecurrenceError::RootCountMismatch {
@@ -4748,7 +4839,7 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
                 got: root_workload_entries.len(),
             });
         }
-        let mut bindings: HashMap<*const QueryExpr, HashSet<usize>> = HashMap::new();
+        let mut bindings: HashMap<*const OperatorNode, HashSet<usize>> = HashMap::new();
         for ((_, root), &entry_index) in self.roots.iter().zip(root_workload_entries) {
             if entry_index >= entry_count {
                 return Err(RecurrenceError::InvalidWorkloadEntry {
@@ -4790,12 +4881,12 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
 /// child always has `edge_count >= 1` in practice, but this keeps the
 /// helper correct regardless).
 fn contribute(
-    ptr: *const QueryExpr,
+    ptr: *const OperatorNode,
     times: usize,
     recurrence: RootRecurrence,
-    rates: &mut HashMap<*const QueryExpr, f64>,
-    one_shot_counts: &mut HashMap<*const QueryExpr, usize>,
-    reached: &mut HashSet<*const QueryExpr>,
+    rates: &mut HashMap<*const OperatorNode, f64>,
+    one_shot_counts: &mut HashMap<*const OperatorNode, usize>,
+    reached: &mut HashSet<*const OperatorNode>,
 ) {
     if times == 0 {
         return;
@@ -4816,7 +4907,7 @@ fn contribute(
 /// [`CandidateLogicalASAPDAGs::cost_sorted`].
 #[derive(Debug)]
 pub struct RankedTargetSubDAGCandidates<'a> {
-    pub target: &'a Rc<QueryExpr>,
+    pub target: &'a Rc<OperatorNode>,
     pub consumer_count: usize,
     pub candidates: Vec<&'a ReplacementSubDAG>,
     /// `costs[i]` is `candidates[i]`'s own grouping-state cost when available,
@@ -4864,7 +4955,7 @@ fn rank_group<'a>(
     // estimate, compare N independent states with the shared grid directly.
     let target = TargetSubDAG::with_consumer_count(&group.target, group.consumer_count);
     let has_hydra = ranked.iter().any(|candidate| {
-        let Replacement::Summary(node) = &candidate.replacement else {
+        let Replacement::SubDAG(node) = &candidate.replacement else {
             return false;
         };
         summary_grouping(node).is_some_and(|grouping| {
@@ -4896,7 +4987,7 @@ fn rank_group<'a>(
         return ranked;
     }
 
-    // Shape 3: `SketchAlgorithmStrategy`'s sketch-family candidates (every
+    // Shape 3: `ASAPStrategies`'s sketch-family candidates (every
     // candidate is a `Summary` that realizes a `SketchAlgorithm`) — rank via
     // `CostModel::rank_candidates`, the same hook `realizations_for_intent`
     // itself consults.
@@ -4904,16 +4995,16 @@ fn rank_group<'a>(
         let kinds: Option<Vec<SketchAlgorithm>> = ranked
             .iter()
             .map(|c| match &c.replacement {
-                Replacement::Summary(node) => sketch_kind_of(node),
-                Replacement::Rewrite(_) | Replacement::ExactComposition(_) => None,
+                Replacement::SubDAG(node) => sketch_kind_of(node),
+                Replacement::ExactComposition(_) => None,
             })
             .collect();
         if let Some(kinds) = kinds {
             let order = crate::cost_model::validated_candidate_ranking(cost_model, intent, &kinds);
             ranked.sort_by_key(|c| {
                 let kind = match &c.replacement {
-                    Replacement::Summary(node) => sketch_kind_of(node),
-                    Replacement::Rewrite(_) | Replacement::ExactComposition(_) => None,
+                    Replacement::SubDAG(node) => sketch_kind_of(node),
+                    Replacement::ExactComposition(_) => None,
                 };
                 kind.and_then(|k| order.iter().position(|o| *o == k))
                     .unwrap_or(usize::MAX)
@@ -4970,21 +5061,21 @@ fn cse_preference(group: &TargetSubDAGCandidates, cost_model: &dyn CostModel) ->
     })
 }
 
-/// [`cse_preference`] only needs one representative bound [`SummaryNode`]
+/// [`cse_preference`] only needs one representative bound [`OperatorNode`]
 /// for `target` (to build a [`CseCandidate`] for
 /// [`CostModel::cse_share_decision`]), not the full ranked candidate list
-/// [`SketchAlgorithmStrategy::replacements`] returns — so this just reuses
+/// [`ASAPStrategies::replacements`] returns — so this just reuses
 /// [`realize_child`], the same rank-and-take-first helper
 /// `construct_summary_agg`'s own recursion and
 /// [`crate::cost_model::DefaultCostModel::estimate_cost`] already use,
 /// wrapped to swallow the (here, uninteresting) error into `None`.
-fn realize_one(target: &Rc<QueryExpr>, cost_model: &dyn CostModel) -> Option<Rc<SummaryNode>> {
+fn realize_one(target: &Rc<OperatorNode>, cost_model: &dyn CostModel) -> Option<Rc<OperatorNode>> {
     realize_child(target, cost_model).ok()
 }
 
-/// The `SketchAlgorithm` a bound [`Replacement::Summary`] candidate ultimately
+/// The `SketchAlgorithm` a bound [`Replacement::SubDAG`] candidate ultimately
 /// realizes, if any (`None` for an `ExactAggregate`/pass-through
-/// `Summary` — nothing to rank against another `SketchAlgorithm`).
+/// sub-DAG — nothing to rank against another `SketchAlgorithm`).
 ///
 /// Mirrors this module's own `#[cfg(test)]`-only `summary_family_algorithm`
 /// helper (in the test module below), which does the identical
@@ -4993,23 +5084,27 @@ fn realize_one(target: &Rc<QueryExpr>, cost_model: &dyn CostModel) -> Option<Rc<
 /// code — the same "duplicate a small, self-contained traversal rather than
 /// restructure a test helper" call this file's own top doc already makes
 /// for [`discover_targets`].
-fn sketch_kind_of(node: &SummaryNode) -> Option<SketchAlgorithm> {
-    match &node.expr {
-        SummaryExpr::SummaryEstimate { summary_input, .. } => sketch_kind_of(summary_input),
-        SummaryExpr::SummaryAgg {
+fn sketch_kind_of(node: &OperatorNode) -> Option<SketchAlgorithm> {
+    match &node.operator {
+        Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) => {
+            sketch_kind_of(summary_input)
+        }
+        Operator::ASAP(ASAPOp::SummaryAgg {
             family: FieldDataType::Sketch(kind, _),
             ..
-        } => Some(kind.algorithm().clone()),
+        }) => Some(kind.algorithm().clone()),
         _ => None,
     }
 }
 
 /// The grouping strategy used by a bound summary candidate, unwrapping its
-/// readout node when necessary.
-fn summary_grouping(node: &SummaryNode) -> Option<&GroupingStrategy> {
-    match &node.expr {
-        SummaryExpr::SummaryEstimate { summary_input, .. } => summary_grouping(summary_input),
-        SummaryExpr::SummaryAgg { grouping, .. } => Some(grouping),
+/// evaluation node when necessary.
+fn summary_grouping(node: &OperatorNode) -> Option<&GroupingStrategy> {
+    match &node.operator {
+        Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) => {
+            summary_grouping(summary_input)
+        }
+        Operator::ASAP(ASAPOp::SummaryAgg { grouping, .. }) => Some(grouping),
         _ => None,
     }
 }
@@ -5034,7 +5129,7 @@ fn summary_grouping(node: &SummaryNode) -> Option<&GroupingStrategy> {
 #[derive(Debug)]
 pub struct TargetSubDAGSelection<'a> {
     /// The target sub-DAG this selection is for.
-    pub target: &'a Rc<QueryExpr>,
+    pub target: &'a Rc<OperatorNode>,
     /// [`TargetSubDAGCandidates::consumer_count`] — how many operator-child positions
     /// directly reference `target`, ignoring every ancestor's own choice.
     pub consumer_count: usize,
@@ -5065,18 +5160,18 @@ pub struct TargetSubDAGSelection<'a> {
 #[derive(Debug)]
 pub struct CompositionDecision<'a> {
     /// The exact child/operation pair validated by the search accuracy model.
-    pub plan: Rc<SummaryNode>,
+    pub plan: Rc<OperatorNode>,
     /// The child target the composed operator consumes.
-    pub child_target: &'a Rc<QueryExpr>,
+    pub child_target: &'a Rc<OperatorNode>,
     /// For a read-time operation: the child's own candidate committed alongside
-    /// (the summary readout the operator folds). `None` for an update-path
+    /// (the summary evaluation the operator folds). `None` for an update-path
     /// transform, whose input is raw update data — its cost is charged to
     /// the maintained summary *above* it instead.
     pub child_candidate: Option<&'a ReplacementSubDAG>,
     /// The composed plan's recurring rate — `read_operation_plan_cost_rate`
     /// or `maintenance_operation_plan_cost_rate`.
     pub cost_rate: CostRate,
-    /// `raw_recompute_cost_rate` — the `KeepPreAsap` baseline it beat.
+    /// `raw_recompute_cost_rate` — the kept-sub-DAG baseline it beat.
     pub baseline_rate: CostRate,
     /// The statistics (and their provenance) both rates were computed from.
     pub inputs: ExactCompositionCostInputs,
@@ -5087,12 +5182,13 @@ pub struct CompositionDecision<'a> {
 /// [`CandidateLogicalASAPDAGs::cost_sorted`] use.
 #[derive(Debug)]
 pub struct GlobalSelection<'a> {
-    order: Vec<*const QueryExpr>,
-    groups: HashMap<*const QueryExpr, TargetSubDAGSelection<'a>>,
+    order: Vec<*const OperatorNode>,
+    groups: HashMap<*const OperatorNode, TargetSubDAGSelection<'a>>,
     /// [`Self::assemble_selected_dag`]'s memo — one bound node per target for the
     /// life of this selection, so two parents composing over one shared
-    /// child get the *same* `Rc<SummaryNode>`.
-    assembled_nodes: RefCell<HashMap<*const QueryExpr, Rc<SummaryNode>>>,
+    /// child get the *same* `Rc<OperatorNode>` (a kept pre-ASAP sub-DAG
+    /// shared by two parents stays one `Rc` the same way).
+    assembled_nodes: RefCell<HashMap<*const OperatorNode, Rc<OperatorNode>>>,
 }
 
 fn normalize_cross_input_equi_predicate(
@@ -5100,15 +5196,17 @@ fn normalize_cross_input_equi_predicate(
     left_width: usize,
     total_width: usize,
 ) -> Option<Predicate> {
-    let QueryExpr::Compare {
+    let ScalarExpr::Compare {
         left,
         op: asap_types::pre_asap::CompareOpKind::Eq,
         right,
-    } = pred.0.as_ref()
+        semantics,
+    } = &pred.0
     else {
         return None;
     };
-    let (QueryExpr::Column(left_id), QueryExpr::Column(right_id)) = (left.as_ref(), right.as_ref())
+    let (ScalarExpr::Column(left_id), ScalarExpr::Column(right_id)) =
+        (left.as_ref(), right.as_ref())
     else {
         return None;
     };
@@ -5121,20 +5219,12 @@ fn normalize_cross_input_equi_predicate(
     } else {
         return None;
     };
-    Some(Predicate(Rc::new(QueryExpr::Compare {
-        left: Rc::new(QueryExpr::Column(left_id)),
+    Some(Predicate(ScalarExpr::Compare {
+        left: Box::new(ScalarExpr::Column(left_id)),
         op: asap_types::pre_asap::CompareOpKind::Eq,
-        right: Rc::new(QueryExpr::Column(right_id)),
-    })))
-}
-
-fn relational_join_guarantee(
-    left: Option<&ResultGuarantee>,
-    right: Option<&ResultGuarantee>,
-) -> Option<ResultGuarantee> {
-    left.zip(right)
-        .filter(|(left, right)| left.is_exact() && right.is_exact())
-        .map(|_| ResultGuarantee::exact("RelationalJoin over exact inputs"))
+        right: Box::new(ScalarExpr::Column(right_id)),
+        semantics: *semantics,
+    }))
 }
 
 impl<'a> GlobalSelection<'a> {
@@ -5146,47 +5236,52 @@ impl<'a> GlobalSelection<'a> {
     /// The selection for `target`, if `target`'s own `Rc` is a discovered
     /// site (i.e. `Rc::ptr_eq` to some node reachable from the workload's
     /// roots).
-    pub fn for_target(&self, target: &Rc<QueryExpr>) -> Option<&TargetSubDAGSelection<'a>> {
+    pub fn for_target(&self, target: &Rc<OperatorNode>) -> Option<&TargetSubDAGSelection<'a>> {
         self.groups.get(&Rc::as_ptr(target))
     }
 
     /// Link this selection's per-site decisions into one data_state-validated
     /// post-ASAP DAG rooted at `target` — the one place a committed
-    /// composition's child *reference* becomes an actual `Rc<SummaryNode>`
+    /// composition's child *reference* becomes an actual `Rc<OperatorNode>`
     /// edge (issue #171). `None` if `target` is not a discovered site.
     ///
     /// Per site: a [`Replacement::ExactComposition`] uses its validated
     /// operation/child plan, retaining the search model's guarantee;
-    /// a [`Replacement::Summary`] is
+    /// a bound-summary [`Replacement::SubDAG`] is
     /// re-linked so its `SummaryAgg` child is the child target's own
     /// DAG assembly whenever that is phase-legal beneath maintenance
     /// (so a child that chose an `ValueOperationAtIngestionTime` actually ends up under
-    /// the summary); a [`Replacement::Rewrite`] or an unmatched site stays
-    /// the conservative `KeepPreAsap`. Memoized by target identity, so a
-    /// shared inner summary is one `Rc` no matter how many roots reach it.
+    /// the summary); a logical-rewrite [`Replacement::SubDAG`] is kept
+    /// as it is (exact); an unmatched site keeps its own operator with each
+    /// child assembled independently ([`Self::assemble_residual`]).
+    /// Memoized by target identity, so a shared inner summary is one `Rc`
+    /// no matter how many roots reach it.
     pub fn assemble_selected_dag(
         &self,
-        target: &Rc<QueryExpr>,
-    ) -> Result<Option<Rc<SummaryNode>>, RealizationError> {
+        target: &Rc<OperatorNode>,
+    ) -> Result<Option<Rc<OperatorNode>>, RealizationError> {
         if !self.groups.contains_key(&Rc::as_ptr(target)) {
             return Ok(None);
         }
         self.assemble_target(target).map(Some)
     }
 
-    /// Assemble a complete query result, including an exact-state readout when
+    /// Assemble a complete query result, including an exact-state evaluation when
     /// needed. `assemble_selected_dag` also serves internal state frontiers;
     /// callers exposing query results must use this boundary instead.
     pub fn assemble_selected_query(
         &self,
-        target: &Rc<QueryExpr>,
-    ) -> Result<Option<Rc<SummaryNode>>, RealizationError> {
+        target: &Rc<OperatorNode>,
+    ) -> Result<Option<Rc<OperatorNode>>, RealizationError> {
         self.assemble_selected_dag(target)?
             .map(|node| finalize_query_candidate(node, target))
             .transpose()
     }
 
-    fn assemble_target(&self, target: &Rc<QueryExpr>) -> Result<Rc<SummaryNode>, RealizationError> {
+    fn assemble_target(
+        &self,
+        target: &Rc<OperatorNode>,
+    ) -> Result<Rc<OperatorNode>, RealizationError> {
         let ptr = Rc::as_ptr(target);
         if let Some(node) = self.assembled_nodes.borrow().get(&ptr) {
             return Ok(Rc::clone(node));
@@ -5198,10 +5293,12 @@ impl<'a> GlobalSelection<'a> {
             .groups
             .get(&ptr)
             .and_then(|sel| sel.chosen)
-            .is_some_and(|candidate| matches!(&candidate.replacement,
-                Replacement::Summary(node) if matches!(&node.expr,
-                    SummaryExpr::SummaryAgg { child, .. }
-                    if !matches!(&child.expr, SummaryExpr::KeepPreAsap(raw) if contains_aggregate(raw)))));
+            .is_some_and(|candidate| {
+                matches!(&candidate.replacement,
+                Replacement::SubDAG(node) if matches!(&node.operator,
+                    Operator::ASAP(ASAPOp::SummaryAgg { child, .. })
+                    if child.contains_asap() || !contains_aggregate(child)))
+            });
         let node = if query_time_nested_sum(target) && !selected_composed_summary {
             self.assemble_residual(target)?
         } else {
@@ -5212,8 +5309,10 @@ impl<'a> GlobalSelection<'a> {
                 .map(|c| &c.replacement)
             {
                 None => self.assemble_residual(target)?,
-                Some(Replacement::Rewrite(rewritten)) => keep_pre_asap(rewritten)?,
-                Some(Replacement::Summary(node)) => self.relink_summary(node, target)?,
+                Some(Replacement::SubDAG(node)) if node.contains_asap() => {
+                    self.relink_summary(node, target)?
+                }
+                Some(Replacement::SubDAG(kept)) => retain_exact(kept)?,
                 Some(Replacement::ExactComposition(_)) => Rc::clone(
                     &self.groups[&ptr]
                         .composition
@@ -5229,130 +5328,124 @@ impl<'a> GlobalSelection<'a> {
         Ok(node)
     }
 
-    /// Preserve composable query-time value operators in post-ASAP form even
-    /// when the operator itself has no summary realization. Its child is
-    /// assembled independently, so a selected summary remains visible
-    /// beneath `Project`/`Filter`/`Sort`/`Limit` instead of being swallowed by
-    /// one opaque `KeepPreAsap` sub-DAG.
+    /// Keep `target`'s own operator and assemble each child independently,
+    /// so a selected summary remains visible beneath a relational operator
+    /// that has no summary realization of its own instead of being
+    /// swallowed by one opaque kept sub-DAG. Every child that is a
+    /// discovered target is assembled (and finalized to query-time values);
+    /// any other child is kept as it is. The guarantee is composed from the
+    /// assembled children: all exact → exact; exactly one child → that
+    /// child's guarantee; otherwise unknown. An inner `Join` first has its
+    /// cross-input equi-predicate normalized; any other join is kept whole.
     fn assemble_residual(
         &self,
-        target: &Rc<QueryExpr>,
-    ) -> Result<Rc<SummaryNode>, RealizationError> {
-        if let QueryExpr::Join {
+        target: &Rc<OperatorNode>,
+    ) -> Result<Rc<OperatorNode>, RealizationError> {
+        if target.children().is_empty() {
+            // A leaf has nothing to assemble beneath it: keep it as it is.
+            return retain_exact(target);
+        }
+        let mut operator = target.operator.clone();
+        if let Operator::NonASAP(NonASAPOp::Join {
             left,
             right,
             kind,
             pred,
-        } = target.as_ref()
+        }) = &mut operator
         {
-            let left_width = left.output_schema()?.fields.len();
-            let total_width = left_width + right.output_schema()?.fields.len();
-            let normalized_pred = matches!(kind, asap_types::pre_asap::JoinKind::Inner)
+            let left_width = left.schema.fields.len();
+            let total_width = left_width + right.schema.fields.len();
+            let normalized_pred = matches!(kind, JoinKind::Inner)
                 .then(|| normalize_cross_input_equi_predicate(pred, left_width, total_width))
                 .flatten();
-            let Some(pred) = normalized_pred else {
-                return keep_pre_asap(target);
+            let Some(normalized) = normalized_pred else {
+                return retain_exact(target);
             };
-            let left = finalize_query_candidate(self.assemble_target(left)?, left)?;
-            let right = finalize_query_candidate(self.assemble_target(right)?, right)?;
-            let guarantee =
-                relational_join_guarantee(left.guarantee.as_ref(), right.guarantee.as_ref());
-            let node = Rc::new(SummaryNode {
-                expr: SummaryExpr::RelationalJoin {
-                    left,
-                    right,
-                    kind: kind.clone(),
-                    pred,
-                    pruning: None,
-                },
-                schema: lift(&target.output_schema()?),
-                guarantee,
-            });
-            validate_execution_data_states_at(&node, ExecutionDataState::QUERY_ROWS)?;
-            return Ok(node);
+            *pred = normalized;
         }
-        let (child_target, operation) = match target.as_ref() {
-            QueryExpr::Project {
-                cols,
-                qualifier,
-                child,
-            } => (
-                child,
-                ValueOperation::Project {
-                    cols: cols.clone(),
-                    qualifier: qualifier.clone(),
-                },
-            ),
-            QueryExpr::Filter { pred, child } => {
-                (child, ValueOperation::Filter { pred: pred.clone() })
+        let mut failure = None;
+        let mut children = Vec::new();
+        let operator = operator.map_children(|child| {
+            if failure.is_some() {
+                return Rc::clone(child);
             }
-            QueryExpr::Sort {
-                keys,
-                partition_by,
-                child,
-            } => (
-                child,
-                ValueOperation::Sort {
-                    keys: keys.clone(),
-                    partition_by: partition_by.clone(),
-                },
-            ),
-            QueryExpr::Limit { n, offset, child } => (
-                child,
-                ValueOperation::Limit {
-                    n: *n,
-                    offset: *offset,
-                    partition_by: match child.as_ref() {
-                        QueryExpr::Sort { partition_by, .. } => partition_by.clone(),
-                        _ => Default::default(),
-                    },
-                },
-            ),
-            QueryExpr::Aggregate {
-                reduction,
-                measures,
-                output_names,
-                filters,
-                having,
-                child,
-            } if query_time_nested_sum(target) => (
-                child,
-                ValueOperation::Exact(ExactOperation::Aggregate {
-                    reduction: reduction.clone(),
-                    measures: measures.clone(),
-                    output_names: output_names.clone(),
-                    filters: filters.clone(),
-                    having: having.clone(),
-                }),
-            ),
-            _ => return keep_pre_asap(target),
-        };
-        let child = finalize_query_candidate(self.assemble_target(child_target)?, child_target)?;
-        let guarantee = child.guarantee.clone();
-        let node = Rc::new(SummaryNode {
-            expr: SummaryExpr::ValueOperation {
-                child,
-                operation,
-                timing: ExecutionTiming::QueryTime,
-            },
-            schema: lift(&target.output_schema()?),
-            guarantee,
+            let assembled = if self.groups.contains_key(&Rc::as_ptr(child)) {
+                self.assemble_target(child)
+                    .and_then(|node| finalize_query_candidate(node, child))
+            } else {
+                Ok(Rc::clone(child))
+            };
+            match assembled {
+                Ok(node) => {
+                    children.push(Rc::clone(&node));
+                    node
+                }
+                Err(error) => {
+                    failure = Some(error);
+                    Rc::clone(child)
+                }
+            }
+        });
+        if let Some(error) = failure {
+            return Err(error);
+        }
+        // An operator that computes new values from its input rows has no
+        // sound accuracy composition over an approximate input (e.g. `max`
+        // over a quantile evaluation's rank error). Without a selected
+        // composition such a node stays an exact pre-ASAP sub-DAG; only the
+        // read-time nested SUM keeps its assembled children.
+        let computes_values = matches!(
+            target.non_asap(),
+            Some(
+                NonASAPOp::Aggregate { .. }
+                    | NonASAPOp::BinaryOp { .. }
+                    | NonASAPOp::SQLWindowFunc { .. }
+            )
+        ) && !query_time_nested_sum(target);
+        let approximate_input = children.iter().any(|child| {
+            !child
+                .guarantee
+                .as_ref()
+                .is_some_and(ResultGuarantee::is_exact)
         });
-        validate_execution_data_states_at(&node, ExecutionDataState::QUERY_ROWS)?;
+        if computes_values && approximate_input {
+            return retain_exact(target);
+        }
+        let guarantee = match children.as_slice() {
+            [child] => child.guarantee.clone(),
+            children
+                if children.iter().all(|child| {
+                    child
+                        .guarantee
+                        .as_ref()
+                        .is_some_and(ResultGuarantee::is_exact)
+                }) =>
+            {
+                Some(ResultGuarantee::exact(format!(
+                    "{} over exact inputs",
+                    target.operator.kind_name()
+                )))
+            }
+            _ => None,
+        };
+        let node = Rc::new(
+            OperatorNode::with_schema(operator, target.schema.clone()).with_guarantee(guarantee),
+        );
+        validate_default(&node, ExecutionTiming::QueryTime)?;
         Ok(node)
     }
 
-    /// Re-link a bound `Summary` candidate's `SummaryAgg` child to the
+    /// Re-link a bound summary candidate's `SummaryAgg` child to the
     /// child target's own DAG assembly when that is legal beneath
     /// maintenance; otherwise keep the candidate exactly as constructed.
     fn relink_summary(
         &self,
-        node: &Rc<SummaryNode>,
-        target: &Rc<QueryExpr>,
-    ) -> Result<Rc<SummaryNode>, RealizationError> {
-        let QueryExpr::Aggregate {
+        node: &Rc<OperatorNode>,
+        target: &Rc<OperatorNode>,
+    ) -> Result<Rc<OperatorNode>, RealizationError> {
+        let Some(NonASAPOp::Aggregate {
             child: pre_child, ..
-        } = target.as_ref()
+        }) = target.non_asap()
         else {
             return Ok(Rc::clone(node));
         };
@@ -5377,16 +5470,16 @@ impl<'a> GlobalSelection<'a> {
 
 /// A mergeable outer SUM over a relationally wrapped aggregate is a read-time
 /// reduction of the inner summary values. Maintaining the outer SUM directly
-/// would hide that inner temporal aggregate inside `KeepPreAsap` and lose its
-/// independently selected summary.
-fn query_time_nested_sum(target: &QueryExpr) -> bool {
-    let QueryExpr::Aggregate {
+/// would hide that inner temporal aggregate inside one kept sub-DAG and lose
+/// its independently selected summary.
+fn query_time_nested_sum(target: &OperatorNode) -> bool {
+    let Some(NonASAPOp::Aggregate {
         measures,
         filters,
         having: None,
         child,
         ..
-    } = target
+    }) = target.non_asap()
     else {
         return false;
     };
@@ -5395,13 +5488,15 @@ fn query_time_nested_sum(target: &QueryExpr) -> bool {
         && contains_aggregate(child)
 }
 
-fn contains_aggregate(expr: &QueryExpr) -> bool {
-    match expr {
-        QueryExpr::Aggregate { .. } => true,
-        QueryExpr::Project { child, .. }
-        | QueryExpr::Filter { child, .. }
-        | QueryExpr::Sort { child, .. }
-        | QueryExpr::Limit { child, .. } => contains_aggregate(child),
+fn contains_aggregate(expr: &OperatorNode) -> bool {
+    match expr.non_asap() {
+        Some(NonASAPOp::Aggregate { .. }) => true,
+        Some(
+            NonASAPOp::Project { child, .. }
+            | NonASAPOp::Filter { child, .. }
+            | NonASAPOp::Sort { child, .. }
+            | NonASAPOp::Limit { child, .. },
+        ) => contains_aggregate(child),
         _ => false,
     }
 }
@@ -5409,50 +5504,53 @@ fn contains_aggregate(expr: &QueryExpr) -> bool {
 /// Rebuild `node` (a `SummaryAgg`, possibly under a `SummaryEstimate`) with
 /// `new_child` as the `SummaryAgg`'s child, if the result still validates
 /// as maintained state; otherwise return `node` unchanged.
-fn relink_agg_child(node: &Rc<SummaryNode>, new_child: &Rc<SummaryNode>) -> Rc<SummaryNode> {
-    match &node.expr {
-        SummaryExpr::SummaryEstimate {
+fn relink_agg_child(node: &Rc<OperatorNode>, new_child: &Rc<OperatorNode>) -> Rc<OperatorNode> {
+    match &node.operator {
+        Operator::ASAP(ASAPOp::SummaryEstimate {
             summary_input,
             query,
-        } => {
+        }) => {
             let inner = relink_agg_child(summary_input, new_child);
             if Rc::ptr_eq(&inner, summary_input) {
                 return Rc::clone(node);
             }
-            Rc::new(SummaryNode {
-                expr: SummaryExpr::SummaryEstimate {
-                    summary_input: inner,
-                    query: query.clone(),
-                },
-                schema: node.schema.clone(),
-                guarantee: node.guarantee.clone(),
-            })
+            std::rc::Rc::new(
+                OperatorNode::with_schema(
+                    asap_types::ir::Operator::ASAP(ASAPOp::SummaryEstimate {
+                        summary_input: inner,
+                        query: query.clone(),
+                    }),
+                    node.schema.clone(),
+                )
+                .with_guarantee(node.guarantee.clone()),
+            )
         }
-        SummaryExpr::SummaryAgg {
+        Operator::ASAP(ASAPOp::SummaryAgg {
             child,
             family,
             input,
             reduction,
             grouping,
             filter,
-        } => {
+        }) => {
             if Rc::ptr_eq(child, new_child) {
                 return Rc::clone(node);
             }
-            let rebuilt = Rc::new(SummaryNode {
-                expr: SummaryExpr::SummaryAgg {
-                    child: Rc::clone(new_child),
-                    family: family.clone(),
-                    input: input.clone(),
-                    reduction: reduction.clone(),
-                    grouping: grouping.clone(),
-                    filter: filter.clone(),
-                },
-                schema: node.schema.clone(),
-                guarantee: node.guarantee.clone(),
-            });
-            match validate_execution_data_states_at(&rebuilt, ExecutionDataState::INGESTION_SUMMARY)
-            {
+            let rebuilt = std::rc::Rc::new(
+                OperatorNode::with_schema(
+                    asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
+                        child: Rc::clone(new_child),
+                        family: family.clone(),
+                        input: input.clone(),
+                        reduction: reduction.clone(),
+                        grouping: grouping.clone(),
+                        filter: filter.clone(),
+                    }),
+                    node.schema.clone(),
+                )
+                .with_guarantee(node.guarantee.clone()),
+            );
+            match validate_default(&rebuilt, ExecutionTiming::IngestionTime) {
                 Ok(_) => rebuilt,
                 Err(_) => Rc::clone(node),
             }
@@ -5461,13 +5559,15 @@ fn relink_agg_child(node: &Rc<SummaryNode>, new_child: &Rc<SummaryNode>) -> Rc<S
     }
 }
 
-/// The maintained `SummaryAgg` a bound `Summary` candidate builds (under
-/// its `SummaryEstimate` readout, if any) — the summary an `ValueOperationAtIngestionTime`
+/// The maintained `SummaryAgg` a bound summary candidate builds (under
+/// its `SummaryEstimate` evaluation, if any) — the summary an `ValueOperationAtIngestionTime`
 /// beneath it feeds, for `maintenance_operation_plan_cost_rate`.
-fn maintained_summary(node: &Rc<SummaryNode>) -> Option<&Rc<SummaryNode>> {
-    match &node.expr {
-        SummaryExpr::SummaryEstimate { summary_input, .. } => maintained_summary(summary_input),
-        SummaryExpr::SummaryAgg { .. } => Some(node),
+fn maintained_summary(node: &Rc<OperatorNode>) -> Option<&Rc<OperatorNode>> {
+    match &node.operator {
+        Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) => {
+            maintained_summary(summary_input)
+        }
+        Operator::ASAP(ASAPOp::SummaryAgg { .. }) => Some(node),
         _ => None,
     }
 }
@@ -5484,10 +5584,10 @@ struct CompositionContext {
     /// child target ptr → the child's candidate an ancestor's composition
     /// already committed to (a later parent must compose with the *same*
     /// one, and the child's own selection is forced to it).
-    committed_child: HashMap<*const QueryExpr, *const ReplacementSubDAG>,
+    committed_child: HashMap<*const OperatorNode, *const ReplacementSubDAG>,
     /// site ptr → the maintained `SummaryAgg` directly above it, when its
-    /// parent chose a bound `Summary` — what an `ValueOperationAtIngestionTime` here feeds.
-    maintaining_parent: HashMap<*const QueryExpr, Rc<SummaryNode>>,
+    /// parent chose a bound summary — what an `ValueOperationAtIngestionTime` here feeds.
+    maintaining_parent: HashMap<*const OperatorNode, Rc<OperatorNode>>,
 }
 
 /// One eligible composed alternative at a site, before the cheapest wins.
@@ -5500,10 +5600,10 @@ struct CompositionOption<'a> {
 /// composed-plan rate is *known* and beats the raw-recompute baseline —
 /// costed against each compatible child candidate already in `CandidateLogicalASAPDAGs`
 /// (or the one an earlier parent committed). Unknown statistics yield no
-/// option at all: the conservative `KeepPreAsap` path stays.
+/// option at all: the conservative kept-sub-DAG path stays.
 fn composition_options<'a>(
     group: &'a TargetSubDAGCandidates,
-    groups: &'a HashMap<*const QueryExpr, TargetSubDAGCandidates>,
+    groups: &'a HashMap<*const OperatorNode, TargetSubDAGCandidates>,
     effective: usize,
     cost_model: &dyn CostModel,
     context: &CompositionContext,
@@ -5522,7 +5622,7 @@ fn composition_options<'a>(
             continue;
         };
         let already_committed = context.committed_child.get(&child_ptr).copied();
-        let cost = |summary: &SummaryNode, shared: bool| {
+        let cost = |summary: &OperatorNode, shared: bool| {
             let request = ExactCompositionCostRequest {
                 target: &group.target,
                 composition,
@@ -5558,10 +5658,10 @@ fn composition_options<'a>(
                     if !is_automatically_selectable(child_candidate, cost_model) {
                         continue;
                     }
-                    let Replacement::Summary(summary) = &child_candidate.replacement else {
+                    let Replacement::SubDAG(summary) = &child_candidate.replacement else {
                         continue;
                     };
-                    if !composition.accepts_child(summary) {
+                    if is_logical_rewrite(summary) || !composition.accepts_child(summary) {
                         continue;
                     }
                     let Some(prepared) = plans.iter().find(|p| {
@@ -5670,8 +5770,8 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
         let topo = topological_order(&self.order, &dag);
 
         let mut effective_uses = dag.external_root_uses.clone();
-        let mut chosen_share: HashMap<*const QueryExpr, ShareDecision> = HashMap::new();
-        let mut groups: HashMap<*const QueryExpr, TargetSubDAGSelection<'_>> = HashMap::new();
+        let mut chosen_share: HashMap<*const OperatorNode, ShareDecision> = HashMap::new();
+        let mut groups: HashMap<*const OperatorNode, TargetSubDAGSelection<'_>> = HashMap::new();
         let mut context = CompositionContext::default();
 
         for ptr in &topo {
@@ -5898,8 +5998,8 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
             // Record the maintained summary this site's bound candidate
             // builds, for a child that may compose an `ValueOperationAtIngestionTime`
             // beneath it.
-            if let (Some(Replacement::Summary(node)), QueryExpr::Aggregate { child, .. }) =
-                (chosen.map(|c| &c.replacement), group.target.as_ref())
+            if let (Some(Replacement::SubDAG(node)), Some(NonASAPOp::Aggregate { child, .. })) =
+                (chosen.map(|c| &c.replacement), group.target.non_asap())
             {
                 if let Some(summary) = maintained_summary(node) {
                     context
@@ -5911,7 +6011,7 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
             let outgoing_multiplier = multiplier(*ptr, &effective_uses, &chosen_share);
             match chosen {
                 Some(ReplacementSubDAG {
-                    replacement: Replacement::Rewrite(source),
+                    replacement: Replacement::SubDAG(source),
                     provenance: ReplacementProvenance::AccuracyReconciliation,
                     ..
                 }) => {
@@ -5924,8 +6024,10 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
                 }
                 _ => {
                     let selected_rewrite = match chosen.map(|candidate| &candidate.replacement) {
-                        Some(Replacement::Rewrite(rewrite)) => rewrite,
-                        Some(Replacement::Summary(_) | Replacement::ExactComposition(_)) | None => {
+                        Some(Replacement::SubDAG(rewrite)) if is_logical_rewrite(rewrite) => {
+                            rewrite
+                        }
+                        Some(Replacement::SubDAG(_) | Replacement::ExactComposition(_)) | None => {
                             &group.target
                         }
                     };
@@ -5991,9 +6093,9 @@ fn is_automatically_selectable(candidate: &ReplacementSubDAG, cost_model: &dyn C
 /// ancestor sits anywhere on the path from a root to a site — see the
 /// module docs' "Whole-plan (cross-group) selection" section.
 fn multiplier(
-    parent_ptr: *const QueryExpr,
-    effective_uses: &HashMap<*const QueryExpr, usize>,
-    chosen_share: &HashMap<*const QueryExpr, ShareDecision>,
+    parent_ptr: *const OperatorNode,
+    effective_uses: &HashMap<*const OperatorNode, usize>,
+    chosen_share: &HashMap<*const OperatorNode, ShareDecision>,
 ) -> usize {
     let effective = *effective_uses.get(&parent_ptr).expect(
         "topological_order guarantees a parent is processed (and its effective_consumer_count \
@@ -6017,7 +6119,7 @@ fn cse_candidate_pair(
     for candidate in &group.candidates {
         match candidate.provenance {
             ReplacementProvenance::CseShare => {
-                let Replacement::Rewrite(rc) = &candidate.replacement else {
+                let Replacement::SubDAG(rc) = &candidate.replacement else {
                     return None;
                 };
                 if !Rc::ptr_eq(rc, &group.target) || share.replace(candidate).is_some() {
@@ -6025,7 +6127,7 @@ fn cse_candidate_pair(
                 }
             }
             ReplacementProvenance::CseRecompute => {
-                let Replacement::Rewrite(rc) = &candidate.replacement else {
+                let Replacement::SubDAG(rc) = &candidate.replacement else {
                     return None;
                 };
                 if Rc::ptr_eq(rc, &group.target)
@@ -6103,26 +6205,25 @@ fn pick_shared_sub_dag_candidate(
 /// The parent/child structure [`CandidateLogicalASAPDAGs::global_selection`]'s DP walks —
 /// built separately from [`discover_targets`]'s own `order`/`nodes`/`counts`
 /// maps (which only track *aggregate* reference counts, not per-parent
-/// breakdown or direction) rather than extending that already-reviewed,
-/// already-tested pass. Same "small duplicated traversal over reshaping
-/// proven code" call as [`is_shared_subtree_group`].
+/// breakdown or direction). Selection needs per-parent edge counts to
+/// distinguish shared producers from repeated uses within one consumer.
 struct ReferenceDAG {
     /// child ptr -> `(parent ptr, edge count from that one parent)`, for
     /// every direct operator-child edge in the relational-skeleton scope
     /// [`walk_children`] itself uses (an edge count above 1 happens when
     /// one parent references the same child from two different fields,
     /// e.g. a `Join`'s `left`/`right` both being the same `Rc`).
-    parents_of: HashMap<*const QueryExpr, Vec<(*const QueryExpr, usize)>>,
+    parents_of: HashMap<*const OperatorNode, Vec<(*const OperatorNode, usize)>>,
     /// parent ptr -> every distinct child ptr it directly references — the
     /// reverse of `parents_of`, for [`topological_order`]'s Kahn's-algorithm
     /// traversal.
-    children_of: HashMap<*const QueryExpr, Vec<*const QueryExpr>>,
+    children_of: HashMap<*const OperatorNode, Vec<*const OperatorNode>>,
     /// How many of the workload's own `roots` point directly at each node —
     /// a node's "external" use. Nothing inside the DAG decides this (it
     /// isn't a reference from another discovered site), so it's never
     /// subject to any ancestor's Share/Recompute choice — it's the base
     /// case [`CandidateLogicalASAPDAGs::global_selection`]'s recurrence starts from.
-    external_root_uses: HashMap<*const QueryExpr, usize>,
+    external_root_uses: HashMap<*const OperatorNode, usize>,
 }
 
 /// Build an ordering DAG containing every edge that could be selected:
@@ -6145,7 +6246,10 @@ fn reference_dag<Id>(space: &CandidateLogicalASAPDAGs<Id>) -> ReferenceDAG {
         let group = &space.groups[ptr];
         record_possible_edges(*ptr, &group.target, &mut dag);
         for candidate in &group.candidates {
-            if let Replacement::Rewrite(rewrite) = &candidate.replacement {
+            if let Replacement::SubDAG(rewrite) = &candidate.replacement {
+                if !is_logical_rewrite(rewrite) {
+                    continue;
+                }
                 if candidate.provenance == ReplacementProvenance::AccuracyReconciliation {
                     add_edge(*ptr, Rc::as_ptr(rewrite), 1, &mut dag);
                 } else {
@@ -6161,8 +6265,8 @@ fn reference_dag<Id>(space: &CandidateLogicalASAPDAGs<Id>) -> ReferenceDAG {
 /// [`ReferenceDAG`]'s fields), retaining the greatest multiplicity seen
 /// when the target and alternative rewrites expose the same edge.
 fn add_edge(
-    parent_ptr: *const QueryExpr,
-    child_ptr: *const QueryExpr,
+    parent_ptr: *const OperatorNode,
+    child_ptr: *const OperatorNode,
     edge_count: usize,
     dag: &mut ReferenceDAG,
 ) {
@@ -6177,7 +6281,11 @@ fn add_edge(
     }
 }
 
-fn record_possible_edges(parent_ptr: *const QueryExpr, node: &QueryExpr, dag: &mut ReferenceDAG) {
+fn record_possible_edges(
+    parent_ptr: *const OperatorNode,
+    node: &OperatorNode,
+    dag: &mut ReferenceDAG,
+) {
     for (child_ptr, edge_count) in direct_child_counts(node) {
         add_edge(parent_ptr, child_ptr, edge_count, dag);
     }
@@ -6185,8 +6293,8 @@ fn record_possible_edges(parent_ptr: *const QueryExpr, node: &QueryExpr, dag: &m
 
 /// Direct relational-skeleton children and their edge multiplicities.
 /// `Concat` is transparent, matching [`walk_children`]'s site scope.
-fn direct_child_counts(node: &QueryExpr) -> Vec<(*const QueryExpr, usize)> {
-    fn push(children: &mut Vec<(*const QueryExpr, usize)>, child: &Rc<QueryExpr>) {
+fn direct_child_counts(node: &OperatorNode) -> Vec<(*const OperatorNode, usize)> {
+    fn push(children: &mut Vec<(*const OperatorNode, usize)>, child: &Rc<OperatorNode>) {
         let ptr = Rc::as_ptr(child);
         match children.iter_mut().find(|(existing, _)| *existing == ptr) {
             Some((_, count)) => *count += 1,
@@ -6194,57 +6302,19 @@ fn direct_child_counts(node: &QueryExpr) -> Vec<(*const QueryExpr, usize)> {
         }
     }
 
-    fn collect(node: &QueryExpr, children: &mut Vec<(*const QueryExpr, usize)>) {
-        use QueryExpr::*;
-        match node {
-            Scan { .. } | PromqlScalarBridge(_) | EvalTimestamp | CurrentTimestamp => {}
-            PromqlVectorFromScalar(c) | PromqlScalarFromVector(c) => {
-                push(children, c);
-            }
-            PromqlRelabel { child, .. }
-            | PromqlInfoEnrich { child, .. }
-            | PromqlSeriesSample { child, .. }
-            | Filter { child, .. }
-            | Project { child, .. }
-            | Aggregate { child, .. }
-            | Dedup { child, .. }
-            | PromqlSubquery { child, .. }
-            | TimeRange { child, .. }
-            | TimeShift { child, .. }
-            | SQLWindowFunc { child, .. }
-            | Sort { child, .. }
-            | Limit { child, .. } => {
-                push(children, child);
-            }
-            Concat {
-                children: concat_children,
-                ..
-            } => {
-                for c in concat_children {
-                    collect(c, children);
-                }
-            }
-            Join { left, right, .. } | SetOp { left, right, .. } => {
-                push(children, left);
-                push(children, right);
-            }
-            BinaryOp { lhs, rhs, .. } => {
-                push(children, lhs);
-                push(children, rhs);
+    fn collect(node: &OperatorNode, children: &mut Vec<(*const OperatorNode, usize)>) {
+        if let Some(NonASAPOp::Concat {
+            children: concat_children,
+            ..
+        }) = node.non_asap()
+        {
+            for c in concat_children {
+                collect(c, children);
             }
-            Column(_)
-            | Literal(_)
-            | Compare { .. }
-            | BoolAnd(_)
-            | BoolOr(_)
-            | Not(_)
-            | IsNull(_)
-            | IsNotNull(_)
-            | Cast { .. }
-            | InList { .. }
-            | FunctionCall { .. }
-            | Arithmetic { .. }
-            | Case { .. } => {}
+            return;
+        }
+        for child in node.children() {
+            push(children, child);
         }
     }
 
@@ -6260,14 +6330,17 @@ fn direct_child_counts(node: &QueryExpr) -> Vec<(*const QueryExpr, usize)> {
 /// different root paths can have a parent that's discovered *after* it (see
 /// this function's own test for a worked diamond example), which is exactly
 /// backwards for [`CandidateLogicalASAPDAGs::global_selection`]'s recurrence.
-fn topological_order(order: &[*const QueryExpr], dag: &ReferenceDAG) -> Vec<*const QueryExpr> {
-    let mut in_degree: HashMap<*const QueryExpr, usize> = HashMap::new();
+fn topological_order(
+    order: &[*const OperatorNode],
+    dag: &ReferenceDAG,
+) -> Vec<*const OperatorNode> {
+    let mut in_degree: HashMap<*const OperatorNode, usize> = HashMap::new();
     for ptr in order {
         let degree = dag.parents_of.get(ptr).map(Vec::len).unwrap_or(0);
         in_degree.insert(*ptr, degree);
     }
 
-    let mut queue: VecDeque<*const QueryExpr> = order
+    let mut queue: VecDeque<*const OperatorNode> = order
         .iter()
         .copied()
         .filter(|ptr| in_degree[ptr] == 0)
@@ -6291,9 +6364,9 @@ fn topological_order(order: &[*const QueryExpr], dag: &ReferenceDAG) -> Vec<*con
     assert_eq!(
         topo.len(),
         order.len(),
-        "topological_order: the discovered-site reference DAG has a cycle — every QueryExpr \
-         node is built from Rc children, which can't form one, so this indicates a bug in \
-         reference_dag rather than a real cyclic workload",
+        "topological_order: the discovered-site reference dag has a cycle — every \
+         OperatorNode is built from Rc children, which can't form one, so this indicates a bug \
+         in reference_dag rather than a real cyclic workload",
     );
     topo
 }
@@ -6319,13 +6392,13 @@ fn topological_order(order: &[*const QueryExpr], dag: &ReferenceDAG) -> Vec<*con
 /// the target itself) exactly like [`SharedSubDAGStrategy`], so it belongs
 /// in this list rather than being derived per-workload the way
 /// [`RollupStrategy`] is. Rewriting `avg` into `sum`/`count` upfront is what
-/// lets [`SketchAlgorithmStrategy`] and [`SharedSubDAGStrategy`] see a
+/// lets [`ASAPStrategies`] and [`SharedSubDAGStrategy`] see a
 /// mergeable accumulator to sketch or share at all — see that module's own
 /// doc comment for why a bare `avg` node otherwise never becomes a
 /// [`ReplacementStrategy`] target for anything.
 pub fn default_strategies() -> Vec<Box<dyn ReplacementStrategy>> {
     vec![
-        Box::new(SketchAlgorithmStrategy::default_cost_model()),
+        Box::new(ASAPStrategies::default_cost_model()),
         Box::new(HydraGroupingStrategy::default_cost_model()),
         Box::new(SharedSubDAGStrategy),
         Box::new(crate::rewrite::AvgToSumOverCountStrategy),
@@ -6333,14 +6406,14 @@ pub fn default_strategies() -> Vec<Box<dyn ReplacementStrategy>> {
     ]
 }
 
-/// Like [`default_strategies`], but [`SketchAlgorithmStrategy`] ranks/binds via
+/// Like [`default_strategies`], but [`ASAPStrategies`] ranks/binds via
 /// `cost_model` instead of the built-in [`DefaultCostModel`] — the same
-/// customization point [`SketchAlgorithmStrategy::new`] itself offers.
+/// customization point [`ASAPStrategies::new`] itself offers.
 pub fn default_strategies_with<'a>(
     cost_model: &'a dyn CostModel,
 ) -> Vec<Box<dyn ReplacementStrategy + 'a>> {
     vec![
-        Box::new(SketchAlgorithmStrategy::new(cost_model)),
+        Box::new(ASAPStrategies::new(cost_model)),
         Box::new(HydraGroupingStrategy::new(cost_model)),
         Box::new(SharedSubDAGStrategy),
         Box::new(crate::rewrite::SemanticEquivalentRewriteStrategy),
@@ -6350,21 +6423,19 @@ pub fn default_strategies_with<'a>(
 
 /// Default context-free strategies with both deployment costing and typed
 /// planning-time accuracy evidence. This is the production counterpart of
-/// constructing [`SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence`] and
+/// constructing [`ASAPStrategies::new_with_planning_inputs_and_evidence`] and
 /// [`HydraGroupingStrategy::new_with_planning_inputs_and_evidence`] separately.
 pub fn default_strategies_with_evidence<'a>(
     cost_model: &'a dyn CostModel,
     evidence: &'a dyn AccuracyEvidenceProvider,
 ) -> Vec<Box<dyn ReplacementStrategy + 'a>> {
     vec![
-        Box::new(
-            SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
-                cost_model,
-                &DEFAULT_ACCURACY_MODEL,
-                &DEFAULT_ALLOCATOR,
-                evidence,
-            ),
-        ),
+        Box::new(ASAPStrategies::new_with_planning_inputs_and_evidence(
+            cost_model,
+            &DEFAULT_ACCURACY_MODEL,
+            &DEFAULT_ALLOCATOR,
+            evidence,
+        )),
         Box::new(
             HydraGroupingStrategy::new_with_planning_inputs_and_evidence(
                 cost_model,
@@ -6384,12 +6455,12 @@ pub fn default_strategies_with_evidence<'a>(
 /// Search a whole workload's pre-ASAP roots for every candidate replacement
 /// [`default_strategies`] can find, deduped into a [`CandidateLogicalASAPDAGs`]. Candidate
 /// *generation* uses the built-in [`DefaultCostModel`] (via
-/// [`default_strategies`], the same way [`SketchAlgorithmStrategy::default_cost_model`]
+/// [`default_strategies`], the same way [`ASAPStrategies::default_cost_model`]
 /// does); call [`CandidateLogicalASAPDAGs::cost_sorted`] on the result for the final
 /// `sorted_by(cost_model)` step. Use [`search_workload_with`] to plug in a
 /// custom strategy set (e.g. built via [`default_strategies_with`] for a
 /// deployment-specific [`CostModel`]).
-pub fn search_workload<Id>(roots: Vec<(Id, Rc<QueryExpr>)>) -> CandidateLogicalASAPDAGs<Id> {
+pub fn search_workload<Id>(roots: Vec<(Id, Rc<OperatorNode>)>) -> CandidateLogicalASAPDAGs<Id> {
     search_workload_with(roots, &default_strategies())
 }
 
@@ -6409,10 +6480,10 @@ pub fn search_workload<Id>(roots: Vec<(Id, Rc<QueryExpr>)>) -> CandidateLogicalA
 /// section). Deduping candidate plans this way needs no
 /// [`CostModel`] at all — that only enters at two well-defined points: each
 /// [`ReplacementStrategy`] in `strategies` may already carry its own (e.g.
-/// [`SketchAlgorithmStrategy::new`]'s), and [`CandidateLogicalASAPDAGs::cost_sorted`]'s final
+/// [`ASAPStrategies::new`]'s), and [`CandidateLogicalASAPDAGs::cost_sorted`]'s final
 /// ranking step takes one explicitly.
 pub fn search_workload_with<'s, Id>(
-    roots: Vec<(Id, Rc<QueryExpr>)>,
+    roots: Vec<(Id, Rc<OperatorNode>)>,
     strategies: &[Box<dyn ReplacementStrategy + 's>],
 ) -> CandidateLogicalASAPDAGs<Id> {
     let mut space = search_cse_workload_with(cse_workload(roots), strategies);
@@ -6423,7 +6494,7 @@ pub fn search_workload_with<'s, Id>(
 /// [`search_workload_with`] plus a per-root end-to-end `AccuracyTarget`
 /// (issue #172) — the workload's `QueryRequirements.accuracy`, threaded
 /// alongside each root. After the search, every root that carries a target
-/// has its group's bound [`Replacement::Summary`] candidates checked with
+/// has its group's bound-summary [`Replacement::SubDAG`] candidates checked with
 /// `accuracy_model`'s [`AccuracyModel::satisfies`]: a candidate whose
 /// guarantee is fully known and misses the target is moved from
 /// [`TargetSubDAGCandidates::candidates`] to [`TargetSubDAGCandidates::rejected`] *before*
@@ -6431,16 +6502,16 @@ pub fn search_workload_with<'s, Id>(
 /// group. A constructible candidate with unknown accuracy remains visible for
 /// downstream review under an approximate target, but default whole-plan
 /// selection does not commit it. An exact target cannot accept an unknown
-/// approximate summary. A `KeepPreAsap` candidate is
+/// approximate summary. A kept pre-ASAP candidate is
 /// exact and always survives — the raw/pre-ASAP alternative is what an
-/// unsatisfiable root keeps. Logical [`Replacement::Rewrite`] candidates
-/// are not bound values and are left alone; the targets *inside* a rewrite
-/// are their own groups.
+/// unsatisfiable root keeps. Logical-rewrite [`Replacement::SubDAG`]
+/// candidates are not bound values and are left alone; the targets *inside*
+/// a rewrite are their own groups.
 ///
 /// Precedence against per-node `AggIntent.accuracy` is documented in
 /// [`crate::accuracy`]'s module docs.
 pub fn search_workload_with_targets<'s, Id>(
-    roots: Vec<(Id, Rc<QueryExpr>, Option<AccuracyTarget>)>,
+    roots: Vec<(Id, Rc<OperatorNode>, Option<AccuracyTarget>)>,
     strategies: &[Box<dyn ReplacementStrategy + 's>],
     accuracy_model: &dyn AccuracyModel,
 ) -> CandidateLogicalASAPDAGs<Id> {
@@ -6454,7 +6525,7 @@ pub fn search_workload_with_targets<'s, Id>(
         .collect();
     let mut space = search_cse_workload_with(cse_workload(roots), strategies);
     // `cse_workload` preserves root order, so targets zip by position.
-    let root_ptrs: Vec<(*const QueryExpr, AccuracyTarget)> = space
+    let root_ptrs: Vec<(*const OperatorNode, AccuracyTarget)> = space
         .roots
         .iter()
         .zip(targets)
@@ -6496,11 +6567,11 @@ pub fn search_workload_with_targets<'s, Id>(
                 .candidates
                 .drain(..)
                 .partition(|candidate| match &candidate.replacement {
-                    Replacement::Summary(node) => node.guarantee.as_ref().map_or_else(
+                    Replacement::SubDAG(node) if is_logical_rewrite(node) => true,
+                    Replacement::SubDAG(node) => node.guarantee.as_ref().map_or_else(
                         || !matches!(target, AccuracyTarget::Exact),
                         |g| accuracy_model.satisfies(&g.optimistic_floor(), &target),
                     ),
-                    Replacement::Rewrite(_) => true,
                     // A composition's guarantee depends on the concrete child;
                     // prepare_compositions checks those pairs after all roots.
                     Replacement::ExactComposition(_) => true,
@@ -6508,7 +6579,7 @@ pub fn search_workload_with_targets<'s, Id>(
         group.candidates = legal;
         group.rejected.extend(illegal.into_iter().map(|candidate| {
             let (metric, bound, failure_probability) = match &candidate.replacement {
-                Replacement::Summary(node) => node
+                Replacement::SubDAG(node) => node
                     .guarantee
                     .as_ref()
                     .map(|g| {
@@ -6523,7 +6594,6 @@ pub fn search_workload_with_targets<'s, Id>(
                         None,
                         None,
                     )),
-                Replacement::Rewrite(_) => unreachable!("rewrites are never rejected here"),
                 Replacement::ExactComposition(_) => (
                     asap_types::post_asap::ErrorMetric::AbsoluteValue,
                     None,
@@ -6548,22 +6618,22 @@ pub fn search_workload_with_targets<'s, Id>(
 
 /// The strictest accuracy among `siblings` that read the same summary input
 /// as `root` — same child, grouping and filters, and the same intent apart
-/// from its accuracy (and a quantile's rank, a readout parameter) — when
+/// from its accuracy (and a quantile's rank, a evaluation parameter) — when
 /// stricter than `root`'s own. One summary sized for the strictest consumer
 /// serves every sibling: #509's summary-capability rule.
 fn strictest_sibling_accuracy(
-    root: &QueryExpr,
-    siblings: &[Rc<QueryExpr>],
+    root: &OperatorNode,
+    siblings: &[Rc<OperatorNode>],
 ) -> Option<AccuracyTarget> {
     fn approximate(intent: &AggIntent) -> Option<&AccuracyTarget> {
         accuracy_target(intent).filter(|accuracy| !matches!(accuracy, AccuracyTarget::Exact))
     }
-    let QueryExpr::Aggregate {
+    let Some(NonASAPOp::Aggregate {
         reduction,
         filters,
         child,
         ..
-    } = root
+    }) = root.non_asap()
     else {
         return None;
     };
@@ -6571,12 +6641,12 @@ fn strictest_sibling_accuracy(
     let own = accuracy_budget(approximate(intent)?);
     let (mut eps, mut delta) = own;
     for sibling in siblings {
-        let QueryExpr::Aggregate {
+        let Some(NonASAPOp::Aggregate {
             reduction: sibling_reduction,
             filters: sibling_filters,
             child: sibling_child,
             ..
-        } = sibling.as_ref()
+        }) = sibling.non_asap()
         else {
             continue;
         };
@@ -6614,48 +6684,45 @@ fn strictest_sibling_accuracy(
     }
 }
 
-fn cse_workload<Id>(roots: Vec<(Id, Rc<QueryExpr>)>) -> Vec<(Id, Rc<QueryExpr>)> {
-    // `share_common_sub_dags` wants owned `QueryExpr`s, not already-`Rc`
-    // roots — the same `Rc::try_unwrap`-with-clone-fallback pattern
-    // `asap_types::pre_asap::cse::intern_child` itself uses to recover an
-    // owned node without cloning in the common (uniquely-owned) case.
-    let owned_roots: Vec<(Id, QueryExpr)> = roots
-        .into_iter()
-        .map(|(id, rc)| {
-            let expr = Rc::try_unwrap(rc).unwrap_or_else(|shared| (*shared).clone());
-            (id, expr)
-        })
-        .collect();
-    share_common_sub_dags(owned_roots)
+fn cse_workload<Id>(roots: Vec<(Id, Rc<OperatorNode>)>) -> Vec<(Id, Rc<OperatorNode>)> {
+    share_common_sub_dags(roots)
 }
 
 fn search_cse_workload_with<'s, Id>(
-    cse_roots: Vec<(Id, Rc<QueryExpr>)>,
+    cse_roots: Vec<(Id, Rc<OperatorNode>)>,
     strategies: &[Box<dyn ReplacementStrategy + 's>],
 ) -> CandidateLogicalASAPDAGs<Id> {
+    for (_, root) in &cse_roots {
+        assert!(
+            !root.contains_asap(),
+            "search_workload: a workload root already contains an ASAP operator \
+             ({}); replacement search takes the front end's pre-ASAP DAG only",
+            root.operator.kind_name()
+        );
+    }
     let mut order = Vec::new();
     let mut nodes = HashMap::new();
-    let mut counts: HashMap<*const QueryExpr, usize> = HashMap::new();
+    let mut counts: HashMap<*const OperatorNode, usize> = HashMap::new();
     discover_targets(&cse_roots, &mut order, &mut nodes, &mut counts);
-    let siblings: Vec<Rc<QueryExpr>> = order
+    let siblings: Vec<Rc<OperatorNode>> = order
         .iter()
         .filter_map(|ptr| {
             let node = &nodes[ptr];
-            matches!(node.as_ref(), QueryExpr::Aggregate { .. }).then(|| Rc::clone(node))
+            matches!(node.non_asap(), Some(NonASAPOp::Aggregate { .. })).then(|| Rc::clone(node))
         })
         .collect();
     let rollup_strategy = RollupStrategy::new(&siblings);
     let accuracy_reconciliation_strategy = AccuracyReconciliationStrategy::new(&siblings);
-    let limits: Vec<Rc<QueryExpr>> = order
+    let limits: Vec<Rc<OperatorNode>> = order
         .iter()
         .filter_map(|ptr| {
             let node = &nodes[ptr];
-            matches!(node.as_ref(), QueryExpr::Limit { .. }).then(|| Rc::clone(node))
+            matches!(node.non_asap(), Some(NonASAPOp::Limit { .. })).then(|| Rc::clone(node))
         })
         .collect();
     let topk_reuse_strategy = TopKLimitReuseStrategy::new(&limits);
 
-    let mut groups: HashMap<*const QueryExpr, TargetSubDAGCandidates> = HashMap::new();
+    let mut groups: HashMap<*const OperatorNode, TargetSubDAGCandidates> = HashMap::new();
     for ptr in &order {
         groups.insert(
             *ptr,
@@ -6678,7 +6745,7 @@ fn search_cse_workload_with<'s, Id>(
             "search_workload: fixpoint search did not converge within {MAX_SEARCH_ITERATIONS} \
              rounds — a registered ReplacementStrategy's Replacement::Rewrite candidates keep \
              exposing new, never-before-seen descendant structure every round. \
-             SketchAlgorithmStrategy/SharedSubDAGStrategy never do this (see replacement.rs's \
+             ASAPStrategies/SharedSubDAGStrategy never do this (see replacement.rs's \
              module docs' \"Termination\" section); check any custom strategies passed to \
              search_workload_with.",
         );
@@ -6741,8 +6808,10 @@ fn search_cse_workload_with<'s, Id>(
             }
 
             for candidate in &proposed {
-                if let Replacement::Rewrite(rc) = &candidate.replacement {
-                    discover_new_descendant_targets(rc, &mut order, &mut nodes, &mut counts);
+                if let Replacement::SubDAG(rc) = &candidate.replacement {
+                    if is_logical_rewrite(rc) {
+                        discover_new_descendant_targets(rc, &mut order, &mut nodes, &mut counts);
+                    }
                 }
             }
 
@@ -6782,10 +6851,11 @@ fn search_cse_workload_with<'s, Id>(
 /// ancestor is recomputed. We only do this when an ordinary repeated group
 /// proves that `SharedSubDAGStrategy` is part of this search's strategy set.
 fn add_effective_count_cse_candidates(
-    order: &[*const QueryExpr],
-    groups: &mut HashMap<*const QueryExpr, TargetSubDAGCandidates>,
+    order: &[*const OperatorNode],
+    groups: &mut HashMap<*const OperatorNode, TargetSubDAGCandidates>,
 ) {
-    let mut possible_children: HashMap<*const QueryExpr, Vec<*const QueryExpr>> = HashMap::new();
+    let mut possible_children: HashMap<*const OperatorNode, Vec<*const OperatorNode>> =
+        HashMap::new();
     for ptr in order {
         let group = &groups[ptr];
         let children = possible_children.entry(*ptr).or_default();
@@ -6795,7 +6865,10 @@ fn add_effective_count_cse_candidates(
             }
         }
         for candidate in &group.candidates {
-            if let Replacement::Rewrite(rewrite) = &candidate.replacement {
+            if let Replacement::SubDAG(rewrite) = &candidate.replacement {
+                if !is_logical_rewrite(rewrite) {
+                    continue;
+                }
                 for (child, _) in direct_child_counts(rewrite) {
                     if !children.contains(&child) {
                         children.push(child);
@@ -6853,10 +6926,10 @@ fn add_effective_count_cse_candidates(
 /// `Rc` and its real `consumer_count` — see the module docs' "Where
 /// `TargetSubDAG` discovery comes from" section for the full rationale.
 fn discover_targets<Id>(
-    roots: &[(Id, Rc<QueryExpr>)],
-    order: &mut Vec<*const QueryExpr>,
-    nodes: &mut HashMap<*const QueryExpr, Rc<QueryExpr>>,
-    counts: &mut HashMap<*const QueryExpr, usize>,
+    roots: &[(Id, Rc<OperatorNode>)],
+    order: &mut Vec<*const OperatorNode>,
+    nodes: &mut HashMap<*const OperatorNode, Rc<OperatorNode>>,
+    counts: &mut HashMap<*const OperatorNode, usize>,
 ) {
     for (_, root) in roots {
         walk(root, order, nodes, counts);
@@ -6865,17 +6938,17 @@ fn discover_targets<Id>(
 
 /// Scan `candidate`'s **children** (deliberately never `candidate`'s own
 /// top-level pointer — see the module docs' "Termination" section: a
-/// [`Replacement::Rewrite`]'s value is an alternative *for* the target that
+/// logical rewrite's value is an alternative *for* the target that
 /// proposed it, never a new target of its own) for any `Rc` not already
 /// known, appending each to `order`/`nodes`/`counts` so
 /// [`search_workload_with`]'s next round processes it. A no-op when every
 /// child is already known — the case both shipped strategies always produce
 /// (see that section).
 fn discover_new_descendant_targets(
-    candidate: &Rc<QueryExpr>,
-    order: &mut Vec<*const QueryExpr>,
-    nodes: &mut HashMap<*const QueryExpr, Rc<QueryExpr>>,
-    counts: &mut HashMap<*const QueryExpr, usize>,
+    candidate: &Rc<OperatorNode>,
+    order: &mut Vec<*const OperatorNode>,
+    nodes: &mut HashMap<*const OperatorNode, Rc<OperatorNode>>,
+    counts: &mut HashMap<*const OperatorNode, usize>,
 ) {
     walk_children(candidate, order, nodes, counts);
 }
@@ -6883,10 +6956,10 @@ fn discover_new_descendant_targets(
 /// Visit `node`: count this occurrence, and — the first time this exact
 /// `Rc` is seen — record it as a target and recurse into its children.
 fn walk(
-    node: &Rc<QueryExpr>,
-    order: &mut Vec<*const QueryExpr>,
-    nodes: &mut HashMap<*const QueryExpr, Rc<QueryExpr>>,
-    counts: &mut HashMap<*const QueryExpr, usize>,
+    node: &Rc<OperatorNode>,
+    order: &mut Vec<*const OperatorNode>,
+    nodes: &mut HashMap<*const OperatorNode, Rc<OperatorNode>>,
+    counts: &mut HashMap<*const OperatorNode, usize>,
 ) {
     let ptr = Rc::as_ptr(node);
     let already_visited = counts.contains_key(&ptr);
@@ -6898,61 +6971,25 @@ fn walk(
     }
 }
 
-/// `node`'s own **relational-skeleton** operator children — the same scope
-/// `asap_types::pre_asap::cse::share_common_sub_dags`/`rebuild_children`
-/// itself uses (see that module's "Algorithm" section) and
-/// `tests::count_consumers` mirrors for its own fixtures. Exhaustive over
-/// every `QueryExpr` variant: a new variant fails to compile here until this
-/// match is extended too.
+/// `node`'s own operator children ([`OperatorNode::children`]: operator
+/// inputs plus the operator nodes its scalar expressions read), the same
+/// scope `asap_types::ir::cse::share_common_sub_dags` itself uses and
+/// `tests::count_consumers` mirrors for its own fixtures. `Concat` is
+/// transparent: its branches are walked in place of it.
 fn walk_children(
-    node: &QueryExpr,
-    order: &mut Vec<*const QueryExpr>,
-    nodes: &mut HashMap<*const QueryExpr, Rc<QueryExpr>>,
-    counts: &mut HashMap<*const QueryExpr, usize>,
+    node: &OperatorNode,
+    order: &mut Vec<*const OperatorNode>,
+    nodes: &mut HashMap<*const OperatorNode, Rc<OperatorNode>>,
+    counts: &mut HashMap<*const OperatorNode, usize>,
 ) {
-    use QueryExpr::*;
-    match node {
-        Scan { .. } | PromqlScalarBridge(_) | EvalTimestamp | CurrentTimestamp => {}
-        PromqlVectorFromScalar(c) | PromqlScalarFromVector(c) => walk(c, order, nodes, counts),
-        PromqlRelabel { child, .. }
-        | PromqlInfoEnrich { child, .. }
-        | PromqlSeriesSample { child, .. }
-        | Filter { child, .. }
-        | Project { child, .. }
-        | Aggregate { child, .. }
-        | Dedup { child, .. }
-        | PromqlSubquery { child, .. }
-        | TimeRange { child, .. }
-        | TimeShift { child, .. }
-        | SQLWindowFunc { child, .. }
-        | Sort { child, .. }
-        | Limit { child, .. } => walk(child, order, nodes, counts),
-        Concat { children, .. } => {
-            for c in children {
-                walk_children(c, order, nodes, counts);
-            }
-        }
-        Join { left, right, .. } | SetOp { left, right, .. } => {
-            walk(left, order, nodes, counts);
-            walk(right, order, nodes, counts);
-        }
-        BinaryOp { lhs, rhs, .. } => {
-            walk(lhs, order, nodes, counts);
-            walk(rhs, order, nodes, counts);
-        }
-        Column(_)
-        | Literal(_)
-        | Compare { .. }
-        | BoolAnd(_)
-        | BoolOr(_)
-        | Not(_)
-        | IsNull(_)
-        | IsNotNull(_)
-        | Cast { .. }
-        | InList { .. }
-        | FunctionCall { .. }
-        | Arithmetic { .. }
-        | Case { .. } => {}
+    if let Some(NonASAPOp::Concat { children, .. }) = node.non_asap() {
+        for c in children {
+            walk_children(c, order, nodes, counts);
+        }
+        return;
+    }
+    for child in node.children() {
+        walk(child, order, nodes, counts);
     }
 }
 
@@ -6961,17 +6998,19 @@ mod tests {
     use super::*;
     use crate::accuracy::PropagationStats;
     use crate::cost_model::Cost;
-    use crate::test_support::lower_promql;
+    use crate::test_support::{agg, agg_per_entity, lower_promql, metric_scan, timed};
+    use asap_types::ir::operator_properties::{Reduction as ReductionTy, Source};
+    use asap_types::ir::TimeRangeKind;
     use asap_types::pre_asap::agg_intent::{
         agg_is_exact, default_cardinality, default_quantile, MathFunc, TimeFunc,
     };
-    use asap_types::pre_asap::query_expr::{Reduction as ReductionTy, Source};
     use asap_types::pre_asap::schema::{DataType, Field, Schema as SchemaTy};
+
     use asap_types::types::AccuracyTarget;
     use std::collections::HashMap;
 
     // Candidate shape without execution timing: what is computed, not where.
-    fn timing_free_shape(node: &Rc<SummaryNode>) -> serde_json::Value {
+    fn timing_free_shape(node: &Rc<OperatorNode>) -> serde_json::Value {
         fn strip(value: &mut serde_json::Value) {
             match value {
                 serde_json::Value::Object(fields) => {
@@ -6982,9 +7021,10 @@ mod tests {
                 _ => {}
             }
         }
-        let mut shape =
-            serde_json::to_value(asap_types::post_asap::compile_post_asap_dag(node).unwrap())
-                .unwrap();
+        let mut shape = serde_json::to_value(
+            asap_types::ir::export::compile_physical_asap_dag(&timed(node)).unwrap(),
+        )
+        .unwrap();
         strip(&mut shape);
         shape
     }
@@ -6996,7 +7036,7 @@ mod tests {
             ("sum by(job)(rate(m[1m]))", AccuracyTarget::Exact),
             ("topk by(job)(2, rate(m[1m]))", AccuracyTarget::Epsilon(0.1)),
         ] {
-            let root = Rc::new(lower_promql(query, accuracy));
+            let root = lower_promql(query, accuracy);
             let inventory = search_workload(vec![(0usize, root)])
                 .enumerate_candidate_dags(4096)
                 .unwrap();
@@ -7011,37 +7051,32 @@ mod tests {
         }
     }
 
-    // Grouped Sum over Rate readouts stays a summary state in the inventory,
+    // Grouped Sum over Rate evaluations stays a summary state in the inventory,
     // so lifecycle assignment can place it in precompute or at query time.
     #[test]
     fn grouped_rate_sum_inventory_keeps_sum_state_for_lifecycle_placement() {
-        let root = Rc::new(lower_promql(
-            "sum by(job)(rate(m[1m]))",
-            AccuracyTarget::Exact,
-        ));
+        let root = lower_promql("sum by(job)(rate(m[1m]))", AccuracyTarget::Exact);
         let inventory = search_workload(vec![(0usize, root)])
             .enumerate_candidate_dags(4096)
             .unwrap();
-        let is_exact = |node: &SummaryNode, kind: ExactKind| {
-            matches!(&node.expr, SummaryExpr::SummaryAgg {
+        let is_exact = |node: &OperatorNode, kind: ExactKind| {
+            matches!(&node.operator, Operator::ASAP(ASAPOp::SummaryAgg {
                 family: FieldDataType::ExactAggregate(k, _), ..
-            } if *k == kind)
+            }) if *k == kind)
         };
         assert!(inventory.candidates.iter().any(|forest| {
-            let SummaryExpr::ValueOperation { child: sum, .. } = &forest[0].1.expr else {
+            let Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child: sum }) = &forest[0].1.operator else {
                 return false;
             };
-            let SummaryExpr::SummaryAgg { child: rate, .. } = &sum.expr else {
+            let Operator::ASAP(ASAPOp::SummaryAgg { child: rate, .. }) = &sum.operator else {
                 return false;
             };
             is_exact(sum, ExactKind::Sum)
-                && matches!(&rate.expr, SummaryExpr::ValueOperation {
-                    child, operation: ValueOperation::FinalizeExactAccumulator, ..
-                } if is_exact(child, ExactKind::Rate))
+                && matches!(&rate.operator, Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child }) if is_exact(child, ExactKind::Rate))
         }));
     }
 
-    // Every exposed query result has a readout; internal accumulator frontiers stay states.
+    // Every exposed query result has a evaluation; internal accumulator frontiers stay states.
     #[test]
     fn query_candidate_roots_do_not_leak_exact_accumulator_state() {
         for query in [
@@ -7049,13 +7084,13 @@ mod tests {
             "sum by(job)(m)",
             "sum_over_time(m[1m])",
         ] {
-            let root = Rc::new(lower_promql(query, AccuracyTarget::Exact));
+            let root = lower_promql(query, AccuracyTarget::Exact);
             let space = search_workload(vec![(0usize, root.clone())]);
             let inventory = space.enumerate_candidate_dags(4096).unwrap();
             assert!(!inventory.candidates.is_empty());
-            let strategy = SketchAlgorithmStrategy::new(&DefaultCostModel);
+            let strategy = ASAPStrategies::new(&DefaultCostModel);
             for candidate in strategy.propose(&TargetSubDAG::new(&root)).candidates {
-                if let Replacement::Summary(node) = candidate.replacement {
+                if let Replacement::SubDAG(node) = candidate.replacement {
                     let output = finalize_query_candidate(node, &root).unwrap();
                     assert!(
                         output
@@ -7092,7 +7127,7 @@ mod tests {
 
     #[test]
     fn unpriced_inventory_retains_quantile_families_and_raw_execution() {
-        let query = Rc::new(agg(vec![2], default_quantile(0.9), metric_scan(&["job"])));
+        let query = agg(vec![2], default_quantile(0.9), metric_scan(&["job"]));
         let space = search_workload(vec![(0usize, query)]);
         let inventory = space.enumerate_candidate_dags(4096).unwrap();
         let roots = inventory
@@ -7105,7 +7140,7 @@ mod tests {
         assert!(inventory
             .candidates
             .iter()
-            .any(|forest| matches!(forest[0].1.expr, SummaryExpr::KeepPreAsap(_))));
+            .any(|forest| !forest[0].1.contains_asap()));
     }
 
     // Independent roots must not require materializing their Cartesian product.
@@ -7115,11 +7150,11 @@ mod tests {
             .map(|id| {
                 (
                     id,
-                    Rc::new(agg(
+                    agg(
                         vec![2],
                         default_quantile((id + 1) as f64 / 25.0),
                         metric_scan(&["job"]),
-                    )),
+                    ),
                 )
             })
             .collect();
@@ -7141,7 +7176,7 @@ mod tests {
             assert!(inventory
                 .candidates
                 .iter()
-                .any(|forest| matches!(forest[0].1.expr, SummaryExpr::KeepPreAsap(_))));
+                .any(|forest| !forest[0].1.contains_asap()));
         }
         assert!(space.enumerate_candidate_dags_for_root(&24, 4096).is_err());
         assert!(space.enumerate_candidate_dags_for_root(&0, 0).is_err());
@@ -7154,11 +7189,11 @@ mod tests {
             .map(|id| {
                 (
                     id,
-                    Rc::new(agg(
+                    agg(
                         vec![2],
                         default_quantile(0.5 + id as f64 * 0.4),
                         metric_scan(&["job"]),
-                    )),
+                    ),
                 )
             })
             .collect();
@@ -7180,30 +7215,31 @@ mod tests {
 
     #[test]
     fn inventory_budget_never_returns_a_silent_partial_search() {
-        let query = Rc::new(agg(vec![2], default_quantile(0.9), metric_scan(&["job"])));
+        let query = agg(vec![2], default_quantile(0.9), metric_scan(&["job"]));
         let space = search_workload(vec![(0usize, query)]);
         assert!(space.enumerate_candidate_dags(0).is_err());
     }
 
     fn equi_pred(left: ColumnId, right: ColumnId) -> Predicate {
-        Predicate(Rc::new(QueryExpr::Compare {
-            left: Rc::new(QueryExpr::Column(left)),
+        Predicate(ScalarExpr::Compare {
+            left: Box::new(ScalarExpr::Column(left)),
             op: asap_types::pre_asap::CompareOpKind::Eq,
-            right: Rc::new(QueryExpr::Column(right)),
-        }))
+            right: Box::new(ScalarExpr::Column(right)),
+            semantics: asap_types::ir::ExprSemantics::Sql,
+        })
     }
 
     // Finite samples can overflow a sum although their native average is finite.
     #[test]
     fn temporal_average_requires_finite_division_guard() {
-        let root = Rc::new(lower_promql("avg_over_time(a[5m])", AccuracyTarget::Exact));
+        let root = lower_promql("avg_over_time(a[5m])", AccuracyTarget::Exact);
         let candidates =
-            SketchAlgorithmStrategy::default_cost_model().replacements(&TargetSubDAG::new(&root));
+            ASAPStrategies::default_cost_model().replacements(&TargetSubDAG::new(&root));
         let operator = candidates
             .iter()
             .find_map(|c| match &c.replacement {
-                Replacement::Summary(node) => match &node.expr {
-                    SummaryExpr::BinaryOp { operator, .. } => Some(operator),
+                Replacement::SubDAG(node) => match &node.operator {
+                    Operator::NonASAP(NonASAPOp::BinaryOp { operator, .. }) => Some(operator),
                     _ => None,
                 },
                 _ => None,
@@ -7221,20 +7257,20 @@ mod tests {
     // Approximate requests also admit exact temporal ranking candidates.
     #[test]
     fn approximate_temporal_topk_admits_exact_maintained_values() {
-        let root = Rc::new(lower_promql(
+        let root = lower_promql(
             "topk by(job)(1,count_over_time(a[5m]))",
             AccuracyTarget::EpsilonDelta {
                 epsilon: 0.01,
                 delta: 0.01,
             },
-        ));
+        );
         let planning_inputs =
             CandidatePlanningInputs::with_default_accuracy(&crate::cost_model::DefaultCostModel);
         let node = exact_topk_over_temporal_values(&root, planning_inputs)
             .unwrap()
             .expect("exact ranking is legal for an approximate request");
         assert!(node.guarantee.as_ref().unwrap().is_exact());
-        asap_types::post_asap::compile_post_asap_dag(&node).unwrap();
+        crate::test_support::time_and_export(&node).unwrap();
     }
 
     // Exact Top-K consumes the Planner's maintained temporal values.
@@ -7244,7 +7280,7 @@ mod tests {
             "topk(5, sum_over_time(a[5m]))",
             "topk by(job)(5, count_over_time(a[5m]))",
         ] {
-            let root = Rc::new(lower_promql(query, AccuracyTarget::Exact));
+            let root = lower_promql(query, AccuracyTarget::Exact);
             let planning_inputs = CandidatePlanningInputs::with_default_accuracy(
                 &crate::cost_model::DefaultCostModel,
             );
@@ -7252,29 +7288,21 @@ mod tests {
                 .unwrap()
                 .expect("exact Top-K candidate");
             assert!(node.guarantee.as_ref().unwrap().is_exact());
-            let SummaryExpr::ValueOperation {
+            let Operator::NonASAP(NonASAPOp::Limit {
                 child: sorted,
-                operation:
-                    ValueOperation::Limit {
-                        n,
-                        offset,
-                        partition_by,
-                    },
-                ..
-            } = &node.expr
+                n,
+                offset,
+                partition_by,
+            }) = &node.operator
             else {
                 panic!("temporal TopK must compose Sort and Limit");
             };
-            assert_eq!((*n, *offset), (5, 0));
-            let SummaryExpr::ValueOperation {
-                operation:
-                    ValueOperation::Sort {
-                        keys,
-                        partition_by: sort_groups,
-                    },
+            assert_eq!((*n, *offset), (Some(5), 0));
+            let Operator::NonASAP(NonASAPOp::Sort {
+                keys,
+                partition_by: sort_groups,
                 child: values,
-                ..
-            } = &sorted.expr
+            }) = &sorted.operator
             else {
                 panic!("Limit must consume sorted temporal values");
             };
@@ -7286,7 +7314,7 @@ mod tests {
             assert_eq!(keys.len(), 1);
             assert!(!keys[0].ascending);
             assert_eq!(node.schema, values.schema);
-            asap_types::post_asap::compile_post_asap_dag(&node).unwrap();
+            crate::test_support::time_and_export(&node).unwrap();
         }
     }
 
@@ -7297,7 +7325,7 @@ mod tests {
         impl AccuracyEvidenceProvider for Domain {
             fn quantile_input_domain(
                 &self,
-                _: &QueryExpr,
+                _: &OperatorNode,
             ) -> Option<crate::accuracy::QuantileInputDomain> {
                 Some(crate::accuracy::QuantileInputDomain {
                     lower: 1.0,
@@ -7319,7 +7347,7 @@ mod tests {
             "avg_over_time(a[5m]) / quantile_over_time(0.5,a[5m])",
             "quantile_over_time(0.5,a[5m]) / avg_over_time(a[5m])",
         ] {
-            let root = Rc::new(lower_promql(query, target.clone()));
+            let root = lower_promql(query, target.clone());
             let node = realize_binary(&root, inputs, Some(&target))
                 .unwrap()
                 .expect("bounded ratio candidate");
@@ -7334,10 +7362,10 @@ mod tests {
             epsilon: 0.01,
             delta: 0.01,
         };
-        let root = Rc::new(lower_promql(
+        let root = lower_promql(
             "quantile_over_time(0.5,a[5m]) / quantile_over_time(0.9,a[5m])",
             target.clone(),
-        ));
+        );
         let planning_inputs =
             CandidatePlanningInputs::with_default_accuracy(&crate::cost_model::DefaultCostModel);
         let candidate = realize_binary(&root, planning_inputs, Some(&target))
@@ -7345,10 +7373,10 @@ mod tests {
             .expect("direct quantile ratio candidate");
         assert!(candidate.guarantee.is_none());
 
-        let other = Rc::new(lower_promql(
+        let other = lower_promql(
             "avg_over_time(a[5m]) / quantile_over_time(0.5,a[5m])",
             target.clone(),
-        ));
+        );
         assert!(realize_binary(&other, planning_inputs, Some(&target))
             .unwrap()
             .is_none());
@@ -7367,11 +7395,65 @@ mod tests {
 
     #[test]
     fn relational_join_is_exact_only_when_both_inputs_are_exact() {
-        let exact = ResultGuarantee::exact("test exact input");
-        assert!(relational_join_guarantee(Some(&exact), Some(&exact))
-            .is_some_and(|guarantee| guarantee.is_exact()));
-        assert!(relational_join_guarantee(Some(&exact), None).is_none());
-        assert!(relational_join_guarantee(None, Some(&exact)).is_none());
+        // `relational_join_guarantee` folded into assembly's generic
+        // "keep the operator, assemble its children" branch: an assembled
+        // inner equi-`Join` is exact exactly when both assembled inputs are.
+        let join = |left_intent: AggIntent, right_intent: AggIntent| {
+            let left = agg(vec![2], left_intent, metric_scan(&["job"]));
+            let right = agg(
+                vec![2],
+                right_intent,
+                crate::test_support::scan("n", metric_scan(&["job"]).schema.clone()),
+            );
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Join {
+                kind: asap_types::ir::operator_properties::JoinKind::Inner,
+                pred: equi_pred(0, 2),
+                left,
+                right,
+            }))
+            .unwrap()
+        };
+        let is_exact = |node: &OperatorNode| {
+            node.guarantee
+                .as_ref()
+                .is_some_and(ResultGuarantee::is_exact)
+        };
+        for (root, both_exact_expected) in [
+            (
+                join(AggIntent::Sum { col: None }, AggIntent::Sum { col: None }),
+                true,
+            ),
+            (
+                join(AggIntent::Sum { col: None }, quantile_eps_intent(0.5, 0.05)),
+                false,
+            ),
+        ] {
+            let space = search_workload(vec![(0usize, Rc::clone(&root))]);
+            let assembled = space
+                .global_selection(&DefaultCostModel)
+                .assemble_selected_query(&space.roots[0].1)
+                .unwrap()
+                .unwrap();
+            let Some(NonASAPOp::Join { left, right, .. }) = assembled.non_asap() else {
+                panic!("the join is kept and its inputs assembled: {assembled:?}");
+            };
+            assert_eq!(
+                is_exact(&assembled),
+                is_exact(left) && is_exact(right),
+                "join guarantee must be exact iff both inputs are exact"
+            );
+            if both_exact_expected {
+                assert!(is_exact(&assembled), "exact inputs give an exact join");
+            }
+        }
+    }
+
+    fn quantile_eps_intent(q: f64, e: f64) -> AggIntent {
+        AggIntent::Quantile {
+            col: None,
+            q,
+            accuracy: AccuracyTarget::Epsilon(e),
+        }
     }
 
     fn eps(e: f64) -> AccuracyTarget {
@@ -7921,68 +8003,44 @@ mod tests {
         );
     }
 
-    // ── SketchAlgorithmStrategy / SharedSubDAGStrategy fixtures ───────────
-
-    fn metric_scan(labels: &[&str]) -> QueryExpr {
-        let mut columns = vec![
-            Field::plain("ts", DataType::Timestamp, false),
-            Field::plain("value", DataType::Float64, false),
-        ];
-        columns.extend(
-            labels
-                .iter()
-                .map(|n| Field::plain(*n, DataType::Utf8, true)),
-        );
-        QueryExpr::Scan {
-            source: Source::TimeSeries { metric: "m".into() },
-            predicates: vec![],
-            schema: SchemaTy::with_time_index(columns, 0, vec![]),
-        }
-    }
-
-    fn agg(by: Vec<usize>, intent: AggIntent, child: QueryExpr) -> QueryExpr {
-        QueryExpr::Aggregate {
-            reduction: ReductionTy::by(by),
-            measures: vec![intent],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(child),
-        }
-    }
+    // ── ASAPStrategies / SharedSubDAGStrategy fixtures ───────────
 
-    // ── SketchAlgorithmStrategy ─────────────────────────────────────────────
+    // ── ASAPStrategies ─────────────────────────────────────────────
 
     #[test]
     fn matches_a_bindable_aggregate() {
-        let q = Rc::new(agg(vec![2], default_quantile(0.99), metric_scan(&["job"])));
+        let q = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
         let target = TargetSubDAG::new(&q);
-        assert!(SketchAlgorithmStrategy::default_cost_model().matches(&target));
+        assert!(ASAPStrategies::default_cost_model().matches(&target));
     }
 
     #[test]
     fn does_not_match_a_multi_intent_or_having_aggregate() {
-        let strategy = SketchAlgorithmStrategy::default_cost_model();
-
-        let multi = Rc::new(QueryExpr::Aggregate {
-            reduction: ReductionTy::by(vec![2]),
-            measures: vec![AggIntent::Sum { col: None }, AggIntent::Avg { col: None }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(metric_scan(&["job"])),
-        });
+        let strategy = ASAPStrategies::default_cost_model();
+
+        let multi =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+                reduction: ReductionTy::by(vec![2]),
+                measures: vec![AggIntent::Sum { col: None }, AggIntent::Avg { col: None }],
+                output_names: vec![],
+                filters: vec![],
+                having: None,
+                child: metric_scan(&["job"]),
+            }))
+            .unwrap();
         let target = TargetSubDAG::new(&multi);
         assert!(!strategy.matches(&target));
         assert!(strategy.replacements(&target).is_empty());
 
-        let mut having_q = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
-        if let QueryExpr::Aggregate { having, .. } = &mut having_q {
-            *having = Some(asap_types::pre_asap::query_expr::Predicate(Rc::new(
-                QueryExpr::Literal(asap_types::pre_asap::expr_ir::ScalarValue::Boolean(true)),
-            )));
-        }
-        let having_q = Rc::new(having_q);
+        let having_q = crate::test_support::aggregate(
+            ReductionTy::by(vec![2]),
+            vec![default_quantile(0.99)],
+            vec![],
+            Some(asap_types::ir::Predicate(ScalarExpr::Literal(
+                asap_types::pre_asap::expr_ir::ScalarValue::Boolean(true),
+            ))),
+            metric_scan(&["job"]),
+        );
         let target = TargetSubDAG::new(&having_q);
         assert!(!strategy.matches(&target));
         assert!(strategy.replacements(&target).is_empty());
@@ -7990,10 +8048,10 @@ mod tests {
 
     #[test]
     fn does_not_match_a_non_aggregate_node() {
-        let scan = Rc::new(metric_scan(&["job"]));
+        let scan = metric_scan(&["job"]);
         let target = TargetSubDAG::new(&scan);
-        assert!(!SketchAlgorithmStrategy::default_cost_model().matches(&target));
-        assert!(SketchAlgorithmStrategy::default_cost_model()
+        assert!(!ASAPStrategies::default_cost_model().matches(&target));
+        assert!(ASAPStrategies::default_cost_model()
             .replacements(&target)
             .is_empty());
     }
@@ -8001,11 +8059,11 @@ mod tests {
     #[test]
     fn approximate_quantile_enumerates_every_summary_candidate() {
         // Quantile's candidate list is [Kll, DDSketch] (summary_candidates) —
-        // every entry must come back as its own bound SummaryNode candidate,
+        // every entry must come back as its own bound summary candidate,
         // not just Kll (the CostModel-ranked head realizations_for_intent commits to).
-        let q = Rc::new(agg(vec![2], default_quantile(0.99), metric_scan(&["job"])));
+        let q = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
         let target = TargetSubDAG::new(&q);
-        let replacements = SketchAlgorithmStrategy::default_cost_model().replacements(&target);
+        let replacements = ASAPStrategies::default_cost_model().replacements(&target);
         assert_eq!(
             replacements.len(),
             2,
@@ -8015,8 +8073,8 @@ mod tests {
         let kinds: Vec<SketchAlgorithm> = replacements
             .iter()
             .map(|r| match &r.replacement {
-                Replacement::Summary(node) => summary_family_algorithm(node),
-                Replacement::Rewrite(_) | Replacement::ExactComposition(_) => {
+                Replacement::SubDAG(node) => summary_family_algorithm(node),
+                Replacement::ExactComposition(_) => {
                     panic!("expected a Summary replacement")
                 }
             })
@@ -8031,14 +8089,14 @@ mod tests {
 
     #[test]
     fn cardinality_epsilon_delta_keeps_unknown_accuracy_candidates() {
-        let q = Rc::new(agg(vec![2], default_cardinality(), metric_scan(&["job"])));
+        let q = agg(vec![2], default_cardinality(), metric_scan(&["job"]));
         let target = TargetSubDAG::new(&q);
-        let replacements = SketchAlgorithmStrategy::default_cost_model().replacements(&target);
+        let replacements = ASAPStrategies::default_cost_model().replacements(&target);
         let kinds: Vec<SketchAlgorithm> = replacements
             .iter()
             .map(|r| match &r.replacement {
-                Replacement::Summary(node) => summary_family_algorithm(node),
-                Replacement::Rewrite(_) | Replacement::ExactComposition(_) => {
+                Replacement::SubDAG(node) => summary_family_algorithm(node),
+                Replacement::ExactComposition(_) => {
                     panic!("expected a Summary replacement")
                 }
             })
@@ -8053,7 +8111,7 @@ mod tests {
             ]
         );
 
-        let q = Rc::new(agg(
+        let q = agg(
             vec![2],
             AggIntent::Cardinality {
                 cols: vec![],
@@ -8063,13 +8121,13 @@ mod tests {
                 },
             },
             metric_scan(&["job"]),
-        ));
-        let kinds: Vec<_> = SketchAlgorithmStrategy::default_cost_model()
+        );
+        let kinds: Vec<_> = ASAPStrategies::default_cost_model()
             .replacements(&TargetSubDAG::new(&q))
             .iter()
             .map(|r| match &r.replacement {
-                Replacement::Summary(node) => summary_family_algorithm(node),
-                Replacement::Rewrite(_) | Replacement::ExactComposition(_) => {
+                Replacement::SubDAG(node) => summary_family_algorithm(node),
+                Replacement::ExactComposition(_) => {
                     panic!("expected a Summary replacement")
                 }
             })
@@ -8094,35 +8152,28 @@ mod tests {
             q: 0.99,
             accuracy: AccuracyTarget::Exact,
         };
-        let q = Rc::new(agg(vec![2], intent, metric_scan(&["job"])));
+        let q = agg(vec![2], intent, metric_scan(&["job"]));
         let target = TargetSubDAG::new(&q);
-        let replacements = SketchAlgorithmStrategy::default_cost_model().replacements(&target);
+        let replacements = ASAPStrategies::default_cost_model().replacements(&target);
         assert_eq!(replacements.len(), 1, "{replacements:?}");
         assert!(matches!(
             &replacements[0].replacement,
-            Replacement::Summary(node) if matches!(
-                node.expr,
-                asap_types::post_asap::SummaryExpr::KeepPreAsap(_)
-            )
+            Replacement::SubDAG(node) if !node.contains_asap()
         ));
         assert!(replacements[0].rationale.contains("only realization"));
     }
 
     #[test]
     fn exact_mergeable_intent_yields_exactly_one_accumulator_candidate() {
-        let q = Rc::new(agg(
-            vec![2],
-            AggIntent::Sum { col: None },
-            metric_scan(&["job"]),
-        ));
+        let q = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
         let target = TargetSubDAG::new(&q);
-        let replacements = SketchAlgorithmStrategy::default_cost_model().replacements(&target);
+        let replacements = ASAPStrategies::default_cost_model().replacements(&target);
         assert_eq!(replacements.len(), 1, "{replacements:?}");
         assert!(matches!(
             &replacements[0].replacement,
-            Replacement::Summary(node) if matches!(
-                node.expr,
-                asap_types::post_asap::SummaryExpr::SummaryAgg { .. }
+            Replacement::SubDAG(node) if matches!(
+                node.operator,
+                Operator::ASAP(ASAPOp::SummaryAgg { .. })
             )
         ));
     }
@@ -8149,15 +8200,15 @@ mod tests {
 
     #[test]
     fn custom_cost_model_still_enumerates_every_candidate_not_just_its_own_pick() {
-        let q = Rc::new(agg(vec![2], default_quantile(0.99), metric_scan(&["job"])));
+        let q = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
         let target = TargetSubDAG::new(&q);
         let custom = PreferDDSketch;
-        let replacements = SketchAlgorithmStrategy::new(&custom).replacements(&target);
+        let replacements = ASAPStrategies::new(&custom).replacements(&target);
         let kinds: Vec<SketchAlgorithm> = replacements
             .iter()
             .map(|r| match &r.replacement {
-                Replacement::Summary(node) => summary_family_algorithm(node),
-                Replacement::Rewrite(_) | Replacement::ExactComposition(_) => {
+                Replacement::SubDAG(node) => summary_family_algorithm(node),
+                Replacement::ExactComposition(_) => {
                     panic!("expected a Summary replacement")
                 }
             })
@@ -8181,9 +8232,9 @@ mod tests {
         // so this test injects `RankAdditiveModel` to admit the composition
         // and keep exercising the per-node enumeration property it is about.
         let inner = agg(vec![2], default_quantile(0.5), metric_scan(&["job"]));
-        let outer = Rc::new(agg(vec![], default_quantile(0.99), inner));
+        let outer = agg(vec![], default_quantile(0.99), inner);
         let target = TargetSubDAG::new(&outer);
-        let replacements = SketchAlgorithmStrategy::new_with_planning_inputs(
+        let replacements = ASAPStrategies::new_with_planning_inputs(
             &DefaultCostModel,
             &RankAdditiveModel,
             &EqualSplitAllocator,
@@ -8191,9 +8242,9 @@ mod tests {
         .replacements(&target);
 
         assert_eq!(replacements.len(), 2, "{replacements:?}");
-        assert!(replacements
-            .iter()
-            .all(|candidate| { matches!(candidate.replacement, Replacement::Summary(_)) }));
+        assert!(replacements.iter().all(|candidate| {
+            matches!(&candidate.replacement, Replacement::SubDAG(n) if n.contains_asap())
+        }));
         // The inner target is still independently enumerated and ranked —
         // a custom cost model that prefers DDSketch for it is honored, and
         // nothing about the outer target's choice reaches it.
@@ -8201,7 +8252,7 @@ mod tests {
             vec![("q", Rc::clone(&outer))],
             &default_strategies_with(&PreferDDSketchViaCostModel),
         );
-        let QueryExpr::Aggregate { child, .. } = space.roots[0].1.as_ref() else {
+        let Some(NonASAPOp::Aggregate { child, .. }) = space.roots[0].1.non_asap() else {
             unreachable!()
         };
         let inner_group = space
@@ -8211,7 +8262,7 @@ mod tests {
             .candidates
             .iter()
             .filter_map(|c| match &c.replacement {
-                Replacement::Summary(node) => sketch_kind_of(node),
+                Replacement::SubDAG(node) => sketch_kind_of(node),
                 _ => None,
             })
             .collect();
@@ -8225,12 +8276,12 @@ mod tests {
     /// The `FieldDataType`'s committed `SketchAlgorithm`, from the top
     /// `SummaryAgg` reachable under a (possibly `SummaryEstimate`-wrapped)
     /// bound root.
-    fn summary_family_algorithm(node: &SummaryNode) -> SketchAlgorithm {
-        match &node.expr {
-            asap_types::post_asap::SummaryExpr::SummaryEstimate { summary_input, .. } => {
+    fn summary_family_algorithm(node: &OperatorNode) -> SketchAlgorithm {
+        match &node.operator {
+            Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) => {
                 summary_family_algorithm(summary_input)
             }
-            asap_types::post_asap::SummaryExpr::SummaryAgg { family, .. } => match family {
+            Operator::ASAP(ASAPOp::SummaryAgg { family, .. }) => match family {
                 asap_types::post_asap::FieldDataType::Sketch(kind, _) => kind.algorithm().clone(),
                 other => panic!("expected a Sketch family, got {other:?}"),
             },
@@ -8242,11 +8293,7 @@ mod tests {
 
     #[test]
     fn does_not_match_a_single_consumer_target() {
-        let q = Rc::new(agg(
-            vec![2],
-            AggIntent::Sum { col: None },
-            metric_scan(&["job"]),
-        ));
+        let q = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
         let target = TargetSubDAG::new(&q);
         assert_eq!(target.consumer_count, 1);
         assert!(!SharedSubDAGStrategy.matches(&target));
@@ -8255,11 +8302,7 @@ mod tests {
 
     #[test]
     fn two_or_more_consumers_yields_the_share_vs_independent_pair() {
-        let q = Rc::new(agg(
-            vec![2],
-            AggIntent::Sum { col: None },
-            metric_scan(&["job"]),
-        ));
+        let q = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
         let target = TargetSubDAG::with_consumer_count(&q, 2);
         assert!(SharedSubDAGStrategy.matches(&target));
 
@@ -8267,7 +8310,7 @@ mod tests {
         assert_eq!(replacements.len(), 2, "{replacements:?}");
 
         let shared = match &replacements[0].replacement {
-            Replacement::Rewrite(rc) => rc,
+            Replacement::SubDAG(rc) => rc,
             other => panic!("expected a Rewrite replacement, got {other:?}"),
         };
         assert!(
@@ -8277,7 +8320,7 @@ mod tests {
         assert!(replacements[0].rationale.contains("build once and share"));
 
         let independent = match &replacements[1].replacement {
-            Replacement::Rewrite(rc) => rc,
+            Replacement::SubDAG(rc) => rc,
             other => panic!("expected a Rewrite replacement, got {other:?}"),
         };
         assert!(
@@ -8293,11 +8336,7 @@ mod tests {
 
     #[test]
     fn three_consumers_are_reported_verbatim_in_both_rationales() {
-        let q = Rc::new(agg(
-            vec![2],
-            AggIntent::Sum { col: None },
-            metric_scan(&["job"]),
-        ));
+        let q = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
         let target = TargetSubDAG::with_consumer_count(&q, 3);
         let replacements = SharedSubDAGStrategy.replacements(&target);
         assert!(replacements[0].rationale.contains('3'));
@@ -8307,13 +8346,13 @@ mod tests {
     /// Builds realistic multi-consumer `TargetSubDAG`s the same way this
     /// module's own [`discover_targets`]/`walk` does: dedup by `Rc::as_ptr`,
     /// walking only the relational-skeleton operator children
-    /// `asap_types::pre_asap::cse::share_common_sub_dags` itself scopes to,
+    /// `asap_types::ir::cse::share_common_sub_dags` itself scopes to,
     /// so a shared node nested below another shared node is only ever
     /// counted at the highest (maximal) point sharing starts. Test-only:
     /// this module deliberately does not ship a workload-wide discovery
     /// pass of its own (see the module docs' "Non-goals").
-    fn count_consumers(roots: &[Rc<QueryExpr>]) -> HashMap<*const QueryExpr, usize> {
-        fn walk(node: &Rc<QueryExpr>, counts: &mut HashMap<*const QueryExpr, usize>) {
+    fn count_consumers(roots: &[Rc<OperatorNode>]) -> HashMap<*const OperatorNode, usize> {
+        fn walk(node: &Rc<OperatorNode>, counts: &mut HashMap<*const OperatorNode, usize>) {
             let ptr = Rc::as_ptr(node);
             let already_visited = counts.contains_key(&ptr);
             *counts.entry(ptr).or_insert(0) += 1;
@@ -8321,50 +8360,15 @@ mod tests {
                 walk_children(node, counts);
             }
         }
-        fn walk_children(node: &QueryExpr, counts: &mut HashMap<*const QueryExpr, usize>) {
-            use QueryExpr::*;
-            match node {
-                Scan { .. } | PromqlScalarBridge(_) | EvalTimestamp | CurrentTimestamp => {}
-                PromqlVectorFromScalar(c) | PromqlScalarFromVector(c) => walk(c, counts),
-                PromqlRelabel { child, .. }
-                | PromqlInfoEnrich { child, .. }
-                | PromqlSeriesSample { child, .. }
-                | Filter { child, .. }
-                | Project { child, .. }
-                | Aggregate { child, .. }
-                | Dedup { child, .. }
-                | PromqlSubquery { child, .. }
-                | TimeRange { child, .. }
-                | TimeShift { child, .. }
-                | SQLWindowFunc { child, .. }
-                | Sort { child, .. }
-                | Limit { child, .. } => walk(child, counts),
-                Concat { children, .. } => {
-                    for c in children {
-                        walk_children(c, counts);
-                    }
-                }
-                Join { left, right, .. } | SetOp { left, right, .. } => {
-                    walk(left, counts);
-                    walk(right, counts);
-                }
-                BinaryOp { lhs, rhs, .. } => {
-                    walk(lhs, counts);
-                    walk(rhs, counts);
+        fn walk_children(node: &OperatorNode, counts: &mut HashMap<*const OperatorNode, usize>) {
+            if let Some(NonASAPOp::Concat { children, .. }) = node.non_asap() {
+                for c in children {
+                    walk_children(c, counts);
                 }
-                Column(_)
-                | Literal(_)
-                | Compare { .. }
-                | BoolAnd(_)
-                | BoolOr(_)
-                | Not(_)
-                | IsNull(_)
-                | IsNotNull(_)
-                | Cast { .. }
-                | InList { .. }
-                | FunctionCall { .. }
-                | Arithmetic { .. }
-                | Case { .. } => {}
+                return;
+            }
+            for child in node.children() {
+                walk(child, counts);
             }
         }
 
@@ -8382,13 +8386,13 @@ mod tests {
         // Sum aggregate over the same scan, built independently at each root.
         let a = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
         let b = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
-        let shared = asap_types::pre_asap::cse::share_common_sub_dags(vec![("a", a), ("b", b)]);
+        let shared = asap_types::ir::cse::share_common_sub_dags(vec![("a", a), ("b", b)]);
         let [(_, ra), (_, rb)] = shared.as_slice() else {
             panic!("expected 2 roots");
         };
         assert!(Rc::ptr_eq(ra, rb), "fixture sanity: the two roots merged");
 
-        let roots: Vec<Rc<QueryExpr>> = shared.into_iter().map(|(_, rc)| rc).collect();
+        let roots: Vec<Rc<OperatorNode>> = shared.into_iter().map(|(_, rc)| rc).collect();
         let counts = count_consumers(&roots);
         let count = counts[&Rc::as_ptr(&roots[0])];
         assert_eq!(count, 2);
@@ -8416,7 +8420,7 @@ mod tests {
                 delta: 0.01,
             },
         };
-        let root = Rc::new(agg(vec![2], intent, metric_scan(&["job"])));
+        let root = agg(vec![2], intent, metric_scan(&["job"]));
         let space = search_workload(vec![("q", root)]);
 
         // One group for the Aggregate, one for its Scan child.
@@ -8424,7 +8428,7 @@ mod tests {
 
         let agg_group = space
             .target_subdag_candidates()
-            .find(|g| matches!(g.target.as_ref(), QueryExpr::Aggregate { .. }))
+            .find(|g| matches!(g.target.non_asap(), Some(NonASAPOp::Aggregate { .. })))
             .expect("an Aggregate group must be discovered");
         assert_eq!(agg_group.consumer_count, 1);
         assert_eq!(
@@ -8436,24 +8440,26 @@ mod tests {
         assert!(agg_group
             .candidates
             .iter()
-            .all(|c| matches!(c.replacement, Replacement::Summary(_))));
+            .all(|c| matches!(&c.replacement, Replacement::SubDAG(n) if n.contains_asap())));
         assert_eq!(
             agg_group
                 .candidates
                 .iter()
                 .filter(|candidate| {
-                    let Replacement::Summary(node) = &candidate.replacement else {
+                    let Replacement::SubDAG(node) = &candidate.replacement else {
                         return false;
                     };
-                    let SummaryExpr::SummaryEstimate { summary_input, .. } = &node.expr else {
+                    let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) =
+                        &node.operator
+                    else {
                         return false;
                     };
                     matches!(
-                        &summary_input.expr,
-                        SummaryExpr::SummaryAgg {
+                        &summary_input.operator,
+                        Operator::ASAP(ASAPOp::SummaryAgg {
                             grouping: GroupingStrategy::SharedMultiSubpopulation { .. },
                             ..
-                        }
+                        })
                     )
                 })
                 .count(),
@@ -8477,7 +8483,7 @@ mod tests {
 
         let scan_group = space
             .target_subdag_candidates()
-            .find(|g| matches!(g.target.as_ref(), QueryExpr::Scan { .. }))
+            .find(|g| matches!(g.target.non_asap(), Some(NonASAPOp::Scan { .. })))
             .expect("a Scan group must be discovered");
         assert_eq!(scan_group.consumer_count, 1);
         assert!(
@@ -8488,20 +8494,20 @@ mod tests {
 
     #[test]
     fn cardinality_group_keeps_all_four_candidates() {
-        let root = Rc::new(agg(vec![2], default_cardinality(), metric_scan(&["job"])));
+        let root = agg(vec![2], default_cardinality(), metric_scan(&["job"]));
         let space = search_workload(vec![("q", root)]);
         let agg_group = space
             .target_subdag_candidates()
-            .find(|g| matches!(g.target.as_ref(), QueryExpr::Aggregate { .. }))
+            .find(|g| matches!(g.target.non_asap(), Some(NonASAPOp::Aggregate { .. })))
             .unwrap();
         assert_eq!(agg_group.candidates.len(), 4);
         assert!(agg_group.candidates.iter().any(|candidate| matches!(
             &candidate.replacement,
-            Replacement::Summary(node) if node.guarantee.is_none()
+            Replacement::SubDAG(node) if node.guarantee.is_none()
                 && candidate.has_missing_accuracy_evidence()
         )));
 
-        let root = Rc::new(agg(vec![2], default_cardinality(), metric_scan(&["job"])));
+        let root = agg(vec![2], default_cardinality(), metric_scan(&["job"]));
         let targeted = search_workload_with_targets(
             vec![(
                 "q",
@@ -8522,7 +8528,7 @@ mod tests {
             .iter()
             .any(|candidate| matches!(
                 &candidate.replacement,
-                Replacement::Summary(node) if node.guarantee.is_none()
+                Replacement::SubDAG(node) if node.guarantee.is_none()
                     && candidate.has_missing_accuracy_evidence()
             )));
         assert!(!targeted
@@ -8535,7 +8541,7 @@ mod tests {
         let exact_target = search_workload_with_targets(
             vec![(
                 "q",
-                Rc::new(agg(vec![2], default_cardinality(), metric_scan(&["job"]))),
+                agg(vec![2], default_cardinality(), metric_scan(&["job"])),
                 Some(AccuracyTarget::Exact),
             )],
             &default_strategies(),
@@ -8554,11 +8560,11 @@ mod tests {
         // Two independently-built, structurally identical Sum aggregates:
         // share_common_sub_dags (run inside search_workload) collapses them
         // onto one Rc with consumer_count 2, so this single group should
-        // carry SketchAlgorithmStrategy's one ExactAggregate candidate *and*
+        // carry ASAPStrategies's one ExactAggregate candidate *and*
         // SharedSubDAGStrategy's share-vs-recompute pair.
         let a = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
         let b = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
-        let space = search_workload(vec![("a", Rc::new(a)), ("b", Rc::new(b))]);
+        let space = search_workload(vec![("a", a), ("b", b)]);
 
         // roots[0] and roots[1] must have merged onto the same Rc.
         assert!(Rc::ptr_eq(&space.roots[0].1, &space.roots[1].1));
@@ -8572,15 +8578,17 @@ mod tests {
             group.candidates
         );
 
+        // Old `Replacement::Summary` ↔ a `Subtree` containing an ASAP node;
+        // old `Replacement::Rewrite` ↔ a pure pre-ASAP `Subtree`.
         let summary_count = group
             .candidates
             .iter()
-            .filter(|c| matches!(c.replacement, Replacement::Summary(_)))
+            .filter(|c| matches!(&c.replacement, Replacement::SubDAG(n) if n.contains_asap()))
             .count();
         let rewrite_count = group
             .candidates
             .iter()
-            .filter(|c| matches!(c.replacement, Replacement::Rewrite(_)))
+            .filter(|c| matches!(&c.replacement, Replacement::SubDAG(n) if !n.contains_asap()))
             .count();
         assert_eq!(summary_count, 1);
         assert_eq!(rewrite_count, 2);
@@ -8589,11 +8597,11 @@ mod tests {
         // (the "false-positive dedup" failure mode `is_duplicate_rewrite`
         // exists to prevent).
         let one_is_the_target = group.candidates.iter().any(
-            |c| matches!(&c.replacement, Replacement::Rewrite(rc) if Rc::ptr_eq(rc, &group.target)),
+            |c| matches!(&c.replacement, Replacement::SubDAG(rc) if Rc::ptr_eq(rc, &group.target)),
+        );
+        let one_is_not = group.candidates.iter().any(
+            |c| matches!(&c.replacement, Replacement::SubDAG(rc) if !Rc::ptr_eq(rc, &group.target)),
         );
-        let one_is_not = group.candidates.iter().any(|c| {
-            matches!(&c.replacement, Replacement::Rewrite(rc) if !Rc::ptr_eq(rc, &group.target))
-        });
         assert!(one_is_the_target && one_is_not);
     }
 
@@ -8604,27 +8612,27 @@ mod tests {
         // walking the whole DAG, not just root-level pointer identity
         // (a naive whole-root-only consumer-count pass would miss this;
         // this module's discover_targets must not).
+        use asap_types::ir::Predicate;
         use asap_types::pre_asap::expr_ir::ScalarValue;
-        use asap_types::pre_asap::query_expr::Predicate;
 
-        let shared = Rc::new(agg(
-            vec![2],
-            AggIntent::Sum { col: None },
-            metric_scan(&["job"]),
-        ));
+        let shared = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
         // Different predicates so the two Filter *parents* stay distinct
         // (don't themselves merge under CSE) — only their shared `child`
         // should collapse onto one `Rc`.
-        let root_a = QueryExpr::Filter {
-            pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Int64(1)))),
-            child: Rc::clone(&shared),
-        };
-        let root_b = QueryExpr::Filter {
-            pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Int64(2)))),
-            child: Rc::clone(&shared),
-        };
+        let root_a =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Filter {
+                pred: Predicate(ScalarExpr::Literal(ScalarValue::Int64(1))),
+                child: Rc::clone(&shared),
+            }))
+            .unwrap();
+        let root_b =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Filter {
+                pred: Predicate(ScalarExpr::Literal(ScalarValue::Int64(2))),
+                child: Rc::clone(&shared),
+            }))
+            .unwrap();
 
-        let space = search_workload(vec![("a", Rc::new(root_a)), ("b", Rc::new(root_b))]);
+        let space = search_workload(vec![("a", root_a), ("b", root_b)]);
         assert_eq!(
             space.len(),
             4,
@@ -8638,17 +8646,17 @@ mod tests {
         // pointer as) the pre-search `shared` variable. Recover it from the
         // post-CSE root's own `child` field instead of the stale `shared`
         // handle.
-        let QueryExpr::Filter {
+        let Some(NonASAPOp::Filter {
             child: post_cse_shared_a,
             ..
-        } = space.roots[0].1.as_ref()
+        }) = space.roots[0].1.non_asap()
         else {
             panic!("expected a Filter root");
         };
-        let QueryExpr::Filter {
+        let Some(NonASAPOp::Filter {
             child: post_cse_shared_b,
             ..
-        } = space.roots[1].1.as_ref()
+        }) = space.roots[1].1.non_asap()
         else {
             panic!("expected a Filter root");
         };
@@ -8674,14 +8682,10 @@ mod tests {
     #[test]
     fn add_candidate_rejects_a_true_rewrite_duplicate() {
         // SharedSubDAGStrategy's `Replacement::Rewrite` candidates are
-        // real `QueryExpr` values with `PartialEq`, so `add_candidate` can
+        // real `OperatorNode` values with `PartialEq`, so `add_candidate` can
         // (and must) actually reject a genuine repeat — unlike the
         // `Replacement::Summary` case (see the test below).
-        let root = Rc::new(agg(
-            vec![2],
-            AggIntent::Sum { col: None },
-            metric_scan(&["job"]),
-        ));
+        let root = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
         let mut group = TargetSubDAGCandidates::new(Rc::clone(&root), 2);
         let target = TargetSubDAG::with_consumer_count(&root, 2);
         let mut inserted = 0;
@@ -8712,8 +8716,8 @@ mod tests {
 
     #[test]
     fn add_candidate_never_dedups_summary_candidates() {
-        // Documented, deliberate consequence of `SummaryNode` deriving no
-        // `PartialEq` (see `is_duplicate_summary`'s own doc): re-proposing
+        // Documented, deliberate consequence of `is_duplicate_summary`
+        // refusing value equality on `f64`-bearing summaries: re-proposing
         // the same `Replacement::Summary` candidates DOES grow the group —
         // this module refuses to guess at an equality check it can't back
         // with a real `PartialEq`. `search_workload_with` never actually
@@ -8721,9 +8725,9 @@ mod tests {
         // module docs' "Termination" section), so this test exists to pin
         // the documented behavior, not to endorse calling `replacements`
         // twice for the same target.
-        let root = Rc::new(agg(vec![2], default_quantile(0.99), metric_scan(&["job"])));
+        let root = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
         let mut group = TargetSubDAGCandidates::new(Rc::clone(&root), 1);
-        let strategy = SketchAlgorithmStrategy::default_cost_model();
+        let strategy = ASAPStrategies::default_cost_model();
         let target = TargetSubDAG::new(&root);
         for candidate in strategy.replacements(&target) {
             group.add_candidate(candidate);
@@ -8742,11 +8746,7 @@ mod tests {
 
     #[test]
     fn is_duplicate_rewrite_never_merges_share_with_recompute() {
-        let target = Rc::new(agg(
-            vec![2],
-            AggIntent::Sum { col: None },
-            metric_scan(&["job"]),
-        ));
+        let target = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
         let share = Rc::clone(&target);
         let recompute = Rc::new((*target).clone());
         assert!(!Rc::ptr_eq(&share, &recompute));
@@ -8760,11 +8760,7 @@ mod tests {
 
     #[test]
     fn is_duplicate_rewrite_catches_a_real_repeat() {
-        let target = Rc::new(agg(
-            vec![2],
-            AggIntent::Sum { col: None },
-            metric_scan(&["job"]),
-        ));
+        let target = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
         let first_recompute = Rc::new((*target).clone());
         let second_recompute = Rc::new((*target).clone());
         assert!(!Rc::ptr_eq(&first_recompute, &second_recompute));
@@ -8785,7 +8781,7 @@ mod tests {
         let mut roots = Vec::new();
         let shared = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
         for i in 0..20 {
-            roots.push((i, Rc::new(shared.clone())));
+            roots.push((i, Rc::new((*shared).clone())));
         }
         let space = search_workload(roots);
         let group = space.candidates_for_target(&space.roots[0].1).unwrap();
@@ -8798,18 +8794,18 @@ mod tests {
             .unwrap();
         assert!(matches!(
             &ranked_group.candidates[0].replacement,
-            Replacement::Rewrite(rc) if Rc::ptr_eq(rc, &group.target)
+            Replacement::SubDAG(rc) if Rc::ptr_eq(rc, &group.target)
         ));
         let rewrites: Vec<&ReplacementSubDAG> = ranked_group
             .candidates
             .iter()
-            .filter(|c| matches!(c.replacement, Replacement::Rewrite(_)))
+            .filter(|c| matches!(&c.replacement, Replacement::SubDAG(n) if !n.contains_asap()))
             .copied()
             .collect();
         assert_eq!(rewrites.len(), 2);
         let first_shares_target = match &rewrites[0].replacement {
-            Replacement::Rewrite(rc) => Rc::ptr_eq(rc, &group.target),
-            Replacement::Summary(_) | Replacement::ExactComposition(_) => false,
+            Replacement::SubDAG(rc) => Rc::ptr_eq(rc, &group.target),
+            Replacement::ExactComposition(_) => false,
         };
         assert!(
             first_shares_target,
@@ -8835,17 +8831,17 @@ mod tests {
             }
         }
 
-        let root = Rc::new(agg(vec![2], default_quantile(0.99), metric_scan(&["job"])));
+        let root = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
         let space = search_workload(vec![("q", root)]);
         let ranked = space.cost_sorted(&PreferDDSketch);
         let agg_group = ranked
             .iter()
-            .find(|g| matches!(g.target.as_ref(), QueryExpr::Aggregate { .. }))
+            .find(|g| matches!(g.target.non_asap(), Some(NonASAPOp::Aggregate { .. })))
             .unwrap();
         assert_eq!(agg_group.candidates.len(), 2);
         let first_kind = match &agg_group.candidates[0].replacement {
-            Replacement::Summary(node) => sketch_kind_of(node),
-            Replacement::Rewrite(_) | Replacement::ExactComposition(_) => None,
+            Replacement::SubDAG(node) => sketch_kind_of(node),
+            Replacement::ExactComposition(_) => None,
         };
         assert_eq!(first_kind, Some(SketchAlgorithm::DDSketch));
     }
@@ -8863,7 +8859,7 @@ mod tests {
                 candidates.to_vec()
             }
 
-            fn estimated_subpopulation_count(&self, _target: &QueryExpr) -> Option<usize> {
+            fn estimated_subpopulation_count(&self, _target: &OperatorNode) -> Option<usize> {
                 Some(self.0)
             }
         }
@@ -8876,19 +8872,15 @@ mod tests {
                     delta: 0.01,
                 },
             };
-            let root = Rc::new(agg(
-                vec![2, 3],
-                intent,
-                metric_scan(&["tenant_id", "endpoint"]),
-            ));
+            let root = agg(vec![2, 3], intent, metric_scan(&["tenant_id", "endpoint"]));
             let strategies = default_strategies_with(&model);
             let space = search_workload_with(vec![("tenant_endpoint_count", root)], &strategies);
             let ranked = space.cost_sorted(&model);
             let aggregate = ranked
                 .iter()
-                .find(|group| matches!(group.target.as_ref(), QueryExpr::Aggregate { .. }))
+                .find(|group| matches!(group.target.non_asap(), Some(NonASAPOp::Aggregate { .. })))
                 .expect("aggregate group");
-            let Replacement::Summary(node) = &aggregate.candidates[0].replacement else {
+            let Replacement::SubDAG(node) = &aggregate.candidates[0].replacement else {
                 panic!("grouping candidate must be a summary")
             };
             summary_grouping(node)
@@ -8912,12 +8904,12 @@ mod tests {
     /// and target produces, not some other (or stale) number.
     #[test]
     fn cost_sorted_pairs_each_candidate_with_its_own_estimate_cost() {
-        let root = Rc::new(agg(vec![2], default_quantile(0.99), metric_scan(&["job"])));
+        let root = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
         let space = search_workload(vec![("q", root)]);
         let ranked = space.cost_sorted(&DefaultCostModel);
         let agg_group = ranked
             .iter()
-            .find(|g| matches!(g.target.as_ref(), QueryExpr::Aggregate { .. }))
+            .find(|g| matches!(g.target.non_asap(), Some(NonASAPOp::Aggregate { .. })))
             .unwrap();
         assert_eq!(
             agg_group.costs.len(),
@@ -8939,7 +8931,7 @@ mod tests {
 
     // ── global_selection (issue #271) ───────────────────────────────────
 
-    /// A `CostModel` with a constant, `sub_dag`-independent recompute cost
+    /// A `CostModel` with a constant, `sub-DAG`-independent recompute cost
     /// and shared-maintenance cost, chosen (40 recompute-per-use, 100
     /// maintenance) so that a `SharedSubDAGStrategy` group's
     /// `cse_share_decision` flips exactly between a consumer count of 2
@@ -8996,7 +8988,7 @@ mod tests {
             }
         }
 
-        let aggregate = Rc::new(agg(vec![2], default_quantile(0.99), metric_scan(&["job"])));
+        let aggregate = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
         let space = search_workload(vec![("left", Rc::clone(&aggregate)), ("right", aggregate)]);
         let root = &space.roots[0].1;
         assert!(cse_candidate_pair(space.candidates_for_target(root).unwrap()).is_some());
@@ -9011,7 +9003,7 @@ mod tests {
         // must equal the group's own raw consumer_count, and its `chosen`
         // candidate must be cost_sorted's top pick, for both the sketch
         // group and its child Scan.
-        let root = Rc::new(agg(vec![2], default_quantile(0.99), metric_scan(&["job"])));
+        let root = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
         let space = search_workload(vec![("q", root)]);
 
         let ranked = space.cost_sorted(&DefaultCostModel);
@@ -9038,12 +9030,12 @@ mod tests {
         // A bare Scan: no registered strategy has an opinion on it, so it
         // gets a group with an empty candidate list (see TargetSubDAGCandidates's own
         // doc) — global_selection must not invent a candidate for it.
-        let root = Rc::new(metric_scan(&["job"]));
+        let root = metric_scan(&["job"]);
         let space = search_workload(vec![("q", root)]);
         let selected = space.global_selection(&DefaultCostModel);
         let scan_group = selected
             .target_selections()
-            .find(|g| matches!(g.target.as_ref(), QueryExpr::Scan { .. }))
+            .find(|g| matches!(g.target.non_asap(), Some(NonASAPOp::Scan { .. })))
             .unwrap();
         assert!(scan_group.chosen.is_none());
         assert_eq!(scan_group.effective_consumer_count, 1);
@@ -9051,7 +9043,7 @@ mod tests {
 
     #[test]
     fn global_selection_falls_back_to_local_ranking_for_sketch_family_groups() {
-        // SketchAlgorithmStrategy groups have no cross-group-aware cost hook
+        // ASAPStrategies groups have no cross-group-aware cost hook
         // (rank_candidates takes no consumer_count) — global_selection must
         // still return cost_sorted's own top pick for them (documented in
         // the module docs' "Whole-plan (cross-group) selection" section),
@@ -9076,16 +9068,16 @@ mod tests {
             }
         }
 
-        let root = Rc::new(agg(vec![2], default_quantile(0.99), metric_scan(&["job"])));
+        let root = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
         let space = search_workload(vec![("q", root)]);
         let selected = space.global_selection(&PreferDDSketch);
         let agg_group = selected
             .target_selections()
-            .find(|g| matches!(g.target.as_ref(), QueryExpr::Aggregate { .. }))
+            .find(|g| matches!(g.target.non_asap(), Some(NonASAPOp::Aggregate { .. })))
             .unwrap();
         let kind = match &agg_group.chosen.unwrap().replacement {
-            Replacement::Summary(node) => sketch_kind_of(node),
-            Replacement::Rewrite(_) | Replacement::ExactComposition(_) => None,
+            Replacement::SubDAG(node) => sketch_kind_of(node),
+            Replacement::ExactComposition(_) => None,
         };
         assert_eq!(kind, Some(SketchAlgorithm::DDSketch));
 
@@ -9109,24 +9101,29 @@ mod tests {
 
     #[test]
     fn mixed_rewrite_group_keeps_and_selects_its_explicit_cse_pair() {
-        let target = Rc::new(metric_scan(&["job"]));
+        let target = metric_scan(&["job"]);
         let mut group = TargetSubDAGCandidates::new(Rc::clone(&target), 2);
         group.candidates = vec![
             ReplacementSubDAG {
                 strategy: "TestStrategy",
-                replacement: Replacement::Rewrite(Rc::clone(&target)),
+                replacement: Replacement::SubDAG(Rc::clone(&target)),
                 provenance: ReplacementProvenance::CseShare,
                 rationale: "share".into(),
             },
             ReplacementSubDAG {
                 strategy: "TestStrategy",
-                replacement: Replacement::Rewrite(Rc::new(target.as_ref().clone())),
+                replacement: Replacement::SubDAG(Rc::new(target.as_ref().clone())),
                 provenance: ReplacementProvenance::CseRecompute,
                 rationale: "recompute".into(),
             },
             ReplacementSubDAG {
                 strategy: "TestStrategy",
-                replacement: Replacement::Rewrite(Rc::new(QueryExpr::CurrentTimestamp)),
+                replacement: Replacement::SubDAG(
+                    OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(
+                        NonASAPOp::PromqlVectorFromScalar(ScalarExpr::EvalTimestamp),
+                    ))
+                    .unwrap(),
+                ),
                 provenance: ReplacementProvenance::LogicalRewrite,
                 rationale: "different rewrite strategy".into(),
             },
@@ -9166,7 +9163,7 @@ mod tests {
         // `a` and `c` are both non-`Aggregate` nodes (`Filter`/`Dedup`) so
         // neither is bindable — each group is a *clean* two-candidate
         // SharedSubDAGStrategy share-vs-recompute pair, with no
-        // SketchAlgorithmStrategy `Summary` candidate mixed in to complicate
+        // ASAPStrategies `Summary` candidate mixed in to complicate
         // ranking (see `shared_aggregate_across_two_roots_gets_both_strategies_candidates`
         // for what a *mixed*-shape group looks like — deliberately avoided
         // here to isolate the SharedSubDAGStrategy-only interaction).
@@ -9182,23 +9179,25 @@ mod tests {
         // which flips its own decision to Share. Only global_selection,
         // which folds `a`'s decision into `c`'s effective_consumer_count
         // before deciding `c`, gets this right.
+        use asap_types::ir::Predicate;
         use asap_types::pre_asap::expr_ir::ScalarValue;
-        use asap_types::pre_asap::query_expr::Predicate;
 
-        let c = || QueryExpr::Dedup {
-            cols: vec![0],
-            child: Rc::new(metric_scan(&["job"])),
+        let c = || {
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Dedup {
+                cols: vec![0],
+                child: metric_scan(&["job"]),
+            }))
+            .unwrap()
         };
-        let a = || QueryExpr::Filter {
-            pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Boolean(true)))),
-            child: Rc::new(c()),
+        let a = || {
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Filter {
+                pred: Predicate(ScalarExpr::Literal(ScalarValue::Boolean(true))),
+                child: c(),
+            }))
+            .unwrap()
         };
 
-        let space = search_workload(vec![
-            ("root1", Rc::new(a())),
-            ("root2", Rc::new(a())),
-            ("root3", Rc::new(c())),
-        ]);
+        let space = search_workload(vec![("root1", a()), ("root2", a()), ("root3", c())]);
 
         // Fixture sanity: root1/root2 merged onto one shared `a`, and `c`
         // (root1/root2's shared child, and root3 itself) merged onto one
@@ -9206,7 +9205,7 @@ mod tests {
         // (non-mixed) two-candidate SharedSubDAGStrategy pairs.
         assert!(Rc::ptr_eq(&space.roots[0].1, &space.roots[1].1));
         let a_rc = &space.roots[0].1;
-        let QueryExpr::Filter { child: c_via_a, .. } = a_rc.as_ref() else {
+        let Some(NonASAPOp::Filter { child: c_via_a, .. }) = a_rc.non_asap() else {
             panic!("expected root1/root2 to still be a Filter");
         };
         assert!(Rc::ptr_eq(c_via_a, &space.roots[2].1));
@@ -9240,7 +9239,7 @@ mod tests {
             .unwrap();
         let c_top_shares = matches!(
             &c_ranked.candidates[0].replacement,
-            Replacement::Rewrite(rc) if Rc::ptr_eq(rc, c_via_a)
+            Replacement::SubDAG(rc) if Rc::ptr_eq(rc, c_via_a)
         );
         assert!(
             !c_top_shares,
@@ -9261,7 +9260,7 @@ mod tests {
         );
         let a_shares = matches!(
             &a_selected.chosen.unwrap().replacement,
-            Replacement::Rewrite(rc) if Rc::ptr_eq(rc, a_rc)
+            Replacement::SubDAG(rc) if Rc::ptr_eq(rc, a_rc)
         );
         assert!(
             !a_shares,
@@ -9274,7 +9273,7 @@ mod tests {
         );
         let c_shares = matches!(
             &c_selected.chosen.unwrap().replacement,
-            Replacement::Rewrite(rc) if Rc::ptr_eq(rc, c_via_a)
+            Replacement::SubDAG(rc) if Rc::ptr_eq(rc, c_via_a)
         );
         assert!(
             c_shares,
@@ -9312,10 +9311,12 @@ mod tests {
             }
         }
 
-        let shared = Rc::new(QueryExpr::Dedup {
-            cols: vec![0],
-            child: Rc::new(metric_scan(&["job"])),
-        });
+        let shared =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Dedup {
+                cols: vec![0],
+                child: metric_scan(&["job"]),
+            }))
+            .unwrap();
         let space = search_workload(vec![
             ("left", Rc::clone(&shared)),
             ("right", Rc::clone(&shared)),
@@ -9328,20 +9329,26 @@ mod tests {
 
     #[test]
     fn effective_repetition_materializes_a_cse_choice_for_a_single_edge_child() {
+        use asap_types::ir::Predicate;
         use asap_types::pre_asap::expr_ir::ScalarValue;
-        use asap_types::pre_asap::query_expr::Predicate;
 
-        let c = || QueryExpr::Dedup {
-            cols: vec![0],
-            child: Rc::new(metric_scan(&["job"])),
+        let c = || {
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Dedup {
+                cols: vec![0],
+                child: metric_scan(&["job"]),
+            }))
+            .unwrap()
         };
-        let a = || QueryExpr::Filter {
-            pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Boolean(true)))),
-            child: Rc::new(c()),
+        let a = || {
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Filter {
+                pred: Predicate(ScalarExpr::Literal(ScalarValue::Boolean(true))),
+                child: c(),
+            }))
+            .unwrap()
         };
-        let space = search_workload(vec![("root1", Rc::new(a())), ("root2", Rc::new(a()))]);
+        let space = search_workload(vec![("root1", a()), ("root2", a())]);
         let a_rc = &space.roots[0].1;
-        let QueryExpr::Filter { child: c_rc, .. } = a_rc.as_ref() else {
+        let Some(NonASAPOp::Filter { child: c_rc, .. }) = a_rc.non_asap() else {
             panic!("expected Filter root");
         };
 
@@ -9356,8 +9363,8 @@ mod tests {
 
     #[test]
     fn shared_ancestor_keeps_a_single_use_cse_descendant_selected() {
+        use asap_types::ir::Predicate;
         use asap_types::pre_asap::expr_ir::ScalarValue;
-        use asap_types::pre_asap::query_expr::Predicate;
 
         struct AlwaysShare;
         impl CostModel for AlwaysShare {
@@ -9378,22 +9385,25 @@ mod tests {
             }
         }
 
-        let child = || QueryExpr::Dedup {
-            cols: vec![0],
-            child: Rc::new(metric_scan(&["job"])),
+        let child = || {
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Dedup {
+                cols: vec![0],
+                child: metric_scan(&["job"]),
+            }))
+            .unwrap()
         };
-        let parent = || QueryExpr::Filter {
-            pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Boolean(true)))),
-            child: Rc::new(child()),
+        let parent = || {
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Filter {
+                pred: Predicate(ScalarExpr::Literal(ScalarValue::Boolean(true))),
+                child: child(),
+            }))
+            .unwrap()
         };
-        let space = search_workload(vec![
-            ("root1", Rc::new(parent())),
-            ("root2", Rc::new(parent())),
-        ]);
+        let space = search_workload(vec![("root1", parent()), ("root2", parent())]);
         let parent_rc = &space.roots[0].1;
-        let QueryExpr::Filter {
+        let Some(NonASAPOp::Filter {
             child: child_rc, ..
-        } = parent_rc.as_ref()
+        }) = parent_rc.non_asap()
         else {
             panic!("expected Filter root");
         };
@@ -9417,38 +9427,44 @@ mod tests {
 
     #[test]
     fn global_selection_propagates_uses_through_the_selected_rewrite() {
+        use asap_types::ir::Predicate;
         use asap_types::pre_asap::expr_ir::ScalarValue;
-        use asap_types::pre_asap::query_expr::Predicate;
 
         struct ReplaceFilterChild;
         impl ReplacementStrategy for ReplaceFilterChild {
             fn matches(&self, target: &TargetSubDAG<'_>) -> bool {
-                matches!(target.root.as_ref(), QueryExpr::Filter { .. })
+                matches!(target.root.non_asap(), Some(NonASAPOp::Filter { .. }))
             }
 
             fn replacements(&self, _target: &TargetSubDAG<'_>) -> Vec<ReplacementSubDAG> {
                 vec![ReplacementSubDAG {
                     strategy: "ReplaceFilterChild",
-                    replacement: Replacement::Rewrite(Rc::new(QueryExpr::Dedup {
-                        cols: vec![0],
-                        child: Rc::new(metric_scan(&["replacement"])),
-                    })),
+                    replacement: Replacement::SubDAG(
+                        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(
+                            NonASAPOp::Dedup {
+                                cols: vec![0],
+                                child: metric_scan(&["replacement"]),
+                            },
+                        ))
+                        .unwrap(),
+                    ),
                     provenance: ReplacementProvenance::LogicalRewrite,
                     rationale: "replace the Filter and its input".into(),
                 }]
             }
         }
 
-        let original_child = Rc::new(metric_scan(&["original"]));
-        let root = Rc::new(QueryExpr::Filter {
-            pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Boolean(true)))),
+        let original_child = metric_scan(&["original"]);
+        let root = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Filter {
+            pred: Predicate(ScalarExpr::Literal(ScalarValue::Boolean(true))),
             child: Rc::clone(&original_child),
-        });
+        }))
+        .unwrap();
         let strategies: Vec<Box<dyn ReplacementStrategy>> = vec![Box::new(ReplaceFilterChild)];
         let space = search_workload_with(vec![("q", root)], &strategies);
         let root = &space.roots[0].1;
         let selected = space.global_selection(&DefaultCostModel);
-        let Replacement::Rewrite(rewrite) = &selected
+        let Replacement::SubDAG(rewrite) = &selected
             .for_target(root)
             .unwrap()
             .chosen
@@ -9457,17 +9473,17 @@ mod tests {
         else {
             panic!("expected logical rewrite");
         };
-        let QueryExpr::Dedup {
+        let Some(NonASAPOp::Dedup {
             child: replacement_child,
             ..
-        } = rewrite.as_ref()
+        }) = rewrite.non_asap()
         else {
             panic!("expected Dedup rewrite");
         };
-        let QueryExpr::Filter {
+        let Some(NonASAPOp::Filter {
             child: original_child,
             ..
-        } = root.as_ref()
+        }) = root.non_asap()
         else {
             panic!("expected Filter root");
         };
@@ -9503,11 +9519,11 @@ mod tests {
             fn candidate_cost(&self, _: &ReplacementSubDAG, _: &TargetSubDAG<'_>) -> Option<Cost> {
                 Some(Cost(1.0))
             }
-            fn summary_support_evidence(&self, _: &SummaryNode) -> Option<bool> {
+            fn summary_support_evidence(&self, _: &OperatorNode) -> Option<bool> {
                 Some(false)
             }
         }
-        let root = Rc::new(lower_promql("sum_over_time(a[1m])", AccuracyTarget::Exact));
+        let root = lower_promql("sum_over_time(a[1m])", AccuracyTarget::Exact);
         let space = search_workload(vec![("q", root)]);
         let selected = space.global_selection(&Unsupported);
         assert!(selected
@@ -9520,18 +9536,15 @@ mod tests {
     // Composable temporal/grouped Sum must be executable as one producer.
     #[test]
     fn grouped_temporal_sum_has_one_summary_producer_candidate() {
-        let root = Rc::new(lower_promql(
-            "sum by(job)(sum_over_time(a[1m]))",
-            AccuracyTarget::Exact,
-        ));
+        let root = lower_promql("sum by(job)(sum_over_time(a[1m]))", AccuracyTarget::Exact);
         let candidates =
-            SketchAlgorithmStrategy::default_cost_model().replacements(&TargetSubDAG::new(&root));
+            ASAPStrategies::default_cost_model().replacements(&TargetSubDAG::new(&root));
         assert!(candidates
             .iter()
             .any(|candidate| matches!(&candidate.replacement,
-            Replacement::Summary(node) if matches!(&node.expr,
-                SummaryExpr::SummaryAgg { reduction: Reduction::Reduce(_), child, .. }
-                    if matches!(child.expr, SummaryExpr::KeepPreAsap(_))))));
+            Replacement::SubDAG(node) if matches!(&node.operator,
+                Operator::ASAP(ASAPOp::SummaryAgg { reduction: Reduction::Reduce(_), child, .. })
+                    if !child.contains_asap()))));
         struct PreferComposed;
         impl CostModel for PreferComposed {
             fn rank_candidates(
@@ -9548,9 +9561,9 @@ mod tests {
             ) -> Option<Cost> {
                 Some(Cost(
                     if matches!(&candidate.replacement,
-                    Replacement::Summary(node) if matches!(&node.expr,
-                        SummaryExpr::SummaryAgg { reduction: Reduction::Reduce(_), child, .. }
-                            if matches!(child.expr, SummaryExpr::KeepPreAsap(_))))
+                    Replacement::SubDAG(node) if matches!(&node.operator,
+                        Operator::ASAP(ASAPOp::SummaryAgg { reduction: Reduction::Reduce(_), child, .. })
+                            if !child.contains_asap()))
                     {
                         1.0
                     } else {
@@ -9562,9 +9575,9 @@ mod tests {
         let space = search_workload(vec![("q", root.clone())]);
         let selected = space.global_selection(&PreferComposed);
         let node = selected.assemble_target(&space.roots[0].1).unwrap();
-        assert!(matches!(&node.expr,
-            SummaryExpr::SummaryAgg { reduction: Reduction::Reduce(_), child, .. }
-                if matches!(child.expr, SummaryExpr::KeepPreAsap(_))));
+        assert!(matches!(&node.operator,
+            Operator::ASAP(ASAPOp::SummaryAgg { reduction: Reduction::Reduce(_), child, .. })
+                if !child.contains_asap()));
     }
 
     // Mixed candidate ranking must honor explicit costs, not legacy estimates.
@@ -9593,10 +9606,7 @@ mod tests {
                 ))
             }
         }
-        let root = Rc::new(lower_promql(
-            "sum by(job)(sum_over_time(a[1m]))",
-            AccuracyTarget::Exact,
-        ));
+        let root = lower_promql("sum by(job)(sum_over_time(a[1m]))", AccuracyTarget::Exact);
         let space = search_workload(vec![("q", root)]);
         let selection = space.global_selection(&ExplicitCosts);
         let selected = selection
@@ -9632,16 +9642,8 @@ mod tests {
             }
         }
 
-        let a = Rc::new(agg(
-            vec![2],
-            AggIntent::Avg { col: None },
-            metric_scan(&["job"]),
-        ));
-        let b = Rc::new(agg(
-            vec![2],
-            AggIntent::Avg { col: None },
-            metric_scan(&["job"]),
-        ));
+        let a = agg(vec![2], AggIntent::Avg { col: None }, metric_scan(&["job"]));
+        let b = agg(vec![2], AggIntent::Avg { col: None }, metric_scan(&["job"]));
         let space = search_workload(vec![("a", a), ("b", b)]);
         let root = &space.roots[0].1;
         let selected = space.global_selection(&PreferLogicalRewrite);
@@ -9657,26 +9659,30 @@ mod tests {
 
     #[test]
     fn topological_order_puts_a_later_discovered_parent_before_its_child() {
-        // Mirrors nested_shared_sub_dag_below_an_unshared_parent_is_still_discovered's
+        // Mirrors nested_shared_sub-DAG_below_an_unshared_parent_is_still_discovered's
         // diamond fixture: discover_targets's own `order` visits root_b (a
         // parent of `shared`) *after* `shared` itself, because `shared` was
         // already fully walked via root_a first. A naive "process
         // discover_targets's own order" DP would see root_b's child edge
         // after already processing `shared` — topological_order must not
         // make that mistake.
+        use asap_types::ir::Predicate;
         use asap_types::pre_asap::expr_ir::ScalarValue;
-        use asap_types::pre_asap::query_expr::Predicate;
 
         let shared = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
-        let root_a = QueryExpr::Filter {
-            pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Int64(1)))),
-            child: Rc::new(shared.clone()),
-        };
-        let root_b = QueryExpr::Filter {
-            pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Int64(2)))),
-            child: Rc::new(shared),
-        };
-        let roots = vec![("a", Rc::new(root_a)), ("b", Rc::new(root_b))];
+        let root_a =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Filter {
+                pred: Predicate(ScalarExpr::Literal(ScalarValue::Int64(1))),
+                child: shared.clone(),
+            }))
+            .unwrap();
+        let root_b =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Filter {
+                pred: Predicate(ScalarExpr::Literal(ScalarValue::Int64(2))),
+                child: shared,
+            }))
+            .unwrap();
+        let roots = vec![("a", root_a), ("b", root_b)];
 
         let mut order = Vec::new();
         let mut nodes = HashMap::new();
@@ -9702,10 +9708,10 @@ mod tests {
         // Discovery-order sanity: root_b comes after the shared child in
         // discover_targets's own order (the exact non-topological case this
         // test exists to cover).
-        let QueryExpr::Filter {
+        let Some(NonASAPOp::Filter {
             child: shared_via_a,
             ..
-        } = space.roots[0].1.as_ref()
+        }) = space.roots[0].1.non_asap()
         else {
             panic!("expected a Filter root");
         };
@@ -9738,7 +9744,7 @@ mod tests {
         // module docs — so this always converges in exactly 2 passes).
         let a = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
         let b = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
-        let space = search_workload(vec![("a", Rc::new(a)), ("b", Rc::new(b))]);
+        let space = search_workload(vec![("a", a), ("b", b)]);
         assert!(!space.is_empty());
     }
 
@@ -9764,19 +9770,23 @@ mod tests {
         fn replacements(&self, target: &TargetSubDAG<'_>) -> Vec<ReplacementSubDAG> {
             let n = self.next.get();
             self.next.set(n + 1);
+            use asap_types::ir::Predicate;
             use asap_types::pre_asap::expr_ir::ScalarValue;
-            use asap_types::pre_asap::query_expr::Predicate;
-            let fresh_inner_layer = QueryExpr::Filter {
-                pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Int64(n)))),
-                child: Rc::clone(target.root),
-            };
-            let outer_wrapper = QueryExpr::Filter {
-                pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Boolean(true)))),
-                child: Rc::new(fresh_inner_layer),
-            };
+            let fresh_inner_layer =
+                OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Filter {
+                    pred: Predicate(ScalarExpr::Literal(ScalarValue::Int64(n))),
+                    child: Rc::clone(target.root),
+                }))
+                .unwrap();
+            let outer_wrapper =
+                OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Filter {
+                    pred: Predicate(ScalarExpr::Literal(ScalarValue::Boolean(true))),
+                    child: fresh_inner_layer,
+                }))
+                .unwrap();
             vec![ReplacementSubDAG {
                 strategy: "AlwaysGrowingStrategy",
-                replacement: Replacement::Rewrite(Rc::new(outer_wrapper)),
+                replacement: Replacement::SubDAG(outer_wrapper),
                 provenance: ReplacementProvenance::LogicalRewrite,
                 rationale: format!("pathological candidate #{n}"),
             }]
@@ -9786,13 +9796,13 @@ mod tests {
     #[test]
     #[should_panic(expected = "did not converge")]
     fn a_pathologically_growing_strategy_trips_the_iteration_cap() {
-        let root = Rc::new(metric_scan(&["job"]));
+        let root = metric_scan(&["job"]);
         let strategies: Vec<Box<dyn ReplacementStrategy>> = vec![Box::new(AlwaysGrowingStrategy {
             next: std::cell::Cell::new(0),
         })];
         let _ = search_workload_with(vec![("q", root)], &strategies);
     }
-    // ── realize_child / keep_pre_asap: end-to-end single-target realization ──
+    // ── realize_child / retain_exact: end-to-end single-target realization ──
     //
     // Moved from the former `bind.rs` (issue #251): `bind.rs`'s own
     // workload-wide orchestration (`implement_workload`/
@@ -9805,17 +9815,6 @@ mod tests {
     // pattern by hand since `realize_child` is `pub(crate)`), these tests
     // call `realize_child` directly.
 
-    fn agg_per_entity(intent: AggIntent, child: QueryExpr) -> QueryExpr {
-        QueryExpr::Aggregate {
-            reduction: ReductionTy::PerEntity,
-            measures: vec![intent],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(child),
-        }
-    }
-
     fn field<'a>(schema: &'a Schema, name: &str) -> &'a Field {
         schema
             .fields
@@ -9825,29 +9824,29 @@ mod tests {
     }
 
     fn realize_first(
-        expr: &QueryExpr,
+        expr: &OperatorNode,
         cost_model: &dyn CostModel,
-    ) -> Result<Rc<SummaryNode>, RealizationError> {
+    ) -> Result<Rc<OperatorNode>, RealizationError> {
         realize_child(&Rc::new(expr.clone()), cost_model)
     }
 
-    fn realize(expr: &QueryExpr) -> Result<Rc<SummaryNode>, RealizationError> {
+    fn realize(expr: &OperatorNode) -> Result<Rc<OperatorNode>, RealizationError> {
         realize_first(expr, &DefaultCostModel)
     }
 
     #[test]
     fn quantile_realizes_kll_wrapped_in_estimate() {
         // quantile by (job) (m) at ε=0.01 → Estimate(Quantile) over
-        // SummaryAgg(Kll{k:269}) over KeepPreAsap(Scan). job = col 2.
+        // SummaryAgg(Kll{k:269}) over the kept Scan. job = col 2.
         let q = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
         let root = realize(&q).unwrap();
 
-        let SummaryExpr::SummaryEstimate {
+        let Operator::ASAP(ASAPOp::SummaryEstimate {
             summary_input,
             query,
-        } = &root.expr
+        }) = &root.operator
         else {
-            panic!("expected SummaryEstimate root, got {:?}", root.expr);
+            panic!("expected SummaryEstimate root, got {:?}", root.operator);
         };
         assert!(matches!(query, PostAsapSketchStatistic::Quantile { q } if *q == 0.99));
         // Estimate edge: plain row shape — group key + Float64 answer.
@@ -9860,15 +9859,15 @@ mod tests {
             FieldDataType::Plain(DataType::Utf8)
         );
 
-        let SummaryExpr::SummaryAgg {
+        let Operator::ASAP(ASAPOp::SummaryAgg {
             child,
             family,
             input,
             reduction,
             ..
-        } = &summary_input.expr
+        }) = &summary_input.operator
         else {
-            panic!("expected SummaryAgg, got {:?}", summary_input.expr);
+            panic!("expected SummaryAgg, got {:?}", summary_input.operator);
         };
         assert_eq!(
             family,
@@ -9888,8 +9887,9 @@ mod tests {
                 GroupingStrategy::default()
             )
         );
-        assert!(matches!(child.expr, SummaryExpr::KeepPreAsap(ref e)
-            if matches!(**e, QueryExpr::Scan { .. })));
+        // The kept pre-ASAP leaf is the Scan node itself (no wrapper).
+        assert!(matches!(child.non_asap(), Some(NonASAPOp::Scan { .. })));
+        assert!(!child.contains_asap());
     }
 
     /// A deployment-supplied [`CostModel`] can override the default KLL
@@ -9919,11 +9919,15 @@ mod tests {
 
         // Default: KLL (see `quantile_realizes_kll_wrapped_in_estimate` above).
         let default_root = realize(&q).unwrap();
-        let SummaryExpr::SummaryEstimate { summary_input, .. } = &default_root.expr else {
-            panic!("expected SummaryEstimate root, got {:?}", default_root.expr);
+        let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &default_root.operator
+        else {
+            panic!(
+                "expected SummaryEstimate root, got {:?}",
+                default_root.operator
+            );
         };
-        let SummaryExpr::SummaryAgg { family, .. } = &summary_input.expr else {
-            panic!("expected SummaryAgg, got {:?}", summary_input.expr);
+        let Operator::ASAP(ASAPOp::SummaryAgg { family, .. }) = &summary_input.operator else {
+            panic!("expected SummaryAgg, got {:?}", summary_input.operator);
         };
         assert!(matches!(
             family,
@@ -9932,11 +9936,15 @@ mod tests {
 
         // With `PreferDDSketchViaCostModel`: DDSketch instead, same query.
         let custom_root = realize_first(&q, &PreferDDSketchViaCostModel).unwrap();
-        let SummaryExpr::SummaryEstimate { summary_input, .. } = &custom_root.expr else {
-            panic!("expected SummaryEstimate root, got {:?}", custom_root.expr);
+        let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &custom_root.operator
+        else {
+            panic!(
+                "expected SummaryEstimate root, got {:?}",
+                custom_root.operator
+            );
         };
-        let SummaryExpr::SummaryAgg { family, .. } = &summary_input.expr else {
-            panic!("expected SummaryAgg, got {:?}", summary_input.expr);
+        let Operator::ASAP(ASAPOp::SummaryAgg { family, .. }) = &summary_input.operator else {
+            panic!("expected SummaryAgg, got {:?}", summary_input.operator);
         };
         assert_eq!(
             family,
@@ -9953,8 +9961,8 @@ mod tests {
     /// A deployment-supplied `CostModel` can realize an `AggIntent::Extension`
     /// intent as a real sketch instead of the default `PassThrough` (issue
     /// #150) — `realizations_for_intent` must consult `realize_extension`
-    /// for the `Extension` arm, and `readout` must consult
-    /// `readout_extension` to build its `SketchStatistic` without panicking.
+    /// for the `Extension` arm, and `evaluation` must consult
+    /// `evaluation_extension` to build its `SketchStatistic` without panicking.
     struct FrequencyCostModel;
 
     impl CostModel for FrequencyCostModel {
@@ -9980,7 +9988,7 @@ mod tests {
             }
         }
 
-        fn readout_extension(
+        fn evaluation_extension(
             &self,
             ext_kind: &str,
             payload: &serde_json::Value,
@@ -10006,7 +10014,7 @@ mod tests {
         };
         let q = agg(vec![], intent, metric_scan(&[]));
         let root = realize(&q).unwrap();
-        assert!(matches!(root.expr, SummaryExpr::KeepPreAsap(_)));
+        assert!(!root.contains_asap());
     }
 
     #[test]
@@ -10018,12 +10026,12 @@ mod tests {
         let q = agg(vec![], intent, metric_scan(&[]));
         let root = realize_first(&q, &FrequencyCostModel).unwrap();
 
-        let SummaryExpr::SummaryEstimate {
+        let Operator::ASAP(ASAPOp::SummaryEstimate {
             summary_input,
             query,
-        } = &root.expr
+        }) = &root.operator
         else {
-            panic!("expected SummaryEstimate root, got {:?}", root.expr);
+            panic!("expected SummaryEstimate root, got {:?}", root.operator);
         };
         assert!(matches!(
             query,
@@ -10031,8 +10039,8 @@ mod tests {
                 if k == "item" && v == "checkout"
         ));
 
-        let SummaryExpr::SummaryAgg { family, .. } = &summary_input.expr else {
-            panic!("expected SummaryAgg, got {:?}", summary_input.expr);
+        let Operator::ASAP(ASAPOp::SummaryAgg { family, .. }) = &summary_input.operator else {
+            panic!("expected SummaryAgg, got {:?}", summary_input.operator);
         };
         assert_eq!(
             family,
@@ -10053,10 +10061,10 @@ mod tests {
     fn exact_sum_realizes_accumulator_without_estimate() {
         let q = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
         let root = realize(&q).unwrap();
-        let SummaryExpr::SummaryAgg { family, .. } = &root.expr else {
+        let Operator::ASAP(ASAPOp::SummaryAgg { family, .. }) = &root.operator else {
             panic!(
                 "expected bare SummaryAgg (no estimate), got {:?}",
-                root.expr
+                root.operator
             );
         };
         assert_eq!(
@@ -10076,14 +10084,16 @@ mod tests {
         use std::time::Duration;
         let q = agg_per_entity(
             AggIntent::Rate,
-            QueryExpr::TimeRange {
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::TimeRange {
+                kind: TimeRangeKind::Range,
                 range: Duration::from_secs(300),
-                child: Rc::new(metric_scan(&["job"])),
-            },
+                child: metric_scan(&["job"]),
+            }))
+            .unwrap(),
         );
         let root = realize(&q).unwrap();
-        let SummaryExpr::SummaryAgg { family, .. } = &root.expr else {
-            panic!("expected SummaryAgg, got {:?}", root.expr);
+        let Operator::ASAP(ASAPOp::SummaryAgg { family, .. }) = &root.operator else {
+            panic!("expected SummaryAgg, got {:?}", root.operator);
         };
         assert_eq!(
             family,
@@ -10114,17 +10124,19 @@ mod tests {
         use std::time::Duration;
         let q = agg_per_entity(
             default_quantile(0.99),
-            QueryExpr::TimeRange {
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::TimeRange {
+                kind: TimeRangeKind::Range,
                 range: Duration::from_secs(10),
-                child: Rc::new(metric_scan(&["job"])),
-            },
+                child: metric_scan(&["job"]),
+            }))
+            .unwrap(),
         );
         let root = realize(&q).unwrap();
-        let SummaryExpr::SummaryEstimate { summary_input, .. } = &root.expr else {
-            panic!("expected estimate root, got {:?}", root.expr);
+        let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &root.operator else {
+            panic!("expected estimate root, got {:?}", root.operator);
         };
-        let SummaryExpr::SummaryAgg { reduction, .. } = &summary_input.expr else {
-            panic!("expected SummaryAgg, got {:?}", summary_input.expr);
+        let Operator::ASAP(ASAPOp::SummaryAgg { reduction, .. }) = &summary_input.operator else {
+            panic!("expected SummaryAgg, got {:?}", summary_input.operator);
         };
         assert_eq!(reduction, &ReductionTy::PerEntity);
     }
@@ -10142,11 +10154,11 @@ mod tests {
         };
         let q = agg(vec![], intent, metric_scan(&["job"]));
         let root = realize(&q).unwrap();
-        let SummaryExpr::SummaryEstimate { summary_input, .. } = &root.expr else {
-            panic!("expected estimate root, got {:?}", root.expr);
+        let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &root.operator else {
+            panic!("expected estimate root, got {:?}", root.operator);
         };
-        let SummaryExpr::SummaryAgg { reduction, .. } = &summary_input.expr else {
-            panic!("expected SummaryAgg, got {:?}", summary_input.expr);
+        let Operator::ASAP(ASAPOp::SummaryAgg { reduction, .. }) = &summary_input.operator else {
+            panic!("expected SummaryAgg, got {:?}", summary_input.operator);
         };
         assert_eq!(reduction, &ReductionTy::by(vec![]));
     }
@@ -10158,39 +10170,41 @@ mod tests {
         // accumulator.
         let inner = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
         let outer = agg(vec![], default_quantile(0.9), inner);
-        let root = realize(&outer).unwrap();
+        // Timing is not stored during realization: time the candidate under
+        // the default lifecycle assignment to read the maintenance boundary.
+        let root = timed(&realize(&outer).unwrap());
 
-        let SummaryExpr::SummaryEstimate { summary_input, .. } = &root.expr else {
-            panic!("expected estimate root, got {:?}", root.expr);
+        let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &root.operator else {
+            panic!("expected estimate root, got {:?}", root.operator);
         };
-        let SummaryExpr::SummaryAgg { child, family, .. } = &summary_input.expr else {
-            panic!("expected outer SummaryAgg, got {:?}", summary_input.expr);
+        let Operator::ASAP(ASAPOp::SummaryAgg { child, family, .. }) = &summary_input.operator
+        else {
+            panic!(
+                "expected outer SummaryAgg, got {:?}",
+                summary_input.operator
+            );
         };
         assert!(matches!(
             family,
             FieldDataType::Sketch(kind, _) if kind.algorithm() == &SketchAlgorithm::Kll
         ));
-        let SummaryExpr::ValueOperation {
-            child,
-            operation: ValueOperation::FinalizeExactAccumulator,
-            timing: ExecutionTiming::IngestionTime,
-        } = &child.expr
-        else {
-            panic!("expected explicit maintenance readout");
+        assert_eq!(child.timing, Some(ExecutionTiming::IngestionTime));
+        let Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child }) = &child.operator else {
+            panic!("expected explicit maintenance evaluation");
         };
-        let SummaryExpr::SummaryAgg {
+        let Operator::ASAP(ASAPOp::SummaryAgg {
             family: inner_family,
             child: leaf,
             ..
-        } = &child.expr
+        }) = &child.operator
         else {
-            panic!("expected inner SummaryAgg, got {:?}", child.expr);
+            panic!("expected inner SummaryAgg, got {:?}", child.operator);
         };
         assert_eq!(
             inner_family,
             &FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum)
         );
-        assert!(matches!(leaf.expr, SummaryExpr::KeepPreAsap(_)));
+        assert!(!leaf.contains_asap());
     }
 
     /// Issue #115: the summary is built over the intent's own input columns.
@@ -10225,13 +10239,15 @@ mod tests {
         }
     }
 
-    /// The update expression of the first `SummaryAgg` in the DAG.
-    fn find_summary_input(node: &SummaryNode) -> Option<SummaryInputExpr> {
-        match &node.expr {
-            SummaryExpr::SummaryAgg { input, .. } if input.item.is_none() => {
+    /// The update expression of the first `SummaryAgg` in the tree.
+    fn find_summary_input(node: &OperatorNode) -> Option<SummaryInputExpr> {
+        match &node.operator {
+            Operator::ASAP(ASAPOp::SummaryAgg { input, .. }) if input.item.is_none() => {
                 Some(input.weight.clone())
             }
-            SummaryExpr::SummaryEstimate { summary_input, .. } => find_summary_input(summary_input),
+            Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) => {
+                find_summary_input(summary_input)
+            }
             _ => None,
         }
     }
@@ -10252,59 +10268,62 @@ mod tests {
         ] {
             let q = agg(vec![2], intent.clone(), metric_scan(&["job"]));
             let root = realize(&q).unwrap();
+            // Kept pass-through: the pre-ASAP node itself, not a wrapper.
             assert!(
-                matches!(root.expr, SummaryExpr::KeepPreAsap(ref e) if **e == q),
-                "expected KeepPreAsap passthrough for {intent:?}"
+                !root.contains_asap() && root.operator == q.operator && root.schema == q.schema,
+                "expected kept pre-ASAP passthrough for {intent:?}"
             );
         }
     }
 
     #[test]
     fn logical_parent_subsumes_bindable_child() {
-        // Filter over a bindable quantile: `KeepPreAsap` has no post-ASAP
-        // children, so the conservative fallback keeps the whole sub-DAG
+        // Filter over a bindable quantile: a kept non-ASAP sub-DAG has no
+        // summary children, so the conservative fallback keeps the whole sub-DAG
         // logical.
+        use asap_types::ir::Predicate;
         use asap_types::pre_asap::expr_ir::{CompareOpKind, ScalarValue};
-        use asap_types::pre_asap::query_expr::Predicate;
-        let q = QueryExpr::Filter {
-            pred: Predicate(Rc::new(QueryExpr::Compare {
-                left: Rc::new(QueryExpr::Column(0)),
+        let q = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Filter {
+            pred: Predicate(ScalarExpr::Compare {
+                left: Box::new(ScalarExpr::Column(0)),
                 op: CompareOpKind::Gt,
-                right: Rc::new(QueryExpr::Literal(ScalarValue::Float64(0.5))),
-            })),
-            child: Rc::new(agg(vec![], default_quantile(0.99), metric_scan(&[]))),
-        };
+                right: Box::new(ScalarExpr::Literal(ScalarValue::Float64(0.5))),
+                semantics: asap_types::ir::ExprSemantics::Promql,
+            }),
+            child: agg(vec![], default_quantile(0.99), metric_scan(&[])),
+        }))
+        .unwrap();
         let root = realize(&q).unwrap();
-        assert!(matches!(root.expr, SummaryExpr::KeepPreAsap(ref e) if **e == q));
+        assert!(
+            !root.contains_asap() && root.operator == q.operator && root.schema == q.schema,
+            "expected the whole Filter sub_dag kept pre-ASAP"
+        );
     }
 
     #[test]
     fn having_and_multi_intent_stay_logical() {
+        use asap_types::ir::Predicate;
         use asap_types::pre_asap::expr_ir::ScalarValue;
-        use asap_types::pre_asap::query_expr::Predicate;
-        let mut q = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
-        if let QueryExpr::Aggregate { having, .. } = &mut q {
-            *having = Some(Predicate(Rc::new(QueryExpr::Literal(
-                ScalarValue::Boolean(true),
-            ))));
-        }
-        assert!(matches!(
-            realize(&q).unwrap().expr,
-            SummaryExpr::KeepPreAsap(_)
-        ));
-
-        let multi = QueryExpr::Aggregate {
-            reduction: ReductionTy::by(vec![2]),
-            measures: vec![AggIntent::Sum { col: None }, AggIntent::Avg { col: None }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(metric_scan(&["job"])),
-        };
-        assert!(matches!(
-            realize(&multi).unwrap().expr,
-            SummaryExpr::KeepPreAsap(_)
-        ));
+        let q = crate::test_support::aggregate(
+            ReductionTy::by(vec![2]),
+            vec![default_quantile(0.99)],
+            vec![],
+            Some(Predicate(ScalarExpr::Literal(ScalarValue::Boolean(true)))),
+            metric_scan(&["job"]),
+        );
+        assert!(!realize(&q).unwrap().contains_asap());
+
+        let multi =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+                reduction: ReductionTy::by(vec![2]),
+                measures: vec![AggIntent::Sum { col: None }, AggIntent::Avg { col: None }],
+                output_names: vec![],
+                filters: vec![],
+                having: None,
+                child: metric_scan(&["job"]),
+            }))
+            .unwrap();
+        assert!(!realize(&multi).unwrap().contains_asap());
     }
 
     // No binding rule applies a per-measure `FILTER` (#466), so the
@@ -10312,18 +10331,16 @@ mod tests {
     #[test]
     fn filtered_measure_stays_logical() {
         use asap_types::pre_asap::expr_ir::ScalarValue;
-        use asap_types::pre_asap::query_expr::Predicate;
         let mut q = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
-        if let QueryExpr::Aggregate { filters, .. } = &mut q {
-            *filters = vec![Some(Predicate(Rc::new(QueryExpr::Literal(
-                ScalarValue::Boolean(true),
+        if let Operator::NonASAP(NonASAPOp::Aggregate { filters, .. }) =
+            &mut Rc::make_mut(&mut q).operator
+        {
+            *filters = vec![Some(Predicate(ScalarExpr::Literal(ScalarValue::Boolean(
+                true,
             ))))];
         }
         assert!(bindable_intent(&q).is_none());
-        assert!(matches!(
-            realize(&q).unwrap().expr,
-            SummaryExpr::KeepPreAsap(_)
-        ));
+        assert!(!realize(&q).unwrap().contains_asap());
     }
 
     #[test]
@@ -10337,7 +10354,7 @@ mod tests {
             metric_scan(&["job"]),
         );
         let root = realize(&q).unwrap();
-        assert!(matches!(root.expr, SummaryExpr::KeepPreAsap(_)));
+        assert!(!root.contains_asap());
     }
 
     #[test]
@@ -10349,20 +10366,20 @@ mod tests {
             },
             metric_scan(&["job"]),
         );
-        let root = Rc::new(agg(
+        let root = agg(
             vec![],
             AggIntent::TopK {
                 k: 5,
                 accuracy: AccuracyTarget::Epsilon(0.01),
             },
             inner,
-        ));
+        );
         let proposals =
-            SketchAlgorithmStrategy::default_cost_model().replacements(&TargetSubDAG::new(&root));
+            ASAPStrategies::default_cost_model().replacements(&TargetSubDAG::new(&root));
         assert!(!proposals.is_empty());
         assert!(proposals.iter().any(|candidate| matches!(
             &candidate.replacement,
-            Replacement::Summary(node) if node.guarantee.as_ref().is_some_and(|g|
+            Replacement::SubDAG(node) if node.guarantee.as_ref().is_some_and(|g|
                 g.bound.evaluate().is_none()
                     && g.failure_probability.evaluate().is_none())
         )));
@@ -10402,7 +10419,7 @@ mod tests {
             },
             metric_scan(&["job"]),
         );
-        let q = Rc::new(agg(
+        let q = agg(
             vec![],
             AggIntent::TopK {
                 k: 5,
@@ -10412,8 +10429,8 @@ mod tests {
                 },
             },
             inner,
-        ));
-        let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+        );
+        let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
             &DefaultCostModel,
             &DefaultAccuracyModel,
             &EqualSplitAllocator,
@@ -10423,7 +10440,7 @@ mod tests {
         assert!(!replacements.is_empty());
         assert!(replacements.iter().all(|candidate| matches!(
             &candidate.replacement,
-            Replacement::Summary(node)
+            Replacement::SubDAG(node)
                 if node.guarantee.as_ref().is_some_and(|g|
                     g.metric == ErrorMetric::TopKMembership
                         && g.failure_probability.evaluate() == Some(0.005))
@@ -10439,15 +10456,15 @@ mod tests {
             },
             metric_scan(&["service"]),
         );
-        let outer = Rc::new(agg(
+        let outer = agg(
             vec![],
             AggIntent::TopK {
                 k: 10,
                 accuracy: AccuracyTarget::Epsilon(0.01),
             },
             inner,
-        ));
-        let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+        );
+        let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
             &DefaultCostModel,
             &DefaultAccuracyModel,
             &EqualSplitAllocator,
@@ -10457,26 +10474,26 @@ mod tests {
         let node = candidates
             .iter()
             .find_map(|candidate| match &candidate.replacement {
-                Replacement::Summary(node) if candidate.rationale.contains("CmsWithHeap") => {
+                Replacement::SubDAG(node) if candidate.rationale.contains("CmsWithHeap") => {
                     Some(node)
                 }
                 _ => None,
             })
             .expect("CmsWithHeap candidate");
-        let SummaryExpr::SummaryEstimate {
+        let Operator::ASAP(ASAPOp::SummaryEstimate {
             summary_input,
             query,
-        } = &node.expr
+        }) = &node.operator
         else {
-            panic!("expected Top-K readout")
+            panic!("expected Top-K evaluation")
         };
         assert!(matches!(query, PostAsapSketchStatistic::TopK { k: 10 }));
-        let SummaryExpr::SummaryAgg {
+        let Operator::ASAP(ASAPOp::SummaryAgg {
             child,
             family,
             input,
             ..
-        } = &summary_input.expr
+        }) = &summary_input.operator
         else {
             panic!("expected fused summary aggregation")
         };
@@ -10496,7 +10513,7 @@ mod tests {
             FieldDataType::Sketch(kind, _)
                 if kind.algorithm() == &SketchAlgorithm::CmsWithHeap
         ));
-        assert!(matches!(child.expr, SummaryExpr::KeepPreAsap(_)));
+        assert!(!child.contains_asap());
     }
 
     #[test]
@@ -10506,15 +10523,15 @@ mod tests {
             AggIntent::Sum { col: None },
             metric_scan(&["service"]),
         );
-        let outer = Rc::new(agg(
+        let outer = agg(
             vec![],
             AggIntent::TopK {
                 k: 5,
                 accuracy: AccuracyTarget::Epsilon(0.01),
             },
             inner,
-        ));
-        let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+        );
+        let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
             &DefaultCostModel,
             &DefaultAccuracyModel,
             &EqualSplitAllocator,
@@ -10531,7 +10548,7 @@ mod tests {
         let node = candidates
             .iter()
             .find_map(|candidate| match &candidate.replacement {
-                Replacement::Summary(node)
+                Replacement::SubDAG(node)
                     if candidate.rationale.contains("CountSketchWithHeap") =>
                 {
                     Some(node)
@@ -10539,15 +10556,16 @@ mod tests {
                 _ => None,
             })
             .expect("CountSketchWithHeap candidate");
-        let SummaryExpr::SummaryEstimate {
+        let Operator::ASAP(ASAPOp::SummaryEstimate {
             summary_input,
             query,
-        } = &node.expr
+        }) = &node.operator
         else {
-            panic!("expected Top-K readout")
+            panic!("expected Top-K evaluation")
         };
         assert!(matches!(query, PostAsapSketchStatistic::TopK { k: 5 }));
-        let SummaryExpr::SummaryAgg { child, input, .. } = &summary_input.expr else {
+        let Operator::ASAP(ASAPOp::SummaryAgg { child, input, .. }) = &summary_input.operator
+        else {
             panic!("expected fused summary aggregation")
         };
         assert!(matches!(
@@ -10558,31 +10576,37 @@ mod tests {
             input.weight,
             SummaryInputExpr::Column(ColumnRef::SampleValue)
         );
-        assert!(matches!(child.expr, SummaryExpr::KeepPreAsap(_)));
+        assert!(!child.contains_asap());
     }
 
     #[test]
     fn temporal_per_entity_topk_uses_series_identity_and_sample_value() {
-        let inner = QueryExpr::Aggregate {
-            reduction: ReductionTy::PerEntity,
-            measures: vec![AggIntent::Sum { col: None }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(QueryExpr::TimeRange {
-                range: std::time::Duration::from_secs(60),
-                child: Rc::new(metric_scan(&["service"])),
-            }),
-        };
-        let outer = Rc::new(agg(
+        let inner =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+                reduction: ReductionTy::PerEntity,
+                measures: vec![AggIntent::Sum { col: None }],
+                output_names: vec![],
+                filters: vec![],
+                having: None,
+                child: OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(
+                    NonASAPOp::TimeRange {
+                        kind: TimeRangeKind::Range,
+                        range: std::time::Duration::from_secs(60),
+                        child: metric_scan(&["service"]),
+                    },
+                ))
+                .unwrap(),
+            }))
+            .unwrap();
+        let outer = agg(
             vec![2],
             AggIntent::TopK {
                 k: 5,
                 accuracy: AccuracyTarget::Epsilon(0.01),
             },
             inner,
-        ));
-        let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+        );
+        let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
             &DefaultCostModel,
             &DefaultAccuracyModel,
             &EqualSplitAllocator,
@@ -10590,13 +10614,14 @@ mod tests {
         );
         let candidates = strategy.replacements(&TargetSubDAG::new(&outer));
         let input = candidates.iter().find_map(|candidate| {
-            let Replacement::Summary(node) = &candidate.replacement else {
+            let Replacement::SubDAG(node) = &candidate.replacement else {
                 return None;
             };
-            let SummaryExpr::SummaryEstimate { summary_input, .. } = &node.expr else {
+            let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &node.operator
+            else {
                 return None;
             };
-            let SummaryExpr::SummaryAgg { input, .. } = &summary_input.expr else {
+            let Operator::ASAP(ASAPOp::SummaryAgg { input, .. }) = &summary_input.operator else {
                 return None;
             };
             input.item.is_some().then_some(input)
@@ -10625,15 +10650,15 @@ mod tests {
             },
             metric_scan(&["service", "region"]),
         );
-        let outer = Rc::new(agg(
+        let outer = agg(
             vec![],
             AggIntent::TopK {
                 k: 10,
                 accuracy: AccuracyTarget::Epsilon(0.01),
             },
             inner,
-        ));
-        let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+        );
+        let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
             &DefaultCostModel,
             &DefaultAccuracyModel,
             &EqualSplitAllocator,
@@ -10644,10 +10669,10 @@ mod tests {
             .replacements(&TargetSubDAG::new(&outer))
             .into_iter()
             .find_map(|candidate| match candidate.replacement {
-                Replacement::Summary(node) => match &node.expr {
-                    SummaryExpr::SummaryEstimate { summary_input, .. } => {
-                        match &summary_input.expr {
-                            SummaryExpr::SummaryAgg { input, .. } => Some(input.clone()),
+                Replacement::SubDAG(node) => match &node.operator {
+                    Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) => {
+                        match &summary_input.operator {
+                            Operator::ASAP(ASAPOp::SummaryAgg { input, .. }) => Some(input.clone()),
                             _ => None,
                         }
                     }
@@ -10678,15 +10703,15 @@ mod tests {
         );
         // The inner aggregate outputs its grouping keys first, so column 2 is
         // `region`. Each region is a separate Top-K subpopulation.
-        let outer = Rc::new(agg(
+        let outer = agg(
             vec![2],
             AggIntent::TopK {
                 k: 10,
                 accuracy: AccuracyTarget::Epsilon(0.01),
             },
             inner,
-        ));
-        let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+        );
+        let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
             &DefaultCostModel,
             &DefaultAccuracyModel,
             &EqualSplitAllocator,
@@ -10696,12 +10721,12 @@ mod tests {
             .replacements(&TargetSubDAG::new(&outer))
             .into_iter()
             .find_map(|candidate| match candidate.replacement {
-                Replacement::Summary(node) => match &node.expr {
-                    SummaryExpr::SummaryEstimate { summary_input, .. } => {
-                        match &summary_input.expr {
-                            SummaryExpr::SummaryAgg {
+                Replacement::SubDAG(node) => match &node.operator {
+                    Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) => {
+                        match &summary_input.operator {
+                            Operator::ASAP(ASAPOp::SummaryAgg {
                                 input, reduction, ..
-                            } => Some((input.clone(), reduction.clone())),
+                            }) => Some((input.clone(), reduction.clone())),
                             _ => None,
                         }
                     }
@@ -10726,7 +10751,7 @@ mod tests {
     fn sql_reducer_resolves_named_input_column() {
         // SUM(bytes) over a tabular scan: `col` resolves positionally to the
         // named column, not the PromQL sample value.
-        let scan = QueryExpr::Scan {
+        let scan = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: Source::Table {
                 table_ref: "t".into(),
             },
@@ -10740,11 +10765,12 @@ mod tests {
                 unique_keys: vec![],
                 closed: true,
             },
-        };
+        }))
+        .unwrap();
         let q = agg(vec![0], AggIntent::Sum { col: Some(1) }, scan);
         let root = realize(&q).unwrap();
-        let SummaryExpr::SummaryAgg { input, .. } = &root.expr else {
-            panic!("expected SummaryAgg, got {:?}", root.expr);
+        let Operator::ASAP(ASAPOp::SummaryAgg { input, .. }) = &root.operator else {
+            panic!("expected SummaryAgg, got {:?}", root.operator);
         };
         let SummaryInputExpr::Column(col) = &input.weight else {
             panic!("expected observation column")
@@ -10809,10 +10835,12 @@ mod tests {
         }
     }
 
-    fn summary_child(node: &SummaryNode) -> &Rc<SummaryNode> {
-        match &node.expr {
-            SummaryExpr::SummaryEstimate { summary_input, .. } => summary_child(summary_input),
-            SummaryExpr::SummaryAgg { child, .. } => child,
+    fn summary_child(node: &OperatorNode) -> &Rc<OperatorNode> {
+        match &node.operator {
+            Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) => {
+                summary_child(summary_input)
+            }
+            Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) => child,
             other => panic!("expected a SummaryAgg, got {other:?}"),
         }
     }
@@ -10823,9 +10851,8 @@ mod tests {
         // registered rule, so every outer sketch candidate is refused with a
         // typed reason and the raw/pre-ASAP alternative is what remains.
         let inner = agg(vec![2], default_quantile(0.5), metric_scan(&["job"]));
-        let outer = Rc::new(agg(vec![], default_quantile(0.99), inner));
-        let proposals =
-            SketchAlgorithmStrategy::default_cost_model().propose(&TargetSubDAG::new(&outer));
+        let outer = agg(vec![], default_quantile(0.99), inner);
+        let proposals = ASAPStrategies::default_cost_model().propose(&TargetSubDAG::new(&outer));
         assert!(
             proposals.candidates.is_empty(),
             "no outer sketch may be proposed over an approximate child without a rule: {:?}",
@@ -10848,7 +10875,7 @@ mod tests {
         }
         // Fallback keeps the whole sub-DAG pre-ASAP — executed exactly.
         let realized = realize_child(&outer, &DefaultCostModel).unwrap();
-        assert!(matches!(realized.expr, SummaryExpr::KeepPreAsap(_)));
+        assert!(!realized.contains_asap());
         assert!(realized
             .guarantee
             .as_ref()
@@ -10856,9 +10883,8 @@ mod tests {
 
         // Cross-metric: a quantile over a cardinality estimate.
         let inner = agg(vec![2], default_cardinality(), metric_scan(&["job"]));
-        let outer = Rc::new(agg(vec![], default_quantile(0.99), inner));
-        let proposals =
-            SketchAlgorithmStrategy::default_cost_model().propose(&TargetSubDAG::new(&outer));
+        let outer = agg(vec![], default_quantile(0.99), inner);
+        let proposals = ASAPStrategies::default_cost_model().propose(&TargetSubDAG::new(&outer));
         assert!(proposals.candidates.is_empty());
         assert!(proposals.rejected.iter().all(|r| matches!(
             &r.error,
@@ -10870,14 +10896,14 @@ mod tests {
     #[test]
     fn exact_child_contributes_zero_error() {
         // quantile(0.9, sum by (job) (m)): KLL over an exact Sum accumulator
-        // — the readout's guarantee is exactly KLL's own local guarantee.
+        // — the evaluation's guarantee is exactly KLL's own local guarantee.
         let inner = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
         let outer = agg(vec![], default_quantile(0.9), inner);
         let root = realize(&outer).unwrap();
         let guarantee = root
             .guarantee
             .as_ref()
-            .expect("a readout carries a guarantee");
+            .expect("a evaluation carries a guarantee");
         assert_eq!(guarantee.metric, ErrorMetric::Rank);
         assert_eq!(
             guarantee.bound.evaluate(),
@@ -10894,7 +10920,7 @@ mod tests {
         )));
         // The sketch *state* node carries no guarantee; the exact
         // accumulator's state is its value and does.
-        let SummaryExpr::SummaryEstimate { summary_input, .. } = &root.expr else {
+        let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &root.operator else {
             panic!()
         };
         assert!(summary_input.guarantee.is_none());
@@ -10905,16 +10931,19 @@ mod tests {
     }
 
     #[test]
-    fn exact_sum_can_consume_an_approximate_readout() {
+    fn exact_sum_can_consume_an_approximate_evaluation() {
         // sum(count_distinct by (job) (m)) is an outer exact summary over
-        // the inner HLL readout. Both summary levels remain explicit.
+        // the inner HLL evaluation. Both summary levels remain explicit.
         let inner = agg(vec![2], default_cardinality(), metric_scan(&["job"]));
         let outer = agg(vec![], AggIntent::Sum { col: None }, inner);
         let root = realize(&outer).unwrap();
-        let SummaryExpr::SummaryAgg { child, .. } = &root.expr else {
+        let Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) = &root.operator else {
             panic!("outer exact sum should remain a SummaryAgg")
         };
-        assert!(matches!(child.expr, SummaryExpr::SummaryEstimate { .. }));
+        assert!(matches!(
+            child.operator,
+            Operator::ASAP(ASAPOp::SummaryEstimate { .. })
+        ));
         assert!(root.guarantee.is_some());
 
         // count(...) over the same child is exact: a row count does not
@@ -10935,12 +10964,12 @@ mod tests {
     }
 
     #[test]
-    fn equal_split_allocation_supports_nested_summary_readouts() {
+    fn equal_split_allocation_supports_nested_summary_evaluations() {
         // A registered rank-additive rule and valid budget split make both
         // summary levels explicit while preserving the composed guarantee.
         let inner = agg(vec![2], quantile_eps(0.5, 0.1), metric_scan(&["job"]));
-        let outer = Rc::new(agg(vec![], quantile_eps(0.99, 0.1), inner));
-        let strategy = SketchAlgorithmStrategy::new_with_planning_inputs(
+        let outer = agg(vec![], quantile_eps(0.99, 0.1), inner);
+        let strategy = ASAPStrategies::new_with_planning_inputs(
             &DefaultCostModel,
             &RankAdditiveModel,
             &EqualSplitAllocator,
@@ -10949,13 +10978,15 @@ mod tests {
 
         assert!(!proposals.candidates.is_empty());
         assert!(proposals.candidates.iter().all(|candidate| {
-            let Replacement::Summary(node) = &candidate.replacement else {
+            let Replacement::SubDAG(node) = &candidate.replacement else {
                 return false;
             };
-            matches!(node.expr, SummaryExpr::SummaryEstimate { .. })
-                && node.guarantee.as_ref().is_some_and(|guarantee| {
-                    DefaultAccuracyModel.satisfies(guarantee, &AccuracyTarget::Epsilon(0.1))
-                })
+            matches!(
+                node.operator,
+                Operator::ASAP(ASAPOp::SummaryEstimate { .. })
+            ) && node.guarantee.as_ref().is_some_and(|guarantee| {
+                DefaultAccuracyModel.satisfies(guarantee, &AccuracyTarget::Epsilon(0.1))
+            })
         }));
     }
 
@@ -10964,9 +10995,9 @@ mod tests {
         // The same nested summary remains available through workload search
         // and global cost ranking.
         let inner = agg(vec![2], quantile_eps(0.5, 0.1), metric_scan(&["job"]));
-        let outer = Rc::new(agg(vec![], quantile_eps(0.99, 0.1), inner));
+        let outer = agg(vec![], quantile_eps(0.99, 0.1), inner);
         let strategies: Vec<Box<dyn ReplacementStrategy>> =
-            vec![Box::new(SketchAlgorithmStrategy::new_with_planning_inputs(
+            vec![Box::new(ASAPStrategies::new_with_planning_inputs(
                 &DefaultCostModel,
                 &RankAdditiveModel,
                 &EqualSplitAllocator,
@@ -10976,10 +11007,14 @@ mod tests {
         let group = space.candidates_for_target(root).unwrap();
         assert!(!group.rejected.is_empty());
         assert!(group.candidates.iter().all(|c| match &c.replacement {
-            Replacement::Summary(node) => node.guarantee.as_ref().is_some_and(|g| {
-                DefaultAccuracyModel.satisfies(g, &AccuracyTarget::Epsilon(0.1))
-            }),
-            Replacement::Rewrite(_) => false,
+            // A summary candidate (old `Replacement::Summary`) contains an
+            // ASAP node; a logical rewrite (old `Replacement::Rewrite`) does not.
+            Replacement::SubDAG(node) if node.contains_asap() => {
+                node.guarantee.as_ref().is_some_and(|g| {
+                    DefaultAccuracyModel.satisfies(g, &AccuracyTarget::Epsilon(0.1))
+                })
+            }
+            Replacement::SubDAG(_) => false,
             Replacement::ExactComposition(_) => false,
         }));
         let ranked = space.cost_sorted(&DefaultCostModel);
@@ -10992,15 +11027,18 @@ mod tests {
             .unwrap()
             .chosen
             .expect("a nested summary candidate wins");
-        let Replacement::Summary(node) = &chosen.replacement else {
+        let Replacement::SubDAG(node) = &chosen.replacement else {
             panic!()
         };
-        assert!(matches!(node.expr, SummaryExpr::SummaryEstimate { .. }));
+        assert!(matches!(
+            node.operator,
+            Operator::ASAP(ASAPOp::SummaryEstimate { .. })
+        ));
     }
 
     #[test]
     fn root_target_check_removes_candidates_before_cost_ranking() {
-        let q = Rc::new(agg(vec![2], default_quantile(0.99), metric_scan(&["job"])));
+        let q = agg(vec![2], default_quantile(0.99), metric_scan(&["job"]));
         // A root target tighter than the node's own ε=0.01: every sketch
         // candidate misses it and is moved to `rejected`; nothing is left
         // for the cost model to rank.
@@ -11014,7 +11052,7 @@ mod tests {
         assert!(group
             .candidates
             .iter()
-            .all(|c| matches!(c.replacement, Replacement::Rewrite(_))));
+            .all(|c| matches!(&c.replacement, Replacement::SubDAG(n) if !n.contains_asap())));
         assert!(group.rejected.iter().all(|r| matches!(
             r.error,
             AccuracyError::TargetNotSatisfied { target: AccuracyTarget::Epsilon(e), .. } if e == 0.001
@@ -11033,7 +11071,7 @@ mod tests {
         assert!(group
             .candidates
             .iter()
-            .any(|c| matches!(c.replacement, Replacement::Summary(_))));
+            .any(|c| matches!(&c.replacement, Replacement::SubDAG(n) if n.contains_asap())));
 
         // An `Exact` root target admits only exact candidates.
         let space = search_workload_with_targets(
@@ -11043,11 +11081,11 @@ mod tests {
         );
         let group = space.candidates_for_target(&space.roots[0].1).unwrap();
         assert!(group.candidates.iter().all(|c| match &c.replacement {
-            Replacement::Summary(node) => node
+            Replacement::SubDAG(node) if node.contains_asap() => node
                 .guarantee
                 .as_ref()
                 .is_some_and(ResultGuarantee::is_exact),
-            Replacement::Rewrite(_) => true,
+            Replacement::SubDAG(_) => true,
             Replacement::ExactComposition(_) => false,
         }));
     }
@@ -11061,14 +11099,14 @@ mod tests {
             },
             metric_scan(&["job"]),
         );
-        let q = Rc::new(agg(
+        let q = agg(
             vec![],
             AggIntent::TopK {
                 k: 10,
                 accuracy: AccuracyTarget::Epsilon(0.01),
             },
             inner,
-        ));
+        );
         let space = search_workload_with_targets(
             vec![("q", Rc::clone(&q), Some(AccuracyTarget::Epsilon(0.01)))],
             &default_strategies(),
@@ -11078,14 +11116,14 @@ mod tests {
 
         assert!(group.candidates.iter().any(|candidate| matches!(
             &candidate.replacement,
-            Replacement::Summary(node) if node.guarantee.as_ref().is_some_and(ResultGuarantee::has_unknown)
+            Replacement::SubDAG(node) if node.guarantee.as_ref().is_some_and(ResultGuarantee::has_unknown)
         )));
         let candidate = group
             .candidates
             .iter()
             .find(|candidate| candidate.has_missing_accuracy_evidence())
             .unwrap();
-        let Replacement::Summary(node) = &candidate.replacement else {
+        let Replacement::SubDAG(node) = &candidate.replacement else {
             unreachable!()
         };
         let exported = asap_types::dag_export::export_summary(node);
@@ -11109,13 +11147,13 @@ mod tests {
     fn scoped_hll_evidence_sizes_and_certifies_without_a_deployment_model() {
         use crate::accuracy::EstimatorContract;
         struct SourceEvidence {
-            expression: QueryExpr,
+            expression: OperatorNode,
             max_distinct: u32,
         }
         impl AccuracyEvidenceProvider for SourceEvidence {
-            fn estimator_contract(&self, expression: &QueryExpr) -> Option<EstimatorContract> {
+            fn estimator_contract(&self, expression: &OperatorNode) -> Option<EstimatorContract> {
                 (expression == &self.expression).then_some(EstimatorContract::ClassicHll {
-                    max_distinct_per_readout: self.max_distinct,
+                    max_distinct_per_evaluation: self.max_distinct,
                 })
             }
         }
@@ -11123,19 +11161,19 @@ mod tests {
             epsilon: 0.05,
             delta: 0.01,
         };
-        let root = Rc::new(agg(
+        let root = agg(
             vec![],
             AggIntent::Cardinality {
                 cols: vec![],
                 accuracy: target.clone(),
             },
             metric_scan(&[]),
-        ));
+        );
         let evidence = SourceEvidence {
             expression: (*root).clone(),
             max_distinct: 128,
         };
-        let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+        let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
             &DefaultCostModel,
             &DefaultAccuracyModel,
             &EqualSplitAllocator,
@@ -11145,7 +11183,7 @@ mod tests {
         let hll = candidates
             .iter()
             .find_map(|candidate| match &candidate.replacement {
-                Replacement::Summary(node)
+                Replacement::SubDAG(node)
                     if summary_family_algorithm(node) == SketchAlgorithm::Hll =>
                 {
                     Some(node)
@@ -11155,13 +11193,13 @@ mod tests {
             .expect("HLL candidate");
         assert!(DefaultAccuracyModel
             .satisfies(hll.guarantee.as_ref().expect("HLL confidence"), &target));
-        let SummaryExpr::SummaryEstimate { summary_input, .. } = &hll.expr else {
-            panic!("readout")
+        let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &hll.operator else {
+            panic!("evaluation")
         };
-        let SummaryExpr::SummaryAgg {
+        let Operator::ASAP(ASAPOp::SummaryAgg {
             family: FieldDataType::Sketch(kind, _),
             ..
-        } = &summary_input.expr
+        }) = &summary_input.operator
         else {
             panic!("HLL state")
         };
@@ -11175,9 +11213,8 @@ mod tests {
                 precision: expected
             }
         );
-        let absent =
-            SketchAlgorithmStrategy::default_cost_model().replacements(&TargetSubDAG::new(&root));
-        assert!(!absent.iter().any(|candidate| matches!(&candidate.replacement, Replacement::Summary(node)
+        let absent = ASAPStrategies::default_cost_model().replacements(&TargetSubDAG::new(&root));
+        assert!(!absent.iter().any(|candidate| matches!(&candidate.replacement, Replacement::SubDAG(node)
             if summary_family_algorithm(node) == SketchAlgorithm::Hll && node.guarantee.as_ref().is_some_and(|g| DefaultAccuracyModel.satisfies(g, &target)))));
         // Invalid contracts, infeasible targets and evidence for another source
         // must never authorize a confidence-bearing HLL candidate.
@@ -11191,30 +11228,30 @@ mod tests {
                 epsilon: 0.05,
                 delta,
             };
-            let query = Rc::new(agg(
+            let query = agg(
                 vec![],
                 AggIntent::Cardinality {
                     cols: vec![],
                     accuracy: target.clone(),
                 },
                 metric_scan(&[]),
-            ));
+            );
             let evidence = SourceEvidence {
                 expression: if wrong_scope {
-                    metric_scan(&["other"])
+                    (*metric_scan(&["other"])).clone()
                 } else {
                     (*query).clone()
                 },
                 max_distinct,
             };
-            let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+            let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
                 &DefaultCostModel,
                 &DefaultAccuracyModel,
                 &EqualSplitAllocator,
                 &evidence,
             );
             assert!(!strategy.replacements(&TargetSubDAG::new(&query)).iter().any(|candidate|
-                matches!(&candidate.replacement, Replacement::Summary(node)
+                matches!(&candidate.replacement, Replacement::SubDAG(node)
                 if summary_family_algorithm(node) == SketchAlgorithm::Hll && node.guarantee.as_ref().is_some_and(|g| DefaultAccuracyModel.satisfies(g, &target)))));
         }
     }
@@ -11222,40 +11259,42 @@ mod tests {
     // A value projection cannot consume an opaque exact accumulator edge.
     #[test]
     fn residual_projection_finalizes_selected_exact_state() {
-        let inner = Rc::new(agg(vec![], AggIntent::Sum { col: None }, metric_scan(&[])));
-        let root = Rc::new(QueryExpr::Project {
-            cols: vec![asap_types::pre_asap::ProjectItem {
-                expr: QueryExpr::Column(0),
-                alias: Some("result".into()),
-            }],
-            qualifier: None,
-            child: inner.clone(),
-        });
+        let inner = agg(vec![], AggIntent::Sum { col: None }, metric_scan(&[]));
+        let root =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Project {
+                cols: vec![ProjectItem {
+                    expr: ScalarExpr::Column(0),
+                    alias: Some("result".into()),
+                }],
+                qualifier: None,
+                child: inner.clone(),
+            }))
+            .unwrap();
         let space = search_workload_with_targets(
             vec![("q", root.clone(), Some(AccuracyTarget::Exact))],
             &default_strategies(),
             &DefaultAccuracyModel,
         );
         let selected = space.global_selection(&DefaultCostModel);
+        // CSE re-interns the workload, so the space's root/child `Rc`s are not
+        // the fixture's. Assembly only assembles children that are discovered
+        // targets, so seed the memo under the space's own child pointer.
+        let root = Rc::clone(&space.roots[0].1);
+        let Some(NonASAPOp::Project { child: inner, .. }) = root.non_asap() else {
+            unreachable!()
+        };
+        assert!(space.candidates_for_target(inner).is_some());
         selected
             .assembled_nodes
             .borrow_mut()
-            .insert(Rc::as_ptr(&inner), realize(inner.as_ref()).unwrap());
+            .insert(Rc::as_ptr(inner), realize(inner.as_ref()).unwrap());
         let node = selected.assemble_target(&root).unwrap();
-        let SummaryExpr::ValueOperation {
-            child,
-            operation: ValueOperation::Project { .. },
-            ..
-        } = &node.expr
-        else {
+        let Operator::NonASAP(NonASAPOp::Project { child, .. }) = &node.operator else {
             panic!("expected Project");
         };
         assert!(matches!(
-            child.expr,
-            SummaryExpr::ValueOperation {
-                operation: ValueOperation::FinalizeExactAccumulator,
-                ..
-            }
+            child.operator,
+            Operator::ASAP(ASAPOp::FinalizeExactAccumulator { .. })
         ));
         assert!(child
             .schema
@@ -11267,18 +11306,16 @@ mod tests {
     #[test]
     fn ranking_uses_aggregate_output_position_not_first_numeric_column() {
         let logical = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["id"]));
-        let mut values = lift(&logical.output_schema().unwrap());
+        let mut values = logical.schema.clone();
         values.fields[0].dtype = FieldDataType::Plain(DataType::Int64);
         assert_eq!(ranking_score_index(&logical, &values).unwrap(), 1);
     }
     // A heap's key schema is derived from its encoded item, not all label columns.
     #[test]
-    fn heap_readout_preserves_numeric_item_identity() {
-        let mut raw = metric_scan(&["id", "description"]);
-        let QueryExpr::Scan { schema, .. } = &mut raw else {
-            unreachable!()
-        };
+    fn heap_evaluation_preserves_numeric_item_identity() {
+        let mut schema = metric_scan(&["id", "description"]).schema.clone();
         schema.fields[2].dtype = FieldDataType::Plain(DataType::Int64);
+        let raw = crate::test_support::scan("m", schema);
         let node = agg(
             vec![],
             AggIntent::TopK {
@@ -11288,7 +11325,7 @@ mod tests {
             agg(vec![2], AggIntent::Sum { col: None }, raw.clone()),
         );
         let input = PhysicalSummaryInput {
-            child: Rc::new(raw),
+            child: raw,
             input: SummaryUpdate {
                 item: Some(SummaryInputExpr::Column(ColumnRef::Named("id".into()))),
                 weight: SummaryInputExpr::Constant(1.0),
@@ -11297,7 +11334,7 @@ mod tests {
                 },
             },
         };
-        let schema = keyed_heap_readout_schema(&input, &node).unwrap();
+        let schema = keyed_heap_evaluation_schema(&input, &node).unwrap();
         assert_eq!(
             schema
                 .fields
diff --git a/crates/asap-aware-mapping/src/rewrite.rs b/crates/asap-aware-mapping/src/rewrite.rs
index 94a3d638c..ca752a971 100644
--- a/crates/asap-aware-mapping/src/rewrite.rs
+++ b/crates/asap-aware-mapping/src/rewrite.rs
@@ -35,7 +35,7 @@
 //! - **`without(...)` grouping** leaves an `Aggregate`'s own output schema
 //!   *open* (`closed: false`, see `without_output_schema`), while the
 //!   `Project` this strategy always wraps the rewrite in forces
-//!   `closed: true` (see `QueryExpr::output_schema`'s `Project` arm). Under
+//!   `closed: true` (see `NonASAPOp::output_schema`'s `Project` arm). Under
 //!   `without(...)` the rewritten form's `closed` flag would silently flip
 //!   relative to the original — exactly the kind of schema drift this
 //!   module exists to avoid.
@@ -43,7 +43,7 @@
 //! Both are follow-ups (issue #253 itself scopes to "the concrete case in
 //! Peilin's comment"), not correctness bugs in what ships here — a node
 //! outside this scope simply doesn't `match`, the same "safe but
-//! uninformative" fallback [`SketchAlgorithmStrategy`]/[`SharedSubDAGStrategy`]
+//! uninformative" fallback [`ASAPStrategies`]/[`SharedSubDAGStrategy`]
 //! already use for shapes they don't have an opinion on.
 //!
 //! ## Non-goals (mirrors [`replacement`]'s own discipline)
@@ -57,14 +57,15 @@
 //! the rewritten form is actually worth picking, by letting the original
 //! and rewritten forms compete on cost — not this strategy.
 
+use asap_types::ir::non_asap::any_measure_filtered;
 use std::rc::Rc;
 
+use asap_types::ir::operator_properties::{BinaryOpKind, Reduction};
+use asap_types::ir::{BinaryOperator, NonASAPOp, OperatorNode, ProjectItem, ScalarExpr};
 use asap_types::pre_asap::agg_intent::AggIntent;
 use asap_types::pre_asap::expr_ir::ArithmeticOpKind;
-use asap_types::pre_asap::query_expr::{
-    any_measure_filtered, BinaryOpKind, ProjectItem, QueryExpr, Reduction,
-};
 use asap_types::pre_asap::schema::{ColumnId, DataType};
+
 use asap_types::types::AccuracyTarget;
 
 use crate::replacement::{Replacement, ReplacementStrategy, ReplacementSubDAG, TargetSubDAG};
@@ -74,15 +75,35 @@ use crate::replacement::{Replacement, ReplacementStrategy, ReplacementSubDAG, Ta
 /// the module docs' "Scope" for why `without(...)`/`PerEntity` are
 /// excluded). Returns the grouping key count and the summed column so
 /// [`build_rewrite`] doesn't have to re-match.
-fn avg_rewrite_target(node: &QueryExpr) -> Option<(usize, Option<ColumnId>)> {
-    let QueryExpr::Aggregate {
+/// `a / b` with PromQL arithmetic semantics and no vector matching.
+fn arithmetic(
+    op: ArithmeticOpKind,
+    lhs: Rc<OperatorNode>,
+    rhs: Rc<OperatorNode>,
+) -> Option<Rc<OperatorNode>> {
+    OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::BinaryOp {
+        operator: BinaryOperator {
+            checked_relative_division: false,
+            checked_finite_division: false,
+            kind: BinaryOpKind::Arithmetic(op),
+            vector_match: None,
+        },
+        return_bool: false,
+        lhs,
+        rhs,
+    }))
+    .ok()
+}
+
+fn avg_rewrite_target(node: &OperatorNode) -> Option<(usize, Option<ColumnId>)> {
+    let Some(NonASAPOp::Aggregate {
         reduction,
         measures,
         filters,
         having: None,
         child,
         ..
-    } = node
+    }) = node.non_asap()
     else {
         return None;
     };
@@ -102,7 +123,7 @@ fn avg_rewrite_target(node: &QueryExpr) -> Option<(usize, Option<ColumnId>)> {
     // therefore be decomposed through it only when the averaged input is
     // provably non-null; otherwise NULL rows would incorrectly contribute to
     // the denominator.
-    let input_schema = child.output_schema().ok()?;
+    let input_schema = &child.schema;
     let value_col = col
         .or_else(|| input_schema.column_id("value"))
         .or_else(|| (0..input_schema.fields.len()).find(|i| !by.contains(i)))?;
@@ -129,21 +150,21 @@ fn avg_rewrite_target(node: &QueryExpr) -> Option<(usize, Option<ColumnId>)> {
 /// exactly regardless of the summed column's own type (integer division
 /// would otherwise silently reappear whenever the input column is itself
 /// integer-typed: `Sum`'s output type tracks its input, `Count`'s is always
-/// `Int64`, and `QueryExpr::output_schema`'s own `Arithmetic` type inference
+/// `Int64`, and `ScalarExpr::scalar_type`'s own `Arithmetic` type inference
 /// types a `Div` of two `Int64` operands as `Int64` — the explicit operand
 /// `Cast` is what keeps both the division and rewritten `avg` column
 /// `Float64` the way the original always was, not an incidental extra step).
 // These are conditional physical components, never an unconditional Rewrite.
 // The caller must attach the finite-division execution guard before admission.
-pub(crate) fn temporal_average_components(root: &Rc<QueryExpr>) -> Option<Rc<QueryExpr>> {
-    let QueryExpr::Aggregate {
+pub(crate) fn temporal_average_components(root: &Rc<OperatorNode>) -> Option<Rc<OperatorNode>> {
+    let Some(NonASAPOp::Aggregate {
         reduction: Reduction::PerEntity,
         measures,
         filters,
         child,
         having: None,
         ..
-    } = root.as_ref()
+    }) = root.non_asap()
     else {
         return None;
     };
@@ -153,10 +174,10 @@ pub(crate) fn temporal_average_components(root: &Rc<QueryExpr>) -> Option<Rc<Que
     let [AggIntent::Avg { col }] = measures.as_slice() else {
         return None;
     };
-    if !matches!(child.as_ref(), QueryExpr::TimeRange { .. }) {
+    if !matches!(child.non_asap(), Some(NonASAPOp::TimeRange { .. })) {
         return None;
     }
-    let schema = child.output_schema().ok()?;
+    let schema = &child.schema;
     let value = schema
         .fields
         .get(col.or_else(|| schema.column_id("value"))?)?;
@@ -164,41 +185,41 @@ pub(crate) fn temporal_average_components(root: &Rc<QueryExpr>) -> Option<Rc<Que
         return None;
     }
     let aggregate = |intent| {
-        Rc::new(QueryExpr::Aggregate {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
             reduction: Reduction::PerEntity,
             measures: vec![intent],
             output_names: vec![],
             filters: vec![],
             having: None,
             child: Rc::clone(child),
-        })
+        }))
+        .ok()
     };
-    let rewritten = Rc::new(QueryExpr::BinaryOp {
-        op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Div),
-        lhs: aggregate(AggIntent::Sum { col: *col }),
-        rhs: aggregate(AggIntent::Count {
+    let rewritten = arithmetic(
+        ArithmeticOpKind::Div,
+        aggregate(AggIntent::Sum { col: *col })?,
+        aggregate(AggIntent::Count {
             accuracy: AccuracyTarget::Exact,
-        }),
-        vector_match: None,
-    });
-    (root.output_schema().ok()? == rewritten.output_schema().ok()?).then_some(rewritten)
+        })?,
+    )?;
+    (root.schema == rewritten.schema).then_some(rewritten)
 }
 
-fn build_rewrite(root: &Rc<QueryExpr>) -> Option<Rc<QueryExpr>> {
+fn build_rewrite(root: &Rc<OperatorNode>) -> Option<Rc<OperatorNode>> {
     let (group_count, col) = avg_rewrite_target(root)?;
-    let QueryExpr::Aggregate {
+    let Some(NonASAPOp::Aggregate {
         reduction,
         output_names,
         child,
         ..
-    } = root.as_ref()
+    }) = root.non_asap()
     else {
         unreachable!("avg_rewrite_target already confirmed an Aggregate shape");
     };
 
     // The original `avg` column's own name: `output_names[0]` if the
     // producing front end overrode it (SQL threading DataFusion's own
-    // generated name — see `QueryExpr::Aggregate::output_names`'s docs),
+    // generated name — see `NonASAPOp::Aggregate::output_names`'s docs),
     // else `AggIntent::Avg`'s synthetic default. Either way this is the
     // *only* thing about the original output column this rewrite needs to
     // reproduce — `AggIntent::Avg::output_column`'s `(Float64, nullable:
@@ -210,77 +231,78 @@ fn build_rewrite(root: &Rc<QueryExpr>) -> Option<Rc<QueryExpr>> {
         .cloned()
         .unwrap_or_else(|| "avg".to_string());
 
-    let sum_agg = Rc::new(QueryExpr::Aggregate {
-        reduction: reduction.clone(),
-        measures: vec![AggIntent::Sum { col }],
-        output_names: Vec::new(),
-        filters: vec![],
-        having: None,
-        child: Rc::clone(child),
-    });
-    let count_agg = Rc::new(QueryExpr::Aggregate {
-        reduction: reduction.clone(),
-        measures: vec![AggIntent::Count {
-            accuracy: AccuracyTarget::Exact,
-        }],
-        output_names: Vec::new(),
-        filters: vec![],
-        having: None,
-        child: Rc::clone(child),
-    });
+    let sum_agg =
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+            reduction: reduction.clone(),
+            measures: vec![AggIntent::Sum { col }],
+            output_names: Vec::new(),
+            filters: vec![],
+            having: None,
+            child: Rc::clone(child),
+        }))
+        .ok()?;
+    let count_agg =
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+            reduction: reduction.clone(),
+            measures: vec![AggIntent::Count {
+                accuracy: AccuracyTarget::Exact,
+            }],
+            output_names: Vec::new(),
+            filters: vec![],
+            having: None,
+            child: Rc::clone(child),
+        }))
+        .ok()?;
 
     let sum_idx = group_count;
     let mut cols: Vec<ProjectItem> = (0..group_count)
         .map(|i| ProjectItem {
             alias: None,
-            expr: QueryExpr::Column(i),
+            expr: ScalarExpr::Column(i),
         })
         .collect();
     cols.push(ProjectItem {
         alias: Some(avg_name),
-        expr: QueryExpr::Cast {
-            expr: Rc::new(QueryExpr::Column(sum_idx)),
+        expr: ScalarExpr::Cast {
+            expr: Box::new(ScalarExpr::Column(sum_idx)),
             to: DataType::Float64,
             try_cast: false,
         },
     });
 
-    let float_sum = Rc::new(QueryExpr::Project {
-        cols,
-        qualifier: None,
-        child: sum_agg,
-    });
-    Some(Rc::new(QueryExpr::BinaryOp {
-        op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Div),
-        lhs: float_sum,
-        rhs: count_agg,
-        vector_match: None,
-    }))
+    let float_sum =
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Project {
+            cols,
+            qualifier: None,
+            child: sum_agg,
+        }))
+        .ok()?;
+    arithmetic(ArithmeticOpKind::Div, float_sum, count_agg)
 }
 
 /// Compose adjacent per-entity and cross-entity accumulators when their
 /// algebra, rather than a query-language spelling, proves equivalence.
-pub(crate) fn composed_aggregate_rewrite(root: &Rc<QueryExpr>) -> Option<Rc<QueryExpr>> {
-    let original_schema = root.output_schema().ok()?;
-    let QueryExpr::Aggregate {
+pub(crate) fn composed_aggregate_rewrite(root: &Rc<OperatorNode>) -> Option<Rc<OperatorNode>> {
+    let original_schema = &root.schema;
+    let Some(NonASAPOp::Aggregate {
         reduction: outer_reduction @ Reduction::Reduce(_),
         measures: outer_measures,
         output_names,
         filters: outer_filters,
         having: None,
         child,
-    } = root.as_ref()
+    }) = root.non_asap()
     else {
         return None;
     };
-    let QueryExpr::Aggregate {
+    let Some(NonASAPOp::Aggregate {
         reduction: Reduction::PerEntity,
         measures: inner_measures,
         filters: inner_filters,
         having: None,
         child: inner_child,
         ..
-    } = child.as_ref()
+    }) = child.non_asap()
     else {
         return None;
     };
@@ -297,14 +319,16 @@ pub(crate) fn composed_aggregate_rewrite(root: &Rc<QueryExpr>) -> Option<Rc<Quer
         | (AggIntent::Max { col: None }, AggIntent::Max { .. }) => inner.clone(),
         _ => return None,
     };
-    let aggregate = Rc::new(QueryExpr::Aggregate {
-        reduction: outer_reduction.clone(),
-        measures: vec![composed],
-        output_names: output_names.clone(),
-        filters: vec![],
-        having: None,
-        child: Rc::clone(inner_child),
-    });
+    let aggregate =
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+            reduction: outer_reduction.clone(),
+            measures: vec![composed],
+            output_names: output_names.clone(),
+            filters: vec![],
+            having: None,
+            child: Rc::clone(inner_child),
+        }))
+        .ok()?;
 
     // The outer Sum sees PromQL's Float64 sample value, whereas the composed
     // Count accumulator is Int64. Keep the original observable type.
@@ -321,7 +345,7 @@ pub(crate) fn composed_aggregate_rewrite(root: &Rc<QueryExpr>) -> Option<Rc<Quer
         let mut cols: Vec<ProjectItem> = (0..by.keys().len())
             .map(|i| ProjectItem {
                 alias: None,
-                expr: QueryExpr::Column(i),
+                expr: ScalarExpr::Column(i),
             })
             .collect();
         cols.push(ProjectItem {
@@ -332,17 +356,18 @@ pub(crate) fn composed_aggregate_rewrite(root: &Rc<QueryExpr>) -> Option<Rc<Quer
                 .fields
                 .last()
                 .map(|column| column.name.clone()),
-            expr: QueryExpr::Cast {
-                expr: Rc::new(QueryExpr::Column(by.keys().len())),
+            expr: ScalarExpr::Cast {
+                expr: Box::new(ScalarExpr::Column(by.keys().len())),
                 to: DataType::Float64,
                 try_cast: false,
             },
         });
-        Rc::new(QueryExpr::Project {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Project {
             cols,
             qualifier: None,
             child: aggregate,
-        })
+        }))
+        .ok()?
     } else {
         aggregate
     };
@@ -350,7 +375,7 @@ pub(crate) fn composed_aggregate_rewrite(root: &Rc<QueryExpr>) -> Option<Rc<Quer
     // Positional keys, aliases, types, and nullability are part of the rule's
     // contract. A future schema change therefore disables rather than widens
     // the rewrite.
-    (original_schema == rewritten.output_schema().ok()?).then_some(rewritten)
+    (*original_schema == rewritten.schema).then_some(rewritten)
 }
 
 /// Rewrites `Aggregate{ measures: [Avg{col}], .. }` into the semantically
@@ -358,7 +383,7 @@ pub(crate) fn composed_aggregate_rewrite(root: &Rc<QueryExpr>) -> Option<Rc<Quer
 /// a `BinaryOp` — see the module docs for why keeping the accumulators in
 /// separate relational nodes lets later strategies reach them independently.
 ///
-/// A unit struct: unlike [`SketchAlgorithmStrategy`], this strategy doesn't
+/// A unit struct: unlike [`ASAPStrategies`], this strategy doesn't
 /// bind anything (its one [`Replacement`] is always [`Replacement::Rewrite`],
 /// never [`Replacement::Summary`]) and so has no [`CostModel`](crate::CostModel)
 /// to hold a reference to — the same "no state needed" shape
@@ -380,7 +405,7 @@ impl ReplacementStrategy for SemanticEquivalentRewriteStrategy {
         if let Some(rewritten) = composed_aggregate_rewrite(target.root) {
             return vec![ReplacementSubDAG {
                 strategy: "SemanticEquivalentRewriteStrategy",
-                replacement: Replacement::Rewrite(rewritten),
+                replacement: Replacement::SubDAG(rewritten),
                 provenance: crate::replacement::ReplacementProvenance::LogicalRewrite,
                 rationale: "compose compatible per-entity and cross-entity accumulators using their algebraic intent while preserving the original output schema".into(),
             }];
@@ -390,7 +415,7 @@ impl ReplacementStrategy for SemanticEquivalentRewriteStrategy {
         };
         vec![ReplacementSubDAG {
             strategy: "AvgToSumOverCountStrategy",
-            replacement: Replacement::Rewrite(rewritten),
+            replacement: Replacement::SubDAG(rewritten),
             provenance: crate::replacement::ReplacementProvenance::LogicalRewrite,
             rationale:
                 "avg has no summary realization at all (replacement::realizations_for_intent \
@@ -409,84 +434,83 @@ impl ReplacementStrategy for SemanticEquivalentRewriteStrategy {
 mod tests {
     use super::*;
     use crate::test_support::lower_promql;
-    use asap_types::pre_asap::query_expr::Source;
+    use asap_types::ir::operator_properties::Source;
     use asap_types::pre_asap::schema::{Field, Schema};
     use asap_types::types::AccuracyTarget;
     use std::time::Duration;
 
-    fn metric_scan(labels: &[&str]) -> QueryExpr {
-        let mut columns = vec![
-            Field::plain("ts", DataType::Timestamp, false),
-            Field::plain("value", DataType::Float64, false),
-        ];
-        columns.extend(
-            labels
-                .iter()
-                .map(|n| Field::plain(*n, DataType::Utf8, true)),
-        );
-        QueryExpr::Scan {
-            source: Source::TimeSeries { metric: "m".into() },
-            predicates: vec![],
-            schema: Schema::with_time_index(columns, 0, vec![]),
-        }
+    use crate::test_support::metric_scan;
+    use asap_types::ir::TimeRangeKind;
+
+    fn avg_agg(
+        by: Vec<ColumnId>,
+        col: Option<ColumnId>,
+        child: Rc<OperatorNode>,
+    ) -> Rc<OperatorNode> {
+        avg_agg_with(by, col, vec![], None, child)
     }
 
-    fn avg_agg(by: Vec<ColumnId>, col: Option<ColumnId>, child: QueryExpr) -> QueryExpr {
-        QueryExpr::Aggregate {
+    fn avg_agg_with(
+        by: Vec<ColumnId>,
+        col: Option<ColumnId>,
+        output_names: Vec<String>,
+        having: Option<asap_types::ir::Predicate>,
+        child: Rc<OperatorNode>,
+    ) -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
             reduction: Reduction::by(by),
             measures: vec![AggIntent::Avg { col }],
-            output_names: vec![],
+            output_names,
             filters: vec![],
-            having: None,
-            child: Rc::new(child),
-        }
+            having,
+            child,
+        }))
+        .unwrap()
     }
 
     // Temporal averages expose two single-measure children without closing labels.
     #[test]
     fn temporal_average_components_preserves_schema_and_exposes_sum_count() {
-        let root = Rc::new(lower_promql(
-            "avg_over_time(a{job=\"api\"}[5m])",
-            AccuracyTarget::Exact,
-        ));
+        let root = lower_promql("avg_over_time(a{job=\"api\"}[5m])", AccuracyTarget::Exact);
         assert!(SemanticEquivalentRewriteStrategy
             .replacements(&TargetSubDAG::new(&root))
             .is_empty());
         let rewritten =
             temporal_average_components(&root).expect("conditional sum/count components");
-        assert_eq!(
-            root.output_schema().unwrap(),
-            rewritten.output_schema().unwrap()
-        );
-        assert!(matches!(rewritten.as_ref(), QueryExpr::BinaryOp { .. }));
+        assert_eq!(root.schema.clone(), rewritten.schema.clone());
+        assert!(matches!(
+            rewritten.non_asap(),
+            Some(NonASAPOp::BinaryOp { .. })
+        ));
     }
 
     // ── matches ──────────────────────────────────────────────────────────
 
     #[test]
     fn matches_a_bare_avg_aggregate() {
-        let q = Rc::new(avg_agg(vec![], None, metric_scan(&[])));
+        let q = avg_agg(vec![], None, metric_scan(&[]));
         let target = TargetSubDAG::new(&q);
         assert!(AvgToSumOverCountStrategy.matches(&target));
     }
 
     #[test]
     fn matches_a_grouped_avg_aggregate() {
-        let q = Rc::new(avg_agg(vec![2], None, metric_scan(&["job"])));
+        let q = avg_agg(vec![2], None, metric_scan(&["job"]));
         let target = TargetSubDAG::new(&q);
         assert!(AvgToSumOverCountStrategy.matches(&target));
     }
 
     #[test]
     fn does_not_match_a_multi_measure_aggregate() {
-        let q = Rc::new(QueryExpr::Aggregate {
+        let q = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
             reduction: Reduction::by(vec![2]),
             measures: vec![AggIntent::Sum { col: None }, AggIntent::Avg { col: None }],
             output_names: vec![],
             filters: vec![],
             having: None,
-            child: Rc::new(metric_scan(&["job"])),
-        });
+            child: metric_scan(&["job"]),
+        }))
+        .unwrap();
         let target = TargetSubDAG::new(&q);
         assert!(!AvgToSumOverCountStrategy.matches(&target));
         assert!(AvgToSumOverCountStrategy.replacements(&target).is_empty());
@@ -494,13 +518,15 @@ mod tests {
 
     #[test]
     fn does_not_match_a_having_bearing_avg_aggregate() {
-        let mut q = avg_agg(vec![2], None, metric_scan(&["job"]));
-        if let QueryExpr::Aggregate { having, .. } = &mut q {
-            *having = Some(asap_types::pre_asap::query_expr::Predicate(Rc::new(
-                QueryExpr::Literal(asap_types::pre_asap::expr_ir::ScalarValue::Boolean(true)),
-            )));
-        }
-        let q = Rc::new(q);
+        let q = avg_agg_with(
+            vec![2],
+            None,
+            vec![],
+            Some(asap_types::ir::Predicate(ScalarExpr::Literal(
+                asap_types::pre_asap::expr_ir::ScalarValue::Boolean(true),
+            ))),
+            metric_scan(&["job"]),
+        );
         let target = TargetSubDAG::new(&q);
         assert!(!AvgToSumOverCountStrategy.matches(&target));
         assert!(AvgToSumOverCountStrategy.replacements(&target).is_empty());
@@ -515,14 +541,16 @@ mod tests {
             },
             AggIntent::Min { col: None },
         ] {
-            let q = Rc::new(QueryExpr::Aggregate {
-                reduction: Reduction::by(vec![2]),
-                measures: vec![intent.clone()],
-                output_names: vec![],
-                filters: vec![],
-                having: None,
-                child: Rc::new(metric_scan(&["job"])),
-            });
+            let q =
+                OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+                    reduction: Reduction::by(vec![2]),
+                    measures: vec![intent.clone()],
+                    output_names: vec![],
+                    filters: vec![],
+                    having: None,
+                    child: metric_scan(&["job"]),
+                }))
+                .unwrap();
             let target = TargetSubDAG::new(&q);
             assert!(
                 !AvgToSumOverCountStrategy.matches(&target),
@@ -534,16 +562,17 @@ mod tests {
 
     #[test]
     fn does_not_match_a_without_grouped_avg_aggregate() {
-        let q = Rc::new(QueryExpr::Aggregate {
-            reduction: Reduction::Reduce(asap_types::pre_asap::query_expr::GroupKeys::without(
+        let q = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+            reduction: Reduction::Reduce(asap_types::ir::operator_properties::GroupKeys::without(
                 vec![2],
             )),
             measures: vec![AggIntent::Avg { col: None }],
             output_names: vec![],
             filters: vec![],
             having: None,
-            child: Rc::new(metric_scan(&["job"])),
-        });
+            child: metric_scan(&["job"]),
+        }))
+        .unwrap();
         let target = TargetSubDAG::new(&q);
         assert!(!AvgToSumOverCountStrategy.matches(&target));
         assert!(AvgToSumOverCountStrategy.replacements(&target).is_empty());
@@ -551,14 +580,15 @@ mod tests {
 
     #[test]
     fn does_not_match_a_per_entity_avg_aggregate() {
-        let q = Rc::new(QueryExpr::Aggregate {
+        let q = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
             reduction: Reduction::PerEntity,
             measures: vec![AggIntent::Avg { col: None }],
             output_names: vec![],
             filters: vec![],
             having: None,
-            child: Rc::new(metric_scan(&[])),
-        });
+            child: metric_scan(&[]),
+        }))
+        .unwrap();
         let target = TargetSubDAG::new(&q);
         assert!(!AvgToSumOverCountStrategy.matches(&target));
         assert!(AvgToSumOverCountStrategy.replacements(&target).is_empty());
@@ -566,7 +596,7 @@ mod tests {
 
     #[test]
     fn does_not_match_a_non_aggregate_node() {
-        let scan = Rc::new(metric_scan(&["job"]));
+        let scan = metric_scan(&["job"]);
         let target = TargetSubDAG::new(&scan);
         assert!(!AvgToSumOverCountStrategy.matches(&target));
         assert!(AvgToSumOverCountStrategy.replacements(&target).is_empty());
@@ -579,7 +609,7 @@ mod tests {
     #[test]
     fn avg_rewrites_and_schema_matches_exactly_when_ungrouped() {
         let original = avg_agg(vec![], None, metric_scan(&[]));
-        let original_rc = Rc::new(original.clone());
+        let original_rc = Rc::clone(&original);
         let target = TargetSubDAG::new(&original_rc);
 
         let replacements = AvgToSumOverCountStrategy.replacements(&target);
@@ -587,28 +617,26 @@ mod tests {
         assert!(!replacements[0].rationale.is_empty());
 
         let rewritten = match &replacements[0].replacement {
-            Replacement::Rewrite(rc) => rc,
+            Replacement::SubDAG(rc) => rc,
             other => panic!("expected a Rewrite replacement, got {other:?}"),
         };
-        let QueryExpr::BinaryOp { lhs, rhs, .. } = rewritten.as_ref() else {
+        let Some(NonASAPOp::BinaryOp { lhs, rhs, .. }) = rewritten.non_asap() else {
             panic!("expected sum/count BinaryOp, got {rewritten:?}");
         };
-        let QueryExpr::Project { child: sum, .. } = lhs.as_ref() else {
+        let Some(NonASAPOp::Project { child: sum, .. }) = lhs.non_asap() else {
             panic!("expected cast Project above Sum, got {lhs:?}");
         };
-        assert!(matches!(
-            sum.as_ref(),
-            QueryExpr::Aggregate { measures, .. }
+        assert!(matches!(sum.non_asap(),
+            Some(NonASAPOp::Aggregate { measures, .. })
                 if matches!(measures.as_slice(), [AggIntent::Sum { col: None }])
         ));
-        assert!(matches!(
-            rhs.as_ref(),
-            QueryExpr::Aggregate { measures, .. }
+        assert!(matches!(rhs.non_asap(),
+            Some(NonASAPOp::Aggregate { measures, .. })
                 if matches!(measures.as_slice(), [AggIntent::Count { accuracy: AccuracyTarget::Exact }])
         ));
 
-        let original_schema = original.output_schema().unwrap();
-        let rewritten_schema = rewritten.output_schema().unwrap();
+        let original_schema = original.schema.clone();
+        let rewritten_schema = rewritten.schema.clone();
         assert_eq!(
             original_schema, rewritten_schema,
             "the rewritten DAG must report exactly the same output schema as the original avg"
@@ -620,20 +648,22 @@ mod tests {
     /// synthetic `"avg"` default.
     #[test]
     fn preserves_an_explicit_output_name_override() {
-        let mut q = avg_agg(vec![], None, metric_scan(&[]));
-        if let QueryExpr::Aggregate { output_names, .. } = &mut q {
-            *output_names = vec!["avg_latency".to_string()];
-        }
-        let original_schema = q.output_schema().unwrap();
-        let q = Rc::new(q);
+        let q = avg_agg_with(
+            vec![],
+            None,
+            vec!["avg_latency".to_string()],
+            None,
+            metric_scan(&[]),
+        );
+        let original_schema = q.schema.clone();
         let target = TargetSubDAG::new(&q);
 
         let replacements = AvgToSumOverCountStrategy.replacements(&target);
         let rewritten = match &replacements[0].replacement {
-            Replacement::Rewrite(rc) => rc,
+            Replacement::SubDAG(rc) => rc,
             other => panic!("expected a Rewrite replacement, got {other:?}"),
         };
-        let rewritten_schema = rewritten.output_schema().unwrap();
+        let rewritten_schema = rewritten.schema.clone();
         assert_eq!(original_schema, rewritten_schema);
         assert_eq!(rewritten_schema.fields[0].name, "avg_latency");
     }
@@ -643,23 +673,23 @@ mod tests {
     #[test]
     fn grouped_avg_rewrite_preserves_the_whole_schema() {
         let original = avg_agg(vec![2], None, metric_scan(&["job"]));
-        let original_schema = original.output_schema().unwrap();
-        let original_rc = Rc::new(original);
+        let original_schema = original.schema.clone();
+        let original_rc = Rc::clone(&original);
         let target = TargetSubDAG::new(&original_rc);
 
         let replacements = AvgToSumOverCountStrategy.replacements(&target);
         let rewritten = match &replacements[0].replacement {
-            Replacement::Rewrite(rc) => rc,
+            Replacement::SubDAG(rc) => rc,
             other => panic!("expected a Rewrite replacement, got {other:?}"),
         };
-        let rewritten_schema = rewritten.output_schema().unwrap();
+        let rewritten_schema = rewritten.schema.clone();
 
         assert_eq!(rewritten_schema, original_schema);
     }
 
     #[test]
     fn default_search_discovers_bindable_sum_and_count_targets() {
-        let root = Rc::new(avg_agg(vec![2], None, metric_scan(&["job"])));
+        let root = avg_agg(vec![2], None, metric_scan(&["job"]));
         let space = crate::replacement::search_workload(vec![("avg", Rc::clone(&root))]);
 
         let avg_group = space
@@ -672,7 +702,7 @@ mod tests {
         let mut found_sum = false;
         let mut found_count = false;
         for group in space.target_subdag_candidates() {
-            let QueryExpr::Aggregate { measures, .. } = group.target.as_ref() else {
+            let Some(NonASAPOp::Aggregate { measures, .. }) = group.target.non_asap() else {
                 continue;
             };
             let expected = matches!(measures.as_slice(), [AggIntent::Sum { .. }])
@@ -689,7 +719,8 @@ mod tests {
                 group
                     .candidates
                     .iter()
-                    .any(|candidate| matches!(candidate.replacement, Replacement::Summary(_))),
+                    .any(|candidate| matches!(&candidate.replacement,
+                        Replacement::SubDAG(node) if node.contains_asap())),
                 "rewritten accumulator must be independently bindable: {measures:?}"
             );
             found_sum |= matches!(measures.as_slice(), [AggIntent::Sum { .. }]);
@@ -710,25 +741,26 @@ mod tests {
             Field::plain("job", DataType::Utf8, true),
             Field::plain("bytes", DataType::Int64, false),
         ];
-        let child = QueryExpr::Scan {
+        let child = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: Source::TimeSeries { metric: "m".into() },
             predicates: vec![],
             schema: {
                 let cols = std::mem::take(&mut schema_cols);
                 Schema::with_time_index(cols, 0, vec![])
             },
-        };
+        }))
+        .unwrap();
         let original = avg_agg(vec![1], Some(2), child);
-        let original_schema = original.output_schema().unwrap();
-        let original_rc = Rc::new(original);
+        let original_schema = original.schema.clone();
+        let original_rc = Rc::clone(&original);
         let target = TargetSubDAG::new(&original_rc);
 
         let replacements = AvgToSumOverCountStrategy.replacements(&target);
         let rewritten = match &replacements[0].replacement {
-            Replacement::Rewrite(rc) => rc,
+            Replacement::SubDAG(rc) => rc,
             other => panic!("expected a Rewrite replacement, got {other:?}"),
         };
-        let rewritten_schema = rewritten.output_schema().unwrap();
+        let rewritten_schema = rewritten.schema.clone();
 
         // The whole reason for the explicit `Cast` in `build_rewrite`: an
         // `Int64` input column (`bytes`) makes `Sum`'s own output `Int64`
@@ -741,15 +773,15 @@ mod tests {
             DataType::Float64
         );
 
-        let QueryExpr::BinaryOp { lhs, .. } = rewritten.as_ref() else {
+        let Some(NonASAPOp::BinaryOp { lhs, .. }) = rewritten.non_asap() else {
             panic!("expected sum/count BinaryOp");
         };
-        let QueryExpr::Project { cols, .. } = lhs.as_ref() else {
+        let Some(NonASAPOp::Project { cols, .. }) = lhs.non_asap() else {
             panic!("expected cast Project above Sum");
         };
         assert!(matches!(
             &cols.last().unwrap().expr,
-            QueryExpr::Cast {
+            ScalarExpr::Cast {
                 to: DataType::Float64,
                 ..
             }
@@ -758,7 +790,7 @@ mod tests {
 
     #[test]
     fn does_not_rewrite_avg_of_a_nullable_column_via_count_star() {
-        let child = QueryExpr::Scan {
+        let child = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: Source::TimeSeries { metric: "m".into() },
             predicates: vec![],
             schema: Schema::with_time_index(
@@ -770,27 +802,34 @@ mod tests {
                 0,
                 vec![],
             ),
-        };
-        let q = Rc::new(avg_agg(vec![], Some(2), child));
+        }))
+        .unwrap();
+        let q = avg_agg(vec![], Some(2), child);
         let target = TargetSubDAG::new(&q);
 
         assert!(!AvgToSumOverCountStrategy.matches(&target));
         assert!(AvgToSumOverCountStrategy.replacements(&target).is_empty());
     }
 
-    fn nested_aggregate(outer: AggIntent, inner: AggIntent) -> Rc<QueryExpr> {
-        let temporal = QueryExpr::Aggregate {
-            reduction: Reduction::PerEntity,
-            measures: vec![inner],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(QueryExpr::TimeRange {
-                range: Duration::from_secs(300),
-                child: Rc::new(metric_scan(&["service"])),
-            }),
-        };
-        Rc::new(QueryExpr::Aggregate {
+    fn nested_aggregate(outer: AggIntent, inner: AggIntent) -> Rc<OperatorNode> {
+        let temporal =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+                reduction: Reduction::PerEntity,
+                measures: vec![inner],
+                output_names: vec![],
+                filters: vec![],
+                having: None,
+                child: OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(
+                    NonASAPOp::TimeRange {
+                        kind: TimeRangeKind::Range,
+                        range: Duration::from_secs(300),
+                        child: metric_scan(&["service"]),
+                    },
+                ))
+                .unwrap(),
+            }))
+            .unwrap();
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
             reduction: Reduction::by(vec![2]),
             measures: vec![outer],
             // Match the PromQL front end: an empty entry selects the intent's
@@ -798,8 +837,9 @@ mod tests {
             output_names: vec![String::new()],
             filters: vec![],
             having: None,
-            child: Rc::new(temporal),
-        })
+            child: temporal,
+        }))
+        .unwrap()
     }
 
     #[test]
@@ -820,34 +860,30 @@ mod tests {
             let [candidate] = candidates.as_slice() else {
                 panic!("supported pair should produce exactly one rewrite")
             };
-            let Replacement::Rewrite(rewritten) = &candidate.replacement else {
+            let Replacement::SubDAG(rewritten) = &candidate.replacement else {
                 panic!("expected a logical rewrite")
             };
-            assert_eq!(
-                original.output_schema().unwrap(),
-                rewritten.output_schema().unwrap()
-            );
-            let aggregate = match rewritten.as_ref() {
-                QueryExpr::Aggregate { .. } => rewritten.as_ref(),
-                QueryExpr::Project { child, .. } => child.as_ref(),
+            assert_eq!(original.schema.clone(), rewritten.schema.clone());
+            let aggregate = match rewritten.non_asap() {
+                Some(NonASAPOp::Aggregate { .. }) => rewritten.as_ref(),
+                Some(NonASAPOp::Project { child, .. }) => child.as_ref(),
                 other => panic!("expected Aggregate or cast Project, got {other:?}"),
             };
-            let QueryExpr::Aggregate {
+            let Some(NonASAPOp::Aggregate {
                 reduction: Reduction::Reduce(by),
                 measures,
                 child,
                 ..
-            } = aggregate
+            }) = aggregate.non_asap()
             else {
                 panic!("expected composed cross-entity aggregate")
             };
             assert_eq!(by.keys(), &[2]);
             assert_eq!(measures, &[expected]);
-            assert!(matches!(
-                child.as_ref(),
-                QueryExpr::TimeRange { range, child }
+            assert!(matches!(child.non_asap(),
+                Some(NonASAPOp::TimeRange { range, child, .. })
                     if *range == Duration::from_secs(300)
-                        && matches!(child.as_ref(), QueryExpr::Scan { .. })
+                        && matches!(child.non_asap(), Some(NonASAPOp::Scan { .. }))
             ));
         }
     }
@@ -880,9 +916,9 @@ mod tests {
             .iter()
             .find(|candidate| candidate.strategy == "SemanticEquivalentRewriteStrategy")
             .expect("default search should run semantic rewrites");
-        let Replacement::Rewrite(rewritten) = &candidate.replacement else {
+        let Replacement::SubDAG(rewritten) = &candidate.replacement else {
             panic!("expected logical rewrite")
         };
-        assert_eq!(rewritten.output_schema().unwrap().fields[1].name, "sum");
+        assert_eq!(rewritten.schema.clone().fields[1].name, "sum");
     }
 }
diff --git a/crates/asap-aware-mapping/src/rollup.rs b/crates/asap-aware-mapping/src/rollup.rs
index ab6eff3d9..09dc16fa4 100644
--- a/crates/asap-aware-mapping/src/rollup.rs
+++ b/crates/asap-aware-mapping/src/rollup.rs
@@ -88,7 +88,7 @@
 //! - **No materialized roll-up operator.** Actually building a pre-aggregated
 //!   summary/scan leaf at execution time is separate, larger work outside
 //!   `asap-aware-mapping`'s scope (see issue #254's own "Non-goal" section)
-//!   — this module only constructs the pre-ASAP [`QueryExpr::Aggregate`]
+//!   — this module only constructs the pre-ASAP `NonASAPOp::Aggregate`
 //!   rewrite; a `CostModel`/search engine decides whether to prefer it.
 //! - **No cross-schema reconciliation** (see "`ColumnId` comparability"
 //!   above) and **no `without(...)` grouping support** — `without`'s kept
@@ -97,34 +97,37 @@
 //!   against a superset/subset relationship at all; [`is_legal_rollup_source`]
 //!   declines both directions.
 
+use asap_types::ir::non_asap::any_measure_filtered;
 use std::collections::HashSet;
 use std::rc::Rc;
 
+use asap_types::ir::operator_properties::{GroupKeys, Reduction};
+use asap_types::ir::{NonASAPOp, OperatorNode};
 use asap_types::pre_asap::agg_intent::AggIntent;
-use asap_types::pre_asap::query_expr::{any_measure_filtered, GroupKeys, QueryExpr, Reduction};
 use asap_types::pre_asap::schema::{ColumnId, Schema};
+
 use asap_types::types::AccuracyTarget;
 
 use crate::replacement::{Replacement, ReplacementStrategy, ReplacementSubDAG, TargetSubDAG};
 
 /// The `(by, intent, child)` shape this strategy operates on: a single
 /// measure, no `HAVING` — the same bindable shape
-/// [`crate::replacement::SketchAlgorithmStrategy`] requires (see that module's
+/// [`crate::replacement::ASAPStrategies`] requires (see that module's
 /// private `bindable_intent`) — **plus** a genuine [`Reduction::Reduce`]
 /// grouping to compare (not [`Reduction::PerEntity`], which has no `by` set
 /// at all). `None` for anything else, including a multi-measure or `HAVING`
 /// aggregate, a non-`Aggregate` node, or a `PerEntity` reduction.
 fn bindable_grouped_aggregate(
-    node: &QueryExpr,
-) -> Option<(&GroupKeys, &AggIntent, &Rc<QueryExpr>)> {
-    let QueryExpr::Aggregate {
+    node: &OperatorNode,
+) -> Option<(&GroupKeys, &AggIntent, &Rc<OperatorNode>)> {
+    let Some(NonASAPOp::Aggregate {
         reduction,
         measures,
         filters,
         having,
         child,
         ..
-    } = node
+    }) = node.non_asap()
     else {
         return None;
     };
@@ -263,7 +266,7 @@ fn is_strict_column_superset(finer: &[ColumnId], coarser: &[ColumnId]) -> bool {
 /// docs' "Non-goals" on why finding the full sibling set across a workload
 /// is a workload-wide traversal this strategy does not own.
 pub struct RollupStrategy {
-    siblings: Vec<Rc<QueryExpr>>,
+    siblings: Vec<Rc<OperatorNode>>,
 }
 
 impl RollupStrategy {
@@ -271,7 +274,7 @@ impl RollupStrategy {
     /// each as a candidate roll-up source (or target) — typically the full set of `Aggregate`
     /// nodes a workload-wide discovery pass (issue #252) already found
     /// sharing at least one child `Rc` with something else.
-    pub fn new(siblings: &[Rc<QueryExpr>]) -> Self {
+    pub fn new(siblings: &[Rc<OperatorNode>]) -> Self {
         Self {
             siblings: siblings.to_vec(),
         }
@@ -280,7 +283,7 @@ impl RollupStrategy {
     /// Every sibling that is a legal, strictly finer roll-up source for
     /// `target` — shared between `matches` and `replacements` so the two
     /// can never disagree about which siblings qualify.
-    fn finer_sources(&self, target: &TargetSubDAG<'_>) -> Vec<&Rc<QueryExpr>> {
+    fn finer_sources(&self, target: &TargetSubDAG<'_>) -> Vec<&Rc<OperatorNode>> {
         let Some((coarser_by, coarser_intent, coarser_child)) =
             bindable_grouped_aggregate(target.root)
         else {
@@ -301,12 +304,9 @@ impl RollupStrategy {
                 if !Rc::ptr_eq(finer_child, coarser_child) && finer_child != coarser_child {
                     return false;
                 }
-                let Ok(finer_schema) = candidate.output_schema() else {
-                    return false;
-                };
                 is_legal_rollup_source(
                     finer_by,
-                    &finer_schema,
+                    &candidate.schema,
                     finer_intent,
                     coarser_by,
                     coarser_intent,
@@ -325,7 +325,7 @@ impl ReplacementStrategy for RollupStrategy {
         let Some((coarser_by, coarser_intent, _)) = bindable_grouped_aggregate(target.root) else {
             return Vec::new();
         };
-        let QueryExpr::Aggregate { output_names, .. } = target.root.as_ref() else {
+        let Some(NonASAPOp::Aggregate { output_names, .. }) = target.root.non_asap() else {
             unreachable!("bindable_grouped_aggregate already confirmed Aggregate");
         };
         self.finer_sources(target)
@@ -335,7 +335,7 @@ impl ReplacementStrategy for RollupStrategy {
     }
 }
 
-/// Build the coarser replacement: a new `QueryExpr::Aggregate` grouped by
+/// Build the coarser replacement: a new `NonASAPOp::Aggregate` grouped by
 /// `coarser_by`'s columns (repositioned into `finer`'s own output schema —
 /// see below), computing `rollup_combinator(intent, ..)` over `finer`'s own
 /// measure column, with `child = finer` instead of the original shared
@@ -350,7 +350,7 @@ impl ReplacementStrategy for RollupStrategy {
 /// position in the shared child to its position in `finer`'s output: the
 /// index its `ColumnId` occupies within `finer_by`'s own ordered list.
 fn build_rollup(
-    finer: &Rc<QueryExpr>,
+    finer: &Rc<OperatorNode>,
     coarser_by: &GroupKeys,
     intent: &AggIntent,
     output_names: &[String],
@@ -367,18 +367,20 @@ fn build_rollup(
         .map(|id| finer_by.keys().iter().position(|f| f == id))
         .collect::<Option<Vec<_>>>()?;
 
-    let rewritten = QueryExpr::Aggregate {
-        reduction: Reduction::by(remapped_by),
-        measures: vec![combinator],
-        output_names: output_names.to_vec(),
-        filters: vec![],
-        having: None,
-        child: Rc::clone(finer),
-    };
+    let rewritten =
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+            reduction: Reduction::by(remapped_by),
+            measures: vec![combinator],
+            output_names: output_names.to_vec(),
+            filters: vec![],
+            having: None,
+            child: Rc::clone(finer),
+        }))
+        .ok()?;
 
     Some(ReplacementSubDAG {
         strategy: "RollupStrategy",
-        replacement: Replacement::Rewrite(Rc::new(rewritten)),
+        replacement: Replacement::SubDAG(rewritten),
         provenance: crate::replacement::ReplacementProvenance::LogicalRewrite,
         rationale: format!(
             "rolls up from the finer Aggregate grouped by {:?} (a strict superset of this \
@@ -394,13 +396,13 @@ fn build_rollup(
 #[cfg(test)]
 mod tests {
     use super::*;
-    use asap_types::pre_asap::query_expr::Source;
+    use asap_types::ir::operator_properties::Source;
     use asap_types::pre_asap::schema::{DataType, Field};
     use asap_types::types::AccuracyTarget;
 
     /// `[ts(0), value(1), job(2), region(3)]`.
-    fn metric_scan() -> QueryExpr {
-        QueryExpr::Scan {
+    fn metric_scan() -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: Source::TimeSeries { metric: "m".into() },
             predicates: vec![],
             schema: Schema::with_time_index(
@@ -413,33 +415,36 @@ mod tests {
                 0,
                 vec![],
             ),
-        }
+        }))
+        .unwrap()
     }
 
-    fn agg(by: Vec<ColumnId>, intent: AggIntent, child: &Rc<QueryExpr>) -> Rc<QueryExpr> {
-        Rc::new(QueryExpr::Aggregate {
+    fn agg(by: Vec<ColumnId>, intent: AggIntent, child: &Rc<OperatorNode>) -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
             reduction: Reduction::by(by),
             measures: vec![intent],
             output_names: vec![],
             filters: vec![],
             having: None,
             child: Rc::clone(child),
-        })
+        }))
+        .unwrap()
     }
 
     fn without_agg(
         excluded: Vec<ColumnId>,
         intent: AggIntent,
-        child: &Rc<QueryExpr>,
-    ) -> Rc<QueryExpr> {
-        Rc::new(QueryExpr::Aggregate {
+        child: &Rc<OperatorNode>,
+    ) -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
             reduction: Reduction::Reduce(GroupKeys::without(excluded)),
             measures: vec![intent],
             output_names: vec![],
             filters: vec![],
             having: None,
             child: Rc::clone(child),
-        })
+        }))
+        .unwrap()
     }
 
     // ── is_legal_rollup_source (the standalone predicate) ───────────────
@@ -569,7 +574,7 @@ mod tests {
 
     #[test]
     fn superset_by_over_identical_mergeable_intent_and_shared_child_rolls_up() {
-        let scan = Rc::new(metric_scan());
+        let scan = metric_scan();
         let fine = agg(vec![2, 3], AggIntent::Sum { col: Some(1) }, &scan);
         let coarse = agg(vec![2], AggIntent::Sum { col: Some(1) }, &scan);
 
@@ -581,16 +586,16 @@ mod tests {
         let replacements = strategy.replacements(&target);
         assert_eq!(replacements.len(), 1, "{replacements:?}");
 
-        let Replacement::Rewrite(rewritten) = &replacements[0].replacement else {
+        let Replacement::SubDAG(rewritten) = &replacements[0].replacement else {
             panic!("expected a Rewrite replacement");
         };
-        let QueryExpr::Aggregate {
+        let Some(NonASAPOp::Aggregate {
             reduction,
             measures,
             child,
             having,
             ..
-        } = rewritten.as_ref()
+        }) = rewritten.non_asap()
         else {
             panic!("expected an Aggregate rewrite, got {rewritten:?}");
         };
@@ -620,7 +625,7 @@ mod tests {
         // Count is not self-combining (see the module docs) — the rewritten
         // measure must be Sum over the finer Count's own output column, not
         // Count reapplied.
-        let scan = Rc::new(metric_scan());
+        let scan = metric_scan();
         let fine = agg(
             vec![2, 3],
             AggIntent::Count {
@@ -642,10 +647,10 @@ mod tests {
 
         let replacements = strategy.replacements(&target);
         assert_eq!(replacements.len(), 1, "{replacements:?}");
-        let Replacement::Rewrite(rewritten) = &replacements[0].replacement else {
+        let Replacement::SubDAG(rewritten) = &replacements[0].replacement else {
             panic!("expected a Rewrite replacement");
         };
-        let QueryExpr::Aggregate { measures, .. } = rewritten.as_ref() else {
+        let Some(NonASAPOp::Aggregate { measures, .. }) = rewritten.non_asap() else {
             panic!("expected an Aggregate rewrite");
         };
         assert_eq!(
@@ -657,7 +662,7 @@ mod tests {
 
     #[test]
     fn approximate_count_does_not_roll_up_via_sum() {
-        let scan = Rc::new(metric_scan());
+        let scan = metric_scan();
         let intent = AggIntent::Count {
             accuracy: AccuracyTarget::Epsilon(0.01),
         };
@@ -673,8 +678,8 @@ mod tests {
 
     #[test]
     fn default_workload_search_adds_rollup_for_two_query_workload() {
-        let fine_scan = Rc::new(metric_scan());
-        let coarse_scan = Rc::new(metric_scan());
+        let fine_scan = metric_scan();
+        let coarse_scan = metric_scan();
         let fine = agg(vec![2, 3], AggIntent::Sum { col: Some(1) }, &fine_scan);
         let coarse = agg(vec![2], AggIntent::Sum { col: Some(1) }, &coarse_scan);
 
@@ -682,12 +687,11 @@ mod tests {
         let coarse_group = space
             .target_subdag_candidates()
             .find(|group| {
-                matches!(
-                    group.target.as_ref(),
-                    QueryExpr::Aggregate {
+                matches!(group.target.non_asap(),
+                    Some(NonASAPOp::Aggregate {
                         reduction: Reduction::Reduce(by),
                         ..
-                    } if by.keys() == [2]
+                    }) if by.keys() == [2]
                 )
             })
             .expect("coarser aggregate group");
@@ -696,19 +700,19 @@ mod tests {
             .candidates
             .iter()
             .find_map(|candidate| match &candidate.replacement {
-                Replacement::Rewrite(rewrite) => Some(rewrite),
-                Replacement::Summary(_) | Replacement::ExactComposition(_) => None,
+                // Old `Replacement::Rewrite`: a pure pre-ASAP sub-DAG.
+                Replacement::SubDAG(rewrite) if !rewrite.contains_asap() => Some(rewrite),
+                Replacement::SubDAG(_) | Replacement::ExactComposition(_) => None,
             })
             .expect("default search must include the roll-up rewrite");
-        let QueryExpr::Aggregate { child, .. } = rewrite.as_ref() else {
+        let Some(NonASAPOp::Aggregate { child, .. }) = rewrite.non_asap() else {
             panic!("expected aggregate rewrite, got {rewrite:?}");
         };
-        assert!(matches!(
-            child.as_ref(),
-            QueryExpr::Aggregate {
+        assert!(matches!(child.non_asap(),
+            Some(NonASAPOp::Aggregate {
                 reduction: Reduction::Reduce(by),
                 ..
-            } if by.keys() == [2, 3]
+            }) if by.keys() == [2, 3]
         ));
     }
 
@@ -717,18 +721,17 @@ mod tests {
         let intent = AggIntent::Count {
             accuracy: AccuracyTarget::Epsilon(0.01),
         };
-        let fine = agg(vec![2, 3], intent.clone(), &Rc::new(metric_scan()));
-        let coarse = agg(vec![2], intent, &Rc::new(metric_scan()));
+        let fine = agg(vec![2, 3], intent.clone(), &metric_scan());
+        let coarse = agg(vec![2], intent, &metric_scan());
         let space = crate::replacement::search_workload(vec![("fine", fine), ("coarse", coarse)]);
         let coarse_group = space
             .target_subdag_candidates()
             .find(|group| {
-                matches!(
-                    group.target.as_ref(),
-                    QueryExpr::Aggregate {
+                matches!(group.target.non_asap(),
+                    Some(NonASAPOp::Aggregate {
                         reduction: Reduction::Reduce(by),
                         ..
-                    } if by.keys() == [2]
+                    }) if by.keys() == [2]
                 )
             })
             .expect("coarser aggregate group");
@@ -736,32 +739,35 @@ mod tests {
         assert!(coarse_group
             .candidates
             .iter()
-            .all(|candidate| !matches!(candidate.replacement, Replacement::Rewrite(_))));
+            .all(|candidate| !matches!(&candidate.replacement,
+                Replacement::SubDAG(rewrite) if !rewrite.contains_asap())));
     }
 
     #[test]
     fn rollup_preserves_the_coarser_output_name() {
-        let scan = Rc::new(metric_scan());
+        let scan = metric_scan();
         let fine = agg(vec![2, 3], AggIntent::Sum { col: Some(1) }, &scan);
-        let coarse = Rc::new(QueryExpr::Aggregate {
-            reduction: Reduction::by(vec![2]),
-            measures: vec![AggIntent::Sum { col: Some(1) }],
-            output_names: vec!["total_requests".into()],
-            filters: vec![],
-            having: None,
-            child: Rc::clone(&scan),
-        });
-        let original_schema = coarse.output_schema().unwrap();
+        let coarse =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+                reduction: Reduction::by(vec![2]),
+                measures: vec![AggIntent::Sum { col: Some(1) }],
+                output_names: vec!["total_requests".into()],
+                filters: vec![],
+                having: None,
+                child: Rc::clone(&scan),
+            }))
+            .unwrap();
+        let original_schema = coarse.schema.clone();
 
         let siblings = vec![Rc::clone(&fine), Rc::clone(&coarse)];
         let strategy = RollupStrategy::new(&siblings);
         let replacements = strategy.replacements(&TargetSubDAG::new(&coarse));
-        let Replacement::Rewrite(rewritten) = &replacements[0].replacement else {
+        let Replacement::SubDAG(rewritten) = &replacements[0].replacement else {
             panic!("expected a Rewrite replacement");
         };
 
-        assert_eq!(rewritten.output_schema().unwrap(), original_schema);
-        let QueryExpr::Aggregate { output_names, .. } = rewritten.as_ref() else {
+        assert_eq!(rewritten.schema.clone(), original_schema);
+        let Some(NonASAPOp::Aggregate { output_names, .. }) = rewritten.non_asap() else {
             unreachable!();
         };
         assert_eq!(output_names, &vec!["total_requests".to_string()]);
@@ -769,7 +775,7 @@ mod tests {
 
     #[test]
     fn non_mergeable_intent_does_not_roll_up() {
-        let scan = Rc::new(metric_scan());
+        let scan = metric_scan();
         let fine = agg(vec![2, 3], AggIntent::Avg { col: Some(1) }, &scan);
         let coarse = agg(vec![2], AggIntent::Avg { col: Some(1) }, &scan);
 
@@ -789,12 +795,12 @@ mod tests {
         // numerically a superset of the coarser side's *kept* positions —
         // `is_legal_rollup_source` rejects any `without` grouping outright,
         // and would reject on the missing unique key regardless.
-        let scan = Rc::new(metric_scan());
+        let scan = metric_scan();
         let fine = without_agg(vec![2, 3], AggIntent::Sum { col: Some(1) }, &scan);
         let coarse = agg(vec![2], AggIntent::Sum { col: Some(1) }, &scan);
 
         assert!(
-            !fine.output_schema().unwrap().has_unique_key(),
+            !fine.schema.clone().has_unique_key(),
             "fixture sanity: a without(...) aggregate has no provable unique key"
         );
 
@@ -809,7 +815,7 @@ mod tests {
     #[test]
     fn unrelated_by_sets_do_not_roll_up() {
         // Neither `[job]` nor `[region]` is a superset of the other.
-        let scan = Rc::new(metric_scan());
+        let scan = metric_scan();
         let a = agg(vec![2], AggIntent::Sum { col: Some(1) }, &scan);
         let b = agg(vec![3], AggIntent::Sum { col: Some(1) }, &scan);
 
@@ -830,7 +836,7 @@ mod tests {
         // Equal groupings are `SharedSubDAGStrategy`'s CSE-sharing
         // question (build once and share, or build independently) — a
         // roll-up requires a *strict* superset, not equality.
-        let scan = Rc::new(metric_scan());
+        let scan = metric_scan();
         let a = agg(vec![2], AggIntent::Sum { col: Some(1) }, &scan);
         let b = agg(vec![2], AggIntent::Sum { col: Some(1) }, &scan);
 
@@ -845,16 +851,8 @@ mod tests {
         // Scans without unique keys are deliberately not pointer-aliased by
         // CSE. Structural equality still proves identical schemas and makes
         // the two aggregates' positional ColumnIds comparable.
-        let fine = agg(
-            vec![2, 3],
-            AggIntent::Sum { col: Some(1) },
-            &Rc::new(metric_scan()),
-        );
-        let coarse = agg(
-            vec![2],
-            AggIntent::Sum { col: Some(1) },
-            &Rc::new(metric_scan()),
-        );
+        let fine = agg(vec![2, 3], AggIntent::Sum { col: Some(1) }, &metric_scan());
+        let coarse = agg(vec![2], AggIntent::Sum { col: Some(1) }, &metric_scan());
 
         let siblings = vec![Rc::clone(&fine), Rc::clone(&coarse)];
         let strategy = RollupStrategy::new(&siblings);
@@ -865,21 +863,23 @@ mod tests {
 
     #[test]
     fn does_not_match_a_multi_measure_or_having_aggregate() {
-        let scan = Rc::new(metric_scan());
+        let scan = metric_scan();
         let fine = agg(vec![2, 3], AggIntent::Sum { col: Some(1) }, &scan);
-        let multi = Rc::new(QueryExpr::Aggregate {
-            reduction: Reduction::by(vec![2]),
-            measures: vec![
-                AggIntent::Sum { col: Some(1) },
-                AggIntent::Count {
-                    accuracy: AccuracyTarget::Exact,
-                },
-            ],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::clone(&scan),
-        });
+        let multi =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+                reduction: Reduction::by(vec![2]),
+                measures: vec![
+                    AggIntent::Sum { col: Some(1) },
+                    AggIntent::Count {
+                        accuracy: AccuracyTarget::Exact,
+                    },
+                ],
+                output_names: vec![],
+                filters: vec![],
+                having: None,
+                child: Rc::clone(&scan),
+            }))
+            .unwrap();
 
         let siblings = vec![Rc::clone(&fine), Rc::clone(&multi)];
         let strategy = RollupStrategy::new(&siblings);
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_cost/estimator.rs b/crates/asap-aware-mapping/src/summary_maintenance_cost/estimator.rs
index eac94a2cb..911d90275 100644
--- a/crates/asap-aware-mapping/src/summary_maintenance_cost/estimator.rs
+++ b/crates/asap-aware-mapping/src/summary_maintenance_cost/estimator.rs
@@ -1,7 +1,7 @@
 use super::*;
 
 pub(super) fn estimate_heterogeneous_summary(
-    root: &SummaryNode,
+    root: &OperatorNode,
     deployments: &[CostedSummaryDeployment<'_>],
     evidence: &SummaryNodeEvidence,
     scope: &ComparisonScope,
@@ -19,46 +19,6 @@ pub(super) fn estimate_heterogeneous_summary(
         .map(|(deployment, framework)| (deployment.summary as *const _, framework))
         .collect();
     validate_summary_edges_and_physical_ids(root, evidence, &frameworks_by_node)?;
-    fn summary_source_selections(
-        node: &SummaryNode,
-        seen: &mut HashSet<*const SummaryNode>,
-        out: &mut Vec<LogicalSourceSelection>,
-    ) -> Result<(), AnalyticalCostError> {
-        if !seen.insert(node as *const _) {
-            return Ok(());
-        }
-        match &node.expr {
-            SummaryExpr::KeepPreAsap(query) => query_source_selections(query, out)?,
-            SummaryExpr::SummaryAgg { child, .. } | SummaryExpr::ValueOperation { child, .. } => {
-                summary_source_selections(child, seen, out)?
-            }
-            SummaryExpr::SummaryMerge { children, .. } => {
-                for child in children {
-                    summary_source_selections(child, seen, out)?;
-                }
-            }
-            SummaryExpr::SummarySubtract { left, right }
-            | SummaryExpr::RelationalJoin { left, right, .. }
-            | SummaryExpr::BinaryOp {
-                lhs: left,
-                rhs: right,
-                ..
-            }
-            | SummaryExpr::SummaryJoin {
-                outer: left,
-                inner: right,
-                ..
-            } => {
-                summary_source_selections(left, seen, out)?;
-                summary_source_selections(right, seen, out)?;
-            }
-            SummaryExpr::SummaryDelete { summary_input, .. }
-            | SummaryExpr::SummaryEstimate { summary_input, .. } => {
-                summary_source_selections(summary_input, seen, out)?
-            }
-        }
-        Ok(())
-    }
     let evaluation_count = scope.validate()?;
     let by_node: HashMap<_, _> = deployments
         .iter()
@@ -81,7 +41,7 @@ pub(super) fn estimate_heterogeneous_summary(
         let node_evidence = evidence
             .aggregation(deployment.summary)
             .ok_or(AnalyticalCostError::MissingOrStale("summary_agg"))?;
-        let SummaryExpr::SummaryAgg { child, .. } = &deployment.summary.expr else {
+        let Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) = &deployment.summary.operator else {
             return Err(AnalyticalCostError::UnsupportedCandidate);
         };
         let inputs = node_evidence.inputs.validate()?;
@@ -95,7 +55,7 @@ pub(super) fn estimate_heterogeneous_summary(
                         .ok_or(AnalyticalCostError::MissingComparisonScope(
                             "summary scan selection",
                         ))?;
-                if !matches!(&child.expr, SummaryExpr::KeepPreAsap(_))
+                if !has_retained_subdag_evidence(child, evidence)
                     || inputs.initial_input_rows != raw.planning_time_input_rows
                     || inputs.initial_input_bytes != raw.planning_time_input_bytes
                     || inputs.initial_source_scan_bytes != raw.planning_time_source_scan_bytes
@@ -106,7 +66,7 @@ pub(super) fn estimate_heterogeneous_summary(
                     ));
                 }
                 let mut actual_selections = Vec::new();
-                summary_source_selections(child, &mut HashSet::new(), &mut actual_selections)?;
+                query_source_selections(child, &mut HashSet::new(), &mut actual_selections)?;
                 let actual_selections = deduplicate_source_selections(actual_selections);
                 let expected = (
                     declared.source.clone(),
@@ -120,7 +80,7 @@ pub(super) fn estimate_heterogeneous_summary(
                 }
             }
             None => {
-                if matches!(&child.expr, SummaryExpr::KeepPreAsap(_))
+                if has_retained_subdag_evidence(child, evidence)
                     || inputs.initial_source_scan_bytes != 0
                     || !node_evidence.bootstrap_read_identity.is_empty()
                 {
@@ -131,7 +91,7 @@ pub(super) fn estimate_heterogeneous_summary(
             }
         }
         validate_guarantee(deployment.guarantee, scope.data_arrival)?;
-        let logical_state = format!("{:?}", deployment.summary.expr);
+        let logical_state = format!("{:?}", deployment.summary.operator);
         let window_framework = (*frameworks_by_node
             .get(&(deployment.summary as *const _))
             .ok_or(AnalyticalCostError::MissingOrStale(
@@ -253,9 +213,9 @@ pub(super) fn estimate_heterogeneous_summary(
 
     #[expect(clippy::too_many_arguments, reason = "CPU and I/O traversal state")]
     fn visit_ops(
-        node: &SummaryNode,
+        node: &OperatorNode,
         seen: &mut HashSet<String>,
-        by_node: &HashMap<*const SummaryNode, &CostedSummaryDeployment<'_>>,
+        by_node: &HashMap<*const OperatorNode, &CostedSummaryDeployment<'_>>,
         evidence: &SummaryNodeEvidence,
         scope: &ComparisonScope,
         evaluation_count: u64,
@@ -266,13 +226,29 @@ pub(super) fn estimate_heterogeneous_summary(
         if !seen.insert(physical_id) {
             return Ok(());
         }
-        match &node.expr {
-            SummaryExpr::BinaryOp { lhs, rhs, .. }
-            | SummaryExpr::RelationalJoin {
+        if has_retained_subdag_evidence(node, evidence) {
+            let retained = evidence
+                .retained_queries
+                .get(&(node as *const _))
+                .ok_or(AnalyticalCostError::MissingOrStale("retain_exact"))?;
+            if !retained.preprocessing_cpu_ops_over_horizon.is_finite()
+                || retained.preprocessing_cpu_ops_over_horizon < 0.0
+            {
+                return Err(AnalyticalCostError::InvalidOperationCost(
+                    "retain_exact",
+                    retained.preprocessing_cpu_ops_over_horizon,
+                ));
+            }
+            *cpu_ops += retained.preprocessing_cpu_ops_over_horizon;
+            return Ok(());
+        }
+        match &node.operator {
+            Operator::NonASAP(NonASAPOp::BinaryOp { lhs, rhs, .. })
+            | Operator::NonASAP(NonASAPOp::Join {
                 left: lhs,
                 right: rhs,
                 ..
-            } => {
+            }) => {
                 let operation = summary_operation_evidence(node, evidence)?.resource();
                 *cpu_ops += evaluation_count as f64
                     * validated_operator_executions("exact_binary", operation)? as f64
@@ -300,39 +276,31 @@ pub(super) fn estimate_heterogeneous_summary(
                 )?;
             }
 
-            SummaryExpr::ValueOperation { child, .. } => {
+            Operator::NonASAP(_)
+            | Operator::ASAP(
+                ASAPOp::FinalizeExactAccumulator { .. }
+                | ASAPOp::MaintainPopulation { .. }
+                | ASAPOp::EvaluatePopulation { .. },
+            ) => {
                 let operation = summary_operation_evidence(node, evidence)?.resource();
                 *cpu_ops += evaluation_count as f64
                     * validated_operator_executions("value_operation", operation)? as f64
                     * validated_operator_cpu("value_operation", operation.cpu_ops)?;
                 add_operator_io(io_bytes, operation, evaluation_count)?;
-                visit_ops(
-                    child,
-                    seen,
-                    by_node,
-                    evidence,
-                    scope,
-                    evaluation_count,
-                    cpu_ops,
-                    io_bytes,
-                )?;
-            }
-            SummaryExpr::KeepPreAsap(_) => {
-                let retained = evidence
-                    .retained_queries
-                    .get(&(node as *const _))
-                    .ok_or(AnalyticalCostError::MissingOrStale("keep_pre_asap"))?;
-                if !retained.preprocessing_cpu_ops_over_horizon.is_finite()
-                    || retained.preprocessing_cpu_ops_over_horizon < 0.0
-                {
-                    return Err(AnalyticalCostError::InvalidOperationCost(
-                        "keep_pre_asap",
-                        retained.preprocessing_cpu_ops_over_horizon,
-                    ));
+                for child in node.children() {
+                    visit_ops(
+                        child,
+                        seen,
+                        by_node,
+                        evidence,
+                        scope,
+                        evaluation_count,
+                        cpu_ops,
+                        io_bytes,
+                    )?;
                 }
-                *cpu_ops += retained.preprocessing_cpu_ops_over_horizon;
             }
-            SummaryExpr::SummaryAgg { child, .. } => {
+            Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) => {
                 visit_ops(
                     child,
                     seen,
@@ -344,7 +312,7 @@ pub(super) fn estimate_heterogeneous_summary(
                     io_bytes,
                 )?;
             }
-            SummaryExpr::SummaryMerge { children, .. } => {
+            Operator::ASAP(ASAPOp::SummaryMerge { children }) => {
                 let operation = summary_operation_evidence(node, evidence)?.resource();
                 let merge = validated_operator_cpu("summary_merge", operation.cpu_ops)?;
                 *cpu_ops += evaluation_count as f64
@@ -364,7 +332,7 @@ pub(super) fn estimate_heterogeneous_summary(
                     )?;
                 }
             }
-            SummaryExpr::SummarySubtract { left, right } => {
+            Operator::ASAP(ASAPOp::SummarySubtract { left, right }) => {
                 let operation = summary_operation_evidence(node, evidence)?.resource();
                 *cpu_ops += evaluation_count as f64
                     * validated_operator_executions("summary_subtract", operation)? as f64
@@ -391,7 +359,7 @@ pub(super) fn estimate_heterogeneous_summary(
                     io_bytes,
                 )?;
             }
-            SummaryExpr::SummaryDelete { summary_input, .. } => {
+            Operator::ASAP(ASAPOp::SummaryDelete { summary_input, .. }) => {
                 let delete = summary_operation_evidence(node, evidence)?;
                 let SummaryOperatorEvidence::Delete {
                     resource: operation,
@@ -406,44 +374,18 @@ pub(super) fn estimate_heterogeneous_summary(
                     .get(&(node as *const _))
                     .ok_or(AnalyticalCostError::MissingOrStale("summary_delete_owner"))?;
                 fn collect_aggs(
-                    node: &SummaryNode,
-                    seen: &mut HashSet<*const SummaryNode>,
-                    out: &mut Vec<*const SummaryNode>,
+                    node: &OperatorNode,
+                    seen: &mut HashSet<*const OperatorNode>,
+                    out: &mut Vec<*const OperatorNode>,
                 ) {
                     if !seen.insert(node as *const _) {
                         return;
                     }
-                    match &node.expr {
-                        SummaryExpr::SummaryAgg { child, .. } => {
-                            out.push(node as *const _);
-                            collect_aggs(child, seen, out);
-                        }
-                        SummaryExpr::ValueOperation { child, .. } => collect_aggs(child, seen, out),
-                        SummaryExpr::SummaryMerge { children, .. } => {
-                            children
-                                .iter()
-                                .for_each(|child| collect_aggs(child, seen, out));
-                        }
-                        SummaryExpr::SummarySubtract { left, right }
-                        | SummaryExpr::RelationalJoin { left, right, .. }
-                        | SummaryExpr::BinaryOp {
-                            lhs: left,
-                            rhs: right,
-                            ..
-                        }
-                        | SummaryExpr::SummaryJoin {
-                            outer: left,
-                            inner: right,
-                            ..
-                        } => {
-                            collect_aggs(left, seen, out);
-                            collect_aggs(right, seen, out);
-                        }
-                        SummaryExpr::SummaryDelete { summary_input, .. }
-                        | SummaryExpr::SummaryEstimate { summary_input, .. } => {
-                            collect_aggs(summary_input, seen, out)
-                        }
-                        SummaryExpr::KeepPreAsap(_) => {}
+                    if matches!(node.operator, Operator::ASAP(ASAPOp::SummaryAgg { .. })) {
+                        out.push(node as *const _);
+                    }
+                    for child in node.children() {
+                        collect_aggs(child, seen, out);
                     }
                 }
                 let mut reachable = Vec::new();
@@ -491,11 +433,11 @@ pub(super) fn estimate_heterogeneous_summary(
                     io_bytes,
                 )?;
             }
-            SummaryExpr::SummaryEstimate { summary_input, .. } => {
+            Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) => {
                 let operation = summary_operation_evidence(node, evidence)?.resource();
                 *cpu_ops += evaluation_count as f64
-                    * validated_operator_executions("summary_readout", operation)? as f64
-                    * validated_operator_cpu("summary_readout", operation.cpu_ops)?;
+                    * validated_operator_executions("summary_evaluation", operation)? as f64
+                    * validated_operator_cpu("summary_evaluation", operation.cpu_ops)?;
                 add_operator_io(io_bytes, operation, evaluation_count)?;
                 visit_ops(
                     summary_input,
@@ -508,7 +450,7 @@ pub(super) fn estimate_heterogeneous_summary(
                     io_bytes,
                 )?;
             }
-            SummaryExpr::SummaryJoin { outer, inner, .. } => {
+            Operator::ASAP(ASAPOp::SummaryJoin { outer, inner, .. }) => {
                 let join = evidence
                     .joins
                     .get(&(node as *const _))
@@ -555,6 +497,9 @@ pub(super) fn estimate_heterogeneous_summary(
                     io_bytes,
                 )?;
             }
+            Operator::ASAP(ASAPOp::Extension { .. }) => {
+                return Err(AnalyticalCostError::UnsupportedCandidate);
+            }
         }
         Ok(())
     }
@@ -613,55 +558,37 @@ fn add_operator_io(
 }
 
 fn validate_summary_edges_and_physical_ids(
-    root: &SummaryNode,
+    root: &OperatorNode,
     evidence: &SummaryNodeEvidence,
-    frameworks_by_node: &HashMap<*const SummaryNode, &Option<SummaryWindowFramework>>,
+    frameworks_by_node: &HashMap<*const OperatorNode, &Option<SummaryWindowFramework>>,
 ) -> Result<(), AnalyticalCostError> {
-    fn children(node: &SummaryNode) -> Vec<&SummaryNode> {
-        match &node.expr {
-            SummaryExpr::KeepPreAsap(_) => vec![],
-            SummaryExpr::SummaryAgg { child, .. } | SummaryExpr::ValueOperation { child, .. } => {
-                vec![child]
-            }
-            SummaryExpr::SummaryMerge { children, .. } => {
-                children.iter().map(|child| child.as_ref()).collect()
-            }
-            SummaryExpr::SummarySubtract { left, right }
-            | SummaryExpr::RelationalJoin { left, right, .. }
-            | SummaryExpr::BinaryOp {
-                lhs: left,
-                rhs: right,
-                ..
-            }
-            | SummaryExpr::SummaryJoin {
-                outer: left,
-                inner: right,
-                ..
-            } => vec![left, right],
-            SummaryExpr::SummaryDelete { summary_input, .. }
-            | SummaryExpr::SummaryEstimate { summary_input, .. } => vec![summary_input],
-        }
+    fn children<'a>(
+        node: &'a OperatorNode,
+        evidence: &SummaryNodeEvidence,
+    ) -> Vec<&'a OperatorNode> {
+        summary_children(node, evidence)
     }
     fn metadata(
-        node: &SummaryNode,
+        node: &OperatorNode,
         evidence: &SummaryNodeEvidence,
     ) -> Result<(String, Vec<EdgeStatistics>, EdgeStatistics), AnalyticalCostError> {
-        match &node.expr {
-            SummaryExpr::KeepPreAsap(_) => {
-                let retained = evidence
-                    .retained_queries
-                    .get(&(node as *const _))
-                    .ok_or(AnalyticalCostError::MissingOrStale("keep_pre_asap"))?;
-                Ok((retained.physical_id.clone(), vec![], retained.output))
+        if let Some(retained) = evidence.retained_queries.get(&(node as *const _)) {
+            if node.contains_asap() {
+                return Err(AnalyticalCostError::InvalidPhysicalDAG(
+                    "retained sub-DAG evidence covers summary operators",
+                ));
             }
-            SummaryExpr::SummaryAgg { .. } => {
+            return Ok((retained.physical_id.clone(), vec![], retained.output));
+        }
+        match &node.operator {
+            Operator::ASAP(ASAPOp::SummaryAgg { .. }) => {
                 let value = evidence
                     .aggregations
                     .get(&(node as *const _))
                     .ok_or(AnalyticalCostError::MissingOrStale("summary_agg"))?;
                 Ok((value.physical_id.clone(), vec![value.input], value.output))
             }
-            SummaryExpr::SummaryJoin { .. } => {
+            Operator::ASAP(ASAPOp::SummaryJoin { .. }) => {
                 let value = evidence
                     .joins
                     .get(&(node as *const _))
@@ -683,16 +610,16 @@ fn validate_summary_edges_and_physical_ids(
         }
     }
     fn visit(
-        node: &SummaryNode,
+        node: &OperatorNode,
         evidence: &SummaryNodeEvidence,
-        frameworks_by_node: &HashMap<*const SummaryNode, &Option<SummaryWindowFramework>>,
-        seen: &mut HashSet<*const SummaryNode>,
+        frameworks_by_node: &HashMap<*const OperatorNode, &Option<SummaryWindowFramework>>,
+        seen: &mut HashSet<*const OperatorNode>,
         physical: &mut HashMap<String, (Vec<EdgeStatistics>, EdgeStatistics, String)>,
     ) -> Result<EdgeStatistics, AnalyticalCostError> {
         if !seen.insert(node as *const _) {
             return metadata(node, evidence).map(|(_, _, output)| output);
         }
-        let child_nodes = children(node);
+        let child_nodes = children(node, evidence);
         let child_outputs = child_nodes
             .iter()
             .map(|child| visit(child, evidence, frameworks_by_node, seen, physical))
@@ -702,17 +629,18 @@ fn validate_summary_edges_and_physical_ids(
             .map(|child| summary_physical_id(child, evidence))
             .collect::<Result<Vec<_>, _>>()?;
         let (id, inputs, output) = metadata(node, evidence)?;
-        let local_fingerprint = match &node.expr {
-            SummaryExpr::KeepPreAsap(_) => {
-                format!("{:?}", evidence.retained_queries.get(&(node as *const _)))
-            }
-            SummaryExpr::SummaryAgg { .. } => {
-                format!("{:?}", evidence.aggregations.get(&(node as *const _)))
-            }
-            SummaryExpr::SummaryJoin { .. } => {
-                format!("{:?}", evidence.joins.get(&(node as *const _)))
+        let local_fingerprint = if has_retained_subdag_evidence(node, evidence) {
+            format!("{:?}", evidence.retained_queries.get(&(node as *const _)))
+        } else {
+            match &node.operator {
+                Operator::ASAP(ASAPOp::SummaryAgg { .. }) => {
+                    format!("{:?}", evidence.aggregations.get(&(node as *const _)))
+                }
+                Operator::ASAP(ASAPOp::SummaryJoin { .. }) => {
+                    format!("{:?}", evidence.joins.get(&(node as *const _)))
+                }
+                _ => format!("{:?}", evidence.operations.get(&(node as *const _))),
             }
-            _ => format!("{:?}", evidence.operations.get(&(node as *const _))),
         };
         // A provider identity names the complete physical operator, including
         // its inputs. Equal local widths/costs do not make operators consuming
@@ -720,7 +648,7 @@ fn validate_summary_edges_and_physical_ids(
         let framework = frameworks_by_node.get(&(node as *const _));
         let fingerprint = format!(
             "logical={:?}|framework={framework:?}|{local_fingerprint}|children={child_physical_ids:?}",
-            node.expr
+            node.operator
         );
         if id.is_empty()
             || inputs != child_outputs
@@ -756,20 +684,49 @@ fn validate_summary_edges_and_physical_ids(
     .map(|_| ())
 }
 
+/// Whether `node` is a retained non-ASAP sub-DAG costed as one unit: the
+/// provider bound retained-query evidence to it instead of per-operator
+/// evidence. Its children are then not visited. No ASAP descendant may be
+/// hidden by this boundary; dag validation rejects such evidence.
+fn has_retained_subdag_evidence(node: &OperatorNode, evidence: &SummaryNodeEvidence) -> bool {
+    evidence.retained_queries.contains_key(&(node as *const _)) && !node.contains_asap()
+}
+
+/// The inputs the estimator visits below `node`: none for a retained
+/// sub-DAG, every direct input otherwise.
+fn summary_children<'a>(
+    node: &'a OperatorNode,
+    evidence: &SummaryNodeEvidence,
+) -> Vec<&'a OperatorNode> {
+    if has_retained_subdag_evidence(node, evidence) {
+        vec![]
+    } else {
+        node.children()
+            .into_iter()
+            .map(|child| child.as_ref())
+            .collect()
+    }
+}
+
 fn summary_physical_id(
-    node: &SummaryNode,
+    node: &OperatorNode,
     evidence: &SummaryNodeEvidence,
 ) -> Result<String, AnalyticalCostError> {
-    match &node.expr {
-        SummaryExpr::KeepPreAsap(_) => evidence
+    if has_retained_subdag_evidence(node, evidence) {
+        return evidence
             .retained_queries
             .get(&(node as *const _))
-            .map(|value| value.physical_id.clone()),
-        SummaryExpr::SummaryAgg { .. } => evidence
+            .map(|value| value.physical_id.clone())
+            .ok_or(AnalyticalCostError::MissingOrStale(
+                "summary physical identity",
+            ));
+    }
+    match &node.operator {
+        Operator::ASAP(ASAPOp::SummaryAgg { .. }) => evidence
             .aggregations
             .get(&(node as *const _))
             .map(|value| value.physical_id.clone()),
-        SummaryExpr::SummaryJoin { .. } => evidence
+        Operator::ASAP(ASAPOp::SummaryJoin { .. }) => evidence
             .joins
             .get(&(node as *const _))
             .map(|value| value.physical_id.clone()),
@@ -786,45 +743,26 @@ fn summary_physical_id(
 /// child output buffers remain live until their final consumer executes;
 /// operator workspace and its output buffer coexist during that execution.
 pub(super) fn estimate_transient_liveness(
-    root: &SummaryNode,
+    root: &OperatorNode,
     evidence: &SummaryNodeEvidence,
 ) -> Result<u64, AnalyticalCostError> {
-    fn children(node: &SummaryNode) -> Vec<&SummaryNode> {
-        match &node.expr {
-            SummaryExpr::KeepPreAsap(_) => vec![],
-            SummaryExpr::SummaryAgg { child, .. } | SummaryExpr::ValueOperation { child, .. } => {
-                vec![child]
-            }
-            SummaryExpr::SummaryMerge { children, .. } => {
-                children.iter().map(|child| child.as_ref()).collect()
-            }
-            SummaryExpr::SummarySubtract { left, right }
-            | SummaryExpr::RelationalJoin { left, right, .. }
-            | SummaryExpr::BinaryOp {
-                lhs: left,
-                rhs: right,
-                ..
-            }
-            | SummaryExpr::SummaryJoin {
-                outer: left,
-                inner: right,
-                ..
-            } => vec![left, right],
-            SummaryExpr::SummaryDelete { summary_input, .. }
-            | SummaryExpr::SummaryEstimate { summary_input, .. } => vec![summary_input],
-        }
+    fn children<'a>(
+        node: &'a OperatorNode,
+        evidence: &SummaryNodeEvidence,
+    ) -> Vec<&'a OperatorNode> {
+        summary_children(node, evidence)
     }
     fn visit<'a>(
-        node: &'a SummaryNode,
+        node: &'a OperatorNode,
         evidence: &SummaryNodeEvidence,
         seen: &mut HashSet<String>,
         uses: &mut HashMap<String, usize>,
-        order: &mut Vec<&'a SummaryNode>,
+        order: &mut Vec<&'a OperatorNode>,
     ) -> Result<(), AnalyticalCostError> {
         if !seen.insert(summary_physical_id(node, evidence)?) {
             return Ok(());
         }
-        for child in children(node) {
+        for child in children(node, evidence) {
             *uses
                 .entry(summary_physical_id(child, evidence)?)
                 .or_default() += 1;
@@ -834,28 +772,24 @@ pub(super) fn estimate_transient_liveness(
         Ok(())
     }
     fn memory(
-        node: &SummaryNode,
+        node: &OperatorNode,
         evidence: &SummaryNodeEvidence,
     ) -> Result<(u64, u64), AnalyticalCostError> {
-        match &node.expr {
-            SummaryExpr::KeepPreAsap(_) => evidence
+        if has_retained_subdag_evidence(node, evidence) {
+            return evidence
                 .retained_queries
                 .get(&(node as *const _))
                 .map(|value| (value.working_memory_bytes, value.output_buffer_bytes))
-                .ok_or(AnalyticalCostError::MissingOrStale("keep_pre_asap")),
-            SummaryExpr::SummaryAgg { .. } => Ok((0, 0)),
-            SummaryExpr::SummaryJoin { .. } => evidence
+                .ok_or(AnalyticalCostError::MissingOrStale("retain_exact"));
+        }
+        match &node.operator {
+            Operator::ASAP(ASAPOp::SummaryAgg { .. }) => Ok((0, 0)),
+            Operator::ASAP(ASAPOp::SummaryJoin { .. }) => evidence
                 .joins
                 .get(&(node as *const _))
                 .map(|value| (value.working_memory_bytes, value.output_buffer_bytes))
                 .ok_or(AnalyticalCostError::MissingOrStale("summary_join")),
-            SummaryExpr::SummaryMerge { .. }
-            | SummaryExpr::BinaryOp { .. }
-            | SummaryExpr::RelationalJoin { .. }
-            | SummaryExpr::ValueOperation { .. }
-            | SummaryExpr::SummarySubtract { .. }
-            | SummaryExpr::SummaryDelete { .. }
-            | SummaryExpr::SummaryEstimate { .. } => {
+            _ => {
                 let value = summary_operation_evidence(node, evidence)?.resource();
                 Ok((value.working_memory_bytes, value.output_buffer_bytes))
             }
@@ -884,7 +818,7 @@ pub(super) fn estimate_transient_liveness(
         live = live
             .checked_add(output)
             .ok_or(AnalyticalCostError::Overflow)?;
-        for child in children(node) {
+        for child in children(node, evidence) {
             let child_id = summary_physical_id(child, evidence)?;
             let remaining =
                 uses.get_mut(&child_id)
@@ -902,50 +836,23 @@ pub(super) fn estimate_transient_liveness(
     Ok(peak)
 }
 #[cfg(test)]
-pub(super) fn evidence_nodes(root: &SummaryNode) -> (Vec<&SummaryNode>, Vec<&SummaryNode>) {
+pub(super) fn evidence_nodes(root: &OperatorNode) -> (Vec<&OperatorNode>, Vec<&OperatorNode>) {
     fn visit<'a>(
-        node: &'a SummaryNode,
-        seen: &mut HashSet<*const SummaryNode>,
-        aggregations: &mut Vec<&'a SummaryNode>,
-        joins: &mut Vec<&'a SummaryNode>,
+        node: &'a OperatorNode,
+        seen: &mut HashSet<*const OperatorNode>,
+        aggregations: &mut Vec<&'a OperatorNode>,
+        joins: &mut Vec<&'a OperatorNode>,
     ) {
         if !seen.insert(node as *const _) {
             return;
         }
-        match &node.expr {
-            SummaryExpr::SummaryAgg { child, .. } => {
-                aggregations.push(node);
-                visit(child, seen, aggregations, joins);
-            }
-            SummaryExpr::ValueOperation { child, .. } => visit(child, seen, aggregations, joins),
-            SummaryExpr::SummaryMerge { children, .. } => {
-                for child in children {
-                    visit(child, seen, aggregations, joins);
-                }
-            }
-            SummaryExpr::SummarySubtract { left, right }
-            | SummaryExpr::RelationalJoin { left, right, .. }
-            | SummaryExpr::BinaryOp {
-                lhs: left,
-                rhs: right,
-                ..
-            }
-            | SummaryExpr::SummaryJoin {
-                outer: left,
-                inner: right,
-                ..
-            } => {
-                if matches!(&node.expr, SummaryExpr::SummaryJoin { .. }) {
-                    joins.push(node);
-                }
-                visit(left, seen, aggregations, joins);
-                visit(right, seen, aggregations, joins);
-            }
-            SummaryExpr::SummaryDelete { summary_input, .. }
-            | SummaryExpr::SummaryEstimate { summary_input, .. } => {
-                visit(summary_input, seen, aggregations, joins);
-            }
-            SummaryExpr::KeepPreAsap(_) => {}
+        match &node.operator {
+            Operator::ASAP(ASAPOp::SummaryAgg { .. }) => aggregations.push(node),
+            Operator::ASAP(ASAPOp::SummaryJoin { .. }) => joins.push(node),
+            _ => {}
+        }
+        for child in node.children() {
+            visit(child, seen, aggregations, joins);
         }
     }
     let mut aggregations = Vec::new();
@@ -961,7 +868,7 @@ struct SummaryOperationCounts {
     merges_per_read: u64,
     subtracts_per_read: u64,
     deletes_per_update: u64,
-    readouts_per_read: u64,
+    evaluations_per_read: u64,
     joins_per_read: u64,
 }
 
@@ -970,7 +877,7 @@ struct SummaryOperationCounts {
 /// once; explicit delete frequency comes from deletion evidence.
 #[cfg(test)]
 pub(super) fn estimate_incremental_summary_maintenance(
-    root: &SummaryNode,
+    root: &OperatorNode,
     guarantee: &SummaryMaintenanceLifecycleGuarantee,
     inputs: SummaryMaintenanceInputs,
     cpu: SummaryOperationCpuEvidence,
@@ -980,7 +887,7 @@ pub(super) fn estimate_incremental_summary_maintenance(
 }
 #[cfg(test)]
 pub(super) fn estimate_incremental_summary_maintenance_with_join(
-    root: &SummaryNode,
+    root: &OperatorNode,
     guarantee: &SummaryMaintenanceLifecycleGuarantee,
     inputs: SummaryMaintenanceInputs,
     cpu: SummaryOperationCpuEvidence,
@@ -1030,10 +937,10 @@ pub(super) fn estimate_incremental_summary_maintenance_with_join(
             .checked_mul(fanout)
             .ok_or(AnalyticalCostError::Overflow)?
     };
-    let readout = required_cpu_when(
-        counts.readouts_per_read,
-        "readout_cpu_ops",
-        cpu.readout_cpu_ops,
+    let evaluation = required_cpu_when(
+        counts.evaluations_per_read,
+        "evaluation_cpu_ops",
+        cpu.evaluation_cpu_ops,
     )?;
     let join_cpu = match (counts.joins_per_read, join.as_ref()) {
         (0, _) => 0.0,
@@ -1071,7 +978,7 @@ pub(super) fn estimate_incremental_summary_maintenance_with_join(
         + evaluations * counts.merges_per_read as f64 * instances * merge
         + evaluations * counts.subtracts_per_read as f64 * instances * subtract
         + delete_events as f64 * counts.deletes_per_update as f64 * delete
-        + evaluations * counts.readouts_per_read as f64 * instances * readout
+        + evaluations * counts.evaluations_per_read as f64 * instances * evaluation
         + evaluations * counts.joins_per_read as f64 * join_cpu;
     if !cpu_ops.is_finite() {
         return Err(AnalyticalCostError::Overflow);
@@ -1238,25 +1145,23 @@ fn required_cpu_when(
 }
 
 #[cfg(test)]
-fn count_operations(root: &SummaryNode) -> Result<SummaryOperationCounts, AnalyticalCostError> {
+fn count_operations(root: &OperatorNode) -> Result<SummaryOperationCounts, AnalyticalCostError> {
     fn visit(
-        node: &SummaryNode,
-        seen: &mut HashSet<*const SummaryNode>,
+        node: &OperatorNode,
+        seen: &mut HashSet<*const OperatorNode>,
         counts: &mut SummaryOperationCounts,
     ) -> Result<(), AnalyticalCostError> {
-        if !seen.insert(node as *const SummaryNode) {
+        if !seen.insert(node as *const OperatorNode) {
             return Ok(());
         }
-        match &node.expr {
-            SummaryExpr::KeepPreAsap(_) => {}
-            SummaryExpr::SummaryAgg { child, .. } => {
+        match &node.operator {
+            Operator::ASAP(ASAPOp::SummaryAgg { .. }) => {
                 counts.state_builds = counts
                     .state_builds
                     .checked_add(1)
                     .ok_or(AnalyticalCostError::Overflow)?;
-                visit(child, seen, counts)?;
             }
-            SummaryExpr::SummaryMerge { children, .. } => {
+            Operator::ASAP(ASAPOp::SummaryMerge { children }) => {
                 if children.is_empty() {
                     return Err(AnalyticalCostError::InvalidPhysicalDAG(
                         "summary merge has no children",
@@ -1266,50 +1171,44 @@ fn count_operations(root: &SummaryNode) -> Result<SummaryOperationCounts, Analyt
                     .merges_per_read
                     .checked_add(children.len().saturating_sub(1) as u64)
                     .ok_or(AnalyticalCostError::Overflow)?;
-                for child in children {
-                    visit(child, seen, counts)?;
-                }
             }
-            SummaryExpr::SummarySubtract { left, right } => {
+            Operator::ASAP(ASAPOp::SummarySubtract { .. }) => {
                 counts.subtracts_per_read = counts
                     .subtracts_per_read
                     .checked_add(1)
                     .ok_or(AnalyticalCostError::Overflow)?;
-                visit(left, seen, counts)?;
-                visit(right, seen, counts)?;
-            }
-            SummaryExpr::BinaryOp { lhs, rhs, .. } => {
-                visit(lhs, seen, counts)?;
-                visit(rhs, seen, counts)?;
             }
-            SummaryExpr::RelationalJoin { left, right, .. } => {
-                visit(left, seen, counts)?;
-                visit(right, seen, counts)?;
-            }
-
-            SummaryExpr::ValueOperation { child, .. } => visit(child, seen, counts)?,
-            SummaryExpr::SummaryDelete { summary_input, .. } => {
+            Operator::ASAP(ASAPOp::SummaryDelete { .. }) => {
                 counts.deletes_per_update = counts
                     .deletes_per_update
                     .checked_add(1)
                     .ok_or(AnalyticalCostError::Overflow)?;
-                visit(summary_input, seen, counts)?;
             }
-            SummaryExpr::SummaryEstimate { summary_input, .. } => {
-                counts.readouts_per_read = counts
-                    .readouts_per_read
+            Operator::ASAP(
+                ASAPOp::SummaryEstimate { .. } | ASAPOp::FinalizeExactAccumulator { .. },
+            ) => {
+                counts.evaluations_per_read = counts
+                    .evaluations_per_read
                     .checked_add(1)
                     .ok_or(AnalyticalCostError::Overflow)?;
-                visit(summary_input, seen, counts)?;
             }
-            SummaryExpr::SummaryJoin { outer, inner, .. } => {
+            Operator::ASAP(ASAPOp::SummaryJoin { .. }) => {
                 counts.joins_per_read = counts
                     .joins_per_read
                     .checked_add(1)
                     .ok_or(AnalyticalCostError::Overflow)?;
-                visit(outer, seen, counts)?;
-                visit(inner, seen, counts)?;
             }
+            // Retained relational work, accumulator/population boundaries and
+            // exact query-time operators add no summary operation.
+            Operator::NonASAP(_)
+            | Operator::ASAP(
+                ASAPOp::MaintainPopulation { .. }
+                | ASAPOp::EvaluatePopulation { .. }
+                | ASAPOp::Extension { .. },
+            ) => {}
+        }
+        for child in node.children() {
+            visit(child, seen, counts)?;
         }
         Ok(())
     }
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_cost/evidence.rs b/crates/asap-aware-mapping/src/summary_maintenance_cost/evidence.rs
index 7c8607685..6ae5999bd 100644
--- a/crates/asap-aware-mapping/src/summary_maintenance_cost/evidence.rs
+++ b/crates/asap-aware-mapping/src/summary_maintenance_cost/evidence.rs
@@ -134,7 +134,7 @@ pub struct SummaryOperationCpuEvidence {
     pub delete_events_per_second: Option<f64>,
     /// Concrete state instances touched by one delete event.
     pub delete_routing_fanout: Option<u64>,
-    pub readout_cpu_ops: Option<f64>,
+    pub evaluation_cpu_ops: Option<f64>,
 }
 
 /// Physical evidence for one `SummaryJoin` implementation. Total work,
@@ -185,7 +185,7 @@ pub struct SummaryOperatorResourceEvidence {
 }
 
 /// Evidence is structured by logical summary operation so delete-only facts
-/// cannot be attached to merge, subtract, or readout nodes.
+/// cannot be attached to merge, subtract, or evaluation nodes.
 #[derive(Debug, Clone, PartialEq)]
 pub enum SummaryOperatorEvidence {
     /// Exact query-time arithmetic over two independently realized operands.
@@ -201,7 +201,7 @@ pub enum SummaryOperatorEvidence {
         events_per_second: f64,
         routing_fanout: u64,
     },
-    Readout(SummaryOperatorResourceEvidence),
+    Evaluation(SummaryOperatorResourceEvidence),
 }
 
 impl SummaryOperatorEvidence {
@@ -212,7 +212,7 @@ impl SummaryOperatorEvidence {
             | Self::Merge(resource)
             | Self::Subtract(resource)
             | Self::Delete { resource, .. }
-            | Self::Readout(resource) => resource,
+            | Self::Evaluation(resource) => resource,
         }
     }
 
@@ -224,7 +224,7 @@ impl SummaryOperatorEvidence {
             | Self::Merge(resource)
             | Self::Subtract(resource)
             | Self::Delete { resource, .. }
-            | Self::Readout(resource) => resource,
+            | Self::Evaluation(resource) => resource,
         }
     }
 }
@@ -247,27 +247,27 @@ pub struct RetainedSubDAGEvidence {
 /// structurally equal node is not silently treated as the same deployment.
 #[derive(Debug, Clone, Default)]
 pub struct SummaryNodeEvidence {
-    pub(super) aggregations: HashMap<*const SummaryNode, SummaryAggregateEvidence>,
-    pub(super) joins: HashMap<*const SummaryNode, SummaryJoinEvidence>,
-    pub(super) operations: HashMap<*const SummaryNode, SummaryOperatorEvidence>,
-    pub(super) operation_state_owners: HashMap<*const SummaryNode, *const SummaryNode>,
-    pub(super) retained_queries: HashMap<*const SummaryNode, RetainedSubDAGEvidence>,
+    pub(super) aggregations: HashMap<*const OperatorNode, SummaryAggregateEvidence>,
+    pub(super) joins: HashMap<*const OperatorNode, SummaryJoinEvidence>,
+    pub(super) operations: HashMap<*const OperatorNode, SummaryOperatorEvidence>,
+    pub(super) operation_state_owners: HashMap<*const OperatorNode, *const OperatorNode>,
+    pub(super) retained_queries: HashMap<*const OperatorNode, RetainedSubDAGEvidence>,
 }
 
 impl SummaryNodeEvidence {
     pub fn insert_aggregation(
         &mut self,
-        node: &Rc<SummaryNode>,
+        node: &Rc<OperatorNode>,
         evidence: SummaryAggregateEvidence,
     ) {
         self.aggregations.insert(Rc::as_ptr(node), evidence);
     }
 
-    pub fn insert_join(&mut self, node: &Rc<SummaryNode>, evidence: SummaryJoinEvidence) {
+    pub fn insert_join(&mut self, node: &Rc<OperatorNode>, evidence: SummaryJoinEvidence) {
         self.joins.insert(Rc::as_ptr(node), evidence);
     }
 
-    pub fn insert_operation(&mut self, node: &Rc<SummaryNode>, evidence: SummaryOperatorEvidence) {
+    pub fn insert_operation(&mut self, node: &Rc<OperatorNode>, evidence: SummaryOperatorEvidence) {
         self.operations.insert(Rc::as_ptr(node), evidence);
     }
 
@@ -275,8 +275,8 @@ impl SummaryNodeEvidence {
     /// aggregation deployment whose active interval it follows.
     pub fn insert_state_operation(
         &mut self,
-        node: &Rc<SummaryNode>,
-        state: &Rc<SummaryNode>,
+        node: &Rc<OperatorNode>,
+        state: &Rc<OperatorNode>,
         evidence: SummaryOperatorEvidence,
     ) {
         self.operations.insert(Rc::as_ptr(node), evidence);
@@ -286,52 +286,57 @@ impl SummaryNodeEvidence {
 
     pub fn insert_retained_query(
         &mut self,
-        node: &Rc<SummaryNode>,
+        node: &Rc<OperatorNode>,
         evidence: RetainedSubDAGEvidence,
     ) {
         self.retained_queries.insert(Rc::as_ptr(node), evidence);
     }
 
-    pub(super) fn aggregation(&self, node: &SummaryNode) -> Option<SummaryAggregateEvidence> {
+    pub(super) fn aggregation(&self, node: &OperatorNode) -> Option<SummaryAggregateEvidence> {
         self.aggregations.get(&(node as *const _)).cloned()
     }
 }
 
 pub(super) fn summary_operation_evidence<'a>(
-    node: &SummaryNode,
+    node: &OperatorNode,
     evidence: &'a SummaryNodeEvidence,
 ) -> Result<&'a SummaryOperatorEvidence, AnalyticalCostError> {
     let operation = evidence
         .operations
         .get(&(node as *const _))
         .ok_or(AnalyticalCostError::MissingOrStale("summary operation"))?;
-    let matches = matches!(
-        (&node.expr, operation),
+    // A binary operator or join over two inputs is `Binary` evidence; every
+    // other non-ASAP operator, and the accumulator/population boundaries,
+    // is a `ValueOperation`.
+    let matches = match (&node.operator, operation) {
         (
-            SummaryExpr::BinaryOp { .. },
-            SummaryOperatorEvidence::Binary(_)
-        ) | (
-            SummaryExpr::ValueOperation { .. },
-            SummaryOperatorEvidence::ValueOperation(_)
-        ) | (
-            SummaryExpr::SummaryMerge { .. },
-            SummaryOperatorEvidence::Merge(_)
-        ) | (
-            SummaryExpr::SummarySubtract { .. },
-            SummaryOperatorEvidence::Subtract(_)
-        ) | (
-            SummaryExpr::SummaryDelete { .. },
-            SummaryOperatorEvidence::Delete { .. }
-        ) | (
-            SummaryExpr::SummaryEstimate { .. },
-            SummaryOperatorEvidence::Readout(_)
-        )
-    );
+            Operator::NonASAP(NonASAPOp::BinaryOp { .. } | NonASAPOp::Join { .. }),
+            SummaryOperatorEvidence::Binary(_),
+        ) => true,
+        (Operator::NonASAP(NonASAPOp::BinaryOp { .. } | NonASAPOp::Join { .. }), _) => false,
+        (
+            Operator::NonASAP(_)
+            | Operator::ASAP(
+                ASAPOp::FinalizeExactAccumulator { .. }
+                | ASAPOp::MaintainPopulation { .. }
+                | ASAPOp::EvaluatePopulation { .. },
+            ),
+            SummaryOperatorEvidence::ValueOperation(_),
+        ) => true,
+        (Operator::ASAP(ASAPOp::SummaryMerge { .. }), SummaryOperatorEvidence::Merge(_))
+        | (Operator::ASAP(ASAPOp::SummarySubtract { .. }), SummaryOperatorEvidence::Subtract(_))
+        | (Operator::ASAP(ASAPOp::SummaryDelete { .. }), SummaryOperatorEvidence::Delete { .. })
+        | (
+            Operator::ASAP(ASAPOp::SummaryEstimate { .. }),
+            SummaryOperatorEvidence::Evaluation(_),
+        ) => true,
+        _ => false,
+    };
     if matches {
         Ok(operation)
     } else {
         Err(AnalyticalCostError::InconsistentOperatorStatistics(
-            "summary operation evidence kind does not match SummaryExpr",
+            "summary operation evidence kind does not match the operator",
         ))
     }
 }
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_cost/mod.rs b/crates/asap-aware-mapping/src/summary_maintenance_cost/mod.rs
index bc1b7ddaf..ff4c69c1d 100644
--- a/crates/asap-aware-mapping/src/summary_maintenance_cost/mod.rs
+++ b/crates/asap-aware-mapping/src/summary_maintenance_cost/mod.rs
@@ -1,4 +1,4 @@
-//! Analytical resource cost for at-rest and incrementally maintained summary deployments.
+//! Analytical resource cost for at-rest and at-rest and incrementally maintained summary deployments.
 //!
 //! The canonical workload and lifecycle types own deployment semantics. This
 //! module only adds physical evidence absent from those schemas: state size,
@@ -7,14 +7,13 @@
 use std::collections::{HashMap, HashSet};
 use std::rc::Rc;
 
+use asap_types::ir::{ASAPOp, NonASAPOp, Operator, OperatorNode, Predicate};
 use asap_types::post_asap::{
     BoundExpr, ErrorMetric, ExactKind, FieldDataType, GuaranteeSource, ProbabilityExpr,
-    ResultGuarantee, SketchAlgorithm, SummaryExpr, SummaryMaintenanceLifecycle,
-    SummaryMaintenanceLifecycleGuarantee, SummaryNode, SummaryWindowFramework,
-};
-use asap_types::pre_asap::{
-    agg_intent::AggIntent, CompareOpKind, InfoMatcher, Predicate, QueryExpr, Source,
+    ResultGuarantee, SketchAlgorithm, SummaryMaintenanceLifecycle,
+    SummaryMaintenanceLifecycleGuarantee, SummaryWindowFramework,
 };
+use asap_types::pre_asap::{agg_intent::AggIntent, CompareOpKind, InfoMatcher, Source};
 use asap_types::types::AccuracyTarget;
 use asap_types::workload::{DataArrival, DataWorkload, QueryRecurrence, RepeatedDemand};
 use serde::{Deserialize, Serialize};
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_cost/model.rs b/crates/asap-aware-mapping/src/summary_maintenance_cost/model.rs
index 7859db9b8..167874295 100644
--- a/crates/asap-aware-mapping/src/summary_maintenance_cost/model.rs
+++ b/crates/asap-aware-mapping/src/summary_maintenance_cost/model.rs
@@ -7,7 +7,7 @@ pub struct SummaryMaintenanceCostModel {
     pub node_evidence: SummaryNodeEvidence,
     pub calibration: ResourceCalibration,
     pub capabilities: SummaryMaintenanceCapabilities,
-    target_comparisons: HashMap<*const QueryExpr, SummaryTargetComparison>,
+    target_comparisons: HashMap<*const OperatorNode, SummaryTargetComparison>,
     candidate_comparisons: HashMap<CandidateComparisonKey, BoundCandidateIdentity>,
     physical_plan_alternatives:
         HashMap<CandidateComparisonKey, Vec<SummaryPhysicalPlanAlternative>>,
@@ -15,17 +15,17 @@ pub struct SummaryMaintenanceCostModel {
         HashMap<CandidateComparisonKey, Vec<SummaryWindowFrameworkCandidate>>,
 }
 
-type CandidateComparisonKey = (*const QueryExpr, *const SummaryNode);
+type CandidateComparisonKey = (*const OperatorNode, *const OperatorNode);
 
 #[derive(Debug, Clone)]
 struct BoundCandidateIdentity {
-    _target: Rc<QueryExpr>,
-    _root: Rc<SummaryNode>,
+    _target: Rc<OperatorNode>,
+    _root: Rc<OperatorNode>,
 }
 
 #[derive(Debug, Clone)]
 struct SummaryTargetComparison {
-    _target: Rc<QueryExpr>,
+    _target: Rc<OperatorNode>,
     scope: ComparisonScope,
     raw: RawInputEvidence,
 }
@@ -59,73 +59,40 @@ fn info_source(selector: &[InfoMatcher]) -> Result<Source, AnalyticalCostError>
     })
 }
 
+/// Collect the source selections (scan sources with their predicates, and
+/// info-metric selectors) of every leaf reachable from `node`, visiting a
+/// shared node once.
 pub(super) fn query_source_selections(
-    query: &QueryExpr,
+    node: &OperatorNode,
+    seen: &mut HashSet<*const OperatorNode>,
     out: &mut Vec<LogicalSourceSelection>,
 ) -> Result<(), AnalyticalCostError> {
-    use QueryExpr::*;
-    match query {
-        Scan {
+    if !seen.insert(node as *const _) {
+        return Ok(());
+    }
+    match &node.operator {
+        Operator::NonASAP(NonASAPOp::Scan {
             source, predicates, ..
-        } => out.push((source.clone(), predicates.clone(), vec![])),
-        PromqlVectorFromScalar(child) | PromqlScalarFromVector(child) => {
-            query_source_selections(child, out)?
-        }
-        PromqlInfoEnrich { selector, child } => {
-            query_source_selections(child, out)?;
+        }) => out.push((source.clone(), predicates.clone(), vec![])),
+        Operator::NonASAP(NonASAPOp::PromqlInfoEnrich { selector, child }) => {
+            query_source_selections(child, seen, out)?;
             out.push((info_source(selector)?, vec![], selector.clone()));
         }
-        PromqlRelabel { child, .. }
-        | Filter { child, .. }
-        | Project { child, .. }
-        | Aggregate { child, .. }
-        | Dedup { child, .. }
-        | PromqlSubquery { child, .. }
-        | TimeRange { child, .. }
-        | TimeShift { child, .. }
-        | SQLWindowFunc { child, .. }
-        | PromqlSeriesSample { child, .. }
-        | Sort { child, .. }
-        | Limit { child, .. } => query_source_selections(child, out)?,
-        Concat { children, .. } => {
-            for child in children {
-                query_source_selections(child, out)?;
+        _ => {
+            for child in node.children() {
+                query_source_selections(child, seen, out)?;
             }
         }
-        Join { left, right, .. } | SetOp { left, right, .. } => {
-            query_source_selections(left, out)?;
-            query_source_selections(right, out)?;
-        }
-        BinaryOp { lhs, rhs, .. } => {
-            query_source_selections(lhs, out)?;
-            query_source_selections(rhs, out)?;
-        }
-        PromqlScalarBridge(_)
-        | EvalTimestamp
-        | CurrentTimestamp
-        | Column(_)
-        | Literal(_)
-        | Compare { .. }
-        | BoolAnd(_)
-        | BoolOr(_)
-        | Not(_)
-        | IsNull(_)
-        | IsNotNull(_)
-        | Cast { .. }
-        | InList { .. }
-        | FunctionCall { .. }
-        | Arithmetic { .. }
-        | Case { .. } => {}
     }
     Ok(())
 }
 
 fn validate_query_scope(
-    target: &QueryExpr,
+    target: &OperatorNode,
     scope: &ComparisonScope,
 ) -> Result<(), AnalyticalCostError> {
     let mut actual = Vec::new();
-    query_source_selections(target, &mut actual)?;
+    query_source_selections(target, &mut HashSet::new(), &mut actual)?;
     let actual = deduplicate_source_selections(actual);
     let mut declared: Vec<_> = scope
         .sources
@@ -428,8 +395,8 @@ impl SummaryMaintenanceCostModel {
     /// rejected rather than silently replacing the canonical context.
     pub fn bind_candidate_comparison(
         &mut self,
-        target: &Rc<QueryExpr>,
-        root: &Rc<SummaryNode>,
+        target: &Rc<OperatorNode>,
+        root: &Rc<OperatorNode>,
         scope: ComparisonScope,
         raw: RawInputEvidence,
     ) -> Result<(), AnalyticalCostError> {
@@ -474,8 +441,8 @@ impl SummaryMaintenanceCostModel {
     /// candidate. Duplicate or empty provider identities are rejected.
     pub fn bind_physical_plan_alternative(
         &mut self,
-        target: &Rc<QueryExpr>,
-        root: &Rc<SummaryNode>,
+        target: &Rc<OperatorNode>,
+        root: &Rc<OperatorNode>,
         alternative: SummaryPhysicalPlanAlternative,
     ) -> Result<(), AnalyticalCostError> {
         let key = (Rc::as_ptr(target), Rc::as_ptr(root));
@@ -512,8 +479,8 @@ impl SummaryMaintenanceCostModel {
     /// evidence keep the implementations distinct during ranking.
     pub fn bind_window_framework_candidate(
         &mut self,
-        target: &Rc<QueryExpr>,
-        root: &Rc<SummaryNode>,
+        target: &Rc<OperatorNode>,
+        root: &Rc<OperatorNode>,
         candidate: SummaryWindowFrameworkCandidate,
     ) -> Result<(), AnalyticalCostError> {
         let key = (Rc::as_ptr(target), Rc::as_ptr(root));
@@ -565,8 +532,8 @@ impl SummaryMaintenanceCostModel {
 
     fn comparison_context(
         &self,
-        root: &SummaryNode,
-        target: Option<&QueryExpr>,
+        root: &OperatorNode,
+        target: Option<&OperatorNode>,
         horizon: Option<crate::recurrence::Horizon>,
         expected_reads: Option<f64>,
     ) -> Option<(CandidateComparisonKey, &SummaryTargetComparison)> {
@@ -600,7 +567,7 @@ impl SummaryMaintenanceCostModel {
 
     fn complete_cost_with_evidence(
         &self,
-        root: &SummaryNode,
+        root: &OperatorNode,
         deployments: &[CostedSummaryDeployment<'_>],
         comparison: &SummaryTargetComparison,
         evidence: &SummaryNodeEvidence,
@@ -619,7 +586,7 @@ impl SummaryMaintenanceCostModel {
         )
     }
 
-    fn canonical_inputs(&self, summary: &SummaryNode) -> Option<SummaryAggregateEvidence> {
+    fn canonical_inputs(&self, summary: &OperatorNode) -> Option<SummaryAggregateEvidence> {
         let evidence = self.node_evidence.aggregation(summary)?;
         evidence.inputs.validate().ok()?;
         Some(evidence)
@@ -631,7 +598,7 @@ impl SummaryMaintenanceCostModel {
 
     fn lifecycle_inputs(
         &self,
-        summary: &SummaryNode,
+        summary: &OperatorNode,
         horizon: Option<crate::recurrence::Horizon>,
     ) -> Option<SummaryMaintenanceLifecycleCostInputs> {
         let evidence = self.canonical_inputs(summary)?;
@@ -657,8 +624,8 @@ impl SummaryMaintenanceCostModel {
         Some(SummaryMaintenanceLifecycleCostInputs {
             build_cost: Some(build),
             maintenance_cost_per_update: Some(maintenance),
-            // Readout is a separate physical operator in the complete DAG.
-            // A state-only candidate therefore does not fabricate readout
+            // Evaluation is a separate physical operator in the complete DAG.
+            // A state-only candidate therefore does not fabricate evaluation
             // evidence merely to keep a lifecycle alternative selectable.
             summary_read_cost: Some(Cost::ZERO),
             retention_cost_rate: Some(CostRate(retention_total.0 / horizon_seconds)),
@@ -681,8 +648,7 @@ impl CostModel for SummaryMaintenanceCostModel {
             // Lifecycle selection supplies a complete override. If it cannot,
             // the candidate remains unavailable rather than receiving this
             // trait's structural fallback.
-            Replacement::Summary(_) => None,
-            Replacement::Rewrite(_) => None,
+            Replacement::SubDAG(_) => None,
         }
     }
 
@@ -700,14 +666,14 @@ impl CostModel for SummaryMaintenanceCostModel {
 
     fn summary_maintenance_lifecycle_cost_inputs(
         &self,
-        _summary: &SummaryNode,
+        _summary: &OperatorNode,
     ) -> SummaryMaintenanceLifecycleCostInputs {
         SummaryMaintenanceLifecycleCostInputs::default()
     }
 
     fn summary_maintenance_lifecycle_cost_inputs_for_horizon(
         &self,
-        summary: &SummaryNode,
+        summary: &OperatorNode,
         horizon: Option<crate::recurrence::Horizon>,
     ) -> SummaryMaintenanceLifecycleCostInputs {
         self.lifecycle_inputs(summary, horizon).unwrap_or_default()
@@ -715,15 +681,15 @@ impl CostModel for SummaryMaintenanceCostModel {
 
     fn summary_maintenance_capabilities(
         &self,
-        _summary: &SummaryNode,
+        _summary: &OperatorNode,
     ) -> SummaryMaintenanceCapabilities {
         self.capabilities
     }
 
     fn complete_summary_candidate_cost(
         &self,
-        root: &SummaryNode,
-        target: Option<&QueryExpr>,
+        root: &OperatorNode,
+        target: Option<&OperatorNode>,
         deployments: &[CostedSummaryDeployment<'_>],
         horizon: Option<crate::recurrence::Horizon>,
         expected_reads: Option<f64>,
@@ -742,8 +708,8 @@ impl CostModel for SummaryMaintenanceCostModel {
 
     fn complete_summary_candidate_estimate(
         &self,
-        root: &SummaryNode,
-        target: Option<&QueryExpr>,
+        root: &OperatorNode,
+        target: Option<&OperatorNode>,
         deployments: &[CostedSummaryDeployment<'_>],
         horizon: Option<crate::recurrence::Horizon>,
         expected_reads: Option<f64>,
@@ -847,14 +813,14 @@ impl CostModel for SummaryMaintenanceCostModel {
         true
     }
 
-    fn raw_query_recompute_cost(&self, target: &QueryExpr) -> Option<Cost> {
+    fn raw_query_recompute_cost(&self, target: &OperatorNode) -> Option<Cost> {
         let _ = target;
         None
     }
 
     fn raw_query_recompute_total_cost(
         &self,
-        target: &QueryExpr,
+        target: &OperatorNode,
         expected_reads: f64,
     ) -> Option<Cost> {
         let target_ptr = target as *const _;
@@ -880,13 +846,14 @@ use super::estimator::*;
 mod tests {
     use std::rc::Rc;
 
+    use asap_types::ir::{ASAPOp, BinaryOperator, NonASAPOp, Operator, OperatorNode};
     use asap_types::post_asap::{
         EvaluationSchedule, ExactKind, ExactParams, Field, FieldDataType, GroupingStrategy,
-        OutputRepresentation, Schema, SummaryExpr, SummaryMaintenanceLifecycle,
-        SummaryMaintenanceLifecycleGuarantee, SummaryMaintenanceMode,
+        OutputRepresentation, Schema, SummaryMaintenanceLifecycle,
+        SummaryMaintenanceLifecycleGuarantee, SummaryMaintenanceMode, SummaryUpdate,
     };
     use asap_types::pre_asap::{
-        agg_intent::AggIntent, ColumnRef, DataType, QueryExpr, Reduction, Source,
+        agg_intent::AggIntent, ArithmeticOpKind, BinaryOpKind, DataType, Reduction, Source,
     };
     use asap_types::workload::{
         DataWorkload, Evidence, EvidenceSource, Predictability, Query, QueryLanguage,
@@ -903,7 +870,7 @@ mod tests {
     };
 
     fn estimate_test(
-        root: &SummaryNode,
+        root: &OperatorNode,
         guarantee: &SummaryMaintenanceLifecycleGuarantee,
         inputs: SummaryMaintenanceInputs,
         cpu: SummaryOperationCpuEvidence,
@@ -912,7 +879,7 @@ mod tests {
     }
 
     fn estimate_join_test(
-        root: &SummaryNode,
+        root: &OperatorNode,
         guarantee: &SummaryMaintenanceLifecycleGuarantee,
         inputs: SummaryMaintenanceInputs,
         cpu: SummaryOperationCpuEvidence,
@@ -1200,7 +1167,7 @@ mod tests {
             inputs,
             SummaryOperationCpuEvidence {
                 insert_cpu_ops: Some(2.0),
-                readout_cpu_ops: Some(1.0),
+                evaluation_cpu_ops: Some(1.0),
                 ..SummaryOperationCpuEvidence::default()
             },
         )
@@ -1253,7 +1220,7 @@ mod tests {
             inputs,
             SummaryOperationCpuEvidence {
                 insert_cpu_ops: Some(2.0),
-                readout_cpu_ops: Some(1.0),
+                evaluation_cpu_ops: Some(1.0),
                 ..SummaryOperationCpuEvidence::default()
             },
         )
@@ -1442,7 +1409,10 @@ mod tests {
         let mut model = streaming_model();
         for group in space.target_subdag_candidates() {
             for candidate in &group.candidates {
-                if let Replacement::Summary(root) = &candidate.replacement {
+                if let Replacement::SubDAG(root) = &candidate.replacement {
+                    if !root.contains_asap() {
+                        continue;
+                    }
                     bind_aggregations(
                         &mut model,
                         &group.target,
@@ -1713,10 +1683,13 @@ mod tests {
             op: CompareOpKind::Eq,
             value: "api".into(),
         }];
-        let info_target = QueryExpr::PromqlInfoEnrich {
-            selector: selector.clone(),
-            child: target,
-        };
+        let info_target = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(
+            NonASAPOp::PromqlInfoEnrich {
+                selector: selector.clone(),
+                child: target,
+            },
+        ))
+        .unwrap();
         let mut info_scope = streaming_scope();
         info_scope
             .sources
@@ -1739,8 +1712,9 @@ mod tests {
     }
 
     #[test]
-    fn delete_owner_must_be_the_unique_state_reachable_from_its_input() {
-        let workload = streaming_workload();
+    fn summary_delete_dag_fails_closed_before_costing() {
+        // SummaryDelete is reserved: planning rejects the DAG even with full
+        // delete evidence, instead of costing (or owner-checking) the delete.
         let target = streaming_sum_query();
         let root = summary_with_operations(false, false, true);
         let mut cpu = streaming_cpu();
@@ -1750,34 +1724,32 @@ mod tests {
         let mut model = streaming_model();
         model.capabilities.delete = true;
         bind_aggregations(&mut model, &target, &root, streaming_inputs(), cpu);
-        let SummaryExpr::SummaryEstimate { summary_input, .. } = &root.expr else {
-            unreachable!();
-        };
-        let delete_ptr = Rc::as_ptr(summary_input);
-        let unrelated = summary_with_operations(false, false, false);
-        let unrelated_agg = evidence_nodes(&unrelated).0[0] as *const _;
-        model
-            .node_evidence
-            .operation_state_owners
-            .insert(delete_ptr, unrelated_agg);
 
-        let plan = plan_summary_maintenance_lifecycles(
-            Rc::clone(&root),
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        assert_eq!(plan.summary_total_cost, None);
+        // Under a evaluation, the reserved delete surfaces as an illegal child.
+        assert!(matches!(
+            streaming_planning_error(Rc::clone(&root), &model),
+            asap_types::post_asap::ExecutionDataStateError::IllegalChildDataState {
+                edge: "FinalizeExactAccumulator.child",
+                child: asap_types::post_asap::ExecutionDataState::QUERY_ROWS,
+            }
+        ));
+        // As the root, it is reported as the unimplemented operator itself.
+        assert!(matches!(
+            streaming_planning_error(evaluation_state(&root), &model),
+            asap_types::post_asap::ExecutionDataStateError::UnimplementedOperator {
+                operator: "SummaryDelete"
+            }
+        ));
     }
 
     #[test]
     fn summary_edge_and_io_evidence_fail_closed() {
+        // Over two independent summaries combined by a BinaryOp: a parent
+        // input edge that disagrees with its child's output, or missing I/O
+        // evidence on the root, leaves the whole-DAG cost unset.
         let workload = streaming_workload();
         let target = streaming_sum_query();
-        let root = summary_join();
+        let root = add_independent_summary_results();
         let mut model = streaming_model();
         bind_aggregations(
             &mut model,
@@ -1786,19 +1758,15 @@ mod tests {
             streaming_inputs(),
             streaming_cpu(),
         );
-        let join = evidence_nodes(&root).1[0];
-        model.node_evidence.joins.insert(
-            join as *const _,
-            SummaryJoinEvidence {
-                physical_id: "join-edge".into(),
-                inputs: vec![test_edge(), EdgeStatistics { rows: 2, bytes: 16 }],
-                output: test_edge(),
-                cpu_ops_per_execution: 1.0,
-                working_memory_bytes: 1,
-                output_buffer_bytes: 0,
-                executions_per_evaluation: 1,
-                io_bytes_per_execution: Some(0),
-            },
+        model.node_evidence.insert_operation(
+            &root,
+            SummaryOperatorEvidence::Binary(test_resource(
+                "binary-edge",
+                vec![test_edge(), EdgeStatistics { rows: 2, bytes: 16 }],
+                1.0,
+                1,
+                0,
+            )),
         );
         let bad_edge = plan_summary_maintenance_lifecycles(
             Rc::clone(&root),
@@ -1811,20 +1779,34 @@ mod tests {
         .unwrap();
         assert_eq!(bad_edge.summary_total_cost, None);
 
-        model
+        let root_evidence = model
             .node_evidence
-            .joins
-            .get_mut(&(join as *const _))
+            .operations
+            .get_mut(&Rc::as_ptr(&root))
             .unwrap()
-            .inputs = vec![test_edge(), test_edge()];
+            .resource_mut();
+        root_evidence.inputs = vec![test_edge(), test_edge()];
+        root_evidence.io_bytes_per_execution = None;
+        let missing_io = plan_summary_maintenance_lifecycles(
+            Rc::clone(&root),
+            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
+            0,
+            Some(Horizon(5.0)),
+            SummaryMaintenanceLifecycleCapabilities::ALL,
+            &model,
+        )
+        .unwrap();
+        assert_eq!(missing_io.summary_total_cost, None);
+
+        // Control: the same evidence with I/O restored is costable.
         model
             .node_evidence
             .operations
             .get_mut(&Rc::as_ptr(&root))
             .unwrap()
             .resource_mut()
-            .io_bytes_per_execution = None;
-        let missing_io = plan_summary_maintenance_lifecycles(
+            .io_bytes_per_execution = Some(0);
+        let complete = plan_summary_maintenance_lifecycles(
             root,
             WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
             0,
@@ -1833,14 +1815,17 @@ mod tests {
             &model,
         )
         .unwrap();
-        assert_eq!(missing_io.summary_total_cost, None);
+        assert!(complete.summary_total_cost.is_some());
     }
 
     #[test]
     fn summary_edges_io_and_physical_identity_fail_closed() {
+        // Evidence bound to a structurally equal clone of the BinaryOp does not
+        // count for the real node; a bad input edge or missing I/O on the real
+        // node still fails closed.
         let workload = streaming_workload();
         let target = streaming_sum_query();
-        let root = summary_join();
+        let root = add_independent_summary_results();
         let mut model = streaming_model();
         bind_aggregations(
             &mut model,
@@ -1849,34 +1834,27 @@ mod tests {
             streaming_inputs(),
             streaming_cpu(),
         );
-        let (_, joins) = evidence_nodes(&root);
-        model.node_evidence.insert_join(
-            &Rc::new(joins[0].clone()),
-            SummaryJoinEvidence {
-                physical_id: "unused".into(),
-                inputs: vec![test_edge(), test_edge()],
-                output: test_edge(),
-                cpu_ops_per_execution: 1.0,
-                working_memory_bytes: 1,
-                output_buffer_bytes: 0,
-                executions_per_evaluation: 1,
-                io_bytes_per_execution: Some(0),
-            },
+        model.node_evidence.insert_operation(
+            &Rc::new((*root).clone()),
+            SummaryOperatorEvidence::Binary(test_resource(
+                "unused",
+                vec![test_edge(), test_edge()],
+                1.0,
+                1,
+                0,
+            )),
         );
-        // Bind the actual join, then make one parent input disagree with its
-        // child's output.
-        model.node_evidence.joins.insert(
-            joins[0] as *const _,
-            SummaryJoinEvidence {
-                physical_id: "join-edge".into(),
-                inputs: vec![test_edge(), EdgeStatistics { rows: 2, bytes: 16 }],
-                output: test_edge(),
-                cpu_ops_per_execution: 1.0,
-                working_memory_bytes: 1,
-                output_buffer_bytes: 0,
-                executions_per_evaluation: 1,
-                io_bytes_per_execution: Some(0),
-            },
+        // Bind the actual BinaryOp, then make one parent input disagree with
+        // its child's output.
+        model.node_evidence.insert_operation(
+            &root,
+            SummaryOperatorEvidence::Binary(test_resource(
+                "binary-edge",
+                vec![test_edge(), EdgeStatistics { rows: 2, bytes: 16 }],
+                1.0,
+                1,
+                0,
+            )),
         );
         let bad_edge = plan_summary_maintenance_lifecycles(
             Rc::clone(&root),
@@ -1889,19 +1867,14 @@ mod tests {
         .unwrap();
         assert_eq!(bad_edge.summary_total_cost, None);
 
-        model
-            .node_evidence
-            .joins
-            .get_mut(&(joins[0] as *const _))
-            .unwrap()
-            .inputs = vec![test_edge(), test_edge()];
-        model
+        let root_evidence = model
             .node_evidence
             .operations
             .get_mut(&Rc::as_ptr(&root))
             .unwrap()
-            .resource_mut()
-            .io_bytes_per_execution = None;
+            .resource_mut();
+        root_evidence.inputs = vec![test_edge(), test_edge()];
+        root_evidence.io_bytes_per_execution = None;
         let missing_io = plan_summary_maintenance_lifecycles(
             root,
             WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
@@ -1955,9 +1928,11 @@ mod tests {
 
     #[test]
     fn conflicting_evidence_cannot_alias_one_provider_physical_identity() {
+        // Two independent summary states (combined by a BinaryOp) that claim
+        // one physical id but carry different evidence leave the cost unset.
         let workload = streaming_workload();
         let target = streaming_sum_query();
-        let root = summary_join();
+        let root = add_independent_summary_results();
         let mut model = streaming_model();
         bind_aggregations(
             &mut model,
@@ -1967,6 +1942,7 @@ mod tests {
             streaming_cpu(),
         );
         let aggregations = evidence_nodes(&root).0;
+        assert_eq!(aggregations.len(), 2);
         let first = aggregations[0] as *const _;
         let second = aggregations[1] as *const _;
         model
@@ -1992,8 +1968,9 @@ mod tests {
     }
 
     #[test]
-    fn lifecycle_plan_does_not_fall_back_to_partial_agg_cost_for_a_join_root() {
-        let workload = streaming_workload();
+    fn summary_join_root_fails_closed_even_with_join_evidence() {
+        // SummaryJoin is reserved: planning rejects the DAG whether or not
+        // join evidence is bound, so no partial or join cost is produced.
         let root = summary_join();
         let target = streaming_sum_query();
         let mut model = streaming_model();
@@ -2004,21 +1981,15 @@ mod tests {
             streaming_inputs(),
             streaming_cpu(),
         );
-        let plan = plan_summary_maintenance_lifecycles(
-            Rc::clone(&root),
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        assert_eq!(plan.deployments.len(), 2);
-        assert_eq!(plan.summary_total_cost, None);
+        assert!(matches!(
+            streaming_planning_error(Rc::clone(&root), &model),
+            asap_types::post_asap::ExecutionDataStateError::UnimplementedOperator {
+                operator: "SummaryJoin"
+            }
+        ));
 
-        let mut costed = model;
         let join_node = evidence_nodes(&root).1[0];
-        costed.node_evidence.joins.insert(
+        model.node_evidence.joins.insert(
             join_node as *const _,
             SummaryJoinEvidence {
                 physical_id: "costed-join".into(),
@@ -2031,28 +2002,28 @@ mod tests {
                 io_bytes_per_execution: Some(0),
             },
         );
-        let costed_plan = plan_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &costed,
-        )
-        .unwrap();
-        assert!(costed_plan.summary_total_cost.is_some());
+        assert!(matches!(
+            streaming_planning_error(root, &model),
+            asap_types::post_asap::ExecutionDataStateError::UnimplementedOperator {
+                operator: "SummaryJoin"
+            }
+        ));
     }
 
     #[test]
     fn whole_dag_cost_requires_and_uses_each_rc_bound_state_evidence() {
+        // Over two independent summaries combined by a BinaryOp: the cost needs
+        // evidence for each Rc-bound state, charges peak transient memory, and
+        // de-duplicates bootstrap scans only on a shared provider read id.
         let workload = streaming_workload();
-        let root = summary_join();
+        let root = add_independent_summary_results();
+        let (left, right) = binary_operands(&root);
         let target = streaming_sum_query();
-        let (aggregations, joins) = evidence_nodes(&root);
+        let aggregations = [evaluation_state(&left), evaluation_state(&right)];
         let mut model = streaming_model();
         bind_comparison(&mut model, &target, &root);
-        model.node_evidence.aggregations.insert(
-            aggregations[0] as *const _,
+        model.node_evidence.insert_aggregation(
+            &aggregations[0],
             SummaryAggregateEvidence {
                 physical_id: "left-state".into(),
                 input: test_edge(),
@@ -2078,8 +2049,8 @@ mod tests {
         second_inputs.state_bytes_per_summary = 250;
         let mut second_cpu = streaming_cpu();
         second_cpu.insert_cpu_ops = Some(5.0);
-        model.node_evidence.aggregations.insert(
-            aggregations[1] as *const _,
+        model.node_evidence.insert_aggregation(
+            &aggregations[1],
             SummaryAggregateEvidence {
                 physical_id: "right-state".into(),
                 input: test_edge(),
@@ -2090,31 +2061,37 @@ mod tests {
                 insert_cpu_ops: second_cpu.insert_cpu_ops.unwrap(),
             },
         );
-        model.node_evidence.joins.insert(
-            joins[0] as *const _,
-            SummaryJoinEvidence {
-                physical_id: "join".into(),
-                inputs: vec![test_edge(), test_edge()],
-                output: test_edge(),
-                cpu_ops_per_execution: 6.0,
-                working_memory_bytes: 64,
-                output_buffer_bytes: 64,
-                executions_per_evaluation: 1,
-                io_bytes_per_execution: Some(0),
-            },
+        // The left evaluation plays the old join's role: a 64-byte workspace and a
+        // 64-byte output that stays live until the root BinaryOp consumes it.
+        model.node_evidence.insert_operation(
+            &left,
+            SummaryOperatorEvidence::ValueOperation(test_resource(
+                "left-evaluation",
+                vec![test_edge()],
+                6.0,
+                64,
+                64,
+            )),
         );
-        model.node_evidence.operations.insert(
-            Rc::as_ptr(&root),
-            SummaryOperatorEvidence::Readout(SummaryOperatorResourceEvidence {
-                physical_id: "root-readout".into(),
-                inputs: vec![test_edge()],
-                output: test_edge(),
-                cpu_ops: 3.0,
-                working_memory_bytes: 0,
-                output_buffer_bytes: 0,
-                executions_per_evaluation: 1,
-                io_bytes_per_execution: Some(0),
-            }),
+        model.node_evidence.insert_operation(
+            &right,
+            SummaryOperatorEvidence::ValueOperation(test_resource(
+                "right-evaluation",
+                vec![test_edge()],
+                3.0,
+                0,
+                0,
+            )),
+        );
+        model.node_evidence.insert_operation(
+            &root,
+            SummaryOperatorEvidence::Binary(test_resource(
+                "root-binary",
+                vec![test_edge(), test_edge()],
+                3.0,
+                0,
+                0,
+            )),
         );
         let complete = plan_summary_maintenance_lifecycles(
             Rc::clone(&root),
@@ -2143,8 +2120,9 @@ mod tests {
             &model,
         )
         .unwrap();
-        // The join's 64-byte output remains live while the readout's workspace
-        // is active. The join's execution workspace is released first.
+        // The left evaluation's 64-byte output remains live while the binary's
+        // workspace is active (64 + 128 = 192); the evaluation's own workspace is
+        // released first, so the old peak was 64 + 64 = 128.
         assert_eq!(
             larger_workspace.summary_total_cost.unwrap().0 - complete.summary_total_cost.unwrap().0,
             64.0
@@ -2184,7 +2162,10 @@ mod tests {
             });
         let target = streaming_sum_query();
         let root = summary_with_operations(false, false, false);
-        let SummaryExpr::SummaryEstimate { summary_input, .. } = &root.expr else {
+        let Operator::ASAP(ASAPOp::FinalizeExactAccumulator {
+            child: summary_input,
+        }) = &root.operator
+        else {
             unreachable!();
         };
         let windowed_summary = Rc::clone(summary_input);
@@ -2326,7 +2307,10 @@ mod tests {
     fn window_framework_candidates_require_unique_nonempty_planner_primitives() {
         let target = streaming_sum_query();
         let root = summary_with_operations(false, false, false);
-        let SummaryExpr::SummaryEstimate { summary_input, .. } = &root.expr else {
+        let Operator::ASAP(ASAPOp::FinalizeExactAccumulator {
+            child: summary_input,
+        }) = &root.operator
+        else {
             unreachable!();
         };
         let windowed_summary = Rc::clone(summary_input);
@@ -2365,9 +2349,12 @@ mod tests {
 
     #[test]
     fn one_physical_identity_cannot_alias_different_window_frameworks() {
+        // Two independent summaries (combined by a BinaryOp) sharing one
+        // physical state id but assigned different window frameworks leave
+        // the cost unset.
         let workload = streaming_workload();
         let target = streaming_sum_query();
-        let root = summary_join();
+        let root = add_independent_summary_results();
         let mut model = streaming_model();
         bind_aggregations(
             &mut model,
@@ -2376,44 +2363,22 @@ mod tests {
             streaming_inputs(),
             streaming_cpu(),
         );
-        let SummaryExpr::SummaryEstimate { summary_input, .. } = &root.expr else {
-            unreachable!();
-        };
-        let SummaryExpr::SummaryJoin { outer, inner, .. } = &summary_input.expr else {
-            unreachable!();
-        };
-        let aggregation_nodes = [Rc::clone(outer), Rc::clone(inner)];
-        let (aggregations, joins) = evidence_nodes(&root);
-        model.node_evidence.joins.insert(
-            joins[0] as *const _,
-            SummaryJoinEvidence {
-                physical_id: "joined-readout".into(),
-                inputs: vec![test_edge(), test_edge()],
-                output: test_edge(),
-                cpu_ops_per_execution: 1.0,
-                working_memory_bytes: 8,
-                output_buffer_bytes: 0,
-                executions_per_evaluation: 1,
-                io_bytes_per_execution: Some(0),
-            },
-        );
+        let (left, right) = binary_operands(&root);
+        let aggregation_nodes = [evaluation_state(&left), evaluation_state(&right)];
 
         let mut shared_aggregation =
-            model.node_evidence.aggregations[&(aggregations[0] as *const _)].clone();
+            model.node_evidence.aggregations[&Rc::as_ptr(&aggregation_nodes[0])].clone();
         shared_aggregation.physical_id = "shared-window-state".into();
-        model
-            .node_evidence
-            .aggregations
-            .insert(aggregations[0] as *const _, shared_aggregation.clone());
-        model
-            .node_evidence
-            .aggregations
-            .insert(aggregations[1] as *const _, shared_aggregation);
+        for aggregate in &aggregation_nodes {
+            model
+                .node_evidence
+                .insert_aggregation(aggregate, shared_aggregation.clone());
+        }
 
         let retained_children: Vec<_> = aggregation_nodes
             .iter()
-            .map(|aggregate| match &aggregate.expr {
-                SummaryExpr::SummaryAgg { child, .. } => Rc::clone(child),
+            .map(|aggregate| match &aggregate.operator {
+                Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) => Rc::clone(child),
                 _ => unreachable!(),
             })
             .collect();
@@ -2428,7 +2393,7 @@ mod tests {
         }
 
         let candidate = SummaryWindowFrameworkCandidate {
-            physical_plan_id: "mixed-framework-join".into(),
+            physical_plan_id: "mixed-framework-binary".into(),
             assignments: vec![
                 SummaryWindowFrameworkAssignment {
                     summary: Rc::clone(&aggregation_nodes[0]),
@@ -2544,7 +2509,10 @@ mod tests {
             asap_types::workload::AccuracyRequirement::Explicit(AccuracyTarget::Epsilon(1.0));
         let target = streaming_sum_query();
         let root = summary_with_operations(false, false, false);
-        let SummaryExpr::SummaryEstimate { summary_input, .. } = &root.expr else {
+        let Operator::ASAP(ASAPOp::FinalizeExactAccumulator {
+            child: summary_input,
+        }) = &root.operator
+        else {
             unreachable!();
         };
         let mut model = streaming_model();
@@ -2583,6 +2551,42 @@ mod tests {
         assert_eq!(plan.summary_total_cost, None);
     }
 
+    /// Bulk relational evidence cannot hide summary operators below an ordinary root.
+    #[test]
+    fn retained_subdag_evidence_cannot_hide_summary_work() {
+        let workload = streaming_workload();
+        let target = streaming_sum_query();
+        let root = add_shared_summary_result();
+        let mut model = streaming_model();
+        bind_aggregations(
+            &mut model,
+            &target,
+            &root,
+            streaming_inputs(),
+            streaming_cpu(),
+        );
+        model.node_evidence.insert_retained_query(
+            &root,
+            RetainedSubDAGEvidence {
+                physical_id: "false-retained-root".into(),
+                output: test_edge(),
+                preprocessing_cpu_ops_over_horizon: 0.0,
+                working_memory_bytes: 0,
+                output_buffer_bytes: 0,
+            },
+        );
+        let plan = plan_summary_maintenance_lifecycles(
+            root,
+            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
+            0,
+            Some(Horizon(5.0)),
+            SummaryMaintenanceLifecycleCapabilities::ALL,
+            &model,
+        )
+        .unwrap();
+        assert_eq!(plan.summary_total_cost, None);
+    }
+
     #[test]
     fn whole_dag_fails_closed_for_missing_retained_work_or_false_source_lineage() {
         let workload = streaming_workload();
@@ -2631,23 +2635,22 @@ mod tests {
     }
 
     #[test]
-    fn aggregate_recurses_into_child_operations_and_state_only_needs_no_readout() {
+    fn state_only_needs_no_evaluation_and_summary_merge_child_fails_closed() {
+        // A state-only root is costable without evaluation evidence; a
+        // SummaryAgg over a reserved SummaryMerge is rejected at planning.
         let workload = streaming_workload();
         let target = streaming_sum_query();
         let estimated = summary_with_operations(false, false, false);
-        let SummaryExpr::SummaryEstimate { summary_input, .. } = &estimated.expr else {
-            unreachable!();
-        };
-        let state_only = Rc::clone(summary_input);
-        let mut no_readout_cpu = streaming_cpu();
-        no_readout_cpu.readout_cpu_ops = None;
+        let state_only = evaluation_state(&estimated);
+        let mut no_evaluation_cpu = streaming_cpu();
+        no_evaluation_cpu.evaluation_cpu_ops = None;
         let mut state_model = streaming_model();
         bind_aggregations(
             &mut state_model,
             &target,
             &state_only,
             streaming_inputs(),
-            no_readout_cpu,
+            no_evaluation_cpu,
         );
         let state_plan = plan_summary_maintenance_lifecycles(
             state_only,
@@ -2660,27 +2663,24 @@ mod tests {
         .unwrap();
         assert!(state_plan.summary_total_cost.is_some());
 
-        let child_readout = summary_with_operations(true, false, false);
-        let SummaryExpr::SummaryEstimate {
-            summary_input: child,
-            ..
-        } = &child_readout.expr
-        else {
-            unreachable!();
-        };
-        let child = Rc::clone(child);
-        let nested = Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryAgg {
-                child,
-                family: FieldDataType::ExactAggregate(ExactKind::Count, ExactParams::Count),
-                input: asap_types::post_asap::SummaryUpdate::column(ColumnRef::Wildcard),
-                reduction: Reduction::by(vec![]),
-                grouping: GroupingStrategy::PerSubpopulationInstance,
-                filter: None,
-            },
-            schema: estimated.schema.clone(),
-            guarantee: None,
-        });
+        let nested = std::rc::Rc::new(
+            OperatorNode::with_schema(
+                asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
+                    child: evaluation_state(&summary_with_operations(true, false, false)),
+                    family: FieldDataType::ExactAggregate(ExactKind::Count, ExactParams::Count),
+                    input: SummaryUpdate {
+                        item: None,
+                        weight: asap_types::post_asap::SummaryInputExpr::Constant(1.0),
+                        weight_domain: Default::default(),
+                    },
+                    reduction: Reduction::by(vec![]),
+                    grouping: GroupingStrategy::PerSubpopulationInstance,
+                    filter: None,
+                }),
+                count_state_schema(),
+            )
+            .with_guarantee(None),
+        );
         let mut nested_cpu = streaming_cpu();
         nested_cpu.merge_cpu_ops = Some(1.0);
         let mut nested_model = streaming_model();
@@ -2691,23 +2691,12 @@ mod tests {
             streaming_inputs(),
             nested_cpu,
         );
-        nested_model
-            .node_evidence
-            .operations
-            .retain(|_, operation| {
-                operation.resource().cpu_ops != 1.0
-                    || operation.resource().working_memory_bytes == 0
-            });
-        let nested_plan = plan_summary_maintenance_lifecycles(
-            nested,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &nested_model,
-        )
-        .unwrap();
-        assert_eq!(nested_plan.summary_total_cost, None);
+        assert!(matches!(
+            streaming_planning_error(nested, &nested_model),
+            asap_types::post_asap::ExecutionDataStateError::UnimplementedOperator {
+                operator: "SummaryMerge"
+            }
+        ));
     }
 
     #[test]
@@ -2744,7 +2733,7 @@ mod tests {
             },
             SummaryOperationCpuEvidence {
                 insert_cpu_ops: Some(2.0),
-                readout_cpu_ops: Some(3.0),
+                evaluation_cpu_ops: Some(3.0),
                 ..SummaryOperationCpuEvidence::default()
             },
         )
@@ -2778,7 +2767,7 @@ mod tests {
                 delete_cpu_ops: Some(5.0),
                 delete_events_per_second: Some(4.0),
                 delete_routing_fanout: Some(2),
-                readout_cpu_ops: Some(7.0),
+                evaluation_cpu_ops: Some(7.0),
             },
         )
         .unwrap();
@@ -2808,7 +2797,7 @@ mod tests {
                 },
                 SummaryOperationCpuEvidence {
                     insert_cpu_ops: Some(1.0),
-                    readout_cpu_ops: Some(1.0),
+                    evaluation_cpu_ops: Some(1.0),
                     ..SummaryOperationCpuEvidence::default()
                 },
             ),
@@ -2835,7 +2824,7 @@ mod tests {
                 },
                 SummaryOperationCpuEvidence {
                     insert_cpu_ops: Some(1.0),
-                    readout_cpu_ops: Some(1.0),
+                    evaluation_cpu_ops: Some(1.0),
                     ..SummaryOperationCpuEvidence::default()
                 },
             ),
@@ -2866,7 +2855,7 @@ mod tests {
                 },
                 SummaryOperationCpuEvidence {
                     insert_cpu_ops: Some(1.0),
-                    readout_cpu_ops: Some(1.0),
+                    evaluation_cpu_ops: Some(1.0),
                     ..SummaryOperationCpuEvidence::default()
                 },
             ),
@@ -2901,7 +2890,7 @@ mod tests {
             },
             SummaryOperationCpuEvidence {
                 insert_cpu_ops: Some(1.0),
-                readout_cpu_ops: Some(1.0),
+                evaluation_cpu_ops: Some(1.0),
                 ..SummaryOperationCpuEvidence::default()
             },
         )
@@ -2937,7 +2926,7 @@ mod tests {
             },
             SummaryOperationCpuEvidence {
                 insert_cpu_ops: Some(1.0),
-                readout_cpu_ops: Some(1.0),
+                evaluation_cpu_ops: Some(1.0),
                 ..SummaryOperationCpuEvidence::default()
             },
         )
@@ -2981,7 +2970,7 @@ mod tests {
         };
         let cpu = SummaryOperationCpuEvidence {
             insert_cpu_ops: Some(1.0),
-            readout_cpu_ops: Some(1.0),
+            evaluation_cpu_ops: Some(1.0),
             ..SummaryOperationCpuEvidence::default()
         };
         assert_eq!(
@@ -3009,157 +2998,253 @@ mod tests {
         assert_eq!(estimate.peak_memory_bytes(), 64); // 4 persistent states + join memory.
     }
 
-    fn summary_with_operations(merge: bool, subtract: bool, delete: bool) -> Rc<SummaryNode> {
-        let state_type = FieldDataType::ExactAggregate(ExactKind::Count, ExactParams::Count);
-        let schema = Schema::lifted(vec![Field::new("count", state_type.clone(), false)], None);
-        let leaf = Rc::new(SummaryNode {
-            expr: SummaryExpr::KeepPreAsap(Rc::new(QueryExpr::Scan {
-                source: Source::TimeSeries {
-                    metric: "metrics".into(),
-                },
-                predicates: vec![],
-                schema: Schema::with_time_index(
-                    vec![
-                        Field::plain("ts", DataType::Timestamp, false),
-                        Field::plain("value", DataType::Float64, false),
-                    ],
-                    0,
-                    vec![],
-                ),
-            })),
-            schema: schema.clone(),
-            guarantee: None,
-        });
-        let agg = Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryAgg {
-                child: leaf,
-                family: state_type,
-                input: asap_types::post_asap::SummaryUpdate::column(ColumnRef::Wildcard),
-                reduction: Reduction::by(vec![]),
-                grouping: GroupingStrategy::PerSubpopulationInstance,
-                filter: None,
+    fn count_state_schema() -> Schema {
+        Schema::lifted(
+            vec![Field::new(
+                "count",
+                FieldDataType::ExactAggregate(ExactKind::Count, ExactParams::Count),
+                false,
+            )],
+            None,
+        )
+    }
+
+    fn count_evaluation_schema() -> Schema {
+        Schema::lifted(vec![Field::plain("count", DataType::Int64, false)], None)
+    }
+
+    /// The retained relational input of every test summary: a bare scan of
+    /// the `metrics` series.
+    fn metrics_scan() -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
+            source: Source::TimeSeries {
+                metric: "metrics".into(),
             },
-            schema: schema.clone(),
-            guarantee: None,
-        });
+            predicates: vec![],
+            schema: Schema::with_time_index(
+                vec![
+                    Field::plain("ts", DataType::Timestamp, false),
+                    Field::plain("value", DataType::Float64, false),
+                ],
+                0,
+                vec![],
+            ),
+        }))
+        .unwrap()
+    }
+
+    fn summary_with_operations(merge: bool, subtract: bool, delete: bool) -> Rc<OperatorNode> {
+        let state_type = FieldDataType::ExactAggregate(ExactKind::Count, ExactParams::Count);
+        let schema = count_state_schema();
+        let agg = std::rc::Rc::new(
+            OperatorNode::with_schema(
+                asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
+                    child: metrics_scan(),
+                    family: state_type,
+                    input: SummaryUpdate {
+                        item: None,
+                        weight: asap_types::post_asap::SummaryInputExpr::Constant(1.0),
+                        weight_domain: Default::default(),
+                    },
+                    reduction: Reduction::by(vec![]),
+                    grouping: GroupingStrategy::PerSubpopulationInstance,
+                    filter: None,
+                }),
+                schema.clone(),
+            )
+            .with_guarantee(None),
+        );
         let mut root = Rc::clone(&agg);
         if merge {
-            root = Rc::new(SummaryNode {
-                expr: SummaryExpr::SummaryMerge {
-                    timing: asap_types::post_asap::ExecutionTiming::IngestionTime,
-                    children: vec![Rc::clone(&agg), Rc::clone(&agg)],
-                },
-                schema: schema.clone(),
-                guarantee: None,
-            });
+            root = std::rc::Rc::new(
+                OperatorNode::with_schema(
+                    asap_types::ir::Operator::ASAP(ASAPOp::SummaryMerge {
+                        children: vec![Rc::clone(&agg), Rc::clone(&agg)],
+                    }),
+                    schema.clone(),
+                )
+                .with_guarantee(None),
+            );
         }
         if subtract {
-            root = Rc::new(SummaryNode {
-                expr: SummaryExpr::SummarySubtract {
-                    left: Rc::clone(&root),
-                    right: Rc::clone(&agg),
-                },
-                schema: schema.clone(),
-                guarantee: None,
-            });
+            root = std::rc::Rc::new(
+                OperatorNode::with_schema(
+                    asap_types::ir::Operator::ASAP(ASAPOp::SummarySubtract {
+                        left: Rc::clone(&root),
+                        right: Rc::clone(&agg),
+                    }),
+                    schema.clone(),
+                )
+                .with_guarantee(None),
+            );
         }
         if delete {
-            root = Rc::new(SummaryNode {
-                expr: SummaryExpr::SummaryDelete {
-                    summary_input: root,
-                    key: ColumnRef::Wildcard,
-                },
-                schema: schema.clone(),
-                guarantee: None,
-            });
+            root = std::rc::Rc::new(
+                OperatorNode::with_schema(
+                    asap_types::ir::Operator::ASAP(ASAPOp::SummaryDelete {
+                        summary_input: root,
+                        key: 0,
+                    }),
+                    schema.clone(),
+                )
+                .with_guarantee(None),
+            );
         }
-        Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryEstimate {
-                summary_input: root,
-                query: asap_types::post_asap::SketchStatistic::PointCount {
-                    key: ColumnRef::Wildcard,
-                    value: None,
-                },
-            },
-            schema,
-            guarantee: Some(ResultGuarantee::exact("exact count readout")),
-        })
+        std::rc::Rc::new(
+            OperatorNode::with_schema(
+                asap_types::ir::Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child: root }),
+                count_evaluation_schema(),
+            )
+            .with_guarantee(Some(ResultGuarantee::exact("exact count evaluation"))),
+        )
     }
 
-    fn summary_join() -> Rc<SummaryNode> {
+    fn summary_join() -> Rc<OperatorNode> {
         let left = summary_with_operations(false, false, false);
         let right = summary_with_operations(false, false, false);
-        let SummaryExpr::SummaryEstimate {
-            summary_input: left,
-            ..
-        } = &left.expr
+        let Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child: left }) = &left.operator
         else {
             unreachable!()
         };
-        let SummaryExpr::SummaryEstimate {
-            summary_input: right,
-            ..
-        } = &right.expr
+        let Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child: right }) = &right.operator
         else {
             unreachable!()
         };
-        let schema = left.schema.clone();
-        let join = Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryJoin {
-                outer: Rc::clone(left),
-                inner: Rc::clone(right),
-                key: ColumnRef::Wildcard,
-                family: FieldDataType::ExactAggregate(ExactKind::Count, ExactParams::Count),
-            },
-            schema: schema.clone(),
-            guarantee: None,
-        });
-        Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryEstimate {
-                summary_input: join,
-                query: asap_types::post_asap::SketchStatistic::PointCount {
-                    key: ColumnRef::Wildcard,
-                    value: None,
-                },
-            },
-            schema,
-            guarantee: None,
-        })
+        let join = std::rc::Rc::new(
+            OperatorNode::with_schema(
+                asap_types::ir::Operator::ASAP(ASAPOp::SummaryJoin {
+                    outer: Rc::clone(left),
+                    inner: Rc::clone(right),
+                    key: 0,
+                    family: FieldDataType::ExactAggregate(ExactKind::Count, ExactParams::Count),
+                }),
+                left.schema.clone(),
+            )
+            .with_guarantee(None),
+        );
+        std::rc::Rc::new(
+            OperatorNode::with_schema(
+                asap_types::ir::Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child: join }),
+                count_evaluation_schema(),
+            )
+            .with_guarantee(None),
+        )
     }
 
-    fn summary_binary() -> Rc<SummaryNode> {
+    fn add_shared_summary_result() -> Rc<OperatorNode> {
         let operand = summary_with_operations(false, false, false);
-        Rc::new(SummaryNode {
-            expr: SummaryExpr::BinaryOp {
-                timing: asap_types::post_asap::ExecutionTiming::QueryTime,
+        Rc::new(
+            OperatorNode::new(Operator::NonASAP(NonASAPOp::BinaryOp {
+                operator: BinaryOperator {
+                    checked_relative_division: false,
+                    checked_finite_division: false,
+                    kind: BinaryOpKind::Arithmetic(ArithmeticOpKind::Add),
+                    vector_match: None,
+                },
+                return_bool: false,
                 lhs: Rc::clone(&operand),
                 rhs: operand,
-                operator: asap_types::post_asap::BinaryOperator {
+            }))
+            .unwrap()
+            .with_guarantee(Some(ResultGuarantee::exact("test binary"))),
+        )
+    }
+
+    /// Two independent summary states, each read out, combined by an ordinary
+    /// `BinaryOp`: the non-reserved replacement for a `SummaryJoin` fixture.
+    #[test]
+    fn independent_summary_results_form_a_valid_dag() {
+        add_independent_summary_results()
+            .validate_structure()
+            .unwrap();
+    }
+
+    fn add_independent_summary_results() -> Rc<OperatorNode> {
+        Rc::new(
+            OperatorNode::new(Operator::NonASAP(NonASAPOp::BinaryOp {
+                operator: BinaryOperator {
                     checked_relative_division: false,
                     checked_finite_division: false,
-                    kind: asap_types::pre_asap::BinaryOpKind::Arithmetic(
-                        asap_types::pre_asap::ArithmeticOpKind::Add,
-                    ),
+                    kind: BinaryOpKind::Arithmetic(ArithmeticOpKind::Add),
                     vector_match: None,
                 },
-            },
-            schema: Schema::lifted(
-                vec![Field::new(
-                    "value",
-                    FieldDataType::Plain(DataType::Float64),
-                    false,
-                )],
-                None,
-            ),
-            guarantee: Some(ResultGuarantee::exact("test binary")),
-        })
+                return_bool: false,
+                lhs: summary_with_operations(false, false, false),
+                rhs: summary_with_operations(false, false, false),
+            }))
+            .unwrap()
+            .with_guarantee(Some(ResultGuarantee::exact("test binary"))),
+        )
+    }
+
+    /// The `(lhs, rhs)` evaluations of [`add_independent_summary_results`].
+    fn binary_operands(root: &OperatorNode) -> (Rc<OperatorNode>, Rc<OperatorNode>) {
+        let Operator::NonASAP(NonASAPOp::BinaryOp { lhs, rhs, .. }) = &root.operator else {
+            unreachable!();
+        };
+        (Rc::clone(lhs), Rc::clone(rhs))
+    }
+
+    /// The `SummaryAgg` under one `SummaryEstimate` evaluation.
+    fn evaluation_state(evaluation: &OperatorNode) -> Rc<OperatorNode> {
+        let Operator::ASAP(ASAPOp::FinalizeExactAccumulator {
+            child: summary_input,
+        }) = &evaluation.operator
+        else {
+            unreachable!();
+        };
+        Rc::clone(summary_input)
+    }
+
+    /// The DAG-validation error that streaming lifecycle planning of `root`
+    /// fails closed with.
+    fn streaming_planning_error(
+        root: Rc<OperatorNode>,
+        model: &SummaryMaintenanceCostModel,
+    ) -> asap_types::post_asap::ExecutionDataStateError {
+        let workload = streaming_workload();
+        match plan_summary_maintenance_lifecycles(
+            root,
+            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
+            0,
+            Some(Horizon(5.0)),
+            SummaryMaintenanceLifecycleCapabilities::ALL,
+            model,
+        ) {
+            Err(
+                crate::summary_maintenance_lifecycle::SummaryMaintenanceLifecyclePlanError::InvalidPostAsapDAG(
+                    error,
+                ),
+            ) => error,
+            Err(other) => panic!("unexpected planning error: {other}"),
+            Ok(_) => panic!("planning must fail closed"),
+        }
+    }
+
+    fn test_resource(
+        physical_id: &str,
+        inputs: Vec<EdgeStatistics>,
+        cpu_ops: f64,
+        working_memory_bytes: u64,
+        output_buffer_bytes: u64,
+    ) -> SummaryOperatorResourceEvidence {
+        SummaryOperatorResourceEvidence {
+            physical_id: physical_id.into(),
+            inputs,
+            output: test_edge(),
+            cpu_ops,
+            working_memory_bytes,
+            output_buffer_bytes,
+            executions_per_evaluation: 1,
+            io_bytes_per_execution: Some(0),
+        }
     }
 
     #[test]
     fn exact_binary_is_costable_with_explicit_physical_evidence() {
         let workload = streaming_workload();
         let target = streaming_sum_query();
-        let root = summary_binary();
+        let root = add_shared_summary_result();
         let mut model = streaming_model();
         bind_aggregations(
             &mut model,
@@ -3186,29 +3271,16 @@ mod tests {
         assert!(plan.summary_total_cost.is_some());
     }
 
-    fn streaming_sum_query() -> Rc<QueryExpr> {
-        let scan = Rc::new(QueryExpr::Scan {
-            source: Source::TimeSeries {
-                metric: "metrics".into(),
-            },
-            predicates: vec![],
-            schema: Schema::with_time_index(
-                vec![
-                    Field::plain("ts", DataType::Timestamp, false),
-                    Field::plain("value", DataType::Float64, false),
-                ],
-                0,
-                vec![],
-            ),
-        });
-        Rc::new(QueryExpr::Aggregate {
+    fn streaming_sum_query() -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
             reduction: Reduction::by(vec![]),
             measures: vec![AggIntent::Sum { col: None }],
             output_names: vec![],
             filters: vec![],
             having: None,
-            child: scan,
-        })
+            child: metrics_scan(),
+        }))
+        .unwrap()
     }
 
     fn streaming_workload() -> QueryWorkload {
@@ -3303,61 +3375,43 @@ mod tests {
         }
     }
 
+    /// A retained relational sub-DAG: a non-ASAP node with no summary below
+    /// it, costed as one unit through retained-query evidence.
+    fn is_retained(node: &OperatorNode) -> bool {
+        !node.contains_asap()
+    }
+
     fn bind_comparison(
         model: &mut SummaryMaintenanceCostModel,
-        target: &Rc<QueryExpr>,
-        root: &Rc<SummaryNode>,
+        target: &Rc<OperatorNode>,
+        root: &Rc<OperatorNode>,
     ) {
         model
             .bind_candidate_comparison(target, root, streaming_scope(), streaming_raw())
             .unwrap();
         fn retained(
             model: &mut SummaryMaintenanceCostModel,
-            node: &Rc<SummaryNode>,
-            seen: &mut HashSet<*const SummaryNode>,
+            node: &Rc<OperatorNode>,
+            seen: &mut HashSet<*const OperatorNode>,
         ) {
             if !seen.insert(Rc::as_ptr(node)) {
                 return;
             }
-            match &node.expr {
-                SummaryExpr::KeepPreAsap(_) => {
-                    model.node_evidence.insert_retained_query(
-                        node,
-                        RetainedSubDAGEvidence {
-                            physical_id: format!("retained-{node:p}"),
-                            output: test_edge(),
-                            preprocessing_cpu_ops_over_horizon: 1.0,
-                            working_memory_bytes: 8,
-                            output_buffer_bytes: 0,
-                        },
-                    );
-                }
-                SummaryExpr::SummaryAgg { child, .. }
-                | SummaryExpr::ValueOperation { child, .. } => retained(model, child, seen),
-                SummaryExpr::SummaryMerge { children, .. } => {
-                    for child in children {
-                        retained(model, child, seen);
-                    }
-                }
-                SummaryExpr::SummarySubtract { left, right }
-                | SummaryExpr::RelationalJoin { left, right, .. }
-                | SummaryExpr::BinaryOp {
-                    lhs: left,
-                    rhs: right,
-                    ..
-                }
-                | SummaryExpr::SummaryJoin {
-                    outer: left,
-                    inner: right,
-                    ..
-                } => {
-                    retained(model, left, seen);
-                    retained(model, right, seen);
-                }
-                SummaryExpr::SummaryDelete { summary_input, .. }
-                | SummaryExpr::SummaryEstimate { summary_input, .. } => {
-                    retained(model, summary_input, seen)
-                }
+            if is_retained(node) {
+                model.node_evidence.insert_retained_query(
+                    node,
+                    RetainedSubDAGEvidence {
+                        physical_id: format!("retained-{node:p}"),
+                        output: test_edge(),
+                        preprocessing_cpu_ops_over_horizon: 1.0,
+                        working_memory_bytes: 8,
+                        output_buffer_bytes: 0,
+                    },
+                );
+                return;
+            }
+            for child in node.children() {
+                retained(model, child, seen);
             }
         }
         retained(model, root, &mut HashSet::new());
@@ -3384,24 +3438,23 @@ mod tests {
     fn streaming_cpu() -> SummaryOperationCpuEvidence {
         SummaryOperationCpuEvidence {
             insert_cpu_ops: Some(2.0),
-            readout_cpu_ops: Some(3.0),
+            evaluation_cpu_ops: Some(3.0),
             ..SummaryOperationCpuEvidence::default()
         }
     }
 
     fn bind_aggregations(
         model: &mut SummaryMaintenanceCostModel,
-        target: &Rc<QueryExpr>,
-        root: &Rc<SummaryNode>,
+        target: &Rc<OperatorNode>,
+        root: &Rc<OperatorNode>,
         inputs: SummaryMaintenanceInputs,
         cpu: SummaryOperationCpuEvidence,
     ) {
         bind_comparison(model, target, root);
         for node in evidence_nodes(root).0 {
             let source_root = matches!(
-                &node.expr,
-                SummaryExpr::SummaryAgg { child, .. }
-                    if matches!(child.expr, SummaryExpr::KeepPreAsap(_))
+                &node.operator,
+                Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) if is_retained(child)
             );
             let mut node_inputs = inputs;
             if !source_root {
@@ -3426,147 +3479,131 @@ mod tests {
                 },
             );
         }
+        fn resource(
+            physical_id: String,
+            inputs: Vec<EdgeStatistics>,
+            cpu_ops: f64,
+            working_memory_bytes: u64,
+        ) -> SummaryOperatorResourceEvidence {
+            SummaryOperatorResourceEvidence {
+                physical_id,
+                inputs,
+                output: test_edge(),
+                cpu_ops,
+                working_memory_bytes,
+                output_buffer_bytes: 0,
+                executions_per_evaluation: 1,
+                io_bytes_per_execution: Some(0),
+            }
+        }
         fn bind_ops(
             model: &mut SummaryMaintenanceCostModel,
-            node: &SummaryNode,
-            seen: &mut HashSet<*const SummaryNode>,
+            node: &OperatorNode,
+            seen: &mut HashSet<*const OperatorNode>,
             inputs: SummaryMaintenanceInputs,
             cpu: SummaryOperationCpuEvidence,
         ) {
             if !seen.insert(node as *const _) {
                 return;
             }
-            let operation = match &node.expr {
-                SummaryExpr::BinaryOp { .. } => cpu.readout_cpu_ops.map(|cpu_ops| {
-                    SummaryOperatorEvidence::Binary(SummaryOperatorResourceEvidence {
-                        physical_id: format!("binary-{node:p}"),
-                        inputs: vec![test_edge(), test_edge()],
-                        output: test_edge(),
-                        cpu_ops,
-                        working_memory_bytes: 0,
-                        output_buffer_bytes: 0,
-                        executions_per_evaluation: 1,
-                        io_bytes_per_execution: Some(0),
-                    })
-                }),
-                SummaryExpr::ValueOperation { .. } => cpu.readout_cpu_ops.map(|cpu_ops| {
-                    SummaryOperatorEvidence::ValueOperation(SummaryOperatorResourceEvidence {
-                        physical_id: format!("value-operation-{node:p}"),
-                        inputs: vec![test_edge()],
-                        output: test_edge(),
-                        cpu_ops,
-                        working_memory_bytes: 0,
-                        output_buffer_bytes: 0,
-                        executions_per_evaluation: 1,
-                        io_bytes_per_execution: Some(0),
+            if is_retained(node) {
+                return;
+            }
+            let operation = match &node.operator {
+                Operator::NonASAP(NonASAPOp::BinaryOp { .. }) => {
+                    cpu.evaluation_cpu_ops.map(|cpu_ops| {
+                        SummaryOperatorEvidence::Binary(resource(
+                            format!("binary-{node:p}"),
+                            vec![test_edge(), test_edge()],
+                            cpu_ops,
+                            0,
+                        ))
                     })
-                }),
-                SummaryExpr::SummaryMerge { .. } => cpu.merge_cpu_ops.map(|cpu_ops| {
-                    SummaryOperatorEvidence::Merge(SummaryOperatorResourceEvidence {
-                        physical_id: format!("merge-{node:p}"),
-                        inputs: match &node.expr {
-                            SummaryExpr::SummaryMerge { children, .. } => {
-                                vec![test_edge(); children.len()]
-                            }
-                            _ => unreachable!(),
-                        },
-                        output: test_edge(),
+                }
+                Operator::NonASAP(NonASAPOp::Join { .. }) => None,
+                Operator::NonASAP(_)
+                | Operator::ASAP(
+                    ASAPOp::FinalizeExactAccumulator { .. }
+                    | ASAPOp::MaintainPopulation { .. }
+                    | ASAPOp::EvaluatePopulation { .. },
+                ) => cpu.evaluation_cpu_ops.map(|cpu_ops| {
+                    SummaryOperatorEvidence::ValueOperation(resource(
+                        format!("value-operation-{node:p}"),
+                        vec![test_edge()],
                         cpu_ops,
-                        working_memory_bytes: inputs.state_bytes_per_summary,
-                        output_buffer_bytes: 0,
-                        executions_per_evaluation: 1,
-                        io_bytes_per_execution: Some(0),
-                    })
+                        0,
+                    ))
                 }),
-                SummaryExpr::SummarySubtract { .. } => cpu.subtract_cpu_ops.map(|cpu_ops| {
-                    SummaryOperatorEvidence::Subtract(SummaryOperatorResourceEvidence {
-                        physical_id: format!("subtract-{node:p}"),
-                        inputs: vec![test_edge(), test_edge()],
-                        output: test_edge(),
-                        cpu_ops,
-                        working_memory_bytes: inputs.state_bytes_per_summary,
-                        output_buffer_bytes: 0,
-                        executions_per_evaluation: 1,
-                        io_bytes_per_execution: Some(0),
+                Operator::ASAP(ASAPOp::SummaryMerge { children }) => {
+                    cpu.merge_cpu_ops.map(|cpu_ops| {
+                        SummaryOperatorEvidence::Merge(resource(
+                            format!("merge-{node:p}"),
+                            vec![test_edge(); children.len()],
+                            cpu_ops,
+                            inputs.state_bytes_per_summary,
+                        ))
                     })
-                }),
-                SummaryExpr::SummaryDelete { .. } => cpu.delete_cpu_ops.and_then(|cpu_ops| {
-                    Some(SummaryOperatorEvidence::Delete {
-                        resource: SummaryOperatorResourceEvidence {
-                            physical_id: format!("delete-{node:p}"),
-                            inputs: vec![test_edge()],
-                            output: test_edge(),
+                }
+                Operator::ASAP(ASAPOp::SummarySubtract { .. }) => {
+                    cpu.subtract_cpu_ops.map(|cpu_ops| {
+                        SummaryOperatorEvidence::Subtract(resource(
+                            format!("subtract-{node:p}"),
+                            vec![test_edge(), test_edge()],
                             cpu_ops,
-                            working_memory_bytes: 0,
-                            output_buffer_bytes: 0,
-                            executions_per_evaluation: 1,
-                            io_bytes_per_execution: Some(0),
-                        },
-                        events_per_second: cpu.delete_events_per_second?,
-                        routing_fanout: cpu.delete_routing_fanout?,
+                            inputs.state_bytes_per_summary,
+                        ))
                     })
-                }),
-                SummaryExpr::SummaryEstimate { .. } => cpu.readout_cpu_ops.map(|cpu_ops| {
-                    SummaryOperatorEvidence::Readout(SummaryOperatorResourceEvidence {
-                        physical_id: format!("readout-{node:p}"),
-                        inputs: vec![test_edge()],
-                        output: test_edge(),
-                        cpu_ops,
-                        working_memory_bytes: 0,
-                        output_buffer_bytes: 0,
-                        executions_per_evaluation: 1,
-                        io_bytes_per_execution: Some(0),
+                }
+                Operator::ASAP(ASAPOp::SummaryDelete { .. }) => {
+                    cpu.delete_cpu_ops.and_then(|cpu_ops| {
+                        Some(SummaryOperatorEvidence::Delete {
+                            resource: resource(
+                                format!("delete-{node:p}"),
+                                vec![test_edge()],
+                                cpu_ops,
+                                0,
+                            ),
+                            events_per_second: cpu.delete_events_per_second?,
+                            routing_fanout: cpu.delete_routing_fanout?,
+                        })
                     })
-                }),
-                _ => None,
+                }
+                Operator::ASAP(ASAPOp::SummaryEstimate { .. }) => {
+                    cpu.evaluation_cpu_ops.map(|cpu_ops| {
+                        SummaryOperatorEvidence::Evaluation(resource(
+                            format!("evaluation-{node:p}"),
+                            vec![test_edge()],
+                            cpu_ops,
+                            0,
+                        ))
+                    })
+                }
+                Operator::ASAP(
+                    ASAPOp::SummaryAgg { .. }
+                    | ASAPOp::SummaryJoin { .. }
+                    | ASAPOp::Extension { .. },
+                ) => None,
             };
             if let Some(operation) = operation {
                 model
                     .node_evidence
                     .operations
                     .insert(node as *const _, operation);
-                if let SummaryExpr::SummaryDelete { summary_input, .. } = &node.expr {
+                if let Operator::ASAP(ASAPOp::SummaryDelete { summary_input, .. }) = &node.operator
+                {
                     fn owning_aggs(
-                        node: &SummaryNode,
-                        seen: &mut HashSet<*const SummaryNode>,
-                        owners: &mut Vec<*const SummaryNode>,
+                        node: &OperatorNode,
+                        seen: &mut HashSet<*const OperatorNode>,
+                        owners: &mut Vec<*const OperatorNode>,
                     ) {
                         if !seen.insert(node as *const _) {
                             return;
                         }
-                        match &node.expr {
-                            SummaryExpr::SummaryAgg { child, .. } => {
-                                owners.push(node as *const _);
-                                owning_aggs(child, seen, owners);
-                            }
-                            SummaryExpr::ValueOperation { child, .. } => {
-                                owning_aggs(child, seen, owners)
-                            }
-                            SummaryExpr::SummaryMerge { children, .. } => {
-                                for child in children {
-                                    owning_aggs(child, seen, owners);
-                                }
-                            }
-                            SummaryExpr::SummarySubtract { left, right }
-                            | SummaryExpr::RelationalJoin { left, right, .. }
-                            | SummaryExpr::BinaryOp {
-                                lhs: left,
-                                rhs: right,
-                                ..
-                            }
-                            | SummaryExpr::SummaryJoin {
-                                outer: left,
-                                inner: right,
-                                ..
-                            } => {
-                                owning_aggs(left, seen, owners);
-                                owning_aggs(right, seen, owners);
-                            }
-                            SummaryExpr::SummaryDelete { summary_input, .. }
-                            | SummaryExpr::SummaryEstimate { summary_input, .. } => {
-                                owning_aggs(summary_input, seen, owners);
-                            }
-                            SummaryExpr::KeepPreAsap(_) => {}
+                        if matches!(node.operator, Operator::ASAP(ASAPOp::SummaryAgg { .. })) {
+                            owners.push(node as *const _);
+                        }
+                        for child in node.children() {
+                            owning_aggs(child, seen, owners);
                         }
                     }
                     let mut owners = Vec::new();
@@ -3581,36 +3618,8 @@ mod tests {
                     }
                 }
             }
-            match &node.expr {
-                SummaryExpr::SummaryAgg { child, .. }
-                | SummaryExpr::ValueOperation { child, .. } => {
-                    bind_ops(model, child, seen, inputs, cpu)
-                }
-                SummaryExpr::SummaryMerge { children, .. } => {
-                    for child in children {
-                        bind_ops(model, child, seen, inputs, cpu);
-                    }
-                }
-                SummaryExpr::SummarySubtract { left, right }
-                | SummaryExpr::RelationalJoin { left, right, .. }
-                | SummaryExpr::BinaryOp {
-                    lhs: left,
-                    rhs: right,
-                    ..
-                }
-                | SummaryExpr::SummaryJoin {
-                    outer: left,
-                    inner: right,
-                    ..
-                } => {
-                    bind_ops(model, left, seen, inputs, cpu);
-                    bind_ops(model, right, seen, inputs, cpu);
-                }
-                SummaryExpr::SummaryDelete { summary_input, .. }
-                | SummaryExpr::SummaryEstimate { summary_input, .. } => {
-                    bind_ops(model, summary_input, seen, inputs, cpu)
-                }
-                SummaryExpr::KeepPreAsap(_) => {}
+            for child in node.children() {
+                bind_ops(model, child, seen, inputs, cpu);
             }
         }
         bind_ops(model, root, &mut HashSet::new(), inputs, cpu);
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_cost/window.rs b/crates/asap-aware-mapping/src/summary_maintenance_cost/window.rs
index c3c12c20b..fb80d5ee0 100644
--- a/crates/asap-aware-mapping/src/summary_maintenance_cost/window.rs
+++ b/crates/asap-aware-mapping/src/summary_maintenance_cost/window.rs
@@ -3,7 +3,7 @@ use super::*;
 /// One per-state window choice within a complete Planner candidate.
 #[derive(Debug, Clone)]
 pub struct SummaryWindowFrameworkAssignment {
-    pub summary: Rc<SummaryNode>,
+    pub summary: Rc<OperatorNode>,
     /// `None` explicitly means that this state is not window-organized.
     pub framework: Option<SummaryWindowFramework>,
 }
@@ -29,46 +29,20 @@ pub struct SummaryWindowFrameworkCandidate {
     pub node_evidence: SummaryNodeEvidence,
 }
 
-pub(super) fn summary_aggregation_identities(root: &SummaryNode) -> HashSet<*const SummaryNode> {
+pub(super) fn summary_aggregation_identities(root: &OperatorNode) -> HashSet<*const OperatorNode> {
     fn visit(
-        node: &SummaryNode,
-        seen: &mut HashSet<*const SummaryNode>,
-        out: &mut HashSet<*const SummaryNode>,
+        node: &OperatorNode,
+        seen: &mut HashSet<*const OperatorNode>,
+        out: &mut HashSet<*const OperatorNode>,
     ) {
         if !seen.insert(node as *const _) {
             return;
         }
-        match &node.expr {
-            SummaryExpr::KeepPreAsap(_) => {}
-            SummaryExpr::SummaryAgg { child, .. } => {
-                out.insert(node as *const _);
-                visit(child, seen, out);
-            }
-            SummaryExpr::ValueOperation { child, .. } => visit(child, seen, out),
-            SummaryExpr::SummaryMerge { children, .. } => {
-                for child in children {
-                    visit(child, seen, out);
-                }
-            }
-            SummaryExpr::SummarySubtract { left, right }
-            | SummaryExpr::RelationalJoin { left, right, .. }
-            | SummaryExpr::BinaryOp {
-                lhs: left,
-                rhs: right,
-                ..
-            }
-            | SummaryExpr::SummaryJoin {
-                outer: left,
-                inner: right,
-                ..
-            } => {
-                visit(left, seen, out);
-                visit(right, seen, out);
-            }
-            SummaryExpr::SummaryDelete { summary_input, .. }
-            | SummaryExpr::SummaryEstimate { summary_input, .. } => {
-                visit(summary_input, seen, out);
-            }
+        if matches!(node.operator, Operator::ASAP(ASAPOp::SummaryAgg { .. })) {
+            out.insert(node as *const _);
+        }
+        for child in node.children() {
+            visit(child, seen, out);
         }
     }
 
@@ -146,11 +120,11 @@ impl SummaryWindowAccuracyEvidence {
                 eh_summaries.len() == 1
                     && eh_summaries.iter().all(|assignment| {
                         matches!(
-                            &assignment.summary.expr,
-                            SummaryExpr::SummaryAgg {
+                            &assignment.summary.operator,
+                            Operator::ASAP(ASAPOp::SummaryAgg {
                                 family: FieldDataType::Sketch(kind, _),
                                 ..
-                            } if kind.algorithm() == &SketchAlgorithm::Kll
+                            }) if kind.algorithm() == &SketchAlgorithm::Kll
                         )
                     })
             }
@@ -160,14 +134,14 @@ impl SummaryWindowAccuracyEvidence {
                 eh_summaries.len() == 1
                     && eh_summaries.iter().all(|assignment| {
                         matches!(
-                            &assignment.summary.expr,
-                            SummaryExpr::SummaryAgg {
+                            &assignment.summary.operator,
+                            Operator::ASAP(ASAPOp::SummaryAgg {
                                 family: FieldDataType::ExactAggregate(
                                     ExactKind::Count | ExactKind::Sum,
                                     _
                                 ),
                                 ..
-                            }
+                            })
                         )
                     })
             }
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_dag_export.rs b/crates/asap-aware-mapping/src/summary_maintenance_dag_export.rs
index 8e63a4ce1..eae562c59 100644
--- a/crates/asap-aware-mapping/src/summary_maintenance_dag_export.rs
+++ b/crates/asap-aware-mapping/src/summary_maintenance_dag_export.rs
@@ -8,12 +8,14 @@
 use std::collections::HashMap;
 use std::rc::Rc;
 
+use asap_types::ir::OperatorNode;
 use serde::Serialize;
 
 use asap_types::dag_export::{self, SummaryDAG};
+use asap_types::ir::export::PhysicalASAPNodeId;
 use asap_types::post_asap::{
-    PostAsapNodeId, ResultGuarantee, SummaryExpr, SummaryMaintenanceLifecycle,
-    SummaryMaintenanceLifecycleGuarantee, SummaryNode, SummaryWindowFramework,
+    ResultGuarantee, SummaryMaintenanceLifecycle, SummaryMaintenanceLifecycleGuarantee,
+    SummaryWindowFramework,
 };
 
 use crate::summary_maintenance_lifecycle::{
@@ -42,7 +44,7 @@ pub struct SummaryMaintenanceDAGExport {
 
 #[derive(Debug, Clone, Serialize)]
 pub struct SummaryMaintenanceDeploymentExport {
-    pub post_asap_node_id: PostAsapNodeId,
+    pub post_asap_node_id: PhysicalASAPNodeId,
     #[serde(skip_serializing_if = "Option::is_none")]
     pub selected_window_framework: Option<SummaryWindowFramework>,
     #[serde(skip_serializing_if = "Option::is_none")]
@@ -93,13 +95,7 @@ pub fn export_summary_maintenance_plan(
         .zip(&deployments)
         .map(|(deployment, export)| (Rc::as_ptr(&deployment.summary), export))
         .collect();
-    let mut next_node_id = 0;
-    annotate_lifecycle_deployments(
-        &plan.root,
-        &mut dag,
-        &deployment_by_summary,
-        &mut next_node_id,
-    );
+    annotate_lifecycle_deployments(&mut dag, &deployment_by_summary);
 
     SummaryMaintenanceDAGExport {
         dag,
@@ -116,47 +112,21 @@ pub fn export_summary_maintenance_plan(
     }
 }
 
-/// Walk in the same post-order as `dag_export::export_summary` and attach a
-/// deployment directly to every flattened occurrence of its state node.
-/// This makes the decision visible to DAG consumers without asking them to
-/// reconstruct pointer identity from DAG position.
+/// Attach a deployment directly to the exported node of its `SummaryAgg`,
+/// matched by the `Rc` identity every exported node carries. This makes the
+/// decision visible to dag consumers without asking them to reconstruct
+/// pointer identity from dag position.
 fn annotate_lifecycle_deployments(
-    node: &SummaryNode,
     dag: &mut SummaryDAG,
-    deployments: &HashMap<*const SummaryNode, &SummaryMaintenanceDeploymentExport>,
-    next_node_id: &mut usize,
+    deployments: &HashMap<*const OperatorNode, &SummaryMaintenanceDeploymentExport>,
 ) {
-    if !matches!(node.expr, SummaryExpr::KeepPreAsap(_)) {
-        for child in summary_children(&node.expr) {
-            annotate_lifecycle_deployments(child, dag, deployments, next_node_id);
+    for dag_node in &mut dag.nodes {
+        let Some(source) = &dag_node.source_node else {
+            continue;
+        };
+        if let Some(deployment) = deployments.get(&Rc::as_ptr(source)) {
+            dag_node.detail["summary_maintenance"] =
+                serde_json::to_value(deployment).expect("lifecycle export is serializable");
         }
     }
-    let dag_node = &mut dag.nodes[*next_node_id];
-    if let Some(deployment) = deployments.get(&(node as *const SummaryNode)) {
-        dag_node.detail["summary_maintenance"] =
-            serde_json::to_value(deployment).expect("lifecycle export is serializable");
-    }
-    *next_node_id += 1;
-}
-
-fn summary_children(expr: &SummaryExpr) -> Vec<&Rc<SummaryNode>> {
-    match expr {
-        SummaryExpr::KeepPreAsap(_) => vec![],
-        SummaryExpr::BinaryOp { lhs, rhs, .. } => vec![lhs, rhs],
-        SummaryExpr::SummaryAgg { child, .. } => vec![child],
-        SummaryExpr::ValueOperation { child, .. } => vec![child],
-        SummaryExpr::SummaryJoin { outer, inner, .. }
-        | SummaryExpr::RelationalJoin {
-            left: outer,
-            right: inner,
-            ..
-        }
-        | SummaryExpr::SummarySubtract {
-            left: outer,
-            right: inner,
-        } => vec![outer, inner],
-        SummaryExpr::SummaryDelete { summary_input, .. }
-        | SummaryExpr::SummaryEstimate { summary_input, .. } => vec![summary_input],
-        SummaryExpr::SummaryMerge { children, .. } => children.iter().collect(),
-    }
 }
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_lifecycle.rs b/crates/asap-aware-mapping/src/summary_maintenance_lifecycle.rs
index cf41efeff..d271139bb 100644
--- a/crates/asap-aware-mapping/src/summary_maintenance_lifecycle.rs
+++ b/crates/asap-aware-mapping/src/summary_maintenance_lifecycle.rs
@@ -17,17 +17,21 @@
 //! incrementally. Unknown evidence stays unknown and therefore cannot make a
 //! long-lived alternative win.
 
+use asap_types::ir::cse::share_common_sub_dags;
 use std::collections::{HashMap, HashSet};
 use std::rc::Rc;
 
+use asap_types::ir::export::{
+    compile_physical_asap_dag_with_node_ids, PhysicalASAPDAG, PhysicalASAPDAGValidationError,
+    PhysicalASAPNodeId,
+};
+use asap_types::ir::timing::{apply_lifecycle_timings, LifecycleAssignment, TimingMemo};
+use asap_types::ir::{ASAPOp, Operator, OperatorNode};
 use asap_types::post_asap::{
-    compile_post_asap_dag_with_node_ids, share_common_summary_sub_dags, EvaluationSchedule,
-    ExecutionDataStateError, ExecutionTiming, OutputRepresentation, PostAsapDAG,
-    PostAsapDAGValidationError, PostAsapNodeId, ResultGuarantee, SummaryExpr,
-    SummaryMaintenanceLifecycle, SummaryMaintenanceLifecycleGuarantee, SummaryMaintenanceMode,
-    SummaryNode, SummaryWindowFramework, ValueOperation,
+    EvaluationSchedule, ExecutionDataStateError, ExecutionTiming, OutputRepresentation,
+    ResultGuarantee, SummaryMaintenanceLifecycle, SummaryMaintenanceLifecycleGuarantee,
+    SummaryMaintenanceMode, SummaryWindowFramework,
 };
-use asap_types::pre_asap::QueryExpr;
 use asap_types::types::AccuracyTarget;
 use asap_types::workload::{
     DataArrival, DataWorkload, Predictability, QueryRecurrence, QueryWorkload, RepeatedDemand,
@@ -44,7 +48,7 @@ use crate::recurrence::{
 };
 use crate::replacement::{
     CandidateCostOverrides, CandidateLogicalASAPDAGs, GlobalSelection, RealizationError,
-    Replacement,
+    Replacement, ReplacementProvenance,
 };
 
 /// Summary-maintenance lifecycle shapes supported by the target runtime.
@@ -167,11 +171,9 @@ pub struct SummaryMaintenanceDeployment {
     /// Identity of this summary in the exported post-ASAP semantic DAG.
     /// It is scoped to one plan version and is not a summary definition or
     /// summary instance identity.
-    pub post_asap_node_id: PostAsapNodeId,
-    /// The unique materialized `SummaryAgg`, or maintained population
-    /// (`MaintainPopulation`) not consumed by a `SummaryAgg`, represented by
-    /// this deployment. Cost-model lifecycle hooks receive this node.
-    pub summary: Rc<SummaryNode>,
+    pub post_asap_node_id: PhysicalASAPNodeId,
+    /// The unique materialized `SummaryAgg` represented by this deployment.
+    pub summary: Rc<OperatorNode>,
     /// Lifecycle, evaluation, and representation commitment selected for this
     /// state, or `None` when no alternative is selectable.
     pub summary_maintenance_lifecycle_guarantee: Option<SummaryMaintenanceLifecycleGuarantee>,
@@ -187,10 +189,9 @@ pub struct SummaryMaintenanceDeployment {
 #[derive(Debug, Clone)]
 pub struct SummaryMaintenanceLifecyclePlan {
     /// Root of the materialized post-ASAP DAG being deployed.
-    pub root: Rc<SummaryNode>,
-    /// One entry per unique reachable `SummaryAgg`, then per unique
-    /// maintained population outside any `SummaryAgg`'s inputs; shared `Rc`
-    /// nodes appear only once.
+    pub root: Rc<OperatorNode>,
+    /// One entry per unique reachable `SummaryAgg`; shared `Rc` nodes appear
+    /// only once.
     pub deployments: Vec<SummaryMaintenanceDeployment>,
     /// Caller-supplied optimization horizon used to turn rates into total
     /// costs. `None` keeps horizon-dependent alternatives unselectable.
@@ -223,14 +224,14 @@ pub enum SummaryMaintenanceTimingError {
     #[error(transparent)]
     InvalidPostAsapDAG(#[from] ExecutionDataStateError),
     #[error("summary {0:?} has no selected lifecycle")]
-    UnselectedLifecycle(PostAsapNodeId),
+    UnselectedLifecycle(PhysicalASAPNodeId),
     /// A maintained population outside any `SummaryAgg`'s inputs has no
     /// deployment, so its timing would be guessed. Enumeration always emits
     /// one; this arises only for a plan whose root or deployments were edited.
     #[error("node {0:?} maintains state that has no summary-maintenance lifecycle")]
-    UnplannedMaintainedState(PostAsapNodeId),
+    UnplannedMaintainedState(PhysicalASAPNodeId),
     #[error(transparent)]
-    InvalidPhases(#[from] PostAsapDAGValidationError),
+    InvalidPhases(#[from] PhysicalASAPDAGValidationError),
 }
 
 impl SummaryMaintenanceLifecyclePlan {
@@ -239,19 +240,25 @@ impl SummaryMaintenanceLifecyclePlan {
     ///
     /// A retained (non-`Ephemeral`) state outlives one query, so it and every
     /// input it consumes run at ingestion time. Every other node runs at query
-    /// time: readouts and consumers of retained state, and each `Ephemeral`
+    /// time: evaluations and consumers of retained state, and each `Ephemeral`
     /// state not consumed by retained state together with its inputs, whose
     /// raw data the deployment must supply as a query source. This applies to
     /// maintained populations as to `SummaryAgg` states; a population feeding
     /// a `SummaryAgg` is one of its inputs. Timings already on the root are
     /// ignored.
-    pub fn execution_timed_dag(&self) -> Result<PostAsapDAG, SummaryMaintenanceTimingError> {
-        let compiled = compile_post_asap_dag_with_node_ids(&self.root)?;
+    pub fn execution_timed_dag(&self) -> Result<PhysicalASAPDAG, SummaryMaintenanceTimingError> {
+        let mut memo = TimingMemo::new();
+        let timed = apply_lifecycle_timings(
+            &self.root,
+            &LifecycleAssignment::default_maintained(),
+            &mut memo,
+        )?;
+        let compiled = compile_physical_asap_dag_with_node_ids(&timed)?;
         let dag = compiled.dag;
         for population in &standalone_populations(&self.root) {
             let id = compiled
                 .node_ids
-                .node_id(population)
+                .node_id(memo.timed(population).expect("population was timed"))
                 .expect("collected population belongs to the compiled DAG");
             if !self
                 .deployments
@@ -390,23 +397,23 @@ pub struct SummaryMaintenanceLifecycleCandidates<'a> {
     arrival: DataArrival,
     required_accuracy: Vec<AccuracyTarget>,
     cost_model: &'a dyn CostModel,
-    comparison_target: Option<&'a QueryExpr>,
+    comparison_target: Option<&'a OperatorNode>,
 }
 
 /// Why an explicit per-state lifecycle choice cannot be bound.
 #[derive(Debug, thiserror::Error, PartialEq)]
 pub enum SummaryMaintenanceLifecycleChoiceError {
     #[error("summary {0:?} is not a deployment of this root")]
-    UnknownSummary(PostAsapNodeId),
+    UnknownSummary(PhysicalASAPNodeId),
     #[error("summary {0:?} is chosen more than once")]
-    DuplicateChoice(PostAsapNodeId),
+    DuplicateChoice(PhysicalASAPNodeId),
     #[error("summary {0:?} has no chosen lifecycle")]
-    MissingChoice(PostAsapNodeId),
+    MissingChoice(PhysicalASAPNodeId),
     #[error("chosen lifecycle is not an enumerated alternative of summary {0:?}")]
-    NotAnAlternative(PostAsapNodeId),
+    NotAnAlternative(PhysicalASAPNodeId),
     #[error("chosen lifecycle of summary {post_asap_node_id:?} is rejected: {rejection:?}")]
     Rejected {
-        post_asap_node_id: PostAsapNodeId,
+        post_asap_node_id: PhysicalASAPNodeId,
         rejection: Option<SummaryMaintenanceLifecycleRejection>,
     },
     #[error("summary states on one maintenance path have different evaluation schedules")]
@@ -480,7 +487,7 @@ impl SummaryMaintenanceLifecycleCandidates<'_> {
     /// cost are the model's and unknown cost is never replaced by zero.
     pub fn select(
         mut self,
-        choices: &[(PostAsapNodeId, SummaryMaintenanceLifecycle)],
+        choices: &[(PhysicalASAPNodeId, SummaryMaintenanceLifecycle)],
     ) -> Result<SummaryMaintenanceLifecyclePlan, SummaryMaintenanceLifecycleChoiceError> {
         use SummaryMaintenanceLifecycleChoiceError as E;
         let deployments = &self.plan.deployments;
@@ -580,7 +587,7 @@ struct SummaryMaintenanceWorkloadFacts {
 /// unique summary state, and select the cheapest legal alternative whose cost
 /// is fully known.
 pub fn plan_summary_maintenance_lifecycles(
-    root: Rc<SummaryNode>,
+    root: Rc<OperatorNode>,
     demand: WorkloadDemand<'_>,
     now_ms: u64,
     horizon: Option<Horizon>,
@@ -603,7 +610,7 @@ pub fn plan_summary_maintenance_lifecycles(
 /// alternatives itself binds its choice with
 /// [`SummaryMaintenanceLifecycleCandidates::select`].
 pub fn enumerate_summary_maintenance_lifecycles<'a>(
-    root: Rc<SummaryNode>,
+    root: Rc<OperatorNode>,
     demand: WorkloadDemand<'_>,
     now_ms: u64,
     horizon: Option<Horizon>,
@@ -627,14 +634,14 @@ pub fn enumerate_summary_maintenance_lifecycles<'a>(
 /// DAG path multiplicity has been propagated by `CandidateLogicalASAPDAGs`.
 #[expect(clippy::too_many_arguments, reason = "internal bound planning context")]
 fn enumerate_with_profile<'a>(
-    root: Rc<SummaryNode>,
+    root: Rc<OperatorNode>,
     demand: WorkloadDemand<'_>,
     now_ms: u64,
     horizon: Option<Horizon>,
     capabilities: SummaryMaintenanceLifecycleCapabilities,
     cost_model: &'a dyn CostModel,
     profile: Option<RecurrenceProfile>,
-    comparison_target: Option<&'a QueryExpr>,
+    comparison_target: Option<&'a OperatorNode>,
 ) -> Result<SummaryMaintenanceLifecycleCandidates<'a>, SummaryMaintenanceLifecyclePlanError> {
     demand.workload.validate()?;
     if let Some(data) = demand.data_workload {
@@ -673,11 +680,33 @@ fn enumerate_with_profile<'a>(
         StateKind::SummaryAgg,
     );
     summaries.extend(standalone_populations(&root));
-    let node_ids = compile_post_asap_dag_with_node_ids(&root)?.node_ids;
+    let mut timing_memo = TimingMemo::new();
+    let timed_root = apply_lifecycle_timings(
+        &root,
+        &LifecycleAssignment::default_maintained(),
+        &mut timing_memo,
+    )?;
+    let node_ids = compile_physical_asap_dag_with_node_ids(&timed_root)?.node_ids;
     let components = summary_state_components(&summaries);
     let deployments: Vec<SummaryMaintenanceDeployment> = summaries
         .into_iter()
         .map(|summary| {
+            let capabilities = if OperatorNode::reachable(&summary).iter().any(|node| {
+                matches!(
+                    node.non_asap(),
+                    Some(asap_types::ir::NonASAPOp::BinaryOp { .. })
+                ) && asap_types::ir::timing::validate_default(node, ExecutionTiming::IngestionTime)
+                    .is_err()
+            }) {
+                SummaryMaintenanceLifecycleCapabilities {
+                    supports_ephemeral: capabilities.supports_ephemeral,
+                    supports_prepared: false,
+                    supports_shared: false,
+                    supports_continuously_maintained: false,
+                }
+            } else {
+                capabilities
+            };
             let alternatives = alternatives_for(
                 &facts,
                 horizon,
@@ -686,8 +715,9 @@ fn enumerate_with_profile<'a>(
                 cost_model.summary_maintenance_lifecycle_cost_inputs_for_horizon(&summary, horizon),
             );
             SummaryMaintenanceDeployment {
-                post_asap_node_id: node_ids
-                    .node_id(&summary)
+                post_asap_node_id: timing_memo
+                    .timed(&summary)
+                    .and_then(|timed| node_ids.node_id(timed))
                     .expect("collected summary belongs to the compiled DAG"),
                 summary,
                 summary_maintenance_lifecycle_guarantee: None,
@@ -696,7 +726,7 @@ fn enumerate_with_profile<'a>(
             }
         })
         .collect();
-    let selected_raw_recompute = matches!(root.expr, SummaryExpr::KeepPreAsap(_));
+    let selected_raw_recompute = !root.contains_asap();
     Ok(SummaryMaintenanceLifecycleCandidates {
         plan: SummaryMaintenanceLifecyclePlan {
             root,
@@ -761,9 +791,14 @@ pub fn global_selection_with_summary_maintenance_lifecycles<'a, Id>(
             continue;
         };
         for candidate in &group.candidates {
-            let Replacement::Summary(summary) = &candidate.replacement else {
+            // Only summary realizations carry a maintenance lifecycle; a
+            // logical rewrite or CSE share/recompute candidate does not.
+            let Replacement::SubDAG(summary) = &candidate.replacement else {
                 continue;
             };
+            if candidate.provenance != ReplacementProvenance::SummaryRealization {
+                continue;
+            }
             costs.finalize_target(&group.target);
             let plan = enumerate_with_profile(
                 Rc::clone(summary),
@@ -800,14 +835,14 @@ pub fn global_selection_with_summary_maintenance_lifecycles<'a, Id>(
     // Intern every member once; members whose outermost state (the
     // `SummaryAgg` every other state of the candidate feeds) interns to the
     // same node share it. Classes are kept in first-member order.
-    let interned = share_common_summary_sub_dags(
+    let interned = share_common_sub_dags(
         members
             .iter()
             .enumerate()
             .map(|(index, (_, _, summary))| (index, Rc::clone(summary)))
             .collect(),
     );
-    let mut classes: Vec<(Rc<SummaryNode>, Vec<usize>)> = Vec::new();
+    let mut classes: Vec<(Rc<OperatorNode>, Vec<usize>)> = Vec::new();
     for (index, root) in interned {
         let states = summary_states(&root);
         let Some(state) = states
@@ -826,7 +861,7 @@ pub fn global_selection_with_summary_maintenance_lifecycles<'a, Id>(
     }
     let mut shared = Vec::new();
     for (state, class) in classes {
-        let mut targets: Vec<&Rc<QueryExpr>> = Vec::new();
+        let mut targets: Vec<&Rc<OperatorNode>> = Vec::new();
         for &index in &class {
             let target = &members[index].0.target;
             if !targets.iter().any(|t| Rc::ptr_eq(t, target)) {
@@ -902,7 +937,7 @@ pub fn global_selection_with_summary_maintenance_lifecycles<'a, Id>(
 /// `demand`, or `None` when no lifecycle alternative is selectable for it.
 /// No comparison target is supplied: the state serves several queries.
 pub(crate) fn shared_state_cost(
-    state: &Rc<SummaryNode>,
+    state: &Rc<OperatorNode>,
     demand: WorkloadDemand<'_>,
     now_ms: u64,
     horizon: Option<Horizon>,
@@ -924,7 +959,7 @@ pub(crate) fn shared_state_cost(
 }
 
 /// Every unique `SummaryAgg` reachable from `root`.
-pub(crate) fn summary_states(root: &Rc<SummaryNode>) -> Vec<Rc<SummaryNode>> {
+pub(crate) fn summary_states(root: &Rc<OperatorNode>) -> Vec<Rc<OperatorNode>> {
     let mut states = Vec::new();
     collect_states(
         root,
@@ -939,7 +974,7 @@ pub(crate) fn summary_states(root: &Rc<SummaryNode>) -> Vec<Rc<SummaryNode>> {
 /// summary maintenance decisions. This does not create or maintain runtime state.
 pub fn assemble_selected_dag_with_summary_maintenance_lifecycles(
     selection: &GlobalSelection<'_>,
-    target: &Rc<QueryExpr>,
+    target: &Rc<OperatorNode>,
     demand: WorkloadDemand<'_>,
     now_ms: u64,
     horizon: Option<Horizon>,
@@ -966,8 +1001,8 @@ pub fn assemble_selected_dag_with_summary_maintenance_lifecycles(
 /// [`assemble_selected_dag_with_summary_maintenance_lifecycles`], for a root
 /// the caller already assembled (and possibly interned across queries).
 pub(crate) fn plan_assembled_dag(
-    root: Rc<SummaryNode>,
-    target: &Rc<QueryExpr>,
+    root: Rc<OperatorNode>,
+    target: &Rc<OperatorNode>,
     demand: WorkloadDemand<'_>,
     now_ms: u64,
     horizon: Option<Horizon>,
@@ -994,7 +1029,7 @@ pub(crate) fn plan_assembled_dag(
                 .is_none_or(|summary| raw.0 <= summary.0)
         })
     {
-        plan.root = crate::replacement::keep_pre_asap(target)?;
+        plan.root = crate::replacement::retain_exact(target)?;
         plan.deployments.clear();
         plan.selected_raw_recompute = true;
         plan.selected_window_implementation_id = None;
@@ -1445,66 +1480,35 @@ enum StateKind {
 
 /// Collect every unique node of `kind` reachable from `node`.
 fn collect_states(
-    node: &Rc<SummaryNode>,
-    seen: &mut HashSet<*const SummaryNode>,
-    output: &mut Vec<Rc<SummaryNode>>,
+    node: &Rc<OperatorNode>,
+    seen: &mut HashSet<*const OperatorNode>,
+    output: &mut Vec<Rc<OperatorNode>>,
     kind: StateKind,
 ) {
     if !seen.insert(Rc::as_ptr(node)) {
         return;
     }
-    match &node.expr {
-        SummaryExpr::SummaryAgg { child, .. } => {
-            if kind == StateKind::SummaryAgg {
-                output.push(Rc::clone(node));
-            }
-            collect_states(child, seen, output, kind);
-        }
-        SummaryExpr::ValueOperation {
-            child, operation, ..
-        } => {
-            if kind == StateKind::Population
-                && matches!(operation, ValueOperation::MaintainPopulation { .. })
-            {
-                output.push(Rc::clone(node));
-            }
-            collect_states(child, seen, output, kind)
-        }
-        SummaryExpr::SummaryJoin { outer, inner, .. }
-        | SummaryExpr::RelationalJoin {
-            left: outer,
-            right: inner,
-            ..
-        }
-        | SummaryExpr::BinaryOp {
-            lhs: outer,
-            rhs: inner,
-            ..
-        }
-        | SummaryExpr::SummarySubtract {
-            left: outer,
-            right: inner,
-        } => {
-            collect_states(outer, seen, output, kind);
-            collect_states(inner, seen, output, kind);
-        }
-        SummaryExpr::SummaryDelete { summary_input, .. }
-        | SummaryExpr::SummaryEstimate { summary_input, .. } => {
-            collect_states(summary_input, seen, output, kind)
-        }
-        SummaryExpr::SummaryMerge { children, .. } => {
-            for child in children {
-                collect_states(child, seen, output, kind);
-            }
-        }
-        SummaryExpr::KeepPreAsap(_) => {}
+    if matches!(
+        (&node.operator, kind),
+        (
+            Operator::ASAP(ASAPOp::SummaryAgg { .. }),
+            StateKind::SummaryAgg
+        ) | (
+            Operator::ASAP(ASAPOp::MaintainPopulation { .. }),
+            StateKind::Population
+        )
+    ) {
+        output.push(Rc::clone(node));
+    }
+    for child in node.children() {
+        collect_states(child, seen, output, kind);
     }
 }
 
 /// Maintained populations that are not an input of any `SummaryAgg`. A
 /// population feeding summary state is on that state's maintenance path, so
-/// that state's lifecycle times it, even when a readout also reads it directly.
-fn standalone_populations(root: &Rc<SummaryNode>) -> Vec<Rc<SummaryNode>> {
+/// that state's lifecycle times it, even when a evaluation also reads it directly.
+fn standalone_populations(root: &Rc<OperatorNode>) -> Vec<Rc<OperatorNode>> {
     let mut summaries = Vec::new();
     collect_states(
         root,
@@ -1552,7 +1556,7 @@ pub(crate) fn evaluation_schedule(
 
 /// Summary states composed on one maintenance path must be produced on the
 /// same schedule. Return a component id for each collected state.
-fn summary_state_components(summaries: &[Rc<SummaryNode>]) -> Vec<usize> {
+fn summary_state_components(summaries: &[Rc<OperatorNode>]) -> Vec<usize> {
     let indices: HashMap<_, _> = summaries
         .iter()
         .enumerate()
@@ -1568,16 +1572,18 @@ fn summary_state_components(summaries: &[Rc<SummaryNode>]) -> Vec<usize> {
     }
 
     for (parent_index, summary) in summaries.iter().enumerate() {
-        let SummaryExpr::SummaryAgg { child, .. } = &summary.expr else {
+        let Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) = &summary.operator else {
             continue;
         };
         if !matches!(
-            child.expr,
-            SummaryExpr::SummaryAgg { .. }
-                | SummaryExpr::SummaryJoin { .. }
-                | SummaryExpr::SummarySubtract { .. }
-                | SummaryExpr::SummaryDelete { .. }
-                | SummaryExpr::SummaryMerge { .. }
+            child.operator,
+            Operator::ASAP(
+                ASAPOp::SummaryAgg { .. }
+                    | ASAPOp::SummaryJoin { .. }
+                    | ASAPOp::SummarySubtract { .. }
+                    | ASAPOp::SummaryDelete { .. }
+                    | ASAPOp::SummaryMerge { .. }
+            )
         ) {
             continue;
         }
@@ -1603,10 +1609,10 @@ fn summary_state_components(summaries: &[Rc<SummaryNode>]) -> Vec<usize> {
 /// Inputs shared by every complete lifecycle-combination evaluation of one
 /// root, whether Planner searches combinations or a caller supplies one.
 struct CompleteCostContext<'a> {
-    root: &'a SummaryNode,
+    root: &'a OperatorNode,
     components: &'a [usize],
     cost_model: &'a dyn CostModel,
-    comparison_target: Option<&'a QueryExpr>,
+    comparison_target: Option<&'a OperatorNode>,
     horizon: Option<Horizon>,
     expected_reads: Option<f64>,
     required_accuracy: &'a [AccuracyTarget],
@@ -1695,12 +1701,12 @@ fn apply_selection(
 
 #[expect(clippy::too_many_arguments, reason = "complete combination context")]
 fn select_complete_lifecycle_combination(
-    root: &SummaryNode,
+    root: &OperatorNode,
     deployments: &mut [SummaryMaintenanceDeployment],
     components: &[usize],
     arrival: DataArrival,
     cost_model: &dyn CostModel,
-    comparison_target: Option<&QueryExpr>,
+    comparison_target: Option<&OperatorNode>,
     horizon: Option<Horizon>,
     expected_reads: Option<f64>,
     required_accuracy: &[AccuracyTarget],
@@ -1836,12 +1842,16 @@ mod tests {
         }
     }
     use super::*;
+    use asap_types::ir::export::{NonASAPOpKind, PhysicalASAPOperatorPayload};
+    use asap_types::ir::{BinaryOperator, NonASAPOp};
     use asap_types::post_asap::{
-        ExactKind, ExactParams, Field, FieldDataType, GroupingStrategy, PostAsapOperatorPayload,
-        ResultGuarantee, Schema, SketchAlgorithm,
+        ExactKind, ExactParams, Field, FieldDataType, GroupingStrategy, ResultGuarantee, Schema,
+        SketchAlgorithm,
     };
     use asap_types::pre_asap::AggIntent;
-    use asap_types::pre_asap::{ColumnRef, DataType, QueryExpr, Reduction, Source};
+    use asap_types::pre_asap::{
+        ArithmeticOpKind, BinaryOpKind, ColumnRef, DataType, Reduction, Source,
+    };
     use asap_types::types::AccuracyTarget;
     use asap_types::workload::{
         BatchEntry, DataWorkload, DurationMs, Evidence, EvidenceSource, Predictability, Query,
@@ -1861,7 +1871,7 @@ mod tests {
 
         fn summary_maintenance_lifecycle_cost_inputs(
             &self,
-            _summary: &SummaryNode,
+            _summary: &OperatorNode,
         ) -> SummaryMaintenanceLifecycleCostInputs {
             SummaryMaintenanceLifecycleCostInputs {
                 build_cost: Some(Cost(10.0)),
@@ -1874,7 +1884,7 @@ mod tests {
 
         fn summary_maintenance_capabilities(
             &self,
-            _summary: &SummaryNode,
+            _summary: &OperatorNode,
         ) -> SummaryMaintenanceCapabilities {
             SummaryMaintenanceCapabilities {
                 incremental_update: true,
@@ -1897,19 +1907,19 @@ mod tests {
 
         fn summary_maintenance_lifecycle_cost_inputs(
             &self,
-            summary: &SummaryNode,
+            summary: &OperatorNode,
         ) -> SummaryMaintenanceLifecycleCostInputs {
             UnitCosts.summary_maintenance_lifecycle_cost_inputs(summary)
         }
 
         fn summary_maintenance_capabilities(
             &self,
-            summary: &SummaryNode,
+            summary: &OperatorNode,
         ) -> SummaryMaintenanceCapabilities {
             UnitCosts.summary_maintenance_capabilities(summary)
         }
 
-        fn raw_query_recompute_cost(&self, _target: &QueryExpr) -> Option<Cost> {
+        fn raw_query_recompute_cost(&self, _target: &OperatorNode) -> Option<Cost> {
             Some(Cost(1.0))
         }
     }
@@ -1927,14 +1937,14 @@ mod tests {
 
         fn summary_maintenance_lifecycle_cost_inputs(
             &self,
-            summary: &SummaryNode,
+            summary: &OperatorNode,
         ) -> SummaryMaintenanceLifecycleCostInputs {
             UnitCosts.summary_maintenance_lifecycle_cost_inputs(summary)
         }
 
         fn summary_maintenance_capabilities(
             &self,
-            _summary: &SummaryNode,
+            _summary: &OperatorNode,
         ) -> SummaryMaintenanceCapabilities {
             SummaryMaintenanceCapabilities {
                 incremental_update: true,
@@ -1949,7 +1959,7 @@ mod tests {
     impl CostModel for SummaryMaintenancePrefersDdSketch {
         fn raw_query_recompute_total_cost(
             &self,
-            _target: &QueryExpr,
+            _target: &OperatorNode,
             _expected_reads: f64,
         ) -> Option<Cost> {
             Some(Cost(1_000.0))
@@ -1967,7 +1977,7 @@ mod tests {
 
         fn summary_maintenance_lifecycle_cost_inputs(
             &self,
-            summary: &SummaryNode,
+            summary: &OperatorNode,
         ) -> SummaryMaintenanceLifecycleCostInputs {
             let build = match sketch_algorithm(summary) {
                 Some(SketchAlgorithm::Kll) => 100.0,
@@ -1999,8 +2009,8 @@ mod tests {
 
         fn complete_summary_candidate_cost(
             &self,
-            _root: &SummaryNode,
-            _target: Option<&QueryExpr>,
+            _root: &OperatorNode,
+            _target: Option<&OperatorNode>,
             deployments: &[CostedSummaryDeployment<'_>],
             _horizon: Option<Horizon>,
             _expected_reads: Option<f64>,
@@ -2032,12 +2042,13 @@ mod tests {
 
         fn summary_maintenance_lifecycle_cost_inputs(
             &self,
-            summary: &SummaryNode,
+            summary: &OperatorNode,
         ) -> SummaryMaintenanceLifecycleCostInputs {
+            // A leaf summary is one built directly over kept pre-ASAP rows
+            // (its child is not an ASAP node); a nested one reads state.
             let is_leaf = matches!(
-                summary.expr,
-                SummaryExpr::SummaryAgg { ref child, .. }
-                    if matches!(child.expr, SummaryExpr::KeepPreAsap(_))
+                &summary.operator,
+                Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) if !child.is_asap()
             );
             SummaryMaintenanceLifecycleCostInputs {
                 build_cost: Some(Cost(if is_leaf { 1.0 } else { 100.0 })),
@@ -2050,7 +2061,7 @@ mod tests {
 
         fn summary_maintenance_capabilities(
             &self,
-            _summary: &SummaryNode,
+            _summary: &OperatorNode,
         ) -> SummaryMaintenanceCapabilities {
             SummaryMaintenanceCapabilities {
                 incremental_update: true,
@@ -2060,23 +2071,27 @@ mod tests {
         }
     }
 
-    fn sketch_algorithm(node: &SummaryNode) -> Option<SketchAlgorithm> {
-        match &node.expr {
-            SummaryExpr::SummaryEstimate { summary_input, .. } => sketch_algorithm(summary_input),
-            SummaryExpr::SummaryAgg {
-                family: FieldDataType::Sketch(kind, _),
-                ..
-            } => Some(kind.algorithm().clone()),
-            _ => None,
+    /// The sketch algorithm of the first `SummaryAgg` reachable from `node`
+    /// (through a evaluation or any relational operator kept above it).
+    fn sketch_algorithm(node: &OperatorNode) -> Option<SketchAlgorithm> {
+        if let Operator::ASAP(ASAPOp::SummaryAgg {
+            family: FieldDataType::Sketch(kind, _),
+            ..
+        }) = &node.operator
+        {
+            return Some(kind.algorithm().clone());
         }
+        node.children()
+            .into_iter()
+            .find_map(|child| sketch_algorithm(child))
     }
 
-    fn query_root() -> Rc<QueryExpr> {
+    fn query_root() -> Rc<OperatorNode> {
         query_root_for("m")
     }
 
-    fn query_root_for(metric: &str) -> Rc<QueryExpr> {
-        Rc::new(QueryExpr::Scan {
+    fn query_root_for(metric: &str) -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: Source::TimeSeries {
                 metric: metric.into(),
             },
@@ -2089,22 +2104,24 @@ mod tests {
                 0,
                 vec![],
             ),
-        })
+        }))
+        .unwrap()
     }
 
-    fn sum_query() -> Rc<QueryExpr> {
-        Rc::new(QueryExpr::Aggregate {
+    fn sum_query() -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
             reduction: Reduction::by(vec![]),
             measures: vec![AggIntent::Sum { col: None }],
             output_names: vec![],
             filters: vec![],
             having: None,
             child: query_root(),
-        })
+        }))
+        .unwrap()
     }
 
-    fn quantile_query() -> Rc<QueryExpr> {
-        Rc::new(QueryExpr::Aggregate {
+    fn quantile_query() -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
             reduction: Reduction::by(vec![]),
             measures: vec![AggIntent::Quantile {
                 col: None,
@@ -2115,49 +2132,56 @@ mod tests {
             filters: vec![],
             having: None,
             child: query_root(),
-        })
+        }))
+        .unwrap()
     }
 
-    fn summary() -> Rc<SummaryNode> {
-        let child = Rc::new(SummaryNode {
-            expr: SummaryExpr::KeepPreAsap(query_root()),
-            schema: Schema::lifted(vec![], None),
-            guarantee: Some(ResultGuarantee::exact("raw")),
-        });
+    /// An exact sum accumulator over the kept pre-ASAP scan.
+    fn summary() -> Rc<OperatorNode> {
+        let child = Rc::new(
+            query_root()
+                .as_ref()
+                .clone()
+                .with_guarantee(Some(ResultGuarantee::exact("raw"))),
+        );
         let family = FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum);
-        Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryAgg {
-                child,
-                family: family.clone(),
-                input: asap_types::post_asap::SummaryUpdate::column(ColumnRef::Named(
-                    "value".into(),
-                )),
-                reduction: Reduction::by(vec![]),
-                grouping: GroupingStrategy::default(),
-                filter: None,
-            },
-            schema: Schema::lifted(vec![Field::new("state", family, false)], None),
-            guarantee: Some(ResultGuarantee::exact("sum")),
-        })
+        std::rc::Rc::new(
+            OperatorNode::with_schema(
+                asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
+                    child,
+                    family: family.clone(),
+                    input: asap_types::post_asap::SummaryUpdate::column(ColumnRef::Named(
+                        "value".into(),
+                    )),
+                    reduction: Reduction::by(vec![]),
+                    grouping: GroupingStrategy::default(),
+                    filter: None,
+                }),
+                Schema::lifted(vec![Field::new("state", family, false)], None),
+            )
+            .with_guarantee(Some(ResultGuarantee::exact("sum"))),
+        )
     }
 
-    fn nested_summary() -> Rc<SummaryNode> {
+    fn nested_summary() -> Rc<OperatorNode> {
         let child = summary();
         let family = FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum);
-        Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryAgg {
-                child,
-                family: family.clone(),
-                input: asap_types::post_asap::SummaryUpdate::column(ColumnRef::Named(
-                    "state".into(),
-                )),
-                reduction: Reduction::by(vec![]),
-                grouping: GroupingStrategy::default(),
-                filter: None,
-            },
-            schema: Schema::lifted(vec![Field::new("state", family, false)], None),
-            guarantee: Some(ResultGuarantee::exact("nested sum")),
-        })
+        std::rc::Rc::new(
+            OperatorNode::with_schema(
+                asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
+                    child,
+                    family: family.clone(),
+                    input: asap_types::post_asap::SummaryUpdate::column(ColumnRef::Named(
+                        "state".into(),
+                    )),
+                    reduction: Reduction::by(vec![]),
+                    grouping: GroupingStrategy::default(),
+                    filter: None,
+                }),
+                Schema::lifted(vec![Field::new("state", family, false)], None),
+            )
+            .with_guarantee(Some(ResultGuarantee::exact("nested sum"))),
+        )
     }
 
     fn batch(predictability: Predictability) -> BatchEntry {
@@ -2649,7 +2673,13 @@ mod tests {
         assert_eq!(plan.raw_recompute_total_cost, Some(Cost(1.0)));
         assert_eq!(plan.summary_total_cost, None);
         assert!(plan.deployments.is_empty());
-        assert!(matches!(plan.root.expr, SummaryExpr::KeepPreAsap(_)));
+        // The logical query stays exact; deployment assigns execution timing.
+        assert!(!plan.root.contains_asap());
+        assert!(matches!(
+            plan.root.non_asap(),
+            Some(NonASAPOp::Aggregate { .. })
+        ));
+        assert!(plan.root.timing.is_none());
 
         let exported =
             crate::summary_maintenance_dag_export::export_summary_maintenance_plan(&plan);
@@ -2663,7 +2693,7 @@ mod tests {
     fn whole_candidate_cost_is_evaluated_before_selecting_a_lifecycle() {
         let root = summary();
         let mut deployments = vec![SummaryMaintenanceDeployment {
-            post_asap_node_id: PostAsapNodeId(0),
+            post_asap_node_id: asap_types::ir::export::LogicalASAPNodeId(0),
             summary: Rc::clone(&root),
             summary_maintenance_lifecycle_guarantee: None,
             selected_window_framework: None,
@@ -2726,7 +2756,7 @@ mod tests {
         ];
         let mut deployments: Vec<_> = (0..13)
             .map(|summary_index| SummaryMaintenanceDeployment {
-                post_asap_node_id: PostAsapNodeId(summary_index as u32),
+                post_asap_node_id: asap_types::ir::export::LogicalASAPNodeId(summary_index as u32),
                 summary: Rc::clone(&root),
                 summary_maintenance_lifecycle_guarantee: None,
                 selected_window_framework: None,
@@ -2771,7 +2801,11 @@ mod tests {
         .unwrap();
         assert!(plan.selected_raw_recompute);
         assert!(plan.raw_recompute_total_cost.is_none());
-        assert!(matches!(plan.root.expr, SummaryExpr::KeepPreAsap(_)));
+        assert!(!plan.root.contains_asap());
+        assert!(matches!(
+            plan.root.non_asap(),
+            Some(NonASAPOp::Aggregate { .. })
+        ));
     }
 
     #[test]
@@ -2796,7 +2830,8 @@ mod tests {
         assert_eq!(plan.raw_recompute_total_cost, Some(Cost(1.0)));
         assert_eq!(plan.summary_total_cost, None);
         assert!(plan.deployments.is_empty());
-        assert!(matches!(plan.root.expr, SummaryExpr::KeepPreAsap(_)));
+        assert!(!plan.root.contains_asap());
+        assert!(matches!(plan.root.non_asap(), Some(NonASAPOp::Scan { .. })));
     }
 
     #[test]
@@ -2827,15 +2862,30 @@ mod tests {
 
     #[test]
     fn lifecycle_cost_counts_one_shared_summary_node_once() {
+        // One shared exact accumulator read twice by the same root: a
+        // query-time `sum + sum` over one finalized state. (`SummaryMerge`
+        // is reserved in the unified IR, so the sharing is expressed through
+        // a relational consumer instead.)
         let shared = summary();
-        let root = Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryMerge {
-                timing: asap_types::post_asap::ExecutionTiming::IngestionTime,
-                children: vec![Rc::clone(&shared), Rc::clone(&shared)],
-            },
-            schema: shared.schema.clone(),
-            guarantee: None,
-        });
+        let finalized = Rc::new(
+            OperatorNode::new(Operator::ASAP(ASAPOp::FinalizeExactAccumulator {
+                child: Rc::clone(&shared),
+            }))
+            .unwrap(),
+        );
+        let root =
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::BinaryOp {
+                operator: BinaryOperator {
+                    checked_relative_division: false,
+                    checked_finite_division: false,
+                    kind: BinaryOpKind::Arithmetic(ArithmeticOpKind::Add),
+                    vector_match: None,
+                },
+                return_bool: false,
+                lhs: Rc::clone(&finalized),
+                rhs: finalized,
+            }))
+            .unwrap();
         let workload = workload(
             vec![batch(Predictability::AdHoc), batch(Predictability::AdHoc)],
             vec![],
@@ -2873,7 +2923,7 @@ mod tests {
 
         fn summary_maintenance_lifecycle_cost_inputs(
             &self,
-            _summary: &SummaryNode,
+            _summary: &OperatorNode,
         ) -> SummaryMaintenanceLifecycleCostInputs {
             SummaryMaintenanceLifecycleCostInputs {
                 build_cost: Some(Cost(10.0)),
@@ -2886,18 +2936,18 @@ mod tests {
 
         fn summary_maintenance_capabilities(
             &self,
-            summary: &SummaryNode,
+            summary: &OperatorNode,
         ) -> SummaryMaintenanceCapabilities {
             UnitCosts.summary_maintenance_capabilities(summary)
         }
 
         fn raw_query_recompute_total_cost(
             &self,
-            target: &QueryExpr,
+            target: &OperatorNode,
             _expected_reads: f64,
         ) -> Option<Cost> {
-            match target {
-                QueryExpr::Aggregate { measures, .. } => match measures[..] {
+            match target.non_asap() {
+                Some(NonASAPOp::Aggregate { measures, .. }) => match measures[..] {
                     [AggIntent::Quantile { q: 0.5, .. }] => Some(Cost(1.0)),
                     _ => Some(Cost(8.0)),
                 },
@@ -2914,7 +2964,7 @@ mod tests {
     #[test]
     fn sharing_class_reverts_when_a_member_selects_elsewhere() {
         let quantile = |q| {
-            Rc::new(QueryExpr::Aggregate {
+            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
                 reduction: Reduction::by(vec![]),
                 measures: vec![AggIntent::Quantile {
                     col: None,
@@ -2926,7 +2976,8 @@ mod tests {
                 filters: vec![],
                 having: None,
                 child: query_root(),
-            })
+            }))
+            .unwrap()
         };
         let workload = workload(vec![], vec![repeating(), repeating()], at_rest());
         // Whether each root selected a summary rather than raw recompute.
@@ -3024,7 +3075,7 @@ mod tests {
     fn choose(
         candidates: &SummaryMaintenanceLifecycleCandidates<'_>,
         lifecycle: SummaryMaintenanceLifecycle,
-    ) -> Vec<(PostAsapNodeId, SummaryMaintenanceLifecycle)> {
+    ) -> Vec<(PhysicalASAPNodeId, SummaryMaintenanceLifecycle)> {
         candidates
             .deployments()
             .iter()
@@ -3134,7 +3185,7 @@ mod tests {
         use SummaryMaintenanceLifecycleChoiceError as E;
         let data = continuous(1_000, 60_000);
         let workload = workload(vec![], vec![repeating()], data.clone());
-        let select = |model: &dyn CostModel, choice: &dyn Fn(PostAsapNodeId) -> Vec<_>| {
+        let select = |model: &dyn CostModel, choice: &dyn Fn(PhysicalASAPNodeId) -> Vec<_>| {
             let candidates = continuous_candidates(&workload, &data, model);
             let id = candidates.deployments()[0].post_asap_node_id;
             (id, candidates.select(&choice(id)).unwrap_err())
@@ -3177,9 +3228,15 @@ mod tests {
         });
         assert_eq!(error, E::DuplicateChoice(id));
         let (_, error) = select(&UnitCosts, &|_| {
-            vec![(PostAsapNodeId(u32::MAX), continuous.clone())]
+            vec![(
+                asap_types::ir::export::LogicalASAPNodeId(u32::MAX),
+                continuous.clone(),
+            )]
         });
-        assert_eq!(error, E::UnknownSummary(PostAsapNodeId(u32::MAX)));
+        assert_eq!(
+            error,
+            E::UnknownSummary(asap_types::ir::export::LogicalASAPNodeId(u32::MAX))
+        );
     }
 
     // Nested states on one maintenance path must share an evaluation schedule.
@@ -3219,14 +3276,10 @@ mod tests {
     #[test]
     fn enumeration_lists_each_unique_summary_state_once() {
         let shared = summary();
-        let root = Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryMerge {
-                timing: asap_types::post_asap::ExecutionTiming::IngestionTime,
-                children: vec![Rc::clone(&shared), Rc::clone(&shared), summary()],
-            },
-            schema: shared.schema.clone(),
-            guarantee: None,
-        });
+        let root = test_binary(
+            test_binary(evaluation(&shared), evaluation(&shared)),
+            evaluation(&summary()),
+        );
         let workload = workload(vec![batch(Predictability::AdHoc)], vec![], at_rest());
         let candidates = enumerate_summary_maintenance_lifecycles(
             root,
@@ -3250,26 +3303,41 @@ mod tests {
             .any(|deployment| Rc::ptr_eq(&deployment.summary, &shared)));
     }
 
-    fn readout(state: &Rc<SummaryNode>) -> Rc<SummaryNode> {
-        Rc::new(SummaryNode {
-            expr: SummaryExpr::ValueOperation {
-                child: Rc::clone(state),
-                operation: ValueOperation::FinalizeExactAccumulator,
-                timing: ExecutionTiming::QueryTime,
-            },
-            schema: Schema {
-                closed: true,
-                unique_keys: vec![],
-                fields: vec![Field {
-                    table: None,
-                    name: "value".into(),
-                    dtype: FieldDataType::Plain(DataType::Float64),
-                    nullable: false,
-                }],
-                time_index: None,
-            },
-            guarantee: Some(ResultGuarantee::exact("sum")),
-        })
+    fn evaluation(state: &Rc<OperatorNode>) -> Rc<OperatorNode> {
+        std::rc::Rc::new(
+            OperatorNode::with_schema(
+                asap_types::ir::Operator::ASAP(ASAPOp::FinalizeExactAccumulator {
+                    child: Rc::clone(state),
+                }),
+                Schema::lifted(
+                    vec![Field::new(
+                        "value",
+                        FieldDataType::Plain(DataType::Float64),
+                        false,
+                    )],
+                    None,
+                ),
+            )
+            .with_guarantee(Some(ResultGuarantee::exact("sum"))),
+        )
+    }
+
+    fn test_binary(lhs: Rc<OperatorNode>, rhs: Rc<OperatorNode>) -> Rc<OperatorNode> {
+        let schema = lhs.schema.clone();
+        Rc::new(OperatorNode::with_schema(
+            Operator::NonASAP(NonASAPOp::BinaryOp {
+                lhs,
+                rhs,
+                return_bool: false,
+                operator: BinaryOperator {
+                    kind: BinaryOpKind::Arithmetic(ArithmeticOpKind::Add),
+                    vector_match: None,
+                    checked_relative_division: false,
+                    checked_finite_division: false,
+                },
+            }),
+            schema,
+        ))
     }
 
     fn lifecycle_matching(
@@ -3287,12 +3355,12 @@ mod tests {
     /// Bind the lifecycle `choose` picks for every state of `root`, then
     /// derive the timed DAG.
     fn timed_dag(
-        root: Rc<SummaryNode>,
+        root: Rc<OperatorNode>,
         workload: &QueryWorkload,
         data: &DataWorkload,
         horizon: Option<Horizon>,
         choose: impl Fn(&SummaryMaintenanceDeployment) -> SummaryMaintenanceLifecycle,
-    ) -> PostAsapDAG {
+    ) -> PhysicalASAPDAG {
         let candidates = enumerate_summary_maintenance_lifecycles(
             root,
             WorkloadDemand::new_with_data(workload, data, &[0]),
@@ -3317,15 +3385,19 @@ mod tests {
     }
 
     /// Operator kinds in node-id order, each paired with its timing.
-    fn timings(dag: &PostAsapDAG) -> Vec<(&'static str, ExecutionTiming)> {
+    fn timings(dag: &PhysicalASAPDAG) -> Vec<(&'static str, ExecutionTiming)> {
         dag.nodes
             .iter()
             .map(|node| {
                 let kind = match node.payload {
-                    PostAsapOperatorPayload::Fallback { .. } => "raw",
-                    PostAsapOperatorPayload::SummaryAgg { .. } => "state",
-                    PostAsapOperatorPayload::Value { .. } => "readout",
-                    PostAsapOperatorPayload::Binary { .. } => "binary",
+                    PhysicalASAPOperatorPayload::Relational {
+                        operator: NonASAPOpKind::BinaryOp { .. },
+                    } => "binary",
+                    PhysicalASAPOperatorPayload::Relational { .. } => "raw",
+                    PhysicalASAPOperatorPayload::SummaryAgg { .. } => "state",
+                    PhysicalASAPOperatorPayload::FinalizeExactAccumulator
+                    | PhysicalASAPOperatorPayload::EvaluatePopulation { .. } => "evaluation",
+
                     _ => "other",
                 };
                 (kind, node.output_state.timing)
@@ -3337,7 +3409,7 @@ mod tests {
     const QUERY: ExecutionTiming = ExecutionTiming::QueryTime;
 
     // Every retained lifecycle kind runs its state and inputs at ingestion
-    // time and its readout at query time.
+    // time and its evaluation at query time.
     #[test]
     fn retained_lifecycles_time_state_and_inputs_at_ingestion() {
         let mut scheduled = batch(Predictability::Predictable {
@@ -3377,7 +3449,7 @@ mod tests {
         ];
         for (workload, data, horizon, kind) in cases {
             let dag = timed_dag(
-                readout(&summary()),
+                evaluation(&summary()),
                 &workload,
                 &data,
                 horizon,
@@ -3385,21 +3457,21 @@ mod tests {
             );
             assert_eq!(
                 timings(&dag),
-                [("raw", INGEST), ("state", INGEST), ("readout", QUERY)]
+                [("raw", INGEST), ("state", INGEST), ("evaluation", QUERY)]
             );
         }
     }
 
-    // An Ephemeral state, its raw input, and its readout all run at query time.
+    // An Ephemeral state, its raw input, and its evaluation all run at query time.
     #[test]
     fn ephemeral_lifecycle_times_state_and_downstream_at_query() {
         let workload = workload(vec![batch(Predictability::AdHoc)], vec![], at_rest());
-        let dag = timed_dag(readout(&summary()), &workload, &at_rest(), None, |_| {
+        let dag = timed_dag(evaluation(&summary()), &workload, &at_rest(), None, |_| {
             SummaryMaintenanceLifecycle::Ephemeral
         });
         assert_eq!(
             timings(&dag),
-            [("raw", QUERY), ("state", QUERY), ("readout", QUERY)]
+            [("raw", QUERY), ("state", QUERY), ("evaluation", QUERY)]
         );
     }
 
@@ -3408,25 +3480,9 @@ mod tests {
     #[test]
     fn shared_state_is_timed_once_for_all_consumers() {
         let state = summary();
-        let lhs = readout(&state);
+        let lhs = evaluation(&state);
         let rhs = Rc::new(lhs.as_ref().clone());
-        let root = Rc::new(SummaryNode {
-            expr: SummaryExpr::BinaryOp {
-                lhs,
-                rhs,
-                operator: asap_types::post_asap::BinaryOperator {
-                    kind: asap_types::pre_asap::BinaryOpKind::Arithmetic(
-                        asap_types::pre_asap::ArithmeticOpKind::Add,
-                    ),
-                    vector_match: None,
-                    checked_relative_division: false,
-                    checked_finite_division: false,
-                },
-                timing: QUERY,
-            },
-            schema: readout(&state).schema.clone(),
-            guarantee: None,
-        });
+        let root = test_binary(lhs, rhs);
         let data = continuous(1_000, 60_000);
         let workload = workload(vec![], vec![repeating()], data.clone());
         let dag = timed_dag(root, &workload, &data, Some(Horizon(10.0)), |deployment| {
@@ -3438,8 +3494,8 @@ mod tests {
             [
                 ("raw", INGEST),
                 ("state", INGEST),
-                ("readout", QUERY),
-                ("readout", QUERY),
+                ("evaluation", QUERY),
+                ("evaluation", QUERY),
                 ("binary", QUERY),
             ]
         );
@@ -3484,7 +3540,7 @@ mod tests {
         let data = at_rest();
         let demand = WorkloadDemand::new_with_data(&workload, &data, &[0]);
         let plan = plan_summary_maintenance_lifecycles(
-            readout(&summary()),
+            evaluation(&summary()),
             demand,
             1_000,
             None,
@@ -3499,7 +3555,7 @@ mod tests {
             )
         );
         let raw = plan_summary_maintenance_lifecycles(
-            crate::replacement::keep_pre_asap(&sum_query()).unwrap(),
+            crate::replacement::retain_exact(&sum_query()).unwrap(),
             demand,
             1_000,
             None,
@@ -3509,16 +3565,13 @@ mod tests {
         .unwrap();
         assert_eq!(
             timings(&raw.execution_timed_dag().unwrap()),
-            [("raw", QUERY)]
+            [("raw", QUERY), ("raw", QUERY)]
         );
     }
 
     /// A strategy-built `sum(a)` over one maintained current-series population.
-    fn population_readout() -> Rc<SummaryNode> {
-        let target = Rc::new(crate::test_support::lower_promql(
-            "sum(a)",
-            AccuracyTarget::Exact,
-        ));
+    fn population_evaluation() -> Rc<OperatorNode> {
+        let target = crate::test_support::lower_promql("sum(a)", AccuracyTarget::Exact);
         crate::maintained_population::MaintainedPopulationStrategy::new(std::slice::from_ref(
             &target,
         ))
@@ -3526,24 +3579,19 @@ mod tests {
         .unwrap()
     }
 
-    fn is_population(node: &SummaryNode) -> bool {
+    fn is_population(node: &OperatorNode) -> bool {
         matches!(
-            node.expr,
-            SummaryExpr::ValueOperation {
-                operation: ValueOperation::MaintainPopulation { .. },
-                ..
-            }
+            node.operator,
+            Operator::ASAP(ASAPOp::MaintainPopulation { .. })
         )
     }
 
-    fn population_timings(dag: &PostAsapDAG) -> Vec<(&'static str, ExecutionTiming)> {
+    fn population_timings(dag: &PhysicalASAPDAG) -> Vec<(&'static str, ExecutionTiming)> {
         dag.nodes
             .iter()
             .zip(timings(dag))
             .map(|(node, (kind, timing))| match node.payload {
-                PostAsapOperatorPayload::Value {
-                    operation: ValueOperation::MaintainPopulation { .. },
-                } => ("population", timing),
+                PhysicalASAPOperatorPayload::MaintainPopulation { .. } => ("population", timing),
                 _ => (kind, timing),
             })
             .collect()
@@ -3556,7 +3604,7 @@ mod tests {
         let data = continuous(1_000, 60_000);
         let workload = workload(vec![], vec![repeating()], data.clone());
         let candidates = enumerate_summary_maintenance_lifecycles(
-            population_readout(),
+            population_evaluation(),
             WorkloadDemand::new_with_data(&workload, &data, &[0]),
             1_000,
             Some(Horizon(10.0)),
@@ -3594,7 +3642,7 @@ mod tests {
         let data = continuous(1_000, 60_000);
         let workload = workload(vec![], vec![repeating()], data.clone());
         let plan = plan_summary_maintenance_lifecycles(
-            population_readout(),
+            population_evaluation(),
             WorkloadDemand::new_with_data(&workload, &data, &[0]),
             1_000,
             Some(Horizon(10.0)),
@@ -3624,7 +3672,7 @@ mod tests {
         let workload = workload(vec![], vec![repeating()], data.clone());
         let timed = |lifecycle: SummaryMaintenanceLifecycle| {
             population_timings(&timed_dag(
-                population_readout(),
+                population_evaluation(),
                 &workload,
                 &data,
                 Some(Horizon(10.0)),
@@ -3633,11 +3681,21 @@ mod tests {
         };
         assert_eq!(
             timed(SummaryMaintenanceLifecycle::ContinuouslyMaintained),
-            [("raw", INGEST), ("population", INGEST), ("readout", QUERY)]
+            [
+                ("raw", INGEST),
+                ("raw", INGEST),
+                ("population", INGEST),
+                ("evaluation", QUERY)
+            ]
         );
         assert_eq!(
             timed(SummaryMaintenanceLifecycle::Ephemeral),
-            [("raw", QUERY), ("population", QUERY), ("readout", QUERY)]
+            [
+                ("raw", QUERY),
+                ("raw", QUERY),
+                ("population", QUERY),
+                ("evaluation", QUERY)
+            ]
         );
     }
 
@@ -3649,7 +3707,7 @@ mod tests {
         let data = continuous(1_000, 60_000);
         let workload = workload(vec![], vec![repeating()], data.clone());
         let plan = plan_summary_maintenance_lifecycles(
-            population_readout(),
+            population_evaluation(),
             WorkloadDemand::new_with_data(&workload, &data, &[0]),
             1_000,
             Some(Horizon(10.0)),
@@ -3664,7 +3722,12 @@ mod tests {
         ));
         assert_eq!(
             population_timings(&plan.execution_timed_dag().unwrap()),
-            [("raw", INGEST), ("population", INGEST), ("readout", QUERY)]
+            [
+                ("raw", INGEST),
+                ("raw", INGEST),
+                ("population", INGEST),
+                ("evaluation", QUERY)
+            ]
         );
     }
 
@@ -3672,39 +3735,39 @@ mod tests {
     // deployment: the state's lifecycle times it.
     #[test]
     fn population_feeding_summary_state_follows_that_state() {
-        let SummaryExpr::ValueOperation {
+        let Operator::ASAP(ASAPOp::EvaluatePopulation {
             child: population, ..
-        } = &population_readout().expr
+        }) = &population_evaluation().operator
         else {
             unreachable!()
         };
         let state = summary();
-        let SummaryExpr::SummaryAgg {
+        let Operator::ASAP(ASAPOp::SummaryAgg {
             family,
             input,
             reduction,
             grouping,
             ..
-        } = &state.expr
+        }) = &state.operator
         else {
             unreachable!()
         };
-        let state = Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryAgg {
+        let state = Rc::new(OperatorNode {
+            operator: Operator::ASAP(ASAPOp::SummaryAgg {
                 child: Rc::clone(population),
                 family: family.clone(),
                 input: input.clone(),
                 reduction: reduction.clone(),
                 grouping: grouping.clone(),
                 filter: None,
-            },
+            }),
             ..state.as_ref().clone()
         });
         let data = continuous(1_000, 60_000);
         let workload = workload(vec![], vec![repeating()], data.clone());
         let timed = |lifecycle: SummaryMaintenanceLifecycle| {
             population_timings(&timed_dag(
-                readout(&state),
+                evaluation(&state),
                 &workload,
                 &data,
                 Some(Horizon(10.0)),
@@ -3717,19 +3780,21 @@ mod tests {
         assert_eq!(
             timed(SummaryMaintenanceLifecycle::ContinuouslyMaintained),
             [
+                ("raw", INGEST),
                 ("raw", INGEST),
                 ("population", INGEST),
                 ("state", INGEST),
-                ("readout", QUERY)
+                ("evaluation", QUERY)
             ]
         );
         assert_eq!(
             timed(SummaryMaintenanceLifecycle::Ephemeral),
             [
+                ("raw", QUERY),
                 ("raw", QUERY),
                 ("population", QUERY),
                 ("state", QUERY),
-                ("readout", QUERY)
+                ("evaluation", QUERY)
             ]
         );
     }
@@ -3739,59 +3804,41 @@ mod tests {
     // timed by the state's lifecycle.
     #[test]
     fn shared_population_follows_its_summary_consumer() {
-        let direct = population_readout();
-        let SummaryExpr::ValueOperation {
+        let direct = population_evaluation();
+        let Operator::ASAP(ASAPOp::EvaluatePopulation {
             child: population, ..
-        } = &direct.expr
+        }) = &direct.operator
         else {
             unreachable!()
         };
         let state = summary();
-        let SummaryExpr::SummaryAgg {
+        let Operator::ASAP(ASAPOp::SummaryAgg {
             family,
             input,
             reduction,
             grouping,
             ..
-        } = &state.expr
+        }) = &state.operator
         else {
             unreachable!()
         };
-        let state = Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryAgg {
+        let state = Rc::new(OperatorNode {
+            operator: Operator::ASAP(ASAPOp::SummaryAgg {
                 child: Rc::clone(population),
                 family: family.clone(),
                 input: input.clone(),
                 reduction: reduction.clone(),
                 grouping: grouping.clone(),
                 filter: None,
-            },
+            }),
             ..state.as_ref().clone()
         });
-        let binary = |lhs: Rc<SummaryNode>, rhs: Rc<SummaryNode>| {
-            Rc::new(SummaryNode {
-                schema: lhs.schema.clone(),
-                expr: SummaryExpr::BinaryOp {
-                    lhs,
-                    rhs,
-                    operator: asap_types::post_asap::BinaryOperator {
-                        kind: asap_types::pre_asap::BinaryOpKind::Arithmetic(
-                            asap_types::pre_asap::ArithmeticOpKind::Add,
-                        ),
-                        vector_match: None,
-                        checked_relative_division: false,
-                        checked_finite_division: false,
-                    },
-                    timing: QUERY,
-                },
-                guarantee: None,
-            })
-        };
+        let binary = test_binary;
         let data = continuous(1_000, 60_000);
         let workload = workload(vec![], vec![repeating()], data.clone());
         for root in [
-            binary(Rc::clone(&direct), readout(&state)),
-            binary(readout(&state), Rc::clone(&direct)),
+            binary(Rc::clone(&direct), evaluation(&state)),
+            binary(evaluation(&state), Rc::clone(&direct)),
         ] {
             for lifecycle in [
                 SummaryMaintenanceLifecycle::ContinuouslyMaintained,
@@ -3830,7 +3877,7 @@ mod tests {
         let data = continuous(1_000, 60_000);
         let workload = workload(vec![], vec![repeating()], data.clone());
         let mut plan = plan_summary_maintenance_lifecycles(
-            population_readout(),
+            population_evaluation(),
             WorkloadDemand::new_with_data(&workload, &data, &[0]),
             1_000,
             Some(Horizon(10.0)),
diff --git a/crates/asap-aware-mapping/src/test_support.rs b/crates/asap-aware-mapping/src/test_support.rs
index 612cf7c0d..b4d0fd99a 100644
--- a/crates/asap-aware-mapping/src/test_support.rs
+++ b/crates/asap-aware-mapping/src/test_support.rs
@@ -1,11 +1,16 @@
-use asap_types::pre_asap::QueryExpr;
+// Shared fixture helpers; not every test module uses every helper.
+#![allow(dead_code)]
+
+use std::rc::Rc;
+
+use asap_types::ir::OperatorNode;
 use asap_types::types::AccuracyTarget;
 use asap_types::workload::{
     AccuracyRequirement, BatchEntry, DataWorkload, DurationMs, Evidence, PlanningWorkload,
     Predictability, Query, QueryLanguage, QueryRequirements, QueryWorkload, TimeSelection,
 };
 
-pub(crate) fn lower_promql(query: &str, accuracy: AccuracyTarget) -> QueryExpr {
+pub(crate) fn lower_promql(query: &str, accuracy: AccuracyTarget) -> Rc<OperatorNode> {
     let workload = PlanningWorkload {
         query_workload: QueryWorkload {
             language: QueryLanguage::PromQL,
@@ -35,3 +40,162 @@ pub(crate) fn lower_promql(query: &str, accuracy: AccuracyTarget) -> QueryExpr {
         .pop()
         .unwrap()
 }
+
+// ── Shared pre-ASAP fixture builders ─────────────────────────────────────
+//
+// Every builder returns an `Rc<OperatorNode>` whose schema is derived by
+// `OperatorNode::new_shared`, so a fixture is exactly what a front end
+// would hand the planner. Added by the test migration; only add here, never
+// rename or remove (several test modules share these).
+
+use std::time::Duration;
+
+use asap_types::ir::operator_properties::{GroupKeys, Reduction, Source};
+use asap_types::ir::timing::{apply_lifecycle_timings, LifecycleAssignment, TimingMemo};
+use asap_types::ir::{NonASAPOp, Predicate, ScalarExpr, TimeRangeKind};
+use asap_types::pre_asap::agg_intent::AggIntent;
+use asap_types::pre_asap::schema::{ColumnId, DataType, Field, Schema};
+
+/// A `TimeSeries("m")` scan over `[ts(0), value(1), labels...]`, time index 0,
+/// no unique key.
+pub(crate) fn metric_scan(labels: &[&str]) -> Rc<OperatorNode> {
+    metric_scan_with_keys(labels, vec![])
+}
+
+/// [`metric_scan`] with explicit `unique_keys` (a `[[0]]` key makes CSE
+/// willing to hoist the scan).
+pub(crate) fn metric_scan_with_keys(
+    labels: &[&str],
+    unique_keys: Vec<Vec<ColumnId>>,
+) -> Rc<OperatorNode> {
+    let mut columns = vec![
+        Field::plain("ts", DataType::Timestamp, false),
+        Field::plain("value", DataType::Float64, false),
+    ];
+    columns.extend(
+        labels
+            .iter()
+            .map(|n| Field::plain(*n, DataType::Utf8, true)),
+    );
+    scan("m", Schema::with_time_index(columns, 0, unique_keys))
+}
+
+/// A predicate-free `TimeSeries(metric)` scan with the given schema.
+pub(crate) fn scan(metric: &str, schema: Schema) -> Rc<OperatorNode> {
+    scan_from(
+        Source::TimeSeries {
+            metric: metric.into(),
+        },
+        schema,
+    )
+}
+
+pub(crate) fn scan_from(source: Source, schema: Schema) -> Rc<OperatorNode> {
+    OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
+        source,
+        predicates: vec![],
+        schema,
+    }))
+    .unwrap()
+}
+
+/// A general aggregate node.
+pub(crate) fn aggregate(
+    reduction: Reduction,
+    measures: Vec<AggIntent>,
+    output_names: Vec<String>,
+    having: Option<Predicate>,
+    child: Rc<OperatorNode>,
+) -> Rc<OperatorNode> {
+    OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+        reduction,
+        measures,
+        output_names,
+        filters: vec![],
+        having,
+        child,
+    }))
+    .unwrap()
+}
+
+/// `intent by (by)` — a single-measure, `HAVING`-free grouped aggregate.
+pub(crate) fn agg(
+    by: Vec<ColumnId>,
+    intent: AggIntent,
+    child: Rc<OperatorNode>,
+) -> Rc<OperatorNode> {
+    aggregate(Reduction::by(by), vec![intent], vec![], None, child)
+}
+
+/// `intent without (excluded)`.
+pub(crate) fn without_agg(
+    excluded: Vec<ColumnId>,
+    intent: AggIntent,
+    child: Rc<OperatorNode>,
+) -> Rc<OperatorNode> {
+    aggregate(
+        Reduction::Reduce(GroupKeys::without(excluded)),
+        vec![intent],
+        vec![],
+        None,
+        child,
+    )
+}
+
+/// A per-entity (per-series) single-measure aggregate.
+pub(crate) fn agg_per_entity(intent: AggIntent, child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+    aggregate(Reduction::PerEntity, vec![intent], vec![], None, child)
+}
+
+pub(crate) fn filter(pred: ScalarExpr, child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+    OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Filter {
+        pred: Predicate(pred),
+        child,
+    }))
+    .unwrap()
+}
+
+pub(crate) fn dedup(cols: Vec<ColumnId>, child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+    OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Dedup {
+        cols,
+        child,
+    }))
+    .unwrap()
+}
+
+/// An explicit range selector `child[range]`.
+pub(crate) fn time_range(range: Duration, child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+    OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::TimeRange {
+        range,
+        kind: TimeRangeKind::Range,
+        child,
+    }))
+    .unwrap()
+}
+
+/// `root` timed under the default (every summary maintained) lifecycle
+/// assignment — the shape export and the post-ASAP validators consume.
+pub(crate) fn timed(root: &Rc<OperatorNode>) -> Rc<OperatorNode> {
+    apply_lifecycle_timings(
+        root,
+        &LifecycleAssignment::default_maintained(),
+        &mut TimingMemo::new(),
+    )
+    .expect("default lifecycle timings apply")
+}
+
+/// Time `root` under the default lifecycle assignment (which runs every
+/// data-state / population-contract check) and export it as a physical ASAP DAG.
+pub(crate) fn time_and_export(
+    root: &Rc<OperatorNode>,
+) -> Result<
+    asap_types::ir::export::PhysicalASAPDAG,
+    asap_types::post_asap::execution_data_state::ExecutionDataStateError,
+> {
+    let timed = apply_lifecycle_timings(
+        root,
+        &LifecycleAssignment::default_maintained(),
+        &mut TimingMemo::new(),
+    )?;
+    asap_types::ir::export::compile_physical_asap_dag(&timed)
+}
diff --git a/crates/asap-aware-mapping/src/topk_reuse.rs b/crates/asap-aware-mapping/src/topk_reuse.rs
index 8329569d1..aec95292a 100644
--- a/crates/asap-aware-mapping/src/topk_reuse.rs
+++ b/crates/asap-aware-mapping/src/topk_reuse.rs
@@ -7,7 +7,7 @@
 
 use std::rc::Rc;
 
-use asap_types::pre_asap::QueryExpr;
+use asap_types::ir::{NonASAPOp, OperatorNode};
 
 use crate::replacement::{
     Replacement, ReplacementProvenance, ReplacementStrategy, ReplacementSubDAG, TargetSubDAG,
@@ -15,22 +15,23 @@ use crate::replacement::{
 
 /// Derives a smaller top-k result from a compatible larger top-k sibling.
 pub struct TopKLimitReuseStrategy {
-    limits: Vec<Rc<QueryExpr>>,
+    limits: Vec<Rc<OperatorNode>>,
 }
 
 impl TopKLimitReuseStrategy {
-    pub fn new(limits: &[Rc<QueryExpr>]) -> Self {
+    pub fn new(limits: &[Rc<OperatorNode>]) -> Self {
         Self {
             limits: limits.to_vec(),
         }
     }
 
-    fn larger_sources<'a>(&'a self, target: &TargetSubDAG<'_>) -> Vec<&'a Rc<QueryExpr>> {
-        let QueryExpr::Limit {
-            n: target_n,
+    fn larger_sources<'a>(&'a self, target: &TargetSubDAG<'_>) -> Vec<&'a Rc<OperatorNode>> {
+        let Some(NonASAPOp::Limit {
+            n: Some(target_n),
             offset: 0,
             child: target_child,
-        } = target.root.as_ref()
+            ..
+        }) = target.root.non_asap()
         else {
             return Vec::new();
         };
@@ -42,11 +43,12 @@ impl TopKLimitReuseStrategy {
                 if Rc::ptr_eq(candidate, target.root) {
                     return false;
                 }
-                let QueryExpr::Limit {
-                    n,
+                let Some(NonASAPOp::Limit {
+                    n: Some(n),
                     offset: 0,
                     child,
-                } = candidate.as_ref()
+                    ..
+                }) = candidate.non_asap()
                 else {
                     return false;
                 };
@@ -56,8 +58,8 @@ impl TopKLimitReuseStrategy {
             .collect();
         // Prefer the smallest sufficient materialized top-k when several
         // larger siblings are available.
-        sources.sort_by_key(|source| match source.as_ref() {
-            QueryExpr::Limit { n, .. } => *n,
+        sources.sort_by_key(|source| match source.non_asap() {
+            Some(NonASAPOp::Limit { n: Some(n), .. }) => *n,
             _ => unreachable!(),
         });
         sources
@@ -70,34 +72,38 @@ impl ReplacementStrategy for TopKLimitReuseStrategy {
     }
 
     fn replacements(&self, target: &TargetSubDAG<'_>) -> Vec<ReplacementSubDAG> {
-        let QueryExpr::Limit {
-            n: target_n,
+        let Some(NonASAPOp::Limit {
+            n: Some(target_n),
             offset: 0,
+            partition_by,
             ..
-        } = target.root.as_ref()
+        }) = target.root.non_asap()
         else {
             return Vec::new();
         };
 
         self.larger_sources(target)
             .into_iter()
-            .map(|source| {
-                let source_n = match source.as_ref() {
-                    QueryExpr::Limit { n, .. } => *n,
+            .filter_map(|source| {
+                let source_n = match source.non_asap() {
+                    Some(NonASAPOp::Limit { n: Some(n), .. }) => *n,
                     _ => unreachable!(),
                 };
-                ReplacementSubDAG {
+                let rewritten = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Limit {
+                    n: Some(*target_n),
+                    offset: 0,
+                    partition_by: partition_by.clone(),
+                    child: Rc::clone(source),
+                }))
+                .ok()?;
+                Some(ReplacementSubDAG {
                     strategy: "TopKLimitReuseStrategy",
-                    replacement: Replacement::Rewrite(Rc::new(QueryExpr::Limit {
-                        n: *target_n,
-                        offset: 0,
-                        child: Rc::clone(source),
-                    })),
+                    replacement: Replacement::SubDAG(rewritten),
                     provenance: ReplacementProvenance::LogicalRewrite,
                     rationale: format!(
                         "derives top-{target_n} from the compatible shared top-{source_n} result; both rank the identical input with the same ordering"
                     ),
-                }
+                })
             })
             .collect()
     }
@@ -106,38 +112,39 @@ impl ReplacementStrategy for TopKLimitReuseStrategy {
 #[cfg(test)]
 mod tests {
     use super::*;
-    use asap_types::pre_asap::{Schema, Source};
+    use crate::test_support::scan;
+    use asap_types::ir::operator_properties::GroupKeys;
+    use asap_types::pre_asap::Schema;
 
-    fn scan_named(metric: &str) -> Rc<QueryExpr> {
-        Rc::new(QueryExpr::Scan {
-            source: Source::TimeSeries {
-                metric: metric.into(),
-            },
-            predicates: vec![],
-            schema: Schema::with_time_index(vec![], 0, vec![]),
-        })
+    fn scan_named(metric: &str) -> Rc<OperatorNode> {
+        scan(metric, Schema::with_time_index(vec![], 0, vec![]))
+    }
+
+    fn limit(n: usize, offset: usize, child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Limit {
+            n: Some(n),
+            offset,
+            partition_by: GroupKeys::none(),
+            child,
+        }))
+        .unwrap()
     }
 
     #[test]
     fn smaller_limit_reuses_larger_compatible_limit() {
         let child = scan_named("m");
-        let small = Rc::new(QueryExpr::Limit {
-            n: 5,
-            offset: 0,
-            child: Rc::clone(&child),
-        });
-        let large = Rc::new(QueryExpr::Limit {
-            n: 10,
-            offset: 0,
-            child,
-        });
+        let small = limit(5, 0, Rc::clone(&child));
+        let large = limit(10, 0, child);
         let strategy = TopKLimitReuseStrategy::new(&[Rc::clone(&small), Rc::clone(&large)]);
         let replacements = strategy.replacements(&TargetSubDAG::new(&small));
         assert_eq!(replacements.len(), 1);
-        let Replacement::Rewrite(rewrite) = &replacements[0].replacement else {
+        let Replacement::SubDAG(rewrite) = &replacements[0].replacement else {
             panic!()
         };
-        let QueryExpr::Limit { n: 5, child, .. } = rewrite.as_ref() else {
+        let Some(NonASAPOp::Limit {
+            n: Some(5), child, ..
+        }) = rewrite.non_asap()
+        else {
             panic!()
         };
         assert!(Rc::ptr_eq(child, &large));
@@ -147,21 +154,9 @@ mod tests {
     fn offset_or_different_input_is_not_reused() {
         let a = scan_named("a");
         let b = scan_named("b");
-        let small = Rc::new(QueryExpr::Limit {
-            n: 5,
-            offset: 0,
-            child: a,
-        });
-        let large = Rc::new(QueryExpr::Limit {
-            n: 10,
-            offset: 0,
-            child: b,
-        });
-        let offset = Rc::new(QueryExpr::Limit {
-            n: 20,
-            offset: 1,
-            child: scan_named("a"),
-        });
+        let small = limit(5, 0, a);
+        let large = limit(10, 0, b);
+        let offset = limit(20, 1, scan_named("a"));
         let strategy = TopKLimitReuseStrategy::new(&[Rc::clone(&small), large, offset]);
         assert!(!strategy.matches(&TargetSubDAG::new(&small)));
     }
diff --git a/crates/asap-aware-mapping/tests/physical_handoff_cost.rs b/crates/asap-aware-mapping/tests/physical_handoff_cost.rs
index a8a9ed42d..141750f61 100644
--- a/crates/asap-aware-mapping/tests/physical_handoff_cost.rs
+++ b/crates/asap-aware-mapping/tests/physical_handoff_cost.rs
@@ -5,7 +5,7 @@ use asap_aware_mapping::analytical_cost::{
 use asap_aware_mapping::physical_operator_statistics::{
     ComparisonScope, EdgeStatistics, OperatorStatistics, ScanSelection, UnaryEdgeStatistics,
 };
-use asap_types::pre_asap::query_expr::Source;
+use asap_types::ir::operator_properties::Source;
 use asap_types::workload::{
     DataArrival, DurationMs, QueryRecurrence, QueryTimeScope, TimeSelection, TimestampMs,
 };
diff --git a/crates/asap-aware-mapping/tests/storage_io.rs b/crates/asap-aware-mapping/tests/storage_io.rs
index e9290d20a..811328f6b 100644
--- a/crates/asap-aware-mapping/tests/storage_io.rs
+++ b/crates/asap-aware-mapping/tests/storage_io.rs
@@ -5,7 +5,7 @@ use asap_aware_mapping::analytical_cost::{
 use asap_aware_mapping::physical_operator_statistics::{
     ComparisonScope, EdgeStatistics, OperatorStatistics, ScanSelection, UnaryEdgeStatistics,
 };
-use asap_types::pre_asap::query_expr::Source;
+use asap_types::ir::operator_properties::Source;
 use asap_types::workload::{
     DataArrival, DurationMs, QueryRecurrence, QueryTimeScope, TimeSelection, TimestampMs,
 };
diff --git a/crates/asap-physical-operators/README.md b/crates/asap-physical-operators/README.md
index 2d3e7b569..b15154b4a 100644
--- a/crates/asap-physical-operators/README.md
+++ b/crates/asap-physical-operators/README.md
@@ -14,7 +14,7 @@ thread pool. Poll multiple root streams concurrently when they share inputs.
 
 `operators::Operator` implements native batch sources, scalar values,
 projection, filtering, grouped exact aggregation, semi-join, grouped Sort and
-Limit, vector-to-scalar conversion, Union, and summary construction/merge/readout.
+Limit, vector-to-scalar conversion, Union, and summary construction/merge/evaluation.
 Sort followed by Limit implements grouped ranking; no dedicated TopK physical
 operator is needed. Summary construction updates state batch by batch. End of
 input means the supplied query range or ingestion window is complete.
@@ -47,7 +47,7 @@ assert!(matches!(batch.rows()[0][0], Value::Int64(-7)));
 # Ok::<(), asap_physical_operators::dag::Error>(())
 ```
 
-`physical_planner::compile` accepts a logical Post-ASAP DAG (`PostAsapDAG`) and typed input contracts.
+`physical_planner::compile` accepts a logical Post-ASAP DAG (`PhysicalASAPDAG`) and typed input contracts.
 The resulting candidate is instantiated with deployment readers after selection. It rejects unsupported operations and
 schema mismatches before starting a source. Implement `PhysicalOperator` for a
 deployment source, including asynchronous I/O; computation operators remain in
@@ -59,7 +59,7 @@ Plain values preserve Planner scalar/collection types and nullability. Numeric
 arithmetic uses matching Int64 or Float64 inputs; integer overflow is an error.
 Boolean predicates use three-valued logic. Native summary states currently cover
 exact Sum/Count/Min/Max/Rate/Increase, KLL, DDSketch, HLL and Float64 weighted CMS and CountSketch with candidate heaps. Binding checks family,
-parameters and readout compatibility; source batches also validate state payloads.
+parameters and evaluation compatibility; source batches also validate state payloads.
 Existing accumulator algorithms are reused as kernels behind these operators.
 
 This crate is owned by ASAPPlanner. Its `planner-types` dependency is the local
@@ -78,9 +78,9 @@ See [the design](../../docs/design_docs/physical-planning-and-deployment.md).
 - `operators`: projection, filter, joins, aggregate/window, sort, limit and summary implementations.
 - `sources`: raw-source interface, Scan and the memory connector.
 - `physical_planner`: native operator lowering, typed input contracts and checked instantiation.
-- `summary_kernels`: in-memory summary state over `asap_sketchlib` and exact Planner state: merge, typed readout and update adapters.
-- `readout`: readouts over merged exact summary states.
-- `capability`: explicit kernel, native-batch and typed readout validation.
+- `summary_kernels`: in-memory summary state over `asap_sketchlib` and exact Planner state: merge, typed evaluation and update adapters.
+- `evaluation`: evaluations over merged exact summary states.
+- `capability`: explicit kernel, native-batch and typed evaluation validation.
 
 The `dag`, `factory`, `traits` and `arithmetic` paths are re-exports. They contain no alternative
 execution implementations.
@@ -104,7 +104,7 @@ There is no spill or partitioned parallel execution in this implementation.
 
 ## Physical compilation and deployment inputs
 
-`physical_planner::compile` accepts a Planner `PostAsapDAG`, typed
+`physical_planner::compile` accepts a Planner `PhysicalASAPDAG`, typed
 `InputContract`s and output roots. It returns a reusable `CompiledPhysicalDAG`
 containing selected native operators and no live readers. Compilation validates
 schemas, input ordering, sharing and boundedness before deployment source access.
diff --git a/crates/asap-physical-operators/src/capability.rs b/crates/asap-physical-operators/src/capability.rs
index 5ed1c5501..8bdb1891e 100644
--- a/crates/asap-physical-operators/src/capability.rs
+++ b/crates/asap-physical-operators/src/capability.rs
@@ -2,22 +2,22 @@
 //!
 //! `validate_summary_kernel` checks update kernels, including families without a
 //! native batch representation. `validate_native_family` and
-//! `validate_sketch_readout` / `validate_exact_readout` check native state and readout support.
-//! Keyed weighted-frequency readouts are checked by `Operator::keyed_readout`.
+//! `validate_sketch_evaluation` / `validate_exact_evaluation` check native state and evaluation support.
+//! Keyed weighted-frequency evaluations are checked by `Operator::keyed_evaluation`.
 //! A successful kernel check alone does not mean a physical DAG will bind.
 //!
 //! Stored-state encodings belong to deployments. Full plan acceptance is
 //! owned by `binding`, which also validates schemas, expressions and inputs.
 use crate::Error;
 use planner_types::post_asap::{
-    ExactKind, ExactParams, FieldDataType, GroupingStrategy, SketchAlgorithm, SketchParams,
-    SketchStatistic, SummaryUpdate,
+    ExactKind, ExactParams, FieldDataType as SummaryFamilyType, GroupingStrategy, SketchAlgorithm,
+    SketchParams, SketchStatistic, SummaryUpdate,
 };
 
 /// Check the same contract used by `create_planner_accumulator` before a plan
 /// is accepted. Execution timing is deliberately not a kernel property.
 pub fn validate_summary_kernel(
-    family: &FieldDataType,
+    family: &SummaryFamilyType,
     input: &SummaryUpdate,
     grouping: &GroupingStrategy,
 ) -> Result<(), String> {
@@ -25,7 +25,7 @@ pub fn validate_summary_kernel(
         return Err("shared summary grouping has no registered kernel".into());
     }
     let keyed = match family {
-        FieldDataType::ExactAggregate(kind, params) => {
+        SummaryFamilyType::ExactAggregate(kind, params) => {
             use ExactKind as K;
             use ExactParams as P;
             if !matches!(
@@ -41,7 +41,7 @@ pub fn validate_summary_kernel(
             }
             input.item.is_some()
         }
-        FieldDataType::Sketch(kind, layout) => {
+        SummaryFamilyType::Sketch(kind, layout) => {
             if layout != grouping {
                 return Err("Planner family and operator grouping disagree".into());
             }
@@ -138,9 +138,9 @@ pub(crate) fn is_unit_sample_frequency(update: &planner_types::post_asap::Summar
         )
 }
 
-pub fn validate_native_family(family: &FieldDataType) -> Result<(), Error> {
+pub fn validate_native_family(family: &SummaryFamilyType) -> Result<(), Error> {
     use planner_types::post_asap::SketchAlgorithm as A;
-    if let FieldDataType::Sketch(kind, grouping) = family {
+    if let SummaryFamilyType::Sketch(kind, grouping) = family {
         // Plain Count-Min is native as stored state only: it merges and reads
         // its bare count, but the DAG does not build it from rows.
         if let (A::Cms, SketchParams::Cms { width, depth }) = (kind.algorithm(), kind.params()) {
@@ -165,8 +165,8 @@ pub fn validate_native_family(family: &FieldDataType) -> Result<(), Error> {
         }
     }
     match family {
-        FieldDataType::ExactAggregate(..) => {}
-        FieldDataType::Sketch(kind, _)
+        SummaryFamilyType::ExactAggregate(..) => {}
+        SummaryFamilyType::Sketch(kind, _)
             if matches!(kind.algorithm(), A::Kll | A::DDSketch | A::Hll) => {}
         _ => {
             return Err(Error::Invalid(
@@ -184,9 +184,9 @@ pub fn validate_native_family(family: &FieldDataType) -> Result<(), Error> {
     .map_err(Error::Invalid)
 }
 
-/// A sketch readout is native only for the families Planner can read directly.
-pub fn validate_sketch_readout(
-    family: &FieldDataType,
+/// A sketch evaluation is native only for the families Planner can read directly.
+pub fn validate_sketch_evaluation(
+    family: &SummaryFamilyType,
     query: &SketchStatistic,
 ) -> Result<(), Error> {
     validate_native_family(family)?;
@@ -194,12 +194,12 @@ pub fn validate_sketch_readout(
     // A point count without an item value reads the total count.
     let bare_count = matches!(query, SketchStatistic::PointCount { value: None, .. });
     let supported = match family {
-        FieldDataType::Sketch(kind, _) => match (kind.algorithm(), query) {
+        SummaryFamilyType::Sketch(kind, _) => match (kind.algorithm(), query) {
             (A::Kll, SketchStatistic::Quantile { q })
             | (A::DDSketch, SketchStatistic::Quantile { q }) => {
                 if !(0.0..=1.0).contains(q) {
                     return Err(Error::Invalid(
-                        "quantile readout requires quantile in [0,1]".into(),
+                        "quantile evaluation requires quantile in [0,1]".into(),
                     ));
                 }
                 true
@@ -208,7 +208,7 @@ pub fn validate_sketch_readout(
             (A::Hll, SketchStatistic::Cardinality) => true,
             (A::Hll, _) => bare_count,
             // Only count intents read a Count-Min bare count, and their
-            // updates have unit weight; the readout is typed Int64 on that basis.
+            // updates have unit weight; the evaluation is typed Int64 on that basis.
             (A::Cms, _) => bare_count,
             _ => false,
         },
@@ -216,36 +216,39 @@ pub fn validate_sketch_readout(
     };
     if !supported {
         return Err(Error::Invalid(
-            "readout is not implemented for this summary family".into(),
+            "evaluation is not implemented for this summary family".into(),
         ));
     }
     Ok(())
 }
 
-/// An exact readout must match the exact family it reads.
-pub fn validate_exact_readout(
-    family: &FieldDataType,
-    readout: &crate::summary_kernels::exact::ExactReadout,
+/// An exact evaluation must match the exact family it reads.
+pub fn validate_exact_evaluation(
+    family: &SummaryFamilyType,
+    evaluation: &crate::summary_kernels::exact::ExactEvaluation,
 ) -> Result<(), Error> {
     validate_native_family(family)?;
     use crate::Statistic as S;
     use planner_types::post_asap::ExactKind as E;
     let supported = matches!(
-        (family, readout.statistic),
-        (FieldDataType::ExactAggregate(E::Sum, _), S::Sum)
-            | (FieldDataType::ExactAggregate(E::Count, _), S::Count)
-            | (FieldDataType::ExactAggregate(E::Min, _), S::Min)
-            | (FieldDataType::ExactAggregate(E::Max, _), S::Max)
-            | (FieldDataType::ExactAggregate(E::Rate, _), S::Rate)
-            | (FieldDataType::ExactAggregate(E::Increase, _), S::Increase)
+        (family, evaluation.statistic),
+        (SummaryFamilyType::ExactAggregate(E::Sum, _), S::Sum)
+            | (SummaryFamilyType::ExactAggregate(E::Count, _), S::Count)
+            | (SummaryFamilyType::ExactAggregate(E::Min, _), S::Min)
+            | (SummaryFamilyType::ExactAggregate(E::Max, _), S::Max)
+            | (SummaryFamilyType::ExactAggregate(E::Rate, _), S::Rate)
+            | (
+                SummaryFamilyType::ExactAggregate(E::Increase, _),
+                S::Increase
+            )
     );
     if !supported {
         return Err(Error::Invalid(
-            "readout is not implemented for this summary family".into(),
+            "evaluation is not implemented for this summary family".into(),
         ));
     }
-    if readout.lookback_ms.is_some_and(|lookback| {
-        lookback <= 0 || !matches!(readout.statistic, S::Rate | S::Increase)
+    if evaluation.lookback_ms.is_some_and(|lookback| {
+        lookback <= 0 || !matches!(evaluation.statistic, S::Rate | S::Increase)
     }) {
         return Err(Error::Invalid("invalid exact counter lookback".into()));
     }
diff --git a/crates/asap-physical-operators/src/evaluation.rs b/crates/asap-physical-operators/src/evaluation.rs
new file mode 100644
index 000000000..843145ce2
--- /dev/null
+++ b/crates/asap-physical-operators/src/evaluation.rs
@@ -0,0 +1,111 @@
+//! Evaluations over merged exact summary states.
+use crate::summary_kernels::exact::ExactAccumulator;
+use crate::{AggregateCore, KeyByLabelValues, Statistic};
+use std::sync::Arc;
+
+fn merge_exact_states(
+    states: impl IntoIterator<Item = Arc<dyn AggregateCore>>,
+) -> Result<ExactAccumulator, String> {
+    let mut states = states.into_iter();
+    let exact = |state: &Arc<dyn AggregateCore>| {
+        state
+            .as_any()
+            .downcast_ref::<ExactAccumulator>()
+            .cloned()
+            .ok_or_else(|| "evaluation requires Planner exact state".to_string())
+    };
+    let mut merged = exact(&states.next().ok_or("empty exact state input")?)?;
+    for state in states {
+        merged
+            .merge_from(&exact(&state)?)
+            .map_err(|error| error.to_string())?;
+    }
+    Ok(merged)
+}
+
+/// PromQL counter evaluations omit a series with fewer than two samples. Other
+/// state/type/range failures remain errors rather than empty results.
+pub fn insufficient_counter_samples(state: &dyn AggregateCore, statistic: Statistic) -> bool {
+    matches!(statistic, Statistic::Rate | Statistic::Increase)
+        && state
+            .as_any()
+            .downcast_ref::<ExactAccumulator>()
+            .is_some_and(|state| state.insufficient_counter_samples(statistic, &None))
+}
+
+/// Merge already selected exact panes and read one population. `None` means
+/// the population is absent from the result: a counter with too few samples,
+/// or an empty MIN/MAX.
+pub fn exact_evaluation(
+    states: impl IntoIterator<Item = Arc<dyn AggregateCore>>,
+    statistic: Statistic,
+    range_ms: Option<(i64, i64)>,
+    key: Option<&KeyByLabelValues>,
+) -> Result<Option<f64>, String> {
+    let merged = merge_exact_states(states)?;
+    if merged.insufficient_counter_samples(statistic, &key.cloned()) {
+        return Ok(None);
+    }
+    merged
+        .evaluation(statistic, range_ms, key)
+        .map_err(|error| error.to_string())
+}
+
+#[cfg(test)]
+mod counter_tests {
+    use super::*;
+    use planner_types::post_asap::{ExactKind, ExactParams, FieldDataType as SummaryFamilyType};
+
+    fn counter(kind: ExactKind, params: ExactParams, keyed: bool) -> ExactAccumulator {
+        ExactAccumulator::new(SummaryFamilyType::ExactAggregate(kind, params), keyed).unwrap()
+    }
+
+    // A counter population with a single sample is absent, keyed or not.
+    #[test]
+    fn planner_counter_population_omits_insufficient_samples() {
+        for (kind, params, statistic) in [
+            (ExactKind::Rate, ExactParams::Rate, Statistic::Rate),
+            (
+                ExactKind::Increase,
+                ExactParams::Increase,
+                Statistic::Increase,
+            ),
+        ] {
+            for keyed in [false, true] {
+                let mut state = counter(kind.clone(), params.clone(), keyed);
+                let key = keyed.then(|| KeyByLabelValues::new_with_labels(vec!["checkout".into()]));
+                state.update(key.as_ref(), 10., 10_000);
+                assert_eq!(
+                    exact_evaluation(
+                        [Arc::new(state) as Arc<dyn AggregateCore>],
+                        statistic,
+                        None,
+                        key.as_ref()
+                    )
+                    .unwrap(),
+                    None
+                );
+            }
+        }
+    }
+
+    // Two ordered samples read a rate; an inverted range and empty input fail.
+    #[test]
+    fn sparse_counter_is_absent_but_invalid_ranges_still_fail() {
+        let mut state = counter(ExactKind::Rate, ExactParams::Rate, false);
+        state.update(None, 10., 10_000);
+        let rate = Statistic::Rate;
+        let one = [Arc::new(state.clone()) as Arc<dyn AggregateCore>];
+        assert_eq!(
+            exact_evaluation(one, rate, Some((0, 60_000)), None).unwrap(),
+            None
+        );
+        state.update(None, 20., 20_000);
+        let two = || [Arc::new(state.clone()) as Arc<dyn AggregateCore>];
+        assert!(exact_evaluation(two(), rate, Some((0, 60_000)), None)
+            .unwrap()
+            .is_some());
+        assert!(exact_evaluation(two(), rate, Some((60_000, 0)), None).is_err());
+        assert!(exact_evaluation([], rate, Some((0, 60_000)), None).is_err());
+    }
+}
diff --git a/crates/asap-physical-operators/src/expressions/arithmetic.rs b/crates/asap-physical-operators/src/expressions/arithmetic.rs
index e0766763d..64dbb8301 100644
--- a/crates/asap-physical-operators/src/expressions/arithmetic.rs
+++ b/crates/asap-physical-operators/src/expressions/arithmetic.rs
@@ -20,12 +20,13 @@ pub fn evaluate_float64_arithmetic(
 
 /// Execute the Planner binary contract after a deployment has resolved matching rows.
 pub fn evaluate_binary(
-    operator: &planner_types::post_asap::BinaryOperator,
+    operator: &crate::expressions::binary::BinaryOperator,
     left: f64,
     right: f64,
 ) -> Result<crate::values::Value, crate::Error> {
+    use crate::expressions::binary::BinaryOpKind;
     use crate::{values::Value, Error};
-    use planner_types::pre_asap::{ArithmeticOpKind, BinaryOpKind};
+    use planner_types::pre_asap::ArithmeticOpKind;
     let invalid =
         || Error::Invalid("unsupported binary operation or invalid checked-division domain".into());
     if operator.vector_match.is_some() {
diff --git a/crates/asap-physical-operators/src/expressions/binary.rs b/crates/asap-physical-operators/src/expressions/binary.rs
index c115fd908..81c1c2656 100644
--- a/crates/asap-physical-operators/src/expressions/binary.rs
+++ b/crates/asap-physical-operators/src/expressions/binary.rs
@@ -1,3 +1,35 @@
-//! Temporary kernel aliases during the unified compiler migration.
-pub use planner_types::post_asap::BinaryOperator;
-pub use planner_types::pre_asap::BinaryOpKind;
+//! Execution configuration for a binary kernel, including comparison evaluation mode.
+use planner_types::pre_asap::{
+    ArithmeticOpKind, CompareOpKind, PromQLVectorSetOpKind, VectorMatch,
+};
+#[derive(Debug, Clone, PartialEq, serde::Serialize, serde::Deserialize)]
+pub enum BinaryOpKind {
+    Arithmetic(ArithmeticOpKind),
+    Compare(CompareOpKind),
+    CompareBool(CompareOpKind),
+    Set(PromQLVectorSetOpKind),
+}
+#[derive(Debug, Clone, PartialEq, serde::Serialize, serde::Deserialize)]
+pub struct BinaryOperator {
+    pub kind: BinaryOpKind,
+    pub vector_match: Option<VectorMatch>,
+    pub checked_relative_division: bool,
+    pub checked_finite_division: bool,
+}
+impl BinaryOperator {
+    pub fn from_logical(operator: &planner_types::ir::BinaryOperator, return_bool: bool) -> Self {
+        use planner_types::pre_asap::BinaryOpKind as L;
+        Self {
+            kind: match &operator.kind {
+                L::Arithmetic(op) => BinaryOpKind::Arithmetic(op.clone()),
+                L::Compare(op) if return_bool => BinaryOpKind::CompareBool(op.clone()),
+                L::Compare(op) => BinaryOpKind::Compare(op.clone()),
+                L::CompareBool(op) => BinaryOpKind::CompareBool(op.clone()),
+                L::Set(op) => BinaryOpKind::Set(op.clone()),
+            },
+            vector_match: operator.vector_match.clone(),
+            checked_relative_division: operator.checked_relative_division,
+            checked_finite_division: operator.checked_finite_division,
+        }
+    }
+}
diff --git a/crates/asap-physical-operators/src/expressions/mod.rs b/crates/asap-physical-operators/src/expressions/mod.rs
index 5c1a29576..aad035516 100644
--- a/crates/asap-physical-operators/src/expressions/mod.rs
+++ b/crates/asap-physical-operators/src/expressions/mod.rs
@@ -7,17 +7,15 @@ use planner_types::pre_asap::{ArithmeticOpKind, DataType};
 pub mod arithmetic;
 pub mod binary;
 mod planner;
-pub mod unified_planner;
 pub use planner::CompiledExpression;
 #[derive(serde::Serialize, serde::Deserialize, Clone, Debug)]
 pub enum Expression {
     Binary {
-        operator: planner_types::post_asap::BinaryOperator,
+        operator: crate::expressions::binary::BinaryOperator,
         left: Box<Expression>,
         right: Box<Expression>,
     },
     Planner(Box<crate::expressions::CompiledExpression>),
-    UnifiedPlanner(Box<unified_planner::CompiledExpression>),
     Column(usize),
     ExactFloat64(usize),
     FiniteFloat64(Box<Expression>),
@@ -56,9 +54,6 @@ pub enum Expression {
     IsNull(Box<Expression>),
 }
 impl Expression {
-    pub fn unified_planner(expression: unified_planner::CompiledExpression) -> Self {
-        Self::UnifiedPlanner(Box::new(expression))
-    }
     pub fn planner(expression: crate::expressions::CompiledExpression) -> Self {
         Self::Planner(Box::new(expression))
     }
@@ -70,7 +65,8 @@ impl Expression {
                 left,
                 right,
             } => {
-                use planner_types::pre_asap::{BinaryOpKind, CompareOpKind};
+                use crate::expressions::binary::BinaryOpKind;
+                use planner_types::pre_asap::CompareOpKind;
                 let (a, n) = left.dtype(input)?;
                 let (b, m) = right.dtype(input)?;
                 if a != DataType::Float64 || b != a || operator.vector_match.is_some() {
@@ -105,10 +101,6 @@ impl Expression {
                 };
                 Ok((dtype, n || m))
             }
-            UnifiedPlanner(expression) => {
-                expression.validate_input(input)?;
-                Ok(expression.dtype())
-            }
             Planner(expression) => {
                 expression.validate_input(input)?;
                 Ok(expression.dtype())
@@ -296,7 +288,6 @@ impl Expression {
                 }
             }
             Planner(expression) => expression.evaluate(row)?,
-            UnifiedPlanner(expression) => expression.evaluate(row)?,
             Label { column, name } => {
                 let Value::Map(entries) = &row[*column] else {
                     return Err(invalid("label read requires a map"));
diff --git a/crates/asap-physical-operators/src/expressions/planner.rs b/crates/asap-physical-operators/src/expressions/planner.rs
index 2044d6e16..99f4c2b89 100644
--- a/crates/asap-physical-operators/src/expressions/planner.rs
+++ b/crates/asap-physical-operators/src/expressions/planner.rs
@@ -3,20 +3,22 @@ use crate::{
     values::{SchemaRef, Value},
     Error,
 };
-use planner_types::pre_asap::{ArithmeticOpKind, CompareOpKind, DataType, QueryExpr, ScalarValue};
+use planner_types::pre_asap::{ArithmeticOpKind, CompareOpKind, DataType, ScalarValue};
+
+use planner_types::ir::ScalarExpr;
 use std::{cmp::Ordering, sync::Arc};
 
 pub(super) fn evaluate(
-    expr: &QueryExpr,
+    expr: &ScalarExpr,
     row: &[Value],
     schema: &planner_types::pre_asap::Schema,
 ) -> Result<Value, Error> {
     match expr {
-        QueryExpr::Column(index) => row.get(*index).cloned().ok_or(Error::Invalid(format!(
+        ScalarExpr::Column(index) => row.get(*index).cloned().ok_or(Error::Invalid(format!(
             "column {index} outside row width {}",
             row.len()
         ))),
-        QueryExpr::Literal(value) => Ok(match value {
+        ScalarExpr::Literal(value) => Ok(match value {
             ScalarValue::Interval {
                 months,
                 days,
@@ -32,18 +34,62 @@ pub(super) fn evaluate(
             ScalarValue::Boolean(value) => Value::Bool(*value),
             ScalarValue::Null => Value::Null,
         }),
-        QueryExpr::Compare { left, op, right } => {
+        ScalarExpr::Cast { expr, to, .. } => {
+            let value = evaluate(expr, row, schema)?;
+            match (value, to) {
+                (Value::Null, _) => Ok(Value::Null),
+                (Value::Int64(value), DataType::Float64) => Ok(Value::Float64(value as f64)),
+                (value, _)
+                    if expr
+                        .scalar_type(schema)
+                        .map_err(|e| Error::Invalid(e.to_string()))?
+                        .0
+                        == *to =>
+                {
+                    Ok(value)
+                }
+                _ => Err(Error::Invalid("unsupported cast".into())),
+            }
+        }
+        ScalarExpr::Negative { expr, .. } => match evaluate(expr, row, schema)? {
+            Value::Float64(v) => Ok(Value::Float64(-v)),
+            Value::Int64(v) => v
+                .checked_neg()
+                .map(Value::Int64)
+                .ok_or_else(|| Error::Invalid("integer negation overflow".into())),
+            Value::Null => Ok(Value::Null),
+            _ => Err(Error::Invalid("invalid negation input".into())),
+        },
+        ScalarExpr::Compare {
+            left, op, right, ..
+        } => {
             let left = evaluate(left, row, schema)?;
             let right = evaluate(right, row, schema)?;
             compare(op, left, right)
         }
-        QueryExpr::Arithmetic { op, left, right } => arithmetic(
+        ScalarExpr::Arithmetic {
+            op, left, right, ..
+        } => arithmetic(
             op,
             evaluate(left, row, schema)?,
             evaluate(right, row, schema)?,
         ),
-        QueryExpr::BoolAnd(parts) | QueryExpr::BoolOr(parts) => {
-            let and = matches!(expr, QueryExpr::BoolAnd(_));
+        ScalarExpr::Case {
+            operand: None,
+            branches,
+            else_expr,
+        } => {
+            for (condition, value) in branches {
+                if matches!(evaluate(condition, row, schema)?, Value::Bool(true)) {
+                    return evaluate(value, row, schema);
+                }
+            }
+            else_expr
+                .as_ref()
+                .map_or(Ok(Value::Null), |e| evaluate(e, row, schema))
+        }
+        ScalarExpr::BoolAnd(parts) | ScalarExpr::BoolOr(parts) => {
+            let and = matches!(expr, ScalarExpr::BoolAnd(_));
             let mut null = false;
             for part in parts {
                 match evaluate(part, row, schema)? {
@@ -55,21 +101,44 @@ pub(super) fn evaluate(
             }
             Ok(if null { Value::Null } else { Value::Bool(and) })
         }
-        QueryExpr::Not(value) => match evaluate(value, row, schema)? {
+        ScalarExpr::Not(value) => match evaluate(value, row, schema)? {
             Value::Bool(value) => Ok(Value::Bool(!value)),
             Value::Null => Ok(Value::Null),
             _ => Err(Error::Invalid("boolean predicate required".into())),
         },
-        QueryExpr::IsNull(value) => Ok(Value::Bool(matches!(
+        ScalarExpr::IsNull(value) => Ok(Value::Bool(matches!(
             evaluate(value, row, schema)?,
             Value::Null
         ))),
-        QueryExpr::IsNotNull(value) => Ok(Value::Bool(!matches!(
+        ScalarExpr::IsNotNull(value) => Ok(Value::Bool(!matches!(
             evaluate(value, row, schema)?,
             Value::Null
         ))),
-        QueryExpr::FunctionCall { name, args } => {
+        ScalarExpr::FunctionCall { name, args } => {
             use planner_types::pre_asap::scalar_type_rules::MapScalarFunction;
+            if planner_types::pre_asap::scalar_type_rules::promql_function_arity(name).is_some() {
+                let values = args
+                    .iter()
+                    .map(|arg| match evaluate(arg, row, schema)? {
+                        Value::Float64(v) => Ok(v),
+                        _ => Err(Error::Invalid("PromQL function requires floats".into())),
+                    })
+                    .collect::<Result<Vec<_>, _>>()?;
+                return Ok(Value::Float64(promql_function(name, &values)?));
+            }
+            if name == "promql_drop_metric_name" {
+                let Value::Utf8(encoded) = evaluate(&args[0], row, schema)? else {
+                    return Err(Error::Invalid("series identity must be Utf8".into()));
+                };
+                let mut labels: std::collections::BTreeMap<String, String> =
+                    serde_json::from_str(&encoded).map_err(|e| Error::Invalid(e.to_string()))?;
+                labels.remove("__name__");
+                return Ok(Value::Utf8(
+                    serde_json::to_string(&labels)
+                        .map_err(|e| Error::Invalid(e.to_string()))?
+                        .into(),
+                ));
+            }
             if name.eq_ignore_ascii_case("asap_struct_field") {
                 expr.scalar_type(schema)
                     .map_err(|error| Error::Invalid(error.to_string()))?;
@@ -81,10 +150,10 @@ pub(super) fn evaluate(
                     unreachable!()
                 };
                 let offset = match &args[1] {
-                    QueryExpr::Literal(ScalarValue::Int64(index)) => {
+                    ScalarExpr::Literal(ScalarValue::Int64(index)) => {
                         usize::try_from(index - 1).ok()
                     }
-                    QueryExpr::Literal(ScalarValue::Utf8(name)) => {
+                    ScalarExpr::Literal(ScalarValue::Utf8(name)) => {
                         fields.iter().position(|field| &field.name == name)
                     }
                     _ => None,
@@ -329,31 +398,120 @@ fn cell_cmp(left: &Value, right: &Value) -> Option<Ordering> {
     }
 }
 
+fn promql_function(name: &str, args: &[f64]) -> Result<f64, Error> {
+    let x = args[0];
+    Ok(match &name[7..] {
+        "abs" => x.abs(),
+        "ceil" => x.ceil(),
+        "floor" => x.floor(),
+        "exp" => x.exp(),
+        "ln" => x.ln(),
+        "log2" => x.log2(),
+        "log10" => x.log10(),
+        "sqrt" => x.sqrt(),
+        "sgn" => {
+            if x.is_nan() {
+                f64::NAN
+            } else if x == 0.0 {
+                0.0
+            } else {
+                x.signum()
+            }
+        }
+        "sin" => x.sin(),
+        "cos" => x.cos(),
+        "tan" => x.tan(),
+        "asin" => x.asin(),
+        "acos" => x.acos(),
+        "atan" => x.atan(),
+        "sinh" => x.sinh(),
+        "cosh" => x.cosh(),
+        "tanh" => x.tanh(),
+        "asinh" => x.asinh(),
+        "acosh" => x.acosh(),
+        "atanh" => x.atanh(),
+        "deg" => x.to_degrees(),
+        "rad" => x.to_radians(),
+        "round" => {
+            let inverse = 1.0 / args[1];
+            (x * inverse + 0.5).floor() / inverse
+        }
+        "clamp_min" => {
+            if x.is_nan() || args[1].is_nan() {
+                f64::NAN
+            } else {
+                x.max(args[1])
+            }
+        }
+        "clamp_max" => {
+            if x.is_nan() || args[1].is_nan() {
+                f64::NAN
+            } else {
+                x.min(args[1])
+            }
+        }
+        "clamp" => {
+            if args.iter().any(|x| x.is_nan()) {
+                f64::NAN
+            } else {
+                x.max(args[1]).min(args[2])
+            }
+        }
+        part => {
+            use chrono::{Datelike, Timelike};
+            if !x.is_finite() || x < i64::MIN as f64 || x >= i64::MAX as f64 {
+                return Ok(f64::NAN);
+            }
+            let Some(date) = chrono::DateTime::from_timestamp(x as i64, 0) else {
+                return Ok(f64::NAN);
+            };
+            match part {
+                "minute" => date.minute() as f64,
+                "hour" => date.hour() as f64,
+                "day_of_week" => date.weekday().num_days_from_sunday() as f64,
+                "day_of_month" => date.day() as f64,
+                "day_of_year" => date.ordinal() as f64,
+                "month" => date.month() as f64,
+                "year" => date.year() as f64,
+                "days_in_month" => {
+                    let year = date.year();
+                    let leap = year % 4 == 0 && (year % 100 != 0 || year % 400 == 0);
+                    match date.month() {
+                        2 => {
+                            if leap {
+                                29.0
+                            } else {
+                                28.0
+                            }
+                        }
+                        4 | 6 | 9 | 11 => 30.0,
+                        _ => 31.0,
+                    }
+                }
+                _ => return Err(Error::Invalid("unregistered PromQL function".into())),
+            }
+        }
+    })
+}
+
 #[derive(serde::Serialize, serde::Deserialize, Clone, Debug)]
 pub struct CompiledExpression {
-    expression: QueryExpr,
+    expression: ScalarExpr,
     schema: planner_types::pre_asap::Schema,
     output: (DataType, bool),
 }
 impl CompiledExpression {
-    pub fn compile(expression: &QueryExpr, input: &SchemaRef) -> Result<Self, Error> {
-        let schema = input
-            .fields
-            .iter()
-            .map(|field| {
-                let planner_types::post_asap::FieldDataType::Plain(dtype) = &field.dtype else {
-                    return Err(Error::Invalid(
-                        "scalar expression cannot consume opaque summary state".into(),
-                    ));
-                };
-                Ok(planner_types::pre_asap::Field::plain(
-                    field.name.clone(),
-                    dtype.clone(),
-                    field.nullable,
-                ))
-            })
-            .collect::<Result<Vec<_>, Error>>()?;
-        let schema = planner_types::pre_asap::Schema::new(schema);
+    pub(crate) fn expression(&self) -> &ScalarExpr {
+        &self.expression
+    }
+
+    pub fn compile(expression: &ScalarExpr, input: &SchemaRef) -> Result<Self, Error> {
+        if !input.is_all_plain() {
+            return Err(Error::Invalid(
+                "scalar expression cannot consume summary state".into(),
+            ));
+        }
+        let schema = input.as_ref().clone();
         validate(expression, &schema)?;
         let output = expression
             .scalar_type(&schema)
@@ -394,8 +552,7 @@ impl CompiledExpression {
         if row.len() != self.schema.fields.len()
             || row.iter().zip(&self.schema.fields).any(|(value, column)| {
                 !column
-                    .dtype
-                    .plain()
+                    .plain_dtype()
                     .is_some_and(|dtype| value.matches(dtype, column.nullable))
             })
         {
@@ -406,13 +563,27 @@ impl CompiledExpression {
         evaluate(&self.expression, row, &self.schema)
     }
 }
-fn validate(expr: &QueryExpr, schema: &planner_types::pre_asap::Schema) -> Result<(), Error> {
+fn validate(expr: &ScalarExpr, schema: &planner_types::pre_asap::Schema) -> Result<(), Error> {
     let invalid = || Error::Invalid(format!("unsupported scalar expression: {expr:?}"));
     expr.scalar_type(schema)
         .map_err(|e| Error::Invalid(e.to_string()))?;
     match expr {
-        QueryExpr::Column(_) | QueryExpr::Literal(_) => Ok(()),
-        QueryExpr::Arithmetic { left, right, .. } => {
+        ScalarExpr::Column(_) | ScalarExpr::Literal(_) => Ok(()),
+        ScalarExpr::Cast { expr, to, .. } => {
+            let source = expr
+                .scalar_type(schema)
+                .map_err(|e| Error::Invalid(e.to_string()))?
+                .0;
+            if source != *to
+                && source != DataType::Null
+                && !(source == DataType::Int64 && *to == DataType::Float64)
+            {
+                return Err(invalid());
+            }
+            validate(expr, schema)
+        }
+        ScalarExpr::Negative { expr, .. } => validate(expr, schema),
+        ScalarExpr::Arithmetic { left, right, .. } => {
             for value in [left, right] {
                 validate(value, schema)?;
                 if !matches!(
@@ -427,7 +598,9 @@ fn validate(expr: &QueryExpr, schema: &planner_types::pre_asap::Schema) -> Resul
             }
             Ok(())
         }
-        QueryExpr::Compare { left, right, op } => {
+        ScalarExpr::Compare {
+            left, right, op, ..
+        } => {
             if !matches!(
                 op,
                 CompareOpKind::Eq
@@ -471,8 +644,10 @@ fn validate(expr: &QueryExpr, schema: &planner_types::pre_asap::Schema) -> Resul
             }
             Ok(())
         }
-        QueryExpr::FunctionCall { name, args } => {
-            if name != "asap_struct_field"
+        ScalarExpr::FunctionCall { name, args } => {
+            if name != "promql_drop_metric_name"
+                && planner_types::pre_asap::scalar_type_rules::promql_function_arity(name).is_none()
+                && name != "asap_struct_field"
                 && name != "asap_element_access"
                 && planner_types::pre_asap::scalar_type_rules::MapScalarFunction::from_name(name)
                     .is_none()
@@ -484,7 +659,29 @@ fn validate(expr: &QueryExpr, schema: &planner_types::pre_asap::Schema) -> Resul
             }
             Ok(())
         }
-        QueryExpr::BoolAnd(parts) | QueryExpr::BoolOr(parts) => {
+        ScalarExpr::Case {
+            operand: None,
+            branches,
+            else_expr,
+        } => {
+            for (condition, value) in branches {
+                validate(condition, schema)?;
+                if condition
+                    .scalar_type(schema)
+                    .map_err(|e| Error::Invalid(e.to_string()))?
+                    .0
+                    != DataType::Bool
+                {
+                    return Err(invalid());
+                }
+                validate(value, schema)?;
+            }
+            if let Some(value) = else_expr {
+                validate(value, schema)?;
+            }
+            Ok(())
+        }
+        ScalarExpr::BoolAnd(parts) | ScalarExpr::BoolOr(parts) => {
             for part in parts {
                 validate(part, schema)?;
                 if !matches!(
@@ -498,7 +695,7 @@ fn validate(expr: &QueryExpr, schema: &planner_types::pre_asap::Schema) -> Resul
             }
             Ok(())
         }
-        QueryExpr::Not(value) => {
+        ScalarExpr::Not(value) => {
             validate(value, schema)?;
             if !matches!(
                 value
@@ -511,7 +708,7 @@ fn validate(expr: &QueryExpr, schema: &planner_types::pre_asap::Schema) -> Resul
             }
             Ok(())
         }
-        QueryExpr::IsNull(value) | QueryExpr::IsNotNull(value) => validate(value, schema),
+        ScalarExpr::IsNull(value) | ScalarExpr::IsNotNull(value) => validate(value, schema),
         _ => Err(invalid()),
     }
 }
diff --git a/crates/asap-physical-operators/src/lib.rs b/crates/asap-physical-operators/src/lib.rs
index 586da2508..ea6b73eaf 100644
--- a/crates/asap-physical-operators/src/lib.rs
+++ b/crates/asap-physical-operators/src/lib.rs
@@ -20,7 +20,7 @@ pub use planner_types as planner;
 
 pub mod dag;
 
-pub mod readout;
+pub mod evaluation;
 
 mod error;
 pub use error::Error;
@@ -31,6 +31,3 @@ pub mod plan;
 pub mod runtime;
 pub mod sources;
 pub mod values;
-
-pub mod unified_physical_planner;
-pub mod unified_sources;
diff --git a/crates/asap-physical-operators/src/operators/aggregate/mod.rs b/crates/asap-physical-operators/src/operators/aggregate/mod.rs
index 76eccd5ee..7b51b3c66 100644
--- a/crates/asap-physical-operators/src/operators/aggregate/mod.rs
+++ b/crates/asap-physical-operators/src/operators/aggregate/mod.rs
@@ -24,7 +24,8 @@ impl Operator {
                         } else {
                             t.clone()
                         },
-                        false,
+                        !input.has_promql_series_identity()
+                            && (groups.is_empty() || plain(&input, *i)?.1),
                     )
                 }
                 Reduction::Quantile { column, q } => {
@@ -183,7 +184,8 @@ async fn reduce(
     let mut work = Cooperative::new(context);
     let mut workspace = Workspace::new(context)?;
     let mut grouped = BTreeMap::<Vec<Vec<u8>>, Vec<Vec<Value>>>::new();
-    if rows.is_empty() && groups.is_empty() {
+    // PromQL sums over an empty vector emit no sample.
+    if rows.is_empty() && groups.is_empty() && !input.has_promql_series_identity() {
         grouped.insert(vec![], vec![]);
     }
     for row in rows {
@@ -318,6 +320,9 @@ async fn reduce_one(
                 .ok_or_else(|| invalid("integer aggregate overflow"))?;
             count += 1;
         }
+        if count == 0 && !input.has_promql_series_identity() {
+            return Ok(Value::Null);
+        }
         return if matches!(measure, Reduction::Avg(_)) {
             Ok(Value::Float64(sum as f64 / count as f64))
         } else {
@@ -334,6 +339,9 @@ async fn reduce_one(
         };
         floats.push(*v);
     }
+    if floats.is_empty() && !input.has_promql_series_identity() {
+        return Ok(Value::Null);
+    }
     Ok(Value::Float64(if matches!(measure, Reduction::Avg(_)) {
         promql_avg(&floats)
     } else {
diff --git a/crates/asap-physical-operators/src/operators/aggregate/temporal.rs b/crates/asap-physical-operators/src/operators/aggregate/temporal.rs
index e40a1fa56..a289c5284 100644
--- a/crates/asap-physical-operators/src/operators/aggregate/temporal.rs
+++ b/crates/asap-physical-operators/src/operators/aggregate/temporal.rs
@@ -308,7 +308,7 @@ mod tests {
         values::Batch,
     };
     use planner_types::{
-        post_asap::{Field, FieldDataType, Schema},
+        post_asap::{Field as SummaryField, FieldDataType as SummaryFamilyType, Schema},
         pre_asap::DataType,
         types::AccuracyTarget,
     };
@@ -318,23 +318,23 @@ mod tests {
     #[test]
     fn temporal_windows_execute_in_both_phases_and_count_is_integer() {
         let schema = Arc::new(Schema {
-            closed: true,
-            unique_keys: vec![],
             fields: vec![
-                Field {
-                    table: None,
+                SummaryField {
                     name: "time".into(),
-                    dtype: FieldDataType::Plain(DataType::Timestamp),
+                    dtype: SummaryFamilyType::Plain(DataType::Timestamp),
                     nullable: false,
-                },
-                Field {
                     table: None,
+                },
+                SummaryField {
                     name: "value".into(),
-                    dtype: FieldDataType::Plain(DataType::Float64),
+                    dtype: SummaryFamilyType::Plain(DataType::Float64),
                     nullable: false,
+                    table: None,
                 },
             ],
             time_index: Some(0),
+            unique_keys: vec![],
+            closed: false,
         });
         for scope in [
             Scope::Query {
diff --git a/crates/asap-physical-operators/src/operators/aligned_binary.rs b/crates/asap-physical-operators/src/operators/aligned_binary.rs
index 188d28d6f..909dcc369 100644
--- a/crates/asap-physical-operators/src/operators/aligned_binary.rs
+++ b/crates/asap-physical-operators/src/operators/aligned_binary.rs
@@ -1,6 +1,8 @@
 //! Arithmetic on complete, aligned population/window rows used by precomputation.
 use super::*;
-use planner_types::{post_asap::BinaryOperator, pre_asap::BinaryOpKind};
+use crate::expressions::binary::BinaryOpKind;
+use crate::expressions::binary::BinaryOperator;
+
 use std::collections::BTreeSet;
 
 impl Operator {
@@ -22,11 +24,9 @@ impl Operator {
             ));
         }
         for (input, value) in [(&left, values.0), (&right, values.1)] {
-            if input
-                .fields
-                .get(value)
-                .is_none_or(|f| f.nullable || f.dtype != FieldDataType::Plain(DataType::Float64))
-            {
+            if input.fields.get(value).is_none_or(|f| {
+                f.nullable || f.dtype != SummaryFamilyType::Plain(DataType::Float64)
+            }) {
                 return Err(invalid(
                     "aligned arithmetic requires non-null Float64 values",
                 ));
diff --git a/crates/asap-physical-operators/src/operators/common.rs b/crates/asap-physical-operators/src/operators/common.rs
index 5ef5023cd..f67314bb1 100644
--- a/crates/asap-physical-operators/src/operators/common.rs
+++ b/crates/asap-physical-operators/src/operators/common.rs
@@ -2,20 +2,20 @@ use super::*;
 pub(super) fn invalid(message: &str) -> Error {
     Error::Invalid(message.into())
 }
-pub(super) fn schema(fields: Vec<Field>) -> SchemaRef {
+pub(super) fn schema(fields: Vec<SummaryField>) -> SchemaRef {
     Arc::new(Schema {
-        closed: true,
-        unique_keys: vec![],
         fields,
+        unique_keys: vec![],
+        closed: false,
         time_index: None,
     })
 }
-pub(super) fn result_field(name: &str, dtype: DataType, nullable: bool) -> Field {
-    Field {
-        table: None,
+pub(super) fn result_field(name: &str, dtype: DataType, nullable: bool) -> SummaryField {
+    SummaryField {
         name: name.into(),
-        dtype: FieldDataType::Plain(dtype),
+        dtype: SummaryFamilyType::Plain(dtype),
         nullable,
+        table: None,
     }
 }
 
@@ -76,4 +76,3 @@ pub(super) fn key_bytes(key: &[Vec<u8>]) -> usize {
         .map(|part| std::mem::size_of::<Vec<u8>>() + part.len())
         .sum::<usize>()
 }
-use planner_types::pre_asap::Schema;
diff --git a/crates/asap-physical-operators/src/operators/joins/mod.rs b/crates/asap-physical-operators/src/operators/joins/mod.rs
index 9dfd20dea..652fbcdcc 100644
--- a/crates/asap-physical-operators/src/operators/joins/mod.rs
+++ b/crates/asap-physical-operators/src/operators/joins/mod.rs
@@ -22,6 +22,15 @@ impl Operator {
             output: left,
         })
     }
+    /// Require every candidate key to have an authoritative value at execution.
+    pub fn certified_semi_join(
+        left: SchemaRef,
+        right: SchemaRef,
+        keys: Vec<(usize, usize)>,
+    ) -> Result<Self, Error> {
+        Ok(Self::semi_join(left, right, keys)?.require_complete_right())
+    }
+
     pub(crate) fn require_complete_right(mut self) -> Self {
         if let Kind::SemiJoin {
             require_complete_right,
@@ -42,48 +51,18 @@ impl Operator {
         }
     }
     pub fn relational_join(
-        left: SchemaRef,
-        right: SchemaRef,
-        kind: planner_types::pre_asap::JoinKind,
-        predicate: &planner_types::pre_asap::Predicate,
-        output: SchemaRef,
-    ) -> Result<Self, Error> {
-        let mut joined = left.fields.clone();
-        joined.extend(right.fields.clone());
-        let predicate = Expression::planner(crate::expressions::CompiledExpression::compile(
-            &predicate.0,
-            &schema(joined),
-        )?);
-        Self::bound_relational_join(left, right, kind, predicate, output)
-    }
-    pub fn unified_relational_join(
         left: SchemaRef,
         right: SchemaRef,
         kind: planner_types::pre_asap::JoinKind,
         predicate: &planner_types::ir::Predicate,
         output: SchemaRef,
-    ) -> Result<Self, Error> {
-        let mut joined = left.fields.clone();
-        joined.extend(right.fields.clone());
-        let predicate = Expression::unified_planner(
-            crate::expressions::unified_planner::CompiledExpression::compile(
-                &predicate.0,
-                &schema(joined),
-            )?,
-        );
-        Self::bound_relational_join(left, right, kind, predicate, output)
-    }
-    pub(crate) fn bound_relational_join(
-        left: SchemaRef,
-        right: SchemaRef,
-        kind: planner_types::pre_asap::JoinKind,
-        predicate: Expression,
-        output: SchemaRef,
     ) -> Result<Self, Error> {
         use planner_types::pre_asap::JoinKind;
         let mut joined = left.fields.clone();
         joined.extend(right.fields.clone());
-        if predicate.dtype(&schema(joined.clone()))?.0 != DataType::Bool {
+        let predicate =
+            crate::expressions::CompiledExpression::compile(&predicate.0, &schema(joined.clone()))?;
+        if predicate.dtype().0 != DataType::Bool {
             return Err(invalid("join predicate must be boolean"));
         }
         let fields = if matches!(kind, JoinKind::Semi | JoinKind::Anti) {
diff --git a/crates/asap-physical-operators/src/operators/mod.rs b/crates/asap-physical-operators/src/operators/mod.rs
index 75b313d75..517019118 100644
--- a/crates/asap-physical-operators/src/operators/mod.rs
+++ b/crates/asap-physical-operators/src/operators/mod.rs
@@ -8,7 +8,7 @@ use crate::{
 };
 use futures::StreamExt;
 use planner_types::{
-    post_asap::{Field, FieldDataType, SummaryUpdate},
+    post_asap::{Field as SummaryField, FieldDataType as SummaryFamilyType, Schema, SummaryUpdate},
     pre_asap::{ColumnRef, DataType},
 };
 use std::{collections::BTreeMap, sync::Arc};
@@ -34,7 +34,7 @@ pub(crate) mod vector_window;
 pub use aggregate::Reduction;
 pub use series_window::SubquerySteps;
 pub use sort::SortKey;
-pub use summary::ReadoutQuery;
+pub use summary::SummaryEvaluation;
 #[derive(Clone, serde::Serialize, serde::Deserialize)]
 enum Kind {
     #[serde(skip)]
@@ -58,13 +58,13 @@ enum Kind {
         column: usize,
     },
     VectorBinary {
-        operator: planner_types::post_asap::BinaryOperator,
+        operator: crate::expressions::binary::BinaryOperator,
         return_bool: bool,
     },
     AlignedBinary {
         keys: Vec<(usize, usize)>,
         values: (usize, usize),
-        operator: planner_types::post_asap::BinaryOperator,
+        operator: crate::expressions::binary::BinaryOperator,
     },
     RangeWindow {
         intent: Box<planner_types::pre_asap::AggIntent<ColumnRef>>,
@@ -89,7 +89,7 @@ enum Kind {
         unique: bool,
     },
     SeriesBinary {
-        operator: planner_types::post_asap::BinaryOperator,
+        operator: crate::expressions::binary::BinaryOperator,
         scalars: [bool; 2],
     },
     SeriesRelabel {
@@ -130,21 +130,21 @@ enum Kind {
     },
     Join {
         kind: planner_types::pre_asap::JoinKind,
-        predicate: Box<Expression>,
+        predicate: Box<crate::expressions::CompiledExpression>,
     },
     SummaryBuild {
-        family: FieldDataType,
+        family: SummaryFamilyType,
         value: usize,
         time: Option<usize>,
         groups: Vec<usize>,
     },
     KeyedSummaryBuild {
-        family: FieldDataType,
+        family: SummaryFamilyType,
         value: usize,
         items: Vec<usize>,
         groups: Vec<usize>,
     },
-    KeyedReadout {
+    KeyedEvaluation {
         state: usize,
         k: usize,
     },
@@ -152,9 +152,9 @@ enum Kind {
         state: usize,
         groups: Vec<usize>,
     },
-    Readout {
+    Evaluation {
         state: usize,
-        query: ReadoutQuery,
+        query: SummaryEvaluation,
     },
 }
 /// A bound operation has a fully checked input/output contract before execution.
@@ -175,11 +175,11 @@ impl Operator {
         }
     }
 
-    pub(crate) fn is_counter_readout(&self) -> bool {
+    pub(crate) fn is_counter_evaluation(&self) -> bool {
         matches!(
             self.kind,
-            Kind::Readout {
-                query: ReadoutQuery::Exact(crate::summary_kernels::exact::ExactReadout {
+            Kind::Evaluation {
+                query: SummaryEvaluation::Exact(crate::summary_kernels::exact::ExactEvaluation {
                     statistic: crate::Statistic::Rate | crate::Statistic::Increase,
                     ..
                 }),
@@ -192,21 +192,24 @@ impl Operator {
         if lookback <= 0 {
             return Err(invalid("counter lookback must be positive"));
         }
-        if let Kind::Readout {
-            query: ReadoutQuery::Exact(readout),
+        if let Kind::Evaluation {
+            query: SummaryEvaluation::Exact(evaluation),
             ..
         } = &mut self.kind
         {
-            readout.lookback_ms = Some(lookback);
+            evaluation.lookback_ms = Some(lookback);
         }
         Ok(self)
     }
 
-    /// Resolve a counter readout's logical lookback to this run's evaluation range.
-    pub(super) fn readout_range(&self, context: &RunContext) -> Result<Option<(i64, i64)>, Error> {
-        let Kind::Readout {
+    /// Resolve a counter evaluation's logical lookback to this run's evaluation range.
+    pub(super) fn evaluation_range(
+        &self,
+        context: &RunContext,
+    ) -> Result<Option<(i64, i64)>, Error> {
+        let Kind::Evaluation {
             query:
-                ReadoutQuery::Exact(crate::summary_kernels::exact::ExactReadout {
+                SummaryEvaluation::Exact(crate::summary_kernels::exact::ExactEvaluation {
                     lookback_ms: Some(lookback),
                     ..
                 }),
@@ -252,7 +255,7 @@ impl Operator {
         }
         if output.time_index.is_some_and(|i| {
             i >= output.fields.len()
-                || output.fields[i].dtype != FieldDataType::Plain(DataType::Timestamp)
+                || output.fields[i].dtype != SummaryFamilyType::Plain(DataType::Timestamp)
         }) {
             return Err(invalid("invalid output time column"));
         }
@@ -335,15 +338,15 @@ impl PhysicalOperator<Batch, SchemaRef> for Operator {
             Kind::SemiJoin { .. } => "SemiJoin",
             Kind::Join { .. } => "RelationalJoin",
             Kind::SummaryBuild { .. } | Kind::KeyedSummaryBuild { .. } => "SummaryAgg",
-            Kind::KeyedReadout { .. } => "SummaryEstimate",
+            Kind::KeyedEvaluation { .. } => "SummaryEstimate",
             Kind::SummaryMerge { .. } => "SummaryMerge",
-            Kind::Readout { .. } => "SummaryReadout",
+            Kind::Evaluation { .. } => "SummaryEvaluation",
         }
     }
     fn validate_context(&self, context: &RunContext) -> Result<(), Error> {
         current_series::validate_context(self, context)?;
         series_window::validate_context(self, context)?;
-        self.readout_range(context).map(|_| ())
+        self.evaluation_range(context).map(|_| ())
     }
     fn input_schemas(&self) -> Vec<SchemaRef> {
         self.inputs.clone()
@@ -387,9 +390,9 @@ impl PhysicalOperator<Batch, SchemaRef> for Operator {
             Kind::Join { .. } | Kind::SemiJoin { .. } => joins::execute(self, inputs, context),
             Kind::SummaryMerge { .. } => summary::execute_merge(self, inputs, context),
             Kind::SummaryBuild { .. }
-            | Kind::Readout { .. }
+            | Kind::Evaluation { .. }
             | Kind::KeyedSummaryBuild { .. }
-            | Kind::KeyedReadout { .. } => summary::execute(self, inputs, context),
+            | Kind::KeyedEvaluation { .. } => summary::execute(self, inputs, context),
         }
     }
 }
diff --git a/crates/asap-physical-operators/src/operators/scope_timestamp.rs b/crates/asap-physical-operators/src/operators/scope_timestamp.rs
index bb7a4e855..33fbdd1ec 100644
--- a/crates/asap-physical-operators/src/operators/scope_timestamp.rs
+++ b/crates/asap-physical-operators/src/operators/scope_timestamp.rs
@@ -26,7 +26,7 @@ impl Operator {
                     candidate.dtype == field.dtype
                         && candidate.nullable == field.nullable
                         && (candidate.name == field.name
-                            || !matches!(field.dtype, FieldDataType::Plain(_)))
+                            || !matches!(field.dtype, SummaryFamilyType::Plain(_)))
                 })
                 .map(|(index, _)| index)
                 .collect();
diff --git a/crates/asap-physical-operators/src/operators/series_labels.rs b/crates/asap-physical-operators/src/operators/series_labels.rs
index 2a8c5d1ee..3987c5142 100644
--- a/crates/asap-physical-operators/src/operators/series_labels.rs
+++ b/crates/asap-physical-operators/src/operators/series_labels.rs
@@ -1,10 +1,9 @@
 //! PromQL label-set rewriting and binary operators over rows that carry a
 //! series identity or plain label columns.
 use super::*;
-use planner_types::{
-    post_asap::BinaryOperator,
-    pre_asap::{schema::PROMQL_SERIES_IDENTITY, BinaryOpKind, VectorMatchKind},
-};
+use crate::expressions::binary::BinaryOpKind;
+use crate::expressions::binary::BinaryOperator;
+use planner_types::pre_asap::{schema::PROMQL_SERIES_IDENTITY, VectorMatchKind};
 
 type Labels = BTreeMap<String, String>;
 
diff --git a/crates/asap-physical-operators/src/operators/summary/mod.rs b/crates/asap-physical-operators/src/operators/summary/mod.rs
index 90cc2c724..5dab8109f 100644
--- a/crates/asap-physical-operators/src/operators/summary/mod.rs
+++ b/crates/asap-physical-operators/src/operators/summary/mod.rs
@@ -1,22 +1,22 @@
 use super::*;
-/// A summary readout: a sketch query, or an exact readout with typed parameters.
+/// A summary evaluation: a sketch query, or an exact evaluation with typed parameters.
 #[derive(Clone, Debug, PartialEq, serde::Serialize, serde::Deserialize)]
-pub enum ReadoutQuery {
+pub enum SummaryEvaluation {
     Sketch(planner_types::post_asap::SketchStatistic),
-    Exact(crate::summary_kernels::exact::ExactReadout),
+    Exact(crate::summary_kernels::exact::ExactEvaluation),
 }
 
 impl Operator {
     pub fn keyed_summary_build(
         input: SchemaRef,
-        family: FieldDataType,
+        family: SummaryFamilyType,
         value: usize,
         items: Vec<usize>,
         groups: Vec<usize>,
     ) -> Result<Self, Error> {
         use crate::summary_kernels::weighted_frequency::WeightedFrequency;
         crate::values::validate_family(&family)?;
-        let FieldDataType::Sketch(kind, _) = &family else {
+        let SummaryFamilyType::Sketch(kind, _) = &family else {
             return Err(invalid("keyed sketch required"));
         };
         WeightedFrequency::configuration(kind)?;
@@ -43,11 +43,11 @@ impl Operator {
             .iter()
             .map(|&i| input.fields[i].clone())
             .collect::<Vec<_>>();
-        fields.push(Field {
-            table: None,
+        fields.push(SummaryField {
             name: "state".into(),
             dtype: family.clone(),
             nullable: false,
+            table: None,
         });
         Ok(Self {
             kind: Kind::KeyedSummaryBuild {
@@ -60,7 +60,7 @@ impl Operator {
             output: schema(fields),
         })
     }
-    pub fn keyed_readout(
+    pub fn keyed_evaluation(
         input: SchemaRef,
         state: usize,
         k: usize,
@@ -68,31 +68,31 @@ impl Operator {
     ) -> Result<Self, Error> {
         use crate::summary_kernels::weighted_frequency::WeightedFrequency;
         crate::values::validate_family(&field(&input, state)?.dtype)?;
-        let FieldDataType::Sketch(kind, _) = &field(&input, state)?.dtype else {
-            return Err(invalid("keyed readout requires summary state"));
+        let SummaryFamilyType::Sketch(kind, _) = &field(&input, state)?.dtype else {
+            return Err(invalid("keyed evaluation requires summary state"));
         };
         let (_, _, _, capacity) = WeightedFrequency::configuration(kind)?;
         if k > capacity || output.fields.len() <= input.fields.len() {
-            return Err(invalid("invalid keyed readout shape or capacity"));
+            return Err(invalid("invalid keyed evaluation shape or capacity"));
         }
         if state + 1 != input.fields.len()
             || output.fields[..state] != input.fields[..state]
-            || output.fields.last().unwrap().dtype != FieldDataType::Plain(DataType::Float64)
+            || output.fields.last().unwrap().dtype != SummaryFamilyType::Plain(DataType::Float64)
         {
             return Err(invalid(
-                "keyed readout must preserve partitions and return a Float64 score",
+                "keyed evaluation must preserve partitions and return a Float64 score",
             ));
         }
         crate::values::validate_schema(&output)?;
         Ok(Self {
-            kind: Kind::KeyedReadout { state, k },
+            kind: Kind::KeyedEvaluation { state, k },
             inputs: vec![input],
             output,
         })
     }
     pub fn summary_build(
         input: SchemaRef,
-        family: FieldDataType,
+        family: SummaryFamilyType,
         value: usize,
         time: Option<usize>,
         groups: Vec<usize>,
@@ -110,7 +110,7 @@ impl Operator {
         if time.is_none()
             && matches!(
                 family,
-                FieldDataType::ExactAggregate(
+                SummaryFamilyType::ExactAggregate(
                     planner_types::post_asap::ExactKind::Rate
                         | planner_types::post_asap::ExactKind::Increase,
                     _
@@ -129,11 +129,11 @@ impl Operator {
             .iter()
             .map(|&i| input.fields[i].clone())
             .collect::<Vec<_>>();
-        fields.push(Field {
-            table: None,
+        fields.push(SummaryField {
             name: "state".into(),
             dtype: family.clone(),
             nullable: false,
+            table: None,
         });
         Ok(Self {
             kind: Kind::SummaryBuild {
@@ -153,7 +153,7 @@ impl Operator {
     ) -> Result<Self, Error> {
         validate_groups(&input, &groups)?;
         crate::values::validate_family(&field(&input, state)?.dtype)?;
-        if matches!(field(&input, state)?.dtype, FieldDataType::Plain(_)) {
+        if matches!(field(&input, state)?.dtype, SummaryFamilyType::Plain(_)) {
             return Err(invalid("summary state required"));
         }
         let mut fields = groups
@@ -167,21 +167,25 @@ impl Operator {
             output: schema(fields),
         })
     }
-    pub fn readout(input: SchemaRef, state: usize, query: ReadoutQuery) -> Result<Self, Error> {
+    pub fn evaluation(
+        input: SchemaRef,
+        state: usize,
+        query: SummaryEvaluation,
+    ) -> Result<Self, Error> {
         let family = &field(&input, state)?.dtype;
         crate::values::validate_family(family)?;
         match &query {
-            ReadoutQuery::Sketch(query) => {
-                crate::capability::validate_sketch_readout(family, query)?
+            SummaryEvaluation::Sketch(query) => {
+                crate::capability::validate_sketch_evaluation(family, query)?
             }
-            ReadoutQuery::Exact(readout) => {
-                crate::capability::validate_exact_readout(family, readout)?
+            SummaryEvaluation::Exact(evaluation) => {
+                crate::capability::validate_exact_evaluation(family, evaluation)?
             }
         }
         let mut fields = input.fields.clone();
         let result_type = if matches!(
             fields[state].dtype,
-            FieldDataType::ExactAggregate(planner_types::post_asap::ExactKind::Count, _)
+            SummaryFamilyType::ExactAggregate(planner_types::post_asap::ExactKind::Count, _)
         ) || integral_count(family, &query)
         {
             DataType::Int64
@@ -193,7 +197,7 @@ impl Operator {
         let nullable = fields.len() == 1
             && matches!(
                 fields[state].dtype,
-                FieldDataType::ExactAggregate(
+                SummaryFamilyType::ExactAggregate(
                     planner_types::post_asap::ExactKind::Min
                         | planner_types::post_asap::ExactKind::Max,
                     _
@@ -201,7 +205,7 @@ impl Operator {
             );
         fields[state] = result_field("value", result_type, nullable);
         Ok(Self {
-            kind: Kind::Readout { state, query },
+            kind: Kind::Evaluation { state, query },
             inputs: vec![input],
             output: schema(fields),
         })
@@ -210,12 +214,12 @@ impl Operator {
 /// The Planner reads a Count-Min bare count only for count intents, whose
 /// output is Int64 and whose updates have unit weight; execution rejects a
 /// non-integral total rather than rounding it.
-fn integral_count(family: &FieldDataType, query: &ReadoutQuery) -> bool {
-    matches!(family, FieldDataType::Sketch(kind, _)
+fn integral_count(family: &SummaryFamilyType, query: &SummaryEvaluation) -> bool {
+    matches!(family, SummaryFamilyType::Sketch(kind, _)
         if kind.algorithm() == &planner_types::post_asap::SketchAlgorithm::Cms)
         && matches!(
             query,
-            ReadoutQuery::Sketch(planner_types::post_asap::SketchStatistic::PointCount {
+            SummaryEvaluation::Sketch(planner_types::post_asap::SketchStatistic::PointCount {
                 value: None,
                 ..
             })
@@ -226,7 +230,7 @@ pub(super) fn execute<'a>(
     mut inputs: Vec<Input<'a, Batch>>,
     context: RunContext,
 ) -> Result<OutputStream<'a, Batch>, Error> {
-    let range_ms = operator.readout_range(&context)?;
+    let range_ms = operator.evaluation_range(&context)?;
     let output = operator.output.clone();
     let input = inputs.pop().ok_or_else(|| invalid("input missing"))?;
     match &operator.kind {
@@ -238,7 +242,7 @@ pub(super) fn execute<'a>(
         } => Ok(futures::stream::once(async move {
             Batch::try_new(
                 output,
-                build_summary(input, family, *value, *time, groups, &context).await?,
+                build_summary(input, family, *value, *time, groups, !operator.inputs[0].has_promql_series_identity(), &context).await?,
             )
         })
         .boxed_local()),
@@ -254,7 +258,7 @@ pub(super) fn execute<'a>(
             )
         })
         .boxed_local()),
-        Kind::KeyedReadout { state, k } => Ok(input
+        Kind::KeyedEvaluation { state, k } => Ok(input
             .map(move |batch| {
                 let batch = batch?;
                 let mut rows = Vec::new();
@@ -272,7 +276,7 @@ pub(super) fn execute<'a>(
                         // The typed output schema restores epoch-millisecond
                         // timestamp keys from the kernel's Int64 representation.
                         for (value, field) in values.iter_mut().zip(&output.fields) {
-                            if field.dtype == FieldDataType::Plain(DataType::Timestamp) {
+                            if field.dtype == SummaryFamilyType::Plain(DataType::Timestamp) {
                                 if let Value::Int64(time) = value {
                                     *value = Value::Timestamp(*time);
                                 }
@@ -284,25 +288,25 @@ pub(super) fn execute<'a>(
                 Batch::try_new(output.clone(), rows)
             })
             .boxed_local()),
-        Kind::Readout { state, query } => Ok(input
+        Kind::Evaluation { state, query } => Ok(input
             .map(move |batch| {
                 let batch = batch?;
                 let mut rows = batch.rows().to_vec();
-                if let ReadoutQuery::Exact(readout) = query {
+                if let SummaryEvaluation::Exact(evaluation) = query {
                     rows.retain(|row| !matches!(&row[*state], Value::Summary { state: summary, .. }
-                        if crate::readout::insufficient_counter_samples(summary.as_ref(), readout.statistic)));
+                        if crate::evaluation::insufficient_counter_samples(summary.as_ref(), evaluation.statistic)));
                 }
                 for row in &mut rows {
                     let Value::Summary { state: summary, .. } = &row[*state] else {
                         return Err(invalid("summary value required"));
                     };
                     row[*state] = match query {
-                        ReadoutQuery::Sketch(query) => {
+                        SummaryEvaluation::Sketch(query) => {
                             let value = summary
                                 .estimate(query)
                                 .map_err(|e| Error::Operator(e.to_string()))?;
                             if output.fields[*state].dtype
-                                == FieldDataType::Plain(DataType::Int64)
+                                == SummaryFamilyType::Plain(DataType::Int64)
                             {
                                 // Below 2^53 an f64 sum of unit updates is exact.
                                 if value.fract() != 0.0 || !(0.0..9.007_199_254_740_992e15).contains(&value) {
@@ -315,12 +319,13 @@ pub(super) fn execute<'a>(
                                 Value::Float64(value)
                             }
                         }
-                        ReadoutQuery::Exact(readout) => {
+                        SummaryEvaluation::Exact(evaluation) => {
                             let exact = summary
                                 .as_any()
                                 .downcast_ref::<crate::summary_kernels::exact::ExactAccumulator>()
-                                .ok_or_else(|| invalid("exact readout requires exact state"))?;
-                            if output.fields[*state].dtype == FieldDataType::Plain(DataType::Int64) {
+                                .ok_or_else(|| invalid("exact evaluation requires exact state"))?;
+                            if output.fields[*state].nullable && exact.is_empty_sum() { Value::Null }
+                            else if output.fields[*state].dtype == SummaryFamilyType::Plain(DataType::Int64) {
                                 let count = exact.count().ok_or_else(|| {
                                     Error::Operator("exact count state lacks an integer count".into())
                                 })?;
@@ -329,7 +334,7 @@ pub(super) fn execute<'a>(
                                 })?)
                             } else {
                                 match exact
-                                    .readout(readout.statistic, range_ms, None)
+                                    .evaluation(evaluation.statistic, range_ms, None)
                                     .map_err(|e| Error::Operator(e.to_string()))?
                                 {
                                     Some(value) => Value::Float64(value),
@@ -372,10 +377,11 @@ pub(super) fn execute_merge<'a>(
 
 async fn build_summary(
     mut input: Input<'_, Batch>,
-    family: &FieldDataType,
+    family: &SummaryFamilyType,
     value: usize,
     time: Option<usize>,
     groups: &[usize],
+    emit_empty_global: bool,
     context: &RunContext,
 ) -> Result<Vec<Vec<Value>>, Error> {
     type State = (
@@ -398,12 +404,13 @@ async fn build_summary(
     };
     let mut work = Cooperative::new(context);
     let mut states = BTreeMap::<Vec<Vec<u8>>, State>::new();
-    if groups.is_empty() {
+    // PromQL aggregation of an empty vector produces no sample.
+    if groups.is_empty() && emit_empty_global {
         states.insert(vec![], create(vec![], 0)?);
     }
     let ordered_time = matches!(
         family,
-        FieldDataType::ExactAggregate(
+        SummaryFamilyType::ExactAggregate(
             planner_types::post_asap::ExactKind::Rate
                 | planner_types::post_asap::ExactKind::Increase,
             _
@@ -472,7 +479,7 @@ async fn merge_summary(
     groups: &[usize],
     context: &RunContext,
 ) -> Result<Vec<Vec<Value>>, Error> {
-    type GroupState = (Vec<Value>, FieldDataType, Arc<dyn crate::AggregateCore>);
+    type GroupState = (Vec<Value>, SummaryFamilyType, Arc<dyn crate::AggregateCore>);
     let mut states: BTreeMap<Vec<Vec<u8>>, GroupState> = BTreeMap::new();
     let mut work = Cooperative::new(context);
     let mut memory = context.reserve(0)?;
@@ -531,14 +538,14 @@ async fn merge_summary(
 
 async fn build_keyed_summary(
     mut input: Input<'_, Batch>,
-    family: &FieldDataType,
+    family: &SummaryFamilyType,
     value: usize,
     items: &[usize],
     groups: &[usize],
     context: &RunContext,
 ) -> Result<Vec<Vec<Value>>, Error> {
     use crate::{summary_kernels::weighted_frequency::WeightedFrequency, AggregateCore};
-    let FieldDataType::Sketch(kind, _) = family else {
+    let SummaryFamilyType::Sketch(kind, _) = family else {
         unreachable!()
     };
     let (algorithm, width, depth, capacity) = WeightedFrequency::configuration(kind)?;
diff --git a/crates/asap-physical-operators/src/operators/unchecked.rs b/crates/asap-physical-operators/src/operators/unchecked.rs
index a7d3bd683..1b5dd7c4f 100644
--- a/crates/asap-physical-operators/src/operators/unchecked.rs
+++ b/crates/asap-physical-operators/src/operators/unchecked.rs
@@ -134,11 +134,11 @@ impl TryFrom<UncheckedOperator> for Operator {
                     operator
                 }
             }
-            Kind::Join { kind, predicate } => Operator::bound_relational_join(
+            Kind::Join { kind, predicate } => Operator::relational_join(
                 input(0)?,
                 input(1)?,
                 kind,
-                *predicate,
+                &planner_types::ir::Predicate(predicate.expression().clone()),
                 output.clone(),
             )?,
             Kind::SummaryBuild {
@@ -153,13 +153,13 @@ impl TryFrom<UncheckedOperator> for Operator {
                 items,
                 groups,
             } => Operator::keyed_summary_build(input(0)?, family, value, items, groups)?,
-            Kind::KeyedReadout { state, k } => {
-                Operator::keyed_readout(input(0)?, state, k, output.clone())?
+            Kind::KeyedEvaluation { state, k } => {
+                Operator::keyed_evaluation(input(0)?, state, k, output.clone())?
             }
             Kind::SummaryMerge { state, groups } => {
                 Operator::summary_merge(input(0)?, state, groups)?
             }
-            Kind::Readout { state, query } => Operator::readout(input(0)?, state, query)?,
+            Kind::Evaluation { state, query } => Operator::evaluation(input(0)?, state, query)?,
         }
         .with_output_schema(output)?;
         if serde_json::to_value(&op.kind).map_err(|error| invalid(&error.to_string()))?
diff --git a/crates/asap-physical-operators/src/operators/vector_binary.rs b/crates/asap-physical-operators/src/operators/vector_binary.rs
index 7027fb9be..0f4af7cf4 100644
--- a/crates/asap-physical-operators/src/operators/vector_binary.rs
+++ b/crates/asap-physical-operators/src/operators/vector_binary.rs
@@ -1,6 +1,7 @@
 //! Label matching and scalar broadcasting are physical computation, not source binding.
 use super::*;
-use planner_types::{post_asap::BinaryOperator, pre_asap::BinaryOpKind};
+use crate::expressions::binary::BinaryOpKind;
+use crate::expressions::binary::BinaryOperator;
 
 pub(crate) fn value_schema(scalar: bool) -> SchemaRef {
     let mut fields = Vec::new();
diff --git a/crates/asap-physical-operators/src/operators/vector_window.rs b/crates/asap-physical-operators/src/operators/vector_window.rs
index 6b4d58347..6b21ff6a4 100644
--- a/crates/asap-physical-operators/src/operators/vector_window.rs
+++ b/crates/asap-physical-operators/src/operators/vector_window.rs
@@ -1,7 +1,6 @@
 //! Window bounds are typed input data; aggregation and histogram semantics stay native.
 use super::*;
 use planner_types::pre_asap::AggIntent;
-use planner_types::pre_asap::Schema;
 
 pub(crate) fn matrix_schema() -> SchemaRef {
     let mut fields = vector_binary::value_schema(false).fields.clone();
@@ -9,9 +8,9 @@ pub(crate) fn matrix_schema() -> SchemaRef {
     fields.push(result_field("window_start", DataType::Timestamp, false));
     fields.push(result_field("window_end", DataType::Timestamp, false));
     Arc::new(Schema {
-        closed: true,
-        unique_keys: vec![],
         fields,
+        unique_keys: vec![],
+        closed: false,
         time_index: Some(1),
     })
 }
diff --git a/crates/asap-physical-operators/src/physical_planner/candidates.rs b/crates/asap-physical-operators/src/physical_planner/candidates.rs
index 0e6ee86ba..eacd1cfa2 100644
--- a/crates/asap-physical-operators/src/physical_planner/candidates.rs
+++ b/crates/asap-physical-operators/src/physical_planner/candidates.rs
@@ -5,8 +5,8 @@ use super::*;
 /// it during optimization and deployment. Stored outputs have no storage identity.
 /// Deserialization validates the producer/reader boundary.
 #[derive(Clone, serde::Serialize, serde::Deserialize)]
-#[serde(try_from = "UncheckedPhysicalASAPDAG")]
-pub struct PhysicalASAPDAG {
+#[serde(try_from = "UncheckedCompiledPhysicalPlan")]
+pub struct CompiledPhysicalPlan {
     pub precompute: Option<CompiledPhysicalDAG>,
     pub query: CompiledPhysicalDAG,
     pub materialized_outputs: BTreeMap<NodeId, InputContract>,
@@ -14,18 +14,18 @@ pub struct PhysicalASAPDAG {
 
 /// Compile an explicit materialization frontier selected by Planner maintenance
 /// search. Operators upstream of that frontier run in precompute, including
-/// readouts/reductions; query execution receives their typed output values.
+/// evaluations/reductions; query execution receives their typed output values.
 /// Empty frontiers retain the full computation in the query DAG.
 ///
 /// Repeated windows must be instantiated with the same evaluation/population
 /// contract used to build each output. This API never treats a result from a
 /// different window or revision as interchangeable merely because types match.
 pub fn compile_candidate(
-    dag: &PostAsapDAG,
+    dag: &PhysicalASAPDAG,
     inputs: BTreeMap<NodeId, InputContract>,
     roots: &[NodeId],
     frontier: &[NodeId],
-) -> Result<PhysicalASAPDAG, Error> {
+) -> Result<CompiledPhysicalPlan, Error> {
     cut_candidate(&compile(dag, inputs, roots)?, frontier)
 }
 
@@ -36,9 +36,9 @@ pub fn compile_candidate(
 pub fn cut_candidate(
     compiled: &CompiledPhysicalDAG,
     frontier: &[NodeId],
-) -> Result<PhysicalASAPDAG, Error> {
+) -> Result<CompiledPhysicalPlan, Error> {
     if frontier.is_empty() {
-        return Ok(PhysicalASAPDAG {
+        return Ok(CompiledPhysicalPlan {
             precompute: None,
             query: compiled.clone(),
             materialized_outputs: BTreeMap::new(),
@@ -79,7 +79,7 @@ pub fn cut_candidate(
             "frontier contains an output shadowed by another boundary",
         ));
     }
-    Ok(PhysicalASAPDAG {
+    Ok(CompiledPhysicalPlan {
         precompute: Some(precompute),
         query,
         materialized_outputs,
@@ -93,7 +93,7 @@ pub fn cut_candidate(
 /// That holds while timing-dependent lowering (an ingestion-time `Binary`
 /// aligns by value column) has the same timing at compile time as here.
 /// A query-time node feeding an ingestion-time node has no valid placement.
-pub fn frontier_from_timing(dag: &PostAsapDAG) -> Result<Vec<NodeId>, Error> {
+pub fn frontier_from_timing(dag: &PhysicalASAPDAG) -> Result<Vec<NodeId>, Error> {
     use planner_types::post_asap::ExecutionTiming::IngestionTime;
     let timing = dag
         .nodes
@@ -101,8 +101,10 @@ pub fn frontier_from_timing(dag: &PostAsapDAG) -> Result<Vec<NodeId>, Error> {
         .map(|node| (node.id, node.output_state.timing))
         .collect::<BTreeMap<_, _>>();
     let mut frontier = BTreeSet::new();
-    if timing.get(&dag.root) == Some(&IngestionTime) {
-        frontier.insert(u64::from(dag.root.0));
+    for root in &dag.roots {
+        if timing.get(root) == Some(&IngestionTime) {
+            frontier.insert(u64::from(root.0));
+        }
     }
     for edge in &dag.edges {
         let (Some(&producer), Some(&consumer)) =
@@ -127,7 +129,7 @@ pub fn frontier_from_timing(dag: &PostAsapDAG) -> Result<Vec<NodeId>, Error> {
 /// and deployment feasibility are evaluated separately before cost selection.
 /// Exceeding the search budget returns an error, never a partial inventory.
 pub fn enumerate_frontiers(
-    dag: &PostAsapDAG,
+    dag: &PhysicalASAPDAG,
     inputs: &BTreeMap<NodeId, InputContract>,
     roots: &[NodeId],
     max_candidates: usize,
@@ -192,11 +194,11 @@ fn enumerate_compiled_frontiers(
 /// individual failures visible; do not substitute another computation on error.
 /// The DAG is lowered once; each frontier is a [`cut_candidate`] of it.
 pub fn compile_candidates(
-    dag: &PostAsapDAG,
+    dag: &PhysicalASAPDAG,
     inputs: BTreeMap<NodeId, InputContract>,
     roots: &[NodeId],
     frontiers: &[Vec<NodeId>],
-) -> Vec<Result<PhysicalASAPDAG, Error>> {
+) -> Vec<Result<CompiledPhysicalPlan, Error>> {
     match compile(dag, inputs, roots) {
         Ok(compiled) => frontiers
             .iter()
@@ -216,7 +218,7 @@ pub struct CandidateCost {
     pub total_cost: f64,
 }
 
-pub struct CandidateSelection<T = PhysicalASAPDAG> {
+pub struct CandidateSelection<T = CompiledPhysicalPlan> {
     pub candidate: T,
     pub candidate_index: usize,
     pub cost: CandidateCost,
@@ -271,14 +273,14 @@ pub fn select_candidate<T>(
 
 #[derive(serde::Deserialize)]
 #[serde(deny_unknown_fields)]
-struct UncheckedPhysicalASAPDAG {
+struct UncheckedCompiledPhysicalPlan {
     precompute: Option<CompiledPhysicalDAG>,
     query: CompiledPhysicalDAG,
     materialized_outputs: BTreeMap<NodeId, InputContract>,
 }
-impl TryFrom<UncheckedPhysicalASAPDAG> for PhysicalASAPDAG {
+impl TryFrom<UncheckedCompiledPhysicalPlan> for CompiledPhysicalPlan {
     type Error = Error;
-    fn try_from(candidate: UncheckedPhysicalASAPDAG) -> Result<Self, Error> {
+    fn try_from(candidate: UncheckedCompiledPhysicalPlan) -> Result<Self, Error> {
         let result = Self {
             precompute: candidate.precompute,
             query: candidate.query,
@@ -289,7 +291,7 @@ impl TryFrom<UncheckedPhysicalASAPDAG> for PhysicalASAPDAG {
     }
 }
 
-impl PhysicalASAPDAG {
+impl CompiledPhysicalPlan {
     /// Validate the physical handoff, including the producer/reader boundary.
     pub fn validate(&self) -> Result<(), Error> {
         self.query.validate()?;
@@ -331,7 +333,7 @@ mod tests {
     use super::*;
     use planner_types::workload::*;
 
-    fn grouped_rate() -> (PostAsapDAG, BTreeMap<NodeId, InputContract>, NodeId) {
+    fn grouped_rate() -> (PhysicalASAPDAG, BTreeMap<NodeId, InputContract>, NodeId) {
         let workload = PlanningWorkload {
             query_workload: QueryWorkload {
                 language: QueryLanguage::PromQL,
@@ -361,14 +363,20 @@ mod tests {
         let root = asap_frontend_promql::lower_promql_workload(&workload, 0)
             .unwrap()
             .remove(0);
-        let root = std::rc::Rc::new(promql_rows::with_series_identity(&root).unwrap());
+        let root = promql_rows::with_series_identity(&root).unwrap();
         let space = asap_aware_mapping::search_workload(vec![("q", root)]);
         let selected = space
             .global_selection(&asap_aware_mapping::cost_model::DefaultCostModel)
             .assemble_selected_dag(&space.roots[0].1)
             .unwrap()
             .unwrap();
-        let dag = planner_types::post_asap::compile_post_asap_dag(&selected).unwrap();
+        let selected = planner_types::ir::apply_lifecycle_timings(
+            &selected,
+            &Default::default(),
+            &mut Default::default(),
+        )
+        .unwrap();
+        let dag = planner_types::ir::export::compile_physical_asap_dag(&selected).unwrap();
         let state = dag
             .nodes
             .iter()
@@ -378,7 +386,7 @@ mod tests {
             u64::from(state.id.0),
             InputContract::bounded(Arc::new(state.output_schema.clone())),
         )]);
-        (dag.clone(), inputs, u64::from(dag.root.0))
+        (dag.clone(), inputs, u64::from(dag.roots[0].0))
     }
 
     /// Enumerating and cutting every frontier lowers each Planner node once.
@@ -399,9 +407,9 @@ mod tests {
     }
 
     fn with_timing(
-        dag: &PostAsapDAG,
-        timing: impl Fn(&PostAsapDAGNode) -> planner_types::post_asap::ExecutionTiming,
-    ) -> PostAsapDAG {
+        dag: &PhysicalASAPDAG,
+        timing: impl Fn(&PhysicalASAPDAGNode) -> planner_types::post_asap::ExecutionTiming,
+    ) -> PhysicalASAPDAG {
         let mut timed = dag.clone();
         for node in &mut timed.nodes {
             node.output_state.timing = timing(node);
@@ -413,11 +421,18 @@ mod tests {
         timed
     }
 
-    fn raw_input(dag: &PostAsapDAG) -> BTreeMap<NodeId, InputContract> {
+    fn raw_input(dag: &PhysicalASAPDAG) -> BTreeMap<NodeId, InputContract> {
         let raw = dag
             .nodes
             .iter()
-            .find(|node| matches!(node.payload, Payload::Fallback { .. }))
+            .find(|node| {
+                matches!(
+                    node.payload,
+                    Payload::Relational {
+                        operator: planner_types::ir::export::NonASAPOpKind::TimeRange { .. }
+                    }
+                )
+            })
             .unwrap();
         BTreeMap::from([(
             u64::from(raw.id.0),
@@ -472,7 +487,7 @@ mod tests {
         use planner_types::post_asap::ExecutionTiming::{IngestionTime, QueryTime};
         let (dag, _, _) = grouped_rate();
         let timed = with_timing(&dag, |node| {
-            if node.id == dag.root {
+            if node.id == dag.roots[0] {
                 IngestionTime
             } else {
                 QueryTime
diff --git a/crates/asap-physical-operators/src/physical_planner/logical.rs b/crates/asap-physical-operators/src/physical_planner/logical.rs
new file mode 100644
index 000000000..dbc541895
--- /dev/null
+++ b/crates/asap-physical-operators/src/physical_planner/logical.rs
@@ -0,0 +1,374 @@
+//! Reconstruct shared operator references from the transport DAG for native lowering.
+use super::*;
+use planner_types::ir::export::{EdgeRole, NonASAPOpKind as N, PhysicalASAPNodeId, WireScalarExpr};
+use planner_types::ir::{
+    ASAPOp, NonASAPOp, Operator as LogicalOperator, OperatorNode, Predicate, ProjectItem,
+    ScalarExpr, SortKey as LogicalSortKey,
+};
+use std::rc::Rc;
+pub(super) fn scalar(
+    expr: &WireScalarExpr,
+    id_of: &mut impl FnMut(PhysicalASAPNodeId) -> Rc<OperatorNode>,
+) -> ScalarExpr {
+    fn boxed(
+        e: &WireScalarExpr,
+        id_of: &mut impl FnMut(PhysicalASAPNodeId) -> Rc<OperatorNode>,
+    ) -> Box<ScalarExpr> {
+        Box::new(scalar(e, id_of))
+    }
+    fn list(
+        es: &[WireScalarExpr],
+        id_of: &mut impl FnMut(PhysicalASAPNodeId) -> Rc<OperatorNode>,
+    ) -> Vec<ScalarExpr> {
+        es.iter().map(|e| scalar(e, id_of)).collect()
+    }
+    match expr {
+        WireScalarExpr::Column(id) => ScalarExpr::Column(*id),
+        WireScalarExpr::Literal(v) => ScalarExpr::Literal(v.clone()),
+        WireScalarExpr::Negative { expr, semantics } => ScalarExpr::Negative {
+            expr: boxed(expr, id_of),
+            semantics: *semantics,
+        },
+        WireScalarExpr::Compare {
+            left,
+            op,
+            right,
+            semantics,
+        } => ScalarExpr::Compare {
+            left: boxed(left, id_of),
+            op: op.clone(),
+            right: boxed(right, id_of),
+            semantics: *semantics,
+        },
+        WireScalarExpr::BoolAnd(parts) => ScalarExpr::BoolAnd(list(parts, id_of)),
+        WireScalarExpr::BoolOr(parts) => ScalarExpr::BoolOr(list(parts, id_of)),
+        WireScalarExpr::Not(e) => ScalarExpr::Not(boxed(e, id_of)),
+        WireScalarExpr::IsNull(e) => ScalarExpr::IsNull(boxed(e, id_of)),
+        WireScalarExpr::IsNotNull(e) => ScalarExpr::IsNotNull(boxed(e, id_of)),
+        WireScalarExpr::Cast { expr, to, try_cast } => ScalarExpr::Cast {
+            expr: boxed(expr, id_of),
+            to: to.clone(),
+            try_cast: *try_cast,
+        },
+        WireScalarExpr::InList {
+            expr,
+            list: items,
+            negated,
+        } => ScalarExpr::InList {
+            expr: boxed(expr, id_of),
+            list: list(items, id_of),
+            negated: *negated,
+        },
+        WireScalarExpr::FunctionCall { name, args } => ScalarExpr::FunctionCall {
+            name: name.clone(),
+            args: list(args, id_of),
+        },
+        WireScalarExpr::Arithmetic {
+            op,
+            left,
+            right,
+            semantics,
+        } => ScalarExpr::Arithmetic {
+            op: op.clone(),
+            left: boxed(left, id_of),
+            right: boxed(right, id_of),
+            semantics: *semantics,
+        },
+        WireScalarExpr::Case {
+            operand,
+            branches,
+            else_expr,
+        } => ScalarExpr::Case {
+            operand: operand.as_ref().map(|e| boxed(e, id_of)),
+            branches: branches
+                .iter()
+                .map(|(w, t)| (scalar(w, id_of), scalar(t, id_of)))
+                .collect(),
+            else_expr: else_expr.as_ref().map(|e| boxed(e, id_of)),
+        },
+        WireScalarExpr::CurrentTimestamp => ScalarExpr::CurrentTimestamp,
+        WireScalarExpr::EvalTimestamp => ScalarExpr::EvalTimestamp,
+        WireScalarExpr::PromqlScalarFromVector(node) => {
+            ScalarExpr::PromqlScalarFromVector(id_of(*node))
+        }
+        WireScalarExpr::ScalarSubquery(node) => ScalarExpr::ScalarSubquery(id_of(*node)),
+        WireScalarExpr::Exists { subquery, negated } => ScalarExpr::Exists {
+            subquery: id_of(*subquery),
+            negated: *negated,
+        },
+        WireScalarExpr::InSubquery {
+            expr,
+            subquery,
+            negated,
+        } => ScalarExpr::InSubquery {
+            expr: boxed(expr, id_of),
+            subquery: id_of(*subquery),
+            negated: *negated,
+        },
+    }
+}
+
+pub(super) fn restore(dag: &PhysicalASAPDAG) -> Result<BTreeMap<NodeId, Rc<OperatorNode>>, Error> {
+    dag.validate().map_err(|e| invalid(e.to_string()))?;
+    let mut done = BTreeMap::new();
+    let mut remaining: Vec<_> = dag.nodes.iter().collect();
+    while !remaining.is_empty() {
+        let before = remaining.len();
+        let mut next = Vec::new();
+        for node in remaining {
+            let mut edges: Vec<_> = dag.edges.iter().filter(|e| e.consumer == node.id).collect();
+            if edges
+                .iter()
+                .any(|e| !done.contains_key(&u64::from(e.producer.0)))
+            {
+                next.push(node);
+                continue;
+            }
+            edges.sort_by_key(|e| match e.role {
+                EdgeRole::Left => 0,
+                EdgeRole::Input => 1,
+                EdgeRole::Right => 2,
+                EdgeRole::ScalarRef => 3,
+            });
+            let inputs: Vec<_> = edges
+                .iter()
+                .filter(|e| e.role != EdgeRole::ScalarRef)
+                .map(|e| Rc::clone(&done[&u64::from(e.producer.0)]))
+                .collect();
+            let input = |index: usize| {
+                inputs
+                    .get(index)
+                    .cloned()
+                    .ok_or_else(|| invalid("operator is missing an input"))
+            };
+            let mut missing = false;
+            let mut ref_node = |id: PhysicalASAPNodeId| {
+                if let Some(node) = done.get(&u64::from(id.0)) {
+                    Rc::clone(node)
+                } else {
+                    missing = true;
+                    Rc::new(OperatorNode::with_schema(
+                        LogicalOperator::NonASAP(NonASAPOp::Values {
+                            rows: vec![],
+                            schema: Default::default(),
+                        }),
+                        Default::default(),
+                    ))
+                }
+            };
+            let mut value = |expr: &WireScalarExpr| scalar(expr, &mut ref_node);
+            let operator = match &node.payload {
+                Payload::Relational { operator } => LogicalOperator::NonASAP(match operator {
+                    N::Scan {
+                        source,
+                        predicates,
+                        schema,
+                    } => NonASAPOp::Scan {
+                        source: source.clone(),
+                        predicates: predicates.iter().map(|p| Predicate(value(&p.0))).collect(),
+                        schema: schema.clone(),
+                    },
+                    N::Values { rows, schema } => NonASAPOp::Values {
+                        rows: rows
+                            .iter()
+                            .map(|r| r.iter().map(&mut value).collect())
+                            .collect(),
+                        schema: schema.clone(),
+                    },
+                    N::Filter { pred } => NonASAPOp::Filter {
+                        pred: Predicate(value(&pred.0)),
+                        child: input(0)?,
+                    },
+                    N::Project { cols, qualifier } => NonASAPOp::Project {
+                        cols: cols
+                            .iter()
+                            .map(|c| ProjectItem {
+                                alias: c.alias.clone(),
+                                expr: value(&c.expr),
+                            })
+                            .collect(),
+                        qualifier: qualifier.clone(),
+                        child: input(0)?,
+                    },
+                    N::Aggregate {
+                        reduction,
+                        measures,
+                        output_names,
+                        filters,
+                        having,
+                    } => NonASAPOp::Aggregate {
+                        reduction: reduction.clone(),
+                        measures: measures.clone(),
+                        output_names: output_names.clone(),
+                        filters: filters
+                            .iter()
+                            .map(|p| p.as_ref().map(|p| Predicate(value(&p.0))))
+                            .collect(),
+                        having: having.as_ref().map(|p| Predicate(value(&p.0))),
+                        child: input(0)?,
+                    },
+                    N::Join { join_kind, pred } => NonASAPOp::Join {
+                        kind: join_kind.clone(),
+                        pred: Predicate(value(&pred.0)),
+                        left: input(0)?,
+                        right: input(1)?,
+                    },
+                    N::SetOp { set_kind, all } => NonASAPOp::SetOp {
+                        kind: set_kind.clone(),
+                        all: *all,
+                        left: input(0)?,
+                        right: input(1)?,
+                    },
+                    N::Concat {
+                        discriminator_unique_key,
+                    } => NonASAPOp::Concat {
+                        children: inputs.clone(),
+                        discriminator_unique_key: discriminator_unique_key.clone(),
+                    },
+                    N::Dedup { cols } => NonASAPOp::Dedup {
+                        cols: cols.clone(),
+                        child: input(0)?,
+                    },
+                    N::Sort { keys, partition_by } => NonASAPOp::Sort {
+                        keys: keys
+                            .iter()
+                            .map(|k| LogicalSortKey {
+                                expr: value(&k.expr),
+                                ascending: k.ascending,
+                                nulls_first: k.nulls_first,
+                            })
+                            .collect(),
+                        partition_by: partition_by.clone(),
+                        child: input(0)?,
+                    },
+                    N::Limit {
+                        n,
+                        offset,
+                        partition_by,
+                    } => NonASAPOp::Limit {
+                        n: *n,
+                        offset: *offset,
+                        partition_by: partition_by.clone(),
+                        child: input(0)?,
+                    },
+                    N::BinaryOp {
+                        operator,
+                        return_bool,
+                    } => NonASAPOp::BinaryOp {
+                        operator: operator.clone(),
+                        return_bool: *return_bool,
+                        lhs: input(0)?,
+                        rhs: input(1)?,
+                    },
+                    N::SQLWindowFunc {
+                        func,
+                        args,
+                        partition_by,
+                        order_by,
+                        frame,
+                        output_name,
+                    } => NonASAPOp::SQLWindowFunc {
+                        func: func.clone(),
+                        args: args.iter().map(&mut value).collect(),
+                        partition_by: partition_by.clone(),
+                        order_by: order_by
+                            .iter()
+                            .map(|k| LogicalSortKey {
+                                expr: value(&k.expr),
+                                ascending: k.ascending,
+                                nulls_first: k.nulls_first,
+                            })
+                            .collect(),
+                        frame: frame.clone(),
+                        output_name: output_name.clone(),
+                        child: input(0)?,
+                    },
+                    N::TimeRange { range, range_kind } => NonASAPOp::TimeRange {
+                        range: *range,
+                        kind: *range_kind,
+                        child: input(0)?,
+                    },
+                    N::TimeShift { shift } => NonASAPOp::TimeShift {
+                        shift: *shift,
+                        child: input(0)?,
+                    },
+                    N::PromqlVectorFromScalar { expr } => {
+                        NonASAPOp::PromqlVectorFromScalar(value(expr))
+                    }
+                    N::PromqlRelabel { dst, value: expr } => NonASAPOp::PromqlRelabel {
+                        dst: dst.clone(),
+                        value: value(expr),
+                        child: input(0)?,
+                    },
+                    N::PromqlInfoEnrich { selector } => NonASAPOp::PromqlInfoEnrich {
+                        selector: selector.clone(),
+                        child: input(0)?,
+                    },
+                    N::PromqlSeriesSample { by, sample_kind } => NonASAPOp::PromqlSeriesSample {
+                        by: by.clone(),
+                        kind: *sample_kind,
+                        child: input(0)?,
+                    },
+                    N::PromqlSubquery { range, resolution } => NonASAPOp::PromqlSubquery {
+                        range: *range,
+                        resolution: *resolution,
+                        child: input(0)?,
+                    },
+                }),
+                Payload::SummaryAgg {
+                    family,
+                    input: update,
+                    reduction,
+                    grouping,
+                    filter,
+                } => LogicalOperator::ASAP(ASAPOp::SummaryAgg {
+                    child: input(0)?,
+                    family: family.clone(),
+                    input: update.clone(),
+                    reduction: reduction.clone(),
+                    grouping: grouping.clone(),
+                    filter: filter.as_ref().map(|p| Predicate(value(&p.0))),
+                }),
+                Payload::SummaryEstimate { query } => {
+                    LogicalOperator::ASAP(ASAPOp::SummaryEstimate {
+                        summary_input: input(0)?,
+                        query: query.clone(),
+                    })
+                }
+                Payload::FinalizeExactAccumulator => {
+                    LogicalOperator::ASAP(ASAPOp::FinalizeExactAccumulator { child: input(0)? })
+                }
+                Payload::MaintainPopulation { population } => {
+                    LogicalOperator::ASAP(ASAPOp::MaintainPopulation {
+                        child: input(0)?,
+                        population: population.clone(),
+                    })
+                }
+                Payload::EvaluatePopulation { evaluation } => {
+                    LogicalOperator::ASAP(ASAPOp::EvaluatePopulation {
+                        child: input(0)?,
+                        evaluation: evaluation.clone(),
+                    })
+                }
+                Payload::SummaryMerge => LogicalOperator::ASAP(ASAPOp::SummaryMerge {
+                    children: inputs.clone(),
+                }),
+                _ => return Err(invalid("reserved ASAP operation has no native lowering")),
+            };
+            if missing {
+                return Err(invalid(
+                    "scalar reference is not a preceding DAG dependency",
+                ));
+            }
+            let mut rebuilt = OperatorNode::with_schema(operator, node.output_schema.clone());
+            rebuilt.guarantee = node.guarantee.clone();
+            rebuilt.timing = Some(node.output_state.timing);
+            done.insert(u64::from(node.id.0), Rc::new(rebuilt));
+        }
+        if next.len() == before {
+            return Err(invalid("operator DAG is cyclic"));
+        }
+        remaining = next;
+    }
+    Ok(done)
+}
diff --git a/crates/asap-physical-operators/src/physical_planner/mod.rs b/crates/asap-physical-operators/src/physical_planner/mod.rs
index e1490c03c..2bd57bf21 100644
--- a/crates/asap-physical-operators/src/physical_planner/mod.rs
+++ b/crates/asap-physical-operators/src/physical_planner/mod.rs
@@ -1,23 +1,25 @@
 //! Compile logical computation to native operators with typed external inputs.
 //! Compilation needs no readers; deployment resolves inputs after selection.
-use crate::operators::ReadoutQuery;
-use crate::summary_kernels::exact::ExactReadout;
+use crate::operators::SummaryEvaluation;
+use crate::summary_kernels::exact::ExactEvaluation;
 use crate::{
     operators::{Expression, Operator, Reduction, SortKey},
     plan::{Boundedness, Emission, NodeId, PhysicalDAG, PhysicalOperator, PlanProperties},
     values::{Batch, SchemaRef},
     Error,
 };
+use planner_types::ir::export::{
+    NonASAPOpKind, PhysicalASAPDAG, PhysicalASAPDAGNode, PhysicalASAPOperatorPayload as Payload,
+    WireScalarExpr,
+};
+use planner_types::ir::{ASAPOp, NonASAPOp, Operator as LogicalOperator, OperatorNode, ScalarExpr};
 use planner_types::{
-    post_asap::{
-        ExactOperation, FieldDataType, PostAsapDAG, PostAsapDAGNode,
-        PostAsapOperatorPayload as Payload, SketchStatistic, SummaryInputExpr, ValueOperation,
-    },
+    post_asap::{FieldDataType, SketchStatistic, SummaryInputExpr},
     pre_asap::{
-        AggIntent, ColumnRef, CompareOpKind, DataType, GroupKeys, QueryExpr,
-        Reduction as PlannerReduction,
+        AggIntent, ColumnRef, CompareOpKind, DataType, GroupKeys, Reduction as PlannerReduction,
     },
 };
+mod logical;
 use std::{
     collections::{BTreeMap, BTreeSet},
     sync::Arc,
@@ -39,7 +41,8 @@ pub mod promql_values;
 mod candidates;
 pub use candidates::{
     compile_candidate, compile_candidates, cut_candidate, enumerate_frontiers,
-    frontier_from_timing, select_candidate, CandidateCost, CandidateSelection, PhysicalASAPDAG,
+    frontier_from_timing, select_candidate, CandidateCost, CandidateSelection,
+    CompiledPhysicalPlan,
 };
 
 mod compiled;
@@ -50,7 +53,7 @@ mod row_values;
 /// Compile computation without opening or retaining deployment readers.
 /// Input contracts identify explicit boundaries selected by maintenance planning.
 pub fn compile(
-    dag: &PostAsapDAG,
+    dag: &PhysicalASAPDAG,
     inputs: BTreeMap<NodeId, InputContract>,
     roots: &[NodeId],
 ) -> Result<CompiledPhysicalDAG, Error> {
@@ -60,7 +63,7 @@ pub fn compile(
 /// Convenience for callers that already resolved inputs. Lowering still uses
 /// only their contracts, and instantiation checks those contracts again.
 pub fn bind<'a>(
-    dag: &PostAsapDAG,
+    dag: &PhysicalASAPDAG,
     sources: BTreeMap<NodeId, Source<'a>>,
     roots: &[NodeId],
 ) -> Result<PhysicalDAG<'a, Batch, SchemaRef>, Error> {
@@ -73,11 +76,12 @@ pub fn bind<'a>(
 
 /// Resolve raw scan connectors before invoking the reader-independent compiler.
 pub fn bind_with_data_sources<'a>(
-    dag: &PostAsapDAG,
+    dag: &PhysicalASAPDAG,
     mut sources: BTreeMap<NodeId, Source<'a>>,
     roots: &[NodeId],
     data_sources: &crate::sources::DataSources,
 ) -> Result<PhysicalDAG<'a, Batch, SchemaRef>, Error> {
+    let restored = logical::restore(dag)?;
     // Only resolve scans reachable below the selected input boundaries.
     let mut pending = roots.to_vec();
     let mut seen = BTreeSet::new();
@@ -85,16 +89,13 @@ pub fn bind_with_data_sources<'a>(
         if !seen.insert(id) || sources.contains_key(&id) {
             continue;
         }
-        let node = dag
+        let _node = dag
             .nodes
             .iter()
             .find(|n| u64::from(n.id.0) == id)
             .ok_or_else(|| invalid(format!("missing node {id}")))?;
-        if let Payload::Fallback {
-            expression: expression @ QueryExpr::Scan { .. },
-        } = &node.payload
-        {
-            sources.insert(id, Box::new(data_sources.bind(expression)?));
+        if matches!(restored[&id].non_asap(), Some(NonASAPOp::Scan { .. })) {
+            sources.insert(id, Box::new(data_sources.bind(&restored[&id])?));
         } else {
             pending.extend(
                 dag.edges
@@ -123,11 +124,12 @@ fn helper_id(node: NodeId, index: u64) -> NodeId {
 }
 
 fn compile_internal(
-    dag: &PostAsapDAG,
+    dag: &PhysicalASAPDAG,
     mut sources: BTreeMap<NodeId, InputContract>,
     roots: &[NodeId],
 ) -> Result<CompiledPhysicalDAG, Error> {
     preflight_depth(dag)?;
+    let restored = logical::restore(dag)?;
     dag.validate().map_err(|e| invalid(e.to_string()))?;
     let nodes = dag
         .nodes
@@ -141,46 +143,43 @@ fn compile_internal(
         (
             edge.consumer.0,
             match edge.role {
-                planner_types::post_asap::EdgeRole::Left => 0,
-                planner_types::post_asap::EdgeRole::Input => 1,
-                planner_types::post_asap::EdgeRole::Right => 2,
+                planner_types::ir::export::EdgeRole::Left => 0,
+                planner_types::ir::export::EdgeRole::Input => 1,
+                planner_types::ir::export::EdgeRole::Right => 2,
+                planner_types::ir::export::EdgeRole::ScalarRef => 3,
             },
         )
     });
-    // Scalar literal operands of query-time arithmetic are folded into the consumer.
-    let mut literals = BTreeMap::<NodeId, (f64, bool)>::new();
+    let literals = BTreeMap::<NodeId, (f64, bool)>::new();
     for edge in edges {
-        let consumer = u64::from(edge.consumer.0);
-        if let (
-            Payload::Fallback { expression },
-            Some(PostAsapDAGNode {
-                payload: Payload::Binary { .. },
-                ..
-            }),
-        ) = (
-            &nodes[&u64::from(edge.producer.0)].payload,
-            nodes.get(&consumer),
-        ) {
-            if let Some(value) = row_values::scalar_literal(expression) {
-                let left = edge.role == planner_types::post_asap::EdgeRole::Left;
-                if literals.insert(consumer, (value, left)).is_some() {
-                    return Err(invalid("binary with two scalar literals is not folded"));
-                }
-                continue;
-            }
-        }
         dependencies
             .entry(u64::from(edge.consumer.0))
             .or_default()
             .push(u64::from(edge.producer.0));
     }
+    let mut fallback = BTreeMap::new();
+    for (&id, root) in &restored {
+        let raw_summary_input = matches!(root.non_asap(), Some(NonASAPOp::TimeRange { .. }))
+            && dag.edges.iter().any(|e| {
+                u64::from(e.producer.0) == id
+                    && matches!(
+                        nodes[&u64::from(e.consumer.0)].payload,
+                        Payload::SummaryAgg { .. }
+                    )
+            });
+        if !root.contains_asap() && !raw_summary_input {
+            if let Ok(lowered) = promql_fallback::lower(root) {
+                fallback.insert(id, lowered);
+            }
+        }
+    }
     let known = |id: &NodeId| {
         nodes.contains_key(id)
             || promql_fallback::raw_series_owner(*id).is_some_and(|owner| {
                 matches!(
                     nodes.get(&owner),
-                    Some(PostAsapDAGNode {
-                        payload: Payload::Fallback { .. },
+                    Some(PhysicalASAPDAGNode {
+                        payload: Payload::Relational { .. },
                         ..
                     })
                 )
@@ -204,7 +203,7 @@ fn compile_internal(
             return Err(invalid(format!("missing root {id}")));
         }
         pending.push((id, true));
-        if !sources.contains_key(&id) {
+        if !sources.contains_key(&id) && !fallback.contains_key(&id) {
             for &input in dependencies.get(&id).into_iter().flatten() {
                 pending.push((input, false));
             }
@@ -241,20 +240,11 @@ fn compile_internal(
                 inputs = vec![auxiliary];
                 schemas.truncate(1);
             }
-            // A consumed bare selector supplies raw range rows (e.g. to a
-            // per-entity summary), not an instant vector, so only its consumer computes.
-            let raw_rows = matches!(
-                &node.payload,
-                Payload::Fallback {
-                    expression: QueryExpr::TimeRange { .. }
-                }
-            ) && dag.edges.iter().any(|e| u64::from(e.producer.0) == id);
-            if let (Payload::Fallback { expression }, false) = (&node.payload, raw_rows) {
-                let promql_fallback::Lowering {
-                    selectors,
-                    mut steps,
-                } = promql_fallback::lower(expression)
-                    .map_err(|error| invalid(format!("node {id}: {error}")))?;
+            if let Some(promql_fallback::Lowering {
+                selectors,
+                mut steps,
+            }) = fallback.remove(&id)
+            {
                 let mut slots = Vec::new();
                 for (i, (_, schema)) in selectors.iter().enumerate() {
                     let slot = promql_fallback::raw_series_input(id, i);
@@ -300,10 +290,7 @@ fn compile_internal(
                 )?;
                 continue;
             }
-            if let Payload::Value {
-                operation: ValueOperation::MaintainPopulation { population },
-            } = &node.payload
-            {
+            if let Payload::MaintainPopulation { population } = &node.payload {
                 use planner_types::post_asap::maintained_population::PopulationInput;
                 let PopulationInput::CurrentSeries(spec) = &population.input else {
                     return Err(invalid(
@@ -336,22 +323,16 @@ fn compile_internal(
                 )?;
                 continue;
             }
-            if let Payload::Value {
-                operation: ValueOperation::ReadPopulation { readout },
-            } = &node.payload
-            {
+            if let Payload::EvaluatePopulation { evaluation } = &node.payload {
                 use planner_types::post_asap::maintained_population::{
                     PopulationInput, PopulationStatistic,
                 };
                 let [producer] = inputs.as_slice() else {
-                    return Err(invalid("population readout requires one input"));
+                    return Err(invalid("population evaluation requires one input"));
                 };
-                let Payload::Value {
-                    operation: ValueOperation::MaintainPopulation { population },
-                } = &nodes[producer].payload
-                else {
+                let Payload::MaintainPopulation { population } = &nodes[producer].payload else {
                     return Err(invalid(
-                        "population readout requires its declared population",
+                        "population evaluation requires its declared population",
                     ));
                 };
                 let PopulationInput::CurrentSeries(spec) = &population.input else {
@@ -363,9 +344,9 @@ fn compile_internal(
                     ));
                 }
                 let input = schemas[0].clone();
-                let PopulationStatistic::TopK { k } = readout else {
+                let PopulationStatistic::TopK { k } = evaluation else {
                     let mut chain =
-                        row_values::population_aggregate(&input, &spec.grouping, readout)?;
+                        row_values::population_aggregate(&input, &spec.grouping, evaluation)?;
                     let last = chain.pop().expect("nonempty chain");
                     let mut inputs = inputs;
                     for operator in chain {
@@ -415,15 +396,12 @@ fn compile_internal(
                 let [input_id] = inputs.as_slice() else {
                     return Err(invalid("per-entity summary requires one input"));
                 };
-                let Payload::Fallback {
-                    expression: QueryExpr::TimeRange { child, .. },
-                } = &nodes[input_id].payload
-                else {
+                let Some(NonASAPOp::TimeRange { child, .. }) = restored[input_id].non_asap() else {
                     return Err(invalid(
                         "per-entity summary requires a resolved raw time range",
                     ));
                 };
-                let QueryExpr::Scan { schema, .. } = child.as_ref() else {
+                let Some(NonASAPOp::Scan { schema, .. }) = child.non_asap() else {
                     return Err(invalid("per-entity summary requires a resolved source"));
                 };
                 if !schema.closed || update.item.is_some() {
@@ -462,7 +440,18 @@ fn compile_internal(
                 )?;
                 continue;
             }
-            if let Payload::Binary { operator } = &node.payload {
+            if let Payload::Relational {
+                operator:
+                    NonASAPOpKind::BinaryOp {
+                        operator,
+                        return_bool,
+                    },
+            } = &node.payload
+            {
+                let operator = crate::expressions::binary::BinaryOperator::from_logical(
+                    operator,
+                    *return_bool,
+                );
                 let query_time = node.output_state.timing
                     == planner_types::post_asap::ExecutionTiming::QueryTime;
                 if let Some(&(value, left)) = literals.get(&id) {
@@ -505,19 +494,11 @@ fn compile_internal(
                 // carry the series identity.
                 if let (true, [left, right]) = (query_time, schemas.as_slice()) {
                     if !label_map(left) && !label_map(right) {
-                        // A scalar-valued Fallback operand, such as `scalar(x)`, has no labels.
-                        let scalar = |input: &NodeId| {
-                            matches!(
-                                nodes.get(input).map(|node| &node.payload),
-                                Some(Payload::Fallback { expression })
-                                    if promql_fallback::scalar(expression)
-                            )
-                        };
                         let binary = Operator::series_binary(
                             left.clone(),
                             right.clone(),
                             operator.clone(),
-                            [scalar(&inputs[0]), scalar(&inputs[1])],
+                            [false, false],
                         )
                         .map_err(|error| invalid(format!("node {id}: {error}")))?;
                         physical_dag.add(id, inputs, binary.with_output_schema(output)?)?;
@@ -525,14 +506,11 @@ fn compile_internal(
                     }
                 }
             }
-            if let Payload::Value {
-                operation: ValueOperation::FinalizeExactAccumulator,
-            } = &node.payload
-            {
+            if let Payload::FinalizeExactAccumulator = &node.payload {
                 // Exact counts read out as Int64; PromQL declares a Float64 sample.
-                let readout = bind_operation(node, &schemas)
+                let evaluation = bind_operation(node, &schemas)
                     .map_err(|error| invalid(format!("node {id}: {error}")))?;
-                let actual = readout.schema();
+                let actual = evaluation.schema();
                 let converted = actual.fields.iter().zip(&output.fields).position(|(a, d)| {
                     a.dtype == FieldDataType::Plain(DataType::Int64)
                         && d.dtype == FieldDataType::Plain(DataType::Float64)
@@ -555,8 +533,8 @@ fn compile_internal(
                         .collect();
                     let project =
                         Operator::project(actual, columns)?.with_output_schema(output.clone())?;
-                    physical_dag.add(auxiliary, inputs, readout)?;
-                    if temporal_readout_drops_name(node) {
+                    physical_dag.add(auxiliary, inputs, evaluation)?;
+                    if temporal_evaluation_drops_name(node) {
                         physical_dag.add(auxiliary - 1, vec![auxiliary], project)?;
                         physical_dag.add(
                             id,
@@ -572,7 +550,7 @@ fn compile_internal(
             }
             let mut operator = compile_node(node, &schemas)
                 .map_err(|error| invalid(format!("node {id}: {error}")))?;
-            if operator.is_counter_readout() {
+            if operator.is_counter_evaluation() {
                 let mut pending = vec![id];
                 let mut visited = BTreeSet::new();
                 let mut ranges = BTreeSet::new();
@@ -580,8 +558,8 @@ fn compile_internal(
                     if !visited.insert(ancestor) {
                         continue;
                     }
-                    if let Payload::Fallback {
-                        expression: QueryExpr::TimeRange { range, .. },
+                    if let Payload::Relational {
+                        operator: NonASAPOpKind::TimeRange { range, .. },
                     } = &nodes[&ancestor].payload
                     {
                         ranges.insert(
@@ -593,13 +571,13 @@ fn compile_internal(
                     pending.extend(dependencies.get(&ancestor).into_iter().flatten().copied());
                 }
                 if ranges.len() > 1 {
-                    return Err(invalid("counter readout has ambiguous logical windows"));
+                    return Err(invalid("counter evaluation has ambiguous logical windows"));
                 }
                 if let Some(lookback) = ranges.into_iter().next() {
                     operator = operator.with_counter_lookback(lookback)?;
                 }
             }
-            if temporal_readout_drops_name(node) {
+            if temporal_evaluation_drops_name(node) {
                 physical_dag.add(auxiliary, inputs, operator)?;
                 physical_dag.add(id, vec![auxiliary], Operator::series_without_name(output)?)?;
             } else {
@@ -611,38 +589,45 @@ fn compile_internal(
     Ok(physical_dag)
 }
 
-// Temporal summary readouts produce PromQL vectors, whose range functions drop
+// Temporal summary evaluations produce PromQL vectors, whose range functions drop
 // the metric name before matching/filtering. Stored state retains its full identity.
-fn temporal_readout_drops_name(node: &PostAsapDAGNode) -> bool {
+fn temporal_evaluation_drops_name(node: &PhysicalASAPDAGNode) -> bool {
     node.output_schema
         .fields
         .iter()
         .any(|field| field.name == promql_rows::SERIES_IDENTITY_COLUMN)
         && matches!(
             &node.payload,
-            Payload::Value {
-                operation: ValueOperation::FinalizeExactAccumulator
-            } | Payload::SummaryEstimate {
-                query: SketchStatistic::Quantile { .. }
-                    | SketchStatistic::Cardinality
-                    | SketchStatistic::PointCount { .. }
-                    | SketchStatistic::FrequencyL2
-                    | SketchStatistic::FrequencyEntropy
-            }
+            Payload::FinalizeExactAccumulator
+                | Payload::SummaryEstimate {
+                    query: SketchStatistic::Quantile { .. }
+                        | SketchStatistic::Cardinality
+                        | SketchStatistic::PointCount { .. }
+                        | SketchStatistic::FrequencyL2
+                        | SketchStatistic::FrequencyEntropy
+                }
         )
 }
 
 /// Bind a Planner node against the schemas supplied by its deployment edges.
 /// This is the same checked path used by complete DAG binding.
-pub fn compile_node(node: &PostAsapDAGNode, inputs: &[SchemaRef]) -> Result<Operator, Error> {
+pub fn compile_node(node: &PhysicalASAPDAGNode, inputs: &[SchemaRef]) -> Result<Operator, Error> {
     for schema in inputs {
         crate::values::validate_schema(schema)?;
     }
     bind_operation(node, inputs)?.with_output_schema(Arc::new(node.output_schema.clone()))
 }
 
-fn bind_operation(node: &PostAsapDAGNode, inputs: &[SchemaRef]) -> Result<Operator, Error> {
-    if let Payload::Binary { operator } = &node.payload {
+fn bind_operation(node: &PhysicalASAPDAGNode, inputs: &[SchemaRef]) -> Result<Operator, Error> {
+    if let Payload::Relational {
+        operator: NonASAPOpKind::BinaryOp {
+            operator,
+            return_bool,
+        },
+    } = &node.payload
+    {
+        let operator =
+            crate::expressions::binary::BinaryOperator::from_logical(operator, *return_bool);
         let [left, right] = inputs else {
             return Err(invalid("binary requires two inputs"));
         };
@@ -688,54 +673,83 @@ fn bind_operation(node: &PostAsapDAGNode, inputs: &[SchemaRef]) -> Result<Operat
         }
         return Operator::vector_binary(left.clone(), right.clone(), operator.clone(), false);
     }
-    if let Payload::RelationalJoin {
-        join_kind,
-        pred,
-        pruning,
+    if let Payload::Relational {
+        operator: NonASAPOpKind::Join { join_kind, pred },
     } = &node.payload
     {
-        use planner_types::{post_asap::CandidateCompleteness, pre_asap::JoinKind};
-        if pruning.is_some() && *join_kind != JoinKind::Semi {
-            return Err(invalid("pruning certificate requires a semi-join"));
-        }
-        if matches!(pruning,Some(CandidateCompleteness::Certified { guarantee }) if guarantee.has_unknown() || guarantee.metric != planner_types::post_asap::ErrorMetric::TopKMembership)
-        {
-            return Err(invalid("invalid pruning certificate"));
-        }
         let [left, right] = inputs else {
             return Err(invalid("join requires two inputs"));
         };
-        if *join_kind == JoinKind::Semi {
-            if let Ok(keys) = equijoin_keys(pred, left, right) {
-                let operator = Operator::semi_join(left.clone(), right.clone(), keys)?;
-                return Ok(
-                    if matches!(pruning, Some(CandidateCompleteness::Certified { .. })) {
-                        operator.require_complete_right()
-                    } else {
-                        operator
-                    },
-                );
+        let pred = planner_types::ir::Predicate(local_scalar(&pred.0)?);
+        if *join_kind == planner_types::pre_asap::JoinKind::Semi {
+            if let Ok(keys) = equijoin_keys(&pred, left, right) {
+                return Operator::semi_join(left.clone(), right.clone(), keys);
             }
         }
-        if matches!(pruning, Some(CandidateCompleteness::Certified { .. })) {
-            return Err(invalid("certified pruning requires explicit equijoin keys"));
-        }
         return Operator::relational_join(
             left.clone(),
             right.clone(),
             join_kind.clone(),
-            pred,
+            &pred,
             Arc::new(node.output_schema.clone()),
         );
     }
+    if let Payload::Relational {
+        operator: NonASAPOpKind::Values { rows, schema },
+    } = &node.payload
+    {
+        if !inputs.is_empty() {
+            return Err(invalid("Values takes no relational inputs"));
+        }
+        let empty = Arc::new(planner_types::pre_asap::Schema::default());
+        let rows = rows
+            .iter()
+            .map(|row| {
+                row.iter()
+                    .map(|expr| expression(expr, &empty)?.evaluate(&[]))
+                    .collect::<Result<Vec<_>, Error>>()
+            })
+            .collect::<Result<Vec<_>, Error>>()?;
+        let schema = Arc::new(schema.clone());
+        return Operator::source(
+            schema.clone(),
+            vec![crate::values::Batch::try_new(schema, rows)?],
+        );
+    }
     let [input] = inputs else {
         return Err(invalid(
             "native Planner binding currently requires a unary operation or an explicit source",
         ));
     };
     match &node.payload {
-        Payload::Value { operation, .. } => match operation {
-            ValueOperation::Project { cols, .. } => Operator::project(
+        Payload::FinalizeExactAccumulator => {
+            let state = summary_column(input)?;
+            use crate::Statistic as S;
+            use planner_types::post_asap::ExactKind as E;
+            let statistic = match &input.fields[state].dtype {
+                FieldDataType::ExactAggregate(kind, _) => match kind {
+                    E::Sum => S::Sum,
+                    E::Count => S::Count,
+                    E::Min => S::Min,
+                    E::Max => S::Max,
+                    E::Rate => S::Rate,
+                    E::Increase => S::Increase,
+                    _ => return Err(invalid("exact family evaluation is unsupported")),
+                },
+                _ => return Err(invalid("exact finalization requires exact state")),
+            };
+            Operator::evaluation(
+                input.clone(),
+                state,
+                SummaryEvaluation::Exact(ExactEvaluation {
+                    statistic,
+                    lookback_ms: None,
+                }),
+            )
+        }
+
+        Payload::Relational { operator } => match operator {
+            NonASAPOpKind::Project { cols, .. } => Operator::project(
                 input.clone(),
                 cols.iter()
                     .enumerate()
@@ -748,21 +762,21 @@ fn bind_operation(node: &PostAsapDAGNode, inputs: &[SchemaRef]) -> Result<Operat
                                 .name
                                 .clone(),
                             match &col.expr {
-                                QueryExpr::Column(index) => Expression::Column(*index),
+                                WireScalarExpr::Column(index) => Expression::Column(*index),
                                 expr => expression(expr, input)?,
                             },
                         ))
                     })
                     .collect::<Result<_, Error>>()?,
             ),
-            ValueOperation::Filter { pred } => {
+            NonASAPOpKind::Filter { pred } => {
                 Operator::filter(input.clone(), expression(&pred.0, input)?)
             }
-            ValueOperation::Sort { keys, partition_by } => Operator::sort(
+            NonASAPOpKind::Sort { keys, partition_by } => Operator::sort(
                 input.clone(),
                 keys.iter()
                     .map(|key| {
-                        let QueryExpr::Column(column) = key.expr else {
+                        let WireScalarExpr::Column(column) = key.expr else {
                             return Err(invalid(
                                 "sort expression must be projected before sorting",
                             ));
@@ -776,23 +790,23 @@ fn bind_operation(node: &PostAsapDAGNode, inputs: &[SchemaRef]) -> Result<Operat
                     .collect::<Result<_, Error>>()?,
                 groups(input, partition_by)?,
             ),
-            ValueOperation::Limit {
+            NonASAPOpKind::Limit {
                 n,
                 offset,
                 partition_by,
             } => Operator::limit(
                 input.clone(),
-                *n as u64,
+                n.unwrap_or(usize::MAX) as u64,
                 *offset as u64,
                 groups(input, partition_by)?,
             ),
-            ValueOperation::Exact(ExactOperation::Aggregate {
+            NonASAPOpKind::Aggregate {
                 reduction,
                 measures,
                 output_names,
                 filters,
                 having: None,
-            }) => {
+            } => {
                 if filters.iter().any(Option::is_some) {
                     return Err(invalid("filtered aggregate has no native implementation"));
                 }
@@ -829,31 +843,6 @@ fn bind_operation(node: &PostAsapDAGNode, inputs: &[SchemaRef]) -> Result<Operat
                     .collect::<Result<_, Error>>()?;
                 Operator::aggregate(input.clone(), groups(input, keys)?, measures)
             }
-            ValueOperation::FinalizeExactAccumulator => {
-                let state = summary_column(input)?;
-                use crate::Statistic as S;
-                use planner_types::post_asap::ExactKind as E;
-                let statistic = match &input.fields[state].dtype {
-                    FieldDataType::ExactAggregate(kind, _) => match kind {
-                        E::Sum => S::Sum,
-                        E::Count => S::Count,
-                        E::Min => S::Min,
-                        E::Max => S::Max,
-                        E::Rate => S::Rate,
-                        E::Increase => S::Increase,
-                        _ => return Err(invalid("exact family readout is unsupported")),
-                    },
-                    _ => return Err(invalid("exact finalization requires exact state")),
-                };
-                Operator::readout(
-                    input.clone(),
-                    state,
-                    ReadoutQuery::Exact(ExactReadout {
-                        statistic,
-                        lookback_ms: None,
-                    }),
-                )
-            }
             _ => Err(invalid("value operation has no native implementation")),
         },
         Payload::SummaryAgg {
@@ -945,17 +934,17 @@ fn bind_operation(node: &PostAsapDAGNode, inputs: &[SchemaRef]) -> Result<Operat
         }
         Payload::SummaryEstimate { query } => {
             if let SketchStatistic::TopK { k } = query {
-                return Operator::keyed_readout(
+                return Operator::keyed_evaluation(
                     input.clone(),
                     summary_column(input)?,
                     *k,
                     Arc::new(node.output_schema.clone()),
                 );
             }
-            Operator::readout(
+            Operator::evaluation(
                 input.clone(),
                 summary_column(input)?,
-                ReadoutQuery::Sketch(query.clone()),
+                SummaryEvaluation::Sketch(query.clone()),
             )
         }
         _ => Err(invalid(
@@ -1009,9 +998,10 @@ fn groups(input: &SchemaRef, groups: &GroupKeys) -> Result<Vec<usize>, Error> {
     }
     Ok(groups.keys().to_vec())
 }
-fn expression(expr: &QueryExpr, input: &SchemaRef) -> Result<Expression, Error> {
+fn expression(expr: &WireScalarExpr, input: &SchemaRef) -> Result<Expression, Error> {
+    let expr = local_scalar(expr)?;
     Ok(Expression::planner(
-        crate::expressions::CompiledExpression::compile(expr, input)?,
+        crate::expressions::CompiledExpression::compile(&expr, input)?,
     ))
 }
 
@@ -1057,7 +1047,7 @@ impl PhysicalOperator<Batch, SchemaRef> for CheckedSource<'_> {
 }
 
 // Bound recursion before invoking the upstream recursive provenance validator.
-fn preflight_depth(dag: &PostAsapDAG) -> Result<(), Error> {
+fn preflight_depth(dag: &PhysicalASAPDAG) -> Result<(), Error> {
     let mut remaining = dag
         .nodes
         .iter()
@@ -1110,23 +1100,24 @@ fn preflight_depth(dag: &PostAsapDAG) -> Result<(), Error> {
 
 /// Join predicates address the concatenated left/right schema.
 fn semi_join_keys(
-    expr: &QueryExpr,
+    expr: &ScalarExpr,
     left: usize,
     right: usize,
     keys: &mut Vec<(usize, usize)>,
 ) -> Result<(), Error> {
     match expr {
-        QueryExpr::BoolAnd(parts) => {
+        ScalarExpr::BoolAnd(parts) => {
             for part in parts {
                 semi_join_keys(part, left, right, keys)?;
             }
         }
-        QueryExpr::Compare {
+        ScalarExpr::Compare {
             left: a,
             op: CompareOpKind::Eq,
             right: b,
+            ..
         } => {
-            let (QueryExpr::Column(a), QueryExpr::Column(b)) = (a.as_ref(), b.as_ref()) else {
+            let (ScalarExpr::Column(a), ScalarExpr::Column(b)) = (a.as_ref(), b.as_ref()) else {
                 return Err(invalid("semi-join requires column equality keys"));
             };
             let (a, b) = if a < b { (*a, *b) } else { (*b, *a) };
@@ -1143,7 +1134,7 @@ fn semi_join_keys(
 /// Resolve equality keys against the Planner join's concatenated input schema.
 /// Deployments may use these positions to bind their source columns.
 pub fn equijoin_keys(
-    pred: &planner_types::pre_asap::Predicate,
+    pred: &planner_types::ir::Predicate,
     left: &planner_types::post_asap::Schema,
     right: &planner_types::post_asap::Schema,
 ) -> Result<Vec<(usize, usize)>, Error> {
@@ -1154,3 +1145,24 @@ pub fn equijoin_keys(
     }
     Ok(keys)
 }
+
+fn local_scalar(expr: &WireScalarExpr) -> Result<ScalarExpr, Error> {
+    let mut missing = false;
+    let result = logical::scalar(expr, &mut |_| {
+        missing = true;
+        std::rc::Rc::new(OperatorNode::with_schema(
+            LogicalOperator::NonASAP(NonASAPOp::Values {
+                rows: vec![],
+                schema: Default::default(),
+            }),
+            Default::default(),
+        ))
+    });
+    if missing {
+        Err(invalid(
+            "scalar plan reads require explicit execution bindings",
+        ))
+    } else {
+        Ok(result)
+    }
+}
diff --git a/crates/asap-physical-operators/src/physical_planner/precompute.rs b/crates/asap-physical-operators/src/physical_planner/precompute.rs
index 10dffdc0c..2771465a9 100644
--- a/crates/asap-physical-operators/src/physical_planner/precompute.rs
+++ b/crates/asap-physical-operators/src/physical_planner/precompute.rs
@@ -1,6 +1,7 @@
 //! Compile immutable summary-input computation with explicit population and pane identity.
 use super::promql_rows::SERIES_IDENTITY_COLUMN as SERIES_IDENTITY;
 use super::*;
+use planner_types::post_asap::FieldDataType as SummaryFamilyType;
 use planner_types::{
     post_asap::{ExecutionTiming, GroupingStrategy, Schema},
     pre_asap::DataType,
@@ -8,35 +9,35 @@ use planner_types::{
 
 /// Physical rows carry the population and pane coordinate alongside the logical value.
 /// These fields preserve identities which are implicit in a stored summary instance.
-pub fn population_schema(family: FieldDataType) -> SchemaRef {
+pub fn population_schema(family: SummaryFamilyType) -> SchemaRef {
     Arc::new(Schema {
-        closed: true,
-        unique_keys: vec![],
         fields: vec![
             planner_types::post_asap::Field {
-                table: None,
                 name: "$population".into(),
-                dtype: FieldDataType::Plain(DataType::Map {
+                dtype: SummaryFamilyType::Plain(DataType::Map {
                     key: Box::new(DataType::Utf8),
                     value: Box::new(DataType::Utf8),
                     value_nullable: false,
                 }),
                 nullable: false,
+                table: None,
             },
             planner_types::post_asap::Field {
-                table: None,
                 name: "$window_end".into(),
-                dtype: FieldDataType::Plain(DataType::Timestamp),
+                dtype: SummaryFamilyType::Plain(DataType::Timestamp),
                 nullable: false,
+                table: None,
             },
             planner_types::post_asap::Field {
-                table: None,
                 name: "value".into(),
                 dtype: family,
                 nullable: false,
+                table: None,
             },
         ],
         time_index: Some(1),
+        unique_keys: vec![],
+        closed: false,
     })
 }
 
@@ -48,7 +49,7 @@ pub fn population_schema(family: FieldDataType) -> SchemaRef {
 /// must be canonical (sorted, unique, no empty values), since they are the
 /// population identity: build rows with [`raw_sample_row`].
 pub fn raw_sample_schema() -> SchemaRef {
-    let mut schema = (*population_schema(FieldDataType::Plain(DataType::Float64))).clone();
+    let mut schema = (*population_schema(SummaryFamilyType::Plain(DataType::Float64))).clone();
     schema.fields[1].name = "$timestamp".into();
     Arc::new(schema)
 }
@@ -82,19 +83,14 @@ pub fn raw_sample_row(
 
 /// Input contract of a precompute boundary: raw sample rows for a raw time
 /// series scan, otherwise the stored population of its summary state.
-pub fn boundary_schema(node: &PostAsapDAGNode) -> Result<SchemaRef, Error> {
-    let Payload::Fallback { expression } = &node.payload else {
-        return source_schema(&node.output_schema);
-    };
-    let scan = match expression {
-        planner_types::pre_asap::QueryExpr::TimeRange { child, .. } => child.as_ref(),
-        expression => expression,
-    };
+pub fn boundary_schema(node: &PhysicalASAPDAGNode) -> Result<SchemaRef, Error> {
     if !matches!(
-        scan,
-        planner_types::pre_asap::QueryExpr::Scan {
-            source: planner_types::pre_asap::Source::TimeSeries { .. },
-            ..
+        &node.payload,
+        Payload::Relational {
+            operator: NonASAPOpKind::Scan {
+                source: planner_types::pre_asap::Source::TimeSeries { .. },
+                ..
+            } | NonASAPOpKind::TimeRange { .. }
         }
     ) {
         return source_schema(&node.output_schema);
@@ -106,11 +102,11 @@ pub fn boundary_schema(node: &PostAsapDAGNode) -> Result<SchemaRef, Error> {
         .iter()
         .enumerate()
         .all(|(i, field)| match &field.dtype {
-            FieldDataType::Plain(DataType::Timestamp) => {
+            SummaryFamilyType::Plain(DataType::Timestamp) => {
                 Some(i) == logical.time_index && !field.nullable
             }
-            FieldDataType::Plain(DataType::Float64) => field.name == "value" && !field.nullable,
-            FieldDataType::Plain(DataType::Utf8) => true,
+            SummaryFamilyType::Plain(DataType::Float64) => field.name == "value" && !field.nullable,
+            SummaryFamilyType::Plain(DataType::Utf8) => true,
             _ => false,
         })
         && !logical
@@ -134,14 +130,14 @@ pub fn source_schema(logical: &Schema) -> Result<SchemaRef, Error> {
     let states = logical
         .fields
         .iter()
-        .filter(|f| !matches!(f.dtype, FieldDataType::Plain(_)))
+        .filter(|f| !matches!(f.dtype, SummaryFamilyType::Plain(_)))
         .collect::<Vec<_>>();
     let [state] = states.as_slice() else {
         return Err(invalid(
             "stored population requires one typed summary state",
         ));
     };
-    if logical.fields.iter().enumerate().any(|(i, field)| matches!(&field.dtype, FieldDataType::Plain(dtype)
+    if logical.fields.iter().enumerate().any(|(i, field)| matches!(&field.dtype, SummaryFamilyType::Plain(dtype)
         if field.nullable || !matches!(dtype, DataType::Utf8) && !(Some(i) == logical.time_index && *dtype == DataType::Timestamp))) {
         return Err(invalid("stored population metadata cannot reconstruct extra value columns"));
     }
@@ -161,7 +157,7 @@ pub fn is_population_schema(schema: &SchemaRef) -> bool {
 /// Compile a complete selected precompute sub-DAG. Inputs are already-computed
 /// state boundaries; the deployment supplies groups, panes and states, never operations.
 pub fn compile(
-    dag: &PostAsapDAG,
+    dag: &PhysicalASAPDAG,
     frontiers: &[NodeId],
     roots: &[NodeId],
 ) -> Result<CompiledPhysicalDAG, Error> {
@@ -184,9 +180,10 @@ pub fn compile(
         (
             edge.consumer.0,
             match edge.role {
-                planner_types::post_asap::EdgeRole::Left => 0,
-                planner_types::post_asap::EdgeRole::Input => 1,
-                planner_types::post_asap::EdgeRole::Right => 2,
+                planner_types::ir::export::EdgeRole::Left => 0,
+                planner_types::ir::export::EdgeRole::Input => 1,
+                planner_types::ir::export::EdgeRole::Right => 2,
+                planner_types::ir::export::EdgeRole::ScalarRef => 3,
             },
         )
     });
@@ -261,7 +258,7 @@ pub fn compile(
     CompiledPhysicalDAG::compose(sources, fragments, roots.to_vec())
 }
 
-fn validate_value_output(node: &PostAsapDAGNode) -> Result<(), Error> {
+fn validate_value_output(node: &PhysicalASAPDAGNode) -> Result<(), Error> {
     let schema = &node.output_schema;
     // Physical population rows already carry the complete identity in `$population`.
     // Typed logical plans may expose its opaque series-identity column as metadata.
@@ -274,7 +271,7 @@ fn validate_value_output(node: &PostAsapDAGNode) -> Result<(), Error> {
     if identities.len() > 1
         || identities
             .iter()
-            .any(|field| field.nullable || field.dtype != FieldDataType::Plain(DataType::Utf8))
+            .any(|field| field.nullable || field.dtype != SummaryFamilyType::Plain(DataType::Utf8))
     {
         return Err(invalid(
             "precompute series identity requires one non-null Utf8 column",
@@ -286,12 +283,11 @@ fn validate_value_output(node: &PostAsapDAGNode) -> Result<(), Error> {
         .enumerate()
         .filter(|(i, field)| Some(*i) != schema.time_index && field.name != identity)
         .collect::<Vec<_>>();
-    if !matches!(values.as_slice(), [(_, field)] if !field.nullable && field.dtype == FieldDataType::Plain(DataType::Float64))
+    if !matches!(values.as_slice(), [(_, field)] if !field.nullable && field.dtype == SummaryFamilyType::Plain(DataType::Float64))
         || schema.time_index.is_some_and(|i| {
-            schema
-                .fields
-                .get(i)
-                .is_none_or(|f| f.nullable || f.dtype != FieldDataType::Plain(DataType::Timestamp))
+            schema.fields.get(i).is_none_or(|f| {
+                f.nullable || f.dtype != SummaryFamilyType::Plain(DataType::Timestamp)
+            })
         })
     {
         return Err(invalid(
@@ -302,9 +298,9 @@ fn validate_value_output(node: &PostAsapDAGNode) -> Result<(), Error> {
 }
 
 fn fragment(
-    node: &PostAsapDAGNode,
+    node: &PhysicalASAPDAGNode,
     schemas: &[SchemaRef],
-    parents: &[&PostAsapDAGNode],
+    parents: &[&PhysicalASAPDAGNode],
 ) -> Result<CompiledPhysicalDAG, Error> {
     let sources = schemas
         .iter()
@@ -320,7 +316,15 @@ fn fragment(
         Ok(id)
     };
     let root = match &node.payload {
-        Payload::Binary { operator } => {
+        Payload::Relational {
+            operator:
+                NonASAPOpKind::BinaryOp {
+                    operator,
+                    return_bool,
+                },
+        } => {
+            let operator =
+                crate::expressions::binary::BinaryOperator::from_logical(operator, *return_bool);
             validate_value_output(node)?;
             if node.output_schema.time_index.is_none()
                 || parents.iter().any(|p| p.output_schema.time_index.is_none())
@@ -343,30 +347,29 @@ fn fragment(
                 )?,
             )?
         }
-        Payload::Value {
-            operation: ValueOperation::FinalizeExactAccumulator,
-        } => {
+        Payload::FinalizeExactAccumulator => {
             let [input] = schemas else {
                 return Err(invalid("finalize requires one state input"));
             };
             validate_value_output(node)?;
             let statistic = match &input.fields[2].dtype {
-                FieldDataType::ExactAggregate(planner_types::post_asap::ExactKind::Sum, _) => {
+                SummaryFamilyType::ExactAggregate(planner_types::post_asap::ExactKind::Sum, _) => {
                     crate::Statistic::Sum
                 }
-                FieldDataType::ExactAggregate(planner_types::post_asap::ExactKind::Count, _) => {
-                    crate::Statistic::Count
-                }
+                SummaryFamilyType::ExactAggregate(
+                    planner_types::post_asap::ExactKind::Count,
+                    _,
+                ) => crate::Statistic::Count,
                 _ => {
                     return Err(invalid(
                         "precompute finalization requires explicit Sum or Count semantics",
                     ))
                 }
             };
-            let read = Operator::readout(
+            let read = Operator::evaluation(
                 input.clone(),
                 2,
-                ReadoutQuery::Exact(ExactReadout {
+                SummaryEvaluation::Exact(ExactEvaluation {
                     statistic,
                     lookback_ms: None,
                 }),
@@ -384,7 +387,9 @@ fn fragment(
                     ),
                 ],
             )?
-            .with_output_schema(population_schema(FieldDataType::Plain(DataType::Float64)))?;
+            .with_output_schema(population_schema(SummaryFamilyType::Plain(
+                DataType::Float64,
+            )))?;
             add(vec![read], project)?
         }
         Payload::SummaryAgg {
@@ -403,12 +408,12 @@ fn fragment(
                 return Err(invalid("summary update requires one input"));
             };
             // Item identities resolve against the complete label set of raw
-            // samples; finalized readouts carry no such identity.
+            // samples; finalized evaluations carry no such identity.
             let raw = *input == raw_sample_schema();
             // A unit-frequency summary (HLL) observes each raw sample value.
             let unit_frequency = raw
                 && crate::capability::is_unit_sample_frequency(update)
-                && matches!(family, FieldDataType::Sketch(kind, _) if !matches!(
+                && matches!(family, SummaryFamilyType::Sketch(kind, _) if !matches!(
                     kind.algorithm(),
                     planner_types::post_asap::SketchAlgorithm::Cms
                         | planner_types::post_asap::SketchAlgorithm::CountSketch
@@ -436,7 +441,7 @@ fn fragment(
                 ));
             }
             if keyed
-                && matches!(family, FieldDataType::Sketch(kind, _) if kind.algorithm() == &planner_types::post_asap::SketchAlgorithm::CmsWithHeap)
+                && matches!(family, SummaryFamilyType::Sketch(kind, _) if kind.algorithm() == &planner_types::post_asap::SketchAlgorithm::CmsWithHeap)
                 && !matches!(
                     update.weight_domain,
                     planner_types::post_asap::WeightDomain::NonNegative { .. }
@@ -461,7 +466,7 @@ fn fragment(
                                 .filter(|field| {
                                     (raw || !field.nullable)
                                         && field.name != SERIES_IDENTITY
-                                        && field.dtype == FieldDataType::Plain(DataType::Utf8)
+                                        && field.dtype == SummaryFamilyType::Plain(DataType::Utf8)
                                 })
                                 .map(|f| f.name.clone())
                                 .ok_or_else(|| {
@@ -481,7 +486,7 @@ fn fragment(
                 SummaryInputExpr::Column(ColumnRef::SampleValue) => Expression::Column(2),
                 SummaryInputExpr::Column(ColumnRef::Named(name))
                     if parents[0].output_schema.fields.iter().any(|f| {
-                        f.name == *name && f.dtype == FieldDataType::Plain(DataType::Float64)
+                        f.name == *name && f.dtype == SummaryFamilyType::Plain(DataType::Float64)
                     }) =>
                 {
                     Expression::Column(2)
@@ -497,7 +502,7 @@ fn fragment(
                 ("$window_end".into(), Expression::Column(1)),
                 ("value".into(), Expression::FiniteFloat64(Box::new(weight))),
             ];
-            let mut fields = population_schema(FieldDataType::Plain(DataType::Float64))
+            let mut fields = population_schema(SummaryFamilyType::Plain(DataType::Float64))
                 .fields
                 .clone();
             if keyed {
@@ -510,10 +515,10 @@ fn fragment(
                 for (index, (expression, dtype)) in items.into_iter().enumerate() {
                     let name = format!("$item{index}");
                     fields.push(planner_types::post_asap::Field {
-                        table: None,
                         name: name.clone(),
-                        dtype: FieldDataType::Plain(dtype),
+                        dtype: SummaryFamilyType::Plain(dtype),
                         nullable: false,
+                        table: None,
                     });
                     columns.push((name, expression));
                 }
@@ -521,9 +526,9 @@ fn fragment(
             let item_columns = (3..fields.len()).collect::<Vec<_>>();
             let project = Operator::project(input.clone(), columns)?.with_output_schema(
                 Arc::new(Schema {
-                    closed: true,
-                    unique_keys: vec![],
                     fields,
+                    unique_keys: vec![],
+                    closed: false,
                     time_index: Some(1),
                 }),
             )?;
@@ -583,7 +588,7 @@ fn raw_items(
         ColumnRef::Named(name) | ColumnRef::Qualified { name, .. }
             if !name.starts_with('$')
                 && scan.fields.iter().all(|f| {
-                    &f.name != name || f.dtype == FieldDataType::Plain(DataType::Utf8)
+                    &f.name != name || f.dtype == SummaryFamilyType::Plain(DataType::Utf8)
                 }) =>
         {
             Some(name.clone())
diff --git a/crates/asap-physical-operators/src/physical_planner/promql_fallback.rs b/crates/asap-physical-operators/src/physical_planner/promql_fallback.rs
index 237504c98..fcd1382ab 100644
--- a/crates/asap-physical-operators/src/physical_planner/promql_fallback.rs
+++ b/crates/asap-physical-operators/src/physical_planner/promql_fallback.rs
@@ -19,14 +19,14 @@ pub(super) fn raw_series_owner(slot: NodeId) -> Option<NodeId> {
 }
 
 /// A selector expression and its raw-series row schema.
-pub type Selector = (QueryExpr, SchemaRef);
+pub type Selector = (OperatorNode, SchemaRef);
 
 /// The selectors a Fallback expression reads, left to right, and the row
 /// schema of the raw series the deployment supplies for each at
 /// [`raw_series_input`]. The rows must cover the selector's window at every
 /// evaluation instant `T`, or at its `@` time: `(T - offset - range, T - offset]`;
 /// under a subquery `[R:S] offset O` that is `(T - O - R - offset - range, T - O - offset]`.
-pub fn raw_series(expression: &QueryExpr) -> Result<Vec<Selector>, Error> {
+pub fn raw_series(expression: &OperatorNode) -> Result<Vec<Selector>, Error> {
     Ok(lower(expression)?.selectors)
 }
 
@@ -43,16 +43,47 @@ pub(super) struct Lowering {
     pub steps: Vec<(Operator, Vec<Input>)>,
 }
 
-pub(super) fn lower(expression: &QueryExpr) -> Result<Lowering, Error> {
+pub(super) fn lower(expression: &OperatorNode) -> Result<Lowering, Error> {
     let mut lowering = Lowering::default();
     lowering.value(expression)?;
     Ok(lowering)
 }
 
-fn declared(expression: &QueryExpr) -> Result<SchemaRef, Error> {
-    let schema = expression
-        .output_schema()
-        .map_err(|error| invalid(error.to_string()))?;
+/// Compile a standalone scalar expression and expose its real series dependencies.
+/// Input slots use root 0; no logical wrapper node is introduced.
+pub fn compile_scalar_root(
+    expr: &ScalarExpr,
+) -> Result<(CompiledPhysicalDAG, Vec<Selector>), Error> {
+    let mut lowering = Lowering::default();
+    lowering.scalar_value(expr)?;
+    let mut inputs = BTreeMap::new();
+    for (i, (_, schema)) in lowering.selectors.iter().enumerate() {
+        inputs.insert(
+            raw_series_input(0, i),
+            InputContract::bounded(schema.clone()),
+        );
+    }
+    let last = lowering.steps.len() - 1;
+    let mut operators = BTreeMap::new();
+    for (i, (operator, dependencies)) in lowering.steps.into_iter().enumerate() {
+        let id = if i == last { 0 } else { i as u64 + 1 };
+        let dependencies = dependencies
+            .into_iter()
+            .map(|input| match input {
+                Input::Raw(i) => raw_series_input(0, i),
+                Input::Step(i) => i as u64 + 1,
+            })
+            .collect();
+        operators.insert(id, (dependencies, operator));
+    }
+    Ok((
+        CompiledPhysicalDAG::from_operators(inputs, operators, vec![0])?,
+        lowering.selectors,
+    ))
+}
+
+fn declared(expression: &OperatorNode) -> Result<SchemaRef, Error> {
+    let schema = expression.schema.clone();
     Ok(Arc::new(lift_plain(&schema)))
 }
 
@@ -69,10 +100,10 @@ fn at(shift: &planner_types::pre_asap::TimeShift) -> Result<Option<i64>, Error>
     }
 }
 
-fn range_anchor(expression: &QueryExpr) -> Option<AtModifier> {
-    match expression {
-        QueryExpr::TimeRange { child, .. } => range_anchor(child),
-        QueryExpr::TimeShift { shift, .. } => shift
+fn range_anchor(expression: &OperatorNode) -> Option<AtModifier> {
+    match expression.expect_non_asap() {
+        NonASAPOp::TimeRange { child, .. } => range_anchor(child),
+        NonASAPOp::TimeShift { shift, .. } => shift
             .at
             .filter(|at| matches!(at, AtModifier::Start | AtModifier::End)),
         _ => None,
@@ -80,32 +111,22 @@ fn range_anchor(expression: &QueryExpr) -> Option<AtModifier> {
 }
 
 /// `TimeRange { range, [TimeShift { offset, @ }], Scan }`: range, offset, `@`.
-fn selector(expression: &QueryExpr) -> Result<(i64, i64, Option<i64>), Error> {
-    let QueryExpr::TimeRange { range, child } = expression else {
+fn selector(expression: &OperatorNode) -> Result<(i64, i64, Option<i64>), Error> {
+    let NonASAPOp::TimeRange { range, child, .. } = expression.expect_non_asap() else {
         return Err(invalid("PromQL operand must be a series selector"));
     };
-    let (offset, at, scan) = match child.as_ref() {
-        QueryExpr::TimeShift { shift, child } => (shift.offset_ms, at(shift)?, child.as_ref()),
+    let (offset, at, scan) = match child.expect_non_asap() {
+        NonASAPOp::TimeShift { shift, child } => {
+            (shift.offset_ms, at(shift)?, child.expect_non_asap())
+        }
         scan => (0, None, scan),
     };
-    if !matches!(scan, QueryExpr::Scan { .. }) {
+    if !matches!(scan, NonASAPOp::Scan { .. }) {
         return Err(invalid("PromQL selector must read one scan"));
     }
     Ok((millis(range)?, offset, at))
 }
 
-/// PromQL scalar-valued expressions have no labels to match. A binary
-/// operator is scalar-valued when both operands are.
-pub(super) fn scalar(expression: &QueryExpr) -> bool {
-    match expression {
-        QueryExpr::PromqlScalarBridge(_)
-        | QueryExpr::PromqlScalarFromVector(_)
-        | QueryExpr::EvalTimestamp => true,
-        QueryExpr::BinaryOp { lhs, rhs, .. } => scalar(lhs) && scalar(rhs),
-        _ => false,
-    }
-}
-
 impl Lowering {
     fn schema(&self, input: &Input) -> SchemaRef {
         match input {
@@ -124,12 +145,12 @@ impl Lowering {
         &mut self,
         operator: Operator,
         inputs: Vec<Input>,
-        logical: &QueryExpr,
+        logical: &OperatorNode,
     ) -> Result<Input, Error> {
         Ok(self.add(operator.with_output_schema(declared(logical)?)?, inputs))
     }
 
-    fn read(&mut self, selector: &QueryExpr) -> Result<Input, Error> {
+    fn read(&mut self, selector: &OperatorNode) -> Result<Input, Error> {
         let schema = declared(selector)?;
         if !schema
             .fields
@@ -145,12 +166,12 @@ impl Lowering {
     }
 
     /// An instant vector, or a scalar for scalar-valued expressions.
-    fn value(&mut self, expression: &QueryExpr) -> Result<Input, Error> {
-        match expression {
-            QueryExpr::Concat { children, .. } => {
-                if !children.iter().all(|branch| matches!(branch,
-                    QueryExpr::PromqlRelabel { child, .. } if matches!(child.as_ref(),
-                        QueryExpr::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::HistogramQuantile { .. }])))) {
+    fn value(&mut self, expression: &OperatorNode) -> Result<Input, Error> {
+        match expression.expect_non_asap() {
+            NonASAPOp::Concat { children, .. } => {
+                if !children.iter().all(|branch| matches!(branch.expect_non_asap(),
+                    NonASAPOp::PromqlRelabel { child, .. } if matches!(child.expect_non_asap(),
+                        NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::HistogramQuantile { .. }])))) {
                     return Err(invalid("PromQL concatenation requires classic histogram quantile branches"));
                 }
                 let inputs = children
@@ -171,15 +192,17 @@ impl Lowering {
                     expression,
                 )
             }
-            QueryExpr::PromqlRelabel { dst, value, child } => {
+            NonASAPOp::PromqlRelabel { dst, value, child } => {
                 let step = self.value(child)?;
                 let input = self.schema(&step);
-                let (replacement, source_regex) = match value.as_ref() {
-                    QueryExpr::Literal(planner_types::pre_asap::ScalarValue::Utf8(value)) => {
+                let (replacement, source_regex) = match value {
+                    ScalarExpr::Literal(planner_types::pre_asap::ScalarValue::Utf8(value)) => {
                         (value.clone(), None)
                     }
-                    QueryExpr::FunctionCall { name, args } if name == "label_replace" => {
-                        let [QueryExpr::Column(source), QueryExpr::Literal(planner_types::pre_asap::ScalarValue::Utf8(pattern)), QueryExpr::Literal(planner_types::pre_asap::ScalarValue::Utf8(
+                    ScalarExpr::FunctionCall { name, args } if name == "label_replace" => {
+                        let [ScalarExpr::Column(source), ScalarExpr::Literal(planner_types::pre_asap::ScalarValue::Utf8(
+                            pattern,
+                        )), ScalarExpr::Literal(planner_types::pre_asap::ScalarValue::Utf8(
                             replacement,
                         ))] = args.as_slice()
                         else {
@@ -204,7 +227,7 @@ impl Lowering {
                 )?;
                 self.push(operator, vec![step], expression)
             }
-            QueryExpr::TimeRange { .. } => {
+            NonASAPOp::TimeRange { .. } => {
                 let (range, offset, at) = selector(expression)?;
                 let input = self.read(expression)?;
                 let schema = self.schema(&input);
@@ -215,7 +238,7 @@ impl Lowering {
                     expression,
                 )
             }
-            QueryExpr::Aggregate {
+            NonASAPOp::Aggregate {
                 reduction: planner_types::pre_asap::Reduction::PerEntity,
                 measures,
                 having: None,
@@ -234,7 +257,7 @@ impl Lowering {
                 let input = self.schema(&step);
                 Ok(self.add(Operator::series_without_name(input)?, vec![step]))
             }
-            QueryExpr::Aggregate {
+            NonASAPOp::Aggregate {
                 reduction: planner_types::pre_asap::Reduction::Reduce(keys),
                 measures,
                 having: None,
@@ -248,7 +271,74 @@ impl Lowering {
                 let input = self.value(child)?;
                 self.aggregate(input, measure, keys, expression)
             }
-            QueryExpr::Sort {
+            NonASAPOp::Project {
+                cols,
+                child,
+                qualifier,
+            } => {
+                let value = planner_types::pre_asap::column_resolution::resolve_column_ref(
+                    &ColumnRef::SampleValue,
+                    &child.schema,
+                )
+                .map_err(|e| invalid(e.to_string()))?;
+                let sample = cols
+                    .iter()
+                    .find(|col| {
+                        col.alias.as_deref() == Some(child.schema.fields[value].name.as_str())
+                    })
+                    .ok_or_else(|| invalid("missing sample projection"))?;
+                let keep_name = matches!(sample.expr, ScalarExpr::Negative { .. });
+                let fields: Vec<_> = child
+                    .schema
+                    .fields
+                    .iter()
+                    .enumerate()
+                    .filter(|(_, field)| keep_name || field.name != "__name__")
+                    .collect();
+                if qualifier.is_some() || cols.len() != fields.len() {
+                    return Err(invalid("unsupported temporal projection shape"));
+                }
+                let mut computed = None;
+                for (col, (index, field)) in cols.iter().zip(fields) {
+                    if col.alias.as_deref() != Some(field.name.as_str()) {
+                        return Err(invalid("unsupported temporal projection alias"));
+                    }
+                    if index == value {
+                        computed = Some(col);
+                    } else {
+                        let expected = if !keep_name
+                            && field.name == planner_types::pre_asap::schema::PROMQL_SERIES_IDENTITY
+                        {
+                            ScalarExpr::FunctionCall {
+                                name: "promql_drop_metric_name".into(),
+                                args: vec![ScalarExpr::Column(index)],
+                            }
+                        } else {
+                            ScalarExpr::Column(index)
+                        };
+                        if col.expr != expected {
+                            return Err(invalid("unsupported temporal projection expression"));
+                        }
+                    }
+                }
+                let computed = computed.ok_or_else(|| invalid("no computed sample"))?;
+                if matches!(
+                    computed.expr,
+                    ScalarExpr::Negative { .. } | ScalarExpr::FunctionCall { .. }
+                ) {
+                    return self.pointwise_projection(cols, child, value, expression, keep_name);
+                }
+                self.sample_scalar_operation(&computed.expr, child, value, expression)
+            }
+            NonASAPOp::Filter { pred, child } => {
+                let value = planner_types::pre_asap::column_resolution::resolve_column_ref(
+                    &ColumnRef::SampleValue,
+                    &child.schema,
+                )
+                .map_err(|e| invalid(e.to_string()))?;
+                self.sample_scalar_operation(&pred.0, child, value, expression)
+            }
+            NonASAPOp::Sort {
                 keys,
                 partition_by,
                 child,
@@ -258,7 +348,7 @@ impl Lowering {
                 let keys = keys
                     .iter()
                     .map(|key| match key.expr {
-                        QueryExpr::Column(column) => Ok(SortKey {
+                        ScalarExpr::Column(column) => Ok(SortKey {
                             column,
                             descending: !key.ascending,
                             nulls_first: key.nulls_first,
@@ -269,70 +359,223 @@ impl Lowering {
                 let groups = groups(&input, partition_by)?;
                 self.push(Operator::sort(input, keys, groups)?, vec![step], expression)
             }
-            QueryExpr::Limit { n, offset, child } => {
+            NonASAPOp::Limit {
+                n, offset, child, ..
+            } => {
                 let step = self.value(child)?;
                 let input = self.schema(&step);
                 // `topk by (...)` partitions through the Sort it limits.
-                let groups = match child.as_ref() {
-                    QueryExpr::Sort { partition_by, .. } => groups(&input, partition_by)?,
+                let groups = match child.expect_non_asap() {
+                    NonASAPOp::Sort { partition_by, .. } => groups(&input, partition_by)?,
                     _ => vec![],
                 };
                 self.push(
-                    Operator::limit(input, *n as u64, *offset as u64, groups)?,
+                    Operator::limit(
+                        input,
+                        n.unwrap_or(usize::MAX) as u64,
+                        *offset as u64,
+                        groups,
+                    )?,
                     vec![step],
                     expression,
                 )
             }
-            QueryExpr::BinaryOp {
-                op,
+            NonASAPOp::BinaryOp {
+                operator,
                 lhs,
                 rhs,
-                vector_match,
+                return_bool,
             } => {
                 let sides = vec![self.value(lhs)?, self.value(rhs)?];
-                let operator = planner_types::post_asap::BinaryOperator {
-                    kind: op.clone(),
-                    vector_match: vector_match.clone(),
-                    checked_relative_division: false,
-                    checked_finite_division: false,
-                };
+                let operator = crate::expressions::binary::BinaryOperator::from_logical(
+                    operator,
+                    *return_bool,
+                );
                 let binary = Operator::series_binary(
                     self.schema(&sides[0]),
                     self.schema(&sides[1]),
                     operator,
-                    [scalar(lhs), scalar(rhs)],
+                    [false, false],
                 )?;
                 self.push(binary, sides, expression)
             }
-            QueryExpr::PromqlScalarFromVector(child) => {
-                let step = self.value(child)?;
-                let input = self.schema(&step);
-                let value = named_column(&input, &ColumnRef::SampleValue)?;
-                self.push(
-                    Operator::vector_to_scalar(input, value)?,
-                    vec![step],
-                    expression,
-                )
-            }
-            QueryExpr::PromqlVectorFromScalar(child) => {
-                let step = self.value(child)?;
+            NonASAPOp::PromqlVectorFromScalar(expr) => {
+                let step = self.scalar_value(expr)?;
                 let input = self.schema(&step);
                 Ok(self.add(
                     Operator::scope_timestamp(input, declared(expression)?)?,
                     vec![step],
                 ))
             }
-            QueryExpr::EvalTimestamp => self.push(Operator::evaluation_time(), vec![], expression),
-            QueryExpr::PromqlScalarBridge(_) => {
-                let value = row_values::scalar_literal(expression)
-                    .ok_or_else(|| invalid("PromQL scalar must be a literal"))?;
-                self.push(
-                    Operator::scalar(crate::values::Value::Float64(value), DataType::Float64)?,
+            _ => Err(invalid("PromQL expression has no native fallback lowering")),
+        }
+    }
+
+    fn pointwise_projection(
+        &mut self,
+        cols: &[planner_types::ir::ProjectItem],
+        child: &OperatorNode,
+        value: usize,
+        output: &OperatorNode,
+        keep_name: bool,
+    ) -> Result<Input, Error> {
+        let mut input = self.value(child)?;
+        let mut projected = cols.to_vec();
+        for col in &mut projected {
+            if col.alias.as_deref() != Some(child.schema.fields[value].name.as_str()) {
+                continue;
+            }
+            if let ScalarExpr::FunctionCall { name, args } = &mut col.expr {
+                if planner_types::pre_asap::scalar_type_rules::promql_function_arity(name).is_none()
+                    || args.first() != Some(&ScalarExpr::Column(value))
+                {
+                    return Err(invalid("unsupported pointwise function"));
+                }
+                for arg in args.iter_mut().skip(1) {
+                    let scalar = self.scalar_value(arg)?;
+                    let left = self.schema(&input);
+                    let right = self.schema(&scalar);
+                    let index = left.fields.len();
+                    let mut schema = (*left).clone();
+                    schema.fields.extend(right.fields.clone());
+                    let join = Operator::relational_join(
+                        left,
+                        right,
+                        planner_types::pre_asap::JoinKind::Inner,
+                        &planner_types::ir::Predicate(ScalarExpr::Literal(
+                            planner_types::pre_asap::ScalarValue::Boolean(true),
+                        )),
+                        Arc::new(schema),
+                    )?;
+                    input = self.add(join, vec![input, scalar]);
+                    *arg = ScalarExpr::Column(index);
+                }
+                if name == "promql_clamp" {
+                    let predicate = ScalarExpr::Not(Box::new(ScalarExpr::Compare {
+                        left: Box::new(args[1].clone()),
+                        right: Box::new(args[2].clone()),
+                        op: planner_types::pre_asap::CompareOpKind::Gt,
+                        semantics: planner_types::ir::ExprSemantics::Promql,
+                    }));
+                    let schema = self.schema(&input);
+                    let predicate =
+                        crate::expressions::CompiledExpression::compile(&predicate, &schema)?;
+                    input = self.add(
+                        Operator::filter(
+                            schema,
+                            crate::expressions::Expression::planner(predicate),
+                        )?,
+                        vec![input],
+                    );
+                }
+            }
+        }
+        let schema = self.schema(&input);
+        let columns = projected
+            .iter()
+            .map(|col| {
+                Ok((
+                    col.alias.clone().unwrap(),
+                    crate::expressions::Expression::planner(
+                        crate::expressions::CompiledExpression::compile(&col.expr, &schema)?,
+                    ),
+                ))
+            })
+            .collect::<Result<Vec<_>, Error>>()?;
+        let project = Operator::project(schema, columns)?;
+        let result = self.push(project, vec![input], output)?;
+        if keep_name {
+            Ok(result)
+        } else {
+            self.push(
+                Operator::series_without_name(self.schema(&result))?,
+                vec![result],
+                output,
+            )
+        }
+    }
+
+    fn sample_scalar_operation(
+        &mut self,
+        expr: &ScalarExpr,
+        child: &OperatorNode,
+        value: usize,
+        output: &OperatorNode,
+    ) -> Result<Input, Error> {
+        let (left, right, kind) = scalar_binary(expr)?;
+        let (scalar, scalar_left) = match (left, right) {
+            (ScalarExpr::Column(i), scalar) if *i == value => (scalar, false),
+            (scalar, ScalarExpr::Column(i)) if *i == value => (scalar, true),
+            _ => {
+                return Err(invalid(
+                    "sample projection requires one vector sample and one scalar",
+                ))
+            }
+        };
+        let vector = self.value(child)?;
+        let scalar = self.scalar_value(scalar)?;
+        let sides = if scalar_left {
+            vec![scalar, vector]
+        } else {
+            vec![vector, scalar]
+        };
+        let operator = Operator::series_binary(
+            self.schema(&sides[0]),
+            self.schema(&sides[1]),
+            kernel(kind),
+            [scalar_left, !scalar_left],
+        )?;
+        self.push(operator, sides, output)
+    }
+
+    fn scalar_value(&mut self, expr: &ScalarExpr) -> Result<Input, Error> {
+        match expr {
+            ScalarExpr::Literal(planner_types::pre_asap::ScalarValue::Float64(value)) => Ok(self
+                .add(
+                    Operator::scalar(crate::values::Value::Float64(*value), DataType::Float64)?,
                     vec![],
-                    expression,
-                )
+                )),
+            ScalarExpr::EvalTimestamp => Ok(self.add(Operator::evaluation_time(), vec![])),
+            ScalarExpr::PromqlScalarFromVector(child) => {
+                let step = self.value(child)?;
+                let input = self.schema(&step);
+                let values: Vec<_> = input
+                    .fields
+                    .iter()
+                    .enumerate()
+                    .filter(|(_, f)| f.dtype == FieldDataType::Plain(DataType::Float64))
+                    .map(|(i, _)| i)
+                    .collect();
+                let [value] = values.as_slice() else {
+                    return Err(invalid("scalar() requires one float sample column"));
+                };
+                let value = *value;
+                Ok(self.add(Operator::vector_to_scalar(input, value)?, vec![step]))
+            }
+            ScalarExpr::Negative { expr, .. } => {
+                let value = self.scalar_value(expr)?;
+                let minus = self.scalar_value(&ScalarExpr::literal_f64(-1.0))?;
+                let op = Operator::series_binary(
+                    self.schema(&value),
+                    self.schema(&minus),
+                    kernel(crate::expressions::binary::BinaryOpKind::Arithmetic(
+                        planner_types::pre_asap::ArithmeticOpKind::Mul,
+                    )),
+                    [true, true],
+                )?;
+                Ok(self.add(op, vec![value, minus]))
+            }
+            _ => {
+                let (left, right, kind) = scalar_binary(expr)?;
+                let sides = vec![self.scalar_value(left)?, self.scalar_value(right)?];
+                let op = Operator::series_binary(
+                    self.schema(&sides[0]),
+                    self.schema(&sides[1]),
+                    kernel(kind),
+                    [true, true],
+                )?;
+                Ok(self.add(op, sides))
             }
-            _ => Err(invalid("PromQL expression has no native fallback lowering")),
         }
     }
 
@@ -340,19 +583,19 @@ impl Lowering {
     fn range_function(
         &mut self,
         function: &AggIntent,
-        matrix: &QueryExpr,
-        logical: &QueryExpr,
+        matrix: &OperatorNode,
+        logical: &OperatorNode,
     ) -> Result<Input, Error> {
         let function = unbound(function)?;
-        let (subquery, offset, at_ms) = match matrix {
-            QueryExpr::TimeShift { shift, child } => (child.as_ref(), shift.offset_ms, at(shift)?),
-            other => (other, 0, None),
+        let (subquery, offset, at_ms) = match matrix.expect_non_asap() {
+            NonASAPOp::TimeShift { shift, child } => (child.as_ref(), shift.offset_ms, at(shift)?),
+            _ => (matrix, 0, None),
         };
-        let QueryExpr::PromqlSubquery {
+        let NonASAPOp::PromqlSubquery {
             range: outer,
             resolution,
             child,
-        } = subquery
+        } = subquery.expect_non_asap()
         else {
             let (range, offset, at) = selector(matrix)?;
             let input = self.read(matrix)?;
@@ -374,8 +617,8 @@ impl Lowering {
             at_ms,
         };
         // Each step evaluates a per-series selection or range function.
-        let (inner, selected) = match child.as_ref() {
-            QueryExpr::Aggregate {
+        let (inner, selected) = match child.expect_non_asap() {
+            NonASAPOp::Aggregate {
                 reduction: planner_types::pre_asap::Reduction::PerEntity,
                 measures,
                 having: None,
@@ -385,7 +628,7 @@ impl Lowering {
                 [inner] => (Some(unbound(inner)?), selected.as_ref()),
                 _ => return Err(invalid("range function requires one measure")),
             },
-            selected => (None, selected),
+            _ => (None, child.as_ref()),
         };
         let (range, inner_offset, inner_at) = selector(selected)?;
         let raw = self.read(selected)?;
@@ -425,7 +668,7 @@ impl Lowering {
         mut step: Input,
         measure: &AggIntent,
         keys: &GroupKeys,
-        logical: &QueryExpr,
+        logical: &OperatorNode,
     ) -> Result<Input, Error> {
         let mut input = self.schema(&step);
         if let AggIntent::HistogramQuantile { q, le } = measure {
@@ -447,10 +690,10 @@ impl Lowering {
         };
         let value = *value;
         let reduction = match measure {
-            AggIntent::Sum { col: None } => Reduction::Sum(value),
-            AggIntent::Avg { col: None } => Reduction::Avg(value),
-            AggIntent::Min { col: None } => Reduction::Min(value),
-            AggIntent::Max { col: None } => Reduction::Max(value),
+            AggIntent::Sum { .. } => Reduction::Sum(value),
+            AggIntent::Avg { .. } => Reduction::Avg(value),
+            AggIntent::Min { .. } => Reduction::Min(value),
+            AggIntent::Max { .. } => Reduction::Max(value),
             AggIntent::Count { .. } => Reduction::Count,
             _ => return Err(invalid("vector aggregate has no native lowering")),
         };
@@ -527,10 +770,10 @@ fn unbound(intent: &AggIntent) -> Result<AggIntent<ColumnRef>, Error> {
         AggIntent::Count { accuracy } => AggIntent::Count {
             accuracy: accuracy.clone(),
         },
-        AggIntent::Sum { col: None } => AggIntent::Sum { col: None },
-        AggIntent::Avg { col: None } => AggIntent::Avg { col: None },
-        AggIntent::Min { col: None } => AggIntent::Min { col: None },
-        AggIntent::Max { col: None } => AggIntent::Max { col: None },
+        AggIntent::Sum { .. } => AggIntent::Sum { col: None },
+        AggIntent::Avg { .. } => AggIntent::Avg { col: None },
+        AggIntent::Min { .. } => AggIntent::Min { col: None },
+        AggIntent::Max { .. } => AggIntent::Max { col: None },
         AggIntent::IRate => AggIntent::IRate,
         AggIntent::IDelta => AggIntent::IDelta,
         AggIntent::Changes => AggIntent::Changes,
@@ -548,3 +791,65 @@ fn unbound(intent: &AggIntent) -> Result<AggIntent<ColumnRef>, Error> {
         _ => return Err(invalid("unsupported PromQL range function")),
     })
 }
+
+fn kernel(
+    kind: crate::expressions::binary::BinaryOpKind,
+) -> crate::expressions::binary::BinaryOperator {
+    crate::expressions::binary::BinaryOperator {
+        kind,
+        vector_match: None,
+        checked_relative_division: false,
+        checked_finite_division: false,
+    }
+}
+
+fn scalar_binary(
+    expr: &ScalarExpr,
+) -> Result<
+    (
+        &ScalarExpr,
+        &ScalarExpr,
+        crate::expressions::binary::BinaryOpKind,
+    ),
+    Error,
+> {
+    use crate::expressions::binary::BinaryOpKind as K;
+    match expr {
+        ScalarExpr::Arithmetic {
+            left,
+            right,
+            op,
+            semantics: planner_types::ir::ExprSemantics::Promql,
+        } => Ok((left, right, K::Arithmetic(op.clone()))),
+        ScalarExpr::Compare {
+            left,
+            right,
+            op,
+            semantics: planner_types::ir::ExprSemantics::Promql,
+        } => Ok((left, right, K::Compare(op.clone()))),
+        ScalarExpr::Case {
+            operand: None,
+            branches,
+            else_expr,
+        } if matches!(else_expr.as_deref(), Some(ScalarExpr::Literal(planner_types::pre_asap::ScalarValue::Float64(v))) if *v == 0.0) =>
+        {
+            let [(
+                ScalarExpr::Compare {
+                    left,
+                    right,
+                    op,
+                    semantics: planner_types::ir::ExprSemantics::Promql,
+                },
+                ScalarExpr::Literal(planner_types::pre_asap::ScalarValue::Float64(v)),
+            )] = branches.as_slice()
+            else {
+                return Err(invalid("unsupported scalar case"));
+            };
+            if *v != 1.0 {
+                return Err(invalid("unsupported scalar case result"));
+            }
+            Ok((left, right, K::CompareBool(op.clone())))
+        }
+        _ => Err(invalid("scalar expression has no native temporal lowering")),
+    }
+}
diff --git a/crates/asap-physical-operators/src/physical_planner/promql_rows.rs b/crates/asap-physical-operators/src/physical_planner/promql_rows.rs
index f3082927b..20992dfe7 100644
--- a/crates/asap-physical-operators/src/physical_planner/promql_rows.rs
+++ b/crates/asap-physical-operators/src/physical_planner/promql_rows.rs
@@ -1,6 +1,10 @@
 //! A bounded PromQL source row carries the entire label set, not just labels
 //! mentioned by the query. The source adapter owns this lossless encoding.
 use super::*;
+use planner_types::ir::export::{
+    compile_physical_asap_dag, compile_physical_asap_dag_with_node_ids,
+};
+use planner_types::post_asap::FieldDataType as SummaryFamilyType;
 use planner_types::pre_asap::DataType;
 use std::rc::Rc;
 
@@ -23,9 +27,9 @@ pub fn decode_series_identity(encoded: &str) -> Result<BTreeMap<String, String>,
 }
 
 /// Resolve the row representation before candidate search; see
-/// [`planner_types::pre_asap::schema::with_promql_series_identity`].
-pub fn with_series_identity(root: &QueryExpr) -> Result<QueryExpr, Error> {
-    planner_types::pre_asap::schema::with_promql_series_identity(root).map_err(invalid)
+/// [`planner_types::ir::schema_support::with_promql_series_identity`].
+pub fn with_series_identity(root: &Rc<OperatorNode>) -> Result<Rc<OperatorNode>, Error> {
+    planner_types::ir::schema_support::with_promql_series_identity(root).map_err(invalid)
 }
 
 /// Construct source rows only from full identities. The named label columns
@@ -45,7 +49,10 @@ pub fn series_row(
         .enumerate()
         .map(|(index, field)| {
             if field.name == SERIES_IDENTITY_COLUMN {
-                if field.dtype != FieldDataType::Plain(DataType::Utf8) || field.nullable || found {
+                if field.dtype != SummaryFamilyType::Plain(DataType::Utf8)
+                    || field.nullable
+                    || found
+                {
                     return Err(invalid("invalid series identity column"));
                 }
                 found = true;
@@ -53,10 +60,10 @@ pub fn series_row(
             } else if Some(index) == schema.time_index {
                 Ok(Value::Timestamp(timestamp))
             } else if field.name == "value"
-                && field.dtype == FieldDataType::Plain(DataType::Float64)
+                && field.dtype == SummaryFamilyType::Plain(DataType::Float64)
             {
                 Ok(Value::Float64(value))
-            } else if field.dtype == FieldDataType::Plain(DataType::Utf8) {
+            } else if field.dtype == SummaryFamilyType::Plain(DataType::Utf8) {
                 Ok(labels.get(&field.name).map_or_else(
                     || Value::Utf8("".into()),
                     |value| Value::Utf8(value.clone().into()),
@@ -75,17 +82,24 @@ pub fn series_row(
 /// Compile the selected TopK computation above an existing maintained-population
 /// source. The boundary supplies the complete eligible vector, not a truncated
 /// TopK result; ranking remains a native physical operator.
-pub fn compile_current_series_readout(
-    selected: &Rc<planner_types::post_asap::SummaryNode>,
+pub fn compile_current_series_evaluation(
+    selected: &Rc<OperatorNode>,
 ) -> Result<CompiledPhysicalDAG, Error> {
     use planner_types::post_asap::{
-        compile_post_asap_dag, maintained_population::PopulationStatistic, Field,
+        maintained_population::PopulationStatistic, Field as SummaryField,
     };
-    let mut dag = compile_post_asap_dag(selected).map_err(|error| invalid(error.to_string()))?;
+    let selected = planner_types::ir::apply_lifecycle_timings(
+        selected,
+        &planner_types::ir::LifecycleAssignment::default_maintained(),
+        &mut planner_types::ir::TimingMemo::new(),
+    )
+    .map_err(|e| invalid(e.to_string()))?;
+    let mut dag =
+        compile_physical_asap_dag(&selected).map_err(|error| invalid(error.to_string()))?;
     // Typed snapshot candidates already carry full identity throughout the DAG.
-    // Cut at the population output, preserving all selected heap/readout nodes.
+    // Cut at the population output, preserving all selected heap/evaluation nodes.
     let populations = dag.nodes.iter().filter(|node| matches!(&node.payload,
-        Payload::Value { operation: ValueOperation::MaintainPopulation { population } }
+        Payload::MaintainPopulation { population }
             if matches!(population.input, planner_types::post_asap::maintained_population::PopulationInput::CurrentSeries(_))
     )).collect::<Vec<_>>();
     if let [population] = populations.as_slice() {
@@ -101,45 +115,30 @@ pub fn compile_current_series_readout(
                     u64::from(population.id.0),
                     InputContract::bounded(Arc::new(population.output_schema.clone())),
                 )]),
-                &[u64::from(dag.root.0)],
+                &dag.roots.iter().map(|r| u64::from(r.0)).collect::<Vec<_>>(),
             );
         }
     }
-    if dag.nodes.len() != 3
-        || !dag.nodes.iter().any(|node| {
-            node.id == dag.root
-                && matches!(
-                    node.payload,
-                    Payload::Value {
-                        operation: ValueOperation::ReadPopulation {
-                            readout: PopulationStatistic::TopK { .. }
-                        }
-                    }
-                )
-        })
-    {
-        return Err(invalid(
-            "expected one selected current-series TopK computation",
-        ));
-    }
     let mut frontier = None;
     for node in &mut dag.nodes {
         match &mut node.payload {
-            Payload::Fallback { expression } => {
-                *expression = with_series_identity(expression)?;
+            Payload::Relational { operator } => {
+                if let NonASAPOpKind::Scan { schema, .. } = operator {
+                    schema.fields.push(SummaryField::new(
+                        SERIES_IDENTITY_COLUMN,
+                        SummaryFamilyType::Plain(DataType::Utf8),
+                        false,
+                    ));
+                    schema.closed = true;
+                }
             }
-            Payload::Value {
-                operation: ValueOperation::MaintainPopulation { .. },
-            } => {
+            Payload::MaintainPopulation { .. } => {
                 frontier = Some(u64::from(node.id.0));
             }
-            Payload::Value {
-                operation:
-                    ValueOperation::ReadPopulation {
-                        readout: PopulationStatistic::TopK { .. },
-                    },
+            Payload::EvaluatePopulation {
+                evaluation: PopulationStatistic::TopK { .. },
             } => {}
-            _ => return Err(invalid("unsupported current-series readout dependency")),
+            _ => return Err(invalid("unsupported current-series evaluation dependency")),
         }
         if node
             .output_schema
@@ -151,11 +150,11 @@ pub fn compile_current_series_readout(
                 "current-series input already has a physical identity column",
             ));
         }
-        node.output_schema.fields.push(Field {
-            table: None,
+        node.output_schema.fields.push(SummaryField {
             name: SERIES_IDENTITY_COLUMN.into(),
-            dtype: FieldDataType::Plain(DataType::Utf8),
+            dtype: SummaryFamilyType::Plain(DataType::Utf8),
             nullable: false,
+            table: None,
         });
     }
     for edge in &mut dag.edges {
@@ -179,48 +178,36 @@ pub fn compile_current_series_readout(
     compile(
         &dag,
         BTreeMap::from([(frontier, InputContract::bounded(schema))]),
-        &[u64::from(dag.root.0)],
+        &dag.roots.iter().map(|r| u64::from(r.0)).collect::<Vec<_>>(),
     )
 }
 
 /// Compile selected ranking or aggregation above an exact per-series Rate
-/// readout. Deployments bind complete window readouts at this boundary;
+/// evaluation. Deployments bind complete window evaluations at this boundary;
 /// the heap is rebuilt independently for each evaluation. This does not move
 /// that frontier to ingestion time or authorize combining finalized rates.
 pub fn compile_rate_ranking(
-    selected: &Rc<planner_types::post_asap::SummaryNode>,
-) -> Result<
-    (
-        Rc<planner_types::post_asap::SummaryNode>,
-        CompiledPhysicalDAG,
-    ),
-    Error,
-> {
-    use planner_types::post_asap::{
-        compile_post_asap_dag_with_node_ids, ExactKind, SummaryExpr, SummaryNode,
-    };
-    fn frontier(node: &Rc<SummaryNode>) -> Option<Rc<SummaryNode>> {
-        match &node.expr {
-            SummaryExpr::ValueOperation {
-                child,
-                operation: ValueOperation::FinalizeExactAccumulator,
-                timing: planner_types::post_asap::ExecutionTiming::QueryTime,
-            } if matches!(&child.expr, SummaryExpr::SummaryAgg {
-                    family: FieldDataType::ExactAggregate(ExactKind::Rate, _),
-                    reduction: planner_types::pre_asap::Reduction::PerEntity,
-                    child: raw, ..
-                } if matches!(&raw.expr, SummaryExpr::KeepPreAsap(expr) if matches!(expr.as_ref(), QueryExpr::TimeRange { .. }))) =>
-            {
-                Some(Rc::clone(node))
-            }
-            SummaryExpr::ValueOperation { child, .. } | SummaryExpr::SummaryAgg { child, .. } => {
-                frontier(child)
-            }
-            SummaryExpr::SummaryEstimate { summary_input, .. } => frontier(summary_input),
-            _ => None,
+    selected: &Rc<OperatorNode>,
+) -> Result<(Rc<OperatorNode>, CompiledPhysicalDAG), Error> {
+    use planner_types::post_asap::ExactKind;
+    fn frontier(node: &Rc<OperatorNode>) -> Option<Rc<OperatorNode>> {
+        if matches!(&node.operator, LogicalOperator::ASAP(ASAPOp::FinalizeExactAccumulator { child })
+            if matches!(&child.operator, LogicalOperator::ASAP(ASAPOp::SummaryAgg {
+                family: FieldDataType::ExactAggregate(ExactKind::Rate, _),
+                reduction: planner_types::pre_asap::Reduction::PerEntity, child: raw, ..
+            }) if matches!(raw.non_asap(), Some(NonASAPOp::TimeRange { .. }))))
+        {
+            return Some(Rc::clone(node));
         }
+        node.children().into_iter().find_map(frontier)
     }
-    let source = frontier(selected)
+    let selected = planner_types::ir::apply_lifecycle_timings(
+        selected,
+        &planner_types::ir::LifecycleAssignment::default_maintained(),
+        &mut planner_types::ir::TimingMemo::new(),
+    )
+    .map_err(|e| invalid(e.to_string()))?;
+    let source = frontier(&selected)
         .ok_or_else(|| invalid("ranking requires one exact per-series Rate frontier"))?;
     if !source
         .schema
@@ -230,7 +217,7 @@ pub fn compile_rate_ranking(
     {
         return Err(invalid("Rate ranking requires complete series identity"));
     }
-    let compiled = compile_post_asap_dag_with_node_ids(selected)
+    let compiled = compile_physical_asap_dag_with_node_ids(&selected)
         .map_err(|error| invalid(error.to_string()))?;
     let id = u64::from(
         compiled
@@ -242,17 +229,22 @@ pub fn compile_rate_ranking(
     let program = compile(
         &compiled.dag,
         BTreeMap::from([(id, InputContract::bounded(Arc::new(source.schema.clone())))]),
-        &[u64::from(compiled.dag.root.0)],
+        &compiled
+            .dag
+            .roots
+            .iter()
+            .map(|r| u64::from(r.0))
+            .collect::<Vec<_>>(),
     )?;
     Ok((source, program))
 }
 
 /// Compile a lifecycle-timed DAG whose heap or grouped Sum over per-series
-/// Rate readouts runs at ingestion time: fresh aggregate state per closed
+/// Rate evaluations runs at ingestion time: fresh aggregate state per closed
 /// window. The input is the complete collection of per-series counter states.
 pub fn compile_fixed_window_rate_aggregation(
-    dag: &planner_types::post_asap::PostAsapDAG,
-) -> Result<PhysicalASAPDAG, Error> {
+    dag: &planner_types::ir::export::PhysicalASAPDAG,
+) -> Result<CompiledPhysicalPlan, Error> {
     use planner_types::post_asap::{ExactKind, ExecutionTiming, SketchAlgorithm};
     let sources = dag
         .nodes
@@ -261,7 +253,7 @@ pub fn compile_fixed_window_rate_aggregation(
             matches!(
                 &n.payload,
                 Payload::SummaryAgg {
-                    family: FieldDataType::ExactAggregate(ExactKind::Rate, _),
+                    family: SummaryFamilyType::ExactAggregate(ExactKind::Rate, _),
                     reduction: planner_types::pre_asap::Reduction::PerEntity,
                     ..
                 }
@@ -275,14 +267,14 @@ pub fn compile_fixed_window_rate_aggregation(
             n.output_state.timing == ExecutionTiming::IngestionTime
                 && match &n.payload {
                     Payload::SummaryAgg {
-                        family: FieldDataType::Sketch(kind, _),
+                        family: SummaryFamilyType::Sketch(kind, _),
                         ..
                     } => matches!(
                         kind.algorithm(),
                         SketchAlgorithm::CmsWithHeap | SketchAlgorithm::CountSketchWithHeap
                     ),
                     Payload::SummaryAgg {
-                        family: FieldDataType::ExactAggregate(ExactKind::Sum, _),
+                        family: SummaryFamilyType::ExactAggregate(ExactKind::Sum, _),
                         ..
                     } => true,
                     _ => false,
@@ -310,7 +302,7 @@ pub fn compile_fixed_window_rate_aggregation(
             u64::from(source.id.0),
             InputContract::bounded(Arc::new(source.output_schema.clone())),
         )]),
-        &[u64::from(dag.root.0)],
+        &dag.roots.iter().map(|r| u64::from(r.0)).collect::<Vec<_>>(),
         &[u64::from(heap.id.0)],
     )
 }
diff --git a/crates/asap-physical-operators/src/physical_planner/promql_values.rs b/crates/asap-physical-operators/src/physical_planner/promql_values.rs
index 880916ed2..a8a091249 100644
--- a/crates/asap-physical-operators/src/physical_planner/promql_values.rs
+++ b/crates/asap-physical-operators/src/physical_planner/promql_values.rs
@@ -1,5 +1,6 @@
 //! Physical scalar/vector contracts preserve complete label sets across native computation.
 use super::*;
+use planner_types::post_asap::FieldDataType as SummaryFamilyType;
 
 pub fn scalar_schema() -> SchemaRef {
     crate::operators::vector_binary::value_schema(true)
@@ -63,7 +64,7 @@ pub fn compile_histogram_quantile() -> Result<CompiledPhysicalDAG, Error> {
 
 /// Compile before deployment chooses readers. Input slots 0 and 1 retain operand order.
 pub fn compile_binary(
-    operator: &planner_types::post_asap::BinaryOperator,
+    operator: &crate::expressions::binary::BinaryOperator,
     return_bool: bool,
     left_scalar: bool,
     right_scalar: bool,
@@ -209,8 +210,8 @@ pub fn compile_vector_to_scalar() -> Result<CompiledPhysicalDAG, Error> {
 
 /// A stored exact-state input retains the complete population identity. The
 /// deployment supplies eligible panes; merging and finalization are computation.
-pub fn exact_state_schema(family: FieldDataType) -> Result<SchemaRef, Error> {
-    if !matches!(family, FieldDataType::ExactAggregate(..)) {
+pub fn exact_state_schema(family: SummaryFamilyType) -> Result<SchemaRef, Error> {
+    if !matches!(family, SummaryFamilyType::ExactAggregate(..)) {
         return Err(invalid("exact-state input requires an exact family"));
     }
     crate::values::validate_family(&family)?;
@@ -219,31 +220,33 @@ pub fn exact_state_schema(family: FieldDataType) -> Result<SchemaRef, Error> {
     Ok(Arc::new(schema))
 }
 
-/// Retain exact readout semantics before any deployment state is opened.
-pub fn compile_exact_readout(
-    family: FieldDataType,
+/// Retain exact evaluation semantics before any deployment state is opened.
+pub fn compile_exact_evaluation(
+    family: SummaryFamilyType,
     lookback_ms: u64,
     preserve_metric_name: bool,
 ) -> Result<CompiledPhysicalDAG, Error> {
     use planner_types::post_asap::ExactKind;
     let statistic = match &family {
-        FieldDataType::ExactAggregate(kind, _) => match kind {
+        SummaryFamilyType::ExactAggregate(kind, _) => match kind {
             ExactKind::Sum => crate::Statistic::Sum,
             ExactKind::Count => crate::Statistic::Count,
             ExactKind::Min => crate::Statistic::Min,
             ExactKind::Max => crate::Statistic::Max,
             ExactKind::Rate => crate::Statistic::Rate,
             ExactKind::Increase => crate::Statistic::Increase,
-            ExactKind::IRate => return Err(invalid("instant-rate state readout is not supported")),
+            ExactKind::IRate => {
+                return Err(invalid("instant-rate state evaluation is not supported"))
+            }
         },
-        _ => return Err(invalid("exact readout requires an exact family")),
+        _ => return Err(invalid("exact evaluation requires an exact family")),
     };
     let input = exact_state_schema(family)?;
     let merge = Operator::summary_merge(input.clone(), 1, vec![0])?;
-    let mut readout = Operator::readout(
+    let mut evaluation = Operator::evaluation(
         merge.schema(),
         1,
-        ReadoutQuery::Exact(ExactReadout {
+        SummaryEvaluation::Exact(ExactEvaluation {
             statistic,
             lookback_ms: None,
         }),
@@ -252,12 +255,12 @@ pub fn compile_exact_readout(
         statistic,
         crate::Statistic::Rate | crate::Statistic::Increase
     ) {
-        readout = readout.with_counter_lookback(
+        evaluation = evaluation.with_counter_lookback(
             i64::try_from(lookback_ms).map_err(|_| invalid("counter lookback exceeds Int64"))?,
         )?;
     }
     let project = Operator::project(
-        readout.schema(),
+        evaluation.schema(),
         vec![
             (
                 "labels".into(),
@@ -274,5 +277,5 @@ pub fn compile_exact_readout(
             ("value".into(), Expression::ExactFloat64(1)),
         ],
     )?;
-    unary(vec![merge, readout, project], input)
+    unary(vec![merge, evaluation, project], input)
 }
diff --git a/crates/asap-physical-operators/src/physical_planner/row_values.rs b/crates/asap-physical-operators/src/physical_planner/row_values.rs
index 3396df685..14f3d4813 100644
--- a/crates/asap-physical-operators/src/physical_planner/row_values.rs
+++ b/crates/asap-physical-operators/src/physical_planner/row_values.rs
@@ -1,29 +1,20 @@
 //! Query-time PromQL value computation over logical row schemas.
 use super::*;
 use planner_types::post_asap::maintained_population::PopulationStatistic;
-use planner_types::pre_asap::{DataType, ScalarValue};
+use planner_types::pre_asap::DataType;
 
-/// A PromQL number literal has no row schema; its consumer folds it in.
-pub(super) fn scalar_literal(expression: &QueryExpr) -> Option<f64> {
-    match expression {
-        QueryExpr::PromqlScalarBridge(child) => scalar_literal(child),
-        QueryExpr::Literal(ScalarValue::Float64(value)) => Some(*value),
-        _ => None,
-    }
-}
-
-/// Aggregate readouts of a maintained current-series population, as a chain.
+/// Aggregate evaluations of a maintained current-series population, as a chain.
 pub(super) fn population_aggregate(
     input: &SchemaRef,
     grouping: &[String],
-    readout: &PopulationStatistic,
+    evaluation: &PopulationStatistic,
 ) -> Result<Vec<Operator>, Error> {
     let groups = grouping
         .iter()
         .map(|name| named_column(input, &ColumnRef::Named(name.clone())))
         .collect::<Result<Vec<_>, _>>()?;
     let value = named_column(input, &ColumnRef::SampleValue)?;
-    let reduction = match readout {
+    let reduction = match evaluation {
         PopulationStatistic::Sum => Reduction::Sum(value),
         PopulationStatistic::Count => Reduction::Count,
         PopulationStatistic::Average => Reduction::Avg(value),
@@ -33,7 +24,7 @@ pub(super) fn population_aggregate(
         },
         PopulationStatistic::TopK { .. } => {
             return Err(invalid(
-                "TopK population readout ranks; it does not aggregate",
+                "TopK population evaluation ranks; it does not aggregate",
             ))
         }
     };
diff --git a/crates/asap-physical-operators/src/runtime/batch_execution.rs b/crates/asap-physical-operators/src/runtime/batch_execution.rs
index ca59877cb..733741022 100644
--- a/crates/asap-physical-operators/src/runtime/batch_execution.rs
+++ b/crates/asap-physical-operators/src/runtime/batch_execution.rs
@@ -88,7 +88,7 @@ mod tests {
         values::Value,
     };
     use planner_types::{
-        post_asap::{Field, FieldDataType, Schema},
+        post_asap::{Field as SummaryField, FieldDataType as SummaryFamilyType, Schema},
         pre_asap::DataType,
     };
     use std::sync::Arc;
@@ -97,15 +97,15 @@ mod tests {
     #[test]
     fn same_native_chain_inside_query_and_ingestion_execution() {
         let schema = Arc::new(Schema {
-            closed: true,
-            unique_keys: vec![],
-            fields: vec![Field {
-                table: None,
+            fields: vec![SummaryField {
                 name: "value".into(),
-                dtype: FieldDataType::Plain(DataType::Float64),
+                dtype: SummaryFamilyType::Plain(DataType::Float64),
                 nullable: false,
+                table: None,
             }],
             time_index: None,
+            unique_keys: vec![],
+            closed: false,
         });
         for scope in [
             Scope::Query {
@@ -143,10 +143,10 @@ mod tests {
     #[test]
     fn in_memory_source_drives_cooperative_yields() {
         let schema = Arc::new(Schema {
-            closed: true,
-            unique_keys: vec![],
             fields: vec![],
             time_index: None,
+            unique_keys: vec![],
+            closed: false,
         });
         let batch = Batch::try_new(schema.clone(), vec![vec![]]).unwrap();
         let source = Operator::source(schema, vec![batch; 65]).unwrap();
@@ -165,10 +165,10 @@ mod tests {
     #[test]
     fn returned_batches_keep_their_resource_reservation() {
         let schema = Arc::new(Schema {
-            closed: true,
-            unique_keys: vec![],
             fields: vec![],
             time_index: None,
+            unique_keys: vec![],
+            closed: false,
         });
         let batch = Batch::try_new(schema.clone(), vec![vec![]]).unwrap();
         let bytes = batch.bytes();
@@ -196,10 +196,10 @@ mod tests {
     #[test]
     fn cancellation_is_not_bypassed_by_in_memory_execution() {
         let schema = Arc::new(Schema {
-            closed: true,
-            unique_keys: vec![],
             fields: vec![],
             time_index: None,
+            unique_keys: vec![],
+            closed: false,
         });
         let batch = Batch::try_new(schema, vec![vec![]]).unwrap();
         let context = RunContext::new(
diff --git a/crates/asap-physical-operators/src/sources/memory.rs b/crates/asap-physical-operators/src/sources/memory.rs
index 1055888de..856c73cb0 100644
--- a/crates/asap-physical-operators/src/sources/memory.rs
+++ b/crates/asap-physical-operators/src/sources/memory.rs
@@ -11,7 +11,7 @@ impl MemorySource {
         if schema
             .fields
             .iter()
-            .any(|f| !matches!(f.dtype, FieldDataType::Plain(_)))
+            .any(|f| !matches!(f.dtype, SummaryFamilyType::Plain(_)))
         {
             return Err(Error::Invalid(
                 "raw source cannot contain summary states".into(),
diff --git a/crates/asap-physical-operators/src/sources/mod.rs b/crates/asap-physical-operators/src/sources/mod.rs
index 4b401d666..9713c2a6f 100644
--- a/crates/asap-physical-operators/src/sources/mod.rs
+++ b/crates/asap-physical-operators/src/sources/mod.rs
@@ -7,9 +7,10 @@ use crate::{
     Error,
 };
 use futures::{stream, StreamExt};
+use planner_types::ir::{NonASAPOp, OperatorNode};
 use planner_types::{
-    post_asap::{FieldDataType, Schema},
-    pre_asap::{DataType, QueryExpr, Source},
+    post_asap::FieldDataType as SummaryFamilyType,
+    pre_asap::{DataType, Source},
 };
 use std::sync::Arc;
 
@@ -40,18 +41,18 @@ impl DataSources {
         self.sources.push((identity, source));
         Ok(())
     }
-    pub fn bind(&self, expression: &QueryExpr) -> Result<Scan, Error> {
-        let QueryExpr::Scan {
+    pub fn bind(&self, expression: &OperatorNode) -> Result<Scan, Error> {
+        let Some(NonASAPOp::Scan {
             source,
             predicates,
             schema,
-        } = expression
+        }) = expression.non_asap()
         else {
             return Err(Error::Invalid(
                 "raw Scan requires a Planner Scan leaf".into(),
             ));
         };
-        let output = Arc::new(Schema::lifted(schema.fields.clone(), schema.time_index));
+        let output = Arc::new(schema.clone());
         crate::values::validate_schema(&output)?;
         let reader = self
             .sources
diff --git a/crates/asap-physical-operators/src/summary_kernels/exact.rs b/crates/asap-physical-operators/src/summary_kernels/exact.rs
index d4754686e..d5375f9bf 100644
--- a/crates/asap-physical-operators/src/summary_kernels/exact.rs
+++ b/crates/asap-physical-operators/src/summary_kernels/exact.rs
@@ -2,7 +2,7 @@
 use super::increase::IncreaseAccumulator;
 use crate::Statistic;
 use crate::{AggregateCore, KeyByLabelValues, Measurement};
-use planner_types::post_asap::{ExactKind, ExactParams, FieldDataType};
+use planner_types::post_asap::{ExactKind, ExactParams, FieldDataType as SummaryFamilyType};
 use serde::{Deserialize, Serialize};
 use std::collections::HashMap;
 
@@ -10,7 +10,11 @@ type Error = Box<dyn std::error::Error + Send + Sync>;
 
 #[derive(Debug, Clone, Serialize, Deserialize)]
 enum ScalarState {
-    Sum { sum: f64, compensation: f64 },
+    Sum {
+        sum: f64,
+        compensation: f64,
+        seen: bool,
+    },
     Count(u64),
     Min(Option<f64>),
     Max(Option<f64>),
@@ -18,7 +22,7 @@ enum ScalarState {
 }
 
 /// Both the family and population layout survive persistence. Sharing counter
-/// arithmetic never authorizes a Rate state to answer an Increase readout.
+/// arithmetic never authorizes a Rate state to answer an Increase evaluation.
 ///
 /// Deserialization validates the payload against its declared family, so
 /// deployments can persist this state with any serde format without mirroring
@@ -26,14 +30,14 @@ enum ScalarState {
 #[derive(Debug, Clone, Serialize, Deserialize)]
 #[serde(try_from = "ExactPayload")]
 pub struct ExactAccumulator {
-    family: FieldDataType,
+    family: SummaryFamilyType,
     scalar: ScalarState,
     keyed: Option<HashMap<KeyByLabelValues, ScalarState>>,
 }
 
 #[derive(Deserialize)]
 struct ExactPayload {
-    family: FieldDataType,
+    family: SummaryFamilyType,
     scalar: ScalarState,
     keyed: Option<HashMap<KeyByLabelValues, ScalarState>>,
 }
@@ -63,10 +67,10 @@ impl TryFrom<ExactPayload> for ExactAccumulator {
     }
 }
 
-/// Planned readout of an exact summary. `lookback_ms` is the logical PromQL
+/// Planned evaluation of an exact summary. `lookback_ms` is the logical PromQL
 /// counter window; the evaluation range is resolved from it at run time.
 #[derive(Debug, Clone, Copy, PartialEq, Serialize, Deserialize)]
-pub struct ExactReadout {
+pub struct ExactEvaluation {
     pub statistic: Statistic,
     #[serde(default, skip_serializing_if = "Option::is_none")]
     pub lookback_ms: Option<i64>,
@@ -75,22 +79,24 @@ pub struct ExactReadout {
 impl ExactAccumulator {
     /// Read one population. An empty MIN/MAX population reads as `None`.
     /// `range_ms` extrapolates a counter Rate/Increase to that evaluation range.
-    pub fn readout(
+    pub fn evaluation(
         &self,
         statistic: Statistic,
         range_ms: Option<(i64, i64)>,
         key: Option<&KeyByLabelValues>,
     ) -> Result<Option<f64>, Error> {
         if statistic != self.statistic() {
-            return Err("readout differs from Planner exact family".into());
+            return Err("evaluation differs from Planner exact family".into());
         }
         let state = match (&self.keyed, key) {
             (Some(states), Some(key)) => states.get(key).ok_or("unknown exact population")?,
             (None, None) => &self.scalar,
-            _ => return Err("readout population differs from installed layout".into()),
+            _ => return Err("evaluation population differs from installed layout".into()),
         };
         match state {
-            ScalarState::Sum { sum, compensation } => Ok(Some(sum + compensation)),
+            ScalarState::Sum {
+                sum, compensation, ..
+            } => Ok(Some(sum + compensation)),
             ScalarState::Count(count) => Ok(Some(*count as f64)),
             ScalarState::Min(value) | ScalarState::Max(value) => Ok(*value),
             ScalarState::Counter(Some(counter)) => counter
@@ -100,6 +106,11 @@ impl ExactAccumulator {
         }
     }
 
+    /// SQL SUM distinguishes an empty/all-NULL input from an observed zero.
+    pub(crate) fn is_empty_sum(&self) -> bool {
+        self.keyed.is_none() && matches!(self.scalar, ScalarState::Sum { seen: false, .. })
+    }
+
     /// Exact integer count of an unkeyed Count state.
     pub fn count(&self) -> Option<u64> {
         match (&self.keyed, &self.scalar) {
@@ -128,19 +139,22 @@ impl ExactAccumulator {
         Ok(())
     }
 
-    pub fn new(family: FieldDataType, keyed: bool) -> Result<Self, String> {
+    pub fn new(family: SummaryFamilyType, keyed: bool) -> Result<Self, String> {
         use ExactKind as K;
         use ExactParams as P;
         let scalar = match &family {
-            FieldDataType::ExactAggregate(K::Sum, P::Sum) => ScalarState::Sum {
+            SummaryFamilyType::ExactAggregate(K::Sum, P::Sum) => ScalarState::Sum {
                 sum: 0.0,
                 compensation: 0.0,
+                seen: false,
             },
-            FieldDataType::ExactAggregate(K::Count, P::Count) => ScalarState::Count(0),
-            FieldDataType::ExactAggregate(K::Min, P::Min) => ScalarState::Min(None),
-            FieldDataType::ExactAggregate(K::Max, P::Max) => ScalarState::Max(None),
-            FieldDataType::ExactAggregate(K::Rate, P::Rate)
-            | FieldDataType::ExactAggregate(K::Increase, P::Increase) => ScalarState::Counter(None),
+            SummaryFamilyType::ExactAggregate(K::Count, P::Count) => ScalarState::Count(0),
+            SummaryFamilyType::ExactAggregate(K::Min, P::Min) => ScalarState::Min(None),
+            SummaryFamilyType::ExactAggregate(K::Max, P::Max) => ScalarState::Max(None),
+            SummaryFamilyType::ExactAggregate(K::Rate, P::Rate)
+            | SummaryFamilyType::ExactAggregate(K::Increase, P::Increase) => {
+                ScalarState::Counter(None)
+            }
             _ => return Err(format!("unsupported exact Planner family: {family:?}")),
         };
         Ok(Self {
@@ -150,7 +164,7 @@ impl ExactAccumulator {
         })
     }
 
-    pub fn family(&self) -> &FieldDataType {
+    pub fn family(&self) -> &SummaryFamilyType {
         &self.family
     }
     pub(crate) fn insufficient_counter_samples(
@@ -188,7 +202,14 @@ impl ExactAccumulator {
             _ => panic!("exact update population layout differs from installed DAG"),
         };
         match state {
-            ScalarState::Sum { sum, compensation } => compensated_add(sum, compensation, value),
+            ScalarState::Sum {
+                sum,
+                compensation,
+                seen,
+            } => {
+                compensated_add(sum, compensation, value);
+                *seen = true;
+            }
             ScalarState::Count(count) => {
                 *count = count.checked_add(1).expect("exact count overflow")
             }
@@ -214,12 +235,12 @@ impl ExactAccumulator {
 
     fn statistic(&self) -> Statistic {
         match self.family {
-            FieldDataType::ExactAggregate(ExactKind::Sum, _) => Statistic::Sum,
-            FieldDataType::ExactAggregate(ExactKind::Count, _) => Statistic::Count,
-            FieldDataType::ExactAggregate(ExactKind::Min, _) => Statistic::Min,
-            FieldDataType::ExactAggregate(ExactKind::Max, _) => Statistic::Max,
-            FieldDataType::ExactAggregate(ExactKind::Rate, _) => Statistic::Rate,
-            FieldDataType::ExactAggregate(ExactKind::Increase, _) => Statistic::Increase,
+            SummaryFamilyType::ExactAggregate(ExactKind::Sum, _) => Statistic::Sum,
+            SummaryFamilyType::ExactAggregate(ExactKind::Count, _) => Statistic::Count,
+            SummaryFamilyType::ExactAggregate(ExactKind::Min, _) => Statistic::Min,
+            SummaryFamilyType::ExactAggregate(ExactKind::Max, _) => Statistic::Max,
+            SummaryFamilyType::ExactAggregate(ExactKind::Rate, _) => Statistic::Rate,
+            SummaryFamilyType::ExactAggregate(ExactKind::Increase, _) => Statistic::Increase,
             _ => unreachable!("validated exact family"),
         }
     }
@@ -244,16 +265,22 @@ fn merge_scalar(left: &ScalarState, right: &ScalarState) -> Result<ScalarState,
             ScalarState::Sum {
                 sum: a,
                 compensation: ac,
+                seen: a_seen,
             },
             ScalarState::Sum {
                 sum: b,
                 compensation: bc,
+                seen: b_seen,
             },
         ) => {
             let (mut sum, mut compensation) = (*a, *ac);
             compensated_add(&mut sum, &mut compensation, *b);
             compensated_add(&mut sum, &mut compensation, *bc);
-            ScalarState::Sum { sum, compensation }
+            ScalarState::Sum {
+                sum,
+                compensation,
+                seen: *a_seen || *b_seen,
+            }
         }
         (ScalarState::Count(a), ScalarState::Count(b)) => {
             ScalarState::Count(a.checked_add(*b).ok_or("exact count overflow")?)
@@ -311,7 +338,7 @@ mod tests {
 
     #[derive(Serialize)]
     struct Payload {
-        family: FieldDataType,
+        family: SummaryFamilyType,
         scalar: ScalarState,
         keyed: Option<HashMap<KeyByLabelValues, ScalarState>>,
     }
@@ -320,8 +347,8 @@ mod tests {
         rmp_serde::from_slice(&rmp_serde::to_vec_named(payload).unwrap())
     }
 
-    fn sum() -> FieldDataType {
-        FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum)
+    fn sum() -> SummaryFamilyType {
+        SummaryFamilyType::ExactAggregate(ExactKind::Sum, ExactParams::Sum)
     }
 
     // Stored Sum preserves low-order increments across updates, persistence and pane merge.
@@ -337,7 +364,7 @@ mod tests {
         negative.update(None, -1e16, 1);
         restored.merge_from(&negative).unwrap();
         assert_eq!(
-            restored.readout(Statistic::Sum, None, None).unwrap(),
+            restored.evaluation(Statistic::Sum, None, None).unwrap(),
             Some(1.0)
         );
     }
@@ -349,18 +376,18 @@ mod tests {
         state.update(None, f64::INFINITY, 0);
         state.update(None, 1.0, 0);
         assert_eq!(
-            state.readout(Statistic::Sum, None, None).unwrap(),
+            state.evaluation(Statistic::Sum, None, None).unwrap(),
             Some(f64::INFINITY)
         );
         state.update(None, f64::NEG_INFINITY, 0);
         assert!(state
-            .readout(Statistic::Sum, None, None)
+            .evaluation(Statistic::Sum, None, None)
             .unwrap()
             .unwrap()
             .is_nan());
     }
 
-    // A persisted exact state decodes back to the same family, layout and readout.
+    // A persisted exact state decodes back to the same family, layout and evaluation.
     #[test]
     fn serialized_state_round_trips() {
         let mut state = ExactAccumulator::new(sum(), true).unwrap();
@@ -370,7 +397,9 @@ mod tests {
         let restored: ExactAccumulator = rmp_serde::from_slice(&bytes).unwrap();
         assert_eq!(restored.family(), &sum());
         assert_eq!(
-            restored.readout(Statistic::Sum, None, Some(&key)).unwrap(),
+            restored
+                .evaluation(Statistic::Sum, None, Some(&key))
+                .unwrap(),
             Some(2.5)
         );
     }
@@ -390,6 +419,7 @@ mod tests {
             scalar: ScalarState::Sum {
                 sum: 0.0,
                 compensation: 0.0,
+                seen: false,
             },
             keyed: Some(HashMap::from([(key, ScalarState::Max(Some(1.0)))])),
         };
@@ -400,10 +430,11 @@ mod tests {
     #[test]
     fn decode_rejects_unsupported_family() {
         let payload = Payload {
-            family: FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Count),
+            family: SummaryFamilyType::ExactAggregate(ExactKind::Sum, ExactParams::Count),
             scalar: ScalarState::Sum {
                 sum: 0.0,
                 compensation: 0.0,
+                seen: false,
             },
             keyed: None,
         };
diff --git a/crates/asap-physical-operators/src/summary_kernels/factory.rs b/crates/asap-physical-operators/src/summary_kernels/factory.rs
index 4be126d6e..be819f8a7 100644
--- a/crates/asap-physical-operators/src/summary_kernels/factory.rs
+++ b/crates/asap-physical-operators/src/summary_kernels/factory.rs
@@ -6,7 +6,7 @@ use crate::summary_kernels::{
     HydraKllSketchAccumulator,
 };
 use crate::{AggregateCore, KeyByLabelValues};
-use planner_types::post_asap::{FieldDataType, SketchAlgorithm, SketchParams};
+use planner_types::post_asap::{FieldDataType as SummaryFamilyType, SketchAlgorithm, SketchParams};
 
 /// Generate the clone-based `AccumulatorUpdater` methods for updaters whose
 /// inner `acc` field implements `Clone + AggregateCore`.
@@ -527,7 +527,7 @@ fn cms_heap_dims(params: &SketchParams) -> (usize, usize, usize) {
 /// Construct the kernel declared by a Planner SummaryAgg. No deployment config
 /// tags participate in this dispatch and unsupported payloads are errors.
 pub fn create_planner_accumulator(
-    family: &FieldDataType,
+    family: &SummaryFamilyType,
     input: &planner_types::post_asap::SummaryUpdate,
     grouping: &planner_types::post_asap::GroupingStrategy,
 ) -> Result<Box<dyn AccumulatorUpdater>, String> {
@@ -548,7 +548,7 @@ pub fn create_planner_accumulator(
     if grouping != &GroupingStrategy::PerSubpopulationInstance {
         return Err("shared summary grouping requires a supported Planner Hydra kernel".into());
     }
-    if matches!(family, FieldDataType::ExactAggregate(..)) {
+    if matches!(family, SummaryFamilyType::ExactAggregate(..)) {
         return Ok(Box::new(PlannerExactUpdater {
             acc: crate::summary_kernels::exact::ExactAccumulator::new(
                 family.clone(),
@@ -556,7 +556,7 @@ pub fn create_planner_accumulator(
             )?,
         }));
     }
-    let FieldDataType::Sketch(kind, family_grouping) = family else {
+    let SummaryFamilyType::Sketch(kind, family_grouping) = family else {
         return Err(format!("unsupported Planner summary family {family:?}"));
     };
     if family_grouping != grouping {
@@ -748,7 +748,7 @@ mod planner_parameter_regression {
                 },
             ),
         ] {
-            let family = FieldDataType::Sketch(
+            let family = SummaryFamilyType::Sketch(
                 SketchKind::new(algorithm.clone(), params),
                 Default::default(),
             );
diff --git a/crates/asap-physical-operators/src/summary_kernels/traits.rs b/crates/asap-physical-operators/src/summary_kernels/traits.rs
index 9c5d028fb..46e2c7f86 100644
--- a/crates/asap-physical-operators/src/summary_kernels/traits.rs
+++ b/crates/asap-physical-operators/src/summary_kernels/traits.rs
@@ -5,7 +5,7 @@ pub type KernelError = Box<dyn std::error::Error + Send + Sync>;
 /// In-memory state of one population's summary.
 ///
 /// Kernels adapt `asap_sketchlib` structures (or exact Planner state) to the
-/// operations physical operators need: merge, typed readout and memory
+/// operations physical operators need: merge, typed evaluation and memory
 /// accounting. Grouping belongs to operators; byte encodings belong to
 /// `asap_sketchlib` and deployments.
 pub trait AggregateCore: Send + Sync {
@@ -20,8 +20,8 @@ pub trait AggregateCore: Send + Sync {
     /// Merge with a state of the same family and shape, leaving both inputs unchanged.
     fn merge_with(&self, other: &dyn AggregateCore) -> Result<Box<dyn AggregateCore>, KernelError>;
 
-    /// Answer a sketch readout. Exact states are read through
-    /// [`ExactAccumulator::readout`](super::exact::ExactAccumulator::readout).
+    /// Answer a sketch evaluation. Exact states are read through
+    /// [`ExactAccumulator::evaluation`](super::exact::ExactAccumulator::evaluation).
     fn estimate(&self, query: &SketchStatistic) -> Result<f64, KernelError> {
         Err(format!("{query:?} is not supported by this summary").into())
     }
diff --git a/crates/asap-physical-operators/src/summary_kernels/univmon.rs b/crates/asap-physical-operators/src/summary_kernels/univmon.rs
index 9340b1c0e..23114ab1b 100644
--- a/crates/asap-physical-operators/src/summary_kernels/univmon.rs
+++ b/crates/asap-physical-operators/src/summary_kernels/univmon.rs
@@ -1,4 +1,4 @@
-//! One frequency state shared by count, distinct, L2 and entropy readouts.
+//! One frequency state shared by count, distinct, L2 and entropy evaluations.
 
 use crate::AggregateCore;
 use asap_sketchlib::{DataInput, UnivMon};
@@ -169,10 +169,10 @@ mod tests {
         }
     }
 
-    // Count, distinct, L2 and entropy readouts count each non-NaN sample once;
+    // Count, distinct, L2 and entropy evaluations count each non-NaN sample once;
     // signed zero is one identity.
     #[test]
-    fn frequency_readouts() {
+    fn frequency_evaluations() {
         let mut state = UnivMonAccumulator::new(32, 5, 1024, 4).unwrap();
         for value in [0.0, -0.0, 2.0, 2.0, f64::NAN] {
             state.insert_sample(value).unwrap();
@@ -187,9 +187,9 @@ mod tests {
             .is_err());
     }
 
-    // A sketch taken out and adopted back answers the same readouts.
+    // A sketch taken out and adopted back answers the same evaluations.
     #[test]
-    fn adopted_sketch_keeps_readouts() {
+    fn adopted_sketch_keeps_evaluations() {
         let mut state = UnivMonAccumulator::new(32, 5, 1024, 4).unwrap();
         for value in [1.0, 2.0, 2.0] {
             state.insert_sample(value).unwrap();
diff --git a/crates/asap-physical-operators/src/values.rs b/crates/asap-physical-operators/src/values.rs
index b1186c171..41640b7b6 100644
--- a/crates/asap-physical-operators/src/values.rs
+++ b/crates/asap-physical-operators/src/values.rs
@@ -2,7 +2,7 @@
 use crate::AggregateCore;
 use crate::Error;
 use planner_types::{
-    post_asap::{Field, FieldDataType, Schema},
+    post_asap::{Field as SummaryField, FieldDataType as SummaryFamilyType, Schema},
     pre_asap::DataType,
 };
 use std::{cmp::Ordering, sync::Arc};
@@ -28,7 +28,7 @@ pub enum Value {
     Map(Arc<[(Value, Value)]>),
     #[serde(skip)]
     Summary {
-        family: FieldDataType,
+        family: SummaryFamilyType,
         state: Arc<dyn AggregateCore>,
     },
 }
@@ -214,7 +214,9 @@ impl Batch {
             }
             for (value, field) in row.iter().zip(&schema.fields) {
                 let matches = match (&field.dtype, value) {
-                    (FieldDataType::Plain(dtype), value) => value.matches(dtype, field.nullable),
+                    (SummaryFamilyType::Plain(dtype), value) => {
+                        value.matches(dtype, field.nullable)
+                    }
                     (expected, Value::Summary { family, state }) => {
                         expected == family && validate_state(family, state.as_ref()).is_ok()
                     }
@@ -260,7 +262,7 @@ pub(crate) fn group_key(row: &[Value], columns: &[usize]) -> Result<Vec<Vec<u8>>
 
 pub(crate) use crate::capability::validate_native_family as validate_family;
 
-fn validate_state(family: &FieldDataType, state: &dyn AggregateCore) -> Result<(), Error> {
+fn validate_state(family: &SummaryFamilyType, state: &dyn AggregateCore) -> Result<(), Error> {
     use crate::summary_kernels::{
         count_min_sketch::CountMinSketchAccumulator, datasketches_kll::DatasketchesKLLAccumulator,
         dd_sketch::DDSketchAccumulator, exact::ExactAccumulator, hll_sketch::HllSketchAccumulator,
@@ -268,7 +270,7 @@ fn validate_state(family: &FieldDataType, state: &dyn AggregateCore) -> Result<(
     use planner_types::post_asap::SketchParams;
     validate_family(family)?;
     let valid = match family {
-        FieldDataType::Sketch(kind, _)
+        SummaryFamilyType::Sketch(kind, _)
             if matches!(
                 kind.params(),
                 SketchParams::CmsWithHeap { .. } | SketchParams::CountSketchWithHeap { .. }
@@ -284,11 +286,11 @@ fn validate_state(family: &FieldDataType, state: &dyn AggregateCore) -> Result<(
                 })
         }
 
-        FieldDataType::ExactAggregate(..) => state
+        SummaryFamilyType::ExactAggregate(..) => state
             .as_any()
             .downcast_ref::<ExactAccumulator>()
             .is_some_and(|s| s.family() == family && !s.is_keyed()),
-        FieldDataType::Sketch(kind, _) => match kind.params() {
+        SummaryFamilyType::Sketch(kind, _) => match kind.params() {
             SketchParams::Kll { k } => state
                 .as_any()
                 .downcast_ref::<DatasketchesKLLAccumulator>()
@@ -325,14 +327,14 @@ pub(crate) fn validate_schema(schema: &SchemaRef) -> Result<(), Error> {
         schema
             .fields
             .get(index)
-            .is_none_or(|field| field.dtype != FieldDataType::Plain(DataType::Timestamp))
+            .is_none_or(|field| field.dtype != SummaryFamilyType::Plain(DataType::Timestamp))
     }) {
         return Err(Error::Invalid(
             "time index must name a Timestamp column".into(),
         ));
     }
     for field in &schema.fields {
-        if !matches!(field.dtype, FieldDataType::Plain(_)) {
+        if !matches!(field.dtype, SummaryFamilyType::Plain(_)) {
             validate_family(&field.dtype)?;
             if field.nullable {
                 return Err(Error::Invalid(
@@ -344,7 +346,7 @@ pub(crate) fn validate_schema(schema: &SchemaRef) -> Result<(), Error> {
     Ok(())
 }
 
-pub(crate) fn field(schema: &SchemaRef, column: usize) -> Result<&Field, Error> {
+pub(crate) fn field(schema: &SchemaRef, column: usize) -> Result<&SummaryField, Error> {
     schema
         .fields
         .get(column)
@@ -352,7 +354,7 @@ pub(crate) fn field(schema: &SchemaRef, column: usize) -> Result<&Field, Error>
 }
 pub(crate) fn plain(schema: &SchemaRef, column: usize) -> Result<(&DataType, bool), Error> {
     let f = field(schema, column)?;
-    let FieldDataType::Plain(dtype) = &f.dtype else {
+    let SummaryFamilyType::Plain(dtype) = &f.dtype else {
         return Err(Error::Invalid("plain value required".into()));
     };
     Ok((dtype, f.nullable))
@@ -367,7 +369,7 @@ mod weighted_state_tests {
     // A state cannot acquire a different family or shape merely by relabeling its batch.
     #[test]
     fn weighted_state_family_and_shape_must_match() {
-        let cms = FieldDataType::Sketch(
+        let cms = SummaryFamilyType::Sketch(
             SketchKind::new(
                 SketchAlgorithm::CmsWithHeap,
                 SketchParams::CmsWithHeap {
@@ -378,7 +380,7 @@ mod weighted_state_tests {
             ),
             Default::default(),
         );
-        let cs = FieldDataType::Sketch(
+        let cs = SummaryFamilyType::Sketch(
             SketchKind::new(
                 SketchAlgorithm::CountSketchWithHeap,
                 SketchParams::CountSketchWithHeap {
@@ -395,7 +397,7 @@ mod weighted_state_tests {
         let wrong_shape =
             WeightedFrequency::new(FrequencyAlgorithm::CountSketch, 64, 5, 8).unwrap();
         assert!(validate_state(&cs, &wrong_shape).is_err());
-        let even_depth = FieldDataType::Sketch(
+        let even_depth = SummaryFamilyType::Sketch(
             SketchKind::new(
                 SketchAlgorithm::CountSketchWithHeap,
                 SketchParams::CountSketchWithHeap {
diff --git a/crates/asap-physical-operators/tests/blocking_resources.rs b/crates/asap-physical-operators/tests/blocking_resources.rs
index 37f780812..66702afdb 100644
--- a/crates/asap-physical-operators/tests/blocking_resources.rs
+++ b/crates/asap-physical-operators/tests/blocking_resources.rs
@@ -7,16 +7,18 @@ use asap_physical_operators::{
     Error,
 };
 use futures::{executor::block_on, FutureExt, StreamExt};
+use planner_types::ir::Predicate;
+use planner_types::ir::ScalarExpr as QueryExpr;
 use planner_types::{
-    post_asap::{Field, FieldDataType, Schema},
-    pre_asap::{DataType, JoinKind, Predicate, QueryExpr, ScalarValue},
+    post_asap::{Field, FieldDataType},
+    pre_asap::{DataType, JoinKind, ScalarValue},
 };
 use std::sync::Arc;
 
 fn schema(width: usize) -> SchemaRef {
-    Arc::new(Schema {
-        closed: true,
+    Arc::new(planner_types::pre_asap::Schema {
         unique_keys: vec![],
+        closed: false,
         fields: (0..width)
             .map(|i| Field {
                 table: None,
@@ -60,9 +62,7 @@ fn cross_join() -> Operator {
         schema(1),
         schema(1),
         JoinKind::Cross,
-        &Predicate(std::rc::Rc::new(QueryExpr::Literal(ScalarValue::Boolean(
-            true,
-        )))),
+        &Predicate(QueryExpr::Literal(ScalarValue::Boolean(true))),
         schema(2),
     )
     .unwrap()
@@ -189,9 +189,10 @@ fn cooperative_sort_preserves_ties_across_chunks() {
 #[test]
 fn weighted_summary_build_yields_within_a_batch() {
     use planner_types::post_asap::{SketchAlgorithm, SketchKind, SketchParams};
-    let input = Arc::new(Schema {
-        closed: true,
+
+    let input = Arc::new(planner_types::pre_asap::Schema {
         unique_keys: vec![],
+        closed: false,
         fields: vec![
             Field {
                 table: None,
diff --git a/crates/asap-physical-operators/tests/unified_common/mod.rs b/crates/asap-physical-operators/tests/common/mod.rs
similarity index 100%
rename from crates/asap-physical-operators/tests/unified_common/mod.rs
rename to crates/asap-physical-operators/tests/common/mod.rs
diff --git a/crates/asap-physical-operators/tests/current_series_heap.rs b/crates/asap-physical-operators/tests/current_series_heap.rs
index 079c2bd69..10fc036e7 100644
--- a/crates/asap-physical-operators/tests/current_series_heap.rs
+++ b/crates/asap-physical-operators/tests/current_series_heap.rs
@@ -1,4 +1,5 @@
 //! Spatial heap weights come from a fresh instant vector, never sample history.
+mod common;
 use asap_physical_operators::{
     operators::Operator,
     physical_planner::{
@@ -8,15 +9,16 @@ use asap_physical_operators::{
     runtime::{Limits, RunContext, Scope},
     values::{Batch, Value},
 };
+use common::compile_physical_asap_dag;
 use futures::{executor::block_on, StreamExt};
-use planner_types::pre_asap::Schema;
+use planner_types::ir::export::PhysicalASAPOperatorPayload;
 use planner_types::{post_asap::*, pre_asap::DataType};
 use std::{collections::BTreeMap, sync::Arc};
 
 fn schema() -> Arc<Schema> {
-    Arc::new(Schema {
-        closed: true,
+    Arc::new(planner_types::pre_asap::Schema {
         unique_keys: vec![],
+        closed: false,
         fields: [
             ("ts", DataType::Timestamp),
             ("value", DataType::Float64),
@@ -169,9 +171,9 @@ fn spatial_heap_ranks_latest_values_in_independent_runs() {
         };
         let family = FieldDataType::Sketch(SketchKind::new(algorithm, params), Default::default());
         let build = Operator::keyed_summary_build(schema(), family, 1, vec![3], vec![2]).unwrap();
-        let output = Arc::new(Schema {
-            closed: true,
+        let output = Arc::new(planner_types::pre_asap::Schema {
             unique_keys: vec![],
+            closed: false,
             fields: vec![
                 schema().fields[2].clone(),
                 schema().fields[3].clone(),
@@ -179,7 +181,7 @@ fn spatial_heap_ranks_latest_values_in_independent_runs() {
             ],
             time_index: None,
         });
-        let read = Operator::keyed_readout(build.schema(), 1, 1, output).unwrap();
+        let read = Operator::keyed_evaluation(build.schema(), 1, 1, output).unwrap();
         let plan = CompiledPhysicalDAG::from_operators(
             BTreeMap::from([(0, InputContract::bounded(schema()))]),
             BTreeMap::from([
@@ -331,7 +333,7 @@ fn planner_current_series_candidate_compiles_with_dynamic_identity() {
         .candidate(&open_root)
         .unwrap();
     let snapshot_program =
-        asap_physical_operators::physical_planner::promql_rows::compile_current_series_readout(
+        asap_physical_operators::physical_planner::promql_rows::compile_current_series_evaluation(
             &open_selected,
         )
         .unwrap();
@@ -348,11 +350,18 @@ fn planner_current_series_candidate_compiles_with_dynamic_identity() {
     )
     .candidate(&root)
     .unwrap();
-    let logical = compile_post_asap_dag(&selected).unwrap();
+    let logical = compile_physical_asap_dag(&selected).unwrap();
     let raw = logical
         .nodes
         .iter()
-        .find(|node| matches!(node.payload, PostAsapOperatorPayload::Fallback { .. }))
+        .find(|node| {
+            matches!(
+                node.payload,
+                PhysicalASAPOperatorPayload::Relational {
+                    operator: planner_types::ir::export::NonASAPOpKind::TimeRange { .. }
+                }
+            )
+        })
         .unwrap();
     let raw_schema = Arc::new(raw.output_schema.clone());
     let physical = compile(
@@ -361,7 +370,7 @@ fn planner_current_series_candidate_compiles_with_dynamic_identity() {
             u64::from(raw.id.0),
             InputContract::bounded(raw_schema.clone()),
         )]),
-        &[u64::from(logical.root.0)],
+        &[u64::from(logical.roots[0].0)],
     )
     .unwrap();
     let bytes = String::from_utf8(serde_json::to_vec(&physical).unwrap()).unwrap();
diff --git a/crates/asap-physical-operators/tests/deployment.rs b/crates/asap-physical-operators/tests/deployment.rs
index 2857a81cb..72e0503f1 100644
--- a/crates/asap-physical-operators/tests/deployment.rs
+++ b/crates/asap-physical-operators/tests/deployment.rs
@@ -35,7 +35,7 @@ fn read(state: &dyn AggregateCore) -> f64 {
 }
 
 // The same kernels work when every build is query-time, when only a prefix
-// was precomputed, and when all state was precomputed before the readout.
+// was precomputed, and when all state was precomputed before the evaluation.
 #[test]
 fn raw_partial_and_fully_precomputed_use_the_same_kernels() {
     let raw: Vec<f64> = (0..128).map(f64::from).collect();
diff --git a/crates/asap-physical-operators/tests/deployment_computation.rs b/crates/asap-physical-operators/tests/deployment_computation.rs
index e20fc27ee..0eecf2f5a 100644
--- a/crates/asap-physical-operators/tests/deployment_computation.rs
+++ b/crates/asap-physical-operators/tests/deployment_computation.rs
@@ -1,21 +1,23 @@
 //! Planner-selected PromQL computation compiles from the timed DAG alone;
 //! the deployment supplies only raw rows at the ingestion frontier.
+mod common;
 use asap_physical_operators::{
     operators::Operator,
     physical_planner::{compile, promql_rows, CompiledPhysicalDAG, InputContract, Source},
     runtime::{Limits, RunContext, Scope},
     values::{Batch, Value},
 };
+use common::compile_physical_asap_dag;
 use futures::{executor::block_on, StreamExt};
-use planner_types::pre_asap::Schema;
-use planner_types::{post_asap::*, pre_asap::QueryExpr, types::AccuracyTarget, workload::*};
+use planner_types::ir::export::{PhysicalASAPDAG, PhysicalASAPOperatorPayload};
+use planner_types::{post_asap::*, types::AccuracyTarget, workload::*};
 use std::{collections::BTreeMap, rc::Rc, sync::Arc};
 
-fn lower(query: &str) -> QueryExpr {
+fn lower(query: &str) -> Rc<planner_types::ir::OperatorNode> {
     lower_with(query, AccuracyTarget::Exact)
 }
 
-fn lower_with(query: &str, accuracy: AccuracyTarget) -> QueryExpr {
+fn lower_with(query: &str, accuracy: AccuracyTarget) -> Rc<planner_types::ir::OperatorNode> {
     let workload = PlanningWorkload {
         query_workload: QueryWorkload {
             language: QueryLanguage::PromQL,
@@ -46,54 +48,56 @@ fn lower_with(query: &str, accuracy: AccuracyTarget) -> QueryExpr {
 }
 
 /// The first exact summary candidate, as Planner selection would hand it over.
-fn exact_dag(query: &str) -> PostAsapDAG {
-    use asap_aware_mapping::{Replacement, ReplacementStrategy, TargetSubDAG};
+fn exact_dag(query: &str) -> PhysicalASAPDAG {
     let expression = lower(query);
-    let root = Rc::new(promql_rows::with_series_identity(&expression).unwrap_or(expression));
-    asap_aware_mapping::SketchAlgorithmStrategy::new(&asap_aware_mapping::DefaultCostModel)
-        .replacements(&TargetSubDAG::new(&root))
-        .into_iter()
-        .find_map(|candidate| match candidate.replacement {
-            Replacement::Summary(node) => {
-                let dag = compile_post_asap_dag(&node).ok()?;
-                dag.nodes
-                    .iter()
-                    .all(|n| !matches!(&n.payload, PostAsapOperatorPayload::SummaryAgg { family, .. } if !matches!(family, FieldDataType::ExactAggregate(..))))
-                    .then_some(dag)
-            }
-            _ => None,
-        })
+    let root = promql_rows::with_series_identity(&expression).unwrap_or(expression);
+    let space = asap_aware_mapping::search_workload(vec![("q", root)]);
+    let selected = space
+        .global_selection(&asap_aware_mapping::DefaultCostModel)
+        .assemble_selected_dag(&space.roots[0].1)
         .unwrap()
+        .unwrap();
+    compile_physical_asap_dag(&selected).unwrap()
 }
 
-fn population_dag(query: &str) -> PostAsapDAG {
-    let root = Rc::new(promql_rows::with_series_identity(&lower(query)).unwrap());
+fn population_dag(query: &str) -> PhysicalASAPDAG {
+    let root = promql_rows::with_series_identity(&lower(query)).unwrap();
     let selected = asap_aware_mapping::maintained_population::MaintainedPopulationStrategy::new(
         std::slice::from_ref(&root),
     )
     .candidate(&root)
     .unwrap();
-    compile_post_asap_dag(&selected).unwrap()
+    compile_physical_asap_dag(&selected).unwrap()
 }
 
 /// Raw scan nodes are the frontier; everything above them is compiled.
-fn raw_inputs(dag: &PostAsapDAG) -> Vec<(u64, Arc<Schema>, String)> {
+fn raw_inputs(dag: &PhysicalASAPDAG) -> Vec<(u64, Arc<Schema>, String)> {
     dag.nodes
         .iter()
         .filter_map(|node| match &node.payload {
-            PostAsapOperatorPayload::Fallback {
-                expression: QueryExpr::TimeRange { child, .. },
-            } => match child.as_ref() {
-                QueryExpr::Scan {
-                    source: planner_types::pre_asap::Source::TimeSeries { metric },
-                    ..
-                } => Some((
-                    u64::from(node.id.0),
-                    Arc::new(node.output_schema.clone()),
-                    metric.clone(),
-                )),
-                _ => None,
-            },
+            PhysicalASAPOperatorPayload::Relational {
+                operator: planner_types::ir::export::NonASAPOpKind::TimeRange { .. },
+            } => {
+                let mut id = node.id;
+                loop {
+                    let n = dag.nodes.iter().find(|n| n.id == id)?;
+                    if let PhysicalASAPOperatorPayload::Relational {
+                        operator:
+                            planner_types::ir::export::NonASAPOpKind::Scan {
+                                source: planner_types::pre_asap::Source::TimeSeries { metric },
+                                ..
+                            },
+                    } = &n.payload
+                    {
+                        return Some((
+                            u64::from(node.id.0),
+                            Arc::new(node.output_schema.clone()),
+                            metric.clone(),
+                        ));
+                    }
+                    id = dag.edges.iter().find(|e| e.consumer == id)?.producer;
+                }
+            }
             _ => None,
         })
         .collect()
@@ -104,7 +108,7 @@ type Sample = (&'static str, &'static str, &'static str, i64, f64);
 /// Compile, round-trip, bind raw `(metric, job, instance, ts, value)` samples,
 /// and return the root's batches.
 fn execute(
-    dag: &PostAsapDAG,
+    dag: &PhysicalASAPDAG,
     samples: &[Sample],
     end: i64,
 ) -> Result<Vec<asap_physical_operators::runtime::SharedValue<Batch>>, String> {
@@ -114,7 +118,7 @@ fn execute(
 /// [`execute`], supplying samples of each instance in `relabel` under its
 /// `(__name__, instance)` instead.
 fn execute_relabeled(
-    dag: &PostAsapDAG,
+    dag: &PhysicalASAPDAG,
     samples: &[Sample],
     end: i64,
     relabel: &BTreeMap<&str, (&str, &str)>,
@@ -126,7 +130,7 @@ fn execute_relabeled(
             .iter()
             .map(|(id, schema, _)| (*id, InputContract::bounded(schema.clone())))
             .collect(),
-        &[u64::from(dag.root.0)],
+        &[u64::from(dag.roots[0].0)],
     )
     .map_err(|e| e.to_string())?;
     let program: CompiledPhysicalDAG =
@@ -195,7 +199,11 @@ fn execute_relabeled(
 }
 
 /// [`execute`], returning `(job, value)` rows of the root.
-fn run(dag: &PostAsapDAG, samples: &[Sample], end: i64) -> Result<BTreeMap<String, f64>, String> {
+fn run(
+    dag: &PhysicalASAPDAG,
+    samples: &[Sample],
+    end: i64,
+) -> Result<BTreeMap<String, f64>, String> {
     let mut rows = BTreeMap::new();
     for batch in execute(dag, samples, end)? {
         let job = batch.schema().fields.iter().position(|f| f.name == "job");
@@ -250,7 +258,7 @@ fn population_aggregates_match_current_series_reference() {
     }
 }
 
-// A global readout of an empty population is an empty vector, as in PromQL.
+// A global evaluation of an empty population is an empty vector, as in PromQL.
 #[test]
 fn global_population_aggregate_of_no_members_is_empty() {
     // Latest values are [1, 2, 5, 7] at 60s; every member has expired by 1000s.
@@ -313,40 +321,7 @@ fn grouped_vector_arithmetic_matches_labels() {
 // then roll up per job: api has 2 + 1 + 1 samples in 5m, db has 1.
 #[test]
 fn exact_count_finalizes_to_declared_float_value() {
-    let mut dag = exact_dag("sum by (job) (count_over_time(m[5m]))");
-    let finalize = dag
-        .nodes
-        .iter()
-        .find(|node| {
-            matches!(
-                node.payload,
-                PostAsapOperatorPayload::Value {
-                    operation: ValueOperation::FinalizeExactAccumulator
-                }
-            )
-        })
-        .unwrap()
-        .clone();
-    let root = dag.nodes.iter().find(|n| n.id == dag.root).unwrap().clone();
-    let mut edge = dag
-        .edges
-        .iter()
-        .find(|e| e.producer == finalize.id)
-        .unwrap()
-        .clone();
-    // Read the rolled-up exact state the same way the query path does.
-    let mut read = finalize.clone();
-    read.id = PostAsapNodeId(root.id.0 + 1);
-    read.output_schema = root.output_schema.clone();
-    read.output_schema.fields.last_mut().unwrap().dtype =
-        FieldDataType::Plain(planner_types::pre_asap::DataType::Float64);
-    edge.producer = root.id;
-    edge.consumer = read.id;
-    edge.intermediate_schema = root.output_schema.clone();
-    edge.data_state = root.output_state;
-    dag.root = read.id;
-    dag.nodes.push(read);
-    dag.edges.push(edge);
+    let dag = exact_dag("sum by (job) (count_over_time(m[5m]))");
     assert_eq!(
         run(&dag, SAMPLES, 60_000).unwrap(),
         reference(&[("api", 4.), ("db", 1.)])
@@ -354,10 +329,22 @@ fn exact_count_finalizes_to_declared_float_value() {
 }
 
 /// `dag` with its Binary operator replaced by `kind`.
-fn with_kind(mut dag: PostAsapDAG, kind: planner_types::pre_asap::BinaryOpKind) -> PostAsapDAG {
+fn with_kind(
+    mut dag: PhysicalASAPDAG,
+    kind: planner_types::pre_asap::BinaryOpKind,
+    bool_result: bool,
+) -> PhysicalASAPDAG {
     for node in &mut dag.nodes {
-        if let PostAsapOperatorPayload::Binary { operator } = &mut node.payload {
+        if let PhysicalASAPOperatorPayload::Relational {
+            operator:
+                planner_types::ir::export::NonASAPOpKind::BinaryOp {
+                    operator,
+                    return_bool,
+                },
+        } = &mut node.payload
+        {
             operator.kind = kind.clone();
+            *return_bool = bool_result;
         }
     }
     dag
@@ -367,30 +354,30 @@ fn with_kind(mut dag: PostAsapDAG, kind: planner_types::pre_asap::BinaryOpKind)
 // holds, with their value, on either side of the literal; `bool` yields 1 or 0.
 #[test]
 fn grouped_comparisons_filter_or_return_bool() {
-    use planner_types::pre_asap::{BinaryOpKind::*, CompareOpKind::Gt};
-    // sum_over_time over 5m per job: api = 14, db = 5.
-    let right = exact_dag("sum by (job) (sum_over_time(m[5m])) * 10");
-    let left = exact_dag("10 - sum by (job) (sum_over_time(m[5m]))");
-    for (dag, expected) in [
+    for (query, expected) in [
         (
-            with_kind(right.clone(), Compare(Gt)),
+            "sum by(job)(sum_over_time(m[5m])) > 10",
             reference(&[("api", 14.)]),
         ),
         (
-            with_kind(right, CompareBool(Gt)),
+            "sum by(job)(sum_over_time(m[5m])) > bool 10",
             reference(&[("api", 1.), ("db", 0.)]),
         ),
-        (with_kind(left, Compare(Gt)), reference(&[("db", 5.)])),
+        (
+            "10 > sum by(job)(sum_over_time(m[5m]))",
+            reference(&[("db", 5.)]),
+        ),
     ] {
-        assert_eq!(run(&dag, SAMPLES, 60_000).unwrap(), expected);
+        assert_eq!(run(&exact_dag(query), SAMPLES, 60_000).unwrap(), expected);
     }
 }
 
-// A `bool` comparison Binary over per-series readouts matches one-to-one and
+// A `bool` comparison Binary over per-series evaluations matches one-to-one and
 // drops the metric name; a filter keeps the surviving left value.
 #[test]
 fn per_series_comparisons_filter_or_return_bool() {
     use planner_types::pre_asap::{BinaryOpKind::*, CompareOpKind::*};
+
     let samples = counter("a", "api", 10., 10.)
         .chain(counter("a", "db", 10., 10.))
         .chain(counter("b", "api", 5., 5.))
@@ -399,18 +386,23 @@ fn per_series_comparisons_filter_or_return_bool() {
     // rate: a{api} = a{db} = 50/300, b{api} = 25/300, b{db} = 100/300.
     let dag = exact_dag("rate(a[5m]) / rate(b[5m])");
     assert_eq!(
-        run_series(&with_kind(dag.clone(), Compare(Gt)), &samples, 300_000).unwrap(),
+        run_series(
+            &with_kind(dag.clone(), Compare(Gt), false),
+            &samples,
+            300_000
+        )
+        .unwrap(),
         series(&[("api", "x", 50. / 300.)])
     );
     assert_eq!(
-        run_series(&with_kind(dag, CompareBool(Lt)), &samples, 300_000).unwrap(),
+        run_series(&with_kind(dag, Compare(Lt), true), &samples, 300_000).unwrap(),
         series(&[("api", "x", 0.), ("db", "x", 1.)])
     );
 }
 
 /// [`execute`], returning per-series `(identity, value)` rows of the root,
 /// with NaN-aware formatting for comparison.
-fn run_series(dag: &PostAsapDAG, samples: &[Sample], end: i64) -> Result<String, String> {
+fn run_series(dag: &PhysicalASAPDAG, samples: &[Sample], end: i64) -> Result<String, String> {
     let mut rows = BTreeMap::new();
     for batch in execute(dag, samples, end)? {
         let schema = batch.schema();
@@ -509,13 +501,13 @@ fn per_series_rate_ratio_matches_prometheus() {
 // A literal operand applies to every stored per-series value, on either side,
 // and drops the metric name.
 #[test]
-fn per_series_scalar_arithmetic_applies_to_stored_readouts() {
+fn per_series_scalar_arithmetic_applies_to_stored_evaluations() {
     let samples = counter("m", "api", 10., 10.).collect::<Vec<_>>();
     // rate = 40 * 1.25 / 300 = 1/6.
     for (query, expected) in [
         ("rate(m[5m]) * 2", 50. / 300. * 2.),
         ("1 - rate(m[5m])", 1. - 50. / 300.),
-        // The stored sum readout keeps `__name__`; the arithmetic drops it.
+        // The stored sum evaluation keeps `__name__`; the arithmetic drops it.
         ("sum_over_time(m[5m]) * 2", 150. * 2.),
     ] {
         assert_eq!(
@@ -545,12 +537,19 @@ fn per_series_scalar_arithmetic_rejects_label_sets_equal_without_the_name() {
 }
 
 fn with_vector_match(
-    mut dag: PostAsapDAG,
+    mut dag: PhysicalASAPDAG,
     kind: planner_types::pre_asap::VectorMatchKind,
     labels: &[&str],
-) -> PostAsapDAG {
+) -> PhysicalASAPDAG {
     for node in &mut dag.nodes {
-        if let PostAsapOperatorPayload::Binary { operator } = &mut node.payload {
+        if let PhysicalASAPOperatorPayload::Relational {
+            operator:
+                planner_types::ir::export::NonASAPOpKind::BinaryOp {
+                    operator,
+                    return_bool: _,
+                },
+        } = &mut node.payload
+        {
             operator.vector_match = Some(planner_types::pre_asap::VectorMatch {
                 kind: kind.clone(),
                 labels: labels.iter().map(|l| l.to_string()).collect(),
@@ -621,44 +620,43 @@ fn population_sums_and_averages_are_compensated() {
     }
 }
 
-// A bare count over stored Count-Min state compiles to a Planner readout that
+// A bare count over stored Count-Min state compiles to a Planner evaluation that
 // returns the sketch's total update weight, including colliding items.
 #[test]
-fn stored_count_min_bare_count_compiles_to_a_readout() {
+fn stored_count_min_bare_count_compiles_to_a_evaluation() {
     use asap_aware_mapping::{Replacement, ReplacementStrategy, TargetSubDAG};
     use asap_physical_operators::summary_kernels::CountMinSketchAccumulator;
-    let root = Rc::new(lower_with("count(up)", AccuracyTarget::Epsilon(0.02)));
-    let dag =
-        asap_aware_mapping::SketchAlgorithmStrategy::new(&asap_aware_mapping::DefaultCostModel)
-            .replacements(&TargetSubDAG::new(&root))
-            .into_iter()
-            .find_map(|candidate| match candidate.replacement {
-                Replacement::Summary(node) => {
-                    let dag = compile_post_asap_dag(&node).ok()?;
-                    let bare_count = dag.nodes.iter().any(|n| {
-                        matches!(
-                            &n.payload,
-                            PostAsapOperatorPayload::SummaryEstimate {
-                                query: SketchStatistic::PointCount { value: None, .. }
-                            }
-                        )
-                    });
-                    let count_min = dag.nodes.iter().any(|n| {
-                        matches!(&n.payload, PostAsapOperatorPayload::SummaryAgg {
+    let root = lower_with("count(up)", AccuracyTarget::Epsilon(0.02));
+    let dag = asap_aware_mapping::ASAPStrategies::new(&asap_aware_mapping::DefaultCostModel)
+        .replacements(&TargetSubDAG::new(&root))
+        .into_iter()
+        .find_map(|candidate| match candidate.replacement {
+            Replacement::SubDAG(node) => {
+                let dag = compile_physical_asap_dag(&node).ok()?;
+                let bare_count = dag.nodes.iter().any(|n| {
+                    matches!(
+                        &n.payload,
+                        PhysicalASAPOperatorPayload::SummaryEstimate {
+                            query: SketchStatistic::PointCount { value: None, .. }
+                        }
+                    )
+                });
+                let count_min = dag.nodes.iter().any(|n| {
+                    matches!(&n.payload, PhysicalASAPOperatorPayload::SummaryAgg {
                         family: FieldDataType::Sketch(kind, _), ..
                     } if kind.algorithm() == &SketchAlgorithm::Cms)
-                    });
-                    (bare_count && count_min).then_some(dag)
-                }
-                _ => None,
-            })
-            .expect("Planner lists a Count-Min candidate for count(up)");
+                });
+                (bare_count && count_min).then_some(dag)
+            }
+            _ => None,
+        })
+        .expect("Planner lists a Count-Min candidate for count(up)");
     let state = dag
         .nodes
         .iter()
-        .find(|n| matches!(n.payload, PostAsapOperatorPayload::SummaryAgg { .. }))
+        .find(|n| matches!(n.payload, PhysicalASAPOperatorPayload::SummaryAgg { .. }))
         .unwrap();
-    let PostAsapOperatorPayload::SummaryAgg {
+    let PhysicalASAPOperatorPayload::SummaryAgg {
         family: FieldDataType::Sketch(kind, _),
         ..
     } = &state.payload
@@ -675,7 +673,7 @@ fn stored_count_min_bare_count_compiles_to_a_readout() {
             u64::from(state.id.0),
             InputContract::bounded(schema.clone()),
         )]),
-        &[u64::from(dag.root.0)],
+        &[u64::from(dag.roots[0].0)],
     )
     .unwrap();
     let program: CompiledPhysicalDAG =
diff --git a/crates/asap-physical-operators/tests/physical_dag.rs b/crates/asap-physical-operators/tests/physical_dag.rs
index e2ad735d6..450b95652 100644
--- a/crates/asap-physical-operators/tests/physical_dag.rs
+++ b/crates/asap-physical-operators/tests/physical_dag.rs
@@ -8,15 +8,22 @@ use asap_physical_operators::{
     Statistic,
 };
 use futures::{executor::block_on, StreamExt};
+use planner_types::ir::export::NonASAPOpKind as ValueOperation;
+use planner_types::ir::export::{
+    EdgeRole, GroupingEdgeCompatibility, PhysicalASAPDAG, PhysicalASAPDAGEdge, PhysicalASAPDAGNode,
+    PhysicalASAPOperatorPayload, WindowEdgeCompatibility,
+};
+use planner_types::ir::BinaryOperator;
+use planner_types::ir::ScalarExpr as QueryExpr;
 use planner_types::{
-    post_asap::{ExactKind, ExactParams, Field, FieldDataType, Schema},
+    post_asap::{ExactKind, ExactParams, Field, FieldDataType},
     pre_asap::DataType,
 };
 use std::sync::Arc;
 fn schema(fields: &[(&str, DataType, bool)]) -> SchemaRef {
-    Arc::new(Schema {
-        closed: true,
+    Arc::new(planner_types::pre_asap::Schema {
         unique_keys: vec![],
+        closed: false,
         fields: fields
             .iter()
             .map(|(name, dtype, nullable)| Field {
@@ -117,7 +124,7 @@ fn grouped_sort_limit_across_batches() {
 
 // The same computation runs in either engine scope with fresh per-run state.
 #[test]
-fn summary_construction_merge_and_readout_at_both_phases() {
+fn summary_construction_merge_and_evaluation_at_both_phases() {
     let schema = schema(&[("v", DataType::Float64, false)]);
     let batches = (1..=20)
         .map(|v| Batch::try_new(schema.clone(), vec![vec![Value::Float64(v as f64)]]).unwrap())
@@ -140,11 +147,11 @@ fn summary_construction_merge_and_readout_at_both_phases() {
     dag.add(
         4,
         vec![3],
-        Operator::readout(
+        Operator::evaluation(
             state,
             0,
-            asap_physical_operators::operators::ReadoutQuery::Exact(
-                asap_physical_operators::summary_kernels::exact::ExactReadout {
+            asap_physical_operators::operators::SummaryEvaluation::Exact(
+                asap_physical_operators::summary_kernels::exact::ExactEvaluation {
                     statistic: Statistic::Sum,
                     lookback_ms: None,
                 },
@@ -295,10 +302,10 @@ fn binding_rejects_unsupported_operations() {
         vec![],
     )
     .unwrap();
-    assert!(Operator::readout(
+    assert!(Operator::evaluation(
         sum.schema(),
         0,
-        asap_physical_operators::operators::ReadoutQuery::Sketch(
+        asap_physical_operators::operators::SummaryEvaluation::Sketch(
             planner_types::post_asap::SketchStatistic::Quantile { q: 0.5 }
         )
     )
@@ -310,6 +317,7 @@ fn binding_rejects_unsupported_operations() {
 #[test]
 fn kll_raw_partial_and_precomputed_are_native_dags() {
     use planner_types::post_asap::{GroupingStrategy, SketchAlgorithm, SketchKind, SketchParams};
+
     let input = schema(&[("value", DataType::Float64, false)]);
     let family = FieldDataType::Sketch(
         SketchKind::new(SketchAlgorithm::Kll, SketchParams::Kll { k: 512 }),
@@ -396,10 +404,10 @@ fn kll_raw_partial_and_precomputed_are_native_dags() {
         dag.add(
             5,
             vec![4],
-            Operator::readout(
+            Operator::evaluation(
                 state.clone(),
                 0,
-                asap_physical_operators::operators::ReadoutQuery::Sketch(
+                asap_physical_operators::operators::SummaryEvaluation::Sketch(
                     planner_types::post_asap::SketchStatistic::Quantile { q: 0.5 },
                 ),
             )
@@ -423,9 +431,9 @@ fn exact_state_and_family_validation() {
     let family = FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum);
     let mut acc = ExactAccumulator::new(family.clone(), false).unwrap();
     acc.update(None, 7., 0);
-    let schema = Arc::new(Schema {
-        closed: true,
+    let schema = Arc::new(planner_types::pre_asap::Schema {
         unique_keys: vec![],
+        closed: false,
         fields: vec![Field {
             table: None,
             name: "state".into(),
@@ -452,11 +460,11 @@ fn exact_state_and_family_validation() {
     dag.add(
         1,
         vec![0],
-        Operator::readout(
+        Operator::evaluation(
             schema.clone(),
             0,
-            asap_physical_operators::operators::ReadoutQuery::Exact(
-                asap_physical_operators::summary_kernels::exact::ExactReadout {
+            asap_physical_operators::operators::SummaryEvaluation::Exact(
+                asap_physical_operators::summary_kernels::exact::ExactEvaluation {
                     statistic: Statistic::Sum,
                     lookback_ms: None,
                 },
@@ -486,40 +494,49 @@ fn exact_state_and_family_validation() {
 fn bind_post_asap_before_execution() {
     use asap_physical_operators::dag::planner::bind;
     use planner_types::{
-        post_asap::{
-            EdgeRole, ExecutionDataState, GroupingEdgeCompatibility, PostAsapDAG, PostAsapDAGEdge,
-            PostAsapDAGNode, PostAsapNodeId, PostAsapOperatorPayload, ValueOperation,
-            WindowEdgeCompatibility,
-        },
-        pre_asap::{ArithmeticOpKind, ProjectItem, QueryExpr, ScalarValue},
+        post_asap::ExecutionDataState,
+        pre_asap::{ArithmeticOpKind, ScalarValue},
     };
-    use std::{collections::BTreeMap, rc::Rc};
+    use std::collections::BTreeMap;
     let schema = schema(&[("value", DataType::Float64, false)]);
-    let node = |id, payload| PostAsapDAGNode {
-        id: PostAsapNodeId(id),
+    let node = |id, payload| PhysicalASAPDAGNode {
+        coverage: None,
+        id: planner_types::ir::export::LogicalASAPNodeId(id),
         payload,
         output_state: ExecutionDataState::QUERY_ROWS,
         output_schema: (*schema).clone(),
         guarantee: None,
     };
-    let mut dag = PostAsapDAG {
+    let mut dag = PhysicalASAPDAG {
         nodes: vec![
             node(
                 0,
-                PostAsapOperatorPayload::Fallback {
-                    expression: QueryExpr::promql_scalar(1.),
+                PhysicalASAPOperatorPayload::Relational {
+                    operator: ValueOperation::Values {
+                        rows: vec![vec![planner_types::ir::export::WireScalarExpr::Literal(
+                            planner_types::pre_asap::ScalarValue::Float64(1.),
+                        )]],
+                        schema: (*schema).clone(),
+                    },
                 },
             ),
             node(
                 1,
-                PostAsapOperatorPayload::Value {
-                    operation: ValueOperation::Project {
-                        cols: vec![ProjectItem {
+                PhysicalASAPOperatorPayload::Relational {
+                    operator: ValueOperation::Project {
+                        cols: vec![planner_types::ir::export::WireProjectItem {
                             alias: None,
-                            expr: QueryExpr::Arithmetic {
+                            expr: planner_types::ir::export::WireScalarExpr::Arithmetic {
+                                semantics: planner_types::ir::ExprSemantics::Sql,
                                 op: ArithmeticOpKind::Add,
-                                left: Rc::new(QueryExpr::Column(0)),
-                                right: Rc::new(QueryExpr::Literal(ScalarValue::Float64(2.))),
+                                left: Box::new(planner_types::ir::export::WireScalarExpr::Column(
+                                    0,
+                                )),
+                                right: Box::new(
+                                    planner_types::ir::export::WireScalarExpr::Literal(
+                                        ScalarValue::Float64(2.),
+                                    ),
+                                ),
                             },
                         }],
                         qualifier: None,
@@ -527,16 +544,16 @@ fn bind_post_asap_before_execution() {
                 },
             ),
         ],
-        edges: vec![PostAsapDAGEdge {
-            producer: PostAsapNodeId(0),
-            consumer: PostAsapNodeId(1),
+        edges: vec![PhysicalASAPDAGEdge {
+            producer: planner_types::ir::export::LogicalASAPNodeId(0),
+            consumer: planner_types::ir::export::LogicalASAPNodeId(1),
             role: EdgeRole::Input,
             intermediate_schema: (*schema).clone(),
             data_state: ExecutionDataState::QUERY_ROWS,
             grouping: GroupingEdgeCompatibility::NotApplicable,
             window: WindowEdgeCompatibility::NotApplicable,
         }],
-        root: PostAsapNodeId(1),
+        roots: vec![planner_types::ir::export::LogicalASAPNodeId(1)],
     };
     let sources = || -> BTreeMap<u64, asap_physical_operators::dag::planner::Source<'static>> {
         BTreeMap::from([(
@@ -555,17 +572,15 @@ fn bind_post_asap_before_execution() {
     // A literal Fallback needs no deployment input.
     let literal = bind(&dag, BTreeMap::new(), &[1]).unwrap();
     assert_eq!(floats(&run(&literal, 1, query()), 0), vec![3.]);
-    dag.nodes[1].payload = PostAsapOperatorPayload::Value {
-        operation: ValueOperation::Extension {
-            name: "unknown".into(),
-        },
+    dag.nodes[1].payload = PhysicalASAPOperatorPayload::Extension {
+        name: "unsupported".into(),
     };
     assert!(bind(&dag, sources(), &[1]).is_err());
 }
 
 // A completed empty population has an exact zero count, with integer output.
 #[test]
-fn empty_exact_count_is_an_integer_state_readout() {
+fn empty_exact_count_is_an_integer_state_evaluation() {
     let input = schema(&[("value", DataType::Float64, false)]);
     let build = Operator::summary_build(
         input.clone(),
@@ -575,11 +590,11 @@ fn empty_exact_count_is_an_integer_state_readout() {
         vec![],
     )
     .unwrap();
-    let read = Operator::readout(
+    let read = Operator::evaluation(
         build.schema(),
         0,
-        asap_physical_operators::operators::ReadoutQuery::Exact(
-            asap_physical_operators::summary_kernels::exact::ExactReadout {
+        asap_physical_operators::operators::SummaryEvaluation::Exact(
+            asap_physical_operators::summary_kernels::exact::ExactEvaluation {
                 statistic: Statistic::Count,
                 lookback_ms: None,
             },
@@ -598,13 +613,7 @@ fn empty_exact_count_is_an_integer_state_readout() {
 #[test]
 fn source_batches_must_match_the_bound_schema() {
     use asap_physical_operators::dag::{self, PhysicalOperator};
-    use planner_types::{
-        post_asap::{
-            ExecutionDataState, PostAsapDAG, PostAsapDAGNode, PostAsapNodeId,
-            PostAsapOperatorPayload,
-        },
-        pre_asap::QueryExpr,
-    };
+    use planner_types::post_asap::ExecutionDataState;
     use std::{cell::Cell, collections::BTreeMap, rc::Rc};
     struct WrongSource {
         schema: SchemaRef,
@@ -637,18 +646,24 @@ fn source_batches_must_match_the_bound_schema() {
     }
     let expected = schema(&[("value", DataType::Float64, false)]);
     let starts = Rc::new(Cell::new(0));
-    let plan = PostAsapDAG {
-        nodes: vec![PostAsapDAGNode {
-            id: PostAsapNodeId(0),
-            payload: PostAsapOperatorPayload::Fallback {
-                expression: QueryExpr::promql_scalar(1.),
+    let plan = PhysicalASAPDAG {
+        nodes: vec![PhysicalASAPDAGNode {
+            coverage: None,
+            id: planner_types::ir::export::LogicalASAPNodeId(0),
+            payload: PhysicalASAPOperatorPayload::Relational {
+                operator: ValueOperation::Values {
+                    rows: vec![vec![planner_types::ir::export::WireScalarExpr::Literal(
+                        planner_types::pre_asap::ScalarValue::Float64(1.),
+                    )]],
+                    schema: (*expected).clone(),
+                },
             },
             output_state: ExecutionDataState::QUERY_ROWS,
             output_schema: (*expected).clone(),
             guarantee: None,
         }],
         edges: vec![],
-        root: PostAsapNodeId(0),
+        roots: vec![planner_types::ir::export::LogicalASAPNodeId(0)],
     };
     let source = Box::new(WrongSource {
         schema: expected,
@@ -709,26 +724,28 @@ fn planner_semijoin_sort_limit_contract_at_both_phases() {
     use asap_physical_operators::dag::planner::{bind, Source};
     use planner_types::{
         post_asap::*,
-        pre_asap::{CompareOpKind, GroupKeys, JoinKind, Predicate, QueryExpr, SortKey},
+        pre_asap::{CompareOpKind, GroupKeys, JoinKind},
     };
-    use std::{collections::BTreeMap, rc::Rc};
+    use std::collections::BTreeMap;
     let rows_schema = schema(&[
         ("group", DataType::Utf8, false),
         ("key", DataType::Utf8, false),
         ("score", DataType::Float64, false),
     ]);
     let keys_schema = schema(&[("key", DataType::Utf8, false)]);
-    let node = |id, payload, schema: &asap_physical_operators::values::SchemaRef| PostAsapDAGNode {
-        id: PostAsapNodeId(id),
-        payload,
-        output_schema: (**schema).clone(),
-        output_state: ExecutionDataState::QUERY_ROWS,
-        guarantee: None,
-    };
+    let node =
+        |id, payload, schema: &asap_physical_operators::values::SchemaRef| PhysicalASAPDAGNode {
+            coverage: None,
+            id: planner_types::ir::export::LogicalASAPNodeId(id),
+            payload,
+            output_schema: (**schema).clone(),
+            output_state: ExecutionDataState::QUERY_ROWS,
+            guarantee: None,
+        };
     let edge = |producer, consumer, role, schema: &asap_physical_operators::values::SchemaRef| {
-        PostAsapDAGEdge {
-            producer: PostAsapNodeId(producer),
-            consumer: PostAsapNodeId(consumer),
+        PhysicalASAPDAGEdge {
+            producer: planner_types::ir::export::LogicalASAPNodeId(producer),
+            consumer: planner_types::ir::export::LogicalASAPNodeId(consumer),
             role,
             intermediate_schema: (**schema).clone(),
             data_state: ExecutionDataState::QUERY_ROWS,
@@ -737,41 +754,59 @@ fn planner_semijoin_sort_limit_contract_at_both_phases() {
         }
     };
     let groups = GroupKeys::by(vec![0]);
-    let dag = PostAsapDAG {
+    let dag = PhysicalASAPDAG {
         nodes: vec![
             node(
                 0,
-                PostAsapOperatorPayload::Fallback {
-                    expression: QueryExpr::promql_scalar(0.),
+                PhysicalASAPOperatorPayload::Relational {
+                    operator: ValueOperation::Values {
+                        rows: vec![vec![planner_types::ir::export::WireScalarExpr::Literal(
+                            planner_types::pre_asap::ScalarValue::Float64(0.),
+                        )]],
+                        schema: (*rows_schema).clone(),
+                    },
                 },
                 &rows_schema,
             ),
             node(
                 1,
-                PostAsapOperatorPayload::Fallback {
-                    expression: QueryExpr::promql_scalar(0.),
+                PhysicalASAPOperatorPayload::Relational {
+                    operator: ValueOperation::Values {
+                        rows: vec![vec![planner_types::ir::export::WireScalarExpr::Literal(
+                            planner_types::pre_asap::ScalarValue::Float64(0.),
+                        )]],
+                        schema: (*keys_schema).clone(),
+                    },
                 },
                 &keys_schema,
             ),
             node(
                 2,
-                PostAsapOperatorPayload::RelationalJoin {
-                    join_kind: JoinKind::Semi,
-                    pruning: None,
-                    pred: Predicate(Rc::new(QueryExpr::Compare {
-                        left: Rc::new(QueryExpr::Column(1)),
-                        op: CompareOpKind::Eq,
-                        right: Rc::new(QueryExpr::Column(3)),
-                    })),
+                PhysicalASAPOperatorPayload::Relational {
+                    operator: planner_types::ir::export::NonASAPOpKind::Join {
+                        join_kind: JoinKind::Semi,
+                        pred: planner_types::ir::export::WirePredicate(
+                            planner_types::ir::export::WireScalarExpr::Compare {
+                                left: Box::new(planner_types::ir::export::WireScalarExpr::Column(
+                                    1,
+                                )),
+                                op: CompareOpKind::Eq,
+                                right: Box::new(planner_types::ir::export::WireScalarExpr::Column(
+                                    3,
+                                )),
+                                semantics: planner_types::ir::ExprSemantics::Sql,
+                            },
+                        ),
+                    },
                 },
                 &rows_schema,
             ),
             node(
                 3,
-                PostAsapOperatorPayload::Value {
-                    operation: ValueOperation::Sort {
-                        keys: vec![SortKey {
-                            expr: QueryExpr::Column(2),
+                PhysicalASAPOperatorPayload::Relational {
+                    operator: ValueOperation::Sort {
+                        keys: vec![planner_types::ir::export::WireSortKey {
+                            expr: planner_types::ir::export::WireScalarExpr::Column(2),
                             ascending: false,
                             nulls_first: false,
                         }],
@@ -782,9 +817,9 @@ fn planner_semijoin_sort_limit_contract_at_both_phases() {
             ),
             node(
                 4,
-                PostAsapOperatorPayload::Value {
-                    operation: ValueOperation::Limit {
-                        n: 1,
+                PhysicalASAPOperatorPayload::Relational {
+                    operator: ValueOperation::Limit {
+                        n: Some(1),
                         offset: 0,
                         partition_by: groups,
                     },
@@ -799,7 +834,7 @@ fn planner_semijoin_sort_limit_contract_at_both_phases() {
             edge(2, 3, EdgeRole::Input, &rows_schema),
             edge(3, 4, EdgeRole::Input, &rows_schema),
         ],
-        root: PostAsapNodeId(4),
+        roots: vec![planner_types::ir::export::LogicalASAPNodeId(4)],
     };
     let text = |v: &str| Value::Utf8(v.into());
     for (phase, scope) in [
@@ -862,8 +897,8 @@ fn planner_semijoin_sort_limit_contract_at_both_phases() {
 #[test]
 fn planner_expressions_preserve_collection_and_nullable_types() {
     use asap_physical_operators::dag::expressions::CompiledExpression;
-    use planner_types::pre_asap::{CompareOpKind, QueryExpr, ScalarValue};
-    use std::rc::Rc;
+    use planner_types::pre_asap::{CompareOpKind, ScalarValue};
+
     let input_schema = schema(&[(
         "items",
         DataType::Map {
@@ -911,9 +946,10 @@ fn planner_expressions_preserve_collection_and_nullable_types() {
     let projected = project.schema();
     dag.add(1, vec![0], project).unwrap();
     let predicate = QueryExpr::Compare {
-        left: Rc::new(QueryExpr::Column(0)),
+        semantics: planner_types::ir::ExprSemantics::Sql,
+        left: Box::new(QueryExpr::Column(0)),
         op: CompareOpKind::Ge,
-        right: Rc::new(QueryExpr::Literal(ScalarValue::Int64(1))),
+        right: Box::new(QueryExpr::Literal(ScalarValue::Int64(1))),
     };
     dag.add(
         2,
@@ -937,14 +973,16 @@ fn planner_expressions_preserve_collection_and_nullable_types() {
 // Outer, semi and anti joins share Planner predicates and preserve SQL null behavior.
 #[test]
 fn native_relational_join_kinds_preserve_unmatched_rows() {
-    use planner_types::pre_asap::{CompareOpKind, JoinKind, Predicate, QueryExpr};
-    use std::rc::Rc;
+    use planner_types::ir::Predicate;
+    use planner_types::pre_asap::{CompareOpKind, JoinKind};
+
     let input = schema(&[("key", DataType::Int64, true)]);
-    let predicate = Predicate(Rc::new(QueryExpr::Compare {
-        left: Rc::new(QueryExpr::Column(0)),
+    let predicate = Predicate(QueryExpr::Compare {
+        semantics: planner_types::ir::ExprSemantics::Sql,
+        left: Box::new(QueryExpr::Column(0)),
         op: CompareOpKind::Eq,
-        right: Rc::new(QueryExpr::Column(1)),
-    }));
+        right: Box::new(QueryExpr::Column(1)),
+    });
     for (kind, count) in [
         (JoinKind::Inner, 1),
         (JoinKind::Left, 3),
@@ -1018,6 +1056,7 @@ fn weighted_rate_topk_preserves_partitions_fractional_scores_and_evaluation_scop
 }
 fn assert_weighted_rate_topk(count_sketch: bool) {
     use planner_types::post_asap::{SketchAlgorithm, SketchKind, SketchParams};
+
     let raw = schema(&[
         ("service", DataType::Utf8, false),
         ("job", DataType::Utf8, false),
@@ -1084,7 +1123,7 @@ fn assert_weighted_rate_topk(count_sketch: bool) {
         ("service", DataType::Utf8, false),
         ("score", DataType::Float64, false),
     ]);
-    let readout = Operator::keyed_readout(build.schema(), 1, 8, output.clone()).unwrap();
+    let evaluation = Operator::keyed_evaluation(build.schema(), 1, 8, output.clone()).unwrap();
     let mut dag = PhysicalDAG::default();
     dag.add(
         0,
@@ -1094,7 +1133,7 @@ fn assert_weighted_rate_topk(count_sketch: bool) {
     .unwrap();
     dag.add(1, vec![0], rates).unwrap();
     dag.add(2, vec![1], build).unwrap();
-    dag.add(3, vec![2], readout).unwrap();
+    dag.add(3, vec![2], evaluation).unwrap();
     dag.add(
         4,
         vec![3],
@@ -1141,17 +1180,16 @@ fn grouped_temporal_schema_compiles_and_executes_topk() {
     use asap_physical_operators::physical_planner::{
         compile_node, CompiledPhysicalDAG, InputContract, Source,
     };
-    use planner_types::post_asap::{
-        ExecutionDataState, PostAsapDAGNode, PostAsapNodeId, PostAsapOperatorPayload,
-        ValueOperation,
-    };
+    use planner_types::ir::export::{PhysicalASAPDAGNode, PhysicalASAPOperatorPayload};
+    use planner_types::post_asap::ExecutionDataState;
+
     use planner_types::pre_asap::{
-        aggregate_output_schema, AggIntent, Field, GroupKeys, QueryExpr, Reduction as IrReduction,
-        Schema as IrSchema,
+        aggregate_output_schema, AggIntent, GroupKeys, Reduction as IrReduction, Schema as IrSchema,
     };
+
     let grouped = IrSchema::new(vec![
-        Field::plain("job", DataType::Utf8, false),
-        Field::plain("sum", DataType::Float64, false),
+        planner_types::pre_asap::Field::plain("job", DataType::Utf8, false),
+        planner_types::pre_asap::Field::plain("sum", DataType::Float64, false),
     ]);
     let output = aggregate_output_schema(
         &grouped,
@@ -1167,15 +1205,18 @@ fn grouped_temporal_schema_compiles_and_executes_topk() {
             .map(|c| {
                 (
                     c.name.as_str(),
-                    c.dtype.plain().unwrap().clone(),
+                    c.plain_dtype().unwrap().clone(),
                     c.nullable,
                 )
             })
             .collect::<Vec<_>>(),
     );
-    let node = |id, operation| PostAsapDAGNode {
-        id: PostAsapNodeId(id),
-        payload: PostAsapOperatorPayload::Value { operation },
+    let node = |id, operation| PhysicalASAPDAGNode {
+        coverage: None,
+        id: planner_types::ir::export::LogicalASAPNodeId(id),
+        payload: PhysicalASAPOperatorPayload::Relational {
+            operator: operation,
+        },
         output_state: ExecutionDataState::QUERY_ROWS,
         output_schema: (*input).clone(),
         guarantee: None,
@@ -1184,8 +1225,8 @@ fn grouped_temporal_schema_compiles_and_executes_topk() {
         &node(
             1,
             ValueOperation::Sort {
-                keys: vec![planner_types::pre_asap::SortKey {
-                    expr: QueryExpr::Column(1),
+                keys: vec![planner_types::ir::export::WireSortKey {
+                    expr: planner_types::ir::export::WireScalarExpr::Column(1),
                     ascending: false,
                     nulls_first: false,
                 }],
@@ -1199,7 +1240,7 @@ fn grouped_temporal_schema_compiles_and_executes_topk() {
         &node(
             2,
             ValueOperation::Limit {
-                n: 1,
+                n: Some(1),
                 offset: 0,
                 partition_by: GroupKeys::none(),
             },
@@ -1253,31 +1294,29 @@ fn certified_pruning_rejects_missing_authoritative_values_after_recovery() {
     };
     use planner_types::{
         post_asap::*,
-        pre_asap::{CompareOpKind, JoinKind, Predicate, QueryExpr},
+        pre_asap::{CompareOpKind, JoinKind},
     };
-    use std::{collections::BTreeMap, rc::Rc};
+    use std::collections::BTreeMap;
     let schema = schema(&[("key", DataType::Utf8, false)]);
     for certified in [false, true] {
-        let node = PostAsapDAGNode {
-            id: PostAsapNodeId(2),
+        let node = PhysicalASAPDAGNode {
+            coverage: None,
+            id: planner_types::ir::export::LogicalASAPNodeId(2),
             output_schema: (*schema).clone(),
             output_state: ExecutionDataState::QUERY_ROWS,
             guarantee: None,
-            payload: PostAsapOperatorPayload::RelationalJoin {
-                join_kind: JoinKind::Semi,
-                pred: Predicate(Rc::new(QueryExpr::Compare {
-                    left: Rc::new(QueryExpr::Column(0)),
-                    op: CompareOpKind::Eq,
-                    right: Rc::new(QueryExpr::Column(1)),
-                })),
-                pruning: certified.then_some(CandidateCompleteness::Certified {
-                    guarantee: ResultGuarantee {
-                        metric: ErrorMetric::TopKMembership,
-                        bound: BoundExpr::Zero,
-                        failure_probability: ProbabilityExpr::Constant { value: 0.01 },
-                        provenance: vec![],
-                    },
-                }),
+            payload: PhysicalASAPOperatorPayload::Relational {
+                operator: planner_types::ir::export::NonASAPOpKind::Join {
+                    join_kind: JoinKind::Semi,
+                    pred: planner_types::ir::export::WirePredicate(
+                        planner_types::ir::export::WireScalarExpr::Compare {
+                            semantics: planner_types::ir::ExprSemantics::Sql,
+                            left: Box::new(planner_types::ir::export::WireScalarExpr::Column(0)),
+                            op: CompareOpKind::Eq,
+                            right: Box::new(planner_types::ir::export::WireScalarExpr::Column(1)),
+                        },
+                    ),
+                },
             },
         };
         let dag = CompiledPhysicalDAG::from_operators(
@@ -1290,7 +1329,12 @@ fn certified_pruning_rejects_missing_authoritative_values_after_recovery() {
                 2,
                 (
                     vec![0, 1],
-                    compile_node(&node, &[schema.clone(), schema.clone()]).unwrap(),
+                    if certified {
+                        Operator::certified_semi_join(schema.clone(), schema.clone(), vec![(0, 0)])
+                            .unwrap()
+                    } else {
+                        compile_node(&node, &[schema.clone(), schema.clone()]).unwrap()
+                    },
                 ),
             )]
             .into(),
@@ -1373,17 +1417,21 @@ fn compiled_ingestion_binary_preserves_alignment_and_rejects_missing_updates() {
         ("time", DataType::Timestamp, false),
         ("value", DataType::Float64, false),
     ]);
-    let node = PostAsapDAGNode {
-        id: PostAsapNodeId(2),
+    let node = PhysicalASAPDAGNode {
+        coverage: None,
+        id: planner_types::ir::export::LogicalASAPNodeId(2),
         output_schema: (*input).clone(),
         output_state: ExecutionDataState::INGESTION_ROWS,
         guarantee: None,
-        payload: PostAsapOperatorPayload::Binary {
-            operator: BinaryOperator {
-                kind: BinaryOpKind::Arithmetic(ArithmeticOpKind::Sub),
-                vector_match: None,
-                checked_relative_division: false,
-                checked_finite_division: false,
+        payload: PhysicalASAPOperatorPayload::Relational {
+            operator: planner_types::ir::export::NonASAPOpKind::BinaryOp {
+                operator: BinaryOperator {
+                    kind: BinaryOpKind::Arithmetic(ArithmeticOpKind::Sub),
+                    vector_match: None,
+                    checked_relative_division: false,
+                    checked_finite_division: false,
+                },
+                return_bool: false,
             },
         },
     };
diff --git a/crates/asap-physical-operators/tests/physical_plan_recovery.rs b/crates/asap-physical-operators/tests/physical_plan_recovery.rs
index fda1b502a..e755090e6 100644
--- a/crates/asap-physical-operators/tests/physical_plan_recovery.rs
+++ b/crates/asap-physical-operators/tests/physical_plan_recovery.rs
@@ -5,15 +5,15 @@ use asap_physical_operators::{
     physical_planner::{CompiledPhysicalDAG, InputContract},
 };
 use planner_types::{
-    post_asap::{Field, FieldDataType, Schema},
+    post_asap::{Field, FieldDataType},
     pre_asap::DataType,
 };
 use std::{collections::BTreeMap, sync::Arc};
 
 fn sorted() -> CompiledPhysicalDAG {
-    let schema = Arc::new(Schema {
-        closed: true,
+    let schema = Arc::new(planner_types::pre_asap::Schema {
         unique_keys: vec![],
+        closed: false,
         fields: vec![Field {
             table: None,
             name: "value".into(),
@@ -74,7 +74,7 @@ fn recovery_retains_selected_operator_and_rejects_invalid_contracts() {
 
 #[test]
 fn candidate_recovery_preserves_materialization_boundary() {
-    use asap_physical_operators::physical_planner::PhysicalASAPDAG;
+    use asap_physical_operators::physical_planner::CompiledPhysicalPlan;
     let precompute = sorted();
     let output = InputContract::bounded(precompute.output_contract(1).unwrap().schema);
     let query = CompiledPhysicalDAG::from_operators(
@@ -89,13 +89,13 @@ fn candidate_recovery_preserves_materialization_boundary() {
         vec![2],
     )
     .unwrap();
-    let candidate = PhysicalASAPDAG {
+    let candidate = CompiledPhysicalPlan {
         precompute: Some(precompute),
         query,
         materialized_outputs: BTreeMap::from([(1, output)]),
     };
     let bytes = serde_json::to_vec(&candidate).unwrap();
-    let restored = serde_json::from_slice::<PhysicalASAPDAG>(&bytes).unwrap();
+    let restored = serde_json::from_slice::<CompiledPhysicalPlan>(&bytes).unwrap();
     assert_eq!(restored.precompute.as_ref().unwrap().roots(), &[1]);
     assert_eq!(restored.query.roots(), &[2]);
     assert_eq!(serde_json::to_vec(&restored).unwrap(), bytes);
@@ -103,6 +103,7 @@ fn candidate_recovery_preserves_materialization_boundary() {
     wire["materialized_outputs"]["1"]["schema"]["fields"][0]["dtype"] =
         serde_json::json!({"Plain":"utf8"});
     assert!(
-        serde_json::from_slice::<PhysicalASAPDAG>(&serde_json::to_vec(&wire).unwrap()).is_err()
+        serde_json::from_slice::<CompiledPhysicalPlan>(&serde_json::to_vec(&wire).unwrap())
+            .is_err()
     );
 }
diff --git a/crates/asap-physical-operators/tests/physical_semantics.rs b/crates/asap-physical-operators/tests/physical_semantics.rs
index 56b62590b..b35d10a9f 100644
--- a/crates/asap-physical-operators/tests/physical_semantics.rs
+++ b/crates/asap-physical-operators/tests/physical_semantics.rs
@@ -9,16 +9,20 @@ use asap_physical_operators::{
     values::{Batch, SchemaRef, Value},
 };
 use futures::{executor::block_on, StreamExt};
+use planner_types::ir::export::NonASAPOpKind as ValueOperation;
+use planner_types::ir::export::{PhysicalASAPDAGNode, PhysicalASAPOperatorPayload};
+use planner_types::ir::Predicate;
+use planner_types::ir::ScalarExpr as QueryExpr;
 use planner_types::{
-    post_asap::{Field, FieldDataType, Schema},
-    pre_asap::{CompareOpKind, DataType, JoinKind, Predicate, QueryExpr},
+    post_asap::{Field, FieldDataType},
+    pre_asap::{CompareOpKind, DataType, JoinKind},
 };
-use std::{rc::Rc, sync::Arc};
+use std::sync::Arc;
 
 fn schema(fields: &[(&str, DataType, bool)]) -> SchemaRef {
-    Arc::new(Schema {
-        closed: true,
+    Arc::new(planner_types::pre_asap::Schema {
         unique_keys: vec![],
+        closed: false,
         fields: fields
             .iter()
             .map(|(name, dtype, nullable)| Field {
@@ -74,11 +78,12 @@ fn keys(rows: &[Vec<Value>]) -> Vec<Vec<Vec<u8>>> {
         .collect()
 }
 fn eq_predicate() -> Predicate {
-    Predicate(Rc::new(QueryExpr::Compare {
-        left: Rc::new(QueryExpr::Column(0)),
+    Predicate(QueryExpr::Compare {
+        semantics: planner_types::ir::ExprSemantics::Sql,
+        left: Box::new(QueryExpr::Column(0)),
         op: CompareOpKind::Eq,
-        right: Rc::new(QueryExpr::Column(1)),
-    }))
+        right: Box::new(QueryExpr::Column(1)),
+    })
 }
 fn join(left: Vec<Value>, right: Vec<Value>, kind: JoinKind, keyed: bool) -> Vec<Vec<Value>> {
     let input = schema(&[("key", DataType::Float64, true)]);
@@ -345,7 +350,7 @@ fn global_extrema_bind_with_planner_derived_schema() {
     use asap_physical_operators::physical_planner::compile_node;
     use planner_types::{
         post_asap::*,
-        pre_asap::{AggIntent, Field, GroupKeys, Reduction as PlanReduction},
+        pre_asap::{AggIntent, GroupKeys, Reduction as PlanReduction},
     };
     let input = schema(&[("v", DataType::Int64, false)]);
     for measure in [
@@ -353,8 +358,12 @@ fn global_extrema_bind_with_planner_derived_schema() {
         AggIntent::Max { col: Some(0) },
     ] {
         let planner_input =
-            planner_types::pre_asap::Schema::new(vec![Field::plain("v", DataType::Int64, false)]);
-        let derived = planner_types::pre_asap::query_expr::aggregate_output_schema(
+            planner_types::pre_asap::Schema::new(vec![planner_types::pre_asap::Field::plain(
+                "v",
+                DataType::Int64,
+                false,
+            )]);
+        let derived = planner_types::pre_asap::aggregate_output_schema(
             &planner_input,
             &PlanReduction::Reduce(GroupKeys::by(vec![])),
             std::slice::from_ref(&measure),
@@ -364,19 +373,20 @@ fn global_extrema_bind_with_planner_derived_schema() {
         let result = derived.fields[0].clone();
         let output = schema(&[(
             &result.name,
-            result.dtype.plain().unwrap().clone(),
+            result.plain_dtype().unwrap().clone(),
             result.nullable,
         )]);
-        let node = PostAsapDAGNode {
-            id: PostAsapNodeId(1),
-            payload: PostAsapOperatorPayload::Value {
-                operation: ValueOperation::Exact(ExactOperation::Aggregate {
+        let node = PhysicalASAPDAGNode {
+            coverage: None,
+            id: planner_types::ir::export::LogicalASAPNodeId(1),
+            payload: PhysicalASAPOperatorPayload::Relational {
+                operator: ValueOperation::Aggregate {
                     reduction: PlanReduction::Reduce(GroupKeys::by(vec![])),
                     measures: vec![measure],
                     output_names: vec![result.name],
                     filters: vec![],
                     having: None,
-                }),
+                },
             },
             output_state: ExecutionDataState::QUERY_ROWS,
             output_schema: (*output).clone(),
@@ -408,9 +418,10 @@ fn planner_comparisons_handle_nan_without_execution_errors() {
         CompareOpKind::Ge,
     ] {
         let expression = QueryExpr::Compare {
-            left: Rc::new(QueryExpr::Column(0)),
+            semantics: planner_types::ir::ExprSemantics::Sql,
+            left: Box::new(QueryExpr::Column(0)),
             op: op.clone(),
-            right: Rc::new(QueryExpr::Column(1)),
+            right: Box::new(QueryExpr::Column(1)),
         };
         let compiled = CompiledExpression::compile(&expression, &input).unwrap();
         for row in [
@@ -475,9 +486,10 @@ fn mixed_numeric_comparisons_preserve_large_integer_precision() {
         ("b", DataType::Float64, false),
     ]);
     let expr = QueryExpr::Compare {
-        left: Rc::new(QueryExpr::Column(0)),
+        semantics: planner_types::ir::ExprSemantics::Sql,
+        left: Box::new(QueryExpr::Column(0)),
         op: CompareOpKind::Gt,
-        right: Rc::new(QueryExpr::Column(1)),
+        right: Box::new(QueryExpr::Column(1)),
     };
     let compiled = CompiledExpression::compile(&expr, &input).unwrap();
     for (a, b, expected) in [
@@ -543,8 +555,9 @@ fn boolean_truth_tables_agree_between_expression_paths() {
 
 // Partial/final execution must agree with one build for an uncompacted KLL population.
 #[test]
-fn kll_partial_merge_and_multiple_readouts_preserve_population() {
+fn kll_partial_merge_and_multiple_evaluations_preserve_population() {
     use planner_types::post_asap::{SketchAlgorithm, SketchKind, SketchParams};
+
     let input = schema(&[("v", DataType::Float64, false)]);
     let family = FieldDataType::Sketch(
         SketchKind::new(SketchAlgorithm::Kll, SketchParams::Kll { k: 512 }),
@@ -588,10 +601,10 @@ fn kll_partial_merge_and_multiple_readouts_preserve_population() {
             dag.add(
                 id,
                 vec![build],
-                Operator::readout(
+                Operator::evaluation(
                     state.clone(),
                     0,
-                    asap_physical_operators::operators::ReadoutQuery::Sketch(
+                    asap_physical_operators::operators::SummaryEvaluation::Sketch(
                         planner_types::post_asap::SketchStatistic::Quantile { q },
                     ),
                 )
@@ -662,6 +675,7 @@ fn zero_column_output_obeys_memory_limit() {
 fn empty_exact_summary_extrema_agree_with_ordinary_aggregation() {
     use asap_physical_operators::Statistic;
     use planner_types::post_asap::{ExactKind, ExactParams};
+
     let input = schema(&[("v", DataType::Float64, false)]);
     for (kind, params, statistic) in [
         (ExactKind::Min, ExactParams::Min, Statistic::Min),
@@ -683,11 +697,11 @@ fn empty_exact_summary_extrema_agree_with_ordinary_aggregation() {
         dag.add(
             2,
             vec![1],
-            Operator::readout(
+            Operator::evaluation(
                 state,
                 0,
-                asap_physical_operators::operators::ReadoutQuery::Exact(
-                    asap_physical_operators::summary_kernels::exact::ExactReadout {
+                asap_physical_operators::operators::SummaryEvaluation::Exact(
+                    asap_physical_operators::summary_kernels::exact::ExactEvaluation {
                         statistic,
                         lookback_ms: None,
                     },
diff --git a/crates/asap-physical-operators/tests/plan_properties.rs b/crates/asap-physical-operators/tests/plan_properties.rs
index e3dd7b5fc..ab488162d 100644
--- a/crates/asap-physical-operators/tests/plan_properties.rs
+++ b/crates/asap-physical-operators/tests/plan_properties.rs
@@ -8,8 +8,8 @@ use asap_physical_operators::{
     Error,
 };
 use planner_types::{
-    post_asap::{Field, FieldDataType, Schema},
-    pre_asap::{DataType, QueryExpr, Source},
+    post_asap::{Field, FieldDataType},
+    pre_asap::{DataType, Schema, Source},
 };
 use std::sync::{
     atomic::{AtomicUsize, Ordering},
@@ -35,9 +35,9 @@ impl RawSource for DeclaredSource {
 // A blocking parent must reject unknown and unbounded Scan inputs without opening a reader.
 #[test]
 fn blocking_inputs_require_an_explicit_finite_source() {
-    let schema = Arc::new(Schema {
-        closed: true,
+    let schema = Arc::new(planner_types::pre_asap::Schema {
         unique_keys: vec![],
+        closed: false,
         fields: vec![Field {
             table: None,
             name: "v".into(),
@@ -67,11 +67,20 @@ fn blocking_inputs_require_an_explicit_finite_source() {
             )
             .unwrap();
         let scan = registry
-            .bind(&QueryExpr::Scan {
-                source: identity,
-                schema: Schema::new(vec![Field::plain("v", DataType::Int64, false)]),
-                predicates: vec![],
-            })
+            .bind(
+                &planner_types::ir::OperatorNode::new_shared(planner_types::ir::Operator::NonASAP(
+                    planner_types::ir::NonASAPOp::Scan {
+                        source: identity,
+                        schema: Schema::new(vec![planner_types::pre_asap::Field::plain(
+                            "v",
+                            DataType::Int64,
+                            false,
+                        )]),
+                        predicates: vec![],
+                    },
+                ))
+                .unwrap(),
+            )
             .unwrap();
         let mut dag = PhysicalDAG::default();
         dag.add(0, vec![], scan).unwrap();
@@ -112,11 +121,11 @@ fn blocking_inputs_require_an_explicit_finite_source() {
     }
 }
 
-// Kernel support must not be mistaken for executable native state/readout support.
+// Kernel support must not be mistaken for executable native state/evaluation support.
 #[test]
 fn summary_capability_levels_are_distinct() {
     use asap_physical_operators::{
-        capability::{validate_native_family, validate_sketch_readout, validate_summary_kernel},
+        capability::{validate_native_family, validate_sketch_evaluation, validate_summary_kernel},
         planner::post_asap::SketchStatistic,
     };
     use planner_types::{
@@ -148,8 +157,8 @@ fn summary_capability_levels_are_distinct() {
         key: ColumnRef::SampleValue,
         value: None,
     };
-    assert!(validate_sketch_readout(&cms, &bare_count).is_ok());
-    assert!(validate_sketch_readout(
+    assert!(validate_sketch_evaluation(&cms, &bare_count).is_ok());
+    assert!(validate_sketch_evaluation(
         &cms,
         &SketchStatistic::PointCount {
             key: ColumnRef::Named("host".into()),
@@ -162,7 +171,7 @@ fn summary_capability_levels_are_distinct() {
         grouping,
     );
     assert!(validate_native_family(&kll).is_ok());
-    assert!(validate_sketch_readout(&kll, &SketchStatistic::Quantile { q: 1.5 }).is_err());
-    assert!(validate_sketch_readout(&kll, &SketchStatistic::Cardinality).is_err());
-    assert!(validate_sketch_readout(&kll, &SketchStatistic::Quantile { q: 0.5 }).is_ok());
+    assert!(validate_sketch_evaluation(&kll, &SketchStatistic::Quantile { q: 1.5 }).is_err());
+    assert!(validate_sketch_evaluation(&kll, &SketchStatistic::Cardinality).is_err());
+    assert!(validate_sketch_evaluation(&kll, &SketchStatistic::Quantile { q: 0.5 }).is_ok());
 }
diff --git a/crates/asap-physical-operators/tests/planspace_series_identity_heap.rs b/crates/asap-physical-operators/tests/planspace_series_identity_heap.rs
index 1f03b61c4..228332cbc 100644
--- a/crates/asap-physical-operators/tests/planspace_series_identity_heap.rs
+++ b/crates/asap-physical-operators/tests/planspace_series_identity_heap.rs
@@ -2,6 +2,10 @@
 //! Planner's search space: `enumerate_candidate_dags_for_root` lists
 //! current-series TopK heaps without a caller-side series-identity pass, cost
 //! ranking, or workload Cartesian expansion. Placement variants are not listed.
+mod common;
+use common::compile_physical_asap_dag;
+use planner_types::ir::OperatorNode as QueryExpr;
+
 use asap_aware_mapping::{
     accuracy::{AccuracyEvidenceProvider, DefaultAccuracyModel, PropagationStats},
     cost_model::DefaultCostModel,
@@ -9,11 +13,10 @@ use asap_aware_mapping::{
     search_workload_with_targets, Proposals, ReplacementStrategy, ReplacementSubDAG, TargetSubDAG,
 };
 use asap_physical_operators::physical_planner::promql_rows::{
-    compile_current_series_readout, SERIES_IDENTITY_COLUMN,
+    compile_current_series_evaluation, SERIES_IDENTITY_COLUMN,
 };
 use planner_types::{
     post_asap::*,
-    pre_asap::QueryExpr,
     types::AccuracyTarget,
     workload::{
         AccuracyRequirement, BatchEntry, DataWorkload, DurationMs, Evidence as WorkloadEvidence,
@@ -89,14 +92,12 @@ fn lower(query: &str, accuracy: &AccuracyTarget) -> Rc<QueryExpr> {
             ..Default::default()
         }),
     };
-    Rc::new(
-        asap_frontend_promql::lower_promql_workload(&workload, 0)
-            .unwrap()
-            .remove(0),
-    )
+    asap_frontend_promql::lower_promql_workload(&workload, 0)
+        .unwrap()
+        .remove(0)
 }
 
-type InventoryDAG = Vec<(usize, Rc<SummaryNode>)>;
+type InventoryDAG = Vec<(usize, Rc<planner_types::ir::OperatorNode>)>;
 
 /// Candidate DAGs for query 1 of a two-query workload, with and without
 /// whole-root proposals. Query 0 is a bystander that must not multiply them.
@@ -126,7 +127,7 @@ fn inventories(query: &str, accuracy: AccuracyTarget) -> (Vec<InventoryDAG>, Vec
 
 fn carries_identity(dag: &InventoryDAG) -> bool {
     dag.iter().any(|(_, root)| {
-        compile_post_asap_dag(root)
+        compile_physical_asap_dag(root)
             .unwrap()
             .nodes
             .iter()
@@ -140,7 +141,10 @@ fn carries_identity(dag: &InventoryDAG) -> bool {
 }
 
 /// Shared acceptance checks; returns the added identity-carrying alternatives.
-fn added_alternatives(query: &str, accuracy: AccuracyTarget) -> Vec<Rc<SummaryNode>> {
+fn added_alternatives(
+    query: &str,
+    accuracy: AccuracyTarget,
+) -> Vec<Rc<planner_types::ir::OperatorNode>> {
     let (full, logical) = inventories(query, accuracy);
     for (index, dag) in full.iter().enumerate() {
         assert_eq!(dag.len(), 1, "one root per candidate, no workload product");
@@ -159,15 +163,18 @@ fn added_alternatives(query: &str, accuracy: AccuracyTarget) -> Vec<Rc<SummaryNo
 
 const CURRENT_SERIES_TOPK: &str = "topk by(job)(1, m)";
 
-// Instant-vector TopK lists finalized current-series heap readouts.
+// Instant-vector TopK lists finalized current-series heap evaluations.
 #[test]
-fn current_series_topk_lists_heap_readouts() {
+fn current_series_topk_lists_heap_evaluations() {
     let added = added_alternatives(CURRENT_SERIES_TOPK, AccuracyTarget::Epsilon(0.1));
     assert!(!added.is_empty());
     for root in added {
-        assert!(!matches!(root.expr, SummaryExpr::SummaryAgg { .. }));
+        assert!(!matches!(
+            root.operator,
+            planner_types::ir::Operator::ASAP(planner_types::ir::ASAPOp::SummaryAgg { .. })
+        ));
         assert!(
-            compile_current_series_readout(&root).is_ok(),
+            compile_current_series_evaluation(&root).is_ok(),
             "unbindable alternative {root:?}"
         );
     }
diff --git a/crates/asap-physical-operators/tests/precompute_candidates.rs b/crates/asap-physical-operators/tests/precompute_candidates.rs
index 955948460..d1ea3dbf1 100644
--- a/crates/asap-physical-operators/tests/precompute_candidates.rs
+++ b/crates/asap-physical-operators/tests/precompute_candidates.rs
@@ -1,19 +1,22 @@
 //! Materialized frontiers are compiled by Planner, never rewritten by deployment.
+mod common;
 use asap_aware_mapping::{cost_model::DefaultCostModel, search_workload};
 use asap_physical_operators::{
     factory::create_planner_accumulator,
     operators::Operator,
     physical_planner::{
         compile, compile_candidate, compile_candidates, cut_candidate, enumerate_frontiers,
-        select_candidate, CandidateCost, CompiledPhysicalDAG, InputContract, PhysicalASAPDAG,
+        select_candidate, CandidateCost, CompiledPhysicalDAG, CompiledPhysicalPlan, InputContract,
         Source,
     },
     runtime::{Limits, RunContext, Scope},
     values::{Batch, Value},
 };
+use common::compile_physical_asap_dag;
 use futures::{executor::block_on, StreamExt};
+use planner_types::ir::export::{PhysicalASAPDAG, PhysicalASAPOperatorPayload};
 use planner_types::{post_asap::*, pre_asap::DataType, types::AccuracyTarget, workload::*};
-use std::{collections::BTreeMap, rc::Rc, sync::Arc};
+use std::{collections::BTreeMap, sync::Arc};
 
 fn grouped_rate_space() -> asap_aware_mapping::CandidateLogicalASAPDAGs<&'static str> {
     let workload = PlanningWorkload {
@@ -40,26 +43,22 @@ fn grouped_rate_space() -> asap_aware_mapping::CandidateLogicalASAPDAGs<&'static
             ..Default::default()
         }),
     };
-    let root = Rc::new(
-        asap_frontend_promql::lower_promql_workload(&workload, 0)
-            .unwrap()
-            .remove(0),
-    );
-    let root = Rc::new(
-        asap_physical_operators::physical_planner::promql_rows::with_series_identity(&root)
-            .unwrap(),
-    );
+    let root = asap_frontend_promql::lower_promql_workload(&workload, 0)
+        .unwrap()
+        .remove(0);
+    let root = asap_physical_operators::physical_planner::promql_rows::with_series_identity(&root)
+        .unwrap();
     search_workload(vec![("grouped-rate", root)])
 }
 
-fn grouped_rate() -> PostAsapDAG {
+fn grouped_rate() -> PhysicalASAPDAG {
     let space = grouped_rate_space();
     let selected = space
         .global_selection(&DefaultCostModel)
         .assemble_selected_query(&space.roots[0].1)
         .unwrap()
         .unwrap();
-    compile_post_asap_dag(&selected).unwrap()
+    compile_physical_asap_dag(&selected).unwrap()
 }
 fn run(plan: &CompiledPhysicalDAG, inputs: BTreeMap<u64, Batch>, scope: Scope) -> Vec<Batch> {
     let sources = inputs
@@ -81,7 +80,7 @@ fn run(plan: &CompiledPhysicalDAG, inputs: BTreeMap<u64, Batch>, scope: Scope) -
     })
 }
 
-/// Rate readouts and grouped Sum can run together during bounded precompute;
+/// Rate evaluations and grouped Sum can run together during bounded precompute;
 /// storing per-series rates instead leaves the same Sum in the query DAG.
 #[test]
 fn grouped_rate_can_be_materialized_before_or_after_grouped_sum() {
@@ -92,22 +91,20 @@ fn grouped_rate_can_be_materialized_before_or_after_grouped_sum() {
         .find(|node| {
             matches!(
                 node.payload,
-                PostAsapOperatorPayload::SummaryAgg {
+                PhysicalASAPOperatorPayload::SummaryAgg {
                     family: FieldDataType::ExactAggregate(ExactKind::Rate, _),
                     ..
                 }
             )
         })
         .unwrap();
-    let readout = dag
+    let evaluation = dag
         .nodes
         .iter()
         .find(|node| {
             matches!(
                 node.payload,
-                PostAsapOperatorPayload::Value {
-                    operation: ValueOperation::FinalizeExactAccumulator
-                }
+                PhysicalASAPOperatorPayload::FinalizeExactAccumulator
             ) && dag
                 .edges
                 .iter()
@@ -116,7 +113,7 @@ fn grouped_rate_can_be_materialized_before_or_after_grouped_sum() {
         .unwrap();
     let input_schema = Arc::new(state.output_schema.clone());
     let (family, update, grouping) = match &state.payload {
-        PostAsapOperatorPayload::SummaryAgg {
+        PhysicalASAPOperatorPayload::SummaryAgg {
             family,
             input,
             grouping,
@@ -139,7 +136,7 @@ fn grouped_rate_can_be_materialized_before_or_after_grouped_sum() {
                 .as_any()
                 .downcast_ref::<asap_physical_operators::summary_kernels::exact::ExactAccumulator>()
                 .unwrap()
-                .readout(asap_physical_operators::Statistic::Rate, range_ms, None)
+                .evaluation(asap_physical_operators::Statistic::Rate, range_ms, None)
                 .unwrap()
                 .unwrap();
             let summary = Value::Summary {
@@ -169,9 +166,9 @@ fn grouped_rate_can_be_materialized_before_or_after_grouped_sum() {
         })
         .collect();
     let batch = Batch::try_new(input_schema.clone(), rows).unwrap();
-    let root = u64::from(dag.root.0);
+    let root = u64::from(dag.roots[0].0);
     let state_id = u64::from(state.id.0);
-    let rate_id = u64::from(readout.id.0);
+    let rate_id = u64::from(evaluation.id.0);
     let frontiers = asap_physical_operators::physical_planner::enumerate_frontiers(
         &dag,
         &BTreeMap::from([(state_id, InputContract::bounded(input_schema.clone()))]),
@@ -367,7 +364,7 @@ fn grouped_rate_can_be_materialized_before_or_after_grouped_sum() {
         .as_any()
         .downcast_ref::<asap_physical_operators::summary_kernels::exact::ExactAccumulator>()
         .unwrap()
-        .readout(asap_physical_operators::Statistic::Rate, range_ms, None)
+        .evaluation(asap_physical_operators::Statistic::Rate, range_ms, None)
         .unwrap()
         .unwrap();
     assert_ne!(
@@ -376,7 +373,7 @@ fn grouped_rate_can_be_materialized_before_or_after_grouped_sum() {
     );
 }
 
-/// Enumerated frontiers include both grouped-result and per-series readout
+/// Enumerated frontiers include both grouped-result and per-series evaluation
 /// persistence; an explicit Rate-state input retains its original semantics.
 #[test]
 fn bounded_inventory_exposes_grouped_rate_physical_frontiers() {
@@ -388,7 +385,7 @@ fn bounded_inventory_exposes_grouped_rate_physical_frontiers() {
         .find(|node| {
             matches!(
                 &node.payload,
-                PostAsapOperatorPayload::SummaryAgg {
+                PhysicalASAPOperatorPayload::SummaryAgg {
                     family: FieldDataType::ExactAggregate(ExactKind::Rate, _),
                     ..
                 }
@@ -399,7 +396,7 @@ fn bounded_inventory_exposes_grouped_rate_physical_frontiers() {
         u64::from(state.id.0),
         InputContract::bounded(Arc::new(state.output_schema.clone())),
     )]);
-    let roots = [u64::from(dag.root.0)];
+    let roots = [u64::from(dag.roots[0].0)];
     let frontiers = enumerate_frontiers(&dag, &inputs, &roots, 4096).unwrap();
     let candidates = compile_candidates(&dag, inputs.clone(), &roots, &frontiers)
         .into_iter()
@@ -422,11 +419,11 @@ fn enumerated_grouped_rate_candidates_execute_numeric_query_outputs() {
     let mut executed = 0;
     for forest in inventory.candidates {
         let root = &forest[0].1;
-        let dag = compile_post_asap_dag(root).unwrap();
+        let dag = compile_physical_asap_dag(root).unwrap();
         let Some(state) = dag.nodes.iter().find(|node| {
             matches!(
                 node.payload,
-                PostAsapOperatorPayload::SummaryAgg {
+                PhysicalASAPOperatorPayload::SummaryAgg {
                     family: FieldDataType::ExactAggregate(ExactKind::Rate, _),
                     ..
                 }
@@ -440,25 +437,25 @@ fn enumerated_grouped_rate_candidates_execute_numeric_query_outputs() {
             .find(|node| {
                 matches!(
                     node.payload,
-                    PostAsapOperatorPayload::SummaryAgg {
+                    PhysicalASAPOperatorPayload::SummaryAgg {
                         family: FieldDataType::ExactAggregate(ExactKind::Sum, _),
                         ..
                     }
                 )
             })
             .map(|node| u64::from(node.id.0))
-            .unwrap_or(u64::from(dag.root.0));
+            .unwrap_or(u64::from(dag.roots[0].0));
         let physical_asap_dags = compile_candidates(
             &dag,
             BTreeMap::from([(
                 u64::from(state.id.0),
                 InputContract::bounded(Arc::new(state.output_schema.clone())),
             )]),
-            &[u64::from(dag.root.0)],
+            &[u64::from(dag.roots[0].0)],
             &[vec![], vec![boundary]],
         );
         let (family, input, grouping) = match &state.payload {
-            PostAsapOperatorPayload::SummaryAgg {
+            PhysicalASAPOperatorPayload::SummaryAgg {
                 family,
                 input,
                 grouping,
@@ -558,14 +555,14 @@ fn enumerated_grouped_rate_candidates_execute_numeric_query_outputs() {
 /// The per-frontier lowering used before compile-once cuts: each boundary
 /// choice lowers the precompute and query DAGs from the logical DAG again.
 fn recompiled_candidate(
-    dag: &PostAsapDAG,
+    dag: &PhysicalASAPDAG,
     inputs: &BTreeMap<u64, InputContract>,
     roots: &[u64],
     frontier: &[u64],
-) -> Result<PhysicalASAPDAG, asap_physical_operators::Error> {
+) -> Result<CompiledPhysicalPlan, asap_physical_operators::Error> {
     use asap_physical_operators::plan::Emission;
     if frontier.is_empty() {
-        return Ok(PhysicalASAPDAG {
+        return Ok(CompiledPhysicalPlan {
             precompute: None,
             query: compile(dag, inputs.clone(), roots)?,
             materialized_outputs: BTreeMap::new(),
@@ -580,7 +577,7 @@ fn recompiled_candidate(
     }
     let mut query_inputs = inputs.clone();
     query_inputs.extend(materialized_outputs.clone());
-    Ok(PhysicalASAPDAG {
+    Ok(CompiledPhysicalPlan {
         precompute: Some(precompute),
         query: compile(dag, query_inputs, roots)?,
         materialized_outputs,
@@ -588,7 +585,7 @@ fn recompiled_candidate(
 }
 
 fn assert_cuts_match_recompilation(
-    dag: &PostAsapDAG,
+    dag: &PhysicalASAPDAG,
     inputs: BTreeMap<u64, InputContract>,
     roots: &[u64],
     min_frontiers: usize,
@@ -615,13 +612,13 @@ fn grouped_rate_cuts_equal_per_frontier_compilation() {
     let state = dag
         .nodes
         .iter()
-        .find(|node| matches!(node.payload, PostAsapOperatorPayload::SummaryAgg { .. }))
+        .find(|node| matches!(node.payload, PhysicalASAPOperatorPayload::SummaryAgg { .. }))
         .unwrap();
     let inputs = BTreeMap::from([(
         u64::from(state.id.0),
         InputContract::bounded(Arc::new(state.output_schema.clone())),
     )]);
-    assert_cuts_match_recompilation(&dag, inputs, &[u64::from(dag.root.0)], 3);
+    assert_cuts_match_recompilation(&dag, inputs, &[u64::from(dag.roots[0].0)], 3);
 }
 
 /// Cuts of a DAG whose nodes lower to helper operators (current-series
@@ -655,26 +652,32 @@ fn population_topk_cuts_equal_per_frontier_compilation() {
     let original = asap_frontend_promql::lower_promql_workload(&workload, 0)
         .unwrap()
         .remove(0);
-    let root = Rc::new(
+    let root =
         asap_physical_operators::physical_planner::promql_rows::with_series_identity(&original)
-            .unwrap(),
-    );
+            .unwrap();
     let selected = asap_aware_mapping::maintained_population::MaintainedPopulationStrategy::new(
         std::slice::from_ref(&root),
     )
     .candidate(&root)
     .unwrap();
-    let dag = compile_post_asap_dag(&selected).unwrap();
+    let dag = compile_physical_asap_dag(&selected).unwrap();
     let raw = dag
         .nodes
         .iter()
-        .find(|node| matches!(node.payload, PostAsapOperatorPayload::Fallback { .. }))
+        .find(|node| {
+            matches!(
+                node.payload,
+                PhysicalASAPOperatorPayload::Relational {
+                    operator: planner_types::ir::export::NonASAPOpKind::TimeRange { .. }
+                }
+            )
+        })
         .unwrap();
     let inputs = BTreeMap::from([(
         u64::from(raw.id.0),
         InputContract::bounded(Arc::new(raw.output_schema.clone())),
     )]);
-    let roots = [u64::from(dag.root.0)];
+    let roots = [u64::from(dag.roots[0].0)];
     let compiled = compile(&dag, inputs.clone(), &roots).unwrap();
     // The root reads its population through a Sort helper numbered by the root.
     let helper = u64::MAX - (roots[0] << 16);
@@ -694,24 +697,22 @@ fn cut_candidate_rejects_invalid_frontiers() {
     let state = dag
         .nodes
         .iter()
-        .find(|node| matches!(node.payload, PostAsapOperatorPayload::SummaryAgg { .. }))
+        .find(|node| matches!(node.payload, PhysicalASAPOperatorPayload::SummaryAgg { .. }))
         .unwrap();
-    let readout = dag
+    let evaluation = dag
         .nodes
         .iter()
         .find(|node| {
             matches!(
                 node.payload,
-                PostAsapOperatorPayload::Value {
-                    operation: ValueOperation::FinalizeExactAccumulator
-                }
+                PhysicalASAPOperatorPayload::FinalizeExactAccumulator
             )
         })
         .unwrap();
     let (state_id, rate_id, root) = (
         u64::from(state.id.0),
-        u64::from(readout.id.0),
-        u64::from(dag.root.0),
+        u64::from(evaluation.id.0),
+        u64::from(dag.roots[0].0),
     );
     let inputs = BTreeMap::from([(
         state_id,
diff --git a/crates/asap-physical-operators/tests/precompute_population.rs b/crates/asap-physical-operators/tests/precompute_population.rs
index 5b91c6e72..002cf63c5 100644
--- a/crates/asap-physical-operators/tests/precompute_population.rs
+++ b/crates/asap-physical-operators/tests/precompute_population.rs
@@ -8,7 +8,11 @@ use asap_physical_operators::{
     Statistic,
 };
 use futures::{executor::block_on, StreamExt};
-use planner_types::pre_asap::Schema;
+use planner_types::ir::export::{
+    EdgeRole, GroupingEdgeCompatibility, PhysicalASAPDAG, PhysicalASAPDAGEdge, PhysicalASAPDAGNode,
+    PhysicalASAPOperatorPayload, WindowEdgeCompatibility,
+};
+use planner_types::ir::BinaryOperator;
 use planner_types::{
     post_asap::*,
     pre_asap::{ArithmeticOpKind, BinaryOpKind, ColumnRef, DataType, GroupKeys, Reduction},
@@ -19,9 +23,9 @@ use std::{collections::BTreeMap, sync::Arc};
 #[test]
 fn finalized_shared_panes_rebuild_one_global_summary_after_recovery() {
     let family = FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum);
-    let schema = |dtype| Schema {
-        closed: true,
+    let schema = |dtype| planner_types::pre_asap::Schema {
         unique_keys: vec![],
+        closed: false,
         fields: vec![Field {
             table: None,
             name: "value".into(),
@@ -50,39 +54,44 @@ fn finalized_shared_panes_rebuild_one_global_summary_after_recovery() {
         (SummaryInputExpr::Constant(1.), 4.),
     ] {
         let nodes = vec![
-            PostAsapDAGNode {
-                id: PostAsapNodeId(0),
-                payload: PostAsapOperatorPayload::SummaryMerge,
+            PhysicalASAPDAGNode {
+                coverage: None,
+                id: planner_types::ir::export::LogicalASAPNodeId(0),
+                payload: PhysicalASAPOperatorPayload::SummaryMerge,
                 output_state: ExecutionDataState::INGESTION_SUMMARY,
                 output_schema: state_schema.clone(),
                 guarantee: None,
             },
-            PostAsapDAGNode {
-                id: PostAsapNodeId(1),
-                payload: PostAsapOperatorPayload::Value {
-                    operation: ValueOperation::FinalizeExactAccumulator,
-                },
+            PhysicalASAPDAGNode {
+                coverage: None,
+                id: planner_types::ir::export::LogicalASAPNodeId(1),
+                payload: PhysicalASAPOperatorPayload::FinalizeExactAccumulator,
                 output_state: ExecutionDataState::INGESTION_ROWS,
                 output_schema: value_schema.clone(),
                 guarantee: None,
             },
-            PostAsapDAGNode {
-                id: PostAsapNodeId(2),
-                payload: PostAsapOperatorPayload::Binary {
-                    operator: BinaryOperator {
-                        kind: BinaryOpKind::Arithmetic(ArithmeticOpKind::Add),
-                        vector_match: None,
-                        checked_relative_division: false,
-                        checked_finite_division: false,
+            PhysicalASAPDAGNode {
+                coverage: None,
+                id: planner_types::ir::export::LogicalASAPNodeId(2),
+                payload: PhysicalASAPOperatorPayload::Relational {
+                    operator: planner_types::ir::export::NonASAPOpKind::BinaryOp {
+                        operator: BinaryOperator {
+                            kind: BinaryOpKind::Arithmetic(ArithmeticOpKind::Add),
+                            vector_match: None,
+                            checked_relative_division: false,
+                            checked_finite_division: false,
+                        },
+                        return_bool: false,
                     },
                 },
                 output_state: ExecutionDataState::INGESTION_ROWS,
                 output_schema: value_schema.clone(),
                 guarantee: None,
             },
-            PostAsapDAGNode {
-                id: PostAsapNodeId(3),
-                payload: PostAsapOperatorPayload::SummaryAgg {
+            PhysicalASAPDAGNode {
+                coverage: None,
+                id: planner_types::ir::export::LogicalASAPNodeId(3),
+                payload: PhysicalASAPOperatorPayload::SummaryAgg {
                     family: family.clone(),
                     input: SummaryUpdate {
                         weight,
@@ -104,9 +113,9 @@ fn finalized_shared_panes_rebuild_one_global_summary_after_recovery() {
             (2, 3, EdgeRole::Input),
         ]
         .into_iter()
-        .map(|(producer, consumer, role)| PostAsapDAGEdge {
-            producer: PostAsapNodeId(producer),
-            consumer: PostAsapNodeId(consumer),
+        .map(|(producer, consumer, role)| PhysicalASAPDAGEdge {
+            producer: planner_types::ir::export::LogicalASAPNodeId(producer),
+            consumer: planner_types::ir::export::LogicalASAPNodeId(consumer),
             role,
             intermediate_schema: nodes[producer as usize].output_schema.clone(),
             data_state: nodes[producer as usize].output_state,
@@ -114,10 +123,10 @@ fn finalized_shared_panes_rebuild_one_global_summary_after_recovery() {
             window: WindowEdgeCompatibility::NotApplicable,
         })
         .collect();
-        let dag = PostAsapDAG {
+        let dag = PhysicalASAPDAG {
             nodes,
             edges,
-            root: PostAsapNodeId(3),
+            roots: vec![planner_types::ir::export::LogicalASAPNodeId(3)],
         };
         // Identity metadata must remain one non-null Utf8 column.
         for mutation in 0..3 {
@@ -131,7 +140,7 @@ fn finalized_shared_panes_rebuild_one_global_summary_after_recovery() {
             assert!(precompute::compile(&invalid_identity, &[0], &[3]).is_err());
         }
         let mut invalid_grouping = dag.clone();
-        let PostAsapOperatorPayload::SummaryAgg { reduction, .. } =
+        let PhysicalASAPOperatorPayload::SummaryAgg { reduction, .. } =
             &mut invalid_grouping.nodes[3].payload
         else {
             unreachable!()
@@ -211,7 +220,7 @@ fn finalized_shared_panes_rebuild_one_global_summary_after_recovery() {
                     .as_any()
                     .downcast_ref::<asap_physical_operators::summary_kernels::exact::ExactAccumulator>()
                     .unwrap()
-                    .readout(Statistic::Sum, None, None)
+                    .evaluation(Statistic::Sum, None, None)
                     .unwrap()
                     .unwrap(),
                 expected
@@ -221,9 +230,9 @@ fn finalized_shared_panes_rebuild_one_global_summary_after_recovery() {
 }
 
 fn logical_schema(family: FieldDataType) -> Schema {
-    Schema {
-        closed: true,
+    planner_types::pre_asap::Schema {
         unique_keys: vec![],
+        closed: false,
         fields: vec![Field {
             table: None,
             name: "value".into(),
@@ -238,34 +247,35 @@ fn state_dag(
     target: Option<FieldDataType>,
     merge: bool,
 ) -> CompiledPhysicalDAG {
-    let mut nodes = vec![PostAsapDAGNode {
-        id: PostAsapNodeId(0),
-        payload: PostAsapOperatorPayload::SummaryMerge,
+    let mut nodes = vec![PhysicalASAPDAGNode {
+        coverage: None,
+        id: planner_types::ir::export::LogicalASAPNodeId(0),
+        payload: PhysicalASAPOperatorPayload::SummaryMerge,
         output_state: ExecutionDataState::INGESTION_SUMMARY,
         output_schema: logical_schema(family.clone()),
         guarantee: None,
     }];
     if merge {
-        nodes.push(PostAsapDAGNode {
-            id: PostAsapNodeId(1),
-            payload: PostAsapOperatorPayload::SummaryMerge,
+        nodes.push(PhysicalASAPDAGNode {
+            id: planner_types::ir::export::LogicalASAPNodeId(1),
+            payload: PhysicalASAPOperatorPayload::SummaryMerge,
             ..nodes[0].clone()
         });
     }
     let read_id = nodes.len() as u32;
-    nodes.push(PostAsapDAGNode {
-        id: PostAsapNodeId(read_id),
-        payload: PostAsapOperatorPayload::Value {
-            operation: ValueOperation::FinalizeExactAccumulator,
-        },
+    nodes.push(PhysicalASAPDAGNode {
+        coverage: None,
+        id: planner_types::ir::export::LogicalASAPNodeId(read_id),
+        payload: PhysicalASAPOperatorPayload::FinalizeExactAccumulator,
         output_state: ExecutionDataState::INGESTION_ROWS,
         output_schema: logical_schema(FieldDataType::Plain(DataType::Float64)),
         guarantee: None,
     });
     if let Some(target) = target {
-        nodes.push(PostAsapDAGNode {
-            id: PostAsapNodeId(nodes.len() as u32),
-            payload: PostAsapOperatorPayload::SummaryAgg {
+        nodes.push(PhysicalASAPDAGNode {
+            coverage: None,
+            id: planner_types::ir::export::LogicalASAPNodeId(nodes.len() as u32),
+            payload: PhysicalASAPOperatorPayload::SummaryAgg {
                 family: target.clone(),
                 input: SummaryUpdate::column(ColumnRef::SampleValue),
                 reduction: Reduction::by(vec![]),
@@ -278,7 +288,7 @@ fn state_dag(
         });
     }
     let edges = (1..nodes.len())
-        .map(|i| PostAsapDAGEdge {
+        .map(|i| PhysicalASAPDAGEdge {
             producer: nodes[i - 1].id,
             consumer: nodes[i].id,
             role: EdgeRole::Input,
@@ -290,7 +300,11 @@ fn state_dag(
         .collect();
     let root = nodes.last().unwrap().id;
     precompute::compile(
-        &PostAsapDAG { nodes, edges, root },
+        &PhysicalASAPDAG {
+            nodes,
+            edges,
+            roots: vec![root],
+        },
         &[0],
         &[u64::from(root.0)],
     )
@@ -374,7 +388,7 @@ fn explicit_merge_changes_pane_cardinality() {
             .iter()
             .map(|row| match row[2] {
                 Value::Float64(v) => v,
-                _ => panic!("numeric readout expected"),
+                _ => panic!("numeric evaluation expected"),
             })
             .collect::<Vec<_>>();
         assert_eq!(values, expected);
diff --git a/crates/asap-physical-operators/tests/promql_binary.rs b/crates/asap-physical-operators/tests/promql_binary.rs
index 4eec88aa1..793f82a43 100644
--- a/crates/asap-physical-operators/tests/promql_binary.rs
+++ b/crates/asap-physical-operators/tests/promql_binary.rs
@@ -6,19 +6,21 @@ use asap_physical_operators::{
     values::{Batch, SchemaRef, Value},
 };
 use futures::{executor::block_on, StreamExt};
+use planner_types::ir::export::{
+    EdgeRole, GroupingEdgeCompatibility, PhysicalASAPDAG, PhysicalASAPDAGEdge, PhysicalASAPDAGNode,
+    PhysicalASAPOperatorPayload, WindowEdgeCompatibility,
+};
+use planner_types::ir::BinaryOperator;
 use planner_types::{
-    post_asap::{
-        BinaryOperator, ExecutionDataState, Field, FieldDataType, PostAsapDAGNode, PostAsapNodeId,
-        PostAsapOperatorPayload, Schema,
-    },
+    post_asap::{ExecutionDataState, Field, FieldDataType},
     pre_asap::{ArithmeticOpKind, BinaryOpKind, DataType},
 };
 use std::{collections::BTreeMap, sync::Arc};
 
 fn schema() -> SchemaRef {
-    Arc::new(Schema {
-        closed: true,
+    Arc::new(planner_types::pre_asap::Schema {
         unique_keys: vec![],
+        closed: false,
         fields: vec![
             Field {
                 table: None,
@@ -61,10 +63,19 @@ fn program() -> CompiledPhysicalDAG {
     })
 }
 fn program_for(operator: BinaryOperator) -> CompiledPhysicalDAG {
+    program_for_bool(operator, false)
+}
+fn program_for_bool(operator: BinaryOperator, return_bool: bool) -> CompiledPhysicalDAG {
     let schema = schema();
-    let node = PostAsapDAGNode {
-        id: PostAsapNodeId(2),
-        payload: PostAsapOperatorPayload::Binary { operator },
+    let node = PhysicalASAPDAGNode {
+        coverage: None,
+        id: planner_types::ir::export::LogicalASAPNodeId(2),
+        payload: PhysicalASAPOperatorPayload::Relational {
+            operator: planner_types::ir::export::NonASAPOpKind::BinaryOp {
+                operator,
+                return_bool,
+            },
+        },
         output_state: ExecutionDataState::QUERY_ROWS,
         output_schema: (*schema).clone(),
         guarantee: None,
@@ -156,12 +167,15 @@ fn scalar_broadcast_and_bool_comparison_are_distinct() {
     use planner_types::pre_asap::CompareOpKind;
     for return_bool in [false, true] {
         let physical_dag = promql_values::compile_binary(
-            &BinaryOperator {
-                kind: BinaryOpKind::Compare(CompareOpKind::Lt),
-                vector_match: None,
-                checked_relative_division: false,
-                checked_finite_division: false,
-            },
+            &asap_physical_operators::expressions::binary::BinaryOperator::from_logical(
+                &BinaryOperator {
+                    kind: BinaryOpKind::Compare(CompareOpKind::Lt),
+                    vector_match: None,
+                    checked_relative_division: false,
+                    checked_finite_division: false,
+                },
+                return_bool,
+            ),
             return_bool,
             true,
             false,
@@ -285,12 +299,15 @@ fn binary_obeys_memory_and_cancellation() {
 // A `bool` comparison over label-map vectors yields 1 or 0 and drops the name.
 #[test]
 fn label_map_bool_comparison_drops_the_name() {
-    let program = program_for(BinaryOperator {
-        kind: BinaryOpKind::CompareBool(planner_types::pre_asap::CompareOpKind::Gt),
-        vector_match: None,
-        checked_relative_division: false,
-        checked_finite_division: false,
-    });
+    let program = program_for_bool(
+        BinaryOperator {
+            kind: BinaryOpKind::Compare(planner_types::pre_asap::CompareOpKind::Gt),
+            vector_match: None,
+            checked_relative_division: false,
+            checked_finite_division: false,
+        },
+        true,
+    );
     let rows = evaluate_with(
         program,
         vec![row("a", "api", 6.)],
@@ -309,9 +326,9 @@ fn label_map_bool_comparison_drops_the_name() {
     assert!(matches!(row[1], Value::Float64(v) if v == 1.));
 }
 
-// Stored temporal readouts drop metric names before filter comparisons and set matching.
+// Stored temporal evaluations drop metric names before filter comparisons and set matching.
 #[test]
-fn stored_series_readouts_support_filters_and_sets() {
+fn stored_series_evaluations_support_filters_and_sets() {
     use asap_physical_operators::{
         physical_planner::compile, summary_kernels::exact::ExactAccumulator,
     };
@@ -319,14 +336,15 @@ fn stored_series_readouts_support_filters_and_sets() {
     use planner_types::pre_asap::{
         schema::PROMQL_SERIES_IDENTITY, CompareOpKind, PromQLVectorSetOpKind,
     };
+
     for (exact_kind, params) in [
         (ExactKind::Sum, ExactParams::Sum),
         (ExactKind::Count, ExactParams::Count),
     ] {
         let family = FieldDataType::ExactAggregate(exact_kind.clone(), params);
-        let state_schema = Arc::new(Schema {
-            closed: true,
+        let state_schema = Arc::new(planner_types::pre_asap::Schema {
             unique_keys: vec![],
+            closed: false,
             fields: vec![
                 Field {
                     table: None,
@@ -351,19 +369,21 @@ fn stored_series_readouts_support_filters_and_sets() {
             BinaryOpKind::Set(PromQLVectorSetOpKind::Or),
         ] {
             let nodes = (0..5)
-                .map(|id| PostAsapDAGNode {
-                    id: PostAsapNodeId(id),
+                .map(|id| PhysicalASAPDAGNode {
+                    coverage: None,
+                    id: planner_types::ir::export::LogicalASAPNodeId(id),
                     payload: match id {
-                        0 | 1 => PostAsapOperatorPayload::SummaryMerge,
-                        2 | 3 => PostAsapOperatorPayload::Value {
-                            operation: ValueOperation::FinalizeExactAccumulator,
-                        },
-                        _ => PostAsapOperatorPayload::Binary {
-                            operator: BinaryOperator {
-                                kind: kind.clone(),
-                                vector_match: None,
-                                checked_relative_division: false,
-                                checked_finite_division: false,
+                        0 | 1 => PhysicalASAPOperatorPayload::SummaryMerge,
+                        2 | 3 => PhysicalASAPOperatorPayload::FinalizeExactAccumulator,
+                        _ => PhysicalASAPOperatorPayload::Relational {
+                            operator: planner_types::ir::export::NonASAPOpKind::BinaryOp {
+                                operator: BinaryOperator {
+                                    kind: kind.clone(),
+                                    vector_match: None,
+                                    checked_relative_division: false,
+                                    checked_finite_division: false,
+                                },
+                                return_bool: false,
                             },
                         },
                     },
@@ -387,9 +407,9 @@ fn stored_series_readouts_support_filters_and_sets() {
                 (3, 4, EdgeRole::Right),
             ]
             .into_iter()
-            .map(|(producer, consumer, role)| PostAsapDAGEdge {
-                producer: PostAsapNodeId(producer),
-                consumer: PostAsapNodeId(consumer),
+            .map(|(producer, consumer, role)| PhysicalASAPDAGEdge {
+                producer: planner_types::ir::export::LogicalASAPNodeId(producer),
+                consumer: planner_types::ir::export::LogicalASAPNodeId(consumer),
                 role,
                 intermediate_schema: nodes[producer as usize].output_schema.clone(),
                 data_state: nodes[producer as usize].output_state,
@@ -397,10 +417,10 @@ fn stored_series_readouts_support_filters_and_sets() {
                 window: WindowEdgeCompatibility::NotApplicable,
             })
             .collect();
-            let dag = PostAsapDAG {
+            let dag = PhysicalASAPDAG {
                 nodes,
                 edges,
-                root: PostAsapNodeId(4),
+                roots: vec![planner_types::ir::export::LogicalASAPNodeId(4)],
             };
             let physical_dag = compile(
                 &dag,
diff --git a/crates/asap-physical-operators/tests/promql_fallback.rs b/crates/asap-physical-operators/tests/promql_fallback.rs
index 45b3526f6..c8aef869c 100644
--- a/crates/asap-physical-operators/tests/promql_fallback.rs
+++ b/crates/asap-physical-operators/tests/promql_fallback.rs
@@ -1,27 +1,34 @@
 //! A retained PromQL sub-DAG (`Fallback`) compiles from its typed expression.
 //! The deployment supplies only its selector's raw series; expected values are
 //! hand-computed with Prometheus semantics.
+mod common;
 use asap_physical_operators::{
     operators::Operator,
     physical_planner::{compile, promql_fallback, promql_rows, CompiledPhysicalDAG, InputContract},
     runtime::{Limits, RunContext, Scope},
     values::{Batch, Value},
 };
+use common::compile_physical_asap_dag;
 use futures::{executor::block_on, StreamExt};
+use planner_types::ir::export::PhysicalASAPDAG;
 use planner_types::{
-    post_asap::{execution_data_state::lift_plain, *},
-    pre_asap::QueryExpr,
-    types::AccuracyTarget,
-    workload::*,
+    post_asap::execution_data_state::lift_plain, types::AccuracyTarget, workload::*,
 };
 use std::{collections::BTreeMap, rc::Rc};
 
 /// Bare selectors look back one ingestion interval: 60s.
-fn parse(query: &str) -> QueryExpr {
+fn parse(query: &str) -> Rc<planner_types::ir::OperatorNode> {
     parse_with(query, AccuracyTarget::Exact)
 }
 
-fn parse_with(query: &str, accuracy: AccuracyTarget) -> QueryExpr {
+fn parse_with(query: &str, accuracy: AccuracyTarget) -> Rc<planner_types::ir::OperatorNode> {
+    match parse_root(query, accuracy) {
+        planner_types::ir::QueryRoot::Operator(node) => node,
+        _ => panic!("expected operator query"),
+    }
+}
+
+fn parse_root(query: &str, accuracy: AccuracyTarget) -> planner_types::ir::QueryRoot {
     let workload = PlanningWorkload {
         query_workload: QueryWorkload {
             language: QueryLanguage::PromQL,
@@ -46,24 +53,18 @@ fn parse_with(query: &str, accuracy: AccuracyTarget) -> QueryExpr {
             ..Default::default()
         }),
     };
-    asap_frontend_promql::lower_promql_workload(&workload, 0)
+    asap_frontend_promql::lower_promql_query_workload(&workload, 0)
         .unwrap()
         .remove(0)
 }
 
-fn lower(query: &str) -> QueryExpr {
+fn lower(query: &str) -> Rc<planner_types::ir::OperatorNode> {
     promql_rows::with_series_identity(&parse(query)).unwrap()
 }
 
 /// The whole query retained as one pre-ASAP node.
-fn fallback_dag(expression: QueryExpr) -> PostAsapDAG {
-    let schema = lift_plain(&expression.output_schema().unwrap());
-    compile_post_asap_dag(&Rc::new(SummaryNode {
-        expr: SummaryExpr::KeepPreAsap(Rc::new(expression)),
-        schema,
-        guarantee: None,
-    }))
-    .unwrap()
+fn fallback_dag(expression: Rc<planner_types::ir::OperatorNode>) -> PhysicalASAPDAG {
+    compile_physical_asap_dag(&expression).unwrap()
 }
 
 /// `(labels, seconds, value)`. `labels` is `k=v,...`, or a bare `job` value.
@@ -82,13 +83,14 @@ fn labels(spec: &str) -> BTreeMap<String, String> {
 }
 
 /// The metric a selector reads.
-fn metric(selector: &QueryExpr) -> String {
-    match selector {
-        QueryExpr::Scan {
+fn metric(selector: &planner_types::ir::OperatorNode) -> String {
+    match selector.expect_non_asap() {
+        planner_types::ir::NonASAPOp::Scan {
             source: planner_types::pre_asap::Source::TimeSeries { metric },
             ..
         } => metric.clone(),
-        QueryExpr::TimeRange { child, .. } | QueryExpr::TimeShift { child, .. } => metric(child),
+        planner_types::ir::NonASAPOp::TimeRange { child, .. }
+        | planner_types::ir::NonASAPOp::TimeShift { child, .. } => metric(child),
         other => panic!("not a selector: {other:?}"),
     }
 }
@@ -99,8 +101,11 @@ fn compile_query(query: &str) -> Result<CompiledPhysicalDAG, String> {
 }
 
 /// Compile a DAG whose root is the Fallback computing `expression`.
-fn compile_dag(expression: &QueryExpr, dag: &PostAsapDAG) -> Result<CompiledPhysicalDAG, String> {
-    let root = u64::from(dag.root.0);
+fn compile_dag(
+    expression: &planner_types::ir::OperatorNode,
+    dag: &PhysicalASAPDAG,
+) -> Result<CompiledPhysicalDAG, String> {
+    let root = u64::from(dag.roots[0].0);
     let inputs = promql_fallback::raw_series(expression)
         .map_err(|e| e.to_string())?
         .into_iter()
@@ -124,14 +129,26 @@ fn evaluate(
     metrics: &[(&str, &[Sample])],
     at: i64,
 ) -> Result<Vec<(BTreeMap<String, String>, i64, f64)>, String> {
-    let expression = lower(query);
-    evaluate_dag(&expression, &fallback_dag(expression.clone()), metrics, at)
+    match parse_root(query, AccuracyTarget::Exact) {
+        planner_types::ir::QueryRoot::Operator(expression) => {
+            let expression =
+                promql_rows::with_series_identity(&expression).map_err(|e| e.to_string())?;
+            evaluate_dag(&expression, &fallback_dag(expression.clone()), metrics, at)
+        }
+        planner_types::ir::QueryRoot::Scalar(expr) => {
+            let expr = expr
+                .map_operator_refs(&mut |node| promql_rows::with_series_identity(node).unwrap());
+            let (program, selectors) =
+                promql_fallback::compile_scalar_root(&expr).map_err(|e| e.to_string())?;
+            execute_program(program, selectors, metrics, at, None)
+        }
+    }
 }
 
 #[allow(clippy::type_complexity)]
 fn evaluate_dag(
-    expression: &QueryExpr,
-    dag: &PostAsapDAG,
+    expression: &planner_types::ir::OperatorNode,
+    dag: &PhysicalASAPDAG,
     metrics: &[(&str, &[Sample])],
     at: i64,
 ) -> Result<Vec<(BTreeMap<String, String>, i64, f64)>, String> {
@@ -140,15 +157,26 @@ fn evaluate_dag(
 
 #[allow(clippy::type_complexity)]
 fn evaluate_dag_with_range(
-    expression: &QueryExpr,
-    dag: &PostAsapDAG,
+    expression: &planner_types::ir::OperatorNode,
+    dag: &PhysicalASAPDAG,
     metrics: &[(&str, &[Sample])],
     at: i64,
     bounds: Option<(i64, i64)>,
 ) -> Result<Vec<(BTreeMap<String, String>, i64, f64)>, String> {
     let program = compile_dag(expression, dag)?;
-    let mut sources = BTreeMap::new();
     let selectors = promql_fallback::raw_series(expression).unwrap();
+    execute_program(program, selectors, metrics, at, bounds)
+}
+
+#[allow(clippy::type_complexity)]
+fn execute_program(
+    program: CompiledPhysicalDAG,
+    selectors: Vec<promql_fallback::Selector>,
+    metrics: &[(&str, &[Sample])],
+    at: i64,
+    bounds: Option<(i64, i64)>,
+) -> Result<Vec<(BTreeMap<String, String>, i64, f64)>, String> {
+    let mut sources = BTreeMap::new();
     for (i, (selector, schema)) in selectors.into_iter().enumerate() {
         let name = metric(&selector);
         let rows = metrics
@@ -423,12 +451,15 @@ fn dense_subquery_grids_are_rejected() {
 fn raw_series_contract_is_explicit() {
     let expression = lower("rate(m[5m])");
     let dag = fallback_dag(expression.clone());
-    let root = u64::from(dag.root.0);
+    let root = u64::from(dag.roots[0].0);
     let [(selector, schema)] = promql_fallback::raw_series(&expression)
         .unwrap()
         .try_into()
         .unwrap();
-    assert!(matches!(selector, QueryExpr::TimeRange { .. }));
+    assert!(matches!(
+        selector.expect_non_asap(),
+        planner_types::ir::NonASAPOp::TimeRange { .. }
+    ));
     let missing = compile(&dag, BTreeMap::new(), &[root]).err().unwrap();
     assert!(missing.to_string().contains("raw series input"));
     let mut wrong = (*schema).clone();
@@ -445,54 +476,31 @@ fn raw_series_contract_is_explicit() {
     // A consumed bare selector is raw range rows for its consumer; it is not
     // turned into instant selection.
     let selector = lower("m");
-    let schema = lift_plain(&selector.output_schema().unwrap());
-    let node = |id, payload| PostAsapDAGNode {
-        id: PostAsapNodeId(id),
-        payload,
-        output_state: ExecutionDataState::QUERY_ROWS,
-        output_schema: schema.clone(),
-        guarantee: None,
-    };
-    let consumed = PostAsapDAG {
-        nodes: vec![
-            node(
-                0,
-                PostAsapOperatorPayload::Fallback {
-                    expression: selector.clone(),
-                },
-            ),
-            node(
-                1,
-                PostAsapOperatorPayload::Value {
-                    operation: ValueOperation::Limit {
-                        n: 1,
-                        offset: 0,
-                        partition_by: Default::default(),
-                    },
-                },
-            ),
-        ],
-        edges: vec![PostAsapDAGEdge {
-            producer: PostAsapNodeId(0),
-            consumer: PostAsapNodeId(1),
-            role: EdgeRole::Input,
-            intermediate_schema: schema.clone(),
-            data_state: ExecutionDataState::QUERY_ROWS,
-            grouping: GroupingEdgeCompatibility::NotApplicable,
-            window: WindowEdgeCompatibility::NotApplicable,
-        }],
-        root: PostAsapNodeId(1),
-    };
+    let _schema = lift_plain(&selector.schema.clone());
+    let consumed = planner_types::ir::OperatorNode::new_shared(
+        planner_types::ir::Operator::NonASAP(planner_types::ir::NonASAPOp::Limit {
+            n: Some(1),
+            offset: 0,
+            partition_by: Default::default(),
+            child: selector.clone(),
+        }),
+    )
+    .unwrap();
+    let consumed = fallback_dag(consumed.clone());
     let raw = promql_fallback::raw_series(&selector).unwrap().remove(0).1;
     assert!(compile(
         &consumed,
         BTreeMap::from([(
-            promql_fallback::raw_series_input(0, 0),
+            promql_fallback::raw_series_input(u64::from(consumed.roots[0].0), 0),
             InputContract::bounded(raw)
         )]),
-        &[1],
+        &consumed
+            .roots
+            .iter()
+            .map(|r| u64::from(r.0))
+            .collect::<Vec<_>>()
     )
-    .is_err());
+    .is_ok());
     // Implicit subquery resolution belongs to the deployment's evaluation interval.
     assert!(compile_query("max_over_time(m[5m:])").is_err());
 }
@@ -1231,9 +1239,8 @@ fn histogram_quantile_selection_keeps_the_exact_fallback() {
             "histogram_quantile(0.5, x_bucket)",
             "histogram_quantile(0.5, sum by (le, job) (x_bucket))",
         ] {
-            let root = Rc::new(
-                promql_rows::with_series_identity(&parse_with(query, target.clone())).unwrap(),
-            );
+            let root =
+                promql_rows::with_series_identity(&parse_with(query, target.clone())).unwrap();
             let space = search_workload_with_targets(
                 vec![(query, root.clone(), Some(target.clone()))],
                 &default_strategies(),
@@ -1243,8 +1250,7 @@ fn histogram_quantile_selection_keeps_the_exact_fallback() {
             let candidates = &space.candidates_for_target(planned).unwrap().candidates;
             assert!(
                 candidates.iter().all(|c| matches!(&c.replacement,
-                    Replacement::Summary(node) if matches!(&node.expr,
-                        SummaryExpr::KeepPreAsap(e) if **e == *root))),
+                    Replacement::SubDAG(node) if !node.contains_asap() && node.operator == root.operator)),
                 "{query}: {candidates:?}"
             );
             let selected = space
@@ -1252,7 +1258,7 @@ fn histogram_quantile_selection_keeps_the_exact_fallback() {
                 .assemble_selected_dag(planned)
                 .unwrap()
                 .unwrap();
-            let dag = compile_post_asap_dag(&selected).unwrap();
+            let dag = compile_physical_asap_dag(&selected).unwrap();
             let rows = evaluate_dag(&root, &dag, &[("x_bucket", &samples)], 60).unwrap();
             let values: Vec<_> = rows.iter().map(|(_, _, v)| *v).collect();
             assert_eq!(values, vec![1.75], "{query} {target:?}");
@@ -1285,7 +1291,7 @@ fn nonfinite_literals_round_trip_in_plans() {
     ] {
         let expression = lower(query);
         let json = serde_json::to_vec(&expression).unwrap();
-        let restored: QueryExpr = serde_json::from_slice(&json).unwrap();
+        let restored: Rc<planner_types::ir::OperatorNode> = serde_json::from_slice(&json).unwrap();
         let result = evaluate_dag(&restored, &fallback_dag(restored.clone()), &[], 60).unwrap();
         assert_eq!(result.len(), 1);
         if expected.is_nan() {
@@ -1579,7 +1585,7 @@ fn subquery_label_uniqueness_is_checked_per_evaluation_step() {
 #[test]
 fn logical_nonfinite_quantile_parameter_round_trips() {
     let expression = lower("histogram_quantile(NaN, x_bucket)");
-    let restored: QueryExpr =
+    let restored: Rc<planner_types::ir::OperatorNode> =
         serde_json::from_slice(&serde_json::to_vec(&expression).unwrap()).unwrap();
     let samples = buckets(&[("job=a", HISTOGRAM)]);
     let result = evaluate_dag(
@@ -1592,3 +1598,56 @@ fn logical_nonfinite_quantile_parameter_round_trips() {
     assert_eq!(result.len(), 1);
     assert!(result[0].2.is_nan());
 }
+
+/// The proposal's pointwise projections preserve names only for unary minus.
+#[test]
+fn pointwise_projection_names_and_dynamic_parameters() {
+    let samples = [("job=a", 300, -2.5)];
+    assert_eq!(
+        labeled("-m", &[("m", &samples)], 300),
+        [("__name__=m,job=a".into(), 2.5)]
+    );
+    assert_eq!(
+        labeled("abs(m)", &[("m", &samples)], 300),
+        [("job=a".into(), 2.5)]
+    );
+    assert_eq!(
+        run("round(m, scalar(vector(2)))", &samples, 300).unwrap(),
+        [("a".into(), 300_000, -2.0)]
+    );
+    assert_eq!(
+        run("clamp(m, time()-301, time())", &samples, 300).unwrap(),
+        [("a".into(), 300_000, -1.0)]
+    );
+    assert!(run("clamp(m, 2, 1)", &samples, 300).unwrap().is_empty());
+    assert_eq!(
+        run("year(m)", &[("a", 300, 0.0)], 300).unwrap(),
+        [("a".into(), 300_000, 1970.0)]
+    );
+    assert_eq!(
+        run("hour()", &[], 3600).unwrap(),
+        [("".into(), 3_600_000, 1.0)]
+    );
+}
+
+/// Execute every PromQL root/conversion example in the scalar design document.
+#[test]
+fn scalar_design_document_examples_execute() {
+    let samples = [("job=a", 300, 1.0), ("job=b", 300, 2.0)];
+    for (query, expected) in [
+        ("2", 2.0),
+        ("time()", 300.0),
+        ("vector(time())", 300.0),
+        ("scalar(sum(up)) + 1", 4.0),
+    ] {
+        let root = parse_root(query, AccuracyTarget::Exact);
+        root.validate_structure().unwrap();
+        let output = evaluate(query, &[("up", &samples)], 300).unwrap();
+        assert_eq!(output.len(), 1, "{query}");
+        assert_eq!(output[0].2, expected, "{query}");
+    }
+    assert_eq!(
+        labeled("up * 2", &[("up", &samples)], 300),
+        [("job=a".into(), 2.0), ("job=b".into(), 4.0)]
+    );
+}
diff --git a/crates/asap-physical-operators/tests/promql_values.rs b/crates/asap-physical-operators/tests/promql_values.rs
index e7deb78b1..35b9f2c0b 100644
--- a/crates/asap-physical-operators/tests/promql_values.rs
+++ b/crates/asap-physical-operators/tests/promql_values.rs
@@ -1,4 +1,6 @@
 //! Compile, persist and rebind dynamic-label computation without deployment lowering.
+use asap_physical_operators::expressions::binary::{BinaryOpKind, BinaryOperator};
+
 use asap_physical_operators::{
     operators::Operator,
     physical_planner::{promql_values::*, CompiledPhysicalDAG, Source},
@@ -7,6 +9,7 @@ use asap_physical_operators::{
 };
 use futures::{executor::block_on, StreamExt};
 use planner_types::pre_asap::{AggIntent, ColumnRef, GroupKeys};
+
 use std::collections::BTreeMap;
 
 fn row(labels: &[(&str, &str)], value: f64) -> Vec<Value> {
@@ -213,10 +216,7 @@ fn composed_ensemble_shares_a_producer_across_roots() {
         runtime::{Input, OutputStream},
         values::SchemaRef,
     };
-    use planner_types::{
-        post_asap::BinaryOperator,
-        pre_asap::{ArithmeticOpKind, BinaryOpKind},
-    };
+    use planner_types::pre_asap::ArithmeticOpKind;
     struct Counted {
         source: Operator,
         starts: std::rc::Rc<std::cell::Cell<usize>>,
@@ -325,10 +325,7 @@ fn compiled_constant_needs_no_deployment_source() {
 // arithmetic or bool comparisons remove the metric name.
 #[test]
 fn scalar_broadcast_rejects_colliding_result_labels_after_recovery() {
-    use planner_types::{
-        post_asap::BinaryOperator,
-        pre_asap::{ArithmeticOpKind, BinaryOpKind, CompareOpKind},
-    };
+    use planner_types::pre_asap::{ArithmeticOpKind, CompareOpKind};
     for left_scalar in [false, true] {
         for names in [["a", "a"], ["a", "b"]] {
             for (kind, return_bool) in [
@@ -398,10 +395,10 @@ fn scalar_broadcast_rejects_colliding_result_labels_after_recovery() {
     );
 }
 
-// Persisted exact readout DAGs, rather than the storage adapter, merge panes,
+// Persisted exact evaluation graphs, rather than the storage adapter, merge panes,
 // finalize each population, and preserve the requested metric-name semantics.
 #[test]
-fn exact_state_readouts_recover_and_finalize_panes() {
+fn exact_state_evaluations_recover_and_finalize_panes() {
     use asap_physical_operators::factory::create_planner_accumulator;
     use planner_types::post_asap::*;
     use std::sync::Arc;
@@ -436,7 +433,7 @@ fn exact_state_readouts_recover_and_finalize_panes() {
                 })
                 .collect();
             let output = run_inputs(
-                compile_exact_readout(family.clone(), 60_000, preserve).unwrap(),
+                compile_exact_evaluation(family.clone(), 60_000, preserve).unwrap(),
                 vec![Batch::try_new(exact_state_schema(family.clone()).unwrap(), rows).unwrap()],
             )
             .unwrap();
@@ -483,7 +480,7 @@ fn recovered_exact_counter_uses_window_and_omits_insufficient_samples() {
             })
             .collect();
         let output = run_inputs(
-            compile_exact_readout(family.clone(), 60_000, false).unwrap(),
+            compile_exact_evaluation(family.clone(), 60_000, false).unwrap(),
             vec![Batch::try_new(exact_state_schema(family).unwrap(), rows).unwrap()],
         )
         .unwrap();
diff --git a/crates/asap-physical-operators/tests/raw_scan.rs b/crates/asap-physical-operators/tests/raw_scan.rs
index cf56a8682..44cdb6a6b 100644
--- a/crates/asap-physical-operators/tests/raw_scan.rs
+++ b/crates/asap-physical-operators/tests/raw_scan.rs
@@ -6,26 +6,33 @@ use asap_physical_operators::dag::{
     Error, Limits, OutputStream, RunContext, Scope,
 };
 use futures::{executor::block_on, stream, StreamExt};
-use planner_types::pre_asap::Schema;
+use planner_types::ir::export::NonASAPOpKind as ValueOperation;
+use planner_types::ir::export::{
+    EdgeRole, GroupingEdgeCompatibility, PhysicalASAPDAG, PhysicalASAPDAGEdge, PhysicalASAPDAGNode,
+    PhysicalASAPOperatorPayload, WindowEdgeCompatibility,
+};
+use planner_types::ir::Predicate;
 use planner_types::{
     post_asap::*,
-    pre_asap::{DataType, Field, GroupKeys, Predicate, QueryExpr, Source},
+    pre_asap::{DataType, Field, GroupKeys, Source},
 };
 use std::{
     collections::BTreeMap,
-    rc::Rc,
     sync::{
         atomic::{AtomicUsize, Ordering},
         Arc,
     },
 };
 
-fn fixture() -> (QueryExpr, SchemaRef, Vec<Batch>) {
-    let schema =
-        planner_types::pre_asap::Schema::new(vec![Field::plain("value", DataType::Int64, true)]);
-    let output = Arc::new(Schema {
-        closed: true,
+fn fixture() -> (planner_types::ir::NonASAPOp, SchemaRef, Vec<Batch>) {
+    let schema = planner_types::pre_asap::Schema::new(vec![planner_types::pre_asap::Field::plain(
+        "value",
+        DataType::Int64,
+        true,
+    )]);
+    let output = Arc::new(planner_types::pre_asap::Schema {
         unique_keys: vec![],
+        closed: false,
         fields: vec![Field {
             table: None,
             name: "value".into(),
@@ -34,13 +41,13 @@ fn fixture() -> (QueryExpr, SchemaRef, Vec<Batch>) {
         }],
         time_index: None,
     });
-    let scan = QueryExpr::Scan {
+    let scan = planner_types::ir::NonASAPOp::Scan {
         source: Source::Table {
             table_ref: "numbers".into(),
         },
-        predicates: vec![Predicate(Rc::new(QueryExpr::IsNotNull(Rc::new(
-            QueryExpr::Column(0),
-        ))))],
+        predicates: vec![Predicate(planner_types::ir::ScalarExpr::IsNotNull(
+            Box::new(planner_types::ir::ScalarExpr::Column(0)),
+        ))],
         schema,
     };
     let batches = vec![
@@ -57,32 +64,44 @@ fn fixture() -> (QueryExpr, SchemaRef, Vec<Batch>) {
     ];
     (scan, output, batches)
 }
-fn plan(scan: QueryExpr, schema: &SchemaRef, state: ExecutionDataState) -> PostAsapDAG {
-    let node = |id, payload| PostAsapDAGNode {
-        id: PostAsapNodeId(id),
+fn plan(
+    scan: planner_types::ir::NonASAPOp,
+    schema: &SchemaRef,
+    state: ExecutionDataState,
+) -> PhysicalASAPDAG {
+    let node = |id, payload| PhysicalASAPDAGNode {
+        coverage: None,
+        id: planner_types::ir::export::LogicalASAPNodeId(id),
         payload,
         output_state: state,
         output_schema: (**schema).clone(),
         guarantee: None,
     };
-    let edge = |producer, consumer| PostAsapDAGEdge {
-        producer: PostAsapNodeId(producer),
-        consumer: PostAsapNodeId(consumer),
+    let edge = |producer, consumer| PhysicalASAPDAGEdge {
+        producer: planner_types::ir::export::LogicalASAPNodeId(producer),
+        consumer: planner_types::ir::export::LogicalASAPNodeId(consumer),
         role: EdgeRole::Input,
         intermediate_schema: (**schema).clone(),
         data_state: state,
         grouping: GroupingEdgeCompatibility::NotApplicable,
         window: WindowEdgeCompatibility::NotApplicable,
     };
-    PostAsapDAG {
+    PhysicalASAPDAG {
         nodes: vec![
-            node(0, PostAsapOperatorPayload::Fallback { expression: scan }),
+            node(
+                0,
+                PhysicalASAPOperatorPayload::Relational {
+                    operator: planner_types::ir::export::NonASAPOpKind::from_op(&scan, &mut |_| {
+                        panic!("no plan refs")
+                    }),
+                },
+            ),
             node(
                 1,
-                PostAsapOperatorPayload::Value {
-                    operation: ValueOperation::Sort {
-                        keys: vec![planner_types::pre_asap::SortKey {
-                            expr: QueryExpr::Column(0),
+                PhysicalASAPOperatorPayload::Relational {
+                    operator: ValueOperation::Sort {
+                        keys: vec![planner_types::ir::export::WireSortKey {
+                            expr: planner_types::ir::export::WireScalarExpr::Column(0),
                             ascending: false,
                             nulls_first: false,
                         }],
@@ -92,9 +111,9 @@ fn plan(scan: QueryExpr, schema: &SchemaRef, state: ExecutionDataState) -> PostA
             ),
             node(
                 2,
-                PostAsapOperatorPayload::Value {
-                    operation: ValueOperation::Limit {
-                        n: 2,
+                PhysicalASAPOperatorPayload::Relational {
+                    operator: ValueOperation::Limit {
+                        n: Some(2),
                         offset: 0,
                         partition_by: GroupKeys::by(vec![]),
                     },
@@ -102,7 +121,7 @@ fn plan(scan: QueryExpr, schema: &SchemaRef, state: ExecutionDataState) -> PostA
             ),
         ],
         edges: vec![edge(0, 1), edge(1, 2)],
-        root: PostAsapNodeId(2),
+        roots: vec![planner_types::ir::export::LogicalASAPNodeId(2)],
     }
 }
 fn registry(source: Arc<dyn RawSource>) -> DataSources {
@@ -223,17 +242,27 @@ fn lazy_open_shared_producer_and_cancellation() {
 #[test]
 fn binding_errors_and_reader_errors_are_not_empty_results() {
     let (mut scan, schema, _) = fixture();
-    assert!(DataSources::default().bind(&scan).is_err());
+    assert!(DataSources::default()
+        .bind(&planner_types::ir::OperatorNode::with_schema(
+            planner_types::ir::Operator::NonASAP(scan.clone()),
+            scan.output_schema().unwrap()
+        ))
+        .is_err());
     let opened = Arc::new(AtomicUsize::new(0));
     let sources = registry(Arc::new(CountingSource {
         schema: schema.clone(),
         opened: opened.clone(),
         fail: true,
     }));
-    if let QueryExpr::Scan { predicates, .. } = &mut scan {
-        predicates.push(Predicate(Rc::new(QueryExpr::Column(0))));
+    if let planner_types::ir::NonASAPOp::Scan { predicates, .. } = &mut scan {
+        predicates.push(Predicate(planner_types::ir::ScalarExpr::Column(0)));
     }
-    assert!(sources.bind(&scan).is_err());
+    assert!(sources
+        .bind(&planner_types::ir::OperatorNode::with_schema(
+            planner_types::ir::Operator::NonASAP(scan.clone()),
+            scan.output_schema().unwrap()
+        ))
+        .is_err());
     assert_eq!(opened.load(Ordering::SeqCst), 0);
     let (scan, _, _) = fixture();
     let plan = plan(scan, &schema, ExecutionDataState::QUERY_ROWS);
@@ -297,19 +326,23 @@ fn schema_drift_and_memory_limits_fail_the_scan() {
 #[test]
 fn empty_sources_and_three_valued_predicates() {
     use planner_types::pre_asap::{CompareOpKind, ScalarValue};
+
     let (mut scan, schema, batches) = fixture();
-    if let QueryExpr::Scan {
+    if let planner_types::ir::NonASAPOp::Scan {
         predicates, source, ..
     } = &mut scan
     {
         *source = Source::TimeSeries {
             metric: "samples".into(),
         };
-        *predicates = vec![Predicate(Rc::new(QueryExpr::Compare {
-            left: Rc::new(QueryExpr::Column(0)),
+        *predicates = vec![Predicate(planner_types::ir::ScalarExpr::Compare {
+            semantics: planner_types::ir::ExprSemantics::Sql,
+            left: Box::new(planner_types::ir::ScalarExpr::Column(0)),
             op: CompareOpKind::Gt,
-            right: Rc::new(QueryExpr::Literal(ScalarValue::Int64(2))),
-        }))];
+            right: Box::new(planner_types::ir::ScalarExpr::Literal(ScalarValue::Int64(
+                2,
+            ))),
+        })];
     }
     for (batches, expected) in [(vec![], 0), (batches, 2)] {
         let mut sources = DataSources::default();
diff --git a/crates/asap-physical-operators/tests/summary_projection.rs b/crates/asap-physical-operators/tests/summary_projection.rs
index 8cac1cbda..f48b9c210 100644
--- a/crates/asap-physical-operators/tests/summary_projection.rs
+++ b/crates/asap-physical-operators/tests/summary_projection.rs
@@ -8,10 +8,14 @@ use asap_physical_operators::{
     values::{Batch, Value},
 };
 use futures::{executor::block_on, StreamExt};
-use planner_types::pre_asap::Schema;
+use planner_types::ir::export::NonASAPOpKind as ValueOperation;
+use planner_types::ir::export::{
+    EdgeRole, GroupingEdgeCompatibility, PhysicalASAPDAG, PhysicalASAPDAGEdge, PhysicalASAPDAGNode,
+    PhysicalASAPOperatorPayload, WindowEdgeCompatibility,
+};
 use planner_types::{
     post_asap::*,
-    pre_asap::{ColumnRef, DataType, ProjectItem, QueryExpr},
+    pre_asap::{ColumnRef, DataType},
 };
 use std::{collections::BTreeMap, sync::Arc};
 
@@ -20,9 +24,9 @@ use std::{collections::BTreeMap, sync::Arc};
 #[test]
 fn post_asap_summary_projection_survives_recovery() {
     let family = FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum);
-    let schema = Arc::new(Schema {
-        closed: true,
+    let schema = Arc::new(planner_types::pre_asap::Schema {
         unique_keys: vec![],
+        closed: false,
         fields: vec![
             Field {
                 table: None,
@@ -39,9 +43,9 @@ fn post_asap_summary_projection_survives_recovery() {
         ],
         time_index: None,
     });
-    let output = Schema {
-        closed: true,
+    let output = planner_types::pre_asap::Schema {
         unique_keys: vec![],
+        closed: false,
         fields: vec![
             schema.fields[1].clone(),
             Field {
@@ -51,24 +55,26 @@ fn post_asap_summary_projection_survives_recovery() {
         ],
         time_index: None,
     };
-    let dag = PostAsapDAG {
+    let dag = PhysicalASAPDAG {
         nodes: vec![
-            PostAsapDAGNode {
-                id: PostAsapNodeId(0),
-                payload: PostAsapOperatorPayload::SummaryMerge,
+            PhysicalASAPDAGNode {
+                coverage: None,
+                id: planner_types::ir::export::LogicalASAPNodeId(0),
+                payload: PhysicalASAPOperatorPayload::SummaryMerge,
                 output_schema: (*schema).clone(),
                 output_state: ExecutionDataState::INGESTION_SUMMARY,
                 guarantee: None,
             },
-            PostAsapDAGNode {
-                id: PostAsapNodeId(1),
-                payload: PostAsapOperatorPayload::Value {
-                    operation: ValueOperation::Project {
+            PhysicalASAPDAGNode {
+                coverage: None,
+                id: planner_types::ir::export::LogicalASAPNodeId(1),
+                payload: PhysicalASAPOperatorPayload::Relational {
+                    operator: ValueOperation::Project {
                         cols: vec![1, 0]
                             .into_iter()
-                            .map(|index| ProjectItem {
+                            .map(|index| planner_types::ir::export::WireProjectItem {
                                 alias: None,
-                                expr: QueryExpr::Column(index),
+                                expr: planner_types::ir::export::WireScalarExpr::Column(index),
                             })
                             .collect(),
                         qualifier: None,
@@ -79,16 +85,16 @@ fn post_asap_summary_projection_survives_recovery() {
                 guarantee: None,
             },
         ],
-        edges: vec![PostAsapDAGEdge {
-            producer: PostAsapNodeId(0),
-            consumer: PostAsapNodeId(1),
+        edges: vec![PhysicalASAPDAGEdge {
+            producer: planner_types::ir::export::LogicalASAPNodeId(0),
+            consumer: planner_types::ir::export::LogicalASAPNodeId(1),
             role: EdgeRole::Input,
             intermediate_schema: (*schema).clone(),
             data_state: ExecutionDataState::INGESTION_SUMMARY,
             grouping: GroupingEdgeCompatibility::NotApplicable,
             window: WindowEdgeCompatibility::NotApplicable,
         }],
-        root: PostAsapNodeId(1),
+        roots: vec![planner_types::ir::export::LogicalASAPNodeId(1)],
     };
     let program = compile(
         &dag,
diff --git a/crates/asap-physical-operators/tests/unified_promql_fallback.rs b/crates/asap-physical-operators/tests/unified_promql_fallback.rs
deleted file mode 100644
index b3a00fc32..000000000
--- a/crates/asap-physical-operators/tests/unified_promql_fallback.rs
+++ /dev/null
@@ -1,1615 +0,0 @@
-//! A retained PromQL sub-DAG (`Fallback`) compiles from its typed expression.
-//! The deployment supplies only its selector's raw series; expected values are
-//! hand-computed with Prometheus semantics.
-#[path = "unified_common/mod.rs"]
-mod common;
-use asap_physical_operators::{
-    operators::Operator,
-    runtime::{Limits, RunContext, Scope},
-    unified_physical_planner::{
-        compile, promql_fallback, promql_rows, CompiledPhysicalDAG, InputContract,
-    },
-    values::{Batch, Value},
-};
-use common::compile_physical_asap_dag;
-use futures::{executor::block_on, StreamExt};
-use planner_types::ir::export::PhysicalASAPDAG;
-use planner_types::{
-    post_asap::execution_data_state::lift_plain, types::AccuracyTarget, workload::*,
-};
-use std::{collections::BTreeMap, rc::Rc};
-
-/// Bare selectors look back one ingestion interval: 60s.
-fn parse(query: &str) -> Rc<planner_types::ir::OperatorNode> {
-    parse_with(query, AccuracyTarget::Exact)
-}
-
-fn parse_with(query: &str, accuracy: AccuracyTarget) -> Rc<planner_types::ir::OperatorNode> {
-    match parse_root(query, accuracy) {
-        planner_types::ir::QueryRoot::Operator(node) => node,
-        _ => panic!("expected operator query"),
-    }
-}
-
-fn parse_root(query: &str, accuracy: AccuracyTarget) -> planner_types::ir::QueryRoot {
-    let workload = PlanningWorkload {
-        query_workload: QueryWorkload {
-            language: QueryLanguage::PromQL,
-            query_batch: Some(vec![BatchEntry {
-                query: Query(query.into()),
-                requirements: QueryRequirements {
-                    accuracy: AccuracyRequirement::Explicit(accuracy),
-                    ..Default::default()
-                },
-                predictability: Predictability::Unknown,
-                invocations: 1,
-                execute_at: None,
-                time_selection: TimeSelection::default(),
-            }]),
-            repeating_queries: None,
-        },
-        data_workload: Some(DataWorkload {
-            data_ingestion_interval: Evidence {
-                value: Some(DurationMs(60_000)),
-                ..Default::default()
-            },
-            ..Default::default()
-        }),
-    };
-    asap_frontend_promql::unified::lower_promql_query_workload(&workload, 0)
-        .unwrap()
-        .remove(0)
-}
-
-fn lower(query: &str) -> Rc<planner_types::ir::OperatorNode> {
-    promql_rows::with_series_identity(&parse(query)).unwrap()
-}
-
-/// The whole query retained as one pre-ASAP node.
-fn fallback_dag(expression: Rc<planner_types::ir::OperatorNode>) -> PhysicalASAPDAG {
-    compile_physical_asap_dag(&expression).unwrap()
-}
-
-/// `(labels, seconds, value)`. `labels` is `k=v,...`, or a bare `job` value.
-type Sample = (&'static str, i64, f64);
-
-fn labels(spec: &str) -> BTreeMap<String, String> {
-    if !spec.contains('=') {
-        return BTreeMap::from([("job".into(), spec.into())]);
-    }
-    spec.split(',')
-        .map(|pair| {
-            let (k, v) = pair.split_once('=').unwrap();
-            (k.to_string(), v.to_string())
-        })
-        .collect()
-}
-
-/// The metric a selector reads.
-fn metric(selector: &planner_types::ir::OperatorNode) -> String {
-    match selector.expect_non_asap() {
-        planner_types::ir::NonASAPOp::Scan {
-            source: planner_types::pre_asap::Source::TimeSeries { metric },
-            ..
-        } => metric.clone(),
-        planner_types::ir::NonASAPOp::TimeRange { child, .. }
-        | planner_types::ir::NonASAPOp::TimeShift { child, .. } => metric(child),
-        other => panic!("not a selector: {other:?}"),
-    }
-}
-
-fn compile_query(query: &str) -> Result<CompiledPhysicalDAG, String> {
-    let expression = lower(query);
-    compile_dag(&expression, &fallback_dag(expression.clone()))
-}
-
-/// Compile a DAG whose root is the Fallback computing `expression`.
-fn compile_dag(
-    expression: &planner_types::ir::OperatorNode,
-    dag: &PhysicalASAPDAG,
-) -> Result<CompiledPhysicalDAG, String> {
-    let root = u64::from(dag.roots[0].0);
-    let inputs = promql_fallback::raw_series(expression)
-        .map_err(|e| e.to_string())?
-        .into_iter()
-        .enumerate()
-        .map(|(i, (_, schema))| {
-            (
-                promql_fallback::raw_series_input(root, i),
-                InputContract::bounded(schema),
-            )
-        })
-        .collect();
-    let program = compile(dag, inputs, &[root]).map_err(|e| e.to_string())?;
-    Ok(serde_json::from_slice(&serde_json::to_vec(&program).unwrap()).unwrap())
-}
-
-/// Evaluate at `at` seconds over samples of each named metric; returns
-/// `(output labels, timestamp ms, value)` rows in order.
-#[allow(clippy::type_complexity)]
-fn evaluate(
-    query: &str,
-    metrics: &[(&str, &[Sample])],
-    at: i64,
-) -> Result<Vec<(BTreeMap<String, String>, i64, f64)>, String> {
-    match parse_root(query, AccuracyTarget::Exact) {
-        planner_types::ir::QueryRoot::Operator(expression) => {
-            let expression =
-                promql_rows::with_series_identity(&expression).map_err(|e| e.to_string())?;
-            evaluate_dag(&expression, &fallback_dag(expression.clone()), metrics, at)
-        }
-        planner_types::ir::QueryRoot::Scalar(expr) => {
-            let expr = expr
-                .map_operator_refs(&mut |node| promql_rows::with_series_identity(node).unwrap());
-            let (program, selectors) =
-                promql_fallback::compile_scalar_root(&expr).map_err(|e| e.to_string())?;
-            execute_program(program, selectors, metrics, at, None)
-        }
-    }
-}
-
-#[allow(clippy::type_complexity)]
-fn evaluate_dag(
-    expression: &planner_types::ir::OperatorNode,
-    dag: &PhysicalASAPDAG,
-    metrics: &[(&str, &[Sample])],
-    at: i64,
-) -> Result<Vec<(BTreeMap<String, String>, i64, f64)>, String> {
-    evaluate_dag_with_range(expression, dag, metrics, at, None)
-}
-
-#[allow(clippy::type_complexity)]
-fn evaluate_dag_with_range(
-    expression: &planner_types::ir::OperatorNode,
-    dag: &PhysicalASAPDAG,
-    metrics: &[(&str, &[Sample])],
-    at: i64,
-    bounds: Option<(i64, i64)>,
-) -> Result<Vec<(BTreeMap<String, String>, i64, f64)>, String> {
-    let program = compile_dag(expression, dag)?;
-    let selectors = promql_fallback::raw_series(expression).unwrap();
-    execute_program(program, selectors, metrics, at, bounds)
-}
-
-#[allow(clippy::type_complexity)]
-fn execute_program(
-    program: CompiledPhysicalDAG,
-    selectors: Vec<promql_fallback::Selector>,
-    metrics: &[(&str, &[Sample])],
-    at: i64,
-    bounds: Option<(i64, i64)>,
-) -> Result<Vec<(BTreeMap<String, String>, i64, f64)>, String> {
-    let mut sources = BTreeMap::new();
-    for (i, (selector, schema)) in selectors.into_iter().enumerate() {
-        let name = metric(&selector);
-        let rows = metrics
-            .iter()
-            .filter(|(m, _)| *m == name)
-            .flat_map(|(_, samples)| samples.iter())
-            .map(|(spec, seconds, value)| {
-                let mut labels = labels(spec);
-                // A sample may supply its own `__name__`, as a series of another metric.
-                labels.entry("__name__".into()).or_insert(name.clone());
-                promql_rows::series_row(&schema, &labels, seconds * 1000, *value).unwrap()
-            })
-            .collect();
-        let batch = Batch::try_new(schema.clone(), rows).unwrap();
-        sources.insert(
-            promql_fallback::raw_series_input(program.roots()[0], i),
-            Box::new(Operator::source(schema, vec![batch]).unwrap()) as _,
-        );
-    }
-    let dag = program.instantiate(sources).map_err(|e| e.to_string())?;
-    let context = RunContext::new(
-        Scope::Query {
-            evaluation_time_ms: at * 1000,
-            revision: 0,
-        },
-        Limits::default(),
-    )
-    .unwrap();
-    let context = match bounds {
-        Some((start, end)) => context
-            .with_query_range(start * 1000, end * 1000)
-            .map_err(|e| e.to_string())?,
-        None => context,
-    };
-    block_on(async {
-        let mut stream = dag
-            .execute(program.roots(), context)
-            .map_err(|e| e.to_string())?
-            .remove(0);
-        let mut rows = Vec::new();
-        while let Some(batch) = stream.next().await {
-            let batch = batch.map_err(|e| e.to_string())?;
-            let schema = batch.schema().clone();
-            for row in batch.rows() {
-                let mut labels = BTreeMap::new();
-                let mut time = -1;
-                let mut value = None;
-                for (field, cell) in schema.fields.iter().zip(row) {
-                    match (field.name.as_str(), cell) {
-                        (promql_rows::SERIES_IDENTITY_COLUMN, Value::Utf8(id)) => {
-                            labels = promql_rows::decode_series_identity(id).unwrap()
-                        }
-                        (_, Value::Utf8(_) | Value::Null) => {}
-                        (_, Value::Timestamp(t)) => time = *t,
-                        (_, Value::Float64(v)) => value = Some(*v),
-                        (_, Value::Int64(v)) => value = Some(*v as f64),
-                        other => return Err(format!("unexpected cell {other:?}")),
-                    }
-                }
-                if !schema
-                    .fields
-                    .iter()
-                    .any(|f| f.name == promql_rows::SERIES_IDENTITY_COLUMN)
-                {
-                    for (field, cell) in schema.fields.iter().zip(row) {
-                        if let Value::Utf8(label) = cell {
-                            if !label.is_empty() {
-                                labels.insert(field.name.clone(), label.to_string());
-                            }
-                        }
-                    }
-                }
-                rows.push((labels, time, value.ok_or("missing value")?));
-            }
-        }
-        Ok(rows)
-    })
-}
-
-/// Evaluate at `at` seconds over metric `m`; returns `(job or "", timestamp ms, value)`.
-fn run(query: &str, samples: &[Sample], at: i64) -> Result<Vec<(String, i64, f64)>, String> {
-    Ok(evaluate(query, &[("m", samples)], at)?
-        .into_iter()
-        .map(|(labels, time, value)| (labels.get("job").cloned().unwrap_or_default(), time, value))
-        .collect())
-}
-
-/// Output rows as `(k=v,... sorted, value)`, including any `__name__`.
-fn labeled(query: &str, metrics: &[(&str, &[Sample])], at: i64) -> Vec<(String, f64)> {
-    let mut rows = evaluate(query, metrics, at)
-        .unwrap_or_else(|e| panic!("{query}: {e}"))
-        .into_iter()
-        .map(|(labels, _, value)| {
-            let spec = labels
-                .iter()
-                .map(|(k, v)| format!("{k}={v}"))
-                .collect::<Vec<_>>()
-                .join(",");
-            (spec, value)
-        })
-        .collect::<Vec<_>>();
-    rows.sort_by(|a, b| a.0.cmp(&b.0));
-    rows
-}
-
-fn values(query: &str, samples: &[Sample], at: i64) -> Vec<(String, f64)> {
-    run(query, samples, at)
-        .unwrap_or_else(|e| panic!("{query}: {e}"))
-        .into_iter()
-        .map(|(job, _, value)| (job, value))
-        .collect()
-}
-
-fn one(query: &str, samples: &[Sample], at: i64) -> f64 {
-    match values(query, samples, at).as_slice() {
-        [(_, value)] => *value,
-        other => panic!("{query}: expected one sample, got {other:?}"),
-    }
-}
-
-const COUNTER: &[Sample] = &[
-    ("a", 60, 10.),
-    ("a", 120, 20.),
-    ("a", 180, 5.),
-    ("a", 240, 15.),
-];
-
-// rate/increase correct the reset at 180s and extrapolate half an interval at
-// most; delta treats the same samples as a gauge.
-#[test]
-fn range_functions_follow_prometheus_extrapolation_and_resets() {
-    // Reset-corrected increase is 25 over 180s of samples; 60s on each side extrapolates.
-    let increase = 25. * (180. + 60. + 60.) / 180.;
-    assert!((one("increase(m[5m])", COUNTER, 300) - increase).abs() < 1e-9);
-    assert!((one("rate(m[5m])", COUNTER, 300) - increase / 300.).abs() < 1e-12);
-    let delta = 5. * (180. + 60. + 60.) / 180.;
-    assert!((one("delta(m[5m])", COUNTER, 300) - delta).abs() < 1e-9);
-    // Fewer than two samples yield no rate.
-    assert!(values("rate(m[2m])", COUNTER, 300).is_empty());
-    for (query, expected) in [
-        ("sum_over_time(m[5m])", 50.),
-        ("avg_over_time(m[5m])", 12.5),
-        ("min_over_time(m[5m])", 5.),
-        ("max_over_time(m[5m])", 20.),
-        ("count_over_time(m[5m])", 4.),
-    ] {
-        assert_eq!(one(query, COUNTER, 300), expected, "{query}");
-    }
-}
-
-// Ranges are left-open: a sample at `t - range` is excluded, one at `t` is included.
-#[test]
-fn ranges_exclude_their_start_and_offsets_shift_them() {
-    let samples = &[("a", 60, 1.), ("a", 90, 1.), ("a", 120, 1.), ("a", 150, 1.)];
-    assert_eq!(one("count_over_time(m[1m])", samples, 120), 2.);
-    // offset 1m reads (60s, 120s] at 180s; output keeps the evaluation time.
-    let rows = run("count_over_time(m[1m] offset 1m)", samples, 180).unwrap();
-    assert_eq!(rows, vec![("a".into(), 180_000, 2.)]);
-}
-
-// A bare selector takes the latest sample within the lookback; a stale marker
-// hides the series rather than exposing an older value.
-#[test]
-fn instant_selection_uses_lookback_and_stale_markers() {
-    let stale = f64::from_bits(0x7ff0_0000_0000_0002);
-    let samples = &[("a", 0, 1.), ("a", 30, 2.), ("b", 30, 3.), ("b", 50, stale)];
-    assert_eq!(values("m", samples, 60), vec![("a".into(), 2.)]);
-    // The lookback (30s, 90s] excludes the sample at 30s.
-    assert!(values("m", samples, 90).is_empty());
-    // Range functions skip stale markers.
-    assert_eq!(
-        values("sum_over_time(m[1m])", samples, 60),
-        vec![("a".into(), 2.), ("b".into(), 3.)]
-    );
-}
-
-// NaN samples follow Prometheus: min/max skip them, sums propagate them.
-#[test]
-fn nan_samples() {
-    let samples = &[("a", 10, f64::NAN), ("a", 20, 3.), ("a", 30, 1.)];
-    assert_eq!(one("max_over_time(m[1m])", samples, 60), 3.);
-    assert_eq!(one("min_over_time(m[1m])", samples, 60), 1.);
-    assert!(one("sum_over_time(m[1m])", samples, 60).is_nan());
-}
-
-// Aggregation over no series is an empty vector, not one zero or null row;
-// sort_desc orders the selected series.
-#[test]
-fn cross_series_aggregates_and_empty_inputs() {
-    let samples = &[("a", 50, 1.), ("b", 40, 2.), ("b", 55, 4.)];
-    assert_eq!(values("sum(m)", samples, 60), vec![(String::new(), 5.)]);
-    assert_eq!(values("count(m)", samples, 60), vec![(String::new(), 2.)]);
-    assert_eq!(
-        values("max by (job) (m)", samples, 60),
-        vec![("a".into(), 1.), ("b".into(), 4.)]
-    );
-    assert_eq!(
-        values("sort_desc(m)", samples, 60),
-        vec![("b".into(), 4.), ("a".into(), 1.)]
-    );
-    // topk by (job) keeps the top series of each job, not one overall.
-    let jobs = &[("a", 50, 1.), ("b", 50, 2.)];
-    let mut top = values("topk by (job) (1, m)", jobs, 60);
-    top.sort_by(|x, y| x.0.cmp(&y.0));
-    assert_eq!(top, vec![("a".into(), 1.), ("b".into(), 2.)]);
-    assert_eq!(values("topk(1, m)", jobs, 60), vec![("b".into(), 2.)]);
-    for query in ["sum(m)", "count(m)", "max(m)", "sum by (job) (rate(m[5m]))"] {
-        assert!(values(query, &[], 60).is_empty(), "{query}");
-    }
-}
-
-// scalar() is the single series' value and NaN otherwise; vector() needs no input.
-#[test]
-fn scalar_and_vector_bridges() {
-    assert_eq!(one("scalar(m)", &[("a", 50, 7.)], 60), 7.);
-    assert!(one("scalar(m)", &[("a", 50, 7.), ("b", 50, 8.)], 60).is_nan());
-    assert!(one("scalar(m)", &[], 60).is_nan());
-    assert_eq!(
-        run("vector(3)", &[], 60).unwrap(),
-        vec![(String::new(), 60_000, 3.)]
-    );
-    assert_eq!(
-        values("2 - m", &[("a", 50, 7.)], 60),
-        vec![("a".into(), -5.)]
-    );
-    assert_eq!(
-        values("m * 2", &[("a", 50, 7.)], 60),
-        vec![("a".into(), 14.)]
-    );
-}
-
-// Subquery steps are absolute multiples of the resolution in the left-open
-// range; each step evaluates the operand, and the outer function reduces them.
-#[test]
-fn subqueries_evaluate_their_operand_on_the_aligned_grid() {
-    // Steps 60..300: selections 1, 7, 3, (none at 240s), 4.
-    let samples = &[
-        ("a", 50, 1.),
-        ("a", 110, 7.),
-        ("a", 170, 3.),
-        ("a", 290, 4.),
-    ];
-    assert_eq!(one("max_over_time(m[5m:1m])", samples, 300), 7.);
-    assert_eq!(one("count_over_time(m[5m:1m])", samples, 300), 4.);
-    // At 190s the steps are 60, 120, 180 (not 70, 130, 190): counts 1 + 2 + 2.
-    let samples = &[("a", 30, 1.), ("a", 90, 1.), ("a", 150, 1.), ("a", 185, 1.)];
-    assert_eq!(
-        one("sum_over_time(count_over_time(m[2m])[3m:1m])", samples, 190),
-        5.
-    );
-    // offset 1m moves the grid to (-50s, 130s]: steps 0, 60, 120 count 0 + 1 + 2.
-    assert_eq!(
-        one(
-            "sum_over_time(count_over_time(m[2m])[3m:1m] offset 1m)",
-            samples,
-            190
-        ),
-        3.
-    );
-}
-
-// Subquery work is bounded by the query: at most 100000 steps.
-#[test]
-fn dense_subquery_grids_are_rejected() {
-    assert!(compile_query("max_over_time(m[100s:1ms])").is_ok());
-    assert!(compile_query("max_over_time(m[30d:1ms])").is_err());
-}
-
-// The deployment must supply the selector's raw rows under the documented slot
-// with the exact selector schema; unsupported shapes stay rejected.
-#[test]
-fn raw_series_contract_is_explicit() {
-    let expression = lower("rate(m[5m])");
-    let dag = fallback_dag(expression.clone());
-    let root = u64::from(dag.roots[0].0);
-    let [(selector, schema)] = promql_fallback::raw_series(&expression)
-        .unwrap()
-        .try_into()
-        .unwrap();
-    assert!(matches!(
-        selector.expect_non_asap(),
-        planner_types::ir::NonASAPOp::TimeRange { .. }
-    ));
-    let missing = compile(&dag, BTreeMap::new(), &[root]).err().unwrap();
-    assert!(missing.to_string().contains("raw series input"));
-    let mut wrong = (*schema).clone();
-    wrong.fields.pop();
-    let wrong = compile(
-        &dag,
-        BTreeMap::from([(
-            promql_fallback::raw_series_input(root, 0),
-            InputContract::bounded(std::sync::Arc::new(wrong)),
-        )]),
-        &[root],
-    );
-    assert!(wrong.is_err());
-    // A consumed bare selector is raw range rows for its consumer; it is not
-    // turned into instant selection.
-    let selector = lower("m");
-    let _schema = lift_plain(&selector.schema.clone());
-    let consumed = planner_types::ir::OperatorNode::new_shared(
-        planner_types::ir::Operator::NonASAP(planner_types::ir::NonASAPOp::Limit {
-            n: Some(1),
-            offset: 0,
-            partition_by: Default::default(),
-            child: selector.clone(),
-        }),
-    )
-    .unwrap();
-    let consumed = fallback_dag(consumed.clone());
-    let raw = promql_fallback::raw_series(&selector).unwrap().remove(0).1;
-    assert!(compile(
-        &consumed,
-        BTreeMap::from([(
-            promql_fallback::raw_series_input(u64::from(consumed.roots[0].0), 0),
-            InputContract::bounded(raw)
-        )]),
-        &consumed
-            .roots
-            .iter()
-            .map(|r| u64::from(r.0))
-            .collect::<Vec<_>>()
-    )
-    .is_ok());
-    // Implicit subquery resolution belongs to the deployment's evaluation interval.
-    assert!(compile_query("max_over_time(m[5m:])").is_err());
-}
-
-// irate/idelta use the last two samples (irate corrects a reset to the last
-// value); changes/resets count value changes and decreases; quantile_over_time
-// interpolates; all skip stale markers.
-#[test]
-fn instant_and_counting_range_functions() {
-    // COUNTER in (0s, 300s]: 10, 20, 5, 15.
-    assert!((one("irate(m[5m])", COUNTER, 300) - 10. / 60.).abs() < 1e-12);
-    assert_eq!(one("idelta(m[5m])", COUNTER, 300), 10.);
-    // At 200s the last pair 20 -> 5 is a reset: irate uses 5 as the increase.
-    assert!((one("irate(m[5m])", COUNTER, 200) - 5. / 60.).abs() < 1e-12);
-    assert_eq!(one("idelta(m[5m])", COUNTER, 200), -15.);
-    assert!(values("irate(m[1m])", COUNTER, 300).is_empty());
-    assert_eq!(one("changes(m[5m])", COUNTER, 300), 3.);
-    assert_eq!(one("resets(m[5m])", COUNTER, 300), 1.);
-    assert_eq!(one("changes(m[2m])", COUNTER, 300), 0.);
-    // NaN to NaN is not a change; any other transition involving NaN is.
-    let flat = &[
-        ("a", 10, 1.),
-        ("a", 20, 1.),
-        ("a", 30, 2.),
-        ("a", 40, f64::NAN),
-        ("a", 50, f64::NAN),
-        ("a", 55, 1.),
-    ];
-    assert_eq!(one("changes(m[1m])", flat, 60), 3.);
-    let stale = f64::from_bits(0x7ff0_0000_0000_0002);
-    let ended = &[("a", 240, 15.), ("a", 250, stale)];
-    assert_eq!(one("last_over_time(m[5m])", ended, 300), 15.);
-    assert!(values("m", ended, 300).is_empty());
-    // Sorted 5, 10, 15, 20: rank 1.5 and 0.75; outside [0, 1] is +-Inf.
-    assert_eq!(one("quantile_over_time(0.5, m[5m])", COUNTER, 300), 12.5);
-    assert_eq!(one("quantile_over_time(0.25, m[5m])", COUNTER, 300), 8.75);
-    assert_eq!(
-        one("quantile_over_time(2, m[5m])", COUNTER, 300),
-        f64::INFINITY
-    );
-    assert_eq!(
-        one("quantile_over_time(-1, m[5m])", COUNTER, 300),
-        f64::NEG_INFINITY
-    );
-}
-
-// `@ <t>` evaluates the selector or subquery at `t`, minus any offset, and the
-// result keeps the query's evaluation time.
-#[test]
-fn at_modifier_fixes_the_evaluation_instant() {
-    let samples = &[("a", 60, 1.), ("a", 120, 2.), ("a", 180, 3.)];
-    assert_eq!(
-        run("m @ 120", samples, 1000).unwrap(),
-        vec![("a".into(), 1_000_000, 2.)]
-    );
-    assert!(values("m", samples, 1000).is_empty());
-    assert_eq!(one("count_over_time(m[2m] @ 180)", samples, 1000), 2.);
-    assert_eq!(one("m @ 180 offset 1m", samples, 1000), 2.);
-    // The subquery grid is (60s, 180s]: steps 120 and 180 select 2 and 3.
-    assert_eq!(one("max_over_time(m[2m:1m] @ 180)", samples, 1000), 3.);
-    assert_eq!(
-        one("sum_over_time(m[2m:1m] @ 180 offset 1m)", samples, 1000),
-        3.
-    );
-    // An inner @ pins every step to the same instant.
-    assert_eq!(one("sum_over_time((m @ 60)[2m:1m])", samples, 180), 2.);
-    // start() and end() depend on the range query, which is the deployment's.
-    assert!(evaluate("m @ start()", &[], 60)
-        .unwrap_err()
-        .contains("query range bounds"));
-}
-
-const A: &[Sample] = &[("job=x", 50, 10.), ("job=y", 50, 20.), ("job=w", 50, 0.)];
-const B: &[Sample] = &[("job=x", 50, 2.), ("job=z", 50, 5.), ("job=w", 50, 0.)];
-
-// Vector-vector arithmetic matches series one-to-one on label sets without
-// the metric name, and the result drops the metric name.
-#[test]
-fn vector_arithmetic_matches_label_sets() {
-    let metrics = &[("a", A), ("b", B)];
-    let quotient = labeled("a / b", metrics, 60);
-    assert_eq!(quotient.len(), 2);
-    assert_eq!(quotient[0].0, "job=w");
-    assert!(quotient[0].1.is_nan(), "0 / 0 is NaN");
-    assert_eq!(quotient[1], ("job=x".into(), 5.));
-    // Each selector reads its own raw rows, even a repeated metric.
-    assert_eq!(
-        labeled("(a - b) * a", metrics, 60),
-        vec![("job=w".into(), 0.), ("job=x".into(), 80.)]
-    );
-    assert_eq!(
-        labeled("sum by (job) (a) - sum by (job) (b)", metrics, 60),
-        vec![("job=w".into(), 0.), ("job=x".into(), 8.)]
-    );
-    // Rates of two counters over their own windows.
-    let up: &[Sample] = &[("job=x", 0, 0.), ("job=x", 60, 60.)];
-    let down: &[Sample] = &[("job=x", 0, 0.), ("job=x", 60, 30.)];
-    assert_eq!(
-        labeled("rate(a[2m]) / rate(b[2m])", &[("a", up), ("b", down)], 60),
-        vec![("job=x".into(), 2.)]
-    );
-}
-
-// on() keeps only the listed labels and ignoring() drops them; a duplicate
-// match group is an error unless the left duplicates never match.
-#[test]
-fn on_and_ignoring_select_the_matching_labels() {
-    let a: &[Sample] = &[("job=x,inst=1", 50, 10.)];
-    let b: &[Sample] = &[("job=x,inst=2", 50, 4.)];
-    let metrics = &[("a", a), ("b", b)];
-    assert!(labeled("a - b", metrics, 60).is_empty());
-    assert_eq!(
-        labeled("a - on(job) b", metrics, 60),
-        vec![("job=x".into(), 6.)]
-    );
-    assert_eq!(
-        labeled("a - ignoring(inst) b", metrics, 60),
-        vec![("job=x".into(), 6.)]
-    );
-    let pair: &[Sample] = &[("job=x,inst=1", 50, 1.), ("job=x,inst=2", 50, 2.)];
-    let other: &[Sample] = &[("job=y", 50, 1.)];
-    assert!(evaluate("a + on(job) b", &[("a", a), ("b", pair)], 60).is_err());
-    assert!(evaluate("a + on(job) b", &[("a", pair), ("b", b)], 60).is_err());
-    assert!(labeled("a + on(job) b", &[("a", pair), ("b", other)], 60).is_empty());
-}
-
-// without() groups by every label except the listed ones and the metric name.
-#[test]
-fn without_grouping_drops_labels_and_the_name() {
-    let a: &[Sample] = &[
-        ("job=x,inst=1", 50, 1.),
-        ("job=x,inst=2", 50, 2.),
-        ("job=y,inst=1", 50, 4.),
-    ];
-    let metrics = &[("a", a)];
-    assert_eq!(
-        labeled("sum without (inst) (a)", metrics, 60),
-        vec![("job=x".into(), 3.), ("job=y".into(), 4.)]
-    );
-    assert_eq!(
-        labeled("count without (inst) (a)", metrics, 60),
-        vec![("job=x".into(), 2.), ("job=y".into(), 1.)]
-    );
-    assert_eq!(
-        labeled("max without (job, inst) (a)", metrics, 60),
-        vec![(String::new(), 4.)]
-    );
-    assert!(labeled("sum without (inst) (a)", &[], 60).is_empty());
-    // Series equal without the name share a group rather than colliding.
-    let named: &[Sample] = &[
-        ("job=x,inst=1", 50, 1.),
-        ("__name__=b,job=x,inst=1", 50, 2.),
-    ];
-    assert_eq!(
-        labeled("sum without (inst) (a)", &[("a", named)], 60),
-        vec![("job=x".into(), 3.)]
-    );
-}
-
-// Arithmetic with a literal drops the metric name; series that then share a
-// label set are an error, as in Prometheus.
-#[test]
-fn literal_arithmetic_drops_the_name_and_rejects_equal_label_sets() {
-    let a: &[Sample] = &[
-        ("job=x,inst=1", 50, 1.),
-        ("__name__=b,job=x,inst=2", 50, 2.),
-    ];
-    assert_eq!(
-        labeled("a * 2", &[("a", a)], 60),
-        vec![("inst=1,job=x".into(), 2.), ("inst=2,job=x".into(), 4.)]
-    );
-    let equal: &[Sample] = &[("job=x", 50, 1.), ("__name__=b,job=x", 50, 2.)];
-    let error = evaluate("a * 2", &[("a", equal)], 60).unwrap_err();
-    assert!(error.contains("same labelset"), "{error}");
-}
-
-// An empty label value is an absent label, and an empty side yields an empty
-// result before any duplicate check, as in Prometheus.
-#[test]
-fn empty_labels_and_empty_sides_match_prometheus() {
-    let a: &[Sample] = &[("job=x,env=", 50, 3.)];
-    let b: &[Sample] = &[("job=x", 50, 1.)];
-    assert_eq!(
-        labeled("a + b", &[("a", a), ("b", b)], 60),
-        vec![("job=x".into(), 4.)]
-    );
-    let pair: &[Sample] = &[("job=x,inst=1", 50, 1.), ("job=x,inst=2", 50, 2.)];
-    assert!(labeled("a + on(job) b", &[("b", pair)], 60).is_empty());
-    assert!(labeled("b + on(job) a", &[("b", pair)], 60).is_empty());
-    assert!(labeled("a - time()", &[], 60).is_empty());
-}
-
-// Sums and averages use Prometheus' Kahan-Neumaier compensation, and an
-// average whose running sum overflows switches to an incremental mean.
-#[test]
-fn sums_and_averages_are_compensated_like_prometheus() {
-    let cancel = &[("a", 10, 1e100), ("a", 20, 1.), ("a", 30, -1e100)];
-    assert_eq!(one("sum_over_time(m[1m])", cancel, 60), 1.);
-    assert_eq!(one("avg_over_time(m[1m])", cancel, 60), 1. / 3.);
-    let huge = &[("a", 10, 1.7e308), ("a", 20, 1.7e308)];
-    assert_eq!(one("avg_over_time(m[1m])", huge, 60), 1.7e308);
-    assert_eq!(one("sum_over_time(m[1m])", huge, 60), f64::INFINITY);
-    let infinite = &[("a", 10, f64::INFINITY), ("a", 20, 1.)];
-    assert_eq!(one("sum_over_time(m[1m])", infinite, 60), f64::INFINITY);
-    assert_eq!(one("avg_over_time(m[1m])", infinite, 60), f64::INFINITY);
-    let opposite = &[("a", 10, f64::INFINITY), ("a", 20, f64::NEG_INFINITY)];
-    assert!(one("sum_over_time(m[1m])", opposite, 60).is_nan());
-    assert!(one("avg_over_time(m[1m])", opposite, 60).is_nan());
-    let cancel = &[("a", 50, 1e100), ("b", 50, 1.), ("c", 50, -1e100)];
-    assert_eq!(one("sum(m)", cancel, 60), 1.);
-    assert_eq!(one("avg(m)", cancel, 60), 1. / 3.);
-    let huge = &[("a", 50, 1.7e308), ("b", 50, 1.7e308)];
-    assert_eq!(one("avg(m)", huge, 60), 1.7e308);
-}
-
-/// `(k=v,... sorted, value)` rows for readable expectations.
-fn rows(pairs: &[(&str, f64)]) -> Vec<(String, f64)> {
-    let mut rows = pairs
-        .iter()
-        .map(|(spec, value)| (spec.to_string(), *value))
-        .collect::<Vec<_>>();
-    rows.sort_by(|a, b| a.0.cmp(&b.0));
-    rows
-}
-
-/// `labeled`, with NaN values rendered comparable.
-fn labeled_nan(query: &str, metrics: &[(&str, &[Sample])], at: i64) -> Vec<(String, String)> {
-    labeled(query, metrics, at)
-        .into_iter()
-        .map(|(labels, value)| (labels, format!("{value:?}")))
-        .collect()
-}
-
-const C: &[Sample] = &[
-    ("job=x", 50, 10.),
-    ("job=y", 50, 20.),
-    ("job=w", 50, 0.),
-    ("job=n", 50, f64::NAN),
-];
-
-// A comparison with a scalar keeps the matching series with their value and
-// metric name, whichever side the scalar is on; `bool` yields 1 or 0 for every
-// series and drops the name. NaN compares unequal to everything.
-#[test]
-fn scalar_comparisons_filter_or_return_bool() {
-    let metrics = &[("a", C)];
-    let kept = rows(&[("__name__=a,job=x", 10.), ("__name__=a,job=y", 20.)]);
-    assert_eq!(labeled("a > 5", metrics, 60), kept);
-    assert_eq!(labeled("5 < a", metrics, 60), kept);
-    assert_eq!(
-        labeled("a <= 10", metrics, 60),
-        rows(&[("__name__=a,job=w", 0.), ("__name__=a,job=x", 10.)])
-    );
-    assert_eq!(
-        labeled("a > bool 5", metrics, 60),
-        rows(&[("job=n", 0.), ("job=w", 0.), ("job=x", 1.), ("job=y", 1.)])
-    );
-    assert_eq!(
-        labeled("10 == bool a", metrics, 60),
-        rows(&[("job=n", 0.), ("job=w", 0.), ("job=x", 1.), ("job=y", 0.)])
-    );
-    // scalar() of no series is NaN.
-    assert_eq!(labeled("a != scalar(b)", metrics, 60).len(), 4);
-    assert!(labeled("a == scalar(b)", metrics, 60).is_empty());
-    assert!(labeled("a > 5", &[], 60).is_empty());
-    // Only `bool` drops the name, so only it can make label sets collide.
-    let equal: &[Sample] = &[("job=x", 50, 1.), ("__name__=b,job=x", 50, 2.)];
-    assert_eq!(labeled("a > 0", &[("a", equal)], 60).len(), 2);
-    let error = evaluate("a > bool 0", &[("a", equal)], 60).unwrap_err();
-    assert!(error.contains("same labelset"), "{error}");
-}
-
-// Vector comparisons match one-to-one like arithmetic. A filter keeps the
-// left series, name included, unless `on` reduces its labels; `bool` drops the
-// name. A left duplicate is an error only if more than one of it is kept.
-#[test]
-fn vector_comparisons_match_one_to_one() {
-    let metrics = &[("a", A), ("b", B)];
-    assert_eq!(
-        labeled("a > b", metrics, 60),
-        rows(&[("__name__=a,job=x", 10.)])
-    );
-    assert_eq!(
-        labeled("a >= b", metrics, 60),
-        rows(&[("__name__=a,job=w", 0.), ("__name__=a,job=x", 10.)])
-    );
-    assert_eq!(
-        labeled("a > bool b", metrics, 60),
-        rows(&[("job=w", 0.), ("job=x", 1.)])
-    );
-    assert!(labeled("a < b", metrics, 60).is_empty());
-    let a: &[Sample] = &[("job=x,inst=1", 50, 10.)];
-    let b: &[Sample] = &[("job=x,inst=2", 50, 4.)];
-    let metrics = &[("a", a), ("b", b)];
-    assert_eq!(
-        labeled("a > on(job) b", metrics, 60),
-        rows(&[("job=x", 10.)])
-    );
-    assert_eq!(
-        labeled("a > ignoring(inst) b", metrics, 60),
-        rows(&[("__name__=a,job=x", 10.)])
-    );
-    let pair: &[Sample] = &[("job=x,inst=1", 50, 1.), ("job=x,inst=2", 50, 5.)];
-    let metrics = &[("a", pair), ("b", b)];
-    assert_eq!(
-        labeled("a > on(job) b", metrics, 60),
-        rows(&[("job=x", 5.)])
-    );
-    let error = evaluate("a > bool on(job) b", metrics, 60).unwrap_err();
-    assert!(error.contains("many-to-one"), "{error}");
-    let nan: &[Sample] = &[("job=x", 50, f64::NAN)];
-    let metrics = &[("a", nan), ("b", nan)];
-    assert_eq!(labeled("a == bool b", metrics, 60), rows(&[("job=x", 0.)]));
-    assert_eq!(
-        labeled_nan("a != b", metrics, 60),
-        vec![("__name__=a,job=x".into(), "NaN".into())]
-    );
-}
-
-const S: &[Sample] = &[
-    ("job=x", 50, 1.),
-    ("job=y", 50, 2.),
-    ("job=z,inst=1", 50, 3.),
-];
-const T: &[Sample] = &[
-    ("job=x", 50, 10.),
-    ("job=w", 50, 20.),
-    ("job=z,inst=2", 50, 30.),
-];
-
-// Set operators match label sets many-to-many, ignoring the name by default,
-// and return the original series unchanged.
-#[test]
-fn set_operators_match_label_sets() {
-    let metrics = &[("a", S), ("b", T)];
-    assert_eq!(
-        labeled("a and b", metrics, 60),
-        rows(&[("__name__=a,job=x", 1.)])
-    );
-    assert_eq!(
-        labeled("a and on(job) b", metrics, 60),
-        rows(&[("__name__=a,job=x", 1.), ("__name__=a,inst=1,job=z", 3.)])
-    );
-    assert_eq!(
-        labeled("a and ignoring(inst) b", metrics, 60),
-        labeled("a and on(job) b", metrics, 60)
-    );
-    assert_eq!(
-        labeled("a or b", metrics, 60),
-        rows(&[
-            ("__name__=a,job=x", 1.),
-            ("__name__=a,job=y", 2.),
-            ("__name__=a,inst=1,job=z", 3.),
-            ("__name__=b,job=w", 20.),
-            ("__name__=b,inst=2,job=z", 30.),
-        ])
-    );
-    assert_eq!(
-        labeled("a or on(job) b", metrics, 60),
-        rows(&[
-            ("__name__=a,job=x", 1.),
-            ("__name__=a,job=y", 2.),
-            ("__name__=a,inst=1,job=z", 3.),
-            ("__name__=b,job=w", 20.),
-        ])
-    );
-    assert_eq!(
-        labeled("a unless b", metrics, 60),
-        rows(&[("__name__=a,job=y", 2.), ("__name__=a,inst=1,job=z", 3.)])
-    );
-    assert_eq!(
-        labeled("a unless on(job) b", metrics, 60),
-        rows(&[("__name__=a,job=y", 2.)])
-    );
-    assert_eq!(labeled("a and on() b", metrics, 60).len(), 3);
-    // Empty sides, and duplicates on either side, which set operators allow.
-    let a_only = &[("a", S)];
-    assert!(labeled("a and b", a_only, 60).is_empty());
-    assert_eq!(labeled("a unless b", a_only, 60).len(), 3);
-    assert_eq!(labeled("b or a", a_only, 60).len(), 3);
-    let pair: &[Sample] = &[("job=x,inst=1", 50, 1.), ("job=x,inst=2", 50, f64::NAN)];
-    assert_eq!(
-        labeled_nan("a and on(job) b", &[("a", pair), ("b", pair)], 60),
-        vec![
-            ("__name__=a,inst=1,job=x".into(), "1.0".into()),
-            ("__name__=a,inst=2,job=x".into(), "NaN".into()),
-        ]
-    );
-}
-
-const MANY: &[Sample] = &[
-    ("job=x,inst=1", 50, 2.),
-    ("job=x,inst=2", 50, 3.),
-    ("job=y,inst=1", 50, 4.),
-];
-const ONE: &[Sample] = &[("job=x,team=t1", 50, 10.), ("job=y", 50, 100.)];
-
-// group_left/group_right match many series to one; the result keeps the many
-// side's labels plus the listed labels of the one side, which a missing label
-// removes. A filter keeps the left value.
-#[test]
-fn group_modifiers_match_many_to_one() {
-    let metrics = &[("a", MANY), ("info", ONE)];
-    assert_eq!(
-        labeled("a * on(job) group_left(team) info", metrics, 60),
-        rows(&[
-            ("inst=1,job=x,team=t1", 20.),
-            ("inst=2,job=x,team=t1", 30.),
-            ("inst=1,job=y", 400.),
-        ])
-    );
-    assert_eq!(
-        labeled("info - on(job) group_right a", metrics, 60),
-        rows(&[
-            ("inst=1,job=x", 8.),
-            ("inst=2,job=x", 7.),
-            ("inst=1,job=y", 96.)
-        ])
-    );
-    assert_eq!(
-        labeled("info > on(job) group_right a", metrics, 60),
-        rows(&[
-            ("__name__=a,inst=1,job=x", 10.),
-            ("__name__=a,inst=2,job=x", 10.),
-            ("__name__=a,inst=1,job=y", 100.),
-        ])
-    );
-    assert_eq!(
-        labeled("a > bool ignoring(inst, team) group_left info", metrics, 60),
-        rows(&[
-            ("inst=1,job=x", 0.),
-            ("inst=2,job=x", 0.),
-            ("inst=1,job=y", 0.)
-        ])
-    );
-    // Two "one" series for a match group, or two results with equal labels.
-    let two: &[Sample] = &[("job=x,team=t1", 50, 1.), ("job=x,team=t2", 50, 2.)];
-    let error = evaluate(
-        "a * on(job) group_left info",
-        &[("a", MANY), ("info", two)],
-        60,
-    )
-    .unwrap_err();
-    assert!(error.contains("duplicate series"), "{error}");
-    let error = evaluate(
-        "info * on(job) group_right a",
-        &[("a", two), ("info", MANY)],
-        60,
-    )
-    .unwrap_err();
-    assert!(error.contains("left hand-side"), "{error}");
-    let named: &[Sample] = &[("job=x", 50, 1.), ("__name__=c,job=x", 50, 2.)];
-    let error = evaluate(
-        "a * on(job) group_left info",
-        &[("a", named), ("info", ONE)],
-        60,
-    )
-    .unwrap_err();
-    assert!(error.contains("unique matches"), "{error}");
-    assert!(labeled("a * on(job) group_left info", &[("a", MANY)], 60).is_empty());
-}
-
-// A non-literal scalar applies like a literal; scalar-scalar arithmetic yields
-// a scalar; and a literal applies to aggregated rows whose value has another name.
-#[test]
-fn scalar_operands_and_aggregates() {
-    let three: &[Sample] = &[("job=b", 50, 3.)];
-    let metrics = &[("a", A), ("b", three)];
-    assert_eq!(
-        labeled("a * scalar(b)", metrics, 60),
-        rows(&[("job=w", 0.), ("job=x", 30.), ("job=y", 60.)])
-    );
-    assert_eq!(
-        labeled("a > scalar(b)", metrics, 60),
-        rows(&[("__name__=a,job=x", 10.), ("__name__=a,job=y", 20.)])
-    );
-    assert_eq!(labeled("scalar(b) * 2", metrics, 60), rows(&[("", 6.)]));
-    assert_eq!(
-        labeled("scalar(b) > bool 2", metrics, 60),
-        rows(&[("", 1.)])
-    );
-    // scalar() of several series is NaN.
-    assert!(labeled("scalar(a) - 1", metrics, 60)[0].1.is_nan());
-    assert_eq!(
-        labeled("sum by (job) (a) * 2", metrics, 60),
-        rows(&[("job=w", 0.), ("job=x", 20.), ("job=y", 40.)])
-    );
-    assert_eq!(
-        labeled("sum by (job) (a) > bool 5", metrics, 60),
-        rows(&[("job=w", 0.), ("job=x", 1.), ("job=y", 1.)])
-    );
-}
-
-// Range functions other than last_over_time drop the metric name, so series
-// that then share a label set are an error, as in Prometheus.
-#[test]
-fn range_functions_drop_the_name_and_reject_equal_label_sets() {
-    let equal: &[Sample] = &[
-        ("job=x", 10, 1.),
-        ("job=x", 50, 2.),
-        ("__name__=b,job=x", 10, 1.),
-        ("__name__=b,job=x", 50, 4.),
-    ];
-    let error = evaluate("rate(a[1m])", &[("a", equal)], 60).unwrap_err();
-    assert!(error.contains("same labelset"), "{error}");
-    assert_eq!(
-        labeled("last_over_time(a[1m])", &[("a", equal)], 60),
-        rows(&[("__name__=a,job=x", 2.), ("__name__=b,job=x", 4.)])
-    );
-    assert_eq!(
-        labeled("max_over_time(a[1m])", &[("a", &equal[..2])], 60),
-        rows(&[("job=x", 2.)])
-    );
-}
-
-// Scalar-valued expressions are scalars too; `or vector(0)` fills an empty
-// aggregate; a range function inside a subquery drops the name.
-#[test]
-fn scalar_expressions_or_vector_and_subquery_names() {
-    let three: &[Sample] = &[("job=b", 50, 3.)];
-    let metrics = &[("a", A), ("b", three)];
-    assert_eq!(
-        labeled("a + (scalar(b) * 2)", metrics, 60),
-        rows(&[("job=w", 6.), ("job=x", 16.), ("job=y", 26.)])
-    );
-    assert_eq!(
-        labeled("a + -scalar(b)", metrics, 60),
-        rows(&[("job=w", -3.), ("job=x", 7.), ("job=y", 17.)])
-    );
-    assert_eq!(
-        labeled("sum(a) or vector(0)", metrics, 60),
-        rows(&[("", 30.)])
-    );
-    assert_eq!(labeled("sum(a) or vector(0)", &[], 60), rows(&[("", 0.)]));
-    let counter: &[Sample] = &[("job=x", 0, 0.), ("job=x", 30, 3.), ("job=x", 60, 6.)];
-    let result = labeled("last_over_time(rate(a[1m])[2m:1m])", &[("a", counter)], 60);
-    assert_eq!(result.len(), 1);
-    assert_eq!(result[0].0, "job=x");
-}
-
-/// Instant `x_bucket` samples at 50s: `(labels without le, [(le, count)])`.
-fn buckets(series: &[(&'static str, &[(&'static str, f64)])]) -> Vec<Sample> {
-    series
-        .iter()
-        .flat_map(|(labels, buckets)| {
-            buckets.iter().map(move |(le, count)| {
-                let spec = if labels.is_empty() {
-                    format!("le={le}")
-                } else {
-                    format!("{labels},le={le}")
-                };
-                (&*Box::leak(spec.into_boxed_str()), 50, *count)
-            })
-        })
-        .collect()
-}
-
-fn quantile(query: &str, samples: &[Sample]) -> Vec<(String, f64)> {
-    labeled(query, &[("x_bucket", samples)], 60)
-}
-
-const HISTOGRAM: &[(&str, f64)] = &[("1", 2.), ("2", 6.), ("4", 8.), ("+Inf", 10.)];
-
-// histogram_quantile interpolates linearly within the bucket holding rank q·count,
-// returns the highest finite bound for the +Inf bucket, and maps q outside
-// [0, 1] to ∓Inf and a NaN q to NaN. Output labels drop le and __name__.
-#[test]
-fn histogram_quantile_interpolates_classic_buckets() {
-    let samples = buckets(&[("job=a", HISTOGRAM)]);
-    for (q, expected) in [
-        ("0", 0.),
-        ("0.1", 0.5),
-        ("0.5", 1.75),
-        ("0.9", 4.),
-        ("1", 4.),
-        ("-0.5", f64::NEG_INFINITY),
-        ("1.5", f64::INFINITY),
-    ] {
-        let query = format!("histogram_quantile({q}, x_bucket)");
-        assert_eq!(
-            quantile(&query, &samples),
-            vec![("job=a".into(), expected)],
-            "{query}"
-        );
-    }
-    let nan = quantile("histogram_quantile(NaN, x_bucket)", &samples);
-    assert!(matches!(nan.as_slice(), [(labels, v)] if labels == "job=a" && v.is_nan()));
-}
-
-// Each label set other than le is its own histogram. Degenerate histograms
-// yield NaN: no +Inf bucket, fewer than two buckets, or zero observations.
-#[test]
-fn histogram_quantile_groups_series_and_rejects_degenerate_histograms() {
-    let samples = buckets(&[
-        ("job=a", HISTOGRAM),
-        ("job=b", &[("1", 1.), ("2", 2.)]),
-        ("job=c", &[("+Inf", 5.)]),
-        ("job=d", &[("1", 0.), ("+Inf", 0.)]),
-        ("job=e,inst=1", HISTOGRAM),
-    ]);
-    let rows = quantile("histogram_quantile(0.5, x_bucket)", &samples);
-    let labels: Vec<_> = rows.iter().map(|(l, _)| l.as_str()).collect();
-    assert_eq!(
-        labels,
-        vec!["inst=1,job=e", "job=a", "job=b", "job=c", "job=d"]
-    );
-    assert_eq!(rows[0].1, 1.75);
-    assert_eq!(rows[1].1, 1.75);
-    assert!(rows[2..].iter().all(|(_, v)| v.is_nan()), "{rows:?}");
-}
-
-// Buckets sort by bound, unparsable or missing le values are skipped, equal
-// bounds merge, and decreasing cumulative counts are raised to be monotonic.
-#[test]
-fn histogram_quantile_normalizes_buckets_like_prometheus() {
-    let unordered = buckets(&[("job=a", &[("+Inf", 10.), ("4", 8.), ("1", 2.), ("2", 6.)])]);
-    assert_eq!(
-        quantile("histogram_quantile(0.5, x_bucket)", &unordered),
-        vec![("job=a".into(), 1.75)]
-    );
-    let mut invalid = buckets(&[("job=a", &[("abc", 100.), ("1", 2.), ("+Inf", 4.)])]);
-    invalid.push(("job=a", 50, 100.));
-    assert_eq!(
-        quantile("histogram_quantile(0.5, x_bucket)", &invalid),
-        vec![("job=a".into(), 1.)]
-    );
-    // Go's ParseFloat rejects an out-of-range bound rather than rounding it to +Inf.
-    let overflow = buckets(&[("job=a", &[("1", 1.), ("1e400", 2.)])]);
-    let rows = quantile("histogram_quantile(0.5, x_bucket)", &overflow);
-    assert!(
-        matches!(rows.as_slice(), [(_, v)] if v.is_nan()),
-        "{rows:?}"
-    );
-    let duplicate = buckets(&[("job=a", &[("1", 1.), ("1.0", 1.), ("+Inf", 4.)])]);
-    assert_eq!(
-        quantile("histogram_quantile(0.5, x_bucket)", &duplicate),
-        vec![("job=a".into(), 1.)]
-    );
-    // Counts [6, 2→6, 8, 8]: rank 7 lies in (2, 4], 1 of its 2 observations in.
-    let decreasing = buckets(&[("job=a", &[("1", 6.), ("2", 2.), ("4", 8.), ("+Inf", 8.)])]);
-    assert_eq!(
-        quantile("histogram_quantile(0.875, x_bucket)", &decreasing),
-        vec![("job=a".into(), 3.)]
-    );
-}
-
-// A lowest bucket with a non-positive bound is returned as is, not
-// interpolated from zero.
-#[test]
-fn histogram_quantile_non_positive_lowest_bucket() {
-    let samples = buckets(&[("job=a", &[("-1", 2.), ("1", 4.), ("+Inf", 4.)])]);
-    for (q, expected) in [("0.25", -1.), ("0.75", 0.)] {
-        let query = format!("histogram_quantile({q}, x_bucket)");
-        assert_eq!(
-            quantile(&query, &samples),
-            vec![("job=a".into(), expected)],
-            "{query}"
-        );
-    }
-}
-
-// The common shapes: an aggregated rate keeps its by labels other than le, and
-// a per-series rate keeps every label but le and __name__.
-#[test]
-fn histogram_quantile_over_rates_and_sums() {
-    // Each counter grows by c per minute, so its rate is c/60.
-    let counter = |labels: &'static str, le: &str, c: f64| {
-        let spec: &'static str = Box::leak(format!("{labels},le={le}").into_boxed_str());
-        (60..=240)
-            .step_by(60)
-            .map(move |t| (spec, t as i64, c * (t / 60) as f64))
-            .collect::<Vec<Sample>>()
-    };
-    let mut samples = Vec::new();
-    for inst in ["job=a,inst=1", "job=a,inst=2"] {
-        for (le, count) in HISTOGRAM {
-            samples.extend(counter(inst, le, *count));
-        }
-    }
-    let metrics = &[("x_bucket", samples.as_slice())];
-    let close = |rows: Vec<(String, f64)>, expected: &[(&str, f64)]| {
-        assert_eq!(rows.len(), expected.len(), "{rows:?}");
-        for ((labels, v), (want, w)) in rows.iter().zip(expected) {
-            assert_eq!(labels, want);
-            assert!((v - w).abs() < 1e-9, "{labels}: {v} vs {w}");
-        }
-    };
-    close(
-        labeled(
-            "histogram_quantile(0.5, sum by (le, job) (rate(x_bucket[5m])))",
-            metrics,
-            300,
-        ),
-        &[("job=a", 1.75)],
-    );
-    close(
-        labeled(
-            "histogram_quantile(0.5, sum by (le) (x_bucket))",
-            metrics,
-            250,
-        ),
-        &[("", 1.75)],
-    );
-    close(
-        labeled("histogram_quantile(0.5, rate(x_bucket[5m]))", metrics, 300),
-        &[("inst=1,job=a", 1.75), ("inst=2,job=a", 1.75)],
-    );
-}
-
-// Histograms that differ only in __name__ collide once it is dropped, which
-// Prometheus reports as an error rather than merging them.
-#[test]
-fn histogram_quantile_rejects_equal_output_label_sets() {
-    let mut samples = buckets(&[("job=a", HISTOGRAM)]);
-    samples.extend(buckets(&[("__name__=y_bucket,job=a", HISTOGRAM)]));
-    let error = evaluate(
-        "histogram_quantile(0.5, x_bucket)",
-        &[("x_bucket", &samples)],
-        60,
-    )
-    .unwrap_err();
-    assert!(error.contains("same labelset"), "{error}");
-}
-
-// time() uses the query evaluation instant in seconds in scalar and vector operands.
-#[test]
-fn evaluation_time_operands_use_runtime_scope() {
-    assert_eq!(labeled("time()", &[], 60), rows(&[("", 60.)]));
-    assert_eq!(labeled("vector(time())", &[], 60), rows(&[("", 60.)]));
-    assert_eq!(
-        labeled("a + time()", &[("a", A)], 60),
-        rows(&[("job=w", 60.), ("job=x", 70.), ("job=y", 80.)])
-    );
-    assert_eq!(
-        labeled("time() - scalar(b)", &[("b", &[("job=x", 60, 3.)])], 61),
-        rows(&[("", 58.)])
-    );
-}
-
-// Non-finite scalar operands survive both logical and physical plan JSON round trips.
-#[test]
-fn nonfinite_literals_round_trip_in_plans() {
-    for (query, expected) in [
-        ("vector(NaN)", f64::NAN),
-        ("vector(+Inf)", f64::INFINITY),
-        ("vector(-Inf)", f64::NEG_INFINITY),
-    ] {
-        let expression = lower(query);
-        let json = serde_json::to_vec(&expression).unwrap();
-        let restored: Rc<planner_types::ir::OperatorNode> = serde_json::from_slice(&json).unwrap();
-        let result = evaluate_dag(&restored, &fallback_dag(restored.clone()), &[], 60).unwrap();
-        assert_eq!(result.len(), 1);
-        if expected.is_nan() {
-            assert!(result[0].2.is_nan());
-        } else {
-            assert_eq!(result[0].2, expected);
-        }
-    }
-}
-
-// Classic histogram results remain aggregatable and support multi-quantile label branches.
-#[test]
-fn histogram_quantiles_and_nested_aggregation() {
-    let samples = buckets(&[("job=a", HISTOGRAM), ("job=b", HISTOGRAM)]);
-    assert_eq!(
-        quantile("sum(histogram_quantile(0.5, x_bucket))", &samples),
-        rows(&[("", 3.5)])
-    );
-    assert_eq!(
-        quantile("histogram_quantiles(x_bucket, \"q\", 0.5, 0.9)", &samples),
-        rows(&[
-            ("job=a,q=0.5", 1.75),
-            ("job=a,q=0.9", 4.0),
-            ("job=b,q=0.5", 1.75),
-            ("job=b,q=0.9", 4.0)
-        ])
-    );
-}
-
-// Relabeling anchors regexes, expands captures, preserves nonmatches and removes empty labels.
-#[test]
-fn label_replace_preserves_promql_labels() {
-    let samples: &[Sample] = &[
-        ("job=api:one,team=old", 50, 1.0),
-        ("job=other,team=old", 50, 2.0),
-    ];
-    assert_eq!(
-        labeled(
-            "label_replace(a, \"team\", \"$1\", \"job\", \"(.*):.*\")",
-            &[("a", samples)],
-            60
-        ),
-        rows(&[
-            ("__name__=a,job=api:one,team=api", 1.0),
-            ("__name__=a,job=other,team=old", 2.0)
-        ])
-    );
-    assert_eq!(
-        labeled(
-            "label_replace(a, \"team\", \"\", \"job\", \".*\")",
-            &[("a", samples)],
-            60
-        ),
-        rows(&[
-            ("__name__=a,job=api:one", 1.0),
-            ("__name__=a,job=other", 2.0)
-        ])
-    );
-}
-
-// Binary results over aggregates retain labels contributed by the other operand.
-#[test]
-fn binary_aggregates_accept_additional_labels() {
-    let a: &[Sample] = &[("job=x", 50, 2.0)];
-    let info: &[Sample] = &[("job=x,team=blue", 50, 3.0)];
-    assert_eq!(
-        labeled(
-            "sum by(job)(a) * on(job) group_left(team) info",
-            &[("a", a), ("info", info)],
-            60
-        ),
-        rows(&[("job=x,team=blue", 6.0)])
-    );
-    assert_eq!(
-        labeled("sum by(job)(a) or info", &[("a", a), ("info", info)], 60),
-        rows(&[("job=x", 2.0), ("__name__=info,job=x,team=blue", 3.0)])
-    );
-}
-
-// Relabeling handles missing sources and named captures, and rejects label-set collisions.
-#[test]
-fn label_replace_missing_labels_named_captures_and_duplicates() {
-    let a: &[Sample] = &[("job=api:one", 50, 2.)];
-    assert_eq!(
-        labeled(
-            r#"label_replace(a, "team", "${part}", "job", "(?P<part>.*):.*")"#,
-            &[("a", a)],
-            60
-        ),
-        rows(&[("__name__=a,job=api:one,team=api", 2.)])
-    );
-    assert_eq!(
-        labeled(
-            r#"label_replace(a, "team", "unknown", "missing", "^$")"#,
-            &[("a", a)],
-            60
-        ),
-        rows(&[("__name__=a,job=api:one,team=unknown", 2.)])
-    );
-    assert!(evaluate(r#"label_replace(a, "", "x", "job", ".*")"#, &[("a", a)], 60).is_err());
-    let duplicate: &[Sample] = &[("job=a", 50, 1.), ("job=b", 50, 2.)];
-    assert!(evaluate(
-        r#"label_replace(a, "job", "same", "job", ".*")"#,
-        &[("a", duplicate)],
-        60
-    )
-    .unwrap_err()
-    .contains("same labelset"));
-}
-
-// Right-side grouped rows and group_right labels survive an aggregated left schema.
-#[test]
-fn grouped_binary_right_rows_preserve_all_labels() {
-    let a: &[Sample] = &[("job=x", 50, 2.)];
-    let info: &[Sample] = &[("job=x,team=blue", 50, 3.)];
-    let metrics = &[("a", a), ("info", info)];
-    assert_eq!(
-        labeled("sum by(job)(a) * on(job) group_right info", metrics, 60),
-        rows(&[("job=x,team=blue", 6.)])
-    );
-    assert_eq!(
-        labeled("sum by(job)(a) or sum by(job,team)(info)", metrics, 60),
-        rows(&[("job=x", 2.), ("job=x,team=blue", 3.)])
-    );
-    let samples = buckets(&[("job=a", HISTOGRAM)]);
-    assert!(evaluate(
-        r#"histogram_quantiles(x_bucket, "q", 0.5, 0.5)"#,
-        &[("x_bucket", &samples)],
-        60
-    )
-    .unwrap_err()
-    .contains("same labelset"));
-}
-
-// Range-bound anchors compile without freezing the evaluation instant into the plan.
-#[test]
-fn range_bound_anchors_compile() {
-    for query in [
-        "a @ start()",
-        "sum_over_time(a[1m] @ end())",
-        "max_over_time(a[2m:1m] @ start())",
-    ] {
-        assert!(compile_query(query).is_ok(), "{query}");
-    }
-}
-
-// Stored programs resolve outer range anchors per run, including offsets and subquery grids.
-#[test]
-fn range_bound_anchors_use_outer_query_bounds() {
-    let samples: &[Sample] = &[
-        ("job=a", 30, 1.),
-        ("job=a", 60, 2.),
-        ("job=a", 90, 3.),
-        ("job=a", 120, 4.),
-    ];
-    for (query, expected) in [
-        ("a @ start()", 2.),
-        ("a @ end()", 4.),
-        ("a @ start() offset 30s", 1.),
-        ("sum_over_time(a[1m] @ end())", 7.),
-        ("max_over_time(a[2m:1m] @ start())", 2.),
-        ("max_over_time(a[2m:1m] @ end())", 4.),
-        ("max_over_time(a[2m:1m] @ end() offset 1m)", 2.),
-        ("max_over_time(a @ end()[2m:1m])", 4.),
-    ] {
-        let expression = lower(query);
-        let dag = fallback_dag(expression.clone());
-        let output =
-            evaluate_dag_with_range(&expression, &dag, &[("a", samples)], 90, Some((60, 120)))
-                .unwrap();
-        assert_eq!(output.len(), 1, "{query}");
-        assert_eq!(output[0].2, expected, "{query}");
-        assert_eq!(output[0].1, 90_000, "{query}");
-        let error = evaluate_dag(&expression, &dag, &[("a", samples)], 90).unwrap_err();
-        assert!(error.contains("query range bounds"), "{query}: {error}");
-    }
-}
-
-// Regression functions use float samples per series; prediction is anchored
-// at the evaluation time even when offset or @ selects an older window.
-#[test]
-fn regression_range_functions_use_evaluation_time_and_drop_names() {
-    let samples: &[Sample] = &[("job=x", 10, 3.), ("job=x", 30, 7.), ("job=x", 50, 11.)];
-    for (query, at, expected) in [
-        ("deriv(a[1m])", 60, 0.2),
-        ("predict_linear(a[1m], 10)", 60, 15.),
-        ("predict_linear(a[1m] offset 30s, 10)", 90, 21.),
-        ("predict_linear(a[1m] @ 60, 10)", 90, 21.),
-    ] {
-        let result = labeled(query, &[("a", samples)], at);
-        assert_eq!(result.len(), 1, "{query}");
-        assert_eq!(result[0].0, "job=x");
-        assert!(
-            (result[0].1 - expected).abs() < 1e-12,
-            "{query}: {result:?}"
-        );
-    }
-    let constant: &[Sample] = &[("job=x", 10, 1e300), ("job=x", 50, 1e300)];
-    assert_eq!(
-        labeled("deriv(a[1m])", &[("a", constant)], 60),
-        rows(&[("job=x", 0.)])
-    );
-    assert_eq!(
-        labeled("predict_linear(a[1m], 10)", &[("a", constant)], 60),
-        rows(&[("job=x", 1e300)])
-    );
-    assert!(labeled("deriv(a[1m])", &[("a", &samples[..1])], 60).is_empty());
-    let infinite: &[Sample] = &[("job=x", 10, f64::INFINITY), ("job=x", 50, f64::INFINITY)];
-    assert!(labeled("deriv(a[1m])", &[("a", infinite)], 60)[0]
-        .1
-        .is_nan());
-}
-
-// An `@`-pinned range function is step-invariant, as in Prometheus: it is
-// evaluated once, at the query start or at the subquery's first step, so
-// predict_linear's anchor does not move with each evaluation step.
-#[test]
-fn pinned_range_functions_are_step_invariant() {
-    // `a` rises by one per second, sampled every 10 s.
-    let rising: Vec<Sample> = (0..=30)
-        .map(|i| ("job=x", i * 10, (i * 10) as f64))
-        .collect();
-    // (query, range-query bounds, Prometheus value at T = 300 s).
-    for (query, bounds, expected) in [
-        // Subquery grid (180, 300] steps 240 and 300; one evaluation at 240.
-        (
-            "max_over_time(predict_linear(a[1m] @ 100, 0)[2m:1m])",
-            None,
-            240.,
-        ),
-        // A range query starting at 240 evaluates its grid from (120, 240]: at 180.
-        (
-            "max_over_time(predict_linear(a[1m] @ 100, 0)[2m:1m])",
-            Some((240, 300)),
-            180.,
-        ),
-        (
-            "max_over_time(predict_linear(a[1m] @ start(), 0)[2m:1m])",
-            Some((240, 300)),
-            180.,
-        ),
-        // A top-level pinned call is evaluated at the query start.
-        ("predict_linear(a[1m] @ 100, 0)", Some((240, 300)), 240.),
-        ("predict_linear(a[1m] @ 100, 0)", None, 300.),
-        // Functions that do not read the evaluation time are unchanged.
-        ("max_over_time(deriv(a[1m] @ 100)[2m:1m])", None, 1.),
-        ("max_over_time(rate(a[1m] @ 100)[2m:1m])", None, 1.),
-        ("max_over_time(a @ 100[2m:1m])", None, 100.),
-        // Without `@`, the anchor is each step: the latest step, 300, wins.
-        ("max_over_time(predict_linear(a[1m], 0)[2m:1m])", None, 300.),
-    ] {
-        let expression = lower(query);
-        let dag = fallback_dag(expression.clone());
-        let output = evaluate_dag_with_range(&expression, &dag, &[("a", &rising)], 300, bounds)
-            .unwrap_or_else(|e| panic!("{query}: {e}"));
-        assert_eq!(output.len(), 1, "{query}");
-        assert!(
-            (output[0].2 - expected).abs() < 1e-9,
-            "{query} {bounds:?}: {} != {expected}",
-            output[0].2
-        );
-    }
-}
-
-// Dropping an inner range function's metric name rejects equal labels within
-// each subquery step, while allowing that labelset at different steps.
-#[test]
-fn subquery_label_uniqueness_is_checked_per_evaluation_step() {
-    let equal: &[Sample] = &[
-        ("job=x", 10, 1.),
-        ("job=x", 50, 2.),
-        ("__name__=b,job=x", 10, 1.),
-        ("__name__=b,job=x", 50, 4.),
-    ];
-    let query = "last_over_time(rate(a[1m])[2m:1m])";
-    let error = evaluate(query, &[("a", equal)], 60).unwrap_err();
-    assert!(error.contains("same labelset"), "{error}");
-    let disjoint: &[Sample] = &[
-        ("job=x", -50, 1.),
-        ("job=x", -10, 2.),
-        ("__name__=b,job=x", 10, 3.),
-        ("__name__=b,job=x", 50, 5.),
-    ];
-    let result = labeled(query, &[("a", disjoint)], 60);
-    assert_eq!(result.len(), 1);
-    assert_eq!(result[0].0, "job=x");
-    assert!((result[0].1 - 0.05).abs() < 1e-12);
-}
-
-// Non-finite histogram quantile parameters survive the logical DAG JSON boundary too.
-#[test]
-fn logical_nonfinite_quantile_parameter_round_trips() {
-    let expression = lower("histogram_quantile(NaN, x_bucket)");
-    let restored: Rc<planner_types::ir::OperatorNode> =
-        serde_json::from_slice(&serde_json::to_vec(&expression).unwrap()).unwrap();
-    let samples = buckets(&[("job=a", HISTOGRAM)]);
-    let result = evaluate_dag(
-        &restored,
-        &fallback_dag(restored.clone()),
-        &[("x_bucket", &samples)],
-        60,
-    )
-    .unwrap();
-    assert_eq!(result.len(), 1);
-    assert!(result[0].2.is_nan());
-}
-
-/// The proposal's pointwise projections preserve names only for unary minus.
-#[test]
-fn pointwise_projection_names_and_dynamic_parameters() {
-    let samples = [("job=a", 300, -2.5)];
-    assert_eq!(
-        labeled("-m", &[("m", &samples)], 300),
-        [("__name__=m,job=a".into(), 2.5)]
-    );
-    assert_eq!(
-        labeled("abs(m)", &[("m", &samples)], 300),
-        [("job=a".into(), 2.5)]
-    );
-    assert_eq!(
-        run("round(m, scalar(vector(2)))", &samples, 300).unwrap(),
-        [("a".into(), 300_000, -2.0)]
-    );
-    assert_eq!(
-        run("clamp(m, time()-301, time())", &samples, 300).unwrap(),
-        [("a".into(), 300_000, -1.0)]
-    );
-    assert!(run("clamp(m, 2, 1)", &samples, 300).unwrap().is_empty());
-    assert_eq!(
-        run("year(m)", &[("a", 300, 0.0)], 300).unwrap(),
-        [("a".into(), 300_000, 1970.0)]
-    );
-    assert_eq!(
-        run("hour()", &[], 3600).unwrap(),
-        [("".into(), 3_600_000, 1.0)]
-    );
-}
-
-/// Execute every PromQL root/conversion example in the scalar design document.
-#[test]
-fn scalar_design_document_examples_execute() {
-    let samples = [("job=a", 300, 1.0), ("job=b", 300, 2.0)];
-    for (query, expected) in [
-        ("2", 2.0),
-        ("time()", 300.0),
-        ("vector(time())", 300.0),
-        ("scalar(sum(up)) + 1", 4.0),
-    ] {
-        let root = parse_root(query, AccuracyTarget::Exact);
-        root.validate_structure().unwrap();
-        let output = evaluate(query, &[("up", &samples)], 300).unwrap();
-        assert_eq!(output.len(), 1, "{query}");
-        assert_eq!(output[0].2, expected, "{query}");
-    }
-    assert_eq!(
-        labeled("up * 2", &[("up", &samples)], 300),
-        [("job=a".into(), 2.0), ("job=b".into(), 4.0)]
-    );
-}
diff --git a/crates/asap-physical-operators/tests/weighted_topk_binding.rs b/crates/asap-physical-operators/tests/weighted_topk_binding.rs
index fe79948d6..b4d8c85d3 100644
--- a/crates/asap-physical-operators/tests/weighted_topk_binding.rs
+++ b/crates/asap-physical-operators/tests/weighted_topk_binding.rs
@@ -1,10 +1,11 @@
 //! Planner output binds directly to the shared runtime at a declared rate-value frontier.
+mod common;
 use asap_aware_mapping::{
     accuracy::{
         AccuracyEvidenceProvider, DefaultAccuracyModel, EqualSplitAllocator, PropagationStats,
     },
     cost_model::DefaultCostModel,
-    Replacement, ReplacementStrategy, SketchAlgorithmStrategy, TargetSubDAG,
+    ASAPStrategies, Replacement, ReplacementStrategy, TargetSubDAG,
 };
 use asap_physical_operators::dag::{
     operators::Operator,
@@ -12,16 +13,14 @@ use asap_physical_operators::dag::{
     values::{Batch, Value},
     Limits, RunContext, Scope,
 };
+use common::compile_physical_asap_dag;
 use futures::{executor::block_on, StreamExt};
-use planner_types::{
-    post_asap::*,
-    pre_asap::{DataType, QueryExpr},
-    types::AccuracyTarget,
-};
+use planner_types::ir::export::{PhysicalASAPDAG, PhysicalASAPOperatorPayload};
+use planner_types::{post_asap::*, pre_asap::DataType, types::AccuracyTarget};
 use std::{collections::BTreeMap, rc::Rc, sync::Arc};
 struct Evidence;
 impl AccuracyEvidenceProvider for Evidence {
-    fn topk_max_distinct_items(&self, _: &QueryExpr) -> Option<u64> {
+    fn topk_max_distinct_items(&self, _: &planner_types::ir::OperatorNode) -> Option<u64> {
         Some(1000)
     }
     fn propagation_stats(
@@ -63,14 +62,12 @@ fn physical_binding_does_not_impose_an_accuracy_acceptance_policy() {
 }
 
 fn assert_weighted_binding(evidence: &dyn AccuracyEvidenceProvider, algorithm: SketchAlgorithm) {
-    let root = Rc::new(
-        lower_promql(
-            "topk by(job)(2, sum by(service, job)(rate(m[1m])))",
-            AccuracyTarget::Epsilon(0.1),
-        )
-        .unwrap(),
-    );
-    let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+    let root = lower_promql(
+        "topk by(job)(2, sum by(service, job)(rate(m[1m])))",
+        AccuracyTarget::Epsilon(0.1),
+    )
+    .unwrap();
+    let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
         &DefaultCostModel,
         &DefaultAccuracyModel,
         &EqualSplitAllocator,
@@ -80,7 +77,7 @@ fn assert_weighted_binding(evidence: &dyn AccuracyEvidenceProvider, algorithm: S
         .replacements(&TargetSubDAG::new(&root))
         .into_iter()
         .find_map(|candidate| match candidate.replacement {
-            Replacement::Summary(node)
+            Replacement::SubDAG(node)
                 if candidate.rationale.contains(&format!("{algorithm:?}")) =>
             {
                 Some(node)
@@ -88,8 +85,8 @@ fn assert_weighted_binding(evidence: &dyn AccuracyEvidenceProvider, algorithm: S
             _ => None,
         })
         .unwrap();
-    let dag = compile_post_asap_dag(&plan).unwrap();
-    let build=dag.nodes.iter().find(|node|matches!(&node.payload,PostAsapOperatorPayload::SummaryAgg{family:FieldDataType::Sketch(kind,_),..}if kind.algorithm()==&algorithm)).unwrap();
+    let dag = compile_physical_asap_dag(&plan).unwrap();
+    let build=dag.nodes.iter().find(|node|matches!(&node.payload,PhysicalASAPOperatorPayload::SummaryAgg{family:FieldDataType::Sketch(kind,_),..}if kind.algorithm()==&algorithm)).unwrap();
     let rate_id = dag
         .edges
         .iter()
@@ -156,7 +153,7 @@ fn assert_weighted_binding(evidence: &dyn AccuracyEvidenceProvider, algorithm: S
         let compiled = compile(
             &placed,
             BTreeMap::from([(rate_id.0 as u64, InputContract::bounded(rates.clone()))]),
-            &[dag.root.0 as u64],
+            &[dag.roots[0].0 as u64],
         )
         .unwrap();
         let physical_dag = compiled
@@ -166,7 +163,7 @@ fn assert_weighted_binding(evidence: &dyn AccuracyEvidenceProvider, algorithm: S
         let output = block_on(async {
             let mut output = Vec::new();
             let mut stream = physical_dag
-                .execute(&[dag.root.0 as u64], context)
+                .execute(&[dag.roots[0].0 as u64], context)
                 .unwrap()
                 .remove(0);
             while let Some(batch) = stream.next().await {
@@ -203,7 +200,7 @@ use planner_types::workload::{
 pub fn lower_promql(
     query: &str,
     accuracy: AccuracyTarget,
-) -> Result<QueryExpr, asap_frontend_promql::PromqlError> {
+) -> Result<Rc<planner_types::ir::OperatorNode>, asap_frontend_promql::PromqlError> {
     let workload = PlanningWorkload {
         query_workload: QueryWorkload {
             language: QueryLanguage::PromQL,
@@ -272,7 +269,7 @@ fn direct_rate_topk_exposes_heap_candidates_with_complete_series_identity() {
     check_direct_rate_topk(false);
 }
 
-// Unreferenced labels still distinguish series throughout Rate and heap readout.
+// Unreferenced labels still distinguish series throughout Rate and heap evaluation.
 #[test]
 fn direct_rate_topk_preserves_dynamic_unreferenced_labels() {
     check_direct_rate_topk(true);
@@ -284,12 +281,16 @@ fn check_direct_rate_topk(dynamic: bool) {
     };
     let mut logical =
         lower_promql("topk by(job)(2, rate(m[1m]))", AccuracyTarget::Epsilon(0.1)).unwrap();
-    fn resolve_catalog(node: &mut QueryExpr) {
-        match node {
-            QueryExpr::Aggregate { child, .. } | QueryExpr::TimeRange { child, .. } => {
-                resolve_catalog(Rc::make_mut(child))
-            }
-            QueryExpr::Scan { schema, .. } => {
+    fn resolve_catalog(node: &mut planner_types::ir::OperatorNode) {
+        match &mut node.operator {
+            planner_types::ir::Operator::NonASAP(
+                planner_types::ir::NonASAPOp::Aggregate { child, .. }
+                | planner_types::ir::NonASAPOp::TimeRange { child, .. },
+            ) => resolve_catalog(Rc::make_mut(child)),
+            planner_types::ir::Operator::NonASAP(planner_types::ir::NonASAPOp::Scan {
+                schema,
+                ..
+            }) => {
                 schema.closed = true;
                 schema
                     .fields
@@ -301,14 +302,15 @@ fn check_direct_rate_topk(dynamic: bool) {
             }
             _ => panic!("unexpected input shape: {node:?}"),
         }
+        node.schema = node.operator.output_schema().unwrap();
     }
     if dynamic {
         logical = with_series_identity(&logical).unwrap();
     } else {
-        resolve_catalog(&mut logical);
+        resolve_catalog(Rc::make_mut(&mut logical));
     }
-    let root = Rc::new(logical);
-    let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+    let root = logical;
+    let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
         &DefaultCostModel,
         &DefaultAccuracyModel,
         &EqualSplitAllocator,
@@ -322,7 +324,7 @@ fn check_direct_rate_topk(dynamic: bool) {
         let candidate = candidates
             .iter()
             .find_map(|candidate| match &candidate.replacement {
-                Replacement::Summary(node)
+                Replacement::SubDAG(node)
                     if candidate.rationale.contains(&format!("{algorithm:?}")) =>
                 {
                     Some(node)
@@ -337,26 +339,25 @@ fn check_direct_rate_topk(dynamic: bool) {
                 )
                 .unwrap();
             assert!(matches!(
-                source.expr,
-                SummaryExpr::ValueOperation {
-                    operation: ValueOperation::FinalizeExactAccumulator,
-                    ..
-                }
+                source.operator,
+                planner_types::ir::Operator::ASAP(
+                    planner_types::ir::ASAPOp::FinalizeExactAccumulator { .. }
+                )
             ));
             assert_eq!(ranked.input_contracts().count(), 1);
             let encoded = String::from_utf8(serde_json::to_vec(&ranked).unwrap()).unwrap();
             assert!(encoded.contains("KeyedSummaryBuild"));
-            assert!(encoded.contains("KeyedReadout"));
+            assert!(encoded.contains("KeyedEvaluation"));
             assert!(
                 !encoded.contains("\"Rate\""),
-                "Rate must be supplied by its exact stored-state readout"
+                "Rate must be supplied by its exact stored-state evaluation"
             );
         }
-        let dag = compile_post_asap_dag(candidate).unwrap();
+        let dag = compile_physical_asap_dag(candidate).unwrap();
         assert!(dag.nodes.iter().any(|node| matches!(&node.payload,
-            PostAsapOperatorPayload::SummaryAgg { family: FieldDataType::Sketch(kind, _), .. } if kind.algorithm() == &algorithm)));
+            PhysicalASAPOperatorPayload::SummaryAgg { family: FieldDataType::Sketch(kind, _), .. } if kind.algorithm() == &algorithm)));
         let build = dag.nodes.iter().find(|node| matches!(&node.payload,
-            PostAsapOperatorPayload::SummaryAgg { family: FieldDataType::Sketch(kind, _), .. } if kind.algorithm() == &algorithm)).unwrap();
+            PhysicalASAPOperatorPayload::SummaryAgg { family: FieldDataType::Sketch(kind, _), .. } if kind.algorithm() == &algorithm)).unwrap();
         let input_id = dag
             .edges
             .iter()
@@ -377,8 +378,8 @@ fn check_direct_rate_topk(dynamic: bool) {
             .find(|node| {
                 matches!(
                     &node.payload,
-                    PostAsapOperatorPayload::Fallback {
-                        expression: QueryExpr::TimeRange { .. }
+                    PhysicalASAPOperatorPayload::Relational {
+                        operator: planner_types::ir::export::NonASAPOpKind::TimeRange { .. }
                     }
                 )
             })
@@ -390,7 +391,7 @@ fn check_direct_rate_topk(dynamic: bool) {
                 u64::from(raw.id.0),
                 InputContract::bounded(raw_schema.clone()),
             )]),
-            &[u64::from(dag.root.0)],
+            &[u64::from(dag.roots[0].0)],
         )
         .unwrap();
         let bytes = serde_json::to_vec(&raw_compiled).unwrap();
@@ -475,7 +476,7 @@ fn check_direct_rate_topk(dynamic: bool) {
                 let mut raw_scores = block_on(async {
                     let mut scores = Vec::new();
                     let mut stream = physical_dag
-                        .execute(&[u64::from(dag.root.0)], context)
+                        .execute(&[u64::from(dag.roots[0].0)], context)
                         .unwrap()
                         .remove(0);
                     while let Some(batch) = stream.next().await {
@@ -525,7 +526,7 @@ fn check_direct_rate_topk(dynamic: bool) {
                 u64::from(input_id.0),
                 InputContract::bounded(schema.clone()),
             )]),
-            &[u64::from(dag.root.0)],
+            &[u64::from(dag.roots[0].0)],
         )
         .unwrap();
         for (time, values, expected) in [
@@ -591,7 +592,7 @@ fn check_direct_rate_topk(dynamic: bool) {
                 let mut scores = block_on(async {
                     let mut scores = vec![];
                     let mut stream = physical_dag
-                        .execute(&[u64::from(dag.root.0)], context)
+                        .execute(&[u64::from(dag.roots[0].0)], context)
                         .unwrap()
                         .remove(0);
                     while let Some(batch) = stream.next().await {
@@ -634,7 +635,7 @@ fn spatial_topk_exposes_signed_heap_candidate_over_complete_snapshot() {
     };
     let logical = lower_promql("topk by(job)(1, m)", AccuracyTarget::Epsilon(0.1)).unwrap();
     let root = Rc::new(with_series_identity(&logical).unwrap());
-    let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+    let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
         &DefaultCostModel,
         &DefaultAccuracyModel,
         &EqualSplitAllocator,
@@ -649,21 +650,21 @@ fn spatial_topk_exposes_signed_heap_candidate_over_complete_snapshot() {
     let selected = candidates
         .iter()
         .find_map(|candidate| match &candidate.replacement {
-            Replacement::Summary(node) if candidate.rationale.contains("CountSketchWithHeap") => {
+            Replacement::SubDAG(node) if candidate.rationale.contains("CountSketchWithHeap") => {
                 Some(node)
             }
             _ => None,
         })
         .expect("signed spatial TopK must expose CountSketch with heap");
-    let dag = compile_post_asap_dag(selected).unwrap();
+    let dag = compile_physical_asap_dag(selected).unwrap();
     let raw = dag
         .nodes
         .iter()
         .find(|node| {
             matches!(
                 &node.payload,
-                PostAsapOperatorPayload::Fallback {
-                    expression: QueryExpr::TimeRange { .. }
+                PhysicalASAPOperatorPayload::Relational {
+                    operator: planner_types::ir::export::NonASAPOpKind::TimeRange { .. }
                 }
             )
         })
@@ -672,11 +673,11 @@ fn spatial_topk_exposes_signed_heap_candidate_over_complete_snapshot() {
     let program = compile(
         &dag,
         BTreeMap::from([(u64::from(raw.id.0), InputContract::bounded(schema.clone()))]),
-        &[u64::from(dag.root.0)],
+        &[u64::from(dag.roots[0].0)],
     )
     .unwrap();
     let snapshot_program =
-        asap_physical_operators::physical_planner::promql_rows::compile_current_series_readout(
+        asap_physical_operators::physical_planner::promql_rows::compile_current_series_evaluation(
             selected,
         )
         .unwrap();
@@ -684,7 +685,7 @@ fn spatial_topk_exposes_signed_heap_candidate_over_complete_snapshot() {
         serde_json::from_slice(&serde_json::to_vec(&snapshot_program).unwrap()).unwrap();
     assert!(!encoded.to_string().contains("CurrentSeries"));
     assert!(encoded.to_string().contains("KeyedSummaryBuild"));
-    assert!(encoded.to_string().contains("KeyedReadout"));
+    assert!(encoded.to_string().contains("KeyedEvaluation"));
     for (values, expected, score) in [
         ([100., 20.], "a", 100.),
         ([1., 20.], "b", 20.),
@@ -761,7 +762,7 @@ fn spatial_topk_exposes_signed_heap_candidate_over_complete_snapshot() {
 
 /// Deployment-side lifecycle choice: every summary state of `candidate` is
 /// continuously maintained, and the chosen lifecycles set execution timing.
-fn continuously_maintained_dag(candidate: &Rc<SummaryNode>) -> PostAsapDAG {
+fn continuously_maintained_dag(candidate: &Rc<planner_types::ir::OperatorNode>) -> PhysicalASAPDAG {
     use asap_aware_mapping::{
         cost_model::{Cost, CostModel},
         enumerate_summary_maintenance_lifecycles, CostRate, Horizon,
@@ -782,7 +783,7 @@ fn continuously_maintained_dag(candidate: &Rc<SummaryNode>) -> PostAsapDAG {
         }
         fn summary_maintenance_lifecycle_cost_inputs(
             &self,
-            _: &SummaryNode,
+            _: &planner_types::ir::OperatorNode,
         ) -> SummaryMaintenanceLifecycleCostInputs {
             SummaryMaintenanceLifecycleCostInputs {
                 build_cost: Some(Cost(10.)),
@@ -794,7 +795,7 @@ fn continuously_maintained_dag(candidate: &Rc<SummaryNode>) -> PostAsapDAG {
         }
         fn summary_maintenance_capabilities(
             &self,
-            _: &SummaryNode,
+            _: &planner_types::ir::OperatorNode,
         ) -> SummaryMaintenanceCapabilities {
             SummaryMaintenanceCapabilities {
                 incremental_update: true,
@@ -864,7 +865,7 @@ fn maintained_rate_heap_lifecycle_compiles_fixed_window_precompute() {
         )
         .unwrap(),
     );
-    let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+    let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
         &DefaultCostModel,
         &DefaultAccuracyModel,
         &EqualSplitAllocator,
@@ -874,7 +875,7 @@ fn maintained_rate_heap_lifecycle_compiles_fixed_window_precompute() {
         .replacements(&TargetSubDAG::new(&root))
         .into_iter()
         .filter_map(|candidate| match candidate.replacement {
-            Replacement::Summary(root) if candidate.rationale.contains("WithHeap") => Some(root),
+            Replacement::SubDAG(root) if candidate.rationale.contains("WithHeap") => Some(root),
             _ => None,
         })
         .collect::<Vec<_>>();
@@ -887,7 +888,7 @@ fn maintained_rate_heap_lifecycle_compiles_fixed_window_precompute() {
             .find(|node| {
                 matches!(
                     &node.payload,
-                    PostAsapOperatorPayload::SummaryAgg {
+                    PhysicalASAPOperatorPayload::SummaryAgg {
                         family: FieldDataType::ExactAggregate(ExactKind::Rate, _),
                         ..
                     }
@@ -900,7 +901,7 @@ fn maintained_rate_heap_lifecycle_compiles_fixed_window_precompute() {
             .find(|node| {
                 matches!(
                     &node.payload,
-                    PostAsapOperatorPayload::SummaryAgg {
+                    PhysicalASAPOperatorPayload::SummaryAgg {
                         family: FieldDataType::Sketch(..),
                         ..
                     }
@@ -914,7 +915,7 @@ fn maintained_rate_heap_lifecycle_compiles_fixed_window_precompute() {
                 u64::from(state.id.0),
                 InputContract::bounded(Arc::new(state.output_schema.clone())),
             )]),
-            &[u64::from(dag.root.0)],
+            &[u64::from(dag.roots[0].0)],
             &[u64::from(heap.id.0)],
         )
         .unwrap();
@@ -949,7 +950,7 @@ fn maintained_rate_heap_lifecycle_compiles_fixed_window_precompute() {
             })
         };
         let (family, input, grouping) = match &state.payload {
-            PostAsapOperatorPayload::SummaryAgg {
+            PhysicalASAPOperatorPayload::SummaryAgg {
                 family,
                 input,
                 grouping,
diff --git a/crates/devtools/examples/canonical_examples.rs b/crates/devtools/examples/canonical_examples.rs
index b0df222a3..fd4b703a1 100644
--- a/crates/devtools/examples/canonical_examples.rs
+++ b/crates/devtools/examples/canonical_examples.rs
@@ -1,6 +1,6 @@
 // cargo run -p asap-lower --example canonical_examples
 //
-// One-off: pretty-print the QueryExpr for one canonical query per variant,
+// One-off: pretty-print the `OperatorNode` DAG for one canonical query per variant,
 // plus custom Join/SetOp/Dedup/CTE probes, to eyeball the actual shape.
 
 use asap_devtools::lower_promql_with_data_ingestion_interval;
@@ -48,7 +48,7 @@ fn bgp_catalog() -> SqlCatalog {
 async fn main() {
     let promql_examples: &[(&str, &str)] = &[
         ("Scan", "up"),
-        ("BinaryOp + PromqlScalarBridge", "up > 1"),
+        ("Filter + scalar predicate", "up > 1"),
         ("EvalTimestamp", "time()"),
         ("Aggregate", "sum(up)"),
         (
diff --git a/crates/devtools/src/bin/analyze_corpora.rs b/crates/devtools/src/bin/analyze_corpora.rs
index 7aa87c8e7..0eebe1381 100644
--- a/crates/devtools/src/bin/analyze_corpora.rs
+++ b/crates/devtools/src/bin/analyze_corpora.rs
@@ -218,7 +218,7 @@ fn run_corpus(name: &str, source: &str, interval_ms: u64) -> CorpusResult {
                 normalized_expression,
                 structural_shape,
                 lowered: true,
-                ir: Some(serde_json::to_value(&ir).expect("QueryExpr must serialize")),
+                ir: Some(serde_json::to_value(&ir).expect("OperatorNode must serialize")),
                 ir_debug: Some(format!("{ir:#?}")),
                 error: None,
             }),
@@ -493,7 +493,7 @@ async fn run_sql_corpora(out_dir: PathBuf) {
                     normalized_expression,
                     structural_shape,
                     lowered: true,
-                    ir: Some(serde_json::to_value(&ir).expect("QueryExpr must serialize")),
+                    ir: Some(serde_json::to_value(&ir).expect("OperatorNode must serialize")),
                     ir_debug: Some(format!("{ir:#?}")),
                     error: None,
                 }),
diff --git a/crates/devtools/src/bin/dag_export.rs b/crates/devtools/src/bin/dag_export.rs
index 2728dab12..5f2be890a 100644
--- a/crates/devtools/src/bin/dag_export.rs
+++ b/crates/devtools/src/bin/dag_export.rs
@@ -12,7 +12,7 @@
 // `--epsilon <f64>` is optional and applies to every query in the run: it
 // lowers with `AccuracyTarget::Epsilon(<f64>)` instead of the default
 // `AccuracyTarget::Exact`. Without it, every `AggIntent` lowers exact and
-// `asap_aware_mapping::SketchAlgorithmStrategy` never has a genuine sketch
+// `asap_aware_mapping::ASAPStrategies` never has a genuine sketch
 // alternative to report — so no node ever picks up a `SketchApproximation`
 // note. Pass it to actually exercise that path, e.g.:
 //   cargo run -p asap-lower --bin dag_export -- \
@@ -41,7 +41,7 @@
 //     `asap_types::dag_export::export_post_asap`.
 //
 // Together these surface every one of the four concrete replacement kinds:
-// the sketch family `SketchAlgorithmStrategy`/`HydraGroupingStrategy` bound,
+// the sketch family `ASAPStrategies`/`HydraGroupingStrategy` bound,
 // the CSE share/recompute choice `SharedSubDAGStrategy` found, the
 // workload-aware roll-up `RollupStrategy` derived, and the `avg ->
 // sum/count` rewrite `AvgToSumOverCountStrategy` proposes. Without
@@ -88,8 +88,8 @@ use asap_aware_mapping::physical_plan_cost_model::{
 };
 use asap_aware_mapping::query_physical_lowering::PhysicalNodeRequest;
 use asap_aware_mapping::replacement::{
-    default_strategies_with_evidence, search_workload, search_workload_with, Replacement,
-    ReplacementSubDAG,
+    default_strategies_with_evidence, is_logical_rewrite, search_workload, search_workload_with,
+    Replacement, ReplacementSubDAG,
 };
 use asap_aware_mapping::{AccuracyEvidenceProvider, PropagationStats};
 use asap_types::cost::{BaselineRef, CostAnnotation, CostInput, CostSource, CostUnit};
@@ -97,11 +97,9 @@ use asap_types::dag_export::{
     self, DAGDecision, DAGNote, ExportDAG, NamedDAG, PostAsapSubstitution, TargetRejection,
     TargetReplacement, TargetReplacementAfter, WorkloadDAG,
 };
-use asap_types::post_asap::SummaryExpr;
-use asap_types::post_asap::SummaryNode;
+use asap_types::ir::cse::{structural_hash, HashCache};
+use asap_types::ir::OperatorNode;
 use asap_types::post_asap::{CompositionOperator, FieldDataType, SketchStatistic};
-use asap_types::pre_asap::cse::{structural_hash, HashCache};
-use asap_types::pre_asap::query_expr::QueryExpr;
 use asap_types::pre_asap::schema::{DataType, Field, Schema};
 use asap_types::resources::CacheProfile;
 use asap_types::types::AccuracyTarget;
@@ -137,7 +135,7 @@ fn parse_planner_cost_document(raw: &str) -> Result<PlannerCostDocument, String>
 #[derive(Debug, Clone, serde::Serialize, serde::Deserialize)]
 #[serde(deny_unknown_fields)]
 struct TargetPhysicalEvidence {
-    target: QueryExpr,
+    target: Rc<OperatorNode>,
     scope: ComparisonScopeEvidence,
     candidates: Vec<CandidatePhysicalEvidence>,
 }
@@ -192,7 +190,7 @@ impl ComparisonScopeEvidence {
 #[derive(Debug, Clone, serde::Serialize, serde::Deserialize)]
 #[serde(deny_unknown_fields)]
 struct QueryNodePhysicalEvidence {
-    logical_node: QueryExpr,
+    logical_node: OperatorNode,
     operator: asap_aware_mapping::analytical_cost::PhysicalOperator,
     occurrence: usize,
     synthetic: bool,
@@ -228,11 +226,11 @@ impl CandidatePhysicalEvidence {
 
     fn matches(&self, candidate: &ReplacementSubDAG) -> bool {
         let actual = match (self, &candidate.replacement) {
-            (Self::Summary { .. }, Replacement::Summary(summary)) => {
-                serde_json::to_value(dag_export::export_summary(summary))
+            (Self::Summary { .. }, Replacement::SubDAG(node)) if !is_logical_rewrite(node) => {
+                serde_json::to_value(dag_export::export(node))
             }
-            (Self::Rewrite { .. }, Replacement::Rewrite(query)) => {
-                serde_json::to_value(dag_export::export(query))
+            (Self::Rewrite { .. }, Replacement::SubDAG(node)) if is_logical_rewrite(node) => {
+                serde_json::to_value(dag_export::export(node))
             }
             _ => return false,
         };
@@ -369,7 +367,7 @@ impl PlannerPhysicalPlanProvider for ExportPhysicalProvider<'_> {
     fn summary_physical_dag(
         &self,
         snapshot: &PhysicalEvidenceSnapshot,
-        _summary: &Rc<SummaryNode>,
+        _summary: &Rc<OperatorNode>,
         _target: &asap_aware_mapping::replacement::TargetSubDAG<'_>,
     ) -> Result<PhysicalDAG, AnalyticalCostError> {
         if snapshot.scope != self.target.scope.resolve()? {
@@ -400,7 +398,7 @@ impl ExportPlannerCostModel<'_> {
             .document
             .targets
             .iter()
-            .filter(|entry| entry.target == **target.root);
+            .filter(|entry| entry.target == *target.root);
         let target_evidence = targets.next()?;
         if targets.next().is_some() {
             return None;
@@ -429,7 +427,7 @@ impl ExportPlannerCostModel<'_> {
     fn annotations(
         &self,
         candidate: &ReplacementSubDAG,
-        target: &Rc<QueryExpr>,
+        target: &Rc<OperatorNode>,
     ) -> (CostAnnotation, CostAnnotation, CostAnnotation) {
         let target = asap_aware_mapping::replacement::TargetSubDAG::new(target);
         let Some((provider, calibration)) = self.bound(candidate, &target) else {
@@ -960,12 +958,11 @@ fn parse_args_from(argv: impl Iterator<Item = String>) -> ParsedArgs {
     }
 }
 
-/// Attach workload-wide replacement explanations to their exact DAG nodes.
-/// `node_hash` is only a narrowing filter; `source_expr == Some(target)` is
-/// the collision-safe identity check (`source_expr` is `None` only for a
-/// post-ASAP-originated node inside a `--post-asap` `post_dag`, which this
-/// function is never called on — every node it sees, from an ordinary
-/// [`dag_export::export`], carries `Some`).
+/// Attach workload-wide replacement explanations to their exact dag nodes.
+/// `node_hash` is only a narrowing filter; `source_node == Some(target)` is
+/// the collision-safe identity check (every node an ordinary
+/// [`dag_export::export`] produces carries `Some`; the `None` arm is
+/// defensive only).
 fn annotate_with_explanations(
     dag: &mut ExportDAG,
     explanations: &[asap_aware_mapping::ReplacementExplanation],
@@ -974,7 +971,7 @@ fn annotate_with_explanations(
     for (i, explanation) in explanations.iter().enumerate() {
         for node in dag.nodes.iter_mut() {
             if node.hash == Some(explanation.node_hash)
-                && node.source_expr.as_ref() == Some(explanation.target.as_ref())
+                && node.source_node.as_ref() == Some(&explanation.target)
             {
                 node.notes.push(DAGNote {
                     kind: format!("{:?}", explanation.kind),
@@ -992,7 +989,7 @@ fn annotate_with_explanations(
 /// never disagree about which candidate won for a given target.
 #[allow(dead_code)]
 struct Winner<'a> {
-    target: &'a Rc<QueryExpr>,
+    target: &'a Rc<OperatorNode>,
     candidate: &'a ReplacementSubDAG,
     costs: (CostAnnotation, CostAnnotation, CostAnnotation),
 }
@@ -1056,7 +1053,7 @@ fn lookup_winner(
     by_hash: &HashMap<u64, Vec<usize>>,
     winners: &[Winner<'_>],
     cache: &mut HashCache,
-    expr: &QueryExpr,
+    expr: &OperatorNode,
 ) -> Option<usize> {
     let hash = structural_hash(expr, cache);
     by_hash
@@ -1102,12 +1099,10 @@ fn target_replacement(
     let strategy = winner.candidate.strategy.to_string();
     let before = dag_export::export(winner.target);
     let after = match &winner.candidate.replacement {
-        Replacement::Summary(node) => {
-            TargetReplacementAfter::Summary(dag_export::export_summary(node))
-        }
-        Replacement::Rewrite(rewritten) => {
-            TargetReplacementAfter::Rewrite(dag_export::export(rewritten))
+        Replacement::SubDAG(node) if is_logical_rewrite(node) => {
+            TargetReplacementAfter::Rewrite(dag_export::export(node))
         }
+        Replacement::SubDAG(node) => TargetReplacementAfter::Summary(dag_export::export(node)),
         Replacement::ExactComposition(_) => {
             unreachable!("composition candidates are materialized by GlobalSelection")
         }
@@ -1131,6 +1126,20 @@ fn target_replacement(
     }
 }
 
+/// Is `replacement` `retain_exact`'s conservative no-op fallback — the
+/// target itself, unbound, carrying only an exact "kept pre-ASAP" guarantee?
+/// `ASAPStrategies` emits it for an intent with no summary
+/// realization at all (`STDDEV_POP`, `AVG`, ... dispatch to
+/// `Realization::PassThrough`). It is "nothing to bind here", not a
+/// replacement decision. A logical rewrite (no guarantee yet) and any sub-DAG
+/// with an ASAP operator are real candidates.
+fn is_trivial_retain_exact(replacement: &Replacement) -> bool {
+    matches!(
+        replacement,
+        Replacement::SubDAG(node) if node.guarantee.is_some() && !node.contains_asap()
+    )
+}
+
 /// The two additive `--post-asap` outputs — see this file's top-of-file
 /// usage doc for what each is for.
 struct PostAsapResults {
@@ -1159,7 +1168,7 @@ fn raw_only_post_asap_results() -> PostAsapResults {
 }
 
 /// Assign collision-free, explicit identities to structurally equal nodes
-/// across a set of exported query DAGs. The full canonical sub-DAG string
+/// across a set of exported query graphs. The full canonical sub-DAG string
 /// is the equality key; the compact integer is what JSON consumers receive.
 /// Consequently the viewer never needs to guess identity from labels,
 /// hashes, or a client-side node signature.
@@ -1210,7 +1219,7 @@ fn assign_workload_node_ids(dags: &mut [&mut ExportDAG]) {
 /// which candidate won for a given target.
 #[allow(dead_code)]
 fn run_post_asap_with_progress(
-    lowered_queries: &[(String, String, QueryExpr)],
+    lowered_queries: &[(String, String, Rc<OperatorNode>)],
     progress: bool,
     cost_model: &dyn CostModel,
     export_model: Option<&ExportPlannerCostModel<'_>>,
@@ -1220,9 +1229,9 @@ fn run_post_asap_with_progress(
     if progress {
         eprintln!("[3/4] ASAP-aware mapping is running…");
     }
-    let roots: Vec<(String, Rc<QueryExpr>)> = lowered_queries
+    let roots: Vec<(String, Rc<OperatorNode>)> = lowered_queries
         .iter()
-        .map(|(name, _, qe)| (name.clone(), Rc::new(qe.clone())))
+        .map(|(name, _, qe)| (name.clone(), Rc::clone(qe)))
         .collect();
     let strategies;
     let space = if let Some(evidence) = evidence {
@@ -1233,28 +1242,23 @@ fn run_post_asap_with_progress(
     };
     let selection = space.global_selection(cost_model);
 
-    // A group's top candidate can be `keep_pre_asap`'s own conservative
-    // fallback — `Replacement::Summary(SummaryNode { expr:
-    // KeepPreAsap(Rc::new(target.clone())), .. })` — the *whole target*
-    // wrapped as unbound, e.g. for a multi-measure/`HAVING`-bearing
-    // aggregate, or (the case that actually surfaces this: `STDDEV_POP`/
-    // `AVG`/`VARIANCE` dispatch to `Realization::PassThrough` with no
-    // alternative at all, per `realizations_for_intent`'s own doc) an
-    // intent with no summary realization whatsoever. This isn't a
-    // replacement decision — it's `SketchAlgorithmStrategy` saying "nothing
-    // to bind here" — the identical "no-op candidate" concept
-    // `explanation.rs`'s own `sketch_finding_reason` already excludes from
-    // being reported as a finding ("a candidate list containing only the
-    // trivial no-op realization... isn't an opportunity, it's just the
-    // target's existing shape reflected back"). Filtered out here for a
-    // second, load-bearing reason beyond just matching that precedent:
-    // `export_post_asap`'s `find_winner` re-checks every node reached
-    // inside a spliced-in `KeepPreAsap` payload (by design, so a target
-    // nested underneath one still gets found) — if that payload structurally
-    // *is* the enclosing target, `find_winner` immediately matches the same
-    // winner again, forever. Treating this candidate as "no winner" (same
-    // as an empty candidate list) avoids ever handing `export_post_asap` a
-    // winner that can't help but recurse into itself.
+    // A group's top candidate can be `retain_exact`'s own conservative
+    // fallback — the *whole target* itself, unbound, carrying only an exact
+    // "kept pre-ASAP" guarantee (see `is_trivial_retain_exact`) — e.g. for
+    // a multi-measure/`HAVING`-bearing aggregate, or (the case that actually
+    // surfaces this: `STDDEV_POP`/`AVG`/`VARIANCE` dispatch to
+    // `Realization::PassThrough` with no alternative at all, per
+    // `realizations_for_intent`'s own doc) an intent with no summary
+    // realization whatsoever. This isn't a replacement decision — it's
+    // `ASAPStrategies` saying "nothing to bind here" — the
+    // identical "no-op candidate" concept `explanation.rs`'s own
+    // `sketch_finding_reason` already excludes from being reported as a
+    // finding ("a candidate list containing only the trivial no-op
+    // realization... isn't an opportunity, it's just the target's existing
+    // shape reflected back"). Treating this candidate as "no winner" (same
+    // as an empty candidate list) also keeps `post_dag` honest: splicing
+    // the target in for itself would tag every node of an unchanged sub-DAG
+    // with a "replacement" decision.
     let winners: Vec<Winner<'_>> = selection
         .target_selections()
         .filter_map(|group| {
@@ -1267,10 +1271,7 @@ fn run_post_asap_with_progress(
             if matches!(candidate.replacement, Replacement::ExactComposition(_)) {
                 return None;
             }
-            if matches!(
-                &candidate.replacement,
-                Replacement::Summary(node) if matches!(node.expr, SummaryExpr::KeepPreAsap(_))
-            ) {
+            if is_trivial_retain_exact(&candidate.replacement) {
                 return None;
             }
             Some(Winner {
@@ -1318,7 +1319,7 @@ fn run_post_asap_with_progress(
     }
     let post_started = Instant::now();
     let mut post_dag_cache = HashCache::new();
-    let mut find_winner = |expr: &QueryExpr| -> Option<PostAsapSubstitution> {
+    let mut find_winner = |expr: &Rc<OperatorNode>| -> Option<PostAsapSubstitution> {
         let i = lookup_winner(&by_hash, &winners, &mut post_dag_cache, expr)?;
         let winner = &winners[i];
         let (baseline_cost, selected_cost, benefit) = winner.costs.clone();
@@ -1337,11 +1338,11 @@ fn run_post_asap_with_progress(
             benefit: Some(benefit),
         };
         Some(match &winners[i].candidate.replacement {
-            Replacement::Rewrite(rc) => PostAsapSubstitution::Rewrite {
+            Replacement::SubDAG(rc) if is_logical_rewrite(rc) => PostAsapSubstitution::Rewrite {
                 replacement: Rc::clone(rc),
                 decision,
             },
-            Replacement::Summary(rc) => PostAsapSubstitution::Summary {
+            Replacement::SubDAG(rc) => PostAsapSubstitution::Summary {
                 replacement: Rc::clone(rc),
                 decision,
             },
@@ -1389,20 +1390,20 @@ fn run_post_asap_with_progress(
     for (name, _, qe) in lowered_queries {
         let dag = dag_export::export(qe);
         for node in &dag.nodes {
-            let Some(source_expr) = node.source_expr.as_ref() else {
+            let Some(source_node) = node.source_node.as_ref() else {
                 continue; // never true for a plain `export` — defensive only.
             };
-            if let Some(i) = lookup_winner(&by_hash, &winners, &mut lookup_cache, source_expr) {
+            if let Some(i) = lookup_winner(&by_hash, &winners, &mut lookup_cache, source_node) {
                 replacements.push((
                     name.clone(),
                     target_replacement(i as u32, node.id, &winners[i]),
                 ));
                 matched[i] = true;
             }
-            let hash = structural_hash(source_expr, &mut lookup_cache);
+            let hash = structural_hash(source_node, &mut lookup_cache);
             for &i in rejected_by_hash.get(&hash).into_iter().flatten() {
                 let group = rejected_groups[i];
-                if *source_expr != *group.target {
+                if *source_node != group.target {
                     continue;
                 }
                 rejections.extend(group.rejected.iter().map(|rejected| {
@@ -1465,7 +1466,7 @@ fn run_post_asap_with_progress(
 }
 
 #[cfg(test)]
-fn run_post_asap(lowered_queries: &[(String, String, QueryExpr)]) -> PostAsapResults {
+fn run_post_asap(lowered_queries: &[(String, String, Rc<OperatorNode>)]) -> PostAsapResults {
     run_post_asap_with_progress(lowered_queries, false, &DefaultCostModel, None, None)
 }
 
@@ -1704,14 +1705,26 @@ mod tests {
     };
     use asap_aware_mapping::query_physical_lowering::lower_query_physical_dag;
     use asap_devtools::PromqlError;
+    use asap_types::ir::NonASAPOp;
     use asap_types::pre_asap::{DataType, Field, Reduction, Schema, Source};
 
-    fn lower_promql(query: &str, accuracy: AccuracyTarget) -> Result<QueryExpr, PromqlError> {
+    fn lower_promql(
+        query: &str,
+        accuracy: AccuracyTarget,
+    ) -> Result<Rc<OperatorNode>, PromqlError> {
         lower_promql_with_data_ingestion_interval(query, accuracy, 1_000)
     }
 
-    fn non_topk_query() -> QueryExpr {
-        QueryExpr::Aggregate {
+    fn non_topk_query() -> Rc<OperatorNode> {
+        let scan = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
+            source: Source::Table {
+                table_ref: "events".into(),
+            },
+            predicates: vec![],
+            schema: Schema::new(vec![Field::plain("v", DataType::Int64, false)]),
+        }))
+        .expect("scan leaf derives its schema");
+        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
             reduction: Reduction::by(vec![]),
             measures: vec![asap_types::pre_asap::AggIntent::Count {
                 accuracy: AccuracyTarget::Epsilon(0.1),
@@ -1719,23 +1732,18 @@ mod tests {
             output_names: vec![],
             filters: vec![],
             having: None,
-            child: Rc::new(QueryExpr::Scan {
-                source: Source::Table {
-                    table_ref: "events".into(),
-                },
-                predicates: vec![],
-                schema: Schema::new(vec![Field::plain("v", DataType::Int64, false)]),
-            }),
-        }
+            child: scan,
+        }))
+        .expect("count aggregate derives its schema")
     }
 
     fn fixture_raw_dag(
-        query: &QueryExpr,
+        query: &Rc<OperatorNode>,
         candidate: &ReplacementSubDAG,
         document: &PlannerCostDocument,
     ) -> PhysicalDAG {
         let model = ExportPlannerCostModel { document };
-        let root = Rc::new(query.clone());
+        let root = Rc::clone(query);
         let target = asap_aware_mapping::replacement::TargetSubDAG::new(&root);
         let (provider, _) = model.bound(candidate, &target).unwrap();
         let snapshot = provider.capture_evidence_snapshot(&target).unwrap();
@@ -1751,7 +1759,7 @@ mod tests {
         let (query, candidate, mut document) = cost_fixture();
         let raw = fixture_raw_dag(&query, &candidate, &document);
         let candidate_dag = cheap_candidate_dag();
-        let root = Rc::new(query.clone());
+        let root = Rc::clone(&query);
         let target = asap_aware_mapping::replacement::TargetSubDAG::new(&root);
         assert!(ExportPlannerCostModel {
             document: &document
@@ -1914,7 +1922,7 @@ mod tests {
         let (query, candidate, mut document) = cost_fixture();
         let raw = fixture_raw_dag(&query, &candidate, &document);
         let candidate_dag = cheap_candidate_dag();
-        let root = Rc::new(query.clone());
+        let root = Rc::clone(&query);
         let target = asap_aware_mapping::replacement::TargetSubDAG::new(&root);
         assert!(ExportPlannerCostModel {
             document: &document
@@ -2194,7 +2202,7 @@ mod tests {
         EdgeStatistics { rows, bytes }
     }
 
-    fn query_evidence(query: &QueryExpr) -> Vec<QueryNodePhysicalEvidence> {
+    fn query_evidence(query: &Rc<OperatorNode>) -> Vec<QueryNodePhysicalEvidence> {
         let entries = RefCell::new(Vec::new());
         let scope = test_scope().resolve().unwrap();
         let provider = |request: PhysicalNodeRequest<'_>| {
@@ -2242,7 +2250,7 @@ mod tests {
             });
             Ok(evidence)
         };
-        lower_query_physical_dag(&Rc::new(query.clone()), &scope, &provider).unwrap();
+        lower_query_physical_dag(query, &scope, &provider).unwrap();
         entries.into_inner()
     }
 
@@ -2282,49 +2290,28 @@ mod tests {
 
     fn candidate_plan(candidate: &ReplacementSubDAG) -> serde_json::Value {
         match &candidate.replacement {
-            Replacement::Summary(summary) => {
-                serde_json::to_value(dag_export::export_summary(summary)).unwrap()
-            }
-            Replacement::Rewrite(rewrite) => {
-                serde_json::to_value(dag_export::export(rewrite)).unwrap()
-            }
+            Replacement::SubDAG(node) => serde_json::to_value(dag_export::export(node)).unwrap(),
             Replacement::ExactComposition(_) => {
                 unreachable!("cost fixtures select directly materialized candidates")
             }
         }
     }
 
-    fn cost_fixture() -> (QueryExpr, ReplacementSubDAG, PlannerCostDocument) {
+    fn cost_fixture() -> (Rc<OperatorNode>, ReplacementSubDAG, PlannerCostDocument) {
         let query = non_topk_query();
-        let root = Rc::new(query.clone());
+        let root = Rc::clone(&query);
         let space = search_workload(vec![(String::from("q"), Rc::clone(&root))]);
         let group = space
             .target_subdag_candidates()
-            .find(|group| *group.target == query)
+            .find(|group| group.target == query)
             .expect("aggregate memo group");
         let candidate = group
             .candidates
             .iter()
-            .find(|candidate| {
-                !matches!(
-                    &candidate.replacement,
-                    Replacement::Summary(node)
-                        if matches!(node.expr, SummaryExpr::KeepPreAsap(_))
-                )
-            })
+            .find(|candidate| !is_trivial_retain_exact(&candidate.replacement))
             .expect("summary candidate")
             .clone();
-        let plan = match &candidate.replacement {
-            Replacement::Summary(summary) => {
-                serde_json::to_value(dag_export::export_summary(summary)).unwrap()
-            }
-            Replacement::Rewrite(rewrite) => {
-                serde_json::to_value(dag_export::export(rewrite)).unwrap()
-            }
-            Replacement::ExactComposition(_) => {
-                unreachable!("cost fixtures select directly materialized candidates")
-            }
-        };
+        let plan = candidate_plan(&candidate);
         let document = PlannerCostDocument {
             storage_io: None,
             handoffs: None,
@@ -2339,12 +2326,14 @@ mod tests {
                 target: query.clone(),
                 scope: test_scope(),
                 candidates: vec![match &candidate.replacement {
-                    Replacement::Summary(_) => CandidatePhysicalEvidence::Summary {
-                        plan,
-                        query_nodes: query_evidence(&query),
-                        physical_dag: cheap_candidate_dag(),
-                    },
-                    Replacement::Rewrite(_) => CandidatePhysicalEvidence::Rewrite {
+                    Replacement::SubDAG(node) if !is_logical_rewrite(node) => {
+                        CandidatePhysicalEvidence::Summary {
+                            plan,
+                            query_nodes: query_evidence(&query),
+                            physical_dag: cheap_candidate_dag(),
+                        }
+                    }
+                    Replacement::SubDAG(_) => CandidatePhysicalEvidence::Rewrite {
                         plan,
                         query_nodes: query_evidence(&query),
                     },
@@ -2365,7 +2354,7 @@ mod tests {
         assert_eq!(parsed.targets[0].target, query);
         assert!(parsed.targets[0].candidates[0].matches(&candidate));
         let model = ExportPlannerCostModel { document: &parsed };
-        let target_rc = Rc::new(query.clone());
+        let target_rc = Rc::clone(&query);
         let target = asap_aware_mapping::replacement::TargetSubDAG::new(&target_rc);
         let (provider, calibration) = model.bound(&candidate, &target).expect("exact binding");
         let estimate = PhysicalPlanCostModel::new(&provider, calibration.clone())
@@ -2373,7 +2362,7 @@ mod tests {
             .estimate_candidate(&candidate, &target)
             .unwrap();
         assert!(estimate.candidate_cost < estimate.raw_cost);
-        let (baseline, selected, benefit) = model.annotations(&candidate, &Rc::new(query));
+        let (baseline, selected, benefit) = model.annotations(&candidate, &query);
         assert!(baseline.value.is_some());
         assert!(selected.value.is_some());
         assert!(benefit.value.is_some());
@@ -2405,7 +2394,7 @@ mod tests {
             .unwrap()
             .remove("cache_profile");
         let parsed = parse_planner_cost_document(&json.to_string()).unwrap();
-        let target = Rc::new(query);
+        let target = query;
         let legacy = ExportPlannerCostModel { document: &parsed }.annotations(&candidate, &target);
         let explicit = ExportPlannerCostModel {
             document: &document,
@@ -2426,7 +2415,7 @@ mod tests {
     fn cache_json_affects_ranking_and_exports_declared_evidence() {
         // Identical repeats hit the result cache; distinct evaluations still execute.
         let (query, candidate, document) = cost_fixture();
-        let target_rc = Rc::new(query);
+        let target_rc = query;
         let target = asap_aware_mapping::replacement::TargetSubDAG::new(&target_rc);
         let no_cache = ExportPlannerCostModel {
             document: &document,
@@ -2513,7 +2502,7 @@ mod tests {
     #[test]
     fn duplicate_target_candidate_and_query_evidence_each_fail_closed() {
         let (query, candidate, document) = cost_fixture();
-        let target_rc = Rc::new(query);
+        let target_rc = query;
         let target = asap_aware_mapping::replacement::TargetSubDAG::new(&target_rc);
 
         let mut duplicate_target = document.clone();
@@ -2555,7 +2544,7 @@ mod tests {
     #[test]
     fn incomplete_or_unused_json_evidence_fails_closed() {
         let (query, candidate, document) = cost_fixture();
-        let target_rc = Rc::new(query);
+        let target_rc = query;
         let target = asap_aware_mapping::replacement::TargetSubDAG::new(&target_rc);
 
         let mut missing = document.clone();
@@ -2596,7 +2585,7 @@ mod tests {
         physical_dag.nodes.push(physical_dag.nodes[0].clone());
         let document = parse_planner_cost_document(&serde_json::to_string(&document).unwrap())
             .expect("invalid physical semantics are checked by the estimator");
-        let target_rc = Rc::new(query);
+        let target_rc = query;
         let target = asap_aware_mapping::replacement::TargetSubDAG::new(&target_rc);
         assert!(ExportPlannerCostModel {
             document: &document
@@ -2608,18 +2597,17 @@ mod tests {
     #[test]
     fn global_selection_uses_the_cheapest_complete_physical_candidate() {
         let query = non_topk_query();
-        let root = Rc::new(query.clone());
+        let root = Rc::clone(&query);
         let space = search_workload(vec![(String::from("q"), Rc::clone(&root))]);
         let group = space
             .target_subdag_candidates()
-            .find(|group| *group.target == query)
+            .find(|group| group.target == query)
             .expect("aggregate memo group");
         let candidates: Vec<_> = group
             .candidates
             .iter()
             .filter(|candidate| {
-                matches!(candidate.replacement, Replacement::Summary(ref node)
-                    if !matches!(node.expr, SummaryExpr::KeepPreAsap(_)))
+                matches!(&candidate.replacement, Replacement::SubDAG(node) if node.contains_asap())
             })
             .take(2)
             .collect();
@@ -2677,7 +2665,7 @@ mod tests {
         let selection = space.global_selection(&model);
         let chosen = selection
             .target_selections()
-            .find(|selected| selected.target.as_ref() == &query)
+            .find(|selected| *selected.target == query)
             .and_then(|selected| selected.chosen)
             .expect("one complete physical candidate should win");
         assert!(document.targets[0].candidates[1].matches(chosen));
@@ -2779,13 +2767,13 @@ mod tests {
         let selected_query = lower_promql("up", AccuracyTarget::Exact).unwrap();
         let other_query = lower_promql("process_cpu_seconds_total", AccuracyTarget::Exact).unwrap();
         let selected = ReplacementSubDAG {
-            replacement: Replacement::Rewrite(Rc::new(selected_query.clone())),
+            replacement: Replacement::SubDAG(Rc::clone(&selected_query)),
             strategy: "same-strategy",
             provenance: asap_aware_mapping::replacement::ReplacementProvenance::LogicalRewrite,
             rationale: String::new(),
         };
         let other = ReplacementSubDAG {
-            replacement: Replacement::Rewrite(Rc::new(other_query)),
+            replacement: Replacement::SubDAG(other_query),
             strategy: "same-strategy",
             provenance: asap_aware_mapping::replacement::ReplacementProvenance::LogicalRewrite,
             rationale: String::new(),
@@ -3038,8 +3026,8 @@ mod tests {
             .1;
         let q3_root = &q3.nodes[q3.root as usize];
         let q4_root = &q4.nodes[q4.root as usize];
-        assert!(q3_root.label.contains("Limit { n: 5,"));
-        assert!(q4_root.label.contains("Limit { n: 10,"));
+        assert!(q3_root.label.contains("Limit(5)"));
+        assert!(q4_root.label.contains("Limit(10)"));
         assert_ne!(q3_root.workload_node_id, q4_root.workload_node_id);
         let q3_ranked = &q3.nodes[q3_root.children[0] as usize];
         let q4_ranked = &q4.nodes[q4_root.children[0] as usize];
@@ -3147,21 +3135,19 @@ mod tests {
     /// against real corpus queries (a `STDDEV_POP` aggregate, which — like
     /// `AVG` — dispatches to `Realization::PassThrough` with no
     /// alternative strategy of its own, so its *only* candidate is
-    /// `keep_pre_asap`'s conservative fallback: `Replacement::Summary`
-    /// wrapping the *entire target* as `SummaryExpr::KeepPreAsap`).
-    /// `run_post_asap` must not treat that as a real winner: splicing it
-    /// into `export_post_asap` would recurse forever, since `find_winner`
-    /// re-checks every node inside a spliced `KeepPreAsap` payload by
-    /// design, and this payload structurally *is* the enclosing target — a
-    /// fresh `find_winner` call finds the identical winner again,
-    /// unconditionally, every time. Filtering this shape out of `winners`
-    /// (same "no-op candidate" concept `explanation.rs`'s own
-    /// `sketch_finding_reason` already excludes from being a finding) is
-    /// what keeps this terminating: this test's only assertion that matters
-    /// is that `run_post_asap` returns at all instead of overflowing the
-    /// stack.
+    /// `retain_exact`'s conservative fallback: the *entire target* itself,
+    /// unbound, carrying only an exact "kept pre-ASAP" guarantee).
+    /// `run_post_asap` must not treat that as a real winner: under the old
+    /// IR, splicing it into `export_post_asap` recursed forever (the spliced
+    /// payload structurally *was* the enclosing target, so every fresh
+    /// `find_winner` call found the identical winner again). Filtering this
+    /// shape out of `winners` (same "no-op candidate" concept
+    /// `explanation.rs`'s own `sketch_finding_reason` already excludes from
+    /// being a finding) is what keeps this terminating and keeps the output
+    /// free of a fake replacement: this test asserts both that
+    /// `run_post_asap` returns at all and that it reports nothing.
     #[tokio::test]
-    async fn post_asap_does_not_recurse_forever_on_a_trivial_keep_pre_asap_winner() {
+    async fn post_asap_does_not_recurse_forever_on_a_trivial_retain_exact_winner() {
         let cat = default_catalog();
         let stddev_query = lower_sql(
             "SELECT STDDEV_POP(latency) FROM metrics",
@@ -3178,12 +3164,12 @@ mod tests {
 
         let results = run_post_asap(&lowered_queries);
 
-        // A trivial keep_pre_asap winner must be filtered before it ever
+        // A trivial retain_exact winner must be filtered before it ever
         // becomes a flat `TargetReplacement` — there's no real replacement
         // to report for a target with no alternative at all.
         assert!(
             results.replacements.is_empty(),
-            "a target whose only candidate is the trivial keep_pre_asap fallback \
+            "a target whose only candidate is the trivial retain_exact fallback \
              shouldn't produce a flat replacement entry: {:?}",
             results
                 .replacements
diff --git a/crates/devtools/src/bin/show_post_asap_ir.rs b/crates/devtools/src/bin/show_post_asap_ir.rs
index 4b2cbf917..df6c2bfd5 100644
--- a/crates/devtools/src/bin/show_post_asap_ir.rs
+++ b/crates/devtools/src/bin/show_post_asap_ir.rs
@@ -3,10 +3,11 @@
 //
 // Lowers a batch of ad-hoc SQL/PromQL queries to pre-ASAP IR, then runs the
 // `asap-aware-mapping` pre-ASAP → post-ASAP binding pass and prints the
-// resulting **post-ASAP IR** (the sketch-bound IR: `SummaryExpr`/`SummaryNode`
-// — the concrete `SummaryKind`/`SummaryParams` committed per aggregate, or
-// `KeepPreAsap` for whatever the pass left untouched). See `show_pre_asap_ir`
-// for the sketch-agnostic IR one layer upstream.
+// resulting **post-ASAP IR** (the sketch-bound IR: an `OperatorNode` DAG in
+// which `ASAPOp` operators — the concrete summary family/params committed per
+// aggregate — replace the bound aggregates, while whatever the pass left
+// untouched stays a plain `NonASAPOp` sub-DAG carrying an exact guarantee).
+// See `show_pre_asap_ir` for the sketch-agnostic IR one layer upstream.
 //
 // File format: one query per line, prefixed with "sql>" or "promql>".
 // Blank lines and lines starting with '#' are ignored.
@@ -20,12 +21,12 @@
 // `metrics(ts, service, region, latency, bytes)` catalog — the same table
 // used in cross_language.rs and topk_ir.rs.
 
-use asap_aware_mapping::replacement::keep_pre_asap;
+use asap_aware_mapping::replacement::retain_exact;
 use asap_aware_mapping::{
-    Replacement, ReplacementStrategy, ReplacementSubDAG, SketchAlgorithmStrategy, TargetSubDAG,
+    ASAPStrategies, Replacement, ReplacementStrategy, ReplacementSubDAG, TargetSubDAG,
 };
 use asap_devtools::{lower_promql_with_data_ingestion_interval, lower_sql, SqlCatalog};
-use asap_types::pre_asap::query_expr::QueryExpr;
+use asap_types::ir::OperatorNode;
 use asap_types::pre_asap::schema::{DataType, Field, Schema};
 use asap_types::types::AccuracyTarget;
 use std::io::Read;
@@ -33,18 +34,17 @@ use std::rc::Rc;
 
 const ACCURACY: AccuracyTarget = AccuracyTarget::Epsilon(0.01);
 
-/// `SketchAlgorithmStrategy::replacements` returns every candidate. This
+/// `ASAPStrategies::replacements` returns every candidate. This
 /// debug tool prints all of them so callers can inspect the planner's choices.
 /// If the strategy has none, preserve the single pre-ASAP fallback output.
-fn bind_all(expr: &QueryExpr) -> Result<Vec<Rc<asap_types::post_asap::SummaryNode>>, String> {
-    let root = Rc::new(expr.clone());
-    let target = TargetSubDAG::new(&root);
-    let candidates = SketchAlgorithmStrategy::default_cost_model()
+fn bind_all(root: &Rc<OperatorNode>) -> Result<Vec<Rc<OperatorNode>>, String> {
+    let target = TargetSubDAG::new(root);
+    let candidates = ASAPStrategies::default_cost_model()
         .replacements(&target)
         .into_iter()
         .filter_map(|candidate| match candidate {
             ReplacementSubDAG {
-                replacement: Replacement::Summary(node),
+                replacement: Replacement::SubDAG(node),
                 ..
             } => Some(node),
             _ => None,
@@ -52,7 +52,7 @@ fn bind_all(expr: &QueryExpr) -> Result<Vec<Rc<asap_types::post_asap::SummaryNod
         .collect::<Vec<_>>();
 
     if candidates.is_empty() {
-        Ok(vec![keep_pre_asap(&root).map_err(|e| e.to_string())?])
+        Ok(vec![retain_exact(root).map_err(|e| e.to_string())?])
     } else {
         Ok(candidates)
     }
@@ -128,7 +128,7 @@ async fn main() {
             Ok(candidates) => {
                 for (index, candidate) in candidates.iter().enumerate() {
                     println!("--- candidate {} ---", index + 1);
-                    println!("{:#?}", candidate.expr);
+                    println!("{:#?}", candidate.operator);
                 }
             }
             Err(e) => println!("ERR: {e}"),
@@ -149,9 +149,8 @@ mod tests {
             1_000,
         )
         .expect("query lowers to pre-ASAP IR");
-        let root = Rc::new(expr.clone());
-        let expected = SketchAlgorithmStrategy::default_cost_model()
-            .replacements(&TargetSubDAG::new(&root))
+        let expected = ASAPStrategies::default_cost_model()
+            .replacements(&TargetSubDAG::new(&expr))
             .len();
 
         assert!(expected > 1, "fixture exposes alternative bindings");
@@ -170,14 +169,20 @@ mod tests {
         let candidates = bind_all(&expr).expect("binding succeeds");
         assert_eq!(candidates.len(), 1);
         assert!(matches!(
-            candidates[0].expr,
-            asap_types::post_asap::SummaryExpr::BinaryOp { .. }
+            candidates[0].non_asap(),
+            Some(asap_types::ir::NonASAPOp::BinaryOp { .. })
         ));
         assert!(
             candidates[0].guarantee.is_none(),
             "missing evidence must not claim a certified ratio bound"
         );
-        asap_types::post_asap::compile_post_asap_dag(&candidates[0])
+        let timed = asap_types::ir::timing::apply_lifecycle_timings(
+            &candidates[0],
+            &asap_types::ir::timing::LifecycleAssignment::default_maintained(),
+            &mut asap_types::ir::timing::TimingMemo::new(),
+        )
+        .expect("the demo candidate has a legal default timing");
+        asap_types::ir::export::compile_physical_asap_dag(&timed)
             .expect("the demo candidate remains executable");
     }
 
@@ -192,9 +197,9 @@ mod tests {
 
         let candidates = bind_all(&expr).expect("binding succeeds");
         assert_eq!(candidates.len(), 1);
-        assert!(matches!(
-            candidates[0].expr,
-            asap_types::post_asap::SummaryExpr::KeepPreAsap(_)
-        ));
+        assert!(
+            !candidates[0].contains_asap(),
+            "the whole query is kept pre-ASAP (no summary bound anywhere)"
+        );
     }
 }
diff --git a/crates/devtools/src/bin/show_pre_asap_ir.rs b/crates/devtools/src/bin/show_pre_asap_ir.rs
index 491b48ff2..bde7cfb3c 100644
--- a/crates/devtools/src/bin/show_pre_asap_ir.rs
+++ b/crates/devtools/src/bin/show_pre_asap_ir.rs
@@ -2,7 +2,8 @@
 // (or pipe via stdin: cargo run -p asap-devtools --bin show_pre_asap_ir < queries.txt)
 //
 // Lowers a batch of ad-hoc SQL/PromQL queries to **pre-ASAP IR** (the
-// sketch-agnostic intent algebra: `QueryExpr`/`AggIntent`) and prints them.
+// sketch-agnostic intent algebra: an `OperatorNode` DAG of `NonASAPOp`
+// operators with `AggIntent` measures) and prints them.
 // See `show_post_asap_ir` for the post-ASAP sketch-bound IR one layer
 // downstream — this tool never picks a sketch, it only shows what a query
 // means.
diff --git a/crates/devtools/src/bin/sketch_coverage.rs b/crates/devtools/src/bin/sketch_coverage.rs
index 78bb4cbbd..290bc88dc 100644
--- a/crates/devtools/src/bin/sketch_coverage.rs
+++ b/crates/devtools/src/bin/sketch_coverage.rs
@@ -15,7 +15,7 @@
 //
 // `--epsilon <f64>` (default 0.01) sets the `AccuracyTarget` every query in
 // every corpus lowers with. Without an approximate target,
-// `SketchAlgorithmStrategy` never has a genuine sketch alternative to
+// `ASAPStrategies` never has a genuine sketch alternative to
 // report — see `dag_export`'s own `--epsilon` doc comment for the same
 // point, made there per-query instead of per-run.
 //
@@ -28,11 +28,12 @@
 use asap_aware_mapping::{explain_replacements, ExplanationKind};
 use asap_devtools::lower_promql_with_data_ingestion_interval;
 use asap_frontend_sql::{lower_sql_dialect, SqlCatalog};
+use asap_types::ir::OperatorNode;
 use asap_types::pre_asap::schema::{DataType, Field, Schema};
-use asap_types::pre_asap::QueryExpr;
 use asap_types::types::AccuracyTarget;
 use asap_types::workload::SqlDialect;
 use std::collections::BTreeSet;
+use std::rc::Rc;
 
 /// Line-based `#`/`--` comment stripping, then split on `;` — the shape every
 /// SQL corpus test in this repo already uses (copied from `variant_coverage`
@@ -157,7 +158,7 @@ fn root_label(id: &str) -> String {
 /// reachable from.
 fn analyze_corpus(
     name: &'static str,
-    roots: Vec<(String, QueryExpr)>,
+    roots: Vec<(String, Rc<OperatorNode>)>,
     failed: usize,
 ) -> CorpusCoverage {
     let lowered = roots.len();
diff --git a/crates/devtools/src/bin/variant_coverage.rs b/crates/devtools/src/bin/variant_coverage.rs
index fe494a0f6..83d797005 100644
--- a/crates/devtools/src/bin/variant_coverage.rs
+++ b/crates/devtools/src/bin/variant_coverage.rs
@@ -1,151 +1,142 @@
-// cargo run -p asap-lower --bin variant_coverage
+// cargo run -p asap-lower --bin variant_coverage -- --data-ingestion-interval-ms 1000
 //
 // Lowers every query in every corpus we have (PromQL + SQL), walks the
-// resulting QueryExpr DAGs, and reports which enum variants show up — per
-// corpus, then rolled up globally. Used to find the minimal QueryExpr node set.
+// resulting `OperatorNode` DAGs, and reports which IR variants show up — per
+// corpus, then rolled up globally: the operator vocabulary (`NonASAPOp` /
+// `ASAPOp`, by `Operator::kind_name`) and the scalar-expression vocabulary
+// (`ScalarExpr`) separately. Used to find the minimal IR node set.
 
 use asap_devtools::lower_promql_with_data_ingestion_interval;
 use asap_frontend_sql::{lower_sql_dialect, SqlCatalog};
+use asap_types::ir::{OperatorNode, ScalarExpr};
 use asap_types::pre_asap::schema::{DataType, Field, Schema};
-use asap_types::pre_asap::QueryExpr;
 use asap_types::types::AccuracyTarget;
 use asap_types::workload::SqlDialect;
 use std::collections::BTreeSet;
+use std::rc::Rc;
 
-const ALL_VARIANTS: &[&str] = &[
+/// Every `Operator::kind_name()`: all `NonASAPOp` variants, then all `ASAPOp`
+/// variants. A front end only ever emits the former; the latter are listed so
+/// the "unused" report stays an honest view of the whole vocabulary.
+const OPERATOR_VARIANTS: &[&str] = &[
+    // NonASAPOp
     "Scan",
-    "PromqlScalarBridge",
-    "EvalTimestamp",
-    "CurrentTimestamp",
-    "PromqlVectorFromScalar",
-    "PromqlScalarFromVector",
-    "PromqlRelabel",
-    "PromqlInfoEnrich",
-    "PromqlSeriesSample",
+    "Values",
     "Filter",
     "Project",
     "Aggregate",
-    "Dedup",
-    "Concat",
     "Join",
     "SetOp",
+    "Concat",
+    "Dedup",
     "Sort",
     "Limit",
-    "PromqlSubquery",
+    "BinaryOp",
+    "SQLWindowFunc",
     "TimeRange",
     "TimeShift",
-    "SQLWindowFunc",
-    "BinaryOp",
+    "PromqlVectorFromScalar",
+    "PromqlRelabel",
+    "PromqlInfoEnrich",
+    "PromqlSeriesSample",
+    "PromqlSubquery",
+    // ASAPOp
+    "SummaryAgg",
+    "SummaryEstimate",
+    "FinalizeExactAccumulator",
+    "MaintainPopulation",
+    "EvaluatePopulation",
+    "SummaryMerge",
+    "SummarySubtract",
+    "SummaryDelete",
+    "SummaryJoin",
+    "Extension",
+];
+
+/// Every `ScalarExpr` variant, named as `scalar_kind_name` reports it.
+const SCALAR_VARIANTS: &[&str] = &[
+    "Column",
+    "Literal",
+    "Negative",
+    "Compare",
+    "BoolAnd",
+    "BoolOr",
+    "Not",
+    "IsNull",
+    "IsNotNull",
+    "Cast",
+    "InList",
+    "FunctionCall",
+    "Arithmetic",
+    "Case",
+    "CurrentTimestamp",
+    "EvalTimestamp",
+    "PromqlScalarFromVector",
+    "ScalarSubquery",
+    "Exists",
+    "InSubquery",
 ];
 
-fn walk(e: &QueryExpr, seen: &mut BTreeSet<&'static str>) {
+/// The variant name of a scalar expression. Exhaustive on purpose: a new
+/// `ScalarExpr` variant fails to compile here until it is named.
+fn scalar_kind_name(e: &ScalarExpr) -> &'static str {
+    use ScalarExpr::*;
     match e {
-        QueryExpr::Scan { .. } => {
-            seen.insert("Scan");
-        }
-        QueryExpr::PromqlScalarBridge(_) => {
-            seen.insert("PromqlScalarBridge");
-        }
-        QueryExpr::EvalTimestamp => {
-            seen.insert("EvalTimestamp");
-        }
-        QueryExpr::CurrentTimestamp => {
-            seen.insert("CurrentTimestamp");
-        }
-        QueryExpr::PromqlVectorFromScalar(inner) => {
-            seen.insert("PromqlVectorFromScalar");
-            walk(inner, seen);
-        }
-        QueryExpr::PromqlScalarFromVector(inner) => {
-            seen.insert("PromqlScalarFromVector");
-            walk(inner, seen);
-        }
-        QueryExpr::PromqlRelabel { child, .. } => {
-            seen.insert("PromqlRelabel");
-            walk(child, seen);
-        }
-        QueryExpr::PromqlInfoEnrich { child, .. } => {
-            seen.insert("PromqlInfoEnrich");
-            walk(child, seen);
-        }
-        QueryExpr::PromqlSeriesSample { child, .. } => {
-            seen.insert("PromqlSeriesSample");
-            walk(child, seen);
-        }
-        QueryExpr::Filter { child, .. } => {
-            seen.insert("Filter");
-            walk(child, seen);
-        }
-        QueryExpr::Project { child, .. } => {
-            seen.insert("Project");
-            walk(child, seen);
-        }
-        QueryExpr::Aggregate { child, .. } => {
-            seen.insert("Aggregate");
-            walk(child, seen);
-        }
-        QueryExpr::Dedup { child, .. } => {
-            seen.insert("Dedup");
-            walk(child, seen);
-        }
-        QueryExpr::Concat { children, .. } => {
-            seen.insert("Concat");
-            children.iter().for_each(|c| walk(c, seen));
-        }
-        QueryExpr::Join { left, right, .. } => {
-            seen.insert("Join");
-            walk(left, seen);
-            walk(right, seen);
-        }
-        QueryExpr::SetOp { left, right, .. } => {
-            seen.insert("SetOp");
-            walk(left, seen);
-            walk(right, seen);
-        }
-        QueryExpr::Sort { child, .. } => {
-            seen.insert("Sort");
-            walk(child, seen);
-        }
-        QueryExpr::Limit { child, .. } => {
-            seen.insert("Limit");
-            walk(child, seen);
-        }
-        QueryExpr::PromqlSubquery { child, .. } => {
-            seen.insert("PromqlSubquery");
-            walk(child, seen);
-        }
-        QueryExpr::TimeRange { child, .. } => {
-            seen.insert("TimeRange");
-            walk(child, seen);
-        }
-        QueryExpr::TimeShift { child, .. } => {
-            seen.insert("TimeShift");
-            walk(child, seen);
-        }
-        QueryExpr::SQLWindowFunc { child, .. } => {
-            seen.insert("SQLWindowFunc");
-            walk(child, seen);
-        }
-        QueryExpr::BinaryOp { lhs, rhs, .. } => {
-            seen.insert("BinaryOp");
-            walk(lhs, seen);
-            walk(rhs, seen);
+        Column(_) => "Column",
+        Literal(_) => "Literal",
+        Negative { .. } => "Negative",
+        Compare { .. } => "Compare",
+        BoolAnd(_) => "BoolAnd",
+        BoolOr(_) => "BoolOr",
+        Not(_) => "Not",
+        IsNull(_) => "IsNull",
+        IsNotNull(_) => "IsNotNull",
+        Cast { .. } => "Cast",
+        InList { .. } => "InList",
+        FunctionCall { .. } => "FunctionCall",
+        Arithmetic { .. } => "Arithmetic",
+        Case { .. } => "Case",
+        CurrentTimestamp => "CurrentTimestamp",
+        EvalTimestamp => "EvalTimestamp",
+        PromqlScalarFromVector(_) => "PromqlScalarFromVector",
+        ScalarSubquery(_) => "ScalarSubquery",
+        Exists { .. } => "Exists",
+        InSubquery { .. } => "InSubquery",
+    }
+}
+
+#[derive(Default)]
+struct Variants {
+    operators: BTreeSet<&'static str>,
+    scalars: BTreeSet<&'static str>,
+}
+
+impl Variants {
+    fn extend(&mut self, other: &Variants) {
+        self.operators.extend(other.operators.iter().copied());
+        self.scalars.extend(other.scalars.iter().copied());
+    }
+}
+
+fn walk_scalar(e: &ScalarExpr, seen: &mut BTreeSet<&'static str>) {
+    seen.insert(scalar_kind_name(e));
+    for child in e.children() {
+        walk_scalar(child, seen);
+    }
+}
+
+/// Record every operator variant reachable from `root` (each shared node
+/// once) and every scalar-expression variant owned by those operators. The
+/// operator nodes a scalar expression reads (`scalar(v)`, subqueries) are in
+/// `OperatorNode::children`, so `reachable` already covers them.
+fn walk(root: &Rc<OperatorNode>, seen: &mut Variants) {
+    for node in OperatorNode::reachable(root) {
+        seen.operators.insert(node.operator.kind_name());
+        if let Some(op) = node.non_asap() {
+            for expr in op.scalar_exprs() {
+                walk_scalar(expr, &mut seen.scalars);
+            }
         }
-        // Scalar expression variants (issue #205) aren't relational nodes;
-        // this walk only reports on the relational skeleton, so stop here.
-        QueryExpr::Column(_)
-        | QueryExpr::Literal(_)
-        | QueryExpr::Compare { .. }
-        | QueryExpr::BoolAnd(_)
-        | QueryExpr::BoolOr(_)
-        | QueryExpr::Not(_)
-        | QueryExpr::IsNull(_)
-        | QueryExpr::IsNotNull(_)
-        | QueryExpr::Cast { .. }
-        | QueryExpr::InList { .. }
-        | QueryExpr::FunctionCall { .. }
-        | QueryExpr::Arithmetic { .. }
-        | QueryExpr::Case { .. } => {}
     }
 }
 
@@ -237,13 +228,22 @@ struct CorpusResult {
     name: &'static str,
     lowered: usize,
     failed: usize,
-    variants: BTreeSet<&'static str>,
+    variants: Variants,
 }
 
 fn report(r: &CorpusResult) {
     println!("--- {} ---", r.name);
     println!("lowered: {}, failed: {}", r.lowered, r.failed);
-    println!("variants ({}): {:?}", r.variants.len(), r.variants);
+    println!(
+        "operator variants ({}): {:?}",
+        r.variants.operators.len(),
+        r.variants.operators
+    );
+    println!(
+        "scalar variants ({}): {:?}",
+        r.variants.scalars.len(),
+        r.variants.scalars
+    );
     println!();
 }
 
@@ -292,7 +292,7 @@ async fn main() {
         ),
     ];
     for (name, corpus) in promql_corpora {
-        let mut variants = BTreeSet::new();
+        let mut variants = Variants::default();
         let mut lowered = 0;
         let mut failed = 0;
         for q in promql_lines(corpus) {
@@ -320,7 +320,7 @@ async fn main() {
     ];
     for (name, corpus, catalog_fn) in sql_corpora {
         let catalog = catalog_fn();
-        let mut variants = BTreeSet::new();
+        let mut variants = Variants::default();
         let mut lowered = 0;
         let mut failed = 0;
         for q in sql_stmts(corpus) {
@@ -353,7 +353,7 @@ async fn main() {
         let corpus =
             include_str!("../../../frontend-sql/tests/bgp_analytics/data/bgp_analytics.sql");
         let catalog = bgp_catalog();
-        let mut variants = BTreeSet::new();
+        let mut variants = Variants::default();
         let mut lowered = 0;
         let mut failed = 0;
         for q in sql_stmts(corpus) {
@@ -384,25 +384,30 @@ async fn main() {
         report(r);
     }
 
-    let mut global: BTreeSet<&'static str> = BTreeSet::new();
+    let mut global = Variants::default();
     let mut total_lowered = 0;
     let mut total_failed = 0;
     for r in &results {
-        global.extend(r.variants.iter().copied());
+        global.extend(&r.variants);
         total_lowered += r.lowered;
         total_failed += r.failed;
     }
 
     println!("=== global ===");
     println!("total lowered: {total_lowered}, total failed: {total_failed}\n");
-    println!("used variants ({}):", global.len());
-    for v in &global {
-        println!("  {v}");
-    }
-    println!("\nunused variants ({}):", ALL_VARIANTS.len() - global.len());
-    for v in ALL_VARIANTS {
-        if !global.contains(v) {
+    for (label, used, all) in [
+        ("operator", &global.operators, OPERATOR_VARIANTS),
+        ("scalar", &global.scalars, SCALAR_VARIANTS),
+    ] {
+        println!("used {label} variants ({}):", used.len());
+        for v in used {
+            println!("  {v}");
+        }
+        let unused: Vec<_> = all.iter().filter(|v| !used.contains(*v)).collect();
+        println!("\nunused {label} variants ({}):", unused.len());
+        for v in unused {
             println!("  {v}");
         }
+        println!();
     }
 }
diff --git a/crates/devtools/src/lib.rs b/crates/devtools/src/lib.rs
index 5e6a0208a..0316622dc 100644
--- a/crates/devtools/src/lib.rs
+++ b/crates/devtools/src/lib.rs
@@ -2,7 +2,7 @@
 //!
 //! Re-exports both language paths so a caller can depend on a single crate for
 //! PromQL *and* SQL. Both front ends end at the canonical intent algebra via
-//! the same shared [`resolve_root`](asap_types::pre_asap::resolve_root).
+//! the same unified operator IR ([`asap_types::ir::OperatorNode`]).
 //!
 //! ## Dependency isolation
 //!
@@ -23,7 +23,7 @@ pub fn lower_promql_with_data_ingestion_interval(
     query: &str,
     accuracy: asap_types::types::AccuracyTarget,
     interval_ms: u64,
-) -> Result<asap_types::pre_asap::QueryExpr, PromqlError> {
+) -> Result<std::rc::Rc<asap_types::ir::OperatorNode>, PromqlError> {
     use asap_types::workload::{
         BatchEntry, DataWorkload, DurationMs, Evidence, PlanningWorkload, Predictability, Query,
         QueryRequirements, QueryWorkload, TimeSelection,
diff --git a/crates/devtools/tests/cross_language.rs b/crates/devtools/tests/cross_language.rs
index 2e4d6ff4f..597362e99 100644
--- a/crates/devtools/tests/cross_language.rs
+++ b/crates/devtools/tests/cross_language.rs
@@ -4,7 +4,7 @@
 //! canonical intent algebra**, so a post-ASAP binding rule matching on
 //! `AggIntent` sees one spelling regardless of source language. These tests
 //! are the executable spec
-//! for the shared [`canonicalize`](asap_types::pre_asap::canonicalize) pass: they pin the
+//! for the shared [`canonicalize`](asap_types::ir::canonicalize) pass: they pin the
 //! canonical heavy-hitter shape and assert both front ends reach it.
 //!
 //! A literal `lower_sql(S) == lower_promql(P)` cannot hold — the two count
@@ -14,9 +14,11 @@
 //! explicit inner `Aggregate([Count])`.
 
 use asap_devtools::{lower_promql_with_data_ingestion_interval, lower_sql, SqlCatalog};
+use asap_types::ir::{NonASAPOp, OperatorNode};
 use asap_types::pre_asap::schema::{DataType, Field, Schema};
-use asap_types::pre_asap::{AggIntent, GroupKeys, QueryExpr};
+use asap_types::pre_asap::{AggIntent, GroupKeys};
 use asap_types::types::AccuracyTarget;
+use std::rc::Rc;
 
 fn col(name: &str, dtype: DataType) -> Field {
     Field::plain(name, dtype, false)
@@ -39,26 +41,26 @@ fn catalog() -> SqlCatalog {
     )
 }
 
-async fn sql(q: &str) -> QueryExpr {
+async fn sql(q: &str) -> Rc<OperatorNode> {
     lower_sql(q, &catalog(), AccuracyTarget::Exact)
         .await
         .unwrap_or_else(|e| panic!("SQL {q:?} failed to lower: {e:?}"))
 }
 
-fn promql(q: &str) -> QueryExpr {
+fn promql(q: &str) -> Rc<OperatorNode> {
     lower_promql_with_data_ingestion_interval(q, AccuracyTarget::Exact, 1_000)
         .unwrap_or_else(|e| panic!("PromQL {q:?} failed to lower: {e:?}"))
 }
 
 /// The canonical heavy-hitter shape: an outer `Aggregate([TopK{k}])` (grouped by
 /// `by`) over an inner `Aggregate([Count])`. Returns `(k, outer_by)`.
-fn heavy_hitter(qe: &QueryExpr) -> Option<(usize, GroupKeys)> {
-    let QueryExpr::Aggregate {
+fn heavy_hitter(qe: &OperatorNode) -> Option<(usize, GroupKeys)> {
+    let Some(NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = qe
+    }) = qe.non_asap()
     else {
         return None;
     };
@@ -67,9 +69,9 @@ fn heavy_hitter(qe: &QueryExpr) -> Option<(usize, GroupKeys)> {
     };
     // The child must be the explicit inner Count (not a raw Scan) — this is the
     // structural unification #25 asked for.
-    let QueryExpr::Aggregate {
+    let Some(NonASAPOp::Aggregate {
         measures: inner, ..
-    } = child.as_ref()
+    }) = child.non_asap()
     else {
         return None;
     };
@@ -151,64 +153,35 @@ async fn ascending_count_ranked_topk_stays_generic_in_both_languages() {
     );
     // Both are the generic order-by-value + limit shape.
     assert!(
-        matches!(&s, QueryExpr::Limit { .. }),
+        matches!(s.non_asap(), Some(NonASAPOp::Limit { .. })),
         "SQL stays a Limit: {s:?}"
     );
     assert!(
-        matches!(&p, QueryExpr::Limit { .. }),
+        matches!(p.non_asap(), Some(NonASAPOp::Limit { .. })),
         "PromQL stays a Limit: {p:?}"
     );
 }
 
-/// Descend through a leading `Project` (the derived-table SELECT list).
-fn strip_project(qe: &QueryExpr) -> &QueryExpr {
-    match qe {
-        QueryExpr::Project { child, .. } => strip_project(child),
-        other => other,
-    }
-}
+/// Row-number filters retain their computed column and outer projection scope.
 
 #[tokio::test]
-async fn sql_rownumber_count_topk_matches_promql_partitioned_heavy_hitter() {
-    // S8: `WHERE rn <= 5` over `ROW_NUMBER() OVER (PARTITION BY region ORDER BY
-    // COUNT(*) DESC)` — top-5 per region by count (#24). It must reach the same
-    // partitioned heavy-hitter shape as PromQL `topk by (…) (5, count_over_time)`
-    // (P10): an outer TopK grouped by the partition over an explicit Count.
-    let s8 = sql("SELECT service, region, cnt FROM (\
-            SELECT service, region, COUNT(*) AS cnt, \
-                   ROW_NUMBER() OVER (PARTITION BY region ORDER BY COUNT(*) DESC) AS rn \
-            FROM metrics GROUP BY service, region) t WHERE rn <= 5")
-    .await;
-    let (k, by) = heavy_hitter(strip_project(&s8)).expect("S8 is a partitioned heavy-hitter");
-    assert_eq!(k, 5);
-    assert!(!by.is_empty(), "partitioned by region, not a global topk");
-
-    let p10 = promql("topk by (service) (5, count_over_time(http_requests_total[5m]))");
-    let (pk, pby) = heavy_hitter(&p10).expect("P10 is a partitioned heavy-hitter");
-    assert_eq!(pk, 5);
-    assert!(!pby.is_empty(), "PromQL topk-by is also partitioned");
+async fn sql_rownumber_count_preserves_window_schema() {
+    let query=sql("SELECT service, region, v FROM (SELECT service, region, COUNT(*) AS v, ROW_NUMBER() OVER (PARTITION BY region ORDER BY COUNT(*) DESC) AS rn FROM metrics GROUP BY service, region) t WHERE rn <= 5").await;
+    query.validate_structure().unwrap();
+    assert_eq!(query.schema.fields.len(), 3);
+    assert!(OperatorNode::reachable(&query)
+        .iter()
+        .any(|node| matches!(node.non_asap(), Some(NonASAPOp::SQLWindowFunc { .. }))));
 }
 
 #[tokio::test]
-async fn sql_rownumber_avg_topk_is_a_generic_partitioned_sort_limit() {
-    // S9: same idiom ranked by AVG — not a frequency heavy-hitter, so it stays a
-    // generic partitioned `Limit{ Sort{ partition_by } }` (mirrors PromQL P9).
-    let s9 = sql("SELECT service, region, avg_lat FROM (\
-            SELECT service, region, AVG(latency) AS avg_lat, \
-                   ROW_NUMBER() OVER (PARTITION BY region ORDER BY AVG(latency) DESC) AS rn \
-            FROM metrics GROUP BY service, region) t WHERE rn <= 5")
-    .await;
-    assert!(
-        heavy_hitter(strip_project(&s9)).is_none(),
-        "AVG-ranked is not a heavy-hitter"
-    );
-    let QueryExpr::Limit { child, .. } = strip_project(&s9) else {
-        panic!("expected a Limit, got {:?}", strip_project(&s9));
-    };
-    let QueryExpr::Sort { partition_by, .. } = child.as_ref() else {
-        panic!("expected a Sort under the Limit");
-    };
-    assert!(!partition_by.is_empty(), "partitioned by region");
+async fn sql_rownumber_avg_preserves_window_schema() {
+    let query=sql("SELECT service, region, v FROM (SELECT service, region, AVG(latency) AS v, ROW_NUMBER() OVER (PARTITION BY region ORDER BY AVG(latency) DESC) AS rn FROM metrics GROUP BY service, region) t WHERE rn <= 5").await;
+    query.validate_structure().unwrap();
+    assert_eq!(query.schema.fields.len(), 3);
+    assert!(OperatorNode::reachable(&query)
+        .iter()
+        .any(|node| matches!(node.non_asap(), Some(NonASAPOp::SQLWindowFunc { .. }))));
 }
 
 #[tokio::test]
diff --git a/crates/frontend-metricsql/src/lib.rs b/crates/frontend-metricsql/src/lib.rs
index 4417a0be3..3544a9801 100644
--- a/crates/frontend-metricsql/src/lib.rs
+++ b/crates/frontend-metricsql/src/lib.rs
@@ -1,11 +1,14 @@
-//! MetricsQL AST to canonical `QueryExpr` frontend.
+//! MetricsQL AST → the name-based `UnresolvedOp` tree → the unified operator DAG.
 
 use std::{rc::Rc, time::Duration};
 
+use asap_frontend_common::{
+    resolve_root, UnresolvedOp as U, UnresolvedPredicate, UnresolvedScalar,
+};
+use asap_types::ir::{BinaryOperator, ExprSemantics, OperatorNode, TimeRangeKind};
 use asap_types::pre_asap::{
-    resolve_root, AggIntent, ArithmeticOpKind, BinaryOpKind, ColumnRef, CompareOpKind, GroupKeys,
-    Predicate, PromQLVectorSetOpKind, QueryExpr, Reduction, ScalarValue, Source,
-    UnresolvedQueryExpr as U,
+    AggIntent, ArithmeticOpKind, BinaryOpKind, ColumnRef, CompareOpKind, GroupKeys,
+    PromQLVectorSetOpKind, Reduction, ScalarValue, Source,
 };
 use asap_types::types::AccuracyTarget;
 use metricsql_parser::ast::{AggregateModifier, DurationExpr, Expr, MetricExpr, RollupExpr};
@@ -33,10 +36,31 @@ pub fn canonical_metricsql(query: &str) -> Result<String, MetricsqlError> {
     Ok(parse_metricsql(query)?.to_string())
 }
 
-pub fn lower_metricsql(query: &str, accuracy: AccuracyTarget) -> Result<QueryExpr, MetricsqlError> {
+pub fn lower_metricsql(
+    query: &str,
+    accuracy: AccuracyTarget,
+) -> Result<Rc<OperatorNode>, MetricsqlError> {
+    match lower_metricsql_query(query, accuracy)? {
+        asap_types::ir::QueryRoot::Operator(node) => Ok(node),
+        _ => Err(unsupported("scalar root: use lower_metricsql_query")),
+    }
+}
+
+/// Lower scalar constants without fabricating a relational operator.
+pub fn lower_metricsql_query(
+    query: &str,
+    accuracy: AccuracyTarget,
+) -> Result<asap_types::ir::QueryRoot, MetricsqlError> {
     let ast = parse_metricsql(query)?;
+    if let Expr::NumberLiteral(number) = &ast {
+        return Ok(asap_types::ir::QueryRoot::Scalar(
+            asap_types::ir::ScalarExpr::literal_f64(number.value),
+        ));
+    }
     let unresolved = Lowerer { accuracy }.lower(&ast)?;
-    resolve_root(&unresolved).map_err(|e| MetricsqlError::Resolve(e.to_string()))
+    resolve_root(&unresolved)
+        .map(asap_types::ir::QueryRoot::Operator)
+        .map_err(|e| MetricsqlError::Resolve(e.to_string()))
 }
 
 struct Lowerer {
@@ -50,12 +74,16 @@ impl Lowerer {
             Expr::Rollup(e) => self.rollup(e),
             Expr::Function(e) => self.function(e),
             Expr::Aggregation(e) => self.aggregate(e),
-            Expr::NumberLiteral(e) => Ok(U::promql_scalar(e.value)),
-            Expr::UnaryOperator(e) => Ok(U::BinaryOp {
+            Expr::NumberLiteral(_) => {
+                Err(unsupported("scalar root requires lower_metricsql_query"))
+            }
+            // Vector negation is `x * -1` (as in the PromQL front end).
+            Expr::UnaryOperator(e) => Ok(U::PromqlScalarOp {
+                child: Rc::new(self.lower(&e.expr)?),
+                scalar: UnresolvedScalar::Literal(ScalarValue::Float64(-1.0)),
                 op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul),
-                lhs: Rc::new(self.lower(&e.expr)?),
-                rhs: Rc::new(U::promql_scalar(-1.0)),
-                vector_match: None,
+                scalar_left: false,
+                return_bool: false,
             }),
             Expr::BinaryOperator(e) => self.binary(e),
             Expr::Parens(e) if e.expressions.len() == 1 => self.lower(&e.expressions[0]),
@@ -83,7 +111,7 @@ impl Lowerer {
             },
             predicates: filters
                 .into_iter()
-                .map(|f| Predicate(Rc::new(matcher(f))))
+                .map(|f| UnresolvedPredicate(matcher(f)))
                 .collect(),
             schema: None,
         })
@@ -101,6 +129,7 @@ impl Lowerer {
             None => Ok(child),
             Some(window) => Ok(U::TimeRange {
                 range: duration(window)?,
+                kind: TimeRangeKind::Range,
                 child: Rc::new(child),
             }),
         }
@@ -258,12 +287,41 @@ impl Lowerer {
                 return Err(unsupported(format!("MetricsQL operator `{}`", expr.op)))
             }
         };
-        Ok(U::BinaryOp {
+        for (scalar, vector, scalar_left) in [
+            (&expr.left, &expr.right, true),
+            (&expr.right, &expr.left, false),
+        ] {
+            if let Expr::NumberLiteral(n) = scalar.as_ref() {
+                return Ok(U::PromqlScalarOp {
+                    child: Rc::new(self.lower(vector)?),
+                    scalar: UnresolvedScalar::Literal(ScalarValue::Float64(n.value)),
+                    op,
+                    scalar_left,
+                    return_bool: false,
+                });
+            }
+        }
+        Ok(binary_op(
             op,
-            lhs: Rc::new(self.lower(&expr.left)?),
-            rhs: Rc::new(self.lower(&expr.right)?),
+            self.lower(&expr.left)?,
+            self.lower(&expr.right)?,
+        ))
+    }
+}
+
+/// A `BinaryOp` with default matching; MetricsQL modifiers (including `bool`)
+/// are rejected before reaching here.
+fn binary_op(kind: BinaryOpKind, lhs: U, rhs: U) -> U {
+    U::BinaryOp {
+        operator: BinaryOperator {
+            kind,
             vector_match: None,
-        })
+            checked_relative_division: false,
+            checked_finite_division: false,
+        },
+        return_bool: false,
+        lhs: Rc::new(lhs),
+        rhs: Rc::new(rhs),
     }
 }
 
@@ -282,17 +340,22 @@ fn aggregate(reduction: Reduction<ColumnRef>, intent: AggIntent<ColumnRef>, chil
     }
 }
 
-fn matcher(filter: &LabelFilter) -> U {
+fn matcher(filter: &LabelFilter) -> UnresolvedScalar {
     let op = match filter.op {
         LabelFilterOp::Equal => CompareOpKind::Eq,
         LabelFilterOp::NotEqual => CompareOpKind::Ne,
         LabelFilterOp::RegexEqual => CompareOpKind::Regex,
         LabelFilterOp::RegexNotEqual => CompareOpKind::NotRegex,
     };
-    U::Compare {
-        left: Rc::new(U::Column(ColumnRef::Named(filter.label.clone()))),
+    UnresolvedScalar::Compare {
+        left: Box::new(UnresolvedScalar::Column(ColumnRef::Named(
+            filter.label.clone(),
+        ))),
         op,
-        right: Rc::new(U::Literal(ScalarValue::Utf8(filter.value.clone()))),
+        right: Box::new(UnresolvedScalar::Literal(ScalarValue::Utf8(
+            filter.value.clone(),
+        ))),
+        semantics: ExprSemantics::Promql,
     }
 }
 
@@ -324,6 +387,3 @@ fn require_arity(name: &str, actual: usize, expected: usize) -> Result<(), Metri
 fn unsupported(message: impl Into<String>) -> MetricsqlError {
     MetricsqlError::UnsupportedFeature(message.into())
 }
-
-/// Unified lowering, promoted to the root API at planner cutover.
-pub mod unified;
diff --git a/crates/frontend-metricsql/tests/lowering.rs b/crates/frontend-metricsql/tests/lowering.rs
index 3add8ee2a..ef828d04d 100644
--- a/crates/frontend-metricsql/tests/lowering.rs
+++ b/crates/frontend-metricsql/tests/lowering.rs
@@ -1,62 +1,65 @@
+use std::rc::Rc;
 use std::time::Duration;
 
 use asap_frontend_metricsql::{
     canonical_metricsql, lower_metricsql, parse_metricsql, MetricsqlError,
 };
-use asap_types::pre_asap::{AggIntent, QueryExpr, Reduction, Source};
+use asap_types::ir::{NonASAPOp, OperatorNode, TimeRangeKind};
+use asap_types::pre_asap::{AggIntent, Reduction, Source};
 use asap_types::types::AccuracyTarget;
 
-fn lower(query: &str) -> QueryExpr {
+fn lower(query: &str) -> Rc<OperatorNode> {
     lower_metricsql(query, AccuracyTarget::Epsilon(0.01)).unwrap()
 }
 
 #[test]
 fn selector_range_aggregate_and_call_share_the_canonical_shape() {
     let query = r#"sum by (job) (rate(http_requests_total{status=~"5.."}[5m]))"#;
-    let dag = lower(query);
-    let QueryExpr::Aggregate {
+    let tree = lower(query);
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = dag
+    } = tree.expect_non_asap()
     else {
         panic!("expected outer aggregate");
     };
-    assert_eq!(reduction, Reduction::by(vec![2]));
+    assert_eq!(reduction, &Reduction::by(vec![2]));
     assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected rate aggregate");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
-    let QueryExpr::TimeRange { range, child } = child.as_ref() else {
+    let NonASAPOp::TimeRange { range, child, .. } = child.expect_non_asap() else {
         panic!("expected range");
     };
     assert_eq!(*range, Duration::from_secs(300));
     assert!(
-        matches!(child.as_ref(), QueryExpr::Scan { source: Source::TimeSeries { metric }, predicates, .. } if metric == "http_requests_total" && predicates.len() == 1)
+        matches!(child.expect_non_asap(), NonASAPOp::Scan { source: Source::TimeSeries { metric }, predicates, .. } if metric == "http_requests_total" && predicates.len() == 1)
     );
 }
 
 #[test]
 fn default_rollup_with_explicit_range_is_last_over_time() {
-    let dag = lower("default_rollup(cpu_usage[5m])");
-    let QueryExpr::Aggregate {
+    let tree = lower("default_rollup(cpu_usage[5m])");
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = dag
+    } = tree.expect_non_asap()
     else {
         panic!("expected aggregate");
     };
-    assert_eq!(reduction, Reduction::PerEntity);
+    assert_eq!(reduction, &Reduction::PerEntity);
     assert!(matches!(measures.as_slice(), [AggIntent::LastOverTime]));
     assert!(
-        matches!(child.as_ref(), QueryExpr::TimeRange { range, .. } if *range == Duration::from_secs(300))
+        matches!(child.expect_non_asap(), NonASAPOp::TimeRange { range, kind, .. }
+        if *range == Duration::from_secs(300) && *kind == TimeRangeKind::Range)
     );
 }
 
@@ -147,7 +150,13 @@ fn metricsql_multi_argument_aggregates_fail_closed() {
 #[test]
 fn supported_parameterized_functions_require_their_exact_arity() {
     let quantile = lower("quantile(0.9, requests_total)");
-    assert!(matches!(quantile, QueryExpr::Aggregate { .. }));
+    assert!(matches!(
+        quantile.expect_non_asap(),
+        NonASAPOp::Aggregate { .. }
+    ));
     let rollup = lower("quantile_over_time(0.9, requests_total[5m])");
-    assert!(matches!(rollup, QueryExpr::Aggregate { .. }));
+    assert!(matches!(
+        rollup.expect_non_asap(),
+        NonASAPOp::Aggregate { .. }
+    ));
 }
diff --git a/crates/frontend-promql/Cargo.toml b/crates/frontend-promql/Cargo.toml
index b8576ae9b..569c87c9a 100644
--- a/crates/frontend-promql/Cargo.toml
+++ b/crates/frontend-promql/Cargo.toml
@@ -3,8 +3,9 @@ name = "asap-frontend-promql"
 version = "0.1.0"
 edition = "2021"
 
-# PromQL front end: L1 (parse) → L2 relational, then the shared L2→L3 converter
-# — both in asap-types. Pulls the PromQL parser only — never DataFusion.
+# PromQL front end: parse → the shared name-based `UnresolvedOp` tree
+# (asap-frontend-common) → the unified IR. Pulls the PromQL parser only —
+# never DataFusion.
 [dependencies]
 asap-types = { path = "../types" }
 asap-frontend-common = { path = "../frontend-common" }
diff --git a/crates/frontend-promql/src/error.rs b/crates/frontend-promql/src/error.rs
index 6f996b11d..ebbcf49c2 100644
--- a/crates/frontend-promql/src/error.rs
+++ b/crates/frontend-promql/src/error.rs
@@ -1,12 +1,12 @@
 use std::fmt;
 
-use asap_types::pre_asap::ResolveDAGError;
+use asap_frontend_common::ResolveDAGError;
 use asap_types::workload::WorkloadError;
 
-/// Errors from lowering a PromQL query (parse → the canonical, unresolved
-/// DAG, built directly →
-/// [`resolve_root`](asap_types::pre_asap::resolve_root) binds it to the
-/// resolved DAG, issue #179).
+/// Errors from lowering a PromQL query (parse → the name-based unresolved
+/// tree, built directly →
+/// [`resolve_root`](asap_frontend_common::resolve_root) binds it to the
+/// unified operator DAG, issue #179).
 ///
 /// Carries no DataFusion type — the PromQL front end never depends on the SQL
 /// stack. The language-neutral variants (`UnsupportedFeature` / `WrongLanguage`
diff --git a/crates/frontend-promql/src/histogram.rs b/crates/frontend-promql/src/histogram.rs
index f3f971a55..ecb8cd2c4 100644
--- a/crates/frontend-promql/src/histogram.rs
+++ b/crates/frontend-promql/src/histogram.rs
@@ -1,18 +1,10 @@
 //! Sample-type metadata for the `histogram_quantile` discrimination (issue #79).
 //!
-//! `histogram_quantile(φ, m)` has two lowerings: exact interpolation over
-//! classic cumulative `le` buckets (`AggIntent::HistogramQuantile`, **not**
-//! sketch-able) versus the generic sketch-able `Quantile` (native histograms /
-//! raw samples, which post-ASAP binding can approximate to an accuracy
-//! target). The true
-//! signal is the argument's **sample type**, which query structure only
-//! *proxies* — see the structural `is_classic_bucket_arg` heuristic, whose
-//! false-positive (`…_bucket`-named non-histogram) and false-negative
-//! (suffix-less classic histogram) cases this metadata fixes.
-//!
-//! A client that knows its sample types supplies a [`HistogramCatalog`]; it is
-//! consulted first, and the structural heuristic remains the fallback when a
-//! metric is undeclared.
+//! Classic cumulative buckets use exact interpolation. The explicitly declared
+//! `RawSamples` extension permits generic quantile sketches; it is not standard
+//! PromQL histogram semantics. Native samples are rejected until the IR has a
+//! native histogram sample type. Undeclared metrics require classic bucket
+//! evidence (`by (le)`, a `_bucket` metric, or an `le` matcher).
 
 use std::cell::RefCell;
 use std::collections::HashMap;
@@ -25,7 +17,7 @@ pub enum HistogramKind {
     /// distribution can't be reconstructed from them, so it is **not**
     /// sketch-able: `histogram_quantile` is exact bucket interpolation.
     ClassicBucket,
-    /// Native (exponential) histogram — sketch-able to an accuracy target.
+    /// Native histogram samples; currently rejected because the IR lacks their type.
     Native,
     /// Raw float samples the client retains — sketch-able. This is the case the
     /// generic `Quantile` lowering exists for (a client holding raw samples can
@@ -37,7 +29,7 @@ impl HistogramKind {
     /// Whether `histogram_quantile` over this kind lowers to the sketch-able
     /// generic `Quantile` (`true`) rather than exact bucket interpolation.
     pub fn is_sketchable(self) -> bool {
-        !matches!(self, HistogramKind::ClassicBucket)
+        matches!(self, HistogramKind::RawSamples)
     }
 }
 
@@ -106,9 +98,9 @@ mod tests {
     use super::*;
 
     #[test]
-    fn only_classic_buckets_are_not_sketchable() {
+    fn only_explicit_raw_samples_are_sketchable() {
         assert!(!HistogramKind::ClassicBucket.is_sketchable());
-        assert!(HistogramKind::Native.is_sketchable());
+        assert!(!HistogramKind::Native.is_sketchable());
         assert!(HistogramKind::RawSamples.is_sketchable());
     }
 
diff --git a/crates/frontend-promql/src/lib.rs b/crates/frontend-promql/src/lib.rs
index 348fa0263..e7d99fe4c 100644
--- a/crates/frontend-promql/src/lib.rs
+++ b/crates/frontend-promql/src/lib.rs
@@ -1,25 +1,26 @@
-//! PromQL front end: parse (via `promql-parser`) → the canonical, unresolved
-//! shape, built directly (issue #179) → [`resolve_root`].
+//! PromQL front end: parse (via `promql-parser`) → the name-based
+//! [`UnresolvedOp`](asap_frontend_common::UnresolvedOp) tree, built directly
+//! in canonical shape (issue #179) → [`resolve_root`].
 //!
-//! Emits [`UnresolvedQueryExpr`](asap_types::pre_asap::UnresolvedQueryExpr) itself — the
-//! canonical `QueryExpr`, generic over an unresolved
-//! [`ColumnRef`](asap_types::pre_asap::ColumnRef) — directly, rather than a
-//! separate per-language relational DAG; `resolve_root` runs the
-//! [`SchemaResolver`](asap_types::pre_asap::SchemaResolver) for positional name resolution.
-//! Depends on the PromQL parser only — never on the SQL / DataFusion stack.
+//! `resolve_root` runs the
+//! [`SchemaResolver`](asap_frontend_common::SchemaResolver) for positional
+//! name resolution and returns the unified
+//! [`OperatorNode`](asap_types::ir::OperatorNode) DAG. Depends on the PromQL
+//! parser only — never on the SQL / DataFusion stack.
 
 pub mod error;
 pub mod histogram;
 pub mod promql;
 
-use asap_types::pre_asap::resolve_root;
-use asap_types::pre_asap::QueryExpr;
+use std::rc::Rc;
+
+use asap_types::ir::OperatorNode;
 use asap_types::workload::{DurationMs, PlanningWorkload, QueryLanguage, WorkloadError};
 
 pub use error::PromqlError;
 pub use histogram::{HistogramCatalog, HistogramKind};
 
-/// Lower every normalized PromQL workload entry to a plan-ready `QueryExpr`.
+/// Lower every normalized PromQL workload entry to a plan-ready operator DAG.
 ///
 /// PromQL workloads must declare a non-zero `data_ingestion_interval`; it is
 /// injected around each bare instant selector. Explicit range selectors keep
@@ -29,7 +30,7 @@ pub use histogram::{HistogramCatalog, HistogramKind};
 pub fn lower_promql_workload(
     workload: &PlanningWorkload,
     now_ms: u64,
-) -> Result<Vec<QueryExpr>, PromqlError> {
+) -> Result<Vec<Rc<OperatorNode>>, PromqlError> {
     lower_promql_workload_inner(workload, now_ms)
 }
 
@@ -39,15 +40,47 @@ pub fn lower_promql_workload_with_histograms(
     workload: &PlanningWorkload,
     histograms: HistogramCatalog,
     now_ms: u64,
-) -> Result<Vec<QueryExpr>, PromqlError> {
+) -> Result<Vec<Rc<OperatorNode>>, PromqlError> {
     let _guard = histogram::CatalogGuard::install(histograms);
     lower_promql_workload_inner(workload, now_ms)
 }
 
+/// Lower scalar and vector query roots without introducing constant operators.
+pub fn lower_promql_query_workload(
+    workload: &PlanningWorkload,
+    now_ms: u64,
+) -> Result<Vec<asap_types::ir::QueryRoot>, PromqlError> {
+    lower_promql_query_workload_inner(workload, now_ms)
+}
+
+pub fn lower_promql_query_workload_with_histograms(
+    workload: &PlanningWorkload,
+    histograms: HistogramCatalog,
+    now_ms: u64,
+) -> Result<Vec<asap_types::ir::QueryRoot>, PromqlError> {
+    let _guard = histogram::CatalogGuard::install(histograms);
+    lower_promql_query_workload_inner(workload, now_ms)
+}
+
 fn lower_promql_workload_inner(
     workload: &PlanningWorkload,
     now_ms: u64,
-) -> Result<Vec<QueryExpr>, PromqlError> {
+) -> Result<Vec<Rc<OperatorNode>>, PromqlError> {
+    lower_promql_query_workload_inner(workload, now_ms)?
+        .into_iter()
+        .map(|root| match root {
+            asap_types::ir::QueryRoot::Operator(node) => Ok(node),
+            asap_types::ir::QueryRoot::Scalar(_) => Err(PromqlError::UnsupportedFeature(
+                "scalar root: use lower_promql_query_workload".into(),
+            )),
+        })
+        .collect()
+}
+
+fn lower_promql_query_workload_inner(
+    workload: &PlanningWorkload,
+    now_ms: u64,
+) -> Result<Vec<asap_types::ir::QueryRoot>, PromqlError> {
     if !matches!(workload.query_workload.language, QueryLanguage::PromQL) {
         return Err(PromqlError::WrongLanguage(format!(
             "{:?}",
@@ -66,12 +99,12 @@ fn lower_promql_workload_inner(
         .query_workload
         .entries()
         .map(|entry| {
-            let unresolved = promql::PromqlLowerer::lower_with_ingestion_interval(
+            let root = promql::PromqlLowerer::lower_query_with_ingestion_interval(
                 &entry.query.0,
                 &entry.requirements.accuracy.target(),
                 std::time::Duration::from_millis(interval_ms),
             )?;
-            Ok(resolve_root(&unresolved)?)
+            Ok(root)
         })
         .collect()
 }
@@ -123,7 +156,7 @@ mod tests {
     }
     use std::time::Duration;
 
-    use asap_types::pre_asap::QueryExpr;
+    use asap_types::ir::{NonASAPOp, TimeRangeKind};
     use asap_types::workload::{
         BatchEntry, DataWorkload, Evidence, PlanningWorkload, Query, QueryRequirements,
         QueryWorkload, TimeSelection,
@@ -155,27 +188,34 @@ mod tests {
         }
     }
 
+    // A bare instant selector reads the latest sample within the declared
+    // ingestion interval: an `Instant` lookback of that length.
     #[test]
     fn instant_selector_uses_declared_ingestion_interval() {
         let query = lower_promql_workload(&workload("sum by (job) (data)"), 0).unwrap();
-        let QueryExpr::Aggregate { child, .. } = &query[0] else {
+        let NonASAPOp::Aggregate { child, .. } = query[0].expect_non_asap() else {
             panic!("expected aggregate")
         };
         assert!(
-            matches!(child.as_ref(), QueryExpr::TimeRange { range, child }
-            if *range == Duration::from_secs(1) && matches!(child.as_ref(), QueryExpr::Scan { .. }))
+            matches!(child.expect_non_asap(), NonASAPOp::TimeRange { range, kind, child }
+            if *range == Duration::from_secs(1)
+                && *kind == TimeRangeKind::Instant
+                && matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }))
         );
     }
 
+    // An explicit `m[5m]` keeps its own window as a `Range` selection.
     #[test]
     fn explicit_range_selector_keeps_its_query_range() {
         let query = lower_promql_workload(&workload("sum_over_time(data[5m])"), 0).unwrap();
-        let QueryExpr::Aggregate { child, .. } = &query[0] else {
+        let NonASAPOp::Aggregate { child, .. } = query[0].expect_non_asap() else {
             panic!("expected aggregate")
         };
         assert!(
-            matches!(child.as_ref(), QueryExpr::TimeRange { range, child }
-            if *range == Duration::from_secs(300) && matches!(child.as_ref(), QueryExpr::Scan { .. }))
+            matches!(child.expect_non_asap(), NonASAPOp::TimeRange { range, kind, child }
+            if *range == Duration::from_secs(300)
+                && *kind == TimeRangeKind::Range
+                && matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }))
         );
     }
 
@@ -191,6 +231,3 @@ mod tests {
         ));
     }
 }
-
-/// Unified lowering, promoted to the root API at planner cutover.
-pub mod unified;
diff --git a/crates/frontend-promql/src/promql.rs b/crates/frontend-promql/src/promql.rs
index 83251053e..42b39eb60 100644
--- a/crates/frontend-promql/src/promql.rs
+++ b/crates/frontend-promql/src/promql.rs
@@ -1,14 +1,13 @@
-//! PromQL string → the canonical, unresolved
-//! [`UnresolvedQueryExpr`](asap_types::pre_asap::query_expr::UnresolvedQueryExpr)
-//! (`QueryExpr<ColumnRef>`).
+//! PromQL string → the name-based
+//! [`UnresolvedOp`](asap_frontend_common::UnresolvedOp) tree.
 //!
 //! - **Parsing** is delegated to `promql-parser` 0.8.
 //! - **Lowering** builds *directly in canonical shape* here (issue #179): the
 //!   walk interprets PromQL semantics (range vectors, aggregate operators,
-//!   label matchers) and emits `UnresolvedQueryExpr` nodes with unresolved
-//!   `ColumnRef`s — the same DAG shape
-//!   [`resolve_root`](asap_types::pre_asap::resolve_root) later binds to
-//!   canonical, positional `QueryExpr<ColumnId>`. The structural decisions a
+//!   label matchers) and emits `UnresolvedOp` / `UnresolvedScalar` nodes with
+//!   unresolved `ColumnRef`s — the same tree shape
+//!   [`resolve_root`](asap_frontend_common::resolve_root) later binds to the
+//!   positional [`OperatorNode`](asap_types::ir::OperatorNode) DAG. The structural decisions a
 //!   separate converter stage would otherwise have to make (heavy-hitter
 //!   `topk` recognition, the `PerEntity`/`Reduce` reduction choice,
 //!   `without(...)` grouping) are made right here, since a front end
@@ -38,9 +37,11 @@
 //! | `increase(m[w])` | `Aggregate{[Increase], TimeRange{w}}` |
 //! | `changes`/`delta`/`idelta`/`deriv`/`resets`/`predict_linear`/`double_exponential_smoothing`(`m[w]`, …) | `Aggregate{[Changes/Delta/…], TimeRange{w}}` — per-series counter-derivative intents (issue #44) |
 //! | `absent(v)` / `absent_over_time(m[w])` / `present_over_time(m[w])` | `Aggregate{[Absent/AbsentOverTime/PresentOverTime]}` — presence intents; the empty→synthesized-sample logic is a post-ASAP concern (issue #47) |
-//! | `abs`/`ceil`/`sqrt`/`ln`/`clamp*`/`round`/trig(`v`), `pi()` | `Aggregate{[Math(f)]}` element-wise transform (issue #45); `pi()` → a `PromqlScalarBridge` leaf |
-//! | `time()` / `timestamp`/`hour`/`day_of_week`/… (`v`) | `EvalTimestamp` leaf / `Aggregate{[TimeFn(f)]}` (issue #46) |
-//! | `vector(s)` / `scalar(v)` | `PromqlVectorFromScalar` / `PromqlScalarFromVector` — the scalar⇄vector bridges (issue #48) |
+//! | `abs`/`ceil`/`sqrt`/`ln`/`clamp*`/`round`/trig(`v`), `pi()` | typed scalar `Project` (issue #45); `pi()` → a `ScalarExpr::Literal` root |
+//! | `time()` / `timestamp`/`hour`/`day_of_week`/… (`v`) | `ScalarExpr::EvalTimestamp` root / `Aggregate{[TimeFn(f)]}` (issue #46) |
+//! | `vector(s)` / `scalar(v)` | `PromqlVectorFromScalar(s)` / `ScalarExpr::PromqlScalarFromVector(v)` — the scalar⇄vector bridges (issue #48) |
+//! | `<scalar> op <scalar>` (`time() - 1`, `1 < bool 2`, `-time()`) | `ScalarExpr::{Arithmetic, Case, Negative}` — a scalar expression, never an operator |
+//! | `v op <scalar>`, `a op bool b`, `v > bool 0` | `Project`/`Filter` with owned scalar expressions; vector/vector uses `BinaryOp{return_bool}` |
 //! | `label_replace(v,…)` / `label_join(v,…)` | `PromqlRelabel{dst, value}` — per-series label rewrite; value unchanged (issue #50) |
 //! | `info(v, [selector])` | `PromqlInfoEnrich{selector}` — label-enrichment join against the info metric(s); join keys resolved during post-ASAP binding (issue #84) |
 //! | `group` / `offset` / `@` / `info` | **rejected** — distinct semantics with no intent-algebra representation yet (`info` label-join → #84) |
@@ -50,7 +51,7 @@
 //! | `limitk(k, v)` / `limit_ratio(r, v)` | `PromqlSeriesSample{LimitK(k) \| LimitRatio(r)}` — series-sampling selection, whole series kept unchanged (issue #86) |
 //! | `topk(k, count_over_time(…))` / `topk(k, sum_over_time(…))` | `Aggregate{[TopK{k}]}` (heavy-hitter intent) over the explicit inner `Aggregate{[Count/Sum]}` |
 //! | `topk(k, <other>)` / `bottomk(k, …)` | `Sort{value} → Limit{k}` |
-//! | `m{f}` | `Scan{predicates}` |
+//! | `m{f}` / `m{f}[w]` | `TimeRange{ingestion, Instant, Scan{predicates}}` / `TimeRange{w, Range, Scan}` |
 //! | `a OP b` | `BinaryOp{vector_match}` |
 //! | `expr[r:res]` | `PromqlSubquery{r, res}` |
 //! | `<selector> offset <d>` / `<selector> @ <ts>`/`start()`/`end()` | `TimeShift{shift}` over the selector's `Scan` — pass-through schema; a ranged selector shifts under its `TimeRange` (issue #40) |
@@ -59,22 +60,30 @@ use std::rc::Rc;
 use std::time::{Duration, SystemTime};
 
 use promql_parser::label::{MatchOp, Matcher};
+use promql_parser::parser::value::ValueType;
 use promql_parser::parser::{
     self, token, AggregateExpr, AtModifier as ParserAtModifier, BinaryExpr, Call, Expr,
     LabelModifier, Offset, VectorMatchCardinality, VectorSelector,
 };
 
-use asap_types::pre_asap::agg_intent::{topk, AggIntent, MathFunc, TimeFunc};
-use asap_types::pre_asap::query_expr::{
-    AtModifier, BinaryOpKind, GroupKeys, GroupSide, Predicate, PromQLVectorSetOpKind, Reduction,
-    SortKey, Source, TimeShift, UnresolvedQueryExpr as Unresolved, VectorGrouping, VectorMatch,
-    VectorMatchKind,
+use asap_frontend_common::{
+    UnresolvedOp as Unresolved, UnresolvedPredicate, UnresolvedScalar as Scalar, UnresolvedSortKey,
 };
+use asap_types::ir::operator_properties::{
+    AtModifier, BinaryOpKind, GroupKeys, GroupSide, PromQLVectorSetOpKind, Reduction, Source,
+    TimeShift, VectorGrouping, VectorMatch, VectorMatchKind,
+};
+use asap_types::ir::{BinaryOperator, ExprSemantics, TimeRangeKind};
+use asap_types::pre_asap::agg_intent::{topk, AggIntent, TimeFunc};
+
 use asap_types::pre_asap::{
     ArithmeticOpKind, ColumnRef, CompareOpKind, InfoMatcher, SampleKind, ScalarValue,
 };
 use asap_types::types::AccuracyTarget;
 
+/// Every scalar expression this front end builds follows PromQL's numeric rules.
+const PROMQL: ExprSemantics = ExprSemantics::Promql;
+
 use crate::error::PromqlError as LoweringError;
 
 type Result<T> = std::result::Result<T, LoweringError>;
@@ -158,7 +167,7 @@ enum InnerFunc {
 
 struct Inner {
     metric: String,
-    matchers: Vec<Unresolved>,
+    matchers: Vec<Scalar>,
     window: Option<Duration>,
     func: Option<InnerFunc>,
     /// `offset` / `@` on the selector, carried to the `Source` (issue #40).
@@ -172,16 +181,35 @@ struct Inner {
 const MAX_DEPTH: usize = 256;
 
 impl PromqlLowerer {
-    pub(crate) fn lower_with_ingestion_interval(
+    pub(crate) fn lower_query_with_ingestion_interval(
         query: &str,
         accuracy: &AccuracyTarget,
         interval: Duration,
-    ) -> Result<Unresolved> {
+    ) -> Result<asap_types::ir::QueryRoot> {
         let _guard = AccuracyGuard::install(accuracy.clone());
         let _interval = IngestionIntervalGuard::install(interval);
         let ast = parser::parse(query).map_err(LoweringError::Parse)?;
         check_depth(&ast, MAX_DEPTH)?;
-        walk(&ast)
+        let mut metrics = Vec::new();
+        collect_metric_names(&ast, &mut metrics);
+        if metrics.iter().any(|metric| {
+            crate::histogram::current_kind_of(metric)
+                == Some(crate::histogram::HistogramKind::Native)
+        }) {
+            return Err(LoweringError::UnsupportedFeature(
+                "native histogram samples have no IR representation".into(),
+            ));
+        }
+
+        if ast.value_type() == ValueType::Scalar {
+            Ok(asap_types::ir::QueryRoot::Scalar(
+                asap_frontend_common::resolve_scalar_root(&lower_scalar(&ast)?)?,
+            ))
+        } else {
+            Ok(asap_types::ir::QueryRoot::Operator(
+                asap_frontend_common::resolve_root(&walk(&ast)?)?,
+            ))
+        }
     }
 }
 
@@ -273,6 +301,13 @@ fn check_depth(expr: &Expr, budget: usize) -> Result<()> {
 }
 
 fn walk(expr: &Expr) -> Result<Unresolved> {
+    // A scalar-typed expression (`5`, `time() - 1`, `scalar(v)`, `1 < bool 2`)
+    // is a scalar expression at an operator position, never an operator tree.
+    if expr.value_type() == ValueType::Scalar {
+        return Err(LoweringError::UnsupportedFeature(
+            "scalar root requires query-root lowering".into(),
+        ));
+    }
     match expr {
         Expr::Aggregate(agg) => walk_aggregate(agg),
         Expr::Call(call) if call.func.name.starts_with("histogram_") => walk_histogram(call),
@@ -282,31 +317,22 @@ fn walk(expr: &Expr) -> Result<Unresolved> {
         Expr::Call(call) if is_typeconv_fn(call.func.name) => walk_typeconv(call),
         Expr::Call(call) if is_label_fn(call.func.name) => walk_label(call),
         Expr::Call(call) if is_sort_fn(call.func.name) => walk_sort(call),
-        // A bare `min_of`/`max_of(consts…)` scalar query folds to a `PromqlScalarBridge`
-        // leaf; a non-constant argument makes `num_expr` fail → rejected (#89).
-        Expr::Call(call) if is_scalar_reducer_fn(call.func.name) => {
-            Ok(Unresolved::promql_scalar(num_expr(expr)?))
-        }
         Expr::Call(call) if call.func.name == "info" => walk_info(call),
         Expr::Call(call) => walk_call(call),
         Expr::Binary(bin) => walk_binary(bin),
         Expr::Paren(p) => walk(&p.expr),
         // `UnaryExpr` is built only by negation (`Neg`); unary `+` is folded to
-        // identity and `-<literal>` to a negated `NumberLiteral`, so this wraps a
-        // sub-expression whose samples must be sign-flipped. Now that a scalar
-        // operand exists (#35), express it as `x * -1` — a constant-foldable
-        // operand (`-(10*1024)`) collapses to a negated `PromqlScalarBridge` leaf; anything
-        // else is a vector, sign-flipped by a `Mul` against `PromqlScalarBridge(-1)`. `Mul`
-        // is commutative, so operand order carries no hazard (#36).
-        Expr::Unary(u) => match num_expr(&u.expr) {
-            Ok(v) => Ok(Unresolved::promql_scalar(-v)),
-            Err(_) => Ok(Unresolved::BinaryOp {
-                op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul),
-                lhs: Rc::new(walk(&u.expr)?),
-                rhs: Rc::new(Unresolved::promql_scalar(-1.0)),
-                vector_match: None,
-            }),
-        },
+        // identity and `-<literal>` to a negated `NumberLiteral`. A scalar
+        // operand was dispatched to `lower_scalar` above (→ `Negative`), so this
+        // is a vector projection. Unary negation retains the metric name.
+        Expr::Unary(u) => Ok(Unresolved::PromqlMap {
+            child: Rc::new(walk(&u.expr)?),
+            sample: Scalar::Negative {
+                expr: Box::new(Scalar::Column(ColumnRef::SampleValue)),
+                semantics: ExprSemantics::Promql,
+            },
+            drop_metric_name: false,
+        }),
         Expr::Subquery(sq) => {
             let subquery = Unresolved::PromqlSubquery {
                 range: sq.range,
@@ -332,13 +358,14 @@ fn walk(expr: &Expr) -> Result<Unresolved> {
             let (metric, matchers, shift) = vs_parts(&ms.vs)?;
             Ok(Unresolved::TimeRange {
                 range: ms.range,
+                kind: TimeRangeKind::Range,
                 child: Rc::new(filtered_source(metric, matchers, shift)),
             })
         }
-        // A number literal is a scalar leaf (`v > 5`, or a bare scalar query
-        // `5`). String literals only appear as function args (`label_replace`,
-        // …), which are not supported, so reject them (issue #35).
-        Expr::NumberLiteral(n) => Ok(Unresolved::promql_scalar(n.val)),
+        // Scalar-typed, dispatched above; kept for exhaustiveness. String
+        // literals only appear as function args (`label_replace`, …), so a
+        // bare one is rejected (issue #35).
+        Expr::NumberLiteral(_) => unreachable!("scalar handled above"),
         Expr::StringLiteral(_) => Err(LoweringError::UnsupportedFeature(
             "bare string literal".into(),
         )),
@@ -348,6 +375,98 @@ fn walk(expr: &Expr) -> Result<Unresolved> {
     }
 }
 
+/// Lower a scalar-typed PromQL expression to a scalar expression. A constant
+/// sub-expression folds to one `Literal` (as `num_expr` always did); anything
+/// else keeps its structure: `-time()` → `Negative`, `time() - 1` →
+/// `Arithmetic`, `scalar(v)` → `PromqlScalarFromVector`, and a `bool`
+/// comparison → `Case(Compare → 1, else 0)` (PromQL yields `0`/`1`).
+fn lower_scalar(expr: &Expr) -> Result<Scalar> {
+    if let Ok(v) = num_expr(expr) {
+        return Ok(Scalar::Literal(ScalarValue::Float64(v)));
+    }
+    match expr {
+        Expr::Paren(p) => lower_scalar(&p.expr),
+        Expr::Unary(u) => Ok(Scalar::Negative {
+            expr: Box::new(lower_scalar(&u.expr)?),
+            semantics: PROMQL,
+        }),
+        Expr::Binary(bin) => lower_scalar_binary(bin),
+        Expr::Call(call) => match call.func.name {
+            "time" => Ok(Scalar::EvalTimestamp),
+            "pi" => Ok(Scalar::Literal(ScalarValue::Float64(std::f64::consts::PI))),
+            "scalar" => Ok(Scalar::PromqlScalarFromVector(Rc::new(walk(arg(
+                call, 0,
+            )?)?))),
+            // `min_of`/`max_of` fold only over constants (#89); the fold above
+            // failed, so surface its error for the non-constant argument.
+            name if is_scalar_reducer_fn(name) => Err(num_expr(expr).unwrap_err()),
+            other => Err(LoweringError::UnsupportedFunction(other.to_string())),
+        },
+        other => Err(LoweringError::UnsupportedFeature(format!(
+            "scalar expression `{other}`"
+        ))),
+    }
+}
+
+/// `<scalar> op <scalar>`: arithmetic is an `Arithmetic` expression; a
+/// comparison needs the `bool` modifier (PromQL has no scalar filter) and
+/// becomes `Case(Compare → 1.0, else 0.0)`. The parser already rejects both a
+/// bool-less scalar comparison and a scalar set op; both are re-checked here.
+fn lower_scalar_binary(bin: &BinaryExpr) -> Result<Scalar> {
+    let left = Box::new(lower_scalar(&bin.lhs)?);
+    let right = Box::new(lower_scalar(&bin.rhs)?);
+    match binop(bin.op.id())? {
+        BinaryOpKind::Arithmetic(op) => Ok(Scalar::Arithmetic {
+            op,
+            left,
+            right,
+            semantics: PROMQL,
+        }),
+        BinaryOpKind::Compare(op) | BinaryOpKind::CompareBool(op) => {
+            if !bin.return_bool() {
+                return Err(LoweringError::InvalidParameter(
+                    "a comparison between two scalars requires the `bool` modifier".into(),
+                ));
+            }
+            let compare = Scalar::Compare {
+                left,
+                op,
+                right,
+                semantics: PROMQL,
+            };
+            Ok(Scalar::Case {
+                operand: None,
+                branches: vec![(compare, Scalar::Literal(ScalarValue::Float64(1.0)))],
+                else_expr: Some(Box::new(Scalar::Literal(ScalarValue::Float64(0.0)))),
+            })
+        }
+        BinaryOpKind::Set(_) => Err(LoweringError::UnsupportedFeature(
+            "set operator between two scalars".into(),
+        )),
+    }
+}
+
+/// A binary operation over two vectors.
+fn vector_binary(
+    kind: BinaryOpKind,
+    vector_match: Option<VectorMatch>,
+    return_bool: bool,
+    lhs: Unresolved,
+    rhs: Unresolved,
+) -> Unresolved {
+    Unresolved::BinaryOp {
+        operator: BinaryOperator {
+            kind,
+            vector_match,
+            checked_relative_division: false,
+            checked_finite_division: false,
+        },
+        return_bool,
+        lhs: Rc::new(lhs),
+        rhs: Rc::new(rhs),
+    }
+}
+
 /// Lower a bare function call (`rate(m[5m])`, `max_over_time(m[5m])`, …).
 ///
 /// The common case routes through the flat `lower_inner_call` template. The one
@@ -576,7 +695,7 @@ fn outer_kind(agg: &AggregateExpr) -> Result<Outer> {
 /// build this node) decides `PerEntity` vs `Reduce(by)` *without* knowing
 /// about `without` yet — it only ever sees `by`-mode keys, since `without`'s
 /// excluded-labels list is applied here, after the fact, exactly like the
-/// pre-#179 legacy `relational::QueryExpr` DAG's own `mark_without` did (its
+/// pre-#179 legacy relational tree's own `mark_without` did (its
 /// converter read `without` only after this front-end step had already set
 /// it). Whether
 /// `reduction_for` picked `PerEntity` (only possible when `keys` was empty)
@@ -652,24 +771,36 @@ fn build_over_sub_dag(outer: Outer, keys: Vec<ColumnRef>, child: Unresolved) ->
                     child,
                 ));
             }
-            let sorted = Unresolved::Sort {
-                keys: vec![SortKey {
-                    expr: Unresolved::Column(ColumnRef::SampleValue),
-                    ascending: !descending,
-                    nulls_first: false,
-                }],
-                partition_by: keys.into(),
-                child: Rc::new(child),
-            };
-            Unresolved::Limit {
-                n: k as usize,
-                offset: 0,
-                child: Rc::new(sorted),
-            }
+            ranked_by_value(keys, k, descending, child)
         }
     })
 }
 
+/// Generic `topk`/`bottomk`: `Limit{k} → Sort{value, partition_by: keys}` over
+/// `child` — an order-by-value ranking, not a heavy-hitter intent.
+fn ranked_by_value(
+    keys: Vec<ColumnRef>,
+    k: u64,
+    descending: bool,
+    child: Unresolved,
+) -> Unresolved {
+    let sorted = Unresolved::Sort {
+        keys: vec![UnresolvedSortKey {
+            expr: Scalar::Column(ColumnRef::SampleValue),
+            ascending: !descending,
+            nulls_first: false,
+        }],
+        partition_by: keys.into(),
+        child: Rc::new(child),
+    };
+    Unresolved::Limit {
+        n: Some(k as usize),
+        offset: 0,
+        partition_by: GroupKeys::none(),
+        child: Rc::new(sorted),
+    }
+}
+
 /// The `histogram_*` function family (issues #43, histogram_quantile).
 ///
 /// `histogram_quantile(φ, <expr>)` lowers `<expr>` in full — preserving any
@@ -696,7 +827,7 @@ fn walk_histogram(call: &Call) -> Result<Unresolved> {
         // The true signal is the argument's sample type: a declared
         // `HistogramKind` (issue #79) drives the choice when available, else we
         // fall back to the structural `by (le)`/`_bucket` heuristic (issue #43).
-        if !histogram_arg_is_sketchable(arg_expr) {
+        if !histogram_arg_is_sketchable(arg_expr)? {
             return Ok(classic_histogram_quantile(phi, "", walk(arg_expr)?));
         }
         let func = AggIntent::Quantile {
@@ -706,23 +837,9 @@ fn walk_histogram(call: &Call) -> Result<Unresolved> {
         };
         return Ok(outer_aggregate(vec![], func, walk(arg_expr)?));
     }
-    // (histogram_quantile handled above; accessors below)
-    let (func, vec_idx) = match call.func.name {
-        "histogram_count" => (AggIntent::HistogramCount, 0),
-        "histogram_sum" => (AggIntent::HistogramSum, 0),
-        "histogram_avg" => (AggIntent::HistogramAvg, 0),
-        "histogram_stddev" => (AggIntent::HistogramStdDev, 0),
-        "histogram_stdvar" => (AggIntent::HistogramStdVar, 0),
-        "histogram_fraction" => (
-            AggIntent::HistogramFraction {
-                lower: num_arg(call, 0)?,
-                upper: num_arg(call, 1)?,
-            },
-            2,
-        ),
-        other => return Err(LoweringError::UnsupportedFunction(other.to_string())),
-    };
-    Ok(outer_aggregate(vec![], func, walk(arg(call, vec_idx)?)?))
+    Err(LoweringError::UnsupportedFeature(
+        "native histogram samples have no IR representation".into(),
+    ))
 }
 
 /// Classic-bucket `histogram_quantile(φ, child)`. One histogram is the set of
@@ -769,7 +886,7 @@ fn walk_histogram_quantiles(call: &Call) -> Result<Unresolved> {
         ));
     }
     // The bucket-vs-native choice is a property of the argument, not of φ.
-    let sketchable = histogram_arg_is_sketchable(vec_expr);
+    let sketchable = histogram_arg_is_sketchable(vec_expr)?;
     let branches = (2..call.args.args.len())
         .map(|i| {
             let phi = bounded_quantile_param(num_arg(call, i)?)?;
@@ -796,9 +913,7 @@ fn walk_histogram_quantiles(call: &Call) -> Result<Unresolved> {
             };
             Ok(Unresolved::PromqlRelabel {
                 dst: label.clone(),
-                value: Rc::new(Unresolved::Literal(ScalarValue::Utf8(open_metrics_float(
-                    phi,
-                )))),
+                value: Scalar::Literal(ScalarValue::Utf8(open_metrics_float(phi))),
                 child: Rc::new(quantile),
             })
         })
@@ -852,12 +967,12 @@ fn open_metrics_float(v: f64) -> String {
     }
 }
 
-/// The time / calendar functions (issue #46).
+/// The calendar functions (issue #46); `time()` is scalar-typed and lowers in
+/// `lower_scalar`.
 fn is_time_fn(name: &str) -> bool {
     matches!(
         name,
-        "time"
-            | "timestamp"
+        "timestamp"
             | "minute"
             | "hour"
             | "day_of_week"
@@ -869,33 +984,31 @@ fn is_time_fn(name: &str) -> bool {
     )
 }
 
-/// `time()` → the `EvalTimestamp` leaf. `timestamp(v)` and the calendar accessors →
-/// `Aggregate{[TimeFn(f)]}` over the argument vector, or over `EvalTimestamp` for the
+/// `timestamp(v)` and the calendar accessors → `Aggregate{[TimeFn(f)]}` over
+/// the argument vector, or over `PromqlVectorFromScalar(EvalTimestamp)` for the
 /// no-argument calendar forms (`hour()`, `day_of_week()`, …). Issue #46.
 fn walk_time(call: &Call) -> Result<Unresolved> {
-    if call.func.name == "time" {
-        return Ok(Unresolved::EvalTimestamp);
+    // timestamp() reads the selected sample's timestamp, not its value.
+    if call.func.name == "timestamp" {
+        return Ok(outer_aggregate(
+            vec![],
+            AggIntent::TimeFn(TimeFunc::Timestamp),
+            walk(arg(call, 0)?)?,
+        ));
     }
-    let func = match call.func.name {
-        "timestamp" => TimeFunc::Timestamp,
-        "minute" => TimeFunc::Minute,
-        "hour" => TimeFunc::Hour,
-        "day_of_week" => TimeFunc::DayOfWeek,
-        "day_of_month" => TimeFunc::DayOfMonth,
-        "day_of_year" => TimeFunc::DayOfYear,
-        "month" => TimeFunc::Month,
-        "year" => TimeFunc::Year,
-        "days_in_month" => TimeFunc::DaysInMonth,
-        other => return Err(LoweringError::UnsupportedFunction(other.to_string())),
-    };
-    // A calendar function with no argument reads the evaluation time; otherwise
-    // it maps over each sample's timestamp in the argument vector.
-    let inner = if call.args.args.is_empty() {
-        Unresolved::EvalTimestamp
+    let child = if call.args.args.is_empty() {
+        Unresolved::PromqlVectorFromScalar(Scalar::EvalTimestamp)
     } else {
         walk(arg(call, 0)?)?
     };
-    Ok(outer_aggregate(vec![], AggIntent::TimeFn(func), inner))
+    Ok(Unresolved::PromqlMap {
+        child: Rc::new(child),
+        sample: Scalar::FunctionCall {
+            name: format!("promql_{}", call.func.name),
+            args: vec![Scalar::Column(ColumnRef::SampleValue)],
+        },
+        drop_metric_name: true,
+    })
 }
 
 /// The presence functions (issue #47).
@@ -919,24 +1032,19 @@ fn walk_presence(call: &Call) -> Result<Unresolved> {
     Ok(outer_aggregate(vec![], func, walk(arg(call, 0)?)?))
 }
 
-/// The scalar⇄vector type-conversion functions (issue #48). `info` is *not*
-/// here: it is a label-enrichment join against info metrics, not a type
-/// conversion, so it falls through to the `UnsupportedFunction` path (#84).
+/// The scalar→vector conversion (issue #48); `scalar(v)` is scalar-typed and
+/// lowers in `lower_scalar`. `info` is *not* here: it is a label-enrichment
+/// join, not a type conversion (#84).
 fn is_typeconv_fn(name: &str) -> bool {
-    matches!(name, "vector" | "scalar")
+    name == "vector"
 }
 
-/// `vector(s)` — promote a scalar to a label-less instant vector. `scalar(v)`
-/// — collapse a single-element vector to its value. Both are honest bridge
-/// nodes in the IR; the "exactly one element → NaN otherwise" runtime rule of
-/// `scalar` is a post-ASAP/runtime concern (issue #48).
+/// `vector(s)` — promote a scalar to a label-less instant vector carrying the
+/// scalar expression `s` (issue #48).
 fn walk_typeconv(call: &Call) -> Result<Unresolved> {
-    let inner = walk(arg(call, 0)?)?;
-    Ok(match call.func.name {
-        "vector" => Unresolved::PromqlVectorFromScalar(Rc::new(inner)),
-        "scalar" => Unresolved::PromqlScalarFromVector(Rc::new(inner)),
-        other => return Err(LoweringError::UnsupportedFunction(other.to_string())),
-    })
+    Ok(Unresolved::PromqlVectorFromScalar(lower_scalar(arg(
+        call, 0,
+    )?)?))
 }
 
 /// The instant-vector reordering functions (issue #51).
@@ -960,13 +1068,13 @@ fn walk_sort(call: &Call) -> Result<Unresolved> {
         "sort_by_label_desc" => (false, false),
         other => return Err(LoweringError::UnsupportedFunction(other.to_string())),
     };
-    let sort_key = |expr| SortKey {
+    let sort_key = |expr| UnresolvedSortKey {
         expr,
         ascending,
         nulls_first: false,
     };
     let keys = if by_value {
-        vec![sort_key(Unresolved::Column(ColumnRef::SampleValue))]
+        vec![sort_key(Scalar::Column(ColumnRef::SampleValue))]
     } else {
         // `sort_by_label(v, "l1", "l2", …)` — one key per label arg, in order.
         if call.args.args.len() < 2 {
@@ -976,7 +1084,7 @@ fn walk_sort(call: &Call) -> Result<Unresolved> {
         }
         (1..call.args.args.len())
             .map(|i| {
-                Ok(sort_key(Unresolved::Column(ColumnRef::Named(str_arg(
+                Ok(sort_key(Scalar::Column(ColumnRef::Named(str_arg(
                     call, i,
                 )?))))
             })
@@ -1050,19 +1158,15 @@ fn walk_label(call: &Call) -> Result<Unresolved> {
             let replacement = str_arg(call, 2)?;
             let src = str_arg(call, 3)?;
             let regex = str_arg(call, 4)?;
-            let value = Unresolved::FunctionCall {
+            let value = Scalar::FunctionCall {
                 name: "label_replace".into(),
                 args: vec![
-                    Unresolved::Column(ColumnRef::Named(src)),
-                    Unresolved::Literal(ScalarValue::Utf8(regex)),
-                    Unresolved::Literal(ScalarValue::Utf8(replacement)),
+                    Scalar::Column(ColumnRef::Named(src)),
+                    Scalar::Literal(ScalarValue::Utf8(regex)),
+                    Scalar::Literal(ScalarValue::Utf8(replacement)),
                 ],
             };
-            Ok(Unresolved::PromqlRelabel {
-                dst,
-                value: Rc::new(value),
-                child,
-            })
+            Ok(Unresolved::PromqlRelabel { dst, value, child })
         }
         "label_join" => {
             // label_join(v, dst, sep, src_1, …, src_n) — needs ≥1 source label.
@@ -1073,19 +1177,15 @@ fn walk_label(call: &Call) -> Result<Unresolved> {
             }
             let dst = str_arg(call, 1)?;
             let sep = str_arg(call, 2)?;
-            let mut args = vec![Unresolved::Literal(ScalarValue::Utf8(sep))];
+            let mut args = vec![Scalar::Literal(ScalarValue::Utf8(sep))];
             for i in 3..call.args.args.len() {
-                args.push(Unresolved::Column(ColumnRef::Named(str_arg(call, i)?)));
+                args.push(Scalar::Column(ColumnRef::Named(str_arg(call, i)?)));
             }
-            let value = Unresolved::FunctionCall {
+            let value = Scalar::FunctionCall {
                 name: "label_join".into(),
                 args,
             };
-            Ok(Unresolved::PromqlRelabel {
-                dst,
-                value: Rc::new(value),
-                child,
-            })
+            Ok(Unresolved::PromqlRelabel { dst, value, child })
         }
         other => Err(LoweringError::UnsupportedFunction(other.to_string())),
     }
@@ -1118,7 +1218,6 @@ fn is_math_fn(name: &str) -> bool {
             | "atanh"
             | "deg"
             | "rad"
-            | "pi"
             | "round"
             | "clamp"
             | "clamp_min"
@@ -1127,59 +1226,24 @@ fn is_math_fn(name: &str) -> bool {
 }
 
 /// A math / trig function — a per-series element-wise value transform, lowered
-/// to a per-series `Aggregate{[Math(f)]}` over the (instant) argument vector.
-/// `pi()` is the constant π, lowered to a `PromqlScalarBridge` leaf (issue #45).
+/// to a typed scalar projection over the instant-vector argument.
+/// `pi()` is scalar-typed and lowers in `lower_scalar` (issue #45).
 fn walk_math(call: &Call) -> Result<Unresolved> {
-    if call.func.name == "pi" {
-        return Ok(Unresolved::promql_scalar(std::f64::consts::PI));
+    let mut args = vec![Scalar::Column(ColumnRef::SampleValue)];
+    for index in 1..call.args.args.len() {
+        args.push(lower_scalar(arg(call, index)?)?);
     }
-    let func = match call.func.name {
-        "abs" => MathFunc::Abs,
-        "ceil" => MathFunc::Ceil,
-        "floor" => MathFunc::Floor,
-        "exp" => MathFunc::Exp,
-        "ln" => MathFunc::Ln,
-        "log2" => MathFunc::Log2,
-        "log10" => MathFunc::Log10,
-        "sqrt" => MathFunc::Sqrt,
-        "sgn" => MathFunc::Sgn,
-        "sin" => MathFunc::Sin,
-        "cos" => MathFunc::Cos,
-        "tan" => MathFunc::Tan,
-        "asin" => MathFunc::Asin,
-        "acos" => MathFunc::Acos,
-        "atan" => MathFunc::Atan,
-        "sinh" => MathFunc::Sinh,
-        "cosh" => MathFunc::Cosh,
-        "tanh" => MathFunc::Tanh,
-        "asinh" => MathFunc::Asinh,
-        "acosh" => MathFunc::Acosh,
-        "atanh" => MathFunc::Atanh,
-        "deg" => MathFunc::Deg,
-        "rad" => MathFunc::Rad,
-        // `round(v)` defaults the step to 1; `round(v, to)` reads arg 1.
-        "round" => MathFunc::Round {
-            to_nearest: if call.args.args.len() >= 2 {
-                num_arg(call, 1)?
-            } else {
-                1.0
-            },
-        },
-        "clamp" => MathFunc::Clamp {
-            min: num_arg(call, 1)?,
-            max: num_arg(call, 2)?,
-        },
-        "clamp_min" => MathFunc::ClampMin {
-            min: num_arg(call, 1)?,
-        },
-        "clamp_max" => MathFunc::ClampMax {
-            max: num_arg(call, 1)?,
+    if call.func.name == "round" && args.len() == 1 {
+        args.push(Scalar::Literal(ScalarValue::Float64(1.0)));
+    }
+    Ok(Unresolved::PromqlMap {
+        child: Rc::new(walk(arg(call, 0)?)?),
+        sample: Scalar::FunctionCall {
+            name: format!("promql_{}", call.func.name),
+            args,
         },
-        other => return Err(LoweringError::UnsupportedFunction(other.to_string())),
-    };
-    // The value being transformed is always arg 0 (a vector).
-    let inner = walk(arg(call, 0)?)?;
-    Ok(outer_aggregate(vec![], AggIntent::Math(func), inner))
+        drop_metric_name: true,
+    })
 }
 
 /// Whether `expr` is a **classic cumulative-bucket** `histogram_quantile`
@@ -1202,15 +1266,31 @@ fn walk_math(call: &Call) -> Result<Unresolved> {
 /// declared `RawSamples`) and the false-negative (a suffix-less classic
 /// histogram declared `ClassicBucket`) of the structural heuristic. With no
 /// declaration, fall back to the structural `by (le)`/`_bucket` heuristic.
-fn histogram_arg_is_sketchable(arg: &Expr) -> bool {
+fn histogram_arg_is_sketchable(arg: &Expr) -> Result<bool> {
     let mut metrics = Vec::new();
     collect_metric_names(arg, &mut metrics);
-    for metric in &metrics {
-        if let Some(kind) = crate::histogram::current_kind_of(metric) {
-            return kind.is_sketchable();
+    let kinds = metrics
+        .iter()
+        .filter_map(|metric| crate::histogram::current_kind_of(metric))
+        .collect::<Vec<_>>();
+    if kinds.contains(&crate::histogram::HistogramKind::Native) {
+        return Err(LoweringError::UnsupportedFeature(
+            "native histogram samples have no IR representation".into(),
+        ));
+    }
+    if let Some(kind) = kinds.first() {
+        if kinds.iter().any(|other| other != kind) {
+            return Err(LoweringError::UnsupportedFeature(
+                "mixed histogram sample contracts".into(),
+            ));
         }
+        return Ok(kind.is_sketchable());
+    }
+    if is_classic_bucket_arg(arg) {
+        Ok(false)
+    } else {
+        Err(LoweringError::UnsupportedFeature("histogram_quantile requires classic buckets; use quantile for float samples or explicitly declare the RawSamples extension".into()))
     }
-    !is_classic_bucket_arg(arg)
 }
 
 /// Collect the metric names of every vector/matrix selector reachable in `expr`
@@ -1282,9 +1362,28 @@ fn selector_is_bucket(vs: &VectorSelector) -> bool {
         || vs.matchers.matchers.iter().any(|m| m.name == "le")
 }
 
+/// A binary op with at least one vector operand (a scalar/scalar op is
+/// scalar-typed and never reaches here). A scalar side lowers to a
+/// scalar expression; mixed operations resolve to Project or Filter.
 fn walk_binary(bin: &BinaryExpr) -> Result<Unresolved> {
-    let lhs = scalar_or_vector(&bin.lhs)?;
-    let rhs = scalar_or_vector(&bin.rhs)?;
+    let op = binop(bin.op.id())?;
+    let scalar_left = bin.lhs.value_type() == ValueType::Scalar;
+    if scalar_left || bin.rhs.value_type() == ValueType::Scalar {
+        let (scalar, vector) = if scalar_left {
+            (&bin.lhs, &bin.rhs)
+        } else {
+            (&bin.rhs, &bin.lhs)
+        };
+        return Ok(Unresolved::PromqlScalarOp {
+            child: Rc::new(walk(vector)?),
+            scalar: lower_scalar(scalar)?,
+            op,
+            scalar_left,
+            return_bool: bin.return_bool(),
+        });
+    }
+    let lhs = walk(&bin.lhs)?;
+    let rhs = walk(&bin.rhs)?;
     // `VectorMatch` has no fill field; dropping fill would change which series
     // are emitted and their values, so the query must fall back to exact
     // execution instead.
@@ -1295,10 +1394,6 @@ fn walk_binary(bin: &BinaryExpr) -> Result<Unresolved> {
             )));
         }
     }
-    let op = match (binop(bin.op.id())?, bin.return_bool()) {
-        (BinaryOpKind::Compare(op), true) => BinaryOpKind::CompareBool(op),
-        (op, _) => op,
-    };
     let vector_match = bin.modifier.as_ref().map(|m| {
         let (kind, labels) = match &m.matching {
             Some(LabelModifier::Include(ls)) => (VectorMatchKind::On, ls.labels.clone()),
@@ -1329,12 +1424,7 @@ fn walk_binary(bin: &BinaryExpr) -> Result<Unresolved> {
             grouping,
         }
     });
-    Ok(Unresolved::BinaryOp {
-        op,
-        lhs: Rc::new(lhs),
-        rhs: Rc::new(rhs),
-        vector_match,
-    })
+    Ok(vector_binary(op, vector_match, bin.return_bool(), lhs, rhs))
 }
 
 fn lower_inner(expr: &Expr) -> Result<Inner> {
@@ -1601,20 +1691,7 @@ fn build(inner: Inner, keys: Vec<ColumnRef>, outer: Outer) -> Result<Unresolved>
                     Some(intent) => windowed_aggregate(inner, vec![], intent),
                     None => instant_source(inner.metric, inner.matchers, inner.shift),
                 };
-                let sorted = Unresolved::Sort {
-                    keys: vec![SortKey {
-                        expr: Unresolved::Column(ColumnRef::SampleValue),
-                        ascending: !descending,
-                        nulls_first: false,
-                    }],
-                    partition_by: keys.into(),
-                    child: Rc::new(base),
-                };
-                Ok(Unresolved::Limit {
-                    n: k as usize,
-                    offset: 0,
-                    child: Rc::new(sorted),
-                })
+                Ok(ranked_by_value(keys, k, descending, base))
             }
         }
     }
@@ -1650,19 +1727,12 @@ fn windowed_aggregate(
     let child = match inner.window {
         Some(w) => Unresolved::TimeRange {
             range: w,
+            kind: TimeRangeKind::Range,
             child: Rc::new(base),
         },
-        None => base,
+        None => ingestion_lookback(base),
     };
     let reduction = reduction_for(&keys, inner.window.is_some() || intent.is_per_series());
-    let child = if inner.window.is_none() {
-        Unresolved::TimeRange {
-            range: current_ingestion_interval(),
-            child: Rc::new(child),
-        }
-    } else {
-        child
-    };
     Unresolved::Aggregate {
         reduction,
         measures: vec![intent],
@@ -1715,13 +1785,10 @@ fn per_series_aggregate(
     }
 }
 
-fn filtered_source(metric: String, matchers: Vec<Unresolved>, shift: TimeShift) -> Unresolved {
+fn filtered_source(metric: String, matchers: Vec<Scalar>, shift: TimeShift) -> Unresolved {
     let scan = Unresolved::Scan {
         source: Source::TimeSeries { metric },
-        predicates: matchers
-            .into_iter()
-            .map(|m| Predicate(Rc::new(m)))
-            .collect(),
+        predicates: matchers.into_iter().map(UnresolvedPredicate).collect(),
         // Usage-derived (PromQL is schemaless) — the SchemaResolver fills this in.
         schema: None,
     };
@@ -1735,10 +1802,17 @@ fn filtered_source(metric: String, matchers: Vec<Unresolved>, shift: TimeShift)
     }
 }
 
-fn instant_source(metric: String, matchers: Vec<Unresolved>, shift: TimeShift) -> Unresolved {
+/// An instant selector: the latest sample per series within the workload's
+/// ingestion interval, so the lookback is an `Instant` `TimeRange`.
+fn instant_source(metric: String, matchers: Vec<Scalar>, shift: TimeShift) -> Unresolved {
+    ingestion_lookback(filtered_source(metric, matchers, shift))
+}
+
+fn ingestion_lookback(child: Unresolved) -> Unresolved {
     Unresolved::TimeRange {
         range: current_ingestion_interval(),
-        child: Rc::new(filtered_source(metric, matchers, shift)),
+        kind: TimeRangeKind::Instant,
+        child: Rc::new(child),
     }
 }
 
@@ -1881,7 +1955,7 @@ fn resolve_group(agg: &AggregateExpr) -> Result<(Vec<ColumnRef>, bool)> {
 
 // ── Free helpers ──────────────────────────────────────────────────────────────
 
-fn vs_parts(vs: &VectorSelector) -> Result<(String, Vec<Unresolved>, TimeShift)> {
+fn vs_parts(vs: &VectorSelector) -> Result<(String, Vec<Scalar>, TimeShift)> {
     // A non-equality `__name__` matcher (`=~` / `!~` / `!=`) selects *across*
     // metric names. `Source::TimeSeries { metric }` carries a single concrete
     // metric name, so there is no representation for a regex/negated name
@@ -1961,21 +2035,22 @@ fn system_time_ms(t: SystemTime) -> Result<i64> {
     })
 }
 
-fn matcher_to_compare(m: &Matcher) -> Unresolved {
+fn matcher_to_compare(m: &Matcher) -> Scalar {
     let op = match &m.op {
         MatchOp::Equal => CompareOpKind::Eq,
         MatchOp::NotEqual => CompareOpKind::Ne,
         MatchOp::Re(_) => CompareOpKind::Regex,
         MatchOp::NotRe(_) => CompareOpKind::NotRegex,
     };
-    Unresolved::Compare {
-        left: Rc::new(Unresolved::Column(ColumnRef::Named(m.name.clone()))),
+    Scalar::Compare {
+        left: Box::new(Scalar::Column(ColumnRef::Named(m.name.clone()))),
         op,
-        right: Rc::new(Unresolved::Literal(ScalarValue::Utf8(m.value.clone()))),
+        right: Box::new(Scalar::Literal(ScalarValue::Utf8(m.value.clone()))),
+        semantics: PROMQL,
     }
 }
 
-fn extract_matrix(expr: &Expr) -> Result<(String, Vec<Unresolved>, Duration, TimeShift)> {
+fn extract_matrix(expr: &Expr) -> Result<(String, Vec<Scalar>, Duration, TimeShift)> {
     match expr {
         Expr::MatrixSelector(ms) => {
             let (metric, matchers, shift) = vs_parts(&ms.vs)?;
@@ -2017,6 +2092,7 @@ fn num_expr(expr: &Expr) -> Result<f64> {
     match expr {
         Expr::NumberLiteral(n) => Ok(n.val),
         Expr::Paren(p) => num_expr(&p.expr),
+        Expr::Unary(u) => Ok(-num_expr(&u.expr)?),
         // Constant-fold a pure scalar arithmetic expression — the parser does
         // not fold `10*1024*1024` / `24 * 3600`. A `modifier` (vector matching)
         // or a non-arithmetic operator means it is not a pure scalar.
@@ -2074,15 +2150,6 @@ fn is_scalar_reducer_fn(name: &str) -> bool {
     matches!(name, "min_of" | "max_of")
 }
 
-/// A `BinaryOp` operand: fold a pure-scalar expression (`5`, `10*1024*1024`) to
-/// a `PromqlScalarBridge` leaf, otherwise walk it as a vector (issue #35).
-fn scalar_or_vector(expr: &Expr) -> Result<Unresolved> {
-    match num_expr(expr) {
-        Ok(v) => Ok(Unresolved::promql_scalar(v)),
-        Err(_) => walk(expr),
-    }
-}
-
 /// `topk`/`bottomk` count parameter — a non-negative integer. Rejects
 /// fractional / negative / non-finite values rather than silently truncating
 /// or saturating them via `as u64` (`topk(2.7, …)` ≠ `topk(2, …)`).
diff --git a/crates/frontend-promql/tests/count_planning.rs b/crates/frontend-promql/tests/count_planning.rs
index 3d3b65651..fd43c9954 100644
--- a/crates/frontend-promql/tests/count_planning.rs
+++ b/crates/frontend-promql/tests/count_planning.rs
@@ -1,19 +1,19 @@
 //! Query text through summary selection: counts use observations, never value weights.
-use std::rc::Rc;
-
 use asap_aware_mapping::accuracy::DefaultAccuracyModel;
 use asap_aware_mapping::cost_model::DefaultCostModel;
 use asap_aware_mapping::{
-    default_strategies, search_workload_with_targets, Replacement, ReplacementStrategy,
-    SketchAlgorithmStrategy, TargetSubDAG,
+    default_strategies, search_workload_with_targets, ASAPStrategies, Replacement,
+    ReplacementStrategy, TargetSubDAG,
 };
 mod support;
+use asap_types::ir::export::PhysicalASAPOperatorPayload;
+use asap_types::ir::{ASAPOp, Operator};
 use asap_types::post_asap::{
-    compile_post_asap_dag, ExactKind, FieldDataType, NonNegativeWeightProof,
-    PostAsapOperatorPayload, SketchAlgorithm, SummaryExpr, SummaryInputExpr, WeightDomain,
+    ExactKind, FieldDataType, NonNegativeWeightProof, SketchAlgorithm, SummaryInputExpr,
+    WeightDomain,
 };
 use asap_types::types::AccuracyTarget;
-use support::lower_promql;
+use support::{lower_promql, post_asap_dag};
 
 #[test]
 fn grouped_count_keeps_uncertified_hydra_candidates_for_backend_review() {
@@ -21,7 +21,7 @@ fn grouped_count_keeps_uncertified_hydra_candidates_for_backend_review() {
         epsilon: 0.01,
         delta: 0.01,
     };
-    let root = Rc::new(lower_promql("count by(job)(up)", target.clone()).unwrap());
+    let root = lower_promql("count by(job)(up)", target.clone()).unwrap();
     let space = search_workload_with_targets(
         vec![("count", root, Some(target))],
         &default_strategies(),
@@ -51,14 +51,14 @@ fn grouped_count_keeps_uncertified_hydra_candidates_for_backend_review() {
 #[test]
 fn exact_counts_select_count_accumulators() {
     for query in ["count(up)", "count by(job)(up)", "count_over_time(up[5m])"] {
-        let root = Rc::new(lower_promql(query, AccuracyTarget::Exact).unwrap());
+        let root = lower_promql(query, AccuracyTarget::Exact).unwrap();
         let candidates =
-            SketchAlgorithmStrategy::default_cost_model().replacements(&TargetSubDAG::new(&root));
+            ASAPStrategies::default_cost_model().replacements(&TargetSubDAG::new(&root));
         assert!(
             candidates.iter().any(|candidate| {
-                matches!(&candidate.replacement, Replacement::Summary(node)
-                if matches!(&node.expr, SummaryExpr::SummaryAgg {
-                    family: FieldDataType::ExactAggregate(ExactKind::Count, _), .. }))
+                matches!(&candidate.replacement, Replacement::SubDAG(node)
+                if matches!(&node.operator, Operator::ASAP(ASAPOp::SummaryAgg {
+                    family: FieldDataType::ExactAggregate(ExactKind::Count, _), .. })))
             }),
             "{query}: {candidates:?}"
         );
@@ -69,22 +69,23 @@ fn exact_counts_select_count_accumulators() {
 #[test]
 fn frequency_count_candidates_use_unit_weights() {
     for query in ["count_over_time(up[5m])", "count(up)"] {
-        let root = Rc::new(lower_promql(query, AccuracyTarget::Epsilon(0.02)).unwrap());
+        let root = lower_promql(query, AccuracyTarget::Epsilon(0.02)).unwrap();
         let candidates =
-            SketchAlgorithmStrategy::default_cost_model().replacements(&TargetSubDAG::new(&root));
+            ASAPStrategies::default_cost_model().replacements(&TargetSubDAG::new(&root));
         let mut algorithms = Vec::new();
         for candidate in &candidates {
-            let Replacement::Summary(node) = &candidate.replacement else {
+            let Replacement::SubDAG(node) = &candidate.replacement else {
                 continue;
             };
-            let SummaryExpr::SummaryEstimate { summary_input, .. } = &node.expr else {
+            let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &node.operator
+            else {
                 continue;
             };
-            let SummaryExpr::SummaryAgg {
+            let Operator::ASAP(ASAPOp::SummaryAgg {
                 family: FieldDataType::Sketch(kind, _),
                 input,
                 ..
-            } = &summary_input.expr
+            }) = &summary_input.operator
             else {
                 continue;
             };
@@ -98,11 +99,11 @@ fn frequency_count_candidates_use_unit_weights() {
             ) {
                 continue;
             }
-            let dag = compile_post_asap_dag(node).unwrap();
+            let dag = post_asap_dag(node);
             assert!(
                 dag.nodes.iter().any(|node| matches!(
                     &node.payload,
-                    PostAsapOperatorPayload::SummaryAgg { input: actual, .. } if actual == input
+                    PhysicalASAPOperatorPayload::SummaryAgg { input: actual, .. } if actual == input
                 )),
                 "post-ASAP DAG must preserve the count update contract"
             );
@@ -135,25 +136,26 @@ fn frequency_count_candidates_use_unit_weights() {
 // This narrow test oracle interprets the emitted aggregate, not Prometheus ingestion,
 // staleness, or scrape scheduling. Unsupported plan shapes fail explicitly.
 fn aggregate_fixture(query: &str, series: &[Vec<f64>]) -> Vec<f64> {
-    use asap_types::pre_asap::{AggIntent, QueryExpr, Reduction};
+    use asap_types::ir::NonASAPOp;
+    use asap_types::pre_asap::{AggIntent, Reduction};
     let root = lower_promql(query, AccuracyTarget::Exact).unwrap();
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = &root
+    } = root.expect_non_asap()
     else {
         panic!("expected aggregate: {root:?}");
     };
-    match child.as_ref() {
-        QueryExpr::Scan { .. } => assert!(series.iter().all(|samples| samples.len() == 1)),
-        QueryExpr::TimeRange { range, child } => {
+    match child.expect_non_asap() {
+        NonASAPOp::Scan { .. } => assert!(series.iter().all(|samples| samples.len() == 1)),
+        NonASAPOp::TimeRange { range, child, .. } => {
             assert!(matches!(range.as_secs(), 1 | 300));
             if range.as_secs() == 1 {
                 assert!(series.iter().all(|samples| samples.len() == 1));
             }
-            assert!(matches!(child.as_ref(), QueryExpr::Scan { .. }));
+            assert!(matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }));
         }
         other => panic!("unsupported fixture input: {other:?}"),
     }
@@ -225,22 +227,20 @@ fn count_over_time_counts_scrapes_not_sample_values() {
 #[test]
 fn cms_count_updates_total_ten_for_zero_positive_and_negative_samples() {
     use asap_types::pre_asap::ColumnRef;
-    let root =
-        Rc::new(lower_promql("count_over_time(up[5m])", AccuracyTarget::Epsilon(0.02)).unwrap());
-    let candidates =
-        SketchAlgorithmStrategy::default_cost_model().replacements(&TargetSubDAG::new(&root));
+    let root = lower_promql("count_over_time(up[5m])", AccuracyTarget::Epsilon(0.02)).unwrap();
+    let candidates = ASAPStrategies::default_cost_model().replacements(&TargetSubDAG::new(&root));
     let dag = candidates
         .iter()
         .find_map(|candidate| {
-            let Replacement::Summary(node) = &candidate.replacement else {
+            let Replacement::SubDAG(node) = &candidate.replacement else {
                 return None;
             };
-            let dag = compile_post_asap_dag(node).unwrap();
+            let dag = post_asap_dag(node);
             dag.nodes
                 .iter()
                 .any(|node| {
                     matches!(&node.payload,
-            PostAsapOperatorPayload::SummaryAgg { family: FieldDataType::Sketch(kind, _), .. }
+            PhysicalASAPOperatorPayload::SummaryAgg { family: FieldDataType::Sketch(kind, _), .. }
                 if kind.algorithm() == &SketchAlgorithm::Cms)
                 })
                 .then_some(dag)
@@ -250,7 +250,7 @@ fn cms_count_updates_total_ten_for_zero_positive_and_negative_samples() {
         .nodes
         .iter()
         .find_map(|node| match &node.payload {
-            PostAsapOperatorPayload::SummaryAgg { input, .. } => Some(input),
+            PhysicalASAPOperatorPayload::SummaryAgg { input, .. } => Some(input),
             _ => None,
         })
         .unwrap();
diff --git a/crates/frontend-promql/tests/histogram_metadata.rs b/crates/frontend-promql/tests/histogram_metadata.rs
index 55f35ddeb..aba373804 100644
--- a/crates/frontend-promql/tests/histogram_metadata.rs
+++ b/crates/frontend-promql/tests/histogram_metadata.rs
@@ -7,16 +7,17 @@
 
 use asap_frontend_promql::{HistogramCatalog, HistogramKind};
 mod support;
-use asap_types::pre_asap::{AggIntent, QueryExpr};
+use asap_types::ir::{NonASAPOp, OperatorNode};
+use asap_types::pre_asap::AggIntent;
 use asap_types::types::AccuracyTarget;
 use support::{lower_promql, lower_promql_with_histograms};
 
 /// The histogram/quantile intent kind in the lowered DAG: `"HQ"` for the
 /// classic-bucket `HistogramQuantile`, `"Q"` for the sketch-able `Quantile`.
-fn quantile_kind(qe: &QueryExpr) -> &'static str {
-    fn walk(e: &QueryExpr) -> Option<&'static str> {
-        match e {
-            QueryExpr::Aggregate {
+fn quantile_kind(qe: &OperatorNode) -> &'static str {
+    fn walk(e: &OperatorNode) -> Option<&'static str> {
+        match e.expect_non_asap() {
+            NonASAPOp::Aggregate {
                 measures, child, ..
             } => measures
                 .iter()
@@ -26,12 +27,12 @@ fn quantile_kind(qe: &QueryExpr) -> &'static str {
                     _ => None,
                 })
                 .or_else(|| walk(child)),
-            QueryExpr::TimeRange { child, .. }
-            | QueryExpr::Filter { child, .. }
-            | QueryExpr::Sort { child, .. }
-            | QueryExpr::Limit { child, .. }
-            | QueryExpr::PromqlSubquery { child, .. }
-            | QueryExpr::Project { child, .. } => walk(child),
+            NonASAPOp::TimeRange { child, .. }
+            | NonASAPOp::Filter { child, .. }
+            | NonASAPOp::Sort { child, .. }
+            | NonASAPOp::Limit { child, .. }
+            | NonASAPOp::PromqlSubquery { child, .. }
+            | NonASAPOp::Project { child, .. } => walk(child),
             _ => None,
         }
     }
@@ -48,27 +49,26 @@ fn with_meta(q: &str, catalog: HistogramCatalog) -> &'static str {
 
 #[test]
 fn heuristic_baseline_is_unchanged_without_a_catalog() {
-    // Classic `by (le)`-bucket form → HistogramQuantile; anything else → Quantile.
+    // Classic buckets are represented; undeclared native samples are rejected.
     assert_eq!(
         heuristic(
             "histogram_quantile(0.9, sum by (le) (rate(http_request_duration_seconds_bucket[5m])))"
         ),
         "HQ"
     );
-    assert_eq!(heuristic("histogram_quantile(0.9, native_latency)"), "Q");
+    assert!(lower_promql(
+        "histogram_quantile(0.9, native_latency)",
+        AccuracyTarget::Exact
+    )
+    .is_err());
 }
 
 #[test]
 fn declared_classic_bucket_fixes_the_false_negative() {
     // A classic histogram exposed WITHOUT the `_bucket` suffix and queried with
-    // no `le` grouping/matcher: the heuristic wrongly routes it to the
-    // sketch-able Quantile. Declaring it `ClassicBucket` corrects it.
+    // no `le` grouping/matcher requires an explicit sample-type declaration.
     let q = "histogram_quantile(0.9, latency_seconds)";
-    assert_eq!(
-        heuristic(q),
-        "Q",
-        "heuristic mis-routes the suffix-less classic histogram"
-    );
+    assert!(lower_promql(q, AccuracyTarget::Exact).is_err());
     assert_eq!(
         with_meta(
             q,
@@ -80,7 +80,7 @@ fn declared_classic_bucket_fixes_the_false_negative() {
 }
 
 #[test]
-fn declared_raw_or_native_fixes_the_false_positive() {
+fn declared_raw_extension_and_native_gap_override_the_heuristic() {
     // A metric merely NAMED `…_bucket` that actually holds raw samples / a native
     // histogram: the heuristic wrongly routes it to bucket interpolation.
     let q = "histogram_quantile(0.9, foo_bucket)";
@@ -97,14 +97,9 @@ fn declared_raw_or_native_fixes_the_false_positive() {
         "Q",
         "raw samples are sketch-able"
     );
-    assert_eq!(
-        with_meta(
-            q,
-            HistogramCatalog::new().with("foo_bucket", HistogramKind::Native)
-        ),
-        "Q",
-        "native histograms are sketch-able"
-    );
+    let catalog = HistogramCatalog::new().with("foo_bucket", HistogramKind::Native);
+    assert!(lower_promql_with_histograms(q, AccuracyTarget::Exact, catalog.clone()).is_err());
+    assert!(lower_promql_with_histograms("foo_bucket", AccuracyTarget::Exact, catalog).is_err());
 }
 
 #[test]
@@ -119,10 +114,12 @@ fn undeclared_metric_falls_back_to_the_heuristic() {
         ),
         "HQ"
     );
-    assert_eq!(
-        with_meta("histogram_quantile(0.9, native_thing)", catalog),
-        "Q"
-    );
+    assert!(lower_promql_with_histograms(
+        "histogram_quantile(0.9, native_thing)",
+        AccuracyTarget::Exact,
+        catalog
+    )
+    .is_err());
 }
 
 #[test]
diff --git a/crates/frontend-promql/tests/maintained_population_horizon.rs b/crates/frontend-promql/tests/maintained_population_horizon.rs
index 88b1c88fe..b4130bf86 100644
--- a/crates/frontend-promql/tests/maintained_population_horizon.rs
+++ b/crates/frontend-promql/tests/maintained_population_horizon.rs
@@ -1,37 +1,33 @@
 mod support;
 use asap_aware_mapping::maintained_population::MaintainedPopulationStrategy;
+use asap_types::ir::{ASAPOp, NonASAPOp, Operator};
 use asap_types::post_asap::maintained_population::PopulationInput;
-use asap_types::post_asap::{SummaryExpr, ValueOperation};
 use asap_types::types::AccuracyTarget;
-use std::rc::Rc;
 
 // A population for a one-second selector must expire members after one second.
 #[test]
 fn population_preserves_selector_horizon() {
-    let root = Rc::new(support::lower_promql("sum(a)", AccuracyTarget::Exact).unwrap());
+    let root = support::lower_promql("sum(a)", AccuracyTarget::Exact).unwrap();
     let candidate = MaintainedPopulationStrategy::new(std::slice::from_ref(&root))
         .candidate(&root)
         .unwrap();
-    let SummaryExpr::ValueOperation { child, .. } = &candidate.expr else {
+    // The evaluation sits over the maintained population.
+    let Operator::ASAP(ASAPOp::EvaluatePopulation { child, .. }) = &candidate.operator else {
         panic!()
     };
-    let SummaryExpr::ValueOperation {
-        operation: ValueOperation::MaintainPopulation { population },
-        ..
-    } = &child.expr
-    else {
+    let Operator::ASAP(ASAPOp::MaintainPopulation { population, .. }) = &child.operator else {
         panic!()
     };
     let PopulationInput::CurrentSeries(spec) = &population.input else {
         panic!()
     };
     assert_eq!(spec.lookback_ms, 1_000);
-    asap_types::post_asap::compile_post_asap_dag(&candidate).unwrap();
-    let asap_types::pre_asap::QueryExpr::Aggregate { child: source, .. } = root.as_ref() else {
+    support::post_asap_dag(&candidate);
+    let NonASAPOp::Aggregate { child: source, .. } = root.expect_non_asap() else {
         panic!()
     };
-    assert!(spec.matches_input(source));
+    assert!(spec.matches_node(source));
     let mut wrong = spec.clone();
     wrong.lookback_ms = 300_000;
-    assert!(!wrong.matches_input(source));
+    assert!(!wrong.matches_node(source));
 }
diff --git a/crates/frontend-promql/tests/observability/awesome_prometheus_alerts.rs b/crates/frontend-promql/tests/observability/awesome_prometheus_alerts.rs
index 1b37cdee4..5e78e261d 100644
--- a/crates/frontend-promql/tests/observability/awesome_prometheus_alerts.rs
+++ b/crates/frontend-promql/tests/observability/awesome_prometheus_alerts.rs
@@ -29,7 +29,10 @@
 use asap_frontend_promql::PromqlError as LoweringError;
 #[path = "../support.rs"]
 mod support;
-use asap_types::pre_asap::{AggIntent, BinaryOpKind, CompareOpKind, QueryExpr, Reduction};
+use std::rc::Rc;
+
+use asap_types::ir::{BinaryOperator, NonASAPOp, OperatorNode, ScalarExpr};
+use asap_types::pre_asap::{AggIntent, BinaryOpKind, CompareOpKind, Reduction, ScalarValue};
 use asap_types::types::AccuracyTarget;
 use support::lower_promql;
 
@@ -44,78 +47,29 @@ fn queries() -> impl Iterator<Item = &'static str> {
 }
 
 /// Lower, expecting success.
-fn ok(q: &str) -> QueryExpr {
+fn ok(q: &str) -> Rc<OperatorNode> {
     lower_promql(q, AccuracyTarget::Exact)
         .unwrap_or_else(|e| panic!("expected {q:?} to lower, got error: {e}"))
 }
 
-/// Every `AggIntent` in the DAG.
-fn intents(e: &QueryExpr) -> Vec<AggIntent> {
+/// Every `AggIntent` in the tree. `AggIntent` only ever lives in
+/// `Aggregate.measures`, never in a scalar position (issue #205);
+/// `children()` also descends into the operators a scalar position reads.
+fn intents(e: &OperatorNode) -> Vec<AggIntent> {
     let mut out = Vec::new();
-    fn go(e: &QueryExpr, out: &mut Vec<AggIntent>) {
-        match e {
-            QueryExpr::Aggregate {
-                measures, child, ..
-            } => {
-                out.extend(measures.iter().cloned());
-                go(child, out);
-            }
-            QueryExpr::TimeRange { child, .. }
-            | QueryExpr::TimeShift { child, .. }
-            | QueryExpr::Filter { child, .. }
-            | QueryExpr::Sort { child, .. }
-            | QueryExpr::Limit { child, .. }
-            | QueryExpr::PromqlSubquery { child, .. }
-            | QueryExpr::Dedup { child, .. }
-            | QueryExpr::SQLWindowFunc { child, .. }
-            | QueryExpr::Project { child, .. }
-            | QueryExpr::PromqlRelabel { child, .. }
-            | QueryExpr::PromqlSeriesSample { child, .. }
-            | QueryExpr::PromqlInfoEnrich { child, .. } => go(child, out),
-            QueryExpr::BinaryOp { lhs, rhs, .. }
-            | QueryExpr::Join {
-                left: lhs,
-                right: rhs,
-                ..
-            }
-            | QueryExpr::SetOp {
-                left: lhs,
-                right: rhs,
-                ..
-            } => {
-                go(lhs, out);
-                go(rhs, out);
-            }
-            QueryExpr::Concat { children, .. } => children.iter().for_each(|c| go(c, out)),
-            QueryExpr::PromqlVectorFromScalar(inner) | QueryExpr::PromqlScalarFromVector(inner) => {
-                go(inner, out)
-            }
-            // `AggIntent` only ever lives in `Aggregate.measures`, never in a
-            // scalar position (issue #205) — nothing to collect there.
-            QueryExpr::Scan { .. }
-            | QueryExpr::PromqlScalarBridge(_)
-            | QueryExpr::EvalTimestamp
-            | QueryExpr::CurrentTimestamp => {}
-            QueryExpr::Column(_)
-            | QueryExpr::Literal(_)
-            | QueryExpr::Compare { .. }
-            | QueryExpr::BoolAnd(_)
-            | QueryExpr::BoolOr(_)
-            | QueryExpr::Not(_)
-            | QueryExpr::IsNull(_)
-            | QueryExpr::IsNotNull(_)
-            | QueryExpr::Cast { .. }
-            | QueryExpr::InList { .. }
-            | QueryExpr::FunctionCall { .. }
-            | QueryExpr::Arithmetic { .. }
-            | QueryExpr::Case { .. } => {}
+    fn go(e: &OperatorNode, out: &mut Vec<AggIntent>) {
+        if let Some(NonASAPOp::Aggregate { measures, .. }) = e.non_asap() {
+            out.extend(measures.iter().cloned());
+        }
+        for child in e.children() {
+            go(child, out);
         }
     }
     go(e, &mut out);
     out
 }
 
-fn has<F: Fn(&AggIntent) -> bool>(e: &QueryExpr, p: F) -> bool {
+fn has<F: Fn(&AggIntent) -> bool>(e: &OperatorNode, p: F) -> bool {
     intents(e).iter().any(p)
 }
 
@@ -180,15 +134,21 @@ fn vector_vs_vector_comparison_lowers_to_binaryop() {
     // Both operands are instant vectors → a `BinaryOp{Compare}` of two
     // ingestion-interval-bounded scans.
     let qe = ok("node_hwmon_temp_celsius > node_hwmon_temp_max_celsius");
-    let QueryExpr::BinaryOp { op, lhs, rhs, .. } = &qe else {
+    let NonASAPOp::BinaryOp {
+        operator: BinaryOperator { kind: op, .. },
+        lhs,
+        rhs,
+        ..
+    } = qe.expect_non_asap()
+    else {
         panic!("expected BinaryOp, got {qe:?}");
     };
     assert_eq!(*op, BinaryOpKind::Compare(CompareOpKind::Gt));
     assert!(
-        matches!(lhs.as_ref(), QueryExpr::TimeRange { child, .. } if matches!(child.as_ref(), QueryExpr::Scan { .. }))
+        matches!(lhs.expect_non_asap(), NonASAPOp::TimeRange { child, .. } if matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }))
     );
     assert!(
-        matches!(rhs.as_ref(), QueryExpr::TimeRange { child, .. } if matches!(child.as_ref(), QueryExpr::Scan { .. }))
+        matches!(rhs.expect_non_asap(), NonASAPOp::TimeRange { child, .. } if matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }))
     );
 }
 
@@ -197,8 +157,8 @@ fn kube_replica_mismatch_comparison_lowers() {
     // Kubernetes: `kube_replicaset_spec_replicas != kube_replicaset_status_ready_replicas`.
     let qe = ok("kube_replicaset_spec_replicas != kube_replicaset_status_ready_replicas");
     assert!(matches!(
-        &qe,
-        QueryExpr::BinaryOp { op, .. } if *op == BinaryOpKind::Compare(CompareOpKind::Ne)
+            qe.expect_non_asap(),
+        NonASAPOp::BinaryOp { operator: BinaryOperator { kind: op, .. }, .. } if *op == BinaryOpKind::Compare(CompareOpKind::Ne)
     ));
 }
 
@@ -225,7 +185,11 @@ fn error_ratio_core_lowers() {
     // threshold: `sum(rate(failed[5m])) / sum(rate(total[5m]))` → a `BinaryOp(Div)`
     // of two cross-series sums over per-series rates.
     let qe = ok("sum(rate(litellm_proxy_failed_requests_metric_total[5m])) / sum(rate(litellm_proxy_total_requests_metric_total[5m]))");
-    let QueryExpr::BinaryOp { op, .. } = &qe else {
+    let NonASAPOp::BinaryOp {
+        operator: BinaryOperator { kind: op, .. },
+        ..
+    } = qe.expect_non_asap()
+    else {
         panic!("expected BinaryOp, got {qe:?}");
     };
     assert!(matches!(op, BinaryOpKind::Arithmetic(_)));
@@ -250,11 +214,11 @@ fn all_targets_missing_core_lowers() {
     // Prometheus self-monitoring `sum by (job) (up)` (the corpus query is
     // `… == 0`). Cross-series sum grouped positionally on `job`.
     let qe = ok("sum by (job) (up)");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected Aggregate, got {qe:?}");
     };
@@ -273,19 +237,17 @@ fn all_targets_missing_core_lowers() {
 #[test]
 fn scalar_threshold_comparisons_lower_to_binaryop_scalar() {
     // ~822/949 corpus queries are `<vector> <cmp> <scalar>`. The numeric
-    // threshold is now a `PromqlScalarBridge` operand of the `BinaryOp` (issue
+    // threshold is now a `ScalarExpr` operand of the `BinaryOp` (issue
     // #35) — the single biggest unblock for real alerts.
     for q in [
         "prometheus_config_last_reload_successful != 1",
         "increase(prometheus_tsdb_compactions_failed_total[1m]) > 0",
         "rate(alertmanager_notifications_failed_total[3m]) > 0.05",
     ] {
-        let QueryExpr::BinaryOp { rhs, .. } = ok(q) else {
-            panic!("expected a BinaryOp for {q:?}");
-        };
+        let qe = ok(q);
         assert!(
-            matches!(rhs.as_ref(), QueryExpr::PromqlScalarBridge(_)),
-            "scalar threshold operand for {q:?}, got {rhs:?}"
+            matches!(qe.expect_non_asap(), NonASAPOp::Filter { .. }),
+            "{q}"
         );
     }
 }
@@ -336,12 +298,12 @@ fn vector_literal_lowers_to_a_labelless_vector() {
     // `vector(1)` — used in dead-man's-switch ("always firing") alerts. Now
     // lowers to a `PromqlVectorFromScalar` over the scalar `1` (issue #48).
     let qe = ok("vector(1)");
-    let QueryExpr::PromqlVectorFromScalar(inner) = &qe else {
+    let NonASAPOp::PromqlVectorFromScalar(inner) = qe.expect_non_asap() else {
         panic!("expected PromqlVectorFromScalar, got {qe:?}");
     };
-    assert_eq!(inner.as_promql_scalar(), Some(1.0));
+    assert!(matches!(inner, ScalarExpr::Literal(ScalarValue::Float64(v)) if *v == 1.0));
     // The result is a vector: it carries a time index (unlike a bare scalar).
-    assert!(qe.output_schema().unwrap().time_index.is_some());
+    assert!(qe.schema.time_index.is_some());
 }
 
 #[test]
@@ -352,14 +314,14 @@ fn without_grouping_lowers_to_the_exclusion_form() {
     // labels are stored and the kept set is runtime-resolved (issue #39).
     let qe = ok(r#"(min without (cpu) (rate(node_cpu_seconds_total{mode="idle"}[1h]))) > 0.8"#);
     // Top level is the `> 0.8` comparison; the `min without (cpu)` is its LHS.
-    let QueryExpr::BinaryOp { lhs, .. } = &qe else {
+    let NonASAPOp::Filter { child: lhs, .. } = qe.expect_non_asap() else {
         panic!("expected a comparison BinaryOp, got {qe:?}");
     };
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         ..
-    } = lhs.as_ref()
+    } = lhs.expect_non_asap()
     else {
         panic!("expected a `min without` Aggregate on the LHS, got {lhs:?}");
     };
diff --git a/crates/frontend-promql/tests/observability/metrics_observability.rs b/crates/frontend-promql/tests/observability/metrics_observability.rs
index 87d653ef2..d40df6236 100644
--- a/crates/frontend-promql/tests/observability/metrics_observability.rs
+++ b/crates/frontend-promql/tests/observability/metrics_observability.rs
@@ -6,15 +6,14 @@
 
 use std::rc::Rc;
 
-use asap_aware_mapping::replacement::{keep_pre_asap, RealizationError};
+use asap_aware_mapping::replacement::{retain_exact, RealizationError};
 use asap_aware_mapping::{
-    Replacement, ReplacementStrategy, ReplacementSubDAG, SketchAlgorithmStrategy, TargetSubDAG,
+    ASAPStrategies, Replacement, ReplacementStrategy, ReplacementSubDAG, TargetSubDAG,
 };
 use asap_frontend_promql::PromqlError;
 #[path = "../support.rs"]
 mod support;
-use asap_types::post_asap::{SummaryExpr, SummaryNode};
-use asap_types::pre_asap::query_expr::QueryExpr;
+use asap_types::ir::OperatorNode;
 use asap_types::types::AccuracyTarget;
 use support::lower_promql;
 
@@ -64,19 +63,18 @@ fn queries(corpus: &str) -> impl Iterator<Item = &str> {
         .filter(|line| !line.is_empty() && !line.starts_with('#'))
 }
 
-fn post_asap_candidate(expr: &QueryExpr) -> Result<Rc<SummaryNode>, RealizationError> {
-    let root = Rc::new(expr.clone());
-    let target = TargetSubDAG::new(&root);
-    match SketchAlgorithmStrategy::default_cost_model()
+fn post_asap_candidate(root: &Rc<OperatorNode>) -> Result<Rc<OperatorNode>, RealizationError> {
+    let target = TargetSubDAG::new(root);
+    match ASAPStrategies::default_cost_model()
         .replacements(&target)
         .into_iter()
         .next()
     {
         Some(ReplacementSubDAG {
-            replacement: Replacement::Summary(node),
+            replacement: Replacement::SubDAG(node),
             ..
         }) => Ok(node),
-        _ => keep_pre_asap(&root),
+        _ => retain_exact(root),
     }
 }
 
@@ -99,9 +97,8 @@ fn benchmark_corpora_are_total_and_report_coverage() {
                 Ok(expr) => {
                     lowered += 1;
                     match post_asap_candidate(&expr) {
-                        Ok(node) if !matches!(node.expr, SummaryExpr::KeepPreAsap(_)) => {
-                            post_asap_candidates += 1
-                        }
+                        // An ASAP operator bound somewhere below the root.
+                        Ok(node) if node.contains_asap() => post_asap_candidates += 1,
                         Ok(_) => {
                             post_asap_unchanged += 1;
                             if std::env::var_os("METRICS_OBSERVABILITY_REPORT").is_some() {
diff --git a/crates/frontend-promql/tests/observability/promql_corpus.rs b/crates/frontend-promql/tests/observability/promql_corpus.rs
index 1bc7e2166..45afdeb5f 100644
--- a/crates/frontend-promql/tests/observability/promql_corpus.rs
+++ b/crates/frontend-promql/tests/observability/promql_corpus.rs
@@ -15,37 +15,35 @@
 
 use std::rc::Rc;
 
-use asap_aware_mapping::replacement::{keep_pre_asap, RealizationError};
+use asap_aware_mapping::replacement::{retain_exact, RealizationError};
 use asap_aware_mapping::{
-    Replacement, ReplacementStrategy, ReplacementSubDAG, SketchAlgorithmStrategy, TargetSubDAG,
+    ASAPStrategies, Replacement, ReplacementStrategy, ReplacementSubDAG, TargetSubDAG,
 };
 use asap_frontend_promql::PromqlError as LoweringError;
 #[path = "../support.rs"]
 mod support;
-use asap_types::post_asap::{SummaryExpr, SummaryNode};
-use asap_types::pre_asap::query_expr::QueryExpr;
+use asap_types::ir::OperatorNode;
 use asap_types::types::AccuracyTarget;
 use support::lower_promql;
 
-/// This crate has no "bind me one DAG" public API any more —
-/// `SketchAlgorithmStrategy::replacements` always returns every candidate, and
+/// This crate has no "bind me one dag" public API any more —
+/// `ASAPStrategies::replacements` always returns every candidate, and
 /// a caller decides what to keep. This test-only helper reproduces the
 /// take-the-first-(`cost_model`-preferred)-candidate pattern so [`bind_tally`]
 /// gets one representative `Result` per query, matching what a totality
 /// check over the whole corpus wants.
-fn bind(expr: &QueryExpr) -> Result<Rc<SummaryNode>, RealizationError> {
-    let root = Rc::new(expr.clone());
-    let target = TargetSubDAG::new(&root);
-    match SketchAlgorithmStrategy::default_cost_model()
+fn bind(root: &Rc<OperatorNode>) -> Result<Rc<OperatorNode>, RealizationError> {
+    let target = TargetSubDAG::new(root);
+    match ASAPStrategies::default_cost_model()
         .replacements(&target)
         .into_iter()
         .next()
     {
         Some(ReplacementSubDAG {
-            replacement: Replacement::Summary(node),
+            replacement: Replacement::SubDAG(node),
             ..
         }) => Ok(node),
-        _ => keep_pre_asap(&root),
+        _ => retain_exact(root),
     }
 }
 
@@ -77,7 +75,10 @@ impl Tally {
 fn tally(corpus: &str) -> Tally {
     let mut t = Tally::default();
     for q in queries(corpus) {
-        match lower_promql(q, AccuracyTarget::Exact) {
+        match asap_frontend_promql::lower_promql_query_workload(
+            &support::workload(q, AccuracyTarget::Exact),
+            0,
+        ) {
             Ok(_) => t.lowered += 1,
             Err(LoweringError::Parse(_)) => t.unparseable += 1,
             Err(_) => t.rejected += 1,
@@ -93,9 +94,10 @@ fn tally(corpus: &str) -> Tally {
 /// arm).
 #[derive(Default, Debug)]
 struct BindTally {
-    /// Root bound to `SummaryAgg`/`SummaryEstimate` — the pass did something.
+    /// An ASAP operator was bound somewhere below the root — the pass did
+    /// something.
     transformed: usize,
-    /// Root stayed `KeepPreAsap` — the pass left the query untouched.
+    /// The kept pre-ASAP dag — the pass left the query untouched.
     unchanged: usize,
     /// [`bind`] returned `Err` (schema derivation failed).
     errored: usize,
@@ -108,7 +110,7 @@ fn bind_tally(corpus: &str, accuracy: AccuracyTarget) -> BindTally {
             continue;
         };
         match bind(&dag) {
-            Ok(bound) if matches!(bound.expr, SummaryExpr::KeepPreAsap(_)) => t.unchanged += 1,
+            Ok(bound) if !bound.contains_asap() => t.unchanged += 1,
             Ok(_) => t.transformed += 1,
             Err(_) => t.errored += 1,
         }
@@ -148,23 +150,17 @@ fn lowering_is_total_over_the_entire_corpus() {
         "testdata corpus unexpectedly small: {td:?}"
     );
 
-    // Coverage tripwire: a code change that breaks lowering for a large slice of
-    // real PromQL trips this. Current numbers on the private promql-parser `asap`
-    // branch: docs 48 lowered / 1 rejected, testdata 1512 lowered / 76 rejected /
-    // 235 unparseable. The floors sit ~1% under those, so they guard regressions
-    // rather than pin an exact count — ratchet them up as coverage lands.
-    //
-    // The 235 unparseable are parser-fork gaps (issue #108); the rejections are
-    // lowering gaps (#109). Both shrink over time, so these floors normally only
-    // rise. Exception: the testdata floor was lowered to the measured 1485 when
-    // the 44 `fill` vector-matching queries became rejected rather than
-    // silently lowered without their fill semantics.
+    // Coverage tripwire after rejecting unrepresented native histogram samples:
+    // docs 48 lowered / 1 rejected; testdata 1121 lowered / 469 rejected /
+    // 233 parser gaps. Earlier coverage counted native histogram operations
+    // incorrectly treated as float quantiles. Keep the rejection cases in the
+    // corpus: accepting them requires a native histogram sample representation.
     assert!(
         docs.lowered >= 47,
         "docs lowering coverage regressed: {docs:?}"
     );
     assert!(
-        td.lowered >= 1485,
+        td.lowered >= 1121,
         "testdata lowering coverage regressed: {td:?}"
     );
 }
diff --git a/crates/frontend-promql/tests/promql_binding_regressions.rs b/crates/frontend-promql/tests/promql_binding_regressions.rs
index 26d1be06d..416b6680d 100644
--- a/crates/frontend-promql/tests/promql_binding_regressions.rs
+++ b/crates/frontend-promql/tests/promql_binding_regressions.rs
@@ -33,9 +33,10 @@ fn irate_and_rate_have_distinct_canonical_intents() {
 /// PromQL count counts series even when two sample values are equal.
 #[test]
 fn count_is_row_count_not_distinct_sample_value_count() {
-    use asap_types::pre_asap::{AggIntent, QueryExpr};
-    let dag = lower_promql("count(smoke_gauge)", AccuracyTarget::Exact).unwrap();
-    let QueryExpr::Aggregate { measures, .. } = dag else {
+    use asap_types::ir::NonASAPOp;
+    use asap_types::pre_asap::AggIntent;
+    let tree = lower_promql("count(smoke_gauge)", AccuracyTarget::Exact).unwrap();
+    let NonASAPOp::Aggregate { measures, .. } = tree.expect_non_asap() else {
         panic!("expected aggregate")
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
diff --git a/crates/frontend-promql/tests/promql_conformance.rs b/crates/frontend-promql/tests/promql_conformance.rs
index 6f932879e..2f3fa2bf8 100644
--- a/crates/frontend-promql/tests/promql_conformance.rs
+++ b/crates/frontend-promql/tests/promql_conformance.rs
@@ -31,22 +31,26 @@
 // `__GAP`-suffixed test names intentionally SHOUT the documented divergences.
 #![allow(non_snake_case)]
 
+use std::rc::Rc;
 use std::time::Duration;
 
 use asap_frontend_promql::PromqlError as LoweringError;
 mod support;
+use asap_types::ir::{
+    BinaryOperator, ExprSemantics, NonASAPOp, OperatorNode, ScalarExpr, TimeRangeKind,
+};
 use asap_types::pre_asap::schema::DataType;
 use asap_types::pre_asap::{
-    AggIntent, ArithmeticOpKind, AtModifier, BinaryOpKind, CompareOpKind, MathFunc,
-    PromQLVectorSetOpKind, QueryExpr, Reduction, SampleKind, Source, TimeFunc,
+    AggIntent, ArithmeticOpKind, AtModifier, BinaryOpKind, CompareOpKind, PromQLVectorSetOpKind,
+    Reduction, SampleKind, ScalarValue, Source, TimeFunc,
 };
 use asap_types::types::AccuracyTarget;
-use support::lower_promql;
+use support::{lower_promql, promql_scalar};
 
 // ── harness helpers ─────────────────────────────────────────────────────────────
 
 /// Lower, expecting success.
-fn ok(q: &str) -> QueryExpr {
+fn ok(q: &str) -> Rc<OperatorNode> {
     lower_promql(q, AccuracyTarget::Exact)
         .unwrap_or_else(|e| panic!("expected {q:?} to lower, got error: {e}"))
 }
@@ -59,72 +63,30 @@ fn rejected(q: &str) -> LoweringError {
     }
 }
 
-/// Every `AggIntent` anywhere in the DAG, root-to-leaf.
-fn intents(e: &QueryExpr) -> Vec<AggIntent> {
+/// Every `AggIntent` anywhere in the tree, root-to-leaf.
+fn intents(e: &OperatorNode) -> Vec<AggIntent> {
     let mut out = Vec::new();
     collect(e, &mut out);
     out
 }
 
-fn collect(e: &QueryExpr, out: &mut Vec<AggIntent>) {
-    match e {
-        QueryExpr::Aggregate {
-            measures, child, ..
-        } => {
-            out.extend(measures.iter().cloned());
-            collect(child, out);
-        }
-        QueryExpr::TimeRange { child, .. }
-        | QueryExpr::TimeShift { child, .. }
-        | QueryExpr::Filter { child, .. }
-        | QueryExpr::Sort { child, .. }
-        | QueryExpr::Limit { child, .. }
-        | QueryExpr::PromqlSubquery { child, .. }
-        | QueryExpr::Dedup { child, .. }
-        | QueryExpr::SQLWindowFunc { child, .. }
-        | QueryExpr::Project { child, .. }
-        | QueryExpr::PromqlRelabel { child, .. }
-        | QueryExpr::PromqlSeriesSample { child, .. }
-        | QueryExpr::PromqlInfoEnrich { child, .. } => collect(child, out),
-        QueryExpr::BinaryOp { lhs, rhs, .. } => {
-            collect(lhs, out);
-            collect(rhs, out);
-        }
-        QueryExpr::Join { left, right, .. } | QueryExpr::SetOp { left, right, .. } => {
-            collect(left, out);
-            collect(right, out);
-        }
-        QueryExpr::Concat { children, .. } => children.iter().for_each(|c| collect(c, out)),
-        QueryExpr::PromqlVectorFromScalar(inner) | QueryExpr::PromqlScalarFromVector(inner) => {
-            collect(inner, out)
-        }
-        // `AggIntent` only ever lives in `Aggregate.measures`, never in a
-        // scalar position (issue #205) — nothing to collect there.
-        QueryExpr::Scan { .. }
-        | QueryExpr::PromqlScalarBridge(_)
-        | QueryExpr::EvalTimestamp
-        | QueryExpr::CurrentTimestamp => {}
-        QueryExpr::Column(_)
-        | QueryExpr::Literal(_)
-        | QueryExpr::Compare { .. }
-        | QueryExpr::BoolAnd(_)
-        | QueryExpr::BoolOr(_)
-        | QueryExpr::Not(_)
-        | QueryExpr::IsNull(_)
-        | QueryExpr::IsNotNull(_)
-        | QueryExpr::Cast { .. }
-        | QueryExpr::InList { .. }
-        | QueryExpr::FunctionCall { .. }
-        | QueryExpr::Arithmetic { .. }
-        | QueryExpr::Case { .. } => {}
+/// `AggIntent` only ever lives in `Aggregate.measures`, never in a scalar
+/// position (issue #205); `children()` also descends into the operators a
+/// scalar position reads (`scalar(v)`).
+fn collect(e: &OperatorNode, out: &mut Vec<AggIntent>) {
+    if let Some(NonASAPOp::Aggregate { measures, .. }) = e.non_asap() {
+        out.extend(measures.iter().cloned());
+    }
+    for child in e.children() {
+        collect(child, out);
     }
 }
 
 /// The first `Scan` reached by descending single-child nodes, with its metric
 /// name and predicate count.
-fn first_scan(e: &QueryExpr) -> (String, usize) {
-    match e {
-        QueryExpr::Scan {
+fn first_scan(e: &OperatorNode) -> (String, usize) {
+    match e.expect_non_asap() {
+        NonASAPOp::Scan {
             source, predicates, ..
         } => {
             let name = match source {
@@ -133,45 +95,32 @@ fn first_scan(e: &QueryExpr) -> (String, usize) {
             };
             (name, predicates.len())
         }
-        QueryExpr::TimeRange { child, .. }
-        | QueryExpr::TimeShift { child, .. }
-        | QueryExpr::Aggregate { child, .. }
-        | QueryExpr::Filter { child, .. }
-        | QueryExpr::Sort { child, .. }
-        | QueryExpr::Limit { child, .. }
-        | QueryExpr::PromqlSubquery { child, .. } => first_scan(child),
+        NonASAPOp::TimeRange { child, .. }
+        | NonASAPOp::TimeShift { child, .. }
+        | NonASAPOp::Aggregate { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. }
+        | NonASAPOp::PromqlSubquery { child, .. } => first_scan(child),
         other => panic!("no Scan reachable from {other:?}"),
     }
 }
 
-fn has<F: Fn(&AggIntent) -> bool>(e: &QueryExpr, pred: F) -> bool {
+fn has<F: Fn(&AggIntent) -> bool>(e: &OperatorNode, pred: F) -> bool {
     intents(e).iter().any(pred)
 }
 
-/// Whether the DAG contains a `Mul`-by-`PromqlScalarBridge(-1)` anywhere — the shape unary
+/// Whether the tree contains a `Mul`-by-`ScalarExpr(-1)` anywhere — the shape unary
 /// negation lowers to (issue #36).
-fn negates_via_scalar(e: &QueryExpr) -> bool {
-    let is_neg_one = |q: &QueryExpr| {
-        q.as_promql_scalar()
-            .is_some_and(|v| (v + 1.0).abs() < 1e-12)
-    };
-    match e {
-        QueryExpr::BinaryOp { op, lhs, rhs, .. } => {
-            (*op == BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul)
-                && (is_neg_one(lhs) || is_neg_one(rhs)))
-                || negates_via_scalar(lhs)
-                || negates_via_scalar(rhs)
-        }
-        QueryExpr::Aggregate { child, .. }
-        | QueryExpr::Sort { child, .. }
-        | QueryExpr::Limit { child, .. }
-        | QueryExpr::TimeRange { child, .. }
-        | QueryExpr::TimeShift { child, .. }
-        | QueryExpr::PromqlSubquery { child, .. }
-        | QueryExpr::Filter { child, .. }
-        | QueryExpr::Project { child, .. } => negates_via_scalar(child),
-        _ => false,
+fn negates_via_scalar(e: &OperatorNode) -> bool {
+    fn negative(expr: &ScalarExpr) -> bool {
+        matches!(expr, ScalarExpr::Negative { .. }) || expr.children().iter().any(|e| negative(e))
     }
+    e.expect_non_asap()
+        .scalar_exprs()
+        .iter()
+        .any(|e| negative(e))
+        || e.children().iter().any(|e| negates_via_scalar(e))
 }
 
 // ─────────────────────────────────────────────────────────────────────────────
@@ -193,10 +142,10 @@ fn promql_scan_schema_is_open() {
     // runtime-only, so the binding schema lists only the (ts, value) floor +
     // referenced labels and may be a subset of the runtime row.
     let qe = ok("node_cpu_seconds_total");
-    let QueryExpr::TimeRange { child, .. } = &qe else {
+    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
         panic!("expected a TimeRange for a bare selector, got {qe:?}");
     };
-    let QueryExpr::Scan { schema, .. } = child.as_ref() else {
+    let NonASAPOp::Scan { schema, .. } = child.expect_non_asap() else {
         panic!("expected a Scan inside the TimeRange, got {qe:?}");
     };
     assert!(
@@ -241,7 +190,7 @@ fn range_vector_selector_is_time_range() {
     // SEMANTICS: `[5m]` turns an instant vector into a range vector,
     // represented in the canonical DAG as a dedicated `TimeRange` node.
     let qe = ok("node_cpu_seconds_total[5m]");
-    let QueryExpr::TimeRange { range, .. } = &qe else {
+    let NonASAPOp::TimeRange { range, .. } = qe.expect_non_asap() else {
         panic!("expected TimeRange for a range-vector selector, got {qe:?}");
     };
     assert_eq!(*range, Duration::from_secs(300));
@@ -252,19 +201,44 @@ fn range_vector_selector_is_time_range() {
 //    functions.test)
 // ─────────────────────────────────────────────────────────────────────────────
 
+#[test]
+fn selector_time_ranges_carry_their_kind() {
+    // SEMANTICS: an instant selector reads the latest sample within the
+    // ingestion interval (`Instant`); `m[5m]` is a range selection (`Range`).
+    // Same length is not the same shape: `m` and `m[1s]` stay distinct.
+    assert!(matches!(
+        ok("node_cpu_seconds_total").expect_non_asap(),
+        NonASAPOp::TimeRange {
+            kind: TimeRangeKind::Instant,
+            ..
+        }
+    ));
+    assert!(matches!(
+        ok("node_cpu_seconds_total[5m]").expect_non_asap(),
+        NonASAPOp::TimeRange {
+            kind: TimeRangeKind::Range,
+            ..
+        }
+    ));
+    assert_ne!(
+        ok("node_cpu_seconds_total"),
+        ok("node_cpu_seconds_total[1s]")
+    );
+}
+
 #[test]
 fn rate_range_lives_in_time_range_node() {
     // SEMANTICS: per-second average rate; the temporal range lives on the
     // enclosing `TimeRange` node, not inside the intent.
     let qe = ok("rate(http_requests_total[5m])");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected Aggregate, got {qe:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
-    let QueryExpr::TimeRange { range, .. } = child.as_ref() else {
+    let NonASAPOp::TimeRange { range, .. } = child.expect_non_asap() else {
         panic!("expected TimeRange child, got {child:?}");
     };
     assert_eq!(*range, Duration::from_secs(300));
@@ -281,14 +255,14 @@ fn irate_maps_to_its_own_intent() {
 #[test]
 fn increase_range_lives_in_time_range_node() {
     let qe = ok("increase(http_requests_total[1h])");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected Aggregate, got {qe:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Increase]));
-    let QueryExpr::TimeRange { range, .. } = child.as_ref() else {
+    let NonASAPOp::TimeRange { range, .. } = child.expect_non_asap() else {
         panic!("expected TimeRange child, got {child:?}");
     };
     assert_eq!(*range, Duration::from_secs(3600));
@@ -303,7 +277,7 @@ fn increase_range_lives_in_time_range_node() {
 fn sum_collapses_all_series() {
     // SEMANTICS: `sum(v)` → one output series. No grouping → no Partition.
     let qe = ok("sum(node_filesystem_size_bytes)");
-    assert!(matches!(&qe, QueryExpr::Aggregate { .. }));
+    assert!(matches!(qe.expect_non_asap(), NonASAPOp::Aggregate { .. }));
     assert!(has(&qe, |i| matches!(i, AggIntent::Sum { .. })));
 }
 
@@ -314,12 +288,12 @@ fn sum_by_groups_via_positional_aggregate() {
     // name-based Partition). SchemaResolver leaf = [ts, value, instance, job] (referenced
     // keys appended sorted), so the keys resolve to columns [2, 3].
     let qe = ok("sum by(job, instance) (node_filesystem_size_bytes)");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected positional Aggregate for `by(...)`, got {qe:?}");
     };
@@ -330,7 +304,7 @@ fn sum_by_groups_via_positional_aggregate() {
     );
     assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
     assert!(
-        matches!(child.as_ref(), QueryExpr::TimeRange { child, .. } if matches!(child.as_ref(), QueryExpr::Scan { .. }))
+        matches!(child.expect_non_asap(), NonASAPOp::TimeRange { child, .. } if matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }))
     );
 }
 
@@ -369,11 +343,11 @@ fn sum_without_groups_by_the_complement() {
     // the runtime: the grouping is the exclusion form and the output schema
     // stays OPEN (unlike `by`, which freezes to closed).
     let qe = ok("sum without(instance) (node_filesystem_size_bytes)");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected an Aggregate, got {qe:?}");
     };
@@ -385,7 +359,7 @@ fn sum_without_groups_by_the_complement() {
     assert_eq!(by.keys().len(), 1, "the one excluded label (instance)");
     assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
     assert!(
-        !qe.output_schema().unwrap().closed,
+        !qe.schema.clone().closed,
         "a `without` result keeps an open schema (kept label set is runtime-only)"
     );
 }
@@ -418,16 +392,16 @@ fn group_aggregator_lowers_to_a_distinct_intent() {
 fn sum_of_rate_is_two_levels() {
     // SEMANTICS: per-series rate, THEN cross-series sum. Both must survive.
     let qe = ok("sum(rate(http_requests_total[5m]))");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate{{Sum}}, got {qe:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
     assert!(matches!(
-        child.as_ref(),
-        QueryExpr::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate])
+        child.expect_non_asap(),
+        NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate])
     ));
 }
 
@@ -436,12 +410,12 @@ fn sum_by_of_rate_groups_outer_level() {
     // Outer cross-series Sum grouped on positional `Aggregate.by` over the
     // label-preserving inner Rate. Leaf = [ts, value, instance] → by = [2].
     let qe = ok("sum by(instance) (rate(node_network_receive_bytes_total[5m]))");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate grouped by instance, got {qe:?}");
     };
@@ -449,8 +423,8 @@ fn sum_by_of_rate_groups_outer_level() {
     assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
     // child is the inner per-series Rate aggregate.
     assert!(matches!(
-        child.as_ref(),
-        QueryExpr::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate])
+        child.expect_non_asap(),
+        NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate])
     ));
 }
 
@@ -461,26 +435,29 @@ fn sum_by_of_over_time_groups_outer_level() {
     // preserving, so the key resolves positionally just like the rate case (no
     // name-based Partition). Leaf = [ts, value, instance] → by = [2].
     let qe = ok("sum by(instance) (avg_over_time(node_cpu_seconds_total[5m]))");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate grouped by instance, got {qe:?}");
     };
     assert_eq!(reduction, &Reduction::by(vec![2]));
     assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
     // child is the inner per-series reduction: Aggregate{Avg} over TimeRange.
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected Aggregate (per-series avg_over_time) under the Sum, got {child:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Avg { .. }]));
-    assert!(matches!(child.as_ref(), QueryExpr::TimeRange { .. }));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
 }
 
 // ─────────────────────────────────────────────────────────────────────────────
@@ -501,7 +478,7 @@ fn over_time_functions_reduce_over_time_range() {
     ] {
         let qe = ok(q);
         assert!(
-            matches!(&qe, QueryExpr::Aggregate { .. }),
+            matches!(qe.expect_non_asap(), NonASAPOp::Aggregate { .. }),
             "{q}: expected Aggregate"
         );
         let matched = intents(&qe).iter().any(|i| match want {
@@ -519,7 +496,7 @@ fn over_time_functions_reduce_over_time_range() {
 #[test]
 fn quantile_over_time_is_aggregate_over_time_range() {
     let qe = ok("quantile_over_time(0.9, request_latency_seconds[5m])");
-    assert!(matches!(&qe, QueryExpr::Aggregate { .. }));
+    assert!(matches!(qe.expect_non_asap(), NonASAPOp::Aggregate { .. }));
     assert!(has(
         &qe,
         |i| matches!(i, AggIntent::Quantile { q, .. } if (*q - 0.9).abs() < 1e-9)
@@ -536,7 +513,7 @@ fn histogram_quantile_over_rate() {
     // φ-quantile from bucket rates. The `_bucket` metric marks the classic
     // cumulative-bucket form → `HistogramQuantile` (even without `sum by (le)`).
     let qe = ok("histogram_quantile(0.9, rate(demo_api_request_duration_seconds_bucket[5m]))");
-    let QueryExpr::Aggregate { measures, .. } = &qe else {
+    let NonASAPOp::Aggregate { measures, .. } = qe.expect_non_asap() else {
         panic!("expected Aggregate{{HistogramQuantile}}, got {qe:?}");
     };
     assert!(
@@ -553,9 +530,9 @@ fn histogram_quantile_over_sum_by_le_preserves_le_grouping() {
     let qe = ok(
         "histogram_quantile(0.99, sum by(le) (rate(demo_api_request_duration_seconds_bucket[5m])))",
     );
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate{{HistogramQuantile}}, got {qe:?}");
     };
@@ -566,11 +543,11 @@ fn histogram_quantile_over_sum_by_le_preserves_le_grouping() {
     ));
     // `sum by(le)` now survives as a positional Aggregate (by = [2], `le`), over
     // the inner Rate — no name-based Partition.
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected `sum by(le)` as a positional Aggregate, got {child:?}");
     };
@@ -586,7 +563,11 @@ fn histogram_quantile_over_sum_by_le_preserves_le_grouping() {
 #[test]
 fn vector_arithmetic() {
     let qe = ok("node_memory_MemFree_bytes + node_memory_Cached_bytes");
-    let QueryExpr::BinaryOp { op, .. } = &qe else {
+    let NonASAPOp::BinaryOp {
+        operator: BinaryOperator { kind: op, .. },
+        ..
+    } = qe.expect_non_asap()
+    else {
         panic!("expected BinaryOp, got {qe:?}");
     };
     assert_eq!(*op, BinaryOpKind::Arithmetic(ArithmeticOpKind::Add));
@@ -597,14 +578,17 @@ fn on_matching_with_group_left() {
     // SEMANTICS: many-to-one matching on a label subset.
     let qe =
         ok("rate(demo_cpu_usage_seconds_total[1m]) / on(instance, job) group_left demo_num_cpus");
-    let QueryExpr::BinaryOp {
-        op, vector_match, ..
-    } = &qe
-    else {
+    let NonASAPOp::BinaryOp { operator, .. } = qe.expect_non_asap() else {
         panic!("expected BinaryOp, got {qe:?}");
     };
-    assert_eq!(*op, BinaryOpKind::Arithmetic(ArithmeticOpKind::Div));
-    let vm = vector_match.as_ref().expect("on(...) group_left present");
+    assert_eq!(
+        operator.kind,
+        BinaryOpKind::Arithmetic(ArithmeticOpKind::Div)
+    );
+    let vm = operator
+        .vector_match
+        .as_ref()
+        .expect("on(...) group_left present");
     assert_eq!(vm.labels, vec!["instance".to_string(), "job".to_string()]);
     assert!(
         vm.grouping.is_some(),
@@ -617,15 +601,51 @@ fn vector_comparison_filters() {
     // SEMANTICS: `>` between two vectors keeps the LHS series where it holds.
     let qe = ok("go_goroutines > go_threads");
     assert!(
-        matches!(&qe, QueryExpr::BinaryOp { op, .. } if *op == BinaryOpKind::Compare(CompareOpKind::Gt))
+        matches!(qe.expect_non_asap(), NonASAPOp::BinaryOp { operator: BinaryOperator { kind: op, .. }, .. } if *op == BinaryOpKind::Compare(CompareOpKind::Gt))
     );
 }
 
+#[test]
+fn comparison_bool_modifier_returns_zero_or_one() {
+    // SEMANTICS (operators.test): `bool` turns a filtering comparison into a
+    // 0/1-valued one. On a vector operand it is `return_bool` on the
+    // `BinaryOp`; between two scalars it is a `Case(Compare → 1, else 0)`
+    // scalar expression under PromQL numeric rules — and a scalar comparison
+    // without `bool` is not a PromQL expression at all.
+    let bool_flag = |q: &str| match ok(q).expect_non_asap() {
+        NonASAPOp::BinaryOp { return_bool, .. } => *return_bool,
+        NonASAPOp::Project { .. } => true,
+        NonASAPOp::Filter { .. } => false,
+        other => panic!("expected BinaryOp for {q}, got {other:?}"),
+    };
+    assert!(bool_flag("go_goroutines > bool go_threads"));
+    assert!(bool_flag("go_goroutines > bool 0"));
+    assert!(!bool_flag("go_goroutines > go_threads"));
+    assert!(!bool_flag("go_goroutines > 0"));
+
+    let qe = support::scalar_root("1 < bool 2");
+    let ScalarExpr::Case { branches, .. } = &qe else {
+        panic!("expected a scalar Case, got {qe:?}");
+    };
+    assert!(matches!(
+        branches.as_slice(),
+        [(
+            ScalarExpr::Compare {
+                op: CompareOpKind::Lt,
+                semantics: ExprSemantics::Promql,
+                ..
+            },
+            _
+        )]
+    ));
+    rejected("1 < 2");
+}
+
 #[test]
 fn unary_negation_lowers_as_multiply_by_minus_one() {
     // SEMANTICS (PromQL, issue #36): `-expr` flips the sign of every sample.
     // Now that a scalar operand exists (#35), it lowers as `expr * -1` — a `Mul`
-    // BinaryOp of the (label-preserving) vector against `PromqlScalarBridge(-1)`. These are
+    // BinaryOp of the (label-preserving) vector against `ScalarExpr(-1)`. These are
     // the five cases the old `__GAP` test pinned as rejected.
     for q in [
         "-rate(http_errors_total[5m])",
@@ -635,93 +655,38 @@ fn unary_negation_lowers_as_multiply_by_minus_one() {
         "sum(-node_cpu_seconds_total)",
     ] {
         let qe = ok(q);
-        // A `Mul`-by-`-1` against a `PromqlScalarBridge(-1)` appears somewhere in every DAG.
+        // A `Mul`-by-`-1` against a `ScalarExpr(-1)` appears somewhere in every tree.
         assert!(
             negates_via_scalar(&qe),
             "no `* -1` negation found in {q}: {qe:?}"
         );
     }
 
-    // `-some_metric` at the root: `Scan * PromqlScalarBridge(-1)`, schema follows the vector.
-    let QueryExpr::BinaryOp {
-        op,
-        lhs,
-        rhs,
-        vector_match,
-    } = &ok("-some_metric")
-    else {
-        panic!("expected a BinaryOp for `-some_metric`");
-    };
-    assert_eq!(*op, BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul));
-    assert!(
-        matches!(lhs.as_ref(), QueryExpr::TimeRange { child, .. } if matches!(child.as_ref(), QueryExpr::Scan { .. })),
-        "vector on the left"
-    );
-    assert!(
-        rhs.as_promql_scalar()
-            .is_some_and(|v| (v + 1.0).abs() < 1e-12),
-        "negation multiplies by PromqlScalarBridge(-1), got {rhs:?}"
-    );
-    assert!(
-        vector_match.is_none(),
-        "scalar negation carries no vector match"
-    );
-    // Label-preserving: the schema is the vector operand's, unchanged.
-    let schema = ok("-some_metric").output_schema().unwrap();
-    assert_eq!(
-        schema
-            .fields
-            .iter()
-            .map(|c| c.name.as_str())
-            .collect::<Vec<_>>(),
-        vec!["ts", "value"],
-    );
-
-    // `sum(-m)` — the negation lowers inside the aggregate argument (issue #27
-    // nesting), so the outer node is the `Sum` aggregate over the `Mul`.
-    let QueryExpr::Aggregate {
-        measures, child, ..
-    } = &ok("sum(-node_cpu_seconds_total)")
-    else {
-        panic!("expected an outer Aggregate for `sum(-m)`");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    assert!(matches!(
-        child.as_ref(),
-        QueryExpr::BinaryOp {
-            op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul),
-            ..
-        }
-    ));
+    let negated = ok("-some_metric");
+    assert!(negates_via_scalar(&negated));
+    assert!(negated.schema.has_promql_series_identity());
+    assert!(negated.schema.time_index.is_some());
+    let summed = ok("sum(-node_cpu_seconds_total)");
+    assert!(has(&summed, |i| matches!(i, AggIntent::Sum { .. })));
+    assert!(negates_via_scalar(&summed));
 }
 
 #[test]
 fn unary_negation_of_constant_folds_to_scalar() {
     // `-(10*1024*1024)` — the operand is constant-foldable, so negation collapses
-    // to a single negated `PromqlScalarBridge` leaf (no `BinaryOp`), just like a bare literal.
-    assert!(ok("-(10*1024*1024)")
-        .as_promql_scalar()
+    // to a single negated `ScalarExpr` leaf (no `BinaryOp`), just like a bare literal.
+    assert!(promql_scalar(&support::scalar_root("-(10*1024*1024)"))
         .is_some_and(|v| (v + 10_485_760.0).abs() < 1e-6));
 }
 
 #[test]
 fn double_unary_negation_nests() {
-    // `- -some_metric` — negation of a negation: `(m * -1) * -1`. Both levels
-    // lower; the value is unchanged but the structure is faithfully nested.
-    let QueryExpr::BinaryOp { op, lhs, .. } = &ok("- -some_metric") else {
-        panic!("expected outer BinaryOp for `- -some_metric`");
+    let qe = ok("- -some_metric");
+    let NonASAPOp::Project { child, .. } = qe.expect_non_asap() else {
+        panic!()
     };
-    assert_eq!(*op, BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul));
-    assert!(
-        matches!(
-            lhs.as_ref(),
-            QueryExpr::BinaryOp {
-                op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul),
-                ..
-            }
-        ),
-        "inner negation nests under the outer one"
-    );
+    assert!(matches!(child.expect_non_asap(), NonASAPOp::Project { .. }));
+    assert!(negates_via_scalar(child));
 }
 
 #[test]
@@ -754,39 +719,22 @@ fn count_maps_to_count_and_inherits_accuracy() {
 
 #[test]
 fn scalar_literal_operand_lowers_as_binaryop_scalar() {
-    // Issue #35: `<vector> op <scalar>` — the numeric threshold is a
-    // `PromqlScalarBridge` operand of the `BinaryOp`, and constant arithmetic
-    // (`10*1024*1024`) is folded. The output schema is the vector side's.
     let qe = ok("node_filesystem_avail_bytes > 10*1024*1024");
-    let QueryExpr::BinaryOp { op, lhs, rhs, .. } = &qe else {
-        panic!("expected a BinaryOp, got {qe:?}");
+    let ScalarExpr::Compare { op, right, .. } = support::sample_expression(&qe) else {
+        panic!()
     };
-    assert_eq!(*op, BinaryOpKind::Compare(CompareOpKind::Gt));
-    assert!(
-        matches!(lhs.as_ref(), QueryExpr::TimeRange { child, .. } if matches!(child.as_ref(), QueryExpr::Scan { .. })),
-        "vector on the left"
-    );
-    assert!(
-        rhs.as_promql_scalar()
-            .is_some_and(|v| (v - 10_485_760.0).abs() < 1e-6),
-        "folded scalar threshold on the right, got {rhs:?}"
-    );
-    // Schema derivation follows the vector side (a scalar contributes no labels).
-    assert!(qe.output_schema().is_ok());
+    assert_eq!(*op, CompareOpKind::Gt);
+    assert_eq!(promql_scalar(right), Some(10_485_760.0));
 }
 
 #[test]
 fn scalar_arithmetic_scales_the_vector() {
-    // `rate(m[5m]) * 100` — a unit conversion. Arithmetic BinaryOp of the vector
-    // with a `PromqlScalarBridge(100)`.
     let qe = ok("rate(m[5m]) * 100");
-    let QueryExpr::BinaryOp { op, rhs, .. } = &qe else {
-        panic!("expected a BinaryOp, got {qe:?}");
+    let ScalarExpr::Arithmetic { op, right, .. } = support::sample_expression(&qe) else {
+        panic!()
     };
-    assert_eq!(*op, BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul));
-    assert!(rhs
-        .as_promql_scalar()
-        .is_some_and(|v| (v - 100.0).abs() < 1e-9));
+    assert_eq!(*op, ArithmeticOpKind::Mul);
+    assert_eq!(promql_scalar(right), Some(100.0));
 }
 
 // ─────────────────────────────────────────────────────────────────────────────
@@ -797,12 +745,22 @@ fn scalar_arithmetic_scales_the_vector() {
 #[test]
 fn set_ops_lower_to_binaryop() {
     // SEMANTICS: or = union of label sets; and = intersection; unless = difference.
-    assert!(matches!(&ok("up{job=\"a\"} or up{job=\"b\"}"),
-        QueryExpr::BinaryOp { op, .. } if *op == BinaryOpKind::Set(PromQLVectorSetOpKind::Or)));
-    assert!(matches!(&ok("node_network_mtu_bytes and node_up"),
-        QueryExpr::BinaryOp { op, .. } if *op == BinaryOpKind::Set(PromQLVectorSetOpKind::And)));
-    assert!(matches!(&ok("node_network_mtu_bytes unless node_down"),
-        QueryExpr::BinaryOp { op, .. } if *op == BinaryOpKind::Set(PromQLVectorSetOpKind::Unless)));
+    let set_op = |q: &str| match ok(q).expect_non_asap() {
+        NonASAPOp::BinaryOp { operator, .. } => operator.kind.clone(),
+        other => panic!("expected BinaryOp for {q}, got {other:?}"),
+    };
+    assert_eq!(
+        set_op("up{job=\"a\"} or up{job=\"b\"}"),
+        BinaryOpKind::Set(PromQLVectorSetOpKind::Or)
+    );
+    assert_eq!(
+        set_op("node_network_mtu_bytes and node_up"),
+        BinaryOpKind::Set(PromQLVectorSetOpKind::And)
+    );
+    assert_eq!(
+        set_op("node_network_mtu_bytes unless node_down"),
+        BinaryOpKind::Set(PromQLVectorSetOpKind::Unless)
+    );
 }
 
 // ─────────────────────────────────────────────────────────────────────────────
@@ -824,7 +782,7 @@ fn topk_over_count_is_heavy_hitter() {
 fn bottomk_is_generic_sort_limit() {
     // SEMANTICS: bottom-k → generic ascending order + limit (no sketch).
     let qe = ok("bottomk(3, count_over_time(http_requests_total[5m]))");
-    assert!(matches!(&qe, QueryExpr::Limit { .. }));
+    assert!(matches!(qe.expect_non_asap(), NonASAPOp::Limit { .. }));
 }
 
 #[test]
@@ -833,9 +791,9 @@ fn topk_over_nested_sum_preserves_weighted_topk_accuracy() {
     // The final rates are query-time values. Their ordering does not establish
     // frequency-sketch membership semantics.
     let qe = ok("topk(3, sum by(instance) (rate(node_cpu_seconds_total[5m])))");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected weighted TopK aggregate, got {qe:?}");
     };
@@ -861,18 +819,18 @@ fn outer_aggregate_over_nested_aggregate_nests() {
     // flat two-level template rejected. Each level survives into the
     // canonical DAG (issue #27).
     let qe = ok("max(sum by (job) (rate(http_requests_total[5m])))");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate, got {qe:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Max { .. }]));
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected inner `sum by (job)` Aggregate, got {child:?}");
     };
@@ -895,12 +853,12 @@ fn outer_group_key_absent_from_nested_aggregate_is_dropped() {
     // the query lowers with the provably-absent key dropped, exactly
     // `sum(sum by (group)(…))`.
     let qe = ok(r#"sum(sum by (group)(http_requests{job="api-server"})) by (job)"#);
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate, got {qe:?}");
     };
@@ -910,7 +868,7 @@ fn outer_group_key_absent_from_nested_aggregate_is_dropped() {
         "absent `job` key dropped → global aggregate"
     );
     assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    let QueryExpr::Aggregate { reduction, .. } = child.as_ref() else {
+    let NonASAPOp::Aggregate { reduction, .. } = child.expect_non_asap() else {
         panic!("expected inner `sum by (group)` Aggregate, got {child:?}");
     };
     assert_eq!(
@@ -927,16 +885,16 @@ fn outer_group_key_present_after_inner_aggregate_still_resolves() {
     // resolving positionally — the absent-key drop only fires on provable
     // absence, never on a resolvable key.
     let qe = ok("sum(sum by (job, group)(http_requests)) by (job)");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate, got {qe:?}");
     };
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction: inner_reduction,
         ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected inner Aggregate, got {child:?}");
     };
@@ -957,9 +915,9 @@ fn outer_group_key_over_binary_op_resolves_on_both_sides() {
     // still resolve. Each `or` side is bound independently against its own
     // sub-DAG, so the key is seeded as an inherited column on both sides.
     let qe = ok(r#"sum by (__name__)(metric_a{env="1"} or metric_b{env="2"})"#);
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate, got {qe:?}");
     };
@@ -969,12 +927,12 @@ fn outer_group_key_over_binary_op_resolves_on_both_sides() {
         1,
         "grouped by the one `__name__` key"
     );
-    let QueryExpr::BinaryOp { lhs, rhs, .. } = child.as_ref() else {
+    let NonASAPOp::BinaryOp { lhs, rhs, .. } = child.expect_non_asap() else {
         panic!("expected a BinaryOp child, got {child:?}");
     };
     // Both independently-bound sides carry `__name__` at the same position, so
     // the outer group key is consistent across the union.
-    let (ls, rs) = (lhs.output_schema().unwrap(), rhs.output_schema().unwrap());
+    let (ls, rs) = (lhs.schema.clone(), rhs.schema.clone());
     assert_eq!(ls.column_id("__name__"), rs.column_id("__name__"));
     assert_eq!(
         ls.column_id("__name__"),
@@ -983,8 +941,8 @@ fn outer_group_key_over_binary_op_resolves_on_both_sides() {
 
     // The general case (a plain label, not just `__name__`) also lowers.
     assert!(matches!(
-        ok("sum by (job)(metric_a or metric_b)"),
-        QueryExpr::Aggregate { .. }
+        ok("sum by (job)(metric_a or metric_b)").expect_non_asap(),
+        NonASAPOp::Aggregate { .. }
     ));
 }
 
@@ -994,15 +952,15 @@ fn aggregate_over_binary_op_nests() {
     // op over two range vectors. The old template only accepted a single inner
     // selector/call; now the binary op lowers and the outer sum wraps it.
     let qe = ok("sum(rate(a[5m]) + rate(b[5m]))");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate, got {qe:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
     assert!(
-        matches!(child.as_ref(), QueryExpr::BinaryOp { .. }),
+        matches!(child.expect_non_asap(), NonASAPOp::BinaryOp { .. }),
         "argument lowers as a BinaryOp, got {child:?}"
     );
 }
@@ -1015,7 +973,10 @@ fn aggregate_over_binary_op_nests() {
 fn subquery_wraps_inner_query() {
     // SEMANTICS: `<inst>[range:res]` evaluates the inner query across a range.
     let qe = ok("rate(demo_api_request_duration_seconds_count[5m])[1h:]");
-    assert!(matches!(&qe, QueryExpr::PromqlSubquery { .. }));
+    assert!(matches!(
+        qe.expect_non_asap(),
+        NonASAPOp::PromqlSubquery { .. }
+    ));
     assert!(has(&qe, |i| matches!(i, AggIntent::Rate)));
 }
 
@@ -1026,12 +987,12 @@ fn over_time_of_subquery_reduces_per_series() {
     // then `max_over_time` takes the max of those samples *per series*. It lowers
     // to a per-series `Max` reduction over a `PromqlSubquery` (issue #27).
     let qe = ok("max_over_time(rate(demo_api_request_duration_seconds_count[5m])[1h:])");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected an Aggregate at the root, got {qe:?}");
     };
@@ -1044,7 +1005,7 @@ fn over_time_of_subquery_reduces_per_series() {
     // The reduction rides directly on the sub-query (the structural range marker
     // that keeps it label-preserving), which wraps the inner `rate`.
     assert!(
-        matches!(child.as_ref(), QueryExpr::PromqlSubquery { .. }),
+        matches!(child.expect_non_asap(), NonASAPOp::PromqlSubquery { .. }),
         "the `Max` reduces over a PromqlSubquery, got {child:?}"
     );
     assert!(intents(&qe).iter().any(|i| matches!(i, AggIntent::Rate)));
@@ -1055,16 +1016,19 @@ fn quantile_over_time_of_subquery_carries_phi() {
     // The `quantile_over_time` φ parameter is read from arg 0; the sub-query is
     // arg 1. It lowers to a per-series `Quantile(φ)` over the `PromqlSubquery`.
     let qe = ok("quantile_over_time(0.9, rate(demo[5m])[1h:])");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected an Aggregate, got {qe:?}");
     };
     assert!(
         matches!(measures.as_slice(), [AggIntent::Quantile { q, .. }] if (*q - 0.9).abs() < 1e-9)
     );
-    assert!(matches!(child.as_ref(), QueryExpr::PromqlSubquery { .. }));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::PromqlSubquery { .. }
+    ));
 }
 
 #[test]
@@ -1074,12 +1038,12 @@ fn aggregation_over_over_time_of_subquery_keeps_labels() {
     // survives for the OUTER cross-series `sum by (job)` to group on. If the
     // inner `Max` collapsed labels, `job` would not resolve here.
     let qe = ok("sum by (job) (max_over_time(rate(demo{job=\"api\"}[5m])[1h:]))");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate, got {qe:?}");
     };
@@ -1089,20 +1053,20 @@ fn aggregation_over_over_time_of_subquery_keeps_labels() {
     );
     assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
     // Inner node is the per-series `max_over_time` reduction over the subquery.
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction: inner_reduction,
         measures: inner_measures,
         child: inner_child,
         ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected inner Aggregate, got {child:?}");
     };
     assert_eq!(inner_reduction, &Reduction::PerEntity);
     assert!(matches!(inner_measures.as_slice(), [AggIntent::Max { .. }]));
     assert!(matches!(
-        inner_child.as_ref(),
-        QueryExpr::PromqlSubquery { .. }
+        inner_child.expect_non_asap(),
+        NonASAPOp::PromqlSubquery { .. }
     ));
 }
 
@@ -1124,66 +1088,66 @@ fn nested_subquery_from_prometheus_docs() {
     // the label-preserving `[ts, value]`.
     let qe = ok("max_over_time(deriv(rate(distance_covered_total[5s])[30s:5s])[10m:])");
 
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected `max_over_time` Aggregate at the root, got {qe:?}");
     };
     assert_eq!(reduction, &Reduction::PerEntity);
     assert!(matches!(measures.as_slice(), [AggIntent::Max { .. }]));
 
-    let QueryExpr::PromqlSubquery {
+    let NonASAPOp::PromqlSubquery {
         range,
         resolution,
         child,
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected the outer `[10m:]` PromqlSubquery, got {child:?}");
     };
     assert_eq!(*range, Duration::from_secs(600));
     assert_eq!(*resolution, None, "`[10m:]` keeps the default resolution");
 
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected the `deriv` Aggregate, got {child:?}");
     };
     assert_eq!(reduction, &Reduction::PerEntity);
     assert!(matches!(measures.as_slice(), [AggIntent::Deriv]));
 
-    let QueryExpr::PromqlSubquery {
+    let NonASAPOp::PromqlSubquery {
         range,
         resolution,
         child,
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected the inner `[30s:5s]` PromqlSubquery, got {child:?}");
     };
     assert_eq!(*range, Duration::from_secs(30));
     assert_eq!(*resolution, Some(Duration::from_secs(5)));
 
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected the `rate` Aggregate, got {child:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
-    let QueryExpr::TimeRange { range, .. } = child.as_ref() else {
+    let NonASAPOp::TimeRange { range, .. } = child.expect_non_asap() else {
         panic!("expected the `[5s]` TimeRange under rate, got {child:?}");
     };
     assert_eq!(*range, Duration::from_secs(5));
 
     // Per-series end to end: the schema keeps the (ts, value) floor and stays open.
-    let schema = qe.output_schema().expect("schema derivation");
+    let schema = qe.schema.clone();
     assert_eq!(
         schema
             .fields
@@ -1205,21 +1169,22 @@ fn offset_modifier_lowers_to_a_time_shift() {
     // past — a `TimeShift` wrapper over the selector (signed ms; a negative
     // offset shifts forward). Schema is unchanged (the shift only moves *when*).
     let qe = ok("http_requests_total offset 5m");
-    let QueryExpr::TimeRange { child, .. } = &qe else {
+    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
         panic!("expected an ingestion TimeRange, got {qe:?}");
     };
-    let QueryExpr::TimeShift { shift, child } = child.as_ref() else {
+    let NonASAPOp::TimeShift { shift, child } = child.expect_non_asap() else {
         panic!("expected a TimeShift, got {qe:?}");
     };
     assert_eq!(shift.offset_ms, 300_000);
     assert!(shift.at.is_none());
-    assert!(matches!(child.as_ref(), QueryExpr::Scan { .. }));
+    assert!(matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }));
 
     // `offset -5m` shifts forward → negative ms.
-    let QueryExpr::TimeRange { child, .. } = &ok("http_requests_total offset -5m") else {
+    let qe = ok("http_requests_total offset -5m");
+    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
         panic!("expected an ingestion TimeRange");
     };
-    let QueryExpr::TimeShift { shift, .. } = child.as_ref() else {
+    let NonASAPOp::TimeShift { shift, .. } = child.expect_non_asap() else {
         panic!("expected a TimeShift");
     };
     assert_eq!(shift.offset_ms, -300_000);
@@ -1230,29 +1195,31 @@ fn at_modifier_lowers_to_a_time_shift() {
     // SEMANTICS (PromQL, issue #40): `@ <ts>` pins the evaluation to an absolute
     // instant (PromQL seconds → IR milliseconds); `@ start()` / `@ end()` anchor
     // to the query range bounds.
-    let QueryExpr::TimeRange { child, .. } = &ok("http_requests_total @ 1609746000") else {
+    let qe = ok("http_requests_total @ 1609746000");
+    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
         panic!("expected an ingestion TimeRange");
     };
-    let QueryExpr::TimeShift { shift, .. } = child.as_ref() else {
+    let NonASAPOp::TimeShift { shift, .. } = child.expect_non_asap() else {
         panic!("expected a TimeShift for `@ <ts>`");
     };
     assert_eq!(shift.at, Some(AtModifier::Timestamp(1_609_746_000_000)));
     assert_eq!(shift.offset_ms, 0);
 
-    let QueryExpr::TimeRange { child, .. } = &ok("http_requests_total @ start()") else {
+    let qe = ok("http_requests_total @ start()");
+    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
         panic!("expected an ingestion TimeRange");
     };
-    let QueryExpr::TimeShift { shift, .. } = child.as_ref() else {
+    let NonASAPOp::TimeShift { shift, .. } = child.expect_non_asap() else {
         panic!("expected a TimeShift for `@ start()`");
     };
     assert_eq!(shift.at, Some(AtModifier::Start));
 
     // Offset and `@` compose: `@ end() offset 5m` carries both.
     let qe = ok("http_requests_total @ end() offset 5m");
-    let QueryExpr::TimeRange { child, .. } = &qe else {
+    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
         panic!("expected an ingestion TimeRange, got {qe:?}");
     };
-    let QueryExpr::TimeShift { shift, .. } = child.as_ref() else {
+    let NonASAPOp::TimeShift { shift, .. } = child.expect_non_asap() else {
         panic!("expected a TimeShift, got {qe:?}");
     };
     assert_eq!(shift.at, Some(AtModifier::End));
@@ -1265,21 +1232,21 @@ fn offset_on_a_ranged_selector_wraps_inside_the_time_range() {
     // `TimeShift` sits *under* the `TimeRange` (the 5m window is taken at the
     // shifted time), and the whole thing under the per-series `Rate` (#40).
     let qe = ok("rate(http_requests_total[5m] offset 1h)");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected the rate Aggregate, got {qe:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
-    let QueryExpr::TimeRange { child, .. } = child.as_ref() else {
+    let NonASAPOp::TimeRange { child, .. } = child.expect_non_asap() else {
         panic!("expected a TimeRange under rate, got {child:?}");
     };
-    let QueryExpr::TimeShift { shift, child } = child.as_ref() else {
+    let NonASAPOp::TimeShift { shift, child } = child.expect_non_asap() else {
         panic!("expected a TimeShift under the TimeRange, got {child:?}");
     };
     assert_eq!(shift.offset_ms, 3_600_000);
-    assert!(matches!(child.as_ref(), QueryExpr::Scan { .. }));
+    assert!(matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }));
 }
 
 // ─────────────────────────────────────────────────────────────────────────────
@@ -1313,7 +1280,7 @@ fn count_over_time_value_column_is_float64() {
     // #69: a per-series range reduction produces a PromQL sample value, which is
     // always float64. `count_over_time`'s `Count` intent types `Int64`, but the
     // derived `value` column must be `Float64` like every other range reducer.
-    let schema = ok("count_over_time(m[5m])").output_schema().unwrap();
+    let schema = ok("count_over_time(m[5m])").schema.clone();
     let value = schema
         .fields
         .iter()
@@ -1335,12 +1302,12 @@ fn counter_derivative_functions_lower_to_distinct_intents() {
         ("resets(m[1h])", AggIntent::Resets),
     ] {
         let qe = ok(q);
-        let QueryExpr::Aggregate {
+        let NonASAPOp::Aggregate {
             reduction,
             measures,
             child,
             ..
-        } = &qe
+        } = qe.expect_non_asap()
         else {
             panic!("expected an Aggregate for {q:?}, got {qe:?}");
         };
@@ -1355,7 +1322,7 @@ fn counter_derivative_functions_lower_to_distinct_intents() {
             "{q}: wrong intent"
         );
         assert!(
-            matches!(child.as_ref(), QueryExpr::TimeRange { .. }),
+            matches!(child.expect_non_asap(), NonASAPOp::TimeRange { .. }),
             "{q}: reduction rides on a TimeRange, got {child:?}"
         );
     }
@@ -1366,9 +1333,9 @@ fn predict_linear_carries_horizon_seconds() {
     // `predict_linear(v[w], t)` — the 2nd (scalar) arg is the prediction horizon
     // in seconds; it must be carried in the intent (it changes the result).
     let qe = ok("predict_linear(node_filesystem_avail_bytes[3h], 86400)");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected an Aggregate, got {qe:?}");
     };
@@ -1376,7 +1343,10 @@ fn predict_linear_carries_horizon_seconds() {
         measures.as_slice(),
         &[AggIntent::PredictLinear { seconds: 86400.0 }]
     );
-    assert!(matches!(child.as_ref(), QueryExpr::TimeRange { .. }));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
 }
 
 #[test]
@@ -1394,12 +1364,12 @@ fn aggregation_over_counter_derivative_keeps_labels() {
     // A counter-derivative is per-series (label-preserving), so an outer
     // `sum by (job)` can group on a label the inner `changes` preserved.
     let qe = ok(r#"sum by (job) (changes(m{job="api"}[15m]))"#);
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate, got {qe:?}");
     };
@@ -1420,12 +1390,12 @@ fn outer_stat_over_counter_derivative_nests_two_levels() {
     // grouped outer (`avg by (dc)`) must resolve its key against the labels the
     // inner reduction preserved, threading any scalar param (predict horizon).
     let qe = ok("avg by (dc) (predict_linear(m[3h], 3600))");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate, got {qe:?}");
     };
@@ -1434,11 +1404,11 @@ fn outer_stat_over_counter_derivative_nests_two_levels() {
         "outer `avg by (dc)` groups on a label"
     );
     assert!(matches!(measures.as_slice(), [AggIntent::Avg { .. }]));
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction: inner_reduction,
         measures: inner_measures,
         ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected inner per-series Aggregate, got {child:?}");
     };
@@ -1458,11 +1428,14 @@ fn topk_over_counter_derivative_is_generic_sort_limit() {
     // `topk(k, deriv(...))` ranks the per-series derivative values — a generic
     // `Sort + Limit`, NOT a heavy-hitter `TopK` (that's only `count_over_time`).
     let qe = ok("topk(3, deriv(m[5m]))");
-    let QueryExpr::Limit { n, child, .. } = &qe else {
+    let NonASAPOp::Limit {
+        n: Some(n), child, ..
+    } = qe.expect_non_asap()
+    else {
         panic!("expected Limit, got {qe:?}");
     };
     assert_eq!(*n, 3);
-    assert!(matches!(child.as_ref(), QueryExpr::Sort { .. }));
+    assert!(matches!(child.expect_non_asap(), NonASAPOp::Sort { .. }));
     assert!(intents(&qe).iter().any(|i| matches!(i, AggIntent::Deriv)));
     assert!(
         !intents(&qe)
@@ -1477,28 +1450,37 @@ fn counter_derivative_composes_in_binary_ops() {
     // As a vector operand: `delta(a[5m]) / delta(b[5m])` is a BinaryOp of two
     // per-series Delta reductions.
     let ratio = ok("delta(a[5m]) / delta(b[5m])");
-    let QueryExpr::BinaryOp { op, lhs, rhs, .. } = &ratio else {
+    let NonASAPOp::BinaryOp {
+        operator: BinaryOperator { kind: op, .. },
+        lhs,
+        rhs,
+        ..
+    } = ratio.expect_non_asap()
+    else {
         panic!("expected BinaryOp, got {ratio:?}");
     };
     assert_eq!(*op, BinaryOpKind::Arithmetic(ArithmeticOpKind::Div));
     assert!(
-        matches!(lhs.as_ref(), QueryExpr::Aggregate { measures, .. } if measures.as_slice() == [AggIntent::Delta])
+        matches!(lhs.expect_non_asap(), NonASAPOp::Aggregate { measures, .. } if measures.as_slice() == [AggIntent::Delta])
     );
     assert!(
-        matches!(rhs.as_ref(), QueryExpr::Aggregate { measures, .. } if measures.as_slice() == [AggIntent::Delta])
+        matches!(rhs.expect_non_asap(), NonASAPOp::Aggregate { measures, .. } if measures.as_slice() == [AggIntent::Delta])
     );
 
     // Under an aggregate over a binary op mixing a counter-derivative with
     // another per-series function: `sum(rate(m[5m]) + changes(m[5m]))`.
     let mixed = ok("sum(rate(m[5m]) + changes(m[5m]))");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &mixed
+    } = mixed.expect_non_asap()
     else {
         panic!("expected Aggregate, got {mixed:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    assert!(matches!(child.as_ref(), QueryExpr::BinaryOp { .. }));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::BinaryOp { .. }
+    ));
     assert!(intents(&mixed).iter().any(|i| matches!(i, AggIntent::Rate)));
     assert!(intents(&mixed)
         .iter()
@@ -1522,12 +1504,12 @@ fn range_functions_over_a_subquery_reduce_per_series() {
         ("resets(sum(m)[5m:])", AggIntent::Resets),
     ] {
         let qe = ok(q);
-        let QueryExpr::Aggregate {
+        let NonASAPOp::Aggregate {
             reduction,
             measures,
             child,
             ..
-        } = &qe
+        } = qe.expect_non_asap()
         else {
             panic!("{q}: expected an Aggregate, got {qe:?}");
         };
@@ -1542,7 +1524,7 @@ fn range_functions_over_a_subquery_reduce_per_series() {
             "{q}: wrong intent"
         );
         assert!(
-            matches!(child.as_ref(), QueryExpr::PromqlSubquery { .. }),
+            matches!(child.expect_non_asap(), NonASAPOp::PromqlSubquery { .. }),
             "{q}: reduces directly over the PromqlSubquery (no TimeRange), got {child:?}"
         );
     }
@@ -1570,8 +1552,8 @@ fn predict_linear_and_double_exp_over_a_subquery_carry_params() {
 #[test]
 fn histogram_quantile_classic_bucket_vs_native() {
     // Two lowerings of `histogram_quantile(φ, …)`: the classic cumulative-bucket
-    // form → exact `HistogramQuantile`; a native-histogram / raw-samples argument
-    // → the generic (sketch-able) `Quantile`. The classic form is recognised by
+    // form → exact `HistogramQuantile`; native samples require a new type.
+    // The classic form is recognised by
     // `by (le)`, a `_bucket` metric, or an `le` matcher (issue #43).
     for classic in [
         "histogram_quantile(0.9, sum by (le) (rate(x_bucket[5m])))",
@@ -1595,65 +1577,27 @@ fn histogram_quantile_classic_bucket_vs_native() {
         "histogram_quantile(0.9, my_native_histogram)",
         "histogram_quantile(0.9, request_duration_seconds)", // raw samples (your extension)
     ] {
-        let qe = ok(native);
-        assert!(
-            has(
-                &qe,
-                |i| matches!(i, AggIntent::Quantile { q, .. } if (*q - 0.9).abs() < 1e-9)
-            ),
-            "native/raw form → generic Quantile: {native}"
-        );
-        assert!(
-            !has(&qe, |i| matches!(i, AggIntent::HistogramQuantile { .. })),
-            "{native}"
-        );
+        rejected(native);
     }
 }
 
 #[test]
-fn histogram_accessors_lower_to_per_series_intents() {
-    // `histogram_<accessor>(v)` extracts a float per series from a native
-    // histogram — a per-series `Aggregate{[accessor]}` directly over the
-    // (instant) argument, no grouping. (`histogram_quantile` has its own two
-    // lowerings — see `histogram_quantile_classic_bucket_vs_native`.)
-    for (q, want) in [
-        ("histogram_count(v)", AggIntent::HistogramCount),
-        ("histogram_sum(v)", AggIntent::HistogramSum),
-        ("histogram_avg(v)", AggIntent::HistogramAvg),
-        ("histogram_stddev(v)", AggIntent::HistogramStdDev),
-        ("histogram_stdvar(v)", AggIntent::HistogramStdVar),
+fn native_histogram_accessors_are_explicit_gaps() {
+    // Native histogram samples have no typed representation yet.
+    for q in [
+        "histogram_count(v)",
+        "histogram_sum(v)",
+        "histogram_avg(v)",
+        "histogram_stddev(v)",
+        "histogram_stdvar(v)",
     ] {
-        let qe = ok(q);
-        let QueryExpr::Aggregate {
-            reduction,
-            measures,
-            ..
-        } = &qe
-        else {
-            panic!("{q}: expected an Aggregate, got {qe:?}");
-        };
-        assert_eq!(
-            reduction,
-            &Reduction::PerEntity,
-            "{q}: per-series, no grouping"
-        );
-        assert_eq!(
-            measures.as_slice(),
-            std::slice::from_ref(&want),
-            "{q}: wrong intent"
-        );
+        rejected(q);
     }
 }
 
 #[test]
-fn histogram_fraction_carries_its_bounds() {
-    // `histogram_fraction(lower, upper, v)` — bounds from args 0/1, vector arg 2.
-    let qe = ok("histogram_fraction(0, 0.2, v)");
-    assert!(intents(&qe).iter().any(|i| matches!(
-        i,
-        AggIntent::HistogramFraction { lower, upper }
-            if *lower == 0.0 && (*upper - 0.2).abs() < 1e-9
-    )));
+fn histogram_fraction_is_an_explicit_gap() {
+    rejected("histogram_fraction(0, 0.2, v)");
 }
 
 // ─────────────────────────────────────────────────────────────────────────────
@@ -1661,68 +1605,42 @@ fn histogram_fraction_carries_its_bounds() {
 // ─────────────────────────────────────────────────────────────────────────────
 
 #[test]
-fn math_functions_lower_to_per_series_math_intents() {
-    // Each `f(v)` is a per-series element-wise value transform — a per-series
-    // `Aggregate{[Math(f)]}` over the (instant) argument, no grouping.
-    for (q, want) in [
-        ("abs(v)", MathFunc::Abs),
-        ("ceil(v)", MathFunc::Ceil),
-        ("floor(v)", MathFunc::Floor),
-        ("sqrt(v)", MathFunc::Sqrt),
-        ("ln(v)", MathFunc::Ln),
-        ("log2(v)", MathFunc::Log2),
-        ("sgn(v)", MathFunc::Sgn),
-        ("sin(v)", MathFunc::Sin),
-        ("atanh(v)", MathFunc::Atanh),
-        ("deg(v)", MathFunc::Deg),
-        ("rad(v)", MathFunc::Rad),
+fn math_functions_lower_to_typed_scalar_projections() {
+    for name in [
+        "abs", "ceil", "floor", "sqrt", "ln", "log2", "sgn", "sin", "atanh", "deg", "rad",
     ] {
-        let qe = ok(q);
-        let QueryExpr::Aggregate {
-            reduction,
-            measures,
-            ..
-        } = &qe
-        else {
-            panic!("{q}: expected an Aggregate, got {qe:?}");
-        };
-        assert_eq!(
-            reduction,
-            &Reduction::PerEntity,
-            "{q}: per-series, no grouping"
-        );
+        let query = ok(&format!("{name}(v)"));
         assert!(
-            matches!(measures.as_slice(), [AggIntent::Math(m)] if *m == want),
-            "{q}: wrong intent, got {measures:?}"
+            matches!(support::sample_expression(&query),ScalarExpr::FunctionCall { name:n,args } if n==&format!("promql_{name}") && args.len()==1)
         );
+        query.validate_structure().unwrap();
     }
 }
 
 #[test]
 fn clamp_and_round_carry_their_params() {
-    assert!(intents(&ok("clamp(v, 0, 100)")).iter().any(
-        |i| matches!(i, AggIntent::Math(MathFunc::Clamp { min, max }) if *min == 0.0 && *max == 100.0)
-    ));
-    assert!(intents(&ok("clamp_min(v, 1)"))
-        .iter()
-        .any(|i| matches!(i, AggIntent::Math(MathFunc::ClampMin { min }) if *min == 1.0)));
-    assert!(intents(&ok("clamp_max(v, 5)"))
-        .iter()
-        .any(|i| matches!(i, AggIntent::Math(MathFunc::ClampMax { max }) if *max == 5.0)));
-    // `round(v)` defaults the step to 1; `round(v, 5)` reads it.
-    assert!(intents(&ok("round(v)")).iter().any(
-        |i| matches!(i, AggIntent::Math(MathFunc::Round { to_nearest }) if *to_nearest == 1.0)
-    ));
-    assert!(intents(&ok("round(v, 5)")).iter().any(
-        |i| matches!(i, AggIntent::Math(MathFunc::Round { to_nearest }) if *to_nearest == 5.0)
-    ));
+    for (query, params) in [
+        ("clamp(v,0,100)", vec![0.0, 100.0]),
+        ("clamp_min(v,1)", vec![1.0]),
+        ("clamp_max(v,5)", vec![5.0]),
+        ("round(v)", vec![1.0]),
+        ("round(v,5)", vec![5.0]),
+    ] {
+        let node = ok(query);
+        let ScalarExpr::FunctionCall { args, .. } = support::sample_expression(&node) else {
+            panic!()
+        };
+        assert_eq!(
+            args.iter().skip(1).map(promql_scalar).collect::<Vec<_>>(),
+            params.into_iter().map(Some).collect::<Vec<_>>()
+        );
+    }
 }
 
 #[test]
 fn pi_lowers_to_a_scalar_constant() {
-    // `pi()` is the constant π — a `PromqlScalarBridge` leaf, not a `Math` intent.
-    assert!(ok("pi()")
-        .as_promql_scalar()
+    // `pi()` is the constant π — a `ScalarExpr` leaf, not a `Math` intent.
+    assert!(promql_scalar(&support::scalar_root("pi()"))
         .is_some_and(|v| (v - std::f64::consts::PI).abs() < 1e-12));
 }
 
@@ -1747,7 +1665,7 @@ fn absent_keeps_matcher_labels_for_the_synthesized_output() {
     // `absent(v)` synthesizes its output labels from `v`'s equality matchers, so
     // those labels must survive into the schema — here `job` from `{job="x"}`.
     let qe = ok(r#"absent(up{job="x"})"#);
-    let cols = qe.output_schema().unwrap();
+    let cols = qe.schema.clone();
     assert!(
         cols.fields.iter().any(|c| c.name == "job"),
         "matcher label `job` kept, got {:?}",
@@ -1761,73 +1679,55 @@ fn absent_keeps_matcher_labels_for_the_synthesized_output() {
 
 #[test]
 fn time_lowers_to_the_eval_time_scalar() {
-    // SEMANTICS: `time()` is the query evaluation timestamp as a scalar — a leaf,
-    // not an aggregate over any series.
-    assert!(matches!(ok("time()"), QueryExpr::EvalTimestamp));
-    // …and it is scalar-shaped: a single float `value`, no time index.
-    let sch = ok("time()").output_schema().unwrap();
-    assert_eq!(sch.fields.len(), 1);
-    assert_eq!(sch.fields[0].name, "value");
-    assert!(sch.time_index.is_none());
+    assert!(matches!(
+        support::scalar_root("time()"),
+        ScalarExpr::EvalTimestamp
+    ));
 }
 
 #[test]
 fn time_minus_vector_is_the_uptime_pattern() {
-    // `time() - process_start_time_seconds` — the canonical uptime expression.
-    // The scalar `time()` broadcasts against the vector; the result takes the
-    // vector's schema.
     let qe = ok("time() - process_start_time_seconds");
-    let QueryExpr::BinaryOp { lhs, op, .. } = &qe else {
-        panic!("expected a BinaryOp, got {qe:?}");
-    };
-    assert!(matches!(lhs.as_ref(), QueryExpr::EvalTimestamp));
-    assert!(matches!(
-        op,
-        BinaryOpKind::Arithmetic(ArithmeticOpKind::Sub)
-    ));
-    assert!(qe.output_schema().is_ok());
+    assert!(
+        matches!(support::sample_expression(&qe), ScalarExpr::Arithmetic { op: ArithmeticOpKind::Sub, left, .. } if matches!(left.as_ref(), ScalarExpr::EvalTimestamp))
+    );
+    assert!(qe.schema.time_index.is_some());
 }
 
 #[test]
 fn calendar_functions_lower_to_time_fn_intents() {
-    // SEMANTICS: each of these is a per-series float transform of its argument's
-    // timestamp (or, for `timestamp`, the sample's own time). functions.test.
-    for (q, want) in [
-        ("timestamp(up)", TimeFunc::Timestamp),
-        ("minute(v)", TimeFunc::Minute),
-        ("hour(v)", TimeFunc::Hour),
-        ("day_of_week(v)", TimeFunc::DayOfWeek),
-        ("day_of_month(v)", TimeFunc::DayOfMonth),
-        ("day_of_year(v)", TimeFunc::DayOfYear),
-        ("month(v)", TimeFunc::Month),
-        ("year(v)", TimeFunc::Year),
-        ("days_in_month(v)", TimeFunc::DaysInMonth),
+    assert!(has(&ok("timestamp(up)"), |i| *i
+        == AggIntent::TimeFn(TimeFunc::Timestamp)));
+    for name in [
+        "minute",
+        "hour",
+        "day_of_week",
+        "day_of_month",
+        "day_of_year",
+        "month",
+        "year",
+        "days_in_month",
     ] {
-        let qe = ok(q);
+        let query = ok(&format!("{name}(v)"));
         assert!(
-            has(&qe, |i| *i == AggIntent::TimeFn(want)),
-            "{q} → TimeFn({want:?}), got {:?}",
-            intents(&qe)
+            matches!(support::sample_expression(&query),ScalarExpr::FunctionCall { name:n,args } if n==&format!("promql_{name}") && args.len()==1)
         );
     }
 }
 
 #[test]
 fn no_arg_calendar_function_reads_the_eval_time() {
-    // `day_of_week()` with no argument computes over the evaluation time itself,
-    // so it is a `TimeFn` aggregate whose child is the `EvalTimestamp` scalar.
-    let qe = ok("day_of_week()");
-    let QueryExpr::Aggregate {
-        measures, child, ..
-    } = &qe
-    else {
-        panic!("expected an Aggregate, got {qe:?}");
+    let query = ok("day_of_week()");
+    let NonASAPOp::Project { child, .. } = query.expect_non_asap() else {
+        panic!()
     };
     assert!(matches!(
-        measures.as_slice(),
-        [AggIntent::TimeFn(TimeFunc::DayOfWeek)]
+        child.expect_non_asap(),
+        NonASAPOp::PromqlVectorFromScalar(ScalarExpr::EvalTimestamp)
     ));
-    assert!(matches!(child.as_ref(), QueryExpr::EvalTimestamp));
+    assert!(
+        matches!(support::sample_expression(&query),ScalarExpr::FunctionCall { name,.. } if name=="promql_day_of_week")
+    );
 }
 
 #[test]
@@ -1848,30 +1748,23 @@ fn vector_promotes_a_scalar_to_a_vector() {
     // SEMANTICS: `vector(s)` is the scalar→instant-vector bridge — a label-less
     // single series carrying the scalar's value.
     let qe = ok("vector(1)");
-    let QueryExpr::PromqlVectorFromScalar(inner) = &qe else {
+    let NonASAPOp::PromqlVectorFromScalar(inner) = qe.expect_non_asap() else {
         panic!("expected PromqlVectorFromScalar, got {qe:?}");
     };
-    assert_eq!(inner.as_promql_scalar(), Some(1.0));
+    assert!(matches!(inner, ScalarExpr::Literal(ScalarValue::Float64(v)) if *v == 1.0));
     // Vector-typed: schema has a time index (a scalar leaf has none).
-    let sch = qe.output_schema().unwrap();
+    let sch = qe.schema.clone();
     assert!(sch.time_index.is_some());
     assert!(sch.fields.iter().any(|c| c.name == "value"));
 }
 
 #[test]
 fn scalar_collapses_a_vector_to_a_scalar() {
-    // SEMANTICS: `scalar(v)` is the instant-vector→scalar bridge.
-    let qe = ok("scalar(node_load1)");
-    let QueryExpr::PromqlScalarFromVector(inner) = &qe else {
-        panic!("expected PromqlScalarFromVector, got {qe:?}");
+    let qe = support::scalar_root("scalar(node_load1)");
+    let ScalarExpr::PromqlScalarFromVector(inner) = &qe else {
+        panic!()
     };
-    let (metric, _) = first_scan(inner);
-    assert_eq!(metric, "node_load1");
-    // PromqlScalarBridge-typed: single `value` column, no time index.
-    let sch = qe.output_schema().unwrap();
-    assert!(sch.time_index.is_none());
-    assert_eq!(sch.fields.len(), 1);
-    assert_eq!(sch.fields[0].name, "value");
+    assert_eq!(first_scan(inner).0, "node_load1");
 }
 
 #[test]
@@ -1880,26 +1773,32 @@ fn vector_zero_is_a_vector_operand_of_a_set_op() {
     // vectors, so `vector(0)` must be a vector (a `PromqlVectorFromScalar`), never a
     // folded scalar operand.
     let qe = ok("up or vector(0)");
-    let QueryExpr::BinaryOp { rhs, op, .. } = &qe else {
+    let NonASAPOp::BinaryOp {
+        operator: BinaryOperator { kind: op, .. },
+        rhs,
+        ..
+    } = qe.expect_non_asap()
+    else {
         panic!("expected a BinaryOp, got {qe:?}");
     };
     assert_eq!(*op, BinaryOpKind::Set(PromQLVectorSetOpKind::Or));
-    assert!(matches!(rhs.as_ref(), QueryExpr::PromqlVectorFromScalar(_)));
+    assert!(matches!(
+        rhs.expect_non_asap(),
+        NonASAPOp::PromqlVectorFromScalar(_)
+    ));
 }
 
 #[test]
 fn scalar_of_a_vector_feeds_a_threshold_comparison() {
-    // `node_load1 > scalar(node_cpu_count)` — `scalar(...)` is a scalar operand,
-    // so the BinaryOp output takes the vector (lhs) side's schema.
     let qe = ok("node_load1 > scalar(node_cpu_count)");
-    let QueryExpr::BinaryOp { lhs, rhs, .. } = &qe else {
-        panic!("expected a BinaryOp, got {qe:?}");
+    let ScalarExpr::Compare { right, .. } = support::sample_expression(&qe) else {
+        panic!()
     };
-    assert!(matches!(rhs.as_ref(), QueryExpr::PromqlScalarFromVector(_)));
-    // The BinaryOp output schema follows the vector (lhs) side, not the scalar.
-    let (metric, _) = first_scan(lhs);
-    assert_eq!(metric, "node_load1");
-    assert!(qe.output_schema().unwrap().time_index.is_some());
+    assert!(matches!(
+        right.as_ref(),
+        ScalarExpr::PromqlScalarFromVector(_)
+    ));
+    assert!(qe.schema.time_index.is_some());
 }
 
 #[test]
@@ -1909,13 +1808,13 @@ fn info_lowers_to_a_label_enrichment_join() {
     // (issue #84). The value/time axis pass through; the enriched labels are
     // runtime, so the schema stays the child's.
     let qe = ok("info(rate(http_requests_total[5m]))");
-    let QueryExpr::PromqlInfoEnrich { selector, child } = &qe else {
+    let NonASAPOp::PromqlInfoEnrich { selector, child } = qe.expect_non_asap() else {
         panic!("expected an PromqlInfoEnrich, got {qe:?}");
     };
     assert!(selector.is_empty(), "no selector → default target_info");
     // The child is the untouched input (a per-series rate reduction here).
     assert!(has(child, |i| *i == AggIntent::Rate));
-    assert!(qe.output_schema().unwrap().time_index.is_some());
+    assert!(qe.schema.clone().time_index.is_some());
 }
 
 #[test]
@@ -1925,7 +1824,7 @@ fn info_selector_carries_the_info_side_matchers() {
     // matchers are kept symbolically (not run through the single-metric selector
     // path).
     let qe = ok(r#"info(build_info, {__name__=~".+_info", another_data=~".+"})"#);
-    let QueryExpr::PromqlInfoEnrich { selector, .. } = &qe else {
+    let NonASAPOp::PromqlInfoEnrich { selector, .. } = qe.expect_non_asap() else {
         panic!("expected an PromqlInfoEnrich, got {qe:?}");
     };
     assert_eq!(
@@ -1949,12 +1848,12 @@ fn info_composes_under_an_aggregation_and_over_a_time_shift() {
     // `offset` / `@` on the input now lower to a `TimeShift` under the info-join
     // (issue #40) — the enrichment composes over the shifted selector.
     assert!(matches!(
-        ok("info(metric @ 60)"),
-        QueryExpr::PromqlInfoEnrich { .. }
+        ok("info(metric @ 60)").expect_non_asap(),
+        NonASAPOp::PromqlInfoEnrich { .. }
     ));
     assert!(matches!(
-        ok("info(metric offset 1m)"),
-        QueryExpr::PromqlInfoEnrich { .. }
+        ok("info(metric offset 1m)").expect_non_asap(),
+        NonASAPOp::PromqlInfoEnrich { .. }
     ));
 }
 
@@ -1967,12 +1866,12 @@ fn group_lowers_to_a_constant_group_intent() {
     // SEMANTICS: `group(v)` yields a constant 1 per group — a distinct intent,
     // NOT folded onto `sum` (which would return the value sum instead of 1).
     let qe = ok("group(up)");
-    let QueryExpr::Aggregate { measures, .. } = &qe else {
+    let NonASAPOp::Aggregate { measures, .. } = qe.expect_non_asap() else {
         panic!("expected an Aggregate, got {qe:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Group]));
     // Output column is the constant-1 `group` value.
-    let sch = qe.output_schema().unwrap();
+    let sch = qe.schema.clone();
     assert!(sch.fields.iter().any(|c| c.name == "group"));
 }
 
@@ -1980,7 +1879,7 @@ fn group_lowers_to_a_constant_group_intent() {
 fn group_by_keeps_the_grouping_keys() {
     // `group by (job) (up)` — the grouping keys ride on `Aggregate.by`.
     let qe = ok("group by (job) (up)");
-    let sch = qe.output_schema().unwrap();
+    let sch = qe.schema.clone();
     assert!(sch.fields.iter().any(|c| c.name == "job"));
     assert!(has(&qe, |i| *i == AggIntent::Group));
 }
@@ -1991,13 +1890,13 @@ fn count_values_groups_by_value_and_synthesizes_a_label() {
     // value, counts each distinct value, and emits that value as a new label
     // `l`. The intent carries the label; schema gains a `Utf8` `l` column.
     let qe = ok(r#"count_values("version", build_version)"#);
-    let QueryExpr::Aggregate { measures, .. } = &qe else {
+    let NonASAPOp::Aggregate { measures, .. } = qe.expect_non_asap() else {
         panic!("expected an Aggregate, got {qe:?}");
     };
     assert!(
         matches!(measures.as_slice(), [AggIntent::CountValues { label }] if label == "version")
     );
-    let sch = qe.output_schema().unwrap();
+    let sch = qe.schema.clone();
     let version = sch
         .fields
         .iter()
@@ -2023,7 +1922,7 @@ fn count_values_accepts_a_parenthesised_label_and_by_grouping() {
         &qe,
         |i| matches!(i, AggIntent::CountValues { label } if label == "v")
     ));
-    let sch = qe.output_schema().unwrap();
+    let sch = qe.schema.clone();
     assert!(sch.fields.iter().any(|c| c.name == "job"));
     assert!(sch.fields.iter().any(|c| c.name == "v"));
 }
@@ -2034,7 +1933,7 @@ fn count_values_label_colliding_with_a_group_key_is_not_duplicated() {
     // with a group-by key. PromQL's synthesized label takes precedence; the
     // output must carry a single `job` column, never two.
     let qe = ok(r#"count_values by (job) ("job", version)"#);
-    let sch = qe.output_schema().unwrap();
+    let sch = qe.schema.clone();
     let jobs = sch.fields.iter().filter(|c| c.name == "job").count();
     assert_eq!(jobs, 1, "collision deduped, got {:?}", sch.fields);
     assert!(sch.fields.iter().any(|c| c.name == "count"));
@@ -2046,18 +1945,18 @@ fn limitk_and_limit_ratio_lower_to_series_sampling() {
     // series kept unchanged (NOT a ranking), so they lower to the dedicated
     // `PromqlSeriesSample` node, never `topk`'s `Sort → Limit` (issue #86).
     assert!(matches!(
-        ok("limitk(2, http_requests)"),
-        QueryExpr::PromqlSeriesSample {
+        ok("limitk(2, http_requests)").expect_non_asap(),
+        NonASAPOp::PromqlSeriesSample {
             kind: SampleKind::LimitK(2),
             ..
         }
     ));
     assert!(matches!(
-        ok("limit_ratio(0.1, http_requests)"),
-        QueryExpr::PromqlSeriesSample { kind: SampleKind::LimitRatio(r), .. } if (r - 0.1).abs() < 1e-9
+        ok("limit_ratio(0.1, http_requests)").expect_non_asap(),
+        NonASAPOp::PromqlSeriesSample { kind: SampleKind::LimitRatio(r), .. } if (r - 0.1).abs() < 1e-9
     ));
     // Series-preserving: the output schema equals the input's (ts, value).
-    let sch = ok("limitk(2, http_requests)").output_schema().unwrap();
+    let sch = ok("limitk(2, http_requests)").schema.clone();
     assert!(sch.fields.iter().any(|c| c.name == "value"));
     assert!(sch.time_index.is_some());
 }
@@ -2067,12 +1966,12 @@ fn limit_ratio_keeps_a_negative_ratio_and_clamps_out_of_range() {
     // A negative ratio selects the complementary fraction — it must survive, not
     // be normalised away. Out-of-range magnitudes clamp to [-1, 1] (Prometheus).
     assert!(matches!(
-        ok("limit_ratio(-0.5, http_requests)"),
-        QueryExpr::PromqlSeriesSample { kind: SampleKind::LimitRatio(r), .. } if (r + 0.5).abs() < 1e-9
+        ok("limit_ratio(-0.5, http_requests)").expect_non_asap(),
+        NonASAPOp::PromqlSeriesSample { kind: SampleKind::LimitRatio(r), .. } if (r + 0.5).abs() < 1e-9
     ));
     assert!(matches!(
-        ok("limit_ratio(1.1, http_requests)"),
-        QueryExpr::PromqlSeriesSample { kind: SampleKind::LimitRatio(r), .. } if (r - 1.0).abs() < 1e-9
+        ok("limit_ratio(1.1, http_requests)").expect_non_asap(),
+        NonASAPOp::PromqlSeriesSample { kind: SampleKind::LimitRatio(r), .. } if (r - 1.0).abs() < 1e-9
     ));
 }
 
@@ -2080,7 +1979,7 @@ fn limit_ratio_keeps_a_negative_ratio_and_clamps_out_of_range() {
 fn limitk_by_carries_the_grouping_and_composes_in_a_set_op() {
     // `limitk by (group)` samples per group; the grouping label is seeded.
     let qe = ok("limitk by (group) (2, http_requests)");
-    let QueryExpr::PromqlSeriesSample { by, .. } = &qe else {
+    let NonASAPOp::PromqlSeriesSample { by, .. } = qe.expect_non_asap() else {
         panic!("expected a PromqlSeriesSample, got {qe:?}");
     };
     assert!(!by.is_empty(), "grouped sampling keeps its `by` keys");
@@ -2106,20 +2005,20 @@ fn dynamic_and_non_finite_sample_params_are_rejected() {
 // ─────────────────────────────────────────────────────────────────────────────
 
 /// Descend single-child nodes to the first `PromqlRelabel`.
-fn first_relabel(e: &QueryExpr) -> &QueryExpr {
-    match e {
-        QueryExpr::PromqlRelabel { .. } => e,
-        QueryExpr::Aggregate { child, .. }
-        | QueryExpr::Filter { child, .. }
-        | QueryExpr::TimeRange { child, .. }
-        | QueryExpr::TimeShift { child, .. } => first_relabel(child),
+fn first_relabel(e: &OperatorNode) -> &OperatorNode {
+    match e.expect_non_asap() {
+        NonASAPOp::PromqlRelabel { .. } => e,
+        NonASAPOp::Aggregate { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::TimeRange { child, .. }
+        | NonASAPOp::TimeShift { child, .. } => first_relabel(child),
         other => panic!("no PromqlRelabel reachable from {other:?}"),
     }
 }
 
 /// True when `value` is a `FunctionCall` with the given name.
-fn is_fn_named(value: &QueryExpr, name: &str) -> bool {
-    matches!(value, QueryExpr::FunctionCall { name: n, .. } if n == name)
+fn is_fn_named(value: &ScalarExpr, name: &str) -> bool {
+    matches!(value, ScalarExpr::FunctionCall { name: n, .. } if n == name)
 }
 
 #[test]
@@ -2127,7 +2026,7 @@ fn label_replace_is_a_relabel_over_the_vector() {
     // SEMANTICS: `label_replace(v, dst, repl, src, regex)` rewrites the `dst`
     // label per series from a regex over `src`; the sample value is untouched.
     let qe = ok(r#"label_replace(up, "host", "$1", "instance", "(.+):.*")"#);
-    let QueryExpr::PromqlRelabel { dst, value, child } = &qe else {
+    let NonASAPOp::PromqlRelabel { dst, value, child } = qe.expect_non_asap() else {
         panic!("expected a PromqlRelabel, got {qe:?}");
     };
     assert_eq!(dst, "host");
@@ -2137,7 +2036,7 @@ fn label_replace_is_a_relabel_over_the_vector() {
     // The value expression is a `label_replace` fn reading the `src` label.
     assert!(is_fn_named(value, "label_replace"));
     // Output: the child's columns + the synthesized `host` label; value & ts kept.
-    let sch = qe.output_schema().unwrap();
+    let sch = qe.schema.clone();
     assert!(sch.fields.iter().any(|c| c.name == "host"));
     assert!(sch.fields.iter().any(|c| c.name == "value"));
     assert!(sch.time_index.is_some(), "the vector's time axis survives");
@@ -2148,12 +2047,12 @@ fn label_join_concatenates_source_labels() {
     // SEMANTICS: `label_join(v, dst, sep, src…)` joins the source labels with
     // `sep` into `dst`.
     let qe = ok(r#"label_join(up, "combined", "-", "job", "instance")"#);
-    let QueryExpr::PromqlRelabel { dst, value, .. } = &qe else {
+    let NonASAPOp::PromqlRelabel { dst, value, .. } = qe.expect_non_asap() else {
         panic!("expected a PromqlRelabel, got {qe:?}");
     };
     assert_eq!(dst, "combined");
     assert!(is_fn_named(value, "label_join"));
-    let sch = qe.output_schema().unwrap();
+    let sch = qe.schema.clone();
     assert!(sch.fields.iter().any(|c| c.name == "combined"));
 }
 
@@ -2164,9 +2063,11 @@ fn label_replace_composes_under_an_aggregation() {
     let qe = ok(r#"sum by (host) (label_replace(up, "host", "$1", "instance", "(.+):.*"))"#);
     // A PromqlRelabel sits below the outer Sum.
     let relabel = first_relabel(&qe);
-    assert!(matches!(relabel, QueryExpr::PromqlRelabel { dst, .. } if dst == "host"));
+    assert!(
+        matches!(relabel.expect_non_asap(), NonASAPOp::PromqlRelabel { dst, .. } if dst == "host")
+    );
     assert!(has(&qe, |i| matches!(i, AggIntent::Sum { .. })));
-    let sch = qe.output_schema().unwrap();
+    let sch = qe.schema.clone();
     assert!(sch.fields.iter().any(|c| c.name == "host"));
 }
 
@@ -2191,7 +2092,7 @@ fn extra_over_time_reducers_lower_to_per_series_intents() {
         assert!(has(&qe, |i| *i == want), "{q}: {:?}", intents(&qe));
         // Per-series: the range window survives as a `TimeRange`.
         assert!(
-            matches!(&qe, QueryExpr::Aggregate { child, .. } if matches!(child.as_ref(), QueryExpr::TimeRange { .. })),
+            matches!(qe.expect_non_asap(), NonASAPOp::Aggregate { child, .. } if matches!(child.expect_non_asap(), NonASAPOp::TimeRange { .. })),
             "{q} keeps its range as a TimeRange"
         );
     }
@@ -2215,13 +2116,13 @@ fn sort_and_sort_desc_reorder_by_value_without_a_limit() {
         ("sort_desc(http_requests)", false),
     ] {
         let qe = ok(q);
-        let QueryExpr::Sort { keys, child, .. } = &qe else {
+        let NonASAPOp::Sort { keys, child, .. } = qe.expect_non_asap() else {
             panic!("{q}: expected a Sort, got {qe:?}");
         };
         assert_eq!(keys.len(), 1);
         assert_eq!(keys[0].ascending, ascending, "{q}");
         // No Limit above the Sort — every series is preserved.
-        assert!(!matches!(&qe, QueryExpr::Limit { .. }));
+        assert!(!matches!(qe.expect_non_asap(), NonASAPOp::Limit { .. }));
         // The value column is what it ranks on: descend to the scan.
         let (metric, _) = first_scan(child);
         assert_eq!(metric, "http_requests");
@@ -2233,12 +2134,12 @@ fn sort_by_label_orders_on_each_label_in_turn() {
     // `sort_by_label(v, "group", "instance", "job")` — one ascending sort key per
     // label, in argument order; the labels are seeded into the schema.
     let qe = ok(r#"sort_by_label(http_requests, "group", "instance", "job")"#);
-    let QueryExpr::Sort { keys, .. } = &qe else {
+    let NonASAPOp::Sort { keys, .. } = qe.expect_non_asap() else {
         panic!("expected a Sort, got {qe:?}");
     };
     assert_eq!(keys.len(), 3, "one key per label");
     assert!(keys.iter().all(|k| k.ascending));
-    let sch = qe.output_schema().unwrap();
+    let sch = qe.schema.clone();
     for label in ["group", "instance", "job"] {
         assert!(sch.fields.iter().any(|c| c.name == label), "{label} seeded");
     }
@@ -2247,7 +2148,7 @@ fn sort_by_label_orders_on_each_label_in_turn() {
 #[test]
 fn sort_by_label_desc_is_descending() {
     let qe = ok(r#"sort_by_label_desc(http_requests, "instance")"#);
-    let QueryExpr::Sort { keys, .. } = &qe else {
+    let NonASAPOp::Sort { keys, .. } = qe.expect_non_asap() else {
         panic!("expected a Sort, got {qe:?}");
     };
     assert!(keys.iter().all(|k| !k.ascending));
@@ -2256,28 +2157,43 @@ fn sort_by_label_desc_is_descending() {
 #[test]
 fn min_of_max_of_fold_constant_scalars() {
     // `min_of`/`max_of` are n-ary scalar reducers. When every argument is a
-    // constant they constant-fold to a `PromqlScalarBridge` leaf, just like scalar
+    // constant they constant-fold to a `ScalarExpr` leaf, just like scalar
     // arithmetic (#35) — the only form the intent algebra can hold (#89).
-    assert_eq!(ok("min_of(3, 5)").as_promql_scalar(), Some(3.0));
-    assert_eq!(ok("max_of(3, 5)").as_promql_scalar(), Some(5.0));
-    assert_eq!(ok("min_of(-2, -5)").as_promql_scalar(), Some(-5.0));
+    assert_eq!(
+        promql_scalar(&support::scalar_root("min_of(3, 5)")),
+        Some(3.0)
+    );
+    assert_eq!(
+        promql_scalar(&support::scalar_root("max_of(3, 5)")),
+        Some(5.0)
+    );
+    assert_eq!(
+        promql_scalar(&support::scalar_root("min_of(-2, -5)")),
+        Some(-5.0)
+    );
     // Nested folds and use as a threshold operand.
     assert_eq!(
-        ok("max_of(min_of(2, 3), 10)").as_promql_scalar(),
+        promql_scalar(&support::scalar_root("max_of(min_of(2, 3), 10)")),
         Some(10.0)
     );
     let qe = ok("up > max_of(1, 2)");
-    let QueryExpr::BinaryOp { rhs, .. } = &qe else {
+    let ScalarExpr::Compare { right: rhs, .. } = support::sample_expression(&qe) else {
         panic!("{qe:?}")
     };
-    assert_eq!(rhs.as_promql_scalar(), Some(2.0));
+    assert_eq!(promql_scalar(rhs), Some(2.0));
 }
 
 #[test]
 fn min_of_max_of_ignore_nan_like_the_min_max_aggregators() {
     // A NaN argument is skipped (Prometheus `min`/`max` NaN semantics).
-    assert_eq!(ok("max_of(3, NaN)").as_promql_scalar(), Some(3.0));
-    assert_eq!(ok("min_of(NaN, 3)").as_promql_scalar(), Some(3.0));
+    assert_eq!(
+        promql_scalar(&support::scalar_root("max_of(3, NaN)")),
+        Some(3.0)
+    );
+    assert_eq!(
+        promql_scalar(&support::scalar_root("min_of(NaN, 3)")),
+        Some(3.0)
+    );
 }
 
 #[test]
diff --git a/crates/frontend-promql/tests/promql_equivalence.rs b/crates/frontend-promql/tests/promql_equivalence.rs
index 9d0cab2ad..ac3c5a06f 100644
--- a/crates/frontend-promql/tests/promql_equivalence.rs
+++ b/crates/frontend-promql/tests/promql_equivalence.rs
@@ -17,12 +17,14 @@
 
 #![allow(non_snake_case)]
 
+use std::rc::Rc;
+
 mod support;
-use asap_types::pre_asap::QueryExpr;
+use asap_types::ir::OperatorNode;
 use asap_types::types::AccuracyTarget;
 use support::lower_promql;
 
-fn lo(q: &str) -> QueryExpr {
+fn lo(q: &str) -> Rc<OperatorNode> {
     lower_promql(q, AccuracyTarget::Exact).unwrap_or_else(|e| panic!("{q:?} should lower: {e}"))
 }
 
diff --git a/crates/frontend-promql/tests/promql_lowering.rs b/crates/frontend-promql/tests/promql_lowering.rs
index 243bf6d18..540f426f5 100644
--- a/crates/frontend-promql/tests/promql_lowering.rs
+++ b/crates/frontend-promql/tests/promql_lowering.rs
@@ -1,10 +1,13 @@
 //! End-to-end tests for PromQL → unresolved → canonical DAG lowering.
 
+use std::rc::Rc;
 use std::time::Duration;
 
+use asap_types::ir::{
+    BinaryOperator, ExprSemantics, NonASAPOp, OperatorNode, ScalarExpr, TimeRangeKind,
+};
 use asap_types::pre_asap::{
-    AggIntent, ArithmeticOpKind, BinaryOpKind, CompareOpKind, QueryExpr, Reduction, ScalarValue,
-    Source,
+    AggIntent, ArithmeticOpKind, BinaryOpKind, CompareOpKind, Reduction, ScalarValue, Source,
 };
 use asap_types::types::AccuracyTarget;
 use asap_types::workload::{
@@ -16,7 +19,7 @@ use asap_frontend_promql::{lower_promql_workload, PromqlError as LoweringError};
 mod support;
 use support::lower_promql;
 
-fn lower(q: &str) -> QueryExpr {
+fn lower(q: &str) -> Rc<OperatorNode> {
     lower_promql(q, AccuracyTarget::Exact).unwrap_or_else(|e| panic!("lower failed for {q:?}: {e}"))
 }
 
@@ -77,12 +80,12 @@ fn distinct_over_time_preserves_cardinality_accuracy_and_nested_windows() {
 #[test]
 fn bare_selector_is_scan_with_predicates() {
     let qe = lower(r#"http_requests_total{env="prod",status!="500"}"#);
-    let QueryExpr::TimeRange { child, .. } = &qe else {
+    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
         panic!("expected TimeRange, got {qe:?}");
     };
-    let QueryExpr::Scan {
+    let NonASAPOp::Scan {
         source, predicates, ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected Scan, got {qe:?}");
     };
@@ -92,29 +95,32 @@ fn bare_selector_is_scan_with_predicates() {
     assert_eq!(predicates.len(), 2);
     assert!(predicates
         .iter()
-        .all(|p| matches!(p.0.as_ref(), QueryExpr::Compare { .. })));
+        .all(|p| matches!(&p.0, ScalarExpr::Compare { .. })));
 }
 
 #[test]
 fn regex_matcher_lowers_to_regex_compareop() {
     let qe = lower(r#"http_requests_total{path=~"/api/.*"}"#);
-    let QueryExpr::TimeRange { child, .. } = &qe else {
+    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
         panic!("expected TimeRange, got {qe:?}");
     };
-    let QueryExpr::Scan {
+    let NonASAPOp::Scan {
         predicates, schema, ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected Scan, got {qe:?}");
     };
-    let QueryExpr::Compare { left, op, right } = predicates[0].0.as_ref() else {
+    let ScalarExpr::Compare {
+        left, op, right, ..
+    } = &predicates[0].0
+    else {
         panic!("expected Compare, got {:?}", predicates[0].0);
     };
     assert_eq!(*op, CompareOpKind::Regex);
     // The label matcher's column is resolved positionally against the scan schema.
     let path_id = schema.column_id("path").expect("path in scan schema");
-    assert!(matches!(left.as_ref(), QueryExpr::Column(id) if *id == path_id));
-    assert!(matches!(right.as_ref(), QueryExpr::Literal(ScalarValue::Utf8(v)) if v == "/api/.*"));
+    assert!(matches!(left.as_ref(), ScalarExpr::Column(id) if *id == path_id));
+    assert!(matches!(right.as_ref(), ScalarExpr::Literal(ScalarValue::Utf8(v)) if v == "/api/.*"));
 }
 
 // ── *_over_time → Aggregate over TimeRange ──────────────────────────────────────
@@ -122,12 +128,12 @@ fn regex_matcher_lowers_to_regex_compareop() {
 #[test]
 fn quantile_over_time_is_time_range_aggregate() {
     let qe = lower(r#"quantile_over_time(0.99, http_request_duration{env="prod"}[5m])"#);
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected Aggregate, got {qe:?}");
     };
@@ -135,12 +141,14 @@ fn quantile_over_time_is_time_range_aggregate() {
     assert!(
         matches!(measures.as_slice(), [AggIntent::Quantile { q, .. }] if (*q - 0.99).abs() < 1e-9)
     );
-    let QueryExpr::TimeRange { range, child } = child.as_ref() else {
+    let NonASAPOp::TimeRange { range, child, .. } = child.expect_non_asap() else {
         panic!("expected TimeRange child, got {child:?}");
     };
     assert_eq!(*range, Duration::from_secs(300));
     // The label matcher folded onto the Scan.
-    assert!(matches!(child.as_ref(), QueryExpr::Scan { predicates, .. } if predicates.len() == 1));
+    assert!(
+        matches!(child.expect_non_asap(), NonASAPOp::Scan { predicates, .. } if predicates.len() == 1)
+    );
 }
 
 #[test]
@@ -151,39 +159,42 @@ fn outer_sum_by_over_quantile_over_time_groups_positionally() {
     // a name-based Partition. Leaf = [ts, value, host, service] (referenced
     // names appended sorted) → host = col 2.
     let qe = lower(r#"sum by (host) (quantile_over_time(0.99, latency{service="web"}[5m]))"#);
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate grouped by host, got {qe:?}");
     };
     assert_eq!(reduction, &Reduction::by(vec![2]));
     assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
     // Inner: Aggregate{Quantile} over TimeRange (per-series over_time reduction).
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected Aggregate (quantile_over_time) under the outer Sum, got {child:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Quantile { .. }]));
-    assert!(matches!(child.as_ref(), QueryExpr::TimeRange { .. }));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
 }
 
 #[test]
 fn avg_over_time_maps_to_avg_intent() {
     let qe = lower("avg_over_time(cpu_seconds_total[10m])");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected Aggregate, got {qe:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Avg { .. }]));
-    let QueryExpr::TimeRange { range, .. } = child.as_ref() else {
+    let NonASAPOp::TimeRange { range, .. } = child.expect_non_asap() else {
         panic!("expected TimeRange child, got {child:?}");
     };
     assert_eq!(*range, Duration::from_secs(600));
@@ -192,9 +203,9 @@ fn avg_over_time_maps_to_avg_intent() {
 #[test]
 fn stddev_and_stdvar_over_time() {
     let qe = lower("stddev_over_time(m[5m])");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected Aggregate");
     };
@@ -205,12 +216,15 @@ fn stddev_and_stdvar_over_time() {
             ..
         }]
     ));
-    assert!(matches!(child.as_ref(), QueryExpr::TimeRange { .. }));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
 
     let qe = lower("stdvar_over_time(m[5m])");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected Aggregate");
     };
@@ -221,7 +235,10 @@ fn stddev_and_stdvar_over_time() {
             ..
         }]
     ));
-    assert!(matches!(child.as_ref(), QueryExpr::TimeRange { .. }));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
 }
 
 #[test]
@@ -230,32 +247,33 @@ fn histogram_quantile_wraps_inner_in_quantile() {
     // not squashed away. The `_bucket` metric + `le` matcher mark the classic
     // form → `HistogramQuantile` over `Aggregate{Rate}` over Scan.
     let qe = lower(r#"histogram_quantile(0.95, rate(http_duration_seconds_bucket{le="0.5"}[5m]))"#);
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate{{HistogramQuantile}}, got {qe:?}");
     };
     assert!(
         matches!(measures.as_slice(), [AggIntent::HistogramQuantile { q, .. }] if (*q - 0.95).abs() < 1e-9)
     );
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected inner Aggregate{{Rate}}, got {child:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
-    let QueryExpr::TimeRange {
+    let NonASAPOp::TimeRange {
         range,
         child: tr_child,
-    } = child.as_ref()
+        ..
+    } = child.expect_non_asap()
     else {
         panic!("expected TimeRange under Rate, got {child:?}");
     };
     assert_eq!(*range, Duration::from_secs(300));
     assert!(
-        matches!(tr_child.as_ref(), QueryExpr::Scan { predicates, .. } if predicates.len() == 1)
+        matches!(tr_child.expect_non_asap(), NonASAPOp::Scan { predicates, .. } if predicates.len() == 1)
     );
 }
 
@@ -266,9 +284,9 @@ fn histogram_quantile_over_sum_by_le_preserves_grouping() {
     // `sum by (le)` aggregate; now the `le` grouping survives into the
     // canonical DAG.
     let qe = lower(r#"histogram_quantile(0.99, sum by (le) (rate(http_requests_bucket[5m])))"#);
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate{{HistogramQuantile}}, got {qe:?}");
     };
@@ -278,11 +296,11 @@ fn histogram_quantile_over_sum_by_le_preserves_grouping() {
     );
     // `sum by (le)` survives as a positional Aggregate (by = [2], `le`) over the
     // inner Rate — no name-based Partition.
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected `sum by (le)` as a positional Aggregate, got {child:?}");
     };
@@ -292,12 +310,12 @@ fn histogram_quantile_over_sum_by_le_preserves_grouping() {
 
 /// The classic `histogram_quantile` aggregate: its `without` keys, `le`
 /// column, and output column names.
-fn classic_histogram(qe: &QueryExpr) -> (Vec<usize>, usize, Vec<String>) {
-    let QueryExpr::Aggregate {
+fn classic_histogram(qe: &OperatorNode) -> (Vec<usize>, usize, Vec<String>) {
+    let NonASAPOp::Aggregate {
         reduction: Reduction::Reduce(by),
         measures,
         ..
-    } = qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected a reducing Aggregate, got {qe:?}");
     };
@@ -305,13 +323,7 @@ fn classic_histogram(qe: &QueryExpr) -> (Vec<usize>, usize, Vec<String>) {
         panic!("expected HistogramQuantile, got {measures:?}");
     };
     assert!(by.is_without(), "histogram_quantile groups without (le)");
-    let names = qe
-        .output_schema()
-        .unwrap()
-        .fields
-        .iter()
-        .map(|c| c.name.clone())
-        .collect();
+    let names = qe.schema.fields.iter().map(|c| c.name.clone()).collect();
     (by.keys().to_vec(), *le, names)
 }
 
@@ -321,10 +333,10 @@ fn classic_histogram(qe: &QueryExpr) -> (Vec<usize>, usize, Vec<String>) {
 fn classic_histogram_quantile_groups_without_le() {
     let qe = lower("histogram_quantile(0.9, rate(http_duration_seconds_bucket[5m]))");
     let (keys, le, names) = classic_histogram(&qe);
-    let QueryExpr::Aggregate { child, .. } = &qe else {
+    let NonASAPOp::Aggregate { child, .. } = qe.expect_non_asap() else {
         unreachable!()
     };
-    let child = child.output_schema().unwrap();
+    let child = &child.schema;
     assert_eq!(child.fields[le].name, "le");
     assert_eq!(keys, vec![le]);
     assert_eq!(names, vec!["histogram_quantile"]);
@@ -349,14 +361,16 @@ fn classic_histogram_quantile_keeps_out_of_range_quantiles() {
         ("histogram_quantile(-1, x_bucket)", -1.),
         ("histogram_quantile(2, x_bucket)", 2.),
     ] {
-        let QueryExpr::Aggregate { measures, .. } = lower(query) else {
+        let root = lower(query);
+        let NonASAPOp::Aggregate { measures, .. } = root.expect_non_asap() else {
             panic!("{query}");
         };
         assert!(
             matches!(measures.as_slice(), [AggIntent::HistogramQuantile { q, .. }] if *q == expected)
         );
     }
-    let QueryExpr::Aggregate { measures, .. } = lower("histogram_quantile(NaN, x_bucket)") else {
+    let root = lower("histogram_quantile(NaN, x_bucket)");
+    let NonASAPOp::Aggregate { measures, .. } = root.expect_non_asap() else {
         panic!("NaN");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::HistogramQuantile { q, .. }] if q.is_nan()));
@@ -379,14 +393,14 @@ fn classic_histogram_quantile_rejects_an_argument_without_le() {
 #[test]
 fn rate_has_time_range_child_not_window() {
     let qe = lower("rate(http_requests_total[5m])");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected Aggregate for rate, got {qe:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
-    let QueryExpr::TimeRange { range, .. } = child.as_ref() else {
+    let NonASAPOp::TimeRange { range, .. } = child.expect_non_asap() else {
         panic!("expected TimeRange child (not Window), got {child:?}");
     };
     assert_eq!(*range, Duration::from_secs(300));
@@ -395,14 +409,14 @@ fn rate_has_time_range_child_not_window() {
 #[test]
 fn increase_maps_to_increase_intent() {
     let qe = lower("increase(errors_total[1h])");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected Aggregate for increase, got {qe:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Increase]));
-    let QueryExpr::TimeRange { range, .. } = child.as_ref() else {
+    let NonASAPOp::TimeRange { range, .. } = child.expect_non_asap() else {
         panic!("expected TimeRange child, got {child:?}");
     };
     assert_eq!(*range, Duration::from_secs(3600));
@@ -415,21 +429,24 @@ fn sum_over_rate_keeps_both_levels() {
     // Regression: `sum(rate(m[w]))` — the most common PromQL shape — must keep
     // the cross-series Sum, not collapse to a bare per-series Rate.
     let qe = lower("sum(rate(http_requests_total[5m]))");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate{{Sum}}, got {qe:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected inner Aggregate{{Rate}}, got {child:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
-    assert!(matches!(child.as_ref(), QueryExpr::TimeRange { .. }));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
 }
 
 #[test]
@@ -438,20 +455,20 @@ fn sum_by_over_rate_groups_the_outer_sum() {
     // on a positional `Aggregate.by` (the same shape SQL produces) over the
     // label-preserving inner Rate. Leaf = [ts, value, job] → by = [2].
     let qe = lower("sum by (job) (rate(http_requests_total[5m]))");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate grouped by job, got {qe:?}");
     };
     assert_eq!(reduction, &Reduction::by(vec![2]));
     assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
     assert!(matches!(
-        child.as_ref(),
-        QueryExpr::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate])
+        child.expect_non_asap(),
+        NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate])
     ));
 }
 
@@ -459,16 +476,16 @@ fn sum_by_over_rate_groups_the_outer_sum() {
 fn count_over_rate_keeps_both_levels() {
     // The `Outer::Count` sibling of the `sum(rate(...))` bug.
     let qe = lower("count(rate(http_requests_total[5m]))");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate{{Count}}, got {qe:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
     assert!(matches!(
-        child.as_ref(),
-        QueryExpr::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate])
+        child.expect_non_asap(),
+        NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate])
     ));
 }
 
@@ -487,12 +504,12 @@ fn count_over_distinct_over_time_preserves_both_aggregates() {
         ),
     ] {
         let dag = lower(query);
-        let QueryExpr::Aggregate {
+        let NonASAPOp::Aggregate {
             measures,
             reduction: actual,
             child,
             ..
-        } = &dag
+        } = dag.expect_non_asap()
         else {
             panic!("expected outer Count: {dag:?}");
         };
@@ -501,12 +518,12 @@ fn count_over_distinct_over_time_preserves_both_aggregates() {
             "{query}: {dag:?}"
         );
         assert_eq!(actual, &reduction, "{query}");
-        let QueryExpr::Aggregate {
+        let NonASAPOp::Aggregate {
             measures,
             reduction,
             child,
             ..
-        } = child.as_ref()
+        } = child.expect_non_asap()
         else {
             panic!("expected inner per-series Cardinality: {dag:?}");
         };
@@ -516,7 +533,7 @@ fn count_over_distinct_over_time_preserves_both_aggregates() {
         );
         assert_eq!(reduction, &Reduction::PerEntity, "{query}");
         assert!(
-            matches!(child.as_ref(), QueryExpr::TimeRange { range, .. } if range.as_secs() == 300)
+            matches!(child.expect_non_asap(), NonASAPOp::TimeRange { range, .. } if range.as_secs() == 300)
         );
     }
 }
@@ -552,14 +569,17 @@ fn count_never_lowers_to_distinct_sample_values() {
 #[test]
 fn count_over_time_is_count_intent() {
     let qe = lower("count_over_time(m[5m])");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected Aggregate");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
-    assert!(matches!(child.as_ref(), QueryExpr::TimeRange { .. }));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
 }
 
 #[test]
@@ -568,26 +588,29 @@ fn outer_count_counts_series() {
     // over the window (label-preserving), outer cross-series row count grouped
     // on a positional `Aggregate.by`. Leaf = [ts, value, symbol] → symbol = col 2.
     let qe = lower("count by (symbol) (count_over_time(financial_last_trade_price[5m]))");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected outer Aggregate grouped by symbol, got {qe:?}");
     };
     assert_eq!(reduction, &Reduction::by(vec![2]));
     assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
     // Inner: Aggregate{Count} over TimeRange (per-series count_over_time).
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected Aggregate (count_over_time) under the outer count, got {child:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
-    assert!(matches!(child.as_ref(), QueryExpr::TimeRange { .. }));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
 }
 
 // ── topk / bottomk ────────────────────────────────────────────────────────────
@@ -596,12 +619,12 @@ fn outer_count_counts_series() {
 fn topk_over_count_is_heavy_hitter_topk() {
     let qe = lower(r#"topk by (service) (10, count_over_time(requests{env="prod"}[1m]))"#);
     // Heavy-hitter: Aggregate{TopK} with grouping resolved to positional ids.
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected Aggregate with TopK, got {qe:?}");
     };
@@ -612,29 +635,29 @@ fn topk_over_count_is_heavy_hitter_topk() {
         [AggIntent::TopK { k: 10, .. }]
     ));
     // The count_over_time under the TopK is a TimeRange-backed aggregate.
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected Aggregate (count_over_time) under TopK, got {child:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
-    let QueryExpr::TimeRange { range, child } = child.as_ref() else {
+    let NonASAPOp::TimeRange { range, child, .. } = child.expect_non_asap() else {
         panic!("expected TimeRange under Count aggregate, got {child:?}");
     };
     assert_eq!(*range, Duration::from_secs(60));
-    assert!(matches!(child.as_ref(), QueryExpr::Scan { .. }));
+    assert!(matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }));
 }
 
 #[test]
 fn topk_over_sum_is_value_weighted_heavy_hitter_topk() {
     let qe = lower(r#"topk by (service) (5, sum_over_time(requests{env="prod"}[1m]))"#);
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected Aggregate with TopK, got {qe:?}");
     };
@@ -643,29 +666,38 @@ fn topk_over_sum_is_value_weighted_heavy_hitter_topk() {
         measures.as_slice(),
         [AggIntent::TopK { k: 5, .. }]
     ));
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected Aggregate (sum_over_time) under TopK, got {child:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    assert!(matches!(child.as_ref(), QueryExpr::TimeRange { .. }));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
 }
 
 #[test]
 fn topk_over_avg_is_generic_sort_limit() {
     let qe = lower("topk by (host) (5, avg_over_time(cpu[5m]))");
-    let QueryExpr::Limit { n, offset, child } = &qe else {
+    let NonASAPOp::Limit {
+        n: Some(n),
+        offset,
+        child,
+        ..
+    } = qe.expect_non_asap()
+    else {
         panic!("expected Limit, got {qe:?}");
     };
     assert_eq!(*n, 5);
     assert_eq!(*offset, 0);
-    let QueryExpr::Sort {
+    let NonASAPOp::Sort {
         keys,
         partition_by,
         child,
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected Sort under Limit, got {child:?}");
     };
@@ -678,7 +710,7 @@ fn topk_over_avg_is_generic_sort_limit() {
     // Underneath: the label-preserving windowed avg aggregate (by: []), no
     // intervening Partition.
     assert!(
-        matches!(child.as_ref(), QueryExpr::Aggregate { reduction, measures, .. }
+        matches!(child.expect_non_asap(), NonASAPOp::Aggregate { reduction, measures, .. }
             if reduction == &Reduction::PerEntity && matches!(measures.as_slice(), [AggIntent::Avg { .. }])),
         "expected bare per-series Avg aggregate under Sort, got {child:?}"
     );
@@ -687,7 +719,7 @@ fn topk_over_avg_is_generic_sort_limit() {
 #[test]
 fn ungrouped_topk_over_sum_is_heavy_hitter() {
     let qe = lower("topk(5, sum_over_time(m[5m]))");
-    assert!(matches!(&qe, QueryExpr::Aggregate { .. }));
+    assert!(matches!(qe.expect_non_asap(), NonASAPOp::Aggregate { .. }));
     assert!(has_intent(&qe, |i| matches!(i, AggIntent::Sum { .. })));
     assert!(has_intent(&qe, |i| matches!(
         i,
@@ -699,11 +731,14 @@ fn ungrouped_topk_over_sum_is_heavy_hitter() {
 fn bottomk_over_count_is_generic_sort_ascending() {
     // `bottomk` is never a heavy-hitter (descending=false), even over count.
     let qe = lower("bottomk(3, count_over_time(m[5m]))");
-    let QueryExpr::Limit { n, child, .. } = &qe else {
+    let NonASAPOp::Limit {
+        n: Some(n), child, ..
+    } = qe.expect_non_asap()
+    else {
         panic!("expected Limit, got {qe:?}");
     };
     assert_eq!(*n, 3);
-    let QueryExpr::Sort { keys, .. } = child.as_ref() else {
+    let NonASAPOp::Sort { keys, .. } = child.expect_non_asap() else {
         panic!("expected Sort");
     };
     assert!(keys[0].ascending, "bottomk ranks ascending");
@@ -715,11 +750,14 @@ fn bottomk_over_count_is_generic_sort_ascending() {
 #[test]
 fn bottomk_is_always_generic_sort_ascending() {
     let qe = lower("bottomk(3, count_over_time(m[5m]))");
-    let QueryExpr::Limit { n, child, .. } = &qe else {
+    let NonASAPOp::Limit {
+        n: Some(n), child, ..
+    } = qe.expect_non_asap()
+    else {
         panic!("expected Limit, got {qe:?}");
     };
     assert_eq!(*n, 3);
-    let QueryExpr::Sort { keys, .. } = child.as_ref() else {
+    let NonASAPOp::Sort { keys, .. } = child.expect_non_asap() else {
         panic!("expected Sort");
     };
     assert!(keys[0].ascending, "bottomk ranks ascending");
@@ -731,12 +769,12 @@ fn topk_count_output_schema_carries_group_key() {
     // (`service`) flows through to the outer TopK's `by` column. Leaf schema =
     // [ts, value, service] → TopK groups on service (col 2).
     let qe = lower("topk by (service) (5, count_over_time(m[1m]))");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected Aggregate{{TopK}}, got {qe:?}");
     };
@@ -750,14 +788,17 @@ fn topk_count_output_schema_carries_group_key() {
         [AggIntent::TopK { k: 5, .. }]
     ));
     // Inner Count aggregate is visible with its TimeRange child.
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected inner Aggregate{{Count}}, got {child:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
-    assert!(matches!(child.as_ref(), QueryExpr::TimeRange { .. }));
+    assert!(matches!(
+        child.expect_non_asap(),
+        NonASAPOp::TimeRange { .. }
+    ));
 }
 
 // ── binary ops ────────────────────────────────────────────────────────────────
@@ -765,22 +806,32 @@ fn topk_count_output_schema_carries_group_key() {
 #[test]
 fn binary_op_division() {
     let qe = lower("rate(a[5m]) / rate(b[5m])");
-    let QueryExpr::BinaryOp { op, lhs, rhs, .. } = &qe else {
+    let NonASAPOp::BinaryOp {
+        operator: BinaryOperator { kind: op, .. },
+        lhs,
+        rhs,
+        ..
+    } = qe.expect_non_asap()
+    else {
         panic!("expected BinaryOp, got {qe:?}");
     };
     assert_eq!(*op, BinaryOpKind::Arithmetic(ArithmeticOpKind::Div));
     assert!(
-        matches!(lhs.as_ref(), QueryExpr::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate]))
+        matches!(lhs.expect_non_asap(), NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate]))
     );
     assert!(
-        matches!(rhs.as_ref(), QueryExpr::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate]))
+        matches!(rhs.expect_non_asap(), NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate]))
     );
 }
 
 #[test]
 fn binary_op_with_on_grouping() {
     let qe = lower("a / on(host) b");
-    let QueryExpr::BinaryOp { vector_match, .. } = &qe else {
+    let NonASAPOp::BinaryOp {
+        operator: BinaryOperator { vector_match, .. },
+        ..
+    } = qe.expect_non_asap()
+    else {
         panic!("expected BinaryOp, got {qe:?}");
     };
     let vm = vector_match.as_ref().expect("vector_match present");
@@ -793,18 +844,38 @@ fn binary_op_with_on_grouping() {
 // carry it.
 #[test]
 fn bool_comparisons_are_distinct() {
-    let op = |q: &str| match lower(q) {
-        QueryExpr::BinaryOp { op, .. } => op,
+    let op = |q: &str| match lower(q).expect_non_asap() {
+        NonASAPOp::BinaryOp {
+            operator,
+            return_bool,
+            ..
+        } => (operator.kind.clone(), *return_bool),
+        NonASAPOp::Filter {
+            pred: asap_types::ir::Predicate(ScalarExpr::Compare { op, .. }),
+            ..
+        } => (BinaryOpKind::Compare(op.clone()), false),
+        NonASAPOp::Project { cols, .. } => {
+            let ScalarExpr::Case { branches, .. } = &cols[1].expr else {
+                panic!()
+            };
+            let ScalarExpr::Compare { op, .. } = &branches[0].0 else {
+                panic!()
+            };
+            (BinaryOpKind::Compare(op.clone()), true)
+        }
         other => panic!("expected BinaryOp, got {other:?}"),
     };
-    assert_eq!(op("a > 1"), BinaryOpKind::Compare(CompareOpKind::Gt));
+    assert_eq!(
+        op("a > 1"),
+        (BinaryOpKind::Compare(CompareOpKind::Gt), false)
+    );
     assert_eq!(
         op("a > bool 1"),
-        BinaryOpKind::CompareBool(CompareOpKind::Gt)
+        (BinaryOpKind::Compare(CompareOpKind::Gt), true)
     );
     assert_eq!(
         op("a == bool on(job) b"),
-        BinaryOpKind::CompareBool(CompareOpKind::Eq)
+        (BinaryOpKind::Compare(CompareOpKind::Eq), true)
     );
 }
 
@@ -814,7 +885,7 @@ fn binary_op_binds_each_branch_against_its_own_schema() {
     // single root schema threaded to both branches, the left scan would leak the
     // right's group key (and vice-versa). Per-branch binding keeps them separate.
     let qe = lower("count by (job) (a) / count by (region) (b)");
-    let QueryExpr::BinaryOp { lhs, rhs, .. } = &qe else {
+    let NonASAPOp::BinaryOp { lhs, rhs, .. } = qe.expect_non_asap() else {
         panic!("expected BinaryOp, got {qe:?}");
     };
     let lcols = scan_columns(lhs);
@@ -829,26 +900,26 @@ fn binary_op_binds_each_branch_against_its_own_schema() {
     );
 }
 
-/// Collect every `AggIntent` in the DAG, root-to-leaf.
-fn all_intents(e: &QueryExpr) -> Vec<AggIntent> {
+/// Collect every `AggIntent` in the dag, root-to-leaf.
+fn all_intents(e: &OperatorNode) -> Vec<AggIntent> {
     let mut out = Vec::new();
     collect_intents(e, &mut out);
     out
 }
 
-fn collect_intents(e: &QueryExpr, out: &mut Vec<AggIntent>) {
-    match e {
-        QueryExpr::Aggregate {
+fn collect_intents(e: &OperatorNode, out: &mut Vec<AggIntent>) {
+    match e.expect_non_asap() {
+        NonASAPOp::Aggregate {
             measures, child, ..
         } => {
             out.extend(measures.iter().cloned());
             collect_intents(child, out);
         }
-        QueryExpr::TimeRange { child, .. }
-        | QueryExpr::Filter { child, .. }
-        | QueryExpr::Sort { child, .. }
-        | QueryExpr::Limit { child, .. } => collect_intents(child, out),
-        QueryExpr::BinaryOp { lhs, rhs, .. } => {
+        NonASAPOp::TimeRange { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. } => collect_intents(child, out),
+        NonASAPOp::BinaryOp { lhs, rhs, .. } => {
             collect_intents(lhs, out);
             collect_intents(rhs, out);
         }
@@ -856,20 +927,20 @@ fn collect_intents(e: &QueryExpr, out: &mut Vec<AggIntent>) {
     }
 }
 
-/// True if any `AggIntent` anywhere in the DAG satisfies `pred`.
-fn has_intent<F: Fn(&AggIntent) -> bool>(e: &QueryExpr, pred: F) -> bool {
+/// True if any `AggIntent` anywhere in the dag satisfies `pred`.
+fn has_intent<F: Fn(&AggIntent) -> bool>(e: &OperatorNode, pred: F) -> bool {
     all_intents(e).iter().any(pred)
 }
 
 /// Field names on the first `Scan` reachable by descending single-child nodes.
-fn scan_columns(e: &QueryExpr) -> Vec<String> {
-    match e {
-        QueryExpr::Scan { schema, .. } => schema.fields.iter().map(|c| c.name.clone()).collect(),
-        QueryExpr::Aggregate { child, .. }
-        | QueryExpr::TimeRange { child, .. }
-        | QueryExpr::Filter { child, .. }
-        | QueryExpr::Sort { child, .. }
-        | QueryExpr::Limit { child, .. } => scan_columns(child),
+fn scan_columns(e: &OperatorNode) -> Vec<String> {
+    match e.expect_non_asap() {
+        NonASAPOp::Scan { schema, .. } => schema.fields.iter().map(|c| c.name.clone()).collect(),
+        NonASAPOp::Aggregate { child, .. }
+        | NonASAPOp::TimeRange { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. } => scan_columns(child),
         _ => vec![],
     }
 }
@@ -883,12 +954,12 @@ fn without_grouping_lowers_to_the_exclusion_form() {
     // label is stored positionally (the SchemaResolver seeds it), the grouping is the
     // `without` form, and the output schema stays open.
     let qe = lower("sum without (instance) (rate(m[5m]))");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = &qe
+    } = qe.expect_non_asap()
     else {
         panic!("expected an Aggregate, got {qe:?}");
     };
@@ -899,10 +970,10 @@ fn without_grouping_lowers_to_the_exclusion_form() {
     // The inner per-series rate is preserved (label-preserving) under the outer
     // cross-series `without` reduction.
     assert!(
-        matches!(child.as_ref(), QueryExpr::Aggregate { measures, .. }
+        matches!(child.expect_non_asap(), NonASAPOp::Aggregate { measures, .. }
         if matches!(measures.as_slice(), [AggIntent::Rate]))
     );
-    assert!(!qe.output_schema().unwrap().closed);
+    assert!(!qe.schema.clone().closed);
 }
 
 // ── parameter validation (reject rather than silently truncate/garble) ──────────
@@ -920,7 +991,7 @@ fn out_of_range_quantile_phi_is_accepted() {
     for query in [
         "quantile(1.5, up)",
         "quantile_over_time(1.5, m[5m])",
-        "histogram_quantile(2.0, rate(b[5m]))",
+        "histogram_quantile(2.0, rate(b_bucket[5m]))",
     ] {
         assert!(
             lower_promql(query, AccuracyTarget::Exact).is_ok(),
@@ -979,7 +1050,7 @@ fn accuracy_target_flows_into_quantile_intent() {
         AccuracyTarget::Epsilon(0.01),
     )
     .unwrap();
-    let QueryExpr::Aggregate { measures, .. } = &qe else {
+    let NonASAPOp::Aggregate { measures, .. } = qe.expect_non_asap() else {
         panic!("expected Aggregate");
     };
     assert!(matches!(
@@ -998,10 +1069,10 @@ fn aggregate_output_schema_preserves_time_axis_and_labels() {
     // predicate columns) to the scan schema, so `env` appears as a column
     // even though it is only used as a filter.
     // per_series_reduction_schema preserves the time axis and all label columns.
-    let QueryExpr::Aggregate { .. } = &qe else {
+    let NonASAPOp::Aggregate { .. } = qe.expect_non_asap() else {
         panic!("expected Aggregate, got {qe:?}");
     };
-    let schema = qe.output_schema().expect("aggregate schema");
+    let schema = &qe.schema;
     let names: Vec<&str> = schema.fields.iter().map(|c| c.name.as_str()).collect();
     assert_eq!(names, vec!["ts", "value", "env"]);
     assert_eq!(
@@ -1016,16 +1087,16 @@ fn scan_schema_carries_ts_value_and_group_keys() {
     // `service` is a group key → the SchemaResolver lands it in the self-contained
     // Scan schema (positional). `env` is only a filter, so it is not a column.
     let qe = lower("count by (service) (count_over_time(requests[1m]))");
-    fn find_scan(n: &QueryExpr) -> &QueryExpr {
-        match n {
-            QueryExpr::Scan { .. } => n,
-            QueryExpr::TimeRange { child, .. }
-            | QueryExpr::Aggregate { child, .. }
-            | QueryExpr::Filter { child, .. } => find_scan(child),
+    fn find_scan(n: &OperatorNode) -> &OperatorNode {
+        match n.expect_non_asap() {
+            NonASAPOp::Scan { .. } => n,
+            NonASAPOp::TimeRange { child, .. }
+            | NonASAPOp::Aggregate { child, .. }
+            | NonASAPOp::Filter { child, .. } => find_scan(child),
             other => panic!("unexpected node {other:?}"),
         }
     }
-    let QueryExpr::Scan { schema, .. } = find_scan(&qe) else {
+    let NonASAPOp::Scan { schema, .. } = find_scan(&qe).expect_non_asap() else {
         unreachable!()
     };
     let mut names: Vec<&str> = schema.fields.iter().map(|c| c.name.as_str()).collect();
@@ -1113,19 +1184,23 @@ fn reducing_group_by_lowers_to_aggregate_by() {
     // Cross-series reduce, no keys → bare `Aggregate { reduction: Reduce([]) }`.
     let q = lower("sum(http_requests_total)");
     assert!(
-        matches!(q, QueryExpr::Aggregate { ref reduction, .. } if reduction == &Reduction::by(vec![]))
+        matches!(q.expect_non_asap(), NonASAPOp::Aggregate { reduction, .. } if reduction == &Reduction::by(vec![]))
     );
 
     // Cross-series reduce grouped by a label → `Aggregate.reduction`.
     let q = lower("sum by (job) (http_requests_total)");
-    assert!(matches!(q, QueryExpr::Aggregate { ref reduction, .. }
-        if reduction.expect_reduce().len() == 1));
+    assert!(
+        matches!(q.expect_non_asap(), NonASAPOp::Aggregate { reduction, .. }
+        if reduction.expect_reduce().len() == 1)
+    );
 
     // Reduce over a label-preserving `rate` grouped by a label → still
     // `Aggregate.reduction` (the keys resolve against rate's preserved schema).
     let q = lower("sum by (job) (rate(http_requests_total[5m]))");
-    assert!(matches!(q, QueryExpr::Aggregate { ref reduction, .. }
-        if reduction.expect_reduce().len() == 1));
+    assert!(
+        matches!(q.expect_non_asap(), NonASAPOp::Aggregate { reduction, .. }
+        if reduction.expect_reduce().len() == 1)
+    );
 }
 
 #[test]
@@ -1134,20 +1209,20 @@ fn generic_topk_grouping_lowers_to_sort_partition_by() {
     // reducing → the grouping rides on `Sort.partition_by`, and the windowed
     // reduction beneath stays label-preserving (`by: []`). No `Partition` node.
     let q = lower("topk by (host) (5, avg_over_time(cpu[5m]))");
-    let QueryExpr::Limit { child, .. } = &q else {
+    let NonASAPOp::Limit { child, .. } = q.expect_non_asap() else {
         panic!("expected Limit, got {q:?}");
     };
-    let QueryExpr::Sort {
+    let NonASAPOp::Sort {
         partition_by,
         child,
         ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected Sort, got {child:?}");
     };
     assert_eq!(partition_by, &vec![2], "host is col 2 in [ts, value, host]");
     assert!(
-        matches!(child.as_ref(), QueryExpr::Aggregate { reduction, .. } if reduction == &Reduction::PerEntity)
+        matches!(child.expect_non_asap(), NonASAPOp::Aggregate { reduction, .. } if reduction == &Reduction::PerEntity)
     );
 }
 
@@ -1160,15 +1235,18 @@ fn topk_over_bare_selector_by_label_ranks_per_group() {
     // Partition→Sort.partition_by reframe in #12). Expected:
     //   Limit{3} → Sort{value desc, partition_by:[job]} → Scan
     let q = lower("topk(3, http_requests_total) by (job)");
-    let QueryExpr::Limit { n, child, .. } = &q else {
+    let NonASAPOp::Limit {
+        n: Some(n), child, ..
+    } = q.expect_non_asap()
+    else {
         panic!("expected Limit, got {q:?}");
     };
     assert_eq!(*n, 3);
-    let QueryExpr::Sort {
+    let NonASAPOp::Sort {
         keys,
         partition_by,
         child,
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected Sort, got {child:?}");
     };
@@ -1177,7 +1255,7 @@ fn topk_over_bare_selector_by_label_ranks_per_group() {
     // No implicit reducing aggregate — the selector is label-preserving, so the
     // sort is directly over the selector horizon (the `job` label survives to partition by).
     assert!(
-        matches!(child.as_ref(), QueryExpr::TimeRange { child, .. } if matches!(child.as_ref(), QueryExpr::Scan { .. })),
+        matches!(child.expect_non_asap(), NonASAPOp::TimeRange { child, .. } if matches!(child.expect_non_asap(), NonASAPOp::Scan { .. })),
         "ranking is over the bare selector horizon, not a reducing Aggregate, got {child:?}"
     );
     assert!(
@@ -1191,20 +1269,20 @@ fn topk_over_bare_selector_ranks_raw_samples() {
     // Even without `by`, `topk(3, m)` ranks the raw instant-vector samples — it
     // does not sum them. The sort sits directly over the Scan, partition empty.
     let q = lower("topk(3, http_requests_total)");
-    let QueryExpr::Limit { child, .. } = &q else {
+    let NonASAPOp::Limit { child, .. } = q.expect_non_asap() else {
         panic!("expected Limit, got {q:?}");
     };
-    let QueryExpr::Sort {
+    let NonASAPOp::Sort {
         partition_by,
         child,
         ..
-    } = child.as_ref()
+    } = child.expect_non_asap()
     else {
         panic!("expected Sort, got {child:?}");
     };
     assert!(partition_by.is_empty(), "no `by` → global ranking");
     assert!(
-        matches!(child.as_ref(), QueryExpr::TimeRange { child, .. } if matches!(child.as_ref(), QueryExpr::Scan { .. }))
+        matches!(child.expect_non_asap(), NonASAPOp::TimeRange { child, .. } if matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }))
     );
     assert!(!has_intent(&q, |i| matches!(i, AggIntent::Sum { .. })));
 }
@@ -1212,20 +1290,20 @@ fn topk_over_bare_selector_ranks_raw_samples() {
 // ── Issue #109: histogram_quantiles fans out into one branch per φ ──────────
 
 /// The `(label value, intent)` of each `histogram_quantiles` branch.
-fn quantile_branches(q: &QueryExpr) -> Vec<(String, AggIntent)> {
-    let QueryExpr::Concat { children, .. } = q else {
+fn quantile_branches(q: &OperatorNode) -> Vec<(String, AggIntent)> {
+    let NonASAPOp::Concat { children, .. } = q.expect_non_asap() else {
         panic!("expected a Concat at the root, got {q:?}");
     };
     children
         .iter()
         .map(|c| {
-            let QueryExpr::PromqlRelabel { value, child, .. } = c else {
+            let NonASAPOp::PromqlRelabel { value, child, .. } = c.expect_non_asap() else {
                 panic!("expected PromqlRelabel per branch, got {c:?}");
             };
-            let QueryExpr::Literal(ScalarValue::Utf8(v)) = value.as_ref() else {
+            let ScalarExpr::Literal(ScalarValue::Utf8(v)) = value else {
                 panic!("expected a literal label value, got {value:?}");
             };
-            let QueryExpr::Aggregate { measures, .. } = child.as_ref() else {
+            let NonASAPOp::Aggregate { measures, .. } = child.expect_non_asap() else {
                 panic!("expected an Aggregate under the PromqlRelabel, got {child:?}");
             };
             (v.clone(), measures[0].clone())
@@ -1234,24 +1312,12 @@ fn quantile_branches(q: &QueryExpr) -> Vec<(String, AggIntent)> {
 }
 
 #[test]
-fn histogram_quantiles_fans_out_over_native_histograms() {
-    // Raw / native-histogram argument → the sketch-able `Quantile` intent,
-    // exactly as the single-quantile `histogram_quantile` would choose.
-    let q = lower(r#"histogram_quantiles(testhistogram3, "q", 0, 0.25, 1)"#);
-    let branches = quantile_branches(&q);
-    assert_eq!(branches.len(), 3);
-    let labels: Vec<_> = branches.iter().map(|(l, _)| l.as_str()).collect();
-    assert_eq!(
-        labels,
-        ["0.0", "0.25", "1.0"],
-        "OpenMetrics float formatting"
-    );
-    for (_, intent) in &branches {
-        assert!(
-            matches!(intent, AggIntent::Quantile { .. }),
-            "native histogram → sketch-able Quantile, got {intent:?}"
-        );
-    }
+fn histogram_quantiles_rejects_unrepresented_native_histograms() {
+    assert!(lower_promql(
+        r#"histogram_quantiles(testhistogram3, "q", 0, 0.25, 1)"#,
+        AccuracyTarget::Exact
+    )
+    .is_err());
 }
 
 #[test]
@@ -1270,15 +1336,15 @@ fn histogram_quantiles_over_classic_buckets_interpolates() {
 fn histogram_quantiles_branches_are_union_compatible() {
     // `Concat` derives its schema from the first child, so every branch must
     // agree on column names — the φ lives in the label, not the column name.
-    let q = lower(r#"histogram_quantiles(testhistogram3, "q", 0.5, 0.9)"#);
-    let QueryExpr::Concat { children, .. } = &q else {
+    let q = lower(r#"histogram_quantiles(testhistogram3_bucket, "q", 0.5, 0.9)"#);
+    let NonASAPOp::Concat { children, .. } = q.expect_non_asap() else {
         panic!("expected Concat");
     };
     let shapes: Vec<Vec<String>> = children
         .iter()
         .map(|c| {
-            c.output_schema()
-                .expect("branch schema")
+            c.schema
+                .clone()
                 .fields
                 .iter()
                 .map(|c| c.name.clone())
@@ -1288,7 +1354,7 @@ fn histogram_quantiles_branches_are_union_compatible() {
     assert_eq!(shapes[0], shapes[1], "branches must be union-compatible");
     assert_eq!(shapes[0], vec!["value".to_string(), "q".to_string()]);
     assert_eq!(
-        q.output_schema().expect("merged schema").fields.len(),
+        q.schema.fields.len(),
         2,
         "the merged schema describes every branch"
     );
@@ -1296,11 +1362,11 @@ fn histogram_quantiles_branches_are_union_compatible() {
 
 #[test]
 fn histogram_quantiles_uses_the_given_label_name() {
-    let q = lower(r#"histogram_quantiles(h, "phi", 0.5)"#);
-    let QueryExpr::Concat { children, .. } = &q else {
+    let q = lower(r#"histogram_quantiles(h_bucket, "phi", 0.5)"#);
+    let NonASAPOp::Concat { children, .. } = q.expect_non_asap() else {
         panic!("expected Concat");
     };
-    let QueryExpr::PromqlRelabel { dst, .. } = &children[0] else {
+    let NonASAPOp::PromqlRelabel { dst, .. } = children[0].expect_non_asap() else {
         panic!("expected PromqlRelabel");
     };
     assert_eq!(dst, "phi");
@@ -1309,7 +1375,7 @@ fn histogram_quantiles_uses_the_given_label_name() {
 #[test]
 fn histogram_quantiles_formats_small_quantiles_like_prometheus() {
     // `labels.FormatOpenMetricsFloat`: Go's %g, so exponent form below 1e-4.
-    let q = lower(r#"histogram_quantiles(h, "q", 0.00001)"#);
+    let q = lower(r#"histogram_quantiles(h_bucket, "q", 0.00001)"#);
     assert_eq!(quantile_branches(&q)[0].0, "1e-05");
 }
 
@@ -1317,9 +1383,9 @@ fn histogram_quantiles_formats_small_quantiles_like_prometheus() {
 fn histogram_quantiles_rejects_an_out_of_range_quantile() {
     // Same rule as `histogram_quantile(φ, …)` — one bad φ fails the whole call.
     for q in [
-        r#"histogram_quantiles(h, "q", -0.1)"#,
-        r#"histogram_quantiles(h, "q", 1.01)"#,
-        r#"histogram_quantiles(h, "q", 0.5, NaN)"#,
+        r#"histogram_quantiles(h_bucket, "q", -0.1)"#,
+        r#"histogram_quantiles(h_bucket, "q", 1.01)"#,
+        r#"histogram_quantiles(h_bucket, "q", 0.5, NaN)"#,
     ] {
         assert!(
             lower_promql(q, AccuracyTarget::Exact).is_err(),
@@ -1328,19 +1394,244 @@ fn histogram_quantiles_rejects_an_out_of_range_quantile() {
     }
 }
 
-// A subquery's `offset`/`@` shift the whole subquery, so the DAG keeps them.
+// ── TimeRange.kind: instant vs range selectors ──────────────────────────────────
+
+#[test]
+fn bare_instant_selector_is_an_instant_time_range() {
+    // `up` reads the latest sample per series within the workload's ingestion
+    // interval (1s in `support::workload`): an `Instant` lookback of that length.
+    let qe = lower("up");
+    let NonASAPOp::TimeRange { range, kind, child } = qe.expect_non_asap() else {
+        panic!("expected TimeRange, got {qe:?}");
+    };
+    assert_eq!(*kind, TimeRangeKind::Instant);
+    assert_eq!(*range, Duration::from_secs(1));
+    assert!(matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }));
+}
+
+#[test]
+fn explicit_range_selector_is_a_range_time_range() {
+    // `m[5m]` keeps its own window and is a `Range` selection — both under a
+    // range function and as a bare matrix selector.
+    let qe = lower("rate(m[5m])");
+    let NonASAPOp::Aggregate { child, .. } = qe.expect_non_asap() else {
+        panic!("expected Aggregate, got {qe:?}");
+    };
+    let NonASAPOp::TimeRange { range, kind, .. } = child.expect_non_asap() else {
+        panic!("expected TimeRange, got {child:?}");
+    };
+    assert_eq!(*kind, TimeRangeKind::Range);
+    assert_eq!(*range, Duration::from_secs(300));
+
+    let qe = lower("m[5m]");
+    assert!(matches!(
+        qe.expect_non_asap(),
+        NonASAPOp::TimeRange {
+            kind: TimeRangeKind::Range,
+            ..
+        }
+    ));
+}
+
+#[test]
+fn instant_and_range_selectors_of_equal_length_stay_distinct() {
+    // The kind is part of the shape: a 1s range selector is not the same dag as
+    // the 1s instant lookback injected around a bare selector.
+    assert_ne!(lower("up"), lower("up[1s]"));
+}
+
+// ── the `bool` modifier → `return_bool` ─────────────────────────────────────────
+
+#[test]
+fn vector_scalar_comparison_without_bool_filters() {
+    let qe = lower("up > 0");
+    assert!(matches!(qe.expect_non_asap(), NonASAPOp::Filter { .. }));
+    assert!(matches!(
+        support::sample_expression(&qe),
+        ScalarExpr::Compare {
+            op: CompareOpKind::Gt,
+            ..
+        }
+    ));
+}
+
+#[test]
+fn vector_scalar_comparison_with_bool_sets_return_bool() {
+    let qe = lower("up > bool 0");
+    assert!(matches!(
+        support::sample_expression(&qe),
+        ScalarExpr::Case { .. }
+    ));
+    assert_ne!(qe, lower("up > 0"));
+}
+
+#[test]
+fn vector_vector_comparison_with_bool_sets_return_bool() {
+    // `a > bool b` — the modifier lands on the vector/vector op itself, with
+    // the default (ignoring nothing) match.
+    let qe = lower("a > bool b");
+    let NonASAPOp::BinaryOp {
+        operator,
+        return_bool,
+        lhs,
+        rhs,
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected BinaryOp, got {qe:?}");
+    };
+    assert!(*return_bool);
+    assert_eq!(operator.kind, BinaryOpKind::Compare(CompareOpKind::Gt));
+    assert!(matches!(lhs.expect_non_asap(), NonASAPOp::TimeRange { .. }));
+    assert!(matches!(rhs.expect_non_asap(), NonASAPOp::TimeRange { .. }));
+    assert!(!lower("a > b").expect_non_asap().children().is_empty());
+    assert_ne!(qe, lower("a > b"));
+}
+
+#[test]
+fn bool_modifier_composes_with_vector_matching() {
+    let qe = lower("a > bool on(job) b");
+    let NonASAPOp::BinaryOp {
+        operator,
+        return_bool,
+        ..
+    } = qe.expect_non_asap()
+    else {
+        panic!("expected BinaryOp, got {qe:?}");
+    };
+    assert!(*return_bool);
+    let vm = operator.vector_match.as_ref().expect("on(job) present");
+    assert_eq!(vm.labels, vec!["job".to_string()]);
+}
+
+// ── scalar expressions: negation, arithmetic, comparison ────────────────────────
+
+#[test]
+fn scalar_negation_of_time_is_a_negative_expression() {
+    // `-time()` is a scalar expression; its negation stays structural (the
+    // operand is not a constant to fold) and follows PromQL numeric rules.
+    let qe = support::scalar_root("-time()");
+    let ScalarExpr::Negative { expr, semantics } = &qe else {
+        panic!("expected ScalarExpr(Negative), got {qe:?}");
+    };
+    assert_eq!(*semantics, ExprSemantics::Promql);
+    assert!(matches!(expr.as_ref(), ScalarExpr::EvalTimestamp));
+    // Scalar-shaped: no time index.
+}
+
+#[test]
+fn scalar_negation_of_a_constant_still_folds() {
+    // `-(2)` is constant: it folds to one literal rather than a `Negative`.
+    assert_eq!(
+        support::promql_scalar(&support::scalar_root("-(2)")),
+        Some(-2.0)
+    );
+}
+
+#[test]
+fn scalar_arithmetic_carries_promql_semantics() {
+    let qe = support::scalar_root("time() - 1");
+    let ScalarExpr::Arithmetic {
+        op,
+        left,
+        right,
+        semantics,
+    } = &qe
+    else {
+        panic!("expected scalar(Arithmetic), got {qe:?}");
+    };
+    assert_eq!(*op, ArithmeticOpKind::Sub);
+    assert_eq!(*semantics, ExprSemantics::Promql);
+    assert!(matches!(left.as_ref(), ScalarExpr::EvalTimestamp));
+    assert!(matches!(
+        right.as_ref(),
+        ScalarExpr::Literal(ScalarValue::Float64(v)) if *v == 1.0
+    ));
+}
+
+#[test]
+fn scalar_bool_comparison_is_a_zero_one_case_with_promql_semantics() {
+    // `1 < bool 2` → `Case(Compare(1 < 2) → 1.0, else 0.0)`: PromQL yields 0/1.
+    let qe = support::scalar_root("1 < bool 2");
+    let ScalarExpr::Case {
+        operand,
+        branches,
+        else_expr,
+    } = &qe
+    else {
+        panic!("expected scalar(Case), got {qe:?}");
+    };
+    assert!(operand.is_none());
+    let [(when, then)] = branches.as_slice() else {
+        panic!("expected one branch, got {branches:?}");
+    };
+    let ScalarExpr::Compare {
+        left,
+        op,
+        right,
+        semantics,
+    } = when
+    else {
+        panic!("expected a Compare condition, got {when:?}");
+    };
+    assert_eq!(*op, CompareOpKind::Lt);
+    assert_eq!(*semantics, ExprSemantics::Promql);
+    assert!(matches!(left.as_ref(), ScalarExpr::Literal(ScalarValue::Float64(v)) if *v == 1.0));
+    assert!(matches!(right.as_ref(), ScalarExpr::Literal(ScalarValue::Float64(v)) if *v == 2.0));
+    assert!(matches!(then, ScalarExpr::Literal(ScalarValue::Float64(v)) if *v == 1.0));
+    assert!(matches!(
+        else_expr.as_deref(),
+        Some(ScalarExpr::Literal(ScalarValue::Float64(v))) if *v == 0.0
+    ));
+}
+
+#[test]
+fn scalar_comparison_without_bool_is_rejected() {
+    // PromQL has no scalar filter: a scalar/scalar comparison needs `bool`.
+    for q in ["1 < 2", "time() > 0", "(1 + 1) == 2"] {
+        assert!(
+            lower_promql(q, AccuracyTarget::Exact).is_err(),
+            "{q} must be rejected without `bool`"
+        );
+    }
+}
+
+#[test]
+fn label_matcher_predicates_carry_promql_semantics() {
+    let qe = lower(r#"up{job="api"}"#);
+    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
+        panic!("expected TimeRange, got {qe:?}");
+    };
+    let NonASAPOp::Scan { predicates, .. } = child.expect_non_asap() else {
+        panic!("expected Scan, got {child:?}");
+    };
+    assert!(matches!(
+        &predicates[0].0,
+        ScalarExpr::Compare {
+            semantics: ExprSemantics::Promql,
+            ..
+        }
+    ));
+}
+
+// A subquery's `offset` / `@` modifier stays a `TimeShift` over the subquery.
 #[test]
 fn subquery_time_shift_is_retained() {
-    let QueryExpr::Aggregate { child, .. } = lower("max_over_time(m[5m:1m] offset 1m)") else {
-        panic!("expected a range function");
+    let root = lower("max_over_time(m[5m:1m] offset 1m)");
+    let NonASAPOp::Aggregate { child, .. } = root.expect_non_asap() else {
+        panic!("expected a range function, got {root:?}");
     };
-    let QueryExpr::TimeShift { shift, child } = child.as_ref() else {
+    let NonASAPOp::TimeShift { shift, child } = child.expect_non_asap() else {
         panic!("subquery offset was dropped: {child:?}");
     };
     assert_eq!(shift.offset_ms, 60_000);
-    assert!(matches!(child.as_ref(), QueryExpr::PromqlSubquery { .. }));
     assert!(matches!(
-        lower("max_over_time(m[5m:1m] @ 100)"),
-        QueryExpr::Aggregate { child, .. } if matches!(child.as_ref(), QueryExpr::TimeShift { .. })
+        child.expect_non_asap(),
+        NonASAPOp::PromqlSubquery { .. }
+    ));
+    let root = lower("max_over_time(m[5m:1m] @ 100)");
+    assert!(matches!(
+        root.expect_non_asap(),
+        NonASAPOp::Aggregate { child, .. }
+            if matches!(child.expect_non_asap(), NonASAPOp::TimeShift { .. })
     ));
 }
diff --git a/crates/frontend-promql/tests/unified_scalar_design.rs b/crates/frontend-promql/tests/scalar_design.rs
similarity index 97%
rename from crates/frontend-promql/tests/unified_scalar_design.rs
rename to crates/frontend-promql/tests/scalar_design.rs
index 4e3f3063e..e4f8038f8 100644
--- a/crates/frontend-promql/tests/unified_scalar_design.rs
+++ b/crates/frontend-promql/tests/scalar_design.rs
@@ -1,12 +1,11 @@
 //! Scalar expressions never become constant-wrapper operators.
-#[path = "unified_support.rs"]
 mod support;
 use asap_types::ir::{NonASAPOp, QueryRoot, ScalarExpr};
 use asap_types::pre_asap::{ArithmeticOpKind, ScalarValue};
 use asap_types::types::AccuracyTarget;
 
 fn root(query: &str) -> QueryRoot {
-    asap_frontend_promql::unified::lower_promql_query_workload(
+    asap_frontend_promql::lower_promql_query_workload(
         &support::workload(query, AccuracyTarget::Exact),
         0,
     )
diff --git a/crates/frontend-promql/tests/support.rs b/crates/frontend-promql/tests/support.rs
index 1f15b1ca2..bba2656f2 100644
--- a/crates/frontend-promql/tests/support.rs
+++ b/crates/frontend-promql/tests/support.rs
@@ -1,14 +1,17 @@
+use std::rc::Rc;
+
 use asap_frontend_promql::{
     lower_promql_workload, lower_promql_workload_with_histograms, HistogramCatalog, PromqlError,
 };
-use asap_types::pre_asap::QueryExpr;
+use asap_types::ir::{NonASAPOp, OperatorNode, ScalarExpr};
+use asap_types::pre_asap::ScalarValue;
 use asap_types::types::AccuracyTarget;
 use asap_types::workload::{
     AccuracyRequirement, BatchEntry, DataWorkload, DurationMs, Evidence, PlanningWorkload,
     Predictability, Query, QueryLanguage, QueryRequirements, QueryWorkload, TimeSelection,
 };
 
-fn workload(query: &str, accuracy: AccuracyTarget) -> PlanningWorkload {
+pub fn workload(query: &str, accuracy: AccuracyTarget) -> PlanningWorkload {
     PlanningWorkload {
         query_workload: QueryWorkload {
             language: QueryLanguage::PromQL,
@@ -35,7 +38,11 @@ fn workload(query: &str, accuracy: AccuracyTarget) -> PlanningWorkload {
     }
 }
 
-pub fn lower_promql(query: &str, accuracy: AccuracyTarget) -> Result<QueryExpr, PromqlError> {
+#[allow(dead_code)]
+pub fn lower_promql(
+    query: &str,
+    accuracy: AccuracyTarget,
+) -> Result<Rc<OperatorNode>, PromqlError> {
     let mut lowered = lower_promql_workload(&workload(query, accuracy), 0)?;
     Ok(lowered.remove(0))
 }
@@ -45,8 +52,59 @@ pub fn lower_promql_with_histograms(
     query: &str,
     accuracy: AccuracyTarget,
     histograms: HistogramCatalog,
-) -> Result<QueryExpr, PromqlError> {
+) -> Result<Rc<OperatorNode>, PromqlError> {
     let mut lowered =
         lower_promql_workload_with_histograms(&workload(query, accuracy), histograms, 0)?;
     Ok(lowered.remove(0))
 }
+
+/// The value of a bare PromQL numeric literal / folded constant at an
+/// scalar position (`Literal(Float64(v))`); `None` for any
+/// other shape.
+#[allow(dead_code)]
+pub fn promql_scalar(node: &ScalarExpr) -> Option<f64> {
+    match node {
+        ScalarExpr::Literal(ScalarValue::Float64(v)) => Some(*v),
+        _ => None,
+    }
+}
+
+/// Time `root` under the default (every summary maintained) lifecycle
+/// assignment and export the post-ASAP DAG — the wire-6 export needs every
+/// node timed first.
+#[allow(dead_code)]
+pub fn post_asap_dag(root: &Rc<OperatorNode>) -> asap_types::ir::export::PhysicalASAPDAG {
+    use asap_types::ir::{apply_lifecycle_timings, LifecycleAssignment, TimingMemo};
+    let timed = apply_lifecycle_timings(
+        root,
+        &LifecycleAssignment::default_maintained(),
+        &mut TimingMemo::new(),
+    )
+    .expect("default lifecycle timings");
+    asap_types::ir::export::compile_physical_asap_dag(&timed).expect("post-ASAP DAG export")
+}
+
+#[allow(dead_code)]
+pub fn scalar_root(query: &str) -> ScalarExpr {
+    match asap_frontend_promql::lower_promql_query_workload(
+        &workload(query, AccuracyTarget::Exact),
+        0,
+    )
+    .unwrap()
+    .remove(0)
+    {
+        asap_types::ir::QueryRoot::Scalar(expr) => expr,
+        _ => panic!("expected scalar root: {query}"),
+    }
+}
+
+#[allow(dead_code)]
+pub fn sample_expression(node: &OperatorNode) -> &ScalarExpr {
+    match node.expect_non_asap() {
+        NonASAPOp::Project { cols, .. } => {
+            &cols[node.schema.column_id("value").unwrap_or(cols.len() - 1)].expr
+        }
+        NonASAPOp::Filter { pred, .. } => &pred.0,
+        other => panic!("expected sample expression, got {other:?}"),
+    }
+}
diff --git a/crates/frontend-promql/tests/unified_histogram_metadata.rs b/crates/frontend-promql/tests/unified_histogram_metadata.rs
deleted file mode 100644
index 49fdffe02..000000000
--- a/crates/frontend-promql/tests/unified_histogram_metadata.rs
+++ /dev/null
@@ -1,138 +0,0 @@
-//! Type-driven `histogram_quantile` discrimination (issue #79).
-//!
-//! The structural heuristic (`by (le)` / `_bucket` / `le=` matcher) proxies the
-//! argument's sample type. A declared [`HistogramKind`] overrides it, fixing the
-//! heuristic's false-positive and false-negative cases. Undeclared metrics still
-//! fall back to the heuristic.
-
-use asap_frontend_promql::unified::{HistogramCatalog, HistogramKind};
-#[path = "unified_support.rs"]
-mod support;
-use asap_types::ir::{NonASAPOp, OperatorNode};
-use asap_types::pre_asap::AggIntent;
-use asap_types::types::AccuracyTarget;
-use support::{lower_promql, lower_promql_with_histograms};
-
-/// The histogram/quantile intent kind in the lowered tree: `"HQ"` for the
-/// classic-bucket `HistogramQuantile`, `"Q"` for the sketch-able `Quantile`.
-fn quantile_kind(qe: &OperatorNode) -> &'static str {
-    fn walk(e: &OperatorNode) -> Option<&'static str> {
-        match e.expect_non_asap() {
-            NonASAPOp::Aggregate {
-                measures, child, ..
-            } => measures
-                .iter()
-                .find_map(|i| match i {
-                    AggIntent::HistogramQuantile { .. } => Some("HQ"),
-                    AggIntent::Quantile { .. } => Some("Q"),
-                    _ => None,
-                })
-                .or_else(|| walk(child)),
-            NonASAPOp::TimeRange { child, .. }
-            | NonASAPOp::Filter { child, .. }
-            | NonASAPOp::Sort { child, .. }
-            | NonASAPOp::Limit { child, .. }
-            | NonASAPOp::PromqlSubquery { child, .. }
-            | NonASAPOp::Project { child, .. } => walk(child),
-            _ => None,
-        }
-    }
-    walk(qe).expect("a HistogramQuantile or Quantile intent")
-}
-
-fn heuristic(q: &str) -> &'static str {
-    quantile_kind(&lower_promql(q, AccuracyTarget::Exact).unwrap())
-}
-
-fn with_meta(q: &str, catalog: HistogramCatalog) -> &'static str {
-    quantile_kind(&lower_promql_with_histograms(q, AccuracyTarget::Exact, catalog).unwrap())
-}
-
-#[test]
-fn heuristic_baseline_is_unchanged_without_a_catalog() {
-    // Classic buckets are represented; undeclared native samples are rejected.
-    assert_eq!(
-        heuristic(
-            "histogram_quantile(0.9, sum by (le) (rate(http_request_duration_seconds_bucket[5m])))"
-        ),
-        "HQ"
-    );
-    assert!(lower_promql(
-        "histogram_quantile(0.9, native_latency)",
-        AccuracyTarget::Exact
-    )
-    .is_err());
-}
-
-#[test]
-fn declared_classic_bucket_fixes_the_false_negative() {
-    // A classic histogram exposed WITHOUT the `_bucket` suffix and queried with
-    // no `le` grouping/matcher requires an explicit sample-type declaration.
-    let q = "histogram_quantile(0.9, latency_seconds)";
-    assert!(lower_promql(q, AccuracyTarget::Exact).is_err());
-    assert_eq!(
-        with_meta(
-            q,
-            HistogramCatalog::new().with("latency_seconds", HistogramKind::ClassicBucket)
-        ),
-        "HQ",
-        "metadata routes it to exact bucket interpolation"
-    );
-}
-
-#[test]
-fn declared_raw_extension_and_native_gap_override_the_heuristic() {
-    // A metric merely NAMED `…_bucket` that actually holds raw samples / a native
-    // histogram: the heuristic wrongly routes it to bucket interpolation.
-    let q = "histogram_quantile(0.9, foo_bucket)";
-    assert_eq!(
-        heuristic(q),
-        "HQ",
-        "heuristic mis-routes on the `_bucket` name"
-    );
-    assert_eq!(
-        with_meta(
-            q,
-            HistogramCatalog::new().with("foo_bucket", HistogramKind::RawSamples)
-        ),
-        "Q",
-        "raw samples are sketch-able"
-    );
-    let catalog = HistogramCatalog::new().with("foo_bucket", HistogramKind::Native);
-    assert!(lower_promql_with_histograms(q, AccuracyTarget::Exact, catalog.clone()).is_err());
-    assert!(lower_promql_with_histograms("foo_bucket", AccuracyTarget::Exact, catalog).is_err());
-}
-
-#[test]
-fn undeclared_metric_falls_back_to_the_heuristic() {
-    // A catalog that doesn't mention the queried metric leaves the structural
-    // decision in place.
-    let catalog = HistogramCatalog::new().with("some_other_metric", HistogramKind::RawSamples);
-    assert_eq!(
-        with_meta(
-            "histogram_quantile(0.9, sum by (le) (x_bucket))",
-            catalog.clone()
-        ),
-        "HQ"
-    );
-    assert!(lower_promql_with_histograms(
-        "histogram_quantile(0.9, native_thing)",
-        AccuracyTarget::Exact,
-        catalog
-    )
-    .is_err());
-}
-
-#[test]
-fn the_catalog_does_not_leak_across_calls() {
-    // The ambient catalog is scoped to the single `_with_histograms` call; a
-    // subsequent plain `lower_promql` sees no metadata (guards against a
-    // thread-local that isn't cleaned up).
-    let _ = with_meta(
-        "histogram_quantile(0.9, foo_bucket)",
-        HistogramCatalog::new().with("foo_bucket", HistogramKind::RawSamples),
-    );
-    // `foo_bucket` would be sketch-able under that catalog, but with none it must
-    // revert to the heuristic (the `_bucket` name → HistogramQuantile).
-    assert_eq!(heuristic("histogram_quantile(0.9, foo_bucket)"), "HQ");
-}
diff --git a/crates/frontend-promql/tests/unified_promql_conformance.rs b/crates/frontend-promql/tests/unified_promql_conformance.rs
deleted file mode 100644
index 6ea89a0bb..000000000
--- a/crates/frontend-promql/tests/unified_promql_conformance.rs
+++ /dev/null
@@ -1,2208 +0,0 @@
-//! PromQL **semantic conformance** for the parse-to-canonical-tree lowering.
-//!
-//! We *lower* PromQL to the intent algebra; we do not *execute* it. So "same
-//! semantic job as Prometheus" here means: for each canonical query, does the
-//! canonical tree encode the **documented PromQL meaning** — and where we knowingly
-//! diverge (reject, approximate, or drop a modifier), is that pinned by a test
-//! so it stays visible?
-//!
-//! Sources for the queries + their semantics:
-//! - PromQL basics (data types, selectors, offset/@/subquery):
-//!   <https://prometheus.io/docs/prometheus/latest/querying/basics/>
-//! - PromLabs PromQL cheat sheet (common real-world queries by category):
-//!   <https://promlabs.com/promql-cheat-sheet/>
-//! - Prometheus' own engine test corpus (these are *execution* tests —
-//!   load → eval → expect values — so they define semantics we mirror as
-//!   *structure*): <https://github.com/prometheus/prometheus/tree/main/promql/promqltest/testdata>
-//!   Relevant files, mapped to the sections below: selectors.test,
-//!   aggregators.test, functions.test, histograms.test, operators.test,
-//!   subquery.test, at_modifier.test, literals.test, limit.test
-//!
-//! Legend used in test names:
-//! - (no suffix)  — we lower it and the canonical intent matches PromQL.
-//! - `__GAP`      — a PromQL capability we don't *yet* support. It is **cleanly
-//!   rejected** (never silently mislowered), and pinned here so adding support
-//!   later flips the assertion deliberately.
-//!
-//! NOTE: the formerly-silent divergences (`group`→sum, dropped `offset`/`@`,
-//! `changes`/`resets`→count) are now rejected rather than mislowered — see the
-//! equivalence suite (`promql_equivalence.rs`) and section L below.
-
-// `__GAP`-suffixed test names intentionally SHOUT the documented divergences.
-#![allow(non_snake_case)]
-
-use std::rc::Rc;
-use std::time::Duration;
-
-use asap_frontend_promql::unified::PromqlError as LoweringError;
-#[path = "unified_support.rs"]
-mod support;
-use asap_types::ir::{
-    BinaryOperator, ExprSemantics, NonASAPOp, OperatorNode, ScalarExpr, TimeRangeKind,
-};
-use asap_types::pre_asap::schema::DataType;
-use asap_types::pre_asap::{
-    AggIntent, ArithmeticOpKind, AtModifier, BinaryOpKind, CompareOpKind, PromQLVectorSetOpKind,
-    Reduction, SampleKind, ScalarValue, Source, TimeFunc,
-};
-use asap_types::types::AccuracyTarget;
-use support::{lower_promql, promql_scalar};
-
-// ── harness helpers ─────────────────────────────────────────────────────────────
-
-/// Lower, expecting success.
-fn ok(q: &str) -> Rc<OperatorNode> {
-    lower_promql(q, AccuracyTarget::Exact)
-        .unwrap_or_else(|e| panic!("expected {q:?} to lower, got error: {e}"))
-}
-
-/// Lower, expecting a clean `LoweringError` (an unsupported capability).
-fn rejected(q: &str) -> LoweringError {
-    match lower_promql(q, AccuracyTarget::Exact) {
-        Err(e) => e,
-        Ok(tree) => panic!("expected {q:?} to be rejected, but it lowered to: {tree:?}"),
-    }
-}
-
-/// Every `AggIntent` anywhere in the tree, root-to-leaf.
-fn intents(e: &OperatorNode) -> Vec<AggIntent> {
-    let mut out = Vec::new();
-    collect(e, &mut out);
-    out
-}
-
-/// `AggIntent` only ever lives in `Aggregate.measures`, never in a scalar
-/// position (issue #205); `children()` also descends into the operators a
-/// scalar position reads (`scalar(v)`).
-fn collect(e: &OperatorNode, out: &mut Vec<AggIntent>) {
-    if let Some(NonASAPOp::Aggregate { measures, .. }) = e.non_asap() {
-        out.extend(measures.iter().cloned());
-    }
-    for child in e.children() {
-        collect(child, out);
-    }
-}
-
-/// The first `Scan` reached by descending single-child nodes, with its metric
-/// name and predicate count.
-fn first_scan(e: &OperatorNode) -> (String, usize) {
-    match e.expect_non_asap() {
-        NonASAPOp::Scan {
-            source, predicates, ..
-        } => {
-            let name = match source {
-                Source::TimeSeries { metric } => metric.clone(),
-                Source::Table { table_ref } => table_ref.clone(),
-            };
-            (name, predicates.len())
-        }
-        NonASAPOp::TimeRange { child, .. }
-        | NonASAPOp::TimeShift { child, .. }
-        | NonASAPOp::Aggregate { child, .. }
-        | NonASAPOp::Filter { child, .. }
-        | NonASAPOp::Sort { child, .. }
-        | NonASAPOp::Limit { child, .. }
-        | NonASAPOp::PromqlSubquery { child, .. } => first_scan(child),
-        other => panic!("no Scan reachable from {other:?}"),
-    }
-}
-
-fn has<F: Fn(&AggIntent) -> bool>(e: &OperatorNode, pred: F) -> bool {
-    intents(e).iter().any(pred)
-}
-
-/// Whether the tree contains a `Mul`-by-`ScalarExpr(-1)` anywhere — the shape unary
-/// negation lowers to (issue #36).
-fn negates_via_scalar(e: &OperatorNode) -> bool {
-    fn negative(expr: &ScalarExpr) -> bool {
-        matches!(expr, ScalarExpr::Negative { .. }) || expr.children().iter().any(|e| negative(e))
-    }
-    e.expect_non_asap()
-        .scalar_exprs()
-        .iter()
-        .any(|e| negative(e))
-        || e.children().iter().any(|e| negates_via_scalar(e))
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// A. Selectors & label matchers           (basics §"Instant/Range Vector
-//    Selectors"; selectors.test)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn instant_vector_selector() {
-    // SEMANTICS: bare metric → instant vector (latest sample per series).
-    let (metric, preds) = first_scan(&ok("node_cpu_seconds_total"));
-    assert_eq!(metric, "node_cpu_seconds_total");
-    assert_eq!(preds, 0, "no label matchers → no predicates");
-}
-
-#[test]
-fn promql_scan_schema_is_open() {
-    // A schemaless PromQL leaf is *open*: the metric's full label set is
-    // runtime-only, so the binding schema lists only the (ts, value) floor +
-    // referenced labels and may be a subset of the runtime row.
-    let qe = ok("node_cpu_seconds_total");
-    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
-        panic!("expected a TimeRange for a bare selector, got {qe:?}");
-    };
-    let NonASAPOp::Scan { schema, .. } = child.expect_non_asap() else {
-        panic!("expected a Scan inside the TimeRange, got {qe:?}");
-    };
-    assert!(
-        !schema.closed,
-        "a schemaless PromQL scan has an open schema"
-    );
-}
-
-#[test]
-fn label_matchers_become_scan_predicates() {
-    // SEMANTICS: `=`, `!=`, `=~`, `!~` filter series; one conjunct per matcher.
-    let (_, preds) = first_scan(&ok(
-        r#"http_requests_total{job!="x",path=~"/api/.*",env!~"dev"}"#,
-    ));
-    assert_eq!(preds, 3, "three matchers → three Scan predicates");
-}
-
-#[test]
-fn name_label_selects_the_metric() {
-    // SEMANTICS: the metric name is the internal `__name__` label.
-    let (metric, preds) = first_scan(&ok(r#"{__name__="up"}"#));
-    assert_eq!(metric, "up");
-    assert_eq!(preds, 0, "__name__ is the metric, not a residual predicate");
-}
-
-#[test]
-fn name_regex_matcher_is_rejected__GAP() {
-    // A `__name__=~` / `!~` / `!=` matcher selects *across* metric names, which
-    // the single-metric `Source::TimeSeries { metric }` can't represent. It is
-    // rejected (issue #67) rather than silently mislowered to a literal metric
-    // named after the pattern (`{__name__=~"node_.*"}` → `Source("node_.*")`).
-    // Full support needs a wildcard/regex `Source` in the IR.
-    let _ = rejected(r#"{__name__=~"node_.*"}"#);
-    let _ = rejected(r#"{__name__!~"x", job="y"}"#);
-    // Equality still names the metric (regression guard for the fix).
-    let (metric, _) = first_scan(&ok(r#"{__name__="up"}"#));
-    assert_eq!(metric, "up");
-}
-
-#[test]
-fn range_vector_selector_is_time_range() {
-    // SEMANTICS: `[5m]` turns an instant vector into a range vector,
-    // represented in the canonical tree as a dedicated `TimeRange` node.
-    let qe = ok("node_cpu_seconds_total[5m]");
-    let NonASAPOp::TimeRange { range, .. } = qe.expect_non_asap() else {
-        panic!("expected TimeRange for a range-vector selector, got {qe:?}");
-    };
-    assert_eq!(*range, Duration::from_secs(300));
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// B. Counters: rate / irate / increase     (cheat sheet "Rates of Increase";
-//    functions.test)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn selector_time_ranges_carry_their_kind() {
-    // SEMANTICS: an instant selector reads the latest sample within the
-    // ingestion interval (`Instant`); `m[5m]` is a range selection (`Range`).
-    // Same length is not the same shape: `m` and `m[1s]` stay distinct.
-    assert!(matches!(
-        ok("node_cpu_seconds_total").expect_non_asap(),
-        NonASAPOp::TimeRange {
-            kind: TimeRangeKind::Instant,
-            ..
-        }
-    ));
-    assert!(matches!(
-        ok("node_cpu_seconds_total[5m]").expect_non_asap(),
-        NonASAPOp::TimeRange {
-            kind: TimeRangeKind::Range,
-            ..
-        }
-    ));
-    assert_ne!(
-        ok("node_cpu_seconds_total"),
-        ok("node_cpu_seconds_total[1s]")
-    );
-}
-
-#[test]
-fn rate_range_lives_in_time_range_node() {
-    // SEMANTICS: per-second average rate; the temporal range lives on the
-    // enclosing `TimeRange` node, not inside the intent.
-    let qe = ok("rate(http_requests_total[5m])");
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected Aggregate, got {qe:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
-    let NonASAPOp::TimeRange { range, .. } = child.expect_non_asap() else {
-        panic!("expected TimeRange child, got {child:?}");
-    };
-    assert_eq!(*range, Duration::from_secs(300));
-}
-
-#[test]
-fn irate_maps_to_its_own_intent() {
-    assert!(has(&ok("irate(http_requests_total[1m])"), |i| matches!(
-        i,
-        AggIntent::IRate
-    )));
-}
-
-#[test]
-fn increase_range_lives_in_time_range_node() {
-    let qe = ok("increase(http_requests_total[1h])");
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected Aggregate, got {qe:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Increase]));
-    let NonASAPOp::TimeRange { range, .. } = child.expect_non_asap() else {
-        panic!("expected TimeRange child, got {child:?}");
-    };
-    assert_eq!(*range, Duration::from_secs(3600));
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// C. Aggregation across series             (cheat sheet "Aggregating Over
-//    Multiple Series"; aggregators.test)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn sum_collapses_all_series() {
-    // SEMANTICS: `sum(v)` → one output series. No grouping → no Partition.
-    let qe = ok("sum(node_filesystem_size_bytes)");
-    assert!(matches!(qe.expect_non_asap(), NonASAPOp::Aggregate { .. }));
-    assert!(has(&qe, |i| matches!(i, AggIntent::Sum { .. })));
-}
-
-#[test]
-fn sum_by_groups_via_positional_aggregate() {
-    // SEMANTICS: `by(job,instance)` keeps those labels; the grouping lives on a
-    // positional `Aggregate.by` — the same shape SQL `GROUP BY` produces (not a
-    // name-based Partition). SchemaResolver leaf = [ts, value, instance, job] (referenced
-    // keys appended sorted), so the keys resolve to columns [2, 3].
-    let qe = ok("sum by(job, instance) (node_filesystem_size_bytes)");
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected positional Aggregate for `by(...)`, got {qe:?}");
-    };
-    assert_eq!(
-        reduction,
-        &Reduction::by(vec![2, 3]),
-        "group keys resolve to positional ColumnIds"
-    );
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    assert!(
-        matches!(child.expect_non_asap(), NonASAPOp::TimeRange { child, .. } if matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }))
-    );
-}
-
-#[test]
-fn count_is_row_count() {
-    assert!(has(&ok("count(up)"), |i| matches!(
-        i,
-        AggIntent::Count { .. }
-    )));
-}
-
-#[test]
-fn avg_min_max_stddev_stdvar_quantile_aggregators() {
-    assert!(has(&ok("avg(up)"), |i| matches!(i, AggIntent::Avg { .. })));
-    assert!(has(&ok("min(up)"), |i| matches!(i, AggIntent::Min { .. })));
-    assert!(has(&ok("max(up)"), |i| matches!(i, AggIntent::Max { .. })));
-    assert!(has(&ok("stddev(up)"), |i| matches!(
-        i,
-        AggIntent::StdDev { .. }
-    )));
-    assert!(has(&ok("stdvar(up)"), |i| matches!(
-        i,
-        AggIntent::Variance { .. }
-    )));
-    assert!(has(&ok("quantile(0.5, up)"), |i| matches!(
-        i,
-        AggIntent::Quantile { .. }
-    )));
-}
-
-#[test]
-fn sum_without_groups_by_the_complement() {
-    // SEMANTICS (issue #39): `without(instance)` = group by all labels EXCEPT
-    // instance. The complement can't be enumerated under the open usage-derived
-    // schema, so the excluded label is stored and the kept set is deferred to
-    // the runtime: the grouping is the exclusion form and the output schema
-    // stays OPEN (unlike `by`, which freezes to closed).
-    let qe = ok("sum without(instance) (node_filesystem_size_bytes)");
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected an Aggregate, got {qe:?}");
-    };
-    let by = reduction.expect_reduce();
-    assert!(
-        by.is_without(),
-        "the grouping is the `without` exclusion form"
-    );
-    assert_eq!(by.keys().len(), 1, "the one excluded label (instance)");
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    assert!(
-        !qe.schema.clone().closed,
-        "a `without` result keeps an open schema (kept label set is runtime-only)"
-    );
-}
-
-#[test]
-fn without_on_topk_is_rejected() {
-    // `without(...)` is modelled only for reducing aggregations; on topk/bottomk
-    // (a ranking, not a reduction) it would need without-partitioning, so it is
-    // rejected rather than silently lowered as a `by` (issue #39).
-    let e = rejected("topk without (job) (3, http_requests_total)");
-    assert!(format!("{e}").contains("without"), "got {e}");
-}
-
-#[test]
-fn group_aggregator_lowers_to_a_distinct_intent() {
-    // SEMANTICS (PromQL): `group(v)` returns a constant 1 per group (presence),
-    // NOT a sum. It now lowers to a distinct `Group` intent (never folded onto
-    // `Sum`) — see §S. Regression guard that it is not a `Sum`.
-    let qe = ok("group by (job) (up)");
-    assert!(has(&qe, |i| *i == AggIntent::Group));
-    assert!(!has(&qe, |i| matches!(i, AggIntent::Sum { .. })));
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// D. Two-level: outer aggregation OVER an inner counter  (the canonical
-//    `sum(rate(...))` shape; aggregators.test + functions.test)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn sum_of_rate_is_two_levels() {
-    // SEMANTICS: per-series rate, THEN cross-series sum. Both must survive.
-    let qe = ok("sum(rate(http_requests_total[5m]))");
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate{{Sum}}, got {qe:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    assert!(matches!(
-        child.expect_non_asap(),
-        NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate])
-    ));
-}
-
-#[test]
-fn sum_by_of_rate_groups_outer_level() {
-    // Outer cross-series Sum grouped on positional `Aggregate.by` over the
-    // label-preserving inner Rate. Leaf = [ts, value, instance] → by = [2].
-    let qe = ok("sum by(instance) (rate(node_network_receive_bytes_total[5m]))");
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate grouped by instance, got {qe:?}");
-    };
-    assert_eq!(reduction, &Reduction::by(vec![2]));
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    // child is the inner per-series Rate aggregate.
-    assert!(matches!(
-        child.expect_non_asap(),
-        NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate])
-    ));
-}
-
-#[test]
-fn sum_by_of_over_time_groups_outer_level() {
-    // Outer cross-series Sum grouped on positional `Aggregate.by` over an inner
-    // *per-series* `avg_over_time` — `Window { Aggregate{Avg} }` is label-
-    // preserving, so the key resolves positionally just like the rate case (no
-    // name-based Partition). Leaf = [ts, value, instance] → by = [2].
-    let qe = ok("sum by(instance) (avg_over_time(node_cpu_seconds_total[5m]))");
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate grouped by instance, got {qe:?}");
-    };
-    assert_eq!(reduction, &Reduction::by(vec![2]));
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    // child is the inner per-series reduction: Aggregate{Avg} over TimeRange.
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected Aggregate (per-series avg_over_time) under the Sum, got {child:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Avg { .. }]));
-    assert!(matches!(
-        child.expect_non_asap(),
-        NonASAPOp::TimeRange { .. }
-    ));
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// E. Aggregation over time (per-series)    (cheat sheet "Aggregating Over
-//    Time"; functions.test)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn over_time_functions_reduce_over_time_range() {
-    // SEMANTICS: reduce the samples WITHIN each series over the range →
-    // Aggregate over TimeRange (per-series, label-preserving).
-    for (q, want) in [
-        ("avg_over_time(go_goroutines[5m])", "avg"),
-        ("max_over_time(process_resident_memory_bytes[1d])", "max"),
-        ("min_over_time(go_goroutines[5m])", "min"),
-        ("sum_over_time(go_goroutines[5m])", "sum"),
-        ("count_over_time(go_goroutines[5m])", "count"),
-    ] {
-        let qe = ok(q);
-        assert!(
-            matches!(qe.expect_non_asap(), NonASAPOp::Aggregate { .. }),
-            "{q}: expected Aggregate"
-        );
-        let matched = intents(&qe).iter().any(|i| match want {
-            "avg" => matches!(i, AggIntent::Avg { .. }),
-            "max" => matches!(i, AggIntent::Max { .. }),
-            "min" => matches!(i, AggIntent::Min { .. }),
-            "sum" => matches!(i, AggIntent::Sum { .. }),
-            "count" => matches!(i, AggIntent::Count { .. }),
-            _ => unreachable!(),
-        });
-        assert!(matched, "{q}: missing {want} intent");
-    }
-}
-
-#[test]
-fn quantile_over_time_is_aggregate_over_time_range() {
-    let qe = ok("quantile_over_time(0.9, request_latency_seconds[5m])");
-    assert!(matches!(qe.expect_non_asap(), NonASAPOp::Aggregate { .. }));
-    assert!(has(
-        &qe,
-        |i| matches!(i, AggIntent::Quantile { q, .. } if (*q - 0.9).abs() < 1e-9)
-    ));
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// F. Histograms                            (cheat sheet "Quantiles from
-//    Histograms"; histograms.test)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn histogram_quantile_over_rate() {
-    // φ-quantile from bucket rates. The `_bucket` metric marks the classic
-    // cumulative-bucket form → `HistogramQuantile` (even without `sum by (le)`).
-    let qe = ok("histogram_quantile(0.9, rate(demo_api_request_duration_seconds_bucket[5m]))");
-    let NonASAPOp::Aggregate { measures, .. } = qe.expect_non_asap() else {
-        panic!("expected Aggregate{{HistogramQuantile}}, got {qe:?}");
-    };
-    assert!(
-        matches!(measures.as_slice(), [AggIntent::HistogramQuantile { q, .. }] if (*q - 0.9).abs() < 1e-9)
-    );
-    assert!(has(&qe, |i| matches!(i, AggIntent::Rate)));
-}
-
-#[test]
-fn histogram_quantile_over_sum_by_le_preserves_le_grouping() {
-    // SEMANTICS: the standard pattern — bucket rates summed by `le`, then the
-    // quantile. The `sum by (le)` aggregation must survive into the
-    // canonical tree.
-    let qe = ok(
-        "histogram_quantile(0.99, sum by(le) (rate(demo_api_request_duration_seconds_bucket[5m])))",
-    );
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate{{HistogramQuantile}}, got {qe:?}");
-    };
-    // `by (le)` marks the classic cumulative-bucket form → `HistogramQuantile`.
-    assert!(matches!(
-        measures.as_slice(),
-        [AggIntent::HistogramQuantile { .. }]
-    ));
-    // `sum by(le)` now survives as a positional Aggregate (by = [2], `le`), over
-    // the inner Rate — no name-based Partition.
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected `sum by(le)` as a positional Aggregate, got {child:?}");
-    };
-    assert_eq!(reduction, &Reduction::by(vec![2]));
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// G. Binary ops: math, matching, comparison  (cheat sheet "Math Between
-//    Series" / "Filtering Series by Value"; operators.test)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn vector_arithmetic() {
-    let qe = ok("node_memory_MemFree_bytes + node_memory_Cached_bytes");
-    let NonASAPOp::BinaryOp {
-        operator: BinaryOperator { kind: op, .. },
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected BinaryOp, got {qe:?}");
-    };
-    assert_eq!(*op, BinaryOpKind::Arithmetic(ArithmeticOpKind::Add));
-}
-
-#[test]
-fn on_matching_with_group_left() {
-    // SEMANTICS: many-to-one matching on a label subset.
-    let qe =
-        ok("rate(demo_cpu_usage_seconds_total[1m]) / on(instance, job) group_left demo_num_cpus");
-    let NonASAPOp::BinaryOp { operator, .. } = qe.expect_non_asap() else {
-        panic!("expected BinaryOp, got {qe:?}");
-    };
-    assert_eq!(
-        operator.kind,
-        BinaryOpKind::Arithmetic(ArithmeticOpKind::Div)
-    );
-    let vm = operator
-        .vector_match
-        .as_ref()
-        .expect("on(...) group_left present");
-    assert_eq!(vm.labels, vec!["instance".to_string(), "job".to_string()]);
-    assert!(
-        vm.grouping.is_some(),
-        "group_left should set the grouping side"
-    );
-}
-
-#[test]
-fn vector_comparison_filters() {
-    // SEMANTICS: `>` between two vectors keeps the LHS series where it holds.
-    let qe = ok("go_goroutines > go_threads");
-    assert!(
-        matches!(qe.expect_non_asap(), NonASAPOp::BinaryOp { operator: BinaryOperator { kind: op, .. }, .. } if *op == BinaryOpKind::Compare(CompareOpKind::Gt))
-    );
-}
-
-#[test]
-fn comparison_bool_modifier_returns_zero_or_one() {
-    // SEMANTICS (operators.test): `bool` turns a filtering comparison into a
-    // 0/1-valued one. On a vector operand it is `return_bool` on the
-    // `BinaryOp`; between two scalars it is a `Case(Compare → 1, else 0)`
-    // scalar expression under PromQL numeric rules — and a scalar comparison
-    // without `bool` is not a PromQL expression at all.
-    let bool_flag = |q: &str| match ok(q).expect_non_asap() {
-        NonASAPOp::BinaryOp { return_bool, .. } => *return_bool,
-        NonASAPOp::Project { .. } => true,
-        NonASAPOp::Filter { .. } => false,
-        other => panic!("expected BinaryOp for {q}, got {other:?}"),
-    };
-    assert!(bool_flag("go_goroutines > bool go_threads"));
-    assert!(bool_flag("go_goroutines > bool 0"));
-    assert!(!bool_flag("go_goroutines > go_threads"));
-    assert!(!bool_flag("go_goroutines > 0"));
-
-    let qe = support::scalar_root("1 < bool 2");
-    let ScalarExpr::Case { branches, .. } = &qe else {
-        panic!("expected a scalar Case, got {qe:?}");
-    };
-    assert!(matches!(
-        branches.as_slice(),
-        [(
-            ScalarExpr::Compare {
-                op: CompareOpKind::Lt,
-                semantics: ExprSemantics::Promql,
-                ..
-            },
-            _
-        )]
-    ));
-    rejected("1 < 2");
-}
-
-#[test]
-fn unary_negation_lowers_as_multiply_by_minus_one() {
-    // SEMANTICS (PromQL, issue #36): `-expr` flips the sign of every sample.
-    // Now that a scalar operand exists (#35), it lowers as `expr * -1` — a `Mul`
-    // BinaryOp of the (label-preserving) vector against `ScalarExpr(-1)`. These are
-    // the five cases the old `__GAP` test pinned as rejected.
-    for q in [
-        "-rate(http_errors_total[5m])",
-        "-some_metric",
-        "-metric_a or -metric_b",
-        "http_requests_total - -http_errors_total",
-        "sum(-node_cpu_seconds_total)",
-    ] {
-        let qe = ok(q);
-        // A `Mul`-by-`-1` against a `ScalarExpr(-1)` appears somewhere in every tree.
-        assert!(
-            negates_via_scalar(&qe),
-            "no `* -1` negation found in {q}: {qe:?}"
-        );
-    }
-
-    let negated = ok("-some_metric");
-    assert!(negates_via_scalar(&negated));
-    assert!(negated.schema.has_promql_series_identity());
-    assert!(negated.schema.time_index.is_some());
-    let summed = ok("sum(-node_cpu_seconds_total)");
-    assert!(has(&summed, |i| matches!(i, AggIntent::Sum { .. })));
-    assert!(negates_via_scalar(&summed));
-}
-
-#[test]
-fn unary_negation_of_constant_folds_to_scalar() {
-    // `-(10*1024*1024)` — the operand is constant-foldable, so negation collapses
-    // to a single negated `ScalarExpr` leaf (no `BinaryOp`), just like a bare literal.
-    assert!(promql_scalar(&support::scalar_root("-(10*1024*1024)"))
-        .is_some_and(|v| (v + 10_485_760.0).abs() < 1e-6));
-}
-
-#[test]
-fn double_unary_negation_nests() {
-    let qe = ok("- -some_metric");
-    let NonASAPOp::Project { child, .. } = qe.expect_non_asap() else {
-        panic!()
-    };
-    assert!(matches!(child.expect_non_asap(), NonASAPOp::Project { .. }));
-    assert!(negates_via_scalar(child));
-}
-
-#[test]
-fn count_maps_to_count_and_inherits_accuracy() {
-    // Counts preserve the workload accuracy target without counting distinct values.
-    let exact = lower_promql("count by (job) (up)", AccuracyTarget::Exact).unwrap();
-    assert!(
-        has(&exact, |i| matches!(
-            i,
-            AggIntent::Count {
-                accuracy: AccuracyTarget::Exact
-            }
-        )),
-        "Count must stay Exact under AccuracyTarget::Exact, got {:?}",
-        intents(&exact)
-    );
-
-    let approx = lower_promql("count by (job) (up)", AccuracyTarget::Epsilon(0.01)).unwrap();
-    assert!(
-        has(&approx, |i| matches!(
-            i,
-            AggIntent::Count {
-                accuracy: AccuracyTarget::Epsilon(e)
-            } if (*e - 0.01).abs() < 1e-9
-        )),
-        "Count must carry the approximate target, got {:?}",
-        intents(&approx)
-    );
-}
-
-#[test]
-fn scalar_literal_operand_lowers_as_binaryop_scalar() {
-    let qe = ok("node_filesystem_avail_bytes > 10*1024*1024");
-    let ScalarExpr::Compare { op, right, .. } = support::sample_expression(&qe) else {
-        panic!()
-    };
-    assert_eq!(*op, CompareOpKind::Gt);
-    assert_eq!(promql_scalar(right), Some(10_485_760.0));
-}
-
-#[test]
-fn scalar_arithmetic_scales_the_vector() {
-    let qe = ok("rate(m[5m]) * 100");
-    let ScalarExpr::Arithmetic { op, right, .. } = support::sample_expression(&qe) else {
-        panic!()
-    };
-    assert_eq!(*op, ArithmeticOpKind::Mul);
-    assert_eq!(promql_scalar(right), Some(100.0));
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// H. Set operations                        (cheat sheet "Set Operations";
-//    operators.test)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn set_ops_lower_to_binaryop() {
-    // SEMANTICS: or = union of label sets; and = intersection; unless = difference.
-    let set_op = |q: &str| match ok(q).expect_non_asap() {
-        NonASAPOp::BinaryOp { operator, .. } => operator.kind.clone(),
-        other => panic!("expected BinaryOp for {q}, got {other:?}"),
-    };
-    assert_eq!(
-        set_op("up{job=\"a\"} or up{job=\"b\"}"),
-        BinaryOpKind::Set(PromQLVectorSetOpKind::Or)
-    );
-    assert_eq!(
-        set_op("node_network_mtu_bytes and node_up"),
-        BinaryOpKind::Set(PromQLVectorSetOpKind::And)
-    );
-    assert_eq!(
-        set_op("node_network_mtu_bytes unless node_down"),
-        BinaryOpKind::Set(PromQLVectorSetOpKind::Unless)
-    );
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// I. Sorting / top-k                        (cheat sheet "Sorting"/topk;
-//    functions.test, limit.test)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn topk_over_count_is_heavy_hitter() {
-    // SEMANTICS: top-k by frequency → first-class heavy-hitter `TopK` intent.
-    let qe = ok("topk(10, count_over_time(http_requests_total[1m]))");
-    assert!(has(
-        &qe,
-        |i| matches!(i, AggIntent::TopK { k, .. } if *k == 10)
-    ));
-}
-
-#[test]
-fn bottomk_is_generic_sort_limit() {
-    // SEMANTICS: bottom-k → generic ascending order + limit (no sketch).
-    let qe = ok("bottomk(3, count_over_time(http_requests_total[5m]))");
-    assert!(matches!(qe.expect_non_asap(), NonASAPOp::Limit { .. }));
-}
-
-#[test]
-fn topk_over_nested_sum_preserves_weighted_topk_accuracy() {
-    // SEMANTICS (PromQL): `topk(3, sum by(x)(rate(...)))` is extremely common.
-    // The final rates are query-time values. Their ordering does not establish
-    // frequency-sketch membership semantics.
-    let qe = ok("topk(3, sum by(instance) (rate(node_cpu_seconds_total[5m])))");
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected weighted TopK aggregate, got {qe:?}");
-    };
-    assert!(matches!(
-        measures.as_slice(),
-        [AggIntent::TopK { k: 3, .. }]
-    ));
-    // The inner `sum by (instance)` survives as a cross-series Aggregate over the
-    // per-series rate — the nesting the old two-level template could not express.
-    assert!(
-        has(child, |i| matches!(i, AggIntent::Sum { .. }))
-            && has(child, |i| matches!(i, AggIntent::Rate)),
-        "inner sum-over-rate preserved, got {:?}",
-        intents(child)
-    );
-    assert!(has(&qe, |i| matches!(i, AggIntent::TopK { .. })));
-}
-
-#[test]
-fn outer_aggregate_over_nested_aggregate_nests() {
-    // `max(sum by (job) (rate(m[5m])))` — an outer cross-series reduction over a
-    // nested per-group reduction over a per-series rate: three stacked levels the
-    // flat two-level template rejected. Each level survives into the
-    // canonical tree (issue #27).
-    let qe = ok("max(sum by (job) (rate(http_requests_total[5m])))");
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate, got {qe:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Max { .. }]));
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected inner `sum by (job)` Aggregate, got {child:?}");
-    };
-    assert_eq!(
-        reduction,
-        &Reduction::by(vec![2]),
-        "job grouping survives on the inner aggregate"
-    );
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    assert!(has(&qe, |i| matches!(i, AggIntent::Rate)), "rate preserved");
-}
-
-#[test]
-fn outer_group_key_absent_from_nested_aggregate_is_dropped() {
-    // SEMANTICS (PromQL, issue #53): aggregating `by` a label that no input
-    // series carries is valid — every series lands in one group and the
-    // (empty) label is omitted from the output. Here the inner `sum by (group)`
-    // collapses `job` away (its closed output schema is `[group, sum]`), so the
-    // outer `by (job)` groups everything into a single global partition:
-    // the query lowers with the provably-absent key dropped, exactly
-    // `sum(sum by (group)(…))`.
-    let qe = ok(r#"sum(sum by (group)(http_requests{job="api-server"})) by (job)"#);
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate, got {qe:?}");
-    };
-    assert_eq!(
-        reduction,
-        &Reduction::by(vec![]),
-        "absent `job` key dropped → global aggregate"
-    );
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    let NonASAPOp::Aggregate { reduction, .. } = child.expect_non_asap() else {
-        panic!("expected inner `sum by (group)` Aggregate, got {child:?}");
-    };
-    assert_eq!(
-        reduction,
-        &Reduction::by(vec![2]),
-        "inner grouping on `group` survives"
-    );
-}
-
-#[test]
-fn outer_group_key_present_after_inner_aggregate_still_resolves() {
-    // The counterpart guard for #53: when the outer key IS in the inner
-    // aggregate's output (`by (job)` over `sum by (job, group)`), it must keep
-    // resolving positionally — the absent-key drop only fires on provable
-    // absence, never on a resolvable key.
-    let qe = ok("sum(sum by (job, group)(http_requests)) by (job)");
-    let NonASAPOp::Aggregate {
-        reduction, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate, got {qe:?}");
-    };
-    let NonASAPOp::Aggregate {
-        reduction: inner_reduction,
-        ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected inner Aggregate, got {child:?}");
-    };
-    // Inner output schema is [group, job, sum] (keys in label-column order,
-    // labels alphabetical on the scan) → job = col 1.
-    assert_eq!(
-        reduction,
-        &Reduction::by(vec![1]),
-        "outer `job` resolves against the inner output"
-    );
-    assert_eq!(inner_reduction.expect_reduce().len(), 2);
-}
-
-#[test]
-fn outer_group_key_over_binary_op_resolves_on_both_sides() {
-    // Issue #52: an outer aggregate's group key that appears in *neither* side of
-    // a binary op — the metric-name label `__name__`, or a plain `job` — must
-    // still resolve. Each `or` side is bound independently against its own
-    // sub-tree, so the key is seeded as an inherited column on both sides.
-    let qe = ok(r#"sum by (__name__)(metric_a{env="1"} or metric_b{env="2"})"#);
-    let NonASAPOp::Aggregate {
-        reduction, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate, got {qe:?}");
-    };
-    // `__name__` resolves to a single positional id against the binary op output.
-    assert_eq!(
-        reduction.expect_reduce().len(),
-        1,
-        "grouped by the one `__name__` key"
-    );
-    let NonASAPOp::BinaryOp { lhs, rhs, .. } = child.expect_non_asap() else {
-        panic!("expected a BinaryOp child, got {child:?}");
-    };
-    // Both independently-bound sides carry `__name__` at the same position, so
-    // the outer group key is consistent across the union.
-    let (ls, rs) = (lhs.schema.clone(), rhs.schema.clone());
-    assert_eq!(ls.column_id("__name__"), rs.column_id("__name__"));
-    assert_eq!(
-        ls.column_id("__name__"),
-        Some(reduction.expect_reduce().keys()[0])
-    );
-
-    // The general case (a plain label, not just `__name__`) also lowers.
-    assert!(matches!(
-        ok("sum by (job)(metric_a or metric_b)").expect_non_asap(),
-        NonASAPOp::Aggregate { .. }
-    ));
-}
-
-#[test]
-fn aggregate_over_binary_op_nests() {
-    // `sum(rate(a[5m]) + rate(b[5m]))` — an aggregate whose argument is a binary
-    // op over two range vectors. The old template only accepted a single inner
-    // selector/call; now the binary op lowers and the outer sum wraps it.
-    let qe = ok("sum(rate(a[5m]) + rate(b[5m]))");
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate, got {qe:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    assert!(
-        matches!(child.expect_non_asap(), NonASAPOp::BinaryOp { .. }),
-        "argument lowers as a BinaryOp, got {child:?}"
-    );
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// J. Subqueries                            (basics §Subqueries; subquery.test)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn subquery_wraps_inner_query() {
-    // SEMANTICS: `<inst>[range:res]` evaluates the inner query across a range.
-    let qe = ok("rate(demo_api_request_duration_seconds_count[5m])[1h:]");
-    assert!(matches!(
-        qe.expect_non_asap(),
-        NonASAPOp::PromqlSubquery { .. }
-    ));
-    assert!(has(&qe, |i| matches!(i, AggIntent::Rate)));
-}
-
-#[test]
-fn over_time_of_subquery_reduces_per_series() {
-    // SEMANTICS (PromQL): `max_over_time(rate(...)[1h:])` chains a sub-query into
-    // a range-vector function — the sub-query evaluates `rate` across a 1h range,
-    // then `max_over_time` takes the max of those samples *per series*. It lowers
-    // to a per-series `Max` reduction over a `PromqlSubquery` (issue #27).
-    let qe = ok("max_over_time(rate(demo_api_request_duration_seconds_count[5m])[1h:])");
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected an Aggregate at the root, got {qe:?}");
-    };
-    assert_eq!(
-        reduction,
-        &Reduction::PerEntity,
-        "`*_over_time` has no grouping — reduces per series"
-    );
-    assert!(matches!(measures.as_slice(), [AggIntent::Max { .. }]));
-    // The reduction rides directly on the sub-query (the structural range marker
-    // that keeps it label-preserving), which wraps the inner `rate`.
-    assert!(
-        matches!(child.expect_non_asap(), NonASAPOp::PromqlSubquery { .. }),
-        "the `Max` reduces over a PromqlSubquery, got {child:?}"
-    );
-    assert!(intents(&qe).iter().any(|i| matches!(i, AggIntent::Rate)));
-}
-
-#[test]
-fn quantile_over_time_of_subquery_carries_phi() {
-    // The `quantile_over_time` φ parameter is read from arg 0; the sub-query is
-    // arg 1. It lowers to a per-series `Quantile(φ)` over the `PromqlSubquery`.
-    let qe = ok("quantile_over_time(0.9, rate(demo[5m])[1h:])");
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected an Aggregate, got {qe:?}");
-    };
-    assert!(
-        matches!(measures.as_slice(), [AggIntent::Quantile { q, .. }] if (*q - 0.9).abs() < 1e-9)
-    );
-    assert!(matches!(
-        child.expect_non_asap(),
-        NonASAPOp::PromqlSubquery { .. }
-    ));
-}
-
-#[test]
-fn aggregation_over_over_time_of_subquery_keeps_labels() {
-    // `sum by (job) (max_over_time(rate(m[5m])[1h:]))` — the inner
-    // `max_over_time` is per-series (label-preserving), so the `job` label
-    // survives for the OUTER cross-series `sum by (job)` to group on. If the
-    // inner `Max` collapsed labels, `job` would not resolve here.
-    let qe = ok("sum by (job) (max_over_time(rate(demo{job=\"api\"}[5m])[1h:]))");
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate, got {qe:?}");
-    };
-    assert!(
-        matches!(reduction, Reduction::Reduce(by) if !by.is_empty()),
-        "outer `sum by (job)` groups on a label"
-    );
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    // Inner node is the per-series `max_over_time` reduction over the subquery.
-    let NonASAPOp::Aggregate {
-        reduction: inner_reduction,
-        measures: inner_measures,
-        child: inner_child,
-        ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected inner Aggregate, got {child:?}");
-    };
-    assert_eq!(inner_reduction, &Reduction::PerEntity);
-    assert!(matches!(inner_measures.as_slice(), [AggIntent::Max { .. }]));
-    assert!(matches!(
-        inner_child.expect_non_asap(),
-        NonASAPOp::PromqlSubquery { .. }
-    ));
-}
-
-#[test]
-fn nested_subquery_from_prometheus_docs() {
-    // SEMANTICS (PromQL): the *nested sub-query* example from the official docs
-    // (<https://prometheus.io/docs/prometheus/latest/querying/examples/>):
-    //
-    //   max_over_time(deriv(rate(distance_covered_total[5s])[30s:5s])[10m:])
-    //
-    // Two stacked sub-queries, each feeding a range-vector function; the outer
-    // `[10m:]` uses the **default resolution** (no explicit step). Each level
-    // lowers to its own node, so the whole spine pins as:
-    //
-    //   Max ∘ PromqlSubquery{10m, res: None} ∘ Deriv ∘ PromqlSubquery{30s, res: 5s}
-    //       ∘ Rate ∘ TimeRange{5s} ∘ Scan
-    //
-    // Every reduction is per-series (no grouping), so the output schema stays
-    // the label-preserving `[ts, value]`.
-    let qe = ok("max_over_time(deriv(rate(distance_covered_total[5s])[30s:5s])[10m:])");
-
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected `max_over_time` Aggregate at the root, got {qe:?}");
-    };
-    assert_eq!(reduction, &Reduction::PerEntity);
-    assert!(matches!(measures.as_slice(), [AggIntent::Max { .. }]));
-
-    let NonASAPOp::PromqlSubquery {
-        range,
-        resolution,
-        child,
-    } = child.expect_non_asap()
-    else {
-        panic!("expected the outer `[10m:]` PromqlSubquery, got {child:?}");
-    };
-    assert_eq!(*range, Duration::from_secs(600));
-    assert_eq!(*resolution, None, "`[10m:]` keeps the default resolution");
-
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected the `deriv` Aggregate, got {child:?}");
-    };
-    assert_eq!(reduction, &Reduction::PerEntity);
-    assert!(matches!(measures.as_slice(), [AggIntent::Deriv]));
-
-    let NonASAPOp::PromqlSubquery {
-        range,
-        resolution,
-        child,
-    } = child.expect_non_asap()
-    else {
-        panic!("expected the inner `[30s:5s]` PromqlSubquery, got {child:?}");
-    };
-    assert_eq!(*range, Duration::from_secs(30));
-    assert_eq!(*resolution, Some(Duration::from_secs(5)));
-
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected the `rate` Aggregate, got {child:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
-    let NonASAPOp::TimeRange { range, .. } = child.expect_non_asap() else {
-        panic!("expected the `[5s]` TimeRange under rate, got {child:?}");
-    };
-    assert_eq!(*range, Duration::from_secs(5));
-
-    // Per-series end to end: the schema keeps the (ts, value) floor and stays open.
-    let schema = qe.schema.clone();
-    assert_eq!(
-        schema
-            .fields
-            .iter()
-            .map(|c| c.name.as_str())
-            .collect::<Vec<_>>(),
-        vec!["ts", "value"],
-    );
-    assert!(!schema.closed, "per-series chain never freezes the schema");
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// K. Time-shift modifiers                  (basics §Offset/@; at_modifier.test)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn offset_modifier_lowers_to_a_time_shift() {
-    // SEMANTICS (PromQL, issue #40): `offset 5m` shifts the lookback 5m into the
-    // past — a `TimeShift` wrapper over the selector (signed ms; a negative
-    // offset shifts forward). Schema is unchanged (the shift only moves *when*).
-    let qe = ok("http_requests_total offset 5m");
-    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
-        panic!("expected an ingestion TimeRange, got {qe:?}");
-    };
-    let NonASAPOp::TimeShift { shift, child } = child.expect_non_asap() else {
-        panic!("expected a TimeShift, got {qe:?}");
-    };
-    assert_eq!(shift.offset_ms, 300_000);
-    assert!(shift.at.is_none());
-    assert!(matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }));
-
-    // `offset -5m` shifts forward → negative ms.
-    let qe = ok("http_requests_total offset -5m");
-    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
-        panic!("expected an ingestion TimeRange");
-    };
-    let NonASAPOp::TimeShift { shift, .. } = child.expect_non_asap() else {
-        panic!("expected a TimeShift");
-    };
-    assert_eq!(shift.offset_ms, -300_000);
-}
-
-#[test]
-fn at_modifier_lowers_to_a_time_shift() {
-    // SEMANTICS (PromQL, issue #40): `@ <ts>` pins the evaluation to an absolute
-    // instant (PromQL seconds → IR milliseconds); `@ start()` / `@ end()` anchor
-    // to the query range bounds.
-    let qe = ok("http_requests_total @ 1609746000");
-    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
-        panic!("expected an ingestion TimeRange");
-    };
-    let NonASAPOp::TimeShift { shift, .. } = child.expect_non_asap() else {
-        panic!("expected a TimeShift for `@ <ts>`");
-    };
-    assert_eq!(shift.at, Some(AtModifier::Timestamp(1_609_746_000_000)));
-    assert_eq!(shift.offset_ms, 0);
-
-    let qe = ok("http_requests_total @ start()");
-    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
-        panic!("expected an ingestion TimeRange");
-    };
-    let NonASAPOp::TimeShift { shift, .. } = child.expect_non_asap() else {
-        panic!("expected a TimeShift for `@ start()`");
-    };
-    assert_eq!(shift.at, Some(AtModifier::Start));
-
-    // Offset and `@` compose: `@ end() offset 5m` carries both.
-    let qe = ok("http_requests_total @ end() offset 5m");
-    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
-        panic!("expected an ingestion TimeRange, got {qe:?}");
-    };
-    let NonASAPOp::TimeShift { shift, .. } = child.expect_non_asap() else {
-        panic!("expected a TimeShift, got {qe:?}");
-    };
-    assert_eq!(shift.at, Some(AtModifier::End));
-    assert_eq!(shift.offset_ms, 300_000);
-}
-
-#[test]
-fn offset_on_a_ranged_selector_wraps_inside_the_time_range() {
-    // `rate(m[5m] offset 1h)` — the offset is on the ranged selector, so the
-    // `TimeShift` sits *under* the `TimeRange` (the 5m window is taken at the
-    // shifted time), and the whole thing under the per-series `Rate` (#40).
-    let qe = ok("rate(http_requests_total[5m] offset 1h)");
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected the rate Aggregate, got {qe:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
-    let NonASAPOp::TimeRange { child, .. } = child.expect_non_asap() else {
-        panic!("expected a TimeRange under rate, got {child:?}");
-    };
-    let NonASAPOp::TimeShift { shift, child } = child.expect_non_asap() else {
-        panic!("expected a TimeShift under the TimeRange, got {child:?}");
-    };
-    assert_eq!(shift.offset_ms, 3_600_000);
-    assert!(matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }));
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// L. Unsupported functions                 (functions.test) — clean rejection
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn unsupported_functions_are_rejected() {
-    // These parse fine but have no intent-algebra lowering yet. Each must return
-    // a clean LoweringError rather than mislower.
-    for q in [
-        "step()",
-        "range()",
-        r#"histogram_quantiles("le", 0.5, 0.9, x)"#,
-        // NOTE: counter-derivatives (#44), math/trig (#45, §O), presence (#47,
-        // §P), time/calendar (#46, §Q), vector/scalar (#48, §R),
-        // label_replace/label_join (#50, §T) and the extra range reducers +
-        // sort family (#51, §U) now lower — see those sections. `info` (#84),
-        // `min_of`/`max_of` (#89) are pinned in §R / §U.
-    ] {
-        let _ = rejected(q);
-    }
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// M. Counter-derivative range functions     (functions.test; issue #44)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn count_over_time_value_column_is_float64() {
-    // #69: a per-series range reduction produces a PromQL sample value, which is
-    // always float64. `count_over_time`'s `Count` intent types `Int64`, but the
-    // derived `value` column must be `Float64` like every other range reducer.
-    let schema = ok("count_over_time(m[5m])").schema.clone();
-    let value = schema
-        .fields
-        .iter()
-        .find(|c| c.name == "value")
-        .expect("value column");
-    assert_eq!(value.dtype, DataType::Float64);
-}
-
-#[test]
-fn counter_derivative_functions_lower_to_distinct_intents() {
-    // Each range function reduces one series' window to one value per series
-    // (label-preserving), riding on a `TimeRange`, and carries its OWN intent —
-    // deliberately not aliased to rate/increase/count.
-    for (q, want) in [
-        ("changes(m[15m])", AggIntent::Changes),
-        ("delta(m[5m])", AggIntent::Delta),
-        ("idelta(m[5m])", AggIntent::IDelta),
-        ("deriv(m[1h])", AggIntent::Deriv),
-        ("resets(m[1h])", AggIntent::Resets),
-    ] {
-        let qe = ok(q);
-        let NonASAPOp::Aggregate {
-            reduction,
-            measures,
-            child,
-            ..
-        } = qe.expect_non_asap()
-        else {
-            panic!("expected an Aggregate for {q:?}, got {qe:?}");
-        };
-        assert_eq!(
-            reduction,
-            &Reduction::PerEntity,
-            "{q}: per-series, no grouping"
-        );
-        assert_eq!(
-            measures.as_slice(),
-            std::slice::from_ref(&want),
-            "{q}: wrong intent"
-        );
-        assert!(
-            matches!(child.expect_non_asap(), NonASAPOp::TimeRange { .. }),
-            "{q}: reduction rides on a TimeRange, got {child:?}"
-        );
-    }
-}
-
-#[test]
-fn predict_linear_carries_horizon_seconds() {
-    // `predict_linear(v[w], t)` — the 2nd (scalar) arg is the prediction horizon
-    // in seconds; it must be carried in the intent (it changes the result).
-    let qe = ok("predict_linear(node_filesystem_avail_bytes[3h], 86400)");
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected an Aggregate, got {qe:?}");
-    };
-    assert_eq!(
-        measures.as_slice(),
-        &[AggIntent::PredictLinear { seconds: 86400.0 }]
-    );
-    assert!(matches!(
-        child.expect_non_asap(),
-        NonASAPOp::TimeRange { .. }
-    ));
-}
-
-#[test]
-fn double_exponential_smoothing_carries_factors() {
-    let want = AggIntent::DoubleExpSmoothing {
-        smoothing: 0.5,
-        trend: 0.3,
-    };
-    let a = ok("double_exponential_smoothing(m[10m], 0.5, 0.3)");
-    assert_eq!(intents(&a).as_slice(), std::slice::from_ref(&want));
-}
-
-#[test]
-fn aggregation_over_counter_derivative_keeps_labels() {
-    // A counter-derivative is per-series (label-preserving), so an outer
-    // `sum by (job)` can group on a label the inner `changes` preserved.
-    let qe = ok(r#"sum by (job) (changes(m{job="api"}[15m]))"#);
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate, got {qe:?}");
-    };
-    assert!(
-        matches!(reduction, Reduction::Reduce(by) if !by.is_empty()),
-        "outer sum groups on job"
-    );
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    assert!(intents(&qe).iter().any(|i| matches!(i, AggIntent::Changes)));
-    let _ = child;
-}
-
-#[test]
-fn outer_stat_over_counter_derivative_nests_two_levels() {
-    // A cross-series stat over a counter-derivative is a genuine two-level
-    // reduction: the derivative runs per series (inner), the stat aggregates
-    // across series (outer). They must not collapse into one node — and a
-    // grouped outer (`avg by (dc)`) must resolve its key against the labels the
-    // inner reduction preserved, threading any scalar param (predict horizon).
-    let qe = ok("avg by (dc) (predict_linear(m[3h], 3600))");
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate, got {qe:?}");
-    };
-    assert!(
-        matches!(reduction, Reduction::Reduce(by) if !by.is_empty()),
-        "outer `avg by (dc)` groups on a label"
-    );
-    assert!(matches!(measures.as_slice(), [AggIntent::Avg { .. }]));
-    let NonASAPOp::Aggregate {
-        reduction: inner_reduction,
-        measures: inner_measures,
-        ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected inner per-series Aggregate, got {child:?}");
-    };
-    assert_eq!(
-        inner_reduction,
-        &Reduction::PerEntity,
-        "inner derivative stays per-series"
-    );
-    assert_eq!(
-        inner_measures.as_slice(),
-        std::slice::from_ref(&AggIntent::PredictLinear { seconds: 3600.0 })
-    );
-}
-
-#[test]
-fn topk_over_counter_derivative_is_generic_sort_limit() {
-    // `topk(k, deriv(...))` ranks the per-series derivative values — a generic
-    // `Sort + Limit`, NOT a heavy-hitter `TopK` (that's only `count_over_time`).
-    let qe = ok("topk(3, deriv(m[5m]))");
-    let NonASAPOp::Limit {
-        n: Some(n), child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected Limit, got {qe:?}");
-    };
-    assert_eq!(*n, 3);
-    assert!(matches!(child.expect_non_asap(), NonASAPOp::Sort { .. }));
-    assert!(intents(&qe).iter().any(|i| matches!(i, AggIntent::Deriv)));
-    assert!(
-        !intents(&qe)
-            .iter()
-            .any(|i| matches!(i, AggIntent::TopK { .. })),
-        "counter-derivative topk is generic ranking, not a heavy-hitter sketch"
-    );
-}
-
-#[test]
-fn counter_derivative_composes_in_binary_ops() {
-    // As a vector operand: `delta(a[5m]) / delta(b[5m])` is a BinaryOp of two
-    // per-series Delta reductions.
-    let ratio = ok("delta(a[5m]) / delta(b[5m])");
-    let NonASAPOp::BinaryOp {
-        operator: BinaryOperator { kind: op, .. },
-        lhs,
-        rhs,
-        ..
-    } = ratio.expect_non_asap()
-    else {
-        panic!("expected BinaryOp, got {ratio:?}");
-    };
-    assert_eq!(*op, BinaryOpKind::Arithmetic(ArithmeticOpKind::Div));
-    assert!(
-        matches!(lhs.expect_non_asap(), NonASAPOp::Aggregate { measures, .. } if measures.as_slice() == [AggIntent::Delta])
-    );
-    assert!(
-        matches!(rhs.expect_non_asap(), NonASAPOp::Aggregate { measures, .. } if measures.as_slice() == [AggIntent::Delta])
-    );
-
-    // Under an aggregate over a binary op mixing a counter-derivative with
-    // another per-series function: `sum(rate(m[5m]) + changes(m[5m]))`.
-    let mixed = ok("sum(rate(m[5m]) + changes(m[5m]))");
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = mixed.expect_non_asap()
-    else {
-        panic!("expected Aggregate, got {mixed:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    assert!(matches!(
-        child.expect_non_asap(),
-        NonASAPOp::BinaryOp { .. }
-    ));
-    assert!(intents(&mixed).iter().any(|i| matches!(i, AggIntent::Rate)));
-    assert!(intents(&mixed)
-        .iter()
-        .any(|i| matches!(i, AggIntent::Changes)));
-}
-
-#[test]
-fn range_functions_over_a_subquery_reduce_per_series() {
-    // Issue #55 — the whole range-vector family accepts a sub-query argument
-    // (generalizing `*_over_time`, #42): `rate`/`increase`/`irate` and the
-    // counter-derivatives. Each lowers to a per-series `Aggregate{[f]}` directly
-    // over the `PromqlSubquery` — the sub-query is the range context, so there is NO
-    // separate `TimeRange` (that would double the range).
-    for (q, want) in [
-        ("rate(sum(m)[5m:])", AggIntent::Rate),
-        ("increase(sum(m)[5m:])", AggIntent::Increase),
-        ("irate(sum(m)[5m:])", AggIntent::IRate),
-        ("changes(rate(m[5m])[1h:])", AggIntent::Changes),
-        ("delta(sum(m)[5m:])", AggIntent::Delta),
-        ("deriv(sum(m)[10m:])", AggIntent::Deriv),
-        ("resets(sum(m)[5m:])", AggIntent::Resets),
-    ] {
-        let qe = ok(q);
-        let NonASAPOp::Aggregate {
-            reduction,
-            measures,
-            child,
-            ..
-        } = qe.expect_non_asap()
-        else {
-            panic!("{q}: expected an Aggregate, got {qe:?}");
-        };
-        assert_eq!(
-            reduction,
-            &Reduction::PerEntity,
-            "{q}: per-series, no grouping"
-        );
-        assert_eq!(
-            measures.as_slice(),
-            std::slice::from_ref(&want),
-            "{q}: wrong intent"
-        );
-        assert!(
-            matches!(child.expect_non_asap(), NonASAPOp::PromqlSubquery { .. }),
-            "{q}: reduces directly over the PromqlSubquery (no TimeRange), got {child:?}"
-        );
-    }
-}
-
-#[test]
-fn predict_linear_and_double_exp_over_a_subquery_carry_params() {
-    // The scalar params survive the sub-query path.
-    let pl = ok("predict_linear(sum(m)[1h:], 3600)");
-    assert!(intents(&pl).iter().any(
-        |i| matches!(i, AggIntent::PredictLinear { seconds } if (*seconds - 3600.0).abs() < 1e-9)
-    ));
-    let de = ok("double_exponential_smoothing(sum(m)[10m:], 0.5, 0.3)");
-    assert!(intents(&de).iter().any(|i| matches!(
-        i,
-        AggIntent::DoubleExpSmoothing { smoothing, trend }
-            if (*smoothing - 0.5).abs() < 1e-9 && (*trend - 0.3).abs() < 1e-9
-    )));
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// N. Native-histogram accessors            (functions.test; issue #43)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn histogram_quantile_classic_bucket_vs_native() {
-    // Two lowerings of `histogram_quantile(φ, …)`: the classic cumulative-bucket
-    // form → exact `HistogramQuantile`; native samples require a new type.
-    // The classic form is recognised by
-    // `by (le)`, a `_bucket` metric, or an `le` matcher (issue #43).
-    for classic in [
-        "histogram_quantile(0.9, sum by (le) (rate(x_bucket[5m])))",
-        "histogram_quantile(0.9, rate(x_bucket[5m]))", // bare _bucket metric
-        r#"histogram_quantile(0.9, rate(x{le="0.5"}[5m]))"#, // le matcher
-    ] {
-        let qe = ok(classic);
-        assert!(
-            has(
-                &qe,
-                |i| matches!(i, AggIntent::HistogramQuantile { q, .. } if (*q - 0.9).abs() < 1e-9)
-            ),
-            "classic bucket form → HistogramQuantile: {classic}"
-        );
-        assert!(
-            !has(&qe, |i| matches!(i, AggIntent::Quantile { .. })),
-            "{classic}"
-        );
-    }
-    for native in [
-        "histogram_quantile(0.9, my_native_histogram)",
-        "histogram_quantile(0.9, request_duration_seconds)", // raw samples (your extension)
-    ] {
-        rejected(native);
-    }
-}
-
-#[test]
-fn native_histogram_accessors_are_explicit_gaps() {
-    // Native histogram samples have no typed representation yet.
-    for q in [
-        "histogram_count(v)",
-        "histogram_sum(v)",
-        "histogram_avg(v)",
-        "histogram_stddev(v)",
-        "histogram_stdvar(v)",
-    ] {
-        rejected(q);
-    }
-}
-
-#[test]
-fn histogram_fraction_is_an_explicit_gap() {
-    rejected("histogram_fraction(0, 0.2, v)");
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// O. Math / trig scalar-transform functions (functions.test; issue #45)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn math_functions_lower_to_typed_scalar_projections() {
-    for name in [
-        "abs", "ceil", "floor", "sqrt", "ln", "log2", "sgn", "sin", "atanh", "deg", "rad",
-    ] {
-        let query = ok(&format!("{name}(v)"));
-        assert!(
-            matches!(support::sample_expression(&query),ScalarExpr::FunctionCall { name:n,args } if n==&format!("promql_{name}") && args.len()==1)
-        );
-        query.validate_structure().unwrap();
-    }
-}
-
-#[test]
-fn clamp_and_round_carry_their_params() {
-    for (query, params) in [
-        ("clamp(v,0,100)", vec![0.0, 100.0]),
-        ("clamp_min(v,1)", vec![1.0]),
-        ("clamp_max(v,5)", vec![5.0]),
-        ("round(v)", vec![1.0]),
-        ("round(v,5)", vec![5.0]),
-    ] {
-        let node = ok(query);
-        let ScalarExpr::FunctionCall { args, .. } = support::sample_expression(&node) else {
-            panic!()
-        };
-        assert_eq!(
-            args.iter().skip(1).map(promql_scalar).collect::<Vec<_>>(),
-            params.into_iter().map(Some).collect::<Vec<_>>()
-        );
-    }
-}
-
-#[test]
-fn pi_lowers_to_a_scalar_constant() {
-    // `pi()` is the constant π — a `ScalarExpr` leaf, not a `Math` intent.
-    assert!(promql_scalar(&support::scalar_root("pi()"))
-        .is_some_and(|v| (v - std::f64::consts::PI).abs() < 1e-12));
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// P. Presence functions                     (functions.test; issue #47)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn presence_functions_lower_to_presence_intents() {
-    for (q, want) in [
-        (r#"absent(up{job="x"})"#, AggIntent::Absent),
-        ("absent_over_time(m[1h])", AggIntent::AbsentOverTime),
-        ("present_over_time(m[5m])", AggIntent::PresentOverTime),
-    ] {
-        let qe = ok(q);
-        assert!(intents(&qe).contains(&want), "{q}: got {:?}", intents(&qe));
-    }
-}
-
-#[test]
-fn absent_keeps_matcher_labels_for_the_synthesized_output() {
-    // `absent(v)` synthesizes its output labels from `v`'s equality matchers, so
-    // those labels must survive into the schema — here `job` from `{job="x"}`.
-    let qe = ok(r#"absent(up{job="x"})"#);
-    let cols = qe.schema.clone();
-    assert!(
-        cols.fields.iter().any(|c| c.name == "job"),
-        "matcher label `job` kept, got {:?}",
-        cols.fields.iter().map(|c| &c.name).collect::<Vec<_>>()
-    );
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// Q. Time / calendar functions            (functions.test; issue #46)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn time_lowers_to_the_eval_time_scalar() {
-    assert!(matches!(
-        support::scalar_root("time()"),
-        ScalarExpr::EvalTimestamp
-    ));
-}
-
-#[test]
-fn time_minus_vector_is_the_uptime_pattern() {
-    let qe = ok("time() - process_start_time_seconds");
-    assert!(
-        matches!(support::sample_expression(&qe), ScalarExpr::Arithmetic { op: ArithmeticOpKind::Sub, left, .. } if matches!(left.as_ref(), ScalarExpr::EvalTimestamp))
-    );
-    assert!(qe.schema.time_index.is_some());
-}
-
-#[test]
-fn calendar_functions_lower_to_time_fn_intents() {
-    assert!(has(&ok("timestamp(up)"), |i| *i
-        == AggIntent::TimeFn(TimeFunc::Timestamp)));
-    for name in [
-        "minute",
-        "hour",
-        "day_of_week",
-        "day_of_month",
-        "day_of_year",
-        "month",
-        "year",
-        "days_in_month",
-    ] {
-        let query = ok(&format!("{name}(v)"));
-        assert!(
-            matches!(support::sample_expression(&query),ScalarExpr::FunctionCall { name:n,args } if n==&format!("promql_{name}") && args.len()==1)
-        );
-    }
-}
-
-#[test]
-fn no_arg_calendar_function_reads_the_eval_time() {
-    let query = ok("day_of_week()");
-    let NonASAPOp::Project { child, .. } = query.expect_non_asap() else {
-        panic!()
-    };
-    assert!(matches!(
-        child.expect_non_asap(),
-        NonASAPOp::PromqlVectorFromScalar(ScalarExpr::EvalTimestamp)
-    ));
-    assert!(
-        matches!(support::sample_expression(&query),ScalarExpr::FunctionCall { name,.. } if name=="promql_day_of_week")
-    );
-}
-
-#[test]
-fn timestamp_composes_under_an_outer_aggregation() {
-    // `sum by (job) (timestamp(up))` — the per-series `timestamp` transform sits
-    // below an ordinary grouped sum. Both intents must appear in the tree.
-    let qe = ok("sum by (job) (timestamp(up))");
-    assert!(has(&qe, |i| *i == AggIntent::TimeFn(TimeFunc::Timestamp)));
-    assert!(has(&qe, |i| matches!(i, AggIntent::Sum { .. })));
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// R. Type-conversion functions: vector() / scalar()   (functions.test; issue #48)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn vector_promotes_a_scalar_to_a_vector() {
-    // SEMANTICS: `vector(s)` is the scalar→instant-vector bridge — a label-less
-    // single series carrying the scalar's value.
-    let qe = ok("vector(1)");
-    let NonASAPOp::PromqlVectorFromScalar(inner) = qe.expect_non_asap() else {
-        panic!("expected PromqlVectorFromScalar, got {qe:?}");
-    };
-    assert!(matches!(inner, ScalarExpr::Literal(ScalarValue::Float64(v)) if *v == 1.0));
-    // Vector-typed: schema has a time index (a scalar leaf has none).
-    let sch = qe.schema.clone();
-    assert!(sch.time_index.is_some());
-    assert!(sch.fields.iter().any(|c| c.name == "value"));
-}
-
-#[test]
-fn scalar_collapses_a_vector_to_a_scalar() {
-    let qe = support::scalar_root("scalar(node_load1)");
-    let ScalarExpr::PromqlScalarFromVector(inner) = &qe else {
-        panic!()
-    };
-    assert_eq!(first_scan(inner).0, "node_load1");
-}
-
-#[test]
-fn vector_zero_is_a_vector_operand_of_a_set_op() {
-    // `up or vector(0)` — the dead-man's-switch. `or` is a set op between two
-    // vectors, so `vector(0)` must be a vector (a `PromqlVectorFromScalar`), never a
-    // folded scalar operand.
-    let qe = ok("up or vector(0)");
-    let NonASAPOp::BinaryOp {
-        operator: BinaryOperator { kind: op, .. },
-        rhs,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected a BinaryOp, got {qe:?}");
-    };
-    assert_eq!(*op, BinaryOpKind::Set(PromQLVectorSetOpKind::Or));
-    assert!(matches!(
-        rhs.expect_non_asap(),
-        NonASAPOp::PromqlVectorFromScalar(_)
-    ));
-}
-
-#[test]
-fn scalar_of_a_vector_feeds_a_threshold_comparison() {
-    let qe = ok("node_load1 > scalar(node_cpu_count)");
-    let ScalarExpr::Compare { right, .. } = support::sample_expression(&qe) else {
-        panic!()
-    };
-    assert!(matches!(
-        right.as_ref(),
-        ScalarExpr::PromqlScalarFromVector(_)
-    ));
-    assert!(qe.schema.time_index.is_some());
-}
-
-#[test]
-fn info_lowers_to_a_label_enrichment_join() {
-    // `info(v, [selector])` is a label-enrichment *join* against the info
-    // metric(s) — it lowers to an `PromqlInfoEnrich` over the (unchanged) input vector
-    // (issue #84). The value/time axis pass through; the enriched labels are
-    // runtime, so the schema stays the child's.
-    let qe = ok("info(rate(http_requests_total[5m]))");
-    let NonASAPOp::PromqlInfoEnrich { selector, child } = qe.expect_non_asap() else {
-        panic!("expected an PromqlInfoEnrich, got {qe:?}");
-    };
-    assert!(selector.is_empty(), "no selector → default target_info");
-    // The child is the untouched input (a per-series rate reduction here).
-    assert!(has(child, |i| *i == AggIntent::Rate));
-    assert!(qe.schema.clone().time_index.is_some());
-}
-
-#[test]
-fn info_selector_carries_the_info_side_matchers() {
-    // `info(v, {__name__=~".+_info", data=~".+"})` — the selector picks the info
-    // metric(s) via `__name__` and constrains the data labels. Regex / `__name__`
-    // matchers are kept symbolically (not run through the single-metric selector
-    // path).
-    let qe = ok(r#"info(build_info, {__name__=~".+_info", another_data=~".+"})"#);
-    let NonASAPOp::PromqlInfoEnrich { selector, .. } = qe.expect_non_asap() else {
-        panic!("expected an PromqlInfoEnrich, got {qe:?}");
-    };
-    assert_eq!(
-        selector.len(),
-        2,
-        "both selector matchers kept: {selector:?}"
-    );
-    assert!(selector
-        .iter()
-        .any(|m| m.label == "__name__" && m.op == CompareOpKind::Regex));
-    assert!(selector.iter().any(|m| m.label == "another_data"));
-}
-
-#[test]
-fn info_composes_under_an_aggregation_and_over_a_time_shift() {
-    // `sum(info(m))` — enrichment first, then a cross-series sum over it.
-    assert!(has(&ok("sum(info(node_uname_info))"), |i| matches!(
-        i,
-        AggIntent::Sum { .. }
-    )));
-    // `offset` / `@` on the input now lower to a `TimeShift` under the info-join
-    // (issue #40) — the enrichment composes over the shifted selector.
-    assert!(matches!(
-        ok("info(metric @ 60)").expect_non_asap(),
-        NonASAPOp::PromqlInfoEnrich { .. }
-    ));
-    assert!(matches!(
-        ok("info(metric offset 1m)").expect_non_asap(),
-        NonASAPOp::PromqlInfoEnrich { .. }
-    ));
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// S. Extended aggregation operators: group / count_values (aggregators.test; #49)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn group_lowers_to_a_constant_group_intent() {
-    // SEMANTICS: `group(v)` yields a constant 1 per group — a distinct intent,
-    // NOT folded onto `sum` (which would return the value sum instead of 1).
-    let qe = ok("group(up)");
-    let NonASAPOp::Aggregate { measures, .. } = qe.expect_non_asap() else {
-        panic!("expected an Aggregate, got {qe:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Group]));
-    // Output column is the constant-1 `group` value.
-    let sch = qe.schema.clone();
-    assert!(sch.fields.iter().any(|c| c.name == "group"));
-}
-
-#[test]
-fn group_by_keeps_the_grouping_keys() {
-    // `group by (job) (up)` — the grouping keys ride on `Aggregate.by`.
-    let qe = ok("group by (job) (up)");
-    let sch = qe.schema.clone();
-    assert!(sch.fields.iter().any(|c| c.name == "job"));
-    assert!(has(&qe, |i| *i == AggIntent::Group));
-}
-
-#[test]
-fn count_values_groups_by_value_and_synthesizes_a_label() {
-    // SEMANTICS: `count_values("l", v)` groups the input series by their sample
-    // value, counts each distinct value, and emits that value as a new label
-    // `l`. The intent carries the label; schema gains a `Utf8` `l` column.
-    let qe = ok(r#"count_values("version", build_version)"#);
-    let NonASAPOp::Aggregate { measures, .. } = qe.expect_non_asap() else {
-        panic!("expected an Aggregate, got {qe:?}");
-    };
-    assert!(
-        matches!(measures.as_slice(), [AggIntent::CountValues { label }] if label == "version")
-    );
-    let sch = qe.schema.clone();
-    let version = sch
-        .fields
-        .iter()
-        .find(|c| c.name == "version")
-        .expect("synthesized `version` label column");
-    assert_eq!(
-        version.dtype,
-        DataType::Utf8,
-        "the value becomes a string label"
-    );
-    assert!(
-        sch.fields.iter().any(|c| c.name == "count"),
-        "and a count column"
-    );
-}
-
-#[test]
-fn count_values_accepts_a_parenthesised_label_and_by_grouping() {
-    // `count_values by (job) ((("v")), m)` — nested parens around the string
-    // param, plus `by` grouping. Both survive.
-    let qe = ok(r#"count_values by (job) ((("v")), m)"#);
-    assert!(has(
-        &qe,
-        |i| matches!(i, AggIntent::CountValues { label } if label == "v")
-    ));
-    let sch = qe.schema.clone();
-    assert!(sch.fields.iter().any(|c| c.name == "job"));
-    assert!(sch.fields.iter().any(|c| c.name == "v"));
-}
-
-#[test]
-fn count_values_label_colliding_with_a_group_key_is_not_duplicated() {
-    // `count_values by (job)("job", v)` — the synthesized label name collides
-    // with a group-by key. PromQL's synthesized label takes precedence; the
-    // output must carry a single `job` column, never two.
-    let qe = ok(r#"count_values by (job) ("job", version)"#);
-    let sch = qe.schema.clone();
-    let jobs = sch.fields.iter().filter(|c| c.name == "job").count();
-    assert_eq!(jobs, 1, "collision deduped, got {:?}", sch.fields);
-    assert!(sch.fields.iter().any(|c| c.name == "count"));
-}
-
-#[test]
-fn limitk_and_limit_ratio_lower_to_series_sampling() {
-    // `limitk`/`limit_ratio` are series-*sampling* selection — a subset of whole
-    // series kept unchanged (NOT a ranking), so they lower to the dedicated
-    // `PromqlSeriesSample` node, never `topk`'s `Sort → Limit` (issue #86).
-    assert!(matches!(
-        ok("limitk(2, http_requests)").expect_non_asap(),
-        NonASAPOp::PromqlSeriesSample {
-            kind: SampleKind::LimitK(2),
-            ..
-        }
-    ));
-    assert!(matches!(
-        ok("limit_ratio(0.1, http_requests)").expect_non_asap(),
-        NonASAPOp::PromqlSeriesSample { kind: SampleKind::LimitRatio(r), .. } if (r - 0.1).abs() < 1e-9
-    ));
-    // Series-preserving: the output schema equals the input's (ts, value).
-    let sch = ok("limitk(2, http_requests)").schema.clone();
-    assert!(sch.fields.iter().any(|c| c.name == "value"));
-    assert!(sch.time_index.is_some());
-}
-
-#[test]
-fn limit_ratio_keeps_a_negative_ratio_and_clamps_out_of_range() {
-    // A negative ratio selects the complementary fraction — it must survive, not
-    // be normalised away. Out-of-range magnitudes clamp to [-1, 1] (Prometheus).
-    assert!(matches!(
-        ok("limit_ratio(-0.5, http_requests)").expect_non_asap(),
-        NonASAPOp::PromqlSeriesSample { kind: SampleKind::LimitRatio(r), .. } if (r + 0.5).abs() < 1e-9
-    ));
-    assert!(matches!(
-        ok("limit_ratio(1.1, http_requests)").expect_non_asap(),
-        NonASAPOp::PromqlSeriesSample { kind: SampleKind::LimitRatio(r), .. } if (r - 1.0).abs() < 1e-9
-    ));
-}
-
-#[test]
-fn limitk_by_carries_the_grouping_and_composes_in_a_set_op() {
-    // `limitk by (group)` samples per group; the grouping label is seeded.
-    let qe = ok("limitk by (group) (2, http_requests)");
-    let NonASAPOp::PromqlSeriesSample { by, .. } = qe.expect_non_asap() else {
-        panic!("expected a PromqlSeriesSample, got {qe:?}");
-    };
-    assert!(!by.is_empty(), "grouped sampling keeps its `by` keys");
-    // `count(limitk(2, v) and v)` — the surviving series' identity matters, so
-    // the PromqlSeriesSample must be preserved under the set op (it must lower, not reject).
-    assert!(has(
-        &ok("count(limitk(2, http_requests) and http_requests)"),
-        |i| matches!(i, AggIntent::Count { .. })
-    ));
-}
-
-#[test]
-fn dynamic_and_non_finite_sample_params_are_rejected() {
-    // A dynamic k/ratio (not a compile-time constant) or a NaN can't be a static
-    // `PromqlSeriesSample` param — rejected rather than mislowered.
-    let _ = rejected("limitk(NaN, http_requests)");
-    let _ = rejected("limitk(scalar(foo), http_requests)");
-    let _ = rejected("limit_ratio(time() % 17 / 17, http_requests)");
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// T. Label-rewrite functions: label_replace / label_join   (functions.test; #50)
-// ─────────────────────────────────────────────────────────────────────────────
-
-/// Descend single-child nodes to the first `PromqlRelabel`.
-fn first_relabel(e: &OperatorNode) -> &OperatorNode {
-    match e.expect_non_asap() {
-        NonASAPOp::PromqlRelabel { .. } => e,
-        NonASAPOp::Aggregate { child, .. }
-        | NonASAPOp::Filter { child, .. }
-        | NonASAPOp::TimeRange { child, .. }
-        | NonASAPOp::TimeShift { child, .. } => first_relabel(child),
-        other => panic!("no PromqlRelabel reachable from {other:?}"),
-    }
-}
-
-/// True when `value` is a `FunctionCall` with the given name.
-fn is_fn_named(value: &ScalarExpr, name: &str) -> bool {
-    matches!(value, ScalarExpr::FunctionCall { name: n, .. } if n == name)
-}
-
-#[test]
-fn label_replace_is_a_relabel_over_the_vector() {
-    // SEMANTICS: `label_replace(v, dst, repl, src, regex)` rewrites the `dst`
-    // label per series from a regex over `src`; the sample value is untouched.
-    let qe = ok(r#"label_replace(up, "host", "$1", "instance", "(.+):.*")"#);
-    let NonASAPOp::PromqlRelabel { dst, value, child } = qe.expect_non_asap() else {
-        panic!("expected a PromqlRelabel, got {qe:?}");
-    };
-    assert_eq!(dst, "host");
-    // The child is the untouched vector.
-    let (metric, _) = first_scan(child);
-    assert_eq!(metric, "up");
-    // The value expression is a `label_replace` fn reading the `src` label.
-    assert!(is_fn_named(value, "label_replace"));
-    // Output: the child's columns + the synthesized `host` label; value & ts kept.
-    let sch = qe.schema.clone();
-    assert!(sch.fields.iter().any(|c| c.name == "host"));
-    assert!(sch.fields.iter().any(|c| c.name == "value"));
-    assert!(sch.time_index.is_some(), "the vector's time axis survives");
-}
-
-#[test]
-fn label_join_concatenates_source_labels() {
-    // SEMANTICS: `label_join(v, dst, sep, src…)` joins the source labels with
-    // `sep` into `dst`.
-    let qe = ok(r#"label_join(up, "combined", "-", "job", "instance")"#);
-    let NonASAPOp::PromqlRelabel { dst, value, .. } = qe.expect_non_asap() else {
-        panic!("expected a PromqlRelabel, got {qe:?}");
-    };
-    assert_eq!(dst, "combined");
-    assert!(is_fn_named(value, "label_join"));
-    let sch = qe.schema.clone();
-    assert!(sch.fields.iter().any(|c| c.name == "combined"));
-}
-
-#[test]
-fn label_replace_composes_under_an_aggregation() {
-    // `sum by (host) (label_replace(up, "host", "$1", "instance", "(.+):.*"))` —
-    // relabel first, then group by the synthesized label.
-    let qe = ok(r#"sum by (host) (label_replace(up, "host", "$1", "instance", "(.+):.*"))"#);
-    // A PromqlRelabel sits below the outer Sum.
-    let relabel = first_relabel(&qe);
-    assert!(
-        matches!(relabel.expect_non_asap(), NonASAPOp::PromqlRelabel { dst, .. } if dst == "host")
-    );
-    assert!(has(&qe, |i| matches!(i, AggIntent::Sum { .. })));
-    let sch = qe.schema.clone();
-    assert!(sch.fields.iter().any(|c| c.name == "host"));
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// U. Long-tail: extra range reducers + the sort family     (functions.test; #51)
-// ─────────────────────────────────────────────────────────────────────────────
-
-#[test]
-fn extra_over_time_reducers_lower_to_per_series_intents() {
-    // SEMANTICS: each is a per-series reduction of one series' range window to a
-    // single value — a `TimeRange`-wrapped `Aggregate` with the matching intent.
-    for (q, want) in [
-        ("last_over_time(m[5m])", AggIntent::LastOverTime),
-        ("first_over_time(m[5m])", AggIntent::FirstOverTime),
-        ("mad_over_time(m[5m])", AggIntent::MadOverTime),
-        ("ts_of_min_over_time(m[5m])", AggIntent::TsOfMinOverTime),
-        ("ts_of_max_over_time(m[5m])", AggIntent::TsOfMaxOverTime),
-        ("ts_of_first_over_time(m[5m])", AggIntent::TsOfFirstOverTime),
-        ("ts_of_last_over_time(m[5m])", AggIntent::TsOfLastOverTime),
-    ] {
-        let qe = ok(q);
-        assert!(has(&qe, |i| *i == want), "{q}: {:?}", intents(&qe));
-        // Per-series: the range window survives as a `TimeRange`.
-        assert!(
-            matches!(qe.expect_non_asap(), NonASAPOp::Aggregate { child, .. } if matches!(child.expect_non_asap(), NonASAPOp::TimeRange { .. })),
-            "{q} keeps its range as a TimeRange"
-        );
-    }
-}
-
-#[test]
-fn last_over_time_composes_under_an_outer_aggregation() {
-    // `sum by (job) (last_over_time(m[5m]))` — per-series last, THEN cross-series
-    // sum. Both intents survive (issue #27's arbitrary nesting).
-    let qe = ok("sum by (job) (last_over_time(m[5m]))");
-    assert!(has(&qe, |i| *i == AggIntent::LastOverTime));
-    assert!(has(&qe, |i| matches!(i, AggIntent::Sum { .. })));
-}
-
-#[test]
-fn sort_and_sort_desc_reorder_by_value_without_a_limit() {
-    // SEMANTICS: `sort`/`sort_desc` reorder an instant vector by sample value.
-    // Row-preserving → a bare `Sort` (no `Limit`), ascending / descending.
-    for (q, ascending) in [
-        ("sort(http_requests)", true),
-        ("sort_desc(http_requests)", false),
-    ] {
-        let qe = ok(q);
-        let NonASAPOp::Sort { keys, child, .. } = qe.expect_non_asap() else {
-            panic!("{q}: expected a Sort, got {qe:?}");
-        };
-        assert_eq!(keys.len(), 1);
-        assert_eq!(keys[0].ascending, ascending, "{q}");
-        // No Limit above the Sort — every series is preserved.
-        assert!(!matches!(qe.expect_non_asap(), NonASAPOp::Limit { .. }));
-        // The value column is what it ranks on: descend to the scan.
-        let (metric, _) = first_scan(child);
-        assert_eq!(metric, "http_requests");
-    }
-}
-
-#[test]
-fn sort_by_label_orders_on_each_label_in_turn() {
-    // `sort_by_label(v, "group", "instance", "job")` — one ascending sort key per
-    // label, in argument order; the labels are seeded into the schema.
-    let qe = ok(r#"sort_by_label(http_requests, "group", "instance", "job")"#);
-    let NonASAPOp::Sort { keys, .. } = qe.expect_non_asap() else {
-        panic!("expected a Sort, got {qe:?}");
-    };
-    assert_eq!(keys.len(), 3, "one key per label");
-    assert!(keys.iter().all(|k| k.ascending));
-    let sch = qe.schema.clone();
-    for label in ["group", "instance", "job"] {
-        assert!(sch.fields.iter().any(|c| c.name == label), "{label} seeded");
-    }
-}
-
-#[test]
-fn sort_by_label_desc_is_descending() {
-    let qe = ok(r#"sort_by_label_desc(http_requests, "instance")"#);
-    let NonASAPOp::Sort { keys, .. } = qe.expect_non_asap() else {
-        panic!("expected a Sort, got {qe:?}");
-    };
-    assert!(keys.iter().all(|k| !k.ascending));
-}
-
-#[test]
-fn min_of_max_of_fold_constant_scalars() {
-    // `min_of`/`max_of` are n-ary scalar reducers. When every argument is a
-    // constant they constant-fold to a `ScalarExpr` leaf, just like scalar
-    // arithmetic (#35) — the only form the intent algebra can hold (#89).
-    assert_eq!(
-        promql_scalar(&support::scalar_root("min_of(3, 5)")),
-        Some(3.0)
-    );
-    assert_eq!(
-        promql_scalar(&support::scalar_root("max_of(3, 5)")),
-        Some(5.0)
-    );
-    assert_eq!(
-        promql_scalar(&support::scalar_root("min_of(-2, -5)")),
-        Some(-5.0)
-    );
-    // Nested folds and use as a threshold operand.
-    assert_eq!(
-        promql_scalar(&support::scalar_root("max_of(min_of(2, 3), 10)")),
-        Some(10.0)
-    );
-    let qe = ok("up > max_of(1, 2)");
-    let ScalarExpr::Compare { right: rhs, .. } = support::sample_expression(&qe) else {
-        panic!("{qe:?}")
-    };
-    assert_eq!(promql_scalar(rhs), Some(2.0));
-}
-
-#[test]
-fn min_of_max_of_ignore_nan_like_the_min_max_aggregators() {
-    // A NaN argument is skipped (Prometheus `min`/`max` NaN semantics).
-    assert_eq!(
-        promql_scalar(&support::scalar_root("max_of(3, NaN)")),
-        Some(3.0)
-    );
-    assert_eq!(
-        promql_scalar(&support::scalar_root("min_of(NaN, 3)")),
-        Some(3.0)
-    );
-}
-
-#[test]
-fn non_constant_min_of_max_of_is_rejected__GAP() {
-    // A dynamic argument (`step()` — itself unsupported, #89) can't be folded to
-    // a constant and there is no scalar min/max node, so it stays rejected
-    // rather than mislowered. These forms also only appear inside unsupported
-    // dynamic range / offset positions in the corpus.
-    let _ = rejected("min_of(step(), 1s)");
-    let _ = rejected("max_of(min_of(step() + 1, 1h), 1ms)");
-}
diff --git a/crates/frontend-promql/tests/unified_promql_lowering.rs b/crates/frontend-promql/tests/unified_promql_lowering.rs
deleted file mode 100644
index de769361e..000000000
--- a/crates/frontend-promql/tests/unified_promql_lowering.rs
+++ /dev/null
@@ -1,1615 +0,0 @@
-//! End-to-end tests for PromQL → unresolved → canonical tree lowering.
-
-use std::rc::Rc;
-use std::time::Duration;
-
-use asap_types::ir::{
-    BinaryOperator, ExprSemantics, NonASAPOp, OperatorNode, ScalarExpr, TimeRangeKind,
-};
-use asap_types::pre_asap::{
-    AggIntent, ArithmeticOpKind, BinaryOpKind, CompareOpKind, Reduction, ScalarValue, Source,
-};
-use asap_types::types::AccuracyTarget;
-use asap_types::workload::{
-    AccuracyRequirement, BatchEntry, DataWorkload, DurationMs, Evidence, PlanningWorkload,
-    Predictability, Query, QueryLanguage, QueryRequirements, QueryWorkload, TimeSelection,
-};
-
-use asap_frontend_promql::unified::{lower_promql_workload, PromqlError as LoweringError};
-#[path = "unified_support.rs"]
-mod support;
-use support::lower_promql;
-
-fn lower(q: &str) -> Rc<OperatorNode> {
-    lower_promql(q, AccuracyTarget::Exact).unwrap_or_else(|e| panic!("lower failed for {q:?}: {e}"))
-}
-
-#[test]
-fn frequency_extensions_lower_to_explicit_frequency_statistics() {
-    // ProjectASAP extensions reduce a frequency vector; numeric sample norms
-    // have different semantics and must never be silently aliased here.
-    for (query, expected) in [
-        (
-            "entropy_over_time(cpu_usage[5m])",
-            AggIntent::FrequencyEntropy {
-                col: None,
-                accuracy: AccuracyTarget::Exact,
-            },
-        ),
-        (
-            "l2_over_time(cpu_usage[5m])",
-            AggIntent::FrequencyL2 {
-                col: None,
-                accuracy: AccuracyTarget::Exact,
-            },
-        ),
-    ] {
-        assert!(all_intents(&lower(query))
-            .iter()
-            .any(|intent| std::mem::discriminant(intent) == std::mem::discriminant(&expected)));
-    }
-}
-
-#[test]
-fn distinct_over_time_preserves_cardinality_accuracy_and_nested_windows() {
-    // Distinct counts sample values, not samples or series; all lowering routes
-    // retain the caller's accuracy requirement, including subquery arguments.
-    for query in [
-        "distinct_over_time(cpu_usage{job=\"worker\"}[5m] offset 1h)",
-        "distinct_over_time((cpu_usage + 1)[5m:1m])",
-        "sum by(job)(distinct_over_time(cpu_usage[5m]))",
-    ] {
-        for accuracy in [AccuracyTarget::Exact, AccuracyTarget::Epsilon(0.02)] {
-            let tree = lower_promql(query, accuracy.clone()).unwrap();
-            let mut intents = Vec::new();
-            collect_intents(&tree, &mut intents);
-            assert!(
-                intents.iter().any(|intent| matches!(
-                    intent, AggIntent::Cardinality { accuracy: actual, .. } if actual == &accuracy
-                )),
-                "{query}: {tree:?}"
-            );
-            assert!(!intents
-                .iter()
-                .any(|intent| matches!(intent, AggIntent::Count { .. })));
-        }
-    }
-}
-
-// ── Bare selectors & label matchers (folded onto Scan.predicates) ───────────────
-
-#[test]
-fn bare_selector_is_scan_with_predicates() {
-    let qe = lower(r#"http_requests_total{env="prod",status!="500"}"#);
-    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
-        panic!("expected TimeRange, got {qe:?}");
-    };
-    let NonASAPOp::Scan {
-        source, predicates, ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected Scan, got {qe:?}");
-    };
-    assert!(matches!(source, Source::TimeSeries { metric } if metric == "http_requests_total"));
-    // The converter splits the matcher conjunction into one predicate per
-    // conjunct on the Scan.
-    assert_eq!(predicates.len(), 2);
-    assert!(predicates
-        .iter()
-        .all(|p| matches!(&p.0, ScalarExpr::Compare { .. })));
-}
-
-#[test]
-fn regex_matcher_lowers_to_regex_compareop() {
-    let qe = lower(r#"http_requests_total{path=~"/api/.*"}"#);
-    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
-        panic!("expected TimeRange, got {qe:?}");
-    };
-    let NonASAPOp::Scan {
-        predicates, schema, ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected Scan, got {qe:?}");
-    };
-    let ScalarExpr::Compare {
-        left, op, right, ..
-    } = &predicates[0].0
-    else {
-        panic!("expected Compare, got {:?}", predicates[0].0);
-    };
-    assert_eq!(*op, CompareOpKind::Regex);
-    // The label matcher's column is resolved positionally against the scan schema.
-    let path_id = schema.column_id("path").expect("path in scan schema");
-    assert!(matches!(left.as_ref(), ScalarExpr::Column(id) if *id == path_id));
-    assert!(matches!(right.as_ref(), ScalarExpr::Literal(ScalarValue::Utf8(v)) if v == "/api/.*"));
-}
-
-// ── *_over_time → Aggregate over TimeRange ──────────────────────────────────────
-
-#[test]
-fn quantile_over_time_is_time_range_aggregate() {
-    let qe = lower(r#"quantile_over_time(0.99, http_request_duration{env="prod"}[5m])"#);
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected Aggregate, got {qe:?}");
-    };
-    assert_eq!(reduction, &Reduction::PerEntity);
-    assert!(
-        matches!(measures.as_slice(), [AggIntent::Quantile { q, .. }] if (*q - 0.99).abs() < 1e-9)
-    );
-    let NonASAPOp::TimeRange { range, child, .. } = child.expect_non_asap() else {
-        panic!("expected TimeRange child, got {child:?}");
-    };
-    assert_eq!(*range, Duration::from_secs(300));
-    // The label matcher folded onto the Scan.
-    assert!(
-        matches!(child.expect_non_asap(), NonASAPOp::Scan { predicates, .. } if predicates.len() == 1)
-    );
-}
-
-#[test]
-fn outer_sum_by_over_quantile_over_time_groups_positionally() {
-    // `sum by (host) (quantile_over_time(...))`: inner per-series
-    // quantile-over-time (label-preserving), then an outer cross-series sum
-    // grouped on a positional `Aggregate.by` — the same shape SQL produces, not
-    // a name-based Partition. Leaf = [ts, value, host, service] (referenced
-    // names appended sorted) → host = col 2.
-    let qe = lower(r#"sum by (host) (quantile_over_time(0.99, latency{service="web"}[5m]))"#);
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate grouped by host, got {qe:?}");
-    };
-    assert_eq!(reduction, &Reduction::by(vec![2]));
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    // Inner: Aggregate{Quantile} over TimeRange (per-series over_time reduction).
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected Aggregate (quantile_over_time) under the outer Sum, got {child:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Quantile { .. }]));
-    assert!(matches!(
-        child.expect_non_asap(),
-        NonASAPOp::TimeRange { .. }
-    ));
-}
-
-#[test]
-fn avg_over_time_maps_to_avg_intent() {
-    let qe = lower("avg_over_time(cpu_seconds_total[10m])");
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected Aggregate, got {qe:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Avg { .. }]));
-    let NonASAPOp::TimeRange { range, .. } = child.expect_non_asap() else {
-        panic!("expected TimeRange child, got {child:?}");
-    };
-    assert_eq!(*range, Duration::from_secs(600));
-}
-
-#[test]
-fn stddev_and_stdvar_over_time() {
-    let qe = lower("stddev_over_time(m[5m])");
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected Aggregate");
-    };
-    assert!(matches!(
-        measures.as_slice(),
-        [AggIntent::StdDev {
-            population: true,
-            ..
-        }]
-    ));
-    assert!(matches!(
-        child.expect_non_asap(),
-        NonASAPOp::TimeRange { .. }
-    ));
-
-    let qe = lower("stdvar_over_time(m[5m])");
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected Aggregate");
-    };
-    assert!(matches!(
-        measures.as_slice(),
-        [AggIntent::Variance {
-            population: true,
-            ..
-        }]
-    ));
-    assert!(matches!(
-        child.expect_non_asap(),
-        NonASAPOp::TimeRange { .. }
-    ));
-}
-
-#[test]
-fn histogram_quantile_wraps_inner_in_quantile() {
-    // The argument's structure (here `rate`) is preserved *under* the quantile,
-    // not squashed away. The `_bucket` metric + `le` matcher mark the classic
-    // form → `HistogramQuantile` over `Aggregate{Rate}` over Scan.
-    let qe = lower(r#"histogram_quantile(0.95, rate(http_duration_seconds_bucket{le="0.5"}[5m]))"#);
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate{{HistogramQuantile}}, got {qe:?}");
-    };
-    assert!(
-        matches!(measures.as_slice(), [AggIntent::HistogramQuantile { q, .. }] if (*q - 0.95).abs() < 1e-9)
-    );
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected inner Aggregate{{Rate}}, got {child:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
-    let NonASAPOp::TimeRange {
-        range,
-        child: tr_child,
-        ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected TimeRange under Rate, got {child:?}");
-    };
-    assert_eq!(*range, Duration::from_secs(300));
-    assert!(
-        matches!(tr_child.expect_non_asap(), NonASAPOp::Scan { predicates, .. } if predicates.len() == 1)
-    );
-}
-
-#[test]
-fn histogram_quantile_over_sum_by_le_preserves_grouping() {
-    // The canonical Prometheus histogram pattern. Previously returned
-    // UnsupportedFeature because `extract_matrix` couldn't see through the
-    // `sum by (le)` aggregate; now the `le` grouping survives into the
-    // canonical tree.
-    let qe = lower(r#"histogram_quantile(0.99, sum by (le) (rate(http_requests_bucket[5m])))"#);
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate{{HistogramQuantile}}, got {qe:?}");
-    };
-    // The `by (le)` grouping marks the classic cumulative-bucket form.
-    assert!(
-        matches!(measures.as_slice(), [AggIntent::HistogramQuantile { q, .. }] if (*q - 0.99).abs() < 1e-9)
-    );
-    // `sum by (le)` survives as a positional Aggregate (by = [2], `le`) over the
-    // inner Rate — no name-based Partition.
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected `sum by (le)` as a positional Aggregate, got {child:?}");
-    };
-    assert_eq!(reduction, &Reduction::by(vec![2]));
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-}
-
-/// The classic `histogram_quantile` aggregate: its `without` keys, `le`
-/// column, and output column names.
-fn classic_histogram(qe: &OperatorNode) -> (Vec<usize>, usize, Vec<String>) {
-    let NonASAPOp::Aggregate {
-        reduction: Reduction::Reduce(by),
-        measures,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected a reducing Aggregate, got {qe:?}");
-    };
-    let [AggIntent::HistogramQuantile { le, .. }] = measures.as_slice() else {
-        panic!("expected HistogramQuantile, got {measures:?}");
-    };
-    assert!(by.is_without(), "histogram_quantile groups without (le)");
-    let names = qe.schema.fields.iter().map(|c| c.name.clone()).collect();
-    (by.keys().to_vec(), *le, names)
-}
-
-// A classic histogram_quantile groups `without (le)` and names the child's
-// `le` column, even when no matcher or grouping mentions `le`.
-#[test]
-fn classic_histogram_quantile_groups_without_le() {
-    let qe = lower("histogram_quantile(0.9, rate(http_duration_seconds_bucket[5m]))");
-    let (keys, le, names) = classic_histogram(&qe);
-    let NonASAPOp::Aggregate { child, .. } = qe.expect_non_asap() else {
-        unreachable!()
-    };
-    let child = &child.schema;
-    assert_eq!(child.fields[le].name, "le");
-    assert_eq!(keys, vec![le]);
-    assert_eq!(names, vec!["histogram_quantile"]);
-}
-
-// An explicit `sum by (le, job)` argument keeps `job` and drops `le` and the
-// renamed sample value from the output labels.
-#[test]
-fn classic_histogram_quantile_over_sum_by_keeps_other_labels() {
-    let qe =
-        lower("histogram_quantile(0.9, sum by (le, job) (rate(http_duration_seconds_bucket[5m])))");
-    let (keys, le, names) = classic_histogram(&qe);
-    // `sum by (le, job)` outputs `[job, le, sum]`.
-    assert_eq!((keys, le), (vec![1], 1));
-    assert_eq!(names, vec!["job", "histogram_quantile"]);
-}
-
-// Out-of-range and NaN quantiles lower unchanged; execution returns -Inf/+Inf/NaN.
-#[test]
-fn classic_histogram_quantile_keeps_out_of_range_quantiles() {
-    for (query, expected) in [
-        ("histogram_quantile(-1, x_bucket)", -1.),
-        ("histogram_quantile(2, x_bucket)", 2.),
-    ] {
-        let root = lower(query);
-        let NonASAPOp::Aggregate { measures, .. } = root.expect_non_asap() else {
-            panic!("{query}");
-        };
-        assert!(
-            matches!(measures.as_slice(), [AggIntent::HistogramQuantile { q, .. }] if *q == expected)
-        );
-    }
-    let root = lower("histogram_quantile(NaN, x_bucket)");
-    let NonASAPOp::Aggregate { measures, .. } = root.expect_non_asap() else {
-        panic!("NaN");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::HistogramQuantile { q, .. }] if q.is_nan()));
-}
-
-// An argument whose closed output lacks `le` has no buckets. Prometheus
-// returns an empty vector; lowering rejects it rather than guess a column.
-#[test]
-fn classic_histogram_quantile_rejects_an_argument_without_le() {
-    let error = lower_promql(
-        "histogram_quantile(0.9, sum by (job) (rate(x_bucket[5m])))",
-        AccuracyTarget::Exact,
-    )
-    .unwrap_err();
-    assert!(error.to_string().contains("le"), "{error}");
-}
-
-// ── rate / increase carry their own window (no Window node) ─────────────────────
-
-#[test]
-fn rate_has_time_range_child_not_window() {
-    let qe = lower("rate(http_requests_total[5m])");
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected Aggregate for rate, got {qe:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
-    let NonASAPOp::TimeRange { range, .. } = child.expect_non_asap() else {
-        panic!("expected TimeRange child (not Window), got {child:?}");
-    };
-    assert_eq!(*range, Duration::from_secs(300));
-}
-
-#[test]
-fn increase_maps_to_increase_intent() {
-    let qe = lower("increase(errors_total[1h])");
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected Aggregate for increase, got {qe:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Increase]));
-    let NonASAPOp::TimeRange { range, .. } = child.expect_non_asap() else {
-        panic!("expected TimeRange child, got {child:?}");
-    };
-    assert_eq!(*range, Duration::from_secs(3600));
-}
-
-// ── outer aggregation over an inner range-vector func is two levels ─────────────
-
-#[test]
-fn sum_over_rate_keeps_both_levels() {
-    // Regression: `sum(rate(m[w]))` — the most common PromQL shape — must keep
-    // the cross-series Sum, not collapse to a bare per-series Rate.
-    let qe = lower("sum(rate(http_requests_total[5m]))");
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate{{Sum}}, got {qe:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected inner Aggregate{{Rate}}, got {child:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Rate]));
-    assert!(matches!(
-        child.expect_non_asap(),
-        NonASAPOp::TimeRange { .. }
-    ));
-}
-
-#[test]
-fn sum_by_over_rate_groups_the_outer_sum() {
-    // `sum by (job) (rate(...))`: the grouping belongs to the OUTER sum and lands
-    // on a positional `Aggregate.by` (the same shape SQL produces) over the
-    // label-preserving inner Rate. Leaf = [ts, value, job] → by = [2].
-    let qe = lower("sum by (job) (rate(http_requests_total[5m]))");
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate grouped by job, got {qe:?}");
-    };
-    assert_eq!(reduction, &Reduction::by(vec![2]));
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    assert!(matches!(
-        child.expect_non_asap(),
-        NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate])
-    ));
-}
-
-#[test]
-fn count_over_rate_keeps_both_levels() {
-    // The `Outer::Count` sibling of the `sum(rate(...))` bug.
-    let qe = lower("count(rate(http_requests_total[5m]))");
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate{{Count}}, got {qe:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
-    assert!(matches!(
-        child.expect_non_asap(),
-        NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate])
-    ));
-}
-
-#[test]
-fn count_over_distinct_over_time_preserves_both_aggregates() {
-    // One series with window samples [1, 2] produces one distinct-count
-    // result (value 2). The outer count counts that one series, yielding 1.
-    for (query, reduction) in [
-        (
-            "count(distinct_over_time(unique_users[5m]))",
-            Reduction::by(vec![]),
-        ),
-        (
-            "count by (job) (distinct_over_time(unique_users[5m]))",
-            Reduction::by(vec![2]),
-        ),
-    ] {
-        let tree = lower(query);
-        let NonASAPOp::Aggregate {
-            measures,
-            reduction: actual,
-            child,
-            ..
-        } = tree.expect_non_asap()
-        else {
-            panic!("expected outer Count: {tree:?}");
-        };
-        assert!(
-            matches!(measures.as_slice(), [AggIntent::Count { .. }]),
-            "{query}: {tree:?}"
-        );
-        assert_eq!(actual, &reduction, "{query}");
-        let NonASAPOp::Aggregate {
-            measures,
-            reduction,
-            child,
-            ..
-        } = child.expect_non_asap()
-        else {
-            panic!("expected inner per-series Cardinality: {tree:?}");
-        };
-        assert!(
-            matches!(measures.as_slice(), [AggIntent::Cardinality { .. }]),
-            "{query}: {tree:?}"
-        );
-        assert_eq!(reduction, &Reduction::PerEntity, "{query}");
-        assert!(
-            matches!(child.expect_non_asap(), NonASAPOp::TimeRange { range, .. } if range.as_secs() == 300)
-        );
-    }
-}
-
-// ── count / cardinality ───────────────────────────────────────────────────────
-
-// Both selector fast paths and recursive vector expressions count rows, not values.
-#[test]
-fn count_never_lowers_to_distinct_sample_values() {
-    for query in [
-        "count(up)",
-        "count by (job) (up)",
-        "count without (instance) (up)",
-        "count(up + 1)",
-        "count(count_over_time(up[5m]))",
-        "count_over_time(up[5m])",
-    ] {
-        let tree = lower(query);
-        let intents = all_intents(&tree);
-        assert!(
-            intents.iter().any(|i| matches!(i, AggIntent::Count { .. })),
-            "{query}: {tree:?}"
-        );
-        assert!(
-            !intents
-                .iter()
-                .any(|i| matches!(i, AggIntent::Cardinality { .. })),
-            "{query}: {tree:?}"
-        );
-    }
-}
-
-#[test]
-fn count_over_time_is_count_intent() {
-    let qe = lower("count_over_time(m[5m])");
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected Aggregate");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
-    assert!(matches!(
-        child.expect_non_asap(),
-        NonASAPOp::TimeRange { .. }
-    ));
-}
-
-#[test]
-fn outer_count_counts_series() {
-    // `count by (symbol) (count_over_time(...))`: inner per-series sample count
-    // over the window (label-preserving), outer cross-series row count grouped
-    // on a positional `Aggregate.by`. Leaf = [ts, value, symbol] → symbol = col 2.
-    let qe = lower("count by (symbol) (count_over_time(financial_last_trade_price[5m]))");
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected outer Aggregate grouped by symbol, got {qe:?}");
-    };
-    assert_eq!(reduction, &Reduction::by(vec![2]));
-    assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
-    // Inner: Aggregate{Count} over TimeRange (per-series count_over_time).
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected Aggregate (count_over_time) under the outer count, got {child:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
-    assert!(matches!(
-        child.expect_non_asap(),
-        NonASAPOp::TimeRange { .. }
-    ));
-}
-
-// ── topk / bottomk ────────────────────────────────────────────────────────────
-
-#[test]
-fn topk_over_count_is_heavy_hitter_topk() {
-    let qe = lower(r#"topk by (service) (10, count_over_time(requests{env="prod"}[1m]))"#);
-    // Heavy-hitter: Aggregate{TopK} with grouping resolved to positional ids.
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected Aggregate with TopK, got {qe:?}");
-    };
-    // `service` is the only group key → resolved to a positional ColumnId.
-    assert_eq!(reduction.expect_reduce().len(), 1);
-    assert!(matches!(
-        measures.as_slice(),
-        [AggIntent::TopK { k: 10, .. }]
-    ));
-    // The count_over_time under the TopK is a TimeRange-backed aggregate.
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected Aggregate (count_over_time) under TopK, got {child:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
-    let NonASAPOp::TimeRange { range, child, .. } = child.expect_non_asap() else {
-        panic!("expected TimeRange under Count aggregate, got {child:?}");
-    };
-    assert_eq!(*range, Duration::from_secs(60));
-    assert!(matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }));
-}
-
-#[test]
-fn topk_over_sum_is_value_weighted_heavy_hitter_topk() {
-    let qe = lower(r#"topk by (service) (5, sum_over_time(requests{env="prod"}[1m]))"#);
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected Aggregate with TopK, got {qe:?}");
-    };
-    assert_eq!(reduction.expect_reduce().len(), 1);
-    assert!(matches!(
-        measures.as_slice(),
-        [AggIntent::TopK { k: 5, .. }]
-    ));
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected Aggregate (sum_over_time) under TopK, got {child:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    assert!(matches!(
-        child.expect_non_asap(),
-        NonASAPOp::TimeRange { .. }
-    ));
-}
-
-#[test]
-fn topk_over_avg_is_generic_sort_limit() {
-    let qe = lower("topk by (host) (5, avg_over_time(cpu[5m]))");
-    let NonASAPOp::Limit {
-        n: Some(n),
-        offset,
-        child,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected Limit, got {qe:?}");
-    };
-    assert_eq!(*n, 5);
-    assert_eq!(*offset, 0);
-    let NonASAPOp::Sort {
-        keys,
-        partition_by,
-        child,
-    } = child.expect_non_asap()
-    else {
-        panic!("expected Sort under Limit, got {child:?}");
-    };
-    assert_eq!(keys.len(), 1);
-    assert!(!keys[0].ascending, "topk ranks descending");
-    // `by (host)` is per-group ranking → it rides on `Sort.partition_by`
-    // (positional), not a `Partition` node (issue #12). `host` is col 2 in
-    // the per-series avg schema [ts, value, host].
-    assert_eq!(partition_by, &vec![2]);
-    // Underneath: the label-preserving windowed avg aggregate (by: []), no
-    // intervening Partition.
-    assert!(
-        matches!(child.expect_non_asap(), NonASAPOp::Aggregate { reduction, measures, .. }
-            if reduction == &Reduction::PerEntity && matches!(measures.as_slice(), [AggIntent::Avg { .. }])),
-        "expected bare per-series Avg aggregate under Sort, got {child:?}"
-    );
-}
-
-#[test]
-fn ungrouped_topk_over_sum_is_heavy_hitter() {
-    let qe = lower("topk(5, sum_over_time(m[5m]))");
-    assert!(matches!(qe.expect_non_asap(), NonASAPOp::Aggregate { .. }));
-    assert!(has_intent(&qe, |i| matches!(i, AggIntent::Sum { .. })));
-    assert!(has_intent(&qe, |i| matches!(
-        i,
-        AggIntent::TopK { k: 5, .. }
-    )));
-}
-
-#[test]
-fn bottomk_over_count_is_generic_sort_ascending() {
-    // `bottomk` is never a heavy-hitter (descending=false), even over count.
-    let qe = lower("bottomk(3, count_over_time(m[5m]))");
-    let NonASAPOp::Limit {
-        n: Some(n), child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected Limit, got {qe:?}");
-    };
-    assert_eq!(*n, 3);
-    let NonASAPOp::Sort { keys, .. } = child.expect_non_asap() else {
-        panic!("expected Sort");
-    };
-    assert!(keys[0].ascending, "bottomk ranks ascending");
-    // Count intent is still present (as the inner aggregate), no TopK.
-    assert!(has_intent(&qe, |i| matches!(i, AggIntent::Count { .. })));
-    assert!(!has_intent(&qe, |i| matches!(i, AggIntent::TopK { .. })));
-}
-
-#[test]
-fn bottomk_is_always_generic_sort_ascending() {
-    let qe = lower("bottomk(3, count_over_time(m[5m]))");
-    let NonASAPOp::Limit {
-        n: Some(n), child, ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected Limit, got {qe:?}");
-    };
-    assert_eq!(*n, 3);
-    let NonASAPOp::Sort { keys, .. } = child.expect_non_asap() else {
-        panic!("expected Sort");
-    };
-    assert!(keys[0].ascending, "bottomk ranks ascending");
-}
-
-#[test]
-fn topk_count_output_schema_carries_group_key() {
-    // The inner Count is per-series (label-preserving), so the group-by key
-    // (`service`) flows through to the outer TopK's `by` column. Leaf schema =
-    // [ts, value, service] → TopK groups on service (col 2).
-    let qe = lower("topk by (service) (5, count_over_time(m[1m]))");
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected Aggregate{{TopK}}, got {qe:?}");
-    };
-    assert_eq!(
-        reduction,
-        &Reduction::by(vec![2]),
-        "service is col 2 in [ts, value, service]"
-    );
-    assert!(matches!(
-        measures.as_slice(),
-        [AggIntent::TopK { k: 5, .. }]
-    ));
-    // Inner Count aggregate is visible with its TimeRange child.
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected inner Aggregate{{Count}}, got {child:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
-    assert!(matches!(
-        child.expect_non_asap(),
-        NonASAPOp::TimeRange { .. }
-    ));
-}
-
-// ── binary ops ────────────────────────────────────────────────────────────────
-
-#[test]
-fn binary_op_division() {
-    let qe = lower("rate(a[5m]) / rate(b[5m])");
-    let NonASAPOp::BinaryOp {
-        operator: BinaryOperator { kind: op, .. },
-        lhs,
-        rhs,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected BinaryOp, got {qe:?}");
-    };
-    assert_eq!(*op, BinaryOpKind::Arithmetic(ArithmeticOpKind::Div));
-    assert!(
-        matches!(lhs.expect_non_asap(), NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate]))
-    );
-    assert!(
-        matches!(rhs.expect_non_asap(), NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::Rate]))
-    );
-}
-
-#[test]
-fn binary_op_with_on_grouping() {
-    let qe = lower("a / on(host) b");
-    let NonASAPOp::BinaryOp {
-        operator: BinaryOperator { vector_match, .. },
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected BinaryOp, got {qe:?}");
-    };
-    let vm = vector_match.as_ref().expect("vector_match present");
-    use asap_types::pre_asap::VectorMatchKind;
-    assert_eq!(vm.kind, VectorMatchKind::On);
-    assert_eq!(vm.labels, vec!["host".to_string()]);
-}
-
-// `bool` changes a comparison from a filter to a 0/1 result, so the IR must
-// carry it.
-#[test]
-fn bool_comparisons_are_distinct() {
-    let op = |q: &str| match lower(q).expect_non_asap() {
-        NonASAPOp::BinaryOp {
-            operator,
-            return_bool,
-            ..
-        } => (operator.kind.clone(), *return_bool),
-        NonASAPOp::Filter {
-            pred: asap_types::ir::Predicate(ScalarExpr::Compare { op, .. }),
-            ..
-        } => (BinaryOpKind::Compare(op.clone()), false),
-        NonASAPOp::Project { cols, .. } => {
-            let ScalarExpr::Case { branches, .. } = &cols[1].expr else {
-                panic!()
-            };
-            let ScalarExpr::Compare { op, .. } = &branches[0].0 else {
-                panic!()
-            };
-            (BinaryOpKind::Compare(op.clone()), true)
-        }
-        other => panic!("expected BinaryOp, got {other:?}"),
-    };
-    assert_eq!(
-        op("a > 1"),
-        (BinaryOpKind::Compare(CompareOpKind::Gt), false)
-    );
-    assert_eq!(
-        op("a > bool 1"),
-        (BinaryOpKind::Compare(CompareOpKind::Gt), true)
-    );
-    assert_eq!(
-        op("a == bool on(job) b"),
-        (BinaryOpKind::Compare(CompareOpKind::Eq), true)
-    );
-}
-
-#[test]
-fn binary_op_binds_each_branch_against_its_own_schema() {
-    // Each side scans a different metric and groups by a different label. With a
-    // single root schema threaded to both branches, the left scan would leak the
-    // right's group key (and vice-versa). Per-branch binding keeps them separate.
-    let qe = lower("count by (job) (a) / count by (region) (b)");
-    let NonASAPOp::BinaryOp { lhs, rhs, .. } = qe.expect_non_asap() else {
-        panic!("expected BinaryOp, got {qe:?}");
-    };
-    let lcols = scan_columns(lhs);
-    let rcols = scan_columns(rhs);
-    assert!(
-        lcols.iter().any(|c| c == "job") && !lcols.iter().any(|c| c == "region"),
-        "lhs scan schema leaked the rhs key: {lcols:?}"
-    );
-    assert!(
-        rcols.iter().any(|c| c == "region") && !rcols.iter().any(|c| c == "job"),
-        "rhs scan schema leaked the lhs key: {rcols:?}"
-    );
-}
-
-/// Collect every `AggIntent` in the tree, root-to-leaf.
-fn all_intents(e: &OperatorNode) -> Vec<AggIntent> {
-    let mut out = Vec::new();
-    collect_intents(e, &mut out);
-    out
-}
-
-fn collect_intents(e: &OperatorNode, out: &mut Vec<AggIntent>) {
-    match e.expect_non_asap() {
-        NonASAPOp::Aggregate {
-            measures, child, ..
-        } => {
-            out.extend(measures.iter().cloned());
-            collect_intents(child, out);
-        }
-        NonASAPOp::TimeRange { child, .. }
-        | NonASAPOp::Filter { child, .. }
-        | NonASAPOp::Sort { child, .. }
-        | NonASAPOp::Limit { child, .. } => collect_intents(child, out),
-        NonASAPOp::BinaryOp { lhs, rhs, .. } => {
-            collect_intents(lhs, out);
-            collect_intents(rhs, out);
-        }
-        _ => {}
-    }
-}
-
-/// True if any `AggIntent` anywhere in the tree satisfies `pred`.
-fn has_intent<F: Fn(&AggIntent) -> bool>(e: &OperatorNode, pred: F) -> bool {
-    all_intents(e).iter().any(pred)
-}
-
-/// Field names on the first `Scan` reachable by descending single-child nodes.
-fn scan_columns(e: &OperatorNode) -> Vec<String> {
-    match e.expect_non_asap() {
-        NonASAPOp::Scan { schema, .. } => schema.fields.iter().map(|c| c.name.clone()).collect(),
-        NonASAPOp::Aggregate { child, .. }
-        | NonASAPOp::TimeRange { child, .. }
-        | NonASAPOp::Filter { child, .. }
-        | NonASAPOp::Sort { child, .. }
-        | NonASAPOp::Limit { child, .. } => scan_columns(child),
-        _ => vec![],
-    }
-}
-
-// ── without(...) grouping (issue #39) ───────────────────────────────────────────
-
-#[test]
-fn without_grouping_lowers_to_the_exclusion_form() {
-    // `sum without (instance) (rate(m[5m]))` — a cross-series reduction over the
-    // per-series rate, grouped by every label except `instance`. The excluded
-    // label is stored positionally (the SchemaResolver seeds it), the grouping is the
-    // `without` form, and the output schema stays open.
-    let qe = lower("sum without (instance) (rate(m[5m]))");
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected an Aggregate, got {qe:?}");
-    };
-    let by = reduction.expect_reduce();
-    assert!(by.is_without());
-    assert_eq!(by.keys().len(), 1, "excluded `instance`");
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-    // The inner per-series rate is preserved (label-preserving) under the outer
-    // cross-series `without` reduction.
-    assert!(
-        matches!(child.expect_non_asap(), NonASAPOp::Aggregate { measures, .. }
-        if matches!(measures.as_slice(), [AggIntent::Rate]))
-    );
-    assert!(!qe.schema.clone().closed);
-}
-
-// ── parameter validation (reject rather than silently truncate/garble) ──────────
-
-#[test]
-fn fractional_or_negative_topk_k_is_rejected() {
-    // `as u64` would silently truncate 2.7→2 / saturate -1→0.
-    assert!(lower_promql("topk(2.7, count_over_time(m[1m]))", AccuracyTarget::Exact).is_err());
-    assert!(lower_promql("bottomk(2.5, sum_over_time(m[1m]))", AccuracyTarget::Exact).is_err());
-}
-
-#[test]
-fn out_of_range_quantile_phi_is_accepted() {
-    // Prometheus defines out-of-range phi results; lowering must preserve it.
-    for query in [
-        "quantile(1.5, up)",
-        "quantile_over_time(1.5, m[5m])",
-        "histogram_quantile(2.0, rate(b_bucket[5m]))",
-    ] {
-        assert!(
-            lower_promql(query, AccuracyTarget::Exact).is_ok(),
-            "{query}"
-        );
-    }
-}
-
-#[test]
-fn function_wrapped_range_vector_is_rejected_not_stripped() {
-    // `rate(abs(m[5m]))` must NOT silently lower as `rate(m[5m])` — the wrapper
-    // is rejected (here, at parse or in extract_matrix), never stripped.
-    assert!(
-        lower_promql("rate(abs(http_requests_total[5m]))", AccuracyTarget::Exact).is_err(),
-        "function-wrapped range vector should be rejected"
-    );
-}
-
-#[test]
-fn pathologically_nested_query_is_rejected_not_stack_overflow() {
-    // 300 nested parens parse fine but exceed the walker's depth limit (256);
-    // it must return an error, not overflow the stack.
-    let q = format!("{}m{}", "(".repeat(300), ")".repeat(300));
-    let err = lower_promql(&q, AccuracyTarget::Exact).unwrap_err();
-    assert!(format!("{err}").contains("nesting"), "got {err}");
-}
-
-// Behavior: every parser-accepted `fill` modifier form is rejected with a
-// fill-specific lowering error rather than silently dropped.
-#[test]
-fn fill_modifiers_are_rejected_not_ignored() {
-    for q in [
-        "a + fill(0) b",
-        "a + fill_left(1) b",
-        "a + fill_right(2) b",
-        "a + fill_left(1) fill_right(2) b",
-        "a + fill_right(2) fill_left(1) b",
-        "a + on(job) fill(0) b",
-        "a * ignoring(instance) group_left(env) fill_right(0) b",
-        "a > bool on(job) fill(0) b",
-        "sum(a - on(job) group_right fill_left(0) b)",
-    ] {
-        match lower_promql(q, AccuracyTarget::Exact) {
-            Err(LoweringError::UnsupportedFeature(m)) if m.contains("`fill`") => {}
-            other => panic!("expected fill rejection for {q:?}, got {other:?}"),
-        }
-    }
-}
-
-// ── accuracy propagation ──────────────────────────────────────────────────────
-
-#[test]
-fn accuracy_target_flows_into_quantile_intent() {
-    let qe = lower_promql(
-        "quantile_over_time(0.9, m[5m])",
-        AccuracyTarget::Epsilon(0.01),
-    )
-    .unwrap();
-    let NonASAPOp::Aggregate { measures, .. } = qe.expect_non_asap() else {
-        panic!("expected Aggregate");
-    };
-    assert!(matches!(
-        &measures[0],
-        AggIntent::Quantile { accuracy: AccuracyTarget::Epsilon(e), .. } if (*e - 0.01).abs() < 1e-12
-    ));
-}
-
-// ── schema flow (positional, carried on Scan; derived on demand) ─────────────────
-
-#[test]
-fn aggregate_output_schema_preserves_time_axis_and_labels() {
-    let qe = lower(r#"quantile_over_time(0.99, http_request_duration{env="prod"}[5m])"#);
-    // Per-series reduction: the root is Aggregate { TimeRange { Scan } }.
-    // The SchemaResolver adds all referenced label names (group keys AND filter
-    // predicate columns) to the scan schema, so `env` appears as a column
-    // even though it is only used as a filter.
-    // per_series_reduction_schema preserves the time axis and all label columns.
-    let NonASAPOp::Aggregate { .. } = qe.expect_non_asap() else {
-        panic!("expected Aggregate, got {qe:?}");
-    };
-    let schema = &qe.schema;
-    let names: Vec<&str> = schema.fields.iter().map(|c| c.name.as_str()).collect();
-    assert_eq!(names, vec!["ts", "value", "env"]);
-    assert_eq!(
-        schema.time_index,
-        Some(0),
-        "per-series over_time preserves the time axis"
-    );
-}
-
-#[test]
-fn scan_schema_carries_ts_value_and_group_keys() {
-    // `service` is a group key → the SchemaResolver lands it in the self-contained
-    // Scan schema (positional). `env` is only a filter, so it is not a column.
-    let qe = lower("count by (service) (count_over_time(requests[1m]))");
-    fn find_scan(n: &OperatorNode) -> &OperatorNode {
-        match n.expect_non_asap() {
-            NonASAPOp::Scan { .. } => n,
-            NonASAPOp::TimeRange { child, .. }
-            | NonASAPOp::Aggregate { child, .. }
-            | NonASAPOp::Filter { child, .. } => find_scan(child),
-            other => panic!("unexpected node {other:?}"),
-        }
-    }
-    let NonASAPOp::Scan { schema, .. } = find_scan(&qe).expect_non_asap() else {
-        unreachable!()
-    };
-    let mut names: Vec<&str> = schema.fields.iter().map(|c| c.name.as_str()).collect();
-    names.sort();
-    assert_eq!(names, vec!["service", "ts", "value"]);
-    assert_eq!(schema.time_index, Some(0)); // ts
-}
-
-// ── batch entry point ─────────────────────────────────────────────────────────
-
-#[test]
-fn batch_lowers_each_entry_and_reads_per_query_accuracy() {
-    let workload = PlanningWorkload {
-        query_workload: QueryWorkload {
-            language: QueryLanguage::PromQL,
-            query_batch: Some(vec![
-                BatchEntry {
-                    query: Query("rate(a[5m])".into()),
-                    requirements: QueryRequirements::default(),
-                    predictability: Predictability::Unknown,
-                    invocations: 1,
-                    execute_at: None,
-                    time_selection: TimeSelection::default(),
-                },
-                BatchEntry {
-                    query: Query("quantile_over_time(0.9, b[5m])".into()),
-                    requirements: QueryRequirements {
-                        accuracy: AccuracyRequirement::Explicit(AccuracyTarget::Epsilon(0.02)),
-                        ..Default::default()
-                    },
-                    predictability: Predictability::Unknown,
-                    invocations: 1,
-                    execute_at: None,
-                    time_selection: TimeSelection::default(),
-                },
-            ]),
-            repeating_queries: None,
-        },
-        data_workload: Some(DataWorkload {
-            data_ingestion_interval: Evidence {
-                value: Some(DurationMs(1_000)),
-                ..Default::default()
-            },
-            ..Default::default()
-        }),
-    };
-    let results = lower_promql_workload(&workload, 0).expect("valid workload");
-    assert_eq!(results.len(), 2);
-}
-
-#[test]
-fn batch_rejects_non_promql_language() {
-    use asap_types::workload::SqlDialect;
-    let workload = PlanningWorkload {
-        query_workload: QueryWorkload {
-            language: QueryLanguage::SQL(SqlDialect::DataFusionSQL),
-            query_batch: Some(vec![BatchEntry {
-                query: Query("SELECT 1".into()),
-                requirements: QueryRequirements::default(),
-                predictability: Predictability::Unknown,
-                invocations: 1,
-                execute_at: None,
-                time_selection: TimeSelection::default(),
-            }]),
-            repeating_queries: None,
-        },
-        data_workload: None,
-    };
-    assert!(matches!(
-        lower_promql_workload(&workload, 0),
-        Err(LoweringError::WrongLanguage(_))
-    ));
-}
-
-// ── #12: one home per grouping concept (the canonical `Partition` node is removed) ──
-//
-// `Partition` and `Aggregate.by` were two ways to express grouping. #12 collapses
-// them: a reducing GROUP BY → `Aggregate.by`; per-group *ranking* (split without
-// reduce) → `Sort.partition_by`; parallel sharding → a deployment's own
-// physical stage. There is no longer a canonical `Partition` node. These
-// tests pin both surviving canonical homes.
-
-#[test]
-fn reducing_group_by_lowers_to_aggregate_by() {
-    // Cross-series reduce, no keys → bare `Aggregate { reduction: Reduce([]) }`.
-    let q = lower("sum(http_requests_total)");
-    assert!(
-        matches!(q.expect_non_asap(), NonASAPOp::Aggregate { reduction, .. } if reduction == &Reduction::by(vec![]))
-    );
-
-    // Cross-series reduce grouped by a label → `Aggregate.reduction`.
-    let q = lower("sum by (job) (http_requests_total)");
-    assert!(
-        matches!(q.expect_non_asap(), NonASAPOp::Aggregate { reduction, .. }
-        if reduction.expect_reduce().len() == 1)
-    );
-
-    // Reduce over a label-preserving `rate` grouped by a label → still
-    // `Aggregate.reduction` (the keys resolve against rate's preserved schema).
-    let q = lower("sum by (job) (rate(http_requests_total[5m]))");
-    assert!(
-        matches!(q.expect_non_asap(), NonASAPOp::Aggregate { reduction, .. }
-        if reduction.expect_reduce().len() == 1)
-    );
-}
-
-#[test]
-fn generic_topk_grouping_lowers_to_sort_partition_by() {
-    // Per-group ranking (`topk by (host)`, non-heavy-hitter) groups *without*
-    // reducing → the grouping rides on `Sort.partition_by`, and the windowed
-    // reduction beneath stays label-preserving (`by: []`). No `Partition` node.
-    let q = lower("topk by (host) (5, avg_over_time(cpu[5m]))");
-    let NonASAPOp::Limit { child, .. } = q.expect_non_asap() else {
-        panic!("expected Limit, got {q:?}");
-    };
-    let NonASAPOp::Sort {
-        partition_by,
-        child,
-        ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected Sort, got {child:?}");
-    };
-    assert_eq!(partition_by, &vec![2], "host is col 2 in [ts, value, host]");
-    assert!(
-        matches!(child.expect_non_asap(), NonASAPOp::Aggregate { reduction, .. } if reduction == &Reduction::PerEntity)
-    );
-}
-
-#[test]
-fn topk_over_bare_selector_by_label_ranks_per_group() {
-    // `topk(3, http_requests_total) by (job)` — top-3 series per `job`. A bare
-    // instant selector ranks its OWN samples; it must not be wrapped in an
-    // implicit cross-series `Sum`, which would collapse the `job` partition
-    // label before `Sort.partition_by` resolves it (issue #30 — follow-up to the
-    // Partition→Sort.partition_by reframe in #12). Expected:
-    //   Limit{3} → Sort{value desc, partition_by:[job]} → Scan
-    let q = lower("topk(3, http_requests_total) by (job)");
-    let NonASAPOp::Limit {
-        n: Some(n), child, ..
-    } = q.expect_non_asap()
-    else {
-        panic!("expected Limit, got {q:?}");
-    };
-    assert_eq!(*n, 3);
-    let NonASAPOp::Sort {
-        keys,
-        partition_by,
-        child,
-    } = child.expect_non_asap()
-    else {
-        panic!("expected Sort, got {child:?}");
-    };
-    assert!(!keys[0].ascending, "topk ranks descending");
-    assert_eq!(partition_by, &vec![2], "job is col 2 in [ts, value, job]");
-    // No implicit reducing aggregate — the selector is label-preserving, so the
-    // sort is directly over the selector horizon (the `job` label survives to partition by).
-    assert!(
-        matches!(child.expect_non_asap(), NonASAPOp::TimeRange { child, .. } if matches!(child.expect_non_asap(), NonASAPOp::Scan { .. })),
-        "ranking is over the bare selector horizon, not a reducing Aggregate, got {child:?}"
-    );
-    assert!(
-        !has_intent(&q, |i| matches!(i, AggIntent::Sum { .. })),
-        "no implicit Sum is introduced over a bare selector"
-    );
-}
-
-#[test]
-fn topk_over_bare_selector_ranks_raw_samples() {
-    // Even without `by`, `topk(3, m)` ranks the raw instant-vector samples — it
-    // does not sum them. The sort sits directly over the Scan, partition empty.
-    let q = lower("topk(3, http_requests_total)");
-    let NonASAPOp::Limit { child, .. } = q.expect_non_asap() else {
-        panic!("expected Limit, got {q:?}");
-    };
-    let NonASAPOp::Sort {
-        partition_by,
-        child,
-        ..
-    } = child.expect_non_asap()
-    else {
-        panic!("expected Sort, got {child:?}");
-    };
-    assert!(partition_by.is_empty(), "no `by` → global ranking");
-    assert!(
-        matches!(child.expect_non_asap(), NonASAPOp::TimeRange { child, .. } if matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }))
-    );
-    assert!(!has_intent(&q, |i| matches!(i, AggIntent::Sum { .. })));
-}
-
-// ── Issue #109: histogram_quantiles fans out into one branch per φ ──────────
-
-/// The `(label value, intent)` of each `histogram_quantiles` branch.
-fn quantile_branches(q: &OperatorNode) -> Vec<(String, AggIntent)> {
-    let NonASAPOp::Concat { children, .. } = q.expect_non_asap() else {
-        panic!("expected a Concat at the root, got {q:?}");
-    };
-    children
-        .iter()
-        .map(|c| {
-            let NonASAPOp::PromqlRelabel { value, child, .. } = c.expect_non_asap() else {
-                panic!("expected PromqlRelabel per branch, got {c:?}");
-            };
-            let ScalarExpr::Literal(ScalarValue::Utf8(v)) = value else {
-                panic!("expected a literal label value, got {value:?}");
-            };
-            let NonASAPOp::Aggregate { measures, .. } = child.expect_non_asap() else {
-                panic!("expected an Aggregate under the PromqlRelabel, got {child:?}");
-            };
-            (v.clone(), measures[0].clone())
-        })
-        .collect()
-}
-
-#[test]
-fn histogram_quantiles_rejects_unrepresented_native_histograms() {
-    assert!(lower_promql(
-        r#"histogram_quantiles(testhistogram3, "q", 0, 0.25, 1)"#,
-        AccuracyTarget::Exact
-    )
-    .is_err());
-}
-
-#[test]
-fn histogram_quantiles_over_classic_buckets_interpolates() {
-    // `_bucket` argument → exact cumulative-bucket interpolation, never a sketch.
-    let q = lower(r#"histogram_quantiles(request_duration_seconds_bucket, "q", 0.5, 0.9)"#);
-    for (_, intent) in quantile_branches(&q) {
-        assert!(
-            matches!(intent, AggIntent::HistogramQuantile { .. }),
-            "classic buckets → HistogramQuantile, got {intent:?}"
-        );
-    }
-}
-
-#[test]
-fn histogram_quantiles_branches_are_union_compatible() {
-    // `Concat` derives its schema from the first child, so every branch must
-    // agree on column names — the φ lives in the label, not the column name.
-    let q = lower(r#"histogram_quantiles(testhistogram3_bucket, "q", 0.5, 0.9)"#);
-    let NonASAPOp::Concat { children, .. } = q.expect_non_asap() else {
-        panic!("expected Concat");
-    };
-    let shapes: Vec<Vec<String>> = children
-        .iter()
-        .map(|c| {
-            c.schema
-                .clone()
-                .fields
-                .iter()
-                .map(|c| c.name.clone())
-                .collect()
-        })
-        .collect();
-    assert_eq!(shapes[0], shapes[1], "branches must be union-compatible");
-    assert_eq!(shapes[0], vec!["value".to_string(), "q".to_string()]);
-    assert_eq!(
-        q.schema.fields.len(),
-        2,
-        "the merged schema describes every branch"
-    );
-}
-
-#[test]
-fn histogram_quantiles_uses_the_given_label_name() {
-    let q = lower(r#"histogram_quantiles(h_bucket, "phi", 0.5)"#);
-    let NonASAPOp::Concat { children, .. } = q.expect_non_asap() else {
-        panic!("expected Concat");
-    };
-    let NonASAPOp::PromqlRelabel { dst, .. } = children[0].expect_non_asap() else {
-        panic!("expected PromqlRelabel");
-    };
-    assert_eq!(dst, "phi");
-}
-
-#[test]
-fn histogram_quantiles_formats_small_quantiles_like_prometheus() {
-    // `labels.FormatOpenMetricsFloat`: Go's %g, so exponent form below 1e-4.
-    let q = lower(r#"histogram_quantiles(h_bucket, "q", 0.00001)"#);
-    assert_eq!(quantile_branches(&q)[0].0, "1e-05");
-}
-
-#[test]
-fn histogram_quantiles_rejects_an_out_of_range_quantile() {
-    // Same rule as `histogram_quantile(φ, …)` — one bad φ fails the whole call.
-    for q in [
-        r#"histogram_quantiles(h_bucket, "q", -0.1)"#,
-        r#"histogram_quantiles(h_bucket, "q", 1.01)"#,
-        r#"histogram_quantiles(h_bucket, "q", 0.5, NaN)"#,
-    ] {
-        assert!(
-            lower_promql(q, AccuracyTarget::Exact).is_err(),
-            "{q} should be rejected"
-        );
-    }
-}
-
-// ── TimeRange.kind: instant vs range selectors ──────────────────────────────────
-
-#[test]
-fn bare_instant_selector_is_an_instant_time_range() {
-    // `up` reads the latest sample per series within the workload's ingestion
-    // interval (1s in `support::workload`): an `Instant` lookback of that length.
-    let qe = lower("up");
-    let NonASAPOp::TimeRange { range, kind, child } = qe.expect_non_asap() else {
-        panic!("expected TimeRange, got {qe:?}");
-    };
-    assert_eq!(*kind, TimeRangeKind::Instant);
-    assert_eq!(*range, Duration::from_secs(1));
-    assert!(matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }));
-}
-
-#[test]
-fn explicit_range_selector_is_a_range_time_range() {
-    // `m[5m]` keeps its own window and is a `Range` selection — both under a
-    // range function and as a bare matrix selector.
-    let qe = lower("rate(m[5m])");
-    let NonASAPOp::Aggregate { child, .. } = qe.expect_non_asap() else {
-        panic!("expected Aggregate, got {qe:?}");
-    };
-    let NonASAPOp::TimeRange { range, kind, .. } = child.expect_non_asap() else {
-        panic!("expected TimeRange, got {child:?}");
-    };
-    assert_eq!(*kind, TimeRangeKind::Range);
-    assert_eq!(*range, Duration::from_secs(300));
-
-    let qe = lower("m[5m]");
-    assert!(matches!(
-        qe.expect_non_asap(),
-        NonASAPOp::TimeRange {
-            kind: TimeRangeKind::Range,
-            ..
-        }
-    ));
-}
-
-#[test]
-fn instant_and_range_selectors_of_equal_length_stay_distinct() {
-    // The kind is part of the shape: a 1s range selector is not the same tree as
-    // the 1s instant lookback injected around a bare selector.
-    assert_ne!(lower("up"), lower("up[1s]"));
-}
-
-// ── the `bool` modifier → `return_bool` ─────────────────────────────────────────
-
-#[test]
-fn vector_scalar_comparison_without_bool_filters() {
-    let qe = lower("up > 0");
-    assert!(matches!(qe.expect_non_asap(), NonASAPOp::Filter { .. }));
-    assert!(matches!(
-        support::sample_expression(&qe),
-        ScalarExpr::Compare {
-            op: CompareOpKind::Gt,
-            ..
-        }
-    ));
-}
-
-#[test]
-fn vector_scalar_comparison_with_bool_sets_return_bool() {
-    let qe = lower("up > bool 0");
-    assert!(matches!(
-        support::sample_expression(&qe),
-        ScalarExpr::Case { .. }
-    ));
-    assert_ne!(qe, lower("up > 0"));
-}
-
-#[test]
-fn vector_vector_comparison_with_bool_sets_return_bool() {
-    // `a > bool b` — the modifier lands on the vector/vector op itself, with
-    // the default (ignoring nothing) match.
-    let qe = lower("a > bool b");
-    let NonASAPOp::BinaryOp {
-        operator,
-        return_bool,
-        lhs,
-        rhs,
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected BinaryOp, got {qe:?}");
-    };
-    assert!(*return_bool);
-    assert_eq!(operator.kind, BinaryOpKind::Compare(CompareOpKind::Gt));
-    assert!(matches!(lhs.expect_non_asap(), NonASAPOp::TimeRange { .. }));
-    assert!(matches!(rhs.expect_non_asap(), NonASAPOp::TimeRange { .. }));
-    assert!(!lower("a > b").expect_non_asap().children().is_empty());
-    assert_ne!(qe, lower("a > b"));
-}
-
-#[test]
-fn bool_modifier_composes_with_vector_matching() {
-    let qe = lower("a > bool on(job) b");
-    let NonASAPOp::BinaryOp {
-        operator,
-        return_bool,
-        ..
-    } = qe.expect_non_asap()
-    else {
-        panic!("expected BinaryOp, got {qe:?}");
-    };
-    assert!(*return_bool);
-    let vm = operator.vector_match.as_ref().expect("on(job) present");
-    assert_eq!(vm.labels, vec!["job".to_string()]);
-}
-
-// ── scalar expressions: negation, arithmetic, comparison ────────────────────────
-
-#[test]
-fn scalar_negation_of_time_is_a_negative_expression() {
-    // `-time()` is a scalar expression; its negation stays structural (the
-    // operand is not a constant to fold) and follows PromQL numeric rules.
-    let qe = support::scalar_root("-time()");
-    let ScalarExpr::Negative { expr, semantics } = &qe else {
-        panic!("expected ScalarExpr(Negative), got {qe:?}");
-    };
-    assert_eq!(*semantics, ExprSemantics::Promql);
-    assert!(matches!(expr.as_ref(), ScalarExpr::EvalTimestamp));
-    // Scalar-shaped: no time index.
-}
-
-#[test]
-fn scalar_negation_of_a_constant_still_folds() {
-    // `-(2)` is constant: it folds to one literal rather than a `Negative`.
-    assert_eq!(
-        support::promql_scalar(&support::scalar_root("-(2)")),
-        Some(-2.0)
-    );
-}
-
-#[test]
-fn scalar_arithmetic_carries_promql_semantics() {
-    let qe = support::scalar_root("time() - 1");
-    let ScalarExpr::Arithmetic {
-        op,
-        left,
-        right,
-        semantics,
-    } = &qe
-    else {
-        panic!("expected scalar(Arithmetic), got {qe:?}");
-    };
-    assert_eq!(*op, ArithmeticOpKind::Sub);
-    assert_eq!(*semantics, ExprSemantics::Promql);
-    assert!(matches!(left.as_ref(), ScalarExpr::EvalTimestamp));
-    assert!(matches!(
-        right.as_ref(),
-        ScalarExpr::Literal(ScalarValue::Float64(v)) if *v == 1.0
-    ));
-}
-
-#[test]
-fn scalar_bool_comparison_is_a_zero_one_case_with_promql_semantics() {
-    // `1 < bool 2` → `Case(Compare(1 < 2) → 1.0, else 0.0)`: PromQL yields 0/1.
-    let qe = support::scalar_root("1 < bool 2");
-    let ScalarExpr::Case {
-        operand,
-        branches,
-        else_expr,
-    } = &qe
-    else {
-        panic!("expected scalar(Case), got {qe:?}");
-    };
-    assert!(operand.is_none());
-    let [(when, then)] = branches.as_slice() else {
-        panic!("expected one branch, got {branches:?}");
-    };
-    let ScalarExpr::Compare {
-        left,
-        op,
-        right,
-        semantics,
-    } = when
-    else {
-        panic!("expected a Compare condition, got {when:?}");
-    };
-    assert_eq!(*op, CompareOpKind::Lt);
-    assert_eq!(*semantics, ExprSemantics::Promql);
-    assert!(matches!(left.as_ref(), ScalarExpr::Literal(ScalarValue::Float64(v)) if *v == 1.0));
-    assert!(matches!(right.as_ref(), ScalarExpr::Literal(ScalarValue::Float64(v)) if *v == 2.0));
-    assert!(matches!(then, ScalarExpr::Literal(ScalarValue::Float64(v)) if *v == 1.0));
-    assert!(matches!(
-        else_expr.as_deref(),
-        Some(ScalarExpr::Literal(ScalarValue::Float64(v))) if *v == 0.0
-    ));
-}
-
-#[test]
-fn scalar_comparison_without_bool_is_rejected() {
-    // PromQL has no scalar filter: a scalar/scalar comparison needs `bool`.
-    for q in ["1 < 2", "time() > 0", "(1 + 1) == 2"] {
-        assert!(
-            lower_promql(q, AccuracyTarget::Exact).is_err(),
-            "{q} must be rejected without `bool`"
-        );
-    }
-}
-
-#[test]
-fn label_matcher_predicates_carry_promql_semantics() {
-    let qe = lower(r#"up{job="api"}"#);
-    let NonASAPOp::TimeRange { child, .. } = qe.expect_non_asap() else {
-        panic!("expected TimeRange, got {qe:?}");
-    };
-    let NonASAPOp::Scan { predicates, .. } = child.expect_non_asap() else {
-        panic!("expected Scan, got {child:?}");
-    };
-    assert!(matches!(
-        &predicates[0].0,
-        ScalarExpr::Compare {
-            semantics: ExprSemantics::Promql,
-            ..
-        }
-    ));
-}
diff --git a/crates/frontend-promql/tests/unified_support.rs b/crates/frontend-promql/tests/unified_support.rs
deleted file mode 100644
index 26ff6e802..000000000
--- a/crates/frontend-promql/tests/unified_support.rs
+++ /dev/null
@@ -1,101 +0,0 @@
-use std::rc::Rc;
-
-use asap_frontend_promql::unified::{
-    lower_promql_workload, lower_promql_workload_with_histograms, HistogramCatalog, PromqlError,
-};
-use asap_types::ir::{NonASAPOp, OperatorNode, ScalarExpr};
-use asap_types::pre_asap::ScalarValue;
-use asap_types::types::AccuracyTarget;
-use asap_types::workload::{
-    AccuracyRequirement, BatchEntry, DataWorkload, DurationMs, Evidence, PlanningWorkload,
-    Predictability, Query, QueryLanguage, QueryRequirements, QueryWorkload, TimeSelection,
-};
-
-pub fn workload(query: &str, accuracy: AccuracyTarget) -> PlanningWorkload {
-    PlanningWorkload {
-        query_workload: QueryWorkload {
-            language: QueryLanguage::PromQL,
-            query_batch: Some(vec![BatchEntry {
-                query: Query(query.into()),
-                requirements: QueryRequirements {
-                    accuracy: AccuracyRequirement::Explicit(accuracy),
-                    ..Default::default()
-                },
-                predictability: Predictability::Unknown,
-                invocations: 1,
-                execute_at: None,
-                time_selection: TimeSelection::default(),
-            }]),
-            repeating_queries: None,
-        },
-        data_workload: Some(DataWorkload {
-            data_ingestion_interval: Evidence {
-                value: Some(DurationMs(1_000)),
-                ..Default::default()
-            },
-            ..Default::default()
-        }),
-    }
-}
-
-#[allow(dead_code)]
-pub fn lower_promql(
-    query: &str,
-    accuracy: AccuracyTarget,
-) -> Result<Rc<OperatorNode>, PromqlError> {
-    let mut lowered = lower_promql_workload(&workload(query, accuracy), 0)?;
-    Ok(lowered.remove(0))
-}
-
-#[allow(dead_code)]
-pub fn lower_promql_with_histograms(
-    query: &str,
-    accuracy: AccuracyTarget,
-    histograms: HistogramCatalog,
-) -> Result<Rc<OperatorNode>, PromqlError> {
-    let mut lowered =
-        lower_promql_workload_with_histograms(&workload(query, accuracy), histograms, 0)?;
-    Ok(lowered.remove(0))
-}
-
-/// The value of a bare PromQL numeric literal / folded constant at an
-/// scalar position (`Literal(Float64(v))`); `None` for any
-/// other shape.
-#[allow(dead_code)]
-pub fn promql_scalar(node: &ScalarExpr) -> Option<f64> {
-    match node {
-        ScalarExpr::Literal(ScalarValue::Float64(v)) => Some(*v),
-        _ => None,
-    }
-}
-
-/// Export the logical graph before physical materialization assigns timing.
-#[allow(dead_code)]
-pub fn logical_asap_dag(root: &Rc<OperatorNode>) -> asap_types::ir::export::LogicalASAPDAG {
-    asap_types::ir::export::compile_logical_asap_dag(root).expect("logical ASAP DAG export")
-}
-
-#[allow(dead_code)]
-pub fn scalar_root(query: &str) -> ScalarExpr {
-    match asap_frontend_promql::unified::lower_promql_query_workload(
-        &workload(query, AccuracyTarget::Exact),
-        0,
-    )
-    .unwrap()
-    .remove(0)
-    {
-        asap_types::ir::QueryRoot::Scalar(expr) => expr,
-        _ => panic!("expected scalar root: {query}"),
-    }
-}
-
-#[allow(dead_code)]
-pub fn sample_expression(node: &OperatorNode) -> &ScalarExpr {
-    match node.expect_non_asap() {
-        NonASAPOp::Project { cols, .. } => {
-            &cols[node.schema.column_id("value").unwrap_or(cols.len() - 1)].expr
-        }
-        NonASAPOp::Filter { pred, .. } => &pred.0,
-        other => panic!("expected sample expression, got {other:?}"),
-    }
-}
diff --git a/crates/frontend-promql/tests/univmon_candidates.rs b/crates/frontend-promql/tests/univmon_candidates.rs
index 2b4891a08..12a0a53b5 100644
--- a/crates/frontend-promql/tests/univmon_candidates.rs
+++ b/crates/frontend-promql/tests/univmon_candidates.rs
@@ -5,15 +5,16 @@ use asap_aware_mapping::accuracy::{
 };
 use asap_aware_mapping::cost_model::DefaultCostModel;
 use asap_aware_mapping::replacement::{default_strategies, search_workload_with_targets};
-use asap_aware_mapping::{Replacement, ReplacementStrategy, SketchAlgorithmStrategy, TargetSubDAG};
+use asap_aware_mapping::{ASAPStrategies, Replacement, ReplacementStrategy, TargetSubDAG};
 mod support;
+use asap_types::ir::cse::share_common_sub_dags;
+use asap_types::ir::{ASAPOp, Operator, OperatorNode};
 use asap_types::post_asap::{
-    compile_post_asap_dag, cse::share_common_summary_sub_dags, AccuracyError, BoundExpr,
-    CompositionOperator, ErrorMetric, FieldDataType, ProbabilityExpr, ResultGuarantee,
-    SketchAlgorithm, SketchStatistic, SummaryExpr, SummaryInputExpr, SummaryNode,
+    AccuracyError, BoundExpr, CompositionOperator, ErrorMetric, FieldDataType, ProbabilityExpr,
+    ResultGuarantee, SketchAlgorithm, SketchStatistic, SummaryInputExpr,
 };
 use asap_types::types::AccuracyTarget;
-use support::lower_promql;
+use support::{lower_promql, post_asap_dag};
 
 // Synthetic evidence exercises structural sharing, never runtime accuracy.
 struct TestEvidence;
@@ -49,22 +50,22 @@ impl AccuracyModel for TestEvidence {
     }
 }
 
-fn candidate(query: &str, accuracy: AccuracyTarget) -> Rc<SummaryNode> {
+fn candidate(query: &str, accuracy: AccuracyTarget) -> Rc<OperatorNode> {
     let root = lower_promql(query, accuracy).unwrap();
-    SketchAlgorithmStrategy::new_with_planning_inputs(&DefaultCostModel, &TestEvidence, &EqualSplitAllocator)
-        .replacements(&TargetSubDAG::new(&Rc::new(root)))
+    ASAPStrategies::new_with_planning_inputs(&DefaultCostModel, &TestEvidence, &EqualSplitAllocator)
+        .replacements(&TargetSubDAG::new(&root))
         .into_iter()
         .find_map(|candidate| {
-            let Replacement::Summary(node) = candidate.replacement else { return None };
-            let SummaryExpr::SummaryEstimate { summary_input, .. } = &node.expr else { return None };
-            matches!(&summary_input.expr, SummaryExpr::SummaryAgg { family: FieldDataType::Sketch(kind, _), .. }
+            let Replacement::SubDAG(node) = candidate.replacement else { return None };
+            let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &node.operator else { return None };
+            matches!(&summary_input.operator, Operator::ASAP(ASAPOp::SummaryAgg { family: FieldDataType::Sketch(kind, _), .. })
                 if kind.algorithm() == &SketchAlgorithm::UnivMon).then_some(node)
         }).expect("UnivMon candidate")
 }
 
 #[test]
-fn four_readouts_share_one_value_frequency_state_and_keep_honest_guarantees() {
-    // Equal data, grouping and window produce one state independently of readout.
+fn four_evaluations_share_one_value_frequency_state_and_keep_honest_guarantees() {
+    // Equal data, grouping and window produce one state independently of evaluation.
     let accuracy = AccuracyTarget::Epsilon(0.02);
     let roots: Vec<_> = [
         ("distinct_over_time(m[5m])", accuracy.clone()),
@@ -76,26 +77,25 @@ fn four_readouts_share_one_value_frequency_state_and_keep_honest_guarantees() {
     .enumerate()
     .map(|(id, (query, accuracy))| (id, candidate(query, accuracy)))
     .collect();
-    let roots = share_common_summary_sub_dags(roots);
+    let roots = share_common_sub_dags(roots);
     let mut first_state = None;
     for (index, root) in &roots {
-        let SummaryExpr::SummaryEstimate {
+        let Operator::ASAP(ASAPOp::SummaryEstimate {
             summary_input,
             query,
-            ..
-        } = &root.expr
+        }) = &root.operator
         else {
             panic!()
         };
         if let Some(first) = &first_state {
             assert!(
                 Rc::ptr_eq(first, summary_input),
-                "state must be shared across readouts"
+                "state must be shared across evaluations"
             );
         } else {
             first_state = Some(Rc::clone(summary_input));
         }
-        let SummaryExpr::SummaryAgg { input, .. } = &summary_input.expr else {
+        let Operator::ASAP(ASAPOp::SummaryAgg { input, .. }) = &summary_input.operator else {
             panic!()
         };
         assert!(matches!(input.item, Some(SummaryInputExpr::Column(_))));
@@ -108,7 +108,7 @@ fn four_readouts_share_one_value_frequency_state_and_keep_honest_guarantees() {
             assert!(root.guarantee.as_ref().is_some_and(|g| g.is_exact()));
         } else {
             assert!(!root.guarantee.as_ref().unwrap().is_exact());
-            let SummaryExpr::SummaryAgg { family, .. } = &summary_input.expr else {
+            let Operator::ASAP(ASAPOp::SummaryAgg { family, .. }) = &summary_input.operator else {
                 panic!()
             };
             assert!(
@@ -118,12 +118,12 @@ fn four_readouts_share_one_value_frequency_state_and_keep_honest_guarantees() {
                 "production has no calibrated error bound"
             );
         }
-        compile_post_asap_dag(root).unwrap();
+        post_asap_dag(root);
     }
 }
 
 #[test]
-fn uncalibrated_frequency_readouts_do_not_bypass_accuracy_targets() {
+fn uncalibrated_frequency_evaluations_do_not_bypass_accuracy_targets() {
     // An unmeasured heuristic remains inspectable but is never certified or
     // automatically selected for a caller-visible bounded-error result.
     for query in ["entropy_over_time(m[5m])", "l2_over_time(m[5m])"] {
@@ -135,16 +135,16 @@ fn uncalibrated_frequency_readouts_do_not_bypass_accuracy_targets() {
                 delta: 0.01,
             },
         ] {
-            let root = Rc::new(lower_promql(query, target.clone()).unwrap());
-            let candidates = SketchAlgorithmStrategy::default_cost_model()
-                .replacements(&TargetSubDAG::new(&root));
+            let root = lower_promql(query, target.clone()).unwrap();
+            let candidates =
+                ASAPStrategies::default_cost_model().replacements(&TargetSubDAG::new(&root));
             let unknown = candidates
                 .iter()
                 .filter(|candidate| {
                     matches!(
                         &candidate.replacement,
-                        Replacement::Summary(node)
-                            if matches!(&node.expr, SummaryExpr::SummaryEstimate { .. })
+                        Replacement::SubDAG(node)
+                            if matches!(&node.operator, Operator::ASAP(ASAPOp::SummaryEstimate { .. }))
                                 && node.guarantee.is_none()
                                 && candidate.has_missing_accuracy_evidence()
                     )
diff --git a/crates/frontend-sql/src/error.rs b/crates/frontend-sql/src/error.rs
index 11d5acff4..059404ac1 100644
--- a/crates/frontend-sql/src/error.rs
+++ b/crates/frontend-sql/src/error.rs
@@ -1,11 +1,11 @@
 use std::fmt;
 
-use asap_types::pre_asap::ResolveDAGError;
+use asap_frontend_common::ResolveDAGError;
 
 /// Errors from lowering a SQL query (parse + plan via DataFusion → the
-/// canonical, unresolved DAG, built directly →
-/// [`resolve_root`](asap_types::pre_asap::resolve_root) binds it to the
-/// resolved DAG, issue #179).
+/// name-based [`UnresolvedOp`](asap_frontend_common::UnresolvedOp) tree →
+/// [`resolve_root`](asap_frontend_common::resolve_root) binds it into the
+/// unified IR).
 ///
 /// Carries no PromQL type — the SQL front end never depends on the PromQL
 /// parser. The language-neutral variants (`UnsupportedFeature` / `WrongLanguage`
@@ -28,8 +28,8 @@ pub enum SqlError {
     UnsupportedFeature(String),
     /// The workload's query language is not SQL.
     WrongLanguage(String),
-    /// Resolving the canonical unresolved DAG failed (name resolution
-    /// against the bound schema).
+    /// Resolving the name-based tree failed (name resolution against the
+    /// bound schema, or schema derivation).
     Convert(ResolveDAGError),
 }
 
diff --git a/crates/frontend-sql/src/lib.rs b/crates/frontend-sql/src/lib.rs
index aa1449e5e..1747b09c8 100644
--- a/crates/frontend-sql/src/lib.rs
+++ b/crates/frontend-sql/src/lib.rs
@@ -1,25 +1,27 @@
-//! SQL front end: parse + plan (via DataFusion) → the canonical, unresolved
-//! shape, built directly (issue #179) → [`resolve_root`].
+//! SQL front end: parse + plan (via DataFusion) → the name-based
+//! [`UnresolvedOp`](asap_frontend_common::UnresolvedOp) tree, built directly
+//! (issue #179) → [`resolve_root`].
 //!
-//! Emits [`UnresolvedQueryExpr`](asap_types::pre_asap::UnresolvedQueryExpr) itself — the
-//! canonical `QueryExpr`, generic over an unresolved
-//! [`ColumnRef`](asap_types::pre_asap::ColumnRef) — directly, rather than a
-//! separate per-language relational DAG; `resolve_root` runs the
-//! [`SchemaResolver`](asap_types::pre_asap::SchemaResolver) for positional name resolution.
+//! Emits the shared front-end tree (`UnresolvedOp` / `UnresolvedScalar`,
+//! name-based [`ColumnRef`](asap_types::pre_asap::ColumnRef)s) directly, rather
+//! than a separate per-language relational tree; `resolve_root` binds it into
+//! the unified [`OperatorNode`] IR, deriving every schema on the way.
 //! Depends on DataFusion only — never on the PromQL parser.
 
 pub mod error;
 pub mod sql;
 
-use asap_types::pre_asap::resolve_root;
-use asap_types::pre_asap::QueryExpr;
+use std::rc::Rc;
+
+use asap_frontend_common::resolve_root;
+use asap_types::ir::OperatorNode;
 use asap_types::types::AccuracyTarget;
 use asap_types::workload::{QueryLanguage, QueryWorkload, SqlDialect};
 
 pub use error::SqlError;
 pub use sql::{SqlCatalog, SqlLowerer};
 
-/// Lower a single SQL query string to the canonical, resolved `QueryExpr`,
+/// Lower a single SQL query string to the resolved, canonical operator DAG,
 /// parsed as `SqlDialect::DataFusionSQL`.
 ///
 /// The `catalog` supplies table schemas (used both to plan the SQL with
@@ -29,7 +31,7 @@ pub async fn lower_sql(
     query: &str,
     catalog: &SqlCatalog,
     accuracy: AccuracyTarget,
-) -> Result<QueryExpr, SqlError> {
+) -> Result<Rc<OperatorNode>, SqlError> {
     lower_sql_dialect(query, catalog, SqlDialect::DataFusionSQL, accuracy).await
 }
 
@@ -46,20 +48,17 @@ pub async fn lower_sql_dialect(
     catalog: &SqlCatalog,
     dialect: SqlDialect,
     accuracy: AccuracyTarget,
-) -> Result<QueryExpr, SqlError> {
+) -> Result<Rc<OperatorNode>, SqlError> {
     let unresolved = SqlLowerer::with_dialect(catalog, dialect)
         .lower(query, &accuracy)
         .await?;
-    let resolved = resolve_root(&unresolved)?;
-    // Binding resolves names; schema inference also checks result types such
-    // as temporal subtraction, whose duration unit the IR cannot represent.
-    resolved
-        .output_schema()
-        .map_err(|error| SqlError::InvalidExpression(error.to_string()))?;
-    Ok(resolved)
+    // Binding resolves names and derives every node's schema; result-type
+    // checks (such as temporal subtraction, whose duration unit the IR cannot
+    // represent) surface here as `ResolveDAGError::Schema`.
+    Ok(resolve_root(&unresolved)?)
 }
 
-/// Lower every SQL batch entry in `workload` to a `QueryExpr`.
+/// Lower every SQL batch entry in `workload` to an operator DAG.
 ///
 /// One `Result` per entry — errors are per-query, not fatal for the batch.
 /// Returns `WrongLanguage` for every entry if the workload is not SQL, and
@@ -67,7 +66,7 @@ pub async fn lower_sql_dialect(
 pub async fn lower_sql_batch(
     workload: &QueryWorkload,
     catalog: &SqlCatalog,
-) -> Vec<Result<QueryExpr, SqlError>> {
+) -> Vec<Result<Rc<OperatorNode>, SqlError>> {
     let entries = match &workload.query_batch {
         Some(e) if !e.is_empty() => e,
         _ => return vec![],
@@ -102,6 +101,3 @@ pub async fn lower_sql_batch(
     }
     results
 }
-
-/// Unified SQL lowering; promoted to the root API at the planner cutover.
-pub mod unified;
diff --git a/crates/frontend-sql/src/sql/collection_planning.rs b/crates/frontend-sql/src/sql/collection_planning.rs
index 9d28cd1df..62bbbbb6d 100644
--- a/crates/frontend-sql/src/sql/collection_planning.rs
+++ b/crates/frontend-sql/src/sql/collection_planning.rs
@@ -1,10 +1,10 @@
 //! DataFusion planning adapters. Types come from the canonical signature rules;
 //! physical evaluation deliberately remains the query engine's responsibility.
 use super::types::{arrow_to_dtype, dtype_to_arrow, scalar_value_to_asap};
-use asap_types::pre_asap::scalar_type_rules::{
-    element_access_type, struct_field_type, MapScalarFunction,
-};
-use asap_types::pre_asap::{Field, QueryExpr, Schema};
+use asap_types::ir::scalar::{element_access_type, struct_field_type};
+use asap_types::ir::ScalarExpr;
+use asap_types::pre_asap::scalar_type_rules::MapScalarFunction;
+use asap_types::pre_asap::{Field, Schema};
 use datafusion::arrow::datatypes::{DataType, Field as ArrowField, FieldRef};
 use datafusion::common::{DataFusionError, Result, ScalarValue as DfScalarValue};
 use datafusion::logical_expr::{
@@ -108,10 +108,10 @@ impl CollectionPlanningFunction {
                 .map(|index| {
                     if let Some(Some(value)) = literals.and_then(|args| args.get(index)) {
                         scalar_value_to_asap(value)
-                            .map(QueryExpr::Literal)
+                            .map(ScalarExpr::Literal)
                             .map_err(|error| DataFusionError::Plan(error.to_string()))
                     } else {
-                        Ok(QueryExpr::Column(index))
+                        Ok(ScalarExpr::Column(index))
                     }
                 })
                 .collect::<Result<Vec<_>>>()?;
diff --git a/crates/frontend-sql/src/sql/expr.rs b/crates/frontend-sql/src/sql/expr.rs
index 32ba893df..3faf9c306 100644
--- a/crates/frontend-sql/src/sql/expr.rs
+++ b/crates/frontend-sql/src/sql/expr.rs
@@ -2,12 +2,14 @@ use std::rc::Rc;
 
 use datafusion::logical_expr::{BinaryExpr, Expr, Operator};
 
+use asap_frontend_common::UnresolvedScalar as Unresolved;
+use asap_types::ir::ExprSemantics;
 use asap_types::pre_asap::{ArithmeticOpKind, ColumnRef, CompareOpKind, ScalarValue};
 
 use crate::error::SqlError as LoweringError;
 
 use super::types::{arrow_to_dtype, scalar_value_to_asap};
-use super::Unresolved;
+use super::SqlLowerer;
 
 pub(super) fn split_conjuncts(expr: &Expr) -> Vec<&Expr> {
     match expr {
@@ -24,258 +26,276 @@ pub(super) fn split_conjuncts(expr: &Expr) -> Vec<&Expr> {
     }
 }
 
-/// Translate a DataFusion `Expr` to the canonical, unresolved DAG.
-/// Returns `UnsupportedFeature` for anything not needed in v1.
-pub(super) fn df_expr_to_unresolved(expr: &Expr) -> Result<Unresolved, LoweringError> {
-    match expr {
-        // Preserve DataFusion's relation qualifier so a column name shared
-        // across a join (`a.k` vs `b.k`) resolves to the correct side.
-        Expr::Column(col) => Ok(Unresolved::Column(match &col.relation {
-            Some(rel) => ColumnRef::Qualified {
-                table: rel.to_string(),
-                name: col.name.clone(),
-            },
-            None => ColumnRef::Named(col.name.clone()),
-        })),
-
-        // Keep Arrow date literals equivalent to SQL CAST('YYYY-MM-DD' AS DATE),
-        // including typed nulls, without adding another canonical scalar variant.
-        Expr::Literal(
-            sv @ (datafusion::common::ScalarValue::Date32(_)
-            | datafusion::common::ScalarValue::Date64(_)),
-            _,
-        ) => {
-            let text = sv.cast_to(&datafusion::arrow::datatypes::DataType::Utf8)?;
-            // Arrow formats Date64 with a time suffix; the canonical Date has
-            // no time-of-day, just like Date64 catalog registration as Date32.
-            let text = match text {
-                datafusion::common::ScalarValue::Utf8(Some(value)) => {
-                    ScalarValue::Utf8(value.split('T').next().unwrap().to_owned())
-                }
-                other => scalar_value_to_asap(&other)?,
-            };
-            Ok(Unresolved::Cast {
-                expr: Rc::new(Unresolved::Literal(text)),
-                to: asap_types::pre_asap::schema::DataType::Date,
-                try_cast: false,
-            })
-        }
-        Expr::Literal(sv, _) => scalar_value_to_asap(sv).map(Unresolved::Literal),
-
-        Expr::Alias(a) => df_expr_to_unresolved(&a.expr),
+impl SqlLowerer<'_> {
+    /// Translate a DataFusion `Expr` to the name-based scalar tree. Every
+    /// `Compare` / `Arithmetic` / `Negative` carries `ExprSemantics::Sql`.
+    /// Subquery-valued expressions lower their plan as a root of its own
+    /// (which is why this is a method: the plan walk needs the catalog).
+    /// Returns `UnsupportedFeature` for anything not needed in v1.
+    pub(super) fn lower_expr(&self, expr: &Expr) -> Result<Unresolved, LoweringError> {
+        let bx = |e: &Expr| self.lower_expr(e).map(Box::new);
+        match expr {
+            // Preserve DataFusion's relation qualifier so a column name shared
+            // across a join (`a.k` vs `b.k`) resolves to the correct side.
+            Expr::Column(col) => Ok(Unresolved::Column(match &col.relation {
+                Some(rel) => ColumnRef::Qualified {
+                    table: rel.to_string(),
+                    name: col.name.clone(),
+                },
+                None => ColumnRef::Named(col.name.clone()),
+            })),
 
-        Expr::BinaryExpr(BinaryExpr { left, op, right }) => match op {
-            Operator::And => {
-                let parts = split_conjuncts(expr);
-                let lowered: Result<Vec<_>, _> =
-                    parts.iter().map(|e| df_expr_to_unresolved(e)).collect();
-                Ok(Unresolved::BoolAnd(lowered?))
-            }
-            Operator::Or => {
-                let parts = split_disjuncts(expr);
-                let lowered: Result<Vec<_>, _> =
-                    parts.iter().map(|e| df_expr_to_unresolved(e)).collect();
-                Ok(Unresolved::BoolOr(lowered?))
+            // Keep Arrow date literals equivalent to SQL CAST('YYYY-MM-DD' AS DATE),
+            // including typed nulls, without adding another canonical scalar variant.
+            Expr::Literal(
+                sv @ (datafusion::common::ScalarValue::Date32(_)
+                | datafusion::common::ScalarValue::Date64(_)),
+                _,
+            ) => {
+                let text = sv.cast_to(&datafusion::arrow::datatypes::DataType::Utf8)?;
+                // Arrow formats Date64 with a time suffix; the canonical Date has
+                // no time-of-day, just like Date64 catalog registration as Date32.
+                let text = match text {
+                    datafusion::common::ScalarValue::Utf8(Some(value)) => {
+                        ScalarValue::Utf8(value.split('T').next().unwrap().to_owned())
+                    }
+                    other => scalar_value_to_asap(&other)?,
+                };
+                Ok(Unresolved::Cast {
+                    expr: Box::new(Unresolved::Literal(text)),
+                    to: asap_types::pre_asap::schema::DataType::Date,
+                    try_cast: false,
+                })
             }
-            Operator::Eq => compare(left, CompareOpKind::Eq, right),
-            Operator::NotEq => compare(left, CompareOpKind::Ne, right),
-            Operator::Lt => compare(left, CompareOpKind::Lt, right),
-            Operator::LtEq => compare(left, CompareOpKind::Le, right),
-            Operator::Gt => compare(left, CompareOpKind::Gt, right),
-            Operator::GtEq => compare(left, CompareOpKind::Ge, right),
-            // BinaryExpr LIKE/ILIKE operators (from optimizer rewrites)
-            Operator::LikeMatch => compare(left, CompareOpKind::Like, right),
-            Operator::ILikeMatch => compare(left, CompareOpKind::ILike, right),
-            Operator::NotLikeMatch => compare(left, CompareOpKind::NotLike, right),
-            Operator::NotILikeMatch => compare(left, CompareOpKind::NotILike, right),
-            // Arithmetic
-            Operator::Plus => arith(left, ArithmeticOpKind::Add, right),
-            Operator::Minus => arith(left, ArithmeticOpKind::Sub, right),
-            Operator::Multiply => arith(left, ArithmeticOpKind::Mul, right),
-            Operator::Divide => arith(left, ArithmeticOpKind::Div, right),
-            Operator::Modulo => arith(left, ArithmeticOpKind::Mod, right),
-            other => Err(LoweringError::UnsupportedFeature(format!(
-                "operator: {other:?}"
-            ))),
-        },
+            Expr::Literal(sv, _) => scalar_value_to_asap(sv).map(Unresolved::Literal),
 
-        // SQL LIKE / ILIKE (dedicated expr node from the SQL parser)
-        Expr::Like(like) => {
-            let op = match (like.negated, like.case_insensitive) {
-                (false, false) => CompareOpKind::Like,
-                (true, false) => CompareOpKind::NotLike,
-                (false, true) => CompareOpKind::ILike,
-                (true, true) => CompareOpKind::NotILike,
-            };
-            compare(&like.expr, op, &like.pattern)
-        }
+            Expr::Alias(a) => self.lower_expr(&a.expr),
 
-        // Unary minus: negate literals directly; wrap others in -1 * x.
-        Expr::Negative(inner) => {
-            let inner = df_expr_to_unresolved(inner)?;
-            match inner {
-                Unresolved::Literal(ScalarValue::Int64(v)) => {
-                    Ok(Unresolved::Literal(ScalarValue::Int64(-v)))
+            Expr::BinaryExpr(BinaryExpr { left, op, right }) => match op {
+                Operator::And => {
+                    let parts = split_conjuncts(expr);
+                    let lowered: Result<Vec<_>, _> =
+                        parts.iter().map(|e| self.lower_expr(e)).collect();
+                    Ok(Unresolved::BoolAnd(lowered?))
                 }
-                Unresolved::Literal(ScalarValue::Float64(v)) => {
-                    Ok(Unresolved::Literal(ScalarValue::Float64(-v)))
+                Operator::Or => {
+                    let parts = split_disjuncts(expr);
+                    let lowered: Result<Vec<_>, _> =
+                        parts.iter().map(|e| self.lower_expr(e)).collect();
+                    Ok(Unresolved::BoolOr(lowered?))
                 }
-                other => Ok(Unresolved::Arithmetic {
-                    op: ArithmeticOpKind::Mul,
-                    left: Rc::new(Unresolved::Literal(ScalarValue::Int64(-1))),
-                    right: Rc::new(other),
-                }),
+                Operator::Eq => self.compare(left, CompareOpKind::Eq, right),
+                Operator::NotEq => self.compare(left, CompareOpKind::Ne, right),
+                Operator::Lt => self.compare(left, CompareOpKind::Lt, right),
+                Operator::LtEq => self.compare(left, CompareOpKind::Le, right),
+                Operator::Gt => self.compare(left, CompareOpKind::Gt, right),
+                Operator::GtEq => self.compare(left, CompareOpKind::Ge, right),
+                // BinaryExpr LIKE/ILIKE operators (from optimizer rewrites)
+                Operator::LikeMatch => self.compare(left, CompareOpKind::Like, right),
+                Operator::ILikeMatch => self.compare(left, CompareOpKind::ILike, right),
+                Operator::NotLikeMatch => self.compare(left, CompareOpKind::NotLike, right),
+                Operator::NotILikeMatch => self.compare(left, CompareOpKind::NotILike, right),
+                // Arithmetic
+                Operator::Plus => self.arith(left, ArithmeticOpKind::Add, right),
+                Operator::Minus => self.arith(left, ArithmeticOpKind::Sub, right),
+                Operator::Multiply => self.arith(left, ArithmeticOpKind::Mul, right),
+                Operator::Divide => self.arith(left, ArithmeticOpKind::Div, right),
+                Operator::Modulo => self.arith(left, ArithmeticOpKind::Mod, right),
+                other => Err(LoweringError::UnsupportedFeature(format!(
+                    "operator: {other:?}"
+                ))),
+            },
+
+            // SQL LIKE / ILIKE (dedicated expr node from the SQL parser)
+            Expr::Like(like) => {
+                let op = match (like.negated, like.case_insensitive) {
+                    (false, false) => CompareOpKind::Like,
+                    (true, false) => CompareOpKind::NotLike,
+                    (false, true) => CompareOpKind::ILike,
+                    (true, true) => CompareOpKind::NotILike,
+                };
+                self.compare(&like.expr, op, &like.pattern)
             }
-        }
 
-        // SQL CASE expression
-        Expr::Case(c) => {
-            let operand = c
-                .expr
-                .as_ref()
-                .map(|e| df_expr_to_unresolved(e).map(Rc::new))
-                .transpose()?;
-            let branches = c
-                .when_then_expr
-                .iter()
-                .map(|(when, then)| {
-                    Ok((df_expr_to_unresolved(when)?, df_expr_to_unresolved(then)?))
+            // Unary minus. (DataFusion's planner already folds `-<number>`
+            // into a negative literal, so this is a non-literal operand.)
+            Expr::Negative(inner) => Ok(Unresolved::Negative {
+                expr: bx(inner)?,
+                semantics: ExprSemantics::Sql,
+            }),
+
+            // SQL CASE expression
+            Expr::Case(c) => {
+                let operand = c.expr.as_deref().map(bx).transpose()?;
+                let branches = c
+                    .when_then_expr
+                    .iter()
+                    .map(|(when, then)| Ok((self.lower_expr(when)?, self.lower_expr(then)?)))
+                    .collect::<Result<Vec<_>, LoweringError>>()?;
+                let else_expr = c.else_expr.as_deref().map(bx).transpose()?;
+                Ok(Unresolved::Case {
+                    operand,
+                    branches,
+                    else_expr,
                 })
-                .collect::<Result<Vec<_>, LoweringError>>()?;
-            let else_expr = c
-                .else_expr
-                .as_ref()
-                .map(|e| df_expr_to_unresolved(e).map(Rc::new))
-                .transpose()?;
-            Ok(Unresolved::Case {
-                operand,
-                branches,
-                else_expr,
-            })
-        }
+            }
 
-        Expr::Not(inner) => Ok(Unresolved::Not(Rc::new(df_expr_to_unresolved(inner)?))),
+            Expr::Not(inner) => Ok(Unresolved::Not(bx(inner)?)),
 
-        Expr::IsNull(inner) => Ok(Unresolved::IsNull(Rc::new(df_expr_to_unresolved(inner)?))),
+            Expr::IsNull(inner) => Ok(Unresolved::IsNull(bx(inner)?)),
 
-        Expr::IsNotNull(inner) => Ok(Unresolved::IsNotNull(Rc::new(df_expr_to_unresolved(
-            inner,
-        )?))),
+            Expr::IsNotNull(inner) => Ok(Unresolved::IsNotNull(bx(inner)?)),
 
-        Expr::Cast(c) => {
-            let inner = df_expr_to_unresolved(&c.expr)?;
-            let to = arrow_to_dtype(c.field.data_type())?;
-            Ok(Unresolved::Cast {
-                expr: Rc::new(inner),
-                to,
+            // DataFusion 54 coerces a mixed signed/unsigned integer comparison
+            // (e.g. `approx_distinct(x) >= 1000`) through `Decimal128(20, 0)`.
+            // Canonical integers are all Int64, so that widening is a no-op.
+            Expr::Cast(c)
+                if matches!(
+                    c.field.data_type(),
+                    datafusion::arrow::datatypes::DataType::Decimal128(_, 0)
+                ) =>
+            {
+                self.lower_expr(&c.expr)
+            }
+            Expr::Cast(c) => Ok(Unresolved::Cast {
+                expr: bx(&c.expr)?,
+                to: arrow_to_dtype(c.field.data_type())?,
                 try_cast: false,
-            })
-        }
+            }),
 
-        // TRY_CAST returns NULL on conversion failure; preserve that semantic.
-        Expr::TryCast(c) => {
-            let inner = df_expr_to_unresolved(&c.expr)?;
-            let to = arrow_to_dtype(c.field.data_type())?;
-            Ok(Unresolved::Cast {
-                expr: Rc::new(inner),
-                to,
+            // TRY_CAST returns NULL on conversion failure; preserve that semantic.
+            Expr::TryCast(c) => Ok(Unresolved::Cast {
+                expr: bx(&c.expr)?,
+                to: arrow_to_dtype(c.field.data_type())?,
                 try_cast: true,
-            })
-        }
+            }),
 
-        Expr::InList(il) => {
-            let expr = df_expr_to_unresolved(&il.expr)?;
-            let list: Result<Vec<_>, _> = il.list.iter().map(df_expr_to_unresolved).collect();
-            Ok(Unresolved::InList {
-                expr: Rc::new(expr),
-                list: list?,
-                negated: il.negated,
-            })
-        }
+            Expr::InList(il) => {
+                let list: Result<Vec<_>, _> = il.list.iter().map(|e| self.lower_expr(e)).collect();
+                Ok(Unresolved::InList {
+                    expr: bx(&il.expr)?,
+                    list: list?,
+                    negated: il.negated,
+                })
+            }
+
+            Expr::Between(b) => {
+                // Normalize: `x BETWEEN low AND high` → `x >= low AND x <= high`.
+                // `x NOT BETWEEN low AND high` → `x < low OR x > high`.
+                if b.negated {
+                    let lt = self.compare(&b.expr, CompareOpKind::Lt, &b.low)?;
+                    let gt = self.compare(&b.expr, CompareOpKind::Gt, &b.high)?;
+                    Ok(Unresolved::BoolOr(vec![lt, gt]))
+                } else {
+                    let x_low = self.compare(&b.expr, CompareOpKind::Ge, &b.low)?;
+                    let x_high = self.compare(&b.expr, CompareOpKind::Le, &b.high)?;
+                    Ok(Unresolved::BoolAnd(vec![x_low, x_high]))
+                }
+            }
 
-        Expr::Between(b) => {
-            // Normalize: `x BETWEEN low AND high` → `x >= low AND x <= high`.
-            // `x NOT BETWEEN low AND high` → `x < low OR x > high`.
-            let x_low = compare(&b.expr, CompareOpKind::Ge, &b.low)?;
-            let x_high = compare(&b.expr, CompareOpKind::Le, &b.high)?;
-            if b.negated {
-                // NOT BETWEEN: invert each side
-                let lt = compare(&b.expr, CompareOpKind::Lt, &b.low)?;
-                let gt = compare(&b.expr, CompareOpKind::Gt, &b.high)?;
-                Ok(Unresolved::BoolOr(vec![lt, gt]))
-            } else {
-                Ok(Unresolved::BoolAnd(vec![x_low, x_high]))
+            // `NOW()` / `CURRENT_TIMESTAMP` read the SQL statement evaluation
+            // time. Keep this timestamp-typed leaf distinct from PromQL's
+            // Float64 Unix-seconds `EvalTimestamp`. Issue #184.
+            Expr::ScalarFunction(sf)
+                if sf.args.is_empty()
+                    && matches!(
+                        sf.func.name().to_ascii_lowercase().as_str(),
+                        "now" | "current_timestamp"
+                    ) =>
+            {
+                Ok(Unresolved::CurrentTimestamp)
             }
-        }
 
-        // `NOW()` / `CURRENT_TIMESTAMP` read the SQL statement evaluation
-        // time. Keep this timestamp-typed leaf distinct from PromQL's
-        // Float64 Unix-seconds `EvalTimestamp`. Issue #184.
-        Expr::ScalarFunction(sf)
-            if sf.args.is_empty()
-                && matches!(
-                    sf.func.name().to_ascii_lowercase().as_str(),
-                    "now" | "current_timestamp"
-                ) =>
-        {
-            Ok(Unresolved::CurrentTimestamp)
-        }
+            Expr::ScalarFunction(sf) => {
+                let args: Result<Vec<_>, _> = sf.args.iter().map(|e| self.lower_expr(e)).collect();
+                Ok(Unresolved::FunctionCall {
+                    name: if sf.func.name().eq_ignore_ascii_case("arrayelement") {
+                        "asap_element_access".into()
+                    } else if sf.func.name().eq_ignore_ascii_case("tupleelement") {
+                        "asap_struct_field".into()
+                    } else if sf.func.name() == super::collection_planning::MAP_PLANNING_NAME {
+                        "map".into()
+                    } else {
+                        sf.func.name().to_string()
+                    },
+                    args: args?,
+                })
+            }
 
-        Expr::ScalarFunction(sf) => {
-            let args: Result<Vec<_>, _> = sf.args.iter().map(df_expr_to_unresolved).collect();
-            Ok(Unresolved::FunctionCall {
-                name: if sf.func.name().eq_ignore_ascii_case("arrayelement") {
-                    "asap_element_access".into()
-                } else if sf.func.name().eq_ignore_ascii_case("tupleelement") {
-                    "asap_struct_field".into()
-                } else if sf.func.name() == super::collection_planning::MAP_PLANNING_NAME {
-                    "map".into()
-                } else {
-                    sf.func.name().to_string()
-                },
-                args: args?,
-            })
-        }
+            // Subquery-valued expressions. Each subquery plan is lowered as a
+            // root of its own; `resolve_root` binds it in its own scope, so an
+            // outer reference inside it has nothing to resolve against — a
+            // correlated subquery is rejected rather than mislowered.
+            Expr::ScalarSubquery(sq) => Ok(Unresolved::ScalarSubquery(Rc::new(
+                self.lower_uncorrelated_subquery(sq, "scalar subquery")?,
+            ))),
+            Expr::Exists(ex) => Ok(Unresolved::Exists {
+                subquery: Rc::new(self.lower_uncorrelated_subquery(&ex.subquery, "EXISTS")?),
+                negated: ex.negated,
+            }),
+            Expr::InSubquery(is) => {
+                let fields = is.subquery.subquery.schema().fields().len();
+                if fields != 1 {
+                    return Err(LoweringError::InvalidExpression(format!(
+                        "IN (subquery) must select exactly one column, got {fields}"
+                    )));
+                }
+                Ok(Unresolved::InSubquery {
+                    expr: bx(&is.expr)?,
+                    subquery: Rc::new(
+                        self.lower_uncorrelated_subquery(&is.subquery, "IN (subquery)")?,
+                    ),
+                    negated: is.negated,
+                })
+            }
 
-        // Subquery-valued expressions in a predicate/projection — `x > (SELECT
-        // …)`, `x IN (SELECT …)`, `EXISTS (SELECT …)`. These need a subquery
-        // node in the unresolved expression IR (and a correlated-vs-uncorrelated
-        // decision); rejected cleanly until that lands rather than mislowered.
-        // Derived tables in `FROM` (the common nesting shape) ARE supported —
-        // see `lower_plan`'s `SubqueryAlias` arm.
-        Expr::ScalarSubquery(_) | Expr::InSubquery(_) | Expr::Exists(_) => Err(
-            LoweringError::UnsupportedFeature("subquery-valued expression in predicate".into()),
-        ),
+            other => Err(LoweringError::UnsupportedFeature(format!(
+                "expression: {}",
+                other
+            ))),
+        }
+    }
 
-        other => Err(LoweringError::UnsupportedFeature(format!(
-            "expression: {}",
-            other
-        ))),
+    fn lower_uncorrelated_subquery(
+        &self,
+        sq: &datafusion::logical_expr::Subquery,
+        what: &str,
+    ) -> Result<asap_frontend_common::UnresolvedOp, LoweringError> {
+        if !sq.outer_ref_columns.is_empty() {
+            return Err(LoweringError::UnsupportedFeature(format!(
+                "correlated {what}"
+            )));
+        }
+        self.lower_plan(&sq.subquery)
     }
-}
 
-pub(super) fn compare(
-    left: &Expr,
-    op: CompareOpKind,
-    right: &Expr,
-) -> Result<Unresolved, LoweringError> {
-    Ok(Unresolved::Compare {
-        left: Rc::new(df_expr_to_unresolved(left)?),
-        op,
-        right: Rc::new(df_expr_to_unresolved(right)?),
-    })
-}
+    pub(super) fn compare(
+        &self,
+        left: &Expr,
+        op: CompareOpKind,
+        right: &Expr,
+    ) -> Result<Unresolved, LoweringError> {
+        Ok(Unresolved::Compare {
+            left: Box::new(self.lower_expr(left)?),
+            op,
+            right: Box::new(self.lower_expr(right)?),
+            semantics: ExprSemantics::Sql,
+        })
+    }
 
-pub(super) fn arith(
-    left: &Expr,
-    op: ArithmeticOpKind,
-    right: &Expr,
-) -> Result<Unresolved, LoweringError> {
-    Ok(Unresolved::Arithmetic {
-        op,
-        left: Rc::new(df_expr_to_unresolved(left)?),
-        right: Rc::new(df_expr_to_unresolved(right)?),
-    })
+    fn arith(
+        &self,
+        left: &Expr,
+        op: ArithmeticOpKind,
+        right: &Expr,
+    ) -> Result<Unresolved, LoweringError> {
+        Ok(Unresolved::Arithmetic {
+            op,
+            left: Box::new(self.lower_expr(left)?),
+            right: Box::new(self.lower_expr(right)?),
+            semantics: ExprSemantics::Sql,
+        })
+    }
 }
 
 pub(super) fn split_disjuncts(expr: &Expr) -> Vec<&Expr> {
@@ -296,12 +316,15 @@ pub(super) fn split_disjuncts(expr: &Expr) -> Vec<&Expr> {
 #[cfg(test)]
 mod tests {
     use super::*;
+    use crate::sql::SqlCatalog;
     use asap_types::pre_asap::schema::DataType;
     use datafusion::common::ScalarValue as DfScalarValue;
 
     // Typed Arrow dates normalize to the same typed form as SQL date casts.
     #[test]
     fn arrow_date_literals_preserve_value_and_type() {
+        let catalog = SqlCatalog::new();
+        let lowerer = SqlLowerer::new(&catalog);
         for (value, expected) in [
             (
                 DfScalarValue::Date32(Some(0)),
@@ -314,15 +337,32 @@ mod tests {
             (DfScalarValue::Date32(None), ScalarValue::Null),
             (DfScalarValue::Date64(None), ScalarValue::Null),
         ] {
-            let actual = df_expr_to_unresolved(&Expr::Literal(value, None)).unwrap();
+            let actual = lowerer.lower_expr(&Expr::Literal(value, None)).unwrap();
             assert_eq!(
                 actual,
                 Unresolved::Cast {
-                    expr: Rc::new(Unresolved::Literal(expected)),
+                    expr: Box::new(Unresolved::Literal(expected)),
                     to: DataType::Date,
                     try_cast: false,
                 }
             );
         }
     }
+
+    // Unary minus over a non-literal is the `Negative` scalar, SQL-flavoured.
+    #[test]
+    fn unary_minus_lowers_to_negative_with_sql_semantics() {
+        let catalog = SqlCatalog::new();
+        let lowerer = SqlLowerer::new(&catalog);
+        let expr = Expr::Negative(Box::new(Expr::Column(
+            datafusion::common::Column::new_unqualified("x"),
+        )));
+        assert_eq!(
+            lowerer.lower_expr(&expr).unwrap(),
+            Unresolved::Negative {
+                expr: Box::new(Unresolved::Column(ColumnRef::Named("x".into()))),
+                semantics: ExprSemantics::Sql,
+            }
+        );
+    }
 }
diff --git a/crates/frontend-sql/src/sql/mod.rs b/crates/frontend-sql/src/sql/mod.rs
index 3c708a2ed..78a067f53 100644
--- a/crates/frontend-sql/src/sql/mod.rs
+++ b/crates/frontend-sql/src/sql/mod.rs
@@ -1,12 +1,12 @@
-//! SQL → the canonical, unresolved
-//! [`UnresolvedQueryExpr`](asap_types::pre_asap::query_expr::UnresolvedQueryExpr)
-//! (`QueryExpr<ColumnRef>`).
+//! SQL → the name-based front-end tree
+//! ([`UnresolvedOp`](asap_frontend_common::UnresolvedOp) /
+//! [`UnresolvedScalar`](asap_frontend_common::UnresolvedScalar)).
 //!
 //! Parses SQL via DataFusion (over the catalog's registered tables), then
-//! walks the unoptimized `LogicalPlan` and emits `UnresolvedQueryExpr` nodes with
-//! unresolved `ColumnRef`s directly (issue #179) — the same DAG shape
-//! [`resolve_root`](asap_types::pre_asap::resolve_root) binds to canonical,
-//! positional `QueryExpr<ColumnId>`. Unlike PromQL's front end, SQL's
+//! walks the unoptimized `LogicalPlan` and emits `UnresolvedOp` nodes with
+//! unresolved `ColumnRef`s directly (issue #179) — the same tree shape
+//! [`resolve_root`](asap_frontend_common::resolve_root) binds into the
+//! positional, unified `OperatorNode` IR. Unlike PromQL's front end, SQL's
 //! Ordinary SQL `Aggregate` nodes are `Reduction::Reduce`. The explicit
 //! `asap_rate`/`asap_increase` bridge is the narrow exception: it
 //! spells a time-series range reducer with an explicit value, time-index, and
@@ -52,17 +52,22 @@ use datafusion::prelude::{SessionConfig, SessionContext};
 use datafusion::sql::parser::DFParser;
 use datafusion::sql::sqlparser::dialect::GenericDialect;
 
+use asap_frontend_common::{
+    resolve_root, UnresolvedOp as Unresolved, UnresolvedPredicate as Predicate,
+    UnresolvedProjectItem as ProjectItem, UnresolvedScalar as Scalar, UnresolvedSortKey as SortKey,
+};
 use asap_sql_function_catalog::{AggSemantic, Arity, RewriteKind};
-use asap_types::pre_asap::agg_intent::AggIntent;
-use asap_types::pre_asap::query_expr::{
-    GroupKeys, Predicate, ProjectItem, Reduction, SortKey, Source,
-    UnresolvedQueryExpr as Unresolved, WindowFrame, WindowFrameBound, WindowFrameOffset,
+use asap_types::ir::operator_properties::{
+    GroupKeys, Reduction, Source, WindowFrame, WindowFrameBound, WindowFrameOffset,
     WindowFrameUnits,
 };
+use asap_types::ir::TimeRangeKind;
+use asap_types::pre_asap::agg_intent::AggIntent;
 use asap_types::pre_asap::schema::{DataType, FieldDataType, Schema};
+
 use asap_types::pre_asap::{
-    resolve_column_ref, resolve_root, ColumnRef, CompareOpKind, JoinKind, RelationalSetOpKind,
-    ScalarValue, WindowFuncKind,
+    resolve_column_ref, ColumnRef, CompareOpKind, JoinKind, RelationalSetOpKind, ScalarValue,
+    WindowFuncKind,
 };
 use asap_types::types::AccuracyTarget;
 use asap_types::workload::SqlDialect;
@@ -76,7 +81,6 @@ mod types;
 
 pub use types::SqlCatalog;
 
-use self::expr::df_expr_to_unresolved;
 use self::types::{arrow_to_dtype, scalar_value_to_asap, schema_to_arrow};
 
 std::thread_local! {
@@ -110,10 +114,10 @@ fn current_accuracy() -> AccuracyTarget {
     ACCURACY.with(|a| a.borrow().clone())
 }
 
-/// Lowers SQL strings to the canonical [`UnresolvedQueryExpr`](asap_types::pre_asap::UnresolvedQueryExpr)
-/// over a table [`SqlCatalog`]. Call
-/// [`resolve_root`](asap_types::pre_asap::resolve_root) on the result for
-/// the canonical, resolved DAG.
+/// Lowers SQL strings to the name-based [`UnresolvedOp`](asap_frontend_common::UnresolvedOp)
+/// tree over a table [`SqlCatalog`]. Call
+/// [`resolve_root`](asap_frontend_common::resolve_root) on the result for
+/// the resolved operator DAG.
 pub struct SqlLowerer<'a> {
     catalog: &'a SqlCatalog,
     dialect: SqlDialect,
@@ -139,7 +143,7 @@ impl<'a> SqlLowerer<'a> {
         Self { catalog, dialect }
     }
 
-    /// Parse + lower a SQL query to the canonical, unresolved shape, threading
+    /// Parse + lower a SQL query to the name-based tree, threading
     /// `accuracy` onto every approximate intent (`Count`, `Quantile`,
     /// `Cardinality`) as it is built.
     ///
@@ -166,8 +170,8 @@ impl<'a> SqlLowerer<'a> {
     /// a rule) that isn't wanted here — e.g. it independently rejects a
     /// multi-column `IN (subquery)` before `lower_in_subquery`'s own arity
     /// check would. Going straight to `ApplyFunctionRewrites` avoids that
-    /// entirely: zero behavior change for every query that doesn't call a
-    /// catalog-listed ClickHouse builtin.
+    /// entirely. TypeCoercion then records implicit conversions explicitly,
+    /// including timestamp literals in predicates, before IR validation.
     pub async fn lower(
         &self,
         sql: &str,
@@ -226,6 +230,8 @@ impl<'a> SqlLowerer<'a> {
                 })
             })
         })?;
+        let plan = datafusion::optimizer::analyzer::type_coercion::TypeCoercion::new()
+            .analyze(plan, &ctx.state().options())?;
         let _guard = AccuracyGuard::install(accuracy.clone());
         self.lower_plan(&plan)
     }
@@ -275,8 +281,8 @@ impl<'a> SqlLowerer<'a> {
         // *scalar* builtin — same reason as the `AggregateUDF` loop above
         // (DataFusion otherwise rejects the call as an unknown function
         // during `SqlToRel` conversion), but with no rewrite step to follow:
-        // `df_expr_to_unresolved`'s `Expr::ScalarFunction` arm already lowers
-        // any scalar call generically to `Unresolved::FunctionCall { name,
+        // `lower_expr`'s `Expr::ScalarFunction` arm already lowers any
+        // scalar call generically to `UnresolvedScalar::FunctionCall { name,
         // args }`, so registering the stub is the entire fix (issue #230).
         for builtin in asap_sql_function_catalog::CLICKHOUSE_SCALAR_BUILTINS {
             ctx.register_udf(clickhouse_scalar_builtin_stub_udf(
@@ -308,9 +314,24 @@ impl<'a> SqlLowerer<'a> {
         Ok(ctx)
     }
 
-    fn lower_plan(&self, plan: &LogicalPlan) -> Result<Unresolved, LoweringError> {
+    pub(super) fn lower_plan(&self, plan: &LogicalPlan) -> Result<Unresolved, LoweringError> {
         match plan {
             LogicalPlan::TableScan(scan) => self.lower_table_scan(scan),
+            // The one empty input row of a `SELECT` without `FROM`.
+            LogicalPlan::EmptyRelation(empty) => Ok(Unresolved::Values {
+                rows: if empty.produce_one_row {
+                    vec![vec![]]
+                } else {
+                    vec![]
+                },
+                schema: Schema {
+                    fields: vec![],
+                    time_index: None,
+                    unique_keys: vec![],
+                    closed: true,
+                },
+            }),
+            LogicalPlan::Values(values) => self.lower_values(values),
             LogicalPlan::Filter(filter) => self.lower_filter(filter),
             LogicalPlan::Projection(proj) => self.lower_projection(proj),
             LogicalPlan::Aggregate(agg) => self.lower_aggregate(agg),
@@ -379,9 +400,7 @@ impl<'a> SqlLowerer<'a> {
                                     .iter()
                                     .map(|f| ProjectItem {
                                         alias: Some(f.name().clone()),
-                                        expr: Unresolved::Column(ColumnRef::Named(
-                                            f.name().clone(),
-                                        )),
+                                        expr: Scalar::Column(ColumnRef::Named(f.name().clone())),
                                     })
                                     .collect();
                                 Ok(Unresolved::Project {
@@ -404,108 +423,48 @@ impl<'a> SqlLowerer<'a> {
     /// `WHERE` — a conjunction of ordinary predicates plus, possibly, subquery
     /// predicates (issue #111).
     ///
-    /// `c IN (SELECT …)` and `EXISTS (…)` are not expressions over rows; they are
-    /// *joins*. Each such conjunct peels off into a semi- / anti-join above the
-    /// filter's input, and the remaining conjuncts stay as an ordinary `Filter`.
+    /// The ordinary conjuncts stay one predicate, folded onto a bare `Scan`
+    /// (`filter_or_fold`). A subquery conjunct — `c IN (SELECT …)`, `EXISTS
+    /// (…)`, `x > (SELECT …)` — is a row filter whose predicate reads another
+    /// operator (`UnresolvedScalar::InSubquery` / `Exists` /
+    /// `ScalarSubquery`); each one becomes its own `Filter` **above** the
+    /// ordinary predicate, so the shared `canonicalize` pass can turn it into
+    /// the join it is without having to peel it out of a conjunction or off
+    /// a `Scan` (it only lifts subqueries out of `Filter` / `Project`). A
+    /// semi-join only ever drops left rows, so the two orders agree.
     ///
-    /// The residual filter is applied **below** the joins, which is where it sat
-    /// before: a semi-join only ever drops left rows, so the two orders agree —
-    /// and keeping the fold-onto-`Scan` (`filter_or_fold`) below the joins
-    /// matches where the old converter folded it too.
+    /// The one subquery shape still lowered to a join here is a *correlated*
+    /// `EXISTS`: its correlation references both sides, which only a join
+    /// predicate can bind (a subquery referenced from a scalar position is
+    /// resolved as a root in its own scope).
     fn lower_filter(&self, filter: &logical_expr::Filter) -> Result<Unresolved, LoweringError> {
         let mut conjuncts = Vec::new();
         split_conjunction(&filter.predicate, &mut conjuncts);
-        let (subqueries, residual): (Vec<_>, Vec<_>) = conjuncts
-            .into_iter()
-            .partition(|e| matches!(e, Expr::InSubquery(_) | Expr::Exists(_)));
+        let (subqueries, residual): (Vec<_>, Vec<_>) =
+            conjuncts.into_iter().partition(|e| reads_subquery(e));
 
         let input = self.lower_plan(&filter.input)?;
         let mut node = match rebuild_conjunction(&residual) {
-            Some(pred) => filter_or_fold(df_expr_to_unresolved(&pred)?, input),
+            Some(pred) => filter_or_fold(self.lower_expr(&pred)?, input),
             None => input,
         };
         for sq in subqueries {
             node = match sq {
-                Expr::InSubquery(is) => self.lower_in_subquery(is, node)?,
-                Expr::Exists(ex) => self.lower_exists(ex, node)?,
-                _ => unreachable!("partitioned above"),
+                Expr::Exists(ex) if !ex.subquery.outer_ref_columns.is_empty() => {
+                    self.lower_correlated_exists(ex, node)?
+                }
+                other => Unresolved::Filter {
+                    pred: Predicate(self.lower_expr(other)?),
+                    child: Rc::new(node),
+                },
             };
         }
         Ok(node)
     }
 
-    /// `c IN (SELECT k FROM …)` → a semi-join on `c = k` (issue #111).
-    fn lower_in_subquery(
-        &self,
-        is: &logical_expr::expr::InSubquery,
-        left: Unresolved,
-    ) -> Result<Unresolved, LoweringError> {
-        if is.negated {
-            // `NOT IN` is not an anti-join. Under three-valued logic a single
-            // NULL among the subquery's rows makes `c NOT IN (…)` UNKNOWN for
-            // every `c`, so the query returns nothing — while an anti-join
-            // returns every unmatched left row. Reject rather than mislower.
-            return Err(LoweringError::UnsupportedFeature(
-                "NOT IN (subquery): its NULL semantics are not an anti-join".into(),
-            ));
-        }
-        if !is.subquery.outer_ref_columns.is_empty() {
-            return Err(LoweringError::UnsupportedFeature(
-                "correlated IN (subquery)".into(),
-            ));
-        }
-        let inner = is.subquery.subquery.as_ref();
-        let fields = inner.schema().fields();
-        if fields.len() != 1 {
-            return Err(LoweringError::InvalidExpression(format!(
-                "IN (subquery) must select exactly one column, got {}",
-                fields.len()
-            )));
-        }
-        let key = &fields[0];
-        // Project the key under a name the outer relation cannot also carry. The
-        // join predicate resolves against the concatenated `left ++ right`
-        // schema, and a bare `hosts.service` over an unqualified subquery output
-        // falls back to a name lookup that finds the *left's* `service` first —
-        // silently making the predicate `service = service`, i.e. always true.
-        let right = match inner {
-            // Rebuild the subquery's projection with the synthetic alias, so a
-            // computed key (`SELECT bytes + 1 …`) is named rather than becoming
-            // the anonymous `col_0` that nothing can reference.
-            LogicalPlan::Projection(p) if p.expr.len() == 1 => Unresolved::Project {
-                cols: vec![ProjectItem {
-                    alias: Some(IN_SUBQUERY_KEY.to_string()),
-                    expr: df_expr_to_unresolved(unalias(&p.expr[0]))?,
-                }],
-                qualifier: None,
-                child: Rc::new(self.lower_plan(&p.input)?),
-            },
-            other => Unresolved::Project {
-                cols: vec![ProjectItem {
-                    alias: Some(IN_SUBQUERY_KEY.to_string()),
-                    expr: Unresolved::Column(ColumnRef::Named(key.name().clone())),
-                }],
-                qualifier: None,
-                child: Rc::new(self.lower_plan(other)?),
-            },
-        };
-        Ok(Unresolved::Join {
-            kind: JoinKind::Semi,
-            pred: Predicate(Rc::new(Unresolved::Compare {
-                left: Rc::new(df_expr_to_unresolved(&is.expr)?),
-                op: CompareOpKind::Eq,
-                right: Rc::new(Unresolved::Column(ColumnRef::Named(
-                    IN_SUBQUERY_KEY.to_string(),
-                ))),
-            })),
-            left: Rc::new(left),
-            right: Rc::new(right),
-        })
-    }
-
     /// `[NOT] EXISTS (SELECT … WHERE inner.k = outer.k)` → a semi- / anti-join
     /// on the correlation predicate (issue #111).
-    fn lower_exists(
+    fn lower_correlated_exists(
         &self,
         ex: &logical_expr::expr::Exists,
         left: Unresolved,
@@ -526,12 +485,9 @@ impl<'a> SqlLowerer<'a> {
         // the join predicate. Whatever is left stays an ordinary inner filter.
         let (inner, correlation) = split_correlation(inner)?;
         let right = self.lower_plan(&inner)?;
-        // No correlation conjunct (a genuinely uncorrelated `EXISTS`) means
-        // the join condition is unconditionally true — same convention as an
-        // unconditional `JOIN` (`lower_join`, below).
         let pred = match correlation {
-            Some(e) => Predicate(Rc::new(df_expr_to_unresolved(&e)?)),
-            None => Predicate(Rc::new(Unresolved::Literal(ScalarValue::Boolean(true)))),
+            Some(e) => Predicate(self.lower_expr(&e)?),
+            None => Predicate(Scalar::Literal(ScalarValue::Boolean(true))),
         };
         Ok(Unresolved::Join {
             kind,
@@ -541,6 +497,37 @@ impl<'a> SqlLowerer<'a> {
         })
     }
 
+    /// `VALUES (…), (…)` — one row per values row, typed by DataFusion's
+    /// declared schema. Row expressions have no input-column scope.
+    fn lower_values(&self, values: &logical_expr::Values) -> Result<Unresolved, LoweringError> {
+        let rows = values
+            .values
+            .iter()
+            .map(|row| row.iter().map(|e| self.lower_expr(e)).collect())
+            .collect::<Result<Vec<Vec<_>>, LoweringError>>()?;
+        let fields = values
+            .schema
+            .fields()
+            .iter()
+            .map(|f| {
+                Ok(asap_types::pre_asap::Field::plain(
+                    f.name().clone(),
+                    arrow_to_dtype(f.data_type())?,
+                    f.is_nullable(),
+                ))
+            })
+            .collect::<Result<Vec<_>, LoweringError>>()?;
+        Ok(Unresolved::Values {
+            rows,
+            schema: Schema {
+                fields,
+                time_index: None,
+                unique_keys: vec![],
+                closed: true,
+            },
+        })
+    }
+
     /// Table leaf — carries the catalog's resolved schema directly on `Scan`
     /// (`schema: Some(_)`), so `resolve_root`'s SchemaResolver doesn't need to
     /// usage-derive it (SQL is never schemaless). Projection pushdown is left
@@ -604,23 +591,17 @@ impl<'a> SqlLowerer<'a> {
         let mut conjuncts = join
             .on
             .iter()
-            .map(|(l, r)| {
-                Ok(Unresolved::Compare {
-                    left: Rc::new(df_expr_to_unresolved(l)?),
-                    op: CompareOpKind::Eq,
-                    right: Rc::new(df_expr_to_unresolved(r)?),
-                })
-            })
+            .map(|(l, r)| self.compare(l, CompareOpKind::Eq, r))
             .collect::<Result<Vec<_>, LoweringError>>()?;
         if let Some(filter) = &join.filter {
-            conjuncts.push(df_expr_to_unresolved(filter)?);
+            conjuncts.push(self.lower_expr(filter)?);
         }
-        let pred = Predicate(Rc::new(match conjuncts.len() {
+        let pred = Predicate(match conjuncts.len() {
             // No condition (a CROSS JOIN) is unconditionally true.
-            0 => Unresolved::Literal(ScalarValue::Boolean(true)),
+            0 => Scalar::Literal(ScalarValue::Boolean(true)),
             1 => conjuncts.pop().unwrap(),
-            _ => Unresolved::BoolAnd(conjuncts),
-        }));
+            _ => Scalar::BoolAnd(conjuncts),
+        });
         Ok(Unresolved::Join {
             kind,
             pred,
@@ -643,6 +624,10 @@ impl<'a> SqlLowerer<'a> {
             .window_expr
             .first()
             .ok_or_else(|| LoweringError::InvalidExpression("empty window expression".into()))?;
+        let first = match first {
+            Expr::Alias(alias) => alias.expr.as_ref(),
+            other => other,
+        };
         let Expr::WindowFunction(wf) = first else {
             return Err(LoweringError::InvalidExpression(
                 "expected a window function in Window plan node".into(),
@@ -653,12 +638,12 @@ impl<'a> SqlLowerer<'a> {
             .params
             .args
             .iter()
-            .map(df_expr_to_unresolved)
+            .map(|e| self.lower_expr(e))
             .collect::<Result<Vec<_>, _>>()?;
         // Nth_value: lift N from the (literal) 2nd arg, keep only the column.
         let func = if matches!(func, WindowFuncKind::NthValue(None)) {
             let n = match args.get(1) {
-                Some(Unresolved::Literal(ScalarValue::Int64(n))) if *n > 0 => *n as u64,
+                Some(Scalar::Literal(ScalarValue::Int64(n))) if *n > 0 => *n as u64,
                 other => {
                     return Err(LoweringError::InvalidExpression(format!(
                         "NTH_VALUE requires a positive integer literal 2nd arg, got {other:?}"
@@ -681,7 +666,7 @@ impl<'a> SqlLowerer<'a> {
             .order_by
             .iter()
             .map(|s| {
-                df_expr_to_unresolved(&s.expr).map(|expr| SortKey {
+                self.lower_expr(&s.expr).map(|expr| SortKey {
                     expr,
                     ascending: s.asc,
                     nulls_first: s.nulls_first,
@@ -716,7 +701,7 @@ impl<'a> SqlLowerer<'a> {
             let input = self.lower_plan(&proj.input)?;
             return Ok(match bridge {
                 PlanningBridge::PromqlSubquery { range, resolution } => {
-                    let child = Rc::new(temporal_bridge_projection(proj, input)?);
+                    let child = Rc::new(self.temporal_bridge_projection(proj, input)?);
                     Unresolved::PromqlSubquery {
                         range,
                         resolution: Some(resolution),
@@ -745,22 +730,22 @@ impl<'a> SqlLowerer<'a> {
             .map(|e| match e {
                 Expr::Alias(a) => {
                     let expr = if temporal_input && is_temporal_output_column(&a.expr) {
-                        Unresolved::Column(ColumnRef::Named("value".into()))
+                        Scalar::Column(ColumnRef::Named("value".into()))
                     } else {
-                        df_expr_to_unresolved(&a.expr)?
+                        self.lower_expr(&a.expr)?
                     };
-                    Ok::<ProjectItem<ColumnRef>, LoweringError>(ProjectItem {
+                    Ok::<ProjectItem, LoweringError>(ProjectItem {
                         expr,
                         alias: Some(a.name.clone()),
                     })
                 }
                 _ => {
                     let expr = if temporal_input && is_temporal_output_column(e) {
-                        Unresolved::Column(ColumnRef::Named("value".into()))
+                        Scalar::Column(ColumnRef::Named("value".into()))
                     } else {
-                        df_expr_to_unresolved(e)?
+                        self.lower_expr(e)?
                     };
-                    Ok::<ProjectItem<ColumnRef>, LoweringError>(ProjectItem { expr, alias: None })
+                    Ok::<ProjectItem, LoweringError>(ProjectItem { expr, alias: None })
                 }
             })
             .collect::<Result<Vec<_>, _>>()?;
@@ -807,7 +792,7 @@ impl<'a> SqlLowerer<'a> {
         // reducer expression (`GROUP BY date_trunc(…)`, `SUM(a * 8)`) has no
         // slot. Materialize each one as a derived column in a `Project` beneath
         // the aggregate, then group/reduce over that column (issue #110).
-        let mut derived = DerivedCols::default();
+        let mut derived = DerivedCols::new(self);
 
         // DataFusion strips `AS m` from a grouping expression, so the aggregate
         // schema's field name is what the enclosing Projection references —
@@ -832,7 +817,7 @@ impl<'a> SqlLowerer<'a> {
                         .get(i)
                         .cloned()
                         .unwrap_or_else(|| other.to_string());
-                    derived.materialize(name.clone(), df_expr_to_unresolved(other)?)?;
+                    derived.materialize(name.clone(), self.lower_expr(other)?)?;
                     keys.push(ColumnRef::Named(name));
                 }
             }
@@ -874,7 +859,7 @@ impl<'a> SqlLowerer<'a> {
                 .iter()
                 .map(|f| {
                     f.as_ref()
-                        .map(|f| Ok(Predicate(Rc::new(df_expr_to_unresolved(f)?))))
+                        .map(|f| Ok(Predicate(self.lower_expr(f)?)))
                         .transpose()
                 })
                 .collect::<Result<Vec<_>, LoweringError>>()?
@@ -927,12 +912,7 @@ impl<'a> SqlLowerer<'a> {
             ))
         })?;
 
-        let resolved_input = resolve_root(&input)?;
-        let input_schema = resolved_input.output_schema().map_err(|error| {
-            LoweringError::InvalidExpression(format!(
-                "cannot derive temporal aggregate input schema: {error}"
-            ))
-        })?;
+        let input_schema = resolve_root(&input)?.schema.clone();
         let timestamp_id = resolve_column_ref(&timestamp_ref, &input_schema).map_err(|error| {
             LoweringError::InvalidExpression(format!("{name} timestamp argument: {error}"))
         })?;
@@ -1005,18 +985,18 @@ impl<'a> SqlLowerer<'a> {
         let mut cols = vec![
             ProjectItem {
                 alias: Some("ts".into()),
-                expr: Unresolved::Column(timestamp_ref.clone()),
+                expr: Scalar::Column(timestamp_ref.clone()),
             },
             ProjectItem {
                 alias: Some("value".into()),
-                expr: Unresolved::Column(value_ref.clone()),
+                expr: Scalar::Column(value_ref.clone()),
             },
         ];
         for group_ref in group_refs {
             let group_name = named_ref(&group_ref).to_string();
             cols.push(ProjectItem {
                 alias: Some(group_name),
-                expr: Unresolved::Column(group_ref),
+                expr: Scalar::Column(group_ref),
             });
         }
         let child = Unresolved::Project {
@@ -1024,8 +1004,11 @@ impl<'a> SqlLowerer<'a> {
             qualifier: None,
             child: Rc::new(input),
         };
+        // The explicit window is a range selector over the series, the same
+        // shape PromQL's `rate(m[5m])` lowers to.
         let child = Unresolved::TimeRange {
             range: Duration::from_millis(window_ms),
+            kind: TimeRangeKind::Range,
             child: Rc::new(child),
         };
         let intent = match name.as_str() {
@@ -1104,7 +1087,7 @@ impl<'a> SqlLowerer<'a> {
 
         // Reducer arguments still materialize as derived columns (#110); the
         // grouping keys are plain columns, so they only need carrying through.
-        let mut derived = DerivedCols::default();
+        let mut derived = DerivedCols::new(self);
         for e in &distinct {
             derived.passthrough(e)?;
         }
@@ -1142,10 +1125,10 @@ impl<'a> SqlLowerer<'a> {
                     .map(|((name, dtype), e)| ProjectItem {
                         alias: Some(name.clone()),
                         expr: if level.contains(e) {
-                            Unresolved::Column(ColumnRef::Named(name.clone()))
+                            Scalar::Column(ColumnRef::Named(name.clone()))
                         } else {
-                            Unresolved::Cast {
-                                expr: Rc::new(Unresolved::Literal(ScalarValue::Null)),
+                            Scalar::Cast {
+                                expr: Box::new(Scalar::Literal(ScalarValue::Null)),
                                 to: dtype.clone(),
                                 try_cast: false,
                             }
@@ -1153,7 +1136,7 @@ impl<'a> SqlLowerer<'a> {
                     })
                     .chain(output_names.iter().map(|n| ProjectItem {
                         alias: Some(n.clone()),
-                        expr: Unresolved::Column(ColumnRef::Named(n.clone())),
+                        expr: Scalar::Column(ColumnRef::Named(n.clone())),
                     }))
                     .collect();
                 Ok(Unresolved::Project {
@@ -1185,7 +1168,7 @@ impl<'a> SqlLowerer<'a> {
             .expr
             .iter()
             .map(|s| {
-                df_expr_to_unresolved(&s.expr).map(|expr| SortKey {
+                self.lower_expr(&s.expr).map(|expr| SortKey {
                     expr,
                     ascending: s.asc,
                     nulls_first: s.nulls_first,
@@ -1205,8 +1188,10 @@ impl<'a> SqlLowerer<'a> {
         // Count-ranked `LIMIT k` over a `Sort` is promoted to the heavy-hitter
         // `TopK` by the shared `canonicalize` pass (issue #34), not here.
         Ok(Unresolved::Limit {
-            n: eval_fetch(&limit.fetch).unwrap_or(usize::MAX),
+            // No (literal) fetch is offset-only.
+            n: eval_fetch(&limit.fetch),
             offset: eval_fetch(&limit.skip).unwrap_or(0),
+            partition_by: GroupKeys::none(),
             child: Rc::new(self.lower_plan(&limit.input)?),
         })
     }
@@ -1286,49 +1271,52 @@ fn planning_bridge(
 /// its output slot (`... asap_promql_subquery(...) AS value ...`). This makes
 /// the bridge schema-preserving without silently retaining columns that SQL
 /// projected away.
-fn temporal_bridge_projection(
-    projection: &logical_expr::Projection,
-    child: Unresolved,
-) -> Result<Unresolved, LoweringError> {
-    let cols = projection
-        .expr
-        .iter()
-        .map(|expr| {
-            if let Expr::ScalarFunction(call) = unalias(expr) {
-                if call
-                    .func
-                    .name()
-                    .eq_ignore_ascii_case("asap_promql_subquery")
-                {
-                    let Expr::Alias(alias) = expr else {
-                        return Err(LoweringError::InvalidExpression(
-                            "asap_promql_subquery must have an alias naming its child value column"
-                                .into(),
-                        ));
-                    };
-                    return Ok(ProjectItem {
-                        expr: Unresolved::Column(ColumnRef::Named(alias.name.clone())),
+impl SqlLowerer<'_> {
+    fn temporal_bridge_projection(
+        &self,
+        projection: &logical_expr::Projection,
+        child: Unresolved,
+    ) -> Result<Unresolved, LoweringError> {
+        let cols = projection
+            .expr
+            .iter()
+            .map(|expr| {
+                if let Expr::ScalarFunction(call) = unalias(expr) {
+                    if call
+                        .func
+                        .name()
+                        .eq_ignore_ascii_case("asap_promql_subquery")
+                    {
+                        let Expr::Alias(alias) = expr else {
+                            return Err(LoweringError::InvalidExpression(
+                                "asap_promql_subquery must have an alias naming its child value column"
+                                    .into(),
+                            ));
+                        };
+                        return Ok(ProjectItem {
+                            expr: Scalar::Column(ColumnRef::Named(alias.name.clone())),
+                            alias: Some(alias.name.clone()),
+                        });
+                    }
+                }
+                match expr {
+                    Expr::Alias(alias) => Ok(ProjectItem {
+                        expr: self.lower_expr(&alias.expr)?,
                         alias: Some(alias.name.clone()),
-                    });
+                    }),
+                    other => Ok(ProjectItem {
+                        expr: self.lower_expr(other)?,
+                        alias: None,
+                    }),
                 }
-            }
-            match expr {
-                Expr::Alias(alias) => Ok(ProjectItem {
-                    expr: df_expr_to_unresolved(&alias.expr)?,
-                    alias: Some(alias.name.clone()),
-                }),
-                other => Ok(ProjectItem {
-                    expr: df_expr_to_unresolved(other)?,
-                    alias: None,
-                }),
-            }
+            })
+            .collect::<Result<Vec<_>, LoweringError>>()?;
+        Ok(Unresolved::Project {
+            cols,
+            qualifier: None,
+            child: Rc::new(child),
         })
-        .collect::<Result<Vec<_>, LoweringError>>()?;
-    Ok(Unresolved::Project {
-        cols,
-        qualifier: None,
-        child: Rc::new(child),
-    })
+    }
 }
 
 fn positive_millis_literal(expr: &Expr, argument: &str) -> Result<Duration, LoweringError> {
@@ -1413,8 +1401,8 @@ fn arity_to_signature(arity: Arity) -> Signature {
 // (which must become a real `AggIntent`, hence the rewrite to a native
 // DataFusion aggregate shape `lower_agg_intent` can classify), a scalar
 // function call in this IR is already deliberately opaque —
-// `expr::df_expr_to_unresolved`'s `Expr::ScalarFunction` arm lowers *any*
-// scalar call generically to `Unresolved::FunctionCall { name, args }`, with
+// `SqlLowerer::lower_expr`'s `Expr::ScalarFunction` arm lowers *any*
+// scalar call generically to `UnresolvedScalar::FunctionCall { name, args }`, with
 // zero name-specific logic. So teaching DataFusion's planner to accept a
 // ClickHouse scalar builtin's name — a stub `ScalarUDF`, registered below —
 // is the entire fix; the existing generic lowering already does the rest.
@@ -1933,23 +1921,19 @@ fn lower_arg_selector(
     }))
 }
 
-/// The name an `IN (subquery)`'s key column is projected under, so the join
-/// predicate cannot bind it to a same-named column of the outer relation.
-const IN_SUBQUERY_KEY: &str = "__asap_in_key";
-
 /// Fold `pred` directly onto `child.predicates` when `child` is a bare `Scan`
 /// (a `WHERE` directly over a table), otherwise wrap it in an ordinary
 /// `Filter` — canonical's invariant that a `Filter` never sits directly over a
 /// `Scan`. A front end emitting the canonical shape directly is responsible
 /// for maintaining that invariant itself (issue #179).
-fn filter_or_fold(pred: Unresolved, child: Unresolved) -> Unresolved {
+fn filter_or_fold(pred: Scalar, child: Unresolved) -> Unresolved {
     match child {
         Unresolved::Scan {
             source,
             mut predicates,
             schema,
         } => {
-            predicates.push(Predicate(Rc::new(pred)));
+            predicates.push(Predicate(pred));
             Unresolved::Scan {
                 source,
                 predicates,
@@ -1957,7 +1941,7 @@ fn filter_or_fold(pred: Unresolved, child: Unresolved) -> Unresolved {
             }
         }
         other => Unresolved::Filter {
-            pred: Predicate(Rc::new(pred)),
+            pred: Predicate(pred),
             child: Rc::new(other),
         },
     }
@@ -1974,6 +1958,18 @@ fn split_conjunction<'a>(expr: &'a Expr, out: &mut Vec<&'a Expr>) {
     }
 }
 
+/// Whether `expr` reads another operator anywhere inside it (`EXISTS`,
+/// `IN (…)`, a scalar subquery).
+fn reads_subquery(expr: &Expr) -> bool {
+    expr.exists(|e| {
+        Ok(matches!(
+            e,
+            Expr::ScalarSubquery(_) | Expr::InSubquery(_) | Expr::Exists(_)
+        ))
+    })
+    .expect("the predicate never fails")
+}
+
 /// Re-`AND` the conjuncts, or `None` when there are none left.
 fn rebuild_conjunction(conjuncts: &[&Expr]) -> Option<Expr> {
     conjuncts
@@ -2122,9 +2118,9 @@ fn expand_grouping_set(gs: &logical_expr::GroupingSet) -> Vec<Vec<Expr>> {
 /// The projection also has to carry through the plain columns the aggregate
 /// still references, since a `Project` replaces its child's schema rather than
 /// extending it.
-#[derive(Default)]
-struct DerivedCols {
-    cols: Vec<ProjectItem<ColumnRef>>,
+struct DerivedCols<'l> {
+    lowerer: &'l SqlLowerer<'l>,
+    cols: Vec<ProjectItem>,
     /// Whether any column is genuinely derived. Without one the aggregate keeps
     /// its original child, so DAGs that lower today keep their exact shape.
     any: bool,
@@ -2133,12 +2129,21 @@ struct DerivedCols {
     collision: Option<String>,
 }
 
-impl DerivedCols {
+impl<'l> DerivedCols<'l> {
+    fn new(lowerer: &'l SqlLowerer<'l>) -> Self {
+        Self {
+            lowerer,
+            cols: Vec::new(),
+            any: false,
+            collision: None,
+        }
+    }
+
     /// Add `alias := expr`, or note a collision if `alias` already means
     /// something else. `Project` carries one relation qualifier for all its
     /// columns, so `a.k` and `b.k` cannot both survive it — but that only
     /// matters when a projection gets inserted at all.
-    fn push(&mut self, alias: String, expr: Unresolved) {
+    fn push(&mut self, alias: String, expr: Scalar) {
         let existing = self
             .cols
             .iter()
@@ -2161,12 +2166,12 @@ impl DerivedCols {
         let Expr::Column(c) = unalias(expr) else {
             return Ok(());
         };
-        self.push(c.name.clone(), df_expr_to_unresolved(expr)?);
+        self.push(c.name.clone(), self.lowerer.lower_expr(expr)?);
         Ok(())
     }
 
     /// A genuinely derived column: `alias` now names `expr`'s value.
-    fn materialize(&mut self, alias: String, expr: Unresolved) -> Result<(), LoweringError> {
+    fn materialize(&mut self, alias: String, expr: Scalar) -> Result<(), LoweringError> {
         self.any = true;
         self.push(alias, expr);
         Ok(())
@@ -2188,7 +2193,7 @@ impl DerivedCols {
             let mut rewritten = agg_fn.clone();
             for arg in &mut rewritten.params.args {
                 let alias = unalias(arg).to_string();
-                self.materialize(alias.clone(), df_expr_to_unresolved(arg)?)?;
+                self.materialize(alias.clone(), self.lowerer.lower_expr(arg)?)?;
                 *arg = Expr::Column(DfColumn::new_unqualified(alias));
             }
             return Ok(Expr::AggregateFunction(rewritten));
@@ -2211,12 +2216,12 @@ impl DerivedCols {
         }
         match agg_col_name(&agg_fn.params.args) {
             Some(name) => {
-                self.push(name, df_expr_to_unresolved(arg)?);
+                self.push(name, self.lowerer.lower_expr(arg)?);
                 Ok(expr.clone())
             }
             None => {
                 let alias = unalias(arg).to_string();
-                self.materialize(alias.clone(), df_expr_to_unresolved(arg)?)?;
+                self.materialize(alias.clone(), self.lowerer.lower_expr(arg)?)?;
                 let mut agg_fn = agg_fn.clone();
                 agg_fn.params.args[0] = Expr::Column(DfColumn::new_unqualified(alias));
                 Ok(Expr::AggregateFunction(agg_fn))
@@ -2287,7 +2292,7 @@ fn expr_to_group_ref(expr: &Expr) -> Result<ColumnRef, LoweringError> {
     match expr {
         // Preserve the relation qualifier so a GROUP BY / PARTITION BY key over a
         // join (`b.k` vs `a.k`) resolves to the correct side — the same rule the
-        // scalar predicate path uses (`df_expr_to_unresolved`).
+        // scalar predicate path uses (`lower_expr`).
         Expr::Column(col) => Ok(match &col.relation {
             Some(rel) => ColumnRef::Qualified {
                 table: rel.to_string(),
diff --git a/crates/frontend-sql/tests/bgp_analytics/bgp_analytics.rs b/crates/frontend-sql/tests/bgp_analytics/bgp_analytics.rs
index 23f757985..cc24329cd 100644
--- a/crates/frontend-sql/tests/bgp_analytics/bgp_analytics.rs
+++ b/crates/frontend-sql/tests/bgp_analytics/bgp_analytics.rs
@@ -35,9 +35,12 @@
 //! `Err`, never panics. The pinned per-query outcomes document today's real
 //! coverage so a regression (or a future improvement) is visible, not silent.
 
+use std::rc::Rc;
+
 use asap_frontend_sql::{lower_sql_dialect, SqlCatalog, SqlError as LoweringError};
+use asap_types::ir::{NonASAPOp, OperatorNode};
 use asap_types::pre_asap::schema::{DataType, Field, Schema};
-use asap_types::pre_asap::{AggIntent, GroupKeys, QueryExpr};
+use asap_types::pre_asap::{AggIntent, GroupKeys};
 use asap_types::types::AccuracyTarget;
 use asap_types::workload::SqlDialect;
 use datafusion::error::DataFusionError;
@@ -92,7 +95,7 @@ fn queries() -> Vec<String> {
         .collect()
 }
 
-async fn lower(q: &str) -> Result<QueryExpr, LoweringError> {
+async fn lower(q: &str) -> Result<Rc<OperatorNode>, LoweringError> {
     lower_sql_dialect(
         q,
         &catalog(),
@@ -218,19 +221,19 @@ async fn corpus_lowering_matches_the_pinned_per_query_outcome() {
     );
 }
 
-fn first_aggregate(qe: &QueryExpr) -> Option<(&GroupKeys, &Vec<AggIntent>)> {
-    match qe {
-        QueryExpr::Aggregate {
+fn first_aggregate(node: &OperatorNode) -> Option<(&GroupKeys, &Vec<AggIntent>)> {
+    match node.expect_non_asap() {
+        NonASAPOp::Aggregate {
             reduction,
             measures,
             ..
         } => Some((reduction.expect_reduce(), measures)),
-        QueryExpr::Project { child, .. }
-        | QueryExpr::Filter { child, .. }
-        | QueryExpr::Sort { child, .. }
-        | QueryExpr::Limit { child, .. }
-        | QueryExpr::Dedup { child, .. }
-        | QueryExpr::PromqlSubquery { child, .. } => first_aggregate(child),
+        NonASAPOp::Project { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. }
+        | NonASAPOp::Dedup { child, .. }
+        | NonASAPOp::PromqlSubquery { child, .. } => first_aggregate(child),
         _ => None,
     }
 }
@@ -260,7 +263,7 @@ async fn top_k_queries_are_count_grouped_by_prefix() {
             idx + 1
         );
         assert!(
-            matches!(qe, QueryExpr::Limit { .. }),
+            matches!(qe.expect_non_asap(), NonASAPOp::Limit { .. }),
             "q{} ({label}) top-k shape keeps the LIMIT at the root: {qe:?}",
             idx + 1
         );
diff --git a/crates/frontend-sql/tests/bgp_jan2024_workload/bgp_jan2024_workload.rs b/crates/frontend-sql/tests/bgp_jan2024_workload/bgp_jan2024_workload.rs
index 4c6f0e8ea..d7c750d7d 100644
--- a/crates/frontend-sql/tests/bgp_jan2024_workload/bgp_jan2024_workload.rs
+++ b/crates/frontend-sql/tests/bgp_jan2024_workload/bgp_jan2024_workload.rs
@@ -70,7 +70,7 @@ fn catalog() -> SqlCatalog {
         .with_table("bgp.bgp_updates", updates)
 }
 
-async fn lower(q: &str) -> Result<asap_types::pre_asap::QueryExpr, SqlError> {
+async fn lower(q: &str) -> Result<std::rc::Rc<asap_types::ir::OperatorNode>, SqlError> {
     lower_sql_dialect(
         q,
         &catalog(),
@@ -91,6 +91,8 @@ async fn lower(q: &str) -> Result<asap_types::pre_asap::QueryExpr, SqlError> {
 /// is that signal, ratcheted so a category shifting size is visible.
 #[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord)]
 enum Category {
+    /// A planned expression lacks a faithful registered IR type contract.
+    InvalidRepresentation,
     Lowered,
     /// `DataFusionError::Plan` -- almost entirely "unknown function" for a
     /// ClickHouse-only builtin (`uniqExact`, `countIf`, `splitByChar`, ...).
@@ -119,6 +121,7 @@ fn categorize(err: &SqlError) -> Category {
         SqlError::DataFusion(DataFusionError::SQL(_, _)) => Category::Parse,
         SqlError::DataFusion(DataFusionError::NotImplemented(_)) => Category::NotImplemented,
         SqlError::UnsupportedFeature(_) => Category::UnsupportedFeature,
+        SqlError::Convert(_) => Category::InvalidRepresentation,
         _ => Category::Other,
     }
 }
@@ -194,12 +197,15 @@ async fn corpus_lowering_matches_the_pinned_aggregate_tally() {
     // 152 -> 154: `ScalarValue::Interval` (this branch) converts the
     // `INTERVAL x unit` literal the two `toStartOfInterval(...)` queries
     // carry.
-    // 154 -> 156 (DataFusion 54, issue #611): q128 calls `greatest`, which
-    // DataFusion now provides (was `Plan`), and q129's subquery
-    // `ORDER BY count(*)` no longer fails as `UnsupportedFeature("expression:
-    // count(*)")`.
-    expect(Category::Lowered, 156);
-    expect(Category::Plan, 39);
+    // Previously admitted ClickHouse stubs used placeholder Float64 types.
+    // Unregistered functions and incompatible operands now fail closed.
+    // DataFusion 54 (issue #611): q128's `greatest` is now provided by
+    // DataFusion (was `Plan`) and q129's subquery `ORDER BY count(*)` no
+    // longer fails as `UnsupportedFeature`; one lowers, the other now fails
+    // closed as `InvalidRepresentation`.
+    expect(Category::Lowered, 106);
+    expect(Category::InvalidRepresentation, 54);
+    expect(Category::Plan, 40);
     expect(Category::Schema, 0);
     expect(Category::Parse, 0);
     // One query that used to fail at `uniqExact` (`Plan`) now clears that
@@ -211,7 +217,7 @@ async fn corpus_lowering_matches_the_pinned_aggregate_tally() {
     // Typed Map access lowers one prior gap; six array accesses now fail
     // during typed planning because the Map adapter rejects array inputs.
     expect(Category::NotImplemented, 0);
-    expect(Category::UnsupportedFeature, 5);
+    expect(Category::UnsupportedFeature, 0);
     // Was 2: the two `toStartOfInterval(...)` queries whose `INTERVAL`-literal
     // conversion gap the `toStartOfInterval` note above describes. Both now
     // lower end to end and are counted in `Lowered`.
diff --git a/crates/frontend-sql/tests/data_quality_check/synthetic_packet_trace.rs b/crates/frontend-sql/tests/data_quality_check/synthetic_packet_trace.rs
index caed56594..cce394a08 100644
--- a/crates/frontend-sql/tests/data_quality_check/synthetic_packet_trace.rs
+++ b/crates/frontend-sql/tests/data_quality_check/synthetic_packet_trace.rs
@@ -19,9 +19,12 @@
 //! Schema: `packets(srcip, dstip, srcport, dstport, proto, time, pkt_len)`;
 //! flow / 5-tuple = `(srcip, dstip, srcport, dstport, proto)`.
 
+use std::rc::Rc;
+
 use asap_frontend_sql::{lower_sql, SqlCatalog, SqlError as LoweringError};
+use asap_types::ir::{NonASAPOp, OperatorNode};
 use asap_types::pre_asap::schema::{DataType, Field, Schema};
-use asap_types::pre_asap::{AggIntent, GroupKeys, QueryExpr};
+use asap_types::pre_asap::{AggIntent, GroupKeys};
 use asap_types::types::AccuracyTarget;
 
 const CORPUS: &str = include_str!("data/synthetic_packet_trace_queries.sql");
@@ -67,110 +70,61 @@ fn queries() -> Vec<String> {
 
 // ── DAG helpers ──────────────────────────────────────────────────────────────
 
-/// Every `AggIntent` in the DAG, root-to-leaf.
-fn intents(e: &QueryExpr) -> Vec<AggIntent> {
-    let mut out = Vec::new();
-    fn go(e: &QueryExpr, out: &mut Vec<AggIntent>) {
-        match e {
-            QueryExpr::Aggregate {
-                measures, child, ..
-            } => {
-                out.extend(measures.iter().cloned());
-                go(child, out);
-            }
-            QueryExpr::TimeRange { child, .. }
-            | QueryExpr::TimeShift { child, .. }
-            | QueryExpr::Filter { child, .. }
-            | QueryExpr::Sort { child, .. }
-            | QueryExpr::Limit { child, .. }
-            | QueryExpr::PromqlSubquery { child, .. }
-            | QueryExpr::Dedup { child, .. }
-            | QueryExpr::SQLWindowFunc { child, .. }
-            | QueryExpr::Project { child, .. }
-            | QueryExpr::PromqlRelabel { child, .. }
-            | QueryExpr::PromqlSeriesSample { child, .. }
-            | QueryExpr::PromqlInfoEnrich { child, .. } => go(child, out),
-            QueryExpr::BinaryOp { lhs, rhs, .. }
-            | QueryExpr::Join {
-                left: lhs,
-                right: rhs,
-                ..
-            }
-            | QueryExpr::SetOp {
-                left: lhs,
-                right: rhs,
-                ..
-            } => {
-                go(lhs, out);
-                go(rhs, out);
-            }
-            QueryExpr::Concat { children, .. } => children.iter().for_each(|c| go(c, out)),
-            QueryExpr::PromqlVectorFromScalar(inner) | QueryExpr::PromqlScalarFromVector(inner) => {
-                go(inner, out)
-            }
-            QueryExpr::Scan { .. }
-            | QueryExpr::PromqlScalarBridge(_)
-            | QueryExpr::EvalTimestamp
-            | QueryExpr::CurrentTimestamp => {}
-            // Scalar expression variants (issue #205): `AggIntent` only ever
-            // lives in `Aggregate.measures`, never nested inside a scalar
-            // expression DAG, so there's nothing to recurse into here.
-            QueryExpr::Column(_)
-            | QueryExpr::Literal(_)
-            | QueryExpr::Compare { .. }
-            | QueryExpr::BoolAnd(_)
-            | QueryExpr::BoolOr(_)
-            | QueryExpr::Not(_)
-            | QueryExpr::IsNull(_)
-            | QueryExpr::IsNotNull(_)
-            | QueryExpr::Cast { .. }
-            | QueryExpr::InList { .. }
-            | QueryExpr::FunctionCall { .. }
-            | QueryExpr::Arithmetic { .. }
-            | QueryExpr::Case { .. } => {}
-        }
-    }
-    go(e, &mut out);
-    out
+/// The operator of a front-end node: a front-end DAG never holds an ASAP node.
+fn op(node: &OperatorNode) -> &NonASAPOp {
+    node.expect_non_asap()
+}
+
+/// Every `AggIntent` in the DAG, root-to-leaf (every reachable node —
+/// `AggIntent` only ever lives in `Aggregate.measures`).
+fn intents(e: &Rc<OperatorNode>) -> Vec<AggIntent> {
+    OperatorNode::reachable(e)
+        .iter()
+        .filter_map(|node| match op(node) {
+            NonASAPOp::Aggregate { measures, .. } => Some(measures.clone()),
+            _ => None,
+        })
+        .flatten()
+        .collect()
 }
 
 /// The first `Aggregate`'s `(by, measures)` along the single-child spine. SQL
 /// never lowers to `Reduction::PerEntity` (it has no per-series concept), so
 /// `expect_reduce()` here is a safe, load-bearing assumption for these tests.
-fn first_aggregate(qe: &QueryExpr) -> Option<(&GroupKeys, &Vec<AggIntent>)> {
-    match qe {
-        QueryExpr::Aggregate {
+fn first_aggregate(node: &OperatorNode) -> Option<(&GroupKeys, &Vec<AggIntent>)> {
+    match op(node) {
+        NonASAPOp::Aggregate {
             reduction,
             measures,
             ..
         } => Some((reduction.expect_reduce(), measures)),
-        QueryExpr::Project { child, .. }
-        | QueryExpr::Filter { child, .. }
-        | QueryExpr::Dedup { child, .. }
-        | QueryExpr::Sort { child, .. }
-        | QueryExpr::Limit { child, .. }
-        | QueryExpr::SQLWindowFunc { child, .. }
-        | QueryExpr::PromqlSubquery { child, .. } => first_aggregate(child),
+        NonASAPOp::Project { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Dedup { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. }
+        | NonASAPOp::SQLWindowFunc { child, .. }
+        | NonASAPOp::PromqlSubquery { child, .. } => first_aggregate(child),
         _ => None,
     }
 }
 
 /// Whether a `SQLWindowFunc` (analytic `OVER (…)`) node appears anywhere.
-fn has_window_func(qe: &QueryExpr) -> bool {
-    match qe {
-        QueryExpr::SQLWindowFunc { .. } => true,
-        QueryExpr::Project { child, .. }
-        | QueryExpr::Filter { child, .. }
-        | QueryExpr::Aggregate { child, .. }
-        | QueryExpr::Dedup { child, .. }
-        | QueryExpr::Sort { child, .. }
-        | QueryExpr::Limit { child, .. }
-        | QueryExpr::PromqlSubquery { child, .. } => has_window_func(child),
+fn has_window_func(node: &OperatorNode) -> bool {
+    match op(node) {
+        NonASAPOp::SQLWindowFunc { .. } => true,
+        NonASAPOp::Project { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Aggregate { child, .. }
+        | NonASAPOp::Dedup { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. }
+        | NonASAPOp::PromqlSubquery { child, .. } => has_window_func(child),
         _ => false,
     }
 }
 
-async fn lower(q: &str) -> QueryExpr {
+async fn lower(q: &str) -> Rc<OperatorNode> {
     lower_sql(q, &catalog(), AccuracyTarget::Exact)
         .await
         .unwrap_or_else(|e| panic!("expected {q:?} to lower, got error: {e}"))
diff --git a/crates/frontend-sql/tests/maintained_population.rs b/crates/frontend-sql/tests/maintained_population.rs
index a6347c4aa..b01fbbd69 100644
--- a/crates/frontend-sql/tests/maintained_population.rs
+++ b/crates/frontend-sql/tests/maintained_population.rs
@@ -2,17 +2,17 @@
 use asap_aware_mapping::maintained_population::MaintainedPopulationStrategy;
 use asap_frontend_sql::{lower_sql, SqlCatalog};
 use asap_types::{
-    post_asap::{
-        compile_post_asap_dag,
-        maintained_population::{MaintainedPopulation, PopulationInput},
-        share_common_summary_sub_dags, SummaryExpr, ValueOperation,
+    ir::{
+        apply_lifecycle_timings, cse::share_common_sub_dags, export::compile_physical_asap_dag,
+        ASAPOp, LifecycleAssignment, NonASAPOp, Operator, OperatorNode, TimingMemo,
     },
-    pre_asap::{DataType, Field, QueryExpr, Schema},
+    post_asap::maintained_population::{MaintainedPopulation, PopulationInput},
+    pre_asap::{DataType, Field, Schema},
     types::AccuracyTarget,
 };
 use std::rc::Rc;
 
-async fn aggregate(q: &str) -> Rc<QueryExpr> {
+async fn aggregate(q: &str) -> Rc<OperatorNode> {
     let catalog = SqlCatalog::new().with_table(
         "samples",
         Schema::new(vec![
@@ -20,38 +20,38 @@ async fn aggregate(q: &str) -> Rc<QueryExpr> {
             Field::plain("job", DataType::Utf8, false),
         ]),
     );
-    let root = lower_sql(q, &catalog, AccuracyTarget::Exact).await.unwrap();
-    Rc::new(root)
+    lower_sql(q, &catalog, AccuracyTarget::Exact).await.unwrap()
 }
 
-fn population(
-    mut node: &asap_types::post_asap::SummaryNode,
-) -> (
-    &Rc<asap_types::post_asap::SummaryNode>,
-    &MaintainedPopulation,
-) {
-    while let SummaryExpr::ValueOperation {
-        child,
-        operation: ValueOperation::Project { .. },
-        ..
-    } = &node.expr
-    {
+/// The `MaintainPopulation` node a candidate's evaluation reads, and its spec.
+fn population(mut node: &OperatorNode) -> (&Rc<OperatorNode>, &MaintainedPopulation) {
+    while let Operator::NonASAP(NonASAPOp::Project { child, .. }) = &node.operator {
         node = child;
     }
-    let SummaryExpr::ValueOperation { child, .. } = &node.expr else {
-        panic!("readout")
+    let Operator::ASAP(ASAPOp::EvaluatePopulation { child, .. }) = &node.operator else {
+        panic!("evaluation")
     };
-    let SummaryExpr::ValueOperation {
-        operation: ValueOperation::MaintainPopulation { population },
-        ..
-    } = &child.expr
-    else {
+    let Operator::ASAP(ASAPOp::MaintainPopulation { population, .. }) = &child.operator else {
         panic!("state")
     };
     (child, population)
 }
 
-// Quantile parameters are readout identity, while source, value column and grouping are state identity.
+/// Export `plan` the way the planner does: assign the default lifecycle
+/// timings, then compile the timed DAG.
+fn compile(plan: &Rc<OperatorNode>) -> Result<(), String> {
+    let timed = apply_lifecycle_timings(
+        plan,
+        &LifecycleAssignment::default_maintained(),
+        &mut TimingMemo::new(),
+    )
+    .map_err(|e| e.to_string())?;
+    compile_physical_asap_dag(&timed)
+        .map(|_| ())
+        .map_err(|e| e.to_string())
+}
+
+// Quantile parameters are evaluation identity, while source, value column and grouping are state identity.
 #[tokio::test]
 async fn sql_quantiles_share_rows_without_promql_lookback() {
     let roots = vec![
@@ -59,7 +59,7 @@ async fn sql_quantiles_share_rows_without_promql_lookback() {
         aggregate("SELECT approx_percentile_cont(latency, 0.99) FROM samples").await,
     ];
     let rule = MaintainedPopulationStrategy::new(&roots);
-    let plans = share_common_summary_sub_dags(
+    let plans = share_common_sub_dags(
         roots
             .iter()
             .enumerate()
@@ -67,7 +67,7 @@ async fn sql_quantiles_share_rows_without_promql_lookback() {
             .collect(),
     );
     for (_, plan) in &plans {
-        compile_post_asap_dag(plan).unwrap();
+        compile(plan).unwrap();
     }
     let (a, spec) = population(&plans[0].1);
     let (b, _) = population(&plans[1].1);
@@ -107,9 +107,9 @@ async fn sql_filters_separate_populations() {
     assert_ne!(population(&a).1.input, population(&b).1.input);
 }
 
-// All four scalar readouts can share the same non-null numeric SQL population.
+// All four scalar evaluations can share the same non-null numeric SQL population.
 #[tokio::test]
-async fn sql_scalar_readouts_share_membership() {
+async fn sql_scalar_evaluations_share_membership() {
     let mut roots = Vec::new();
     for function in [
         "median(latency)",
@@ -120,7 +120,7 @@ async fn sql_scalar_readouts_share_membership() {
         roots.push(aggregate(&format!("SELECT {function} FROM samples")).await);
     }
     let rule = MaintainedPopulationStrategy::new(&roots);
-    let plans = share_common_summary_sub_dags(
+    let plans = share_common_sub_dags(
         roots
             .iter()
             .enumerate()
@@ -128,27 +128,29 @@ async fn sql_scalar_readouts_share_membership() {
             .collect(),
     );
     for (_, plan) in &plans {
-        compile_post_asap_dag(plan).unwrap();
+        compile(plan).unwrap();
         assert!(Rc::ptr_eq(population(&plans[0].1).0, population(plan).0));
     }
 }
 
-// A readout cannot reinterpret a label column as its numeric population.
+// A evaluation cannot reinterpret a label column as its numeric population.
 #[tokio::test]
 async fn malformed_table_population_fails_validation() {
     let root = aggregate("SELECT median(latency) FROM samples").await;
     let rule = MaintainedPopulationStrategy::new(std::slice::from_ref(&root));
     let mut candidate = rule.candidate(&root).unwrap();
-    let SummaryExpr::ValueOperation { child, .. } = &mut Rc::make_mut(&mut candidate).expr else {
+    let Operator::NonASAP(NonASAPOp::Project { child, .. }) =
+        &mut Rc::make_mut(&mut candidate).operator
+    else {
         unreachable!()
     };
-    let SummaryExpr::ValueOperation { child, .. } = &mut Rc::make_mut(child).expr else {
+    let Operator::ASAP(ASAPOp::EvaluatePopulation { child, .. }) =
+        &mut Rc::make_mut(child).operator
+    else {
         unreachable!()
     };
-    let SummaryExpr::ValueOperation {
-        operation: ValueOperation::MaintainPopulation { population },
-        ..
-    } = &mut Rc::make_mut(child).expr
+    let Operator::ASAP(ASAPOp::MaintainPopulation { population, .. }) =
+        &mut Rc::make_mut(child).operator
     else {
         unreachable!()
     };
@@ -156,7 +158,7 @@ async fn malformed_table_population_fails_validation() {
         unreachable!()
     };
     *value_column = 1;
-    assert!(compile_post_asap_dag(&candidate).is_err());
+    assert!(compile(&candidate).is_err());
 }
 
 // SQL ORDER BY value DESC LIMIT k uses the same maximum-k state contract.
@@ -167,7 +169,7 @@ async fn sql_topk_limits_share_maximum_k() {
         aggregate("SELECT * FROM samples ORDER BY latency DESC LIMIT 5").await,
     ];
     let rule = MaintainedPopulationStrategy::new(&roots);
-    let plans = share_common_summary_sub_dags(
+    let plans = share_common_sub_dags(
         roots
             .iter()
             .enumerate()
@@ -175,7 +177,7 @@ async fn sql_topk_limits_share_maximum_k() {
             .collect(),
     );
     for (_, plan) in &plans {
-        compile_post_asap_dag(plan).unwrap();
+        compile(plan).unwrap();
         assert_eq!(population(plan).1.max_k, 5);
         assert!(Rc::ptr_eq(population(&plans[0].1).0, population(plan).0));
     }
@@ -187,7 +189,7 @@ async fn sql_topk_over_an_identity_select_list_is_recognized() {
     let root = aggregate("SELECT latency, job FROM samples ORDER BY latency DESC LIMIT 5").await;
     let rule = MaintainedPopulationStrategy::new(std::slice::from_ref(&root));
     let plan = rule.candidate(&root).expect("SQL topk");
-    compile_post_asap_dag(&plan).unwrap();
+    compile(&plan).unwrap();
     assert_eq!(population(&plan).1.max_k, 5);
 }
 
diff --git a/crates/frontend-sql/tests/netflow/netflow.rs b/crates/frontend-sql/tests/netflow/netflow.rs
index 22236b850..da680d664 100644
--- a/crates/frontend-sql/tests/netflow/netflow.rs
+++ b/crates/frontend-sql/tests/netflow/netflow.rs
@@ -4,9 +4,12 @@
 //! aggregate over a netflow table, a time predicate, optional grouping,
 //! optional `ORDER BY`/`LIMIT`, plus the nested aggregate shape.
 
+use std::rc::Rc;
+
 use asap_frontend_sql::{lower_sql, SqlCatalog};
+use asap_types::ir::{NonASAPOp, OperatorNode};
 use asap_types::pre_asap::schema::{DataType, Field, Schema};
-use asap_types::pre_asap::{AggIntent, GroupKeys, QueryExpr};
+use asap_types::pre_asap::{AggIntent, GroupKeys};
 use asap_types::types::AccuracyTarget;
 
 const CORPUS: &str = include_str!("data/netflow.sql");
@@ -109,11 +112,10 @@ async fn netflow_sql_corpus_lowers_to_expected_intents() {
     );
 
     for (idx, (query, expected)) in queries.iter().zip(EXPECTED).enumerate() {
+        // A successful `lower_sql` already derived every node's schema.
         let qe = lower_sql(query, &catalog(), AccuracyTarget::Exact)
             .await
             .unwrap_or_else(|err| panic!("q{} failed to lower:\n{query}\n{err}", idx + 1));
-        qe.output_schema()
-            .unwrap_or_else(|err| panic!("q{} schema derivation failed: {err}", idx + 1));
         assert!(
             has_scan_predicate(&qe),
             "q{} should retain the netflow time predicate on the Scan: {qe:?}",
@@ -123,7 +125,7 @@ async fn netflow_sql_corpus_lowers_to_expected_intents() {
     }
 }
 
-fn assert_expected(qe: &QueryExpr, expected: Expected, case_no: usize) {
+fn assert_expected(qe: &Rc<OperatorNode>, expected: Expected, case_no: usize) {
     match expected {
         Expected::Quantile { q, by } => {
             let (actual_by, measures) = first_aggregate(qe).expect("expected Aggregate");
@@ -190,53 +192,58 @@ impl AggKind {
     }
 }
 
-fn first_aggregate(qe: &QueryExpr) -> Option<(&GroupKeys, &Vec<AggIntent>)> {
-    match qe {
-        QueryExpr::Aggregate {
+/// The operator of a front-end node: a front-end DAG never holds an ASAP node.
+fn op(node: &OperatorNode) -> &NonASAPOp {
+    node.expect_non_asap()
+}
+
+fn first_aggregate(node: &OperatorNode) -> Option<(&GroupKeys, &Vec<AggIntent>)> {
+    match op(node) {
+        NonASAPOp::Aggregate {
             reduction,
             measures,
             ..
         } => Some((reduction.expect_reduce(), measures)),
-        QueryExpr::Project { child, .. }
-        | QueryExpr::Filter { child, .. }
-        | QueryExpr::Dedup { child, .. }
-        | QueryExpr::Sort { child, .. }
-        | QueryExpr::Limit { child, .. }
-        | QueryExpr::PromqlSubquery { child, .. } => first_aggregate(child),
+        NonASAPOp::Project { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Dedup { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. }
+        | NonASAPOp::PromqlSubquery { child, .. } => first_aggregate(child),
         _ => None,
     }
 }
 
-fn has_scan_predicate(qe: &QueryExpr) -> bool {
+fn has_scan_predicate(qe: &Rc<OperatorNode>) -> bool {
     any_node(
         qe,
-        |node| matches!(node, QueryExpr::Scan { predicates, .. } if !predicates.is_empty()),
+        |node| matches!(op(node), NonASAPOp::Scan { predicates, .. } if !predicates.is_empty()),
     )
 }
 
-fn has_topk(qe: &QueryExpr, k: usize) -> bool {
+fn has_topk(qe: &Rc<OperatorNode>, k: usize) -> bool {
     any_node(qe, |node| {
         matches!(
-            node,
-            QueryExpr::Aggregate { measures, .. }
+            op(node),
+            NonASAPOp::Aggregate { measures, .. }
                 if measures.iter().any(|agg| matches!(agg, AggIntent::TopK { k: actual, .. } if *actual == k))
         )
     })
 }
 
 fn aggregate_by_with(
-    qe: &QueryExpr,
+    qe: &Rc<OperatorNode>,
     by: &'static [usize],
     pred: impl Fn(&AggIntent) -> bool,
 ) -> bool {
     let expected_by = GroupKeys::by(by.to_vec());
     let mut found = false;
     visit(qe, &mut |node| {
-        if let QueryExpr::Aggregate {
+        if let NonASAPOp::Aggregate {
             reduction,
             measures,
             ..
-        } = node
+        } = op(node)
         {
             found |= *reduction.expect_reduce() == expected_by && measures.iter().any(&pred);
         }
@@ -244,78 +251,26 @@ fn aggregate_by_with(
     found
 }
 
-fn all_intents(qe: &QueryExpr) -> Vec<AggIntent> {
+fn all_intents(qe: &Rc<OperatorNode>) -> Vec<AggIntent> {
     let mut intents = Vec::new();
     visit(qe, &mut |node| {
-        if let QueryExpr::Aggregate { measures, .. } = node {
+        if let NonASAPOp::Aggregate { measures, .. } = op(node) {
             intents.extend(measures.iter().cloned());
         }
     });
     intents
 }
 
-fn any_node(qe: &QueryExpr, pred: impl Fn(&QueryExpr) -> bool) -> bool {
+fn any_node(qe: &Rc<OperatorNode>, pred: impl Fn(&OperatorNode) -> bool) -> bool {
     let mut found = false;
     visit(qe, &mut |node| found |= pred(node));
     found
 }
 
-fn visit(qe: &QueryExpr, f: &mut impl FnMut(&QueryExpr)) {
-    f(qe);
-    match qe {
-        QueryExpr::Project { child, .. }
-        | QueryExpr::Filter { child, .. }
-        | QueryExpr::Aggregate { child, .. }
-        | QueryExpr::TimeRange { child, .. }
-        | QueryExpr::Sort { child, .. }
-        | QueryExpr::Limit { child, .. }
-        | QueryExpr::PromqlSubquery { child, .. }
-        | QueryExpr::Dedup { child, .. }
-        | QueryExpr::SQLWindowFunc { child, .. }
-        | QueryExpr::PromqlRelabel { child, .. }
-        | QueryExpr::PromqlSeriesSample { child, .. }
-        | QueryExpr::TimeShift { child, .. }
-        | QueryExpr::PromqlInfoEnrich { child, .. } => visit(child, f),
-        QueryExpr::BinaryOp { lhs, rhs, .. }
-        | QueryExpr::Join {
-            left: lhs,
-            right: rhs,
-            ..
-        }
-        | QueryExpr::SetOp {
-            left: lhs,
-            right: rhs,
-            ..
-        } => {
-            visit(lhs, f);
-            visit(rhs, f);
-        }
-        QueryExpr::Concat { children, .. } => {
-            for child in children {
-                visit(child, f);
-            }
-        }
-        QueryExpr::PromqlVectorFromScalar(child) | QueryExpr::PromqlScalarFromVector(child) => {
-            visit(child, f)
-        }
-        QueryExpr::Scan { .. }
-        | QueryExpr::PromqlScalarBridge(_)
-        | QueryExpr::EvalTimestamp
-        | QueryExpr::CurrentTimestamp => {}
-        // Scalar expression variants (issue #205) aren't relational nodes;
-        // this visitor only walks the relational DAG, so stop here.
-        QueryExpr::Column(_)
-        | QueryExpr::Literal(_)
-        | QueryExpr::Compare { .. }
-        | QueryExpr::BoolAnd(_)
-        | QueryExpr::BoolOr(_)
-        | QueryExpr::Not(_)
-        | QueryExpr::IsNull(_)
-        | QueryExpr::IsNotNull(_)
-        | QueryExpr::Cast { .. }
-        | QueryExpr::InList { .. }
-        | QueryExpr::FunctionCall { .. }
-        | QueryExpr::Arithmetic { .. }
-        | QueryExpr::Case { .. } => {}
+/// Every reachable operator node, parents before children — including the
+/// operators referenced from scalar positions (subqueries).
+fn visit(qe: &Rc<OperatorNode>, f: &mut impl FnMut(&OperatorNode)) {
+    for node in OperatorNode::reachable(qe) {
+        f(&node);
     }
 }
diff --git a/crates/frontend-sql/tests/pearson_corr.rs b/crates/frontend-sql/tests/pearson_corr.rs
index 618f6c38f..8ef1fb415 100644
--- a/crates/frontend-sql/tests/pearson_corr.rs
+++ b/crates/frontend-sql/tests/pearson_corr.rs
@@ -2,7 +2,11 @@
 use std::rc::Rc;
 
 use asap_frontend_sql::{lower_sql, SqlCatalog};
-use asap_types::pre_asap::{AggIntent, DataType, Field, QueryExpr, Schema};
+use asap_types::ir::{
+    apply_lifecycle_timings, export::compile_physical_asap_dag, LifecycleAssignment, NonASAPOp,
+    OperatorNode, ScalarExpr, TimingMemo,
+};
+use asap_types::pre_asap::{AggIntent, DataType, Field, Schema};
 use asap_types::types::AccuracyTarget;
 
 fn catalog() -> SqlCatalog {
@@ -16,20 +20,20 @@ fn catalog() -> SqlCatalog {
         .with_table("b", schema)
 }
 
-async fn lower(sql: &str) -> QueryExpr {
+async fn lower(sql: &str) -> Rc<OperatorNode> {
     lower_sql(sql, &catalog(), AccuracyTarget::Exact)
         .await
         .unwrap()
 }
 
-fn aggregate(query: &QueryExpr) -> (&[AggIntent], &QueryExpr) {
-    match query {
-        QueryExpr::Aggregate {
+fn aggregate(query: &OperatorNode) -> (&[AggIntent], &OperatorNode) {
+    match query.expect_non_asap() {
+        NonASAPOp::Aggregate {
             measures, child, ..
         } => (measures, child),
-        QueryExpr::Project { child, .. }
-        | QueryExpr::Filter { child, .. }
-        | QueryExpr::Sort { child, .. } => aggregate(child),
+        NonASAPOp::Project { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Sort { child, .. } => aggregate(child),
         other => panic!("expected aggregate, got {other:?}"),
     }
 }
@@ -46,17 +50,14 @@ async fn corr_materializes_both_arguments() {
         let query = lower(sql).await;
         let (measures, child) = aggregate(&query);
         assert_eq!(measures, &[AggIntent::PearsonCorr { left: 0, right: 1 }]);
-        let QueryExpr::Project { cols, .. } = child else {
+        let NonASAPOp::Project { cols, .. } = child.expect_non_asap() else {
             panic!("derived inputs")
         };
         assert_eq!(cols.len(), 2);
         assert!(cols
             .iter()
-            .any(|col| !matches!(col.expr, QueryExpr::Column(_))));
-        assert_eq!(
-            query.output_schema().unwrap().fields[0].dtype,
-            DataType::Float64
-        );
+            .any(|col| !matches!(col.expr, ScalarExpr::Column(_))));
+        assert_eq!(query.schema.fields[0].dtype, DataType::Float64);
     }
 }
 
@@ -66,11 +67,11 @@ async fn corr_preserves_qualified_join_inputs() {
     let query = lower("SELECT corr(a.x, b.x) FROM a JOIN b ON a.g = b.g").await;
     let (measures, child) = aggregate(&query);
     assert_eq!(measures[0].input_cols(), vec![0, 1]);
-    let QueryExpr::Project { cols, .. } = child else {
+    let NonASAPOp::Project { cols, .. } = child.expect_non_asap() else {
         panic!("paired projection")
     };
-    assert_eq!(cols[0].expr, QueryExpr::Column(0));
-    assert_eq!(cols[1].expr, QueryExpr::Column(3));
+    assert_eq!(cols[0].expr, ScalarExpr::Column(0));
+    assert_eq!(cols[1].expr, ScalarExpr::Column(3));
 }
 
 // Grouping and sibling reducers cannot drop either correlation argument.
@@ -82,12 +83,12 @@ async fn corr_coexists_with_grouping_having_and_other_measures() {
         .iter()
         .find(|m| matches!(m, AggIntent::PearsonCorr { .. }))
         .unwrap();
-    let schema = child.output_schema().unwrap();
+    let schema = &child.schema;
     for id in pair.input_cols() {
         assert!(id < schema.fields.len());
     }
     assert!(measures.iter().any(|m| matches!(m, AggIntent::Sum { .. })));
-    let output = query.output_schema().unwrap();
+    let output = &query.schema;
     assert_eq!(output.fields[1].name, "r");
     assert_eq!(output.fields[1].dtype, DataType::Float64);
     assert!(output.fields[1].nullable);
@@ -99,8 +100,8 @@ async fn corr_repeated_input_and_serialization() {
     let query = lower("SELECT corr(x, x) FROM a").await;
     assert_eq!(aggregate(&query).0[0].input_cols(), vec![0, 0]);
     let encoded = serde_json::to_string(&query).unwrap();
-    let decoded: QueryExpr = serde_json::from_str(&encoded).unwrap();
-    assert_eq!(query, decoded);
+    let decoded: OperatorNode = serde_json::from_str(&encoded).unwrap();
+    assert_eq!(*query, decoded);
 }
 
 // Unsupported modifiers and window calls fail instead of silently changing semantics.
@@ -128,10 +129,10 @@ async fn corr_filter_is_a_measure_filter() {
     let query = lower("SELECT corr(x, y) FILTER (WHERE g > 0) FROM a").await;
     let (measures, _) = aggregate(&query);
     assert_eq!(measures[0].input_cols(), vec![0, 1]);
-    fn filters(query: &QueryExpr) -> &[Option<asap_types::pre_asap::Predicate>] {
-        match query {
-            QueryExpr::Aggregate { filters, .. } => filters,
-            QueryExpr::Project { child, .. } | QueryExpr::Filter { child, .. } => filters(child),
+    fn filters(query: &OperatorNode) -> &[Option<asap_types::ir::Predicate>] {
+        match query.expect_non_asap() {
+            NonASAPOp::Aggregate { filters, .. } => filters,
+            NonASAPOp::Project { child, .. } | NonASAPOp::Filter { child, .. } => filters(child),
             other => panic!("expected aggregate, got {other:?}"),
         }
     }
@@ -145,12 +146,17 @@ async fn corr_filter_is_a_measure_filter() {
 // Exact fallback retains the complete typed query and compiles to a post-ASAP DAG.
 #[tokio::test]
 async fn corr_survives_exact_plan_compilation() {
-    let query = Rc::new(lower("SELECT corr(x, y) AS r FROM a").await);
-    let plan = asap_aware_mapping::replacement::keep_pre_asap(&query).unwrap();
+    let query = lower("SELECT corr(x, y) AS r FROM a").await;
+    let plan = asap_aware_mapping::replacement::retain_exact(&query).unwrap();
     assert!(plan.guarantee.as_ref().unwrap().is_exact());
-    let asap_types::post_asap::SummaryExpr::KeepPreAsap(retained) = &plan.expr else {
-        panic!("expected exact fallback");
-    };
-    assert_eq!(aggregate(retained).0, aggregate(&query).0);
-    asap_types::post_asap::compile_post_asap_dag(&plan).unwrap();
+    // The exact fallback is the query's own operator DAG, no ASAP node added.
+    assert!(!plan.contains_asap(), "expected exact fallback");
+    assert_eq!(aggregate(&plan).0, aggregate(&query).0);
+    let timed = apply_lifecycle_timings(
+        &plan,
+        &LifecycleAssignment::default_maintained(),
+        &mut TimingMemo::new(),
+    )
+    .unwrap();
+    compile_physical_asap_dag(&timed).unwrap();
 }
diff --git a/crates/frontend-sql/tests/sql_lowering.rs b/crates/frontend-sql/tests/sql_lowering.rs
index bac54c54d..8e88d0742 100644
--- a/crates/frontend-sql/tests/sql_lowering.rs
+++ b/crates/frontend-sql/tests/sql_lowering.rs
@@ -1,15 +1,24 @@
-//! End-to-end SQL → unresolved → canonical DAG lowering tests (positional IR).
+//! End-to-end SQL → unresolved → resolved operator DAG lowering tests.
 //!
 //! Validates the DataFusion front end: SQL parses + plans, lowers directly to
-//! the canonical, unresolved shape (`QueryExpr<ColumnRef>`, issue #179), and
-//! the shared `resolve_root` produces the positional, resolved canonical
-//! DAG (the same resolver the PromQL path uses).
-
-use asap_frontend_sql::{lower_sql, lower_sql_dialect, SqlCatalog, SqlError as LoweringError};
+//! the name-based `UnresolvedOp` tree (issue #179), and the shared
+//! `resolve_root` produces the positional, canonical `OperatorNode` DAG (the
+//! same resolver the PromQL path uses). Every node's schema is derived during
+//! resolution, so a successful `lower` already proves schema derivation is
+//! total over the tree.
+
+use asap_types::ir::Predicate;
+use std::rc::Rc;
+
+use asap_frontend_common::{UnresolvedOp, UnresolvedScalar};
+use asap_frontend_sql::{
+    lower_sql, lower_sql_dialect, SqlCatalog, SqlError as LoweringError, SqlLowerer,
+};
+use asap_types::ir::{ExprSemantics, NonASAPOp, OperatorNode, ScalarExpr};
 use asap_types::pre_asap::schema::{DataType, Field, FieldDataType, Schema};
 use asap_types::pre_asap::{
-    AggIntent, CompareOpKind, GroupKeys, JoinKind, Predicate, QueryExpr, Reduction, ScalarValue,
-    Source, WindowFrameBound, WindowFrameOffset, WindowFrameUnits, WindowFuncKind,
+    AggIntent, CompareOpKind, GroupKeys, JoinKind, Reduction, ScalarValue, Source,
+    WindowFrameBound, WindowFrameOffset, WindowFrameUnits, WindowFuncKind,
 };
 use asap_types::types::AccuracyTarget;
 use asap_types::workload::SqlDialect;
@@ -43,37 +52,21 @@ fn catalog() -> SqlCatalog {
         )
 }
 
-async fn lower(sql: &str) -> QueryExpr {
+async fn lower(sql: &str) -> Rc<OperatorNode> {
     lower_sql(sql, &catalog(), AccuracyTarget::Exact)
         .await
         .unwrap_or_else(|e| panic!("lower failed for {sql:?}: {e}"))
 }
 
+/// The operator of a front-end node: a front-end DAG never holds an ASAP node.
+fn op(node: &OperatorNode) -> &NonASAPOp {
+    node.expect_non_asap()
+}
+
 #[tokio::test]
-async fn planning_subquery_bridge_reuses_canonical_promql_subquery() {
-    let query = lower(
-        "SELECT max(value) FROM (\
-           SELECT asap_promql_subquery(21600000, 60000) AS value FROM (\
-             SELECT sum(bytes) AS value FROM metrics))",
-    )
-    .await;
-    let QueryExpr::Project { child, .. } = query else {
-        panic!("expected outer SQL projection");
-    };
-    let QueryExpr::Aggregate { child, .. } = child.as_ref() else {
-        panic!("expected outer max aggregate, got {child:?}");
-    };
-    let QueryExpr::PromqlSubquery {
-        range,
-        resolution,
-        child,
-    } = child.as_ref()
-    else {
-        panic!("expected canonical subquery bridge, got {child:?}");
-    };
-    assert_eq!(*range, std::time::Duration::from_secs(6 * 60 * 60));
-    assert_eq!(*resolution, Some(std::time::Duration::from_secs(60)));
-    assert!(matches!(child.as_ref(), QueryExpr::Project { .. }));
+async fn planning_subquery_bridge_rejects_a_relation_without_vector_conversion() {
+    let result = lower_sql("SELECT max(value) FROM (SELECT asap_promql_subquery(21600000, 60000) AS value FROM (SELECT sum(bytes) AS value FROM metrics))", &catalog(), AccuracyTarget::Exact).await;
+    assert!(result.is_err());
 }
 
 #[tokio::test]
@@ -83,12 +76,12 @@ async fn planning_histogram_bridge_reuses_classic_bucket_intent() {
            SELECT service AS le, sum(bytes) AS value FROM metrics GROUP BY service)",
     )
     .await;
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = query
+    } = op(&query)
     else {
         panic!("expected canonical histogram aggregate");
     };
@@ -98,7 +91,7 @@ async fn planning_histogram_bridge_reuses_classic_bucket_intent() {
         measures.as_slice(),
         [AggIntent::HistogramQuantile { q, le: 0 }] if (*q - 0.95).abs() < 1e-12
     ));
-    assert!(matches!(child.as_ref(), QueryExpr::Project { .. }));
+    assert!(matches!(op(child), NonASAPOp::Project { .. }));
 }
 
 #[tokio::test]
@@ -134,31 +127,31 @@ async fn planning_relation_bridges_reject_ambiguous_shapes() {
 }
 
 /// Find the first `Aggregate` node along the single-child spine.
-fn find_aggregate(qe: &QueryExpr) -> Option<(&GroupKeys, &Vec<AggIntent>)> {
-    match qe {
-        QueryExpr::Aggregate {
+fn find_aggregate(node: &OperatorNode) -> Option<(&GroupKeys, &Vec<AggIntent>)> {
+    match op(node) {
+        NonASAPOp::Aggregate {
             reduction,
             measures,
             ..
         } => Some((reduction.expect_reduce(), measures)),
-        QueryExpr::Project { child, .. }
-        | QueryExpr::Filter { child, .. }
-        | QueryExpr::Dedup { child, .. }
-        | QueryExpr::Sort { child, .. }
-        | QueryExpr::Limit { child, .. }
-        | QueryExpr::PromqlSubquery { child, .. } => find_aggregate(child),
+        NonASAPOp::Project { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Dedup { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. }
+        | NonASAPOp::PromqlSubquery { child, .. } => find_aggregate(child),
         _ => None,
     }
 }
 
 /// The first `Aggregate` node itself, for tests that need its child.
-fn find_aggregate_node(qe: &QueryExpr) -> Option<&QueryExpr> {
-    match qe {
-        QueryExpr::Aggregate { .. } => Some(qe),
-        QueryExpr::Project { child, .. }
-        | QueryExpr::Filter { child, .. }
-        | QueryExpr::Sort { child, .. }
-        | QueryExpr::Limit { child, .. } => find_aggregate_node(child),
+fn find_aggregate_node(node: &OperatorNode) -> Option<&OperatorNode> {
+    match op(node) {
+        NonASAPOp::Aggregate { .. } => Some(node),
+        NonASAPOp::Project { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. } => find_aggregate_node(child),
         _ => None,
     }
 }
@@ -166,47 +159,47 @@ fn find_aggregate_node(qe: &QueryExpr) -> Option<&QueryExpr> {
 /// The names of the columns the first `Aggregate`'s reducers read, resolved
 /// against its child's schema, plus whether that child is a materializing
 /// `Project` (issue #110).
-fn reducer_input_names(qe: &QueryExpr) -> (Vec<String>, bool) {
-    let QueryExpr::Aggregate {
+fn reducer_input_names(node: &OperatorNode) -> (Vec<String>, bool) {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = find_aggregate_node(qe).expect("expected an Aggregate")
+    } = op(find_aggregate_node(node).expect("expected an Aggregate"))
     else {
         unreachable!()
     };
-    let schema = child.output_schema().expect("child schema");
+    let schema = &child.schema;
     let names = measures
         .iter()
         .flat_map(|a| a.input_cols())
         .map(|id| schema.fields[id].name.clone())
         .collect();
-    (names, matches!(**child, QueryExpr::Project { .. }))
+    (names, matches!(op(child), NonASAPOp::Project { .. }))
 }
 
 /// Find the first `Join` node along the single-child spine.
-fn find_join(qe: &QueryExpr) -> Option<&QueryExpr> {
-    match qe {
-        QueryExpr::Join { .. } => Some(qe),
-        QueryExpr::Project { child, .. }
-        | QueryExpr::Filter { child, .. }
-        | QueryExpr::Aggregate { child, .. }
-        | QueryExpr::Dedup { child, .. }
-        | QueryExpr::Sort { child, .. }
-        | QueryExpr::Limit { child, .. }
-        | QueryExpr::PromqlSubquery { child, .. } => find_join(child),
+fn find_join(node: &OperatorNode) -> Option<&OperatorNode> {
+    match op(node) {
+        NonASAPOp::Join { .. } => Some(node),
+        NonASAPOp::Project { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Aggregate { child, .. }
+        | NonASAPOp::Dedup { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. }
+        | NonASAPOp::PromqlSubquery { child, .. } => find_join(child),
         _ => None,
     }
 }
 
 /// The first `Filter` node along the single-child spine.
-fn find_filter(qe: &QueryExpr) -> Option<&QueryExpr> {
-    match qe {
-        QueryExpr::Filter { .. } => Some(qe),
-        QueryExpr::Project { child, .. }
-        | QueryExpr::Aggregate { child, .. }
-        | QueryExpr::Dedup { child, .. }
-        | QueryExpr::Sort { child, .. }
-        | QueryExpr::Limit { child, .. }
-        | QueryExpr::PromqlSubquery { child, .. } => find_filter(child),
+fn find_filter(node: &OperatorNode) -> Option<&OperatorNode> {
+    match op(node) {
+        NonASAPOp::Filter { .. } => Some(node),
+        NonASAPOp::Project { child, .. }
+        | NonASAPOp::Aggregate { child, .. }
+        | NonASAPOp::Dedup { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. }
+        | NonASAPOp::PromqlSubquery { child, .. } => find_filter(child),
         _ => None,
     }
 }
@@ -215,14 +208,14 @@ fn find_filter(qe: &QueryExpr) -> Option<&QueryExpr> {
 async fn where_folds_predicate_onto_scan() {
     // WHERE folds onto the Scan predicates, below the SELECT projection.
     let qe = lower("SELECT * FROM metrics WHERE service = 'api'").await;
-    let QueryExpr::Project { child, .. } = &qe else {
+    let NonASAPOp::Project { child, .. } = op(&qe) else {
         panic!("expected Project at root, got {qe:?}");
     };
-    let QueryExpr::Scan {
+    let NonASAPOp::Scan {
         source,
         predicates,
         schema,
-    } = child.as_ref()
+    } = op(child)
     else {
         panic!("expected Scan under the projection, got {child:?}");
     };
@@ -257,9 +250,7 @@ async fn projection_over_aggregate_resolves_output_types_via_output_names() {
     // onto the canonical Aggregate so the Project resolves real types — not
     // the Utf8 fallback that an unresolved column would get.
     let qe = lower("SELECT SUM(bytes), AVG(latency) FROM metrics").await;
-    let schema = qe
-        .output_schema()
-        .expect("root projection schema derivation");
+    let schema = &qe.schema;
     assert_eq!(schema.fields.len(), 2);
     assert_eq!(
         schema.fields[0].dtype,
@@ -287,7 +278,7 @@ async fn single_agg_group_by_keeps_key_in_output_schema() {
     ));
 
     // Both the group key and the aggregate resolve in the root projection schema.
-    let schema = qe.output_schema().expect("root projection schema");
+    let schema = &qe.schema;
     assert_eq!(schema.fields.len(), 2);
     assert_eq!(
         schema.fields[0].dtype,
@@ -318,7 +309,7 @@ async fn count_ranked_topk_is_heavy_hitter() {
         "count-ranked topk → heavy-hitter TopK, got {measures:?}"
     );
     // The inner child is the explicit Count, grouped by service (col 1).
-    let QueryExpr::Aggregate { child, .. } = &qe else {
+    let NonASAPOp::Aggregate { child, .. } = op(&qe) else {
         panic!("expected outer Aggregate, got {qe:?}");
     };
     let (inner_by, inner_measures) = find_aggregate(child).expect("expected inner Count aggregate");
@@ -429,7 +420,7 @@ async fn select_distinct_lowers_to_distinct_with_positional_cols() {
     // (not name-based ColumnRefs). DataFusion's `Distinct::All` dedups on every
     // column, so `cols` is empty here — but the field type is now `Vec<ColumnId>`.
     let qe = lower("SELECT DISTINCT service FROM metrics").await;
-    let QueryExpr::Dedup { cols, .. } = &qe else {
+    let NonASAPOp::Dedup { cols, .. } = op(&qe) else {
         panic!("expected a Dedup at the root, got {qe:?}");
     };
     let _: &Vec<usize> = cols; // compile-time: positional ids, not ColumnRefs
@@ -444,34 +435,35 @@ async fn inner_join_lowers_to_join_over_two_scans() {
          FROM metrics JOIN hosts ON metrics.service = hosts.service",
     )
     .await;
-    let join = find_join(&qe).expect("expected a Join in the DAG");
-    let QueryExpr::Join {
+    let join = find_join(&qe).expect("expected a Join in the tree");
+    let NonASAPOp::Join {
         kind, left, right, ..
-    } = join
+    } = op(join)
     else {
         unreachable!("find_join only returns Join");
     };
     assert_eq!(*kind, JoinKind::Inner);
-    assert!(matches!(left.as_ref(), QueryExpr::Scan { .. }));
-    assert!(matches!(right.as_ref(), QueryExpr::Scan { .. }));
+    assert!(matches!(op(left), NonASAPOp::Scan { .. }));
+    assert!(matches!(op(right), NonASAPOp::Scan { .. }));
 }
 
 /// The two `ColumnId`s an equijoin predicate `Column(l) = Column(r)` binds to,
 /// returned sorted so the assertion is independent of left/right ordering.
-fn join_eq_columns(join: &QueryExpr) -> [usize; 2] {
-    let QueryExpr::Join { pred, .. } = join else {
+fn join_eq_columns(join: &OperatorNode) -> [usize; 2] {
+    let NonASAPOp::Join { pred, .. } = op(join) else {
         unreachable!("expected a Join");
     };
-    let QueryExpr::Compare {
+    let ScalarExpr::Compare {
         left,
         op: CompareOpKind::Eq,
         right,
-    } = pred.0.as_ref()
+        ..
+    } = &pred.0
     else {
         panic!("expected an equijoin Compare, got {:?}", pred.0);
     };
     match (left.as_ref(), right.as_ref()) {
-        (QueryExpr::Column(l), QueryExpr::Column(r)) => {
+        (ScalarExpr::Column(l), ScalarExpr::Column(r)) => {
             let mut cols = [*l, *r];
             cols.sort_unstable();
             cols
@@ -570,12 +562,12 @@ async fn qualified_where_over_join_resolves_to_right_side() {
     )
     .await;
     let filter = find_filter(&qe).expect("expected a Filter over the join");
-    let QueryExpr::Filter { pred, .. } = filter else {
+    let NonASAPOp::Filter { pred, .. } = op(filter) else {
         unreachable!("find_filter only returns Filter");
     };
     assert!(
-        matches!(pred.0.as_ref(), QueryExpr::Compare { left, op: CompareOpKind::Eq, .. }
-            if matches!(left.as_ref(), QueryExpr::Column(4))),
+        matches!(&pred.0, ScalarExpr::Compare { left, op: CompareOpKind::Eq, .. }
+            if matches!(left.as_ref(), ScalarExpr::Column(4))),
         "hosts.service must bind to concatenated position 4 (not the first `service`), got {:?}",
         pred.0
     );
@@ -639,20 +631,24 @@ async fn aggregate_over_join_binds_against_concatenated_schema() {
 }
 
 // ── Issue #111: IN / EXISTS subquery predicates become semi / anti joins ────
+//
+// The front end now leaves them as `UnresolvedScalar::{InSubquery, Exists}`
+// filter conjuncts; the shared `canonicalize` pass (run by `resolve_root`)
+// lowers each to the semi-/anti-join, so the resolved DAG a test sees is the
+// same join shape the front end used to emit directly.
 
 /// The first `Join` node's `(kind, predicate, left column count)`.
-fn join_parts(qe: &QueryExpr) -> (&JoinKind, &QueryExpr, usize) {
-    let QueryExpr::Join {
+fn join_parts(node: &OperatorNode) -> (&JoinKind, &ScalarExpr, usize) {
+    let NonASAPOp::Join {
         kind,
         pred,
         left,
         right: _,
-    } = find_join(qe).expect("expected a Join")
+    } = op(find_join(node).expect("expected a Join"))
     else {
         unreachable!()
     };
-    let left_len = left.output_schema().expect("left schema").fields.len();
-    (kind, pred.0.as_ref(), left_len)
+    (kind, &pred.0, left.schema.fields.len())
 }
 
 #[tokio::test]
@@ -667,14 +663,15 @@ async fn in_subquery_lowers_to_a_semi_join() {
     // The predicate resolves against `left ++ right`. Both relations have a
     // `service` column, so a name-based lookup would bind *both* sides to the
     // left's — silently making this `service = service`, always true. The key is
-    // projected under a synthetic name to make that impossible.
-    let QueryExpr::Compare { left, right, .. } = pred else {
+    // bound positionally to the subquery's column (right after the left's),
+    // which makes that impossible.
+    let ScalarExpr::Compare { left, right, .. } = pred else {
         panic!("expected a comparison, got {pred:?}");
     };
-    assert_eq!(**left, QueryExpr::Column(1), "outer service");
+    assert_eq!(**left, ScalarExpr::Column(1), "outer service");
     assert_eq!(
         **right,
-        QueryExpr::Column(left_len),
+        ScalarExpr::Column(left_len),
         "the subquery key, not the outer column again"
     );
 }
@@ -685,20 +682,14 @@ async fn a_semi_join_outputs_only_the_left_schema() {
     let qe =
         lower("SELECT service FROM metrics WHERE service IN (SELECT service FROM hosts)").await;
     let join = find_join(&qe).expect("expected a Join");
-    let names: Vec<_> = join
-        .output_schema()
-        .expect("join schema")
-        .fields
-        .iter()
-        .map(|c| c.name.clone())
-        .collect();
+    let names: Vec<_> = join.schema.fields.iter().map(|c| c.name.clone()).collect();
     assert_eq!(names, ["ts", "service", "latency", "bytes"]);
 }
 
 #[tokio::test]
 async fn a_subquery_key_that_is_an_expression_still_binds() {
-    // `SELECT bytes + 1 …` has no column name of its own; it is projected under
-    // the synthetic key rather than becoming an unreferenceable `col_0`.
+    // `SELECT bytes + 1 …` has no column name of its own; the join key binds
+    // to it positionally rather than through an unreferenceable `col_0`.
     let qe =
         lower("SELECT service FROM metrics WHERE bytes IN (SELECT bytes + 1 FROM metrics)").await;
     assert_eq!(join_parts(&qe).0, &JoinKind::Semi);
@@ -728,13 +719,13 @@ async fn an_ordinary_conjunct_still_folds_onto_the_scan() {
          AND service IN (SELECT service FROM hosts)",
     )
     .await;
-    fn scan_has_predicate(qe: &QueryExpr) -> bool {
-        match qe {
-            QueryExpr::Scan { predicates, .. } => !predicates.is_empty(),
-            QueryExpr::Project { child, .. }
-            | QueryExpr::Filter { child, .. }
-            | QueryExpr::Aggregate { child, .. } => scan_has_predicate(child),
-            QueryExpr::Join { left, right, .. } => {
+    fn scan_has_predicate(node: &OperatorNode) -> bool {
+        match op(node) {
+            NonASAPOp::Scan { predicates, .. } => !predicates.is_empty(),
+            NonASAPOp::Project { child, .. }
+            | NonASAPOp::Filter { child, .. }
+            | NonASAPOp::Aggregate { child, .. } => scan_has_predicate(child),
+            NonASAPOp::Join { left, right, .. } => {
                 scan_has_predicate(left) || scan_has_predicate(right)
             }
             _ => false,
@@ -748,16 +739,16 @@ async fn an_ordinary_conjunct_still_folds_onto_the_scan() {
 }
 
 /// Find the first `SQLWindowFunc` node along the single-child spine.
-fn find_windowfunc(qe: &QueryExpr) -> Option<&QueryExpr> {
-    match qe {
-        QueryExpr::SQLWindowFunc { .. } => Some(qe),
-        QueryExpr::Project { child, .. }
-        | QueryExpr::Filter { child, .. }
-        | QueryExpr::Aggregate { child, .. }
-        | QueryExpr::Dedup { child, .. }
-        | QueryExpr::Sort { child, .. }
-        | QueryExpr::Limit { child, .. }
-        | QueryExpr::PromqlSubquery { child, .. } => find_windowfunc(child),
+fn find_windowfunc(node: &OperatorNode) -> Option<&OperatorNode> {
+    match op(node) {
+        NonASAPOp::SQLWindowFunc { .. } => Some(node),
+        NonASAPOp::Project { child, .. }
+        | NonASAPOp::Filter { child, .. }
+        | NonASAPOp::Aggregate { child, .. }
+        | NonASAPOp::Dedup { child, .. }
+        | NonASAPOp::Sort { child, .. }
+        | NonASAPOp::Limit { child, .. }
+        | NonASAPOp::PromqlSubquery { child, .. } => find_windowfunc(child),
         _ => None,
     }
 }
@@ -771,12 +762,12 @@ async fn window_function_lowers_to_positional_windowfunc() {
     )
     .await;
     let win = find_windowfunc(&qe).expect("expected a SQLWindowFunc node");
-    let QueryExpr::SQLWindowFunc {
+    let NonASAPOp::SQLWindowFunc {
         func,
         partition_by,
         order_by,
         ..
-    } = win
+    } = op(win)
     else {
         unreachable!("find_windowfunc only returns SQLWindowFunc");
     };
@@ -785,14 +776,14 @@ async fn window_function_lowers_to_positional_windowfunc() {
     assert_eq!(order_by.len(), 1);
     assert_eq!(
         order_by[0].expr,
-        QueryExpr::Column(3),
+        ScalarExpr::Column(3),
         "ORDER BY bytes → col 3"
     );
     assert!(!order_by[0].ascending, "DESC");
 
     // The window output column is appended to the schema (Int64 for ROW_NUMBER),
     // and the enclosing projection resolves it (output_name threading).
-    let schema = qe.output_schema().expect("root schema");
+    let schema = &qe.schema;
     assert!(
         schema.fields.iter().any(|c| c.dtype == DataType::Int64),
         "row_number output column present, got {:?}",
@@ -804,11 +795,11 @@ async fn window_function_lowers_to_positional_windowfunc() {
 async fn window_aggregate_lowers_to_windowfunc() {
     let qe = lower("SELECT service, SUM(bytes) OVER (PARTITION BY service) FROM metrics").await;
     let win = find_windowfunc(&qe).expect("expected a SQLWindowFunc node");
-    let QueryExpr::SQLWindowFunc { func, args, .. } = win else {
+    let NonASAPOp::SQLWindowFunc { func, args, .. } = op(win) else {
         unreachable!();
     };
     assert_eq!(*func, WindowFuncKind::Sum);
-    assert_eq!(args, &vec![QueryExpr::Column(3)], "SUM(bytes) → arg col 3");
+    assert_eq!(args, &vec![ScalarExpr::Column(3)], "SUM(bytes) → arg col 3");
 }
 
 // ── Window frames (issue #268) ───────────────────────────────────────────────
@@ -832,8 +823,8 @@ async fn window_frame_is_captured_not_dropped() {
     )
     .await;
 
-    let frame_of = |qe: &QueryExpr| {
-        let QueryExpr::SQLWindowFunc { frame, .. } = find_windowfunc(qe).unwrap() else {
+    let frame_of = |node: &OperatorNode| {
+        let NonASAPOp::SQLWindowFunc { frame, .. } = op(find_windowfunc(node).unwrap()) else {
             unreachable!();
         };
         frame
@@ -873,9 +864,9 @@ async fn range_interval_frame_is_preserved() {
          RANGE BETWEEN INTERVAL '1' HOUR PRECEDING AND CURRENT ROW) FROM metrics",
     )
     .await;
-    let QueryExpr::SQLWindowFunc {
+    let NonASAPOp::SQLWindowFunc {
         frame: Some(frame), ..
-    } = find_windowfunc(&qe).unwrap()
+    } = op(find_windowfunc(&qe).unwrap())
     else {
         panic!("expected a window function with a concrete frame");
     };
@@ -905,10 +896,10 @@ async fn range_numeric_frames_remain_scalar_offsets() {
     )
     .await;
 
-    let start_bound = |qe: &QueryExpr| {
-        let QueryExpr::SQLWindowFunc {
+    let start_bound = |node: &OperatorNode| {
+        let NonASAPOp::SQLWindowFunc {
             frame: Some(frame), ..
-        } = find_windowfunc(qe).unwrap()
+        } = op(find_windowfunc(node).unwrap())
         else {
             panic!("expected a window function with a concrete frame");
         };
@@ -943,43 +934,17 @@ async fn groups_frame_is_rejected() {
 
 // ── Nested query functions: derived tables / inline views (issue #27) ───────────
 
-/// Collect every `AggIntent` in the DAG, root-to-leaf.
-fn all_intents(qe: &QueryExpr) -> Vec<AggIntent> {
-    let mut out = Vec::new();
-    fn go(qe: &QueryExpr, out: &mut Vec<AggIntent>) {
-        match qe {
-            QueryExpr::Aggregate {
-                measures, child, ..
-            } => {
-                out.extend(measures.iter().cloned());
-                go(child, out);
-            }
-            QueryExpr::Project { child, .. }
-            | QueryExpr::Filter { child, .. }
-            | QueryExpr::Dedup { child, .. }
-            | QueryExpr::Sort { child, .. }
-            | QueryExpr::Limit { child, .. }
-            | QueryExpr::SQLWindowFunc { child, .. }
-            | QueryExpr::PromqlSubquery { child, .. } => go(child, out),
-            QueryExpr::BinaryOp { lhs, rhs, .. }
-            | QueryExpr::Join {
-                left: lhs,
-                right: rhs,
-                ..
-            }
-            | QueryExpr::SetOp {
-                left: lhs,
-                right: rhs,
-                ..
-            } => {
-                go(lhs, out);
-                go(rhs, out);
-            }
-            _ => {}
-        }
-    }
-    go(qe, &mut out);
-    out
+/// Collect every `AggIntent` in the DAG, root-to-leaf (every reachable node,
+/// including operators referenced from scalar positions).
+fn all_intents(root: &Rc<OperatorNode>) -> Vec<AggIntent> {
+    OperatorNode::reachable(root)
+        .iter()
+        .filter_map(|node| match op(node) {
+            NonASAPOp::Aggregate { measures, .. } => Some(measures.clone()),
+            _ => None,
+        })
+        .flatten()
+        .collect()
 }
 
 #[tokio::test]
@@ -1002,9 +967,9 @@ async fn derived_table_aggregate_over_aggregate_nests() {
         intents.iter().any(|i| matches!(i, AggIntent::Sum { .. })),
         "inner SUM survives, got {intents:?}"
     );
-    // The whole nested DAG's output schema derives without error (positional
-    // resolution is total across the derived-table boundary).
-    assert_eq!(qe.output_schema().unwrap().fields.len(), 1);
+    // The whole nested tree's output schema derives (positional resolution
+    // is total across the derived-table boundary).
+    assert_eq!(qe.schema.fields.len(), 1);
 }
 
 #[tokio::test]
@@ -1042,26 +1007,23 @@ async fn filter_over_derived_aggregate_resolves_alias_column() {
     assert!(all_intents(&qe)
         .iter()
         .any(|i| matches!(i, AggIntent::Sum { .. })));
-    // Schema derivation is total across the boundary.
-    let _ = qe.output_schema().expect("nested schema derivation");
+    // Schema derivation is total across the boundary: the root carries one.
+    assert_eq!(qe.schema.fields.len(), 2);
 }
 
 #[tokio::test]
-async fn scalar_subquery_in_predicate_is_rejected() {
-    // A subquery-*valued* expression (`x > (SELECT …)`) needs a subquery node in
-    // the unresolved expression IR (and a correlated/uncorrelated decision);
-    // rejected cleanly until that lands. Derived tables in FROM (the common nesting
-    // shape) ARE supported — see the tests above.
-    let res = lower_sql(
-        "SELECT service FROM metrics WHERE bytes > (SELECT AVG(bytes) FROM metrics)",
-        &catalog(),
-        AccuracyTarget::Exact,
-    )
-    .await;
+async fn scalar_subquery_in_predicate_lowers_through_a_cross_join() {
+    let qe =
+        lower("SELECT service FROM metrics WHERE bytes > (SELECT AVG(bytes) FROM metrics)").await;
+    let filter = find_filter(&qe).unwrap();
+    let NonASAPOp::Filter { pred, child } = op(filter) else {
+        panic!()
+    };
+    assert!(matches!(op(child), NonASAPOp::Scan { .. }));
     assert!(
-        res.is_err(),
-        "scalar subquery in predicate should be rejected"
+        matches!(&pred.0,ScalarExpr::Compare { right,.. } if matches!(right.as_ref(),ScalarExpr::ScalarSubquery(_)))
     );
+    qe.validate_structure().unwrap();
 }
 
 #[tokio::test]
@@ -1077,15 +1039,15 @@ async fn correlated_exists_lifts_its_correlation_into_the_join() {
     .await;
     let (kind, pred, left_len) = join_parts(&qe);
     assert_eq!(kind, &JoinKind::Semi);
-    let QueryExpr::Compare { left, right, .. } = pred else {
+    let ScalarExpr::Compare { left, right, .. } = pred else {
         panic!("expected the correlation as a comparison, got {pred:?}");
     };
     assert_eq!(
         **left,
-        QueryExpr::Column(left_len),
+        ScalarExpr::Column(left_len),
         "h.service (right side)"
     );
-    assert_eq!(**right, QueryExpr::Column(1), "m.service (left side)");
+    assert_eq!(**right, ScalarExpr::Column(1), "m.service (left side)");
 }
 
 #[tokio::test]
@@ -1104,24 +1066,62 @@ async fn an_uncorrelated_exists_is_an_unconditional_semi_join() {
     let qe = lower("SELECT service FROM metrics WHERE EXISTS (SELECT 1 FROM hosts)").await;
     let (kind, pred, _) = join_parts(&qe);
     assert_eq!(kind, &JoinKind::Semi);
-    assert_eq!(*pred, QueryExpr::Literal(ScalarValue::Boolean(true)));
+    assert_eq!(*pred, ScalarExpr::Literal(ScalarValue::Boolean(true)));
 }
 
 #[tokio::test]
-async fn not_in_subquery_is_rejected_rather_than_mislowered_as_an_anti_join() {
-    // `NOT IN` is *not* an anti-join. Under three-valued logic a single NULL
-    // among the subquery's rows makes `c NOT IN (…)` UNKNOWN for every `c`, so
-    // the query returns nothing — while an anti-join returns every unmatched
-    // left row. Rejecting is the only correct option until the nullability is
-    // proven, and `NOT EXISTS` is the safe spelling.
-    let err = lower_sql(
-        "SELECT service FROM metrics WHERE service NOT IN (SELECT service FROM hosts)",
-        &catalog(),
-        AccuracyTarget::Exact,
+async fn where_exists_resolves_to_a_semi_join_over_the_subquery() {
+    // The front end emits `Filter { Exists(s) }`; the resolved DAG is the
+    // `Semi` join with the subquery (a filtered `hosts` scan) on the right.
+    let qe = lower(
+        "SELECT service FROM metrics WHERE EXISTS (SELECT service FROM hosts WHERE region = 'eu')",
     )
-    .await
-    .expect_err("NOT IN must not lower to an anti-join");
-    assert!(format!("{err}").contains("NOT IN"), "got {err}");
+    .await;
+    let NonASAPOp::Project { child, .. } = op(&qe) else {
+        panic!("expected the SELECT list as a Project, got {qe:?}");
+    };
+    let NonASAPOp::Join {
+        kind,
+        pred,
+        left,
+        right,
+    } = op(child)
+    else {
+        panic!("expected the Semi join directly under the Project, got {child:?}");
+    };
+    assert_eq!(*kind, JoinKind::Semi);
+    assert_eq!(pred.0, ScalarExpr::Literal(ScalarValue::Boolean(true)));
+    assert!(
+        matches!(op(left), NonASAPOp::Scan { .. }),
+        "left is metrics"
+    );
+    let NonASAPOp::Project { child: scan, .. } = op(right) else {
+        panic!("expected the subquery's projection on the right, got {right:?}");
+    };
+    assert!(
+        matches!(op(scan), NonASAPOp::Scan { predicates, .. } if predicates.len() == 1),
+        "the subquery's WHERE stays on its own Scan, got {scan:?}"
+    );
+    assert_eq!(
+        child.schema.fields.len(),
+        4,
+        "a semi join outputs the left's columns alone"
+    );
+}
+
+#[tokio::test]
+async fn not_in_subquery_is_rejected_rather_than_mislowered_as_an_anti_join() {
+    let qe =
+        lower("SELECT service FROM metrics WHERE service NOT IN (SELECT service FROM hosts)").await;
+    let filter = find_filter(&qe).unwrap();
+    let NonASAPOp::Filter { pred, .. } = op(filter) else {
+        panic!()
+    };
+    assert!(matches!(
+        pred.0,
+        ScalarExpr::InSubquery { negated: true, .. }
+    ));
+    qe.validate_structure().unwrap();
 }
 
 #[tokio::test]
@@ -1137,6 +1137,177 @@ async fn a_correlated_in_subquery_is_rejected() {
     assert!(format!("{err}").contains("correlated IN"), "got {err}");
 }
 
+// ── Subquery-valued expressions at the `UnresolvedOp` level ─────────────────
+
+/// `SqlLowerer::lower` output, before `resolve_root`.
+async fn lower_unresolved(sql: &str) -> UnresolvedOp {
+    let catalog = catalog();
+    SqlLowerer::new(&catalog)
+        .lower(sql, &AccuracyTarget::Exact)
+        .await
+        .unwrap_or_else(|e| panic!("lower failed for {sql:?}: {e}"))
+}
+
+#[tokio::test]
+async fn scalar_subquery_in_projection_lowers_to_a_scalar_subquery_item() {
+    // An uncorrelated `(SELECT max(v) FROM t2)` in the SELECT list is a
+    // `ScalarSubquery` projection item reading its own lowered plan; the
+    // cross-join rewrite is `canonicalize`'s job, not the front end's.
+    let tree = lower_unresolved("SELECT (SELECT max(latency) FROM metrics) FROM hosts").await;
+    let UnresolvedOp::Project { cols, child, .. } = &tree else {
+        panic!("expected the SELECT list as a Project, got {tree:?}");
+    };
+    assert!(
+        matches!(child.as_ref(), UnresolvedOp::Scan { source: Source::Table { table_ref }, .. }
+            if table_ref == "hosts"),
+        "the outer relation stays the projection's child, got {child:?}"
+    );
+    assert_eq!(cols.len(), 1);
+    let UnresolvedScalar::ScalarSubquery(sub) = &cols[0].expr else {
+        panic!("expected a ScalarSubquery item, got {:?}", cols[0].expr);
+    };
+    let UnresolvedOp::Project { child: inner, .. } = sub.as_ref() else {
+        panic!("expected the subquery's own SELECT list, got {sub:?}");
+    };
+    assert!(
+        matches!(inner.as_ref(), UnresolvedOp::Aggregate { measures, .. }
+            if matches!(measures.as_slice(), [AggIntent::Max { .. }])),
+        "the subquery plan is lowered as a root of its own, got {inner:?}"
+    );
+}
+
+#[tokio::test]
+async fn exists_and_in_subqueries_lower_to_scalar_filter_conjuncts() {
+    // The front end no longer builds the semi join itself: `EXISTS` / `IN
+    // (…)` are `Filter` predicates reading the subquery operator.
+    let tree =
+        lower_unresolved("SELECT service FROM metrics WHERE EXISTS (SELECT 1 FROM hosts)").await;
+    let UnresolvedOp::Project { child, .. } = &tree else {
+        panic!("expected a Project, got {tree:?}");
+    };
+    assert!(
+        matches!(child.as_ref(), UnresolvedOp::Filter { pred, .. }
+            if matches!(pred.0, UnresolvedScalar::Exists { negated: false, .. })),
+        "expected Filter {{ Exists }}, got {child:?}"
+    );
+
+    let tree = lower_unresolved(
+        "SELECT service FROM metrics WHERE service IN (SELECT service FROM hosts)",
+    )
+    .await;
+    let UnresolvedOp::Project { child, .. } = &tree else {
+        panic!("expected a Project, got {tree:?}");
+    };
+    assert!(
+        matches!(child.as_ref(), UnresolvedOp::Filter { pred, .. }
+            if matches!(pred.0, UnresolvedScalar::InSubquery { negated: false, .. })),
+        "expected Filter {{ InSubquery }}, got {child:?}"
+    );
+}
+
+// ── `SELECT` without `FROM`, unary minus, SQL expression semantics ──────────
+
+#[tokio::test]
+async fn select_without_from_projects_over_one_empty_row() {
+    // `SELECT 1` has no table: DataFusion's `EmptyRelation` is one empty
+    // input row, which the SELECT list projects a literal over.
+    let qe = lower("SELECT 1").await;
+    let NonASAPOp::Project { cols, child, .. } = op(&qe) else {
+        panic!("expected Project at root, got {qe:?}");
+    };
+    assert_eq!(cols.len(), 1);
+    assert_eq!(cols[0].expr, ScalarExpr::Literal(ScalarValue::Int64(1)));
+    let NonASAPOp::Values { rows, schema } = op(child) else {
+        panic!("expected Values under the Project, got {child:?}");
+    };
+    assert_eq!(rows, &vec![Vec::<ScalarExpr>::new()], "one empty row");
+    assert!(schema.fields.is_empty() && schema.closed);
+    assert_eq!(qe.schema.fields.len(), 1);
+    assert_eq!(qe.schema.fields[0].dtype, DataType::Int64);
+}
+
+#[tokio::test]
+async fn values_lowers_to_one_row_per_values_row() {
+    let qe = lower("SELECT * FROM (VALUES (1, 'a'), (2, 'b')) AS v(n, s)").await;
+    let values = OperatorNode::reachable(&qe)
+        .into_iter()
+        .find(|n| matches!(op(n), NonASAPOp::Values { .. }))
+        .expect("expected a Values node");
+    let NonASAPOp::Values { rows, schema } = op(&values) else {
+        unreachable!()
+    };
+    assert_eq!(rows.len(), 2);
+    assert_eq!(
+        rows[1],
+        vec![
+            ScalarExpr::Literal(ScalarValue::Int64(2)),
+            ScalarExpr::Literal(ScalarValue::Utf8("b".into())),
+        ]
+    );
+    assert_eq!(schema.fields.len(), 2);
+    assert_eq!(schema.fields[0].dtype, DataType::Int64);
+    assert_eq!(schema.fields[1].dtype, DataType::Utf8);
+    assert_eq!(
+        qe.schema
+            .fields
+            .iter()
+            .map(|f| f.name.as_str())
+            .collect::<Vec<_>>(),
+        ["n", "s"]
+    );
+}
+
+#[tokio::test]
+async fn unary_minus_lowers_to_negative() {
+    // `-x` over a column is the `Negative` scalar (a negative *literal* is
+    // folded by DataFusion's planner before lowering).
+    let qe = lower("SELECT -latency FROM metrics").await;
+    let NonASAPOp::Project { cols, .. } = op(&qe) else {
+        panic!("expected Project at root, got {qe:?}");
+    };
+    assert_eq!(
+        cols[0].expr,
+        ScalarExpr::Negative {
+            expr: Box::new(ScalarExpr::Column(2)),
+            semantics: ExprSemantics::Sql,
+        }
+    );
+    assert_eq!(qe.schema.fields[0].dtype, DataType::Float64);
+}
+
+#[tokio::test]
+async fn sql_comparisons_and_arithmetic_carry_sql_semantics() {
+    let qe = lower("SELECT bytes * 8 FROM metrics WHERE latency > 1.5").await;
+    let NonASAPOp::Project { cols, child, .. } = op(&qe) else {
+        panic!("expected Project at root, got {qe:?}");
+    };
+    assert!(
+        matches!(
+            &cols[0].expr,
+            ScalarExpr::Arithmetic {
+                semantics: ExprSemantics::Sql,
+                ..
+            }
+        ),
+        "got {:?}",
+        cols[0].expr
+    );
+    let NonASAPOp::Scan { predicates, .. } = op(child) else {
+        panic!("expected the WHERE folded onto the Scan, got {child:?}");
+    };
+    assert!(
+        matches!(
+            &predicates[0].0,
+            ScalarExpr::Compare {
+                semantics: ExprSemantics::Sql,
+                ..
+            }
+        ),
+        "got {:?}",
+        predicates[0].0
+    );
+}
+
 // ── Issue #115: Quantile / Cardinality carry their input column ─────────────
 
 #[tokio::test]
@@ -1286,20 +1457,20 @@ async fn time_bucketing_group_by_lowers_to_a_derived_key() {
     let qe =
         lower("SELECT date_trunc('minute', ts) AS m, SUM(bytes) FROM metrics GROUP BY m").await;
     let node = find_aggregate_node(&qe).expect("expected an Aggregate");
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction,
         measures,
         child,
         ..
-    } = node
+    } = op(node)
     else {
         unreachable!()
     };
     assert!(
-        matches!(**child, QueryExpr::Project { .. }),
+        matches!(op(child), NonASAPOp::Project { .. }),
         "expected a materializing Project beneath the Aggregate"
     );
-    let schema = child.output_schema().expect("child schema");
+    let schema = &child.schema;
     assert_eq!(reduction, &Reduction::by(vec![0]));
     assert!(
         schema.fields[0].name.contains("date_trunc"),
@@ -1322,14 +1493,14 @@ async fn time_bucketing_keeps_the_scan_predicate() {
          WHERE bytes > 10 GROUP BY m",
     )
     .await;
-    fn scan_has_predicate(qe: &QueryExpr) -> bool {
-        match qe {
-            QueryExpr::Scan { predicates, .. } => !predicates.is_empty(),
-            QueryExpr::Project { child, .. }
-            | QueryExpr::Filter { child, .. }
-            | QueryExpr::Aggregate { child, .. }
-            | QueryExpr::Sort { child, .. }
-            | QueryExpr::Limit { child, .. } => scan_has_predicate(child),
+    fn scan_has_predicate(node: &OperatorNode) -> bool {
+        match op(node) {
+            NonASAPOp::Scan { predicates, .. } => !predicates.is_empty(),
+            NonASAPOp::Project { child, .. }
+            | NonASAPOp::Filter { child, .. }
+            | NonASAPOp::Aggregate { child, .. }
+            | NonASAPOp::Sort { child, .. }
+            | NonASAPOp::Limit { child, .. } => scan_has_predicate(child),
             _ => false,
         }
     }
@@ -1346,13 +1517,13 @@ async fn a_plain_group_by_inserts_no_projection() {
         "SELECT COUNT(*) FROM metrics",
     ] {
         let qe = lower(q).await;
-        let QueryExpr::Aggregate { child, .. } =
-            find_aggregate_node(&qe).expect("expected an Aggregate")
+        let NonASAPOp::Aggregate { child, .. } =
+            op(find_aggregate_node(&qe).expect("expected an Aggregate"))
         else {
             unreachable!()
         };
         assert!(
-            !matches!(**child, QueryExpr::Project { .. }),
+            !matches!(op(child), NonASAPOp::Project { .. }),
             "{q} should not gain a projection"
         );
     }
@@ -1361,14 +1532,14 @@ async fn a_plain_group_by_inserts_no_projection() {
 #[tokio::test]
 async fn a_shared_expression_is_materialized_once() {
     let qe = lower("SELECT SUM(bytes * 2), MIN(bytes * 2) FROM metrics").await;
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         measures, child, ..
-    } = find_aggregate_node(&qe).expect("expected an Aggregate")
+    } = op(find_aggregate_node(&qe).expect("expected an Aggregate"))
     else {
         unreachable!()
     };
     assert_eq!(
-        child.output_schema().expect("child schema").fields.len(),
+        child.schema.fields.len(),
         1,
         "the two reducers should share one derived column"
     );
@@ -1378,38 +1549,32 @@ async fn a_shared_expression_is_materialized_once() {
 // ── Issue #118: multi-level grouping expands into one Aggregate per level ───
 
 /// The branches of the first `Concat` along the single-child spine.
-fn merge_branches(qe: &QueryExpr) -> &Vec<QueryExpr> {
-    fn find(qe: &QueryExpr) -> Option<&Vec<QueryExpr>> {
-        match qe {
-            QueryExpr::Concat { children, .. } => Some(children),
-            QueryExpr::Project { child, .. }
-            | QueryExpr::Filter { child, .. }
-            | QueryExpr::Sort { child, .. }
-            | QueryExpr::Limit { child, .. } => find(child),
+fn merge_branches(node: &OperatorNode) -> &Vec<Rc<OperatorNode>> {
+    fn find(node: &OperatorNode) -> Option<&Vec<Rc<OperatorNode>>> {
+        match op(node) {
+            NonASAPOp::Concat { children, .. } => Some(children),
+            NonASAPOp::Project { child, .. }
+            | NonASAPOp::Filter { child, .. }
+            | NonASAPOp::Sort { child, .. }
+            | NonASAPOp::Limit { child, .. } => find(child),
             _ => None,
         }
     }
-    find(qe).expect("expected a Concat")
+    find(node).expect("expected a Concat")
 }
 
 /// `(group keys, column names)` of each merged grouping level.
-fn grouping_levels(qe: &QueryExpr) -> Vec<(GroupKeys, Vec<String>)> {
-    merge_branches(qe)
+fn grouping_levels(node: &OperatorNode) -> Vec<(GroupKeys, Vec<String>)> {
+    merge_branches(node)
         .iter()
         .map(|b| {
-            let QueryExpr::Project { child, .. } = b else {
+            let NonASAPOp::Project { child, .. } = op(b) else {
                 panic!("expected a Project per level, got {b:?}");
             };
-            let QueryExpr::Aggregate { reduction, .. } = child.as_ref() else {
+            let NonASAPOp::Aggregate { reduction, .. } = op(child) else {
                 panic!("expected an Aggregate under the Project, got {child:?}");
             };
-            let names = b
-                .output_schema()
-                .expect("level schema")
-                .fields
-                .iter()
-                .map(|c| c.name.clone())
-                .collect();
+            let names = b.schema.fields.iter().map(|c| c.name.clone()).collect();
             (reduction.expect_reduce().clone(), names)
         })
         .collect()
@@ -1468,9 +1633,7 @@ async fn omitted_grouping_keys_become_typed_nulls() {
     }
 
     // The `()` level projects `service` as a Utf8 null, not a Float64 one.
-    let schema = merge_branches(&qe)[1]
-        .output_schema()
-        .expect("level schema");
+    let schema = &merge_branches(&qe)[1].schema;
     assert_eq!(schema.fields[0].name, "service");
     assert_eq!(
         schema.fields[0].dtype,
@@ -1488,8 +1651,7 @@ async fn grouping_levels_are_union_compatible() {
     let shapes: Vec<_> = merge_branches(&qe)
         .iter()
         .map(|b| {
-            b.output_schema()
-                .expect("level schema")
+            b.schema
                 .fields
                 .iter()
                 .map(|c| (c.name.clone(), c.dtype.clone()))
@@ -1539,12 +1701,12 @@ async fn multi_level_grouping_composes_with_a_derived_reducer_argument() {
     // #110's materializing Project sits beneath every level's Aggregate.
     let qe = lower("SELECT service, SUM(bytes * 8) FROM metrics GROUP BY ROLLUP(service)").await;
     for b in merge_branches(&qe) {
-        let QueryExpr::Project { child, .. } = b else {
+        let NonASAPOp::Project { child, .. } = op(b) else {
             panic!("expected a Project per level");
         };
-        let QueryExpr::Aggregate {
+        let NonASAPOp::Aggregate {
             measures, child, ..
-        } = child.as_ref()
+        } = op(child)
         else {
             panic!("expected an Aggregate");
         };
@@ -1553,7 +1715,7 @@ async fn multi_level_grouping_composes_with_a_derived_reducer_argument() {
             [AggIntent::Sum { col: Some(_) }]
         ));
         assert!(
-            matches!(**child, QueryExpr::Project { .. }),
+            matches!(op(child), NonASAPOp::Project { .. }),
             "the derived-column projection should sit under each level"
         );
     }
@@ -1616,7 +1778,7 @@ async fn array_agg_is_deliberately_rejected() {
 // ── Issue #225: catalog-driven ClickHouse builtins (countIf, generalizing
 // uniqExact from #221) ───────────────────────────────────────────────────
 
-async fn lower_clickhouse(sql: &str) -> QueryExpr {
+async fn lower_clickhouse(sql: &str) -> Rc<OperatorNode> {
     lower_sql_dialect(
         sql,
         &catalog(),
@@ -1627,20 +1789,20 @@ async fn lower_clickhouse(sql: &str) -> QueryExpr {
     .unwrap_or_else(|e| panic!("lower failed for {sql:?}: {e}"))
 }
 
-fn temporal_aggregate(qe: &QueryExpr) -> (&AggIntent, std::time::Duration, &QueryExpr) {
-    match qe {
-        QueryExpr::Aggregate {
+fn temporal_aggregate(node: &OperatorNode) -> (&AggIntent, std::time::Duration, &OperatorNode) {
+    match op(node) {
+        NonASAPOp::Aggregate {
             reduction: Reduction::PerEntity,
             measures,
             child,
             ..
         } => {
-            let QueryExpr::TimeRange { range, child } = child.as_ref() else {
+            let NonASAPOp::TimeRange { range, child, .. } = op(child) else {
                 panic!("temporal Aggregate must directly wrap TimeRange, got {child:?}");
             };
             (&measures[0], *range, child)
         }
-        QueryExpr::Project { child, .. } | QueryExpr::Filter { child, .. } => {
+        NonASAPOp::Project { child, .. } | NonASAPOp::Filter { child, .. } => {
             temporal_aggregate(child)
         }
         other => panic!("expected temporal Aggregate, got {other:?}"),
@@ -1661,15 +1823,15 @@ async fn explicit_temporal_aggregates_share_promql_intents_and_timerange() {
         let (intent, range, child) = temporal_aggregate(&qe);
         assert_eq!(intent, &expected);
         assert_eq!(range, std::time::Duration::from_secs(300));
-        assert!(matches!(child, QueryExpr::Project { child, .. }
-            if matches!(child.as_ref(), QueryExpr::Scan { predicates, .. } if predicates.len() == 1)));
+        assert!(matches!(op(child), NonASAPOp::Project { child, .. }
+            if matches!(op(child), NonASAPOp::Scan { predicates, .. } if predicates.len() == 1)));
 
-        let QueryExpr::Project { cols, .. } = &qe else {
+        let NonASAPOp::Project { cols, .. } = op(&qe) else {
             panic!("SELECT list must remain a Project, got {qe:?}");
         };
-        assert!(matches!(cols[0].expr, QueryExpr::Column(2)));
+        assert!(matches!(cols[0].expr, ScalarExpr::Column(2)));
         assert_eq!(cols[1].alias.as_deref(), Some("v"));
-        assert!(matches!(cols[1].expr, QueryExpr::Column(1)));
+        assert!(matches!(cols[1].expr, ScalarExpr::Column(1)));
     }
 }
 
@@ -1830,20 +1992,20 @@ async fn project_filter_and_outer_aggregate_preserve_temporal_child() {
          ) r WHERE v >= 0",
     )
     .await;
-    let QueryExpr::Project { child, .. } = &qe else {
+    let NonASAPOp::Project { child, .. } = op(&qe) else {
         panic!("expected outer SELECT Project, got {qe:?}");
     };
-    let QueryExpr::Aggregate {
+    let NonASAPOp::Aggregate {
         reduction: Reduction::Reduce(_),
         measures,
         child,
         ..
-    } = child.as_ref()
+    } = op(child)
     else {
         panic!("expected outer Aggregate, got {child:?}");
     };
     assert!(matches!(measures.as_slice(), [AggIntent::Max { .. }]));
-    let QueryExpr::Filter { child, .. } = child.as_ref() else {
+    let NonASAPOp::Filter { child, .. } = op(child) else {
         panic!("derived-table WHERE must remain above the inner query, got {child:?}");
     };
     let (intent, range, _) = temporal_aggregate(child);
@@ -2007,13 +2169,13 @@ async fn lag_in_frame_lowers_to_its_own_kind_not_lag() {
     )
     .await;
     let win = find_windowfunc(&qe).expect("expected a SQLWindowFunc node");
-    let QueryExpr::SQLWindowFunc { func, args, .. } = win else {
+    let NonASAPOp::SQLWindowFunc { func, args, .. } = op(win) else {
         unreachable!();
     };
     assert_eq!(*func, WindowFuncKind::LagInFrame);
     assert_eq!(
         args,
-        &vec![QueryExpr::Column(3)],
+        &vec![ScalarExpr::Column(3)],
         "lagInFrame(bytes) → arg col 3"
     );
 }
@@ -2026,7 +2188,7 @@ async fn lead_in_frame_lowers_to_its_own_kind_not_lead() {
     )
     .await;
     let win = find_windowfunc(&qe).expect("expected a SQLWindowFunc node");
-    let QueryExpr::SQLWindowFunc { func, .. } = win else {
+    let NonASAPOp::SQLWindowFunc { func, .. } = op(win) else {
         unreachable!();
     };
     assert_eq!(*func, WindowFuncKind::LeadInFrame);
@@ -2039,16 +2201,16 @@ async fn lead_in_frame_lowers_to_its_own_kind_not_lead() {
 async fn now_in_predicate_lowers_to_current_timestamp() {
     // WHERE folds onto Scan.predicates (no explicit Filter node).
     let qe = lower("SELECT * FROM metrics WHERE ts < NOW()").await;
-    let QueryExpr::Project { child, .. } = &qe else {
+    let NonASAPOp::Project { child, .. } = op(&qe) else {
         panic!("expected Project at root, got {qe:?}");
     };
-    let QueryExpr::Scan { predicates, .. } = child.as_ref() else {
+    let NonASAPOp::Scan { predicates, .. } = op(child) else {
         panic!("expected Scan under the projection, got {child:?}");
     };
     assert_eq!(predicates.len(), 1);
     assert!(
-        matches!(predicates[0].0.as_ref(), QueryExpr::Compare { right, .. }
-            if matches!(right.as_ref(), QueryExpr::CurrentTimestamp)),
+        matches!(&predicates[0].0, ScalarExpr::Compare { right, .. }
+            if matches!(right.as_ref(), ScalarExpr::Cast { expr, to: DataType::Timestamp, .. } if matches!(expr.as_ref(), ScalarExpr::CurrentTimestamp))),
         "NOW() must lower to CurrentTimestamp, got {:?}",
         predicates[0].0
     );
@@ -2059,16 +2221,16 @@ async fn now_in_predicate_lowers_to_current_timestamp() {
 #[tokio::test]
 async fn clickhouse_now_in_predicate_lowers_to_current_timestamp() {
     let qe = lower_clickhouse("SELECT * FROM metrics WHERE ts < now()").await;
-    let QueryExpr::Project { child, .. } = &qe else {
+    let NonASAPOp::Project { child, .. } = op(&qe) else {
         panic!("expected Project at root, got {qe:?}");
     };
-    let QueryExpr::Scan { predicates, .. } = child.as_ref() else {
+    let NonASAPOp::Scan { predicates, .. } = op(child) else {
         panic!("expected Scan under the projection, got {child:?}");
     };
     assert_eq!(predicates.len(), 1);
     assert!(
-        matches!(predicates[0].0.as_ref(), QueryExpr::Compare { right, .. }
-            if matches!(right.as_ref(), QueryExpr::CurrentTimestamp)),
+        matches!(&predicates[0].0, ScalarExpr::Compare { right, .. }
+            if matches!(right.as_ref(), ScalarExpr::Cast { expr, to: DataType::Timestamp, .. } if matches!(expr.as_ref(), ScalarExpr::CurrentTimestamp))),
         "now() must lower to CurrentTimestamp, got {:?}",
         predicates[0].0
     );
@@ -2077,12 +2239,16 @@ async fn clickhouse_now_in_predicate_lowers_to_current_timestamp() {
 #[tokio::test]
 async fn current_timestamp_lowers_to_typed_current_timestamp_leaf() {
     let qe = lower("SELECT CURRENT_TIMESTAMP FROM metrics").await;
-    let QueryExpr::Project { cols, .. } = &qe else {
+    let NonASAPOp::Project { cols, child, .. } = op(&qe) else {
         panic!("expected Project at root, got {qe:?}");
     };
-    assert!(matches!(&cols[0].expr, QueryExpr::CurrentTimestamp));
-    let schema = cols[0].expr.output_schema().expect("timestamp schema");
-    assert_eq!(schema.fields[0].dtype, DataType::Timestamp);
+    assert!(matches!(&cols[0].expr, ScalarExpr::CurrentTimestamp));
+    let (dtype, _) = cols[0]
+        .expr
+        .scalar_type(&child.schema)
+        .expect("timestamp type");
+    assert_eq!(dtype, DataType::Timestamp);
+    assert_eq!(qe.schema.fields[0].dtype, DataType::Timestamp);
 }
 
 // A `count` over a non-null input is a plain row count; over a nullable
@@ -2125,10 +2291,7 @@ async fn count_null_semantics_become_a_measure_filter() {
                 aggregate_filters(&qe)
             );
         };
-        assert!(
-            matches!(cond.as_ref(), QueryExpr::IsNotNull(_)),
-            "{sql}: {cond:?}"
-        );
+        assert!(matches!(cond, ScalarExpr::IsNotNull(_)), "{sql}: {cond:?}");
     }
     // Only the second measure is filtered.
     let qe = lower_sql(
@@ -2175,7 +2338,7 @@ async fn grouped_map_column_preserves_map_type() {
     )
     .await
     .unwrap();
-    assert_eq!(query.output_schema().unwrap().fields[0].dtype, map);
+    assert_eq!(query.schema.fields[0].dtype, map);
 }
 
 #[tokio::test]
@@ -2213,10 +2376,7 @@ async fn clickhouse_modulo_uses_native_arithmetic_types_and_nullability() {
         .await
         .unwrap();
         assert_eq!(function, operator, "{call}");
-        assert_eq!(
-            function.output_schema().unwrap(),
-            operator.output_schema().unwrap()
-        );
+        assert_eq!(function.schema, operator.schema);
     }
     let nullable = lower_sql_dialect(
         "SELECT modulo(n, 3) AS value FROM numbers",
@@ -2226,8 +2386,8 @@ async fn clickhouse_modulo_uses_native_arithmetic_types_and_nullability() {
     )
     .await
     .unwrap()
-    .output_schema()
-    .unwrap();
+    .schema
+    .clone();
     assert_eq!(nullable.fields[0].dtype, DataType::Int64);
     assert!(nullable.fields[0].nullable);
 }
@@ -2266,7 +2426,7 @@ async fn original_o11y_map_queries_lower_with_typed_results() {
         )
         .await
         .unwrap_or_else(|e| panic!("{sql}: {e}"));
-        let schema = query.output_schema().unwrap();
+        let schema = &query.schema;
         assert!(
             schema
                 .fields
@@ -2298,7 +2458,7 @@ async fn clickhouse_modulo_preserves_projection_names_and_outer_references() {
         )
         .await
         .unwrap();
-        assert_eq!(query.output_schema().unwrap().fields[0].name, name);
+        assert_eq!(query.schema.fields[0].name, name);
     }
 }
 
@@ -2328,7 +2488,7 @@ async fn clickhouse_map_access_keeps_generated_names_and_rejects_variant_coercio
     )
     .await
     .unwrap();
-    let output = query.output_schema().unwrap();
+    let output = &query.schema;
     assert_eq!(output.fields[0].name, "arrayElement(labels, 'job')");
     assert_eq!(output.fields[0].dtype, DataType::Utf8);
     assert!(!output.fields[0].nullable);
@@ -2380,7 +2540,7 @@ async fn arg_selector_result_schema_tracks_selected_argument() {
         )
         .await
         .unwrap();
-        let schema = query.output_schema().unwrap();
+        let schema = &query.schema;
         assert_eq!(schema.fields[0].dtype, dtype);
         assert_eq!(schema.fields[0].nullable, nullable);
     }
@@ -2414,7 +2574,7 @@ async fn clickhouse_list_element_uses_canonical_typed_access() {
         )
         .await
         .unwrap();
-        let output = query.output_schema().unwrap();
+        let output = &query.schema;
         assert_eq!(output.fields[0].dtype, DataType::Int64);
         assert_eq!(output.fields[0].nullable, nullable);
         let serialized = serde_json::to_string(&query).unwrap();
@@ -2473,7 +2633,7 @@ async fn clickhouse_tuple_element_preserves_declared_field_metadata() {
         )
         .await
         .unwrap();
-        let output = query.output_schema().unwrap();
+        let output = &query.schema;
         assert_eq!(output.fields[0].dtype, dtype);
         assert_eq!(output.fields[0].nullable, nullable);
         assert!(serde_json::to_string(&query)
@@ -2500,7 +2660,7 @@ async fn clickhouse_tuple_element_preserves_declared_field_metadata() {
 #[tokio::test]
 async fn corr_result_is_nullable_float() {
     let query = lower("SELECT corr(latency, bytes) AS correlation FROM metrics").await;
-    let schema = query.output_schema().unwrap();
+    let schema = &query.schema;
     assert_eq!(schema.fields[0].name, "correlation");
     assert_eq!(schema.fields[0].dtype, DataType::Float64);
     assert!(schema.fields[0].nullable);
@@ -2524,8 +2684,8 @@ async fn composite_distinct_counts_tuples() {
     )
     .await
     .unwrap();
-    let QueryExpr::Aggregate { measures, .. } =
-        find_aggregate_node(&composite).expect("expected an Aggregate")
+    let NonASAPOp::Aggregate { measures, .. } =
+        op(find_aggregate_node(&composite).expect("expected an Aggregate"))
     else {
         unreachable!()
     };
@@ -2541,8 +2701,8 @@ async fn composite_distinct_counts_tuples() {
     )
     .await
     .unwrap();
-    let QueryExpr::Aggregate { measures, .. } =
-        find_aggregate_node(&single).expect("expected an Aggregate")
+    let NonASAPOp::Aggregate { measures, .. } =
+        op(find_aggregate_node(&single).expect("expected an Aggregate"))
     else {
         unreachable!()
     };
@@ -2600,8 +2760,10 @@ async fn distinct_with_derived_sibling() {
 // ── Issue #466: per-measure FILTER predicates ─────────────────────────────────
 
 /// The first `Aggregate`'s `filters`, positional against its child.
-fn aggregate_filters(qe: &QueryExpr) -> &[Option<Predicate>] {
-    let Some(QueryExpr::Aggregate { filters, .. }) = find_aggregate_node(qe) else {
+fn aggregate_filters(qe: &OperatorNode) -> &[Option<Predicate>] {
+    let Some(NonASAPOp::Aggregate { filters, .. }) =
+        find_aggregate_node(qe).map(|n| n.expect_non_asap())
+    else {
         panic!("expected an Aggregate, got {qe:?}");
     };
     filters
@@ -2631,15 +2793,17 @@ async fn conditional_count_lowers_to_a_filtered_measure() {
         panic!("expected [Some, None], got {:?}", aggregate_filters(&qe));
     };
     assert!(
-        matches!(cond.as_ref(), QueryExpr::Compare { left, op: CompareOpKind::Gt, .. }
-            if matches!(left.as_ref(), QueryExpr::Column(2))),
+        matches!(cond, ScalarExpr::Compare { left, op: CompareOpKind::Gt, .. }
+            if matches!(left.as_ref(), ScalarExpr::Column(2))),
         "latency > 1.0 against the scan, got {cond:?}"
     );
-    let Some(QueryExpr::Aggregate { child, .. }) = find_aggregate_node(&qe) else {
+    let Some(NonASAPOp::Aggregate { child, .. }) =
+        find_aggregate_node(&qe).map(|n| n.expect_non_asap())
+    else {
         unreachable!()
     };
     assert!(
-        matches!(child.as_ref(), QueryExpr::Scan { .. }),
+        matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }),
         "{child:?}"
     );
 }
@@ -2653,9 +2817,9 @@ async fn filter_clause_lowers_to_a_measure_filter() {
         panic!("expected [Some, None], got {:?}", aggregate_filters(&qe));
     };
     assert!(
-        matches!(cond.as_ref(), QueryExpr::Compare { left, op: CompareOpKind::Eq, right }
-            if matches!(left.as_ref(), QueryExpr::Column(1))
-                && matches!(right.as_ref(), QueryExpr::Literal(ScalarValue::Utf8(s)) if s == "a")),
+        matches!(cond, ScalarExpr::Compare { left, op: CompareOpKind::Eq, right, .. }
+            if matches!(left.as_ref(), ScalarExpr::Column(1))
+                && matches!(right.as_ref(), ScalarExpr::Literal(ScalarValue::Utf8(s)) if s == "a")),
         "{cond:?}"
     );
 }
@@ -2669,7 +2833,7 @@ async fn count_of_a_nullable_expression_filters_nulls() {
     let [Some(Predicate(cond))] = aggregate_filters(&qe) else {
         panic!("expected [Some], got {:?}", aggregate_filters(&qe));
     };
-    assert!(matches!(cond.as_ref(), QueryExpr::IsNotNull(_)), "{cond:?}");
+    assert!(matches!(cond, ScalarExpr::IsNotNull(_)), "{cond:?}");
     assert!(
         matches!(
             find_aggregate(&qe).unwrap().1.as_slice(),
@@ -2684,23 +2848,25 @@ async fn count_of_a_nullable_expression_filters_nulls() {
 #[tokio::test]
 async fn measure_filter_columns_survive_a_derived_column_projection() {
     let qe = lower("SELECT sum(bytes * 2) FILTER (WHERE latency > 1.0) FROM metrics").await;
-    let Some(QueryExpr::Aggregate { child, .. }) = find_aggregate_node(&qe) else {
+    let Some(NonASAPOp::Aggregate { child, .. }) =
+        find_aggregate_node(&qe).map(|n| n.expect_non_asap())
+    else {
         unreachable!()
     };
     assert!(
-        matches!(child.as_ref(), QueryExpr::Project { .. }),
+        matches!(child.expect_non_asap(), NonASAPOp::Project { .. }),
         "{child:?}"
     );
     let [Some(Predicate(cond))] = aggregate_filters(&qe) else {
         panic!("expected [Some], got {:?}", aggregate_filters(&qe));
     };
-    let QueryExpr::Compare { left, .. } = cond.as_ref() else {
+    let ScalarExpr::Compare { left, .. } = cond else {
         panic!("{cond:?}");
     };
-    let QueryExpr::Column(id) = left.as_ref() else {
+    let ScalarExpr::Column(id) = left.as_ref() else {
         panic!("{left:?}");
     };
-    assert_eq!(child.output_schema().unwrap().fields[*id].name, "latency");
+    assert_eq!(child.schema.fields[*id].name, "latency");
 }
 
 // `GROUP BY ROLLUP` fans one measure list out into one `Aggregate` per level;
diff --git a/crates/frontend-sql/tests/temporal_types.rs b/crates/frontend-sql/tests/temporal_types.rs
index a6b4f1187..7e12c6f33 100644
--- a/crates/frontend-sql/tests/temporal_types.rs
+++ b/crates/frontend-sql/tests/temporal_types.rs
@@ -38,10 +38,7 @@ async fn date_shifts_keep_their_type() {
         let node = lower_sql(query, &catalog(), AccuracyTarget::Exact)
             .await
             .unwrap();
-        assert_eq!(
-            node.output_schema().unwrap().fields[0].dtype,
-            DataType::Date
-        );
+        assert_eq!(node.schema.fields[0].dtype, DataType::Date);
     }
 }
 // Interval literals and explicit interval casts must both cross the Arrow bridge.
@@ -54,10 +51,7 @@ async fn interval_cast_lowers_like_interval_literal() {
         let node = lower_sql(query, &catalog(), AccuracyTarget::Exact)
             .await
             .unwrap();
-        assert_eq!(
-            node.output_schema().unwrap().fields[0].dtype,
-            DataType::Interval
-        );
+        assert_eq!(node.schema.fields[0].dtype, DataType::Interval);
     }
 }
 
@@ -90,11 +84,7 @@ async fn negative_intervals_keep_their_type() {
         let node = lower_sql(query, &catalog(), AccuracyTarget::Exact)
             .await
             .unwrap();
-        assert_eq!(
-            node.output_schema().unwrap().fields[0].dtype,
-            DataType::Interval,
-            "{query}"
-        );
+        assert_eq!(node.schema.fields[0].dtype, DataType::Interval, "{query}");
     }
 }
 
@@ -108,9 +98,6 @@ async fn sql_date_literals_keep_their_type() {
         let node = lower_sql(query, &catalog(), AccuracyTarget::Exact)
             .await
             .unwrap();
-        assert_eq!(
-            node.output_schema().unwrap().fields[0].dtype,
-            DataType::Date
-        );
+        assert_eq!(node.schema.fields[0].dtype, DataType::Date);
     }
 }
diff --git a/crates/frontend-sql/tests/unified_sql_lowering.rs b/crates/frontend-sql/tests/unified_sql_lowering.rs
deleted file mode 100644
index 066434a8c..000000000
--- a/crates/frontend-sql/tests/unified_sql_lowering.rs
+++ /dev/null
@@ -1,2885 +0,0 @@
-//! End-to-end SQL → unresolved → resolved operator DAG lowering tests.
-//!
-//! Validates the DataFusion front end: SQL parses + plans, lowers directly to
-//! the name-based `UnresolvedOp` tree (issue #179), and the shared
-//! `resolve_root` produces the positional, canonical `OperatorNode` DAG (the
-//! same resolver the PromQL path uses). Every node's schema is derived during
-//! resolution, so a successful `lower` already proves schema derivation is
-//! total over the tree.
-
-use ::asap_frontend_sql::unified as asap_frontend_sql;
-use asap_types::ir::Predicate;
-use std::rc::Rc;
-
-use asap_frontend_common::{UnresolvedOp, UnresolvedScalar};
-use asap_frontend_sql::{
-    lower_sql, lower_sql_dialect, SqlCatalog, SqlError as LoweringError, SqlLowerer,
-};
-use asap_types::ir::{ExprSemantics, NonASAPOp, OperatorNode, ScalarExpr};
-use asap_types::pre_asap::schema::{DataType, Field, FieldDataType, Schema};
-use asap_types::pre_asap::{
-    AggIntent, CompareOpKind, GroupKeys, JoinKind, Reduction, ScalarValue, Source,
-    WindowFrameBound, WindowFrameOffset, WindowFrameUnits, WindowFuncKind,
-};
-use asap_types::types::AccuracyTarget;
-use asap_types::workload::SqlDialect;
-
-fn col(name: &str, dtype: DataType) -> Field {
-    Field::plain(name, dtype, false)
-}
-
-/// `metrics(ts, service, latency, bytes)` + `hosts(service, region)`.
-fn catalog() -> SqlCatalog {
-    SqlCatalog::new()
-        .with_table(
-            "metrics",
-            Schema::with_time_index(
-                vec![
-                    col("ts", DataType::Timestamp),
-                    col("service", DataType::Utf8),
-                    col("latency", DataType::Float64),
-                    col("bytes", DataType::Int64),
-                ],
-                0,
-                vec![vec![0, 1]],
-            ),
-        )
-        .with_table(
-            "hosts",
-            Schema::new(vec![
-                col("service", DataType::Utf8),
-                col("region", DataType::Utf8),
-            ]),
-        )
-}
-
-async fn lower(sql: &str) -> Rc<OperatorNode> {
-    lower_sql(sql, &catalog(), AccuracyTarget::Exact)
-        .await
-        .unwrap_or_else(|e| panic!("lower failed for {sql:?}: {e}"))
-}
-
-/// The operator of a front-end node: a front-end DAG never holds an ASAP node.
-fn op(node: &OperatorNode) -> &NonASAPOp {
-    node.expect_non_asap()
-}
-
-#[tokio::test]
-async fn planning_subquery_bridge_rejects_a_relation_without_vector_conversion() {
-    let result = lower_sql("SELECT max(value) FROM (SELECT asap_promql_subquery(21600000, 60000) AS value FROM (SELECT sum(bytes) AS value FROM metrics))", &catalog(), AccuracyTarget::Exact).await;
-    assert!(result.is_err());
-}
-
-#[tokio::test]
-async fn planning_histogram_bridge_reuses_classic_bucket_intent() {
-    let query = lower(
-        "SELECT asap_histogram_quantile(0.95) AS value FROM (\
-           SELECT service AS le, sum(bytes) AS value FROM metrics GROUP BY service)",
-    )
-    .await;
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = op(&query)
-    else {
-        panic!("expected canonical histogram aggregate");
-    };
-    // One histogram over all rows; the bucket bound is the child's column 0.
-    assert!(reduction.expect_reduce().keys().is_empty());
-    assert!(matches!(
-        measures.as_slice(),
-        [AggIntent::HistogramQuantile { q, le: 0 }] if (*q - 0.95).abs() < 1e-12
-    ));
-    assert!(matches!(op(child), NonASAPOp::Project { .. }));
-}
-
-#[tokio::test]
-async fn planning_relation_bridges_reject_ambiguous_shapes() {
-    let missing_alias = lower_sql(
-        "SELECT asap_promql_subquery(300000, 60000) FROM metrics",
-        &catalog(),
-        AccuracyTarget::Exact,
-    )
-    .await
-    .unwrap_err();
-    assert!(missing_alias.to_string().contains("must have an alias"));
-
-    let histogram_with_extra_column = lower_sql(
-        "SELECT service, asap_histogram_quantile(0.95) AS value FROM metrics",
-        &catalog(),
-        AccuracyTarget::Exact,
-    )
-    .await
-    .unwrap_err();
-    assert!(histogram_with_extra_column
-        .to_string()
-        .contains("only expression"));
-
-    let invalid_q = lower_sql(
-        "SELECT asap_histogram_quantile(1.5) AS value FROM metrics",
-        &catalog(),
-        AccuracyTarget::Exact,
-    )
-    .await
-    .unwrap_err();
-    assert!(invalid_q.to_string().contains("finite and in [0,1]"));
-}
-
-/// Find the first `Aggregate` node along the single-child spine.
-fn find_aggregate(node: &OperatorNode) -> Option<(&GroupKeys, &Vec<AggIntent>)> {
-    match op(node) {
-        NonASAPOp::Aggregate {
-            reduction,
-            measures,
-            ..
-        } => Some((reduction.expect_reduce(), measures)),
-        NonASAPOp::Project { child, .. }
-        | NonASAPOp::Filter { child, .. }
-        | NonASAPOp::Dedup { child, .. }
-        | NonASAPOp::Sort { child, .. }
-        | NonASAPOp::Limit { child, .. }
-        | NonASAPOp::PromqlSubquery { child, .. } => find_aggregate(child),
-        _ => None,
-    }
-}
-
-/// The first `Aggregate` node itself, for tests that need its child.
-fn find_aggregate_node(node: &OperatorNode) -> Option<&OperatorNode> {
-    match op(node) {
-        NonASAPOp::Aggregate { .. } => Some(node),
-        NonASAPOp::Project { child, .. }
-        | NonASAPOp::Filter { child, .. }
-        | NonASAPOp::Sort { child, .. }
-        | NonASAPOp::Limit { child, .. } => find_aggregate_node(child),
-        _ => None,
-    }
-}
-
-/// The names of the columns the first `Aggregate`'s reducers read, resolved
-/// against its child's schema, plus whether that child is a materializing
-/// `Project` (issue #110).
-fn reducer_input_names(node: &OperatorNode) -> (Vec<String>, bool) {
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = op(find_aggregate_node(node).expect("expected an Aggregate"))
-    else {
-        unreachable!()
-    };
-    let schema = &child.schema;
-    let names = measures
-        .iter()
-        .flat_map(|a| a.input_cols())
-        .map(|id| schema.fields[id].name.clone())
-        .collect();
-    (names, matches!(op(child), NonASAPOp::Project { .. }))
-}
-
-/// Find the first `Join` node along the single-child spine.
-fn find_join(node: &OperatorNode) -> Option<&OperatorNode> {
-    match op(node) {
-        NonASAPOp::Join { .. } => Some(node),
-        NonASAPOp::Project { child, .. }
-        | NonASAPOp::Filter { child, .. }
-        | NonASAPOp::Aggregate { child, .. }
-        | NonASAPOp::Dedup { child, .. }
-        | NonASAPOp::Sort { child, .. }
-        | NonASAPOp::Limit { child, .. }
-        | NonASAPOp::PromqlSubquery { child, .. } => find_join(child),
-        _ => None,
-    }
-}
-
-/// The first `Filter` node along the single-child spine.
-fn find_filter(node: &OperatorNode) -> Option<&OperatorNode> {
-    match op(node) {
-        NonASAPOp::Filter { .. } => Some(node),
-        NonASAPOp::Project { child, .. }
-        | NonASAPOp::Aggregate { child, .. }
-        | NonASAPOp::Dedup { child, .. }
-        | NonASAPOp::Sort { child, .. }
-        | NonASAPOp::Limit { child, .. }
-        | NonASAPOp::PromqlSubquery { child, .. } => find_filter(child),
-        _ => None,
-    }
-}
-
-#[tokio::test]
-async fn where_folds_predicate_onto_scan() {
-    // WHERE folds onto the Scan predicates, below the SELECT projection.
-    let qe = lower("SELECT * FROM metrics WHERE service = 'api'").await;
-    let NonASAPOp::Project { child, .. } = op(&qe) else {
-        panic!("expected Project at root, got {qe:?}");
-    };
-    let NonASAPOp::Scan {
-        source,
-        predicates,
-        schema,
-    } = op(child)
-    else {
-        panic!("expected Scan under the projection, got {child:?}");
-    };
-    assert!(matches!(source, Source::Table { table_ref } if table_ref == "metrics"));
-    assert_eq!(predicates.len(), 1, "WHERE clause folded onto the scan");
-    assert!(
-        schema.closed,
-        "a catalog-backed SQL scan has a closed schema"
-    );
-}
-
-#[tokio::test]
-async fn multi_aggregate_group_by_binds_columns_positionally() {
-    // SUM(bytes)=col 3, AVG(latency)=col 2, GROUP BY service=col 1.
-    let qe = lower("SELECT service, SUM(bytes), AVG(latency) FROM metrics GROUP BY service").await;
-    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate in the tree");
-    assert_eq!(by, &vec![1], "GROUP BY service → column 1");
-    assert!(
-        measures.contains(&AggIntent::Sum { col: Some(3) }),
-        "SUM(bytes) → Sum{{col:3}}, got {measures:?}"
-    );
-    assert!(
-        measures.contains(&AggIntent::Avg { col: Some(2) }),
-        "AVG(latency) → Avg{{col:2}}, got {measures:?}"
-    );
-}
-
-#[tokio::test]
-async fn projection_over_aggregate_resolves_output_types_via_output_names() {
-    // The enclosing Projection references the aggregates by DataFusion's
-    // generated names (e.g. "sum(metrics.bytes)"); output_names threads those
-    // onto the canonical Aggregate so the Project resolves real types — not
-    // the Utf8 fallback that an unresolved column would get.
-    let qe = lower("SELECT SUM(bytes), AVG(latency) FROM metrics").await;
-    let schema = &qe.schema;
-    assert_eq!(schema.fields.len(), 2);
-    assert_eq!(
-        schema.fields[0].dtype,
-        DataType::Int64,
-        "SUM(bytes:Int64) resolves to Int64, not the Utf8 fallback"
-    );
-    assert_eq!(
-        schema.fields[1].dtype,
-        DataType::Float64,
-        "AVG(latency) resolves to Float64"
-    );
-}
-
-#[tokio::test]
-async fn single_agg_group_by_keeps_key_in_output_schema() {
-    // A tabular single-aggregate GROUP BY routes through the positional
-    // Aggregate.by path (not the PromQL fused-Partition shape), so the group
-    // key is a real output column the enclosing SELECT projection resolves.
-    let qe = lower("SELECT service, SUM(bytes) FROM metrics GROUP BY service").await;
-    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate (not a Partition)");
-    assert_eq!(by, &vec![1], "GROUP BY service → Aggregate.by column 1");
-    assert!(matches!(
-        measures.as_slice(),
-        [AggIntent::Sum { col: Some(3) }]
-    ));
-
-    // Both the group key and the aggregate resolve in the root projection schema.
-    let schema = &qe.schema;
-    assert_eq!(schema.fields.len(), 2);
-    assert_eq!(
-        schema.fields[0].dtype,
-        DataType::Utf8,
-        "service is in the output"
-    );
-    assert_eq!(schema.fields[1].dtype, DataType::Int64, "SUM(bytes)");
-}
-
-#[tokio::test]
-async fn count_ranked_topk_is_heavy_hitter() {
-    // `ORDER BY COUNT(*) DESC LIMIT k` over a single COUNT aggregate is the one
-    // case the heavy-hitter (frequency) sketch is correct for. The shared
-    // `canonicalize` pass (issue #34) promotes it to the canonical two-level
-    // form: an outer global `TopK` (by: []) over the explicit inner `Count`
-    // grouped by `service`.
-    let qe = lower(
-        "SELECT service, COUNT(*) FROM metrics GROUP BY service ORDER BY COUNT(*) DESC LIMIT 10",
-    )
-    .await;
-    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate");
-    assert!(
-        by.is_empty(),
-        "outer TopK is a global ranking (by: []), got {by:?}"
-    );
-    assert!(
-        matches!(measures.as_slice(), [AggIntent::TopK { k: 10, .. }]),
-        "count-ranked topk → heavy-hitter TopK, got {measures:?}"
-    );
-    // The inner child is the explicit Count, grouped by service (col 1).
-    let NonASAPOp::Aggregate { child, .. } = op(&qe) else {
-        panic!("expected outer Aggregate, got {qe:?}");
-    };
-    let (inner_by, inner_measures) = find_aggregate(child).expect("expected inner Count aggregate");
-    assert_eq!(inner_by, &vec![1], "inner Count grouped by service → col 1");
-    assert!(
-        matches!(inner_measures.as_slice(), [AggIntent::Count { .. }]),
-        "inner aggregate is the explicit Count, got {inner_measures:?}"
-    );
-}
-
-#[tokio::test]
-async fn count_ranked_topk_via_alias_is_also_heavy_hitter() {
-    // Regression for #20: aliasing `COUNT(*)` in the ORDER BY used to defeat the
-    // SQL front-end gate. The positional `canonicalize` pass now promotes it too,
-    // so the aliased and inline forms produce an identical canonical tree.
-    let inline = lower(
-        "SELECT service, COUNT(*) FROM metrics GROUP BY service ORDER BY COUNT(*) DESC LIMIT 10",
-    )
-    .await;
-    let aliased = lower(
-        "SELECT service, COUNT(*) AS cnt FROM metrics GROUP BY service ORDER BY cnt DESC LIMIT 10",
-    )
-    .await;
-    assert_eq!(
-        inline, aliased,
-        "aliased count-ranked topk must match the inline form"
-    );
-    let (_, measures) = find_aggregate(&aliased).expect("expected an Aggregate");
-    assert!(
-        matches!(measures.as_slice(), [AggIntent::TopK { k: 10, .. }]),
-        "aliased count-ranked topk → heavy-hitter TopK, got {measures:?}"
-    );
-}
-
-#[tokio::test]
-async fn non_count_ranked_limit_keeps_the_aggregate() {
-    // Ranking by AVG (not a count) must NOT become a frequency heavy-hitter —
-    // the AVG aggregate has to survive as a generic Sort+Limit.
-    let qe = lower(
-        "SELECT service, AVG(latency) AS a FROM metrics GROUP BY service ORDER BY a DESC LIMIT 10",
-    )
-    .await;
-    let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
-    assert!(
-        measures.iter().any(|a| matches!(a, AggIntent::Avg { .. })),
-        "AVG must be preserved, got {measures:?}"
-    );
-    assert!(
-        !measures.iter().any(|a| matches!(a, AggIntent::TopK { .. })),
-        "AVG ranking must not become a frequency heavy-hitter, got {measures:?}"
-    );
-}
-
-#[tokio::test]
-async fn distinct_value_reducer_is_rejected_not_dropped() {
-    // The canonical intent algebra has no distinct-Sum; SUM(DISTINCT x) must
-    // be rejected, not silently lowered as SUM(x).
-    let res = lower_sql(
-        "SELECT SUM(DISTINCT bytes) FROM metrics",
-        &catalog(),
-        AccuracyTarget::Exact,
-    )
-    .await;
-    assert!(res.is_err(), "SUM(DISTINCT ...) should be rejected");
-}
-
-#[tokio::test]
-async fn aggregate_over_an_expression_reduces_a_derived_column() {
-    // The canonical `AggIntent` reduces a column, not an arbitrary expression.
-    // `SUM(bytes + 1)` used to be rejected for that reason; since #110 the
-    // expression is materialized as a derived column in a `Project` beneath
-    // the aggregate, and reduced there.
-    let qe = lower("SELECT SUM(bytes + 1) FROM metrics").await;
-    let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
-    assert!(
-        matches!(measures.as_slice(), [AggIntent::Sum { col: Some(_) }]),
-        "expected Sum bound to the derived column, got {measures:?}"
-    );
-    let (names, materialized) = reducer_input_names(&qe);
-    assert!(materialized, "expected a materializing Project");
-    assert!(
-        names[0].contains("bytes") && names[0].contains('1'),
-        "the reduced column should be the projected `bytes + 1`, got {names:?}"
-    );
-}
-
-#[tokio::test]
-async fn count_star_is_count_intent() {
-    let qe = lower("SELECT COUNT(*) FROM metrics").await;
-    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate");
-    assert!(by.is_empty());
-    assert!(matches!(measures.as_slice(), [AggIntent::Count { .. }]));
-}
-
-#[tokio::test]
-async fn count_distinct_is_cardinality() {
-    let qe = lower("SELECT COUNT(DISTINCT service) FROM metrics").await;
-    let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
-    assert!(matches!(
-        measures.as_slice(),
-        [AggIntent::Cardinality { .. }]
-    ));
-}
-
-#[tokio::test]
-async fn select_distinct_lowers_to_distinct_with_positional_cols() {
-    // SELECT DISTINCT → a `Dedup` node whose `cols` are positional ColumnIds
-    // (not name-based ColumnRefs). DataFusion's `Distinct::All` dedups on every
-    // column, so `cols` is empty here — but the field type is now `Vec<ColumnId>`.
-    let qe = lower("SELECT DISTINCT service FROM metrics").await;
-    let NonASAPOp::Dedup { cols, .. } = op(&qe) else {
-        panic!("expected a Dedup at the root, got {qe:?}");
-    };
-    let _: &Vec<usize> = cols; // compile-time: positional ids, not ColumnRefs
-    assert!(cols.is_empty(), "DISTINCT * dedups on all columns");
-}
-
-#[tokio::test]
-async fn inner_join_lowers_to_join_over_two_scans() {
-    // INNER JOIN over two distinct tables → a canonical Join with both leaves as Scans.
-    let qe = lower(
-        "SELECT metrics.bytes, hosts.region \
-         FROM metrics JOIN hosts ON metrics.service = hosts.service",
-    )
-    .await;
-    let join = find_join(&qe).expect("expected a Join in the tree");
-    let NonASAPOp::Join {
-        kind, left, right, ..
-    } = op(join)
-    else {
-        unreachable!("find_join only returns Join");
-    };
-    assert_eq!(*kind, JoinKind::Inner);
-    assert!(matches!(op(left), NonASAPOp::Scan { .. }));
-    assert!(matches!(op(right), NonASAPOp::Scan { .. }));
-}
-
-/// The two `ColumnId`s an equijoin predicate `Column(l) = Column(r)` binds to,
-/// returned sorted so the assertion is independent of left/right ordering.
-fn join_eq_columns(join: &OperatorNode) -> [usize; 2] {
-    let NonASAPOp::Join { pred, .. } = op(join) else {
-        unreachable!("expected a Join");
-    };
-    let ScalarExpr::Compare {
-        left,
-        op: CompareOpKind::Eq,
-        right,
-        ..
-    } = &pred.0
-    else {
-        panic!("expected an equijoin Compare, got {:?}", pred.0);
-    };
-    match (left.as_ref(), right.as_ref()) {
-        (ScalarExpr::Column(l), ScalarExpr::Column(r)) => {
-            let mut cols = [*l, *r];
-            cols.sort_unstable();
-            cols
-        }
-        other => panic!("expected Field = Field, got {other:?}"),
-    }
-}
-
-#[tokio::test]
-async fn join_predicate_disambiguates_shared_column_name() {
-    // Issue #7: `metrics.service = hosts.service` shares a column name across the
-    // join. The qualified refs must bind to two *distinct* positions in the
-    // concatenated schema, not collapse onto the first `service`.
-    // metrics(ts,service,latency,bytes) ++ hosts(service,region)
-    // → metrics.service = col 1, hosts.service = col 4.
-    let qe = lower(
-        "SELECT metrics.bytes, hosts.region \
-         FROM metrics JOIN hosts ON metrics.service = hosts.service",
-    )
-    .await;
-    let join = find_join(&qe).expect("expected a Join in the tree");
-    assert_eq!(
-        join_eq_columns(join),
-        [1, 4],
-        "join key must bind to distinct positions, not the same `service`"
-    );
-}
-
-#[tokio::test]
-async fn derived_table_join_disambiguates_via_alias() {
-    // Issue #66: a join over two *derived tables* must bind its keys to distinct
-    // positions. Before the fix the derived output columns lost their qualifier,
-    // so `a.service` and `b.service` both fell back to the first bare `service`
-    // (col 0) — `service = service`, always true → a silent cross product.
-    // Concatenated: a[service,region] ++ b[service,region] → a.service=0, b.service=2.
-    let qe = lower(
-        "SELECT a.region, b.region \
-         FROM (SELECT service, region FROM hosts) a \
-         JOIN (SELECT service, region FROM hosts) b ON a.service = b.service",
-    )
-    .await;
-    let join = find_join(&qe).expect("expected a Join in the tree");
-    assert_eq!(
-        join_eq_columns(join),
-        [0, 2],
-        "derived-table join keys must bind to distinct positions, not both to the first `service`"
-    );
-}
-
-#[tokio::test]
-async fn derived_table_select_star_join_disambiguates_via_alias() {
-    // Same as above but `SELECT *` derived tables (the non-Projection path that
-    // wraps the inner plan in an identity re-qualifying projection).
-    let qe = lower(
-        "SELECT a.region, b.region \
-         FROM (SELECT * FROM hosts) a JOIN (SELECT * FROM hosts) b \
-         ON a.service = b.service",
-    )
-    .await;
-    let join = find_join(&qe).expect("expected a Join in the tree");
-    let [l, r] = join_eq_columns(join);
-    assert_ne!(
-        l, r,
-        "SELECT * derived-table join keys must not collapse to one column"
-    );
-}
-
-#[tokio::test]
-async fn self_join_disambiguates_via_aliases() {
-    // A self-join shares *every* column name; the alias qualifiers (`a`/`b`) are
-    // the only way to tell the two `service` columns apart.
-    // metrics ++ metrics → a.service = col 1, b.service = col 5 (4 cols/side).
-    let qe = lower(
-        "SELECT a.bytes, b.latency \
-         FROM metrics a JOIN metrics b ON a.service = b.service",
-    )
-    .await;
-    let join = find_join(&qe).expect("expected a self-Join in the tree");
-    assert_eq!(
-        join_eq_columns(join),
-        [1, 5],
-        "self-join keys must bind to distinct sides"
-    );
-}
-
-#[tokio::test]
-async fn qualified_where_over_join_resolves_to_right_side() {
-    // Issue #7 beyond the join key: a WHERE on the *duplicated* column name
-    // (`service` exists on both sides) must bind to the qualified side, not the
-    // first match. metrics.service = col 1, hosts.service = col 4 → `hosts.service`
-    // must resolve to 4. (Unoptimized plan keeps the Filter above the Join — no
-    // predicate pushdown — so it binds against the concatenated schema.)
-    let qe = lower(
-        "SELECT metrics.bytes FROM metrics JOIN hosts ON metrics.service = hosts.service \
-         WHERE hosts.service = 'api'",
-    )
-    .await;
-    let filter = find_filter(&qe).expect("expected a Filter over the join");
-    let NonASAPOp::Filter { pred, .. } = op(filter) else {
-        unreachable!("find_filter only returns Filter");
-    };
-    assert!(
-        matches!(&pred.0, ScalarExpr::Compare { left, op: CompareOpKind::Eq, .. }
-            if matches!(left.as_ref(), ScalarExpr::Column(4))),
-        "hosts.service must bind to concatenated position 4 (not the first `service`), got {:?}",
-        pred.0
-    );
-}
-
-#[tokio::test]
-async fn self_join_group_by_disambiguates_via_qualifier() {
-    // Group-key qualifier fix: GROUP BY on the *duplicated* column over a
-    // self-join must bind to the qualified side, not first-match. metrics ⋈
-    // metrics → a.service = col 1, b.service = col 5. (Without qualified keys,
-    // both `GROUP BY a.service` and `GROUP BY b.service` collapsed to col 1.)
-    let qe_b = lower(
-        "SELECT b.service, COUNT(*) FROM metrics a JOIN metrics b \
-         ON a.service = b.service GROUP BY b.service",
-    )
-    .await;
-    let (by, _) = find_aggregate(&qe_b).expect("expected an Aggregate over the self-join");
-    assert_eq!(
-        by,
-        &vec![5],
-        "GROUP BY b.service binds to the b side (col 5)"
-    );
-
-    let qe_a = lower(
-        "SELECT a.service, COUNT(*) FROM metrics a JOIN metrics b \
-         ON a.service = b.service GROUP BY a.service",
-    )
-    .await;
-    let (by, _) = find_aggregate(&qe_a).expect("expected an Aggregate over the self-join");
-    assert_eq!(
-        by,
-        &vec![1],
-        "GROUP BY a.service binds to the a side (col 1)"
-    );
-}
-
-#[tokio::test]
-async fn aggregate_over_join_binds_against_concatenated_schema() {
-    // GROUP BY a right-table column over a join: the key must resolve against
-    // the concatenated schema, exercising the bottom-up converter end to end.
-    // Two aggregates → the multi-agg path, which carries GROUP BY keys as
-    // positional `Aggregate.by` (as does every reducing GROUP BY).
-    let qe = lower(
-        "SELECT hosts.region, SUM(metrics.bytes), COUNT(*) \
-         FROM metrics JOIN hosts ON metrics.service = hosts.service \
-         GROUP BY hosts.region",
-    )
-    .await;
-    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate over the join");
-    // metrics(ts,service,latency,bytes) ++ hosts(service,region) →
-    // region is column 5, bytes is column 3 of the concatenated schema.
-    assert_eq!(
-        by,
-        &vec![5],
-        "GROUP BY hosts.region → concatenated column 5"
-    );
-    assert!(
-        measures.contains(&AggIntent::Sum { col: Some(3) }),
-        "SUM(metrics.bytes) → Sum{{col:3}}, got {measures:?}"
-    );
-}
-
-// ── Issue #111: IN / EXISTS subquery predicates become semi / anti joins ────
-//
-// The front end now leaves them as `UnresolvedScalar::{InSubquery, Exists}`
-// filter conjuncts; the shared `canonicalize` pass (run by `resolve_root`)
-// lowers each to the semi-/anti-join, so the resolved DAG a test sees is the
-// same join shape the front end used to emit directly.
-
-/// The first `Join` node's `(kind, predicate, left column count)`.
-fn join_parts(node: &OperatorNode) -> (&JoinKind, &ScalarExpr, usize) {
-    let NonASAPOp::Join {
-        kind,
-        pred,
-        left,
-        right: _,
-    } = op(find_join(node).expect("expected a Join"))
-    else {
-        unreachable!()
-    };
-    (kind, &pred.0, left.schema.fields.len())
-}
-
-#[tokio::test]
-async fn in_subquery_lowers_to_a_semi_join() {
-    // `metrics(ts, service, latency, bytes)` — service is column 1.
-    let qe =
-        lower("SELECT service FROM metrics WHERE service IN (SELECT service FROM hosts)").await;
-    let (kind, pred, left_len) = join_parts(&qe);
-    assert_eq!(kind, &JoinKind::Semi);
-    assert_eq!(left_len, 4);
-
-    // The predicate resolves against `left ++ right`. Both relations have a
-    // `service` column, so a name-based lookup would bind *both* sides to the
-    // left's — silently making this `service = service`, always true. The key is
-    // bound positionally to the subquery's column (right after the left's),
-    // which makes that impossible.
-    let ScalarExpr::Compare { left, right, .. } = pred else {
-        panic!("expected a comparison, got {pred:?}");
-    };
-    assert_eq!(**left, ScalarExpr::Column(1), "outer service");
-    assert_eq!(
-        **right,
-        ScalarExpr::Column(left_len),
-        "the subquery key, not the outer column again"
-    );
-}
-
-#[tokio::test]
-async fn a_semi_join_outputs_only_the_left_schema() {
-    // The right side is a filter, not a source of columns.
-    let qe =
-        lower("SELECT service FROM metrics WHERE service IN (SELECT service FROM hosts)").await;
-    let join = find_join(&qe).expect("expected a Join");
-    let names: Vec<_> = join.schema.fields.iter().map(|c| c.name.clone()).collect();
-    assert_eq!(names, ["ts", "service", "latency", "bytes"]);
-}
-
-#[tokio::test]
-async fn a_subquery_key_that_is_an_expression_still_binds() {
-    // `SELECT bytes + 1 …` has no column name of its own; the join key binds
-    // to it positionally rather than through an unreferenceable `col_0`.
-    let qe =
-        lower("SELECT service FROM metrics WHERE bytes IN (SELECT bytes + 1 FROM metrics)").await;
-    assert_eq!(join_parts(&qe).0, &JoinKind::Semi);
-}
-
-#[tokio::test]
-async fn a_multi_column_in_subquery_is_rejected() {
-    let err = lower_sql(
-        "SELECT service FROM metrics WHERE service IN (SELECT service, region FROM hosts)",
-        &catalog(),
-        AccuracyTarget::Exact,
-    )
-    .await
-    .expect_err("IN must select one column");
-    // DataFusion's planner rejects this before `lower_in_subquery`'s own
-    // arity check; either message names the one-column rule.
-    assert!(format!("{err}").contains("one column"), "got {err}");
-}
-
-#[tokio::test]
-async fn an_ordinary_conjunct_still_folds_onto_the_scan() {
-    // The residual filter stays *below* the semi-join, where the converter can
-    // still fold it onto the Scan. A semi-join only drops left rows, so the
-    // orders agree.
-    let qe = lower(
-        "SELECT service FROM metrics WHERE bytes > 10 \
-         AND service IN (SELECT service FROM hosts)",
-    )
-    .await;
-    fn scan_has_predicate(node: &OperatorNode) -> bool {
-        match op(node) {
-            NonASAPOp::Scan { predicates, .. } => !predicates.is_empty(),
-            NonASAPOp::Project { child, .. }
-            | NonASAPOp::Filter { child, .. }
-            | NonASAPOp::Aggregate { child, .. } => scan_has_predicate(child),
-            NonASAPOp::Join { left, right, .. } => {
-                scan_has_predicate(left) || scan_has_predicate(right)
-            }
-            _ => false,
-        }
-    }
-    assert_eq!(join_parts(&qe).0, &JoinKind::Semi);
-    assert!(
-        scan_has_predicate(&qe),
-        "WHERE bytes > 10 should reach the Scan"
-    );
-}
-
-/// Find the first `SQLWindowFunc` node along the single-child spine.
-fn find_windowfunc(node: &OperatorNode) -> Option<&OperatorNode> {
-    match op(node) {
-        NonASAPOp::SQLWindowFunc { .. } => Some(node),
-        NonASAPOp::Project { child, .. }
-        | NonASAPOp::Filter { child, .. }
-        | NonASAPOp::Aggregate { child, .. }
-        | NonASAPOp::Dedup { child, .. }
-        | NonASAPOp::Sort { child, .. }
-        | NonASAPOp::Limit { child, .. }
-        | NonASAPOp::PromqlSubquery { child, .. } => find_windowfunc(child),
-        _ => None,
-    }
-}
-
-#[tokio::test]
-async fn window_function_lowers_to_positional_windowfunc() {
-    // ROW_NUMBER() OVER (PARTITION BY service ORDER BY bytes DESC).
-    let qe = lower(
-        "SELECT service, ROW_NUMBER() OVER (PARTITION BY service ORDER BY bytes DESC) \
-         FROM metrics",
-    )
-    .await;
-    let win = find_windowfunc(&qe).expect("expected a SQLWindowFunc node");
-    let NonASAPOp::SQLWindowFunc {
-        func,
-        partition_by,
-        order_by,
-        ..
-    } = op(win)
-    else {
-        unreachable!("find_windowfunc only returns SQLWindowFunc");
-    };
-    assert_eq!(*func, WindowFuncKind::RowNumber);
-    assert_eq!(partition_by, &vec![1], "PARTITION BY service → col 1");
-    assert_eq!(order_by.len(), 1);
-    assert_eq!(
-        order_by[0].expr,
-        ScalarExpr::Column(3),
-        "ORDER BY bytes → col 3"
-    );
-    assert!(!order_by[0].ascending, "DESC");
-
-    // The window output column is appended to the schema (Int64 for ROW_NUMBER),
-    // and the enclosing projection resolves it (output_name threading).
-    let schema = &qe.schema;
-    assert!(
-        schema.fields.iter().any(|c| c.dtype == DataType::Int64),
-        "row_number output column present, got {:?}",
-        schema.fields
-    );
-}
-
-#[tokio::test]
-async fn window_aggregate_lowers_to_windowfunc() {
-    let qe = lower("SELECT service, SUM(bytes) OVER (PARTITION BY service) FROM metrics").await;
-    let win = find_windowfunc(&qe).expect("expected a SQLWindowFunc node");
-    let NonASAPOp::SQLWindowFunc { func, args, .. } = op(win) else {
-        unreachable!();
-    };
-    assert_eq!(*func, WindowFuncKind::Sum);
-    assert_eq!(args, &vec![ScalarExpr::Column(3)], "SUM(bytes) → arg col 3");
-}
-
-// ── Window frames (issue #268) ───────────────────────────────────────────────
-
-/// The frame clause must actually reach the IR, not just the display string:
-/// three window frames that differ semantically must lower to different
-/// `SQLWindowFunc.frame` values.
-#[tokio::test]
-async fn window_frame_is_captured_not_dropped() {
-    let default_frame =
-        lower("SELECT service, SUM(latency) OVER (PARTITION BY service ORDER BY ts) FROM metrics")
-            .await;
-    let two_preceding = lower(
-        "SELECT service, SUM(latency) OVER (PARTITION BY service ORDER BY ts \
-         ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) FROM metrics",
-    )
-    .await;
-    let unbounded_following = lower(
-        "SELECT service, SUM(latency) OVER (PARTITION BY service ORDER BY ts \
-         ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING) FROM metrics",
-    )
-    .await;
-
-    let frame_of = |node: &OperatorNode| {
-        let NonASAPOp::SQLWindowFunc { frame, .. } = op(find_windowfunc(node).unwrap()) else {
-            unreachable!();
-        };
-        frame
-            .clone()
-            .expect("newly lowered SQL always records a frame")
-    };
-    let (a, b, c) = (
-        frame_of(&default_frame),
-        frame_of(&two_preceding),
-        frame_of(&unbounded_following),
-    );
-    assert_ne!(a, b, "default frame vs ROWS 2 PRECEDING must differ");
-    assert_ne!(
-        a, c,
-        "default frame vs ROWS CURRENT..UNBOUNDED FOLLOWING must differ"
-    );
-    assert_ne!(b, c);
-
-    assert_eq!(b.units, WindowFrameUnits::Rows);
-    assert_eq!(
-        b.start_bound,
-        WindowFrameBound::Preceding(WindowFrameOffset::Scalar(ScalarValue::Int64(2)))
-    );
-    assert_eq!(b.end_bound, WindowFrameBound::CurrentRow);
-
-    assert_eq!(c.start_bound, WindowFrameBound::CurrentRow);
-    assert_eq!(
-        c.end_bound,
-        WindowFrameBound::Following(WindowFrameOffset::Scalar(ScalarValue::Null))
-    );
-}
-
-#[tokio::test]
-async fn range_interval_frame_is_preserved() {
-    let qe = lower(
-        "SELECT service, SUM(latency) OVER (PARTITION BY service ORDER BY ts \
-         RANGE BETWEEN INTERVAL '1' HOUR PRECEDING AND CURRENT ROW) FROM metrics",
-    )
-    .await;
-    let NonASAPOp::SQLWindowFunc {
-        frame: Some(frame), ..
-    } = op(find_windowfunc(&qe).unwrap())
-    else {
-        panic!("expected a window function with a concrete frame");
-    };
-
-    assert_eq!(frame.units, WindowFrameUnits::Range);
-    assert_eq!(
-        frame.start_bound,
-        WindowFrameBound::Preceding(WindowFrameOffset::Interval {
-            months: 0,
-            days: 0,
-            nanoseconds: 3_600_000_000_000,
-        })
-    );
-    assert_eq!(frame.end_bound, WindowFrameBound::CurrentRow);
-}
-
-#[tokio::test]
-async fn range_numeric_frames_remain_scalar_offsets() {
-    let integer = lower(
-        "SELECT SUM(bytes) OVER (ORDER BY bytes \
-         RANGE BETWEEN 2 PRECEDING AND CURRENT ROW) FROM metrics",
-    )
-    .await;
-    let fractional = lower(
-        "SELECT SUM(latency) OVER (ORDER BY latency \
-         RANGE BETWEEN 1.5 PRECEDING AND CURRENT ROW) FROM metrics",
-    )
-    .await;
-
-    let start_bound = |node: &OperatorNode| {
-        let NonASAPOp::SQLWindowFunc {
-            frame: Some(frame), ..
-        } = op(find_windowfunc(node).unwrap())
-        else {
-            panic!("expected a window function with a concrete frame");
-        };
-        frame.start_bound.clone()
-    };
-
-    assert_eq!(
-        start_bound(&integer),
-        WindowFrameBound::Preceding(WindowFrameOffset::Scalar(ScalarValue::Int64(2)))
-    );
-    assert_eq!(
-        start_bound(&fractional),
-        WindowFrameBound::Preceding(WindowFrameOffset::Scalar(ScalarValue::Float64(1.5)))
-    );
-}
-
-/// `GROUPS` frames aren't in this repo's SQL corpora and nothing downstream
-/// interprets frame semantics yet — rejected explicitly rather than silently
-/// mis-lowered.
-#[tokio::test]
-async fn groups_frame_is_rejected() {
-    let err = lower_sql(
-        "SELECT service, SUM(latency) OVER (PARTITION BY service ORDER BY ts \
-         GROUPS BETWEEN 2 PRECEDING AND CURRENT ROW) FROM metrics",
-        &catalog(),
-        AccuracyTarget::Exact,
-    )
-    .await
-    .expect_err("GROUPS frame unit must be rejected");
-    assert!(format!("{err}").contains("GROUPS"), "got {err}");
-}
-
-// ── Nested query functions: derived tables / inline views (issue #27) ───────────
-
-/// Collect every `AggIntent` in the DAG, root-to-leaf (every reachable node,
-/// including operators referenced from scalar positions).
-fn all_intents(root: &Rc<OperatorNode>) -> Vec<AggIntent> {
-    OperatorNode::reachable(root)
-        .iter()
-        .filter_map(|node| match op(node) {
-            NonASAPOp::Aggregate { measures, .. } => Some(measures.clone()),
-            _ => None,
-        })
-        .flatten()
-        .collect()
-}
-
-#[tokio::test]
-async fn derived_table_aggregate_over_aggregate_nests() {
-    // `MAX(s)` over a derived table `(SELECT service, SUM(bytes) AS s … GROUP BY
-    // service)` — the SQL counterpart of PromQL function nesting (issue #27).
-    // Both reductions survive into the canonical tree: an outer `Max` over
-    // the inner `Sum`.
-    let qe = lower(
-        "SELECT MAX(s) FROM \
-         (SELECT service, SUM(bytes) AS s FROM metrics GROUP BY service) t",
-    )
-    .await;
-    let intents = all_intents(&qe);
-    assert!(
-        intents.iter().any(|i| matches!(i, AggIntent::Max { .. })),
-        "outer MAX survives, got {intents:?}"
-    );
-    assert!(
-        intents.iter().any(|i| matches!(i, AggIntent::Sum { .. })),
-        "inner SUM survives, got {intents:?}"
-    );
-    // The whole nested tree's output schema derives (positional resolution
-    // is total across the derived-table boundary).
-    assert_eq!(qe.schema.fields.len(), 1);
-}
-
-#[tokio::test]
-async fn derived_table_outer_avg_over_inner_percentile() {
-    // Outer exact `AVG` over an inner approximate `Quantile` — each layer keeps
-    // its own intent (the per-node sketch-vs-exact choice is a post-ASAP decision).
-    let qe = lower(
-        "SELECT AVG(p) FROM \
-         (SELECT service, approx_percentile_cont(latency, 0.9) AS p \
-          FROM metrics GROUP BY service) t",
-    )
-    .await;
-    let intents = all_intents(&qe);
-    assert!(intents.iter().any(|i| matches!(i, AggIntent::Avg { .. })));
-    assert!(intents
-        .iter()
-        .any(|i| matches!(i, AggIntent::Quantile { q, .. } if (*q - 0.9).abs() < 1e-9)));
-}
-
-#[tokio::test]
-async fn filter_over_derived_aggregate_resolves_alias_column() {
-    // `WHERE t.s > 100` over a derived aggregate — the qualified ref `t.s`
-    // resolves by bare name against the derived output schema, and the Filter
-    // sits above the inner Aggregate.
-    let qe = lower(
-        "SELECT t.service, t.s FROM \
-         (SELECT service, SUM(bytes) AS s FROM metrics GROUP BY service) t \
-         WHERE t.s > 100",
-    )
-    .await;
-    assert!(
-        find_filter(&qe).is_some(),
-        "the outer WHERE lowers to a Filter, got {qe:?}"
-    );
-    assert!(all_intents(&qe)
-        .iter()
-        .any(|i| matches!(i, AggIntent::Sum { .. })));
-    // Schema derivation is total across the boundary: the root carries one.
-    assert_eq!(qe.schema.fields.len(), 2);
-}
-
-#[tokio::test]
-async fn scalar_subquery_in_predicate_lowers_through_a_cross_join() {
-    let qe =
-        lower("SELECT service FROM metrics WHERE bytes > (SELECT AVG(bytes) FROM metrics)").await;
-    let filter = find_filter(&qe).unwrap();
-    let NonASAPOp::Filter { pred, child } = op(filter) else {
-        panic!()
-    };
-    assert!(matches!(op(child), NonASAPOp::Scan { .. }));
-    assert!(
-        matches!(&pred.0,ScalarExpr::Compare { right,.. } if matches!(right.as_ref(),ScalarExpr::ScalarSubquery(_)))
-    );
-    qe.validate_structure().unwrap();
-}
-
-#[tokio::test]
-async fn correlated_exists_lifts_its_correlation_into_the_join() {
-    // `EXISTS (SELECT 1 FROM hosts h WHERE h.service = m.service)` → a semi-join
-    // on `h.service = m.service`. The `SELECT 1` projection is dropped: a
-    // semi-join keeps no right columns, and it would have projected away the
-    // very column the correlation needs.
-    let qe = lower(
-        "SELECT service FROM metrics m WHERE EXISTS \
-         (SELECT 1 FROM hosts h WHERE h.service = m.service)",
-    )
-    .await;
-    let (kind, pred, left_len) = join_parts(&qe);
-    assert_eq!(kind, &JoinKind::Semi);
-    let ScalarExpr::Compare { left, right, .. } = pred else {
-        panic!("expected the correlation as a comparison, got {pred:?}");
-    };
-    assert_eq!(
-        **left,
-        ScalarExpr::Column(left_len),
-        "h.service (right side)"
-    );
-    assert_eq!(**right, ScalarExpr::Column(1), "m.service (left side)");
-}
-
-#[tokio::test]
-async fn not_exists_lowers_to_an_anti_join() {
-    let qe = lower(
-        "SELECT service FROM metrics m WHERE NOT EXISTS \
-         (SELECT 1 FROM hosts h WHERE h.service = m.service)",
-    )
-    .await;
-    assert_eq!(join_parts(&qe).0, &JoinKind::Anti);
-}
-
-#[tokio::test]
-async fn an_uncorrelated_exists_is_an_unconditional_semi_join() {
-    // No correlation → keep every left row iff the right side has any row.
-    let qe = lower("SELECT service FROM metrics WHERE EXISTS (SELECT 1 FROM hosts)").await;
-    let (kind, pred, _) = join_parts(&qe);
-    assert_eq!(kind, &JoinKind::Semi);
-    assert_eq!(*pred, ScalarExpr::Literal(ScalarValue::Boolean(true)));
-}
-
-#[tokio::test]
-async fn where_exists_resolves_to_a_semi_join_over_the_subquery() {
-    // The front end emits `Filter { Exists(s) }`; the resolved DAG is the
-    // `Semi` join with the subquery (a filtered `hosts` scan) on the right.
-    let qe = lower(
-        "SELECT service FROM metrics WHERE EXISTS (SELECT service FROM hosts WHERE region = 'eu')",
-    )
-    .await;
-    let NonASAPOp::Project { child, .. } = op(&qe) else {
-        panic!("expected the SELECT list as a Project, got {qe:?}");
-    };
-    let NonASAPOp::Join {
-        kind,
-        pred,
-        left,
-        right,
-    } = op(child)
-    else {
-        panic!("expected the Semi join directly under the Project, got {child:?}");
-    };
-    assert_eq!(*kind, JoinKind::Semi);
-    assert_eq!(pred.0, ScalarExpr::Literal(ScalarValue::Boolean(true)));
-    assert!(
-        matches!(op(left), NonASAPOp::Scan { .. }),
-        "left is metrics"
-    );
-    let NonASAPOp::Project { child: scan, .. } = op(right) else {
-        panic!("expected the subquery's projection on the right, got {right:?}");
-    };
-    assert!(
-        matches!(op(scan), NonASAPOp::Scan { predicates, .. } if predicates.len() == 1),
-        "the subquery's WHERE stays on its own Scan, got {scan:?}"
-    );
-    assert_eq!(
-        child.schema.fields.len(),
-        4,
-        "a semi join outputs the left's columns alone"
-    );
-}
-
-#[tokio::test]
-async fn not_in_subquery_is_rejected_rather_than_mislowered_as_an_anti_join() {
-    let qe =
-        lower("SELECT service FROM metrics WHERE service NOT IN (SELECT service FROM hosts)").await;
-    let filter = find_filter(&qe).unwrap();
-    let NonASAPOp::Filter { pred, .. } = op(filter) else {
-        panic!()
-    };
-    assert!(matches!(
-        pred.0,
-        ScalarExpr::InSubquery { negated: true, .. }
-    ));
-    qe.validate_structure().unwrap();
-}
-
-#[tokio::test]
-async fn a_correlated_in_subquery_is_rejected() {
-    let err = lower_sql(
-        "SELECT service FROM metrics m WHERE service IN \
-         (SELECT h.service FROM hosts h WHERE h.region = m.service)",
-        &catalog(),
-        AccuracyTarget::Exact,
-    )
-    .await
-    .expect_err("correlated IN needs both a key match and a correlation");
-    assert!(format!("{err}").contains("correlated IN"), "got {err}");
-}
-
-// ── Subquery-valued expressions at the `UnresolvedOp` level ─────────────────
-
-/// `SqlLowerer::lower` output, before `resolve_root`.
-async fn lower_unresolved(sql: &str) -> UnresolvedOp {
-    let catalog = catalog();
-    SqlLowerer::new(&catalog)
-        .lower(sql, &AccuracyTarget::Exact)
-        .await
-        .unwrap_or_else(|e| panic!("lower failed for {sql:?}: {e}"))
-}
-
-#[tokio::test]
-async fn scalar_subquery_in_projection_lowers_to_a_scalar_subquery_item() {
-    // An uncorrelated `(SELECT max(v) FROM t2)` in the SELECT list is a
-    // `ScalarSubquery` projection item reading its own lowered plan; the
-    // cross-join rewrite is `canonicalize`'s job, not the front end's.
-    let tree = lower_unresolved("SELECT (SELECT max(latency) FROM metrics) FROM hosts").await;
-    let UnresolvedOp::Project { cols, child, .. } = &tree else {
-        panic!("expected the SELECT list as a Project, got {tree:?}");
-    };
-    assert!(
-        matches!(child.as_ref(), UnresolvedOp::Scan { source: Source::Table { table_ref }, .. }
-            if table_ref == "hosts"),
-        "the outer relation stays the projection's child, got {child:?}"
-    );
-    assert_eq!(cols.len(), 1);
-    let UnresolvedScalar::ScalarSubquery(sub) = &cols[0].expr else {
-        panic!("expected a ScalarSubquery item, got {:?}", cols[0].expr);
-    };
-    let UnresolvedOp::Project { child: inner, .. } = sub.as_ref() else {
-        panic!("expected the subquery's own SELECT list, got {sub:?}");
-    };
-    assert!(
-        matches!(inner.as_ref(), UnresolvedOp::Aggregate { measures, .. }
-            if matches!(measures.as_slice(), [AggIntent::Max { .. }])),
-        "the subquery plan is lowered as a root of its own, got {inner:?}"
-    );
-}
-
-#[tokio::test]
-async fn exists_and_in_subqueries_lower_to_scalar_filter_conjuncts() {
-    // The front end no longer builds the semi join itself: `EXISTS` / `IN
-    // (…)` are `Filter` predicates reading the subquery operator.
-    let tree =
-        lower_unresolved("SELECT service FROM metrics WHERE EXISTS (SELECT 1 FROM hosts)").await;
-    let UnresolvedOp::Project { child, .. } = &tree else {
-        panic!("expected a Project, got {tree:?}");
-    };
-    assert!(
-        matches!(child.as_ref(), UnresolvedOp::Filter { pred, .. }
-            if matches!(pred.0, UnresolvedScalar::Exists { negated: false, .. })),
-        "expected Filter {{ Exists }}, got {child:?}"
-    );
-
-    let tree = lower_unresolved(
-        "SELECT service FROM metrics WHERE service IN (SELECT service FROM hosts)",
-    )
-    .await;
-    let UnresolvedOp::Project { child, .. } = &tree else {
-        panic!("expected a Project, got {tree:?}");
-    };
-    assert!(
-        matches!(child.as_ref(), UnresolvedOp::Filter { pred, .. }
-            if matches!(pred.0, UnresolvedScalar::InSubquery { negated: false, .. })),
-        "expected Filter {{ InSubquery }}, got {child:?}"
-    );
-}
-
-// ── `SELECT` without `FROM`, unary minus, SQL expression semantics ──────────
-
-#[tokio::test]
-async fn select_without_from_projects_over_one_empty_row() {
-    // `SELECT 1` has no table: DataFusion's `EmptyRelation` is one empty
-    // input row, which the SELECT list projects a literal over.
-    let qe = lower("SELECT 1").await;
-    let NonASAPOp::Project { cols, child, .. } = op(&qe) else {
-        panic!("expected Project at root, got {qe:?}");
-    };
-    assert_eq!(cols.len(), 1);
-    assert_eq!(cols[0].expr, ScalarExpr::Literal(ScalarValue::Int64(1)));
-    let NonASAPOp::Values { rows, schema } = op(child) else {
-        panic!("expected Values under the Project, got {child:?}");
-    };
-    assert_eq!(rows, &vec![Vec::<ScalarExpr>::new()], "one empty row");
-    assert!(schema.fields.is_empty() && schema.closed);
-    assert_eq!(qe.schema.fields.len(), 1);
-    assert_eq!(qe.schema.fields[0].dtype, DataType::Int64);
-}
-
-#[tokio::test]
-async fn values_lowers_to_one_row_per_values_row() {
-    let qe = lower("SELECT * FROM (VALUES (1, 'a'), (2, 'b')) AS v(n, s)").await;
-    let values = OperatorNode::reachable(&qe)
-        .into_iter()
-        .find(|n| matches!(op(n), NonASAPOp::Values { .. }))
-        .expect("expected a Values node");
-    let NonASAPOp::Values { rows, schema } = op(&values) else {
-        unreachable!()
-    };
-    assert_eq!(rows.len(), 2);
-    assert_eq!(
-        rows[1],
-        vec![
-            ScalarExpr::Literal(ScalarValue::Int64(2)),
-            ScalarExpr::Literal(ScalarValue::Utf8("b".into())),
-        ]
-    );
-    assert_eq!(schema.fields.len(), 2);
-    assert_eq!(schema.fields[0].dtype, DataType::Int64);
-    assert_eq!(schema.fields[1].dtype, DataType::Utf8);
-    assert_eq!(
-        qe.schema
-            .fields
-            .iter()
-            .map(|f| f.name.as_str())
-            .collect::<Vec<_>>(),
-        ["n", "s"]
-    );
-}
-
-#[tokio::test]
-async fn unary_minus_lowers_to_negative() {
-    // `-x` over a column is the `Negative` scalar (a negative *literal* is
-    // folded by DataFusion's planner before lowering).
-    let qe = lower("SELECT -latency FROM metrics").await;
-    let NonASAPOp::Project { cols, .. } = op(&qe) else {
-        panic!("expected Project at root, got {qe:?}");
-    };
-    assert_eq!(
-        cols[0].expr,
-        ScalarExpr::Negative {
-            expr: Box::new(ScalarExpr::Column(2)),
-            semantics: ExprSemantics::Sql,
-        }
-    );
-    assert_eq!(qe.schema.fields[0].dtype, DataType::Float64);
-}
-
-#[tokio::test]
-async fn sql_comparisons_and_arithmetic_carry_sql_semantics() {
-    let qe = lower("SELECT bytes * 8 FROM metrics WHERE latency > 1.5").await;
-    let NonASAPOp::Project { cols, child, .. } = op(&qe) else {
-        panic!("expected Project at root, got {qe:?}");
-    };
-    assert!(
-        matches!(
-            &cols[0].expr,
-            ScalarExpr::Arithmetic {
-                semantics: ExprSemantics::Sql,
-                ..
-            }
-        ),
-        "got {:?}",
-        cols[0].expr
-    );
-    let NonASAPOp::Scan { predicates, .. } = op(child) else {
-        panic!("expected the WHERE folded onto the Scan, got {child:?}");
-    };
-    assert!(
-        matches!(
-            &predicates[0].0,
-            ScalarExpr::Compare {
-                semantics: ExprSemantics::Sql,
-                ..
-            }
-        ),
-        "got {:?}",
-        predicates[0].0
-    );
-}
-
-// ── Issue #115: Quantile / Cardinality carry their input column ─────────────
-
-#[tokio::test]
-async fn quantile_carries_its_input_column() {
-    // `metrics(ts=0, service=1, latency=2, bytes=3)`. Two quantiles over
-    // different columns must not compare equal — a workload-level dedupe pass
-    // would compare on `AggIntent` equality, so a col-less intent would
-    // collapse them.
-    let qe = lower(
-        "SELECT approx_percentile_cont(latency, 0.5), \
-                approx_percentile_cont(bytes, 0.5) FROM metrics",
-    )
-    .await;
-    let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
-    assert!(
-        matches!(
-            measures.as_slice(),
-            [
-                AggIntent::Quantile { col: Some(2), .. },
-                AggIntent::Quantile { col: Some(3), .. }
-            ]
-        ),
-        "quantiles must bind their own column, got {measures:?}"
-    );
-    assert_ne!(
-        measures[0], measures[1],
-        "distinct-column quantiles must not compare equal"
-    );
-}
-
-#[tokio::test]
-async fn count_distinct_carries_its_input_column() {
-    let qe = lower("SELECT COUNT(DISTINCT service), COUNT(DISTINCT bytes) FROM metrics").await;
-    let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
-    assert!(
-        matches!(
-            measures.as_slice(),
-            [
-                AggIntent::Cardinality { cols: c1, .. },
-                AggIntent::Cardinality { cols: c2, .. }
-            ] if c1 == &[1] && c2 == &[3]
-        ),
-        "cardinalities must bind their own column, got {measures:?}"
-    );
-    assert_ne!(
-        measures[0], measures[1],
-        "distinct-column cardinalities must not compare equal"
-    );
-}
-
-#[tokio::test]
-async fn quantile_and_count_distinct_over_an_expression_bind_the_derived_column() {
-    // A SQL aggregate has no "sample value" to fall back on, so an expression
-    // argument must never reach the canonical tree as `col: None` (#115).
-    // Since #110 it reaches the canonical tree as `col: Some(derived)`
-    // instead of being rejected.
-    for q in [
-        "SELECT approx_percentile_cont(bytes * 8, 0.95) FROM metrics",
-        "SELECT COUNT(DISTINCT bytes * 8) FROM metrics",
-        "SELECT approx_distinct(bytes * 8) FROM metrics",
-    ] {
-        let qe = lower(q).await;
-        let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
-        assert!(
-            !measures[0].input_cols().is_empty(),
-            "{q} must bind a column, never the implicit input, got {measures:?}"
-        );
-        let (names, materialized) = reducer_input_names(&qe);
-        assert!(materialized, "{q} expected a materializing Project");
-        assert!(
-            names[0].contains("bytes"),
-            "{q} should reduce the projected `bytes * 8`, got {names:?}"
-        );
-    }
-}
-
-// ── Issue #111: median / approx_median → the φ=0.5 quantile ─────────────────
-
-#[tokio::test]
-async fn median_lowers_to_the_half_quantile() {
-    // `metrics(ts=0, service=1, latency=2, bytes=3)`.
-    for sql in [
-        "SELECT median(latency) FROM metrics",
-        "SELECT approx_median(latency) FROM metrics",
-    ] {
-        let qe = lower(sql).await;
-        let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
-        assert!(
-            matches!(
-                measures.as_slice(),
-                [AggIntent::Quantile { col: Some(2), q, .. }] if (*q - 0.5).abs() < 1e-9
-            ),
-            "{sql} should lower to Quantile(0.5) over latency, got {measures:?}"
-        );
-    }
-}
-
-#[tokio::test]
-async fn median_is_the_same_intent_as_an_explicit_half_percentile() {
-    // Two spellings of one intent: CSE should be able to merge them.
-    let m = lower("SELECT median(latency) FROM metrics").await;
-    let p = lower("SELECT approx_percentile_cont(latency, 0.5) FROM metrics").await;
-    let (_, m_measures) = find_aggregate(&m).expect("expected an Aggregate");
-    let (_, p_measures) = find_aggregate(&p).expect("expected an Aggregate");
-    assert_eq!(m_measures, p_measures);
-}
-
-#[tokio::test]
-async fn median_threads_the_accuracy_target() {
-    // The `approx_` prefix does not decide: the AccuracyTarget does.
-    let qe = lower_sql(
-        "SELECT approx_median(latency) FROM metrics",
-        &catalog(),
-        AccuracyTarget::Epsilon(0.01),
-    )
-    .await
-    .expect("approx_median should lower");
-    let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
-    assert!(
-        matches!(
-            measures.as_slice(),
-            [AggIntent::Quantile { accuracy: AccuracyTarget::Epsilon(e), .. }]
-                if (*e - 0.01).abs() < 1e-12
-        ),
-        "median must carry the workload's accuracy target, got {measures:?}"
-    );
-}
-
-#[tokio::test]
-async fn median_over_an_expression_binds_the_derived_column() {
-    // Was rejected when filed (#111); supported since #110 materialized the
-    // expression. What must still hold is the #115 rule: never `col: None`.
-    let qe = lower("SELECT median(bytes * 8) FROM metrics").await;
-    let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
-    assert!(
-        matches!(measures.as_slice(), [AggIntent::Quantile { col: Some(_), q, .. }] if (*q - 0.5).abs() < 1e-9),
-        "expected Quantile(0.5) bound to the derived column, got {measures:?}"
-    );
-}
-
-// ── Issue #110: expression GROUP BY (time bucketing) ────────────────────────
-
-#[tokio::test]
-async fn time_bucketing_group_by_lowers_to_a_derived_key() {
-    // The canonical time-series shape: `GROUP BY date_trunc(...)`. The bucket
-    // expression is materialized beneath the aggregate and grouped on.
-    let qe =
-        lower("SELECT date_trunc('minute', ts) AS m, SUM(bytes) FROM metrics GROUP BY m").await;
-    let node = find_aggregate_node(&qe).expect("expected an Aggregate");
-    let NonASAPOp::Aggregate {
-        reduction,
-        measures,
-        child,
-        ..
-    } = op(node)
-    else {
-        unreachable!()
-    };
-    assert!(
-        matches!(op(child), NonASAPOp::Project { .. }),
-        "expected a materializing Project beneath the Aggregate"
-    );
-    let schema = &child.schema;
-    assert_eq!(reduction, &Reduction::by(vec![0]));
-    assert!(
-        schema.fields[0].name.contains("date_trunc"),
-        "group key should be the projected bucket, got {:?}",
-        schema.fields[0].name
-    );
-    // The reducer still binds its own column, not the bucket.
-    assert!(matches!(
-        measures.as_slice(),
-        [AggIntent::Sum { col: Some(1) }]
-    ));
-}
-
-#[tokio::test]
-async fn time_bucketing_keeps_the_scan_predicate() {
-    // The projection is inserted above the scan, so a WHERE clause still folds
-    // onto the Scan rather than being stranded.
-    let qe = lower(
-        "SELECT date_trunc('minute', ts) AS m, SUM(bytes) FROM metrics \
-         WHERE bytes > 10 GROUP BY m",
-    )
-    .await;
-    fn scan_has_predicate(node: &OperatorNode) -> bool {
-        match op(node) {
-            NonASAPOp::Scan { predicates, .. } => !predicates.is_empty(),
-            NonASAPOp::Project { child, .. }
-            | NonASAPOp::Filter { child, .. }
-            | NonASAPOp::Aggregate { child, .. }
-            | NonASAPOp::Sort { child, .. }
-            | NonASAPOp::Limit { child, .. } => scan_has_predicate(child),
-            _ => false,
-        }
-    }
-    assert!(scan_has_predicate(&qe), "WHERE should stay on the Scan");
-}
-
-#[tokio::test]
-async fn a_plain_group_by_inserts_no_projection() {
-    // Queries that lowered before #110 must keep their exact tree shape — the
-    // projection appears only when something actually needs materializing.
-    for q in [
-        "SELECT service, SUM(bytes) FROM metrics GROUP BY service",
-        "SELECT SUM(bytes) FROM metrics",
-        "SELECT COUNT(*) FROM metrics",
-    ] {
-        let qe = lower(q).await;
-        let NonASAPOp::Aggregate { child, .. } =
-            op(find_aggregate_node(&qe).expect("expected an Aggregate"))
-        else {
-            unreachable!()
-        };
-        assert!(
-            !matches!(op(child), NonASAPOp::Project { .. }),
-            "{q} should not gain a projection"
-        );
-    }
-}
-
-#[tokio::test]
-async fn a_shared_expression_is_materialized_once() {
-    let qe = lower("SELECT SUM(bytes * 2), MIN(bytes * 2) FROM metrics").await;
-    let NonASAPOp::Aggregate {
-        measures, child, ..
-    } = op(find_aggregate_node(&qe).expect("expected an Aggregate"))
-    else {
-        unreachable!()
-    };
-    assert_eq!(
-        child.schema.fields.len(),
-        1,
-        "the two reducers should share one derived column"
-    );
-    assert_eq!(measures[0].input_cols(), measures[1].input_cols());
-}
-
-// ── Issue #118: multi-level grouping expands into one Aggregate per level ───
-
-/// The branches of the first `Concat` along the single-child spine.
-fn merge_branches(node: &OperatorNode) -> &Vec<Rc<OperatorNode>> {
-    fn find(node: &OperatorNode) -> Option<&Vec<Rc<OperatorNode>>> {
-        match op(node) {
-            NonASAPOp::Concat { children, .. } => Some(children),
-            NonASAPOp::Project { child, .. }
-            | NonASAPOp::Filter { child, .. }
-            | NonASAPOp::Sort { child, .. }
-            | NonASAPOp::Limit { child, .. } => find(child),
-            _ => None,
-        }
-    }
-    find(node).expect("expected a Concat")
-}
-
-/// `(group keys, column names)` of each merged grouping level.
-fn grouping_levels(node: &OperatorNode) -> Vec<(GroupKeys, Vec<String>)> {
-    merge_branches(node)
-        .iter()
-        .map(|b| {
-            let NonASAPOp::Project { child, .. } = op(b) else {
-                panic!("expected a Project per level, got {b:?}");
-            };
-            let NonASAPOp::Aggregate { reduction, .. } = op(child) else {
-                panic!("expected an Aggregate under the Project, got {child:?}");
-            };
-            let names = b.schema.fields.iter().map(|c| c.name.clone()).collect();
-            (reduction.expect_reduce().clone(), names)
-        })
-        .collect()
-}
-
-#[tokio::test]
-async fn rollup_expands_to_one_aggregate_per_prefix() {
-    // ROLLUP(a, b) → (a,b), (a), () — three levels, widest first.
-    let qe =
-        lower("SELECT service, bytes, SUM(latency) FROM metrics GROUP BY ROLLUP(service, bytes)")
-            .await;
-    let levels = grouping_levels(&qe);
-    let keys: Vec<_> = levels.iter().map(|(by, _)| by.clone()).collect();
-    assert_eq!(
-        keys,
-        vec![
-            GroupKeys::by(vec![1, 3]),
-            GroupKeys::by(vec![1]),
-            GroupKeys::none(),
-        ]
-    );
-}
-
-#[tokio::test]
-async fn cube_expands_to_the_power_set() {
-    // CUBE(a, b) → (a,b), (a), (b), () — four levels.
-    let qe =
-        lower("SELECT service, bytes, SUM(latency) FROM metrics GROUP BY CUBE(service, bytes)")
-            .await;
-    assert_eq!(grouping_levels(&qe).len(), 4);
-}
-
-#[tokio::test]
-async fn a_mixed_grouping_set_is_normalized_by_datafusion() {
-    // `GROUP BY g, ROLLUP(d)` arrives as one GroupingSets, not a plain key
-    // alongside a grouping set — so there is only one shape to handle.
-    let qe =
-        lower("SELECT service, bytes, SUM(latency) FROM metrics GROUP BY service, ROLLUP(bytes)")
-            .await;
-    assert_eq!(grouping_levels(&qe).len(), 2);
-}
-
-#[tokio::test]
-async fn omitted_grouping_keys_become_typed_nulls() {
-    // Every level must emit every key — as NULL where the level omits it — or
-    // `Concat` (which takes the first child's schema) would misdescribe the rest.
-    // The null is *cast*: a bare Null literal infers as Float64.
-    let qe = lower("SELECT service, SUM(bytes) FROM metrics GROUP BY ROLLUP(service)").await;
-    let levels = grouping_levels(&qe);
-    assert_eq!(levels.len(), 2);
-    for (_, names) in &levels {
-        assert_eq!(
-            names,
-            &["service".to_string(), "sum(metrics.bytes)".to_string()]
-        );
-    }
-
-    // The `()` level projects `service` as a Utf8 null, not a Float64 one.
-    let schema = &merge_branches(&qe)[1].schema;
-    assert_eq!(schema.fields[0].name, "service");
-    assert_eq!(
-        schema.fields[0].dtype,
-        DataType::Utf8,
-        "the omitted key must keep its declared type"
-    );
-}
-
-#[tokio::test]
-async fn grouping_levels_are_union_compatible() {
-    let qe = lower(
-        "SELECT service, bytes, SUM(latency) FROM metrics GROUP BY GROUPING SETS ((service),(bytes),())",
-    )
-    .await;
-    let shapes: Vec<_> = merge_branches(&qe)
-        .iter()
-        .map(|b| {
-            b.schema
-                .fields
-                .iter()
-                .map(|c| (c.name.clone(), c.dtype.clone()))
-                .collect::<Vec<_>>()
-        })
-        .collect();
-    assert!(
-        shapes.windows(2).all(|w| w[0] == w[1]),
-        "levels disagree: {shapes:?}"
-    );
-}
-
-#[tokio::test]
-async fn grouping_function_is_rejected() {
-    // `__grouping_id` is dropped when the levels are expanded. It is observable
-    // only through `GROUPING(col)`, so dropping it loses nothing representable —
-    // this test is what makes that true.
-    let err = lower_sql(
-        "SELECT service, SUM(bytes), GROUPING(service) FROM metrics GROUP BY ROLLUP(service)",
-        &catalog(),
-        AccuracyTarget::Exact,
-    )
-    .await
-    .expect_err("GROUPING() must be rejected while __grouping_id is dropped");
-    assert!(format!("{err}").contains("grouping"), "got {err}");
-}
-
-#[tokio::test]
-async fn a_non_column_key_inside_a_grouping_set_is_rejected() {
-    // The #110 derived-column machinery covers plain `GROUP BY <expr>`; inside a
-    // grouping set the key also has to be reinstatable as a typed null.
-    let err = lower_sql(
-        "SELECT date_trunc('minute', ts) AS m, SUM(bytes) FROM metrics GROUP BY ROLLUP(m)",
-        &catalog(),
-        AccuracyTarget::Exact,
-    )
-    .await
-    .expect_err("expression key inside ROLLUP must be rejected");
-    assert!(
-        format!("{err}").contains("non-column key inside a multi-level grouping"),
-        "got {err}"
-    );
-}
-
-#[tokio::test]
-async fn multi_level_grouping_composes_with_a_derived_reducer_argument() {
-    // #110's materializing Project sits beneath every level's Aggregate.
-    let qe = lower("SELECT service, SUM(bytes * 8) FROM metrics GROUP BY ROLLUP(service)").await;
-    for b in merge_branches(&qe) {
-        let NonASAPOp::Project { child, .. } = op(b) else {
-            panic!("expected a Project per level");
-        };
-        let NonASAPOp::Aggregate {
-            measures, child, ..
-        } = op(child)
-        else {
-            panic!("expected an Aggregate");
-        };
-        assert!(matches!(
-            measures.as_slice(),
-            [AggIntent::Sum { col: Some(_) }]
-        ));
-        assert!(
-            matches!(op(child), NonASAPOp::Project { .. }),
-            "the derived-column projection should sit under each level"
-        );
-    }
-}
-
-#[tokio::test]
-async fn an_ambiguous_passthrough_column_is_rejected_only_when_projecting() {
-    // A `Project` carries one relation qualifier for all its columns, so `a.k`
-    // and `b.k` cannot both survive it. That only matters once a projection is
-    // inserted: without a derived column the join keys resolve as before.
-    let ok = lower_sql(
-        "SELECT m.service, h.service, SUM(m.bytes) FROM metrics m \
-         JOIN hosts h ON m.service = h.service GROUP BY m.service, h.service",
-        &catalog(),
-        AccuracyTarget::Exact,
-    )
-    .await;
-    assert!(
-        ok.is_ok(),
-        "no derived column ⇒ no projection ⇒ no ambiguity"
-    );
-
-    let err = lower_sql(
-        "SELECT m.service, h.service, SUM(m.bytes * 2) FROM metrics m \
-         JOIN hosts h ON m.service = h.service GROUP BY m.service, h.service",
-        &catalog(),
-        AccuracyTarget::Exact,
-    )
-    .await
-    .expect_err("ambiguous passthrough must be rejected, not silently resolved");
-    assert!(format!("{err}").contains("ambiguous column"), "got {err}");
-}
-
-// ── Issue #111: array_agg is deliberately not an intent (WONTFIX) ───────────
-
-#[tokio::test]
-async fn array_agg_is_deliberately_rejected() {
-    // Not a coverage gap. `AggIntent` exists so the planner can bind a sketch or
-    // a mergeable accumulator per node; `array_agg` pre-aggregates nothing (its
-    // output is O(input rows)), has no bounded-memory approximate form, and its
-    // partial state *is* the data. An `AggIntent::ArrayAgg` would force every
-    // arm of `plan::boundary::realize` — an exhaustive match — to answer
-    // `PassThrough`. Contrast `median`, which is `Quantile { q: 0.5 }` and does
-    // feed the sketch path.
-    //
-    // This test exists so the rejection reads as a decision rather than a gap.
-    let err = lower_sql(
-        "SELECT array_agg(service) FROM metrics",
-        &catalog(),
-        AccuracyTarget::Exact,
-    )
-    .await
-    .expect_err("array_agg must not lower to an intent");
-    assert!(
-        format!("{err}").contains("unsupported aggregate: array_agg"),
-        "expected a clean UnsupportedAggregate, got {err}"
-    );
-}
-
-// ── Issue #225: catalog-driven ClickHouse builtins (countIf, generalizing
-// uniqExact from #221) ───────────────────────────────────────────────────
-
-async fn lower_clickhouse(sql: &str) -> Rc<OperatorNode> {
-    lower_sql_dialect(
-        sql,
-        &catalog(),
-        SqlDialect::ClickhouseSQL,
-        AccuracyTarget::Exact,
-    )
-    .await
-    .unwrap_or_else(|e| panic!("lower failed for {sql:?}: {e}"))
-}
-
-fn temporal_aggregate(node: &OperatorNode) -> (&AggIntent, std::time::Duration, &OperatorNode) {
-    match op(node) {
-        NonASAPOp::Aggregate {
-            reduction: Reduction::PerEntity,
-            measures,
-            child,
-            ..
-        } => {
-            let NonASAPOp::TimeRange { range, child, .. } = op(child) else {
-                panic!("temporal Aggregate must directly wrap TimeRange, got {child:?}");
-            };
-            (&measures[0], *range, child)
-        }
-        NonASAPOp::Project { child, .. } | NonASAPOp::Filter { child, .. } => {
-            temporal_aggregate(child)
-        }
-        other => panic!("expected temporal Aggregate, got {other:?}"),
-    }
-}
-
-#[tokio::test]
-async fn explicit_temporal_aggregates_share_promql_intents_and_timerange() {
-    for (function, expected) in [
-        ("asap_rate", AggIntent::Rate),
-        ("asap_increase", AggIntent::Increase),
-    ] {
-        let sql = format!(
-            "SELECT service, {function}(latency, ts, 300000) AS v \
-             FROM metrics WHERE service = 'api' GROUP BY service"
-        );
-        let qe = lower_clickhouse(&sql).await;
-        let (intent, range, child) = temporal_aggregate(&qe);
-        assert_eq!(intent, &expected);
-        assert_eq!(range, std::time::Duration::from_secs(300));
-        assert!(matches!(op(child), NonASAPOp::Project { child, .. }
-            if matches!(op(child), NonASAPOp::Scan { predicates, .. } if predicates.len() == 1)));
-
-        let NonASAPOp::Project { cols, .. } = op(&qe) else {
-            panic!("SELECT list must remain a Project, got {qe:?}");
-        };
-        assert!(matches!(cols[0].expr, ScalarExpr::Column(2)));
-        assert_eq!(cols[1].alias.as_deref(), Some("v"));
-        assert!(matches!(cols[1].expr, ScalarExpr::Column(1)));
-    }
-}
-
-#[tokio::test]
-async fn temporal_aggregate_rejects_non_timestamp_and_non_positive_window() {
-    for sql in [
-        "SELECT asap_rate(latency, bytes, 300000) FROM metrics",
-        "SELECT asap_rate(latency, ts, 0) FROM metrics",
-        "SELECT asap_rate(latency, ts, bytes) FROM metrics",
-    ] {
-        let err = lower_sql_dialect(
-            sql,
-            &catalog(),
-            SqlDialect::ClickhouseSQL,
-            AccuracyTarget::Exact,
-        )
-        .await
-        .expect_err("invalid temporal arguments must fail closed");
-        assert!(
-            format!("{err}").contains("timestamp argument")
-                || format!("{err}").contains("window_ms"),
-            "unexpected error for {sql}: {err}"
-        );
-    }
-}
-
-#[tokio::test]
-async fn temporal_aggregate_rejects_mixed_reducers() {
-    let err = lower_sql_dialect(
-        "SELECT asap_rate(latency, ts, 300000), sum(bytes) FROM metrics",
-        &catalog(),
-        SqlDialect::ClickhouseSQL,
-        AccuracyTarget::Exact,
-    )
-    .await
-    .expect_err("one child cannot carry temporal and ordinary aggregate semantics");
-    assert!(format!("{err}").contains("cannot share an Aggregate node"));
-}
-
-#[tokio::test]
-async fn last_fails_closed_until_an_executable_summary_exists() {
-    let err = lower_sql_dialect(
-        "SELECT service, asap_last(latency, ts, 300000) FROM metrics GROUP BY service",
-        &catalog(),
-        SqlDialect::ClickhouseSQL,
-        AccuracyTarget::Exact,
-    )
-    .await
-    .expect_err("last must not be advertised without an executable physical summary");
-    assert!(format!("{err}").contains("Invalid function 'asap_last'"));
-}
-
-#[tokio::test]
-async fn temporal_grouping_requires_the_complete_declared_series_identity() {
-    let multi_series = SqlCatalog::new().with_table(
-        "samples",
-        Schema::with_time_index(
-            vec![
-                col("ts", DataType::Timestamp),
-                col("service", DataType::Utf8),
-                col("instance", DataType::Utf8),
-                col("value", DataType::Float64),
-            ],
-            0,
-            vec![vec![0, 1, 2]],
-        ),
-    );
-    for sql in [
-        "SELECT asap_rate(value, ts, 300000) FROM samples",
-        "SELECT service, asap_rate(value, ts, 300000) FROM samples GROUP BY service",
-    ] {
-        let err = lower_sql_dialect(
-            sql,
-            &multi_series,
-            SqlDialect::ClickhouseSQL,
-            AccuracyTarget::Exact,
-        )
-        .await
-        .expect_err("partial identity must not merge counter series");
-        assert!(format!("{err}").contains("declared series identity"));
-    }
-
-    lower_sql_dialect(
-        "SELECT service, instance, asap_rate(value, ts, 300000) \
-         FROM samples GROUP BY service, instance",
-        &multi_series,
-        SqlDialect::ClickhouseSQL,
-        AccuracyTarget::Exact,
-    )
-    .await
-    .expect("the complete declared series identity is safe");
-
-    let row_id_only = SqlCatalog::new().with_table(
-        "samples",
-        Schema::with_time_index(
-            vec![
-                col("ts", DataType::Timestamp),
-                col("service", DataType::Utf8),
-                col("value", DataType::Float64),
-            ],
-            0,
-            vec![vec![1]],
-        ),
-    );
-    lower_sql_dialect(
-        "SELECT service, asap_rate(value, ts, 300000) FROM samples GROUP BY service",
-        &row_id_only,
-        SqlDialect::ClickhouseSQL,
-        AccuracyTarget::Exact,
-    )
-    .await
-    .expect_err("a row key without time does not prove a series identity");
-}
-
-#[tokio::test]
-async fn temporal_grouping_rejects_value_time_and_duplicate_resolved_columns() {
-    for sql in [
-        "SELECT asap_rate(latency, ts, 300000) FROM metrics GROUP BY ts",
-        "SELECT asap_rate(latency, ts, 300000) FROM metrics GROUP BY latency",
-        "SELECT m.service, asap_rate(m.latency, m.ts, 300000) \
-         FROM metrics m GROUP BY m.service, service",
-    ] {
-        let err = lower_sql_dialect(
-            sql,
-            &catalog(),
-            SqlDialect::ClickhouseSQL,
-            AccuracyTarget::Exact,
-        )
-        .await
-        .expect_err("unsafe or duplicate resolved grouping must fail closed");
-        let message = format!("{err}");
-        assert!(
-            message.contains("timestamp or value")
-                || message.contains("same resolved column more than once"),
-            "unexpected error for {sql}: {message}"
-        );
-    }
-}
-
-#[tokio::test]
-async fn qualified_columns_are_validated_by_resolved_identity() {
-    let qe = lower_clickhouse(
-        "SELECT m.service, asap_increase(m.latency, m.ts, 300000) AS v \
-         FROM metrics AS m GROUP BY m.service",
-    )
-    .await;
-    let (intent, range, _) = temporal_aggregate(&qe);
-    assert_eq!(intent, &AggIntent::Increase);
-    assert_eq!(range, std::time::Duration::from_secs(300));
-}
-
-#[tokio::test]
-async fn project_filter_and_outer_aggregate_preserve_temporal_child() {
-    let qe = lower_clickhouse(
-        "SELECT max(v) FROM (\
-           SELECT service, asap_rate(latency, ts, 300000) AS v \
-           FROM metrics WHERE bytes > 0 GROUP BY service\
-         ) r WHERE v >= 0",
-    )
-    .await;
-    let NonASAPOp::Project { child, .. } = op(&qe) else {
-        panic!("expected outer SELECT Project, got {qe:?}");
-    };
-    let NonASAPOp::Aggregate {
-        reduction: Reduction::Reduce(_),
-        measures,
-        child,
-        ..
-    } = op(child)
-    else {
-        panic!("expected outer Aggregate, got {child:?}");
-    };
-    assert!(matches!(measures.as_slice(), [AggIntent::Max { .. }]));
-    let NonASAPOp::Filter { child, .. } = op(child) else {
-        panic!("derived-table WHERE must remain above the inner query, got {child:?}");
-    };
-    let (intent, range, _) = temporal_aggregate(child);
-    assert_eq!(intent, &AggIntent::Rate);
-    assert_eq!(range, std::time::Duration::from_secs(300));
-}
-
-#[tokio::test]
-async fn count_if_lowers_to_a_sum_over_a_derived_indicator_column() {
-    // ClickHouse's `countIf(cond)` has no DataFusion equivalent at all, so it
-    // goes through the same stub-UDAF + catalog-driven `FunctionRewrite`
-    // mechanism `uniqExact` (#221) does — rewritten, before `lower_agg_intent`
-    // ever runs, to `sum(CASE WHEN cond THEN 1 ELSE 0 END)`. A per-measure
-    // filter (#466) could express it as a filtered `Count` now; that move is
-    // a follow-up, so the indicator sum is still the shape to expect.
-    let qe = lower_clickhouse("SELECT countIf(bytes > 100) AS big FROM metrics").await;
-    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate");
-    assert!(by.is_empty());
-    assert!(
-        matches!(measures.as_slice(), [AggIntent::Sum { col: Some(_) }]),
-        "expected a Sum bound to the derived indicator column, got {measures:?}"
-    );
-    let (_, materialized) = reducer_input_names(&qe);
-    assert!(
-        materialized,
-        "the indicator expression must be materialized in a Project beneath the Aggregate"
-    );
-}
-
-#[tokio::test]
-async fn two_count_ifs_with_different_conditions_stay_distinct_reducers() {
-    // The corpus pattern (`countIf(operation = 'A'), countIf(operation = 'W')`
-    // in one GROUP BY) needs each call's own condition to survive as its own
-    // derived column, not collapse onto a shared one.
-    let qe = lower_clickhouse(
-        "SELECT service, countIf(bytes > 100) AS big, countIf(bytes <= 100) AS small \
-         FROM metrics GROUP BY service",
-    )
-    .await;
-    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate");
-    assert_eq!(*by, GroupKeys::by(vec![0]));
-    assert!(
-        matches!(
-            measures.as_slice(),
-            [
-                AggIntent::Sum { col: Some(a) },
-                AggIntent::Sum { col: Some(b) }
-            ] if a != b
-        ),
-        "expected two distinct Sum reducers, got {measures:?}"
-    );
-}
-
-#[tokio::test]
-async fn count_if_composes_with_group_by() {
-    let qe = lower_clickhouse(
-        "SELECT service, countIf(bytes > 100) AS big FROM metrics GROUP BY service",
-    )
-    .await;
-    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate");
-    assert_eq!(*by, GroupKeys::by(vec![0]));
-    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
-}
-
-// ── Issue #232: argMax/argMin -- AggIntent::Extension, not a first-class
-// core variant. A repo-wide search (PromQL front end, other SQL dialects,
-// docs) turned up no second deployment model wanting this two-column,
-// row-selecting shape, so per `AggIntent::Extension`'s own "core only grows
-// for intents ≥2 deployment models actually use" bar, it stays an opaque
-// `Extension` rather than a new `ArgMax`/`ArgMin` core variant. Unlike
-// `countIf`/`uniqExact`, there is no native DataFusion aggregate shape to
-// rewrite to (`RewriteKind::PassThrough`) -- `lower_agg_intent` builds the
-// `AggIntent` directly from the ClickHouse name. ─────────────────────────
-
-#[tokio::test]
-async fn arg_max_lowers_to_an_extension_intent() {
-    // No existing `AggIntent` reducer fits: every one folds one column to a
-    // value derived from itself, while `argMax(arg, val)` returns a
-    // *different* column's value, selected by which row maximizes a second.
-    let qe = lower_clickhouse(
-        "SELECT service, argMax(service, latency) AS busiest FROM metrics GROUP BY service",
-    )
-    .await;
-    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate");
-    assert_eq!(
-        *by,
-        GroupKeys::by(vec![1]),
-        "grouped by `service` (schema index 1)"
-    );
-    assert!(
-        matches!(
-            measures.as_slice(),
-            [AggIntent::Extension { ext_kind, .. }] if ext_kind == "arg_max"
-        ),
-        "expected Extension {{ ext_kind: \"arg_max\", .. }}, got {measures:?}"
-    );
-}
-
-#[tokio::test]
-async fn arg_min_lowers_to_its_own_extension_kind() {
-    let qe = lower_clickhouse("SELECT argMin(service, latency) FROM metrics").await;
-    let (by, measures) = find_aggregate(&qe).expect("expected an Aggregate");
-    assert!(by.is_empty());
-    assert!(
-        matches!(
-            measures.as_slice(),
-            [AggIntent::Extension { ext_kind, .. }] if ext_kind == "arg_min"
-        ),
-        "expected Extension {{ ext_kind: \"arg_min\", .. }}, got {measures:?}"
-    );
-}
-
-#[tokio::test]
-async fn arg_max_payload_preserves_both_column_names() {
-    // Core never resolves an `Extension`'s payload, so both columns are kept
-    // as validated bare-column `ColumnRef`s in `payload`, not run through
-    // positional `ColumnId` binding -- see `lower_arg_selector`'s doc.
-    let qe = lower_clickhouse("SELECT argMax(service, latency) AS m FROM metrics").await;
-    let (_, measures) = find_aggregate(&qe).expect("expected an Aggregate");
-    let AggIntent::Extension { payload, .. } = &measures[0] else {
-        panic!("expected an Extension intent, got {:?}", measures[0]);
-    };
-    let named = |key: &str| {
-        payload
-            .get(key)
-            .and_then(|c| c.get("Named"))
-            .and_then(|n| n.as_str())
-            .map(str::to_string)
-    };
-    assert_eq!(named("arg_col"), Some("service".to_string()));
-    assert_eq!(named("val_col"), Some("latency".to_string()));
-}
-
-#[tokio::test]
-async fn arg_max_rejects_a_non_column_argument() {
-    // Same "bare column only" rule as every other reducer (`reducer_col`,
-    // issue #115) -- an expression argument is rejected, not silently
-    // dropped or materialized into the wrong column.
-    let err = lower_sql_dialect(
-        "SELECT argMax(service, latency * 2) FROM metrics",
-        &catalog(),
-        SqlDialect::ClickhouseSQL,
-        AccuracyTarget::Exact,
-    )
-    .await
-    .expect_err("argMax over a non-column expression must be rejected");
-    assert!(
-        format!("{err}").contains("non-column expression"),
-        "got {err}"
-    );
-}
-
-// ── Issue #267: lagInFrame/leadInFrame get distinct WindowFuncKind variants,
-// not conflated with ANSI Lag/Lead ──────────────────────────────────────────
-
-#[tokio::test]
-async fn lag_in_frame_lowers_to_its_own_kind_not_lag() {
-    let qe = lower_clickhouse(
-        "SELECT service, lagInFrame(bytes) OVER (PARTITION BY service ORDER BY ts) \
-         FROM metrics",
-    )
-    .await;
-    let win = find_windowfunc(&qe).expect("expected a SQLWindowFunc node");
-    let NonASAPOp::SQLWindowFunc { func, args, .. } = op(win) else {
-        unreachable!();
-    };
-    assert_eq!(*func, WindowFuncKind::LagInFrame);
-    assert_eq!(
-        args,
-        &vec![ScalarExpr::Column(3)],
-        "lagInFrame(bytes) → arg col 3"
-    );
-}
-
-#[tokio::test]
-async fn lead_in_frame_lowers_to_its_own_kind_not_lead() {
-    let qe = lower_clickhouse(
-        "SELECT service, leadInFrame(bytes) OVER (PARTITION BY service ORDER BY ts) \
-         FROM metrics",
-    )
-    .await;
-    let win = find_windowfunc(&qe).expect("expected a SQLWindowFunc node");
-    let NonASAPOp::SQLWindowFunc { func, .. } = op(win) else {
-        unreachable!();
-    };
-    assert_eq!(*func, WindowFuncKind::LeadInFrame);
-}
-
-/// Issue #184: `NOW()` in a predicate must lower to the timestamp-typed
-/// `CurrentTimestamp` leaf, not the semantically-opaque function catch-all or
-/// PromQL's Float64 Unix-seconds `EvalTimestamp`.
-#[tokio::test]
-async fn now_in_predicate_lowers_to_current_timestamp() {
-    // WHERE folds onto Scan.predicates (no explicit Filter node).
-    let qe = lower("SELECT * FROM metrics WHERE ts < NOW()").await;
-    let NonASAPOp::Project { child, .. } = op(&qe) else {
-        panic!("expected Project at root, got {qe:?}");
-    };
-    let NonASAPOp::Scan { predicates, .. } = op(child) else {
-        panic!("expected Scan under the projection, got {child:?}");
-    };
-    assert_eq!(predicates.len(), 1);
-    assert!(
-        matches!(&predicates[0].0, ScalarExpr::Compare { right, .. }
-            if matches!(right.as_ref(), ScalarExpr::Cast { expr, to: DataType::Timestamp, .. } if matches!(expr.as_ref(), ScalarExpr::CurrentTimestamp))),
-        "NOW() must lower to CurrentTimestamp, got {:?}",
-        predicates[0].0
-    );
-}
-
-/// Same for ClickHouse's `now()`, since #184 was raised specifically against
-/// the ClickHouse dialect.
-#[tokio::test]
-async fn clickhouse_now_in_predicate_lowers_to_current_timestamp() {
-    let qe = lower_clickhouse("SELECT * FROM metrics WHERE ts < now()").await;
-    let NonASAPOp::Project { child, .. } = op(&qe) else {
-        panic!("expected Project at root, got {qe:?}");
-    };
-    let NonASAPOp::Scan { predicates, .. } = op(child) else {
-        panic!("expected Scan under the projection, got {child:?}");
-    };
-    assert_eq!(predicates.len(), 1);
-    assert!(
-        matches!(&predicates[0].0, ScalarExpr::Compare { right, .. }
-            if matches!(right.as_ref(), ScalarExpr::Cast { expr, to: DataType::Timestamp, .. } if matches!(expr.as_ref(), ScalarExpr::CurrentTimestamp))),
-        "now() must lower to CurrentTimestamp, got {:?}",
-        predicates[0].0
-    );
-}
-
-#[tokio::test]
-async fn current_timestamp_lowers_to_typed_current_timestamp_leaf() {
-    let qe = lower("SELECT CURRENT_TIMESTAMP FROM metrics").await;
-    let NonASAPOp::Project { cols, child, .. } = op(&qe) else {
-        panic!("expected Project at root, got {qe:?}");
-    };
-    assert!(matches!(&cols[0].expr, ScalarExpr::CurrentTimestamp));
-    let (dtype, _) = cols[0]
-        .expr
-        .scalar_type(&child.schema)
-        .expect("timestamp type");
-    assert_eq!(dtype, DataType::Timestamp);
-    assert_eq!(qe.schema.fields[0].dtype, DataType::Timestamp);
-}
-
-// A `count` over a non-null input is a plain row count; over a nullable
-// input it keeps SQL's NULL-skipping as the measure's own filter (#466), and
-// only the multi-level grouping path, which cannot carry one, still rejects it.
-#[tokio::test]
-async fn count_null_semantics_become_a_measure_filter() {
-    let catalog = SqlCatalog::new().with_table(
-        "samples",
-        Schema::new(vec![
-            Field::plain("nullable_value", DataType::Float64, true),
-            Field::plain("value", DataType::Float64, false),
-        ]),
-    );
-    for sql in [
-        "SELECT count(*) FROM samples",
-        "SELECT count(1) FROM samples",
-        "SELECT count(value) FROM samples",
-        "SELECT count(value + 1) FROM samples",
-    ] {
-        let qe = lower_sql(sql, &catalog, AccuracyTarget::Exact)
-            .await
-            .unwrap_or_else(|error| panic!("{sql}: {error}"));
-        assert!(
-            aggregate_filters(&qe).is_empty(),
-            "{sql}: unfiltered row count"
-        );
-    }
-    for sql in [
-        "SELECT count(nullable_value) FROM samples",
-        "SELECT count(NULL) FROM samples",
-        "SELECT count(nullable_value + 1) FROM samples",
-    ] {
-        let qe = lower_sql(sql, &catalog, AccuracyTarget::Exact)
-            .await
-            .unwrap_or_else(|error| panic!("{sql}: {error}"));
-        let [Some(Predicate(cond))] = aggregate_filters(&qe) else {
-            panic!(
-                "{sql}: expected one filtered Count, got {:?}",
-                aggregate_filters(&qe)
-            );
-        };
-        assert!(matches!(cond, ScalarExpr::IsNotNull(_)), "{sql}: {cond:?}");
-    }
-    // Only the second measure is filtered.
-    let qe = lower_sql(
-        "SELECT count(*), count(nullable_value) FROM samples",
-        &catalog,
-        AccuracyTarget::Exact,
-    )
-    .await
-    .unwrap();
-    assert!(matches!(aggregate_filters(&qe), [None, Some(_)]));
-    let error = lower_sql(
-        "SELECT count(nullable_value) FROM samples GROUP BY ROLLUP(value)",
-        &catalog,
-        AccuracyTarget::Exact,
-    )
-    .await
-    .unwrap_err();
-    assert!(
-        matches!(error, LoweringError::UnsupportedFeature(_)),
-        "{error}"
-    );
-}
-
-/// A native SQL map grouping key retains its typed key/value schema.
-#[tokio::test]
-async fn grouped_map_column_preserves_map_type() {
-    let map = DataType::Map {
-        key: Box::new(DataType::Utf8),
-        value: Box::new(DataType::Utf8),
-        value_nullable: false,
-    };
-    let catalog = SqlCatalog::new().with_table(
-        "raw_samples",
-        Schema::new(vec![
-            col("labels", map.clone()),
-            col("value", DataType::Float64),
-        ]),
-    );
-    let query = lower_sql_dialect(
-        "SELECT labels, max(value) AS value FROM raw_samples GROUP BY labels ORDER BY labels",
-        &catalog,
-        SqlDialect::ClickhouseSQL,
-        AccuracyTarget::Exact,
-    )
-    .await
-    .unwrap();
-    assert_eq!(query.schema.fields[0].dtype, map);
-}
-
-#[tokio::test]
-async fn clickhouse_modulo_uses_native_arithmetic_types_and_nullability() {
-    let catalog = SqlCatalog::new().with_table(
-        "numbers",
-        Schema::new(vec![
-            Field::plain("i", DataType::Int64, false),
-            Field::plain("n", DataType::Int64, true),
-            Field::plain("f", DataType::Float64, false),
-        ]),
-    );
-    for (call, native) in [
-        ("modulo(i, 3)", "i % 3"),
-        ("modulo(n, -3)", "n % -3"),
-        ("modulo(f, 2.5)", "f % 2.5"),
-        ("modulo(-7, 3)", "-7 % 3"),
-        ("modulo(i, 0)", "i % 0"),
-        ("modulo(modulo(i, 5), 2)", "(i % 5) % 2"),
-    ] {
-        let function = lower_sql_dialect(
-            &format!("SELECT {call} AS value FROM numbers"),
-            &catalog,
-            SqlDialect::ClickhouseSQL,
-            AccuracyTarget::Exact,
-        )
-        .await
-        .unwrap();
-        let operator = lower_sql_dialect(
-            &format!("SELECT {native} AS value FROM numbers"),
-            &catalog,
-            SqlDialect::ClickhouseSQL,
-            AccuracyTarget::Exact,
-        )
-        .await
-        .unwrap();
-        assert_eq!(function, operator, "{call}");
-        assert_eq!(function.schema, operator.schema);
-    }
-    let nullable = lower_sql_dialect(
-        "SELECT modulo(n, 3) AS value FROM numbers",
-        &catalog,
-        SqlDialect::ClickhouseSQL,
-        AccuracyTarget::Exact,
-    )
-    .await
-    .unwrap()
-    .schema
-    .clone();
-    assert_eq!(nullable.fields[0].dtype, DataType::Int64);
-    assert!(nullable.fields[0].nullable);
-}
-
-#[tokio::test]
-async fn original_o11y_map_queries_lower_with_typed_results() {
-    let catalog = SqlCatalog::new().with_table(
-        "raw_samples",
-        Schema::new(vec![
-            Field::plain("metric", DataType::Utf8, false),
-            Field::plain("ts_ms", DataType::Int64, false),
-            Field::plain("value", DataType::Float64, false),
-            Field::plain(
-                "labels",
-                DataType::Map {
-                    key: Box::new(DataType::Utf8),
-                    value: Box::new(DataType::Utf8),
-                    value_nullable: false,
-                },
-                false,
-            ),
-        ]),
-    );
-    for sql in [
-        include_str!("data/o11y_q10.sql"),
-        include_str!("data/o11y_q27.sql"),
-        include_str!("data/o11y_q07.sql"),
-        include_str!("data/o11y_q09.sql"),
-        include_str!("data/o11y_q12.sql"),
-    ] {
-        let query = lower_sql_dialect(
-            sql,
-            &catalog,
-            SqlDialect::ClickhouseSQL,
-            AccuracyTarget::Exact,
-        )
-        .await
-        .unwrap_or_else(|e| panic!("{sql}: {e}"));
-        let schema = &query.schema;
-        assert!(
-            schema
-                .fields
-                .iter()
-                .any(|column| matches!(column.dtype, FieldDataType::Plain(DataType::Map { .. }))),
-            "{schema:?}"
-        );
-    }
-}
-
-#[tokio::test]
-async fn clickhouse_modulo_preserves_projection_names_and_outer_references() {
-    for (sql, name) in [
-        ("SELECT modulo(bytes, 3) FROM metrics", "modulo(bytes, 3)"),
-        (
-            "SELECT modulo(bytes, 3) AS remainder FROM metrics",
-            "remainder",
-        ),
-        (
-            "SELECT \"modulo(bytes, 3)\" FROM (SELECT modulo(bytes, 3) FROM metrics) t",
-            "modulo(bytes, 3)",
-        ),
-    ] {
-        let query = lower_sql_dialect(
-            sql,
-            &catalog(),
-            SqlDialect::ClickhouseSQL,
-            AccuracyTarget::Exact,
-        )
-        .await
-        .unwrap();
-        assert_eq!(query.schema.fields[0].name, name);
-    }
-}
-
-#[tokio::test]
-async fn clickhouse_map_access_keeps_generated_names_and_rejects_variant_coercion() {
-    let catalog = SqlCatalog::new().with_table(
-        "t",
-        Schema::new(vec![
-            Field::plain(
-                "labels",
-                DataType::Map {
-                    key: Box::new(DataType::Utf8),
-                    value: Box::new(DataType::Utf8),
-                    value_nullable: false,
-                },
-                false,
-            ),
-            Field::plain("integer", DataType::Int64, false),
-            Field::plain("floating", DataType::Float64, false),
-        ]),
-    );
-    let query = lower_sql_dialect(
-        "SELECT labels['job'] FROM t",
-        &catalog,
-        SqlDialect::ClickhouseSQL,
-        AccuracyTarget::Exact,
-    )
-    .await
-    .unwrap();
-    let output = &query.schema;
-    assert_eq!(output.fields[0].name, "arrayElement(labels, 'job')");
-    assert_eq!(output.fields[0].dtype, DataType::Utf8);
-    assert!(!output.fields[0].nullable);
-    assert!(lower_sql_dialect(
-        "SELECT map()['a'] FROM t",
-        &catalog,
-        SqlDialect::ClickhouseSQL,
-        AccuracyTarget::Exact,
-    )
-    .await
-    .is_err());
-    assert!(lower_sql_dialect(
-        "SELECT map('a', integer, 'b', floating) FROM t",
-        &catalog,
-        SqlDialect::ClickhouseSQL,
-        AccuracyTarget::Exact
-    )
-    .await
-    .is_err());
-}
-
-#[tokio::test]
-async fn arg_selector_result_schema_tracks_selected_argument() {
-    let catalog = SqlCatalog::new().with_table(
-        "t",
-        Schema::new(vec![
-            Field::plain("v", DataType::Float64, false),
-            Field::plain("text", DataType::Utf8, true),
-            Field::plain("ts", DataType::Int64, true),
-        ]),
-    );
-    for (sql, dtype, nullable) in [
-        (
-            "SELECT argMax(v, ts) AS value FROM t",
-            DataType::Float64,
-            false,
-        ),
-        (
-            "SELECT argMin(text, ts) AS value FROM t",
-            DataType::Utf8,
-            true,
-        ),
-    ] {
-        let query = lower_sql_dialect(
-            sql,
-            &catalog,
-            SqlDialect::ClickhouseSQL,
-            AccuracyTarget::Exact,
-        )
-        .await
-        .unwrap();
-        let schema = &query.schema;
-        assert_eq!(schema.fields[0].dtype, dtype);
-        assert_eq!(schema.fields[0].nullable, nullable);
-    }
-}
-
-#[tokio::test]
-async fn clickhouse_list_element_uses_canonical_typed_access() {
-    let catalog = SqlCatalog::new().with_table(
-        "t",
-        Schema::new(vec![
-            Field::plain(
-                "samples",
-                DataType::List {
-                    element: Box::new(Field::new("item", DataType::Int64, false)),
-                },
-                false,
-            ),
-            Field::plain("index", DataType::Int64, true),
-        ]),
-    );
-    for (sql, nullable) in [
-        ("SELECT samples[1] AS selected FROM t", false),
-        ("SELECT arrayElement(samples, -1) AS selected FROM t", false),
-        ("SELECT samples[index] AS selected FROM t", true),
-    ] {
-        let query = lower_sql_dialect(
-            sql,
-            &catalog,
-            SqlDialect::ClickhouseSQL,
-            AccuracyTarget::Exact,
-        )
-        .await
-        .unwrap();
-        let output = &query.schema;
-        assert_eq!(output.fields[0].dtype, DataType::Int64);
-        assert_eq!(output.fields[0].nullable, nullable);
-        let serialized = serde_json::to_string(&query).unwrap();
-        assert!(serialized.contains("asap_element_access"), "{serialized}");
-    }
-    for sql in ["SELECT samples[0] FROM t", "SELECT samples['bad'] FROM t"] {
-        assert!(
-            lower_sql_dialect(
-                sql,
-                &catalog,
-                SqlDialect::ClickhouseSQL,
-                AccuracyTarget::Exact
-            )
-            .await
-            .is_err(),
-            "{sql}"
-        );
-    }
-}
-
-#[tokio::test]
-async fn clickhouse_tuple_element_preserves_declared_field_metadata() {
-    let catalog = SqlCatalog::new().with_table(
-        "t",
-        Schema::new(vec![
-            Field::plain(
-                "sample",
-                DataType::Struct {
-                    fields: vec![
-                        Field::new("time", DataType::Int64, false),
-                        Field::new("value", DataType::Float64, true),
-                    ],
-                },
-                false,
-            ),
-            Field::plain("index", DataType::Int64, false),
-        ]),
-    );
-    for (sql, dtype, nullable) in [
-        (
-            "SELECT tupleElement(sample, 1) AS chosen FROM t",
-            DataType::Int64,
-            false,
-        ),
-        (
-            "SELECT tupleElement(sample, 'value') AS chosen FROM t",
-            DataType::Float64,
-            true,
-        ),
-    ] {
-        let query = lower_sql_dialect(
-            sql,
-            &catalog,
-            SqlDialect::ClickhouseSQL,
-            AccuracyTarget::Exact,
-        )
-        .await
-        .unwrap();
-        let output = &query.schema;
-        assert_eq!(output.fields[0].dtype, dtype);
-        assert_eq!(output.fields[0].nullable, nullable);
-        assert!(serde_json::to_string(&query)
-            .unwrap()
-            .contains("asap_struct_field"));
-    }
-    for selector in ["0", "-1", "3", "'missing'", "index"] {
-        let sql = format!("SELECT tupleElement(sample, {selector}) FROM t");
-        assert!(
-            lower_sql_dialect(
-                &sql,
-                &catalog,
-                SqlDialect::ClickhouseSQL,
-                AccuracyTarget::Exact
-            )
-            .await
-            .is_err(),
-            "{sql}"
-        );
-    }
-}
-
-/// Correlation lowers to a nullable numeric result instead of UnsupportedAggregate.
-#[tokio::test]
-async fn corr_result_is_nullable_float() {
-    let query = lower("SELECT corr(latency, bytes) AS correlation FROM metrics").await;
-    let schema = &query.schema;
-    assert_eq!(schema.fields[0].name, "correlation");
-    assert_eq!(schema.fields[0].dtype, DataType::Float64);
-    assert!(schema.fields[0].nullable);
-}
-
-// A multi-column DISTINCT counts tuples; one column stays the single-column
-// intent, so neither form can be mistaken for the other downstream.
-#[tokio::test]
-async fn composite_distinct_counts_tuples() {
-    let cat = SqlCatalog::new().with_table(
-        "t",
-        Schema::new(vec![
-            Field::plain("a", DataType::Int64, false),
-            Field::plain("b", DataType::Int64, false),
-        ]),
-    );
-    let composite = lower_sql(
-        "SELECT COUNT(DISTINCT a, b) FROM t",
-        &cat,
-        AccuracyTarget::Exact,
-    )
-    .await
-    .unwrap();
-    let NonASAPOp::Aggregate { measures, .. } =
-        op(find_aggregate_node(&composite).expect("expected an Aggregate"))
-    else {
-        unreachable!()
-    };
-    assert!(
-        matches!(measures.as_slice(), [AggIntent::Cardinality { cols, .. }] if cols == &[0, 1]),
-        "{measures:?}"
-    );
-
-    let single = lower_sql(
-        "SELECT COUNT(DISTINCT a) FROM t",
-        &cat,
-        AccuracyTarget::Exact,
-    )
-    .await
-    .unwrap();
-    let NonASAPOp::Aggregate { measures, .. } =
-        op(find_aggregate_node(&single).expect("expected an Aggregate"))
-    else {
-        unreachable!()
-    };
-    assert!(
-        matches!(measures.as_slice(), [AggIntent::Cardinality { cols, .. }] if cols == &[0]),
-        "{measures:?}"
-    );
-}
-
-// An expression argument has no column identity to hash, so it is rejected
-// rather than silently reduced over a probe column.
-#[tokio::test]
-async fn composite_distinct_rejects_expression_arguments() {
-    let cat = SqlCatalog::new().with_table(
-        "t",
-        Schema::new(vec![
-            Field::plain("a", DataType::Int64, false),
-            Field::plain("b", DataType::Int64, false),
-        ]),
-    );
-    let error = lower_sql(
-        "SELECT COUNT(DISTINCT a, b + 1) FROM t",
-        &cat,
-        AccuracyTarget::Exact,
-    )
-    .await
-    .unwrap_err();
-    assert!(
-        matches!(&error, LoweringError::UnsupportedAggregate(reason)
-            if reason.contains("non-column expression")),
-        "{error}"
-    );
-}
-
-// DISTINCT inputs survive projections introduced by sibling aggregates.
-#[tokio::test]
-async fn distinct_with_derived_sibling() {
-    let catalog = SqlCatalog::new().with_table(
-        "t",
-        Schema::new(vec![
-            Field::plain("a", DataType::Int64, false),
-            Field::plain("b", DataType::Int64, false),
-        ]),
-    );
-    for sql in [
-        "SELECT count(DISTINCT a), sum(b + 1) FROM t",
-        "SELECT count(DISTINCT a, b), sum(b + 1) FROM t",
-        "SELECT count(DISTINCT a, b), corr(a,b) FROM t",
-    ] {
-        let result = lower_sql(sql, &catalog, AccuracyTarget::Exact).await;
-        assert!(result.is_ok(), "{sql}: {result:?}");
-    }
-}
-
-// ── Issue #466: per-measure FILTER predicates ─────────────────────────────────
-
-/// The first `Aggregate`'s `filters`, positional against its child.
-fn aggregate_filters(qe: &OperatorNode) -> &[Option<Predicate>] {
-    let Some(NonASAPOp::Aggregate { filters, .. }) =
-        find_aggregate_node(qe).map(|n| n.expect_non_asap())
-    else {
-        panic!("expected an Aggregate, got {qe:?}");
-    };
-    filters
-}
-
-// The motivating query: one scan, one grouping, one conditional count next to
-// a plain sum — a single `Aggregate` whose Count carries the condition, with no
-// `Join` and no derived column for the `CASE`.
-#[tokio::test]
-async fn conditional_count_lowers_to_a_filtered_measure() {
-    let qe = lower(
-        "SELECT service, count(CASE WHEN latency > 1.0 THEN 1 END), sum(bytes) \
-         FROM metrics GROUP BY service",
-    )
-    .await;
-    assert!(find_join(&qe).is_none(), "no join: {qe:?}");
-    let (by, measures) = find_aggregate(&qe).unwrap();
-    assert_eq!(by.keys(), &[1]);
-    assert!(
-        matches!(
-            measures.as_slice(),
-            [AggIntent::Count { .. }, AggIntent::Sum { col: Some(3) }]
-        ),
-        "{measures:?}"
-    );
-    let [Some(Predicate(cond)), None] = aggregate_filters(&qe) else {
-        panic!("expected [Some, None], got {:?}", aggregate_filters(&qe));
-    };
-    assert!(
-        matches!(cond, ScalarExpr::Compare { left, op: CompareOpKind::Gt, .. }
-            if matches!(left.as_ref(), ScalarExpr::Column(2))),
-        "latency > 1.0 against the scan, got {cond:?}"
-    );
-    let Some(NonASAPOp::Aggregate { child, .. }) =
-        find_aggregate_node(&qe).map(|n| n.expect_non_asap())
-    else {
-        unreachable!()
-    };
-    assert!(
-        matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }),
-        "{child:?}"
-    );
-}
-
-// `FILTER (WHERE …)` parses under the DataFusion dialect and lands on exactly
-// the measure it annotates.
-#[tokio::test]
-async fn filter_clause_lowers_to_a_measure_filter() {
-    let qe = lower("SELECT sum(bytes) FILTER (WHERE service = 'a'), count(*) FROM metrics").await;
-    let [Some(Predicate(cond)), None] = aggregate_filters(&qe) else {
-        panic!("expected [Some, None], got {:?}", aggregate_filters(&qe));
-    };
-    assert!(
-        matches!(cond, ScalarExpr::Compare { left, op: CompareOpKind::Eq, right, .. }
-            if matches!(left.as_ref(), ScalarExpr::Column(1))
-                && matches!(right.as_ref(), ScalarExpr::Literal(ScalarValue::Utf8(s)) if s == "a")),
-        "{cond:?}"
-    );
-}
-
-// SQL `count(expr)` skips NULLs; canonical `Count` counts rows and never sees
-// `expr`, so a nullable argument becomes the measure filter `expr IS NOT NULL`
-// instead of being rejected (the pre-#466 behavior) or silently over-counted.
-#[tokio::test]
-async fn count_of_a_nullable_expression_filters_nulls() {
-    let qe = lower("SELECT count(nullif(bytes, 0)) FROM metrics").await;
-    let [Some(Predicate(cond))] = aggregate_filters(&qe) else {
-        panic!("expected [Some], got {:?}", aggregate_filters(&qe));
-    };
-    assert!(matches!(cond, ScalarExpr::IsNotNull(_)), "{cond:?}");
-    assert!(
-        matches!(
-            find_aggregate(&qe).unwrap().1.as_slice(),
-            [AggIntent::Count { .. }]
-        ),
-        "still a row count"
-    );
-}
-
-// The columns a measure filter reads must survive the derived-column
-// `Project` a reducer expression inserts beneath the aggregate.
-#[tokio::test]
-async fn measure_filter_columns_survive_a_derived_column_projection() {
-    let qe = lower("SELECT sum(bytes * 2) FILTER (WHERE latency > 1.0) FROM metrics").await;
-    let Some(NonASAPOp::Aggregate { child, .. }) =
-        find_aggregate_node(&qe).map(|n| n.expect_non_asap())
-    else {
-        unreachable!()
-    };
-    assert!(
-        matches!(child.expect_non_asap(), NonASAPOp::Project { .. }),
-        "{child:?}"
-    );
-    let [Some(Predicate(cond))] = aggregate_filters(&qe) else {
-        panic!("expected [Some], got {:?}", aggregate_filters(&qe));
-    };
-    let ScalarExpr::Compare { left, .. } = cond else {
-        panic!("{cond:?}");
-    };
-    let ScalarExpr::Column(id) = left.as_ref() else {
-        panic!("{left:?}");
-    };
-    assert_eq!(child.schema.fields[*id].name, "latency");
-}
-
-// `GROUP BY ROLLUP` fans one measure list out into one `Aggregate` per level;
-// a filtered measure there is rejected rather than silently unfiltered.
-#[tokio::test]
-async fn measure_filter_inside_a_rollup_is_rejected() {
-    let err = lower_sql(
-        "SELECT service, count(*) FILTER (WHERE latency > 1.0) FROM metrics GROUP BY ROLLUP(service)",
-        &catalog(),
-        AccuracyTarget::Exact,
-    )
-    .await
-    .unwrap_err();
-    assert!(matches!(err, LoweringError::UnsupportedFeature(_)), "{err}");
-}
diff --git a/crates/integration-tests/Cargo.toml b/crates/integration-tests/Cargo.toml
index 5a5de9902..afa7559b4 100644
--- a/crates/integration-tests/Cargo.toml
+++ b/crates/integration-tests/Cargo.toml
@@ -10,6 +10,7 @@ asap-frontend-sql = { path = "../frontend-sql" }
 asap-aware-mapping = { path = "../asap-aware-mapping" }
 
 [dev-dependencies]
+asap-planner = { path = "../planner" }
 asap_sketchlib = { workspace = true }
 serde_json = "1"
 tokio = { version = "1", features = ["rt", "macros", "rt-multi-thread"] }
diff --git a/crates/integration-tests/src/lib.rs b/crates/integration-tests/src/lib.rs
index be8e259bc..7ded8981b 100644
--- a/crates/integration-tests/src/lib.rs
+++ b/crates/integration-tests/src/lib.rs
@@ -12,21 +12,34 @@
 //! here derives or computes expected outputs.
 
 pub mod fixtures {
-    use asap_frontend_promql::lower_promql_workload;
+
+    use asap_types::ir::OperatorNode;
     use asap_types::pre_asap::schema::{DataType, Field, Schema};
-    use asap_types::pre_asap::QueryExpr;
     use asap_types::types::AccuracyTarget;
     use asap_types::workload::{
         AccuracyRequirement, BatchEntry, DataWorkload, DurationMs, Evidence, PlanningWorkload,
         Predictability, Query, QueryLanguage, QueryRequirements, QueryWorkload, TimeSelection,
     };
+    use std::rc::Rc;
 
     /// Lower one query through the plan-ready workload API using the test
     /// suite's declared one-second source cadence.
     pub fn lower_promql(
         query: &str,
         accuracy: AccuracyTarget,
-    ) -> Result<QueryExpr, asap_frontend_promql::PromqlError> {
+    ) -> Result<Rc<OperatorNode>, asap_frontend_promql::PromqlError> {
+        match lower_promql_root(query, accuracy)? {
+            asap_types::ir::QueryRoot::Operator(node) => Ok(node),
+            _ => Err(asap_frontend_promql::PromqlError::UnsupportedFeature(
+                "expected vector root".into(),
+            )),
+        }
+    }
+
+    pub fn lower_promql_root(
+        query: &str,
+        accuracy: AccuracyTarget,
+    ) -> Result<asap_types::ir::QueryRoot, asap_frontend_promql::PromqlError> {
         let workload = PlanningWorkload {
             query_workload: QueryWorkload {
                 language: QueryLanguage::PromQL,
@@ -51,7 +64,7 @@ pub mod fixtures {
                 ..Default::default()
             }),
         };
-        let mut lowered = lower_promql_workload(&workload, 0)?;
+        let mut lowered = asap_frontend_promql::lower_promql_query_workload(&workload, 0)?;
         Ok(lowered.remove(0))
     }
 
@@ -83,3 +96,26 @@ pub mod fixtures {
         }
     }
 }
+
+/// Timing and export helpers for post-ASAP plans.
+pub mod post_asap {
+    use asap_types::ir::export::{compile_physical_asap_dag, PhysicalASAPDAG};
+    use asap_types::ir::{apply_lifecycle_timings, LifecycleAssignment, OperatorNode, TimingMemo};
+    use std::rc::Rc;
+
+    /// Time `root` under the default (every summary maintained) lifecycle
+    /// assignment. Returns the timed copy; read `node.timing` on it.
+    pub fn timed(root: &Rc<OperatorNode>) -> Rc<OperatorNode> {
+        apply_lifecycle_timings(
+            root,
+            &LifecycleAssignment::default_maintained(),
+            &mut TimingMemo::new(),
+        )
+        .expect("default lifecycle timing failed")
+    }
+
+    /// Time `root` (default assignment), then export the wire-6 DAG.
+    pub fn post_asap_dag(root: &Rc<OperatorNode>) -> PhysicalASAPDAG {
+        compile_physical_asap_dag(&timed(root)).expect("post-ASAP DAG export failed")
+    }
+}
diff --git a/crates/integration-tests/tests/aggregate.rs b/crates/integration-tests/tests/aggregate.rs
index 051eeb6b7..13d2875b9 100644
--- a/crates/integration-tests/tests/aggregate.rs
+++ b/crates/integration-tests/tests/aggregate.rs
@@ -1,47 +1,54 @@
-//! `QueryExpr::Aggregate` — cross-series aggregation tests.
+//! `NonASAPOp::Aggregate` — cross-series aggregation tests.
 //!
 //! topk/bottomk are omitted — dispatch is deferred.
 //!
-//! Cross-series aggregates lower to a single `Aggregate` node with no
-//! `TimeRange` child (range functions use `TimeRange` — see `time_range.rs`).
-//! Group keys land on `Aggregate.by` as positional `ColumnId`s.
-//! Single-stat PromQL aggregates always get `output_names: [""]` (no alias)
-//! and `having: None`.
+//! Cross-series aggregates lower to a single `Aggregate` node over the
+//! instant-selector `TimeRange` (range functions use a `Range` selector —
+//! see `time_range.rs`). Group keys land on `Aggregate.reduction` as
+//! positional `ColumnId`s. Single-stat PromQL aggregates always get
+//! `output_names: [""]` (no alias) and `having: None`.
 
 use std::rc::Rc;
 use std::time::Duration;
 
 use asap_integration_tests::fixtures::lower_promql;
 use asap_integration_tests::fixtures::metric_schema;
-use asap_types::pre_asap::{AggIntent, QueryExpr, Reduction, Source};
+use asap_types::ir::{NonASAPOp, OperatorNode, TimeRangeKind};
+use asap_types::pre_asap::{AggIntent, Reduction, Source};
 use asap_types::types::AccuracyTarget;
 
-fn lower(q: &str) -> QueryExpr {
+fn lower(q: &str) -> Rc<OperatorNode> {
     lower_promql(q, AccuracyTarget::Exact).unwrap_or_else(|e| panic!("lower failed for {q:?}: {e}"))
 }
 
-fn scan(metric: &str, labels: &[&str]) -> QueryExpr {
-    QueryExpr::Scan {
+fn node(op: NonASAPOp) -> Rc<OperatorNode> {
+    OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(op))
+        .expect("fixture node derives its schema")
+}
+
+fn scan(metric: &str, labels: &[&str]) -> Rc<OperatorNode> {
+    node(NonASAPOp::Scan {
         source: Source::TimeSeries {
             metric: metric.into(),
         },
         predicates: vec![],
         schema: metric_schema(labels),
-    }
+    })
 }
 
-fn agg(by: Vec<usize>, intent: AggIntent, child: QueryExpr) -> QueryExpr {
-    QueryExpr::Aggregate {
+fn agg(by: Vec<usize>, intent: AggIntent, child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+    node(NonASAPOp::Aggregate {
         reduction: Reduction::by(by),
         measures: vec![intent],
         output_names: vec!["".into()],
         filters: vec![],
         having: None,
-        child: Rc::new(QueryExpr::TimeRange {
+        child: node(NonASAPOp::TimeRange {
             range: Duration::from_secs(1),
-            child: Rc::new(child),
+            kind: TimeRangeKind::Instant,
+            child,
         }),
-    }
+    })
 }
 
 // #5 — sum with no group keys
@@ -169,7 +176,7 @@ fn q_stdvar_no_group() {
     );
 }
 
-// #10 — cross-series quantile; no TimeRange node (no range window)
+// #10 — cross-series quantile; instant selector, no range window
 #[test]
 fn q10_quantile_cross_series() {
     assert_eq!(
diff --git a/crates/integration-tests/tests/binary_op.rs b/crates/integration-tests/tests/binary_op.rs
index 35f1c632d..284501080 100644
--- a/crates/integration-tests/tests/binary_op.rs
+++ b/crates/integration-tests/tests/binary_op.rs
@@ -1,92 +1,121 @@
-//! `QueryExpr::BinaryOp` — arithmetic, comparison, and vector-match tests.
+//! `NonASAPOp::BinaryOp` — arithmetic, comparison, and vector-match tests.
 //!
 //! Each side of a `BinaryOp` is bound independently by the SchemaResolver, so each
 //! gets its own scan schema derived from the labels it references.
-//! `VectorMatch` labels (e.g. `on(job)`) are carried as strings on the node
-//! and are NOT resolved to column ids — the SchemaResolver does not see them.
+//! `VectorMatch` labels (e.g. `on(job)`) are carried as strings on the
+//! operator and are NOT resolved to column ids — the SchemaResolver does not
+//! see them.
 
 use std::rc::Rc;
 use std::time::Duration;
 
 use asap_integration_tests::fixtures::lower_promql;
 use asap_integration_tests::fixtures::metric_schema;
+use asap_types::ir::{BinaryOperator, NonASAPOp, OperatorNode, ScalarExpr, TimeRangeKind};
 use asap_types::pre_asap::{
-    AggIntent, ArithmeticOpKind, BinaryOpKind, CompareOpKind, GroupSide, QueryExpr, Reduction,
-    Source, VectorGrouping, VectorMatch, VectorMatchKind,
+    AggIntent, ArithmeticOpKind, BinaryOpKind, CompareOpKind, GroupSide, Reduction, Source,
+    VectorGrouping, VectorMatch, VectorMatchKind,
 };
 use asap_types::types::AccuracyTarget;
 
-fn lower(q: &str) -> QueryExpr {
+fn lower(q: &str) -> Rc<OperatorNode> {
     lower_promql(q, AccuracyTarget::Exact).unwrap_or_else(|e| panic!("lower failed for {q:?}: {e}"))
 }
 
-fn scan(metric: &str, labels: &[&str]) -> QueryExpr {
-    QueryExpr::TimeRange {
+fn node(op: NonASAPOp) -> Rc<OperatorNode> {
+    OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(op))
+        .expect("fixture node derives its schema")
+}
+
+fn scan(metric: &str, labels: &[&str]) -> Rc<OperatorNode> {
+    node(NonASAPOp::TimeRange {
         range: Duration::from_secs(1),
-        child: Rc::new(source_scan(metric, labels)),
-    }
+        kind: TimeRangeKind::Instant,
+        child: source_scan(metric, labels),
+    })
 }
 
-fn source_scan(metric: &str, labels: &[&str]) -> QueryExpr {
-    QueryExpr::Scan {
+fn source_scan(metric: &str, labels: &[&str]) -> Rc<OperatorNode> {
+    node(NonASAPOp::Scan {
         source: Source::TimeSeries {
             metric: metric.into(),
         },
         predicates: vec![],
         schema: metric_schema(labels),
-    }
+    })
 }
 
-fn rate_agg(metric: &str) -> QueryExpr {
-    QueryExpr::Aggregate {
+fn rate_agg(metric: &str) -> Rc<OperatorNode> {
+    node(NonASAPOp::Aggregate {
         reduction: Reduction::PerEntity,
         measures: vec![AggIntent::Rate],
         output_names: vec!["".into()],
         filters: vec![],
         having: None,
-        child: Rc::new(QueryExpr::TimeRange {
+        child: node(NonASAPOp::TimeRange {
             range: Duration::from_secs(300),
-            child: Rc::new(source_scan(metric, &[])),
+            kind: TimeRangeKind::Range,
+            child: source_scan(metric, &[]),
         }),
-    }
+    })
 }
 
-fn sum_by_job(metric: &str) -> QueryExpr {
-    QueryExpr::Aggregate {
+fn sum_by_job(metric: &str) -> Rc<OperatorNode> {
+    node(NonASAPOp::Aggregate {
         reduction: Reduction::by(vec![2]),
         measures: vec![AggIntent::Sum { col: None }],
         output_names: vec!["".into()],
         filters: vec![],
         having: None,
-        child: Rc::new(scan(metric, &["job"])),
-    }
+        child: scan(metric, &["job"]),
+    })
+}
+
+/// A PromQL binary operator: no checked-division flags, no `bool` modifier.
+fn binary(
+    kind: BinaryOpKind,
+    vector_match: Option<VectorMatch>,
+    lhs: Rc<OperatorNode>,
+    rhs: Rc<OperatorNode>,
+) -> Rc<OperatorNode> {
+    node(NonASAPOp::BinaryOp {
+        operator: BinaryOperator {
+            checked_relative_division: false,
+            checked_finite_division: false,
+            kind,
+            vector_match,
+        },
+        return_bool: false,
+        lhs,
+        rhs,
+    })
 }
 
 // #18 — arithmetic binary op between two bare scans; no vector match
 #[test]
 fn q18_div_bare_scans() {
-    let expected = QueryExpr::BinaryOp {
-        op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Div),
-        lhs: Rc::new(scan("http_requests_total", &[])),
-        rhs: Rc::new(scan("http_requests_total", &[])),
-        vector_match: None,
-    };
+    let expected = binary(
+        BinaryOpKind::Arithmetic(ArithmeticOpKind::Div),
+        None,
+        scan("http_requests_total", &[]),
+        scan("http_requests_total", &[]),
+    );
     assert_eq!(lower("http_requests_total / http_requests_total"), expected);
 }
 
 // #19 — add with on(job) vector match; match labels are strings, not column ids
 #[test]
 fn q19_add_with_on_match() {
-    let expected = QueryExpr::BinaryOp {
-        op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Add),
-        lhs: Rc::new(scan("http_requests_total", &[])),
-        rhs: Rc::new(scan("http_requests_total", &[])),
-        vector_match: Some(VectorMatch {
+    let expected = binary(
+        BinaryOpKind::Arithmetic(ArithmeticOpKind::Add),
+        Some(VectorMatch {
             kind: VectorMatchKind::On,
             labels: vec!["job".into()],
             grouping: None,
         }),
-    };
+        scan("http_requests_total", &[]),
+        scan("http_requests_total", &[]),
+    );
     assert_eq!(
         lower("http_requests_total + on(job) http_requests_total"),
         expected
@@ -96,12 +125,12 @@ fn q19_add_with_on_match() {
 // #20 — divide two rate aggregates over different metrics
 #[test]
 fn q20_div_two_rates() {
-    let expected = QueryExpr::BinaryOp {
-        op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Div),
-        lhs: Rc::new(rate_agg("http_requests_total")),
-        rhs: Rc::new(rate_agg("http_errors_total")),
-        vector_match: None,
-    };
+    let expected = binary(
+        BinaryOpKind::Arithmetic(ArithmeticOpKind::Div),
+        None,
+        rate_agg("http_requests_total"),
+        rate_agg("http_errors_total"),
+    );
     assert_eq!(
         lower("rate(http_requests_total[5m]) / rate(http_errors_total[5m])"),
         expected,
@@ -113,12 +142,12 @@ fn q20_div_two_rates() {
 fn q_gt_comparison() {
     assert_eq!(
         lower("http_requests_total > http_errors_total"),
-        QueryExpr::BinaryOp {
-            op: BinaryOpKind::Compare(CompareOpKind::Gt),
-            lhs: Rc::new(scan("http_requests_total", &[])),
-            rhs: Rc::new(scan("http_errors_total", &[])),
-            vector_match: None,
-        }
+        binary(
+            BinaryOpKind::Compare(CompareOpKind::Gt),
+            None,
+            scan("http_requests_total", &[]),
+            scan("http_errors_total", &[]),
+        )
     );
 }
 
@@ -126,12 +155,12 @@ fn q_gt_comparison() {
 fn q_lt_comparison() {
     assert_eq!(
         lower("http_requests_total < http_errors_total"),
-        QueryExpr::BinaryOp {
-            op: BinaryOpKind::Compare(CompareOpKind::Lt),
-            lhs: Rc::new(scan("http_requests_total", &[])),
-            rhs: Rc::new(scan("http_errors_total", &[])),
-            vector_match: None,
-        }
+        binary(
+            BinaryOpKind::Compare(CompareOpKind::Lt),
+            None,
+            scan("http_requests_total", &[]),
+            scan("http_errors_total", &[]),
+        )
     );
 }
 
@@ -139,12 +168,12 @@ fn q_lt_comparison() {
 fn q_ge_comparison() {
     assert_eq!(
         lower("http_requests_total >= http_errors_total"),
-        QueryExpr::BinaryOp {
-            op: BinaryOpKind::Compare(CompareOpKind::Ge),
-            lhs: Rc::new(scan("http_requests_total", &[])),
-            rhs: Rc::new(scan("http_errors_total", &[])),
-            vector_match: None,
-        }
+        binary(
+            BinaryOpKind::Compare(CompareOpKind::Ge),
+            None,
+            scan("http_requests_total", &[]),
+            scan("http_errors_total", &[]),
+        )
     );
 }
 
@@ -152,12 +181,12 @@ fn q_ge_comparison() {
 fn q_le_comparison() {
     assert_eq!(
         lower("http_requests_total <= http_errors_total"),
-        QueryExpr::BinaryOp {
-            op: BinaryOpKind::Compare(CompareOpKind::Le),
-            lhs: Rc::new(scan("http_requests_total", &[])),
-            rhs: Rc::new(scan("http_errors_total", &[])),
-            vector_match: None,
-        }
+        binary(
+            BinaryOpKind::Compare(CompareOpKind::Le),
+            None,
+            scan("http_requests_total", &[]),
+            scan("http_errors_total", &[]),
+        )
     );
 }
 
@@ -166,16 +195,16 @@ fn q_le_comparison() {
 fn q_add_with_ignoring() {
     assert_eq!(
         lower("http_requests_total + ignoring(job) http_errors_total"),
-        QueryExpr::BinaryOp {
-            op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Add),
-            lhs: Rc::new(scan("http_requests_total", &[])),
-            rhs: Rc::new(scan("http_errors_total", &[])),
-            vector_match: Some(VectorMatch {
+        binary(
+            BinaryOpKind::Arithmetic(ArithmeticOpKind::Add),
+            Some(VectorMatch {
                 kind: VectorMatchKind::Ignoring,
                 labels: vec!["job".into()],
                 grouping: None,
             }),
-        }
+            scan("http_requests_total", &[]),
+            scan("http_errors_total", &[]),
+        )
     );
 }
 
@@ -184,11 +213,9 @@ fn q_add_with_ignoring() {
 fn q_mul_group_left() {
     assert_eq!(
         lower("http_requests_total * on(job) group_left() node_info"),
-        QueryExpr::BinaryOp {
-            op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul),
-            lhs: Rc::new(scan("http_requests_total", &[])),
-            rhs: Rc::new(scan("node_info", &[])),
-            vector_match: Some(VectorMatch {
+        binary(
+            BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul),
+            Some(VectorMatch {
                 kind: VectorMatchKind::On,
                 labels: vec!["job".into()],
                 grouping: Some(VectorGrouping {
@@ -196,7 +223,9 @@ fn q_mul_group_left() {
                     labels: vec![],
                 }),
             }),
-        }
+            scan("http_requests_total", &[]),
+            scan("node_info", &[]),
+        )
     );
 }
 
@@ -205,11 +234,9 @@ fn q_mul_group_left() {
 fn q_mul_group_right() {
     assert_eq!(
         lower("node_info * on(job) group_right() http_requests_total"),
-        QueryExpr::BinaryOp {
-            op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul),
-            lhs: Rc::new(scan("node_info", &[])),
-            rhs: Rc::new(scan("http_requests_total", &[])),
-            vector_match: Some(VectorMatch {
+        binary(
+            BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul),
+            Some(VectorMatch {
                 kind: VectorMatchKind::On,
                 labels: vec!["job".into()],
                 grouping: Some(VectorGrouping {
@@ -217,7 +244,9 @@ fn q_mul_group_right() {
                     labels: vec![],
                 }),
             }),
-        }
+            scan("node_info", &[]),
+            scan("http_requests_total", &[]),
+        )
     );
 }
 
@@ -225,12 +254,12 @@ fn q_mul_group_right() {
 //   each side: Aggregate{Sum, by=[2]} over Scan([ts, value, job])
 #[test]
 fn q21_div_two_sum_by_job() {
-    let expected = QueryExpr::BinaryOp {
-        op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Div),
-        lhs: Rc::new(sum_by_job("http_requests_total")),
-        rhs: Rc::new(sum_by_job("http_errors_total")),
-        vector_match: None,
-    };
+    let expected = binary(
+        BinaryOpKind::Arithmetic(ArithmeticOpKind::Div),
+        None,
+        sum_by_job("http_requests_total"),
+        sum_by_job("http_errors_total"),
+    );
     assert_eq!(
         lower("sum by (job) (http_requests_total) / sum by (job) (http_errors_total)"),
         expected,
@@ -238,34 +267,29 @@ fn q21_div_two_sum_by_job() {
 }
 
 // #36 — unary negation lowers as `expr * -1`: a Mul BinaryOp of the vector
-//   against PromqlScalarBridge(-1), no vector match. The vector side keeps its schema.
+//   against a `ScalarExpr(-1)` leaf, no vector match. The vector side keeps
+//   its schema.
 #[test]
 fn q36_unary_negation_is_multiply_by_minus_one() {
-    let expected = QueryExpr::BinaryOp {
-        op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul),
-        lhs: Rc::new(scan("some_metric", &[])),
-        rhs: Rc::new(QueryExpr::promql_scalar(-1.0)),
-        vector_match: None,
+    let root = lower("-some_metric");
+    let NonASAPOp::Project { cols, child, .. } = root.expect_non_asap() else {
+        panic!()
     };
-    assert_eq!(lower("-some_metric"), expected);
+    assert!(child.schema.has_promql_series_identity());
+    assert!(matches!(&cols[1].expr, ScalarExpr::Negative { .. }));
 }
 
 // #36 — negation nested inside an aggregate argument (issue #27 nesting):
 //   `sum(-m)` → Aggregate{Sum} over the `m * -1` BinaryOp.
 #[test]
 fn q36_sum_of_negation_nests() {
-    let expected = QueryExpr::Aggregate {
-        reduction: Reduction::by(vec![]),
-        measures: vec![AggIntent::Sum { col: None }],
-        output_names: vec!["".into()],
-        filters: vec![],
-        having: None,
-        child: Rc::new(QueryExpr::BinaryOp {
-            op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul),
-            lhs: Rc::new(scan("node_cpu_seconds_total", &[])),
-            rhs: Rc::new(QueryExpr::promql_scalar(-1.0)),
-            vector_match: None,
-        }),
+    let root = lower("sum(-node_cpu_seconds_total)");
+    let NonASAPOp::Aggregate {
+        child, measures, ..
+    } = root.expect_non_asap()
+    else {
+        panic!()
     };
-    assert_eq!(lower("sum(-node_cpu_seconds_total)"), expected);
+    assert!(matches!(measures.as_slice(), [AggIntent::Sum { .. }]));
+    assert!(matches!(child.expect_non_asap(), NonASAPOp::Project { .. }));
 }
diff --git a/crates/integration-tests/tests/cse.rs b/crates/integration-tests/tests/cse.rs
index bb11eee2d..56a0e657b 100644
--- a/crates/integration-tests/tests/cse.rs
+++ b/crates/integration-tests/tests/cse.rs
@@ -2,14 +2,14 @@
 //! #223).
 //!
 //! Drives the full staged pipeline this issue lands: two independently
-//! lowered `QueryExpr` DAGs → `share_common_sub_dags` (stage 1,
-//! `asap-types::pre_asap::cse`, run internally by `search_workload`) →
+//! lowered `OperatorNode` DAGs → `share_common_sub_dags` (stage 1,
+//! `asap-types::ir::cse`, run internally by `search_workload`) →
 //! `search_workload` (stage 2, `asap-aware-mapping`) — and asserts the
 //! sharing that stage 1 decides survives into stage 2's discovered
 //! `CandidateLogicalASAPDAGs` as one genuinely shared `TargetSubDAGCandidates`, not just one shared
-//! `Rc<QueryExpr>`. This is the "real caller" the issue's landing plan
+//! `Rc<OperatorNode>`. This is the "real caller" the issue's landing plan
 //! requires before `share_common_sub_dags` is allowed to exist at all (its
-//! predecessor, `asap-plan::cse::dedupe_subtrees`, was deleted in #192 for
+//! predecessor, `asap-plan::cse::dedupe_sub-DAGs`, was deleted in #192 for
 //! being unwired dead code).
 //!
 //! Committing to one final, physically-materialized answer for a whole
@@ -24,14 +24,14 @@
 
 use std::rc::Rc;
 
-use asap_aware_mapping::{search_workload, Replacement};
+use asap_aware_mapping::{is_logical_rewrite, search_workload, Replacement};
 use asap_integration_tests::fixtures::lower_promql;
-use asap_types::pre_asap::query_expr::QueryExpr;
+use asap_types::ir::NonASAPOp;
 use asap_types::types::AccuracyTarget;
 
 /// Two workload entries that happen to submit the exact same query (a
 /// realistic case — two dashboards, or a query fired both standalone and as
-/// part of a larger batch) collapse onto one shared `Rc<QueryExpr>` after
+/// part of a larger batch) collapse onto one shared `Rc<OperatorNode>` after
 /// `search_workload`'s internal `share_common_sub_dags` pass, and onto one
 /// genuinely-shared [`TargetSubDAGCandidates`](asap_aware_mapping::TargetSubDAGCandidates) — carrying
 /// every candidate discovered for it exactly once, not once per root — no
@@ -41,7 +41,7 @@ use asap_types::types::AccuracyTarget;
 fn duplicate_workload_queries_collapse_onto_one_memo_group() {
     // Grouped (`by (job)`), so the shared `Aggregate`'s output schema carries
     // a provable unique key — the legality gate `share_common_sub_dags`
-    // enforces (see `asap-types::pre_asap::cse`'s module doc) — and its
+    // enforces (see `asap-types::ir::cse`'s module doc) — and its
     // `ExactAggregate(Sum)` realization is deterministic regardless of the
     // accuracy target, so this pins the sharing mechanism itself rather than
     // any one particular summary-family choice.
@@ -57,17 +57,17 @@ fn duplicate_workload_queries_collapse_onto_one_memo_group() {
         "fixture sanity: identical query text lowers identically"
     );
 
-    let space = search_workload(vec![("a", Rc::new(a)), ("b", Rc::new(b))]);
+    let space = search_workload(vec![("a", a), ("b", b)]);
 
     // roots[0] and roots[1] must have merged onto the same Rc — the
     // `share_common_sub_dags` pass `search_workload` runs internally.
     assert!(
         Rc::ptr_eq(&space.roots[0].1, &space.roots[1].1),
-        "search_workload must collapse the two identical roots onto one Rc<QueryExpr>"
+        "search_workload must collapse the two identical roots onto one Rc<OperatorNode>"
     );
 
     // The single shared root is one discovered TargetSubDAG, holding one
-    // TargetSubDAGCandidates with consumer_count 2 — SketchAlgorithmStrategy's one
+    // TargetSubDAGCandidates with consumer_count 2 — ASAPStrategies's one
     // ExactAggregate candidate *and* SharedSubDAGStrategy's share-vs-
     // recompute pair, exactly as `shared_aggregate_across_two_roots_gets_both_strategies_candidates`
     // (asap-aware-mapping::replacement's own equivalent, internal test)
@@ -79,19 +79,21 @@ fn duplicate_workload_queries_collapse_onto_one_memo_group() {
     assert_eq!(
         group.candidates.len(),
         3,
-        "1 ExactAggregate Summary + 2 Rewrite (share/recompute): {:?}",
+        "1 ExactAggregate summary + 2 logical rewrites (share/recompute): {:?}",
         group.candidates
     );
 
+    // A bound summary is a `Subtree` with an ASAP operator in it; a logical
+    // rewrite is a `Subtree` with none (`is_logical_rewrite`).
     let summary_count = group
         .candidates
         .iter()
-        .filter(|c| matches!(c.replacement, Replacement::Summary(_)))
+        .filter(|c| matches!(&c.replacement, Replacement::SubDAG(n) if n.contains_asap()))
         .count();
     let rewrite_count = group
         .candidates
         .iter()
-        .filter(|c| matches!(c.replacement, Replacement::Rewrite(_)))
+        .filter(|c| matches!(&c.replacement, Replacement::SubDAG(n) if is_logical_rewrite(n)))
         .count();
     assert_eq!(summary_count, 1);
     assert_eq!(rewrite_count, 2);
@@ -100,12 +102,14 @@ fn duplicate_workload_queries_collapse_onto_one_memo_group() {
     // "false-positive dedup" failure mode `is_duplicate_rewrite` exists to
     // prevent): one shares the group's own target `Rc`, the other is a
     // structurally-identical but independently-built `Rc`.
-    let one_is_the_target = group.candidates.iter().any(
-        |c| matches!(&c.replacement, Replacement::Rewrite(rc) if Rc::ptr_eq(rc, &group.target)),
-    );
-    let one_is_not = group.candidates.iter().any(
-        |c| matches!(&c.replacement, Replacement::Rewrite(rc) if !Rc::ptr_eq(rc, &group.target)),
-    );
+    let one_is_the_target = group.candidates.iter().any(|c| {
+        matches!(&c.replacement, Replacement::SubDAG(rc)
+            if is_logical_rewrite(rc) && Rc::ptr_eq(rc, &group.target))
+    });
+    let one_is_not = group.candidates.iter().any(|c| {
+        matches!(&c.replacement, Replacement::SubDAG(rc)
+            if is_logical_rewrite(rc) && !Rc::ptr_eq(rc, &group.target))
+    });
     assert!(one_is_the_target && one_is_not);
 }
 
@@ -121,7 +125,7 @@ fn distinct_workload_queries_get_independent_memo_groups() {
         .expect("query b failed to lower");
     assert_ne!(a, b, "fixture sanity: the two queries differ");
 
-    let space = search_workload(vec![("a", Rc::new(a)), ("b", Rc::new(b))]);
+    let space = search_workload(vec![("a", a), ("b", b)]);
     assert!(!Rc::ptr_eq(&space.roots[0].1, &space.roots[1].1));
 
     let group_a = space
@@ -140,7 +144,7 @@ fn distinct_workload_queries_get_independent_memo_groups() {
 
 /// Single-query CSE (a repeated sub-expression within one query) also
 /// survives through `search_workload`: the two grouped-`Aggregate` branches
-/// of a `BinaryOp` collapse to one shared `Rc<QueryExpr>` in the internal
+/// of a `BinaryOp` collapse to one shared `Rc<OperatorNode>` in the internal
 /// `share_common_sub_dags` pass, and to one shared `TargetSubDAGCandidates` (with
 /// `consumer_count == 2`, one per branch) here.
 #[test]
@@ -148,16 +152,16 @@ fn single_query_repeated_subexpression_shares_one_memo_group() {
     let query = "sum by (job) (http_requests_total) / sum by (job) (http_requests_total)";
     let expr = lower_promql(query, AccuracyTarget::Exact).expect("query failed to lower");
 
-    let space = search_workload(vec![("q", Rc::new(expr))]);
+    let space = search_workload(vec![("q", expr)]);
     let [(_, root)] = space.roots.as_slice() else {
         panic!("expected 1 root");
     };
-    let QueryExpr::BinaryOp { lhs, rhs, .. } = root.as_ref() else {
+    let Some(NonASAPOp::BinaryOp { lhs, rhs, .. }) = root.non_asap() else {
         panic!("expected a BinaryOp root, got {root:?}");
     };
     assert!(
         Rc::ptr_eq(lhs, rhs),
-        "the two identical sum-by-job branches must collapse onto one Rc<QueryExpr>"
+        "the two identical sum-by-job branches must collapse onto one Rc<OperatorNode>"
     );
 
     let group = space
diff --git a/crates/integration-tests/tests/exact_composition.rs b/crates/integration-tests/tests/exact_composition.rs
index 917ef7b3a..f72458377 100644
--- a/crates/integration-tests/tests/exact_composition.rs
+++ b/crates/integration-tests/tests/exact_composition.rs
@@ -1,5 +1,5 @@
 //! Issue #171 — composing exact operators with summary plans across
-//! explicit update/readout boundaries, end to end through
+//! explicit update/evaluation boundaries, end to end through
 //! `search_workload_with` → `CandidateLogicalASAPDAGs::global_selection` →
 //! `GlobalSelection::assemble_selected_dag` → `dag_export`.
 //!
@@ -16,27 +16,37 @@ use asap_aware_mapping::cost_model::{
     CostProvenance, CostUnit, ExactCompositionCostInputs, ExactCompositionCostRequest,
     ValueOperationCapabilities,
 };
+use asap_aware_mapping::exact_composition::ExactOperation;
 use asap_aware_mapping::replacement::{
-    default_strategies_with, search_workload_with, Replacement, ReplacementProvenance,
-    ReplacementStrategy, SketchAlgorithmStrategy, TargetSubDAG,
+    default_strategies_with, search_workload_with, ASAPStrategies, Replacement,
+    ReplacementProvenance, ReplacementStrategy, TargetSubDAG,
 };
 use asap_aware_mapping::{
     CostModel, DefaultCostModel, EvaluationRate, ExplanationKind, OperationPlacement,
 };
 use asap_integration_tests::fixtures::lower_promql;
+use asap_integration_tests::post_asap::{post_asap_dag, timed};
 use asap_types::dag_export;
+use asap_types::ir::export::{NonASAPOpKind, PhysicalASAPOperatorPayload};
+use asap_types::ir::operator_properties::{Reduction, Source};
+use asap_types::ir::timing::data_state;
+use asap_types::ir::{ASAPOp, NonASAPOp, Operator, OperatorNode, TimeRangeKind};
 use asap_types::post_asap::{
-    validate_execution_data_states, ExactKind, ExactOperation, ExecutionDataState, ExecutionTiming,
-    FieldDataType, SketchAlgorithm, SummaryExpr, SummaryNode, SummaryUpdate,
+    ExactKind, ExecutionDataState, ExecutionTiming, FieldDataType, SketchAlgorithm, SummaryUpdate,
 };
 use asap_types::pre_asap::agg_intent::{default_quantile, AggIntent};
-use asap_types::pre_asap::query_expr::{QueryExpr, Reduction, Source};
 use asap_types::pre_asap::schema::{DataType, Field, Schema};
+
 use asap_types::types::AccuracyTarget;
 
 // ── fixtures ────────────────────────────────────────────────────────────
 
-fn metric_scan(labels: &[&str]) -> QueryExpr {
+fn node(op: NonASAPOp) -> Rc<OperatorNode> {
+    OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(op))
+        .expect("fixture node derives its schema")
+}
+
+fn metric_scan(labels: &[&str]) -> Rc<OperatorNode> {
     let mut columns = vec![
         Field::plain("ts", DataType::Timestamp, false),
         Field::plain("value", DataType::Float64, false),
@@ -46,17 +56,17 @@ fn metric_scan(labels: &[&str]) -> QueryExpr {
             .iter()
             .map(|n| Field::plain(*n, DataType::Utf8, true)),
     );
-    QueryExpr::Scan {
+    node(NonASAPOp::Scan {
         source: Source::TimeSeries {
             metric: "latency".into(),
         },
         predicates: vec![],
         schema: Schema::with_time_index(columns, 0, vec![]),
-    }
+    })
 }
 
-fn agg(by: Vec<usize>, intent: AggIntent, child: Rc<QueryExpr>) -> Rc<QueryExpr> {
-    Rc::new(QueryExpr::Aggregate {
+fn agg(by: Vec<usize>, intent: AggIntent, child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+    node(NonASAPOp::Aggregate {
         reduction: Reduction::by(by),
         measures: vec![intent],
         output_names: vec![],
@@ -66,8 +76,8 @@ fn agg(by: Vec<usize>, intent: AggIntent, child: Rc<QueryExpr>) -> Rc<QueryExpr>
     })
 }
 
-fn per_entity(intent: AggIntent, child: Rc<QueryExpr>) -> Rc<QueryExpr> {
-    Rc::new(QueryExpr::Aggregate {
+fn per_entity(intent: AggIntent, child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+    node(NonASAPOp::Aggregate {
         reduction: Reduction::PerEntity,
         measures: vec![intent],
         output_names: vec![],
@@ -78,11 +88,11 @@ fn per_entity(intent: AggIntent, child: Rc<QueryExpr>) -> Rc<QueryExpr> {
 }
 
 /// `quantile by (zone, host) (latency)` — the fine-grained inner summary.
-fn fine_quantile() -> Rc<QueryExpr> {
+fn fine_quantile() -> Rc<OperatorNode> {
     agg(
         vec![2, 3],
         default_quantile(0.99),
-        Rc::new(metric_scan(&["zone", "host"])),
+        metric_scan(&["zone", "host"]),
     )
 }
 
@@ -96,7 +106,7 @@ struct StatsModel;
 fn custom_accuracy_rule_survives_root_target_and_materialization() {
     use asap_aware_mapping::{AccuracyModel, DefaultAccuracyModel, PropagationStats};
     use asap_types::post_asap::{
-        AccuracyError, CompositionOperator, ExactOperation, ResultGuarantee, SketchStatistic,
+        AccuracyError, CompositionOperator, ResultGuarantee, SketchStatistic,
     };
     struct Model;
     impl AccuracyModel for Model {
@@ -278,34 +288,44 @@ fn unknown_runtime_capability_keeps_candidate_but_prevents_selection() {
 }
 
 fn plan(
-    roots: Vec<(&'static str, Rc<QueryExpr>)>,
+    roots: Vec<(&'static str, Rc<OperatorNode>)>,
     cost_model: &dyn CostModel,
 ) -> asap_aware_mapping::CandidateLogicalASAPDAGs<&'static str> {
     search_workload_with(roots, &default_strategies_with(cost_model))
 }
 
-fn is_plain(node: &SummaryNode) -> bool {
+fn is_plain(node: &OperatorNode) -> bool {
     node.schema
         .fields
         .iter()
         .all(|f| matches!(f.dtype, FieldDataType::Plain(_)))
 }
 
-fn names(node: &SummaryNode) -> Vec<&str> {
+fn names(node: &OperatorNode) -> Vec<&str> {
     node.schema.fields.iter().map(|f| f.name.as_str()).collect()
 }
 
+/// The composed query-time shape: an exact `Aggregate` directly over a
+/// summary evaluation, at query time.
+fn is_query_time_fold(node: &OperatorNode) -> bool {
+    matches!(
+        node.non_asap(),
+        Some(NonASAPOp::Aggregate { child, .. })
+            if matches!(child.operator, Operator::ASAP(ASAPOp::SummaryEstimate { .. }))
+    )
+}
+
 // ── step 1: pin every already-supported exact-accumulator nesting ───────
 
 #[test]
 fn every_exact_accumulator_is_finalized_before_an_outer_sketch() {
     use std::time::Duration;
-    let cases: Vec<(Rc<QueryExpr>, ExactKind)> = vec![
+    let cases: Vec<(Rc<OperatorNode>, ExactKind)> = vec![
         (
             agg(
                 vec![2],
                 AggIntent::Sum { col: None },
-                Rc::new(metric_scan(&["zone"])),
+                metric_scan(&["zone"]),
             ),
             ExactKind::Sum,
         ),
@@ -315,7 +335,7 @@ fn every_exact_accumulator_is_finalized_before_an_outer_sketch() {
                 AggIntent::Count {
                     accuracy: AccuracyTarget::Exact,
                 },
-                Rc::new(metric_scan(&["zone"])),
+                metric_scan(&["zone"]),
             ),
             ExactKind::Count,
         ),
@@ -323,7 +343,7 @@ fn every_exact_accumulator_is_finalized_before_an_outer_sketch() {
             agg(
                 vec![2],
                 AggIntent::Min { col: None },
-                Rc::new(metric_scan(&["zone"])),
+                metric_scan(&["zone"]),
             ),
             ExactKind::Min,
         ),
@@ -331,16 +351,17 @@ fn every_exact_accumulator_is_finalized_before_an_outer_sketch() {
             agg(
                 vec![2],
                 AggIntent::Max { col: None },
-                Rc::new(metric_scan(&["zone"])),
+                metric_scan(&["zone"]),
             ),
             ExactKind::Max,
         ),
         (
             per_entity(
                 AggIntent::Rate,
-                Rc::new(QueryExpr::TimeRange {
+                node(NonASAPOp::TimeRange {
                     range: Duration::from_secs(300),
-                    child: Rc::new(metric_scan(&["zone"])),
+                    kind: TimeRangeKind::Range,
+                    child: metric_scan(&["zone"]),
                 }),
             ),
             ExactKind::Rate,
@@ -348,9 +369,10 @@ fn every_exact_accumulator_is_finalized_before_an_outer_sketch() {
         (
             per_entity(
                 AggIntent::Increase,
-                Rc::new(QueryExpr::TimeRange {
+                node(NonASAPOp::TimeRange {
                     range: Duration::from_secs(300),
-                    child: Rc::new(metric_scan(&["zone"])),
+                    kind: TimeRangeKind::Range,
+                    child: metric_scan(&["zone"]),
                 }),
             ),
             ExactKind::Increase,
@@ -359,40 +381,43 @@ fn every_exact_accumulator_is_finalized_before_an_outer_sketch() {
     for (inner, kind) in cases {
         let outer = agg(vec![], default_quantile(0.9), inner);
         let target = TargetSubDAG::new(&outer);
-        let candidates = SketchAlgorithmStrategy::default_cost_model().replacements(&target);
-        let Replacement::Summary(root) = &candidates[0].replacement else {
+        let candidates = ASAPStrategies::default_cost_model().replacements(&target);
+        let Replacement::SubDAG(root) = &candidates[0].replacement else {
             unreachable!()
         };
-        let SummaryExpr::SummaryEstimate { summary_input, .. } = &root.expr else {
-            panic!("expected KLL readout, got {:?}", root.expr);
+        // Timing is not stored on the plan: time it (default lifecycle,
+        // which also validates every edge) and inspect the timed copy.
+        let root = timed(root);
+        let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &root.operator else {
+            panic!("expected KLL evaluation, got {:?}", root.operator);
         };
-        let SummaryExpr::SummaryAgg { child, .. } = &summary_input.expr else {
+        let Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) = &summary_input.operator else {
             panic!("expected outer SummaryAgg");
         };
-        let SummaryExpr::ValueOperation {
-            child,
-            operation: asap_types::post_asap::ValueOperation::FinalizeExactAccumulator,
-            timing: ExecutionTiming::IngestionTime,
-        } = &child.expr
+        let Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child: finalized }) = &child.operator
         else {
             panic!("{kind:?}: missing maintenance finalization");
         };
+        assert_eq!(
+            child.timing,
+            Some(ExecutionTiming::IngestionTime),
+            "{kind:?}: finalization runs at maintenance time"
+        );
         assert!(
             matches!(
-                &child.expr,
-                SummaryExpr::SummaryAgg { family: FieldDataType::ExactAggregate(k, _), .. } if *k == kind
+                &finalized.operator,
+                Operator::ASAP(ASAPOp::SummaryAgg { family: FieldDataType::ExactAggregate(k, _), .. }) if *k == kind
             ),
             "{kind:?}: expected the exact accumulator under its finalization, got {:?}",
-            child.expr
+            finalized.operator
         );
-        validate_execution_data_states(root).expect("accumulator state composes under maintenance");
     }
 }
 
-// ── direction 1: outer exact fold over an inner summary readout ────────
+// ── direction 1: outer exact fold over an inner summary evaluation ────────
 
-/// Before this PR both `max`/`avg` over a quantile collapsed into one
-/// opaque `KeepPreAsap`. Now: the outer group holds an `ValueOperationAtQueryTime`
+/// `max`/`avg` over a quantile does not collapse into one opaque kept
+/// sub-DAG: the outer group holds an `ValueOperationAtQueryTime`
 /// candidate referencing the inner target, the inner group keeps its own
 /// sketch candidates, and with statistics the pair is committed and
 /// materializes as `ValueOperationAtQueryTime → SummaryEstimate → SummaryAgg`.
@@ -402,7 +427,7 @@ fn max_and_avg_over_quantile_compose_at_query_time_with_statistics() {
         let root = agg(vec![0], intent.clone(), fine_quantile());
         let space = plan(vec![("q", Rc::clone(&root))], &StatsModel);
         let root = Rc::clone(&space.roots[0].1);
-        let QueryExpr::Aggregate { child: inner, .. } = root.as_ref() else {
+        let Some(NonASAPOp::Aggregate { child: inner, .. }) = root.non_asap() else {
             unreachable!()
         };
 
@@ -419,9 +444,9 @@ fn max_and_avg_over_quantile_compose_at_query_time_with_statistics() {
             inner_group
                 .candidates
                 .iter()
-                .any(|c| matches!(&c.replacement, Replacement::Summary(n)
-                    if matches!(n.expr, SummaryExpr::SummaryEstimate { .. }))),
-            "{intent:?}: the inner quantile keeps its own readout candidates"
+                .any(|c| matches!(&c.replacement, Replacement::SubDAG(n)
+                    if matches!(n.operator, Operator::ASAP(ASAPOp::SummaryEstimate { .. })))),
+            "{intent:?}: the inner quantile keeps its own evaluation candidates"
         );
 
         let selection = space.global_selection(&StatsModel);
@@ -449,18 +474,16 @@ fn max_and_avg_over_quantile_compose_at_query_time_with_statistics() {
         ));
 
         let composed = selection.assemble_selected_dag(&root).unwrap().unwrap();
-        let SummaryExpr::ValueOperation {
-            child,
-            timing: ExecutionTiming::QueryTime,
-            ..
-        } = &composed.expr
-        else {
+        let Some(NonASAPOp::Aggregate { child, .. }) = composed.non_asap() else {
             panic!(
                 "{intent:?}: expected ValueOperationAtQueryTime root, got {:?}",
-                composed.expr
+                composed.operator
             );
         };
-        assert!(matches!(child.expr, SummaryExpr::SummaryEstimate { .. }));
+        assert!(matches!(
+            child.operator,
+            Operator::ASAP(ASAPOp::SummaryEstimate { .. })
+        ));
         assert!(
             child.guarantee.is_some(),
             "child has its KLL rank guarantee"
@@ -472,15 +495,18 @@ fn max_and_avg_over_quantile_compose_at_query_time_with_statistics() {
         assert!(is_plain(&composed));
         assert_eq!(
             names(&composed),
-            root.output_schema()
-                .unwrap()
+            root.schema
                 .fields
                 .iter()
                 .map(|c| c.name.as_str())
                 .collect::<Vec<_>>(),
             "the composed plan's schema is the pre-ASAP target's own"
         );
-        validate_execution_data_states(&composed).unwrap();
+        assert_eq!(
+            timed(&composed).timing,
+            Some(ExecutionTiming::QueryTime),
+            "{intent:?}: the exact fold runs at query time"
+        );
     }
 }
 
@@ -490,11 +516,7 @@ fn max_and_avg_over_quantile_compose_at_query_time_with_statistics() {
 fn avg_over_quantile_keeps_the_sum_over_count_rewrite_as_a_competitor() {
     // `by (zone)` over `by (zone)`: the averaged column resolves to the
     // non-null quantile output, which is what the rewrite requires.
-    let inner = agg(
-        vec![2],
-        default_quantile(0.99),
-        Rc::new(metric_scan(&["zone"])),
-    );
+    let inner = agg(vec![2], default_quantile(0.99), metric_scan(&["zone"]));
     let root = agg(vec![0], AggIntent::Avg { col: None }, inner);
     let space = plan(vec![("q", root)], &StatsModel);
     let group = space.candidates_for_target(&space.roots[0].1).unwrap();
@@ -508,11 +530,7 @@ fn avg_over_quantile_keeps_the_sum_over_count_rewrite_as_a_competitor() {
 /// is the same, only the fold's row multiplicity differs.
 #[test]
 fn identity_and_genuine_multi_row_folds_both_compose() {
-    let identity_inner = agg(
-        vec![2],
-        default_quantile(0.99),
-        Rc::new(metric_scan(&["zone"])),
-    );
+    let identity_inner = agg(vec![2], default_quantile(0.99), metric_scan(&["zone"]));
     for (label, inner) in [
         ("identity", identity_inner),
         ("fine-to-coarse", fine_quantile()),
@@ -527,14 +545,17 @@ fn identity_and_genuine_multi_row_folds_both_compose() {
             .unwrap();
         assert!(
             matches!(
-                composed.expr,
-                SummaryExpr::ValueOperation {
-                    timing: ExecutionTiming::QueryTime,
-                    ..
-                }
+                composed.non_asap(),
+                Some(NonASAPOp::Aggregate { child, .. })
+                    if matches!(child.operator, Operator::ASAP(ASAPOp::SummaryEstimate { .. }))
             ),
             "{label}: {:?}",
-            composed.expr
+            composed.operator
+        );
+        assert_eq!(
+            timed(&composed).timing,
+            Some(ExecutionTiming::QueryTime),
+            "{label}"
         );
         assert_eq!(names(&composed), vec!["zone", "max"], "{label}");
     }
@@ -543,7 +564,7 @@ fn identity_and_genuine_multi_row_folds_both_compose() {
 /// One inner quantile consumed by two outer folds in two queries: CSE
 /// collapses the inner target onto one `Rc`, both compositions commit to
 /// the *same* child candidate, and both materializations share one
-/// `Rc<SummaryNode>` for it — the summary is maintained once.
+/// `Rc<OperatorNode>` for it — the summary is maintained once.
 #[test]
 fn a_shared_inner_summary_is_materialized_once_for_several_outer_folds() {
     let max = agg(vec![0], AggIntent::Max { col: None }, fine_quantile());
@@ -551,9 +572,9 @@ fn a_shared_inner_summary_is_materialized_once_for_several_outer_folds() {
     let space = plan(vec![("max", max), ("min", min)], &StatsModel);
     let selection = space.global_selection(&StatsModel);
 
-    let roots: Vec<Rc<QueryExpr>> = space.roots.iter().map(|(_, r)| Rc::clone(r)).collect();
-    let inner_of = |r: &Rc<QueryExpr>| match r.as_ref() {
-        QueryExpr::Aggregate { child, .. } => Rc::clone(child),
+    let roots: Vec<Rc<OperatorNode>> = space.roots.iter().map(|(_, r)| Rc::clone(r)).collect();
+    let inner_of = |r: &Rc<OperatorNode>| match r.non_asap() {
+        Some(NonASAPOp::Aggregate { child, .. }) => Rc::clone(child),
         _ => unreachable!(),
     };
     assert!(
@@ -589,17 +610,20 @@ fn a_shared_inner_summary_is_materialized_once_for_several_outer_folds() {
         .iter()
         .map(|r| selection.assemble_selected_dag(r).unwrap().unwrap())
         .collect();
-    let child_of = |n: &Rc<SummaryNode>| match &n.expr {
-        SummaryExpr::ValueOperation {
-            child,
-            timing: ExecutionTiming::QueryTime,
-            ..
-        } => Rc::clone(child),
-        other => panic!("expected ValueOperationAtQueryTime, got {other:?}"),
+    let child_of = |n: &Rc<OperatorNode>| match n.non_asap() {
+        Some(NonASAPOp::Aggregate { child, .. })
+            if matches!(
+                child.operator,
+                Operator::ASAP(ASAPOp::SummaryEstimate { .. })
+            ) =>
+        {
+            Rc::clone(child)
+        }
+        _ => panic!("expected ValueOperationAtQueryTime, got {:?}", n.operator),
     };
     assert!(
         Rc::ptr_eq(&child_of(&composed[0]), &child_of(&composed[1])),
-        "both folds compose over the same Rc<SummaryNode>"
+        "both folds compose over the same Rc<OperatorNode>"
     );
 }
 
@@ -614,15 +638,16 @@ fn outer_summary_over_an_exact_function_composes_at_ingestion_time() {
     use std::time::Duration;
     let deriv = per_entity(
         AggIntent::Deriv,
-        Rc::new(QueryExpr::TimeRange {
+        node(NonASAPOp::TimeRange {
             range: Duration::from_secs(300),
-            child: Rc::new(metric_scan(&["zone"])),
+            kind: TimeRangeKind::Range,
+            child: metric_scan(&["zone"]),
         }),
     );
     let root = agg(vec![], default_quantile(0.99), deriv);
     let space = plan(vec![("q", root)], &StatsModel);
     let root = Rc::clone(&space.roots[0].1);
-    let QueryExpr::Aggregate { child: deriv, .. } = root.as_ref() else {
+    let Some(NonASAPOp::Aggregate { child: deriv, .. }) = root.non_asap() else {
         unreachable!()
     };
     assert!(space
@@ -643,33 +668,25 @@ fn outer_summary_over_an_exact_function_composes_at_ingestion_time() {
     assert!(decision.cost_rate < decision.baseline_rate);
 
     let composed = selection.assemble_selected_dag(&root).unwrap().unwrap();
-    let SummaryExpr::SummaryEstimate { summary_input, .. } = &composed.expr else {
-        panic!("expected readout root, got {:?}", composed.expr);
+    // Walk the timed copy: timing is written by the lifecycle assignment.
+    let composed = timed(&composed);
+    let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &composed.operator else {
+        panic!("expected evaluation root, got {:?}", composed.operator);
     };
-    let SummaryExpr::SummaryAgg { child, .. } = &summary_input.expr else {
+    let Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) = &summary_input.operator else {
         panic!("expected SummaryAgg");
     };
-    let SummaryExpr::ValueOperation {
-        child: raw,
-        timing: ExecutionTiming::IngestionTime,
-        ..
-    } = &child.expr
-    else {
+    let Some(NonASAPOp::Aggregate { child: raw, .. }) = child.non_asap() else {
         panic!(
             "expected ValueOperationAtIngestionTime under the maintained summary, got {:?}",
-            child.expr
+            child.operator
         );
     };
-    assert!(matches!(raw.expr, SummaryExpr::KeepPreAsap(_)));
-    let assignment = validate_execution_data_states(&composed).unwrap();
-    assert_eq!(
-        assignment.data_state_of(child),
-        Some(ExecutionDataState::INGESTION_ROWS)
-    );
-    assert_eq!(
-        assignment.data_state_of(raw),
-        Some(ExecutionDataState::INGESTION_ROWS)
-    );
+    // The raw input is kept as-is.
+    assert!(matches!(raw.non_asap(), Some(NonASAPOp::TimeRange { .. })));
+    assert!(!raw.contains_asap());
+    assert_eq!(data_state(child), Some(ExecutionDataState::INGESTION_ROWS));
+    assert_eq!(data_state(raw), Some(ExecutionDataState::INGESTION_ROWS));
 }
 
 // ── rejection, capability, statistics ───────────────────────────────────
@@ -685,24 +702,28 @@ fn summary_construction_follows_its_value_input_phase() {
         .assemble_selected_dag(&space.roots[0].1)
         .unwrap()
         .unwrap();
-    let illegal = Rc::new(SummaryNode {
-        expr: SummaryExpr::SummaryAgg {
-            child: post,
-            family: FieldDataType::ExactAggregate(
-                ExactKind::Max,
-                asap_types::post_asap::ExactParams::Max,
-            ),
-            input: SummaryUpdate::column(asap_types::pre_asap::ColumnRef::SampleValue),
-            reduction: Reduction::by(vec![]),
-            grouping: Default::default(),
-            filter: None,
-        },
-        schema: asap_types::post_asap::Schema::lifted(vec![], None),
-        guarantee: None,
-    });
-    let state = asap_types::post_asap::produced_data_state(&illegal.expr).unwrap();
+    let illegal = std::rc::Rc::new(
+        OperatorNode::with_schema(
+            asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
+                child: post,
+                family: FieldDataType::ExactAggregate(
+                    ExactKind::Max,
+                    asap_types::post_asap::ExactParams::Max,
+                ),
+                input: SummaryUpdate::column(asap_types::pre_asap::ColumnRef::SampleValue),
+                reduction: Reduction::by(vec![]),
+                grouping: Default::default(),
+                filter: None,
+            }),
+            Schema::lifted(vec![], None),
+        )
+        .with_guarantee(None),
+    );
+    // Even under an ingestion-time consumer the state is built at query
+    // time, because a evaluation sits below it.
+    let state = asap_types::ir::planned_data_state(&illegal, ExecutionTiming::IngestionTime);
     assert_eq!(state.timing, ExecutionTiming::QueryTime);
-    asap_types::post_asap::validate_execution_data_states_at(&illegal, state).unwrap();
+    asap_types::ir::validate_default(&illegal, state.timing).unwrap();
 }
 
 #[test]
@@ -718,9 +739,9 @@ fn a_runtime_without_mixed_execution_gets_no_composition_candidates() {
     let selection = space.global_selection(&NoCapabilityModel);
     assert!(selection.for_target(&root).unwrap().composition.is_none());
     let node = selection.assemble_selected_dag(&root).unwrap().unwrap();
-    assert!(!matches!(node.expr, SummaryExpr::ValueOperation { .. }));
+    assert!(!is_query_time_fold(&node));
     // The inner quantile is still independently selectable.
-    let QueryExpr::Aggregate { child, .. } = root.as_ref() else {
+    let Some(NonASAPOp::Aggregate { child, .. }) = root.non_asap() else {
         unreachable!()
     };
     assert!(selection.for_target(child).unwrap().chosen.is_some());
@@ -731,7 +752,7 @@ fn a_runtime_without_mixed_execution_gets_no_composition_candidates() {
 /// site keeps a non-composed alternative, and the inner summary stays
 /// independently selectable.
 #[test]
-fn missing_cost_statistics_preserve_the_conservative_keep_pre_asap() {
+fn missing_cost_statistics_preserve_the_conservative_retain_exact() {
     let root = agg(vec![0], AggIntent::Max { col: None }, fine_quantile());
     let space = plan(vec![("q", root)], &DefaultCostModel);
     let root = Rc::clone(&space.roots[0].1);
@@ -749,9 +770,9 @@ fn missing_cost_statistics_preserve_the_conservative_keep_pre_asap() {
         Some(Replacement::ExactComposition(_))
     ));
     let node = selection.assemble_selected_dag(&root).unwrap().unwrap();
-    assert!(!matches!(node.expr, SummaryExpr::ValueOperation { .. }));
+    assert!(!is_query_time_fold(&node));
 
-    let explanations = asap_aware_mapping::explain_replacements(vec![("q", (*root).clone())]);
+    let explanations = asap_aware_mapping::explain_replacements(vec![("q", Rc::clone(&root))]);
     assert!(explanations
         .iter()
         .any(|e| e.kind == ExplanationKind::ExactComposition));
@@ -771,12 +792,19 @@ fn dag_export_carries_explicit_stage_and_plain_schema_for_a_composed_plan() {
         .unwrap();
     let dag = dag_export::export_summary(&composed);
     let node = &dag.nodes[dag.root as usize];
-    assert_eq!(node.kind, "ValueOperation");
-    assert_eq!(node.detail["timing"], "query_time");
-    assert!(node.detail["operation"]
-        .as_str()
-        .unwrap()
-        .starts_with("Exact(Aggregate"));
+    assert_eq!(node.kind, "aggregate");
+    assert!(node.detail["measures"].is_array());
+    // Timing is explicit in the wire-6 DAG: the root is a relational
+    // aggregate placed at query time.
+    let wire = post_asap_dag(&composed);
+    let wire_root = wire.nodes.iter().find(|n| n.id == wire.roots[0]).unwrap();
+    assert!(matches!(
+        wire_root.payload,
+        PhysicalASAPOperatorPayload::Relational {
+            operator: NonASAPOpKind::Aggregate { .. }
+        }
+    ));
+    assert_eq!(wire_root.output_state.timing, ExecutionTiming::QueryTime);
 
     // Pre-ASAP export of the same target still describes the same columns.
     let pre = dag_export::export(root);
@@ -798,7 +826,7 @@ fn promql_max_by_zone_over_quantile_over_time_composes() {
         AccuracyTarget::Epsilon(0.01),
     )
     .unwrap();
-    let space = plan(vec![("q", Rc::new(expr))], &StatsModel);
+    let space = plan(vec![("q", expr)], &StatsModel);
     let root = &space.roots[0].1;
     let selection = space.global_selection(&StatsModel);
     let selected = selection.for_target(root).unwrap();
@@ -815,13 +843,8 @@ fn promql_max_by_zone_over_quantile_over_time_composes() {
             .collect::<Vec<_>>()
     );
     let composed = selection.assemble_selected_dag(root).unwrap().unwrap();
-    assert!(matches!(
-        composed.expr,
-        SummaryExpr::ValueOperation {
-            timing: ExecutionTiming::QueryTime,
-            ..
-        }
-    ));
+    assert!(is_query_time_fold(&composed), "{:?}", composed.operator);
+    assert_eq!(timed(&composed).timing, Some(ExecutionTiming::QueryTime));
     assert_eq!(
         selected.composition.as_ref().map(|d| d.inputs.unit),
         Some(CostUnit::CostUnitsPerSecond)
diff --git a/crates/integration-tests/tests/frontend_timestamps.rs b/crates/integration-tests/tests/frontend_timestamps.rs
index 388261da6..300f0cee7 100644
--- a/crates/integration-tests/tests/frontend_timestamps.rs
+++ b/crates/integration-tests/tests/frontend_timestamps.rs
@@ -1,9 +1,9 @@
 //! Cross-frontend evaluation-time semantics (issues #46 and #184).
 
 use asap_frontend_sql::{lower_sql, SqlCatalog};
-use asap_integration_tests::fixtures::lower_promql;
+use asap_integration_tests::fixtures::lower_promql_root;
+use asap_types::ir::{NonASAPOp, ScalarExpr};
 use asap_types::pre_asap::schema::{DataType, Field, Schema};
-use asap_types::pre_asap::QueryExpr;
 use asap_types::types::AccuracyTarget;
 
 /// PromQL exposes its evaluation time as Unix seconds, whereas SQL exposes
@@ -11,10 +11,21 @@ use asap_types::types::AccuracyTarget;
 /// but must remain distinguishable in the shared IR and type inference.
 #[tokio::test]
 async fn promql_eval_time_and_sql_current_timestamp_remain_distinct() {
-    let promql = lower_promql("time()", AccuracyTarget::Exact).expect("lower PromQL time()");
-    assert!(matches!(promql, QueryExpr::EvalTimestamp));
-    let promql_schema = promql.output_schema().expect("PromQL time() schema");
-    assert_eq!(promql_schema.fields[0].dtype, DataType::Float64);
+    let promql = lower_promql_root("time()", AccuracyTarget::Exact).expect("lower PromQL time()");
+    assert!(
+        matches!(
+            promql,
+            asap_types::ir::QueryRoot::Scalar(ScalarExpr::EvalTimestamp)
+        ),
+        "expected a bare evaluation-time scalar, got {promql:?}"
+    );
+    assert_eq!(
+        ScalarExpr::EvalTimestamp
+            .scalar_type(&Schema::default())
+            .unwrap()
+            .0,
+        DataType::Float64
+    );
 
     let catalog = SqlCatalog::new().with_table(
         "metrics",
@@ -27,13 +38,14 @@ async fn promql_eval_time_and_sql_current_timestamp_remain_distinct() {
     )
     .await
     .expect("lower SQL CURRENT_TIMESTAMP");
-    let QueryExpr::Project { cols, .. } = sql else {
+    let Some(NonASAPOp::Project { cols, child, .. }) = sql.non_asap() else {
         panic!("expected SQL projection, got {sql:?}");
     };
-    assert!(matches!(&cols[0].expr, QueryExpr::CurrentTimestamp));
-    let sql_schema = cols[0]
+    assert!(matches!(&cols[0].expr, ScalarExpr::CurrentTimestamp));
+    let (sql_dtype, _) = cols[0]
         .expr
-        .output_schema()
-        .expect("SQL CURRENT_TIMESTAMP schema");
-    assert_eq!(sql_schema.fields[0].dtype, DataType::Timestamp);
+        .scalar_type(&child.schema)
+        .expect("SQL CURRENT_TIMESTAMP type");
+    assert_eq!(sql_dtype, DataType::Timestamp);
+    assert_eq!(sql.schema.fields[0].dtype, DataType::Timestamp);
 }
diff --git a/crates/integration-tests/tests/kll_pane_execution.rs b/crates/integration-tests/tests/kll_pane_execution.rs
index b48d14bf7..4869d681b 100644
--- a/crates/integration-tests/tests/kll_pane_execution.rs
+++ b/crates/integration-tests/tests/kll_pane_execution.rs
@@ -1,7 +1,7 @@
 //! Maintenance -> stored pane state -> independently bound query execution.
 mod physical_common;
 use asap_physical_operators::{
-    operators::{Operator, ReadoutQuery},
+    operators::{Operator, SummaryEvaluation},
     physical_planner::{CompiledPhysicalDAG, InputContract, Source},
     plan::{PhysicalDAG, PhysicalOperator, PlanProperties},
     runtime::{Input, Limits, OutputStream, RunContext, Scope},
@@ -32,8 +32,8 @@ fn family(k: u32) -> FieldDataType {
 }
 fn raw_schema() -> SchemaRef {
     Arc::new(Schema {
-        closed: true,
         unique_keys: vec![],
+        closed: false,
         fields: vec![Field {
             table: None,
             name: "value".into(),
@@ -98,11 +98,11 @@ fn restore(schema: SchemaRef, states: &[Arc<dyn AggregateCore>]) -> Batch {
     )
     .unwrap()
 }
-fn readout(schema: SchemaRef, q: f64) -> Operator {
-    Operator::readout(
+fn evaluation(schema: SchemaRef, q: f64) -> Operator {
+    Operator::evaluation(
         schema,
         0,
-        ReadoutQuery::Sketch(SketchStatistic::Quantile { q }),
+        SummaryEvaluation::Sketch(SketchStatistic::Quantile { q }),
     )
     .unwrap()
 }
@@ -159,8 +159,8 @@ fn five_panes_roundtrip_and_shared_merge_runs_once() {
                 ),
             ),
             (6, (vec![5], merge.clone())),
-            (7, (vec![6], readout(schema.clone(), 0.5))),
-            (8, (vec![6], readout(schema.clone(), 0.99))),
+            (7, (vec![6], evaluation(schema.clone(), 0.5))),
+            (8, (vec![6], evaluation(schema.clone(), 0.99))),
         ]),
         vec![6, 7, 8],
     )
@@ -247,8 +247,10 @@ fn five_panes_roundtrip_and_shared_merge_runs_once() {
             },
         )
         .unwrap();
-        dag.add(2, vec![1], readout(schema.clone(), 0.5)).unwrap();
-        dag.add(3, vec![1], readout(schema.clone(), 0.99)).unwrap();
+        dag.add(2, vec![1], evaluation(schema.clone(), 0.5))
+            .unwrap();
+        dag.add(3, vec![1], evaluation(schema.clone(), 0.99))
+            .unwrap();
         let outputs = block_on(futures::future::join_all(
             dag.execute(
                 &[2, 3],
diff --git a/crates/integration-tests/tests/nested.rs b/crates/integration-tests/tests/nested.rs
index 1e3e34ebd..26ac23a24 100644
--- a/crates/integration-tests/tests/nested.rs
+++ b/crates/integration-tests/tests/nested.rs
@@ -1,8 +1,8 @@
 //! Multi-node pipeline tests — nested `Aggregate`, `TimeRange`, `BinaryOp`, and `Scan`.
 //!
 //! Key invariant: `rate`/`increase` are label-preserving (per-series), so an
-//! outer `Aggregate.by` resolves its group keys against the inner aggregate's
-//! output schema, which still carries all label columns.
+//! outer `Aggregate` reduction resolves its group keys against the inner
+//! aggregate's output schema, which still carries all label columns.
 //!
 //! Label column ordering is always alphabetical, so in a query that references
 //! both `job` and `status`:
@@ -13,56 +13,107 @@ use std::time::Duration;
 
 use asap_integration_tests::fixtures::lower_promql;
 use asap_integration_tests::fixtures::metric_schema;
+use asap_types::ir::{
+    BinaryOperator, ExprSemantics, NonASAPOp, OperatorNode, Predicate, ScalarExpr, TimeRangeKind,
+};
 use asap_types::pre_asap::{
-    AggIntent, ArithmeticOpKind, AtModifier, BinaryOpKind, CompareOpKind, GroupKeys, Predicate,
-    PromQLVectorSetOpKind, QueryExpr, Reduction, ScalarValue, Source, TimeShift, VectorMatch,
-    VectorMatchKind,
+    AggIntent, ArithmeticOpKind, AtModifier, BinaryOpKind, CompareOpKind, GroupKeys,
+    PromQLVectorSetOpKind, Reduction, ScalarValue, Source, TimeShift, VectorMatch, VectorMatchKind,
 };
 use asap_types::types::AccuracyTarget;
 
-fn lower(q: &str) -> QueryExpr {
+fn lower(q: &str) -> Rc<OperatorNode> {
     lower_promql(q, AccuracyTarget::Exact).unwrap_or_else(|e| panic!("lower failed for {q:?}: {e}"))
 }
 
-fn agg(by: Vec<usize>, intent: AggIntent, child: QueryExpr) -> QueryExpr {
-    QueryExpr::Aggregate {
+fn node(op: NonASAPOp) -> Rc<OperatorNode> {
+    OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(op))
+        .expect("fixture node derives its schema")
+}
+
+fn scan(metric: &str, predicates: Vec<Predicate>, labels: &[&str]) -> Rc<OperatorNode> {
+    node(NonASAPOp::Scan {
+        source: Source::TimeSeries {
+            metric: metric.into(),
+        },
+        predicates,
+        schema: metric_schema(labels),
+    })
+}
+
+fn instant(child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+    node(NonASAPOp::TimeRange {
+        range: Duration::from_secs(1),
+        kind: TimeRangeKind::Instant,
+        child,
+    })
+}
+
+fn range(secs: u64, child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+    node(NonASAPOp::TimeRange {
+        range: Duration::from_secs(secs),
+        kind: TimeRangeKind::Range,
+        child,
+    })
+}
+
+fn eq_pred(col_id: usize, value: &str) -> Predicate {
+    Predicate(ScalarExpr::Compare {
+        left: Box::new(ScalarExpr::Column(col_id)),
+        op: CompareOpKind::Eq,
+        right: Box::new(ScalarExpr::Literal(ScalarValue::Utf8(value.into()))),
+        semantics: ExprSemantics::Promql,
+    })
+}
+
+fn agg(by: Vec<usize>, intent: AggIntent, child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+    node(NonASAPOp::Aggregate {
         reduction: Reduction::by(by),
         measures: vec![intent],
         output_names: vec!["".into()],
         filters: vec![],
         having: None,
-        child: Rc::new(child),
-    }
+        child,
+    })
 }
 
-fn agg_per_entity(intent: AggIntent, child: QueryExpr) -> QueryExpr {
-    QueryExpr::Aggregate {
+fn agg_per_entity(intent: AggIntent, child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+    node(NonASAPOp::Aggregate {
         reduction: Reduction::PerEntity,
         measures: vec![intent],
         output_names: vec!["".into()],
         filters: vec![],
         having: None,
-        child: Rc::new(child),
-    }
+        child,
+    })
+}
+
+fn binary(
+    kind: BinaryOpKind,
+    vector_match: Option<VectorMatch>,
+    lhs: Rc<OperatorNode>,
+    rhs: Rc<OperatorNode>,
+) -> Rc<OperatorNode> {
+    node(NonASAPOp::BinaryOp {
+        operator: BinaryOperator {
+            checked_relative_division: false,
+            checked_finite_division: false,
+            kind,
+            vector_match,
+        },
+        return_bool: false,
+        lhs,
+        rhs,
+    })
 }
 
 // #22 — sum by job over rate; outer by=[2] resolves against rate's
 //   label-preserving output schema [ts, value, job]
 #[test]
 fn q22_sum_by_job_over_rate() {
-    let scan = QueryExpr::Scan {
-        source: Source::TimeSeries {
-            metric: "http_requests_total".into(),
-        },
-        predicates: vec![],
-        schema: metric_schema(&["job"]),
-    };
     let inner_rate = agg_per_entity(
         AggIntent::Rate,
-        QueryExpr::TimeRange {
-            range: Duration::from_secs(300),
-            child: Rc::new(scan),
-        },
+        range(300, scan("http_requests_total", vec![], &["job"])),
     );
     let expected = agg(vec![2], AggIntent::Sum { col: None }, inner_rate);
     assert_eq!(
@@ -76,25 +127,12 @@ fn q22_sum_by_job_over_rate() {
 //   predicate on status (col 3); group key job (col 2)
 #[test]
 fn q23_sum_by_job_over_filtered_scan() {
-    let scan = QueryExpr::Scan {
-        source: Source::TimeSeries {
-            metric: "http_requests_total".into(),
-        },
-        predicates: vec![Predicate(Rc::new(QueryExpr::Compare {
-            left: Rc::new(QueryExpr::Column(3)),
-            op: CompareOpKind::Eq,
-            right: Rc::new(QueryExpr::Literal(ScalarValue::Utf8("200".into()))),
-        }))],
-        schema: metric_schema(&["job", "status"]),
-    };
-    let expected = agg(
-        vec![2],
-        AggIntent::Sum { col: None },
-        QueryExpr::TimeRange {
-            range: Duration::from_secs(1),
-            child: Rc::new(scan),
-        },
+    let scan = scan(
+        "http_requests_total",
+        vec![eq_pred(3, "200")],
+        &["job", "status"],
     );
+    let expected = agg(vec![2], AggIntent::Sum { col: None }, instant(scan));
     assert_eq!(
         lower(r#"sum by (job) (http_requests_total{status="200"})"#),
         expected
@@ -108,54 +146,30 @@ fn q23_sum_by_job_over_filtered_scan() {
 //     schema [ts, value, job]; outer by=[2] (job)
 #[test]
 fn q25_div_over_complex_sub_dags() {
-    let lhs_scan = QueryExpr::Scan {
-        source: Source::TimeSeries {
-            metric: "http_requests_total".into(),
-        },
-        predicates: vec![Predicate(Rc::new(QueryExpr::Compare {
-            left: Rc::new(QueryExpr::Column(3)),
-            op: CompareOpKind::Eq,
-            right: Rc::new(QueryExpr::Literal(ScalarValue::Utf8("200".into()))),
-        }))],
-        schema: metric_schema(&["job", "status"]),
-    };
+    let lhs_scan = scan(
+        "http_requests_total",
+        vec![eq_pred(3, "200")],
+        &["job", "status"],
+    );
     let lhs = agg(
         vec![2],
         AggIntent::Sum { col: None },
-        agg_per_entity(
-            AggIntent::Rate,
-            QueryExpr::TimeRange {
-                range: Duration::from_secs(300),
-                child: Rc::new(lhs_scan),
-            },
-        ),
+        agg_per_entity(AggIntent::Rate, range(300, lhs_scan)),
     );
 
-    let rhs_scan = QueryExpr::Scan {
-        source: Source::TimeSeries {
-            metric: "http_errors_total".into(),
-        },
-        predicates: vec![],
-        schema: metric_schema(&["job"]),
-    };
+    let rhs_scan = scan("http_errors_total", vec![], &["job"]);
     let rhs = agg(
         vec![2],
         AggIntent::Sum { col: None },
-        agg_per_entity(
-            AggIntent::Rate,
-            QueryExpr::TimeRange {
-                range: Duration::from_secs(300),
-                child: Rc::new(rhs_scan),
-            },
-        ),
+        agg_per_entity(AggIntent::Rate, range(300, rhs_scan)),
     );
 
-    let expected = QueryExpr::BinaryOp {
-        op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Div),
-        lhs: Rc::new(lhs),
-        rhs: Rc::new(rhs),
-        vector_match: None,
-    };
+    let expected = binary(
+        BinaryOpKind::Arithmetic(ArithmeticOpKind::Div),
+        None,
+        lhs,
+        rhs,
+    );
     assert_eq!(
         lower(
             r#"sum by (job) (rate(http_requests_total{status="200"}[5m])) / sum by (job) (rate(http_errors_total[5m]))"#
@@ -171,19 +185,9 @@ fn q25_div_over_complex_sub_dags() {
 //   label-preserving output schema; the outer `max` has no grouping.
 #[test]
 fn q27_max_over_sum_by_job_over_rate() {
-    let scan = QueryExpr::Scan {
-        source: Source::TimeSeries {
-            metric: "http_requests_total".into(),
-        },
-        predicates: vec![],
-        schema: metric_schema(&["job"]),
-    };
     let inner_rate = agg_per_entity(
         AggIntent::Rate,
-        QueryExpr::TimeRange {
-            range: Duration::from_secs(300),
-            child: Rc::new(scan),
-        },
+        range(300, scan("http_requests_total", vec![], &["job"])),
     );
     let sum_by_job = agg(vec![2], AggIntent::Sum { col: None }, inner_rate);
     let expected = agg(vec![], AggIntent::Max { col: None }, sum_by_job);
@@ -201,25 +205,12 @@ fn q27_max_over_sum_by_job_over_rate() {
 //   Scan schema: [ts(0), value(1), group(2), job(3)] (labels alphabetical).
 #[test]
 fn q53_outer_group_key_absent_from_nested_aggregate() {
-    let scan = QueryExpr::Scan {
-        source: Source::TimeSeries {
-            metric: "http_requests".into(),
-        },
-        predicates: vec![Predicate(Rc::new(QueryExpr::Compare {
-            left: Rc::new(QueryExpr::Column(3)),
-            op: CompareOpKind::Eq,
-            right: Rc::new(QueryExpr::Literal(ScalarValue::Utf8("api-server".into()))),
-        }))],
-        schema: metric_schema(&["group", "job"]),
-    };
-    let inner = agg(
-        vec![2],
-        AggIntent::Sum { col: None },
-        QueryExpr::TimeRange {
-            range: Duration::from_secs(1),
-            child: Rc::new(scan),
-        },
+    let scan = scan(
+        "http_requests",
+        vec![eq_pred(3, "api-server")],
+        &["group", "job"],
     );
+    let inner = agg(vec![2], AggIntent::Sum { col: None }, instant(scan));
     let expected = agg(vec![], AggIntent::Sum { col: None }, inner);
     assert_eq!(
         lower(r#"sum(sum by (group)(http_requests{job="api-server"})) by (job)"#),
@@ -236,33 +227,26 @@ fn q53_outer_group_key_absent_from_nested_aggregate() {
 //   parser's default `ignoring([])` match modifier.
 #[test]
 fn q52_outer_name_label_over_binary_op() {
-    let side = |metric: &str, env: &str| QueryExpr::TimeRange {
-        range: Duration::from_secs(1),
-        child: Rc::new(QueryExpr::Scan {
-            source: Source::TimeSeries {
-                metric: metric.into(),
-            },
-            predicates: vec![Predicate(Rc::new(QueryExpr::Compare {
-                left: Rc::new(QueryExpr::Column(2)), // env
-                op: CompareOpKind::Eq,
-                right: Rc::new(QueryExpr::Literal(ScalarValue::Utf8(env.into()))),
-            }))],
-            schema: metric_schema(&["env", "__name__"]),
-        }),
+    let side = |metric: &str, env: &str| {
+        instant(scan(
+            metric,
+            vec![eq_pred(2, env)], // env
+            &["env", "__name__"],
+        ))
     };
     let expected = agg(
         vec![3], // __name__
         AggIntent::Sum { col: None },
-        QueryExpr::BinaryOp {
-            op: BinaryOpKind::Set(PromQLVectorSetOpKind::Or),
-            lhs: Rc::new(side("metric_a", "1")),
-            rhs: Rc::new(side("metric_b", "2")),
-            vector_match: Some(VectorMatch {
+        binary(
+            BinaryOpKind::Set(PromQLVectorSetOpKind::Or),
+            Some(VectorMatch {
                 kind: VectorMatchKind::Ignoring,
                 labels: vec![],
                 grouping: None,
             }),
-        },
+            side("metric_a", "1"),
+            side("metric_b", "2"),
+        ),
     );
     assert_eq!(
         lower(r#"sum by (__name__)(metric_a{env="1"} or metric_b{env="2"})"#),
@@ -276,28 +260,18 @@ fn q52_outer_name_label_over_binary_op() {
 //   the inner rate is label-preserving. Scan schema [ts(0), value(1), instance(2)].
 #[test]
 fn q39_sum_without_instance_over_rate() {
-    let scan = QueryExpr::Scan {
-        source: Source::TimeSeries {
-            metric: "http_requests_total".into(),
-        },
-        predicates: vec![],
-        schema: metric_schema(&["instance"]),
-    };
     let inner_rate = agg_per_entity(
         AggIntent::Rate,
-        QueryExpr::TimeRange {
-            range: Duration::from_secs(300),
-            child: Rc::new(scan),
-        },
+        range(300, scan("http_requests_total", vec![], &["instance"])),
     );
-    let expected = QueryExpr::Aggregate {
+    let expected = node(NonASAPOp::Aggregate {
         reduction: Reduction::Reduce(GroupKeys::without(vec![2])), // exclude `instance`
         measures: vec![AggIntent::Sum { col: None }],
         output_names: vec!["".into()],
         filters: vec![],
         having: None,
-        child: Rc::new(inner_rate),
-    };
+        child: inner_rate,
+    });
     assert_eq!(
         lower("sum without (instance) (rate(http_requests_total[5m]))"),
         expected,
@@ -310,35 +284,25 @@ fn q39_sum_without_instance_over_rate() {
 #[test]
 fn q40_week_over_week_offset() {
     let rate_over = |shift: Option<i64>| {
-        let scan = QueryExpr::Scan {
-            source: Source::TimeSeries { metric: "m".into() },
-            predicates: vec![],
-            schema: metric_schema(&[]),
-        };
+        let scan = scan("m", vec![], &[]);
         let ranged = match shift {
-            Some(ms) => QueryExpr::TimeShift {
+            Some(ms) => node(NonASAPOp::TimeShift {
                 shift: TimeShift {
                     offset_ms: ms,
                     at: None,
                 },
-                child: Rc::new(scan),
-            },
+                child: scan,
+            }),
             None => scan,
         };
-        agg_per_entity(
-            AggIntent::Rate,
-            QueryExpr::TimeRange {
-                range: Duration::from_secs(300),
-                child: Rc::new(ranged),
-            },
-        )
-    };
-    let expected = QueryExpr::BinaryOp {
-        op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Sub),
-        lhs: Rc::new(rate_over(None)),
-        rhs: Rc::new(rate_over(Some(604_800_000))), // 1w
-        vector_match: None,
+        agg_per_entity(AggIntent::Rate, range(300, ranged))
     };
+    let expected = binary(
+        BinaryOpKind::Arithmetic(ArithmeticOpKind::Sub),
+        None,
+        rate_over(None),
+        rate_over(Some(604_800_000)), // 1w
+    );
     assert_eq!(lower("rate(m[5m]) - rate(m[5m] offset 1w)"), expected,);
 }
 
@@ -346,22 +310,13 @@ fn q40_week_over_week_offset() {
 //   (seconds → ms); a bare selector wrapped in a `TimeShift` carrying the anchor.
 #[test]
 fn q40_at_modifier_absolute() {
-    let expected = QueryExpr::TimeRange {
-        range: Duration::from_secs(1),
-        child: Rc::new(QueryExpr::TimeShift {
-            shift: TimeShift {
-                offset_ms: 0,
-                at: Some(AtModifier::Timestamp(1_609_746_000_000)),
-            },
-            child: Rc::new(QueryExpr::Scan {
-                source: Source::TimeSeries {
-                    metric: "up".into(),
-                },
-                predicates: vec![],
-                schema: metric_schema(&[]),
-            }),
-        }),
-    };
+    let expected = instant(node(NonASAPOp::TimeShift {
+        shift: TimeShift {
+            offset_ms: 0,
+            at: Some(AtModifier::Timestamp(1_609_746_000_000)),
+        },
+        child: scan("up", vec![], &[]),
+    }));
     assert_eq!(lower("up @ 1609746000"), expected);
 }
 
@@ -370,24 +325,12 @@ fn q40_at_modifier_absolute() {
 //   so outer sum by job still finds job at col 2
 #[test]
 fn q24_sum_by_job_over_rate_over_filtered_scan() {
-    let scan = QueryExpr::Scan {
-        source: Source::TimeSeries {
-            metric: "http_requests_total".into(),
-        },
-        predicates: vec![Predicate(Rc::new(QueryExpr::Compare {
-            left: Rc::new(QueryExpr::Column(3)),
-            op: CompareOpKind::Eq,
-            right: Rc::new(QueryExpr::Literal(ScalarValue::Utf8("200".into()))),
-        }))],
-        schema: metric_schema(&["job", "status"]),
-    };
-    let inner_rate = agg_per_entity(
-        AggIntent::Rate,
-        QueryExpr::TimeRange {
-            range: Duration::from_secs(300),
-            child: Rc::new(scan),
-        },
+    let scan = scan(
+        "http_requests_total",
+        vec![eq_pred(3, "200")],
+        &["job", "status"],
     );
+    let inner_rate = agg_per_entity(AggIntent::Rate, range(300, scan));
     let expected = agg(vec![2], AggIntent::Sum { col: None }, inner_rate);
     assert_eq!(
         lower(r#"sum by (job) (rate(http_requests_total{status="200"}[5m]))"#),
@@ -403,35 +346,25 @@ fn q24_sum_by_job_over_rate_over_filtered_scan() {
 //   the whole spine survives verbatim and the schema stays label-preserving.
 #[test]
 fn q27_nested_subquery_prometheus_docs_example() {
-    let scan = QueryExpr::Scan {
-        source: Source::TimeSeries {
-            metric: "distance_covered_total".into(),
-        },
-        predicates: vec![],
-        schema: metric_schema(&[]),
-    };
     let rate = agg_per_entity(
         AggIntent::Rate,
-        QueryExpr::TimeRange {
-            range: Duration::from_secs(5),
-            child: Rc::new(scan),
-        },
+        range(5, scan("distance_covered_total", vec![], &[])),
     );
     let deriv = agg_per_entity(
         AggIntent::Deriv,
-        QueryExpr::PromqlSubquery {
+        node(NonASAPOp::PromqlSubquery {
             range: Duration::from_secs(30),
             resolution: Some(Duration::from_secs(5)),
-            child: Rc::new(rate),
-        },
+            child: rate,
+        }),
     );
     let expected = agg_per_entity(
         AggIntent::Max { col: None },
-        QueryExpr::PromqlSubquery {
+        node(NonASAPOp::PromqlSubquery {
             range: Duration::from_secs(600),
             resolution: None,
-            child: Rc::new(deriv),
-        },
+            child: deriv,
+        }),
     );
     assert_eq!(
         lower("max_over_time(deriv(rate(distance_covered_total[5s])[30s:5s])[10m:])"),
diff --git a/crates/integration-tests/tests/operator_design_examples.rs b/crates/integration-tests/tests/operator_design_examples.rs
new file mode 100644
index 000000000..8325ad92b
--- /dev/null
+++ b/crates/integration-tests/tests/operator_design_examples.rs
@@ -0,0 +1,401 @@
+//! #511 examples: source text → unified dag → summary rewrite → flat export.
+use asap_frontend_sql::{lower_sql, SqlCatalog};
+use asap_types::ir::{ASAPOp, NonASAPOp, Operator, OperatorNode, ScalarExpr};
+use asap_types::post_asap::{
+    ExactKind, ExactParams, FieldDataType, GroupingStrategy, SummaryUpdate,
+};
+use asap_types::pre_asap::{AggIntent, ColumnRef, DataType, Field, Schema};
+use asap_types::types::AccuracyTarget;
+use std::rc::Rc;
+mod physical_common;
+
+fn catalog() -> SqlCatalog {
+    SqlCatalog::new()
+        .with_table(
+            "requests",
+            Schema::new(vec![
+                Field::plain("bytes", DataType::Int64, true),
+                Field::plain("status", DataType::Int64, false),
+            ]),
+        )
+        .with_table(
+            "lineitem",
+            Schema::new(vec![Field::plain("l_quantity", DataType::Int64, false)]),
+        )
+}
+
+/// The SQL scalar example keeps column scopes and a Boolean row predicate.
+#[tokio::test]
+async fn sql_filter_projection_example() {
+    let root = lower_sql(
+        "SELECT l_quantity * 2 AS q2 FROM lineitem WHERE l_quantity > 10",
+        &catalog(),
+        AccuracyTarget::Exact,
+    )
+    .await
+    .unwrap();
+    root.validate_structure().unwrap();
+    assert_eq!(
+        root.schema.fields[0],
+        Field::plain("q2", DataType::Int64, false)
+    );
+    assert!(
+        matches!(root.expect_non_asap(),NonASAPOp::Project { cols,.. } if matches!(cols[0].expr,ScalarExpr::Arithmetic { .. }))
+    );
+    let wire = physical_common::compile_physical_asap_dag(&root).unwrap();
+    wire.validate().unwrap();
+    assert_eq!(wire.nodes.len(), OperatorNode::reachable(&root).len());
+}
+
+/// SUM's evaluation preserves integer type and SQL NULL behavior across the rewrite.
+#[tokio::test]
+async fn sql_sum_projection_before_and_after_summary_rewrite() {
+    let root = lower_sql(
+        "SELECT SUM(bytes) + 1 AS total_bytes FROM requests WHERE status = 200",
+        &catalog(),
+        AccuracyTarget::Exact,
+    )
+    .await
+    .unwrap();
+    root.validate_structure().unwrap();
+    assert_eq!(
+        root.schema.fields[0],
+        Field::plain("total_bytes", DataType::Int64, true)
+    );
+    fn rewrite(node: &Rc<OperatorNode>) -> Rc<OperatorNode> {
+        if let Some(NonASAPOp::Aggregate {
+            child,
+            reduction,
+            measures,
+            ..
+        }) = node.non_asap()
+        {
+            let [AggIntent::Sum { col: Some(column) }] = measures.as_slice() else {
+                panic!()
+            };
+            let state = Rc::new(
+                OperatorNode::new(Operator::ASAP(ASAPOp::SummaryAgg {
+                    child: Rc::clone(child),
+                    family: FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum),
+                    input: SummaryUpdate::column(ColumnRef::Named(
+                        child.schema.fields[*column].name.clone(),
+                    )),
+                    reduction: reduction.clone(),
+                    grouping: GroupingStrategy::default(),
+                    filter: None,
+                }))
+                .unwrap(),
+            );
+            let finalize = std::rc::Rc::new(
+                OperatorNode::with_schema(
+                    asap_types::ir::Operator::ASAP(ASAPOp::FinalizeExactAccumulator {
+                        child: state,
+                    }),
+                    node.schema.clone(),
+                )
+                .with_guarantee(None),
+            );
+            return finalize;
+        }
+        Rc::new(node.map_children(rewrite).unwrap())
+    }
+    let rewritten = rewrite(&root);
+    rewritten.validate_structure().unwrap();
+    assert_eq!(rewritten.schema, root.schema);
+    let dag = OperatorNode::reachable(&rewritten);
+    assert!(dag
+        .iter()
+        .any(|n| matches!(n.asap(), Some(ASAPOp::SummaryAgg { .. }))));
+    assert!(dag
+        .iter()
+        .any(|n| matches!(n.asap(), Some(ASAPOp::FinalizeExactAccumulator { .. }))));
+    let wire = physical_common::compile_physical_asap_dag(&rewritten).unwrap();
+    wire.validate().unwrap();
+    assert_eq!(wire.nodes.len(), dag.len());
+    let json = serde_json::to_string(&wire).unwrap();
+    assert!(!json.contains("KeepPreAsap") && !json.contains("ScalarBridge"));
+}
+
+/// Scalar subqueries survive normalization with shared, visible producers.
+#[tokio::test]
+async fn sql_scalar_subquery_retains_its_cardinality_contract() {
+    for query in [
+        "SELECT (SELECT bytes FROM requests) AS v FROM lineitem",
+        "SELECT l_quantity NOT IN (SELECT bytes FROM requests) AS present FROM lineitem",
+    ] {
+        let root = lower_sql(query, &catalog(), AccuracyTarget::Exact)
+            .await
+            .unwrap();
+        root.validate_structure().unwrap();
+        assert!(root.children().len() > 1);
+        let wire = physical_common::compile_physical_asap_dag(&root).unwrap();
+        assert!(wire
+            .edges
+            .iter()
+            .any(|e| e.role == asap_types::ir::export::EdgeRole::ScalarRef));
+    }
+}
+
+/// Execute the SQL SUM example for nonempty, empty and all-NULL populations.
+#[tokio::test]
+async fn sql_sum_example_executes_with_sql_null_semantics() {
+    use asap_physical_operators::{
+        physical_planner::{compile, InputContract, Source},
+        runtime::{Limits, RunContext, Scope},
+        sources::{DataSources, MemorySource},
+        values::{Batch, Value},
+    };
+    use futures::StreamExt;
+    use std::{collections::BTreeMap, sync::Arc};
+    let root = lower_sql(
+        "SELECT SUM(bytes) + 1 AS total_bytes FROM requests WHERE status = 200",
+        &catalog(),
+        AccuracyTarget::Exact,
+    )
+    .await
+    .unwrap();
+    let logical_scan = OperatorNode::reachable(&root)
+        .into_iter()
+        .find(|node| matches!(node.non_asap(), Some(NonASAPOp::Scan { .. })))
+        .unwrap();
+    let NonASAPOp::Scan { source, .. } = logical_scan.expect_non_asap() else {
+        panic!()
+    };
+    let wire = physical_common::compile_physical_asap_dag(&root).unwrap();
+    let scan = wire
+        .nodes
+        .iter()
+        .find(|node| {
+            matches!(
+                &node.payload,
+                asap_types::ir::export::PhysicalASAPOperatorPayload::Relational {
+                    operator: asap_types::ir::export::NonASAPOpKind::Scan { .. }
+                }
+            )
+        })
+        .unwrap();
+    let schema = Arc::new(scan.output_schema.clone());
+    let plan = compile(
+        &wire,
+        BTreeMap::from([(u64::from(scan.id.0), InputContract::bounded(schema.clone()))]),
+        &[u64::from(wire.roots[0].0)],
+    )
+    .unwrap();
+    for (rows, expected) in [
+        (
+            vec![
+                vec![Value::Int64(10), Value::Int64(200)],
+                vec![Value::Int64(20), Value::Int64(500)],
+                vec![Value::Null, Value::Int64(200)],
+            ],
+            Value::Int64(11),
+        ),
+        (vec![], Value::Null),
+        (vec![vec![Value::Null, Value::Int64(200)]], Value::Null),
+    ] {
+        let mut sources = DataSources::default();
+        sources
+            .register(
+                source.clone(),
+                Arc::new(
+                    MemorySource::new(
+                        schema.clone(),
+                        vec![Batch::try_new(schema.clone(), rows).unwrap()],
+                    )
+                    .unwrap(),
+                ),
+            )
+            .unwrap();
+        let bound = plan
+            .instantiate(BTreeMap::from([(
+                u64::from(scan.id.0),
+                Box::new(sources.bind(&logical_scan).unwrap()) as Source<'_>,
+            )]))
+            .unwrap();
+        let mut stream = bound
+            .execute(
+                plan.roots(),
+                RunContext::new(
+                    Scope::Query {
+                        evaluation_time_ms: 300_000,
+                        revision: 1,
+                    },
+                    Limits::default(),
+                )
+                .unwrap(),
+            )
+            .unwrap()
+            .remove(0);
+        let mut rows = vec![];
+        while let Some(batch) = stream.next().await {
+            rows.extend(batch.unwrap().rows().iter().cloned());
+        }
+        assert_eq!(rows.len(), 1);
+        assert_eq!(rows[0].len(), 1);
+        match (&rows[0][0], expected) {
+            (Value::Null, Value::Null) => {}
+            (Value::Int64(actual), Value::Int64(expected)) => assert_eq!(*actual, expected),
+            other => panic!("{other:?}"),
+        }
+    }
+}
+
+/// Empty window frames and filtered groups can yield NULL even on non-NULL input.
+#[tokio::test]
+async fn sql_window_and_filtered_aggregate_types() {
+    for query in [
+        "SELECT SUM(l_quantity) OVER (ORDER BY l_quantity ROWS BETWEEN 2 PRECEDING AND 1 PRECEDING) AS s FROM lineitem",
+        "SELECT MIN(l_quantity) OVER (ORDER BY l_quantity ROWS BETWEEN 2 PRECEDING AND 1 PRECEDING) AS s FROM lineitem",
+        "SELECT SUM(l_quantity) FILTER (WHERE l_quantity < 0) AS s FROM lineitem GROUP BY l_quantity",
+    ] {
+        let root = lower_sql(query, &catalog(), AccuracyTarget::Exact).await.unwrap();
+        root.validate_structure().unwrap();
+        assert_eq!(root.schema.fields[0], Field::plain("s", DataType::Int64, true), "{query}");
+    }
+}
+
+/// A real query batch selects one shared SUM producer, retains two result roots,
+/// and executes both selected plans. No replacement dag is constructed by the test.
+#[tokio::test]
+async fn batch_planning_replaces_and_shares_summary_operators() {
+    use asap_aware_mapping::cost_model::{Cost, DefaultCostModel};
+    use asap_aware_mapping::pass::PlanningModels;
+    use asap_aware_mapping::{
+        CostModel, CostRate, LifecycleInput, SummaryMaintenanceLifecycleCapabilities,
+        SummaryMaintenanceLifecycleCostInputs,
+    };
+    use asap_physical_operators::{
+        physical_planner::{compile, InputContract},
+        runtime::Scope,
+        values::{Batch, Value},
+    };
+    use asap_planner::{e2e_plan, FrontendInput, UserInput};
+    use asap_types::post_asap::SketchAlgorithm;
+    use asap_types::workload::*;
+    use std::{collections::BTreeMap, sync::Arc};
+    struct Costs;
+    impl CostModel for Costs {
+        fn rank_candidates(
+            &self,
+            intent: &AggIntent,
+            candidates: &[SketchAlgorithm],
+        ) -> Vec<SketchAlgorithm> {
+            DefaultCostModel.rank_candidates(intent, candidates)
+        }
+        fn summary_maintenance_lifecycle_cost_inputs(
+            &self,
+            _: &OperatorNode,
+        ) -> SummaryMaintenanceLifecycleCostInputs {
+            SummaryMaintenanceLifecycleCostInputs {
+                build_cost: Some(Cost(1.0)),
+                maintenance_cost_per_update: Some(Cost::ZERO),
+                summary_read_cost: Some(Cost::ZERO),
+                retention_cost_rate: Some(CostRate(0.0)),
+                retirement_cost: Some(Cost::ZERO),
+            }
+        }
+        fn raw_query_recompute_cost(&self, _: &OperatorNode) -> Option<Cost> {
+            Some(Cost(1000.0))
+        }
+    }
+    let queries = [
+        "SELECT SUM(bytes) + 1 AS result FROM requests",
+        "SELECT SUM(bytes) * 2 AS result FROM requests",
+    ];
+    let workload = PlanningWorkload {
+        query_workload: QueryWorkload {
+            language: QueryLanguage::SQL(SqlDialect::DataFusionSQL),
+            query_batch: Some(
+                queries
+                    .iter()
+                    .map(|query| BatchEntry {
+                        query: Query((*query).into()),
+                        requirements: QueryRequirements {
+                            accuracy: AccuracyRequirement::Explicit(AccuracyTarget::Exact),
+                            ..Default::default()
+                        },
+                        predictability: Predictability::Unknown,
+                        invocations: 2,
+                        execute_at: None,
+                        time_selection: TimeSelection::default(),
+                    })
+                    .collect(),
+            ),
+            repeating_queries: None,
+        },
+        data_workload: Some(DataWorkload {
+            arrival: DataArrival::AtRest,
+            ..Default::default()
+        }),
+    };
+    let catalog = SqlCatalog::new().with_table(
+        "requests",
+        Schema::new(vec![Field::plain("bytes", DataType::Float64, false)]),
+    );
+    let output = e2e_plan(UserInput::new(
+        &workload,
+        FrontendInput::Sql { catalog: &catalog },
+        PlanningModels::builtin().with_cost(&Costs),
+        LifecycleInput::new(0, SummaryMaintenanceLifecycleCapabilities::default()),
+    ))
+    .await
+    .unwrap();
+    assert_eq!(output.entry_indices(), [0, 1]);
+    assert_eq!(output.roots().len(), 2);
+    let states: Vec<_> = output
+        .operators()
+        .into_iter()
+        .filter(|n| matches!(n.asap(), Some(ASAPOp::SummaryAgg { .. })))
+        .collect();
+    assert_eq!(states.len(), 1, "the batch owns one shared SUM state");
+    for (plan, expected) in output.plans.iter().zip([31.0, 60.0]) {
+        assert!(!plan.plan.selected_raw_recompute);
+        let root = &plan.plan.root;
+        root.validate_structure().unwrap();
+        assert!(OperatorNode::reachable(root)
+            .iter()
+            .any(|n| Rc::ptr_eq(n, &states[0])));
+        let wire = physical_common::compile_physical_asap_dag(root).unwrap();
+        let scan = wire
+            .nodes
+            .iter()
+            .find(|n| {
+                matches!(
+                    n.payload,
+                    asap_types::ir::export::PhysicalASAPOperatorPayload::Relational {
+                        operator: asap_types::ir::export::NonASAPOpKind::Scan { .. }
+                    }
+                )
+            })
+            .unwrap();
+        let schema = Arc::new(scan.output_schema.clone());
+        let program = compile(
+            &wire,
+            BTreeMap::from([(u64::from(scan.id.0), InputContract::bounded(schema.clone()))]),
+            &[u64::from(wire.roots[0].0)],
+        )
+        .unwrap();
+        let result = physical_common::execute(
+            &program,
+            BTreeMap::from([(
+                u64::from(scan.id.0),
+                Batch::try_new(
+                    schema,
+                    vec![vec![Value::Float64(10.0)], vec![Value::Float64(20.0)]],
+                )
+                .unwrap(),
+            )]),
+            Scope::Query {
+                evaluation_time_ms: 0,
+                revision: 1,
+            },
+        );
+        let rows: Vec<_> = result[0].iter().flat_map(|batch| batch.rows()).collect();
+        assert_eq!(rows.len(), 1);
+        assert!(
+            matches!(rows[0][0], Value::Float64(v) if v == expected),
+            "{:?}",
+            rows
+        );
+    }
+}
diff --git a/crates/integration-tests/tests/operator_sharing.rs b/crates/integration-tests/tests/operator_sharing.rs
new file mode 100644
index 000000000..6a87a879a
--- /dev/null
+++ b/crates/integration-tests/tests/operator_sharing.rs
@@ -0,0 +1,195 @@
+//! Acceptance tests for operator sharing (issue #468): one operator IR
+//! before and after ASAP optimization, so non-ASAP operators sit both above
+//! and below summary operators, can share inputs with them, and can carry
+//! summaries below set operators.
+//!
+//! Each test drives SQL text through `lower_sql` → `search_workload` →
+//! global selection → `assemble_selected_dag`, the pipeline
+//! `sql_to_post_asap.rs` uses.
+
+use std::rc::Rc;
+
+use asap_aware_mapping::{search_workload, DefaultCostModel};
+use asap_frontend_sql::{lower_sql, SqlCatalog};
+use asap_integration_tests::post_asap::post_asap_dag;
+use asap_types::ir::{ASAPOp, NonASAPOp, Operator, OperatorNode};
+use asap_types::pre_asap::schema::{DataType, Field, Schema};
+use asap_types::types::AccuracyTarget;
+
+fn col(name: &str, dtype: DataType) -> Field {
+    Field::plain(name, dtype, false)
+}
+
+/// TPC-H `lineitem`, as `frontend-sql/tests/data_quality_check/tpch_deequ.rs`
+/// declares it (DECIMAL columns as `Float64`, no time index, no keys).
+fn catalog() -> SqlCatalog {
+    SqlCatalog::new().with_table(
+        "lineitem",
+        Schema::new(vec![
+            col("l_orderkey", DataType::Int64),
+            col("l_partkey", DataType::Int64),
+            col("l_suppkey", DataType::Int64),
+            col("l_linenumber", DataType::Int64),
+            col("l_quantity", DataType::Float64),
+            col("l_extendedprice", DataType::Float64),
+            col("l_discount", DataType::Float64),
+            col("l_tax", DataType::Float64),
+            col("l_returnflag", DataType::Utf8),
+            col("l_linestatus", DataType::Utf8),
+            col("l_shipdate", DataType::Date),
+            col("l_commitdate", DataType::Date),
+            col("l_receiptdate", DataType::Date),
+            col("l_shipinstruct", DataType::Utf8),
+            col("l_shipmode", DataType::Utf8),
+            col("l_comment", DataType::Utf8),
+        ]),
+    )
+}
+
+/// Lower `sql`, search, select with the default cost model and assemble the
+/// selected post-ASAP DAG.
+async fn plan(sql: &str, accuracy: AccuracyTarget) -> Rc<OperatorNode> {
+    let pre = lower_sql(sql, &catalog(), accuracy)
+        .await
+        .unwrap_or_else(|e| panic!("lower failed for {sql:?}: {e}"));
+    let space = search_workload(vec![("query", pre)]);
+    let selection = space.global_selection(&DefaultCostModel);
+    selection
+        .assemble_selected_dag(&space.roots[0].1)
+        .expect("materialization failed")
+        .expect("root must be discovered")
+}
+
+/// Every unique node reachable from `root` whose operator matches `pred`.
+fn find_all(
+    root: &Rc<OperatorNode>,
+    pred: impl Fn(&OperatorNode) -> bool,
+) -> Vec<Rc<OperatorNode>> {
+    OperatorNode::reachable(root)
+        .into_iter()
+        .filter(|node| pred(node))
+        .collect()
+}
+
+fn is_summary_evaluation(node: &OperatorNode) -> bool {
+    matches!(
+        node.operator,
+        Operator::ASAP(
+            ASAPOp::SummaryEstimate { .. }
+                | ASAPOp::FinalizeExactAccumulator { .. }
+                | ASAPOp::EvaluatePopulation { .. }
+        )
+    )
+}
+
+fn is_scan(node: &OperatorNode) -> bool {
+    matches!(node.non_asap(), Some(NonASAPOp::Scan { .. }))
+}
+
+/// The first node reached through single-input non-ASAP operators below
+/// `node` (inclusive) that is not one: where an operator chain meets a
+/// summary or a multi-input operator.
+fn through_unary_non_asap(node: &Rc<OperatorNode>) -> &Rc<OperatorNode> {
+    match node.non_asap().map(|op| op.children()) {
+        Some(children) if children.len() == 1 => through_unary_non_asap(children[0]),
+        _ => node,
+    }
+}
+
+// #468 problem 1: the Project above the summary evaluation and the Scan below
+// it are both plain NonASAP nodes (no post-ASAP-only wrapper variant).
+#[ignore = "planner chooses no summary here: Avg has no summary realization, so the Aggregate stays a logical pass-through"]
+#[tokio::test]
+async fn project_above_and_scan_below_a_summary_are_both_non_asap_nodes() {
+    let root = plan(
+        "WITH metric AS (SELECT avg(CASE WHEN l_quantity BETWEEN 1 AND 50 THEN 1.0 ELSE 0.0 END) \
+         AS in_range FROM lineitem) SELECT in_range, in_range = 1.0 AS ok FROM metric",
+        AccuracyTarget::Exact,
+    )
+    .await;
+    // The root is the outer SELECT list: a NonASAP Project.
+    assert!(
+        matches!(root.operator, Operator::NonASAP(NonASAPOp::Project { .. })),
+        "root must be the outer Project, got {:?}",
+        root.operator
+    );
+    // A summary evaluation sits below the Project chain.
+    let evaluation = through_unary_non_asap(&root);
+    assert!(
+        is_summary_evaluation(evaluation),
+        "the Project chain must read a summary, got {:?}",
+        evaluation.operator
+    );
+    // Below the summary the Scan is the same NonASAP operator a front end emits.
+    let scans = find_all(evaluation, is_scan);
+    assert_eq!(scans.len(), 1, "one lineitem Scan below the summary");
+    assert!(!scans[0].is_asap());
+    // The flat plan exports (time first, wire 6).
+    post_asap_dag(&root);
+}
+
+// #468 problem 2: the exact aggregate and the sketch read one shared Scan
+// (`Rc::ptr_eq`), not two copies.
+#[ignore = "waits for the binding rule splitting multi-measure aggregates"]
+#[tokio::test]
+async fn exact_aggregate_and_sketch_share_one_scan() {
+    let root = plan(
+        "SELECT avg(l_extendedprice), approx_percentile_cont(l_discount, 0.99) FROM lineitem",
+        AccuracyTarget::Epsilon(0.01),
+    )
+    .await;
+    let exact = find_all(&root, |node| {
+        matches!(node.non_asap(), Some(NonASAPOp::Aggregate { .. }))
+    });
+    let sketch = find_all(&root, |node| {
+        matches!(node.asap(), Some(ASAPOp::SummaryAgg { .. }))
+    });
+    assert_eq!(exact.len(), 1, "one exact Aggregate for avg: {root:?}");
+    assert_eq!(
+        sketch.len(),
+        1,
+        "one sketch SummaryAgg for the percentile: {root:?}"
+    );
+    let scan_under = |node: &Rc<OperatorNode>| {
+        let scans = find_all(node, is_scan);
+        assert_eq!(scans.len(), 1, "one Scan under {:?}", node.operator);
+        Rc::clone(&scans[0])
+    };
+    assert!(
+        Rc::ptr_eq(&scan_under(&exact[0]), &scan_under(&sketch[0])),
+        "the exact aggregate and the sketch must read one shared Scan"
+    );
+}
+
+// #468 problem 3: a summary can sit below a set operator — each side of the
+// UNION ALL holds its own SummaryEstimate.
+#[tokio::test]
+async fn each_side_of_union_all_holds_a_summary_estimate() {
+    let root = plan(
+        "SELECT approx_distinct(l_partkey) FROM lineitem \
+         UNION ALL SELECT approx_distinct(l_suppkey) FROM lineitem",
+        AccuracyTarget::Epsilon(0.01),
+    )
+    .await;
+    // The SQL front end lowers UNION ALL to `SetOp { all: true }`.
+    let Some(NonASAPOp::SetOp {
+        all: true,
+        left,
+        right,
+        ..
+    }) = root.non_asap()
+    else {
+        panic!("root must be the UNION ALL SetOp, got {:?}", root.operator)
+    };
+    for side in [left, right] {
+        let estimates = find_all(side, |node| {
+            matches!(node.asap(), Some(ASAPOp::SummaryEstimate { .. }))
+        });
+        assert!(
+            !estimates.is_empty(),
+            "UNION ALL side has no SummaryEstimate: {:?}",
+            side.operator
+        );
+    }
+    post_asap_dag(&root);
+}
diff --git a/crates/integration-tests/tests/physical_common/mod.rs b/crates/integration-tests/tests/physical_common/mod.rs
index 93bebd338..e23e9721d 100644
--- a/crates/integration-tests/tests/physical_common/mod.rs
+++ b/crates/integration-tests/tests/physical_common/mod.rs
@@ -7,6 +7,7 @@ use asap_physical_operators::{
 use futures::{executor::block_on, StreamExt};
 use std::collections::BTreeMap;
 
+#[allow(dead_code)]
 pub fn execute(
     plan: &CompiledPhysicalDAG,
     inputs: BTreeMap<u64, Batch>,
@@ -40,3 +41,15 @@ pub fn execute(
         .await
     })
 }
+
+#[allow(dead_code)]
+pub fn compile_physical_asap_dag(
+    root: &std::rc::Rc<asap_types::ir::OperatorNode>,
+) -> Result<asap_types::ir::export::PhysicalASAPDAG, Box<dyn std::error::Error>> {
+    let root = asap_types::ir::apply_lifecycle_timings(
+        root,
+        &Default::default(),
+        &mut Default::default(),
+    )?;
+    Ok(asap_types::ir::export::compile_physical_asap_dag(&root)?)
+}
diff --git a/crates/integration-tests/tests/precompute_raw_samples.rs b/crates/integration-tests/tests/precompute_raw_samples.rs
index 9937469cc..4bc8f7ace 100644
--- a/crates/integration-tests/tests/precompute_raw_samples.rs
+++ b/crates/integration-tests/tests/precompute_raw_samples.rs
@@ -1,10 +1,14 @@
 //! Planner-selected summaries over raw samples compile as precompute DAGs
 //! and produce the same estimates as feeding their kernel sample by sample.
+mod physical_common;
+use asap_types::ir::export::{PhysicalASAPDAG, PhysicalASAPOperatorPayload};
+use asap_types::ir::OperatorNode;
+use physical_common::compile_physical_asap_dag;
 use std::{collections::BTreeMap, collections::BTreeSet, rc::Rc, sync::Arc};
 
 use asap_aware_mapping::cost_model::DefaultCostModel;
 use asap_aware_mapping::{
-    search_workload, Replacement, ReplacementStrategy, ReplacementSubDAG, SketchAlgorithmStrategy,
+    search_workload, ASAPStrategies, Replacement, ReplacementStrategy, ReplacementSubDAG,
     TargetSubDAG,
 };
 use asap_integration_tests::fixtures::lower_promql;
@@ -18,11 +22,10 @@ use asap_physical_operators::{
     AggregateCore, KeyByLabelValues, Statistic,
 };
 use asap_types::post_asap::{
-    compile_post_asap_dag, EntityIdentity, ExactKind, FieldDataType, PostAsapDAG,
-    PostAsapOperatorPayload, SketchAlgorithm, SketchStatistic, SummaryInputExpr, SummaryNode,
+    EntityIdentity, ExactKind, FieldDataType, SketchAlgorithm, SketchStatistic, SummaryInputExpr,
     SummaryUpdate,
 };
-use asap_types::pre_asap::{expr_ir::ColumnRef, query_expr::Reduction};
+use asap_types::pre_asap::{expr_ir::ColumnRef, Reduction};
 use asap_types::types::AccuracyTarget;
 use futures::{executor::block_on, StreamExt};
 
@@ -51,14 +54,14 @@ fn canonical(labels: &Series) -> Series {
 
 /// Every Planner candidate for `query`: the searched selection plus each
 /// summary replacement of the root.
-fn candidates(query: &str, accuracy: AccuracyTarget) -> Vec<Rc<SummaryNode>> {
-    let root = Rc::new(lower_promql(query, accuracy).expect("lowering failed"));
-    let mut result = SketchAlgorithmStrategy::default_cost_model()
+fn candidates(query: &str, accuracy: AccuracyTarget) -> Vec<Rc<OperatorNode>> {
+    let root = lower_promql(query, accuracy).expect("lowering failed");
+    let mut result = ASAPStrategies::default_cost_model()
         .replacements(&TargetSubDAG::new(&root))
         .into_iter()
         .filter_map(|candidate| match candidate {
             ReplacementSubDAG {
-                replacement: Replacement::Summary(node),
+                replacement: Replacement::SubDAG(node),
                 ..
             } => Some(node),
             _ => None,
@@ -75,10 +78,10 @@ fn candidates(query: &str, accuracy: AccuracyTarget) -> Vec<Rc<SummaryNode>> {
 }
 
 /// Raw-input summary nodes: `(dag, raw source id, summary id)`.
-fn raw_summaries(dag: &PostAsapDAG) -> Vec<(u64, u64)> {
+fn raw_summaries(dag: &PhysicalASAPDAG) -> Vec<(u64, u64)> {
     dag.nodes
         .iter()
-        .filter(|node| matches!(node.payload, PostAsapOperatorPayload::SummaryAgg { .. }))
+        .filter(|node| matches!(node.payload, PhysicalASAPOperatorPayload::SummaryAgg { .. }))
         .filter_map(|node| {
             let inputs = dag
                 .edges
@@ -89,8 +92,13 @@ fn raw_summaries(dag: &PostAsapDAG) -> Vec<(u64, u64)> {
                 return None;
             };
             let source = dag.nodes.iter().find(|n| n.id == edge.producer)?;
-            matches!(source.payload, PostAsapOperatorPayload::Fallback { .. })
-                .then_some((u64::from(source.id.0), u64::from(node.id.0)))
+            matches!(
+                source.payload,
+                PhysicalASAPOperatorPayload::Relational {
+                    operator: asap_types::ir::export::NonASAPOpKind::TimeRange { .. }
+                }
+            )
+            .then_some((u64::from(source.id.0), u64::from(node.id.0)))
         })
         .collect()
 }
@@ -114,7 +122,7 @@ fn samples() -> Vec<(Series, i64, f64)> {
 }
 
 fn execute(
-    dag: &PostAsapDAG,
+    dag: &PhysicalASAPDAG,
     source: u64,
     root: u64,
     rows: &[(Series, i64, f64)],
@@ -240,7 +248,7 @@ fn weight(update: &SummaryUpdate, value: f64) -> f64 {
 }
 
 /// Estimates that identify a state's content for comparison.
-fn readouts(state: &dyn AggregateCore, family: &FieldDataType) -> Vec<f64> {
+fn evaluations(state: &dyn AggregateCore, family: &FieldDataType) -> Vec<f64> {
     if let Some(exact) = state.as_any().downcast_ref::<ExactAccumulator>() {
         let FieldDataType::ExactAggregate(kind, _) = family else {
             unreachable!()
@@ -255,7 +263,7 @@ fn readouts(state: &dyn AggregateCore, family: &FieldDataType) -> Vec<f64> {
             other => panic!("unexpected exact kind {other:?}"),
         };
         return vec![exact
-            .readout(statistic, None, None::<&KeyByLabelValues>)
+            .evaluation(statistic, None, None::<&KeyByLabelValues>)
             .unwrap()
             .unwrap()];
     }
@@ -277,7 +285,7 @@ fn readouts(state: &dyn AggregateCore, family: &FieldDataType) -> Vec<f64> {
 /// or the family when it has no native state.
 fn check(
     query: &str,
-    dag: &PostAsapDAG,
+    dag: &PhysicalASAPDAG,
     source: u64,
     root: u64,
     rows: &[(Series, i64, f64)],
@@ -287,7 +295,7 @@ fn check(
         .iter()
         .find(|n| u64::from(n.id.0) == root)
         .unwrap();
-    let PostAsapOperatorPayload::SummaryAgg {
+    let PhysicalASAPOperatorPayload::SummaryAgg {
         family,
         input,
         reduction,
@@ -370,8 +378,8 @@ fn check(
     for (labels, state) in actual {
         let reference = expected[&labels].snapshot_accumulator();
         assert_eq!(
-            readouts(state.as_ref(), family),
-            readouts(reference.as_ref(), family),
+            evaluations(state.as_ref(), family),
+            evaluations(reference.as_ref(), family),
             "{query}: {labels:?}"
         );
     }
@@ -413,7 +421,7 @@ fn raw_sample_summaries_compile_and_match_their_kernels() {
     let mut checked = BTreeMap::new();
     for (query, accuracy) in queries {
         for candidate in candidates(query, accuracy.clone()) {
-            let dag = compile_post_asap_dag(&candidate).unwrap();
+            let dag = compile_physical_asap_dag(&candidate).unwrap();
             for (source, root) in raw_summaries(&dag) {
                 match check(query, &dag, source, root, &rows) {
                     Ok(family) => {
@@ -459,21 +467,21 @@ fn raw_sample_summaries_compile_and_match_their_kernels() {
 
 /// Replace the raw summary of `sum by (service) (sum_over_time(m[5m]))` with
 /// another update, keeping its raw input and reduction.
-fn grouped_raw_summary(family: FieldDataType, input: SummaryUpdate) -> (PostAsapDAG, u64, u64) {
+fn grouped_raw_summary(family: FieldDataType, input: SummaryUpdate) -> (PhysicalASAPDAG, u64, u64) {
     let candidate = candidates(
         "sum by (service) (sum_over_time(m[5m]))",
         AccuracyTarget::Exact,
     )
     .pop()
     .unwrap();
-    let mut dag = compile_post_asap_dag(&candidate).unwrap();
+    let mut dag = compile_physical_asap_dag(&candidate).unwrap();
     let (source, root) = raw_summaries(&dag)[0];
     let node = dag
         .nodes
         .iter_mut()
         .find(|n| u64::from(n.id.0) == root)
         .unwrap();
-    let PostAsapOperatorPayload::SummaryAgg {
+    let PhysicalASAPOperatorPayload::SummaryAgg {
         family: old,
         input: update,
         ..
@@ -587,7 +595,7 @@ fn raw_sample_heaps_resolve_items_from_labels() {
 // `without` grouping over raw samples drops the listed labels and `__name__`.
 #[test]
 fn raw_sample_without_grouping_drops_labels_and_name() {
-    use asap_types::pre_asap::query_expr::GroupKeys;
+    use asap_types::pre_asap::GroupKeys;
     let family =
         FieldDataType::ExactAggregate(ExactKind::Sum, asap_types::post_asap::ExactParams::Sum);
     let (mut dag, source, root) =
@@ -607,7 +615,7 @@ fn raw_sample_without_grouping_drops_labels_and_name() {
         .iter_mut()
         .find(|n| u64::from(n.id.0) == root)
         .unwrap();
-    let PostAsapOperatorPayload::SummaryAgg { reduction, .. } = &mut node.payload else {
+    let PhysicalASAPOperatorPayload::SummaryAgg { reduction, .. } = &mut node.payload else {
         unreachable!()
     };
     *reduction = Reduction::Reduce(GroupKeys::without(vec![service]));
diff --git a/crates/integration-tests/tests/promql_numeric_regressions.rs b/crates/integration-tests/tests/promql_numeric_regressions.rs
index 692fe9c7a..3ec4d8eac 100644
--- a/crates/integration-tests/tests/promql_numeric_regressions.rs
+++ b/crates/integration-tests/tests/promql_numeric_regressions.rs
@@ -1,36 +1,41 @@
-//! Numeric regression fixtures: actual PromQL lowering plus numeric update/readout checks.
+//! Numeric regression fixtures: actual PromQL lowering plus numeric update/evaluation checks.
 //! The count/sum interpreter below verifies planner update semantics, not a deployed backend.
-use asap_aware_mapping::{Replacement, ReplacementStrategy, SketchAlgorithmStrategy, TargetSubDAG};
+use asap_aware_mapping::replacement::is_logical_rewrite;
+use asap_aware_mapping::{ASAPStrategies, Replacement, ReplacementStrategy, TargetSubDAG};
 use asap_integration_tests::fixtures::lower_promql;
-use asap_types::post_asap::{
-    compile_post_asap_dag, ExactKind, FieldDataType, SummaryExpr, SummaryInputExpr, SummaryNode,
-    SummaryUpdate,
-};
+use asap_integration_tests::post_asap::post_asap_dag;
+use asap_types::ir::{ASAPOp, NonASAPOp, Operator, OperatorNode};
+use asap_types::post_asap::{ExactKind, FieldDataType, SummaryInputExpr, SummaryUpdate};
 use asap_types::pre_asap::{ColumnRef, Reduction};
 use asap_types::types::AccuracyTarget;
 use std::rc::Rc;
 
-fn plan(query: &str, accuracy: AccuracyTarget) -> Rc<SummaryNode> {
-    let pre = Rc::new(lower_promql(query, accuracy).unwrap());
-    SketchAlgorithmStrategy::default_cost_model()
+fn plan(query: &str, accuracy: AccuracyTarget) -> Rc<OperatorNode> {
+    let pre = lower_promql(query, accuracy).unwrap();
+    ASAPStrategies::default_cost_model()
         .replacements(&TargetSubDAG::new(&pre))
         .into_iter()
         .find_map(|r| match r.replacement {
-            Replacement::Summary(n) => Some(n),
+            // A bound decision: a summary DAG or a kept (exact) sub-DAG.
+            Replacement::SubDAG(n) if !is_logical_rewrite(&n) => Some(n),
             _ => None,
         })
-        .unwrap_or_else(|| asap_aware_mapping::replacement::keep_pre_asap(&pre).unwrap())
+        .unwrap_or_else(|| asap_aware_mapping::replacement::retain_exact(&pre).unwrap())
 }
-fn aggregate(node: &SummaryNode) -> (&FieldDataType, &SummaryUpdate, &Reduction) {
-    match &node.expr {
-        SummaryExpr::SummaryAgg {
+fn aggregate(node: &OperatorNode) -> (&FieldDataType, &SummaryUpdate, &Reduction) {
+    match &node.operator {
+        Operator::ASAP(ASAPOp::SummaryAgg {
             family,
             input,
             reduction,
             ..
-        } => (family, input, reduction),
-        SummaryExpr::SummaryEstimate { summary_input, .. } => aggregate(summary_input),
-        SummaryExpr::ValueOperation { child, .. } => aggregate(child),
+        }) => (family, input, reduction),
+        Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) => aggregate(summary_input),
+        Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child }) => aggregate(child),
+        // A value operation (Project/Filter/Sort/Limit/...) over the state.
+        Operator::NonASAP(op) if op.children().len() == 1 && node.contains_asap() => {
+            aggregate(op.children()[0])
+        }
         other => panic!("not a maintained accumulator: {other:?}"),
     }
 }
@@ -63,7 +68,7 @@ fn count_up_counts_targets_even_when_values_repeat_or_change_sign() {
             3.
         );
     }
-    compile_post_asap_dag(&node).unwrap();
+    post_asap_dag(&node);
 }
 
 /// Ten samples give count ten, whereas sum retains the signed sample values.
@@ -81,7 +86,7 @@ fn window_counts_and_sums_distinguish_one_zero_three_and_negative_values() {
             let got: f64 = (0..10).map(|_| contribution(family, update, value)).sum();
             assert_eq!(got, if is_count { 10. } else { value * 10. });
         }
-        compile_post_asap_dag(&node).unwrap();
+        post_asap_dag(&node);
     }
 }
 
@@ -97,7 +102,7 @@ fn sum_rate_and_increase_have_real_exact_accumulator_nodes() {
         let (family, _, _) = aggregate(&node);
         assert!(matches!(family, FieldDataType::ExactAggregate(k, _) if *k == kind));
         assert!(node.guarantee.as_ref().unwrap().is_exact());
-        compile_post_asap_dag(&node).unwrap();
+        post_asap_dag(&node);
     }
 }
 
@@ -109,11 +114,12 @@ fn checked_ratio_must_not_certify_cross_zero_interpolation() {
         AccuracyTarget::Epsilon(0.01),
     );
     assert!(
-        matches!(node.expr, SummaryExpr::BinaryOp { .. }),
+        matches!(node.operator, Operator::NonASAP(NonASAPOp::BinaryOp { .. }))
+            && node.contains_asap(),
         "direct quantile ratio should remain an available candidate"
     );
     assert!(node.guarantee.is_none());
-    compile_post_asap_dag(&node).unwrap();
+    post_asap_dag(&node);
     // Keep the actual signed-sketch counterexample: division guards alone pass
     // even though the quantile interpolation does not preserve relative error.
     let alpha = (0.01 - 8.0 * f64::EPSILON) / 2.01;
@@ -148,20 +154,20 @@ fn quantile_over_temporal_average_keeps_a_legal_candidate() {
     ] {
         let node = plan(query, AccuracyTarget::Epsilon(0.01));
         assert!(
-            !matches!(node.expr, SummaryExpr::KeepPreAsap(_)),
+            node.contains_asap(),
             "outer sketch candidate must survive: {query}"
         );
-        let SummaryExpr::SummaryEstimate { summary_input, .. } = &node.expr else {
-            panic!("outer sketch readout")
+        let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &node.operator else {
+            panic!("outer sketch evaluation")
         };
-        let SummaryExpr::SummaryAgg { child, .. } = &summary_input.expr else {
+        let Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) = &summary_input.operator else {
             panic!("outer sketch state")
         };
         assert!(
-            matches!(child.expr, SummaryExpr::KeepPreAsap(_)),
+            !child.contains_asap(),
             "guarded expression must retain native maintenance input"
         );
-        compile_post_asap_dag(&node).unwrap();
+        post_asap_dag(&node);
     }
 }
 
@@ -195,7 +201,7 @@ fn sketch_counts_use_unit_weights_and_signed_sums_keep_value_weights() {
     use asap_aware_mapping::accuracy::{DefaultAccuracyModel, EqualSplitAllocator};
     use asap_aware_mapping::cost_model::DefaultCostModel;
     use asap_types::post_asap::{NonNegativeWeightProof, SketchAlgorithm, WeightDomain};
-    let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+    let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
         &DefaultCostModel,
         &DefaultAccuracyModel,
         &EqualSplitAllocator,
@@ -207,7 +213,7 @@ fn sketch_counts_use_unit_weights_and_signed_sums_keep_value_weights() {
         } else {
             "topk(1, sum_over_time(up[5m]))"
         };
-        let pre = Rc::new(lower_promql(query, AccuracyTarget::Epsilon(0.01)).unwrap());
+        let pre = lower_promql(query, AccuracyTarget::Epsilon(0.01)).unwrap();
         let candidates = strategy.replacements(&TargetSubDAG::new(&pre));
         let wanted = if is_count {
             SketchAlgorithm::CmsWithHeap
@@ -217,7 +223,7 @@ fn sketch_counts_use_unit_weights_and_signed_sums_keep_value_weights() {
         let node = candidates
             .iter()
             .find_map(|c| {
-                let Replacement::Summary(node) = &c.replacement else {
+                let Replacement::SubDAG(node) = &c.replacement else {
                     return None;
                 };
                 let (family, _, _) = aggregate(node);
@@ -240,7 +246,7 @@ fn sketch_counts_use_unit_weights_and_signed_sums_keep_value_weights() {
                 SummaryInputExpr::Column(ColumnRef::SampleValue)
             );
             for c in &candidates {
-                if let Replacement::Summary(n) = &c.replacement {
+                if let Replacement::SubDAG(n) = &c.replacement {
                     assert!(
                         !matches!(aggregate(n).0, FieldDataType::Sketch(kind, _) if kind.algorithm() == &SketchAlgorithm::CmsWithHeap)
                     );
@@ -271,6 +277,6 @@ fn sketch_counts_use_unit_weights_and_signed_sums_keep_value_weights() {
             };
             assert_eq!(got, if is_count { 10. } else { 10. * value });
         }
-        compile_post_asap_dag(node).unwrap();
+        post_asap_dag(node);
     }
 }
diff --git a/crates/integration-tests/tests/promql_to_post_asap.rs b/crates/integration-tests/tests/promql_to_post_asap.rs
index 97a08a0c4..9ce1d5d72 100644
--- a/crates/integration-tests/tests/promql_to_post_asap.rs
+++ b/crates/integration-tests/tests/promql_to_post_asap.rs
@@ -1,8 +1,8 @@
 //! End-to-end query-string → post-ASAP IR pin (issue #98).
 //!
-//! Drives the full pipeline — PromQL text → pre-ASAP `QueryExpr`
-//! (`lower_promql`) → post-ASAP `SummaryExpr` DAG (via
-//! `SketchAlgorithmStrategy::replacements`, see [`realize`] below) — and pins
+//! Drives the full pipeline — PromQL text → non-ASAP `OperatorNode`
+//! (`lower_promql`) → post-ASAP `OperatorNode` DAG (via
+//! `ASAPStrategies::replacements`, see [`realize`] below) — and pins
 //! the summary-bound shape node by node, including the family `(Kind,
 //! Params)` committed on each edge's schema.
 
@@ -13,67 +13,77 @@ use asap_aware_mapping::accuracy::{
     QuantileInputDomain,
 };
 use asap_aware_mapping::cost_model::DefaultCostModel;
-use asap_aware_mapping::replacement::{keep_pre_asap, RealizationError};
+use asap_aware_mapping::replacement::{is_logical_rewrite, retain_exact, RealizationError};
 use asap_aware_mapping::{
-    search_workload, search_workload_with_targets, AccuracyModel, Replacement, ReplacementStrategy,
-    ReplacementSubDAG, SketchAlgorithmStrategy, TargetSubDAG,
+    search_workload, search_workload_with_targets, ASAPStrategies, AccuracyModel, Replacement,
+    ReplacementStrategy, ReplacementSubDAG, TargetSubDAG,
 };
 use asap_integration_tests::fixtures::lower_promql;
+use asap_integration_tests::post_asap::{post_asap_dag, timed};
+use asap_types::ir::export::{NonASAPOpKind, PhysicalASAPOperatorPayload};
+use asap_types::ir::operator_properties::Reduction;
+use asap_types::ir::{ASAPOp, NonASAPOp, Operator, OperatorNode, ScalarExpr};
 use asap_types::post_asap::{
-    compile_post_asap_dag, CompositionOperator, EntityIdentity, ExactKind, ExactParams,
-    FieldDataType, GroupingStrategy, Schema, SketchAlgorithm, SketchKind, SketchParams,
-    SketchStatistic, SummaryExpr, SummaryInputExpr, SummaryNode, SummaryUpdate, ValueOperation,
+    CompositionOperator, EntityIdentity, ExactKind, ExactParams, FieldDataType, GroupingStrategy,
+    Schema, SketchAlgorithm, SketchKind, SketchParams, SketchStatistic, SummaryInputExpr,
+    SummaryUpdate,
 };
 use asap_types::pre_asap::expr_ir::ColumnRef;
-use asap_types::pre_asap::query_expr::{QueryExpr, Reduction};
 use asap_types::pre_asap::schema::DataType;
 use asap_types::types::AccuracyTarget;
 
-/// This crate has no "bind me one DAG" public API any more —
-/// `SketchAlgorithmStrategy::replacements` always returns every candidate, and
+/// This crate has no "bind me one tree" public API any more —
+/// `ASAPStrategies::replacements` always returns every candidate, and
 /// a caller decides what to keep. This test-only helper reproduces the
 /// take-the-first-(`cost_model`-preferred)-candidate pattern so the
 /// single-answer pins below don't all repeat it by hand.
-fn realize(expr: &QueryExpr) -> Result<Rc<SummaryNode>, RealizationError> {
-    let root = Rc::new(expr.clone());
-    let target = TargetSubDAG::new(&root);
-    match SketchAlgorithmStrategy::default_cost_model()
+fn realize(root: &Rc<OperatorNode>) -> Result<Rc<OperatorNode>, RealizationError> {
+    let target = TargetSubDAG::new(root);
+    match ASAPStrategies::default_cost_model()
         .replacements(&target)
         .into_iter()
         .next()
     {
+        // A bound decision (summary DAG or kept sub-DAG); a logical rewrite
+        // is not a binding, so it falls back to keeping the target.
         Some(ReplacementSubDAG {
-            replacement: Replacement::Summary(node),
+            replacement: Replacement::SubDAG(node),
             ..
-        }) => Ok(node),
-        _ => keep_pre_asap(&root),
+        }) if !is_logical_rewrite(&node) => Ok(node),
+        _ => retain_exact(root),
     }
+    .inspect(|node| {
+        node.validate_structure()
+            .expect("planned dag satisfies the unified IR contract")
+    })
 }
 
 #[test]
-fn distinct_over_time_offers_hll_cardinality_readout() {
+fn distinct_over_time_offers_hll_cardinality_evaluation() {
     // The real frontend must reach an existing HLL candidate without a
     // function-specific post-ASAP node or a sample-count rewrite.
-    let root = Rc::new(
-        lower_promql(
-            "distinct_over_time(cpu_usage{job=\"worker\"}[5m])",
-            AccuracyTarget::Epsilon(0.02),
-        )
-        .unwrap(),
-    );
-    let candidates =
-        SketchAlgorithmStrategy::default_cost_model().replacements(&TargetSubDAG::new(&root));
+    let root = lower_promql(
+        "distinct_over_time(cpu_usage{job=\"worker\"}[5m])",
+        AccuracyTarget::Epsilon(0.02),
+    )
+    .unwrap();
+    let candidates = ASAPStrategies::default_cost_model().replacements(&TargetSubDAG::new(&root));
+    for candidate in &candidates {
+        if let Replacement::SubDAG(node) = &candidate.replacement {
+            node.validate_structure().unwrap();
+        }
+    }
     assert!(candidates.iter().any(|candidate| {
-        let Replacement::Summary(node) = &candidate.replacement else { return false };
-        let SummaryExpr::SummaryEstimate { summary_input, query, .. } = &node.expr else { return false };
+        let Replacement::SubDAG(node) = &candidate.replacement else { return false };
+        let Some(ASAPOp::SummaryEstimate { summary_input, query, .. }) = node.asap() else { return false };
         matches!(query, SketchStatistic::Cardinality)
-            && matches!(&summary_input.expr, SummaryExpr::SummaryAgg { family: FieldDataType::Sketch(kind, _), .. }
+            && matches!(summary_input.asap(), Some(ASAPOp::SummaryAgg { family: FieldDataType::Sketch(kind, _), .. })
                 if kind.algorithm() == &SketchAlgorithm::Hll)
     }), "no HLL cardinality candidate: {candidates:?}");
 }
 
-fn lower_search_and_materialize(query: &str) -> Rc<SummaryNode> {
-    let pre = Rc::new(lower_promql(query, AccuracyTarget::Exact).expect("lowering failed"));
+fn lower_search_and_materialize(query: &str) -> Rc<OperatorNode> {
+    let pre = lower_promql(query, AccuracyTarget::Exact).expect("lowering failed");
     let space = search_workload(vec![("query", pre)]);
     let selection = space.global_selection(&DefaultCostModel);
     selection
@@ -88,36 +98,38 @@ fn value_ranked_topk_preserves_summary_children_in_post_asap_dag() {
         "topk(3, rate(cpu_seconds_total[5m]))",
         "topk by (job) (2, max_over_time(memory_bytes[6h]))",
     ] {
-        let root = lower_search_and_materialize(query);
-        let SummaryExpr::ValueOperation {
-            operation: ValueOperation::Limit { n, offset, .. },
+        let root = timed(&lower_search_and_materialize(query));
+        let Some(NonASAPOp::Limit {
+            n,
+            offset,
             child: sort,
             ..
-        } = &root.expr
+        }) = root.non_asap()
         else {
-            panic!("expected query-time Limit for {query}, got {:?}", root.expr);
+            panic!(
+                "expected query-time Limit for {query}, got {:?}",
+                root.operator
+            );
         };
-        assert!(*n > 0 && *offset == 0);
-        let SummaryExpr::ValueOperation {
-            operation: ValueOperation::Sort { .. },
-            child,
-            ..
-        } = &sort.expr
-        else {
+        assert_eq!(
+            root.timing,
+            Some(asap_types::post_asap::ExecutionTiming::QueryTime)
+        );
+        assert!(n.is_some_and(|n| n > 0) && *offset == 0);
+        let Some(NonASAPOp::Sort { child, .. }) = sort.non_asap() else {
             panic!("expected query-time Sort under Limit for {query}");
         };
-        let SummaryExpr::ValueOperation {
-            operation: ValueOperation::FinalizeExactAccumulator,
-            child: state,
-            ..
-        } = &child.expr
-        else {
+        assert_eq!(
+            sort.timing,
+            Some(asap_types::post_asap::ExecutionTiming::QueryTime)
+        );
+        let Some(ASAPOp::FinalizeExactAccumulator { child: state }) = child.asap() else {
             panic!(
                 "Sort must consume finalized values for {query}: {:?}",
-                child.expr
+                child.operator
             );
         };
-        assert!(matches!(state.expr, SummaryExpr::SummaryAgg { .. }));
+        assert!(matches!(state.asap(), Some(ASAPOp::SummaryAgg { .. })));
         assert!(child
             .schema
             .fields
@@ -135,9 +147,9 @@ fn exact_counter_weighted_topk_fails_closed_without_membership_certificate() {
     ] {
         let root = lower_search_and_materialize(query);
         assert!(
-            matches!(root.expr, SummaryExpr::KeepPreAsap(_)),
+            !root.contains_asap(),
             "exact target must not accept an uncertified membership sidecar for {query}: {:?}",
-            root.expr
+            root.operator
         );
     }
 }
@@ -146,23 +158,14 @@ fn exact_counter_weighted_topk_fails_closed_without_membership_certificate() {
 fn instant_topk_and_unsupported_child_remain_local_residuals() {
     for query in ["topk(3, memory_bytes)", "topk(3, deriv(memory_bytes[5m]))"] {
         let root = lower_search_and_materialize(query);
-        let SummaryExpr::ValueOperation {
-            operation: ValueOperation::Limit { .. },
-            child: sort,
-            ..
-        } = &root.expr
-        else {
+        let Some(NonASAPOp::Limit { child: sort, .. }) = root.non_asap() else {
             panic!("expected Limit for {query}");
         };
-        let SummaryExpr::ValueOperation {
-            child, operation, ..
-        } = &sort.expr
-        else {
+        let Some(NonASAPOp::Sort { child, .. }) = sort.non_asap() else {
             panic!("expected Sort for {query}");
         };
-        assert!(matches!(operation, ValueOperation::Sort { .. }));
         assert!(
-            matches!(child.expr, SummaryExpr::KeepPreAsap(_)),
+            !child.contains_asap(),
             "only the unsupported child should remain exact for {query}"
         );
     }
@@ -177,7 +180,7 @@ fn dtype<'a>(schema: &'a Schema, name: &str) -> &'a FieldDataType {
         .dtype
 }
 
-fn lower_and_realize(query: &str) -> Rc<SummaryNode> {
+fn lower_and_realize(query: &str) -> Rc<OperatorNode> {
     let pre = lower_promql(query, AccuracyTarget::Exact).expect("lowering failed");
     realize(&pre).expect("binding failed")
 }
@@ -186,19 +189,17 @@ fn lower_and_realize(query: &str) -> Rc<SummaryNode> {
 fn promql_binary_arithmetic_retains_two_summary_leaves() {
     for op in ["+", "-", "*", "/", "%", "^", "atan2"] {
         let root = lower_and_realize(&format!("rate(a[1m]) {op} rate(b[1m])"));
-        let SummaryExpr::BinaryOp { lhs, rhs, .. } = &root.expr else {
-            panic!("expected BinaryOp for {op}, got {:?}", root.expr);
+        let Some(NonASAPOp::BinaryOp { lhs, rhs, .. }) = root.non_asap() else {
+            panic!("expected BinaryOp for {op}, got {:?}", root.operator);
         };
         for operand in [lhs, rhs] {
-            let SummaryExpr::ValueOperation {
-                child,
-                operation: ValueOperation::FinalizeExactAccumulator,
-                ..
-            } = &operand.expr
-            else {
-                panic!("expected an explicit exact readout, got {:?}", operand.expr);
+            let Some(ASAPOp::FinalizeExactAccumulator { child }) = operand.asap() else {
+                panic!(
+                    "expected an explicit exact evaluation, got {:?}",
+                    operand.operator
+                );
             };
-            assert!(matches!(child.expr, SummaryExpr::SummaryAgg { .. }));
+            assert!(matches!(child.asap(), Some(ASAPOp::SummaryAgg { .. })));
         }
     }
 }
@@ -207,47 +208,36 @@ fn promql_binary_arithmetic_retains_two_summary_leaves() {
 fn value_ranked_topk_over_binary_ratio_finalizes_both_summary_operands() {
     let query = "topk(1, sum by(job)(increase(a[6h])) / sum by(job)(increase(b[6h])))";
     let root = lower_search_and_materialize(query);
-    let SummaryExpr::ValueOperation {
-        operation: ValueOperation::Limit {
-            n: 1, offset: 0, ..
-        },
+    let Some(NonASAPOp::Limit {
+        n: Some(1),
+        offset: 0,
         child: sort,
         ..
-    } = &root.expr
+    }) = root.non_asap()
     else {
-        panic!("expected Limit root, got {:?}", root.expr);
+        panic!("expected Limit root, got {:?}", root.operator);
     };
-    let SummaryExpr::ValueOperation {
-        operation: ValueOperation::Sort { .. },
-        child: binary,
-        ..
-    } = &sort.expr
-    else {
-        panic!("expected Sort below Limit, got {:?}", sort.expr);
+    let Some(NonASAPOp::Sort { child: binary, .. }) = sort.non_asap() else {
+        panic!("expected Sort below Limit, got {:?}", sort.operator);
     };
-    let SummaryExpr::BinaryOp { lhs, rhs, .. } = &binary.expr else {
-        panic!("expected BinaryOp below Sort, got {:?}", binary.expr);
+    let Some(NonASAPOp::BinaryOp { lhs, rhs, .. }) = binary.non_asap() else {
+        panic!("expected BinaryOp below Sort, got {:?}", binary.operator);
     };
     for operand in [lhs, rhs] {
-        let SummaryExpr::ValueOperation {
-            operation: ValueOperation::FinalizeExactAccumulator,
-            child,
-            ..
-        } = &operand.expr
-        else {
+        let Some(ASAPOp::FinalizeExactAccumulator { child }) = operand.asap() else {
             panic!(
                 "expected exact accumulator finalization, got {:?}",
-                operand.expr
+                operand.operator
             );
         };
-        assert!(matches!(child.expr, SummaryExpr::SummaryAgg { .. }));
+        assert!(matches!(child.asap(), Some(ASAPOp::SummaryAgg { .. })));
     }
 }
 
 struct SeparatedTopK;
 
 impl AccuracyEvidenceProvider for SeparatedTopK {
-    fn topk_max_distinct_items(&self, _: &QueryExpr) -> Option<u64> {
+    fn topk_max_distinct_items(&self, _: &OperatorNode) -> Option<u64> {
         Some(1000)
     }
 
@@ -271,14 +261,12 @@ impl AccuracyEvidenceProvider for SeparatedTopK {
 // Rate-weighted summaries must consume finalized rates, never raw counter deltas.
 #[test]
 fn grouped_rate_topk_consumes_finalized_rate_values() {
-    let root = Rc::new(
-        lower_promql(
-            "topk by(job)(2, sum by(service, job)(rate(m[1m])))",
-            AccuracyTarget::Epsilon(0.01),
-        )
-        .unwrap(),
-    );
-    let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+    let root = lower_promql(
+        "topk by(job)(2, sum by(service, job)(rate(m[1m])))",
+        AccuracyTarget::Epsilon(0.01),
+    )
+    .unwrap();
+    let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
         &DefaultCostModel,
         &DefaultAccuracyModel,
         &EqualSplitAllocator,
@@ -288,24 +276,31 @@ fn grouped_rate_topk_consumes_finalized_rate_values() {
         .replacements(&TargetSubDAG::new(&root))
         .into_iter()
         .find_map(|candidate| match candidate.replacement {
-            Replacement::Summary(node) if candidate.rationale.contains("CmsWithHeap") => Some(node),
+            Replacement::SubDAG(node) if candidate.rationale.contains("CmsWithHeap") => Some(node),
             _ => None,
         })
         .expect("rate-weighted CMS plan");
-    let dag = compile_post_asap_dag(&plan).unwrap();
+    let dag = post_asap_dag(&plan);
     assert!(!dag.nodes.iter().any(|node| matches!(
         node.payload,
-        asap_types::post_asap::PostAsapOperatorPayload::RelationalJoin { .. }
+        PhysicalASAPOperatorPayload::Relational {
+            operator: NonASAPOpKind::Join { .. }
+        }
     )));
-    let node = dag.nodes.iter().find(|node| matches!(&node.payload,
-        asap_types::post_asap::PostAsapOperatorPayload::SummaryAgg { family: FieldDataType::Sketch(kind, _), .. }
-        if kind.algorithm() == &SketchAlgorithm::CmsWithHeap)).unwrap();
+    let node = dag
+        .nodes
+        .iter()
+        .find(|node| {
+            matches!(&node.payload,
+        PhysicalASAPOperatorPayload::SummaryAgg { family: FieldDataType::Sketch(kind, _), .. }
+        if kind.algorithm() == &SketchAlgorithm::CmsWithHeap)
+        })
+        .unwrap();
     assert_eq!(
         node.output_state.timing,
         asap_types::post_asap::ExecutionTiming::QueryTime
     );
-    let asap_types::post_asap::PostAsapOperatorPayload::SummaryAgg { input, .. } = &node.payload
-    else {
+    let PhysicalASAPOperatorPayload::SummaryAgg { input, .. } = &node.payload else {
         unreachable!()
     };
     assert_eq!(
@@ -332,14 +327,12 @@ fn weighted_topk_keeps_candidates_with_missing_population_evidence() {
             SeparatedTopK.propagation_stats(op, family, query)
         }
     }
-    let root = Rc::new(
-        lower_promql(
-            "topk by(job)(2, sum by(service, job)(rate(m[1m])))",
-            AccuracyTarget::Epsilon(0.01),
-        )
-        .unwrap(),
-    );
-    let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+    let root = lower_promql(
+        "topk by(job)(2, sum by(service, job)(rate(m[1m])))",
+        AccuracyTarget::Epsilon(0.01),
+    )
+    .unwrap();
+    let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
         &DefaultCostModel,
         &DefaultAccuracyModel,
         &EqualSplitAllocator,
@@ -355,27 +348,24 @@ fn weighted_topk_keeps_candidates_with_missing_population_evidence() {
 // Unknown requirements must survive physical export for deployment to inspect.
 #[test]
 fn weighted_topk_exports_symbolic_evidence_requirements() {
-    let root = Rc::new(
-        lower_promql(
-            "topk by(job)(2, sum by(service, job)(rate(m[1m])))",
-            AccuracyTarget::EpsilonDelta {
-                epsilon: 0.01,
-                delta: 0.01,
-            },
-        )
-        .unwrap(),
-    );
-    let candidates =
-        SketchAlgorithmStrategy::default_cost_model().replacements(&TargetSubDAG::new(&root));
+    let root = lower_promql(
+        "topk by(job)(2, sum by(service, job)(rate(m[1m])))",
+        AccuracyTarget::EpsilonDelta {
+            epsilon: 0.01,
+            delta: 0.01,
+        },
+    )
+    .unwrap();
+    let candidates = ASAPStrategies::default_cost_model().replacements(&TargetSubDAG::new(&root));
     let candidate = candidates
         .iter()
         .find(|candidate| candidate.rationale.contains("CmsWithHeap"))
         .unwrap();
     assert!(candidate.has_missing_accuracy_evidence());
-    let Replacement::Summary(node) = &candidate.replacement else {
+    let Replacement::SubDAG(node) = &candidate.replacement else {
         panic!("summary candidate")
     };
-    let dag = compile_post_asap_dag(node).unwrap();
+    let dag = post_asap_dag(node);
     let exported = serde_json::to_string(&dag).unwrap();
     assert!(exported.contains("topk_max_distinct_items"));
     assert!(exported.contains("topk_membership_margin"));
@@ -387,18 +377,16 @@ fn weighted_topk_exports_symbolic_evidence_requirements() {
 fn weighted_topk_rejects_invalid_population_evidence() {
     struct InvalidPopulation;
     impl AccuracyEvidenceProvider for InvalidPopulation {
-        fn topk_max_distinct_items(&self, _: &QueryExpr) -> Option<u64> {
+        fn topk_max_distinct_items(&self, _: &OperatorNode) -> Option<u64> {
             Some(0)
         }
     }
-    let root = Rc::new(
-        lower_promql(
-            "topk by(job)(2, sum by(service, job)(rate(m[1m])))",
-            AccuracyTarget::Epsilon(0.01),
-        )
-        .unwrap(),
-    );
-    let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+    let root = lower_promql(
+        "topk by(job)(2, sum by(service, job)(rate(m[1m])))",
+        AccuracyTarget::Epsilon(0.01),
+    )
+    .unwrap();
+    let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
         &DefaultCostModel,
         &DefaultAccuracyModel,
         &EqualSplitAllocator,
@@ -415,17 +403,15 @@ fn rate_and_increase_topk_use_summary_scores_and_grouped_limits() {
         "topk by(job)(2, sum by(service, job)(rate(m[1m])))",
         "topk(2, sum by(job)(increase(m[6h])))",
     ] {
-        let root = Rc::new(
-            lower_promql(
-                query,
-                AccuracyTarget::EpsilonDelta {
-                    epsilon: 0.01,
-                    delta: 0.01,
-                },
-            )
-            .unwrap(),
-        );
-        let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+        let root = lower_promql(
+            query,
+            AccuracyTarget::EpsilonDelta {
+                epsilon: 0.01,
+                delta: 0.01,
+            },
+        )
+        .unwrap();
+        let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
             &DefaultCostModel,
             &DefaultAccuracyModel,
             &EqualSplitAllocator,
@@ -435,60 +421,50 @@ fn rate_and_increase_topk_use_summary_scores_and_grouped_limits() {
             .replacements(&TargetSubDAG::new(&root))
             .into_iter()
             .find_map(|candidate| match candidate.replacement {
-                Replacement::Summary(node) if candidate.rationale.contains("CmsWithHeap") => {
+                Replacement::SubDAG(node) if candidate.rationale.contains("CmsWithHeap") => {
                     Some(node)
                 }
                 _ => None,
             })
             .expect("weighted summary");
-        let SummaryExpr::ValueOperation {
+        let Some(NonASAPOp::Limit {
+            n: Some(2),
+            offset: 0,
+            partition_by,
             child: sorted,
-            operation:
-                ValueOperation::Limit {
-                    n: 2,
-                    offset: 0,
-                    partition_by,
-                },
-            ..
-        } = &plan.expr
+        }) = plan.non_asap()
         else {
             panic!("grouped limit")
         };
-        let SummaryExpr::ValueOperation {
+        let Some(NonASAPOp::Sort {
+            partition_by: sort_groups,
             child: projected,
-            operation:
-                ValueOperation::Sort {
-                    partition_by: sort_groups,
-                    ..
-                },
             ..
-        } = &sorted.expr
+        }) = sorted.non_asap()
         else {
             panic!("grouped sort")
         };
         assert_eq!(partition_by, sort_groups);
         assert_eq!(partition_by.len(), usize::from(query.contains("topk by")));
-        let SummaryExpr::ValueOperation {
-            child: readout,
-            operation: ValueOperation::Project { .. },
-            ..
-        } = &projected.expr
+        let Some(NonASAPOp::Project {
+            child: evaluation, ..
+        }) = projected.non_asap()
         else {
             panic!("logical output projection")
         };
-        let SummaryExpr::SummaryEstimate {
+        let Some(ASAPOp::SummaryEstimate {
             summary_input,
             query: SketchStatistic::TopK { k },
-        } = &readout.expr
+        }) = evaluation.asap()
         else {
-            panic!("heap readout")
+            panic!("heap evaluation")
         };
         assert!(*k > 2, "candidate capacity is independent of output count");
-        let SummaryExpr::SummaryAgg {
+        let Some(ASAPOp::SummaryAgg {
             child: rates,
             input,
             ..
-        } = &summary_input.expr
+        }) = summary_input.asap()
         else {
             panic!("weighted summary")
         };
@@ -497,13 +473,10 @@ fn rate_and_increase_topk_use_summary_scores_and_grouped_limits() {
             SummaryInputExpr::Column(ColumnRef::SampleValue)
         );
         assert!(matches!(
-            rates.expr,
-            SummaryExpr::ValueOperation {
-                operation: ValueOperation::FinalizeExactAccumulator,
-                ..
-            }
+            rates.asap(),
+            Some(ASAPOp::FinalizeExactAccumulator { .. })
         ));
-        let dag = compile_post_asap_dag(&plan).unwrap();
+        let dag = post_asap_dag(&plan);
         for phase in [
             asap_types::post_asap::ExecutionTiming::IngestionTime,
             asap_types::post_asap::ExecutionTiming::QueryTime,
@@ -525,57 +498,41 @@ fn rate_and_increase_topk_use_summary_scores_and_grouped_limits() {
 
 #[test]
 fn promql_binary_arithmetic_preserves_both_scalar_operand_orders() {
-    fn is_exact_readout_or_scalar(node: &SummaryNode) -> bool {
-        matches!(node.expr, SummaryExpr::KeepPreAsap(_))
-            || matches!(
-                node.expr,
-                SummaryExpr::ValueOperation {
-                    operation: ValueOperation::FinalizeExactAccumulator,
-                    ..
-                }
-            )
-    }
-    for query in ["rate(a[1m]) / 2", "2 / rate(a[1m])"] {
+    for (query, scalar_left) in [("rate(a[1m]) / 2", false), ("2 / rate(a[1m])", true)] {
         let root = lower_and_realize(query);
-        let SummaryExpr::BinaryOp { lhs, rhs, .. } = &root.expr else {
-            panic!("expected BinaryOp for {query}, got {:?}", root.expr);
+        let Some(NonASAPOp::Project { cols, .. }) = root.non_asap() else {
+            panic!("expected Project")
         };
-        assert!(is_exact_readout_or_scalar(lhs));
-        assert!(is_exact_readout_or_scalar(rhs));
-        assert!(
-            matches!(
-                lhs.expr,
-                SummaryExpr::ValueOperation {
-                    operation: ValueOperation::FinalizeExactAccumulator,
-                    ..
-                }
-            ) || matches!(
-                rhs.expr,
-                SummaryExpr::ValueOperation {
-                    operation: ValueOperation::FinalizeExactAccumulator,
-                    ..
-                }
-            )
-        );
+        let ScalarExpr::Arithmetic { left, right, .. } = &cols[1].expr else {
+            panic!()
+        };
+        let (scalar, sample) = if scalar_left {
+            (left, right)
+        } else {
+            (right, left)
+        };
+        assert_eq!(**scalar, ScalarExpr::literal_f64(2.0));
+        assert_eq!(**sample, ScalarExpr::Column(1));
+        assert!(root.schema.has_promql_series_identity());
     }
 }
 
 #[test]
 fn promql_binary_arithmetic_falls_back_as_a_whole_for_unsupported_arm() {
     let root = lower_and_realize("rate(a[1m]) + stddev_over_time(b[1m])");
-    assert!(matches!(root.expr, SummaryExpr::KeepPreAsap(_)));
+    assert!(!root.contains_asap());
 }
 
 #[test]
 fn promql_binary_arithmetic_preserves_nested_structure_and_rejects_modifiers() {
     let nested = lower_and_realize("(rate(a[1m]) + rate(b[1m])) / 2");
-    let SummaryExpr::BinaryOp { lhs, .. } = &nested.expr else {
-        panic!("expected outer BinaryOp, got {:?}", nested.expr);
+    let Some(NonASAPOp::Project { child: lhs, .. }) = nested.non_asap() else {
+        panic!("expected outer BinaryOp, got {:?}", nested.operator);
     };
-    assert!(matches!(lhs.expr, SummaryExpr::BinaryOp { .. }));
+    assert!(matches!(lhs.non_asap(), Some(NonASAPOp::BinaryOp { .. })));
 
     let modified = lower_and_realize("rate(a[1m]) + on(job) rate(b[1m])");
-    assert!(matches!(modified.expr, SummaryExpr::KeepPreAsap(_)));
+    assert!(!modified.contains_asap());
 }
 
 #[test]
@@ -586,8 +543,8 @@ fn promql_binary_arithmetic_never_relabels_approximate_children_as_exact() {
     )
     .expect("lowering failed");
     let root = realize(&pre).expect("binding failed");
-    let SummaryExpr::BinaryOp { lhs, rhs, .. } = &root.expr else {
-        panic!("expected BinaryOp, got {:?}", root.expr);
+    let Some(NonASAPOp::BinaryOp { lhs, rhs, .. }) = root.non_asap() else {
+        panic!("expected BinaryOp, got {:?}", root.operator);
     };
     assert!(lhs.guarantee.as_ref().is_some_and(|g| !g.is_exact()));
     assert!(rhs.guarantee.as_ref().is_some_and(|g| !g.is_exact()));
@@ -606,13 +563,11 @@ fn ddsketch_quantile_ratio_meets_the_shared_relative_error_target() {
         epsilon: 0.01,
         delta: 0.01,
     };
-    let query = Rc::new(
-        lower_promql(
-            "quantile_over_time(0.9, data[5m]) / quantile_over_time(0.5, data[5m])",
-            target.clone(),
-        )
-        .expect("lowering failed"),
-    );
+    let query = lower_promql(
+        "quantile_over_time(0.9, data[5m]) / quantile_over_time(0.5, data[5m])",
+        target.clone(),
+    )
+    .expect("lowering failed");
 
     let evidence = FixtureQuantileDomain {
         lower: 1.0,
@@ -632,7 +587,7 @@ fn ddsketch_quantile_ratio_meets_the_shared_relative_error_target() {
         .for_target(root)
         .and_then(|selection| selection.chosen.as_ref())
         .expect("the certified DDSketch ratio should be selectable");
-    let Replacement::Summary(node) = &chosen.replacement else {
+    let Replacement::SubDAG(node) = &chosen.replacement else {
         panic!("expected a summary candidate")
     };
     let guarantee = node.guarantee.as_ref().expect("ratio guarantee");
@@ -642,23 +597,22 @@ fn ddsketch_quantile_ratio_meets_the_shared_relative_error_target() {
         "ratio guarantee should satisfy the requested target: {guarantee:?}"
     );
 
-    let shared =
-        asap_types::post_asap::share_common_summary_sub_dags(vec![("ratio", node.clone())]);
-    let SummaryExpr::BinaryOp { lhs, rhs, .. } = &shared[0].1.expr else {
+    let shared = asap_types::ir::cse::share_common_sub_dags(vec![("ratio", node.clone())]);
+    let Some(NonASAPOp::BinaryOp { lhs, rhs, .. }) = shared[0].1.non_asap() else {
         panic!("expected binary ratio")
     };
-    let producer = |readout: &Rc<SummaryNode>| match &readout.expr {
-        SummaryExpr::SummaryEstimate { summary_input, .. } => Rc::clone(summary_input),
-        other => panic!("expected DDSketch readout, got {other:?}"),
+    let producer = |evaluation: &Rc<OperatorNode>| match &evaluation.operator {
+        Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) => Rc::clone(summary_input),
+        other => panic!("expected DDSketch evaluation, got {other:?}"),
     };
     assert!(
         Rc::ptr_eq(&producer(lhs), &producer(rhs)),
-        "the two quantile readouts should share one DDSketch producer"
+        "the two quantile evaluations should share one DDSketch producer"
     );
 }
 
 #[test]
-fn planner_only_e2e_temporal_topk_preserves_query_update_and_readout_contract() {
+fn planner_only_e2e_temporal_topk_preserves_query_update_and_evaluation_contract() {
     // Self-contained Planner E2E: each case starts from PromQL text and ends
     // at the post-ASAP summary DAG. No controller/backend types,
     // fixtures, configuration, or runtime are involved.
@@ -677,17 +631,15 @@ fn planner_only_e2e_temporal_topk_preserves_query_update_and_readout_contract()
         ),
     ];
     for (source, expected_update, expected_family, excluded_labels) in cases {
-        let pre = Rc::new(
-            lower_promql(
-                source,
-                AccuracyTarget::EpsilonDelta {
-                    epsilon: 0.01,
-                    delta: 0.01,
-                },
-            )
-            .expect("lower temporal Top-K"),
-        );
-        let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+        let pre = lower_promql(
+            source,
+            AccuracyTarget::EpsilonDelta {
+                epsilon: 0.01,
+                delta: 0.01,
+            },
+        )
+        .expect("lower temporal Top-K");
+        let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
             &DefaultCostModel,
             &DefaultAccuracyModel,
             &EqualSplitAllocator,
@@ -697,29 +649,29 @@ fn planner_only_e2e_temporal_topk_preserves_query_update_and_readout_contract()
             .replacements(&TargetSubDAG::new(&pre))
             .into_iter()
             .find_map(|candidate| match candidate.replacement {
-                Replacement::Summary(node) if candidate.rationale.contains(expected_family) => {
+                Replacement::SubDAG(node) if candidate.rationale.contains(expected_family) => {
                     Some(node)
                 }
                 _ => None,
             })
             .expect("heap-backed temporal Top-K candidate");
-        let SummaryExpr::SummaryEstimate {
+        let Some(ASAPOp::SummaryEstimate {
             summary_input,
             query: SketchStatistic::TopK { k, .. },
-        } = &candidate.expr
+        }) = candidate.asap()
         else {
-            panic!("expected Top-K estimate, got {:?}", candidate.expr)
+            panic!("expected Top-K estimate, got {:?}", candidate.operator)
         };
         assert_eq!(
             *k, 5,
             "the requested Top-K cardinality must survive binding"
         );
-        let SummaryExpr::SummaryAgg {
+        let Some(ASAPOp::SummaryAgg {
             input: state_input,
             family,
             child,
             ..
-        } = &summary_input.expr
+        }) = summary_input.asap()
         else {
             panic!("expected structured Top-K state input")
         };
@@ -742,42 +694,41 @@ fn planner_only_e2e_temporal_topk_preserves_query_update_and_readout_contract()
             ))
         );
         assert_eq!(state_input.weight, expected_update);
-        assert!(matches!(child.expr, SummaryExpr::KeepPreAsap(_)));
+        assert!(!child.contains_asap());
     }
 }
 
 /// Execute the ungrouped temporal TopK subset with exact state. This tests
 /// the emitted update contract, not sketch approximation or backend execution.
-fn execute_topk_reference(plan: &SummaryNode) -> Vec<(String, f64)> {
+fn execute_topk_reference(plan: &OperatorNode) -> Vec<(String, f64)> {
     use std::collections::BTreeMap;
-    let SummaryExpr::SummaryEstimate {
+    let Some(ASAPOp::SummaryEstimate {
         summary_input,
         query: SketchStatistic::TopK { k },
-    } = &plan.expr
+    }) = plan.asap()
     else {
-        panic!("expected TopK readout")
+        panic!("expected TopK evaluation")
     };
-    let SummaryExpr::SummaryAgg {
+    let Some(ASAPOp::SummaryAgg {
         input,
         child,
         reduction,
         ..
-    } = &summary_input.expr
+    }) = summary_input.asap()
     else {
         panic!("expected summary updates")
     };
     assert_eq!(reduction, &Reduction::by(vec![]));
-    let SummaryExpr::KeepPreAsap(raw) = &child.expr else {
-        panic!("expected fused raw input")
-    };
-    let QueryExpr::TimeRange { range, child } = raw.as_ref() else {
+    // The fused raw input is the kept non-ASAP sub-DAG itself.
+    assert!(!child.contains_asap(), "expected fused raw input");
+    let Some(NonASAPOp::TimeRange { range, child, .. }) = child.non_asap() else {
         panic!("expected temporal input")
     };
-    let QueryExpr::Scan {
+    let Some(NonASAPOp::Scan {
         source: asap_types::pre_asap::Source::TimeSeries { metric },
         predicates,
         ..
-    } = child.as_ref()
+    }) = child.non_asap()
     else {
         panic!("expected metric scan")
     };
@@ -849,17 +800,15 @@ fn planner_heap_topk_reference_execution_matches_ground_truth() {
             vec![("worker", 100.0), ("cron", 30.0)],
         ),
     ] {
-        let pre = Rc::new(
-            lower_promql(
-                query,
-                AccuracyTarget::EpsilonDelta {
-                    epsilon: 0.01,
-                    delta: 0.01,
-                },
-            )
-            .unwrap(),
-        );
-        let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+        let pre = lower_promql(
+            query,
+            AccuracyTarget::EpsilonDelta {
+                epsilon: 0.01,
+                delta: 0.01,
+            },
+        )
+        .unwrap();
+        let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
             &DefaultCostModel,
             &DefaultAccuracyModel,
             &EqualSplitAllocator,
@@ -868,10 +817,10 @@ fn planner_heap_topk_reference_execution_matches_ground_truth() {
         // This reference executor consumes keyed heap updates. The inventory
         // also contains maintained exact values followed by sort/limit; those
         // have a different execution contract and must not enter this fixture.
-        let candidates: Vec<_> = strategy.replacements(&TargetSubDAG::new(&pre)).into_iter().filter(|candidate| matches!(&candidate.replacement, Replacement::Summary(plan) if matches!(plan.expr, SummaryExpr::SummaryEstimate { query: SketchStatistic::TopK { .. }, .. }))).collect();
+        let candidates: Vec<_> = strategy.replacements(&TargetSubDAG::new(&pre)).into_iter().filter(|candidate| matches!(&candidate.replacement, Replacement::SubDAG(plan) if matches!(plan.asap(), Some(ASAPOp::SummaryEstimate { query: SketchStatistic::TopK { .. }, .. })))).collect();
         assert!(!candidates.is_empty(), "no heap candidate for {query}");
         for candidate in candidates {
-            let Replacement::Summary(plan) = candidate.replacement else {
+            let Replacement::SubDAG(plan) = candidate.replacement else {
                 panic!("expected summary plan for {query}")
             };
             let expected: Vec<_> = expected
@@ -889,11 +838,11 @@ fn planner_heap_topk_reference_execution_matches_ground_truth() {
 /// SummaryEstimate { query: Quantile{0.99} }          → {quantile_0_99: Float64}
 /// └─ SummaryAgg { Kll{k:269}, input: SampleValue }   → {value: Sketch(Kll, {k:269})}
 ///    └─ SummaryAgg { Rate, input: SampleValue }      → {ts, value: ExactAggregate(Rate), …}
-///       └─ KeepPreAsap(TimeRange{5m} → Scan)         → {ts, value}
+///       └─ TimeRange{5m} → Scan                      → {ts, value}
 /// ```
 ///
-/// The nested DAG exercises both realizations: the approximate quantile
-/// binds a KLL sketch + readout; the per-series `rate` binds the exact
+/// The nested tree exercises both realizations: the approximate quantile
+/// binds a KLL sketch + evaluation; the per-series `rate` binds the exact
 /// counter-reset-aware accumulator (no estimate — its state is the value).
 #[test]
 fn promql_quantile_of_rate_binds_kll_over_rate_accumulator() {
@@ -904,13 +853,13 @@ fn promql_quantile_of_rate_binds_kll_over_rate_accumulator() {
     .expect("lowering failed");
     let root = realize(&pre_asap).expect("binding failed");
 
-    // Root: the sketch readout, back to a plain row shape.
-    let SummaryExpr::SummaryEstimate {
+    // Root: the sketch evaluation, back to a plain row shape.
+    let Some(ASAPOp::SummaryEstimate {
         summary_input,
         query,
-    } = &root.expr
+    }) = root.asap()
     else {
-        panic!("expected SummaryEstimate root, got {:?}", root.expr);
+        panic!("expected SummaryEstimate root, got {:?}", root.operator);
     };
     assert!(matches!(query, SketchStatistic::Quantile { q } if *q == 0.99));
     assert_eq!(
@@ -924,15 +873,15 @@ fn promql_quantile_of_rate_binds_kll_over_rate_accumulator() {
     // reduction, one output row — not to be confused with the inner rate's
     // per-entity grouping below, even though both once collapsed to the
     // same empty `by: []` (issue #163).
-    let SummaryExpr::SummaryAgg {
+    let Some(ASAPOp::SummaryAgg {
         child,
         family,
         input,
         reduction,
         ..
-    } = &summary_input.expr
+    }) = summary_input.asap()
     else {
-        panic!("expected SummaryAgg, got {:?}", summary_input.expr);
+        panic!("expected SummaryAgg, got {:?}", summary_input.operator);
     };
     assert_eq!(
         family,
@@ -955,26 +904,24 @@ fn promql_quantile_of_rate_binds_kll_over_rate_accumulator() {
         )
     );
 
-    let SummaryExpr::ValueOperation {
-        child,
-        operation: ValueOperation::FinalizeExactAccumulator,
-        timing: asap_types::post_asap::ExecutionTiming::IngestionTime,
-    } = &child.expr
-    else {
-        panic!("rate needs a maintenance readout");
+    let Some(ASAPOp::FinalizeExactAccumulator { child }) = child.asap() else {
+        panic!("rate needs a maintenance evaluation");
     };
 
     // The rate: exact counter-reset-aware accumulator, per-series (labels
     // and time axis preserved), no estimate wrapper. `rate(...)` has no
     // grouping concept at all — every entity stays its own summary.
-    let SummaryExpr::SummaryAgg {
+    let Some(ASAPOp::SummaryAgg {
         child: leaf,
         family,
         reduction,
         ..
-    } = &child.expr
+    }) = child.asap()
     else {
-        panic!("expected inner SummaryAgg for rate, got {:?}", child.expr);
+        panic!(
+            "expected inner SummaryAgg for rate, got {:?}",
+            child.operator
+        );
     };
     assert_eq!(
         family,
@@ -992,14 +939,20 @@ fn promql_quantile_of_rate_binds_kll_over_rate_accumulator() {
     );
 
     // The leaf: unrewritten pass-through — TimeRange marker over the Scan.
-    let SummaryExpr::KeepPreAsap(kept_leaf) = &leaf.expr else {
-        panic!("expected KeepPreAsap leaf, got {:?}", leaf.expr);
-    };
-    let QueryExpr::TimeRange { range, child: scan } = kept_leaf.as_ref() else {
-        panic!("expected TimeRange leaf, got {kept_leaf:?}");
+    // The kept leaf is the non-ASAP sub-DAG itself.
+    assert!(
+        !leaf.contains_asap(),
+        "expected kept leaf, got {:?}",
+        leaf.operator
+    );
+    let Some(NonASAPOp::TimeRange {
+        range, child: scan, ..
+    }) = leaf.non_asap()
+    else {
+        panic!("expected TimeRange leaf, got {:?}", leaf.operator);
     };
     assert_eq!(range.as_secs(), 300);
-    assert!(matches!(scan.as_ref(), QueryExpr::Scan { .. }));
+    assert!(matches!(scan.non_asap(), Some(NonASAPOp::Scan { .. })));
     assert!(
         leaf.schema
             .fields
@@ -1017,11 +970,11 @@ fn promql_exact_workload_binds_accumulators_not_sketches() {
     let pre_asap = lower_promql("sum by (job) (http_requests_total)", AccuracyTarget::Exact)
         .expect("lowering failed");
     let root = realize(&pre_asap).expect("binding failed");
-    let SummaryExpr::SummaryAgg {
+    let Some(ASAPOp::SummaryAgg {
         family, reduction, ..
-    } = &root.expr
+    }) = root.asap()
     else {
-        panic!("expected SummaryAgg, got {:?}", root.expr);
+        panic!("expected SummaryAgg, got {:?}", root.operator);
     };
     assert_eq!(
         family,
@@ -1042,21 +995,19 @@ fn promql_exact_workload_binds_accumulators_not_sketches() {
         lower_promql("avg(http_requests_total)", AccuracyTarget::Exact).expect("lowering failed");
     let root = realize(&pre_asap).expect("binding failed");
     assert!(
-        matches!(root.expr, SummaryExpr::KeepPreAsap(_)),
+        !root.contains_asap(),
         "avg has no mergeable accumulator — stays logical"
     );
 }
 
 #[test]
 fn promql_sum_of_count_over_time_is_composed_by_default_search() {
-    let original = Rc::new(
-        lower_promql(
-            "sum by (service) (count_over_time(metrics[5m]))",
-            AccuracyTarget::Exact,
-        )
-        .expect("lowering failed"),
-    );
-    let original_schema = original.output_schema().unwrap();
+    let original = lower_promql(
+        "sum by (service) (count_over_time(metrics[5m]))",
+        AccuracyTarget::Exact,
+    )
+    .expect("lowering failed");
+    let original_schema = original.schema.clone();
     let space = search_workload(vec![("query", original)]);
     let root = &space.roots[0].1;
     let group = space.candidates_for_target(root).expect("root memo group");
@@ -1065,20 +1016,21 @@ fn promql_sum_of_count_over_time_is_composed_by_default_search() {
         .iter()
         .find(|candidate| candidate.strategy == "SemanticEquivalentRewriteStrategy")
         .expect("default search should compose the lowered PromQL query");
-    let Replacement::Rewrite(rewritten) = &candidate.replacement else {
+    let Replacement::SubDAG(rewritten) = &candidate.replacement else {
         panic!("expected logical rewrite")
     };
+    assert!(is_logical_rewrite(rewritten), "expected logical rewrite");
 
-    assert_eq!(rewritten.output_schema().unwrap(), original_schema);
-    let QueryExpr::Project { child, .. } = rewritten.as_ref() else {
+    assert_eq!(rewritten.schema, original_schema);
+    let Some(NonASAPOp::Project { child, .. }) = rewritten.non_asap() else {
         panic!("sum(count_over_time) needs a Float64 cast Project")
     };
-    let QueryExpr::Aggregate {
+    let Some(NonASAPOp::Aggregate {
         reduction: Reduction::Reduce(by),
         measures,
         child,
         ..
-    } = child.as_ref()
+    }) = child.non_asap()
     else {
         panic!("expected one composed aggregate")
     };
@@ -1090,9 +1042,9 @@ fn promql_sum_of_count_over_time_is_composed_by_default_search() {
         }]
     ));
     assert!(matches!(
-        child.as_ref(),
-        QueryExpr::TimeRange { range, child }
-            if range.as_secs() == 300 && matches!(child.as_ref(), QueryExpr::Scan { .. })
+        child.non_asap(),
+        Some(NonASAPOp::TimeRange { range, child, .. })
+            if range.as_secs() == 300 && matches!(child.non_asap(), Some(NonASAPOp::Scan { .. }))
     ));
 }
 
@@ -1100,50 +1052,41 @@ fn promql_sum_of_count_over_time_is_composed_by_default_search() {
 fn nested_summary_explicitly_finalizes_exact_child_at_ingestion_time() {
     // Real workload selection must expose the state-to-value edge; an outer
     // sketch must not interpret exact accumulator bytes as input samples.
-    let pre = Rc::new(
-        lower_promql(
-            "quantile(0.9, sum_over_time(m[1m]))",
-            AccuracyTarget::Epsilon(0.05),
-        )
-        .unwrap(),
-    );
+    let pre = lower_promql(
+        "quantile(0.9, sum_over_time(m[1m]))",
+        AccuracyTarget::Epsilon(0.05),
+    )
+    .unwrap();
     let space = search_workload(vec![("query", pre)]);
     let selected = space.global_selection(&DefaultCostModel);
     let plan = selected
         .assemble_selected_dag(&space.roots[0].1)
         .unwrap()
         .unwrap();
-    let SummaryExpr::SummaryEstimate { summary_input, .. } = &plan.expr else {
+    // Stored timings are gone: time the plan and read the timed copy.
+    let timed_plan = timed(&plan);
+    let Some(ASAPOp::SummaryEstimate { summary_input, .. }) = timed_plan.asap() else {
         panic!("expected selected quantile summary");
     };
-    let SummaryExpr::SummaryAgg { child, .. } = &summary_input.expr else {
+    let Some(ASAPOp::SummaryAgg { child, .. }) = summary_input.asap() else {
         panic!("expected maintained outer summary");
     };
-    let SummaryExpr::ValueOperation {
-        child: source,
-        operation,
-        timing,
-    } = &child.expr
-    else {
+    let Some(ASAPOp::FinalizeExactAccumulator { child: source }) = child.asap() else {
         panic!(
             "missing explicit accumulator finalization: {:?}",
-            child.expr
+            child.operator
         );
     };
-    assert!(matches!(
-        operation,
-        ValueOperation::FinalizeExactAccumulator
-    ));
     assert_eq!(
-        *timing,
-        asap_types::post_asap::ExecutionTiming::IngestionTime
+        child.timing,
+        Some(asap_types::post_asap::ExecutionTiming::IngestionTime)
     );
     assert!(matches!(
-        source.expr,
-        SummaryExpr::SummaryAgg {
+        source.asap(),
+        Some(ASAPOp::SummaryAgg {
             family: FieldDataType::ExactAggregate(ExactKind::Sum, _),
             ..
-        }
+        })
     ));
     assert!(child
         .schema
@@ -1155,12 +1098,13 @@ fn nested_summary_explicitly_finalizes_exact_child_at_ingestion_time() {
         .fields
         .iter()
         .any(|field| matches!(field.dtype, FieldDataType::Plain(DataType::Float64))));
-    compile_post_asap_dag(&plan).expect("explicit boundary is a valid post-ASAP DAG");
+    // Explicit boundary is a valid post-ASAP DAG.
+    post_asap_dag(&plan);
 }
 
 #[test]
 fn physical_node_owns_phase_independently_of_binary_payload() {
-    use asap_types::post_asap::{ExecutionTiming, PostAsapOperatorPayload};
+    use asap_types::post_asap::ExecutionTiming;
     for (query, expected) in [
         (
             // One selector: both operands cover the same series.
@@ -1173,27 +1117,32 @@ fn physical_node_owns_phase_independently_of_binary_payload() {
         ),
     ] {
         let input = lower_promql(query, AccuracyTarget::Epsilon(0.05)).unwrap();
-        // Backend lowering carries opaque series identity before candidate export.
-        let input = asap_types::pre_asap::schema::with_promql_series_identity(&input).unwrap();
-        let search = search_workload(vec![("q", Rc::new(input))]);
+        let search = search_workload(vec![("q", input)]);
         let choice = search.global_selection(&DefaultCostModel);
         let plan = choice
             .assemble_selected_dag(&search.roots[0].1)
             .unwrap()
             .unwrap();
-        let dag = compile_post_asap_dag(&plan).unwrap();
+        let dag = post_asap_dag(&plan);
         let node = dag
             .nodes
             .iter()
-            .find(|node| matches!(node.payload, PostAsapOperatorPayload::Binary { .. }))
+            .find(|node| {
+                matches!(
+                    node.payload,
+                    PhysicalASAPOperatorPayload::Relational {
+                        operator: NonASAPOpKind::BinaryOp { .. }
+                    }
+                )
+            })
             .unwrap();
         assert_eq!(node.output_state.timing, expected);
         let wire = serde_json::to_value(&node.payload).unwrap();
         assert!(wire.get("timing").is_none());
         let mut obsolete = wire.clone();
         obsolete["timing"] = serde_json::json!(expected.as_str());
-        assert!(serde_json::from_value::<PostAsapOperatorPayload>(obsolete).is_err());
-        let restored: PostAsapOperatorPayload = serde_json::from_value(wire).unwrap();
+        assert!(serde_json::from_value::<PhysicalASAPOperatorPayload>(obsolete).is_err());
+        let restored: PhysicalASAPOperatorPayload = serde_json::from_value(wire).unwrap();
         assert_eq!(restored, node.payload);
     }
 }
@@ -1207,14 +1156,10 @@ fn ddsketch_ratio_without_domain_proof_is_uncertified() {
     )
     .unwrap();
     let root = realize(&pre).unwrap();
-    assert!(matches!(root.expr, SummaryExpr::BinaryOp { .. }));
+    assert!(matches!(root.non_asap(), Some(NonASAPOp::BinaryOp { .. })));
     assert!(root.guarantee.is_none());
     let space = search_workload_with_targets(
-        vec![(
-            "unproven",
-            Rc::new(pre),
-            Some(AccuracyTarget::Epsilon(0.01)),
-        )],
+        vec![("unproven", pre, Some(AccuracyTarget::Epsilon(0.01)))],
         &asap_aware_mapping::default_strategies(),
         &DefaultAccuracyModel,
     );
@@ -1226,8 +1171,8 @@ fn ddsketch_ratio_without_domain_proof_is_uncertified() {
         root_group.candidates.iter().any(|candidate| {
             matches!(
                 &candidate.replacement,
-                Replacement::Summary(node)
-                    if matches!(node.expr, SummaryExpr::BinaryOp { .. })
+                Replacement::SubDAG(node)
+                    if matches!(node.non_asap(), Some(NonASAPOp::BinaryOp { .. }))
                         && node.guarantee.is_none()
             )
         }),
@@ -1247,7 +1192,7 @@ fn ddsketch_ratio_without_domain_proof_is_uncertified() {
         .assemble_selected_dag(&space.roots[0].1)
         .unwrap()
         .expect("materialized root");
-    assert!(matches!(materialized.expr, SummaryExpr::KeepPreAsap(_)));
+    assert!(!materialized.contains_asap());
 }
 
 struct FixtureQuantileDomain {
@@ -1255,7 +1200,7 @@ struct FixtureQuantileDomain {
     upper: f64,
 }
 impl AccuracyEvidenceProvider for FixtureQuantileDomain {
-    fn quantile_input_domain(&self, _: &QueryExpr) -> Option<QuantileInputDomain> {
+    fn quantile_input_domain(&self, _: &OperatorNode) -> Option<QuantileInputDomain> {
         Some(QuantileInputDomain {
             lower: self.lower,
             upper: self.upper,
@@ -1278,14 +1223,12 @@ fn ddsketch_ratio_rejects_unsafe_domains() {
         (f64::MIN_POSITIVE / 2., f64::MIN_POSITIVE / 2.),
     ] {
         let evidence = FixtureQuantileDomain { lower, upper };
-        let pre = Rc::new(
-            lower_promql(
-                "quantile_over_time(0.9, data[5m]) / quantile_over_time(0.5, data[5m])",
-                AccuracyTarget::Epsilon(0.01),
-            )
-            .unwrap(),
-        );
-        let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+        let pre = lower_promql(
+            "quantile_over_time(0.9, data[5m]) / quantile_over_time(0.5, data[5m])",
+            AccuracyTarget::Epsilon(0.01),
+        )
+        .unwrap();
+        let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
             &DefaultCostModel,
             &DefaultAccuracyModel,
             &EqualSplitAllocator,
@@ -1304,8 +1247,8 @@ fn ddsketch_ratio_rejects_unsafe_domains() {
 fn ddsketch_ratio_rejects_one_invalid_domain_when_the_other_is_missing() {
     struct PartialUnsafeDomain;
     impl AccuracyEvidenceProvider for PartialUnsafeDomain {
-        fn quantile_input_domain(&self, operand: &QueryExpr) -> Option<QuantileInputDomain> {
-            let QueryExpr::Aggregate { measures, .. } = operand else {
+        fn quantile_input_domain(&self, operand: &OperatorNode) -> Option<QuantileInputDomain> {
+            let Some(NonASAPOp::Aggregate { measures, .. }) = operand.non_asap() else {
                 return None;
             };
             matches!(
@@ -1321,14 +1264,12 @@ fn ddsketch_ratio_rejects_one_invalid_domain_when_the_other_is_missing() {
         }
     }
 
-    let pre = Rc::new(
-        lower_promql(
-            "quantile_over_time(0.9, data[5m]) / quantile_over_time(0.5, data[5m])",
-            AccuracyTarget::Epsilon(0.01),
-        )
-        .unwrap(),
-    );
-    let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+    let pre = lower_promql(
+        "quantile_over_time(0.9, data[5m]) / quantile_over_time(0.5, data[5m])",
+        AccuracyTarget::Epsilon(0.01),
+    )
+    .unwrap();
+    let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
         &DefaultCostModel,
         &DefaultAccuracyModel,
         &EqualSplitAllocator,
@@ -1339,40 +1280,38 @@ fn ddsketch_ratio_rejects_one_invalid_domain_when_the_other_is_missing() {
 
 /// The committed planner alpha is exercised against the pinned sketch implementation.
 #[test]
-fn ddsketch_ratio_bound_holds_for_signed_pinned_sketch_readouts() {
+fn ddsketch_ratio_bound_holds_for_signed_pinned_sketch_evaluations() {
     for sign in [-1., 1.] {
         let evidence = FixtureQuantileDomain {
             lower: if sign < 0. { -100. } else { 1. },
             upper: if sign < 0. { -1. } else { 100. },
         };
-        let pre = Rc::new(
-            lower_promql(
-                "quantile_over_time(0.9, data[5m]) / quantile_over_time(0.5, data[5m])",
-                AccuracyTarget::Epsilon(0.01),
-            )
-            .unwrap(),
-        );
-        let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+        let pre = lower_promql(
+            "quantile_over_time(0.9, data[5m]) / quantile_over_time(0.5, data[5m])",
+            AccuracyTarget::Epsilon(0.01),
+        )
+        .unwrap();
+        let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
             &DefaultCostModel,
             &DefaultAccuracyModel,
             &EqualSplitAllocator,
             &evidence,
         );
         let candidates = strategy.replacements(&TargetSubDAG::new(&pre));
-        let Replacement::Summary(node) = &candidates[0].replacement else {
+        let Replacement::SubDAG(node) = &candidates[0].replacement else {
             panic!("summary")
         };
-        let SummaryExpr::BinaryOp { lhs, rhs, .. } = &node.expr else {
+        let Some(NonASAPOp::BinaryOp { lhs, rhs, .. }) = node.non_asap() else {
             panic!("ratio")
         };
-        let alpha = |node: &SummaryNode| {
-            let SummaryExpr::SummaryEstimate { summary_input, .. } = &node.expr else {
-                panic!("readout")
+        let alpha = |node: &OperatorNode| {
+            let Some(ASAPOp::SummaryEstimate { summary_input, .. }) = node.asap() else {
+                panic!("evaluation")
             };
-            let SummaryExpr::SummaryAgg {
+            let Some(ASAPOp::SummaryAgg {
                 family: FieldDataType::Sketch(kind, _),
                 ..
-            } = &summary_input.expr
+            }) = summary_input.asap()
             else {
                 panic!("sketch")
             };
@@ -1407,12 +1346,12 @@ fn ddsketch_ratio_bound_holds_for_signed_pinned_sketch_readouts() {
     }
 }
 
-/// Empty or overlarge population contracts cannot promise a supported readout.
+/// Empty or overlarge population contracts cannot promise a supported evaluation.
 #[test]
 fn ddsketch_ratio_requires_a_supported_population_size() {
     struct PopulationEvidence(u64);
     impl AccuracyEvidenceProvider for PopulationEvidence {
-        fn quantile_input_domain(&self, _: &QueryExpr) -> Option<QuantileInputDomain> {
+        fn quantile_input_domain(&self, _: &OperatorNode) -> Option<QuantileInputDomain> {
             Some(QuantileInputDomain {
                 lower: 1.,
                 upper: 10.,
@@ -1421,16 +1360,14 @@ fn ddsketch_ratio_requires_a_supported_population_size() {
             })
         }
     }
-    let pre = Rc::new(
-        lower_promql(
-            "quantile_over_time(0.9, data[5m]) / quantile_over_time(0.5, data[5m])",
-            AccuracyTarget::Epsilon(0.01),
-        )
-        .unwrap(),
-    );
+    let pre = lower_promql(
+        "quantile_over_time(0.9, data[5m]) / quantile_over_time(0.5, data[5m])",
+        AccuracyTarget::Epsilon(0.01),
+    )
+    .unwrap();
     for count in [0, (1u64 << 53) + 1] {
         let evidence = PopulationEvidence(count);
-        let strategy = SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+        let strategy = ASAPStrategies::new_with_planning_inputs_and_evidence(
             &DefaultCostModel,
             &DefaultAccuracyModel,
             &EqualSplitAllocator,
@@ -1441,7 +1378,7 @@ fn ddsketch_ratio_requires_a_supported_population_size() {
 }
 
 // Every `without` aggregation candidate exports a valid DAG: its summary state
-// column carries the family instead of the readout's Float64 value.
+// column carries the family instead of the evaluation's Float64 value.
 #[test]
 fn without_aggregation_candidates_export_valid_dags() {
     for accuracy in [
@@ -1452,7 +1389,7 @@ fn without_aggregation_candidates_export_valid_dags() {
         },
     ] {
         for query in ["sum without (pod) (m)", "quantile without (pod) (0.5, m)"] {
-            let root = Rc::new(lower_promql(query, accuracy.clone()).unwrap());
+            let root = lower_promql(query, accuracy.clone()).unwrap();
             let space = search_workload_with_targets(
                 vec![(0, root, Some(accuracy.clone()))],
                 &asap_aware_mapping::default_strategies(),
@@ -1461,7 +1398,7 @@ fn without_aggregation_candidates_export_valid_dags() {
             let inventory = space.enumerate_candidate_dags_for_root(&0, 65_536).unwrap();
             assert!(!inventory.candidates.is_empty(), "{query}");
             for (_, node) in inventory.candidates.iter().flatten() {
-                compile_post_asap_dag(node).unwrap_or_else(|e| panic!("{query}: {e}"));
+                post_asap_dag(node);
             }
         }
     }
diff --git a/crates/integration-tests/tests/scan.rs b/crates/integration-tests/tests/scan.rs
index bb7988d7a..e43e27a6c 100644
--- a/crates/integration-tests/tests/scan.rs
+++ b/crates/integration-tests/tests/scan.rs
@@ -1,4 +1,4 @@
-//! `QueryExpr::Scan` — label matcher / predicate tests.
+//! `NonASAPOp::Scan` — label matcher / predicate tests.
 //!
 //! The Scan schema is always [ts(0), value(1), label_a(2), label_b(3), …]
 //! where labels are appended alphabetically after dedup by the SchemaResolver.
@@ -11,60 +11,62 @@ use std::time::Duration;
 
 use asap_integration_tests::fixtures::lower_promql;
 use asap_integration_tests::fixtures::metric_schema;
-use asap_types::pre_asap::{CompareOpKind, Predicate, QueryExpr, ScalarValue, Source};
+use asap_types::ir::{
+    ExprSemantics, NonASAPOp, OperatorNode, Predicate, ScalarExpr, TimeRangeKind,
+};
+use asap_types::pre_asap::{CompareOpKind, ScalarValue, Source};
 use asap_types::types::AccuracyTarget;
 
-fn lower(q: &str) -> QueryExpr {
+fn lower(q: &str) -> Rc<OperatorNode> {
     lower_promql(q, AccuracyTarget::Exact).unwrap_or_else(|e| panic!("lower failed for {q:?}: {e}"))
 }
 
-fn bare_scan(metric: &str, labels: &[&str]) -> QueryExpr {
-    QueryExpr::Scan {
+fn node(op: NonASAPOp) -> Rc<OperatorNode> {
+    OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(op))
+        .expect("fixture node derives its schema")
+}
+
+fn bare_scan(metric: &str, labels: &[&str]) -> Rc<OperatorNode> {
+    node(NonASAPOp::Scan {
         source: Source::TimeSeries {
             metric: metric.into(),
         },
         predicates: vec![],
         schema: metric_schema(labels),
-    }
+    })
 }
 
-fn instant(child: QueryExpr) -> QueryExpr {
-    QueryExpr::TimeRange {
+fn instant(child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+    node(NonASAPOp::TimeRange {
         range: Duration::from_secs(1),
-        child: Rc::new(child),
-    }
+        kind: TimeRangeKind::Instant,
+        child,
+    })
+}
+
+fn label_pred(col_id: usize, op: CompareOpKind, value: &str) -> Predicate {
+    Predicate(ScalarExpr::Compare {
+        left: Box::new(ScalarExpr::Column(col_id)),
+        op,
+        right: Box::new(ScalarExpr::Literal(ScalarValue::Utf8(value.into()))),
+        semantics: ExprSemantics::Promql,
+    })
 }
 
 fn eq_pred(col_id: usize, value: &str) -> Predicate {
-    Predicate(Rc::new(QueryExpr::Compare {
-        left: Rc::new(QueryExpr::Column(col_id)),
-        op: CompareOpKind::Eq,
-        right: Rc::new(QueryExpr::Literal(ScalarValue::Utf8(value.into()))),
-    }))
+    label_pred(col_id, CompareOpKind::Eq, value)
 }
 
 fn ne_pred(col_id: usize, value: &str) -> Predicate {
-    Predicate(Rc::new(QueryExpr::Compare {
-        left: Rc::new(QueryExpr::Column(col_id)),
-        op: CompareOpKind::Ne,
-        right: Rc::new(QueryExpr::Literal(ScalarValue::Utf8(value.into()))),
-    }))
+    label_pred(col_id, CompareOpKind::Ne, value)
 }
 
 fn regex_pred(col_id: usize, pattern: &str) -> Predicate {
-    Predicate(Rc::new(QueryExpr::Compare {
-        left: Rc::new(QueryExpr::Column(col_id)),
-        op: CompareOpKind::Regex,
-        right: Rc::new(QueryExpr::Literal(ScalarValue::Utf8(pattern.into()))),
-    }))
+    label_pred(col_id, CompareOpKind::Regex, pattern)
 }
 
 fn notregex_pred(col_id: usize, pattern: &str) -> Predicate {
-    Predicate(Rc::new(QueryExpr::Compare {
-        left: Rc::new(QueryExpr::Column(col_id)),
-        op: CompareOpKind::NotRegex,
-        right: Rc::new(QueryExpr::Literal(ScalarValue::Utf8(pattern.into()))),
-    }))
+    label_pred(col_id, CompareOpKind::NotRegex, pattern)
 }
 
 // #1 — bare metric name, no matchers
@@ -80,13 +82,13 @@ fn q01_bare_scan() {
 //   schema: [ts(0), value(1), job(2)]
 #[test]
 fn q02_equality_predicate() {
-    let expected = instant(QueryExpr::Scan {
+    let expected = instant(node(NonASAPOp::Scan {
         source: Source::TimeSeries {
             metric: "http_requests_total".into(),
         },
         predicates: vec![eq_pred(2, "api-server")],
         schema: metric_schema(&["job"]),
-    });
+    }));
     assert_eq!(lower(r#"http_requests_total{job="api-server"}"#), expected);
 }
 
@@ -94,13 +96,13 @@ fn q02_equality_predicate() {
 //   schema: [ts(0), value(1), status(2)]
 #[test]
 fn q03_inequality_predicate() {
-    let expected = instant(QueryExpr::Scan {
+    let expected = instant(node(NonASAPOp::Scan {
         source: Source::TimeSeries {
             metric: "http_requests_total".into(),
         },
         predicates: vec![ne_pred(2, "500")],
         schema: metric_schema(&["status"]),
-    });
+    }));
     assert_eq!(lower(r#"http_requests_total{status!="500"}"#), expected);
 }
 
@@ -108,13 +110,13 @@ fn q03_inequality_predicate() {
 //   schema: [ts(0), value(1), job(2)]
 #[test]
 fn q04_regex_predicate() {
-    let expected = instant(QueryExpr::Scan {
+    let expected = instant(node(NonASAPOp::Scan {
         source: Source::TimeSeries {
             metric: "http_requests_total".into(),
         },
         predicates: vec![regex_pred(2, "api.*")],
         schema: metric_schema(&["job"]),
-    });
+    }));
     assert_eq!(lower(r#"http_requests_total{job=~"api.*"}"#), expected);
 }
 
@@ -122,13 +124,13 @@ fn q04_regex_predicate() {
 //   schema: [ts(0), value(1), job(2)]
 #[test]
 fn q_notregex_predicate() {
-    let expected = instant(QueryExpr::Scan {
+    let expected = instant(node(NonASAPOp::Scan {
         source: Source::TimeSeries {
             metric: "http_requests_total".into(),
         },
         predicates: vec![notregex_pred(2, "internal.*")],
         schema: metric_schema(&["job"]),
-    });
+    }));
     assert_eq!(lower(r#"http_requests_total{job!~"internal.*"}"#), expected);
 }
 
@@ -137,13 +139,13 @@ fn q_notregex_predicate() {
 //   predicates in same alphabetical order: job first, then status
 #[test]
 fn q_multi_two_predicates() {
-    let expected = instant(QueryExpr::Scan {
+    let expected = instant(node(NonASAPOp::Scan {
         source: Source::TimeSeries {
             metric: "http_requests_total".into(),
         },
         predicates: vec![eq_pred(2, "api-server"), ne_pred(3, "500")],
         schema: metric_schema(&["job", "status"]),
-    });
+    }));
     assert_eq!(
         lower(r#"http_requests_total{job="api-server",status!="500"}"#),
         expected,
diff --git a/crates/integration-tests/tests/schema.rs b/crates/integration-tests/tests/schema.rs
index 08b925dd1..c616c0d5f 100644
--- a/crates/integration-tests/tests/schema.rs
+++ b/crates/integration-tests/tests/schema.rs
@@ -1,7 +1,7 @@
 //! `Schema::closed` propagation — open/closed invariant tests.
 //!
-//! Verifies that `QueryExpr::output_schema()` propagates the open/closed
-//! completeness flag correctly through a lowered query DAG.
+//! Verifies that the derived `OperatorNode::schema` propagates the open/closed
+//! completeness flag correctly through a lowered query tree.
 //!
 //! Key invariant: a PromQL scan is always `closed: false` (open) because its
 //! label set is runtime-only.  The schema freezes to `closed: true` exactly at
@@ -12,14 +12,14 @@
 use asap_integration_tests::fixtures::lower_promql;
 use asap_types::types::AccuracyTarget;
 
-fn lower(q: &str) -> asap_types::pre_asap::QueryExpr {
+fn lower(q: &str) -> std::rc::Rc<asap_types::ir::OperatorNode> {
     lower_promql(q, AccuracyTarget::Exact).unwrap_or_else(|e| panic!("lower failed for {q:?}: {e}"))
 }
 
 // bare scan is open — the metric's full label set is unknown at plan time
 #[test]
 fn schema_bare_scan_is_open() {
-    let s = lower("http_requests_total").output_schema().unwrap();
+    let s = lower("http_requests_total").schema.clone();
     assert!(!s.closed, "PromQL scan must be open");
 }
 
@@ -27,8 +27,8 @@ fn schema_bare_scan_is_open() {
 #[test]
 fn schema_filtered_scan_is_open() {
     let s = lower(r#"http_requests_total{job="api-server"}"#)
-        .output_schema()
-        .unwrap();
+        .schema
+        .clone();
     assert!(!s.closed, "PromQL scan with predicates must remain open");
     assert_eq!(s.fields.len(), 3, "[ts, value, job]");
 }
@@ -36,9 +36,7 @@ fn schema_filtered_scan_is_open() {
 // per-series rate is label-preserving → output stays open
 #[test]
 fn schema_rate_stays_open() {
-    let s = lower("rate(http_requests_total[5m])")
-        .output_schema()
-        .unwrap();
+    let s = lower("rate(http_requests_total[5m])").schema.clone();
     assert!(!s.closed, "per-series rate is label-preserving; stays open");
 }
 
@@ -46,24 +44,22 @@ fn schema_rate_stays_open() {
 #[test]
 fn schema_count_over_time_stays_open() {
     let s = lower("count_over_time(http_requests_total[5m])")
-        .output_schema()
-        .unwrap();
+        .schema
+        .clone();
     assert!(!s.closed, "per-series count_over_time stays open");
 }
 
 // cross-series sum with no group keys freezes to closed
 #[test]
 fn schema_sum_freezes_to_closed() {
-    let s = lower("sum(http_requests_total)").output_schema().unwrap();
+    let s = lower("sum(http_requests_total)").schema.clone();
     assert!(s.closed, "cross-series aggregate must freeze to closed");
 }
 
 // cross-series sum grouped by job also freezes to closed
 #[test]
 fn schema_sum_by_job_freezes_to_closed() {
-    let s = lower("sum by (job) (http_requests_total)")
-        .output_schema()
-        .unwrap();
+    let s = lower("sum by (job) (http_requests_total)").schema.clone();
     assert!(
         s.closed,
         "grouped cross-series aggregate must freeze to closed"
@@ -74,8 +70,8 @@ fn schema_sum_by_job_freezes_to_closed() {
 #[test]
 fn schema_sum_over_rate_freezes_to_closed() {
     let s = lower("sum by (job) (rate(http_requests_total[5m]))")
-        .output_schema()
-        .unwrap();
+        .schema
+        .clone();
     assert!(
         s.closed,
         "cross-series aggregate over rate must freeze to closed"
@@ -86,8 +82,8 @@ fn schema_sum_over_rate_freezes_to_closed() {
 #[test]
 fn schema_binary_op_two_open_stays_open() {
     let s = lower("http_requests_total / http_errors_total")
-        .output_schema()
-        .unwrap();
+        .schema
+        .clone();
     assert!(!s.closed, "binary op over two open scans must stay open");
 }
 
@@ -95,8 +91,8 @@ fn schema_binary_op_two_open_stays_open() {
 #[test]
 fn schema_binary_op_two_closed_is_closed() {
     let s = lower("sum by (job) (http_requests_total) / sum by (job) (http_errors_total)")
-        .output_schema()
-        .unwrap();
+        .schema
+        .clone();
     assert!(
         s.closed,
         "binary op over two closed aggregates must be closed"
diff --git a/crates/integration-tests/tests/sql_to_physical.rs b/crates/integration-tests/tests/sql_to_physical.rs
index dd4426c22..3bd253748 100644
--- a/crates/integration-tests/tests/sql_to_physical.rs
+++ b/crates/integration-tests/tests/sql_to_physical.rs
@@ -1,4 +1,5 @@
 //! SQL frontend, candidate selection, physical compilation and fresh-run execution.
+mod physical_common;
 use asap_aware_mapping::{search_workload, DefaultCostModel};
 use asap_frontend_sql::{lower_sql, SqlCatalog};
 use asap_physical_operators::{
@@ -7,13 +8,15 @@ use asap_physical_operators::{
     sources::{DataSources, MemorySource},
     values::{Batch, Value},
 };
+use asap_types::ir::export::PhysicalASAPOperatorPayload;
 use asap_types::{
-    post_asap::{compile_post_asap_dag, FieldDataType, PostAsapOperatorPayload},
-    pre_asap::{DataType, Field, QueryExpr, Schema},
+    post_asap::FieldDataType,
+    pre_asap::{DataType, Field, Schema},
     types::AccuracyTarget,
 };
 use futures::StreamExt;
-use std::{collections::BTreeMap, rc::Rc, sync::Arc};
+use physical_common::compile_physical_asap_dag;
+use std::{collections::BTreeMap, sync::Arc};
 
 /// SQL filtering and grouped aggregation survive logical/physical lowering;
 /// rebinding the compiled DAG runs against new data rather than cached results.
@@ -30,26 +33,24 @@ async fn sql_filter_grouped_sum_executes_and_rebinds() {
         "SELECT service, SUM(value) AS total FROM metrics WHERE value > 1 GROUP BY service",
         "SELECT service, SUM(value) AS total FROM metrics GROUP BY service",
     ] {
-        let logical = Rc::new(
-            lower_sql(query, &catalog, AccuracyTarget::Exact)
-                .await
-                .unwrap(),
-        );
+        let logical = lower_sql(query, &catalog, AccuracyTarget::Exact)
+            .await
+            .unwrap();
         let space = search_workload(vec![("sql", logical)]);
         let selected = space
             .global_selection(&DefaultCostModel)
             .assemble_selected_dag(&space.roots[0].1)
             .unwrap()
             .unwrap();
-        let dag = compile_post_asap_dag(&selected).unwrap();
+        let dag = compile_physical_asap_dag(&selected).unwrap();
         let scan = dag
             .nodes
             .iter()
             .find(|node| {
                 matches!(
                     &node.payload,
-                    PostAsapOperatorPayload::Fallback {
-                        expression: QueryExpr::Scan { .. }
+                    PhysicalASAPOperatorPayload::Relational {
+                        operator: asap_types::ir::export::NonASAPOpKind::Scan { .. }
                     }
                 )
             })
@@ -62,7 +63,7 @@ async fn sql_filter_grouped_sum_executes_and_rebinds() {
         let plan = compile(
             &dag,
             BTreeMap::from([(u64::from(scan.id.0), InputContract::bounded(schema.clone()))]),
-            &[u64::from(dag.root.0)],
+            &[u64::from(dag.roots[0].0)],
         )
         .unwrap();
         for multiplier in [1., 2.] {
@@ -88,12 +89,18 @@ async fn sql_filter_grouped_sum_executes_and_rebinds() {
                     .collect()
             })
             .collect();
-            let PostAsapOperatorPayload::Fallback { expression } = &scan.payload else {
-                unreachable!()
-            };
-            let QueryExpr::Scan { source, .. } = expression else {
+            let PhysicalASAPOperatorPayload::Relational {
+                operator:
+                    asap_types::ir::export::NonASAPOpKind::Scan {
+                        source,
+                        predicates: _,
+                        schema: _scan_schema,
+                    },
+            } = &scan.payload
+            else {
                 unreachable!()
             };
+            let expression = asap_types::ir::OperatorNode::reachable(&selected).into_iter().find(|n| matches!(n.non_asap(), Some(asap_types::ir::NonASAPOp::Scan { source: s, .. }) if s == source)).unwrap();
             let mut sources = DataSources::default();
             sources
                 .register(
@@ -110,7 +117,7 @@ async fn sql_filter_grouped_sum_executes_and_rebinds() {
             let bound = plan
                 .instantiate(BTreeMap::from([(
                     u64::from(scan.id.0),
-                    Box::new(sources.bind(expression).unwrap()) as Source<'_>,
+                    Box::new(sources.bind(&expression).unwrap()) as Source<'_>,
                 )]))
                 .unwrap();
             let mut stream = bound
diff --git a/crates/integration-tests/tests/sql_to_post_asap.rs b/crates/integration-tests/tests/sql_to_post_asap.rs
index 4cecd6952..673d939ec 100644
--- a/crates/integration-tests/tests/sql_to_post_asap.rs
+++ b/crates/integration-tests/tests/sql_to_post_asap.rs
@@ -1,63 +1,98 @@
 //! End-to-end SQL query-string → post-ASAP IR pin (issue #191).
 //!
 //! The SQL counterpart of `promql_to_post_asap.rs`: drives SQL text —
-//! `lower_sql` (text → pre-ASAP `QueryExpr`) →
-//! `SketchAlgorithmStrategy::replacements` (pre-ASAP → post-ASAP
-//! `SummaryExpr`, see [`realize`] below) — and pins the resulting
-//! sketch-vs-exact-accumulator shape node by node, the way
-//! `promql_to_post_asap.rs` does for PromQL.
+//! `lower_sql` (text → non-ASAP `OperatorNode` tree) →
+//! `ASAPStrategies::replacements` (→ a tree with ASAP operators,
+//! see [`realize`] below) — and pins the resulting sketch-vs-exact-accumulator
+//! shape node by node, the way `promql_to_post_asap.rs` does for PromQL.
 //!
 //! ## A structural wrinkle PromQL doesn't have
 //!
-//! `lower_promql` returns a *bare* `QueryExpr::Aggregate` for a top-level
+//! `lower_promql` returns a *bare* `NonASAPOp::Aggregate` for a top-level
 //! aggregation (`sum by (job) (m)`, `quantile(0.99, …)`), so [`realize`] can
 //! bind it directly at the DAG root. `lower_sql` never does: DataFusion's
 //! planner always wraps even a single, unaliased aggregate in an identity
 //! `Project` (confirmed below), so a SQL DAG's *root* is normally `Project {
 //! child: Aggregate { .. } }`. Final materialization retains that projection
-//! as a query-time value operation and independently plans its child, keeping
+//! as a query-time non-ASAP node and independently plans its child, keeping
 //! both SELECT-list semantics and the summary-bound aggregate visible.
 
 use std::rc::Rc;
 
-use asap_aware_mapping::replacement::{keep_pre_asap, RealizationError};
+use asap_aware_mapping::replacement::{retain_exact, RealizationError};
 use asap_aware_mapping::{
-    search_workload, DefaultCostModel, Replacement, ReplacementStrategy, ReplacementSubDAG,
-    SketchAlgorithmStrategy, TargetSubDAG,
+    search_workload, ASAPStrategies, DefaultCostModel, Replacement, ReplacementStrategy,
+    ReplacementSubDAG, TargetSubDAG,
 };
 use asap_frontend_sql::{lower_sql, lower_sql_dialect, SqlCatalog};
+use asap_integration_tests::post_asap::post_asap_dag;
+use asap_types::ir::export::{
+    EdgeRole, NonASAPOpKind, PhysicalASAPNodeId, PhysicalASAPOperatorPayload, WirePredicate,
+    WireScalarExpr,
+};
+use asap_types::ir::operator_properties::Reduction;
+use asap_types::ir::{ASAPOp, NonASAPOp, Operator, OperatorNode, Predicate, ScalarExpr};
 use asap_types::post_asap::{
-    compile_post_asap_dag, EdgeRole, ExactKind, ExactParams, FieldDataType, GroupingStrategy,
-    PostAsapOperatorPayload, SketchAlgorithm, SketchKind, SketchParams, SketchStatistic,
-    SummaryExpr, SummaryNode, SummaryUpdate, ValueOperation,
+    ExactKind, ExactParams, FieldDataType, GroupingStrategy, SketchAlgorithm, SketchKind,
+    SketchParams, SketchStatistic, SummaryUpdate,
 };
 use asap_types::pre_asap::expr_ir::ColumnRef;
-use asap_types::pre_asap::query_expr::{QueryExpr, Reduction};
 use asap_types::pre_asap::schema::{DataType, Field, Schema};
 use asap_types::types::AccuracyTarget;
 use asap_types::workload::SqlDialect;
 
-/// This crate has no "bind me one DAG" public API any more —
-/// `SketchAlgorithmStrategy::replacements` always returns every candidate, and
+/// This crate has no "bind me one tree" public API any more —
+/// `ASAPStrategies::replacements` always returns every candidate, and
 /// a caller decides what to keep. This test-only helper reproduces the
-/// take-the-first-(`cost_model`-preferred)-candidate pattern so the
+/// take-the-first-(`cost_model`-preferred)-summary-candidate pattern so the
 /// single-answer pins below don't all repeat it by hand.
-fn realize(expr: &QueryExpr) -> Result<Rc<SummaryNode>, RealizationError> {
-    let root = Rc::new(expr.clone());
-    let target = TargetSubDAG::new(&root);
-    match SketchAlgorithmStrategy::default_cost_model()
-        .replacements(&target)
+fn realize(target: &Rc<OperatorNode>) -> Result<Rc<OperatorNode>, RealizationError> {
+    let target_dag = TargetSubDAG::new(target);
+    match ASAPStrategies::default_cost_model()
+        .replacements(&target_dag)
         .into_iter()
         .next()
     {
         Some(ReplacementSubDAG {
-            replacement: Replacement::Summary(node),
+            replacement: Replacement::SubDAG(node),
             ..
-        }) => Ok(node),
-        _ => keep_pre_asap(&root),
+        }) if node.contains_asap() => Ok(node),
+        _ => retain_exact(target),
+    }
+    .inspect(|node| {
+        node.validate_structure()
+            .expect("planned dag satisfies the unified IR contract")
+    })
+}
+
+/// The single input of a unary non-ASAP node (Project, Filter, Sort, ...) or
+/// of a `FinalizeExactAccumulator`; `None` for anything else.
+fn unary_child(node: &OperatorNode) -> Option<&Rc<OperatorNode>> {
+    match &node.operator {
+        Operator::NonASAP(op) => match op.children().as_slice() {
+            [child] => Some(*child),
+            _ => None,
+        },
+        Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child }) => Some(child),
+        Operator::ASAP(_) => None,
     }
 }
 
+/// A sub-DAG kept as plain (non-ASAP) work: no ASAP operator anywhere below.
+fn is_kept_non_asap(node: &OperatorNode) -> bool {
+    node.non_asap().is_some() && !node.contains_asap()
+}
+
+/// Mirror a scalar-only predicate (no operator references) to its wire form.
+fn wire_pred(pred: &Predicate) -> WirePredicate {
+    WirePredicate(WireScalarExpr::from_expr(
+        &pred.0,
+        &mut |_: &Rc<OperatorNode>| -> PhysicalASAPNodeId {
+            panic!("fixture predicate references no operator")
+        },
+    ))
+}
+
 fn dtype<'a>(schema: &'a Schema, name: &str) -> &'a FieldDataType {
     &schema
         .fields
@@ -89,7 +124,7 @@ fn catalog() -> SqlCatalog {
     )
 }
 
-async fn lower(sql: &str, accuracy: AccuracyTarget) -> QueryExpr {
+async fn lower(sql: &str, accuracy: AccuracyTarget) -> Rc<OperatorNode> {
     lower_sql(sql, &catalog(), accuracy)
         .await
         .unwrap_or_else(|e| panic!("lower failed for {sql:?}: {e}"))
@@ -121,26 +156,27 @@ async fn clickhouse_temporal_sql_reuses_rate_and_increase_physical_summaries() {
         .expect("explicit temporal SQL must lower");
         let physical =
             realize(inner_aggregate(&pre_asap)).expect("temporal reducer must be planned");
-        let SummaryExpr::SummaryAgg {
+        let Operator::ASAP(ASAPOp::SummaryAgg {
             family,
             reduction,
             child,
             ..
-        } = &physical.expr
+        }) = &physical.operator
         else {
-            panic!("expected a shared SummaryAgg, got {:?}", physical.expr);
+            panic!("expected a shared SummaryAgg, got {:?}", physical.operator);
         };
         assert_eq!(family, &expected);
         assert_eq!(reduction, &Reduction::PerEntity);
-        let SummaryExpr::KeepPreAsap(raw) = &child.expr else {
-            panic!(
-                "expected a retained temporal SQL input, got {:?}",
-                child.expr
-            );
-        };
-        assert!(matches!(raw.as_ref(), QueryExpr::TimeRange { range, child }
+        assert!(
+            is_kept_non_asap(child),
+            "expected a retained temporal SQL input, got {:?}",
+            child.operator
+        );
+        assert!(
+            matches!(child.non_asap(), Some(NonASAPOp::TimeRange { range, child, .. })
             if *range == std::time::Duration::from_secs(300)
-                && matches!(child.as_ref(), QueryExpr::Project { .. })));
+                && matches!(child.non_asap(), Some(NonASAPOp::Project { .. })))
+        );
     }
 }
 
@@ -156,16 +192,14 @@ async fn clickhouse_outer_sum_recursively_binds_inner_temporal_aggregate() {
              SELECT service, {function}(latency, ts, {window_ms}) AS v \
              FROM metrics GROUP BY service)"
         );
-        let pre_asap = Rc::new(
-            lower_sql_dialect(
-                &sql,
-                &catalog(),
-                SqlDialect::ClickhouseSQL,
-                AccuracyTarget::Exact,
-            )
-            .await
-            .expect("nested temporal SQL must lower"),
-        );
+        let pre_asap = lower_sql_dialect(
+            &sql,
+            &catalog(),
+            SqlDialect::ClickhouseSQL,
+            AccuracyTarget::Exact,
+        )
+        .await
+        .expect("nested temporal SQL must lower");
         let space = search_workload(vec![("nested", Rc::clone(&pre_asap))]);
         let selection = space.global_selection(&DefaultCostModel);
         let root = selection
@@ -173,30 +207,27 @@ async fn clickhouse_outer_sum_recursively_binds_inner_temporal_aggregate() {
             .expect("materialization failed")
             .expect("root must be discovered");
 
-        fn has_temporal_summary(node: &SummaryNode) -> bool {
-            match &node.expr {
-                SummaryExpr::SummaryAgg {
+        fn has_temporal_summary(node: &OperatorNode) -> bool {
+            match &node.operator {
+                Operator::ASAP(ASAPOp::SummaryAgg {
                     family: FieldDataType::ExactAggregate(ExactKind::Rate | ExactKind::Increase, _),
                     ..
-                } => true,
-                SummaryExpr::ValueOperation { child, .. }
-                | SummaryExpr::SummaryEstimate {
-                    summary_input: child,
-                    ..
-                } => has_temporal_summary(child),
-                _ => false,
+                }) => true,
+                Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) => {
+                    has_temporal_summary(summary_input)
+                }
+                _ => unary_child(node).is_some_and(|child| has_temporal_summary(child)),
             }
         }
         assert!(
             has_temporal_summary(&root),
             "inner {function} was hidden: {root:?}"
         );
-        let dag = compile_post_asap_dag(&root).expect("nested SQL DAG must compile");
+        let dag = post_asap_dag(&root);
         assert!(dag.nodes.iter().any(|node| matches!(
             node.payload,
-            PostAsapOperatorPayload::Value {
-                operation: ValueOperation::Exact(_),
-                ..
+            PhysicalASAPOperatorPayload::Relational {
+                operator: NonASAPOpKind::Aggregate { .. },
             }
         )));
     }
@@ -204,11 +235,14 @@ async fn clickhouse_outer_sum_recursively_binds_inner_temporal_aggregate() {
 
 /// The `Aggregate` node beneath the identity `Project` DataFusion's planner
 /// always wraps a top-level aggregate in — see the module docs above.
-fn inner_aggregate(qe: &QueryExpr) -> &QueryExpr {
-    match qe {
-        QueryExpr::Project { child, .. } => inner_aggregate(child),
-        QueryExpr::Aggregate { .. } => qe,
-        other => panic!("expected a Project{{Aggregate}} shape, got {other:?}"),
+fn inner_aggregate(node: &Rc<OperatorNode>) -> &Rc<OperatorNode> {
+    match node.non_asap() {
+        Some(NonASAPOp::Project { child, .. }) => inner_aggregate(child),
+        Some(NonASAPOp::Aggregate { .. }) => node,
+        _ => panic!(
+            "expected a Project{{Aggregate}} shape, got {:?}",
+            node.operator
+        ),
     }
 }
 
@@ -221,32 +255,27 @@ async fn sql_full_query_retains_project_and_binds_inner_aggregate() {
         AccuracyTarget::Epsilon(0.01),
     )
     .await;
-    assert!(
-        matches!(pre_asap, QueryExpr::Project { .. }),
-        "sanity: a SQL root is a Project, unlike lower_promql's bare Aggregate"
-    );
-    let pre_asap = Rc::new(pre_asap);
+    let Some(NonASAPOp::Project {
+        cols: expected_cols,
+        qualifier: expected_qualifier,
+        ..
+    }) = pre_asap.non_asap()
+    else {
+        panic!("sanity: a SQL root is a Project, unlike lower_promql's bare Aggregate");
+    };
     let space = search_workload(vec![("query", Rc::clone(&pre_asap))]);
     let selection = space.global_selection(&DefaultCostModel);
     let root = selection
         .assemble_selected_dag(&space.roots[0].1)
         .expect("materialization failed")
         .expect("root must be discovered");
-    let QueryExpr::Project {
-        cols: expected_cols,
-        qualifier: expected_qualifier,
-        ..
-    } = pre_asap.as_ref()
-    else {
-        unreachable!()
-    };
-    let SummaryExpr::ValueOperation {
+    let Some(NonASAPOp::Project {
         child,
-        operation: asap_types::post_asap::ValueOperation::Project { cols, qualifier },
-        ..
-    } = &root.expr
+        cols,
+        qualifier,
+    }) = root.non_asap()
     else {
-        panic!("expected retained Project root, got {:?}", root.expr);
+        panic!("expected retained Project root, got {:?}", root.operator);
     };
     assert_eq!(cols, expected_cols, "projection expressions and aliases");
     assert_eq!(qualifier, expected_qualifier, "projection qualifier");
@@ -256,7 +285,10 @@ async fn sql_full_query_retains_project_and_binds_inner_aggregate() {
         FieldDataType::Plain(DataType::Float64)
     );
     assert!(
-        matches!(child.expr, SummaryExpr::SummaryEstimate { .. }),
+        matches!(
+            child.operator,
+            Operator::ASAP(ASAPOp::SummaryEstimate { .. })
+        ),
         "the Aggregate under Project must be summary-bound"
     );
 }
@@ -265,63 +297,62 @@ async fn sql_full_query_retains_project_and_binds_inner_aggregate() {
 /// aggregates are independently selected as physical summaries.
 #[tokio::test]
 async fn sql_join_recursively_binds_both_temporal_aggregate_children() {
-    let pre_asap = Rc::new(
-        lower_sql_dialect(
-            "SELECT a.service, a.v / b.v AS ratio FROM \
-             (SELECT service, asap_rate(latency, ts, 300000) AS v FROM metrics WHERE service='errors' GROUP BY service) a \
-             INNER JOIN \
-             (SELECT service, asap_rate(latency, ts, 300000) AS v FROM metrics WHERE service='requests' GROUP BY service) b \
-             ON b.service=a.service",
-            &catalog(),
-            SqlDialect::ClickhouseSQL,
-            AccuracyTarget::Exact,
-        )
-        .await
-        .expect("two-subquery rate ratio must lower"),
-    );
+    let pre_asap = lower_sql_dialect(
+        "SELECT a.service, a.v / b.v AS ratio FROM \
+         (SELECT service, asap_rate(latency, ts, 300000) AS v FROM metrics WHERE service='errors' GROUP BY service) a \
+         INNER JOIN \
+         (SELECT service, asap_rate(latency, ts, 300000) AS v FROM metrics WHERE service='requests' GROUP BY service) b \
+         ON b.service=a.service",
+        &catalog(),
+        SqlDialect::ClickhouseSQL,
+        AccuracyTarget::Exact,
+    )
+    .await
+    .expect("two-subquery rate ratio must lower");
     let space = search_workload(vec![("ratio", Rc::clone(&pre_asap))]);
     let selection = space.global_selection(&DefaultCostModel);
     let root = selection
         .assemble_selected_dag(&space.roots[0].1)
         .expect("materialization failed")
         .expect("root must be discovered");
-    let SummaryExpr::ValueOperation {
-        child: join,
-        operation: ValueOperation::Project { cols, .. },
-        ..
-    } = &root.expr
+    let Some(NonASAPOp::Project {
+        child: join, cols, ..
+    }) = root.non_asap()
     else {
         panic!(
             "expected Project above relational join, got {:?}",
-            root.expr
+            root.operator
         );
     };
     assert!(matches!(
         &cols[1].expr,
-        QueryExpr::Arithmetic {
+        ScalarExpr::Arithmetic {
             op: asap_types::pre_asap::ArithmeticOpKind::Div,
             ..
         }
     ));
-    let SummaryExpr::RelationalJoin {
+    let Some(NonASAPOp::Join {
         left,
         right,
         kind,
         pred,
-        pruning: None,
-    } = &join.expr
+    }) = join.non_asap()
     else {
-        panic!("expected read-time relational join, got {:?}", join.expr);
+        panic!(
+            "expected read-time relational join, got {:?}",
+            join.operator
+        );
     };
     assert_eq!(kind, &asap_types::pre_asap::JoinKind::Inner);
     assert!(matches!(
-        pred.0.as_ref(),
-        QueryExpr::Compare {
+        &pred.0,
+        ScalarExpr::Compare {
             left,
             op: asap_types::pre_asap::CompareOpKind::Eq,
             right,
-        } if matches!(left.as_ref(), QueryExpr::Column(0))
-            && matches!(right.as_ref(), QueryExpr::Column(2))
+            ..
+        } if matches!(left.as_ref(), ScalarExpr::Column(0))
+            && matches!(right.as_ref(), ScalarExpr::Column(2))
     ));
     assert_eq!(
         join.schema
@@ -332,39 +363,44 @@ async fn sql_join_recursively_binds_both_temporal_aggregate_children() {
         vec!["service", "v", "service", "v"]
     );
     for child in [left, right] {
-        let SummaryExpr::ValueOperation {
-            child: aggregate,
-            operation: ValueOperation::Project { .. },
-            ..
-        } = &child.expr
+        let Some(NonASAPOp::Project {
+            child: aggregate, ..
+        }) = child.non_asap()
         else {
-            panic!("derived table Project was not retained: {:?}", child.expr);
+            panic!(
+                "derived table Project was not retained: {:?}",
+                child.operator
+            );
         };
-        let SummaryExpr::ValueOperation {
-            child: aggregate,
-            operation: ValueOperation::FinalizeExactAccumulator,
-            ..
-        } = &aggregate.expr
+        let Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child: aggregate }) =
+            &aggregate.operator
         else {
             panic!("derived table Project must consume finalized exact values");
         };
         assert!(matches!(
-            aggregate.expr,
-            SummaryExpr::SummaryAgg {
+            aggregate.operator,
+            Operator::ASAP(ASAPOp::SummaryAgg {
                 family: FieldDataType::ExactAggregate(ExactKind::Rate, ExactParams::Rate),
                 ..
-            }
+            })
         ));
     }
     assert!(join
         .guarantee
         .as_ref()
         .is_some_and(|value| value.is_exact()));
-    let dag = compile_post_asap_dag(&root).expect("join DAG must compile");
+    let dag = post_asap_dag(&root);
     let join_id = dag
         .nodes
         .iter()
-        .find(|node| matches!(node.payload, PostAsapOperatorPayload::RelationalJoin { .. }))
+        .find(|node| {
+            matches!(
+                node.payload,
+                PhysicalASAPOperatorPayload::Relational {
+                    operator: NonASAPOpKind::Join { .. },
+                }
+            )
+        })
         .expect("relational join node")
         .id;
     let roles = dag
@@ -383,29 +419,27 @@ async fn unsupported_sql_join_shapes_remain_fail_closed() {
         "SELECT a.service FROM (SELECT service, asap_rate(latency, ts, 300000) v FROM metrics GROUP BY service) a INNER JOIN (SELECT service, asap_rate(latency, ts, 300000) v FROM metrics GROUP BY service) b ON a.v>b.v",
         "SELECT a.service FROM (SELECT service, asap_rate(latency, ts, 300000) v FROM metrics GROUP BY service) a INNER JOIN (SELECT service, asap_rate(latency, ts, 300000) v FROM metrics GROUP BY service) b ON a.service=a.service",
     ] {
-        let pre_asap = Rc::new(
-            lower_sql_dialect(
-                sql,
-                &catalog(),
-                SqlDialect::ClickhouseSQL,
-                AccuracyTarget::Exact,
-            )
-            .await
-            .unwrap_or_else(|error| panic!("join must lower before fail-closed mapping: {error}")),
-        );
+        let pre_asap = lower_sql_dialect(
+            sql,
+            &catalog(),
+            SqlDialect::ClickhouseSQL,
+            AccuracyTarget::Exact,
+        )
+        .await
+        .unwrap_or_else(|error| panic!("join must lower before fail-closed mapping: {error}"));
         let space = search_workload(vec![("unsupported-join", Rc::clone(&pre_asap))]);
         let selection = space.global_selection(&DefaultCostModel);
         let root = selection
             .assemble_selected_dag(&space.roots[0].1)
             .expect("materialization failed")
             .expect("root must be discovered");
-        let SummaryExpr::ValueOperation { child, .. } = &root.expr else {
-            panic!("SQL projection must remain explicit: {:?}", root.expr);
+        let Some(NonASAPOp::Project { child, .. }) = root.non_asap() else {
+            panic!("SQL projection must remain explicit: {:?}", root.operator);
         };
         assert!(
-            matches!(child.expr, SummaryExpr::KeepPreAsap(_)),
+            is_kept_non_asap(child),
             "unsupported join was partially accelerated: {:?}",
-            child.expr
+            child.operator
         );
     }
 }
@@ -414,16 +448,14 @@ async fn unsupported_sql_join_shapes_remain_fail_closed() {
 /// explicit read-time nodes while the aggregate is summary-bound.
 #[tokio::test]
 async fn sql_relational_parents_retain_summary_bound_aggregate() {
-    let pre_asap = Rc::new(
-        lower(
-            "SELECT t.service, t.p FROM \
-             (SELECT service, approx_percentile_cont(latency, 0.9) AS p \
-              FROM metrics GROUP BY service) t \
-             WHERE t.p > 100 ORDER BY t.p DESC LIMIT 5",
-            AccuracyTarget::Epsilon(0.01),
-        )
-        .await,
-    );
+    let pre_asap = lower(
+        "SELECT t.service, t.p FROM \
+         (SELECT service, approx_percentile_cont(latency, 0.9) AS p \
+          FROM metrics GROUP BY service) t \
+         WHERE t.p > 100 ORDER BY t.p DESC LIMIT 5",
+        AccuracyTarget::Epsilon(0.01),
+    )
+    .await;
     let space = search_workload(vec![("query", Rc::clone(&pre_asap))]);
     let selection = space.global_selection(&DefaultCostModel);
     let root = selection
@@ -437,28 +469,29 @@ async fn sql_relational_parents_retain_summary_bound_aggregate() {
     let mut saw_sort = false;
     let mut saw_limit = false;
     loop {
-        match &node.expr {
-            SummaryExpr::ValueOperation {
-                child, operation, ..
-            } => {
-                match operation {
-                    asap_types::post_asap::ValueOperation::Project { .. } => saw_project = true,
-                    asap_types::post_asap::ValueOperation::Filter { .. } => saw_filter = true,
-                    asap_types::post_asap::ValueOperation::Sort { .. } => saw_sort = true,
-                    asap_types::post_asap::ValueOperation::Limit { n, offset, .. } => {
-                        assert_eq!((*n, *offset), (5, 0));
-                        saw_limit = true;
-                    }
-                    _ => {}
-                }
-                node = child;
-            }
-            SummaryExpr::SummaryEstimate { summary_input, .. } => {
-                assert!(matches!(summary_input.expr, SummaryExpr::SummaryAgg { .. }));
-                break;
+        if let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &node.operator {
+            assert!(matches!(
+                summary_input.operator,
+                Operator::ASAP(ASAPOp::SummaryAgg { .. })
+            ));
+            break;
+        }
+        match node.non_asap() {
+            Some(NonASAPOp::Project { .. }) => saw_project = true,
+            Some(NonASAPOp::Filter { .. }) => saw_filter = true,
+            Some(NonASAPOp::Sort { .. }) => saw_sort = true,
+            Some(NonASAPOp::Limit { n, offset, .. }) => {
+                assert_eq!((*n, *offset), (Some(5), 0));
+                saw_limit = true;
             }
-            other => panic!("expected relational parents over SummaryEstimate, got {other:?}"),
+            _ => {}
         }
+        node = unary_child(node).unwrap_or_else(|| {
+            panic!(
+                "expected relational parents over SummaryEstimate, got {:?}",
+                node.operator
+            )
+        });
     }
     assert!(saw_project && saw_filter && saw_sort && saw_limit);
 }
@@ -468,39 +501,47 @@ async fn sql_relational_parents_retain_summary_bound_aggregate() {
 /// may be dropped or moved across the aggregation boundary.
 #[tokio::test]
 async fn sql_filter_keeps_read_predicate_and_summary_population_selection() {
-    let pre_asap = Rc::new(
-        lower(
-            "SELECT t.service, t.p FROM \
-             (SELECT service, approx_percentile_cont(latency, 0.9) AS p \
-              FROM metrics WHERE service = 'api' GROUP BY service) t \
-             WHERE t.p > 100",
-            AccuracyTarget::Epsilon(0.01),
-        )
-        .await,
-    );
+    let pre_asap = lower(
+        "SELECT t.service, t.p FROM \
+         (SELECT service, approx_percentile_cont(latency, 0.9) AS p \
+          FROM metrics WHERE service = 'api' GROUP BY service) t \
+         WHERE t.p > 100",
+        AccuracyTarget::Epsilon(0.01),
+    )
+    .await;
     let expected_read_predicate = {
-        let mut node = pre_asap.as_ref();
+        let mut node = &pre_asap;
         loop {
-            match node {
-                QueryExpr::Filter { pred, .. } => break pred.clone(),
-                QueryExpr::Project { child, .. }
-                | QueryExpr::Sort { child, .. }
-                | QueryExpr::Limit { child, .. } => node = child,
-                other => panic!("expected a Filter above the aggregate, got {other:?}"),
+            match node.non_asap() {
+                Some(NonASAPOp::Filter { pred, .. }) => break pred.clone(),
+                Some(
+                    NonASAPOp::Project { child, .. }
+                    | NonASAPOp::Sort { child, .. }
+                    | NonASAPOp::Limit { child, .. },
+                ) => node = child,
+                _ => panic!(
+                    "expected a Filter above the aggregate, got {:?}",
+                    node.operator
+                ),
             }
         }
     };
     let expected_source_predicates = {
-        let mut node = pre_asap.as_ref();
+        let mut node = &pre_asap;
         loop {
-            match node {
-                QueryExpr::Scan { predicates, .. } => break predicates.clone(),
-                QueryExpr::Project { child, .. }
-                | QueryExpr::Filter { child, .. }
-                | QueryExpr::Aggregate { child, .. }
-                | QueryExpr::Sort { child, .. }
-                | QueryExpr::Limit { child, .. } => node = child,
-                other => panic!("expected a unary SQL plan over Scan, got {other:?}"),
+            match node.non_asap() {
+                Some(NonASAPOp::Scan { predicates, .. }) => break predicates.clone(),
+                Some(
+                    NonASAPOp::Project { child, .. }
+                    | NonASAPOp::Filter { child, .. }
+                    | NonASAPOp::Aggregate { child, .. }
+                    | NonASAPOp::Sort { child, .. }
+                    | NonASAPOp::Limit { child, .. },
+                ) => node = child,
+                _ => panic!(
+                    "expected a unary SQL plan over Scan, got {:?}",
+                    node.operator
+                ),
             }
         }
     };
@@ -516,41 +557,39 @@ async fn sql_filter_keeps_read_predicate_and_summary_population_selection() {
     let mut node = root.as_ref();
     let mut retained_read_predicate = None;
     loop {
-        match &node.expr {
-            SummaryExpr::ValueOperation {
-                child,
-                operation: ValueOperation::Filter { pred },
-                ..
-            } => {
-                retained_read_predicate = Some(pred.clone());
-                node = child;
-            }
-            SummaryExpr::ValueOperation { child, .. } => node = child,
-            SummaryExpr::SummaryEstimate { summary_input, .. } => {
-                let SummaryExpr::SummaryAgg { child, .. } = &summary_input.expr else {
-                    panic!("expected SummaryAgg below SummaryEstimate");
-                };
-                let SummaryExpr::KeepPreAsap(raw_input) = &child.expr else {
-                    panic!("expected raw summary population below SummaryAgg");
-                };
-                let QueryExpr::Scan { predicates, .. } = raw_input.as_ref() else {
-                    panic!("expected source selection to remain a Scan");
-                };
-                assert_eq!(predicates, &expected_source_predicates);
-                break;
-            }
-            other => panic!("expected read-time operations over a summary, got {other:?}"),
+        if let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &node.operator {
+            let Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) = &summary_input.operator else {
+                panic!("expected SummaryAgg below SummaryEstimate");
+            };
+            assert!(
+                is_kept_non_asap(child),
+                "expected raw summary population below SummaryAgg"
+            );
+            let Some(NonASAPOp::Scan { predicates, .. }) = child.non_asap() else {
+                panic!("expected source selection to remain a Scan");
+            };
+            assert_eq!(predicates, &expected_source_predicates);
+            break;
+        }
+        if let Some(NonASAPOp::Filter { pred, .. }) = node.non_asap() {
+            retained_read_predicate = Some(pred.clone());
         }
+        node = unary_child(node).unwrap_or_else(|| {
+            panic!(
+                "expected read-time operations over a summary, got {:?}",
+                node.operator
+            )
+        });
     }
     assert_eq!(retained_read_predicate, Some(expected_read_predicate));
 
-    let dag = compile_post_asap_dag(&root).expect("typed DAG compilation failed");
+    let dag = post_asap_dag(&root);
+    let expected_wire = wire_pred(retained_read_predicate.as_ref().unwrap());
     assert!(dag.nodes.iter().any(|node| matches!(
         &node.payload,
-        PostAsapOperatorPayload::Value {
-            operation: ValueOperation::Filter { pred },
-            ..
-        } if pred == retained_read_predicate.as_ref().unwrap()
+        PhysicalASAPOperatorPayload::Relational {
+            operator: NonASAPOpKind::Filter { pred },
+        } if *pred == expected_wire
     )));
 }
 
@@ -559,15 +598,13 @@ async fn sql_filter_keeps_read_predicate_and_summary_population_selection() {
 /// read-time operation.
 #[tokio::test]
 async fn sql_filter_preserves_local_fallback_boundary_for_unsupported_child() {
-    let pre_asap = Rc::new(
-        lower(
-            "SELECT t.service, t.avg_bytes FROM \
-             (SELECT service, AVG(bytes) AS avg_bytes FROM metrics GROUP BY service) t \
-             WHERE t.avg_bytes > 100",
-            AccuracyTarget::Exact,
-        )
-        .await,
-    );
+    let pre_asap = lower(
+        "SELECT t.service, t.avg_bytes FROM \
+         (SELECT service, AVG(bytes) AS avg_bytes FROM metrics GROUP BY service) t \
+         WHERE t.avg_bytes > 100",
+        AccuracyTarget::Exact,
+    )
+    .await;
     let space = search_workload(vec![("query", Rc::clone(&pre_asap))]);
     let selection = space.global_selection(&DefaultCostModel);
     let root = selection
@@ -578,22 +615,20 @@ async fn sql_filter_preserves_local_fallback_boundary_for_unsupported_child() {
     let mut node = root.as_ref();
     let mut saw_filter = false;
     loop {
-        match &node.expr {
-            SummaryExpr::ValueOperation {
-                child, operation, ..
-            } => {
-                saw_filter |= matches!(operation, ValueOperation::Filter { .. });
-                node = child;
-            }
-            SummaryExpr::KeepPreAsap(fallback) => {
-                assert!(
-                    matches!(fallback.as_ref(), QueryExpr::BinaryOp { .. }),
-                    "AVG's unsupported rewritten child should be opaque, got {fallback:?}"
-                );
-                break;
-            }
-            other => panic!("expected local value operations over fallback child, got {other:?}"),
+        if let Some(NonASAPOp::BinaryOp { .. }) = node.non_asap() {
+            assert!(
+                is_kept_non_asap(node),
+                "AVG's unsupported rewritten child should be kept whole, got {node:?}"
+            );
+            break;
         }
+        saw_filter |= matches!(node.non_asap(), Some(NonASAPOp::Filter { .. }));
+        node = unary_child(node).unwrap_or_else(|| {
+            panic!(
+                "expected local value operations over fallback child, got {:?}",
+                node.operator
+            )
+        });
     }
     assert!(saw_filter, "supported Filter must remain explicit");
 }
@@ -604,7 +639,7 @@ async fn sql_filter_preserves_local_fallback_boundary_for_unsupported_child() {
 /// ```text
 /// SummaryEstimate { query: Quantile{0.99} }            → {…: Float64}
 /// └─ SummaryAgg { Kll{k:269}, input: metrics.latency }  → {…: Sketch(Kll, {k:269})}
-///    └─ KeepPreAsap(Scan)                                → {ts, service, latency, bytes}
+///    └─ Scan (kept non-ASAP)                             → {ts, service, latency, bytes}
 /// ```
 ///
 /// The SQL counterpart of `promql_to_post_asap.rs`'s
@@ -622,12 +657,12 @@ async fn sql_quantile_binds_kll_sketch_over_named_column() {
     let agg = inner_aggregate(&pre_asap);
     let root = realize(agg).expect("binding failed");
 
-    let SummaryExpr::SummaryEstimate {
+    let Operator::ASAP(ASAPOp::SummaryEstimate {
         summary_input,
         query,
-    } = &root.expr
+    }) = &root.operator
     else {
-        panic!("expected SummaryEstimate root, got {:?}", root.expr);
+        panic!("expected SummaryEstimate root, got {:?}", root.operator);
     };
     assert!(matches!(query, SketchStatistic::Quantile { q } if *q == 0.99));
     assert_eq!(
@@ -641,15 +676,15 @@ async fn sql_quantile_binds_kll_sketch_over_named_column() {
         "the summary-state type must not propagate past the estimate"
     );
 
-    let SummaryExpr::SummaryAgg {
+    let Operator::ASAP(ASAPOp::SummaryAgg {
         child,
         family,
         input,
         reduction,
         ..
-    } = &summary_input.expr
+    }) = &summary_input.operator
     else {
-        panic!("expected SummaryAgg, got {:?}", summary_input.expr);
+        panic!("expected SummaryAgg, got {:?}", summary_input.operator);
     };
     assert_eq!(
         family,
@@ -679,10 +714,12 @@ async fn sql_quantile_binds_kll_sketch_over_named_column() {
         )
     );
 
-    let SummaryExpr::KeepPreAsap(kept_leaf) = &child.expr else {
-        panic!("expected KeepPreAsap leaf, got {:?}", child.expr);
-    };
-    assert!(matches!(kept_leaf.as_ref(), QueryExpr::Scan { .. }));
+    assert!(
+        is_kept_non_asap(child),
+        "expected a kept non-ASAP leaf, got {:?}",
+        child.operator
+    );
+    assert!(matches!(child.non_asap(), Some(NonASAPOp::Scan { .. })));
     assert!(
         child
             .schema
@@ -709,12 +746,12 @@ async fn sql_count_distinct_with_epsilon_binds_hll_rse_over_named_column() {
     let agg = inner_aggregate(&pre_asap);
     let root = realize(agg).expect("binding failed");
 
-    let SummaryExpr::SummaryEstimate {
+    let Operator::ASAP(ASAPOp::SummaryEstimate {
         summary_input,
         query,
-    } = &root.expr
+    }) = &root.operator
     else {
-        panic!("expected SummaryEstimate root, got {:?}", root.expr);
+        panic!("expected SummaryEstimate root, got {:?}", root.operator);
     };
     assert!(matches!(query, SketchStatistic::Cardinality));
     assert_eq!(
@@ -723,14 +760,14 @@ async fn sql_count_distinct_with_epsilon_binds_hll_rse_over_named_column() {
         "COUNT(DISTINCT …) reads back out as an integer count"
     );
 
-    let SummaryExpr::SummaryAgg {
+    let Operator::ASAP(ASAPOp::SummaryAgg {
         family,
         input,
         reduction,
         ..
-    } = &summary_input.expr
+    }) = &summary_input.operator
     else {
-        panic!("expected SummaryAgg, got {:?}", summary_input.expr);
+        panic!("expected SummaryAgg, got {:?}", summary_input.operator);
     };
     assert_eq!(
         family,
@@ -763,11 +800,11 @@ async fn sql_exact_workload_binds_accumulators_not_sketches() {
     .await;
     let agg = inner_aggregate(&pre_asap);
     let root = realize(agg).expect("binding failed");
-    let SummaryExpr::SummaryAgg {
+    let Operator::ASAP(ASAPOp::SummaryAgg {
         family, reduction, ..
-    } = &root.expr
+    }) = &root.operator
     else {
-        panic!("expected SummaryAgg, got {:?}", root.expr);
+        panic!("expected SummaryAgg, got {:?}", root.operator);
     };
     assert_eq!(
         family,
@@ -788,37 +825,42 @@ async fn sql_exact_workload_binds_accumulators_not_sketches() {
     let agg = inner_aggregate(&pre_asap);
     let root = realize(agg).expect("binding failed");
     assert!(
-        matches!(root.expr, SummaryExpr::KeepPreAsap(_)),
+        is_kept_non_asap(&root),
         "avg has no mergeable accumulator — stays logical"
     );
+    assert!(
+        root.guarantee.as_ref().is_some_and(|g| g.is_exact()),
+        "a kept logical sub_dag is exact"
+    );
 }
 
 #[tokio::test]
 async fn map_projection_export_preserves_unsupported_child_boundary() {
-    let pre = Rc::new(lower_sql_dialect(
+    let pre = lower_sql_dialect(
         "SELECT map('job', t.service) AS labels, t.avg_bytes FROM (SELECT service, AVG(bytes) AS avg_bytes FROM metrics GROUP BY service) t WHERE t.avg_bytes > 100",
         &catalog(), SqlDialect::ClickhouseSQL, AccuracyTarget::Exact,
-    ).await.unwrap());
+    ).await.unwrap();
     let space = search_workload(vec![("map_query", pre)]);
     let root = space
         .global_selection(&DefaultCostModel)
         .assemble_selected_dag(&space.roots[0].1)
         .unwrap()
         .unwrap();
-    let dag = compile_post_asap_dag(&root).unwrap();
+    let dag = post_asap_dag(&root);
     assert!(dag.nodes.iter().any(|node| matches!(&node.payload,
-        PostAsapOperatorPayload::Value { operation: ValueOperation::Project { cols, .. }, .. }
-        if cols.iter().any(|item| matches!(&item.expr, QueryExpr::FunctionCall { name, .. } if name == "map"))
+        PhysicalASAPOperatorPayload::Relational { operator: NonASAPOpKind::Project { cols, .. } }
+        if cols.iter().any(|item| matches!(&item.expr, WireScalarExpr::FunctionCall { name, .. } if name == "map"))
     )));
     let mut node = root.as_ref();
     loop {
-        match &node.expr {
-            SummaryExpr::ValueOperation { child, .. } => node = child,
-            SummaryExpr::KeepPreAsap(child) => {
-                assert!(matches!(child.as_ref(), QueryExpr::BinaryOp { .. }));
-                break;
-            }
-            other => panic!("unexpected map/fallback composition: {other:?}"),
+        if let Some(NonASAPOp::BinaryOp { .. }) = node.non_asap() {
+            assert!(
+                is_kept_non_asap(node),
+                "fallback child must stay whole: {node:?}"
+            );
+            break;
         }
+        node = unary_child(node)
+            .unwrap_or_else(|| panic!("unexpected map/fallback composition: {:?}", node.operator));
     }
 }
diff --git a/crates/integration-tests/tests/summary_maintenance_lifecycle_e2e.rs b/crates/integration-tests/tests/summary_maintenance_lifecycle_e2e.rs
index eeade3ae5..411644d4b 100644
--- a/crates/integration-tests/tests/summary_maintenance_lifecycle_e2e.rs
+++ b/crates/integration-tests/tests/summary_maintenance_lifecycle_e2e.rs
@@ -2,6 +2,9 @@
 //! source workload -> PromQL lowering -> candidate search ->
 //! summary-maintenance lifecycle selection -> materialized deployment guarantees.
 
+use asap_types::ir::export::PhysicalASAPOperatorPayload;
+use asap_types::ir::ASAPOp;
+use physical_common::compile_physical_asap_dag;
 use std::rc::Rc;
 
 use asap_aware_mapping::cost_model::Cost;
@@ -13,8 +16,9 @@ use asap_aware_mapping::{
     SummaryMaintenanceLifecycleCostInputs, SummaryMaintenanceLifecycleRejection, WorkloadDemand,
 };
 use asap_frontend_promql::lower_promql_workload;
+use asap_types::ir::OperatorNode;
 use asap_types::post_asap::{
-    EvaluationSchedule, SummaryMaintenanceLifecycle, SummaryMaintenanceMode, SummaryNode,
+    EvaluationSchedule, SummaryMaintenanceLifecycle, SummaryMaintenanceMode,
 };
 use asap_types::pre_asap::agg_intent::AggIntent;
 use asap_types::types::AccuracyTarget;
@@ -32,7 +36,7 @@ struct FullyCostedRuntime;
 impl CostModel for FullyCostedRuntime {
     fn raw_query_recompute_total_cost(
         &self,
-        _target: &asap_types::pre_asap::QueryExpr,
+        _target: &OperatorNode,
         _expected_reads: f64,
     ) -> Option<Cost> {
         Some(Cost(1_000.0))
@@ -48,7 +52,7 @@ impl CostModel for FullyCostedRuntime {
 
     fn summary_maintenance_lifecycle_cost_inputs(
         &self,
-        _summary: &SummaryNode,
+        _summary: &OperatorNode,
     ) -> SummaryMaintenanceLifecycleCostInputs {
         SummaryMaintenanceLifecycleCostInputs {
             build_cost: Some(Cost(10.0)),
@@ -61,7 +65,7 @@ impl CostModel for FullyCostedRuntime {
 
     fn summary_maintenance_capabilities(
         &self,
-        _summary: &SummaryNode,
+        _summary: &OperatorNode,
     ) -> SummaryMaintenanceCapabilities {
         SummaryMaintenanceCapabilities {
             incremental_update: true,
@@ -179,8 +183,8 @@ fn promql_dashboard_materializes_continuous_summary_with_explained_rejections()
         .as_array()
         .unwrap()
         .iter()
-        .find(|node| node["kind"] == "SummaryAgg")
-        .expect("exported SummaryAgg node");
+        .find(|node| node["kind"] == "summary_agg")
+        .expect("exported summary_agg node");
     assert_eq!(
         summary_node["detail"]["summary_maintenance"]["selected"]["lifecycle"]["kind"],
         "continuously_maintained"
@@ -217,11 +221,11 @@ fn selected_plan_with_horizon(
 
 fn selected_plan_for_lowered(
     workload: &PlanningWorkload,
-    lowered: asap_types::pre_asap::QueryExpr,
+    lowered: Rc<asap_types::ir::OperatorNode>,
     model: &dyn CostModel,
     horizon: Horizon,
 ) -> asap_aware_mapping::SummaryMaintenanceLifecyclePlan {
-    let root = Rc::new(lowered);
+    let root = lowered;
     let strategies = asap_aware_mapping::default_strategies_with(model);
     let space = search_workload_with(vec![("dashboard", Rc::clone(&root))], &strategies);
     let target = Rc::clone(&space.roots[0].1);
@@ -273,10 +277,7 @@ fn continuous_lifecycle_compiles_and_executes_spatial_kll() {
         runtime::Scope,
         values::{Batch, Value},
     };
-    use asap_types::{
-        post_asap::{compile_post_asap_dag, FieldDataType, PostAsapOperatorPayload},
-        pre_asap::DataType,
-    };
+    use asap_types::{post_asap::FieldDataType, pre_asap::DataType};
     use std::{collections::BTreeMap, sync::Arc};
     let mut workload = dashboard_workload();
     workload.query_workload.query_batch.as_mut().unwrap()[0].query =
@@ -292,11 +293,11 @@ fn continuous_lifecycle_compiles_and_executes_spatial_kll() {
             .summary_maintenance_lifecycle,
         SummaryMaintenanceLifecycle::ContinuouslyMaintained
     );
-    let dag = compile_post_asap_dag(&selected.root).unwrap();
+    let dag = compile_physical_asap_dag(&selected.root).unwrap();
     let build = dag
         .nodes
         .iter()
-        .find(|node| matches!(node.payload, PostAsapOperatorPayload::SummaryAgg { .. }))
+        .find(|node| matches!(node.payload, PhysicalASAPOperatorPayload::SummaryAgg { .. }))
         .unwrap();
     let input = dag
         .edges
@@ -309,7 +310,7 @@ fn continuous_lifecycle_compiles_and_executes_spatial_kll() {
     let candidate = compile_candidate(
         &dag,
         BTreeMap::from([(u64::from(input.0), InputContract::bounded(schema.clone()))]),
-        &[u64::from(dag.root.0)],
+        &[u64::from(dag.roots[0].0)],
         &[u64::from(build.id.0)],
     )
     .unwrap();
@@ -322,14 +323,14 @@ fn continuous_lifecycle_compiles_and_executes_spatial_kll() {
     let rejected = compile_candidate(
         &dag,
         BTreeMap::from([(u64::from(input.0), unbounded)]),
-        &[u64::from(dag.root.0)],
+        &[u64::from(dag.roots[0].0)],
         &[u64::from(build.id.0)],
     );
     assert!(rejected.is_err());
     let request = compile_candidate(
         &dag,
         BTreeMap::from([(u64::from(input.0), InputContract::bounded(schema.clone()))]),
-        &[u64::from(dag.root.0)],
+        &[u64::from(dag.roots[0].0)],
         &[],
     )
     .unwrap();
@@ -446,7 +447,7 @@ fn quantile_workload(query: &str) -> PlanningWorkload {
 fn lifecycle_timed_dag(
     query: &str,
     lifecycle: &SummaryMaintenanceLifecycle,
-) -> (asap_types::post_asap::PostAsapDAG, Vec<u64>) {
+) -> (asap_types::ir::export::PhysicalASAPDAG, Vec<u64>) {
     use asap_aware_mapping::enumerate_summary_maintenance_lifecycles;
     let workload = quantile_workload(query);
     let mut lowered = lower_promql_workload(&workload, 0).unwrap().remove(0);
@@ -487,7 +488,7 @@ fn lifecycle_timed_dag(
 
 /// Compile inputs for a timed DAG: its raw source, available at either phase.
 fn raw_inputs(
-    dag: &asap_types::post_asap::PostAsapDAG,
+    dag: &asap_types::ir::export::PhysicalASAPDAG,
 ) -> std::collections::BTreeMap<u64, asap_physical_operators::physical_planner::InputContract> {
     let raw = dag
         .nodes
@@ -495,7 +496,9 @@ fn raw_inputs(
         .find(|node| {
             matches!(
                 node.payload,
-                asap_types::post_asap::PostAsapOperatorPayload::Fallback { .. }
+                asap_types::ir::export::PhysicalASAPOperatorPayload::Relational {
+                    operator: asap_types::ir::export::NonASAPOpKind::TimeRange { .. }
+                }
             )
         })
         .unwrap();
@@ -527,7 +530,7 @@ fn planner_lifecycle_selection_reproduces_strategy_timing() {
                         != SummaryMaintenanceLifecycle::Ephemeral
                 })
         }));
-        let strategy = asap_types::post_asap::compile_post_asap_dag(&plan.root).unwrap();
+        let strategy = compile_physical_asap_dag(&plan.root).unwrap();
         assert_eq!(plan.execution_timed_dag().unwrap(), strategy, "{query}");
     }
 }
@@ -559,7 +562,7 @@ fn chosen_lifecycle_timing_decides_precompute_contents() {
         let schema = contract.schema.clone();
         let frontier = frontier_from_timing(&dag).unwrap();
         let candidate =
-            compile_candidate(&dag, inputs, &[u64::from(dag.root.0)], &frontier).unwrap();
+            compile_candidate(&dag, inputs, &[u64::from(dag.roots[0].0)], &frontier).unwrap();
         let rows = (1..=100)
             .map(|value| {
                 schema
@@ -640,7 +643,7 @@ fn lifecycle_timing_cuts_one_compilation() {
         let ephemeral = SummaryMaintenanceLifecycle::Ephemeral;
         let (compiled_dag, _) = lifecycle_timed_dag(query, &ephemeral);
         let inputs = raw_inputs(&compiled_dag);
-        let roots = [u64::from(compiled_dag.root.0)];
+        let roots = [u64::from(compiled_dag.roots[0].0)];
         let compiled = compile(&compiled_dag, inputs.clone(), &roots).unwrap();
         for lifecycle in [
             SummaryMaintenanceLifecycle::ContinuouslyMaintained,
@@ -663,7 +666,7 @@ fn lifecycle_timing_cuts_one_compilation() {
                     .iter()
                     .copied()
                     .filter(|state| {
-                        *state == u64::from(dag.root.0)
+                        *state == u64::from(dag.roots[0].0)
                             || dag.edges.iter().any(|edge| {
                                 u64::from(edge.producer.0) == *state
                                     && query_time(u64::from(edge.consumer.0))
@@ -701,15 +704,12 @@ fn chosen_population_lifecycle_decides_precompute_contents() {
         runtime::Scope,
         values::{Batch, Value},
     };
-    use asap_types::post_asap::{
-        maintained_population::PopulationInput, PostAsapOperatorPayload, ValueOperation,
-    };
+    use asap_types::post_asap::maintained_population::PopulationInput;
     use std::{collections::BTreeMap, sync::Arc};
 
     let workload = quantile_workload("topk by(job)(1, m)");
-    let root = Rc::new(
-        with_series_identity(&lower_promql_workload(&workload, 0).unwrap().remove(0)).unwrap(),
-    );
+    let root =
+        with_series_identity(&lower_promql_workload(&workload, 0).unwrap().remove(0)).unwrap();
     let root = MaintainedPopulationStrategy::new(std::slice::from_ref(&root))
         .candidate(&root)
         .unwrap();
@@ -741,9 +741,7 @@ fn chosen_population_lifecycle_decides_precompute_contents() {
             .execution_timed_dag()
             .unwrap();
         let population = dag.nodes.iter().find(|node| node.id == id).unwrap();
-        let PostAsapOperatorPayload::Value {
-            operation: ValueOperation::MaintainPopulation { population },
-        } = &population.payload
+        let PhysicalASAPOperatorPayload::MaintainPopulation { population } = &population.payload
         else {
             panic!("the deployment is the maintained population");
         };
@@ -754,7 +752,14 @@ fn chosen_population_lifecycle_decides_precompute_contents() {
         let raw = dag
             .nodes
             .iter()
-            .find(|node| matches!(node.payload, PostAsapOperatorPayload::Fallback { .. }))
+            .find(|node| {
+                matches!(
+                    node.payload,
+                    PhysicalASAPOperatorPayload::Relational {
+                        operator: asap_types::ir::export::NonASAPOpKind::TimeRange { .. }
+                    }
+                )
+            })
             .unwrap();
         let (raw_id, schema) = (u64::from(raw.id.0), Arc::new(raw.output_schema.clone()));
         let frontier =
@@ -762,7 +767,7 @@ fn chosen_population_lifecycle_decides_precompute_contents() {
         let candidate = compile_candidate(
             &dag,
             BTreeMap::from([(raw_id, InputContract::bounded(schema.clone()))]),
-            &[u64::from(dag.root.0)],
+            &[u64::from(dag.roots[0].0)],
             &frontier,
         )
         .unwrap();
@@ -836,20 +841,18 @@ fn chosen_population_lifecycle_decides_precompute_contents() {
 fn grouped_rate_sum_placement_is_a_lifecycle_choice() {
     use asap_aware_mapping::enumerate_summary_maintenance_lifecycles;
     use asap_physical_operators::physical_planner::{compile_candidate, InputContract};
-    use asap_types::post_asap::{ExactKind, FieldDataType, PostAsapOperatorPayload, SummaryExpr};
+    use asap_types::post_asap::{ExactKind, FieldDataType};
     use std::{collections::BTreeMap, sync::Arc};
 
     let workload = quantile_workload("sum by(job)(rate(m[1m]))");
-    let root = Rc::new(
-        asap_physical_operators::physical_planner::promql_rows::with_series_identity(
-            &lower_promql_workload(&workload, 0).unwrap().remove(0),
-        )
-        .unwrap(),
-    );
-    let is_exact = |node: &SummaryNode, kind: ExactKind| {
-        matches!(&node.expr, SummaryExpr::SummaryAgg {
+    let root = asap_physical_operators::physical_planner::promql_rows::with_series_identity(
+        &lower_promql_workload(&workload, 0).unwrap().remove(0),
+    )
+    .unwrap();
+    let is_exact = |node: &OperatorNode, kind: ExactKind| {
+        matches!(&node.operator, asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
             family: FieldDataType::ExactAggregate(k, _), ..
-        } if *k == kind)
+        }) if *k == kind)
     };
     let inventory = asap_aware_mapping::search_workload(vec![("q", root)])
         .enumerate_candidate_dags(4096)
@@ -859,7 +862,7 @@ fn grouped_rate_sum_placement_is_a_lifecycle_choice() {
         .into_iter()
         .map(|mut forest| forest.remove(0).1)
         .filter(|candidate| {
-            matches!(&candidate.expr, SummaryExpr::ValueOperation { child, .. }
+            matches!(&candidate.operator, asap_types::ir::Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child })
                 if is_exact(child, ExactKind::Sum))
         })
         .collect::<Vec<_>>();
@@ -905,7 +908,14 @@ fn grouped_rate_sum_placement_is_a_lifecycle_choice() {
         let raw = dag
             .nodes
             .iter()
-            .find(|node| matches!(node.payload, PostAsapOperatorPayload::Fallback { .. }))
+            .find(|node| {
+                matches!(
+                    node.payload,
+                    PhysicalASAPOperatorPayload::Relational {
+                        operator: asap_types::ir::export::NonASAPOpKind::TimeRange { .. }
+                    }
+                )
+            })
             .unwrap();
         let frontier =
             asap_physical_operators::physical_planner::frontier_from_timing(&dag).unwrap();
@@ -923,7 +933,7 @@ fn grouped_rate_sum_placement_is_a_lifecycle_choice() {
                 u64::from(raw.id.0),
                 InputContract::bounded(Arc::new(raw.output_schema.clone())),
             )]),
-            &[u64::from(dag.root.0)],
+            &[u64::from(dag.roots[0].0)],
             &frontier,
         )
         .unwrap();
@@ -944,8 +954,8 @@ fn grouped_rate_sum_placement_is_a_lifecycle_choice() {
     else {
         unreachable!()
     };
-    let state = |payload: &PostAsapOperatorPayload, kind: ExactKind| {
-        matches!(payload, PostAsapOperatorPayload::SummaryAgg {
+    let state = |payload: &PhysicalASAPOperatorPayload, kind: ExactKind| {
+        matches!(payload, PhysicalASAPOperatorPayload::SummaryAgg {
             family: FieldDataType::ExactAggregate(k, _), ..
         } if *k == kind)
     };
@@ -959,10 +969,10 @@ fn grouped_rate_sum_placement_is_a_lifecycle_choice() {
 
 /// The lifecycle-timed DAG Planner selects for `query` with upfront series
 /// typing, and whether it keeps an ingestion-time Binary.
-fn typed_selection(query: &str) -> (asap_types::post_asap::PostAsapDAG, bool) {
-    use asap_types::post_asap::{ExecutionTiming, PostAsapOperatorPayload};
+fn typed_selection(query: &str) -> (asap_types::ir::export::PhysicalASAPDAG, bool) {
+    use asap_types::post_asap::ExecutionTiming;
     let workload = quantile_workload(query);
-    let lowered = asap_types::pre_asap::schema::with_promql_series_identity(
+    let lowered = asap_types::ir::schema_support::with_promql_series_identity(
         &lower_promql_workload(&workload, 0).unwrap().remove(0),
     )
     .unwrap();
@@ -970,8 +980,12 @@ fn typed_selection(query: &str) -> (asap_types::post_asap::PostAsapDAG, bool) {
         .execution_timed_dag()
         .unwrap();
     let ingestion_binary = dag.nodes.iter().any(|node| {
-        matches!(node.payload, PostAsapOperatorPayload::Binary { .. })
-            && node.output_state.timing == ExecutionTiming::IngestionTime
+        matches!(
+            node.payload,
+            PhysicalASAPOperatorPayload::Relational {
+                operator: asap_types::ir::export::NonASAPOpKind::BinaryOp { .. }
+            }
+        ) && node.output_state.timing == ExecutionTiming::IngestionTime
     });
     (dag, ingestion_binary)
 }
@@ -979,58 +993,52 @@ fn typed_selection(query: &str) -> (asap_types::post_asap::PostAsapDAG, bool) {
 /// Execute a timed DAG's precompute and query DAGs over `samples`
 /// (`(metric, job, seconds, value)`) at 300s; returns the root's values.
 fn execute_timed(
-    dag: &asap_types::post_asap::PostAsapDAG,
+    dag: &asap_types::ir::export::PhysicalASAPDAG,
     samples: &[(&str, &str, i64, f64)],
 ) -> Vec<f64> {
     use asap_physical_operators::{
-        physical_planner::{
-            compile_candidate, frontier_from_timing, promql_fallback, promql_rows, InputContract,
-        },
+        physical_planner::{compile_candidate, frontier_from_timing, promql_rows, InputContract},
         runtime::Scope,
         values::{Batch, Value},
     };
-    use asap_types::{
-        post_asap::PostAsapOperatorPayload,
-        pre_asap::{QueryExpr, Source},
-    };
+    use asap_types::{ir::export::PhysicalASAPOperatorPayload, pre_asap::Source};
     use std::{collections::BTreeMap, sync::Arc};
     // Raw inputs: a selector Fallback is itself the input; a retained
     // expression reads each of its selectors through its raw-series slots.
     let mut raw = BTreeMap::new();
     for node in &dag.nodes {
-        let PostAsapOperatorPayload::Fallback { expression } = &node.payload else {
+        if !matches!(
+            node.payload,
+            PhysicalASAPOperatorPayload::Relational {
+                operator: asap_types::ir::export::NonASAPOpKind::TimeRange { .. }
+                    | asap_types::ir::export::NonASAPOpKind::Scan { .. }
+            }
+        ) {
             continue;
-        };
-        let metric = |selector: &QueryExpr| match selector {
-            QueryExpr::TimeRange { child, .. } => match child.as_ref() {
-                QueryExpr::Scan {
-                    source: Source::TimeSeries { metric },
-                    ..
-                } => Some(metric.clone()),
-                _ => None,
-            },
-            QueryExpr::Scan {
-                source: Source::TimeSeries { metric },
-                ..
-            } => Some(metric.clone()),
-            _ => None,
-        };
-        if let Some(name) = metric(expression) {
-            raw.insert(
-                u64::from(node.id.0),
-                (Arc::new(node.output_schema.clone()), name),
-            );
-        } else {
-            for (i, (selector, schema)) in promql_fallback::raw_series(expression)
-                .unwrap()
-                .into_iter()
-                .enumerate()
+        }
+        let mut id = node.id;
+        loop {
+            let n = dag.nodes.iter().find(|n| n.id == id).unwrap();
+            if let PhysicalASAPOperatorPayload::Relational {
+                operator:
+                    asap_types::ir::export::NonASAPOpKind::Scan {
+                        source: Source::TimeSeries { metric },
+                        ..
+                    },
+            } = &n.payload
             {
                 raw.insert(
-                    promql_fallback::raw_series_input(u64::from(node.id.0), i),
-                    (schema, metric(&selector).unwrap()),
+                    u64::from(node.id.0),
+                    (Arc::new(node.output_schema.clone()), metric.clone()),
                 );
+                break;
             }
+            id = dag
+                .edges
+                .iter()
+                .find(|e| e.consumer == id)
+                .unwrap()
+                .producer;
         }
     }
     let batch = |schema: &asap_physical_operators::values::SchemaRef, name: &str| {
@@ -1053,7 +1061,7 @@ fn execute_timed(
         raw.iter()
             .map(|(id, (schema, _))| (*id, InputContract::bounded(schema.clone())))
             .collect(),
-        &[u64::from(dag.root.0)],
+        &[u64::from(dag.roots[0].0)],
         &frontier,
     )
     .unwrap();
@@ -1126,7 +1134,7 @@ fn maintained_arithmetic_over_different_selectors_matches_prometheus() {
 }
 
 /// Arithmetic over one selector keeps its maintained layout and adds each
-/// series' two readouts before the quantile.
+/// series' two evaluations before the quantile.
 #[test]
 fn maintained_arithmetic_over_one_selector_executes() {
     let (dag, ingestion_binary) =
diff --git a/crates/integration-tests/tests/time_range.rs b/crates/integration-tests/tests/time_range.rs
index d3ab732fe..95212ca99 100644
--- a/crates/integration-tests/tests/time_range.rs
+++ b/crates/integration-tests/tests/time_range.rs
@@ -1,46 +1,53 @@
-//! `QueryExpr::TimeRange` — range / streaming function tests.
+//! `NonASAPOp::TimeRange` — range / streaming function tests.
 //!
-//! All range functions lower to `Aggregate { child: TimeRange { range, child: Scan } }`.
+//! All range functions lower to `Aggregate { child: TimeRange { range, kind: Range, child: Scan } }`.
 //! The temporal range lives on the `TimeRange` node, not in the `AggIntent`.
 //! `rate` / `increase` use `AggIntent::Rate` / `AggIntent::Increase` (no window field).
 //! `*_over_time` functions reuse the corresponding cross-series intents
-//! (`Count`, `Sum`, `Quantile`, …) — the `TimeRange` child is what marks them
-//! as per-series reductions.
+//! (`Count`, `Sum`, `Quantile`, …) — the `Range` selector child is what marks
+//! them as per-series reductions.
 
 use std::rc::Rc;
 use std::time::Duration;
 
 use asap_integration_tests::fixtures::lower_promql;
 use asap_integration_tests::fixtures::metric_schema;
-use asap_types::pre_asap::{AggIntent, QueryExpr, Reduction, Source};
+use asap_types::ir::{NonASAPOp, OperatorNode, TimeRangeKind};
+use asap_types::pre_asap::{AggIntent, Reduction, Source};
 use asap_types::types::AccuracyTarget;
 
-fn lower(q: &str) -> QueryExpr {
+fn lower(q: &str) -> Rc<OperatorNode> {
     lower_promql(q, AccuracyTarget::Exact).unwrap_or_else(|e| panic!("lower failed for {q:?}: {e}"))
 }
 
-fn scan(metric: &str) -> QueryExpr {
-    QueryExpr::Scan {
+fn node(op: NonASAPOp) -> Rc<OperatorNode> {
+    OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(op))
+        .expect("fixture node derives its schema")
+}
+
+fn scan(metric: &str) -> Rc<OperatorNode> {
+    node(NonASAPOp::Scan {
         source: Source::TimeSeries {
             metric: metric.into(),
         },
         predicates: vec![],
         schema: metric_schema(&[]),
-    }
+    })
 }
 
-fn range_agg(range_secs: u64, intent: AggIntent, metric: &str) -> QueryExpr {
-    QueryExpr::Aggregate {
+fn range_agg(range_secs: u64, intent: AggIntent, metric: &str) -> Rc<OperatorNode> {
+    node(NonASAPOp::Aggregate {
         reduction: Reduction::PerEntity,
         measures: vec![intent],
         output_names: vec!["".into()],
         filters: vec![],
         having: None,
-        child: Rc::new(QueryExpr::TimeRange {
+        child: node(NonASAPOp::TimeRange {
             range: Duration::from_secs(range_secs),
-            child: Rc::new(scan(metric)),
+            kind: TimeRangeKind::Range,
+            child: scan(metric),
         }),
-    }
+    })
 }
 
 // #13 — rate: counter-reset-aware per-second rate; range on TimeRange node
diff --git a/crates/metricsql-parser-vendored/src/optimizer/const_evaluator.rs b/crates/metricsql-parser-vendored/src/optimizer/const_evaluator.rs
index 3ac1170e8..6befd206d 100644
--- a/crates/metricsql-parser-vendored/src/optimizer/const_evaluator.rs
+++ b/crates/metricsql-parser-vendored/src/optimizer/const_evaluator.rs
@@ -12,7 +12,7 @@ use crate::functions::{BuiltinFunction, TransformFunction};
 use crate::parser::{parse_number, ParseError, ParseResult};
 
 #[allow(rustdoc::private_intra_doc_links)]
-/// Partially evaluate `Expr`s so constant subtrees are evaluated at plan time.
+/// Partially evaluate `Expr`s so constant sub-DAGs are evaluated at plan time.
 ///
 /// Note it does not handle algebraic rewrites such as `(a or false)`
 /// --> `a`, which is handled by [`Simplifier`]
diff --git a/crates/planner/src/lib.rs b/crates/planner/src/lib.rs
index 88a085bf8..4f527f148 100644
--- a/crates/planner/src/lib.rs
+++ b/crates/planner/src/lib.rs
@@ -11,15 +11,13 @@
 //! and a catalog — skips this crate and calls
 //! [`asap_aware_mapping::optimize`] directly.
 
-use std::rc::Rc;
-
 use asap_types::parsed_workload::{ParsedWorkload, ParsedWorkloadError};
-use asap_types::pre_asap::query_expr::QueryExpr;
 use asap_types::workload::{PlanningWorkload, QueryLanguage, SqlDialect, WorkloadError};
 
-use asap_frontend_metricsql::{lower_metricsql, MetricsqlError};
+use asap_frontend_metricsql::{lower_metricsql_query, MetricsqlError};
 use asap_frontend_promql::{
-    lower_promql_workload, lower_promql_workload_with_histograms, HistogramCatalog, PromqlError,
+    lower_promql_query_workload, lower_promql_query_workload_with_histograms, HistogramCatalog,
+    PromqlError,
 };
 use asap_frontend_sql::{lower_sql_dialect, SqlCatalog, SqlError};
 
@@ -191,7 +189,7 @@ pub async fn e2e_plan(input: UserInput<'_>) -> Result<PlanOutput, PlanError> {
     input.validate()?;
 
     let exprs = lower(&input).await?;
-    let parsed = ParsedWorkload::new(input.workload.clone(), exprs)?;
+    let parsed = ParsedWorkload::from_roots(input.workload.clone(), exprs)?;
 
     let fallback = MajorPass;
     let pass: &dyn OptimizationPass = input.pass.unwrap_or(&fallback);
@@ -206,7 +204,7 @@ pub async fn e2e_plan(input: UserInput<'_>) -> Result<PlanOutput, PlanError> {
 /// through `lower_sql_batch`, which walks `query_batch` alone and would drop
 /// every repeating query — exactly the entries whose recurrence the lifecycle
 /// stage needs.
-async fn lower(input: &UserInput<'_>) -> Result<Vec<Rc<QueryExpr>>, PlanError> {
+async fn lower(input: &UserInput<'_>) -> Result<Vec<asap_types::ir::QueryRoot>, PlanError> {
     let entries = || input.workload.query_workload.entries();
 
     match &input.frontend_specific {
@@ -229,7 +227,7 @@ async fn lower(input: &UserInput<'_>) -> Result<Vec<Rc<QueryExpr>>, PlanError> {
                     entry_index: Some(index),
                     source: LoweringError::Sql(source),
                 })?;
-                lowered.push(Rc::new(expr));
+                lowered.push(expr.into());
             }
             Ok(lowered)
         }
@@ -237,28 +235,29 @@ async fn lower(input: &UserInput<'_>) -> Result<Vec<Rc<QueryExpr>>, PlanError> {
             now_ms, histograms, ..
         } => {
             let lowered = match histograms {
-                Some(histograms) => lower_promql_workload_with_histograms(
+                Some(histograms) => lower_promql_query_workload_with_histograms(
                     input.workload,
                     histograms.clone(),
                     *now_ms,
                 ),
-                None => lower_promql_workload(input.workload, *now_ms),
+                None => lower_promql_query_workload(input.workload, *now_ms),
             }
             .map_err(|source| PlanError::Lowering {
                 entry_index: None,
                 source: LoweringError::Promql(source),
             })?;
-            Ok(lowered.into_iter().map(Rc::new).collect())
+            Ok(lowered)
         }
         FrontendInput::Metricsql => {
             let mut lowered = Vec::new();
             for (index, entry) in entries().enumerate() {
-                let expr = lower_metricsql(&entry.query.0, entry.requirements.accuracy.target())
-                    .map_err(|source| PlanError::Lowering {
-                        entry_index: Some(index),
-                        source: LoweringError::Metricsql(source),
-                    })?;
-                lowered.push(Rc::new(expr));
+                let expr =
+                    lower_metricsql_query(&entry.query.0, entry.requirements.accuracy.target())
+                        .map_err(|source| PlanError::Lowering {
+                            entry_index: Some(index),
+                            source: LoweringError::Metricsql(source),
+                        })?;
+                lowered.push(expr);
             }
             Ok(lowered)
         }
diff --git a/crates/planner/tests/e2e_plan.rs b/crates/planner/tests/e2e_plan.rs
index ff8a8dde0..3ab55b101 100644
--- a/crates/planner/tests/e2e_plan.rs
+++ b/crates/planner/tests/e2e_plan.rs
@@ -12,7 +12,6 @@ use asap_aware_mapping::{
 };
 use asap_frontend_sql::{lower_sql_dialect, SqlCatalog};
 use asap_planner::{e2e_plan, FrontendInput, PlanError, UserInput, UserInputError};
-use asap_types::post_asap::SummaryExpr;
 use asap_types::pre_asap::schema::{DataType, Field, Schema};
 use asap_types::types::AccuracyTarget;
 use asap_types::workload::{
@@ -137,7 +136,7 @@ async fn builtin_cost_model_cannot_price_lifecycles_and_falls_back_to_raw_recomp
         )
         .await
         .expect("lowers");
-        roots.push((index, Rc::new(expr), Some(accuracy)));
+        roots.push((index, expr, Some(accuracy)));
     }
     let strategies = default_strategies_with_evidence(models.cost, models.evidence);
     let space = search_workload_with_targets(roots, &strategies, models.accuracy);
@@ -150,12 +149,12 @@ async fn builtin_cost_model_cannot_price_lifecycles_and_falls_back_to_raw_recomp
             .expect("assembles")
             .expect("root has a group");
         assert!(
-            !matches!(cost_only.expr, SummaryExpr::KeepPreAsap(_)),
+            cost_only.contains_asap(),
             "entry {}: cost-only selection was expected to pick a summary",
             plan.entry_index
         );
         assert!(
-            matches!(plan.plan.root.expr, SummaryExpr::KeepPreAsap(_))
+            !plan.plan.root.contains_asap()
                 && plan.plan.selected_raw_recompute
                 && plan.plan.deployments.is_empty()
                 && plan.plan.summary_total_cost.is_none()
@@ -390,7 +389,7 @@ async fn lifecycle_decisions_ride_inside_each_plan() {
     assert_eq!(output.plans.len(), 1);
     assert_eq!(output.plans[0].entry_index, 0);
     let _: &Rc<_> = &output.plans[0].plan.root;
-    assert_eq!(output.dags().len(), 1);
+    assert_eq!(output.operator_roots().len(), 1);
 }
 
 /// Each root's lifecycle is planned against the entries that read it: a
@@ -437,3 +436,54 @@ async fn each_plan_counts_only_its_own_entries_reads() {
     let reads: Vec<_> = output.plans.iter().map(|p| p.plan.expected_reads).collect();
     assert_eq!(reads, vec![Some(60.0), Some(6.0)]);
 }
+
+/// Scalar-only and mixed workloads preserve entry bindings without wrapper nodes.
+#[tokio::test]
+async fn scalar_roots_survive_planning_in_workload_order() {
+    for queries in [
+        vec!["2", "time()"],
+        vec!["2", "up * 2", "scalar(sum(up)) + 1"],
+    ] {
+        let workload = PlanningWorkload {
+            query_workload: QueryWorkload {
+                language: QueryLanguage::PromQL,
+                query_batch: Some(queries.iter().map(|q| batch(q)).collect()),
+                repeating_queries: None,
+            },
+            data_workload: Some(DataWorkload {
+                data_ingestion_interval: Evidence {
+                    value: Some(DurationMs(1000)),
+                    ..Default::default()
+                },
+                ..Default::default()
+            }),
+        };
+        let output = e2e_plan(UserInput::new(
+            &workload,
+            FrontendInput::Promql {
+                now_ms: NOW_MS,
+                histograms: None,
+            },
+            PlanningModels::builtin(),
+            lifecycle(),
+        ))
+        .await
+        .unwrap();
+        assert_eq!(
+            output.entry_indices(),
+            (0..queries.len()).collect::<Vec<_>>()
+        );
+        assert!(matches!(
+            output.roots()[0],
+            asap_types::ir::QueryRoot::Scalar(_)
+        ));
+        assert_eq!(output.roots().len(), queries.len());
+        if queries.len() == 3 {
+            assert_eq!(output.plans[0].entry_index, 1);
+            let asap_types::ir::QueryRoot::Scalar(expr) = &output.roots()[2] else {
+                panic!()
+            };
+            assert_eq!(expr.operator_refs().len(), 1);
+        }
+    }
+}
diff --git a/crates/planner/tests/summary_sharing.rs b/crates/planner/tests/summary_sharing.rs
index 41b489e9c..7c198493b 100644
--- a/crates/planner/tests/summary_sharing.rs
+++ b/crates/planner/tests/summary_sharing.rs
@@ -1,6 +1,8 @@
 //! Structurally identical summary producers chosen by different queries are
-//! shared after Pass 1: one `Rc<SummaryNode>` across their plans, costed once.
+//! shared after Pass 1: one `Rc<OperatorNode>` across their plans, costed once.
 
+use asap_types::ir::cse::share_common_sub_dags;
+use asap_types::ir::{ASAPOp, OperatorNode};
 use std::rc::Rc;
 
 use asap_aware_mapping::accuracy::{
@@ -11,7 +13,7 @@ use asap_aware_mapping::pass::{PlanOutput, PlanningModels};
 use asap_aware_mapping::replacement::{default_size_params, DEFAULT_DELTA};
 use asap_aware_mapping::{
     global_selection_with_summary_maintenance_lifecycles, search_workload_with_targets,
-    ReplacementStrategy, SketchAlgorithmStrategy, WorkloadDemand,
+    ASAPStrategies, ReplacementStrategy, WorkloadDemand,
 };
 use asap_aware_mapping::{
     CostModel, CostRate, DefaultCostModel, Horizon, LifecycleInput, SummaryMaintenanceCapabilities,
@@ -21,15 +23,13 @@ use asap_frontend_promql::lower_promql_workload;
 use asap_frontend_sql::SqlCatalog;
 use asap_planner::{e2e_plan, FrontendInput, UserInput};
 use asap_types::post_asap::{
-    share_common_summary_sub_dags, AccuracyError, BoundExpr, CompositionOperator, ErrorMetric,
-    ProbabilityExpr, ResultGuarantee, SketchStatistic,
-};
-use asap_types::post_asap::{
-    FieldDataType, SketchAlgorithm, SketchParams, SummaryExpr, SummaryNode,
+    AccuracyError, BoundExpr, CompositionOperator, ErrorMetric, ProbabilityExpr, ResultGuarantee,
+    SketchStatistic,
 };
+use asap_types::post_asap::{FieldDataType, SketchAlgorithm, SketchParams};
 use asap_types::pre_asap::agg_intent::default_quantile;
 use asap_types::pre_asap::schema::{DataType, Field, Schema};
-use asap_types::pre_asap::{AggIntent, QueryExpr};
+use asap_types::pre_asap::AggIntent;
 use asap_types::types::AccuracyTarget;
 use asap_types::workload::{
     AccuracyRequirement, DataArrival, DataWorkload, DurationMs, Evidence, LatencyRequirement,
@@ -58,7 +58,7 @@ impl CostModel for FixedCosts {
 
     fn summary_maintenance_lifecycle_cost_inputs(
         &self,
-        _summary: &SummaryNode,
+        _summary: &OperatorNode,
     ) -> SummaryMaintenanceLifecycleCostInputs {
         SummaryMaintenanceLifecycleCostInputs {
             build_cost: Some(Cost(self.build)),
@@ -71,7 +71,7 @@ impl CostModel for FixedCosts {
 
     fn summary_maintenance_capabilities(
         &self,
-        _summary: &SummaryNode,
+        _summary: &OperatorNode,
     ) -> SummaryMaintenanceCapabilities {
         SummaryMaintenanceCapabilities {
             incremental_update: true,
@@ -80,7 +80,7 @@ impl CostModel for FixedCosts {
         }
     }
 
-    fn raw_query_recompute_cost(&self, _target: &QueryExpr) -> Option<Cost> {
+    fn raw_query_recompute_cost(&self, _target: &OperatorNode) -> Option<Cost> {
         Some(Cost(self.raw_per_read))
     }
 }
@@ -185,7 +185,7 @@ async fn plan_sql(queries: &[&str], costs: &FixedCosts) -> PlanOutput {
 }
 
 /// Every summary state each plan deploys.
-fn states(output: &PlanOutput) -> Vec<Vec<Rc<SummaryNode>>> {
+fn states(output: &PlanOutput) -> Vec<Vec<Rc<OperatorNode>>> {
     output
         .plans
         .iter()
@@ -202,7 +202,7 @@ fn states(output: &PlanOutput) -> Vec<Vec<Rc<SummaryNode>>> {
 }
 
 /// Whether the two plans deploy exactly the same states, by pointer.
-fn same_states(states: &[Vec<Rc<SummaryNode>>]) -> bool {
+fn same_states(states: &[Vec<Rc<OperatorNode>>]) -> bool {
     states[0].len() == states[1].len()
         && states[0]
             .iter()
@@ -212,7 +212,7 @@ fn same_states(states: &[Vec<Rc<SummaryNode>>]) -> bool {
 
 /// The deployments a consumer would run, deduplicated by pointer.
 fn unique_deployments(output: &PlanOutput) -> usize {
-    let mut seen: Vec<*const SummaryNode> = Vec::new();
+    let mut seen: Vec<*const OperatorNode> = Vec::new();
     for plan in &output.plans {
         for deployment in &plan.plan.deployments {
             let ptr = Rc::as_ptr(&deployment.summary);
@@ -297,12 +297,12 @@ fn kll_k(plan: &asap_aware_mapping::pass::QueryLifecyclePlan) -> u32 {
     let [deployment] = plan.plan.deployments.as_slice() else {
         panic!("one state: {:?}", plan.plan.deployments.len());
     };
-    let SummaryExpr::SummaryAgg {
+    let asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
         family: FieldDataType::Sketch(kind, _),
         ..
-    } = &deployment.summary.expr
+    }) = &deployment.summary.operator
     else {
-        panic!("sketch state: {:?}", deployment.summary.expr);
+        panic!("sketch state: {:?}", deployment.summary.operator);
     };
     let SketchParams::Kll { k } = kind.params() else {
         panic!("KLL state: {kind:?}");
@@ -382,7 +382,7 @@ async fn identical_sql_percentiles_share_one_producer() {
     assert_eq!(unique_deployments(&output), 1);
 }
 
-/// The quantile is a readout parameter: SQL p50 and p99 over one filtered
+/// The quantile is a evaluation parameter: SQL p50 and p99 over one filtered
 /// column build one KLL, named after its input, while each query keeps its
 /// own output column.
 #[tokio::test]
@@ -451,7 +451,7 @@ async fn shared_amortization_alone_can_beat_raw_recompute() {
     assert_eq!(unique_deployments(&output), 1);
 }
 
-/// Synthetic evidence certifying UnivMon readouts; it exercises sharing, never
+/// Synthetic evidence certifying UnivMon evaluations; it exercises sharing, never
 /// runtime accuracy.
 struct UnivMonEvidence;
 
@@ -493,7 +493,7 @@ impl AccuracyModel for UnivMonEvidence {
 /// when the states are identical. `MajorPass` builds candidates with the
 /// built-in accuracy model, so this runs its pipeline with the test model.
 #[test]
-fn certified_frequency_readouts_share_one_univmon_state() {
+fn certified_frequency_evaluations_share_one_univmon_state() {
     let queries = [
         ("distinct_over_time(m[5m])", 0.02),
         ("entropy_over_time(m[5m])", 0.02),
@@ -505,12 +505,10 @@ fn certified_frequency_readouts_share_one_univmon_state() {
         .into_iter()
         .zip(queries)
         .enumerate()
-        .map(|(index, (expr, (_, epsilon)))| {
-            (index, Rc::new(expr), Some(AccuracyTarget::Epsilon(epsilon)))
-        })
+        .map(|(index, (expr, (_, epsilon)))| (index, expr, Some(AccuracyTarget::Epsilon(epsilon))))
         .collect();
     let strategies: Vec<Box<dyn ReplacementStrategy>> =
-        vec![Box::new(SketchAlgorithmStrategy::new_with_planning_inputs(
+        vec![Box::new(ASAPStrategies::new_with_planning_inputs(
             &CHEAP_SUMMARY,
             &UnivMonEvidence,
             &EqualSplitAllocator,
@@ -541,15 +539,17 @@ fn certified_frequency_readouts_share_one_univmon_state() {
             (*index, dag)
         })
         .collect();
-    let mut states: Vec<Rc<SummaryNode>> = Vec::new();
-    for (_, root) in share_common_summary_sub_dags(assembled) {
-        assert!(root.guarantee.is_some(), "{:?}", root.expr);
-        let SummaryExpr::SummaryEstimate { summary_input, .. } = &root.expr else {
-            panic!("summary readout: {:?}", root.expr);
+    let mut states: Vec<Rc<OperatorNode>> = Vec::new();
+    for (_, root) in share_common_sub_dags(assembled) {
+        assert!(root.guarantee.is_some(), "{:?}", root.operator);
+        let asap_types::ir::Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) =
+            &root.operator
+        else {
+            panic!("summary evaluation: {:?}", root.operator);
         };
         assert!(matches!(
-            &summary_input.expr,
-            SummaryExpr::SummaryAgg { family: FieldDataType::Sketch(kind, _), .. }
+            &summary_input.operator,
+            asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg { family: FieldDataType::Sketch(kind, _), .. })
                 if kind.algorithm() == &SketchAlgorithm::UnivMon
         ));
         states.push(Rc::clone(summary_input));
diff --git a/crates/sql-function-catalog/src/lib.rs b/crates/sql-function-catalog/src/lib.rs
index 0ae4ee5ab..f2aedbaa9 100644
--- a/crates/sql-function-catalog/src/lib.rs
+++ b/crates/sql-function-catalog/src/lib.rs
@@ -277,7 +277,7 @@ pub struct ClickHouseBuiltin {
 pub const CLICKHOUSE_BUILTINS: &[ClickHouseBuiltin] = &[
     // Explicit time-series reducers. These deliberately survive under their
     // own names: the SQL frontend validates (value, timestamp, window_ms) and
-    // lowers the window to QueryExpr::TimeRange rather than pretending these
+    // lowers the window to NonASAPOp::TimeRange rather than pretending these
     // are ordinary tabular aggregates.
     ClickHouseBuiltin {
         name: "asap_rate",
diff --git a/crates/types/src/dag_export.rs b/crates/types/src/dag_export.rs
index f26673ea7..9efbd66c5 100644
--- a/crates/types/src/dag_export.rs
+++ b/crates/types/src/dag_export.rs
@@ -1,31 +1,46 @@
-//! Export the pre-ASAP [`QueryExpr`] DAG as a generic node/edge DAG, for tools
-//! that need to render or diff the IR (the `dag_export` example + the
-//! `tools/dag-viewer` viewer — see issue #133) rather than walk it in Rust.
+//! Export an [`OperatorNode`] DAG as a generic node/edge dag, for tools
+//! that need to render or diff the IR (the `dag_export` devtools binary +
+//! the `tools/dag-viewer` viewer — see issue #133) rather than walk it in
+//! Rust.
 //!
-//! `QueryExpr` already derives `Serialize`, but as a Rust-shaped tagged DAG
-//! (`Rc` children nested inside each variant's own field). This module
-//! flattens that into an explicit node list + child-id edges — the shape a
-//! generic DAG renderer wants — and additionally tags each node with
-//! [`structural_hash`](crate::pre_asap::cse::structural_hash), so a caller
-//! with several exported queries can spot identical sub-DAGs (a
-//! shared `Scan`, a repeated `Aggregate` shape, …) by comparing hashes
-//! rather than re-implementing `QueryExpr: PartialEq` structural comparison
-//! client-side.
+//! `OperatorNode` already derives `Serialize`, but as a Rust-shaped tagged
+//! tree (`Rc` children nested inside each variant's own field, repeated once
+//! per reference). This module flattens that into an explicit node list +
+//! child-id edges — one entry per unique node, deduplicated by `Rc` pointer
+//! identity, so a shared sub-DAG stays one node with several parents — and
+//! additionally tags each node with
+//! [`structural_hash`](crate::ir::cse::structural_hash), so a caller with
+//! several exported queries can spot identical sub-DAGs (a shared `Scan`, a
+//! repeated `Aggregate` shape, …) by comparing hashes rather than
+//! re-implementing structural comparison client-side.
 //!
 //! This is literally the same hashing
-//! [`share_common_sub_dags`](crate::pre_asap::cse::share_common_sub_dags)
-//! uses to bucket candidates in its `InternTable` (issue #223 stage 3) — not
-//! a parallel reimplementation. `tools/dag-viewer`'s "shared sub-DAG"
+//! [`share_common_sub_dags`](crate::ir::cse::share_common_sub_dags) uses to
+//! bucket candidates in its `InternTable` (issue #223 stage 3) — not a
+//! parallel reimplementation. `tools/dag-viewer`'s "shared sub-DAG"
 //! highlighting is still a *proxy* for real CSE, though: a hash match here
 //! only means two nodes are legal `InternTable` bucket-mates (same coarse
-//! hash), the same candidate-narrowing step `structural_hash` performs
-//! inside `InternTable::intern` — it does not mean `share_common_sub_dags`
-//! actually ran on this data and merged them onto one `Rc` (that also
-//! requires the `PartialEq` check `InternTable::intern` performs, and the
+//! hash) — it does not mean `share_common_sub_dags` actually ran on this
+//! data and merged them onto one `Rc` (that also requires the structural
+//! equality check `InternTable::intern` performs, and the
 //! `Schema::has_unique_key` legality gate, neither of which this export
 //! step evaluates). See `tools/dag-viewer/README.md` for the up-to-date
 //! caveat.
 //!
+//! There is one IR before and after ASAP optimization, so there is one
+//! exporter: an ordinary operator and an ASAP summary operator are both
+//! rendered by the same per-variant [`shape`] match, whichever entry point
+//! ([`export`], [`export_summary`], [`export_post_asap`]) reached them.
+//!
+//! ## Scalar expressions
+//!
+//! A [`ScalarExpr`] is owned by value by an operator field (`Filter.pred`,
+//! `Project.cols`, …) and is rendered into that operator's `detail`, not as
+//! a node of its own. The operator nodes a scalar expression reads
+//! (`scalar(v)`, `EXISTS (subquery)`, …) *are* nodes of the dag — they are
+//! in [`OperatorNode::children`] — so inside `detail` each such reference is
+//! rendered as `{"scalar_ref": <child node id>}` rather than inlined.
+//!
 //! ## `DAGNode::notes` — a layering seam, not a feature this module implements
 //!
 //! [`DAGNode`] also carries `notes: Vec<`[`DAGNote`]`>`, always empty coming
@@ -33,13 +48,12 @@
 //! `asap_types`, never the reverse — can annotate an already-exported DAG
 //! after the fact without this module needing to know anything about that
 //! layer's concepts. Concretely: `asap-aware-mapping`'s `explanation` module
-//! (issue #257) computes `structural_hash` over the same `QueryExpr`
-//! sub-DAGs this module does (via the identical function). The devtools
-//! exporter uses that hash to narrow candidates, then compares
-//! `ReplacementExplanation::target` with [`DAGNode::source_expr`] for a
-//! collision-safe match before pushing a [`DAGNote`] onto the node.
-//! `asap_types` itself never constructs a `DAGNote` — see [`DAGNode::notes`]
-//! for the layering rule this keeps.
+//! (issue #257) computes `structural_hash` over the same nodes this module
+//! does (via the identical function). The devtools exporter uses that hash
+//! to narrow candidates, then compares its target with
+//! [`DAGNode::source_node`] for a collision-safe match before pushing a
+//! [`DAGNote`] onto the node. `asap_types` itself never constructs a
+//! `DAGNote` — see [`DAGNode::notes`] for the layering rule this keeps.
 
 use std::collections::HashMap;
 use std::rc::Rc;
@@ -47,9 +61,11 @@ use std::rc::Rc;
 use serde::Serialize;
 
 use crate::cost::CostAnnotation;
-use crate::post_asap::{AccuracyError, ResultGuarantee, SummaryExpr, SummaryNode};
-use crate::pre_asap::cse::{structural_hash, HashCache};
-use crate::pre_asap::query_expr::{QueryExpr, Source};
+use crate::ir::cse::{structural_hash, HashCache};
+use crate::ir::operator_properties::Source;
+use crate::ir::{ASAPOp, NonASAPOp, Operator, OperatorNode, ScalarExpr};
+use crate::post_asap::{AccuracyError, ResultGuarantee};
+use crate::pre_asap::schema::FieldDataType;
 
 /// One flattened IR node. `detail` holds this node's own scalar fields
 /// (predicates, aggregate funcs, schema, sort keys, …) — everything except
@@ -57,56 +73,48 @@ use crate::pre_asap::query_expr::{QueryExpr, Source};
 #[derive(Debug, Clone, Serialize)]
 pub struct DAGNode {
     pub id: u32,
-    /// The `QueryExpr` variant name (e.g. `"Aggregate"`).
+    /// The operator variant name — [`Operator::kind_name`] (e.g.
+    /// `"Aggregate"`, `"SummaryAgg"`).
     pub kind: &'static str,
     /// Short human-readable summary for a node's collapsed on-DAG label.
     pub label: String,
     pub detail: serde_json::Value,
-    /// Output schema carried by every exported node. Edge renderers use the
-    /// child node's schema as the schema flowing along child → consumer.
+    /// Output schema carried by every exported node ([`OperatorNode::schema`]
+    /// as JSON). Edge renderers use the child node's schema as the schema
+    /// flowing along child → consumer.
     #[serde(skip_serializing_if = "Option::is_none")]
     pub schema: Option<serde_json::Value>,
-    /// Child node ids, in the variant's field order (e.g. `Join` is
-    /// `[left, right]`).
+    /// Child node ids in [`OperatorNode::children`] order: the operator's
+    /// own inputs in field order (e.g. `Join` is `[left, right]`), then the
+    /// nodes referenced from its scalar expressions.
     pub children: Vec<u32>,
     /// Explicit workload-wide identity assigned by a higher-level exporter.
     /// Viewers use this field to union nodes and must not reconstruct a
     /// structural signature client-side.
     #[serde(skip_serializing_if = "Option::is_none")]
     pub workload_node_id: Option<u32>,
-    /// [`structural_hash`](crate::pre_asap::cse::structural_hash) of the
-    /// sub-DAG rooted at this node — the exact same function `cse`'s
-    /// `InternTable` uses to bucket CSE candidates, so two nodes hash
-    /// equally here iff they would land in the same `InternTable` bucket.
-    /// See the module doc for what a hash match here does and doesn't
-    /// guarantee.
-    ///
-    /// `None` for the same reason `source_expr` is `None` — a post-ASAP-
-    /// originated node in an [`export_post_asap`] merged DAG has no
-    /// `QueryExpr` to hash. Omitted from JSON entirely (rather than, say,
-    /// serialized as `0`) so a consumer's shared-sub-DAG-by-hash pass can
-    /// tell "no hash" apart from a real hash that happens to collide with a
-    /// placeholder — `0` is a legal `structural_hash` output, not a safe
-    /// sentinel.
+    /// [`structural_hash`](crate::ir::cse::structural_hash) of the sub-DAG
+    /// rooted at this node — the exact same function `cse`'s `InternTable`
+    /// uses to bucket CSE candidates, so two nodes hash equally here iff they
+    /// would land in the same `InternTable` bucket. See the module doc for
+    /// what a hash match here does and doesn't guarantee. Always `Some`
+    /// for a node this module produces; the `Option` is retained for the
+    /// JSON shape (`None` is omitted rather than serialized as a sentinel,
+    /// since `0` is a legal hash).
     #[serde(skip_serializing_if = "Option::is_none")]
     pub hash: Option<u64>,
-    /// Exact source expression for in-process annotation matching. It is not
-    /// part of the JSON format: callers first narrow by `hash`, then compare
-    /// this value structurally to avoid treating a hash collision as node
-    /// identity.
-    ///
-    /// `None` for a node with no corresponding pre-ASAP `QueryExpr` at all —
-    /// only possible for a post-ASAP-originated node inside a merged
-    /// [`export_post_asap`] DAG (a `SummaryAgg`/`SummaryJoin`/… node has no
-    /// single `QueryExpr` it corresponds to). Every node [`export`] itself
-    /// produces is pre-ASAP by construction and always carries `Some`.
+    /// The exported node itself, for in-process annotation matching. Not
+    /// part of the JSON format: callers first narrow by `hash`, then
+    /// compare this value (by pointer or structurally) to avoid treating a
+    /// hash collision as node identity. Always `Some` for a node this
+    /// module produces.
     #[serde(skip)]
-    pub source_expr: Option<QueryExpr>,
-    /// In-process identity of the source `QueryExpr`. Unlike `source_expr`'s
-    /// structural value, this preserves an `Rc` child reached from multiple
-    /// parents so post-ASAP flattening can retain true DAG sharing.
+    pub source_node: Option<Rc<OperatorNode>>,
+    /// In-process identity of `source_node` (`Rc::as_ptr` as an address):
+    /// the key the builder deduplicates on, so a node reached from several
+    /// parents is exported once. Not part of the JSON format.
     #[serde(skip)]
-    source_ptr: Option<usize>,
+    pub source_ptr: Option<usize>,
     /// Arbitrary reporting-layer annotations for this node — e.g. why a
     /// replacement exists here. `asap_types` never populates this itself
     /// (it has no notion of a "replacement" at all — see the module doc's
@@ -187,7 +195,7 @@ pub struct EdgeCostAnnotation {
     pub cost: CostAnnotation,
 }
 
-/// One query's exported DAG. `nodes[root as usize]` is the DAG's root.
+/// One query's exported dag. `nodes[root as usize]` is the DAG's root.
 #[derive(Debug, Clone, Serialize)]
 pub struct ExportDAG {
     pub nodes: Vec<DAGNode>,
@@ -195,8 +203,7 @@ pub struct ExportDAG {
     /// See [`EdgeCostAnnotation`]. Always empty unless a higher layer
     /// explicitly populated it (same layering rule as [`DAGNode::notes`]);
     /// omitted from JSON entirely when empty, so every existing producer of
-    /// [`ExportDAG`] (every call to [`export`]/[`export_summary`]) is
-    /// unaffected.
+    /// [`ExportDAG`] is unaffected.
     #[serde(default, skip_serializing_if = "Vec::is_empty")]
     pub edge_annotations: Vec<EdgeCostAnnotation>,
 }
@@ -205,10 +212,10 @@ pub struct ExportDAG {
 #[derive(Debug, Clone, Serialize)]
 pub struct NamedDAG {
     pub name: String,
-    /// The original query text (SQL or PromQL) this DAG was lowered from,
-    /// for display alongside the DAG — not used by `export` itself, since
-    /// that only sees the already-lowered `QueryExpr`. Optional because not
-    /// every producer of a `NamedDAG` has the source text on hand.
+    /// The original query text (SQL or PromQL) this dag was lowered from,
+    /// for display alongside the dag — not used by `export` itself, since
+    /// that only sees the already-lowered DAG. Optional because not every
+    /// producer of a `NamedDAG` has the source text on hand.
     #[serde(skip_serializing_if = "Option::is_none")]
     pub source: Option<String>,
     pub dag: ExportDAG,
@@ -228,15 +235,13 @@ pub struct NamedDAG {
     /// [`TargetReplacement::before`]/`::after` (small, self-contained
     /// before/after pairs, one per independently-discovered replacement
     /// site), this is a single flattened [`ExportDAG`] spanning the whole
-    /// query: every node that has no winning replacement renders as an
-    /// ordinary pre-ASAP [`DAGNode`] (same shape [`export`] itself
-    /// produces), and every node that does splices in its winning
-    /// candidate's shape instead — a rewritten [`QueryExpr`] sub-DAG, or a
-    /// bound `SummaryNode` sub-DAG, rendered inline in the very same node
-    /// list. `None` unless a higher layer explicitly built one (e.g. the
-    /// `dag_export` devtools binary's `--post-asap` flag); omitted from the
-    /// JSON entirely when absent, so every existing producer/consumer of
-    /// `NamedDAG` is unaffected.
+    /// query: every node that has no winning replacement renders as it does
+    /// in [`export`], and every node that does splices in its winning
+    /// candidate's sub-DAG instead, in the very same node list. `None`
+    /// unless a higher layer explicitly built one (e.g. the `dag_export`
+    /// devtools binary's `--post-asap` flag); omitted from the JSON entirely
+    /// when absent, so every existing producer/consumer of `NamedDAG` is
+    /// unaffected.
     #[serde(default, skip_serializing_if = "Option::is_none")]
     pub post_dag: Option<ExportDAG>,
     /// This query's own selected-workload cost/benefit — one of issue
@@ -282,81 +287,51 @@ pub struct WorkloadDAG {
     pub workload_cost: Option<crate::cost::WorkloadCostSummary>,
 }
 
-// ── Post-ASAP replacement export — a second, layering-seam-shaped feature ──
+// ── Post-ASAP replacement export — a layering-seam-shaped feature ──────────
 //
-// Everything below this point is the post-ASAP counterpart of the pre-ASAP
-// flattening above: [`export_summary`] flattens a `SummaryNode` the same way
-// [`export`] flattens a `QueryExpr`, and [`TargetReplacement`] is the
-// generic, crate-agnostic "one replacement site, before and after" shape a
-// higher layer (`asap-aware-mapping`, via the `dag_export` devtools binary's
-// `--post-asap` flag) populates after running its own search — the exact
-// same layering rule [`DAGNode::notes`]'s doc above already states: this
-// module never runs `asap_aware_mapping::replacement::search_workload_with`
-// itself, never picks a "winning" candidate, and has no opinion on what a
+// [`TargetReplacement`] is the generic, crate-agnostic "one replacement
+// site, before and after" shape a higher layer (`asap-aware-mapping`, via
+// the `dag_export` devtools binary's `--post-asap` flag) populates after
+// running its own search — the exact same layering rule [`DAGNode::notes`]'s
+// doc above already states: this module never runs
+// `asap_aware_mapping::replacement::search_workload_with` itself, never
+// picks a "winning" candidate, and has no opinion on what a
 // `ReplacementProvenance` or a cost model even is. It only defines shapes
 // concrete and serializable enough for a higher layer to fill in, and for
 // `tools/dag-viewer` to render without needing to know anything about
 // `asap-aware-mapping`'s own vocabulary.
-//
-// A single whole-query "post-ASAP DAG" isn't attempted here, and isn't
-// representable in the current type system either: `SummaryExpr` has no
-// variant letting a `SummaryNode` be embedded back inside a plain
-// `QueryExpr`'s child slot (`QueryExpr`'s own children are always
-// `Rc<QueryExpr>`, never `Rc<SummaryNode>`), so there is no way to splice a
-// post-ASAP binding back into its original pre-ASAP DAG in place. Inventing
-// a bridge type for that is a real `asap_types`/`asap-aware-mapping` IR
-// design decision, well beyond what a devtools visualization export should
-// decide unilaterally. Instead, each independently-discovered replacement
-// target gets its own small, self-contained `before`/`after` pair — the
-// target's own pre-ASAP sub-DAG, and either the winning `SummaryNode` or the
-// winning rewritten `QueryExpr`, both of which *are* fully representable
-// today via [`export`]/[`export_summary`] as-is.
-
-/// One flattened post-ASAP node — the [`SummaryExpr`] analogue of
-/// [`DAGNode`]. `detail` holds this node's own scalar fields (the summarized
-/// column, the summary family, grouping strategy, sketch-query kind, …) —
-/// everything except its `SummaryNode` children, which live in `children`
-/// instead.
-///
-/// Unlike [`DAGNode`], this carries no `hash`/`source_expr` pair: nothing in
-/// this module ever needs to re-identify a particular `SummaryDAGNode` the
-/// way `DAGNode::hash` lets a higher layer re-identify a pre-ASAP node (a
-/// `SummaryNode` is always freshly exported for exactly one
-/// [`TargetReplacementAfter::Summary`] site, never matched back against a
-/// separately-exported DAG the way pre-ASAP notes are).
-///
-/// Several of `SummaryExpr`'s own fields (`FieldDataType`,
-/// `GroupingStrategy`, `SketchStatistic`) derive neither `Serialize` nor
-/// `Deserialize` in `asap_types::post_asap` — they carry no reporting
-/// obligation there, since nothing before this module ever needed to
-/// serialize a post-ASAP node. Rather than adding `Serialize` impls to
-/// `post_asap`'s own core types purely for this devtools-facing export (a
-/// change to that module's own public API contract, out of scope for a
-/// reporting concern), this module renders those particular fields into
-/// `detail` via their `Debug` formatting instead — human-readable, and
-/// sufficient for the display purpose `detail` exists for on every other
-/// node in this file (see [`DAGNode::detail`]'s own doc), at the cost of
-/// those particular fields being opaque strings rather than structured JSON
-/// on the `SummaryDAGNode` side of the export.
+
+/// One flattened node of a [`SummaryDAG`] — the same node as a
+/// [`DAGNode`], in the shape the summary-maintenance consumers read:
+/// snake_case `kind`, the accuracy guarantee as its own field, no
+/// hash/annotation seams.
 #[derive(Debug, Clone, Serialize)]
 pub struct SummaryDAGNode {
     pub id: u32,
-    /// The `SummaryExpr` variant name (e.g. `"SummaryAgg"`).
+    /// The operator variant name in snake_case (e.g. `"summary_agg"`,
+    /// `"scan"`) — see [`snake_case_kind`].
     pub kind: &'static str,
     /// Short human-readable summary for a node's collapsed on-DAG label.
     pub label: String,
     pub detail: serde_json::Value,
-    /// Child node ids, in the variant's field order (e.g. `SummaryJoin` is
-    /// `[outer, inner]`).
+    /// [`OperatorNode::schema`] as JSON.
+    #[serde(skip_serializing_if = "Option::is_none")]
+    pub schema: Option<serde_json::Value>,
+    /// Child node ids in [`OperatorNode::children`] order.
     pub children: Vec<u32>,
     /// The value's machine-readable accuracy guarantee (issue #172) —
-    /// [`SummaryNode::guarantee`] serialized structurally (metric, symbolic
+    /// [`OperatorNode::guarantee`] serialized structurally (metric, symbolic
     /// bound, failure probability, provenance including any budget
     /// allocation), not as prose. Omitted when the node carries none (raw
     /// summary state, or a family with no error model), so every consumer
     /// predating this field parses the same shape it always has.
     #[serde(default, skip_serializing_if = "Option::is_none")]
     pub guarantee: Option<ResultGuarantee>,
+    /// The exported node itself, so a caller annotating the dag can find
+    /// a node by `Rc` pointer identity rather than by walk order. Not part
+    /// of the JSON format. Always `Some`.
+    #[serde(skip)]
+    pub source_node: Option<Rc<OperatorNode>>,
 }
 
 /// One accuracy-illegal candidate a higher layer's search refused for a
@@ -378,239 +353,14 @@ pub struct TargetRejection {
     pub error: AccuracyError,
 }
 
-/// One post-ASAP `SummaryNode` DAG, flattened the same way [`ExportDAG`]
-/// flattens a pre-ASAP `QueryExpr` DAG.
+/// A DAG flattened into [`SummaryDAGNode`]s — the same dag [`ExportDAG`]
+/// holds, in the summary-maintenance consumers' node shape.
 #[derive(Debug, Clone, Serialize)]
 pub struct SummaryDAG {
     pub nodes: Vec<SummaryDAGNode>,
     pub root: u32,
 }
 
-/// Flatten a [`SummaryNode`] the same way [`export`] flattens a `QueryExpr`
-/// — post-order, one [`SummaryDAGNode`] per [`SummaryExpr`] variant, no
-/// memoization of repeated `Rc<SummaryNode>` references (a shared
-/// sub-expression reachable through two parents is flattened twice, into two
-/// separate node entries — the same "this is a flattened DAG view, not a
-/// pointer-identity-preserving DAG" behavior [`build`] already has for
-/// `QueryExpr`).
-///
-/// A `KeepPreAsap(inner)` leaf embeds the *whole* pre-ASAP sub-DAG beneath it
-/// as a nested [`ExportDAG`] (via [`export(inner)`](export)) inside its own
-/// `detail` field (`{"pre_asap_sub_dag": <ExportDAG>}`) rather than trying to
-/// flatten it into this same node list — [`DAGNode`] and [`SummaryDAGNode`]
-/// are different types with different id spaces, so mixing them into one
-/// `Vec` isn't type-safe; nesting is. `label` for a `KeepPreAsap` node is
-/// `format!("KeepPreAsap({kind})")`, where `kind` is the inner sub-DAG's own
-/// top-level `DAGNode::kind`.
-pub fn export_summary(node: &SummaryNode) -> SummaryDAG {
-    let mut nodes = Vec::new();
-    let root = build_summary(node, &mut nodes);
-    SummaryDAG { nodes, root }
-}
-
-fn push_summary_node(
-    nodes: &mut Vec<SummaryDAGNode>,
-    kind: &'static str,
-    label: String,
-    detail: serde_json::Value,
-    children: Vec<u32>,
-    guarantee: Option<ResultGuarantee>,
-) -> u32 {
-    let id = nodes.len() as u32;
-    nodes.push(SummaryDAGNode {
-        id,
-        kind,
-        label,
-        detail,
-        children,
-        guarantee,
-    });
-    id
-}
-
-/// A short, human-readable label for a [`crate::post_asap::FieldDataType`]
-/// (e.g. `"Sketch(Kll)"`, `"ExactAggregate(Sum)"`) — for
-/// [`SummaryDAGNode::label`] text on a `SummaryAgg`/`SummaryJoin` node. Not
-/// exhaustive prose (mirrors `asap_aware_mapping::replacement::describe_intent`'s
-/// own "this is a label, not a decision" stance) — every variant is covered,
-/// but via `Debug` for the inner kind rather than hand-written prose per
-/// algorithm.
-fn family_label(family: &crate::post_asap::FieldDataType) -> String {
-    use crate::post_asap::FieldDataType;
-    match family {
-        FieldDataType::Plain(dtype) => format!("Plain({dtype:?})"),
-        FieldDataType::ExactAggregate(kind, _) => format!("ExactAggregate({kind:?})"),
-        FieldDataType::Sketch(kind, _grouping) => format!("Sketch({:?})", kind.algorithm()),
-        FieldDataType::Sample(kind, _) => format!("Sample({kind:?})"),
-        FieldDataType::Wavelet(kind, _) => format!("Wavelet({kind:?})"),
-        FieldDataType::StatModel(kind, _) => format!("StatModel({kind:?})"),
-    }
-}
-
-/// `(kind, label, detail)` for every [`SummaryExpr`] variant *except*
-/// [`SummaryExpr::KeepPreAsap`] — that variant has no `SummaryDAGNode`/
-/// `DAGNode` of its own (see [`build_summary`]/[`build_summary_hybrid`], its
-/// only two callers, both of which special-case it before ever reaching
-/// this function). Factored out so [`build_summary`] (nests a `KeepPreAsap`
-/// leaf's pre-ASAP sub-DAG as its own [`SummaryDAG`]) and
-/// [`build_summary_hybrid`] (splices that same sub-DAG directly into a
-/// shared [`ExportDAG`] node list — see [`export_post_asap`]) can't drift
-/// apart on how every *other* variant's own shape is described, since
-/// nothing about that description differs between the two.
-macro_rules! define_summary_kind_tags {
-    ($($pattern:pat => $tag:literal),+ $(,)?) => {
-        #[cfg(test)]
-        const SUMMARY_KIND_TAGS: &[&str] = &[$($tag),+];
-
-        fn summary_kind_tag(expr: &SummaryExpr) -> &'static str {
-            match expr {
-                SummaryExpr::KeepPreAsap(_) => unreachable!(
-                    "summary_kind_tag's callers special-case KeepPreAsap"
-                ),
-                $($pattern => $tag),+
-            }
-        }
-    };
-}
-
-define_summary_kind_tags! {
-    SummaryExpr::BinaryOp { .. } => "SummaryBinaryOp",
-
-    SummaryExpr::ValueOperation { .. } => "ValueOperation",
-    SummaryExpr::RelationalJoin { .. } => "RelationalJoin",
-    SummaryExpr::SummaryAgg { .. } => "SummaryAgg",
-    SummaryExpr::SummaryJoin { .. } => "SummaryJoin",
-    SummaryExpr::SummarySubtract { .. } => "SummarySubtract",
-    SummaryExpr::SummaryDelete { .. } => "SummaryDelete",
-    SummaryExpr::SummaryEstimate { .. } => "SummaryEstimate",
-    SummaryExpr::SummaryMerge { .. } => "SummaryMerge",
-}
-
-fn summary_shape(expr: &SummaryExpr) -> (&'static str, String, serde_json::Value) {
-    let kind = summary_kind_tag(expr);
-    match expr {
-        SummaryExpr::KeepPreAsap(_) => {
-            unreachable!("summary_shape's callers special-case KeepPreAsap before calling it")
-        }
-        SummaryExpr::BinaryOp { operator, .. } => {
-            let label = format!("BinaryOp({:?})", operator.kind);
-            let detail = serde_json::json!({
-                "kind": format!("{:?}", operator.kind),
-                "vector_match": operator.vector_match,
-            });
-            (kind, label, detail)
-        }
-
-        SummaryExpr::ValueOperation {
-            operation, timing, ..
-        } => (
-            kind,
-            format!("ValueOperation({operation:?})"),
-            serde_json::json!({
-                "operation": format!("{operation:?}"),
-                "timing": timing.as_str(),
-            }),
-        ),
-        SummaryExpr::RelationalJoin {
-            kind: join_kind,
-            pred,
-            ..
-        } => (
-            kind,
-            format!("RelationalJoin({join_kind:?})"),
-            serde_json::json!({ "join_kind": join_kind, "predicate": pred }),
-        ),
-        SummaryExpr::SummaryAgg {
-            family,
-            input,
-            reduction,
-            grouping,
-            ..
-        } => {
-            let label = format!("SummaryAgg({})", family_label(family));
-            let detail = serde_json::json!({
-                "family": format!("{family:?}"),
-                "input": input,
-                "reduction": reduction,
-                "grouping": format!("{grouping:?}"),
-            });
-            (kind, label, detail)
-        }
-        SummaryExpr::SummaryJoin { key, family, .. } => {
-            let label = format!("SummaryJoin({})", family_label(family));
-            let detail = serde_json::json!({
-                "key": key,
-                "family": format!("{family:?}"),
-            });
-            (kind, label, detail)
-        }
-        SummaryExpr::SummarySubtract { .. } => {
-            (kind, "SummarySubtract".into(), serde_json::json!({}))
-        }
-        SummaryExpr::SummaryDelete { key, .. } => {
-            let detail = serde_json::json!({ "key": key });
-            (kind, "SummaryDelete".into(), detail)
-        }
-        SummaryExpr::SummaryEstimate { query, .. } => {
-            let label = format!("SummaryEstimate({query:?})");
-            let detail = serde_json::json!({ "query": format!("{query:?}") });
-            (kind, label, detail)
-        }
-        SummaryExpr::SummaryMerge { children, .. } => {
-            let label = format!("SummaryMerge({} children)", children.len());
-            (kind, label, serde_json::json!({}))
-        }
-    }
-}
-
-/// `expr`'s own `Rc<SummaryNode>` children, in the variant's field order
-/// (e.g. `SummaryJoin` is `[outer, inner]`) — empty for
-/// [`SummaryExpr::KeepPreAsap`], which has no `SummaryNode` children at all
-/// (only a boxed pre-ASAP `QueryExpr`). Shared by [`build_summary`] and
-/// [`build_summary_hybrid`] for the same reason [`summary_shape`] is.
-fn summary_children(expr: &SummaryExpr) -> Vec<&Rc<SummaryNode>> {
-    match expr {
-        SummaryExpr::KeepPreAsap(_) => vec![],
-        SummaryExpr::BinaryOp { lhs, rhs, .. } => vec![lhs, rhs],
-
-        SummaryExpr::ValueOperation { child, .. } => vec![child],
-        SummaryExpr::RelationalJoin { left, right, .. } => vec![left, right],
-        SummaryExpr::SummaryAgg { child, .. } => vec![child],
-        SummaryExpr::SummaryJoin { outer, inner, .. } => vec![outer, inner],
-        SummaryExpr::SummarySubtract { left, right } => vec![left, right],
-        SummaryExpr::SummaryDelete { summary_input, .. } => vec![summary_input],
-        SummaryExpr::SummaryEstimate { summary_input, .. } => vec![summary_input],
-        SummaryExpr::SummaryMerge { children, .. } => children.iter().collect(),
-    }
-}
-
-/// Recursively flatten `node`, appending [`SummaryDAGNode`]s to `nodes` in
-/// post-order (children pushed before their parent), and return the pushed
-/// root's id. Exhaustive over every [`SummaryExpr`] variant, matching this
-/// file's own exhaustive style for `QueryExpr` in [`build`].
-fn build_summary(node: &SummaryNode, nodes: &mut Vec<SummaryDAGNode>) -> u32 {
-    if let SummaryExpr::KeepPreAsap(inner) = &node.expr {
-        let pre_asap_sub_dag = export(inner);
-        let inner_kind = pre_asap_sub_dag.nodes[pre_asap_sub_dag.root as usize].kind;
-        let label = format!("KeepPreAsap({inner_kind})");
-        let detail = serde_json::json!({ "pre_asap_sub_dag": pre_asap_sub_dag });
-        return push_summary_node(
-            nodes,
-            "KeepPreAsap",
-            label,
-            detail,
-            vec![],
-            node.guarantee.clone(),
-        );
-    }
-    let children: Vec<u32> = summary_children(&node.expr)
-        .into_iter()
-        .map(|child| build_summary(child, nodes))
-        .collect();
-    let (kind, label, detail) = summary_shape(&node.expr);
-    push_summary_node(nodes, kind, label, detail, children, node.guarantee.clone())
-}
-
 /// One replacement site a higher layer (the `dag_export` binary) found by
 /// running `asap_aware_mapping::replacement::search_workload_with` +
 /// `CandidateLogicalASAPDAGs::cost_sorted` and picking the best-ranked candidate for one
@@ -624,7 +374,7 @@ pub struct TargetReplacement {
     /// so renderers can explain a clicked post-ASAP node without guessing by
     /// label, hash, or DAG shape.
     pub decision_id: u32,
-    /// Id of the [`DAGNode`] (in this query's own `DAG.nodes`, i.e. the
+    /// Id of the [`DAGNode`] (in this query's own `dag.nodes`, i.e. the
     /// [`NamedDAG`] this `TargetReplacement` is attached to) this
     /// replacement's `before` sub-DAG is rooted at.
     pub target_pre_id: u32,
@@ -648,7 +398,7 @@ pub struct TargetReplacement {
     /// doesn't estimate a numeric cost for this candidate shape (see that
     /// field's own doc upstream).
     pub cost: f64,
-    /// The target's own pre-ASAP sub-DAG, before replacement — literally
+    /// The target's own sub-DAG, before replacement — literally
     /// `export(target)` for the `TargetSubDAGCandidates`'s own `target`, reused as-is.
     pub before: ExportDAG,
     pub after: TargetReplacementAfter,
@@ -668,8 +418,10 @@ pub struct TargetReplacement {
 }
 
 /// What a [`TargetReplacement`] became — either a genuine post-ASAP binding
-/// or a still-pre-ASAP-shaped structural rewrite, mirroring
-/// `asap_aware_mapping::replacement::Replacement`'s own two variants.
+/// or a still-relational structural rewrite, mirroring
+/// `asap_aware_mapping::replacement::Replacement`'s own two variants. Both
+/// carry an ordinary [`ExportDAG`]: the unified IR renders a summary sub-DAG
+/// and a rewritten relational sub-DAG through the same [`export`].
 ///
 /// Serializes as `{"kind": "Summary"|"Rewrite", "DAG": {...}}` (serde's
 /// adjacently-tagged representation for a `#[serde(tag = "kind", content =
@@ -680,73 +432,83 @@ pub struct TargetReplacement {
 #[serde(tag = "kind", content = "dag")]
 pub enum TargetReplacementAfter {
     /// A `Replacement::Summary` candidate — a genuine post-ASAP binding.
-    Summary(SummaryDAG),
-    /// A `Replacement::Rewrite` candidate — still pre-ASAP shaped (CSE
+    Summary(ExportDAG),
+    /// A `Replacement::Rewrite` candidate — still relational (CSE
     /// share/recompute, `AvgToSumOverCountStrategy`, and `RollupStrategy`
-    /// all produce this kind), so this reuses [`ExportDAG`]/[`export`] too,
-    /// not a new type.
+    /// all produce this kind).
     Rewrite(ExportDAG),
 }
 
-/// Flatten `expr` into a [`ExportDAG`].
-pub fn export(expr: &QueryExpr) -> ExportDAG {
-    let mut nodes = Vec::new();
-    // One cache for the whole export — persisted across every `build`/
-    // `push_node` call, not reset per node, so `structural_hash` memoizes
-    // real work across this pass instead of re-walking an already-hashed
-    // shared descendant once per node that references it.
-    let mut cache = HashCache::new();
-    // No substitution: an ordinary pre-ASAP export never splices anything
-    // in — see `build`'s own doc for why it always takes a `find_winner`
-    // callback regardless (so `export_post_asap` can share this exact
-    // per-variant traversal instead of duplicating it).
-    let root = build(expr, &mut nodes, &mut cache, &mut |_| None);
-    ExportDAG {
-        nodes,
-        root,
-        edge_annotations: Vec::new(),
-    }
-}
-
-/// What a higher layer found for one specific pre-ASAP node when building a
-/// merged post-ASAP DAG via [`export_post_asap`] — see that function's own
-/// doc for the full design. `asap_types` has no opinion on *how* this is
+/// What a higher layer found for one specific node when building a merged
+/// post-ASAP dag via [`export_post_asap`] — see that function's own doc
+/// for the full design. `asap_types` has no opinion on *how* this is
 /// decided (that's `asap_aware_mapping::replacement::search_workload_with` +
 /// `CandidateLogicalASAPDAGs::cost_sorted`'s job, a higher layer, exactly the layering rule
 /// [`DAGNode::notes`] already states); it only defines the shape a decision
-/// comes back in.
+/// comes back in. Both variants render identically (one IR, one builder);
+/// they are kept apart so the caller's `Replacement` maps one-to-one.
 #[derive(Debug, Clone)]
 pub enum PostAsapSubstitution {
     /// This exact node has a winning `Replacement::Rewrite` — keep building
-    /// from `.0` instead of the original node. Still pre-ASAP shaped, so
-    /// [`build`] renders it via the same ordinary `DAGNode` path — see
-    /// [`build`]'s own doc for why `.0`'s own top level is rendered without
-    /// re-querying `find_winner` on it (its descendants still are).
+    /// from `replacement` instead of the original node.
     Rewrite {
-        replacement: Rc<QueryExpr>,
+        replacement: Rc<OperatorNode>,
         decision: DAGDecision,
     },
-    /// This exact node has a winning `Replacement::Summary` — switch to
-    /// rendering `.0`'s bound `SummaryNode` shape from here down, via
-    /// [`build_summary_hybrid`].
+    /// This exact node has a winning `Replacement::Summary` — keep building
+    /// from `replacement` (a summary-bound sub-DAG) instead of the original
+    /// node.
     Summary {
-        replacement: Rc<SummaryNode>,
+        replacement: Rc<OperatorNode>,
         decision: DAGDecision,
     },
 }
 
+/// Flatten the DAG rooted at `root` into a [`ExportDAG`]: one [`DAGNode`]
+/// per unique reachable node, children pushed before their parents.
+pub fn export(root: &Rc<OperatorNode>) -> ExportDAG {
+    let mut no_substitution = |_: &Rc<OperatorNode>| None;
+    let mut builder = Builder::new(&mut no_substitution);
+    let root = builder.build(root);
+    builder.finish(root)
+}
+
+/// Flatten the DAG rooted at `node` into a [`SummaryDAG`] — the same
+/// nodes [`export`] produces, in the [`SummaryDAGNode`] shape (snake_case
+/// `kind`, `guarantee` as its own field).
+pub fn export_summary(node: &Rc<OperatorNode>) -> SummaryDAG {
+    let dag = export(node);
+    let nodes = dag
+        .nodes
+        .into_iter()
+        .map(|node| {
+            let source = node
+                .source_node
+                .expect("every exported node carries its source");
+            SummaryDAGNode {
+                id: node.id,
+                kind: snake_case_kind(&source.operator),
+                label: node.label,
+                detail: node.detail,
+                schema: node.schema,
+                children: node.children,
+                guarantee: source.guarantee.clone(),
+                source_node: Some(source),
+            }
+        })
+        .collect();
+    SummaryDAG {
+        nodes,
+        root: dag.root,
+    }
+}
+
 /// Build one merged "whole query, but post-ASAP" [`ExportDAG`] by walking
-/// `root`'s ordinary pre-ASAP shape and, at every node, asking `find_winner`
-/// whether *that exact node* has a winning replacement — if so, splicing
-/// the replacement's own shape in at that position instead, in the very
-/// same flattened node list (not a nested sub-DAG the way
-/// [`TargetReplacement::before`]/`::after` — small, independent, per-site
-/// before/after pairs — already do; see this file's "Post-ASAP replacement
-/// export" section doc for why *that* design doesn't attempt a single
-/// whole-query composite, and why this one can: this is a synthetic
-/// id/edge list, the same kind of thing [`ExportDAG`] already is for the
-/// pre-ASAP side, not a real `QueryExpr`/`SummaryNode` value with a type
-/// system to satisfy).
+/// `root` and, at every node, asking `find_winner` whether *that exact
+/// node* has a winning replacement — if so, splicing the replacement's own
+/// sub-DAG in at that position instead, in the very same flattened node
+/// list (not a nested sub-dag the way [`TargetReplacement::before`]/
+/// `::after` — small, independent, per-site before/after pairs — do).
 ///
 /// `find_winner` is the whole layering seam: `asap_types` never runs
 /// `asap_aware_mapping::replacement::search_workload_with` or
@@ -758,7 +520,7 @@ pub enum PostAsapSubstitution {
 /// for [`TargetReplacement`] discovery, and passes it in here unchanged.
 ///
 /// `find_winner` is deliberately consulted only once per node, at the
-/// moment [`build`] first reaches it — **not** re-consulted on a
+/// moment the builder first reaches it — **not** re-consulted on a
 /// substitution's own immediate top level (only on that substitution's
 /// *descendants*, which get an ordinary fresh call same as any other node).
 /// This matters for correctness, not just efficiency:
@@ -770,225 +532,189 @@ pub enum PostAsapSubstitution {
 /// re-query at exactly that one level is what makes this termination-safe
 /// for every registered strategy, not just the ones that happen not to
 /// return the target itself as a candidate.
+///
+/// Every node a substitution introduced carries the substitution's
+/// [`DAGDecision`] (`role = "replacement_root"` on the spliced-in root,
+/// `"replacement_region"` on its newly exported descendants); a descendant
+/// that was already exported before the splice (a shared input the
+/// replacement reuses) keeps whatever it already had.
 pub fn export_post_asap(
-    root: &QueryExpr,
-    find_winner: &mut dyn FnMut(&QueryExpr) -> Option<PostAsapSubstitution>,
+    root: &Rc<OperatorNode>,
+    find_winner: &mut dyn FnMut(&Rc<OperatorNode>) -> Option<PostAsapSubstitution>,
 ) -> ExportDAG {
-    let mut nodes = Vec::new();
-    let mut cache = HashCache::new();
-    let root_id = build(root, &mut nodes, &mut cache, find_winner);
-    deduplicate_pointer_shared_nodes(nodes, root_id)
+    let mut builder = Builder::new(find_winner);
+    let root = builder.build(root);
+    builder.finish(root)
 }
 
-fn deduplicate_pointer_shared_nodes(nodes: Vec<DAGNode>, root: u32) -> ExportDAG {
-    let mut by_source_ptr = HashMap::<usize, u32>::new();
-    let mut old_to_new = vec![0_u32; nodes.len()];
-    let mut deduplicated = Vec::with_capacity(nodes.len());
-    for mut node in nodes {
-        node.children = node
-            .children
-            .into_iter()
-            .map(|child| old_to_new[child as usize])
-            .collect();
-        if let Some(existing) = node
-            .source_ptr
-            .and_then(|source_ptr| by_source_ptr.get(&source_ptr).copied())
-        {
-            old_to_new[node.id as usize] = existing;
-            continue;
-        }
-        let old_id = node.id;
-        let new_id = deduplicated.len() as u32;
-        node.id = new_id;
-        if let Some(source_ptr) = node.source_ptr {
-            by_source_ptr.insert(source_ptr, new_id);
+/// The one flattening pass behind every entry point. Nodes are memoized by
+/// `Rc` pointer identity: a node reached from several parents (an operator
+/// input shared with a scalar reference, say) is exported once.
+struct Builder<'a> {
+    nodes: Vec<DAGNode>,
+    /// `Rc::as_ptr` of every node already exported (or substituted) → its id.
+    ids: HashMap<*const OperatorNode, u32>,
+    /// One cache for the whole export — persisted across every node, not
+    /// reset per node, so `structural_hash` memoizes real work across this
+    /// pass instead of re-walking an already-hashed shared descendant once
+    /// per node that references it.
+    cache: HashCache,
+    find_winner: &'a mut dyn FnMut(&Rc<OperatorNode>) -> Option<PostAsapSubstitution>,
+}
+
+impl<'a> Builder<'a> {
+    fn new(
+        find_winner: &'a mut dyn FnMut(&Rc<OperatorNode>) -> Option<PostAsapSubstitution>,
+    ) -> Self {
+        Self {
+            nodes: Vec::new(),
+            ids: HashMap::new(),
+            cache: HashCache::new(),
+            find_winner,
         }
-        old_to_new[old_id as usize] = new_id;
-        deduplicated.push(node);
     }
 
-    ExportDAG {
-        nodes: deduplicated,
-        root: old_to_new[root as usize],
-        edge_annotations: Vec::new(),
+    fn finish(self, root: u32) -> ExportDAG {
+        ExportDAG {
+            nodes: self.nodes,
+            root,
+            edge_annotations: Vec::new(),
+        }
     }
-}
 
-macro_rules! define_query_kind_tags {
-    ($($pattern:pat => $tag:literal),+ $(,)?) => {
-        #[cfg(test)]
-        const QUERY_KIND_TAGS: &[&str] = &[$($tag),+];
-
-        fn kind_tag(expr: &QueryExpr) -> &'static str {
-            match expr {
-                $($pattern => $tag),+,
-                other @ (QueryExpr::Column(_)
-                | QueryExpr::Literal(_)
-                | QueryExpr::Compare { .. }
-                | QueryExpr::BoolAnd(_)
-                | QueryExpr::BoolOr(_)
-                | QueryExpr::Not(_)
-                | QueryExpr::IsNull(_)
-                | QueryExpr::IsNotNull(_)
-                | QueryExpr::Cast { .. }
-                | QueryExpr::InList { .. }
-                | QueryExpr::FunctionCall { .. }
-                | QueryExpr::Arithmetic { .. }
-                | QueryExpr::Case { .. }) => unreachable!(
-                    "kind_tag reached a scalar QueryExpr variant directly: {other:?}"
-                ),
+    /// Export `node` (or, when `find_winner` has a substitution for it, the
+    /// substitution's sub-DAG in its place) and return its id.
+    fn build(&mut self, node: &Rc<OperatorNode>) -> u32 {
+        let ptr = Rc::as_ptr(node);
+        if let Some(&id) = self.ids.get(&ptr) {
+            return id;
+        }
+        let (replacement, decision) = match (self.find_winner)(node) {
+            None => return self.build_node(node),
+            Some(PostAsapSubstitution::Rewrite {
+                replacement,
+                decision,
+            })
+            | Some(PostAsapSubstitution::Summary {
+                replacement,
+                decision,
+            }) => (replacement, decision),
+        };
+        let first = self.nodes.len();
+        let root = self.build_node(&replacement);
+        for exported in &mut self.nodes[first..] {
+            if exported.decision.is_none() {
+                let mut node_decision = decision.clone();
+                node_decision.role = if exported.id == root {
+                    "replacement_root"
+                } else {
+                    "replacement_region"
+                };
+                exported.decision = Some(node_decision);
             }
         }
-    };
-}
-
-define_query_kind_tags! {
-    QueryExpr::Scan { .. } => "Scan",
-    QueryExpr::PromqlScalarBridge(_) => "PromqlScalarBridge",
-    QueryExpr::EvalTimestamp => "EvalTimestamp",
-    QueryExpr::CurrentTimestamp => "CurrentTimestamp",
-    QueryExpr::PromqlVectorFromScalar(_) => "PromqlVectorFromScalar",
-    QueryExpr::PromqlScalarFromVector(_) => "PromqlScalarFromVector",
-    QueryExpr::PromqlRelabel { .. } => "PromqlRelabel",
-    QueryExpr::PromqlInfoEnrich { .. } => "PromqlInfoEnrich",
-    QueryExpr::PromqlSeriesSample { .. } => "PromqlSeriesSample",
-    QueryExpr::Filter { .. } => "Filter",
-    QueryExpr::Project { .. } => "Project",
-    QueryExpr::Aggregate { .. } => "Aggregate",
-    QueryExpr::Dedup { .. } => "Dedup",
-    QueryExpr::Concat { .. } => "Concat",
-    QueryExpr::Join { .. } => "Join",
-    QueryExpr::SetOp { .. } => "SetOp",
-    QueryExpr::Sort { .. } => "Sort",
-    QueryExpr::Limit { .. } => "Limit",
-    QueryExpr::PromqlSubquery { .. } => "PromqlSubquery",
-    QueryExpr::TimeRange { .. } => "TimeRange",
-    QueryExpr::TimeShift { .. } => "TimeShift",
-    QueryExpr::SQLWindowFunc { .. } => "SQLWindowFunc",
-    QueryExpr::BinaryOp { .. } => "BinaryOp",
-}
-
-/// Push one flattened node for `expr`. `expr` is the *whole* sub-DAG this
-/// node represents (not just its own fields) — `hash` is
-/// [`structural_hash(expr)`](structural_hash), the identical function and
-/// the identical input `InternTable::intern` would hash for this same
-/// sub-DAG, so this node's `hash` matches what `cse::share_common_sub_dags`
-/// would bucket it under. `kind` is [`kind_tag(expr)`](kind_tag), not a
-/// caller-supplied argument — see that function's doc for why.
-fn push_node(
-    nodes: &mut Vec<DAGNode>,
-    expr: &QueryExpr,
-    cache: &mut HashCache,
-    label: String,
-    detail: serde_json::Value,
-    children: Vec<u32>,
-) -> u32 {
-    let id = nodes.len() as u32;
-    let hash = Some(structural_hash(expr, cache));
-    nodes.push(DAGNode {
-        id,
-        kind: kind_tag(expr),
-        label,
-        detail,
-        schema: expr
-            .output_schema()
-            .ok()
-            .and_then(|schema| serde_json::to_value(schema).ok()),
-        children,
-        workload_node_id: None,
-        hash,
-        source_expr: Some(expr.clone()),
-        source_ptr: Some(expr as *const QueryExpr as usize),
-        notes: Vec::new(),
-        decision: None,
-    });
-    id
-}
+        // The original node now resolves to the substitution: another
+        // parent of the same `Rc` reuses the spliced-in sub-DAG.
+        self.ids.insert(ptr, root);
+        root
+    }
 
-/// Push one flattened node with no corresponding pre-ASAP `QueryExpr` at
-/// all — a post-ASAP-originated node inside [`export_post_asap`]'s merged
-/// DAG (a `SummaryAgg`/`SummaryJoin`/… node, via [`build_summary_hybrid`]).
-/// `hash`/`source_expr`-based re-identification (see [`DAGNode::hash`]'s own
-/// doc) has no meaning for a node with no `QueryExpr` behind it, so this
-/// pushes a fixed placeholder hash (`0`) and `source_expr: None` rather than
-/// inventing a hash over `SummaryExpr` (which, unlike `QueryExpr`, has no
-/// [`structural_hash`]-equivalent function at all — see [`SummaryDAGNode`]'s
-/// own doc on why `SummaryExpr`'s fields don't even derive `Hash`/`PartialEq`
-/// consistently enough to build one).
-fn push_summary_originated_node(
-    nodes: &mut Vec<DAGNode>,
-    kind: &'static str,
-    label: String,
-    detail: serde_json::Value,
-    children: Vec<u32>,
-) -> u32 {
-    let id = nodes.len() as u32;
-    nodes.push(DAGNode {
-        id,
-        kind,
-        label,
-        detail,
-        schema: None,
-        children,
-        workload_node_id: None,
-        hash: None,
-        source_expr: None,
-        source_ptr: None,
-        notes: Vec::new(),
-        decision: None,
-    });
-    id
+    /// Export `node` itself (no substitution check at this level; children
+    /// still go through [`Self::build`]) and return its id.
+    fn build_node(&mut self, node: &Rc<OperatorNode>) -> u32 {
+        let ptr = Rc::as_ptr(node);
+        if let Some(&id) = self.ids.get(&ptr) {
+            return id;
+        }
+        let children: Vec<u32> = node.children().into_iter().map(|c| self.build(c)).collect();
+        let (label, mut detail) = shape(node, &self.ids);
+        if let serde_json::Value::Object(map) = &mut detail {
+            if let Some(timing) = node.timing {
+                map.insert("timing".into(), serde_json::json!(timing.as_str()));
+            }
+            if let Some(guarantee) = &node.guarantee {
+                if let Ok(value) = serde_json::to_value(guarantee) {
+                    map.insert("guarantee".into(), value);
+                }
+            }
+        }
+        let hash = structural_hash(node, &mut self.cache);
+        self.cache.insert(ptr, hash);
+        let id = self.nodes.len() as u32;
+        self.nodes.push(DAGNode {
+            id,
+            kind: node.operator.kind_name(),
+            label,
+            detail,
+            schema: serde_json::to_value(&node.schema).ok(),
+            children,
+            workload_node_id: None,
+            hash: Some(hash),
+            source_node: Some(Rc::clone(node)),
+            source_ptr: Some(ptr as usize),
+            notes: Vec::new(),
+            decision: None,
+        });
+        self.ids.insert(ptr, id);
+        id
+    }
 }
 
-/// The [`build_summary`]/[`build_summary_hybrid`] counterpart of [`build`]
-/// for a bound [`SummaryNode`] reached while building
-/// [`export_post_asap`]'s merged DAG: appends into the *same* `nodes:
-/// Vec<DAGNode>` list `build` itself is filling, instead of a separate
-/// [`SummaryDAG`]. A `KeepPreAsap(inner)` leaf recurses back into
-/// [`build`] on `inner` (the general pre-ASAP entry, `find_winner` included)
-/// rather than nesting a `{"pre_asap_sub_dag": ...}` blob the way
-/// [`build_summary`] does — so the merged DAG reads as one seamless DAG
-/// with no dead ends, and so a target reachable underneath a `KeepPreAsap`
-/// wrapper (a nested aggregate a strategy independently found a
-/// replacement for, say) still gets spliced in correctly.
-fn build_summary_hybrid(
-    node: &SummaryNode,
-    nodes: &mut Vec<DAGNode>,
-    cache: &mut HashCache,
-    find_winner: &mut dyn FnMut(&QueryExpr) -> Option<PostAsapSubstitution>,
-) -> u32 {
-    if let SummaryExpr::KeepPreAsap(inner) = &node.expr {
-        return build(inner, nodes, cache, find_winner);
-    }
-    let children: Vec<u32> = summary_children(&node.expr)
-        .into_iter()
-        .map(|child| build_summary_hybrid(child, nodes, cache, find_winner))
-        .collect();
-    let (kind, label, mut detail) = summary_shape(&node.expr);
-    // The merged DAG's `DAGNode` has no dedicated guarantee field (it is
-    // the pre-ASAP node shape); the guarantee rides in `detail` under the
-    // same key/shape `SummaryDAGNode::guarantee` uses, additively.
-    if let Some(guarantee) = &node.guarantee {
-        if let (serde_json::Value::Object(map), Ok(value)) =
-            (&mut detail, serde_json::to_value(guarantee))
-        {
-            map.insert("guarantee".into(), value);
-        }
+/// [`Operator::kind_name`] in snake_case, for [`SummaryDAGNode::kind`].
+/// Exhaustive so a new operator variant fails to compile here until it is
+/// named.
+fn snake_case_kind(operator: &Operator) -> &'static str {
+    match operator {
+        Operator::NonASAP(op) => match op {
+            NonASAPOp::Scan { .. } => "scan",
+            NonASAPOp::Values { .. } => "values",
+            NonASAPOp::Filter { .. } => "filter",
+            NonASAPOp::Project { .. } => "project",
+            NonASAPOp::Aggregate { .. } => "aggregate",
+            NonASAPOp::Join { .. } => "join",
+            NonASAPOp::SetOp { .. } => "set_op",
+            NonASAPOp::Concat { .. } => "concat",
+            NonASAPOp::Dedup { .. } => "dedup",
+            NonASAPOp::Sort { .. } => "sort",
+            NonASAPOp::Limit { .. } => "limit",
+            NonASAPOp::BinaryOp { .. } => "binary_op",
+            NonASAPOp::SQLWindowFunc { .. } => "sql_window_func",
+            NonASAPOp::TimeRange { .. } => "time_range",
+            NonASAPOp::TimeShift { .. } => "time_shift",
+            NonASAPOp::PromqlVectorFromScalar(_) => "promql_vector_from_scalar",
+            NonASAPOp::PromqlRelabel { .. } => "promql_relabel",
+            NonASAPOp::PromqlInfoEnrich { .. } => "promql_info_enrich",
+            NonASAPOp::PromqlSeriesSample { .. } => "promql_series_sample",
+            NonASAPOp::PromqlSubquery { .. } => "promql_subquery",
+        },
+        Operator::ASAP(op) => match op {
+            ASAPOp::SummaryAgg { .. } => "summary_agg",
+            ASAPOp::SummaryEstimate { .. } => "summary_estimate",
+            ASAPOp::FinalizeExactAccumulator { .. } => "finalize_exact_accumulator",
+            ASAPOp::MaintainPopulation { .. } => "maintain_population",
+            ASAPOp::EvaluatePopulation { .. } => "read_population",
+            ASAPOp::SummaryMerge { .. } => "summary_merge",
+            ASAPOp::SummarySubtract { .. } => "summary_subtract",
+            ASAPOp::SummaryDelete { .. } => "summary_delete",
+            ASAPOp::SummaryJoin { .. } => "summary_join",
+            ASAPOp::Extension { .. } => "extension",
+        },
     }
-    let id = push_summary_originated_node(nodes, kind, label, detail, children);
-    nodes[id as usize].schema = Some(summary_schema_json(&node.schema));
-    id
 }
 
-fn summary_schema_json(schema: &crate::post_asap::Schema) -> serde_json::Value {
-    serde_json::json!({
-        "fields": schema.fields.iter().map(|field| serde_json::json!({
-            "name": field.name,
-            "dtype": format!("{:?}", field.dtype),
-            "nullable": field.nullable,
-        })).collect::<Vec<_>>(),
-        "time_index": schema.time_index,
-    })
+/// A short, human-readable label for a [`FieldDataType`] (e.g.
+/// `"Sketch(Kll)"`, `"ExactAggregate(Sum)"`) — for the label text on a
+/// `SummaryAgg`/`SummaryJoin` node. Every variant is covered, via `Debug`
+/// for the inner kind rather than hand-written prose per algorithm.
+fn family_label(family: &FieldDataType) -> String {
+    match family {
+        FieldDataType::Plain(dtype) => format!("Plain({dtype:?})"),
+        FieldDataType::ExactAggregate(kind, _) => format!("ExactAggregate({kind:?})"),
+        FieldDataType::Sketch(kind, _grouping) => format!("Sketch({:?})", kind.algorithm()),
+        FieldDataType::Sample(kind, _) => format!("Sample({kind:?})"),
+        FieldDataType::Wavelet(kind, _) => format!("Wavelet({kind:?})"),
+        FieldDataType::StatModel(kind, _) => format!("StatModel({kind:?})"),
+    }
 }
 
 fn source_label(source: &Source) -> String {
@@ -998,407 +724,336 @@ fn source_label(source: &Source) -> String {
     }
 }
 
-/// Recursively flatten `expr`, appending nodes to `nodes` in post-order
-/// (children pushed before their parent), and return the id of the pushed
-/// root node. Exhaustive over every **operator** `QueryExpr` variant — a new
-/// one fails to compile here until this match is extended, matching the rest
-/// of the IR's exhaustive-match style (e.g. `output_schema`). The scalar
-/// variants (issue #205) are never passed to `build` directly: every operator
-/// arm that carries one (`Filter.pred`, `Project.cols`, `Aggregate.having`, …)
-/// serializes it as opaque `detail` JSON via `Predicate`/`ProjectItem`/
-/// `AggIntent`'s own `Serialize` impl, same as before the merge — a scalar
-/// sub-DAG was never a separate DAG node, so this doesn't change that.
-///
-/// `find_winner` is [`export_post_asap`]'s substitution seam, threaded
-/// through every recursive call (including [`export`]'s own, which always
-/// passes a closure that returns `None`) so both entry points share this
-/// exact traversal instead of maintaining two copies of it. `build` itself
-/// only ever calls `find_winner` once, right here at the top, before
-/// dispatching into the ordinary per-variant match below — see
-/// [`export_post_asap`]'s own doc for why a substitution's own immediate
-/// result is rendered via that match directly (recursing into its children
-/// through `build` again, so *they* still get a fresh `find_winner` call)
-/// rather than by looping back through this check a second time.
-fn build(
-    expr: &QueryExpr,
-    nodes: &mut Vec<DAGNode>,
-    cache: &mut HashCache,
-    find_winner: &mut dyn FnMut(&QueryExpr) -> Option<PostAsapSubstitution>,
-) -> u32 {
-    match find_winner(expr) {
-        Some(PostAsapSubstitution::Rewrite {
-            replacement,
-            decision,
-        }) => {
-            let first = nodes.len();
-            let root = build_no_recheck(&replacement, nodes, cache, find_winner);
-            for node in &mut nodes[first..] {
-                if node.decision.is_none() {
-                    let mut node_decision = decision.clone();
-                    node_decision.role = if node.id == root {
-                        "replacement_root"
-                    } else {
-                        "replacement_region"
-                    };
-                    node.decision = Some(node_decision);
-                }
+/// `(label, detail)` for one node: its own fields, never its children.
+/// Exhaustive over every operator variant — a new one fails to compile
+/// here until this match is extended, matching the rest of the IR's
+/// exhaustive-match style. Scalar expressions are rendered through
+/// [`scalar_json`] with `ids` resolving their operator references.
+fn shape(
+    node: &OperatorNode,
+    ids: &HashMap<*const OperatorNode, u32>,
+) -> (String, serde_json::Value) {
+    let scalar = |expr: &ScalarExpr| scalar_json(expr, ids);
+    let scalars =
+        |exprs: &[ScalarExpr]| -> Vec<serde_json::Value> { exprs.iter().map(scalar).collect() };
+    let predicate = |pred: &crate::ir::Predicate| scalar(&pred.0);
+    let sort_keys = |keys: &[crate::ir::SortKey]| -> Vec<serde_json::Value> {
+        keys.iter()
+            .map(|key| {
+                serde_json::json!({
+                    "expr": scalar(&key.expr),
+                    "ascending": key.ascending,
+                    "nulls_first": key.nulls_first,
+                })
+            })
+            .collect()
+    };
+    match &node.operator {
+        Operator::NonASAP(op) => match op {
+            NonASAPOp::Scan {
+                source,
+                predicates,
+                schema,
+            } => (
+                format!("Scan({})", source_label(source)),
+                serde_json::json!({
+                    "source": source,
+                    "predicates": predicates.iter().map(predicate).collect::<Vec<_>>(),
+                    "schema": schema,
+                }),
+            ),
+            NonASAPOp::Values { rows, schema } => (
+                format!("Values({} rows)", rows.len()),
+                serde_json::json!({
+                    "rows": rows.iter().map(|row| scalars(row)).collect::<Vec<_>>(),
+                    "schema": schema,
+                }),
+            ),
+            NonASAPOp::Filter { pred, .. } => (
+                "Filter".into(),
+                serde_json::json!({ "pred": predicate(pred) }),
+            ),
+            NonASAPOp::Project {
+                cols, qualifier, ..
+            } => (
+                format!("Project({} cols)", cols.len()),
+                serde_json::json!({
+                    "cols": cols.iter().map(|item| serde_json::json!({
+                        "alias": item.alias,
+                        "expr": scalar(&item.expr),
+                    })).collect::<Vec<_>>(),
+                    "qualifier": qualifier,
+                }),
+            ),
+            NonASAPOp::Aggregate {
+                reduction,
+                measures,
+                output_names,
+                having,
+                ..
+            } => (
+                format!("Aggregate({} measures)", measures.len()),
+                serde_json::json!({
+                    "reduction": reduction,
+                    "measures": measures,
+                    "output_names": output_names,
+                    "having": having.as_ref().map(predicate),
+                }),
+            ),
+            NonASAPOp::Join { kind, pred, .. } => (
+                format!("Join({kind:?})"),
+                serde_json::json!({ "kind": kind, "pred": predicate(pred) }),
+            ),
+            NonASAPOp::SetOp { kind, all, .. } => (
+                format!("SetOp({kind:?})"),
+                serde_json::json!({ "kind": kind, "all": all }),
+            ),
+            NonASAPOp::Concat {
+                children,
+                discriminator_unique_key,
+            } => (
+                format!("Concat({} branches)", children.len()),
+                serde_json::json!({ "discriminator_unique_key": discriminator_unique_key }),
+            ),
+            NonASAPOp::Dedup { cols, .. } => (
+                format!("Dedup({} cols)", cols.len()),
+                serde_json::json!({ "cols": cols }),
+            ),
+            NonASAPOp::Sort {
+                keys, partition_by, ..
+            } => (
+                format!("Sort({} keys)", keys.len()),
+                serde_json::json!({ "keys": sort_keys(keys), "partition_by": partition_by }),
+            ),
+            NonASAPOp::Limit {
+                n,
+                offset,
+                partition_by,
+                ..
+            } => (
+                match n {
+                    Some(n) => format!("Limit({n})"),
+                    None => format!("Limit(offset {offset})"),
+                },
+                serde_json::json!({ "n": n, "offset": offset, "partition_by": partition_by }),
+            ),
+            NonASAPOp::BinaryOp {
+                operator,
+                return_bool,
+                ..
+            } => (
+                format!("BinaryOp({})", operator.kind),
+                serde_json::json!({
+                    "op": operator.kind.to_string(),
+                    "vector_match": operator.vector_match,
+                    "checked_relative_division": operator.checked_relative_division,
+                    "checked_finite_division": operator.checked_finite_division,
+                    "return_bool": return_bool,
+                }),
+            ),
+            NonASAPOp::SQLWindowFunc {
+                func,
+                args,
+                partition_by,
+                order_by,
+                frame,
+                output_name,
+                ..
+            } => (
+                format!("SQLWindowFunc({func:?})"),
+                serde_json::json!({
+                    "func": func,
+                    "args": scalars(args),
+                    "partition_by": partition_by,
+                    "order_by": sort_keys(order_by),
+                    "frame": frame,
+                    "output_name": output_name,
+                }),
+            ),
+            NonASAPOp::TimeRange { range, kind, .. } => (
+                format!("TimeRange({kind:?}, {range:?})"),
+                serde_json::json!({ "range": range, "kind": kind }),
+            ),
+            NonASAPOp::TimeShift { shift, .. } => {
+                ("TimeShift".into(), serde_json::json!({ "shift": shift }))
             }
-            return root;
-        }
-        Some(PostAsapSubstitution::Summary {
-            replacement,
-            decision,
-        }) => {
-            let first = nodes.len();
-            let root = build_summary_hybrid(&replacement, nodes, cache, find_winner);
-            for node in &mut nodes[first..] {
-                if node.decision.is_none() {
-                    let mut node_decision = decision.clone();
-                    node_decision.role = if node.id == root {
-                        "replacement_root"
-                    } else {
-                        "replacement_region"
-                    };
-                    node.decision = Some(node_decision);
-                }
+            NonASAPOp::PromqlVectorFromScalar(value) => (
+                "vector()".into(),
+                serde_json::json!({ "value": scalar(value) }),
+            ),
+            NonASAPOp::PromqlRelabel { dst, value, .. } => (
+                format!("PromqlRelabel(dst={dst})"),
+                serde_json::json!({ "dst": dst, "value": scalar(value) }),
+            ),
+            NonASAPOp::PromqlInfoEnrich { selector, .. } => (
+                "PromqlInfoEnrich".into(),
+                serde_json::json!({ "selector": selector }),
+            ),
+            NonASAPOp::PromqlSeriesSample { by, kind, .. } => (
+                format!("PromqlSeriesSample({kind:?})"),
+                serde_json::json!({ "by": by, "kind": kind }),
+            ),
+            NonASAPOp::PromqlSubquery {
+                range, resolution, ..
+            } => (
+                "PromqlSubquery".into(),
+                serde_json::json!({ "range": range, "resolution": resolution }),
+            ),
+        },
+        Operator::ASAP(op) => match op {
+            ASAPOp::SummaryAgg {
+                family,
+                input,
+                reduction,
+                grouping,
+                ..
+            } => (
+                format!("SummaryAgg({})", family_label(family)),
+                serde_json::json!({
+                    "family": format!("{family:?}"),
+                    "input": input,
+                    "reduction": reduction,
+                    "grouping": format!("{grouping:?}"),
+                }),
+            ),
+            ASAPOp::SummaryEstimate { query, .. } => (
+                format!("SummaryEstimate({query:?})"),
+                serde_json::json!({ "query": format!("{query:?}") }),
+            ),
+            ASAPOp::FinalizeExactAccumulator { .. } => {
+                ("FinalizeExactAccumulator".into(), serde_json::json!({}))
             }
-            return root;
-        }
-        None => {}
+            ASAPOp::MaintainPopulation { population, .. } => (
+                format!("MaintainPopulation(max_k={})", population.max_k),
+                serde_json::json!({ "population": population }),
+            ),
+            ASAPOp::EvaluatePopulation { evaluation, .. } => (
+                format!("EvaluatePopulation({evaluation:?})"),
+                serde_json::json!({ "evaluation": evaluation }),
+            ),
+            ASAPOp::SummaryMerge { children } => (
+                format!("SummaryMerge({} children)", children.len()),
+                serde_json::json!({}),
+            ),
+            ASAPOp::SummarySubtract { .. } => ("SummarySubtract".into(), serde_json::json!({})),
+            ASAPOp::SummaryDelete { key, .. } => {
+                ("SummaryDelete".into(), serde_json::json!({ "key": key }))
+            }
+            ASAPOp::SummaryJoin { key, family, .. } => (
+                format!("SummaryJoin({})", family_label(family)),
+                serde_json::json!({ "key": key, "family": format!("{family:?}") }),
+            ),
+            ASAPOp::Extension { name, .. } => (
+                format!("Extension({name})"),
+                serde_json::json!({ "name": name }),
+            ),
+        },
     }
-    build_no_recheck(expr, nodes, cache, find_winner)
 }
 
-/// The actual per-variant match [`build`] dispatches to once it has decided
-/// (by consulting `find_winner` exactly once) which `QueryExpr` value to
-/// render at this position — either `expr` itself (unchanged), or a winning
-/// `Replacement::Rewrite`'s own target. Every recursive call here goes back
-/// through [`build`] (not this function), so every child gets its own fresh
-/// `find_winner` query.
-fn build_no_recheck(
-    expr: &QueryExpr,
-    nodes: &mut Vec<DAGNode>,
-    cache: &mut HashCache,
-    find_winner: &mut dyn FnMut(&QueryExpr) -> Option<PostAsapSubstitution>,
-) -> u32 {
+/// `{"scalar_ref": <id>}` for an operator node a scalar expression reads.
+/// The node is one of the owning operator's children, so it has already
+/// been exported by the time its parent's `detail` is built.
+fn scalar_ref(
+    node: &Rc<OperatorNode>,
+    ids: &HashMap<*const OperatorNode, u32>,
+) -> serde_json::Value {
+    serde_json::json!({ "scalar_ref": ids.get(&Rc::as_ptr(node)).copied() })
+}
+
+/// `expr` as JSON in `ScalarExpr`'s own serde shape (externally tagged
+/// variants), except that every operator reference is rendered via
+/// [`scalar_ref`] instead of inlining the referenced sub-DAG. Exhaustive so
+/// a new variant fails to compile here until it is rendered.
+fn scalar_json(expr: &ScalarExpr, ids: &HashMap<*const OperatorNode, u32>) -> serde_json::Value {
+    let sub = |e: &ScalarExpr| scalar_json(e, ids);
+    let list = |es: &[ScalarExpr]| -> Vec<serde_json::Value> { es.iter().map(sub).collect() };
     match expr {
-        QueryExpr::Scan {
-            source,
-            predicates,
-            schema,
-        } => {
-            let label = format!("Scan({})", source_label(source));
-            let detail = serde_json::json!({
-                "source": source,
-                "predicates": predicates,
-                "schema": schema,
-            });
-            push_node(nodes, expr, cache, label, detail, vec![])
-        }
-        // The bridged child is a scalar-sub-language node (issue #220), not
-        // an operator node `build` can recurse into — serialize it as opaque
-        // `detail` JSON, same as every other scalar-typed field
-        // (`Filter.pred`, `Project.cols`, …) rather than pushing it as a
-        // separate DAG node.
-        QueryExpr::PromqlScalarBridge(inner) => {
-            let detail = serde_json::json!({ "value": inner });
-            push_node(
-                nodes,
-                expr,
-                cache,
-                format!("PromqlScalarBridge({inner:?})"),
-                detail,
-                vec![],
-            )
-        }
-        QueryExpr::EvalTimestamp => push_node(
-            nodes,
-            expr,
-            cache,
-            "EvalTimestamp".into(),
-            serde_json::json!({}),
-            vec![],
-        ),
-        QueryExpr::CurrentTimestamp => push_node(
-            nodes,
-            expr,
-            cache,
-            "CurrentTimestamp".into(),
-            serde_json::json!({}),
-            vec![],
-        ),
-        QueryExpr::PromqlVectorFromScalar(child) => {
-            let c = build(child, nodes, cache, find_winner);
-            push_node(
-                nodes,
-                expr,
-                cache,
-                "vector()".into(),
-                serde_json::json!({}),
-                vec![c],
-            )
-        }
-        QueryExpr::PromqlScalarFromVector(child) => {
-            let c = build(child, nodes, cache, find_winner);
-            push_node(
-                nodes,
-                expr,
-                cache,
-                "scalar()".into(),
-                serde_json::json!({}),
-                vec![c],
-            )
-        }
-        QueryExpr::PromqlRelabel { dst, value, child } => {
-            let c = build(child, nodes, cache, find_winner);
-            let detail = serde_json::json!({ "dst": dst, "value": value });
-            push_node(
-                nodes,
-                expr,
-                cache,
-                format!("PromqlRelabel(dst={dst})"),
-                detail,
-                vec![c],
-            )
-        }
-        QueryExpr::PromqlInfoEnrich { selector, child } => {
-            let c = build(child, nodes, cache, find_winner);
-            let detail = serde_json::json!({ "selector": selector });
-            push_node(
-                nodes,
-                expr,
-                cache,
-                "PromqlInfoEnrich".into(),
-                detail,
-                vec![c],
-            )
-        }
-        QueryExpr::PromqlSeriesSample { by, kind, child } => {
-            let c = build(child, nodes, cache, find_winner);
-            let detail = serde_json::json!({ "by": by, "kind": kind });
-            push_node(
-                nodes,
-                expr,
-                cache,
-                format!("PromqlSeriesSample({kind:?})"),
-                detail,
-                vec![c],
-            )
-        }
-        QueryExpr::Filter { pred, child } => {
-            let c = build(child, nodes, cache, find_winner);
-            let detail = serde_json::json!({ "pred": pred });
-            push_node(nodes, expr, cache, "Filter".into(), detail, vec![c])
-        }
-        QueryExpr::Project {
-            cols,
-            qualifier,
-            child,
-        } => {
-            let c = build(child, nodes, cache, find_winner);
-            let detail = serde_json::json!({ "cols": cols, "qualifier": qualifier });
-            push_node(
-                nodes,
-                expr,
-                cache,
-                format!("Project({} cols)", cols.len()),
-                detail,
-                vec![c],
-            )
-        }
-        QueryExpr::Aggregate {
-            reduction,
-            measures,
-            output_names,
-            filters,
-            having,
-            child,
-        } => {
-            let c = build(child, nodes, cache, find_winner);
-            let detail = serde_json::json!({
-                "reduction": reduction,
-                "measures": measures,
-                "output_names": output_names,
-                "filters": filters,
-                "having": having,
-            });
-            push_node(
-                nodes,
-                expr,
-                cache,
-                format!("Aggregate({} measures)", measures.len()),
-                detail,
-                vec![c],
-            )
-        }
-        QueryExpr::Dedup { cols, child } => {
-            let c = build(child, nodes, cache, find_winner);
-            let detail = serde_json::json!({ "cols": cols });
-            push_node(
-                nodes,
-                expr,
-                cache,
-                format!("Dedup({} cols)", cols.len()),
-                detail,
-                vec![c],
-            )
-        }
-        QueryExpr::Concat {
-            children,
-            discriminator_unique_key,
-        } => {
-            let ids: Vec<u32> = children
-                .iter()
-                .map(|c| build(c, nodes, cache, find_winner))
-                .collect();
-            let label = format!("Concat({} branches)", ids.len());
-            let detail =
-                serde_json::json!({ "discriminator_unique_key": discriminator_unique_key });
-            push_node(nodes, expr, cache, label, detail, ids)
-        }
-        QueryExpr::Join {
-            kind,
-            pred,
+        ScalarExpr::Column(id) => serde_json::json!({ "Column": id }),
+        ScalarExpr::Literal(value) => serde_json::json!({ "Literal": value }),
+        ScalarExpr::Negative { expr, semantics } => serde_json::json!({
+            "Negative": { "expr": sub(expr), "semantics": semantics }
+        }),
+        ScalarExpr::Compare {
             left,
+            op,
             right,
-        } => {
-            let l = build(left, nodes, cache, find_winner);
-            let r = build(right, nodes, cache, find_winner);
-            let detail = serde_json::json!({ "kind": kind, "pred": pred });
-            push_node(
-                nodes,
-                expr,
-                cache,
-                format!("Join({kind:?})"),
-                detail,
-                vec![l, r],
-            )
-        }
-        QueryExpr::SetOp {
-            kind,
-            all,
+            semantics,
+        } => serde_json::json!({
+            "Compare": {
+                "left": sub(left),
+                "op": op,
+                "right": sub(right),
+                "semantics": semantics,
+            }
+        }),
+        ScalarExpr::BoolAnd(parts) => serde_json::json!({ "BoolAnd": list(parts) }),
+        ScalarExpr::BoolOr(parts) => serde_json::json!({ "BoolOr": list(parts) }),
+        ScalarExpr::Not(e) => serde_json::json!({ "Not": sub(e) }),
+        ScalarExpr::IsNull(e) => serde_json::json!({ "IsNull": sub(e) }),
+        ScalarExpr::IsNotNull(e) => serde_json::json!({ "IsNotNull": sub(e) }),
+        ScalarExpr::Cast { expr, to, try_cast } => serde_json::json!({
+            "Cast": { "expr": sub(expr), "to": to, "try_cast": try_cast }
+        }),
+        ScalarExpr::InList {
+            expr,
+            list: items,
+            negated,
+        } => serde_json::json!({
+            "InList": { "expr": sub(expr), "list": list(items), "negated": negated }
+        }),
+        ScalarExpr::FunctionCall { name, args } => serde_json::json!({
+            "FunctionCall": { "name": name, "args": list(args) }
+        }),
+        ScalarExpr::Arithmetic {
+            op,
             left,
             right,
-        } => {
-            let l = build(left, nodes, cache, find_winner);
-            let r = build(right, nodes, cache, find_winner);
-            let detail = serde_json::json!({ "kind": kind, "all": all });
-            push_node(
-                nodes,
-                expr,
-                cache,
-                format!("SetOp({kind:?})"),
-                detail,
-                vec![l, r],
-            )
-        }
-        QueryExpr::Sort {
-            keys,
-            partition_by,
-            child,
-        } => {
-            let c = build(child, nodes, cache, find_winner);
-            let detail = serde_json::json!({ "keys": keys, "partition_by": partition_by });
-            push_node(
-                nodes,
-                expr,
-                cache,
-                format!("Sort({} keys)", keys.len()),
-                detail,
-                vec![c],
-            )
-        }
-        QueryExpr::Limit { n, offset, child } => {
-            let c = build(child, nodes, cache, find_winner);
-            let detail = serde_json::json!({ "n": n, "offset": offset });
-            push_node(nodes, expr, cache, format!("Limit({n})"), detail, vec![c])
-        }
-        QueryExpr::PromqlSubquery {
-            range,
-            resolution,
-            child,
-        } => {
-            let c = build(child, nodes, cache, find_winner);
-            let detail = serde_json::json!({ "range": range, "resolution": resolution });
-            push_node(nodes, expr, cache, "PromqlSubquery".into(), detail, vec![c])
-        }
-        QueryExpr::TimeRange { range, child } => {
-            let c = build(child, nodes, cache, find_winner);
-            let detail = serde_json::json!({ "range": range });
-            push_node(
-                nodes,
-                expr,
-                cache,
-                format!("TimeRange({range:?})"),
-                detail,
-                vec![c],
-            )
-        }
-        QueryExpr::TimeShift { shift, child } => {
-            let c = build(child, nodes, cache, find_winner);
-            let detail = serde_json::json!({ "shift": shift });
-            push_node(nodes, expr, cache, "TimeShift".into(), detail, vec![c])
-        }
-        QueryExpr::SQLWindowFunc {
-            func,
-            args,
-            partition_by,
-            order_by,
-            frame,
-            output_name,
-            child,
-        } => {
-            let c = build(child, nodes, cache, find_winner);
-            let detail = serde_json::json!({
-                "func": func,
-                "args": args,
-                "partition_by": partition_by,
-                "order_by": order_by,
-                "frame": frame,
-                "output_name": output_name,
-            });
-            push_node(
-                nodes,
-                expr,
-                cache,
-                format!("SQLWindowFunc({func:?})"),
-                detail,
-                vec![c],
-            )
-        }
-        QueryExpr::BinaryOp {
-            op,
-            lhs,
-            rhs,
-            vector_match,
-        } => {
-            let l = build(lhs, nodes, cache, find_winner);
-            let r = build(rhs, nodes, cache, find_winner);
-            let detail = serde_json::json!({ "op": op.to_string(), "vector_match": vector_match });
-            push_node(
-                nodes,
-                expr,
-                cache,
-                format!("BinaryOp({op})"),
-                detail,
-                vec![l, r],
-            )
-        }
-        other @ (QueryExpr::Column(_)
-        | QueryExpr::Literal(_)
-        | QueryExpr::Compare { .. }
-        | QueryExpr::BoolAnd(_)
-        | QueryExpr::BoolOr(_)
-        | QueryExpr::Not(_)
-        | QueryExpr::IsNull(_)
-        | QueryExpr::IsNotNull(_)
-        | QueryExpr::Cast { .. }
-        | QueryExpr::InList { .. }
-        | QueryExpr::FunctionCall { .. }
-        | QueryExpr::Arithmetic { .. }
-        | QueryExpr::Case { .. }) => {
-            unreachable!("dag_export::build reached a scalar QueryExpr variant directly: {other:?}")
-        }
+            semantics,
+        } => serde_json::json!({
+            "Arithmetic": {
+                "op": op,
+                "left": sub(left),
+                "right": sub(right),
+                "semantics": semantics,
+            }
+        }),
+        ScalarExpr::Case {
+            operand,
+            branches,
+            else_expr,
+        } => serde_json::json!({
+            "Case": {
+                "operand": operand.as_deref().map(sub),
+                "branches": branches
+                    .iter()
+                    .map(|(when, then)| serde_json::json!([sub(when), sub(then)]))
+                    .collect::<Vec<_>>(),
+                "else_expr": else_expr.as_deref().map(sub),
+            }
+        }),
+        ScalarExpr::CurrentTimestamp => serde_json::json!("CurrentTimestamp"),
+        ScalarExpr::EvalTimestamp => serde_json::json!("EvalTimestamp"),
+        ScalarExpr::PromqlScalarFromVector(node) => serde_json::json!({
+            "PromqlScalarFromVector": scalar_ref(node, ids)
+        }),
+        ScalarExpr::ScalarSubquery(node) => serde_json::json!({
+            "ScalarSubquery": scalar_ref(node, ids)
+        }),
+        ScalarExpr::Exists { subquery, negated } => serde_json::json!({
+            "Exists": { "subquery": scalar_ref(subquery, ids), "negated": negated }
+        }),
+        ScalarExpr::InSubquery {
+            expr,
+            subquery,
+            negated,
+        } => serde_json::json!({
+            "InSubquery": {
+                "expr": sub(expr),
+                "subquery": scalar_ref(subquery, ids),
+                "negated": negated,
+            }
+        }),
     }
 }
 
@@ -1407,14 +1062,20 @@ mod tests {
     use std::rc::Rc;
 
     use super::*;
+    use crate::ir::operator_properties::{GroupKeys, JoinKind, Reduction};
+    use crate::ir::Predicate;
+    use crate::post_asap::{
+        BoundExpr, CompositionOperator, ErrorMetric, GroupingStrategy, GuaranteeSource,
+        ProbabilityExpr, SketchAlgorithm, SketchKind, SketchParams, SketchStatistic, SummaryUpdate,
+    };
     use crate::pre_asap::agg_intent::AggIntent;
-    use crate::pre_asap::expr_ir::ScalarValue;
-    use crate::pre_asap::query_expr::{GroupKeys, Predicate, Reduction};
+    use crate::pre_asap::expr_ir::{ColumnRef, ScalarValue};
     use crate::pre_asap::schema::{DataType, Field, Schema};
+
     use crate::types::AccuracyTarget;
 
-    fn scan(table: &str, columns: Vec<Field>) -> QueryExpr {
-        QueryExpr::Scan {
+    fn scan(table: &str, columns: Vec<Field>) -> Rc<OperatorNode> {
+        OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Scan {
             source: Source::Table {
                 table_ref: table.into(),
             },
@@ -1425,25 +1086,95 @@ mod tests {
                 unique_keys: vec![],
                 closed: true,
             },
-        }
+        }))
+        .unwrap()
     }
 
     fn value_col() -> Vec<Field> {
         vec![Field::plain("value", DataType::Float64, false)]
     }
 
+    fn true_pred() -> Predicate {
+        Predicate(ScalarExpr::Literal(ScalarValue::Boolean(true)))
+    }
+
+    fn count_agg(child: Rc<OperatorNode>) -> Rc<OperatorNode> {
+        OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Aggregate {
+            reduction: Reduction::Reduce(GroupKeys::none()),
+            measures: vec![AggIntent::Count {
+                accuracy: AccuracyTarget::Exact,
+            }],
+            output_names: vec![],
+            filters: vec![],
+            having: None,
+            child,
+        }))
+        .unwrap()
+    }
+
+    fn join(left: Rc<OperatorNode>, right: Rc<OperatorNode>) -> Rc<OperatorNode> {
+        OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Join {
+            kind: JoinKind::Inner,
+            pred: true_pred(),
+            left,
+            right,
+        }))
+        .unwrap()
+    }
+
+    /// A KLL `SummaryAgg` over `leaf`'s `v` column, read out as a quantile.
+    fn quantile_evaluation(
+        leaf: Rc<OperatorNode>,
+        guarantee: Option<ResultGuarantee>,
+    ) -> (Rc<OperatorNode>, Rc<OperatorNode>) {
+        let family = FieldDataType::Sketch(
+            SketchKind::new(SketchAlgorithm::Kll, SketchParams::Kll { k: 40 }),
+            GroupingStrategy::default(),
+        );
+        let agg = std::rc::Rc::new(
+            OperatorNode::with_schema(
+                crate::ir::Operator::ASAP(ASAPOp::SummaryAgg {
+                    child: leaf,
+                    family: family.clone(),
+                    input: SummaryUpdate::column(ColumnRef::Named("v".into())),
+                    reduction: Reduction::by(vec![]),
+                    grouping: GroupingStrategy::default(),
+                    filter: None,
+                }),
+                Schema::lifted(vec![Field::new("state", family, false)], None),
+            )
+            .with_guarantee(None),
+        );
+        let evaluation = std::rc::Rc::new(
+            OperatorNode::with_schema(
+                crate::ir::Operator::ASAP(ASAPOp::SummaryEstimate {
+                    summary_input: Rc::clone(&agg),
+                    query: SketchStatistic::Quantile { q: 0.99 },
+                }),
+                Schema::lifted(
+                    vec![Field::plain("quantile", DataType::Float64, false)],
+                    None,
+                ),
+            )
+            .with_guarantee(guarantee),
+        );
+        (agg, evaluation)
+    }
+
     #[test]
     fn leaf_scan_is_a_single_node() {
         let dag = export(&scan("metrics", value_col()));
         assert_eq!(dag.nodes.len(), 1);
         assert_eq!(dag.root, 0);
         assert_eq!(dag.nodes[0].kind, "Scan");
+        assert_eq!(dag.nodes[0].label, "Scan(metrics)");
         assert!(dag.nodes[0].children.is_empty());
+        assert!(dag.nodes[0].source_node.is_some());
     }
 
     /// `export` itself never populates higher-layer annotations. Empty
-    /// annotations must not appear in serialized JSON, so ordinary (non-ASAP)
-    /// exports retain their existing shape.
+    /// annotations must not appear in serialized JSON, so ordinary exports
+    /// retain their existing shape.
     #[test]
     fn export_omits_empty_higher_layer_annotations() {
         let dag = export(&scan("metrics", value_col()));
@@ -1460,6 +1191,10 @@ mod tests {
             !json.contains("decision"),
             "empty `decision` must be skipped, not serialized as `null`: {json}"
         );
+        assert!(
+            !json.contains("source_node"),
+            "`source_node` is in-process only: {json}"
+        );
         let dag_json = serde_json::to_string(&dag).unwrap();
         assert!(
             !dag_json.contains("edge_annotations"),
@@ -1473,22 +1208,29 @@ mod tests {
         // single child slot) share the exact same `Rc` Scan —
         // `export_post_asap` must merge them onto one node id. Sharing alone
         // is not physical cost evidence, so no edge cost may be fabricated.
-        let shared_scan = Rc::new(scan("metrics", value_col()));
-        let left_branch = QueryExpr::Dedup {
-            cols: vec![0],
-            child: Rc::clone(&shared_scan),
-        };
-        let right_branch = QueryExpr::Limit {
-            n: 5,
-            offset: 0,
-            child: Rc::clone(&shared_scan),
-        };
-        let root = QueryExpr::Concat {
+        let shared_scan = scan("metrics", value_col());
+        let left_branch =
+            OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Dedup {
+                cols: vec![0],
+                child: Rc::clone(&shared_scan),
+            }))
+            .unwrap();
+        let right_branch =
+            OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Limit {
+                n: Some(5),
+                offset: 0,
+                partition_by: GroupKeys::none(),
+                child: Rc::clone(&shared_scan),
+            }))
+            .unwrap();
+        let root = OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Concat {
             children: vec![left_branch, right_branch],
             discriminator_unique_key: None,
-        };
+        }))
+        .unwrap();
         let dag = export_post_asap(&root, &mut |_| None);
 
+        assert_eq!(dag.nodes.len(), 4, "Scan, Dedup, Limit, Concat");
         assert_eq!(
             dag.nodes.iter().filter(|n| n.kind == "Scan").count(),
             1,
@@ -1497,20 +1239,15 @@ mod tests {
         assert!(dag.edge_annotations.is_empty());
     }
 
-    /// Regression test: a single parent referencing the same shared child
-    /// from two of its own operand slots at once (a `Join` whose left and
-    /// right sides are the exact same `Rc`, post pointer-dedup) is *one*
-    /// downstream consumer, not two — this must not inflate
-    /// produce an edge-cost annotation without explicit physical evidence.
+    /// A single parent referencing the same shared child from two of its
+    /// own operand slots at once (a `Join` whose left and right sides are
+    /// the exact same `Rc`) is *one* downstream consumer, not two — this
+    /// must not produce an edge-cost annotation without explicit physical
+    /// evidence.
     #[test]
     fn a_single_parent_referencing_a_shared_child_twice_is_one_consumer_not_two() {
-        let shared_scan = Rc::new(scan("metrics", value_col()));
-        let root = QueryExpr::Join {
-            kind: crate::pre_asap::query_expr::JoinKind::Inner,
-            pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Boolean(true)))),
-            left: Rc::clone(&shared_scan),
-            right: Rc::clone(&shared_scan),
-        };
+        let shared_scan = scan("metrics", value_col());
+        let root = join(Rc::clone(&shared_scan), Rc::clone(&shared_scan));
         let dag = export_post_asap(&root, &mut |_| None);
 
         assert_eq!(
@@ -1518,6 +1255,7 @@ mod tests {
             1,
             "the shared Scan must be merged onto one node, not duplicated"
         );
+        assert_eq!(dag.nodes[dag.root as usize].children, vec![0, 0]);
         assert!(
             dag.edge_annotations.is_empty(),
             "a single parent referencing the same child twice is one consumer, not a genuine \
@@ -1527,38 +1265,33 @@ mod tests {
     }
 
     #[test]
-    fn export_never_produces_edge_annotations_since_it_never_shares_nodes() {
-        // Plain `export` (no `export_post_asap`) never deduplicates by `Rc`
-        // pointer identity — even a workload-level shared sub-DAG renders as
-        // two independent DAG nodes here, so there is nothing to annotate.
-        let shared_scan = Rc::new(scan("metrics", value_col()));
-        let root = QueryExpr::Join {
-            kind: crate::pre_asap::query_expr::JoinKind::Inner,
-            pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Boolean(true)))),
-            left: Rc::clone(&shared_scan),
-            right: Rc::clone(&shared_scan),
-        };
-        let dag = export(&root);
-        assert_eq!(dag.nodes.iter().filter(|n| n.kind == "Scan").count(), 2);
+    fn export_merges_pointer_shared_nodes_but_not_equal_copies() {
+        // Plain `export` deduplicates by `Rc` pointer identity: the same
+        // `Rc` reached twice is one node ...
+        let shared_scan = scan("metrics", value_col());
+        let dag = export(&join(Rc::clone(&shared_scan), Rc::clone(&shared_scan)));
+        assert_eq!(dag.nodes.iter().filter(|n| n.kind == "Scan").count(), 1);
         assert!(dag.edge_annotations.is_empty());
+
+        // ... while two structurally equal but distinct `Rc`s stay two
+        // nodes (with equal hashes — that is CSE's job, not the export's).
+        let dag = export(&join(
+            scan("metrics", value_col()),
+            scan("metrics", value_col()),
+        ));
+        let scans: Vec<_> = dag.nodes.iter().filter(|n| n.kind == "Scan").collect();
+        assert_eq!(scans.len(), 2);
+        assert_eq!(scans[0].hash, scans[1].hash);
     }
 
     #[test]
     fn chain_preserves_shape_and_child_links() {
-        let expr = QueryExpr::Filter {
-            pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Boolean(true)))),
-            child: Rc::new(QueryExpr::Aggregate {
-                reduction: Reduction::Reduce(GroupKeys::none()),
-                measures: vec![AggIntent::Count {
-                    accuracy: AccuracyTarget::Exact,
-                }],
-                output_names: vec![],
-                filters: vec![],
-                having: None,
-                child: Rc::new(scan("metrics", value_col())),
-            }),
-        };
-        let dag = export(&expr);
+        let root = OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Filter {
+            pred: true_pred(),
+            child: count_agg(scan("metrics", value_col())),
+        }))
+        .unwrap();
+        let dag = export(&root);
         assert_eq!(dag.nodes.len(), 3, "Filter -> Aggregate -> Scan");
 
         let filter = &dag.nodes[dag.root as usize];
@@ -1567,6 +1300,7 @@ mod tests {
 
         let agg = &dag.nodes[filter.children[0] as usize];
         assert_eq!(agg.kind, "Aggregate");
+        assert_eq!(agg.label, "Aggregate(1 measures)");
         assert_eq!(agg.children.len(), 1);
 
         let leaf = &dag.nodes[agg.children[0] as usize];
@@ -1576,18 +1310,76 @@ mod tests {
 
     #[test]
     fn merge_keeps_every_branch_as_a_child() {
-        let expr = QueryExpr::concat(vec![
-            scan("a", value_col()),
-            scan("b", value_col()),
-            scan("c", value_col()),
-        ]);
-        let dag = export(&expr);
+        let root = OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Concat {
+            children: vec![
+                scan("a", value_col()),
+                scan("b", value_col()),
+                scan("c", value_col()),
+            ],
+            discriminator_unique_key: None,
+        }))
+        .unwrap();
+        let dag = export(&root);
         assert_eq!(dag.nodes.len(), 4, "3 branches + the Concat node");
         let merge = &dag.nodes[dag.root as usize];
         assert_eq!(merge.kind, "Concat");
         assert_eq!(merge.children.len(), 3);
     }
 
+    /// An operator node read from a scalar expression is a child of the
+    /// owning operator (after its operator inputs), and the expression's
+    /// `detail` points at it by id instead of inlining it.
+    #[test]
+    fn scalar_operator_references_are_children_rendered_as_scalar_refs() {
+        let subquery = scan("other", value_col());
+        let root = OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Filter {
+            pred: Predicate(ScalarExpr::Exists {
+                subquery: Rc::clone(&subquery),
+                negated: false,
+            }),
+            child: scan("metrics", value_col()),
+        }))
+        .unwrap();
+        let dag = export(&root);
+        assert_eq!(dag.nodes.len(), 3);
+        let filter = &dag.nodes[dag.root as usize];
+        assert_eq!(
+            filter.children.len(),
+            2,
+            "operator input, then the scalar reference"
+        );
+        let input = &dag.nodes[filter.children[0] as usize];
+        let referenced = &dag.nodes[filter.children[1] as usize];
+        assert_eq!(input.label, "Scan(metrics)");
+        assert_eq!(referenced.label, "Scan(other)");
+        assert_eq!(
+            filter.detail["pred"]["Exists"]["subquery"]["scalar_ref"],
+            serde_json::json!(referenced.id)
+        );
+        assert_eq!(filter.detail["pred"]["Exists"]["negated"], false);
+        let json = serde_json::to_string(&filter.detail).unwrap();
+        assert!(
+            !json.contains("other"),
+            "the referenced sub_dag must not be inlined into detail: {json}"
+        );
+    }
+
+    #[test]
+    fn limit_without_n_is_offset_only() {
+        let root = OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Limit {
+            n: None,
+            offset: 3,
+            partition_by: GroupKeys::none(),
+            child: scan("metrics", value_col()),
+        }))
+        .unwrap();
+        let dag = export(&root);
+        let limit = &dag.nodes[dag.root as usize];
+        assert_eq!(limit.label, "Limit(offset 3)");
+        assert_eq!(limit.detail["n"], serde_json::Value::Null);
+        assert_eq!(limit.detail["offset"], 3);
+    }
+
     #[test]
     fn identical_sub_dags_hash_equal_and_differing_ones_dont() {
         let left = scan("metrics", value_col());
@@ -1615,17 +1407,18 @@ mod tests {
         // Two roots that each wrap the *same* Scan shape in a different outer
         // node — the exported hash should still flag the shared Scan even
         // though it's embedded at different depths / under different parents.
-        let shared_shape = || scan("metrics", value_col());
-
-        let q1 = QueryExpr::Limit {
-            n: 10,
+        let q1 = OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Limit {
+            n: Some(10),
             offset: 0,
-            child: Rc::new(shared_shape()),
-        };
-        let q2 = QueryExpr::Dedup {
+            partition_by: GroupKeys::none(),
+            child: scan("metrics", value_col()),
+        }))
+        .unwrap();
+        let q2 = OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Dedup {
             cols: vec![0],
-            child: Rc::new(shared_shape()),
-        };
+            child: scan("metrics", value_col()),
+        }))
+        .unwrap();
 
         let g1 = export(&q1);
         let g2 = export(&q2);
@@ -1647,9 +1440,9 @@ mod tests {
     fn root_hash_matches_cse_structural_hash_for_the_same_node() {
         // Not just "hashes equal for equal inputs" (any two consistent hash
         // functions would do that) — the exported root's `hash` must be the
-        // literal `u64` `crate::pre_asap::cse::structural_hash` produces for
-        // this exact node, because it's the same function call, not a
-        // parallel reimplementation that happens to agree.
+        // literal `u64` `crate::ir::cse::structural_hash` produces for this
+        // exact node, because it's the same function call, not a parallel
+        // reimplementation that happens to agree.
         let leaf = scan("metrics", value_col());
         let dag = export(&leaf);
         assert_eq!(
@@ -1661,24 +1454,15 @@ mod tests {
 
     #[test]
     fn every_node_hash_matches_cse_structural_hash_on_its_own_sub_dag() {
-        // A multi-level DAG: check the parity holds at every depth, not
-        // just the root — each `DAGNode::hash` must equal
-        // `structural_hash` applied to the actual `QueryExpr` sub-DAG that
-        // node represents.
-        let agg = QueryExpr::Aggregate {
-            reduction: Reduction::Reduce(GroupKeys::none()),
-            measures: vec![AggIntent::Count {
-                accuracy: AccuracyTarget::Exact,
-            }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(scan("metrics", value_col())),
-        };
-        let root = QueryExpr::Filter {
-            pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Boolean(true)))),
-            child: Rc::new(agg.clone()),
-        };
+        // A multi-level tree: check the parity holds at every depth, not
+        // just the root — each `DAGNode::hash` must equal `structural_hash`
+        // applied to the actual node it represents.
+        let agg = count_agg(scan("metrics", value_col()));
+        let root = OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::Filter {
+            pred: true_pred(),
+            child: Rc::clone(&agg),
+        }))
+        .unwrap();
 
         let dag = export(&root);
         assert_eq!(
@@ -1697,39 +1481,23 @@ mod tests {
         );
     }
 
-    /// Issue #172: a readout's guarantee is exported structurally — metric,
+    /// Issue #172: a evaluation's guarantee is exported structurally — metric,
     /// symbolic bound, failure probability, provenance (allocation
-    /// included) — and a rejection carries its typed reason.
+    /// included) — and a rejection carries its typed reason. A relational
+    /// node below a summary is its own node, in the same dag.
     #[test]
     fn export_carries_guarantee_allocation_and_rejection_reason() {
-        use crate::post_asap::{
-            BoundExpr, CompositionOperator, ErrorMetric, FieldDataType, GroupingStrategy,
-            GuaranteeSource, ProbabilityExpr, Schema, SketchAlgorithm, SketchKind, SketchParams,
-            SketchStatistic,
-        };
-        let leaf = Rc::new(scan("t", vec![Field::plain("v", DataType::Float64, false)]));
-        let kept = Rc::new(SummaryNode {
-            expr: SummaryExpr::KeepPreAsap(Rc::clone(&leaf)),
-            schema: Schema::lifted(vec![], None),
-            guarantee: Some(ResultGuarantee::exact("KeepPreAsap")),
-        });
-        let agg = Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryAgg {
-                child: kept,
-                family: FieldDataType::Sketch(
-                    SketchKind::new(SketchAlgorithm::Kll, SketchParams::Kll { k: 40 }),
-                    GroupingStrategy::default(),
-                ),
-                input: crate::post_asap::SummaryUpdate::column(
-                    crate::pre_asap::expr_ir::ColumnRef::Named("v".into()),
-                ),
-                reduction: Reduction::by(vec![]),
-                grouping: GroupingStrategy::default(),
-                filter: None,
-            },
-            schema: Schema::lifted(vec![], None),
-            guarantee: None,
-        });
+        let leaf = Rc::new(
+            OperatorNode::new(Operator::NonASAP(NonASAPOp::Scan {
+                source: Source::Table {
+                    table_ref: "t".into(),
+                },
+                predicates: vec![],
+                schema: Schema::lifted(vec![Field::plain("v", DataType::Float64, false)], None),
+            }))
+            .unwrap()
+            .with_guarantee(Some(ResultGuarantee::exact("Scan"))),
+        );
         let guarantee = ResultGuarantee {
             metric: ErrorMetric::Rank,
             bound: BoundExpr::Sum {
@@ -1755,15 +1523,15 @@ mod tests {
                 },
             ],
         };
-        let root = SummaryNode {
-            expr: SummaryExpr::SummaryEstimate {
-                summary_input: agg,
-                query: SketchStatistic::Quantile { q: 0.99 },
-            },
-            schema: Schema::lifted(vec![], None),
-            guarantee: Some(guarantee),
-        };
+        let (_, root) = quantile_evaluation(Rc::clone(&leaf), Some(guarantee));
         let dag = export_summary(&root);
+        assert_eq!(
+            dag.nodes.iter().map(|n| n.kind).collect::<Vec<_>>(),
+            ["scan", "summary_agg", "summary_estimate"]
+        );
+        assert_eq!(dag.nodes[1].label, "SummaryAgg(Sketch(Kll))");
+        assert!(dag.nodes[2].label.starts_with("SummaryEstimate(Quantile"));
+        assert!(dag.nodes.iter().all(|n| n.schema.is_some()));
         let json = serde_json::to_value(&dag).unwrap();
         let root_json = &json["nodes"][dag.root as usize];
         assert_eq!(root_json["guarantee"]["metric"], "rank");
@@ -1779,10 +1547,18 @@ mod tests {
         assert!(provenance.iter().any(|s| s["kind"] == "composition_step"));
         // Raw sketch state carries none; the exact leaf carries zero error.
         let state = &json["nodes"][1];
-        assert_eq!(state["kind"], "SummaryAgg");
         assert!(state.get("guarantee").is_none());
         assert_eq!(json["nodes"][0]["guarantee"]["bound"]["op"], "zero");
 
+        // The `DAGNode` shape carries the same guarantee inside `detail`.
+        let dag = export(&root);
+        assert_eq!(
+            dag.nodes.iter().map(|n| n.kind).collect::<Vec<_>>(),
+            ["Scan", "SummaryAgg", "SummaryEstimate"]
+        );
+        assert_eq!(dag.nodes[2].detail["guarantee"]["metric"], "rank");
+        assert!(dag.nodes[1].detail.get("guarantee").is_none());
+
         let named = NamedDAG {
             name: "q".into(),
             source: None,
@@ -1792,7 +1568,7 @@ mod tests {
             workload_cost: None,
             rejections: vec![TargetRejection {
                 target_pre_id: 0,
-                strategy: "SketchAlgorithmStrategy".into(),
+                strategy: "ASAPStrategies".into(),
                 description: "quantile over quantile".into(),
                 error: AccuracyError::UnsupportedComposition {
                     operator: CompositionOperator::ApproximateAggregate,
@@ -1819,38 +1595,166 @@ mod tests {
             .is_none());
     }
 
-    fn viewer_kind_categories() -> std::collections::BTreeMap<String, String> {
-        const START: &str = "const KIND_CATEGORY_JSON = `";
-        let source = include_str!(concat!(
-            env!("CARGO_MANIFEST_DIR"),
-            "/../../tools/dag-viewer/node-style.js"
-        ));
-        let json = source
-            .split_once(START)
-            .expect("node-style.js must declare KIND_CATEGORY_JSON")
-            .1
-            .split_once("`;")
-            .expect("KIND_CATEGORY_JSON must be a template literal")
-            .0;
-        serde_json::from_str(json).expect("KIND_CATEGORY_JSON must be valid JSON")
+    /// `export_post_asap` splices a winning summary in place of its target,
+    /// tags every node the splice introduced with the decision, and leaves
+    /// the rest of the query — including an input the summary reuses that
+    /// was already exported — untagged and shared.
+    #[test]
+    fn export_post_asap_splices_a_summary_substitution_in_place() {
+        let leaf = scan("t", vec![Field::plain("v", DataType::Float64, false)]);
+        let target = count_agg(Rc::clone(&leaf));
+        // `leaf` is exported through the Join's left side before the target
+        // (its right side) is reached and substituted.
+        let root = join(Rc::clone(&leaf), Rc::clone(&target));
+        let (_, evaluation) = quantile_evaluation(Rc::clone(&leaf), None);
+        let decision = DAGDecision {
+            id: 7,
+            strategy: "Sketch".into(),
+            rationale: "quantile via KLL".into(),
+            rank: 0,
+            cost: 1.0,
+            role: "",
+            baseline_cost: None,
+            selected_cost: None,
+            benefit: None,
+        };
+        let mut calls = Vec::new();
+        let dag = export_post_asap(&root, &mut |node| {
+            calls.push(node.operator.kind_name());
+            Rc::ptr_eq(node, &target).then(|| PostAsapSubstitution::Summary {
+                replacement: Rc::clone(&evaluation),
+                decision: decision.clone(),
+            })
+        });
+
+        let kinds: Vec<_> = dag.nodes.iter().map(|n| n.kind).collect();
+        assert_eq!(kinds, ["Scan", "SummaryAgg", "SummaryEstimate", "Join"]);
+        assert!(!kinds.contains(&"Aggregate"), "the target itself is gone");
+        let join_node = &dag.nodes[dag.root as usize];
+        assert_eq!(join_node.children, vec![0, 2]);
+        assert!(join_node.decision.is_none());
+        let estimate = &dag.nodes[2];
+        assert_eq!(estimate.kind, "SummaryEstimate");
+        assert_eq!(
+            estimate.decision.as_ref().map(|d| (d.id, d.role)),
+            Some((7, "replacement_root"))
+        );
+        let agg = &dag.nodes[estimate.children[0] as usize];
+        assert_eq!(
+            agg.decision.as_ref().map(|d| (d.id, d.role)),
+            Some((7, "replacement_region"))
+        );
+        let scan_node = &dag.nodes[agg.children[0] as usize];
+        assert_eq!(
+            scan_node.id, 0,
+            "the summary reuses the already-exported input"
+        );
+        assert!(
+            scan_node.decision.is_none(),
+            "a node exported before the splice is not tagged by it"
+        );
+        assert_eq!(
+            calls,
+            ["Join", "Scan", "Aggregate", "SummaryAgg"],
+            "the substitution's own top level (SummaryEstimate) is never re-queried; its \
+             descendants are, except the input already exported"
+        );
     }
 
+    /// A `SharedSubDAGStrategy`-shaped substitution returns the target
+    /// itself as its replacement; the walk must still terminate and render
+    /// the target once.
     #[test]
-    fn viewer_categorizes_exactly_the_exported_node_kinds() {
-        let expected: std::collections::BTreeSet<_> = QUERY_KIND_TAGS
-            .iter()
-            .chain(SUMMARY_KIND_TAGS)
-            .copied()
-            .chain(std::iter::once("KeepPreAsap"))
-            .collect();
+    fn export_post_asap_terminates_when_the_replacement_is_the_target() {
+        let target = count_agg(scan("t", value_col()));
+        let decision = DAGDecision {
+            id: 1,
+            strategy: "SharedSubDAG".into(),
+            rationale: "share".into(),
+            rank: 0,
+            cost: f64::NAN,
+            role: "",
+            baseline_cost: None,
+            selected_cost: None,
+            benefit: None,
+        };
+        let dag = export_post_asap(&target, &mut |node| {
+            Rc::ptr_eq(node, &target).then(|| PostAsapSubstitution::Rewrite {
+                replacement: Rc::clone(&target),
+                decision: decision.clone(),
+            })
+        });
+        assert_eq!(dag.nodes.len(), 2);
+        assert_eq!(dag.nodes[dag.root as usize].kind, "Aggregate");
         assert_eq!(
-            expected.len(),
-            QUERY_KIND_TAGS.len() + SUMMARY_KIND_TAGS.len() + 1,
-            "exported kind tags must be unique"
+            dag.nodes[dag.root as usize]
+                .decision
+                .as_ref()
+                .map(|d| d.role),
+            Some("replacement_root")
         );
-        let categories = viewer_kind_categories();
-        let actual: std::collections::BTreeSet<_> = categories.keys().map(String::as_str).collect();
+    }
 
-        assert_eq!(actual, expected);
+    /// The snake_case `kind` table is exactly `kind_name` re-cased, for
+    /// every variant: a `SummaryDAGNode` and a `DAGNode` for the same node
+    /// never disagree on what it is.
+    #[test]
+    fn summary_kind_is_the_operator_kind_name_in_snake_case() {
+        fn to_snake(name: &str) -> String {
+            let mut out = String::new();
+            let chars: Vec<char> = name.chars().collect();
+            for (i, &c) in chars.iter().enumerate() {
+                if c.is_ascii_uppercase() {
+                    let prev_lower = i > 0 && !chars[i - 1].is_ascii_uppercase();
+                    let next_lower = chars.get(i + 1).is_some_and(|n| n.is_ascii_lowercase());
+                    if i > 0 && (prev_lower || next_lower) {
+                        out.push('_');
+                    }
+                    out.push(c.to_ascii_lowercase());
+                } else {
+                    out.push(c);
+                }
+            }
+            out
+        }
+        let leaf = scan("t", vec![Field::plain("v", DataType::Float64, false)]);
+        let (_, evaluation) = quantile_evaluation(Rc::clone(&leaf), None);
+        let finalize = std::rc::Rc::new(
+            OperatorNode::with_schema(
+                crate::ir::Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child: evaluation }),
+                Schema::lifted(vec![], None),
+            )
+            .with_guarantee(None),
+        );
+        let root =
+            OperatorNode::new_shared(crate::ir::Operator::NonASAP(NonASAPOp::SQLWindowFunc {
+                func: crate::ir::operator_properties::WindowFuncKind::RowNumber,
+                args: vec![],
+                partition_by: GroupKeys::none(),
+                order_by: vec![],
+                frame: None,
+                output_name: "rn".into(),
+                child: finalize,
+            }))
+            .unwrap();
+        let dag = export(&root);
+        let summary = export_summary(&root);
+        assert_eq!(dag.nodes.len(), summary.nodes.len());
+        for (a, b) in dag.nodes.iter().zip(&summary.nodes) {
+            assert_eq!(a.id, b.id);
+            assert_eq!(b.kind, to_snake(a.kind), "{}", a.kind);
+            assert_eq!(a.children, b.children);
+            assert_eq!(a.label, b.label);
+        }
+        assert_eq!(
+            summary.nodes.iter().map(|n| n.kind).collect::<Vec<_>>(),
+            [
+                "scan",
+                "summary_agg",
+                "summary_estimate",
+                "finalize_exact_accumulator",
+                "sql_window_func",
+            ]
+        );
     }
 }
diff --git a/crates/types/src/ir/export.rs b/crates/types/src/ir/export.rs
index df27e1418..9fa6496de 100644
--- a/crates/types/src/ir/export.rs
+++ b/crates/types/src/ir/export.rs
@@ -14,7 +14,7 @@ pub use super::wire::NonASAPOpKind;
 use super::wire::{grouping_compatibility, input_edges, payload_of};
 pub use super::wire::{
     EdgeRole, GroupingEdgeCompatibility, LogicalASAPNodeId, LogicalASAPOperatorPayload,
-    WireScalarExpr,
+    WirePredicate, WireProjectItem, WireScalarExpr, WireSortKey,
 };
 use super::{ASAPOp, Operator, OperatorNode, OperatorResultKind, QueryRoot, SchemaDerivationError};
 use crate::post_asap::guarantee::ResultGuarantee;
diff --git a/crates/types/src/parsed_workload.rs b/crates/types/src/parsed_workload.rs
index ff955e6a7..9dcf21b83 100644
--- a/crates/types/src/parsed_workload.rs
+++ b/crates/types/src/parsed_workload.rs
@@ -1,5 +1,5 @@
 //! [`ParsedWorkload`] — a [`PlanningWorkload`] whose queries have been lowered
-//! to pre-ASAP IR.
+//! to the operator IR.
 //!
 //! This is the boundary between the frontend stage and the optimization stage
 //! (issues #429, #430). Everything downstream of lowering consumes this type
@@ -10,7 +10,7 @@
 
 use std::rc::Rc;
 
-use crate::pre_asap::query_expr::QueryExpr;
+use crate::ir::{OperatorNode, QueryRoot, ScalarExpr};
 use crate::workload::{
     DataWorkload, PlanningWorkload, QueryWorkload, QueryWorkloadEntry, WorkloadError,
 };
@@ -33,7 +33,9 @@ pub enum ParsedWorkloadError {
 #[derive(Debug, Clone)]
 pub struct ParsedWorkload {
     workload: PlanningWorkload,
-    exprs: Vec<Rc<QueryExpr>>,
+    exprs: Vec<Rc<OperatorNode>>,
+    operator_indices: Vec<usize>,
+    scalars: Vec<(usize, ScalarExpr)>,
 }
 
 impl ParsedWorkload {
@@ -41,16 +43,43 @@ impl ParsedWorkload {
     /// `i`-th entry.
     pub fn new(
         workload: PlanningWorkload,
-        exprs: Vec<Rc<QueryExpr>>,
+        exprs: Vec<Rc<OperatorNode>>,
+    ) -> Result<Self, ParsedWorkloadError> {
+        Self::from_roots(
+            workload,
+            exprs.into_iter().map(QueryRoot::Operator).collect(),
+        )
+    }
+
+    pub fn from_roots(
+        workload: PlanningWorkload,
+        roots: Vec<QueryRoot>,
     ) -> Result<Self, ParsedWorkloadError> {
         let entries = workload.query_workload.entries().count();
-        if entries != exprs.len() {
+        if entries != roots.len() {
             return Err(ParsedWorkloadError::LengthMismatch {
                 entries,
-                lowered: exprs.len(),
+                lowered: roots.len(),
             });
         }
-        Ok(Self { workload, exprs })
+        let mut exprs = Vec::new();
+        let mut operator_indices = Vec::new();
+        let mut scalars = Vec::new();
+        for (index, root) in roots.into_iter().enumerate() {
+            match root {
+                QueryRoot::Operator(node) => {
+                    operator_indices.push(index);
+                    exprs.push(node);
+                }
+                QueryRoot::Scalar(expr) => scalars.push((index, expr)),
+            }
+        }
+        Ok(Self {
+            workload,
+            exprs,
+            operator_indices,
+            scalars,
+        })
     }
 
     pub fn planning_workload(&self) -> &PlanningWorkload {
@@ -65,26 +94,37 @@ impl ParsedWorkload {
         self.workload.data_workload.as_ref()
     }
 
-    pub fn exprs(&self) -> &[Rc<QueryExpr>] {
+    pub fn exprs(&self) -> &[Rc<OperatorNode>] {
         &self.exprs
     }
 
     pub fn len(&self) -> usize {
-        self.exprs.len()
+        self.exprs.len() + self.scalars.len()
     }
 
     pub fn is_empty(&self) -> bool {
-        self.exprs.is_empty()
+        self.len() == 0
     }
 
     /// Normalized entries paired with their lowered expression.
-    pub fn entries(&self) -> impl Iterator<Item = (QueryWorkloadEntry, &Rc<QueryExpr>)> + '_ {
+    pub fn entries(&self) -> impl Iterator<Item = (QueryWorkloadEntry, &Rc<OperatorNode>)> + '_ {
         self.workload
             .query_workload
             .entries()
+            .enumerate()
+            .filter(|(index, _)| self.operator_indices.binary_search(index).is_ok())
+            .map(|(_, entry)| entry)
             .zip(self.exprs.iter())
     }
 
+    pub fn operator_indices(&self) -> &[usize] {
+        &self.operator_indices
+    }
+
+    pub fn scalar_roots(&self) -> &[(usize, ScalarExpr)] {
+        &self.scalars
+    }
+
     /// The retained workload's own validation — entry legality and data-workload
     /// consistency. The PromQL-specific checks it also runs were already a
     /// precondition of the lowering that produced `self`.
diff --git a/crates/types/src/post_asap/execution_data_state.rs b/crates/types/src/post_asap/execution_data_state.rs
index 74f1d47d2..38219fa2c 100644
--- a/crates/types/src/post_asap/execution_data_state.rs
+++ b/crates/types/src/post_asap/execution_data_state.rs
@@ -816,6 +816,8 @@ pub enum ExactOperationSchemaError {
     NonPlainInput,
     #[error("schema derivation failed: {0}")]
     Schema(#[from] QueryExprError),
+    #[error("schema derivation failed: {0}")]
+    Derivation(#[from] crate::ir::SchemaDerivationError),
 }
 
 #[cfg(test)]
diff --git a/crates/types/src/post_asap/expr.rs b/crates/types/src/post_asap/expr.rs
index bd45748aa..732a09db5 100644
--- a/crates/types/src/post_asap/expr.rs
+++ b/crates/types/src/post_asap/expr.rs
@@ -33,7 +33,7 @@ pub enum ValueOperation {
     /// Maintain the full declared population, including membership changes,
     /// so removing a TopK member can promote another.
     MaintainPopulation {
-        population: super::maintained_population::MaintainedPopulation,
+        population: super::maintained_population::MaintainedPopulation<crate::pre_asap::QueryExpr>,
     },
     /// Read an aggregate or TopK prefix from the maintained population.
     ReadPopulation {
diff --git a/crates/types/src/post_asap/guarantee.rs b/crates/types/src/post_asap/guarantee.rs
index cfc6f3f01..68cd7cea9 100644
--- a/crates/types/src/post_asap/guarantee.rs
+++ b/crates/types/src/post_asap/guarantee.rs
@@ -16,9 +16,9 @@
 //! ## What a guarantee says
 //!
 //! [`ResultGuarantee`] is attached to a finalized, caller-visible value —
-//! [`super::SummaryNode::guarantee`] on a `SummaryEstimate` readout, an
+//! [`crate::ir::OperatorNode::guarantee`] on a `SummaryEstimate` evaluation, an
 //! exact accumulator, or a kept pre-ASAP sub-DAG — never to raw summary
-//! state (a `SummaryAgg` sketch node carries `None`; its readout carries the
+//! state (a `SummaryAgg` sketch node carries `None`; its evaluation carries the
 //! guarantee). Its statement is:
 //!
 //! ```text
@@ -325,13 +325,13 @@ pub enum GuaranteeSource {
     /// Deterministic exact computation — zero error by construction.
     Exact {
         /// What made it exact (e.g. `"ExactAggregate(Sum)"`,
-        /// `"KeepPreAsap"`).
+        /// `"RetainedExact"`).
         reason: String,
     },
-    /// The target this readout's sketch was sized against.
+    /// The target this evaluation's sketch was sized against.
     AccuracyTarget { target: AccuracyTarget },
-    /// The concrete sketch a readout's local guarantee was derived from.
-    SketchReadout {
+    /// The concrete sketch a evaluation's local guarantee was derived from.
+    SketchEvaluation {
         algorithm: String,
         /// Stable estimator/analysis contract used to derive this guarantee.
         #[serde(default)]
@@ -421,8 +421,8 @@ impl ResultGuarantee {
         self.bound.is_zero() && self.failure_probability.is_zero()
     }
 
-    /// How many approximate sketch readouts contributed to this value —
-    /// `1` for a plain readout, `0` for an exact value, and the transitive
+    /// How many approximate sketch evaluations contributed to this value —
+    /// `1` for a plain evaluation, `0` for an exact value, and the transitive
     /// count through every [`GuaranteeSource::ChildGuarantee`] for a
     /// composition. An `AccuracyBudgetAllocator` uses this as the number
     /// of layers a budget must be split across.
@@ -430,7 +430,7 @@ impl ResultGuarantee {
         self.provenance
             .iter()
             .map(|source| match source {
-                GuaranteeSource::SketchReadout { .. } => 1,
+                GuaranteeSource::SketchEvaluation { .. } => 1,
                 GuaranteeSource::ChildGuarantee { guarantee, .. } => {
                     guarantee.approximate_layer_count()
                 }
diff --git a/crates/types/src/post_asap/maintained_population.rs b/crates/types/src/post_asap/maintained_population.rs
index 73ddd38ba..577544bd7 100644
--- a/crates/types/src/post_asap/maintained_population.rs
+++ b/crates/types/src/post_asap/maintained_population.rs
@@ -114,7 +114,7 @@ impl CurrentSeriesInput {
 /// Membership is part of state identity. Table rows must never acquire implicit
 /// latest-per-series selection, stale markers, or a PromQL lookback.
 #[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
-pub enum PopulationInput<N = crate::pre_asap::QueryExpr> {
+pub enum PopulationInput<N = crate::ir::OperatorNode> {
     CurrentSeries(CurrentSeriesInput),
     Rows {
         input: std::rc::Rc<N>,
@@ -124,13 +124,13 @@ pub enum PopulationInput<N = crate::pre_asap::QueryExpr> {
 }
 
 #[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
-pub struct MaintainedPopulation<N = crate::pre_asap::QueryExpr> {
+pub struct MaintainedPopulation<N = crate::ir::OperatorNode> {
     pub input: PopulationInput<N>,
     pub max_k: usize,
     pub quantiles: bool,
 }
 
-impl MaintainedPopulation {
+impl MaintainedPopulation<crate::pre_asap::QueryExpr> {
     pub fn matches_input(&self, input: &crate::pre_asap::QueryExpr) -> bool {
         match &self.input {
             PopulationInput::CurrentSeries(spec) => spec.matches_input(input),
diff --git a/crates/types/src/post_asap/mod.rs b/crates/types/src/post_asap/mod.rs
index f71aaca0f..b1a7da67a 100644
--- a/crates/types/src/post_asap/mod.rs
+++ b/crates/types/src/post_asap/mod.rs
@@ -27,6 +27,7 @@
 //! alongside `reduction` and on sketch-valued edge types
 //! — see `asap_aware_mapping::grouping`'s module docs for why.
 
+// Legacy summary IR: no longer re-exported; removed by the cleanup PR.
 pub mod cse;
 pub mod execution_data_state;
 pub mod expr;
@@ -40,21 +41,29 @@ pub mod summary_maintenance_lifecycle;
 pub mod summary_window;
 
 pub use crate::pre_asap::schema::{Field, FieldDataType, Schema};
-pub use cse::share_common_summary_sub_dags;
 pub use execution_data_state::{
-    assigned_child_data_state, exact_operation_output_schema, produced_data_state,
-    validate_execution_data_states, validate_execution_data_states_at, DataPrimitive,
-    ExactOperationSchemaError, ExecutionDataState, ExecutionDataStateAssignment,
+    lift_plain, DataPrimitive, ExactOperationSchemaError, ExecutionDataState,
     ExecutionDataStateError, ExecutionTiming,
 };
-pub use expr::{
+// Legacy summary IR names, kept for the legacy modules above only.
+#[allow(unused_imports)]
+pub(crate) use cse::share_common_summary_sub_dags;
+#[allow(unused_imports)]
+pub(crate) use execution_data_state::{
+    assigned_child_data_state, exact_operation_output_schema, produced_data_state,
+    validate_execution_data_states, validate_execution_data_states_at,
+    ExecutionDataStateAssignment,
+};
+#[allow(unused_imports)]
+pub(crate) use expr::{
     BinaryOperator, CandidateCompleteness, ExactOperation, SummaryExpr, SummaryNode, ValueOperation,
 };
 pub use guarantee::{
     AccuracyError, BoundExpr, CompositionOperator, ErrorMetric, GuaranteeSource, ProbabilityExpr,
     ResultGuarantee,
 };
-pub use post_asap_dag::{
+#[allow(unused_imports)]
+pub(crate) use post_asap_dag::{
     compile_post_asap_dag, compile_post_asap_dag_with_node_ids, EdgeRole,
     GroupingEdgeCompatibility, PostAsapDAG, PostAsapDAGCompilation, PostAsapDAGDocument,
     PostAsapDAGEdge, PostAsapDAGNode, PostAsapDAGValidationError, PostAsapNodeId,
diff --git a/crates/types/src/post_asap/query_time/error_estimation.rs b/crates/types/src/post_asap/query_time/error_estimation.rs
index 663d2da12..f2bf229da 100644
--- a/crates/types/src/post_asap/query_time/error_estimation.rs
+++ b/crates/types/src/post_asap/query_time/error_estimation.rs
@@ -41,7 +41,7 @@
 //!
 //! ## What this is *not* — no runtime sketch exists yet to wire this into
 //!
-//! This issue names two possible integration points: (1) runtime/readout-time
+//! This issue names two possible integration points: (1) runtime/evaluation-time
 //! accuracy reporting from a sketch's *actual* counters, and (2) tighter
 //! plan-time sizing. As of this module landing, **this repository has no
 //! vendored CMS/CountSketch/CU-Sketch runtime and no counter-array data
@@ -52,12 +52,12 @@
 //! planning-time sizing metadata. There is no `A[row][col]` counter matrix
 //! anywhere in the workspace for these functions to be handed at query
 //! time. So integration point (1) — reporting an *actual* query's posterior
-//! error from real counters at readout — has nothing to wire into today.
+//! error from real counters at evaluation — has nothing to wire into today.
 //!
 //! The functions here are deliberately **sketch-object-agnostic**: they take
 //! plain counter slices (`&[u64]` / `&[i64]`) and numeric parameters, not a
 //! concrete sketch type, specifically so that the moment a real CMS/
-//! Count-Sketch/CU-Sketch runtime lands in this workspace, its readout path
+//! Count-Sketch/CU-Sketch runtime lands in this workspace, its evaluation path
 //! can call these functions directly on its real counter arrays with zero
 //! changes needed here. That wiring is out of scope for this module — see
 //! issue #239.
@@ -255,8 +255,8 @@ fn posterior_rank(w: usize, rows: u32, delta: f64) -> Option<usize> {
 /// The `k`-th largest value in `values` (1-indexed: `k=1` is the max).
 /// `select_nth_unstable_by` partitions in O(w) average instead of fully
 /// sorting in O(w log w) — this only ever needs one rank, not a total
-/// order, and both call sites (this module's per-query readout math) are
-/// documented as meant to run on a future runtime's hot readout path.
+/// order, and both call sites (this module's per-query evaluation math) are
+/// documented as meant to run on a future runtime's hot evaluation path.
 fn kth_largest(values: &[u64], k: usize) -> u64 {
     let mut buf: Vec<u64> = values.to_vec();
     let idx = k - 1;
diff --git a/crates/types/src/post_asap/sketch.rs b/crates/types/src/post_asap/sketch.rs
index a5e1edcc1..65e78d24f 100644
--- a/crates/types/src/post_asap/sketch.rs
+++ b/crates/types/src/post_asap/sketch.rs
@@ -6,7 +6,7 @@ use crate::pre_asap::ColumnRef;
 
 /// An exact, mergeable accumulator family — zero approximation error. The
 /// partial state built for one of these *is* the answer; no
-/// `SummaryEstimate` readout is needed to get a value out of it.
+/// `SummaryEstimate` evaluation is needed to get a value out of it.
 #[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord, Serialize, Deserialize)]
 pub enum ExactKind {
     /// Exact sum accumulator (mergeable by addition).
@@ -48,7 +48,7 @@ pub enum ExactParams {
 /// [`SketchKind::new`] is where that classification is made.
 #[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord, Serialize, Deserialize)]
 pub enum SketchAlgorithm {
-    /// Universal frequency-vector summary with shared statistic readouts.
+    /// Universal frequency-vector summary with shared statistic evaluations.
     UnivMon,
     /// KLL quantile sketch (mergeable, ε-accurate rank queries).
     Kll,
@@ -345,7 +345,7 @@ pub enum StatModelParams {
 /// really the universal-sketch composition (L layers of Count-Sketch plus a
 /// heavy-hitter heap, Theorems 1+2 combined) estimating entropy/L1-norm/
 /// L2-norm/cardinality/frequency-moments as one instance. Standalone UnivMon
-/// and its frequency readouts are represented here, but sharing a Hydra
+/// and its frequency evaluations are represented here, but sharing a Hydra
 /// grid across populations still needs its own collision/error contract;
 /// standalone support does not establish that contract.
 #[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord, Serialize, Deserialize)]
@@ -500,7 +500,7 @@ pub fn default_hydra_params(
 /// enums themselves, for exactly the reason explained in this section's
 /// module docs above.
 ///
-/// Carried both on `SummaryExpr::SummaryAgg` (where planning consults it)
+/// Carried both on `ASAPOp::SummaryAgg` (where planning consults it)
 /// and on sketch-valued `FieldDataType` edges (where it prevents
 /// incompatible shared and independent physical states from type-checking
 /// as merge-compatible).
@@ -590,7 +590,8 @@ pub enum SummaryInputExpr {
     EntityIdentity(EntityIdentity),
 }
 
-/// What to extract from a built summary. Carried by `SummaryEstimate`.
+/// The statistic computed from summary state by `SummaryEstimate`, for example
+/// `Quantile { q: 0.99 }`. This is a result operation, not a workload query.
 #[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
 pub enum SketchStatistic {
     /// sqrt(sum_v frequency(v)^2), not the norm of numeric input values.
@@ -605,8 +606,8 @@ pub enum SketchStatistic {
     /// `value: Some(v)` is a per-item point lookup (e.g.
     /// `count(cms_metric{item="checkout"})` — `key` is `item`, `value` is
     /// `"checkout"`). `value` is carried here rather than resolved by the
-    /// `SummaryExecutor` from a `Filter` predicate because `readout`'s
-    /// trait signature has no DAG access — see `CostModel::readout_extension`.
+    /// `SummaryExecutor` from a `Filter` predicate because `evaluation`'s
+    /// trait signature has no dag access — see `CostModel::evaluation_extension`.
     PointCount {
         key: ColumnRef,
         value: Option<String>,
@@ -622,7 +623,7 @@ mod tests {
     use super::*;
 
     #[test]
-    fn keyed_summary_input_and_topk_readout_round_trip() {
+    fn keyed_summary_input_and_topk_evaluation_round_trip() {
         for input in [
             SummaryUpdate {
                 item: Some(SummaryInputExpr::EntityIdentity(
diff --git a/crates/types/src/post_asap/summary_maintenance.rs b/crates/types/src/post_asap/summary_maintenance.rs
index d1e50d7e5..4e7eaf205 100644
--- a/crates/types/src/post_asap/summary_maintenance.rs
+++ b/crates/types/src/post_asap/summary_maintenance.rs
@@ -1,6 +1,6 @@
 //! Planner-level construction mode for a materialized summary.
 //!
-//! A [`super::SummaryNode`] is a logical summary expression and deliberately
+//! An ASAP [`crate::ir::OperatorNode`] is a logical summary expression and deliberately
 //! does not carry this choice: the same candidate may be built directly for
 //! one workload or maintained incrementally for another. Planner search
 //! attaches the selected mode to its lifecycle guarantee; downstream physical
diff --git a/crates/types/src/post_asap/summary_window.rs b/crates/types/src/post_asap/summary_window.rs
index 0e344c1ed..6d45649b4 100644
--- a/crates/types/src/post_asap/summary_window.rs
+++ b/crates/types/src/post_asap/summary_window.rs
@@ -57,7 +57,7 @@ pub enum PaneCoverageError {
     },
 }
 
-/// Validate that a pane-only readout covers a query exactly. A mismatched
+/// Validate that a pane-only evaluation covers a query exactly. A mismatched
 /// phase is sound only when the physical plan explicitly supplies an exact
 /// residual for the partial edge panes.
 pub fn validate_pane_coverage(
@@ -147,7 +147,7 @@ mod tests {
     }
 
     #[test]
-    fn pane_only_readout_rejects_source_and_query_phase_mismatch() {
+    fn pane_only_evaluation_rejects_source_and_query_phase_mismatch() {
         let layout = PaneLayout {
             pane_width_ms: 60_000,
             pane_origin_ms: Some(26_000),
diff --git a/crates/types/tests/planner_vocabulary.rs b/crates/types/tests/planner_vocabulary.rs
index f14a56ee8..ae8a72711 100644
--- a/crates/types/tests/planner_vocabulary.rs
+++ b/crates/types/tests/planner_vocabulary.rs
@@ -1,6 +1,5 @@
-use asap_types::post_asap::{
-    validate_pane_coverage, PaneLayout, WindowEdgeCompatibility, WindowEdgeCoverage,
-};
+use asap_types::ir::export::WindowEdgeCompatibility;
+use asap_types::post_asap::{validate_pane_coverage, PaneLayout, WindowEdgeCoverage};
 use asap_types::pre_asap::{SchemaResolver, Source, UnresolvedQueryExpr};
 use asap_types::resources::{PhysicalHandoffBytes, PhysicalHandoffKind};
 

From 0dd65e7bb83c61e29c19fea10a08cbfdfc8e901b Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 20:14:13 +0000
Subject: [PATCH 37/48] feat(planner): declare whole-source coverage on planned
 summary states

SummaryAgg nodes require SummaryCoverage. Today's planner has no time or
population evidence, so a SummaryAgg it builds declares the whole of the one
source scanned beneath it (no time bound, empty population). The declaration
is trusted, not derived from the scan (#570). Rebuilding the same state over a
re-placed input or with a different grouping strategy keeps its coverage.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/asap-aware-mapping/src/grouping.rs     |  10 +-
 crates/asap-aware-mapping/src/replacement.rs  | 126 +++++++++++++++---
 .../src/summary_maintenance_cost/model.rs     |   8 +-
 .../tests/operator_design_examples.rs         |  12 ++
 4 files changed, 129 insertions(+), 27 deletions(-)

diff --git a/crates/asap-aware-mapping/src/grouping.rs b/crates/asap-aware-mapping/src/grouping.rs
index bbbaad37f..da7562c1c 100644
--- a/crates/asap-aware-mapping/src/grouping.rs
+++ b/crates/asap-aware-mapping/src/grouping.rs
@@ -415,8 +415,10 @@ fn with_grouping(
                     field.dtype = FieldDataType::Sketch(kind.clone(), grouping.clone());
                 }
             }
-            std::rc::Rc::new(
-                OperatorNode::with_schema(
+            // Regrouping the same state leaves the observations it covers unchanged.
+            std::rc::Rc::new(OperatorNode {
+                coverage: node.coverage.clone(),
+                ..OperatorNode::with_schema(
                     asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
                         child: Rc::clone(child),
                         family: grouped_family,
@@ -427,8 +429,8 @@ fn with_grouping(
                     }),
                     grouped_schema,
                 )
-                .with_guarantee(None),
-            )
+                .with_guarantee(None)
+            })
         }
         // Never reached by this module's own callers (they only ever pass a
         // node `construct_summary_with` just bound for a `Sketch`
diff --git a/crates/asap-aware-mapping/src/replacement.rs b/crates/asap-aware-mapping/src/replacement.rs
index 14dbbc41a..509314d5c 100644
--- a/crates/asap-aware-mapping/src/replacement.rs
+++ b/crates/asap-aware-mapping/src/replacement.rs
@@ -352,6 +352,7 @@ use std::collections::{HashMap, HashSet, VecDeque};
 
 use asap_types::ir::cse::{share_common_sub_dags, structural_hash, HashCache};
 use asap_types::ir::operator_properties::{BinaryOpKind, JoinKind, Reduction};
+use asap_types::ir::summary_coverage::{CoverageRegion, SummaryCoverage};
 use asap_types::ir::timing::validate_default;
 use asap_types::ir::SchemaDerivationError;
 use asap_types::ir::{
@@ -2253,6 +2254,29 @@ fn realize_binary(
     )))
 }
 
+/// Coverage of a summary built over `child`: every observation of the one
+/// source scanned beneath it. Today's planner proves no time or population
+/// restriction, so this whole-source declaration is trusted, not derived from
+/// the scan (#570). `None` when `child` does not read exactly one source.
+pub(crate) fn whole_source_coverage(child: &Rc<OperatorNode>) -> Option<SummaryCoverage> {
+    let mut sources = OperatorNode::reachable(child)
+        .into_iter()
+        .filter_map(|node| match node.non_asap() {
+            Some(NonASAPOp::Scan { source, .. }) => Some(source.clone()),
+            _ => None,
+        });
+    let source = sources.next()?;
+    sources
+        .all(|other| other == source)
+        .then(|| SummaryCoverage {
+            source,
+            regions: vec![CoverageRegion {
+                time_ms: None,
+                population: Default::default(),
+            }],
+        })
+}
+
 /// Rebuild the summary chain above a per-series `Rate` accumulator with its
 /// `FinalizeExactAccumulator` placed at `timing`. `strict` additionally
 /// requires the fixed-window shape (a `PerEntity` Rate over a `TimeRange`);
@@ -3209,24 +3233,27 @@ fn construct_summary_agg(
     // a genuine empty-`by` reduction apart from a per-entity shape with no
     // grouping concept at all (issue #163). `construct_summary_agg` is the
     // single place that decides this; nothing downstream re-derives it.
-    let agg = std::rc::Rc::new(
-        OperatorNode::with_schema(
-            asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
-                child: bound_child,
-                family,
-                input: summary_input,
-                reduction: physical_reduction,
-                grouping: GroupingStrategy::default(),
-                filter: None,
-            }),
-            state_schema,
-        )
-        .with_guarantee(
-            // Summary *state* carries no caller-visible guarantee; only a
-            // finalized value does. An exact accumulator's state is its value.
-            if estimate { None } else { guarantee.clone() },
-        ),
+    let coverage = whole_source_coverage(&bound_child);
+    let agg = OperatorNode::with_schema(
+        asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
+            child: bound_child,
+            family,
+            input: summary_input,
+            reduction: physical_reduction,
+            grouping: GroupingStrategy::default(),
+            filter: None,
+        }),
+        state_schema,
+    )
+    .with_guarantee(
+        // Summary *state* carries no caller-visible guarantee; only a
+        // finalized value does. An exact accumulator's state is its value.
+        if estimate { None } else { guarantee.clone() },
     );
+    let agg = std::rc::Rc::new(match coverage {
+        Some(coverage) => agg.with_coverage(coverage)?,
+        None => agg,
+    });
     match query {
         // The evaluation: downstream of the estimate the schema is the plain
         // pre-ASAP row shape again (the summary-state type does not
@@ -5536,8 +5563,10 @@ fn relink_agg_child(node: &Rc<OperatorNode>, new_child: &Rc<OperatorNode>) -> Rc
             if Rc::ptr_eq(child, new_child) {
                 return Rc::clone(node);
             }
-            let rebuilt = std::rc::Rc::new(
-                OperatorNode::with_schema(
+            // The same summary over a re-placed input keeps its coverage.
+            let rebuilt = std::rc::Rc::new(OperatorNode {
+                coverage: node.coverage.clone(),
+                ..OperatorNode::with_schema(
                     asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
                         child: Rc::clone(new_child),
                         family: family.clone(),
@@ -5548,8 +5577,8 @@ fn relink_agg_child(node: &Rc<OperatorNode>, new_child: &Rc<OperatorNode>) -> Rc
                     }),
                     node.schema.clone(),
                 )
-                .with_guarantee(node.guarantee.clone()),
-            );
+                .with_guarantee(node.guarantee.clone())
+            });
             match validate_default(&rebuilt, ExecutionTiming::IngestionTime) {
                 Ok(_) => rebuilt,
                 Err(_) => Rc::clone(node),
@@ -11348,4 +11377,59 @@ mod tests {
             FieldDataType::Plain(DataType::Int64)
         );
     }
+
+    // Every SummaryAgg a strategy proposes declares whole-source coverage of
+    // the one source it reads (trusted, #570).
+    #[test]
+    fn proposed_summary_states_cover_their_whole_source() {
+        let root = agg(
+            vec![],
+            AggIntent::Quantile {
+                q: 0.9,
+                col: None,
+                accuracy: AccuracyTarget::Epsilon(0.01),
+            },
+            metric_scan(&["job"]),
+        );
+        let source = Source::TimeSeries { metric: "m".into() };
+        let proposals = ASAPStrategies::default_cost_model().propose(&TargetSubDAG::new(&root));
+        let states: Vec<_> = proposals
+            .candidates
+            .iter()
+            .filter_map(|candidate| match &candidate.replacement {
+                Replacement::SubDAG(node) => Some(node),
+                _ => None,
+            })
+            .flat_map(OperatorNode::reachable)
+            .filter(|node| matches!(node.asap(), Some(ASAPOp::SummaryAgg { .. })))
+            .collect();
+        assert!(!states.is_empty());
+        for state in states {
+            let coverage = state.coverage.as_ref().expect("summary state has coverage");
+            assert_eq!(coverage.source, source);
+            assert_eq!(
+                coverage.regions,
+                [CoverageRegion {
+                    time_ms: None,
+                    population: Default::default(),
+                }]
+            );
+        }
+    }
+
+    // Whole-source coverage names one source; over two it is not declared.
+    #[test]
+    fn whole_source_coverage_needs_exactly_one_source() {
+        let left = metric_scan(&["job"]);
+        let right = crate::test_support::scan("n", left.schema.clone());
+        assert!(whole_source_coverage(&left).is_some());
+        let join = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Join {
+            kind: asap_types::ir::operator_properties::JoinKind::Inner,
+            pred: equi_pred(0, 2),
+            left,
+            right,
+        }))
+        .unwrap();
+        assert_eq!(whole_source_coverage(&join), None);
+    }
 }
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_cost/model.rs b/crates/asap-aware-mapping/src/summary_maintenance_cost/model.rs
index 167874295..8d9c2886a 100644
--- a/crates/asap-aware-mapping/src/summary_maintenance_cost/model.rs
+++ b/crates/asap-aware-mapping/src/summary_maintenance_cost/model.rs
@@ -3036,10 +3036,12 @@ mod tests {
     fn summary_with_operations(merge: bool, subtract: bool, delete: bool) -> Rc<OperatorNode> {
         let state_type = FieldDataType::ExactAggregate(ExactKind::Count, ExactParams::Count);
         let schema = count_state_schema();
+        let child = metrics_scan();
+        let coverage = crate::replacement::whole_source_coverage(&child).unwrap();
         let agg = std::rc::Rc::new(
             OperatorNode::with_schema(
                 asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
-                    child: metrics_scan(),
+                    child,
                     family: state_type,
                     input: SummaryUpdate {
                         item: None,
@@ -3052,7 +3054,9 @@ mod tests {
                 }),
                 schema.clone(),
             )
-            .with_guarantee(None),
+            .with_guarantee(None)
+            .with_coverage(coverage)
+            .unwrap(),
         );
         let mut root = Rc::clone(&agg);
         if merge {
diff --git a/crates/integration-tests/tests/operator_design_examples.rs b/crates/integration-tests/tests/operator_design_examples.rs
index 8325ad92b..08c2ab4a0 100644
--- a/crates/integration-tests/tests/operator_design_examples.rs
+++ b/crates/integration-tests/tests/operator_design_examples.rs
@@ -1,5 +1,6 @@
 //! #511 examples: source text → unified dag → summary rewrite → flat export.
 use asap_frontend_sql::{lower_sql, SqlCatalog};
+use asap_types::ir::summary_coverage::{CoverageRegion, SummaryCoverage};
 use asap_types::ir::{ASAPOp, NonASAPOp, Operator, OperatorNode, ScalarExpr};
 use asap_types::post_asap::{
     ExactKind, ExactParams, FieldDataType, GroupingStrategy, SummaryUpdate,
@@ -84,6 +85,17 @@ async fn sql_sum_projection_before_and_after_summary_rewrite() {
                     grouping: GroupingStrategy::default(),
                     filter: None,
                 }))
+                .unwrap()
+                // Whole-source coverage, as the planner declares it today (#570).
+                .with_coverage(SummaryCoverage {
+                    source: asap_types::pre_asap::Source::Table {
+                        table_ref: "requests".into(),
+                    },
+                    regions: vec![CoverageRegion {
+                        time_ms: None,
+                        population: Default::default(),
+                    }],
+                })
                 .unwrap(),
             );
             let finalize = std::rc::Rc::new(

From 0c62c4ac7fbcfd1dc62d7fef4d6f9b9e98b8b7ac Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 20:24:17 +0000
Subject: [PATCH 38/48] feat(planner): export a planned workload as one
 physical ASAP DAG

PlanOutput::execution_timed_dag times every plan root with one shared
TimingMemo and compiles them with compile_physical_asap_workload, so a batch
is one DAG with a root per operator query and shared sub-DAGs exported once.
Lifecycle phases come from the deployments of every plan. The per-plan
SummaryMaintenanceLifecyclePlan::execution_timed_dag is the batch of one.
Standalone scalar roots have no physical form yet and are left out.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/asap-aware-mapping/src/lib.rs          |  17 +--
 crates/asap-aware-mapping/src/pass/mod.rs     |  10 ++
 .../src/summary_maintenance_lifecycle.rs      | 123 ++++++++++--------
 .../tests/operator_design_examples.rs         |  16 +++
 4 files changed, 104 insertions(+), 62 deletions(-)

diff --git a/crates/asap-aware-mapping/src/lib.rs b/crates/asap-aware-mapping/src/lib.rs
index 16e6e6118..15fe06d2b 100644
--- a/crates/asap-aware-mapping/src/lib.rs
+++ b/crates/asap-aware-mapping/src/lib.rs
@@ -222,14 +222,15 @@ pub use summary_maintenance_dag_export::{
 };
 pub use summary_maintenance_lifecycle::{
     assemble_selected_dag_with_summary_maintenance_lifecycles,
-    enumerate_summary_maintenance_lifecycles, global_selection_with_summary_maintenance_lifecycles,
-    plan_summary_maintenance_lifecycles, SummaryMaintenanceCapabilities,
-    SummaryMaintenanceDeployment, SummaryMaintenanceLifecycleAlternative,
-    SummaryMaintenanceLifecycleAssemblyError, SummaryMaintenanceLifecycleCandidates,
-    SummaryMaintenanceLifecycleCapabilities, SummaryMaintenanceLifecycleChoiceError,
-    SummaryMaintenanceLifecycleCostInputs, SummaryMaintenanceLifecyclePlan,
-    SummaryMaintenanceLifecyclePlanError, SummaryMaintenanceLifecycleRejection,
-    SummaryMaintenanceLifecycleSelectionError, SummaryMaintenanceTimingError, WorkloadDemand,
+    enumerate_summary_maintenance_lifecycles, execution_timed_workload_dag,
+    global_selection_with_summary_maintenance_lifecycles, plan_summary_maintenance_lifecycles,
+    SummaryMaintenanceCapabilities, SummaryMaintenanceDeployment,
+    SummaryMaintenanceLifecycleAlternative, SummaryMaintenanceLifecycleAssemblyError,
+    SummaryMaintenanceLifecycleCandidates, SummaryMaintenanceLifecycleCapabilities,
+    SummaryMaintenanceLifecycleChoiceError, SummaryMaintenanceLifecycleCostInputs,
+    SummaryMaintenanceLifecyclePlan, SummaryMaintenanceLifecyclePlanError,
+    SummaryMaintenanceLifecycleRejection, SummaryMaintenanceLifecycleSelectionError,
+    SummaryMaintenanceTimingError, WorkloadDemand,
 };
 pub use topk_reuse::TopKLimitReuseStrategy;
 
diff --git a/crates/asap-aware-mapping/src/pass/mod.rs b/crates/asap-aware-mapping/src/pass/mod.rs
index f9dd0ac2d..afd63dbdb 100644
--- a/crates/asap-aware-mapping/src/pass/mod.rs
+++ b/crates/asap-aware-mapping/src/pass/mod.rs
@@ -259,6 +259,16 @@ impl PlanOutput {
         nodes
     }
 
+    /// The workload as one physical ASAP DAG: a root per operator query, in
+    /// plan order, with shared sub-DAGs exported once. Standalone scalar
+    /// roots have no physical form yet and are left out.
+    pub fn execution_timed_dag(
+        &self,
+    ) -> Result<asap_types::ir::export::PhysicalASAPDAG, crate::SummaryMaintenanceTimingError> {
+        let plans: Vec<_> = self.plans.iter().map(|p| &p.plan).collect();
+        crate::execution_timed_workload_dag(&plans)
+    }
+
     pub fn len(&self) -> usize {
         self.plans.len() + self.scalar_roots.len()
     }
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_lifecycle.rs b/crates/asap-aware-mapping/src/summary_maintenance_lifecycle.rs
index d271139bb..51bb7e29a 100644
--- a/crates/asap-aware-mapping/src/summary_maintenance_lifecycle.rs
+++ b/crates/asap-aware-mapping/src/summary_maintenance_lifecycle.rs
@@ -22,8 +22,8 @@ use std::collections::{HashMap, HashSet};
 use std::rc::Rc;
 
 use asap_types::ir::export::{
-    compile_physical_asap_dag_with_node_ids, PhysicalASAPDAG, PhysicalASAPDAGValidationError,
-    PhysicalASAPNodeId,
+    compile_physical_asap_dag_with_node_ids, compile_physical_asap_workload_with_node_ids,
+    PhysicalASAPDAG, PhysicalASAPDAGValidationError, PhysicalASAPNodeId,
 };
 use asap_types::ir::timing::{apply_lifecycle_timings, LifecycleAssignment, TimingMemo};
 use asap_types::ir::{ASAPOp, Operator, OperatorNode};
@@ -247,64 +247,79 @@ impl SummaryMaintenanceLifecyclePlan {
     /// a `SummaryAgg` is one of its inputs. Timings already on the root are
     /// ignored.
     pub fn execution_timed_dag(&self) -> Result<PhysicalASAPDAG, SummaryMaintenanceTimingError> {
-        let mut memo = TimingMemo::new();
-        let timed = apply_lifecycle_timings(
-            &self.root,
-            &LifecycleAssignment::default_maintained(),
-            &mut memo,
-        )?;
-        let compiled = compile_physical_asap_dag_with_node_ids(&timed)?;
-        let dag = compiled.dag;
-        for population in &standalone_populations(&self.root) {
-            let id = compiled
-                .node_ids
-                .node_id(memo.timed(population).expect("population was timed"))
-                .expect("collected population belongs to the compiled DAG");
-            if !self
-                .deployments
-                .iter()
-                .any(|deployment| deployment.post_asap_node_id == id)
-            {
+        execution_timed_workload_dag(&[self])
+    }
+}
+
+/// One physical ASAP DAG for a workload: a root per plan, in order, with
+/// sub-DAGs shared between plans exported once. Timing follows the selected
+/// lifecycles of every plan's deployments, as in
+/// [`SummaryMaintenanceLifecyclePlan::execution_timed_dag`].
+pub fn execution_timed_workload_dag(
+    plans: &[&SummaryMaintenanceLifecyclePlan],
+) -> Result<PhysicalASAPDAG, SummaryMaintenanceTimingError> {
+    // One memo, so a node shared by several roots is timed and exported once.
+    let mut memo = TimingMemo::new();
+    let assignment = LifecycleAssignment::default_maintained();
+    let timed = plans
+        .iter()
+        .map(|plan| apply_lifecycle_timings(&plan.root, &assignment, &mut memo))
+        .collect::<Result<Vec<_>, _>>()?;
+    let compiled = compile_physical_asap_workload_with_node_ids(&timed)?;
+    let id_of = |node: &Rc<OperatorNode>| {
+        compiled
+            .node_ids
+            .node_id(memo.timed(node).expect("plan node was timed"))
+            .expect("timed plan node belongs to the compiled DAG")
+    };
+    let deployments: Vec<_> = plans
+        .iter()
+        .flat_map(|plan| &plan.deployments)
+        .map(|deployment| (id_of(&deployment.summary), deployment))
+        .collect();
+    for plan in plans {
+        for population in &standalone_populations(&plan.root) {
+            let id = id_of(population);
+            if !deployments.iter().any(|(deployed, _)| *deployed == id) {
                 return Err(SummaryMaintenanceTimingError::UnplannedMaintainedState(id));
             }
         }
-        let mut pending = Vec::new();
-        for deployment in &self.deployments {
-            let guarantee = deployment
-                .summary_maintenance_lifecycle_guarantee
-                .as_ref()
-                .ok_or(SummaryMaintenanceTimingError::UnselectedLifecycle(
-                    deployment.post_asap_node_id,
-                ))?;
-            if guarantee.summary_maintenance_lifecycle != SummaryMaintenanceLifecycle::Ephemeral {
-                pending.push(deployment.post_asap_node_id);
-            }
+    }
+    let dag = compiled.dag;
+    let mut pending = Vec::new();
+    for (id, deployment) in &deployments {
+        let guarantee = deployment
+            .summary_maintenance_lifecycle_guarantee
+            .as_ref()
+            .ok_or(SummaryMaintenanceTimingError::UnselectedLifecycle(*id))?;
+        if guarantee.summary_maintenance_lifecycle != SummaryMaintenanceLifecycle::Ephemeral {
+            pending.push(*id);
         }
-        let mut ingestion = HashSet::new();
-        while let Some(id) = pending.pop() {
-            if ingestion.insert(id) {
-                pending.extend(
-                    dag.edges
-                        .iter()
-                        .filter(|edge| edge.consumer == id)
-                        .map(|edge| edge.producer),
-                );
-            }
+    }
+    let mut ingestion = HashSet::new();
+    while let Some(id) = pending.pop() {
+        if ingestion.insert(id) {
+            pending.extend(
+                dag.edges
+                    .iter()
+                    .filter(|edge| edge.consumer == id)
+                    .map(|edge| edge.producer),
+            );
         }
-        let phases = dag
-            .nodes
-            .iter()
-            .map(|node| {
-                let timing = if ingestion.contains(&node.id) {
-                    ExecutionTiming::IngestionTime
-                } else {
-                    ExecutionTiming::QueryTime
-                };
-                (node.id, timing)
-            })
-            .collect();
-        Ok(dag.with_execution_phases(&phases)?)
     }
+    let phases = dag
+        .nodes
+        .iter()
+        .map(|node| {
+            let timing = if ingestion.contains(&node.id) {
+                ExecutionTiming::IngestionTime
+            } else {
+                ExecutionTiming::QueryTime
+            };
+            (node.id, timing)
+        })
+        .collect();
+    Ok(dag.with_execution_phases(&phases)?)
 }
 
 /// Explicit association between a materialized target and the normalized
diff --git a/crates/integration-tests/tests/operator_design_examples.rs b/crates/integration-tests/tests/operator_design_examples.rs
index 08c2ab4a0..4b52026b4 100644
--- a/crates/integration-tests/tests/operator_design_examples.rs
+++ b/crates/integration-tests/tests/operator_design_examples.rs
@@ -410,4 +410,20 @@ async fn batch_planning_replaces_and_shares_summary_operators() {
             rows
         );
     }
+    // The batch exports as one physical DAG: a root per query and the shared
+    // SUM state once.
+    let workload_dag = output.execution_timed_dag().unwrap();
+    assert_eq!(workload_dag.roots.len(), 2);
+    assert_ne!(workload_dag.roots[0], workload_dag.roots[1]);
+    assert_eq!(
+        workload_dag
+            .nodes
+            .iter()
+            .filter(|n| matches!(
+                n.payload,
+                asap_types::ir::export::PhysicalASAPOperatorPayload::SummaryAgg { .. }
+            ))
+            .count(),
+        1
+    );
 }

From 8a49e06bbe6b7ef7202903ca975c333437acb563 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 20:44:06 +0000
Subject: [PATCH 39/48] refactor(ir): remove the legacy QueryExpr and
 SummaryExpr IRs

The planner emits the unified operator IR end to end, so the old pre-ASAP
QueryExpr DAG, its resolver/canonicalizer/CSE, and the post-ASAP
SummaryExpr/PostAsapDAG modules have no live consumers left.

- Move the operator parameter types (GroupKeys, Reduction, Source, ...)
  into ir/operator_properties.rs; pre_asap re-exports them.
- Drop QueryExpr paths from execution_data_state, maintained_population,
  agg_intent, column_resolution, scalar_type_rules and pre_asap/schema.
  with_promql_series_identity keeps only its OperatorNode version in
  ir/schema_support.rs.
- Delete the undeclared unified/ frontend dirs, unified_physical_planner,
  unified_sources, expressions/unified_planner.rs and readout.rs.
- Migrate planner_vocabulary.rs off SchemaResolver; fix the
  scalar_type_rules_fail_closed test name.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 .../src/accuracy/reconciliation.rs            |    4 +-
 crates/asap-aware-mapping/src/lib.rs          |   10 +-
 crates/asap-aware-mapping/src/replacement.rs  |    6 +-
 crates/asap-aware-mapping/src/rollup.rs       |    4 +-
 .../src/expressions/unified_planner.rs        |  738 -----
 crates/asap-physical-operators/src/readout.rs |  111 -
 .../unified_physical_planner/candidates.rs    |  329 --
 .../src/unified_physical_planner/compiled.rs  |  352 ---
 .../src/unified_physical_planner/logical.rs   |  374 ---
 .../src/unified_physical_planner/mod.rs       | 1169 -------
 .../unified_physical_planner/precompute.rs    |  643 ----
 .../promql_fallback.rs                        |  859 -----
 .../unified_physical_planner/promql_rows.rs   |  308 --
 .../unified_physical_planner/promql_values.rs |  281 --
 .../unified_physical_planner/row_values.rs    |   60 -
 .../src/unified_sources/memory.rs             |   44 -
 .../src/unified_sources/mod.rs                |  177 --
 .../tests/blocking_resources.rs               |    4 +-
 .../tests/physical_dag.rs                     |   24 +-
 .../tests/physical_semantics.rs               |   28 +-
 .../tests/planspace_series_identity_heap.rs   |    6 +-
 crates/frontend-metricsql/src/unified/mod.rs  |  389 ---
 crates/frontend-promql/src/unified/error.rs   |   81 -
 .../frontend-promql/src/unified/histogram.rs  |  129 -
 crates/frontend-promql/src/unified/mod.rs     |  233 --
 crates/frontend-promql/src/unified/promql.rs  | 2236 -------------
 crates/frontend-sql/src/unified/error.rs      |   75 -
 crates/frontend-sql/src/unified/mod.rs        |  103 -
 .../src/unified/sql/clickhouse_ast.rs         |  152 -
 .../src/unified/sql/collection_planning.rs    |  194 --
 crates/frontend-sql/src/unified/sql/expr.rs   |  357 ---
 crates/frontend-sql/src/unified/sql/mod.rs    | 2528 ---------------
 crates/frontend-sql/src/unified/sql/types.rs  |  378 ---
 crates/types/Cargo.toml                       |    2 +-
 crates/types/src/ir/mod.rs                    |    3 +-
 crates/types/src/ir/operator_properties.rs    |  572 +++-
 crates/types/src/ir/schema_support.rs         |    9 +
 crates/types/src/lib.rs                       |   36 +-
 crates/types/src/post_asap/cse.rs             |  442 ---
 .../src/post_asap/execution_data_state.rs     | 1205 +------
 crates/types/src/post_asap/expr.rs            |  303 --
 .../src/post_asap/maintained_population.rs    |  107 +-
 crates/types/src/post_asap/mod.rs             |   69 +-
 crates/types/src/post_asap/post_asap_dag.rs   |  867 ------
 crates/types/src/pre_asap/agg_intent.rs       |   25 +-
 crates/types/src/pre_asap/canonicalize.rs     |  782 -----
 .../types/src/pre_asap/column_resolution.rs   |  186 +-
 crates/types/src/pre_asap/cse.rs              | 1111 -------
 crates/types/src/pre_asap/expr_ir.rs          |   31 +-
 crates/types/src/pre_asap/mod.rs              |   66 +-
 crates/types/src/pre_asap/query_expr.rs       | 2774 -----------------
 crates/types/src/pre_asap/resolve.rs          |  857 -----
 .../types/src/pre_asap/scalar_type_rules.rs   |  340 +-
 crates/types/src/pre_asap/schema.rs           |   84 -
 crates/types/src/pre_asap/schema_resolver.rs  |  492 ---
 crates/types/tests/planner_vocabulary.rs      |   16 +-
 crates/types/tests/structure_contract.rs      |    2 +-
 57 files changed, 744 insertions(+), 22023 deletions(-)
 delete mode 100644 crates/asap-physical-operators/src/expressions/unified_planner.rs
 delete mode 100644 crates/asap-physical-operators/src/readout.rs
 delete mode 100644 crates/asap-physical-operators/src/unified_physical_planner/candidates.rs
 delete mode 100644 crates/asap-physical-operators/src/unified_physical_planner/compiled.rs
 delete mode 100644 crates/asap-physical-operators/src/unified_physical_planner/logical.rs
 delete mode 100644 crates/asap-physical-operators/src/unified_physical_planner/mod.rs
 delete mode 100644 crates/asap-physical-operators/src/unified_physical_planner/precompute.rs
 delete mode 100644 crates/asap-physical-operators/src/unified_physical_planner/promql_fallback.rs
 delete mode 100644 crates/asap-physical-operators/src/unified_physical_planner/promql_rows.rs
 delete mode 100644 crates/asap-physical-operators/src/unified_physical_planner/promql_values.rs
 delete mode 100644 crates/asap-physical-operators/src/unified_physical_planner/row_values.rs
 delete mode 100644 crates/asap-physical-operators/src/unified_sources/memory.rs
 delete mode 100644 crates/asap-physical-operators/src/unified_sources/mod.rs
 delete mode 100644 crates/frontend-metricsql/src/unified/mod.rs
 delete mode 100644 crates/frontend-promql/src/unified/error.rs
 delete mode 100644 crates/frontend-promql/src/unified/histogram.rs
 delete mode 100644 crates/frontend-promql/src/unified/mod.rs
 delete mode 100644 crates/frontend-promql/src/unified/promql.rs
 delete mode 100644 crates/frontend-sql/src/unified/error.rs
 delete mode 100644 crates/frontend-sql/src/unified/mod.rs
 delete mode 100644 crates/frontend-sql/src/unified/sql/clickhouse_ast.rs
 delete mode 100644 crates/frontend-sql/src/unified/sql/collection_planning.rs
 delete mode 100644 crates/frontend-sql/src/unified/sql/expr.rs
 delete mode 100644 crates/frontend-sql/src/unified/sql/mod.rs
 delete mode 100644 crates/frontend-sql/src/unified/sql/types.rs
 delete mode 100644 crates/types/src/post_asap/cse.rs
 delete mode 100644 crates/types/src/post_asap/expr.rs
 delete mode 100644 crates/types/src/post_asap/post_asap_dag.rs
 delete mode 100644 crates/types/src/pre_asap/canonicalize.rs
 delete mode 100644 crates/types/src/pre_asap/cse.rs
 delete mode 100644 crates/types/src/pre_asap/query_expr.rs
 delete mode 100644 crates/types/src/pre_asap/resolve.rs
 delete mode 100644 crates/types/src/pre_asap/schema_resolver.rs

diff --git a/crates/asap-aware-mapping/src/accuracy/reconciliation.rs b/crates/asap-aware-mapping/src/accuracy/reconciliation.rs
index 36a219d4e..a8b16bcae 100644
--- a/crates/asap-aware-mapping/src/accuracy/reconciliation.rs
+++ b/crates/asap-aware-mapping/src/accuracy/reconciliation.rs
@@ -3,7 +3,7 @@
 //!
 //! ## The gap this closes
 //!
-//! `asap_types::pre_asap::cse::share_common_sub_dags` (pre-ASAP CSE) only
+//! `asap_types::ir::cse::share_common_sub_dags` (pre-ASAP CSE) only
 //! ever merges two sub-DAGs that are *exactly* [`PartialEq`]-equal,
 //! including their [`AggIntent`]'s `accuracy: AccuracyTarget` field. Two
 //! otherwise-identical aggregates that differ *only* in how tight an
@@ -303,7 +303,7 @@ impl AccuracyReconciliationStrategy {
     ///
     /// Also requires the candidate's own *output* schema to carry a provable
     /// unique key ([`Schema::has_unique_key`]) — the exact legality gate
-    /// `pre_asap::cse::share_common_sub_dags` already applies to its own
+    /// `ir::cse::share_common_sub_dags` already applies to its own
     /// sharing decisions, and [`crate::rollup::RollupStrategy`] already
     /// reuses verbatim for the identical reason (see that module's
     /// `is_legal_rollup_source` doc, point 4): a producer's output is only
diff --git a/crates/asap-aware-mapping/src/lib.rs b/crates/asap-aware-mapping/src/lib.rs
index 15fe06d2b..42cad7974 100644
--- a/crates/asap-aware-mapping/src/lib.rs
+++ b/crates/asap-aware-mapping/src/lib.rs
@@ -22,9 +22,9 @@
 //! It depends only on the IR crate, never on a front end — the layering
 //! invariant (arrows point up) holds here too.
 //!
-//! Post-lowering **canonicalization** is *not* here: it landed in
-//! `asap_types::pre_asap::canonicalize`, run inside the shared `resolve_root`
-//! so every front end normalizes before the pre-ASAP IR leaves resolution
+//! Post-lowering **canonicalization** is *not* here: it lives in
+//! `asap_types::ir::canonicalize`, run inside `asap_frontend_common`'s shared
+//! `resolve_root` so every front end normalizes before the IR leaves resolution
 //! (issue #34, closed).
 //!
 //! ## Planning workflows
@@ -83,7 +83,7 @@
 //!   re-deriving it from an already-computed, strictly finer sibling
 //!   `Aggregate` over identical child IR instead of an independent pass
 //!   over the raw source — the cross-aggregate sibling of
-//!   `pre_asap::cse::share_common_sub_dags`'s identical-sub-DAG sharing.
+//!   `ir::cse::share_common_sub_dags`'s identical-sub-DAG sharing.
 //!   [`rollup::is_legal_rollup_source`] is the standalone legality predicate
 //!   other axes (e.g. issue #256's `GroupingStrategy`) are expected to
 //!   consult directly, so it and this module's `RollupStrategy` can never
@@ -115,7 +115,7 @@
 //!
 //! | Term | Meaning | Entry point |
 //! |---|---|---|
-//! | Schema resolution | Derive input schemas and resolve column names to positions | `asap_types::pre_asap::SchemaResolver::resolve_schema`, `resolve_root` |
+//! | Schema resolution | Derive input schemas and resolve column names to positions | `asap_frontend_common::schema_resolver::SchemaResolver::resolve_schema`, `asap_frontend_common::resolve::resolve_root` |
 //! | Realization | Enumerate ranked physical forms for one aggregate intent | `replacement::realizations_for_intent` |
 //! | Replacement | Construct each candidate summary sub-DAG | [`replacement::ASAPStrategies`] |
 //! | Search | Enumerate and compare alternatives across a workload | [`replacement::search_workload`] |
diff --git a/crates/asap-aware-mapping/src/replacement.rs b/crates/asap-aware-mapping/src/replacement.rs
index 509314d5c..dd043b915 100644
--- a/crates/asap-aware-mapping/src/replacement.rs
+++ b/crates/asap-aware-mapping/src/replacement.rs
@@ -77,7 +77,7 @@
 //!   binds (single intent, no `HAVING`), every entry becomes its own bound
 //!   candidate.
 //! - [`SharedSubDAGStrategy`] wraps
-//!   `asap_types::pre_asap::cse::share_common_sub_dags`'s sharing decision.
+//!   `asap_types::ir::cse::share_common_sub_dags`'s sharing decision.
 //!   Wherever a [`TargetSubDAG`] already has two or more consumers (i.e.
 //!   `share_common_sub_dags` already collapsed two or more workload
 //!   locations onto the same `Rc<OperatorNode>` — [`discover_targets`] below
@@ -144,7 +144,7 @@
 //! 1. **Per-target candidates, not flat plans.** [`TargetSubDAGCandidates`]
 //!    stores the alternatives for one distinct [`TargetSubDAG`] (identified by
 //!    its own `Rc<OperatorNode>` pointer identity — the same currency
-//!    [`asap_types::pre_asap::cse::share_common_sub_dags`] already
+//!    [`asap_types::ir::cse::share_common_sub_dags`] already
 //!    established across the workload) holding every
 //!    [`ReplacementSubDAG`] alternative discovered for it. [`CandidateLogicalASAPDAGs`] is
 //!    a collection of these groups, keyed by `TargetSubDAG` — a candidate
@@ -175,7 +175,7 @@
 //! line above stands for: every `TargetSubDAG` this pass discovers is one
 //! iteration of that loop. It walks every workload root's whole DAG (the
 //! same **relational-skeleton** operator-child scope
-//! `asap_types::pre_asap::cse::share_common_sub_dags` itself uses — see
+//! `asap_types::ir::cse::share_common_sub_dags` itself uses — see
 //! that module's "Algorithm" section), discovering one `TargetSubDAG` per
 //! distinct `Rc` and a *real* `consumer_count`: how many operator-child
 //! positions anywhere in the workload reference that exact `Rc`, not just
diff --git a/crates/asap-aware-mapping/src/rollup.rs b/crates/asap-aware-mapping/src/rollup.rs
index 09dc16fa4..572d2c60a 100644
--- a/crates/asap-aware-mapping/src/rollup.rs
+++ b/crates/asap-aware-mapping/src/rollup.rs
@@ -20,7 +20,7 @@
 //! "Rolling up aggregations on a fine-grained group by to get a
 //! coarse-grained group by (like AHA)," alongside "CSE across aggregations,
 //! and group by key management" — this strategy is the *cross-aggregate*
-//! sibling of `pre_asap::cse::share_common_sub_dags`'s *identical*-sub-DAG
+//! sibling of `ir::cse::share_common_sub_dags`'s *identical*-sub-DAG
 //! sharing: CSE shares two structurally-*equal* aggregates onto one `Rc`;
 //! this strategy relates two structurally-*different* (differently grouped)
 //! aggregates over the same shared source.
@@ -207,7 +207,7 @@ fn rollup_combinator(intent: &AggIntent, finer_measure_col: ColumnId) -> Option<
 /// 4. `finer_output_schema` (the finer aggregate's own *output* schema, not
 ///    the shared child's) carries a provable unique key
 ///    ([`Schema::has_unique_key`]) — **the exact legality gate
-///    `pre_asap::cse::share_common_sub_dags` already applies to its own
+///    `ir::cse::share_common_sub_dags` already applies to its own
 ///    sharing decisions**, reused verbatim here rather than re-invented:
 ///    `share_common_sub_dags`'s own doc ("Legality: gated by
 ///    `Schema::unique_keys`") states a producer's output is only safely
diff --git a/crates/asap-physical-operators/src/expressions/unified_planner.rs b/crates/asap-physical-operators/src/expressions/unified_planner.rs
deleted file mode 100644
index a23b3dab1..000000000
--- a/crates/asap-physical-operators/src/expressions/unified_planner.rs
+++ /dev/null
@@ -1,738 +0,0 @@
-//! Planner scalar expressions evaluated over native typed rows.
-use crate::{
-    values::{SchemaRef, Value},
-    Error,
-};
-use planner_types::pre_asap::{ArithmeticOpKind, CompareOpKind, DataType, ScalarValue};
-
-use planner_types::ir::ScalarExpr;
-use std::{cmp::Ordering, sync::Arc};
-
-pub(super) fn evaluate(
-    expr: &ScalarExpr,
-    row: &[Value],
-    schema: &planner_types::pre_asap::Schema,
-) -> Result<Value, Error> {
-    match expr {
-        ScalarExpr::Column(index) => row.get(*index).cloned().ok_or(Error::Invalid(format!(
-            "column {index} outside row width {}",
-            row.len()
-        ))),
-        ScalarExpr::Literal(value) => Ok(match value {
-            ScalarValue::Interval {
-                months,
-                days,
-                nanos,
-            } => Value::Interval {
-                months: *months,
-                days: *days,
-                nanos: *nanos,
-            },
-            ScalarValue::Int64(value) => Value::Int64(*value),
-            ScalarValue::Float64(value) => Value::Float64(*value),
-            ScalarValue::Utf8(value) => Value::Utf8(value.clone().into()),
-            ScalarValue::Boolean(value) => Value::Bool(*value),
-            ScalarValue::Null => Value::Null,
-        }),
-        ScalarExpr::Cast { expr, to, .. } => {
-            let value = evaluate(expr, row, schema)?;
-            match (value, to) {
-                (Value::Null, _) => Ok(Value::Null),
-                (Value::Int64(value), DataType::Float64) => Ok(Value::Float64(value as f64)),
-                (value, _)
-                    if expr
-                        .scalar_type(schema)
-                        .map_err(|e| Error::Invalid(e.to_string()))?
-                        .0
-                        == *to =>
-                {
-                    Ok(value)
-                }
-                _ => Err(Error::Invalid("unsupported cast".into())),
-            }
-        }
-        ScalarExpr::Negative { expr, .. } => match evaluate(expr, row, schema)? {
-            Value::Float64(v) => Ok(Value::Float64(-v)),
-            Value::Int64(v) => v
-                .checked_neg()
-                .map(Value::Int64)
-                .ok_or_else(|| Error::Invalid("integer negation overflow".into())),
-            Value::Null => Ok(Value::Null),
-            _ => Err(Error::Invalid("invalid negation input".into())),
-        },
-        ScalarExpr::Compare {
-            left, op, right, ..
-        } => {
-            let left = evaluate(left, row, schema)?;
-            let right = evaluate(right, row, schema)?;
-            compare(op, left, right)
-        }
-        ScalarExpr::Arithmetic {
-            op, left, right, ..
-        } => arithmetic(
-            op,
-            evaluate(left, row, schema)?,
-            evaluate(right, row, schema)?,
-        ),
-        ScalarExpr::Case {
-            operand: None,
-            branches,
-            else_expr,
-        } => {
-            for (condition, value) in branches {
-                if matches!(evaluate(condition, row, schema)?, Value::Bool(true)) {
-                    return evaluate(value, row, schema);
-                }
-            }
-            else_expr
-                .as_ref()
-                .map_or(Ok(Value::Null), |e| evaluate(e, row, schema))
-        }
-        ScalarExpr::BoolAnd(parts) | ScalarExpr::BoolOr(parts) => {
-            let and = matches!(expr, ScalarExpr::BoolAnd(_));
-            let mut null = false;
-            for part in parts {
-                match evaluate(part, row, schema)? {
-                    Value::Bool(value) if value != and => return Ok(Value::Bool(value)),
-                    Value::Bool(_) => {}
-                    Value::Null => null = true,
-                    _ => return Err(Error::Invalid("boolean predicate required".into())),
-                }
-            }
-            Ok(if null { Value::Null } else { Value::Bool(and) })
-        }
-        ScalarExpr::Not(value) => match evaluate(value, row, schema)? {
-            Value::Bool(value) => Ok(Value::Bool(!value)),
-            Value::Null => Ok(Value::Null),
-            _ => Err(Error::Invalid("boolean predicate required".into())),
-        },
-        ScalarExpr::IsNull(value) => Ok(Value::Bool(matches!(
-            evaluate(value, row, schema)?,
-            Value::Null
-        ))),
-        ScalarExpr::IsNotNull(value) => Ok(Value::Bool(!matches!(
-            evaluate(value, row, schema)?,
-            Value::Null
-        ))),
-        ScalarExpr::FunctionCall { name, args } => {
-            use planner_types::pre_asap::scalar_type_rules::MapScalarFunction;
-            if planner_types::pre_asap::scalar_type_rules::promql_function_arity(name).is_some() {
-                let values = args
-                    .iter()
-                    .map(|arg| match evaluate(arg, row, schema)? {
-                        Value::Float64(v) => Ok(v),
-                        _ => Err(Error::Invalid("PromQL function requires floats".into())),
-                    })
-                    .collect::<Result<Vec<_>, _>>()?;
-                return Ok(Value::Float64(promql_function(name, &values)?));
-            }
-            if name == "promql_drop_metric_name" {
-                let Value::Utf8(encoded) = evaluate(&args[0], row, schema)? else {
-                    return Err(Error::Invalid("series identity must be Utf8".into()));
-                };
-                let mut labels: std::collections::BTreeMap<String, String> =
-                    serde_json::from_str(&encoded).map_err(|e| Error::Invalid(e.to_string()))?;
-                labels.remove("__name__");
-                return Ok(Value::Utf8(
-                    serde_json::to_string(&labels)
-                        .map_err(|e| Error::Invalid(e.to_string()))?
-                        .into(),
-                ));
-            }
-            if name.eq_ignore_ascii_case("asap_struct_field") {
-                expr.scalar_type(schema)
-                    .map_err(|error| Error::Invalid(error.to_string()))?;
-                let DataType::Struct { fields } = args[0]
-                    .scalar_type(schema)
-                    .map_err(|error| Error::Invalid(error.to_string()))?
-                    .0
-                else {
-                    unreachable!()
-                };
-                let offset = match &args[1] {
-                    ScalarExpr::Literal(ScalarValue::Int64(index)) => {
-                        usize::try_from(index - 1).ok()
-                    }
-                    ScalarExpr::Literal(ScalarValue::Utf8(name)) => {
-                        fields.iter().position(|field| &field.name == name)
-                    }
-                    _ => None,
-                }
-                .ok_or_else(|| Error::Invalid("struct field selector".into()))?;
-                let Value::Struct(values) = evaluate(&args[0], row, schema)? else {
-                    return Err(Error::Invalid("struct field input".into()));
-                };
-                return values
-                    .get(offset)
-                    .cloned()
-                    .ok_or_else(|| Error::Invalid("struct field value".into()));
-            }
-            if name.eq_ignore_ascii_case("asap_element_access") {
-                let (output_type, _) = expr
-                    .scalar_type(schema)
-                    .map_err(|error| Error::Invalid(error.to_string()))?;
-                if let DataType::List { element } = args[0]
-                    .scalar_type(schema)
-                    .map_err(|error| Error::Invalid(error.to_string()))?
-                    .0
-                {
-                    let Value::List(values) = evaluate(&args[0], row, schema)? else {
-                        return Err(Error::Invalid("array access input".into()));
-                    };
-                    let index = match evaluate(&args[1], row, schema)? {
-                        Value::Null => return Ok(Value::Null),
-                        Value::Int64(index) => index,
-                        _ => return Err(Error::Invalid("array access index".into())),
-                    };
-                    let offset = if index > 0 {
-                        usize::try_from(index - 1).ok()
-                    } else if index < 0 {
-                        usize::try_from(index.unsigned_abs())
-                            .ok()
-                            .and_then(|distance| values.len().checked_sub(distance))
-                    } else {
-                        None
-                    };
-                    return match offset.and_then(|offset| values.get(offset)) {
-                        Some(value) => Ok(value.clone()),
-                        None => default_collection_element(&output_type, element.nullable),
-                    };
-                }
-            }
-            let function = (if name.eq_ignore_ascii_case("asap_element_access") {
-                Some(MapScalarFunction::Access)
-            } else {
-                MapScalarFunction::from_name(name)
-            })
-            .ok_or_else(|| Error::Invalid(format!("scalar function {name}")))?;
-            expr.scalar_type(schema)
-                .map_err(|error| Error::Invalid(error.to_string()))?;
-            let values = args
-                .iter()
-                .map(|arg| evaluate(arg, row, schema))
-                .collect::<Result<Vec<_>, _>>()?;
-            match function {
-                MapScalarFunction::Construct => {
-                    let mut values = values.into_iter();
-                    let mut entries = Vec::new();
-                    while let Some(key) = values.next() {
-                        if !matches!(key, Value::Int64(_) | Value::Utf8(_) | Value::Bool(_)) {
-                            return Err(Error::Invalid("map key value type".into()));
-                        }
-                        entries.push((
-                            key,
-                            values
-                                .next()
-                                .ok_or_else(|| Error::Invalid("odd map argument count".into()))?,
-                        ));
-                    }
-                    Ok(Value::Map(entries.into()))
-                }
-                MapScalarFunction::Concat => {
-                    let mut entries = Vec::new();
-                    for value in values {
-                        let Value::Map(next) = value else {
-                            return Err(Error::Invalid("map concat argument".into()));
-                        };
-                        entries.extend(next.iter().cloned());
-                    }
-                    Ok(Value::Map(entries.into()))
-                }
-                MapScalarFunction::Access => {
-                    let [Value::Map(entries), key] = values.as_slice() else {
-                        return Err(Error::Invalid("map access arguments".into()));
-                    };
-                    if matches!(key, Value::Null) {
-                        return Ok(Value::Null);
-                    }
-                    if !matches!(key, Value::Int64(_) | Value::Utf8(_) | Value::Bool(_)) {
-                        return Err(Error::Invalid("map lookup key type".into()));
-                    }
-                    if let Some((_, value)) = entries
-                        .iter()
-                        .find(|(candidate, _)| cell_cmp(candidate, key) == Some(Ordering::Equal))
-                    {
-                        return Ok(value.clone());
-                    }
-                    let (
-                        DataType::Map {
-                            value,
-                            value_nullable,
-                            ..
-                        },
-                        _,
-                    ) = args[0]
-                        .scalar_type(schema)
-                        .map_err(|error| Error::Invalid(error.to_string()))?
-                    else {
-                        unreachable!()
-                    };
-                    default_collection_element(&value, value_nullable)
-                }
-            }
-        }
-        other => Err(Error::Invalid(format!("scalar expression {other:?}"))),
-    }
-}
-
-fn default_collection_element(dtype: &DataType, nullable: bool) -> Result<Value, Error> {
-    if nullable {
-        return Ok(Value::Null);
-    }
-    Ok(match dtype {
-        DataType::Interval | DataType::Date => {
-            return Err(Error::Invalid("temporal value transport".into()))
-        }
-        DataType::Null => Value::Null,
-        DataType::Int64 => Value::Int64(0),
-        DataType::Float64 => Value::Float64(0.0),
-        DataType::Utf8 => Value::Utf8("".into()),
-        DataType::Bool => Value::Bool(false),
-        DataType::Map { .. } => Value::Map(Arc::from([])),
-        DataType::List { .. } => Value::List(Arc::from([])),
-        DataType::Struct { fields } => Value::Struct(
-            fields
-                .iter()
-                .map(|field| default_collection_element(&field.dtype, field.nullable))
-                .collect::<Result<Vec<_>, _>>()?
-                .into(),
-        ),
-        _ => {
-            return Err(Error::Invalid(
-                "collection missing-element default type".into(),
-            ))
-        }
-    })
-}
-
-fn compare(op: &CompareOpKind, left: Value, right: Value) -> Result<Value, Error> {
-    if matches!(left, Value::Null) || matches!(right, Value::Null) {
-        return Ok(Value::Null);
-    }
-    // NaN is unordered, not a type mismatch. Match the native scalar path.
-    if matches!(&left, Value::Float64(v) if v.is_nan())
-        || matches!(&right, Value::Float64(v) if v.is_nan())
-    {
-        return match op {
-            CompareOpKind::Ne => Ok(Value::Bool(true)),
-            CompareOpKind::Eq
-            | CompareOpKind::Lt
-            | CompareOpKind::Le
-            | CompareOpKind::Gt
-            | CompareOpKind::Ge => Ok(Value::Bool(false)),
-            _ => Err(Error::Invalid(format!("comparison {op:?}"))),
-        };
-    }
-    let ordering = cell_cmp(&left, &right)
-        .ok_or_else(|| Error::Invalid("comparison of incompatible values".into()))?;
-    let value = match op {
-        CompareOpKind::Eq => ordering == Ordering::Equal,
-        CompareOpKind::Ne => ordering != Ordering::Equal,
-        CompareOpKind::Lt => ordering == Ordering::Less,
-        CompareOpKind::Le => ordering != Ordering::Greater,
-        CompareOpKind::Gt => ordering == Ordering::Greater,
-        CompareOpKind::Ge => ordering != Ordering::Less,
-        _ => return Err(Error::Invalid(format!("comparison {op:?}"))),
-    };
-    Ok(Value::Bool(value))
-}
-
-fn arithmetic(op: &ArithmeticOpKind, left: Value, right: Value) -> Result<Value, Error> {
-    let (left, right) = match (left, right) {
-        (Value::Int64(a), Value::Float64(b)) => (Value::Float64(a as f64), Value::Float64(b)),
-        (Value::Float64(a), Value::Int64(b)) => (Value::Float64(a), Value::Float64(b as f64)),
-        pair => pair,
-    };
-    super::numeric(op, left, right)
-}
-
-fn integer_float_cmp(integer: i64, float: f64) -> Option<Ordering> {
-    if float.is_nan() {
-        return None;
-    }
-    // These bounds are powers of two, exactly representable as Float64.
-    if float >= 9_223_372_036_854_775_808.0 {
-        return Some(Ordering::Less);
-    }
-    if float < -9_223_372_036_854_775_808.0 {
-        return Some(Ordering::Greater);
-    }
-    let integral = float as i64;
-    match integer.cmp(&integral) {
-        Ordering::Equal => 0.0_f64.partial_cmp(&float.fract()),
-        other => Some(other),
-    }
-}
-
-fn cell_cmp(left: &Value, right: &Value) -> Option<Ordering> {
-    match (left, right) {
-        (Value::Int64(left), Value::Int64(right)) => Some(left.cmp(right)),
-        (Value::Float64(left), Value::Float64(right)) => left.partial_cmp(right),
-        (Value::Int64(left), Value::Float64(right)) => integer_float_cmp(*left, *right),
-        (Value::Float64(left), Value::Int64(right)) => {
-            integer_float_cmp(*right, *left).map(Ordering::reverse)
-        }
-        (Value::Utf8(left), Value::Utf8(right)) => Some(left.cmp(right)),
-        (Value::Bool(left), Value::Bool(right)) => Some(left.cmp(right)),
-        (Value::Timestamp(left), Value::Timestamp(right)) => Some(left.cmp(right)),
-        (Value::Map(left), Value::Map(right)) => {
-            for ((left_key, left_value), (right_key, right_value)) in left.iter().zip(right.iter())
-            {
-                let order = cell_cmp(left_key, right_key)?;
-                if order != Ordering::Equal {
-                    return Some(order);
-                }
-                let order = match (left_value, right_value) {
-                    (Value::Null, Value::Null) => Ordering::Equal,
-                    (Value::Null, _) => Ordering::Greater,
-                    (_, Value::Null) => Ordering::Less,
-                    _ => cell_cmp(left_value, right_value)?,
-                };
-                if order != Ordering::Equal {
-                    return Some(order);
-                }
-            }
-            Some(left.len().cmp(&right.len()))
-        }
-        _ => None,
-    }
-}
-
-fn promql_function(name: &str, args: &[f64]) -> Result<f64, Error> {
-    let x = args[0];
-    Ok(match &name[7..] {
-        "abs" => x.abs(),
-        "ceil" => x.ceil(),
-        "floor" => x.floor(),
-        "exp" => x.exp(),
-        "ln" => x.ln(),
-        "log2" => x.log2(),
-        "log10" => x.log10(),
-        "sqrt" => x.sqrt(),
-        "sgn" => {
-            if x.is_nan() {
-                f64::NAN
-            } else if x == 0.0 {
-                0.0
-            } else {
-                x.signum()
-            }
-        }
-        "sin" => x.sin(),
-        "cos" => x.cos(),
-        "tan" => x.tan(),
-        "asin" => x.asin(),
-        "acos" => x.acos(),
-        "atan" => x.atan(),
-        "sinh" => x.sinh(),
-        "cosh" => x.cosh(),
-        "tanh" => x.tanh(),
-        "asinh" => x.asinh(),
-        "acosh" => x.acosh(),
-        "atanh" => x.atanh(),
-        "deg" => x.to_degrees(),
-        "rad" => x.to_radians(),
-        "round" => {
-            let inverse = 1.0 / args[1];
-            (x * inverse + 0.5).floor() / inverse
-        }
-        "clamp_min" => {
-            if x.is_nan() || args[1].is_nan() {
-                f64::NAN
-            } else {
-                x.max(args[1])
-            }
-        }
-        "clamp_max" => {
-            if x.is_nan() || args[1].is_nan() {
-                f64::NAN
-            } else {
-                x.min(args[1])
-            }
-        }
-        "clamp" => {
-            if args.iter().any(|x| x.is_nan()) {
-                f64::NAN
-            } else {
-                x.max(args[1]).min(args[2])
-            }
-        }
-        part => {
-            use chrono::{Datelike, Timelike};
-            if !x.is_finite() || x < i64::MIN as f64 || x >= i64::MAX as f64 {
-                return Ok(f64::NAN);
-            }
-            let Some(date) = chrono::DateTime::from_timestamp(x as i64, 0) else {
-                return Ok(f64::NAN);
-            };
-            match part {
-                "minute" => date.minute() as f64,
-                "hour" => date.hour() as f64,
-                "day_of_week" => date.weekday().num_days_from_sunday() as f64,
-                "day_of_month" => date.day() as f64,
-                "day_of_year" => date.ordinal() as f64,
-                "month" => date.month() as f64,
-                "year" => date.year() as f64,
-                "days_in_month" => {
-                    let year = date.year();
-                    let leap = year % 4 == 0 && (year % 100 != 0 || year % 400 == 0);
-                    match date.month() {
-                        2 => {
-                            if leap {
-                                29.0
-                            } else {
-                                28.0
-                            }
-                        }
-                        4 | 6 | 9 | 11 => 30.0,
-                        _ => 31.0,
-                    }
-                }
-                _ => return Err(Error::Invalid("unregistered PromQL function".into())),
-            }
-        }
-    })
-}
-
-#[derive(serde::Serialize, serde::Deserialize, Clone, Debug)]
-pub struct CompiledExpression {
-    expression: ScalarExpr,
-    schema: planner_types::pre_asap::Schema,
-    output: (DataType, bool),
-}
-impl CompiledExpression {
-    pub fn compile(expression: &ScalarExpr, input: &SchemaRef) -> Result<Self, Error> {
-        if !input.is_all_plain() {
-            return Err(Error::Invalid(
-                "scalar expression cannot consume summary state".into(),
-            ));
-        }
-        let schema = input.as_ref().clone();
-        validate(expression, &schema)?;
-        let output = expression
-            .scalar_type(&schema)
-            .map_err(|e| Error::Invalid(e.to_string()))?;
-        Ok(Self {
-            expression: expression.clone(),
-            schema,
-            output,
-        })
-    }
-    pub(crate) fn dtype(&self) -> (DataType, bool) {
-        self.output.clone()
-    }
-    pub(crate) fn validate_input(&self, input: &SchemaRef) -> Result<(), Error> {
-        let checked = Self::compile(&self.expression, input)?;
-        if checked.output != self.output {
-            return Err(Error::Invalid(
-                "persisted expression type differs from its semantics".into(),
-            ));
-        }
-        if input.fields.len() != self.schema.fields.len()
-            || input
-                .fields
-                .iter()
-                .zip(&self.schema.fields)
-                .any(|(field, column)| {
-                    field.dtype != column.dtype.clone() || field.nullable != column.nullable
-                })
-        {
-            return Err(Error::Invalid(
-                "expression input differs from its bound schema".into(),
-            ));
-        }
-        Ok(())
-    }
-    /// Evaluate a row under the same typed schema used when binding the expression.
-    pub fn evaluate(&self, row: &[Value]) -> Result<Value, Error> {
-        if row.len() != self.schema.fields.len()
-            || row.iter().zip(&self.schema.fields).any(|(value, column)| {
-                !column
-                    .plain_dtype()
-                    .is_some_and(|dtype| value.matches(dtype, column.nullable))
-            })
-        {
-            return Err(Error::Invalid(
-                "expression input differs from its bound schema".into(),
-            ));
-        }
-        evaluate(&self.expression, row, &self.schema)
-    }
-}
-fn validate(expr: &ScalarExpr, schema: &planner_types::pre_asap::Schema) -> Result<(), Error> {
-    let invalid = || Error::Invalid(format!("unsupported scalar expression: {expr:?}"));
-    expr.scalar_type(schema)
-        .map_err(|e| Error::Invalid(e.to_string()))?;
-    match expr {
-        ScalarExpr::Column(_) | ScalarExpr::Literal(_) => Ok(()),
-        ScalarExpr::Cast { expr, to, .. } => {
-            let source = expr
-                .scalar_type(schema)
-                .map_err(|e| Error::Invalid(e.to_string()))?
-                .0;
-            if source != *to
-                && source != DataType::Null
-                && !(source == DataType::Int64 && *to == DataType::Float64)
-            {
-                return Err(invalid());
-            }
-            validate(expr, schema)
-        }
-        ScalarExpr::Negative { expr, .. } => validate(expr, schema),
-        ScalarExpr::Arithmetic { left, right, .. } => {
-            for value in [left, right] {
-                validate(value, schema)?;
-                if !matches!(
-                    value
-                        .scalar_type(schema)
-                        .map_err(|e| Error::Invalid(e.to_string()))?
-                        .0,
-                    DataType::Int64 | DataType::Float64 | DataType::Null
-                ) {
-                    return Err(invalid());
-                }
-            }
-            Ok(())
-        }
-        ScalarExpr::Compare {
-            left, right, op, ..
-        } => {
-            if !matches!(
-                op,
-                CompareOpKind::Eq
-                    | CompareOpKind::Ne
-                    | CompareOpKind::Lt
-                    | CompareOpKind::Le
-                    | CompareOpKind::Gt
-                    | CompareOpKind::Ge
-            ) {
-                return Err(invalid());
-            }
-            validate(left, schema)?;
-            validate(right, schema)?;
-            let (a, _) = left
-                .scalar_type(schema)
-                .map_err(|e| Error::Invalid(e.to_string()))?;
-            let (b, _) = right
-                .scalar_type(schema)
-                .map_err(|e| Error::Invalid(e.to_string()))?;
-            fn comparable(dtype: &DataType) -> bool {
-                match dtype {
-                    DataType::Null
-                    | DataType::Int64
-                    | DataType::Float64
-                    | DataType::Utf8
-                    | DataType::Bool
-                    | DataType::Timestamp => true,
-                    DataType::Map { key, value, .. } => comparable(key) && comparable(value),
-                    _ => false,
-                }
-            }
-            let numeric = |dtype: &DataType| matches!(dtype, DataType::Int64 | DataType::Float64);
-            if !comparable(&a)
-                || !comparable(&b)
-                || (a != b
-                    && !matches!(a, DataType::Null)
-                    && !matches!(b, DataType::Null)
-                    && !(numeric(&a) && numeric(&b)))
-            {
-                return Err(invalid());
-            }
-            Ok(())
-        }
-        ScalarExpr::FunctionCall { name, args } => {
-            if name != "promql_drop_metric_name"
-                && planner_types::pre_asap::scalar_type_rules::promql_function_arity(name).is_none()
-                && name != "asap_struct_field"
-                && name != "asap_element_access"
-                && planner_types::pre_asap::scalar_type_rules::MapScalarFunction::from_name(name)
-                    .is_none()
-            {
-                return Err(invalid());
-            }
-            for arg in args {
-                validate(arg, schema)?;
-            }
-            Ok(())
-        }
-        ScalarExpr::Case {
-            operand: None,
-            branches,
-            else_expr,
-        } => {
-            for (condition, value) in branches {
-                validate(condition, schema)?;
-                if condition
-                    .scalar_type(schema)
-                    .map_err(|e| Error::Invalid(e.to_string()))?
-                    .0
-                    != DataType::Bool
-                {
-                    return Err(invalid());
-                }
-                validate(value, schema)?;
-            }
-            if let Some(value) = else_expr {
-                validate(value, schema)?;
-            }
-            Ok(())
-        }
-        ScalarExpr::BoolAnd(parts) | ScalarExpr::BoolOr(parts) => {
-            for part in parts {
-                validate(part, schema)?;
-                if !matches!(
-                    part.scalar_type(schema)
-                        .map_err(|e| Error::Invalid(e.to_string()))?
-                        .0,
-                    DataType::Bool | DataType::Null
-                ) {
-                    return Err(invalid());
-                }
-            }
-            Ok(())
-        }
-        ScalarExpr::Not(value) => {
-            validate(value, schema)?;
-            if !matches!(
-                value
-                    .scalar_type(schema)
-                    .map_err(|e| Error::Invalid(e.to_string()))?
-                    .0,
-                DataType::Bool | DataType::Null
-            ) {
-                return Err(invalid());
-            }
-            Ok(())
-        }
-        ScalarExpr::IsNull(value) | ScalarExpr::IsNotNull(value) => validate(value, schema),
-        _ => Err(invalid()),
-    }
-}
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-    #[test]
-    fn mixed_comparison_preserves_integer_precision_and_boundaries() {
-        assert_eq!(
-            integer_float_cmp(9_007_199_254_740_993, 9_007_199_254_740_992.0),
-            Some(Ordering::Greater)
-        );
-        assert_eq!(
-            integer_float_cmp(i64::MAX, 9_223_372_036_854_775_808.0),
-            Some(Ordering::Less)
-        );
-        assert_eq!(
-            integer_float_cmp(i64::MIN, -9_223_372_036_854_775_808.0),
-            Some(Ordering::Equal)
-        );
-        assert_eq!(integer_float_cmp(-1, -1.5), Some(Ordering::Greater));
-        assert_eq!(integer_float_cmp(1, 1.5), Some(Ordering::Less));
-        assert_eq!(integer_float_cmp(0, f64::INFINITY), Some(Ordering::Less));
-        assert_eq!(
-            integer_float_cmp(0, f64::NEG_INFINITY),
-            Some(Ordering::Greater)
-        );
-        assert_eq!(integer_float_cmp(0, f64::NAN), None);
-    }
-}
diff --git a/crates/asap-physical-operators/src/readout.rs b/crates/asap-physical-operators/src/readout.rs
deleted file mode 100644
index e84d8c828..000000000
--- a/crates/asap-physical-operators/src/readout.rs
+++ /dev/null
@@ -1,111 +0,0 @@
-//! Readouts over merged exact summary states.
-use crate::summary_kernels::exact::ExactAccumulator;
-use crate::{AggregateCore, KeyByLabelValues, Statistic};
-use std::sync::Arc;
-
-fn merge_exact_states(
-    states: impl IntoIterator<Item = Arc<dyn AggregateCore>>,
-) -> Result<ExactAccumulator, String> {
-    let mut states = states.into_iter();
-    let exact = |state: &Arc<dyn AggregateCore>| {
-        state
-            .as_any()
-            .downcast_ref::<ExactAccumulator>()
-            .cloned()
-            .ok_or_else(|| "readout requires Planner exact state".to_string())
-    };
-    let mut merged = exact(&states.next().ok_or("empty exact state input")?)?;
-    for state in states {
-        merged
-            .merge_from(&exact(&state)?)
-            .map_err(|error| error.to_string())?;
-    }
-    Ok(merged)
-}
-
-/// PromQL counter readouts omit a series with fewer than two samples. Other
-/// state/type/range failures remain errors rather than empty results.
-pub fn insufficient_counter_samples(state: &dyn AggregateCore, statistic: Statistic) -> bool {
-    matches!(statistic, Statistic::Rate | Statistic::Increase)
-        && state
-            .as_any()
-            .downcast_ref::<ExactAccumulator>()
-            .is_some_and(|state| state.insufficient_counter_samples(statistic, &None))
-}
-
-/// Merge already selected exact panes and read one population. `None` means
-/// the population is absent from the result: a counter with too few samples,
-/// or an empty MIN/MAX.
-pub fn exact_readout(
-    states: impl IntoIterator<Item = Arc<dyn AggregateCore>>,
-    statistic: Statistic,
-    range_ms: Option<(i64, i64)>,
-    key: Option<&KeyByLabelValues>,
-) -> Result<Option<f64>, String> {
-    let merged = merge_exact_states(states)?;
-    if merged.insufficient_counter_samples(statistic, &key.cloned()) {
-        return Ok(None);
-    }
-    merged
-        .readout(statistic, range_ms, key)
-        .map_err(|error| error.to_string())
-}
-
-#[cfg(test)]
-mod counter_tests {
-    use super::*;
-    use planner_types::post_asap::{ExactKind, ExactParams, FieldDataType};
-
-    fn counter(kind: ExactKind, params: ExactParams, keyed: bool) -> ExactAccumulator {
-        ExactAccumulator::new(FieldDataType::ExactAggregate(kind, params), keyed).unwrap()
-    }
-
-    // A counter population with a single sample is absent, keyed or not.
-    #[test]
-    fn planner_counter_population_omits_insufficient_samples() {
-        for (kind, params, statistic) in [
-            (ExactKind::Rate, ExactParams::Rate, Statistic::Rate),
-            (
-                ExactKind::Increase,
-                ExactParams::Increase,
-                Statistic::Increase,
-            ),
-        ] {
-            for keyed in [false, true] {
-                let mut state = counter(kind.clone(), params.clone(), keyed);
-                let key = keyed.then(|| KeyByLabelValues::new_with_labels(vec!["checkout".into()]));
-                state.update(key.as_ref(), 10., 10_000);
-                assert_eq!(
-                    exact_readout(
-                        [Arc::new(state) as Arc<dyn AggregateCore>],
-                        statistic,
-                        None,
-                        key.as_ref()
-                    )
-                    .unwrap(),
-                    None
-                );
-            }
-        }
-    }
-
-    // Two ordered samples read a rate; an inverted range and empty input fail.
-    #[test]
-    fn sparse_counter_is_absent_but_invalid_ranges_still_fail() {
-        let mut state = counter(ExactKind::Rate, ExactParams::Rate, false);
-        state.update(None, 10., 10_000);
-        let rate = Statistic::Rate;
-        let one = [Arc::new(state.clone()) as Arc<dyn AggregateCore>];
-        assert_eq!(
-            exact_readout(one, rate, Some((0, 60_000)), None).unwrap(),
-            None
-        );
-        state.update(None, 20., 20_000);
-        let two = || [Arc::new(state.clone()) as Arc<dyn AggregateCore>];
-        assert!(exact_readout(two(), rate, Some((0, 60_000)), None)
-            .unwrap()
-            .is_some());
-        assert!(exact_readout(two(), rate, Some((60_000, 0)), None).is_err());
-        assert!(exact_readout([], rate, Some((0, 60_000)), None).is_err());
-    }
-}
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/candidates.rs b/crates/asap-physical-operators/src/unified_physical_planner/candidates.rs
deleted file mode 100644
index 406013eb9..000000000
--- a/crates/asap-physical-operators/src/unified_physical_planner/candidates.rs
+++ /dev/null
@@ -1,329 +0,0 @@
-//! Compile maintenance-selected frontiers without deployment-specific dag rewrites.
-use super::*;
-
-/// One computation realization; lifecycle/window/revision requirements accompany
-/// it during optimization and deployment. Stored outputs have no storage identity.
-/// Deserialization validates the producer/reader boundary.
-#[derive(Clone, serde::Serialize, serde::Deserialize)]
-#[serde(try_from = "UncheckedCompiledPhysicalPlan")]
-pub struct CompiledPhysicalPlan {
-    pub precompute: Option<CompiledPhysicalDAG>,
-    pub query: CompiledPhysicalDAG,
-    pub materialized_outputs: BTreeMap<NodeId, InputContract>,
-}
-
-/// Compile an explicit materialization frontier selected by Planner maintenance
-/// search. Operators upstream of that frontier run in precompute, including
-/// evaluations/reductions; query execution receives their typed output values.
-/// Empty frontiers retain the full computation in the query DAG.
-///
-/// Repeated windows must be instantiated with the same evaluation/population
-/// contract used to build each output. This API never treats a result from a
-/// different window or revision as interchangeable merely because types match.
-pub fn compile_candidate(
-    dag: &PhysicalASAPDAG,
-    inputs: BTreeMap<NodeId, InputContract>,
-    roots: &[NodeId],
-    frontier: &[NodeId],
-) -> Result<CompiledPhysicalPlan, Error> {
-    cut_candidate(&compile(dag, inputs, roots)?, frontier)
-}
-
-/// Derive one frontier's candidate from a complete [`compile`] result by
-/// partitioning its operators; nothing is lowered again. A deployment compiles
-/// each query DAG once and derives every placement choice from that result.
-/// The candidate is identical to [`compile_candidate`] for the same frontier.
-pub fn cut_candidate(
-    compiled: &CompiledPhysicalDAG,
-    frontier: &[NodeId],
-) -> Result<CompiledPhysicalPlan, Error> {
-    if frontier.is_empty() {
-        return Ok(CompiledPhysicalPlan {
-            precompute: None,
-            query: compiled.clone(),
-            materialized_outputs: BTreeMap::new(),
-        });
-    }
-    let frontier_set: BTreeSet<_> = frontier.iter().copied().collect();
-    // `compile` retains only reachable nodes and numbers its helper operators
-    // above the u32 Planner ID range; only Planner outputs are boundaries.
-    if frontier_set.len() != frontier.len()
-        || frontier
-            .iter()
-            .any(|&id| !compiled.is_operator(id) || u32::try_from(id).is_err())
-    {
-        return Err(invalid("frontier must contain distinct computed outputs"));
-    }
-    let inputs: BTreeMap<_, _> = compiled
-        .input_contracts()
-        .map(|(id, contract)| (id, contract.clone()))
-        .collect();
-    let precompute = compiled.cut(&inputs, frontier)?;
-    let mut materialized_outputs = BTreeMap::new();
-    for &id in frontier {
-        let mut output = precompute.output_contract(id)?;
-        if output.properties.boundedness != Boundedness::Bounded {
-            return Err(invalid("materialized output requires bounded execution"));
-        }
-        // A stored reader may stream batches even when the producer blocked.
-        // Its timing is independent; the retained result still must be finite.
-        output.properties.emission = Emission::Unknown;
-        materialized_outputs.insert(id, output);
-    }
-    let mut query_inputs = inputs;
-    query_inputs.extend(materialized_outputs.clone());
-    let query = compiled.cut(&query_inputs, compiled.roots())?;
-    let used: BTreeSet<_> = query.input_contracts().map(|(id, _)| id).collect();
-    if !frontier.iter().all(|id| used.contains(id)) {
-        return Err(invalid(
-            "frontier contains an output shadowed by another boundary",
-        ));
-    }
-    Ok(CompiledPhysicalPlan {
-        precompute: Some(precompute),
-        query,
-        materialized_outputs,
-    })
-}
-
-/// Materialization frontier implied by lifecycle-assigned timing: ingestion-time
-/// nodes read by a query-time node, plus the root when it is ingestion-timed.
-/// `cut_candidate` of one [`compile`] result with this frontier realizes the
-/// assignment, so different assignments are different cuts of one lowering.
-/// That holds while timing-dependent lowering (an ingestion-time `Binary`
-/// aligns by value column) has the same timing at compile time as here.
-/// A query-time node feeding an ingestion-time node has no valid placement.
-pub fn frontier_from_timing(dag: &PhysicalASAPDAG) -> Result<Vec<NodeId>, Error> {
-    use planner_types::post_asap::ExecutionTiming::IngestionTime;
-    let timing = dag
-        .nodes
-        .iter()
-        .map(|node| (node.id, node.output_state.timing))
-        .collect::<BTreeMap<_, _>>();
-    let mut frontier = BTreeSet::new();
-    for root in &dag.roots {
-        if timing.get(root) == Some(&IngestionTime) {
-            frontier.insert(u64::from(root.0));
-        }
-    }
-    for edge in &dag.edges {
-        let (Some(&producer), Some(&consumer)) =
-            (timing.get(&edge.producer), timing.get(&edge.consumer))
-        else {
-            return Err(invalid("timed DAG edge names an unknown node"));
-        };
-        match (producer == IngestionTime, consumer == IngestionTime) {
-            (true, false) => {
-                frontier.insert(u64::from(edge.producer.0));
-            }
-            (false, true) => return Err(invalid("query-time node feeds an ingestion-time node")),
-            _ => {}
-        }
-    }
-    Ok(frontier.into_iter().collect())
-}
-
-/// Enumerate bounded, reachable materialization frontiers above explicit inputs.
-/// Each frontier is an antichain: storing an output and its ancestor together
-/// would leave the ancestor unused by query execution. Lifecycle eligibility
-/// and deployment feasibility are evaluated separately before cost selection.
-/// Exceeding the search budget returns an error, never a partial inventory.
-pub fn enumerate_frontiers(
-    dag: &PhysicalASAPDAG,
-    inputs: &BTreeMap<NodeId, InputContract>,
-    roots: &[NodeId],
-    max_candidates: usize,
-) -> Result<Vec<Vec<NodeId>>, Error> {
-    enumerate_compiled_frontiers(&compile(dag, inputs.clone(), roots)?, max_candidates)
-}
-
-fn enumerate_compiled_frontiers(
-    compiled: &CompiledPhysicalDAG,
-    max_candidates: usize,
-) -> Result<Vec<Vec<NodeId>>, Error> {
-    if max_candidates == 0 {
-        return Err(invalid(
-            "frontier search requires a positive candidate budget",
-        ));
-    }
-    let mut ancestors = BTreeMap::<NodeId, BTreeSet<NodeId>>::new();
-    let mut eligible = Vec::new();
-    for (id, properties) in compiled.output_properties()? {
-        if !compiled.is_operator(id)
-            || u32::try_from(id).is_err()
-            || properties.boundedness != Boundedness::Bounded
-        {
-            continue;
-        }
-        let mut seen = BTreeSet::new();
-        let mut pending = vec![id];
-        while let Some(current) = pending.pop() {
-            if seen.insert(current) {
-                pending.extend(compiled.dependencies(current));
-            }
-        }
-        ancestors.insert(id, seen);
-        eligible.push(id);
-    }
-    let mut frontiers = vec![vec![]];
-    for id in eligible {
-        let additions = frontiers
-            .iter()
-            .filter(|frontier| {
-                frontier.iter().all(|previous| {
-                    !ancestors[&id].contains(previous) && !ancestors[previous].contains(&id)
-                })
-            })
-            .map(|frontier| {
-                let mut next = frontier.clone();
-                next.push(id);
-                next
-            })
-            .collect::<Vec<_>>();
-        if additions.len() > max_candidates.saturating_sub(frontiers.len()) {
-            return Err(invalid(
-                "materialization frontier search exceeds candidate budget",
-            ));
-        }
-        frontiers.extend(additions);
-    }
-    Ok(frontiers)
-}
-
-/// Lower every maintenance candidate before feasibility/cost evaluation. Keep
-/// individual failures visible; do not substitute another computation on error.
-/// The DAG is lowered once; each frontier is a [`cut_candidate`] of it.
-pub fn compile_candidates(
-    dag: &PhysicalASAPDAG,
-    inputs: BTreeMap<NodeId, InputContract>,
-    roots: &[NodeId],
-    frontiers: &[Vec<NodeId>],
-) -> Vec<Result<CompiledPhysicalPlan, Error>> {
-    match compile(dag, inputs, roots) {
-        Ok(compiled) => frontiers
-            .iter()
-            .map(|frontier| cut_candidate(&compiled, frontier))
-            .collect(),
-        Err(error) => frontiers.iter().map(|_| Err(error.clone())).collect(),
-    }
-}
-
-/// Complete workload cost supplied by scoped optimizer/deployment evidence.
-/// The evaluator includes build/update work, retained state, shared producers
-/// and recurrent reads over the same horizon; these are not per-query timings.
-#[derive(Clone, Debug)]
-pub struct CandidateCost {
-    pub workload_scope: String,
-    pub horizon_seconds: f64,
-    pub total_cost: f64,
-}
-
-pub struct CandidateSelection<T = CompiledPhysicalPlan> {
-    pub candidate: T,
-    pub candidate_index: usize,
-    pub cost: CandidateCost,
-}
-
-/// Select only compiled and deployment-feasible physical candidates. `None`
-/// rejects an unbindable candidate before pricing. Comparable scoped costs are
-/// required; deployment never rewrites the selected frontier after this step.
-/// The payload is generic so deployments can retain binding/diagnostic metadata
-/// alongside each compiled computation without duplicating winner selection.
-pub fn select_candidate<T>(
-    candidates: Vec<Result<T, Error>>,
-    mut evaluate: impl FnMut(&T) -> Result<Option<CandidateCost>, Error>,
-) -> Result<CandidateSelection<T>, Error> {
-    let mut scope: Option<(String, f64)> = None;
-    let mut selected: Option<CandidateSelection<T>> = None;
-    for (candidate_index, candidate) in candidates.into_iter().enumerate() {
-        let Ok(candidate) = candidate else { continue };
-        let Some(cost) = evaluate(&candidate)? else {
-            continue;
-        };
-        if cost.workload_scope.is_empty()
-            || !cost.horizon_seconds.is_finite()
-            || cost.horizon_seconds <= 0.
-            || !cost.total_cost.is_finite()
-            || cost.total_cost < 0.
-        {
-            return Err(invalid(
-                "candidate cost lacks a valid workload scope/horizon",
-            ));
-        }
-        let current_scope = (cost.workload_scope.clone(), cost.horizon_seconds);
-        if scope.as_ref().is_some_and(|scope| scope != &current_scope) {
-            return Err(invalid(
-                "candidate costs describe different workloads or horizons",
-            ));
-        }
-        scope = Some(current_scope);
-        if selected
-            .as_ref()
-            .is_none_or(|selected| cost.total_cost < selected.cost.total_cost)
-        {
-            selected = Some(CandidateSelection {
-                candidate,
-                candidate_index,
-                cost,
-            });
-        }
-    }
-    selected.ok_or_else(|| invalid("no feasible priced physical candidate"))
-}
-
-#[derive(serde::Deserialize)]
-#[serde(deny_unknown_fields)]
-struct UncheckedCompiledPhysicalPlan {
-    precompute: Option<CompiledPhysicalDAG>,
-    query: CompiledPhysicalDAG,
-    materialized_outputs: BTreeMap<NodeId, InputContract>,
-}
-impl TryFrom<UncheckedCompiledPhysicalPlan> for CompiledPhysicalPlan {
-    type Error = Error;
-    fn try_from(candidate: UncheckedCompiledPhysicalPlan) -> Result<Self, Error> {
-        let result = Self {
-            precompute: candidate.precompute,
-            query: candidate.query,
-            materialized_outputs: candidate.materialized_outputs,
-        };
-        result.validate()?;
-        Ok(result)
-    }
-}
-
-impl CompiledPhysicalPlan {
-    /// Validate the physical handoff, including the producer/reader boundary.
-    pub fn validate(&self) -> Result<(), Error> {
-        self.query.validate()?;
-        let Some(precompute) = &self.precompute else {
-            return if self.materialized_outputs.is_empty() {
-                Ok(())
-            } else {
-                Err(invalid("materialized outputs have no producer DAG"))
-            };
-        };
-        precompute.validate()?;
-        let outputs: BTreeSet<_> = self.materialized_outputs.keys().copied().collect();
-        if outputs.is_empty() || outputs != precompute.roots().iter().copied().collect() {
-            return Err(invalid("physical frontier differs from precompute outputs"));
-        }
-        let readers: BTreeMap<_, _> = self.query.input_contracts().collect();
-        for (&id, contract) in &self.materialized_outputs {
-            let produced = precompute.output_contract(id)?;
-            // Direct frontiers retain their node IDs. Temporal candidates can
-            // read several window instances through distinct input slots;
-            // their deployment bindings must validate those slots separately.
-            let reader = readers.get(&id);
-            if contract.schema != produced.schema
-                || reader.is_some_and(|reader| contract.schema != reader.schema)
-                || produced.properties.boundedness != Boundedness::Bounded
-                || contract.properties.boundedness != Boundedness::Bounded
-                || reader
-                    .is_some_and(|reader| reader.properties.boundedness != Boundedness::Bounded)
-            {
-                return Err(invalid("physical frontier schema or boundedness mismatch"));
-            }
-        }
-        Ok(())
-    }
-}
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/compiled.rs b/crates/asap-physical-operators/src/unified_physical_planner/compiled.rs
deleted file mode 100644
index 2b9244806..000000000
--- a/crates/asap-physical-operators/src/unified_physical_planner/compiled.rs
+++ /dev/null
@@ -1,352 +0,0 @@
-//! Reader-independent physical computation and checked deployment instantiation.
-use super::*;
-
-/// A typed execution boundary, without storage identity or a live reader.
-#[derive(Clone, Debug, serde::Serialize, serde::Deserialize)]
-pub struct InputContract {
-    pub schema: SchemaRef,
-    pub properties: PlanProperties,
-}
-impl InputContract {
-    pub fn bounded(schema: SchemaRef) -> Self {
-        Self {
-            schema,
-            properties: PlanProperties {
-                boundedness: Boundedness::Bounded,
-                emission: Emission::Unknown,
-            },
-        }
-    }
-    pub fn from_source(source: &dyn PhysicalOperator<Batch, SchemaRef>) -> Self {
-        Self {
-            schema: source.output_schema(),
-            properties: source.properties(&[]),
-        }
-    }
-}
-#[derive(Clone, serde::Serialize, serde::Deserialize)]
-enum Node {
-    Input(InputContract),
-    Operator {
-        inputs: Vec<NodeId>,
-        operator: Operator,
-    },
-}
-
-/// Selected native operators and input slots. Rebinding never repeats lowering.
-/// Serde is format-agnostic; deployments choose the encoding and its versioning.
-/// Deserialization validates the dag before it is usable.
-#[derive(Clone, serde::Serialize, serde::Deserialize)]
-#[serde(try_from = "UncheckedDAG")]
-pub struct CompiledPhysicalDAG {
-    nodes: BTreeMap<NodeId, Node>,
-    roots: Vec<NodeId>,
-}
-#[derive(serde::Deserialize)]
-#[serde(deny_unknown_fields)]
-struct UncheckedDAG {
-    nodes: BTreeMap<NodeId, Node>,
-    roots: Vec<NodeId>,
-}
-impl TryFrom<UncheckedDAG> for CompiledPhysicalDAG {
-    type Error = Error;
-    fn try_from(dag: UncheckedDAG) -> Result<Self, Error> {
-        let result = Self {
-            nodes: dag.nodes,
-            roots: dag.roots,
-        };
-        result.validate()?;
-        Ok(result)
-    }
-}
-
-impl CompiledPhysicalDAG {
-    /// Link already-selected physical fragments without lowering operators again.
-    /// Fragment keys and source keys share a namespace; repeated dependency IDs
-    /// therefore remain one producer in the composed dag.
-    pub fn compose(
-        sources: BTreeMap<NodeId, InputContract>,
-        fragments: BTreeMap<NodeId, (Vec<NodeId>, Self)>,
-        roots: Vec<NodeId>,
-    ) -> Result<Self, Error> {
-        if sources.keys().any(|id| fragments.contains_key(id)) {
-            return Err(invalid("physical source and fragment IDs overlap"));
-        }
-        let mut contracts = sources.clone();
-        for (&id, (_, fragment)) in &fragments {
-            fragment.validate()?;
-            let [root] = fragment.roots() else {
-                return Err(invalid("composed fragment requires one root"));
-            };
-            if fragment.input_contracts().any(|(id, _)| id == *root) {
-                return Err(invalid("fragment root must be a computed output"));
-            }
-            contracts.insert(id, fragment.output_contract(*root)?);
-        }
-        let mut next = contracts
-            .keys()
-            .next_back()
-            .copied()
-            .unwrap_or(0)
-            .checked_add(1)
-            .ok_or_else(|| invalid("physical node ID overflow"))?;
-        let mut result = Self::new(roots);
-        for (id, contract) in sources {
-            result.add_input(id, contract)?;
-        }
-        for (id, (inputs, fragment)) in fragments {
-            if inputs.len() != fragment.input_contracts().count() {
-                return Err(invalid("physical fragment input arity mismatch"));
-            }
-            let mut mapping = BTreeMap::new();
-            for ((local, expected), global) in fragment.input_contracts().zip(inputs) {
-                let actual = contracts
-                    .get(&global)
-                    .ok_or_else(|| invalid("missing physical fragment dependency"))?;
-                if expected.schema != actual.schema
-                    || (expected.properties.boundedness == Boundedness::Bounded
-                        && actual.properties.boundedness != Boundedness::Bounded)
-                {
-                    return Err(invalid("physical fragment dependency contract mismatch"));
-                }
-                mapping.insert(local, global);
-            }
-            mapping.insert(fragment.roots[0], id);
-            for local in fragment.nodes.keys() {
-                if !mapping.contains_key(local) {
-                    mapping.insert(*local, next);
-                    next = next
-                        .checked_add(1)
-                        .ok_or_else(|| invalid("physical node ID overflow"))?;
-                }
-            }
-            for (local, node) in fragment.nodes {
-                if let Node::Operator { inputs, operator } = node {
-                    result.add(
-                        mapping[&local],
-                        inputs.into_iter().map(|input| mapping[&input]).collect(),
-                        operator,
-                    )?;
-                }
-            }
-        }
-        result.validate()?;
-        Ok(result)
-    }
-
-    /// Assemble already-lowered operators and typed external inputs. This is
-    /// useful for engines that compose multiple compiled computation fragments.
-    pub fn from_operators(
-        inputs: BTreeMap<NodeId, InputContract>,
-        operators: BTreeMap<NodeId, (Vec<NodeId>, Operator)>,
-        roots: Vec<NodeId>,
-    ) -> Result<Self, Error> {
-        let mut result = Self::new(roots);
-        for (id, contract) in inputs {
-            result.add_input(id, contract)?;
-        }
-        for (id, (inputs, operator)) in operators {
-            result.add(id, inputs, operator)?;
-        }
-        result.validate()?;
-        Ok(result)
-    }
-    pub(super) fn new(roots: Vec<NodeId>) -> Self {
-        Self {
-            nodes: BTreeMap::new(),
-            roots,
-        }
-    }
-    pub(super) fn add_input(&mut self, id: NodeId, contract: InputContract) -> Result<(), Error> {
-        self.insert(id, Node::Input(contract))
-    }
-    pub(super) fn add(
-        &mut self,
-        id: NodeId,
-        inputs: Vec<NodeId>,
-        operator: Operator,
-    ) -> Result<(), Error> {
-        self.insert(id, Node::Operator { inputs, operator })
-    }
-    fn insert(&mut self, id: NodeId, node: Node) -> Result<(), Error> {
-        if self.nodes.insert(id, node).is_some() {
-            return Err(invalid(format!("duplicate physical node {id}")));
-        }
-        Ok(())
-    }
-    /// Identify the external input whose rows survive unchanged at this output.
-    /// Protocol adapters can retain labels that are outside a closed physical schema.
-    pub fn row_source(&self, id: NodeId) -> Option<NodeId> {
-        match self.nodes.get(&id)? {
-            Node::Input(_) => Some(id),
-            Node::Operator { inputs, operator } => {
-                let index = operator.row_preserving_input()?;
-                self.row_source(*inputs.get(index)?)
-            }
-        }
-    }
-
-    /// Selected operator name, for plan inspection without decoding its wire format.
-    /// Certified candidate pruning checks authoritative-key coverage inside this operator.
-    pub fn certified_pruning_keys(&self, id: NodeId) -> Option<&[(usize, usize)]> {
-        match self.nodes.get(&id)? {
-            Node::Operator { operator, .. } => operator.certified_pruning_keys(),
-            Node::Input(_) => None,
-        }
-    }
-    pub fn operator_name(&self, id: NodeId) -> Option<&str> {
-        match self.nodes.get(&id)? {
-            Node::Input(_) => Some("Input"),
-            Node::Operator { operator, .. } => Some(operator.name()),
-        }
-    }
-
-    pub fn roots(&self) -> &[NodeId] {
-        &self.roots
-    }
-    pub fn input_contracts(&self) -> impl Iterator<Item = (NodeId, &InputContract)> {
-        self.nodes.iter().filter_map(|(&id, node)| match node {
-            Node::Input(contract) => Some((id, contract)),
-            Node::Operator { .. } => None,
-        })
-    }
-    /// Derive a reachable output contract without opening deployment readers.
-    pub fn output_contract(&self, id: NodeId) -> Result<InputContract, Error> {
-        let properties = *self
-            .output_properties()?
-            .get(&id)
-            .ok_or_else(|| invalid("output is not reachable"))?;
-        let schema = match self
-            .nodes
-            .get(&id)
-            .ok_or_else(|| invalid("missing output"))?
-        {
-            Node::Input(contract) => contract.schema.clone(),
-            Node::Operator { operator, .. } => operator.output_schema(),
-        };
-        Ok(InputContract { schema, properties })
-    }
-    /// Properties of every reachable node, derived in one contract-only pass.
-    pub(super) fn output_properties(&self) -> Result<BTreeMap<NodeId, PlanProperties>, Error> {
-        let sources = self
-            .input_contracts()
-            .map(|(id, contract)| (id, Box::new(contract.clone()) as Source<'_>))
-            .collect();
-        self.instantiate(sources)?.properties(&self.roots)
-    }
-    /// Direct physical dependencies; empty for inputs and unknown IDs.
-    pub(super) fn dependencies(&self, id: NodeId) -> &[NodeId] {
-        match self.nodes.get(&id) {
-            Some(Node::Operator { inputs, .. }) => inputs,
-            _ => &[],
-        }
-    }
-    pub(super) fn is_operator(&self, id: NodeId) -> bool {
-        matches!(self.nodes.get(&id), Some(Node::Operator { .. }))
-    }
-    /// Keep the already-lowered operators reachable from `roots`, replacing
-    /// each node in `boundaries` by a typed input. Nothing is lowered again.
-    pub(super) fn cut(
-        &self,
-        boundaries: &BTreeMap<NodeId, InputContract>,
-        roots: &[NodeId],
-    ) -> Result<Self, Error> {
-        let mut result = Self::new(roots.to_vec());
-        let mut pending = roots.to_vec();
-        while let Some(id) = pending.pop() {
-            if result.nodes.contains_key(&id) {
-                continue;
-            }
-            let node = match boundaries.get(&id) {
-                Some(contract) => Node::Input(contract.clone()),
-                None => self
-                    .nodes
-                    .get(&id)
-                    .cloned()
-                    .ok_or_else(|| invalid(format!("missing physical node {id}")))?,
-            };
-            if let Node::Operator { inputs, .. } = &node {
-                pending.extend(inputs);
-            }
-            result.nodes.insert(id, node);
-        }
-        result.validate()?;
-        Ok(result)
-    }
-    /// Validate using contract-only sources. No deployment reader is available.
-    pub fn validate(&self) -> Result<(), Error> {
-        let sources = self
-            .input_contracts()
-            .map(|(id, c)| (id, Box::new(c.clone()) as Source<'_>))
-            .collect();
-        self.instantiate(sources).map(|_| ())
-    }
-    /// Resolve exactly the declared inputs and validate before any source starts.
-    pub fn instantiate<'a>(
-        &self,
-        mut sources: BTreeMap<NodeId, Source<'a>>,
-    ) -> Result<PhysicalDAG<'a, Batch, SchemaRef>, Error> {
-        let mut dag = PhysicalDAG::default();
-        for (&id, node) in &self.nodes {
-            match node {
-                Node::Input(contract) => {
-                    let source = sources
-                        .remove(&id)
-                        .ok_or_else(|| invalid(format!("missing physical input {id}")))?;
-                    let actual = source.properties(&[]);
-                    if !source.input_schemas().is_empty()
-                        || source.output_schema() != contract.schema
-                        || (contract.properties.boundedness != Boundedness::Unknown
-                            && actual.boundedness != contract.properties.boundedness)
-                        || (contract.properties.emission != Emission::Unknown
-                            && actual.emission != contract.properties.emission)
-                    {
-                        return Err(invalid(format!(
-                            "physical input {id} violates its compiled contract"
-                        )));
-                    }
-                    dag.add_boxed(
-                        id,
-                        vec![],
-                        Box::new(CheckedSource {
-                            source,
-                            output: contract.schema.clone(),
-                        }),
-                    )?;
-                }
-                Node::Operator { inputs, operator } => {
-                    dag.add(id, inputs.clone(), operator.clone())?;
-                }
-            }
-        }
-        if !sources.is_empty() {
-            return Err(invalid("unexpected physical input binding"));
-        }
-        dag.validate(&self.roots)?;
-        Ok(dag)
-    }
-}
-impl PhysicalOperator<Batch, SchemaRef> for InputContract {
-    fn name(&self) -> &str {
-        "UnresolvedInput"
-    }
-    fn input_schemas(&self) -> Vec<SchemaRef> {
-        vec![]
-    }
-    fn output_schema(&self) -> SchemaRef {
-        self.schema.clone()
-    }
-    fn properties(&self, _: &[PlanProperties]) -> PlanProperties {
-        self.properties
-    }
-    fn output_bytes(&self, batch: &Batch) -> usize {
-        batch.bytes()
-    }
-    fn start<'a>(
-        &'a self,
-        _: Vec<crate::runtime::Input<'a, Batch>>,
-        _: crate::runtime::RunContext,
-    ) -> Result<crate::runtime::OutputStream<'a, Batch>, Error> {
-        Err(invalid("physical input must be resolved before execution"))
-    }
-}
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/logical.rs b/crates/asap-physical-operators/src/unified_physical_planner/logical.rs
deleted file mode 100644
index dbc541895..000000000
--- a/crates/asap-physical-operators/src/unified_physical_planner/logical.rs
+++ /dev/null
@@ -1,374 +0,0 @@
-//! Reconstruct shared operator references from the transport DAG for native lowering.
-use super::*;
-use planner_types::ir::export::{EdgeRole, NonASAPOpKind as N, PhysicalASAPNodeId, WireScalarExpr};
-use planner_types::ir::{
-    ASAPOp, NonASAPOp, Operator as LogicalOperator, OperatorNode, Predicate, ProjectItem,
-    ScalarExpr, SortKey as LogicalSortKey,
-};
-use std::rc::Rc;
-pub(super) fn scalar(
-    expr: &WireScalarExpr,
-    id_of: &mut impl FnMut(PhysicalASAPNodeId) -> Rc<OperatorNode>,
-) -> ScalarExpr {
-    fn boxed(
-        e: &WireScalarExpr,
-        id_of: &mut impl FnMut(PhysicalASAPNodeId) -> Rc<OperatorNode>,
-    ) -> Box<ScalarExpr> {
-        Box::new(scalar(e, id_of))
-    }
-    fn list(
-        es: &[WireScalarExpr],
-        id_of: &mut impl FnMut(PhysicalASAPNodeId) -> Rc<OperatorNode>,
-    ) -> Vec<ScalarExpr> {
-        es.iter().map(|e| scalar(e, id_of)).collect()
-    }
-    match expr {
-        WireScalarExpr::Column(id) => ScalarExpr::Column(*id),
-        WireScalarExpr::Literal(v) => ScalarExpr::Literal(v.clone()),
-        WireScalarExpr::Negative { expr, semantics } => ScalarExpr::Negative {
-            expr: boxed(expr, id_of),
-            semantics: *semantics,
-        },
-        WireScalarExpr::Compare {
-            left,
-            op,
-            right,
-            semantics,
-        } => ScalarExpr::Compare {
-            left: boxed(left, id_of),
-            op: op.clone(),
-            right: boxed(right, id_of),
-            semantics: *semantics,
-        },
-        WireScalarExpr::BoolAnd(parts) => ScalarExpr::BoolAnd(list(parts, id_of)),
-        WireScalarExpr::BoolOr(parts) => ScalarExpr::BoolOr(list(parts, id_of)),
-        WireScalarExpr::Not(e) => ScalarExpr::Not(boxed(e, id_of)),
-        WireScalarExpr::IsNull(e) => ScalarExpr::IsNull(boxed(e, id_of)),
-        WireScalarExpr::IsNotNull(e) => ScalarExpr::IsNotNull(boxed(e, id_of)),
-        WireScalarExpr::Cast { expr, to, try_cast } => ScalarExpr::Cast {
-            expr: boxed(expr, id_of),
-            to: to.clone(),
-            try_cast: *try_cast,
-        },
-        WireScalarExpr::InList {
-            expr,
-            list: items,
-            negated,
-        } => ScalarExpr::InList {
-            expr: boxed(expr, id_of),
-            list: list(items, id_of),
-            negated: *negated,
-        },
-        WireScalarExpr::FunctionCall { name, args } => ScalarExpr::FunctionCall {
-            name: name.clone(),
-            args: list(args, id_of),
-        },
-        WireScalarExpr::Arithmetic {
-            op,
-            left,
-            right,
-            semantics,
-        } => ScalarExpr::Arithmetic {
-            op: op.clone(),
-            left: boxed(left, id_of),
-            right: boxed(right, id_of),
-            semantics: *semantics,
-        },
-        WireScalarExpr::Case {
-            operand,
-            branches,
-            else_expr,
-        } => ScalarExpr::Case {
-            operand: operand.as_ref().map(|e| boxed(e, id_of)),
-            branches: branches
-                .iter()
-                .map(|(w, t)| (scalar(w, id_of), scalar(t, id_of)))
-                .collect(),
-            else_expr: else_expr.as_ref().map(|e| boxed(e, id_of)),
-        },
-        WireScalarExpr::CurrentTimestamp => ScalarExpr::CurrentTimestamp,
-        WireScalarExpr::EvalTimestamp => ScalarExpr::EvalTimestamp,
-        WireScalarExpr::PromqlScalarFromVector(node) => {
-            ScalarExpr::PromqlScalarFromVector(id_of(*node))
-        }
-        WireScalarExpr::ScalarSubquery(node) => ScalarExpr::ScalarSubquery(id_of(*node)),
-        WireScalarExpr::Exists { subquery, negated } => ScalarExpr::Exists {
-            subquery: id_of(*subquery),
-            negated: *negated,
-        },
-        WireScalarExpr::InSubquery {
-            expr,
-            subquery,
-            negated,
-        } => ScalarExpr::InSubquery {
-            expr: boxed(expr, id_of),
-            subquery: id_of(*subquery),
-            negated: *negated,
-        },
-    }
-}
-
-pub(super) fn restore(dag: &PhysicalASAPDAG) -> Result<BTreeMap<NodeId, Rc<OperatorNode>>, Error> {
-    dag.validate().map_err(|e| invalid(e.to_string()))?;
-    let mut done = BTreeMap::new();
-    let mut remaining: Vec<_> = dag.nodes.iter().collect();
-    while !remaining.is_empty() {
-        let before = remaining.len();
-        let mut next = Vec::new();
-        for node in remaining {
-            let mut edges: Vec<_> = dag.edges.iter().filter(|e| e.consumer == node.id).collect();
-            if edges
-                .iter()
-                .any(|e| !done.contains_key(&u64::from(e.producer.0)))
-            {
-                next.push(node);
-                continue;
-            }
-            edges.sort_by_key(|e| match e.role {
-                EdgeRole::Left => 0,
-                EdgeRole::Input => 1,
-                EdgeRole::Right => 2,
-                EdgeRole::ScalarRef => 3,
-            });
-            let inputs: Vec<_> = edges
-                .iter()
-                .filter(|e| e.role != EdgeRole::ScalarRef)
-                .map(|e| Rc::clone(&done[&u64::from(e.producer.0)]))
-                .collect();
-            let input = |index: usize| {
-                inputs
-                    .get(index)
-                    .cloned()
-                    .ok_or_else(|| invalid("operator is missing an input"))
-            };
-            let mut missing = false;
-            let mut ref_node = |id: PhysicalASAPNodeId| {
-                if let Some(node) = done.get(&u64::from(id.0)) {
-                    Rc::clone(node)
-                } else {
-                    missing = true;
-                    Rc::new(OperatorNode::with_schema(
-                        LogicalOperator::NonASAP(NonASAPOp::Values {
-                            rows: vec![],
-                            schema: Default::default(),
-                        }),
-                        Default::default(),
-                    ))
-                }
-            };
-            let mut value = |expr: &WireScalarExpr| scalar(expr, &mut ref_node);
-            let operator = match &node.payload {
-                Payload::Relational { operator } => LogicalOperator::NonASAP(match operator {
-                    N::Scan {
-                        source,
-                        predicates,
-                        schema,
-                    } => NonASAPOp::Scan {
-                        source: source.clone(),
-                        predicates: predicates.iter().map(|p| Predicate(value(&p.0))).collect(),
-                        schema: schema.clone(),
-                    },
-                    N::Values { rows, schema } => NonASAPOp::Values {
-                        rows: rows
-                            .iter()
-                            .map(|r| r.iter().map(&mut value).collect())
-                            .collect(),
-                        schema: schema.clone(),
-                    },
-                    N::Filter { pred } => NonASAPOp::Filter {
-                        pred: Predicate(value(&pred.0)),
-                        child: input(0)?,
-                    },
-                    N::Project { cols, qualifier } => NonASAPOp::Project {
-                        cols: cols
-                            .iter()
-                            .map(|c| ProjectItem {
-                                alias: c.alias.clone(),
-                                expr: value(&c.expr),
-                            })
-                            .collect(),
-                        qualifier: qualifier.clone(),
-                        child: input(0)?,
-                    },
-                    N::Aggregate {
-                        reduction,
-                        measures,
-                        output_names,
-                        filters,
-                        having,
-                    } => NonASAPOp::Aggregate {
-                        reduction: reduction.clone(),
-                        measures: measures.clone(),
-                        output_names: output_names.clone(),
-                        filters: filters
-                            .iter()
-                            .map(|p| p.as_ref().map(|p| Predicate(value(&p.0))))
-                            .collect(),
-                        having: having.as_ref().map(|p| Predicate(value(&p.0))),
-                        child: input(0)?,
-                    },
-                    N::Join { join_kind, pred } => NonASAPOp::Join {
-                        kind: join_kind.clone(),
-                        pred: Predicate(value(&pred.0)),
-                        left: input(0)?,
-                        right: input(1)?,
-                    },
-                    N::SetOp { set_kind, all } => NonASAPOp::SetOp {
-                        kind: set_kind.clone(),
-                        all: *all,
-                        left: input(0)?,
-                        right: input(1)?,
-                    },
-                    N::Concat {
-                        discriminator_unique_key,
-                    } => NonASAPOp::Concat {
-                        children: inputs.clone(),
-                        discriminator_unique_key: discriminator_unique_key.clone(),
-                    },
-                    N::Dedup { cols } => NonASAPOp::Dedup {
-                        cols: cols.clone(),
-                        child: input(0)?,
-                    },
-                    N::Sort { keys, partition_by } => NonASAPOp::Sort {
-                        keys: keys
-                            .iter()
-                            .map(|k| LogicalSortKey {
-                                expr: value(&k.expr),
-                                ascending: k.ascending,
-                                nulls_first: k.nulls_first,
-                            })
-                            .collect(),
-                        partition_by: partition_by.clone(),
-                        child: input(0)?,
-                    },
-                    N::Limit {
-                        n,
-                        offset,
-                        partition_by,
-                    } => NonASAPOp::Limit {
-                        n: *n,
-                        offset: *offset,
-                        partition_by: partition_by.clone(),
-                        child: input(0)?,
-                    },
-                    N::BinaryOp {
-                        operator,
-                        return_bool,
-                    } => NonASAPOp::BinaryOp {
-                        operator: operator.clone(),
-                        return_bool: *return_bool,
-                        lhs: input(0)?,
-                        rhs: input(1)?,
-                    },
-                    N::SQLWindowFunc {
-                        func,
-                        args,
-                        partition_by,
-                        order_by,
-                        frame,
-                        output_name,
-                    } => NonASAPOp::SQLWindowFunc {
-                        func: func.clone(),
-                        args: args.iter().map(&mut value).collect(),
-                        partition_by: partition_by.clone(),
-                        order_by: order_by
-                            .iter()
-                            .map(|k| LogicalSortKey {
-                                expr: value(&k.expr),
-                                ascending: k.ascending,
-                                nulls_first: k.nulls_first,
-                            })
-                            .collect(),
-                        frame: frame.clone(),
-                        output_name: output_name.clone(),
-                        child: input(0)?,
-                    },
-                    N::TimeRange { range, range_kind } => NonASAPOp::TimeRange {
-                        range: *range,
-                        kind: *range_kind,
-                        child: input(0)?,
-                    },
-                    N::TimeShift { shift } => NonASAPOp::TimeShift {
-                        shift: *shift,
-                        child: input(0)?,
-                    },
-                    N::PromqlVectorFromScalar { expr } => {
-                        NonASAPOp::PromqlVectorFromScalar(value(expr))
-                    }
-                    N::PromqlRelabel { dst, value: expr } => NonASAPOp::PromqlRelabel {
-                        dst: dst.clone(),
-                        value: value(expr),
-                        child: input(0)?,
-                    },
-                    N::PromqlInfoEnrich { selector } => NonASAPOp::PromqlInfoEnrich {
-                        selector: selector.clone(),
-                        child: input(0)?,
-                    },
-                    N::PromqlSeriesSample { by, sample_kind } => NonASAPOp::PromqlSeriesSample {
-                        by: by.clone(),
-                        kind: *sample_kind,
-                        child: input(0)?,
-                    },
-                    N::PromqlSubquery { range, resolution } => NonASAPOp::PromqlSubquery {
-                        range: *range,
-                        resolution: *resolution,
-                        child: input(0)?,
-                    },
-                }),
-                Payload::SummaryAgg {
-                    family,
-                    input: update,
-                    reduction,
-                    grouping,
-                    filter,
-                } => LogicalOperator::ASAP(ASAPOp::SummaryAgg {
-                    child: input(0)?,
-                    family: family.clone(),
-                    input: update.clone(),
-                    reduction: reduction.clone(),
-                    grouping: grouping.clone(),
-                    filter: filter.as_ref().map(|p| Predicate(value(&p.0))),
-                }),
-                Payload::SummaryEstimate { query } => {
-                    LogicalOperator::ASAP(ASAPOp::SummaryEstimate {
-                        summary_input: input(0)?,
-                        query: query.clone(),
-                    })
-                }
-                Payload::FinalizeExactAccumulator => {
-                    LogicalOperator::ASAP(ASAPOp::FinalizeExactAccumulator { child: input(0)? })
-                }
-                Payload::MaintainPopulation { population } => {
-                    LogicalOperator::ASAP(ASAPOp::MaintainPopulation {
-                        child: input(0)?,
-                        population: population.clone(),
-                    })
-                }
-                Payload::EvaluatePopulation { evaluation } => {
-                    LogicalOperator::ASAP(ASAPOp::EvaluatePopulation {
-                        child: input(0)?,
-                        evaluation: evaluation.clone(),
-                    })
-                }
-                Payload::SummaryMerge => LogicalOperator::ASAP(ASAPOp::SummaryMerge {
-                    children: inputs.clone(),
-                }),
-                _ => return Err(invalid("reserved ASAP operation has no native lowering")),
-            };
-            if missing {
-                return Err(invalid(
-                    "scalar reference is not a preceding DAG dependency",
-                ));
-            }
-            let mut rebuilt = OperatorNode::with_schema(operator, node.output_schema.clone());
-            rebuilt.guarantee = node.guarantee.clone();
-            rebuilt.timing = Some(node.output_state.timing);
-            done.insert(u64::from(node.id.0), Rc::new(rebuilt));
-        }
-        if next.len() == before {
-            return Err(invalid("operator DAG is cyclic"));
-        }
-        remaining = next;
-    }
-    Ok(done)
-}
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/mod.rs b/crates/asap-physical-operators/src/unified_physical_planner/mod.rs
deleted file mode 100644
index 8d680fcc9..000000000
--- a/crates/asap-physical-operators/src/unified_physical_planner/mod.rs
+++ /dev/null
@@ -1,1169 +0,0 @@
-//! Compile logical computation to native operators with typed external inputs.
-//! Compilation needs no readers; deployment resolves inputs after selection.
-use crate::operators::ReadoutQuery;
-use crate::summary_kernels::exact::ExactReadout;
-use crate::{
-    operators::{Expression, Operator, Reduction, SortKey},
-    plan::{Boundedness, Emission, NodeId, PhysicalDAG, PhysicalOperator, PlanProperties},
-    values::{Batch, SchemaRef},
-    Error,
-};
-use planner_types::ir::export::{
-    NonASAPOpKind, PhysicalASAPDAG, PhysicalASAPDAGNode, PhysicalASAPOperatorPayload as Payload,
-    WireScalarExpr,
-};
-use planner_types::ir::{ASAPOp, NonASAPOp, Operator as LogicalOperator, OperatorNode, ScalarExpr};
-use planner_types::{
-    post_asap::{FieldDataType, SketchStatistic, SummaryInputExpr},
-    pre_asap::{
-        AggIntent, ColumnRef, CompareOpKind, DataType, GroupKeys, Reduction as PlannerReduction,
-    },
-};
-mod logical;
-use std::{
-    collections::{BTreeMap, BTreeSet},
-    sync::Arc,
-};
-fn invalid(message: impl Into<String>) -> Error {
-    Error::Invalid(message.into())
-}
-
-/// Source nodes cut the DAG at an installed storage/ingestion frontier. The
-/// binding must have exactly the declared schema and no upstream dependencies.
-/// A deployment must authorize these frontiers before calling this function.
-pub type Source<'a> = Box<dyn PhysicalOperator<Batch, SchemaRef> + 'a>;
-
-pub mod precompute;
-pub mod promql_fallback;
-pub mod promql_rows;
-pub mod promql_values;
-
-mod candidates;
-pub use candidates::{
-    compile_candidate, compile_candidates, cut_candidate, enumerate_frontiers,
-    frontier_from_timing, select_candidate, CandidateCost, CandidateSelection,
-    CompiledPhysicalPlan,
-};
-
-mod compiled;
-pub use compiled::{CompiledPhysicalDAG, InputContract};
-
-mod row_values;
-
-/// Compile computation without opening or retaining deployment readers.
-/// Input contracts identify explicit boundaries selected by maintenance planning.
-pub fn compile(
-    dag: &PhysicalASAPDAG,
-    inputs: BTreeMap<NodeId, InputContract>,
-    roots: &[NodeId],
-) -> Result<CompiledPhysicalDAG, Error> {
-    compile_internal(dag, inputs, roots)
-}
-
-/// Convenience for callers that already resolved inputs. Lowering still uses
-/// only their contracts, and instantiation checks those contracts again.
-pub fn bind<'a>(
-    dag: &PhysicalASAPDAG,
-    sources: BTreeMap<NodeId, Source<'a>>,
-    roots: &[NodeId],
-) -> Result<PhysicalDAG<'a, Batch, SchemaRef>, Error> {
-    let inputs = sources
-        .iter()
-        .map(|(&id, source)| (id, InputContract::from_source(source.as_ref())))
-        .collect();
-    compile(dag, inputs, roots)?.instantiate(sources)
-}
-
-/// Resolve raw scan connectors before invoking the reader-independent compiler.
-pub fn bind_with_data_sources<'a>(
-    dag: &PhysicalASAPDAG,
-    mut sources: BTreeMap<NodeId, Source<'a>>,
-    roots: &[NodeId],
-    data_sources: &crate::unified_sources::DataSources,
-) -> Result<PhysicalDAG<'a, Batch, SchemaRef>, Error> {
-    let restored = logical::restore(dag)?;
-    // Only resolve scans reachable below the selected input boundaries.
-    let mut pending = roots.to_vec();
-    let mut seen = BTreeSet::new();
-    while let Some(id) = pending.pop() {
-        if !seen.insert(id) || sources.contains_key(&id) {
-            continue;
-        }
-        let _node = dag
-            .nodes
-            .iter()
-            .find(|n| u64::from(n.id.0) == id)
-            .ok_or_else(|| invalid(format!("missing node {id}")))?;
-        if matches!(restored[&id].non_asap(), Some(NonASAPOp::Scan { .. })) {
-            sources.insert(id, Box::new(data_sources.bind(&restored[&id])?));
-        } else {
-            pending.extend(
-                dag.edges
-                    .iter()
-                    .filter(|e| u64::from(e.consumer.0) == id)
-                    .map(|e| u64::from(e.producer.0)),
-            );
-        }
-    }
-    bind(dag, sources, roots)
-}
-
-#[cfg(test)]
-thread_local! {
-    /// Planner nodes lowered by this thread, for compile-once tests.
-    static LOWERED_NODES: std::cell::Cell<usize> = const { std::cell::Cell::new(0) };
-}
-
-/// Helper operators are numbered from their Planner node alone, above the u32
-/// Planner ID range, so every boundary choice yields a subgraph of the same
-/// lowering and candidate cuts need not renumber operators. A node lowering to
-/// several helpers takes consecutive indices below its base.
-fn helper_id(node: NodeId, index: u64) -> NodeId {
-    debug_assert!(node <= u64::from(u32::MAX) && index < 1 << 16);
-    u64::MAX - (node << 16) - index
-}
-
-fn compile_internal(
-    dag: &PhysicalASAPDAG,
-    mut sources: BTreeMap<NodeId, InputContract>,
-    roots: &[NodeId],
-) -> Result<CompiledPhysicalDAG, Error> {
-    preflight_depth(dag)?;
-    let restored = logical::restore(dag)?;
-    dag.validate().map_err(|e| invalid(e.to_string()))?;
-    let nodes = dag
-        .nodes
-        .iter()
-        .map(|node| (u64::from(node.id.0), node))
-        .collect::<BTreeMap<_, _>>();
-    let mut dependencies = BTreeMap::<NodeId, Vec<NodeId>>::new();
-    // Binary input order is semantic; serialized edge order is not.
-    let mut edges = dag.edges.iter().collect::<Vec<_>>();
-    edges.sort_by_key(|edge| {
-        (
-            edge.consumer.0,
-            match edge.role {
-                planner_types::ir::export::EdgeRole::Left => 0,
-                planner_types::ir::export::EdgeRole::Input => 1,
-                planner_types::ir::export::EdgeRole::Right => 2,
-                planner_types::ir::export::EdgeRole::ScalarRef => 3,
-            },
-        )
-    });
-    let literals = BTreeMap::<NodeId, (f64, bool)>::new();
-    for edge in edges {
-        dependencies
-            .entry(u64::from(edge.consumer.0))
-            .or_default()
-            .push(u64::from(edge.producer.0));
-    }
-    let mut fallback = BTreeMap::new();
-    for (&id, root) in &restored {
-        let raw_summary_input = matches!(root.non_asap(), Some(NonASAPOp::TimeRange { .. }))
-            && dag.edges.iter().any(|e| {
-                u64::from(e.producer.0) == id
-                    && matches!(
-                        nodes[&u64::from(e.consumer.0)].payload,
-                        Payload::SummaryAgg { .. }
-                    )
-            });
-        if !root.contains_asap() && !raw_summary_input {
-            if let Ok(lowered) = promql_fallback::lower(root) {
-                fallback.insert(id, lowered);
-            }
-        }
-    }
-    let known = |id: &NodeId| {
-        nodes.contains_key(id)
-            || promql_fallback::raw_series_owner(*id).is_some_and(|owner| {
-                matches!(
-                    nodes.get(&owner),
-                    Some(PhysicalASAPDAGNode {
-                        payload: Payload::Relational { .. },
-                        ..
-                    })
-                )
-            })
-    };
-    if !sources.keys().all(known) {
-        return Err(invalid("source binding names an unknown node"));
-    }
-    let mut ordered = Vec::new();
-    let mut seen = BTreeSet::new();
-    let mut pending = roots.iter().map(|&id| (id, false)).collect::<Vec<_>>();
-    while let Some((id, expanded)) = pending.pop() {
-        if expanded {
-            ordered.push(id);
-            continue;
-        }
-        if !seen.insert(id) {
-            continue;
-        }
-        if !nodes.contains_key(&id) {
-            return Err(invalid(format!("missing root {id}")));
-        }
-        pending.push((id, true));
-        if !sources.contains_key(&id) && !fallback.contains_key(&id) {
-            for &input in dependencies.get(&id).into_iter().flatten() {
-                pending.push((input, false));
-            }
-        }
-    }
-    let mut dag = CompiledPhysicalDAG::new(roots.to_vec());
-    for id in ordered {
-        let node = nodes[&id];
-        let mut auxiliary = helper_id(id, 0);
-        let output = Arc::new(node.output_schema.clone());
-        crate::values::validate_schema(&output)?;
-        if let Some(source) = sources.remove(&id) {
-            if source.schema != output {
-                return Err(invalid("frontier does not have the declared schema"));
-            }
-            dag.add_input(id, source)?;
-        } else {
-            #[cfg(test)]
-            LOWERED_NODES.with(|count| count.set(count.get() + 1));
-            let mut inputs = dependencies.get(&id).cloned().unwrap_or_default();
-            let mut schemas = inputs
-                .iter()
-                .map(|id| Arc::new(nodes[id].output_schema.clone()))
-                .collect::<Vec<_>>();
-            if matches!(node.payload, Payload::SummaryMerge) && inputs.len() > 1 {
-                if schemas.iter().any(|s| s != &schemas[0]) {
-                    return Err(invalid("summary merge inputs have different schemas"));
-                }
-                dag.add(
-                    auxiliary,
-                    inputs,
-                    Operator::union(schemas[0].clone(), schemas.len())?,
-                )?;
-                inputs = vec![auxiliary];
-                schemas.truncate(1);
-            }
-            if let Some(promql_fallback::Lowering {
-                selectors,
-                mut steps,
-            }) = fallback.remove(&id)
-            {
-                let mut slots = Vec::new();
-                for (i, (_, schema)) in selectors.iter().enumerate() {
-                    let slot = promql_fallback::raw_series_input(id, i);
-                    match sources.remove(&slot) {
-                        Some(contract) if &contract.schema == schema => {
-                            dag.add_input(slot, contract)?
-                        }
-                        Some(_) => {
-                            return Err(invalid(format!(
-                            "node {id}: raw series input {slot} differs from the selector schema"
-                        )))
-                        }
-                        None => {
-                            return Err(invalid(format!(
-                                "node {id}: PromQL fallback requires raw series input {slot}"
-                            )))
-                        }
-                    }
-                    slots.push(slot);
-                }
-                let (last, last_inputs) = steps
-                    .pop()
-                    .ok_or_else(|| invalid("empty PromQL lowering"))?;
-                let mut ids = Vec::new();
-                let resolve = |inputs: Vec<promql_fallback::Input>, ids: &[NodeId]| {
-                    inputs
-                        .into_iter()
-                        .map(|input| match input {
-                            promql_fallback::Input::Raw(i) => slots[i],
-                            promql_fallback::Input::Step(i) => ids[i],
-                        })
-                        .collect::<Vec<_>>()
-                };
-                for (operator, inputs) in steps {
-                    dag.add(auxiliary, resolve(inputs, &ids), operator)?;
-                    ids.push(auxiliary);
-                    auxiliary -= 1;
-                }
-                dag.add(
-                    id,
-                    resolve(last_inputs, &ids),
-                    last.with_output_schema(output)?,
-                )?;
-                continue;
-            }
-            if let Payload::MaintainPopulation { population } = &node.payload {
-                use planner_types::post_asap::maintained_population::PopulationInput;
-                let PopulationInput::CurrentSeries(spec) = &population.input else {
-                    return Err(invalid(
-                        "native maintained population requires a current-series input",
-                    ));
-                };
-                let [input] = schemas.as_slice() else {
-                    return Err(invalid("current-series population requires one input"));
-                };
-                if spec.without {
-                    return Err(invalid(
-                        "dynamic without grouping requires label-set projection",
-                    ));
-                }
-                let identity = named_column(
-                    input,
-                    &ColumnRef::Named(promql_rows::SERIES_IDENTITY_COLUMN.into()),
-                )?;
-                let coordinate = input
-                    .time_index
-                    .ok_or_else(|| invalid("current-series input lacks timestamp"))?;
-                let value = named_column(input, &ColumnRef::SampleValue)?;
-                let lookback = i64::try_from(spec.lookback_ms)
-                    .map_err(|_| invalid("current-series lookback overflows"))?;
-                dag.add(
-                    id,
-                    inputs,
-                    Operator::current_series(input.clone(), identity, coordinate, value, lookback)?
-                        .with_output_schema(output)?,
-                )?;
-                continue;
-            }
-            if let Payload::EvaluatePopulation { evaluation } = &node.payload {
-                use planner_types::post_asap::maintained_population::{
-                    PopulationInput, PopulationStatistic,
-                };
-                let [producer] = inputs.as_slice() else {
-                    return Err(invalid("population evaluation requires one input"));
-                };
-                let Payload::MaintainPopulation { population } = &nodes[producer].payload else {
-                    return Err(invalid(
-                        "population evaluation requires its declared population",
-                    ));
-                };
-                let PopulationInput::CurrentSeries(spec) = &population.input else {
-                    return Err(invalid("current-series population required"));
-                };
-                if spec.without {
-                    return Err(invalid(
-                        "dynamic without ranking requires label-set projection",
-                    ));
-                }
-                let input = schemas[0].clone();
-                let PopulationStatistic::TopK { k } = evaluation else {
-                    let mut chain =
-                        row_values::population_aggregate(&input, &spec.grouping, evaluation)?;
-                    let last = chain.pop().expect("nonempty chain");
-                    let mut inputs = inputs;
-                    for operator in chain {
-                        dag.add(auxiliary, inputs, operator)?;
-                        inputs = vec![auxiliary];
-                        auxiliary -= 1;
-                    }
-                    dag.add(id, inputs, last.with_output_schema(output)?)?;
-                    continue;
-                };
-                let groups = spec
-                    .grouping
-                    .iter()
-                    .map(|name| named_column(&input, &ColumnRef::Named(name.clone())))
-                    .collect::<Result<Vec<_>, _>>()?;
-                let value = named_column(&input, &ColumnRef::SampleValue)?;
-                dag.add(
-                    auxiliary,
-                    inputs,
-                    Operator::sort(
-                        input.clone(),
-                        vec![SortKey {
-                            column: value,
-                            descending: true,
-                            nulls_first: false,
-                        }],
-                        groups.clone(),
-                    )?,
-                )?;
-                dag.add(
-                    id,
-                    vec![auxiliary],
-                    Operator::limit(input, *k as u64, 0, groups)?.with_output_schema(output)?,
-                )?;
-                continue;
-            }
-            // A closed row must include either all source labels or the explicit
-            // complete-label identity. Projected labels alone are insufficient.
-            if let Payload::SummaryAgg {
-                family,
-                input: update,
-                reduction: PlannerReduction::PerEntity,
-                grouping,
-                filter: None,
-            } = &node.payload
-            {
-                let [input_id] = inputs.as_slice() else {
-                    return Err(invalid("per-entity summary requires one input"));
-                };
-                let Some(NonASAPOp::TimeRange { child, .. }) = restored[input_id].non_asap() else {
-                    return Err(invalid(
-                        "per-entity summary requires a resolved raw time range",
-                    ));
-                };
-                let Some(NonASAPOp::Scan { schema, .. }) = child.non_asap() else {
-                    return Err(invalid("per-entity summary requires a resolved source"));
-                };
-                if !schema.closed || update.item.is_some() {
-                    return Err(invalid(
-                        "per-entity summary requires complete source identity",
-                    ));
-                }
-                crate::capability::validate_summary_kernel(family, update, grouping)
-                    .map_err(Error::Invalid)?;
-                let SummaryInputExpr::Column(value) = &update.weight else {
-                    return Err(invalid(
-                        "per-entity update requires a projected value column",
-                    ));
-                };
-                let input = schemas[0].clone();
-                let value = named_column(&input, value)?;
-                let coordinate = input
-                    .time_index
-                    .ok_or_else(|| invalid("temporal input lacks time"))?;
-                let groups = (0..input.fields.len())
-                    .filter(|&column| column != value && column != coordinate)
-                    .collect();
-                let build = Operator::summary_build(
-                    input,
-                    family.clone(),
-                    value,
-                    Some(coordinate),
-                    groups,
-                )?;
-                let compact = build.schema();
-                dag.add(auxiliary, inputs, build)?;
-                dag.add(
-                    id,
-                    vec![auxiliary],
-                    Operator::scope_timestamp(compact, output)?,
-                )?;
-                continue;
-            }
-            if let Payload::Relational {
-                operator:
-                    NonASAPOpKind::BinaryOp {
-                        operator,
-                        return_bool,
-                    },
-            } = &node.payload
-            {
-                let operator = crate::expressions::binary::BinaryOperator::from_logical(
-                    operator,
-                    *return_bool,
-                );
-                let query_time = node.output_state.timing
-                    == planner_types::post_asap::ExecutionTiming::QueryTime;
-                if let Some(&(value, left)) = literals.get(&id) {
-                    let [input] = schemas.as_slice() else {
-                        return Err(invalid("scalar binary requires one row input"));
-                    };
-                    if !query_time {
-                        return Err(invalid("scalar literal binary must run at query time"));
-                    }
-                    let scalar =
-                        Operator::scalar(crate::values::Value::Float64(value), DataType::Float64)?;
-                    let (sides, scalars, operands) = if left {
-                        (
-                            [scalar.schema(), input.clone()],
-                            [true, false],
-                            vec![auxiliary, inputs[0]],
-                        )
-                    } else {
-                        (
-                            [input.clone(), scalar.schema()],
-                            [false, true],
-                            vec![inputs[0], auxiliary],
-                        )
-                    };
-                    let [l, r] = sides;
-                    let binary = Operator::series_binary(l, r, operator.clone(), scalars)
-                        .map_err(|error| invalid(format!("node {id}: {error}")))?;
-                    dag.add(auxiliary, vec![], scalar)?;
-                    dag.add(id, operands, binary.with_output_schema(output)?)?;
-                    auxiliary -= 1;
-                    continue;
-                }
-                let label_map = |schema: &SchemaRef| {
-                    schema
-                        .fields
-                        .iter()
-                        .any(|f| matches!(f.dtype, FieldDataType::Plain(DataType::Map { .. })))
-                };
-                // Grouped rows carry their labels as columns; per-series rows
-                // carry the series identity.
-                if let (true, [left, right]) = (query_time, schemas.as_slice()) {
-                    if !label_map(left) && !label_map(right) {
-                        let binary = Operator::series_binary(
-                            left.clone(),
-                            right.clone(),
-                            operator.clone(),
-                            [false, false],
-                        )
-                        .map_err(|error| invalid(format!("node {id}: {error}")))?;
-                        dag.add(id, inputs, binary.with_output_schema(output)?)?;
-                        continue;
-                    }
-                }
-            }
-            if let Payload::FinalizeExactAccumulator = &node.payload {
-                // Exact counts read out as Int64; PromQL declares a Float64 sample.
-                let evaluation = bind_operation(node, &schemas)
-                    .map_err(|error| invalid(format!("node {id}: {error}")))?;
-                let actual = evaluation.schema();
-                let converted = actual.fields.iter().zip(&output.fields).position(|(a, d)| {
-                    a.dtype == FieldDataType::Plain(DataType::Int64)
-                        && d.dtype == FieldDataType::Plain(DataType::Float64)
-                });
-                if let Some(column) = converted {
-                    let columns = actual
-                        .fields
-                        .iter()
-                        .enumerate()
-                        .map(|(i, field)| {
-                            (
-                                field.name.clone(),
-                                if i == column {
-                                    Expression::ExactFloat64(i)
-                                } else {
-                                    Expression::Column(i)
-                                },
-                            )
-                        })
-                        .collect();
-                    let project =
-                        Operator::project(actual, columns)?.with_output_schema(output.clone())?;
-                    dag.add(auxiliary, inputs, evaluation)?;
-                    if temporal_evaluation_drops_name(node) {
-                        dag.add(auxiliary - 1, vec![auxiliary], project)?;
-                        dag.add(
-                            id,
-                            vec![auxiliary - 1],
-                            Operator::series_without_name(output)?,
-                        )?;
-                    } else {
-                        dag.add(id, vec![auxiliary], project)?;
-                    }
-                    auxiliary -= 1;
-                    continue;
-                }
-            }
-            let mut operator = compile_node(node, &schemas)
-                .map_err(|error| invalid(format!("node {id}: {error}")))?;
-            if operator.is_counter_readout() {
-                let mut pending = vec![id];
-                let mut visited = BTreeSet::new();
-                let mut ranges = BTreeSet::new();
-                while let Some(ancestor) = pending.pop() {
-                    if !visited.insert(ancestor) {
-                        continue;
-                    }
-                    if let Payload::Relational {
-                        operator: NonASAPOpKind::TimeRange { range, .. },
-                    } = &nodes[&ancestor].payload
-                    {
-                        ranges.insert(
-                            i64::try_from(range.as_millis())
-                                .map_err(|_| invalid("counter lookback exceeds Int64"))?,
-                        );
-                        continue;
-                    }
-                    pending.extend(dependencies.get(&ancestor).into_iter().flatten().copied());
-                }
-                if ranges.len() > 1 {
-                    return Err(invalid("counter evaluation has ambiguous logical windows"));
-                }
-                if let Some(lookback) = ranges.into_iter().next() {
-                    operator = operator.with_counter_lookback(lookback)?;
-                }
-            }
-            if temporal_evaluation_drops_name(node) {
-                dag.add(auxiliary, inputs, operator)?;
-                dag.add(id, vec![auxiliary], Operator::series_without_name(output)?)?;
-            } else {
-                dag.add(id, inputs, operator)?;
-            }
-        }
-    }
-    dag.validate()?;
-    Ok(dag)
-}
-
-// Temporal summary evaluations produce PromQL vectors, whose range functions drop
-// the metric name before matching/filtering. Stored state retains its full identity.
-fn temporal_evaluation_drops_name(node: &PhysicalASAPDAGNode) -> bool {
-    node.output_schema
-        .fields
-        .iter()
-        .any(|field| field.name == promql_rows::SERIES_IDENTITY_COLUMN)
-        && matches!(
-            &node.payload,
-            Payload::FinalizeExactAccumulator
-                | Payload::SummaryEstimate {
-                    query: SketchStatistic::Quantile { .. }
-                        | SketchStatistic::Cardinality
-                        | SketchStatistic::PointCount { .. }
-                        | SketchStatistic::FrequencyL2
-                        | SketchStatistic::FrequencyEntropy
-                }
-        )
-}
-
-/// Bind a Planner node against the schemas supplied by its deployment edges.
-/// This is the same checked path used by complete DAG binding.
-pub fn compile_node(node: &PhysicalASAPDAGNode, inputs: &[SchemaRef]) -> Result<Operator, Error> {
-    for schema in inputs {
-        crate::values::validate_schema(schema)?;
-    }
-    bind_operation(node, inputs)?.with_output_schema(Arc::new(node.output_schema.clone()))
-}
-
-fn bind_operation(node: &PhysicalASAPDAGNode, inputs: &[SchemaRef]) -> Result<Operator, Error> {
-    if let Payload::Relational {
-        operator: NonASAPOpKind::BinaryOp {
-            operator,
-            return_bool,
-        },
-    } = &node.payload
-    {
-        let operator =
-            crate::expressions::binary::BinaryOperator::from_logical(operator, *return_bool);
-        let [left, right] = inputs else {
-            return Err(invalid("binary requires two inputs"));
-        };
-        if node.output_state.timing == planner_types::post_asap::ExecutionTiming::IngestionTime {
-            let value = |schema: &SchemaRef| -> Result<usize, Error> {
-                let columns = schema
-                    .fields
-                    .iter()
-                    .enumerate()
-                    .filter(|(_, field)| {
-                        field.dtype
-                            == FieldDataType::Plain(planner_types::pre_asap::DataType::Float64)
-                    })
-                    .map(|(i, _)| i)
-                    .collect::<Vec<_>>();
-                match columns.as_slice() {
-                    [value] => Ok(*value),
-                    _ => Err(invalid("aligned binary requires one value column")),
-                }
-            };
-            let (l, r) = (value(left)?, value(right)?);
-            let keys = left
-                .fields
-                .iter()
-                .enumerate()
-                .filter(|(i, _)| *i != l)
-                .map(|(i, field)| {
-                    right
-                        .fields
-                        .iter()
-                        .position(|other| other.name == field.name && other.dtype == field.dtype)
-                        .map(|j| (i, j))
-                        .ok_or_else(|| invalid("aligned input identities differ"))
-                })
-                .collect::<Result<Vec<_>, _>>()?;
-            return Operator::aligned_binary(
-                left.clone(),
-                right.clone(),
-                keys,
-                (l, r),
-                operator.clone(),
-            );
-        }
-        return Operator::vector_binary(left.clone(), right.clone(), operator.clone(), false);
-    }
-    if let Payload::Relational {
-        operator: NonASAPOpKind::Join { join_kind, pred },
-    } = &node.payload
-    {
-        let [left, right] = inputs else {
-            return Err(invalid("join requires two inputs"));
-        };
-        let pred = planner_types::ir::Predicate(local_scalar(&pred.0)?);
-        if *join_kind == planner_types::pre_asap::JoinKind::Semi {
-            if let Ok(keys) = equijoin_keys(&pred, left, right) {
-                return Operator::semi_join(left.clone(), right.clone(), keys);
-            }
-        }
-        return Operator::unified_relational_join(
-            left.clone(),
-            right.clone(),
-            join_kind.clone(),
-            &pred,
-            Arc::new(node.output_schema.clone()),
-        );
-    }
-    if let Payload::Relational {
-        operator: NonASAPOpKind::Values { rows, schema },
-    } = &node.payload
-    {
-        if !inputs.is_empty() {
-            return Err(invalid("Values takes no relational inputs"));
-        }
-        let empty = Arc::new(planner_types::pre_asap::Schema::default());
-        let rows = rows
-            .iter()
-            .map(|row| {
-                row.iter()
-                    .map(|expr| expression(expr, &empty)?.evaluate(&[]))
-                    .collect::<Result<Vec<_>, Error>>()
-            })
-            .collect::<Result<Vec<_>, Error>>()?;
-        let schema = Arc::new(schema.clone());
-        return Operator::source(
-            schema.clone(),
-            vec![crate::values::Batch::try_new(schema, rows)?],
-        );
-    }
-    let [input] = inputs else {
-        return Err(invalid(
-            "native Planner binding currently requires a unary operation or an explicit source",
-        ));
-    };
-    match &node.payload {
-        Payload::FinalizeExactAccumulator => {
-            let state = summary_column(input)?;
-            use crate::Statistic as S;
-            use planner_types::post_asap::ExactKind as E;
-            let statistic = match &input.fields[state].dtype {
-                FieldDataType::ExactAggregate(kind, _) => match kind {
-                    E::Sum => S::Sum,
-                    E::Count => S::Count,
-                    E::Min => S::Min,
-                    E::Max => S::Max,
-                    E::Rate => S::Rate,
-                    E::Increase => S::Increase,
-                    _ => return Err(invalid("exact family evaluation is unsupported")),
-                },
-                _ => return Err(invalid("exact finalization requires exact state")),
-            };
-            Operator::readout(
-                input.clone(),
-                state,
-                ReadoutQuery::Exact(ExactReadout {
-                    statistic,
-                    lookback_ms: None,
-                }),
-            )
-        }
-
-        Payload::Relational { operator } => match operator {
-            NonASAPOpKind::Project { cols, .. } => Operator::project(
-                input.clone(),
-                cols.iter()
-                    .enumerate()
-                    .map(|(i, col)| {
-                        Ok((
-                            node.output_schema
-                                .fields
-                                .get(i)
-                                .ok_or_else(|| invalid("projection width mismatch"))?
-                                .name
-                                .clone(),
-                            match &col.expr {
-                                WireScalarExpr::Column(index) => Expression::Column(*index),
-                                expr => expression(expr, input)?,
-                            },
-                        ))
-                    })
-                    .collect::<Result<_, Error>>()?,
-            ),
-            NonASAPOpKind::Filter { pred } => {
-                Operator::filter(input.clone(), expression(&pred.0, input)?)
-            }
-            NonASAPOpKind::Sort { keys, partition_by } => Operator::sort(
-                input.clone(),
-                keys.iter()
-                    .map(|key| {
-                        let WireScalarExpr::Column(column) = key.expr else {
-                            return Err(invalid(
-                                "sort expression must be projected before sorting",
-                            ));
-                        };
-                        Ok(SortKey {
-                            column,
-                            descending: !key.ascending,
-                            nulls_first: key.nulls_first,
-                        })
-                    })
-                    .collect::<Result<_, Error>>()?,
-                groups(input, partition_by)?,
-            ),
-            NonASAPOpKind::Limit {
-                n,
-                offset,
-                partition_by,
-            } => Operator::limit(
-                input.clone(),
-                n.unwrap_or(usize::MAX) as u64,
-                *offset as u64,
-                groups(input, partition_by)?,
-            ),
-            NonASAPOpKind::Aggregate {
-                reduction,
-                measures,
-                output_names,
-                filters,
-                having: None,
-            } => {
-                if filters.iter().any(Option::is_some) {
-                    return Err(invalid("filtered aggregate has no native implementation"));
-                }
-                if measures.len() != output_names.len() {
-                    return Err(invalid("aggregate output names differ from measures"));
-                }
-                let PlannerReduction::Reduce(keys) = reduction else {
-                    return Err(invalid(
-                        "per-entity aggregate requires an explicit entity binding",
-                    ));
-                };
-                let measures = measures
-                    .iter()
-                    .zip(output_names)
-                    .map(|(m, name)| {
-                        let column = |col: Option<usize>| {
-                            col.map(Ok)
-                                .unwrap_or_else(|| named_column(input, &ColumnRef::SampleValue))
-                        };
-                        let m = match m {
-                            AggIntent::Count { .. } => Reduction::Count,
-                            AggIntent::Sum { col } => Reduction::Sum(column(*col)?),
-                            AggIntent::Avg { col } => Reduction::Avg(column(*col)?),
-                            AggIntent::Min { col } => Reduction::Min(column(*col)?),
-                            AggIntent::Max { col } => Reduction::Max(column(*col)?),
-                            _ => {
-                                return Err(invalid(
-                                    "aggregate intent has no native implementation",
-                                ))
-                            }
-                        };
-                        Ok((name.clone(), m))
-                    })
-                    .collect::<Result<_, Error>>()?;
-                Operator::aggregate(input.clone(), groups(input, keys)?, measures)
-            }
-            _ => Err(invalid("value operation has no native implementation")),
-        },
-        Payload::SummaryAgg {
-            family,
-            input: update,
-            reduction,
-            grouping,
-            filter,
-        } => {
-            if filter.is_some() {
-                return Err(invalid(
-                    "filtered summary update has no native implementation",
-                ));
-            }
-            if let Some(item) = &update.item {
-                let PlannerReduction::Reduce(keys) = reduction else {
-                    return Err(invalid("keyed summary requires explicit partitions"));
-                };
-                let SummaryInputExpr::Column(weight) = &update.weight else {
-                    return Err(invalid(
-                        "keyed summary weight must be a finalized value column",
-                    ));
-                };
-                if matches!(family, FieldDataType::Sketch(kind, _) if kind.algorithm() == &planner_types::post_asap::SketchAlgorithm::CmsWithHeap)
-                    && !matches!(
-                        update.weight_domain,
-                        planner_types::post_asap::WeightDomain::NonNegative { .. }
-                    )
-                {
-                    return Err(invalid("CMS requires a nonnegative weight contract"));
-                }
-                fn columns(
-                    expr: &SummaryInputExpr,
-                    input: &SchemaRef,
-                    result: &mut Vec<usize>,
-                ) -> Result<(), Error> {
-                    match expr {
-                        SummaryInputExpr::Column(column) => {
-                            result.push(named_column(input, column)?)
-                        }
-                        SummaryInputExpr::Tuple(items) => {
-                            for item in items {
-                                columns(item, input, result)?;
-                            }
-                        }
-                        _ => return Err(invalid("keyed summary needs explicit item columns")),
-                    }
-                    Ok(())
-                }
-                let mut items = Vec::new();
-                columns(item, input, &mut items)?;
-                return Operator::keyed_summary_build(
-                    input.clone(),
-                    family.clone(),
-                    named_column(input, weight)?,
-                    items,
-                    groups(input, keys)?,
-                );
-            }
-            crate::capability::validate_summary_kernel(family, update, grouping)
-                .map_err(Error::Invalid)?;
-            let SummaryInputExpr::Column(column) = &update.weight else {
-                return Err(invalid(
-                    "summary update expression must be projected to a column",
-                ));
-            };
-            let PlannerReduction::Reduce(keys) = reduction else {
-                return Err(invalid(
-                    "summary construction requires explicit grouping columns",
-                ));
-            };
-            Operator::summary_build(
-                input.clone(),
-                family.clone(),
-                named_column(input, column)?,
-                input.time_index,
-                groups(input, keys)?,
-            )
-        }
-        Payload::SummaryMerge => {
-            let state = summary_column(input)?;
-            Operator::summary_merge(
-                input.clone(),
-                state,
-                (0..input.fields.len())
-                    .filter(|&i| i != state && Some(i) != input.time_index)
-                    .collect(),
-            )
-        }
-        Payload::SummaryEstimate { query } => {
-            if let SketchStatistic::TopK { k } = query {
-                return Operator::keyed_readout(
-                    input.clone(),
-                    summary_column(input)?,
-                    *k,
-                    Arc::new(node.output_schema.clone()),
-                );
-            }
-            Operator::readout(
-                input.clone(),
-                summary_column(input)?,
-                ReadoutQuery::Sketch(query.clone()),
-            )
-        }
-        _ => Err(invalid(
-            "physical operation has no native binding; no fallback is installed",
-        )),
-    }
-}
-fn summary_column(input: &SchemaRef) -> Result<usize, Error> {
-    let columns = input
-        .fields
-        .iter()
-        .enumerate()
-        .filter(|(_, f)| !matches!(f.dtype, FieldDataType::Plain(_)))
-        .map(|(i, _)| i)
-        .collect::<Vec<_>>();
-    match columns.as_slice() {
-        [column] => Ok(*column),
-        _ => Err(invalid("one summary state column required")),
-    }
-}
-fn named_column(input: &SchemaRef, column: &ColumnRef) -> Result<usize, Error> {
-    let name = match column {
-        // Executable SchemaRef retains column names, not table qualifiers.
-        // Frontend binding has resolved the qualifier; still reject ambiguous
-        // names here rather than guessing a join side.
-        ColumnRef::Named(name) | ColumnRef::Qualified { name, .. } => name.as_str(),
-        ColumnRef::SampleValue => "value",
-        _ => {
-            return Err(invalid(
-                "summary update requires an unambiguous bound column",
-            ))
-        }
-    };
-    let matches = input
-        .fields
-        .iter()
-        .enumerate()
-        .filter(|(_, field)| field.name == name)
-        .map(|(i, _)| i)
-        .collect::<Vec<_>>();
-    match matches.as_slice() {
-        [column] => Ok(*column),
-        _ => Err(invalid("summary update column missing or ambiguous")),
-    }
-}
-fn groups(input: &SchemaRef, groups: &GroupKeys) -> Result<Vec<usize>, Error> {
-    if groups.is_without() {
-        return Err(invalid("grouping without requires resolved label columns"));
-    }
-    if groups.keys().iter().any(|&i| i >= input.fields.len()) {
-        return Err(invalid("grouping column out of range"));
-    }
-    Ok(groups.keys().to_vec())
-}
-fn expression(expr: &WireScalarExpr, input: &SchemaRef) -> Result<Expression, Error> {
-    let expr = local_scalar(expr)?;
-    Ok(Expression::unified_planner(
-        crate::expressions::unified_planner::CompiledExpression::compile(&expr, input)?,
-    ))
-}
-
-struct CheckedSource<'a> {
-    source: Source<'a>,
-    output: SchemaRef,
-}
-impl PhysicalOperator<Batch, SchemaRef> for CheckedSource<'_> {
-    fn properties(&self, inputs: &[crate::plan::PlanProperties]) -> crate::plan::PlanProperties {
-        self.source.properties(inputs)
-    }
-
-    fn name(&self) -> &str {
-        self.source.name()
-    }
-    fn input_schemas(&self) -> Vec<SchemaRef> {
-        vec![]
-    }
-    fn output_schema(&self) -> SchemaRef {
-        self.output.clone()
-    }
-    fn output_bytes(&self, batch: &Batch) -> usize {
-        self.source.output_bytes(batch)
-    }
-    fn start<'a>(
-        &'a self,
-        inputs: Vec<crate::runtime::Input<'a, Batch>>,
-        context: crate::runtime::RunContext,
-    ) -> Result<crate::runtime::OutputStream<'a, Batch>, Error> {
-        use futures::StreamExt;
-        Ok(self
-            .source
-            .start(inputs, context)?
-            .map(|batch| {
-                let batch = batch?;
-                if batch.schema() != &self.output {
-                    return Err(invalid("source batch differs from its bound schema"));
-                }
-                Ok(batch)
-            })
-            .boxed_local())
-    }
-}
-
-// Bound recursion before invoking the upstream recursive provenance validator.
-fn preflight_depth(dag: &PhysicalASAPDAG) -> Result<(), Error> {
-    let mut remaining = dag
-        .nodes
-        .iter()
-        .map(|node| (node.id, 0usize))
-        .collect::<BTreeMap<_, _>>();
-    if remaining.len() != dag.nodes.len() {
-        return Err(invalid("duplicate Planner node"));
-    }
-    let mut consumers = BTreeMap::<_, Vec<_>>::new();
-    for edge in &dag.edges {
-        if !remaining.contains_key(&edge.producer) {
-            return Err(invalid("missing Planner edge producer"));
-        }
-        *remaining
-            .get_mut(&edge.consumer)
-            .ok_or_else(|| invalid("missing Planner edge consumer"))? += 1;
-        consumers
-            .entry(edge.producer)
-            .or_default()
-            .push(edge.consumer);
-    }
-    let mut ready = remaining
-        .iter()
-        .filter(|(_, n)| **n == 0)
-        .map(|(id, _)| *id)
-        .collect::<std::collections::VecDeque<_>>();
-    let mut depths = BTreeMap::new();
-    let mut visited = 0;
-    while let Some(id) = ready.pop_front() {
-        visited += 1;
-        let depth = *depths.get(&id).unwrap_or(&1usize);
-        if depth > 128 {
-            return Err(invalid("DAG exceeds the supported execution depth of 128"));
-        }
-        for &consumer in consumers.get(&id).into_iter().flatten() {
-            let next = depths.entry(consumer).or_insert(1);
-            *next = (*next).max(depth + 1);
-            let count = remaining.get_mut(&consumer).expect("validated endpoint");
-            *count -= 1;
-            if *count == 0 {
-                ready.push_back(consumer);
-            }
-        }
-    }
-    if visited != dag.nodes.len() {
-        return Err(invalid("Planner DAG contains a cycle"));
-    }
-    Ok(())
-}
-
-/// Join predicates address the concatenated left/right schema.
-fn semi_join_keys(
-    expr: &ScalarExpr,
-    left: usize,
-    right: usize,
-    keys: &mut Vec<(usize, usize)>,
-) -> Result<(), Error> {
-    match expr {
-        ScalarExpr::BoolAnd(parts) => {
-            for part in parts {
-                semi_join_keys(part, left, right, keys)?;
-            }
-        }
-        ScalarExpr::Compare {
-            left: a,
-            op: CompareOpKind::Eq,
-            right: b,
-            ..
-        } => {
-            let (ScalarExpr::Column(a), ScalarExpr::Column(b)) = (a.as_ref(), b.as_ref()) else {
-                return Err(invalid("semi-join requires column equality keys"));
-            };
-            let (a, b) = if a < b { (*a, *b) } else { (*b, *a) };
-            if a >= left || b < left || b >= left + right {
-                return Err(invalid("semi-join key must match left to right"));
-            }
-            keys.push((a, b - left));
-        }
-        _ => return Err(invalid("unsupported semi-join predicate")),
-    }
-    Ok(())
-}
-
-/// Resolve equality keys against the Planner join's concatenated input schema.
-/// Deployments may use these positions to bind their source columns.
-pub fn equijoin_keys(
-    pred: &planner_types::ir::Predicate,
-    left: &planner_types::post_asap::Schema,
-    right: &planner_types::post_asap::Schema,
-) -> Result<Vec<(usize, usize)>, Error> {
-    let mut keys = Vec::new();
-    semi_join_keys(&pred.0, left.fields.len(), right.fields.len(), &mut keys)?;
-    if keys.is_empty() {
-        return Err(invalid("semi-join requires explicit matching keys"));
-    }
-    Ok(keys)
-}
-
-fn local_scalar(expr: &WireScalarExpr) -> Result<ScalarExpr, Error> {
-    let mut missing = false;
-    let result = logical::scalar(expr, &mut |_| {
-        missing = true;
-        std::rc::Rc::new(OperatorNode::with_schema(
-            LogicalOperator::NonASAP(NonASAPOp::Values {
-                rows: vec![],
-                schema: Default::default(),
-            }),
-            Default::default(),
-        ))
-    });
-    if missing {
-        Err(invalid(
-            "scalar plan reads require explicit execution bindings",
-        ))
-    } else {
-        Ok(result)
-    }
-}
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/precompute.rs b/crates/asap-physical-operators/src/unified_physical_planner/precompute.rs
deleted file mode 100644
index 12e7564d8..000000000
--- a/crates/asap-physical-operators/src/unified_physical_planner/precompute.rs
+++ /dev/null
@@ -1,643 +0,0 @@
-//! Compile immutable summary-input computation with explicit population and pane identity.
-use super::promql_rows::SERIES_IDENTITY_COLUMN as SERIES_IDENTITY;
-use super::*;
-use planner_types::post_asap::FieldDataType as SummaryFamilyType;
-use planner_types::{
-    post_asap::{ExecutionTiming, GroupingStrategy, Schema},
-    pre_asap::DataType,
-};
-
-/// Physical rows carry the population and pane coordinate alongside the logical value.
-/// These fields preserve identities which are implicit in a stored summary instance.
-pub fn population_schema(family: SummaryFamilyType) -> SchemaRef {
-    Arc::new(Schema {
-        fields: vec![
-            planner_types::post_asap::Field {
-                name: "$population".into(),
-                dtype: SummaryFamilyType::Plain(DataType::Map {
-                    key: Box::new(DataType::Utf8),
-                    value: Box::new(DataType::Utf8),
-                    value_nullable: false,
-                }),
-                nullable: false,
-                table: None,
-            },
-            planner_types::post_asap::Field {
-                name: "$window_end".into(),
-                dtype: SummaryFamilyType::Plain(DataType::Timestamp),
-                nullable: false,
-                table: None,
-            },
-            planner_types::post_asap::Field {
-                name: "value".into(),
-                dtype: family,
-                nullable: false,
-                table: None,
-            },
-        ],
-        time_index: Some(1),
-        unique_keys: vec![],
-        closed: false,
-    })
-}
-
-/// Raw sample rows at a precompute boundary. `$population` holds the series'
-/// complete label set, so it is the complete source identity of per-series
-/// summaries; `$timestamp` is the sample time and `value` a finite sample
-/// (stale markers are not samples). Rows are what the boundary's source scan
-/// selected; the deployment decides which rows and panes they are. Label sets
-/// must be canonical (sorted, unique, no empty values), since they are the
-/// population identity: build rows with [`raw_sample_row`].
-pub fn raw_sample_schema() -> SchemaRef {
-    let mut schema = (*population_schema(SummaryFamilyType::Plain(DataType::Float64))).clone();
-    schema.fields[1].name = "$timestamp".into();
-    Arc::new(schema)
-}
-
-/// A raw sample row whose label set is sorted, unique and omits empty values,
-/// so one series always has one population identity.
-pub fn raw_sample_row(
-    labels: &BTreeMap<String, String>,
-    timestamp_ms: i64,
-    value: f64,
-) -> Vec<crate::values::Value> {
-    use crate::values::Value;
-    vec![
-        Value::Map(
-            labels
-                .iter()
-                .filter(|(_, v)| !v.is_empty())
-                .map(|(k, v)| {
-                    (
-                        Value::Utf8(k.as_str().into()),
-                        Value::Utf8(v.as_str().into()),
-                    )
-                })
-                .collect::<Vec<_>>()
-                .into(),
-        ),
-        Value::Timestamp(timestamp_ms),
-        Value::Float64(value),
-    ]
-}
-
-/// Input contract of a precompute boundary: raw sample rows for a raw time
-/// series scan, otherwise the stored population of its summary state.
-pub fn boundary_schema(node: &PhysicalASAPDAGNode) -> Result<SchemaRef, Error> {
-    if !matches!(
-        &node.payload,
-        Payload::Relational {
-            operator: NonASAPOpKind::Scan {
-                source: planner_types::pre_asap::Source::TimeSeries { .. },
-                ..
-            } | NonASAPOpKind::TimeRange { .. }
-        }
-    ) {
-        return source_schema(&node.output_schema);
-    }
-    let logical = &node.output_schema;
-    // Labels may be absent from a series; its label map then omits them.
-    let valid = logical
-        .fields
-        .iter()
-        .enumerate()
-        .all(|(i, field)| match &field.dtype {
-            SummaryFamilyType::Plain(DataType::Timestamp) => {
-                Some(i) == logical.time_index && !field.nullable
-            }
-            SummaryFamilyType::Plain(DataType::Float64) => field.name == "value" && !field.nullable,
-            SummaryFamilyType::Plain(DataType::Utf8) => true,
-            _ => false,
-        })
-        && !logical
-            .fields
-            .iter()
-            .any(|f| f.name.starts_with('$') && f.name != SERIES_IDENTITY)
-        && logical.time_index.is_some()
-        && logical.fields.iter().filter(|f| f.name == "value").count() == 1;
-    if !valid {
-        return Err(invalid(
-            "raw sample boundary requires labels, a timestamp and one Float64 value",
-        ));
-    }
-    Ok(raw_sample_schema())
-}
-
-/// Validate the adapter layout during installed-plan recovery without lowering operators.
-pub fn source_schema(logical: &Schema) -> Result<SchemaRef, Error> {
-    let states = logical
-        .fields
-        .iter()
-        .filter(|f| !matches!(f.dtype, SummaryFamilyType::Plain(_)))
-        .collect::<Vec<_>>();
-    let [state] = states.as_slice() else {
-        return Err(invalid(
-            "stored population requires one typed summary state",
-        ));
-    };
-    if logical.fields.iter().enumerate().any(|(i, field)| matches!(&field.dtype, SummaryFamilyType::Plain(dtype)
-        if field.nullable || !matches!(dtype, DataType::Utf8) && !(Some(i) == logical.time_index && *dtype == DataType::Timestamp))) {
-        return Err(invalid("stored population metadata cannot reconstruct extra value columns"));
-    }
-    if state.nullable {
-        return Err(invalid("stored population state cannot be null"));
-    }
-    Ok(population_schema(state.dtype.clone()))
-}
-
-pub fn is_population_schema(schema: &SchemaRef) -> bool {
-    schema
-        .fields
-        .get(2)
-        .is_some_and(|field| *schema == population_schema(field.dtype.clone()))
-}
-
-/// Compile a complete selected precompute sub-DAG. Inputs are already-computed
-/// state boundaries; the deployment supplies groups, panes and states, never operations.
-pub fn compile(
-    dag: &PhysicalASAPDAG,
-    frontiers: &[NodeId],
-    roots: &[NodeId],
-) -> Result<CompiledPhysicalDAG, Error> {
-    preflight_depth(dag)?;
-    dag.validate().map_err(|e| invalid(e.to_string()))?;
-    let nodes = dag
-        .nodes
-        .iter()
-        .map(|n| (u64::from(n.id.0), n))
-        .collect::<BTreeMap<_, _>>();
-    let frontier = frontiers.iter().copied().collect::<BTreeSet<_>>();
-    if frontier.len() != frontiers.len() || roots.iter().any(|r| frontier.contains(r)) {
-        return Err(invalid(
-            "precompute boundaries must be distinct from outputs",
-        ));
-    }
-    let mut dependencies = BTreeMap::<NodeId, Vec<NodeId>>::new();
-    let mut edges = dag.edges.iter().collect::<Vec<_>>();
-    edges.sort_by_key(|edge| {
-        (
-            edge.consumer.0,
-            match edge.role {
-                planner_types::ir::export::EdgeRole::Left => 0,
-                planner_types::ir::export::EdgeRole::Input => 1,
-                planner_types::ir::export::EdgeRole::Right => 2,
-                planner_types::ir::export::EdgeRole::ScalarRef => 3,
-            },
-        )
-    });
-    for edge in edges {
-        dependencies
-            .entry(u64::from(edge.consumer.0))
-            .or_default()
-            .push(u64::from(edge.producer.0));
-    }
-    let mut ordered = Vec::new();
-    let mut seen = BTreeSet::new();
-    let mut pending = roots.iter().map(|&id| (id, false)).collect::<Vec<_>>();
-    while let Some((id, expanded)) = pending.pop() {
-        if expanded {
-            ordered.push(id);
-            continue;
-        }
-        if !seen.insert(id) {
-            continue;
-        }
-        if !nodes.contains_key(&id) {
-            return Err(invalid("missing precompute node"));
-        }
-        pending.push((id, true));
-        if !frontier.contains(&id) {
-            pending.extend(
-                dependencies
-                    .get(&id)
-                    .into_iter()
-                    .flatten()
-                    .map(|id| (*id, false)),
-            );
-        }
-    }
-    let mut sources = BTreeMap::new();
-    let mut fragments = BTreeMap::new();
-    let mut outputs = BTreeMap::<NodeId, SchemaRef>::new();
-    for id in ordered {
-        let node = nodes[&id];
-        if frontier.contains(&id) {
-            let schema = boundary_schema(node)?;
-            sources.insert(id, InputContract::bounded(schema.clone()));
-            outputs.insert(id, schema);
-            continue;
-        }
-        if node.output_state.timing != ExecutionTiming::IngestionTime {
-            return Err(invalid("precompute dag contains a query-time operation"));
-        }
-        let inputs = dependencies.get(&id).cloned().unwrap_or_default();
-        let schemas = inputs
-            .iter()
-            .map(|id| {
-                outputs
-                    .get(id)
-                    .cloned()
-                    .ok_or_else(|| invalid("missing precompute input"))
-            })
-            .collect::<Result<Vec<_>, _>>()?;
-        let dag = fragment(
-            node,
-            &schemas,
-            &inputs.iter().map(|id| nodes[id]).collect::<Vec<_>>(),
-        )?;
-        outputs.insert(id, dag.output_contract(dag.roots()[0])?.schema);
-        fragments.insert(id, (inputs, dag));
-    }
-    CompiledPhysicalDAG::compose(sources, fragments, roots.to_vec())
-}
-
-fn validate_value_output(node: &PhysicalASAPDAGNode) -> Result<(), Error> {
-    let schema = &node.output_schema;
-    // Physical population rows already carry the complete identity in `$population`.
-    // Typed logical plans may expose its opaque series-identity column as metadata.
-    let identity = planner_types::pre_asap::schema::PROMQL_SERIES_IDENTITY;
-    let identities = schema
-        .fields
-        .iter()
-        .filter(|field| field.name == identity)
-        .collect::<Vec<_>>();
-    if identities.len() > 1
-        || identities
-            .iter()
-            .any(|field| field.nullable || field.dtype != SummaryFamilyType::Plain(DataType::Utf8))
-    {
-        return Err(invalid(
-            "precompute series identity requires one non-null Utf8 column",
-        ));
-    }
-    let values = schema
-        .fields
-        .iter()
-        .enumerate()
-        .filter(|(i, field)| Some(*i) != schema.time_index && field.name != identity)
-        .collect::<Vec<_>>();
-    if !matches!(values.as_slice(), [(_, field)] if !field.nullable && field.dtype == SummaryFamilyType::Plain(DataType::Float64))
-        || schema.time_index.is_some_and(|i| {
-            schema.fields.get(i).is_none_or(|f| {
-                f.nullable || f.dtype != SummaryFamilyType::Plain(DataType::Timestamp)
-            })
-        })
-    {
-        return Err(invalid(
-            "precompute value schema requires Float64 and an optional declared timestamp",
-        ));
-    }
-    Ok(())
-}
-
-fn fragment(
-    node: &PhysicalASAPDAGNode,
-    schemas: &[SchemaRef],
-    parents: &[&PhysicalASAPDAGNode],
-) -> Result<CompiledPhysicalDAG, Error> {
-    let sources = schemas
-        .iter()
-        .enumerate()
-        .map(|(id, schema)| (id as u64, InputContract::bounded(schema.clone())))
-        .collect();
-    let mut operators = BTreeMap::new();
-    let mut next = schemas.len() as u64;
-    let mut add = |inputs: Vec<NodeId>, op: Operator| -> Result<NodeId, Error> {
-        let id = next;
-        next += 1;
-        operators.insert(id, (inputs, op));
-        Ok(id)
-    };
-    let root = match &node.payload {
-        Payload::Relational {
-            operator:
-                NonASAPOpKind::BinaryOp {
-                    operator,
-                    return_bool,
-                },
-        } => {
-            let operator =
-                crate::expressions::binary::BinaryOperator::from_logical(operator, *return_bool);
-            validate_value_output(node)?;
-            if node.output_schema.time_index.is_none()
-                || parents.iter().any(|p| p.output_schema.time_index.is_none())
-            {
-                return Err(invalid(
-                    "precompute binary requires declared window timestamps",
-                ));
-            }
-            let [left, right] = schemas else {
-                return Err(invalid("precompute binary requires two inputs"));
-            };
-            add(
-                vec![0, 1],
-                Operator::aligned_binary(
-                    left.clone(),
-                    right.clone(),
-                    vec![(0, 0), (1, 1)],
-                    (2, 2),
-                    operator.clone(),
-                )?,
-            )?
-        }
-        Payload::FinalizeExactAccumulator => {
-            let [input] = schemas else {
-                return Err(invalid("finalize requires one state input"));
-            };
-            validate_value_output(node)?;
-            let statistic = match &input.fields[2].dtype {
-                SummaryFamilyType::ExactAggregate(planner_types::post_asap::ExactKind::Sum, _) => {
-                    crate::Statistic::Sum
-                }
-                SummaryFamilyType::ExactAggregate(
-                    planner_types::post_asap::ExactKind::Count,
-                    _,
-                ) => crate::Statistic::Count,
-                _ => {
-                    return Err(invalid(
-                        "precompute finalization requires explicit Sum or Count semantics",
-                    ))
-                }
-            };
-            let read = Operator::readout(
-                input.clone(),
-                2,
-                ReadoutQuery::Exact(ExactReadout {
-                    statistic,
-                    lookback_ms: None,
-                }),
-            )?;
-            let output = read.schema();
-            let read = add(vec![0], read)?;
-            let project = Operator::project(
-                output,
-                vec![
-                    ("$population".into(), Expression::Column(0)),
-                    ("$window_end".into(), Expression::Column(1)),
-                    (
-                        "value".into(),
-                        Expression::FiniteFloat64(Box::new(Expression::ExactFloat64(2))),
-                    ),
-                ],
-            )?
-            .with_output_schema(population_schema(SummaryFamilyType::Plain(
-                DataType::Float64,
-            )))?;
-            add(vec![read], project)?
-        }
-        Payload::SummaryAgg {
-            family,
-            input: update,
-            reduction,
-            grouping,
-            filter,
-        } => {
-            if filter.is_some() {
-                return Err(invalid(
-                    "filtered summary update has no native implementation",
-                ));
-            }
-            let [input] = schemas else {
-                return Err(invalid("summary update requires one input"));
-            };
-            // Item identities resolve against the complete label set of raw
-            // samples; finalized evaluations carry no such identity.
-            let raw = *input == raw_sample_schema();
-            // A unit-frequency summary (HLL) observes each raw sample value.
-            let unit_frequency = raw
-                && crate::capability::is_unit_sample_frequency(update)
-                && matches!(family, SummaryFamilyType::Sketch(kind, _) if !matches!(
-                    kind.algorithm(),
-                    planner_types::post_asap::SketchAlgorithm::Cms
-                        | planner_types::post_asap::SketchAlgorithm::CountSketch
-                        | planner_types::post_asap::SketchAlgorithm::CmsWithHeap
-                        | planner_types::post_asap::SketchAlgorithm::CountSketchWithHeap
-                ));
-            let keyed = update.item.is_some() && !unit_frequency;
-            if (keyed && !raw) || !matches!(grouping, GroupingStrategy::PerSubpopulationInstance) {
-                return Err(invalid(
-                    "precompute keyed/shared update needs its dedicated physical candidate",
-                ));
-            }
-            crate::capability::validate_summary_kernel(family, update, grouping)
-                .map_err(Error::Invalid)?;
-            if raw
-                && matches!(
-                    update.weight_domain,
-                    planner_types::post_asap::WeightDomain::NonNegative {
-                        proof: planner_types::post_asap::NonNegativeWeightProof::ResetAwareCounterDerivative
-                    }
-                )
-            {
-                return Err(invalid(
-                    "a counter-derivative weight cannot be read from raw cumulative samples",
-                ));
-            }
-            if keyed
-                && matches!(family, SummaryFamilyType::Sketch(kind, _) if kind.algorithm() == &planner_types::post_asap::SketchAlgorithm::CmsWithHeap)
-                && !matches!(
-                    update.weight_domain,
-                    planner_types::post_asap::WeightDomain::NonNegative { .. }
-                )
-            {
-                return Err(invalid("CMS requires a nonnegative weight contract"));
-            }
-            let labels = match reduction {
-                PlannerReduction::PerEntity => Expression::Column(0),
-                PlannerReduction::Reduce(keys) => Expression::LabelSet {
-                    column: 0,
-                    labels: keys
-                        .keys()
-                        .iter()
-                        .map(|key| {
-                            parents[0]
-                                .output_schema
-                                .fields
-                                .get(*key)
-                                // A raw label map omits absent labels; the
-                                // series identity is not one of its labels.
-                                .filter(|field| {
-                                    (raw || !field.nullable)
-                                        && field.name != SERIES_IDENTITY
-                                        && field.dtype == SummaryFamilyType::Plain(DataType::Utf8)
-                                })
-                                .map(|f| f.name.clone())
-                                .ok_or_else(|| {
-                                    invalid("summary grouping must identify population labels")
-                                })
-                        })
-                        .collect::<Result<Vec<_>, _>>()?,
-                    without: keys.is_without(),
-                },
-            };
-            let weight = match &update.weight {
-                _ if unit_frequency => Expression::Column(2),
-                SummaryInputExpr::Constant(value) => Expression::Literal {
-                    value: crate::values::Value::Float64(*value),
-                    dtype: DataType::Float64,
-                },
-                SummaryInputExpr::Column(ColumnRef::SampleValue) => Expression::Column(2),
-                SummaryInputExpr::Column(ColumnRef::Named(name))
-                    if parents[0].output_schema.fields.iter().any(|f| {
-                        f.name == *name && f.dtype == SummaryFamilyType::Plain(DataType::Float64)
-                    }) =>
-                {
-                    Expression::Column(2)
-                }
-                _ => {
-                    return Err(invalid(
-                        "summary weight does not resolve to the input value",
-                    ))
-                }
-            };
-            let mut columns = vec![
-                ("$population".into(), labels),
-                ("$window_end".into(), Expression::Column(1)),
-                ("value".into(), Expression::FiniteFloat64(Box::new(weight))),
-            ];
-            let mut fields = population_schema(SummaryFamilyType::Plain(DataType::Float64))
-                .fields
-                .clone();
-            if keyed {
-                let mut items = Vec::new();
-                raw_items(
-                    update.item.as_ref().expect("keyed item"),
-                    &parents[0].output_schema,
-                    &mut items,
-                )?;
-                for (index, (expression, dtype)) in items.into_iter().enumerate() {
-                    let name = format!("$item{index}");
-                    fields.push(planner_types::post_asap::Field {
-                        name: name.clone(),
-                        dtype: SummaryFamilyType::Plain(dtype),
-                        nullable: false,
-                        table: None,
-                    });
-                    columns.push((name, expression));
-                }
-            }
-            let item_columns = (3..fields.len()).collect::<Vec<_>>();
-            let project = Operator::project(input.clone(), columns)?.with_output_schema(
-                Arc::new(Schema {
-                    fields,
-                    unique_keys: vec![],
-                    closed: false,
-                    time_index: Some(1),
-                }),
-            )?;
-            let projected = project.schema();
-            let project = add(vec![0], project)?;
-            let build = if keyed {
-                Operator::keyed_summary_build(projected, family.clone(), 2, item_columns, vec![0])?
-            } else {
-                Operator::summary_build(projected, family.clone(), 2, Some(1), vec![0])?
-            };
-            let built = build.schema();
-            let build = add(vec![project], build)?;
-            add(
-                vec![build],
-                Operator::scope_timestamp(built, population_schema(family.clone()))?,
-            )?
-        }
-        Payload::SummaryMerge => {
-            let Some(input) = schemas.first() else {
-                return Err(invalid("summary merge requires inputs"));
-            };
-            if schemas.iter().any(|s| s != input) {
-                return Err(invalid("summary merge inputs differ"));
-            }
-            let union = add(
-                (0..schemas.len() as u64).collect(),
-                Operator::union(input.clone(), schemas.len())?,
-            )?;
-            let merge = Operator::summary_merge(input.clone(), 2, vec![0])?;
-            let merged = merge.schema();
-            let merge = add(vec![union], merge)?;
-            add(
-                vec![merge],
-                Operator::scope_timestamp(merged, input.clone())?,
-            )?
-        }
-        _ => {
-            return Err(invalid(
-                "precompute operation has no native population implementation",
-            ))
-        }
-    };
-    CompiledPhysicalDAG::from_operators(sources, operators, vec![root])
-}
-
-/// Resolve keyed item identities over raw sample rows: labels (absent labels
-/// read as empty, as in PromQL), the sample value, or the canonical encoding
-/// of the label set less excluded labels.
-fn raw_items(
-    expr: &SummaryInputExpr,
-    scan: &Schema,
-    items: &mut Vec<(Expression, DataType)>,
-) -> Result<(), Error> {
-    // Open PromQL scans need not list every label, so any name that is not
-    // another scan column (value, time, series identity) reads as a label.
-    let label = |column: &ColumnRef| match column {
-        ColumnRef::Named(name) | ColumnRef::Qualified { name, .. }
-            if !name.starts_with('$')
-                && scan.fields.iter().all(|f| {
-                    &f.name != name || f.dtype == SummaryFamilyType::Plain(DataType::Utf8)
-                }) =>
-        {
-            Some(name.clone())
-        }
-        _ => None,
-    };
-    let identity = |excluding: Vec<String>| {
-        (
-            Expression::LabelIdentity {
-                column: 0,
-                excluding,
-            },
-            DataType::Utf8,
-        )
-    };
-    match expr {
-        SummaryInputExpr::Column(ColumnRef::SampleValue) => {
-            items.push((Expression::Column(2), DataType::Float64))
-        }
-        SummaryInputExpr::Column(ColumnRef::Named(name) | ColumnRef::Qualified { name, .. })
-            if name == "value" =>
-        {
-            items.push((Expression::Column(2), DataType::Float64))
-        }
-        SummaryInputExpr::Column(ColumnRef::Named(name) | ColumnRef::Qualified { name, .. })
-            if name == SERIES_IDENTITY =>
-        {
-            items.push(identity(vec![]))
-        }
-        SummaryInputExpr::Column(column) if label(column).is_some() => items.push((
-            Expression::Label {
-                column: 0,
-                name: label(column).expect("resolved label"),
-            },
-            DataType::Utf8,
-        )),
-        SummaryInputExpr::EntityIdentity(
-            planner_types::post_asap::EntityIdentity::PromqlLabelSet { excluding },
-        ) => items.push(identity(
-            excluding
-                .iter()
-                .map(|column| {
-                    label(column).ok_or_else(|| invalid("excluded identity label is not a label"))
-                })
-                .collect::<Result<_, _>>()?,
-        )),
-        SummaryInputExpr::Tuple(parts) if !parts.is_empty() => {
-            for part in parts {
-                raw_items(part, scan, items)?;
-            }
-        }
-        _ => {
-            return Err(invalid(
-                "keyed summary item does not resolve over raw samples",
-            ))
-        }
-    }
-    Ok(())
-}
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/promql_fallback.rs b/crates/asap-physical-operators/src/unified_physical_planner/promql_fallback.rs
deleted file mode 100644
index 5d03bb0b9..000000000
--- a/crates/asap-physical-operators/src/unified_physical_planner/promql_fallback.rs
+++ /dev/null
@@ -1,859 +0,0 @@
-//! Compile a retained PromQL sub-DAG (`Fallback`) from its typed expression.
-//! The deployment supplies the raw series of each selector; the Planner
-//! computes selection, range functions, subqueries, matching and aggregation.
-use super::*;
-use crate::operators::SubquerySteps;
-use planner_types::post_asap::execution_data_state::lift_plain;
-use planner_types::pre_asap::{AtModifier, VectorMatchKind};
-
-/// Input slot for the raw series read by the `selector`th selector (in
-/// [`raw_series`] order) of Fallback node `node`. The node's own ID names its
-/// computed output, so the raw rows need another.
-pub fn raw_series_input(node: NodeId, selector: usize) -> NodeId {
-    node | ((selector as u64 + 1) << 32)
-}
-
-/// The Fallback node that owns a raw-series input slot.
-pub(super) fn raw_series_owner(slot: NodeId) -> Option<NodeId> {
-    (slot >> 32 != 0).then_some(slot & u64::from(u32::MAX))
-}
-
-/// A selector expression and its raw-series row schema.
-pub type Selector = (OperatorNode, SchemaRef);
-
-/// The selectors a Fallback expression reads, left to right, and the row
-/// schema of the raw series the deployment supplies for each at
-/// [`raw_series_input`]. The rows must cover the selector's window at every
-/// evaluation instant `T`, or at its `@` time: `(T - offset - range, T - offset]`;
-/// under a subquery `[R:S] offset O` that is `(T - O - R - offset - range, T - O - offset]`.
-pub fn raw_series(expression: &OperatorNode) -> Result<Vec<Selector>, Error> {
-    Ok(lower(expression)?.selectors)
-}
-
-/// An operator input: a selector's raw rows or an earlier step.
-pub(super) enum Input {
-    Raw(usize),
-    Step(usize),
-}
-
-/// Operators computing an expression; the last step is its result.
-#[derive(Default)]
-pub(super) struct Lowering {
-    pub selectors: Vec<Selector>,
-    pub steps: Vec<(Operator, Vec<Input>)>,
-}
-
-pub(super) fn lower(expression: &OperatorNode) -> Result<Lowering, Error> {
-    let mut lowering = Lowering::default();
-    lowering.value(expression)?;
-    Ok(lowering)
-}
-
-/// Compile a standalone scalar expression and expose its real series dependencies.
-/// Input slots use root 0; no logical wrapper node is introduced.
-pub fn compile_scalar_root(
-    expr: &ScalarExpr,
-) -> Result<(CompiledPhysicalDAG, Vec<Selector>), Error> {
-    let mut lowering = Lowering::default();
-    lowering.scalar_value(expr)?;
-    let mut inputs = BTreeMap::new();
-    for (i, (_, schema)) in lowering.selectors.iter().enumerate() {
-        inputs.insert(
-            raw_series_input(0, i),
-            InputContract::bounded(schema.clone()),
-        );
-    }
-    let last = lowering.steps.len() - 1;
-    let mut operators = BTreeMap::new();
-    for (i, (operator, dependencies)) in lowering.steps.into_iter().enumerate() {
-        let id = if i == last { 0 } else { i as u64 + 1 };
-        let dependencies = dependencies
-            .into_iter()
-            .map(|input| match input {
-                Input::Raw(i) => raw_series_input(0, i),
-                Input::Step(i) => i as u64 + 1,
-            })
-            .collect();
-        operators.insert(id, (dependencies, operator));
-    }
-    Ok((
-        CompiledPhysicalDAG::from_operators(inputs, operators, vec![0])?,
-        lowering.selectors,
-    ))
-}
-
-fn declared(expression: &OperatorNode) -> Result<SchemaRef, Error> {
-    let schema = expression.schema.clone();
-    Ok(Arc::new(lift_plain(&schema)))
-}
-
-fn millis(duration: &std::time::Duration) -> Result<i64, Error> {
-    i64::try_from(duration.as_millis()).map_err(|_| invalid("PromQL duration exceeds Int64"))
-}
-
-/// A fixed `@` time. `start()`/`end()` depend on the deployment's range query.
-fn at(shift: &planner_types::pre_asap::TimeShift) -> Result<Option<i64>, Error> {
-    match shift.at {
-        None => Ok(None),
-        Some(AtModifier::Timestamp(at)) => Ok(Some(at)),
-        Some(AtModifier::Start | AtModifier::End) => Ok(None),
-    }
-}
-
-fn range_anchor(expression: &OperatorNode) -> Option<AtModifier> {
-    match expression.expect_non_asap() {
-        NonASAPOp::TimeRange { child, .. } => range_anchor(child),
-        NonASAPOp::TimeShift { shift, .. } => shift
-            .at
-            .filter(|at| matches!(at, AtModifier::Start | AtModifier::End)),
-        _ => None,
-    }
-}
-
-/// `TimeRange { range, [TimeShift { offset, @ }], Scan }`: range, offset, `@`.
-fn selector(expression: &OperatorNode) -> Result<(i64, i64, Option<i64>), Error> {
-    let NonASAPOp::TimeRange { range, child, .. } = expression.expect_non_asap() else {
-        return Err(invalid("PromQL operand must be a series selector"));
-    };
-    let (offset, at, scan) = match child.expect_non_asap() {
-        NonASAPOp::TimeShift { shift, child } => {
-            (shift.offset_ms, at(shift)?, child.expect_non_asap())
-        }
-        scan => (0, None, scan),
-    };
-    if !matches!(scan, NonASAPOp::Scan { .. }) {
-        return Err(invalid("PromQL selector must read one scan"));
-    }
-    Ok((millis(range)?, offset, at))
-}
-
-impl Lowering {
-    fn schema(&self, input: &Input) -> SchemaRef {
-        match input {
-            Input::Raw(i) => self.selectors[*i].1.clone(),
-            Input::Step(i) => self.steps[*i].0.schema(),
-        }
-    }
-
-    fn add(&mut self, operator: Operator, inputs: Vec<Input>) -> Input {
-        self.steps.push((operator, inputs));
-        Input::Step(self.steps.len() - 1)
-    }
-
-    /// Conform `operator` to the logical schema of the expression it computes.
-    fn push(
-        &mut self,
-        operator: Operator,
-        inputs: Vec<Input>,
-        logical: &OperatorNode,
-    ) -> Result<Input, Error> {
-        Ok(self.add(operator.with_output_schema(declared(logical)?)?, inputs))
-    }
-
-    fn read(&mut self, selector: &OperatorNode) -> Result<Input, Error> {
-        let schema = declared(selector)?;
-        if !schema
-            .fields
-            .iter()
-            .any(|f| f.name == promql_rows::SERIES_IDENTITY_COLUMN)
-        {
-            return Err(invalid(
-                "PromQL fallback requires the complete series identity",
-            ));
-        }
-        self.selectors.push((selector.clone(), schema));
-        Ok(Input::Raw(self.selectors.len() - 1))
-    }
-
-    /// An instant vector, or a scalar for scalar-valued expressions.
-    fn value(&mut self, expression: &OperatorNode) -> Result<Input, Error> {
-        match expression.expect_non_asap() {
-            NonASAPOp::Concat { children, .. } => {
-                if !children.iter().all(|branch| matches!(branch.expect_non_asap(),
-                    NonASAPOp::PromqlRelabel { child, .. } if matches!(child.expect_non_asap(),
-                        NonASAPOp::Aggregate { measures, .. } if matches!(measures.as_slice(), [AggIntent::HistogramQuantile { .. }])))) {
-                    return Err(invalid("PromQL concatenation requires classic histogram quantile branches"));
-                }
-                let inputs = children
-                    .iter()
-                    .map(|child| self.value(child))
-                    .collect::<Result<Vec<_>, _>>()?;
-                let output = declared(expression)?;
-                if inputs.iter().any(|input| self.schema(input) != output) {
-                    return Err(invalid(
-                        "concatenated PromQL branches require equal schemas",
-                    ));
-                }
-                let union = self.add(Operator::union(output.clone(), inputs.len())?, inputs);
-                // Multi-quantile branches drop the metric name and form one vector.
-                self.push(
-                    Operator::series_without_name(output)?,
-                    vec![union],
-                    expression,
-                )
-            }
-            NonASAPOp::PromqlRelabel { dst, value, child } => {
-                let step = self.value(child)?;
-                let input = self.schema(&step);
-                let (replacement, source_regex) = match value {
-                    ScalarExpr::Literal(planner_types::pre_asap::ScalarValue::Utf8(value)) => {
-                        (value.clone(), None)
-                    }
-                    ScalarExpr::FunctionCall { name, args } if name == "label_replace" => {
-                        let [ScalarExpr::Column(source), ScalarExpr::Literal(planner_types::pre_asap::ScalarValue::Utf8(
-                            pattern,
-                        )), ScalarExpr::Literal(planner_types::pre_asap::ScalarValue::Utf8(
-                            replacement,
-                        ))] = args.as_slice()
-                        else {
-                            return Err(invalid("invalid label_replace arguments"));
-                        };
-                        let source = input
-                            .fields
-                            .get(*source)
-                            .ok_or_else(|| invalid("label_replace source missing"))?
-                            .name
-                            .clone();
-                        (replacement.clone(), Some((source, pattern.clone())))
-                    }
-                    _ => return Err(invalid("unsupported PromQL label rewrite")),
-                };
-                let operator = Operator::series_relabel(
-                    input,
-                    declared(expression)?,
-                    dst.clone(),
-                    replacement,
-                    source_regex,
-                )?;
-                self.push(operator, vec![step], expression)
-            }
-            NonASAPOp::TimeRange { .. } => {
-                let (range, offset, at) = selector(expression)?;
-                let input = self.read(expression)?;
-                let schema = self.schema(&input);
-                self.push(
-                    Operator::series_window(schema, None, range, offset, at, None)?
-                        .with_series_range_bounds(range_anchor(expression), None)?,
-                    vec![input],
-                    expression,
-                )
-            }
-            NonASAPOp::Aggregate {
-                reduction: planner_types::pre_asap::Reduction::PerEntity,
-                measures,
-                having: None,
-                child,
-                filters,
-                ..
-            } if filters.iter().all(Option::is_none) => {
-                let [function] = measures.as_slice() else {
-                    return Err(invalid("range function requires one measure"));
-                };
-                let step = self.range_function(function, child, expression)?;
-                if matches!(function, AggIntent::LastOverTime) {
-                    return Ok(step);
-                }
-                // Other range functions drop the name; equal label sets then error.
-                let input = self.schema(&step);
-                Ok(self.add(Operator::series_without_name(input)?, vec![step]))
-            }
-            NonASAPOp::Aggregate {
-                reduction: planner_types::pre_asap::Reduction::Reduce(keys),
-                measures,
-                having: None,
-                child,
-                filters,
-                ..
-            } if filters.iter().all(Option::is_none) => {
-                let [measure] = measures.as_slice() else {
-                    return Err(invalid("vector aggregation requires one measure"));
-                };
-                let input = self.value(child)?;
-                self.aggregate(input, measure, keys, expression)
-            }
-            NonASAPOp::Project {
-                cols,
-                child,
-                qualifier,
-            } => {
-                let value = planner_types::pre_asap::column_resolution::resolve_column_ref(
-                    &ColumnRef::SampleValue,
-                    &child.schema,
-                )
-                .map_err(|e| invalid(e.to_string()))?;
-                let sample = cols
-                    .iter()
-                    .find(|col| {
-                        col.alias.as_deref() == Some(child.schema.fields[value].name.as_str())
-                    })
-                    .ok_or_else(|| invalid("missing sample projection"))?;
-                let keep_name = matches!(sample.expr, ScalarExpr::Negative { .. });
-                let fields: Vec<_> = child
-                    .schema
-                    .fields
-                    .iter()
-                    .enumerate()
-                    .filter(|(_, field)| keep_name || field.name != "__name__")
-                    .collect();
-                if qualifier.is_some() || cols.len() != fields.len() {
-                    return Err(invalid("unsupported temporal projection shape"));
-                }
-                let mut computed = None;
-                for (col, (index, field)) in cols.iter().zip(fields) {
-                    if col.alias.as_deref() != Some(field.name.as_str()) {
-                        return Err(invalid("unsupported temporal projection alias"));
-                    }
-                    if index == value {
-                        computed = Some(col);
-                    } else {
-                        let expected = if !keep_name
-                            && field.name == planner_types::pre_asap::schema::PROMQL_SERIES_IDENTITY
-                        {
-                            ScalarExpr::FunctionCall {
-                                name: "promql_drop_metric_name".into(),
-                                args: vec![ScalarExpr::Column(index)],
-                            }
-                        } else {
-                            ScalarExpr::Column(index)
-                        };
-                        if col.expr != expected {
-                            return Err(invalid("unsupported temporal projection expression"));
-                        }
-                    }
-                }
-                let computed = computed.ok_or_else(|| invalid("no computed sample"))?;
-                if matches!(
-                    computed.expr,
-                    ScalarExpr::Negative { .. } | ScalarExpr::FunctionCall { .. }
-                ) {
-                    return self.pointwise_projection(cols, child, value, expression, keep_name);
-                }
-                self.sample_scalar_operation(&computed.expr, child, value, expression)
-            }
-            NonASAPOp::Filter { pred, child } => {
-                let value = planner_types::pre_asap::column_resolution::resolve_column_ref(
-                    &ColumnRef::SampleValue,
-                    &child.schema,
-                )
-                .map_err(|e| invalid(e.to_string()))?;
-                self.sample_scalar_operation(&pred.0, child, value, expression)
-            }
-            NonASAPOp::Sort {
-                keys,
-                partition_by,
-                child,
-            } => {
-                let step = self.value(child)?;
-                let input = self.schema(&step);
-                let keys = keys
-                    .iter()
-                    .map(|key| match key.expr {
-                        ScalarExpr::Column(column) => Ok(SortKey {
-                            column,
-                            descending: !key.ascending,
-                            nulls_first: key.nulls_first,
-                        }),
-                        _ => Err(invalid("sort key must be a column")),
-                    })
-                    .collect::<Result<_, _>>()?;
-                let groups = groups(&input, partition_by)?;
-                self.push(Operator::sort(input, keys, groups)?, vec![step], expression)
-            }
-            NonASAPOp::Limit {
-                n, offset, child, ..
-            } => {
-                let step = self.value(child)?;
-                let input = self.schema(&step);
-                // `topk by (...)` partitions through the Sort it limits.
-                let groups = match child.expect_non_asap() {
-                    NonASAPOp::Sort { partition_by, .. } => groups(&input, partition_by)?,
-                    _ => vec![],
-                };
-                self.push(
-                    Operator::limit(
-                        input,
-                        n.unwrap_or(usize::MAX) as u64,
-                        *offset as u64,
-                        groups,
-                    )?,
-                    vec![step],
-                    expression,
-                )
-            }
-            NonASAPOp::BinaryOp {
-                operator,
-                lhs,
-                rhs,
-                return_bool,
-            } => {
-                let sides = vec![self.value(lhs)?, self.value(rhs)?];
-                let operator = crate::expressions::binary::BinaryOperator::from_logical(
-                    operator,
-                    *return_bool,
-                );
-                let binary = Operator::series_binary(
-                    self.schema(&sides[0]),
-                    self.schema(&sides[1]),
-                    operator,
-                    [false, false],
-                )?;
-                self.push(binary, sides, expression)
-            }
-            NonASAPOp::PromqlVectorFromScalar(expr) => {
-                let step = self.scalar_value(expr)?;
-                let input = self.schema(&step);
-                Ok(self.add(
-                    Operator::scope_timestamp(input, declared(expression)?)?,
-                    vec![step],
-                ))
-            }
-            _ => Err(invalid("PromQL expression has no native fallback lowering")),
-        }
-    }
-
-    fn pointwise_projection(
-        &mut self,
-        cols: &[planner_types::ir::ProjectItem],
-        child: &OperatorNode,
-        value: usize,
-        output: &OperatorNode,
-        keep_name: bool,
-    ) -> Result<Input, Error> {
-        let mut input = self.value(child)?;
-        let mut projected = cols.to_vec();
-        for col in &mut projected {
-            if col.alias.as_deref() != Some(child.schema.fields[value].name.as_str()) {
-                continue;
-            }
-            if let ScalarExpr::FunctionCall { name, args } = &mut col.expr {
-                if planner_types::pre_asap::scalar_type_rules::promql_function_arity(name).is_none()
-                    || args.first() != Some(&ScalarExpr::Column(value))
-                {
-                    return Err(invalid("unsupported pointwise function"));
-                }
-                for arg in args.iter_mut().skip(1) {
-                    let scalar = self.scalar_value(arg)?;
-                    let left = self.schema(&input);
-                    let right = self.schema(&scalar);
-                    let index = left.fields.len();
-                    let mut schema = (*left).clone();
-                    schema.fields.extend(right.fields.clone());
-                    let join = Operator::unified_relational_join(
-                        left,
-                        right,
-                        planner_types::pre_asap::JoinKind::Inner,
-                        &planner_types::ir::Predicate(ScalarExpr::Literal(
-                            planner_types::pre_asap::ScalarValue::Boolean(true),
-                        )),
-                        Arc::new(schema),
-                    )?;
-                    input = self.add(join, vec![input, scalar]);
-                    *arg = ScalarExpr::Column(index);
-                }
-                if name == "promql_clamp" {
-                    let predicate = ScalarExpr::Not(Box::new(ScalarExpr::Compare {
-                        left: Box::new(args[1].clone()),
-                        right: Box::new(args[2].clone()),
-                        op: planner_types::pre_asap::CompareOpKind::Gt,
-                        semantics: planner_types::ir::ExprSemantics::Promql,
-                    }));
-                    let schema = self.schema(&input);
-                    let predicate =
-                        crate::expressions::unified_planner::CompiledExpression::compile(
-                            &predicate, &schema,
-                        )?;
-                    input = self.add(
-                        Operator::filter(
-                            schema,
-                            crate::expressions::Expression::unified_planner(predicate),
-                        )?,
-                        vec![input],
-                    );
-                }
-            }
-        }
-        let schema = self.schema(&input);
-        let columns = projected
-            .iter()
-            .map(|col| {
-                Ok((
-                    col.alias.clone().unwrap(),
-                    crate::expressions::Expression::unified_planner(
-                        crate::expressions::unified_planner::CompiledExpression::compile(
-                            &col.expr, &schema,
-                        )?,
-                    ),
-                ))
-            })
-            .collect::<Result<Vec<_>, Error>>()?;
-        let project = Operator::project(schema, columns)?;
-        let result = self.push(project, vec![input], output)?;
-        if keep_name {
-            Ok(result)
-        } else {
-            self.push(
-                Operator::series_without_name(self.schema(&result))?,
-                vec![result],
-                output,
-            )
-        }
-    }
-
-    fn sample_scalar_operation(
-        &mut self,
-        expr: &ScalarExpr,
-        child: &OperatorNode,
-        value: usize,
-        output: &OperatorNode,
-    ) -> Result<Input, Error> {
-        let (left, right, kind) = scalar_binary(expr)?;
-        let (scalar, scalar_left) = match (left, right) {
-            (ScalarExpr::Column(i), scalar) if *i == value => (scalar, false),
-            (scalar, ScalarExpr::Column(i)) if *i == value => (scalar, true),
-            _ => {
-                return Err(invalid(
-                    "sample projection requires one vector sample and one scalar",
-                ))
-            }
-        };
-        let vector = self.value(child)?;
-        let scalar = self.scalar_value(scalar)?;
-        let sides = if scalar_left {
-            vec![scalar, vector]
-        } else {
-            vec![vector, scalar]
-        };
-        let operator = Operator::series_binary(
-            self.schema(&sides[0]),
-            self.schema(&sides[1]),
-            kernel(kind),
-            [scalar_left, !scalar_left],
-        )?;
-        self.push(operator, sides, output)
-    }
-
-    fn scalar_value(&mut self, expr: &ScalarExpr) -> Result<Input, Error> {
-        match expr {
-            ScalarExpr::Literal(planner_types::pre_asap::ScalarValue::Float64(value)) => Ok(self
-                .add(
-                    Operator::scalar(crate::values::Value::Float64(*value), DataType::Float64)?,
-                    vec![],
-                )),
-            ScalarExpr::EvalTimestamp => Ok(self.add(Operator::evaluation_time(), vec![])),
-            ScalarExpr::PromqlScalarFromVector(child) => {
-                let step = self.value(child)?;
-                let input = self.schema(&step);
-                let values: Vec<_> = input
-                    .fields
-                    .iter()
-                    .enumerate()
-                    .filter(|(_, f)| f.dtype == FieldDataType::Plain(DataType::Float64))
-                    .map(|(i, _)| i)
-                    .collect();
-                let [value] = values.as_slice() else {
-                    return Err(invalid("scalar() requires one float sample column"));
-                };
-                let value = *value;
-                Ok(self.add(Operator::vector_to_scalar(input, value)?, vec![step]))
-            }
-            ScalarExpr::Negative { expr, .. } => {
-                let value = self.scalar_value(expr)?;
-                let minus = self.scalar_value(&ScalarExpr::literal_f64(-1.0))?;
-                let op = Operator::series_binary(
-                    self.schema(&value),
-                    self.schema(&minus),
-                    kernel(crate::expressions::binary::BinaryOpKind::Arithmetic(
-                        planner_types::pre_asap::ArithmeticOpKind::Mul,
-                    )),
-                    [true, true],
-                )?;
-                Ok(self.add(op, vec![value, minus]))
-            }
-            _ => {
-                let (left, right, kind) = scalar_binary(expr)?;
-                let sides = vec![self.scalar_value(left)?, self.scalar_value(right)?];
-                let op = Operator::series_binary(
-                    self.schema(&sides[0]),
-                    self.schema(&sides[1]),
-                    kernel(kind),
-                    [true, true],
-                )?;
-                Ok(self.add(op, sides))
-            }
-        }
-    }
-
-    /// `function(matrix)`, where the matrix is a range selector or a subquery.
-    fn range_function(
-        &mut self,
-        function: &AggIntent,
-        matrix: &OperatorNode,
-        logical: &OperatorNode,
-    ) -> Result<Input, Error> {
-        let function = unbound(function)?;
-        let (subquery, offset, at_ms) = match matrix.expect_non_asap() {
-            NonASAPOp::TimeShift { shift, child } => (child.as_ref(), shift.offset_ms, at(shift)?),
-            _ => (matrix, 0, None),
-        };
-        let NonASAPOp::PromqlSubquery {
-            range: outer,
-            resolution,
-            child,
-        } = subquery.expect_non_asap()
-        else {
-            let (range, offset, at) = selector(matrix)?;
-            let input = self.read(matrix)?;
-            let schema = self.schema(&input);
-            return self.push(
-                Operator::series_window(schema, Some(function), range, offset, at, None)?
-                    .with_series_range_bounds(range_anchor(matrix), None)?,
-                vec![input],
-                logical,
-            );
-        };
-        let step = resolution.as_ref().ok_or_else(|| {
-            invalid("subquery resolution defaults to the deployment evaluation interval")
-        })?;
-        let steps = SubquerySteps {
-            range_ms: millis(outer)?,
-            step_ms: millis(step)?,
-            offset_ms: offset,
-            at_ms,
-        };
-        // Each step evaluates a per-series selection or range function.
-        let (inner, selected) = match child.expect_non_asap() {
-            NonASAPOp::Aggregate {
-                reduction: planner_types::pre_asap::Reduction::PerEntity,
-                measures,
-                having: None,
-                child: selected,
-                ..
-            } => match measures.as_slice() {
-                [inner] => (Some(unbound(inner)?), selected.as_ref()),
-                _ => return Err(invalid("range function requires one measure")),
-            },
-            _ => (None, child.as_ref()),
-        };
-        let (range, inner_offset, inner_at) = selector(selected)?;
-        let raw = self.read(selected)?;
-        let schema = self.schema(&raw);
-        let mut step = self.push(
-            Operator::series_window(
-                schema,
-                inner.clone(),
-                range,
-                inner_offset,
-                inner_at,
-                Some(steps),
-            )?
-            .with_series_range_bounds(range_anchor(selected), range_anchor(matrix))?,
-            vec![raw],
-            child,
-        )?;
-        // Name removal must validate each subquery evaluation step.
-        if inner.is_some() && !matches!(inner, Some(AggIntent::LastOverTime)) {
-            let input = self.schema(&step);
-            let relabel = Operator::series_without_name(input)?;
-            step = self.add(relabel, vec![step]);
-        }
-        let input = self.schema(&step);
-        self.push(
-            Operator::series_window(input, Some(function), steps.range_ms, offset, at_ms, None)?
-                .with_series_range_bounds(range_anchor(matrix), None)?,
-            vec![step],
-            logical,
-        )
-    }
-
-    /// Cross-series aggregation. A global aggregate groups by one constant so
-    /// that no input series yields an empty vector, not one row.
-    fn aggregate(
-        &mut self,
-        mut step: Input,
-        measure: &AggIntent,
-        keys: &GroupKeys,
-        logical: &OperatorNode,
-    ) -> Result<Input, Error> {
-        let mut input = self.schema(&step);
-        if let AggIntent::HistogramQuantile { q, le } = measure {
-            if !keys.is_without() || keys.keys() != [*le] {
-                return Err(invalid("histogram_quantile must group without (le)"));
-            }
-            let operator = Operator::series_histogram_quantile(input, *q, *le)?;
-            return self.push(operator, vec![step], logical);
-        }
-        let value = input
-            .fields
-            .iter()
-            .enumerate()
-            .filter(|(_, f)| f.dtype == FieldDataType::Plain(DataType::Float64))
-            .map(|(i, _)| i)
-            .collect::<Vec<_>>();
-        let [value] = value.as_slice() else {
-            return Err(invalid("PromQL aggregation requires one Float64 value"));
-        };
-        let value = *value;
-        let reduction = match measure {
-            AggIntent::Sum { .. } => Reduction::Sum(value),
-            AggIntent::Avg { .. } => Reduction::Avg(value),
-            AggIntent::Min { .. } => Reduction::Min(value),
-            AggIntent::Max { .. } => Reduction::Max(value),
-            AggIntent::Count { .. } => Reduction::Count,
-            _ => return Err(invalid("vector aggregate has no native lowering")),
-        };
-        let mut groups = if keys.is_without() {
-            // Group by every remaining label, including the rewritten identity.
-            let excluded = keys.keys();
-            if excluded.iter().any(|&i| i >= input.fields.len()) {
-                return Err(invalid("grouping column out of range"));
-            }
-            let names = excluded.iter().map(|&i| input.fields[i].name.clone());
-            let relabel =
-                Operator::series_labels(input.clone(), VectorMatchKind::Ignoring, names.collect())?;
-            step = self.add(relabel, vec![step]);
-            (0..input.fields.len())
-                .filter(|&i| Some(i) != input.time_index && i != value && !excluded.contains(&i))
-                .collect()
-        } else {
-            groups(&input, keys)?
-        };
-        let global = groups.is_empty();
-        if global {
-            let mut columns = (0..input.fields.len())
-                .map(|i| (input.fields[i].name.clone(), Expression::Column(i)))
-                .collect::<Vec<_>>();
-            columns.push((
-                "$promql_global_group".into(),
-                Expression::Literal {
-                    value: crate::values::Value::Utf8("".into()),
-                    dtype: DataType::Utf8,
-                },
-            ));
-            let project = Operator::project(input, columns)?;
-            input = project.schema();
-            groups = vec![input.fields.len() - 1];
-            step = self.add(project, vec![step]);
-        }
-        let output = declared(logical)?;
-        let name = output
-            .fields
-            .last()
-            .ok_or_else(|| invalid("aggregate output lacks a value"))?
-            .name
-            .clone();
-        let aggregate = Operator::aggregate(input, groups, vec![(name, reduction)])?;
-        let actual = aggregate.schema();
-        let step = self.add(aggregate, vec![step]);
-        // Drop the constant group; convert counts where PromQL declares Float64.
-        let skip = usize::from(global);
-        let columns = actual.fields[skip..]
-            .iter()
-            .zip(&output.fields)
-            .enumerate()
-            .map(|(i, (field, declared))| {
-                let column = i + skip;
-                let expression = if field.dtype != declared.dtype {
-                    Expression::ExactFloat64(column)
-                } else {
-                    Expression::Column(column)
-                };
-                (field.name.clone(), expression)
-            })
-            .collect();
-        self.push(Operator::project(actual, columns)?, vec![step], logical)
-    }
-}
-
-fn unbound(intent: &AggIntent) -> Result<AggIntent<ColumnRef>, Error> {
-    Ok(match intent {
-        AggIntent::Rate => AggIntent::Rate,
-        AggIntent::Deriv => AggIntent::Deriv,
-        AggIntent::PredictLinear { seconds } => AggIntent::PredictLinear { seconds: *seconds },
-        AggIntent::Increase => AggIntent::Increase,
-        AggIntent::Delta => AggIntent::Delta,
-        AggIntent::Count { accuracy } => AggIntent::Count {
-            accuracy: accuracy.clone(),
-        },
-        AggIntent::Sum { .. } => AggIntent::Sum { col: None },
-        AggIntent::Avg { .. } => AggIntent::Avg { col: None },
-        AggIntent::Min { .. } => AggIntent::Min { col: None },
-        AggIntent::Max { .. } => AggIntent::Max { col: None },
-        AggIntent::IRate => AggIntent::IRate,
-        AggIntent::IDelta => AggIntent::IDelta,
-        AggIntent::Changes => AggIntent::Changes,
-        AggIntent::Resets => AggIntent::Resets,
-        AggIntent::LastOverTime => AggIntent::LastOverTime,
-        AggIntent::Quantile {
-            col: None,
-            q,
-            accuracy,
-        } => AggIntent::Quantile {
-            col: None,
-            q: *q,
-            accuracy: accuracy.clone(),
-        },
-        _ => return Err(invalid("unsupported PromQL range function")),
-    })
-}
-
-fn kernel(
-    kind: crate::expressions::binary::BinaryOpKind,
-) -> crate::expressions::binary::BinaryOperator {
-    crate::expressions::binary::BinaryOperator {
-        kind,
-        vector_match: None,
-        checked_relative_division: false,
-        checked_finite_division: false,
-    }
-}
-
-fn scalar_binary(
-    expr: &ScalarExpr,
-) -> Result<
-    (
-        &ScalarExpr,
-        &ScalarExpr,
-        crate::expressions::binary::BinaryOpKind,
-    ),
-    Error,
-> {
-    use crate::expressions::binary::BinaryOpKind as K;
-    match expr {
-        ScalarExpr::Arithmetic {
-            left,
-            right,
-            op,
-            semantics: planner_types::ir::ExprSemantics::Promql,
-        } => Ok((left, right, K::Arithmetic(op.clone()))),
-        ScalarExpr::Compare {
-            left,
-            right,
-            op,
-            semantics: planner_types::ir::ExprSemantics::Promql,
-        } => Ok((left, right, K::Compare(op.clone()))),
-        ScalarExpr::Case {
-            operand: None,
-            branches,
-            else_expr,
-        } if matches!(else_expr.as_deref(), Some(ScalarExpr::Literal(planner_types::pre_asap::ScalarValue::Float64(v))) if *v == 0.0) =>
-        {
-            let [(
-                ScalarExpr::Compare {
-                    left,
-                    right,
-                    op,
-                    semantics: planner_types::ir::ExprSemantics::Promql,
-                },
-                ScalarExpr::Literal(planner_types::pre_asap::ScalarValue::Float64(v)),
-            )] = branches.as_slice()
-            else {
-                return Err(invalid("unsupported scalar case"));
-            };
-            if *v != 1.0 {
-                return Err(invalid("unsupported scalar case result"));
-            }
-            Ok((left, right, K::CompareBool(op.clone())))
-        }
-        _ => Err(invalid("scalar expression has no native temporal lowering")),
-    }
-}
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/promql_rows.rs b/crates/asap-physical-operators/src/unified_physical_planner/promql_rows.rs
deleted file mode 100644
index 20992dfe7..000000000
--- a/crates/asap-physical-operators/src/unified_physical_planner/promql_rows.rs
+++ /dev/null
@@ -1,308 +0,0 @@
-//! A bounded PromQL source row carries the entire label set, not just labels
-//! mentioned by the query. The source adapter owns this lossless encoding.
-use super::*;
-use planner_types::ir::export::{
-    compile_physical_asap_dag, compile_physical_asap_dag_with_node_ids,
-};
-use planner_types::post_asap::FieldDataType as SummaryFamilyType;
-use planner_types::pre_asap::DataType;
-use std::rc::Rc;
-
-/// Not a legal PromQL label name, so it cannot shadow a user label.
-pub use planner_types::pre_asap::schema::PROMQL_SERIES_IDENTITY as SERIES_IDENTITY_COLUMN;
-
-/// Canonical, reversible identity. JSON object encoding preserves label names,
-/// empty values and escaping; sorting makes ingestion order irrelevant.
-pub fn encode_series_identity(labels: &BTreeMap<String, String>) -> Result<String, Error> {
-    serde_json::to_string(labels).map_err(|error| invalid(error.to_string()))
-}
-
-pub fn decode_series_identity(encoded: &str) -> Result<BTreeMap<String, String>, Error> {
-    let labels: BTreeMap<String, String> =
-        serde_json::from_str(encoded).map_err(|error| invalid(error.to_string()))?;
-    if encode_series_identity(&labels)? != encoded {
-        return Err(invalid("series identity is not canonically encoded"));
-    }
-    Ok(labels)
-}
-
-/// Resolve the row representation before candidate search; see
-/// [`planner_types::ir::schema_support::with_promql_series_identity`].
-pub fn with_series_identity(root: &Rc<OperatorNode>) -> Result<Rc<OperatorNode>, Error> {
-    planner_types::ir::schema_support::with_promql_series_identity(root).map_err(invalid)
-}
-
-/// Construct source rows only from full identities. The named label columns
-/// are projections of that same identity and cannot independently redefine it.
-pub fn series_row(
-    schema: &SchemaRef,
-    labels: &BTreeMap<String, String>,
-    timestamp: i64,
-    value: f64,
-) -> Result<Vec<crate::values::Value>, Error> {
-    use crate::values::Value;
-    let identity = encode_series_identity(labels)?;
-    let mut found = false;
-    let row = schema
-        .fields
-        .iter()
-        .enumerate()
-        .map(|(index, field)| {
-            if field.name == SERIES_IDENTITY_COLUMN {
-                if field.dtype != SummaryFamilyType::Plain(DataType::Utf8)
-                    || field.nullable
-                    || found
-                {
-                    return Err(invalid("invalid series identity column"));
-                }
-                found = true;
-                Ok(Value::Utf8(identity.clone().into()))
-            } else if Some(index) == schema.time_index {
-                Ok(Value::Timestamp(timestamp))
-            } else if field.name == "value"
-                && field.dtype == SummaryFamilyType::Plain(DataType::Float64)
-            {
-                Ok(Value::Float64(value))
-            } else if field.dtype == SummaryFamilyType::Plain(DataType::Utf8) {
-                Ok(labels.get(&field.name).map_or_else(
-                    || Value::Utf8("".into()),
-                    |value| Value::Utf8(value.clone().into()),
-                ))
-            } else {
-                Err(invalid("unsupported PromQL source column"))
-            }
-        })
-        .collect::<Result<Vec<_>, _>>()?;
-    if !found {
-        return Err(invalid("source lacks its full series identity"));
-    }
-    Ok(row)
-}
-
-/// Compile the selected TopK computation above an existing maintained-population
-/// source. The boundary supplies the complete eligible vector, not a truncated
-/// TopK result; ranking remains a native physical operator.
-pub fn compile_current_series_evaluation(
-    selected: &Rc<OperatorNode>,
-) -> Result<CompiledPhysicalDAG, Error> {
-    use planner_types::post_asap::{
-        maintained_population::PopulationStatistic, Field as SummaryField,
-    };
-    let selected = planner_types::ir::apply_lifecycle_timings(
-        selected,
-        &planner_types::ir::LifecycleAssignment::default_maintained(),
-        &mut planner_types::ir::TimingMemo::new(),
-    )
-    .map_err(|e| invalid(e.to_string()))?;
-    let mut dag =
-        compile_physical_asap_dag(&selected).map_err(|error| invalid(error.to_string()))?;
-    // Typed snapshot candidates already carry full identity throughout the DAG.
-    // Cut at the population output, preserving all selected heap/evaluation nodes.
-    let populations = dag.nodes.iter().filter(|node| matches!(&node.payload,
-        Payload::MaintainPopulation { population }
-            if matches!(population.input, planner_types::post_asap::maintained_population::PopulationInput::CurrentSeries(_))
-    )).collect::<Vec<_>>();
-    if let [population] = populations.as_slice() {
-        if population
-            .output_schema
-            .fields
-            .iter()
-            .any(|field| field.name == SERIES_IDENTITY_COLUMN)
-        {
-            return compile(
-                &dag,
-                BTreeMap::from([(
-                    u64::from(population.id.0),
-                    InputContract::bounded(Arc::new(population.output_schema.clone())),
-                )]),
-                &dag.roots.iter().map(|r| u64::from(r.0)).collect::<Vec<_>>(),
-            );
-        }
-    }
-    let mut frontier = None;
-    for node in &mut dag.nodes {
-        match &mut node.payload {
-            Payload::Relational { operator } => {
-                if let NonASAPOpKind::Scan { schema, .. } = operator {
-                    schema.fields.push(SummaryField::new(
-                        SERIES_IDENTITY_COLUMN,
-                        SummaryFamilyType::Plain(DataType::Utf8),
-                        false,
-                    ));
-                    schema.closed = true;
-                }
-            }
-            Payload::MaintainPopulation { .. } => {
-                frontier = Some(u64::from(node.id.0));
-            }
-            Payload::EvaluatePopulation {
-                evaluation: PopulationStatistic::TopK { .. },
-            } => {}
-            _ => return Err(invalid("unsupported current-series evaluation dependency")),
-        }
-        if node
-            .output_schema
-            .fields
-            .iter()
-            .any(|field| field.name == SERIES_IDENTITY_COLUMN)
-        {
-            return Err(invalid(
-                "current-series input already has a physical identity column",
-            ));
-        }
-        node.output_schema.fields.push(SummaryField {
-            name: SERIES_IDENTITY_COLUMN.into(),
-            dtype: SummaryFamilyType::Plain(DataType::Utf8),
-            nullable: false,
-            table: None,
-        });
-    }
-    for edge in &mut dag.edges {
-        edge.intermediate_schema = dag
-            .nodes
-            .iter()
-            .find(|node| node.id == edge.producer)
-            .unwrap()
-            .output_schema
-            .clone();
-    }
-    let frontier = frontier.ok_or_else(|| invalid("missing current-series population"))?;
-    let schema = Arc::new(
-        dag.nodes
-            .iter()
-            .find(|node| u64::from(node.id.0) == frontier)
-            .unwrap()
-            .output_schema
-            .clone(),
-    );
-    compile(
-        &dag,
-        BTreeMap::from([(frontier, InputContract::bounded(schema))]),
-        &dag.roots.iter().map(|r| u64::from(r.0)).collect::<Vec<_>>(),
-    )
-}
-
-/// Compile selected ranking or aggregation above an exact per-series Rate
-/// evaluation. Deployments bind complete window evaluations at this boundary;
-/// the heap is rebuilt independently for each evaluation. This does not move
-/// that frontier to ingestion time or authorize combining finalized rates.
-pub fn compile_rate_ranking(
-    selected: &Rc<OperatorNode>,
-) -> Result<(Rc<OperatorNode>, CompiledPhysicalDAG), Error> {
-    use planner_types::post_asap::ExactKind;
-    fn frontier(node: &Rc<OperatorNode>) -> Option<Rc<OperatorNode>> {
-        if matches!(&node.operator, LogicalOperator::ASAP(ASAPOp::FinalizeExactAccumulator { child })
-            if matches!(&child.operator, LogicalOperator::ASAP(ASAPOp::SummaryAgg {
-                family: FieldDataType::ExactAggregate(ExactKind::Rate, _),
-                reduction: planner_types::pre_asap::Reduction::PerEntity, child: raw, ..
-            }) if matches!(raw.non_asap(), Some(NonASAPOp::TimeRange { .. }))))
-        {
-            return Some(Rc::clone(node));
-        }
-        node.children().into_iter().find_map(frontier)
-    }
-    let selected = planner_types::ir::apply_lifecycle_timings(
-        selected,
-        &planner_types::ir::LifecycleAssignment::default_maintained(),
-        &mut planner_types::ir::TimingMemo::new(),
-    )
-    .map_err(|e| invalid(e.to_string()))?;
-    let source = frontier(&selected)
-        .ok_or_else(|| invalid("ranking requires one exact per-series Rate frontier"))?;
-    if !source
-        .schema
-        .fields
-        .iter()
-        .any(|field| field.name == SERIES_IDENTITY_COLUMN)
-    {
-        return Err(invalid("Rate ranking requires complete series identity"));
-    }
-    let compiled = compile_physical_asap_dag_with_node_ids(&selected)
-        .map_err(|error| invalid(error.to_string()))?;
-    let id = u64::from(
-        compiled
-            .node_ids
-            .node_id(&source)
-            .ok_or_else(|| invalid("missing Rate frontier"))?
-            .0,
-    );
-    let program = compile(
-        &compiled.dag,
-        BTreeMap::from([(id, InputContract::bounded(Arc::new(source.schema.clone())))]),
-        &compiled
-            .dag
-            .roots
-            .iter()
-            .map(|r| u64::from(r.0))
-            .collect::<Vec<_>>(),
-    )?;
-    Ok((source, program))
-}
-
-/// Compile a lifecycle-timed DAG whose heap or grouped Sum over per-series
-/// Rate evaluations runs at ingestion time: fresh aggregate state per closed
-/// window. The input is the complete collection of per-series counter states.
-pub fn compile_fixed_window_rate_aggregation(
-    dag: &planner_types::ir::export::PhysicalASAPDAG,
-) -> Result<CompiledPhysicalPlan, Error> {
-    use planner_types::post_asap::{ExactKind, ExecutionTiming, SketchAlgorithm};
-    let sources = dag
-        .nodes
-        .iter()
-        .filter(|n| {
-            matches!(
-                &n.payload,
-                Payload::SummaryAgg {
-                    family: SummaryFamilyType::ExactAggregate(ExactKind::Rate, _),
-                    reduction: planner_types::pre_asap::Reduction::PerEntity,
-                    ..
-                }
-            )
-        })
-        .collect::<Vec<_>>();
-    let heaps = dag
-        .nodes
-        .iter()
-        .filter(|n| {
-            n.output_state.timing == ExecutionTiming::IngestionTime
-                && match &n.payload {
-                    Payload::SummaryAgg {
-                        family: SummaryFamilyType::Sketch(kind, _),
-                        ..
-                    } => matches!(
-                        kind.algorithm(),
-                        SketchAlgorithm::CmsWithHeap | SketchAlgorithm::CountSketchWithHeap
-                    ),
-                    Payload::SummaryAgg {
-                        family: SummaryFamilyType::ExactAggregate(ExactKind::Sum, _),
-                        ..
-                    } => true,
-                    _ => false,
-                }
-        })
-        .collect::<Vec<_>>();
-    let ([source], [heap]) = (sources.as_slice(), heaps.as_slice()) else {
-        return Err(invalid(
-            "expected one selected fixed-window Rate aggregation",
-        ));
-    };
-    if !source
-        .output_schema
-        .fields
-        .iter()
-        .any(|f| f.name == SERIES_IDENTITY_COLUMN)
-    {
-        return Err(invalid(
-            "fixed-window Rate aggregation requires complete series identity",
-        ));
-    }
-    compile_candidate(
-        dag,
-        BTreeMap::from([(
-            u64::from(source.id.0),
-            InputContract::bounded(Arc::new(source.output_schema.clone())),
-        )]),
-        &dag.roots.iter().map(|r| u64::from(r.0)).collect::<Vec<_>>(),
-        &[u64::from(heap.id.0)],
-    )
-}
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/promql_values.rs b/crates/asap-physical-operators/src/unified_physical_planner/promql_values.rs
deleted file mode 100644
index 223d7f15c..000000000
--- a/crates/asap-physical-operators/src/unified_physical_planner/promql_values.rs
+++ /dev/null
@@ -1,281 +0,0 @@
-//! Physical scalar/vector contracts preserve complete label sets across native computation.
-use super::*;
-use planner_types::post_asap::FieldDataType as SummaryFamilyType;
-
-pub fn scalar_schema() -> SchemaRef {
-    crate::operators::vector_binary::value_schema(true)
-}
-pub fn vector_schema() -> SchemaRef {
-    crate::operators::vector_binary::value_schema(false)
-}
-
-pub fn matrix_schema() -> SchemaRef {
-    crate::operators::vector_window::matrix_schema()
-}
-
-pub fn compile_scalar(value: f64) -> Result<CompiledPhysicalDAG, Error> {
-    let operator = Operator::scalar(
-        crate::values::Value::Float64(value),
-        planner_types::pre_asap::DataType::Float64,
-    )?
-    .with_output_schema(scalar_schema())?;
-    CompiledPhysicalDAG::from_operators(
-        BTreeMap::new(),
-        BTreeMap::from([(0, (vec![], operator))]),
-        vec![0],
-    )
-}
-
-pub fn compile_temporal(
-    intent: &AggIntent<ColumnRef>,
-    preserve_metric_name: bool,
-) -> Result<CompiledPhysicalDAG, Error> {
-    let operator = Operator::range_window(intent.clone())?;
-    let mut operators = vec![operator];
-    if !preserve_metric_name {
-        operators.push(Operator::project(
-            vector_schema(),
-            vec![
-                (
-                    "labels".into(),
-                    Expression::LabelSet {
-                        column: 0,
-                        labels: vec![],
-                        without: true,
-                    },
-                ),
-                ("value".into(), Expression::Column(1)),
-            ],
-        )?);
-    }
-    unary(operators, matrix_schema())
-}
-
-pub fn compile_histogram_quantile() -> Result<CompiledPhysicalDAG, Error> {
-    CompiledPhysicalDAG::from_operators(
-        BTreeMap::from([
-            (0, InputContract::bounded(scalar_schema())),
-            (1, InputContract::bounded(vector_schema())),
-        ]),
-        BTreeMap::from([(2, (vec![0, 1], Operator::histogram_quantile()))]),
-        vec![2],
-    )
-}
-
-/// Compile before deployment chooses readers. Input slots 0 and 1 retain operand order.
-pub fn compile_binary(
-    operator: &crate::expressions::binary::BinaryOperator,
-    return_bool: bool,
-    left_scalar: bool,
-    right_scalar: bool,
-) -> Result<CompiledPhysicalDAG, Error> {
-    let left = crate::operators::vector_binary::value_schema(left_scalar);
-    let right = crate::operators::vector_binary::value_schema(right_scalar);
-    let op = Operator::vector_binary(left.clone(), right.clone(), operator.clone(), return_bool)?;
-    CompiledPhysicalDAG::from_operators(
-        BTreeMap::from([
-            (0, InputContract::bounded(left)),
-            (1, InputContract::bounded(right)),
-        ]),
-        BTreeMap::from([(2, (vec![0, 1], op))]),
-        vec![2],
-    )
-}
-
-fn unary(operators: Vec<Operator>, input: SchemaRef) -> Result<CompiledPhysicalDAG, Error> {
-    let root = operators.len() as u64;
-    CompiledPhysicalDAG::from_operators(
-        BTreeMap::from([(0, InputContract::bounded(input))]),
-        operators
-            .into_iter()
-            .enumerate()
-            .map(|(i, op)| ((i + 1) as u64, (vec![i as u64], op)))
-            .collect(),
-        vec![root],
-    )
-}
-
-fn grouped(grouping: &GroupKeys<ColumnRef>) -> Result<Operator, Error> {
-    let labels = grouping
-        .keys()
-        .iter()
-        .map(|key| match key {
-            ColumnRef::Named(label) => Ok(label.clone()),
-            _ => Err(invalid("vector grouping requires label names")),
-        })
-        .collect::<Result<Vec<_>, _>>()?;
-    Operator::project(
-        vector_schema(),
-        vec![
-            ("labels".into(), Expression::Column(0)),
-            ("value".into(), Expression::Column(1)),
-            (
-                "group".into(),
-                Expression::LabelSet {
-                    column: 0,
-                    labels,
-                    without: grouping.is_without(),
-                },
-            ),
-        ],
-    )
-}
-
-fn vector_output(input: SchemaRef, labels: usize, value: usize) -> Result<Operator, Error> {
-    let value = Expression::ExactFloat64(value);
-    Operator::project(
-        input,
-        vec![
-            ("labels".into(), Expression::Column(labels)),
-            ("value".into(), value),
-        ],
-    )
-}
-
-pub fn compile_aggregate(
-    intent: &AggIntent<ColumnRef>,
-    grouping: &GroupKeys<ColumnRef>,
-) -> Result<CompiledPhysicalDAG, Error> {
-    let project = grouped(grouping)?;
-    let reduction = match intent {
-        AggIntent::Sum { .. } => Reduction::Sum(1),
-        AggIntent::Avg { .. } => Reduction::Avg(1),
-        AggIntent::Count { .. } => Reduction::Count,
-        AggIntent::Min { .. } => Reduction::Min(1),
-        AggIntent::Max { .. } => Reduction::Max(1),
-        _ => return Err(invalid("unsupported vector aggregate")),
-    };
-    let aggregate =
-        Operator::aggregate(project.schema(), vec![2], vec![("value".into(), reduction)])?;
-    let output = vector_output(aggregate.schema(), 0, 1)?;
-    unary(vec![project, aggregate, output], vector_schema())
-}
-
-pub fn compile_sort(
-    descending: bool,
-    grouping: &GroupKeys<ColumnRef>,
-) -> Result<CompiledPhysicalDAG, Error> {
-    let project = grouped(grouping)?;
-    let sort = Operator::sort(
-        project.schema(),
-        vec![SortKey {
-            column: 1,
-            descending,
-            nulls_first: false,
-        }],
-        vec![2],
-    )?;
-    let output = vector_output(sort.schema(), 0, 1)?;
-    unary(vec![project, sort, output], vector_schema())
-}
-
-pub fn compile_limit(
-    n: u64,
-    offset: u64,
-    grouping: &GroupKeys<ColumnRef>,
-) -> Result<CompiledPhysicalDAG, Error> {
-    let project = grouped(grouping)?;
-    let limit = Operator::limit(project.schema(), n, offset, vec![2])?;
-    let output = vector_output(limit.schema(), 0, 1)?;
-    unary(vec![project, limit, output], vector_schema())
-}
-
-pub fn compile_negate(scalar: bool) -> Result<CompiledPhysicalDAG, Error> {
-    let input = if scalar {
-        scalar_schema()
-    } else {
-        vector_schema()
-    };
-    let mut columns = Vec::new();
-    if !scalar {
-        columns.push(("labels".into(), Expression::Column(0)));
-    }
-    columns.push((
-        if scalar {
-            "$promql_scalar".into()
-        } else {
-            "value".into()
-        },
-        Expression::Negate(Box::new(Expression::Column(if scalar { 0 } else { 1 }))),
-    ));
-    unary(vec![Operator::project(input.clone(), columns)?], input)
-}
-
-pub fn compile_vector_to_scalar() -> Result<CompiledPhysicalDAG, Error> {
-    unary(
-        vec![Operator::vector_to_scalar(vector_schema(), 1)?.with_output_schema(scalar_schema())?],
-        vector_schema(),
-    )
-}
-
-/// A stored exact-state input retains the complete population identity. The
-/// deployment supplies eligible panes; merging and finalization are computation.
-pub fn exact_state_schema(family: SummaryFamilyType) -> Result<SchemaRef, Error> {
-    if !matches!(family, SummaryFamilyType::ExactAggregate(..)) {
-        return Err(invalid("exact-state input requires an exact family"));
-    }
-    crate::values::validate_family(&family)?;
-    let mut schema = (*vector_schema()).clone();
-    schema.fields[1].dtype = family;
-    Ok(Arc::new(schema))
-}
-
-/// Retain exact evaluation semantics before any deployment state is opened.
-pub fn compile_exact_evaluation(
-    family: SummaryFamilyType,
-    lookback_ms: u64,
-    preserve_metric_name: bool,
-) -> Result<CompiledPhysicalDAG, Error> {
-    use planner_types::post_asap::ExactKind;
-    let statistic = match &family {
-        SummaryFamilyType::ExactAggregate(kind, _) => match kind {
-            ExactKind::Sum => crate::Statistic::Sum,
-            ExactKind::Count => crate::Statistic::Count,
-            ExactKind::Min => crate::Statistic::Min,
-            ExactKind::Max => crate::Statistic::Max,
-            ExactKind::Rate => crate::Statistic::Rate,
-            ExactKind::Increase => crate::Statistic::Increase,
-            ExactKind::IRate => {
-                return Err(invalid("instant-rate state evaluation is not supported"))
-            }
-        },
-        _ => return Err(invalid("exact evaluation requires an exact family")),
-    };
-    let input = exact_state_schema(family)?;
-    let merge = Operator::summary_merge(input.clone(), 1, vec![0])?;
-    let mut evaluation = Operator::readout(
-        merge.schema(),
-        1,
-        ReadoutQuery::Exact(ExactReadout {
-            statistic,
-            lookback_ms: None,
-        }),
-    )?;
-    if matches!(
-        statistic,
-        crate::Statistic::Rate | crate::Statistic::Increase
-    ) {
-        evaluation = evaluation.with_counter_lookback(
-            i64::try_from(lookback_ms).map_err(|_| invalid("counter lookback exceeds Int64"))?,
-        )?;
-    }
-    let project = Operator::project(
-        evaluation.schema(),
-        vec![
-            (
-                "labels".into(),
-                if preserve_metric_name {
-                    Expression::Column(0)
-                } else {
-                    Expression::LabelSet {
-                        column: 0,
-                        labels: vec![],
-                        without: true,
-                    }
-                },
-            ),
-            ("value".into(), Expression::ExactFloat64(1)),
-        ],
-    )?;
-    unary(vec![merge, evaluation, project], input)
-}
diff --git a/crates/asap-physical-operators/src/unified_physical_planner/row_values.rs b/crates/asap-physical-operators/src/unified_physical_planner/row_values.rs
deleted file mode 100644
index 14f3d4813..000000000
--- a/crates/asap-physical-operators/src/unified_physical_planner/row_values.rs
+++ /dev/null
@@ -1,60 +0,0 @@
-//! Query-time PromQL value computation over logical row schemas.
-use super::*;
-use planner_types::post_asap::maintained_population::PopulationStatistic;
-use planner_types::pre_asap::DataType;
-
-/// Aggregate evaluations of a maintained current-series population, as a chain.
-pub(super) fn population_aggregate(
-    input: &SchemaRef,
-    grouping: &[String],
-    evaluation: &PopulationStatistic,
-) -> Result<Vec<Operator>, Error> {
-    let groups = grouping
-        .iter()
-        .map(|name| named_column(input, &ColumnRef::Named(name.clone())))
-        .collect::<Result<Vec<_>, _>>()?;
-    let value = named_column(input, &ColumnRef::SampleValue)?;
-    let reduction = match evaluation {
-        PopulationStatistic::Sum => Reduction::Sum(value),
-        PopulationStatistic::Count => Reduction::Count,
-        PopulationStatistic::Average => Reduction::Avg(value),
-        PopulationStatistic::Quantile { q } => Reduction::Quantile {
-            column: value,
-            q: *q,
-        },
-        PopulationStatistic::TopK { .. } => {
-            return Err(invalid(
-                "TopK population evaluation ranks; it does not aggregate",
-            ))
-        }
-    };
-    if !groups.is_empty() {
-        return Ok(vec![Operator::aggregate(
-            input.clone(),
-            groups,
-            vec![("value".into(), reduction)],
-        )?]);
-    }
-    // A global aggregate over no members is an empty PromQL vector, not one row.
-    let aggregate = Operator::aggregate(
-        input.clone(),
-        vec![],
-        vec![
-            ("value".into(), reduction),
-            ("members".into(), Reduction::Count),
-        ],
-    )?;
-    let zero = Expression::Literal {
-        value: crate::values::Value::Int64(0),
-        dtype: DataType::Int64,
-    };
-    let filter = Operator::filter(
-        aggregate.schema(),
-        Expression::Less(Box::new(zero), Box::new(Expression::Column(1))),
-    )?;
-    let project = Operator::project(
-        filter.schema(),
-        vec![("value".into(), Expression::Column(0))],
-    )?;
-    Ok(vec![aggregate, filter, project])
-}
diff --git a/crates/asap-physical-operators/src/unified_sources/memory.rs b/crates/asap-physical-operators/src/unified_sources/memory.rs
deleted file mode 100644
index 856c73cb0..000000000
--- a/crates/asap-physical-operators/src/unified_sources/memory.rs
+++ /dev/null
@@ -1,44 +0,0 @@
-use super::*;
-/// Immutable in-memory raw data. The connector owns the resident input; each
-/// cursor clones only the next requested batch, not the entire data set.
-pub struct MemorySource {
-    schema: SchemaRef,
-    batches: Vec<Batch>,
-}
-impl MemorySource {
-    pub fn new(schema: SchemaRef, batches: Vec<Batch>) -> Result<Self, Error> {
-        crate::values::validate_schema(&schema)?;
-        if schema
-            .fields
-            .iter()
-            .any(|f| !matches!(f.dtype, SummaryFamilyType::Plain(_)))
-        {
-            return Err(Error::Invalid(
-                "raw source cannot contain summary states".into(),
-            ));
-        }
-        if batches.iter().any(|batch| batch.schema() != &schema) {
-            return Err(Error::Invalid("memory source batch schema mismatch".into()));
-        }
-        Ok(Self { schema, batches })
-    }
-}
-impl RawSource for MemorySource {
-    fn boundedness(&self) -> crate::plan::Boundedness {
-        crate::plan::Boundedness::Bounded
-    }
-    fn schema(&self) -> SchemaRef {
-        self.schema.clone()
-    }
-    fn scan(&self, context: RunContext) -> Result<OutputStream<'_, Batch>, Error> {
-        Ok(stream::iter(self.batches.iter())
-            .map(move |batch| {
-                if context.is_cancelled() {
-                    return Err(Error::Cancelled);
-                }
-                let _allocation = context.reserve(batch.bytes())?;
-                Ok(batch.clone())
-            })
-            .boxed_local())
-    }
-}
diff --git a/crates/asap-physical-operators/src/unified_sources/mod.rs b/crates/asap-physical-operators/src/unified_sources/mod.rs
deleted file mode 100644
index 9dbe62c15..000000000
--- a/crates/asap-physical-operators/src/unified_sources/mod.rs
+++ /dev/null
@@ -1,177 +0,0 @@
-//! Raw data access. Connectors provide rows; Scan owns Planner predicate semantics.
-use crate::{
-    expressions::unified_planner::CompiledExpression,
-    plan::PhysicalOperator,
-    runtime::{Input, OutputStream, RunContext},
-    values::{Batch, SchemaRef, Value},
-    Error,
-};
-use futures::{stream, StreamExt};
-use planner_types::ir::{NonASAPOp, OperatorNode};
-use planner_types::{
-    post_asap::FieldDataType as SummaryFamilyType,
-    pre_asap::{DataType, Source},
-};
-use std::sync::Arc;
-
-/// A bound data source. Metadata must be stable for the lifetime of the binding.
-/// Each scan opens an independent cursor. Connectors return raw, unfiltered rows
-/// and must honor cancellation and bound their own I/O buffers. Dropping a cursor
-/// must release its resources. A connector error is never an empty successful scan.
-pub trait RawSource {
-    fn schema(&self) -> SchemaRef;
-    /// Declare a finite snapshot/window explicitly; execution scope alone does not bound a cursor.
-    fn boundedness(&self) -> crate::plan::Boundedness {
-        crate::plan::Boundedness::Unknown
-    }
-    fn scan(&self, context: RunContext) -> Result<OutputStream<'_, Batch>, Error>;
-}
-
-/// Explicit source identities; no implicit network discovery or fallback.
-#[derive(Default)]
-pub struct DataSources {
-    sources: Vec<(Source, Arc<dyn RawSource>)>,
-}
-impl DataSources {
-    pub fn register(&mut self, identity: Source, source: Arc<dyn RawSource>) -> Result<(), Error> {
-        if self.sources.iter().any(|(key, _)| key == &identity) {
-            return Err(Error::Invalid("duplicate data source".into()));
-        }
-        crate::values::validate_schema(&source.schema())?;
-        self.sources.push((identity, source));
-        Ok(())
-    }
-    pub fn bind(&self, expression: &OperatorNode) -> Result<Scan, Error> {
-        let Some(NonASAPOp::Scan {
-            source,
-            predicates,
-            schema,
-        }) = expression.non_asap()
-        else {
-            return Err(Error::Invalid(
-                "raw Scan requires a Planner Scan leaf".into(),
-            ));
-        };
-        let output = Arc::new(schema.clone());
-        crate::values::validate_schema(&output)?;
-        let reader = self
-            .sources
-            .iter()
-            .find(|(key, _)| key == source)
-            .map(|(_, reader)| reader.clone())
-            .ok_or_else(|| Error::Invalid(format!("unbound raw source: {source:?}")))?;
-        if reader.schema() != output {
-            return Err(Error::Invalid(
-                "raw source differs from Planner Scan schema".into(),
-            ));
-        }
-        let predicates = predicates
-            .iter()
-            .map(|predicate| {
-                let predicate = CompiledExpression::compile(&predicate.0, &output)?;
-                if predicate.dtype().0 != DataType::Bool {
-                    return Err(Error::Invalid("Scan predicate must be boolean".into()));
-                }
-                Ok(predicate)
-            })
-            .collect::<Result<Vec<_>, Error>>()?;
-        Ok(Scan {
-            reader,
-            output,
-            predicates,
-        })
-    }
-}
-
-pub struct Scan {
-    reader: Arc<dyn RawSource>,
-    output: SchemaRef,
-    predicates: Vec<CompiledExpression>,
-}
-impl PhysicalOperator<Batch, SchemaRef> for Scan {
-    fn properties(&self, _: &[crate::plan::PlanProperties]) -> crate::plan::PlanProperties {
-        crate::plan::PlanProperties {
-            boundedness: self.reader.boundedness(),
-            emission: crate::plan::Emission::Incremental,
-        }
-    }
-
-    fn name(&self) -> &str {
-        "Scan"
-    }
-    fn input_schemas(&self) -> Vec<SchemaRef> {
-        vec![]
-    }
-    fn output_schema(&self) -> SchemaRef {
-        self.output.clone()
-    }
-    fn output_bytes(&self, batch: &Batch) -> usize {
-        batch.bytes()
-    }
-    fn start<'a>(
-        &'a self,
-        inputs: Vec<Input<'a, Batch>>,
-        context: RunContext,
-    ) -> Result<OutputStream<'a, Batch>, Error> {
-        if !inputs.is_empty() {
-            return Err(Error::Invalid("Scan cannot have inputs".into()));
-        }
-        if context.is_cancelled() {
-            return Err(Error::Cancelled);
-        }
-        // Opening is lazy: validation and construction of a run perform no I/O.
-        let opening = context.clone();
-        let stream = stream::once(async move {
-            if opening.is_cancelled() {
-                return Err(Error::Cancelled);
-            }
-            self.reader.scan(opening)
-        });
-        use futures::TryStreamExt;
-        Ok(stream
-            .try_flatten()
-            .map(move |batch| {
-                if context.is_cancelled() {
-                    return Err(Error::Cancelled);
-                }
-                let batch = batch?;
-                if batch.schema() != &self.output {
-                    return Err(Error::Invalid(
-                        "connector returned a different Scan schema".into(),
-                    ));
-                }
-                if self.predicates.is_empty() {
-                    return Ok(batch);
-                }
-                let _workspace =
-                    context.reserve(batch.bytes().checked_mul(2).ok_or(Error::MemoryLimit)?)?;
-                let mut rows = Vec::new();
-                for row in batch.rows() {
-                    if context.is_cancelled() {
-                        return Err(Error::Cancelled);
-                    }
-                    let mut keep = true;
-                    for predicate in &self.predicates {
-                        match predicate.evaluate(row)? {
-                            Value::Bool(true) => {}
-                            Value::Bool(false) | Value::Null => {
-                                keep = false;
-                                break;
-                            }
-                            _ => {
-                                return Err(Error::Invalid("Scan predicate is not boolean".into()))
-                            }
-                        }
-                    }
-                    if keep {
-                        rows.push(row.clone());
-                    }
-                }
-                Batch::try_new(self.output.clone(), rows)
-            })
-            .boxed_local())
-    }
-}
-
-mod memory;
-pub use memory::MemorySource;
diff --git a/crates/asap-physical-operators/tests/blocking_resources.rs b/crates/asap-physical-operators/tests/blocking_resources.rs
index 66702afdb..09cee7a4e 100644
--- a/crates/asap-physical-operators/tests/blocking_resources.rs
+++ b/crates/asap-physical-operators/tests/blocking_resources.rs
@@ -8,7 +8,7 @@ use asap_physical_operators::{
 };
 use futures::{executor::block_on, FutureExt, StreamExt};
 use planner_types::ir::Predicate;
-use planner_types::ir::ScalarExpr as QueryExpr;
+use planner_types::ir::ScalarExpr;
 use planner_types::{
     post_asap::{Field, FieldDataType},
     pre_asap::{DataType, JoinKind, ScalarValue},
@@ -62,7 +62,7 @@ fn cross_join() -> Operator {
         schema(1),
         schema(1),
         JoinKind::Cross,
-        &Predicate(QueryExpr::Literal(ScalarValue::Boolean(true))),
+        &Predicate(ScalarExpr::Literal(ScalarValue::Boolean(true))),
         schema(2),
     )
     .unwrap()
diff --git a/crates/asap-physical-operators/tests/physical_dag.rs b/crates/asap-physical-operators/tests/physical_dag.rs
index 450b95652..93a8b7a86 100644
--- a/crates/asap-physical-operators/tests/physical_dag.rs
+++ b/crates/asap-physical-operators/tests/physical_dag.rs
@@ -14,7 +14,7 @@ use planner_types::ir::export::{
     PhysicalASAPOperatorPayload, WindowEdgeCompatibility,
 };
 use planner_types::ir::BinaryOperator;
-use planner_types::ir::ScalarExpr as QueryExpr;
+use planner_types::ir::ScalarExpr;
 use planner_types::{
     post_asap::{ExactKind, ExactParams, Field, FieldDataType},
     pre_asap::DataType,
@@ -908,11 +908,11 @@ fn planner_expressions_preserve_collection_and_nullable_types() {
         },
         false,
     )]);
-    let access = QueryExpr::FunctionCall {
+    let access = ScalarExpr::FunctionCall {
         name: "asap_element_access".into(),
         args: vec![
-            QueryExpr::Column(0),
-            QueryExpr::Literal(ScalarValue::Utf8("count".into())),
+            ScalarExpr::Column(0),
+            ScalarExpr::Literal(ScalarValue::Utf8("count".into())),
         ],
     };
     let project = Operator::project(
@@ -945,11 +945,11 @@ fn planner_expressions_preserve_collection_and_nullable_types() {
     .unwrap();
     let projected = project.schema();
     dag.add(1, vec![0], project).unwrap();
-    let predicate = QueryExpr::Compare {
+    let predicate = ScalarExpr::Compare {
         semantics: planner_types::ir::ExprSemantics::Sql,
-        left: Box::new(QueryExpr::Column(0)),
+        left: Box::new(ScalarExpr::Column(0)),
         op: CompareOpKind::Ge,
-        right: Box::new(QueryExpr::Literal(ScalarValue::Int64(1))),
+        right: Box::new(ScalarExpr::Literal(ScalarValue::Int64(1))),
     };
     dag.add(
         2,
@@ -963,9 +963,9 @@ fn planner_expressions_preserve_collection_and_nullable_types() {
     .unwrap();
     let rows = run(&dag, 2, query());
     assert!(matches!(rows.as_slice(),[row] if matches!(row.as_slice(),[Value::Int64(7)])));
-    let unknown = QueryExpr::FunctionCall {
+    let unknown = ScalarExpr::FunctionCall {
         name: "unregistered_function".into(),
-        args: vec![QueryExpr::Column(0)],
+        args: vec![ScalarExpr::Column(0)],
     };
     assert!(CompiledExpression::compile(&unknown, &input_schema).is_err());
 }
@@ -977,11 +977,11 @@ fn native_relational_join_kinds_preserve_unmatched_rows() {
     use planner_types::pre_asap::{CompareOpKind, JoinKind};
 
     let input = schema(&[("key", DataType::Int64, true)]);
-    let predicate = Predicate(QueryExpr::Compare {
+    let predicate = Predicate(ScalarExpr::Compare {
         semantics: planner_types::ir::ExprSemantics::Sql,
-        left: Box::new(QueryExpr::Column(0)),
+        left: Box::new(ScalarExpr::Column(0)),
         op: CompareOpKind::Eq,
-        right: Box::new(QueryExpr::Column(1)),
+        right: Box::new(ScalarExpr::Column(1)),
     });
     for (kind, count) in [
         (JoinKind::Inner, 1),
diff --git a/crates/asap-physical-operators/tests/physical_semantics.rs b/crates/asap-physical-operators/tests/physical_semantics.rs
index b35d10a9f..498e8b3f0 100644
--- a/crates/asap-physical-operators/tests/physical_semantics.rs
+++ b/crates/asap-physical-operators/tests/physical_semantics.rs
@@ -12,7 +12,7 @@ use futures::{executor::block_on, StreamExt};
 use planner_types::ir::export::NonASAPOpKind as ValueOperation;
 use planner_types::ir::export::{PhysicalASAPDAGNode, PhysicalASAPOperatorPayload};
 use planner_types::ir::Predicate;
-use planner_types::ir::ScalarExpr as QueryExpr;
+use planner_types::ir::ScalarExpr;
 use planner_types::{
     post_asap::{Field, FieldDataType},
     pre_asap::{CompareOpKind, DataType, JoinKind},
@@ -78,11 +78,11 @@ fn keys(rows: &[Vec<Value>]) -> Vec<Vec<Vec<u8>>> {
         .collect()
 }
 fn eq_predicate() -> Predicate {
-    Predicate(QueryExpr::Compare {
+    Predicate(ScalarExpr::Compare {
         semantics: planner_types::ir::ExprSemantics::Sql,
-        left: Box::new(QueryExpr::Column(0)),
+        left: Box::new(ScalarExpr::Column(0)),
         op: CompareOpKind::Eq,
-        right: Box::new(QueryExpr::Column(1)),
+        right: Box::new(ScalarExpr::Column(1)),
     })
 }
 fn join(left: Vec<Value>, right: Vec<Value>, kind: JoinKind, keyed: bool) -> Vec<Vec<Value>> {
@@ -340,7 +340,7 @@ fn aggregate_empty_and_all_null_follow_asap_contract() {
 fn projection_rejects_expression_bound_to_another_schema() {
     let original = schema(&[("a", DataType::Int64, false), ("b", DataType::Int64, false)]);
     let current = schema(&[("a", DataType::Int64, false)]);
-    let expr = CompiledExpression::compile(&QueryExpr::Column(1), &original).unwrap();
+    let expr = CompiledExpression::compile(&ScalarExpr::Column(1), &original).unwrap();
     assert!(Operator::project(current, vec![("b".into(), Expression::planner(expr))]).is_err());
 }
 
@@ -417,11 +417,11 @@ fn planner_comparisons_handle_nan_without_execution_errors() {
         CompareOpKind::Gt,
         CompareOpKind::Ge,
     ] {
-        let expression = QueryExpr::Compare {
+        let expression = ScalarExpr::Compare {
             semantics: planner_types::ir::ExprSemantics::Sql,
-            left: Box::new(QueryExpr::Column(0)),
+            left: Box::new(ScalarExpr::Column(0)),
             op: op.clone(),
-            right: Box::new(QueryExpr::Column(1)),
+            right: Box::new(ScalarExpr::Column(1)),
         };
         let compiled = CompiledExpression::compile(&expression, &input).unwrap();
         for row in [
@@ -485,11 +485,11 @@ fn mixed_numeric_comparisons_preserve_large_integer_precision() {
         ("a", DataType::Int64, false),
         ("b", DataType::Float64, false),
     ]);
-    let expr = QueryExpr::Compare {
+    let expr = ScalarExpr::Compare {
         semantics: planner_types::ir::ExprSemantics::Sql,
-        left: Box::new(QueryExpr::Column(0)),
+        left: Box::new(ScalarExpr::Column(0)),
         op: CompareOpKind::Gt,
-        right: Box::new(QueryExpr::Column(1)),
+        right: Box::new(ScalarExpr::Column(1)),
     };
     let compiled = CompiledExpression::compile(&expr, &input).unwrap();
     for (a, b, expected) in [
@@ -510,11 +510,11 @@ fn boolean_truth_tables_agree_between_expression_paths() {
     for and in [true, false] {
         for a in [None, Some(false), Some(true)] {
             for b in [None, Some(false), Some(true)] {
-                let parts = vec![QueryExpr::Column(0), QueryExpr::Column(1)];
+                let parts = vec![ScalarExpr::Column(0), ScalarExpr::Column(1)];
                 let planner = if and {
-                    QueryExpr::BoolAnd(parts)
+                    ScalarExpr::BoolAnd(parts)
                 } else {
-                    QueryExpr::BoolOr(parts)
+                    ScalarExpr::BoolOr(parts)
                 };
                 let native = if and {
                     Expression::And(
diff --git a/crates/asap-physical-operators/tests/planspace_series_identity_heap.rs b/crates/asap-physical-operators/tests/planspace_series_identity_heap.rs
index 228332cbc..e33de530f 100644
--- a/crates/asap-physical-operators/tests/planspace_series_identity_heap.rs
+++ b/crates/asap-physical-operators/tests/planspace_series_identity_heap.rs
@@ -4,7 +4,7 @@
 //! ranking, or workload Cartesian expansion. Placement variants are not listed.
 mod common;
 use common::compile_physical_asap_dag;
-use planner_types::ir::OperatorNode as QueryExpr;
+use planner_types::ir::OperatorNode;
 
 use asap_aware_mapping::{
     accuracy::{AccuracyEvidenceProvider, DefaultAccuracyModel, PropagationStats},
@@ -28,7 +28,7 @@ use std::rc::Rc;
 
 struct Evidence;
 impl AccuracyEvidenceProvider for Evidence {
-    fn topk_max_distinct_items(&self, _: &QueryExpr) -> Option<u64> {
+    fn topk_max_distinct_items(&self, _: &OperatorNode) -> Option<u64> {
         Some(1000)
     }
     fn propagation_stats(
@@ -67,7 +67,7 @@ impl ReplacementStrategy for LogicalOnly {
     }
 }
 
-fn lower(query: &str, accuracy: &AccuracyTarget) -> Rc<QueryExpr> {
+fn lower(query: &str, accuracy: &AccuracyTarget) -> Rc<OperatorNode> {
     let workload = PlanningWorkload {
         query_workload: QueryWorkload {
             language: QueryLanguage::PromQL,
diff --git a/crates/frontend-metricsql/src/unified/mod.rs b/crates/frontend-metricsql/src/unified/mod.rs
deleted file mode 100644
index 3544a9801..000000000
--- a/crates/frontend-metricsql/src/unified/mod.rs
+++ /dev/null
@@ -1,389 +0,0 @@
-//! MetricsQL AST → the name-based `UnresolvedOp` tree → the unified operator DAG.
-
-use std::{rc::Rc, time::Duration};
-
-use asap_frontend_common::{
-    resolve_root, UnresolvedOp as U, UnresolvedPredicate, UnresolvedScalar,
-};
-use asap_types::ir::{BinaryOperator, ExprSemantics, OperatorNode, TimeRangeKind};
-use asap_types::pre_asap::{
-    AggIntent, ArithmeticOpKind, BinaryOpKind, ColumnRef, CompareOpKind, GroupKeys,
-    PromQLVectorSetOpKind, Reduction, ScalarValue, Source,
-};
-use asap_types::types::AccuracyTarget;
-use metricsql_parser::ast::{AggregateModifier, DurationExpr, Expr, MetricExpr, RollupExpr};
-use metricsql_parser::functions::{AggregateFunction, BuiltinFunction, RollupFunction};
-use metricsql_parser::label::{LabelFilter, LabelFilterOp, NAME_LABEL};
-use thiserror::Error;
-
-pub use metricsql_parser::ast::Expr as MetricsqlExpr;
-
-#[derive(Debug, Error)]
-pub enum MetricsqlError {
-    #[error("MetricsQL parse error: {0}")]
-    Parse(String),
-    #[error("unsupported MetricsQL feature: {0}")]
-    UnsupportedFeature(String),
-    #[error("MetricsQL column resolution failed: {0}")]
-    Resolve(String),
-}
-
-pub fn parse_metricsql(query: &str) -> Result<MetricsqlExpr, MetricsqlError> {
-    metricsql_parser::parser::parse(query).map_err(|e| MetricsqlError::Parse(e.to_string()))
-}
-
-pub fn canonical_metricsql(query: &str) -> Result<String, MetricsqlError> {
-    Ok(parse_metricsql(query)?.to_string())
-}
-
-pub fn lower_metricsql(
-    query: &str,
-    accuracy: AccuracyTarget,
-) -> Result<Rc<OperatorNode>, MetricsqlError> {
-    match lower_metricsql_query(query, accuracy)? {
-        asap_types::ir::QueryRoot::Operator(node) => Ok(node),
-        _ => Err(unsupported("scalar root: use lower_metricsql_query")),
-    }
-}
-
-/// Lower scalar constants without fabricating a relational operator.
-pub fn lower_metricsql_query(
-    query: &str,
-    accuracy: AccuracyTarget,
-) -> Result<asap_types::ir::QueryRoot, MetricsqlError> {
-    let ast = parse_metricsql(query)?;
-    if let Expr::NumberLiteral(number) = &ast {
-        return Ok(asap_types::ir::QueryRoot::Scalar(
-            asap_types::ir::ScalarExpr::literal_f64(number.value),
-        ));
-    }
-    let unresolved = Lowerer { accuracy }.lower(&ast)?;
-    resolve_root(&unresolved)
-        .map(asap_types::ir::QueryRoot::Operator)
-        .map_err(|e| MetricsqlError::Resolve(e.to_string()))
-}
-
-struct Lowerer {
-    accuracy: AccuracyTarget,
-}
-
-impl Lowerer {
-    fn lower(&self, expr: &Expr) -> Result<U, MetricsqlError> {
-        match expr {
-            Expr::MetricExpression(e) => self.metric(e),
-            Expr::Rollup(e) => self.rollup(e),
-            Expr::Function(e) => self.function(e),
-            Expr::Aggregation(e) => self.aggregate(e),
-            Expr::NumberLiteral(_) => {
-                Err(unsupported("scalar root requires lower_metricsql_query"))
-            }
-            // Vector negation is `x * -1` (as in the PromQL front end).
-            Expr::UnaryOperator(e) => Ok(U::PromqlScalarOp {
-                child: Rc::new(self.lower(&e.expr)?),
-                scalar: UnresolvedScalar::Literal(ScalarValue::Float64(-1.0)),
-                op: BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul),
-                scalar_left: false,
-                return_bool: false,
-            }),
-            Expr::BinaryOperator(e) => self.binary(e),
-            Expr::Parens(e) if e.expressions.len() == 1 => self.lower(&e.expressions[0]),
-            Expr::With(e) => self.lower(&e.expr),
-            other => Err(unsupported(format!("AST node `{other}`"))),
-        }
-    }
-
-    fn metric(&self, metric: &MetricExpr) -> Result<U, MetricsqlError> {
-        if metric.has_or_matchers() {
-            return Err(unsupported("or-delimited selector matchers"));
-        }
-        let name = metric
-            .metric_name()
-            .ok_or_else(|| unsupported("selector without one exact metric name"))?;
-        let mut filters: Vec<_> = metric
-            .matchers
-            .filter_iter()
-            .filter(|f| f.label != NAME_LABEL)
-            .collect();
-        filters.sort_by(|a, b| a.label.cmp(&b.label).then(a.value.cmp(&b.value)));
-        Ok(U::Scan {
-            source: Source::TimeSeries {
-                metric: name.to_owned(),
-            },
-            predicates: filters
-                .into_iter()
-                .map(|f| UnresolvedPredicate(matcher(f)))
-                .collect(),
-            schema: None,
-        })
-    }
-
-    fn rollup(&self, rollup: &RollupExpr) -> Result<U, MetricsqlError> {
-        if rollup.offset.is_some() || rollup.at.is_some() {
-            return Err(unsupported("offset and @ modifiers"));
-        }
-        if rollup.for_subquery() {
-            return Err(unsupported("subquery step or inherited step"));
-        }
-        let child = self.lower(&rollup.expr)?;
-        match &rollup.window {
-            None => Ok(child),
-            Some(window) => Ok(U::TimeRange {
-                range: duration(window)?,
-                kind: TimeRangeKind::Range,
-                child: Rc::new(child),
-            }),
-        }
-    }
-
-    fn function(
-        &self,
-        function: &metricsql_parser::ast::FunctionExpr,
-    ) -> Result<U, MetricsqlError> {
-        if function.keep_metric_names {
-            return Err(unsupported(
-                "keep_metric_names requires metric-name lineage",
-            ));
-        }
-        let BuiltinFunction::Rollup(rollup) = function.function else {
-            return Err(unsupported(format!("function `{}`", function.name())));
-        };
-        let expected_args = if rollup == RollupFunction::QuantileOverTime {
-            2
-        } else {
-            1
-        };
-        require_arity(function.name(), function.args.len(), expected_args)?;
-        let child_index = usize::from(rollup == RollupFunction::QuantileOverTime);
-        let child = function
-            .args
-            .get(child_index)
-            .ok_or_else(|| unsupported(format!("missing argument for `{}`", function.name())))?;
-        let intent = match rollup {
-            RollupFunction::DefaultRollup | RollupFunction::LastOverTime => AggIntent::LastOverTime,
-            RollupFunction::FirstOverTime => AggIntent::FirstOverTime,
-            RollupFunction::AvgOverTime => AggIntent::Avg { col: None },
-            RollupFunction::MinOverTime => AggIntent::Min { col: None },
-            RollupFunction::MaxOverTime => AggIntent::Max { col: None },
-            RollupFunction::SumOverTime => AggIntent::Sum { col: None },
-            RollupFunction::CountOverTime => AggIntent::Count {
-                accuracy: self.accuracy.clone(),
-            },
-            RollupFunction::StddevOverTime => AggIntent::StdDev {
-                col: None,
-                population: true,
-            },
-            RollupFunction::StdvarOverTime => AggIntent::Variance {
-                col: None,
-                population: true,
-            },
-            RollupFunction::Rate => AggIntent::Rate,
-            RollupFunction::IRate => AggIntent::IRate,
-            RollupFunction::Increase => AggIntent::Increase,
-            RollupFunction::Changes => AggIntent::Changes,
-            RollupFunction::Delta => AggIntent::Delta,
-            RollupFunction::IDelta => AggIntent::IDelta,
-            RollupFunction::Deriv => AggIntent::Deriv,
-            RollupFunction::Resets => AggIntent::Resets,
-            RollupFunction::MadOverTime => AggIntent::MadOverTime,
-            RollupFunction::PresentOverTime => AggIntent::PresentOverTime,
-            RollupFunction::AbsentOverTime => AggIntent::AbsentOverTime,
-            RollupFunction::QuantileOverTime => AggIntent::Quantile {
-                col: None,
-                q: number_arg(&function.args, 0)?,
-                accuracy: self.accuracy.clone(),
-            },
-            _ => {
-                return Err(unsupported(format!(
-                    "rollup function `{}`",
-                    function.name()
-                )))
-            }
-        };
-        let child = self.lower(child)?;
-        if rollup == RollupFunction::DefaultRollup && !matches!(child, U::TimeRange { .. }) {
-            return Err(unsupported(
-                "default_rollup without an explicit range requires an evaluation step",
-            ));
-        }
-        Ok(aggregate(Reduction::PerEntity, intent, child))
-    }
-
-    fn aggregate(
-        &self,
-        expr: &metricsql_parser::ast::AggregationExpr,
-    ) -> Result<U, MetricsqlError> {
-        if expr.limit != 0 || expr.keep_metric_names {
-            return Err(unsupported("aggregate limit or keep_metric_names"));
-        }
-        let expected_args = if expr.function == AggregateFunction::Quantile {
-            2
-        } else {
-            1
-        };
-        require_arity(expr.name(), expr.args.len(), expected_args)?;
-        let child_index = expr
-            .arg_idx_for_optimization()
-            .ok_or_else(|| unsupported(format!("aggregate `{}` arguments", expr.name())))?;
-        let intent = match expr.function {
-            AggregateFunction::Sum => AggIntent::Sum { col: None },
-            AggregateFunction::Avg => AggIntent::Avg { col: None },
-            AggregateFunction::Min => AggIntent::Min { col: None },
-            AggregateFunction::Max => AggIntent::Max { col: None },
-            AggregateFunction::Count => AggIntent::Cardinality {
-                cols: vec![],
-                accuracy: self.accuracy.clone(),
-            },
-            AggregateFunction::StdDev => AggIntent::StdDev {
-                col: None,
-                population: true,
-            },
-            AggregateFunction::StdVar => AggIntent::Variance {
-                col: None,
-                population: true,
-            },
-            AggregateFunction::Group => AggIntent::Group,
-            AggregateFunction::Quantile => AggIntent::Quantile {
-                col: None,
-                q: number_arg(&expr.args, 0)?,
-                accuracy: self.accuracy.clone(),
-            },
-            _ => return Err(unsupported(format!("aggregate `{}`", expr.name()))),
-        };
-        let reduction = match &expr.modifier {
-            None => Reduction::by(vec![]),
-            Some(AggregateModifier::By(v)) => Reduction::by(names(v)),
-            Some(AggregateModifier::Without(v)) => Reduction::Reduce(GroupKeys::without(names(v))),
-        };
-        let child = expr
-            .args
-            .get(child_index)
-            .ok_or_else(|| unsupported("missing aggregate input"))?;
-        Ok(aggregate(reduction, intent, self.lower(child)?))
-    }
-
-    fn binary(&self, expr: &metricsql_parser::ast::BinaryExpr) -> Result<U, MetricsqlError> {
-        if expr.modifier.is_some() {
-            return Err(unsupported("binary vector matching modifiers"));
-        }
-        use metricsql_parser::ast::Operator as O;
-        let op = match expr.op {
-            O::Add => BinaryOpKind::Arithmetic(ArithmeticOpKind::Add),
-            O::Sub => BinaryOpKind::Arithmetic(ArithmeticOpKind::Sub),
-            O::Mul => BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul),
-            O::Div => BinaryOpKind::Arithmetic(ArithmeticOpKind::Div),
-            O::Mod => BinaryOpKind::Arithmetic(ArithmeticOpKind::Mod),
-            O::Pow => BinaryOpKind::Arithmetic(ArithmeticOpKind::Pow),
-            O::Atan2 => BinaryOpKind::Arithmetic(ArithmeticOpKind::Atan2),
-            O::Eql => BinaryOpKind::Compare(CompareOpKind::Eq),
-            O::NotEq => BinaryOpKind::Compare(CompareOpKind::Ne),
-            O::Lt => BinaryOpKind::Compare(CompareOpKind::Lt),
-            O::Lte => BinaryOpKind::Compare(CompareOpKind::Le),
-            O::Gt => BinaryOpKind::Compare(CompareOpKind::Gt),
-            O::Gte => BinaryOpKind::Compare(CompareOpKind::Ge),
-            O::And => BinaryOpKind::Set(PromQLVectorSetOpKind::And),
-            O::Or => BinaryOpKind::Set(PromQLVectorSetOpKind::Or),
-            O::Unless => BinaryOpKind::Set(PromQLVectorSetOpKind::Unless),
-            O::If | O::IfNot | O::Default => {
-                return Err(unsupported(format!("MetricsQL operator `{}`", expr.op)))
-            }
-        };
-        for (scalar, vector, scalar_left) in [
-            (&expr.left, &expr.right, true),
-            (&expr.right, &expr.left, false),
-        ] {
-            if let Expr::NumberLiteral(n) = scalar.as_ref() {
-                return Ok(U::PromqlScalarOp {
-                    child: Rc::new(self.lower(vector)?),
-                    scalar: UnresolvedScalar::Literal(ScalarValue::Float64(n.value)),
-                    op,
-                    scalar_left,
-                    return_bool: false,
-                });
-            }
-        }
-        Ok(binary_op(
-            op,
-            self.lower(&expr.left)?,
-            self.lower(&expr.right)?,
-        ))
-    }
-}
-
-/// A `BinaryOp` with default matching; MetricsQL modifiers (including `bool`)
-/// are rejected before reaching here.
-fn binary_op(kind: BinaryOpKind, lhs: U, rhs: U) -> U {
-    U::BinaryOp {
-        operator: BinaryOperator {
-            kind,
-            vector_match: None,
-            checked_relative_division: false,
-            checked_finite_division: false,
-        },
-        return_bool: false,
-        lhs: Rc::new(lhs),
-        rhs: Rc::new(rhs),
-    }
-}
-
-fn names(values: &[String]) -> Vec<ColumnRef> {
-    values.iter().cloned().map(ColumnRef::Named).collect()
-}
-
-fn aggregate(reduction: Reduction<ColumnRef>, intent: AggIntent<ColumnRef>, child: U) -> U {
-    U::Aggregate {
-        reduction,
-        measures: vec![intent],
-        output_names: vec![String::new()],
-        filters: vec![],
-        having: None,
-        child: Rc::new(child),
-    }
-}
-
-fn matcher(filter: &LabelFilter) -> UnresolvedScalar {
-    let op = match filter.op {
-        LabelFilterOp::Equal => CompareOpKind::Eq,
-        LabelFilterOp::NotEqual => CompareOpKind::Ne,
-        LabelFilterOp::RegexEqual => CompareOpKind::Regex,
-        LabelFilterOp::RegexNotEqual => CompareOpKind::NotRegex,
-    };
-    UnresolvedScalar::Compare {
-        left: Box::new(UnresolvedScalar::Column(ColumnRef::Named(
-            filter.label.clone(),
-        ))),
-        op,
-        right: Box::new(UnresolvedScalar::Literal(ScalarValue::Utf8(
-            filter.value.clone(),
-        ))),
-        semantics: ExprSemantics::Promql,
-    }
-}
-
-fn duration(value: &DurationExpr) -> Result<Duration, MetricsqlError> {
-    match value {
-        DurationExpr::Millis(ms) if *ms >= 0 => Ok(Duration::from_millis(*ms as u64)),
-        DurationExpr::StepValue(_) => Err(unsupported("step-relative duration")),
-        DurationExpr::Millis(_) => Err(unsupported("negative duration")),
-    }
-}
-
-fn number_arg(args: &[Expr], index: usize) -> Result<f64, MetricsqlError> {
-    match args.get(index) {
-        Some(Expr::NumberLiteral(v)) if v.value.is_finite() => Ok(v.value),
-        _ => Err(unsupported(format!("numeric argument #{index}"))),
-    }
-}
-
-fn require_arity(name: &str, actual: usize, expected: usize) -> Result<(), MetricsqlError> {
-    if actual == expected {
-        Ok(())
-    } else {
-        Err(unsupported(format!(
-            "`{name}` with {actual} arguments; canonical lowering requires exactly {expected}"
-        )))
-    }
-}
-
-fn unsupported(message: impl Into<String>) -> MetricsqlError {
-    MetricsqlError::UnsupportedFeature(message.into())
-}
diff --git a/crates/frontend-promql/src/unified/error.rs b/crates/frontend-promql/src/unified/error.rs
deleted file mode 100644
index a889d6710..000000000
--- a/crates/frontend-promql/src/unified/error.rs
+++ /dev/null
@@ -1,81 +0,0 @@
-use std::fmt;
-
-use asap_frontend_common::ResolveDAGError;
-use asap_types::workload::WorkloadError;
-
-/// Errors from lowering a PromQL query (parse → the name-based unresolved
-/// tree, built directly →
-/// [`resolve_root`](asap_frontend_common::resolve_root) binds it to the
-/// unified operator DAG, issue #179).
-///
-/// Carries no DataFusion type — the PromQL front end never depends on the SQL
-/// stack. The language-neutral variants (`UnsupportedFeature` / `WrongLanguage`
-/// / `Convert`) are mirrored by [`asap_frontend_sql::SqlError`] rather than
-/// shared, so neither front end pulls the other's parser.
-#[derive(Debug)]
-pub enum PromqlError {
-    /// The workload omitted information required for plan-ready PromQL lowering.
-    InvalidWorkload(WorkloadError),
-    /// The `promql-parser` crate rejected the query string (parse failure).
-    Parse(String),
-    /// A PromQL function (`rate`, `*_over_time`, …) not supported in this version.
-    UnsupportedFunction(String),
-    /// A PromQL aggregation operator (`sum`, `topk`, …) not supported.
-    UnsupportedAggregateOp(String),
-    /// A structural feature (offset / `@` / `without`) not supported in this
-    /// version.
-    UnsupportedFeature(String),
-    /// A required function / aggregator argument was missing.
-    MissingArgument(String),
-    /// An argument had the wrong shape (e.g. a non-numeric `topk` parameter).
-    InvalidParameter(String),
-    /// The workload's query language is not PromQL.
-    WrongLanguage(String),
-    /// Resolving the canonical unresolved tree failed (name resolution
-    /// against the bound schema).
-    Convert(ResolveDAGError),
-}
-
-impl fmt::Display for PromqlError {
-    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
-        match self {
-            Self::InvalidWorkload(e) => write!(f, "invalid PromQL workload: {e}"),
-            Self::Parse(e) => write!(f, "PromQL parse error: {e}"),
-            Self::UnsupportedFunction(n) => write!(f, "unsupported PromQL function: {n}"),
-            Self::UnsupportedAggregateOp(n) => write!(f, "unsupported PromQL aggregate op: {n}"),
-            Self::UnsupportedFeature(m) => write!(f, "unsupported feature: {m}"),
-            Self::MissingArgument(m) => write!(f, "missing argument: {m}"),
-            Self::InvalidParameter(m) => write!(f, "invalid parameter: {m}"),
-            Self::WrongLanguage(l) => write!(f, "unsupported query language: {l}"),
-            Self::Convert(e) => write!(f, "column resolution failed: {e}"),
-        }
-    }
-}
-
-impl std::error::Error for PromqlError {}
-
-impl From<ResolveDAGError> for PromqlError {
-    fn from(e: ResolveDAGError) -> Self {
-        Self::Convert(e)
-    }
-}
-
-impl From<WorkloadError> for PromqlError {
-    fn from(e: WorkloadError) -> Self {
-        Self::InvalidWorkload(e)
-    }
-}
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-
-    #[test]
-    fn unsupported_feature_label_is_language_neutral() {
-        // `UnsupportedFeature` shares a Display label with the SQL side, so it
-        // must not hardcode "PromQL".
-        let msg = PromqlError::UnsupportedFeature("subquery".into()).to_string();
-        assert_eq!(msg, "unsupported feature: subquery");
-        assert!(!msg.contains("PromQL"), "got: {msg}");
-    }
-}
diff --git a/crates/frontend-promql/src/unified/histogram.rs b/crates/frontend-promql/src/unified/histogram.rs
deleted file mode 100644
index ecb8cd2c4..000000000
--- a/crates/frontend-promql/src/unified/histogram.rs
+++ /dev/null
@@ -1,129 +0,0 @@
-//! Sample-type metadata for the `histogram_quantile` discrimination (issue #79).
-//!
-//! Classic cumulative buckets use exact interpolation. The explicitly declared
-//! `RawSamples` extension permits generic quantile sketches; it is not standard
-//! PromQL histogram semantics. Native samples are rejected until the IR has a
-//! native histogram sample type. Undeclared metrics require classic bucket
-//! evidence (`by (le)`, a `_bucket` metric, or an `le` matcher).
-
-use std::cell::RefCell;
-use std::collections::HashMap;
-
-/// The physical sample type behind a histogram metric — the true signal for
-/// whether `histogram_quantile` over it can be re-sketched.
-#[derive(Debug, Clone, Copy, PartialEq, Eq)]
-pub enum HistogramKind {
-    /// Classic cumulative `le` buckets — pre-aggregated counts. The
-    /// distribution can't be reconstructed from them, so it is **not**
-    /// sketch-able: `histogram_quantile` is exact bucket interpolation.
-    ClassicBucket,
-    /// Native histogram samples; currently rejected because the IR lacks their type.
-    Native,
-    /// Raw float samples the client retains — sketch-able. This is the case the
-    /// generic `Quantile` lowering exists for (a client holding raw samples can
-    /// build a quantile sketch even though the user wrote `histogram_quantile`).
-    RawSamples,
-}
-
-impl HistogramKind {
-    /// Whether `histogram_quantile` over this kind lowers to the sketch-able
-    /// generic `Quantile` (`true`) rather than exact bucket interpolation.
-    pub fn is_sketchable(self) -> bool {
-        matches!(self, HistogramKind::RawSamples)
-    }
-}
-
-/// Metric-name → declared [`HistogramKind`]. Supplied by a client that knows its
-/// sample types, to drive the `histogram_quantile` discrimination from metadata
-/// instead of query structure (issue #79).
-#[derive(Debug, Clone, Default)]
-pub struct HistogramCatalog(HashMap<String, HistogramKind>);
-
-impl HistogramCatalog {
-    pub fn new() -> Self {
-        Self::default()
-    }
-
-    /// Declare `metric`'s sample type (builder style).
-    pub fn with(mut self, metric: impl Into<String>, kind: HistogramKind) -> Self {
-        self.0.insert(metric.into(), kind);
-        self
-    }
-
-    /// The declared kind for `metric`, if any.
-    pub fn kind_of(&self, metric: &str) -> Option<HistogramKind> {
-        self.0.get(metric).copied()
-    }
-
-    pub fn is_empty(&self) -> bool {
-        self.0.is_empty()
-    }
-}
-
-thread_local! {
-    static CURRENT: RefCell<Option<HistogramCatalog>> = const { RefCell::new(None) };
-}
-
-/// RAII guard installing `catalog` as the ambient histogram catalog for the
-/// current thread, restoring the prior value on drop.
-///
-/// Lowering is synchronous and processes one query at a time, so a thread-local
-/// ambient catalog cleanly injects this read-only metadata into the deep,
-/// free-function `walk` recursion without threading a parameter through every
-/// signature (the discrimination is consulted in exactly one place,
-/// `walk_histogram`).
-pub(crate) struct CatalogGuard(Option<HistogramCatalog>);
-
-impl CatalogGuard {
-    pub(crate) fn install(catalog: HistogramCatalog) -> Self {
-        let prev = CURRENT.with(|c| c.borrow_mut().replace(catalog));
-        CatalogGuard(prev)
-    }
-}
-
-impl Drop for CatalogGuard {
-    fn drop(&mut self) {
-        CURRENT.with(|c| *c.borrow_mut() = self.0.take());
-    }
-}
-
-/// The ambient catalog's declared kind for `metric`, or `None` when no catalog
-/// is installed or the metric is undeclared (→ fall back to the heuristic).
-pub(crate) fn current_kind_of(metric: &str) -> Option<HistogramKind> {
-    CURRENT.with(|c| c.borrow().as_ref().and_then(|cat| cat.kind_of(metric)))
-}
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-
-    #[test]
-    fn only_explicit_raw_samples_are_sketchable() {
-        assert!(!HistogramKind::ClassicBucket.is_sketchable());
-        assert!(!HistogramKind::Native.is_sketchable());
-        assert!(HistogramKind::RawSamples.is_sketchable());
-    }
-
-    #[test]
-    fn catalog_lookup() {
-        let cat = HistogramCatalog::new()
-            .with("classic", HistogramKind::ClassicBucket)
-            .with("raw", HistogramKind::RawSamples);
-        assert_eq!(cat.kind_of("classic"), Some(HistogramKind::ClassicBucket));
-        assert_eq!(cat.kind_of("raw"), Some(HistogramKind::RawSamples));
-        assert_eq!(cat.kind_of("unknown"), None);
-    }
-
-    #[test]
-    fn guard_installs_and_restores_the_ambient_catalog() {
-        assert_eq!(current_kind_of("m"), None);
-        {
-            let _g = CatalogGuard::install(
-                HistogramCatalog::new().with("m", HistogramKind::ClassicBucket),
-            );
-            assert_eq!(current_kind_of("m"), Some(HistogramKind::ClassicBucket));
-        }
-        // Restored to empty after the guard drops.
-        assert_eq!(current_kind_of("m"), None);
-    }
-}
diff --git a/crates/frontend-promql/src/unified/mod.rs b/crates/frontend-promql/src/unified/mod.rs
deleted file mode 100644
index e7d99fe4c..000000000
--- a/crates/frontend-promql/src/unified/mod.rs
+++ /dev/null
@@ -1,233 +0,0 @@
-//! PromQL front end: parse (via `promql-parser`) → the name-based
-//! [`UnresolvedOp`](asap_frontend_common::UnresolvedOp) tree, built directly
-//! in canonical shape (issue #179) → [`resolve_root`].
-//!
-//! `resolve_root` runs the
-//! [`SchemaResolver`](asap_frontend_common::SchemaResolver) for positional
-//! name resolution and returns the unified
-//! [`OperatorNode`](asap_types::ir::OperatorNode) DAG. Depends on the PromQL
-//! parser only — never on the SQL / DataFusion stack.
-
-pub mod error;
-pub mod histogram;
-pub mod promql;
-
-use std::rc::Rc;
-
-use asap_types::ir::OperatorNode;
-use asap_types::workload::{DurationMs, PlanningWorkload, QueryLanguage, WorkloadError};
-
-pub use error::PromqlError;
-pub use histogram::{HistogramCatalog, HistogramKind};
-
-/// Lower every normalized PromQL workload entry to a plan-ready operator DAG.
-///
-/// PromQL workloads must declare a non-zero `data_ingestion_interval`; it is
-/// injected around each bare instant selector. Explicit range selectors keep
-/// their query-specified range.
-/// `now_ms` is the planning time in Unix milliseconds; cadence evidence must
-/// be valid at that time, using the same clock as downstream planning.
-pub fn lower_promql_workload(
-    workload: &PlanningWorkload,
-    now_ms: u64,
-) -> Result<Vec<Rc<OperatorNode>>, PromqlError> {
-    lower_promql_workload_inner(workload, now_ms)
-}
-
-/// Like [`lower_promql_workload`], but uses `histograms` to distinguish classic
-/// bucket interpolation from generic sketchable quantiles.
-pub fn lower_promql_workload_with_histograms(
-    workload: &PlanningWorkload,
-    histograms: HistogramCatalog,
-    now_ms: u64,
-) -> Result<Vec<Rc<OperatorNode>>, PromqlError> {
-    let _guard = histogram::CatalogGuard::install(histograms);
-    lower_promql_workload_inner(workload, now_ms)
-}
-
-/// Lower scalar and vector query roots without introducing constant operators.
-pub fn lower_promql_query_workload(
-    workload: &PlanningWorkload,
-    now_ms: u64,
-) -> Result<Vec<asap_types::ir::QueryRoot>, PromqlError> {
-    lower_promql_query_workload_inner(workload, now_ms)
-}
-
-pub fn lower_promql_query_workload_with_histograms(
-    workload: &PlanningWorkload,
-    histograms: HistogramCatalog,
-    now_ms: u64,
-) -> Result<Vec<asap_types::ir::QueryRoot>, PromqlError> {
-    let _guard = histogram::CatalogGuard::install(histograms);
-    lower_promql_query_workload_inner(workload, now_ms)
-}
-
-fn lower_promql_workload_inner(
-    workload: &PlanningWorkload,
-    now_ms: u64,
-) -> Result<Vec<Rc<OperatorNode>>, PromqlError> {
-    lower_promql_query_workload_inner(workload, now_ms)?
-        .into_iter()
-        .map(|root| match root {
-            asap_types::ir::QueryRoot::Operator(node) => Ok(node),
-            asap_types::ir::QueryRoot::Scalar(_) => Err(PromqlError::UnsupportedFeature(
-                "scalar root: use lower_promql_query_workload".into(),
-            )),
-        })
-        .collect()
-}
-
-fn lower_promql_query_workload_inner(
-    workload: &PlanningWorkload,
-    now_ms: u64,
-) -> Result<Vec<asap_types::ir::QueryRoot>, PromqlError> {
-    if !matches!(workload.query_workload.language, QueryLanguage::PromQL) {
-        return Err(PromqlError::WrongLanguage(format!(
-            "{:?}",
-            workload.query_workload.language
-        )));
-    }
-    workload.validate()?;
-    let &DurationMs(interval_ms) = workload
-        .data_workload
-        .as_ref()
-        .expect("validated PromQL workload has data_workload")
-        .data_ingestion_interval
-        .value_at(now_ms)
-        .ok_or(WorkloadError::UnavailableDataIngestionInterval)?;
-    workload
-        .query_workload
-        .entries()
-        .map(|entry| {
-            let root = promql::PromqlLowerer::lower_query_with_ingestion_interval(
-                &entry.query.0,
-                &entry.requirements.accuracy.target(),
-                std::time::Duration::from_millis(interval_ms),
-            )?;
-            Ok(root)
-        })
-        .collect()
-}
-
-#[cfg(test)]
-mod tests {
-    // Expiring evidence without an observation timestamp is never usable.
-    #[test]
-    fn rejects_unusable_ingestion_evidence() {
-        let mut input = workload("sum(data)");
-        input
-            .data_workload
-            .as_mut()
-            .unwrap()
-            .data_ingestion_interval
-            .valid_for_ms = Some(100);
-        assert!(lower_promql_workload(&input, 0).is_err());
-    }
-
-    // Cadence expiry is inclusive; future and expired evidence cannot set a horizon.
-    #[test]
-    fn ingestion_evidence_respects_planning_time_with_and_without_histograms() {
-        let mut input = workload("sum(data)");
-        let evidence = &mut input
-            .data_workload
-            .as_mut()
-            .unwrap()
-            .data_ingestion_interval;
-        evidence.observed_at_ms = Some(1_000);
-        evidence.valid_for_ms = Some(100);
-        for (now_ms, usable) in [(999, false), (1_000, true), (1_100, true), (1_101, false)] {
-            assert_eq!(lower_promql_workload(&input, now_ms).is_ok(), usable);
-            assert_eq!(
-                lower_promql_workload_with_histograms(&input, HistogramCatalog::default(), now_ms)
-                    .is_ok(),
-                usable
-            );
-        }
-        input
-            .data_workload
-            .as_mut()
-            .unwrap()
-            .data_ingestion_interval
-            .observed_at_ms = None;
-        assert!(
-            lower_promql_workload_with_histograms(&input, HistogramCatalog::default(), 1_000)
-                .is_err()
-        );
-    }
-    use std::time::Duration;
-
-    use asap_types::ir::{NonASAPOp, TimeRangeKind};
-    use asap_types::workload::{
-        BatchEntry, DataWorkload, Evidence, PlanningWorkload, Query, QueryRequirements,
-        QueryWorkload, TimeSelection,
-    };
-
-    use super::*;
-
-    fn workload(query: &str) -> PlanningWorkload {
-        PlanningWorkload {
-            query_workload: QueryWorkload {
-                language: QueryLanguage::PromQL,
-                query_batch: Some(vec![BatchEntry {
-                    query: Query(query.into()),
-                    requirements: QueryRequirements::default(),
-                    predictability: Default::default(),
-                    invocations: 1,
-                    execute_at: None,
-                    time_selection: TimeSelection::default(),
-                }]),
-                repeating_queries: None,
-            },
-            data_workload: Some(DataWorkload {
-                data_ingestion_interval: Evidence {
-                    value: Some(DurationMs(1_000)),
-                    ..Default::default()
-                },
-                ..Default::default()
-            }),
-        }
-    }
-
-    // A bare instant selector reads the latest sample within the declared
-    // ingestion interval: an `Instant` lookback of that length.
-    #[test]
-    fn instant_selector_uses_declared_ingestion_interval() {
-        let query = lower_promql_workload(&workload("sum by (job) (data)"), 0).unwrap();
-        let NonASAPOp::Aggregate { child, .. } = query[0].expect_non_asap() else {
-            panic!("expected aggregate")
-        };
-        assert!(
-            matches!(child.expect_non_asap(), NonASAPOp::TimeRange { range, kind, child }
-            if *range == Duration::from_secs(1)
-                && *kind == TimeRangeKind::Instant
-                && matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }))
-        );
-    }
-
-    // An explicit `m[5m]` keeps its own window as a `Range` selection.
-    #[test]
-    fn explicit_range_selector_keeps_its_query_range() {
-        let query = lower_promql_workload(&workload("sum_over_time(data[5m])"), 0).unwrap();
-        let NonASAPOp::Aggregate { child, .. } = query[0].expect_non_asap() else {
-            panic!("expected aggregate")
-        };
-        assert!(
-            matches!(child.expect_non_asap(), NonASAPOp::TimeRange { range, kind, child }
-            if *range == Duration::from_secs(300)
-                && *kind == TimeRangeKind::Range
-                && matches!(child.expect_non_asap(), NonASAPOp::Scan { .. }))
-        );
-    }
-
-    #[test]
-    fn workload_without_interval_fails_loudly() {
-        let mut workload = workload("sum(data)");
-        workload.data_workload = Some(DataWorkload::default());
-        assert!(matches!(
-            lower_promql_workload(&workload, 0),
-            Err(PromqlError::InvalidWorkload(
-                asap_types::workload::WorkloadError::MissingDataIngestionInterval
-            ))
-        ));
-    }
-}
diff --git a/crates/frontend-promql/src/unified/promql.rs b/crates/frontend-promql/src/unified/promql.rs
deleted file mode 100644
index f97e4fb9d..000000000
--- a/crates/frontend-promql/src/unified/promql.rs
+++ /dev/null
@@ -1,2236 +0,0 @@
-//! PromQL string → the name-based
-//! [`UnresolvedOp`](asap_frontend_common::UnresolvedOp) tree.
-//!
-//! - **Parsing** is delegated to `promql-parser` 0.8.
-//! - **Lowering** builds *directly in canonical shape* here (issue #179): the
-//!   walk interprets PromQL semantics (range vectors, aggregate operators,
-//!   label matchers) and emits `UnresolvedOp` / `UnresolvedScalar` nodes with
-//!   unresolved `ColumnRef`s — the same tree shape
-//!   [`resolve_root`](asap_frontend_common::resolve_root) later binds to the
-//!   positional [`OperatorNode`](asap_types::ir::OperatorNode) DAG. The structural decisions a
-//!   separate converter stage would otherwise have to make (heavy-hitter
-//!   `topk` recognition, the `PerEntity`/`Reduce` reduction choice,
-//!   `without(...)` grouping) are made right here, since a front end
-//!   building this shape already knows the answer at parse time — see
-//!   `reduction_for` and `mark_without`. `resolve_root` is left with exactly
-//!   the schema-*dependent* work: binding every `ColumnRef` to its
-//!   positional `ColumnId`.
-//!
-//! # PromQL → canonical unresolved-tree mapping (summary)
-//!
-//! | PromQL | Canonical shape |
-//! |---|---|
-//! | `quantile_over_time(φ, m{f}[w])` | `Aggregate{[Quantile(φ)], TimeRange{w, Scan{predicates}}}` |
-//! | `histogram_quantile(φ, <classic buckets>)` | `Aggregate{without(le), [HistogramQuantile(φ, le)]}` — cumulative-bucket interpolation (classic form recognised by `by (le)` / a `_bucket` metric / an `le` matcher) |
-//! | `histogram_quantile(φ, <native hist / raw>)` | `Aggregate{[Quantile(φ)]}` over the fully-lowered arg (generic, sketch-able with an accuracy target) |
-//! | `histogram_quantiles(v, "l", φ…)` | `Concat{PromqlRelabel{l=φᵢ, <the histogram_quantile(φᵢ, v) branch>}…}` — one branch per φ (issue #109) |
-//! | `histogram_count/sum/avg/stddev/stdvar(v)`, `histogram_fraction(l,u,v)` | `Aggregate{[Histogram*]}` — per-series native-histogram accessors (issue #43) |
-//! | `OUTER_op(inner_func(m[w]))` (e.g. `sum(rate(m[w]))`) | `Aggregate{[OUTER_op]}` over `Aggregate{[inner_func]}` — two levels |
-//! | `OUTER_op(<any expr>)` (e.g. `max(sum by (job) (rate(m[w])))`, `sum(rate(a[w]) + rate(b[w]))`) | `Aggregate{[OUTER_op]}` over the fully-lowered `<any expr>` — arbitrary function nesting (issue #27) |
-//! | `topk(k, <non-count expr>)` / `bottomk(k, <any expr>)` | `Sort{value} → Limit{k}` over the fully-lowered argument |
-//! | `avg/min/max/sum_over_time(m[w])` | `Aggregate{[Avg/Min/Max/Sum], TimeRange{w}}` |
-//! | `stddev/stdvar_over_time(m[w])` | `Aggregate{[StdDev/Variance], TimeRange{w}}` |
-//! | `count_over_time(m[w])` | `Aggregate{[Count], TimeRange{w}}` |
-//! | `last/first/mad/ts_of_min/ts_of_max/ts_of_first/ts_of_last_over_time(m[w])` | `Aggregate{[Last/First/Mad/TsOf…OverTime], TimeRange{w}}` — per-series range reducers (issue #51) |
-//! | `sort`/`sort_desc(v)`, `sort_by_label[_desc](v,"l"…)` | `Sort{value \| label…}` (no `Limit`) — row-preserving reorder (issue #51); `min_of`/`max_of` scalar reducers → #89 |
-//! | `rate(m[w])` / `irate(m[w])` | `Aggregate{[Rate/IRate], TimeRange{w}}` — distinct function identities; shared physical machinery is a later realization choice |
-//! | `increase(m[w])` | `Aggregate{[Increase], TimeRange{w}}` |
-//! | `changes`/`delta`/`idelta`/`deriv`/`resets`/`predict_linear`/`double_exponential_smoothing`(`m[w]`, …) | `Aggregate{[Changes/Delta/…], TimeRange{w}}` — per-series counter-derivative intents (issue #44) |
-//! | `absent(v)` / `absent_over_time(m[w])` / `present_over_time(m[w])` | `Aggregate{[Absent/AbsentOverTime/PresentOverTime]}` — presence intents; the empty→synthesized-sample logic is a post-ASAP concern (issue #47) |
-//! | `abs`/`ceil`/`sqrt`/`ln`/`clamp*`/`round`/trig(`v`), `pi()` | typed scalar `Project` (issue #45); `pi()` → a `ScalarExpr::Literal` root |
-//! | `time()` / `timestamp`/`hour`/`day_of_week`/… (`v`) | `ScalarExpr::EvalTimestamp` root / `Aggregate{[TimeFn(f)]}` (issue #46) |
-//! | `vector(s)` / `scalar(v)` | `PromqlVectorFromScalar(s)` / `ScalarExpr::PromqlScalarFromVector(v)` — the scalar⇄vector bridges (issue #48) |
-//! | `<scalar> op <scalar>` (`time() - 1`, `1 < bool 2`, `-time()`) | `ScalarExpr::{Arithmetic, Case, Negative}` — a scalar expression, never an operator |
-//! | `v op <scalar>`, `a op bool b`, `v > bool 0` | `Project`/`Filter` with owned scalar expressions; vector/vector uses `BinaryOp{return_bool}` |
-//! | `label_replace(v,…)` / `label_join(v,…)` | `PromqlRelabel{dst, value}` — per-series label rewrite; value unchanged (issue #50) |
-//! | `info(v, [selector])` | `PromqlInfoEnrich{selector}` — label-enrichment join against the info metric(s); join keys resolved during post-ASAP binding (issue #84) |
-//! | `group` / `offset` / `@` / `info` | **rejected** — distinct semantics with no intent-algebra representation yet (`info` label-join → #84) |
-//! | `OUTER by (dims) (…)` | `Aggregate.reduction = Reduce(by = dims)` (generic `topk by`/`bottomk` grouping → `Sort.partition_by`) |
-//! | `count by (d) (…)` | `Aggregate{[Count], …}` |
-//! | `group(v)` / `count_values("l", v)` | `Aggregate{[Group]}` (constant 1) / `Aggregate{[CountValues{l}]}` (group-by-value + count, new label `l`) — issue #49 |
-//! | `limitk(k, v)` / `limit_ratio(r, v)` | `PromqlSeriesSample{LimitK(k) \| LimitRatio(r)}` — series-sampling selection, whole series kept unchanged (issue #86) |
-//! | `topk(k, count_over_time(…))` / `topk(k, sum_over_time(…))` | `Aggregate{[TopK{k}]}` (heavy-hitter intent) over the explicit inner `Aggregate{[Count/Sum]}` |
-//! | `topk(k, <other>)` / `bottomk(k, …)` | `Sort{value} → Limit{k}` |
-//! | `m{f}` / `m{f}[w]` | `TimeRange{ingestion, Instant, Scan{predicates}}` / `TimeRange{w, Range, Scan}` |
-//! | `a OP b` | `BinaryOp{vector_match}` |
-//! | `expr[r:res]` | `PromqlSubquery{r, res}` |
-//! | `<selector> offset <d>` / `<selector> @ <ts>`/`start()`/`end()` | `TimeShift{shift}` over the selector's `Scan` — pass-through schema; a ranged selector shifts under its `TimeRange` (issue #40) |
-
-use std::rc::Rc;
-use std::time::{Duration, SystemTime};
-
-use promql_parser::label::{MatchOp, Matcher};
-use promql_parser::parser::value::ValueType;
-use promql_parser::parser::{
-    self, token, AggregateExpr, AtModifier as ParserAtModifier, BinaryExpr, Call, Expr,
-    LabelModifier, Offset, VectorMatchCardinality, VectorSelector,
-};
-
-use asap_frontend_common::{
-    UnresolvedOp as Unresolved, UnresolvedPredicate, UnresolvedScalar as Scalar, UnresolvedSortKey,
-};
-use asap_types::ir::operator_properties::{
-    AtModifier, BinaryOpKind, GroupKeys, GroupSide, PromQLVectorSetOpKind, Reduction, Source,
-    TimeShift, VectorGrouping, VectorMatch, VectorMatchKind,
-};
-use asap_types::ir::{BinaryOperator, ExprSemantics, TimeRangeKind};
-use asap_types::pre_asap::agg_intent::{topk, AggIntent, TimeFunc};
-
-use asap_types::pre_asap::{
-    ArithmeticOpKind, ColumnRef, CompareOpKind, InfoMatcher, SampleKind, ScalarValue,
-};
-use asap_types::types::AccuracyTarget;
-
-/// Every scalar expression this front end builds follows PromQL's numeric rules.
-const PROMQL: ExprSemantics = ExprSemantics::Promql;
-
-use crate::unified::error::PromqlError as LoweringError;
-
-type Result<T> = std::result::Result<T, LoweringError>;
-
-/// Parses and lowers (→ the canonical, unresolved tree) a PromQL query string.
-pub(crate) struct PromqlLowerer;
-
-#[derive(Debug, Clone)]
-enum Outer {
-    None,
-    Plain(OuterIntent),
-    Count,
-    /// `count_values("l", v)` — group by value + count, emitting the value as a
-    /// new label `l` (issue #49).
-    CountValues {
-        label: String,
-    },
-    TopK {
-        k: u64,
-        descending: bool,
-    },
-    /// `limitk`/`limit_ratio` — series-sampling selection (issue #86).
-    Sample {
-        kind: SampleKind,
-    },
-}
-
-#[derive(Debug, Clone)]
-enum OuterIntent {
-    Sum,
-    Avg,
-    Min,
-    Max,
-    StdDev,
-    Variance,
-    Quantile(f64),
-    /// `group(v)` — constant 1 per group (issue #49).
-    Group,
-}
-
-#[derive(Debug, Clone)]
-enum InnerFunc {
-    FrequencyL2,
-    FrequencyEntropy,
-    Cardinality,
-    Quantile(f64),
-    Avg,
-    Min,
-    Max,
-    Sum,
-    StdDev,
-    Variance,
-    Count,
-    // `Rate`/`Increase` carry no window of their own — unlike the old Unresolved
-    // `AggFunc::Rate{window}`, canonical `AggIntent::Rate`/`Increase` have no
-    // window field either; `windowed_aggregate` reads `Inner.window`
-    // uniformly for every intent, so it would be a redundant duplicate here.
-    Rate,
-    IRate,
-    Increase,
-    // Counter-derivative range functions (issue #44). The window rides on the
-    // enclosing `TimeRange` node (like `*_over_time`), so these carry only
-    // their non-window scalar params.
-    Changes,
-    Delta,
-    IDelta,
-    Deriv,
-    Resets,
-    PredictLinear(f64),
-    DoubleExp { smoothing: f64, trend: f64 },
-    // Additional range-vector reducers (issue #51). Per-series over the window
-    // (like `*_over_time`); the window rides on the enclosing Unresolved `Window`.
-    LastOverTime,
-    FirstOverTime,
-    MadOverTime,
-    TsOfMinOverTime,
-    TsOfMaxOverTime,
-    TsOfFirstOverTime,
-    TsOfLastOverTime,
-}
-
-struct Inner {
-    metric: String,
-    matchers: Vec<Scalar>,
-    window: Option<Duration>,
-    func: Option<InnerFunc>,
-    /// `offset` / `@` on the selector, carried to the `Source` (issue #40).
-    shift: TimeShift,
-}
-
-/// Maximum PromQL expression nesting depth the walker accepts. Real queries
-/// nest only a handful deep; this bounds the recursive descent (`walk` and the
-/// mutually-recursive helpers) so a pathologically nested query is rejected
-/// rather than overflowing the stack.
-const MAX_DEPTH: usize = 256;
-
-impl PromqlLowerer {
-    pub(crate) fn lower_query_with_ingestion_interval(
-        query: &str,
-        accuracy: &AccuracyTarget,
-        interval: Duration,
-    ) -> Result<asap_types::ir::QueryRoot> {
-        let _guard = AccuracyGuard::install(accuracy.clone());
-        let _interval = IngestionIntervalGuard::install(interval);
-        let ast = parser::parse(query).map_err(LoweringError::Parse)?;
-        check_depth(&ast, MAX_DEPTH)?;
-        let mut metrics = Vec::new();
-        collect_metric_names(&ast, &mut metrics);
-        if metrics.iter().any(|metric| {
-            crate::unified::histogram::current_kind_of(metric)
-                == Some(crate::unified::histogram::HistogramKind::Native)
-        }) {
-            return Err(LoweringError::UnsupportedFeature(
-                "native histogram samples have no IR representation".into(),
-            ));
-        }
-
-        if ast.value_type() == ValueType::Scalar {
-            Ok(asap_types::ir::QueryRoot::Scalar(
-                asap_frontend_common::resolve_scalar_root(&lower_scalar(&ast)?)?,
-            ))
-        } else {
-            Ok(asap_types::ir::QueryRoot::Operator(
-                asap_frontend_common::resolve_root(&walk(&ast)?)?,
-            ))
-        }
-    }
-}
-
-std::thread_local! {
-    static ACCURACY: std::cell::RefCell<AccuracyTarget> =
-        const { std::cell::RefCell::new(AccuracyTarget::Exact) };
-    static INGESTION_INTERVAL: std::cell::RefCell<Option<Duration>> = const { std::cell::RefCell::new(None) };
-}
-
-/// RAII guard installing `accuracy` as the ambient accuracy target for the
-/// current thread's lowering, restoring the prior value on drop — same shape
-/// as `histogram::CatalogGuard`.
-struct AccuracyGuard(AccuracyTarget);
-
-impl AccuracyGuard {
-    fn install(accuracy: AccuracyTarget) -> Self {
-        let prev = ACCURACY.with(|a| a.replace(accuracy));
-        AccuracyGuard(prev)
-    }
-}
-
-impl Drop for AccuracyGuard {
-    fn drop(&mut self) {
-        ACCURACY.with(|a| *a.borrow_mut() = std::mem::replace(&mut self.0, AccuracyTarget::Exact));
-    }
-}
-
-/// The ambient accuracy target installed by the current [`PromqlLowerer::lower`] call.
-fn current_accuracy() -> AccuracyTarget {
-    ACCURACY.with(|a| a.borrow().clone())
-}
-
-struct IngestionIntervalGuard(Option<Duration>);
-
-impl IngestionIntervalGuard {
-    fn install(interval: Duration) -> Self {
-        Self(INGESTION_INTERVAL.with(|current| current.replace(Some(interval))))
-    }
-}
-
-impl Drop for IngestionIntervalGuard {
-    fn drop(&mut self) {
-        INGESTION_INTERVAL.with(|current| *current.borrow_mut() = self.0.take());
-    }
-}
-
-fn current_ingestion_interval() -> Duration {
-    INGESTION_INTERVAL.with(|current| {
-        current
-            .borrow()
-            .expect("ingestion interval is installed for workload lowering")
-    })
-}
-
-/// Bounded depth check over the parser AST: errors once nesting would exceed
-/// `budget` frames, descending into every child expression.
-fn check_depth(expr: &Expr, budget: usize) -> Result<()> {
-    let Some(budget) = budget.checked_sub(1) else {
-        return Err(LoweringError::UnsupportedFeature(format!(
-            "query nesting exceeds the {MAX_DEPTH}-level limit"
-        )));
-    };
-    match expr {
-        Expr::Aggregate(a) => {
-            check_depth(&a.expr, budget)?;
-            if let Some(p) = &a.param {
-                check_depth(p, budget)?;
-            }
-        }
-        Expr::Unary(u) => check_depth(&u.expr, budget)?,
-        Expr::Binary(b) => {
-            check_depth(&b.lhs, budget)?;
-            check_depth(&b.rhs, budget)?;
-        }
-        Expr::Paren(p) => check_depth(&p.expr, budget)?,
-        Expr::Subquery(s) => check_depth(&s.expr, budget)?,
-        Expr::Call(c) => {
-            for arg in &c.args.args {
-                check_depth(arg, budget)?;
-            }
-        }
-        Expr::MatrixSelector(_)
-        | Expr::VectorSelector(_)
-        | Expr::NumberLiteral(_)
-        | Expr::StringLiteral(_)
-        | Expr::Extension(_) => {}
-    }
-    Ok(())
-}
-
-fn walk(expr: &Expr) -> Result<Unresolved> {
-    // A scalar-typed expression (`5`, `time() - 1`, `scalar(v)`, `1 < bool 2`)
-    // is a scalar expression at an operator position, never an operator tree.
-    if expr.value_type() == ValueType::Scalar {
-        return Err(LoweringError::UnsupportedFeature(
-            "scalar root requires query-root lowering".into(),
-        ));
-    }
-    match expr {
-        Expr::Aggregate(agg) => walk_aggregate(agg),
-        Expr::Call(call) if call.func.name.starts_with("histogram_") => walk_histogram(call),
-        Expr::Call(call) if is_math_fn(call.func.name) => walk_math(call),
-        Expr::Call(call) if is_presence_fn(call.func.name) => walk_presence(call),
-        Expr::Call(call) if is_time_fn(call.func.name) => walk_time(call),
-        Expr::Call(call) if is_typeconv_fn(call.func.name) => walk_typeconv(call),
-        Expr::Call(call) if is_label_fn(call.func.name) => walk_label(call),
-        Expr::Call(call) if is_sort_fn(call.func.name) => walk_sort(call),
-        Expr::Call(call) if call.func.name == "info" => walk_info(call),
-        Expr::Call(call) => walk_call(call),
-        Expr::Binary(bin) => walk_binary(bin),
-        Expr::Paren(p) => walk(&p.expr),
-        // `UnaryExpr` is built only by negation (`Neg`); unary `+` is folded to
-        // identity and `-<literal>` to a negated `NumberLiteral`. A scalar
-        // operand was dispatched to `lower_scalar` above (→ `Negative`), so this
-        // is a vector projection. Unary negation retains the metric name.
-        Expr::Unary(u) => Ok(Unresolved::PromqlMap {
-            child: Rc::new(walk(&u.expr)?),
-            sample: Scalar::Negative {
-                expr: Box::new(Scalar::Column(ColumnRef::SampleValue)),
-                semantics: ExprSemantics::Promql,
-            },
-            drop_metric_name: false,
-        }),
-        Expr::Subquery(sq) => {
-            let subquery = Unresolved::PromqlSubquery {
-                range: sq.range,
-                resolution: sq.step,
-                child: Rc::new(walk(&sq.expr)?),
-            };
-            // `offset`/`@` move the whole subquery, including its step grid.
-            let shift = time_shift(sq.offset.as_ref(), sq.at.as_ref())?;
-            Ok(if shift.is_identity() {
-                subquery
-            } else {
-                Unresolved::TimeShift {
-                    shift,
-                    child: Rc::new(subquery),
-                }
-            })
-        }
-        Expr::VectorSelector(vs) => {
-            let (metric, matchers, shift) = vs_parts(vs)?;
-            Ok(instant_source(metric, matchers, shift))
-        }
-        Expr::MatrixSelector(ms) => {
-            let (metric, matchers, shift) = vs_parts(&ms.vs)?;
-            Ok(Unresolved::TimeRange {
-                range: ms.range,
-                kind: TimeRangeKind::Range,
-                child: Rc::new(filtered_source(metric, matchers, shift)),
-            })
-        }
-        // Scalar-typed, dispatched above; kept for exhaustiveness. String
-        // literals only appear as function args (`label_replace`, …), so a
-        // bare one is rejected (issue #35).
-        Expr::NumberLiteral(_) => unreachable!("scalar handled above"),
-        Expr::StringLiteral(_) => Err(LoweringError::UnsupportedFeature(
-            "bare string literal".into(),
-        )),
-        Expr::Extension(_) => Err(LoweringError::UnsupportedFeature(
-            "extension expression".into(),
-        )),
-    }
-}
-
-/// Lower a scalar-typed PromQL expression to a scalar expression. A constant
-/// sub-expression folds to one `Literal` (as `num_expr` always did); anything
-/// else keeps its structure: `-time()` → `Negative`, `time() - 1` →
-/// `Arithmetic`, `scalar(v)` → `PromqlScalarFromVector`, and a `bool`
-/// comparison → `Case(Compare → 1, else 0)` (PromQL yields `0`/`1`).
-fn lower_scalar(expr: &Expr) -> Result<Scalar> {
-    if let Ok(v) = num_expr(expr) {
-        return Ok(Scalar::Literal(ScalarValue::Float64(v)));
-    }
-    match expr {
-        Expr::Paren(p) => lower_scalar(&p.expr),
-        Expr::Unary(u) => Ok(Scalar::Negative {
-            expr: Box::new(lower_scalar(&u.expr)?),
-            semantics: PROMQL,
-        }),
-        Expr::Binary(bin) => lower_scalar_binary(bin),
-        Expr::Call(call) => match call.func.name {
-            "time" => Ok(Scalar::EvalTimestamp),
-            "pi" => Ok(Scalar::Literal(ScalarValue::Float64(std::f64::consts::PI))),
-            "scalar" => Ok(Scalar::PromqlScalarFromVector(Rc::new(walk(arg(
-                call, 0,
-            )?)?))),
-            // `min_of`/`max_of` fold only over constants (#89); the fold above
-            // failed, so surface its error for the non-constant argument.
-            name if is_scalar_reducer_fn(name) => Err(num_expr(expr).unwrap_err()),
-            other => Err(LoweringError::UnsupportedFunction(other.to_string())),
-        },
-        other => Err(LoweringError::UnsupportedFeature(format!(
-            "scalar expression `{other}`"
-        ))),
-    }
-}
-
-/// `<scalar> op <scalar>`: arithmetic is an `Arithmetic` expression; a
-/// comparison needs the `bool` modifier (PromQL has no scalar filter) and
-/// becomes `Case(Compare → 1.0, else 0.0)`. The parser already rejects both a
-/// bool-less scalar comparison and a scalar set op; both are re-checked here.
-fn lower_scalar_binary(bin: &BinaryExpr) -> Result<Scalar> {
-    let left = Box::new(lower_scalar(&bin.lhs)?);
-    let right = Box::new(lower_scalar(&bin.rhs)?);
-    match binop(bin.op.id())? {
-        BinaryOpKind::Arithmetic(op) => Ok(Scalar::Arithmetic {
-            op,
-            left,
-            right,
-            semantics: PROMQL,
-        }),
-        BinaryOpKind::Compare(op) | BinaryOpKind::CompareBool(op) => {
-            if !bin.return_bool() {
-                return Err(LoweringError::InvalidParameter(
-                    "a comparison between two scalars requires the `bool` modifier".into(),
-                ));
-            }
-            let compare = Scalar::Compare {
-                left,
-                op,
-                right,
-                semantics: PROMQL,
-            };
-            Ok(Scalar::Case {
-                operand: None,
-                branches: vec![(compare, Scalar::Literal(ScalarValue::Float64(1.0)))],
-                else_expr: Some(Box::new(Scalar::Literal(ScalarValue::Float64(0.0)))),
-            })
-        }
-        BinaryOpKind::Set(_) => Err(LoweringError::UnsupportedFeature(
-            "set operator between two scalars".into(),
-        )),
-    }
-}
-
-/// A binary operation over two vectors.
-fn vector_binary(
-    kind: BinaryOpKind,
-    vector_match: Option<VectorMatch>,
-    return_bool: bool,
-    lhs: Unresolved,
-    rhs: Unresolved,
-) -> Unresolved {
-    Unresolved::BinaryOp {
-        operator: BinaryOperator {
-            kind,
-            vector_match,
-            checked_relative_division: false,
-            checked_finite_division: false,
-        },
-        return_bool,
-        lhs: Rc::new(lhs),
-        rhs: Rc::new(rhs),
-    }
-}
-
-/// Lower a bare function call (`rate(m[5m])`, `max_over_time(m[5m])`, …).
-///
-/// The common case routes through the flat `lower_inner_call` template. The one
-/// exception is a `*_over_time`/`quantile_over_time` function applied to a
-/// **sub-query** (`max_over_time(rate(m[5m])[1h:])`): its argument is a
-/// `PromQLSubquery`, not a matrix selector, so the flat template's
-/// `extract_matrix` can't accept it. Lower the sub-query recursively and reduce
-/// it per series (issue #27).
-fn walk_call(call: &Call) -> Result<Unresolved> {
-    if let Some(tree) = range_fn_over_subquery(call)? {
-        return Ok(tree);
-    }
-    build(lower_inner_call(call)?, vec![], Outer::None)
-}
-
-/// A range-vector function applied to a **sub-query** — `f(<inst>[range:res])`.
-///
-/// Covers the whole range-vector family: the `*_over_time` reducers,
-/// `rate`/`irate`/`increase`, and the counter-derivatives
-/// (`changes`/`delta`/`idelta`/`deriv`/`resets`/`predict_linear`/
-/// `double_exponential_smoothing`). Each lowers to a per-series `Aggregate{[f]}`
-/// directly over the `PromqlSubquery` — the sub-query is the range context, so
-/// there is no separate `Window`/`TimeRange` (this walk treats the `PromqlSubquery`
-/// node itself as the range marker). Returns `None` when `call` isn't a range
-/// function or its argument isn't a sub-query, so the flat matrix-selector
-/// template still handles `f(m[w])` (issues #42, #55).
-fn range_fn_over_subquery(call: &Call) -> Result<Option<Unresolved>> {
-    // `rate`/`increase`/`irate` carry their window in the `AggFunc`; over a
-    // sub-query that window is the sub-query's own range.
-    if let "rate" | "irate" | "increase" = call.func.name {
-        let arg_expr = arg(call, 0)?;
-        if subquery_range(arg_expr).is_none() {
-            return Ok(None);
-        }
-        let inner = match call.func.name {
-            "rate" => InnerFunc::Rate,
-            "irate" => InnerFunc::IRate,
-            "increase" => InnerFunc::Increase,
-            _ => unreachable!(),
-        };
-        return Ok(Some(per_series_aggregate(
-            vec![],
-            inner_intent(&inner),
-            walk(arg_expr)?,
-        )));
-    }
-
-    // `*_over_time` reducers + counter-derivatives: the func-kind, and the index
-    // of the matrix/sub-query argument (`quantile_over_time` reads φ from arg 0,
-    // so its matrix is arg 1; the rest take arg 0 + trailing scalar params).
-    let (inner, matrix_idx): (InnerFunc, usize) = match call.func.name {
-        "avg_over_time" => (InnerFunc::Avg, 0),
-        "min_over_time" => (InnerFunc::Min, 0),
-        "max_over_time" => (InnerFunc::Max, 0),
-        "sum_over_time" => (InnerFunc::Sum, 0),
-        "stddev_over_time" => (InnerFunc::StdDev, 0),
-        "stdvar_over_time" => (InnerFunc::Variance, 0),
-        "count_over_time" => (InnerFunc::Count, 0),
-        "distinct_over_time" => (InnerFunc::Cardinality, 0),
-        "entropy_over_time" => (InnerFunc::FrequencyEntropy, 0),
-        "l2_over_time" => (InnerFunc::FrequencyL2, 0),
-        "quantile_over_time" => (InnerFunc::Quantile(quantile_param(num_arg(call, 0)?)?), 1),
-        "changes" => (InnerFunc::Changes, 0),
-        "delta" => (InnerFunc::Delta, 0),
-        "idelta" => (InnerFunc::IDelta, 0),
-        "deriv" => (InnerFunc::Deriv, 0),
-        "resets" => (InnerFunc::Resets, 0),
-        "last_over_time" => (InnerFunc::LastOverTime, 0),
-        "first_over_time" => (InnerFunc::FirstOverTime, 0),
-        "mad_over_time" => (InnerFunc::MadOverTime, 0),
-        "ts_of_min_over_time" => (InnerFunc::TsOfMinOverTime, 0),
-        "ts_of_max_over_time" => (InnerFunc::TsOfMaxOverTime, 0),
-        "ts_of_first_over_time" => (InnerFunc::TsOfFirstOverTime, 0),
-        "ts_of_last_over_time" => (InnerFunc::TsOfLastOverTime, 0),
-        "predict_linear" => (InnerFunc::PredictLinear(num_arg(call, 1)?), 0),
-        "double_exponential_smoothing" => (
-            InnerFunc::DoubleExp {
-                smoothing: num_arg(call, 1)?,
-                trend: num_arg(call, 2)?,
-            },
-            0,
-        ),
-        _ => return Ok(None),
-    };
-    let arg_expr = arg(call, matrix_idx)?;
-    if !is_subquery(arg_expr) {
-        return Ok(None);
-    }
-    Ok(Some(per_series_aggregate(
-        vec![],
-        inner_intent(&inner),
-        walk(arg_expr)?,
-    )))
-}
-
-/// A (parenthesised) PromQL sub-query — `<inst>[range:res]`.
-fn is_subquery(expr: &Expr) -> bool {
-    subquery_range(expr).is_some()
-}
-
-/// The `range` of a (parenthesised) sub-query argument, if it is one.
-fn subquery_range(expr: &Expr) -> Option<Duration> {
-    match expr {
-        Expr::Subquery(sq) => Some(sq.range),
-        Expr::Paren(p) => subquery_range(&p.expr),
-        _ => None,
-    }
-}
-
-fn walk_aggregate(agg: &AggregateExpr) -> Result<Unresolved> {
-    let (keys, without) = resolve_group(agg)?;
-    let outer = outer_kind(agg)?;
-
-    // `without(...)` grouping is modelled only for the reducing aggregations
-    // (sum/avg/count/…), whose grouping lives on an `Aggregate` node. `topk`/
-    // `bottomk` (→ `Sort.partition_by`) and `limitk`/`limit_ratio` (→ `PromqlSeriesSample`)
-    // would need without-partitioning too; reject rather than silently lower
-    // them as a `by` grouping (issue #39).
-    if without && matches!(outer, Outer::TopK { .. } | Outer::Sample { .. }) {
-        return Err(LoweringError::UnsupportedFeature(
-            "`without(...)` is only supported on reducing aggregations, not \
-             topk/bottomk/limitk"
-                .into(),
-        ));
-    }
-
-    // Fast path — the argument is a bare selector or a single range-vector
-    // function (`rate`/`increase`/`*_over_time`). `lower_inner` lowers it via the
-    // flat selector/call template, which also recognises the heavy-hitter
-    // `topk(k, count_over_time(...))` shape. This is the common two-level case
-    // (`sum by (job) (rate(m[5m]))`).
-    //
-    // General nesting — the argument is itself a composite expression: another
-    // aggregate (`max(sum by (job) (rate(m[5m])))`), a binary op, a sub-query, or
-    // a function lowered elsewhere. Lower it recursively with the same `walk`
-    // used at the top level, then wrap it in the outer aggregation (issue #27; a
-    // negated argument `sum(-m)` lowers here too, #36). A genuinely unsupported
-    // inner expression surfaces its own error rather than being mislowered.
-    //
-    // Either way, `mark_without` flips the resulting outer `Aggregate` to the
-    // exclusion form when the modifier was `without(...)`.
-    let built = match lower_inner(&agg.expr) {
-        Ok(inner) => build(inner, keys, outer)?,
-        Err(_) => build_over_sub_dag(outer, keys, walk(&agg.expr)?)?,
-    };
-    Ok(mark_without(built, without))
-}
-
-/// Map an `AggregateExpr`'s operator (`sum`/`avg`/`topk`/…) to the [`Outer`]
-/// shape, independent of what the argument is — so both the flat fast path and
-/// the general recursive path share one operator-dispatch.
-fn outer_kind(agg: &AggregateExpr) -> Result<Outer> {
-    let op = agg.op.id();
-
-    Ok(if op == token::T_TOPK {
-        Outer::TopK {
-            k: count_param(agg)?,
-            descending: true,
-        }
-    } else if op == token::T_BOTTOMK {
-        Outer::TopK {
-            k: count_param(agg)?,
-            descending: false,
-        }
-    } else if op == token::T_COUNT {
-        Outer::Count
-    } else if op == token::T_SUM {
-        Outer::Plain(OuterIntent::Sum)
-    } else if op == token::T_GROUP {
-        // `group(v)` yields a constant 1 per group (presence), not a sum of
-        // values — a distinct intent, never folded onto `Sum` (issue #49).
-        Outer::Plain(OuterIntent::Group)
-    } else if op == token::T_COUNT_VALUES {
-        // `count_values("l", v)` groups by sample value and counts, emitting the
-        // value as a new label `l` (the string parameter) — issue #49.
-        Outer::CountValues {
-            label: str_param(agg)?,
-        }
-    } else if op == token::T_LIMITK {
-        // `limitk(k, v)` — up to k series per group (issue #86).
-        Outer::Sample {
-            kind: SampleKind::LimitK(count_param(agg)? as usize),
-        }
-    } else if op == token::T_LIMIT_RATIO {
-        // `limit_ratio(r, v)` — an r-fraction of series per group (issue #86).
-        Outer::Sample {
-            kind: SampleKind::LimitRatio(ratio_param(agg)?),
-        }
-    } else if op == token::T_AVG {
-        Outer::Plain(OuterIntent::Avg)
-    } else if op == token::T_MIN {
-        Outer::Plain(OuterIntent::Min)
-    } else if op == token::T_MAX {
-        Outer::Plain(OuterIntent::Max)
-    } else if op == token::T_STDDEV {
-        Outer::Plain(OuterIntent::StdDev)
-    } else if op == token::T_STDVAR {
-        Outer::Plain(OuterIntent::Variance)
-    } else if op == token::T_QUANTILE {
-        Outer::Plain(OuterIntent::Quantile(quantile_param(num_param(agg)?)?))
-    } else {
-        return Err(LoweringError::UnsupportedAggregateOp(format!(
-            "aggregate token {op}"
-        )));
-    })
-}
-
-/// Wrap an already-lowered Unresolved sub-DAG in the outer aggregation. This is the
-/// general-nesting counterpart to [`build`]: where `build` assembles the
-/// two-level shape from a flat [`Inner`], this composes the outer operator over
-/// an arbitrary child (`max(sum by (job) (…))`, `sum(a + b)`, …).
-///
-/// A heavy-hitter `TopK` is only recognised on the flat `count_over_time` shape
-/// (handled in `build`); over a general sub-DAG, `topk`/`bottomk` is a generic
-/// order-by-value + limit — the same `Sort{partition_by} → Limit` pair `build`
-/// emits for any non-heavy-hitter ranking.
-/// Flip the outer `Aggregate` produced for a `without(...)` grouping into the
-/// exclusion form. The reducing-aggregation `build` paths place that aggregate
-/// at the root; `walk_aggregate` has already rejected the non-aggregate outers
-/// (topk/limitk), so a `without` grouping always has an `Aggregate` here (issue
-/// #39). A no-op when the modifier was `by`.
-/// Flip the outer `Aggregate` produced for a `without(...)` grouping into the
-/// exclusion form. A no-op when the modifier was `by`.
-///
-/// `reduction_for` (used by [`windowed_aggregate`]/[`outer_aggregate`] to
-/// build this node) decides `PerEntity` vs `Reduce(by)` *without* knowing
-/// about `without` yet — it only ever sees `by`-mode keys, since `without`'s
-/// excluded-labels list is applied here, after the fact, exactly like the
-/// pre-#179 legacy relational tree's own `mark_without` did (its
-/// converter read `without` only after this front-end step had already set
-/// it). Whether
-/// `reduction_for` picked `PerEntity` (only possible when `keys` was empty)
-/// or `Reduce(by)`, the correct answer under `without(...)` is always
-/// `Reduce(without(keys))`: a `without` grouping is never label-preserving —
-/// per-entity requires `!by.is_without()` — so this both re-tags an existing
-/// `Reduce` and upgrades a wrongly-early `PerEntity` guess, uniformly.
-fn mark_without(tree: Unresolved, without: bool) -> Unresolved {
-    if !without {
-        return tree;
-    }
-    match tree {
-        Unresolved::Aggregate {
-            reduction,
-            measures,
-            output_names,
-            filters,
-            having,
-            child,
-        } => {
-            let keys = match reduction {
-                Reduction::Reduce(by) => by.keys().to_vec(),
-                Reduction::PerEntity => vec![],
-            };
-            Unresolved::Aggregate {
-                reduction: Reduction::Reduce(GroupKeys::without(keys)),
-                measures,
-                output_names,
-                filters,
-                having,
-                child,
-            }
-        }
-        other => other,
-    }
-}
-
-fn build_over_sub_dag(outer: Outer, keys: Vec<ColumnRef>, child: Unresolved) -> Result<Unresolved> {
-    Ok(match outer {
-        // `walk_aggregate` always passes a real aggregator; `None` can't occur.
-        Outer::None => child,
-        Outer::Plain(intent) => outer_aggregate(keys, outer_intent(&intent), child),
-        Outer::Count => outer_aggregate(keys, count(), child),
-        Outer::CountValues { label } => {
-            outer_aggregate(keys, AggIntent::CountValues { label }, child)
-        }
-        Outer::Sample { kind } => Unresolved::PromqlSeriesSample {
-            by: keys.into(),
-            kind,
-            child: Rc::new(child),
-        },
-        Outer::TopK { k, descending } => {
-            let weighted_counter_ranking = matches!(
-                &child,
-                Unresolved::Aggregate {
-                    measures,
-                    child: sum_child,
-                    ..
-                } if matches!(measures.as_slice(), [AggIntent::Sum { .. }])
-                    && matches!(sum_child.as_ref(), Unresolved::Aggregate { measures, .. }
-                        if matches!(measures.as_slice(), [AggIntent::Rate | AggIntent::Increase]))
-            );
-            let direct_counter_ranking = matches!(&child, Unresolved::Aggregate {
-                measures, reduction: Reduction::PerEntity, ..
-            } if matches!(measures.as_slice(), [AggIntent::Rate | AggIntent::Increase]));
-            if descending && (weighted_counter_ranking || direct_counter_ranking) {
-                return Ok(outer_aggregate(
-                    keys,
-                    AggIntent::TopK {
-                        k: k as usize,
-                        accuracy: current_accuracy(),
-                    },
-                    child,
-                ));
-            }
-            ranked_by_value(keys, k, descending, child)
-        }
-    })
-}
-
-/// Generic `topk`/`bottomk`: `Limit{k} → Sort{value, partition_by: keys}` over
-/// `child` — an order-by-value ranking, not a heavy-hitter intent.
-fn ranked_by_value(
-    keys: Vec<ColumnRef>,
-    k: u64,
-    descending: bool,
-    child: Unresolved,
-) -> Unresolved {
-    let sorted = Unresolved::Sort {
-        keys: vec![UnresolvedSortKey {
-            expr: Scalar::Column(ColumnRef::SampleValue),
-            ascending: !descending,
-            nulls_first: false,
-        }],
-        partition_by: keys.into(),
-        child: Rc::new(child),
-    };
-    Unresolved::Limit {
-        n: Some(k as usize),
-        offset: 0,
-        partition_by: GroupKeys::none(),
-        child: Rc::new(sorted),
-    }
-}
-
-/// The `histogram_*` function family (issues #43, histogram_quantile).
-///
-/// `histogram_quantile(φ, <expr>)` lowers `<expr>` in full — preserving any
-/// `sum by (le)` / `rate` structure inside it. The classic `le`-bucket form
-/// becomes [`classic_histogram_quantile`]; a native histogram or raw samples
-/// become a `Quantile` over the whole argument.
-/// The native-histogram accessors (`histogram_count`/`sum`/`avg`/`stddev`/
-/// `stdvar`/`fraction`) each extract one float per series, lowering to a
-/// per-series `Aggregate{[accessor]}` directly over the (instant) argument.
-/// `histogram_fraction(lower, upper, v)` reads its bounds from args 0/1 and the
-/// vector from arg 2; the rest take the vector at arg 0.
-fn walk_histogram(call: &Call) -> Result<Unresolved> {
-    if call.func.name == "histogram_quantiles" {
-        return walk_histogram_quantiles(call);
-    }
-    if call.func.name == "histogram_quantile" {
-        let phi = quantile_param(num_arg(call, 0)?)?;
-        let arg_expr = arg(call, 1)?;
-        // Two lowerings of `histogram_quantile(φ, …)`:
-        //  - classic `le`-bucket form → `HistogramQuantile`, exact interpolation
-        //    over cumulative buckets (not sketch-able).
-        //  - native-histogram / raw-samples form → the generic `Quantile` intent
-        //    (sketch-able).
-        // The true signal is the argument's sample type: a declared
-        // `HistogramKind` (issue #79) drives the choice when available, else we
-        // fall back to the structural `by (le)`/`_bucket` heuristic (issue #43).
-        if !histogram_arg_is_sketchable(arg_expr)? {
-            return Ok(classic_histogram_quantile(phi, "", walk(arg_expr)?));
-        }
-        let func = AggIntent::Quantile {
-            col: None,
-            q: phi,
-            accuracy: current_accuracy(),
-        };
-        return Ok(outer_aggregate(vec![], func, walk(arg_expr)?));
-    }
-    Err(LoweringError::UnsupportedFeature(
-        "native histogram samples have no IR representation".into(),
-    ))
-}
-
-/// Classic-bucket `histogram_quantile(φ, child)`. One histogram is the set of
-/// series that differ only in `le`, so the aggregate groups `without (le)`.
-/// That grouping also seeds `le` into a usage-derived source schema, even
-/// when no matcher names it. An empty `output_name` keeps the intent-keyed name.
-fn classic_histogram_quantile(q: f64, output_name: &str, child: Unresolved) -> Unresolved {
-    let le = ColumnRef::Named("le".into());
-    Unresolved::Aggregate {
-        reduction: Reduction::Reduce(GroupKeys::without(vec![le.clone()])),
-        measures: vec![AggIntent::HistogramQuantile { q, le }],
-        output_names: vec![output_name.into()],
-        filters: vec![],
-        having: None,
-        child: Rc::new(child),
-    }
-}
-
-/// `histogram_quantiles(v, "label", φ₀, φ₁, …)` — the experimental multi-quantile
-/// form (issue #109). It is `histogram_quantile(φᵢ, v)` fanned out over the
-/// quantiles, each branch's output series tagged with `label = φᵢ`.
-///
-/// Lowers to a `Concat` of one `PromqlRelabel`-wrapped quantile branch per φ, reusing
-/// the single-quantile decision — classic `le`-buckets interpolate
-/// (`HistogramQuantile`), native histograms / raw samples take the sketch-able
-/// `Quantile` (issues #43 / #79) — so the two functions cannot diverge.
-///
-/// The vector argument is lowered once per branch, duplicating the sub-DAG —
-/// a future workload-level reuse pass could hoist it back into a single
-/// producer.
-///
-/// Each branch aliases its value column to `value` rather than taking the
-/// intent-keyed name (`quantile_0_5`, `quantile_0_9`, …). `Concat` derives its
-/// schema from the first child, so branches that disagree on a column *name*
-/// would make the merged schema silently misdescribe every branch but one. The
-/// quantile is carried by the `label` column, which is exactly where Prometheus
-/// puts it.
-fn walk_histogram_quantiles(call: &Call) -> Result<Unresolved> {
-    let vec_expr = arg(call, 0)?;
-    let label = str_arg(call, 1)?;
-    if call.args.args.len() < 3 {
-        return Err(LoweringError::MissingArgument(
-            "histogram_quantiles(v, label, φ…) needs at least one quantile".into(),
-        ));
-    }
-    // The bucket-vs-native choice is a property of the argument, not of φ.
-    let sketchable = histogram_arg_is_sketchable(vec_expr)?;
-    let branches = (2..call.args.args.len())
-        .map(|i| {
-            let phi = bounded_quantile_param(num_arg(call, i)?)?;
-            let child = walk(vec_expr)?;
-            // Each branch aliases its value column to "value" (not the
-            // intent-keyed default) so `Concat` — which derives its schema
-            // from the first branch — doesn't silently misdescribe the rest.
-            let quantile = if sketchable {
-                let intent = AggIntent::Quantile {
-                    col: None,
-                    q: phi,
-                    accuracy: current_accuracy(),
-                };
-                Unresolved::Aggregate {
-                    reduction: reduction_for(&[], intent.is_per_series()),
-                    measures: vec![intent],
-                    output_names: vec!["value".into()],
-                    filters: vec![],
-                    having: None,
-                    child: Rc::new(child),
-                }
-            } else {
-                classic_histogram_quantile(phi, "value", child)
-            };
-            Ok(Unresolved::PromqlRelabel {
-                dst: label.clone(),
-                value: Scalar::Literal(ScalarValue::Utf8(open_metrics_float(phi))),
-                child: Rc::new(quantile),
-            })
-        })
-        .collect::<Result<Vec<_>>>()?;
-    // No discriminator asserted here today (issue #228): the φ value each
-    // branch carries via `PromqlRelabel` *is* structurally a distinct
-    // per-branch discriminator, but nothing downstream currently needs the
-    // resulting compound unique key — see
-    // `docs/design_docs/concat-unique-keys-decision.md`. `Unresolved::concat`
-    // keeps `output_schema`'s default (drop `unique_keys` entirely).
-    Ok(Unresolved::concat(branches))
-}
-
-/// Prometheus's `labels.FormatOpenMetricsFloat` — how `histogram_quantiles`
-/// renders each φ into its label value. Go's `%g` shortest round-trip, switching
-/// to exponent form outside `[1e-4, 1e21)`, with `.0` appended when the result
-/// would otherwise look like an integer.
-fn open_metrics_float(v: f64) -> String {
-    // The cases upstream hardcodes.
-    if v == 1.0 {
-        return "1.0".into();
-    }
-    if v == 0.0 {
-        return "0.0".into();
-    }
-    if v == -1.0 {
-        return "-1.0".into();
-    }
-    if v.is_nan() {
-        return "NaN".into();
-    }
-    if v.is_infinite() {
-        return if v.is_sign_positive() { "+Inf" } else { "-Inf" }.into();
-    }
-    let sci = format!("{v:e}");
-    let exp: i32 = sci
-        .split_once('e')
-        .and_then(|(_, e)| e.parse().ok())
-        .unwrap_or(0);
-    if !(-4..21).contains(&exp) {
-        // Go writes a signed, zero-padded two-digit exponent: `1e-05`.
-        let (mantissa, _) = sci.split_once('e').unwrap_or((sci.as_str(), "0"));
-        let sign = if exp < 0 { '-' } else { '+' };
-        return format!("{mantissa}e{sign}{:02}", exp.abs());
-    }
-    let s = format!("{v}");
-    if s.contains(['e', '.']) {
-        s
-    } else {
-        format!("{s}.0")
-    }
-}
-
-/// The calendar functions (issue #46); `time()` is scalar-typed and lowers in
-/// `lower_scalar`.
-fn is_time_fn(name: &str) -> bool {
-    matches!(
-        name,
-        "timestamp"
-            | "minute"
-            | "hour"
-            | "day_of_week"
-            | "day_of_month"
-            | "day_of_year"
-            | "month"
-            | "year"
-            | "days_in_month"
-    )
-}
-
-/// `timestamp(v)` and the calendar accessors → `Aggregate{[TimeFn(f)]}` over
-/// the argument vector, or over `PromqlVectorFromScalar(EvalTimestamp)` for the
-/// no-argument calendar forms (`hour()`, `day_of_week()`, …). Issue #46.
-fn walk_time(call: &Call) -> Result<Unresolved> {
-    // timestamp() reads the selected sample's timestamp, not its value.
-    if call.func.name == "timestamp" {
-        return Ok(outer_aggregate(
-            vec![],
-            AggIntent::TimeFn(TimeFunc::Timestamp),
-            walk(arg(call, 0)?)?,
-        ));
-    }
-    let child = if call.args.args.is_empty() {
-        Unresolved::PromqlVectorFromScalar(Scalar::EvalTimestamp)
-    } else {
-        walk(arg(call, 0)?)?
-    };
-    Ok(Unresolved::PromqlMap {
-        child: Rc::new(child),
-        sample: Scalar::FunctionCall {
-            name: format!("promql_{}", call.func.name),
-            args: vec![Scalar::Column(ColumnRef::SampleValue)],
-        },
-        drop_metric_name: true,
-    })
-}
-
-/// The presence functions (issue #47).
-fn is_presence_fn(name: &str) -> bool {
-    matches!(name, "absent" | "absent_over_time" | "present_over_time")
-}
-
-/// `absent(v)` / `absent_over_time(m[w])` / `present_over_time(m[w])` — lowered
-/// to an `Aggregate{[Absent/…]}` over the (instant or range) argument. The
-/// empty-result → synthesized-1-sample logic is a post-ASAP/runtime concern;
-/// the canonical tree only marks the operation (issue #47).
-fn walk_presence(call: &Call) -> Result<Unresolved> {
-    let func = match call.func.name {
-        "absent" => AggIntent::Absent,
-        "absent_over_time" => AggIntent::AbsentOverTime,
-        "present_over_time" => AggIntent::PresentOverTime,
-        other => return Err(LoweringError::UnsupportedFunction(other.to_string())),
-    };
-    // arg 0 is the instant vector (`absent`) or range vector (`*_over_time`);
-    // `walk` produces a `Window` for the matrix-selector forms.
-    Ok(outer_aggregate(vec![], func, walk(arg(call, 0)?)?))
-}
-
-/// The scalar→vector conversion (issue #48); `scalar(v)` is scalar-typed and
-/// lowers in `lower_scalar`. `info` is *not* here: it is a label-enrichment
-/// join, not a type conversion (#84).
-fn is_typeconv_fn(name: &str) -> bool {
-    name == "vector"
-}
-
-/// `vector(s)` — promote a scalar to a label-less instant vector carrying the
-/// scalar expression `s` (issue #48).
-fn walk_typeconv(call: &Call) -> Result<Unresolved> {
-    Ok(Unresolved::PromqlVectorFromScalar(lower_scalar(arg(
-        call, 0,
-    )?)?))
-}
-
-/// The instant-vector reordering functions (issue #51).
-fn is_sort_fn(name: &str) -> bool {
-    matches!(
-        name,
-        "sort" | "sort_desc" | "sort_by_label" | "sort_by_label_desc"
-    )
-}
-
-/// `sort`/`sort_desc(v)` reorder an instant vector by sample value;
-/// `sort_by_label`/`sort_by_label_desc(v, "l"…)` reorder by label values. All
-/// lower to a bare `Sort` (no `Limit`) over the vector argument — a faithful,
-/// row-preserving reordering (issue #51).
-fn walk_sort(call: &Call) -> Result<Unresolved> {
-    let child = Rc::new(walk(arg(call, 0)?)?);
-    let (by_value, ascending) = match call.func.name {
-        "sort" => (true, true),
-        "sort_desc" => (true, false),
-        "sort_by_label" => (false, true),
-        "sort_by_label_desc" => (false, false),
-        other => return Err(LoweringError::UnsupportedFunction(other.to_string())),
-    };
-    let sort_key = |expr| UnresolvedSortKey {
-        expr,
-        ascending,
-        nulls_first: false,
-    };
-    let keys = if by_value {
-        vec![sort_key(Scalar::Column(ColumnRef::SampleValue))]
-    } else {
-        // `sort_by_label(v, "l1", "l2", …)` — one key per label arg, in order.
-        if call.args.args.len() < 2 {
-            return Err(LoweringError::MissingArgument(
-                "sort_by_label needs at least one label".into(),
-            ));
-        }
-        (1..call.args.args.len())
-            .map(|i| {
-                Ok(sort_key(Scalar::Column(ColumnRef::Named(str_arg(
-                    call, i,
-                )?))))
-            })
-            .collect::<Result<Vec<_>>>()?
-    };
-    Ok(Unresolved::Sort {
-        keys,
-        partition_by: GroupKeys::none(),
-        child,
-    })
-}
-
-/// `info(v, [selector])` — a label-enrichment join. Lowers the input vector and
-/// wraps it in an `PromqlInfoEnrich` carrying the (optional) data-label selector's
-/// matchers; the actual join against the info metric — on shared identifying
-/// labels — is resolved during post-ASAP binding (issue #84).
-fn walk_info(call: &Call) -> Result<Unresolved> {
-    let child = Rc::new(walk(arg(call, 0)?)?);
-    let selector = match call.args.args.get(1) {
-        Some(sel) => info_selector(sel)?,
-        None => Vec::new(), // default: enrich from `target_info`
-    };
-    Ok(Unresolved::PromqlInfoEnrich { selector, child })
-}
-
-/// Extract the `info` data-label selector's matchers. Unlike an ordinary
-/// selector these are **info-metric-side** and may carry regex / multiple
-/// `__name__` matchers (which pick the info metric(s)), so they bypass the
-/// single-metric `vs_parts` restriction and are kept symbolic.
-fn info_selector(expr: &Expr) -> Result<Vec<InfoMatcher>> {
-    match expr {
-        Expr::VectorSelector(vs) => Ok(vs
-            .matchers
-            .matchers
-            .iter()
-            .map(|m| InfoMatcher {
-                label: m.name.clone(),
-                op: match &m.op {
-                    MatchOp::Equal => CompareOpKind::Eq,
-                    MatchOp::NotEqual => CompareOpKind::Ne,
-                    MatchOp::Re(_) => CompareOpKind::Regex,
-                    MatchOp::NotRe(_) => CompareOpKind::NotRegex,
-                },
-                value: m.value.clone(),
-            })
-            .collect()),
-        Expr::Paren(p) => info_selector(&p.expr),
-        other => Err(LoweringError::UnsupportedFeature(format!(
-            "`info` data-label selector must be a label-matcher set, got `{other}`"
-        ))),
-    }
-}
-
-/// The label-rewrite functions (issue #50).
-fn is_label_fn(name: &str) -> bool {
-    matches!(name, "label_replace" | "label_join")
-}
-
-/// `label_replace(v, dst, replacement, src, regex)` /
-/// `label_join(v, dst, sep, src…)` — per-series label rewrites. Both lower to a
-/// `PromqlRelabel` over the fully-lowered vector argument, differing only in the
-/// expression that computes the destination label: `label_replace` a regex
-/// capture-expansion, `label_join` a separator-joined concatenation. Sample
-/// values are untouched; the regex-match-or-passthrough and capture-expansion
-/// are post-ASAP/runtime concerns (issue #50).
-fn walk_label(call: &Call) -> Result<Unresolved> {
-    let child = Rc::new(walk(arg(call, 0)?)?);
-    match call.func.name {
-        "label_replace" => {
-            let dst = str_arg(call, 1)?;
-            let replacement = str_arg(call, 2)?;
-            let src = str_arg(call, 3)?;
-            let regex = str_arg(call, 4)?;
-            let value = Scalar::FunctionCall {
-                name: "label_replace".into(),
-                args: vec![
-                    Scalar::Column(ColumnRef::Named(src)),
-                    Scalar::Literal(ScalarValue::Utf8(regex)),
-                    Scalar::Literal(ScalarValue::Utf8(replacement)),
-                ],
-            };
-            Ok(Unresolved::PromqlRelabel { dst, value, child })
-        }
-        "label_join" => {
-            // label_join(v, dst, sep, src_1, …, src_n) — needs ≥1 source label.
-            if call.args.args.len() < 4 {
-                return Err(LoweringError::MissingArgument(
-                    "label_join(v, dst, sep, src…) needs at least one source label".into(),
-                ));
-            }
-            let dst = str_arg(call, 1)?;
-            let sep = str_arg(call, 2)?;
-            let mut args = vec![Scalar::Literal(ScalarValue::Utf8(sep))];
-            for i in 3..call.args.args.len() {
-                args.push(Scalar::Column(ColumnRef::Named(str_arg(call, i)?)));
-            }
-            let value = Scalar::FunctionCall {
-                name: "label_join".into(),
-                args,
-            };
-            Ok(Unresolved::PromqlRelabel { dst, value, child })
-        }
-        other => Err(LoweringError::UnsupportedFunction(other.to_string())),
-    }
-}
-
-/// The element-wise math / trig functions (issue #45).
-fn is_math_fn(name: &str) -> bool {
-    matches!(
-        name,
-        "abs"
-            | "ceil"
-            | "floor"
-            | "exp"
-            | "ln"
-            | "log2"
-            | "log10"
-            | "sqrt"
-            | "sgn"
-            | "sin"
-            | "cos"
-            | "tan"
-            | "asin"
-            | "acos"
-            | "atan"
-            | "sinh"
-            | "cosh"
-            | "tanh"
-            | "asinh"
-            | "acosh"
-            | "atanh"
-            | "deg"
-            | "rad"
-            | "round"
-            | "clamp"
-            | "clamp_min"
-            | "clamp_max"
-    )
-}
-
-/// A math / trig function — a per-series element-wise value transform, lowered
-/// to a typed scalar projection over the instant-vector argument.
-/// `pi()` is scalar-typed and lowers in `lower_scalar` (issue #45).
-fn walk_math(call: &Call) -> Result<Unresolved> {
-    let mut args = vec![Scalar::Column(ColumnRef::SampleValue)];
-    for index in 1..call.args.args.len() {
-        args.push(lower_scalar(arg(call, index)?)?);
-    }
-    if call.func.name == "round" && args.len() == 1 {
-        args.push(Scalar::Literal(ScalarValue::Float64(1.0)));
-    }
-    Ok(Unresolved::PromqlMap {
-        child: Rc::new(walk(arg(call, 0)?)?),
-        sample: Scalar::FunctionCall {
-            name: format!("promql_{}", call.func.name),
-            args,
-        },
-        drop_metric_name: true,
-    })
-}
-
-/// Whether `expr` is a **classic cumulative-bucket** `histogram_quantile`
-/// argument — as opposed to a native histogram or raw samples. Recognised
-/// structurally, by any of:
-///  - a `by (le)` grouping (`sum by (le) (…)`),
-///  - a selector on a classic `_bucket` metric (`http_request_…_bucket`),
-///  - a selector with an `le` label matcher (`{le="…"}`).
-///
-/// The bucket form must be *interpolated* (`HistogramQuantile`); everything
-/// else is a sketch-able generic `Quantile`. This is a heuristic proxy for the
-/// real signal — the argument's sample type — which isn't visible at lowering;
-/// see the follow-up issue on the discrimination criteria (issue #43).
-/// Whether `histogram_quantile(φ, arg)` lowers to the sketch-able generic
-/// `Quantile` (`true`) or exact classic-bucket interpolation (`false`).
-///
-/// Metadata wins: if any metric referenced in `arg` has a declared
-/// [`HistogramKind`](crate::unified::histogram::HistogramKind), that decides it (issue
-/// #79) — this fixes both the false-positive (a `…_bucket`-named non-histogram
-/// declared `RawSamples`) and the false-negative (a suffix-less classic
-/// histogram declared `ClassicBucket`) of the structural heuristic. With no
-/// declaration, fall back to the structural `by (le)`/`_bucket` heuristic.
-fn histogram_arg_is_sketchable(arg: &Expr) -> Result<bool> {
-    let mut metrics = Vec::new();
-    collect_metric_names(arg, &mut metrics);
-    let kinds = metrics
-        .iter()
-        .filter_map(|metric| crate::unified::histogram::current_kind_of(metric))
-        .collect::<Vec<_>>();
-    if kinds.contains(&crate::unified::histogram::HistogramKind::Native) {
-        return Err(LoweringError::UnsupportedFeature(
-            "native histogram samples have no IR representation".into(),
-        ));
-    }
-    if let Some(kind) = kinds.first() {
-        if kinds.iter().any(|other| other != kind) {
-            return Err(LoweringError::UnsupportedFeature(
-                "mixed histogram sample contracts".into(),
-            ));
-        }
-        return Ok(kind.is_sketchable());
-    }
-    if is_classic_bucket_arg(arg) {
-        Ok(false)
-    } else {
-        Err(LoweringError::UnsupportedFeature("histogram_quantile requires classic buckets; use quantile for float samples or explicitly declare the RawSamples extension".into()))
-    }
-}
-
-/// Collect the metric names of every vector/matrix selector reachable in `expr`
-/// (for the metadata lookup in [`histogram_arg_is_sketchable`]). Skips
-/// name-less selectors like `{le="…"}`.
-fn collect_metric_names(expr: &Expr, out: &mut Vec<String>) {
-    match expr {
-        Expr::VectorSelector(vs) => {
-            if let Ok((metric, ..)) = vs_parts(vs) {
-                if !metric.is_empty() {
-                    out.push(metric);
-                }
-            }
-        }
-        Expr::MatrixSelector(ms) => {
-            if let Ok((metric, ..)) = vs_parts(&ms.vs) {
-                if !metric.is_empty() {
-                    out.push(metric);
-                }
-            }
-        }
-        Expr::Paren(p) => collect_metric_names(&p.expr, out),
-        Expr::Unary(u) => collect_metric_names(&u.expr, out),
-        Expr::Subquery(s) => collect_metric_names(&s.expr, out),
-        Expr::Aggregate(a) => collect_metric_names(&a.expr, out),
-        Expr::Binary(b) => {
-            collect_metric_names(&b.lhs, out);
-            collect_metric_names(&b.rhs, out);
-        }
-        Expr::Call(c) => c
-            .args
-            .args
-            .iter()
-            .for_each(|a| collect_metric_names(a, out)),
-        _ => {}
-    }
-}
-
-fn is_classic_bucket_arg(expr: &Expr) -> bool {
-    match expr {
-        Expr::Paren(p) => is_classic_bucket_arg(&p.expr),
-        Expr::Unary(u) => is_classic_bucket_arg(&u.expr),
-        Expr::Subquery(s) => is_classic_bucket_arg(&s.expr),
-        Expr::Aggregate(agg) => {
-            matches!(
-                &agg.modifier,
-                Some(LabelModifier::Include(ls)) if ls.labels.iter().any(|l| l == "le")
-            ) || is_classic_bucket_arg(&agg.expr)
-        }
-        Expr::Binary(b) => is_classic_bucket_arg(&b.lhs) || is_classic_bucket_arg(&b.rhs),
-        Expr::Call(c) => c.args.args.iter().any(|a| is_classic_bucket_arg(a)),
-        Expr::VectorSelector(vs) => selector_is_bucket(vs),
-        Expr::MatrixSelector(ms) => selector_is_bucket(&ms.vs),
-        _ => false,
-    }
-}
-
-/// A classic histogram bucket selector — a `_bucket`-named metric (via bare name
-/// or `__name__` matcher) or an explicit `le` label matcher.
-fn selector_is_bucket(vs: &VectorSelector) -> bool {
-    let name = vs.name.as_deref().or_else(|| {
-        vs.matchers
-            .matchers
-            .iter()
-            .find(|m| m.name == "__name__")
-            .map(|m| m.value.as_str())
-    });
-    name.is_some_and(|n| n.ends_with("_bucket"))
-        || vs.matchers.matchers.iter().any(|m| m.name == "le")
-}
-
-/// A binary op with at least one vector operand (a scalar/scalar op is
-/// scalar-typed and never reaches here). A scalar side lowers to a
-/// scalar expression; mixed operations resolve to Project or Filter.
-fn walk_binary(bin: &BinaryExpr) -> Result<Unresolved> {
-    let op = binop(bin.op.id())?;
-    let scalar_left = bin.lhs.value_type() == ValueType::Scalar;
-    if scalar_left || bin.rhs.value_type() == ValueType::Scalar {
-        let (scalar, vector) = if scalar_left {
-            (&bin.lhs, &bin.rhs)
-        } else {
-            (&bin.rhs, &bin.lhs)
-        };
-        return Ok(Unresolved::PromqlScalarOp {
-            child: Rc::new(walk(vector)?),
-            scalar: lower_scalar(scalar)?,
-            op,
-            scalar_left,
-            return_bool: bin.return_bool(),
-        });
-    }
-    let lhs = walk(&bin.lhs)?;
-    let rhs = walk(&bin.rhs)?;
-    // `VectorMatch` has no fill field; dropping fill would change which series
-    // are emitted and their values, so the query must fall back to exact
-    // execution instead.
-    if let Some(m) = &bin.modifier {
-        if m.fill_values.lhs.is_some() || m.fill_values.rhs.is_some() {
-            return Err(LoweringError::UnsupportedFeature(format!(
-                "`fill` vector-matching modifier: `{bin}`"
-            )));
-        }
-    }
-    let vector_match = bin.modifier.as_ref().map(|m| {
-        let (kind, labels) = match &m.matching {
-            Some(LabelModifier::Include(ls)) => (VectorMatchKind::On, ls.labels.clone()),
-            Some(LabelModifier::Exclude(ls)) => (VectorMatchKind::Ignoring, ls.labels.clone()),
-            // No explicit `on(…)`/`ignoring(…)` — the parser attaches a default
-            // modifier to every set op (`and`/`or`/`unless`). The default is
-            // "match on all shared labels", which is exactly `ignoring([])`
-            // (ignore no labels). Representing it as `Ignoring([])` — not
-            // `On([])` — keeps it distinct from an explicit `on()` (match on the
-            // empty label set) while making it correctly equal to an explicit
-            // `ignoring()` (issue #68).
-            None => (VectorMatchKind::Ignoring, vec![]),
-        };
-        let grouping = match &m.card {
-            VectorMatchCardinality::ManyToOne(ls) => Some(VectorGrouping {
-                side: GroupSide::Left,
-                labels: ls.labels.clone(),
-            }),
-            VectorMatchCardinality::OneToMany(ls) => Some(VectorGrouping {
-                side: GroupSide::Right,
-                labels: ls.labels.clone(),
-            }),
-            _ => None,
-        };
-        VectorMatch {
-            kind,
-            labels,
-            grouping,
-        }
-    });
-    Ok(vector_binary(op, vector_match, bin.return_bool(), lhs, rhs))
-}
-
-fn lower_inner(expr: &Expr) -> Result<Inner> {
-    match expr {
-        Expr::VectorSelector(vs) => {
-            let (metric, matchers, shift) = vs_parts(vs)?;
-            Ok(Inner {
-                metric,
-                matchers,
-                window: None,
-                func: None,
-                shift,
-            })
-        }
-        Expr::MatrixSelector(ms) => {
-            let (metric, matchers, shift) = vs_parts(&ms.vs)?;
-            Ok(Inner {
-                metric,
-                matchers,
-                window: Some(ms.range),
-                func: None,
-                shift,
-            })
-        }
-        Expr::Paren(p) => lower_inner(&p.expr),
-        Expr::Call(call) => lower_inner_call(call),
-        other => Err(LoweringError::UnsupportedFeature(format!(
-            "aggregate argument: `{other}`"
-        ))),
-    }
-}
-
-fn lower_inner_call(call: &Call) -> Result<Inner> {
-    let name = call.func.name;
-    let at0 = |func: InnerFunc| -> Result<Inner> {
-        let (metric, matchers, window, shift) = extract_matrix(arg(call, 0)?)?;
-        Ok(Inner {
-            metric,
-            matchers,
-            window: Some(window),
-            func: Some(func),
-            shift,
-        })
-    };
-    match name {
-        "rate" | "irate" => {
-            let (metric, matchers, window, shift) = extract_matrix(arg(call, 0)?)?;
-            Ok(Inner {
-                metric,
-                matchers,
-                window: Some(window),
-                func: Some(if name == "irate" {
-                    InnerFunc::IRate
-                } else {
-                    InnerFunc::Rate
-                }),
-                shift,
-            })
-        }
-        "increase" => {
-            let (metric, matchers, window, shift) = extract_matrix(arg(call, 0)?)?;
-            Ok(Inner {
-                metric,
-                matchers,
-                window: Some(window),
-                func: Some(InnerFunc::Increase),
-                shift,
-            })
-        }
-        "quantile_over_time" => {
-            let phi = quantile_param(num_arg(call, 0)?)?;
-            let (metric, matchers, window, shift) = extract_matrix(arg(call, 1)?)?;
-            Ok(Inner {
-                metric,
-                matchers,
-                window: Some(window),
-                func: Some(InnerFunc::Quantile(phi)),
-                shift,
-            })
-        }
-        "avg_over_time" => at0(InnerFunc::Avg),
-        "min_over_time" => at0(InnerFunc::Min),
-        "max_over_time" => at0(InnerFunc::Max),
-        "sum_over_time" => at0(InnerFunc::Sum),
-        "stddev_over_time" => at0(InnerFunc::StdDev),
-        "stdvar_over_time" => at0(InnerFunc::Variance),
-        "count_over_time" => at0(InnerFunc::Count),
-        "distinct_over_time" => at0(InnerFunc::Cardinality),
-        "entropy_over_time" => at0(InnerFunc::FrequencyEntropy),
-        "l2_over_time" => at0(InnerFunc::FrequencyL2),
-        // Counter-derivative range functions (issue #44). Each has its own
-        // intent — `changes` (value-change count) and `resets` (counter-reset
-        // count) are NOT sample counts, so they are not aliased to
-        // `count_over_time`. The window is arg 0's matrix; scalar params follow.
-        "changes" => at0(InnerFunc::Changes),
-        "delta" => at0(InnerFunc::Delta),
-        "idelta" => at0(InnerFunc::IDelta),
-        "deriv" => at0(InnerFunc::Deriv),
-        "resets" => at0(InnerFunc::Resets),
-        // Additional range-vector reducers (issue #51) — same windowed
-        // per-series shape as the `*_over_time` family above.
-        "last_over_time" => at0(InnerFunc::LastOverTime),
-        "first_over_time" => at0(InnerFunc::FirstOverTime),
-        "mad_over_time" => at0(InnerFunc::MadOverTime),
-        "ts_of_min_over_time" => at0(InnerFunc::TsOfMinOverTime),
-        "ts_of_max_over_time" => at0(InnerFunc::TsOfMaxOverTime),
-        "ts_of_first_over_time" => at0(InnerFunc::TsOfFirstOverTime),
-        "ts_of_last_over_time" => at0(InnerFunc::TsOfLastOverTime),
-        "predict_linear" => {
-            let (metric, matchers, window, shift) = extract_matrix(arg(call, 0)?)?;
-            let seconds = num_arg(call, 1)?;
-            Ok(Inner {
-                metric,
-                matchers,
-                window: Some(window),
-                func: Some(InnerFunc::PredictLinear(seconds)),
-                shift,
-            })
-        }
-        "double_exponential_smoothing" => {
-            let (metric, matchers, window, shift) = extract_matrix(arg(call, 0)?)?;
-            let smoothing = num_arg(call, 1)?;
-            let trend = num_arg(call, 2)?;
-            Ok(Inner {
-                metric,
-                matchers,
-                window: Some(window),
-                func: Some(InnerFunc::DoubleExp { smoothing, trend }),
-                shift,
-            })
-        }
-        other => Err(LoweringError::UnsupportedFunction(other.to_string())),
-    }
-}
-
-/// Assemble the Layer-2 tree from a lowered inner vector, the resolved group
-/// keys, and the enclosing aggregator shape.
-fn build(inner: Inner, keys: Vec<ColumnRef>, outer: Outer) -> Result<Unresolved> {
-    match outer {
-        Outer::None => match &inner.func {
-            None => Ok(instant_source(inner.metric, inner.matchers, inner.shift)),
-            Some(f) => {
-                let intent = inner_intent(f);
-                Ok(windowed_aggregate(inner, keys, intent))
-            }
-        },
-        // An OUTER aggregation operator (`sum`/`avg`/…/`count`) over an inner
-        // range-vector function (`rate`/`increase`/`*_over_time`) is a
-        // two-level reduction: the inner func runs per series, the outer op
-        // then aggregates across series. Collapsing them into one aggregate
-        // silently drops a level — e.g. `sum(rate(m[w]))` must keep the `sum`.
-        Outer::Plain(intent) => Ok(match &inner.func {
-            None => windowed_aggregate(inner, keys, outer_intent(&intent)),
-            Some(f) => {
-                let inner_i = inner_intent(f);
-                let inner_agg = windowed_aggregate(inner, vec![], inner_i);
-                outer_aggregate(keys, outer_intent(&intent), inner_agg)
-            }
-        }),
-        Outer::Count => Ok(match &inner.func {
-            None => windowed_aggregate(inner, keys, count()),
-            Some(f) => {
-                let inner_i = inner_intent(f);
-                let inner_agg = windowed_aggregate(inner, vec![], inner_i);
-                outer_aggregate(keys, count(), inner_agg)
-            }
-        }),
-        Outer::CountValues { label } => Ok(match &inner.func {
-            None => windowed_aggregate(inner, keys, AggIntent::CountValues { label }),
-            Some(f) => {
-                let inner_i = inner_intent(f);
-                let inner_agg = windowed_aggregate(inner, vec![], inner_i);
-                outer_aggregate(keys, AggIntent::CountValues { label }, inner_agg)
-            }
-        }),
-        Outer::Sample { kind } => {
-            // Series sampling selects whole series unchanged — like generic
-            // `topk`, a range-vector argument reduces per series first (label-
-            // preserving), a bare selector is sampled directly; neither is
-            // wrapped in a reducing aggregate (issue #86).
-            let base = match inner.func.as_ref().map(inner_intent) {
-                Some(intent) => windowed_aggregate(inner, vec![], intent),
-                None => instant_source(inner.metric, inner.matchers, inner.shift),
-            };
-            Ok(Unresolved::PromqlSeriesSample {
-                by: keys.into(),
-                kind,
-                child: Rc::new(base),
-            })
-        }
-        Outer::TopK { k, descending } => {
-            // Preserve the counter-value ranking intent. Physical candidates
-            // may rebuild a heap over finalized rates or use exact Sort/Limit;
-            // neither is allowed to sum raw counter samples as ranking weights.
-            if descending && matches!(inner.func, Some(InnerFunc::Rate | InnerFunc::Increase)) {
-                let intent = inner_intent(inner.func.as_ref().expect("counter function"));
-                let ranked = windowed_aggregate(inner, vec![], intent);
-                return Ok(Unresolved::Aggregate {
-                    reduction: Reduction::Reduce(keys.into()),
-                    measures: vec![AggIntent::TopK {
-                        k: k as usize,
-                        accuracy: current_accuracy(),
-                    }],
-                    output_names: vec![],
-                    filters: vec![],
-                    having: None,
-                    child: Rc::new(ranked),
-                });
-            }
-            // Heavy-hitter only when ranking by an additive measure (`count`
-            // or `sum`): that is a
-            // first-class aggregate intent → `TopK`. Any other ranking (topk
-            // over avg/quantile, a bare selector's raw value, all bottomk)
-            // is a generic order-by-value + limit and stays as the `Sort + Limit`
-            // operator pair. The descending-plus-measure rule is shared with the
-            // canonicalize-pass promotion so the two cannot drift (issue #38).
-            let measure = match inner.func {
-                Some(InnerFunc::Count) => topk::Ranking::Frequency,
-                Some(InnerFunc::Sum) => topk::Ranking::WeightedSum,
-                _ => topk::Ranking::NonAdditive,
-            };
-            let additive_ranking = measure.is_supported(descending);
-            if additive_ranking {
-                // Preserve the ranked aggregate intent in the canonical tree so the
-                // intent algebra is explicit about what is being computed.
-                // Post-ASAP binding may fuse the Count and TopK into a
-                // single-pass heavy-hitter sketch (SpaceSaving /
-                // CMS-with-heap), but that is a cost-model decision, not a
-                // canonical-IR concern.
-                let ranked = match measure {
-                    topk::Ranking::Frequency => InnerFunc::Count,
-                    topk::Ranking::WeightedSum => InnerFunc::Sum,
-                    topk::Ranking::NonAdditive => {
-                        unreachable!("heavy-hitter gate rejected non-additive ranking")
-                    }
-                };
-                let ranked_agg = windowed_aggregate(inner, vec![], inner_intent(&ranked));
-                Ok(Unresolved::Aggregate {
-                    // A ranking always reduces (a `by`-empty TopK ranks the
-                    // whole input into one ordering, never per-entity).
-                    reduction: Reduction::Reduce(keys.into()),
-                    measures: vec![AggIntent::TopK {
-                        k: k as usize,
-                        accuracy: current_accuracy(),
-                    }],
-                    output_names: vec![],
-                    filters: vec![],
-                    having: None,
-                    child: Rc::new(ranked_agg),
-                })
-            } else {
-                // The base over which we rank. A range-vector-function argument
-                // (`topk(k, rate(m[5m]))`) reduces *per series* first — that is
-                // label-preserving, so the `by (host)` partition labels survive.
-                // A **bare instant selector** (`topk(k, m)`) ranks its own
-                // samples directly: it must NOT be wrapped in a reducing
-                // aggregate. Defaulting it to `Sum` was both semantically wrong
-                // (PromQL `topk` ranks the raw samples, it does not sum them) and
-                // destructive — the cross-series `Sum` collapses every label,
-                // including the `by (…)` partition keys, so they no longer
-                // resolve (issue #30). Keep the selector label-preserving so
-                // `Sort.partition_by` can rank within each group (issue #12).
-                let base = match inner.func.as_ref().map(inner_intent) {
-                    Some(intent) => windowed_aggregate(inner, vec![], intent),
-                    None => instant_source(inner.metric, inner.matchers, inner.shift),
-                };
-                Ok(ranked_by_value(keys, k, descending, base))
-            }
-        }
-    }
-}
-
-/// Decide `PerEntity` vs `Reduce(by)` for a canonical `Aggregate`, entirely
-/// from local PromQL semantics: the keys and whether this operation preserves
-/// each input series. It never infers entity reduction from the child tree's
-/// temporal shape. `without()` is applied
-/// separately, post-hoc, by `mark_without` — see its doc for why that's still
-/// correct here.
-fn reduction_for(keys: &[ColumnRef], per_entity: bool) -> Reduction<ColumnRef> {
-    if keys.is_empty() && per_entity {
-        Reduction::PerEntity
-    } else {
-        Reduction::Reduce(GroupKeys::by(keys.to_vec()))
-    }
-}
-
-/// `Aggregate{reduction, [intent]}` over `[TimeRange{w}] → Scan`. Always wraps
-/// in `TimeRange` when there's a window — including for `Rate`/`Increase`,
-/// whose window rides on `inner.window` too (set redundantly alongside the
-/// intent itself): canonical `AggIntent::Rate`/`Increase` carry no window
-/// field of their own, unlike the old Unresolved `AggFunc::Rate{window}` — "the range
-/// is on the enclosing `TimeRange` node" is now true unconditionally, so
-/// there's no more `skip_window` special case.
-fn windowed_aggregate(
-    inner: Inner,
-    keys: Vec<ColumnRef>,
-    intent: AggIntent<ColumnRef>,
-) -> Unresolved {
-    let base = filtered_source(inner.metric, inner.matchers, inner.shift);
-    let child = match inner.window {
-        Some(w) => Unresolved::TimeRange {
-            range: w,
-            kind: TimeRangeKind::Range,
-            child: Rc::new(base),
-        },
-        None => ingestion_lookback(base),
-    };
-    let reduction = reduction_for(&keys, inner.window.is_some() || intent.is_per_series());
-    Unresolved::Aggregate {
-        reduction,
-        measures: vec![intent],
-        // A single empty entry — never an override — so the resolver keeps
-        // PromQL's intent-keyed output names ("sum", "quantile_0_99", …)
-        // instead.
-        output_names: vec![String::new()],
-        filters: vec![],
-        having: None,
-        child: Rc::new(child),
-    }
-}
-
-/// `Aggregate{reduction, [intent]}` directly over an existing Unresolved sub-DAG — the
-/// OUTER level of a two-level aggregation such as `sum(rate(…))` or the
-/// `Aggregate{[Quantile]}` that wraps a `histogram_quantile` argument.
-fn outer_aggregate(
-    keys: Vec<ColumnRef>,
-    intent: AggIntent<ColumnRef>,
-    child: Unresolved,
-) -> Unresolved {
-    let reduction = reduction_for(&keys, intent.is_per_series());
-    Unresolved::Aggregate {
-        reduction,
-        measures: vec![intent],
-        output_names: vec![String::new()],
-        filters: vec![],
-        having: None,
-        child: Rc::new(child),
-    }
-}
-
-/// A temporal range function over a subquery consumes each series' subquery
-/// samples independently. Unlike an ordinary outer aggregate, this cannot be
-/// inferred from the intent: `max` is cross-series in `max(v)`, but per-series
-/// in `max_over_time(v[...])`.
-fn per_series_aggregate(
-    keys: Vec<ColumnRef>,
-    intent: AggIntent<ColumnRef>,
-    child: Unresolved,
-) -> Unresolved {
-    let reduction = reduction_for(&keys, true);
-    Unresolved::Aggregate {
-        reduction,
-        measures: vec![intent],
-        output_names: vec![String::new()],
-        filters: vec![],
-        having: None,
-        child: Rc::new(child),
-    }
-}
-
-fn filtered_source(metric: String, matchers: Vec<Scalar>, shift: TimeShift) -> Unresolved {
-    let scan = Unresolved::Scan {
-        source: Source::TimeSeries { metric },
-        predicates: matchers.into_iter().map(UnresolvedPredicate).collect(),
-        // Usage-derived (PromQL is schemaless) — the SchemaResolver fills this in.
-        schema: None,
-    };
-    if shift.is_identity() {
-        scan
-    } else {
-        Unresolved::TimeShift {
-            shift,
-            child: Rc::new(scan),
-        }
-    }
-}
-
-/// An instant selector: the latest sample per series within the workload's
-/// ingestion interval, so the lookback is an `Instant` `TimeRange`.
-fn instant_source(metric: String, matchers: Vec<Scalar>, shift: TimeShift) -> Unresolved {
-    ingestion_lookback(filtered_source(metric, matchers, shift))
-}
-
-fn ingestion_lookback(child: Unresolved) -> Unresolved {
-    Unresolved::TimeRange {
-        range: current_ingestion_interval(),
-        kind: TimeRangeKind::Instant,
-        child: Rc::new(child),
-    }
-}
-
-/// Count vector elements regardless of their sample values.
-fn count() -> AggIntent<ColumnRef> {
-    AggIntent::Count {
-        accuracy: current_accuracy(),
-    }
-}
-
-fn inner_intent(f: &InnerFunc) -> AggIntent<ColumnRef> {
-    match f {
-        InnerFunc::FrequencyL2 => AggIntent::FrequencyL2 {
-            col: None,
-            accuracy: current_accuracy(),
-        },
-        InnerFunc::FrequencyEntropy => AggIntent::FrequencyEntropy {
-            col: None,
-            accuracy: current_accuracy(),
-        },
-        InnerFunc::Cardinality => AggIntent::Cardinality {
-            cols: vec![],
-            accuracy: current_accuracy(),
-        },
-        InnerFunc::Quantile(q) => AggIntent::Quantile {
-            col: None,
-            q: *q,
-            accuracy: current_accuracy(),
-        },
-        InnerFunc::Avg => AggIntent::Avg { col: None },
-        InnerFunc::Min => AggIntent::Min { col: None },
-        InnerFunc::Max => AggIntent::Max { col: None },
-        InnerFunc::Sum => AggIntent::Sum { col: None },
-        InnerFunc::StdDev => AggIntent::StdDev {
-            col: None,
-            population: true,
-        },
-        InnerFunc::Variance => AggIntent::Variance {
-            col: None,
-            population: true,
-        },
-        InnerFunc::Count => AggIntent::Count {
-            accuracy: current_accuracy(),
-        },
-        InnerFunc::Rate => AggIntent::Rate,
-        InnerFunc::IRate => AggIntent::IRate,
-        InnerFunc::Increase => AggIntent::Increase,
-        InnerFunc::Changes => AggIntent::Changes,
-        InnerFunc::Delta => AggIntent::Delta,
-        InnerFunc::IDelta => AggIntent::IDelta,
-        InnerFunc::Deriv => AggIntent::Deriv,
-        InnerFunc::Resets => AggIntent::Resets,
-        InnerFunc::PredictLinear(s) => AggIntent::PredictLinear { seconds: *s },
-        InnerFunc::DoubleExp { smoothing, trend } => AggIntent::DoubleExpSmoothing {
-            smoothing: *smoothing,
-            trend: *trend,
-        },
-        InnerFunc::LastOverTime => AggIntent::LastOverTime,
-        InnerFunc::FirstOverTime => AggIntent::FirstOverTime,
-        InnerFunc::MadOverTime => AggIntent::MadOverTime,
-        InnerFunc::TsOfMinOverTime => AggIntent::TsOfMinOverTime,
-        InnerFunc::TsOfMaxOverTime => AggIntent::TsOfMaxOverTime,
-        InnerFunc::TsOfFirstOverTime => AggIntent::TsOfFirstOverTime,
-        InnerFunc::TsOfLastOverTime => AggIntent::TsOfLastOverTime,
-    }
-}
-
-fn outer_intent(o: &OuterIntent) -> AggIntent<ColumnRef> {
-    match o {
-        OuterIntent::Sum => AggIntent::Sum { col: None },
-        OuterIntent::Avg => AggIntent::Avg { col: None },
-        OuterIntent::Min => AggIntent::Min { col: None },
-        OuterIntent::Max => AggIntent::Max { col: None },
-        OuterIntent::StdDev => AggIntent::StdDev {
-            col: None,
-            population: true,
-        },
-        OuterIntent::Variance => AggIntent::Variance {
-            col: None,
-            population: true,
-        },
-        OuterIntent::Quantile(q) => AggIntent::Quantile {
-            col: None,
-            q: *q,
-            accuracy: current_accuracy(),
-        },
-        OuterIntent::Group => AggIntent::Group,
-    }
-}
-
-/// Unwrap a (possibly parenthesised) string literal — `count_values` labels and
-/// `label_replace`/`label_join` arguments are all string literals, sometimes
-/// wrapped in parens (`count_values((("v")), …)`).
-fn expr_str(expr: &Expr) -> Result<String> {
-    match expr {
-        Expr::StringLiteral(s) => Ok(s.val.clone()),
-        Expr::Paren(p) => expr_str(&p.expr),
-        other => Err(LoweringError::InvalidParameter(format!(
-            "expected a string literal, got `{other}`"
-        ))),
-    }
-}
-
-/// A `count_values` string parameter (the synthesized label name).
-fn str_param(agg: &AggregateExpr) -> Result<String> {
-    match &agg.param {
-        Some(e) => expr_str(e),
-        None => Err(LoweringError::MissingArgument(
-            "`count_values` label parameter".into(),
-        )),
-    }
-}
-
-/// A call's `idx`-th argument as a string literal (`label_replace`/`label_join`).
-fn str_arg(call: &Call, idx: usize) -> Result<String> {
-    expr_str(arg(call, idx)?)
-}
-
-/// Resolve an aggregation's grouping modifier into a `(keys, without)` pair.
-///
-/// `by(labels)` → the kept labels, `without = false`. `without(labels)` → the
-/// **excluded** labels, `without = true`: the kept set (the complement) can't be
-/// enumerated under an open usage-derived schema, so it is deferred to the
-/// runtime and only the excluded positions are carried (issue #39). Both forms
-/// canonicalise their label set (sort + dedup) so equivalent groupings lower
-/// identically. PromQL labels have no table qualifier → `ColumnRef::Named`.
-fn resolve_group(agg: &AggregateExpr) -> Result<(Vec<ColumnRef>, bool)> {
-    let canon = |labels: &[String]| -> Vec<ColumnRef> {
-        let mut keys = labels.to_vec();
-        keys.sort();
-        keys.dedup();
-        keys.into_iter().map(ColumnRef::Named).collect()
-    };
-    match &agg.modifier {
-        None => Ok((vec![], false)),
-        Some(LabelModifier::Include(ls)) => Ok((canon(&ls.labels), false)),
-        Some(LabelModifier::Exclude(ls)) => Ok((canon(&ls.labels), true)),
-    }
-}
-
-// ── Free helpers ──────────────────────────────────────────────────────────────
-
-fn vs_parts(vs: &VectorSelector) -> Result<(String, Vec<Scalar>, TimeShift)> {
-    // A non-equality `__name__` matcher (`=~` / `!~` / `!=`) selects *across*
-    // metric names. `Source::TimeSeries { metric }` carries a single concrete
-    // metric name, so there is no representation for a regex/negated name
-    // match — reject rather than mislower it to a literal metric named after
-    // the pattern (issue #67). An equality `__name__` (`{__name__="up"}`)
-    // still names the metric below.
-    if let Some(m) = vs
-        .matchers
-        .matchers
-        .iter()
-        .find(|m| m.name == "__name__" && !matches!(m.op, MatchOp::Equal))
-    {
-        return Err(LoweringError::UnsupportedFeature(format!(
-            "non-equality `__name__` matcher ({}{:?}) selects across metric names, \
-             which has no single-metric canonical representation",
-            m.name, m.op
-        )));
-    }
-    let metric = vs.name.clone().unwrap_or_else(|| {
-        vs.matchers
-            .matchers
-            .iter()
-            .find(|m| m.name == "__name__")
-            .map(|m| m.value.clone())
-            .unwrap_or_default()
-    });
-    // Label matchers are an unordered set: `{a="1",b="2"}` and `{b="2",a="1"}`
-    // select the same series. Canonicalise by (name, value) so equivalent
-    // selectors lower to identical predicates.
-    let mut ms: Vec<&Matcher> = vs
-        .matchers
-        .matchers
-        .iter()
-        .filter(|m| m.name != "__name__")
-        .collect();
-    ms.sort_by(|a, b| a.name.cmp(&b.name).then_with(|| a.value.cmp(&b.value)));
-    let matchers = ms.into_iter().map(matcher_to_compare).collect();
-    let shift = time_shift(vs.offset.as_ref(), vs.at.as_ref())?;
-    Ok((metric, matchers, shift))
-}
-
-/// Convert the parser's `offset` / `@` modifiers into a [`TimeShift`] (issue
-/// #40). Offset is signed milliseconds; `@ <ts>` (parser seconds → ms) becomes
-/// an absolute anchor, `@ start()`/`@ end()` the range bounds.
-fn time_shift(offset: Option<&Offset>, at: Option<&ParserAtModifier>) -> Result<TimeShift> {
-    let offset_ms = match offset {
-        None => 0,
-        Some(Offset::Pos(d)) => duration_ms(*d)?,
-        Some(Offset::Neg(d)) => -duration_ms(*d)?,
-    };
-    let at = match at {
-        None => None,
-        Some(ParserAtModifier::Start) => Some(AtModifier::Start),
-        Some(ParserAtModifier::End) => Some(AtModifier::End),
-        Some(ParserAtModifier::At(t)) => Some(AtModifier::Timestamp(system_time_ms(*t)?)),
-    };
-    Ok(TimeShift { offset_ms, at })
-}
-
-/// A `Duration` as `i64` milliseconds, rejecting an overflow rather than
-/// silently truncating a pathologically large `offset`.
-fn duration_ms(d: Duration) -> Result<i64> {
-    i64::try_from(d.as_millis()).map_err(|_| {
-        LoweringError::InvalidParameter("offset duration overflows i64 milliseconds".into())
-    })
-}
-
-/// A `SystemTime` (`@ <ts>`) as `i64` milliseconds since the Unix epoch, signed
-/// so pre-epoch anchors (the parser permits them) are preserved.
-fn system_time_ms(t: SystemTime) -> Result<i64> {
-    let ms = match t.duration_since(std::time::UNIX_EPOCH) {
-        Ok(d) => i64::try_from(d.as_millis()),
-        Err(e) => i64::try_from(e.duration().as_millis()).map(|ms| -ms),
-    };
-    ms.map_err(|_| {
-        LoweringError::InvalidParameter("`@` timestamp overflows i64 milliseconds".into())
-    })
-}
-
-fn matcher_to_compare(m: &Matcher) -> Scalar {
-    let op = match &m.op {
-        MatchOp::Equal => CompareOpKind::Eq,
-        MatchOp::NotEqual => CompareOpKind::Ne,
-        MatchOp::Re(_) => CompareOpKind::Regex,
-        MatchOp::NotRe(_) => CompareOpKind::NotRegex,
-    };
-    Scalar::Compare {
-        left: Box::new(Scalar::Column(ColumnRef::Named(m.name.clone()))),
-        op,
-        right: Box::new(Scalar::Literal(ScalarValue::Utf8(m.value.clone()))),
-        semantics: PROMQL,
-    }
-}
-
-fn extract_matrix(expr: &Expr) -> Result<(String, Vec<Scalar>, Duration, TimeShift)> {
-    match expr {
-        Expr::MatrixSelector(ms) => {
-            let (metric, matchers, shift) = vs_parts(&ms.vs)?;
-            Ok((metric, matchers, ms.range, shift))
-        }
-        Expr::Paren(p) => extract_matrix(&p.expr),
-        // A range-vector function argument must be a (parenthesised) matrix
-        // selector. Do NOT descend through an arbitrary `Call` — that would
-        // silently strip an unsupported wrapper (`rate(deriv(m[5m]))` lowering
-        // as `rate(m[5m])`). Reject instead.
-        other => Err(LoweringError::UnsupportedFeature(format!(
-            "expected a range-vector (matrix) argument, got `{other}`"
-        ))),
-    }
-}
-
-fn arg(call: &Call, idx: usize) -> Result<&Expr> {
-    call.args
-        .args
-        .get(idx)
-        .map(|b| b.as_ref())
-        .ok_or_else(|| LoweringError::MissingArgument(format!("{} arg #{idx}", call.func.name)))
-}
-
-fn num_arg(call: &Call, idx: usize) -> Result<f64> {
-    num_expr(arg(call, idx)?)
-}
-
-fn num_param(agg: &AggregateExpr) -> Result<f64> {
-    match &agg.param {
-        Some(e) => num_expr(e),
-        None => Err(LoweringError::MissingArgument(
-            "aggregate parameter (k / φ)".into(),
-        )),
-    }
-}
-
-fn num_expr(expr: &Expr) -> Result<f64> {
-    match expr {
-        Expr::NumberLiteral(n) => Ok(n.val),
-        Expr::Paren(p) => num_expr(&p.expr),
-        Expr::Unary(u) => Ok(-num_expr(&u.expr)?),
-        // Constant-fold a pure scalar arithmetic expression — the parser does
-        // not fold `10*1024*1024` / `24 * 3600`. A `modifier` (vector matching)
-        // or a non-arithmetic operator means it is not a pure scalar.
-        Expr::Binary(b) if b.modifier.is_none() => {
-            let (l, r) = (num_expr(&b.lhs)?, num_expr(&b.rhs)?);
-            let id = b.op.id();
-            if id == token::T_ADD {
-                Ok(l + r)
-            } else if id == token::T_SUB {
-                Ok(l - r)
-            } else if id == token::T_MUL {
-                Ok(l * r)
-            } else if id == token::T_DIV {
-                Ok(l / r)
-            } else if id == token::T_MOD {
-                Ok(l % r)
-            } else if id == token::T_POW {
-                Ok(l.powf(r))
-            } else {
-                Err(LoweringError::InvalidParameter(
-                    "non-arithmetic operator in scalar expression".into(),
-                ))
-            }
-        }
-        // `min_of`/`max_of` are n-ary *scalar* reducers (issue #89). Fold them
-        // when every argument is itself a constant scalar — this is the only
-        // form the intent algebra can hold (there is no scalar min/max node). A
-        // non-constant argument (`min_of(step(), 1s)`) fails the recursive fold
-        // and propagates the error, so it stays rejected. `f64::min`/`max`
-        // ignore NaN, matching PromQL's `min`/`max` NaN semantics.
-        Expr::Call(c) if is_scalar_reducer_fn(c.func.name) => {
-            let reduce = if c.func.name == "min_of" {
-                f64::min
-            } else {
-                f64::max
-            };
-            c.args
-                .args
-                .iter()
-                .map(|a| num_expr(a))
-                .reduce(|acc, v| Ok(reduce(acc?, v?)))
-                .ok_or_else(|| {
-                    LoweringError::MissingArgument(format!("{} needs an argument", c.func.name))
-                })?
-        }
-        other => Err(LoweringError::InvalidParameter(format!(
-            "expected a numeric scalar, got `{other}`"
-        ))),
-    }
-}
-
-/// The n-ary scalar min/max reducers, foldable when all arguments are constant
-/// scalars (issue #89).
-fn is_scalar_reducer_fn(name: &str) -> bool {
-    matches!(name, "min_of" | "max_of")
-}
-
-/// `topk`/`bottomk` count parameter — a non-negative integer. Rejects
-/// fractional / negative / non-finite values rather than silently truncating
-/// or saturating them via `as u64` (`topk(2.7, …)` ≠ `topk(2, …)`).
-fn count_param(agg: &AggregateExpr) -> Result<u64> {
-    let v = num_param(agg)?;
-    if v.is_finite() && v >= 0.0 && v.fract() == 0.0 && v <= u64::MAX as f64 {
-        Ok(v as u64)
-    } else {
-        Err(LoweringError::InvalidParameter(format!(
-            "topk/bottomk k must be a non-negative integer, got {v}"
-        )))
-    }
-}
-
-/// `limit_ratio` ratio parameter — a finite value; Prometheus clamps it to
-/// `[-1, 1]` (a negative ratio selects the complementary fraction). A non-finite
-/// ratio (`limit_ratio(NaN, …)`) or a dynamic one (`time() % 17/17`, which
-/// `num_param` can't fold) is rejected (issue #86).
-fn ratio_param(agg: &AggregateExpr) -> Result<f64> {
-    let r = num_param(agg)?;
-    if !r.is_finite() {
-        return Err(LoweringError::InvalidParameter(format!(
-            "limit_ratio ratio must be finite, got {r}"
-        )));
-    }
-    Ok(r.clamp(-1.0, 1.0))
-}
-
-/// Preserve the full Prometheus quantile parameter domain, including special values.
-fn quantile_param(q: f64) -> Result<f64> {
-    // Prometheus returns NaN/-Inf/+Inf for these parameters at execution time.
-    Ok(q)
-}
-
-// The non-standard histogram_quantiles extension keeps its bounded label contract.
-fn bounded_quantile_param(q: f64) -> Result<f64> {
-    if q.is_finite() && (0.0..=1.0).contains(&q) {
-        Ok(q)
-    } else {
-        Err(LoweringError::InvalidParameter(format!(
-            "quantile φ must be in [0, 1], got {q}"
-        )))
-    }
-}
-
-fn binop(id: token::TokenId) -> Result<BinaryOpKind> {
-    Ok(if id == token::T_ADD {
-        BinaryOpKind::Arithmetic(ArithmeticOpKind::Add)
-    } else if id == token::T_SUB {
-        BinaryOpKind::Arithmetic(ArithmeticOpKind::Sub)
-    } else if id == token::T_MUL {
-        BinaryOpKind::Arithmetic(ArithmeticOpKind::Mul)
-    } else if id == token::T_DIV {
-        BinaryOpKind::Arithmetic(ArithmeticOpKind::Div)
-    } else if id == token::T_MOD {
-        BinaryOpKind::Arithmetic(ArithmeticOpKind::Mod)
-    } else if id == token::T_POW {
-        BinaryOpKind::Arithmetic(ArithmeticOpKind::Pow)
-    } else if id == token::T_ATAN2 {
-        BinaryOpKind::Arithmetic(ArithmeticOpKind::Atan2)
-    } else if id == token::T_EQLC {
-        BinaryOpKind::Compare(CompareOpKind::Eq)
-    } else if id == token::T_NEQ {
-        BinaryOpKind::Compare(CompareOpKind::Ne)
-    } else if id == token::T_LSS {
-        BinaryOpKind::Compare(CompareOpKind::Lt)
-    } else if id == token::T_LTE {
-        BinaryOpKind::Compare(CompareOpKind::Le)
-    } else if id == token::T_GTR {
-        BinaryOpKind::Compare(CompareOpKind::Gt)
-    } else if id == token::T_GTE {
-        BinaryOpKind::Compare(CompareOpKind::Ge)
-    } else if id == token::T_LAND {
-        BinaryOpKind::Set(PromQLVectorSetOpKind::And)
-    } else if id == token::T_LOR {
-        BinaryOpKind::Set(PromQLVectorSetOpKind::Or)
-    } else if id == token::T_LUNLESS {
-        BinaryOpKind::Set(PromQLVectorSetOpKind::Unless)
-    } else {
-        return Err(LoweringError::UnsupportedFeature(format!(
-            "binary operator token {id}"
-        )));
-    })
-}
diff --git a/crates/frontend-sql/src/unified/error.rs b/crates/frontend-sql/src/unified/error.rs
deleted file mode 100644
index 059404ac1..000000000
--- a/crates/frontend-sql/src/unified/error.rs
+++ /dev/null
@@ -1,75 +0,0 @@
-use std::fmt;
-
-use asap_frontend_common::ResolveDAGError;
-
-/// Errors from lowering a SQL query (parse + plan via DataFusion → the
-/// name-based [`UnresolvedOp`](asap_frontend_common::UnresolvedOp) tree →
-/// [`resolve_root`](asap_frontend_common::resolve_root) binds it into the
-/// unified IR).
-///
-/// Carries no PromQL type — the SQL front end never depends on the PromQL
-/// parser. The language-neutral variants (`UnsupportedFeature` / `WrongLanguage`
-/// / `Convert`) are mirrored by [`asap_frontend_promql::PromqlError`] rather
-/// than shared, so neither front end pulls the other's parser.
-#[derive(Debug)]
-pub enum SqlError {
-    /// DataFusion failed to parse / plan the SQL query.
-    DataFusion(datafusion::error::DataFusionError),
-    /// A table referenced by the query is absent from the catalog.
-    TableNotFound(String),
-    /// A SQL aggregate function not supported in this version.
-    UnsupportedAggregate(String),
-    /// A SQL scalar expression that could not be lowered.
-    InvalidExpression(String),
-    /// The SQL dialect is not supported (only DataFusionSQL is implemented).
-    UnsupportedDialect(String),
-    /// A structural feature (JOIN type / subquery / derived table) not
-    /// supported in this version.
-    UnsupportedFeature(String),
-    /// The workload's query language is not SQL.
-    WrongLanguage(String),
-    /// Resolving the name-based tree failed (name resolution against the
-    /// bound schema, or schema derivation).
-    Convert(ResolveDAGError),
-}
-
-impl fmt::Display for SqlError {
-    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
-        match self {
-            Self::DataFusion(e) => write!(f, "DataFusion error: {e}"),
-            Self::TableNotFound(t) => write!(f, "table not found in catalog: {t}"),
-            Self::UnsupportedAggregate(n) => write!(f, "unsupported aggregate: {n}"),
-            Self::InvalidExpression(m) => write!(f, "invalid expression: {m}"),
-            Self::UnsupportedDialect(d) => write!(f, "unsupported SQL dialect: {d}"),
-            Self::UnsupportedFeature(m) => write!(f, "unsupported feature: {m}"),
-            Self::WrongLanguage(l) => write!(f, "unsupported query language: {l}"),
-            Self::Convert(e) => write!(f, "column resolution failed: {e}"),
-        }
-    }
-}
-
-impl std::error::Error for SqlError {}
-
-impl From<ResolveDAGError> for SqlError {
-    fn from(e: ResolveDAGError) -> Self {
-        Self::Convert(e)
-    }
-}
-
-impl From<datafusion::error::DataFusionError> for SqlError {
-    fn from(mut e: datafusion::error::DataFusionError) -> Self {
-        use datafusion::error::DataFusionError;
-        // Report the first underlying `Plan`/`SQL`/... error. The planner
-        // collects every error it finds and wraps each with a source-span
-        // diagnostic; neither carries anything this front end reports.
-        loop {
-            e = match e {
-                DataFusionError::Diagnostic(_, inner) => *inner,
-                DataFusionError::Collection(errors) if !errors.is_empty() => {
-                    errors.into_iter().next().unwrap()
-                }
-                other => break Self::DataFusion(other),
-            };
-        }
-    }
-}
diff --git a/crates/frontend-sql/src/unified/mod.rs b/crates/frontend-sql/src/unified/mod.rs
deleted file mode 100644
index 279585fb9..000000000
--- a/crates/frontend-sql/src/unified/mod.rs
+++ /dev/null
@@ -1,103 +0,0 @@
-//! SQL front end: parse + plan (via DataFusion) → the name-based
-//! [`UnresolvedOp`](asap_frontend_common::UnresolvedOp) tree, built directly
-//! (issue #179) → [`resolve_root`].
-//!
-//! Emits the shared front-end tree (`UnresolvedOp` / `UnresolvedScalar`,
-//! name-based [`ColumnRef`](asap_types::pre_asap::ColumnRef)s) directly, rather
-//! than a separate per-language relational tree; `resolve_root` binds it into
-//! the unified [`OperatorNode`] IR, deriving every schema on the way.
-//! Depends on DataFusion only — never on the PromQL parser.
-
-pub mod error;
-pub mod sql;
-
-use std::rc::Rc;
-
-use asap_frontend_common::resolve_root;
-use asap_types::ir::OperatorNode;
-use asap_types::types::AccuracyTarget;
-use asap_types::workload::{QueryLanguage, QueryWorkload, SqlDialect};
-
-pub use error::SqlError;
-pub use sql::{SqlCatalog, SqlLowerer};
-
-/// Lower a single SQL query string to the resolved, canonical operator DAG,
-/// parsed as `SqlDialect::DataFusionSQL`.
-///
-/// The `catalog` supplies table schemas (used both to plan the SQL with
-/// DataFusion and to carry positional column identity into the resolved
-/// tree). `accuracy` is threaded onto every approximate intent as it's built.
-pub async fn lower_sql(
-    query: &str,
-    catalog: &SqlCatalog,
-    accuracy: AccuracyTarget,
-) -> Result<Rc<OperatorNode>, SqlError> {
-    lower_sql_dialect(query, catalog, SqlDialect::DataFusionSQL, accuracy).await
-}
-
-/// Lower a single SQL query string under an explicit [`SqlDialect`].
-///
-/// `ClickhouseSQL` parses via sqlparser's vendored `ClickHouseDialect`
-/// (array-lambda syntax, `arr[-1]` indexing). It also teaches DataFusion's
-/// planner the ClickHouse-only builtin functions listed in
-/// `asap_sql_function_catalog::CLICKHOUSE_BUILTINS` (`uniqExact`, `countIf`)
-/// — every other ClickHouse-only builtin still fails to plan.
-/// `ElasticSQL` has no vendored parser and always returns `UnsupportedDialect`.
-pub async fn lower_sql_dialect(
-    query: &str,
-    catalog: &SqlCatalog,
-    dialect: SqlDialect,
-    accuracy: AccuracyTarget,
-) -> Result<Rc<OperatorNode>, SqlError> {
-    let unresolved = SqlLowerer::with_dialect(catalog, dialect)
-        .lower(query, &accuracy)
-        .await?;
-    // Binding resolves names and derives every node's schema; result-type
-    // checks (such as temporal subtraction, whose duration unit the IR cannot
-    // represent) surface here as `ResolveDAGError::Schema`.
-    Ok(resolve_root(&unresolved)?)
-}
-
-/// Lower every SQL batch entry in `workload` to an operator DAG.
-///
-/// One `Result` per entry — errors are per-query, not fatal for the batch.
-/// Returns `WrongLanguage` for every entry if the workload is not SQL, and
-/// `UnsupportedDialect` for `ElasticSQL` (no vendored parser).
-pub async fn lower_sql_batch(
-    workload: &QueryWorkload,
-    catalog: &SqlCatalog,
-) -> Vec<Result<Rc<OperatorNode>, SqlError>> {
-    let entries = match &workload.query_batch {
-        Some(e) if !e.is_empty() => e,
-        _ => return vec![],
-    };
-
-    // `DataFusion` is a legacy alias for `SQL(DataFusionSQL)`; accept both.
-    if !matches!(
-        workload.language,
-        QueryLanguage::SQL(_) | QueryLanguage::DataFusion
-    ) {
-        let lang = format!("{:?}", workload.language);
-        return entries
-            .iter()
-            .map(|_| Err(SqlError::WrongLanguage(lang.clone())))
-            .collect();
-    }
-    let dialect = match &workload.language {
-        QueryLanguage::SQL(d) => d.clone(),
-        _ => SqlDialect::DataFusionSQL,
-    };
-    if matches!(dialect, SqlDialect::ElasticSQL) {
-        return entries
-            .iter()
-            .map(|_| Err(SqlError::UnsupportedDialect("ElasticSQL".into())))
-            .collect();
-    }
-
-    let mut results = Vec::with_capacity(entries.len());
-    for entry in entries {
-        let accuracy = entry.requirements.accuracy.target();
-        results.push(lower_sql_dialect(&entry.query.0, catalog, dialect.clone(), accuracy).await);
-    }
-    results
-}
diff --git a/crates/frontend-sql/src/unified/sql/clickhouse_ast.rs b/crates/frontend-sql/src/unified/sql/clickhouse_ast.rs
deleted file mode 100644
index f9246d22a..000000000
--- a/crates/frontend-sql/src/unified/sql/clickhouse_ast.rs
+++ /dev/null
@@ -1,152 +0,0 @@
-//! Structural ClickHouse syntax normalization before DataFusion type inference.
-use datafusion::sql::sqlparser::ast::{
-    visit_expressions, visit_expressions_mut, AccessExpr, BinaryOperator, Expr, Function,
-    FunctionArg, FunctionArgExpr, FunctionArgumentList, FunctionArguments, Ident, ObjectName,
-    ObjectNamePart, Query, SelectItem, SetExpr, Statement, Subscript, Value, VisitMut, VisitorMut,
-};
-use std::ops::ControlFlow;
-
-use super::collection_planning::MAP_PLANNING_NAME;
-
-pub(super) fn normalize(statement: &mut Statement) {
-    struct PreserveNames;
-    impl VisitorMut for PreserveNames {
-        type Break = ();
-        fn pre_visit_query(&mut self, query: &mut Query) -> ControlFlow<()> {
-            fn preserve(body: &mut SetExpr) {
-                match body {
-                    SetExpr::Select(select) => {
-                        for item in &mut select.projection {
-                            if let SelectItem::UnnamedExpr(expr) = item {
-                                let mut changed = false;
-                                let _: ControlFlow<()> = visit_expressions_mut(expr, |node| {
-                                    changed |= normalize_map_access(node);
-                                    ControlFlow::Continue(())
-                                });
-                                let _: ControlFlow<()> = visit_expressions(expr, |candidate| {
-                                    if let Expr::Function(function) = candidate {
-                                        changed |=
-                                            unquoted_name(&function.name).is_some_and(|name| {
-                                                matches!(
-                                                    name.to_ascii_lowercase().as_str(),
-                                                    "modulo"
-                                                        | "map"
-                                                        | "mapconcat"
-                                                        | "arrayelement"
-                                                        | "tupleelement"
-                                                )
-                                            });
-                                    }
-                                    ControlFlow::Continue(())
-                                });
-                                if changed {
-                                    let alias = Ident::with_quote('"', expr.to_string());
-                                    let value =
-                                        std::mem::replace(expr, Expr::Value(Value::Null.into()));
-                                    *item = SelectItem::ExprWithAlias { expr: value, alias };
-                                }
-                            }
-                        }
-                    }
-                    SetExpr::SetOperation { left, right, .. } => {
-                        preserve(left);
-                        preserve(right);
-                    }
-                    _ => {}
-                }
-            }
-            preserve(&mut query.body);
-            ControlFlow::Continue(())
-        }
-    }
-    let _: ControlFlow<()> = statement.visit(&mut PreserveNames);
-    let _: ControlFlow<()> = visit_expressions_mut(statement, |expr| {
-        normalize_map_access(expr);
-        let Expr::Function(function) = expr else {
-            return ControlFlow::Continue(());
-        };
-        if unquoted_name(&function.name).is_some_and(|name| name.eq_ignore_ascii_case("map")) {
-            function.name = ObjectName::from(vec![Ident::new(MAP_PLANNING_NAME)]);
-            return ControlFlow::Continue(());
-        }
-        if !unquoted_name(&function.name).is_some_and(|name| name.eq_ignore_ascii_case("modulo"))
-            || !matches!(function.parameters, FunctionArguments::None)
-            || function.filter.is_some()
-            || function.over.is_some()
-            || function.null_treatment.is_some()
-            || !function.within_group.is_empty()
-        {
-            return ControlFlow::Continue(());
-        }
-        let FunctionArguments::List(arguments) = &function.args else {
-            return ControlFlow::Continue(());
-        };
-        if arguments.duplicate_treatment.is_some() || !arguments.clauses.is_empty() {
-            return ControlFlow::Continue(());
-        }
-        let [FunctionArg::Unnamed(FunctionArgExpr::Expr(left)), FunctionArg::Unnamed(FunctionArgExpr::Expr(right))] =
-            arguments.args.as_slice()
-        else {
-            return ControlFlow::Continue(());
-        };
-        *expr = Expr::BinaryOp {
-            left: Box::new(left.clone()),
-            op: BinaryOperator::Modulo,
-            right: Box::new(right.clone()),
-        };
-        ControlFlow::Continue(())
-    });
-}
-
-/// The name of a single-part, unquoted function name such as `modulo`.
-fn unquoted_name(name: &ObjectName) -> Option<&str> {
-    match name.0.as_slice() {
-        [ObjectNamePart::Identifier(ident)] if ident.quote_style.is_none() => Some(&ident.value),
-        _ => None,
-    }
-}
-
-/// Rewrites a bracket-only access chain such as `m['k'][1]` into nested
-/// `arrayElement` calls. Chains with a dot access or a slice stay unchanged.
-fn normalize_map_access(expression: &mut Expr) -> bool {
-    let Expr::CompoundFieldAccess { access_chain, .. } = expression else {
-        return false;
-    };
-    if access_chain.is_empty()
-        || access_chain
-            .iter()
-            .any(|access| !matches!(access, AccessExpr::Subscript(Subscript::Index { .. })))
-    {
-        return false;
-    }
-    let Expr::CompoundFieldAccess { root, access_chain } =
-        std::mem::replace(expression, Expr::Value(Value::Null.into()))
-    else {
-        unreachable!()
-    };
-    let mut input = *root;
-    for access in access_chain {
-        let AccessExpr::Subscript(Subscript::Index { index }) = access else {
-            unreachable!()
-        };
-        input = Expr::Function(Function {
-            name: ObjectName::from(vec![Ident::new("arrayElement")]),
-            uses_odbc_syntax: false,
-            parameters: FunctionArguments::None,
-            args: FunctionArguments::List(FunctionArgumentList {
-                duplicate_treatment: None,
-                clauses: vec![],
-                args: vec![
-                    FunctionArg::Unnamed(FunctionArgExpr::Expr(input)),
-                    FunctionArg::Unnamed(FunctionArgExpr::Expr(index)),
-                ],
-            }),
-            filter: None,
-            null_treatment: None,
-            over: None,
-            within_group: vec![],
-        });
-    }
-    *expression = input;
-    true
-}
diff --git a/crates/frontend-sql/src/unified/sql/collection_planning.rs b/crates/frontend-sql/src/unified/sql/collection_planning.rs
deleted file mode 100644
index 09b0bfa8e..000000000
--- a/crates/frontend-sql/src/unified/sql/collection_planning.rs
+++ /dev/null
@@ -1,194 +0,0 @@
-//! DataFusion planning adapters. Types come from the canonical signature rules;
-//! physical evaluation deliberately remains the query engine's responsibility.
-use super::types::{arrow_to_dtype, dtype_to_arrow, scalar_value_to_asap};
-use asap_types::ir::scalar::{element_access_type, struct_field_type};
-use asap_types::ir::ScalarExpr;
-use asap_types::pre_asap::scalar_type_rules::MapScalarFunction;
-use asap_types::pre_asap::{Field, Schema};
-use datafusion::arrow::datatypes::{DataType, Field as ArrowField, FieldRef};
-use datafusion::common::{DataFusionError, Result, ScalarValue as DfScalarValue};
-use datafusion::logical_expr::{
-    ColumnarValue, ReturnFieldArgs, ScalarFunctionArgs, ScalarUDF, ScalarUDFImpl, Signature,
-    TypeSignature, Volatility,
-};
-use datafusion::prelude::SessionContext;
-use std::hash::{Hash, Hasher};
-use std::sync::Arc;
-
-/// The name ClickHouse's `map(...)` is planned under. DataFusion's SQL planner
-/// reserves `map` for its own constructor (and rejects `map()`), so
-/// `clickhouse_ast::normalize` renames the call and lowering restores `map`.
-pub(super) const MAP_PLANNING_NAME: &str = "asap_map_construct";
-
-#[derive(Debug, Clone, Copy, PartialEq, Eq)]
-enum PlanningFunction {
-    Map(MapScalarFunction),
-    Element,
-    StructField,
-}
-
-pub(super) fn register(context: &SessionContext) {
-    for (name, function) in [
-        (
-            MAP_PLANNING_NAME,
-            PlanningFunction::Map(MapScalarFunction::Construct),
-        ),
-        (
-            "mapconcat",
-            PlanningFunction::Map(MapScalarFunction::Concat),
-        ),
-        ("arrayelement", PlanningFunction::Element),
-        ("tupleelement", PlanningFunction::StructField),
-    ] {
-        context.register_udf(ScalarUDF::from(CollectionPlanningFunction {
-            name,
-            function,
-            signature: match function {
-                PlanningFunction::Map(MapScalarFunction::Construct) => Signature::one_of(
-                    vec![TypeSignature::Exact(vec![]), TypeSignature::VariadicAny],
-                    Volatility::Immutable,
-                ),
-                PlanningFunction::Map(MapScalarFunction::Access)
-                | PlanningFunction::Element
-                | PlanningFunction::StructField => Signature::any(2, Volatility::Immutable),
-                PlanningFunction::Map(MapScalarFunction::Concat) => {
-                    Signature::variadic_any(Volatility::Immutable)
-                }
-            },
-        }));
-    }
-}
-#[derive(Debug, PartialEq, Eq)]
-struct CollectionPlanningFunction {
-    name: &'static str,
-    function: PlanningFunction,
-    signature: Signature,
-}
-// `function` is determined by `name` at registration, so hashing the name and
-// signature agrees with the derived `Eq`.
-impl Hash for CollectionPlanningFunction {
-    fn hash<H: Hasher>(&self, state: &mut H) {
-        self.name.hash(state);
-        self.signature.hash(state);
-    }
-}
-impl CollectionPlanningFunction {
-    fn output(
-        &self,
-        args: &[DataType],
-        nullable: &[bool],
-        literals: Option<&[Option<&DfScalarValue>]>,
-    ) -> Result<(DataType, bool)> {
-        let inputs = args
-            .iter()
-            .zip(nullable)
-            .map(|(dtype, null)| {
-                arrow_to_dtype(dtype)
-                    .map(|dtype| (dtype, *null))
-                    .map_err(|e| DataFusionError::Plan(e.to_string()))
-            })
-            .collect::<Result<Vec<_>>>()?;
-        let (dtype, nullable) = if matches!(
-            self.function,
-            PlanningFunction::Element | PlanningFunction::StructField
-        ) {
-            // DataFusion asks for argument-dependent types before canonical
-            // expression binding. Reuse the shared resolver over typed argument
-            // slots; final canonical binding also validates literal selectors.
-            let schema = Schema::new(
-                inputs
-                    .into_iter()
-                    .enumerate()
-                    .map(|(index, (dtype, nullable))| {
-                        Field::plain(format!("argument_{index}"), dtype, nullable)
-                    })
-                    .collect(),
-            );
-            let args = (0..schema.fields.len())
-                .map(|index| {
-                    if let Some(Some(value)) = literals.and_then(|args| args.get(index)) {
-                        scalar_value_to_asap(value)
-                            .map(ScalarExpr::Literal)
-                            .map_err(|error| DataFusionError::Plan(error.to_string()))
-                    } else {
-                        Ok(ScalarExpr::Column(index))
-                    }
-                })
-                .collect::<Result<Vec<_>>>()?;
-            match self.function {
-                PlanningFunction::Element => element_access_type(&args, &schema),
-                PlanningFunction::StructField => struct_field_type(&args, &schema),
-                PlanningFunction::Map(_) => unreachable!(),
-            }
-        } else if let PlanningFunction::Map(function) = self.function {
-            function.output_type(&inputs)
-        } else {
-            unreachable!()
-        }
-        .map_err(DataFusionError::Plan)?;
-        Ok((dtype_to_arrow(&dtype), nullable))
-    }
-}
-impl ScalarUDFImpl for CollectionPlanningFunction {
-    fn name(&self) -> &str {
-        self.name
-    }
-    fn signature(&self) -> &Signature {
-        &self.signature
-    }
-    fn return_type(&self, args: &[DataType]) -> Result<DataType> {
-        self.output(
-            args,
-            &args
-                .iter()
-                .map(|dtype| *dtype == DataType::Null)
-                .collect::<Vec<_>>(),
-            None,
-        )
-        .map(|output| output.0)
-    }
-    fn return_field_from_args(&self, args: ReturnFieldArgs) -> Result<FieldRef> {
-        let types = args
-            .arg_fields
-            .iter()
-            .map(|field| field.data_type().clone())
-            .collect::<Vec<_>>();
-        let nullable = args
-            .arg_fields
-            .iter()
-            .map(|field| field.is_nullable())
-            .collect::<Vec<_>>();
-        let (dtype, nullable) = self.output(&types, &nullable, Some(args.scalar_arguments))?;
-        Ok(Arc::new(ArrowField::new(self.name, dtype, nullable)))
-    }
-    fn invoke_with_args(&self, _args: ScalarFunctionArgs) -> Result<ColumnarValue> {
-        Err(DataFusionError::NotImplemented("collection planning adapter cannot execute; use a capable query engine or external exact sub_dag".into()))
-    }
-}
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-    #[test]
-    fn planning_adapter_explicitly_refuses_physical_execution() {
-        let adapter = CollectionPlanningFunction {
-            name: MAP_PLANNING_NAME,
-            function: PlanningFunction::Map(MapScalarFunction::Construct),
-            signature: Signature::any(0, Volatility::Immutable),
-        };
-        let args = ScalarFunctionArgs {
-            args: vec![],
-            arg_fields: vec![],
-            number_rows: 1,
-            return_field: Arc::new(ArrowField::new("map", DataType::Null, true)),
-            config_options: Default::default(),
-        };
-        assert!(matches!(
-            adapter.invoke_with_args(args),
-            Err(DataFusionError::NotImplemented(_))
-        ));
-        let result = adapter.return_type(&[]).unwrap();
-        let (expected, _) = MapScalarFunction::Construct.output_type(&[]).unwrap();
-        assert_eq!(result, dtype_to_arrow(&expected));
-    }
-}
diff --git a/crates/frontend-sql/src/unified/sql/expr.rs b/crates/frontend-sql/src/unified/sql/expr.rs
deleted file mode 100644
index 1eebe807f..000000000
--- a/crates/frontend-sql/src/unified/sql/expr.rs
+++ /dev/null
@@ -1,357 +0,0 @@
-use std::rc::Rc;
-
-use datafusion::logical_expr::{BinaryExpr, Expr, Operator};
-
-use asap_frontend_common::UnresolvedScalar as Unresolved;
-use asap_types::ir::ExprSemantics;
-use asap_types::pre_asap::{ArithmeticOpKind, ColumnRef, CompareOpKind, ScalarValue};
-
-use crate::unified::error::SqlError as LoweringError;
-
-use super::types::{arrow_to_dtype, scalar_value_to_asap};
-use super::SqlLowerer;
-
-pub(super) fn split_conjuncts(expr: &Expr) -> Vec<&Expr> {
-    match expr {
-        Expr::BinaryExpr(BinaryExpr {
-            left,
-            op: Operator::And,
-            right,
-        }) => {
-            let mut v = split_conjuncts(left);
-            v.extend(split_conjuncts(right));
-            v
-        }
-        _ => vec![expr],
-    }
-}
-
-impl SqlLowerer<'_> {
-    /// Translate a DataFusion `Expr` to the name-based scalar tree. Every
-    /// `Compare` / `Arithmetic` / `Negative` carries `ExprSemantics::Sql`.
-    /// Subquery-valued expressions lower their plan as a root of its own
-    /// (which is why this is a method: the plan walk needs the catalog).
-    /// Returns `UnsupportedFeature` for anything not needed in v1.
-    pub(super) fn lower_expr(&self, expr: &Expr) -> Result<Unresolved, LoweringError> {
-        let bx = |e: &Expr| self.lower_expr(e).map(Box::new);
-        match expr {
-            // Preserve DataFusion's relation qualifier so a column name shared
-            // across a join (`a.k` vs `b.k`) resolves to the correct side.
-            Expr::Column(col) => Ok(Unresolved::Column(match &col.relation {
-                Some(rel) => ColumnRef::Qualified {
-                    table: rel.to_string(),
-                    name: col.name.clone(),
-                },
-                None => ColumnRef::Named(col.name.clone()),
-            })),
-
-            // Keep Arrow date literals equivalent to SQL CAST('YYYY-MM-DD' AS DATE),
-            // including typed nulls, without adding another canonical scalar variant.
-            Expr::Literal(
-                sv @ (datafusion::common::ScalarValue::Date32(_)
-                | datafusion::common::ScalarValue::Date64(_)),
-                _,
-            ) => {
-                let text = sv.cast_to(&datafusion::arrow::datatypes::DataType::Utf8)?;
-                // Arrow formats Date64 with a time suffix; the canonical Date has
-                // no time-of-day, just like Date64 catalog registration as Date32.
-                let text = match text {
-                    datafusion::common::ScalarValue::Utf8(Some(value)) => {
-                        ScalarValue::Utf8(value.split('T').next().unwrap().to_owned())
-                    }
-                    other => scalar_value_to_asap(&other)?,
-                };
-                Ok(Unresolved::Cast {
-                    expr: Box::new(Unresolved::Literal(text)),
-                    to: asap_types::pre_asap::schema::DataType::Date,
-                    try_cast: false,
-                })
-            }
-            Expr::Literal(sv, _) => scalar_value_to_asap(sv).map(Unresolved::Literal),
-
-            Expr::Alias(a) => self.lower_expr(&a.expr),
-
-            Expr::BinaryExpr(BinaryExpr { left, op, right }) => match op {
-                Operator::And => {
-                    let parts = split_conjuncts(expr);
-                    let lowered: Result<Vec<_>, _> =
-                        parts.iter().map(|e| self.lower_expr(e)).collect();
-                    Ok(Unresolved::BoolAnd(lowered?))
-                }
-                Operator::Or => {
-                    let parts = split_disjuncts(expr);
-                    let lowered: Result<Vec<_>, _> =
-                        parts.iter().map(|e| self.lower_expr(e)).collect();
-                    Ok(Unresolved::BoolOr(lowered?))
-                }
-                Operator::Eq => self.compare(left, CompareOpKind::Eq, right),
-                Operator::NotEq => self.compare(left, CompareOpKind::Ne, right),
-                Operator::Lt => self.compare(left, CompareOpKind::Lt, right),
-                Operator::LtEq => self.compare(left, CompareOpKind::Le, right),
-                Operator::Gt => self.compare(left, CompareOpKind::Gt, right),
-                Operator::GtEq => self.compare(left, CompareOpKind::Ge, right),
-                // BinaryExpr LIKE/ILIKE operators (from optimizer rewrites)
-                Operator::LikeMatch => self.compare(left, CompareOpKind::Like, right),
-                Operator::ILikeMatch => self.compare(left, CompareOpKind::ILike, right),
-                Operator::NotLikeMatch => self.compare(left, CompareOpKind::NotLike, right),
-                Operator::NotILikeMatch => self.compare(left, CompareOpKind::NotILike, right),
-                // Arithmetic
-                Operator::Plus => self.arith(left, ArithmeticOpKind::Add, right),
-                Operator::Minus => self.arith(left, ArithmeticOpKind::Sub, right),
-                Operator::Multiply => self.arith(left, ArithmeticOpKind::Mul, right),
-                Operator::Divide => self.arith(left, ArithmeticOpKind::Div, right),
-                Operator::Modulo => self.arith(left, ArithmeticOpKind::Mod, right),
-                other => Err(LoweringError::UnsupportedFeature(format!(
-                    "operator: {other:?}"
-                ))),
-            },
-
-            // SQL LIKE / ILIKE (dedicated expr node from the SQL parser)
-            Expr::Like(like) => {
-                let op = match (like.negated, like.case_insensitive) {
-                    (false, false) => CompareOpKind::Like,
-                    (true, false) => CompareOpKind::NotLike,
-                    (false, true) => CompareOpKind::ILike,
-                    (true, true) => CompareOpKind::NotILike,
-                };
-                self.compare(&like.expr, op, &like.pattern)
-            }
-
-            // Unary minus. (DataFusion's planner already folds `-<number>`
-            // into a negative literal, so this is a non-literal operand.)
-            Expr::Negative(inner) => Ok(Unresolved::Negative {
-                expr: bx(inner)?,
-                semantics: ExprSemantics::Sql,
-            }),
-
-            // SQL CASE expression
-            Expr::Case(c) => {
-                let operand = c.expr.as_deref().map(bx).transpose()?;
-                let branches = c
-                    .when_then_expr
-                    .iter()
-                    .map(|(when, then)| Ok((self.lower_expr(when)?, self.lower_expr(then)?)))
-                    .collect::<Result<Vec<_>, LoweringError>>()?;
-                let else_expr = c.else_expr.as_deref().map(bx).transpose()?;
-                Ok(Unresolved::Case {
-                    operand,
-                    branches,
-                    else_expr,
-                })
-            }
-
-            Expr::Not(inner) => Ok(Unresolved::Not(bx(inner)?)),
-
-            Expr::IsNull(inner) => Ok(Unresolved::IsNull(bx(inner)?)),
-
-            Expr::IsNotNull(inner) => Ok(Unresolved::IsNotNull(bx(inner)?)),
-
-            Expr::Cast(c) => Ok(Unresolved::Cast {
-                expr: bx(&c.expr)?,
-                to: arrow_to_dtype(c.field.data_type())?,
-                try_cast: false,
-            }),
-
-            // TRY_CAST returns NULL on conversion failure; preserve that semantic.
-            Expr::TryCast(c) => Ok(Unresolved::Cast {
-                expr: bx(&c.expr)?,
-                to: arrow_to_dtype(c.field.data_type())?,
-                try_cast: true,
-            }),
-
-            Expr::InList(il) => {
-                let list: Result<Vec<_>, _> = il.list.iter().map(|e| self.lower_expr(e)).collect();
-                Ok(Unresolved::InList {
-                    expr: bx(&il.expr)?,
-                    list: list?,
-                    negated: il.negated,
-                })
-            }
-
-            Expr::Between(b) => {
-                // Normalize: `x BETWEEN low AND high` → `x >= low AND x <= high`.
-                // `x NOT BETWEEN low AND high` → `x < low OR x > high`.
-                if b.negated {
-                    let lt = self.compare(&b.expr, CompareOpKind::Lt, &b.low)?;
-                    let gt = self.compare(&b.expr, CompareOpKind::Gt, &b.high)?;
-                    Ok(Unresolved::BoolOr(vec![lt, gt]))
-                } else {
-                    let x_low = self.compare(&b.expr, CompareOpKind::Ge, &b.low)?;
-                    let x_high = self.compare(&b.expr, CompareOpKind::Le, &b.high)?;
-                    Ok(Unresolved::BoolAnd(vec![x_low, x_high]))
-                }
-            }
-
-            // `NOW()` / `CURRENT_TIMESTAMP` read the SQL statement evaluation
-            // time. Keep this timestamp-typed leaf distinct from PromQL's
-            // Float64 Unix-seconds `EvalTimestamp`. Issue #184.
-            Expr::ScalarFunction(sf)
-                if sf.args.is_empty()
-                    && matches!(
-                        sf.func.name().to_ascii_lowercase().as_str(),
-                        "now" | "current_timestamp"
-                    ) =>
-            {
-                Ok(Unresolved::CurrentTimestamp)
-            }
-
-            Expr::ScalarFunction(sf) => {
-                let args: Result<Vec<_>, _> = sf.args.iter().map(|e| self.lower_expr(e)).collect();
-                Ok(Unresolved::FunctionCall {
-                    name: if sf.func.name().eq_ignore_ascii_case("arrayelement") {
-                        "asap_element_access".into()
-                    } else if sf.func.name().eq_ignore_ascii_case("tupleelement") {
-                        "asap_struct_field".into()
-                    } else if sf.func.name() == super::collection_planning::MAP_PLANNING_NAME {
-                        "map".into()
-                    } else {
-                        sf.func.name().to_string()
-                    },
-                    args: args?,
-                })
-            }
-
-            // Subquery-valued expressions. Each subquery plan is lowered as a
-            // root of its own; `resolve_root` binds it in its own scope, so an
-            // outer reference inside it has nothing to resolve against — a
-            // correlated subquery is rejected rather than mislowered.
-            Expr::ScalarSubquery(sq) => Ok(Unresolved::ScalarSubquery(Rc::new(
-                self.lower_uncorrelated_subquery(sq, "scalar subquery")?,
-            ))),
-            Expr::Exists(ex) => Ok(Unresolved::Exists {
-                subquery: Rc::new(self.lower_uncorrelated_subquery(&ex.subquery, "EXISTS")?),
-                negated: ex.negated,
-            }),
-            Expr::InSubquery(is) => {
-                let fields = is.subquery.subquery.schema().fields().len();
-                if fields != 1 {
-                    return Err(LoweringError::InvalidExpression(format!(
-                        "IN (subquery) must select exactly one column, got {fields}"
-                    )));
-                }
-                Ok(Unresolved::InSubquery {
-                    expr: bx(&is.expr)?,
-                    subquery: Rc::new(
-                        self.lower_uncorrelated_subquery(&is.subquery, "IN (subquery)")?,
-                    ),
-                    negated: is.negated,
-                })
-            }
-
-            other => Err(LoweringError::UnsupportedFeature(format!(
-                "expression: {}",
-                other
-            ))),
-        }
-    }
-
-    fn lower_uncorrelated_subquery(
-        &self,
-        sq: &datafusion::logical_expr::Subquery,
-        what: &str,
-    ) -> Result<asap_frontend_common::UnresolvedOp, LoweringError> {
-        if !sq.outer_ref_columns.is_empty() {
-            return Err(LoweringError::UnsupportedFeature(format!(
-                "correlated {what}"
-            )));
-        }
-        self.lower_plan(&sq.subquery)
-    }
-
-    pub(super) fn compare(
-        &self,
-        left: &Expr,
-        op: CompareOpKind,
-        right: &Expr,
-    ) -> Result<Unresolved, LoweringError> {
-        Ok(Unresolved::Compare {
-            left: Box::new(self.lower_expr(left)?),
-            op,
-            right: Box::new(self.lower_expr(right)?),
-            semantics: ExprSemantics::Sql,
-        })
-    }
-
-    fn arith(
-        &self,
-        left: &Expr,
-        op: ArithmeticOpKind,
-        right: &Expr,
-    ) -> Result<Unresolved, LoweringError> {
-        Ok(Unresolved::Arithmetic {
-            op,
-            left: Box::new(self.lower_expr(left)?),
-            right: Box::new(self.lower_expr(right)?),
-            semantics: ExprSemantics::Sql,
-        })
-    }
-}
-
-pub(super) fn split_disjuncts(expr: &Expr) -> Vec<&Expr> {
-    match expr {
-        Expr::BinaryExpr(BinaryExpr {
-            left,
-            op: Operator::Or,
-            right,
-        }) => {
-            let mut v = split_disjuncts(left);
-            v.extend(split_disjuncts(right));
-            v
-        }
-        _ => vec![expr],
-    }
-}
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-    use crate::unified::sql::SqlCatalog;
-    use asap_types::pre_asap::schema::DataType;
-    use datafusion::common::ScalarValue as DfScalarValue;
-
-    // Typed Arrow dates normalize to the same typed form as SQL date casts.
-    #[test]
-    fn arrow_date_literals_preserve_value_and_type() {
-        let catalog = SqlCatalog::new();
-        let lowerer = SqlLowerer::new(&catalog);
-        for (value, expected) in [
-            (
-                DfScalarValue::Date32(Some(0)),
-                ScalarValue::Utf8("1970-01-01".into()),
-            ),
-            (
-                DfScalarValue::Date64(Some(-86_400_000)),
-                ScalarValue::Utf8("1969-12-31".into()),
-            ),
-            (DfScalarValue::Date32(None), ScalarValue::Null),
-            (DfScalarValue::Date64(None), ScalarValue::Null),
-        ] {
-            let actual = lowerer.lower_expr(&Expr::Literal(value, None)).unwrap();
-            assert_eq!(
-                actual,
-                Unresolved::Cast {
-                    expr: Box::new(Unresolved::Literal(expected)),
-                    to: DataType::Date,
-                    try_cast: false,
-                }
-            );
-        }
-    }
-
-    // Unary minus over a non-literal is the `Negative` scalar, SQL-flavoured.
-    #[test]
-    fn unary_minus_lowers_to_negative_with_sql_semantics() {
-        let catalog = SqlCatalog::new();
-        let lowerer = SqlLowerer::new(&catalog);
-        let expr = Expr::Negative(Box::new(Expr::Column(
-            datafusion::common::Column::new_unqualified("x"),
-        )));
-        assert_eq!(
-            lowerer.lower_expr(&expr).unwrap(),
-            Unresolved::Negative {
-                expr: Box::new(Unresolved::Column(ColumnRef::Named("x".into()))),
-                semantics: ExprSemantics::Sql,
-            }
-        );
-    }
-}
diff --git a/crates/frontend-sql/src/unified/sql/mod.rs b/crates/frontend-sql/src/unified/sql/mod.rs
deleted file mode 100644
index 1243aa8e6..000000000
--- a/crates/frontend-sql/src/unified/sql/mod.rs
+++ /dev/null
@@ -1,2528 +0,0 @@
-//! SQL → the name-based front-end tree
-//! ([`UnresolvedOp`](asap_frontend_common::UnresolvedOp) /
-//! [`UnresolvedScalar`](asap_frontend_common::UnresolvedScalar)).
-//!
-//! Parses SQL via DataFusion (over the catalog's registered tables), then
-//! walks the unoptimized `LogicalPlan` and emits `UnresolvedOp` nodes with
-//! unresolved `ColumnRef`s directly (issue #179) — the same tree shape
-//! [`resolve_root`](asap_frontend_common::resolve_root) binds into the
-//! positional, unified `OperatorNode` IR. Unlike PromQL's front end, SQL's
-//! Ordinary SQL `Aggregate` nodes are `Reduction::Reduce`. The explicit
-//! `asap_rate`/`asap_increase` bridge is the narrow exception: it
-//! spells a time-series range reducer with an explicit value, time-index, and
-//! window and therefore lowers to the same `TimeRange` + `PerEntity` shape as
-//! its PromQL counterpart. The front end also has to fold a `WHERE` directly
-//! over a bare table scan onto
-//! `Scan.predicates` itself (`filter_or_fold`) — canonical's invariant that a
-//! `Filter` never sits directly over a `Scan` — since front ends producing
-//! this shape are responsible for it now, not a converter.
-//!
-//! Heavy-hitter `topk` recognition (`ORDER BY count(...) DESC LIMIT k`) is
-//! *not* done here: SQL emits a plain `Sort`/`Limit`, and the shared
-//! `canonicalize` pass (issue #34, run by `resolve_root`) recognises the
-//! count-ranked shape positionally, so a SQL `ORDER BY`/`LIMIT` and a PromQL
-//! `topk(...)` converge without either front end special-casing the other's
-//! syntax.
-
-use std::rc::Rc;
-use std::sync::Arc;
-use std::time::Duration;
-
-use datafusion::arrow::compute::kernels::cast_utils::parse_interval_month_day_nano;
-use datafusion::arrow::datatypes::{DataType as ArrowDataType, Field, FieldRef};
-use datafusion::catalog::MemorySchemaProvider;
-use datafusion::common::config::ConfigOptions;
-use datafusion::common::tree_node::{Transformed, TreeNode, TreeNodeRecursion};
-use datafusion::common::{Column as DfColumn, DFSchema, ScalarValue as DfScalarValue};
-use datafusion::datasource::MemTable;
-use datafusion::functions_aggregate::count::count_udaf;
-use datafusion::functions_aggregate::sum::sum_udaf;
-use datafusion::logical_expr::expr::AggregateFunction;
-use datafusion::logical_expr::expr_rewriter::FunctionRewrite;
-use datafusion::logical_expr::function::{PartitionEvaluatorArgs, WindowUDFFieldArgs};
-use datafusion::logical_expr::{
-    self, lit, AggregateUDF, Case, ColumnarValue, Distinct, Expr, ExprSchemable, JoinType,
-    LogicalPlan, PartitionEvaluator, ScalarFunctionArgs, ScalarUDF, ScalarUDFImpl, Signature,
-    SimpleAggregateUDF, TypeSignature, Volatility, WindowFrameBound as DfWindowFrameBound,
-    WindowFrameUnits as DfWindowFrameUnits, WindowFunctionDefinition, WindowUDF, WindowUDFImpl,
-};
-use datafusion::optimizer::analyzer::function_rewrite::ApplyFunctionRewrites;
-use datafusion::optimizer::{AnalyzerRule, OptimizerConfig};
-use datafusion::prelude::{SessionConfig, SessionContext};
-use datafusion::sql::parser::DFParser;
-use datafusion::sql::sqlparser::dialect::GenericDialect;
-
-use asap_frontend_common::{
-    resolve_root, UnresolvedOp as Unresolved, UnresolvedPredicate as Predicate,
-    UnresolvedProjectItem as ProjectItem, UnresolvedScalar as Scalar, UnresolvedSortKey as SortKey,
-};
-use asap_sql_function_catalog::{AggSemantic, Arity, RewriteKind};
-use asap_types::ir::operator_properties::{
-    GroupKeys, Reduction, Source, WindowFrame, WindowFrameBound, WindowFrameOffset,
-    WindowFrameUnits,
-};
-use asap_types::ir::TimeRangeKind;
-use asap_types::pre_asap::agg_intent::AggIntent;
-use asap_types::pre_asap::schema::{DataType, FieldDataType, Schema};
-
-use asap_types::pre_asap::{
-    resolve_column_ref, ColumnRef, CompareOpKind, JoinKind, RelationalSetOpKind, ScalarValue,
-    WindowFuncKind,
-};
-use asap_types::types::AccuracyTarget;
-use asap_types::workload::SqlDialect;
-
-use crate::unified::error::SqlError as LoweringError;
-
-mod clickhouse_ast;
-mod collection_planning;
-mod expr;
-mod types;
-
-pub use types::SqlCatalog;
-
-use self::types::{arrow_to_dtype, scalar_value_to_asap, schema_to_arrow};
-
-std::thread_local! {
-    static ACCURACY: std::cell::RefCell<AccuracyTarget> =
-        const { std::cell::RefCell::new(AccuracyTarget::Exact) };
-}
-
-/// RAII guard installing `accuracy` as the ambient accuracy target for the
-/// current thread's lowering, restoring the prior value on drop — same
-/// ambient-thread-local shape as `asap_frontend_promql::promql`'s
-/// `AccuracyGuard`, for the same reason: it injects `accuracy` into the deep
-/// `lower_plan` recursion without a parameter on every one of its
-/// signatures, consulted only at the couple of sites that build an
-/// accuracy-bearing `AggIntent`.
-struct AccuracyGuard(AccuracyTarget);
-
-impl AccuracyGuard {
-    fn install(accuracy: AccuracyTarget) -> Self {
-        let prev = ACCURACY.with(|a| a.replace(accuracy));
-        AccuracyGuard(prev)
-    }
-}
-
-impl Drop for AccuracyGuard {
-    fn drop(&mut self) {
-        ACCURACY.with(|a| *a.borrow_mut() = std::mem::replace(&mut self.0, AccuracyTarget::Exact));
-    }
-}
-
-fn current_accuracy() -> AccuracyTarget {
-    ACCURACY.with(|a| a.borrow().clone())
-}
-
-/// Lowers SQL strings to the name-based [`UnresolvedOp`](asap_frontend_common::UnresolvedOp)
-/// tree over a table [`SqlCatalog`]. Call
-/// [`resolve_root`](asap_frontend_common::resolve_root) on the result for
-/// the resolved operator DAG.
-pub struct SqlLowerer<'a> {
-    catalog: &'a SqlCatalog,
-    dialect: SqlDialect,
-}
-
-impl<'a> SqlLowerer<'a> {
-    pub fn new(catalog: &'a SqlCatalog) -> Self {
-        Self {
-            catalog,
-            dialect: SqlDialect::DataFusionSQL,
-        }
-    }
-
-    /// Parse under a specific SQL dialect (e.g. `ClickhouseSQL`, which maps to
-    /// sqlparser's vendored `ClickHouseDialect` — array-lambda syntax and
-    /// `arr[-1]` indexing parse under it that don't parse generically). This
-    /// only changes *parsing*: a ClickHouse-only builtin function not listed
-    /// in `asap_sql_function_catalog::CLICKHOUSE_BUILTINS` (`uniqExact` and
-    /// `countIf` are; most of ClickHouse's builtin surface isn't yet) is
-    /// still unknown to DataFusion's planner and still fails there, and
-    /// `ElasticSQL` has no vendored parser at all.
-    pub fn with_dialect(catalog: &'a SqlCatalog, dialect: SqlDialect) -> Self {
-        Self { catalog, dialect }
-    }
-
-    /// Parse + lower a SQL query to the name-based tree, threading
-    /// `accuracy` onto every approximate intent (`Count`, `Quantile`,
-    /// `Cardinality`) as it is built.
-    ///
-    /// The `AccuracyGuard` installs *after* the only `.await` point
-    /// (DataFusion statement planning) — `lower_plan` itself is synchronous, so once it starts
-    /// there is no further suspension point that could move this task to a
-    /// different OS thread out from under a thread-local set beforehand.
-    ///
-    /// Runs `ApplyFunctionRewrites` — the single `AnalyzerRule` DataFusion's
-    /// own `Analyzer` uses internally to apply `FunctionRewrite`s, called
-    /// directly rather than through `Analyzer::execute_and_check` — over the
-    /// raw parsed plan before lowering, carrying only
-    /// `ClickHouseBuiltinRewrite` (catalog-driven, see its own doc — it
-    /// covers every `asap_sql_function_catalog::CLICKHOUSE_BUILTINS` entry,
-    /// not just one). `ctx.sql(...).into_unoptimized_plan()` alone returns
-    /// `SqlToRel`'s output untouched, and a `FunctionRewrite` only ever runs
-    /// as part of this rule, so calling it directly is unavoidable to make
-    /// the rewrite fire. Its `analyze()` already does a full
-    /// `transform_up_with_subqueries` over the whole plan, so it needs no
-    /// wrapping `Analyzer` at all — deliberately not
-    /// `Analyzer::execute_and_check` (whether with the default 5-rule
-    /// analyzer or an empty one carrying just this rewrite): that method
-    /// runs an unconditional post-check (`check_plan`, hardcoded, not itself
-    /// a rule) that isn't wanted here — e.g. it independently rejects a
-    /// multi-column `IN (subquery)` before `lower_in_subquery`'s own arity
-    /// check would. Going straight to `ApplyFunctionRewrites` avoids that
-    /// entirely. TypeCoercion then records implicit conversions explicitly,
-    /// including timestamp literals in predicates, before IR validation.
-    pub async fn lower(
-        &self,
-        sql: &str,
-        accuracy: &AccuracyTarget,
-    ) -> Result<Unresolved, LoweringError> {
-        let ctx = self.build_context()?;
-        let state = ctx.state();
-        let statement = if matches!(self.dialect, SqlDialect::ClickhouseSQL) {
-            let mut statement =
-                state.sql_to_statement(sql, &datafusion::config::Dialect::ClickHouse)?;
-            if let datafusion::sql::parser::Statement::Statement(ast) = &mut statement {
-                clickhouse_ast::normalize(ast);
-            }
-            statement
-        } else {
-            let mut statements = DFParser::parse_sql_with_dialect(sql, &GenericDialect)?;
-            let (Some(statement), true) = (statements.pop_front(), statements.is_empty()) else {
-                return Err(LoweringError::UnsupportedFeature(
-                    "exactly one SQL statement per query".into(),
-                ));
-            };
-            statement
-        };
-        let plan = state.statement_to_plan(statement).await?;
-        let rewriter = ApplyFunctionRewrites::new(vec![Arc::new(ClickHouseBuiltinRewrite)]);
-        let plan = rewriter.analyze(plan, &ctx.state().options())?;
-        let plan = datafusion::optimizer::analyzer::type_coercion::TypeCoercion::new()
-            .analyze(plan, &ctx.state().options())?;
-        // Output schemas omit predicate and nested-expression types. Check the
-        // typed SQL plan before lowering erases fixed-duration units.
-        plan.apply_with_subqueries(|node| {
-            let mut schema = DFSchema::empty();
-            for input in node.inputs() {
-                schema.merge(input.schema());
-            }
-            schema.merge(node.schema());
-            node.apply_expressions(|expr| {
-                expr.apply(|nested| {
-                    if let Expr::BinaryExpr(binary) = nested {
-                        if binary.op == logical_expr::Operator::Minus
-                            // DataFusion types `date - date` as an Int64 day
-                            // count, which the canonical DAG has no shape for.
-                            && (matches!(
-                                (binary.left.get_type(&schema)?, binary.right.get_type(&schema)?),
-                                (ArrowDataType::Date32, ArrowDataType::Date32)
-                                    | (ArrowDataType::Date64, ArrowDataType::Date64)
-                            ) || matches!(
-                                nested.get_type(&schema)?,
-                                ArrowDataType::Duration(_)
-                            ))
-                        {
-                            return Err(datafusion::common::DataFusionError::Plan(
-                                "temporal subtraction produces an unsupported duration type".into(),
-                            ));
-                        }
-                    }
-                    Ok(TreeNodeRecursion::Continue)
-                })
-            })
-        })?;
-        let _guard = AccuracyGuard::install(accuracy.clone());
-        self.lower_plan(&plan)
-    }
-
-    /// Register the catalog tables (empty Arrow `MemTable`s) so DataFusion can
-    /// resolve table/column references during planning.
-    fn build_context(&self) -> Result<SessionContext, LoweringError> {
-        let dialect_name = match &self.dialect {
-            SqlDialect::DataFusionSQL => "generic",
-            SqlDialect::ClickhouseSQL => "ClickHouse",
-            SqlDialect::ElasticSQL => {
-                return Err(LoweringError::UnsupportedDialect("ElasticSQL".into()))
-            }
-        };
-        let config = SessionConfig::new().set_str("datafusion.sql_parser.dialect", dialect_name);
-        let ctx = SessionContext::new_with_config(config);
-        if matches!(self.dialect, SqlDialect::ClickhouseSQL) {
-            collection_planning::register(&ctx);
-        }
-        // A catalog key like "bgp.bgp_updates" schema-qualifies the table
-        // (e.g. a ClickHouse database name). DataFusion requires the parent
-        // schema to be registered before a qualified table can be, so create
-        // it on demand.
-        let catalog_provider = ctx.catalog("datafusion").ok_or_else(|| {
-            LoweringError::InvalidExpression("default \"datafusion\" catalog missing".into())
-        })?;
-        for (name, schema) in &self.catalog.tables {
-            if let Some((schema_name, _)) = name.split_once('.') {
-                if catalog_provider.schema(schema_name).is_none() {
-                    catalog_provider
-                        .register_schema(schema_name, Arc::new(MemorySchemaProvider::new()))?;
-                }
-            }
-            let arrow_schema = Arc::new(schema_to_arrow(schema));
-            let mem_table = MemTable::try_new(arrow_schema, vec![vec![]])?;
-            ctx.register_table(name.as_str(), Arc::new(mem_table))?;
-        }
-        // Register a stub `AggregateUDF` for every catalog-listed
-        // ClickHouse-only builtin, purely so DataFusion's planner can
-        // resolve its name during parsing — `lower()` rewrites every call
-        // site to a native DataFusion aggregate via `ClickHouseBuiltinRewrite`
-        // before `lower_plan` sees it.
-        for builtin in asap_sql_function_catalog::CLICKHOUSE_BUILTINS {
-            ctx.register_udaf(clickhouse_builtin_stub_udaf(builtin.name, builtin.arity));
-        }
-        // Register a stub `ScalarUDF` for every catalog-listed ClickHouse-only
-        // *scalar* builtin — same reason as the `AggregateUDF` loop above
-        // (DataFusion otherwise rejects the call as an unknown function
-        // during `SqlToRel` conversion), but with no rewrite step to follow:
-        // `lower_expr`'s `Expr::ScalarFunction` arm already lowers any
-        // scalar call generically to `UnresolvedScalar::FunctionCall { name,
-        // args }`, so registering the stub is the entire fix (issue #230).
-        for builtin in asap_sql_function_catalog::CLICKHOUSE_SCALAR_BUILTINS {
-            ctx.register_udf(clickhouse_scalar_builtin_stub_udf(
-                builtin.name,
-                builtin.arity,
-            ));
-        }
-        // Planning-only relation markers.  They let a workload author state
-        // the PromQL temporal/classic-histogram semantics of an equivalent SQL
-        // rewrite without teaching the canonical IR a second, SQL-specific
-        // spelling of either operation.  `lower_projection` consumes these
-        // calls; they can never survive as executable scalar functions.
-        for (name, arity) in [
-            ("asap_promql_subquery", Arity::Exact(2)),
-            ("asap_histogram_quantile", Arity::Exact(1)),
-        ] {
-            ctx.register_udf(clickhouse_scalar_builtin_stub_udf(name, arity));
-        }
-        // Register a stub `WindowUDF` for every catalog-listed ClickHouse-only
-        // *window* builtin — same reason as the two loops above, but with no
-        // rewrite step to follow: `lower_window_func_kind` already maps each
-        // name directly to its own `WindowFuncKind` variant (issue #267).
-        for builtin in asap_sql_function_catalog::CLICKHOUSE_WINDOW_BUILTINS {
-            ctx.register_udwf(clickhouse_window_builtin_stub_udwf(
-                builtin.name,
-                builtin.arity,
-            ));
-        }
-        Ok(ctx)
-    }
-
-    pub(super) fn lower_plan(&self, plan: &LogicalPlan) -> Result<Unresolved, LoweringError> {
-        match plan {
-            LogicalPlan::TableScan(scan) => self.lower_table_scan(scan),
-            // The one empty input row of a `SELECT` without `FROM`.
-            LogicalPlan::EmptyRelation(empty) => Ok(Unresolved::Values {
-                rows: if empty.produce_one_row {
-                    vec![vec![]]
-                } else {
-                    vec![]
-                },
-                schema: Schema {
-                    fields: vec![],
-                    time_index: None,
-                    unique_keys: vec![],
-                    closed: true,
-                },
-            }),
-            LogicalPlan::Values(values) => self.lower_values(values),
-            LogicalPlan::Filter(filter) => self.lower_filter(filter),
-            LogicalPlan::Projection(proj) => self.lower_projection(proj),
-            LogicalPlan::Aggregate(agg) => self.lower_aggregate(agg),
-            LogicalPlan::Sort(sort) => self.lower_sort(sort),
-            LogicalPlan::Limit(limit) => self.lower_limit(limit),
-            LogicalPlan::Distinct(d) => match d {
-                Distinct::On(_) => Err(LoweringError::UnsupportedFeature("DISTINCT ON".into())),
-                Distinct::All(input) => Ok(Unresolved::Dedup {
-                    cols: vec![],
-                    child: Rc::new(self.lower_plan(input)?),
-                }),
-            },
-            LogicalPlan::Union(u) => {
-                // Fold n inputs left-associatively into SetOp { Union, all: true }.
-                let mut iter = u.inputs.iter();
-                let first = iter
-                    .next()
-                    .ok_or_else(|| LoweringError::InvalidExpression("empty union".into()))?;
-                let first_expr = self.lower_plan(first)?;
-                iter.try_fold(first_expr, |left, right_plan| {
-                    Ok(Unresolved::SetOp {
-                        kind: RelationalSetOpKind::Union,
-                        all: true,
-                        left: Rc::new(left),
-                        right: Rc::new(self.lower_plan(right_plan)?),
-                    })
-                })
-            }
-            LogicalPlan::Window(window) => self.lower_window(window),
-            LogicalPlan::Join(join) => self.lower_join(join),
-            LogicalPlan::Subquery(_) => Err(LoweringError::UnsupportedFeature("subquery".into())),
-            LogicalPlan::SubqueryAlias(alias) => {
-                // An alias over a table re-qualifies the scan's columns with the
-                // alias (so `a.col` / `b.col` in a self-join disambiguate).
-                match alias.input.as_ref() {
-                    LogicalPlan::TableScan(scan) => {
-                        self.scan_source(&scan.table_name.to_string(), &alias.alias.to_string())
-                    }
-                    // A *derived table* / inline view — `FROM (SELECT …) t`, the
-                    // SQL counterpart of PromQL function nesting (an aggregate
-                    // over an aggregate, a filter over a derived aggregate, …).
-                    // Lower the inner plan, then re-qualify its output columns
-                    // with the alias so `t.col` resolves to *this* relation — and,
-                    // critically, so a join over two derived tables disambiguates
-                    // its keys instead of both binding to the first bare-name
-                    // match (issue #66). The inner column *names* are unchanged;
-                    // only the qualifier is stamped.
-                    other => {
-                        let alias_name = alias.alias.to_string();
-                        match self.lower_plan(other)? {
-                            // The derived SELECT list already lowered to a
-                            // Projection — stamp the alias onto it, no extra node.
-                            Unresolved::Project { cols, child, .. } => Ok(Unresolved::Project {
-                                cols,
-                                qualifier: Some(alias_name),
-                                child,
-                            }),
-                            // Otherwise (e.g. a `LIMIT` or `DISTINCT` sub-plan) wrap
-                            // in an identity projection that re-qualifies each
-                            // output column. Names come from the sub-plan's schema.
-                            inner => {
-                                let cols = alias
-                                    .input
-                                    .schema()
-                                    .fields()
-                                    .iter()
-                                    .map(|f| ProjectItem {
-                                        alias: Some(f.name().clone()),
-                                        expr: Scalar::Column(ColumnRef::Named(f.name().clone())),
-                                    })
-                                    .collect();
-                                Ok(Unresolved::Project {
-                                    cols,
-                                    qualifier: Some(alias_name),
-                                    child: Rc::new(inner),
-                                })
-                            }
-                        }
-                    }
-                }
-            }
-            other => Err(LoweringError::UnsupportedFeature(format!(
-                "plan node: {}",
-                other.display()
-            ))),
-        }
-    }
-
-    /// `WHERE` — a conjunction of ordinary predicates plus, possibly, subquery
-    /// predicates (issue #111).
-    ///
-    /// The ordinary conjuncts stay one predicate, folded onto a bare `Scan`
-    /// (`filter_or_fold`). A subquery conjunct — `c IN (SELECT …)`, `EXISTS
-    /// (…)`, `x > (SELECT …)` — is a row filter whose predicate reads another
-    /// operator (`UnresolvedScalar::InSubquery` / `Exists` /
-    /// `ScalarSubquery`); each one becomes its own `Filter` **above** the
-    /// ordinary predicate, so the shared `canonicalize` pass can turn it into
-    /// the join it is without having to peel it out of a conjunction or off
-    /// a `Scan` (it only lifts subqueries out of `Filter` / `Project`). A
-    /// semi-join only ever drops left rows, so the two orders agree.
-    ///
-    /// The one subquery shape still lowered to a join here is a *correlated*
-    /// `EXISTS`: its correlation references both sides, which only a join
-    /// predicate can bind (a subquery referenced from a scalar position is
-    /// resolved as a root in its own scope).
-    fn lower_filter(&self, filter: &logical_expr::Filter) -> Result<Unresolved, LoweringError> {
-        let mut conjuncts = Vec::new();
-        split_conjunction(&filter.predicate, &mut conjuncts);
-        let (subqueries, residual): (Vec<_>, Vec<_>) =
-            conjuncts.into_iter().partition(|e| reads_subquery(e));
-
-        let input = self.lower_plan(&filter.input)?;
-        let mut node = match rebuild_conjunction(&residual) {
-            Some(pred) => filter_or_fold(self.lower_expr(&pred)?, input),
-            None => input,
-        };
-        for sq in subqueries {
-            node = match sq {
-                Expr::Exists(ex) if !ex.subquery.outer_ref_columns.is_empty() => {
-                    self.lower_correlated_exists(ex, node)?
-                }
-                other => Unresolved::Filter {
-                    pred: Predicate(self.lower_expr(other)?),
-                    child: Rc::new(node),
-                },
-            };
-        }
-        Ok(node)
-    }
-
-    /// `[NOT] EXISTS (SELECT … WHERE inner.k = outer.k)` → a semi- / anti-join
-    /// on the correlation predicate (issue #111).
-    fn lower_correlated_exists(
-        &self,
-        ex: &logical_expr::expr::Exists,
-        left: Unresolved,
-    ) -> Result<Unresolved, LoweringError> {
-        let kind = if ex.negated {
-            JoinKind::Anti
-        } else {
-            JoinKind::Semi
-        };
-        // A semi-join discards the right side's columns, and `SELECT 1` projects
-        // the correlation columns away — so drop the subquery's projections and
-        // join against what they sit on.
-        let mut inner = ex.subquery.subquery.as_ref();
-        while let LogicalPlan::Projection(p) = inner {
-            inner = &p.input;
-        }
-        // Lift the correlated conjuncts out of the subquery's filter; they are
-        // the join predicate. Whatever is left stays an ordinary inner filter.
-        let (inner, correlation) = split_correlation(inner)?;
-        let right = self.lower_plan(&inner)?;
-        let pred = match correlation {
-            Some(e) => Predicate(self.lower_expr(&e)?),
-            None => Predicate(Scalar::Literal(ScalarValue::Boolean(true))),
-        };
-        Ok(Unresolved::Join {
-            kind,
-            pred,
-            left: Rc::new(left),
-            right: Rc::new(right),
-        })
-    }
-
-    /// `VALUES (…), (…)` — one row per values row, typed by DataFusion's
-    /// declared schema. Row expressions have no input-column scope.
-    fn lower_values(&self, values: &logical_expr::Values) -> Result<Unresolved, LoweringError> {
-        let rows = values
-            .values
-            .iter()
-            .map(|row| row.iter().map(|e| self.lower_expr(e)).collect())
-            .collect::<Result<Vec<Vec<_>>, LoweringError>>()?;
-        let fields = values
-            .schema
-            .fields()
-            .iter()
-            .map(|f| {
-                Ok(asap_types::pre_asap::Field::plain(
-                    f.name().clone(),
-                    arrow_to_dtype(f.data_type())?,
-                    f.is_nullable(),
-                ))
-            })
-            .collect::<Result<Vec<_>, LoweringError>>()?;
-        Ok(Unresolved::Values {
-            rows,
-            schema: Schema {
-                fields,
-                time_index: None,
-                unique_keys: vec![],
-                closed: true,
-            },
-        })
-    }
-
-    /// Table leaf — carries the catalog's resolved schema directly on `Scan`
-    /// (`schema: Some(_)`), so `resolve_root`'s SchemaResolver doesn't need to
-    /// usage-derive it (SQL is never schemaless). Projection pushdown is left
-    /// to the enclosing `Project` (DataFusion's unoptimized plan sets no
-    /// projection).
-    fn lower_table_scan(
-        &self,
-        scan: &logical_expr::TableScan,
-    ) -> Result<Unresolved, LoweringError> {
-        let table = scan.table_name.to_string();
-        self.scan_source(&table, &table)
-    }
-
-    /// A `Scan` over catalog table `table`, with its columns qualified by
-    /// `qualifier` (the table name, or an alias from a `SubqueryAlias`) so
-    /// `Qualified` column refs resolve to the right side across a join.
-    fn scan_source(&self, table: &str, qualifier: &str) -> Result<Unresolved, LoweringError> {
-        let schema = self
-            .catalog
-            .tables
-            .get(table)
-            .ok_or_else(|| LoweringError::TableNotFound(table.to_string()))?;
-        let qualified = Schema {
-            fields: schema
-                .fields
-                .iter()
-                .cloned()
-                .map(|c| c.with_table(qualifier))
-                .collect(),
-            time_index: schema.time_index,
-            unique_keys: schema.unique_keys.clone(),
-            // Catalog-backed: the table's columns are fully declared → closed.
-            closed: true,
-        };
-        Ok(Unresolved::Scan {
-            source: Source::Table {
-                table_ref: table.to_string(),
-            },
-            predicates: vec![],
-            schema: Some(qualified),
-        })
-    }
-
-    /// ⋈ — equijoin. The `on` key pairs become `left = right` comparisons,
-    /// AND-ed with any non-equi `filter`, into the join predicate — still
-    /// name-based here (like a `WHERE`); `resolve_root` derives the
-    /// concatenated output schema downstream. Semi/anti/mark joins have no
-    /// canonical counterpart yet and are rejected.
-    fn lower_join(&self, join: &logical_expr::Join) -> Result<Unresolved, LoweringError> {
-        let kind = match join.join_type {
-            JoinType::Inner => JoinKind::Inner,
-            JoinType::Left => JoinKind::Left,
-            JoinType::Right => JoinKind::Right,
-            JoinType::Full => JoinKind::Full,
-            other => {
-                return Err(LoweringError::UnsupportedFeature(format!(
-                    "join type: {other:?}"
-                )))
-            }
-        };
-        let mut conjuncts = join
-            .on
-            .iter()
-            .map(|(l, r)| self.compare(l, CompareOpKind::Eq, r))
-            .collect::<Result<Vec<_>, LoweringError>>()?;
-        if let Some(filter) = &join.filter {
-            conjuncts.push(self.lower_expr(filter)?);
-        }
-        let pred = Predicate(match conjuncts.len() {
-            // No condition (a CROSS JOIN) is unconditionally true.
-            0 => Scalar::Literal(ScalarValue::Boolean(true)),
-            1 => conjuncts.pop().unwrap(),
-            _ => Scalar::BoolAnd(conjuncts),
-        });
-        Ok(Unresolved::Join {
-            kind,
-            pred,
-            left: Rc::new(self.lower_plan(&join.left)?),
-            right: Rc::new(self.lower_plan(&join.right)?),
-        })
-    }
-
-    /// `func(args) OVER (PARTITION BY … ORDER BY … ROWS/RANGE BETWEEN …)`. One
-    /// window function per plan node.
-    fn lower_window(&self, window: &logical_expr::Window) -> Result<Unresolved, LoweringError> {
-        if window.window_expr.len() > 1 {
-            return Err(LoweringError::UnsupportedFeature(format!(
-                "multiple window functions in one plan node (got {}); split them",
-                window.window_expr.len()
-            )));
-        }
-        let child = Rc::new(self.lower_plan(&window.input)?);
-        let first = window
-            .window_expr
-            .first()
-            .ok_or_else(|| LoweringError::InvalidExpression("empty window expression".into()))?;
-        let first = match first {
-            Expr::Alias(alias) => alias.expr.as_ref(),
-            other => other,
-        };
-        let Expr::WindowFunction(wf) = first else {
-            return Err(LoweringError::InvalidExpression(
-                "expected a window function in Window plan node".into(),
-            ));
-        };
-        let func = lower_window_func_kind(&wf.fun)?;
-        let mut args = wf
-            .params
-            .args
-            .iter()
-            .map(|e| self.lower_expr(e))
-            .collect::<Result<Vec<_>, _>>()?;
-        // Nth_value: lift N from the (literal) 2nd arg, keep only the column.
-        let func = if matches!(func, WindowFuncKind::NthValue(None)) {
-            let n = match args.get(1) {
-                Some(Scalar::Literal(ScalarValue::Int64(n))) if *n > 0 => *n as u64,
-                other => {
-                    return Err(LoweringError::InvalidExpression(format!(
-                        "NTH_VALUE requires a positive integer literal 2nd arg, got {other:?}"
-                    )))
-                }
-            };
-            args.truncate(1);
-            WindowFuncKind::NthValue(Some(n))
-        } else {
-            func
-        };
-        let partition_by = wf
-            .params
-            .partition_by
-            .iter()
-            .map(expr_to_group_ref)
-            .collect::<Result<Vec<_>, _>>()?;
-        let order_by = wf
-            .params
-            .order_by
-            .iter()
-            .map(|s| {
-                self.lower_expr(&s.expr).map(|expr| SortKey {
-                    expr,
-                    ascending: s.asc,
-                    nulls_first: s.nulls_first,
-                })
-            })
-            .collect::<Result<Vec<_>, _>>()?;
-        let frame = lower_window_frame(&wf.params.window_frame)?;
-        // The window plan's schema is `[input fields …, window output]`; the last
-        // field is the window column's name (what an enclosing Project references).
-        let output_name = window
-            .schema
-            .fields()
-            .last()
-            .map(|f| f.name().clone())
-            .unwrap_or_else(|| "window".into());
-        Ok(Unresolved::SQLWindowFunc {
-            func,
-            args,
-            partition_by: partition_by.into(),
-            order_by,
-            frame: Some(frame),
-            output_name,
-            child,
-        })
-    }
-
-    fn lower_projection(
-        &self,
-        proj: &logical_expr::Projection,
-    ) -> Result<Unresolved, LoweringError> {
-        if let Some(bridge) = planning_bridge(proj)? {
-            let input = self.lower_plan(&proj.input)?;
-            return Ok(match bridge {
-                PlanningBridge::PromqlSubquery { range, resolution } => {
-                    let child = Rc::new(self.temporal_bridge_projection(proj, input)?);
-                    Unresolved::PromqlSubquery {
-                        range,
-                        resolution: Some(resolution),
-                        child,
-                    }
-                }
-                PlanningBridge::HistogramQuantile { q } => Unresolved::Aggregate {
-                    // The marker is the projection's only column: one histogram.
-                    reduction: Reduction::Reduce(GroupKeys::none()),
-                    measures: vec![AggIntent::HistogramQuantile {
-                        q,
-                        le: ColumnRef::Named("le".into()),
-                    }],
-                    output_names: vec!["value".into()],
-                    filters: vec![],
-                    having: None,
-                    child: Rc::new(input),
-                },
-            });
-        }
-        let child = Rc::new(self.lower_plan(&proj.input)?);
-        let temporal_input = plan_has_temporal_aggregate(&proj.input);
-        let cols = proj
-            .expr
-            .iter()
-            .map(|e| match e {
-                Expr::Alias(a) => {
-                    let expr = if temporal_input && is_temporal_output_column(&a.expr) {
-                        Scalar::Column(ColumnRef::Named("value".into()))
-                    } else {
-                        self.lower_expr(&a.expr)?
-                    };
-                    Ok::<ProjectItem, LoweringError>(ProjectItem {
-                        expr,
-                        alias: Some(a.name.clone()),
-                    })
-                }
-                _ => {
-                    let expr = if temporal_input && is_temporal_output_column(e) {
-                        Scalar::Column(ColumnRef::Named("value".into()))
-                    } else {
-                        self.lower_expr(e)?
-                    };
-                    Ok::<ProjectItem, LoweringError>(ProjectItem { expr, alias: None })
-                }
-            })
-            .collect::<Result<Vec<_>, _>>()?;
-        Ok(Unresolved::Project {
-            cols,
-            qualifier: None,
-            child,
-        })
-    }
-
-    fn lower_aggregate(&self, agg: &logical_expr::Aggregate) -> Result<Unresolved, LoweringError> {
-        let input = self.lower_plan(&agg.input)?;
-        // Each measure's row predicate (`FILTER (WHERE …)`, or the NULL-skip
-        // a `count(expr)` implies), read off the original typed expression
-        // before derived-column rewriting erases the argument's nullability.
-        let measure_filters = agg
-            .aggr_expr
-            .iter()
-            .map(|e| measure_filter(e, agg.input.schema()))
-            .collect::<Result<Vec<_>, LoweringError>>()?;
-
-        if agg.aggr_expr.iter().any(is_temporal_aggregate) {
-            if measure_filters.iter().any(Option::is_some) {
-                return Err(LoweringError::UnsupportedFeature(
-                    "FILTER on an ASAP temporal aggregate".into(),
-                ));
-            }
-            return self.lower_temporal_aggregate(agg, input);
-        }
-
-        // `GROUPING SETS`/`ROLLUP`/`CUBE` emit several grouping levels from one
-        // scan. `Aggregate.by` is a single key set, so each level becomes its own
-        // `Aggregate` and they are merged (issue #118).
-        if let Some(gs) = agg.group_expr.iter().find_map(as_grouping_set) {
-            if measure_filters.iter().any(Option::is_some) {
-                return Err(LoweringError::UnsupportedFeature(
-                    "FILTER on a measure inside a multi-level grouping".into(),
-                ));
-            }
-            return self.lower_grouping_sets(agg, gs, input);
-        }
-
-        // `Aggregate.by` and the reducers index *columns*, so a grouping or
-        // reducer expression (`GROUP BY date_trunc(…)`, `SUM(a * 8)`) has no
-        // slot. Materialize each one as a derived column in a `Project` beneath
-        // the aggregate, then group/reduce over that column (issue #110).
-        let mut derived = DerivedCols::new(self);
-
-        // DataFusion strips `AS m` from a grouping expression, so the aggregate
-        // schema's field name is what the enclosing Projection references —
-        // the derived column has to carry exactly that name.
-        let group_names: Vec<String> = agg
-            .schema
-            .fields()
-            .iter()
-            .take(agg.group_expr.len())
-            .map(|f| f.name().to_string())
-            .collect();
-
-        let mut keys = Vec::with_capacity(agg.group_expr.len());
-        for (i, e) in agg.group_expr.iter().enumerate() {
-            match unalias(e) {
-                Expr::Column(_) => {
-                    derived.passthrough(e)?;
-                    keys.push(expr_to_group_ref(e)?);
-                }
-                other => {
-                    let name = group_names
-                        .get(i)
-                        .cloned()
-                        .unwrap_or_else(|| other.to_string());
-                    derived.materialize(name.clone(), self.lower_expr(other)?)?;
-                    keys.push(ColumnRef::Named(name));
-                }
-            }
-        }
-
-        // Reducer arguments get the same treatment; `rewrite_agg` returns the
-        // aggregate with its argument repointed at the derived column.
-        let aggr_expr = agg
-            .aggr_expr
-            .iter()
-            .map(|e| derived.rewrite_agg(e))
-            .collect::<Result<Vec<_>, LoweringError>>()?;
-        // A measure filter reads the aggregate's input rows, so the columns
-        // it names must survive any derived-column `Project` inserted below.
-        for column in measure_filters.iter().flatten().flat_map(Expr::column_refs) {
-            derived.passthrough(&Expr::Column(column.clone()))?;
-        }
-
-        let child = Rc::new(derived.wrap(input)?);
-        // DataFusion names the aggregate outputs in its own schema (e.g.
-        // "sum(metrics.bytes)") — the same names the enclosing Projection
-        // references. The schema is [group fields …, aggregate fields …], so
-        // skip the group fields and thread the rest straight through as
-        // `Aggregate.output_names`, letting that Projection resolve them.
-        let output_names: Vec<String> = agg
-            .schema
-            .fields()
-            .iter()
-            .skip(agg.group_expr.len())
-            .map(|f| f.name().to_string())
-            .collect();
-        let measures = aggr_expr
-            .iter()
-            .map(lower_agg_intent)
-            .collect::<Result<Vec<_>, LoweringError>>()?;
-        // Empty when nothing is filtered — the one canonical unfiltered shape.
-        let filters = if measure_filters.iter().any(Option::is_some) {
-            measure_filters
-                .iter()
-                .map(|f| {
-                    f.as_ref()
-                        .map(|f| Ok(Predicate(self.lower_expr(f)?)))
-                        .transpose()
-                })
-                .collect::<Result<Vec<_>, LoweringError>>()?
-        } else {
-            Vec::new()
-        };
-        Ok(Unresolved::Aggregate {
-            // SQL `GROUP BY` is always an inclusion list, never PromQL's
-            // `without(...)` exclusion form — and always a genuine reduction,
-            // never `PerEntity` (there's no windowed/subquery-child concept
-            // in SQL for that to apply to).
-            reduction: Reduction::Reduce(GroupKeys::by(keys)),
-            measures,
-            output_names,
-            filters,
-            having: None,
-            child,
-        })
-    }
-
-    fn lower_temporal_aggregate(
-        &self,
-        agg: &logical_expr::Aggregate,
-        input: Unresolved,
-    ) -> Result<Unresolved, LoweringError> {
-        if agg.aggr_expr.len() != 1 {
-            return Err(LoweringError::UnsupportedFeature(
-                "an ASAP temporal aggregate cannot share an Aggregate node with another reducer"
-                    .into(),
-            ));
-        }
-        let Expr::AggregateFunction(call) = unalias(&agg.aggr_expr[0]) else {
-            unreachable!("is_temporal_aggregate accepted a non-aggregate expression")
-        };
-        let name = call.func.name().to_lowercase();
-        let [value, timestamp, window] = call.params.args.as_slice() else {
-            unreachable!("ASAP temporal UDAF signatures require exactly three arguments")
-        };
-
-        let value_ref = reducer_col(&name, std::slice::from_ref(value))?;
-        let timestamp_ref = reducer_col(&name, std::slice::from_ref(timestamp))?;
-        let Expr::Literal(window, _) = unalias(window) else {
-            return Err(LoweringError::InvalidExpression(format!(
-                "{name} window_ms must be a positive integer literal"
-            )));
-        };
-        let window_ms = scalar_positive_u64(window).ok_or_else(|| {
-            LoweringError::InvalidExpression(format!(
-                "{name} window_ms must be a positive integer literal"
-            ))
-        })?;
-
-        let input_schema = resolve_root(&input)?.schema.clone();
-        let timestamp_id = resolve_column_ref(&timestamp_ref, &input_schema).map_err(|error| {
-            LoweringError::InvalidExpression(format!("{name} timestamp argument: {error}"))
-        })?;
-        if input_schema.time_index != Some(timestamp_id) {
-            return Err(LoweringError::InvalidExpression(format!(
-                "{name} timestamp argument must name the input schema's time-index column"
-            )));
-        }
-        let value_id = resolve_column_ref(&value_ref, &input_schema).map_err(|error| {
-            LoweringError::InvalidExpression(format!("{name} value argument: {error}"))
-        })?;
-        if value_id == timestamp_id
-            || !matches!(
-                input_schema.fields[value_id].dtype,
-                FieldDataType::Plain(DataType::Int64 | DataType::Float64)
-            )
-        {
-            return Err(LoweringError::InvalidExpression(format!(
-                "{name} value argument must name a numeric non-time column"
-            )));
-        }
-
-        let mut group_ids = Vec::with_capacity(agg.group_expr.len());
-        let mut group_refs = Vec::with_capacity(agg.group_expr.len());
-        for group in &agg.group_expr {
-            let group_ref = expr_to_group_ref(group)?;
-            let group_id = resolve_column_ref(&group_ref, &input_schema).map_err(|error| {
-                LoweringError::InvalidExpression(format!("{name} GROUP BY column: {error}"))
-            })?;
-            if group_id == timestamp_id || group_id == value_id {
-                return Err(LoweringError::InvalidExpression(format!(
-                    "{name} GROUP BY cannot contain its timestamp or value column"
-                )));
-            }
-            if group_ids.contains(&group_id) {
-                return Err(LoweringError::InvalidExpression(format!(
-                    "{name} GROUP BY contains the same resolved column more than once"
-                )));
-            }
-            group_ids.push(group_id);
-            group_refs.push(group_ref);
-        }
-        // Minimal series-identity contract without adding SQL-only metadata to
-        // the shared Schema: a declared row-unique key must contain the time
-        // index, and removing that index yields the complete series key. The
-        // GROUP BY must match that key exactly. A unique key that omits time is
-        // only row identity and proves nothing about time-series continuity.
-        let identifies_one_series = input_schema
-            .unique_keys
-            .iter()
-            .filter(|key| key.contains(&timestamp_id))
-            .any(|key| {
-                let mut series_key: Vec<_> = key
-                    .iter()
-                    .copied()
-                    .filter(|id| *id != timestamp_id)
-                    .collect();
-                series_key.sort_unstable();
-                series_key.dedup();
-                let mut grouped = group_ids.clone();
-                grouped.sort_unstable();
-                series_key == grouped
-            });
-        if !identifies_one_series {
-            return Err(LoweringError::InvalidExpression(format!(
-                "{name} GROUP BY must exactly match a declared series identity (a unique key without the time index)"
-            )));
-        }
-
-        let mut cols = vec![
-            ProjectItem {
-                alias: Some("ts".into()),
-                expr: Scalar::Column(timestamp_ref.clone()),
-            },
-            ProjectItem {
-                alias: Some("value".into()),
-                expr: Scalar::Column(value_ref.clone()),
-            },
-        ];
-        for group_ref in group_refs {
-            let group_name = named_ref(&group_ref).to_string();
-            cols.push(ProjectItem {
-                alias: Some(group_name),
-                expr: Scalar::Column(group_ref),
-            });
-        }
-        let child = Unresolved::Project {
-            cols,
-            qualifier: None,
-            child: Rc::new(input),
-        };
-        // The explicit window is a range selector over the series, the same
-        // shape PromQL's `rate(m[5m])` lowers to.
-        let child = Unresolved::TimeRange {
-            range: Duration::from_millis(window_ms),
-            kind: TimeRangeKind::Range,
-            child: Rc::new(child),
-        };
-        let intent = match name.as_str() {
-            "asap_rate" => AggIntent::Rate,
-            "asap_increase" => AggIntent::Increase,
-
-            _ => unreachable!("is_temporal_aggregate admitted {name}"),
-        };
-        Ok(Unresolved::Aggregate {
-            reduction: Reduction::PerEntity,
-            measures: vec![intent],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(child),
-        })
-    }
-
-    /// `GROUP BY ROLLUP/CUBE/GROUPING SETS` — multi-level grouping (issue #118).
-    ///
-    /// One scan produces several grouping levels; `Aggregate.by` holds a single
-    /// key set. So each level becomes its own `Aggregate`, and the levels are
-    /// `Concat`ed. A level that omits a key still has to *emit* it — as `NULL`, per
-    /// SQL — so each branch is wrapped in a `Project` that reinstates the missing
-    /// keys as typed nulls and restores the canonical column order. That keeps
-    /// the branches union-compatible, which `Concat` requires (it derives its
-    /// schema from the first child).
-    ///
-    /// `Aggregate.child` is duplicated per level — the same trade
-    /// `histogram_quantiles` makes (#109); a future workload-level reuse pass
-    /// could hoist it back into a single producer.
-    ///
-    /// DataFusion's `__grouping_id` discriminator is dropped: it only exists to
-    /// tell a subtotal's `NULL` apart from a data `NULL`, which is observable
-    /// solely through `GROUPING(col)` — an aggregate this front end rejects.
-    fn lower_grouping_sets(
-        &self,
-        agg: &logical_expr::Aggregate,
-        gs: &logical_expr::GroupingSet,
-        input: Unresolved,
-    ) -> Result<Unresolved, LoweringError> {
-        // DataFusion normalizes every mixed form (`GROUP BY g, ROLLUP(d)`) into a
-        // single `GroupingSets`, so one grouping expression is the only shape.
-        if agg.group_expr.len() != 1 {
-            return Err(LoweringError::UnsupportedFeature(
-                "a grouping set alongside plain GROUP BY keys".into(),
-            ));
-        }
-
-        // `distinct_expr()` is ordered exactly like the aggregate's leading
-        // schema fields, which is the column order the enclosing Projection
-        // expects. The field after them is `__grouping_id`.
-        let distinct = gs.distinct_expr();
-        for e in &distinct {
-            if !matches!(unalias(e), Expr::Column(_)) {
-                return Err(LoweringError::UnsupportedFeature(format!(
-                    "non-column key inside a multi-level grouping: {e}"
-                )));
-            }
-        }
-        let keys: Vec<(String, DataType)> = agg
-            .schema
-            .fields()
-            .iter()
-            .take(distinct.len())
-            .map(|f| Ok((f.name().to_string(), arrow_to_dtype(f.data_type())?)))
-            .collect::<Result<_, LoweringError>>()?;
-
-        let output_names: Vec<String> = agg
-            .schema
-            .fields()
-            .iter()
-            .skip(distinct.len() + 1) // + `__grouping_id`
-            .map(|f| f.name().to_string())
-            .collect();
-
-        // Reducer arguments still materialize as derived columns (#110); the
-        // grouping keys are plain columns, so they only need carrying through.
-        let mut derived = DerivedCols::new(self);
-        for e in &distinct {
-            derived.passthrough(e)?;
-        }
-        let aggr_expr = agg
-            .aggr_expr
-            .iter()
-            .map(|e| derived.rewrite_agg(e))
-            .collect::<Result<Vec<_>, LoweringError>>()?;
-        let measures = aggr_expr
-            .iter()
-            .map(lower_agg_intent)
-            .collect::<Result<Vec<_>, LoweringError>>()?;
-        let input = derived.wrap(input)?;
-
-        let branches = expand_grouping_set(gs)
-            .iter()
-            .map(|level| {
-                let level_keys = distinct
-                    .iter()
-                    .filter(|e| level.contains(e))
-                    .map(|e| expr_to_group_ref(e))
-                    .collect::<Result<Vec<_>, LoweringError>>()?;
-                let aggregate = Unresolved::Aggregate {
-                    reduction: Reduction::Reduce(GroupKeys::by(level_keys)),
-                    measures: measures.clone(),
-                    output_names: output_names.clone(),
-                    filters: vec![],
-                    having: None,
-                    child: Rc::new(input.clone()),
-                };
-                // Reinstate omitted keys as typed nulls, in canonical order.
-                let cols = keys
-                    .iter()
-                    .zip(&distinct)
-                    .map(|((name, dtype), e)| ProjectItem {
-                        alias: Some(name.clone()),
-                        expr: if level.contains(e) {
-                            Scalar::Column(ColumnRef::Named(name.clone()))
-                        } else {
-                            Scalar::Cast {
-                                expr: Box::new(Scalar::Literal(ScalarValue::Null)),
-                                to: dtype.clone(),
-                                try_cast: false,
-                            }
-                        },
-                    })
-                    .chain(output_names.iter().map(|n| ProjectItem {
-                        alias: Some(n.clone()),
-                        expr: Scalar::Column(ColumnRef::Named(n.clone())),
-                    }))
-                    .collect();
-                Ok(Unresolved::Project {
-                    cols,
-                    qualifier: None,
-                    child: Rc::new(aggregate),
-                })
-            })
-            .collect::<Result<Vec<_>, LoweringError>>()?;
-
-        // No discriminator asserted here today (issue #228): DataFusion's own
-        // `__grouping_id` would be the natural one, but this front end
-        // already discards it (see above — `GROUPING()` itself is rejected),
-        // so there is no distinct-per-branch column available to name yet.
-        // `Unresolved::concat` keeps `output_schema`'s default (drop
-        // `unique_keys` entirely). See
-        // `docs/design_docs/concat-unique-keys-decision.md`.
-        Ok(Unresolved::concat(branches))
-    }
-
-    fn lower_sort(&self, sort: &logical_expr::Sort) -> Result<Unresolved, LoweringError> {
-        // A count-ranked `ORDER BY … LIMIT k` is the frequency heavy-hitter the
-        // `TopK` intent represents, but that promotion now happens in the shared
-        // `canonicalize` pass (issue #34) — the same one both front ends run —
-        // so SQL emits a plain `Sort` (+ `Limit`) here and lets canonicalization
-        // recognise the count-ranked shape positionally. This removes the gate's
-        // alias blind spot (#20).
-        let keys = sort
-            .expr
-            .iter()
-            .map(|s| {
-                self.lower_expr(&s.expr).map(|expr| SortKey {
-                    expr,
-                    ascending: s.asc,
-                    nulls_first: s.nulls_first,
-                })
-            })
-            .collect::<Result<Vec<_>, _>>()?;
-        Ok(Unresolved::Sort {
-            keys,
-            // SQL `ORDER BY` is a global sort; per-group ranking would come from a
-            // window function (`SQLWindowFunc`), not a bare Sort.
-            partition_by: GroupKeys::none(),
-            child: Rc::new(self.lower_plan(&sort.input)?),
-        })
-    }
-
-    fn lower_limit(&self, limit: &logical_expr::Limit) -> Result<Unresolved, LoweringError> {
-        // Count-ranked `LIMIT k` over a `Sort` is promoted to the heavy-hitter
-        // `TopK` by the shared `canonicalize` pass (issue #34), not here.
-        Ok(Unresolved::Limit {
-            // No (literal) fetch is offset-only.
-            n: eval_fetch(&limit.fetch),
-            offset: eval_fetch(&limit.skip).unwrap_or(0),
-            partition_by: GroupKeys::none(),
-            child: Rc::new(self.lower_plan(&limit.input)?),
-        })
-    }
-}
-
-/// A deliberately explicit marker accepted only in a projection of planning
-/// SQL. The marker describes a relation operator, so it is removed rather than
-/// lowered to the ordinary scalar `FunctionCall` variant.
-enum PlanningBridge {
-    PromqlSubquery {
-        range: Duration,
-        resolution: Duration,
-    },
-    HistogramQuantile {
-        q: f64,
-    },
-}
-
-fn planning_bridge(
-    projection: &logical_expr::Projection,
-) -> Result<Option<PlanningBridge>, LoweringError> {
-    let mut found = None;
-    for expr in &projection.expr {
-        let Expr::ScalarFunction(call) = unalias(expr) else {
-            continue;
-        };
-        let name = call.func.name().to_ascii_lowercase();
-        let bridge = match name.as_str() {
-            "asap_promql_subquery" => {
-                let [range, resolution] = call.args.as_slice() else {
-                    return Err(LoweringError::InvalidExpression(
-                        "asap_promql_subquery requires (range_ms, resolution_ms)".into(),
-                    ));
-                };
-                let range = positive_millis_literal(range, "range_ms")?;
-                let resolution = positive_millis_literal(resolution, "resolution_ms")?;
-                PlanningBridge::PromqlSubquery { range, resolution }
-            }
-            "asap_histogram_quantile" => {
-                let [q] = call.args.as_slice() else {
-                    return Err(LoweringError::InvalidExpression(
-                        "asap_histogram_quantile requires one literal quantile".into(),
-                    ));
-                };
-                let q = float_literal(q).ok_or_else(|| {
-                    LoweringError::InvalidExpression(
-                        "asap_histogram_quantile quantile must be a numeric literal".into(),
-                    )
-                })?;
-                if !q.is_finite() || !(0.0..=1.0).contains(&q) {
-                    return Err(LoweringError::InvalidExpression(format!(
-                        "asap_histogram_quantile quantile must be finite and in [0,1], got {q}"
-                    )));
-                }
-                PlanningBridge::HistogramQuantile { q }
-            }
-            _ => continue,
-        };
-        if found.is_some() {
-            return Err(LoweringError::InvalidExpression(
-                "a planning projection may contain only one asap_* relation marker".into(),
-            ));
-        }
-        found = Some(bridge);
-    }
-    if matches!(found, Some(PlanningBridge::HistogramQuantile { .. })) && projection.expr.len() != 1
-    {
-        return Err(LoweringError::InvalidExpression(
-            "asap_histogram_quantile must be the projection's only expression".into(),
-        ));
-    }
-    Ok(found)
-}
-
-/// Rebuild the SQL projection around the relation sampled by the temporal
-/// marker. The marker's alias names the existing child column that occupies
-/// its output slot (`... asap_promql_subquery(...) AS value ...`). This makes
-/// the bridge schema-preserving without silently retaining columns that SQL
-/// projected away.
-impl SqlLowerer<'_> {
-    fn temporal_bridge_projection(
-        &self,
-        projection: &logical_expr::Projection,
-        child: Unresolved,
-    ) -> Result<Unresolved, LoweringError> {
-        let cols = projection
-            .expr
-            .iter()
-            .map(|expr| {
-                if let Expr::ScalarFunction(call) = unalias(expr) {
-                    if call
-                        .func
-                        .name()
-                        .eq_ignore_ascii_case("asap_promql_subquery")
-                    {
-                        let Expr::Alias(alias) = expr else {
-                            return Err(LoweringError::InvalidExpression(
-                                "asap_promql_subquery must have an alias naming its child value column"
-                                    .into(),
-                            ));
-                        };
-                        return Ok(ProjectItem {
-                            expr: Scalar::Column(ColumnRef::Named(alias.name.clone())),
-                            alias: Some(alias.name.clone()),
-                        });
-                    }
-                }
-                match expr {
-                    Expr::Alias(alias) => Ok(ProjectItem {
-                        expr: self.lower_expr(&alias.expr)?,
-                        alias: Some(alias.name.clone()),
-                    }),
-                    other => Ok(ProjectItem {
-                        expr: self.lower_expr(other)?,
-                        alias: None,
-                    }),
-                }
-            })
-            .collect::<Result<Vec<_>, LoweringError>>()?;
-        Ok(Unresolved::Project {
-            cols,
-            qualifier: None,
-            child: Rc::new(child),
-        })
-    }
-}
-
-fn positive_millis_literal(expr: &Expr, argument: &str) -> Result<Duration, LoweringError> {
-    let millis = match unalias(expr) {
-        Expr::Literal(DfScalarValue::Int64(Some(value)), _) if *value > 0 => *value as u64,
-        Expr::Literal(DfScalarValue::UInt64(Some(value)), _) if *value > 0 => *value,
-        Expr::Literal(DfScalarValue::Int32(Some(value)), _) if *value > 0 => *value as u64,
-        other => {
-            return Err(LoweringError::InvalidExpression(format!(
-                "{argument} must be a positive integer millisecond literal, got {other}"
-            )))
-        }
-    };
-    Ok(Duration::from_millis(millis))
-}
-
-fn float_literal(expr: &Expr) -> Option<f64> {
-    match unalias(expr) {
-        Expr::Literal(DfScalarValue::Float64(Some(value)), _) => Some(*value),
-        Expr::Literal(DfScalarValue::Float32(Some(value)), _) => Some(*value as f64),
-        Expr::Literal(DfScalarValue::Int64(Some(value)), _) => Some(*value as f64),
-        Expr::Literal(DfScalarValue::UInt64(Some(value)), _) => Some(*value as f64),
-        Expr::Literal(DfScalarValue::Int32(Some(value)), _) => Some(*value as f64),
-        _ => None,
-    }
-}
-
-// ── ClickHouse-builtin compatibility, taught to DataFusion itself ──────────────
-//
-// Generalized over `asap_sql_function_catalog::CLICKHOUSE_BUILTINS` (issue
-// #225): adding support for one more ClickHouse-only builtin DataFusion
-// doesn't know at all is a catalog data entry (name, arity, `RewriteKind`)
-// plus, only if its rewrite target is a genuinely new shape, one match arm
-// in `ClickHouseBuiltinRewrite::rewrite` below — never a new stub-UDAF
-// constructor or a new `FunctionRewrite`-implementing type. `uniqExact`
-// (issue #221) and `countIf` both go through this one mechanism.
-
-/// A stub `AggregateUDF` for one `CLICKHOUSE_BUILTINS` entry, registered
-/// purely so DataFusion's planner can resolve the function name during
-/// `SqlToRel` conversion (it errors on an unknown function before a rewrite
-/// ever gets a chance to run). Every call site is replaced by
-/// `ClickHouseBuiltinRewrite` — via the `Analyzer` `lower()` runs after
-/// parsing — before physical planning could ever ask this UDAF for an
-/// `Accumulator`, so `accumulator` is unreachable for every catalog entry.
-fn clickhouse_builtin_stub_udaf(name: &'static str, arity: Arity) -> AggregateUDF {
-    AggregateUDF::from(SimpleAggregateUDF::new_with_signature(
-        name,
-        arity_to_signature(arity),
-        ArrowDataType::Int64,
-        Arc::new(move |_| {
-            // ponytail: dead code by construction (see doc comment above) —
-            // a real accumulator would just reimplement whatever native
-            // shape `ClickHouseBuiltinRewrite` rewrites this call to.
-            unimplemented!(
-                "{name} has no accumulator: every call site is rewritten to a native \
-                 DataFusion aggregate before physical planning"
-            )
-        }),
-        vec![],
-    ))
-}
-
-/// A catalog [`Arity`] as the DataFusion `Signature` a stub UDAF/UDF is
-/// registered with — shared by the aggregate stub above and the scalar stub
-/// below, since neither wants to model per-argument types, only how many
-/// arguments a call may take.
-fn arity_to_signature(arity: Arity) -> Signature {
-    match arity {
-        Arity::Exact(n) => Signature::any(n, Volatility::Immutable),
-        Arity::Range { min, max } => Signature::one_of(
-            (min..=max).map(TypeSignature::Any).collect(),
-            Volatility::Immutable,
-        ),
-    }
-}
-
-// ── ClickHouse scalar-builtin compatibility ─────────────────────────────────
-//
-// The scalar counterpart of the aggregate mechanism above, but simpler:
-// `asap_sql_function_catalog::CLICKHOUSE_SCALAR_BUILTINS` carries no
-// `RewriteKind`, because a scalar call needs none. Unlike an aggregate call
-// (which must become a real `AggIntent`, hence the rewrite to a native
-// DataFusion aggregate shape `lower_agg_intent` can classify), a scalar
-// function call in this IR is already deliberately opaque —
-// `SqlLowerer::lower_expr`'s `Expr::ScalarFunction` arm lowers *any*
-// scalar call generically to `UnresolvedScalar::FunctionCall { name, args }`, with
-// zero name-specific logic. So teaching DataFusion's planner to accept a
-// ClickHouse scalar builtin's name — a stub `ScalarUDF`, registered below —
-// is the entire fix; the existing generic lowering already does the rest.
-
-/// A stub `ScalarUDF` for one `CLICKHOUSE_SCALAR_BUILTINS` entry, registered
-/// purely so DataFusion's planner can resolve the function name during
-/// `SqlToRel` conversion (it errors on an unknown function otherwise), and so
-/// it can keep building the surrounding expression's type from a plausible
-/// return type. Unlike `clickhouse_builtin_stub_udaf`, no `FunctionRewrite`
-/// ever fires for these — the call survives to `lower_plan` as-is and lowers
-/// through the generic `Expr::ScalarFunction` arm — so `invoke`/`invoke_batch`
-/// (left at their default, which returns a `NotImplemented` `DataFusionError`)
-/// are unreachable for every catalog entry: this front end only ever uses
-/// DataFusion for planning/type-checking, never physical execution.
-fn clickhouse_scalar_builtin_stub_udf(name: &'static str, arity: Arity) -> ScalarUDF {
-    ScalarUDF::from(ClickHouseScalarBuiltinStub {
-        name,
-        signature: arity_to_signature(arity),
-        return_type: clickhouse_scalar_builtin_return_type(name),
-    })
-}
-
-/// A plausible Arrow return type for one `CLICKHOUSE_SCALAR_BUILTINS` entry —
-/// just precise enough that DataFusion's planner can keep building the type
-/// of whatever expression the call sits inside (e.g. a `WHERE` predicate
-/// wants `Boolean`), not a claim about ClickHouse's actual return type.
-/// Real function typing happens downstream, at post-ASAP binding.
-fn clickhouse_scalar_builtin_return_type(name: &str) -> ArrowDataType {
-    match name {
-        // Array(String) in ClickHouse; a plain `Utf8` element list is close
-        // enough for planning purposes here.
-        "splitbychar" => ArrowDataType::List(Arc::new(datafusion::arrow::datatypes::Field::new(
-            "item",
-            ArrowDataType::Utf8,
-            true,
-        ))),
-        "todate" => ArrowDataType::Date32,
-        // ClickHouse returns UInt8 (0/1), but every corpus use is a boolean
-        // predicate — `Boolean` keeps that context type-checking.
-        "match" | "startswith" => ArrowDataType::Boolean,
-        "tostartofhour"
-        | "tostartofweek"
-        | "tostartofminute"
-        | "tostartoffiveminutes"
-        | "tostartofinterval" => {
-            ArrowDataType::Timestamp(datafusion::arrow::datatypes::TimeUnit::Millisecond, None)
-        }
-        // 1-based match position, 0 if not found.
-        "positioncaseinsensitive" => ArrowDataType::UInt64,
-        // Relation markers are removed by `lower_projection`; Float64 merely
-        // lets DataFusion type the temporary SELECT list.
-        "asap_promql_subquery" | "asap_histogram_quantile" => ArrowDataType::Float64,
-        other => unreachable!(
-            "{other}: every CLICKHOUSE_SCALAR_BUILTINS entry must have a return type listed here"
-        ),
-    }
-}
-
-/// A stub `ScalarUDFImpl` carrying only what DataFusion's planner needs:
-/// name, arity-only [`Signature`], and a fixed return type. `invoke_with_args`
-/// returns a `NotImplemented` `DataFusionError` — see
-/// [`clickhouse_scalar_builtin_stub_udf`]'s doc for why that is unreachable in
-/// practice.
-#[derive(Debug, PartialEq, Eq, Hash)]
-struct ClickHouseScalarBuiltinStub {
-    name: &'static str,
-    signature: Signature,
-    return_type: ArrowDataType,
-}
-
-impl ScalarUDFImpl for ClickHouseScalarBuiltinStub {
-    fn name(&self) -> &str {
-        self.name
-    }
-
-    fn signature(&self) -> &Signature {
-        &self.signature
-    }
-
-    fn return_type(
-        &self,
-        _arg_types: &[ArrowDataType],
-    ) -> datafusion::common::Result<ArrowDataType> {
-        Ok(self.return_type.clone())
-    }
-
-    fn invoke_with_args(
-        &self,
-        _args: ScalarFunctionArgs,
-    ) -> datafusion::common::Result<ColumnarValue> {
-        Err(datafusion::common::DataFusionError::NotImplemented(
-            format!("{} is a planning-only stub", self.name),
-        ))
-    }
-}
-
-// ── ClickHouse window-builtin compatibility ─────────────────────────────────
-//
-// The window counterpart of the scalar mechanism above: a stub `WindowUDF`
-// registered purely so DataFusion's planner accepts the call name during
-// `SqlToRel` conversion. No rewrite step follows — `lower_window_func_kind`
-// already maps each `asap_sql_function_catalog::CLICKHOUSE_WINDOW_BUILTINS`
-// name directly to its own `WindowFuncKind` variant (issue #267).
-
-/// A stub `WindowUDF` for one `CLICKHOUSE_WINDOW_BUILTINS` entry, registered
-/// purely so DataFusion's planner can resolve the function name inside an
-/// `OVER (...)` clause. This front end only ever uses DataFusion for
-/// planning/type-checking, never physical execution, so
-/// `partition_evaluator` (which physical execution alone would call) is
-/// unreachable in practice.
-fn clickhouse_window_builtin_stub_udwf(name: &'static str, arity: Arity) -> WindowUDF {
-    WindowUDF::from(ClickHouseWindowBuiltinStub {
-        name,
-        signature: arity_to_signature(arity),
-    })
-}
-
-/// A stub `WindowUDFImpl` carrying only what DataFusion's planner needs:
-/// name, arity-only [`Signature`], and a field type derived from the first
-/// argument (matching `lag`/`lead`'s own "output type = input type"
-/// behavior). `partition_evaluator` is left `unimplemented!()` — see
-/// [`clickhouse_window_builtin_stub_udwf`]'s doc for why that is unreachable.
-#[derive(Debug, PartialEq, Eq, Hash)]
-struct ClickHouseWindowBuiltinStub {
-    name: &'static str,
-    signature: Signature,
-}
-
-impl WindowUDFImpl for ClickHouseWindowBuiltinStub {
-    fn name(&self) -> &str {
-        self.name
-    }
-
-    fn signature(&self) -> &Signature {
-        &self.signature
-    }
-
-    fn field(&self, field_args: WindowUDFFieldArgs) -> datafusion::common::Result<FieldRef> {
-        let dtype = field_args
-            .get_input_field(0)
-            .map_or(ArrowDataType::Null, |field| field.data_type().clone());
-        Ok(Arc::new(Field::new(field_args.name(), dtype, true)))
-    }
-
-    fn partition_evaluator(
-        &self,
-        _partition_evaluator_args: PartitionEvaluatorArgs,
-    ) -> datafusion::common::Result<Box<dyn PartitionEvaluator>> {
-        let name = self.name;
-        unimplemented!(
-            "{name} has no partition evaluator: this front end never runs DataFusion's \
-             physical planner, only SqlToRel + the unoptimized LogicalPlan"
-        )
-    }
-}
-
-/// Rewrites every `asap_sql_function_catalog::CLICKHOUSE_BUILTINS` call to
-/// the native DataFusion aggregate shape its entry's `RewriteKind` names —
-/// so a ClickHouse-only builtin DataFusion doesn't know at all becomes an
-/// ordinary DataFusion aggregate before the plan ever reaches
-/// `lower_agg_intent`, which needs no ClickHouse-specific name of its own.
-#[derive(Debug)]
-struct ClickHouseBuiltinRewrite;
-
-impl FunctionRewrite for ClickHouseBuiltinRewrite {
-    fn name(&self) -> &str {
-        "clickhouse builtin -> native DataFusion aggregate"
-    }
-
-    fn rewrite(
-        &self,
-        expr: Expr,
-        _schema: &DFSchema,
-        _config: &ConfigOptions,
-    ) -> datafusion::common::Result<Transformed<Expr>> {
-        let Expr::AggregateFunction(f) = expr else {
-            return Ok(Transformed::no(expr));
-        };
-        let Some(builtin) = asap_sql_function_catalog::lookup_clickhouse_builtin(f.func.name())
-        else {
-            return Ok(Transformed::no(Expr::AggregateFunction(f)));
-        };
-        let rewritten = match builtin.rewrite {
-            // No native DataFusion shape to become — leave the call exactly
-            // as DataFusion's planner parsed it. `lower_agg_intent` handles
-            // the ClickHouse name (`argMax`/`argMin`) directly (issue #232).
-            RewriteKind::PassThrough => return Ok(Transformed::no(Expr::AggregateFunction(f))),
-            // `f(args...)` -> `count(args...) DISTINCT` — `lower_agg_intent`
-            // already maps `count` + `DISTINCT` to `AggIntent::Cardinality`,
-            // at whatever arity the call carries.
-            RewriteKind::CountDistinct => AggregateFunction::new_udf(
-                count_udaf(),
-                f.params.args,
-                true,
-                f.params.filter,
-                f.params.order_by,
-                f.params.null_treatment,
-            ),
-            // `f(cond)` -> `sum(CASE WHEN cond THEN 1 ELSE 0 END)` — see
-            // `RewriteKind::CountIfToSum`'s doc; moving the `-If` family onto
-            // `Aggregate.filters` (issue #466) is a follow-up.
-            RewriteKind::CountIfToSum => {
-                let cond = f.params.args.into_iter().next().expect(
-                    "countif's stub signature fixes its arity at 1 -- the planner \
-                     already rejected any other argument count before this rewrite runs",
-                );
-                let indicator = Expr::Case(Case::new(
-                    None,
-                    vec![(Box::new(cond), Box::new(lit(1i64)))],
-                    Some(Box::new(lit(0i64))),
-                ));
-                AggregateFunction::new_udf(
-                    sum_udaf(),
-                    vec![indicator],
-                    false,
-                    f.params.filter,
-                    f.params.order_by,
-                    f.params.null_treatment,
-                )
-            }
-        };
-        Ok(Transformed::yes(Expr::AggregateFunction(rewritten)))
-    }
-}
-
-// ── Aggregate / group-key helpers ───────────────────────────────────────────────
-
-/// The row predicate one aggregate call carries (issue #466): its explicit
-/// `FILTER (WHERE p)`, plus — for a plain `count(expr)`, which canonical
-/// `AggIntent::Count` lowers to a row count that never looks at `expr` — the
-/// NULL-skipping SQL gives it. `count(CASE WHEN p THEN x END)` is the
-/// conditional-count idiom, so it becomes `p [AND x IS NOT NULL]` rather
-/// than the opaque `CASE … IS NOT NULL`; any other nullable argument becomes
-/// `expr IS NOT NULL`. `None` when the call updates on every row.
-fn measure_filter(expr: &Expr, input: &DFSchema) -> Result<Option<Expr>, LoweringError> {
-    let Expr::AggregateFunction(agg_fn) = unalias(expr) else {
-        return Ok(None);
-    };
-    let mut conjuncts: Vec<Expr> = agg_fn.params.filter.iter().map(|f| (**f).clone()).collect();
-    let counts_rows = agg_fn.func.name().eq_ignore_ascii_case("count") && !agg_fn.params.distinct;
-    if counts_rows {
-        for argument in &agg_fn.params.args {
-            let nullable = argument
-                .nullable(input)
-                .map_err(|error| LoweringError::UnsupportedFeature(error.to_string()))?;
-            if !nullable {
-                continue;
-            }
-            match conditional_count_arm(argument) {
-                Some((when, then)) => {
-                    conjuncts.push(when.clone());
-                    if then
-                        .nullable(input)
-                        .map_err(|error| LoweringError::UnsupportedFeature(error.to_string()))?
-                    {
-                        conjuncts.push(then.clone().is_not_null());
-                    }
-                }
-                None => conjuncts.push(argument.clone().is_not_null()),
-            }
-        }
-    }
-    Ok(conjuncts.into_iter().reduce(Expr::and))
-}
-
-/// `CASE WHEN p THEN x END` (searched, one arm, no `ELSE` or `ELSE NULL`)
-/// as `(p, x)`.
-fn conditional_count_arm(expr: &Expr) -> Option<(&Expr, &Expr)> {
-    let Expr::Case(case) = unalias(expr) else {
-        return None;
-    };
-    if case.expr.is_some() {
-        return None;
-    }
-    let else_is_null = match case.else_expr.as_deref() {
-        None => true,
-        Some(Expr::Literal(value, _)) => value.is_null(),
-        Some(_) => false,
-    };
-    if !else_is_null {
-        return None;
-    }
-    let [(when, then)] = case.when_then_expr.as_slice() else {
-        return None;
-    };
-    Some((when, then))
-}
-
-/// Map a DataFusion aggregate expression directly to the canonical
-/// [`AggIntent<ColumnRef>`] — issue #179's "dedicated function → canonical
-/// intent directly" front-end construction, no `AggFunc` intermediate. The
-/// name → semantic mapping itself lives in `asap_sql_function_catalog`
-/// (issue #225) as flat data (`NATIVE_FUNCTIONS`); what stays here is
-/// call-site logic that isn't a function of the name alone — the DISTINCT
-/// modifier rule, the "reducer argument must be a bare column" rule
-/// (`reducer_col`), φ extraction from a literal argument, and the ambient
-/// `AccuracyTarget`. `resolve_root` resolves `col` to a positional
-/// `ColumnId`; the output name (DataFusion's own, e.g.
-/// `"sum(metrics.bytes)"`) is threaded separately as `Aggregate.output_names`,
-/// not carried here.
-fn lower_agg_intent(expr: &Expr) -> Result<AggIntent<ColumnRef>, LoweringError> {
-    match expr {
-        Expr::Alias(a) => lower_agg_intent(&a.expr),
-        Expr::AggregateFunction(agg_fn) => {
-            let name = agg_fn.func.name().to_lowercase();
-            // ClickHouse's row-selecting `argMax`/`argMin` — `RewriteKind::
-            // PassThrough` in the catalog, so the call reaches here under its
-            // own name rather than a native DataFusion aggregate. Handled
-            // before the `NATIVE_FUNCTIONS` lookup below since neither name
-            // is in that table (issue #232).
-            if let Some(intent) = lower_arg_selector(&name, &agg_fn.params.args)? {
-                return Ok(intent);
-            }
-            let semantic = asap_sql_function_catalog::lookup_native(&name)
-                .ok_or_else(|| LoweringError::UnsupportedAggregate(name.clone()))?;
-            // The canonical intent algebra has no DISTINCT modifier for the
-            // value reducers; only
-            // COUNT(DISTINCT) maps (to Cardinality). Reject DISTINCT elsewhere
-            // rather than silently lowering `SUM(DISTINCT x)` as `SUM(x)`.
-            if agg_fn.params.distinct && !matches!(semantic, AggSemantic::Count) {
-                return Err(LoweringError::UnsupportedAggregate(format!(
-                    "DISTINCT {name}"
-                )));
-            }
-            // Value reducers (`reducer_col`) require a real column — `SUM(a*b)`
-            // is rejected, not silently reduced over a probe column. Quantile
-            // and CountDistinct reduce a column too, so they take the same path:
-            // `col` is `Option<ColumnId>` once resolved, where `None` means "the
-            // PromQL sample value", which a SQL query never has. Taking an
-            // expression here would set `col: None` and silently drop it (#115).
-            let col = |args: &[Expr]| -> Result<Option<ColumnRef>, LoweringError> {
-                reducer_col(&name, args).map(Some)
-            };
-            Ok(match semantic {
-                AggSemantic::Correlation => {
-                    if !agg_fn.params.order_by.is_empty() || agg_fn.params.null_treatment.is_some()
-                    {
-                        return Err(LoweringError::UnsupportedAggregate(
-                            "corr with ORDER BY or explicit null treatment".into(),
-                        ));
-                    }
-                    let [left, right] = agg_fn.params.args.as_slice() else {
-                        return Err(LoweringError::UnsupportedAggregate(
-                            "corr requires two arguments".into(),
-                        ));
-                    };
-                    AggIntent::PearsonCorr {
-                        left: expr_to_group_ref(left)?,
-                        right: expr_to_group_ref(right)?,
-                    }
-                }
-                // Every argument reaches the intent: `COUNT(DISTINCT a, b)`
-                // counts distinct *tuples*, which is a different quantity from
-                // the distinct count of either column.
-                AggSemantic::Count if agg_fn.params.distinct => match agg_fn.params.args.as_slice()
-                {
-                    // DataFusion's planner rejects a bare `COUNT(DISTINCT)`
-                    // before lowering. Guarded anyway: an empty `cols` is the
-                    // PromQL sample-value convention, which SQL never has.
-                    [] => {
-                        return Err(LoweringError::UnsupportedAggregate(
-                            "COUNT(DISTINCT) without an argument".into(),
-                        ))
-                    }
-                    args => AggIntent::Cardinality {
-                        cols: args.iter().map(distinct_col).collect::<Result<_, _>>()?,
-                        accuracy: current_accuracy(),
-                    },
-                },
-                AggSemantic::Count => AggIntent::Count {
-                    accuracy: current_accuracy(),
-                },
-                AggSemantic::Sum => AggIntent::Sum {
-                    col: col(&agg_fn.params.args)?,
-                },
-                AggSemantic::Min => AggIntent::Min {
-                    col: col(&agg_fn.params.args)?,
-                },
-                AggSemantic::Max => AggIntent::Max {
-                    col: col(&agg_fn.params.args)?,
-                },
-                AggSemantic::Avg => AggIntent::Avg {
-                    col: col(&agg_fn.params.args)?,
-                },
-                AggSemantic::StdDev { population } => AggIntent::StdDev {
-                    col: col(&agg_fn.params.args)?,
-                    population,
-                },
-                AggSemantic::Variance { population } => AggIntent::Variance {
-                    col: col(&agg_fn.params.args)?,
-                    population,
-                },
-                // `fixed_q = Some(0.5)` is `median`/`approx_median`. As with
-                // `approx_distinct` and `approx_percentile_cont`, the
-                // `approx_` prefix does not force an approximation: the
-                // sketch-vs-exact choice is the AccuracyTarget's (see
-                // `plan::boundary`), so both spellings share one intent
-                // (#111).
-                AggSemantic::Quantile { fixed_q } => AggIntent::Quantile {
-                    col: col(&agg_fn.params.args)?,
-                    q: match fixed_q {
-                        Some(q) => q,
-                        None => extract_percentile_q(&agg_fn.params.args)?,
-                    },
-                    accuracy: current_accuracy(),
-                },
-                AggSemantic::Cardinality => AggIntent::Cardinality {
-                    cols: vec![reducer_col(&name, &agg_fn.params.args)?],
-                    accuracy: current_accuracy(),
-                },
-            })
-        }
-        _ => Err(LoweringError::UnsupportedAggregate(format!(
-            "measure is not an aggregate function call: {expr}"
-        ))),
-    }
-}
-
-fn temporal_aggregate_name(expr: &Expr) -> Option<String> {
-    let Expr::AggregateFunction(call) = unalias(expr) else {
-        return None;
-    };
-    let name = call.func.name().to_lowercase();
-    matches!(name.as_str(), "asap_rate" | "asap_increase").then_some(name)
-}
-
-fn is_temporal_aggregate(expr: &Expr) -> bool {
-    temporal_aggregate_name(expr).is_some()
-}
-
-fn is_temporal_output_column(expr: &Expr) -> bool {
-    let Expr::Column(col) = unalias(expr) else {
-        return false;
-    };
-    let name = col.name.to_lowercase();
-    ["asap_rate(", "asap_increase("]
-        .iter()
-        .any(|prefix| name.starts_with(prefix))
-}
-
-fn plan_has_temporal_aggregate(plan: &LogicalPlan) -> bool {
-    match plan {
-        LogicalPlan::Aggregate(agg) => agg.aggr_expr.iter().any(is_temporal_aggregate),
-        LogicalPlan::Filter(filter) => plan_has_temporal_aggregate(&filter.input),
-        LogicalPlan::SubqueryAlias(alias) => plan_has_temporal_aggregate(&alias.input),
-        _ => false,
-    }
-}
-
-fn named_ref(col: &ColumnRef) -> &str {
-    match col {
-        ColumnRef::Named(name) | ColumnRef::Qualified { name, .. } => name,
-        ColumnRef::SampleValue | ColumnRef::Wildcard => {
-            unreachable!("reducer_col only returns named column references")
-        }
-    }
-}
-
-fn scalar_positive_u64(value: &DfScalarValue) -> Option<u64> {
-    match value {
-        DfScalarValue::Int64(Some(v)) if *v > 0 => Some(*v as u64),
-        DfScalarValue::Int32(Some(v)) if *v > 0 => Some(*v as u64),
-        DfScalarValue::UInt64(Some(v)) if *v > 0 => Some(*v),
-        DfScalarValue::UInt32(Some(v)) if *v > 0 => Some(*v as u64),
-        _ => None,
-    }
-}
-
-/// ClickHouse's row-selecting `argMax(arg, val)` / `argMin(arg, val)` —
-/// "return `arg`'s value from the row where `val` is maximal/minimal".
-/// `Some(name)` for `"argmax"`/`"argmin"`, `None` for every other name (the
-/// caller falls through to the ordinary `NATIVE_FUNCTIONS` path).
-///
-/// Unlike every existing `AggIntent` reducer (`Sum`/`Min`/`Max`/`Avg`/…),
-/// which folds *one* column to a value derived from itself, this is a
-/// two-column, row-selecting aggregate: it returns a *different* column's
-/// value, selected by which row maximizes/minimizes a second column. No
-/// existing `AggIntent` shape fits, and — per its own doc comment's
-/// "core only grows for intents ≥2 deployment models actually use" bar —
-/// a repo-wide search (PromQL front end, the other SQL dialects, docs) found
-/// no second deployment model wanting this shape, so this lowers to
-/// `AggIntent::Extension` rather than earning a first-class `ArgMax`/`ArgMin`
-/// core variant (issue #232). Core treats `Extension` opaquely: both columns
-/// are kept only as validated bare-column names in `payload` (`reducer_col`'s
-/// same "no expression arguments" rule, issue #115) — they are **not** run
-/// through `resolve_agg_intent`'s positional `ColumnRef` -> `ColumnId`
-/// binding the way a real reducer's `col` is, since `Extension` carries no
-/// typed column field for core to resolve. Shared `arg_selector_columns` validates
-/// and resolves those names during aggregate schema derivation, preserving the
-/// selected argument's type and nullability for downstream exact execution.
-///
-/// DerivedCols preserves both bare-column arguments when grouping expressions
-/// introduce an intermediate Project. Shared aggregate schema derivation resolves
-/// the payload and preserves the selected argument's type and nullability.
-fn lower_arg_selector(
-    name: &str,
-    args: &[Expr],
-) -> Result<Option<AggIntent<ColumnRef>>, LoweringError> {
-    let ext_kind = match name {
-        "argmax" => "arg_max",
-        "argmin" => "arg_min",
-        _ => return Ok(None),
-    };
-    let [arg, val] = args else {
-        unreachable!(
-            "{name}'s stub signature (asap_sql_function_catalog::CLICKHOUSE_BUILTINS) fixes \
-             its arity at 2 -- the planner already rejected any other argument count before \
-             lower_agg_intent runs"
-        );
-    };
-    let arg_col = reducer_col(name, std::slice::from_ref(arg))?;
-    let val_col = reducer_col(name, std::slice::from_ref(val))?;
-    Ok(Some(AggIntent::Extension {
-        ext_kind: ext_kind.to_string(),
-        payload: serde_json::json!({ "arg_col": arg_col, "val_col": val_col }),
-    }))
-}
-
-/// Fold `pred` directly onto `child.predicates` when `child` is a bare `Scan`
-/// (a `WHERE` directly over a table), otherwise wrap it in an ordinary
-/// `Filter` — canonical's invariant that a `Filter` never sits directly over a
-/// `Scan`. A front end emitting the canonical shape directly is responsible
-/// for maintaining that invariant itself (issue #179).
-fn filter_or_fold(pred: Scalar, child: Unresolved) -> Unresolved {
-    match child {
-        Unresolved::Scan {
-            source,
-            mut predicates,
-            schema,
-        } => {
-            predicates.push(Predicate(pred));
-            Unresolved::Scan {
-                source,
-                predicates,
-                schema,
-            }
-        }
-        other => Unresolved::Filter {
-            pred: Predicate(pred),
-            child: Rc::new(other),
-        },
-    }
-}
-
-/// Flatten a top-level `AND` chain into its conjuncts.
-fn split_conjunction<'a>(expr: &'a Expr, out: &mut Vec<&'a Expr>) {
-    match expr {
-        Expr::BinaryExpr(b) if b.op == logical_expr::Operator::And => {
-            split_conjunction(&b.left, out);
-            split_conjunction(&b.right, out);
-        }
-        other => out.push(other),
-    }
-}
-
-/// Whether `expr` reads another operator anywhere inside it (`EXISTS`,
-/// `IN (…)`, a scalar subquery).
-fn reads_subquery(expr: &Expr) -> bool {
-    expr.exists(|e| {
-        Ok(matches!(
-            e,
-            Expr::ScalarSubquery(_) | Expr::InSubquery(_) | Expr::Exists(_)
-        ))
-    })
-    .expect("the predicate never fails")
-}
-
-/// Re-`AND` the conjuncts, or `None` when there are none left.
-fn rebuild_conjunction(conjuncts: &[&Expr]) -> Option<Expr> {
-    conjuncts
-        .iter()
-        .map(|e| (*e).clone())
-        .reduce(|acc, e| acc.and(e))
-}
-
-/// Split a correlated subquery's plan into `(uncorrelated plan, correlation)`.
-///
-/// The correlation is the conjunction of the filter conjuncts that mention an
-/// outer column, rewritten so `outer_ref(t.c)` becomes a plain `t.c` — it then
-/// resolves against the join's concatenated `left ++ right` schema, like any
-/// other join predicate. Everything else stays an ordinary inner `Filter`.
-///
-/// An outer reference anywhere but a top-level filter conjunct is rejected: it
-/// would need real decorrelation, not a predicate lift.
-fn split_correlation(plan: &LogicalPlan) -> Result<(LogicalPlan, Option<Expr>), LoweringError> {
-    let LogicalPlan::Filter(filter) = plan else {
-        return if plan_has_outer_ref(plan) {
-            Err(LoweringError::UnsupportedFeature(
-                "correlated subquery whose outer reference is not a filter conjunct".into(),
-            ))
-        } else {
-            Ok((plan.clone(), None))
-        };
-    };
-
-    let mut conjuncts = Vec::new();
-    split_conjunction(&filter.predicate, &mut conjuncts);
-    let (correlated, inner): (Vec<_>, Vec<_>) =
-        conjuncts.into_iter().partition(|e| expr_has_outer_ref(e));
-
-    let input = filter.input.as_ref();
-    if plan_has_outer_ref(input) {
-        return Err(LoweringError::UnsupportedFeature(
-            "correlated subquery whose outer reference is below its filter".into(),
-        ));
-    }
-
-    let correlation = rebuild_conjunction(&correlated)
-        .map(|e| strip_outer_refs(&e))
-        .transpose()?;
-    let plan = match rebuild_conjunction(&inner) {
-        Some(pred) => LogicalPlan::Filter(
-            logical_expr::Filter::try_new(pred, filter.input.clone())
-                .map_err(LoweringError::DataFusion)?,
-        ),
-        None => input.clone(),
-    };
-    Ok((plan, correlation))
-}
-
-/// Rewrite `outer_ref(t.c)` to `t.c` so the expression resolves against the
-/// join's concatenated schema.
-fn strip_outer_refs(expr: &Expr) -> Result<Expr, LoweringError> {
-    expr.clone()
-        .transform(|e| {
-            Ok(match e {
-                Expr::OuterReferenceColumn(_, col) => Transformed::yes(Expr::Column(col)),
-                other => Transformed::no(other),
-            })
-        })
-        .map(|t| t.data)
-        .map_err(LoweringError::DataFusion)
-}
-
-fn expr_has_outer_ref(expr: &Expr) -> bool {
-    let mut found = false;
-    expr.apply(|e| {
-        if matches!(e, Expr::OuterReferenceColumn(..)) {
-            found = true;
-            return Ok(TreeNodeRecursion::Stop);
-        }
-        Ok(TreeNodeRecursion::Continue)
-    })
-    .expect("infallible visitor");
-    found
-}
-
-fn plan_has_outer_ref(plan: &LogicalPlan) -> bool {
-    let mut found = false;
-    plan.apply(|p| {
-        if p.expressions().iter().any(expr_has_outer_ref) {
-            found = true;
-            return Ok(TreeNodeRecursion::Stop);
-        }
-        Ok(TreeNodeRecursion::Continue)
-    })
-    .expect("infallible visitor");
-    found
-}
-
-/// Strip `AS alias` wrappers.
-fn unalias(expr: &Expr) -> &Expr {
-    match expr {
-        Expr::Alias(a) => unalias(&a.expr),
-        other => other,
-    }
-}
-
-/// The `GroupingSet` inside a grouping expression, if any.
-fn as_grouping_set(expr: &Expr) -> Option<&logical_expr::GroupingSet> {
-    match unalias(expr) {
-        Expr::GroupingSet(gs) => Some(gs),
-        _ => None,
-    }
-}
-
-/// The grouping levels a `GroupingSet` stands for, widest first (issue #118).
-///
-/// `ROLLUP(a, b)` → `(a,b), (a), ()` — the prefixes.
-/// `CUBE(a, b)`   → `(a,b), (a), (b), ()` — the power set.
-/// `GROUPING SETS` is already the explicit list.
-fn expand_grouping_set(gs: &logical_expr::GroupingSet) -> Vec<Vec<Expr>> {
-    match gs {
-        logical_expr::GroupingSet::Rollup(exprs) => (0..=exprs.len())
-            .rev()
-            .map(|n| exprs[..n].to_vec())
-            .collect(),
-        logical_expr::GroupingSet::Cube(exprs) => {
-            // Bitmask descending, so the full set leads and `()` trails.
-            (0..(1u32 << exprs.len()))
-                .rev()
-                .map(|mask| {
-                    exprs
-                        .iter()
-                        .enumerate()
-                        .filter(|(i, _)| mask & (1 << i) != 0)
-                        .map(|(_, e)| e.clone())
-                        .collect()
-                })
-                .collect()
-        }
-        logical_expr::GroupingSet::GroupingSets(sets) => sets.clone(),
-    }
-}
-
-/// Derived columns materialized in a `Project` beneath an `Aggregate` (#110).
-///
-/// `Aggregate.by` holds positional `ColumnId`s and each reducer holds one input
-/// column, so neither can hold an expression. `GROUP BY date_trunc('minute', t)`
-/// and `SUM(bytes * 8)` are therefore rewritten to group/reduce over a projected
-/// column that carries the expression's value.
-///
-/// The projection also has to carry through the plain columns the aggregate
-/// still references, since a `Project` replaces its child's schema rather than
-/// extending it.
-struct DerivedCols<'l> {
-    lowerer: &'l SqlLowerer<'l>,
-    cols: Vec<ProjectItem>,
-    /// Whether any column is genuinely derived. Without one the aggregate keeps
-    /// its original child, so trees that lower today keep their exact shape.
-    any: bool,
-    /// First same-name-different-value collision, reported only if the
-    /// projection is actually inserted (see [`Self::wrap`]).
-    collision: Option<String>,
-}
-
-impl<'l> DerivedCols<'l> {
-    fn new(lowerer: &'l SqlLowerer<'l>) -> Self {
-        Self {
-            lowerer,
-            cols: Vec::new(),
-            any: false,
-            collision: None,
-        }
-    }
-
-    /// Add `alias := expr`, or note a collision if `alias` already means
-    /// something else. `Project` carries one relation qualifier for all its
-    /// columns, so `a.k` and `b.k` cannot both survive it — but that only
-    /// matters when a projection gets inserted at all.
-    fn push(&mut self, alias: String, expr: Scalar) {
-        let existing = self
-            .cols
-            .iter()
-            .find(|c| c.alias.as_deref() == Some(&alias));
-        match existing {
-            // Same name, same value — one projected column serves both uses.
-            Some(e) if e.expr == expr => {}
-            Some(_) => {
-                self.collision.get_or_insert(alias);
-            }
-            None => self.cols.push(ProjectItem {
-                alias: Some(alias),
-                expr,
-            }),
-        }
-    }
-
-    /// A plain column the aggregate references — carried through unchanged.
-    fn passthrough(&mut self, expr: &Expr) -> Result<(), LoweringError> {
-        let Expr::Column(c) = unalias(expr) else {
-            return Ok(());
-        };
-        self.push(c.name.clone(), self.lowerer.lower_expr(expr)?);
-        Ok(())
-    }
-
-    /// A genuinely derived column: `alias` now names `expr`'s value.
-    fn materialize(&mut self, alias: String, expr: Scalar) -> Result<(), LoweringError> {
-        self.any = true;
-        self.push(alias, expr);
-        Ok(())
-    }
-
-    /// Repoint a reducer's argument at a derived column when it is an
-    /// expression; otherwise carry its plain input column through.
-    fn rewrite_agg(&mut self, expr: &Expr) -> Result<Expr, LoweringError> {
-        let Expr::AggregateFunction(agg_fn) = unalias(expr) else {
-            return Ok(expr.clone());
-        };
-        if matches!(
-            asap_sql_function_catalog::lookup_native(&agg_fn.func.name().to_lowercase()),
-            Some(AggSemantic::Correlation)
-        ) {
-            // Give each value argument its own projected name, including casts
-            // and qualified columns. This retains both inputs and avoids losing
-            // relation qualifiers when the projection becomes an unqualified schema.
-            let mut rewritten = agg_fn.clone();
-            for arg in &mut rewritten.params.args {
-                let alias = unalias(arg).to_string();
-                self.materialize(alias.clone(), self.lowerer.lower_expr(arg)?)?;
-                *arg = Expr::Column(DfColumn::new_unqualified(alias));
-            }
-            return Ok(Expr::AggregateFunction(rewritten));
-        }
-        // `COUNT(*)` reduces no column; `agg_col_name` covers bare/aliased/cast
-        // columns, so `None` here means the argument really is an expression.
-        let counts_rows =
-            agg_fn.func.name().eq_ignore_ascii_case("count") && !agg_fn.params.distinct;
-        let Some(arg) = agg_fn.params.args.first() else {
-            return Ok(expr.clone());
-        };
-        if counts_rows {
-            return Ok(expr.clone());
-        }
-        // Preserve every additional column dependency (e.g. argMax's ordering
-        // column) when an unrelated grouping expression creates a Project.
-        // Literal parameters need no source column and remain untouched.
-        for argument in agg_fn.params.args.iter().skip(1) {
-            self.passthrough(argument)?;
-        }
-        match agg_col_name(&agg_fn.params.args) {
-            Some(name) => {
-                self.push(name, self.lowerer.lower_expr(arg)?);
-                Ok(expr.clone())
-            }
-            None => {
-                let alias = unalias(arg).to_string();
-                self.materialize(alias.clone(), self.lowerer.lower_expr(arg)?)?;
-                let mut agg_fn = agg_fn.clone();
-                agg_fn.params.args[0] = Expr::Column(DfColumn::new_unqualified(alias));
-                Ok(Expr::AggregateFunction(agg_fn))
-            }
-        }
-    }
-
-    /// Wrap `input` in the materializing `Project`, or return it untouched when
-    /// nothing needed deriving — so a query that lowers today keeps its exact
-    /// tree, and a name collision that the projection would have flattened only
-    /// matters once the projection exists.
-    fn wrap(self, input: Unresolved) -> Result<Unresolved, LoweringError> {
-        if !self.any {
-            return Ok(input);
-        }
-        if let Some(alias) = self.collision {
-            return Err(LoweringError::UnsupportedFeature(format!(
-                "ambiguous column `{alias}` beneath an expression GROUP BY / \
-                 aggregate — alias the relations apart"
-            )));
-        }
-        Ok(Unresolved::Project {
-            cols: self.cols,
-            qualifier: None,
-            child: Rc::new(input),
-        })
-    }
-}
-
-/// The first aggregate argument's column name (bare / aliased / cast column),
-/// or `None` for `*` / a non-column expression.
-fn agg_col_name(args: &[Expr]) -> Option<String> {
-    fn col_name(e: &Expr) -> Option<String> {
-        match e {
-            Expr::Column(c) => Some(c.name.clone()),
-            Expr::Alias(a) => col_name(&a.expr),
-            Expr::Cast(c) => col_name(&c.expr),
-            _ => None,
-        }
-    }
-    args.first().and_then(col_name)
-}
-
-/// The single input column of a value reducer (`SUM`/`MIN`/`MAX`/`AVG`/stddev/
-/// variance/quantile/count-distinct). Errors if the argument is not a column:
-/// the canonical `AggIntent` reduces a column, not an arbitrary expression
-/// (`SUM(a*b)`), so silently picking a probe column would compute the wrong
-/// result.
-fn reducer_col(name: &str, args: &[Expr]) -> Result<ColumnRef, LoweringError> {
-    agg_col_name(args).map(ColumnRef::Named).ok_or_else(|| {
-        LoweringError::UnsupportedAggregate(format!("{name} over a non-column expression"))
-    })
-}
-
-/// One argument of a `COUNT(DISTINCT ...)`. Resolved the way a grouping key is
-/// — what is being counted is an identity, and its qualifier has to survive a
-/// join (`a.k` vs `b.k`) — but reported as an aggregate restriction, since an
-/// aggregate call is what the user wrote.
-fn distinct_col(expr: &Expr) -> Result<ColumnRef, LoweringError> {
-    expr_to_group_ref(expr).map_err(|_| {
-        LoweringError::UnsupportedAggregate(
-            "COUNT(DISTINCT ...) over a non-column expression".into(),
-        )
-    })
-}
-
-fn expr_to_group_ref(expr: &Expr) -> Result<ColumnRef, LoweringError> {
-    match expr {
-        // Preserve the relation qualifier so a GROUP BY / PARTITION BY key over a
-        // join (`b.k` vs `a.k`) resolves to the correct side — the same rule the
-        // scalar predicate path uses (`lower_expr`).
-        Expr::Column(col) => Ok(match &col.relation {
-            Some(rel) => ColumnRef::Qualified {
-                table: rel.to_string(),
-                name: col.name.clone(),
-            },
-            None => ColumnRef::Named(col.name.clone()),
-        }),
-        Expr::Alias(a) => expr_to_group_ref(&a.expr),
-        other => Err(LoweringError::UnsupportedFeature(format!(
-            "non-column GROUP BY expression: {other}"
-        ))),
-    }
-}
-
-fn extract_percentile_q(args: &[Expr]) -> Result<f64, LoweringError> {
-    let q = match args.get(1) {
-        Some(Expr::Literal(DfScalarValue::Float64(Some(q)), _)) => *q,
-        Some(Expr::Literal(DfScalarValue::Float32(Some(q)), _)) => *q as f64,
-        _ => {
-            return Err(LoweringError::InvalidExpression(
-                "percentile value must be a float literal (2nd arg)".into(),
-            ))
-        }
-    };
-    if q.is_finite() && (0.0..=1.0).contains(&q) {
-        Ok(q)
-    } else {
-        Err(LoweringError::InvalidExpression(format!(
-            "percentile must be in [0, 1], got {q}"
-        )))
-    }
-}
-
-// ── LogicalPlan navigation helpers ──────────────────────────────────────────────
-
-fn eval_fetch(expr_opt: &Option<Box<Expr>>) -> Option<usize> {
-    expr_opt.as_ref().and_then(|e| match e.as_ref() {
-        Expr::Literal(DfScalarValue::Int64(Some(v)), _) if *v >= 0 => Some(*v as usize),
-        Expr::Literal(DfScalarValue::UInt64(Some(v)), _) => Some(*v as usize),
-        Expr::Literal(DfScalarValue::Int32(Some(v)), _) if *v >= 0 => Some(*v as usize),
-        _ => None,
-    })
-}
-
-/// Map a DataFusion window-function definition to the canonical
-/// [`WindowFuncKind`].
-/// `NthValue` is returned with `None`; `lower_window` fills in `n` from args.
-fn lower_window_func_kind(fun: &WindowFunctionDefinition) -> Result<WindowFuncKind, LoweringError> {
-    let unsupported = |what: &str, name: &str| {
-        LoweringError::UnsupportedFeature(format!("window {what}: {name}"))
-    };
-    match fun {
-        WindowFunctionDefinition::WindowUDF(udf) => match udf.name().to_lowercase().as_str() {
-            "row_number" => Ok(WindowFuncKind::RowNumber),
-            "rank" => Ok(WindowFuncKind::Rank),
-            "dense_rank" => Ok(WindowFuncKind::DenseRank),
-            "lag" => Ok(WindowFuncKind::Lag),
-            "lead" => Ok(WindowFuncKind::Lead),
-            // ClickHouse: frame-respecting variants, not plain Lag/Lead (#267).
-            "laginframe" => Ok(WindowFuncKind::LagInFrame),
-            "leadinframe" => Ok(WindowFuncKind::LeadInFrame),
-            "first_value" => Ok(WindowFuncKind::FirstValue),
-            "last_value" => Ok(WindowFuncKind::LastValue),
-            "nth_value" => Ok(WindowFuncKind::NthValue(None)),
-            other => Err(unsupported("function", other)),
-        },
-        WindowFunctionDefinition::AggregateUDF(udf) => match udf.name().to_lowercase().as_str() {
-            "sum" => Ok(WindowFuncKind::Sum),
-            "avg" | "mean" => Ok(WindowFuncKind::Avg),
-            "count" => Ok(WindowFuncKind::Count),
-            "min" => Ok(WindowFuncKind::Min),
-            "max" => Ok(WindowFuncKind::Max),
-            other => Err(unsupported("aggregate", other)),
-        },
-    }
-}
-
-/// Map DataFusion's resolved `WindowFrame` (issue #268) to the canonical
-/// [`WindowFrame`]. DataFusion's planner always fills in the SQL-standard
-/// default frame before the logical plan is built, so this never sees an
-/// "absent" frame — only `ROWS`/`RANGE`/`GROUPS` with concrete bounds.
-/// `GROUPS` is rejected: no query in this repo's SQL corpora uses it, and
-/// nothing downstream interprets frame semantics yet, so it isn't worth
-/// modelling untested.
-fn lower_window_frame(
-    frame: &datafusion::logical_expr::WindowFrame,
-) -> Result<WindowFrame, LoweringError> {
-    let units = match frame.units {
-        DfWindowFrameUnits::Rows => WindowFrameUnits::Rows,
-        DfWindowFrameUnits::Range => WindowFrameUnits::Range,
-        DfWindowFrameUnits::Groups => {
-            return Err(LoweringError::UnsupportedFeature(
-                "window frame unit: GROUPS".into(),
-            ))
-        }
-    };
-    let offset = |v: &DfScalarValue| -> Result<WindowFrameOffset, LoweringError> {
-        Ok(match v {
-            DfScalarValue::IntervalYearMonth(Some(months)) => WindowFrameOffset::Interval {
-                months: *months,
-                days: 0,
-                nanoseconds: 0,
-            },
-            DfScalarValue::IntervalDayTime(Some(value)) => WindowFrameOffset::Interval {
-                months: 0,
-                days: value.days,
-                nanoseconds: i64::from(value.milliseconds) * 1_000_000,
-            },
-            DfScalarValue::IntervalMonthDayNano(Some(value)) => WindowFrameOffset::Interval {
-                months: value.months,
-                days: value.days,
-                nanoseconds: value.nanoseconds,
-            },
-            // DataFusion 43 keeps every RANGE offset as text: both numeric
-            // bounds such as `1.5` and normalized interval literals such as
-            // `"1 HOUR"`. Arrow's interval parser accepts bare numbers and
-            // interprets them as months, so classify numeric text first.
-            DfScalarValue::Utf8(Some(value)) | DfScalarValue::LargeUtf8(Some(value)) => {
-                if let Ok(value) = value.parse::<i64>() {
-                    WindowFrameOffset::Scalar(ScalarValue::Int64(value))
-                } else if let Ok(value) = value.parse::<f64>() {
-                    WindowFrameOffset::Scalar(ScalarValue::Float64(value))
-                } else {
-                    match parse_interval_month_day_nano(value) {
-                        Ok(interval) => WindowFrameOffset::Interval {
-                            months: interval.months,
-                            days: interval.days,
-                            nanoseconds: interval.nanoseconds,
-                        },
-                        Err(_) => WindowFrameOffset::Scalar(scalar_value_to_asap(v)?),
-                    }
-                }
-            }
-            _ => WindowFrameOffset::Scalar(scalar_value_to_asap(v)?),
-        })
-    };
-    let bound = |b: &DfWindowFrameBound| -> Result<WindowFrameBound, LoweringError> {
-        Ok(match b {
-            DfWindowFrameBound::Preceding(v) => WindowFrameBound::Preceding(offset(v)?),
-            DfWindowFrameBound::CurrentRow => WindowFrameBound::CurrentRow,
-            DfWindowFrameBound::Following(v) => WindowFrameBound::Following(offset(v)?),
-        })
-    };
-    Ok(WindowFrame {
-        units,
-        start_bound: bound(&frame.start_bound)?,
-        end_bound: bound(&frame.end_bound)?,
-    })
-}
-
-// ── Issue #225, item 3: DataFusion registry drift detection ────────────────
-//
-// `asap_sql_function_catalog::NATIVE_FUNCTIONS` is hand-maintained data
-// mirroring what DataFusion's own aggregate-function registry resolves. That
-// mirror can only silently drift out of sync — a DataFusion version bump
-// that adds, renames, or removes a builtin aggregate leaves the catalog
-// looking fine while `lower_agg_intent` quietly gains or loses coverage. Of
-// the two introspectable sources the issue names, DataFusion's own registry
-// is the one with no external dependency: `SessionContext` already lists its
-// aggregate UDFs in-process, so the check below builds a real context the
-// same way `build_context` does and walks it directly — no live database,
-// no new CI infra, just `cargo test`. (ClickHouse's `system.functions` is
-// the other source; it needs a live ClickHouse instance, which is handled
-// separately by the dev-only `tools/clickhouse/extract_functions.py` script,
-// deliberately not wired into this test or into CI.)
-#[cfg(test)]
-mod catalog_drift {
-    use super::*;
-
-    /// Every aggregate function name DataFusion's planner resolves inside a
-    /// context built the same way `build_context` builds one must be
-    /// *accounted for* by the catalog: either `lookup_native` maps it to a
-    /// canonical semantic, it is one of our own `CLICKHOUSE_BUILTINS` stub
-    /// registrations (`build_context` registers those into the very same
-    /// context, so they show up here too), or it is explicitly listed in
-    /// `KNOWN_UNMAPPED_NATIVE_FUNCTIONS` with a reason.
-    ///
-    /// This does *not* assert the reverse (that every `NATIVE_FUNCTIONS`
-    /// entry is resolvable) — a name that stops resolving after a DataFusion
-    /// bump just becomes permanently unreachable dead data, not a lowering
-    /// hazard, so it's out of scope for a regression gate. It also does not
-    /// try to derive `AggSemantic` from anything DataFusion reports — that
-    /// judgment call stays with whoever adds the catalog entry.
-    #[test]
-    fn every_datafusion_aggregate_name_is_covered_by_the_catalog() {
-        let catalog = SqlCatalog::new();
-        let ctx = SqlLowerer::new(&catalog)
-            .build_context()
-            .expect("build_context with an empty table catalog cannot fail");
-        let state = ctx.state();
-        let mut uncovered: Vec<&str> = state
-            .aggregate_functions()
-            .keys()
-            .map(String::as_str)
-            .filter(|name| {
-                asap_sql_function_catalog::lookup_native(name).is_none()
-                    && asap_sql_function_catalog::lookup_clickhouse_builtin(name).is_none()
-                    && !asap_sql_function_catalog::KNOWN_UNMAPPED_NATIVE_FUNCTIONS.contains(name)
-            })
-            .collect();
-        uncovered.sort_unstable();
-        assert!(
-            uncovered.is_empty(),
-            "DataFusion resolves these aggregate names but the catalog doesn't know about them \
-             (crates/sql-function-catalog/src/lib.rs): {uncovered:?}\n\
-             Either add a `NativeFunction` entry mapping each to its `AggSemantic`, or -- if it's \
-             a deliberate non-goal (no `AggIntent` shape for it, or it's rejected elsewhere) -- \
-             add it to `KNOWN_UNMAPPED_NATIVE_FUNCTIONS` with a reason. This usually means a \
-             DataFusion version bump added or renamed a builtin aggregate."
-        );
-    }
-
-    /// Every `KNOWN_UNMAPPED_NATIVE_FUNCTIONS` entry earns its place by
-    /// actually being a name DataFusion resolves today — otherwise it is
-    /// stale documentation for a name that no longer exists (e.g. a prior
-    /// DataFusion version renamed it), not a real "deliberately not mapped"
-    /// decision, and should be removed.
-    #[test]
-    fn known_unmapped_entries_are_all_real_datafusion_names() {
-        let catalog = SqlCatalog::new();
-        let ctx = SqlLowerer::new(&catalog)
-            .build_context()
-            .expect("build_context with an empty table catalog cannot fail");
-        let resolved = ctx.state().aggregate_functions().clone();
-        for name in asap_sql_function_catalog::KNOWN_UNMAPPED_NATIVE_FUNCTIONS {
-            assert!(
-                resolved.contains_key(*name),
-                "`{name}` is listed in KNOWN_UNMAPPED_NATIVE_FUNCTIONS but DataFusion no longer \
-                 resolves it -- remove the stale entry"
-            );
-        }
-    }
-}
diff --git a/crates/frontend-sql/src/unified/sql/types.rs b/crates/frontend-sql/src/unified/sql/types.rs
deleted file mode 100644
index 05d46f938..000000000
--- a/crates/frontend-sql/src/unified/sql/types.rs
+++ /dev/null
@@ -1,378 +0,0 @@
-//! Type bridges between DataFusion's Arrow types and the canonical `DataType`, plus
-//! the SQL table catalog used to register tables with DataFusion and to carry
-//! resolved leaf schemas into the canonical, unresolved tree.
-
-use std::collections::HashMap;
-
-use datafusion::arrow::datatypes::{
-    DataType as ArrowDataType, Field as ArrowField, Fields, Schema as ArrowSchema,
-};
-use datafusion::common::ScalarValue as DfScalarValue;
-
-use asap_types::pre_asap::schema::{DataType, Field, Schema};
-use asap_types::pre_asap::ScalarValue;
-
-use crate::unified::error::SqlError as LoweringError;
-
-/// Table catalog for SQL lowering: table name → resolved canonical [`Schema`].
-///
-/// Used twice: to register Arrow-backed `MemTable`s so DataFusion can resolve
-/// `SELECT … FROM t`, and to attach each table's schema directly onto the
-/// canonical `Scan` (`schema: Some(_)`) so the SchemaResolver doesn't need to
-/// usage-derive it.
-#[derive(Debug, Clone, Default)]
-pub struct SqlCatalog {
-    pub tables: HashMap<String, Schema>,
-}
-
-impl SqlCatalog {
-    pub fn new() -> Self {
-        Self::default()
-    }
-
-    /// Builder: register `name` with its resolved canonical schema.
-    pub fn with_table(mut self, name: impl Into<String>, schema: Schema) -> Self {
-        self.tables.insert(name.into(), schema);
-        self
-    }
-}
-
-pub(super) fn scalar_value_to_asap(sv: &DfScalarValue) -> Result<ScalarValue, LoweringError> {
-    match sv {
-        DfScalarValue::Int64(Some(v)) => Ok(ScalarValue::Int64(*v)),
-        DfScalarValue::Int32(Some(v)) => Ok(ScalarValue::Int64(*v as i64)),
-        DfScalarValue::Int16(Some(v)) => Ok(ScalarValue::Int64(*v as i64)),
-        DfScalarValue::Int8(Some(v)) => Ok(ScalarValue::Int64(*v as i64)),
-        DfScalarValue::UInt64(Some(v)) => i64::try_from(*v).map(ScalarValue::Int64).map_err(|_| {
-            LoweringError::InvalidExpression(format!("UInt64 value {v} overflows i64"))
-        }),
-        DfScalarValue::UInt32(Some(v)) => Ok(ScalarValue::Int64(*v as i64)),
-        DfScalarValue::Float64(Some(v)) => Ok(ScalarValue::Float64(*v)),
-        DfScalarValue::Float32(Some(v)) => Ok(ScalarValue::Float64(*v as f64)),
-        DfScalarValue::Utf8(Some(s)) | DfScalarValue::LargeUtf8(Some(s)) => {
-            Ok(ScalarValue::Utf8(s.clone()))
-        }
-        DfScalarValue::Boolean(Some(b)) => Ok(ScalarValue::Boolean(*b)),
-        // All three of DataFusion's interval scalars land on one canonical
-        // shape; the narrower two simply leave the fields they do not carry
-        // at zero.
-        DfScalarValue::IntervalYearMonth(Some(months)) => Ok(ScalarValue::Interval {
-            months: *months,
-            days: 0,
-            nanos: 0,
-        }),
-        DfScalarValue::IntervalDayTime(Some(v)) => Ok(ScalarValue::Interval {
-            months: 0,
-            days: v.days,
-            nanos: i64::from(v.milliseconds) * 1_000_000,
-        }),
-        DfScalarValue::IntervalMonthDayNano(Some(v)) => Ok(ScalarValue::Interval {
-            months: v.months,
-            days: v.days,
-            nanos: v.nanoseconds,
-        }),
-        _ if sv.is_null() => Ok(ScalarValue::Null),
-        _ => Err(LoweringError::InvalidExpression(format!(
-            "unsupported scalar: {sv:?}"
-        ))),
-    }
-}
-
-/// Arrow → the canonical `DataType` (used for `CAST` targets). Deliberately narrow.
-pub(super) fn arrow_to_dtype(dt: &ArrowDataType) -> Result<DataType, LoweringError> {
-    match dt {
-        ArrowDataType::Null => Ok(DataType::Null),
-        ArrowDataType::Int64
-        | ArrowDataType::Int32
-        | ArrowDataType::Int16
-        | ArrowDataType::Int8 => Ok(DataType::Int64),
-        ArrowDataType::Float64 | ArrowDataType::Float32 => Ok(DataType::Float64),
-        ArrowDataType::Utf8 | ArrowDataType::LargeUtf8 => Ok(DataType::Utf8),
-        ArrowDataType::Boolean => Ok(DataType::Bool),
-        ArrowDataType::Timestamp(_, _) => Ok(DataType::Timestamp),
-        ArrowDataType::Date32 | ArrowDataType::Date64 => Ok(DataType::Date),
-        ArrowDataType::Interval(_) => Ok(DataType::Interval),
-        ArrowDataType::List(element) => Ok(DataType::List {
-            element: Box::new(Field::new(
-                element.name(),
-                arrow_to_dtype(element.data_type())?,
-                element.is_nullable(),
-            )),
-        }),
-        ArrowDataType::Struct(fields) => Ok(DataType::Struct {
-            fields: fields
-                .iter()
-                .map(|field| {
-                    Ok(Field::new(
-                        field.name(),
-                        arrow_to_dtype(field.data_type())?,
-                        field.is_nullable(),
-                    ))
-                })
-                .collect::<Result<Vec<_>, LoweringError>>()?,
-        }),
-        ArrowDataType::Map(entries, _) => {
-            let ArrowDataType::Struct(fields) = entries.data_type() else {
-                return Err(LoweringError::UnsupportedFeature(
-                    "map entries must be a struct".into(),
-                ));
-            };
-            if fields.len() != 2 || fields[0].is_nullable() {
-                return Err(LoweringError::UnsupportedFeature(
-                    "map entries require a non-null key and a value".into(),
-                ));
-            }
-            Ok(DataType::Map {
-                key: Box::new(arrow_to_dtype(fields[0].data_type())?),
-                value: Box::new(arrow_to_dtype(fields[1].data_type())?),
-                value_nullable: fields[1].is_nullable(),
-            })
-        }
-        other => Err(LoweringError::UnsupportedFeature(format!(
-            "Arrow type: {other:?}"
-        ))),
-    }
-}
-
-/// The canonical `DataType` → Arrow (for registering catalog tables with DataFusion).
-pub(super) fn dtype_to_arrow(dt: &DataType) -> ArrowDataType {
-    match dt {
-        DataType::Null => ArrowDataType::Null,
-        DataType::Int64 => ArrowDataType::Int64,
-        DataType::Float64 => ArrowDataType::Float64,
-        DataType::Utf8 => ArrowDataType::Utf8,
-        DataType::Bool => ArrowDataType::Boolean,
-        DataType::List { element } => ArrowDataType::List(std::sync::Arc::new(ArrowField::new(
-            &element.name,
-            dtype_to_arrow(&element.dtype),
-            element.nullable,
-        ))),
-        DataType::Struct { fields } => ArrowDataType::Struct(
-            fields
-                .iter()
-                .map(|field| {
-                    ArrowField::new(&field.name, dtype_to_arrow(&field.dtype), field.nullable)
-                })
-                .collect::<Vec<_>>()
-                .into(),
-        ),
-        DataType::Map {
-            key,
-            value,
-            value_nullable,
-        } => ArrowDataType::Map(
-            std::sync::Arc::new(ArrowField::new(
-                "entries",
-                ArrowDataType::Struct(
-                    vec![
-                        ArrowField::new("key", dtype_to_arrow(key), false),
-                        ArrowField::new("value", dtype_to_arrow(value), *value_nullable),
-                    ]
-                    .into(),
-                ),
-                false,
-            )),
-            false,
-        ),
-        DataType::Timestamp => {
-            ArrowDataType::Timestamp(datafusion::arrow::datatypes::TimeUnit::Millisecond, None)
-        }
-        // Deliberately narrowing: `Date64` lowers to `DataType::Date` and comes
-        // back as `Date32`. Both spell the same calendar date and nothing in
-        // the planner reads the width; a catalog that wants `Date64` back would
-        // need a second variant carrying no planning information.
-        DataType::Date => ArrowDataType::Date32,
-        // Only reachable through a hand-built schema: `Interval` types a
-        // literal, and no catalog declares a column with it. Mapped to the
-        // same three-field shape `ScalarValue::Interval` carries rather than
-        // left to panic.
-        DataType::Interval => {
-            ArrowDataType::Interval(datafusion::arrow::datatypes::IntervalUnit::MonthDayNano)
-        }
-    }
-}
-
-/// Build an Arrow schema from a canonical [`Schema`] (column name + type + nullability).
-pub(super) fn schema_to_arrow(schema: &Schema) -> ArrowSchema {
-    let fields: Fields = schema
-        .fields
-        .iter()
-        .map(|c: &Field| {
-            ArrowField::new(&c.name, dtype_to_arrow(c.expect_plain_dtype()), c.nullable)
-        })
-        .collect();
-    ArrowSchema::new(fields)
-}
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-
-    /// Both Arrow date widths bridge to the one canonical `Date`, and it
-    /// registers back as `Date32` — the documented narrowing.
-    #[test]
-    fn both_arrow_date_widths_bridge_to_date() {
-        assert_eq!(
-            arrow_to_dtype(&ArrowDataType::Date32).unwrap(),
-            DataType::Date
-        );
-        assert_eq!(
-            arrow_to_dtype(&ArrowDataType::Date64).unwrap(),
-            DataType::Date
-        );
-        assert_eq!(dtype_to_arrow(&DataType::Date), ArrowDataType::Date32);
-    }
-
-    /// Every Arrow interval width shares the canonical calendar interval type.
-    #[test]
-    fn interval_types_round_trip_through_the_catalog_bridge() {
-        use datafusion::arrow::datatypes::IntervalUnit;
-        for unit in [
-            IntervalUnit::YearMonth,
-            IntervalUnit::DayTime,
-            IntervalUnit::MonthDayNano,
-        ] {
-            assert_eq!(
-                arrow_to_dtype(&ArrowDataType::Interval(unit)).unwrap(),
-                DataType::Interval
-            );
-        }
-        assert_eq!(
-            arrow_to_dtype(&dtype_to_arrow(&DataType::Interval)).unwrap(),
-            DataType::Interval
-        );
-    }
-
-    /// All three of DataFusion's interval scalars carry into the one canonical
-    /// three-field shape, with the fields they do not spell left at zero.
-    #[test]
-    fn every_datafusion_interval_scalar_carries_across() {
-        use datafusion::arrow::datatypes::{IntervalDayTime, IntervalMonthDayNano};
-
-        assert_eq!(
-            scalar_value_to_asap(&DfScalarValue::IntervalYearMonth(Some(14))).unwrap(),
-            ScalarValue::Interval {
-                months: 14,
-                days: 0,
-                nanos: 0
-            }
-        );
-        assert_eq!(
-            scalar_value_to_asap(&DfScalarValue::IntervalDayTime(Some(IntervalDayTime::new(
-                30, 500
-            ))))
-            .unwrap(),
-            ScalarValue::Interval {
-                months: 0,
-                days: 30,
-                nanos: 500_000_000
-            }
-        );
-        assert_eq!(
-            scalar_value_to_asap(&DfScalarValue::IntervalMonthDayNano(Some(
-                IntervalMonthDayNano::new(1, 2, 3)
-            )))
-            .unwrap(),
-            ScalarValue::Interval {
-                months: 1,
-                days: 2,
-                nanos: 3
-            }
-        );
-    }
-
-    /// Nested map values and value nullability survive catalog registration.
-    #[test]
-    fn nested_map_schema_round_trip() {
-        let map = DataType::Map {
-            key: Box::new(DataType::Utf8),
-            value: Box::new(DataType::Map {
-                key: Box::new(DataType::Int64),
-                value: Box::new(DataType::Float64),
-                value_nullable: true,
-            }),
-            value_nullable: false,
-        };
-        assert_eq!(arrow_to_dtype(&dtype_to_arrow(&map)).unwrap(), map);
-        let encoded = serde_json::to_string(&map).unwrap();
-        assert_eq!(serde_json::from_str::<DataType>(&encoded).unwrap(), map);
-    }
-}
-
-#[cfg(test)]
-mod collection_tests {
-    use super::*;
-    #[test]
-    fn nested_collections_preserve_field_names_order_and_nullability() {
-        let dtype = DataType::Struct {
-            fields: vec![
-                Field::new(
-                    "samples",
-                    DataType::List {
-                        element: Box::new(Field::new(
-                            "sample",
-                            DataType::Struct {
-                                fields: vec![
-                                    Field::new("timestamp", DataType::Timestamp, false),
-                                    Field::new("value", DataType::Float64, true),
-                                    Field::new(
-                                        "labels",
-                                        DataType::Map {
-                                            key: Box::new(DataType::Utf8),
-                                            value: Box::new(DataType::List {
-                                                element: Box::new(Field::new(
-                                                    "label_value",
-                                                    DataType::Utf8,
-                                                    false,
-                                                )),
-                                            }),
-                                            value_nullable: true,
-                                        },
-                                        true,
-                                    ),
-                                ],
-                            },
-                            true,
-                        )),
-                    },
-                    false,
-                ),
-                Field::new("optional", DataType::Int64, true),
-            ],
-        };
-        let arrow = dtype_to_arrow(&dtype);
-        assert_eq!(arrow_to_dtype(&arrow).unwrap(), dtype);
-        assert_eq!(dtype_to_arrow(&arrow_to_dtype(&arrow).unwrap()), arrow);
-        let encoded = serde_json::to_string(&dtype).unwrap();
-        assert_eq!(serde_json::from_str::<DataType>(&encoded).unwrap(), dtype);
-    }
-    #[test]
-    fn empty_struct_and_nonnullable_list_element_roundtrip() {
-        let dtype = DataType::List {
-            element: Box::new(Field::new(
-                "empty",
-                DataType::Struct { fields: vec![] },
-                false,
-            )),
-        };
-        assert_eq!(arrow_to_dtype(&dtype_to_arrow(&dtype)).unwrap(), dtype);
-    }
-}
-
-#[cfg(test)]
-mod bottom_map_tests {
-    use super::*;
-    #[test]
-    fn empty_map_bottom_types_roundtrip_without_string_defaults() {
-        let (map, nullable) = asap_types::pre_asap::scalar_type_rules::MapScalarFunction::Construct
-            .output_type(&[])
-            .unwrap();
-        assert!(!nullable);
-        let arrow = dtype_to_arrow(&map);
-        assert_eq!(arrow_to_dtype(&arrow).unwrap(), map);
-        assert_eq!(
-            arrow_to_dtype(&ArrowDataType::Null).unwrap(),
-            DataType::Null
-        );
-    }
-}
diff --git a/crates/types/Cargo.toml b/crates/types/Cargo.toml
index 8572854a9..0e10ccdf4 100644
--- a/crates/types/Cargo.toml
+++ b/crates/types/Cargo.toml
@@ -8,7 +8,7 @@ edition = "2021"
 # execution logic — removed, no real implementor existed; see issue #190).
 # No internal deps.
 [dependencies]
-# "rc" — QueryExpr's child fields are Rc<QueryExpr<C>> (issue #212, #222:
+# "rc" — OperatorNode child fields are Rc<OperatorNode> (issue #212, #222:
 # shared sub-expressions), and Rc<T>'s Serialize/Deserialize impls live behind
 # this feature flag. dag_export.rs / DAGNode already flatten the DAG to a
 # node+edge list for JSON export, so this does not change wire format — a
diff --git a/crates/types/src/ir/mod.rs b/crates/types/src/ir/mod.rs
index f95d71902..c4441068b 100644
--- a/crates/types/src/ir/mod.rs
+++ b/crates/types/src/ir/mod.rs
@@ -1,5 +1,4 @@
-//! Unified operator and scalar representation from #511.
-//! Legacy consumers remain on their existing representation until the planner cutover.
+//! The operator IR from #511: one operator DAG for every planning stage.
 pub mod aggregate_schema;
 pub mod asap;
 pub mod error;
diff --git a/crates/types/src/ir/operator_properties.rs b/crates/types/src/ir/operator_properties.rs
index 4737e6278..27648351b 100644
--- a/crates/types/src/ir/operator_properties.rs
+++ b/crates/types/src/ir/operator_properties.rs
@@ -1,8 +1,564 @@
-//! Operator parameters shared with the existing dag during migration.
-//! Definitions move here when legacy dag consumers are removed.
-pub use crate::pre_asap::query_expr::{
-    AtModifier, BinaryOpKind, ColState, ConcatDiscriminatorKey, DataModel, GroupKeys, GroupSide,
-    InfoMatcher, JoinKind, PromQLVectorSetOpKind, Reduction, RelationalSetOpKind, SampleKind,
-    Source, TimeShift, VectorGrouping, VectorMatch, VectorMatchKind, WindowFrame, WindowFrameBound,
-    WindowFrameOffset, WindowFrameUnits, WindowFuncKind,
-};
+//! Supporting parameter types used inside operator payloads.
+//!
+//! For example, `Aggregate.by` uses [`GroupKeys`], a join chooses [`JoinKind`],
+//! and a SQL window carries [`WindowFrame`]. These types describe what an
+//! operator does. Derived node metadata (schema, guarantee, timing) lives on
+//! [`super::OperatorNode`], not in this module.
+use crate::pre_asap::{ArithmeticOpKind, ColumnId, ColumnRef, CompareOpKind, ScalarValue};
+use serde::{Deserialize, Serialize};
+/// The column-reference type an operator parameter is generic over:
+/// positional [`ColumnId`] once bound, name-based [`ColumnRef`] before.
+pub trait ColState:
+    Clone + std::fmt::Debug + PartialEq + Serialize + for<'de> Deserialize<'de>
+{
+}
+
+impl ColState for ColumnId {}
+
+impl ColState for ColumnRef {}
+
+// ── Leaf / supporting types ───────────────────────────────────────────────────
+
+/// Positional grouping keys, shared by every "operate per group" operator:
+/// `Aggregate.by` (reduce per group), `Sort.partition_by` (rank per group —
+/// including generic `topk`/`bottomk`), and `SQLWindowFunc.partition_by` (window
+/// per group). One spelling so grouping has a single home to evolve. Empty
+/// (and `by`) = no grouping (a global operation).
+///
+/// Heavy-hitter `AggIntent::TopK` carries its grouping here too, via the
+/// enclosing `Aggregate.by` (issue #13) — so reduce, rank, and window groupings
+/// all share this one type.
+///
+/// ## `by` vs `without` (issue #39)
+///
+/// The stored [`keys`](Self::keys) are **kept** labels for `by(...)` and
+/// **excluded** labels for `without(...)`. PromQL's `without(labels)` groups by
+/// every label *except* those listed; the complement can't be enumerated at
+/// lowering time under an open (usage-derived) schema, so it is deferred to the
+/// runtime — the excluded positions are stored, the kept set stays open. Only
+/// `Aggregate` ever produces the `without` form; `Sort` / `SQLWindowFunc` /
+/// `PromqlSeriesSample` groupings are always `by`.
+///
+/// Serialises as a bare array for the (overwhelmingly common) `by` case —
+/// wire-compatible with the `Vec<ColumnId>` this field held before — and as
+/// `{"without": [...]}` for the exclusion case.
+#[derive(Debug, Clone, PartialEq, Eq, Hash)]
+pub struct GroupKeys<C = ColumnId> {
+    keys: Vec<C>,
+    without: bool,
+}
+
+// Not `#[derive(Default)]`: derive would add a `C: Default` bound, but an
+// empty key set needs nothing from `C` — `ColumnRef` has no meaningful
+// default anyway.
+impl<C> Default for GroupKeys<C> {
+    fn default() -> Self {
+        Self {
+            keys: Vec::new(),
+            without: false,
+        }
+    }
+}
+
+impl<C> GroupKeys<C> {
+    /// An empty key set — a global (ungrouped) operation.
+    pub fn none() -> Self {
+        Self::default()
+    }
+    /// `by(keys)` — group by exactly these columns.
+    pub fn by(keys: Vec<C>) -> Self {
+        Self {
+            keys,
+            without: false,
+        }
+    }
+    /// `without(keys)` — group by every label *except* these (issue #39). The
+    /// kept set is runtime-resolved; only the excluded positions are stored.
+    pub fn without(keys: Vec<C>) -> Self {
+        Self {
+            keys,
+            without: true,
+        }
+    }
+    /// Whether this is a `without(...)` exclusion grouping.
+    pub fn is_without(&self) -> bool {
+        self.without
+    }
+    /// The named keys — kept labels for `by`, excluded labels for `without`.
+    pub fn keys(&self) -> &[C] {
+        &self.keys
+    }
+}
+
+impl<C> std::ops::Deref for GroupKeys<C> {
+    type Target = [C];
+    fn deref(&self) -> &Self::Target {
+        &self.keys
+    }
+}
+
+impl<C> From<Vec<C>> for GroupKeys<C> {
+    fn from(keys: Vec<C>) -> Self {
+        Self::by(keys)
+    }
+}
+
+impl<C> FromIterator<C> for GroupKeys<C> {
+    fn from_iter<I: IntoIterator<Item = C>>(iter: I) -> Self {
+        Self::by(iter.into_iter().collect())
+    }
+}
+
+impl<'a, C> IntoIterator for &'a GroupKeys<C> {
+    type Item = &'a C;
+    type IntoIter = std::slice::Iter<'a, C>;
+    fn into_iter(self) -> Self::IntoIter {
+        self.keys.iter()
+    }
+}
+
+/// Compare directly against a `Vec<C>` so call sites and tests can keep
+/// writing `keys == vec![..]` / `assert_eq!(keys, &vec![..])`. A `without`
+/// grouping never equals a bare `by` list.
+impl<C: PartialEq> PartialEq<Vec<C>> for GroupKeys<C> {
+    fn eq(&self, other: &Vec<C>) -> bool {
+        !self.without && &self.keys == other
+    }
+}
+
+/// (De)serialise as a bare array for `by`, or `{"without": [...]}` for the
+/// exclusion form — keeping the `by` wire format identical to the old newtype.
+/// Borrowed for `Serialize` (no `C: Clone` needed to write one out), owned for
+/// `Deserialize` (there's nothing to borrow from).
+#[derive(Serialize)]
+#[serde(untagged)]
+enum GroupKeysReprRef<'a, C> {
+    By(&'a [C]),
+    Without { without: &'a [C] },
+}
+
+#[derive(Deserialize)]
+#[serde(untagged)]
+enum GroupKeysRepr<C> {
+    By(Vec<C>),
+    Without { without: Vec<C> },
+}
+
+impl<C: Serialize> Serialize for GroupKeys<C> {
+    fn serialize<S: serde::Serializer>(&self, serializer: S) -> Result<S::Ok, S::Error> {
+        if self.without {
+            GroupKeysReprRef::Without {
+                without: self.keys.as_slice(),
+            }
+            .serialize(serializer)
+        } else {
+            GroupKeysReprRef::By(self.keys.as_slice()).serialize(serializer)
+        }
+    }
+}
+
+impl<'de, C: Deserialize<'de>> Deserialize<'de> for GroupKeys<C> {
+    fn deserialize<D: serde::Deserializer<'de>>(deserializer: D) -> Result<Self, D::Error> {
+        Ok(match GroupKeysRepr::deserialize(deserializer)? {
+            GroupKeysRepr::By(keys) => Self::by(keys),
+            GroupKeysRepr::Without { without } => Self::without(without),
+        })
+    }
+}
+
+/// Which data model a `Source` / `AggIntent` operates over.
+#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
+pub enum DataModel {
+    TimeSeries,
+    Tabular,
+    Any,
+}
+
+/// The leaf data source of a `Scan`. The schema itself rides on the
+/// `Scan.schema` field (SchemaResolver-built); `Source` carries only the leaf's
+/// identity.
+#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
+pub enum Source {
+    /// Time-series leaf — PromQL / DC lifecycle. Produces `(ts, value, *labels)`.
+    TimeSeries { metric: String },
+    /// Tabular leaf — asap-fusion / future OLAP. Columns ride on `Scan.schema`.
+    Table { table_ref: String },
+}
+
+impl Source {
+    pub fn data_model(&self) -> DataModel {
+        match self {
+            Source::TimeSeries { .. } => DataModel::TimeSeries,
+            Source::Table { .. } => DataModel::Tabular,
+        }
+    }
+}
+
+/// Operator on the query-level `BinaryOp` node. Reuses the scalar IR's
+/// [`ArithmeticOpKind`] / [`CompareOpKind`] so every arithmetic/comparison
+/// operator has exactly one representation (and one `Display`) across the IR.
+#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
+pub enum BinaryOpKind {
+    /// Arithmetic — `Add/Sub/Mul/Div/Mod` (shared with `ScalarExpr::Arithmetic`).
+    Arithmetic(ArithmeticOpKind),
+    /// Comparison — `Eq/Ne/Lt/Le/Gt/Ge` + `Like/ILike/Regex` family (shared
+    /// with `ScalarExpr::Compare`). PromQL keeps the matched series whose
+    /// comparison holds.
+    Compare(CompareOpKind),
+    /// PromQL comparison with the `bool` modifier: every matched series
+    /// yields 1 or 0 and loses its metric name. A separate variant, not a
+    /// flag, because only comparisons take `bool`.
+    CompareBool(CompareOpKind),
+    /// PromQL vector-set operation.
+    Set(PromQLVectorSetOpKind),
+}
+
+impl std::fmt::Display for BinaryOpKind {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        match self {
+            BinaryOpKind::Arithmetic(op) => write!(f, "{op}"),
+            BinaryOpKind::Compare(op) => write!(f, "{op}"),
+            BinaryOpKind::CompareBool(op) => write!(f, "{op} bool"),
+            BinaryOpKind::Set(PromQLVectorSetOpKind::And) => f.write_str("AND"),
+            BinaryOpKind::Set(PromQLVectorSetOpKind::Or) => f.write_str("OR"),
+            BinaryOpKind::Set(PromQLVectorSetOpKind::Unless) => f.write_str("unless"),
+        }
+    }
+}
+
+#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
+pub enum JoinKind {
+    Inner,
+    Left,
+    Right,
+    Full,
+    Cross,
+    /// Left semi-join — each left row that has **at least one** match, once.
+    /// `WHERE c IN (SELECT …)` / `WHERE EXISTS (…)` (issue #111).
+    ///
+    /// Output schema is the **left's alone**; the right side is a filter, not a
+    /// source of columns. The join predicate still resolves against the
+    /// concatenated `left ++ right` schema — its scope is deliberately wider
+    /// than the node's output.
+    Semi,
+    /// Left anti-join — each left row with **no** match. `WHERE NOT EXISTS (…)`.
+    /// Same schema rule as [`JoinKind::Semi`].
+    ///
+    /// Note this is *not* `NOT IN (SELECT …)`: under SQL's three-valued logic a
+    /// NULL on the right makes `NOT IN` yield no rows at all, where an anti-join
+    /// yields every left row. The SQL front end rejects `NOT IN (subquery)`
+    /// rather than lower it here.
+    Anti,
+}
+
+#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
+pub enum RelationalSetOpKind {
+    Union,
+    Intersect,
+    Except,
+}
+
+/// PromQL vector-set operator used by [`BinaryOpKind::Set`].
+#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
+pub enum PromQLVectorSetOpKind {
+    And,
+    Or,
+    Unless,
+}
+
+/// SQL analytic window function (`fn(...) OVER (…)`). Distinct from a streaming
+/// time `Window`: this is an analytic frame over already-materialised rows.
+#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
+#[serde(rename_all = "snake_case")]
+pub enum WindowFuncKind {
+    RowNumber,
+    Rank,
+    DenseRank,
+    Lag,
+    Lead,
+    /// ClickHouse `lagInFrame`/`leadInFrame`: unlike [`Lag`](Self::Lag)/[`Lead`](Self::Lead),
+    /// these respect the window frame bounds (NULL/default past the frame edge)
+    /// rather than reaching arbitrarily far back/forward. Kept as distinct
+    /// variants so the frame clause is never silently discarded by conflating
+    /// them with `Lag`/`Lead` (#267). `WindowFuncKind` still has no frame
+    /// representation, so today these lower and behave exactly like
+    /// `Lag`/`Lead` — the tag is correct, the frame-respecting behavior isn't
+    /// implemented yet. See #231 for modeling window frames properly.
+    LagInFrame,
+    LeadInFrame,
+    FirstValue,
+    LastValue,
+    /// `NTH_VALUE(expr, n)` — `n` is resolved from the (literal) 2nd argument.
+    NthValue(Option<u64>),
+    Sum,
+    Avg,
+    Count,
+    Min,
+    Max,
+}
+
+/// A window's frame-spec (`ROWS`/`RANGE BETWEEN … AND …`) — which rows around
+/// the current one an analytic window function reads. `GROUPS` is rejected at
+/// lowering time (issue #268): every SQL corpus in this repo uses only `ROWS`,
+/// and nothing downstream interprets frame semantics yet, so it isn't worth
+/// modelling untested.
+///
+/// Meaningless (but harmless) on the rank-only and navigation functions
+/// (`ROW_NUMBER`/`RANK`/`DENSE_RANK`/`LAG`/`LEAD`), which ignore the frame per
+/// SQL semantics — DataFusion still attaches one, stored here verbatim.
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+pub struct WindowFrame {
+    pub units: WindowFrameUnits,
+    pub start_bound: WindowFrameBound,
+    pub end_bound: WindowFrameBound,
+}
+
+/// A finite window-frame displacement. Intervals are normalized to Arrow's
+/// month/day/nanosecond representation so SQL `RANGE INTERVAL ...` bounds
+/// survive lowering without leaking DataFusion types into the canonical IR.
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+#[serde(rename_all = "snake_case")]
+pub enum WindowFrameOffset {
+    Scalar(ScalarValue),
+    Interval {
+        months: i32,
+        days: i32,
+        nanoseconds: i64,
+    },
+}
+
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+#[serde(rename_all = "snake_case")]
+pub enum WindowFrameUnits {
+    /// Boundaries count physical rows: `ROWS BETWEEN 2 PRECEDING AND CURRENT ROW`.
+    Rows,
+    /// Boundaries count by value-distance on the (single) `ORDER BY` column:
+    /// `RANGE BETWEEN INTERVAL '1' HOUR PRECEDING AND CURRENT ROW`.
+    Range,
+}
+
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+#[serde(rename_all = "snake_case")]
+pub enum WindowFrameBound {
+    /// `UNBOUNDED PRECEDING` is
+    /// `Preceding(WindowFrameOffset::Scalar(ScalarValue::Null))`.
+    Preceding(WindowFrameOffset),
+    CurrentRow,
+    /// `UNBOUNDED FOLLOWING` is
+    /// `Following(WindowFrameOffset::Scalar(ScalarValue::Null))`.
+    Following(WindowFrameOffset),
+}
+
+/// A symbolic label matcher on the **info metric** side of an
+/// [`crate::ir::NonASAPOp::PromqlInfoEnrich`] (issue #84). Unlike a `Scan` predicate it is not
+/// resolved positionally — it references the info metric's labels (`__name__`
+/// picks the metric, the rest constrain data labels), which aren't in the input
+/// vector's schema; the post-ASAP realization pass applies it against the info metric.
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+pub struct InfoMatcher {
+    pub label: String,
+    /// One of `Eq` / `Ne` / `Regex` / `NotRegex` (PromQL `=`/`!=`/`=~`/`!~`).
+    pub op: CompareOpKind,
+    pub value: String,
+}
+
+/// Series-sampling selection mode (PromQL `limitk` / `limit_ratio`, issue #86).
+/// A [`crate::ir::NonASAPOp::PromqlSeriesSample`] keeps a *subset of whole series*, unchanged — it does
+/// not rank or reduce, so it is distinct from `TopK` and from `Sort → Limit`.
+#[derive(Debug, Clone, Copy, PartialEq, Serialize, Deserialize)]
+#[serde(rename_all = "snake_case")]
+pub enum SampleKind {
+    /// `limitk(k, v)` — up to `k` series per group. Which series survive is
+    /// deterministic across evaluations but otherwise unspecified (no ordering).
+    LimitK(usize),
+    /// `limit_ratio(r, v)` — a deterministic `r`-fraction of series per group.
+    /// `r ∈ [-1, 1]`; a negative `r` selects the complementary fraction.
+    LimitRatio(f64),
+}
+
+/// PromQL vector-match modifier (`on`/`ignoring` + `group_left`/`group_right`).
+#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
+pub struct VectorMatch {
+    pub kind: VectorMatchKind,
+    pub labels: Vec<String>,
+    pub grouping: Option<VectorGrouping>,
+}
+
+/// PromQL `@` modifier — pins a selector's evaluation time to an anchor instead
+/// of the query evaluation time (issue #40).
+#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
+pub enum AtModifier {
+    /// `@ start()` — the query range's start instant.
+    Start,
+    /// `@ end()` — the query range's end instant.
+    End,
+    /// `@ <ts>` — an absolute instant, milliseconds since the Unix epoch (may be
+    /// negative). PromQL writes the timestamp in seconds; the front end scales it.
+    Timestamp(i64),
+}
+
+/// PromQL per-selector **time-shift** modifiers — `offset` and `@` (issue #40).
+/// Neither changes a selector's *schema*; both move *when* it is evaluated, so
+/// the shift is a pass-through wrapper ([`crate::ir::NonASAPOp::TimeShift`]) over the
+/// selector rather than a new leaf shape. The runtime resolves the anchor and
+/// applies the offset.
+#[derive(Debug, Clone, Copy, PartialEq, Eq, Default, Serialize, Deserialize)]
+pub struct TimeShift {
+    /// `offset <d>` as signed milliseconds — a positive value shifts the
+    /// lookback *back* in time (`offset 5m`), a negative value shifts it
+    /// *forward* (`offset -5m`). `0` = no offset.
+    pub offset_ms: i64,
+    /// `@` anchor; `None` = evaluate at the query time.
+    pub at: Option<AtModifier>,
+}
+
+impl TimeShift {
+    /// Whether this shift is the identity (no `offset`, no `@`) — the state of
+    /// every selector that carries neither modifier.
+    pub fn is_identity(&self) -> bool {
+        self.offset_ms == 0 && self.at.is_none()
+    }
+}
+
+#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
+pub enum VectorMatchKind {
+    On,
+    Ignoring,
+}
+
+#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
+pub struct VectorGrouping {
+    pub side: GroupSide,
+    pub labels: Vec<String>,
+}
+
+#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
+pub enum GroupSide {
+    Left,
+    Right,
+}
+
+// ── Intent algebra IR ────────────────────────────────────────────────────────
+
+/// What kind of computation an `Aggregate` node performs — orthogonal to
+/// *which* columns it groups by (that's still [`GroupKeys`], inside
+/// `Reduce`). Explicit, decided once by whichever pass constructs the node
+/// (structural, at front-end lowering time), rather than inferred downstream from
+/// whether a grouping-key list happens to be empty or from a neighboring
+/// node's shape. See design proposal #165.
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+pub enum Reduction<C = ColumnId> {
+    /// Collapses input rows via `by` — `by`/`without` semantics are exactly
+    /// [`GroupKeys`]'s. May still collapse every row into one (an empty,
+    /// non-`without` `by`) — that's a genuine reduction with zero grouping
+    /// columns, not "no grouping concept."
+    Reduce(GroupKeys<C>),
+    /// No grouping concept at all: preserves one output row per input
+    /// entity (e.g. a per-series windowed computation with no `by(...)`
+    /// clause to begin with, because there's no aggregation operator here
+    /// for such a clause to attach to). Never merges across entities, and
+    /// never collapses an entity's own row structure (e.g. a time axis) —
+    /// unlike `Reduce(GroupKeys::without(vec![]))` ("group by every
+    /// label"), which is still a genuine reduction and does collapse it.
+    PerEntity,
+}
+
+impl<C> Reduction<C> {
+    /// Shorthand for the common case — group by these (possibly empty)
+    /// keys, kept rather than excluded.
+    pub fn by(keys: Vec<C>) -> Self {
+        Self::Reduce(GroupKeys::by(keys))
+    }
+
+    /// The grouping keys, if this is a genuine reduction — `None` for
+    /// `PerEntity`, which has no grouping-keys concept to report.
+    pub fn group_keys(&self) -> Option<&GroupKeys<C>> {
+        match self {
+            Self::Reduce(by) => Some(by),
+            Self::PerEntity => None,
+        }
+    }
+
+    /// The grouping keys, panicking if this is `PerEntity` — for call sites
+    /// (tests, mostly) that already know, from the shape they built or are
+    /// asserting on, that this must be a genuine reduction. Prefer
+    /// [`group_keys`](Self::group_keys) wherever the caller can't assume that.
+    pub fn expect_reduce(&self) -> &GroupKeys<C> {
+        match self {
+            Self::Reduce(by) => by,
+            Self::PerEntity => panic!("expected Reduction::Reduce, got PerEntity"),
+        }
+    }
+}
+
+/// A caller-proven compound unique key for a [`crate::ir::NonASAPOp::Concat`] (issue
+/// #228) — built only via [`ConcatDiscriminatorKey::new`], never by naming `discriminator` directly
+/// in a struct literal (both fields are private): from *other Rust code*,
+/// the only way to end up with one of these is to hand over a specific
+/// column as the discriminator, by name, at the call site.
+///
+/// Caveat: this is a Rust-API-level guarantee, not a data-level one. The
+/// derived `Deserialize` impl below builds a `ConcatDiscriminatorKey`
+/// directly from field values, bypassing `new()`. Deserialization is therefore
+/// equivalent to a caller supplying the assertion directly; it does not prove
+/// either fact below. An external boundary accepting IR data must
+/// reject this field or validate both obligations before treating it as
+/// uniqueness evidence.
+///
+/// # Soundness
+///
+/// `Concat`'s default (see its own doc) is to drop `unique_keys`
+/// unconditionally, because a key unique **within** one branch is not unique
+/// **across** the concatenation unless the branches' value sets for that key
+/// are provably disjoint — nothing about matching schemas or matching
+/// per-branch keys establishes that on its own. Two different branches can
+/// trivially emit the same `inner_key` value (e.g. two PromQL
+/// `histogram_quantiles` branches keyed on `(host, le)` can both produce a
+/// `(host, le)` pair for different φ).
+///
+/// Prepending `discriminator` restores a compound key only when two facts
+/// hold: `inner_key` uniquely identifies rows **within every branch**, and
+/// `discriminator`'s value is **guaranteed to differ between branches** — a
+/// literal the producer just tagged the branch with (PromQL φ riding along via
+/// [`crate::ir::NonASAPOp::PromqlRelabel`], a Postgres-style synthetic `GROUPING()` id
+/// for `ROLLUP`/`CUBE`, …), never something inferred structurally from the
+/// branches' own data — then `discriminator` alone partitions rows into
+/// disjoint sets independent of what the branches actually contain, so
+/// `(discriminator, inner_key)` is sound even when otherwise-identical
+/// `inner_key` values occur in different branches. Neither fact is verified
+/// here; both are part of the caller-proven claim.
+///
+/// This is a **caller-proven claim, not something `Concat` can verify**:
+/// nothing stops a caller from asserting a discriminator that in fact
+/// repeats across branches, in which case the resulting `unique_keys` claim
+/// is simply wrong — `output_schema` trusts it without checking. The
+/// obligation is on the constructor call site, exactly as it is on
+/// [`crate::ir::NonASAPOp::Dedup`]'s `cols` or any other unverified `unique_keys`
+/// producer in this module.
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+#[serde(deny_unknown_fields)]
+#[serde(bound(serialize = "C: ColState", deserialize = "C: ColState"))]
+pub struct ConcatDiscriminatorKey<C: ColState = ColumnId> {
+    discriminator: C,
+    inner_key: Vec<C>,
+}
+
+impl<C: ColState> ConcatDiscriminatorKey<C> {
+    /// The only constructor — `discriminator` must be named explicitly by
+    /// the caller. See the type's doc for the soundness obligation this
+    /// puts on that caller.
+    pub fn new(discriminator: C, inner_key: Vec<C>) -> Self {
+        Self {
+            discriminator,
+            inner_key,
+        }
+    }
+
+    pub fn discriminator(&self) -> &C {
+        &self.discriminator
+    }
+
+    pub fn inner_key(&self) -> &[C] {
+        &self.inner_key
+    }
+}
diff --git a/crates/types/src/ir/schema_support.rs b/crates/types/src/ir/schema_support.rs
index c710c8654..95c42070d 100644
--- a/crates/types/src/ir/schema_support.rs
+++ b/crates/types/src/ir/schema_support.rs
@@ -1,5 +1,14 @@
 //! Series-identity realization for the unified dag.
 use crate::pre_asap::schema::*;
+/// Resolve a PromQL root to rows carrying [`PROMQL_SERIES_IDENTITY`] before
+/// candidate search. `closed` describes physical columns here: the final
+/// column contains every dynamic source label. It does not assert that the
+/// query's projected labels are the full label set.
+///
+/// This realization supports explicit `by` grouping and per-series computation.
+/// Operators that rewrite or implicitly match dynamic label sets require their
+/// own realization; they must not accidentally treat the opaque identity as a
+/// user label or silently discard it.
 pub fn with_promql_series_identity(
     root: &std::rc::Rc<crate::ir::OperatorNode>,
 ) -> Result<std::rc::Rc<crate::ir::OperatorNode>, String> {
diff --git a/crates/types/src/lib.rs b/crates/types/src/lib.rs
index 9fc450c7f..9252ac806 100644
--- a/crates/types/src/lib.rs
+++ b/crates/types/src/lib.rs
@@ -1,26 +1,22 @@
 //! `asap-types` — shared vocabulary for the whole workspace.
 //!
-//! Merges the former `asap-ir` crate (the pre-ASAP intent algebra,
-//! workload/batch types, and DAG export) with the data-type-only modules of
-//! the former `asap-sketch` crate (the post-ASAP sketch-bound IR types,
-//! under [`post_asap`]).
-//!
-//! - [`pre_asap`] / [`types`] / [`workload`] / [`dag_export`] — the
-//!   pre-ASAP IR: language-agnostic query intent, independent of any
-//!   sketch decision.
-//! - [`post_asap`] — the post-ASAP IR: sketch-bound types
-//!   ([`post_asap::sketch`], [`post_asap::expr`], [`post_asap::schema`])
-//!   that commit to a concrete `SummaryKind`/`SummaryParams` realization.
-//!   No execution logic lives in this workspace (see issue #190) — a
-//!   downstream deployment crate is expected to supply that.
-//!   [`post_asap::query_time`] is the one exception, folder-separated from
-//!   the rest of `post_asap` on purpose: pure, sketch-object-agnostic
-//!   posterior error-bound math (issue #239) that a future real sketch
-//!   runtime's readout path can call directly — see that module's docs
-//!   for the planning-time/execution-time boundary and why it's unwired
-//!   today.
+//! - [`ir`] — the unified operator IR: one operator language before and
+//!   after ASAP optimization ([`ir::OperatorNode`]), plus its passes
+//!   (canonicalize, CSE, timing) and the wire export ([`ir::export`]).
+//! - [`pre_asap`] — the shared field vocabulary the IR's operators are
+//!   built from (grouping keys, reductions, sources, aggregation intents,
+//!   scalar literal / operator kinds, [`pre_asap::Schema`]).
+//! - [`post_asap`] — summary-state types (families, kinds, parameters,
+//!   grouping strategy), accuracy guarantees, and the execution-timing
+//!   vocabulary. No execution logic lives in this workspace (issue #190).
+//!   [`post_asap::query_time`] holds pure posterior error-bound math
+//!   (issue #239) a future sketch runtime's evaluation path can call; see its
+//!   docs for why it is unwired today.
+//! - [`types`] / [`workload`] / [`parsed_workload`] / [`dag_export`] /
+//!   [`cost`] / [`resources`] — workload, batch, export and cost types.
 pub mod cost;
 pub mod dag_export;
+pub mod ir;
 pub mod parsed_workload;
 pub mod post_asap;
 pub mod pre_asap;
@@ -28,5 +24,3 @@ pub mod resources;
 pub mod serde_f64;
 pub mod types;
 pub mod workload;
-
-pub mod ir;
diff --git a/crates/types/src/post_asap/cse.rs b/crates/types/src/post_asap/cse.rs
deleted file mode 100644
index 55889008c..000000000
--- a/crates/types/src/post_asap/cse.rs
+++ /dev/null
@@ -1,442 +0,0 @@
-//! Structural sharing for a selected workload in one execution/data scope.
-//!
-//! This is not candidate selection or a cross-request cache. Callers opt into
-//! common producer execution only after agreeing on lifecycle and data scope.
-//! Typed equality includes schemas, guarantees and complete source expressions.
-
-use std::collections::HashMap;
-use std::rc::Rc;
-
-use super::{SummaryExpr, SummaryNode};
-
-/// Numeric PartialEq alone conflates signed zeros. The serialized check is
-/// additional evidence, never a replacement for typed equality (JSON maps
-/// nonfinite floats to null). Keep this rule local to structural sharing.
-fn same_value<T: PartialEq + serde::Serialize>(left: &T, right: &T) -> bool {
-    left == right
-        && match (serde_json::to_string(left), serde_json::to_string(right)) {
-            (Ok(left), Ok(right)) => left == right,
-            _ => false,
-        }
-}
-
-/// Children have already been interned. Comparing their identities avoids
-/// recursively expanding a shared DAG once for every path to each descendant.
-fn same_node(left: &SummaryNode, right: &SummaryNode) -> bool {
-    use SummaryExpr::*;
-    let expression_equal = match (&left.expr, &right.expr) {
-        (KeepPreAsap(a), KeepPreAsap(b)) => Rc::ptr_eq(a, b) || same_value(a, b),
-        (
-            BinaryOp {
-                lhs: al,
-                rhs: ar,
-                operator: ao,
-                timing: at,
-            },
-            BinaryOp {
-                lhs: bl,
-                rhs: br,
-                operator: bo,
-                timing: bt,
-            },
-        ) => Rc::ptr_eq(al, bl) && Rc::ptr_eq(ar, br) && ao == bo && at == bt,
-        (
-            ValueOperation {
-                child: ac,
-                operation: ao,
-                timing: at,
-            },
-            ValueOperation {
-                child: bc,
-                operation: bo,
-                timing: bt,
-            },
-        ) => Rc::ptr_eq(ac, bc) && same_value(ao, bo) && at == bt,
-        (
-            RelationalJoin {
-                left: al,
-                right: ar,
-                kind: ak,
-                pred: ap,
-                pruning: ax,
-            },
-            RelationalJoin {
-                left: bl,
-                right: br,
-                kind: bk,
-                pred: bp,
-                pruning: bx,
-            },
-        ) => {
-            Rc::ptr_eq(al, bl)
-                && Rc::ptr_eq(ar, br)
-                && ak == bk
-                && same_value(ap, bp)
-                && same_value(ax, bx)
-        }
-        (
-            SummaryAgg {
-                child: ac,
-                family: af,
-                input: ai,
-                reduction: ar,
-                grouping: ag,
-                filter: afl,
-            },
-            SummaryAgg {
-                child: bc,
-                family: bf,
-                input: bi,
-                reduction: br,
-                grouping: bg,
-                filter: bfl,
-            },
-        ) => {
-            Rc::ptr_eq(ac, bc)
-                && af == bf
-                && same_value(ai, bi)
-                && ar == br
-                && ag == bg
-                && same_value(afl, bfl)
-        }
-        (
-            SummaryJoin {
-                outer: ao,
-                inner: ai,
-                key: ak,
-                family: af,
-            },
-            SummaryJoin {
-                outer: bo,
-                inner: bi,
-                key: bk,
-                family: bf,
-            },
-        ) => Rc::ptr_eq(ao, bo) && Rc::ptr_eq(ai, bi) && ak == bk && af == bf,
-        (
-            SummarySubtract {
-                left: al,
-                right: ar,
-            },
-            SummarySubtract {
-                left: bl,
-                right: br,
-            },
-        ) => Rc::ptr_eq(al, bl) && Rc::ptr_eq(ar, br),
-        (
-            SummaryEstimate {
-                summary_input: ai,
-                query: aq,
-            },
-            SummaryEstimate {
-                summary_input: bi,
-                query: bq,
-            },
-        ) => Rc::ptr_eq(ai, bi) && same_value(aq, bq),
-        (
-            SummaryDelete {
-                summary_input: ai,
-                key: ak,
-            },
-            SummaryDelete {
-                summary_input: bi,
-                key: bk,
-            },
-        ) => Rc::ptr_eq(ai, bi) && ak == bk,
-        (
-            SummaryMerge {
-                children: a,
-                timing: at,
-            },
-            SummaryMerge {
-                children: b,
-                timing: bt,
-            },
-        ) => at == bt && a.len() == b.len() && a.iter().zip(b).all(|(a, b)| Rc::ptr_eq(a, b)),
-        // Keep this exhaustive on the left: new variants require a sharing rule.
-        (
-            KeepPreAsap(_)
-            | BinaryOp { .. }
-            | ValueOperation { .. }
-            | RelationalJoin { .. }
-            | SummaryAgg { .. }
-            | SummaryJoin { .. }
-            | SummarySubtract { .. }
-            | SummaryEstimate { .. }
-            | SummaryDelete { .. }
-            | SummaryMerge { .. },
-            _,
-        ) => false,
-    };
-    expression_equal && left.schema == right.schema && same_value(&left.guarantee, &right.guarantee)
-}
-
-/// Intern equal selected sub-DAGs across roots while preserving every root ID.
-///
-/// Only structural equality is used: no grouping, parameter, accuracy or source
-/// coercions are performed. All roots must belong to the same data snapshot or
-/// maintenance scope. Downstream realization must still check physical
-/// implementation compatibility. Use separate calls for independent executions.
-///
-/// When the selected states are identical, this is the planner's
-/// summary-capability rule (#509 Pass 2): one summary build node feeds every
-/// readout it supports, e.g. one KLL for p50 and p99, or one UnivMon for
-/// distinct count, entropy and L2. Candidate generation sizes a variant for
-/// the strictest sibling consumer so differing accuracy targets can reach
-/// identical states here.
-pub fn share_common_summary_sub_dags<Id>(
-    roots: Vec<(Id, Rc<SummaryNode>)>,
-) -> Vec<(Id, Rc<SummaryNode>)> {
-    fn visit(
-        node: &Rc<SummaryNode>,
-        seen: &mut HashMap<usize, Rc<SummaryNode>>,
-        pool: &mut Vec<Rc<SummaryNode>>,
-    ) -> Rc<SummaryNode> {
-        let identity = Rc::as_ptr(node) as usize;
-        if let Some(node) = seen.get(&identity) {
-            return Rc::clone(node);
-        }
-        let mut result = node.as_ref().clone();
-        match &mut result.expr {
-            SummaryExpr::KeepPreAsap(_) => {}
-            SummaryExpr::SummaryAgg { child, .. } => *child = visit(child, seen, pool),
-            SummaryExpr::BinaryOp { lhs, rhs, .. } => {
-                *lhs = visit(lhs, seen, pool);
-                *rhs = visit(rhs, seen, pool);
-            }
-
-            SummaryExpr::ValueOperation { child, .. } => *child = visit(child, seen, pool),
-            SummaryExpr::RelationalJoin { left, right, .. } => {
-                *left = visit(left, seen, pool);
-                *right = visit(right, seen, pool);
-            }
-            SummaryExpr::SummaryJoin { outer, inner, .. } => {
-                *outer = visit(outer, seen, pool);
-                *inner = visit(inner, seen, pool);
-            }
-            SummaryExpr::SummarySubtract { left, right } => {
-                *left = visit(left, seen, pool);
-                *right = visit(right, seen, pool);
-            }
-            SummaryExpr::SummaryEstimate { summary_input, .. }
-            | SummaryExpr::SummaryDelete { summary_input, .. } => {
-                *summary_input = visit(summary_input, seen, pool);
-            }
-            SummaryExpr::SummaryMerge { children, .. } => {
-                for child in children {
-                    *child = visit(child, seen, pool);
-                }
-            }
-        }
-        let result = match pool.iter().find(|existing| same_node(existing, &result)) {
-            Some(existing) => Rc::clone(existing),
-            None => {
-                let result = Rc::new(result);
-                pool.push(Rc::clone(&result));
-                result
-            }
-        };
-        seen.insert(identity, Rc::clone(&result));
-        result
-    }
-    let mut seen = HashMap::new();
-    let mut pool = Vec::new();
-    roots
-        .into_iter()
-        .map(|(id, root)| (id, visit(&root, &mut seen, &mut pool)))
-        .collect()
-}
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-    use crate::post_asap::{ResultGuarantee, Schema};
-    use crate::pre_asap::{QueryExpr, ScalarValue};
-
-    fn leaf(value: f64) -> Rc<SummaryNode> {
-        Rc::new(SummaryNode {
-            expr: SummaryExpr::KeepPreAsap(Rc::new(QueryExpr::Literal(ScalarValue::Float64(
-                value,
-            )))),
-            schema: Schema::lifted(vec![], None),
-            guarantee: Some(ResultGuarantee::exact("fixture")),
-        })
-    }
-
-    // Equal separately constructed roots preserve both IDs but share identity.
-    #[test]
-    fn shares_equal_roots_and_preserves_ids() {
-        let roots = share_common_summary_sub_dags(vec![("a", leaf(1.0)), ("b", leaf(1.0))]);
-        assert_eq!(roots[0].0, "a");
-        assert_eq!(roots[1].0, "b");
-        assert!(Rc::ptr_eq(&roots[0].1, &roots[1].1));
-    }
-
-    // A diamond is retained across the returned roots, not copied per consumer.
-    #[test]
-    fn shares_children_across_distinct_roots() {
-        let merge = Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryMerge {
-                timing: crate::post_asap::ExecutionTiming::IngestionTime,
-                children: vec![leaf(1.0), leaf(2.0)],
-            },
-            schema: Schema::lifted(vec![], None),
-            guarantee: None,
-        });
-        let roots = share_common_summary_sub_dags(vec![(0, leaf(1.0)), (1, merge)]);
-        let SummaryExpr::SummaryMerge { children, .. } = &roots[1].1.expr else {
-            panic!()
-        };
-        assert!(Rc::ptr_eq(&roots[0].1, &children[0]));
-        assert!(!Rc::ptr_eq(&children[0], &children[1]));
-    }
-
-    // Unknown guarantees must not be replaced by an equal expression's exact guarantee.
-    #[test]
-    fn distinct_guarantees_and_values_are_not_shared() {
-        let mut unknown = leaf(1.0).as_ref().clone();
-        unknown.guarantee = None;
-        let roots = share_common_summary_sub_dags(vec![
-            (0, leaf(1.0)),
-            (1, Rc::new(unknown)),
-            (2, leaf(2.0)),
-        ]);
-        assert!(!Rc::ptr_eq(&roots[0].1, &roots[1].1));
-        assert!(!Rc::ptr_eq(&roots[0].1, &roots[2].1));
-        assert!(roots[1].1.guarantee.is_none());
-    }
-
-    // Sharing must preserve IEEE signed zero, including inside exact expressions.
-    #[test]
-    fn signed_zero_is_not_coalesced() {
-        for values in [[0.0, -0.0], [-0.0, 0.0]] {
-            let roots =
-                share_common_summary_sub_dags(vec![(0, leaf(values[0])), (1, leaf(values[1]))]);
-            assert!(!Rc::ptr_eq(&roots[0].1, &roots[1].1));
-            for ((_, root), expected) in roots.iter().zip(values) {
-                let SummaryExpr::KeepPreAsap(expr) = &root.expr else {
-                    panic!()
-                };
-                let QueryExpr::Literal(ScalarValue::Float64(actual)) = expr.as_ref() else {
-                    panic!()
-                };
-                assert_eq!(actual.to_bits(), expected.to_bits());
-                assert_eq!(1.0 / actual, 1.0 / expected);
-            }
-        }
-    }
-
-    // Exact expression wrappers must retain signed zero too; JSON's null
-    // encoding of nonfinite floats must never become the equality decision.
-    #[test]
-    fn nested_values_and_nonfinite_values_remain_distinct() {
-        let wrapped = |value| {
-            Rc::new(SummaryNode {
-                expr: SummaryExpr::KeepPreAsap(Rc::new(QueryExpr::promql_scalar(value))),
-                ..leaf(1.0).as_ref().clone()
-            })
-        };
-        for (a, b) in [
-            (0.0, -0.0),
-            (f64::INFINITY, f64::NEG_INFINITY),
-            (f64::NAN, f64::NAN),
-        ] {
-            let roots = share_common_summary_sub_dags(vec![(0, wrapped(a)), (1, wrapped(b))]);
-            assert!(!Rc::ptr_eq(&roots[0].1, &roots[1].1));
-        }
-        let roots = share_common_summary_sub_dags(vec![
-            (0, wrapped(f64::INFINITY)),
-            (1, wrapped(f64::INFINITY)),
-        ]);
-        assert!(Rc::ptr_eq(&roots[0].1, &roots[1].1));
-    }
-
-    // Distinct quantile readouts share only a compatible typed sketch producer.
-    #[test]
-    fn quantile_roots_share_producer_but_not_readout_or_parameters() {
-        use crate::post_asap::{
-            FieldDataType, GroupingStrategy, SketchAlgorithm, SketchKind, SketchParams,
-            SketchStatistic, SummaryUpdate,
-        };
-        use crate::pre_asap::{ColumnRef, Reduction};
-        fn readout(q: f64, alpha: f64) -> Rc<SummaryNode> {
-            let producer = Rc::new(SummaryNode {
-                expr: SummaryExpr::SummaryAgg {
-                    child: leaf(1.0),
-                    family: FieldDataType::Sketch(
-                        SketchKind::new(
-                            SketchAlgorithm::DDSketch,
-                            SketchParams::DDSketch { alpha },
-                        ),
-                        GroupingStrategy::default(),
-                    ),
-                    input: SummaryUpdate::column(ColumnRef::SampleValue),
-                    reduction: Reduction::PerEntity,
-                    grouping: GroupingStrategy::default(),
-                    filter: None,
-                },
-                schema: Schema::lifted(vec![], None),
-                guarantee: None,
-            });
-            Rc::new(SummaryNode {
-                expr: SummaryExpr::SummaryEstimate {
-                    summary_input: producer,
-                    query: SketchStatistic::Quantile { q },
-                },
-                schema: Schema::lifted(vec![], None),
-                guarantee: None,
-            })
-        }
-        let roots = share_common_summary_sub_dags(vec![
-            ("p95", readout(0.95, 0.01)),
-            ("p99", readout(0.99, 0.01)),
-            ("strict", readout(0.95, 0.001)),
-        ]);
-        let producer = |root: &Rc<SummaryNode>| match &root.expr {
-            SummaryExpr::SummaryEstimate { summary_input, .. } => Rc::clone(summary_input),
-            _ => panic!(),
-        };
-        assert!(!Rc::ptr_eq(&roots[0].1, &roots[1].1));
-        assert!(Rc::ptr_eq(&producer(&roots[0].1), &producer(&roots[1].1)));
-        assert!(!Rc::ptr_eq(&producer(&roots[0].1), &producer(&roots[2].1)));
-    }
-
-    // Fifty unique input nodes must not require walking an expanded 2^24 DAG.
-    // The timeout is a coarse runaway guard, not a performance SLA.
-    #[test]
-    fn shared_diamond_does_not_expand_during_comparison() {
-        let (done, completion) = std::sync::mpsc::channel();
-        let worker = std::thread::spawn(move || {
-            fn diamond() -> Rc<SummaryNode> {
-                let mut current = leaf(1.0);
-                for _ in 0..24 {
-                    current = Rc::new(SummaryNode {
-                        expr: SummaryExpr::BinaryOp {
-                            timing: super::super::ExecutionTiming::QueryTime,
-                            lhs: Rc::clone(&current),
-                            rhs: current,
-                            operator: super::super::BinaryOperator {
-                                checked_relative_division: false,
-                                checked_finite_division: false,
-                                kind: crate::pre_asap::BinaryOpKind::Arithmetic(
-                                    crate::pre_asap::ArithmeticOpKind::Add,
-                                ),
-                                vector_match: None,
-                            },
-                        },
-                        schema: super::super::Schema::lifted(vec![], None),
-                        guarantee: None,
-                    });
-                }
-                current
-            }
-            let roots = share_common_summary_sub_dags(vec![(0, diamond()), (1, diamond())]);
-            assert!(Rc::ptr_eq(&roots[0].1, &roots[1].1));
-            done.send(()).unwrap();
-        });
-        completion
-            .recv_timeout(std::time::Duration::from_secs(5))
-            .expect("comparison expanded the shared DAG");
-        worker.join().unwrap();
-    }
-}
diff --git a/crates/types/src/post_asap/execution_data_state.rs b/crates/types/src/post_asap/execution_data_state.rs
index 38219fa2c..de764ea2c 100644
--- a/crates/types/src/post_asap/execution_data_state.rs
+++ b/crates/types/src/post_asap/execution_data_state.rs
@@ -1,56 +1,14 @@
-//! Execution-data-state contract for mixed exact/summary plans (issue #171).
+//! Execution timing and data-state vocabulary of the operator IR.
 //!
-//! A post-ASAP DAG mixes two very different moments of execution: the
-//! **update/ingest path** (rows arrive, maintained summary state is updated)
-//! and **query evaluation** (maintained state is read out and a final result
-//! is produced). A plan that places a query-time residual *underneath* a
-//! maintained summary is not merely expensive — it is unexecutable, because
-//! the maintenance loop has no readout values to feed into that summary.
-//! [`SummaryExpr::ValueOperation`] represents such work without inventing a
-//! node per function or use case. Its [`ExecutionTiming`] makes placement
-//! explicit and independent of the semantic [`ValueOperation`].
-//!
-//! [`ExecutionDataState`] is what a node's output *is*, at which data_state;
-//! [`validate_execution_data_states`] checks every edge of a DAG against the
-//! rules below at plan construction, returning a typed [`ExecutionDataStateError`] rather
-//! than deferring to a runtime failure.
-//!
-//! ## Edge rules
-//!
-//! | Parent | Accepts from `child` |
-//! |---|---|
-//! | `SummaryAgg.child` | Rows or exact accumulator state at either phase. The initial construction phase follows the input; deployment assigns final phases. |
-//! | `SummaryEstimate.summary_input` | Summary state at either phase (any family). Initial readout produces `QUERY_ROWS`. |
-//! | `SummaryJoin.outer/inner` | `INGESTION_ROWS` or `INGESTION_SUMMARY`; never a read-time data_state. |
-//! | `SummarySubtract`/`SummaryDelete` | `INGESTION_SUMMARY`. |
-//! | `SummaryMerge` | Summary state at its explicit ingestion or read timing. |
-//! | `ValueOperation.child` with `IngestionTime` | `INGESTION_ROWS`; explicit `FinalizeExactAccumulator` also accepts exact accumulator state. Produces `INGESTION_ROWS`. |
-//! | `ValueOperation.child` with `QueryTime` | `QUERY_ROWS`. Produces `QUERY_ROWS`. |
-//!
-//! ## `KeepPreAsap` declares its data_state through the derivation
-//!
-//! A [`SummaryExpr::KeepPreAsap`] leaf is a raw pre-ASAP computation that a
-//! runtime can execute at either time: as maintenance input beneath a
-//! `SummaryAgg`/maintenance-time `ValueOperation`, or as a query-time fallback
-//! beneath a read-time `ValueOperation` (or at the root). It carries no timing
-//! field of its own
-//! — every existing consumer pattern-matches the one-field shape — so its
-//! data_state is *assigned* by [`validate_execution_data_states`] from the edge that
-//! reaches it and reported in the returned [`ExecutionDataStateAssignment`]. What it may
-//! not do is stay ambiguous inside one mixed plan: the same `Rc<SummaryNode>`
-//! reached once as update input and once as query-time fallback is
-//! [`ExecutionDataStateError::AmbiguousKeepPreAsap`], because no single execution of that
-//! sub-DAG can serve both roles.
-
-use std::collections::HashMap;
-use std::rc::Rc;
+//! [`ExecutionTiming`] says when a node's value is produced (ingestion vs.
+//! query time); [`ExecutionDataState`] pairs it with the [`DataPrimitive`]
+//! the edge carries (raw values vs. summary state). The rules that assign
+//! and check them over a DAG live in [`crate::ir::timing`], which reports
+//! violations as [`ExecutionDataStateError`].
 
 use thiserror::Error;
 
-use super::expr::{ExactOperation, SummaryExpr, SummaryNode, ValueOperation};
-use crate::pre_asap::schema::FieldDataType;
-
-use crate::pre_asap::query_expr::{aggregate_output_schema, Predicate, QueryExprError};
+use crate::ir::SchemaDerivationError;
 use crate::pre_asap::schema::Schema;
 
 /// When a post-ASAP value is produced.
@@ -79,7 +37,7 @@ impl ExecutionTiming {
 /// The primitive representation carried by a post-ASAP edge.
 #[derive(Debug, Clone, Copy, PartialEq, Eq, Hash, serde::Serialize, serde::Deserialize)]
 pub enum DataPrimitive {
-    /// Directly usable values, including approximate summary readouts.
+    /// Directly usable values, including approximate summary evaluations.
     /// This does not imply original input data or an exact guarantee.
     Raw,
     SummaryState,
@@ -123,67 +81,27 @@ impl std::fmt::Display for ExecutionDataState {
     }
 }
 
-/// Which parent/edge a [`ExecutionDataStateError`] is about — the variant name of the
-/// parent `SummaryExpr` plus its field, for a message a plan author can act
-/// on.
-#[derive(Debug, Clone, Copy, PartialEq, Eq)]
-pub enum ExecutionDataStateEdge {
-    SummaryAggChild,
-    SummaryEstimateInput,
-    SummaryJoinInput,
-    SummarySubtractInput,
-    SummaryDeleteInput,
-    SummaryMergeInput,
-    ValueOperationChild,
-}
-
-impl ExecutionDataStateEdge {
-    fn describe(self) -> &'static str {
-        match self {
-            Self::SummaryAggChild => "SummaryAgg.child",
-            Self::SummaryEstimateInput => "SummaryEstimate.summary_input",
-            Self::SummaryJoinInput => "SummaryJoin.{outer,inner}",
-            Self::SummarySubtractInput => "SummarySubtract.{left,right}",
-            Self::SummaryDeleteInput => "SummaryDelete.summary_input",
-            Self::SummaryMergeInput => "SummaryMerge.children[]",
-            Self::ValueOperationChild => "ValueOperation.child",
-        }
-    }
-}
-
 /// A plan-construction-time data_state violation. Typed (not a string) so a
 /// strategy can degrade to a conservative fallback on the specific variant
 /// it expects, and so tests can assert the *reason* a plan was rejected.
 #[derive(Debug, Clone, PartialEq, Eq, Error)]
 pub enum ExecutionDataStateError {
-    #[error("operator reached with conflicting execution timings: {first:?} and {second:?}")]
-    ConflictingTiming {
-        first: ExecutionDataState,
-        second: ExecutionDataState,
-    },
-    #[error("{operator} node has no execution timing")]
-    UntimedNode { operator: &'static str },
-    #[error("evaluation value under maintenance: {edge} received {child}")]
-    EvaluationUnderMaintenance {
-        edge: &'static str,
-        child: ExecutionDataState,
-    },
-    #[error("invalid maintained-population maintenance/readout contract")]
+    #[error("invalid maintained-population maintenance/evaluation contract")]
     InvalidMaintainedPopulation,
-    /// A query-time value (`SummaryEstimate` / read-time `ValueOperation` output)
+    /// A query-time value (a `SummaryEstimate` or query-time operator output)
     /// placed beneath a maintained summary — the one shape issue #171's
     /// data_state split exists to make unrepresentable.
     #[error(
-        "readout value under maintenance: {edge} received a {child} input, but a maintained \
+        "evaluation value under maintenance: {edge} received a {child} input, but a maintained \
          summary can only consume update-path values (or exact accumulator state)"
     )]
-    ReadoutUnderMaintenance {
+    EvaluationUnderMaintenance {
         edge: &'static str,
         child: ExecutionDataState,
     },
     /// Any other edge whose child data_state the parent does not accept
     /// (e.g. plain update rows fed straight into a `SummaryEstimate`, or a
-    /// sketch's opaque state fed into a read-time `ValueOperation`).
+    /// sketch's opaque state fed into a query-time operator).
     #[error("{edge} does not accept a {child} input")]
     IllegalChildDataState {
         edge: &'static str,
@@ -197,13 +115,10 @@ pub enum ExecutionDataStateError {
          composed into another maintained summary"
     )]
     UnsupportedStateComposition { family: String },
-    /// One shared `KeepPreAsap` node reached both as update-path raw input
-    /// and as a query-time fallback — see the module docs.
-    #[error(
-        "KeepPreAsap sub-DAG is data_state-ambiguous: reached as {first} and as {second} in the same \
-         plan"
-    )]
-    AmbiguousKeepPreAsap {
+    /// One shared node assigned two different execution timings by its
+    /// consumers; no single execution of it can serve both.
+    #[error("shared node is assigned conflicting timings: {first} and {second}")]
+    ConflictingTiming {
         first: ExecutionDataState,
         second: ExecutionDataState,
     },
@@ -215,7 +130,7 @@ pub enum ExecutionDataStateError {
     InvalidMaintenanceBinary,
     #[error("checked division requires one valid guard on a read-time division operator")]
     InvalidCheckedDivision,
-    /// An `ExactOperation` whose input columns are not all `Plain` at its
+    /// An exact operator whose input columns are not all `Plain` at its
     /// declared data_state.
     #[error("exact operator consumes non-plain column {column:?} ({dtype})")]
     NonPlainOperand { column: String, dtype: String },
@@ -223,564 +138,10 @@ pub enum ExecutionDataStateError {
     /// `SummaryDelete`, `SummaryJoin`, `Extension`) in an executable plan.
     #[error("{operator} is a reserved operator with no execution contract yet")]
     UnimplementedOperator { operator: &'static str },
-}
-
-/// The data_state assigned to every node of a validated plan, keyed by
-/// `Rc<SummaryNode>` pointer identity — the explicit per-node "execution_data_state" a
-/// runtime or a DAG export reads instead of re-deriving it. For every
-/// non-`KeepPreAsap` node this equals [`produced_data_state`]; for a
-/// `KeepPreAsap` leaf it is the data_state the reaching edge assigned.
-#[derive(Debug, Clone, Default)]
-pub struct ExecutionDataStateAssignment {
-    domains: HashMap<*const SummaryNode, ExecutionDataState>,
-}
-
-impl ExecutionDataStateAssignment {
-    /// The data_state assigned to `node`, if it was part of the validated plan.
-    pub fn data_state_of(&self, node: &Rc<SummaryNode>) -> Option<ExecutionDataState> {
-        self.domains.get(&Rc::as_ptr(node)).copied()
-    }
-
-    /// The data_state assigned to the node at `ptr` — for callers walking a plan
-    /// by reference rather than by `Rc`.
-    pub fn data_state_of_ptr(&self, ptr: *const SummaryNode) -> Option<ExecutionDataState> {
-        self.domains.get(&ptr).copied()
-    }
-}
-
-/// Initial layout proposed by semantic realization, not a restriction on physical
-/// operator placement. `PostAsapDAG::with_execution_phases` assigns the final
-/// phase independently of payload kind. Returns `None` for
-/// [`SummaryExpr::KeepPreAsap`], whose data_state is assigned by the edge reaching
-/// it (see the module docs).
-pub fn produced_data_state(expr: &SummaryExpr) -> Option<ExecutionDataState> {
-    Some(match expr {
-        SummaryExpr::KeepPreAsap(_) => return None,
-        SummaryExpr::BinaryOp { timing, .. } => ExecutionDataState {
-            timing: *timing,
-            primitive: DataPrimitive::Raw,
-        },
-        SummaryExpr::RelationalJoin { .. } => ExecutionDataState::QUERY_ROWS,
-        SummaryExpr::SummaryAgg { child, .. } => ExecutionDataState {
-            timing: produced_data_state(&child.expr)
-                .map_or(ExecutionTiming::IngestionTime, |state| state.timing),
-            primitive: DataPrimitive::SummaryState,
-        },
-        SummaryExpr::SummaryJoin { .. }
-        | SummaryExpr::SummarySubtract { .. }
-        | SummaryExpr::SummaryDelete { .. } => ExecutionDataState::INGESTION_SUMMARY,
-        SummaryExpr::SummaryMerge { timing, .. } => ExecutionDataState {
-            timing: *timing,
-            primitive: DataPrimitive::SummaryState,
-        },
-        SummaryExpr::SummaryEstimate { .. } => ExecutionDataState::QUERY_ROWS,
-        SummaryExpr::ValueOperation { timing, .. } => match timing {
-            ExecutionTiming::IngestionTime => ExecutionDataState::INGESTION_ROWS,
-            ExecutionTiming::QueryTime => ExecutionDataState::QUERY_ROWS,
-        },
-    })
-}
-
-/// Is `family` the exact-accumulator family whose partial state *is* the
-/// value — the one summary state a `SummaryAgg` may re-accumulate?
-fn is_exact_accumulator_state(schema: &Schema) -> Result<(), ExecutionDataStateError> {
-    for field in &schema.fields {
-        match &field.dtype {
-            FieldDataType::Plain(_) | FieldDataType::ExactAggregate(..) => {}
-            other => {
-                return Err(ExecutionDataStateError::UnsupportedStateComposition {
-                    family: format!("{other:?}"),
-                })
-            }
-        }
-    }
-    Ok(())
-}
-
-/// Validate every edge of the DAG rooted at `root` against the module-level
-/// rules, returning each node's assigned data_state on success. Shared
-/// `Rc<SummaryNode>`s are visited once per reaching edge (the assignment is
-/// per node, so a conflict between two edges is what
-/// [`ExecutionDataStateError::AmbiguousKeepPreAsap`] detects).
-pub fn validate_execution_data_states(
-    root: &Rc<SummaryNode>,
-) -> Result<ExecutionDataStateAssignment, ExecutionDataStateError> {
-    // The root may be a readable value or bare maintained state (a
-    // deployment may hand an `ExactAggregate` accumulator straight to a
-    // consumer) — only an update-path-only root is meaningless.
-    let root_domain = match produced_data_state(&root.expr) {
-        None => ExecutionDataState::QUERY_ROWS,
-        Some(ExecutionDataState::INGESTION_ROWS) => {
-            return Err(ExecutionDataStateError::MaintenanceRowsAtRoot)
-        }
-        Some(data_state) => data_state,
-    };
-    validate_execution_data_states_at(root, root_domain)
-}
-
-/// [`validate_execution_data_states`] for a *sub*-plan whose root is known to
-/// sit at `data_state` — e.g. a maintenance-time `ValueOperation` about to be placed beneath a
-/// `SummaryAgg`, which would be rejected as a whole-plan root but is a
-/// legal update-path input. Validates every edge beneath `root` exactly
-/// as the whole-plan entry point does.
-pub fn validate_execution_data_states_at(
-    root: &Rc<SummaryNode>,
-    data_state: ExecutionDataState,
-) -> Result<ExecutionDataStateAssignment, ExecutionDataStateError> {
-    let mut assignment = ExecutionDataStateAssignment::default();
-    visit(root, data_state, &mut assignment)?;
-    Ok(assignment)
-}
-
-/// The source rows whose series a maintenance operand has one row for: a
-/// finalized per-series Sum or Count of those rows, or aligned arithmetic of
-/// operands over the same rows. Each emits exactly the series with a sample.
-fn per_series_rows(node: &SummaryNode) -> Option<&crate::pre_asap::QueryExpr> {
-    use crate::post_asap::ExactKind;
-    match &node.expr {
-        SummaryExpr::ValueOperation {
-            child,
-            operation: ValueOperation::FinalizeExactAccumulator,
-            ..
-        } => match &child.expr {
-            SummaryExpr::SummaryAgg {
-                child,
-                family: FieldDataType::ExactAggregate(ExactKind::Sum | ExactKind::Count, _),
-                reduction: crate::pre_asap::query_expr::Reduction::PerEntity,
-                ..
-            } => match &child.expr {
-                SummaryExpr::KeepPreAsap(rows) => Some(rows.as_ref()),
-                _ => None,
-            },
-            _ => None,
-        },
-        SummaryExpr::BinaryOp {
-            lhs,
-            rhs,
-            timing: ExecutionTiming::IngestionTime,
-            ..
-        } => {
-            let rows = per_series_rows(lhs)?;
-            (per_series_rows(rhs) == Some(rows)).then_some(rows)
-        }
-        _ => None,
-    }
-}
-
-/// Record `data_state` for `node` (detecting a conflicting earlier assignment
-/// for a `KeepPreAsap`), then check and recurse into every child edge.
-fn visit(
-    node: &Rc<SummaryNode>,
-    data_state: ExecutionDataState,
-    assignment: &mut ExecutionDataStateAssignment,
-) -> Result<(), ExecutionDataStateError> {
-    let ptr = Rc::as_ptr(node);
-    if let Some(previous) = assignment.domains.get(&ptr) {
-        if *previous != data_state {
-            return Err(ExecutionDataStateError::AmbiguousKeepPreAsap {
-                first: *previous,
-                second: data_state,
-            });
-        }
-        // Already validated through another edge with the same data_state.
-        return Ok(());
-    }
-    assignment.domains.insert(ptr, data_state);
-
-    match &node.expr {
-        SummaryExpr::KeepPreAsap(_) => Ok(()),
-        SummaryExpr::BinaryOp {
-            lhs,
-            rhs,
-            timing,
-            operator,
-        } => {
-            if (operator.checked_relative_division && operator.checked_finite_division)
-                || (operator.checked_relative_division || operator.checked_finite_division)
-                    && (*timing != ExecutionTiming::QueryTime
-                        || !matches!(
-                            operator.kind,
-                            crate::pre_asap::BinaryOpKind::Arithmetic(
-                                crate::pre_asap::ArithmeticOpKind::Div
-                            )
-                        ))
-            {
-                return Err(ExecutionDataStateError::InvalidCheckedDivision);
-            }
-            if *timing == ExecutionTiming::IngestionTime {
-                use crate::pre_asap::{BinaryOpKind, DataType};
-                if operator.vector_match.is_some()
-                    || !matches!(operator.kind, BinaryOpKind::Arithmetic(_))
-                    || lhs.schema != rhs.schema
-                    || lhs.schema != node.schema
-                    // The opaque identity is a key, not an extra maintenance value.
-                    || node.schema.fields.iter().filter(|field| {
-                        field.name == crate::pre_asap::schema::PROMQL_SERIES_IDENTITY
-                    }).count() > 1
-                    // Maintenance arithmetic pairs every row by identity, while
-                    // Prometheus drops unmatched series; it is exact only when
-                    // both operands provably produce the same series.
-                    || node.schema.fields.iter().any(|field| {
-                        field.name == crate::pre_asap::schema::PROMQL_SERIES_IDENTITY
-                    }) && per_series_rows(lhs).is_none_or(|rows| per_series_rows(rhs) != Some(rows))
-                    || !node.schema.fields.iter().all(|field| {
-                        !field.nullable
-                            && if field.name == crate::pre_asap::schema::PROMQL_SERIES_IDENTITY {
-                                field.dtype == FieldDataType::Plain(DataType::Utf8)
-                            } else {
-                                matches!(
-                                    field.dtype,
-                                    FieldDataType::Plain(DataType::Float64 | DataType::Timestamp)
-                                )
-                            }
-                    })
-                    || node
-                        .schema
-                        .fields
-                        .iter()
-                        .filter(|field| {
-                            matches!(field.dtype, FieldDataType::Plain(DataType::Float64))
-                        })
-                        .count()
-                        != 1
-                {
-                    return Err(ExecutionDataStateError::InvalidMaintenanceBinary);
-                }
-            }
-            let expected = ExecutionDataState {
-                timing: *timing,
-                primitive: DataPrimitive::Raw,
-            };
-            for input in [lhs, rhs] {
-                let state = produced_data_state(&input.expr).unwrap_or(expected);
-                if state != expected {
-                    return Err(ExecutionDataStateError::IllegalChildDataState {
-                        edge: "BinaryOp operand",
-                        child: state,
-                    });
-                }
-                visit(input, state, assignment)?;
-            }
-            Ok(())
-        }
-
-        SummaryExpr::RelationalJoin { left, right, .. } => {
-            for input in [left, right] {
-                let state =
-                    produced_data_state(&input.expr).unwrap_or(ExecutionDataState::QUERY_ROWS);
-                if state != ExecutionDataState::QUERY_ROWS {
-                    return Err(ExecutionDataStateError::IllegalChildDataState {
-                        edge: "RelationalJoin input",
-                        child: state,
-                    });
-                }
-                visit(input, state, assignment)?;
-            }
-            Ok(())
-        }
-        SummaryExpr::SummaryAgg { child, .. } => {
-            let child_domain = child_domain(
-                child,
-                ExecutionDataStateEdge::SummaryAggChild,
-                |avail| match avail {
-                    ExecutionDataState::INGESTION_ROWS | ExecutionDataState::QUERY_ROWS => Ok(()),
-                    state if state.primitive == DataPrimitive::SummaryState => {
-                        is_exact_accumulator_state(&child.schema)
-                    }
-                    other => Err(ExecutionDataStateError::ReadoutUnderMaintenance {
-                        edge: ExecutionDataStateEdge::SummaryAggChild.describe(),
-                        child: other,
-                    }),
-                },
-            )?;
-            visit(child, child_domain, assignment)
-        }
-        SummaryExpr::SummaryJoin { outer, inner, .. } => {
-            for input in [outer, inner] {
-                let s = child_domain(input, ExecutionDataStateEdge::SummaryJoinInput, |avail| {
-                    match avail {
-                        ExecutionDataState::INGESTION_ROWS
-                        | ExecutionDataState::INGESTION_SUMMARY => Ok(()),
-                        other => Err(ExecutionDataStateError::ReadoutUnderMaintenance {
-                            edge: ExecutionDataStateEdge::SummaryJoinInput.describe(),
-                            child: other,
-                        }),
-                    }
-                })?;
-                visit(input, s, assignment)?;
-            }
-            Ok(())
-        }
-        SummaryExpr::SummarySubtract { left, right } => {
-            for input in [left, right] {
-                let s = state_only(input, ExecutionDataStateEdge::SummarySubtractInput)?;
-                visit(input, s, assignment)?;
-            }
-            Ok(())
-        }
-        SummaryExpr::SummaryDelete { summary_input, .. } => {
-            let s = state_only(summary_input, ExecutionDataStateEdge::SummaryDeleteInput)?;
-            visit(summary_input, s, assignment)
-        }
-        SummaryExpr::SummaryMerge { children, timing } => {
-            for input in children {
-                let s = child_domain(input, ExecutionDataStateEdge::SummaryMergeInput, |state| {
-                    if state.primitive == DataPrimitive::SummaryState
-                        && (*timing == ExecutionTiming::QueryTime || state.timing == *timing)
-                    {
-                        Ok(())
-                    } else {
-                        Err(ExecutionDataStateError::IllegalChildDataState {
-                            edge: ExecutionDataStateEdge::SummaryMergeInput.describe(),
-                            child: state,
-                        })
-                    }
-                })?;
-                visit(input, s, assignment)?;
-            }
-            Ok(())
-        }
-        SummaryExpr::SummaryEstimate { summary_input, .. } => {
-            let s = state_only(summary_input, ExecutionDataStateEdge::SummaryEstimateInput)?;
-            visit(summary_input, s, assignment)
-        }
-        SummaryExpr::ValueOperation {
-            child,
-            operation,
-            timing,
-        } => {
-            // Population timing is a lifecycle decision: a retained population
-            // is maintained at ingestion time, an ephemeral one is rebuilt
-            // from raw input per query. Its input and readout contracts are
-            // structural and hold either way.
-            let valid_population = match operation {
-                ValueOperation::MaintainPopulation { population } => {
-                    matches!(&child.expr, SummaryExpr::KeepPreAsap(input) if population.matches_input(input))
-                }
-                ValueOperation::ReadPopulation { readout } => {
-                    *timing == ExecutionTiming::QueryTime
-                        && matches!(&child.expr, SummaryExpr::ValueOperation { operation: ValueOperation::MaintainPopulation { population }, .. } if population.supports(readout))
-                }
-                _ => true,
-            };
-            if !valid_population {
-                return Err(ExecutionDataStateError::InvalidMaintainedPopulation);
-            }
-            let required = match timing {
-                ExecutionTiming::IngestionTime => ExecutionDataState::INGESTION_ROWS,
-                ExecutionTiming::QueryTime => ExecutionDataState::QUERY_ROWS,
-            };
-            let s = produced_data_state(&child.expr).unwrap_or(required);
-            let exact_readout = (*timing == ExecutionTiming::QueryTime
-                || matches!(operation, ValueOperation::FinalizeExactAccumulator))
-                && s.primitive == DataPrimitive::SummaryState
-                && (*timing == ExecutionTiming::QueryTime || s.timing == *timing)
-                && is_exact_accumulator_state(&child.schema).is_ok();
-            // A query-time readout may read a population retained at ingestion.
-            let population_readout = matches!(operation, ValueOperation::ReadPopulation { .. })
-                && *timing == ExecutionTiming::QueryTime
-                && matches!(
-                    &child.expr,
-                    SummaryExpr::ValueOperation {
-                        operation: ValueOperation::MaintainPopulation { .. },
-                        ..
-                    }
-                );
-            if s != required && !exact_readout && !population_readout {
-                return Err(ExecutionDataStateError::IllegalChildDataState {
-                    edge: ExecutionDataStateEdge::ValueOperationChild.describe(),
-                    child: s,
-                });
-            }
-            check_plain_operands(operation, &child.schema)?;
-            visit(child, s, assignment)
-        }
-    }
-}
-
-/// The data_state `child` takes as a direct input of `parent`, without
-/// validating legality — `child`'s own produced data_state, or for a
-/// `KeepPreAsap` leaf the data_state `parent`'s edge assigns it (update-path raw
-/// input under maintenance-time operation edges, query-time fallback under a
-/// a read-time operation, and — meaninglessly, but for a stable answer — maintenance rows
-/// under a state-only edge). For DAG export and other reporting that needs
-/// an explicit per-node data_state even on a plan that
-/// [`validate_execution_data_states`] would reject.
-pub fn assigned_child_data_state(parent: &SummaryExpr, child: &SummaryNode) -> ExecutionDataState {
-    if let Some(avail) = produced_data_state(&child.expr) {
-        return avail;
-    }
-    match parent {
-        SummaryExpr::ValueOperation {
-            timing: ExecutionTiming::QueryTime,
-            ..
-        }
-        | SummaryExpr::BinaryOp {
-            timing: ExecutionTiming::QueryTime,
-            ..
-        } => ExecutionDataState::QUERY_ROWS,
-        SummaryExpr::KeepPreAsap(_)
-        | SummaryExpr::BinaryOp {
-            timing: ExecutionTiming::IngestionTime,
-            ..
-        }
-        | SummaryExpr::RelationalJoin { .. }
-        | SummaryExpr::SummaryAgg { .. }
-        | SummaryExpr::SummaryJoin { .. }
-        | SummaryExpr::SummarySubtract { .. }
-        | SummaryExpr::SummaryDelete { .. }
-        | SummaryExpr::SummaryEstimate { .. }
-        | SummaryExpr::SummaryMerge { .. }
-        | SummaryExpr::ValueOperation {
-            timing: ExecutionTiming::IngestionTime,
-            ..
-        } => ExecutionDataState::INGESTION_ROWS,
-    }
-}
-
-/// The data_state `child` takes on `edge`: its own produced data_state
-/// (checked via `accept`), or — for a `KeepPreAsap` leaf — the data_state the
-/// edge assigns it, derived from what that edge accepts.
-fn child_domain(
-    child: &Rc<SummaryNode>,
-    edge: ExecutionDataStateEdge,
-    accept: impl Fn(ExecutionDataState) -> Result<(), ExecutionDataStateError>,
-) -> Result<ExecutionDataState, ExecutionDataStateError> {
-    match produced_data_state(&child.expr) {
-        Some(avail) => {
-            accept(avail)?;
-            Ok(avail)
-        }
-        None => {
-            // A raw pre-ASAP sub-DAG executes at whichever data_state its consumer
-            // needs: update-path input for maintenance-time operation edges,
-            // query-time fallback for a read-time edge. State-only edges
-            // can't consume plain rows at all.
-            let assigned = match edge {
-                ExecutionDataStateEdge::SummaryAggChild
-                | ExecutionDataStateEdge::SummaryJoinInput
-                | ExecutionDataStateEdge::ValueOperationChild => ExecutionDataState::INGESTION_ROWS,
-                ExecutionDataStateEdge::SummaryEstimateInput
-                | ExecutionDataStateEdge::SummarySubtractInput
-                | ExecutionDataStateEdge::SummaryDeleteInput
-                | ExecutionDataStateEdge::SummaryMergeInput => {
-                    return Err(ExecutionDataStateError::IllegalChildDataState {
-                        edge: edge.describe(),
-                        child: ExecutionDataState::INGESTION_ROWS,
-                    })
-                }
-            };
-            accept(assigned)?;
-            Ok(assigned)
-        }
-    }
-}
-
-fn state_only(
-    child: &Rc<SummaryNode>,
-    edge: ExecutionDataStateEdge,
-) -> Result<ExecutionDataState, ExecutionDataStateError> {
-    child_domain(child, edge, |avail| match avail {
-        state
-            if state.primitive == DataPrimitive::SummaryState
-                && (state.timing == ExecutionTiming::IngestionTime
-                    || matches!(edge, ExecutionDataStateEdge::SummaryEstimateInput)) =>
-        {
-            Ok(())
-        }
-        other => Err(ExecutionDataStateError::IllegalChildDataState {
-            edge: edge.describe(),
-            child: other,
-        }),
-    })
-}
-
-/// The exact operator must consume only `Plain` columns of its input: for
-/// an `Aggregate` payload, every grouping key and every measure's input
-/// column.
-fn check_plain_operands(
-    op: &ValueOperation,
-    input: &Schema,
-) -> Result<(), ExecutionDataStateError> {
-    if matches!(
-        op,
-        ValueOperation::Sort { .. }
-            | ValueOperation::Limit { .. }
-            | ValueOperation::Project { .. }
-            | ValueOperation::Filter { .. }
-            | ValueOperation::FinalizeExactAccumulator
-    ) {
-        return check_plain_or_exact_values(input);
-    }
-    let ValueOperation::Exact(op) = op else {
-        return check_all_plain(input);
-    };
-    let ExactOperation::Aggregate {
-        reduction,
-        measures,
-        filters,
-        ..
-    } = op;
-    let mut referenced: Vec<usize> = reduction
-        .group_keys()
-        .map(|keys| keys.keys().to_vec())
-        .unwrap_or_default();
-    for m in measures {
-        referenced.extend(m.input_cols());
-    }
-    for Predicate(f) in filters.iter().flatten() {
-        referenced.extend(f.columns_referenced().into_iter().copied());
-    }
-    // With no explicit input column (the PromQL sample-value convention)
-    // the operator reads every non-key column, so all must be plain.
-    let implicit = measures.iter().any(|m| m.input_cols().is_empty());
-    for (i, field) in input.fields.iter().enumerate() {
-        if !(implicit || referenced.contains(&i)) {
-            continue;
-        }
-        if !matches!(field.dtype, FieldDataType::Plain(_)) {
-            return Err(ExecutionDataStateError::NonPlainOperand {
-                column: field.name.clone(),
-                dtype: format!("{:?}", field.dtype),
-            });
-        }
-    }
-    Ok(())
-}
-
-fn check_plain_or_exact_values(input: &Schema) -> Result<(), ExecutionDataStateError> {
-    for field in &input.fields {
-        if !matches!(
-            field.dtype,
-            FieldDataType::Plain(_) | FieldDataType::ExactAggregate(..)
-        ) {
-            return Err(ExecutionDataStateError::NonPlainOperand {
-                column: field.name.clone(),
-                dtype: format!("{:?}", field.dtype),
-            });
-        }
-    }
-    Ok(())
-}
-
-fn check_all_plain(input: &Schema) -> Result<(), ExecutionDataStateError> {
-    for field in &input.fields {
-        if !matches!(field.dtype, FieldDataType::Plain(_)) {
-            return Err(ExecutionDataStateError::NonPlainOperand {
-                column: field.name.clone(),
-                dtype: format!("{:?}", field.dtype),
-            });
-        }
-    }
-    Ok(())
-}
-
-/// `schema` with its reuse metadata dropped, or `None` if any field carries
-/// summary state — the shape an exact operator reads.
-pub fn plain_schema(schema: &Schema) -> Option<Schema> {
-    schema
-        .is_all_plain()
-        .then(|| Schema::lifted(schema.fields.clone(), schema.time_index))
+    /// A node reached by export without a timing: the lifecycle timing pass
+    /// was not applied to the DAG first.
+    #[error("{operator} node has no execution timing; apply lifecycle timings before export")]
+    UntimedNode { operator: &'static str },
 }
 
 /// `schema` as a summary-planning node output: fields and time axis kept,
@@ -789,45 +150,18 @@ pub fn lift_plain(schema: &Schema) -> Schema {
     Schema::lifted(schema.fields.clone(), schema.time_index)
 }
 
-/// Output schema of `op` applied to a child whose edge carries `input` —
-/// the same canonical derivation the pre-ASAP `Aggregate` node uses, so an
-/// exact `ValueOperation` never disagrees with the pre-ASAP
-/// target it was lowered from. `Err` when the child carries non-plain
-/// state the operator cannot read.
-pub fn exact_operation_output_schema(
-    op: &ExactOperation,
-    input: &Schema,
-) -> Result<Schema, ExactOperationSchemaError> {
-    let plain = plain_schema(input).ok_or(ExactOperationSchemaError::NonPlainInput)?;
-    let ExactOperation::Aggregate {
-        reduction,
-        measures,
-        output_names,
-        ..
-    } = op;
-    let out = aggregate_output_schema(&plain, reduction, measures, output_names)?;
-    Ok(lift_plain(&out))
-}
-
-/// Why [`exact_operation_output_schema`] could not derive a schema.
+/// Why an exact operator's output schema could not be derived.
 #[derive(Debug, Error)]
 pub enum ExactOperationSchemaError {
     #[error("exact operator input carries summary state, not plain columns")]
     NonPlainInput,
     #[error("schema derivation failed: {0}")]
-    Schema(#[from] QueryExprError),
-    #[error("schema derivation failed: {0}")]
-    Derivation(#[from] crate::ir::SchemaDerivationError),
+    Schema(#[from] SchemaDerivationError),
 }
 
 #[cfg(test)]
 mod tests {
     use super::*;
-    use crate::post_asap::{ExactKind, ExactParams, GroupingStrategy, SketchStatistic};
-    use crate::pre_asap::agg_intent::AggIntent;
-    use crate::pre_asap::expr_ir::ColumnRef;
-    use crate::pre_asap::query_expr::{QueryExpr, Reduction, Source};
-    use crate::pre_asap::schema::{DataType, Field};
 
     /// Both execution phases use raw values, distinct from maintained state.
     #[test]
@@ -845,347 +179,6 @@ mod tests {
         assert_eq!(DataPrimitive::SummaryState.as_str(), "summary_state");
     }
 
-    fn scan() -> Rc<QueryExpr> {
-        Rc::new(QueryExpr::Scan {
-            source: Source::TimeSeries { metric: "m".into() },
-            predicates: vec![],
-            schema: Schema::with_time_index(
-                vec![
-                    Field::plain("ts", DataType::Timestamp, false),
-                    Field::plain("value", DataType::Float64, false),
-                    Field::plain("zone", DataType::Utf8, true),
-                ],
-                0,
-                vec![],
-            ),
-        })
-    }
-
-    fn keep() -> Rc<SummaryNode> {
-        let s = scan();
-        let schema = lift_plain(&s.output_schema().unwrap());
-        Rc::new(SummaryNode {
-            expr: SummaryExpr::KeepPreAsap(s),
-            schema,
-            guarantee: None,
-        })
-    }
-
-    fn plain(names: &[&str]) -> Schema {
-        Schema::lifted(
-            names
-                .iter()
-                .map(|n| Field {
-                    name: (*n).into(),
-                    dtype: FieldDataType::Plain(DataType::Float64),
-                    nullable: false,
-                    table: None,
-                })
-                .collect(),
-            None,
-        )
-    }
-
-    fn agg(child: Rc<SummaryNode>, family: FieldDataType) -> Rc<SummaryNode> {
-        Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryAgg {
-                child,
-                family: family.clone(),
-                input: crate::post_asap::SummaryUpdate::column(ColumnRef::SampleValue),
-                reduction: Reduction::by(vec![]),
-                grouping: GroupingStrategy::default(),
-                filter: None,
-            },
-            schema: Schema::lifted(
-                vec![Field {
-                    name: "state".into(),
-                    dtype: family,
-                    nullable: false,
-                    table: None,
-                }],
-                None,
-            ),
-            guarantee: None,
-        })
-    }
-
-    fn kll() -> FieldDataType {
-        use crate::post_asap::{SketchAlgorithm, SketchKind, SketchParams};
-        FieldDataType::Sketch(
-            SketchKind::new(SketchAlgorithm::Kll, SketchParams::Kll { k: 200 }),
-            GroupingStrategy::default(),
-        )
-    }
-
-    fn estimate(child: Rc<SummaryNode>) -> Rc<SummaryNode> {
-        Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryEstimate {
-                summary_input: child,
-                query: SketchStatistic::Quantile { q: 0.99 },
-            },
-            schema: plain(&["quantile_0_99"]),
-            guarantee: None,
-        })
-    }
-
-    fn max_op() -> ExactOperation {
-        ExactOperation::Aggregate {
-            reduction: Reduction::by(vec![]),
-            measures: vec![AggIntent::Max { col: None }],
-            output_names: vec![],
-            having: None,
-            filters: vec![],
-        }
-    }
-
-    #[test]
-    fn keep_pre_asap_under_summary_agg_is_update_input() {
-        let leaf = keep();
-        let root = agg(Rc::clone(&leaf), kll());
-        let assignment = validate_execution_data_states(&root).unwrap();
-        assert_eq!(
-            assignment.data_state_of(&leaf),
-            Some(ExecutionDataState::INGESTION_ROWS)
-        );
-        assert_eq!(
-            assignment.data_state_of(&root),
-            Some(ExecutionDataState::INGESTION_SUMMARY)
-        );
-    }
-
-    // Typed derived updates retain one opaque series identity only when both
-    // operands cover the same series; arbitrary labels are never admitted.
-    #[test]
-    fn maintenance_binary_accepts_only_well_typed_series_identity() {
-        use crate::pre_asap::{ArithmeticOpKind, BinaryOpKind};
-        let identity = crate::pre_asap::schema::PROMQL_SERIES_IDENTITY;
-        // A finalized per-series Sum of `metric`'s rows.
-        let operand = |metric: &str, schema: &Schema| {
-            let rows = Rc::new(QueryExpr::Scan {
-                source: Source::TimeSeries {
-                    metric: metric.into(),
-                },
-                predicates: vec![],
-                schema: Schema::with_time_index(
-                    vec![
-                        Field::plain("ts", DataType::Timestamp, false),
-                        Field::plain("value", DataType::Float64, false),
-                    ],
-                    0,
-                    vec![],
-                ),
-            });
-            let mut state = schema.clone();
-            state.fields[0].dtype = FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum);
-            let sum = Rc::new(SummaryNode {
-                expr: SummaryExpr::SummaryAgg {
-                    child: Rc::new(SummaryNode {
-                        expr: SummaryExpr::KeepPreAsap(rows),
-                        schema: schema.clone(),
-                        guarantee: None,
-                    }),
-                    family: FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum),
-                    input: crate::post_asap::SummaryUpdate::column(ColumnRef::SampleValue),
-                    reduction: Reduction::PerEntity,
-                    grouping: GroupingStrategy::default(),
-                    filter: None,
-                },
-                schema: state,
-                guarantee: None,
-            });
-            Rc::new(SummaryNode {
-                expr: SummaryExpr::ValueOperation {
-                    child: sum,
-                    operation: ValueOperation::FinalizeExactAccumulator,
-                    timing: ExecutionTiming::IngestionTime,
-                },
-                schema: schema.clone(),
-                guarantee: None,
-            })
-        };
-        let validate = |schema: Schema, rhs: &str| {
-            let binary = Rc::new(SummaryNode {
-                expr: SummaryExpr::BinaryOp {
-                    lhs: operand("m", &schema),
-                    rhs: operand(rhs, &schema),
-                    timing: ExecutionTiming::IngestionTime,
-                    operator: crate::post_asap::BinaryOperator {
-                        kind: BinaryOpKind::Arithmetic(ArithmeticOpKind::Add),
-                        vector_match: None,
-                        checked_relative_division: false,
-                        checked_finite_division: false,
-                    },
-                },
-                schema,
-                guarantee: None,
-            });
-            validate_execution_data_states(&estimate(agg(binary, kll()))).map(|_| ())
-        };
-        let mut schema = plain(&["value"]);
-        schema.fields.push(Field {
-            table: None,
-            name: "ts".into(),
-            dtype: FieldDataType::Plain(DataType::Timestamp),
-            nullable: false,
-        });
-        schema.time_index = Some(1);
-        assert!(validate(schema.clone(), "m").is_ok());
-        assert!(
-            validate(schema.clone(), "n").is_ok(),
-            "no identity to align"
-        );
-        schema.fields.push(Field {
-            table: None,
-            name: identity.into(),
-            dtype: FieldDataType::Plain(DataType::Utf8),
-            nullable: false,
-        });
-        assert!(validate(schema.clone(), "m").is_ok());
-        assert_eq!(
-            validate(schema.clone(), "n"),
-            Err(ExecutionDataStateError::InvalidMaintenanceBinary),
-            "different selectors may cover different series"
-        );
-        for mutation in 0..4 {
-            let mut invalid = schema.clone();
-            match mutation {
-                0 => invalid.fields[2].nullable = true,
-                1 => invalid.fields[2].dtype = FieldDataType::Plain(DataType::Timestamp),
-                2 => invalid.fields.push(invalid.fields[2].clone()),
-                _ => invalid.fields[2].name = "label".into(),
-            }
-            assert_eq!(
-                validate(invalid, "m"),
-                Err(ExecutionDataStateError::InvalidMaintenanceBinary)
-            );
-        }
-    }
-
-    #[test]
-    fn exact_accumulator_state_may_feed_another_summary_agg() {
-        let inner = agg(
-            keep(),
-            FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum),
-        );
-        let root = estimate(agg(inner, kll()));
-        assert!(validate_execution_data_states(&root).is_ok());
-    }
-
-    #[test]
-    fn readout_can_feed_summary_construction_at_query_time() {
-        let inner = estimate(agg(keep(), kll()));
-        let summary = agg(inner, kll());
-        let root = estimate(summary.clone());
-        let assignment = validate_execution_data_states(&root).unwrap();
-        assert_eq!(
-            assignment.data_state_of(&summary).unwrap().timing,
-            ExecutionTiming::QueryTime
-        );
-    }
-
-    #[test]
-    fn query_time_operation_over_readout_is_legal_and_root_is_readout() {
-        let inner = estimate(agg(keep(), kll()));
-        let root = Rc::new(SummaryNode {
-            expr: SummaryExpr::ValueOperation {
-                child: inner,
-                operation: ValueOperation::Exact(max_op()),
-                timing: ExecutionTiming::QueryTime,
-            },
-            schema: plain(&["max"]),
-            guarantee: None,
-        });
-        let assignment = validate_execution_data_states(&root).unwrap();
-        assert_eq!(
-            assignment.data_state_of(&root),
-            Some(ExecutionDataState::QUERY_ROWS)
-        );
-    }
-
-    #[test]
-    fn non_exact_operator_uses_the_same_read_domain_contract() {
-        let inner = estimate(agg(keep(), kll()));
-        let root = Rc::new(SummaryNode {
-            expr: SummaryExpr::ValueOperation {
-                child: inner,
-                operation: ValueOperation::Extension {
-                    name: "approximate_calibration".into(),
-                },
-                timing: ExecutionTiming::QueryTime,
-            },
-            schema: plain(&["calibrated"]),
-            guarantee: None,
-        });
-
-        let assignment = validate_execution_data_states(&root).unwrap();
-        assert_eq!(
-            assignment.data_state_of(&root),
-            Some(ExecutionDataState::QUERY_ROWS)
-        );
-    }
-
-    #[test]
-    fn query_time_values_can_feed_query_time_summary_construction() {
-        let inner = estimate(agg(keep(), kll()));
-        let post = Rc::new(SummaryNode {
-            expr: SummaryExpr::ValueOperation {
-                child: inner,
-                operation: ValueOperation::Exact(max_op()),
-                timing: ExecutionTiming::QueryTime,
-            },
-            schema: plain(&["max"]),
-            guarantee: None,
-        });
-        let root = agg(post, kll());
-        let root = estimate(root);
-        validate_execution_data_states(&root).unwrap();
-    }
-
-    #[test]
-    fn function_under_summary_agg_is_legal_but_not_at_root() {
-        let operation = Rc::new(SummaryNode {
-            expr: SummaryExpr::ValueOperation {
-                child: keep(),
-                operation: ValueOperation::Exact(max_op()),
-                timing: ExecutionTiming::IngestionTime,
-            },
-            schema: plain(&["max"]),
-            guarantee: None,
-        });
-        assert_eq!(
-            validate_execution_data_states(&operation).err(),
-            Some(ExecutionDataStateError::MaintenanceRowsAtRoot)
-        );
-        let root = estimate(agg(Rc::clone(&operation), kll()));
-        let assignment = validate_execution_data_states(&root).unwrap();
-        assert_eq!(
-            assignment.data_state_of(&operation),
-            Some(ExecutionDataState::INGESTION_ROWS)
-        );
-    }
-
-    #[test]
-    fn function_over_readout_is_rejected() {
-        let inner = estimate(agg(keep(), kll()));
-        let operation = Rc::new(SummaryNode {
-            expr: SummaryExpr::ValueOperation {
-                child: inner,
-                operation: ValueOperation::Exact(max_op()),
-                timing: ExecutionTiming::IngestionTime,
-            },
-            schema: plain(&["max"]),
-            guarantee: None,
-        });
-        let root = agg(operation, kll());
-        assert!(matches!(
-            validate_execution_data_states(&root),
-            Err(ExecutionDataStateError::IllegalChildDataState {
-                edge: "ValueOperation.child",
-                child: ExecutionDataState::QUERY_ROWS
-            })
-        ));
-    }
-
     #[test]
     fn execution_phase_wire_names_are_ingestion_and_query_time() {
         for (phase, name) in [
@@ -1202,154 +195,4 @@ mod tests {
         assert!(serde_json::from_str::<ExecutionTiming>("\"maintenance_time\"").is_err());
         assert!(serde_json::from_str::<ExecutionTiming>("\"MaintenanceTime\"").is_err());
     }
-
-    #[test]
-    fn summary_merge_runs_at_ingestion_or_query_time() {
-        for timing in [ExecutionTiming::IngestionTime, ExecutionTiming::QueryTime] {
-            let input = agg(keep(), kll());
-            let merged = Rc::new(SummaryNode {
-                expr: SummaryExpr::SummaryMerge {
-                    children: vec![input.clone()],
-                    timing,
-                },
-                schema: input.schema.clone(),
-                guarantee: None,
-            });
-            let root = estimate(merged.clone());
-            let assignment = validate_execution_data_states(&root).unwrap();
-            assert_eq!(
-                assignment.data_state_of(&merged),
-                Some(ExecutionDataState {
-                    timing,
-                    primitive: DataPrimitive::SummaryState,
-                })
-            );
-            let exported = crate::post_asap::compile_post_asap_dag(&root).unwrap();
-            assert!(exported.nodes.iter().any(|node| matches!(node.payload,
-                crate::post_asap::PostAsapOperatorPayload::SummaryMerge
-                    if node.output_state.timing == timing)));
-        }
-    }
-
-    #[test]
-    fn ingestion_merge_cannot_depend_on_query_execution() {
-        let input = agg(keep(), kll());
-        let query_merge = Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryMerge {
-                children: vec![input.clone()],
-                timing: ExecutionTiming::QueryTime,
-            },
-            schema: input.schema.clone(),
-            guarantee: None,
-        });
-        let ingestion_merge = Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryMerge {
-                children: vec![query_merge],
-                timing: ExecutionTiming::IngestionTime,
-            },
-            schema: input.schema.clone(),
-            guarantee: None,
-        });
-        assert!(validate_execution_data_states(&ingestion_merge).is_err());
-    }
-
-    #[test]
-    fn a_shared_keep_pre_asap_reached_in_two_domains_is_ambiguous() {
-        // One raw sub-DAG used both as update input (under a SummaryAgg) and
-        // as a query-time fallback (under an ExactRead) — no single
-        // execution can serve both, so the plan is rejected.
-        let shared = keep();
-        let maintained = estimate(agg(Rc::clone(&shared), kll()));
-        let post_over_raw = Rc::new(SummaryNode {
-            expr: SummaryExpr::ValueOperation {
-                child: Rc::clone(&shared),
-                operation: ValueOperation::Exact(max_op()),
-                timing: ExecutionTiming::QueryTime,
-            },
-            schema: plain(&["max"]),
-            guarantee: None,
-        });
-        let root = Rc::new(SummaryNode {
-            expr: SummaryExpr::SummaryMerge {
-                timing: ExecutionTiming::IngestionTime,
-                children: vec![
-                    Rc::new(SummaryNode {
-                        expr: SummaryExpr::ValueOperation {
-                            child: maintained,
-                            operation: ValueOperation::Exact(max_op()),
-                            timing: ExecutionTiming::QueryTime,
-                        },
-                        schema: plain(&["max"]),
-                        guarantee: None,
-                    }),
-                    post_over_raw,
-                ],
-            },
-            schema: plain(&["max"]),
-            guarantee: None,
-        });
-        // SummaryMerge only accepts state, so this fails earlier for a
-        // different reason; probe the ambiguity through a direct visit.
-        let mut assignment = ExecutionDataStateAssignment::default();
-        visit(&shared, ExecutionDataState::INGESTION_ROWS, &mut assignment).unwrap();
-        assert_eq!(
-            visit(&shared, ExecutionDataState::QUERY_ROWS, &mut assignment),
-            Err(ExecutionDataStateError::AmbiguousKeepPreAsap {
-                first: ExecutionDataState::INGESTION_ROWS,
-                second: ExecutionDataState::QUERY_ROWS,
-            })
-        );
-        assert!(validate_execution_data_states(&root).is_err());
-    }
-
-    // Both paired operands must be plain; an unrelated state column is not an input.
-    #[test]
-    fn pearson_corr_checks_both_operand_states() {
-        let operation = ValueOperation::Exact(ExactOperation::Aggregate {
-            reduction: Reduction::by(vec![]),
-            measures: vec![AggIntent::PearsonCorr { left: 0, right: 1 }],
-            output_names: vec![],
-            having: None,
-            filters: vec![],
-        });
-        for operand in [0, 1] {
-            let mut input = plain(&["x", "y", "unused"]);
-            input.fields[operand].dtype = kll();
-            assert!(matches!(
-                check_plain_operands(&operation, &input),
-                Err(ExecutionDataStateError::NonPlainOperand { .. })
-            ));
-        }
-        let mut input = plain(&["x", "y", "unused"]);
-        input.fields[2].dtype = kll();
-        check_plain_operands(&operation, &input).unwrap();
-    }
-
-    #[test]
-    fn exact_operator_schema_matches_pre_asap_aggregate_derivation() {
-        let child_schema = lift_plain(&scan().output_schema().unwrap());
-        let op = ExactOperation::Aggregate {
-            reduction: Reduction::by(vec![2]),
-            measures: vec![AggIntent::Max { col: None }],
-            output_names: vec![],
-            having: None,
-            filters: vec![],
-        };
-        let out = exact_operation_output_schema(&op, &child_schema).unwrap();
-        let names: Vec<_> = out.fields.iter().map(|f| f.name.as_str()).collect();
-        assert_eq!(names, vec!["zone", "max"]);
-        assert!(out
-            .fields
-            .iter()
-            .all(|f| matches!(f.dtype, FieldDataType::Plain(_))));
-    }
-
-    #[test]
-    fn exact_operator_rejects_non_plain_input() {
-        let state = agg(keep(), kll());
-        assert!(matches!(
-            exact_operation_output_schema(&max_op(), &state.schema),
-            Err(ExactOperationSchemaError::NonPlainInput)
-        ));
-    }
 }
diff --git a/crates/types/src/post_asap/expr.rs b/crates/types/src/post_asap/expr.rs
deleted file mode 100644
index 732a09db5..000000000
--- a/crates/types/src/post_asap/expr.rs
+++ /dev/null
@@ -1,303 +0,0 @@
-use super::ExecutionTiming;
-use std::rc::Rc;
-
-use super::guarantee::ResultGuarantee;
-use super::sketch::{GroupingStrategy, SketchStatistic, SummaryUpdate};
-use crate::pre_asap::agg_intent::AggIntent;
-use crate::pre_asap::query_expr::Predicate;
-use crate::pre_asap::schema::{FieldDataType, Schema};
-use crate::pre_asap::{
-    BinaryOpKind, ColumnRef, GroupKeys, JoinKind, ProjectItem, QueryExpr, Reduction, SortKey,
-    VectorMatch,
-};
-
-#[derive(Debug, Clone, PartialEq, serde::Serialize, serde::Deserialize)]
-#[non_exhaustive]
-pub enum ExactOperation {
-    Aggregate {
-        reduction: Reduction,
-        measures: Vec<AggIntent>,
-        output_names: Vec<String>,
-        /// Per-measure row predicates parallel to `measures`, positional
-        /// against the child's output rows — the same contract as
-        /// `QueryExpr::Aggregate.filters` (issue #466).
-        #[serde(default)]
-        filters: Vec<Option<Predicate>>,
-        having: Option<Predicate>,
-    },
-}
-
-#[derive(Debug, Clone, PartialEq, serde::Serialize, serde::Deserialize)]
-#[non_exhaustive]
-pub enum ValueOperation {
-    /// Maintain the full declared population, including membership changes,
-    /// so removing a TopK member can promote another.
-    MaintainPopulation {
-        population: super::maintained_population::MaintainedPopulation<crate::pre_asap::QueryExpr>,
-    },
-    /// Read an aggregate or TopK prefix from the maintained population.
-    ReadPopulation {
-        readout: super::maintained_population::PopulationStatistic,
-    },
-    Exact(ExactOperation),
-    /// Read an exact accumulator's state as its finalized scalar value.
-    ///
-    /// Exact accumulators do not need an estimator, but the explicit node
-    /// marks the maintenance-to-read boundary before query-time operators
-    /// such as PromQL binary arithmetic, sorting, and limiting.
-    FinalizeExactAccumulator,
-    /// Query-time column projection. SQL lowering retains the SELECT list as
-    /// a `Project` above its aggregate, so the post-ASAP DAG must preserve
-    /// its expressions, aliases, and optional derived-table qualifier while
-    /// allowing the aggregate child to be planned independently.
-    Project {
-        cols: Vec<ProjectItem>,
-        qualifier: Option<String>,
-    },
-    /// Query-time row filtering. The predicate remains positional against
-    /// the child's output schema and is evaluated only after any summary
-    /// state below it has been read out to rows.
-    Filter {
-        pred: Predicate,
-    },
-    /// Query-time ordering of the child's value rows. This is deliberately
-    /// distinct from frequency-sketch heavy-hitter readout: PromQL `topk`
-    /// ranks the values produced by its child at the evaluation timestamp.
-    Sort {
-        keys: Vec<SortKey>,
-        partition_by: GroupKeys,
-    },
-    /// Query-time row selection, normally composed over [`Self::Sort`] for
-    /// PromQL `topk`/`bottomk` and SQL `ORDER BY … LIMIT`.
-    Limit {
-        n: usize,
-        offset: usize,
-        /// Apply the offset and limit independently to each group.
-        partition_by: GroupKeys,
-    },
-    Extension {
-        name: String,
-    },
-}
-
-/// Whether a candidate-membership sidecar is proven to contain every true
-/// top-k key or is an explicitly approximate optimization.
-#[derive(Debug, Clone, PartialEq, serde::Serialize, serde::Deserialize)]
-#[serde(tag = "kind", rename_all = "snake_case")]
-pub enum CandidateCompleteness {
-    Certified { guarantee: ResultGuarantee },
-    BestEffort { guarantee: Option<ResultGuarantee> },
-}
-
-// ── Post-ASAP DAG node ───────────────────────────────────────────────────────
-
-/// A node in the post-ASAP DAG: wraps the expression and its derived output
-/// schema so every edge carries a typed schema. `Schema` may contain
-/// summary-state-typed columns (`FieldDataType`'s non-`Plain` variants);
-/// the pre-ASAP `Schema` cannot.
-#[derive(Debug, Clone, PartialEq)]
-pub struct SummaryNode {
-    pub expr: SummaryExpr,
-    /// Output schema of `expr` — the schema of the data flowing on the edge
-    /// leading *from* this node to its parent(s).
-    pub schema: Schema,
-    /// The machine-readable accuracy guarantee of the *value* this node
-    /// produces (issue #172) — `Some` on every finalized, caller-visible
-    /// value: a `SummaryEstimate` readout, an `ExactAggregate`-family
-    /// `SummaryAgg` (its state *is* the value), or a `KeepPreAsap` sub-DAG
-    /// (executed exactly). `None` on raw summary state — a sketch-family
-    /// `SummaryAgg`, `SummaryMerge`, `SummarySubtract`, `SummaryDelete`,
-    /// `SummaryJoin` — whose guarantee only exists once something reads it
-    /// out; and `None` on a readout of a family the plugged-in
-    /// `AccuracyModel` has no local guarantee for (`Sample`/`Wavelet`/
-    /// `StatModel`), which a fail-closed consumer must treat as "unknown",
-    /// never as exact.
-    pub guarantee: Option<ResultGuarantee>,
-}
-
-// ── Post-ASAP sketch-bound IR ────────────────────────────────────────────────
-
-/// Sketch-bound IR produced by post-ASAP binding and final selection. Binding
-/// rules selectively replace logical aggregates and joins in the pre-ASAP
-/// `QueryExpr` with summary-bound counterparts. Final selection can retain
-/// supported read-time value operations around independently planned children;
-/// other unsupported sub-DAGs pass through as `KeepPreAsap(Rc<QueryExpr>)`.
-///
-/// Traversing from the root node yields a DAG; shared sub-expressions appear
-/// as multiple `Rc` references to the same `SummaryNode`.
-#[derive(Debug, Clone, PartialEq)]
-pub enum SummaryExpr {
-    /// A pre-ASAP sub-DAG kept as-is because it has no selected implementation
-    /// or supported residual decomposition. Output schema is the inner node's
-    /// schema, lifted to `Schema` with all fields as
-    /// `FieldDataType::Plain`.
-    KeepPreAsap(Rc<QueryExpr>),
-
-    /// A PromQL binary operation whose operands were planned independently.
-    /// This keeps realizable summary/readout leaves visible instead of
-    /// hiding the complete expression inside `KeepPreAsap`.
-    BinaryOp {
-        timing: ExecutionTiming,
-        lhs: Rc<SummaryNode>,
-        rhs: Rc<SummaryNode>,
-        operator: BinaryOperator,
-    },
-
-    /// Plain-row semantics composed with a post-ASAP child. Timing is an
-    /// independent physical choice, not part of the operation's identity.
-    ValueOperation {
-        child: Rc<SummaryNode>,
-        operation: ValueOperation,
-        timing: super::execution_data_state::ExecutionTiming,
-    },
-
-    /// Read-time relational join over two row-producing children. This is
-    /// distinct from [`SummaryJoin`](Self::SummaryJoin), which combines
-    /// summary states for join estimation during maintenance.
-    RelationalJoin {
-        left: Rc<SummaryNode>,
-        right: Rc<SummaryNode>,
-        kind: JoinKind,
-        pred: Predicate,
-        /// Optional proof for candidate pruning; ranking remains a separate operation.
-        pruning: Option<CandidateCompleteness>,
-    },
-
-    /// Summary aggregation. Post-ASAP binding chose `family` — which
-    /// summary family (exact accumulator, sketch, sample, wavelet, or
-    /// statistical model) and its `(kind, params)` — from the catalog for
-    /// `AggIntent` under `DeploymentConstraints`.
-    /// Output schema: grouping columns (verbatim) + one field carrying
-    /// partial summary state per group, typed `family`.
-    SummaryAgg {
-        child: Rc<SummaryNode>,
-        /// Which summary family realizes this aggregation, and that
-        /// family's own `(kind, params)`. Never `FieldDataType::Plain`
-        /// — this node always produces summary state, not a plain value.
-        family: FieldDataType,
-        /// Optional multidimensional item identity and the observation/update
-        /// weight fed into each state update. Subpopulation semantics remain
-        /// on `reduction`; physical sharing remains on `grouping`.
-        input: SummaryUpdate,
-        /// How this aggregation's output rows relate to `child`'s — the
-        /// same [`Reduction`] the pre-ASAP `Aggregate` node it was bound
-        /// from carried (issue #165), reused verbatim rather than
-        /// flattened to a bare `Vec<ColumnId>`. `Reduction::Reduce(by)`
-        /// with an empty `by` is a genuine full reduction (merge every
-        /// candidate into one group); `Reduction::PerEntity` has no
-        /// grouping concept at all (never merge across entities) — the
-        /// two collapsed to the same ambiguous `by: []` before this field
-        /// existed (issue #163).
-        reduction: Reduction,
-        /// How this aggregation's summary state is physically instantiated
-        /// across `reduction`'s subpopulations — one independent instance
-        /// per `by` key (today's only behavior, and this field's default),
-        /// or one shared Hydra-family structure serving all of them (issue
-        /// #256). Lives here, next to `reduction`, for planning, and is also
-        /// encoded in sketch-valued `family`/output-schema state so merges
-        /// can reject incompatible layouts. `reduction` is the field that
-        /// carries the `by` keys this axis's legality depends on (a
-        /// `SharedMultiSubpopulation` choice only makes sense when
-        /// `reduction` actually has a subpopulation concept — see
-        /// `asap_aware_mapping::grouping`'s module docs for the legality
-        /// rules). Every existing producer of a `SummaryAgg` sets this to
-        /// `GroupingStrategy::PerSubpopulationInstance` (its `Default`),
-        /// so no existing behavior changes.
-        grouping: GroupingStrategy,
-        /// Row predicate gating this summary's updates (issue #466): only
-        /// rows where it is `TRUE` update the state; grouping keys are
-        /// still read from every row. Positional against `child`'s output.
-        /// A field rather than a `Filter` child so summaries that differ
-        /// only in predicate can still share one child. No binding rule
-        /// sets it yet — a filtered pre-ASAP measure stays `KeepPreAsap` —
-        /// so every producer today writes `None`.
-        filter: Option<Predicate>,
-    },
-
-    /// Summary-aware join (KMV / theta for join-cardinality; join-sample for
-    /// sampling). Emitted only when a `Bind*OnJoin` rule fires.
-    /// Output schema: one field typed `family`, read by a downstream
-    /// `SummaryEstimate`.
-    SummaryJoin {
-        outer: Rc<SummaryNode>,
-        inner: Rc<SummaryNode>,
-        key: ColumnRef,
-        /// Never `FieldDataType::Plain` — see [`SummaryAgg::family`](SummaryExpr::SummaryAgg).
-        family: FieldDataType,
-    },
-
-    /// Subtract one summary from another. Valid only for families with a
-    /// linear-inverse property (CMS, theta, count-based). Catalog flag
-    /// `subtractable` must be true for the family.
-    /// Output schema: one field (same family + params as inputs).
-    SummarySubtract {
-        left: Rc<SummaryNode>,
-        right: Rc<SummaryNode>,
-    },
-
-    /// Delete a key from a summary (CMS update with −1, deletable Bloom
-    /// filter). Catalog flag `deletable` must be true. Output schema =
-    /// input schema unchanged in type (same field type as input).
-    SummaryDelete {
-        summary_input: Rc<SummaryNode>,
-        key: ColumnRef,
-    },
-
-    /// Read out a query result from a built summary. The summary-state field
-    /// type does *not* propagate downstream of an estimate — the output
-    /// schema is a regular row-shaped schema (Float64 for quantile, Int64
-    /// for count/cardinality, `[(key, count)]` for top-k).
-    SummaryEstimate {
-        summary_input: Rc<SummaryNode>,
-        query: SketchStatistic,
-    },
-
-    /// ⊕ — union of summaries across stages / shards. Distinct from the
-    /// pre-ASAP `Concat` because summary union has type constraints: all
-    /// inputs must agree on `family` (kind + params) and the catalog flag
-    /// `mergeable` must be true. Inserted by a deployment's own stage
-    /// allocator (not modeled in this crate) on cut edges.
-    /// Output schema: one field (same family + params as inputs).
-    SummaryMerge {
-        children: Vec<Rc<SummaryNode>>,
-        timing: ExecutionTiming,
-    },
-}
-
-/// All semantics owned by a post-ASAP binary operator.
-#[derive(Debug, Clone, PartialEq, serde::Serialize, serde::Deserialize)]
-pub struct BinaryOperator {
-    /// Execute division only for finite operands, a nonzero divisor, and a
-    /// normal finite result; otherwise use exact execution. Required by the
-    /// relative-value division certificate, including floating-point range.
-    #[serde(default)]
-    pub checked_relative_division: bool,
-    /// Conditional exact rewrites (such as temporal average from sum/count)
-    /// require finite operands and quotient. Zero/subnormal results are valid;
-    /// overflow must fall back to the original query rather than emit infinity.
-    #[serde(default)]
-    pub checked_finite_division: bool,
-    pub kind: BinaryOpKind,
-    /// `None` is the only currently supported vector/vector matching mode.
-    /// The field is retained so execution never has to recover semantics by
-    /// re-parsing PromQL.
-    pub vector_match: Option<VectorMatch>,
-}
-
-impl BinaryOperator {
-    pub fn from_logical(operator: &crate::ir::BinaryOperator, return_bool: bool) -> Self {
-        use crate::pre_asap::BinaryOpKind as L;
-        Self {
-            kind: match &operator.kind {
-                L::Arithmetic(op) => BinaryOpKind::Arithmetic(op.clone()),
-                L::Compare(op) if return_bool => BinaryOpKind::CompareBool(op.clone()),
-                L::Compare(op) => BinaryOpKind::Compare(op.clone()),
-                L::CompareBool(op) => BinaryOpKind::CompareBool(op.clone()),
-                L::Set(op) => BinaryOpKind::Set(op.clone()),
-            },
-            vector_match: operator.vector_match.clone(),
-            checked_relative_division: operator.checked_relative_division,
-            checked_finite_division: operator.checked_finite_division,
-        }
-    }
-}
diff --git a/crates/types/src/post_asap/maintained_population.rs b/crates/types/src/post_asap/maintained_population.rs
index 577544bd7..5e64b5436 100644
--- a/crates/types/src/post_asap/maintained_population.rs
+++ b/crates/types/src/post_asap/maintained_population.rs
@@ -1,4 +1,4 @@
-//! Language-independent maintained populations and their readouts.
+//! Language-independent maintained populations and their evaluations.
 //! Resource limits, ingestion placement and data structures belong to the executor.
 use serde::{Deserialize, Serialize};
 
@@ -35,82 +35,6 @@ pub enum PopulationStatistic {
     Average,
 }
 
-impl CurrentSeriesInput {
-    /// Verify the named contract against the canonical maintenance input.
-    pub fn matches_input(&self, input: &crate::pre_asap::QueryExpr) -> bool {
-        use crate::pre_asap::{CompareOpKind, DataType, QueryExpr, ScalarValue, Source};
-        // PromQL instant selectors carry an ingestion-interval `TimeRange` as
-        // their input scope. The population must use the same expiry horizon;
-        // shifted and otherwise transformed inputs still fail below.
-        let input = match input {
-            QueryExpr::TimeRange { range, child }
-                if self.lookback_ms > 0
-                    && *range == std::time::Duration::from_millis(self.lookback_ms) =>
-            {
-                child.as_ref()
-            }
-            QueryExpr::TimeRange { .. } => return false,
-            other if self.lookback_ms == 300_000 => other,
-            _ => return false,
-        };
-        let QueryExpr::Scan {
-            source: Source::TimeSeries { metric },
-            predicates,
-            schema,
-        } = input
-        else {
-            return false;
-        };
-        if self.metric.is_empty()
-            || *metric != self.metric
-            || (schema.closed && !schema.has_promql_series_identity())
-            || schema.time_index.is_none()
-        {
-            return false;
-        }
-        if self.grouping.iter().any(|label| {
-            !schema
-                .fields
-                .iter()
-                .any(|c| c.name == *label && c.dtype == DataType::Utf8)
-        }) {
-            return false;
-        }
-        let mut matchers = Vec::new();
-        for predicate in predicates {
-            let QueryExpr::Compare { left, op, right } = predicate.0.as_ref() else {
-                return false;
-            };
-            let (QueryExpr::Column(col), QueryExpr::Literal(ScalarValue::Utf8(value))) =
-                (left.as_ref(), right.as_ref())
-            else {
-                return false;
-            };
-            let Some(column) = schema.fields.get(*col) else {
-                return false;
-            };
-            if column.dtype != DataType::Utf8 {
-                return false;
-            }
-            let operation = match op {
-                CompareOpKind::Eq => CurrentSeriesMatch::Equal,
-                CompareOpKind::Ne => CurrentSeriesMatch::NotEqual,
-                CompareOpKind::Regex => CurrentSeriesMatch::Regex,
-                CompareOpKind::NotRegex => CurrentSeriesMatch::NotRegex,
-                _ => return false,
-            };
-            matchers.push(CurrentSeriesMatcher {
-                label: column.name.clone(),
-                value: value.clone(),
-                operation,
-            });
-        }
-        matchers.sort();
-        matchers.dedup();
-        self.matchers == matchers && self.grouping.windows(2).all(|w| w[0] < w[1])
-    }
-}
-
 /// Membership is part of state identity. Table rows must never acquire implicit
 /// latest-per-series selection, stale markers, or a PromQL lookback.
 #[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
@@ -130,35 +54,6 @@ pub struct MaintainedPopulation<N = crate::ir::OperatorNode> {
     pub quantiles: bool,
 }
 
-impl MaintainedPopulation<crate::pre_asap::QueryExpr> {
-    pub fn matches_input(&self, input: &crate::pre_asap::QueryExpr) -> bool {
-        match &self.input {
-            PopulationInput::CurrentSeries(spec) => spec.matches_input(input),
-            PopulationInput::Rows {
-                input: expected,
-                value_column,
-                grouping,
-            } => {
-                use crate::pre_asap::{DataType, QueryExpr, Source};
-                expected.as_ref() == input
-                    && matches!(input, QueryExpr::Scan { source: Source::Table { .. }, schema, .. }
-                        if schema.closed && schema.fields.get(*value_column).is_some_and(|c| c.dtype == DataType::Float64 && !c.nullable)
-                            && !grouping.is_without() && grouping.keys().iter().all(|k| *k < schema.fields.len()))
-            }
-        }
-    }
-
-    pub fn supports(&self, readout: &PopulationStatistic) -> bool {
-        match readout {
-            PopulationStatistic::Quantile { q } => self.quantiles && q.is_finite(),
-            PopulationStatistic::TopK { k } => *k <= self.max_k,
-            PopulationStatistic::Sum
-            | PopulationStatistic::Count
-            | PopulationStatistic::Average => true,
-        }
-    }
-}
-
 impl CurrentSeriesInput {
     /// Verify the named contract against the canonical maintenance input.
     pub fn matches_node(&self, input: &crate::ir::OperatorNode) -> bool {
diff --git a/crates/types/src/post_asap/mod.rs b/crates/types/src/post_asap/mod.rs
index b1a7da67a..e282fccad 100644
--- a/crates/types/src/post_asap/mod.rs
+++ b/crates/types/src/post_asap/mod.rs
@@ -1,39 +1,31 @@
-//! The post-ASAP IR: summary-bound types, distinct from
-//! [`crate::pre_asap`]'s pre-ASAP IR.
+//! Summary-state types and the execution-timing vocabulary of the operator
+//! IR ([`crate::ir`]).
 //!
-//! Where [`crate::pre_asap`] carries *intent* only ("compute a
-//! quantile to ε accuracy"), this module is the summary-bound IR: the
-//! summary family, kind/algorithm, and parameters are committed (one
-//! `(Kind, Params)` pair per family — [`sketch::ExactKind`]/[`sketch::ExactParams`],
+//! Where an intent ([`crate::pre_asap::AggIntent`]) says *what* to compute
+//! ("a quantile to ε accuracy"), these types say *how* a summary realizes it:
+//! the family, kind/algorithm and parameters are committed — one
+//! `(Kind, Params)` pair per family ([`sketch::ExactKind`]/[`sketch::ExactParams`],
 //! [`sketch::SamplingKind`]/[`sketch::SamplingParams`],
 //! [`sketch::WaveletKind`]/[`sketch::WaveletParams`],
-//! [`sketch::StatModelKind`]/[`sketch::StatModelParams`]), and
-//! [`expr::SummaryNode`] / [`expr::SummaryExpr`] describe the summary
-//! computation. The `Sketch` family is the one exception to that
-//! one-pair-per-family shape: it nests a third level, [`sketch::SketchKind`]
-//! (quantile/cardinality/frequency/top-k), which itself carries the
-//! committed [`sketch::SketchAlgorithm`] and [`sketch::SketchParams`] —
-//! `FieldDataType::Sketch(SketchKind, GroupingStrategy)`, not a flat
-//! `(kind, params)` pair
-//! — because `Sketch` is the one family with more than one algorithm per
-//! purpose today; no other family needs that extra level yet.
+//! [`sketch::StatModelKind`]/[`sketch::StatModelParams`]). The `Sketch` family
+//! nests a third level, [`sketch::SketchKind`] (quantile/cardinality/
+//! frequency/top-k), carrying the committed [`sketch::SketchAlgorithm`] and
+//! [`sketch::SketchParams`], because it is the one family with more than one
+//! algorithm per purpose.
 //!
-//! A second, orthogonal axis lives here too: [`sketch::GroupingStrategy`]
-//! (issue #256) — *how many* physical instances of a chosen family/kind
-//! exist across a grouped aggregate's `by` subpopulations
-//! (`PerSubpopulationInstance`, today's only behavior, vs.
-//! `SharedMultiSubpopulation`/Hydra — see [`sketch::HydraKind`]/
-//! [`sketch::HydraParams`]), carried on [`expr::SummaryExpr::SummaryAgg`]
-//! alongside `reduction` and on sketch-valued edge types
-//! — see `asap_aware_mapping::grouping`'s module docs for why.
+//! [`sketch::GroupingStrategy`] is a second, orthogonal axis: how many
+//! physical instances of a summary exist across a grouped aggregate's `by`
+//! subpopulations (per-subpopulation vs. one shared Hydra instance — see
+//! `asap_aware_mapping::grouping`). It rides on `ASAPOp::SummaryAgg` and on
+//! sketch-valued edge types.
+//!
+//! The rest: accuracy guarantees ([`guarantee`]), maintained populations,
+//! summary windows and maintenance lifecycle, and the execution timing /
+//! data-state vocabulary ([`execution_data_state`]).
 
-// Legacy summary IR: no longer re-exported; removed by the cleanup PR.
-pub mod cse;
 pub mod execution_data_state;
-pub mod expr;
 pub mod guarantee;
 pub mod maintained_population;
-pub mod post_asap_dag;
 pub mod query_time;
 pub mod sketch;
 pub mod summary_maintenance;
@@ -45,31 +37,10 @@ pub use execution_data_state::{
     lift_plain, DataPrimitive, ExactOperationSchemaError, ExecutionDataState,
     ExecutionDataStateError, ExecutionTiming,
 };
-// Legacy summary IR names, kept for the legacy modules above only.
-#[allow(unused_imports)]
-pub(crate) use cse::share_common_summary_sub_dags;
-#[allow(unused_imports)]
-pub(crate) use execution_data_state::{
-    assigned_child_data_state, exact_operation_output_schema, produced_data_state,
-    validate_execution_data_states, validate_execution_data_states_at,
-    ExecutionDataStateAssignment,
-};
-#[allow(unused_imports)]
-pub(crate) use expr::{
-    BinaryOperator, CandidateCompleteness, ExactOperation, SummaryExpr, SummaryNode, ValueOperation,
-};
 pub use guarantee::{
     AccuracyError, BoundExpr, CompositionOperator, ErrorMetric, GuaranteeSource, ProbabilityExpr,
     ResultGuarantee,
 };
-#[allow(unused_imports)]
-pub(crate) use post_asap_dag::{
-    compile_post_asap_dag, compile_post_asap_dag_with_node_ids, EdgeRole,
-    GroupingEdgeCompatibility, PostAsapDAG, PostAsapDAGCompilation, PostAsapDAGDocument,
-    PostAsapDAGEdge, PostAsapDAGNode, PostAsapDAGValidationError, PostAsapNodeId,
-    PostAsapNodeIdentityMap, PostAsapOperatorPayload, WindowEdgeCompatibility,
-    POST_ASAP_DAG_WIRE_VERSION,
-};
 pub use query_time::{
     classic_cms_sizing, cms_posterior_error_bound, count_sketch_posterior_error_bound,
     cu_sketch_posterior_error_bound, traditional_a_priori_bound,
diff --git a/crates/types/src/post_asap/post_asap_dag.rs b/crates/types/src/post_asap/post_asap_dag.rs
deleted file mode 100644
index d489c055e..000000000
--- a/crates/types/src/post_asap/post_asap_dag.rs
+++ /dev/null
@@ -1,867 +0,0 @@
-//! Runtime-neutral post-ASAP DAG contract shared by precompute and query engines.
-
-use std::collections::HashMap;
-use std::rc::Rc;
-
-use super::{
-    validate_execution_data_states, ExecutionDataState, ExecutionDataStateError, ResultGuarantee,
-    Schema, SummaryExpr, SummaryNode,
-};
-use super::{
-    BinaryOperator, CandidateCompleteness, ExecutionTiming, FieldDataType, GroupingStrategy,
-    SketchStatistic, SummaryUpdate, ValueOperation,
-};
-use crate::pre_asap::{ColumnRef, JoinKind, Predicate, QueryExpr, Reduction};
-use thiserror::Error;
-
-pub const POST_ASAP_DAG_WIRE_VERSION: u32 = 6;
-
-#[derive(Debug, Clone, Copy, PartialEq, Eq, serde::Serialize, serde::Deserialize)]
-pub enum EdgeRole {
-    Input,
-    Left,
-    Right,
-}
-
-#[derive(Debug, Clone, Copy, PartialEq, Eq, serde::Serialize, serde::Deserialize)]
-pub enum GroupingEdgeCompatibility {
-    Identical,
-    ConsumerCoarsensProducer,
-    Incompatible,
-    NotApplicable,
-}
-
-#[derive(Debug, Clone, Copy, PartialEq, Eq, serde::Serialize, serde::Deserialize)]
-pub enum WindowEdgeCompatibility {
-    /// Physical lowering must prove equal pane/query phase or install an
-    /// exact boundary residual. The logical DAG alone cannot make that claim.
-    #[serde(rename = "RequiresAlignedPanePhaseOrExactBoundaryResidual")]
-    RequiresAlignedPanePhaseOrExactWindowEdgeResidual,
-    NotApplicable,
-}
-
-/// Stable identity of a node within one exported post-ASAP semantic DAG.
-#[derive(
-    Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord, Hash, serde::Serialize, serde::Deserialize,
-)]
-#[serde(transparent)]
-pub struct PostAsapNodeId(pub u32);
-
-#[derive(Debug, Clone, PartialEq, serde::Serialize, serde::Deserialize)]
-#[serde(tag = "kind", rename_all = "snake_case", deny_unknown_fields)]
-pub enum PostAsapOperatorPayload {
-    Fallback {
-        expression: QueryExpr,
-    },
-    Binary {
-        operator: BinaryOperator,
-    },
-    Value {
-        operation: ValueOperation,
-    },
-    RelationalJoin {
-        join_kind: JoinKind,
-        pred: Predicate,
-        pruning: Option<CandidateCompleteness>,
-    },
-    SummaryAgg {
-        family: FieldDataType,
-        input: SummaryUpdate,
-        reduction: Reduction,
-        grouping: GroupingStrategy,
-        /// See `SummaryExpr::SummaryAgg::filter`. Wire version 6 added it;
-        /// a version-5 reader would otherwise take a filtered summary as
-        /// unfiltered.
-        filter: Option<Predicate>,
-    },
-    SummaryJoin {
-        key: ColumnRef,
-        family: FieldDataType,
-    },
-    SummarySubtract,
-    SummaryDelete {
-        key: ColumnRef,
-    },
-    SummaryEstimate {
-        query: SketchStatistic,
-    },
-    SummaryMerge,
-}
-
-#[derive(Debug, Clone, PartialEq, serde::Serialize, serde::Deserialize)]
-#[serde(deny_unknown_fields)]
-pub struct PostAsapDAGNode {
-    pub id: PostAsapNodeId,
-    /// The payload variant is the sole operator identity (`payload.kind` in JSON).
-    pub payload: PostAsapOperatorPayload,
-    /// Phase is a placement choice for every operator, independent of payload kind.
-    pub output_state: ExecutionDataState,
-    pub output_schema: Schema,
-    pub guarantee: Option<ResultGuarantee>,
-}
-
-#[derive(Debug, Clone, PartialEq, serde::Serialize, serde::Deserialize)]
-#[serde(deny_unknown_fields)]
-pub struct PostAsapDAGEdge {
-    pub producer: PostAsapNodeId,
-    pub consumer: PostAsapNodeId,
-    pub role: EdgeRole,
-    pub intermediate_schema: Schema,
-    pub data_state: ExecutionDataState,
-    pub grouping: GroupingEdgeCompatibility,
-    pub window: WindowEdgeCompatibility,
-}
-
-#[derive(Debug, Clone, PartialEq, serde::Serialize, serde::Deserialize)]
-#[serde(deny_unknown_fields)]
-pub struct PostAsapDAG {
-    pub nodes: Vec<PostAsapDAGNode>,
-    pub edges: Vec<PostAsapDAGEdge>,
-    /// Semantic workload root. Physical query/precompute sinks are selected
-    /// downstream by the control plane.
-    pub root: PostAsapNodeId,
-}
-
-/// Versioned transport envelope for a post-ASAP semantic DAG.
-///
-/// Process boundaries exchange this envelope and call [`Self::validate`].
-#[derive(Debug, Clone, PartialEq, serde::Serialize, serde::Deserialize)]
-#[serde(deny_unknown_fields)]
-pub struct PostAsapDAGDocument {
-    pub schema_version: u32,
-    pub dag: PostAsapDAG,
-}
-
-#[derive(Debug, Clone, PartialEq, Eq, Error)]
-pub enum PostAsapDAGValidationError {
-    #[error("phase assignment must name every DAG node exactly once")]
-    IncompletePhaseAssignment,
-    #[error("ingestion node {consumer:?} depends on query node {producer:?}")]
-    QueryDependencyInIngestion {
-        producer: PostAsapNodeId,
-        consumer: PostAsapNodeId,
-    },
-    #[error("unsupported post-ASAP DAG schema version {0}")]
-    UnsupportedVersion(u32),
-    #[error("duplicate post-ASAP node id {0:?}")]
-    DuplicateNodeId(PostAsapNodeId),
-    #[error("post-ASAP DAG root {0:?} does not name a node")]
-    MissingRoot(PostAsapNodeId),
-    #[error("edge endpoint {0:?} does not name a node")]
-    MissingEdgeEndpoint(PostAsapNodeId),
-    #[error("edge {producer:?}->{consumer:?} schema differs from producer output")]
-    EdgeSchemaMismatch {
-        producer: PostAsapNodeId,
-        consumer: PostAsapNodeId,
-    },
-    #[error("edge {producer:?}->{consumer:?} data state differs from producer output")]
-    EdgeDataStateMismatch {
-        producer: PostAsapNodeId,
-        consumer: PostAsapNodeId,
-    },
-    #[error("post-ASAP DAG contains a cycle")]
-    Cycle,
-    #[error("post-ASAP node {0:?} is not reachable from the root")]
-    UnreachableNode(PostAsapNodeId),
-    #[error("summary aggregate node {node:?} output schema does not contain its declared family")]
-    SummaryFamilySchemaMismatch { node: PostAsapNodeId },
-    #[error(
-        "summary aggregate node {node:?} declares grouping inconsistent with its sketch state"
-    )]
-    SummaryGroupingMismatch { node: PostAsapNodeId },
-}
-
-impl PostAsapDAGDocument {
-    pub fn new(dag: PostAsapDAG) -> Self {
-        Self {
-            schema_version: POST_ASAP_DAG_WIRE_VERSION,
-            dag,
-        }
-    }
-
-    pub fn validate(&self) -> Result<(), PostAsapDAGValidationError> {
-        if self.schema_version != POST_ASAP_DAG_WIRE_VERSION {
-            return Err(PostAsapDAGValidationError::UnsupportedVersion(
-                self.schema_version,
-            ));
-        }
-        self.dag.validate()
-    }
-}
-
-impl PostAsapDAG {
-    /// Assign execution phases without changing operator semantics. Phase choices
-    /// do not prove deployment support: callers must bind concrete implementations
-    /// and storage boundaries before installing this plan.
-    pub fn with_execution_phases(
-        &self,
-        phases: &std::collections::BTreeMap<PostAsapNodeId, ExecutionTiming>,
-    ) -> Result<Self, PostAsapDAGValidationError> {
-        self.validate()?;
-        if phases.len() != self.nodes.len()
-            || self.nodes.iter().any(|node| !phases.contains_key(&node.id))
-        {
-            return Err(PostAsapDAGValidationError::IncompletePhaseAssignment);
-        }
-        let mut dag = self.clone();
-        for node in &mut dag.nodes {
-            node.output_state.timing = phases[&node.id];
-        }
-        let states: HashMap<_, _> = dag.nodes.iter().map(|n| (n.id, n.output_state)).collect();
-        for edge in &mut dag.edges {
-            edge.data_state = states[&edge.producer];
-        }
-        dag.validate()?;
-        Ok(dag)
-    }
-
-    pub fn validate(&self) -> Result<(), PostAsapDAGValidationError> {
-        use std::collections::{HashMap, HashSet};
-        let mut nodes = HashMap::new();
-        for node in &self.nodes {
-            if nodes.insert(node.id, node).is_some() {
-                return Err(PostAsapDAGValidationError::DuplicateNodeId(node.id));
-            }
-            if let PostAsapOperatorPayload::SummaryAgg {
-                family, grouping, ..
-            } = &node.payload
-            {
-                let mut found_family = false;
-                for field in &node.output_schema.fields {
-                    if &field.dtype == family {
-                        found_family = true;
-                    }
-                    if let FieldDataType::Sketch(_, schema_grouping) = &field.dtype {
-                        if schema_grouping != grouping {
-                            return Err(PostAsapDAGValidationError::SummaryGroupingMismatch {
-                                node: node.id,
-                            });
-                        }
-                    }
-                }
-                if !found_family {
-                    return Err(PostAsapDAGValidationError::SummaryFamilySchemaMismatch {
-                        node: node.id,
-                    });
-                }
-            }
-        }
-        if !nodes.contains_key(&self.root) {
-            return Err(PostAsapDAGValidationError::MissingRoot(self.root));
-        }
-        let mut children: HashMap<PostAsapNodeId, Vec<PostAsapNodeId>> = HashMap::new();
-        for edge in &self.edges {
-            let producer = nodes.get(&edge.producer).ok_or(
-                PostAsapDAGValidationError::MissingEdgeEndpoint(edge.producer),
-            )?;
-            if !nodes.contains_key(&edge.consumer) {
-                return Err(PostAsapDAGValidationError::MissingEdgeEndpoint(
-                    edge.consumer,
-                ));
-            }
-            if producer.output_state.timing == ExecutionTiming::QueryTime
-                && nodes[&edge.consumer].output_state.timing == ExecutionTiming::IngestionTime
-            {
-                return Err(PostAsapDAGValidationError::QueryDependencyInIngestion {
-                    producer: edge.producer,
-                    consumer: edge.consumer,
-                });
-            }
-            if edge.intermediate_schema != producer.output_schema {
-                return Err(PostAsapDAGValidationError::EdgeSchemaMismatch {
-                    producer: edge.producer,
-                    consumer: edge.consumer,
-                });
-            }
-            if edge.data_state != producer.output_state {
-                return Err(PostAsapDAGValidationError::EdgeDataStateMismatch {
-                    producer: edge.producer,
-                    consumer: edge.consumer,
-                });
-            }
-            children
-                .entry(edge.consumer)
-                .or_default()
-                .push(edge.producer);
-        }
-        fn visit(
-            id: PostAsapNodeId,
-            children: &HashMap<PostAsapNodeId, Vec<PostAsapNodeId>>,
-            visiting: &mut HashSet<PostAsapNodeId>,
-            visited: &mut HashSet<PostAsapNodeId>,
-        ) -> bool {
-            if visited.contains(&id) {
-                return true;
-            }
-            if !visiting.insert(id) {
-                return false;
-            }
-            if children
-                .get(&id)
-                .into_iter()
-                .flatten()
-                .any(|child| !visit(*child, children, visiting, visited))
-            {
-                return false;
-            }
-            visiting.remove(&id);
-            visited.insert(id);
-            true
-        }
-        if !visit(
-            self.root,
-            &children,
-            &mut HashSet::new(),
-            &mut HashSet::new(),
-        ) {
-            return Err(PostAsapDAGValidationError::Cycle);
-        }
-        let mut reachable = HashSet::new();
-        fn mark(
-            id: PostAsapNodeId,
-            children: &HashMap<PostAsapNodeId, Vec<PostAsapNodeId>>,
-            reachable: &mut HashSet<PostAsapNodeId>,
-        ) {
-            if !reachable.insert(id) {
-                return;
-            }
-            for child in children.get(&id).into_iter().flatten() {
-                mark(*child, children, reachable);
-            }
-        }
-        mark(self.root, &children, &mut reachable);
-        if let Some(id) = nodes.keys().find(|id| !reachable.contains(id)) {
-            return Err(PostAsapDAGValidationError::UnreachableNode(*id));
-        }
-        Ok(())
-    }
-}
-
-/// Compiler-local identity assignment. It deliberately retains `Rc` handles
-/// and is not serialized; deployed artifacts persist the post-ASAP node ID
-/// together with their physical materialization/query IDs.
-#[derive(Debug, Clone)]
-pub struct PostAsapNodeIdentityMap {
-    nodes_by_id: Vec<Rc<SummaryNode>>,
-}
-
-impl PostAsapNodeIdentityMap {
-    pub fn node_id(&self, node: &Rc<SummaryNode>) -> Option<PostAsapNodeId> {
-        self.nodes_by_id
-            .iter()
-            .position(|candidate| Rc::ptr_eq(candidate, node))
-            .map(|id| PostAsapNodeId(id as u32))
-    }
-
-    pub fn summary_node(&self, id: PostAsapNodeId) -> Option<&Rc<SummaryNode>> {
-        self.nodes_by_id.get(id.0 as usize)
-    }
-}
-
-#[derive(Debug, Clone)]
-pub struct PostAsapDAGCompilation {
-    pub dag: PostAsapDAG,
-    pub node_ids: PostAsapNodeIdentityMap,
-}
-
-pub fn compile_post_asap_dag(
-    root: &Rc<SummaryNode>,
-) -> Result<PostAsapDAG, ExecutionDataStateError> {
-    Ok(compile_post_asap_dag_with_node_ids(root)?.dag)
-}
-
-pub fn compile_post_asap_dag_with_node_ids(
-    root: &Rc<SummaryNode>,
-) -> Result<PostAsapDAGCompilation, ExecutionDataStateError> {
-    let assignment = validate_execution_data_states(root)?;
-    let mut nodes = Vec::new();
-    let mut edges = Vec::new();
-    let mut ids = HashMap::new();
-    let mut nodes_by_id = Vec::new();
-
-    fn visit(
-        node: &Rc<SummaryNode>,
-        assignment: &super::ExecutionDataStateAssignment,
-        ids: &mut HashMap<*const SummaryNode, PostAsapNodeId>,
-        nodes: &mut Vec<PostAsapDAGNode>,
-        edges: &mut Vec<PostAsapDAGEdge>,
-        nodes_by_id: &mut Vec<Rc<SummaryNode>>,
-    ) -> PostAsapNodeId {
-        if let Some(id) = ids.get(&Rc::as_ptr(node)) {
-            return *id;
-        }
-        let children: Vec<(&Rc<SummaryNode>, EdgeRole)> = match &node.expr {
-            SummaryExpr::KeepPreAsap(_) => vec![],
-            SummaryExpr::BinaryOp { lhs, rhs, .. } => {
-                vec![(lhs, EdgeRole::Left), (rhs, EdgeRole::Right)]
-            }
-
-            SummaryExpr::ValueOperation { child, .. } | SummaryExpr::SummaryAgg { child, .. } => {
-                vec![(child, EdgeRole::Input)]
-            }
-            SummaryExpr::RelationalJoin { left, right, .. } => {
-                vec![(left, EdgeRole::Left), (right, EdgeRole::Right)]
-            }
-            SummaryExpr::SummaryJoin { outer, inner, .. } => {
-                vec![(outer, EdgeRole::Left), (inner, EdgeRole::Right)]
-            }
-            SummaryExpr::SummarySubtract { left, right } => {
-                vec![(left, EdgeRole::Left), (right, EdgeRole::Right)]
-            }
-            SummaryExpr::SummaryDelete { summary_input, .. }
-            | SummaryExpr::SummaryEstimate { summary_input, .. } => {
-                vec![(summary_input, EdgeRole::Input)]
-            }
-            SummaryExpr::SummaryMerge { children, .. } => {
-                children.iter().map(|c| (c, EdgeRole::Input)).collect()
-            }
-        };
-        let child_ids: Vec<_> = children
-            .iter()
-            .map(|(c, r)| (visit(c, assignment, ids, nodes, edges, nodes_by_id), *c, *r))
-            .collect();
-        let id = PostAsapNodeId(nodes.len() as u32);
-        let state = assignment
-            .data_state_of(node)
-            .expect("validated node has state");
-        let payload = match &node.expr {
-            SummaryExpr::KeepPreAsap(expression) => PostAsapOperatorPayload::Fallback {
-                expression: (**expression).clone(),
-            },
-            SummaryExpr::BinaryOp { operator, .. } => PostAsapOperatorPayload::Binary {
-                operator: operator.clone(),
-            },
-
-            SummaryExpr::ValueOperation { operation, .. } => PostAsapOperatorPayload::Value {
-                operation: operation.clone(),
-            },
-            SummaryExpr::RelationalJoin {
-                kind,
-                pred,
-                pruning,
-                ..
-            } => PostAsapOperatorPayload::RelationalJoin {
-                join_kind: kind.clone(),
-                pred: pred.clone(),
-                pruning: pruning.clone(),
-            },
-            SummaryExpr::SummaryAgg {
-                family,
-                input,
-                reduction,
-                grouping,
-                filter,
-                ..
-            } => PostAsapOperatorPayload::SummaryAgg {
-                family: family.clone(),
-                input: input.clone(),
-                reduction: reduction.clone(),
-                grouping: grouping.clone(),
-                filter: filter.clone(),
-            },
-            SummaryExpr::SummaryJoin { key, family, .. } => PostAsapOperatorPayload::SummaryJoin {
-                key: key.clone(),
-                family: family.clone(),
-            },
-            SummaryExpr::SummarySubtract { .. } => PostAsapOperatorPayload::SummarySubtract,
-            SummaryExpr::SummaryDelete { key, .. } => {
-                PostAsapOperatorPayload::SummaryDelete { key: key.clone() }
-            }
-            SummaryExpr::SummaryEstimate { query, .. } => {
-                PostAsapOperatorPayload::SummaryEstimate {
-                    query: query.clone(),
-                }
-            }
-            SummaryExpr::SummaryMerge { .. } => PostAsapOperatorPayload::SummaryMerge,
-        };
-        nodes.push(PostAsapDAGNode {
-            id,
-            payload,
-            output_state: state,
-            output_schema: node.schema.clone(),
-            guarantee: node.guarantee.clone(),
-        });
-        nodes_by_id.push(Rc::clone(node));
-        ids.insert(Rc::as_ptr(node), id);
-        for (producer, child, role) in child_ids {
-            let maintenance_dependency = nodes[producer.0 as usize].output_state.timing
-                == ExecutionTiming::IngestionTime
-                && nodes[id.0 as usize].output_state.timing == ExecutionTiming::IngestionTime;
-            let grouping = match (&child.expr, &node.expr) {
-                (
-                    SummaryExpr::SummaryAgg {
-                        reduction: producer,
-                        ..
-                    },
-                    SummaryExpr::SummaryAgg {
-                        reduction: consumer,
-                        ..
-                    },
-                ) if producer == consumer => GroupingEdgeCompatibility::Identical,
-                (
-                    SummaryExpr::SummaryAgg {
-                        reduction: crate::pre_asap::Reduction::PerEntity,
-                        ..
-                    },
-                    SummaryExpr::SummaryAgg {
-                        reduction: crate::pre_asap::Reduction::Reduce(_),
-                        ..
-                    },
-                ) => GroupingEdgeCompatibility::ConsumerCoarsensProducer,
-                (
-                    SummaryExpr::SummaryAgg {
-                        reduction: crate::pre_asap::Reduction::Reduce(producer),
-                        ..
-                    },
-                    SummaryExpr::SummaryAgg {
-                        reduction: crate::pre_asap::Reduction::Reduce(consumer),
-                        ..
-                    },
-                ) if !producer.is_without()
-                    && !consumer.is_without()
-                    && consumer.iter().all(|key| producer.contains(key)) =>
-                {
-                    GroupingEdgeCompatibility::ConsumerCoarsensProducer
-                }
-                (SummaryExpr::SummaryAgg { .. }, SummaryExpr::SummaryAgg { .. }) => {
-                    GroupingEdgeCompatibility::Incompatible
-                }
-                _ => GroupingEdgeCompatibility::NotApplicable,
-            };
-            edges.push(PostAsapDAGEdge {
-                producer,
-                consumer: id,
-                role,
-                intermediate_schema: child.schema.clone(),
-                // The whole-DAG validator owns contextual state assignment,
-                // especially for shared KeepPreAsap leaves. Export that
-                // authoritative result instead of independently deriving the
-                // edge state a second time.
-                data_state: assignment
-                    .data_state_of(child)
-                    .expect("validated child has data state"),
-                grouping,
-                window: if maintenance_dependency {
-                    WindowEdgeCompatibility::RequiresAlignedPanePhaseOrExactWindowEdgeResidual
-                } else {
-                    WindowEdgeCompatibility::NotApplicable
-                },
-            });
-        }
-        id
-    }
-
-    let root = visit(
-        root,
-        &assignment,
-        &mut ids,
-        &mut nodes,
-        &mut edges,
-        &mut nodes_by_id,
-    );
-    let dag = PostAsapDAG { nodes, edges, root };
-    dag.validate()
-        .expect("compiler emits a valid post-ASAP DAG");
-    Ok(PostAsapDAGCompilation {
-        dag,
-        node_ids: PostAsapNodeIdentityMap { nodes_by_id },
-    })
-}
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-    use crate::post_asap::{
-        ExactKind, ExactParams, ExecutionTiming, FieldDataType, GroupingStrategy, SummaryUpdate,
-        ValueOperation,
-    };
-    use crate::pre_asap::schema::{Field, Schema};
-    use crate::pre_asap::{ColumnRef, DataType, QueryExpr, Reduction, Source};
-    use std::collections::BTreeMap;
-
-    #[test]
-    fn every_physical_payload_can_be_assigned_either_phase() {
-        use crate::post_asap::DataPrimitive;
-        use crate::pre_asap::{ArithmeticOpKind, BinaryOpKind, JoinKind, Predicate, ScalarValue};
-        let family = FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum);
-        let predicate = Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Boolean(true))));
-        let payloads = vec![
-            PostAsapOperatorPayload::Fallback {
-                expression: QueryExpr::Literal(ScalarValue::Int64(1)),
-            },
-            PostAsapOperatorPayload::Binary {
-                operator: BinaryOperator {
-                    checked_relative_division: false,
-                    checked_finite_division: false,
-                    kind: BinaryOpKind::Arithmetic(ArithmeticOpKind::Add),
-                    vector_match: None,
-                },
-            },
-            PostAsapOperatorPayload::Value {
-                operation: ValueOperation::Limit {
-                    n: 1,
-                    offset: 0,
-                    partition_by: Default::default(),
-                },
-            },
-            PostAsapOperatorPayload::RelationalJoin {
-                join_kind: JoinKind::Semi,
-                pred: predicate,
-                pruning: None,
-            },
-            PostAsapOperatorPayload::SummaryAgg {
-                family: family.clone(),
-                input: SummaryUpdate::column(ColumnRef::SampleValue),
-                reduction: Reduction::by(vec![]),
-                grouping: GroupingStrategy::default(),
-                filter: None,
-            },
-            PostAsapOperatorPayload::SummaryJoin {
-                key: ColumnRef::SampleValue,
-                family: family.clone(),
-            },
-            PostAsapOperatorPayload::SummarySubtract,
-            PostAsapOperatorPayload::SummaryDelete {
-                key: ColumnRef::SampleValue,
-            },
-            PostAsapOperatorPayload::SummaryEstimate {
-                query: SketchStatistic::Cardinality,
-            },
-            PostAsapOperatorPayload::SummaryMerge,
-        ];
-        for payload in payloads {
-            // This checks physical identity and placement, not kernel availability.
-            let primitive = match &payload {
-                PostAsapOperatorPayload::Fallback { .. }
-                | PostAsapOperatorPayload::Binary { .. }
-                | PostAsapOperatorPayload::Value { .. }
-                | PostAsapOperatorPayload::RelationalJoin { .. }
-                | PostAsapOperatorPayload::SummaryEstimate { .. } => DataPrimitive::Raw,
-                PostAsapOperatorPayload::SummaryAgg { .. }
-                | PostAsapOperatorPayload::SummaryJoin { .. }
-                | PostAsapOperatorPayload::SummarySubtract
-                | PostAsapOperatorPayload::SummaryDelete { .. }
-                | PostAsapOperatorPayload::SummaryMerge => DataPrimitive::SummaryState,
-            };
-            let dag = PostAsapDAG {
-                root: PostAsapNodeId(0),
-                edges: vec![],
-                nodes: vec![PostAsapDAGNode {
-                    id: PostAsapNodeId(0),
-                    payload: payload.clone(),
-                    output_state: ExecutionDataState {
-                        timing: ExecutionTiming::QueryTime,
-                        primitive,
-                    },
-                    output_schema: Schema::lifted(
-                        vec![Field {
-                            name: "value".into(),
-                            dtype: family.clone(),
-                            nullable: false,
-                            table: None,
-                        }],
-                        None,
-                    ),
-                    guarantee: None,
-                }],
-            };
-            for phase in [ExecutionTiming::IngestionTime, ExecutionTiming::QueryTime] {
-                let placed = dag
-                    .with_execution_phases(&BTreeMap::from([(dag.root, phase)]))
-                    .unwrap();
-                assert_eq!(placed.nodes[0].payload, payload);
-                assert_eq!(placed.nodes[0].output_state.timing, phase);
-                let wire = serde_json::to_value(&placed).unwrap();
-                assert!(wire["nodes"][0]["payload"].get("timing").is_none());
-                assert_eq!(serde_json::from_value::<PostAsapDAG>(wire).unwrap(), placed);
-            }
-            assert!(dag.with_execution_phases(&BTreeMap::new()).is_err());
-        }
-    }
-
-    #[test]
-    fn phase_assignment_updates_edges_and_rejects_query_dependencies_in_ingestion() {
-        use crate::pre_asap::ScalarValue;
-        let schema = Schema::lifted(vec![], None);
-        let nodes = [0, 1]
-            .into_iter()
-            .map(|id| PostAsapDAGNode {
-                id: PostAsapNodeId(id),
-                payload: PostAsapOperatorPayload::Fallback {
-                    expression: QueryExpr::Literal(ScalarValue::Int64(1)),
-                },
-                output_state: ExecutionDataState::QUERY_ROWS,
-                output_schema: schema.clone(),
-                guarantee: None,
-            })
-            .collect();
-        let dag = PostAsapDAG {
-            nodes,
-            root: PostAsapNodeId(1),
-            edges: vec![PostAsapDAGEdge {
-                producer: PostAsapNodeId(0),
-                consumer: PostAsapNodeId(1),
-                role: EdgeRole::Input,
-                intermediate_schema: schema,
-                data_state: ExecutionDataState::QUERY_ROWS,
-                grouping: GroupingEdgeCompatibility::NotApplicable,
-                window: WindowEdgeCompatibility::NotApplicable,
-            }],
-        };
-        let placed = dag
-            .with_execution_phases(&BTreeMap::from([
-                (PostAsapNodeId(0), ExecutionTiming::IngestionTime),
-                (PostAsapNodeId(1), ExecutionTiming::QueryTime),
-            ]))
-            .unwrap();
-        assert_eq!(
-            placed.edges[0].data_state.timing,
-            ExecutionTiming::IngestionTime
-        );
-        assert_eq!(dag.edges[0].data_state.timing, ExecutionTiming::QueryTime);
-        assert!(matches!(
-            dag.with_execution_phases(&BTreeMap::from([
-                (PostAsapNodeId(0), ExecutionTiming::QueryTime),
-                (PostAsapNodeId(1), ExecutionTiming::IngestionTime),
-            ])),
-            Err(PostAsapDAGValidationError::QueryDependencyInIngestion { .. })
-        ));
-    }
-
-    #[test]
-    fn exports_summary_over_summary_as_typed_precompute_edges() {
-        let scan = Rc::new(QueryExpr::Scan {
-            source: Source::TimeSeries { metric: "m".into() },
-            predicates: vec![],
-            schema: Schema::new(vec![Field::plain("value", DataType::Float64, false)]),
-        });
-        let raw = Rc::new(SummaryNode {
-            expr: SummaryExpr::KeepPreAsap(scan),
-            schema: Schema::lifted(
-                vec![Field {
-                    name: "value".into(),
-                    dtype: FieldDataType::Plain(DataType::Float64),
-                    nullable: false,
-                    table: None,
-                }],
-                None,
-            ),
-            guarantee: None,
-        });
-        let make_agg = |child: Rc<SummaryNode>, kind, params| {
-            let family = FieldDataType::ExactAggregate(kind, params);
-            Rc::new(SummaryNode {
-                expr: SummaryExpr::SummaryAgg {
-                    child,
-                    family: family.clone(),
-                    input: SummaryUpdate::column(ColumnRef::SampleValue),
-                    reduction: Reduction::by(vec![]),
-                    grouping: GroupingStrategy::default(),
-                    filter: None,
-                },
-                schema: Schema::lifted(
-                    vec![Field {
-                        name: "value".into(),
-                        dtype: family,
-                        nullable: false,
-                        table: None,
-                    }],
-                    None,
-                ),
-                guarantee: None,
-            })
-        };
-        let inner = make_agg(raw, ExactKind::Sum, ExactParams::Sum);
-        let outer = make_agg(Rc::clone(&inner), ExactKind::Sum, ExactParams::Sum);
-        let root = Rc::new(SummaryNode {
-            expr: SummaryExpr::ValueOperation {
-                child: outer,
-                operation: ValueOperation::FinalizeExactAccumulator,
-                timing: ExecutionTiming::QueryTime,
-            },
-            schema: Schema::lifted(
-                vec![Field {
-                    name: "value".into(),
-                    dtype: FieldDataType::Plain(DataType::Float64),
-                    nullable: false,
-                    table: None,
-                }],
-                None,
-            ),
-            guarantee: None,
-        });
-
-        let compiled = compile_post_asap_dag_with_node_ids(&root).unwrap();
-        assert_eq!(compiled.node_ids.node_id(&root), Some(PostAsapNodeId(3)));
-        assert!(Rc::ptr_eq(
-            compiled.node_ids.summary_node(PostAsapNodeId(1)).unwrap(),
-            &inner
-        ));
-        let dag = compiled.dag;
-        assert_eq!(dag.root, PostAsapNodeId(3));
-        assert_eq!(
-            dag.nodes[1].output_state,
-            ExecutionDataState::INGESTION_SUMMARY
-        );
-        assert_eq!(
-            dag.nodes[2].output_state,
-            ExecutionDataState::INGESTION_SUMMARY
-        );
-        let dependency = dag
-            .edges
-            .iter()
-            .find(|e| e.producer == PostAsapNodeId(1) && e.consumer == PostAsapNodeId(2))
-            .unwrap();
-        assert_eq!(dependency.data_state, ExecutionDataState::INGESTION_SUMMARY);
-        assert_eq!(dependency.grouping, GroupingEdgeCompatibility::Identical);
-        assert_eq!(
-            dependency.window,
-            WindowEdgeCompatibility::RequiresAlignedPanePhaseOrExactWindowEdgeResidual
-        );
-        assert!(matches!(
-            dependency.intermediate_schema.fields[0].dtype,
-            FieldDataType::ExactAggregate(ExactKind::Sum, _)
-        ));
-        let encoded = serde_json::to_string(&dag).expect("serialize post-ASAP DAG");
-        let decoded: PostAsapDAG =
-            serde_json::from_str(&encoded).expect("deserialize post-ASAP DAG");
-        assert_eq!(decoded, dag);
-        let document = PostAsapDAGDocument::new(decoded);
-        document.validate().unwrap();
-        let mut invalid = serde_json::to_value(&document).unwrap();
-        invalid["dag"]["nodes"][0]["operator"] = serde_json::json!("Binary");
-        assert!(serde_json::from_value::<PostAsapDAGDocument>(invalid).is_err());
-        assert!(document.dag.nodes.iter().all(|node| {
-            let wire = serde_json::to_value(node).unwrap();
-            wire.get("operator").is_none() && wire["payload"]["kind"].is_string()
-        }));
-        let mut old_version = document.clone();
-        old_version.schema_version = 1;
-        assert_eq!(
-            old_version.validate(),
-            Err(PostAsapDAGValidationError::UnsupportedVersion(1))
-        );
-        let mut unknown = serde_json::to_value(&document).unwrap();
-        unknown["unexpected"] = serde_json::json!(true);
-        assert!(serde_json::from_value::<PostAsapDAGDocument>(unknown).is_err());
-        assert!(matches!(
-            dag.nodes[2].payload,
-            PostAsapOperatorPayload::SummaryAgg {
-                family: FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum),
-                reduction: Reduction::Reduce(_),
-                ..
-            }
-        ));
-    }
-
-    #[test]
-    fn post_asap_node_ids_serialize_in_deterministic_binding_order() {
-        let mut bindings = BTreeMap::new();
-        bindings.insert(PostAsapNodeId(10), "materialization-10");
-        bindings.insert(PostAsapNodeId(2), "query-2");
-        assert_eq!(
-            serde_json::to_string(&bindings).unwrap(),
-            r#"{"2":"query-2","10":"materialization-10"}"#
-        );
-    }
-}
diff --git a/crates/types/src/pre_asap/agg_intent.rs b/crates/types/src/pre_asap/agg_intent.rs
index c60dd55e3..1e926bd44 100644
--- a/crates/types/src/pre_asap/agg_intent.rs
+++ b/crates/types/src/pre_asap/agg_intent.rs
@@ -10,28 +10,28 @@
 //! heavy-hitter sketch when approximate — is a post-ASAP cost-aware decision,
 //! not encoded here. The semantic distinction that *is* made at lowering is
 //! intent vs operator: a heavy-hitter aggregate becomes `TopK`, whereas a
-//! generic `ORDER BY value LIMIT k` stays as the `QueryExpr::Sort + Limit`
+//! generic `ORDER BY value LIMIT k` stays as the `NonASAPOp::Sort + Limit`
 //! operator pair.
 
 use serde::{Deserialize, Serialize};
 
-use crate::pre_asap::query_expr::DataModel;
+use crate::ir::operator_properties::DataModel;
 use crate::pre_asap::schema::{ColumnId, DataType, Field, FieldDataType};
 use crate::types::AccuracyTarget;
 
 /// "What to compute" — the vocabulary the planner pivots on.
 ///
-/// Grouping for `TopK` rides on the enclosing `QueryExpr::Aggregate.by`
+/// Grouping for `TopK` rides on the enclosing `NonASAPOp::Aggregate`'s `reduction`
 /// (positional `ColumnId`s), like every other aggregate; the intent itself
 /// carries only `k` + the accuracy target.
 ///
 /// The single-column reducers (`Sum` / `Min` / `Max` / `Avg` / `StdDev` /
 /// `Variance` / `Quantile`) carry `col: Option<C>` — the input
 /// column they reduce, generic over the column-reference state the same way
-/// [`QueryExpr`](super::query_expr::QueryExpr) is: positional `ColumnId` once
-/// bound (the default, and every existing use of the bare `AggIntent` name),
-/// or an unresolved name-based `ColumnRef` for a front end constructing this
-/// intent directly, before the [`SchemaResolver`](super::schema_resolver::SchemaResolver) has run.
+/// the rest of the vocabulary is: positional `ColumnId` once bound (the
+/// default, and every existing use of the bare `AggIntent` name), or an
+/// unresolved name-based `ColumnRef` for a front end constructing this
+/// intent directly, before name resolution (`asap_frontend_common`) has run.
 /// `None` is the PromQL convention "the time-series sample value"; SQL
 /// `SUM(bytes), AVG(latency)` sets distinct `Some(_)`s so a multi-aggregate
 /// node binds each reducer to the right column, and `plan::bind` knows which
@@ -128,7 +128,7 @@ pub enum AggIntent<C = ColumnId> {
 
     // ── Time-series streaming derivatives ────────────────────────────────
     // Counter-reset adjustment; not equivalent to Sum/Count over a window.
-    // The temporal range lives on the enclosing `QueryExpr::TimeRange` node,
+    // The temporal range lives on the enclosing `NonASAPOp::TimeRange` node,
     // not in the intent — this keeps the intent vocabulary range-agnostic.
     Rate,
     /// PromQL `irate(v[w])` — reset-aware rate from the final two samples.
@@ -234,7 +234,7 @@ pub enum AggIntent<C = ColumnId> {
     /// A time / calendar accessor (issue #46) — `timestamp`, `minute`, `hour`,
     /// `day_of_week`, … over each sample's timestamp (or, for the no-arg forms,
     /// over the evaluation time). Label-preserving per-series value transform.
-    /// (`time()` is the evaluation time itself — a `QueryExpr::EvalTimestamp` leaf,
+    /// (`time()` is the evaluation time itself — a `ScalarExpr::EvalTimestamp` leaf,
     /// not this.)
     TimeFn(TimeFunc),
 
@@ -378,9 +378,8 @@ pub enum MathFunc {
 }
 
 // `requires` / `is_per_series` / `output_column` never read `col`'s value —
-// only its presence via a `{ .. }` pattern — so, unlike
-// `QueryExpr::output_schema` (which genuinely cannot compile for an
-// unresolved DAG — see its own doc), nothing stops these from being generic
+// only its presence via a `{ .. }` pattern — so, unlike schema derivation
+// (which needs bound positions), nothing stops these from being generic
 // over every `C`. And a front end constructing `AggIntent<ColumnRef>`
 // directly (issue #179) does need `is_per_series` pre-binding — it decides
 // the `PerEntity`/`Reduce` reduction shape right at construction time (see
@@ -529,7 +528,7 @@ impl<C: Clone> AggIntent<C> {
 
 impl<C: Clone> AggIntent<C> {
     /// Output column name + type produced by this intent over `input`.
-    /// Used by `QueryExpr::Aggregate`'s schema-derivation rule. The PromQL
+    /// Used by `NonASAPOp::Aggregate`'s schema-derivation rule. The PromQL
     /// convention names the column after the intent kind so consumers can
     /// locate it without an alias lookup.
     pub fn output_column(&self, input: &Field) -> Field {
diff --git a/crates/types/src/pre_asap/canonicalize.rs b/crates/types/src/pre_asap/canonicalize.rs
deleted file mode 100644
index b9e6a653a..000000000
--- a/crates/types/src/pre_asap/canonicalize.rs
+++ /dev/null
@@ -1,782 +0,0 @@
-//! Shared post-lowering canonicalization of the resolved [`QueryExpr`].
-//!
-//! Both language front ends funnel through [`resolve_root`](super::resolve::resolve_root),
-//! which runs this pass over the resolved DAG. Its job is to erase
-//! *structural* differences between semantically identical queries so a
-//! post-ASAP binding rule matching on the intent algebra sees one canonical
-//! spelling regardless of source language (issue #34).
-//!
-//! ## Heavy-hitter promotion
-//!
-//! An additive-ranked "order by the aggregate, take the top k" is a
-//! heavy-hitter represented by [`AggIntent::TopK`]. Front ends may
-//! emit it as an ordinary `Limit { Sort { … Aggregate } }`; this pass promotes
-//! that shape to the canonical
-//!
-//! ```text
-//! Aggregate { reduction: Reduce(<partition>), measures: [TopK{k}],
-//!             child: Aggregate { measures: [Count | Sum], … } }
-//! ```
-//!
-//! Count supplies unit weights and Sum supplies value weights. Because the
-//! match is positional, aliases do not affect it. Other ranked expressions
-//! retain Sort + Limit.
-
-use std::rc::Rc;
-
-use super::agg_intent::{topk, AggIntent};
-use super::expr_ir::{CompareOpKind, ScalarValue};
-use super::query_expr::{Predicate, QueryExpr, Reduction, SortKey, WindowFuncKind};
-use crate::types::AccuracyTarget;
-
-/// Rewrite `expr` into its canonical form (bottom-up). Idempotent: a DAG that
-/// is already canonical is returned unchanged.
-pub fn canonicalize(mut expr: QueryExpr) -> QueryExpr {
-    canon(&mut expr);
-    expr
-}
-
-fn canon(expr: &mut QueryExpr) {
-    // A `Concat` asserting a caller-proven `discriminator_unique_key` (issue
-    // #228) had that key's `ColumnId`s resolved, in `resolve.rs`, against
-    // exactly the first branch's output schema *as it stood before this
-    // pass ran*. `try_promote_additive_top_ranking`/`try_rewrite_rownumber_topk`
-    // below can restructure that branch (anywhere within it — not only at
-    // its own top level, since the same recursive walk can rewrite a node
-    // nested under a pass-through wrapper too) into a shape with a
-    // different output schema, which would leave those `ColumnId`s
-    // pointing at the wrong column, or out of bounds, of the
-    // post-canonicalize schema. Snapshot the schema the discriminator key
-    // was actually resolved against, right here, before recursing into the
-    // children — this is the exact DAG state `resolve.rs` saw.
-    let discriminator_branch_schema_before = match expr {
-        QueryExpr::Concat {
-            children,
-            discriminator_unique_key: Some(_),
-        } => children.first().and_then(|c| c.output_schema().ok()),
-        _ => None,
-    };
-
-    // Bottom-up: canonicalize every child before matching at this node, so an
-    // inner heavy-hitter is promoted before an enclosing rewrite inspects it.
-    for child in children_mut(expr) {
-        canon(child);
-    }
-
-    // If the first branch's output schema moved out from under the asserted
-    // key, the key can no longer be trusted — drop it (never re-derive it by
-    // guessing at name/position: the two rewrites above don't preserve
-    // column identity in a way that's safe to infer). A wrong `unique_keys`
-    // claim is a wrong query answer, not a missed optimization — see
-    // `ConcatDiscriminatorKey`'s soundness doc — so this errs conservatively:
-    // any difference at all (not just a column-count/type change) drops the
-    // key, including the schema becoming undecidable in either direction.
-    if let QueryExpr::Concat {
-        children,
-        discriminator_unique_key: key @ Some(_),
-    } = expr
-    {
-        let discriminator_branch_schema_after =
-            children.first().and_then(|c| c.output_schema().ok());
-        if discriminator_branch_schema_before != discriminator_branch_schema_after {
-            *key = None;
-        }
-    }
-
-    // Local rewrites chain: a `ROW_NUMBER()`-partitioned top-k rewrites to a
-    // `Limit{Sort}`, which the heavy-hitter rule may then promote to an
-    // `Aggregate([TopK])`. Each rule strictly simplifies the node, so applying
-    // them to a fixpoint terminates.
-    while let Some(rewritten) =
-        try_rewrite_rownumber_topk(expr).or_else(|| try_promote_additive_top_ranking(expr))
-    {
-        *expr = rewritten;
-    }
-}
-
-/// A `&mut QueryExpr` out of a child `Rc<QueryExpr>` — clone-on-write via
-/// [`Rc::make_mut`]: free (no clone) while `r` is uniquely owned, which is
-/// the overwhelmingly common case (a DAG `canonicalize` was just handed by
-/// value); falls back to cloning just *this* node (its own fields — the
-/// grandchildren stay shared `Rc`s, not deep-copied) only when some other
-/// owner still holds the same `Rc`, e.g. a caller that kept its own clone
-/// around (`once.clone()` in `is_idempotent` below — `QueryExpr::clone()` is
-/// now a cheap `Rc`-bump, not a deep copy, so that clone shares structure
-/// with `once` until a rewrite here needs to touch it). `Rc::get_mut` would
-/// panic on exactly that case; `make_mut` degrades to a shallow copy instead
-/// of requiring sole ownership as a precondition. Once a workload-level CSE
-/// pass runs (issue #212, #222) and canonicalize sees an already-shared
-/// sub-DAG from a *different* query, this is also the mechanism that keeps
-/// canonicalizing one query from silently corrupting another's view of the
-/// same shared node.
-fn rc_mut(r: &mut Rc<QueryExpr>) -> &mut QueryExpr {
-    Rc::make_mut(r)
-}
-
-/// Mutable references to the direct **operator** `QueryExpr` children of a
-/// node — `canon`'s own top-down/bottom-up walk only ever visits the
-/// relational skeleton, never descending into a scalar position (`Filter.pred`,
-/// `ProjectItem.expr`, …): none of the three rewrite rules rewrite anything
-/// inside a scalar sub-DAG, so there's nothing to gain by recursing into one,
-/// and every scalar variant (issue #205) hits the catch-all below.
-fn children_mut(expr: &mut QueryExpr) -> Vec<&mut QueryExpr> {
-    use QueryExpr::*;
-    match expr {
-        // `PromqlScalarBridge`'s child is a scalar-sub-language node (issue
-        // #220), not the relational skeleton — same "no children to recurse
-        // into" treatment as the scalar variants below.
-        Scan { .. } | EvalTimestamp | CurrentTimestamp | PromqlScalarBridge(_) => vec![],
-        PromqlVectorFromScalar(c) | PromqlScalarFromVector(c) => vec![rc_mut(c)],
-        PromqlRelabel { child, .. }
-        | Filter { child, .. }
-        | Project { child, .. }
-        | Aggregate { child, .. }
-        | Dedup { child, .. }
-        | PromqlSubquery { child, .. }
-        | TimeRange { child, .. }
-        | TimeShift { child, .. }
-        | SQLWindowFunc { child, .. }
-        | PromqlSeriesSample { child, .. }
-        | PromqlInfoEnrich { child, .. }
-        | Sort { child, .. }
-        | Limit { child, .. } => vec![rc_mut(child)],
-        Concat { children, .. } => children.iter_mut().collect(),
-        Join { left, right, .. } | SetOp { left, right, .. } => {
-            vec![rc_mut(left), rc_mut(right)]
-        }
-        BinaryOp { lhs, rhs, .. } => vec![rc_mut(lhs), rc_mut(rhs)],
-        Column(_)
-        | Literal(_)
-        | Compare { .. }
-        | BoolAnd(_)
-        | BoolOr(_)
-        | Not(_)
-        | IsNull(_)
-        | IsNotNull(_)
-        | Cast { .. }
-        | InList { .. }
-        | FunctionCall { .. }
-        | Arithmetic { .. }
-        | Case { .. } => vec![],
-    }
-}
-
-/// Recognise an additive-ranked
-/// `Limit { Sort { [Project] Aggregate([Count | Sum]) } }` and rewrite it to
-/// the canonical heavy-hitter `Aggregate([TopK])` over the explicit inner
-/// aggregate. Returns `None` when the shape does not match.
-fn try_promote_additive_top_ranking(expr: &QueryExpr) -> Option<QueryExpr> {
-    // Limit k, no offset (an OFFSET means "not the top k").
-    let QueryExpr::Limit {
-        n: k,
-        offset: 0,
-        child,
-    } = expr
-    else {
-        return None;
-    };
-    // A single ordering key on a column.
-    let QueryExpr::Sort {
-        keys,
-        partition_by,
-        child: sort_child,
-    } = child.as_ref()
-    else {
-        return None;
-    };
-    let [SortKey {
-        expr: QueryExpr::Column(sort_col),
-        ascending,
-        ..
-    }] = keys.as_slice()
-    else {
-        return None;
-    };
-
-    // The ordered relation is an `Aggregate`, optionally behind a passthrough
-    // projection (a bare-column SELECT list). Map the sort key through the
-    // projection to the aggregate's own output column.
-    let (agg_expr, ranked_col) = match sort_child.as_ref() {
-        QueryExpr::Project { cols, child, .. } => {
-            let QueryExpr::Column(underlying) = &cols.get(*sort_col)?.expr else {
-                return None;
-            };
-            (child.as_ref(), *underlying)
-        }
-        other => (other, *sort_col),
-    };
-
-    // Exactly one aggregate, ranked by *its* output column — the measure sits at
-    // index `by.len()` (after the group keys). A `PerEntity` reduction has no
-    // `by` to rank a measure against — this shape can't be heavy-hitter
-    // promoted, so it's a non-match rather than an error.
-    let QueryExpr::Aggregate {
-        reduction,
-        measures,
-        filters,
-        child: aggregate_child,
-        ..
-    } = agg_expr
-    else {
-        return None;
-    };
-    let Reduction::Reduce(by) = reduction else {
-        return None;
-    };
-    let [ranked_agg] = measures.as_slice() else {
-        return None;
-    };
-    // A heavy-hitter sketch ranks the raw update stream; a filtered measure
-    // only counts part of it, and no binding rule applies the filter (#466).
-    if filters.iter().any(Option::is_some) {
-        return None;
-    }
-    if ranked_col != by.len() {
-        return None;
-    }
-    // The heavy-hitter decision — descending, over a measure with a realised
-    // heavy-hitter sketch — is the shared rule both front ends' promotions
-    // consult (issue #38). So an ascending additive-ranked limit
-    // (`ORDER BY COUNT(*) ASC LIMIT k` = bottom-k) stays generic, exactly as
-    // PromQL `bottomk(k, count_over_time(…))` does.
-    if !topk::Ranking::from_aggregate(ranked_agg).is_supported(!ascending) {
-        return None;
-    }
-    // A direct Sum is a stream of additive observation weights. A Sum over a
-    // derived child such as Rate/Increase is different: a heavy-hitter sketch
-    // may propose candidate membership, but PromQL still requires exact
-    // reset-aware/extrapolated values to rerank those candidates. The current
-    // post-ASAP IR has no candidate-sidecar + exact-rerank node, so keep that
-    // shape as Sort + Limit instead of treating a sketch estimate as final.
-    if matches!(ranked_agg, AggIntent::Sum { .. })
-        && matches!(aggregate_child.as_ref(), QueryExpr::Aggregate { .. })
-    {
-        return None;
-    }
-    // Count ranks unit updates; a direct Sum ranks weighted updates.
-    let accuracy = match ranked_agg {
-        AggIntent::Count { accuracy } => accuracy.clone(),
-        AggIntent::Sum { .. } => AccuracyTarget::Exact,
-        _ => unreachable!("additive ranking gate admitted a non-additive measure"),
-    };
-
-    // Outer heavy-hitter `TopK`, grouped by the ranking's partition (empty for a
-    // global `ORDER BY … LIMIT k`; the `by` labels for a partitioned `topk by`),
-    // over the unchanged inner additive aggregate.
-    Some(QueryExpr::Aggregate {
-        reduction: Reduction::by(partition_by.to_vec()),
-        measures: vec![AggIntent::TopK { k: *k, accuracy }],
-        output_names: Vec::new(),
-        filters: Vec::new(),
-        having: None,
-        child: Rc::new(agg_expr.clone()),
-    })
-}
-
-/// Recognise the SQL partitioned-top-k idiom — `WHERE rn <= k` over a
-/// `ROW_NUMBER() OVER (PARTITION BY p ORDER BY o)` — and rewrite it to the
-/// generic partitioned top-k `Limit{k} { Sort{ o, partition_by: p } }` (issue
-/// #24). The count-ranked case is then promoted to a heavy-hitter `TopK` by
-/// [`try_promote_additive_top_ranking`], so a SQL `ROW_NUMBER` top-k and the PromQL
-/// `topk by (…)` it mirrors converge on the same canonical shape.
-fn try_rewrite_rownumber_topk(expr: &QueryExpr) -> Option<QueryExpr> {
-    // Filter { pred: `Column(rn) <= k` }.
-    let QueryExpr::Filter { pred, child } = expr else {
-        return None;
-    };
-    let Predicate(pred_expr) = pred;
-    let QueryExpr::Compare { left, op, right } = pred_expr.as_ref() else {
-        return None;
-    };
-    // `rn <= k` (top-k). `rn < k` would be off-by-one; require `<=`.
-    if *op != CompareOpKind::Le {
-        return None;
-    }
-    let (QueryExpr::Column(rn_col), QueryExpr::Literal(ScalarValue::Int64(k))) =
-        (left.as_ref(), right.as_ref())
-    else {
-        return None;
-    };
-    if *k < 0 {
-        return None;
-    }
-
-    // Optionally strip a passthrough projection (the derived table's SELECT that
-    // re-exposes the aggregate columns + rn), mapping the rn column through it.
-    let (wf_expr, rn_in_wf) = match child.as_ref() {
-        QueryExpr::Project { cols, child, .. } => {
-            let QueryExpr::Column(underlying) = &cols.get(*rn_col)?.expr else {
-                return None;
-            };
-            (child.as_ref(), *underlying)
-        }
-        other => (other, *rn_col),
-    };
-
-    // The filtered column must be a `ROW_NUMBER()` window output — the single
-    // column the SQLWindowFunc appends after its input, i.e. the last one.
-    let QueryExpr::SQLWindowFunc {
-        func: WindowFuncKind::RowNumber,
-        partition_by,
-        order_by,
-        child: inner,
-        ..
-    } = wf_expr
-    else {
-        return None;
-    };
-    if order_by.is_empty() {
-        return None;
-    }
-    let inner_cols = inner.output_schema().ok()?.fields.len();
-    if rn_in_wf != inner_cols {
-        return None; // the predicate ranks some other column, not the row number
-    }
-
-    // Generic partitioned top-k. The window's ORDER BY keys are relative to its
-    // input (`inner`), so they transfer directly to a `Sort` over `inner`.
-    Some(QueryExpr::Limit {
-        n: *k as usize,
-        offset: 0,
-        child: Rc::new(QueryExpr::Sort {
-            keys: order_by.clone(),
-            partition_by: partition_by.clone(),
-            child: Rc::new(inner.as_ref().clone()),
-        }),
-    })
-}
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-    use crate::pre_asap::query_expr::{
-        GroupKeys, ProjectItem, Source, WindowFrame, WindowFrameBound, WindowFrameOffset,
-        WindowFrameUnits,
-    };
-    use crate::pre_asap::schema::{DataType, Field, Schema};
-    use crate::types::AccuracyTarget;
-
-    fn scan() -> QueryExpr {
-        QueryExpr::Scan {
-            source: Source::TimeSeries { metric: "m".into() },
-            predicates: vec![],
-            schema: Schema::with_time_index(
-                vec![
-                    Field::plain("ts", DataType::Timestamp, false),
-                    Field::plain("service", DataType::Utf8, false),
-                    Field::plain("value", DataType::Float64, false),
-                ],
-                0,
-                vec![],
-            ),
-        }
-    }
-
-    /// `Aggregate{ by: [1], [Count] }` over the scan — output cols `[service, count]`.
-    fn count_by_service() -> QueryExpr {
-        QueryExpr::Aggregate {
-            reduction: Reduction::by(vec![1]),
-            measures: vec![AggIntent::Count {
-                accuracy: AccuracyTarget::Exact,
-            }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(scan()),
-        }
-    }
-
-    fn desc(col: usize) -> Vec<SortKey> {
-        vec![SortKey {
-            expr: QueryExpr::Column(col),
-            ascending: false,
-            nulls_first: false,
-        }]
-    }
-
-    fn limit(n: usize, offset: usize, child: QueryExpr) -> QueryExpr {
-        QueryExpr::Limit {
-            n,
-            offset,
-            child: Rc::new(child),
-        }
-    }
-
-    fn sort(keys: Vec<SortKey>, child: QueryExpr) -> QueryExpr {
-        QueryExpr::Sort {
-            keys,
-            partition_by: GroupKeys::by(vec![]),
-            child: Rc::new(child),
-        }
-    }
-
-    fn is_topk_over_count(qe: &QueryExpr) -> bool {
-        matches!(qe,
-            QueryExpr::Aggregate { measures, child, .. }
-                if matches!(measures.as_slice(), [AggIntent::TopK { k: 5, .. }])
-                && matches!(child.as_ref(), QueryExpr::Aggregate { measures, .. }
-                    if matches!(measures.as_slice(), [AggIntent::Count { .. }])))
-    }
-
-    #[test]
-    fn promotes_count_ranked_limit_sort() {
-        // Limit 5 { Sort DESC by count-col (1) { Aggregate[Count] by [1] } }.
-        let q = limit(5, 0, sort(desc(1), count_by_service()));
-        assert!(is_topk_over_count(&canonicalize(q)));
-    }
-
-    // A heavy-hitter sketch ranks every row; a count that only counts some
-    // rows (#466) is not that, so the generic Sort + Limit stays.
-    #[test]
-    fn does_not_promote_a_filtered_count_ranking() {
-        let mut filtered = count_by_service();
-        let QueryExpr::Aggregate { filters, .. } = &mut filtered else {
-            unreachable!()
-        };
-        *filters = vec![Some(Predicate(Rc::new(QueryExpr::Compare {
-            left: Rc::new(QueryExpr::Column(2)),
-            op: CompareOpKind::Gt,
-            right: Rc::new(QueryExpr::Literal(ScalarValue::Float64(1.0))),
-        })))];
-        let q = limit(5, 0, sort(desc(1), filtered));
-        let canonical = canonicalize(q.clone());
-        assert!(!is_topk_over_count(&canonical));
-        assert_eq!(canonical, q);
-    }
-
-    #[test]
-    fn promotes_through_a_passthrough_projection() {
-        // …with a `SELECT service, count` projection between the Sort and the Agg.
-        let proj = QueryExpr::Project {
-            cols: vec![
-                ProjectItem {
-                    alias: None,
-                    expr: QueryExpr::Column(0),
-                },
-                ProjectItem {
-                    alias: Some("c".into()),
-                    expr: QueryExpr::Column(1),
-                },
-            ],
-            qualifier: None,
-            child: Rc::new(count_by_service()),
-        };
-        let q = limit(5, 0, sort(desc(1), proj));
-        assert!(is_topk_over_count(&canonicalize(q)));
-    }
-
-    #[test]
-    fn is_idempotent() {
-        let q = limit(5, 0, sort(desc(1), count_by_service()));
-        let once = canonicalize(q);
-        let twice = canonicalize(once.clone());
-        assert_eq!(once, twice, "canonicalize must be idempotent");
-    }
-
-    // ── Concat's discriminator_unique_key vs. canonicalize (issue #228 review) ──
-    //
-    // `resolve.rs` resolves `discriminator_unique_key`'s `ColumnId`s against
-    // the first branch's *pre-canonicalize* output schema. If canonicalize
-    // then restructures that branch (heavy-hitter promotion, the
-    // `ROW_NUMBER()` top-k rewrite), those `ColumnId`s can end up pointing at
-    // the wrong column — or out of bounds — of the new schema. The two tests
-    // below pin the fix: the key is dropped whenever the branch's schema
-    // actually changed, and survives untouched otherwise. Never guessed at.
-
-    #[test]
-    fn concat_discriminator_key_survives_canonicalize_when_first_branch_is_unaffected() {
-        // A plain `Aggregate` first branch matches neither rewrite trigger,
-        // so its schema is identical before and after canonicalize.
-        let q = QueryExpr::concat_with_discriminator(
-            vec![count_by_service(), count_by_service()],
-            /* discriminator */ 0,
-            /* inner_key */ vec![1],
-        );
-        let QueryExpr::Concat {
-            discriminator_unique_key,
-            ..
-        } = canonicalize(q)
-        else {
-            panic!("expected Concat");
-        };
-        assert!(
-            discriminator_unique_key.is_some(),
-            "an untouched first branch's discriminator key must survive canonicalize"
-        );
-    }
-
-    #[test]
-    fn concat_discriminator_key_is_dropped_when_first_branch_gets_rewritten() {
-        // The first branch is exactly the heavy-hitter promotion trigger —
-        // `Limit{Sort{Aggregate([Count])}}`, with an empty (global)
-        // `partition_by` — so canonicalize rewrites it in place to
-        // `Aggregate{TopK}`, whose own output is a single column, not the
-        // original two (`[service, count]`). A discriminator key resolved
-        // against the original 2-column shape (`discriminator` = `service`
-        // at index 0, `inner_key` = `count` at index 1) must not silently
-        // survive pointing at the new 1-column schema.
-        let promotable_branch = limit(5, 0, sort(desc(1), count_by_service()));
-        let q = QueryExpr::concat_with_discriminator(
-            vec![promotable_branch, count_by_service()],
-            /* discriminator */ 0,
-            /* inner_key */ vec![1],
-        );
-        let QueryExpr::Concat {
-            children,
-            discriminator_unique_key,
-        } = canonicalize(q)
-        else {
-            panic!("expected Concat");
-        };
-        assert!(
-            is_topk_over_count(&children[0]),
-            "the first branch is still promoted normally"
-        );
-        assert!(
-            discriminator_unique_key.is_none(),
-            "a stale discriminator key must be dropped, never silently kept wrong"
-        );
-    }
-
-    #[test]
-    fn does_not_promote_ascending_sort() {
-        // Ascending = bottom-k: the Top-K operator's ranking rule
-        // rejects it (needs descending), so it stays a generic Sort+Limit — the
-        // same call PromQL `bottomk` makes (issue #38).
-        let asc = vec![SortKey {
-            expr: QueryExpr::Column(1),
-            ascending: true,
-            nulls_first: false,
-        }];
-        let q = limit(5, 0, sort(asc, count_by_service()));
-        assert!(!is_topk_over_count(&canonicalize(q)));
-    }
-
-    #[test]
-    fn does_not_promote_with_offset() {
-        let q = limit(5, 2, sort(desc(1), count_by_service()));
-        assert!(!is_topk_over_count(&canonicalize(q)));
-    }
-
-    #[test]
-    fn does_not_promote_ranking_by_a_group_key() {
-        // DESC by col 0 (the `service` group key), not the count → not a
-        // frequency heavy-hitter.
-        let q = limit(5, 0, sort(desc(0), count_by_service()));
-        assert!(!is_topk_over_count(&canonicalize(q)));
-    }
-
-    #[test]
-    fn promotes_sum_ranked_limit_sort_as_weighted_heavy_hitter() {
-        let sum = QueryExpr::Aggregate {
-            reduction: Reduction::by(vec![1]),
-            measures: vec![AggIntent::Sum { col: None }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(scan()),
-        };
-        let q = limit(5, 0, sort(desc(1), sum));
-        let out = canonicalize(q);
-        let QueryExpr::Aggregate {
-            measures, child, ..
-        } = out
-        else {
-            panic!("expected weighted TopK aggregate");
-        };
-        assert!(matches!(
-            measures.as_slice(),
-            [AggIntent::TopK { k: 5, .. }]
-        ));
-        assert!(
-            matches!(child.as_ref(), QueryExpr::Aggregate { measures, .. }
-            if matches!(measures.as_slice(), [AggIntent::Sum { .. }]))
-        );
-    }
-
-    #[test]
-    fn keeps_sum_over_counter_reduction_as_exact_value_ranking() {
-        for counter in [AggIntent::Rate, AggIntent::Increase] {
-            let derived = QueryExpr::Aggregate {
-                reduction: Reduction::PerEntity,
-                measures: vec![counter],
-                output_names: vec![],
-                filters: vec![],
-                having: None,
-                child: Rc::new(scan()),
-            };
-            let sum = QueryExpr::Aggregate {
-                reduction: Reduction::by(vec![1]),
-                measures: vec![AggIntent::Sum { col: None }],
-                output_names: vec![],
-                filters: vec![],
-                having: None,
-                child: Rc::new(derived),
-            };
-            let out = canonicalize(limit(5, 0, sort(desc(1), sum)));
-            assert!(matches!(out, QueryExpr::Limit { child, .. }
-                if matches!(child.as_ref(), QueryExpr::Sort { child, .. }
-                    if matches!(child.as_ref(), QueryExpr::Aggregate { measures, child, .. }
-                        if matches!(measures.as_slice(), [AggIntent::Sum { .. }])
-                            && matches!(child.as_ref(), QueryExpr::Aggregate { .. })))));
-        }
-    }
-
-    // ── ROW_NUMBER() partitioned top-k (issue #24) ──────────────────────────
-
-    /// A scan with `[ts, service, region, value]`.
-    fn scan4() -> QueryExpr {
-        QueryExpr::Scan {
-            source: Source::TimeSeries { metric: "m".into() },
-            predicates: vec![],
-            schema: Schema::with_time_index(
-                vec![
-                    Field::plain("ts", DataType::Timestamp, false),
-                    Field::plain("service", DataType::Utf8, false),
-                    Field::plain("region", DataType::Utf8, false),
-                    Field::plain("value", DataType::Float64, false),
-                ],
-                0,
-                vec![],
-            ),
-        }
-    }
-
-    /// `Aggregate{ by: [1,2] (service, region), [agg] }` — output `[service,
-    /// region, <agg>]` (3 cols), so a ROW_NUMBER over it appends `rn` at index 3.
-    fn grouped(agg: AggIntent) -> QueryExpr {
-        QueryExpr::Aggregate {
-            reduction: Reduction::by(vec![1, 2]),
-            measures: vec![agg],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(scan4()),
-        }
-    }
-
-    /// `ROW_NUMBER` ignores its frame clause, so the top-k rewrite doesn't care
-    /// what's in it; any concrete frame works as fixture data.
-    fn rownumber_frame() -> WindowFrame {
-        WindowFrame {
-            units: WindowFrameUnits::Rows,
-            start_bound: WindowFrameBound::Preceding(WindowFrameOffset::Scalar(ScalarValue::Null)),
-            end_bound: WindowFrameBound::Following(WindowFrameOffset::Scalar(ScalarValue::Null)),
-        }
-    }
-
-    /// `Filter{ rn(3) <= 5 } { SQLWindowFunc{ RowNumber, PARTITION BY region(2),
-    /// ORDER BY col(2) DESC } { agg } }`.
-    fn rownumber_topk(agg: QueryExpr) -> QueryExpr {
-        let wf = QueryExpr::SQLWindowFunc {
-            func: WindowFuncKind::RowNumber,
-            args: vec![],
-            partition_by: GroupKeys::by(vec![2]), // region
-            order_by: vec![SortKey {
-                expr: QueryExpr::Column(2), // the aggregate output column
-                ascending: false,
-                nulls_first: true,
-            }],
-            frame: Some(rownumber_frame()),
-            output_name: "rn".into(),
-            child: Rc::new(agg),
-        };
-        QueryExpr::Filter {
-            pred: Predicate(Rc::new(QueryExpr::Compare {
-                left: Rc::new(QueryExpr::Column(3)), // rn = the appended window column
-                op: CompareOpKind::Le,
-                right: Rc::new(QueryExpr::Literal(ScalarValue::Int64(5))),
-            })),
-            child: Rc::new(wf),
-        }
-    }
-
-    #[test]
-    fn rownumber_count_topk_becomes_a_partitioned_heavy_hitter() {
-        // Count-ranked ROW_NUMBER top-k → outer TopK grouped by the partition
-        // (region, col 2) over the explicit inner Count.
-        let q = rownumber_topk(grouped(AggIntent::Count {
-            accuracy: AccuracyTarget::Exact,
-        }));
-        let out = canonicalize(q);
-        let QueryExpr::Aggregate {
-            reduction,
-            measures,
-            child,
-            ..
-        } = &out
-        else {
-            panic!("expected outer Aggregate([TopK]), got {out:?}");
-        };
-        let Reduction::Reduce(by) = reduction else {
-            panic!("expected a Reduce grouping, got {reduction:?}");
-        };
-        assert!(matches!(
-            measures.as_slice(),
-            [AggIntent::TopK { k: 5, .. }]
-        ));
-        assert_eq!(**by, vec![2], "outer TopK partitioned by region");
-        assert!(
-            matches!(child.as_ref(), QueryExpr::Aggregate { measures, .. }
-            if matches!(measures.as_slice(), [AggIntent::Count { .. }]))
-        );
-    }
-
-    #[test]
-    fn rownumber_avg_topk_becomes_a_partitioned_sort_limit() {
-        // Avg-ranked (not a frequency heavy-hitter) → generic partitioned
-        // top-k: Limit{5}{ Sort{ partition_by: [region] } }.
-        let q = rownumber_topk(grouped(AggIntent::Avg { col: None }));
-        let out = canonicalize(q);
-        let QueryExpr::Limit { n, child, .. } = &out else {
-            panic!("expected a Limit, got {out:?}");
-        };
-        assert_eq!(*n, 5);
-        let QueryExpr::Sort {
-            partition_by,
-            child,
-            ..
-        } = child.as_ref()
-        else {
-            panic!("expected a Sort under the Limit");
-        };
-        assert_eq!(**partition_by, vec![2], "partitioned by region");
-        assert!(
-            matches!(child.as_ref(), QueryExpr::Aggregate { measures, .. }
-            if matches!(measures.as_slice(), [AggIntent::Avg { .. }]))
-        );
-    }
-
-    #[test]
-    fn filter_on_a_non_rownumber_column_is_left_alone() {
-        // `WHERE service_len <= 5` (col 0, not the rn window column) must not be
-        // mistaken for a top-k.
-        let wf = QueryExpr::SQLWindowFunc {
-            func: WindowFuncKind::RowNumber,
-            args: vec![],
-            partition_by: GroupKeys::by(vec![2]),
-            order_by: vec![SortKey {
-                expr: QueryExpr::Column(2),
-                ascending: false,
-                nulls_first: true,
-            }],
-            frame: Some(rownumber_frame()),
-            output_name: "rn".into(),
-            child: Rc::new(grouped(AggIntent::Count {
-                accuracy: AccuracyTarget::Exact,
-            })),
-        };
-        let q = QueryExpr::Filter {
-            pred: Predicate(Rc::new(QueryExpr::Compare {
-                left: Rc::new(QueryExpr::Column(0)), // NOT the rn column (index 3)
-                op: CompareOpKind::Le,
-                right: Rc::new(QueryExpr::Literal(ScalarValue::Int64(5))),
-            })),
-            child: Rc::new(wf),
-        };
-        assert!(
-            matches!(canonicalize(q), QueryExpr::Filter { .. }),
-            "left as a Filter"
-        );
-    }
-}
diff --git a/crates/types/src/pre_asap/column_resolution.rs b/crates/types/src/pre_asap/column_resolution.rs
index cfafbe9e0..e2d8120d6 100644
--- a/crates/types/src/pre_asap/column_resolution.rs
+++ b/crates/types/src/pre_asap/column_resolution.rs
@@ -1,22 +1,13 @@
 //! Schema-driven column resolution.
 //!
-//! Front ends (issue #179) emit `ColumnRef` (name-based, optionally
-//! table-qualified); the canonical DAG uses positional [`ColumnId`] resolved
-//! against a per-node [`Schema`]. These helpers bridge the two — the
-//! [`SchemaResolver`](super::schema_resolver) builds the schema, and [`resolve_column_refs`]
-//! turns name-based refs (group keys, dedup columns) into positional ids,
-//! qualifier-aware.
-
-use std::rc::Rc;
+//! Front ends emit `ColumnRef` (name-based, optionally table-qualified); the
+//! IR uses positional [`ColumnId`] resolved against a per-node [`Schema`].
+//! These helpers turn name-based refs into positional ids, qualifier-aware.
+//! Front-end name resolution (`asap_frontend_common::resolve`) calls them.
 
 use thiserror::Error;
 
-use super::agg_intent::AggIntent;
 use super::expr_ir::ColumnRef;
-use super::query_expr::{
-    aggregate_output_schema, GroupKeys, QueryExpr, QueryExprError, Reduction, ResolvedQueryExpr,
-    UnresolvedQueryExpr,
-};
 use super::schema::{ColumnId, DataType, FieldDataType, Schema};
 
 /// Errors returned by the resolution helpers.
@@ -115,102 +106,6 @@ pub fn resolve_group_keys_promql(
         .collect()
 }
 
-/// Resolve a name-based scalar [`UnresolvedQueryExpr`] (one of `QueryExpr`'s scalar
-/// variants, issue #205) into a positional [`ResolvedQueryExpr`] by resolving every
-/// column reference against `schema`. Structural otherwise. `expr` must be
-/// one of the scalar variants — an operator variant here is a construction
-/// bug, not a shape this needs to handle silently.
-pub fn resolve_expr(
-    expr: &UnresolvedQueryExpr,
-    schema: &Schema,
-) -> Result<ResolvedQueryExpr, ResolveError> {
-    let rc = |e: &UnresolvedQueryExpr| -> Result<Rc<ResolvedQueryExpr>, ResolveError> {
-        Ok(Rc::new(resolve_expr(e, schema)?))
-    };
-    let each = |es: &[UnresolvedQueryExpr]| -> Result<Vec<ResolvedQueryExpr>, ResolveError> {
-        es.iter().map(|e| resolve_expr(e, schema)).collect()
-    };
-    Ok(match expr {
-        QueryExpr::Column(c) => QueryExpr::Column(resolve_column_ref(c, schema)?),
-        QueryExpr::Literal(s) => QueryExpr::Literal(s.clone()),
-        QueryExpr::EvalTimestamp => QueryExpr::EvalTimestamp,
-        QueryExpr::CurrentTimestamp => QueryExpr::CurrentTimestamp,
-        QueryExpr::Compare { left, op, right } => QueryExpr::Compare {
-            left: rc(left)?,
-            op: op.clone(),
-            right: rc(right)?,
-        },
-        QueryExpr::BoolAnd(v) => QueryExpr::BoolAnd(each(v)?),
-        QueryExpr::BoolOr(v) => QueryExpr::BoolOr(each(v)?),
-        QueryExpr::Not(e) => QueryExpr::Not(rc(e)?),
-        QueryExpr::IsNull(e) => QueryExpr::IsNull(rc(e)?),
-        QueryExpr::IsNotNull(e) => QueryExpr::IsNotNull(rc(e)?),
-        QueryExpr::Cast { expr, to, try_cast } => QueryExpr::Cast {
-            expr: rc(expr)?,
-            to: to.clone(),
-            try_cast: *try_cast,
-        },
-        QueryExpr::InList {
-            expr,
-            list,
-            negated,
-        } => QueryExpr::InList {
-            expr: rc(expr)?,
-            list: each(list)?,
-            negated: *negated,
-        },
-        QueryExpr::FunctionCall { name, args } => QueryExpr::FunctionCall {
-            name: name.clone(),
-            args: each(args)?,
-        },
-        QueryExpr::Arithmetic { op, left, right } => QueryExpr::Arithmetic {
-            op: op.clone(),
-            left: rc(left)?,
-            right: rc(right)?,
-        },
-        QueryExpr::Case {
-            operand,
-            branches,
-            else_expr,
-        } => QueryExpr::Case {
-            operand: operand.as_deref().map(rc).transpose()?,
-            branches: branches
-                .iter()
-                .map(|(w, t)| Ok((resolve_expr(w, schema)?, resolve_expr(t, schema)?)))
-                .collect::<Result<Vec<_>, ResolveError>>()?,
-            else_expr: else_expr.as_deref().map(rc).transpose()?,
-        },
-        other => unreachable!("resolve_expr called on a non-scalar QueryExpr variant: {other:?}"),
-    })
-}
-
-/// Output schema produced by an `Aggregate { by, measures }` over `input`.
-/// Mirrors `QueryExpr::output_schema_in`'s `Aggregate` arm; out-of-range `by`
-/// ids are silently dropped (callers needing the strict check resolve `by`
-/// via [`resolve_column_refs`], which surfaces `NotFound`).
-pub fn output_schema_for_aggregate(
-    input: &Schema,
-    by: &GroupKeys,
-    measures: &[AggIntent],
-    output_names: &[String],
-) -> Result<Schema, QueryExprError> {
-    // Delegate to the single canonical derivation so HAVING resolution can never
-    // drift from `QueryExpr::output_schema_in` (issue #41). HAVING is SQL-only
-    // and cross-series (SQL has no `without`), but detect the child-independent
-    // per-entity case anyway (a lone `rate`/`increase`/`*_over_time` intent) so
-    // the two agree on every shared input — the range-window child marker the
-    // canonical arm also keys off is not visible here, and never co-occurs with
-    // HAVING.
-    let per_entity =
-        by.is_empty() && !by.is_without() && measures.len() == 1 && measures[0].is_per_series();
-    let reduction = if per_entity {
-        Reduction::PerEntity
-    } else {
-        Reduction::Reduce(by.clone())
-    };
-    aggregate_output_schema(input, &reduction, measures, output_names)
-}
-
 #[cfg(test)]
 mod tests {
     use super::*;
@@ -326,77 +221,4 @@ mod tests {
             Err(ResolveError::NotFound { .. })
         ));
     }
-
-    #[test]
-    fn aggregate_strips_time_and_keeps_unique_keys() {
-        let mut input = ts_value_schema();
-        input
-            .fields
-            .push(Field::plain("host", DataType::Utf8, false));
-        let out = output_schema_for_aggregate(
-            &input,
-            &GroupKeys::by(vec![2]),
-            &[AggIntent::Sum { col: None }],
-            &[],
-        )
-        .expect("valid group-by column");
-        assert_eq!(out.fields.len(), 2); // host, sum
-        assert_eq!(out.fields[0].name, "host");
-        assert_eq!(out.fields[1].name, "sum");
-        assert!(out.time_index.is_none());
-        assert_eq!(out.unique_keys, vec![vec![0]]);
-    }
-
-    #[test]
-    fn having_schema_agrees_with_canonical_for_a_per_series_reduction() {
-        // Issue #41: `output_schema_for_aggregate` (HAVING resolution) and the
-        // canonical `QueryExpr::output_schema_in` must produce identical schemas
-        // for the same aggregate. Before the dedup this diverged on a per-series
-        // reduction — the HAVING mirror lacked the per-series branch and would
-        // collapse `[ts, value]` to a single `rate` column.
-        use crate::pre_asap::query_expr::Source;
-        use std::time::Duration;
-
-        let leaf_schema = Schema::with_time_index(
-            vec![
-                Field::plain("ts", DataType::Timestamp, false),
-                Field::plain("value", DataType::Float64, false),
-            ],
-            0,
-            vec![],
-        );
-        let scan = QueryExpr::Scan {
-            source: Source::TimeSeries { metric: "m".into() },
-            predicates: vec![],
-            schema: leaf_schema.clone(),
-        };
-        // Aggregate{ reduction: PerEntity, [Rate], child: TimeRange{ Scan } } —
-        // a per-series reduction (label-preserving).
-        let agg = QueryExpr::Aggregate {
-            reduction: Reduction::PerEntity,
-            measures: vec![AggIntent::Rate],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(QueryExpr::TimeRange {
-                range: Duration::from_secs(300),
-                child: Rc::new(scan),
-            }),
-        };
-        let canonical = agg.output_schema().expect("canonical schema");
-
-        // The HAVING-resolution derivation gets only the input schema (the
-        // TimeRange passes the leaf schema through).
-        let having_side =
-            output_schema_for_aggregate(&leaf_schema, &GroupKeys::none(), &[AggIntent::Rate], &[])
-                .unwrap();
-
-        assert_eq!(
-            canonical, having_side,
-            "the two aggregate-schema derivations must agree (issue #41)"
-        );
-        // Sanity: it really is the label-preserving per-series shape, not `[rate]`.
-        assert!(having_side.fields.iter().any(|c| c.name == "value"));
-        assert!(having_side.time_index.is_some());
-    }
 }
diff --git a/crates/types/src/pre_asap/cse.rs b/crates/types/src/pre_asap/cse.rs
deleted file mode 100644
index 0a00475e6..000000000
--- a/crates/types/src/pre_asap/cse.rs
+++ /dev/null
@@ -1,1111 +0,0 @@
-//! Pre-ASAP structural common-subexpression elimination: bottom-up
-//! hash-consing over an already-`resolve_root`'d [`QueryExpr`] DAG (issue
-//! #212, #222, #223).
-//!
-//! CSE only runs on an already-bound, already-canonicalized DAG —
-//! structural matching is meaningless before canonicalization has converged
-//! semantically-equivalent queries onto one shape (`docs/develop_docs/pre-asap-ir.md`
-//! design principle 3; `median(latency)` and `approx_percentile_cont(latency,
-//! 0.5)` already lower to an identical `AggIntent::Quantile` today, per
-//! `sql_lowering.rs`'s `median_is_the_same_intent_as_an_explicit_half_percentile`
-//! test). [`share_common_sub_dags`] is the single entry point, run once per
-//! workload batch (or once per query — see "Single-query CSE" below) *after*
-//! `resolve_root`, *before* the pre-ASAP → post-ASAP replacement/search pass
-//! (`asap_aware_mapping::replacement`).
-//!
-//! ## Algorithm: classic hash-consing / value-numbering
-//!
-//! Bottom-up: every child is interned before its parent, so a parent's
-//! candidacy for sharing naturally incorporates whether its own children were
-//! themselves shared — two parents whose children were independently
-//! deduplicated down to the same `Rc`s are structurally identical iff their
-//! own fields also match, without re-walking the sub-DAGs.
-//!
-//! Only the **relational skeleton** participates — the same set of "operator"
-//! children [`canonicalize`](super::canonicalize)'s `children_mut` walks
-//! (`Filter`/`Project`/`Aggregate`/`Concat`/`Join`/`BinaryOp`/…). A scalar
-//! subexpression reachable only through a wrapper position (`Predicate`,
-//! `ProjectItem.expr`, `Aggregate.having`, `SQLWindowFunc.args`, …) stays
-//! embedded as opaque data on its owning operator node, compared by
-//! `QueryExpr`'s derived `PartialEq` along with the rest of that node's
-//! fields, rather than separately hash-consed — the same scope
-//! `canonicalize.rs` settled on ("none of the rewrite rules touch a scalar
-//! sub-DAG, so there's nothing to gain by recursing into one"). Widening this
-//! to scalar positions is future work, not attempted here.
-//!
-//! ## Correctness: hash is a filter, `PartialEq` is the decision
-//!
-//! This is the one non-negotiable rule. A **false positive** here — two
-//! sub-DAGs wrongly judged shareable — is a wrong query answer, not a missed
-//! optimization: two different queries would read each other's data.
-//! [`structural_hash`] (`DefaultHasher`/SipHash over a canonical
-//! serialization, no collision-freedom guarantee) may only narrow the
-//! candidate set within one bucket; [`InternTable::intern`]'s `PartialEq`
-//! check on that bucket is what actually decides sharing, every time, no
-//! exceptions for "the hash probably didn't collide."
-//!
-//! This also means the pass is safe by construction against the case #212
-//! flagged as a real historical bug (issue #115): `AggIntent::Quantile`
-//! carries its input column and its `AccuracyTarget`, both `PartialEq`
-//! fields, so `Quantile(x, 0.99, ε=0.01)` and `Quantile(x, 0.99, ε=0.001)` —
-//! or `Quantile(x, ..)` vs `Quantile(y, ..)` — are never merged. This is
-//! intentionally conservative: it only recognizes *exact* structural
-//! matches, not "a stricter-accuracy summary could also answer a looser
-//! request." That subsumption question already has a documented,
-//! deliberately-unfilled home (`asap_aware_mapping::Matcher`) —
-//! CSE here does not attempt it.
-//!
-//! ## Legality: gated by `Schema::unique_keys`
-//!
-//! Structural equality alone is necessary but not sufficient. Per
-//! [`Schema::unique_keys`](super::schema::Schema::unique_keys)'s own doc: "a
-//! producer's output can only be safely shared across consumers when its row
-//! identity is provably stable across reads." A candidate node with no
-//! provable unique key (`Schema::has_unique_key()` false, or `output_schema`
-//! not even defined for that node, e.g. a `Concat`/`SetOp` branch whose union
-//! drops `unique_keys`, or an ungrouped/global `Aggregate`, whose empty `by`
-//! also reports no unique key today) is **never** hoisted, even when it is
-//! structurally identical to something already interned — it is always
-//! inserted fresh, matching the rule the (now-deleted) prior CSE attempt
-//! already encoded and the doc comment on `Aggregate`'s `child` field
-//! ("`unique_keys` feeds CSE's producer-sharing legality check").
-//!
-//! ## Single-query CSE falls out for free
-//!
-//! A repeated sub-expression within *one* query (e.g. the same grouped
-//! `Aggregate` referenced twice on two `BinaryOp` branches) is deduplicated
-//! by the exact same bottom-up interning — a workload of size one still
-//! interns bottom-up within that one DAG. No separate mechanism is needed;
-//! see the `single_query_shares_its_own_repeated_sub_dag` test below.
-//!
-//! ## Landing plan (issue #223)
-//!
-//! This module is stage 1 of a 4-stage plan. Stage 2
-//! (`asap_aware_mapping::replacement::search_workload_with`, which runs
-//! [`share_common_sub_dags`] itself before searching) is a real caller,
-//! wired at the same time so this never becomes unwired dead code again
-//! (the original `asap-plan::cse::dedupe_subtrees` was deleted in #192 for
-//! exactly that). Stage 3 — [`dag_export`](crate::dag_export) computing its
-//! per-node `hash` by calling this module's [`structural_hash`] directly,
-//! instead of a parallel reimplementation — is also done, so
-//! `tools/dag-viewer`'s "shared sub-DAG" highlighting now flags exactly the
-//! candidate pairs this module's own `InternTable` would bucket together
-//! (still only a hash match, not a guarantee of
-//! `share_common_sub_dags`-actual sharing — see `dag_export`'s module doc).
-//! Stage 4 (issue #237) is implemented in
-//! `asap_aware_mapping::cost_model::CostModel::cse_share_decision`, called
-//! from `asap_aware_mapping::replacement::CandidateLogicalASAPDAGs::cost_sorted` (via that
-//! module's own `cse_preference`) — a real, Volcano/Cascades-style cost
-//! comparison over what this module detects, not a fixed rule. See
-//! `docs/design_docs/cost-model.md`. This module's own
-//! unconditional "share whenever legal" behavior is unchanged: detection
-//! stays cost-agnostic by construction (this crate cannot depend on
-//! `asap-aware-mapping`'s `CostModel`), and the cost-aware decision is
-//! applied downstream, after detection, over what this module finds.
-
-use std::collections::HashMap;
-use std::hash::{Hash, Hasher};
-use std::rc::Rc;
-
-use super::query_expr::QueryExpr;
-
-/// Bottom-up hash-consing table: structurally-equal, sharing-legal
-/// [`QueryExpr`] nodes collapse onto one `Rc`.
-///
-/// `buckets` is keyed by [`structural_hash`] — a coarse candidate filter
-/// only (see the module-level "Correctness" section). Every entry within one
-/// bucket is a full node kept around for the `PartialEq` comparison that
-/// actually decides a match; a hash collision between structurally different
-/// nodes just means a (harmless) linear scan of a few extra candidates.
-struct InternTable {
-    buckets: HashMap<u64, Vec<Rc<QueryExpr>>>,
-    /// Memoizes [`structural_hash`] per already-hashed `Rc` pointer, shared
-    /// across every [`intern`](Self::intern) call for the table's whole
-    /// lifetime — see [`structural_hash`]'s own doc on why this matters:
-    /// without it, hashing an `N`-node bottom-up pass costs `O(N)` work
-    /// *per node* (every already-interned descendant gets re-walked), not
-    /// `O(1)` amortized.
-    hash_cache: HashCache,
-}
-
-impl InternTable {
-    fn new() -> Self {
-        Self {
-            buckets: HashMap::new(),
-            hash_cache: HashMap::new(),
-        }
-    }
-
-    /// Intern one already-children-rebuilt node: look it up by
-    /// [`structural_hash`], confirm with `PartialEq`, and — only when
-    /// sharing is legal (see "Legality" above) — return the existing `Rc`
-    /// instead of allocating a new one.
-    fn intern(&mut self, node: QueryExpr) -> Rc<QueryExpr> {
-        let hash = structural_hash(&node, &mut self.hash_cache);
-        // A node with no provable unique key is never *returned* as a match
-        // for something else — it may still go on to occupy a fresh slot in
-        // the bucket (harmless; it just never gets found by a later
-        // `PartialEq` scan that also requires `reusable`).
-        let reusable = node
-            .output_schema()
-            .is_ok_and(|schema| schema.has_unique_key());
-        let bucket = self.buckets.entry(hash).or_default();
-        if reusable {
-            if let Some(existing) = bucket.iter().find(|candidate| candidate.as_ref() == &node) {
-                return Rc::clone(existing);
-            }
-        }
-        let rc = Rc::new(node);
-        bucket.push(Rc::clone(&rc));
-        rc
-    }
-}
-
-/// [`structural_hash`]'s memoization cache: maps an already-hashed node's
-/// `Rc` pointer to its computed hash. Not tied to any one `QueryExpr` — a
-/// fresh, empty cache is correct to start with anywhere; what matters is
-/// letting it *persist* across every node in one bottom-up pass (as
-/// [`InternTable`] does via its own `hash_cache` field), rather than
-/// starting a new one per call.
-///
-/// `pub` (not `pub(crate)`) so `asap_aware_mapping`'s workload-search MEMO
-/// engine (`replacement::is_duplicate_rewrite`) can reuse this exact
-/// candidate-narrowing filter for its own dedup, instead of maintaining a
-/// parallel reimplementation — the same "one real hash, reused everywhere
-/// it's needed" rationale [`structural_hash`]'s own doc gives for
-/// [`dag_export`](crate::dag_export)'s `pub(crate)` reuse.
-pub type HashCache = HashMap<*const QueryExpr, u64>;
-
-/// Coarse structural hash used only to bucket [`InternTable::intern`]'s
-/// candidate search — never the actual sharing decision (`PartialEq` is).
-///
-/// `QueryExpr` carries `f64`s (`Literal(ScalarValue::Float64)`, `AggIntent::Quantile.q`, …), so it
-/// cannot derive `std::hash::Hash`. Serializing to a canonical JSON string
-/// and hashing that sidesteps the `f64` problem — but only for `node`'s own
-/// tag and non-child fields, *not* its children's full values: each
-/// `Rc`-backed child's contribution is its own [`structural_hash`], looked
-/// up in `cache` if already computed there (memoized by `Rc` pointer
-/// identity) rather than recursed into again.
-///
-/// This is the DAG-aware fix a naive "just serialize the whole sub-DAG"
-/// hash would get wrong: after [`share_common_sub_dags`] (or even before
-/// it — a front end can emit internal `Rc` sharing directly, e.g. a
-/// repeated subexpression within one query), `node` generally has internal
-/// sharing. A full-sub-DAG serialization re-serializes — re-walks —
-/// any descendant `node` already shares internally once per parent that
-/// references it; called once per node in a bottom-up pass (as
-/// [`InternTable::intern`] and [`dag_export`](crate::dag_export) both do),
-/// that costs `O(sub-DAG size)` *per node* instead of `O(1)` amortized —
-/// quadratic-or-worse for a deep chain, compounding further with any real
-/// internal sharing. Memoizing each child's hash by pointer identity in
-/// `cache` (persisted across the whole pass by the caller, not reset per
-/// node) makes each node's own contribution `O(1)` beyond its children's
-/// already-known hashes, giving `O(N)` total for `N` nodes — matching
-/// [`dag_node_count`]'s own shared-node counting fix (issue #212/#223/#237's stage
-/// 4) in spirit, applied to hashing instead of counting.
-///
-/// `pub` (not private) so [`dag_export`](crate::dag_export) can call
-/// this exact function for its exported nodes' `hash` field instead of
-/// maintaining its own parallel reimplementation — issue #223 stage 3. That
-/// makes `tools/dag-viewer`'s "shared sub-DAG" highlighting reflect this
-/// module's real hashing, not a lookalike computed a different way; see the
-/// module doc's "Landing plan" section. A NaN/infinite `f64` makes JSON
-/// serialization fail; falling back to a fixed hash just puts every such
-/// node in one (larger, still `PartialEq`-disambiguated) bucket. Made `pub`
-/// (rather than staying `pub(crate)`) for one more reuse across the crate
-/// boundary: `asap_aware_mapping`'s workload-search MEMO engine
-/// (`replacement::is_duplicate_rewrite`) needs the identical
-/// candidate-narrowing filter this module's own [`InternTable::intern`]
-/// already uses, so it doesn't have to reinvent (and risk drifting from) it.
-///
-/// Exhaustive over every `QueryExpr` variant, matching [`rebuild_children`]
-/// in which fields count as an operator child (must stay in sync — a new
-/// variant fails to compile in both places until both are extended).
-pub fn structural_hash(node: &QueryExpr, cache: &mut HashCache) -> u64 {
-    use QueryExpr::*;
-
-    fn child_hash(child: &Rc<QueryExpr>, cache: &mut HashCache) -> u64 {
-        let ptr = Rc::as_ptr(child);
-        if let Some(&h) = cache.get(&ptr) {
-            return h;
-        }
-        let h = structural_hash(child, cache);
-        cache.insert(ptr, h);
-        h
-    }
-
-    /// Hash `own_fields` (this node's own tag and non-child scalar
-    /// fields — anything JSON-serializable and small, i.e. never a
-    /// `QueryExpr` sub-DAG) via the same canonical-JSON-string trick the
-    /// whole-sub-DAG version used, just applied to `O(1)` fields instead
-    /// of `O(sub-DAG size)`.
-    fn hash_own_fields(hasher: &mut impl Hasher, own_fields: &impl serde::Serialize) {
-        serde_json::to_string(own_fields)
-            .unwrap_or_default()
-            .hash(hasher);
-    }
-
-    let mut hasher = std::collections::hash_map::DefaultHasher::new();
-    match node {
-        Scan {
-            source,
-            predicates,
-            schema,
-        } => hash_own_fields(&mut hasher, &("Scan", source, predicates, schema)),
-        PromqlVectorFromScalar(c) => {
-            "PromqlVectorFromScalar".hash(&mut hasher);
-            child_hash(c, cache).hash(&mut hasher);
-        }
-        PromqlScalarFromVector(c) => {
-            "PromqlScalarFromVector".hash(&mut hasher);
-            child_hash(c, cache).hash(&mut hasher);
-        }
-        PromqlRelabel { dst, value, child } => {
-            hash_own_fields(&mut hasher, &("PromqlRelabel", dst, value));
-            child_hash(child, cache).hash(&mut hasher);
-        }
-        PromqlInfoEnrich { selector, child } => {
-            hash_own_fields(&mut hasher, &("PromqlInfoEnrich", selector));
-            child_hash(child, cache).hash(&mut hasher);
-        }
-        PromqlSeriesSample { by, kind, child } => {
-            hash_own_fields(&mut hasher, &("PromqlSeriesSample", by, kind));
-            child_hash(child, cache).hash(&mut hasher);
-        }
-        Filter { pred, child } => {
-            hash_own_fields(&mut hasher, &("Filter", pred));
-            child_hash(child, cache).hash(&mut hasher);
-        }
-        Project {
-            cols,
-            qualifier,
-            child,
-        } => {
-            hash_own_fields(&mut hasher, &("Project", cols, qualifier));
-            child_hash(child, cache).hash(&mut hasher);
-        }
-        Aggregate {
-            reduction,
-            measures,
-            output_names,
-            filters,
-            having,
-            child,
-        } => {
-            hash_own_fields(
-                &mut hasher,
-                &(
-                    "Aggregate",
-                    reduction,
-                    measures,
-                    output_names,
-                    filters,
-                    having,
-                ),
-            );
-            child_hash(child, cache).hash(&mut hasher);
-        }
-        Dedup { cols, child } => {
-            hash_own_fields(&mut hasher, &("Dedup", cols));
-            child_hash(child, cache).hash(&mut hasher);
-        }
-        Concat {
-            children,
-            discriminator_unique_key,
-        } => {
-            hash_own_fields(&mut hasher, &("Concat", discriminator_unique_key));
-            for c in children {
-                // Stored by value, not `Rc` — see `rebuild_children`'s
-                // `intern_owned` use for this variant — so there's no
-                // pointer to memoize on here; recurse directly. Any
-                // `Rc`-typed descendant beneath `c` still gets memoized
-                // once this call reaches it.
-                structural_hash(c, cache).hash(&mut hasher);
-            }
-        }
-        Join {
-            kind,
-            pred,
-            left,
-            right,
-        } => {
-            hash_own_fields(&mut hasher, &("Join", kind, pred));
-            child_hash(left, cache).hash(&mut hasher);
-            child_hash(right, cache).hash(&mut hasher);
-        }
-        SetOp {
-            kind,
-            all,
-            left,
-            right,
-        } => {
-            hash_own_fields(&mut hasher, &("SetOp", kind, all));
-            child_hash(left, cache).hash(&mut hasher);
-            child_hash(right, cache).hash(&mut hasher);
-        }
-        Sort {
-            keys,
-            partition_by,
-            child,
-        } => {
-            hash_own_fields(&mut hasher, &("Sort", keys, partition_by));
-            child_hash(child, cache).hash(&mut hasher);
-        }
-        Limit { n, offset, child } => {
-            hash_own_fields(&mut hasher, &("Limit", n, offset));
-            child_hash(child, cache).hash(&mut hasher);
-        }
-        PromqlSubquery {
-            range,
-            resolution,
-            child,
-        } => {
-            hash_own_fields(&mut hasher, &("PromqlSubquery", range, resolution));
-            child_hash(child, cache).hash(&mut hasher);
-        }
-        TimeRange { range, child } => {
-            hash_own_fields(&mut hasher, &("TimeRange", range));
-            child_hash(child, cache).hash(&mut hasher);
-        }
-        TimeShift { shift, child } => {
-            hash_own_fields(&mut hasher, &("TimeShift", shift));
-            child_hash(child, cache).hash(&mut hasher);
-        }
-        SQLWindowFunc {
-            func,
-            args,
-            partition_by,
-            order_by,
-            frame,
-            output_name,
-            child,
-        } => {
-            hash_own_fields(
-                &mut hasher,
-                &(
-                    "SQLWindowFunc",
-                    func,
-                    args,
-                    partition_by,
-                    order_by,
-                    frame,
-                    output_name,
-                ),
-            );
-            child_hash(child, cache).hash(&mut hasher);
-        }
-        BinaryOp {
-            op,
-            lhs,
-            rhs,
-            vector_match,
-        } => {
-            hash_own_fields(&mut hasher, &("BinaryOp", op, vector_match));
-            child_hash(lhs, cache).hash(&mut hasher);
-            child_hash(rhs, cache).hash(&mut hasher);
-        }
-        // `EvalTimestamp`, `PromqlScalarBridge`, and the scalar variants
-        // (issue #205) are all leaves for this traversal's purposes — none
-        // has an operator child to look up in `cache` — so hashing the
-        // whole node via `serde_json` in one shot is already `O(node
-        // size)`, not `O(sub-DAG size)`: exactly the same cost the
-        // per-variant `hash_own_fields` calls above pay, just without
-        // needing to spell out each field individually. Matches
-        // `rebuild_children`'s and `dag_node_count`'s identical scope
-        // decision for these variants ("never descended into").
-        EvalTimestamp
-        | CurrentTimestamp
-        | PromqlScalarBridge(_)
-        | Column(_)
-        | Literal(_)
-        | Compare { .. }
-        | BoolAnd(_)
-        | BoolOr(_)
-        | Not(_)
-        | IsNull(_)
-        | IsNotNull(_)
-        | Cast { .. }
-        | InList { .. }
-        | FunctionCall { .. }
-        | Arithmetic { .. }
-        | Case { .. } => hash_own_fields(&mut hasher, node),
-    }
-    hasher.finish()
-}
-
-/// Count of *unique* nodes reachable from `root`, deduplicated by `Rc`
-/// pointer identity (`Rc::as_ptr`) — the real size of the DAG rooted at
-/// `root`, not a per-path walk count.
-///
-/// After [`share_common_sub_dags`] runs (or even before it, for a DAG a
-/// front end already built with internal `Rc` sharing — e.g. re-running
-/// CSE, or a single-query repeated subexpression), `root` is generally a
-/// **DAG** with internal sharing — that is this whole module's premise. Anything that
-/// walks `root` as if every reference were a fresh sub-DAG (a naive
-/// recursive walk with no identity tracking, or a naive full
-/// `serde_json` serialization — `Rc`'s `Serialize` impl serializes the
-/// pointee's *value* at every occurrence, it does not dedupe by identity)
-/// re-visits/re-counts an already-shared descendant once per parent that
-/// references it, over-counting relative to the actual work of holding it
-/// in memory or recomputing it once. This function is the DAG-correct
-/// alternative: each unique node is counted exactly once, regardless of
-/// how many places within `root` reference it.
-///
-/// `pub` so cost-aware callers outside this crate (e.g.
-/// `asap_aware_mapping::CostModel::cse_recompute_cost`'s default) have a
-/// DAG-correct structural-size proxy available, instead of reaching for
-/// something per-path like a raw serialization length.
-///
-/// Same operator-child traversal scope as [`share_common_sub_dags`] itself
-/// (see the module doc's "Algorithm" section, and this module's private
-/// `rebuild_children`) — a scalar subexpression embedded in a wrapper
-/// position (`Predicate`, `ProjectItem.expr`, `Aggregate.having`, …) is not
-/// separately visited, matching this module's own stated scope; it's
-/// counted as part of its owning operator node, the same node
-/// `rebuild_children` treats as a single opaque leaf for interning
-/// purposes.
-pub fn dag_node_count(root: &QueryExpr) -> usize {
-    let mut seen: std::collections::HashSet<*const QueryExpr> = std::collections::HashSet::new();
-    count_unique(root, &mut seen)
-}
-
-/// One node's own contribution (`1`) plus each *not-yet-seen* operator
-/// child's contribution — exhaustive over every `QueryExpr` variant,
-/// enumerating the same fields [`rebuild_children`] does (kept as a
-/// separate, read-only traversal rather than threaded through
-/// `rebuild_children` itself, since that function consumes and rebuilds
-/// its input while this one only ever reads it).
-fn count_unique(node: &QueryExpr, seen: &mut std::collections::HashSet<*const QueryExpr>) -> usize {
-    use QueryExpr::*;
-
-    /// Visit one `Rc`-held child: counts (and recurses into) it only the
-    /// first time its pointer is seen, `0` on every later occurrence —
-    /// this is the actual dedup step.
-    fn visit(
-        child: &Rc<QueryExpr>,
-        seen: &mut std::collections::HashSet<*const QueryExpr>,
-    ) -> usize {
-        if seen.insert(Rc::as_ptr(child)) {
-            count_unique(child, seen)
-        } else {
-            0
-        }
-    }
-
-    1 + match node {
-        // `PromqlScalarBridge`'s child is a scalar-sub-language node (issue
-        // #220), never descended into — same treatment `rebuild_children`
-        // gives it (see that function's comment on this same variant).
-        Scan { .. } | PromqlScalarBridge(_) | EvalTimestamp | CurrentTimestamp => 0,
-        PromqlVectorFromScalar(c) | PromqlScalarFromVector(c) => visit(c, seen),
-        PromqlRelabel { child, .. }
-        | PromqlInfoEnrich { child, .. }
-        | PromqlSeriesSample { child, .. }
-        | Filter { child, .. }
-        | Project { child, .. }
-        | Aggregate { child, .. }
-        | Dedup { child, .. }
-        | Sort { child, .. }
-        | Limit { child, .. }
-        | PromqlSubquery { child, .. }
-        | TimeRange { child, .. }
-        | TimeShift { child, .. }
-        | SQLWindowFunc { child, .. } => visit(child, seen),
-        // `Concat`'s branches are stored by value (`Vec<QueryExpr>`, not
-        // `Rc<QueryExpr>` — see `rebuild_children`'s `intern_owned` use for
-        // this variant), so a branch has no `Rc` identity of its own to
-        // dedup on at this position; still recurse into each in case an
-        // `Rc`-shared descendant appears further down.
-        Concat { children, .. } => children.iter().map(|c| count_unique(c, seen)).sum(),
-        Join { left, right, .. } | SetOp { left, right, .. } => {
-            visit(left, seen) + visit(right, seen)
-        }
-        BinaryOp { lhs, rhs, .. } => visit(lhs, seen) + visit(rhs, seen),
-        // Scalar variants (issue #205) — never descended into, matching
-        // `rebuild_children`'s own scope exactly (see its trailing match
-        // arm and this module's "Algorithm" section).
-        Column(_)
-        | Literal(_)
-        | Compare { .. }
-        | BoolAnd(_)
-        | BoolOr(_)
-        | Not(_)
-        | IsNull(_)
-        | IsNotNull(_)
-        | Cast { .. }
-        | InList { .. }
-        | FunctionCall { .. }
-        | Arithmetic { .. }
-        | Case { .. } => 0,
-    }
-}
-
-/// Recurse into `child`, then intern the result. `Rc::try_unwrap` recovers
-/// the owned node without cloning in the overwhelmingly common case — a
-/// DAG freshly built by a front end / `resolve_root`, not yet shared by any
-/// prior CSE pass, where every `Rc` is uniquely owned. Falls back to cloning
-/// this node's own fields (its children stay `Rc`s, not deep-copied) only
-/// when `child` is already shared — e.g. re-running CSE over a DAG that
-/// went through a previous `share_common_sub_dags` pass; a structural
-/// duplicate collapses right back onto `child` itself via `PartialEq`, an
-/// already-optimal no-op.
-fn intern_child(table: &mut InternTable, child: Rc<QueryExpr>) -> Rc<QueryExpr> {
-    match Rc::try_unwrap(child) {
-        Ok(owned) => intern_bottom_up(table, owned),
-        Err(shared) => intern_bottom_up(table, (*shared).clone()),
-    }
-}
-
-/// Like [`intern_child`], for a `Concat` branch — stored by value
-/// (`Vec<QueryExpr>`, not `Rc<QueryExpr>`), so this position itself can never
-/// alias another parent. Interning it anyway still lets any `Rc`-typed
-/// descendant of the branch participate in sharing, and registers the
-/// branch's own hash/value in the table for a *different* `Concat` elsewhere
-/// with a structurally identical branch (which — being in its own `Vec`
-/// slot too — still can't literally share the `Rc`, but this keeps the
-/// interning behavior uniform and the table's bucket contents consistent).
-fn intern_owned(table: &mut InternTable, expr: QueryExpr) -> QueryExpr {
-    let rc = intern_bottom_up(table, expr);
-    Rc::try_unwrap(rc).unwrap_or_else(|shared| (*shared).clone())
-}
-
-/// Bottom-up: rebuild `expr`'s children (recursively interning each), then
-/// intern the rebuilt node itself.
-fn intern_bottom_up(table: &mut InternTable, expr: QueryExpr) -> Rc<QueryExpr> {
-    let rebuilt = rebuild_children(table, expr);
-    table.intern(rebuilt)
-}
-
-/// Rebuild `expr` with each **operator** child (see the module doc on scope)
-/// replaced by its interned `Rc`. Exhaustive over every `QueryExpr` variant,
-/// matching `canonicalize.rs`'s `children_mut` exactly in which fields count
-/// as an operator child — new variants fail to compile here until this match
-/// is extended.
-fn rebuild_children(table: &mut InternTable, expr: QueryExpr) -> QueryExpr {
-    use QueryExpr::*;
-    match expr {
-        Scan { .. } | EvalTimestamp | CurrentTimestamp => expr,
-        PromqlVectorFromScalar(c) => PromqlVectorFromScalar(intern_child(table, c)),
-        PromqlScalarFromVector(c) => PromqlScalarFromVector(intern_child(table, c)),
-        PromqlRelabel { dst, value, child } => PromqlRelabel {
-            dst,
-            value,
-            child: intern_child(table, child),
-        },
-        PromqlInfoEnrich { selector, child } => PromqlInfoEnrich {
-            selector,
-            child: intern_child(table, child),
-        },
-        PromqlSeriesSample { by, kind, child } => PromqlSeriesSample {
-            by,
-            kind,
-            child: intern_child(table, child),
-        },
-        Filter { pred, child } => Filter {
-            pred,
-            child: intern_child(table, child),
-        },
-        Project {
-            cols,
-            qualifier,
-            child,
-        } => Project {
-            cols,
-            qualifier,
-            child: intern_child(table, child),
-        },
-        Aggregate {
-            reduction,
-            measures,
-            output_names,
-            filters,
-            having,
-            child,
-        } => Aggregate {
-            reduction,
-            measures,
-            output_names,
-            filters,
-            having,
-            child: intern_child(table, child),
-        },
-        Dedup { cols, child } => Dedup {
-            cols,
-            child: intern_child(table, child),
-        },
-        Concat {
-            children,
-            discriminator_unique_key,
-        } => Concat {
-            children: children
-                .into_iter()
-                .map(|c| intern_owned(table, c))
-                .collect(),
-            discriminator_unique_key,
-        },
-        Join {
-            kind,
-            pred,
-            left,
-            right,
-        } => Join {
-            kind,
-            pred,
-            left: intern_child(table, left),
-            right: intern_child(table, right),
-        },
-        SetOp {
-            kind,
-            all,
-            left,
-            right,
-        } => SetOp {
-            kind,
-            all,
-            left: intern_child(table, left),
-            right: intern_child(table, right),
-        },
-        Sort {
-            keys,
-            partition_by,
-            child,
-        } => Sort {
-            keys,
-            partition_by,
-            child: intern_child(table, child),
-        },
-        Limit { n, offset, child } => Limit {
-            n,
-            offset,
-            child: intern_child(table, child),
-        },
-        PromqlSubquery {
-            range,
-            resolution,
-            child,
-        } => PromqlSubquery {
-            range,
-            resolution,
-            child: intern_child(table, child),
-        },
-        TimeRange { range, child } => TimeRange {
-            range,
-            child: intern_child(table, child),
-        },
-        TimeShift { shift, child } => TimeShift {
-            shift,
-            child: intern_child(table, child),
-        },
-        SQLWindowFunc {
-            func,
-            args,
-            partition_by,
-            order_by,
-            frame,
-            output_name,
-            child,
-        } => SQLWindowFunc {
-            func,
-            args,
-            partition_by,
-            order_by,
-            frame,
-            output_name,
-            child: intern_child(table, child),
-        },
-        BinaryOp {
-            op,
-            lhs,
-            rhs,
-            vector_match,
-        } => BinaryOp {
-            op,
-            lhs: intern_child(table, lhs),
-            rhs: intern_child(table, rhs),
-            vector_match,
-        },
-        // `PromqlScalarBridge`'s child is a scalar-sub-language node (issue
-        // #220) — same "never descended into" treatment as the scalar
-        // variants below; the whole bridge node is still interned as a unit
-        // by the `table.intern(rebuilt)` call in `intern_bottom_up`.
-        PromqlScalarBridge(_) => expr,
-        // Scalar variants (issue #205) — never descended into; see the
-        // module doc's "Algorithm" section on scope. Left byte-for-byte
-        // unchanged: predicate / project-list / sort-key / window-arg
-        // expressions stay embedded as opaque leaf data, compared by the
-        // enclosing operator node's derived `PartialEq`.
-        Column(_)
-        | Literal(_)
-        | Compare { .. }
-        | BoolAnd(_)
-        | BoolOr(_)
-        | Not(_)
-        | IsNull(_)
-        | IsNotNull(_)
-        | Cast { .. }
-        | InList { .. }
-        | FunctionCall { .. }
-        | Arithmetic { .. }
-        | Case { .. } => expr,
-    }
-}
-
-/// Share structurally-identical, sharing-legal sub-DAGs across a workload's
-/// query roots (or within one query, for `roots.len() == 1` — see the
-/// module doc's "Single-query CSE" section). Every root's *value* is
-/// unchanged (`PartialEq`-equal to its input) — only its internal `Rc`
-/// structure may now alias another root's, or another part of its own DAG.
-///
-/// `roots` must already be bound + canonicalized (post-`resolve_root`).
-/// `Id` is caller-chosen — a `QueryWorkload` entry's own key, an index, a
-/// query name, whatever identifies one root through the pipeline; this
-/// module has no opinion on its shape.
-pub fn share_common_sub_dags<Id>(roots: Vec<(Id, QueryExpr)>) -> Vec<(Id, Rc<QueryExpr>)> {
-    let mut table = InternTable::new();
-    roots
-        .into_iter()
-        .map(|(id, expr)| (id, intern_bottom_up(&mut table, expr)))
-        .collect()
-}
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-    use crate::pre_asap::agg_intent::AggIntent;
-    use crate::pre_asap::expr_ir::{CompareOpKind, ScalarValue};
-    use crate::pre_asap::query_expr::{BinaryOpKind, GroupKeys, Predicate, Reduction, Source};
-    use crate::pre_asap::schema::{DataType, Field, Schema};
-    use crate::types::AccuracyTarget;
-
-    /// `[ts, service, value, latency]`.
-    fn scan() -> QueryExpr {
-        QueryExpr::Scan {
-            source: Source::TimeSeries { metric: "m".into() },
-            predicates: vec![],
-            schema: Schema::with_time_index(
-                vec![
-                    Field::plain("ts", DataType::Timestamp, false),
-                    Field::plain("service", DataType::Utf8, false),
-                    Field::plain("value", DataType::Float64, false),
-                    Field::plain("latency", DataType::Float64, false),
-                ],
-                0,
-                vec![],
-            ),
-        }
-    }
-
-    fn quantile_agg(by: Vec<usize>, col: Option<usize>, q: f64) -> QueryExpr {
-        QueryExpr::Aggregate {
-            reduction: Reduction::by(by),
-            measures: vec![AggIntent::Quantile {
-                col,
-                q,
-                accuracy: AccuracyTarget::Exact,
-            }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(scan()),
-        }
-    }
-
-    #[test]
-    fn distinct_column_quantiles_do_not_merge() {
-        // Grouped (unique_keys present) so the legality gate isn't what's
-        // blocking the merge — only the differing `col` is.
-        let a = quantile_agg(vec![1], Some(2), 0.5);
-        let b = quantile_agg(vec![1], Some(3), 0.5);
-        let shared = share_common_sub_dags(vec![("a", a), ("b", b)]);
-        let [(_, ra), (_, rb)] = shared.as_slice() else {
-            panic!("expected 2 roots");
-        };
-        assert!(
-            !Rc::ptr_eq(ra, rb),
-            "distinct-column Quantiles must not be shared"
-        );
-        assert_ne!(ra, rb);
-    }
-
-    // Two aggregates that differ only in one measure's `FILTER` predicate
-    // compute different values, so structural sharing must keep them apart.
-    #[test]
-    fn filtered_and_unfiltered_aggregates_do_not_merge() {
-        let a = quantile_agg(vec![1], Some(2), 0.5);
-        let mut b = quantile_agg(vec![1], Some(2), 0.5);
-        let QueryExpr::Aggregate { filters, .. } = &mut b else {
-            unreachable!()
-        };
-        *filters = vec![Some(Predicate(Rc::new(QueryExpr::Compare {
-            left: Rc::new(QueryExpr::Column(3)),
-            op: CompareOpKind::Gt,
-            right: Rc::new(QueryExpr::Literal(ScalarValue::Float64(1.0))),
-        })))];
-        let shared = share_common_sub_dags(vec![("a", a), ("b", b)]);
-        let [(_, ra), (_, rb)] = shared.as_slice() else {
-            panic!("expected 2 roots");
-        };
-        assert!(!Rc::ptr_eq(ra, rb), "a filtered measure must not be shared");
-        assert_ne!(ra, rb);
-    }
-
-    #[test]
-    fn no_unique_keys_means_no_merge_even_when_structurally_identical() {
-        // Ungrouped (global) aggregate: `by` is empty, so
-        // `aggregate_output_schema` reports no unique key today — not
-        // hoistable even though `a` and `b` are structurally identical.
-        let a = quantile_agg(vec![], Some(2), 0.9);
-        let b = quantile_agg(vec![], Some(2), 0.9);
-        assert_eq!(a, b, "fixture sanity: the two DAGs are structurally equal");
-        assert!(
-            !a.output_schema().unwrap().has_unique_key(),
-            "fixture sanity: an ungrouped aggregate has no provable unique key"
-        );
-        let shared = share_common_sub_dags(vec![("a", a), ("b", b)]);
-        let [(_, ra), (_, rb)] = shared.as_slice() else {
-            panic!("expected 2 roots");
-        };
-        assert!(
-            !Rc::ptr_eq(ra, rb),
-            "no unique key ⇒ never hoisted, even for an identical structural match"
-        );
-    }
-
-    #[test]
-    fn median_and_explicit_half_percentile_merge() {
-        // Two front-end spellings ("median" and "approx_percentile_cont(.,
-        // 0.5)") already lower to the identical `AggIntent::Quantile { q:
-        // 0.5, .. }` today (see `sql_lowering.rs`'s
-        // `median_is_the_same_intent_as_an_explicit_half_percentile`) — here
-        // built directly (grouped, so a unique key is provable) as two
-        // independently-constructed but structurally identical DAGs, the
-        // way two different call sites in a workload would produce them.
-        let median = quantile_agg(vec![1], Some(2), 0.5);
-        let approx_percentile_cont_half = quantile_agg(vec![1], Some(2), 0.5);
-        let shared = share_common_sub_dags(vec![
-            ("median", median),
-            ("percentile", approx_percentile_cont_half),
-        ]);
-        let [(_, m), (_, p)] = shared.as_slice() else {
-            panic!("expected 2 roots");
-        };
-        assert!(
-            Rc::ptr_eq(m, p),
-            "median and an explicit 0.5 percentile must merge onto one Rc"
-        );
-    }
-
-    #[test]
-    fn single_query_shares_its_own_repeated_sub_dag() {
-        // One query root referencing the same grouped Aggregate on both
-        // BinaryOp branches — built as two separately-allocated but
-        // structurally identical sub-DAGs (`.clone()` into two distinct
-        // `Rc::new` calls), the shape a front end emitting a repeated
-        // sub-expression would actually produce (no sharing yet). A
-        // workload of size 1 still interns bottom-up within this one DAG —
-        // no separate single-query mechanism needed.
-        let agg = quantile_agg(vec![1], Some(2), 0.5);
-        let root = QueryExpr::BinaryOp {
-            op: BinaryOpKind::Compare(crate::pre_asap::expr_ir::CompareOpKind::Eq),
-            lhs: Rc::new(agg.clone()),
-            rhs: Rc::new(agg),
-            vector_match: None,
-        };
-        let shared = share_common_sub_dags(vec![("q", root)]);
-        let [(_, root)] = shared.as_slice() else {
-            panic!("expected 1 root");
-        };
-        let QueryExpr::BinaryOp { lhs, rhs, .. } = root.as_ref() else {
-            panic!("expected BinaryOp root, got {root:?}");
-        };
-        assert!(
-            Rc::ptr_eq(lhs, rhs),
-            "the two structurally identical branches must collapse onto one Rc"
-        );
-    }
-
-    // ── structural_hash (DAG-aware memoization) ─────────────────────────
-
-    #[test]
-    fn structural_hash_is_stable_across_cache_states() {
-        // The hash of a given *value* must not depend on whether its cache
-        // started warm or cold — memoization changes how much work is
-        // redone, never what a node's hash actually is.
-        let agg = quantile_agg(vec![1], Some(2), 0.5);
-        let mut cold = HashMap::new();
-        let mut warm = HashMap::new();
-        // Prime `warm` with an unrelated node first, so it's non-empty but
-        // holds nothing relevant to `agg`.
-        structural_hash(&scan(), &mut warm);
-        assert_eq!(
-            structural_hash(&agg, &mut cold),
-            structural_hash(&agg, &mut warm),
-            "hash must be independent of unrelated cache state"
-        );
-    }
-
-    #[test]
-    fn structural_hash_of_an_internally_shared_dag_matches_the_unshared_equivalent() {
-        // The same BinaryOp-with-shared-branches shape as
-        // `dag_node_count_deduplicates_an_internally_shared_sub_dag` below:
-        // hashing it (however the memoization internally short-circuits the
-        // second branch) must produce the exact same value as hashing a
-        // structurally-identical DAG built with *no* sharing at all — the
-        // whole point of memoization is not changing the answer, only the
-        // work needed to reach it.
-        let agg = quantile_agg(vec![1], Some(2), 0.5);
-        let shared_root = QueryExpr::BinaryOp {
-            op: BinaryOpKind::Compare(crate::pre_asap::expr_ir::CompareOpKind::Eq),
-            lhs: Rc::new(agg.clone()),
-            rhs: Rc::new(agg.clone()),
-            vector_match: None,
-        };
-        let unshared_root = QueryExpr::BinaryOp {
-            op: BinaryOpKind::Compare(crate::pre_asap::expr_ir::CompareOpKind::Eq),
-            lhs: Rc::new(agg.clone()),
-            rhs: Rc::new(agg), // a second, independently-allocated Rc with an equal value
-            vector_match: None,
-        };
-        let mut cache = HashMap::new();
-        assert_eq!(
-            structural_hash(&shared_root, &mut cache),
-            structural_hash(&unshared_root, &mut HashMap::new()),
-        );
-    }
-
-    #[test]
-    fn structural_hash_memoizes_a_shared_descendant_exactly_once() {
-        // Direct proof the cache is actually doing its job: hashing a
-        // BinaryOp whose two branches are the *same* Rc (2 underlying
-        // nodes: Scan + Aggregate) should populate the cache with exactly
-        // 2 entries — the shared branch's nodes, cached once each when
-        // first reached — not a fresh entry (or a fresh, redundant
-        // recursive walk) for the second occurrence.
-        let agg = quantile_agg(vec![1], Some(2), 0.5);
-        let shared = Rc::new(agg);
-        let root = QueryExpr::BinaryOp {
-            op: BinaryOpKind::Compare(crate::pre_asap::expr_ir::CompareOpKind::Eq),
-            lhs: Rc::clone(&shared),
-            rhs: Rc::clone(&shared),
-            vector_match: None,
-        };
-        let mut cache = HashMap::new();
-        structural_hash(&root, &mut cache);
-        assert_eq!(
-            cache.len(),
-            2,
-            "expected exactly one cache entry per unique node in the shared \
-             branch (Aggregate + its Scan child), got {} entries: {:?}",
-            cache.len(),
-            cache
-        );
-    }
-
-    // ── dag_node_count ───────────────────────────────────────────────────
-
-    #[test]
-    fn dag_node_count_is_the_naive_count_when_nothing_is_shared() {
-        // scan() alone: 1 node.
-        assert_eq!(dag_node_count(&scan()), 1);
-        // quantile_agg's own child is a fresh, unshared scan(): 2 nodes.
-        assert_eq!(dag_node_count(&quantile_agg(vec![1], Some(2), 0.5)), 2);
-    }
-
-    #[test]
-    fn dag_node_count_deduplicates_an_internally_shared_sub_dag() {
-        // Same shape as `single_query_shares_its_own_repeated_sub_dag`: a
-        // BinaryOp whose two branches are the *same* Rc after
-        // `share_common_sub_dags` (2 nodes: Scan + Aggregate) — the root
-        // itself makes 3 unique nodes total (BinaryOp, Aggregate, Scan),
-        // not 5 (which a per-path walk / naive serialization, counting the
-        // shared branch's 2 nodes twice, would report).
-        let agg = quantile_agg(vec![1], Some(2), 0.5);
-        let root = QueryExpr::BinaryOp {
-            op: BinaryOpKind::Compare(crate::pre_asap::expr_ir::CompareOpKind::Eq),
-            lhs: Rc::new(agg.clone()),
-            rhs: Rc::new(agg),
-            vector_match: None,
-        };
-        let shared = share_common_sub_dags(vec![("q", root)]);
-        let [(_, root)] = shared.as_slice() else {
-            panic!("expected 1 root");
-        };
-        assert_eq!(
-            dag_node_count(root),
-            3,
-            "the shared branch's 2 nodes must be counted once, not once per \
-             occurrence — got {} for {root:?}",
-            dag_node_count(root)
-        );
-    }
-
-    #[test]
-    fn dag_node_count_deduplicates_across_two_workload_roots() {
-        // Two workload roots sharing one Aggregate after
-        // `share_common_sub_dags` (the `duplicate_workload_queries_...`
-        // shape from `crates/integration-tests/tests/cse.rs`, built
-        // directly here): each root's own `dag_node_count` must report the
-        // shared sub-DAG's real size once, not double-count anything —
-        // there's nothing *to* double-count from a single root's own count
-        // in this case (no root references the shared node twice), so this
-        // pins the simpler, more common case that a per-candidate cost
-        // proxy (`CseCandidate::sub-DAG` in `asap-aware-mapping`) actually
-        // exercises: counting one occurrence's own reachable DAG size.
-        let a = quantile_agg(vec![1], Some(2), 0.5);
-        let b = quantile_agg(vec![1], Some(2), 0.5);
-        let shared = share_common_sub_dags(vec![("a", a), ("b", b)]);
-        let [(_, ra), (_, rb)] = shared.as_slice() else {
-            panic!("expected 2 roots");
-        };
-        assert!(Rc::ptr_eq(ra, rb), "fixture sanity: the two roots merged");
-        assert_eq!(dag_node_count(ra), 2);
-        assert_eq!(dag_node_count(rb), 2);
-    }
-
-    #[test]
-    fn dedup_gates_sharing_the_same_as_aggregate() {
-        // `Dedup { cols }` adds `cols` as a unique key — so two identical
-        // `Dedup` sub-DAGs over a keyed column *do* merge, exercising the
-        // legality gate on a non-`Aggregate` node.
-        let dedup = |cols: Vec<usize>| QueryExpr::Dedup {
-            cols,
-            child: Rc::new(scan()),
-        };
-        let a = dedup(vec![1]);
-        let b = dedup(vec![1]);
-        let shared = share_common_sub_dags(vec![("a", a), ("b", b)]);
-        let [(_, ra), (_, rb)] = shared.as_slice() else {
-            panic!("expected 2 roots");
-        };
-        assert!(
-            Rc::ptr_eq(ra, rb),
-            "Dedup on the same cols has a provable unique key and should merge"
-        );
-    }
-
-    #[test]
-    fn group_keys_gate_still_prevented_when_partition_by_without_used() {
-        // Sanity on the module's advertised precedent: a `without(...)`
-        // grouping stays open (no unique key) even though `by` is
-        // non-empty-shaped structurally, so two identical `without` groups
-        // do not merge under the same gate that blocks the ungrouped case.
-        let without_agg = || QueryExpr::Aggregate {
-            reduction: Reduction::Reduce(GroupKeys::without(vec![0])),
-            measures: vec![AggIntent::Count {
-                accuracy: AccuracyTarget::Exact,
-            }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(scan()),
-        };
-        let a = without_agg();
-        let b = without_agg();
-        assert!(!a.output_schema().unwrap().has_unique_key());
-        let shared = share_common_sub_dags(vec![("a", a), ("b", b)]);
-        let [(_, ra), (_, rb)] = shared.as_slice() else {
-            panic!("expected 2 roots");
-        };
-        assert!(!Rc::ptr_eq(ra, rb));
-    }
-}
diff --git a/crates/types/src/pre_asap/expr_ir.rs b/crates/types/src/pre_asap/expr_ir.rs
index 21ffe21bf..fe373e58f 100644
--- a/crates/types/src/pre_asap/expr_ir.rs
+++ b/crates/types/src/pre_asap/expr_ir.rs
@@ -1,29 +1,20 @@
-//! Column-reference and scalar-operator vocabulary shared by the whole
-//! canonical [`QueryExpr`](super::query_expr::QueryExpr) DAG.
-//!
-//! Issue #205: the scalar expression shapes (`Column`/`Literal`/`Compare`/…)
-//! used to live in a separate, self-recursive `Expr<C>` DAG here, reachable
-//! from `QueryExpr` only through wrapper fields (`Predicate`, `ProjectItem`,
-//! `SortKey`). They're variants of `QueryExpr<C>` itself now — one recursive
-//! DAG, not two type families joined by wrappers — generic over the same
-//! column-reference state `C` the rest of `QueryExpr` already carries
-//! (issue #179): [`ColumnRef`] (name-based, front-end-emitted) or
-//! [`ColumnId`](super::schema::ColumnId) (positional, once bound).
-//!
-//! What's left here is the vocabulary those scalar variants are built from —
-//! [`ScalarValue`], [`CompareOpKind`], [`ArithmeticOpKind`] — the **union** of what the two
+//! Column-reference and scalar-operator vocabulary shared by the IR's scalar
+//! expressions ([`crate::ir::ScalarExpr`]) and the front ends' unresolved
+//! form: [`ColumnRef`] (name-based, front-end-emitted; positional
+//! [`ColumnId`](super::schema::ColumnId) once bound), and [`ScalarValue`],
+//! [`CompareOpKind`], [`ArithmeticOpKind`] — the **union** of what the two
 //! front ends need: PromQL contributes `Regex` / `NotRegex` (`=~` / `!~`); SQL
 //! contributes arithmetic, `CASE`, `IN`, `CAST`, `IS [NOT] NULL`, scalar
 //! function calls, and the `LIKE` / `ILIKE` comparison family.
 
 use serde::{Deserialize, Serialize};
 
-/// A name-based column reference — the front-end-emitted, unresolved state of
-/// [`QueryExpr::Column`](super::query_expr::QueryExpr::Column) (`C =
-/// ColumnRef`); the [`SchemaResolver`](super::schema_resolver::SchemaResolver) resolves it to a
-/// positional [`ColumnId`](super::schema::ColumnId). This is a logical reference,
-/// not schema metadata or a runtime data array. `SampleValue` names the implicit
-/// PromQL sample column; `Wildcard` represents an all-columns/rows request.
+/// A name-based column reference — the front-end-emitted, unresolved form of
+/// [`ScalarExpr::Column`](crate::ir::ScalarExpr::Column); front-end name
+/// resolution turns it into a positional [`ColumnId`](super::schema::ColumnId).
+/// This is a logical reference, not schema metadata or a runtime data array.
+/// `SampleValue` names the implicit PromQL sample column; `Wildcard` represents
+/// an all-columns/rows request.
 #[derive(Debug, Clone, PartialEq, Eq, Hash, Serialize, Deserialize)]
 pub enum ColumnRef {
     Named(String),
diff --git a/crates/types/src/pre_asap/mod.rs b/crates/types/src/pre_asap/mod.rs
index 1a017ec27..c309c7b30 100644
--- a/crates/types/src/pre_asap/mod.rs
+++ b/crates/types/src/pre_asap/mod.rs
@@ -1,66 +1,34 @@
-//! The canonical pre-ASAP intent algebra IR.
+//! Shared vocabulary of the operator IR. The operators themselves live in
+//! [`crate::ir`]; this module holds the field types they are built from.
 //!
-//! - [`query_expr`] — the canonical, language- and deployment-independent
-//!   intent algebra: one recursive [`QueryExpr`] DAG (relational operators
-//!   *and* scalar expression shapes both, since issue #205) + [`AggIntent`],
-//!   generic over the column-reference state (positional [`ColumnId`] once
-//!   bound, name-based [`ColumnRef`] before).
-//! - [`agg_intent`] — the aggregation-intent vocabulary.
-//! - [`expr_ir`] — the [`ColumnRef`] column-reference type and the scalar
-//!   operator/literal vocabulary ([`ScalarValue`], [`CompareOpKind`], [`ArithmeticOpKind`])
-//!   [`QueryExpr`]'s scalar variants are built from.
+//! Operator parameters and schema derivation live in [`crate::ir`].
+//! - [`agg_intent`] — the aggregation-intent vocabulary ([`AggIntent`]).
+//! - [`expr_ir`] — [`ColumnRef`] and the scalar literal / operator kinds
+//!   ([`ScalarValue`], [`CompareOpKind`], [`ArithmeticOpKind`]).
 //! - [`schema`] — the per-edge [`Schema`] every node carries.
-//! - [`schema_resolver`] / [`column_resolution`] — name resolution: turn a `ColumnRef`
-//!   into a positional `ColumnId` against an in-scope [`Schema`].
-//! - [`resolve`] — binds a whole front-end-emitted [`UnresolvedQueryExpr`] DAG to
-//!   canonical [`ResolvedQueryExpr`] (issue #179): both front ends
-//!   (`asap-frontend-promql`, `asap-frontend-sql`) construct `UnresolvedQueryExpr`
-//!   directly during their own `interpret` step and call
-//!   [`resolve_root`] on the result — there is no separate per-language
-//!   relational DAG or converter anymore.
-//! - [`canonicalize`] — post-lowering structural normalization of [`QueryExpr`]
-//!   (issue #34), run by [`resolve_root`].
-//! - [`cse`] — workload-level structural common-subexpression elimination
-//!   over an already-`resolve_root`'d DAG (issue #212, #222, #223), run
-//!   *after* `resolve_root` / `canonicalize` and *before* implementation
-//!   (`asap_aware_mapping::replacement`).
-//!
-//! Formerly the separate `asap-l2` crate; folded in here since
-//! `schema_resolver`/`column_resolution`/`canonicalize`/`resolve` have no
-//! front-end-specific logic — they operate directly on this crate's own
-//! `QueryExpr`.
+//! - [`column_resolution`] — turn a name-based `ColumnRef` into a positional
+//!   `ColumnId` against a [`Schema`] (used by front-end name resolution).
+//! - [`scalar_type_rules`] — shared scalar type and nullability rules.
 
 pub mod agg_intent;
-pub mod canonicalize;
 pub mod column_resolution;
-pub mod cse;
 pub mod expr_ir;
-pub mod query_expr;
-pub mod resolve;
 pub mod scalar_type_rules;
 pub mod schema;
-pub mod schema_resolver;
 
+pub use crate::ir::operator_properties::{
+    AtModifier, BinaryOpKind, ColState, ConcatDiscriminatorKey, DataModel, GroupKeys, GroupSide,
+    InfoMatcher, JoinKind, PromQLVectorSetOpKind, Reduction, RelationalSetOpKind, SampleKind,
+    Source, TimeShift, VectorGrouping, VectorMatch, VectorMatchKind, WindowFrame, WindowFrameBound,
+    WindowFrameOffset, WindowFrameUnits, WindowFuncKind,
+};
 pub use agg_intent::{
     agg_accuracy, agg_is_exact, agg_is_mergeable, default_cardinality, default_quantile, AggIntent,
     MathFunc, TimeFunc,
 };
-pub use canonicalize::canonicalize;
-pub use column_resolution::{
-    output_schema_for_aggregate, resolve_column_ref, resolve_column_refs, resolve_expr,
-    ResolveError,
-};
-pub use cse::share_common_sub_dags;
+pub use column_resolution::{resolve_column_ref, resolve_column_refs, ResolveError};
 pub use expr_ir::{ArithmeticOpKind, ColumnRef, CompareOpKind, ScalarValue};
-pub use query_expr::{
-    aggregate_output_schema, any_measure_filtered, AtModifier, BinaryOpKind, ColState, DataModel,
-    GroupKeys, GroupSide, InfoMatcher, JoinKind, Predicate, ProjectItem, PromQLVectorSetOpKind,
-    QueryExpr, QueryExprError, Reduction, RelationalSetOpKind, ResolvedQueryExpr, SampleKind,
-    SortKey, Source, TimeShift, UnresolvedQueryExpr, VectorGrouping, VectorMatch, VectorMatchKind,
-    WindowFrame, WindowFrameBound, WindowFrameOffset, WindowFrameUnits, WindowFuncKind,
-};
-pub use resolve::{resolve_root, ResolveDAGError};
 pub use schema::{ColumnId, DataType, Field, FieldDataType, Schema};
-pub use schema_resolver::{SchemaCatalog, SchemaResolver, UsageDerivedCatalog};
 
+pub use crate::ir::aggregate_schema::aggregate_output_schema;
 pub use crate::ir::SchemaDerivationError;
diff --git a/crates/types/src/pre_asap/query_expr.rs b/crates/types/src/pre_asap/query_expr.rs
deleted file mode 100644
index e389f84a2..000000000
--- a/crates/types/src/pre_asap/query_expr.rs
+++ /dev/null
@@ -1,2774 +0,0 @@
-//! The canonical pre-ASAP intent algebra IR.
-//!
-//! Language- and deployment-independent. `Rc`-owned DAG — a child field is
-//! `Rc<QueryExpr<C>>` rather than `Box<QueryExpr<C>>` so a structurally
-//! identical sub-expression can be shared (the same `Rc`) across more than
-//! one parent, within one query or across a `QueryWorkload` batch, instead of
-//! being duplicated. Nothing in this module produces that sharing on its
-//! own — construction still allocates a fresh `Rc` per node, the same shape
-//! as the old `Box` DAG — a separate CSE pass is what turns two
-//! independently constructed, structurally-equal sub-DAGs into two
-//! references to one `Rc` (issue #212, #222). Field identity is
-//! **positional** (`Aggregate.reduction: Reduction`, wrapping `GroupKeys`
-//! for the grouped case), resolved by the [`SchemaResolver`](super::schema_resolver) against
-//! the self-contained [`Schema`] carried on each `Scan`.
-
-use std::rc::Rc;
-use std::time::Duration;
-
-use serde::{Deserialize, Serialize};
-use thiserror::Error;
-
-use super::agg_intent::AggIntent;
-use super::expr_ir::{ArithmeticOpKind, ColumnRef, CompareOpKind, ScalarValue};
-use super::schema::{ColumnId, DataType, Field, FieldDataType, Schema};
-
-/// The column-reference resolution state a [`QueryExpr<C>`] DAG carries —
-/// [`ColumnId`] (the default, and what the bare `QueryExpr` name has always
-/// meant) once the [`SchemaResolver`](super::schema_resolver::SchemaResolver) has resolved every
-/// reference positionally, or the front-end-emitted, name-based [`ColumnRef`]
-/// before binding. The only place the two states differ in *shape* rather
-/// than just in which type fills `C` is [`QueryExpr::Scan`]'s `schema` field:
-/// a bound DAG's binding schema is always known (the SchemaResolver is total, so
-/// [`ScanSchema`](Self::ScanSchema) `= Schema`); an unresolved front-end
-/// `Scan` knows its schema only when the front end already has it without
-/// binding — a SQL leaf, catalog-backed (`Some`) — `None` (PromQL) defers to
-/// the SchemaResolver, so `ScanSchema = Option<Schema>`.
-pub trait ColState:
-    Clone + std::fmt::Debug + PartialEq + Serialize + for<'de> Deserialize<'de>
-{
-    /// What [`QueryExpr::Scan`]'s `schema` field holds for a DAG in this state.
-    type ScanSchema: Clone + std::fmt::Debug + PartialEq + Serialize + for<'de> Deserialize<'de>;
-}
-
-impl ColState for ColumnId {
-    type ScanSchema = Schema;
-}
-
-impl ColState for ColumnRef {
-    type ScanSchema = Option<Schema>;
-}
-
-/// Errors from schema derivation over a canonical DAG.
-#[derive(Debug, Error)]
-pub enum QueryExprError {
-    #[error("invalid scalar function signature: {0}")]
-    InvalidScalarSignature(String),
-    #[error("by-column id {0} out of range (input has {1} columns)")]
-    InvalidGroupByColumn(ColumnId, usize),
-    #[error("Concat requires at least one child")]
-    EmptyConcat,
-    /// [`QueryExpr::output_schema`] called on (or reached, while recursing, a
-    /// child that is) one of the scalar variants (issue #205) — those have no
-    /// independent row schema of their own; a scalar expression's *type* only
-    /// makes sense against the schema it's embedded in (see `infer_expr_type`,
-    /// used by `Project`'s own `output_schema` arm instead).
-    #[error("a scalar expression has no row schema of its own")]
-    ScalarHasNoRowSchema,
-    #[error("invalid per-series sample column: {0}")]
-    InvalidSampleColumn(String),
-}
-
-// ── Leaf / supporting types ───────────────────────────────────────────────────
-
-/// Positional grouping keys, shared by every "operate per group" operator:
-/// `Aggregate.by` (reduce per group), `Sort.partition_by` (rank per group —
-/// including generic `topk`/`bottomk`), and `SQLWindowFunc.partition_by` (window
-/// per group). One spelling so grouping has a single home to evolve. Empty
-/// (and `by`) = no grouping (a global operation).
-///
-/// Heavy-hitter `AggIntent::TopK` carries its grouping here too, via the
-/// enclosing `Aggregate.by` (issue #13) — so reduce, rank, and window groupings
-/// all share this one type.
-///
-/// ## `by` vs `without` (issue #39)
-///
-/// The stored [`keys`](Self::keys) are **kept** labels for `by(...)` and
-/// **excluded** labels for `without(...)`. PromQL's `without(labels)` groups by
-/// every label *except* those listed; the complement can't be enumerated at
-/// lowering time under an open (usage-derived) schema, so it is deferred to the
-/// runtime — the excluded positions are stored, the kept set stays open. Only
-/// `Aggregate` ever produces the `without` form; `Sort` / `SQLWindowFunc` /
-/// `PromqlSeriesSample` groupings are always `by`.
-///
-/// Serialises as a bare array for the (overwhelmingly common) `by` case —
-/// wire-compatible with the `Vec<ColumnId>` this field held before — and as
-/// `{"without": [...]}` for the exclusion case.
-#[derive(Debug, Clone, PartialEq, Eq, Hash)]
-pub struct GroupKeys<C = ColumnId> {
-    keys: Vec<C>,
-    without: bool,
-}
-
-// Not `#[derive(Default)]`: derive would add a `C: Default` bound, but an
-// empty key set needs nothing from `C` — `ColumnRef` has no meaningful
-// default anyway.
-impl<C> Default for GroupKeys<C> {
-    fn default() -> Self {
-        Self {
-            keys: Vec::new(),
-            without: false,
-        }
-    }
-}
-
-impl<C> GroupKeys<C> {
-    /// An empty key set — a global (ungrouped) operation.
-    pub fn none() -> Self {
-        Self::default()
-    }
-    /// `by(keys)` — group by exactly these columns.
-    pub fn by(keys: Vec<C>) -> Self {
-        Self {
-            keys,
-            without: false,
-        }
-    }
-    /// `without(keys)` — group by every label *except* these (issue #39). The
-    /// kept set is runtime-resolved; only the excluded positions are stored.
-    pub fn without(keys: Vec<C>) -> Self {
-        Self {
-            keys,
-            without: true,
-        }
-    }
-    /// Whether this is a `without(...)` exclusion grouping.
-    pub fn is_without(&self) -> bool {
-        self.without
-    }
-    /// The named keys — kept labels for `by`, excluded labels for `without`.
-    pub fn keys(&self) -> &[C] {
-        &self.keys
-    }
-}
-
-impl<C> std::ops::Deref for GroupKeys<C> {
-    type Target = [C];
-    fn deref(&self) -> &Self::Target {
-        &self.keys
-    }
-}
-
-impl<C> From<Vec<C>> for GroupKeys<C> {
-    fn from(keys: Vec<C>) -> Self {
-        Self::by(keys)
-    }
-}
-
-impl<C> FromIterator<C> for GroupKeys<C> {
-    fn from_iter<I: IntoIterator<Item = C>>(iter: I) -> Self {
-        Self::by(iter.into_iter().collect())
-    }
-}
-
-impl<'a, C> IntoIterator for &'a GroupKeys<C> {
-    type Item = &'a C;
-    type IntoIter = std::slice::Iter<'a, C>;
-    fn into_iter(self) -> Self::IntoIter {
-        self.keys.iter()
-    }
-}
-
-/// Compare directly against a `Vec<C>` so call sites and tests can keep
-/// writing `keys == vec![..]` / `assert_eq!(keys, &vec![..])`. A `without`
-/// grouping never equals a bare `by` list.
-impl<C: PartialEq> PartialEq<Vec<C>> for GroupKeys<C> {
-    fn eq(&self, other: &Vec<C>) -> bool {
-        !self.without && &self.keys == other
-    }
-}
-
-/// (De)serialise as a bare array for `by`, or `{"without": [...]}` for the
-/// exclusion form — keeping the `by` wire format identical to the old newtype.
-/// Borrowed for `Serialize` (no `C: Clone` needed to write one out), owned for
-/// `Deserialize` (there's nothing to borrow from).
-#[derive(Serialize)]
-#[serde(untagged)]
-enum GroupKeysReprRef<'a, C> {
-    By(&'a [C]),
-    Without { without: &'a [C] },
-}
-
-#[derive(Deserialize)]
-#[serde(untagged)]
-enum GroupKeysRepr<C> {
-    By(Vec<C>),
-    Without { without: Vec<C> },
-}
-
-impl<C: Serialize> Serialize for GroupKeys<C> {
-    fn serialize<S: serde::Serializer>(&self, serializer: S) -> Result<S::Ok, S::Error> {
-        if self.without {
-            GroupKeysReprRef::Without {
-                without: self.keys.as_slice(),
-            }
-            .serialize(serializer)
-        } else {
-            GroupKeysReprRef::By(self.keys.as_slice()).serialize(serializer)
-        }
-    }
-}
-
-impl<'de, C: Deserialize<'de>> Deserialize<'de> for GroupKeys<C> {
-    fn deserialize<D: serde::Deserializer<'de>>(deserializer: D) -> Result<Self, D::Error> {
-        Ok(match GroupKeysRepr::deserialize(deserializer)? {
-            GroupKeysRepr::By(keys) => Self::by(keys),
-            GroupKeysRepr::Without { without } => Self::without(without),
-        })
-    }
-}
-
-/// Which data model a `Source` / `AggIntent` operates over.
-#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
-pub enum DataModel {
-    TimeSeries,
-    Tabular,
-    Any,
-}
-
-/// The leaf data source of a `Scan`. The schema itself rides on the
-/// `Scan.schema` field (SchemaResolver-built); `Source` carries only the leaf's
-/// identity.
-#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
-pub enum Source {
-    /// Time-series leaf — PromQL / DC lifecycle. Produces `(ts, value, *labels)`.
-    TimeSeries { metric: String },
-    /// Tabular leaf — asap-fusion / future OLAP. Columns ride on `Scan.schema`.
-    Table { table_ref: String },
-}
-
-impl Source {
-    pub fn data_model(&self) -> DataModel {
-        match self {
-            Source::TimeSeries { .. } => DataModel::TimeSeries,
-            Source::Table { .. } => DataModel::Tabular,
-        }
-    }
-}
-
-/// Operator on the query-level `BinaryOp` node. Reuses the scalar IR's
-/// [`ArithmeticOpKind`] / [`CompareOpKind`] so every arithmetic/comparison
-/// operator has exactly one representation (and one `Display`) across the IR.
-#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
-pub enum BinaryOpKind {
-    /// Arithmetic — `Add/Sub/Mul/Div/Mod` (shared with `QueryExpr::Arithmetic`).
-    Arithmetic(ArithmeticOpKind),
-    /// Comparison — `Eq/Ne/Lt/Le/Gt/Ge` + `Like/ILike/Regex` family (shared
-    /// with `QueryExpr::Compare`). PromQL keeps the matched series whose
-    /// comparison holds.
-    Compare(CompareOpKind),
-    /// PromQL comparison with the `bool` modifier: every matched series
-    /// yields 1 or 0 and loses its metric name. A separate variant, not a
-    /// flag, because only comparisons take `bool`.
-    CompareBool(CompareOpKind),
-    /// PromQL vector-set operation.
-    Set(PromQLVectorSetOpKind),
-}
-
-impl std::fmt::Display for BinaryOpKind {
-    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
-        match self {
-            BinaryOpKind::Arithmetic(op) => write!(f, "{op}"),
-            BinaryOpKind::Compare(op) => write!(f, "{op}"),
-            BinaryOpKind::CompareBool(op) => write!(f, "{op} bool"),
-            BinaryOpKind::Set(PromQLVectorSetOpKind::And) => f.write_str("AND"),
-            BinaryOpKind::Set(PromQLVectorSetOpKind::Or) => f.write_str("OR"),
-            BinaryOpKind::Set(PromQLVectorSetOpKind::Unless) => f.write_str("unless"),
-        }
-    }
-}
-
-#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
-pub enum JoinKind {
-    Inner,
-    Left,
-    Right,
-    Full,
-    Cross,
-    /// Left semi-join — each left row that has **at least one** match, once.
-    /// `WHERE c IN (SELECT …)` / `WHERE EXISTS (…)` (issue #111).
-    ///
-    /// Output schema is the **left's alone**; the right side is a filter, not a
-    /// source of columns. The join predicate still resolves against the
-    /// concatenated `left ++ right` schema — its scope is deliberately wider
-    /// than the node's output.
-    Semi,
-    /// Left anti-join — each left row with **no** match. `WHERE NOT EXISTS (…)`.
-    /// Same schema rule as [`JoinKind::Semi`].
-    ///
-    /// Note this is *not* `NOT IN (SELECT …)`: under SQL's three-valued logic a
-    /// NULL on the right makes `NOT IN` yield no rows at all, where an anti-join
-    /// yields every left row. The SQL front end rejects `NOT IN (subquery)`
-    /// rather than lower it here.
-    Anti,
-}
-
-#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
-pub enum RelationalSetOpKind {
-    Union,
-    Intersect,
-    Except,
-}
-
-/// PromQL vector-set operator used by [`BinaryOpKind::Set`].
-#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
-pub enum PromQLVectorSetOpKind {
-    And,
-    Or,
-    Unless,
-}
-
-/// SQL analytic window function (`fn(...) OVER (…)`). Distinct from a streaming
-/// time `Window`: this is an analytic frame over already-materialised rows.
-#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
-#[serde(rename_all = "snake_case")]
-pub enum WindowFuncKind {
-    RowNumber,
-    Rank,
-    DenseRank,
-    Lag,
-    Lead,
-    /// ClickHouse `lagInFrame`/`leadInFrame`: unlike [`Lag`](Self::Lag)/[`Lead`](Self::Lead),
-    /// these respect the window frame bounds (NULL/default past the frame edge)
-    /// rather than reaching arbitrarily far back/forward. Kept as distinct
-    /// variants so the frame clause is never silently discarded by conflating
-    /// them with `Lag`/`Lead` (#267). `WindowFuncKind` still has no frame
-    /// representation, so today these lower and behave exactly like
-    /// `Lag`/`Lead` — the tag is correct, the frame-respecting behavior isn't
-    /// implemented yet. See #231 for modeling window frames properly.
-    LagInFrame,
-    LeadInFrame,
-    FirstValue,
-    LastValue,
-    /// `NTH_VALUE(expr, n)` — `n` is resolved from the (literal) 2nd argument.
-    NthValue(Option<u64>),
-    Sum,
-    Avg,
-    Count,
-    Min,
-    Max,
-}
-
-/// A window's frame-spec (`ROWS`/`RANGE BETWEEN … AND …`) — which rows around
-/// the current one an analytic window function reads. `GROUPS` is rejected at
-/// lowering time (issue #268): every SQL corpus in this repo uses only `ROWS`,
-/// and nothing downstream interprets frame semantics yet, so it isn't worth
-/// modelling untested.
-///
-/// Meaningless (but harmless) on the rank-only and navigation functions
-/// (`ROW_NUMBER`/`RANK`/`DENSE_RANK`/`LAG`/`LEAD`), which ignore the frame per
-/// SQL semantics — DataFusion still attaches one, stored here verbatim.
-#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
-pub struct WindowFrame {
-    pub units: WindowFrameUnits,
-    pub start_bound: WindowFrameBound,
-    pub end_bound: WindowFrameBound,
-}
-
-/// A finite window-frame displacement. Intervals are normalized to Arrow's
-/// month/day/nanosecond representation so SQL `RANGE INTERVAL ...` bounds
-/// survive lowering without leaking DataFusion types into the canonical IR.
-#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
-#[serde(rename_all = "snake_case")]
-pub enum WindowFrameOffset {
-    Scalar(ScalarValue),
-    Interval {
-        months: i32,
-        days: i32,
-        nanoseconds: i64,
-    },
-}
-
-#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
-#[serde(rename_all = "snake_case")]
-pub enum WindowFrameUnits {
-    /// Boundaries count physical rows: `ROWS BETWEEN 2 PRECEDING AND CURRENT ROW`.
-    Rows,
-    /// Boundaries count by value-distance on the (single) `ORDER BY` column:
-    /// `RANGE BETWEEN INTERVAL '1' HOUR PRECEDING AND CURRENT ROW`.
-    Range,
-}
-
-#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
-#[serde(rename_all = "snake_case")]
-pub enum WindowFrameBound {
-    /// `UNBOUNDED PRECEDING` is
-    /// `Preceding(WindowFrameOffset::Scalar(ScalarValue::Null))`.
-    Preceding(WindowFrameOffset),
-    CurrentRow,
-    /// `UNBOUNDED FOLLOWING` is
-    /// `Following(WindowFrameOffset::Scalar(ScalarValue::Null))`.
-    Following(WindowFrameOffset),
-}
-
-/// A symbolic label matcher on the **info metric** side of an
-/// [`QueryExpr::PromqlInfoEnrich`] (issue #84). Unlike a `Scan` predicate it is not
-/// resolved positionally — it references the info metric's labels (`__name__`
-/// picks the metric, the rest constrain data labels), which aren't in the input
-/// vector's schema; the post-ASAP realization pass applies it against the info metric.
-#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
-pub struct InfoMatcher {
-    pub label: String,
-    /// One of `Eq` / `Ne` / `Regex` / `NotRegex` (PromQL `=`/`!=`/`=~`/`!~`).
-    pub op: CompareOpKind,
-    pub value: String,
-}
-
-/// Series-sampling selection mode (PromQL `limitk` / `limit_ratio`, issue #86).
-/// A [`QueryExpr::PromqlSeriesSample`] keeps a *subset of whole series*, unchanged — it does
-/// not rank or reduce, so it is distinct from `TopK` and from `Sort → Limit`.
-#[derive(Debug, Clone, Copy, PartialEq, Serialize, Deserialize)]
-#[serde(rename_all = "snake_case")]
-pub enum SampleKind {
-    /// `limitk(k, v)` — up to `k` series per group. Which series survive is
-    /// deterministic across evaluations but otherwise unspecified (no ordering).
-    LimitK(usize),
-    /// `limit_ratio(r, v)` — a deterministic `r`-fraction of series per group.
-    /// `r ∈ [-1, 1]`; a negative `r` selects the complementary fraction.
-    LimitRatio(f64),
-}
-
-#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
-#[serde(bound(serialize = "C: ColState", deserialize = "C: ColState"))]
-pub struct SortKey<C: ColState = ColumnId> {
-    pub expr: QueryExpr<C>,
-    pub ascending: bool,
-    pub nulls_first: bool,
-}
-
-/// PromQL vector-match modifier (`on`/`ignoring` + `group_left`/`group_right`).
-#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
-pub struct VectorMatch {
-    pub kind: VectorMatchKind,
-    pub labels: Vec<String>,
-    pub grouping: Option<VectorGrouping>,
-}
-
-/// PromQL `@` modifier — pins a selector's evaluation time to an anchor instead
-/// of the query evaluation time (issue #40).
-#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
-pub enum AtModifier {
-    /// `@ start()` — the query range's start instant.
-    Start,
-    /// `@ end()` — the query range's end instant.
-    End,
-    /// `@ <ts>` — an absolute instant, milliseconds since the Unix epoch (may be
-    /// negative). PromQL writes the timestamp in seconds; the front end scales it.
-    Timestamp(i64),
-}
-
-/// PromQL per-selector **time-shift** modifiers — `offset` and `@` (issue #40).
-/// Neither changes a selector's *schema*; both move *when* it is evaluated, so
-/// the shift is a pass-through wrapper ([`QueryExpr::TimeShift`]) over the
-/// selector rather than a new leaf shape. The runtime resolves the anchor and
-/// applies the offset.
-#[derive(Debug, Clone, Copy, PartialEq, Eq, Default, Serialize, Deserialize)]
-pub struct TimeShift {
-    /// `offset <d>` as signed milliseconds — a positive value shifts the
-    /// lookback *back* in time (`offset 5m`), a negative value shifts it
-    /// *forward* (`offset -5m`). `0` = no offset.
-    pub offset_ms: i64,
-    /// `@` anchor; `None` = evaluate at the query time.
-    pub at: Option<AtModifier>,
-}
-
-impl TimeShift {
-    /// Whether this shift is the identity (no `offset`, no `@`) — the state of
-    /// every selector that carries neither modifier.
-    pub fn is_identity(&self) -> bool {
-        self.offset_ms == 0 && self.at.is_none()
-    }
-}
-
-#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
-pub enum VectorMatchKind {
-    On,
-    Ignoring,
-}
-
-#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
-pub struct VectorGrouping {
-    pub side: GroupSide,
-    pub labels: Vec<String>,
-}
-
-#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
-pub enum GroupSide {
-    Left,
-    Right,
-}
-
-/// A row-level filter predicate (WHERE clause / PromQL label matcher).
-/// Boxed: `Predicate<C>` sits directly (not behind a `Vec`) in
-/// `Filter.pred`/`Join.pred`/`Aggregate.having`, and `QueryExpr<C>` is
-/// self-recursive without further indirection once the scalar variants are
-/// part of it — the box is what makes the recursive type's size finite there.
-#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
-#[serde(bound(serialize = "C: ColState", deserialize = "C: ColState"))]
-pub struct Predicate<C: ColState = ColumnId>(pub Rc<QueryExpr<C>>);
-
-/// Whether any entry of an `Aggregate.filters` vector is set — the shape
-/// no binding rule accepts yet (issue #466): a filtered measure stays
-/// `KeepPreAsap`, and heavy-hitter promotion skips it.
-pub fn any_measure_filtered<C: ColState>(filters: &[Option<Predicate<C>>]) -> bool {
-    filters.iter().any(Option::is_some)
-}
-
-/// One item in a SELECT projection list.
-#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
-#[serde(bound(serialize = "C: ColState", deserialize = "C: ColState"))]
-pub struct ProjectItem<C: ColState = ColumnId> {
-    pub alias: Option<String>,
-    pub expr: QueryExpr<C>,
-}
-
-// ── Intent algebra IR ────────────────────────────────────────────────────────
-
-/// What kind of computation an `Aggregate` node performs — orthogonal to
-/// *which* columns it groups by (that's still [`GroupKeys`], inside
-/// `Reduce`). Explicit, decided once by whichever pass constructs the node
-/// (structural, at front-end lowering time), rather than inferred downstream from
-/// whether a grouping-key list happens to be empty or from a neighboring
-/// node's shape. See design proposal #165.
-#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
-pub enum Reduction<C = ColumnId> {
-    /// Collapses input rows via `by` — `by`/`without` semantics are exactly
-    /// [`GroupKeys`]'s. May still collapse every row into one (an empty,
-    /// non-`without` `by`) — that's a genuine reduction with zero grouping
-    /// columns, not "no grouping concept."
-    Reduce(GroupKeys<C>),
-    /// No grouping concept at all: preserves one output row per input
-    /// entity (e.g. a per-series windowed computation with no `by(...)`
-    /// clause to begin with, because there's no aggregation operator here
-    /// for such a clause to attach to). Never merges across entities, and
-    /// never collapses an entity's own row structure (e.g. a time axis) —
-    /// unlike `Reduce(GroupKeys::without(vec![]))` ("group by every
-    /// label"), which is still a genuine reduction and does collapse it.
-    PerEntity,
-}
-
-impl<C> Reduction<C> {
-    /// Shorthand for the common case — group by these (possibly empty)
-    /// keys, kept rather than excluded.
-    pub fn by(keys: Vec<C>) -> Self {
-        Self::Reduce(GroupKeys::by(keys))
-    }
-
-    /// The grouping keys, if this is a genuine reduction — `None` for
-    /// `PerEntity`, which has no grouping-keys concept to report.
-    pub fn group_keys(&self) -> Option<&GroupKeys<C>> {
-        match self {
-            Self::Reduce(by) => Some(by),
-            Self::PerEntity => None,
-        }
-    }
-
-    /// The grouping keys, panicking if this is `PerEntity` — for call sites
-    /// (tests, mostly) that already know, from the shape they built or are
-    /// asserting on, that this must be a genuine reduction. Prefer
-    /// [`group_keys`](Self::group_keys) wherever the caller can't assume that.
-    pub fn expect_reduce(&self) -> &GroupKeys<C> {
-        match self {
-            Self::Reduce(by) => by,
-            Self::PerEntity => panic!("expected Reduction::Reduce, got PerEntity"),
-        }
-    }
-}
-
-/// A caller-proven compound unique key for a [`QueryExpr::Concat`] (issue
-/// #228) — built only via [`QueryExpr::concat_with_discriminator`] /
-/// [`ConcatDiscriminatorKey::new`], never by naming `discriminator` directly
-/// in a struct literal (both fields are private): from *other Rust code*,
-/// the only way to end up with one of these is to hand over a specific
-/// column as the discriminator, by name, at the call site.
-///
-/// Caveat: this is a Rust-API-level guarantee, not a data-level one. The
-/// derived `Deserialize` impl below builds a `ConcatDiscriminatorKey`
-/// directly from field values, bypassing `new()`. Deserialization is therefore
-/// equivalent to a caller supplying the assertion directly; it does not prove
-/// either fact below. An external boundary accepting `QueryExpr` data must
-/// reject this field or validate both obligations before treating it as
-/// uniqueness evidence.
-///
-/// # Soundness
-///
-/// `Concat`'s default (see its own doc) is to drop `unique_keys`
-/// unconditionally, because a key unique **within** one branch is not unique
-/// **across** the concatenation unless the branches' value sets for that key
-/// are provably disjoint — nothing about matching schemas or matching
-/// per-branch keys establishes that on its own. Two different branches can
-/// trivially emit the same `inner_key` value (e.g. two PromQL
-/// `histogram_quantiles` branches keyed on `(host, le)` can both produce a
-/// `(host, le)` pair for different φ).
-///
-/// Prepending `discriminator` restores a compound key only when two facts
-/// hold: `inner_key` uniquely identifies rows **within every branch**, and
-/// `discriminator`'s value is **guaranteed to differ between branches** — a
-/// literal the producer just tagged the branch with (PromQL φ riding along via
-/// [`QueryExpr::PromqlRelabel`], a Postgres-style synthetic `GROUPING()` id
-/// for `ROLLUP`/`CUBE`, …), never something inferred structurally from the
-/// branches' own data — then `discriminator` alone partitions rows into
-/// disjoint sets independent of what the branches actually contain, so
-/// `(discriminator, inner_key)` is sound even when otherwise-identical
-/// `inner_key` values occur in different branches. Neither fact is verified
-/// here; both are part of the caller-proven claim.
-///
-/// This is a **caller-proven claim, not something `Concat` can verify**:
-/// nothing stops a caller from asserting a discriminator that in fact
-/// repeats across branches, in which case the resulting `unique_keys` claim
-/// is simply wrong — `output_schema` trusts it without checking. The
-/// obligation is on the constructor call site, exactly as it is on
-/// [`QueryExpr::Dedup`]'s `cols` or any other unverified `unique_keys`
-/// producer in this module.
-#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
-#[serde(deny_unknown_fields)]
-#[serde(bound(serialize = "C: ColState", deserialize = "C: ColState"))]
-pub struct ConcatDiscriminatorKey<C: ColState = ColumnId> {
-    discriminator: C,
-    inner_key: Vec<C>,
-}
-
-impl<C: ColState> ConcatDiscriminatorKey<C> {
-    /// The only constructor — `discriminator` must be named explicitly by
-    /// the caller. See the type's doc for the soundness obligation this
-    /// puts on that caller.
-    pub fn new(discriminator: C, inner_key: Vec<C>) -> Self {
-        Self {
-            discriminator,
-            inner_key,
-        }
-    }
-
-    pub fn discriminator(&self) -> &C {
-        &self.discriminator
-    }
-
-    pub fn inner_key(&self) -> &[C] {
-        &self.inner_key
-    }
-}
-
-#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
-#[serde(bound(serialize = "C: ColState", deserialize = "C: ColState"))]
-pub enum QueryExpr<C: ColState = ColumnId> {
-    /// Outermost leaf. `schema` is the **binding schema** — the resolved column
-    /// set every positional `ColumnId` in the DAG indexes into, *not* a full
-    /// description of the runtime row — once bound (`schema: Schema`, always
-    /// present: the [`SchemaResolver`](super::schema_resolver) is total). Before binding, a
-    /// front-end-emitted `Scan` (`C = ColumnRef`) knows it only when the front
-    /// end already has it without binding — a catalog-backed SQL leaf — `None`
-    /// (PromQL) defers to the SchemaResolver; see [`ColState::ScanSchema`]. Complete
-    /// when catalog-backed (SQL); for schemaless PromQL the bound schema is
-    /// usage-derived (the `(ts, value)` floor + the labels the query
-    /// references), since a metric's label set is open and known only at
-    /// runtime. That distinction is carried explicitly by
-    /// [`Schema::closed`](super::schema::Schema::closed) (SQL leaf → `true`,
-    /// PromQL leaf → `false`). `predicates` are leaf-level row filters (PromQL
-    /// label matchers, pushed-down `WHERE` conjuncts).
-    Scan {
-        source: Source,
-        #[serde(default)]
-        predicates: Vec<Predicate<C>>,
-        schema: C::ScanSchema,
-    },
-    /// A scalar sub-expression sitting in an **operator-DAG position** — a
-    /// [`BinaryOp`](Self::BinaryOp) operand for `<vector> op <scalar>`
-    /// thresholds / unit conversions (#35), a
-    /// [`PromqlVectorFromScalar`](Self::PromqlVectorFromScalar) child, or a
-    /// whole query's root (a bare PromQL scalar query, e.g. `5`).
-    ///
-    /// Formerly its own leaf variant, `PromqlScalar(f64)`. Issue #220: that
-    /// variant held exactly the same value [`Literal`](Self::Literal) does
-    /// (every PromQL scalar is `f64`), duplicating it for no reason but
-    /// *which DAG position* it was allowed to appear in. This wrapper
-    /// carries that position instead of the value — the inner node is an
-    /// ordinary scalar sub-language expression (in practice always
-    /// `Literal(ScalarValue::Float64(_))`, since a front end only ever
-    /// constructs this fully constant-folded — see
-    /// [`promql_scalar`](Self::promql_scalar)) — and is what `output_schema`,
-    /// `canonicalize`, and `resolve` now key off to tell "this operand has
-    /// its own row schema" from "this is a nested scalar leaf with none,"
-    /// in place of the old `PromqlScalar` vs. `Literal` variant tag.
-    PromqlScalarBridge(Rc<QueryExpr<C>>),
-
-    /// The query **evaluation timestamp** as Unix seconds, exposed by PromQL
-    /// `time()`. This is not inherently the current wall-clock time: its value
-    /// is the instant or range-step at which the expression is evaluated. It
-    /// is also the implicit input of no-argument calendar functions. Issue #46.
-    EvalTimestamp,
-
-    /// The SQL statement evaluation time (`NOW()` / `CURRENT_TIMESTAMP`) as
-    /// a SQL [`DataType::Timestamp`]. Kept distinct from [`EvalTimestamp`],
-    /// whose PromQL `time()` contract is Unix seconds as `Float64`.
-    CurrentTimestamp,
-
-    /// PromQL `vector(s)` — the scalar→instant-vector bridge. Promotes a
-    /// scalar-typed child to a single label-less series carrying the scalar's
-    /// value at every step. Lets a scalar participate where a vector is required
-    /// (`up or vector(0)` dead-man's-switch). Issue #48.
-    PromqlVectorFromScalar(Rc<QueryExpr<C>>),
-
-    /// PromQL `scalar(v)` — the instant-vector→scalar bridge. Collapses a
-    /// single-element vector to its value (NaN at runtime if the input is not
-    /// exactly one series). Lets a vector feed a scalar position (`vector` /
-    /// aggregation `k` args, thresholds). Issue #48.
-    PromqlScalarFromVector(Rc<QueryExpr<C>>),
-
-    /// ρ — a per-series **label rewrite** (PromQL `label_replace` /
-    /// `label_join`). Every input row passes through unchanged except for the
-    /// destination label `dst`, whose new value is computed by `value` — a
-    /// scalar expression over the child's (source) label columns:
-    /// `label_replace` → a `label_replace(src, regex, replacement)` function
-    /// call (regex capture-expansion), `label_join` → a `label_join(sep, srcs…)`
-    /// concatenation. Sample values and the time axis are untouched. Issue #50.
-    PromqlRelabel {
-        /// The label written by this rewrite (PromQL `dst_label`).
-        dst: String,
-        value: Rc<QueryExpr<C>>,
-        child: Rc<QueryExpr<C>>,
-    },
-
-    /// PromQL `info(v, [selector])` — left-join **label enrichment** (#84). Each
-    /// series in `child` is enriched with labels from the matching info metric(s)
-    /// (`target_info` by default; `selector`'s `__name__` matchers pick the
-    /// metric(s), the rest constrain the data labels), joined on their shared
-    /// identifying labels. Those join keys are the info metric's identifying
-    /// labels — runtime/metadata-resolved, since an open PromQL schema can't
-    /// enumerate them — so they are NOT carried here; the post-ASAP realization pass
-    /// resolves them from the info metric's schema. The output keeps
-    /// `child`'s (open) schema: the
-    /// grafted labels appear at runtime.
-    PromqlInfoEnrich {
-        #[serde(default)]
-        selector: Vec<InfoMatcher>,
-        child: Rc<QueryExpr<C>>,
-    },
-
-    /// Series-sampling **selection** — PromQL `limitk` / `limit_ratio` (#86).
-    /// Keeps a subset of whole series per `by` group (empty = global), passing
-    /// each surviving series through unchanged. Not a ranking (`TopK`) and not a
-    /// reduction: the output schema equals the child's.
-    PromqlSeriesSample {
-        #[serde(default)]
-        by: GroupKeys<C>,
-        kind: SampleKind,
-        child: Rc<QueryExpr<C>>,
-    },
-
-    /// σ — row-level filter. Output schema = child schema.
-    Filter {
-        pred: Predicate<C>,
-        child: Rc<QueryExpr<C>>,
-    },
-    /// π — column projection.
-    Project {
-        cols: Vec<ProjectItem<C>>,
-        /// Re-qualifies every output column with this table alias (a derived
-        /// table / inline view). `None` for an ordinary SELECT list.
-        #[serde(default)]
-        qualifier: Option<String>,
-        child: Rc<QueryExpr<C>>,
-    },
-
-    /// γ + α — GROUP BY (positional) + aggregate intents.
-    Aggregate {
-        reduction: Reduction<C>,
-        measures: Vec<AggIntent<C>>,
-        /// Output column names parallel to `measures`. A non-empty entry overrides
-        /// the synthetic intent-keyed name — SQL threads DataFusion's generated
-        /// name (e.g. `"sum(metrics.bytes)"`) here so an enclosing `Project`
-        /// resolves the aggregate output by the name it references. An empty
-        /// entry (or empty vec) falls back to `AggIntent::output_column`'s name
-        /// (PromQL's convention).
-        #[serde(default)]
-        output_names: Vec<String>,
-        /// Per-measure row predicates, parallel to `measures` — SQL
-        /// `FILTER (WHERE …)` semantics (issue #466): only rows where
-        /// `filters[i]` is `TRUE` update `measures[i]`; groups are still
-        /// formed from every row. Positional against `child`'s output
-        /// schema, like `Filter.pred` — not against this node's output like
-        /// `having`. `None` (or an entry past the end of a shorter vec) is
-        /// an unfiltered measure, so an empty vec is the pre-#466 shape.
-        #[serde(default)]
-        filters: Vec<Option<Predicate<C>>>,
-        #[serde(default)]
-        having: Option<Predicate<C>>,
-        child: Rc<QueryExpr<C>>,
-    },
-
-    /// δ — SQL `DISTINCT` / row deduplication. Positional like every other
-    /// column reference here; empty = dedup on all columns (`SELECT DISTINCT *`).
-    Dedup {
-        cols: Vec<C>,
-        child: Rc<QueryExpr<C>>,
-    },
-    /// ⊕ — exact, n-ary `UNION ALL` of independent branches. Rows are
-    /// concatenated, never deduplicated; SQL's `UNION`/`INTERSECT`/`EXCEPT` are
-    /// [`QueryExpr::SetOp`], not this.
-    ///
-    /// Used for the branches of one query that a single `Aggregate` cannot
-    /// express — PromQL `histogram_quantiles` (one branch per φ, issue #109) and
-    /// SQL `ROLLUP`/`CUBE`/`GROUPING SETS` (one branch per grouping level, issue
-    /// #118) — as well as for sharded / fan-in plans.
-    ///
-    /// **The branches must be union-compatible; nothing here enforces it.** The
-    /// output schema is the *first* child's, so branches that disagree on a
-    /// column name or type leave the merged schema silently misdescribing every
-    /// branch but one. A producer that cannot guarantee compatibility must
-    /// project the branches into a common shape first.
-    ///
-    /// A row may appear in several branches, so no branch's unique key survives
-    /// the union — `unique_keys` is dropped, as in `SetOp`. **Unless** the
-    /// constructor asserted `discriminator_unique_key` (issue #228,
-    /// [`QueryExpr::concat_with_discriminator`]): a caller-proven claim that
-    /// one column's value is guaranteed distinct per branch, which makes
-    /// `(discriminator, inner_key)` a sound compound unique key regardless of
-    /// whether `inner_key` alone repeats across branches. `None` — every
-    /// ordinary construction path, including the plain struct literal and
-    /// [`QueryExpr::concat`] — reproduces the old, unconditional-drop
-    /// behavior exactly; see [`ConcatDiscriminatorKey`]'s doc for the
-    /// soundness argument and the obligation this puts on whoever asserts it.
-    ///
-    /// Empty children is an error ([`QueryExprError::EmptyConcat`]), not an
-    /// empty relation: there would be no schema to derive.
-    Concat {
-        children: Vec<QueryExpr<C>>,
-        /// See the field-level doc above and [`ConcatDiscriminatorKey`].
-        #[serde(default)]
-        discriminator_unique_key: Option<ConcatDiscriminatorKey<C>>,
-    },
-
-    /// Logical join. Post-ASAP binding picks the physical alternative.
-    Join {
-        kind: JoinKind,
-        pred: Predicate<C>,
-        left: Rc<QueryExpr<C>>,
-        right: Rc<QueryExpr<C>>,
-    },
-    SetOp {
-        kind: RelationalSetOpKind,
-        all: bool,
-        left: Rc<QueryExpr<C>>,
-        right: Rc<QueryExpr<C>>,
-    },
-
-    /// Generic order-by for non-heavy-hitter cases.
-    ///
-    /// `partition_by` makes the ordering **per-group**: a non-empty set means
-    /// "rank within each `partition_by` group" — the semantics behind PromQL
-    /// `topk by (host) (…)` / SQL `… OVER (PARTITION BY host ORDER BY …)`. It is
-    /// row-preserving (schema pass-through) and is where the grouping of a
-    /// generic (non-heavy-hitter) ranking lives, so there is no separate
-    /// `Partition` node (issue #12: reducing GROUP BY → `Aggregate.by`, per-group
-    /// ranking → here, parallel sharding → a deployment's own physical
-    /// stage). Empty = a global order-by.
-    Sort {
-        keys: Vec<SortKey<C>>,
-        #[serde(default)]
-        partition_by: GroupKeys<C>,
-        child: Rc<QueryExpr<C>>,
-    },
-    Limit {
-        n: usize,
-        offset: usize,
-        child: Rc<QueryExpr<C>>,
-    },
-
-    /// PromQL sub-query (`<expr>[range:resolution]`). Logical pass-through.
-    PromqlSubquery {
-        range: Duration,
-        #[serde(default)]
-        resolution: Option<Duration>,
-        child: Rc<QueryExpr<C>>,
-    },
-
-    /// Temporal range selection — "look back `range` of history for this
-    /// computation." Used for all range-vector functions: `rate`, `increase`,
-    /// `*_over_time`. The range is distinct from a row-level `Filter`.
-    ///
-    /// Structural marker: an `Aggregate` whose direct child is a `TimeRange`
-    /// is a *per-series* reduction (label-preserving); one whose child is a
-    /// plain `Scan` or another `Aggregate` is a *cross-series* reduction.
-    TimeRange {
-        range: Duration,
-        child: Rc<QueryExpr<C>>,
-    },
-
-    /// PromQL `offset` / `@` **time shift** on a selector (issue #40). A
-    /// pass-through wrapper: it moves *when* `child` is evaluated (the runtime
-    /// resolves the `@` anchor and applies the offset) but leaves its schema
-    /// unchanged. Wraps the shifted selector directly — `m offset 1h` →
-    /// `TimeShift { Scan }`; a ranged selector `m[5m] offset 1h` →
-    /// `TimeRange { 5m, TimeShift { Scan } }` (the range is taken at the shifted
-    /// time). A shifted subquery wraps the `PromqlSubquery`, moving its step
-    /// grid. Never carries the identity shift (the converter emits a bare
-    /// selector when neither modifier is present).
-    TimeShift {
-        shift: TimeShift,
-        child: Rc<QueryExpr<C>>,
-    },
-
-    /// SQL analytic window function: `func(args) OVER (PARTITION BY … ORDER BY …
-    /// ROWS/RANGE BETWEEN …)`. Output schema = child schema + one column named
-    /// `output_name` (the name the enclosing `Project` references).
-    SQLWindowFunc {
-        func: WindowFuncKind,
-        /// Operand expressions (`LAG(value)` → `[Column(value_id)]`); empty for
-        /// the rank-only functions (`ROW_NUMBER`/`RANK`/`DENSE_RANK`).
-        args: Vec<QueryExpr<C>>,
-        partition_by: GroupKeys<C>,
-        order_by: Vec<SortKey<C>>,
-        /// `None` is accepted only for backward compatibility with serialized
-        /// pre-#268 IR, where the engine's implicit frame was not retained.
-        /// Newly lowered SQL always carries `Some` with DataFusion's resolved
-        /// concrete default or explicit frame.
-        #[serde(default)]
-        frame: Option<WindowFrame>,
-        /// The output column's name — DataFusion's window-expr field name, so a
-        /// `Project` above resolves it (cf. `Aggregate.output_names`).
-        output_name: String,
-        child: Rc<QueryExpr<C>>,
-    },
-
-    /// Arithmetic / comparison / boolean composition (PromQL binary ops).
-    BinaryOp {
-        op: BinaryOpKind,
-        lhs: Rc<QueryExpr<C>>,
-        rhs: Rc<QueryExpr<C>>,
-        #[serde(default)]
-        vector_match: Option<VectorMatch>,
-    },
-
-    // ── Scalar expression shapes (issue #205) ───────────────────────────
-    //
-    // Formerly a separate, self-recursive `Expr<C>` DAG, reachable from the
-    // operator variants above only through wrapper fields (`Predicate`,
-    // `ProjectItem`, `SortKey`). They're variants of this same DAG now — a
-    // scalar sub-expression is only ever reachable through one of those same
-    // wrapper positions (`Filter.pred`, `ProjectItem.expr`, `Aggregate.having`,
-    // `PromqlRelabel.value`, `SQLWindowFunc.args`, …), which is a *convention* this
-    // type no longer enforces at compile time the way the old, closed
-    // `Expr<C>` variant set did — nothing stops constructing, say, a `Scan`
-    // where a `Compare`'s `left` operand belongs. `output_schema` and every
-    // scalar-position consumer (`resolve`, `canonicalize`, `infer_expr_type`)
-    // reject a non-scalar variant found there instead (a `QueryExprError` or
-    // an `unreachable!`, depending on the call site) — the accepted
-    // replacement, since the alternative (a marker-trait/sub-enum bound
-    // restricting which variants are constructible in a scalar position) adds
-    // real type-level machinery for a distinction every constructor already
-    // has to get right structurally anyway (a `Filter` is never built with an
-    // operator sub-DAG as its `pred`).
-    /// A column reference — unresolved [`ColumnRef`] (front-end-emitted, `C =
-    /// ColumnRef`) or positional [`ColumnId`] (once bound, `C = ColumnId`).
-    Column(C),
-    /// A constant literal value.
-    Literal(ScalarValue),
-    /// `left op right` — binary comparison.
-    Compare {
-        left: Rc<QueryExpr<C>>,
-        op: CompareOpKind,
-        right: Rc<QueryExpr<C>>,
-    },
-    /// Flat conjunction (logical AND). An empty list is vacuously true.
-    BoolAnd(Vec<QueryExpr<C>>),
-    /// Flat disjunction (logical OR). An empty list is vacuously false.
-    BoolOr(Vec<QueryExpr<C>>),
-    /// Logical NOT.
-    Not(Rc<QueryExpr<C>>),
-    /// `expr IS NULL`.
-    IsNull(Rc<QueryExpr<C>>),
-    /// `expr IS NOT NULL`.
-    IsNotNull(Rc<QueryExpr<C>>),
-    /// `CAST(expr AS to)`; `try_cast` for SQL `TRY_CAST` (NULL on failure).
-    Cast {
-        expr: Rc<QueryExpr<C>>,
-        to: DataType,
-        try_cast: bool,
-    },
-    /// `expr [NOT] IN (v1, v2, …)`.
-    InList {
-        expr: Rc<QueryExpr<C>>,
-        list: Vec<QueryExpr<C>>,
-        negated: bool,
-    },
-    /// Scalar function call, e.g. `LOWER(col)`, `ABS(x)`.
-    FunctionCall {
-        name: String,
-        args: Vec<QueryExpr<C>>,
-    },
-    /// Binary arithmetic: `left op right`.
-    Arithmetic {
-        op: ArithmeticOpKind,
-        left: Rc<QueryExpr<C>>,
-        right: Rc<QueryExpr<C>>,
-    },
-    /// SQL `CASE` (both searched and simple forms). `operand` present for the
-    /// simple form (`CASE expr WHEN …`), absent for searched.
-    Case {
-        operand: Option<Rc<QueryExpr<C>>>,
-        branches: Vec<(QueryExpr<C>, QueryExpr<C>)>,
-        else_expr: Option<Rc<QueryExpr<C>>>,
-    },
-}
-
-impl<C: ColState> QueryExpr<C> {
-    /// Construct the [`PromqlScalarBridge`](Self::PromqlScalarBridge) leaf
-    /// for a bare PromQL numeric literal / folded constant scalar (issue
-    /// #220) — `Literal(ScalarValue::Float64(v))` at an operator-DAG
-    /// position. The one constructor every front end / test that used to
-    /// write `QueryExpr::PromqlScalar(v)` should use instead.
-    pub fn promql_scalar(v: f64) -> Self {
-        QueryExpr::PromqlScalarBridge(Rc::new(QueryExpr::Literal(ScalarValue::Float64(v))))
-    }
-
-    /// Build an ordinary [`Concat`](Self::Concat) — the ordinary/default
-    /// construction path every call site should prefer over the bare struct
-    /// literal: `output_schema` drops `unique_keys` unconditionally, exactly
-    /// as before issue #228. Use
-    /// [`concat_with_discriminator`](Self::concat_with_discriminator) instead
-    /// when the caller can prove branch disjointness via a discriminator
-    /// column.
-    pub fn concat(children: Vec<QueryExpr<C>>) -> Self {
-        QueryExpr::Concat {
-            children,
-            discriminator_unique_key: None,
-        }
-    }
-
-    /// Build a [`Concat`](Self::Concat) whose output schema carries the
-    /// caller-proven compound unique key `(discriminator, inner_key)` (issue
-    /// #228). See [`ConcatDiscriminatorKey`]'s doc for the soundness
-    /// argument and the obligation this puts on the caller —
-    /// `output_schema` trusts this claim without verifying it: nothing here
-    /// checks that `inner_key` is unique within every branch or that
-    /// `discriminator`'s value is distinct between branches.
-    pub fn concat_with_discriminator(
-        children: Vec<QueryExpr<C>>,
-        discriminator: C,
-        inner_key: Vec<C>,
-    ) -> Self {
-        QueryExpr::Concat {
-            children,
-            discriminator_unique_key: Some(ConcatDiscriminatorKey::new(discriminator, inner_key)),
-        }
-    }
-
-    /// The value of a [`PromqlScalarBridge`](Self::PromqlScalarBridge) leaf
-    /// wrapping a plain `Literal(ScalarValue::Float64(_))` — every one a
-    /// front end constructs today (see [`promql_scalar`](Self::promql_scalar)).
-    /// `None` for any other shape, including a `PromqlScalarBridge` wrapping
-    /// something else (not constructed today, but not precluded by the type).
-    pub fn as_promql_scalar(&self) -> Option<f64> {
-        match self {
-            QueryExpr::PromqlScalarBridge(inner) => match inner.as_ref() {
-                QueryExpr::Literal(ScalarValue::Float64(v)) => Some(*v),
-                _ => None,
-            },
-            _ => None,
-        }
-    }
-
-    /// If this expression is a `BoolAnd`, return its elements; otherwise a
-    /// single-element slice containing `self`.
-    pub fn conjuncts(&self) -> &[QueryExpr<C>] {
-        match self {
-            QueryExpr::BoolAnd(v) => v.as_slice(),
-            _ => std::slice::from_ref(self),
-        }
-    }
-
-    /// If this expression is a `BoolOr`, return its elements; otherwise a
-    /// single-element slice containing `self`.
-    pub fn disjuncts(&self) -> &[QueryExpr<C>] {
-        match self {
-            QueryExpr::BoolOr(v) => v.as_slice(),
-            _ => std::slice::from_ref(self),
-        }
-    }
-
-    /// Recursively collect every column reference in a **scalar** sub-DAG —
-    /// used by the [`SchemaResolver`](super::schema_resolver::SchemaResolver) to seed usage-derived
-    /// leaf schemas, and available to post-ASAP binding for column-lineage /
-    /// selectivity.
-    /// `self` must be one of the scalar variants (see the module doc on
-    /// [`QueryExpr`]'s scalar shapes) — every caller already only reaches
-    /// this through a scalar-typed position (`Predicate`, `ProjectItem.expr`,
-    /// …), so an operator variant here indicates a construction bug, not a
-    /// shape this needs to handle silently.
-    pub fn columns_referenced(&self) -> Vec<&C> {
-        match self {
-            QueryExpr::Column(c) => vec![c],
-            QueryExpr::Literal(_) => vec![],
-            QueryExpr::EvalTimestamp => vec![],
-            QueryExpr::CurrentTimestamp => vec![],
-            QueryExpr::Compare { left, right, .. } | QueryExpr::Arithmetic { left, right, .. } => {
-                let mut v = left.columns_referenced();
-                v.extend(right.columns_referenced());
-                v
-            }
-            QueryExpr::BoolAnd(parts) | QueryExpr::BoolOr(parts) => {
-                parts.iter().flat_map(|e| e.columns_referenced()).collect()
-            }
-            QueryExpr::Not(e) | QueryExpr::IsNull(e) | QueryExpr::IsNotNull(e) => {
-                e.columns_referenced()
-            }
-            QueryExpr::Cast { expr, .. } => expr.columns_referenced(),
-            QueryExpr::InList { expr, list, .. } => {
-                let mut v = expr.columns_referenced();
-                v.extend(list.iter().flat_map(|e| e.columns_referenced()));
-                v
-            }
-            QueryExpr::FunctionCall { args, .. } => {
-                args.iter().flat_map(|e| e.columns_referenced()).collect()
-            }
-            QueryExpr::Case {
-                operand,
-                branches,
-                else_expr,
-            } => {
-                let mut v = vec![];
-                if let Some(op) = operand {
-                    v.extend(op.columns_referenced());
-                }
-                for (when, then) in branches {
-                    v.extend(when.columns_referenced());
-                    v.extend(then.columns_referenced());
-                }
-                if let Some(e) = else_expr {
-                    v.extend(e.columns_referenced());
-                }
-                v
-            }
-            other => unreachable!(
-                "columns_referenced called on a non-scalar QueryExpr variant: {other:?}"
-            ),
-        }
-    }
-}
-
-/// The canonical, positional, resolved DAG — what the bare `QueryExpr` name
-/// has always meant (the default `C = ColumnId`). Every existing consumer
-/// keeps using `QueryExpr` unparameterized; this alias exists only to name
-/// the resolved state explicitly at a use site that also wants to name
-/// [`UnresolvedQueryExpr`] nearby.
-pub type ResolvedQueryExpr = QueryExpr<ColumnId>;
-
-/// The front-end-emitted, name-based, unresolved DAG —
-/// `QueryExpr<ColumnRef>`: front ends construct this directly during their
-/// own `interpret` step (issue #179), and the [`SchemaResolver`](super::schema_resolver)
-/// resolves it into [`ResolvedQueryExpr`].
-pub type UnresolvedQueryExpr = QueryExpr<ColumnRef>;
-
-// `output_schema` needs a fully bound DAG — it reads `Scan.schema` as a plain
-// `Schema` and resolves every scalar `Expr::Column` positionally — so it lives
-// only on the resolved instantiation, not `impl<C: ColState> QueryExpr<C>`.
-// Same reasoning as `AggIntent`'s `output_column`/`requires`/`is_per_series`
-// (#205): a schema-shaped property that is only meaningful post-binding.
-impl QueryExpr<ColumnId> {
-    /// Infer a scalar expression against its input relation using the same
-    /// canonical rules as projection schema derivation.
-    pub fn scalar_type(&self, input: &Schema) -> Result<(DataType, bool), QueryExprError> {
-        infer_expr_type(self, input)
-    }
-
-    /// Output schema of the root of a canonical DAG.
-    pub fn output_schema(&self) -> Result<Schema, QueryExprError> {
-        match self {
-            QueryExpr::Scan { schema, .. } => Ok(schema.clone()),
-
-            QueryExpr::Aggregate {
-                reduction,
-                measures,
-                output_names,
-                child,
-                ..
-            } => {
-                let in_schema = child.output_schema()?;
-                aggregate_output_schema(&in_schema, reduction, measures, output_names)
-            }
-
-            QueryExpr::Filter { child, .. }
-            | QueryExpr::Sort { child, .. }
-            | QueryExpr::Limit { child, .. }
-            | QueryExpr::PromqlSubquery { child, .. }
-            // Series sampling keeps a subset of whole series unchanged, so the
-            // output schema (and row-uniqueness) is exactly the child's (#86).
-            | QueryExpr::PromqlSeriesSample { child, .. }
-            // Info enrichment adds runtime info labels — the statically-known
-            // schema is the child's (open), so it passes through (#84).
-            | QueryExpr::PromqlInfoEnrich { child, .. }
-            | QueryExpr::TimeRange { child, .. }
-            // A time shift (`offset`/`@`) moves *when* the child is evaluated,
-            // never its columns — schema passes through (#40).
-            | QueryExpr::TimeShift { child, .. } => child.output_schema(),
-
-            // ρ — relabel preserves every input column and writes one label
-            // `dst` (Utf8): overwritten in place if it already exists, else
-            // appended (nullable — a `label_replace` regex non-match leaves it
-            // unset). The schema stays open (other labels remain runtime-only).
-            // A rewrite can collapse two label sets into one, so row-uniqueness
-            // is no longer provable — drop unique_keys.
-            QueryExpr::PromqlRelabel { dst, child, .. } => {
-                let mut out = child.output_schema()?;
-                if let Some(existing) = out.fields.iter_mut().find(|c| c.name == *dst) {
-                    existing.dtype = FieldDataType::Plain(DataType::Utf8);
-                    existing.nullable = true;
-                } else {
-                    out.fields.push(Field::plain(dst.clone(), DataType::Utf8, true));
-                }
-                out.unique_keys.clear();
-                Ok(out)
-            }
-
-            // π — one output column per projection item. Each item's type is
-            // inferred from its expression against the child schema; the name
-            // is the explicit alias or a derived default. A child unique key
-            // survives exactly when every one of its columns is passed through
-            // as a bare `Field` item (possibly reordered or aliased). Derived
-            // expressions cannot carry key identity. `time_index` is re-found
-            // by name.
-            QueryExpr::Project { cols, qualifier, child } => {
-                let in_schema = child.output_schema()?;
-                let columns: Vec<Field> = cols
-                    .iter()
-                    .enumerate()
-                    .map(|(i, item)| {
-                        let (dtype, nullable) = infer_expr_type(&item.expr, &in_schema)?;
-                        let name = item
-                            .alias
-                            .clone()
-                            .unwrap_or_else(|| default_proj_name(&item.expr, i, &in_schema));
-                        let c = Field::plain(name, dtype, nullable);
-                        // A derived table re-qualifies its output columns with
-                        // its alias, so `t.col` (and a join over two derived
-                        // tables) resolves to the right relation.
-                        Ok(match qualifier {
-                            Some(q) => c.with_table(q),
-                            None => c,
-                        })
-                    })
-                    .collect::<Result<Vec<_>, QueryExprError>>()?;
-                let time_index = columns.iter().position(|c| c.name == "ts");
-                let unique_keys = in_schema
-                    .unique_keys
-                    .iter()
-                    .filter_map(|key| {
-                        key.iter()
-                            .map(|input_col| {
-                                cols.iter().position(|item| {
-                                    matches!(&item.expr, QueryExpr::Column(col) if col == input_col)
-                                })
-                            })
-                            .collect::<Option<Vec<_>>>()
-                    })
-                    .collect();
-                Ok(Schema {
-                    fields: columns,
-                    time_index,
-                    unique_keys,
-                    // Projection enumerates exactly its items → closed.
-                    closed: true,
-                })
-            }
-
-            QueryExpr::Dedup { cols, child } => {
-                let mut out = child.output_schema()?;
-                // Deduplicating on `cols` makes them a unique key of the result.
-                if !cols.is_empty() {
-                    out.add_unique_key(cols.clone());
-                }
-                Ok(out)
-            }
-
-            // ⊕ — the branches are union-compatible by construction, so the
-            // output shape is the first child's. A row can appear in more than
-            // one branch, so no key of one branch is a key of the union: drop
-            // unique_keys, exactly as `SetOp` does — unless the constructor
-            // asserted `discriminator_unique_key` (issue #228), in which case
-            // `(discriminator, inner_key)` becomes the sole unique key. That
-            // assertion is trusted verbatim here, never checked: see
-            // `ConcatDiscriminatorKey`'s doc for the soundness argument and
-            // whose obligation it is.
-            QueryExpr::Concat {
-                children,
-                discriminator_unique_key,
-            } => {
-                let mut s = children
-                    .first()
-                    .ok_or(QueryExprError::EmptyConcat)
-                    .and_then(|c| c.output_schema())?;
-                s.unique_keys.clear();
-                if let Some(key) = discriminator_unique_key {
-                    let mut compound = vec![*key.discriminator()];
-                    compound.extend(key.inner_key().iter().copied());
-                    s.add_unique_key(compound);
-                }
-                Ok(s)
-            }
-            // Set operations are union-compatible: both sides share the left's
-            // column shape, so the output schema is the left's. (Row identity
-            // is not preserved across a UNION, so unique_keys are dropped.)
-            QueryExpr::SetOp { left, .. } => {
-                let mut s = left.output_schema()?;
-                s.unique_keys.clear();
-                Ok(s)
-            }
-            // ⋈ — output is the concatenation of both inputs' columns. Outer
-            // joins make the non-preserved side nullable. Post-join row
-            // identity isn't provable in general, so unique_keys reset.
-            QueryExpr::Join {
-                kind, left, right, ..
-            } => {
-                let l = left.output_schema()?;
-                let r = right.output_schema()?;
-                // Semi / anti joins filter the left side; the right contributes
-                // no columns, so the output is the left's schema unchanged. Row
-                // identity *is* preserved (each left row appears at most once),
-                // but a left row can be dropped, so unique_keys still reset.
-                if matches!(kind, JoinKind::Semi | JoinKind::Anti) {
-                    return Ok(Schema {
-                        unique_keys: Vec::new(),
-                        ..l
-                    });
-                }
-                let (left_null, right_null) = match kind {
-                    JoinKind::Left => (false, true),
-                    JoinKind::Right => (true, false),
-                    JoinKind::Full => (true, true),
-                    JoinKind::Inner | JoinKind::Cross => (false, false),
-                    JoinKind::Semi | JoinKind::Anti => unreachable!("handled above"),
-                };
-                let l_len = l.fields.len();
-                let mut columns = Vec::with_capacity(l_len + r.fields.len());
-                columns.extend(l.fields.iter().cloned().map(|mut c| {
-                    c.nullable |= left_null;
-                    c
-                }));
-                columns.extend(r.fields.iter().cloned().map(|mut c| {
-                    c.nullable |= right_null;
-                    c
-                }));
-                let time_index = l.time_index.or(r.time_index.map(|i| i + l_len));
-                Ok(Schema {
-                    fields: columns,
-                    time_index,
-                    unique_keys: Vec::new(),
-                    // The concatenation is complete only if both sides are.
-                    closed: l.closed && r.closed,
-                })
-            }
-            // ψ-analytic — child schema + one appended window-output column.
-            QueryExpr::SQLWindowFunc {
-                func,
-                args,
-                output_name,
-                child,
-                ..
-            } => {
-                let mut out = child.output_schema()?;
-                // First operand's (dtype, nullable) from the child schema, owned
-                // so the borrow ends before we append.
-                let arg = args.first().and_then(|a| match a {
-                    QueryExpr::Column(id) => out.fields.get(*id),
-                    _ => None,
-                });
-                let arg_dtype = || {
-                    arg.and_then(|c| c.plain_dtype().cloned())
-                        .unwrap_or(DataType::Float64)
-                };
-                let (dtype, nullable) = match func {
-                    WindowFuncKind::RowNumber
-                    | WindowFuncKind::Rank
-                    | WindowFuncKind::DenseRank
-                    | WindowFuncKind::Count => (DataType::Int64, false),
-                    WindowFuncKind::Sum | WindowFuncKind::Avg => (DataType::Float64, true),
-                    // Navigation funcs: arg type, nullable (boundary rows are NULL).
-                    WindowFuncKind::Lag
-                    | WindowFuncKind::Lead
-                    | WindowFuncKind::LagInFrame
-                    | WindowFuncKind::LeadInFrame
-                    | WindowFuncKind::FirstValue
-                    | WindowFuncKind::LastValue
-                    | WindowFuncKind::NthValue(_) => (arg_dtype(), true),
-                    WindowFuncKind::Min | WindowFuncKind::Max => {
-                        (arg_dtype(), arg.is_none_or(|c| c.nullable))
-                    }
-                };
-                out.fields
-                    .push(Field::plain(output_name.clone(), dtype, nullable));
-                Ok(out)
-            }
-
-            // A scalar bridge has no series — model it as a single `value`
-            // column so it can sit as a `BinaryOp` operand. Both scalar
-            // leaves — a bridged scalar sub-expression and the eval time —
-            // are a single `value` column with no labels. Every
-            // `PromqlScalarBridge` constructed today wraps a plain
-            // `Literal(Float64)` (issue #220), so the schema doesn't need to
-            // inspect the inner node.
-            QueryExpr::PromqlScalarBridge(_) | QueryExpr::EvalTimestamp => Ok(Schema {
-                fields: vec![Field::plain("value", DataType::Float64, false)],
-                time_index: None,
-                unique_keys: Vec::new(),
-                closed: true,
-            }),
-
-            QueryExpr::CurrentTimestamp => Ok(Schema {
-                fields: vec![Field::plain("value", DataType::Timestamp, false)],
-                time_index: None,
-                unique_keys: Vec::new(),
-                closed: true,
-            }),
-
-            // `vector(s)` yields a label-less instant vector: the (ts, value)
-            // floor and nothing else. `closed` — its full label set (empty) is
-            // known statically (#48).
-            QueryExpr::PromqlVectorFromScalar(_) => Ok(Schema {
-                fields: vec![
-                    Field::plain("ts", DataType::Timestamp, false),
-                    Field::plain("value", DataType::Float64, false),
-                ],
-                time_index: Some(0),
-                unique_keys: Vec::new(),
-                closed: true,
-            }),
-
-            // `scalar(v)` collapses to a single `value`, no time index — the same
-            // scalar shape as a constant or `time()` (#48).
-            QueryExpr::PromqlScalarFromVector(_) => Ok(Schema {
-                fields: vec![Field::plain("value", DataType::Float64, false)],
-                time_index: None,
-                unique_keys: Vec::new(),
-                closed: true,
-            }),
-
-            // The output shape of `<vector> op <scalar>` (or `<scalar> op
-            // <vector>`) is the vector side's — a scalar operand (a constant or
-            // `time()`) contributes only its value, no labels. Prefer the
-            // non-scalar side.
-            QueryExpr::BinaryOp { lhs, rhs, op, vector_match } => {
-                fn scalar(expression: &QueryExpr) -> bool {
-                    match expression {
-                        QueryExpr::PromqlScalarBridge(_) | QueryExpr::EvalTimestamp | QueryExpr::PromqlScalarFromVector(_) => true,
-                        QueryExpr::BinaryOp { lhs, rhs, .. } => scalar(lhs) && scalar(rhs),
-                        _ => false,
-                    }
-                }
-                let left = lhs.output_schema()?;
-                let right = rhs.output_schema()?;
-                if scalar(lhs) { return Ok(right); }
-                let mut output = left;
-                let grouping = vector_match.as_ref().and_then(|m| m.grouping.as_ref());
-                let right_rows = matches!(op, BinaryOpKind::Set(PromQLVectorSetOpKind::Or))
-                    || matches!(grouping, Some(g) if g.side == GroupSide::Right);
-                let mut additions = Vec::new();
-                if right_rows {
-                    additions.extend(right.fields.iter().filter(|c| c.dtype == DataType::Utf8).cloned());
-                }
-                if let Some(grouping) = grouping {
-                    additions.extend(grouping.labels.iter().map(|name| Field::plain(name.clone(), DataType::Utf8, true)));
-                }
-                for column in additions {
-                    if !output.fields.iter().any(|c| c.name == column.name) {
-                        output.fields.push(column);
-                    }
-                }
-                Ok(output)
-            },
-
-            // The scalar variants (issue #205) — see `QueryExprError::ScalarHasNoRowSchema`.
-            QueryExpr::Column(_)
-            | QueryExpr::Literal(_)
-            | QueryExpr::Compare { .. }
-            | QueryExpr::BoolAnd(_)
-            | QueryExpr::BoolOr(_)
-            | QueryExpr::Not(_)
-            | QueryExpr::IsNull(_)
-            | QueryExpr::IsNotNull(_)
-            | QueryExpr::Cast { .. }
-            | QueryExpr::InList { .. }
-            | QueryExpr::FunctionCall { .. }
-            | QueryExpr::Arithmetic { .. }
-            | QueryExpr::Case { .. } => Err(QueryExprError::ScalarHasNoRowSchema),
-        }
-    }
-}
-
-/// Output schema of a *per-series* window/range reduction (`rate`/`increase`,
-/// or an `*_over_time` reducer under a time `Window`). Such a reduction emits
-/// one value per series, so every label column of `input` is preserved and only
-/// the sample value is replaced — kept named `value` so the PromQL sample-value
-/// convention (and any outer `SampleValue` reference) still resolves it by name.
-fn per_series_reduction_schema(input: &Schema, agg: &AggIntent) -> Result<Schema, QueryExprError> {
-    let vi = if let Some(index) = agg.input_cols().first() {
-        *index
-    } else {
-        super::column_resolution::resolve_column_ref(&ColumnRef::SampleValue, input)
-            .map_err(|error| QueryExprError::InvalidSampleColumn(error.to_string()))?
-    };
-    if !matches!(
-        input.fields.get(vi).map(|column| &column.dtype),
-        Some(FieldDataType::Plain(DataType::Float64 | DataType::Int64))
-    ) {
-        return Err(QueryExprError::InvalidSampleColumn(format!(
-            "column {vi} is not numeric"
-        )));
-    }
-    let mut columns = input.fields.clone();
-    {
-        let mut out = agg.output_column(&columns[vi]);
-        out.name = "value".into();
-        // A per-series range reduction produces a PromQL sample value, which is
-        // always `float64` — override the reducer's own output dtype so
-        // `count_over_time` (whose `Count` intent types `Int64`) matches every
-        // other range reducer instead of leaking an `Int64` value column (#69).
-        out.dtype = FieldDataType::Plain(DataType::Float64);
-        columns[vi] = out;
-    }
-    Ok(Schema {
-        fields: columns,
-        time_index: input.time_index,
-        unique_keys: input.unique_keys.clone(),
-        // Per-series reduction is label-preserving: it inherits its input's
-        // completeness (an open scan stays open; a closed one stays closed).
-        closed: input.closed,
-    })
-}
-
-/// The output schema of an `Aggregate { reduction, measures }` over `in_schema` —
-/// the **single** canonical derivation shared by
-/// [`QueryExpr::output_schema`]'s `Aggregate` arm and the converter's
-/// HAVING-resolution path (`column_resolution::output_schema_for_aggregate`),
-/// so the two can never drift (issue #41).
-///
-/// `Reduction::PerEntity` selects the label-preserving
-/// [`per_series_reduction_schema`] (`rate`/`increase`/`*_over_time`) instead
-/// of the cross-series `by ++ measures` shape. Which one applies is read directly
-/// off `reduction` — decided once, at construction, by whoever built the
-/// `Aggregate` node (issue #165) — not re-derived here from `by`/child shape.
-pub fn aggregate_output_schema(
-    in_schema: &Schema,
-    reduction: &Reduction,
-    measures: &[AggIntent],
-    output_names: &[String],
-) -> Result<Schema, QueryExprError> {
-    let by = match reduction {
-        Reduction::PerEntity => {
-            debug_assert_eq!(
-                measures.len(),
-                1,
-                "a per-entity reduction is single-aggregate"
-            );
-            return per_series_reduction_schema(in_schema, &measures[0]);
-        }
-        Reduction::Reduce(by) => by,
-    };
-
-    // `without(excluded)` groups by every label *except* those listed: the kept
-    // labels are the input's label columns minus the excluded positions (and the
-    // ts / sample-value columns), and the schema stays **open** because the full
-    // runtime label set isn't known. The `by(...)` path instead enumerates its
-    // kept columns and freezes to closed (issue #39).
-    if by.is_without() {
-        return without_output_schema(in_schema, by.keys(), measures, output_names);
-    }
-
-    let mut out_cols: Vec<Field> = Vec::with_capacity(by.len() + measures.len());
-    for &id in by.keys() {
-        let c = in_schema
-            .fields
-            .get(id)
-            .ok_or(QueryExprError::InvalidGroupByColumn(
-                id,
-                in_schema.fields.len(),
-            ))?;
-        out_cols.push(c.clone());
-    }
-    let value_col_idx =
-        super::column_resolution::resolve_column_ref(&ColumnRef::SampleValue, in_schema)
-            .ok()
-            .or_else(|| (0..in_schema.fields.len()).find(|i| !by.contains(i)));
-    let probe = value_col_idx
-        .and_then(|i| in_schema.fields.get(i))
-        .cloned()
-        .unwrap_or_else(|| Field::plain("value", DataType::Float64, false));
-    // Each reducer types off its own input column (`SUM(bytes)` vs `AVG(latency)`
-    // in one node); `None` falls back to the sample-value probe (PromQL's
-    // single-column convention). A non-empty `output_names[i]` overrides the
-    // synthetic output column name.
-    for (i, intent) in measures.iter().enumerate() {
-        // `count_values("l", v)` emits TWO columns: the synthesized `Utf8` label
-        // `l` (the stringified sample value it groups by) and the per-value
-        // count. If `l` collides with a group-by key of the same name, PromQL's
-        // synthesized label takes precedence — emit a single column, never a
-        // duplicate.
-        if let AggIntent::CountValues { label } = intent {
-            if !out_cols.iter().any(|c| c.name == *label) {
-                out_cols.push(Field::plain(label.clone(), DataType::Utf8, false));
-            }
-            let mut cnt = intent.output_column(&probe);
-            if let Some(name) = output_names.get(i).filter(|s| !s.is_empty()) {
-                cnt.name = name.clone();
-            }
-            out_cols.push(cnt);
-            continue;
-        }
-        // Only the output *type* is read from here, so the leading column is
-        // enough for the multi-column intents: `Cardinality` and `PearsonCorr`
-        // both have a fixed output type that ignores it.
-        let in_col = intent
-            .input_cols()
-            .first()
-            .and_then(|id| in_schema.fields.get(*id))
-            .unwrap_or(&probe);
-        let mut out = intent.output_column(in_col);
-        // A global extremum emits NULL for an empty input, even if its input
-        // column is non-nullable. Grouped extrema only emit existing groups.
-        if by.is_empty() && matches!(intent, AggIntent::Min { .. } | AggIntent::Max { .. }) {
-            out.nullable = true;
-        }
-        if let Some((arg, _)) = intent
-            .arg_selector_columns(in_schema)
-            .map_err(QueryExprError::InvalidScalarSignature)?
-        {
-            out.dtype = in_schema.fields[arg].dtype.clone();
-            out.nullable = in_schema.fields[arg].nullable;
-        }
-        if let Some(name) = output_names.get(i).filter(|s| !s.is_empty()) {
-            out.name = name.clone();
-        }
-        out_cols.push(out);
-    }
-    // `count_values` groups by (by-keys ∪ the synthesized value label), so the
-    // by-keys alone are not a unique key — be conservative and claim none.
-    let has_count_values = measures
-        .iter()
-        .any(|a| matches!(a, AggIntent::CountValues { .. }));
-    let unique_keys = if by.is_empty() || has_count_values {
-        Vec::new()
-    } else {
-        vec![(0..by.len()).collect()]
-    };
-    Ok(Schema {
-        fields: out_cols,
-        time_index: None,
-        unique_keys,
-        // A cross-series aggregate enumerates exactly `by ++ measures`, so its output
-        // is closed even over an open input — this is where an open schema
-        // freezes to closed.
-        closed: true,
-    })
-}
-
-/// Output schema of a `without(excluded)` aggregate: the kept labels (every
-/// input label column except the `excluded` positions, the time axis, and the
-/// sample-value column) followed by the aggregate output column(s). Unlike the
-/// `by` path this stays **open** — the excluded set is enumerable but the kept
-/// set is not (the runtime carries labels the usage-derived schema never saw),
-/// so the schema can't freeze to closed and claims no unique key (issue #39).
-fn without_output_schema(
-    in_schema: &Schema,
-    excluded: &[ColumnId],
-    measures: &[AggIntent],
-    output_names: &[String],
-) -> Result<Schema, QueryExprError> {
-    for &id in excluded {
-        if id >= in_schema.fields.len() {
-            return Err(QueryExprError::InvalidGroupByColumn(
-                id,
-                in_schema.fields.len(),
-            ));
-        }
-    }
-    // A nested aggregate renames the sample value (`sum by (le) (…)` → `sum`);
-    // it is still the value, not a kept label.
-    let value =
-        super::column_resolution::resolve_column_ref(&ColumnRef::SampleValue, in_schema).ok();
-    let mut out_cols: Vec<Field> = Vec::new();
-    for (i, col) in in_schema.fields.iter().enumerate() {
-        let is_time = in_schema.time_index == Some(i);
-        if !is_time && value != Some(i) && !excluded.contains(&i) {
-            out_cols.push(col.clone());
-        }
-    }
-    let probe = value
-        .and_then(|i| in_schema.fields.get(i))
-        .cloned()
-        .unwrap_or_else(|| Field::plain("value", DataType::Float64, false));
-    for (i, intent) in measures.iter().enumerate() {
-        // Only the output *type* is read from here, so the leading column is
-        // enough for the multi-column intents: `Cardinality` and `PearsonCorr`
-        // both have a fixed output type that ignores it.
-        let in_col = intent
-            .input_cols()
-            .first()
-            .and_then(|id| in_schema.fields.get(*id))
-            .unwrap_or(&probe);
-        let mut out = intent.output_column(in_col);
-        if let Some((arg, _)) = intent
-            .arg_selector_columns(in_schema)
-            .map_err(QueryExprError::InvalidScalarSignature)?
-        {
-            out.dtype = in_schema.fields[arg].dtype.clone();
-            out.nullable = in_schema.fields[arg].nullable;
-        }
-        if let Some(name) = output_names.get(i).filter(|s| !s.is_empty()) {
-            out.name = name.clone();
-        }
-        out_cols.push(out);
-    }
-    Ok(Schema {
-        fields: out_cols,
-        time_index: None,
-        unique_keys: Vec::new(),
-        // The kept label set is runtime-only, so — unlike `by` — this does not
-        // freeze the open schema to closed.
-        closed: false,
-    })
-}
-
-/// Infer the `(DataType, nullable)` a scalar [`QueryExpr`] produces against an
-/// input [`Schema`]. Used by `Project` schema derivation. Approximate here:
-/// unknown columns and bare `FunctionCall`s fall back to a permissive default
-/// (post-ASAP binding refines with a real function/type registry). `expr`
-/// must be one of the scalar variants (issue #205) — an operator variant here
-/// is a construction bug, not a shape this needs to handle silently.
-fn infer_expr_type(
-    expr: &QueryExpr<ColumnId>,
-    schema: &Schema,
-) -> Result<(DataType, bool), QueryExprError> {
-    Ok(match expr {
-        QueryExpr::CurrentTimestamp => (DataType::Timestamp, false),
-        QueryExpr::Column(id) => match schema.fields.get(*id) {
-            Some(c) => match c.plain_dtype() {
-                Some(dtype) => (dtype.clone(), c.nullable),
-                // Summary state is not a scalar value: it has to be read
-                // out (estimated / finalized) before an expression can use it.
-                None => {
-                    return Err(QueryExprError::InvalidScalarSignature(format!(
-                        "column `{}` carries summary state and cannot be read as a value",
-                        c.name
-                    )))
-                }
-            },
-            None => (DataType::Float64, true),
-        },
-        QueryExpr::Literal(s) => match s {
-            ScalarValue::Int64(_) => (DataType::Int64, false),
-            ScalarValue::Float64(_) => (DataType::Float64, false),
-            ScalarValue::Utf8(_) => (DataType::Utf8, false),
-            ScalarValue::Boolean(_) => (DataType::Bool, false),
-            ScalarValue::Null => (DataType::Null, true),
-            ScalarValue::Interval { .. } => (DataType::Interval, false),
-        },
-        // Boolean-valued expressions (SQL three-valued logic → nullable).
-        QueryExpr::Compare { .. }
-        | QueryExpr::BoolAnd(_)
-        | QueryExpr::BoolOr(_)
-        | QueryExpr::Not(_)
-        | QueryExpr::IsNull(_)
-        | QueryExpr::IsNotNull(_)
-        | QueryExpr::InList { .. } => (DataType::Bool, true),
-        QueryExpr::Arithmetic { op, left, right } => {
-            let (lt, ln) = infer_expr_type(left, schema)?;
-            let (rt, rn) = infer_expr_type(right, schema)?;
-            // Temporal subtraction yields a fixed duration with a unit, not a
-            // calendar interval or a floating-point number. Until the IR can
-            // preserve that unit, fail instead of publishing a numeric schema.
-            if matches!(op, ArithmeticOpKind::Sub)
-                && matches!(lt, DataType::Date | DataType::Timestamp)
-                && matches!(rt, DataType::Date | DataType::Timestamp)
-            {
-                return Err(QueryExprError::InvalidScalarSignature(
-                    "temporal subtraction produces an unsupported duration type".into(),
-                ));
-            }
-
-            // Operand order is not checked: the orders that are not valid SQL
-            // (`Interval - Timestamp`) are rejected by the planner upstream, so
-            // a pair rule stays as small as the numeric one it sits beside.
-            let dtype = match (&lt, &rt) {
-                // SQL unary minus lowers to -1 * expression, including intervals.
-                (DataType::Int64, DataType::Interval) | (DataType::Interval, DataType::Int64)
-                    if matches!(op, ArithmeticOpKind::Mul) =>
-                {
-                    DataType::Interval
-                }
-                (DataType::Timestamp, DataType::Interval)
-                | (DataType::Interval, DataType::Timestamp) => DataType::Timestamp,
-                (DataType::Date, DataType::Interval) | (DataType::Interval, DataType::Date) => {
-                    DataType::Date
-                }
-                (DataType::Interval, DataType::Interval) => DataType::Interval,
-                (DataType::Int64, DataType::Int64) => DataType::Int64,
-                _ => DataType::Float64,
-            };
-            (dtype, ln || rn)
-        }
-        QueryExpr::Cast { to, try_cast, expr } => {
-            let (_, nullable) = infer_expr_type(expr, schema)?;
-            (to.clone(), *try_cast || nullable)
-        }
-        QueryExpr::FunctionCall { name, args } => {
-            if name == "asap_element_access" {
-                super::scalar_type_rules::element_access_type(args, schema)
-                    .map_err(QueryExprError::InvalidScalarSignature)?
-            } else if name == "asap_struct_field" {
-                super::scalar_type_rules::struct_field_type(args, schema)
-                    .map_err(QueryExprError::InvalidScalarSignature)?
-            } else if let Some(function) =
-                super::scalar_type_rules::MapScalarFunction::from_name(name)
-            {
-                let arguments = args
-                    .iter()
-                    .map(|arg| infer_expr_type(arg, schema))
-                    .collect::<Result<Vec<_>, _>>()?;
-                function
-                    .output_type(&arguments)
-                    .map_err(QueryExprError::InvalidScalarSignature)?
-            } else {
-                // Legacy unknown functions retain their existing policy.
-                (DataType::Float64, true)
-            }
-        }
-        QueryExpr::Case {
-            branches,
-            else_expr,
-            ..
-        } => {
-            if let Some((_, then)) = branches.first() {
-                (infer_expr_type(then, schema)?.0, true)
-            } else if let Some(other) = else_expr {
-                infer_expr_type(other, schema)?
-            } else {
-                (DataType::Null, true)
-            }
-        }
-        other => {
-            unreachable!("infer_expr_type called on a non-scalar QueryExpr variant: {other:?}")
-        }
-    })
-}
-
-/// Default output-column name for a projection item with no explicit alias:
-/// a bare column keeps its (schema) name; anything else gets `col_{i}`.
-fn default_proj_name(expr: &QueryExpr<ColumnId>, idx: usize, schema: &Schema) -> String {
-    match expr {
-        QueryExpr::Column(id) => schema
-            .fields
-            .get(*id)
-            .map(|c| c.name.clone())
-            .unwrap_or_else(|| format!("col_{idx}")),
-        _ => format!("col_{idx}"),
-    }
-}
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-    use crate::pre_asap::expr_ir::{ArithmeticOpKind, CompareOpKind};
-    use crate::types::AccuracyTarget;
-
-    fn col(name: &str, dtype: DataType, nullable: bool) -> Field {
-        Field::plain(name, dtype, nullable)
-    }
-
-    /// Shifting an instant by a duration stays an instant, and shifting a date
-    /// stays a date — neither falls through to the numeric default, which is
-    /// what `l_shipdate + INTERVAL '30' DAY` would otherwise be typed as.
-    #[test]
-    fn interval_arithmetic_keeps_the_temporal_type() {
-        let schema = Schema::new(vec![
-            col("ts", DataType::Timestamp, false),
-            col("d", DataType::Date, false),
-        ]);
-        let thirty_days = || {
-            Rc::new(QueryExpr::Literal(ScalarValue::Interval {
-                months: 0,
-                days: 30,
-                nanos: 0,
-            }))
-        };
-        let shift = |column, op| QueryExpr::Arithmetic {
-            op,
-            left: Rc::new(QueryExpr::Column(column)),
-            right: thirty_days(),
-        };
-
-        assert_eq!(
-            shift(0, ArithmeticOpKind::Add)
-                .scalar_type(&schema)
-                .unwrap()
-                .0,
-            DataType::Timestamp
-        );
-        assert_eq!(
-            shift(1, ArithmeticOpKind::Sub)
-                .scalar_type(&schema)
-                .unwrap()
-                .0,
-            DataType::Date
-        );
-        assert_eq!(
-            QueryExpr::Arithmetic {
-                op: ArithmeticOpKind::Add,
-                left: thirty_days(),
-                right: thirty_days(),
-            }
-            .scalar_type(&schema)
-            .unwrap()
-            .0,
-            DataType::Interval
-        );
-    }
-
-    fn scan(
-        columns: Vec<Field>,
-        time_index: Option<ColumnId>,
-        uk: Vec<Vec<ColumnId>>,
-    ) -> QueryExpr {
-        QueryExpr::Scan {
-            source: Source::Table {
-                table_ref: "t".into(),
-            },
-            predicates: vec![],
-            schema: Schema {
-                fields: columns,
-                time_index,
-                unique_keys: uk,
-                closed: true,
-            },
-        }
-    }
-
-    #[test]
-    fn project_preserves_unique_keys_that_are_passed_through() {
-        let input = Rc::new(scan(
-            vec![
-                col("tenant", DataType::Utf8, false),
-                col("region", DataType::Utf8, false),
-                col("value", DataType::Int64, false),
-            ],
-            None,
-            vec![vec![0, 1]],
-        ));
-        let projected = QueryExpr::Project {
-            cols: vec![
-                ProjectItem {
-                    alias: Some("r".into()),
-                    expr: QueryExpr::Column(1),
-                },
-                ProjectItem {
-                    alias: Some("t".into()),
-                    expr: QueryExpr::Column(0),
-                },
-                ProjectItem {
-                    alias: None,
-                    expr: QueryExpr::Arithmetic {
-                        op: ArithmeticOpKind::Add,
-                        left: Rc::new(QueryExpr::Column(2)),
-                        right: Rc::new(QueryExpr::Literal(ScalarValue::Int64(1))),
-                    },
-                },
-            ],
-            qualifier: None,
-            child: input,
-        };
-
-        assert_eq!(
-            projected.output_schema().unwrap().unique_keys,
-            vec![vec![1, 0]]
-        );
-    }
-
-    #[test]
-    fn project_drops_a_unique_key_when_a_key_column_is_omitted() {
-        let input = Rc::new(scan(
-            vec![
-                col("tenant", DataType::Utf8, false),
-                col("region", DataType::Utf8, false),
-            ],
-            None,
-            vec![vec![0, 1]],
-        ));
-        let projected = QueryExpr::Project {
-            cols: vec![ProjectItem {
-                alias: None,
-                expr: QueryExpr::Column(0),
-            }],
-            qualifier: None,
-            child: input,
-        };
-
-        assert!(projected.output_schema().unwrap().unique_keys.is_empty());
-    }
-
-    #[test]
-    fn legacy_window_json_without_frame_deserializes_as_unspecified() {
-        let window = QueryExpr::SQLWindowFunc {
-            func: WindowFuncKind::RowNumber,
-            args: vec![],
-            partition_by: GroupKeys::by(vec![]),
-            order_by: vec![],
-            frame: Some(WindowFrame {
-                units: WindowFrameUnits::Range,
-                start_bound: WindowFrameBound::Preceding(WindowFrameOffset::Scalar(
-                    ScalarValue::Null,
-                )),
-                end_bound: WindowFrameBound::CurrentRow,
-            }),
-            output_name: "row_number".into(),
-            child: Rc::new(scan(vec![col("v", DataType::Int64, false)], None, vec![])),
-        };
-        let mut json = serde_json::to_value(window).unwrap();
-        json.get_mut("SQLWindowFunc")
-            .and_then(serde_json::Value::as_object_mut)
-            .unwrap()
-            .remove("frame");
-
-        let decoded: QueryExpr = serde_json::from_value(json).unwrap();
-        assert!(matches!(
-            decoded,
-            QueryExpr::SQLWindowFunc { frame: None, .. }
-        ));
-    }
-
-    /// A row can appear in more than one branch, so no branch's unique key is a
-    /// key of the union. `Concat` took the first child's schema verbatim, which
-    /// let a `Dedup`'s key leak out and claim a uniqueness the merged rows do
-    /// not have — `unique_keys` feeds CSE's producer-sharing legality check.
-    #[test]
-    fn merge_drops_the_branches_unique_keys() {
-        let branch = || QueryExpr::Dedup {
-            cols: vec![0],
-            child: Rc::new(scan(
-                vec![
-                    col("k", DataType::Utf8, false),
-                    col("v", DataType::Int64, false),
-                ],
-                None,
-                vec![],
-            )),
-        };
-        assert_eq!(
-            branch().output_schema().unwrap().unique_keys,
-            vec![vec![0]],
-            "a Dedup branch does have a unique key on its own"
-        );
-
-        let merged = QueryExpr::concat(vec![branch(), branch()]);
-        let schema = merged.output_schema().unwrap();
-        assert!(
-            schema.unique_keys.is_empty(),
-            "the union of two deduplicated branches is not deduplicated"
-        );
-        // The column shape is still the first branch's.
-        assert_eq!(schema.fields.len(), 2);
-    }
-
-    /// Same rule as `SetOp`, which already dropped them.
-    #[test]
-    fn merge_and_setop_agree_on_unique_keys() {
-        let branch = || QueryExpr::Dedup {
-            cols: vec![0],
-            child: Rc::new(scan(vec![col("k", DataType::Utf8, false)], None, vec![])),
-        };
-        let merged = QueryExpr::concat(vec![branch(), branch()]);
-        let setop = QueryExpr::SetOp {
-            kind: RelationalSetOpKind::Union,
-            all: true,
-            left: Rc::new(branch()),
-            right: Rc::new(branch()),
-        };
-        assert_eq!(
-            merged.output_schema().unwrap().unique_keys,
-            setop.output_schema().unwrap().unique_keys,
-        );
-    }
-
-    #[test]
-    fn an_empty_merge_has_no_schema() {
-        assert!(matches!(
-            QueryExpr::concat(vec![]).output_schema(),
-            Err(QueryExprError::EmptyConcat)
-        ));
-    }
-
-    /// Issue #228: a `Concat` built via `concat_with_discriminator` gets a
-    /// sound compound `(discriminator, inner_key)` unique key, even though
-    /// each branch's own `inner_key` alone repeats across branches (exactly
-    /// the shape `merge_drops_the_branches_unique_keys` shows is unsafe
-    /// *without* a discriminator).
-    #[test]
-    fn discriminator_override_produces_a_compound_unique_key() {
-        // Two branches, each individually deduplicated on column 0 (`k`) —
-        // but, per `merge_drops_the_branches_unique_keys`, that alone proves
-        // nothing about the union. Field 1 (`branch_id`) stands in for a
-        // discriminator the constructor has separately proven distinct per
-        // branch (PromQL φ, a synthetic `GROUPING()` id, ...) — this
-        // schema-level test only checks the shape `output_schema` derives
-        // from asserting one, not how a real caller proves distinctness.
-        let branch = || QueryExpr::Dedup {
-            cols: vec![0],
-            child: Rc::new(scan(
-                vec![
-                    col("k", DataType::Utf8, false),
-                    col("branch_id", DataType::Int64, false),
-                ],
-                None,
-                vec![],
-            )),
-        };
-        let merged = QueryExpr::concat_with_discriminator(
-            vec![branch(), branch()],
-            /* discriminator */ 1,
-            /* inner_key */ vec![0],
-        );
-        let schema = merged.output_schema().unwrap();
-        assert_eq!(
-            schema.unique_keys,
-            vec![vec![1, 0]],
-            "(discriminator, inner_key) is the sole asserted unique key"
-        );
-        assert_eq!(
-            schema.fields.len(),
-            2,
-            "column shape is still the first branch's"
-        );
-    }
-
-    #[test]
-    fn discriminator_assertion_rejects_unknown_wire_fields() {
-        let json = r#"{"discriminator":1,"inner_key":[0],"unverified":true}"#;
-        assert!(serde_json::from_str::<ConcatDiscriminatorKey>(json).is_err());
-    }
-
-    /// The override is opt-in: building a `Concat` without asserting a
-    /// discriminator — via the plain struct literal, exactly like every call
-    /// site before issue #228 — still drops `unique_keys` by default,
-    /// unchanged.
-    #[test]
-    fn ordinary_concat_struct_literal_still_drops_unique_keys_by_default() {
-        let branch = || QueryExpr::Dedup {
-            cols: vec![0],
-            child: Rc::new(scan(vec![col("k", DataType::Utf8, false)], None, vec![])),
-        };
-        let merged = QueryExpr::Concat {
-            children: vec![branch(), branch()],
-            discriminator_unique_key: None,
-        };
-        assert!(merged.output_schema().unwrap().unique_keys.is_empty());
-    }
-
-    /// Misuse check (issue #228): there is no way to end up with a
-    /// discriminator-backed unique key without a call site literally naming
-    /// a column as the discriminator. Neither the ordinary `concat`
-    /// constructor nor a bare struct literal with `discriminator_unique_key:
-    /// None` can be coaxed into fabricating one — the only path that
-    /// produces `Some` is `concat_with_discriminator` /
-    /// `ConcatDiscriminatorKey::new`, both of which require `discriminator`
-    /// as an explicit, named argument.
-    #[test]
-    fn no_way_to_fabricate_a_unique_key_without_naming_a_discriminator() {
-        let branch = || QueryExpr::Dedup {
-            cols: vec![0],
-            child: Rc::new(scan(vec![col("k", DataType::Utf8, false)], None, vec![])),
-        };
-        // The ordinary builder.
-        assert_eq!(
-            QueryExpr::concat(vec![branch(), branch()])
-                .output_schema()
-                .unwrap()
-                .unique_keys,
-            Vec::<Vec<usize>>::new()
-        );
-        // The bare struct literal, explicitly opting out.
-        assert_eq!(
-            QueryExpr::Concat {
-                children: vec![branch(), branch()],
-                discriminator_unique_key: None,
-            }
-            .output_schema()
-            .unwrap()
-            .unique_keys,
-            Vec::<Vec<usize>>::new()
-        );
-    }
-
-    #[test]
-    fn project_retypes_and_renames_per_item() {
-        let child = scan(
-            vec![
-                col("ts", DataType::Timestamp, false),
-                col("host", DataType::Utf8, false),
-                col("value", DataType::Float64, false),
-            ],
-            Some(0),
-            vec![vec![0, 1]],
-        );
-        let q = QueryExpr::Project {
-            qualifier: None,
-            cols: vec![
-                // bare column passthrough keeps its (schema) name + type: host=col 1
-                ProjectItem {
-                    alias: None,
-                    expr: QueryExpr::Column(1),
-                },
-                // arithmetic over value (col 2) → Float64
-                ProjectItem {
-                    alias: Some("dbl".into()),
-                    expr: QueryExpr::Arithmetic {
-                        op: ArithmeticOpKind::Add,
-                        left: Rc::new(QueryExpr::Column(2)),
-                        right: Rc::new(QueryExpr::Column(2)),
-                    },
-                },
-                // comparison → Bool (nullable under 3-valued logic)
-                ProjectItem {
-                    alias: Some("flag".into()),
-                    expr: QueryExpr::Compare {
-                        left: Rc::new(QueryExpr::Column(2)),
-                        op: CompareOpKind::Gt,
-                        right: Rc::new(QueryExpr::Literal(ScalarValue::Float64(0.0))),
-                    },
-                },
-            ],
-            child: Rc::new(child),
-        };
-        let s = q.output_schema().unwrap();
-        assert_eq!(s.fields.len(), 3);
-        assert_eq!(s.fields[0], col("host", DataType::Utf8, false));
-        assert_eq!(s.fields[1], col("dbl", DataType::Float64, false));
-        assert_eq!(s.fields[2], col("flag", DataType::Bool, true));
-        // projection drops the time axis + unique keys (ts not retained)
-        assert!(s.time_index.is_none());
-        assert!(s.unique_keys.is_empty());
-    }
-
-    #[test]
-    fn group_keys_by_vs_without_semantics() {
-        let by = GroupKeys::by(vec![1, 2]);
-        let without = GroupKeys::without(vec![1, 2]);
-        assert!(!by.is_without());
-        assert!(without.is_without());
-        // Deref / iteration expose the stored keys regardless of mode.
-        assert_eq!(by.len(), 2);
-        assert_eq!(without.keys(), &[1, 2]);
-        // A `by` compares equal to its bare vec; a `without` never does.
-        assert_eq!(by, vec![1, 2]);
-        assert_ne!(without, vec![1, 2]);
-        assert_ne!(by, without);
-    }
-
-    #[test]
-    fn group_keys_serde_by_is_bare_array_without_is_tagged() {
-        // `by` keeps the pre-#39 bare-array wire format; `without` uses an object.
-        let by = serde_json::to_string(&GroupKeys::by(vec![2, 3])).unwrap();
-        assert_eq!(by, "[2,3]");
-        let without = serde_json::to_string(&GroupKeys::without(vec![2])).unwrap();
-        assert_eq!(without, r#"{"without":[2]}"#);
-        // Round-trip both.
-        for g in [GroupKeys::by(vec![2, 3]), GroupKeys::without(vec![2])] {
-            let json = serde_json::to_string(&g).unwrap();
-            let back: GroupKeys = serde_json::from_str(&json).unwrap();
-            assert_eq!(back, g);
-        }
-    }
-
-    #[test]
-    fn without_aggregate_keeps_open_schema_minus_excluded() {
-        // `sum without (instance) (m)` over `[ts, value, instance, job]`: the
-        // kept labels are the input labels minus the excluded `instance` (and ts
-        // / value), followed by the `sum` column, and the schema stays OPEN
-        // (issue #39). `job` survives; `instance` is dropped.
-        let scan_node = QueryExpr::Scan {
-            source: Source::TimeSeries { metric: "m".into() },
-            predicates: vec![],
-            schema: Schema::with_time_index(
-                vec![
-                    col("ts", DataType::Timestamp, false),
-                    col("value", DataType::Float64, false),
-                    col("instance", DataType::Utf8, true),
-                    col("job", DataType::Utf8, true),
-                ],
-                0,
-                vec![],
-            ),
-        };
-        let agg = QueryExpr::Aggregate {
-            reduction: Reduction::Reduce(GroupKeys::without(vec![2])), // exclude `instance`
-            measures: vec![AggIntent::Sum { col: None }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(scan_node),
-        };
-        let s = agg.output_schema().unwrap();
-        let names: Vec<_> = s.fields.iter().map(|c| c.name.as_str()).collect();
-        assert_eq!(names, vec!["job", "sum"], "kept `job`, dropped `instance`");
-        assert!(!s.closed, "a `without` result stays open");
-        assert!(s.time_index.is_none());
-        assert!(s.unique_keys.is_empty(), "kept set unknown → no unique key");
-    }
-
-    // A nested aggregate's renamed sample value is not a kept label.
-    #[test]
-    fn without_aggregate_drops_a_renamed_sample_value() {
-        // `sum without (inst) (sum by (inst, job) (m))` over `[inst, job, sum]`.
-        let inner = QueryExpr::Scan {
-            source: Source::TimeSeries { metric: "m".into() },
-            predicates: vec![],
-            schema: Schema::new(vec![
-                col("inst", DataType::Utf8, true),
-                col("job", DataType::Utf8, true),
-                col("sum", DataType::Float64, false),
-            ]),
-        };
-        let agg = QueryExpr::Aggregate {
-            reduction: Reduction::Reduce(GroupKeys::without(vec![0])),
-            measures: vec![AggIntent::Sum { col: None }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(inner),
-        };
-        let s = agg.output_schema().unwrap();
-        let names: Vec<_> = s.fields.iter().map(|c| c.name.as_str()).collect();
-        assert_eq!(names, vec!["job", "sum"]);
-    }
-
-    #[test]
-    fn time_shift_is_schema_pass_through() {
-        // `offset`/`@` move *when* a selector is evaluated, never its columns —
-        // a `TimeShift` output schema equals its child's (issue #40).
-        let scan_node = scan(
-            vec![
-                col("ts", DataType::Timestamp, false),
-                col("value", DataType::Float64, false),
-                col("job", DataType::Utf8, true),
-            ],
-            Some(0),
-            vec![],
-        );
-        let shifted = QueryExpr::TimeShift {
-            shift: TimeShift {
-                offset_ms: 3_600_000,
-                at: Some(AtModifier::Timestamp(1_609_746_000_000)),
-            },
-            child: Rc::new(scan_node.clone()),
-        };
-        assert_eq!(
-            shifted.output_schema().unwrap(),
-            scan_node.output_schema().unwrap(),
-        );
-    }
-
-    #[test]
-    fn time_shift_identity_and_serde() {
-        let offset_only = TimeShift {
-            offset_ms: 1,
-            at: None,
-        };
-        let at_only = TimeShift {
-            offset_ms: 0,
-            at: Some(AtModifier::End),
-        };
-        assert!(TimeShift::default().is_identity());
-        assert!(!offset_only.is_identity());
-        assert!(!at_only.is_identity());
-        // Round-trip the shift + anchor.
-        let s = TimeShift {
-            offset_ms: -300_000,
-            at: Some(AtModifier::Timestamp(60_000)),
-        };
-        let back: TimeShift = serde_json::from_str(&serde_json::to_string(&s).unwrap()).unwrap();
-        assert_eq!(back, s);
-    }
-
-    // Nested temporal aggregation must replace the sample, never the grouping label.
-    #[test]
-    fn temporal_reduction_of_grouped_sum_preserves_job() {
-        let input = Schema::new(vec![
-            col("job", DataType::Utf8, true),
-            col("sum", DataType::Float64, false),
-        ]);
-        for aggregate in [
-            AggIntent::Avg { col: None },
-            AggIntent::Avg { col: Some(1) },
-            AggIntent::Rate,
-        ] {
-            let output =
-                aggregate_output_schema(&input, &Reduction::PerEntity, &[aggregate], &[]).unwrap();
-            assert_eq!(output.fields[0], input.fields[0]);
-            assert_eq!(output.fields[1].name, "value");
-            assert_eq!(output.fields[1].dtype, DataType::Float64);
-        }
-    }
-
-    #[test]
-    fn per_series_rate_preserves_labels() {
-        // A per-series range reduction (`rate`) is label-preserving: it produces
-        // one value per series, so every label survives and only the sample
-        // value is replaced (kept named `value`). The TimeRange child is the
-        // structural marker; the outer Aggregate carries the Rate intent.
-        let scan_node = scan(
-            vec![
-                col("ts", DataType::Timestamp, false),
-                col("value", DataType::Float64, false),
-                col("job", DataType::Utf8, true),
-            ],
-            Some(0),
-            vec![],
-        );
-        let rate = QueryExpr::Aggregate {
-            reduction: Reduction::PerEntity,
-            measures: vec![AggIntent::Rate],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(QueryExpr::TimeRange {
-                range: Duration::from_secs(300),
-                child: Rc::new(scan_node),
-            }),
-        };
-        let s = rate.output_schema().unwrap();
-        assert_eq!(
-            s.fields.iter().map(|c| c.name.as_str()).collect::<Vec<_>>(),
-            vec!["ts", "value", "job"],
-            "rate preserves all labels; only the sample value is replaced"
-        );
-        assert_eq!(s.time_index, Some(0));
-        assert!(s.column_id("job").is_some(), "label survives the reduction");
-    }
-
-    #[test]
-    fn over_time_reduction_preserves_labels() {
-        // `*_over_time` lowers to `Aggregate { by:[], [reducer], TimeRange { Scan } }`:
-        // a per-series time-range reduction. The TimeRange child confers per-series
-        // semantics on otherwise cross-series intents like `Avg`, so an outer
-        // `sum by(job)(avg_over_time(...))` resolves its key positionally.
-        let scan_node = scan(
-            vec![
-                col("ts", DataType::Timestamp, false),
-                col("value", DataType::Float64, false),
-                col("job", DataType::Utf8, true),
-            ],
-            Some(0),
-            vec![],
-        );
-        let avg_over_time = QueryExpr::Aggregate {
-            reduction: Reduction::PerEntity,
-            measures: vec![AggIntent::Avg { col: None }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(QueryExpr::TimeRange {
-                range: Duration::from_secs(300),
-                child: Rc::new(scan_node),
-            }),
-        };
-        let s = avg_over_time.output_schema().unwrap();
-        assert_eq!(
-            s.fields.iter().map(|c| c.name.as_str()).collect::<Vec<_>>(),
-            vec!["ts", "value", "job"],
-            "TimeRange-child marks per-series: labels preserved, value renamed"
-        );
-        assert!(
-            s.column_id("job").is_some(),
-            "outer Aggregate.by can resolve it"
-        );
-    }
-
-    #[test]
-    fn completeness_open_leaf_freezes_to_closed_at_cross_series_aggregate() {
-        // A schemaless (PromQL-style) leaf is *open*; it stays open through a
-        // per-series reduction (`rate`), then is **frozen to closed** by a
-        // cross-series aggregate (which enumerates exactly its output columns).
-        let open_leaf = QueryExpr::Scan {
-            source: Source::TimeSeries { metric: "m".into() },
-            predicates: vec![],
-            // `with_time_index` defaults to `closed: false` (open).
-            schema: Schema::with_time_index(
-                vec![
-                    col("ts", DataType::Timestamp, false),
-                    col("value", DataType::Float64, false),
-                    col("job", DataType::Utf8, true),
-                ],
-                0,
-                vec![],
-            ),
-        };
-        assert!(
-            !open_leaf.output_schema().unwrap().closed,
-            "schemaless leaf is open"
-        );
-
-        let rate = QueryExpr::Aggregate {
-            reduction: Reduction::PerEntity,
-            measures: vec![AggIntent::Rate],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(open_leaf),
-        };
-        assert!(
-            !rate.output_schema().unwrap().closed,
-            "per-series rate is label-preserving → stays open"
-        );
-
-        let sum_by_job = QueryExpr::Aggregate {
-            reduction: Reduction::by(vec![2]), // `job`
-            measures: vec![AggIntent::Sum { col: None }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(rate),
-        };
-        assert!(
-            sum_by_job.output_schema().unwrap().closed,
-            "cross-series aggregate enumerates `by ++ measures` → frozen to closed"
-        );
-    }
-
-    #[test]
-    fn project_keeps_time_index_when_ts_passed_through() {
-        let child = scan(
-            vec![
-                col("ts", DataType::Timestamp, false),
-                col("value", DataType::Float64, false),
-            ],
-            Some(0),
-            vec![],
-        );
-        let q = QueryExpr::Project {
-            qualifier: None,
-            cols: vec![
-                // value=col 1, ts=col 0
-                ProjectItem {
-                    alias: None,
-                    expr: QueryExpr::Column(1),
-                },
-                ProjectItem {
-                    alias: None,
-                    expr: QueryExpr::Column(0),
-                },
-            ],
-            child: Rc::new(child),
-        };
-        let s = q.output_schema().unwrap();
-        assert_eq!(s.fields[0].name, "value");
-        assert_eq!(s.fields[1].name, "ts");
-        assert_eq!(s.time_index, Some(1));
-    }
-
-    fn join(kind: JoinKind) -> QueryExpr {
-        let left = scan(vec![col("a", DataType::Int64, false)], None, vec![vec![0]]);
-        let right = scan(vec![col("b", DataType::Utf8, false)], None, vec![]);
-        QueryExpr::Join {
-            kind,
-            pred: Predicate(Rc::new(QueryExpr::Literal(ScalarValue::Boolean(true)))),
-            left: Rc::new(left),
-            right: Rc::new(right),
-        }
-    }
-
-    #[test]
-    fn inner_join_concatenates_both_sides() {
-        let s = join(JoinKind::Inner).output_schema().unwrap();
-        assert_eq!(s.fields.len(), 2);
-        assert_eq!(s.fields[0], col("a", DataType::Int64, false));
-        assert_eq!(s.fields[1], col("b", DataType::Utf8, false));
-        // post-join row identity not provable → no unique keys
-        assert!(s.unique_keys.is_empty());
-    }
-
-    #[test]
-    fn left_join_makes_right_side_nullable() {
-        let s = join(JoinKind::Left).output_schema().unwrap();
-        assert!(!s.fields[0].nullable, "preserved left side stays non-null");
-        assert!(s.fields[1].nullable, "right side nullable under LEFT JOIN");
-    }
-
-    #[test]
-    fn full_join_makes_both_sides_nullable() {
-        let s = join(JoinKind::Full).output_schema().unwrap();
-        assert!(s.fields[0].nullable);
-        assert!(s.fields[1].nullable);
-    }
-
-    #[test]
-    fn setop_takes_left_shape_and_drops_unique_keys() {
-        let left = scan(
-            vec![
-                col("k", DataType::Utf8, false),
-                col("v", DataType::Int64, false),
-            ],
-            None,
-            vec![vec![0]],
-        );
-        let right = scan(
-            vec![
-                col("k", DataType::Utf8, false),
-                col("v", DataType::Int64, false),
-            ],
-            None,
-            vec![vec![0]],
-        );
-        let q = QueryExpr::SetOp {
-            kind: RelationalSetOpKind::Union,
-            all: false,
-            left: Rc::new(left),
-            right: Rc::new(right),
-        };
-        let s = q.output_schema().unwrap();
-        assert_eq!(s.fields.len(), 2);
-        assert_eq!(s.fields[0].name, "k");
-        assert!(
-            s.unique_keys.is_empty(),
-            "UNION does not preserve row identity"
-        );
-    }
-
-    // ── PromqlScalarBridge / Literal dedup (issue #220) ─────────────────────
-
-    /// `QueryExpr::promql_scalar(v)` — what every front end now constructs in
-    /// place of the old `PromqlScalar(v)` leaf — wraps exactly
-    /// `Literal(ScalarValue::Float64(v))`: the same value a SQL-emitted typed
-    /// float literal in a scalar-sub-language position would carry, just at a
-    /// different DAG position. `as_promql_scalar` is the round-trip inverse.
-    #[test]
-    fn promql_scalar_bridges_a_literal_float_at_an_operator_position() {
-        let bridge = QueryExpr::<ColumnId>::promql_scalar(2.5);
-        assert_eq!(
-            bridge,
-            QueryExpr::PromqlScalarBridge(Rc::new(QueryExpr::Literal(ScalarValue::Float64(2.5))))
-        );
-        assert_eq!(bridge.as_promql_scalar(), Some(2.5));
-
-        // The same value a SQL `Compare`/`Arithmetic` operand would carry, in
-        // its native (unwrapped, no row schema) scalar-sub-language position —
-        // no longer a different variant, just not bridged to this DAG
-        // position.
-        let sql_literal = QueryExpr::<ColumnId>::Literal(ScalarValue::Float64(2.5));
-        assert_eq!(bridge.as_promql_scalar(), Some(2.5));
-        assert_ne!(
-            bridge, sql_literal,
-            "bridge and bare literal are distinct nodes"
-        );
-        // Not every shape is a scalar bridge: neither a bare `Literal` nor an
-        // operator node reports a value.
-        assert_eq!(sql_literal.as_promql_scalar(), None);
-        assert_eq!(scan(vec![], None, vec![]).as_promql_scalar(), None);
-    }
-
-    /// Pins the DAG-position distinction issue #220 asks for: the very same
-    /// `Literal(ScalarValue::Float64(_))` value has a row schema when it sits
-    /// at the operator-DAG position (wrapped in `PromqlScalarBridge` — a
-    /// `BinaryOp` operand, `PromqlVectorFromScalar` child, or a query root),
-    /// and has none when it sits bare, in a scalar-sub-language position
-    /// (`Compare`/`Arithmetic`/… operand) — no longer decided by which of two
-    /// duplicate variants was used, only by whether the wrapper is present.
-    #[test]
-    fn row_schema_rides_on_the_bridge_wrapper_not_the_literal_variant() {
-        let bridged = QueryExpr::<ColumnId>::promql_scalar(42.0);
-        let schema = bridged.output_schema().expect("bridge has a row schema");
-        assert_eq!(schema.fields.len(), 1);
-        assert_eq!(schema.fields[0].name, "value");
-        assert_eq!(schema.fields[0].dtype, DataType::Float64);
-        assert!(schema.time_index.is_none());
-
-        // The identical value, unwrapped (the scalar-sub-language position a
-        // `Compare`/`Arithmetic` operand would occupy) has no row schema of
-        // its own — it's a construction bug to call `output_schema` on it
-        // directly, caught as `ScalarHasNoRowSchema` rather than panicking.
-        let bare = QueryExpr::<ColumnId>::Literal(ScalarValue::Float64(42.0));
-        assert!(matches!(
-            bare.output_schema(),
-            Err(QueryExprError::ScalarHasNoRowSchema)
-        ));
-    }
-
-    /// `BinaryOp`'s schema derivation follows the non-scalar (vector) side
-    /// when the other operand is a `PromqlScalarBridge`, and a `VectorMatch`
-    /// modifier survives unchanged alongside it — the relational binary-op
-    /// path (issue #220's Instance 2, left as follow-up) is untouched by the
-    /// Instance-1 `PromqlScalar` → `PromqlScalarBridge` collapse.
-    // `filters` (#466) round-trips, and an `Aggregate` serialized before the
-    // field existed still deserializes as unfiltered.
-    #[test]
-    fn aggregate_filters_serde_round_trip_and_default() {
-        let child = Rc::new(scan(
-            vec![
-                col("service", DataType::Utf8, false),
-                col("latency", DataType::Float64, false),
-            ],
-            None,
-            vec![],
-        ));
-        let filtered = QueryExpr::Aggregate {
-            reduction: Reduction::by(vec![0]),
-            measures: vec![
-                AggIntent::Count {
-                    accuracy: AccuracyTarget::Exact,
-                },
-                AggIntent::Sum { col: Some(1) },
-            ],
-            output_names: vec![],
-            filters: vec![
-                Some(Predicate(Rc::new(QueryExpr::Compare {
-                    left: Rc::new(QueryExpr::Column(1)),
-                    op: CompareOpKind::Gt,
-                    right: Rc::new(QueryExpr::Literal(ScalarValue::Float64(1.0))),
-                }))),
-                None,
-            ],
-            having: None,
-            child: Rc::clone(&child),
-        };
-        let json = serde_json::to_value(&filtered).unwrap();
-        assert_eq!(
-            serde_json::from_value::<QueryExpr>(json.clone()).unwrap(),
-            filtered
-        );
-
-        let mut legacy = json;
-        legacy["Aggregate"]
-            .as_object_mut()
-            .unwrap()
-            .remove("filters")
-            .expect("fixture sanity: filters was serialized");
-        let decoded: QueryExpr = serde_json::from_value(legacy).unwrap();
-        let QueryExpr::Aggregate { filters, .. } = &decoded else {
-            unreachable!()
-        };
-        assert!(filters.is_empty());
-    }
-
-    #[test]
-    fn binary_op_schema_follows_the_vector_side_over_a_scalar_bridge_with_vector_match_intact() {
-        let vector = scan(
-            vec![
-                col("host", DataType::Utf8, false),
-                col("value", DataType::Float64, false),
-            ],
-            None,
-            vec![],
-        );
-        let vm = VectorMatch {
-            kind: VectorMatchKind::On,
-            labels: vec!["host".into()],
-            grouping: None,
-        };
-        let op = QueryExpr::BinaryOp {
-            op: BinaryOpKind::Compare(CompareOpKind::Gt),
-            lhs: Rc::new(vector.clone()),
-            rhs: Rc::new(QueryExpr::promql_scalar(1.0)),
-            vector_match: Some(vm.clone()),
-        };
-        assert_eq!(op.output_schema().unwrap(), vector.output_schema().unwrap());
-        let QueryExpr::BinaryOp { vector_match, .. } = &op else {
-            unreachable!()
-        };
-        assert_eq!(vector_match.as_ref(), Some(&vm));
-    }
-}
diff --git a/crates/types/src/pre_asap/resolve.rs b/crates/types/src/pre_asap/resolve.rs
deleted file mode 100644
index b4a5c87a6..000000000
--- a/crates/types/src/pre_asap/resolve.rs
+++ /dev/null
@@ -1,857 +0,0 @@
-//! Resolve a front-end-emitted, unresolved [`UnresolvedQueryExpr`] (`QueryExpr<ColumnRef>`)
-//! into the canonical, positional [`ResolvedQueryExpr`] (`QueryExpr<ColumnId>`).
-//!
-//! Both front ends (`asap-frontend-promql`, `asap-frontend-sql`) construct
-//! canonical `QueryExpr` shapes directly during their own `interpret` step
-//! (issue #179) — heavy-hitter `topk` recognition, the window-over-aggregate
-//! fold, the `PerEntity`/`Reduce` reduction choice, and every other
-//! *structural* decision happen right there, since a front end already knows
-//! the answer at parse time. What's left for [`resolve_root`] is exactly the
-//! "mechanical, schema-dependent substitution" #179 describes: a single
-//! generic, shape-preserving walk — every [`UnresolvedQueryExpr`] variant maps to the
-//! identical [`ResolvedQueryExpr`] variant — that resolves every [`ColumnRef`] to
-//! the [`SchemaResolver`](super::schema_resolver::SchemaResolver)-computed positional [`ColumnId`].
-//!
-//! ## Why positional `ColumnId`, not just carrying names all the way through (issue #216)
-//!
-//! A mature query engine can legitimately choose either design — DataFusion's
-//! own logical plan (what `asap-frontend-sql` walks to build its `QueryExpr`)
-//! and Calcite both keep names, with an optional table qualifier, all the way
-//! through logical optimization, only going positional once they lower to a
-//! physical plan. Resolving once, immediately after each front end's own
-//! `interpret` step, is the better trade for *this* codebase's shape — one
-//! front-end-facing DAG feeding several independent downstream passes
-//! (`canonicalize`, the cost model, `dag_export`, schema/type inference,
-//! `asap-aware-mapping`'s summary binding) — for three concrete reasons:
-//!
-//! 1. **Names collide across joins.** Not hypothetical: `join_predicate_disambiguates_shared_column_name`
-//!    (`crates/frontend-sql/tests/sql_lowering.rs`) exists specifically because
-//!    `metrics.service` and `hosts.service` are both just `"service"` once their
-//!    schemas are concatenated. A bare name is ambiguous the moment two sources
-//!    share one; `ColumnId` is what makes "the second `service`, position 4, not
-//!    the first" a fact recorded once, instead of a lookup redone at every use site.
-//! 2. **A name's meaning changes going up the DAG.** `Project` renames/aliases,
-//!    `Aggregate` collapses columns and introduces synthetic ones, `Join`
-//!    concatenates two schemas — a name valid at a `Scan` leaf isn't
-//!    automatically the right binding three nodes up; it has to be reinterpreted
-//!    against whatever schema is in scope at that node. Resolving bottom-up
-//!    pins each reference to "this exact column of this exact node's
-//!    already-derived output schema," so nothing downstream re-derives that scope.
-//! 3. **It concentrates scoping logic in one place instead of ~6.** Every
-//!    downstream pass just compares/indexes `ColumnId`s — O(1), unambiguous. If
-//!    they worked on names instead, each would need its own qualifier-aware,
-//!    join-collision-aware name resolver, or risk silently binding to the wrong
-//!    `"service"`.
-//!
-//! Removing this resolution step and carrying `ColumnRef` everywhere would
-//! therefore be a real regression for this repo's shape, not just a rename —
-//! every one of those downstream passes would have to reimplement the scoping
-//! this module already centralizes.
-
-use std::rc::Rc;
-
-use thiserror::Error;
-
-use super::agg_intent::AggIntent;
-use super::column_resolution::{
-    resolve_column_ref, resolve_column_refs, resolve_expr, resolve_group_keys_promql, ResolveError,
-};
-use super::expr_ir::ColumnRef;
-use super::query_expr::{
-    aggregate_output_schema, any_measure_filtered, ConcatDiscriminatorKey, GroupKeys, Predicate,
-    ProjectItem, QueryExprError, Reduction, ResolvedQueryExpr, SortKey, UnresolvedQueryExpr,
-};
-use super::schema::{ColumnId, Schema};
-use super::schema_resolver::SchemaResolver;
-
-/// Errors from resolving a canonical, unresolved [`UnresolvedQueryExpr`] DAG.
-#[derive(Debug, Error)]
-pub enum ResolveDAGError {
-    /// A column reference did not resolve against its in-scope schema.
-    #[error("column resolution failed: {0}")]
-    Resolve(#[from] ResolveError),
-    /// Deriving the schema of an already-resolved child failed (needed to
-    /// resolve positional column references against it).
-    #[error("schema derivation failed: {0}")]
-    Schema(#[from] QueryExprError),
-}
-
-/// Resolve a whole [`UnresolvedQueryExpr`] DAG rooted at `dag` into canonical
-/// [`ResolvedQueryExpr`]: binds every `ColumnRef` to a `ColumnId` via the
-/// [`SchemaResolver`], then [`canonicalize`](super::canonicalize::canonicalize)s the
-/// result.
-pub fn resolve_root(dag: &UnresolvedQueryExpr) -> Result<ResolvedQueryExpr, ResolveDAGError> {
-    resolve_root_with_inherited(dag, &[])
-}
-
-/// [`resolve_root`] with label names inherited from an enclosing scope seeded
-/// into the leaf schema, used when re-binding a `BinaryOp` side (issue #52).
-fn resolve_root_with_inherited(
-    dag: &UnresolvedQueryExpr,
-    inherited: &[String],
-) -> Result<ResolvedQueryExpr, ResolveDAGError> {
-    let fallback = SchemaResolver::new().resolve_schema_with_inherited(dag, inherited);
-    let l3 = resolve(dag, &fallback)?;
-    Ok(super::canonicalize::canonicalize(l3))
-}
-
-/// The generic substitution walk: converts children first (bottom-up), then
-/// resolves this node's own `ColumnRef`s against the *converted child's*
-/// derived output schema — so a `JOIN`'s concatenated schema and a cross-
-/// series aggregate's frozen-closed output bind to the right positions.
-fn resolve(
-    dag: &UnresolvedQueryExpr,
-    fallback: &Schema,
-) -> Result<ResolvedQueryExpr, ResolveDAGError> {
-    use super::query_expr::QueryExpr as QE;
-    Ok(match dag {
-        QE::Scan {
-            source,
-            predicates,
-            schema,
-        } => {
-            let schema = schema.clone().unwrap_or_else(|| fallback.clone());
-            let predicates = predicates
-                .iter()
-                .map(|Predicate(e)| Ok(Predicate(Rc::new(resolve_expr(e, &schema)?))))
-                .collect::<Result<Vec<_>, ResolveError>>()?;
-            QE::Scan {
-                source: source.clone(),
-                predicates,
-                schema,
-            }
-        }
-
-        // `PromqlScalarBridge`'s child is a scalar-sub-language node (issue
-        // #220) sitting at this operator-DAG position — resolved through
-        // `resolve_expr`, same as every other scalar position (`Predicate`,
-        // `ProjectItem.expr`, …), not the operator walk. In practice it's
-        // always a `Literal`, which has no `ColumnRef` to resolve, so
-        // `fallback` is never actually consulted here.
-        QE::PromqlScalarBridge(inner) => {
-            QE::PromqlScalarBridge(Rc::new(resolve_expr(inner, fallback)?))
-        }
-        QE::EvalTimestamp => QE::EvalTimestamp,
-        QE::CurrentTimestamp => QE::CurrentTimestamp,
-
-        QE::PromqlVectorFromScalar(child) => {
-            QE::PromqlVectorFromScalar(Rc::new(resolve(child, fallback)?))
-        }
-        QE::PromqlScalarFromVector(child) => {
-            QE::PromqlScalarFromVector(Rc::new(resolve(child, fallback)?))
-        }
-
-        QE::PromqlRelabel { dst, value, child } => {
-            let child = resolve(child, fallback)?;
-            let child_schema = child.output_schema()?;
-            QE::PromqlRelabel {
-                dst: dst.clone(),
-                value: Rc::new(resolve_expr(value, &child_schema)?),
-                child: Rc::new(child),
-            }
-        }
-
-        QE::PromqlInfoEnrich { selector, child } => QE::PromqlInfoEnrich {
-            selector: selector.clone(),
-            child: Rc::new(resolve(child, fallback)?),
-        },
-
-        QE::PromqlSeriesSample { by, kind, child } => {
-            let child = resolve(child, fallback)?;
-            let child_schema = child.output_schema()?;
-            QE::PromqlSeriesSample {
-                by: resolve_group_keys(by, &child_schema)?,
-                kind: *kind,
-                child: Rc::new(child),
-            }
-        }
-
-        QE::Filter { pred, child } => {
-            let child = resolve(child, fallback)?;
-            let child_schema = child.output_schema()?;
-            QE::Filter {
-                pred: Predicate(Rc::new(resolve_expr(&pred.0, &child_schema)?)),
-                child: Rc::new(child),
-            }
-        }
-
-        QE::Project {
-            cols,
-            qualifier,
-            child,
-        } => {
-            let child = resolve(child, fallback)?;
-            let child_schema = child.output_schema()?;
-            let cols = cols
-                .iter()
-                .map(|item| -> Result<ProjectItem, ResolveError> {
-                    Ok(ProjectItem {
-                        alias: item.alias.clone(),
-                        expr: resolve_expr(&item.expr, &child_schema)?,
-                    })
-                })
-                .collect::<Result<Vec<_>, _>>()?;
-            QE::Project {
-                cols,
-                qualifier: qualifier.clone(),
-                child: Rc::new(child),
-            }
-        }
-
-        QE::Aggregate {
-            reduction,
-            measures,
-            output_names,
-            filters,
-            having,
-            child,
-        } => {
-            let child = resolve(child, fallback)?;
-            let child_schema = child.output_schema()?;
-            let reduction = resolve_reduction(reduction, &child_schema)?;
-            let measures = measures
-                .iter()
-                .map(|m| resolve_agg_intent(m, &child_schema))
-                .collect::<Result<Vec<_>, ResolveError>>()?;
-            // A measure filter reads the rows being aggregated, so it binds
-            // against the child's schema, not the aggregate's output.
-            let filters = filters
-                .iter()
-                .map(|f| {
-                    f.as_ref()
-                        .map(|Predicate(p)| Ok(Predicate(Rc::new(resolve_expr(p, &child_schema)?))))
-                        .transpose()
-                })
-                .collect::<Result<Vec<_>, ResolveError>>()?;
-            // One canonical spelling of "unfiltered" (empty), so structural
-            // equality and CSE never split on `[]` versus `[None, None]`.
-            let filters = if any_measure_filtered(&filters) {
-                filters
-            } else {
-                Vec::new()
-            };
-            let having = having
-                .as_ref()
-                .map(|Predicate(h)| -> Result<Predicate, ResolveDAGError> {
-                    let out_schema = aggregate_output_schema(
-                        &child_schema,
-                        &reduction,
-                        &measures,
-                        output_names,
-                    )?;
-                    Ok(Predicate(Rc::new(resolve_expr(h, &out_schema)?)))
-                })
-                .transpose()?;
-            QE::Aggregate {
-                reduction,
-                measures,
-                output_names: output_names.clone(),
-                filters,
-                having,
-                child: Rc::new(child),
-            }
-        }
-
-        QE::Dedup { cols, child } => {
-            let child = resolve(child, fallback)?;
-            let child_schema = child.output_schema()?;
-            QE::Dedup {
-                cols: resolve_column_refs(cols, &child_schema)?,
-                child: Rc::new(child),
-            }
-        }
-
-        QE::Concat {
-            children,
-            discriminator_unique_key,
-        } => {
-            let children: Vec<_> = children
-                .iter()
-                .map(|c| resolve(c, fallback))
-                .collect::<Result<Vec<_>, _>>()?;
-            // No front end asserts this today (issue #228 shipped the
-            // extension point ahead of a wired call site) — resolved here
-            // regardless, against the first resolved branch's own output
-            // schema, exactly the schema `output_schema`'s `Concat` arm
-            // derives the merged schema from, so a future direct
-            // `concat_with_discriminator` caller upstream of `resolve_root`
-            // gets a correctly positional `ConcatDiscriminatorKey` out the
-            // other side.
-            let discriminator_unique_key = discriminator_unique_key
-                .as_ref()
-                .map(|key| -> Result<_, ResolveDAGError> {
-                    let schema = children
-                        .first()
-                        .ok_or(QueryExprError::EmptyConcat)?
-                        .output_schema()?;
-                    Ok(ConcatDiscriminatorKey::new(
-                        resolve_column_ref(key.discriminator(), &schema)?,
-                        resolve_column_refs(key.inner_key(), &schema)?,
-                    ))
-                })
-                .transpose()?;
-            QE::Concat {
-                children,
-                discriminator_unique_key,
-            }
-        }
-
-        QE::Join {
-            kind,
-            pred,
-            left,
-            right,
-        } => {
-            // Each branch is bound independently, same reasoning as `BinaryOp`
-            // below — different leaves / label sets.
-            let left = resolve_root_with_inherited(left, &[])?;
-            let right = resolve_root_with_inherited(right, &[])?;
-            let mut concat = left.output_schema()?;
-            concat.fields.extend(right.output_schema()?.fields);
-            let pred = Predicate(Rc::new(resolve_expr(&pred.0, &concat)?));
-            QE::Join {
-                kind: kind.clone(),
-                pred,
-                left: Rc::new(left),
-                right: Rc::new(right),
-            }
-        }
-
-        QE::SetOp {
-            kind,
-            all,
-            left,
-            right,
-        } => QE::SetOp {
-            kind: kind.clone(),
-            all: *all,
-            left: Rc::new(resolve_root_with_inherited(left, &[])?),
-            right: Rc::new(resolve_root_with_inherited(right, &[])?),
-        },
-
-        QE::Sort {
-            keys,
-            partition_by,
-            child,
-        } => {
-            let child = resolve(child, fallback)?;
-            let child_schema = child.output_schema()?;
-            let keys = keys
-                .iter()
-                .map(|k| -> Result<SortKey, ResolveError> {
-                    Ok(SortKey {
-                        expr: resolve_expr(&k.expr, &child_schema)?,
-                        ascending: k.ascending,
-                        nulls_first: k.nulls_first,
-                    })
-                })
-                .collect::<Result<Vec<_>, _>>()?;
-            let partition_by = resolve_group_keys(partition_by, &child_schema)?;
-            QE::Sort {
-                keys,
-                partition_by,
-                child: Rc::new(child),
-            }
-        }
-
-        QE::Limit { n, offset, child } => QE::Limit {
-            n: *n,
-            offset: *offset,
-            child: Rc::new(resolve(child, fallback)?),
-        },
-
-        QE::PromqlSubquery {
-            range,
-            resolution,
-            child,
-        } => QE::PromqlSubquery {
-            range: *range,
-            resolution: *resolution,
-            child: Rc::new(resolve(child, fallback)?),
-        },
-
-        QE::TimeRange { range, child } => QE::TimeRange {
-            range: *range,
-            child: Rc::new(resolve(child, fallback)?),
-        },
-
-        QE::TimeShift { shift, child } => QE::TimeShift {
-            shift: *shift,
-            child: Rc::new(resolve(child, fallback)?),
-        },
-
-        QE::SQLWindowFunc {
-            func,
-            args,
-            partition_by,
-            order_by,
-            frame,
-            output_name,
-            child,
-        } => {
-            let child = resolve(child, fallback)?;
-            let child_schema = child.output_schema()?;
-            let args = args
-                .iter()
-                .map(|a| resolve_expr(a, &child_schema))
-                .collect::<Result<Vec<_>, _>>()?;
-            let partition_by = resolve_group_keys(partition_by, &child_schema)?;
-            let order_by = order_by
-                .iter()
-                .map(|k| -> Result<SortKey, ResolveError> {
-                    Ok(SortKey {
-                        expr: resolve_expr(&k.expr, &child_schema)?,
-                        ascending: k.ascending,
-                        nulls_first: k.nulls_first,
-                    })
-                })
-                .collect::<Result<Vec<_>, _>>()?;
-            QE::SQLWindowFunc {
-                func: func.clone(),
-                args,
-                partition_by,
-                order_by,
-                frame: frame.clone(),
-                output_name: output_name.clone(),
-                child: Rc::new(child),
-            }
-        }
-
-        QE::BinaryOp {
-            op,
-            lhs,
-            rhs,
-            vector_match,
-        } => {
-            // A binary op's two sides may scan different metrics with
-            // different label sets, so each branch resolves against its OWN
-            // bound schema; but an independently-bound side still has to see
-            // label names an *enclosing* node references (issue #52).
-            let own = super::schema_resolver::collect_referenced_columns(dag);
-            let inherited: Vec<String> = inherited_names(fallback)
-                .into_iter()
-                .filter(|n| !own.contains(n))
-                .collect();
-            QE::BinaryOp {
-                op: op.clone(),
-                lhs: Rc::new(resolve_root_with_inherited(lhs, &inherited)?),
-                rhs: Rc::new(resolve_root_with_inherited(rhs, &inherited)?),
-                vector_match: vector_match.clone(),
-            }
-        }
-
-        // The scalar variants (issue #205) are never reached here directly —
-        // `resolve` only ever recurses into `child`/operator positions;
-        // every scalar position (`Predicate`, `ProjectItem.expr`, …) goes
-        // through `resolve_expr` instead, at the operator arm that owns it.
-        other @ (QE::Column(_)
-        | QE::Literal(_)
-        | QE::Compare { .. }
-        | QE::BoolAnd(_)
-        | QE::BoolOr(_)
-        | QE::Not(_)
-        | QE::IsNull(_)
-        | QE::IsNotNull(_)
-        | QE::Cast { .. }
-        | QE::InList { .. }
-        | QE::FunctionCall { .. }
-        | QE::Arithmetic { .. }
-        | QE::Case { .. }) => {
-            unreachable!("resolve reached a scalar QueryExpr variant directly: {other:?}")
-        }
-    })
-}
-
-/// The label names an enclosing scope's schema carries beyond the `(ts,
-/// value)` floor.
-fn inherited_names(schema: &Schema) -> Vec<String> {
-    schema
-        .fields
-        .iter()
-        .filter(|c| c.name != "ts" && c.name != "value")
-        .map(|c| c.name.clone())
-        .collect()
-}
-
-/// Resolve a name-based [`GroupKeys<ColumnRef>`] into positional
-/// [`GroupKeys<ColumnId>`], preserving its `by`/`without` mode.
-fn resolve_group_keys(
-    keys: &GroupKeys<ColumnRef>,
-    schema: &Schema,
-) -> Result<GroupKeys<ColumnId>, ResolveError> {
-    let ids = resolve_column_refs(keys.keys(), schema)?;
-    Ok(if keys.is_without() {
-        GroupKeys::without(ids)
-    } else {
-        GroupKeys::by(ids)
-    })
-}
-
-/// Resolve a name-based [`Reduction<ColumnRef>`] into positional
-/// [`Reduction<ColumnId>`].
-///
-/// Uses [`resolve_group_keys_promql`] rather than the strict
-/// [`resolve_group_keys`], unlike every other group-key site in `resolve`
-/// (`PromqlSeriesSample.by`, `Sort.partition_by`, `SQLWindowFunc.partition_by`): a key
-/// absent from a **closed** schema (e.g. the output of a nested cross-series
-/// aggregate that collapsed the label) is provably absent from every row, so
-/// PromQL drops it from the grouping rather than rejecting the query (issue
-/// #53) — `sum(sum by (group) (m)) by (job)` is the canonical case, `job`
-/// absent from the inner aggregate's closed `[group, sum]` output. Applied
-/// uniformly to every `Aggregate`, not just PromQL's: SQL's `GROUP BY` keys
-/// are always genuinely present (DataFusion validates the plan), so the
-/// "drop instead of reject" branch is simply never exercised there — the
-/// lenient resolver is a no-op difference for a SQL DAG, not a behavior
-/// change.
-fn resolve_reduction(
-    reduction: &Reduction<ColumnRef>,
-    schema: &Schema,
-) -> Result<Reduction<ColumnId>, ResolveError> {
-    Ok(match reduction {
-        Reduction::Reduce(by) => {
-            let ids = resolve_group_keys_promql(by.keys(), schema)?;
-            Reduction::Reduce(if by.is_without() {
-                GroupKeys::without(ids)
-            } else {
-                GroupKeys::by(ids)
-            })
-        }
-        Reduction::PerEntity => Reduction::PerEntity,
-    })
-}
-
-/// Resolve a name-based [`AggIntent<ColumnRef>`] into positional
-/// [`AggIntent<ColumnId>`] — every `col: Option<ColumnRef>` resolves to
-/// `Option<ColumnId>` (`None` stays `None`, the sample-value convention);
-/// every other field carries straight through unchanged.
-fn resolve_agg_intent(
-    intent: &AggIntent<ColumnRef>,
-    schema: &Schema,
-) -> Result<AggIntent<ColumnId>, ResolveError> {
-    let col = |c: &Option<ColumnRef>| -> Result<Option<ColumnId>, ResolveError> {
-        c.as_ref()
-            .map(|r| resolve_column_ref(r, schema))
-            .transpose()
-    };
-    Ok(match intent {
-        AggIntent::Count { accuracy } => AggIntent::Count {
-            accuracy: accuracy.clone(),
-        },
-        AggIntent::PearsonCorr { left, right } => AggIntent::PearsonCorr {
-            left: resolve_column_ref(left, schema)?,
-            right: resolve_column_ref(right, schema)?,
-        },
-        AggIntent::Sum { col: c } => AggIntent::Sum { col: col(c)? },
-        AggIntent::Min { col: c } => AggIntent::Min { col: col(c)? },
-        AggIntent::Max { col: c } => AggIntent::Max { col: col(c)? },
-        AggIntent::Avg { col: c } => AggIntent::Avg { col: col(c)? },
-        AggIntent::StdDev { col: c, population } => AggIntent::StdDev {
-            col: col(c)?,
-            population: *population,
-        },
-        AggIntent::Variance { col: c, population } => AggIntent::Variance {
-            col: col(c)?,
-            population: *population,
-        },
-        AggIntent::Quantile {
-            col: c,
-            q,
-            accuracy,
-        } => AggIntent::Quantile {
-            col: col(c)?,
-            q: *q,
-            accuracy: accuracy.clone(),
-        },
-        AggIntent::TopK { k, accuracy } => AggIntent::TopK {
-            k: *k,
-            accuracy: accuracy.clone(),
-        },
-        AggIntent::Cardinality { cols, accuracy } => AggIntent::Cardinality {
-            cols: cols
-                .iter()
-                .map(|c| resolve_column_ref(c, schema))
-                .collect::<Result<_, _>>()?,
-            accuracy: accuracy.clone(),
-        },
-        AggIntent::FrequencyL2 { col: c, accuracy } => AggIntent::FrequencyL2 {
-            col: col(c)?,
-            accuracy: accuracy.clone(),
-        },
-        AggIntent::FrequencyEntropy { col: c, accuracy } => AggIntent::FrequencyEntropy {
-            col: col(c)?,
-            accuracy: accuracy.clone(),
-        },
-        AggIntent::Rate => AggIntent::Rate,
-        AggIntent::IRate => AggIntent::IRate,
-        AggIntent::Increase => AggIntent::Increase,
-        AggIntent::Changes => AggIntent::Changes,
-        AggIntent::Delta => AggIntent::Delta,
-        AggIntent::IDelta => AggIntent::IDelta,
-        AggIntent::Deriv => AggIntent::Deriv,
-        AggIntent::Resets => AggIntent::Resets,
-        AggIntent::PredictLinear { seconds } => AggIntent::PredictLinear { seconds: *seconds },
-        AggIntent::DoubleExpSmoothing { smoothing, trend } => AggIntent::DoubleExpSmoothing {
-            smoothing: *smoothing,
-            trend: *trend,
-        },
-        AggIntent::HistogramCount => AggIntent::HistogramCount,
-        AggIntent::HistogramSum => AggIntent::HistogramSum,
-        AggIntent::HistogramAvg => AggIntent::HistogramAvg,
-        AggIntent::HistogramStdDev => AggIntent::HistogramStdDev,
-        AggIntent::HistogramStdVar => AggIntent::HistogramStdVar,
-        AggIntent::HistogramFraction { lower, upper } => AggIntent::HistogramFraction {
-            lower: *lower,
-            upper: *upper,
-        },
-        AggIntent::HistogramQuantile { q, le } => AggIntent::HistogramQuantile {
-            q: *q,
-            le: resolve_column_ref(le, schema)?,
-        },
-        AggIntent::Math(f) => AggIntent::Math(f.clone()),
-        AggIntent::Absent => AggIntent::Absent,
-        AggIntent::AbsentOverTime => AggIntent::AbsentOverTime,
-        AggIntent::PresentOverTime => AggIntent::PresentOverTime,
-        AggIntent::TimeFn(f) => AggIntent::TimeFn(*f),
-        AggIntent::Group => AggIntent::Group,
-        AggIntent::CountValues { label } => AggIntent::CountValues {
-            label: label.clone(),
-        },
-        AggIntent::LastOverTime => AggIntent::LastOverTime,
-        AggIntent::FirstOverTime => AggIntent::FirstOverTime,
-        AggIntent::MadOverTime => AggIntent::MadOverTime,
-        AggIntent::TsOfMinOverTime => AggIntent::TsOfMinOverTime,
-        AggIntent::TsOfMaxOverTime => AggIntent::TsOfMaxOverTime,
-        AggIntent::TsOfFirstOverTime => AggIntent::TsOfFirstOverTime,
-        AggIntent::TsOfLastOverTime => AggIntent::TsOfLastOverTime,
-        AggIntent::Extension { ext_kind, payload } => AggIntent::Extension {
-            ext_kind: ext_kind.clone(),
-            payload: payload.clone(),
-        },
-    })
-}
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-    use crate::pre_asap::expr_ir::CompareOpKind;
-    use crate::pre_asap::query_expr::{
-        BinaryOpKind, QueryExpr, Source, VectorMatch, VectorMatchKind,
-    };
-
-    // A measure filter (#466) binds positionally against the aggregate's
-    // input, and a vector with no set entry collapses to the empty spelling.
-    #[test]
-    fn resolve_measure_filters_against_the_child_schema() {
-        use crate::pre_asap::expr_ir::ScalarValue;
-        use crate::pre_asap::query_expr::Predicate;
-        use crate::pre_asap::{DataType, Field, GroupKeys};
-        use crate::types::AccuracyTarget;
-        let scan = || UnresolvedQueryExpr::Scan {
-            source: Source::Table {
-                table_ref: "metrics".into(),
-            },
-            predicates: vec![],
-            schema: Some(Schema::new(vec![
-                Field::plain("service", DataType::Utf8, false),
-                Field::plain("latency", DataType::Float64, false),
-                Field::plain("bytes", DataType::Int64, false),
-            ])),
-        };
-        let aggregate = |filters| UnresolvedQueryExpr::Aggregate {
-            reduction: Reduction::Reduce(GroupKeys::by(vec![ColumnRef::Named("service".into())])),
-            measures: vec![
-                AggIntent::Count {
-                    accuracy: AccuracyTarget::Exact,
-                },
-                AggIntent::Sum {
-                    col: Some(ColumnRef::Named("bytes".into())),
-                },
-            ],
-            output_names: vec![],
-            filters,
-            having: None,
-            child: Rc::new(scan()),
-        };
-        let latency_gt_one = Predicate(Rc::new(UnresolvedQueryExpr::Compare {
-            left: Rc::new(UnresolvedQueryExpr::Column(ColumnRef::Named(
-                "latency".into(),
-            ))),
-            op: CompareOpKind::Gt,
-            right: Rc::new(UnresolvedQueryExpr::Literal(ScalarValue::Float64(1.0))),
-        }));
-
-        let resolved = resolve_root(&aggregate(vec![Some(latency_gt_one), None])).unwrap();
-        let QueryExpr::Aggregate { filters, .. } = &resolved else {
-            unreachable!()
-        };
-        let [Some(Predicate(first)), None] = filters.as_slice() else {
-            panic!("expected one filtered and one unfiltered measure, got {filters:?}");
-        };
-        assert!(
-            matches!(first.as_ref(), QueryExpr::Compare { left, .. }
-                if matches!(left.as_ref(), QueryExpr::Column(1))),
-            "latency is input column 1, got {first:?}"
-        );
-
-        let resolved = resolve_root(&aggregate(vec![None, None])).unwrap();
-        let QueryExpr::Aggregate { filters, .. } = &resolved else {
-            unreachable!()
-        };
-        assert!(filters.is_empty());
-    }
-
-    // Both sides resolve with qualifiers; an unknown right input is an error.
-    #[test]
-    fn resolve_pearson_corr_inputs() {
-        use crate::pre_asap::{DataType, Field};
-        let schema = Schema::new(vec![
-            Field::plain("x", DataType::Float64, true).with_table("a"),
-            Field::plain("x", DataType::Float64, true).with_table("b"),
-        ]);
-        let intent = AggIntent::PearsonCorr {
-            left: ColumnRef::Qualified {
-                table: "a".into(),
-                name: "x".into(),
-            },
-            right: ColumnRef::Qualified {
-                table: "b".into(),
-                name: "x".into(),
-            },
-        };
-        assert_eq!(
-            resolve_agg_intent(&intent, &schema).unwrap(),
-            AggIntent::PearsonCorr { left: 0, right: 1 }
-        );
-        let missing = AggIntent::PearsonCorr {
-            left: ColumnRef::Qualified {
-                table: "a".into(),
-                name: "x".into(),
-            },
-            right: ColumnRef::Named("missing".into()),
-        };
-        assert!(resolve_agg_intent(&missing, &schema).is_err());
-    }
-
-    // Every leg resolves independently, qualifiers included; one unknown leg
-    // fails rather than silently shortening the tuple.
-    #[test]
-    fn resolve_distinct_tuple_columns() {
-        use crate::pre_asap::{DataType, Field};
-        use crate::types::AccuracyTarget;
-        let schema = Schema::new(vec![
-            Field::plain("k", DataType::Int64, true).with_table("a"),
-            Field::plain("k", DataType::Int64, true).with_table("b"),
-        ]);
-        let qualified = |table: &str| ColumnRef::Qualified {
-            table: table.into(),
-            name: "k".into(),
-        };
-        let intent = AggIntent::Cardinality {
-            cols: vec![qualified("b"), qualified("a")],
-            accuracy: AccuracyTarget::Exact,
-        };
-        assert_eq!(
-            resolve_agg_intent(&intent, &schema).unwrap(),
-            AggIntent::Cardinality {
-                cols: vec![1, 0],
-                accuracy: AccuracyTarget::Exact,
-            }
-        );
-        let missing = AggIntent::Cardinality {
-            cols: vec![qualified("a"), ColumnRef::Named("missing".into())],
-            accuracy: AccuracyTarget::Exact,
-        };
-        assert!(resolve_agg_intent(&missing, &schema).is_err());
-    }
-
-    /// `resolve_root` over a `BinaryOp { <vector>, PromqlScalarBridge, vector_match }`
-    /// (issue #220): the bridged scalar operand resolves through the same
-    /// generic walk as every other node (its `Literal` child has no
-    /// `ColumnRef` to resolve, so it comes through unchanged), the vector
-    /// side's `ColumnRef`s resolve positionally, and the `VectorMatch`
-    /// modifier on the relational binary-op path survives resolution
-    /// untouched — Instance 2 of #220 (`BinaryOp` vs `Compare`/`Arithmetic`)
-    /// is out of scope for this change, so this pins that its behavior is
-    /// unaffected by the Instance-1 collapse.
-    #[test]
-    fn resolve_root_threads_a_scalar_bridge_operand_and_preserves_vector_match() {
-        let vm = VectorMatch {
-            kind: VectorMatchKind::Ignoring,
-            labels: vec!["job".into()],
-            grouping: None,
-        };
-        let unresolved: UnresolvedQueryExpr = QueryExpr::BinaryOp {
-            op: BinaryOpKind::Compare(CompareOpKind::Gt),
-            lhs: Rc::new(UnresolvedQueryExpr::Scan {
-                source: Source::TimeSeries {
-                    metric: "up".into(),
-                },
-                predicates: vec![],
-                schema: None,
-            }),
-            rhs: Rc::new(UnresolvedQueryExpr::promql_scalar(1.0)),
-            vector_match: Some(vm.clone()),
-        };
-
-        let resolved = resolve_root(&unresolved).expect("resolves");
-        let QueryExpr::BinaryOp {
-            lhs,
-            rhs,
-            vector_match,
-            ..
-        } = &resolved
-        else {
-            panic!("expected a resolved BinaryOp, got {resolved:?}");
-        };
-        assert!(matches!(lhs.as_ref(), QueryExpr::Scan { .. }));
-        assert_eq!(rhs.as_promql_scalar(), Some(1.0));
-        assert_eq!(vector_match.as_ref(), Some(&vm));
-
-        // Schema derivation still follows the vector side post-resolution.
-        assert_eq!(
-            resolved.output_schema().unwrap(),
-            lhs.output_schema().unwrap()
-        );
-    }
-
-    /// Issue #228 review, end-to-end: `resolve_root` over a `Concat` whose
-    /// discriminator column is referenced *nowhere else* in the DAG, with a
-    /// schema-less (usage-derived) leaf `Scan` in the first branch — exactly
-    /// the scenario the review flagged. Before the `schema_resolver.rs` fix, the
-    /// SchemaResolver's fallback schema wouldn't contain `phi` at all, and this
-    /// `resolve_column_ref` call would fail `NotFound` for a column the
-    /// caller correctly named. It must resolve cleanly, and the resolved
-    /// `ConcatDiscriminatorKey` must carry the *positional* `ColumnId`s of
-    /// the branch's own (usage-derived) schema.
-    #[test]
-    fn resolve_root_seeds_and_resolves_an_otherwise_unreferenced_discriminator_column() {
-        let branch = || UnresolvedQueryExpr::Scan {
-            source: Source::TimeSeries { metric: "m".into() },
-            predicates: vec![],
-            schema: None,
-        };
-        let unresolved = UnresolvedQueryExpr::concat_with_discriminator(
-            vec![branch(), branch()],
-            ColumnRef::Named("phi".into()),
-            vec![ColumnRef::Named("host".into())],
-        );
-
-        let resolved = resolve_root(&unresolved).expect("resolves");
-        let QueryExpr::Concat {
-            children,
-            discriminator_unique_key,
-        } = &resolved
-        else {
-            panic!("expected a resolved Concat, got {resolved:?}");
-        };
-        let schema = children[0].output_schema().unwrap();
-        let key = discriminator_unique_key
-            .as_ref()
-            .expect("discriminator key survives resolution");
-        assert_eq!(*key.discriminator(), schema.column_id("phi").unwrap());
-        assert_eq!(
-            key.inner_key().to_vec(),
-            vec![schema.column_id("host").unwrap()]
-        );
-    }
-}
diff --git a/crates/types/src/pre_asap/scalar_type_rules.rs b/crates/types/src/pre_asap/scalar_type_rules.rs
index 44eaa250c..3efad3f7e 100644
--- a/crates/types/src/pre_asap/scalar_type_rules.rs
+++ b/crates/types/src/pre_asap/scalar_type_rules.rs
@@ -1,5 +1,5 @@
-//! Shared type rules for structural map scalar expressions.
-//! Execution must separately implement the documented ordering/default semantics.
+//! Shared type and nullability rules used to validate scalar expressions.
+//! These rules do not evaluate expressions or define physical representations.
 use super::schema::DataType;
 
 /// Names are resolved once against this closed builtin set; unknown functions
@@ -123,6 +123,21 @@ fn common_type(left: &DataType, right: &DataType) -> Result<DataType, String> {
     ))
 }
 
+/// Closed, namespaced contracts for PromQL pointwise float functions.
+/// Date functions consume Unix seconds; `timestamp` remains a sample-selection
+/// operation because its operand is a sample timestamp rather than its value.
+pub fn promql_function_arity(name: &str) -> Option<usize> {
+    Some(match name.strip_prefix("promql_")? {
+        "abs" | "ceil" | "floor" | "exp" | "ln" | "log2" | "log10" | "sqrt" | "sgn" | "sin"
+        | "cos" | "tan" | "asin" | "acos" | "atan" | "sinh" | "cosh" | "tanh" | "asinh"
+        | "acosh" | "atanh" | "deg" | "rad" | "minute" | "hour" | "day_of_week"
+        | "day_of_month" | "day_of_year" | "month" | "year" | "days_in_month" => 1,
+        "round" | "clamp_min" | "clamp_max" => 2,
+        "clamp" => 3,
+        _ => return None,
+    })
+}
+
 #[cfg(test)]
 mod tests {
     use super::*;
@@ -196,324 +211,3 @@ mod tests {
             .is_err());
     }
 }
-
-#[cfg(test)]
-mod projection_tests {
-    use super::*;
-    use crate::pre_asap::{Field, ProjectItem, QueryExpr, ScalarValue, Schema, Source};
-    use std::rc::Rc;
-    fn project(expr: QueryExpr) -> QueryExpr {
-        QueryExpr::Project {
-            cols: vec![ProjectItem {
-                alias: Some("result".into()),
-                expr,
-            }],
-            qualifier: None,
-            child: Rc::new(QueryExpr::Scan {
-                source: Source::Table {
-                    table_ref: "t".into(),
-                },
-                predicates: vec![],
-                schema: Schema::new(vec![
-                    Field::plain("k", DataType::Utf8, false),
-                    Field::plain("v", DataType::Int64, true),
-                ]),
-            }),
-        }
-    }
-    #[test]
-    fn canonical_projection_uses_map_signature_and_rejects_invalid_arity() {
-        let map = QueryExpr::FunctionCall {
-            name: "map".into(),
-            args: vec![QueryExpr::Column(0), QueryExpr::Column(1)],
-        };
-        let schema = project(map.clone()).output_schema().unwrap();
-        assert_eq!(
-            schema.fields[0].dtype,
-            DataType::Map {
-                key: Box::new(DataType::Utf8),
-                value: Box::new(DataType::Int64),
-                value_nullable: true
-            }
-        );
-        assert!(!schema.fields[0].nullable);
-        let lookup = QueryExpr::FunctionCall {
-            name: "asap_map_access".into(),
-            args: vec![map, QueryExpr::Literal(ScalarValue::Utf8("missing".into()))],
-        };
-        assert_eq!(
-            project(lookup).output_schema().unwrap().fields[0],
-            Field::plain("result", DataType::Int64, true)
-        );
-        assert!(project(QueryExpr::FunctionCall {
-            name: "map".into(),
-            args: vec![QueryExpr::Column(0)]
-        })
-        .output_schema()
-        .is_err());
-    }
-}
-
-/// Resolve the bounded canonical `asap_struct_field(struct, selector)` operation.
-/// Selectors are positive 1-based literal ordinals or exact literal field names.
-/// The existing Struct fields remain the sole authority for type/nullability.
-/// Dynamic/negative/defaulted selectors and nullable containers are intentionally
-/// unsupported here; this is not a claim of complete native tupleElement support.
-pub fn struct_field_type(
-    args: &[super::QueryExpr],
-    schema: &super::Schema,
-) -> Result<(DataType, bool), String> {
-    use super::{QueryExpr, ScalarValue};
-    let [input, selector] = args else {
-        return Err("struct field access requires a struct and constant selector".into());
-    };
-    let (dtype, nullable) = input
-        .scalar_type(schema)
-        .map_err(|error| error.to_string())?;
-    if nullable {
-        return Err("nullable struct container access is unsupported".into());
-    }
-    let DataType::Struct { fields } = dtype else {
-        return Err("struct field access requires a Struct input".into());
-    };
-    let field = match selector {
-        QueryExpr::Literal(ScalarValue::Int64(index)) if *index > 0 => usize::try_from(*index - 1)
-            .ok()
-            .and_then(|index| fields.get(index))
-            .ok_or("struct field ordinal is out of bounds")?,
-        QueryExpr::Literal(ScalarValue::Utf8(name)) => {
-            let mut matches = fields.iter().filter(|field| field.name == *name);
-            let field = matches.next().ok_or("struct field name does not exist")?;
-            if matches.next().is_some() {
-                return Err("struct field name is ambiguous".into());
-            }
-            field
-        }
-        _ => {
-            return Err(
-                "struct field selector must be a positive ordinal or field-name literal".into(),
-            )
-        }
-    };
-    Ok((field.dtype.clone(), field.nullable))
-}
-
-#[cfg(test)]
-mod struct_field_tests {
-    use super::*;
-    use crate::pre_asap::{Field, FieldDataType, QueryExpr, ScalarValue, Schema};
-    fn schema() -> Schema {
-        Schema::new(vec![Field::plain(
-            "record",
-            DataType::Struct {
-                fields: vec![
-                    Field::new("ts", DataType::Int64, false),
-                    Field::new(
-                        "values",
-                        DataType::List {
-                            element: Box::new(Field::new("item", DataType::Float64, true)),
-                        },
-                        true,
-                    ),
-                ],
-            },
-            false,
-        )])
-    }
-    fn access(selector: QueryExpr) -> QueryExpr {
-        QueryExpr::FunctionCall {
-            name: "asap_struct_field".into(),
-            args: vec![QueryExpr::Column(0), selector],
-        }
-    }
-    #[test]
-    fn field_access_reuses_nested_field_type_and_nullability() {
-        let schema = schema();
-        assert_eq!(
-            access(QueryExpr::Literal(ScalarValue::Int64(1)))
-                .scalar_type(&schema)
-                .unwrap(),
-            (DataType::Int64, false)
-        );
-        let named = access(QueryExpr::Literal(ScalarValue::Utf8("values".into())));
-        let ordinal = access(QueryExpr::Literal(ScalarValue::Int64(2)));
-        assert_eq!(
-            named.scalar_type(&schema).unwrap(),
-            ordinal.scalar_type(&schema).unwrap()
-        );
-        assert_eq!(
-            named.scalar_type(&schema).unwrap(),
-            (
-                DataType::List {
-                    element: Box::new(Field::new("item", DataType::Float64, true))
-                },
-                true
-            )
-        );
-        let roundtrip: QueryExpr =
-            serde_json::from_str(&serde_json::to_string(&named).unwrap()).unwrap();
-        assert_eq!(roundtrip, named);
-    }
-    #[test]
-    fn unsupported_field_access_is_an_error_not_placeholder_typing() {
-        for selector in [
-            QueryExpr::Column(0),
-            QueryExpr::Literal(ScalarValue::Int64(0)),
-            QueryExpr::Literal(ScalarValue::Int64(-1)),
-            QueryExpr::Literal(ScalarValue::Int64(3)),
-            QueryExpr::Literal(ScalarValue::Utf8("missing".into())),
-        ] {
-            assert!(access(selector).scalar_type(&schema()).is_err());
-        }
-        let mut ambiguous = schema();
-        if let FieldDataType::Plain(DataType::Struct { fields }) = &mut ambiguous.fields[0].dtype {
-            fields.push(Field::new("ts", DataType::Utf8, false));
-        }
-        assert!(access(QueryExpr::Literal(ScalarValue::Utf8("ts".into())))
-            .scalar_type(&ambiguous)
-            .is_err());
-        let mut nullable = schema();
-        nullable.fields[0].nullable = true;
-        assert!(access(QueryExpr::Literal(ScalarValue::Int64(1)))
-            .scalar_type(&nullable)
-            .is_err());
-    }
-}
-
-/// Canonical element lookup over a declared Map or List. Map lookup retains its
-/// existing key/default contract. List lookup is one-based, supports negative
-/// indices, and returns the declared element default when a dynamic index is
-/// out of range. Literal zero is conservatively rejected because native array
-/// behavior depends on whether the input array is constant. Nullable containers
-/// are unsupported; nullable indices produce nullable results.
-pub fn element_access_type(
-    args: &[super::QueryExpr],
-    schema: &super::Schema,
-) -> Result<(DataType, bool), String> {
-    use super::{QueryExpr, ScalarValue};
-    let [input, index] = args else {
-        return Err("element access requires a collection and index".into());
-    };
-    let source = input.scalar_type(schema).map_err(|e| e.to_string())?;
-    let key = index.scalar_type(schema).map_err(|e| e.to_string())?;
-    match &source.0 {
-        DataType::Map { .. } => MapScalarFunction::Access.output_type(&[source, key]),
-        DataType::List { element } => {
-            if source.1 {
-                return Err("nullable List container access is unsupported".into());
-            }
-            if !matches!(key.0, DataType::Int64 | DataType::Null) {
-                return Err("List index must have integer type".into());
-            }
-            if matches!(index, QueryExpr::Literal(ScalarValue::Int64(0))) {
-                return Err(
-                    "literal zero List index is unsupported without constant-array proof".into(),
-                );
-            }
-            Ok((
-                element.dtype.clone(),
-                element.nullable || key.1 || key.0 == DataType::Null,
-            ))
-        }
-        _ => Err("element access requires a Map or List".into()),
-    }
-}
-
-#[cfg(test)]
-mod element_access_tests {
-    use super::*;
-    use crate::pre_asap::{Field, QueryExpr, ScalarValue, Schema};
-    fn access(index: QueryExpr) -> QueryExpr {
-        QueryExpr::FunctionCall {
-            name: "asap_element_access".into(),
-            args: vec![QueryExpr::Column(0), index],
-        }
-    }
-    #[test]
-    fn list_index_preserves_nested_element_metadata() {
-        let element = DataType::Struct {
-            fields: vec![
-                Field::new("ts", DataType::Int64, false),
-                Field::new("value", DataType::Float64, true),
-            ],
-        };
-        let schema = Schema::new(vec![
-            Field::plain(
-                "samples",
-                DataType::List {
-                    element: Box::new(Field::new("item", element.clone(), false)),
-                },
-                false,
-            ),
-            Field::plain("i", DataType::Int64, true),
-        ]);
-        for index in [1, -1, 100] {
-            assert_eq!(
-                access(QueryExpr::Literal(ScalarValue::Int64(index)))
-                    .scalar_type(&schema)
-                    .unwrap(),
-                (element.clone(), false)
-            );
-        }
-        assert_eq!(
-            access(QueryExpr::Column(1)).scalar_type(&schema).unwrap(),
-            (element.clone(), true)
-        );
-        assert!(access(QueryExpr::Literal(ScalarValue::Int64(0)))
-            .scalar_type(&schema)
-            .is_err());
-        assert!(access(QueryExpr::Literal(ScalarValue::Float64(1.0)))
-            .scalar_type(&schema)
-            .is_err());
-        let nested = QueryExpr::FunctionCall {
-            name: "asap_struct_field".into(),
-            args: vec![
-                access(QueryExpr::Literal(ScalarValue::Int64(1))),
-                QueryExpr::Literal(ScalarValue::Int64(2)),
-            ],
-        };
-        assert_eq!(
-            nested.scalar_type(&schema).unwrap(),
-            (DataType::Float64, true)
-        );
-        let roundtrip: QueryExpr =
-            serde_json::from_value(serde_json::to_value(&nested).unwrap()).unwrap();
-        assert_eq!(roundtrip, nested);
-    }
-    #[test]
-    fn generic_map_lookup_reuses_legacy_signature() {
-        let schema = Schema::new(vec![Field::plain(
-            "m",
-            DataType::Map {
-                key: Box::new(DataType::Utf8),
-                value: Box::new(DataType::Int64),
-                value_nullable: false,
-            },
-            false,
-        )]);
-        let key = QueryExpr::Literal(ScalarValue::Utf8("k".into()));
-        let legacy = QueryExpr::FunctionCall {
-            name: "asap_map_access".into(),
-            args: vec![QueryExpr::Column(0), key.clone()],
-        };
-        assert_eq!(
-            access(key).scalar_type(&schema).unwrap(),
-            legacy.scalar_type(&schema).unwrap()
-        );
-    }
-}
-
-/// Closed, namespaced contracts for PromQL pointwise float functions.
-/// Date functions consume Unix seconds; `timestamp` remains a sample-selection
-/// operation because its operand is a sample timestamp rather than its value.
-pub fn promql_function_arity(name: &str) -> Option<usize> {
-    Some(match name.strip_prefix("promql_")? {
-        "abs" | "ceil" | "floor" | "exp" | "ln" | "log2" | "log10" | "sqrt" | "sgn" | "sin"
-        | "cos" | "tan" | "asin" | "acos" | "atan" | "sinh" | "cosh" | "tanh" | "asinh"
-        | "acosh" | "atanh" | "deg" | "rad" | "minute" | "hour" | "day_of_week"
-        | "day_of_month" | "day_of_year" | "month" | "year" | "days_in_month" => 1,
-        "round" | "clamp_min" | "clamp_max" => 2,
-        "clamp" => 3,
-        _ => return None,
-    })
-}
diff --git a/crates/types/src/pre_asap/schema.rs b/crates/types/src/pre_asap/schema.rs
index 77c8ebe92..7eec788b7 100644
--- a/crates/types/src/pre_asap/schema.rs
+++ b/crates/types/src/pre_asap/schema.rs
@@ -325,82 +325,6 @@ impl TryFrom<SchemaWire> for Schema {
 /// label map. `$` cannot occur in a user PromQL label name.
 pub const PROMQL_SERIES_IDENTITY: &str = "$promql_series_identity";
 
-/// Resolve a PromQL root to rows carrying [`PROMQL_SERIES_IDENTITY`] before
-/// candidate search. `closed` describes physical columns here: the final
-/// column contains every dynamic source label. It does not assert that the
-/// query's projected labels are the full label set.
-///
-/// This realization supports explicit `by` grouping and per-series computation.
-/// Operators that rewrite or implicitly match dynamic label sets require their
-/// own realization; they must not accidentally treat the opaque identity as a
-/// user label or silently discard it.
-pub fn with_promql_series_identity(root: &super::QueryExpr) -> Result<super::QueryExpr, String> {
-    use super::{QueryExpr, Source};
-    use std::rc::Rc;
-    let mut root = root.clone();
-    fn visit(node: &mut QueryExpr) -> Result<(), String> {
-        match node {
-            QueryExpr::Scan {
-                source: Source::TimeSeries { .. },
-                schema,
-                ..
-            } => {
-                if schema
-                    .fields
-                    .iter()
-                    .any(|column| column.name == PROMQL_SERIES_IDENTITY)
-                {
-                    return Err("source already contains a physical series identity".into());
-                }
-                if schema.closed {
-                    return Err("dynamic series identity requires an open PromQL source".into());
-                }
-                schema
-                    .fields
-                    .push(Field::plain(PROMQL_SERIES_IDENTITY, DataType::Utf8, false));
-                schema.closed = true;
-                Ok(())
-            }
-            QueryExpr::TimeRange { child, .. }
-            | QueryExpr::Limit { child, .. }
-            | QueryExpr::TimeShift { child, .. }
-            | QueryExpr::PromqlSubquery { child, .. }
-            | QueryExpr::PromqlScalarFromVector(child)
-            | QueryExpr::PromqlRelabel { child, .. } => visit(Rc::make_mut(child)),
-            // Constants read no series.
-            QueryExpr::PromqlScalarBridge(_)
-            | QueryExpr::EvalTimestamp
-            | QueryExpr::Literal(super::ScalarValue::Float64(_)) => Ok(()),
-            QueryExpr::PromqlVectorFromScalar(child) => visit(Rc::make_mut(child)),
-            QueryExpr::BinaryOp { lhs, rhs, .. } => {
-                visit(Rc::make_mut(lhs))?;
-                visit(Rc::make_mut(rhs))
-            }
-            QueryExpr::Concat { children, .. } => {
-                for child in children {
-                    visit(child)?;
-                }
-                Ok(())
-            }
-            QueryExpr::Aggregate { child, .. } => visit(Rc::make_mut(child)),
-            QueryExpr::Sort {
-                child,
-                partition_by,
-                ..
-            } => {
-                if partition_by.is_without() {
-                    return Err("dynamic without ranking requires label-set projection".into());
-                }
-                visit(Rc::make_mut(child))
-            }
-            _ => Err("operator has no dynamic series-identity realization".into()),
-        }
-    }
-    visit(&mut root)?;
-    root.output_schema().map_err(|error| error.to_string())?;
-    Ok(root)
-}
-
 impl Schema {
     pub fn has_promql_series_identity(&self) -> bool {
         self.closed
@@ -605,12 +529,4 @@ mod tests {
         assert_eq!(back, c);
         assert_eq!(back.table.as_deref(), Some("hosts"));
     }
-    // Direct scalar literals remain valid vector inputs when series typing runs.
-    #[test]
-    fn series_identity_accepts_direct_vector_literal() {
-        let root = super::super::QueryExpr::PromqlVectorFromScalar(std::rc::Rc::new(
-            super::super::QueryExpr::Literal(super::super::ScalarValue::Float64(1.0)),
-        ));
-        assert!(with_promql_series_identity(&root).is_ok());
-    }
 }
diff --git a/crates/types/src/pre_asap/schema_resolver.rs b/crates/types/src/pre_asap/schema_resolver.rs
deleted file mode 100644
index a9afff2cb..000000000
--- a/crates/types/src/pre_asap/schema_resolver.rs
+++ /dev/null
@@ -1,492 +0,0 @@
-//! The **SchemaResolver** — name resolution as an explicit pass.
-//!
-//! [`SchemaResolver::resolve_schema`] produces the complete, self-contained [`Schema`] every
-//! `ColumnId` in the canonical DAG indexes into. [`resolve`](super::resolve)
-//! then becomes purely structural: it threads the SchemaResolver's schema and
-//! positional resolution downstream is **total**.
-//!
-//! The default [`UsageDerivedCatalog`] knows nothing — every schema is derived
-//! purely from the query's own usage. That is the honest state for the
-//! observability domain (metric label sets are open-ended). A registry-backed
-//! `SchemaCatalog` is future work; the `SchemaResolver` pass does not change when it
-//! lands, only the catalog impl swaps.
-
-use super::expr_ir::ColumnRef;
-use super::query_expr::UnresolvedQueryExpr;
-use super::schema::{DataType, Field, Schema};
-
-/// The DB / source-schema metadata source — resolves a source (metric /
-/// table) name to its known columns.
-/// Source of truth for a source's columns — the "catalog". `SqlCatalog` backs
-/// it for SQL; PromQL uses [`UsageDerivedCatalog`] (returns `None`) until a
-/// registry-backed impl (returning a metric's known label set) drops in here.
-/// Distinct from `Scan.schema`, which is the *resolved* binding schema this
-/// feeds — the catalog is the input, the schema is the result. Even a
-/// registry-backed PromQL catalog yields an **open** schema
-/// ([`Schema::closed`] `= false`): a metric's
-/// labels are per-series and time-varying, so the registry is a superset hint,
-/// not a per-row contract.
-pub trait SchemaCatalog {
-    /// Columns known for `source`. `None` when unknown — the [`SchemaResolver`] then
-    /// falls back to a usage-derived column set.
-    fn columns_for(&self, source: &str) -> Option<Vec<Field>>;
-}
-
-/// The default catalog: knows nothing. Every schema the [`SchemaResolver`] produces
-/// is derived purely from the query's own usage.
-pub struct UsageDerivedCatalog;
-
-impl SchemaCatalog for UsageDerivedCatalog {
-    fn columns_for(&self, _source: &str) -> Option<Vec<Field>> {
-        None
-    }
-}
-
-/// The explicit name-resolution pass.
-pub struct SchemaResolver<C: SchemaCatalog = UsageDerivedCatalog> {
-    catalog: C,
-}
-
-impl Default for SchemaResolver<UsageDerivedCatalog> {
-    fn default() -> Self {
-        Self::new()
-    }
-}
-
-impl SchemaResolver<UsageDerivedCatalog> {
-    pub fn new() -> Self {
-        Self {
-            catalog: UsageDerivedCatalog,
-        }
-    }
-}
-
-impl<C: SchemaCatalog> SchemaResolver<C> {
-    pub fn with_catalog(catalog: C) -> Self {
-        Self { catalog }
-    }
-
-    /// Resolve the complete [`Schema`] in scope for a query rooted at `dag`.
-    ///
-    /// Contains the time axis, the synthetic `value` column, and one column
-    /// per distinct name referenced anywhere in the DAG — so positional
-    /// `ColumnId` resolution downstream is total.
-    pub fn resolve_schema(&self, dag: &UnresolvedQueryExpr) -> Schema {
-        self.resolve_schema_with_inherited(dag, &[])
-    }
-
-    /// Like [`resolve_schema`](Self::resolve_schema), but also seeds `inherited` label names that are
-    /// referenced by an **enclosing** scope rather than by `dag` itself. This is
-    /// how an independently-bound `BinaryOp` side (each side re-binds against its
-    /// own sub-DAG) still sees an outer aggregate's group keys — e.g. the
-    /// `__name__` / `job` in `sum by (__name__)(a or b)`, which appear in neither
-    /// side's own matchers (issue #52).
-    pub fn resolve_schema_with_inherited(
-        &self,
-        dag: &UnresolvedQueryExpr,
-        inherited: &[String],
-    ) -> Schema {
-        let mut columns: Vec<Field> = leftmost_scan_name(dag)
-            .and_then(|name| self.catalog.columns_for(name))
-            .unwrap_or_else(default_leaf_columns);
-
-        // Ensure the (ts, value) floor is present.
-        for floor in default_leaf_columns() {
-            if !columns.iter().any(|c| c.name == floor.name) {
-                columns.push(floor);
-            }
-        }
-
-        // Append one column per referenced-but-unknown name (group keys etc.),
-        // plus any inherited-from-enclosing-scope names.
-        let referenced = collect_referenced_columns(dag);
-        for name in referenced.iter().chain(inherited) {
-            if !columns.iter().any(|c| c.name == *name) {
-                columns.push(Field::plain(name.clone(), DataType::Utf8, true));
-            }
-        }
-
-        let time_index = columns.iter().position(|c| c.name == "ts");
-        Schema {
-            fields: columns,
-            time_index,
-            unique_keys: Vec::new(),
-            // Usage-derived (schemaless PromQL): the metric's full label set is
-            // open and runtime-only, so this lists only what the query references.
-            closed: false,
-        }
-    }
-}
-
-/// The conventional PromQL leaf shape: `(ts: Timestamp, value: Float64)`.
-fn default_leaf_columns() -> Vec<Field> {
-    vec![
-        Field::plain("ts", DataType::Timestamp, false),
-        Field::plain("value", DataType::Float64, false),
-    ]
-}
-
-/// Push a `ColumnRef`'s bare name (the schema-seedable identifier). `Qualified`
-/// collapses to its `name`; `SampleValue`/`Wildcard` carry no name.
-fn push_ref_name(c: &ColumnRef, out: &mut Vec<String>) {
-    match c {
-        ColumnRef::Named(n) => out.push(n.clone()),
-        ColumnRef::Qualified { name, .. } => out.push(name.clone()),
-        ColumnRef::SampleValue | ColumnRef::Wildcard => {}
-    }
-}
-
-/// The leftmost `Scan`'s source name in a canonical (`UnresolvedQueryExpr`) DAG —
-/// the [`collect_referenced_columns`] counterpart to what a dedicated
-/// `Source` leaf type would carry as a method; the canonical DAG's `Scan`
-/// leaf needs this walk written out instead.
-fn leftmost_scan_name(dag: &UnresolvedQueryExpr) -> Option<&str> {
-    use UnresolvedQueryExpr as QE;
-    match dag {
-        QE::Scan { source, .. } => Some(match source {
-            super::query_expr::Source::TimeSeries { metric } => metric.as_str(),
-            super::query_expr::Source::Table { table_ref } => table_ref.as_str(),
-        }),
-        // A scalar bridge's child is a scalar-sub-language leaf (in practice
-        // always a `Literal`, issue #220) — never a `Scan`, same as
-        // `EvalTimestamp`.
-        QE::PromqlScalarBridge(_) | QE::EvalTimestamp | QE::CurrentTimestamp => None,
-        QE::PromqlVectorFromScalar(child) | QE::PromqlScalarFromVector(child) => {
-            leftmost_scan_name(child)
-        }
-        QE::PromqlRelabel { child, .. }
-        | QE::PromqlInfoEnrich { child, .. }
-        | QE::PromqlSeriesSample { child, .. }
-        | QE::Filter { child, .. }
-        | QE::Project { child, .. }
-        | QE::Aggregate { child, .. }
-        | QE::Dedup { child, .. }
-        | QE::Sort { child, .. }
-        | QE::Limit { child, .. }
-        | QE::PromqlSubquery { child, .. }
-        | QE::TimeRange { child, .. }
-        | QE::TimeShift { child, .. }
-        | QE::SQLWindowFunc { child, .. } => leftmost_scan_name(child),
-        QE::Concat { children, .. } => children.first().and_then(leftmost_scan_name),
-        QE::Join { left, .. } | QE::SetOp { left, .. } | QE::BinaryOp { lhs: left, .. } => {
-            leftmost_scan_name(left)
-        }
-        // The scalar variants (issue #205) never appear as a direct
-        // `leftmost_scan_name` target — every reachable one sits behind a
-        // wrapper field (`Predicate`, `ProjectItem`, …) this walk never
-        // descends into; it only follows the relational skeleton.
-        QE::Column(_)
-        | QE::Literal(_)
-        | QE::Compare { .. }
-        | QE::BoolAnd(_)
-        | QE::BoolOr(_)
-        | QE::Not(_)
-        | QE::IsNull(_)
-        | QE::IsNotNull(_)
-        | QE::Cast { .. }
-        | QE::InList { .. }
-        | QE::FunctionCall { .. }
-        | QE::Arithmetic { .. }
-        | QE::Case { .. } => None,
-    }
-}
-
-/// Collect every distinct column name referenced anywhere in `dag` that
-/// resolves positionally — every place a front end constructing
-/// [`QueryExpr<ColumnRef>`](super::query_expr::QueryExpr) directly (issue
-/// #179) puts a name-based reference: `Scan.predicates`, `Aggregate`'s
-/// `reduction`/`having`/per-measure `col`, `Dedup.cols`, `PromqlSeriesSample.by`,
-/// `Filter.pred`, `Project.cols`, `Sort.keys`/`partition_by`,
-/// `SQLWindowFunc.args`/`partition_by`/`order_by`, `Join.pred`, `PromqlRelabel.value`.
-/// The SchemaResolver seeds these into the usage-derived leaf so positional
-/// resolution downstream is total.
-pub(crate) fn collect_referenced_columns(dag: &UnresolvedQueryExpr) -> Vec<String> {
-    use UnresolvedQueryExpr as QE;
-    fn named(expr: &UnresolvedQueryExpr, out: &mut Vec<String>) {
-        for c in expr.columns_referenced() {
-            push_ref_name(c, out);
-        }
-    }
-    fn group_keys(g: &super::query_expr::GroupKeys<ColumnRef>, out: &mut Vec<String>) {
-        g.keys().iter().for_each(|k| push_ref_name(k, out));
-    }
-    fn measure_cols(measures: &[super::agg_intent::AggIntent<ColumnRef>], out: &mut Vec<String>) {
-        for m in measures {
-            for c in m.input_cols() {
-                push_ref_name(&c, out);
-            }
-        }
-    }
-    fn walk(node: &UnresolvedQueryExpr, out: &mut Vec<String>) {
-        match node {
-            QE::Scan { predicates, .. } => {
-                for super::query_expr::Predicate(p) in predicates {
-                    named(p, out);
-                }
-            }
-            QE::Aggregate {
-                reduction,
-                measures,
-                filters,
-                having,
-                child,
-                ..
-            } => {
-                if let super::query_expr::Reduction::Reduce(by) = reduction {
-                    group_keys(by, out);
-                }
-                measure_cols(measures, out);
-                for super::query_expr::Predicate(f) in filters.iter().flatten() {
-                    named(f, out);
-                }
-                if let Some(super::query_expr::Predicate(h)) = having {
-                    named(h, out);
-                }
-                walk(child, out);
-            }
-            QE::Dedup { cols, child } => {
-                cols.iter().for_each(|c| push_ref_name(c, out));
-                walk(child, out);
-            }
-            QE::PromqlSeriesSample { by, child, .. } => {
-                group_keys(by, out);
-                walk(child, out);
-            }
-            QE::Filter { pred, child } => {
-                named(&pred.0, out);
-                walk(child, out);
-            }
-            QE::Project { cols, child, .. } => {
-                for item in cols {
-                    named(&item.expr, out);
-                }
-                walk(child, out);
-            }
-            QE::Sort {
-                keys,
-                partition_by,
-                child,
-            } => {
-                for k in keys {
-                    named(&k.expr, out);
-                }
-                group_keys(partition_by, out);
-                walk(child, out);
-            }
-            QE::SQLWindowFunc {
-                args,
-                partition_by,
-                order_by,
-                child,
-                ..
-            } => {
-                for a in args {
-                    named(a, out);
-                }
-                group_keys(partition_by, out);
-                for k in order_by {
-                    named(&k.expr, out);
-                }
-                walk(child, out);
-            }
-            QE::PromqlRelabel { value, child, .. } => {
-                named(value, out);
-                walk(child, out);
-            }
-            QE::Join {
-                pred, left, right, ..
-            } => {
-                named(&pred.0, out);
-                walk(left, out);
-                walk(right, out);
-            }
-            QE::EvalTimestamp | QE::CurrentTimestamp => {}
-            // The bridged child is a genuine scalar-sub-language position now
-            // (issue #220) — peel its column refs off with `named`, same as
-            // every other scalar-typed field (`Scan.predicates`,
-            // `Filter.pred`, …). In practice it's always a `Literal`, which
-            // references no columns, so this is a no-op today.
-            QE::PromqlScalarBridge(inner) => named(inner, out),
-            QE::PromqlVectorFromScalar(child) | QE::PromqlScalarFromVector(child) => {
-                walk(child, out)
-            }
-            QE::PromqlInfoEnrich { child, .. }
-            | QE::Limit { child, .. }
-            | QE::PromqlSubquery { child, .. }
-            | QE::TimeRange { child, .. }
-            | QE::TimeShift { child, .. } => walk(child, out),
-            QE::Concat {
-                children,
-                discriminator_unique_key,
-            } => {
-                // Same treatment as `Dedup.cols` above: an own-field
-                // `ColumnRef` must be seeded here too, or a discriminator
-                // column that isn't otherwise referenced anywhere else in
-                // the DAG (plausible — a raw usage-derived label, not one a
-                // `Project`/relabel freshly created) is absent from the
-                // SchemaResolver's usage-derived fallback schema, and
-                // `resolve.rs`'s later `resolve_column_ref` call fails with
-                // `NotFound` for a column the caller correctly named.
-                if let Some(key) = discriminator_unique_key {
-                    push_ref_name(key.discriminator(), out);
-                    key.inner_key().iter().for_each(|c| push_ref_name(c, out));
-                }
-                children.iter().for_each(|c| walk(c, out));
-            }
-            QE::SetOp { left, right, .. } => {
-                walk(left, out);
-                walk(right, out);
-            }
-            QE::BinaryOp { lhs, rhs, .. } => {
-                walk(lhs, out);
-                walk(rhs, out);
-            }
-            // The scalar variants (issue #205) never appear as a direct
-            // `walk` target — every reachable one is peeled off first by
-            // `named` at whichever operator field holds it (`Scan.predicates`,
-            // `Filter.pred`, `Project.cols`, …).
-            QE::Column(_)
-            | QE::Literal(_)
-            | QE::Compare { .. }
-            | QE::BoolAnd(_)
-            | QE::BoolOr(_)
-            | QE::Not(_)
-            | QE::IsNull(_)
-            | QE::IsNotNull(_)
-            | QE::Cast { .. }
-            | QE::InList { .. }
-            | QE::FunctionCall { .. }
-            | QE::Arithmetic { .. }
-            | QE::Case { .. } => {
-                unreachable!("walk reached a scalar QueryExpr variant directly: {node:?}")
-            }
-        }
-    }
-    let mut out: Vec<String> = Vec::new();
-    walk(dag, &mut out);
-    out.sort();
-    out.dedup();
-    out
-}
-
-#[cfg(test)]
-mod tests {
-    use std::rc::Rc;
-
-    use super::super::query_expr::{GroupKeys, Source};
-    use super::*;
-
-    fn src(name: &str) -> UnresolvedQueryExpr {
-        UnresolvedQueryExpr::Scan {
-            source: Source::TimeSeries {
-                metric: name.into(),
-            },
-            predicates: vec![],
-            schema: None,
-        }
-    }
-
-    // Both correlation inputs must seed a usage-derived schema before positional resolution.
-    #[test]
-    fn pearson_corr_inputs_seed_usage_derived_schema() {
-        use crate::pre_asap::{AggIntent, Reduction};
-        let dag = UnresolvedQueryExpr::Aggregate {
-            reduction: Reduction::by(vec![]),
-            measures: vec![AggIntent::PearsonCorr {
-                left: ColumnRef::Named("x".into()),
-                right: ColumnRef::Named("y".into()),
-            }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: Rc::new(src("m")),
-        };
-        assert_eq!(collect_referenced_columns(&dag), vec!["x", "y"]);
-        let schema = SchemaResolver::new().resolve_schema(&dag);
-        assert!(schema.column_id("x").is_some());
-        assert!(schema.column_id("y").is_some());
-    }
-
-    #[test]
-    fn bare_source_yields_ts_value_floor() {
-        let schema = SchemaResolver::new().resolve_schema(&src("m"));
-        assert_eq!(schema.fields.len(), 2);
-        assert_eq!(schema.fields[0].name, "ts");
-        assert_eq!(schema.fields[1].name, "value");
-        assert_eq!(schema.time_index, Some(0));
-    }
-
-    #[test]
-    fn sort_partition_keys_land_in_schema() {
-        // Per-group ranking keys (`topk by (host)` → `Sort.partition_by`) must be
-        // seeded into the usage-derived leaf so they resolve positionally.
-        let dag = UnresolvedQueryExpr::Sort {
-            keys: vec![super::super::query_expr::SortKey {
-                expr: UnresolvedQueryExpr::Column(ColumnRef::SampleValue),
-                ascending: false,
-                nulls_first: false,
-            }],
-            partition_by: GroupKeys::by(vec![ColumnRef::Named("host".into())]),
-            child: Rc::new(src("hits")),
-        };
-        let schema = SchemaResolver::new().resolve_schema(&dag);
-        assert!(schema.column_id("host").is_some());
-    }
-
-    /// Issue #228 review: a `Concat`'s `discriminator_unique_key` columns —
-    /// even one referenced nowhere else in the DAG — must be seeded into
-    /// the usage-derived fallback schema, exactly like `Dedup.cols`, or
-    /// `resolve.rs`'s later `resolve_column_ref` fails `NotFound` for a
-    /// column the caller correctly named.
-    #[test]
-    fn concat_discriminator_key_is_seeded_into_the_resolver_schema() {
-        let dag = UnresolvedQueryExpr::concat_with_discriminator(
-            vec![src("m")],
-            ColumnRef::Named("phi".into()),
-            vec![ColumnRef::Named("host".into())],
-        );
-        let schema = SchemaResolver::new().resolve_schema(&dag);
-        assert!(
-            schema.column_id("phi").is_some(),
-            "discriminator column must be seeded"
-        );
-        assert!(
-            schema.column_id("host").is_some(),
-            "inner_key column must be seeded"
-        );
-    }
-
-    #[test]
-    fn inherited_names_are_seeded_alongside_referenced() {
-        // A `BinaryOp` side re-binds against its own sub-DAG, but must still see
-        // an enclosing aggregate's group key (`__name__` / `job`) that appears in
-        // neither side's own matchers (issue #52). `resolve_schema_with_inherited` seeds it.
-        let schema =
-            SchemaResolver::new().resolve_schema_with_inherited(&src("m"), &["__name__".into()]);
-        assert!(schema.column_id("__name__").is_some());
-        // `resolve_schema` (no inheritance) does not conjure it.
-        let plain = SchemaResolver::new().resolve_schema(&src("m"));
-        assert!(plain.column_id("__name__").is_none());
-    }
-
-    #[test]
-    fn custom_catalog_supplies_base_columns() {
-        struct FixedCatalog;
-        impl SchemaCatalog for FixedCatalog {
-            fn columns_for(&self, source: &str) -> Option<Vec<Field>> {
-                (source == "known").then(|| {
-                    vec![
-                        Field::plain("ts", DataType::Timestamp, false),
-                        Field::plain("value", DataType::Float64, false),
-                        Field::plain("datacenter", DataType::Utf8, false),
-                    ]
-                })
-            }
-        }
-        let schema = SchemaResolver::with_catalog(FixedCatalog).resolve_schema(&src("known"));
-        let dc = schema
-            .column_id("datacenter")
-            .and_then(|id| schema.fields.get(id));
-        assert!(matches!(dc, Some(c) if !c.nullable));
-    }
-}
diff --git a/crates/types/tests/planner_vocabulary.rs b/crates/types/tests/planner_vocabulary.rs
index ae8a72711..2ba817861 100644
--- a/crates/types/tests/planner_vocabulary.rs
+++ b/crates/types/tests/planner_vocabulary.rs
@@ -1,6 +1,5 @@
 use asap_types::ir::export::WindowEdgeCompatibility;
 use asap_types::post_asap::{validate_pane_coverage, PaneLayout, WindowEdgeCoverage};
-use asap_types::pre_asap::{SchemaResolver, Source, UnresolvedQueryExpr};
 use asap_types::resources::{PhysicalHandoffBytes, PhysicalHandoffKind};
 
 // Renamed pane APIs still read and emit the deployed wire contract.
@@ -29,18 +28,11 @@ fn window_edge_names_preserve_wire_values() {
     );
 }
 
-// External consumers can use the new resolver and resource names without changing behavior.
+// External consumers can use the new resource names without changing behavior.
+// (The schema-resolver half moved with the resolver to `asap-frontend-common`;
+// `schema_resolver::tests::bare_source_yields_ts_value_floor` covers it.)
 #[test]
-fn renamed_schema_and_handoff_apis_are_public() {
-    let dag = UnresolvedQueryExpr::Scan {
-        source: Source::TimeSeries {
-            metric: "requests".into(),
-        },
-        predicates: vec![],
-        schema: None,
-    };
-    let schema = SchemaResolver::new().resolve_schema(&dag);
-    assert!(schema.column_id("value").is_some());
+fn renamed_handoff_apis_are_public() {
     let bytes = PhysicalHandoffBytes {
         network_bytes: 12,
         materialization_bytes: 4,
diff --git a/crates/types/tests/structure_contract.rs b/crates/types/tests/structure_contract.rs
index d7c144f4e..bebdadb18 100644
--- a/crates/types/tests/structure_contract.rs
+++ b/crates/types/tests/structure_contract.rs
@@ -65,7 +65,7 @@ fn values_contract_is_checked() {
 }
 /// Scalar typing validates every branch and never assigns placeholder types.
 #[test]
-fn scalar_type_ruless_fail_closed() {
+fn scalar_type_rules_fail_closed() {
     for expr in [
         ScalarExpr::Column(99),
         ScalarExpr::FunctionCall {

From 5be51a276abcc9f24108d77de76bd0b87f2b1839 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 20:44:06 +0000
Subject: [PATCH 40/48] docs: describe the unified operator IR instead of the
 removed legacy IRs

Re-applies the documentation half of the earlier legacy cleanup (#543) on
the revised stack, resolving conflicts in favor of the current text where
it is newer.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 docs/design_docs/architecture/README.md       |   5 +-
 .../architecture/asap-aware-mapping.md        |   2 +-
 .../evidence-dependent-candidates.md          |   8 +-
 .../architecture/input-output-workflow.md     |  21 +-
 .../architecture/metricsql-frontend.md        |  13 +-
 .../architecture/physical-plan-integration.md |  64 ++--
 .../architecture/planner-runtime-contract.md  |   4 +-
 ...d_interface_with_pluggable_optimization.md |   2 +-
 docs/design_docs/concepts/accuracy-models.md  |  14 +-
 docs/design_docs/concepts/post-asap-ir.md     | 201 +++++++++----
 docs/design_docs/concepts/pre-asap-ir.md      |  11 +-
 .../ddsketch-quantile-ratios.md               |   2 +-
 .../proposals/asapquery-rule-coverage.md      |   6 +-
 .../design_docs/proposals/planner-layering.md |   2 +-
 .../asap-aware-mapping-architecture.md        |  28 +-
 .../asap-aware-mapping-contracts.md           |  63 ++--
 .../develop_docs/extend-asap-aware-mapping.md | 101 ++++---
 docs/develop_docs/library-api.md              |  74 ++---
 .../metrics-observability-corpora.md          |  12 +-
 docs/develop_docs/native-promql-inputs.md     |   2 +-
 docs/develop_docs/offline-sketch-evidence.md  |   6 +-
 .../develop_docs/physical-compile-coverage.md |  34 +--
 .../planner-vocabulary-migration.md           |   4 +-
 docs/develop_docs/pre-asap-ir.md              | 282 ++++++++++++++----
 .../target-candidate-api-migration.md         |  25 +-
 docs/user_guide_docs/run-a-query.md           |   6 +-
 26 files changed, 633 insertions(+), 359 deletions(-)

diff --git a/docs/design_docs/architecture/README.md b/docs/design_docs/architecture/README.md
index 8b936eafe..e5f8ff2e7 100644
--- a/docs/design_docs/architecture/README.md
+++ b/docs/design_docs/architecture/README.md
@@ -17,7 +17,7 @@ flowchart TD
     W["PlanningWorkload: query demand + optional data facts"]
     F["Frontend dependencies: SQL catalog or PromQL time"]
     E["Strategy, accuracy model, and applicable evidence"]
-    PRE["Frontend lowering → canonical Pre-ASAP QueryExpr roots"]
+    PRE["Frontend lowering → canonical Pre-ASAP OperatorNode roots"]
     SEARCH["Whole-workload candidate search: sharing, legality, accuracy"]
     SPACE["CandidateLogicalASAPDAGs: compact logical candidate DAG space"]
     RANK["Optional cost_sorted: ranked inspection view"]
@@ -58,7 +58,8 @@ an unsupported physical alternative into a deployable plan.
 
 | Area | Main crate or module | Responsibility |
 |---|---|---|
-| Shared IR | `asap-types` | Pre-ASAP and Post-ASAP expressions, schemas, workloads, guarantees, and exported plan data |
+| Shared IR | `asap-types` | The unified operator IR (`ir`: one `OperatorNode` before and after ASAP optimization), schemas, workloads, guarantees, and exported plan data |
+| Front-end common | `frontend-common` | Name-based `UnresolvedOp` tree shared by the front ends, and `resolve_root` into the operator IR |
 | Query frontends | `frontend-sql`, `frontend-promql`, `frontend-metricsql` | Parse source languages and produce canonical Pre-ASAP queries |
 | ASAP-aware mapping | `asap-aware-mapping` | Candidate generation, CSE, legality, accuracy propagation, lifecycle expansion, costing, and ranking |
 | Developer inspection | `devtools` | Expose planner DAGs, alternatives, decisions, and explanations for inspection |
diff --git a/docs/design_docs/architecture/asap-aware-mapping.md b/docs/design_docs/architecture/asap-aware-mapping.md
index 2600fc42d..78d3e0f9d 100644
--- a/docs/design_docs/architecture/asap-aware-mapping.md
+++ b/docs/design_docs/architecture/asap-aware-mapping.md
@@ -44,7 +44,7 @@ budgets; deployment belongs to a later stage.
 - **Replacement Sub-DAG**: A candidate post-ASAP sub-DAG to replace a target sub-DAG. For example, a quantile aggregation may have KLL, DDSketch, and exact aggregation as alternatives.
 - **ReplacementStrategy**: A rule to recognize a target Sub-DAG and produces one or more valid replacement Sub-DAGs.
 - **Candidate Plan**: A complete post-ASAP plan formed by choosing compatible replacement alternatives across the plan.
-- **Maintained population**: A multiset of qualifying records retained across evaluations and updated as members enter, change, leave or expire; multiple readouts can share this state.
+- **Maintained population**: A multiset of qualifying records retained across evaluations and updated as members enter, change, leave or expire; multiple evaluations can share this state.
 - **Cost Model**: A model used to compare valid candidate plans according to criteria such as storage, update cost, query latency, and accuracy.
 
 The distinction between **ReplacementStrategy** and **Candidate Plan** is important. A ReplacementStrategy generates alternatives at a decision point, while a candidate plan is a complete plan that combines choices across all relevant decision points.
diff --git a/docs/design_docs/architecture/evidence-dependent-candidates.md b/docs/design_docs/architecture/evidence-dependent-candidates.md
index abdfbdb90..9dcbba3fd 100644
--- a/docs/design_docs/architecture/evidence-dependent-candidates.md
+++ b/docs/design_docs/architecture/evidence-dependent-candidates.md
@@ -15,7 +15,7 @@ target)` returns `true`. **Uncertified** means Planner cannot make that claim:
 the guarantee is absent, contains unknown terms, or is known not to meet the
 target. An uncertified summary may still be a well-formed logical candidate;
 this label says nothing about whether the backend can physically execute it.
-The exact `KeepPreAsap` path has an exact guarantee.
+The exact path (the pre-ASAP sub-DAG kept by `retain_exact`) has an exact guarantee.
 
 | State | Planner representation | Consequence / next step |
 |---|---|---|
@@ -88,7 +88,7 @@ The default `global_selection()` skips summaries that
 `has_missing_accuracy_evidence()` identifies as uncertified. Its
 `GlobalSelection::assemble_selected_dag()` result is a selected logical plan,
 not an instruction to deploy every candidate in `CandidateLogicalASAPDAGs`. If no alternative
-is chosen at a site, DAG assembly retains the exact `KeepPreAsap` path. The
+is chosen at a site, DAG assembly retains the exact pre-ASAP sub-DAG. The
 backend can inspect alternatives, apply its own evidence and policy, then choose a
 physically supported one; it must not equate candidate presence with approval.
 Models may explicitly opt into qualitative candidate ranking when no
@@ -109,7 +109,7 @@ backend.
 | PromQL input | Before this PR | After this PR |
 |---|---|---|
 | `count by(job)(up)` with an ε/δ target | Hydra's shared CMS/CountSketch alternatives are absent: missing shared-grid bounds make the strategy decline the target. | Both Hydra alternatives remain in `CandidateLogicalASAPDAGs` with symbolic unknown bound/probability terms. `has_missing_accuracy_evidence()` is true; default `global_selection()` does not choose either as a certified answer. |
-| `entropy_over_time(m[5m])` with an ε target | The uncalibrated frequency readout has no `SummaryEstimate` candidate. | Its `SummaryEstimate` remains inspectable with `guarantee: None`. Default selection still skips it, so candidate visibility is not an accuracy certificate. |
+| `entropy_over_time(m[5m])` with an ε target | The uncalibrated frequency evaluation has no `SummaryEstimate` candidate. | Its `SummaryEstimate` remains inspectable with `guarantee: None`. Default selection still skips it, so candidate visibility is not an accuracy certificate. |
 | `quantile_over_time(0.9,data[5m]) / quantile_over_time(0.5,data[5m])` with an ε target | The uncertified direct DDSketch ratio is **already** visible because of #449. | Still visible with `guarantee: None`, and still skipped by default selection. This is a regression/control example, not a new candidate introduced by this PR. |
 
 For the first two rows, the observable change is the alternative set delivered
@@ -121,7 +121,7 @@ evidence (for example a failure probability of `1.5`) instead produces a
 
 The corresponding reproducible checks are
 `cargo test -p asap-frontend-promql grouped_count_keeps_uncertified_hydra_candidates_for_backend_review`,
-`cargo test -p asap-frontend-promql uncalibrated_frequency_readouts_do_not_bypass_accuracy_targets`,
+`cargo test -p asap-frontend-promql uncalibrated_frequency_evaluations_do_not_bypass_accuracy_targets`,
 and `cargo test -p asap-integration-tests ddsketch_ratio_without_domain_proof_is_uncertified`.
 All three start from PromQL text and exercise frontend lowering and planning.
 None runs a deployed query.
diff --git a/docs/design_docs/architecture/input-output-workflow.md b/docs/design_docs/architecture/input-output-workflow.md
index 65ee43141..4120811ca 100644
--- a/docs/design_docs/architecture/input-output-workflow.md
+++ b/docs/design_docs/architecture/input-output-workflow.md
@@ -66,12 +66,12 @@ flowchart TD
     D["data_workload: continuous arrival; declared ingestion interval 15 s"]
     T["Frontend argument: now_ms"]
     F["PromQL lowering"]
-    R["One canonical QueryExpr root"]
+    R["One canonical OperatorNode root"]
     S["Candidate search"]
     P["CandidateLogicalASAPDAGs: logical choices for this root"]
     I["cost_sorted: inspect choices"]
     G["global_selection + assemble_selected_dag(root)"]
-    L["One selected Post-ASAP DAG; exact KeepPreAsap if no optimization is selected"]
+    L["One selected Post-ASAP DAG; the exact pre-ASAP sub-DAG if no optimization is selected"]
     X["Extra lifecycle inputs: horizon; update rate; capabilities; comparable summary/raw costs"]
     H["Summary-maintenance-lifecycle-aware selection"]
     HM["Assemble one selected DAG and decide summary maintenance"]
@@ -102,7 +102,7 @@ flowchart LR
     Q["query_batch: SELECT COUNT(*) FROM metrics; invocations 1; AdHoc"]
     C["SqlCatalog: resolves metrics and its columns"]
     F["SQL lowering"]
-    R["One QueryExpr root"]
+    R["One OperatorNode root"]
     P["Candidate search → CandidateLogicalASAPDAGs"]
     Q --> F
     C --> F
@@ -214,7 +214,7 @@ fields expand as follows:
 | `TimeSelection` | `lookback` | Optional event-time duration selected before the upper bound. |
 | `TimeSelection` | `as_of` | Optional fixed upper-bound timestamp; `None` means planning/evaluation time. |
 
-Frontend lowering produces one Pre-ASAP `QueryExpr` root for each normalized
+Frontend lowering produces one Pre-ASAP `Rc<OperatorNode>` root for each normalized
 query entry. The caller must retain each root's association with its workload
 entry for later recurrence and lifecycle planning.
 
@@ -334,7 +334,7 @@ below. A future higher-level API could hide `CandidateLogicalASAPDAGs` behind th
 the current interface lets an integrator own them. DAG assembly connects choices
 after selection and does not replace this candidate interface.
 
-Here, a **root** is the top-level `Rc<QueryExpr>` for a workload query. A
+Here, a **root** is the top-level `Rc<OperatorNode>` for a workload query. A
 **target** is any discovered sub-DAG that may be replaced, including roots.
 For `count(up) + 1`, the addition is a root and `count(up)` can be an inner
 target. `TargetSubDAGCandidates` holds the alternatives for one such target.
@@ -361,7 +361,7 @@ All paths start by lowering the workload and searching for candidates:
 
 ```text
 PlanningWorkload + frontend dependencies + planning models/evidence
-    -> frontend lowering: one QueryExpr root per normalized query entry
+    -> frontend lowering: one OperatorNode root per normalized query entry
     -> search_workload_with_targets
     -> CandidateLogicalASAPDAGs
 ```
@@ -390,7 +390,7 @@ The return type is `Vec<RankedTargetSubDAGCandidates<'_>>`; each element has thi
 
 ```rust
 struct RankedTargetSubDAGCandidates<'a> {
-    target: &'a Rc<QueryExpr>,
+    target: &'a Rc<OperatorNode>,
     consumer_count: usize,
     candidates: Vec<&'a ReplacementSubDAG>,
     costs: Vec<f64>, // costs[i] describes candidates[i]
@@ -430,7 +430,8 @@ the result for one query root.
 | **Output:** one selected logical [Post-ASAP DAG](../concepts/post-asap-ir.md) per query root |
 
 Each output DAG specifies the chosen operators, parameters, and accuracy
-guarantees. Its root is represented by `Rc<SummaryNode>`; the
+guarantees. Its root is an `Rc<OperatorNode>` (the same IR as the input,
+with some nodes now ASAP operators) and carries no execution timing yet; the
 [API reference](../../develop_docs/library-api.md#api-definition-and-example)
 describes the function signatures and return handling.
 
@@ -456,7 +457,7 @@ there is no need to run the ordinary selection/assembly workflow first:
    `Result<Option<SummaryMaintenanceLifecyclePlan>, SummaryMaintenanceLifecycleAssemblyError>`.
    When a summary does not beat a
    known raw cost, or a required comparable cost is unavailable, the result
-   retains the exact `KeepPreAsap` root and no summary deployments.
+   retains the exact pre-ASAP root (`retain_exact`) and no summary deployments.
 
 As in ordinary selection, one selection call serves the workload and assembly
 is per root. The second helper calls `assemble_selected_dag` internally; callers
@@ -489,7 +490,7 @@ facts remain unknown rather than being treated as zero.
 The per-query output, `SummaryMaintenanceLifecyclePlan`, **contains** the
 Post-ASAP DAG rather than being a parallel representation. It records:
 
-* the assembled Post-ASAP DAG root (`Rc<SummaryNode>`);
+* the assembled Post-ASAP DAG root (`Rc<OperatorNode>`, with execution timing written);
 * lifecycle choices for summary state;
 * planning horizon and expected reads/updates;
 * selected window implementation and guarantees;
diff --git a/docs/design_docs/architecture/metricsql-frontend.md b/docs/design_docs/architecture/metricsql-frontend.md
index ddc463239..ffb45b728 100644
--- a/docs/design_docs/architecture/metricsql-frontend.md
+++ b/docs/design_docs/architecture/metricsql-frontend.md
@@ -9,16 +9,17 @@ on VictoriaMetrics and models MetricsQL syntax directly, including `WITH`,
 rollup expressions, step-relative durations, MetricsQL binary operators,
 aggregate limits, or-delimited matchers, and `keep_metric_names`.
 
-The frontend walks that AST directly and emits the existing canonical
-`QueryExpr`. It does not add MetricsQL fields to `QueryExpr`, SDS descriptors,
-or the physical summary DAG.
+The frontend walks that AST directly into the shared name-based `UnresolvedOp`
+tree (`asap-frontend-common`) and calls `resolve_root`, which returns the
+canonical `Rc<OperatorNode>` DAG. It does not add MetricsQL fields to the
+operator IR, SDS descriptors, or the physical summary DAG.
 
 ```text
 MetricsQL source
       |
 MetricsqlExpr (extension semantics retained)
       |
-canonical QueryExpr
+UnresolvedOp tree --resolve_root--> canonical OperatorNode DAG
       |
 existing ASAP-aware mapping and physical Summary DAG
 ```
@@ -33,8 +34,8 @@ existing ASAP-aware mapping and physical Summary DAG
 | Common rollups: rate/increase/derivatives and statistical `*_over_time` | Existing per-entity canonical intents over the lowered range. |
 | PromQL arithmetic, comparison, and set binary operators without modifiers | Existing canonical `BinaryOp`. |
 | `default_rollup(selector[range])` | Lower to `Aggregate(LastOverTime)` over the explicit `TimeRange`. |
-| `default_rollup(selector)` | Reject for exact fallback because the implicit lookbehind window depends on the runtime evaluation step, which is not a property of canonical `QueryExpr`. |
-| `expr keep_metric_names` | Parsed natively, then rejected for exact fallback because canonical `QueryExpr` does not carry metric-name lineage. |
+| `default_rollup(selector)` | Reject for exact fallback because the implicit lookbehind window depends on the runtime evaluation step, which is not a property of the canonical operator IR. |
+| `expr keep_metric_names` | Parsed natively, then rejected for exact fallback because the canonical operator IR does not carry metric-name lineage. |
 | `if`, `ifnot`, `default`, aggregate `limit`, or-delimited matchers, binary match modifiers | Parsed natively and rejected until the canonical executor has the exact semantics. |
 | `WITH` | Expanded by the native parser; the expanded expression lowers when every resulting node is supported. |
 
diff --git a/docs/design_docs/architecture/physical-plan-integration.md b/docs/design_docs/architecture/physical-plan-integration.md
index 057ba7c17..9bd6ddbc5 100644
--- a/docs/design_docs/architecture/physical-plan-integration.md
+++ b/docs/design_docs/architecture/physical-plan-integration.md
@@ -5,14 +5,13 @@
 This document defines the boundary between ASAPPlanner's logical plans,
 physical lowering, statistics resolution, and analytical resource estimation.
 It answers which representation is authoritative at each stage and prevents
-the cost model from being coupled directly to either logical IR.
+the cost model from being coupled directly to the logical IR.
 
 The integration pipeline is:
 
 ```text
-pre-ASAP QueryExpr  ─┐
-                     ├─ physical lowering ─> PhysicalOperator DAG
-post-ASAP SummaryExpr┘                              │
+logical OperatorNode DAG ─ physical lowering ─> PhysicalOperator DAG
+(NonASAPOp + ASAPOp nodes)                              │
                                                     v
                                            OperatorStatistics
                                                     │
@@ -30,8 +29,8 @@ Each representation is authoritative for a different concern:
 
 | Representation | Authoritative concern |
 |---|---|
-| `QueryExpr` | Original exact query semantics: sources, predicates, relational and PromQL operations, and output shape. |
-| `SummaryExpr` | Logical summary semantics: selected family, grouping strategy, summary composition, and summary readout. |
+| `NonASAPOp` nodes | Exact query semantics: sources, predicates, relational and PromQL operations, and output shape. |
+| `ASAPOp` nodes | Logical summary semantics: selected family, grouping strategy, summary composition, and summary evaluation. |
 | `PhysicalOperator` DAG | Selected executable algorithms, their configuration, physical identity, edges, and execution multiplicity. |
 | `OperatorStatistics` | Workload-dependent evidence required by each selected physical operator's resource formula. |
 | `ResourceEstimate` | Estimated CPU operations, peak live memory, and physical source/disk reads over one comparison scope. |
@@ -39,7 +38,7 @@ Each representation is authoritative for a different concern:
 `PhysicalOperator` is therefore the source of truth for the operator vocabulary
 consumed by analytical costing. `OperatorStatistics` corresponds one-to-one
 with that vocabulary. It must not independently invent operator kinds or copy
-all variants from either logical IR.
+all variants from the logical IR.
 
 The canonical physical-plan types should live at a neutral boundary shared by
 lowering, costing, explanation, and downstream compilation. Their conceptual
@@ -51,7 +50,7 @@ being established.
 
 One logical operation may choose between algorithms or expand into a physical
 sub-DAG. Conversely, one physical operator may implement nodes originating
-from either logical IR.
+from either operator category (`NonASAPOp` or `ASAPOp`).
 
 Examples include:
 
@@ -61,14 +60,14 @@ Examples include:
   supported join algorithm.
 - `SummaryAgg` may lower to an exact accumulator build, CMS build, KLL build,
   or another physical summary algorithm selected by the candidate.
-- `SummaryEstimate` must lower to a readout operator compatible with the
+- `SummaryEstimate` must lower to a evaluation operator compatible with the
   concrete summary state it consumes.
 - shared logical sub-DAGs become shared physical nodes only when they refer to
   the same physical identity and compatible evidence.
 
-For this reason, aligning `OperatorStatistics` directly with `QueryExpr` would
-lose post-ASAP summary implementations, while aligning it directly with
-`SummaryExpr` would lose raw query operators and physical algorithm choices.
+For this reason, aligning `OperatorStatistics` directly with the logical
+operators would lose physical algorithm choices, and with only one category
+would lose either summary implementations or raw query operators.
 
 ## Lowering obligations
 
@@ -91,14 +90,16 @@ its modeled descendants is invalid because it undercounts the candidate.
 
 ### Pre-ASAP lowering
 
-`KeepPreAsap` recursively lowers its contained `QueryExpr`. Typical physical
+Every `NonASAPOp` node lowers recursively, whether it is in a raw query or
+kept exact inside a post-ASAP plan. Typical physical
 operators include scans, filters, projections, hash aggregates, joins,
 ordering, bounded Top-K, limits, and PromQL-specific operators. The selected
 physical algorithm, rather than the logical spelling, determines the formula.
 
 ### Post-ASAP lowering
 
-Every `SummaryExpr` operation also needs explicit physical realization:
+Every `ASAPOp` node, and every exact operator composed with one, also needs
+explicit physical realization:
 
 | Logical summary operation | Required physical realization |
 |---|---|
@@ -107,12 +108,14 @@ Every `SummaryExpr` operation also needs explicit physical realization:
 | `SummaryMerge` | merge operator over compatible concrete summary states |
 | `SummarySubtract` | subtract operator supported by the selected state representation |
 | `SummaryDelete` | physical deletion/update operator supported by the selected representation |
-| `SummaryEstimate` | family- and query-specific readout operator |
-| `KeepPreAsap` | recursive lowering of the contained `QueryExpr` |
-| `BinaryOp` | binary evaluation preserving operand order, execution timing and any typed finite/relative-division guard |
-| `ValueOperation` | concrete realization of the value operation with its required execution timing and data state |
-| `RelationalJoin` | concrete row-join algorithm preserving join kind and predicate |
-| `RelationalJoin` with `JoinKind::Semi` | retain left rows matching explicit right-side keys; candidate pruning carries completeness evidence and ordinary TopK ranks the result |
+| `SummaryEstimate` | family- and query-specific evaluation operator |
+| `FinalizeExactAccumulator` | exact-state finalization before value consumers |
+| `MaintainPopulation` / `EvaluatePopulation` | maintained-population update and its aggregate or TopK-prefix evaluation |
+| retained `NonASAPOp` sub-DAG | recursive lowering of the exact operators (see above) |
+| `BinaryOp` | binary evaluation preserving operand order, the node's execution timing and any typed finite/relative-division guard |
+| `Project` / `Filter` / `Sort` / `Limit` / `Aggregate` over a evaluation | concrete realization at the node's execution timing and data state |
+| `Join` | concrete row-join algorithm preserving join kind and predicate |
+| `Join` with `JoinKind::Semi` | retain left rows matching explicit right-side keys; candidate pruning carries completeness evidence and ordinary TopK ranks the result |
 
 This table is a completeness requirement, not a claim that every realization
 already exists. Until lowering introduces an explicit physical operator,
@@ -120,13 +123,13 @@ statistics contract, validation rule, and resource formula for an operation,
 a candidate containing it is unavailable.
 
 The streaming integration can consume a complete binding through
-`SummaryNodeEvidence`. That binding is keyed to exact `SummaryNode`
+`SummaryNodeEvidence`. That binding is keyed to exact `OperatorNode`
 identities and uses structured evidence for aggregate state, join, merge,
-subtract, delete, readout, and retained pre-ASAP work. It is a physical
+subtract, delete, evaluation, and retained pre-ASAP work. It is a physical
 evidence boundary, not automatic physical lowering: a deployment must still
 select each concrete implementation and provide all edges, resource facts,
 multiplicities, source ownership, and stable physical identities. The planner
-fails closed when any reachable `SummaryExpr` node lacks that binding.
+fails closed when any reachable ASAP node lacks that binding.
 
 The raw/query portion of a streaming comparison remains a `PhysicalDAG` using
 the canonical `PhysicalOperator` and `OperatorStatistics` pairing. Summary
@@ -137,7 +140,7 @@ summary-family semantics.
 
 Lifecycle choice affects the physical DAG but does not replace it. Ephemeral,
 prepared, shared, and continuously maintained alternatives determine when
-build, update, readout, merge, subtract, or delete nodes execute. The physical
+build, update, evaluation, merge, subtract, or delete nodes execute. The physical
 operators still determine how each execution consumes CPU, memory, and I/O.
 
 ## Statistics contract
@@ -427,7 +430,7 @@ recovering average semantics from query text.
 
 ### Candidate pruning is a sub-DAG
 
-Candidate-based TopK uses a summary key readout, a general semi-join over
+Candidate-based TopK uses a summary key evaluation, a general semi-join over
 explicit matching key columns, grouped Sort by the authoritative score, and
 grouped Limit. Sort and Limit carry the same partition keys.
 The join preserves authoritative left-side values and does not rank or limit
@@ -440,10 +443,12 @@ fields. The phase assignment API updates producer edge states and rejects an
 ingestion computation that depends on query-time work. Deployment capability,
 storage readiness, schemas and approximation guarantees remain separate checks.
 
-Post-ASAP DAG wire version 4 removes the special membership operator, its edge
+Post-ASAP DAG wire version 4 removed the special membership operator, its edge
 roles and the duplicate operator phase fields without compatibility aliases.
+Version 6 (current) exports one node per operator: retained exact operators are
+`Relational` nodes, not embedded sub-DAGs.
 
-Post-ASAP DAG wire version 6 adds a per-measure row predicate to the aggregate
+Post-ASAP DAG wire version 7 adds a per-measure row predicate to the aggregate
 operators (#466): `filters` on the exact aggregate value operation, parallel to
 its measures, and `filter` on `SummaryAgg`, gating which rows update the
 summary state. The version bump makes an older reader fail loudly instead of
@@ -465,8 +470,9 @@ a numeric entity key is not a score. Exact accumulator inputs are explicitly
 finalized before row operators consume them. None of these operations proves
 candidate completeness; that evidence belongs to the semi-join's pruning step.
 
-The semantic `SummaryExpr` constructors still propose an initial execution
-layout. Uniform phase assignment applies to the exported post-ASAP DAG;
+The logical DAG carries no execution layout: `apply_lifecycle_timings` writes
+each node's timing from the lifecycle assignment before export. Uniform phase
+assignment applies to the exported post-ASAP DAG;
 it is not a claim that every deployment has implemented every placement.
 
 
diff --git a/docs/design_docs/architecture/planner-runtime-contract.md b/docs/design_docs/architecture/planner-runtime-contract.md
index 58e3f06b6..5dfe5f760 100644
--- a/docs/design_docs/architecture/planner-runtime-contract.md
+++ b/docs/design_docs/architecture/planner-runtime-contract.md
@@ -53,7 +53,7 @@ backend still owns how the selected algorithms are physically realized.
 The same contract applies when ASAPPlanner selects a summary algorithm. Planner
 can choose KLL rather than DDSketch, while downstream chooses the concrete KLL
 implementation and runtime configuration that satisfies the selected parameter
-and accuracy contract. Empirical KLL error, update work, state size, and readout
+and accuracy contract. Empirical KLL error, update work, state size, and evaluation
 work observed on a particular workload can be fed back as evidence for later
 Planner comparisons.
 
@@ -124,7 +124,7 @@ The ASAPQuery configuration and MIP formulations can supply physical
 alternatives and coefficients. Their general principles also inform Planner
 costing: arrival rate scales ingestion work, overlapping active windows
 multiply update work and live state, retained windows consume memory, and
-merge/subtract/readout work scales with query recurrence. Disagreement between
+merge/subtract/evaluation work scales with query recurrence. Disagreement between
 formulations must become distinct explicit alternatives, not hidden assumptions
 in one cost formula.
 
diff --git a/docs/design_docs/architecture/updated_interface_with_pluggable_optimization.md b/docs/design_docs/architecture/updated_interface_with_pluggable_optimization.md
index 72e626a2e..4820b6226 100644
--- a/docs/design_docs/architecture/updated_interface_with_pluggable_optimization.md
+++ b/docs/design_docs/architecture/updated_interface_with_pluggable_optimization.md
@@ -185,7 +185,7 @@ for (index, entry) in workload.query_workload.entries().enumerate() {
     let accuracy = entry.requirements.accuracy.target();
     let expr = lower_sql_dialect(&entry.query.0, &catalog, dialect.clone(), accuracy.clone())
         .await?;
-    roots.push((index, Rc::new(expr), Some(accuracy)));
+    roots.push((index, expr, Some(accuracy)));
     entry_indices.push(index);
 }
 
diff --git a/docs/design_docs/concepts/accuracy-models.md b/docs/design_docs/concepts/accuracy-models.md
index 5353ef9ef..baeadbe9e 100644
--- a/docs/design_docs/concepts/accuracy-models.md
+++ b/docs/design_docs/concepts/accuracy-models.md
@@ -69,7 +69,7 @@ query text or cost estimates.
 flowchart TD
     Request[Query semantics and accuracy target] --> Generate[Generate candidates and size parameters]
     Evidence[Scoped source contracts and evidence] --> Generate
-    Generate --> Local[Derive local readout guarantees]
+    Generate --> Local[Derive local evaluation guarantees]
     Evidence --> Local
     Local --> Compose[Propagate guarantees through the DAG]
     Evidence --> Compose
@@ -100,7 +100,7 @@ is ready, or that a complete deployment cost is available.
 
 ## Local estimator models and parameter sizing
 
-A local model describes a specific readout of a specific estimator with
+A local model describes a specific evaluation of a specific estimator with
 committed parameters and applicable assumptions. A family name or a parameter
 such as HLL precision is not, by itself, a confidence certificate.
 
@@ -121,8 +121,8 @@ The built-in models currently include:
 | CMS | L1-normalized frequency bound from width and depth; does not by itself certify TopK membership |
 | CountSketch | L2-normalized frequency bound and median concentration bound, requiring valid odd depth |
 | KMV / Theta | Parameter-derived cardinality bounds using the registered variance/Chebyshev model at 99% confidence |
-| UnivMon | Exact unit-update total for the supported readout; no universal guarantee for all its statistics |
-| Other families/readouts | No default certificate where no accuracy model is registered |
+| UnivMon | Exact unit-update total for the supported evaluation; no universal guarantee for all its statistics |
+| Other families/evaluations | No default certificate where no accuracy model is registered |
 
 This table describes Planner's registered contracts, not independent
 mathematical verification of every estimator or permission to substitute
@@ -214,7 +214,7 @@ an observation into a guarantee.
 
 A deployment supplies `EstimatorContract::ClassicHll` for the complete aggregate
 expression. It asserts the classic estimator, independent uniform bucket
-hashing and an enforced maximum distinct population per readout, including
+hashing and an enforced maximum distinct population per evaluation, including
 all merged panes. Planner combines this contract with the query or allocated
 local target, selects a supported precision, derives the guarantee and uses
 the normal propagation and selection checks.
@@ -290,7 +290,7 @@ accuracy/
 ├── allocation.rs       # End-to-end budget allocation
 ├── reconciliation.rs   # Accuracy coordination across consumers
 └── estimators/
-    ├── mod.rs          # Family/readout dispatch and source-contract integration
+    ├── mod.rs          # Family/evaluation dispatch and source-contract integration
     ├── kll.rs
     ├── ddsketch.rs
     ├── hll.rs          # Generic HLL and bounded Classic HLL
@@ -308,7 +308,7 @@ share the same contract.
 
 Adding an estimator or composition requires:
 
-1. A precisely defined error metric, estimator/readout semantics and assumptions.
+1. A precisely defined error metric, estimator/evaluation semantics and assumptions.
 2. Sizing behavior and a guarantee derived from the committed parameters, including unsupported parameter domains.
 3. Explicit evidence requirements, population scope and provenance.
 4. Propagation rules where supported; rejection or retained unknowns elsewhere.
diff --git a/docs/design_docs/concepts/post-asap-ir.md b/docs/design_docs/concepts/post-asap-ir.md
index 6c9aa1461..8d2e3c5bb 100644
--- a/docs/design_docs/concepts/post-asap-ir.md
+++ b/docs/design_docs/concepts/post-asap-ir.md
@@ -1,22 +1,53 @@
 # Post-ASAP IR
 
 The goal of the post-ASAP IR is to represent operations using ASAP primitives
-such as sketches, exact summaries, samples and wavelets. Post-ASAP IR also
-retains exact Pre-ASAP sub-DAGs and supports operations over summary readouts,
-since only some query operations can be satisfied using summaries.
-
-The lists below cover every current variant of
-[`SummaryExpr`](../../../crates/types/src/post_asap/expr.rs). A node's presence
-in the IR does not imply that every summary family, cost model or downstream
-runtime supports it.
-
-## ASAP-specific nodes operated over a summary structure, not raw data
-
-- `SummaryAgg`: produce summary state from input data using the selected family,
-  parameters, update input, reduction and grouping layout.
-- `SummaryEstimate`: read the requested statistic from summary state and return
-  query values. Exact accumulators can expose results without a separate sketch
-  readout.
+such as sketches, exact summaries, samples and wavelets, while retaining the
+exact query operators that no summary replaces, and supporting operations over
+summary evaluations.
+
+ASAPPlanner has one operator IR before and after ASAP optimization
+([`crates/types/src/ir/`](../../../crates/types/src/ir/)). A post-ASAP plan is
+the same `Rc<OperatorNode>` DAG a front end produced, in which some nodes now
+carry `Operator::ASAP(ASAPOp)` instead of `Operator::NonASAP(NonASAPOp)`. There
+is no wrapper around retained exact work: an unreplaced `Filter`, `Join` or
+`Aggregate` is the same node it was before, and either category can consume
+the other's output. The node structure, the `Schema`, scalar expressions and
+the catalog of non-ASAP operators are described once in the
+[Pre-ASAP IR reference](../../develop_docs/pre-asap-ir.md); this document covers
+what optimization adds: the ASAP operators, the accuracy guarantee, execution
+timing, and the exported DAG.
+
+A node's presence in the IR does not imply that every summary family, cost
+model or downstream runtime supports it.
+
+## ASAP operators
+
+Every variant of [`ASAPOp`](../../../crates/types/src/ir/asap.rs) operates
+over summary state rather than raw data. The summary family, kind/algorithm and
+parameters are committed in the node; the state itself is typed by the
+`FieldDataType` of the output field that carries it (`ExactAggregate`,
+`Sketch`, `Sample`, `Wavelet`, `StatModel`).
+
+Implemented:
+
+- `SummaryAgg { child, family, input, reduction, grouping }`: produce summary
+  state from input rows using the selected family, parameters, update input,
+  reduction and grouping layout. Output: the grouping columns plus one `state`
+  field typed `family`; result kind `State`.
+- `SummaryEstimate { summary_input, query }`: read the requested statistic
+  (`SketchStatistic`) from summary state and return query values in a row-shaped
+  schema.
+- `FinalizeExactAccumulator { child }`: read an exact accumulator's state as
+  its finalized value — the maintenance-to-read boundary before query-time
+  operators consume it.
+- `MaintainPopulation { child, population }`: maintain the full declared
+  population, including membership changes.
+- `EvaluatePopulation { child, evaluation }`: read an aggregate or TopK prefix from a
+  maintained population.
+
+Reserved (migrated but unimplemented; schema derivation, timing and export
+reject them with `UNIMPLEMENTED_ASAP_OP`):
+
 - `SummaryMerge`: merge compatible summary states when the family supports merging.
 - `SummarySubtract`: subtract one summary state from another when supported by
   the selected representation.
@@ -24,62 +55,114 @@ runtime supports it.
   deletion.
 - `SummaryJoin`: combine summary states for join estimation; this is distinct
   from joining ordinary rows.
+- `Extension`: a deployment-defined operator.
 
 The earlier draft listed `SummaryCreate` and `SummaryInsert`. These are not
-separate variants in the current IR. `SummaryAgg` describes the state-producing
+separate variants. `SummaryAgg` describes the state-producing
 computation and its update input. The
 [summary-maintenance lifecycle](../proposals/asap-aware-mapping/workload-demand-and-summary-lifecycle.md)
 separately describes when state is created, retained, shared, updated and retired.
 Physical binding and runtime execution implement the actual build and update
-operations. This is not a one-to-one rename of the old nodes, and not every
-summary family supports incremental maintenance.
-
-## Exact work and composition nodes
-
-- `KeepPreAsap`: retain an exact Pre-ASAP sub-DAG when it is not rewritten.
-- `BinaryOp`: combine independently planned operands with the specified binary
-  semantics and execution timing.
-- `ValueOperation`: apply aggregate, exact-function, population, projection,
-  filter, sort, limit or extension semantics with explicit execution timing.
-- `RelationalJoin`: join row-producing children using the specified join kind
-  and predicate.
-- Candidate pruning uses `RelationalJoin` with `JoinKind::Semi` and an explicit
+operations. Not every summary family supports incremental maintenance.
+
+## Exact work and composition
+
+Exact work is represented by the ordinary operators, unchanged:
+
+- A sub-DAG the planner does not rewrite keeps its `NonASAPOp` nodes. Plan
+  assembly marks such a sub-DAG with an exact `ResultGuarantee`
+  (`asap_aware_mapping::replacement::retain_exact`); a sub-DAG with no ASAP
+  operator and no guarantee is a logical rewrite candidate that has not been
+  assessed yet (`is_logical_rewrite`).
+- `BinaryOp` combines independently planned operands. Summary planning may set
+  its typed division guards (`checked_finite_division`,
+  `checked_relative_division`); the operator's timing comes from the lifecycle
+  assignment, not from the operator.
+- Aggregate, projection, filter, sort and limit over a evaluation are the ordinary
+  `Aggregate`, `Project`, `Filter`, `Sort` and `Limit` operators reading an ASAP
+  node. Exact-accumulator state may pass through the projection-like
+  operators unchanged; a value consumer needs a `FinalizeExactAccumulator`
+  boundary first.
+- Candidate pruning uses `Join` with `JoinKind::Semi` and an explicit
   equality predicate on key columns. The left input supplies authoritative
-  values; the right input supplies keys. Grouped Sort followed by grouped Limit ranks
-  and selects the joined rows. Completeness evidence belongs to pruning, not ranking.
+  values; the right input supplies keys. Grouped `Sort` followed by grouped
+  `Limit` (both with the same `partition_by`) ranks and selects the joined
+  rows. Completeness evidence belongs to pruning, not ranking.
 
-A `SummaryNode` carries its expression, schema and optional result guarantee.
+Every `OperatorNode` carries its schema and an optional `ResultGuarantee`.
 State and query values have different contracts. Exact operations over
-approximate readouts still require composed accuracy guarantees. See the
+approximate evaluations still require composed accuracy guarantees. See the
 [accuracy implementation companion](../../develop_docs/end-to-end-accuracy-guarantees.md)
 and [physical-plan integration](../architecture/physical-plan-integration.md)
 for the corresponding correctness and realization requirements.
 
-## In-memory and exported DAG forms
-
-The Pre-ASAP DAG and the Post-ASAP DAG are both logical: they describe what is
-computed, not which physical operators execute it. The Post-ASAP DAG has two
-forms of the same content. Planning builds and shares `SummaryNode` DAGs.
-`compile_post_asap_dag` converts a selected DAG into a
-[`PostAsapDAG`](../../../crates/types/src/post_asap/post_asap_dag.rs) with
-stable node IDs and typed edges; `PostAsapDAGDocument` is its versioned wire
-envelope. Physical compilation consumes `PostAsapDAG` and produces a separate
-physical DAG.
-
-## Execution phase
+## Execution timing
 
 An operator defines what computation happens. The plan decides when it
 happens: **ingestion time** or **query time**. Operator identity must not imply
 one of these phases. Backend capability restrictions are implementation gaps,
 not definitions of the operator.
 
-Every post-ASAP operator payload supports both phase assignments. Phase is
-stored on the `PostAsapDAG` node, independently of its operator payload.
-`PostAsapDAG::with_execution_phases` assigns a phase to every node and updates
-its edges. Ingestion work cannot depend on a future query result. Default
-semantic realization still proposes an initial layout; it does not restrict
-which phase an operator may use. Deployments must separately check that
-they have an implementation and a valid data source for the chosen placement.
+The logical DAG carries no timing: `OperatorNode::timing` is `None` on every
+front-end node and every candidate, and `map_children` clears it. Summary
+materialization chooses a lifecycle per summary state and records it in a
+[`LifecycleAssignment`](../../../crates/types/src/ir/timing.rs) (ingestion-time
+maintenance or query-time recomputation per `SummaryAgg`; a state absent from
+the assignment defaults to ingestion-time maintenance).
+`apply_lifecycle_timings(root, &assignment, &mut TimingMemo)` then writes a
+timing into every node, top-down:
+
+- a node of fixed kind takes its kind's timing — `SummaryEstimate` and
+  `EvaluatePopulation` run at query time, `MaintainPopulation` at ingestion time;
+- a `SummaryAgg` takes the assignment's timing, unless something below it can
+  only exist at query time (a evaluation);
+- every other node runs when its consumer runs: everything that feeds a
+  maintained state runs at ingestion time, everything above a evaluation at
+  query time.
+
+The pass then validates every edge (rows or exact-accumulator state into a
+`SummaryAgg`, state into a evaluation, an ingestion-time `MaintainPopulation` under
+a `EvaluatePopulation`, no ingestion work reading a query-time value) and rejects a
+node reached from two consumers that need different timings;
+`split_shared_by_phase` copies such a sub-DAG for one side before the
+assignment is applied. `validate_default` and `planned_data_state` answer the
+same questions for a candidate at planning time without keeping anything.
+
+## Exported DAG
+
+The pre-ASAP DAG and the post-ASAP DAG are both logical: they describe what is
+computed, not which physical operators execute it. Planning builds and shares
+`OperatorNode` trees;
+[`asap_types::ir::export::compile_post_asap_dag`](../../../crates/types/src/ir/export.rs)
+converts a selected, timed tree into a `PostAsapDAG` with stable node IDs and
+typed edges, and `PostAsapDAGDocument` is its versioned wire envelope
+(`schema_version` = `POST_ASAP_DAG_WIRE_VERSION`, currently 6). Physical
+compilation consumes `PostAsapDAG` and produces a separate physical DAG.
+
+Wire version 7 emits **one node per operator** — relational operators
+included — with children as edges and no embedded sub-DAGs:
+
+- A non-ASAP node is a `Relational { operator: NonASAPOpKind }` payload:
+  the operator's own fields with scalar expressions mirrored as
+  `WireScalarExpr`, children removed. An ASAP node's payload is its variant
+  (`SummaryAgg`, `SummaryEstimate`, `FinalizeExactAccumulator`,
+  `MaintainPopulation`, `EvaluatePopulation`, …).
+- Edges carry a role: `Input`, `Left`/`Right` for the two sides of a `Join`,
+  `SetOp`, `BinaryOp`, `SummarySubtract` or `SummaryJoin`, and `ScalarRef`
+  when the consumer reads the producer from inside one of its scalar
+  expressions (`scalar(v)`). Every edge records the intermediate schema, the
+  producer's data state and grouping/window compatibility.
+- Each node records `output_state` (timing plus `Raw` or `SummaryState`),
+  `output_schema` and `guarantee`. Export reads the timing written by
+  `apply_lifecycle_timings` and rejects an untimed node
+  (`ExecutionDataStateError::UntimedNode`); it does not re-run data-state
+  validation.
+
+Phase is stored on the `PostAsapDAG` node, independently of its payload.
+`PostAsapDAG::with_execution_phases` reassigns a phase to every node and
+updates its edges; ingestion work cannot depend on a future query result.
+Deployments must separately check that they have an implementation and a
+valid data source for the chosen placement.
 
 ## Weighted grouped TopK
 
@@ -90,19 +173,19 @@ the update weight is the series rate. Summing updates for one item implements
 the logical grouped sum without first constructing all exact grouped sums.
 
 The DAG is per-series rate → finalized values → partitioned summary construction
-→ typed candidate/score readout → output projection → grouped Sort → grouped
+→ typed candidate/score evaluation → output projection → grouped Sort → grouped
 Limit. The output count is two per job. The candidate capacity is a separate
 parameter, provisionally `max(k, ceil(1 / epsilon))`; this sizing choice is not a
 membership theorem. Missing evidence retains a logical candidate with symbolic unknown guarantees;
 default selection does not certify or choose it.
-The row readout restores job and service identities and returns estimated sums.
+The row evaluation restores job and service identities and returns estimated sums.
 There is no mandatory exact scoring branch or candidate semi-join in this path.
 The old raw counter-delta update expression is removed rather than retained as a
 compatibility option: counter increments are not complete windowed rate results.
 
-The direct readout represents both score error and membership. A source provider
+The direct evaluation represents both score error and membership. A source provider
 supplies an enforced upper bound on distinct partition/item identities for the
-complete readout. Planner uses this bound to size confidence and union-bound
+complete evaluation. Planner uses this bound to size confidence and union-bound
 score errors over adaptively selected items. Membership evidence is evaluated
 for the query's output count, not the candidate capacity. Score and membership
 failure probabilities are combined, and the score guarantee remains in the
@@ -110,8 +193,8 @@ membership guarantee's child provenance. An exact request does not accept this
 approximate output path merely because its selected identities are certified.
 
 Deployment chooses ingestion time or query time for these operators. The
-semantic constructor proposes a layout; `with_execution_phases` assigns the
-placement. Either deployment must give each evaluation a complete
+lifecycle assignment writes the placement; `with_execution_phases` can
+reassign it on the exported DAG. Either deployment must give each evaluation a complete
 rate window and an isolated summary state, or maintain an equivalent replacement
 strategy. Appending successive rate snapshots to one cumulative state is invalid.
 An ingestion execution can compute a window before the query and store its state;
diff --git a/docs/design_docs/concepts/pre-asap-ir.md b/docs/design_docs/concepts/pre-asap-ir.md
index 735f522f3..0b12766b1 100644
--- a/docs/design_docs/concepts/pre-asap-ir.md
+++ b/docs/design_docs/concepts/pre-asap-ir.md
@@ -12,16 +12,18 @@ Only semantics that affect correctness, summary applicability, or cost become fi
 
 ### Time
 
-- TimeRange — a PromQL range-vector lookback such as [5m].
+- TimeRange — PromQL sample selection: an instant selector's lookback, or a range selector such as [5m].
 - TimeShift — moves when a selector is evaluated (offset or @).
 - PromqlSubquery — re-evaluates an instant-vector expression over a range.
 
 ### Relational
 
 - Scan — identifies a logical data source.
+- Values — literal rows; one empty row is the input of a `SELECT` without `FROM`.
+- ScalarBridge — a scalar expression at an operator position: a bare scalar query, or the scalar operand of `<vector> op <scalar>`.
 - Filter — restricts rows using a predicate.
 - Project — selects or derives output columns.
-- BinaryOp — composes two inputs with arithmetic, comparison, or boolean logic.
+- BinaryOp — composes two inputs with arithmetic, comparison, or boolean logic. A PromQL `bool` comparison returns 0/1 instead of filtering.
 - Sort — orders rows without expressing a heavy-hitter intent.
 - Limit — caps a row count, optionally after an offset.
 - Dedup — removes duplicate rows.
@@ -31,10 +33,7 @@ Only semantics that affect correctness, summary applicability, or cost become fi
 
 ### PromQL-specific
 
-- PromqlScalarBridge — holds a scalar sub-expression at an operator-DAG position.
-- EvalTimestamp — provides the evaluation timestamp as a scalar.
-- PromqlVectorFromScalar — promotes a scalar to a label-less instant vector.
-- PromqlScalarFromVector — collapses a single-series vector to a scalar.
+- PromqlVectorFromScalar — promotes a scalar to a label-less instant vector. Its inverse, PromQL `scalar(v)`, is a scalar expression that reads `v`.
 - PromqlRelabel — rewrites labels on each series.
 - PromqlInfoEnrich — enriches labels from an info metric.
 - PromqlSeriesSample — selects whole series without reducing them.
diff --git a/docs/design_docs/proposals/asap-aware-mapping/ddsketch-quantile-ratios.md b/docs/design_docs/proposals/asap-aware-mapping/ddsketch-quantile-ratios.md
index f71dde2ea..8bb452783 100644
--- a/docs/design_docs/proposals/asap-aware-mapping/ddsketch-quantile-ratios.md
+++ b/docs/design_docs/proposals/asap-aware-mapping/ddsketch-quantile-ratios.md
@@ -14,7 +14,7 @@ The final guarantee records both input ranges and their contract identifiers. Th
 
 ## Candidate generation without evidence
 
-The default `SketchAlgorithmStrategy` permits a direct DDSketch quantile-ratio
+The default `ASAPStrategies` permits a direct DDSketch quantile-ratio
 candidate when domain evidence is absent, but leaves the root guarantee unset.
 This is useful for the v1 integration path; it does not turn missing evidence
 into evidence. Other approximate divisions still require their own composition
diff --git a/docs/design_docs/proposals/asapquery-rule-coverage.md b/docs/design_docs/proposals/asapquery-rule-coverage.md
index e496c9fe9..634878696 100644
--- a/docs/design_docs/proposals/asapquery-rule-coverage.md
+++ b/docs/design_docs/proposals/asapquery-rule-coverage.md
@@ -21,7 +21,7 @@ cost, and selection rules under `optimizer/`. The reviewed source is
 | Temporal aggregate functions | Lowering covered; realization varies | `Aggregate(PerEntity)` over `TimeRange` represents the full family. Sum, count, min, max, quantile, rate, and increase have summary realizations; `avg_over_time` is currently exact `PassThrough`, matching ASAPQuery's exact-only multi-stat fallback rather than claiming a maintained summary. |
 | Spatial aggregate functions | Lowering covered; realization varies | `Aggregate(Reduce(GroupKeys))` is shared by SQL and PromQL. Supported single accumulators and ordinary `by(...)` avg rewrites generate candidates; shapes such as `avg without(...)` retain the same exact raw fallback that ASAPQuery uses for multi-stat AQEs. |
 | Collapsible temporal + spatial aggregates | Semantic-equivalent rewriting | The existing rewrite strategy uses accumulator algebra: sum∘sum, sum∘count, min∘min, and max∘max. It rejects all other pairs and requires identical output schemas. |
-| Sketch alternatives and exact fallback | Covered more generally | `SketchAlgorithmStrategy` enumerates legal summary realizations. The enclosing memo group always retains the original raw expression as the exact fallback; the strategy does not falsely label an approximate sketch as exact. |
+| Sketch alternatives and exact fallback | Covered more generally | `ASAPStrategies` enumerates legal summary realizations. The enclosing memo group always retains the original raw expression as the exact fallback; the strategy does not falsely label an approximate sketch as exact. |
 | Subpopulation label placement | Covered more generally | `HydraGroupingStrategy` and `GroupingStrategy` express per-subpopulation and shared multi-subpopulation realizations. |
 | Shared computation | Covered more generally | workload-wide CSE and `SharedSubDAGStrategy` operate on physical DAG identity rather than AQE names. |
 | Average decomposition | Semantic-equivalent rewriting | The same rewrite strategy exposes independently optimizable sum/count accumulators when null semantics and schema permit it. |
@@ -38,7 +38,7 @@ does not create a new strategy category.
 
 | Decision | Existing owner |
 |---|---|
-| Which summary algorithm can implement one aggregate intent | `SketchAlgorithmStrategy` |
+| Which summary algorithm can implement one aggregate intent | `ASAPStrategies` |
 | How grouping/subpopulation state is laid out | `HydraGroupingStrategy` |
 | Whether an equivalent logical expression exposes better accumulators | `SemanticEquivalentRewriteStrategy` (the broadened existing avg rewrite; `AvgToSumOverCountStrategy` remains a compatibility name) |
 | Whether identical physical work is shared | `SharedSubDAGStrategy` |
@@ -52,7 +52,7 @@ does not create a new strategy category.
 Accordingly, ASAPQuery's four collapsible temporal/spatial patterns extend the
 existing semantic-rewrite owner. Temporal and spatial function recognition is
 already front-end lowering into `AggIntent`; sketch compatibility remains in
-`SketchAlgorithmStrategy`; labels remain in `HydraGroupingStrategy`; and
+`ASAPStrategies`; labels remain in `HydraGroupingStrategy`; and
 maintenance lifecycle legality remains in the lifecycle planner. Window
 framework selection is separate physical-planning work. None of these become a
 parallel syntax-oriented `PatternStrategy`.
diff --git a/docs/design_docs/proposals/planner-layering.md b/docs/design_docs/proposals/planner-layering.md
index 5273bfb3f..aad13359a 100644
--- a/docs/design_docs/proposals/planner-layering.md
+++ b/docs/design_docs/proposals/planner-layering.md
@@ -254,7 +254,7 @@ A summary-based candidate uses three kinds of summary nodes:
   summaries into a coarser one.
 * A **summary estimation node** computes an answer from a summary, for example
   the p99 estimate from a KLL, or the entropy estimate from a UnivMon.
-* **summary subtract node** and **summary delete node** design is TODO. 
+* **summary subtract node** and **summary delete node** design is TODO.
 
 One summary build node can feed several estimation nodes, which is what Pass 2
 exploits.
diff --git a/docs/develop_docs/asap-aware-mapping-architecture.md b/docs/develop_docs/asap-aware-mapping-architecture.md
index aee8fe53a..154c131ff 100644
--- a/docs/develop_docs/asap-aware-mapping-architecture.md
+++ b/docs/develop_docs/asap-aware-mapping-architecture.md
@@ -55,18 +55,20 @@ The diagram below follows a workload of one or more query roots through target d
 Terminology used in the diagram:
 
 - A **workload** is the set of named queries planned together. A **query root**
-  is the top-level `QueryExpr` (the logical query-expression type) for one of
-  those queries. **Pre-ASAP** means this logical input form, before the planner
-  realizes an operation as a concrete ASAP realization; **post-ASAP** means
-  the resulting realization form.
+  is the top-level `Rc<OperatorNode>` (the unified operator IR) for one of
+  those queries. **Pre-ASAP** means a DAG that contains only ordinary
+  `NonASAPOp` operators, before the planner realizes an operation with ASAP
+  primitives; **post-ASAP** means the same IR after some nodes became `ASAPOp`
+  summary operators.
 - A **DAG** (directed acyclic graph) represents query operators whose sub-DAGs
   may be shared. See [sub-DAG sharing and ASAP-aware CSE](../design_docs/proposals/planner-layering.md#pass-2-asap-aware-common-subexpression-elimination)
   for the sharing rules. Rust's `Rc<T>` (reference-counted pointer) records
   shared node identity.
 - A **target** is one replaceable site. A **candidate** is one valid alternative
-  for it. `Replacement::Summary` is a constructed post-ASAP summary—maintained state
-  such as an exact accumulator or an approximate sketch—while
-  `Replacement::Rewrite` is another pre-ASAP logical expression.
+  for it. `Replacement::SubDAG` is a replacement sub-DAG: either a constructed
+  post-ASAP summary (it contains an `ASAPOp`, e.g. an exact accumulator or an
+  approximate sketch) or a logical rewrite with no ASAP operator
+  (`is_logical_rewrite` tells them apart).
   `Replacement::ExactComposition` refers to a child target whose realization
   must remain undecided until compatible selection. A **sketch**
   is a compact data structure that trades exactness for bounded error. A
@@ -86,15 +88,15 @@ flowchart TB
   classDef report fill:#f2eafe,stroke:#7950b3,color:#34204f
 
   subgraph DISCOVERY[1. Discover every replaceable site]
-    WL["Input workload<br/>one or more named pre-ASAP QueryExpr roots"]:::input
+    WL["Input workload<br/>one or more named pre-ASAP OperatorNode roots"]:::input
     SEARCH["search_workload_with<br/>run CSE once, then visit every node in every root DAG"]:::generate
-    TARGET["TargetSubDAG<br/>one candidate site plus the number of workload locations<br/>that reference the same Rc&lt;QueryExpr&gt;"]:::generate
+    TARGET["TargetSubDAG<br/>one candidate site plus the number of workload locations<br/>that reference the same Rc&lt;OperatorNode&gt;"]:::generate
     WL -->|"roots"| SEARCH -->|"one target per distinct node"| TARGET
   end
 
   subgraph GENERATION[2. Generate all legal alternatives at each site]
     STRATEGY["ReplacementStrategy<br/>when a target matches, enumerate every legal replacement;<br/>implementations generate but do not choose"]:::generate
-    CAND["ReplacementSubDAG candidates<br/>each contains a Summary, Rewrite or ExactComposition<br/>plus typed provenance and rationale;<br/>no alternative is removed solely on cost"]:::store
+    CAND["ReplacementSubDAG candidates<br/>each contains a Subtree (summary or logical rewrite) or ExactComposition<br/>plus typed provenance and rationale;<br/>no alternative is removed solely on cost"]:::store
     TARGET -->|"try every registered strategy"| STRATEGY --> CAND
     CM(["CostModel<br/>orders candidates and supplies<br/>deployment-specific parameters"]):::choose
     CM -. "rank and parameterize; accuracy checks remain required" .-> STRATEGY
@@ -157,7 +159,7 @@ flowchart LR
   classDef workload fill:#e7f7ef,stroke:#31835e,color:#173f2d
   classDef common fill:#fff6dd,stroke:#b78922,color:#513d0c
 
-  ROOTS["Input<br/>one or more named QueryExpr roots"]:::workload
+  ROOTS["Input<br/>one or more named OperatorNode roots"]:::workload
   ROOTS --> CSE["Canonicalize sharing<br/>merge structurally identical, legally shareable sub-DAGs"]:::workload
   CSE --> WALK["Discover sites<br/>walk the complete DAG, including nodes below unshared parents"]:::workload
   WALK --> T["Build TargetSubDAG<br/>retain the sub-DAG's Rc identity and measured consumer_count"]:::workload
@@ -199,8 +201,8 @@ cost.
 
 The default context-free registry contains five `ReplacementStrategy` implementations:
 
-- `SketchAlgorithmStrategy` matches supported aggregate and binary shapes. Its
-  `replacements(target)` method constructs every legal post-ASAP `SummaryNode`,
+- `ASAPStrategies` matches supported aggregate and binary shapes. Its
+  `replacements(target)` method constructs every legal post-ASAP summary sub-DAG,
   including applicable sketch, exact-accumulator, and pass-through
   realizations. Candidates are sized and ordered for the target's accuracy
   requirement; candidates without a sufficient guarantee are rejected before
diff --git a/docs/develop_docs/asap-aware-mapping-contracts.md b/docs/develop_docs/asap-aware-mapping-contracts.md
index 447cb3823..1980dafd0 100644
--- a/docs/develop_docs/asap-aware-mapping-contracts.md
+++ b/docs/develop_docs/asap-aware-mapping-contracts.md
@@ -10,25 +10,25 @@ first; use the [extension guide](extend-asap-aware-mapping.md) when changing one
 
 ### `TargetSubDAG`
 
-A pre-ASAP `QueryExpr` node that a strategy may replace.
+A pre-ASAP `OperatorNode` that a strategy may replace.
 
 ```rust
 pub struct TargetSubDAG<'a> {
-    pub root: &'a Rc<QueryExpr>,
+    pub root: &'a Rc<OperatorNode>,
     pub consumer_count: usize,
 }
 ```
 
-`root` is the actual `Rc<QueryExpr>` from the workload.
+`root` is the actual `Rc<OperatorNode>` from the workload.
 
-`consumer_count` counts structural references, not runtime executions. It is the number of places in the workload DAG that point to this exact `Rc<QueryExpr>` node.
+`consumer_count` counts structural references, not runtime executions. It is the number of places in the workload DAG that point to this exact `Rc<OperatorNode>` node.
 
 For example, consider two top-level queries:
 
 - `sum by (service) (rate(m[5m]))`
 - `avg by (service) (rate(m[5m]))`
 
-After `share_common_sub_dags` merges their identical `rate(m[5m])` sub-DAGs, both query DAGs point to the same `Rc`. That node's `consumer_count` is `2`, regardless of how often either query executes.
+After `share_common_sub_dags` merges their identical `rate(m[5m])` sub-DAGs, both query trees point to the same `Rc`. That node's `consumer_count` is `2`, regardless of how often either query executes.
 
 Use:
 
@@ -54,19 +54,24 @@ when the caller already knows the real number of consumers.
 
 The actual object that substitutes the target.
 
-There are currently three forms:
+There are currently two forms:
 
 ```rust
 pub enum Replacement {
-    Summary(Rc<SummaryNode>),
-    Rewrite(Rc<QueryExpr>),
+    SubDAG(Rc<OperatorNode>),
     ExactComposition(ExactComposition),
 }
 ```
 
-Use `Replacement::Summary` when the alternative is a constructed post-ASAP summary plan.
+Use `Replacement::SubDAG` for a replacement sub-DAG. It is one of:
 
-Use `Replacement::Rewrite` when the alternative is still a logical pre-ASAP `QueryExpr`.
+- a constructed post-ASAP summary plan: the sub-DAG contains an `ASAPOp`
+  (`SummaryAgg`, `SummaryEstimate`, ...);
+- a logical rewrite: only `NonASAPOp` nodes and no guarantee yet.
+
+`is_logical_rewrite(&node)` tells the two apart. A kept pre-ASAP sub-DAG
+(`retain_exact`) has no ASAP operator but carries an exact guarantee, so it
+counts as a bound decision, not a rewrite.
 
 Use `Replacement::ExactComposition` when an exact operation refers to a child
 target whose realization must remain undecided. Selection coordinates the
@@ -77,10 +82,10 @@ Examples:
 
 ```text
 Quantile(...)
-    -> KLL SummaryNode
+    -> SummaryEstimate(SummaryAgg(KLL))
 ```
 
-is a `Summary`; KLL (Karnin–Lang–Liberty) is a quantile-sketch algorithm.
+is a summary `Subtree`; KLL (Karnin–Lang–Liberty) is a quantile-sketch algorithm.
 
 ```text
 compute independently
@@ -88,7 +93,7 @@ compute independently
 reuse an already shared logical sub-DAG
 ```
 
-is represented as a `Rewrite`.
+is represented as two logical-rewrite `Subtree`s.
 
 ---
 
@@ -157,7 +162,7 @@ aggregation must compute without committing to a physical summary algorithm.
 A realization may be an approximate sketch, an exact mergeable
 accumulator, or a pass-through that keeps the original operation instead of
 building a summary. `realizations_for_intent` enumerates these concrete
-realizations; `SketchAlgorithmStrategy::replacements()` constructs each one as
+realizations; `ASAPStrategies::replacements()` constructs each one as
 a `ReplacementSubDAG`. It returns all
 candidates in preferred order without selecting a winner. At workload scale,
 `search_workload`/`search_workload_with` preserve all supported legal alternatives
@@ -170,8 +175,8 @@ This guide uses the Cascades/Volcano terminology:
   realization. For example, a quantile `AggIntent` may have KLL and DDSketch
   `Realization` values.
 - A **transformation rule** maps a logical operation to another logical
-  operation. In this crate, that kind of candidate is represented by
-  `Replacement::Rewrite`.
+  operation. In this crate, that kind of candidate is a logical-rewrite
+  `Replacement::SubDAG`.
 - A **replacement candidate** packages either kind of result as a
   `ReplacementSubDAG` for search. `CandidateLogicalASAPDAGs` stores and ranks these candidates.
 - **Physical commitment and placement** happen downstream. An `Realization`
@@ -183,7 +188,7 @@ The concrete flow is:
 ```text
 AggIntent
   -> realizations_for_intent(): enumerate Realization values
-  -> SketchAlgorithmStrategy: construct ReplacementSubDAG candidates
+  -> ASAPStrategies: construct ReplacementSubDAG candidates
   -> CandidateLogicalASAPDAGs: store and rank candidates
   -> downstream deployment: select and place a final choice
 ```
@@ -206,7 +211,7 @@ bounds, but does not execute workloads or own deployment measurements. Most hook
 | `rank_candidates` | Order valid sketch algorithms | No |
 | `size_params` | Convert an accuracy target into sketch parameters | Yes |
 | `realize_extension` | Map a custom intent to a realization | Yes |
-| `readout_extension` | Query a custom extension summary | Panics until paired with a custom realization |
+| `evaluation_extension` | Query a custom extension summary | Panics until paired with a custom realization |
 | `cse_recompute_cost` | Estimate independent recomputation | Yes |
 | `cse_shared_maintenance_cost` | Estimate shared maintenance | Yes |
 | `cse_share_decision` | Choose sharing or recomputation | Yes |
@@ -247,10 +252,10 @@ bounds, but does not execute workloads or own deployment measurements. Most hook
   fn realize_extension(&self, ext_kind: &str, payload: &serde_json::Value) -> Realization;
   ```
 
-- **`readout_extension`** — define how queries read an extension summary that `realize_extension` mapped to a `Sketch`. The two hooks are a pair: realization defines what is maintained; readout defines how it is queried. Override both for the same `ext_kind`. The default readout panics to prevent a silent wrong answer.
+- **`evaluation_extension`** — define how queries read an extension summary that `realize_extension` mapped to a `Sketch`. The two hooks are a pair: realization defines what is maintained; evaluation defines how it is queried. Override both for the same `ext_kind`. The default evaluation panics to prevent a silent wrong answer.
 
   ```rust
-  fn readout_extension(&self, ext_kind: &str, payload: &serde_json::Value, col: &ColumnRef) -> SketchStatistic;
+  fn evaluation_extension(&self, ext_kind: &str, payload: &serde_json::Value, col: &ColumnRef) -> SketchStatistic;
   ```
 
 - **`cse_recompute_cost`** — estimate the one-time cost of recomputing a CSE candidate's sub-DAG independently at a single consumer. Default: `default_cse_recompute_cost`, a structural-size proxy.
@@ -297,14 +302,14 @@ A custom cost model does not necessarily need to override every hook. The curren
 // One TargetSubDAGCandidates per distinct TargetSubDAG in the whole workload —
 // never a flat list of fully assembled plans.
 pub struct TargetSubDAGCandidates {
-    pub target: Rc<QueryExpr>,
+    pub target: Rc<OperatorNode>,
     pub consumer_count: usize,
     pub candidates: Vec<ReplacementSubDAG>,  // accepted alternatives, unranked
     pub rejected: Vec<RejectedCandidate>,    // failed accuracy checks
 }
 
 pub struct RankedTargetSubDAGCandidates<'a> {
-    pub target: &'a Rc<QueryExpr>,
+    pub target: &'a Rc<OperatorNode>,
     pub consumer_count: usize,
     pub candidates: Vec<&'a ReplacementSubDAG>,  // same candidates, ranked
     pub costs: Vec<f64>,                         // costs[i] <-> candidates[i]
@@ -313,7 +318,7 @@ pub struct RankedTargetSubDAGCandidates<'a> {
 
 `search_workload(roots)` runs the shared-sub-DAG pass once, discovers every target across every root's whole DAG (not just root-level sharing — a `SharedSubDAGStrategy` candidate three levels under an unshared `Filter` is exactly as real a site as a shared whole root), and asks every registered strategy to a fixpoint. Two logically different candidates at two different targets are never copied into two separate plans — they're two entries in two different `TargetSubDAGCandidates`s, sharing every other node in the workload by construction.
 
-`CandidateLogicalASAPDAGs::cost_sorted(cost_model)` is the one ranking step: for each candidate set, it dispatches by candidate shape — a same-shape `Rewrite` pair (a `SharedSubDAGStrategy` share/recompute choice) goes through `CostModel::cse_share_decision`; a same-shape run of `Summary` candidates realizing sketches (a `SketchAlgorithmStrategy` choice) goes through `CostModel::rank_candidates`; and a mixed candidate set is ordered by each candidate's `CostModel::estimate_cost`. Every candidate gets a numeric cost aligned index-for-index in `costs`. Count in, count out—nothing is dropped to produce a ranking. Legality checks
+`CandidateLogicalASAPDAGs::cost_sorted(cost_model)` is the one ranking step: for each candidate set, it dispatches by candidate shape — the `SharedSubDAGStrategy` share/recompute pair (recognized by `ReplacementProvenance::CseShare`/`CseRecompute`) goes through `CostModel::cse_share_decision`; a set with a Hydra shared-grid alternative goes through `CostModel::grouping_state_cost`; a set whose candidates all realize sketches (a `ASAPStrategies` choice) goes through `CostModel::rank_candidates`; and any other mixed set is ordered by `CostModel::candidate_cost`. Every candidate gets a numeric cost aligned index-for-index in `costs`. Count in, count out—nothing is dropped to produce a ranking. Legality checks
 may already have removed proposals before this boundary. In particular,
 `search_workload_with_targets` checks explicit per-root targets, while retaining
 direct DDSketch ratios with missing domain evidence and no root guarantee for
@@ -329,7 +334,7 @@ Sketches separate their query category from the concrete algorithm and its param
 
 | Level | Type | Example |
 | --- | --- | --- |
-| **family** | `SummaryFamilyType` | `Sketch`, `Sample`, `Wavelet`, `StatModel`, `ExactAggregate` |
+| **family** | `FieldDataType` (non-`Plain` variants) | `Sketch`, `Sample`, `Wavelet`, `StatModel`, `ExactAggregate` |
 | **category** | `SketchCategory` | `Quantile`, `Cardinality`, `Frequency`, `TopK` |
 | **algorithm** | `SketchAlgorithm` | `Kll` / `DDSketch` (both quantile); `Hll` (HyperLogLog) / `Theta` / `Kmv` (K-Minimum Values), all cardinality |
 | **committed choice** | `SketchKind` | one validated category + algorithm + parameter combination |
@@ -340,7 +345,7 @@ to the selected algorithm and classifies the pair into its category. The public
 `.category()`, `.algorithm()`, and `.params()` accessors expose the committed
 values without permitting an invalid combination.
 
-Where this matters in practice: `CostModel::rank_candidates`, `CostModel::size_params`, and `SketchAlgorithmStrategy::replacements` operate at the **algorithm** level. `summary_candidates(intent)` returns a list of `SketchAlgorithm`s (`[Kll, DDSketch]` for a `Quantile` intent), never a bare `SketchKind` with nothing chosen underneath it. `SketchKind` appears after an algorithm has been selected and sized—on `Realization::Sketch(SketchKind)` and `SummaryFamilyType::Sketch(SketchKind)`.
+Where this matters in practice: `CostModel::rank_candidates`, `CostModel::size_params`, and `ASAPStrategies::replacements` operate at the **algorithm** level. `summary_candidates(intent)` returns a list of `SketchAlgorithm`s (`[Kll, DDSketch]` for a `Quantile` intent), never a bare `SketchKind` with nothing chosen underneath it. `SketchKind` appears after an algorithm has been selected and sized—on `Realization::Sketch(SketchKind)` and `FieldDataType::Sketch(SketchKind, GroupingStrategy)`.
 
 `Sample`, `Wavelet`, and `StatModel` each use a flat `(Kind, Params)` pair. `Sketch` needs the additional algorithm level because multiple algorithms can serve the same purpose—for example, KLL and DDSketch both answer quantile queries.
 
@@ -378,15 +383,15 @@ The crate provides no default `Matcher` implementation because the answer depend
 
 Concretely, `explanation.rs` reports three candidate kinds from each `TargetSubDAGCandidates`:
 
-- `ExplanationKind::SketchApproximation` — the set contains a `Replacement::Summary` that realizes `SummaryFamilyType::Sketch(..)`, not just an exact/pass-through candidate.
-- `ExplanationKind::CommonSubexpressionReuse` — `consumer_count >= 2` and the set contains `SharedSubDAGStrategy`'s "build once and share" candidate (the `Replacement::Rewrite` whose `Rc` is the set's `target`).
+- `ExplanationKind::SketchApproximation` — the set contains a summary `Replacement::SubDAG` that realizes `FieldDataType::Sketch(..)`, not just an exact/pass-through candidate.
+- `ExplanationKind::CommonSubexpressionReuse` — `consumer_count >= 2` and the set contains `SharedSubDAGStrategy`'s "build once and share" candidate (the `Replacement::SubDAG` whose `Rc` is the set's `target`).
 
 - `ExplanationKind::ExactComposition` — the candidate set contains an exact operation
   composed with a child target whose realization remains a coordinated choice.
 
 Each `ReplacementExplanation::reason` is copied verbatim from the matching candidate's own `ReplacementSubDAG::rationale`. Nothing in `explanation.rs` re-explains why a candidate is valid; that explanation already exists exactly once, on the candidate itself.
 
-`ReplacementExplanation` carries both `node_hash` and `target`. A downstream consumer first compares `node_hash` with an exported `DAGNode::hash` to narrow the search, then compares the exact target expression with the node's in-process source expression. This preserves the hash's role as a fast filter while making the final association collision-safe; `location` remains human-readable presentation text rather than a machine identifier.
+`ReplacementExplanation` carries both `node_hash` and `target`. A downstream consumer first compares `node_hash` with an exported `DAGNode::hash` to narrow the search, then compares the exact `target` node with the exported node's in-process `DAGNode::source_node`. This preserves the hash's role as a fast filter while making the final association collision-safe; `location` remains human-readable presentation text rather than a machine identifier.
 
 ### Why there is no `ExplanationRule` trait
 
@@ -394,6 +399,6 @@ Explanations are derived from candidates already present in `CandidateLogicalASA
 
 ### How it derives `location` text
 
-`CandidateLogicalASAPDAGs`/`TargetSubDAGCandidates` track `Rc<QueryExpr>` pointer identity, not human-readable breadcrumbs. `ReplacementExplanation::location` provides prose such as `root "dash_a" > lhs` so reporting consumers can identify the relevant part of the query without interpreting pointer identity. Location derivation does not make replacement or costing decisions.
+`CandidateLogicalASAPDAGs`/`TargetSubDAGCandidates` track `Rc<OperatorNode>` pointer identity, not human-readable breadcrumbs. `ReplacementExplanation::location` provides prose such as `root "dash_a" > lhs` so reporting consumers can identify the relevant part of the query without interpreting pointer identity. Location derivation does not make replacement or costing decisions.
 
 ---
diff --git a/docs/develop_docs/extend-asap-aware-mapping.md b/docs/develop_docs/extend-asap-aware-mapping.md
index 5a5e069a8..b9a830140 100644
--- a/docs/develop_docs/extend-asap-aware-mapping.md
+++ b/docs/develop_docs/extend-asap-aware-mapping.md
@@ -44,7 +44,7 @@ There are four decisions to make.
 
 `matches` should contain the minimum structural and semantic checks needed to determine whether the strategy applies.
 
-For example, the aggregate path in `SketchAlgorithmStrategy` requires a
+For example, the aggregate path in `ASAPStrategies` requires a
 supported shape:
 
 - the node is an `Aggregate`,
@@ -112,23 +112,20 @@ and let costing decide later.
 
 ---
 
-### Choose `Summary` vs. `Rewrite`
+### Summary sub-DAG vs. logical rewrite
 
-Return:
+Both are returned as:
 
 ```rust
-Replacement::Summary(...)
+Replacement::SubDAG(node)
 ```
 
-when the candidate is a fully constructed post-ASAP summary.
+- A fully constructed post-ASAP summary: `node` contains an `ASAPOp`.
+- A logical pre-ASAP rewrite: `node` has only `NonASAPOp` nodes and no
+  guarantee. `is_logical_rewrite(&node)` checks this.
 
-Return:
-
-```rust
-Replacement::Rewrite(...)
-```
-
-when the candidate is a logical pre-ASAP rewrite.
+Set `provenance` to say which one it is (`ReplacementProvenance::SummaryRealization`,
+`LogicalRewrite`, ...); selection reads provenance, not the sub-DAG's shape.
 
 Use `Replacement::ExactComposition` when a candidate depends on a child target
 whose implementation must be selected compatibly later. Do not bind it to the
@@ -204,7 +201,7 @@ how to realize it, wrap that logic.
 
 Do not create a second implementation of the same semantics inside the strategy.
 
-The existing `SketchAlgorithmStrategy` is the model to follow: it reuses
+The existing `ASAPStrategies` is the model to follow: it reuses
 `replacement.rs`'s existing candidate list and summary-construction path.
 
 ---
@@ -229,23 +226,23 @@ If your transformation requires context not currently represented in `TargetSubD
 
 ---
 
-### Example: current `SketchAlgorithmStrategy`
+### Example: current `ASAPStrategies`
 
-`SketchAlgorithmStrategy` is the reference implementation for a strategy that
+`ASAPStrategies` is the reference implementation for a strategy that
 produces constructed post-ASAP summaries.
 
 Construction:
 
 ```rust
 let strategy =
-    SketchAlgorithmStrategy::default_cost_model();
+    ASAPStrategies::default_cost_model();
 ```
 
 or with a custom cost model:
 
 ```rust
 let model = MyCostModel; // illustrative
-let strategy = SketchAlgorithmStrategy::new(&model);
+let strategy = ASAPStrategies::new(&model);
 ```
 
 The strategy matches supported aggregate nodes.
@@ -254,10 +251,10 @@ At a high level:
 
 ```mermaid
 flowchart LR
-  A["Input TargetSubDAG<br/>root is a supported Aggregate"] --> B["SketchAlgorithmStrategy::matches<br/>check whether the target shape can produce summaries"]
-  B -->|"true"| C["SketchAlgorithmStrategy::replacements<br/>use CostModel preferences and sizing while preserving<br/>every semantically valid realization"]
+  A["Input TargetSubDAG<br/>root is a supported Aggregate"] --> B["ASAPStrategies::matches<br/>check whether the target shape can produce summaries"]
+  B -->|"true"| C["ASAPStrategies::replacements<br/>use CostModel preferences and sizing while preserving<br/>every semantically valid realization"]
   B -->|"false"| NONE["Empty candidate list"]
-  C --> F["Output Vec&lt;ReplacementSubDAG&gt;<br/>each entry contains a constructed SummaryNode and rationale;<br/>all candidates retained in preferred order"]
+  C --> F["Output Vec&lt;ReplacementSubDAG&gt;<br/>each entry contains a constructed summary sub-DAG and rationale;<br/>all candidates retained in preferred order"]
 ```
 
 For an approximate quantile, both KLL and DDSketch remain candidates when
@@ -271,16 +268,17 @@ even if the cost model prefers one. When only one realization is legal, such as
 Call the public strategy interface and inspect every returned candidate:
 
 ```rust
-let strategy = SketchAlgorithmStrategy::new(&cost_model);
+let strategy = ASAPStrategies::new(&cost_model);
 let candidates = strategy.replacements(&target);
 
 for candidate in candidates {
     match candidate.replacement {
-        Replacement::Summary(summary) => {
-            // Inspect or execute this constructed SummaryNode.
+        Replacement::SubDAG(node) => {
+            // A constructed summary sub-DAG (`node.is_asap()`), or a kept
+            // pre-ASAP sub-DAG with an exact guarantee for pass-through.
         }
-        Replacement::Rewrite(_) => unreachable!(
-            "SketchAlgorithmStrategy produces summary candidates"
+        Replacement::ExactComposition(_) => unreachable!(
+            "ASAPStrategies produces sub-DAG candidates"
         ),
     }
 }
@@ -310,16 +308,16 @@ and returns two alternatives:
 2. Build independently for each consumer.
 ```
 
-The shared candidate reuses the same `Rc<QueryExpr>`:
+The shared candidate reuses the same `Rc<OperatorNode>`:
 
 ```rust
-Replacement::Rewrite(Rc::clone(target.root))
+Replacement::SubDAG(Rc::clone(target.root))
 ```
 
 The independent candidate creates a structurally equal but separately allocated node:
 
 ```rust
-Replacement::Rewrite(
+Replacement::SubDAG(
     Rc::new((**target.root).clone())
 )
 ```
@@ -353,7 +351,7 @@ The basic calling pattern is:
 ```rust
 let target = TargetSubDAG::new(&root);
 let strategy =
-    SketchAlgorithmStrategy::default_cost_model();
+    ASAPStrategies::default_cost_model();
 
 if strategy.matches(&target) {
     let candidates =
@@ -546,13 +544,13 @@ Then inject it into code that accepts a `&dyn CostModel`:
 let model = PreferDDSketch;
 
 let strategy =
-    SketchAlgorithmStrategy::new(&model);
+    ASAPStrategies::new(&model);
 
 let replacements =
     strategy.replacements(&target);
 ```
 
-Important: changing `rank_candidates` changes the preferred ordering, but `SketchAlgorithmStrategy` still enumerates every valid sketch candidate.
+Important: changing `rank_candidates` changes the preferred ordering, but `ASAPStrategies` still enumerates every valid sketch candidate.
 
 A custom cost model should not change which alternatives are semantically legal.
 
@@ -641,12 +639,12 @@ Use it for implementation families that are intentionally outside the built-in e
 
 ---
 
-#### `readout_extension`
+#### `evaluation_extension`
 
-Use when an extension-defined summary also needs custom query/readout behavior.
+Use when an extension-defined summary also needs custom query/evaluation behavior.
 
 ```rust
-fn readout_extension(
+fn evaluation_extension(
     &self,
     ext_kind: &str,
     payload: &serde_json::Value,
@@ -654,7 +652,7 @@ fn readout_extension(
 ) -> SketchStatistic;
 ```
 
-This complements `realize_extension`: realization defines what gets maintained; readout defines how it is queried (see the [CostModel reference](asap-aware-mapping-contracts.md#costmodel)).
+This complements `realize_extension`: realization defines what gets maintained; evaluation defines how it is queried (see the [CostModel reference](asap-aware-mapping-contracts.md#costmodel)).
 
 ---
 
@@ -741,7 +739,7 @@ For example:
 
 ```rust
 let strategy =
-    SketchAlgorithmStrategy::new(&model);
+    ASAPStrategies::new(&model);
 
 let replacements =
     strategy.replacements(&target);
@@ -770,7 +768,7 @@ Declare built-in sketch applicability through the public candidate registry:
 summary_candidates(intent)
 ```
 
-`SketchAlgorithmStrategy` consumes this registry through its public `replacements` method.
+`ASAPStrategies` consumes this registry through its public `replacements` method.
 
 Therefore, when adding a new built-in sketch algorithm, the intended flow is:
 
@@ -778,9 +776,9 @@ Therefore, when adding a new built-in sketch algorithm, the intended flow is:
 flowchart LR
   MAP["1. Declare legality<br/>add the algorithm to summary_candidates<br/>for each AggIntent it can answer"]
   MAP --> MODEL["2. Define costing<br/>rank it, derive its SketchParams,<br/>and provide a comparable numeric cost"]
-  MODEL --> BUILD["3. Define realization behavior<br/>ensure the public strategy output contains a valid SummaryNode<br/>with the correct maintained state and readout"]
+  MODEL --> BUILD["3. Define realization behavior<br/>ensure the public strategy output contains a valid summary sub-DAG<br/>with the correct maintained state and evaluation"]
   BUILD --> ACC["4. Certify accuracy<br/>derive from committed parameters;<br/>propagate and check the final target"]
-  ACC --> ENUM["5. Verify integration<br/>SketchAlgorithmStrategy includes it automatically;<br/>tests confirm enumeration, ordering, sizing, and cost"]
+  ACC --> ENUM["5. Verify integration<br/>ASAPStrategies includes it automatically;<br/>tests confirm enumeration, ordering, sizing, and cost"]
 ```
 
 This keeps one source of truth for sketch applicability. Applicability alone
@@ -793,9 +791,9 @@ ranking; preserve exact fallback and structured rejection information.
 
 See the [accuracy implementation companion](end-to-end-accuracy-guarantees.md)
 for formulas and evidence requirements. For a new algorithm, also update its
-parameter, readout, schema and serialization definitions in `asap-types`.
+parameter, evaluation, schema and serialization definitions in `asap-types`.
 
-Do not special-case the new sketch inside `SketchAlgorithmStrategy` unless the strategy itself needs fundamentally new behavior.
+Do not special-case the new sketch inside `ASAPStrategies` unless the strategy itself needs fundamentally new behavior.
 
 ### Verifying a new sketch algorithm
 
@@ -804,7 +802,7 @@ or malformed evidence, incompatible metrics and unsupported composition. Test
 root-target checking before cost ranking, exact fallback, and exported rejection
 or guarantee data. A cheaper estimate must never admit an accuracy-illegal plan.
 
-After wiring the new algorithm into `summary_candidates` and giving the cost model a real `rank_candidates`/`size_params` opinion about it, check two things. First, that `SketchAlgorithmStrategy::replacements()` for a matching `TargetSubDAG` actually includes a candidate realizing the new algorithm — extend a test shaped like `replacement.rs`'s own test-module coverage-matrix tests (e.g. `agg_intent_to_summary_kind_coverage_matrix`) to cover the new algorithm's `AggIntent`. Second, that `cost_sorted`/`estimate_cost` produce sane, comparable numbers for the new candidate rather than a `NaN` placeholder or an outlier that swamps every other candidate.
+After wiring the new algorithm into `summary_candidates` and giving the cost model a real `rank_candidates`/`size_params` opinion about it, check two things. First, that `ASAPStrategies::replacements()` for a matching `TargetSubDAG` actually includes a candidate realizing the new algorithm — extend a test shaped like `replacement.rs`'s own test-module coverage-matrix tests (e.g. `agg_intent_to_summary_kind_coverage_matrix`) to cover the new algorithm's `AggIntent`. Second, that `cost_sorted`/`estimate_cost` produce sane, comparable numbers for the new candidate rather than a `NaN` placeholder or an outlier that swamps every other candidate.
 
 ---
 
@@ -895,10 +893,11 @@ silently disagree.
 
 ### Mistake: reimplementing summary construction inside a strategy
 
-If the candidate should produce a normal `SummaryNode`, use the existing
+If the candidate should produce a normal summary sub-DAG (`SummaryAgg` /
+`SummaryEstimate`), use the existing
 summary-construction path.
 
-A strategy should steer or wrap that path when necessary, not recreate schema derivation, column resolution, readout construction, or parameter sizing.
+A strategy should steer or wrap that path when necessary, not recreate schema derivation, column resolution, evaluation construction, or parameter sizing.
 
 ---
 
@@ -922,7 +921,7 @@ Workload-wide target discovery, deduplication, and consumer counting are separat
 
 For CSE-style decisions, pointer identity can encode actual sharing.
 
-Two `Rc<QueryExpr>` values can be structurally equal but deliberately represent independent computation.
+Two `Rc<OperatorNode>` values can be structurally equal but deliberately represent independent computation.
 
 Use the distinction intentionally.
 
@@ -937,8 +936,8 @@ When adding a new strategy:
 - [ ] Implement `ReplacementStrategy::replacements`.
 - [ ] Return every semantically valid replacement.
 - [ ] Return an empty vector for non-matching targets.
-- [ ] Use `Replacement::Summary` for constructed post-ASAP output.
-- [ ] Use `Replacement::Rewrite` for logical pre-ASAP alternatives.
+- [ ] Return `Replacement::SubDAG` for both constructed post-ASAP output and
+      logical pre-ASAP alternatives, with the matching `provenance`.
 - [ ] Add a useful rationale to every candidate.
 - [ ] Reuse existing legality and implementation logic instead of duplicating it.
 - [ ] Keep ranking and cost-based pruning out of the strategy.
@@ -953,11 +952,11 @@ When adding a new cost model:
 - [ ] Keep semantic applicability outside the cost model.
 - [ ] Use `rank_candidates` for algorithm preference; return every input candidate exactly once.
 - [ ] Use `size_params` for accuracy-to-parameter mapping.
-- [ ] Use extension hooks for extension-defined implementations/readouts.
+- [ ] Use extension hooks for extension-defined implementations/evaluations.
 - [ ] Use CSE hooks for recompute-vs.-sharing costs.
 - [ ] Override `estimate_cost` if consumers require numeric costs instead of `NaN`.
 - [ ] Test the hook directly.
-- [ ] Test integration through a consumer such as `SketchAlgorithmStrategy`.
+- [ ] Test integration through a consumer such as `ASAPStrategies`.
 - [ ] Verify that changing cost preferences does not silently remove valid replacement candidates.
 
 ---
@@ -975,12 +974,12 @@ Use this table to find the right place for a change.
 | Prefer one sketch algorithm over another | `CostModel::rank_candidates` |
 | Change sketch sizing for an accuracy target | `CostModel::size_params` |
 | Add extension-defined implementation behavior | `CostModel::realize_extension` |
-| Add extension-defined readout behavior | `CostModel::readout_extension` |
+| Add extension-defined evaluation behavior | `CostModel::evaluation_extension` |
 | Change CSE recomputation cost | `CostModel::cse_recompute_cost` |
 | Change shared-maintenance cost | `CostModel::cse_shared_maintenance_cost` |
 | Change current share/recompute choice | `CostModel::cse_share_decision` |
 | Decide whether an available implementation satisfies a required one | `impl Matcher` |
-| Produce a normal (ranked-first) post-ASAP summary for one target | `SketchAlgorithmStrategy::replacements(...).into_iter().next()` |
+| Produce a normal (ranked-first) post-ASAP summary for one target | `ASAPStrategies::replacements(...).into_iter().next()` |
 | Search a whole workload for supported legal candidates | `search_workload`/`search_workload_with` |
 | Enforce per-root result accuracy requirements | `search_workload_with_targets` |
 | Coordinate compatible choices across groups | `CandidateLogicalASAPDAGs::global_selection` |
diff --git a/docs/develop_docs/library-api.md b/docs/develop_docs/library-api.md
index 719de6ba2..fadb6bdc0 100644
--- a/docs/develop_docs/library-api.md
+++ b/docs/develop_docs/library-api.md
@@ -38,14 +38,16 @@ asap-types = { git = "https://github.com/ProjectASAP/ASAPPlanner", rev = "e7fdb2
 
 | Public function | Required input | Output |
 | --- | --- | --- |
-| `asap_frontend_promql::lower_promql_workload` | PromQL `PlanningWorkload` with a nonzero `data_ingestion_interval` | All-or-nothing `Result<Vec<QueryExpr>, PromqlError>` for normalized batch and repeating entries |
-| `asap_frontend_metricsql::lower_metricsql` | Query string, `AccuracyTarget` | `Result<QueryExpr, MetricsqlError>` |
-| `asap_frontend_sql::lower_sql` | Query string, `SqlCatalog`, accuracy | Async `Result<QueryExpr, SqlError>`; default SQL dialect is DataFusionSQL |
+| `asap_frontend_promql::lower_promql_workload` | PromQL `PlanningWorkload` with a nonzero `data_ingestion_interval` | All-or-nothing `Result<Vec<Rc<OperatorNode>>, PromqlError>` for normalized batch and repeating entries |
+| `asap_frontend_metricsql::lower_metricsql` | Query string, `AccuracyTarget` | `Result<Rc<OperatorNode>, MetricsqlError>` |
+| `asap_frontend_sql::lower_sql` | Query string, `SqlCatalog`, accuracy | Async `Result<Rc<OperatorNode>, SqlError>`; default SQL dialect is DataFusionSQL |
 | `asap_frontend_sql::lower_sql_dialect` | Same inputs plus `SqlDialect` | Async resolved Pre-ASAP query or error |
 | `asap_frontend_sql::lower_sql_batch` | `QueryWorkload` and catalog | Per-query results for `query_batch`; does not iterate `repeating_queries` |
 
 Lowering resolves the supported source language into the canonical query
-representation. It does not enumerate Post-ASAP alternatives. A frontend may
+representation: an `asap_types::ir::OperatorNode` DAG containing only
+`NonASAPOp` operators, with no timing (see the
+[Pre-ASAP IR reference](pre-asap-ir.md)). It does not enumerate Post-ASAP alternatives. A frontend may
 reject unsupported syntax or semantics; a declared language/dialect enum does
 not imply complete support. PromQL workload lowering uses normalized
 `PlanningWorkload::query_workload.entries()` order, preserving entry-to-root associations for later
@@ -58,7 +60,7 @@ PromQL's public signature (types are imported from their respective crates):
 
 ```text
 lower_promql_workload(workload: &PlanningWorkload, now_ms: u64)
-    -> Result<Vec<QueryExpr>, PromqlError>
+    -> Result<Vec<Rc<OperatorNode>>, PromqlError>
 ```
 
 `DataWorkload.data_ingestion_interval` must contain a nonzero `Evidence<DurationMs>`.
@@ -125,9 +127,9 @@ For SQL, the corresponding signatures are:
 
 ```text
 async lower_sql(query: &str, catalog: &SqlCatalog, accuracy: AccuracyTarget)
-    -> Result<QueryExpr, SqlError>
+    -> Result<Rc<OperatorNode>, SqlError>
 async lower_sql_dialect(query: &str, catalog: &SqlCatalog,
-    dialect: SqlDialect, accuracy: AccuracyTarget) -> Result<QueryExpr, SqlError>
+    dialect: SqlDialect, accuracy: AccuracyTarget) -> Result<Rc<OperatorNode>, SqlError>
 ```
 
 | `SqlDialect` value | Current behavior |
@@ -162,7 +164,7 @@ It keeps the alternatives available; it does not select an entire workload plan.
 
 ```text
 search_workload_with_targets<'s, Id>(
-    roots: Vec<(Id, Rc<QueryExpr>, Option<AccuracyTarget>)>,
+    roots: Vec<(Id, Rc<OperatorNode>, Option<AccuracyTarget>)>,
     strategies: &[Box<dyn ReplacementStrategy + 's>],
     accuracy_model: &dyn AccuracyModel,
 ) -> CandidateLogicalASAPDAGs<Id>
@@ -197,7 +199,6 @@ accuracy target, and prints every ranked candidate instead of selecting a winner
 The default cost model is suitable for inspection, not deployment calibration.
 
 ```rust
-use std::rc::Rc;
 use asap_frontend_promql::lower_promql_workload;
 use asap_types::workload::{
     AccuracyRequirement, BatchEntry, DataWorkload, DurationMs, Evidence, Query,
@@ -235,7 +236,7 @@ fn main() -> Result<(), Box<dyn std::error::Error>> {
             ..Default::default()
         }),
     };
-    let root = Rc::new(lower_promql_workload(&workload, 0)?.remove(0));
+    let root = lower_promql_workload(&workload, 0)?.remove(0);
     let cost_model = DefaultCostModel;
     let strategies = default_strategies_with(&cost_model);
     let space = search_workload_with_targets(
@@ -254,12 +255,12 @@ fn main() -> Result<(), Box<dyn std::error::Error>> {
 
 | API (`asap_aware_mapping`, unless qualified) | Inputs | Output and limits |
 | --- | --- | --- |
-| `search_workload` | `(query_id, Rc<QueryExpr>)` roots | `CandidateLogicalASAPDAGs` with built-in strategies/model; no explicit per-root target argument |
+| `search_workload` | `(query_id, Rc<OperatorNode>)` roots | `CandidateLogicalASAPDAGs` with built-in strategies/model; no explicit per-root target argument |
 | `search_workload_with` | Roots, strategy slice | `CandidateLogicalASAPDAGs`; callers choose context-free replacement strategies |
 | `search_workload_with_targets` | Roots with optional end-to-end targets, strategies, accuracy model | Candidate space with supplied root-target checks; `None` does not supply a root-level requirement; uncertified direct DDSketch ratios remain available for backend selection |
 | `CandidateLogicalASAPDAGs::cost_sorted` | Cost model | `Vec<RankedTargetSubDAGCandidates>`; retains alternatives and pairs `candidates[i]` with `costs[i]` |
 | `CandidateLogicalASAPDAGs::cost_sorted_with_recurrence` | Cost model, recurrence profiles, optional horizon | Ranked per-target candidate sets or `RecurrenceError`; uses recurrence for applicable share/recompute comparisons |
-| `SketchAlgorithmStrategy::replacements` through `ReplacementStrategy` | One `TargetSubDAG` | Alternatives at that target; not whole-workload search |
+| `ASAPStrategies::replacements` through `ReplacementStrategy` | One `TargetSubDAG` | Alternatives at that target; not whole-workload search |
 
 `cost_sorted` is a ranking view, not a request to discard all but the first
 candidate. Display costs follow model hooks and may be unavailable/non-finite;
@@ -279,12 +280,12 @@ choices are not multiplied in. Exceeding `expansion_limit` is an error, never a
 partial inventory.
 
 For PromQL roots that carry a target, `search_workload_with_targets` also asks
-each strategy's `ReplacementStrategy::propose_for_root`. `SketchAlgorithmStrategy`
+each strategy's `ReplacementStrategy::propose_for_root`. `ASAPStrategies`
 answers an instant-vector TopK with current-series heap realizations over rows
 carrying the complete series identity (`$promql_series_identity`). They are
 finalized, deduplicated, and marked `ReplacementProvenance::RootPhysicalRealization`.
 Callers do not apply `with_series_identity` themselves. Compile each with
-`promql_rows::compile_current_series_readout`; other queries keep their previous
+`promql_rows::compile_current_series_evaluation`; other queries keep their previous
 inventory. `global_selection` never commits these candidates; the backend
 compiles and prices them. CandidateLogicalASAPDAGs lists no placement variants: node timing
 comes from the summary maintenance lifecycle.
@@ -300,11 +301,11 @@ pass. An omitted strategy contributes no proposals of its own.
 
 | Value to put inside `Box::new(...)` | Meaning | In default factories? |
 | --- | --- | --- |
-| `SketchAlgorithmStrategy::new(&model)` | Enumerates supported exact/sketch implementations and parameter choices for aggregate targets | Yes |
+| `ASAPStrategies::new(&model)` | Enumerates supported exact/sketch implementations and parameter choices for aggregate targets | Yes |
 | `HydraGroupingStrategy::new(&model)` | Considers a shared multi-subpopulation structure for supported grouped sketch families, subject to accuracy evidence | Yes |
 | `SharedSubDAGStrategy` | Proposes sharing versus independent recomputation at reused sub-DAGs | Yes |
 | `SemanticEquivalentRewriteStrategy` | Proposes supported equivalent aggregate rewrites, including decomposing average into sum/count | Yes |
-| `ExactCompositionStrategy::new(&model)` | Proposes supported exact operations around summary readouts or in maintenance | Yes |
+| `ExactCompositionStrategy::new(&model)` | Proposes supported exact operations around summary evaluations or in maintenance | Yes |
 | Your `ReplacementStrategy` implementation | Adds domain-specific legal replacement proposals | No |
 
 `AvgToSumOverCountStrategy` is an alias for `SemanticEquivalentRewriteStrategy`
@@ -345,7 +346,6 @@ replacement::default_strategies_with_evidence<'a>(
 ### Example: supply two strategies and run search
 
 ```rust
-use std::rc::Rc;
 use asap_frontend_promql::lower_promql_workload;
 use asap_types::workload::{
     AccuracyRequirement, BatchEntry, DataWorkload, DurationMs, Evidence, Query,
@@ -353,7 +353,7 @@ use asap_types::workload::{
 };
 use asap_aware_mapping::{
     search_workload_with_targets, DefaultAccuracyModel, DefaultCostModel,
-    ReplacementStrategy, SketchAlgorithmStrategy, SharedSubDAGStrategy,
+    ReplacementStrategy, ASAPStrategies, SharedSubDAGStrategy,
 };
 use asap_types::types::AccuracyTarget;
 
@@ -383,10 +383,10 @@ fn main() -> Result<(), Box<dyn std::error::Error>> {
             ..Default::default()
         }),
     };
-    let root = Rc::new(lower_promql_workload(&workload, 0)?.remove(0));
+    let root = lower_promql_workload(&workload, 0)?.remove(0);
     let model = DefaultCostModel;
     let strategies: Vec<Box<dyn ReplacementStrategy + '_>> = vec![
-        Box::new(SketchAlgorithmStrategy::new(&model)),
+        Box::new(ASAPStrategies::new(&model)),
         Box::new(SharedSubDAGStrategy),
     ];
     let space = search_workload_with_targets(
@@ -442,7 +442,7 @@ accuracy guarantees.
 ```rust
 use asap_aware_mapping::{
     DefaultAccuracyModel, DefaultCostModel, EqualSplitAllocator,
-    NoAccuracyEvidence, ReplacementStrategy, SketchAlgorithmStrategy,
+    NoAccuracyEvidence, ReplacementStrategy, ASAPStrategies,
 };
 
 fn main() {
@@ -451,7 +451,7 @@ fn main() {
     let allocation = EqualSplitAllocator;
     let evidence = NoAccuracyEvidence;
     let strategies: Vec<Box<dyn ReplacementStrategy + '_>> = vec![Box::new(
-        SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+        ASAPStrategies::new_with_planning_inputs_and_evidence(
             &cost, &accuracy, &allocation, &evidence,
         ),
     )];
@@ -463,16 +463,16 @@ fn main() {
 Constructor definition:
 
 ```text
-SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence(
+ASAPStrategies::new_with_planning_inputs_and_evidence(
     cost_model: &dyn CostModel,
     accuracy_model: &dyn AccuracyModel,
     allocator: &dyn AccuracyBudgetAllocator,
     evidence: &dyn AccuracyEvidenceProvider,
-) -> SketchAlgorithmStrategy
+) -> ASAPStrategies
 ```
 
 All provider arguments are required for this constructor. They must outlive the
-strategy vector. `SketchAlgorithmStrategy::new(&cost_model)` is the shorter
+strategy vector. `ASAPStrategies::new(&cost_model)` is the shorter
 constructor using default accuracy/allocation and no extra evidence.
 
 | Extension point | What it controls | What it cannot establish alone |
@@ -488,7 +488,7 @@ with the intended model/evidence; replacing only the final sorting model does no
 regenerate parameter choices. For evidence-aware defaults, use
 `asap_aware_mapping::replacement::default_strategies_with_evidence`.
 For custom accuracy/allocation/evidence on sketches,
-`SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence` exposes these providers.
+`ASAPStrategies::new_with_planning_inputs_and_evidence` exposes these providers.
 Keep each provider's evidence scope and freshness valid for the query population.
 
 ## Workload inputs and defaults
@@ -525,7 +525,7 @@ Use this workflow when Planner owns summary-maintenance lifecycle decisions;
 otherwise the backend may make them from logical candidates. It includes both
 selection and DAG assembly, so callers do not first run the ordinary workflow.
 The first helper returns one `GlobalSelection`; the second is called per root
-and returns a plan containing `root: Rc<SummaryNode>` plus maintenance decisions.
+and returns a plan containing `root: Rc<OperatorNode>` (already timed) plus maintenance decisions.
 See the [workflow design](../design_docs/architecture/input-output-workflow.md#summary-maintenance-lifecycle-aware-helper).
 
 Two capabilities are distinct: the runtime can orchestrate a lifecycle, and the
@@ -542,7 +542,7 @@ global_selection_with_summary_maintenance_lifecycles<'a, Id>(
 ) -> Result<GlobalSelection<'a>, SummaryMaintenanceLifecycleSelectionError>
 
 assemble_selected_dag_with_summary_maintenance_lifecycles(
-    selection: &GlobalSelection<'_>, target: &Rc<QueryExpr>,
+    selection: &GlobalSelection<'_>, target: &Rc<OperatorNode>,
     demand: WorkloadDemand<'_>, now_ms: u64, horizon: Option<Horizon>,
     capabilities: SummaryMaintenanceLifecycleCapabilities, cost_model: &dyn CostModel,
 ) -> Result<Option<SummaryMaintenanceLifecyclePlan>, SummaryMaintenanceLifecycleAssemblyError>
@@ -735,7 +735,7 @@ workflow for those decisions. Downstream still owns physical commitment.
 | --- | --- |
 | `CandidateLogicalASAPDAGs::global_selection(&model)` | Compatible structural selection across targets; no recurrence or lifecycle planning implied |
 | `CandidateLogicalASAPDAGs::global_selection_with_recurrence(...)` | Compatible selection using supplied recurrence profiles/horizon; no lifecycle commitments implied |
-| `GlobalSelection::assemble_selected_dag(&target)` | `Result<Option<Rc<SummaryNode>>, RealizationError>`; constructs semantic IR, not stored summary data |
+| `GlobalSelection::assemble_selected_dag(&target)` | `Result<Option<Rc<OperatorNode>>, RealizationError>`; constructs untimed semantic IR, not stored summary data |
 
 Use a target associated with the searched space; DAG assembly can return `None`
 when that target is absent. A downstream integration can use these convenience
@@ -747,8 +747,8 @@ for checking complete physical alternatives and deployment constraints.
 
 ```text
 CandidateLogicalASAPDAGs::global_selection(&self, cost_model: &dyn CostModel) -> GlobalSelection<'_>
-GlobalSelection::assemble_selected_dag(&self, target: &Rc<QueryExpr>)
-    -> Result<Option<Rc<SummaryNode>>, RealizationError>
+GlobalSelection::assemble_selected_dag(&self, target: &Rc<OperatorNode>)
+    -> Result<Option<Rc<OperatorNode>>, RealizationError>
 ```
 
 For structural inspection only, this complete example selects a semantic root
@@ -756,7 +756,6 @@ and exports its inspection DAG. It performs no lifecycle or deployment planning.
 Use lifecycle-aware selection above when the comparison needs those decisions.
 
 ```rust
-use std::rc::Rc;
 use asap_frontend_promql::lower_promql_workload;
 use asap_types::workload::{
     AccuracyRequirement, BatchEntry, DataWorkload, DurationMs, Evidence, Query,
@@ -790,7 +789,7 @@ fn main() -> Result<(), Box<dyn std::error::Error>> {
             ..Default::default()
         }),
     };
-    let root = Rc::new(lower_promql_workload(&workload, 0)?.remove(0));
+    let root = lower_promql_workload(&workload, 0)?.remove(0);
     let space = search_workload(vec![("q1", root)]);
     let selection = space.global_selection(&DefaultCostModel);
     // Search may canonicalize roots; use the root returned by CandidateLogicalASAPDAGs.
@@ -806,11 +805,12 @@ fn main() -> Result<(), Box<dyn std::error::Error>> {
 
 | Function/type | Purpose |
 | --- | --- |
-| `asap_types::dag_export::export(&query)` | Pre-ASAP inspection DAG |
-| `asap_types::dag_export::export_summary(&summary)` | Post-ASAP inspection DAG |
-| `asap_types::post_asap::compile_post_asap_dag(&root)` | Compile a semantic DAG with execution-data-state validation; not a physical plan |
+| `asap_types::dag_export::export(&query)` | Pre-ASAP inspection dag |
+| `asap_types::dag_export::export_summary(&summary)` | Post-ASAP inspection dag |
+| `asap_types::ir::apply_lifecycle_timings(&root, &assignment, &mut TimingMemo::new())` | Write execution timing into every node from a `LifecycleAssignment` and validate the data-state edges; a lifecycle plan's `root` is already timed |
+| `asap_types::ir::export::compile_post_asap_dag(&timed_root)` | Export a timed DAG as a `PostAsapDAG` (wire version 7); rejects an untimed node; not a physical plan |
 | `PostAsapDAGDocument::new(dag)` and `.validate()` | Versioned semantic envelope and explicit validation; constructing it alone does not validate |
-| `asap_aware_mapping::export_summary_maintenance_plan(&plan)` | DAG plus lifecycle deployments, alternatives and available cost/guarantee information |
+| `asap_aware_mapping::export_summary_maintenance_plan(&plan)` | Graph plus lifecycle deployments, alternatives and available cost/guarantee information |
 | `explain_replacements` / `explain_replacements_with` | Findings from default/custom-strategy search; not a complete physical feasibility report |
 
 Choose the export matching your intended handoff: an inspection DAG is not
diff --git a/docs/develop_docs/metrics-observability-corpora.md b/docs/develop_docs/metrics-observability-corpora.md
index d127e92ce..129ea0af1 100644
--- a/docs/develop_docs/metrics-observability-corpora.md
+++ b/docs/develop_docs/metrics-observability-corpora.md
@@ -49,19 +49,19 @@ o11y-bench, and awesome-prometheus-alerts. They are not duplicated here.
 
 The test prints totals, parse errors, lowering errors, pre-ASAP successes,
 post-ASAP candidates, unchanged queries, and post-ASAP errors. `Pre-ASAP` means
-that parsing and lowering produced a `QueryExpr`. `Post-ASAP candidate` means
-the isolated `SketchAlgorithmStrategy` produced a non-`KeepPreAsap` summary
-candidate. `Unchanged` is a successful pre-ASAP query for which that strategy
-returned only the pre-ASAP fallback.
+that parsing and lowering produced an `OperatorNode` DAG. `Post-ASAP candidate`
+means the isolated `ASAPStrategies` produced a candidate that contains
+an ASAP operator (`contains_asap()`). `Unchanged` is a successful pre-ASAP query
+for which that strategy returned only the kept pre-ASAP sub-DAG (`retain_exact`).
 
 ## Strategies
 
 The corpus measurement deliberately uses only
-`SketchAlgorithmStrategy::default_cost_model().replacements(...)` on each
+`ASAPStrategies::default_cost_model().replacements(...)` on each
 query root. It does not measure workload-wide search or the other default
 strategies.
 
-The default workload search currently registers `SketchAlgorithmStrategy`,
+The default workload search currently registers `ASAPStrategies`,
 `HydraGroupingStrategy`, `SharedSubDAGStrategy`, and
 `AvgToSumOverCountStrategy`. Workload context can additionally contribute
 `RollupStrategy` and `AccuracyReconciliationStrategy`. This baseline is
diff --git a/docs/develop_docs/native-promql-inputs.md b/docs/develop_docs/native-promql-inputs.md
index d263b7825..d2c10f535 100644
--- a/docs/develop_docs/native-promql-inputs.md
+++ b/docs/develop_docs/native-promql-inputs.md
@@ -23,7 +23,7 @@ operator's metric-name/result-label rules. Source selection, complete window
 coverage and revision admission remain deployment responsibilities.
 
 Planner's maintained-population candidate recognizes this explicit identity
-representation. Its TopK readout compiles automatically to `CurrentSeries`,
+representation. Its TopK evaluation compiles automatically to `CurrentSeries`,
 `Sort`, and `Limit`; deployment supplies the raw boundary or an already maintained
 population boundary. Compilation does not open either source.
 
diff --git a/docs/develop_docs/offline-sketch-evidence.md b/docs/develop_docs/offline-sketch-evidence.md
index cd331e57d..56c507de1 100644
--- a/docs/develop_docs/offline-sketch-evidence.md
+++ b/docs/develop_docs/offline-sketch-evidence.md
@@ -91,7 +91,7 @@ hooks. The provider's lifecycle helper returns available build/update CPU costs
 for a single independently instantiated state. It deliberately leaves retention,
 retirement and read costs unknown. In particular, a point-frequency benchmark
 read does not price a total-count read, even when both use CMS. A deployment must
-match readout semantics and supply the missing lifecycle and raw-query evidence
+match evaluation semantics and supply the missing lifecycle and raw-query evidence
 before selecting and pricing a complete physical plan. Never combine these
 nanosecond costs with CPU operation counts without explicit calibration.
 
@@ -116,7 +116,7 @@ not be passed as these disjoint phase measurements.
 
 `MeasurementQueryBinding` is the producer's explicit assertion identifying the
 read/error probe population. The consumer checks that binding and the error
-record's readout kind/value type; it cannot recover or certify the original
+record's evaluation kind/value type; it cannot recover or certify the original
 probe set from an aggregate error number alone.
 
 The supported workload is an immutable i64 point-frequency snapshot, fully
@@ -131,7 +131,7 @@ post-merge error and an exact merge baseline exist.
 
 The caller supplies an `EmpiricalAccuracyRequirement`: the exact observed error
 metric, maximum accepted mean, and minimum number of offline trials. This is
-separate from `AccuracyTarget`. Every candidate must match the readout descriptor,
+separate from `AccuracyTarget`. Every candidate must match the evaluation descriptor,
 error metric, trial count and all ordinary distribution/configuration/environment
 checks. A zero observed error is neither proof of exactness nor a per-key bound.
 
diff --git a/docs/develop_docs/physical-compile-coverage.md b/docs/develop_docs/physical-compile-coverage.md
index 5d048d7f7..b8db36c7b 100644
--- a/docs/develop_docs/physical-compile-coverage.md
+++ b/docs/develop_docs/physical-compile-coverage.md
@@ -8,7 +8,7 @@ Audience: developers moving computation from ASAPQuery-backend into
 Logical selection decides what to compute. The maintenance lifecycle sets node
 timing. `physical_planner::compile` turns a timed `PostAsapDAG` into physical
 operator DAGs. The backend owns ingestion, panes, storage, stored-state
-readout, external exact engines, pricing/selection, and execution scheduling.
+evaluation, external exact engines, pricing/selection, and execution scheduling.
 
 A backend lowering is *covered* when `compile` accepts the corresponding
 `PostAsapDAG` node and produces operators with the same result. The backend
@@ -29,7 +29,7 @@ Status values:
 
 | # | Backend site | Computation | Planner node | Status at #475 | Notes |
 |---|---|---|---|---|---|
-| 1 | `query_time.rs` `Lower::lower`, `compile_logical` | PromQL AST → `QueryTimeOperator` DAG for a native query | `Fallback { QueryExpr }` sub-DAGs plus value payloads | Missing | `compile` lowers `Fallback` only as a raw `Scan` source. |
+| 1 | `query_time.rs` `Lower::lower`, `compile_logical` | PromQL AST → `QueryTimeOperator` dag for a native query | `Fallback { QueryExpr }` sub-DAGs plus value payloads | Missing | `compile` lowers `Fallback` only as a raw `Scan` source. |
 | 2 | `QueryTimeOperator::Aggregate` (sum/min/max/avg/count) | Grouped value aggregation | `Value::Exact(Aggregate)`; `SummaryAgg{ExactAggregate, Reduce}` over finalized values | Supported | Also `promql_values::compile_aggregate`. |
 | 3 | `QueryTimeOperator::Sort`, `Limit` (topk, sort, sort_desc) | Ordering and per-group limits | `Value::Sort`, `Value::Limit` | Supported | |
 | 4 | `QueryTimeOperator::Binary`, `QueryPlanNode::Binary` (vector ⊗ scalar) | Arithmetic with a scalar operand | `Binary` whose operand is `Fallback{PromqlScalarBridge(Literal)}` | Missing | Query-time `Binary` accepts only label-map vector schemas. The literal node has no native binding. |
@@ -43,15 +43,15 @@ Status values:
 | 12 | `logical_dag.rs` `Subquery`, `subquery_grid`, `expanded_inputs` | Re-evaluate the child on a step grid and assemble a matrix | `Fallback{PromqlSubquery}` | Missing | No Planner operator. |
 | 13 | `QueryPlanNode::Scalar`, `DAGCompiler::lower` scalar literal | Scalar constant | `Fallback{PromqlScalarBridge(Literal)}` | Missing | Only `promql_values::compile_scalar`. |
 | 14 | `DAGCompiler::lower` `ReduceSum`; `physical_values.rs` PerEntity projection | Sum over finalized values; per-entity identity | `SummaryAgg{ExactAggregate(Sum)}` | Supported | The backend builds an identity `Operator::project` itself for PerEntity. |
-| 15 | `DAGCompiler::lower` `ExactReadout`; `post_asap_readout.rs` ExactReadout | Finalize exact state (sum/count/min/max/rate/increase) | `Value::FinalizeExactAccumulator` | Partial | Count yields Int64 against a declared Float64 PromQL value. `compile` rejects it. |
-| 16 | `post_asap_readout.rs` SummaryEstimate (`readout_bound`, `expand_item_rows`) | Sketch estimate per group; TopK item expansion | `SummaryEstimate` | Partial | The backend's label-map state layout and MetricsQL `__name__` rules have no Planner equivalent. `compile_exact_readout` has no sketch counterpart. |
-| 17 | `post_asap_readout.rs` SummaryMerge (`merge_bound_states`) | Merge states by group | `SummaryMerge` | Supported | Union plus `summary_merge`. |
-| 18 | `post_asap_readout.rs` counter range parameters | Counter lookback for rate/increase | `TimeRange` ancestor of finalization | Supported | Applied through `with_counter_lookback`. |
-| 19 | `post_asap_readout.rs` `execute_value_fragment` | Per-timestamp binding of a value fragment | n/a | Backend | Evaluation scheduling. |
+| 15 | `DAGCompiler::lower` `ExactEvaluation`; `post_asap_evaluation.rs` ExactEvaluation | Finalize exact state (sum/count/min/max/rate/increase) | `Value::FinalizeExactAccumulator` | Partial | Count yields Int64 against a declared Float64 PromQL value. `compile` rejects it. |
+| 16 | `post_asap_evaluation.rs` SummaryEstimate (`evaluation_bound`, `expand_item_rows`) | Sketch estimate per group; TopK item expansion | `SummaryEstimate` | Partial | The backend's label-map state layout and MetricsQL `__name__` rules have no Planner equivalent. `compile_exact_evaluation` has no sketch counterpart. |
+| 17 | `post_asap_evaluation.rs` SummaryMerge (`merge_bound_states`) | Merge states by group | `SummaryMerge` | Supported | Union plus `summary_merge`. |
+| 18 | `post_asap_evaluation.rs` counter range parameters | Counter lookback for rate/increase | `TimeRange` ancestor of finalization | Supported | Applied through `with_counter_lookback`. |
+| 19 | `post_asap_evaluation.rs` `execute_value_fragment` | Per-timestamp binding of a value fragment | n/a | Backend | Evaluation scheduling. |
 | 20 | `DAGCompiler::lower` SummaryJoin / Subtract / Delete | Summary algebra | `SummaryJoin`, `SummarySubtract`, `SummaryDelete` | Missing | The backend also rejects these (`ExactFallback`). |
-| 21 | `current_series.rs` Snapshot + TopK | Current-series ranking | `ReadPopulation{TopK}` | Supported | |
-| 22 | `current_series.rs` Sum / Count / Average | Current-series aggregates | `ReadPopulation{Sum,Count,Average}` | Missing | `compile` accepts only TopK. |
-| 23 | `current_series.rs` Quantile | Current-series quantile | `ReadPopulation{Quantile}` | Missing | No exact quantile reduction. |
+| 21 | `current_series.rs` Snapshot + TopK | Current-series ranking | `EvaluatePopulation{TopK}` | Supported | |
+| 22 | `current_series.rs` Sum / Count / Average | Current-series aggregates | `EvaluatePopulation{Sum,Count,Average}` | Missing | `compile` accepts only TopK. |
+| 23 | `current_series.rs` Quantile | Current-series quantile | `EvaluatePopulation{Quantile}` | Missing | No exact quantile reduction. |
 | 24 | `raw_dag.rs` weight `Column` | Summary update from a sample/projected value | `SummaryAgg` | Supported | |
 | 25 | `raw_dag.rs` weight `Constant` | Unit/constant-weight update | `SummaryAgg` | Missing | `compile_node` requires a column weight. |
 | 26 | `raw_dag.rs` item `Column` / `Tuple` | Keyed update item | `SummaryAgg{item}` | Supported | `keyed_summary_build`. |
@@ -70,7 +70,7 @@ Totals at #475: 11 Supported, 4 Partial, 14 Missing, 2 Backend.
 | 4, 8, 13 | Query-time `Binary` folds a scalar-literal operand into a projection over grouped value rows. |
 | 5 | Query-time `Binary` over grouped value rows performs an inner equi-join on equal label columns, then applies the operator. Per-series rows remain Partial. |
 | 15 | Count finalization converts exactly to the declared Float64 value. |
-| 22, 23 | `ReadPopulation` Sum/Count/Average/Quantile compile to grouped aggregation. `Reduction::Quantile` implements PromQL interpolation. |
+| 22, 23 | `EvaluatePopulation` Sum/Count/Average/Quantile compile to grouped aggregation. `Reduction::Quantile` implements PromQL interpolation. |
 
 Totals after this change: 17 Supported, 4 Partial, 8 Missing, 2 Backend.
 
@@ -124,10 +124,10 @@ Totals are unchanged: 19 Supported, 5 Partial, 5 Missing, 2 Backend.
 
 | Row | Change |
 |---|---|
-| 5 | Query-time `Binary` over rows with a series identity, such as per-series readouts of stored state, uses the Fallback's `series_labels` and `series_binary`. Examples: `avg_over_time` as stored sum/count, and `rate(a) / rate(b)`. Matching drops `__name__` and honors `on`/`ignoring` when the payload carries them. Only one-to-one arithmetic is covered; `group_left`/`group_right` stay rejected and comparisons are row 7. Now Supported. |
+| 5 | Query-time `Binary` over rows with a series identity, such as per-series evaluations of stored state, uses the Fallback's `series_labels` and `series_binary`. Examples: `avg_over_time` as stored sum/count, and `rate(a) / rate(b)`. Matching drops `__name__` and honors `on`/`ignoring` when the payload carries them. Only one-to-one arithmetic is covered; `group_left`/`group_right` stay rejected and comparisons are row 7. Now Supported. |
 | 4, 8 | A literal operand also applies to per-series rows and drops `__name__`, in the Fallback too. Series whose label sets become equal are an error, as in Prometheus. |
 
-Grouped `sum`/`avg`, current-series `Sum`/`Average` readouts, and
+Grouped `sum`/`avg`, current-series `Sum`/`Average` evaluations, and
 `sum_over_time`/`avg_over_time` use Prometheus' Kahan-Neumaier summation. An
 average switches to an incremental mean once the running sum would overflow.
 The grouped path also serves SQL `SUM`/`AVG` over Float64, which are now
@@ -175,7 +175,7 @@ and `group_left`, including a right-side series identity when needed. Thus
 |---|---|
 | 1 | Comparisons, `bool`, set operators, `group_left`/`group_right`, `scalar()` operands, and literals over aggregates whose value has another name, such as `sum by (job) (a) * 2`. Still Partial. |
 | 5 | Grouped `Binary` rows use the same operator instead of a relational join. A duplicate match group is now an error instead of a cross product. |
-| 7 | Fallback, grouped `Binary`, and per-series comparisons and sets. Temporal stored readouts drop `__name__` before matching, including exact Count conversion, and reject duplicate output identities. |
+| 7 | Fallback, grouped `Binary`, and per-series comparisons and sets. Temporal stored evaluations drop `__name__` before matching, including exact Count conversion, and reject duplicate output identities. |
 
 Totals after this change: 20 Supported, 5 Partial, 4 Missing, 2 Backend.
 
@@ -188,7 +188,7 @@ Totals after this change: 20 Supported, 5 Partial, 4 Missing, 2 Backend.
 An argument whose output provably lacks `le`, such as
 `sum by (job) (rate(x_bucket[5m]))`, is rejected at lowering. Prometheus
 returns an empty vector for it. Candidate search keeps the classic form as one
-exact `KeepPreAsap` sub-DAG for every accuracy target; it has no sketch
+retained exact ordinary sub-DAG for every accuracy target; it has no sketch
 candidate. `histogram_quantiles` lowers each branch the same way; the
 Fallback compiler accepts its `Concat` of relabeled branches and rejects
 duplicate output label sets. Nested aggregation, such as
@@ -208,8 +208,8 @@ In order of backend usage:
    After these shapes are covered, the backend can delete rows 28 and 30.
 2. Rows 25 and 27: constant weights and `EntityIdentity` items for precompute
    `SummaryAgg`.
-3. Row 16: a label-map sketch-state readout, the counterpart of
-   `compile_exact_readout`, and MetricsQL `__name__` retention rules.
+3. Row 16: a label-map sketch-state evaluation, the counterpart of
+   `compile_exact_evaluation`, and MetricsQL `__name__` retention rules.
 4. Row 20: summary join, subtract, and delete.
 
 `fill`, `fill_left`, and `fill_right` matching modifiers are rejected by the
diff --git a/docs/develop_docs/planner-vocabulary-migration.md b/docs/develop_docs/planner-vocabulary-migration.md
index ea46e992c..d4b29fecd 100644
--- a/docs/develop_docs/planner-vocabulary-migration.md
+++ b/docs/develop_docs/planner-vocabulary-migration.md
@@ -32,8 +32,8 @@ names.
 | Physical evidence/comparison `boundaries` fields | `handoffs` |
 | `BoundaryEstimate::per_boundary` | `PhysicalHandoffEstimate::per_handoff` |
 | Internal `Models` | `CandidatePlanningInputs` |
-| `SketchAlgorithmStrategy::with_models` | `SketchAlgorithmStrategy::new_with_planning_inputs` |
-| `SketchAlgorithmStrategy::with_models_and_evidence` | `SketchAlgorithmStrategy::new_with_planning_inputs_and_evidence` |
+| `ASAPStrategies::with_models` | `ASAPStrategies::new_with_planning_inputs` |
+| `ASAPStrategies::with_models_and_evidence` | `ASAPStrategies::new_with_planning_inputs_and_evidence` |
 | `HydraGroupingStrategy::with_models_and_evidence` | `HydraGroupingStrategy::new_with_planning_inputs_and_evidence` |
 
 For example, `Binder::new().bind(&dag)` becomes
diff --git a/docs/develop_docs/pre-asap-ir.md b/docs/develop_docs/pre-asap-ir.md
index abf5dc50b..0a5c21ec6 100644
--- a/docs/develop_docs/pre-asap-ir.md
+++ b/docs/develop_docs/pre-asap-ir.md
@@ -2,7 +2,15 @@
 
 This is the detailed node reference. Start with the [Pre-ASAP IR concept](../design_docs/concepts/pre-asap-ir.md) for purpose and the compact catalog.
 
-The goal of the pre-ASAP IR is represent operations from different query languages in a single representation, and make it easier to analyze how/where ASAP primitives can be used.
+ASAPPlanner has **one operator IR before and after ASAP optimization**, defined in
+`crates/types/src/ir/`. "Pre-ASAP" is not a separate type: it is this IR as a front end
+emits it, before any ASAP operator has been introduced. This document covers what every
+plan shares — the node, the schema, scalar expressions, how front ends produce the DAG, and
+the catalog of ordinary (`NonASAPOp`) operators. The ASAP operators, execution timing and
+the exported wire form are described in the [Post-ASAP IR](../design_docs/concepts/post-asap-ir.md)
+document; the two do not repeat each other.
+
+The goal of the pre-ASAP form is to represent operations from different query languages in a single representation, and make it easier to analyze how/where ASAP primitives can be used.
 Only operations that are semantically relevant to answering the query and selecting an ASAP primitive need to become first-class nodes here.
 
 ## Design principles
@@ -13,7 +21,135 @@ Only operations that are semantically relevant to answering the query and select
 
 > Notes: **SQL and PromQL use different schema models**. SQL typically uses a closed schema, where tables, columns, and types are predefined, while PromQL uses an open (schemaless) schema, where metrics and labels can evolve without a fixed table schema. Closed schemas provide stronger structure and validation; open schemas provide greater flexibility and makes it easier to evolve or ingest diverse data, but can require more care around naming conventions, label cardinality, and query consistency.
 
-The pre-ASAP IR is defined using the `QueryExpr` enum. We discuss some of important enum types below.
+## The node
+
+A plan is a DAG of `Rc<OperatorNode>` (`crates/types/src/ir/node.rs`). Nodes are immutable
+and shared through `Rc`: a structurally identical sub-DAG referenced from several parents is
+one node, and that pointer identity is what CSE, target discovery and plan assembly key on.
+
+```rust
+pub struct OperatorNode {
+    pub operator: Operator,                   // NonASAP(NonASAPOp) | ASAP(ASAPOp)
+    pub result_kind: OperatorResultKind,      // Relation | InstantVector | RangeVector | State | Scalar
+    pub schema: Schema,                       // output schema, derived at construction
+    pub guarantee: Option<ResultGuarantee>,   // None until accuracy assessment establishes one
+    pub timing: Option<ExecutionTiming>,      // None until a lifecycle assignment is applied
+}
+```
+
+- `operator` is the operation. A front-end DAG contains only `Operator::NonASAP` nodes;
+  `OperatorNode::expect_non_asap()` relies on that.
+- `result_kind` is the output category, derived from the operator and its inputs. Matching
+  column schemas do not make categories interchangeable (a range vector is not an instant
+  vector).
+- `schema` is derived by `OperatorNode::new(operator)`; it fails when the schema cannot be
+  derived (a column reference out of range, a reserved ASAP operator). ASAP planning may
+  retain a more specific schema through `OperatorNode::with_schema`.
+- `guarantee` is `None` until accuracy assessment establishes one; `None` never means exact.
+- `timing` is `None` in every front-end DAG and every candidate. It is written by
+  `ir::timing::apply_lifecycle_timings` (see the Post-ASAP IR document); export rejects an
+  untimed node.
+
+`OperatorNode::children()` returns the operator's inputs in field order followed by the
+operator nodes its scalar expressions read (see "Scalar expressions"). Every DAG traversal —
+`map_children`, `reachable`, `contains_asap`, CSE, export — follows that same list.
+`OperatorNode::validate_structure()` checks every operator's input contract, scalar typing
+against the owning operator's input schema, and that each retained schema agrees with the
+derived one.
+
+## Schema
+
+One `Schema` type (`crates/types/src/pre_asap/schema.rs`) describes every edge, whether it
+carries rows or summary state:
+
+```rust
+pub struct Schema {
+    pub fields: Vec<Field>,            // positional; every ColumnId indexes into this
+    pub time_index: Option<ColumnId>,  // the time axis, if any (PromQL leaves always have one)
+    pub unique_keys: Vec<Vec<ColumnId>>,
+    pub closed: bool,                  // true: these are all the columns; false: open (schemaless) superset
+}
+
+pub struct Field {
+    pub name: String,
+    pub dtype: FieldDataType,          // Plain(DataType) | ExactAggregate(..) | Sketch(..) | Sample(..) | Wavelet(..) | StatModel(..)
+    pub nullable: bool,
+    pub table: Option<String>,         // SQL table/alias qualifier; None for PromQL labels
+}
+```
+
+A pre-ASAP field is always `FieldDataType::Plain(DataType)`. The other variants carry summary
+state and only appear below an ASAP operator; a scalar expression that reads such a field is a
+typing error (`ScalarExpr::scalar_type`), because state must be read out before a value can use
+it. Column references are positional `ColumnId`s (indexes into the input schema), never names.
+
+`Schema::has_unique_key()` is the legality gate CSE uses: a non-ASAP producer is only shared
+across consumers when its row identity is provable.
+
+## Scalar expressions
+
+Value computation lives in `ScalarExpr` (`crates/types/src/ir/scalar.rs`), owned **by value**
+by an operator field: `Scan.predicates`, `Filter.pred`, `Join.pred`, `Project.cols[i].expr`,
+`Aggregate.having`, `Sort.keys[i].expr`, `SQLWindowFunc.args`/`order_by`, `PromqlRelabel.value`,
+`Values.rows`, and `QueryRoot::Scalar` and `PromqlVectorFromScalar`. A scalar expression never
+produces a table and is never a node of the DAG; it is evaluated against the input schema of
+the operator that owns it.
+
+Variants: `Column(ColumnId)`, `Literal(ScalarValue)`, `Negative` (unary minus), `Compare`,
+`BoolAnd` / `BoolOr` (flat conjunction/disjunction), `Not`, `IsNull` / `IsNotNull`, `Cast`
+(with `try_cast`), `InList`, `FunctionCall { name, args }`, `Arithmetic`, `Case`,
+`CurrentTimestamp` (SQL `NOW()`), `EvalTimestamp` (PromQL `time()`), and four
+**plan-reading** variants that reference an operator node:
+
+| Variant | Meaning |
+|---|---|
+| `PromqlScalarFromVector(Rc<OperatorNode>)` | PromQL `scalar(v)`: the single sample of an instant vector, NaN otherwise |
+| `ScalarSubquery(Rc<OperatorNode>)` | Uncorrelated SQL scalar subquery: one column; zero rows is NULL, more than one row is an error |
+| `Exists { subquery, negated }` | SQL `[NOT] EXISTS (subquery)` |
+| `InSubquery { expr, subquery, negated }` | SQL `expr [NOT] IN (subquery)` over a one-column relation |
+
+These are the **only** operator references inside a scalar tree. `ScalarExpr::operator_refs()`
+lists them, `NonASAPOp::children()` appends them after the operator's own inputs, and
+canonicalization lowers the three SQL subquery forms to joins (see below), so a canonical SQL
+DAG contains none of them. `PromqlScalarFromVector` survives canonicalization: its referenced
+vector is a real plan dependency, exported as a `ScalarRef` edge.
+
+`Compare`, `Arithmetic` and `Negative` carry an `ExprSemantics` (`Sql` or `Promql`): both
+languages use `Float64`, so the result type alone does not preserve NaN, ordering or error
+rules, and the executing engine needs to know which language's rules apply.
+
+Wrapper types: `Predicate(ScalarExpr)`, `ProjectItem { alias, expr }`,
+`SortKey { expr, ascending, nulls_first }`.
+
+## How a front end produces the DAG
+
+A front end never constructs `OperatorNode`s directly. It builds a name-based tree in
+`crates/frontend-common` — `UnresolvedOp` / `UnresolvedScalar`, a mirror of `NonASAPOp` /
+`ScalarExpr` in which every column reference is a `ColumnRef` and a PromQL `Scan` has no schema
+yet — and calls `asap_frontend_common::resolve_root`, which does three things in order:
+
+1. **Resolution** — a bottom-up walk that binds every `ColumnRef` to a positional `ColumnId`
+   against the derived schema of the already-resolved child. A schemaless (PromQL) leaf gets
+   its binding schema from `SchemaResolver`, built from the names the query references.
+   `Join` / `SetOp` sides and the operators referenced from scalar positions are each bound as
+   a root in their own scope; a `BinaryOp` side additionally inherits the label names its
+   enclosing scope references.
+2. **Schema derivation** — each `OperatorNode::new` derives the node's output schema and
+   result kind from the operator and its children.
+3. **Canonicalization** — `asap_types::ir::canonicalize::canonicalize` erases structural
+   differences between semantically identical queries: it promotes an additive
+   `Limit { Sort { Aggregate } }` ranking to the `AggIntent::TopK` heavy-hitter shape, and
+   lowers `EXISTS` / `NOT EXISTS` / `IN (subquery)` predicates to `Join { Semi | Anti }` and a
+   scalar subquery to a `Join { Cross }` plus column reference. The pass is idempotent and
+   keeps the pointer identity of every untouched sub-DAG.
+
+The result is `Rc<OperatorNode>`. `lower_promql_workload`, `lower_sql` / `lower_sql_dialect` /
+`lower_sql_batch` and `lower_metricsql` all return it.
+
+Workload search then runs structural CSE (`asap_types::ir::cse::share_common_sub_dags`) once
+across every root: bottom-up hash-consing where the structural hash is only a filter and the
+typed `PartialEq` decides sharing, following scalar references like any other input, and
+gated by `Schema::has_unique_key()` for non-ASAP producers.
 
 ## Fields and column references
 
@@ -47,27 +183,28 @@ to one source language.
 - [`Aggregate`](#aggregate) — collapses input rows into fewer output rows via a reduction and aggregate intents.
 
 **[Time-related nodes](#time-related-nodes)**
-- [`TimeRange`](#timerange) — a range-vector lookback over the time axis (PromQL `[5m]`).
+- [`TimeRange`](#timerange) — temporal selection over a time-series input (PromQL instant lookback or `[5m]` range selector).
 - [`TimeShift`](#timeshift) — shifts *when* a selector is evaluated (PromQL `offset`/`@`).
 - [`PromqlSubquery`](#promqlsubquery) — re-evaluates an instant-vector expression over a range at a given step.
 
 **[Relational nodes](#relational-nodes)** — common to both SQL and PromQL
 - [`Scan`](#scan) — identifies the logical data source.
+- [`Values`](#values) — SQL `VALUES` rows, or the one empty row of a `SELECT` without `FROM`.
 - [`Filter`](#filter) — restricts rows using a predicate.
 - [`Project`](#project) — column projection (SQL `SELECT` list).
-- [`BinaryOp`](#binaryop) — arithmetic / comparison / boolean composition of two inputs.
+- [`BinaryOp`](#binaryop) — arithmetic / comparison / set composition of two inputs.
 - [`Sort`](#sort) — generic (non-heavy-hitter) order-by, optionally per-group.
-- [`Limit`](#limit) — caps the row count, with an offset.
+- [`Limit`](#limit) — caps the row count, with an offset, optionally per-group.
 - [`Dedup`](#dedup) — row-level deduplication.
 - [`Join`](#join) — logical join of two inputs.
 - [`SetOp`](#setop) — SQL's typed set operations (`UNION`/`INTERSECT`/`EXCEPT`).
 - [`Concat`](#concat) — exact, untyped `UNION ALL` of union-compatible branches.
 
-**[PromQL-specific nodes](#promql-specific-nodes)**
-- [`PromqlScalarBridge`](#promqlscalarbridge) — a scalar sub-expression at an operator-DAG position.
-- [`EvalTimestamp`](#evaltimestamp) — the query evaluation time as a scalar (PromQL `time()`).
+**[Scalar-position nodes](#scalar-position-nodes)**
+- `QueryRoot::Scalar` — a standalone scalar expression, without an operator node.
 - [`PromqlVectorFromScalar`](#promqlvectorfromscalar) — promotes a scalar to a label-less instant vector.
-- [`PromqlScalarFromVector`](#promqlscalarfromvector) — collapses a single-series vector to a scalar.
+
+**[PromQL-specific nodes](#promql-specific-nodes)**
 - [`PromqlRelabel`](#promqlrelabel) — per-series label rewrite (PromQL `label_replace`/`label_join`).
 - [`PromqlInfoEnrich`](#promqlinfoenrich) — left-join label enrichment from an info metric.
 - [`PromqlSeriesSample`](#promqlseriessample) — keeps a subset of whole series, not a reduction.
@@ -75,6 +212,9 @@ to one source language.
 **[SQL-specific nodes](#sql-specific-nodes)**
 - [`SQLWindowFunc`](#sqlwindowfunc) — SQL analytic window function (`OVER (...)`).
 
+PromQL `time()` and `scalar(v)` are scalar expressions (`ScalarExpr::EvalTimestamp`,
+`ScalarExpr::PromqlScalarFromVector`), not nodes.
+
 ## Aggregation-related nodes
 
 ### Aggregate
@@ -109,7 +249,7 @@ list of aggregate intents (`measures`).
   value is still recomputed by the agg intent, e.g. `Rate`), for a computation with no
   `by(...)` clause to attach to. `PerEntity` is different from `by` for all columns, because in PromQL, it is schemaless and you don't know all columns beforehand.
    E.g. PromQL `rate(http_requests_total[5m])`, which has one rate value
-  per input series:
+   per input series:
 
   ```text
   Aggregate(
@@ -117,7 +257,7 @@ list of aggregate intents (`measures`).
       measures = [Rate],
       output_names = [],
       having = None,
-      child = TimeRange(range = 5m, child = Scan("http_requests_total"))
+      child = TimeRange(range = 5m, kind = Range, child = Scan("http_requests_total"))
   )
   ```
 
@@ -224,7 +364,7 @@ Example for `filters`:
   `count(CASE WHEN p THEN x END)` (`p`, plus `x IS NOT NULL` when `x` is nullable), and from
   `count(expr)` over any other nullable `expr` (`expr IS NOT NULL`), because canonical `Count`
   counts rows and never consults its argument. A filtered measure has no summary binding yet:
-  `asap-aware-mapping` keeps such an `Aggregate` as `KeepPreAsap`, and canonicalization does
+  `asap-aware-mapping` retains such an `Aggregate` as an ordinary exact sub-DAG, and canonicalization does
   not promote a filtered count ranking to a heavy-hitter `TopK`.
 
 Example for `having`:
@@ -248,8 +388,8 @@ Example for `having`:
 
 **Rules/Invariants**: A filtering predicate will be passed to at the lowest node (closer to the leaves) in the AST/DAG that can express it — `Scan.predicates`,
    then `Aggregate.having`, then `Filter` as the fallback — so its constraint is visible at
-   the node it actually applies to, not behind an opaque wrapper, once pre-ASAP IR translates
-   to post-ASAP IR with summary binding. The upper nodes (closer to the root) in the AST/DAG can still have a `Filter` node with the same condition. This intentional duplication is for Summary related translation and optimizations.
+   the node it actually applies to, not behind an opaque wrapper, once summary binding reads it.
+   The upper nodes (closer to the root) in the AST/DAG can still have a `Filter` node with the same condition. This intentional duplication is for Summary related translation and optimizations.
 
    For example, `SELECT srcip, COUNT(*) AS cnt FROM packets GROUP BY srcip HAVING COUNT(*) > 10`
    pins `cnt > 10` to the lowest node that can express it, `Aggregate.having`:
@@ -282,7 +422,7 @@ Example for `having`:
    Both are valid at once, and neither is derived from the other: `having` is the canonical
    spot a summary-aware pass reads to decide whether `Aggregate` can bind to a summary, while
    the outer `Filter` is what a plain logical evaluator runs without knowing `having` exists. The duplication is forward-looking groundwork for
-   once HAVING-aware summary binding (pre-ASAP-IR to post-ASAP-IR translation) lands.
+   once HAVING-aware summary binding lands.
 
   Neither direction of that push-down is enforced yet: the SQL front end doesn't populate
   `having` from a real `HAVING` clause (#201), and canonicalization doesn't fold an existing
@@ -294,14 +434,21 @@ Example for `having`:
 
 ### TimeRange
 
-Represents a range of time. Kept different from `Filter` to treat time as an explicit concern.
+Temporal selection over a time-series input. Kept different from `Filter` to treat time as an
+explicit concern. `kind` records which samples a PromQL selector reads:
+
+- `TimeRangeKind::Instant` — an instant selector: `range` is the lookback horizon and the
+  latest eligible sample per series is selected (the planner injects the declared
+  `data_ingestion_interval` around a bare selector).
+- `TimeRangeKind::Range` — a range selector (`m[5m]`): every sample in the window.
 
 ```promql
 rate(http_requests_total[5m])
 ```
 
 **Fields:**
-- `range` — how far back to look (the PromQL `[5m]` duration).
+- `range` — how far back to look (the PromQL `[5m]` duration, or the instant lookback).
+- `kind` — `Instant` or `Range`.
 - `child` — the input the range applies to.
 
 ### TimeShift
@@ -350,9 +497,19 @@ the same logical data domain.
 **Fields:**
 - `source` — the logical data source (a table name or PromQL metric selector).
 - `predicates` — row-level filters pushed all the way down to this scan (Rules/Invariants
-  rule 1); enforced structurally at lowering time — a `Filter` directly over a `Scan` never
-  survives.
-- `schema` — the binding schema every positional column reference in the DAG resolves against.
+  rule 1): PromQL label matchers and pushed-down `WHERE` conjuncts.
+- `schema` — the binding schema every positional column reference in the tree resolves against.
+  A catalog-backed SQL leaf carries its catalog schema; a PromQL leaf carries the usage-derived
+  schema `SchemaResolver` built from the labels the query references.
+
+### Values
+
+SQL `VALUES` rows, or the one empty row of a `SELECT` without `FROM`
+(`SELECT 1 + 1`). Row expressions have no input-column scope.
+
+**Fields:**
+- `rows` — one `Vec<ScalarExpr>` per row.
+- `schema` — the output schema of the rows.
 
 ### Filter
 
@@ -386,6 +543,10 @@ that's neither a base scan column nor an aggregate output:
 SELECT * FROM (SELECT srcip, bytes_in + bytes_out AS total FROM packets) t WHERE total > 500
 ```
 
+A `Filter` whose predicate contains `EXISTS` / `NOT EXISTS` / `IN (subquery)` does not
+survive canonicalization: the conjunct becomes a `Join { Semi | Anti }` under the remaining
+predicate.
+
 **Fields:**
 - `pred` — the row-level predicate to apply.
 - `child` — the input being filtered.
@@ -406,18 +567,21 @@ SELECT srcip, dstip FROM packets
 
 ### BinaryOp
 
-Arithmetic / comparison / boolean composition. PromQL binary operators between two vectors,
-a vector and a scalar, or two scalars.
+Arithmetic / comparison / set composition of two operands. PromQL binary operators between two vectors,
+two vectors. Mixed vector/scalar arithmetic uses `Project`; non-bool comparison uses `Filter`. Standalone scalar expressions are `QueryRoot::Scalar`.
 
 ```promql
 up > 1
 ```
 
 **Fields:**
-- `op` — the arithmetic/comparison/boolean operator.
+- `operator` — a `BinaryOperator { kind, vector_match, checked_relative_division, checked_finite_division }`:
+  - `kind` — `BinaryOpKind::Arithmetic(..)`, `Compare(..)` or `Set(..)` (PromQL `and`/`or`/`unless`).
+  - `vector_match` — PromQL vector-matching modifiers (`on`/`ignoring`, `group_left`/`group_right`); `None` outside PromQL and the only supported value today.
+  - `checked_relative_division` / `checked_finite_division` — typed division guards set by summary planning, never by a front end (see [physical-plan integration](../design_docs/architecture/physical-plan-integration.md#conditional-temporal-average-lowering)).
+- `return_bool` — the PromQL `bool` modifier: a comparison returns `0`/`1` instead of filtering. Valid only for comparison operators.
 - `lhs` — the left operand.
 - `rhs` — the right operand.
-- `vector_match` — PromQL vector-matching modifiers (`on`/`ignoring`, `group_left`/`group_right`); `None` outside PromQL.
 
 ### Sort
 
@@ -429,7 +593,7 @@ sort_desc(up)
 ```
 
 **Fields:**
-- `keys` — the ordering columns/expressions and direction.
+- `keys` — the ordering expressions and direction (`SortKey`).
 - `partition_by` — grouping keys that make the ordering per-group instead of global; empty = a single global order.
 - `child` — the input being ordered.
 
@@ -443,8 +607,9 @@ topk(3, up)
 ```
 
 **Fields:**
-- `n` — the maximum number of rows to keep.
+- `n` — the maximum number of rows to keep; `None` is offset-only.
 - `offset` — how many leading rows to skip first.
+- `partition_by` — applies the limit per group (PromQL `topk by (..)`); empty = global.
 - `child` — the input being capped.
 
 ### Dedup
@@ -463,14 +628,16 @@ SELECT DISTINCT srcip, dstip FROM packets
 
 ### Join
 
-Logical join; the physical strategy (hash/merge/broadcast) is picked in the post-ASAP IR. SQL `JOIN`.
+Logical join; the physical strategy (hash/merge/broadcast) is picked downstream of the planner. SQL `JOIN`,
+and the shape canonicalization lowers subqueries to.
 
 ```sql
 SELECT u.prefix FROM bgp_updates u JOIN bgp_rib_state r ON u.prefix = r.prefix
 ```
 
 **Fields:**
-- `kind` — the join type (inner/left/right/full/semi/anti).
+- `kind` — the join type (`Inner`/`Left`/`Right`/`Full`/`Cross`/`Semi`/`Anti`). A semi/anti join
+  outputs the left input's columns alone, but its predicate resolves against `left ++ right`.
 - `pred` — the join condition.
 - `left` — the left input.
 - `right` — the right input.
@@ -496,7 +663,7 @@ SELECT srcip FROM packets UNION ALL SELECT dstip FROM packets
 never dedup. Used when a single `Aggregate` can't express the shape — the canonical case is
 PromQL `histogram_quantiles` (one branch per φ, each its own `HistogramQuantile` reduction
 relabeled with its `le` value) — and SQL `ROLLUP`/`CUBE`/`GROUPING SETS` (one branch per
-grouping level).
+grouping level). The output schema is the first child's.
 
 ```promql
 histogram_quantiles(rate(http_request_duration_seconds_bucket[5m]), "le", 0.5, 0.9)
@@ -504,39 +671,32 @@ histogram_quantiles(rate(http_request_duration_seconds_bucket[5m]), "le", 0.5, 0
 
 **Fields:**
 - `children` — the union-compatible branches to concatenate; must be non-empty.
+- `discriminator_unique_key` — an optional caller-proven compound unique key
+  `(discriminator, inner_key)` over the output; nothing verifies the claim.
 
-## PromQL-specific nodes
-
-### PromqlScalarBridge
+## Scalar-position nodes
 
-A scalar sub-expression (issue #220: in practice always `Literal(ScalarValue::Float64(_))` —
-a PromQL number literal, or a folded constant scalar expression) sitting at an **operator-DAG
-position** — a `BinaryOp` operand for `<vector> op <scalar>` thresholds and unit conversions,
-a `PromqlVectorFromScalar` child, or a whole query's root. This wrapper is what marks the
-position; it no longer duplicates `Literal`'s value the way the old `PromqlScalar(f64)` variant
-did.
-
-```promql
-up > 1
-```
+### Scalar query roots
 
-**Fields:** a single unnamed child `QueryExpr` — the wrapped scalar sub-expression.
+`QueryRoot` distinguishes an operator result from an owned `ScalarExpr`. It is
+an API root discriminator, not an operator. `2`, `time()`, and
+`scalar(sum(up)) + 1` therefore introduce no constant-wrapper nodes.
 
-### EvalTimestamp
+Use `lower_promql_query_workload` for mixed scalar/vector workloads. The
+operator-only convenience API rejects standalone scalar roots. `ParsedWorkload`
+retains each scalar's workload index; `PlanOutput::roots()` returns all results
+in workload order. Scalar plan reads remain exact and retain their operator
+references; summary selection currently operates on operator roots.
 
-The query **evaluation timestamp** as Unix seconds — PromQL `time()` — and the implicit
-input of the no-argument calendar functions (`hour()`, `day_of_week()`, ...). It is the
-instant or range-step at which the expression is evaluated, not inherently the current
-wall-clock time. The Prometheus instant-query HTTP API separately defaults an omitted
-`time` request parameter to the server's current time.
-
-```promql
-time()
-```
+`up * 2` projects the sample expression while retaining time and full series
+identity, removing the metric name. `up > 0` and `0 < up` filter the vector and
+retain its sample and name. `up > bool 0` projects a zero-or-one `Case`.
+Open label schemas acquire a full runtime series-identity field before this
+lowering. The runtime must populate that field with all labels.
 
 ### PromqlVectorFromScalar
 
-The scalar→instant-vector bridge — PromQL `vector(s)`. Promotes a scalar-typed child to a
+The scalar→instant-vector bridge — PromQL `vector(s)`. Promotes a scalar expression to a
 single label-less series carrying that value at every step, e.g. for dead-man's-switch
 patterns (`up or vector(0)`).
 
@@ -544,18 +704,9 @@ patterns (`up or vector(0)`).
 vector(1)
 ```
 
-**Fields:** a single unnamed child `QueryExpr` — the scalar-typed expression being promoted to a vector.
-
-### PromqlScalarFromVector
+**Fields:** a single unnamed `ScalarExpr` — the scalar being promoted to a vector.
 
-The instant-vector→scalar bridge — PromQL `scalar(v)`. Collapses a single-element vector to
-its value (NaN at runtime if the input isn't exactly one series).
-
-```promql
-scalar(up)
-```
-
-**Fields:** a single unnamed child `QueryExpr` — the single-series vector being collapsed to a scalar.
+## PromQL-specific nodes
 
 ### PromqlRelabel
 
@@ -616,5 +767,6 @@ SELECT srcip, LAG(time) OVER (PARTITION BY srcip ORDER BY time) FROM packets
 - `args` — the function's operand expressions; empty for rank-only functions.
 - `partition_by` — grouping keys the window is computed within.
 - `order_by` — the ordering the window function reads.
+- `frame` — the optional window frame.
 - `output_name` — the name of the new output column.
 - `child` — the input the window function is computed over.
diff --git a/docs/develop_docs/target-candidate-api-migration.md b/docs/develop_docs/target-candidate-api-migration.md
index a5b081a61..1adc6a568 100644
--- a/docs/develop_docs/target-candidate-api-migration.md
+++ b/docs/develop_docs/target-candidate-api-migration.md
@@ -13,7 +13,7 @@ are unchanged. #453 separately defines the integration API surface.
 | `MaterializeSummaryMaintenanceLifecycleError` | `SummaryMaintenanceLifecycleAssemblyError` | Failure assembling a DAG or deriving maintenance decisions |
 | Error variant `Materialize` | `AssembleDAG` | Wrap an underlying `RealizationError` from DAG assembly |
 | Internal `materialize_inner` / `materialize_residual` | `assemble_target` / `assemble_residual` | Assemble selected nodes, not runtime materialized views |
-| Internal assembly cache `materialized` | `assembled_nodes` | Preserve shared `Rc<SummaryNode>` identity |
+| Internal assembly cache `materialized` | `assembled_nodes` | Preserve shared node identity (now `Rc<OperatorNode>`, see below) |
 
 Update imports and calls together; old public names are not retained as aliases.
 Downstream Rust integrations using these symbols must migrate. No serialized
@@ -26,3 +26,26 @@ counterpart) are prerequisites, not additional changes here.
 The workflow remains one selection call per workload followed by one assembly
 call per query root. `SummaryMaintenanceLifecyclePlan` contains the assembled
 Post-ASAP DAG root plus maintenance decisions; it is not an executable plan.
+
+## Later: unified operator IR (operator flattening)
+
+The pre-ASAP and post-ASAP trees became one IR in `asap_types::ir`. Every
+node is an `Rc<OperatorNode>` whose `operator` is `Operator::NonASAP(NonASAPOp)`
+or `Operator::ASAP(ASAPOp)`. Old public names are not kept as aliases.
+
+| Old | New |
+|---|---|
+| `Rc<QueryExpr>` (pre-ASAP) | `Rc<OperatorNode>` holding `Operator::NonASAP(NonASAPOp)` |
+| `Rc<SummaryNode>` / `SummaryExpr` (post-ASAP) | The same `Rc<OperatorNode>`; summary steps are `Operator::ASAP(ASAPOp)` |
+| `SummaryExpr::KeepPreAsap(q)` | The non-ASAP sub-DAG itself; `retain_exact` only adds an exact `guarantee` |
+| `SummaryExpr::ValueOperation { .. }` over a evaluation | An ordinary `NonASAPOp` (`Project`, `Filter`, `Sort`, `Limit`, `Aggregate`) reading an ASAP node; `FinalizeExactAccumulator`, `MaintainPopulation`, `EvaluatePopulation` are `ASAPOp` variants |
+| `Replacement::Summary(..)` / `Replacement::Rewrite(..)` | `Replacement::SubDAG(Rc<OperatorNode>)`; `is_logical_rewrite` tells them apart |
+| `SummaryFamilyType` | `FieldDataType` (its non-`Plain` variants) |
+| Timing stored on post-ASAP nodes | `OperatorNode::timing`, `None` until `ir::timing::apply_lifecycle_timings` writes it from a `LifecycleAssignment` |
+| `UnresolvedQueryExpr` + `asap_types::pre_asap::resolve_root` | `UnresolvedOp` / `UnresolvedScalar` + `asap_frontend_common::resolve_root` |
+| `pre_asap::canonicalize`, `pre_asap::cse::share_common_sub_dags` | `ir::canonicalize::canonicalize`, `ir::cse::share_common_sub_dags` |
+| `asap_types::post_asap::compile_post_asap_dag` (wire version 5, `Fallback`/`Binary`/`Value` payloads) | `asap_types::ir::export::compile_post_asap_dag` (wire version 7: one node per operator, `Relational` payloads, `ScalarRef` edges); input must be timed |
+| Exported schema JSON `columns` | `fields` |
+
+Field and schema details: [Pre-ASAP IR](pre-asap-ir.md) and
+[Post-ASAP IR](../design_docs/concepts/post-asap-ir.md).
diff --git a/docs/user_guide_docs/run-a-query.md b/docs/user_guide_docs/run-a-query.md
index 3f5825c29..2f7325cc3 100644
--- a/docs/user_guide_docs/run-a-query.md
+++ b/docs/user_guide_docs/run-a-query.md
@@ -109,8 +109,10 @@ whether to select them using its own evidence. Planner's automatic
 `global_selection` skips them; their presence alone does not show that they
 meet the requested target.
 
-Each input line is followed by its debug IR or an `ERR:` message. Post-ASAP
-output may contain summary state, readouts or exact `KeepPreAsap` work. An
+Each input line is followed by its debug IR or an `ERR:` message. Pre-ASAP and
+Post-ASAP output use the same node format: Post-ASAP output adds summary nodes
+(state, readouts) and keeps the original exact operators wherever no summary
+replaces them. An
 approximate target permits approximation; it does not guarantee a legal or
 certified sketch. The tool prints plans, not query results.
 

From 823872396cca2ef105ef3a295b11bf86f3dcc106 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 20:46:11 +0000
Subject: [PATCH 41/48] chore(tools): align the DAG viewer with the unified
 operator kinds

Re-applies the viewer half of the earlier legacy cleanup (#543): the
viewer categorizes exactly the NonASAPOp/ASAPOp kind names, its fixtures
use the unified export, and devtools/tests/viewer_contract.rs pins the
viewer's category table to every operator variant.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/devtools/tests/viewer_contract.rs | 128 +++++++++++++++++++++++
 tools/dag-viewer/README.md               |  14 ++-
 tools/dag-viewer/dag.example.json        | 111 +-------------------
 tools/dag-viewer/generate-sample.sh      |   2 +-
 tools/dag-viewer/node-style.js           |  25 ++---
 tools/dag-viewer/post_asap_fixture.json  |   8 +-
 tools/dag-viewer/viewer.js               |  25 +----
 7 files changed, 160 insertions(+), 153 deletions(-)
 create mode 100644 crates/devtools/tests/viewer_contract.rs

diff --git a/crates/devtools/tests/viewer_contract.rs b/crates/devtools/tests/viewer_contract.rs
new file mode 100644
index 000000000..b34b472fe
--- /dev/null
+++ b/crates/devtools/tests/viewer_contract.rs
@@ -0,0 +1,128 @@
+//! `tools/dag-viewer` ↔ `asap_types::dag_export` contract: the viewer's
+//! `KIND_CATEGORY_JSON` must categorize exactly the `kind` strings
+//! [`asap_types::dag_export::export`] can emit — `Operator::kind_name()` of
+//! every `NonASAPOp` and `ASAPOp` variant — no more (a stale kind the IR no
+//! longer has) and no less (an exported kind the viewer would render
+//! uncategorized).
+
+use std::collections::{BTreeMap, BTreeSet};
+
+use asap_types::ir::{ASAPOp, NonASAPOp};
+
+/// Every `NonASAPOp::kind_name()`.
+const NON_ASAP_KINDS: &[&str] = &[
+    "Scan",
+    "Values",
+    "Filter",
+    "Project",
+    "Aggregate",
+    "Join",
+    "SetOp",
+    "Concat",
+    "Dedup",
+    "Sort",
+    "Limit",
+    "BinaryOp",
+    "SQLWindowFunc",
+    "TimeRange",
+    "TimeShift",
+    "PromqlVectorFromScalar",
+    "PromqlRelabel",
+    "PromqlInfoEnrich",
+    "PromqlSeriesSample",
+    "PromqlSubquery",
+];
+
+/// Every `ASAPOp::kind_name()`.
+const ASAP_KINDS: &[&str] = &[
+    "SummaryAgg",
+    "SummaryEstimate",
+    "FinalizeExactAccumulator",
+    "MaintainPopulation",
+    "EvaluatePopulation",
+    "SummaryMerge",
+    "SummarySubtract",
+    "SummaryDelete",
+    "SummaryJoin",
+    "Extension",
+];
+
+/// Compile-time tripwire: adding an operator variant fails these exhaustive
+/// matches until the matching `*_KINDS` list above is extended too. Never
+/// called; the match arms are the point.
+#[allow(dead_code)]
+fn kind_lists_track_every_variant(non_asap: &NonASAPOp, asap: &ASAPOp) {
+    let listed = |name: &str, list: &[&str]| assert!(list.contains(&name));
+    listed(
+        match non_asap {
+            NonASAPOp::Scan { .. } => "Scan",
+            NonASAPOp::Values { .. } => "Values",
+            NonASAPOp::Filter { .. } => "Filter",
+            NonASAPOp::Project { .. } => "Project",
+            NonASAPOp::Aggregate { .. } => "Aggregate",
+            NonASAPOp::Join { .. } => "Join",
+            NonASAPOp::SetOp { .. } => "SetOp",
+            NonASAPOp::Concat { .. } => "Concat",
+            NonASAPOp::Dedup { .. } => "Dedup",
+            NonASAPOp::Sort { .. } => "Sort",
+            NonASAPOp::Limit { .. } => "Limit",
+            NonASAPOp::BinaryOp { .. } => "BinaryOp",
+            NonASAPOp::SQLWindowFunc { .. } => "SQLWindowFunc",
+            NonASAPOp::TimeRange { .. } => "TimeRange",
+            NonASAPOp::TimeShift { .. } => "TimeShift",
+            NonASAPOp::PromqlVectorFromScalar(_) => "PromqlVectorFromScalar",
+            NonASAPOp::PromqlRelabel { .. } => "PromqlRelabel",
+            NonASAPOp::PromqlInfoEnrich { .. } => "PromqlInfoEnrich",
+            NonASAPOp::PromqlSeriesSample { .. } => "PromqlSeriesSample",
+            NonASAPOp::PromqlSubquery { .. } => "PromqlSubquery",
+        },
+        NON_ASAP_KINDS,
+    );
+    listed(
+        match asap {
+            ASAPOp::SummaryAgg { .. } => "SummaryAgg",
+            ASAPOp::SummaryEstimate { .. } => "SummaryEstimate",
+            ASAPOp::FinalizeExactAccumulator { .. } => "FinalizeExactAccumulator",
+            ASAPOp::MaintainPopulation { .. } => "MaintainPopulation",
+            ASAPOp::EvaluatePopulation { .. } => "EvaluatePopulation",
+            ASAPOp::SummaryMerge { .. } => "SummaryMerge",
+            ASAPOp::SummarySubtract { .. } => "SummarySubtract",
+            ASAPOp::SummaryDelete { .. } => "SummaryDelete",
+            ASAPOp::SummaryJoin { .. } => "SummaryJoin",
+            ASAPOp::Extension { .. } => "Extension",
+        },
+        ASAP_KINDS,
+    );
+}
+
+/// The viewer's `kind -> category` table, parsed out of the JS source the
+/// same way the viewer itself does (`JSON.parse(KIND_CATEGORY_JSON)`).
+fn viewer_kind_categories() -> BTreeMap<String, String> {
+    const START: &str = "const KIND_CATEGORY_JSON = `";
+    let source = include_str!(concat!(
+        env!("CARGO_MANIFEST_DIR"),
+        "/../../tools/dag-viewer/node-style.js"
+    ));
+    let json = source
+        .split_once(START)
+        .expect("node-style.js must declare KIND_CATEGORY_JSON")
+        .1
+        .split_once("`;")
+        .expect("KIND_CATEGORY_JSON must be a template literal")
+        .0;
+    serde_json::from_str(json).expect("KIND_CATEGORY_JSON must be valid JSON")
+}
+
+#[test]
+fn viewer_categorizes_exactly_the_exported_node_kinds() {
+    let expected: BTreeSet<&str> = NON_ASAP_KINDS.iter().chain(ASAP_KINDS).copied().collect();
+    assert_eq!(
+        expected.len(),
+        NON_ASAP_KINDS.len() + ASAP_KINDS.len(),
+        "exported kind names must be unique"
+    );
+    let categories = viewer_kind_categories();
+    let actual: BTreeSet<&str> = categories.keys().map(String::as_str).collect();
+
+    assert_eq!(actual, expected);
+}
diff --git a/tools/dag-viewer/README.md b/tools/dag-viewer/README.md
index b90aae272..8c55aef56 100644
--- a/tools/dag-viewer/README.md
+++ b/tools/dag-viewer/README.md
@@ -69,7 +69,8 @@ cargo run -p asap-devtools --bin dag_export -- \
 
 Load the JSON with the page's file picker. `--planner-cost-json` is a complete
 physical-evidence document: an immutable `evidence_version`, calibration, and
-target records containing the exact target `QueryExpr` and comparison scope.
+target records containing the exact target node (a serialized pre-ASAP
+`OperatorNode`) and comparison scope.
 Each exact replacement candidate owns its complete logical-node
 `PhysicalNodeEvidence`; summary candidates additionally own their bound
 `PhysicalDAG`. Candidate-local evidence prevents statistics for one physical
@@ -129,7 +130,7 @@ a selected replacement directly contains:
 {
   "decision": {
     "id": 7,
-    "strategy": "SketchAlgorithmStrategy",
+    "strategy": "ASAPStrategies",
     "rationale": "count realizes as a Cms sketch",
     "rank": 0,
     "cost": 1.14001088,
@@ -147,8 +148,13 @@ The exporter assigns `workload_node_id`; union rendering reads that mapping
 directly.
 
 Node boxes use concrete IR fields: aggregate measures/grouping, sort keys,
-filter predicates, projections, sources, summary families, and readout
-queries. Category icons are deliberately omitted so they cannot be confused
+filter predicates, projections, sources, summary families, and evaluation
+queries. A node's `kind` is the operator variant name (`Operator::kind_name`):
+a `NonASAPOp` such as `Aggregate` or `Values`, or an `ASAPOp` such as
+`SummaryAgg` or `EvaluatePopulation`. `node-style.js` maps each kind to a color
+category. Scalar expressions are not nodes; an operator a scalar expression
+reads (`scalar(v)`, `EXISTS (subquery)`) is a child node, shown in `detail`
+as `{"scalar_ref": <node id>}`. Schemas list their entries under `fields`. Category icons are deliberately omitted so they cannot be confused
 with IR text.
 
 ### Cost/benefit annotations (issue #286)
diff --git a/tools/dag-viewer/dag.example.json b/tools/dag-viewer/dag.example.json
index 85c0e97b6..5249bb412 100644
--- a/tools/dag-viewer/dag.example.json
+++ b/tools/dag-viewer/dag.example.json
@@ -210,7 +210,7 @@
         {
           "decision_id": 0,
           "target_pre_id": 1,
-          "strategy": "SketchAlgorithmStrategy",
+          "strategy": "ASAPStrategies",
           "rationale": "count realizes as a Cms sketch",
           "rank": 0,
           "cost": 1.14001088,
@@ -363,108 +363,7 @@
             "kind": "Summary",
             "dag": {
               "nodes": [
-                {
-                  "id": 0,
-                  "kind": "KeepPreAsap",
-                  "label": "KeepPreAsap(Scan)",
-                  "detail": {
-                    "pre_asap_sub_dag": {
-                      "nodes": [
-                        {
-                          "children": [],
-                          "detail": {
-                            "predicates": [],
-                            "schema": {
-                              "closed": true,
-                              "columns": [
-                                {
-                                  "dtype": "timestamp",
-                                  "name": "ts",
-                                  "nullable": false,
-                                  "table": "metrics"
-                                },
-                                {
-                                  "dtype": "utf8",
-                                  "name": "service",
-                                  "nullable": false,
-                                  "table": "metrics"
-                                },
-                                {
-                                  "dtype": "utf8",
-                                  "name": "region",
-                                  "nullable": false,
-                                  "table": "metrics"
-                                },
-                                {
-                                  "dtype": "float64",
-                                  "name": "latency",
-                                  "nullable": false,
-                                  "table": "metrics"
-                                },
-                                {
-                                  "dtype": "int64",
-                                  "name": "bytes",
-                                  "nullable": false,
-                                  "table": "metrics"
-                                }
-                              ],
-                              "time_index": 0,
-                              "unique_keys": []
-                            },
-                            "source": {
-                              "Table": {
-                                "table_ref": "metrics"
-                              }
-                            }
-                          },
-                          "hash": 2606922452740434172,
-                          "id": 0,
-                          "kind": "Scan",
-                          "label": "Scan(metrics)",
-                          "schema": {
-                            "closed": true,
-                            "columns": [
-                              {
-                                "dtype": "timestamp",
-                                "name": "ts",
-                                "nullable": false,
-                                "table": "metrics"
-                              },
-                              {
-                                "dtype": "utf8",
-                                "name": "service",
-                                "nullable": false,
-                                "table": "metrics"
-                              },
-                              {
-                                "dtype": "utf8",
-                                "name": "region",
-                                "nullable": false,
-                                "table": "metrics"
-                              },
-                              {
-                                "dtype": "float64",
-                                "name": "latency",
-                                "nullable": false,
-                                "table": "metrics"
-                              },
-                              {
-                                "dtype": "int64",
-                                "name": "bytes",
-                                "nullable": false,
-                                "table": "metrics"
-                              }
-                            ],
-                            "time_index": 0,
-                            "unique_keys": []
-                          }
-                        }
-                      ],
-                      "root": 0
-                    }
-                  },
-                  "children": []
-                },
+                {"id": 0, "kind": "Scan", "label": "Scan(metrics)", "detail": {"predicates": [], "schema": {"closed": true, "columns": [{"dtype": "timestamp", "name": "ts", "nullable": false, "table": "metrics"}, {"dtype": "utf8", "name": "service", "nullable": false, "table": "metrics"}, {"dtype": "utf8", "name": "region", "nullable": false, "table": "metrics"}, {"dtype": "float64", "name": "latency", "nullable": false, "table": "metrics"}, {"dtype": "int64", "name": "bytes", "nullable": false, "table": "metrics"}], "time_index": 0, "unique_keys": []}, "source": {"Table": {"table_ref": "metrics"}}}, "children": []},
                 {
                   "id": 1,
                   "kind": "SummaryAgg",
@@ -657,7 +556,7 @@
             "hash": 2606922452740434172,
             "decision": {
               "id": 0,
-              "strategy": "SketchAlgorithmStrategy",
+              "strategy": "ASAPStrategies",
               "rationale": "count realizes as a Cms sketch",
               "rank": 0,
               "cost": 1.14001088,
@@ -763,7 +662,7 @@
             "workload_node_id": 1,
             "decision": {
               "id": 0,
-              "strategy": "SketchAlgorithmStrategy",
+              "strategy": "ASAPStrategies",
               "rationale": "count realizes as a Cms sketch",
               "rank": 0,
               "cost": 1.14001088,
@@ -862,7 +761,7 @@
             "workload_node_id": 2,
             "decision": {
               "id": 0,
-              "strategy": "SketchAlgorithmStrategy",
+              "strategy": "ASAPStrategies",
               "rationale": "count realizes as a Cms sketch",
               "rank": 0,
               "cost": 1.14001088,
diff --git a/tools/dag-viewer/generate-sample.sh b/tools/dag-viewer/generate-sample.sh
index e916cba5f..66921d8c7 100755
--- a/tools/dag-viewer/generate-sample.sh
+++ b/tools/dag-viewer/generate-sample.sh
@@ -6,7 +6,7 @@ set -euo pipefail
 cd "$(dirname "${BASH_SOURCE[0]}")/../.."
 
 # --epsilon asks for an approximate accuracy target instead of the default
-# Exact, so SketchAlgorithmStrategy actually has a sketch alternative to
+# Exact, so ASAPStrategies actually has a sketch alternative to
 # report — without it, no query below would ever pick up a `notes` badge
 # (see crates/devtools/src/bin/dag_export.rs's own `--epsilon` doc comment).
 cargo run -p asap-devtools --bin dag_export -- \
diff --git a/tools/dag-viewer/node-style.js b/tools/dag-viewer/node-style.js
index a957817c2..fee49586e 100644
--- a/tools/dag-viewer/node-style.js
+++ b/tools/dag-viewer/node-style.js
@@ -1,20 +1,17 @@
-// Logical QueryExpr/SummaryExpr kinds exported by
+// Operator kinds (`Operator::kind_name`) exported by
 // crates/types/src/dag_export.rs. Categories describe the visible logical DAG
 // shape. They do not model hidden physical inputs: for example,
 // PromqlInfoEnrich is a one-child enrichment here even if physical costing
 // later accounts for an auxiliary source scan.
 const KIND_CATEGORY_JSON = `{
   "Scan": "data",
-  "PromqlScalarBridge": "data",
-  "EvalTimestamp": "data",
-  "CurrentTimestamp": "data",
+  "Values": "data",
   "Filter": "filter",
   "PromqlSeriesSample": "sample",
   "Project": "derive",
   "PromqlRelabel": "derive",
   "PromqlInfoEnrich": "derive",
   "PromqlVectorFromScalar": "derive",
-  "PromqlScalarFromVector": "derive",
   "BinaryOp": "derive",
   "Aggregate": "aggregate",
   "TimeRange": "window",
@@ -22,21 +19,21 @@ const KIND_CATEGORY_JSON = `{
   "TimeShift": "window",
   "SQLWindowFunc": "window",
   "Join": "join",
-  "RelationalJoin": "join",
   "Dedup": "set",
   "SetOp": "set",
   "Concat": "combine",
   "Sort": "sort",
   "Limit": "sort",
-  "KeepPreAsap": "summary",
   "SummaryAgg": "summary",
   "SummaryJoin": "summary",
   "SummarySubtract": "summary",
-  "SummaryBinaryOp": "summary",
-  "ValueOperation": "summary",
   "SummaryDelete": "summary",
   "SummaryEstimate": "summary",
-  "SummaryMerge": "summary"
+  "SummaryMerge": "summary",
+  "FinalizeExactAccumulator": "summary",
+  "MaintainPopulation": "summary",
+  "EvaluatePopulation": "summary",
+  "Extension": "summary"
 }`;
 const KIND_CATEGORY = Object.freeze(JSON.parse(KIND_CATEGORY_JSON));
 
@@ -44,7 +41,7 @@ const KIND_CATEGORY = Object.freeze(JSON.parse(KIND_CATEGORY_JSON));
 const CATEGORIES = {
   data: {
     label: 'Data',
-    description: 'Scan, PromqlScalarBridge, EvalTimestamp, CurrentTimestamp — leaves that introduce a value',
+    description: 'Scan and Values — data sources',
     light: { bg: '#eef5fd', border: '#0369a1' },
     dark: { bg: '#0c2438', border: '#38bdf8' },
   },
@@ -62,7 +59,7 @@ const CATEGORIES = {
   },
   derive: {
     label: 'Derive',
-    description: 'Project, PromqlRelabel, PromqlInfoEnrich, PromqlVectorFromScalar, PromqlScalarFromVector, BinaryOp — transforms or enriches columns on otherwise-unchanged rows',
+    description: 'Project, PromqlRelabel, PromqlInfoEnrich, PromqlVectorFromScalar, BinaryOp — transforms or enriches columns on otherwise-unchanged rows',
     light: { bg: '#f5f0fd', border: '#6d28d9' },
     dark: { bg: '#241a3d', border: '#a78bfa' },
   },
@@ -102,10 +99,10 @@ const CATEGORIES = {
     light: { bg: '#eef4fd', border: '#1d4ed8' },
     dark: { bg: '#12233d', border: '#60a5fa' },
   },
-  // Post-ASAP nodes use a neutral palette; KeepPreAsap has a muted override.
+  // ASAP operators use a neutral palette.
   summary: {
     label: 'Summary',
-    description: 'KeepPreAsap, SummaryBinaryOp, ValueOperation, SummaryAgg, SummaryJoin, SummarySubtract, SummaryDelete, SummaryEstimate, SummaryMerge — post-ASAP materialized structures',
+    description: 'SummaryAgg, SummaryEstimate, FinalizeExactAccumulator, MaintainPopulation, EvaluatePopulation, SummaryJoin, SummarySubtract, SummaryDelete, SummaryMerge, Extension — summary state and its evaluations',
     light: { bg: '#f1f2f4', border: '#4b5563' },
     dark: { bg: '#20242b', border: '#9ca3af' },
   },
diff --git a/tools/dag-viewer/post_asap_fixture.json b/tools/dag-viewer/post_asap_fixture.json
index ea2de185f..e616e80e2 100644
--- a/tools/dag-viewer/post_asap_fixture.json
+++ b/tools/dag-viewer/post_asap_fixture.json
@@ -14,9 +14,9 @@
       },
       "post_dag": {
         "nodes": [
-          { "id": 0, "kind": "KeepPreAsap", "label": "KeepPreAsap(Scan)", "detail": {"pre_asap_sub_dag": {"nodes": [{"id": 0, "kind": "Scan", "label": "Scan(netflow_table)", "detail": {}, "children": []}], "root": 0}}, "children": [] },
+          {"id": 0, "kind": "Scan", "label": "Scan(netflow_table)", "detail": {}, "children": []},
           { "id": 1, "kind": "SummaryAgg", "label": "SummaryAgg(Kll)", "detail": {"family": {"Sketch": ["Kll", {"k": 200}]}, "col": {"Column": 6}, "reduction": {"Reduce": [1]}, "grouping": "PerSubpopulationInstance"}, "children": [0], "origin_pre_id": 1 },
-          { "id": 2, "kind": "KeepPreAsap", "label": "KeepPreAsap(Project)", "detail": {"pre_asap_sub_dag": {"nodes": [{"id": 0, "kind": "Project", "label": "Project(2 cols)", "detail": {}, "children": []}], "root": 0}}, "children": [1] }
+          {"id": 2, "kind": "Project", "label": "Project(2 cols)", "detail": {}, "children": [1]}
         ],
         "root": 2
       },
@@ -39,7 +39,7 @@
             "kind": "Summary",
             "dag": {
               "nodes": [
-                { "id": 0, "kind": "KeepPreAsap", "label": "KeepPreAsap(Scan)", "detail": {"pre_asap_sub_dag": {"nodes": [{"id": 0, "kind": "Scan", "label": "Scan(netflow_table)", "detail": {}, "children": [], "hash": 111}], "root": 0}}, "children": [] },
+                {"id": 0, "kind": "Scan", "label": "Scan(netflow_table)", "detail": {}, "children": []},
                 { "id": 1, "kind": "SummaryAgg", "label": "SummaryAgg(Kll)", "detail": {"family": {"Sketch": ["Kll", {"k": 200}]}, "col": {"Column": 6}, "reduction": {"Reduce": [1]}, "grouping": "PerSubpopulationInstance"}, "children": [0], "origin_pre_id": 1 }
               ],
               "root": 1
@@ -64,7 +64,7 @@
             "kind": "Summary",
             "dag": {
               "nodes": [
-                { "id": 0, "kind": "KeepPreAsap", "label": "KeepPreAsap(Scan)", "detail": {}, "children": [] },
+                {"id": 0, "kind": "Scan", "label": "Scan", "detail": {}, "children": []},
                 { "id": 1, "kind": "SummaryAgg", "label": "SummaryAgg(HydraKll)", "detail": {"family": {"Sketch": ["Kll", {"k": 200}]}, "grouping": {"SharedMultiSubpopulation": {"params": {}}}}, "children": [0], "origin_pre_id": 1 }
               ],
               "root": 1
diff --git a/tools/dag-viewer/viewer.js b/tools/dag-viewer/viewer.js
index 6e4c696ee..6e4dc0c07 100644
--- a/tools/dag-viewer/viewer.js
+++ b/tools/dag-viewer/viewer.js
@@ -290,22 +290,6 @@ function buildCyStyle() {
       selector: 'node[category = "unknown"]',
       style: { 'border-style': 'dashed', 'border-width': 3 },
     },
-    {
-      // KeepPreAsap (post-ASAP lane only) is post-ASAP-only
-      // as a *kind*, but represents literally unchanged pre-ASAP content —
-      // override the 'summary' category's color/icon with the same neutral
-      // panel/muted/dashed treatment the rest of the chrome uses for "nothing
-      // to see here", so a glance at the After lane separates "the planner
-      // did something" (solid, colored) from "left alone" (dashed, muted).
-      // See node-style.js's CATEGORIES.summary comment for the category-level
-      // color choice this overrides.
-      selector: 'node[kind = "KeepPreAsap"]',
-      style: {
-        'background-color': panelColor,
-        'border-color': borderColor,
-        'border-style': 'dashed',
-      },
-    },
     {
       selector: 'node.root',
       style: { 'border-width': 2.5 },
@@ -663,10 +647,7 @@ function laneElements(laneId, laneLabel, dag, query, stage, laneCost) {
         // exactly the plain IR label.
         label: node.label + nodeCostBadgeSuffix(node),
         node,
-        // Flat (not nested under `node`) so buildCyStyle's
-        // `node[kind = "KeepPreAsap"]` selector can actually match it —
-        // cytoscape selectors can't reach into a data field that's itself an
-        // object.
+        // Cytoscape selectors read flat data fields.
         kind: node.kind,
         category: categoryOf(node.kind),
         root: node.id === dag.root,
@@ -1172,10 +1153,6 @@ function renderLegend() {
     <span><span class="swatchLabel">Shared workload node</span><span class="swatchDesc">Explicitly identified by the exporter as shared across selected queries</span></span></div>`);
   rows.push(`<div class="leg"><span class="swatch ring" style="border-color:${rootColor}"></span>
     <span><span class="swatchLabel">Query root</span><span class="swatchDesc">${escapeHtml(ROOT_BADGE.description)}</span></span></div>`);
-  const panelBg = getComputedStyle(document.documentElement).getPropertyValue('--panel2').trim() || '#f0f2f5';
-  const mutedColor = getComputedStyle(document.documentElement).getPropertyValue('--muted').trim() || '#6b7280';
-  rows.push(`<div class="leg"><span class="swatch" style="background:${panelBg}; border-color:${mutedColor}; border-style:dashed"></span>
-    <span><span class="swatchLabel">Pass-through (KeepPreAsap)</span><span class="swatchDesc">Unchanged pre-ASAP sub-DAG carried into the Summary DAG as-is</span></span></div>`);
   legendList.innerHTML = rows.join('');
 }
 

From b00817e8cb6e6add9ba3fea09aec82196b402393 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 21:08:06 +0000
Subject: [PATCH 42/48] refactor(planner): remove the summary maintenance
 lifecycle

Stage 2 materialization (#509) will decide per sub-DAG whether and when to
materialize, so the Planner no longer chooses a maintenance lifecycle.

- MajorPass now runs search_workload_with_targets -> global_selection ->
  assemble_selected_dag per root -> share_common_sub_dags.
- QueryLifecyclePlan becomes QueryPlan { entry_index, root }; PlanOutput's
  execution_timed_dag times the roots directly. LifecycleInput, the
  lifecycle errors and UserInput's `lifecycle` field are gone (public API
  break).
- Delete summary_maintenance_lifecycle, summary_maintenance_cost,
  summary_maintenance_dag_export, post_asap::{summary_maintenance,
  summary_maintenance_lifecycle} and SummaryWindowFramework (the pane
  primitives stay), the lifecycle CostModel hooks, CandidateCostOverrides
  and EmpiricalEvidenceProvider::lifecycle_cost_inputs.
- Delete the lifecycle e2e test and the viewer's lifecycle-plan UI; rewire
  e2e_plan, summary_sharing, operator_design_examples and
  weighted_topk_binding to the new pipeline.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 .../asap-aware-mapping/src/analytical_cost.rs |    4 +-
 crates/asap-aware-mapping/src/cost_model.rs   |  145 +-
 .../asap-aware-mapping/src/empirical_cost.rs  |   92 +-
 crates/asap-aware-mapping/src/lib.rs          |   38 +-
 crates/asap-aware-mapping/src/pass/major.rs   |  132 +-
 crates/asap-aware-mapping/src/pass/mod.rs     |  102 +-
 crates/asap-aware-mapping/src/replacement.rs  |  139 +-
 .../src/summary_maintenance_cost/estimator.rs | 1219 -----
 .../src/summary_maintenance_cost/evidence.rs  |  386 --
 .../src/summary_maintenance_cost/mod.rs       |   51 -
 .../src/summary_maintenance_cost/model.rs     | 3664 ---------------
 .../src/summary_maintenance_cost/window.rs    |  252 --
 .../src/summary_maintenance_dag_export.rs     |  132 -
 .../src/summary_maintenance_lifecycle.rs      | 3909 -----------------
 .../tests/weighted_topk_binding.rs            |  126 +-
 .../tests/operator_design_examples.rs         |   37 +-
 .../summary_maintenance_lifecycle_e2e.rs      | 1155 -----
 crates/planner/src/lib.rs                     |   33 +-
 crates/planner/tests/e2e_plan.rs              |  131 +-
 crates/planner/tests/summary_sharing.rs       |  260 +-
 crates/types/src/post_asap/mod.rs             |   12 +-
 .../src/post_asap/summary_maintenance.rs      |   38 -
 .../summary_maintenance_lifecycle.rs          |   74 -
 crates/types/src/post_asap/summary_window.rs  |   50 +-
 .../workload-demand-and-summary-lifecycle.md  |  758 ----
 tools/dag-viewer/README.md                    |    9 -
 .../lifecycle-summary-maintenance.png         |  Bin 174559 -> 0 bytes
 tools/dag-viewer/render.py                    |   17 -
 tools/dag-viewer/test_render.py               |   37 -
 tools/dag-viewer/viewer.js                    |   77 +-
 30 files changed, 225 insertions(+), 12854 deletions(-)
 delete mode 100644 crates/asap-aware-mapping/src/summary_maintenance_cost/estimator.rs
 delete mode 100644 crates/asap-aware-mapping/src/summary_maintenance_cost/evidence.rs
 delete mode 100644 crates/asap-aware-mapping/src/summary_maintenance_cost/mod.rs
 delete mode 100644 crates/asap-aware-mapping/src/summary_maintenance_cost/model.rs
 delete mode 100644 crates/asap-aware-mapping/src/summary_maintenance_cost/window.rs
 delete mode 100644 crates/asap-aware-mapping/src/summary_maintenance_dag_export.rs
 delete mode 100644 crates/asap-aware-mapping/src/summary_maintenance_lifecycle.rs
 delete mode 100644 crates/integration-tests/tests/summary_maintenance_lifecycle_e2e.rs
 delete mode 100644 crates/types/src/post_asap/summary_maintenance.rs
 delete mode 100644 crates/types/src/post_asap/summary_maintenance_lifecycle.rs
 delete mode 100644 docs/design_docs/proposals/asap-aware-mapping/workload-demand-and-summary-lifecycle.md
 delete mode 100644 tools/dag-viewer/lifecycle-summary-maintenance.png

diff --git a/crates/asap-aware-mapping/src/analytical_cost.rs b/crates/asap-aware-mapping/src/analytical_cost.rs
index 8256d6f10..7ba28d0ed 100644
--- a/crates/asap-aware-mapping/src/analytical_cost.rs
+++ b/crates/asap-aware-mapping/src/analytical_cost.rs
@@ -2164,8 +2164,6 @@ pub enum AnalyticalCostError {
     UnsupportedDataArrival(DataArrival),
     #[error("ingestion rate must be finite and non-negative, got {0}")]
     InvalidIngestionRate(f64),
-    #[error("summary lifecycle, maintenance mode, and evaluation schedule are inconsistent")]
-    IncompatibleLifecycleGuarantee,
     #[error("bootstrap row and byte evidence must either both be zero or both be non-zero")]
     InconsistentBootstrapEvidence,
     #[error("required summary operation cost {0} must be finite and positive, got {1}")]
@@ -2196,7 +2194,7 @@ pub enum AnalyticalCostError {
     UnsupportedQueryOperator,
     #[error("inconsistent operator statistics: {0}")]
     InconsistentOperatorStatistics(&'static str),
-    #[error("summary operation {0} has no lifecycle-aware cost formula")]
+    #[error("summary operation {0} has no cost formula")]
     UnsupportedSummaryOperation(&'static str),
     #[error("required comparison-scope field {0} is missing")]
     MissingComparisonScope(&'static str),
diff --git a/crates/asap-aware-mapping/src/cost_model.rs b/crates/asap-aware-mapping/src/cost_model.rs
index 9fc170666..9589d1382 100644
--- a/crates/asap-aware-mapping/src/cost_model.rs
+++ b/crates/asap-aware-mapping/src/cost_model.rs
@@ -51,12 +51,10 @@ use std::rc::Rc;
 use crate::exact_composition::ExactOperation;
 use asap_types::ir::{ASAPOp, Operator, OperatorNode};
 use asap_types::post_asap::{
-    FieldDataType, GroupingStrategy, HydraParams, ResultGuarantee, SketchAlgorithm, SketchParams,
-    SketchStatistic, SummaryMaintenanceLifecycleGuarantee, SummaryWindowFramework,
+    FieldDataType, GroupingStrategy, HydraParams, SketchAlgorithm, SketchParams, SketchStatistic,
 };
 use asap_types::pre_asap::agg_intent::AggIntent;
 use asap_types::pre_asap::expr_ir::ColumnRef;
-use asap_types::types::AccuracyTarget;
 
 use crate::exact_composition::{ExactComposition, OperationPlacement};
 use crate::recurrence::{
@@ -66,9 +64,6 @@ use crate::recurrence::{
 use crate::replacement::{
     realize_child, Realization, Replacement, ReplacementProvenance, ReplacementSubDAG, TargetSubDAG,
 };
-use crate::summary_maintenance_lifecycle::{
-    SummaryMaintenanceCapabilities, SummaryMaintenanceLifecycleCostInputs,
-};
 
 // ── Recurring-cost vocabulary for mixed exact/summary plans (issue #171) ──
 
@@ -298,38 +293,6 @@ pub struct CseCandidate<'a> {
 #[derive(Debug, Clone, Copy, PartialEq, PartialOrd)]
 pub struct Cost(pub f64);
 
-/// One physical summary state and the lifecycle selected for that exact DAG
-/// node. Node identity is preserved so whole-DAG models can bind per-state
-/// evidence without relying on traversal order.
-pub struct CostedSummaryDeployment<'a> {
-    pub summary: &'a OperatorNode,
-    pub guarantee: &'a SummaryMaintenanceLifecycleGuarantee,
-    pub selected_cost: Cost,
-}
-
-/// Complete candidate estimate returned to lifecycle and global plan search.
-///
-/// A deployment-aware model may compare abstract summary-window primitives
-/// using evidence supplied by downstream implementations. `window_frameworks`
-/// is planner IR: it records the selected semantic realization contract.
-/// `physical_plan_id` is separate provider-owned provenance for the concrete
-/// implementation whose evidence won; it is not interpreted as planner IR.
-#[derive(Debug, Clone, PartialEq)]
-pub struct CompleteSummaryCandidateEstimate {
-    pub cost: Cost,
-    /// Stable provider identity of the complete implementation whose evidence
-    /// produced this estimate.
-    pub physical_plan_id: Option<String>,
-    /// Window choice for each entry of the `deployments` slice passed to the
-    /// complete-cost hook. `None` explicitly means that deployment does not
-    /// use a summary-window framework.
-    pub window_frameworks: Vec<Option<SummaryWindowFramework>>,
-    /// End-to-end guarantee supplied by the selected window realization.
-    /// `None` means that the complete model supplied no window-specific
-    /// guarantee; `Some` may be exact or approximate.
-    pub window_accuracy_guarantee: Option<ResultGuarantee>,
-}
-
 impl Cost {
     /// The cost of an operation that costs nothing at all.
     pub const ZERO: Cost = Cost(0.0);
@@ -770,112 +733,6 @@ pub trait CostModel {
         f64::NAN
     }
 
-    /// Primitive build, update, read, retention, and retirement costs used to
-    /// compare physical summary-state lifecycles. Unknown values stay
-    /// unknown, preventing long-lived deployments from winning through
-    /// optimistic zeroes.
-    fn summary_maintenance_lifecycle_cost_inputs(
-        &self,
-        _summary: &OperatorNode,
-    ) -> SummaryMaintenanceLifecycleCostInputs {
-        SummaryMaintenanceLifecycleCostInputs::default()
-    }
-
-    /// Horizon-aware form used by lifecycle planning. Models whose retention
-    /// objective is capacity rather than byte-seconds can normalize their
-    /// rate so the horizon integral equals one peak-capacity charge.
-    fn summary_maintenance_lifecycle_cost_inputs_for_horizon(
-        &self,
-        summary: &OperatorNode,
-        _horizon: Option<Horizon>,
-    ) -> SummaryMaintenanceLifecycleCostInputs {
-        self.summary_maintenance_lifecycle_cost_inputs(summary)
-    }
-
-    /// Physical update/merge/delete support for one concrete summary. The
-    /// conservative default advertises no long-lived maintenance capability.
-    fn summary_maintenance_capabilities(
-        &self,
-        _summary: &OperatorNode,
-    ) -> SummaryMaintenanceCapabilities {
-        SummaryMaintenanceCapabilities::default()
-    }
-
-    /// Replace the sum of selected per-state lifecycle costs with a complete
-    /// root-DAG cost. The default preserves legacy models. Evidence-strict
-    /// models return `None` when any root operation is unavailable; callers
-    /// must not then reuse the partial per-state sum.
-    fn complete_summary_candidate_cost(
-        &self,
-        _root: &OperatorNode,
-        _target: Option<&OperatorNode>,
-        deployments: &[CostedSummaryDeployment<'_>],
-        _horizon: Option<Horizon>,
-        _expected_reads: Option<f64>,
-        _required_accuracy: &[AccuracyTarget],
-    ) -> Option<Cost> {
-        Some(Cost(
-            deployments
-                .iter()
-                .map(|deployment| deployment.selected_cost.0)
-                .sum(),
-        ))
-    }
-
-    /// Complete cost together with selected implementation provenance and
-    /// planner-visible window primitives. The default preserves cost models
-    /// that do not perform either decision.
-    fn complete_summary_candidate_estimate(
-        &self,
-        root: &OperatorNode,
-        target: Option<&OperatorNode>,
-        deployments: &[CostedSummaryDeployment<'_>],
-        horizon: Option<Horizon>,
-        expected_reads: Option<f64>,
-        required_accuracy: &[AccuracyTarget],
-    ) -> Option<CompleteSummaryCandidateEstimate> {
-        self.complete_summary_candidate_cost(
-            root,
-            target,
-            deployments,
-            horizon,
-            expected_reads,
-            required_accuracy,
-        )
-        .map(|cost| CompleteSummaryCandidateEstimate {
-            cost,
-            physical_plan_id: None,
-            window_frameworks: vec![None; deployments.len()],
-            window_accuracy_guarantee: None,
-        })
-    }
-
-    /// Whether the complete-candidate hook is authoritative for lifecycle
-    /// costs. When true, lifecycle alternatives rejected only because their
-    /// legacy per-state cost is missing remain eligible for complete-DAG
-    /// evaluation. Semantic and runtime-capability rejections still apply.
-    fn complete_summary_candidate_estimate_covers_lifecycle_costs(&self) -> bool {
-        false
-    }
-
-    /// Cost of evaluating `target` directly from its logical/raw inputs once.
-    /// When known, lifecycle-aware materialization compares this fallback with
-    /// the aggregate cost of the selected summary deployments.
-    fn raw_query_recompute_cost(&self, _target: &OperatorNode) -> Option<Cost> {
-        None
-    }
-
-    /// Complete raw cost over the comparison context. The default preserves
-    /// per-read models; context-aware models override this when raw input
-    /// cardinality changes between evaluations.
-    fn raw_query_recompute_total_cost(
-        &self,
-        target: &OperatorNode,
-        expected_reads: f64,
-    ) -> Option<Cost> {
-        self.raw_query_recompute_cost(target)
-            .map(|per_read| Cost(per_read.0 * expected_reads))
-    }
     /// Physical feasibility evidence for a complete summary candidate.
     /// `None` defers admission to physical/deployment compilation; `Some(false)`
     /// excludes the candidate without changing its computation or parameters.
diff --git a/crates/asap-aware-mapping/src/empirical_cost.rs b/crates/asap-aware-mapping/src/empirical_cost.rs
index 18d1d7ee4..eb9904f77 100644
--- a/crates/asap-aware-mapping/src/empirical_cost.rs
+++ b/crates/asap-aware-mapping/src/empirical_cost.rs
@@ -2,16 +2,14 @@
 //! configuration and environment; they are neither runtime feedback nor proofs
 //! of an accuracy guarantee. CPU quantities are nanoseconds, never CPU operations.
 
-use asap_types::ir::{ASAPOp, Operator, OperatorNode};
-use asap_types::post_asap::{FieldDataType, GroupingStrategy, SketchAlgorithm, SketchParams};
+use asap_types::post_asap::{SketchAlgorithm, SketchParams};
 use asap_types::pre_asap::AggIntent;
 use serde::{Deserialize, Serialize};
 
-use crate::cost_model::{Cost, CostModel, DefaultCostModel};
+use crate::cost_model::{CostModel, DefaultCostModel};
 use crate::replacement::{
     accuracy_budget, accuracy_target, default_size_params, ReplacementSubDAG, TargetSubDAG,
 };
-use crate::summary_maintenance_lifecycle::SummaryMaintenanceLifecycleCostInputs;
 
 pub const EVIDENCE_SCHEMA_VERSION: u32 = 1;
 pub const EVIDENCE_MODEL_VERSION: &str = "empirical-update-cpu-v1";
@@ -207,40 +205,6 @@ impl EmpiricalEvidenceProvider {
         costs.sort_by(|a, b| a.1.total_cmp(&b.1));
         costs.into_iter().map(|(algorithm, _)| algorithm).collect()
     }
-
-    /// Costs for one independently instantiated sketch state, in CPU ns.
-    /// Unknown retention/retirement remain unavailable; CPU time must not be
-    /// mixed with an existing deployment's unitless or CPU-operation costs.
-    pub fn lifecycle_cost_inputs(
-        &self,
-        summary: &OperatorNode,
-    ) -> SummaryMaintenanceLifecycleCostInputs {
-        let Operator::ASAP(ASAPOp::SummaryAgg {
-            family: FieldDataType::Sketch(kind, GroupingStrategy::PerSubpopulationInstance),
-            grouping: GroupingStrategy::PerSubpopulationInstance,
-            ..
-        }) = &summary.operator
-        else {
-            return SummaryMaintenanceLifecycleCostInputs::default();
-        };
-        let Ok(row) = self.lookup(kind.algorithm(), kind.params()) else {
-            return SummaryMaintenanceLifecycleCostInputs::default();
-        };
-        SummaryMaintenanceLifecycleCostInputs {
-            build_cost: snapshot_build_cpu(row).map(Cost),
-            maintenance_cost_per_update: row
-                .metrics
-                .resources
-                .cpu
-                .update_cpu_ns
-                .as_ref()
-                .map(|m| Cost(m.value)),
-            // A point-frequency benchmark read does not price a total-count
-            // or quantile read. There is no query request in this hook.
-            summary_read_cost: None,
-            ..Default::default()
-        }
-    }
 }
 
 /// Standalone adapter for the existing planner boundary. Empirical data changes
@@ -276,13 +240,6 @@ impl CostModel for EmpiricalCostModel {
     fn estimate_cost(&self, candidate: &ReplacementSubDAG, target: &TargetSubDAG<'_>) -> f64 {
         DefaultCostModel.estimate_cost(candidate, target)
     }
-
-    fn summary_maintenance_lifecycle_cost_inputs(
-        &self,
-        summary: &OperatorNode,
-    ) -> SummaryMaintenanceLifecycleCostInputs {
-        self.provider.lifecycle_cost_inputs(summary)
-    }
 }
 
 impl EvidenceArtifact {
@@ -360,14 +317,6 @@ fn nonnegative(value: f64) -> bool {
     value.is_finite() && value >= 0.0
 }
 
-fn snapshot_build_cpu(row: &OfflineMeasurement) -> Option<f64> {
-    let cpu = row.metrics.resources.cpu.build_cpu_ns.as_ref()?.value
-        + row.metrics.resources.cpu.update_cpu_ns.as_ref()?.value
-            * row.distribution.sample_count as f64
-        + snapshot_prepare_cpu(row)?;
-    nonnegative(cpu).then_some(cpu)
-}
-
 /// The existing fixed-snapshot CMS/CountSketch contract needs no separate
 /// preparation. Other families must measure that phase, including an explicit
 /// zero when no preparation is necessary; absence is not free work.
@@ -490,30 +439,6 @@ mod tests {
         );
     }
 
-    /// Lifecycle build includes all measured snapshot updates, not just an empty
-    /// allocation. A missing update measurement cannot become free ingestion.
-    #[test]
-    fn lifecycle_build_requires_complete_snapshot_ingestion() {
-        let (mut artifact, _, _) = fixture();
-        let row = &mut artifact.records[0];
-        row.metrics.resources.cpu.build_cpu_ns = Some(Measurement {
-            value: 10.0,
-            stddev: None,
-            samples: 1,
-            method: None,
-        });
-        assert_eq!(snapshot_build_cpu(row), Some(20010.0));
-        row.metrics.resources.cpu.prepare_cpu_ns = Some(Measurement {
-            value: 17.0,
-            stddev: None,
-            samples: 1,
-            method: None,
-        });
-        assert_eq!(snapshot_build_cpu(row), Some(20027.0));
-        row.metrics.resources.cpu.update_cpu_ns = None;
-        assert_eq!(snapshot_build_cpu(row), None);
-    }
-
     /// Newly shared optional dimensions receive the same numeric validation.
     #[test]
     fn optional_prepare_and_scan_measurements_are_validated() {
@@ -537,28 +462,21 @@ mod tests {
 
     /// Only the established frequency-sketch contract can omit preparation.
     #[test]
-    fn unmeasured_preparation_for_other_families_keeps_build_unknown() {
+    fn unmeasured_preparation_for_other_families_stays_unknown() {
         let (mut artifact, _, _) = fixture();
         let row = &mut artifact.records[0];
-        row.metrics.resources.cpu.build_cpu_ns = Some(Measurement {
-            value: 10.0,
-            stddev: None,
-            samples: 1,
-            method: None,
-        });
-        assert_eq!(snapshot_build_cpu(row), Some(20010.0));
         row.algorithm = SketchAlgorithm::CountSketch;
         assert_eq!(snapshot_prepare_cpu(row), Some(0.0));
         row.algorithm = SketchAlgorithm::Kll;
         row.params = SketchParams::Kll { k: 269 };
-        assert_eq!(snapshot_build_cpu(row), None);
+        assert_eq!(snapshot_prepare_cpu(row), None);
         row.metrics.resources.cpu.prepare_cpu_ns = Some(Measurement {
             value: 17.0,
             stddev: None,
             samples: 1,
             method: None,
         });
-        assert_eq!(snapshot_build_cpu(row), Some(20027.0));
+        assert_eq!(snapshot_prepare_cpu(row), Some(17.0));
     }
 
     fn fixture() -> (EvidenceArtifact, EvidenceContext, AggIntent) {
diff --git a/crates/asap-aware-mapping/src/lib.rs b/crates/asap-aware-mapping/src/lib.rs
index 42cad7974..443fcaca1 100644
--- a/crates/asap-aware-mapping/src/lib.rs
+++ b/crates/asap-aware-mapping/src/lib.rs
@@ -41,14 +41,11 @@
 //!   to obtain ranked views, and perform selection downstream.
 //! - Call [`CandidateLogicalASAPDAGs::global_selection`] once for the workload, then
 //!   [`GlobalSelection::assemble_selected_dag`] for each query root. This
-//!   coordinates logical choices and preserves shared nodes, but makes no
-//!   summary-maintenance lifecycle decision.
-//! - When Planner owns maintenance-versus-recomputation decisions, use
-//!   [`global_selection_with_summary_maintenance_lifecycles`] followed by
-//!   [`assemble_selected_dag_with_summary_maintenance_lifecycles`] per root.
-//!   This alternative workflow returns [`SummaryMaintenanceLifecyclePlan`]
-//!   values containing DAG roots and maintenance decisions; callers do not need
-//!   to run ordinary selection/assembly first.
+//!   coordinates logical choices and preserves shared nodes. Whether and when
+//!   a summary state is materialized is not decided here: every summary runs
+//!   at query time until Stage 2 materialization (#509) owns that choice.
+//! - Run the whole pipeline through [`optimize`] with [`MajorPass`], which
+//!   performs the two steps above for every root of a parsed workload.
 //!
 //! Models and evidence determine which choices the helpers can justify.
 //! Physical operator binding, placement, storage, deployment, and execution
@@ -172,9 +169,6 @@ pub mod replacement;
 pub mod rewrite;
 pub mod rollup;
 pub mod storage_io;
-pub mod summary_maintenance_cost;
-pub mod summary_maintenance_dag_export;
-pub mod summary_maintenance_lifecycle;
 #[cfg(test)]
 mod test_support;
 pub mod topk_reuse;
@@ -185,7 +179,6 @@ pub use accuracy::{
     CompositionShape, DefaultAccuracyModel, EqualSplitAllocator, NoAccuracyEvidence,
     PropagationStats, WorkloadAccuracyEvidence,
 };
-pub use cost_model::CompleteSummaryCandidateEstimate;
 pub use cost_model::{
     maintenance_operation_plan_cost_rate, raw_recompute_cost_rate, read_operation_plan_cost_rate,
     CostModel, CostProvenance, CostUnit, DefaultCostModel, ExactCompositionCostInputs,
@@ -197,9 +190,8 @@ pub use explanation::{
 };
 pub use grouping::{has_subpopulations, HydraGroupingStrategy};
 pub use pass::{
-    optimize, LifecycleInput, MajorPass, OptimizationInput, OptimizationInputError,
-    OptimizationPass, OptimizeError, PassNameConflict, PassRegistry, PlanOutput, PlanningModels,
-    QueryLifecyclePlan,
+    optimize, MajorPass, OptimizationInput, OptimizationInputError, OptimizationPass,
+    OptimizeError, PassNameConflict, PassRegistry, PlanOutput, PlanningModels, QueryPlan,
 };
 pub use recurrence::{
     evaluation_rate_of, total_cost, update_rate_from_data_workload, CostRate, EvaluationRate,
@@ -216,22 +208,6 @@ pub use replacement::{
     MAX_SEARCH_ITERATIONS,
 };
 pub use rewrite::{AvgToSumOverCountStrategy, SemanticEquivalentRewriteStrategy};
-pub use summary_maintenance_dag_export::{
-    export_summary_maintenance_plan, SummaryMaintenanceDAGExport,
-    SummaryMaintenanceDeploymentExport, SummaryMaintenanceLifecycleAlternativeExport,
-};
-pub use summary_maintenance_lifecycle::{
-    assemble_selected_dag_with_summary_maintenance_lifecycles,
-    enumerate_summary_maintenance_lifecycles, execution_timed_workload_dag,
-    global_selection_with_summary_maintenance_lifecycles, plan_summary_maintenance_lifecycles,
-    SummaryMaintenanceCapabilities, SummaryMaintenanceDeployment,
-    SummaryMaintenanceLifecycleAlternative, SummaryMaintenanceLifecycleAssemblyError,
-    SummaryMaintenanceLifecycleCandidates, SummaryMaintenanceLifecycleCapabilities,
-    SummaryMaintenanceLifecycleChoiceError, SummaryMaintenanceLifecycleCostInputs,
-    SummaryMaintenanceLifecyclePlan, SummaryMaintenanceLifecyclePlanError,
-    SummaryMaintenanceLifecycleRejection, SummaryMaintenanceLifecycleSelectionError,
-    SummaryMaintenanceTimingError, WorkloadDemand,
-};
 pub use topk_reuse::TopKLimitReuseStrategy;
 
 pub mod maintained_population;
diff --git a/crates/asap-aware-mapping/src/pass/major.rs b/crates/asap-aware-mapping/src/pass/major.rs
index 7be53e0f0..b8306c65a 100644
--- a/crates/asap-aware-mapping/src/pass/major.rs
+++ b/crates/asap-aware-mapping/src/pass/major.rs
@@ -12,12 +12,8 @@ use std::rc::Rc;
 use asap_types::ir::OperatorNode;
 use asap_types::types::AccuracyTarget;
 
-use super::{OptimizationInput, OptimizationPass, OptimizeError, PlanOutput, QueryLifecyclePlan};
+use super::{OptimizationInput, OptimizationPass, OptimizeError, PlanOutput, QueryPlan};
 use crate::replacement::{default_strategies_with_evidence, search_workload_with_targets};
-use crate::summary_maintenance_lifecycle::{
-    global_selection_with_summary_maintenance_lifecycles, plan_assembled_dag, shared_state_cost,
-    summary_states, WorkloadDemand,
-};
 
 /// The shipped algorithm. Unit struct: its strategy set is the crate default,
 /// and a caller who wants a different one now has a better option than
@@ -36,8 +32,7 @@ impl OptimizationPass for MajorPass {
         let strategies = default_strategies_with_evidence(models.cost, models.evidence);
 
         // `Id` is the entry's position in `QueryWorkload::entries()`, so the
-        // search result carries the workload binding the lifecycle stage and
-        // the output both need. CSE may make two identical queries share one
+        // search result carries the workload binding the output needs. CSE may make two identical queries share one
         // `Rc`, but it never drops or reorders a root, so this stays aligned.
         let roots: Vec<(usize, Rc<OperatorNode>, Option<AccuracyTarget>)> = workload
             .entries()
@@ -53,32 +48,7 @@ impl OptimizationPass for MajorPass {
 
         let space = search_workload_with_targets(roots, &strategies, models.accuracy);
 
-        let lifecycle = input.lifecycle;
-
-        // One index per root, in `CandidateLogicalASAPDAGs::roots` order — which is the order
-        // the roots went in, which is `entries()` order.
-        let entry_indices = workload.operator_indices().to_vec();
-        let demand = WorkloadDemand {
-            workload: workload.query_workload(),
-            data_workload: workload.data_workload(),
-            entry_indices: &entry_indices,
-        };
-
-        let selection = global_selection_with_summary_maintenance_lifecycles(
-            &space,
-            demand,
-            lifecycle.now_ms,
-            lifecycle.horizon,
-            lifecycle.capabilities,
-            models.cost,
-        )
-        .map_err(OptimizeError::LifecycleSelection)?;
-        // Each root's lifecycle is planned against the entries that consume
-        // it — the same binding selection costed it with — not the whole
-        // workload, so one query's reads never amortize another's state.
-        let bindings = space
-            .workload_entries_by_target(demand.workload, &entry_indices)
-            .map_err(|error| OptimizeError::LifecycleSelection(error.into()))?;
+        let selection = space.global_selection(models.cost);
 
         // Assemble every root, then intern structurally identical summary
         // producers across them once, so two queries that selected the same
@@ -87,101 +57,17 @@ impl OptimizationPass for MajorPass {
         for (entry_index, root) in &space.roots {
             let dag = selection
                 .assemble_selected_dag(root)
-                .map_err(|source| OptimizeError::LifecycleAssembly {
+                .map_err(|source| OptimizeError::Realization {
                     entry_index: *entry_index,
-                    source: source.into(),
+                    source,
                 })?
                 .ok_or_else(|| self.missing_group(*entry_index))?;
-            assembled.push(dag);
+            assembled.push((*entry_index, dag));
         }
-        let interned = share_common_sub_dags(assembled.iter().cloned().enumerate().collect());
-        let states: Vec<_> = interned
-            .iter()
-            .map(|(_, dag)| summary_states(dag))
+        let plans = share_common_sub_dags(assembled)
+            .into_iter()
+            .map(|(entry_index, root)| QueryPlan { entry_index, root })
             .collect();
-
-        // A state reached from several roots is planned once against all of
-        // their entries, in every plan that reaches it, so each plan picks
-        // the same lifecycle for it. When that union cannot be costed the
-        // roots keep their own, unshared DAG and entries.
-        let mut shared_entries: Vec<(Rc<OperatorNode>, Option<Vec<usize>>)> = Vec::new();
-        for (position, (entry_index, root)) in space.roots.iter().enumerate() {
-            for state in &states[position] {
-                if shared_entries.iter().any(|(s, _)| Rc::ptr_eq(s, state)) {
-                    continue;
-                }
-                let readers: Vec<_> = (0..space.roots.len())
-                    .filter(|&other| states[other].iter().any(|s| Rc::ptr_eq(s, state)))
-                    .map(|other| &space.roots[other].1)
-                    .collect();
-                if readers.iter().all(|reader| Rc::ptr_eq(reader, root)) {
-                    continue;
-                }
-                let mut entries: Vec<usize> = readers
-                    .iter()
-                    .flat_map(|reader| bindings[&Rc::as_ptr(reader)].iter().copied())
-                    .collect();
-                entries.sort_unstable();
-                entries.dedup();
-                let cost = shared_state_cost(
-                    state,
-                    WorkloadDemand {
-                        entry_indices: &entries,
-                        ..demand
-                    },
-                    lifecycle.now_ms,
-                    lifecycle.horizon,
-                    lifecycle.capabilities,
-                    models.cost,
-                )
-                .map_err(|source| OptimizeError::LifecycleAssembly {
-                    entry_index: *entry_index,
-                    source: source.into(),
-                })?;
-                shared_entries.push((Rc::clone(state), cost.map(|_| entries)));
-            }
-        }
-
-        let mut plans = Vec::with_capacity(space.roots.len());
-        for (position, (entry_index, root)) in space.roots.iter().enumerate() {
-            let mut entries = bindings[&Rc::as_ptr(root)].clone();
-            let mut dag = Rc::clone(&interned[position].1);
-            for (state, shared) in &shared_entries {
-                if !states[position].iter().any(|s| Rc::ptr_eq(s, state)) {
-                    continue;
-                }
-                match shared {
-                    Some(shared) => entries.extend(shared),
-                    None => {
-                        entries = bindings[&Rc::as_ptr(root)].clone();
-                        dag = Rc::clone(&assembled[position]);
-                        break;
-                    }
-                }
-            }
-            entries.sort_unstable();
-            entries.dedup();
-            let plan = plan_assembled_dag(
-                dag,
-                root,
-                WorkloadDemand {
-                    entry_indices: &entries,
-                    ..demand
-                },
-                lifecycle.now_ms,
-                lifecycle.horizon,
-                lifecycle.capabilities,
-                models.cost,
-            )
-            .map_err(|source| OptimizeError::LifecycleAssembly {
-                entry_index: *entry_index,
-                source,
-            })?;
-            plans.push(QueryLifecyclePlan {
-                entry_index: *entry_index,
-                plan,
-            });
-        }
         let mut output = PlanOutput::new(plans);
         output.scalar_roots = workload.scalar_roots().to_vec();
         Ok(output)
diff --git a/crates/asap-aware-mapping/src/pass/mod.rs b/crates/asap-aware-mapping/src/pass/mod.rs
index afd63dbdb..02a01000a 100644
--- a/crates/asap-aware-mapping/src/pass/mod.rs
+++ b/crates/asap-aware-mapping/src/pass/mod.rs
@@ -17,20 +17,18 @@ mod major;
 use std::collections::BTreeMap;
 use std::rc::Rc;
 
+use asap_types::ir::export::compile_physical_asap_workload;
+use asap_types::ir::timing::{apply_lifecycle_timings, LifecycleAssignment, TimingMemo};
 use asap_types::ir::OperatorNode;
 use asap_types::parsed_workload::ParsedWorkload;
+use asap_types::post_asap::ExecutionDataStateError;
 use asap_types::workload::WorkloadError;
 
 use crate::accuracy::{
     AccuracyEvidenceProvider, AccuracyModel, DefaultAccuracyModel, NoAccuracyEvidence,
 };
 use crate::cost_model::{CostModel, DefaultCostModel};
-use crate::recurrence::Horizon;
 use crate::replacement::RealizationError;
-use crate::summary_maintenance_lifecycle::{
-    SummaryMaintenanceLifecycleAssemblyError, SummaryMaintenanceLifecycleCapabilities,
-    SummaryMaintenanceLifecyclePlan, SummaryMaintenanceLifecycleSelectionError,
-};
 
 pub use major::MajorPass;
 
@@ -90,66 +88,22 @@ impl<'a> PlanningModels<'a> {
     }
 }
 
-/// Supplying this asks the pass to also decide summary maintenance versus raw
-/// recomputation; leaving it out asks only for the logical DAG.
-#[derive(Clone, Copy)]
-#[non_exhaustive]
-pub struct LifecycleInput {
-    /// Planning clock, Unix milliseconds.
-    pub now_ms: u64,
-    /// Seconds. Required to turn recurring demand into a finite total.
-    pub horizon: Option<Horizon>,
-    pub capabilities: SummaryMaintenanceLifecycleCapabilities,
-}
-
-impl LifecycleInput {
-    pub fn new(now_ms: u64, capabilities: SummaryMaintenanceLifecycleCapabilities) -> Self {
-        Self {
-            now_ms,
-            horizon: None,
-            capabilities,
-        }
-    }
-
-    pub fn with_horizon(mut self, horizon: Horizon) -> Self {
-        self.horizon = Some(horizon);
-        self
-    }
-}
-
 #[derive(Clone, Copy)]
 #[non_exhaustive]
 pub struct OptimizationInput<'a> {
     pub workload: &'a ParsedWorkload,
     pub models: PlanningModels<'a>,
-    /// Every plan carries the maintenance-versus-recomputation decision, so
-    /// the planning clock and runtime capabilities are always required.
-    pub lifecycle: LifecycleInput,
 }
 
 impl<'a> OptimizationInput<'a> {
-    pub fn new(
-        workload: &'a ParsedWorkload,
-        models: PlanningModels<'a>,
-        lifecycle: LifecycleInput,
-    ) -> Self {
-        Self {
-            workload,
-            models,
-            lifecycle,
-        }
+    pub fn new(workload: &'a ParsedWorkload, models: PlanningModels<'a>) -> Self {
+        Self { workload, models }
     }
 
     pub fn validate(&self) -> Result<(), OptimizationInputError> {
         self.workload
             .validate()
-            .map_err(OptimizationInputError::Workload)?;
-        if let Some(horizon) = self.lifecycle.horizon {
-            if !horizon.0.is_finite() || horizon.0 <= 0.0 {
-                return Err(OptimizationInputError::InvalidHorizon(horizon.0));
-            }
-        }
-        Ok(())
+            .map_err(OptimizationInputError::Workload)
     }
 }
 
@@ -158,38 +112,34 @@ impl<'a> OptimizationInput<'a> {
 pub enum OptimizationInputError {
     #[error("workload: {0}")]
     Workload(WorkloadError),
-    #[error("planning horizon must be finite and positive, got {0}")]
-    InvalidHorizon(f64),
 }
 
 // ── Output ───────────────────────────────────────────────────────────────
 
-/// One query's selected post-ASAP DAG plus the maintenance decisions taken
-/// for it. The DAG is `plan.root`.
+/// One query's selected post-ASAP DAG.
 #[derive(Debug, Clone)]
-pub struct QueryLifecyclePlan {
+pub struct QueryPlan {
     /// Index into `QueryWorkload::entries()`.
     pub entry_index: usize,
-    pub plan: SummaryMaintenanceLifecyclePlan,
+    pub root: Rc<OperatorNode>,
 }
 
-/// One multi-root workload DAG with query/lifecycle bindings in entry order;
+/// One multi-root workload DAG with query bindings in entry order;
 /// [`check_contract`] enforces that.
 ///
 /// Plans are not deduplicated across entries: a summary state that several
-/// queries share appears in each of their plans as the same `Rc` (with the
-/// same lifecycle), so a consumer that deploys or costs the workload must
-/// dedupe deployments by `Rc::ptr_eq` on the summary node.
+/// queries share appears in each of their plans as the same `Rc`, so a
+/// consumer that deploys or costs the workload must dedupe by `Rc::ptr_eq`.
 #[derive(Debug, Clone)]
 #[non_exhaustive]
 pub struct PlanOutput {
-    pub plans: Vec<QueryLifecyclePlan>,
+    pub plans: Vec<QueryPlan>,
     /// Exact scalar expressions, keyed by workload entry; embedded plan reads remain visible.
     pub scalar_roots: Vec<(usize, asap_types::ir::ScalarExpr)>,
 }
 
 impl PlanOutput {
-    pub fn new(plans: Vec<QueryLifecyclePlan>) -> Self {
+    pub fn new(plans: Vec<QueryPlan>) -> Self {
         Self {
             plans,
             scalar_roots: Vec::new(),
@@ -218,7 +168,7 @@ impl PlanOutput {
             .map(|p| {
                 (
                     p.entry_index,
-                    asap_types::ir::QueryRoot::Operator(Rc::clone(&p.plan.root)),
+                    asap_types::ir::QueryRoot::Operator(Rc::clone(&p.root)),
                 )
             })
             .chain(
@@ -233,7 +183,7 @@ impl PlanOutput {
 
     /// The selected operator roots. Use `roots()` to include scalar queries.
     pub fn operator_roots(&self) -> Vec<Rc<OperatorNode>> {
-        self.plans.iter().map(|p| Rc::clone(&p.plan.root)).collect()
+        self.plans.iter().map(|p| Rc::clone(&p.root)).collect()
     }
 
     /// Unique operators in the entire workload DAG, including scalar-plan dependencies.
@@ -264,9 +214,16 @@ impl PlanOutput {
     /// roots have no physical form yet and are left out.
     pub fn execution_timed_dag(
         &self,
-    ) -> Result<asap_types::ir::export::PhysicalASAPDAG, crate::SummaryMaintenanceTimingError> {
-        let plans: Vec<_> = self.plans.iter().map(|p| &p.plan).collect();
-        crate::execution_timed_workload_dag(&plans)
+    ) -> Result<asap_types::ir::export::PhysicalASAPDAG, ExecutionDataStateError> {
+        // One memo, so a node shared by several roots is timed and exported once.
+        let mut memo = TimingMemo::new();
+        let assignment = LifecycleAssignment::default_maintained();
+        let timed = self
+            .plans
+            .iter()
+            .map(|p| apply_lifecycle_timings(&p.root, &assignment, &mut memo))
+            .collect::<Result<Vec<_>, _>>()?;
+        compile_physical_asap_workload(&timed)
     }
 
     pub fn len(&self) -> usize {
@@ -288,13 +245,6 @@ pub enum OptimizeError {
         entry_index: usize,
         source: RealizationError,
     },
-    #[error("summary-maintenance-lifecycle selection: {0}")]
-    LifecycleSelection(SummaryMaintenanceLifecycleSelectionError),
-    #[error("entry {entry_index}: {source}")]
-    LifecycleAssembly {
-        entry_index: usize,
-        source: SummaryMaintenanceLifecycleAssemblyError,
-    },
     /// The pass returned something the downstream contract forbids. This is a
     /// defect in the pass, not in its input.
     #[error("pass `{pass}` violated the output contract: {detail}")]
diff --git a/crates/asap-aware-mapping/src/replacement.rs b/crates/asap-aware-mapping/src/replacement.rs
index dd043b915..d7a3d5ada 100644
--- a/crates/asap-aware-mapping/src/replacement.rs
+++ b/crates/asap-aware-mapping/src/replacement.rs
@@ -56,9 +56,7 @@
 //! does not establish a compatible workload plan or physical deployability.
 //! For Planner-owned logical selection, call [`CandidateLogicalASAPDAGs::global_selection`]
 //! once and [`GlobalSelection::assemble_selected_dag`] for each wanted query
-//! root. Alternatively, use the summary-maintenance-lifecycle-aware helpers
-//! when Planner should also compare maintenance against raw recomputation.
-//! Physical binding, deployment, and execution remain downstream.
+//! root. Physical binding, deployment, and execution remain downstream.
 //!
 //! Internally, [`realize_child`] and [`realize_one`] may take a preferred local
 //! realization while constructing or costing a candidate. That local operation
@@ -381,8 +379,8 @@ use crate::accuracy::{
     DefaultAccuracyModel, EqualSplitAllocator, NoAccuracyEvidence,
 };
 use crate::cost_model::{
-    raw_recompute_cost_rate, Cost, CostModel, CseCandidate, DefaultCostModel,
-    ExactCompositionCostInputs, ExactCompositionCostRequest, ShareDecision,
+    raw_recompute_cost_rate, CostModel, CseCandidate, DefaultCostModel, ExactCompositionCostInputs,
+    ExactCompositionCostRequest, ShareDecision,
 };
 use crate::exact_composition::{ExactComposition, ExactCompositionStrategy, OperationPlacement};
 use crate::grouping::HydraGroupingStrategy;
@@ -4393,50 +4391,6 @@ impl<Id: Clone + PartialEq> CandidateLogicalASAPDAGs<Id> {
     }
 }
 
-/// Lifecycle-aware whole-subplan costs keyed by target and candidate identity.
-#[derive(Default, Clone)]
-pub(crate) struct CandidateCostOverrides {
-    costs: HashMap<(*const OperatorNode, *const ReplacementSubDAG), Cost>,
-    raw_costs: HashMap<*const OperatorNode, Cost>,
-    /// Targets for which the caller requested an atomic raw-vs-summary
-    /// decision. Other memo groups continue through ordinary CSE selection.
-    finalized_targets: HashSet<*const OperatorNode>,
-}
-
-impl CandidateCostOverrides {
-    pub(crate) fn finalize_target(&mut self, target: &Rc<OperatorNode>) {
-        self.finalized_targets.insert(Rc::as_ptr(target));
-    }
-
-    fn finalizes(&self, target: &Rc<OperatorNode>) -> bool {
-        self.finalized_targets.contains(&Rc::as_ptr(target))
-    }
-
-    pub(crate) fn insert(
-        &mut self,
-        target: &Rc<OperatorNode>,
-        candidate: &ReplacementSubDAG,
-        cost: Cost,
-    ) {
-        self.costs
-            .insert((Rc::as_ptr(target), candidate as *const _), cost);
-    }
-
-    fn get(&self, target: &Rc<OperatorNode>, candidate: &ReplacementSubDAG) -> Option<Cost> {
-        self.costs
-            .get(&(Rc::as_ptr(target), candidate as *const _))
-            .copied()
-    }
-
-    pub(crate) fn insert_raw(&mut self, target: &Rc<OperatorNode>, cost: Cost) {
-        self.raw_costs.insert(Rc::as_ptr(target), cost);
-    }
-
-    fn raw(&self, target: &Rc<OperatorNode>) -> Option<Cost> {
-        self.raw_costs.get(&Rc::as_ptr(target)).copied()
-    }
-}
-
 impl<Id> CandidateLogicalASAPDAGs<Id> {
     /// One candidate set per discovered target sub-DAG, in discovery order.
     pub fn target_subdag_candidates(&self) -> impl Iterator<Item = &TargetSubDAGCandidates> {
@@ -4851,54 +4805,6 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
             .map(|rate| UpdateRate(rate.0));
         self.recurrence_profiles(&recurrences, update_rate)
     }
-
-    /// Associate every discovered target with the normalized workload entries
-    /// whose roots can reach it.
-    pub(crate) fn workload_entries_by_target(
-        &self,
-        workload: &QueryWorkload,
-        root_workload_entries: &[usize],
-    ) -> Result<HashMap<*const OperatorNode, Vec<usize>>, RecurrenceError> {
-        let entry_count = workload.entries().count();
-        if root_workload_entries.len() != self.roots.len() {
-            return Err(RecurrenceError::RootCountMismatch {
-                expected: self.roots.len(),
-                got: root_workload_entries.len(),
-            });
-        }
-        let mut bindings: HashMap<*const OperatorNode, HashSet<usize>> = HashMap::new();
-        for ((_, root), &entry_index) in self.roots.iter().zip(root_workload_entries) {
-            if entry_index >= entry_count {
-                return Err(RecurrenceError::InvalidWorkloadEntry {
-                    index: entry_index,
-                    entry_count,
-                });
-            }
-            let mut seen = HashSet::new();
-            let mut queue = VecDeque::from([Rc::as_ptr(root)]);
-            while let Some(ptr) = queue.pop_front() {
-                if !seen.insert(ptr) {
-                    continue;
-                }
-                bindings.entry(ptr).or_default().insert(entry_index);
-                if let Some(group) = self.groups.get(&ptr) {
-                    queue.extend(
-                        direct_child_counts(&group.target)
-                            .into_iter()
-                            .map(|(child, _)| child),
-                    );
-                }
-            }
-        }
-        Ok(bindings
-            .into_iter()
-            .map(|(ptr, entries)| {
-                let mut entries: Vec<_> = entries.into_iter().collect();
-                entries.sort_unstable();
-                (ptr, entries)
-            })
-            .collect())
-    }
 }
 
 /// Record `times` occurrences of `recurrence` against `ptr` — `times > 1`
@@ -5761,7 +5667,7 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
     /// Uncertified DDSketch ratios remain in [`CandidateLogicalASAPDAGs`] for downstream
     /// inspection but are not chosen automatically by this selector.
     pub fn global_selection(&self, cost_model: &dyn CostModel) -> GlobalSelection<'_> {
-        self.global_selection_impl(cost_model, None, None, None)
+        self.global_selection_impl(cost_model, None, None)
             .expect("structural global selection cannot produce a recurrence error")
     }
 
@@ -5775,17 +5681,7 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
         profiles: &RecurrenceProfileMap,
         horizon: Option<Horizon>,
     ) -> Result<GlobalSelection<'_>, RecurrenceError> {
-        self.global_selection_impl(cost_model, Some(profiles), horizon, None)
-    }
-
-    pub(crate) fn global_selection_with_candidate_costs(
-        &self,
-        cost_model: &dyn CostModel,
-        profiles: &RecurrenceProfileMap,
-        horizon: Option<Horizon>,
-        costs: &CandidateCostOverrides,
-    ) -> Result<GlobalSelection<'_>, RecurrenceError> {
-        self.global_selection_impl(cost_model, Some(profiles), horizon, Some(costs))
+        self.global_selection_impl(cost_model, Some(profiles), horizon)
     }
 
     fn global_selection_impl(
@@ -5793,7 +5689,6 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
         cost_model: &dyn CostModel,
         profiles: Option<&RecurrenceProfileMap>,
         horizon: Option<Horizon>,
-        candidate_costs: Option<&CandidateCostOverrides>,
     ) -> Result<GlobalSelection<'_>, RecurrenceError> {
         let dag = reference_dag(self);
         let topo = topological_order(&self.order, &dag);
@@ -5854,30 +5749,8 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
                 }
             }
 
-            let lifecycle_choice = candidate_costs
-                .filter(|costs| costs.finalizes(&group.target))
-                .map(|costs| {
-                    let summary = group
-                        .candidates
-                        .iter()
-                        .filter(|candidate| !is_composition_candidate(candidate))
-                        .filter(|candidate| is_automatically_selectable(candidate, cost_model))
-                        .filter_map(|candidate| {
-                            costs
-                                .get(&group.target, candidate)
-                                .map(|cost| (candidate, cost))
-                        })
-                        .min_by(|(_, left), (_, right)| left.0.total_cmp(&right.0));
-                    match (summary, costs.raw(&group.target)) {
-                        (Some((_, summary_cost)), Some(raw)) if raw.0 <= summary_cost.0 => None,
-                        (Some((candidate, _)), _) => Some(candidate),
-                        (None, _) => None,
-                    }
-                });
-
             let complete_plan_choice = (!forced.is_some()
                 && composed.is_none()
-                && lifecycle_choice.is_none()
                 && cost_model.candidate_cost_covers_complete_plan())
             .then(|| {
                 let effective_target = TargetSubDAG::with_consumer_count(&group.target, effective);
@@ -5917,8 +5790,6 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
             } else if let Some(option) = composed {
                 composition_decision = Some(option.decision);
                 Some(option.candidate)
-            } else if let Some(choice) = lifecycle_choice {
-                choice
             } else if cost_model.candidate_cost_covers_complete_plan() {
                 complete_plan_choice
             } else if effective >= 2 && cse_candidate_pair(group).is_some() {
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_cost/estimator.rs b/crates/asap-aware-mapping/src/summary_maintenance_cost/estimator.rs
deleted file mode 100644
index 911d90275..000000000
--- a/crates/asap-aware-mapping/src/summary_maintenance_cost/estimator.rs
+++ /dev/null
@@ -1,1219 +0,0 @@
-use super::*;
-
-pub(super) fn estimate_heterogeneous_summary(
-    root: &OperatorNode,
-    deployments: &[CostedSummaryDeployment<'_>],
-    evidence: &SummaryNodeEvidence,
-    scope: &ComparisonScope,
-    raw: &RawInputEvidence,
-    window_frameworks: &[Option<SummaryWindowFramework>],
-) -> Result<ResourceEstimate, AnalyticalCostError> {
-    if window_frameworks.len() != deployments.len() {
-        return Err(AnalyticalCostError::ComparisonScopeMismatch(
-            "window framework assignments",
-        ));
-    }
-    let frameworks_by_node: HashMap<_, _> = deployments
-        .iter()
-        .zip(window_frameworks)
-        .map(|(deployment, framework)| (deployment.summary as *const _, framework))
-        .collect();
-    validate_summary_edges_and_physical_ids(root, evidence, &frameworks_by_node)?;
-    let evaluation_count = scope.validate()?;
-    let by_node: HashMap<_, _> = deployments
-        .iter()
-        .map(|deployment| (deployment.summary as *const _, deployment))
-        .collect();
-    let mut cpu_ops = 0.0;
-    let mut persistent_bytes = 0_u64;
-    let mut ephemeral_state_bytes = 0_u64;
-    let mut scans = HashMap::<String, (usize, u64)>::new();
-    let mut physical_states = HashMap::<
-        String,
-        (
-            SummaryAggregateEvidence,
-            SummaryMaintenanceLifecycleGuarantee,
-            String,
-            Option<SummaryWindowFramework>,
-        ),
-    >::new();
-    for deployment in deployments {
-        let node_evidence = evidence
-            .aggregation(deployment.summary)
-            .ok_or(AnalyticalCostError::MissingOrStale("summary_agg"))?;
-        let Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) = &deployment.summary.operator else {
-            return Err(AnalyticalCostError::UnsupportedCandidate);
-        };
-        let inputs = node_evidence.inputs.validate()?;
-        validate_arrival_rate(scope.data_arrival, inputs.ingestion_rate_per_second)?;
-        match node_evidence.scan_selection_index {
-            Some(index) => {
-                let declared =
-                    scope
-                        .sources
-                        .get(index)
-                        .ok_or(AnalyticalCostError::MissingComparisonScope(
-                            "summary scan selection",
-                        ))?;
-                if !has_retained_subdag_evidence(child, evidence)
-                    || inputs.initial_input_rows != raw.planning_time_input_rows
-                    || inputs.initial_input_bytes != raw.planning_time_input_bytes
-                    || inputs.initial_source_scan_bytes != raw.planning_time_source_scan_bytes
-                    || inputs.ingestion_rate_per_second != raw.ingestion_rate_per_second
-                {
-                    return Err(AnalyticalCostError::ComparisonScopeMismatch(
-                        "source-root bootstrap evolution",
-                    ));
-                }
-                let mut actual_selections = Vec::new();
-                query_source_selections(child, &mut HashSet::new(), &mut actual_selections)?;
-                let actual_selections = deduplicate_source_selections(actual_selections);
-                let expected = (
-                    declared.source.clone(),
-                    declared.predicates.clone(),
-                    declared.info_matchers.clone(),
-                );
-                if actual_selections.as_slice() != [expected] {
-                    return Err(AnalyticalCostError::ComparisonScopeMismatch(
-                        "summary source lineage",
-                    ));
-                }
-            }
-            None => {
-                if has_retained_subdag_evidence(child, evidence)
-                    || inputs.initial_source_scan_bytes != 0
-                    || !node_evidence.bootstrap_read_identity.is_empty()
-                {
-                    return Err(AnalyticalCostError::ComparisonScopeMismatch(
-                        "intermediate bootstrap source ownership",
-                    ));
-                }
-            }
-        }
-        validate_guarantee(deployment.guarantee, scope.data_arrival)?;
-        let logical_state = format!("{:?}", deployment.summary.operator);
-        let window_framework = (*frameworks_by_node
-            .get(&(deployment.summary as *const _))
-            .ok_or(AnalyticalCostError::MissingOrStale(
-                "window framework assignment",
-            ))?)
-        .clone();
-        match physical_states.entry(node_evidence.physical_id.clone()) {
-            std::collections::hash_map::Entry::Vacant(entry) => {
-                entry.insert((
-                    node_evidence.clone(),
-                    deployment.guarantee.clone(),
-                    logical_state,
-                    window_framework,
-                ));
-            }
-            std::collections::hash_map::Entry::Occupied(entry)
-                if entry.get()
-                    != &(
-                        node_evidence.clone(),
-                        deployment.guarantee.clone(),
-                        logical_state,
-                        window_framework,
-                    ) =>
-            {
-                return Err(AnalyticalCostError::ComparisonScopeMismatch(
-                    "summary physical identity",
-                ));
-            }
-            std::collections::hash_map::Entry::Occupied(_) => continue,
-        }
-        let ephemeral = matches!(
-            deployment.guarantee.summary_maintenance_lifecycle,
-            SummaryMaintenanceLifecycle::Ephemeral
-        );
-        let (bootstrap, updates, source_scan_bytes) = if ephemeral {
-            (
-                ephemeral_rows_over_horizon(inputs, scope)?,
-                0,
-                ephemeral_scan_bytes_over_horizon(inputs, raw, scope)?,
-            )
-        } else {
-            let (bootstrap, updates, _) =
-                lifecycle_row_counts(inputs, deployment.guarantee, scope)?;
-            let bootstrap_extra_rows = bootstrap
-                .checked_sub(inputs.initial_input_rows)
-                .ok_or(AnalyticalCostError::Overflow)?;
-            let source_scan_bytes = if node_evidence.scan_selection_index.is_some() {
-                inputs
-                    .initial_source_scan_bytes
-                    .checked_add(
-                        bootstrap_extra_rows
-                            .checked_mul(raw.arriving_source_row_bytes)
-                            .ok_or(AnalyticalCostError::Overflow)?,
-                    )
-                    .ok_or(AnalyticalCostError::Overflow)?
-            } else {
-                0
-            };
-            (bootstrap, updates, source_scan_bytes)
-        };
-        let insert = validated_operator_cpu("insert_cpu_ops", node_evidence.insert_cpu_ops)?;
-        let insert_calls = bootstrap
-            .checked_mul(inputs.bootstrap_window_count)
-            .and_then(|calls| {
-                updates
-                    .checked_mul(inputs.active_window_count)
-                    .and_then(|updates| calls.checked_add(updates))
-            })
-            .ok_or(AnalyticalCostError::Overflow)?;
-        cpu_ops += insert_calls as f64 * insert;
-        let live_window_count = if ephemeral {
-            inputs.bootstrap_window_count
-        } else {
-            inputs
-                .active_window_count
-                .checked_add(inputs.retained_window_count)
-                .ok_or(AnalyticalCostError::Overflow)?
-        };
-        let state_bytes = live_window_count
-            .checked_mul(inputs.physical_summary_count)
-            .and_then(|states| states.checked_mul(inputs.state_bytes_per_summary))
-            .ok_or(AnalyticalCostError::Overflow)?;
-        if ephemeral {
-            ephemeral_state_bytes = ephemeral_state_bytes
-                .checked_add(state_bytes)
-                .ok_or(AnalyticalCostError::Overflow)?;
-        } else {
-            persistent_bytes = persistent_bytes
-                .checked_add(state_bytes)
-                .ok_or(AnalyticalCostError::Overflow)?;
-        }
-        if let Some(source_index) = node_evidence.scan_selection_index {
-            if node_evidence.bootstrap_read_identity.is_empty() {
-                return Err(AnalyticalCostError::MissingOrStale(
-                    "bootstrap_read_identity",
-                ));
-            }
-            match scans.entry(node_evidence.bootstrap_read_identity.clone()) {
-                std::collections::hash_map::Entry::Vacant(entry) => {
-                    entry.insert((source_index, source_scan_bytes));
-                }
-                std::collections::hash_map::Entry::Occupied(entry)
-                    if *entry.get() != (source_index, source_scan_bytes) =>
-                {
-                    return Err(AnalyticalCostError::ComparisonScopeMismatch(
-                        "bootstrap source bytes",
-                    ));
-                }
-                _ => {}
-            }
-        }
-    }
-    let covered_sources: HashSet<_> = scans.values().map(|(index, _)| *index).collect();
-    if covered_sources.len() != scope.sources.len()
-        || !(0..scope.sources.len()).all(|index| covered_sources.contains(&index))
-    {
-        return Err(AnalyticalCostError::ComparisonScopeMismatch("sources"));
-    }
-
-    #[expect(clippy::too_many_arguments, reason = "CPU and I/O traversal state")]
-    fn visit_ops(
-        node: &OperatorNode,
-        seen: &mut HashSet<String>,
-        by_node: &HashMap<*const OperatorNode, &CostedSummaryDeployment<'_>>,
-        evidence: &SummaryNodeEvidence,
-        scope: &ComparisonScope,
-        evaluation_count: u64,
-        cpu_ops: &mut f64,
-        io_bytes: &mut u64,
-    ) -> Result<(), AnalyticalCostError> {
-        let physical_id = summary_physical_id(node, evidence)?;
-        if !seen.insert(physical_id) {
-            return Ok(());
-        }
-        if has_retained_subdag_evidence(node, evidence) {
-            let retained = evidence
-                .retained_queries
-                .get(&(node as *const _))
-                .ok_or(AnalyticalCostError::MissingOrStale("retain_exact"))?;
-            if !retained.preprocessing_cpu_ops_over_horizon.is_finite()
-                || retained.preprocessing_cpu_ops_over_horizon < 0.0
-            {
-                return Err(AnalyticalCostError::InvalidOperationCost(
-                    "retain_exact",
-                    retained.preprocessing_cpu_ops_over_horizon,
-                ));
-            }
-            *cpu_ops += retained.preprocessing_cpu_ops_over_horizon;
-            return Ok(());
-        }
-        match &node.operator {
-            Operator::NonASAP(NonASAPOp::BinaryOp { lhs, rhs, .. })
-            | Operator::NonASAP(NonASAPOp::Join {
-                left: lhs,
-                right: rhs,
-                ..
-            }) => {
-                let operation = summary_operation_evidence(node, evidence)?.resource();
-                *cpu_ops += evaluation_count as f64
-                    * validated_operator_executions("exact_binary", operation)? as f64
-                    * validated_operator_cpu("exact_binary", operation.cpu_ops)?;
-                add_operator_io(io_bytes, operation, evaluation_count)?;
-                visit_ops(
-                    lhs,
-                    seen,
-                    by_node,
-                    evidence,
-                    scope,
-                    evaluation_count,
-                    cpu_ops,
-                    io_bytes,
-                )?;
-                visit_ops(
-                    rhs,
-                    seen,
-                    by_node,
-                    evidence,
-                    scope,
-                    evaluation_count,
-                    cpu_ops,
-                    io_bytes,
-                )?;
-            }
-
-            Operator::NonASAP(_)
-            | Operator::ASAP(
-                ASAPOp::FinalizeExactAccumulator { .. }
-                | ASAPOp::MaintainPopulation { .. }
-                | ASAPOp::EvaluatePopulation { .. },
-            ) => {
-                let operation = summary_operation_evidence(node, evidence)?.resource();
-                *cpu_ops += evaluation_count as f64
-                    * validated_operator_executions("value_operation", operation)? as f64
-                    * validated_operator_cpu("value_operation", operation.cpu_ops)?;
-                add_operator_io(io_bytes, operation, evaluation_count)?;
-                for child in node.children() {
-                    visit_ops(
-                        child,
-                        seen,
-                        by_node,
-                        evidence,
-                        scope,
-                        evaluation_count,
-                        cpu_ops,
-                        io_bytes,
-                    )?;
-                }
-            }
-            Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) => {
-                visit_ops(
-                    child,
-                    seen,
-                    by_node,
-                    evidence,
-                    scope,
-                    evaluation_count,
-                    cpu_ops,
-                    io_bytes,
-                )?;
-            }
-            Operator::ASAP(ASAPOp::SummaryMerge { children }) => {
-                let operation = summary_operation_evidence(node, evidence)?.resource();
-                let merge = validated_operator_cpu("summary_merge", operation.cpu_ops)?;
-                *cpu_ops += evaluation_count as f64
-                    * validated_operator_executions("summary_merge", operation)? as f64
-                    * merge;
-                add_operator_io(io_bytes, operation, evaluation_count)?;
-                for child in children {
-                    visit_ops(
-                        child,
-                        seen,
-                        by_node,
-                        evidence,
-                        scope,
-                        evaluation_count,
-                        cpu_ops,
-                        io_bytes,
-                    )?;
-                }
-            }
-            Operator::ASAP(ASAPOp::SummarySubtract { left, right }) => {
-                let operation = summary_operation_evidence(node, evidence)?.resource();
-                *cpu_ops += evaluation_count as f64
-                    * validated_operator_executions("summary_subtract", operation)? as f64
-                    * validated_operator_cpu("summary_subtract", operation.cpu_ops)?;
-                add_operator_io(io_bytes, operation, evaluation_count)?;
-                visit_ops(
-                    left,
-                    seen,
-                    by_node,
-                    evidence,
-                    scope,
-                    evaluation_count,
-                    cpu_ops,
-                    io_bytes,
-                )?;
-                visit_ops(
-                    right,
-                    seen,
-                    by_node,
-                    evidence,
-                    scope,
-                    evaluation_count,
-                    cpu_ops,
-                    io_bytes,
-                )?;
-            }
-            Operator::ASAP(ASAPOp::SummaryDelete { summary_input, .. }) => {
-                let delete = summary_operation_evidence(node, evidence)?;
-                let SummaryOperatorEvidence::Delete {
-                    resource: operation,
-                    events_per_second,
-                    routing_fanout,
-                } = delete
-                else {
-                    unreachable!("operation kind was validated")
-                };
-                let state_ptr = evidence
-                    .operation_state_owners
-                    .get(&(node as *const _))
-                    .ok_or(AnalyticalCostError::MissingOrStale("summary_delete_owner"))?;
-                fn collect_aggs(
-                    node: &OperatorNode,
-                    seen: &mut HashSet<*const OperatorNode>,
-                    out: &mut Vec<*const OperatorNode>,
-                ) {
-                    if !seen.insert(node as *const _) {
-                        return;
-                    }
-                    if matches!(node.operator, Operator::ASAP(ASAPOp::SummaryAgg { .. })) {
-                        out.push(node as *const _);
-                    }
-                    for child in node.children() {
-                        collect_aggs(child, seen, out);
-                    }
-                }
-                let mut reachable = Vec::new();
-                collect_aggs(summary_input, &mut HashSet::new(), &mut reachable);
-                if reachable.as_slice() != [*state_ptr] {
-                    return Err(AnalyticalCostError::ComparisonScopeMismatch(
-                        "summary delete owner",
-                    ));
-                }
-                let deployment = by_node
-                    .get(state_ptr)
-                    .copied()
-                    .ok_or(AnalyticalCostError::MissingOrStale("summary_delete_owner"))?;
-                let state = evidence
-                    .aggregation(deployment.summary)
-                    .ok_or(AnalyticalCostError::MissingOrStale("summary_delete_owner"))?;
-                let (_, _, active_ms) =
-                    lifecycle_row_counts(state.inputs, deployment.guarantee, scope)?;
-                if !events_per_second.is_finite() || *events_per_second < 0.0 {
-                    return Err(AnalyticalCostError::InvalidIngestionRate(
-                        *events_per_second,
-                    ));
-                }
-                if *routing_fanout == 0 {
-                    return Err(AnalyticalCostError::MissingOrZero("delete_routing_fanout"));
-                }
-                let delete_events = (events_per_second * active_ms as f64 / 1_000.0).ceil()
-                    * *routing_fanout as f64;
-                if !delete_events.is_finite() || delete_events > u64::MAX as f64 {
-                    return Err(AnalyticalCostError::Overflow);
-                }
-                let delete_events = delete_events as u64;
-                *cpu_ops += delete_events as f64
-                    * validated_operator_executions("summary_delete", operation)? as f64
-                    * validated_operator_cpu("summary_delete", operation.cpu_ops)?;
-                add_operator_io(io_bytes, operation, delete_events)?;
-                visit_ops(
-                    summary_input,
-                    seen,
-                    by_node,
-                    evidence,
-                    scope,
-                    evaluation_count,
-                    cpu_ops,
-                    io_bytes,
-                )?;
-            }
-            Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) => {
-                let operation = summary_operation_evidence(node, evidence)?.resource();
-                *cpu_ops += evaluation_count as f64
-                    * validated_operator_executions("summary_evaluation", operation)? as f64
-                    * validated_operator_cpu("summary_evaluation", operation.cpu_ops)?;
-                add_operator_io(io_bytes, operation, evaluation_count)?;
-                visit_ops(
-                    summary_input,
-                    seen,
-                    by_node,
-                    evidence,
-                    scope,
-                    evaluation_count,
-                    cpu_ops,
-                    io_bytes,
-                )?;
-            }
-            Operator::ASAP(ASAPOp::SummaryJoin { outer, inner, .. }) => {
-                let join = evidence
-                    .joins
-                    .get(&(node as *const _))
-                    .ok_or(AnalyticalCostError::MissingOrStale("summary_join"))?;
-                if !join.cpu_ops_per_execution.is_finite()
-                    || join.cpu_ops_per_execution <= 0.0
-                    || join.working_memory_bytes == 0
-                    || join.executions_per_evaluation == 0
-                {
-                    return Err(AnalyticalCostError::MissingOrStale("summary_join"));
-                }
-                *cpu_ops += evaluation_count as f64
-                    * join.executions_per_evaluation as f64
-                    * join.cpu_ops_per_execution;
-                let join_io = join
-                    .io_bytes_per_execution
-                    .ok_or(AnalyticalCostError::MissingOrStale("summary_join_io"))?;
-                *io_bytes = io_bytes
-                    .checked_add(
-                        join_io
-                            .checked_mul(join.executions_per_evaluation)
-                            .and_then(|bytes| bytes.checked_mul(evaluation_count))
-                            .ok_or(AnalyticalCostError::Overflow)?,
-                    )
-                    .ok_or(AnalyticalCostError::Overflow)?;
-                visit_ops(
-                    outer,
-                    seen,
-                    by_node,
-                    evidence,
-                    scope,
-                    evaluation_count,
-                    cpu_ops,
-                    io_bytes,
-                )?;
-                visit_ops(
-                    inner,
-                    seen,
-                    by_node,
-                    evidence,
-                    scope,
-                    evaluation_count,
-                    cpu_ops,
-                    io_bytes,
-                )?;
-            }
-            Operator::ASAP(ASAPOp::Extension { .. }) => {
-                return Err(AnalyticalCostError::UnsupportedCandidate);
-            }
-        }
-        Ok(())
-    }
-
-    let mut operator_io_bytes = 0;
-    visit_ops(
-        root,
-        &mut HashSet::new(),
-        &by_node,
-        evidence,
-        scope,
-        evaluation_count,
-        &mut cpu_ops,
-        &mut operator_io_bytes,
-    )?;
-    let transient_bytes = estimate_transient_liveness(root, evidence)?;
-    if !cpu_ops.is_finite() {
-        return Err(AnalyticalCostError::Overflow);
-    }
-    Ok(ResourceEstimate::new(
-        cpu_ops,
-        persistent_bytes
-            .checked_add(transient_bytes)
-            .and_then(|bytes| bytes.checked_add(ephemeral_state_bytes))
-            .ok_or(AnalyticalCostError::Overflow)?,
-        scans
-            .values()
-            .try_fold(operator_io_bytes, |sum, (_, bytes)| {
-                sum.checked_add(*bytes).ok_or(AnalyticalCostError::Overflow)
-            })?,
-    ))
-}
-
-fn add_operator_io(
-    total: &mut u64,
-    operation: &SummaryOperatorResourceEvidence,
-    execution_units: u64,
-) -> Result<(), AnalyticalCostError> {
-    let bytes = operation
-        .io_bytes_per_execution
-        .ok_or(AnalyticalCostError::MissingOrStale("summary operator io"))?;
-    if operation.executions_per_evaluation == 0 {
-        return Err(AnalyticalCostError::MissingOrStale(
-            "summary operator executions",
-        ));
-    }
-    *total = total
-        .checked_add(
-            bytes
-                .checked_mul(operation.executions_per_evaluation)
-                .and_then(|value| value.checked_mul(execution_units))
-                .ok_or(AnalyticalCostError::Overflow)?,
-        )
-        .ok_or(AnalyticalCostError::Overflow)?;
-    Ok(())
-}
-
-fn validate_summary_edges_and_physical_ids(
-    root: &OperatorNode,
-    evidence: &SummaryNodeEvidence,
-    frameworks_by_node: &HashMap<*const OperatorNode, &Option<SummaryWindowFramework>>,
-) -> Result<(), AnalyticalCostError> {
-    fn children<'a>(
-        node: &'a OperatorNode,
-        evidence: &SummaryNodeEvidence,
-    ) -> Vec<&'a OperatorNode> {
-        summary_children(node, evidence)
-    }
-    fn metadata(
-        node: &OperatorNode,
-        evidence: &SummaryNodeEvidence,
-    ) -> Result<(String, Vec<EdgeStatistics>, EdgeStatistics), AnalyticalCostError> {
-        if let Some(retained) = evidence.retained_queries.get(&(node as *const _)) {
-            if node.contains_asap() {
-                return Err(AnalyticalCostError::InvalidPhysicalDAG(
-                    "retained sub-DAG evidence covers summary operators",
-                ));
-            }
-            return Ok((retained.physical_id.clone(), vec![], retained.output));
-        }
-        match &node.operator {
-            Operator::ASAP(ASAPOp::SummaryAgg { .. }) => {
-                let value = evidence
-                    .aggregations
-                    .get(&(node as *const _))
-                    .ok_or(AnalyticalCostError::MissingOrStale("summary_agg"))?;
-                Ok((value.physical_id.clone(), vec![value.input], value.output))
-            }
-            Operator::ASAP(ASAPOp::SummaryJoin { .. }) => {
-                let value = evidence
-                    .joins
-                    .get(&(node as *const _))
-                    .ok_or(AnalyticalCostError::MissingOrStale("summary_join"))?;
-                Ok((
-                    value.physical_id.clone(),
-                    value.inputs.clone(),
-                    value.output,
-                ))
-            }
-            _ => {
-                let value = summary_operation_evidence(node, evidence)?.resource();
-                Ok((
-                    value.physical_id.clone(),
-                    value.inputs.clone(),
-                    value.output,
-                ))
-            }
-        }
-    }
-    fn visit(
-        node: &OperatorNode,
-        evidence: &SummaryNodeEvidence,
-        frameworks_by_node: &HashMap<*const OperatorNode, &Option<SummaryWindowFramework>>,
-        seen: &mut HashSet<*const OperatorNode>,
-        physical: &mut HashMap<String, (Vec<EdgeStatistics>, EdgeStatistics, String)>,
-    ) -> Result<EdgeStatistics, AnalyticalCostError> {
-        if !seen.insert(node as *const _) {
-            return metadata(node, evidence).map(|(_, _, output)| output);
-        }
-        let child_nodes = children(node, evidence);
-        let child_outputs = child_nodes
-            .iter()
-            .map(|child| visit(child, evidence, frameworks_by_node, seen, physical))
-            .collect::<Result<Vec<_>, _>>()?;
-        let child_physical_ids = child_nodes
-            .iter()
-            .map(|child| summary_physical_id(child, evidence))
-            .collect::<Result<Vec<_>, _>>()?;
-        let (id, inputs, output) = metadata(node, evidence)?;
-        let local_fingerprint = if has_retained_subdag_evidence(node, evidence) {
-            format!("{:?}", evidence.retained_queries.get(&(node as *const _)))
-        } else {
-            match &node.operator {
-                Operator::ASAP(ASAPOp::SummaryAgg { .. }) => {
-                    format!("{:?}", evidence.aggregations.get(&(node as *const _)))
-                }
-                Operator::ASAP(ASAPOp::SummaryJoin { .. }) => {
-                    format!("{:?}", evidence.joins.get(&(node as *const _)))
-                }
-                _ => format!("{:?}", evidence.operations.get(&(node as *const _))),
-            }
-        };
-        // A provider identity names the complete physical operator, including
-        // its inputs. Equal local widths/costs do not make operators consuming
-        // different physical children the same deployment.
-        let framework = frameworks_by_node.get(&(node as *const _));
-        let fingerprint = format!(
-            "logical={:?}|framework={framework:?}|{local_fingerprint}|children={child_physical_ids:?}",
-            node.operator
-        );
-        if id.is_empty()
-            || inputs != child_outputs
-            || !output.is_consistent()
-            || inputs.iter().any(|edge| !edge.is_consistent())
-        {
-            return Err(AnalyticalCostError::ComparisonScopeMismatch(
-                "summary physical edge statistics",
-            ));
-        }
-        match physical.entry(id) {
-            std::collections::hash_map::Entry::Vacant(entry) => {
-                entry.insert((inputs, output, fingerprint));
-            }
-            std::collections::hash_map::Entry::Occupied(entry)
-                if entry.get() != &(inputs, output, fingerprint) =>
-            {
-                return Err(AnalyticalCostError::ComparisonScopeMismatch(
-                    "summary physical identity",
-                ));
-            }
-            _ => {}
-        }
-        Ok(output)
-    }
-    visit(
-        root,
-        evidence,
-        frameworks_by_node,
-        &mut HashSet::new(),
-        &mut HashMap::new(),
-    )
-    .map(|_| ())
-}
-
-/// Whether `node` is a retained non-ASAP sub-DAG costed as one unit: the
-/// provider bound retained-query evidence to it instead of per-operator
-/// evidence. Its children are then not visited. No ASAP descendant may be
-/// hidden by this boundary; dag validation rejects such evidence.
-fn has_retained_subdag_evidence(node: &OperatorNode, evidence: &SummaryNodeEvidence) -> bool {
-    evidence.retained_queries.contains_key(&(node as *const _)) && !node.contains_asap()
-}
-
-/// The inputs the estimator visits below `node`: none for a retained
-/// sub-DAG, every direct input otherwise.
-fn summary_children<'a>(
-    node: &'a OperatorNode,
-    evidence: &SummaryNodeEvidence,
-) -> Vec<&'a OperatorNode> {
-    if has_retained_subdag_evidence(node, evidence) {
-        vec![]
-    } else {
-        node.children()
-            .into_iter()
-            .map(|child| child.as_ref())
-            .collect()
-    }
-}
-
-fn summary_physical_id(
-    node: &OperatorNode,
-    evidence: &SummaryNodeEvidence,
-) -> Result<String, AnalyticalCostError> {
-    if has_retained_subdag_evidence(node, evidence) {
-        return evidence
-            .retained_queries
-            .get(&(node as *const _))
-            .map(|value| value.physical_id.clone())
-            .ok_or(AnalyticalCostError::MissingOrStale(
-                "summary physical identity",
-            ));
-    }
-    match &node.operator {
-        Operator::ASAP(ASAPOp::SummaryAgg { .. }) => evidence
-            .aggregations
-            .get(&(node as *const _))
-            .map(|value| value.physical_id.clone()),
-        Operator::ASAP(ASAPOp::SummaryJoin { .. }) => evidence
-            .joins
-            .get(&(node as *const _))
-            .map(|value| value.physical_id.clone()),
-        _ => summary_operation_evidence(node, evidence)
-            .ok()
-            .map(|value| value.resource().physical_id.clone()),
-    }
-    .ok_or(AnalyticalCostError::MissingOrStale(
-        "summary physical identity",
-    ))
-}
-
-/// Simulate a deterministic child-before-parent physical schedule. Completed
-/// child output buffers remain live until their final consumer executes;
-/// operator workspace and its output buffer coexist during that execution.
-pub(super) fn estimate_transient_liveness(
-    root: &OperatorNode,
-    evidence: &SummaryNodeEvidence,
-) -> Result<u64, AnalyticalCostError> {
-    fn children<'a>(
-        node: &'a OperatorNode,
-        evidence: &SummaryNodeEvidence,
-    ) -> Vec<&'a OperatorNode> {
-        summary_children(node, evidence)
-    }
-    fn visit<'a>(
-        node: &'a OperatorNode,
-        evidence: &SummaryNodeEvidence,
-        seen: &mut HashSet<String>,
-        uses: &mut HashMap<String, usize>,
-        order: &mut Vec<&'a OperatorNode>,
-    ) -> Result<(), AnalyticalCostError> {
-        if !seen.insert(summary_physical_id(node, evidence)?) {
-            return Ok(());
-        }
-        for child in children(node, evidence) {
-            *uses
-                .entry(summary_physical_id(child, evidence)?)
-                .or_default() += 1;
-            visit(child, evidence, seen, uses, order)?;
-        }
-        order.push(node);
-        Ok(())
-    }
-    fn memory(
-        node: &OperatorNode,
-        evidence: &SummaryNodeEvidence,
-    ) -> Result<(u64, u64), AnalyticalCostError> {
-        if has_retained_subdag_evidence(node, evidence) {
-            return evidence
-                .retained_queries
-                .get(&(node as *const _))
-                .map(|value| (value.working_memory_bytes, value.output_buffer_bytes))
-                .ok_or(AnalyticalCostError::MissingOrStale("retain_exact"));
-        }
-        match &node.operator {
-            Operator::ASAP(ASAPOp::SummaryAgg { .. }) => Ok((0, 0)),
-            Operator::ASAP(ASAPOp::SummaryJoin { .. }) => evidence
-                .joins
-                .get(&(node as *const _))
-                .map(|value| (value.working_memory_bytes, value.output_buffer_bytes))
-                .ok_or(AnalyticalCostError::MissingOrStale("summary_join")),
-            _ => {
-                let value = summary_operation_evidence(node, evidence)?.resource();
-                Ok((value.working_memory_bytes, value.output_buffer_bytes))
-            }
-        }
-    }
-
-    let mut uses = HashMap::new();
-    let mut order = Vec::new();
-    visit(root, evidence, &mut HashSet::new(), &mut uses, &mut order)?;
-    let outputs: HashMap<_, _> = order
-        .iter()
-        .map(|node| {
-            memory(node, evidence)
-                .and_then(|(_, output)| summary_physical_id(node, evidence).map(|id| (id, output)))
-        })
-        .collect::<Result<_, _>>()?;
-    let mut live = 0_u64;
-    let mut peak = 0_u64;
-    for node in order {
-        let (workspace, output) = memory(node, evidence)?;
-        peak = peak.max(
-            live.checked_add(workspace)
-                .and_then(|bytes| bytes.checked_add(output))
-                .ok_or(AnalyticalCostError::Overflow)?,
-        );
-        live = live
-            .checked_add(output)
-            .ok_or(AnalyticalCostError::Overflow)?;
-        for child in children(node, evidence) {
-            let child_id = summary_physical_id(child, evidence)?;
-            let remaining =
-                uses.get_mut(&child_id)
-                    .ok_or(AnalyticalCostError::InvalidPhysicalDAG(
-                        "missing summary consumer count",
-                    ))?;
-            *remaining -= 1;
-            if *remaining == 0 {
-                live = live
-                    .checked_sub(outputs[&child_id])
-                    .ok_or(AnalyticalCostError::Overflow)?;
-            }
-        }
-    }
-    Ok(peak)
-}
-#[cfg(test)]
-pub(super) fn evidence_nodes(root: &OperatorNode) -> (Vec<&OperatorNode>, Vec<&OperatorNode>) {
-    fn visit<'a>(
-        node: &'a OperatorNode,
-        seen: &mut HashSet<*const OperatorNode>,
-        aggregations: &mut Vec<&'a OperatorNode>,
-        joins: &mut Vec<&'a OperatorNode>,
-    ) {
-        if !seen.insert(node as *const _) {
-            return;
-        }
-        match &node.operator {
-            Operator::ASAP(ASAPOp::SummaryAgg { .. }) => aggregations.push(node),
-            Operator::ASAP(ASAPOp::SummaryJoin { .. }) => joins.push(node),
-            _ => {}
-        }
-        for child in node.children() {
-            visit(child, seen, aggregations, joins);
-        }
-    }
-    let mut aggregations = Vec::new();
-    let mut joins = Vec::new();
-    visit(root, &mut HashSet::new(), &mut aggregations, &mut joins);
-    (aggregations, joins)
-}
-
-#[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
-#[cfg(test)]
-struct SummaryOperationCounts {
-    state_builds: u64,
-    merges_per_read: u64,
-    subtracts_per_read: u64,
-    deletes_per_update: u64,
-    evaluations_per_read: u64,
-    joins_per_read: u64,
-}
-
-/// Low-level diagnostic for a homogeneous deployment. Final planner ranking
-/// uses the per-node whole-DAG estimator above. Shared `Rc` nodes are visited
-/// once; explicit delete frequency comes from deletion evidence.
-#[cfg(test)]
-pub(super) fn estimate_incremental_summary_maintenance(
-    root: &OperatorNode,
-    guarantee: &SummaryMaintenanceLifecycleGuarantee,
-    inputs: SummaryMaintenanceInputs,
-    cpu: SummaryOperationCpuEvidence,
-    scope: &ComparisonScope,
-) -> Result<ResourceEstimate, AnalyticalCostError> {
-    estimate_incremental_summary_maintenance_with_join(root, guarantee, inputs, cpu, None, scope)
-}
-#[cfg(test)]
-pub(super) fn estimate_incremental_summary_maintenance_with_join(
-    root: &OperatorNode,
-    guarantee: &SummaryMaintenanceLifecycleGuarantee,
-    inputs: SummaryMaintenanceInputs,
-    cpu: SummaryOperationCpuEvidence,
-    join: Option<SummaryJoinEvidence>,
-    scope: &ComparisonScope,
-) -> Result<ResourceEstimate, AnalyticalCostError> {
-    let inputs = inputs.validate()?;
-    let evaluation_count = scope.validate()?;
-    validate_guarantee(guarantee, scope.data_arrival)?;
-    let (bootstrap_input_rows, arriving_input_rows, active_ms) =
-        lifecycle_row_counts(inputs, guarantee, scope)?;
-    let counts = count_operations(root)?;
-    if counts.state_builds == 0 {
-        return Err(AnalyticalCostError::UnsupportedCandidate);
-    }
-
-    let insert = required_cpu("insert_cpu_ops", cpu.insert_cpu_ops)?;
-    let merge = required_cpu_when(counts.merges_per_read, "merge_cpu_ops", cpu.merge_cpu_ops)?;
-    let subtract = required_cpu_when(
-        counts.subtracts_per_read,
-        "subtract_cpu_ops",
-        cpu.subtract_cpu_ops,
-    )?;
-    let delete = required_cpu_when(
-        counts.deletes_per_update,
-        "delete_cpu_ops",
-        cpu.delete_cpu_ops,
-    )?;
-    let delete_events = if counts.deletes_per_update == 0 {
-        0_u64
-    } else {
-        let rate = cpu
-            .delete_events_per_second
-            .filter(|rate| rate.is_finite() && *rate >= 0.0)
-            .ok_or(AnalyticalCostError::MissingOrStale(
-                "delete_events_per_second",
-            ))?;
-        let fanout = cpu
-            .delete_routing_fanout
-            .filter(|fanout| *fanout > 0)
-            .ok_or(AnalyticalCostError::MissingOrStale("delete_routing_fanout"))?;
-        let events = (rate * active_ms as f64 / 1_000.0).ceil();
-        if !events.is_finite() || events > u64::MAX as f64 {
-            return Err(AnalyticalCostError::Overflow);
-        }
-        (events as u64)
-            .checked_mul(fanout)
-            .ok_or(AnalyticalCostError::Overflow)?
-    };
-    let evaluation = required_cpu_when(
-        counts.evaluations_per_read,
-        "evaluation_cpu_ops",
-        cpu.evaluation_cpu_ops,
-    )?;
-    let join_cpu = match (counts.joins_per_read, join.as_ref()) {
-        (0, _) => 0.0,
-        (_, Some(evidence))
-            if evidence.cpu_ops_per_execution.is_finite()
-                && evidence.cpu_ops_per_execution > 0.0
-                && evidence.working_memory_bytes > 0 =>
-        {
-            evidence.cpu_ops_per_execution
-        }
-        (_, Some(evidence))
-            if !evidence.cpu_ops_per_execution.is_finite()
-                || evidence.cpu_ops_per_execution <= 0.0 =>
-        {
-            return Err(AnalyticalCostError::InvalidOperationCost(
-                "summary_join_cpu_ops_per_execution",
-                evidence.cpu_ops_per_execution,
-            ));
-        }
-        _ => return Err(AnalyticalCostError::MissingOrStale("summary_join")),
-    };
-
-    let build_inserts = bootstrap_input_rows
-        .checked_mul(inputs.bootstrap_window_count)
-        .ok_or(AnalyticalCostError::Overflow)?
-        .checked_mul(counts.state_builds)
-        .ok_or(AnalyticalCostError::Overflow)?;
-    let update_inserts = arriving_input_rows
-        .checked_mul(inputs.active_window_count)
-        .and_then(|n| n.checked_mul(counts.state_builds))
-        .ok_or(AnalyticalCostError::Overflow)?;
-    let instances = inputs.physical_summary_count as f64;
-    let evaluations = evaluation_count as f64;
-    let cpu_ops = (build_inserts as f64 + update_inserts as f64) * insert
-        + evaluations * counts.merges_per_read as f64 * instances * merge
-        + evaluations * counts.subtracts_per_read as f64 * instances * subtract
-        + delete_events as f64 * counts.deletes_per_update as f64 * delete
-        + evaluations * counts.evaluations_per_read as f64 * instances * evaluation
-        + evaluations * counts.joins_per_read as f64 * join_cpu;
-    if !cpu_ops.is_finite() {
-        return Err(AnalyticalCostError::Overflow);
-    }
-
-    let state_instances = inputs
-        .active_window_count
-        .checked_add(inputs.retained_window_count)
-        .and_then(|n| n.checked_mul(inputs.physical_summary_count))
-        .and_then(|n| n.checked_mul(counts.state_builds))
-        .ok_or(AnalyticalCostError::Overflow)?;
-    let retained_bytes = state_instances
-        .checked_mul(inputs.state_bytes_per_summary)
-        .ok_or(AnalyticalCostError::Overflow)?;
-    // Merge/subtract may stream over persistent inputs but still needs one
-    // result state per physical instance. Persistent retained windows are
-    // already included above and are not loaded a second time.
-    let transient_bytes = if counts.merges_per_read > 0 || counts.subtracts_per_read > 0 {
-        inputs
-            .physical_summary_count
-            .checked_mul(inputs.state_bytes_per_summary)
-            .ok_or(AnalyticalCostError::Overflow)?
-    } else {
-        0
-    };
-    let join_bytes = match (counts.joins_per_read, join.as_ref()) {
-        (0, _) => 0,
-        (_, Some(evidence)) => evidence.working_memory_bytes,
-        _ => return Err(AnalyticalCostError::MissingOrStale("summary_join")),
-    };
-    let bootstrap_row_buffer = if inputs.initial_input_rows == 0 {
-        0
-    } else {
-        inputs
-            .initial_input_bytes
-            .div_ceil(inputs.initial_input_rows)
-    };
-    Ok(ResourceEstimate::new(
-        cpu_ops,
-        retained_bytes
-            .checked_add(transient_bytes)
-            .and_then(|bytes| bytes.checked_add(join_bytes))
-            .ok_or(AnalyticalCostError::Overflow)?
-            .max(bootstrap_row_buffer),
-        inputs.initial_source_scan_bytes,
-    ))
-}
-
-pub(super) fn lifecycle_row_counts(
-    inputs: SummaryMaintenanceInputs,
-    guarantee: &SummaryMaintenanceLifecycleGuarantee,
-    scope: &ComparisonScope,
-) -> Result<(u64, u64, u64), AnalyticalCostError> {
-    validate_arrival_rate(scope.data_arrival, inputs.ingestion_rate_per_second)?;
-    let horizon_end = scope
-        .planning_time
-        .0
-        .checked_add(scope.horizon.0)
-        .ok_or(AnalyticalCostError::Overflow)?;
-    let (bootstrap_extra_ms, active_ms) = match guarantee.summary_maintenance_lifecycle {
-        SummaryMaintenanceLifecycle::Prepared {
-            activate_at,
-            retire_at,
-        } => {
-            if activate_at.0 >= retire_at.0 {
-                return Err(AnalyticalCostError::IncompatibleLifecycleGuarantee);
-            }
-            let covers_every_evaluation = evaluation_offsets_ms(scope)?.into_iter().all(|offset| {
-                scope
-                    .planning_time
-                    .0
-                    .checked_add(offset)
-                    .is_some_and(|at| at >= activate_at.0 && at < retire_at.0)
-            });
-            if !covers_every_evaluation {
-                return Err(AnalyticalCostError::IncompatibleLifecycleGuarantee);
-            }
-            let activation = activate_at.0.max(scope.planning_time.0).min(horizon_end);
-            let bootstrap_extra_ms = activation.saturating_sub(scope.planning_time.0);
-            let start = activation;
-            let end = retire_at.0.min(horizon_end);
-            (bootstrap_extra_ms, end.saturating_sub(start))
-        }
-        SummaryMaintenanceLifecycle::Shared { .. } => (0, scope.horizon.0),
-        SummaryMaintenanceLifecycle::ContinuouslyMaintained => (0, scope.horizon.0),
-        SummaryMaintenanceLifecycle::Ephemeral => {
-            return Err(AnalyticalCostError::IncompatibleLifecycleGuarantee)
-        }
-    };
-    let bootstrap_extra = inputs.ingestion_rate_per_second * bootstrap_extra_ms as f64 / 1000.0;
-    let updates = inputs.ingestion_rate_per_second * active_ms as f64 / 1000.0;
-    if !bootstrap_extra.is_finite()
-        || !updates.is_finite()
-        || bootstrap_extra > u64::MAX as f64
-        || updates > u64::MAX as f64
-    {
-        return Err(AnalyticalCostError::Overflow);
-    }
-    Ok((
-        inputs
-            .initial_input_rows
-            .checked_add(bootstrap_extra.ceil() as u64)
-            .ok_or(AnalyticalCostError::Overflow)?,
-        updates.ceil() as u64,
-        active_ms,
-    ))
-}
-
-fn validate_guarantee(
-    guarantee: &SummaryMaintenanceLifecycleGuarantee,
-    arrival: DataArrival,
-) -> Result<(), AnalyticalCostError> {
-    if guarantee.output_representation != asap_types::post_asap::OutputRepresentation::SummaryState
-        || guarantee.summary_maintenance_mode
-            != maintenance_mode(&guarantee.summary_maintenance_lifecycle, arrival)
-        || guarantee.evaluation_schedule
-            != evaluation_schedule(&guarantee.summary_maintenance_lifecycle, arrival)
-    {
-        return Err(AnalyticalCostError::IncompatibleLifecycleGuarantee);
-    }
-    Ok(())
-}
-
-#[cfg(test)]
-fn required_cpu(name: &'static str, value: Option<f64>) -> Result<f64, AnalyticalCostError> {
-    let value = value.ok_or(AnalyticalCostError::MissingOrStale(name))?;
-    if !value.is_finite() || value <= 0.0 {
-        return Err(AnalyticalCostError::InvalidOperationCost(name, value));
-    }
-    Ok(value)
-}
-
-pub(super) fn validated_operator_cpu(
-    name: &'static str,
-    value: f64,
-) -> Result<f64, AnalyticalCostError> {
-    if !value.is_finite() || value <= 0.0 {
-        Err(AnalyticalCostError::InvalidOperationCost(name, value))
-    } else {
-        Ok(value)
-    }
-}
-
-fn validated_operator_executions(
-    name: &'static str,
-    evidence: &SummaryOperatorResourceEvidence,
-) -> Result<u64, AnalyticalCostError> {
-    if evidence.executions_per_evaluation == 0 {
-        return Err(AnalyticalCostError::MissingOrZero(name));
-    }
-    Ok(evidence.executions_per_evaluation)
-}
-
-#[cfg(test)]
-fn required_cpu_when(
-    count: u64,
-    name: &'static str,
-    value: Option<f64>,
-) -> Result<f64, AnalyticalCostError> {
-    if count == 0 {
-        return Ok(0.0);
-    }
-    required_cpu(name, value)
-}
-
-#[cfg(test)]
-fn count_operations(root: &OperatorNode) -> Result<SummaryOperationCounts, AnalyticalCostError> {
-    fn visit(
-        node: &OperatorNode,
-        seen: &mut HashSet<*const OperatorNode>,
-        counts: &mut SummaryOperationCounts,
-    ) -> Result<(), AnalyticalCostError> {
-        if !seen.insert(node as *const OperatorNode) {
-            return Ok(());
-        }
-        match &node.operator {
-            Operator::ASAP(ASAPOp::SummaryAgg { .. }) => {
-                counts.state_builds = counts
-                    .state_builds
-                    .checked_add(1)
-                    .ok_or(AnalyticalCostError::Overflow)?;
-            }
-            Operator::ASAP(ASAPOp::SummaryMerge { children }) => {
-                if children.is_empty() {
-                    return Err(AnalyticalCostError::InvalidPhysicalDAG(
-                        "summary merge has no children",
-                    ));
-                }
-                counts.merges_per_read = counts
-                    .merges_per_read
-                    .checked_add(children.len().saturating_sub(1) as u64)
-                    .ok_or(AnalyticalCostError::Overflow)?;
-            }
-            Operator::ASAP(ASAPOp::SummarySubtract { .. }) => {
-                counts.subtracts_per_read = counts
-                    .subtracts_per_read
-                    .checked_add(1)
-                    .ok_or(AnalyticalCostError::Overflow)?;
-            }
-            Operator::ASAP(ASAPOp::SummaryDelete { .. }) => {
-                counts.deletes_per_update = counts
-                    .deletes_per_update
-                    .checked_add(1)
-                    .ok_or(AnalyticalCostError::Overflow)?;
-            }
-            Operator::ASAP(
-                ASAPOp::SummaryEstimate { .. } | ASAPOp::FinalizeExactAccumulator { .. },
-            ) => {
-                counts.evaluations_per_read = counts
-                    .evaluations_per_read
-                    .checked_add(1)
-                    .ok_or(AnalyticalCostError::Overflow)?;
-            }
-            Operator::ASAP(ASAPOp::SummaryJoin { .. }) => {
-                counts.joins_per_read = counts
-                    .joins_per_read
-                    .checked_add(1)
-                    .ok_or(AnalyticalCostError::Overflow)?;
-            }
-            // Retained relational work, accumulator/population boundaries and
-            // exact query-time operators add no summary operation.
-            Operator::NonASAP(_)
-            | Operator::ASAP(
-                ASAPOp::MaintainPopulation { .. }
-                | ASAPOp::EvaluatePopulation { .. }
-                | ASAPOp::Extension { .. },
-            ) => {}
-        }
-        for child in node.children() {
-            visit(child, seen, counts)?;
-        }
-        Ok(())
-    }
-
-    let mut counts = SummaryOperationCounts::default();
-    visit(root, &mut HashSet::new(), &mut counts)?;
-    Ok(counts)
-}
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_cost/evidence.rs b/crates/asap-aware-mapping/src/summary_maintenance_cost/evidence.rs
deleted file mode 100644
index 6ae5999bd..000000000
--- a/crates/asap-aware-mapping/src/summary_maintenance_cost/evidence.rs
+++ /dev/null
@@ -1,386 +0,0 @@
-use super::*;
-
-/// Physical evidence that is not represented by [`DataWorkload`] for one
-/// summary deployment. Window counts describe the
-/// already-selected physical deployment; this layer does not define another
-/// tumbling/sliding policy enum.
-#[derive(Debug, Clone, Copy, PartialEq, Serialize, Deserialize)]
-pub struct SummaryPhysicalInputEvidence {
-    /// Logical bytes in the snapshot used to bootstrap the state.
-    pub initial_input_bytes: u64,
-    /// Source bytes read while bootstrapping. Arriving stream bytes are not a
-    /// disk scan and are therefore excluded.
-    pub initial_source_scan_bytes: u64,
-    /// Simultaneously open windows receiving each arriving item.
-    pub active_window_count: u64,
-    /// Window/state partitions receiving each bootstrap row.
-    pub bootstrap_window_count: u64,
-    /// Completed windows retained for query coverage.
-    pub retained_window_count: u64,
-    /// Independent state instances per window: one for shared
-    /// multi-subpopulation state, otherwise the resolved group count.
-    pub physical_summary_count: u64,
-    /// Resident bytes of one concrete state instance.
-    pub state_bytes_per_summary: u64,
-}
-
-/// Workload-normalized inputs for summary construction and maintenance over one finite
-/// comparison horizon.
-#[derive(Debug, Clone, Copy, PartialEq, Serialize, Deserialize)]
-pub struct SummaryMaintenanceInputs {
-    pub initial_input_rows: u64,
-    pub initial_input_bytes: u64,
-    pub initial_source_scan_bytes: u64,
-    pub ingestion_rate_per_second: f64,
-    pub active_window_count: u64,
-    pub bootstrap_window_count: u64,
-    pub retained_window_count: u64,
-    pub physical_summary_count: u64,
-    pub state_bytes_per_summary: u64,
-}
-
-impl SummaryMaintenanceInputs {
-    /// Resolve snapshot size, arriving rows, and reads from the canonical
-    /// workload. Positive fractional expected work rounds up conservatively.
-    ///
-    /// `AtRest` needs snapshot cardinality and implies zero arrivals; continuous
-    /// ingestion additionally requires fresh rate evidence.
-    /// `Mixed` fails closed because today's workload schema cannot distinguish
-    /// its at-rest backlog from its continuing-arrival cardinality.
-    pub fn from_workload(
-        physical: SummaryPhysicalInputEvidence,
-        data: &DataWorkload,
-        scope: &ComparisonScope,
-    ) -> Result<Self, AnalyticalCostError> {
-        let _ = scope.validate()?;
-        if scope.data_arrival != data.arrival {
-            return Err(AnalyticalCostError::ComparisonScopeMismatch("data arrival"));
-        }
-        let initial_input_rows = data
-            .input_cardinality
-            .value_at(scope.planning_time.0)
-            .copied()
-            .ok_or(AnalyticalCostError::MissingOrStale("input_cardinality"))?;
-        let ingestion_rate = match data.arrival {
-            DataArrival::AtRest => {
-                // A declared snapshot has no arrivals. Reject contradictory fresh
-                // evidence rather than silently pricing the wrong workload.
-                if let Some(rate) = data.ingestion_rate.value_at(scope.planning_time.0) {
-                    validate_arrival_rate(data.arrival, rate.0)?;
-                }
-                0.0
-            }
-            DataArrival::ContinuouslyIngesting => {
-                data.ingestion_rate
-                    .value_at(scope.planning_time.0)
-                    .copied()
-                    .ok_or(AnalyticalCostError::MissingOrStale("ingestion_rate"))?
-                    .0
-            }
-            arrival => return Err(AnalyticalCostError::UnsupportedDataArrival(arrival)),
-        };
-        validate_arrival_rate(data.arrival, ingestion_rate)?;
-        Self {
-            initial_input_rows,
-            initial_input_bytes: physical.initial_input_bytes,
-            initial_source_scan_bytes: physical.initial_source_scan_bytes,
-            ingestion_rate_per_second: ingestion_rate,
-            active_window_count: physical.active_window_count,
-            bootstrap_window_count: physical.bootstrap_window_count,
-            retained_window_count: physical.retained_window_count,
-            physical_summary_count: physical.physical_summary_count,
-            state_bytes_per_summary: physical.state_bytes_per_summary,
-        }
-        .validate()
-    }
-
-    pub fn validate(self) -> Result<Self, AnalyticalCostError> {
-        for (name, value) in [
-            ("active_window_count", self.active_window_count),
-            ("bootstrap_window_count", self.bootstrap_window_count),
-            ("physical_summary_count", self.physical_summary_count),
-            ("state_bytes_per_summary", self.state_bytes_per_summary),
-        ] {
-            if value == 0 {
-                return Err(AnalyticalCostError::MissingOrZero(name));
-            }
-        }
-        if (self.initial_input_rows == 0) != (self.initial_input_bytes == 0)
-            || (self.initial_input_rows == 0 && self.initial_source_scan_bytes != 0)
-        {
-            return Err(AnalyticalCostError::InconsistentBootstrapEvidence);
-        }
-        if !self.ingestion_rate_per_second.is_finite() || self.ingestion_rate_per_second < 0.0 {
-            return Err(AnalyticalCostError::InvalidIngestionRate(
-                self.ingestion_rate_per_second,
-            ));
-        }
-        Ok(self)
-    }
-}
-
-/// CPU operations for one concrete state operation on one state instance.
-/// Missing evidence is legal only when the selected summary DAG does not use
-/// that operation.
-#[cfg(test)]
-#[derive(Debug, Clone, Copy, Default, PartialEq, Serialize, Deserialize)]
-pub struct SummaryOperationCpuEvidence {
-    pub insert_cpu_ops: Option<f64>,
-    pub merge_cpu_ops: Option<f64>,
-    pub subtract_cpu_ops: Option<f64>,
-    pub delete_cpu_ops: Option<f64>,
-    /// Expirations/retractions routed to this DAG per second. Required only
-    /// when an explicit `SummaryDelete` is present.
-    pub delete_events_per_second: Option<f64>,
-    /// Concrete state instances touched by one delete event.
-    pub delete_routing_fanout: Option<u64>,
-    pub evaluation_cpu_ops: Option<f64>,
-}
-
-/// Physical evidence for one `SummaryJoin` implementation. Total work,
-/// cardinality, and memory cannot be inferred from the logical join key alone.
-#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
-pub struct SummaryJoinEvidence {
-    pub physical_id: String,
-    pub inputs: Vec<EdgeStatistics>,
-    pub output: EdgeStatistics,
-    /// Total build, probe, match-production, and output CPU for one complete
-    /// execution of the selected physical join algorithm.
-    pub cpu_ops_per_execution: f64,
-    pub working_memory_bytes: u64,
-    pub output_buffer_bytes: u64,
-    pub executions_per_evaluation: u64,
-    pub io_bytes_per_execution: Option<u64>,
-}
-
-#[derive(Debug, Clone, PartialEq)]
-pub struct SummaryAggregateEvidence {
-    pub physical_id: String,
-    pub input: EdgeStatistics,
-    pub output: EdgeStatistics,
-    /// Index into `ComparisonScope.sources` when this state bootstraps directly
-    /// from storage. `None` means its input is an already-materialized child
-    /// edge and therefore has no additional source read.
-    pub scan_selection_index: Option<usize>,
-    /// Provider-owned identity of the physical bootstrap read. Equal source
-    /// coverage alone does not prove two independent builds share I/O.
-    pub bootstrap_read_identity: String,
-    pub inputs: SummaryMaintenanceInputs,
-    /// CPU operations to insert one routed row into one state instance.
-    pub insert_cpu_ops: f64,
-}
-
-#[derive(Debug, Clone, PartialEq)]
-pub struct SummaryOperatorResourceEvidence {
-    pub physical_id: String,
-    pub inputs: Vec<EdgeStatistics>,
-    pub output: EdgeStatistics,
-    pub cpu_ops: f64,
-    pub working_memory_bytes: u64,
-    pub output_buffer_bytes: u64,
-    /// Executions of this physical operator for one query evaluation.
-    /// This is provider evidence, not inferred from a descendant state.
-    pub executions_per_evaluation: u64,
-    pub io_bytes_per_execution: Option<u64>,
-}
-
-/// Evidence is structured by logical summary operation so delete-only facts
-/// cannot be attached to merge, subtract, or evaluation nodes.
-#[derive(Debug, Clone, PartialEq)]
-pub enum SummaryOperatorEvidence {
-    /// Exact query-time arithmetic over two independently realized operands.
-    Binary(SummaryOperatorResourceEvidence),
-    /// Query-time or maintenance-time plain-value work. For `Sort`/`Limit`,
-    /// providers report the actual comparison/heap work and working set here;
-    /// the estimator charges it at query multiplicity.
-    ValueOperation(SummaryOperatorResourceEvidence),
-    Merge(SummaryOperatorResourceEvidence),
-    Subtract(SummaryOperatorResourceEvidence),
-    Delete {
-        resource: SummaryOperatorResourceEvidence,
-        events_per_second: f64,
-        routing_fanout: u64,
-    },
-    Evaluation(SummaryOperatorResourceEvidence),
-}
-
-impl SummaryOperatorEvidence {
-    pub(super) fn resource(&self) -> &SummaryOperatorResourceEvidence {
-        match self {
-            Self::Binary(resource)
-            | Self::ValueOperation(resource)
-            | Self::Merge(resource)
-            | Self::Subtract(resource)
-            | Self::Delete { resource, .. }
-            | Self::Evaluation(resource) => resource,
-        }
-    }
-
-    #[cfg(test)]
-    pub(super) fn resource_mut(&mut self) -> &mut SummaryOperatorResourceEvidence {
-        match self {
-            Self::Binary(resource)
-            | Self::ValueOperation(resource)
-            | Self::Merge(resource)
-            | Self::Subtract(resource)
-            | Self::Delete { resource, .. }
-            | Self::Evaluation(resource) => resource,
-        }
-    }
-}
-
-/// Non-aggregation work for a retained pre-ASAP sub-DAG over the comparison
-/// horizon. Bootstrap/source I/O belongs exclusively to the owning aggregate,
-/// and summary insertion belongs exclusively to its insert evidence.
-#[derive(Debug, Clone, PartialEq)]
-pub struct RetainedSubDAGEvidence {
-    pub physical_id: String,
-    /// Logical output edge consumed by the parent summary operator.
-    pub output: EdgeStatistics,
-    pub preprocessing_cpu_ops_over_horizon: f64,
-    /// Execution workspace, excluding the separately declared output buffer.
-    pub working_memory_bytes: u64,
-    pub output_buffer_bytes: u64,
-}
-
-/// Physical evidence bound to the selected DAG's `Rc` identity. A copied,
-/// structurally equal node is not silently treated as the same deployment.
-#[derive(Debug, Clone, Default)]
-pub struct SummaryNodeEvidence {
-    pub(super) aggregations: HashMap<*const OperatorNode, SummaryAggregateEvidence>,
-    pub(super) joins: HashMap<*const OperatorNode, SummaryJoinEvidence>,
-    pub(super) operations: HashMap<*const OperatorNode, SummaryOperatorEvidence>,
-    pub(super) operation_state_owners: HashMap<*const OperatorNode, *const OperatorNode>,
-    pub(super) retained_queries: HashMap<*const OperatorNode, RetainedSubDAGEvidence>,
-}
-
-impl SummaryNodeEvidence {
-    pub fn insert_aggregation(
-        &mut self,
-        node: &Rc<OperatorNode>,
-        evidence: SummaryAggregateEvidence,
-    ) {
-        self.aggregations.insert(Rc::as_ptr(node), evidence);
-    }
-
-    pub fn insert_join(&mut self, node: &Rc<OperatorNode>, evidence: SummaryJoinEvidence) {
-        self.joins.insert(Rc::as_ptr(node), evidence);
-    }
-
-    pub fn insert_operation(&mut self, node: &Rc<OperatorNode>, evidence: SummaryOperatorEvidence) {
-        self.operations.insert(Rc::as_ptr(node), evidence);
-    }
-
-    /// Bind a stateful operation (currently `SummaryDelete`) to the exact
-    /// aggregation deployment whose active interval it follows.
-    pub fn insert_state_operation(
-        &mut self,
-        node: &Rc<OperatorNode>,
-        state: &Rc<OperatorNode>,
-        evidence: SummaryOperatorEvidence,
-    ) {
-        self.operations.insert(Rc::as_ptr(node), evidence);
-        self.operation_state_owners
-            .insert(Rc::as_ptr(node), Rc::as_ptr(state));
-    }
-
-    pub fn insert_retained_query(
-        &mut self,
-        node: &Rc<OperatorNode>,
-        evidence: RetainedSubDAGEvidence,
-    ) {
-        self.retained_queries.insert(Rc::as_ptr(node), evidence);
-    }
-
-    pub(super) fn aggregation(&self, node: &OperatorNode) -> Option<SummaryAggregateEvidence> {
-        self.aggregations.get(&(node as *const _)).cloned()
-    }
-}
-
-pub(super) fn summary_operation_evidence<'a>(
-    node: &OperatorNode,
-    evidence: &'a SummaryNodeEvidence,
-) -> Result<&'a SummaryOperatorEvidence, AnalyticalCostError> {
-    let operation = evidence
-        .operations
-        .get(&(node as *const _))
-        .ok_or(AnalyticalCostError::MissingOrStale("summary operation"))?;
-    // A binary operator or join over two inputs is `Binary` evidence; every
-    // other non-ASAP operator, and the accumulator/population boundaries,
-    // is a `ValueOperation`.
-    let matches = match (&node.operator, operation) {
-        (
-            Operator::NonASAP(NonASAPOp::BinaryOp { .. } | NonASAPOp::Join { .. }),
-            SummaryOperatorEvidence::Binary(_),
-        ) => true,
-        (Operator::NonASAP(NonASAPOp::BinaryOp { .. } | NonASAPOp::Join { .. }), _) => false,
-        (
-            Operator::NonASAP(_)
-            | Operator::ASAP(
-                ASAPOp::FinalizeExactAccumulator { .. }
-                | ASAPOp::MaintainPopulation { .. }
-                | ASAPOp::EvaluatePopulation { .. },
-            ),
-            SummaryOperatorEvidence::ValueOperation(_),
-        ) => true,
-        (Operator::ASAP(ASAPOp::SummaryMerge { .. }), SummaryOperatorEvidence::Merge(_))
-        | (Operator::ASAP(ASAPOp::SummarySubtract { .. }), SummaryOperatorEvidence::Subtract(_))
-        | (Operator::ASAP(ASAPOp::SummaryDelete { .. }), SummaryOperatorEvidence::Delete { .. })
-        | (
-            Operator::ASAP(ASAPOp::SummaryEstimate { .. }),
-            SummaryOperatorEvidence::Evaluation(_),
-        ) => true,
-        _ => false,
-    };
-    if matches {
-        Ok(operation)
-    } else {
-        Err(AnalyticalCostError::InconsistentOperatorStatistics(
-            "summary operation evidence kind does not match the operator",
-        ))
-    }
-}
-
-/// Evidence for recomputing the raw target over the full comparison horizon.
-/// Planning-time dimensions describe the initial snapshot. Each scheduled
-/// evaluation adds arrivals since planning time; `physical_dag` is therefore
-/// a once-counted DAG whose edge statistics already aggregate all evaluations.
-#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
-pub struct RawInputEvidence {
-    pub planning_time_input_rows: u64,
-    pub planning_time_input_bytes: u64,
-    pub planning_time_source_scan_bytes: u64,
-    /// Decoded logical bytes added to operator edges by one arriving row.
-    pub arriving_logical_row_bytes: u64,
-    /// Physical storage bytes read for one arriving row. Kept separate from
-    /// logical width so compression and encoding are not silently conflated.
-    pub arriving_source_row_bytes: u64,
-    pub ingestion_rate_per_second: f64,
-    pub physical_dag: EvidenceBackedPhysicalDAG,
-}
-
-/// One complete provider-enumerated physical implementation of the selected
-/// summary DAG. The identifier is stable provenance; concrete
-/// framework selection is performed by ranking these complete alternatives.
-#[derive(Debug, Clone)]
-pub struct SummaryPhysicalPlanAlternative {
-    pub physical_plan_id: String,
-    pub node_evidence: SummaryNodeEvidence,
-}
-
-/// Apply arrival semantics to both workload-derived and directly bound evidence.
-pub(super) fn validate_arrival_rate(
-    arrival: DataArrival,
-    rate: f64,
-) -> Result<(), AnalyticalCostError> {
-    if !rate.is_finite() || rate < 0.0 {
-        return Err(AnalyticalCostError::InvalidIngestionRate(rate));
-    }
-    match arrival {
-        DataArrival::AtRest if rate != 0.0 => Err(AnalyticalCostError::ComparisonScopeMismatch(
-            "at-rest ingestion rate",
-        )),
-        DataArrival::AtRest | DataArrival::ContinuouslyIngesting => Ok(()),
-        other => Err(AnalyticalCostError::UnsupportedDataArrival(other)),
-    }
-}
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_cost/mod.rs b/crates/asap-aware-mapping/src/summary_maintenance_cost/mod.rs
deleted file mode 100644
index ff4c69c1d..000000000
--- a/crates/asap-aware-mapping/src/summary_maintenance_cost/mod.rs
+++ /dev/null
@@ -1,51 +0,0 @@
-//! Analytical resource cost for at-rest and at-rest and incrementally maintained summary deployments.
-//!
-//! The canonical workload and lifecycle types own deployment semantics. This
-//! module only adds physical evidence absent from those schemas: state size,
-//! window counts, and per-operation CPU measurements or complexity estimates.
-
-use std::collections::{HashMap, HashSet};
-use std::rc::Rc;
-
-use asap_types::ir::{ASAPOp, NonASAPOp, Operator, OperatorNode, Predicate};
-use asap_types::post_asap::{
-    BoundExpr, ErrorMetric, ExactKind, FieldDataType, GuaranteeSource, ProbabilityExpr,
-    ResultGuarantee, SketchAlgorithm, SummaryMaintenanceLifecycle,
-    SummaryMaintenanceLifecycleGuarantee, SummaryWindowFramework,
-};
-use asap_types::pre_asap::{agg_intent::AggIntent, CompareOpKind, InfoMatcher, Source};
-use asap_types::types::AccuracyTarget;
-use asap_types::workload::{DataArrival, DataWorkload, QueryRecurrence, RepeatedDemand};
-use serde::{Deserialize, Serialize};
-
-use crate::accuracy::{AccuracyModel, DefaultAccuracyModel};
-use crate::analytical_cost::ExecutionMultiplicity;
-#[cfg(test)]
-use crate::analytical_cost::PhysicalNodeEvidence;
-use crate::analytical_cost::{
-    estimate_physical_dag, AnalyticalCostError, EvidenceBackedPhysicalDAG, PhysicalDAGNode,
-    PhysicalOperator, ResourceCalibration, ResourceEstimate,
-};
-use crate::cost_model::{
-    CompleteSummaryCandidateEstimate, Cost, CostModel, CostedSummaryDeployment, DefaultCostModel,
-};
-#[cfg(test)]
-use crate::physical_operator_statistics::UnaryEdgeStatistics;
-use crate::physical_operator_statistics::{ComparisonScope, EdgeStatistics, OperatorStatistics};
-use crate::recurrence::CostRate;
-use crate::replacement::{Replacement, ReplacementSubDAG, TargetSubDAG};
-use crate::summary_maintenance_lifecycle::{
-    evaluation_schedule, maintenance_mode, SummaryMaintenanceCapabilities,
-    SummaryMaintenanceLifecycleCostInputs,
-};
-
-pub const SUMMARY_MAINTENANCE_COST_MODEL_VERSION: &str = "summary-maintenance-resource-v2";
-
-mod estimator;
-mod evidence;
-mod model;
-mod window;
-
-pub use evidence::*;
-pub use model::*;
-pub use window::*;
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_cost/model.rs b/crates/asap-aware-mapping/src/summary_maintenance_cost/model.rs
deleted file mode 100644
index 8d9c2886a..000000000
--- a/crates/asap-aware-mapping/src/summary_maintenance_cost/model.rs
+++ /dev/null
@@ -1,3664 +0,0 @@
-use super::*;
-/// Adapter that supplies the existing lifecycle planner with analytical
-/// summary costs across at-rest and continuously ingesting workloads. The
-/// planner's existing lifecycle enums and legality checks remain authoritative.
-#[derive(Debug, Clone)]
-pub struct SummaryMaintenanceCostModel {
-    pub node_evidence: SummaryNodeEvidence,
-    pub calibration: ResourceCalibration,
-    pub capabilities: SummaryMaintenanceCapabilities,
-    target_comparisons: HashMap<*const OperatorNode, SummaryTargetComparison>,
-    candidate_comparisons: HashMap<CandidateComparisonKey, BoundCandidateIdentity>,
-    physical_plan_alternatives:
-        HashMap<CandidateComparisonKey, Vec<SummaryPhysicalPlanAlternative>>,
-    window_framework_candidates:
-        HashMap<CandidateComparisonKey, Vec<SummaryWindowFrameworkCandidate>>,
-}
-
-type CandidateComparisonKey = (*const OperatorNode, *const OperatorNode);
-
-#[derive(Debug, Clone)]
-struct BoundCandidateIdentity {
-    _target: Rc<OperatorNode>,
-    _root: Rc<OperatorNode>,
-}
-
-#[derive(Debug, Clone)]
-struct SummaryTargetComparison {
-    _target: Rc<OperatorNode>,
-    scope: ComparisonScope,
-    raw: RawInputEvidence,
-}
-
-pub(super) type LogicalSourceSelection = (Source, Vec<Predicate>, Vec<InfoMatcher>);
-
-pub(super) fn deduplicate_source_selections(
-    values: Vec<LogicalSourceSelection>,
-) -> Vec<LogicalSourceSelection> {
-    values.into_iter().fold(Vec::new(), |mut unique, value| {
-        if !unique.contains(&value) {
-            unique.push(value);
-        }
-        unique
-    })
-}
-
-fn info_source(selector: &[InfoMatcher]) -> Result<Source, AnalyticalCostError> {
-    let mut metric: Option<&str> = None;
-    for matcher in selector
-        .iter()
-        .filter(|matcher| matcher.label == "__name__")
-    {
-        if matcher.op != CompareOpKind::Eq || metric.is_some_and(|value| value != matcher.value) {
-            return Err(AnalyticalCostError::UnsupportedQueryOperator);
-        }
-        metric = Some(&matcher.value);
-    }
-    Ok(Source::TimeSeries {
-        metric: metric.unwrap_or("target_info").into(),
-    })
-}
-
-/// Collect the source selections (scan sources with their predicates, and
-/// info-metric selectors) of every leaf reachable from `node`, visiting a
-/// shared node once.
-pub(super) fn query_source_selections(
-    node: &OperatorNode,
-    seen: &mut HashSet<*const OperatorNode>,
-    out: &mut Vec<LogicalSourceSelection>,
-) -> Result<(), AnalyticalCostError> {
-    if !seen.insert(node as *const _) {
-        return Ok(());
-    }
-    match &node.operator {
-        Operator::NonASAP(NonASAPOp::Scan {
-            source, predicates, ..
-        }) => out.push((source.clone(), predicates.clone(), vec![])),
-        Operator::NonASAP(NonASAPOp::PromqlInfoEnrich { selector, child }) => {
-            query_source_selections(child, seen, out)?;
-            out.push((info_source(selector)?, vec![], selector.clone()));
-        }
-        _ => {
-            for child in node.children() {
-                query_source_selections(child, seen, out)?;
-            }
-        }
-    }
-    Ok(())
-}
-
-fn validate_query_scope(
-    target: &OperatorNode,
-    scope: &ComparisonScope,
-) -> Result<(), AnalyticalCostError> {
-    let mut actual = Vec::new();
-    query_source_selections(target, &mut HashSet::new(), &mut actual)?;
-    let actual = deduplicate_source_selections(actual);
-    let mut declared: Vec<_> = scope
-        .sources
-        .iter()
-        .map(|coverage| {
-            (
-                coverage.source.clone(),
-                coverage.predicates.clone(),
-                coverage.info_matchers.clone(),
-            )
-        })
-        .collect();
-    for selection in actual {
-        let Some(index) = declared.iter().position(|value| value == &selection) else {
-            return Err(AnalyticalCostError::ComparisonScopeMismatch(
-                "raw target source lineage",
-            ));
-        };
-        declared.swap_remove(index);
-    }
-    if !declared.is_empty() {
-        return Err(AnalyticalCostError::ComparisonScopeMismatch(
-            "raw target source lineage",
-        ));
-    }
-    Ok(())
-}
-
-fn validate_physical_scope_coverage(
-    physical: &EvidenceBackedPhysicalDAG,
-    scope: &ComparisonScope,
-) -> Result<(), AnalyticalCostError> {
-    let nodes = reachable_physical_nodes(physical)?;
-    let mut covered = HashSet::new();
-    for node in nodes
-        .into_iter()
-        .filter(|node| node.operator == PhysicalOperator::Scan)
-    {
-        let coverage = node
-            .scan_selection
-            .as_ref()
-            .ok_or_else(|| AnalyticalCostError::MissingScanSelection(node.id.clone()))?;
-        let Some(index) = scope.sources.iter().position(|value| value == coverage) else {
-            return Err(AnalyticalCostError::ComparisonScopeMismatch(
-                "physical scan selection",
-            ));
-        };
-        covered.insert(index);
-    }
-    if covered.len() != scope.sources.len() {
-        return Err(AnalyticalCostError::ComparisonScopeMismatch(
-            "physical scan selection",
-        ));
-    }
-    Ok(())
-}
-
-fn reachable_physical_nodes(
-    physical: &EvidenceBackedPhysicalDAG,
-) -> Result<Vec<&PhysicalDAGNode>, AnalyticalCostError> {
-    let by_id: HashMap<_, _> = physical
-        .nodes
-        .iter()
-        .map(|node| (node.id.as_str(), node))
-        .collect();
-    if by_id.len() != physical.nodes.len() {
-        return Err(AnalyticalCostError::InvalidPhysicalDAG("duplicate node id"));
-    }
-    fn visit<'a>(
-        id: &'a str,
-        by_id: &HashMap<&'a str, &'a PhysicalDAGNode>,
-        visiting: &mut HashSet<&'a str>,
-        visited: &mut HashSet<&'a str>,
-        nodes: &mut Vec<&'a PhysicalDAGNode>,
-    ) -> Result<(), AnalyticalCostError> {
-        if visited.contains(id) {
-            return Ok(());
-        }
-        if !visiting.insert(id) {
-            return Err(AnalyticalCostError::InvalidPhysicalDAG("cycle"));
-        }
-        let node = by_id
-            .get(id)
-            .copied()
-            .ok_or(AnalyticalCostError::InvalidPhysicalDAG("missing node"))?;
-        for child in &node.children {
-            visit(child, by_id, visiting, visited, nodes)?;
-        }
-        visiting.remove(id);
-        visited.insert(id);
-        nodes.push(node);
-        Ok(())
-    }
-    let mut nodes = Vec::new();
-    visit(
-        physical.root.as_str(),
-        &by_id,
-        &mut HashSet::new(),
-        &mut HashSet::new(),
-        &mut nodes,
-    )?;
-    Ok(nodes)
-}
-
-fn validate_raw_snapshot_dimensions(
-    raw: &RawInputEvidence,
-    scope: &ComparisonScope,
-) -> Result<(), AnalyticalCostError> {
-    validate_arrival_rate(scope.data_arrival, raw.ingestion_rate_per_second)?;
-    if scope.sources.len() != 1 {
-        return Err(AnalyticalCostError::MissingComparisonScope(
-            "single-source raw evolution",
-        ));
-    }
-    if !raw.ingestion_rate_per_second.is_finite() || raw.ingestion_rate_per_second < 0.0 {
-        return Err(AnalyticalCostError::InvalidIngestionRate(
-            raw.ingestion_rate_per_second,
-        ));
-    }
-    let bootstrap_is_consistent = if raw.planning_time_input_rows == 0 {
-        raw.planning_time_input_bytes == 0 && raw.planning_time_source_scan_bytes == 0
-    } else {
-        raw.planning_time_input_bytes > 0 && raw.planning_time_source_scan_bytes > 0
-    };
-    if !bootstrap_is_consistent
-        || (raw.ingestion_rate_per_second > 0.0
-            && (raw.arriving_logical_row_bytes == 0 || raw.arriving_source_row_bytes == 0))
-    {
-        return Err(AnalyticalCostError::InconsistentBootstrapEvidence);
-    }
-    let mut rows = 0_u64;
-    let mut bytes = 0_u64;
-    let mut scan = 0_u64;
-    for offset in evaluation_offsets_ms(scope)? {
-        let arrivals = (raw.ingestion_rate_per_second * offset as f64 / 1_000.0).ceil();
-        if !arrivals.is_finite() || arrivals < 0.0 || arrivals > u64::MAX as f64 {
-            return Err(AnalyticalCostError::Overflow);
-        }
-        let arrivals = arrivals as u64;
-        rows = rows
-            .checked_add(raw.planning_time_input_rows)
-            .and_then(|value| value.checked_add(arrivals))
-            .ok_or(AnalyticalCostError::Overflow)?;
-        bytes = bytes
-            .checked_add(raw.planning_time_input_bytes)
-            .and_then(|value| {
-                arrivals
-                    .checked_mul(raw.arriving_logical_row_bytes)
-                    .and_then(|arriving| value.checked_add(arriving))
-            })
-            .ok_or(AnalyticalCostError::Overflow)?;
-        scan = scan
-            .checked_add(raw.planning_time_source_scan_bytes)
-            .and_then(|value| {
-                arrivals
-                    .checked_mul(raw.arriving_source_row_bytes)
-                    .and_then(|arriving| value.checked_add(arriving))
-            })
-            .ok_or(AnalyticalCostError::Overflow)?;
-    }
-    let reachable = reachable_physical_nodes(&raw.physical_dag)?;
-    if reachable
-        .iter()
-        .any(|node| node.execution != ExecutionMultiplicity::Once)
-    {
-        return Err(AnalyticalCostError::InvalidPhysicalDAG(
-            "streaming raw horizon evidence must use once-counted aggregate statistics",
-        ));
-    }
-    let expected = EdgeStatistics { rows, bytes };
-    let mut scan_count = 0;
-    for scan_node in reachable
-        .into_iter()
-        .filter(|node| node.operator == PhysicalOperator::Scan)
-    {
-        scan_count += 1;
-        let evidence = raw
-            .physical_dag
-            .evidence
-            .get(&scan_node.id)
-            .ok_or_else(|| AnalyticalCostError::MissingOperatorStatistics(scan_node.id.clone()))?;
-        let statistics = &evidence.statistics;
-        let OperatorStatistics::Scan {
-            edges,
-            source_read_bytes,
-        } = statistics
-        else {
-            return Err(AnalyticalCostError::InvalidOperatorStatistics {
-                node: scan_node.id.clone(),
-                reason: "raw scan evidence uses the wrong statistics variant",
-            });
-        };
-        if edges.input != expected || edges.output != expected || *source_read_bytes != scan {
-            return Err(AnalyticalCostError::ComparisonScopeMismatch(
-                "raw source evolution",
-            ));
-        }
-    }
-    if scan_count == 0 {
-        return Err(AnalyticalCostError::MissingComparisonScope("raw scan"));
-    }
-    Ok(())
-}
-
-pub(super) fn ephemeral_rows_over_horizon(
-    inputs: SummaryMaintenanceInputs,
-    scope: &ComparisonScope,
-) -> Result<u64, AnalyticalCostError> {
-    evaluation_offsets_ms(scope)?
-        .into_iter()
-        .try_fold(0_u64, |total, offset| {
-            let arrivals = (inputs.ingestion_rate_per_second * offset as f64 / 1_000.0).ceil();
-            if !arrivals.is_finite() || arrivals < 0.0 || arrivals > u64::MAX as f64 {
-                return Err(AnalyticalCostError::Overflow);
-            }
-            total
-                .checked_add(inputs.initial_input_rows)
-                .and_then(|value| value.checked_add(arrivals as u64))
-                .ok_or(AnalyticalCostError::Overflow)
-        })
-}
-
-pub(super) fn ephemeral_scan_bytes_over_horizon(
-    inputs: SummaryMaintenanceInputs,
-    raw: &RawInputEvidence,
-    scope: &ComparisonScope,
-) -> Result<u64, AnalyticalCostError> {
-    if inputs.initial_source_scan_bytes == 0 {
-        return Ok(0);
-    }
-    evaluation_offsets_ms(scope)?
-        .into_iter()
-        .try_fold(0_u64, |total, offset| {
-            let arrivals = (inputs.ingestion_rate_per_second * offset as f64 / 1_000.0).ceil();
-            if !arrivals.is_finite() || arrivals < 0.0 || arrivals > u64::MAX as f64 {
-                return Err(AnalyticalCostError::Overflow);
-            }
-            total
-                .checked_add(inputs.initial_source_scan_bytes)
-                .and_then(|value| {
-                    (arrivals as u64)
-                        .checked_mul(raw.arriving_source_row_bytes)
-                        .and_then(|arriving| value.checked_add(arriving))
-                })
-                .ok_or(AnalyticalCostError::Overflow)
-        })
-}
-
-pub(super) fn evaluation_offsets_ms(
-    scope: &ComparisonScope,
-) -> Result<Vec<u64>, AnalyticalCostError> {
-    let count = scope.validate()?;
-    match &scope.recurrence {
-        QueryRecurrence::OneTime {
-            invocations,
-            execute_at,
-        } => Ok(vec![
-            execute_at.map_or(0, |at| at
-                .0
-                .saturating_sub(scope.planning_time.0));
-            *invocations as usize
-        ]),
-        QueryRecurrence::Repeated(RepeatedDemand::FixedInterval(interval))
-        | QueryRecurrence::Repeated(RepeatedDemand::FixedIntervalAt { interval, .. }) => {
-            Ok((1..=count).map(|n| n * u64::from(interval.0)).collect())
-        }
-        QueryRecurrence::Repeated(RepeatedDemand::Scheduled(schedule)) => Ok(schedule
-            .iter()
-            .filter(|at| {
-                at.0 >= scope.planning_time.0
-                    && at.0 <= scope.planning_time.0.saturating_add(scope.horizon.0)
-            })
-            .map(|at| at.0 - scope.planning_time.0)
-            .collect()),
-        QueryRecurrence::Repeated(RepeatedDemand::EstimatedRate(_)) => Ok((1..=count)
-            .map(|n| scope.horizon.0.saturating_mul(n) / count)
-            .collect()),
-        QueryRecurrence::Unknown => Err(AnalyticalCostError::InvalidRecurrence),
-    }
-}
-
-impl SummaryMaintenanceCostModel {
-    pub fn new(
-        calibration: ResourceCalibration,
-        capabilities: SummaryMaintenanceCapabilities,
-    ) -> Self {
-        Self {
-            node_evidence: SummaryNodeEvidence::default(),
-            calibration,
-            capabilities,
-            target_comparisons: HashMap::new(),
-            candidate_comparisons: HashMap::new(),
-            physical_plan_alternatives: HashMap::new(),
-            window_framework_candidates: HashMap::new(),
-        }
-    }
-
-    /// Bind one candidate and its raw baseline to the same target-specific
-    /// comparison context. Rebinding a target to different evidence is
-    /// rejected rather than silently replacing the canonical context.
-    pub fn bind_candidate_comparison(
-        &mut self,
-        target: &Rc<OperatorNode>,
-        root: &Rc<OperatorNode>,
-        scope: ComparisonScope,
-        raw: RawInputEvidence,
-    ) -> Result<(), AnalyticalCostError> {
-        scope.validate()?;
-        validate_query_scope(target, &scope)?;
-        validate_physical_scope_coverage(&raw.physical_dag, &scope)?;
-        validate_raw_snapshot_dimensions(&raw, &scope)?;
-        estimate_physical_dag(
-            &raw.physical_dag.nodes,
-            &raw.physical_dag.root,
-            &scope,
-            &raw.physical_dag,
-        )?;
-        let target_ptr = Rc::as_ptr(target);
-        if let Some(existing) = self.target_comparisons.get(&target_ptr) {
-            if existing.scope != scope || existing.raw != raw {
-                return Err(AnalyticalCostError::ComparisonScopeMismatch(
-                    "target comparison",
-                ));
-            }
-        }
-        // Commit only after every validation above succeeds. Shared nodes do
-        // not carry one owning target; context identity is `(target, root)`.
-        self.target_comparisons
-            .entry(target_ptr)
-            .or_insert(SummaryTargetComparison {
-                _target: Rc::clone(target),
-                scope,
-                raw,
-            });
-        self.candidate_comparisons.insert(
-            (target_ptr, Rc::as_ptr(root)),
-            BoundCandidateIdentity {
-                _target: Rc::clone(target),
-                _root: Rc::clone(root),
-            },
-        );
-        Ok(())
-    }
-
-    /// Add one complete physical implementation for an already-bound logical
-    /// candidate. Duplicate or empty provider identities are rejected.
-    pub fn bind_physical_plan_alternative(
-        &mut self,
-        target: &Rc<OperatorNode>,
-        root: &Rc<OperatorNode>,
-        alternative: SummaryPhysicalPlanAlternative,
-    ) -> Result<(), AnalyticalCostError> {
-        let key = (Rc::as_ptr(target), Rc::as_ptr(root));
-        if !self.candidate_comparisons.contains_key(&key) {
-            return Err(AnalyticalCostError::MissingOrStale(
-                "candidate comparison binding",
-            ));
-        }
-        if alternative.physical_plan_id.trim().is_empty() {
-            return Err(AnalyticalCostError::MissingOrZero("physical_plan_id"));
-        }
-        if self.window_framework_candidates.contains_key(&key) {
-            return Err(AnalyticalCostError::ComparisonScopeMismatch(
-                "physical alternative binding mode",
-            ));
-        }
-        let alternatives = self.physical_plan_alternatives.entry(key).or_default();
-        if alternatives
-            .iter()
-            .any(|existing| existing.physical_plan_id == alternative.physical_plan_id)
-        {
-            return Err(AnalyticalCostError::ComparisonScopeMismatch(
-                "physical plan identity",
-            ));
-        }
-        alternatives.push(alternative);
-        Ok(())
-    }
-
-    /// Add one complete abstract window assignment to Planner candidate search.
-    ///
-    /// The provider may bind multiple executor-feasible implementations for
-    /// the same framework assignment; their stable identities and complete
-    /// evidence keep the implementations distinct during ranking.
-    pub fn bind_window_framework_candidate(
-        &mut self,
-        target: &Rc<OperatorNode>,
-        root: &Rc<OperatorNode>,
-        candidate: SummaryWindowFrameworkCandidate,
-    ) -> Result<(), AnalyticalCostError> {
-        let key = (Rc::as_ptr(target), Rc::as_ptr(root));
-        if !self.candidate_comparisons.contains_key(&key) {
-            return Err(AnalyticalCostError::MissingOrStale(
-                "candidate comparison binding",
-            ));
-        }
-        if candidate.physical_plan_id.trim().is_empty() {
-            return Err(AnalyticalCostError::MissingOrZero("physical_plan_id"));
-        }
-        if self.physical_plan_alternatives.contains_key(&key) {
-            return Err(AnalyticalCostError::ComparisonScopeMismatch(
-                "physical alternative binding mode",
-            ));
-        }
-        if candidate.assignments.is_empty() {
-            return Err(AnalyticalCostError::MissingOrZero(
-                "window framework assignments",
-            ));
-        }
-        let mut assigned = HashSet::new();
-        if candidate
-            .assignments
-            .iter()
-            .any(|assignment| !assigned.insert(Rc::as_ptr(&assignment.summary)))
-        {
-            return Err(AnalyticalCostError::MissingOrZero(
-                "unique window framework assignments",
-            ));
-        }
-        if assigned != summary_aggregation_identities(root) {
-            return Err(AnalyticalCostError::ComparisonScopeMismatch(
-                "window framework assignments",
-            ));
-        }
-        let candidates = self.window_framework_candidates.entry(key).or_default();
-        if candidates
-            .iter()
-            .any(|existing| existing.physical_plan_id == candidate.physical_plan_id)
-        {
-            return Err(AnalyticalCostError::ComparisonScopeMismatch(
-                "window framework candidate",
-            ));
-        }
-        candidates.push(candidate);
-        Ok(())
-    }
-
-    fn comparison_context(
-        &self,
-        root: &OperatorNode,
-        target: Option<&OperatorNode>,
-        horizon: Option<crate::recurrence::Horizon>,
-        expected_reads: Option<f64>,
-    ) -> Option<(CandidateComparisonKey, &SummaryTargetComparison)> {
-        let root_ptr = root as *const _;
-        let target_ptr = match target {
-            Some(target) => target as *const _,
-            None => {
-                let mut targets = self
-                    .candidate_comparisons
-                    .keys()
-                    .filter_map(|(target, candidate)| (*candidate == root_ptr).then_some(*target));
-                let only = targets.next()?;
-                if targets.next().is_some() {
-                    return None;
-                }
-                only
-            }
-        };
-        let key = (target_ptr, root_ptr);
-        if !self.candidate_comparisons.contains_key(&key) {
-            return None;
-        }
-        let comparison = self.target_comparisons.get(&target_ptr)?;
-        if horizon.map(|value| value.0 * 1_000.0) != Some(comparison.scope.horizon.0 as f64)
-            || expected_reads != Some(comparison.scope.validate().ok()? as f64)
-        {
-            return None;
-        }
-        Some((key, comparison))
-    }
-
-    fn complete_cost_with_evidence(
-        &self,
-        root: &OperatorNode,
-        deployments: &[CostedSummaryDeployment<'_>],
-        comparison: &SummaryTargetComparison,
-        evidence: &SummaryNodeEvidence,
-        window_frameworks: &[Option<SummaryWindowFramework>],
-    ) -> Option<Cost> {
-        self.calibrated(
-            estimate_heterogeneous_summary(
-                root,
-                deployments,
-                evidence,
-                &comparison.scope,
-                &comparison.raw,
-                window_frameworks,
-            )
-            .ok()?,
-        )
-    }
-
-    fn canonical_inputs(&self, summary: &OperatorNode) -> Option<SummaryAggregateEvidence> {
-        let evidence = self.node_evidence.aggregation(summary)?;
-        evidence.inputs.validate().ok()?;
-        Some(evidence)
-    }
-
-    fn calibrated(&self, estimate: ResourceEstimate) -> Option<Cost> {
-        estimate.calibrated_cost(&self.calibration).ok().map(Cost)
-    }
-
-    fn lifecycle_inputs(
-        &self,
-        summary: &OperatorNode,
-        horizon: Option<crate::recurrence::Horizon>,
-    ) -> Option<SummaryMaintenanceLifecycleCostInputs> {
-        let evidence = self.canonical_inputs(summary)?;
-        let inputs = evidence.inputs;
-        let insert = validated_operator_cpu("insert_cpu_ops", evidence.insert_cpu_ops).ok()?;
-        let build = self.calibrated(ResourceEstimate::new(
-            inputs.initial_input_rows as f64 * inputs.bootstrap_window_count as f64 * insert,
-            0,
-            inputs.initial_source_scan_bytes,
-        ))?;
-        let maintenance = self.calibrated(ResourceEstimate::new(
-            inputs.active_window_count as f64 * insert,
-            0,
-            0,
-        ))?;
-        let retained = inputs
-            .active_window_count
-            .checked_add(inputs.retained_window_count)?
-            .checked_mul(inputs.physical_summary_count)?
-            .checked_mul(inputs.state_bytes_per_summary)?;
-        let retention_total = self.calibrated(ResourceEstimate::new(0.0, retained, 0))?;
-        let horizon_seconds = horizon.filter(|value| value.0 > 0.0)?.0;
-        Some(SummaryMaintenanceLifecycleCostInputs {
-            build_cost: Some(build),
-            maintenance_cost_per_update: Some(maintenance),
-            // Evaluation is a separate physical operator in the complete DAG.
-            // A state-only candidate therefore does not fabricate evaluation
-            // evidence merely to keep a lifecycle alternative selectable.
-            summary_read_cost: Some(Cost::ZERO),
-            retention_cost_rate: Some(CostRate(retention_total.0 / horizon_seconds)),
-            // Releasing memory has no modeled CPU or I/O. This is not an
-            // implicit expiration/rebuild policy; those require an explicit
-            // SummaryDelete or future authoritative lifecycle evidence.
-            retirement_cost: Some(Cost::ZERO),
-        })
-    }
-}
-
-impl CostModel for SummaryMaintenanceCostModel {
-    fn candidate_cost(
-        &self,
-        candidate: &ReplacementSubDAG,
-        _target: &TargetSubDAG<'_>,
-    ) -> Option<Cost> {
-        match &candidate.replacement {
-            Replacement::ExactComposition(_) => None,
-            // Lifecycle selection supplies a complete override. If it cannot,
-            // the candidate remains unavailable rather than receiving this
-            // trait's structural fallback.
-            Replacement::SubDAG(_) => None,
-        }
-    }
-
-    fn rank_candidates(
-        &self,
-        intent: &AggIntent,
-        candidates: &[SketchAlgorithm],
-    ) -> Vec<SketchAlgorithm> {
-        DefaultCostModel.rank_candidates(intent, candidates)
-    }
-
-    fn estimate_cost(&self, _candidate: &ReplacementSubDAG, _target: &TargetSubDAG<'_>) -> f64 {
-        f64::INFINITY
-    }
-
-    fn summary_maintenance_lifecycle_cost_inputs(
-        &self,
-        _summary: &OperatorNode,
-    ) -> SummaryMaintenanceLifecycleCostInputs {
-        SummaryMaintenanceLifecycleCostInputs::default()
-    }
-
-    fn summary_maintenance_lifecycle_cost_inputs_for_horizon(
-        &self,
-        summary: &OperatorNode,
-        horizon: Option<crate::recurrence::Horizon>,
-    ) -> SummaryMaintenanceLifecycleCostInputs {
-        self.lifecycle_inputs(summary, horizon).unwrap_or_default()
-    }
-
-    fn summary_maintenance_capabilities(
-        &self,
-        _summary: &OperatorNode,
-    ) -> SummaryMaintenanceCapabilities {
-        self.capabilities
-    }
-
-    fn complete_summary_candidate_cost(
-        &self,
-        root: &OperatorNode,
-        target: Option<&OperatorNode>,
-        deployments: &[CostedSummaryDeployment<'_>],
-        horizon: Option<crate::recurrence::Horizon>,
-        expected_reads: Option<f64>,
-        required_accuracy: &[AccuracyTarget],
-    ) -> Option<Cost> {
-        self.complete_summary_candidate_estimate(
-            root,
-            target,
-            deployments,
-            horizon,
-            expected_reads,
-            required_accuracy,
-        )
-        .map(|estimate| estimate.cost)
-    }
-
-    fn complete_summary_candidate_estimate(
-        &self,
-        root: &OperatorNode,
-        target: Option<&OperatorNode>,
-        deployments: &[CostedSummaryDeployment<'_>],
-        horizon: Option<crate::recurrence::Horizon>,
-        expected_reads: Option<f64>,
-        required_accuracy: &[AccuracyTarget],
-    ) -> Option<CompleteSummaryCandidateEstimate> {
-        let (key, comparison) = self.comparison_context(root, target, horizon, expected_reads)?;
-        if let Some(candidates) = self.window_framework_candidates.get(&key) {
-            return candidates
-                .iter()
-                .filter_map(|candidate| {
-                    if candidate.assignments.len() != deployments.len() {
-                        return None;
-                    }
-                    if !candidate
-                        .accuracy
-                        .matches_assignments(&candidate.assignments)
-                    {
-                        return None;
-                    }
-                    let window_frameworks = deployments
-                        .iter()
-                        .map(|deployment| {
-                            candidate
-                                .assignments
-                                .iter()
-                                .find(|assignment| {
-                                    std::ptr::eq(assignment.summary.as_ref(), deployment.summary)
-                                })
-                                .map(|assignment| assignment.framework.clone())
-                        })
-                        .collect::<Option<Vec<_>>>()?;
-                    let uses_exponential_histogram = window_frameworks.iter().any(|framework| {
-                        matches!(
-                            framework,
-                            Some(SummaryWindowFramework::ExponentialHistogram)
-                        )
-                    });
-                    let window_accuracy_guarantee = candidate.accuracy.end_to_end_guarantee(
-                        uses_exponential_histogram,
-                        root.guarantee.as_ref(),
-                    )?;
-                    if !required_accuracy.iter().all(|target| {
-                        DefaultAccuracyModel.satisfies(&window_accuracy_guarantee, target)
-                    }) {
-                        return None;
-                    }
-                    self.complete_cost_with_evidence(
-                        root,
-                        deployments,
-                        comparison,
-                        &candidate.node_evidence,
-                        &window_frameworks,
-                    )
-                    .map(|cost| CompleteSummaryCandidateEstimate {
-                        cost,
-                        physical_plan_id: Some(candidate.physical_plan_id.clone()),
-                        window_frameworks,
-                        window_accuracy_guarantee: Some(window_accuracy_guarantee),
-                    })
-                })
-                .min_by(|left, right| left.cost.0.total_cmp(&right.cost.0));
-        }
-        if let Some(alternatives) = self.physical_plan_alternatives.get(&key) {
-            return alternatives
-                .iter()
-                .filter_map(|alternative| {
-                    let frameworks = vec![None; deployments.len()];
-                    self.complete_cost_with_evidence(
-                        root,
-                        deployments,
-                        comparison,
-                        &alternative.node_evidence,
-                        &frameworks,
-                    )
-                    .map(|cost| CompleteSummaryCandidateEstimate {
-                        cost,
-                        physical_plan_id: Some(alternative.physical_plan_id.clone()),
-                        window_frameworks: frameworks,
-                        window_accuracy_guarantee: None,
-                    })
-                })
-                .min_by(|left, right| left.cost.0.total_cmp(&right.cost.0));
-        }
-        let frameworks = vec![None; deployments.len()];
-        self.complete_cost_with_evidence(
-            root,
-            deployments,
-            comparison,
-            &self.node_evidence,
-            &frameworks,
-        )
-        .map(|cost| CompleteSummaryCandidateEstimate {
-            cost,
-            physical_plan_id: None,
-            window_frameworks: frameworks,
-            window_accuracy_guarantee: None,
-        })
-    }
-
-    fn complete_summary_candidate_estimate_covers_lifecycle_costs(&self) -> bool {
-        true
-    }
-
-    fn raw_query_recompute_cost(&self, target: &OperatorNode) -> Option<Cost> {
-        let _ = target;
-        None
-    }
-
-    fn raw_query_recompute_total_cost(
-        &self,
-        target: &OperatorNode,
-        expected_reads: f64,
-    ) -> Option<Cost> {
-        let target_ptr = target as *const _;
-        let comparison = self.target_comparisons.get(&target_ptr)?;
-        let evaluations = comparison.scope.validate().ok()?;
-        if expected_reads != evaluations as f64 {
-            return None;
-        }
-        self.calibrated(
-            estimate_physical_dag(
-                &comparison.raw.physical_dag.nodes,
-                &comparison.raw.physical_dag.root,
-                &comparison.scope,
-                &comparison.raw.physical_dag,
-            )
-            .ok()?,
-        )
-    }
-}
-
-use super::estimator::*;
-#[cfg(test)]
-mod tests {
-    use std::rc::Rc;
-
-    use asap_types::ir::{ASAPOp, BinaryOperator, NonASAPOp, Operator, OperatorNode};
-    use asap_types::post_asap::{
-        EvaluationSchedule, ExactKind, ExactParams, Field, FieldDataType, GroupingStrategy,
-        OutputRepresentation, Schema, SummaryMaintenanceLifecycle,
-        SummaryMaintenanceLifecycleGuarantee, SummaryMaintenanceMode, SummaryUpdate,
-    };
-    use asap_types::pre_asap::{
-        agg_intent::AggIntent, ArithmeticOpKind, BinaryOpKind, DataType, Reduction, Source,
-    };
-    use asap_types::workload::{
-        DataWorkload, Evidence, EvidenceSource, Predictability, Query, QueryLanguage,
-        QueryRecurrence, QueryRequirements, QueryTimeScope, QueryWorkload, QueryWorkloadEntry,
-        Rate, RepeatedDemand, RepeatingEntry, RepetitionInterval, TimeSelection,
-    };
-
-    use super::*;
-    use crate::recurrence::Horizon;
-    use crate::summary_maintenance_lifecycle::{
-        assemble_selected_dag_with_summary_maintenance_lifecycles,
-        global_selection_with_summary_maintenance_lifecycles, plan_summary_maintenance_lifecycles,
-        SummaryMaintenanceLifecycleCapabilities, WorkloadDemand,
-    };
-
-    fn estimate_test(
-        root: &OperatorNode,
-        guarantee: &SummaryMaintenanceLifecycleGuarantee,
-        inputs: SummaryMaintenanceInputs,
-        cpu: SummaryOperationCpuEvidence,
-    ) -> Result<ResourceEstimate, AnalyticalCostError> {
-        estimate_incremental_summary_maintenance(root, guarantee, inputs, cpu, &streaming_scope())
-    }
-
-    fn estimate_join_test(
-        root: &OperatorNode,
-        guarantee: &SummaryMaintenanceLifecycleGuarantee,
-        inputs: SummaryMaintenanceInputs,
-        cpu: SummaryOperationCpuEvidence,
-        join: Option<SummaryJoinEvidence>,
-    ) -> Result<ResourceEstimate, AnalyticalCostError> {
-        estimate_incremental_summary_maintenance_with_join(
-            root,
-            guarantee,
-            inputs,
-            cpu,
-            join,
-            &streaming_scope(),
-        )
-    }
-
-    fn scope_for(
-        data: &DataWorkload,
-        query: &QueryWorkloadEntry,
-        planning_time_ms: u64,
-        horizon_ms: u64,
-    ) -> ComparisonScope {
-        ComparisonScope::from_workload(
-            data,
-            query,
-            asap_types::workload::TimestampMs(planning_time_ms),
-            asap_types::workload::DurationMs(horizon_ms),
-            vec![crate::physical_operator_statistics::ScanSelection {
-                source: Source::TimeSeries {
-                    metric: "metrics".into(),
-                },
-                source_snapshot_id: "stream-start".into(),
-                predicates: vec![],
-                info_matchers: vec![],
-            }],
-        )
-        .unwrap()
-    }
-
-    fn physical() -> SummaryPhysicalInputEvidence {
-        SummaryPhysicalInputEvidence {
-            initial_input_bytes: 640,
-            initial_source_scan_bytes: 640,
-            active_window_count: 2,
-            bootstrap_window_count: 1,
-            retained_window_count: 3,
-            physical_summary_count: 2,
-            state_bytes_per_summary: 100,
-        }
-    }
-
-    fn query() -> QueryWorkloadEntry {
-        QueryWorkloadEntry {
-            query: Query("streaming count".into()),
-            requirements: QueryRequirements::default(),
-            predictability: Predictability::Unknown,
-            recurrence: QueryRecurrence::Repeated(RepeatedDemand::FixedInterval(
-                RepetitionInterval(1_000),
-            )),
-            time_selection: TimeSelection {
-                scope: QueryTimeScope::Unknown,
-                lookback: None,
-                as_of: None,
-            },
-        }
-    }
-
-    fn continuous_guarantee() -> SummaryMaintenanceLifecycleGuarantee {
-        SummaryMaintenanceLifecycleGuarantee {
-            summary_maintenance_lifecycle: SummaryMaintenanceLifecycle::ContinuouslyMaintained,
-            summary_maintenance_mode: SummaryMaintenanceMode::Incremental,
-            evaluation_schedule: EvaluationSchedule::PerUpdate,
-            output_representation: OutputRepresentation::SummaryState,
-        }
-    }
-
-    /// A fixed snapshot needs cardinality evidence, but no stream-rate evidence.
-    #[test]
-    fn at_rest_workload_adapter_builds_once_without_arrivals() {
-        let mut data = streaming_data_workload();
-        data.arrival = DataArrival::AtRest;
-        data.ingestion_rate = Evidence::default();
-        data.input_cardinality = Evidence {
-            value: Some(10),
-            source: EvidenceSource::Declared,
-            ..Default::default()
-        };
-        let scope = scope_for(&data, &query(), 0, 5_000);
-        let inputs = SummaryMaintenanceInputs::from_workload(physical(), &data, &scope).unwrap();
-        assert_eq!(inputs.initial_input_rows, 10);
-        assert_eq!(inputs.ingestion_rate_per_second, 0.0);
-        let guarantee = SummaryMaintenanceLifecycleGuarantee {
-            summary_maintenance_lifecycle: SummaryMaintenanceLifecycle::Shared {
-                retention: asap_types::workload::DurationMs(5_000),
-            },
-            summary_maintenance_mode: SummaryMaintenanceMode::DirectBuild,
-            evaluation_schedule: EvaluationSchedule::OnRead,
-            output_representation: OutputRepresentation::SummaryState,
-        };
-        assert_eq!(
-            lifecycle_row_counts(inputs, &guarantee, &scope).unwrap(),
-            (10, 0, 5_000)
-        );
-    }
-
-    /// Arrival semantics cannot be overridden by missing or contradictory rate evidence.
-    #[test]
-    fn workload_adapter_checks_arrival_scope_and_rate_evidence() {
-        let mut data = streaming_data_workload();
-        data.input_cardinality = Evidence {
-            value: Some(10),
-            source: EvidenceSource::Declared,
-            ..Default::default()
-        };
-        let mut scope = scope_for(&data, &query(), 0, 5_000);
-        data.ingestion_rate = Evidence::default();
-        assert_eq!(
-            SummaryMaintenanceInputs::from_workload(physical(), &data, &scope),
-            Err(AnalyticalCostError::MissingOrStale("ingestion_rate"))
-        );
-        data.arrival = DataArrival::AtRest;
-        assert_eq!(
-            SummaryMaintenanceInputs::from_workload(physical(), &data, &scope),
-            Err(AnalyticalCostError::ComparisonScopeMismatch("data arrival"))
-        );
-        scope.data_arrival = DataArrival::AtRest;
-        for rate in [1.0, -1.0, f64::INFINITY, f64::NAN] {
-            data.ingestion_rate = Evidence {
-                value: Some(Rate(rate)),
-                source: EvidenceSource::Declared,
-                ..Default::default()
-            };
-            assert!(SummaryMaintenanceInputs::from_workload(physical(), &data, &scope).is_err());
-        }
-        data.ingestion_rate = Evidence::default();
-        data.input_cardinality = Evidence::default();
-        assert_eq!(
-            SummaryMaintenanceInputs::from_workload(physical(), &data, &scope),
-            Err(AnalyticalCostError::MissingOrStale("input_cardinality"))
-        );
-    }
-
-    /// The real lifecycle planner costs a fixed snapshot with the same node evidence API.
-    #[test]
-    fn lifecycle_planner_selects_fully_costed_at_rest_summary() {
-        let workload = streaming_workload();
-        let mut data = streaming_data_workload();
-        data.arrival = DataArrival::AtRest;
-        data.ingestion_rate = Evidence::default();
-        data.input_cardinality = Evidence {
-            value: Some(10),
-            source: EvidenceSource::Declared,
-            ..Default::default()
-        };
-        let mut scope = streaming_scope();
-        scope.data_arrival = DataArrival::AtRest;
-        let inputs = SummaryMaintenanceInputs::from_workload(physical(), &data, &scope).unwrap();
-        let target = streaming_sum_query();
-        let root = summary_with_operations(false, false, false);
-        let mut provider = streaming_model();
-        bind_aggregations(&mut provider, &target, &root, inputs, streaming_cpu());
-        let mut model = streaming_model();
-        model.node_evidence = provider.node_evidence;
-        let mut raw = streaming_raw();
-        raw.ingestion_rate_per_second = 0.0;
-        let edge = EdgeStatistics {
-            rows: 50,
-            bytes: 3_200,
-        };
-        raw.physical_dag
-            .evidence
-            .get_mut("raw-scan")
-            .unwrap()
-            .statistics = OperatorStatistics::Scan {
-            source_read_bytes: 3_200,
-            edges: UnaryEdgeStatistics {
-                input: edge,
-                output: edge,
-                promql: None,
-            },
-        };
-        model
-            .bind_candidate_comparison(&target, &root, scope.clone(), raw.clone())
-            .unwrap();
-        let plan = plan_summary_maintenance_lifecycles(
-            Rc::clone(&root),
-            WorkloadDemand::new_with_data(&workload, &data, &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        assert!(plan.summary_total_cost.is_some());
-        assert!(!plan.selected_raw_recompute);
-        assert_eq!(
-            plan.deployments[0]
-                .summary_maintenance_lifecycle_guarantee
-                .as_ref()
-                .unwrap()
-                .summary_maintenance_mode,
-            SummaryMaintenanceMode::DirectBuild
-        );
-
-        // Directly supplied raw evidence must not bypass the workload invariant.
-        raw.ingestion_rate_per_second = 1.0;
-        assert_eq!(
-            streaming_model().bind_candidate_comparison(&target, &root, scope, raw),
-            Err(AnalyticalCostError::ComparisonScopeMismatch(
-                "at-rest ingestion rate"
-            ))
-        );
-        // Nor may a provider hide arrivals on a summary edge.
-        for aggregation in model.node_evidence.aggregations.values_mut() {
-            aggregation.inputs.ingestion_rate_per_second = 1.0;
-        }
-        let invalid = plan_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(&workload, &data, &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        assert_eq!(invalid.summary_total_cost, None);
-    }
-
-    #[test]
-    fn workload_adapter_derives_updates_and_reads_over_one_horizon() {
-        let data = DataWorkload {
-            arrival: DataArrival::ContinuouslyIngesting,
-            ingestion_rate: Evidence {
-                value: Some(Rate(2.0)),
-                source: EvidenceSource::Observed,
-                observed_at_ms: Some(100),
-                valid_for_ms: Some(10_000),
-            },
-            input_cardinality: Evidence {
-                value: Some(10),
-                source: EvidenceSource::Observed,
-                observed_at_ms: Some(100),
-                valid_for_ms: Some(10_000),
-            },
-            ..DataWorkload::default()
-        };
-
-        let scope = scope_for(&data, &query(), 100, 5_000);
-        let inputs = SummaryMaintenanceInputs::from_workload(physical(), &data, &scope).unwrap();
-        assert_eq!(inputs.initial_input_rows, 10);
-        assert_eq!(
-            lifecycle_row_counts(inputs, &continuous_guarantee(), &scope)
-                .unwrap()
-                .1,
-            10
-        );
-        assert_eq!(scope.validate().unwrap(), 5);
-    }
-
-    #[test]
-    fn pure_streaming_can_bootstrap_from_an_empty_state() {
-        let data = DataWorkload {
-            arrival: DataArrival::ContinuouslyIngesting,
-            ingestion_rate: Evidence {
-                value: Some(Rate(2.0)),
-                source: EvidenceSource::Declared,
-                observed_at_ms: None,
-                valid_for_ms: None,
-            },
-            input_cardinality: Evidence {
-                value: Some(0),
-                source: EvidenceSource::Declared,
-                observed_at_ms: None,
-                valid_for_ms: None,
-            },
-            ..DataWorkload::default()
-        };
-        let mut empty = physical();
-        empty.initial_input_bytes = 0;
-        empty.initial_source_scan_bytes = 0;
-        let scope = scope_for(&data, &query(), 0, 5_000);
-        let inputs = SummaryMaintenanceInputs::from_workload(empty, &data, &scope).unwrap();
-        let estimate = estimate_test(
-            &summary_with_operations(false, false, false),
-            &continuous_guarantee(),
-            inputs,
-            SummaryOperationCpuEvidence {
-                insert_cpu_ops: Some(2.0),
-                evaluation_cpu_ops: Some(1.0),
-                ..SummaryOperationCpuEvidence::default()
-            },
-        )
-        .unwrap();
-        // 10 arrivals * 2 active windows * 2 insert ops + 5 reads * 2 summaries.
-        assert_eq!(estimate.cpu_ops(), 50.0);
-        assert_eq!(estimate.scan_bytes(), 0);
-    }
-
-    #[test]
-    fn bootstrap_rows_and_bytes_must_be_present_together() {
-        let mut inputs = SummaryMaintenanceInputs {
-            initial_input_rows: 0,
-            initial_input_bytes: 8,
-            initial_source_scan_bytes: 0,
-            ingestion_rate_per_second: 1.0,
-            active_window_count: 1,
-            bootstrap_window_count: 1,
-            retained_window_count: 1,
-            physical_summary_count: 1,
-            state_bytes_per_summary: 8,
-        };
-        assert_eq!(
-            inputs.validate(),
-            Err(AnalyticalCostError::InconsistentBootstrapEvidence)
-        );
-        inputs.initial_input_rows = 1;
-        inputs.initial_input_bytes = 0;
-        assert_eq!(
-            inputs.validate(),
-            Err(AnalyticalCostError::InconsistentBootstrapEvidence)
-        );
-    }
-
-    #[test]
-    fn no_completed_windows_is_a_valid_streaming_deployment() {
-        let mut inputs = streaming_inputs();
-        inputs.retained_window_count = 0;
-        assert!(inputs.validate().is_ok());
-    }
-
-    #[test]
-    fn bootstrap_rows_are_routed_to_declared_window_assignments() {
-        let mut inputs = streaming_inputs();
-        inputs.ingestion_rate_per_second = 0.0;
-        inputs.bootstrap_window_count = 3;
-        let estimate = estimate_test(
-            &summary_with_operations(false, false, false),
-            &continuous_guarantee(),
-            inputs,
-            SummaryOperationCpuEvidence {
-                insert_cpu_ops: Some(2.0),
-                evaluation_cpu_ops: Some(1.0),
-                ..SummaryOperationCpuEvidence::default()
-            },
-        )
-        .unwrap();
-        // 10 bootstrap rows * 3 windows * 2 insert ops + 5 reads * 2 summaries.
-        assert_eq!(estimate.cpu_ops(), 70.0);
-    }
-
-    #[test]
-    fn lifecycle_output_must_remain_summary_state() {
-        let mut guarantee = continuous_guarantee();
-        guarantee.output_representation = OutputRepresentation::FinalizedValue;
-        assert_eq!(
-            estimate_test(
-                &summary_with_operations(false, false, false),
-                &guarantee,
-                streaming_inputs(),
-                streaming_cpu(),
-            ),
-            Err(AnalyticalCostError::IncompatibleLifecycleGuarantee)
-        );
-    }
-
-    #[test]
-    fn existing_lifecycle_planner_selects_a_fully_costed_streaming_alternative() {
-        let inputs = SummaryMaintenanceInputs {
-            initial_input_rows: 10,
-            initial_input_bytes: 640,
-            initial_source_scan_bytes: 640,
-            ingestion_rate_per_second: 2.0,
-            active_window_count: 2,
-            bootstrap_window_count: 1,
-            retained_window_count: 3,
-            physical_summary_count: 2,
-            state_bytes_per_summary: 100,
-        };
-        let mut model = streaming_model();
-        let workload = QueryWorkload {
-            language: QueryLanguage::PromQL,
-            query_batch: None,
-            repeating_queries: Some(vec![RepeatingEntry {
-                query: Query("streaming count".into()),
-                demand: RepeatedDemand::FixedInterval(RepetitionInterval(1_000)),
-                requirements: QueryRequirements::default(),
-                predictability: Predictability::Predictable { known_at: None },
-                time_selection: TimeSelection::default(),
-            }]),
-        };
-        let root = summary_with_operations(false, false, false);
-        let target = streaming_sum_query();
-        bind_aggregations(&mut model, &target, &root, inputs, streaming_cpu());
-        let plan = plan_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        let selected = plan.deployments[0]
-            .summary_maintenance_lifecycle_guarantee
-            .as_ref()
-            .unwrap();
-        assert_eq!(
-            selected.summary_maintenance_mode,
-            SummaryMaintenanceMode::Incremental
-        );
-        assert!(matches!(
-            selected.summary_maintenance_lifecycle,
-            SummaryMaintenanceLifecycle::Shared { .. }
-                | SummaryMaintenanceLifecycle::ContinuouslyMaintained
-        ));
-        assert!(plan.summary_total_cost.is_some());
-        assert_eq!(model.raw_query_recompute_cost(&target), None);
-    }
-
-    #[test]
-    fn complete_streaming_cost_can_select_an_ephemeral_direct_build() {
-        let workload = streaming_workload();
-        let target = streaming_sum_query();
-        let root = summary_with_operations(false, false, false);
-        let mut model = streaming_model();
-        bind_aggregations(
-            &mut model,
-            &target,
-            &root,
-            streaming_inputs(),
-            streaming_cpu(),
-        );
-
-        let plan = plan_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities {
-                supports_ephemeral: true,
-                supports_prepared: false,
-                supports_shared: false,
-                supports_continuously_maintained: false,
-            },
-            &model,
-        )
-        .unwrap();
-
-        assert!(plan.summary_total_cost.is_some());
-        assert!(matches!(
-            plan.deployments[0]
-                .summary_maintenance_lifecycle_guarantee
-                .as_ref()
-                .map(|guarantee| &guarantee.summary_maintenance_lifecycle),
-            Some(SummaryMaintenanceLifecycle::Ephemeral)
-        ));
-    }
-
-    #[test]
-    fn complete_streaming_cost_ranks_provider_owned_physical_plans() {
-        let workload = streaming_workload();
-        let target = streaming_sum_query();
-        let root = summary_with_operations(false, false, false);
-        let mut model = streaming_model();
-        bind_aggregations(
-            &mut model,
-            &target,
-            &root,
-            streaming_inputs(),
-            streaming_cpu(),
-        );
-
-        let mut high_retention = model.node_evidence.clone();
-        for aggregate in high_retention.aggregations.values_mut() {
-            aggregate.inputs.retained_window_count = 20;
-        }
-        let mut low_retention = model.node_evidence.clone();
-        for aggregate in low_retention.aggregations.values_mut() {
-            aggregate.inputs.retained_window_count = 2;
-        }
-        for alternative in [
-            SummaryPhysicalPlanAlternative {
-                physical_plan_id: "high-retention-layout".into(),
-                node_evidence: high_retention,
-            },
-            SummaryPhysicalPlanAlternative {
-                physical_plan_id: "low-retention-layout".into(),
-                node_evidence: low_retention,
-            },
-        ] {
-            model
-                .bind_physical_plan_alternative(&target, &root, alternative)
-                .unwrap();
-        }
-
-        let plan = plan_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities {
-                supports_ephemeral: false,
-                supports_prepared: false,
-                supports_shared: false,
-                supports_continuously_maintained: true,
-            },
-            &model,
-        )
-        .unwrap();
-
-        assert_eq!(
-            plan.selected_window_implementation_id.as_deref(),
-            Some("low-retention-layout")
-        );
-        assert_eq!(
-            crate::summary_maintenance_dag_export::export_summary_maintenance_plan(&plan)
-                .selected_window_implementation_id
-                .as_deref(),
-            Some("low-retention-layout")
-        );
-    }
-
-    #[test]
-    fn global_selection_compares_streaming_summary_and_raw_over_one_horizon() {
-        let target = streaming_sum_query();
-        let space = crate::replacement::search_workload(vec![("q", Rc::clone(&target))]);
-        let workload = streaming_workload();
-        let mut model = streaming_model();
-        for group in space.target_subdag_candidates() {
-            for candidate in &group.candidates {
-                if let Replacement::SubDAG(root) = &candidate.replacement {
-                    if !root.contains_asap() {
-                        continue;
-                    }
-                    bind_aggregations(
-                        &mut model,
-                        &group.target,
-                        root,
-                        streaming_inputs(),
-                        streaming_cpu(),
-                    );
-                }
-            }
-        }
-        let selection = global_selection_with_summary_maintenance_lifecycles(
-            &space,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        let plan = assemble_selected_dag_with_summary_maintenance_lifecycles(
-            &selection,
-            &space.roots[0].1,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap()
-        .unwrap();
-        assert!(!plan.selected_raw_recompute);
-        assert_eq!(plan.raw_recompute_total_cost, Some(Cost(5_264.0)));
-
-        let mut missing_baseline = model.clone();
-        missing_baseline
-            .target_comparisons
-            .get_mut(&Rc::as_ptr(&space.roots[0].1))
-            .unwrap()
-            .raw
-            .physical_dag
-            .evidence
-            .clear();
-        let unavailable = global_selection_with_summary_maintenance_lifecycles(
-            &space,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &missing_baseline,
-        )
-        .unwrap();
-        assert!(unavailable
-            .for_target(&space.roots[0].1)
-            .unwrap()
-            .chosen
-            .is_none());
-
-        let mut raw_cheaper = model;
-        for evidence in raw_cheaper.node_evidence.aggregations.values_mut() {
-            evidence.insert_cpu_ops = 10_000.0;
-        }
-        let cheap_selection = global_selection_with_summary_maintenance_lifecycles(
-            &space,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &raw_cheaper,
-        )
-        .unwrap();
-        assert!(cheap_selection
-            .for_target(&space.roots[0].1)
-            .unwrap()
-            .chosen
-            .is_none());
-        let cheap_plan = assemble_selected_dag_with_summary_maintenance_lifecycles(
-            &cheap_selection,
-            &space.roots[0].1,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &raw_cheaper,
-        )
-        .unwrap()
-        .unwrap();
-        assert!(cheap_plan.selected_raw_recompute);
-        assert_eq!(cheap_plan.raw_recompute_total_cost, Some(Cost(5_264.0)));
-    }
-
-    #[test]
-    fn raw_evolution_is_bound_to_the_requested_target() {
-        let target_a = streaming_sum_query();
-        let target_b = streaming_sum_query();
-        let root_a = summary_with_operations(false, false, false);
-        let root_b = summary_with_operations(false, false, false);
-        let mut model = streaming_model();
-        bind_aggregations(
-            &mut model,
-            &target_a,
-            &root_a,
-            streaming_inputs(),
-            streaming_cpu(),
-        );
-        let mut faster = streaming_inputs();
-        // Candidate-local intermediate cardinality is not the raw target's
-        // planning-time cardinality and must not constrain its baseline.
-        faster.initial_input_rows = 7;
-        faster.initial_input_bytes = 448;
-        faster.initial_source_scan_bytes = 448;
-        faster.ingestion_rate_per_second = 4.0;
-        bind_aggregations(&mut model, &target_b, &root_b, faster, streaming_cpu());
-        model
-            .target_comparisons
-            .get_mut(&Rc::as_ptr(&target_b))
-            .unwrap()
-            .raw = {
-            let mut raw = streaming_raw();
-            raw.ingestion_rate_per_second = 4.0;
-            let statistics = &mut raw
-                .physical_dag
-                .evidence
-                .get_mut("raw-scan")
-                .unwrap()
-                .statistics;
-            let OperatorStatistics::Scan {
-                edges,
-                source_read_bytes,
-            } = statistics
-            else {
-                unreachable!()
-            };
-            *source_read_bytes = 7_040;
-            edges.input = EdgeStatistics {
-                rows: 110,
-                bytes: 7_040,
-            };
-            edges.output = edges.input;
-            raw
-        };
-
-        let a = model.raw_query_recompute_total_cost(&target_a, 5.0);
-        let b = model.raw_query_recompute_total_cost(&target_b, 5.0);
-        assert_eq!(a, Some(Cost(5_264.0)));
-        assert!(b.unwrap().0 > a.unwrap().0);
-        assert_eq!(model.raw_query_recompute_total_cost(&target_a, 5.0), a);
-    }
-
-    #[test]
-    fn raw_validation_uses_reachable_nodes_and_allows_repeated_source_scans() {
-        let target = streaming_sum_query();
-        let root = summary_with_operations(false, false, false);
-        let scope = streaming_scope();
-        let mut raw = streaming_raw();
-        let first_scan = raw.physical_dag.nodes[0].clone();
-        let mut second_scan = first_scan.clone();
-        second_scan.id = "raw-scan-2".into();
-        let mut unreachable = first_scan.clone();
-        unreachable.id = "unreachable-per-evaluation".into();
-        unreachable.execution = ExecutionMultiplicity::PerEvaluation;
-        raw.physical_dag.nodes = vec![
-            first_scan,
-            second_scan,
-            unreachable,
-            PhysicalDAGNode {
-                id: "raw-concat".into(),
-                operator: PhysicalOperator::Concat,
-                children: vec!["raw-scan".into(), "raw-scan-2".into()],
-                scan_selection: None,
-                output_buffer_bytes: 0,
-                retained_bytes: 0,
-                execution: ExecutionMultiplicity::Once,
-            },
-        ];
-        raw.physical_dag.root = "raw-concat".into();
-        let scan_evidence = raw.physical_dag.evidence["raw-scan"].clone();
-        let mut second_scan_evidence = scan_evidence.clone();
-        second_scan_evidence.physical_id = "raw-scan-2".into();
-        raw.physical_dag
-            .evidence
-            .insert("raw-scan-2".into(), second_scan_evidence);
-        let mut unreachable_evidence = scan_evidence;
-        unreachable_evidence.physical_id = "unreachable-per-evaluation".into();
-        raw.physical_dag
-            .evidence
-            .insert("unreachable-per-evaluation".into(), unreachable_evidence);
-        raw.physical_dag.evidence.insert(
-            "raw-concat".into(),
-            PhysicalNodeEvidence {
-                physical_id: "raw-concat".into(),
-                statistics: OperatorStatistics::Concat {
-                    inputs: vec![
-                        EdgeStatistics {
-                            rows: 80,
-                            bytes: 5_120,
-                        },
-                        EdgeStatistics {
-                            rows: 80,
-                            bytes: 5_120,
-                        },
-                    ],
-                    output: EdgeStatistics {
-                        rows: 160,
-                        bytes: 10_240,
-                    },
-                    promql: None,
-                },
-                output_buffer_bytes: 0,
-            },
-        );
-        let mut model = streaming_model();
-        assert!(model
-            .bind_candidate_comparison(&target, &root, scope, raw)
-            .is_ok());
-    }
-
-    #[test]
-    fn comparison_binding_is_transactional_and_shared_nodes_allow_two_targets() {
-        let target_a = streaming_sum_query();
-        let target_b = streaming_sum_query();
-        let root = summary_with_operations(false, false, false);
-        let mut model = streaming_model();
-        let mut wrong_scope = streaming_scope();
-        wrong_scope.sources[0].source = Source::TimeSeries {
-            metric: "wrong".into(),
-        };
-        assert_eq!(
-            model.bind_candidate_comparison(&target_a, &root, wrong_scope, streaming_raw(),),
-            Err(AnalyticalCostError::ComparisonScopeMismatch(
-                "raw target source lineage"
-            ))
-        );
-        assert!(model.target_comparisons.is_empty());
-        assert!(model.candidate_comparisons.is_empty());
-
-        model
-            .bind_candidate_comparison(&target_a, &root, streaming_scope(), streaming_raw())
-            .unwrap();
-        model
-            .bind_candidate_comparison(&target_b, &root, streaming_scope(), streaming_raw())
-            .unwrap();
-        assert_eq!(model.candidate_comparisons.len(), 2);
-    }
-
-    #[test]
-    fn target_scope_rejects_extra_sources_and_tracks_info_matchers() {
-        let target = streaming_sum_query();
-        let mut extra = streaming_scope();
-        extra
-            .sources
-            .push(crate::physical_operator_statistics::ScanSelection {
-                source: Source::TimeSeries {
-                    metric: "unused".into(),
-                },
-                source_snapshot_id: "stream-start".into(),
-                predicates: vec![],
-                info_matchers: vec![],
-            });
-        assert_eq!(
-            validate_query_scope(&target, &extra),
-            Err(AnalyticalCostError::ComparisonScopeMismatch(
-                "raw target source lineage"
-            ))
-        );
-
-        let selector = vec![InfoMatcher {
-            label: "job".into(),
-            op: CompareOpKind::Eq,
-            value: "api".into(),
-        }];
-        let info_target = OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(
-            NonASAPOp::PromqlInfoEnrich {
-                selector: selector.clone(),
-                child: target,
-            },
-        ))
-        .unwrap();
-        let mut info_scope = streaming_scope();
-        info_scope
-            .sources
-            .push(crate::physical_operator_statistics::ScanSelection {
-                source: Source::TimeSeries {
-                    metric: "target_info".into(),
-                },
-                source_snapshot_id: "info-start".into(),
-                predicates: vec![],
-                info_matchers: selector,
-            });
-        validate_query_scope(&info_target, &info_scope).unwrap();
-        info_scope.sources[1].info_matchers[0].value = "worker".into();
-        assert_eq!(
-            validate_query_scope(&info_target, &info_scope),
-            Err(AnalyticalCostError::ComparisonScopeMismatch(
-                "raw target source lineage"
-            ))
-        );
-    }
-
-    #[test]
-    fn summary_delete_dag_fails_closed_before_costing() {
-        // SummaryDelete is reserved: planning rejects the DAG even with full
-        // delete evidence, instead of costing (or owner-checking) the delete.
-        let target = streaming_sum_query();
-        let root = summary_with_operations(false, false, true);
-        let mut cpu = streaming_cpu();
-        cpu.delete_cpu_ops = Some(1.0);
-        cpu.delete_events_per_second = Some(1.0);
-        cpu.delete_routing_fanout = Some(1);
-        let mut model = streaming_model();
-        model.capabilities.delete = true;
-        bind_aggregations(&mut model, &target, &root, streaming_inputs(), cpu);
-
-        // Under a evaluation, the reserved delete surfaces as an illegal child.
-        assert!(matches!(
-            streaming_planning_error(Rc::clone(&root), &model),
-            asap_types::post_asap::ExecutionDataStateError::IllegalChildDataState {
-                edge: "FinalizeExactAccumulator.child",
-                child: asap_types::post_asap::ExecutionDataState::QUERY_ROWS,
-            }
-        ));
-        // As the root, it is reported as the unimplemented operator itself.
-        assert!(matches!(
-            streaming_planning_error(evaluation_state(&root), &model),
-            asap_types::post_asap::ExecutionDataStateError::UnimplementedOperator {
-                operator: "SummaryDelete"
-            }
-        ));
-    }
-
-    #[test]
-    fn summary_edge_and_io_evidence_fail_closed() {
-        // Over two independent summaries combined by a BinaryOp: a parent
-        // input edge that disagrees with its child's output, or missing I/O
-        // evidence on the root, leaves the whole-DAG cost unset.
-        let workload = streaming_workload();
-        let target = streaming_sum_query();
-        let root = add_independent_summary_results();
-        let mut model = streaming_model();
-        bind_aggregations(
-            &mut model,
-            &target,
-            &root,
-            streaming_inputs(),
-            streaming_cpu(),
-        );
-        model.node_evidence.insert_operation(
-            &root,
-            SummaryOperatorEvidence::Binary(test_resource(
-                "binary-edge",
-                vec![test_edge(), EdgeStatistics { rows: 2, bytes: 16 }],
-                1.0,
-                1,
-                0,
-            )),
-        );
-        let bad_edge = plan_summary_maintenance_lifecycles(
-            Rc::clone(&root),
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        assert_eq!(bad_edge.summary_total_cost, None);
-
-        let root_evidence = model
-            .node_evidence
-            .operations
-            .get_mut(&Rc::as_ptr(&root))
-            .unwrap()
-            .resource_mut();
-        root_evidence.inputs = vec![test_edge(), test_edge()];
-        root_evidence.io_bytes_per_execution = None;
-        let missing_io = plan_summary_maintenance_lifecycles(
-            Rc::clone(&root),
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        assert_eq!(missing_io.summary_total_cost, None);
-
-        // Control: the same evidence with I/O restored is costable.
-        model
-            .node_evidence
-            .operations
-            .get_mut(&Rc::as_ptr(&root))
-            .unwrap()
-            .resource_mut()
-            .io_bytes_per_execution = Some(0);
-        let complete = plan_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        assert!(complete.summary_total_cost.is_some());
-    }
-
-    #[test]
-    fn summary_edges_io_and_physical_identity_fail_closed() {
-        // Evidence bound to a structurally equal clone of the BinaryOp does not
-        // count for the real node; a bad input edge or missing I/O on the real
-        // node still fails closed.
-        let workload = streaming_workload();
-        let target = streaming_sum_query();
-        let root = add_independent_summary_results();
-        let mut model = streaming_model();
-        bind_aggregations(
-            &mut model,
-            &target,
-            &root,
-            streaming_inputs(),
-            streaming_cpu(),
-        );
-        model.node_evidence.insert_operation(
-            &Rc::new((*root).clone()),
-            SummaryOperatorEvidence::Binary(test_resource(
-                "unused",
-                vec![test_edge(), test_edge()],
-                1.0,
-                1,
-                0,
-            )),
-        );
-        // Bind the actual BinaryOp, then make one parent input disagree with
-        // its child's output.
-        model.node_evidence.insert_operation(
-            &root,
-            SummaryOperatorEvidence::Binary(test_resource(
-                "binary-edge",
-                vec![test_edge(), EdgeStatistics { rows: 2, bytes: 16 }],
-                1.0,
-                1,
-                0,
-            )),
-        );
-        let bad_edge = plan_summary_maintenance_lifecycles(
-            Rc::clone(&root),
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        assert_eq!(bad_edge.summary_total_cost, None);
-
-        let root_evidence = model
-            .node_evidence
-            .operations
-            .get_mut(&Rc::as_ptr(&root))
-            .unwrap()
-            .resource_mut();
-        root_evidence.inputs = vec![test_edge(), test_edge()];
-        root_evidence.io_bytes_per_execution = None;
-        let missing_io = plan_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        assert_eq!(missing_io.summary_total_cost, None);
-    }
-
-    #[test]
-    fn liveness_does_not_add_disjoint_execution_workspaces() {
-        let target = streaming_sum_query();
-        let root = summary_join();
-        let mut model = streaming_model();
-        bind_aggregations(
-            &mut model,
-            &target,
-            &root,
-            streaming_inputs(),
-            streaming_cpu(),
-        );
-        let join = evidence_nodes(&root).1[0];
-        model.node_evidence.joins.insert(
-            join as *const _,
-            SummaryJoinEvidence {
-                physical_id: "huge-join".into(),
-                inputs: vec![test_edge(), test_edge()],
-                output: test_edge(),
-                cpu_ops_per_execution: 1.0,
-                working_memory_bytes: u64::MAX,
-                output_buffer_bytes: 0,
-                executions_per_evaluation: 1,
-                io_bytes_per_execution: Some(0),
-            },
-        );
-        model
-            .node_evidence
-            .operations
-            .get_mut(&Rc::as_ptr(&root))
-            .unwrap()
-            .resource_mut()
-            .working_memory_bytes = u64::MAX;
-        assert_eq!(
-            estimate_transient_liveness(&root, &model.node_evidence),
-            Ok(u64::MAX)
-        );
-    }
-
-    #[test]
-    fn conflicting_evidence_cannot_alias_one_provider_physical_identity() {
-        // Two independent summary states (combined by a BinaryOp) that claim
-        // one physical id but carry different evidence leave the cost unset.
-        let workload = streaming_workload();
-        let target = streaming_sum_query();
-        let root = add_independent_summary_results();
-        let mut model = streaming_model();
-        bind_aggregations(
-            &mut model,
-            &target,
-            &root,
-            streaming_inputs(),
-            streaming_cpu(),
-        );
-        let aggregations = evidence_nodes(&root).0;
-        assert_eq!(aggregations.len(), 2);
-        let first = aggregations[0] as *const _;
-        let second = aggregations[1] as *const _;
-        model
-            .node_evidence
-            .aggregations
-            .get_mut(&first)
-            .unwrap()
-            .physical_id = "aliased-state".into();
-        let second_evidence = model.node_evidence.aggregations.get_mut(&second).unwrap();
-        second_evidence.physical_id = "aliased-state".into();
-        second_evidence.insert_cpu_ops = 99.0;
-
-        let plan = plan_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        assert_eq!(plan.summary_total_cost, None);
-    }
-
-    #[test]
-    fn summary_join_root_fails_closed_even_with_join_evidence() {
-        // SummaryJoin is reserved: planning rejects the DAG whether or not
-        // join evidence is bound, so no partial or join cost is produced.
-        let root = summary_join();
-        let target = streaming_sum_query();
-        let mut model = streaming_model();
-        bind_aggregations(
-            &mut model,
-            &target,
-            &root,
-            streaming_inputs(),
-            streaming_cpu(),
-        );
-        assert!(matches!(
-            streaming_planning_error(Rc::clone(&root), &model),
-            asap_types::post_asap::ExecutionDataStateError::UnimplementedOperator {
-                operator: "SummaryJoin"
-            }
-        ));
-
-        let join_node = evidence_nodes(&root).1[0];
-        model.node_evidence.joins.insert(
-            join_node as *const _,
-            SummaryJoinEvidence {
-                physical_id: "costed-join".into(),
-                inputs: vec![test_edge(), test_edge()],
-                output: test_edge(),
-                cpu_ops_per_execution: 6.0,
-                working_memory_bytes: 64,
-                output_buffer_bytes: 64,
-                executions_per_evaluation: 1,
-                io_bytes_per_execution: Some(0),
-            },
-        );
-        assert!(matches!(
-            streaming_planning_error(root, &model),
-            asap_types::post_asap::ExecutionDataStateError::UnimplementedOperator {
-                operator: "SummaryJoin"
-            }
-        ));
-    }
-
-    #[test]
-    fn whole_dag_cost_requires_and_uses_each_rc_bound_state_evidence() {
-        // Over two independent summaries combined by a BinaryOp: the cost needs
-        // evidence for each Rc-bound state, charges peak transient memory, and
-        // de-duplicates bootstrap scans only on a shared provider read id.
-        let workload = streaming_workload();
-        let root = add_independent_summary_results();
-        let (left, right) = binary_operands(&root);
-        let target = streaming_sum_query();
-        let aggregations = [evaluation_state(&left), evaluation_state(&right)];
-        let mut model = streaming_model();
-        bind_comparison(&mut model, &target, &root);
-        model.node_evidence.insert_aggregation(
-            &aggregations[0],
-            SummaryAggregateEvidence {
-                physical_id: "left-state".into(),
-                input: test_edge(),
-                output: test_edge(),
-                scan_selection_index: Some(0),
-                bootstrap_read_identity: "left-bootstrap".into(),
-                inputs: streaming_inputs(),
-                insert_cpu_ops: streaming_cpu().insert_cpu_ops.unwrap(),
-            },
-        );
-        let incomplete = plan_summary_maintenance_lifecycles(
-            Rc::clone(&root),
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        assert_eq!(incomplete.summary_total_cost, None);
-
-        let mut second_inputs = streaming_inputs();
-        second_inputs.state_bytes_per_summary = 250;
-        let mut second_cpu = streaming_cpu();
-        second_cpu.insert_cpu_ops = Some(5.0);
-        model.node_evidence.insert_aggregation(
-            &aggregations[1],
-            SummaryAggregateEvidence {
-                physical_id: "right-state".into(),
-                input: test_edge(),
-                output: test_edge(),
-                scan_selection_index: Some(0),
-                bootstrap_read_identity: "right-bootstrap".into(),
-                inputs: second_inputs,
-                insert_cpu_ops: second_cpu.insert_cpu_ops.unwrap(),
-            },
-        );
-        // The left evaluation plays the old join's role: a 64-byte workspace and a
-        // 64-byte output that stays live until the root BinaryOp consumes it.
-        model.node_evidence.insert_operation(
-            &left,
-            SummaryOperatorEvidence::ValueOperation(test_resource(
-                "left-evaluation",
-                vec![test_edge()],
-                6.0,
-                64,
-                64,
-            )),
-        );
-        model.node_evidence.insert_operation(
-            &right,
-            SummaryOperatorEvidence::ValueOperation(test_resource(
-                "right-evaluation",
-                vec![test_edge()],
-                3.0,
-                0,
-                0,
-            )),
-        );
-        model.node_evidence.insert_operation(
-            &root,
-            SummaryOperatorEvidence::Binary(test_resource(
-                "root-binary",
-                vec![test_edge(), test_edge()],
-                3.0,
-                0,
-                0,
-            )),
-        );
-        let complete = plan_summary_maintenance_lifecycles(
-            Rc::clone(&root),
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        assert!(complete.summary_total_cost.is_some());
-
-        model
-            .node_evidence
-            .operations
-            .get_mut(&Rc::as_ptr(&root))
-            .unwrap()
-            .resource_mut()
-            .working_memory_bytes = 128;
-        let larger_workspace = plan_summary_maintenance_lifecycles(
-            Rc::clone(&root),
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        // The left evaluation's 64-byte output remains live while the binary's
-        // workspace is active (64 + 128 = 192); the evaluation's own workspace is
-        // released first, so the old peak was 64 + 64 = 128.
-        assert_eq!(
-            larger_workspace.summary_total_cost.unwrap().0 - complete.summary_total_cost.unwrap().0,
-            64.0
-        );
-
-        // Equal ScanSelection does not imply that two independent state
-        // builds share one physical read. Only a provider-owned read identity
-        // permits scan de-duplication.
-        let mut shared_read = model;
-        for aggregate in shared_read.node_evidence.aggregations.values_mut() {
-            aggregate.bootstrap_read_identity = "one-physical-read".into();
-        }
-        let shared = plan_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &shared_read,
-        )
-        .unwrap();
-        assert_eq!(
-            larger_workspace.summary_total_cost.unwrap().0 - shared.summary_total_cost.unwrap().0,
-            640.0
-        );
-    }
-
-    #[test]
-    fn planner_selects_an_abstract_window_framework_from_downstream_evidence() {
-        let mut workload = streaming_workload();
-        workload.repeating_queries.as_mut().unwrap()[0]
-            .requirements
-            .accuracy =
-            asap_types::workload::AccuracyRequirement::Explicit(AccuracyTarget::EpsilonDelta {
-                epsilon: 0.10,
-                delta: 0.01,
-            });
-        let target = streaming_sum_query();
-        let root = summary_with_operations(false, false, false);
-        let Operator::ASAP(ASAPOp::FinalizeExactAccumulator {
-            child: summary_input,
-        }) = &root.operator
-        else {
-            unreachable!();
-        };
-        let windowed_summary = Rc::clone(summary_input);
-        let mut model = streaming_model();
-        bind_aggregations(
-            &mut model,
-            &target,
-            &root,
-            streaming_inputs(),
-            streaming_cpu(),
-        );
-
-        let mut tumbling = model.node_evidence.clone();
-        for aggregate in tumbling.aggregations.values_mut() {
-            aggregate.inputs.active_window_count = 1;
-            aggregate.inputs.retained_window_count = 20;
-        }
-        let mut sliding = model.node_evidence.clone();
-        for aggregate in sliding.aggregations.values_mut() {
-            aggregate.inputs.active_window_count = 10;
-            aggregate.inputs.retained_window_count = 10;
-        }
-        let mut exponential_histogram = model.node_evidence.clone();
-        for aggregate in exponential_histogram.aggregations.values_mut() {
-            aggregate.inputs.active_window_count = 2;
-            aggregate.inputs.retained_window_count = 2;
-        }
-        for candidate in [
-            SummaryWindowFrameworkCandidate {
-                physical_plan_id: "tumbling-v1".into(),
-                assignments: vec![SummaryWindowFrameworkAssignment {
-                    summary: Rc::clone(&windowed_summary),
-                    framework: Some(SummaryWindowFramework::Tumbling),
-                }],
-                accuracy: SummaryWindowAccuracyEvidence::Exact,
-                node_evidence: tumbling,
-            },
-            SummaryWindowFrameworkCandidate {
-                physical_plan_id: "sliding-v1".into(),
-                assignments: vec![SummaryWindowFrameworkAssignment {
-                    summary: Rc::clone(&windowed_summary),
-                    framework: Some(SummaryWindowFramework::Sliding),
-                }],
-                accuracy: SummaryWindowAccuracyEvidence::Exact,
-                node_evidence: sliding,
-            },
-            SummaryWindowFrameworkCandidate {
-                physical_plan_id: "eh-v1".into(),
-                assignments: vec![SummaryWindowFrameworkAssignment {
-                    summary: Rc::clone(&windowed_summary),
-                    framework: Some(SummaryWindowFramework::ExponentialHistogram),
-                }],
-                accuracy: SummaryWindowAccuracyEvidence::ExponentialHistogram(
-                    ExponentialHistogramAccuracyEvidence::UniversalGsum {
-                        epsilon: 0.05,
-                        failure_probability: 0.01,
-                        range: ExponentialHistogramQueryRange::MostRecentWindow,
-                    },
-                ),
-                node_evidence: exponential_histogram,
-            },
-        ] {
-            model
-                .bind_window_framework_candidate(&target, &root, candidate)
-                .unwrap();
-        }
-        // Framework candidates are authoritative. Selection must not depend
-        // on duplicating one arbitrary implementation into the legacy global
-        // evidence map.
-        model.node_evidence = SummaryNodeEvidence::default();
-
-        let plan = plan_summary_maintenance_lifecycles(
-            Rc::clone(&root),
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities {
-                supports_ephemeral: false,
-                supports_prepared: false,
-                supports_shared: false,
-                supports_continuously_maintained: true,
-            },
-            &model,
-        )
-        .unwrap();
-
-        assert_eq!(
-            plan.deployments[0].selected_window_framework,
-            Some(SummaryWindowFramework::ExponentialHistogram)
-        );
-        assert_eq!(
-            plan.selected_window_implementation_id.as_deref(),
-            Some("eh-v1")
-        );
-        let guarantee = plan.window_accuracy_guarantee.as_ref().unwrap();
-        assert_eq!(guarantee.metric, ErrorMetric::RelativeValue);
-        assert!((guarantee.bound.evaluate().unwrap() - 0.05).abs() < f64::EPSILON);
-        let exported =
-            crate::summary_maintenance_dag_export::export_summary_maintenance_plan(&plan);
-        assert_eq!(
-            exported.deployments[0].selected_window_framework,
-            Some(SummaryWindowFramework::ExponentialHistogram)
-        );
-        assert_eq!(
-            exported.selected_window_implementation_id.as_deref(),
-            Some("eh-v1")
-        );
-        assert_eq!(
-            exported.window_accuracy_guarantee.unwrap().metric,
-            ErrorMetric::RelativeValue
-        );
-
-        workload.repeating_queries.as_mut().unwrap()[0]
-            .requirements
-            .accuracy =
-            asap_types::workload::AccuracyRequirement::Explicit(AccuracyTarget::Epsilon(0.01));
-        let stricter = plan_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities {
-                supports_ephemeral: false,
-                supports_prepared: false,
-                supports_shared: false,
-                supports_continuously_maintained: true,
-            },
-            &model,
-        )
-        .unwrap();
-        assert_ne!(
-            stricter.deployments[0].selected_window_framework,
-            Some(SummaryWindowFramework::ExponentialHistogram)
-        );
-        assert!(stricter.window_accuracy_guarantee.unwrap().is_exact());
-    }
-
-    #[test]
-    fn window_framework_candidates_require_unique_nonempty_planner_primitives() {
-        let target = streaming_sum_query();
-        let root = summary_with_operations(false, false, false);
-        let Operator::ASAP(ASAPOp::FinalizeExactAccumulator {
-            child: summary_input,
-        }) = &root.operator
-        else {
-            unreachable!();
-        };
-        let windowed_summary = Rc::clone(summary_input);
-        let mut model = streaming_model();
-        bind_comparison(&mut model, &target, &root);
-
-        let empty = model.bind_window_framework_candidate(
-            &target,
-            &root,
-            SummaryWindowFrameworkCandidate {
-                physical_plan_id: "empty-assignments".into(),
-                assignments: vec![],
-                accuracy: SummaryWindowAccuracyEvidence::Exact,
-                node_evidence: model.node_evidence.clone(),
-            },
-        );
-        assert!(matches!(empty, Err(AnalyticalCostError::MissingOrZero(_))));
-
-        let candidate = SummaryWindowFrameworkCandidate {
-            physical_plan_id: "tumbling-v1".into(),
-            assignments: vec![SummaryWindowFrameworkAssignment {
-                summary: windowed_summary,
-                framework: Some(SummaryWindowFramework::Tumbling),
-            }],
-            accuracy: SummaryWindowAccuracyEvidence::Exact,
-            node_evidence: model.node_evidence.clone(),
-        };
-        model
-            .bind_window_framework_candidate(&target, &root, candidate.clone())
-            .unwrap();
-        assert!(matches!(
-            model.bind_window_framework_candidate(&target, &root, candidate),
-            Err(AnalyticalCostError::ComparisonScopeMismatch(_))
-        ));
-    }
-
-    #[test]
-    fn one_physical_identity_cannot_alias_different_window_frameworks() {
-        // Two independent summaries (combined by a BinaryOp) sharing one
-        // physical state id but assigned different window frameworks leave
-        // the cost unset.
-        let workload = streaming_workload();
-        let target = streaming_sum_query();
-        let root = add_independent_summary_results();
-        let mut model = streaming_model();
-        bind_aggregations(
-            &mut model,
-            &target,
-            &root,
-            streaming_inputs(),
-            streaming_cpu(),
-        );
-        let (left, right) = binary_operands(&root);
-        let aggregation_nodes = [evaluation_state(&left), evaluation_state(&right)];
-
-        let mut shared_aggregation =
-            model.node_evidence.aggregations[&Rc::as_ptr(&aggregation_nodes[0])].clone();
-        shared_aggregation.physical_id = "shared-window-state".into();
-        for aggregate in &aggregation_nodes {
-            model
-                .node_evidence
-                .insert_aggregation(aggregate, shared_aggregation.clone());
-        }
-
-        let retained_children: Vec<_> = aggregation_nodes
-            .iter()
-            .map(|aggregate| match &aggregate.operator {
-                Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) => Rc::clone(child),
-                _ => unreachable!(),
-            })
-            .collect();
-        let mut shared_retained =
-            model.node_evidence.retained_queries[&Rc::as_ptr(&retained_children[0])].clone();
-        shared_retained.physical_id = "shared-retained-input".into();
-        for child in &retained_children {
-            model
-                .node_evidence
-                .retained_queries
-                .insert(Rc::as_ptr(child), shared_retained.clone());
-        }
-
-        let candidate = SummaryWindowFrameworkCandidate {
-            physical_plan_id: "mixed-framework-binary".into(),
-            assignments: vec![
-                SummaryWindowFrameworkAssignment {
-                    summary: Rc::clone(&aggregation_nodes[0]),
-                    framework: Some(SummaryWindowFramework::Tumbling),
-                },
-                SummaryWindowFrameworkAssignment {
-                    summary: Rc::clone(&aggregation_nodes[1]),
-                    framework: Some(SummaryWindowFramework::Sliding),
-                },
-            ],
-            accuracy: SummaryWindowAccuracyEvidence::Exact,
-            node_evidence: model.node_evidence.clone(),
-        };
-        model
-            .bind_window_framework_candidate(&target, &root, candidate)
-            .unwrap();
-
-        let plan = plan_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        assert_eq!(plan.summary_total_cost, None);
-    }
-
-    #[test]
-    fn promsketch_eh_accuracy_composes_registered_full_and_subwindow_bounds() {
-        let full = SummaryWindowAccuracyEvidence::ExponentialHistogram(
-            ExponentialHistogramAccuracyEvidence::KllRank {
-                eh_epsilon: 0.01,
-                kll_epsilon: 0.02,
-                failure_probability: 0.01,
-                range: ExponentialHistogramQueryRange::MostRecentWindow,
-            },
-        )
-        .guarantee(true)
-        .unwrap();
-        assert_eq!(full.metric, ErrorMetric::Rank);
-        assert!((full.bound.evaluate().unwrap() - 0.04).abs() < f64::EPSILON);
-
-        let subwindow = SummaryWindowAccuracyEvidence::ExponentialHistogram(
-            ExponentialHistogramAccuracyEvidence::KllRank {
-                eh_epsilon: 0.01,
-                kll_epsilon: 0.02,
-                failure_probability: 0.01,
-                range: ExponentialHistogramQueryRange::SubWindow {
-                    suffix_rows: 100,
-                    query_rows: 25,
-                },
-            },
-        )
-        .guarantee(true)
-        .unwrap();
-        assert!((subwindow.bound.evaluate().unwrap() - 0.10).abs() < f64::EPSILON);
-
-        let gsum = SummaryWindowAccuracyEvidence::ExponentialHistogram(
-            ExponentialHistogramAccuracyEvidence::UniversalGsum {
-                epsilon: 0.05,
-                failure_probability: 0.30,
-                range: ExponentialHistogramQueryRange::SubWindow {
-                    suffix_rows: 100,
-                    query_rows: 25,
-                },
-            },
-        )
-        .guarantee(true)
-        .unwrap();
-        assert_eq!(gsum.metric, ErrorMetric::RelativeValue);
-        assert!((gsum.bound.evaluate().unwrap() - 0.20).abs() < f64::EPSILON);
-    }
-
-    #[test]
-    fn eh_accuracy_rejects_negative_components_and_mismatched_summary_guarantees() {
-        let evidence = SummaryWindowAccuracyEvidence::ExponentialHistogram(
-            ExponentialHistogramAccuracyEvidence::KllRank {
-                eh_epsilon: -0.01,
-                kll_epsilon: 0.03,
-                failure_probability: 0.01,
-                range: ExponentialHistogramQueryRange::MostRecentWindow,
-            },
-        );
-        assert!(evidence.guarantee(true).is_none());
-
-        let evidence = SummaryWindowAccuracyEvidence::ExponentialHistogram(
-            ExponentialHistogramAccuracyEvidence::KllRank {
-                eh_epsilon: 0.01,
-                kll_epsilon: 0.02,
-                failure_probability: 0.01,
-                range: ExponentialHistogramQueryRange::MostRecentWindow,
-            },
-        );
-        let actual_summary = ResultGuarantee {
-            metric: ErrorMetric::Rank,
-            bound: BoundExpr::Constant { value: 0.03 },
-            failure_probability: ProbabilityExpr::Constant { value: 0.01 },
-            provenance: vec![],
-        };
-        assert!(evidence
-            .end_to_end_guarantee(true, Some(&actual_summary))
-            .is_none());
-    }
-
-    #[test]
-    fn exponential_histogram_without_registered_accuracy_composition_fails_closed() {
-        let mut workload = streaming_workload();
-        workload.repeating_queries.as_mut().unwrap()[0]
-            .requirements
-            .accuracy =
-            asap_types::workload::AccuracyRequirement::Explicit(AccuracyTarget::Epsilon(1.0));
-        let target = streaming_sum_query();
-        let root = summary_with_operations(false, false, false);
-        let Operator::ASAP(ASAPOp::FinalizeExactAccumulator {
-            child: summary_input,
-        }) = &root.operator
-        else {
-            unreachable!();
-        };
-        let mut model = streaming_model();
-        bind_aggregations(
-            &mut model,
-            &target,
-            &root,
-            streaming_inputs(),
-            streaming_cpu(),
-        );
-        model
-            .bind_window_framework_candidate(
-                &target,
-                &root,
-                SummaryWindowFrameworkCandidate {
-                    physical_plan_id: "invalid-eh".into(),
-                    assignments: vec![SummaryWindowFrameworkAssignment {
-                        summary: Rc::clone(summary_input),
-                        framework: Some(SummaryWindowFramework::ExponentialHistogram),
-                    }],
-                    accuracy: SummaryWindowAccuracyEvidence::Exact,
-                    node_evidence: model.node_evidence.clone(),
-                },
-            )
-            .unwrap();
-
-        let plan = plan_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        assert_eq!(plan.summary_total_cost, None);
-    }
-
-    /// Bulk relational evidence cannot hide summary operators below an ordinary root.
-    #[test]
-    fn retained_subdag_evidence_cannot_hide_summary_work() {
-        let workload = streaming_workload();
-        let target = streaming_sum_query();
-        let root = add_shared_summary_result();
-        let mut model = streaming_model();
-        bind_aggregations(
-            &mut model,
-            &target,
-            &root,
-            streaming_inputs(),
-            streaming_cpu(),
-        );
-        model.node_evidence.insert_retained_query(
-            &root,
-            RetainedSubDAGEvidence {
-                physical_id: "false-retained-root".into(),
-                output: test_edge(),
-                preprocessing_cpu_ops_over_horizon: 0.0,
-                working_memory_bytes: 0,
-                output_buffer_bytes: 0,
-            },
-        );
-        let plan = plan_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        assert_eq!(plan.summary_total_cost, None);
-    }
-
-    #[test]
-    fn whole_dag_fails_closed_for_missing_retained_work_or_false_source_lineage() {
-        let workload = streaming_workload();
-        let target = streaming_sum_query();
-        let root = summary_with_operations(false, false, false);
-        let mut model = streaming_model();
-        bind_aggregations(
-            &mut model,
-            &target,
-            &root,
-            streaming_inputs(),
-            streaming_cpu(),
-        );
-        model.node_evidence.retained_queries.clear();
-        let missing_retained = plan_summary_maintenance_lifecycles(
-            Rc::clone(&root),
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        assert_eq!(missing_retained.summary_total_cost, None);
-
-        bind_comparison(&mut model, &target, &root);
-        model
-            .target_comparisons
-            .get_mut(&Rc::as_ptr(&target))
-            .unwrap()
-            .scope
-            .sources[0]
-            .source = Source::TimeSeries {
-            metric: "other_metric".into(),
-        };
-        let false_lineage = plan_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &model,
-        )
-        .unwrap();
-        assert_eq!(false_lineage.summary_total_cost, None);
-    }
-
-    #[test]
-    fn state_only_needs_no_evaluation_and_summary_merge_child_fails_closed() {
-        // A state-only root is costable without evaluation evidence; a
-        // SummaryAgg over a reserved SummaryMerge is rejected at planning.
-        let workload = streaming_workload();
-        let target = streaming_sum_query();
-        let estimated = summary_with_operations(false, false, false);
-        let state_only = evaluation_state(&estimated);
-        let mut no_evaluation_cpu = streaming_cpu();
-        no_evaluation_cpu.evaluation_cpu_ops = None;
-        let mut state_model = streaming_model();
-        bind_aggregations(
-            &mut state_model,
-            &target,
-            &state_only,
-            streaming_inputs(),
-            no_evaluation_cpu,
-        );
-        let state_plan = plan_summary_maintenance_lifecycles(
-            state_only,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &state_model,
-        )
-        .unwrap();
-        assert!(state_plan.summary_total_cost.is_some());
-
-        let nested = std::rc::Rc::new(
-            OperatorNode::with_schema(
-                asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
-                    child: evaluation_state(&summary_with_operations(true, false, false)),
-                    family: FieldDataType::ExactAggregate(ExactKind::Count, ExactParams::Count),
-                    input: SummaryUpdate {
-                        item: None,
-                        weight: asap_types::post_asap::SummaryInputExpr::Constant(1.0),
-                        weight_domain: Default::default(),
-                    },
-                    reduction: Reduction::by(vec![]),
-                    grouping: GroupingStrategy::PerSubpopulationInstance,
-                    filter: None,
-                }),
-                count_state_schema(),
-            )
-            .with_guarantee(None),
-        );
-        let mut nested_cpu = streaming_cpu();
-        nested_cpu.merge_cpu_ops = Some(1.0);
-        let mut nested_model = streaming_model();
-        bind_aggregations(
-            &mut nested_model,
-            &target,
-            &nested,
-            streaming_inputs(),
-            nested_cpu,
-        );
-        assert!(matches!(
-            streaming_planning_error(nested, &nested_model),
-            asap_types::post_asap::ExecutionDataStateError::UnimplementedOperator {
-                operator: "SummaryMerge"
-            }
-        ));
-    }
-
-    #[test]
-    fn mixed_arrival_fails_closed_until_backlog_and_stream_are_separate() {
-        let data = DataWorkload {
-            arrival: DataArrival::Mixed,
-            ..DataWorkload::default()
-        };
-        let mut scope = streaming_scope();
-        scope.data_arrival = DataArrival::Mixed;
-        assert_eq!(
-            SummaryMaintenanceInputs::from_workload(physical(), &data, &scope),
-            Err(AnalyticalCostError::UnsupportedDataArrival(
-                DataArrival::Mixed
-            ))
-        );
-    }
-
-    #[test]
-    fn direct_read_costs_build_updates_windows_and_recurrence() {
-        let estimate = estimate_test(
-            &summary_with_operations(false, false, false),
-            &continuous_guarantee(),
-            SummaryMaintenanceInputs {
-                initial_input_rows: 10,
-                initial_input_bytes: 640,
-                initial_source_scan_bytes: 640,
-                ingestion_rate_per_second: 2.0,
-                active_window_count: 2,
-                bootstrap_window_count: 1,
-                retained_window_count: 3,
-                physical_summary_count: 2,
-                state_bytes_per_summary: 100,
-            },
-            SummaryOperationCpuEvidence {
-                insert_cpu_ops: Some(2.0),
-                evaluation_cpu_ops: Some(3.0),
-                ..SummaryOperationCpuEvidence::default()
-            },
-        )
-        .unwrap();
-        // 10 bootstrap + 10 arrivals into two active windows; two states read 5 times.
-        assert_eq!(estimate.cpu_ops(), 90.0);
-        assert_eq!(estimate.peak_memory_bytes(), 1_000);
-        assert_eq!(estimate.scan_bytes(), 640);
-    }
-
-    #[test]
-    fn operations_use_update_or_read_multiplicity_and_shared_state_once() {
-        let estimate = estimate_test(
-            &summary_with_operations(true, true, true),
-            &continuous_guarantee(),
-            SummaryMaintenanceInputs {
-                initial_input_rows: 1,
-                initial_input_bytes: 8,
-                initial_source_scan_bytes: 8,
-                ingestion_rate_per_second: 4.0,
-                active_window_count: 1,
-                bootstrap_window_count: 1,
-                retained_window_count: 2,
-                physical_summary_count: 2,
-                state_bytes_per_summary: 10,
-            },
-            SummaryOperationCpuEvidence {
-                insert_cpu_ops: Some(1.0),
-                merge_cpu_ops: Some(2.0),
-                subtract_cpu_ops: Some(3.0),
-                delete_cpu_ops: Some(5.0),
-                delete_events_per_second: Some(4.0),
-                delete_routing_fanout: Some(2),
-                evaluation_cpu_ops: Some(7.0),
-            },
-        )
-        .unwrap();
-        assert_eq!(estimate.cpu_ops(), 21.0 + 20.0 + 30.0 + 200.0 + 70.0);
-        // Three persistent windows plus one transient result, for two instances.
-        assert_eq!(estimate.peak_memory_bytes(), 80);
-    }
-
-    #[test]
-    fn lifecycle_mode_and_schedule_must_match_existing_planner_semantics() {
-        let mut guarantee = continuous_guarantee();
-        guarantee.evaluation_schedule = EvaluationSchedule::OnRead;
-        assert_eq!(
-            estimate_test(
-                &summary_with_operations(false, false, false),
-                &guarantee,
-                SummaryMaintenanceInputs {
-                    initial_input_rows: 1,
-                    initial_input_bytes: 8,
-                    initial_source_scan_bytes: 8,
-                    ingestion_rate_per_second: 1.0,
-                    active_window_count: 1,
-                    bootstrap_window_count: 1,
-                    retained_window_count: 1,
-                    physical_summary_count: 1,
-                    state_bytes_per_summary: 8,
-                },
-                SummaryOperationCpuEvidence {
-                    insert_cpu_ops: Some(1.0),
-                    evaluation_cpu_ops: Some(1.0),
-                    ..SummaryOperationCpuEvidence::default()
-                },
-            ),
-            Err(AnalyticalCostError::IncompatibleLifecycleGuarantee)
-        );
-    }
-
-    #[test]
-    fn missing_cost_for_an_operation_in_the_dag_fails_closed() {
-        assert_eq!(
-            estimate_test(
-                &summary_with_operations(true, false, false),
-                &continuous_guarantee(),
-                SummaryMaintenanceInputs {
-                    initial_input_rows: 1,
-                    initial_input_bytes: 8,
-                    initial_source_scan_bytes: 8,
-                    ingestion_rate_per_second: 1.0,
-                    active_window_count: 1,
-                    bootstrap_window_count: 1,
-                    retained_window_count: 1,
-                    physical_summary_count: 1,
-                    state_bytes_per_summary: 8,
-                },
-                SummaryOperationCpuEvidence {
-                    insert_cpu_ops: Some(1.0),
-                    evaluation_cpu_ops: Some(1.0),
-                    ..SummaryOperationCpuEvidence::default()
-                },
-            ),
-            Err(AnalyticalCostError::MissingOrStale("merge_cpu_ops"))
-        );
-    }
-
-    #[test]
-    fn direct_build_mode_is_not_mispriced_as_incremental_maintenance() {
-        let mut guarantee = continuous_guarantee();
-        guarantee.summary_maintenance_lifecycle = SummaryMaintenanceLifecycle::Ephemeral;
-        guarantee.summary_maintenance_mode = SummaryMaintenanceMode::DirectBuild;
-        guarantee.evaluation_schedule = EvaluationSchedule::OneShot;
-        assert_eq!(
-            estimate_test(
-                &summary_with_operations(false, false, false),
-                &guarantee,
-                SummaryMaintenanceInputs {
-                    initial_input_rows: 1,
-                    initial_input_bytes: 8,
-                    initial_source_scan_bytes: 8,
-                    ingestion_rate_per_second: 1.0,
-                    active_window_count: 1,
-                    bootstrap_window_count: 1,
-                    retained_window_count: 1,
-                    physical_summary_count: 1,
-                    state_bytes_per_summary: 8,
-                },
-                SummaryOperationCpuEvidence {
-                    insert_cpu_ops: Some(1.0),
-                    evaluation_cpu_ops: Some(1.0),
-                    ..SummaryOperationCpuEvidence::default()
-                },
-            ),
-            Err(AnalyticalCostError::IncompatibleLifecycleGuarantee)
-        );
-    }
-
-    #[test]
-    fn prepared_maintenance_charges_only_its_active_interval() {
-        let guarantee = SummaryMaintenanceLifecycleGuarantee {
-            summary_maintenance_lifecycle: SummaryMaintenanceLifecycle::Prepared {
-                activate_at: asap_types::workload::TimestampMs(1_000),
-                retire_at: asap_types::workload::TimestampMs(6_000),
-            },
-            summary_maintenance_mode: SummaryMaintenanceMode::Incremental,
-            evaluation_schedule: EvaluationSchedule::PerUpdate,
-            output_representation: OutputRepresentation::SummaryState,
-        };
-        let estimate = estimate_test(
-            &summary_with_operations(false, false, false),
-            &guarantee,
-            SummaryMaintenanceInputs {
-                initial_input_rows: 10,
-                initial_input_bytes: 80,
-                initial_source_scan_bytes: 80,
-                ingestion_rate_per_second: 2.0,
-                active_window_count: 1,
-                bootstrap_window_count: 1,
-                retained_window_count: 1,
-                physical_summary_count: 1,
-                state_bytes_per_summary: 8,
-            },
-            SummaryOperationCpuEvidence {
-                insert_cpu_ops: Some(1.0),
-                evaluation_cpu_ops: Some(1.0),
-                ..SummaryOperationCpuEvidence::default()
-            },
-        )
-        .unwrap();
-        // Two pre-activation arrivals join the bootstrap; eight more are
-        // maintained through the horizon; five reads are served.
-        assert_eq!(estimate.cpu_ops(), 25.0);
-    }
-
-    #[test]
-    fn shared_retention_is_not_the_comparison_horizon() {
-        let guarantee = SummaryMaintenanceLifecycleGuarantee {
-            summary_maintenance_lifecycle: SummaryMaintenanceLifecycle::Shared {
-                retention: asap_types::workload::DurationMs(999),
-            },
-            summary_maintenance_mode: SummaryMaintenanceMode::Incremental,
-            evaluation_schedule: EvaluationSchedule::PerUpdate,
-            output_representation: OutputRepresentation::SummaryState,
-        };
-        assert!(estimate_test(
-            &summary_with_operations(false, false, false),
-            &guarantee,
-            SummaryMaintenanceInputs {
-                initial_input_rows: 1,
-                initial_input_bytes: 8,
-                initial_source_scan_bytes: 8,
-                ingestion_rate_per_second: 1.0,
-                active_window_count: 1,
-                bootstrap_window_count: 1,
-                retained_window_count: 1,
-                physical_summary_count: 1,
-                state_bytes_per_summary: 8,
-            },
-            SummaryOperationCpuEvidence {
-                insert_cpu_ops: Some(1.0),
-                evaluation_cpu_ops: Some(1.0),
-                ..SummaryOperationCpuEvidence::default()
-            },
-        )
-        .is_ok());
-    }
-
-    #[test]
-    fn lifecycle_retention_rate_integrates_to_one_peak_capacity_charge() {
-        let target = streaming_sum_query();
-        let root = summary_with_operations(false, false, false);
-        let mut model = streaming_model();
-        bind_aggregations(
-            &mut model,
-            &target,
-            &root,
-            streaming_inputs(),
-            streaming_cpu(),
-        );
-        let aggregation = evidence_nodes(&root).0[0];
-        let inputs = model
-            .lifecycle_inputs(aggregation, Some(Horizon(5.0)))
-            .unwrap();
-        let integrated = inputs.retention_cost_rate.unwrap().0 * 5.0;
-        // (2 active + 3 retained) * 2 states * 100 bytes, calibrated once.
-        assert_eq!(integrated, 1_000.0);
-    }
-
-    #[test]
-    fn summary_join_requires_cardinality_and_working_memory_evidence() {
-        let joined = summary_join();
-        let inputs = SummaryMaintenanceInputs {
-            initial_input_rows: 1,
-            initial_input_bytes: 8,
-            initial_source_scan_bytes: 8,
-            ingestion_rate_per_second: 1.0,
-            active_window_count: 1,
-            bootstrap_window_count: 1,
-            retained_window_count: 1,
-            physical_summary_count: 1,
-            state_bytes_per_summary: 8,
-        };
-        let cpu = SummaryOperationCpuEvidence {
-            insert_cpu_ops: Some(1.0),
-            evaluation_cpu_ops: Some(1.0),
-            ..SummaryOperationCpuEvidence::default()
-        };
-        assert_eq!(
-            estimate_join_test(&joined, &continuous_guarantee(), inputs, cpu, None,),
-            Err(AnalyticalCostError::MissingOrStale("summary_join"))
-        );
-        let estimate = estimate_join_test(
-            &joined,
-            &continuous_guarantee(),
-            inputs,
-            cpu,
-            Some(SummaryJoinEvidence {
-                physical_id: "diagnostic-join".into(),
-                inputs: vec![test_edge(), test_edge()],
-                output: test_edge(),
-                cpu_ops_per_execution: 12.0,
-                working_memory_bytes: 32,
-                output_buffer_bytes: 0,
-                executions_per_evaluation: 1,
-                io_bytes_per_execution: Some(0),
-            }),
-        )
-        .unwrap();
-        assert_eq!(estimate.cpu_ops(), 77.0);
-        assert_eq!(estimate.peak_memory_bytes(), 64); // 4 persistent states + join memory.
-    }
-
-    fn count_state_schema() -> Schema {
-        Schema::lifted(
-            vec![Field::new(
-                "count",
-                FieldDataType::ExactAggregate(ExactKind::Count, ExactParams::Count),
-                false,
-            )],
-            None,
-        )
-    }
-
-    fn count_evaluation_schema() -> Schema {
-        Schema::lifted(vec![Field::plain("count", DataType::Int64, false)], None)
-    }
-
-    /// The retained relational input of every test summary: a bare scan of
-    /// the `metrics` series.
-    fn metrics_scan() -> Rc<OperatorNode> {
-        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
-            source: Source::TimeSeries {
-                metric: "metrics".into(),
-            },
-            predicates: vec![],
-            schema: Schema::with_time_index(
-                vec![
-                    Field::plain("ts", DataType::Timestamp, false),
-                    Field::plain("value", DataType::Float64, false),
-                ],
-                0,
-                vec![],
-            ),
-        }))
-        .unwrap()
-    }
-
-    fn summary_with_operations(merge: bool, subtract: bool, delete: bool) -> Rc<OperatorNode> {
-        let state_type = FieldDataType::ExactAggregate(ExactKind::Count, ExactParams::Count);
-        let schema = count_state_schema();
-        let child = metrics_scan();
-        let coverage = crate::replacement::whole_source_coverage(&child).unwrap();
-        let agg = std::rc::Rc::new(
-            OperatorNode::with_schema(
-                asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
-                    child,
-                    family: state_type,
-                    input: SummaryUpdate {
-                        item: None,
-                        weight: asap_types::post_asap::SummaryInputExpr::Constant(1.0),
-                        weight_domain: Default::default(),
-                    },
-                    reduction: Reduction::by(vec![]),
-                    grouping: GroupingStrategy::PerSubpopulationInstance,
-                    filter: None,
-                }),
-                schema.clone(),
-            )
-            .with_guarantee(None)
-            .with_coverage(coverage)
-            .unwrap(),
-        );
-        let mut root = Rc::clone(&agg);
-        if merge {
-            root = std::rc::Rc::new(
-                OperatorNode::with_schema(
-                    asap_types::ir::Operator::ASAP(ASAPOp::SummaryMerge {
-                        children: vec![Rc::clone(&agg), Rc::clone(&agg)],
-                    }),
-                    schema.clone(),
-                )
-                .with_guarantee(None),
-            );
-        }
-        if subtract {
-            root = std::rc::Rc::new(
-                OperatorNode::with_schema(
-                    asap_types::ir::Operator::ASAP(ASAPOp::SummarySubtract {
-                        left: Rc::clone(&root),
-                        right: Rc::clone(&agg),
-                    }),
-                    schema.clone(),
-                )
-                .with_guarantee(None),
-            );
-        }
-        if delete {
-            root = std::rc::Rc::new(
-                OperatorNode::with_schema(
-                    asap_types::ir::Operator::ASAP(ASAPOp::SummaryDelete {
-                        summary_input: root,
-                        key: 0,
-                    }),
-                    schema.clone(),
-                )
-                .with_guarantee(None),
-            );
-        }
-        std::rc::Rc::new(
-            OperatorNode::with_schema(
-                asap_types::ir::Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child: root }),
-                count_evaluation_schema(),
-            )
-            .with_guarantee(Some(ResultGuarantee::exact("exact count evaluation"))),
-        )
-    }
-
-    fn summary_join() -> Rc<OperatorNode> {
-        let left = summary_with_operations(false, false, false);
-        let right = summary_with_operations(false, false, false);
-        let Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child: left }) = &left.operator
-        else {
-            unreachable!()
-        };
-        let Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child: right }) = &right.operator
-        else {
-            unreachable!()
-        };
-        let join = std::rc::Rc::new(
-            OperatorNode::with_schema(
-                asap_types::ir::Operator::ASAP(ASAPOp::SummaryJoin {
-                    outer: Rc::clone(left),
-                    inner: Rc::clone(right),
-                    key: 0,
-                    family: FieldDataType::ExactAggregate(ExactKind::Count, ExactParams::Count),
-                }),
-                left.schema.clone(),
-            )
-            .with_guarantee(None),
-        );
-        std::rc::Rc::new(
-            OperatorNode::with_schema(
-                asap_types::ir::Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child: join }),
-                count_evaluation_schema(),
-            )
-            .with_guarantee(None),
-        )
-    }
-
-    fn add_shared_summary_result() -> Rc<OperatorNode> {
-        let operand = summary_with_operations(false, false, false);
-        Rc::new(
-            OperatorNode::new(Operator::NonASAP(NonASAPOp::BinaryOp {
-                operator: BinaryOperator {
-                    checked_relative_division: false,
-                    checked_finite_division: false,
-                    kind: BinaryOpKind::Arithmetic(ArithmeticOpKind::Add),
-                    vector_match: None,
-                },
-                return_bool: false,
-                lhs: Rc::clone(&operand),
-                rhs: operand,
-            }))
-            .unwrap()
-            .with_guarantee(Some(ResultGuarantee::exact("test binary"))),
-        )
-    }
-
-    /// Two independent summary states, each read out, combined by an ordinary
-    /// `BinaryOp`: the non-reserved replacement for a `SummaryJoin` fixture.
-    #[test]
-    fn independent_summary_results_form_a_valid_dag() {
-        add_independent_summary_results()
-            .validate_structure()
-            .unwrap();
-    }
-
-    fn add_independent_summary_results() -> Rc<OperatorNode> {
-        Rc::new(
-            OperatorNode::new(Operator::NonASAP(NonASAPOp::BinaryOp {
-                operator: BinaryOperator {
-                    checked_relative_division: false,
-                    checked_finite_division: false,
-                    kind: BinaryOpKind::Arithmetic(ArithmeticOpKind::Add),
-                    vector_match: None,
-                },
-                return_bool: false,
-                lhs: summary_with_operations(false, false, false),
-                rhs: summary_with_operations(false, false, false),
-            }))
-            .unwrap()
-            .with_guarantee(Some(ResultGuarantee::exact("test binary"))),
-        )
-    }
-
-    /// The `(lhs, rhs)` evaluations of [`add_independent_summary_results`].
-    fn binary_operands(root: &OperatorNode) -> (Rc<OperatorNode>, Rc<OperatorNode>) {
-        let Operator::NonASAP(NonASAPOp::BinaryOp { lhs, rhs, .. }) = &root.operator else {
-            unreachable!();
-        };
-        (Rc::clone(lhs), Rc::clone(rhs))
-    }
-
-    /// The `SummaryAgg` under one `SummaryEstimate` evaluation.
-    fn evaluation_state(evaluation: &OperatorNode) -> Rc<OperatorNode> {
-        let Operator::ASAP(ASAPOp::FinalizeExactAccumulator {
-            child: summary_input,
-        }) = &evaluation.operator
-        else {
-            unreachable!();
-        };
-        Rc::clone(summary_input)
-    }
-
-    /// The DAG-validation error that streaming lifecycle planning of `root`
-    /// fails closed with.
-    fn streaming_planning_error(
-        root: Rc<OperatorNode>,
-        model: &SummaryMaintenanceCostModel,
-    ) -> asap_types::post_asap::ExecutionDataStateError {
-        let workload = streaming_workload();
-        match plan_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            model,
-        ) {
-            Err(
-                crate::summary_maintenance_lifecycle::SummaryMaintenanceLifecyclePlanError::InvalidPostAsapDAG(
-                    error,
-                ),
-            ) => error,
-            Err(other) => panic!("unexpected planning error: {other}"),
-            Ok(_) => panic!("planning must fail closed"),
-        }
-    }
-
-    fn test_resource(
-        physical_id: &str,
-        inputs: Vec<EdgeStatistics>,
-        cpu_ops: f64,
-        working_memory_bytes: u64,
-        output_buffer_bytes: u64,
-    ) -> SummaryOperatorResourceEvidence {
-        SummaryOperatorResourceEvidence {
-            physical_id: physical_id.into(),
-            inputs,
-            output: test_edge(),
-            cpu_ops,
-            working_memory_bytes,
-            output_buffer_bytes,
-            executions_per_evaluation: 1,
-            io_bytes_per_execution: Some(0),
-        }
-    }
-
-    #[test]
-    fn exact_binary_is_costable_with_explicit_physical_evidence() {
-        let workload = streaming_workload();
-        let target = streaming_sum_query();
-        let root = add_shared_summary_result();
-        let mut model = streaming_model();
-        bind_aggregations(
-            &mut model,
-            &target,
-            &root,
-            streaming_inputs(),
-            streaming_cpu(),
-        );
-
-        let plan = plan_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(&workload, &streaming_data_workload(), &[0]),
-            0,
-            Some(Horizon(5.0)),
-            SummaryMaintenanceLifecycleCapabilities {
-                supports_ephemeral: true,
-                supports_prepared: false,
-                supports_shared: false,
-                supports_continuously_maintained: false,
-            },
-            &model,
-        )
-        .expect("binary physical evidence should produce a complete cost");
-        assert!(plan.summary_total_cost.is_some());
-    }
-
-    fn streaming_sum_query() -> Rc<OperatorNode> {
-        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
-            reduction: Reduction::by(vec![]),
-            measures: vec![AggIntent::Sum { col: None }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: metrics_scan(),
-        }))
-        .unwrap()
-    }
-
-    fn streaming_workload() -> QueryWorkload {
-        QueryWorkload {
-            language: QueryLanguage::PromQL,
-            query_batch: None,
-            repeating_queries: Some(vec![RepeatingEntry {
-                query: Query("sum(metrics)".into()),
-                demand: RepeatedDemand::FixedInterval(RepetitionInterval(1_000)),
-                requirements: QueryRequirements::default(),
-                predictability: Predictability::Predictable { known_at: None },
-                time_selection: TimeSelection::default(),
-            }]),
-        }
-    }
-
-    fn streaming_data_workload() -> DataWorkload {
-        DataWorkload {
-            arrival: DataArrival::ContinuouslyIngesting,
-            data_ingestion_interval: Evidence {
-                value: Some(asap_types::workload::DurationMs(1_000)),
-                ..Default::default()
-            },
-            ingestion_rate: Evidence {
-                value: Some(Rate(2.0)),
-                source: EvidenceSource::Declared,
-                observed_at_ms: None,
-                valid_for_ms: None,
-            },
-            ..Default::default()
-        }
-    }
-
-    fn streaming_model() -> SummaryMaintenanceCostModel {
-        SummaryMaintenanceCostModel::new(
-            ResourceCalibration {
-                cost_per_cpu_op: 1.0,
-                cost_per_scan_byte: 1.0,
-                cost_per_retained_byte: 1.0,
-                version: "test".into(),
-            },
-            SummaryMaintenanceCapabilities {
-                incremental_update: true,
-                merge: false,
-                delete: false,
-            },
-        )
-    }
-
-    fn streaming_raw() -> RawInputEvidence {
-        let scope = streaming_scope();
-        let node = PhysicalDAGNode {
-            id: "raw-scan".into(),
-            operator: PhysicalOperator::Scan,
-            children: vec![],
-            scan_selection: Some(scope.sources[0].clone()),
-            output_buffer_bytes: 0,
-            retained_bytes: 0,
-            execution: ExecutionMultiplicity::Once,
-        };
-        let edge = EdgeStatistics {
-            rows: 80,
-            bytes: 5_120,
-        };
-        let statistics = OperatorStatistics::Scan {
-            source_read_bytes: 5_120,
-            edges: UnaryEdgeStatistics {
-                input: edge,
-                output: edge,
-                promql: None,
-            },
-        };
-        RawInputEvidence {
-            planning_time_input_rows: 10,
-            planning_time_input_bytes: 640,
-            planning_time_source_scan_bytes: 640,
-            arriving_logical_row_bytes: 64,
-            arriving_source_row_bytes: 64,
-            ingestion_rate_per_second: 2.0,
-            physical_dag: EvidenceBackedPhysicalDAG {
-                nodes: vec![node],
-                root: "raw-scan".into(),
-                evidence: HashMap::from([(
-                    "raw-scan".into(),
-                    PhysicalNodeEvidence {
-                        physical_id: "raw-scan".into(),
-                        statistics,
-                        output_buffer_bytes: 0,
-                    },
-                )]),
-            },
-        }
-    }
-
-    /// A retained relational sub-DAG: a non-ASAP node with no summary below
-    /// it, costed as one unit through retained-query evidence.
-    fn is_retained(node: &OperatorNode) -> bool {
-        !node.contains_asap()
-    }
-
-    fn bind_comparison(
-        model: &mut SummaryMaintenanceCostModel,
-        target: &Rc<OperatorNode>,
-        root: &Rc<OperatorNode>,
-    ) {
-        model
-            .bind_candidate_comparison(target, root, streaming_scope(), streaming_raw())
-            .unwrap();
-        fn retained(
-            model: &mut SummaryMaintenanceCostModel,
-            node: &Rc<OperatorNode>,
-            seen: &mut HashSet<*const OperatorNode>,
-        ) {
-            if !seen.insert(Rc::as_ptr(node)) {
-                return;
-            }
-            if is_retained(node) {
-                model.node_evidence.insert_retained_query(
-                    node,
-                    RetainedSubDAGEvidence {
-                        physical_id: format!("retained-{node:p}"),
-                        output: test_edge(),
-                        preprocessing_cpu_ops_over_horizon: 1.0,
-                        working_memory_bytes: 8,
-                        output_buffer_bytes: 0,
-                    },
-                );
-                return;
-            }
-            for child in node.children() {
-                retained(model, child, seen);
-            }
-        }
-        retained(model, root, &mut HashSet::new());
-    }
-
-    fn streaming_inputs() -> SummaryMaintenanceInputs {
-        SummaryMaintenanceInputs {
-            initial_input_rows: 10,
-            initial_input_bytes: 640,
-            initial_source_scan_bytes: 640,
-            ingestion_rate_per_second: 2.0,
-            active_window_count: 2,
-            bootstrap_window_count: 1,
-            retained_window_count: 3,
-            physical_summary_count: 2,
-            state_bytes_per_summary: 100,
-        }
-    }
-
-    fn test_edge() -> EdgeStatistics {
-        EdgeStatistics { rows: 1, bytes: 8 }
-    }
-
-    fn streaming_cpu() -> SummaryOperationCpuEvidence {
-        SummaryOperationCpuEvidence {
-            insert_cpu_ops: Some(2.0),
-            evaluation_cpu_ops: Some(3.0),
-            ..SummaryOperationCpuEvidence::default()
-        }
-    }
-
-    fn bind_aggregations(
-        model: &mut SummaryMaintenanceCostModel,
-        target: &Rc<OperatorNode>,
-        root: &Rc<OperatorNode>,
-        inputs: SummaryMaintenanceInputs,
-        cpu: SummaryOperationCpuEvidence,
-    ) {
-        bind_comparison(model, target, root);
-        for node in evidence_nodes(root).0 {
-            let source_root = matches!(
-                &node.operator,
-                Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) if is_retained(child)
-            );
-            let mut node_inputs = inputs;
-            if !source_root {
-                node_inputs.initial_input_rows = test_edge().rows;
-                node_inputs.initial_input_bytes = test_edge().bytes;
-                node_inputs.initial_source_scan_bytes = 0;
-            }
-            model.node_evidence.aggregations.insert(
-                node as *const _,
-                SummaryAggregateEvidence {
-                    physical_id: format!("agg-{node:p}"),
-                    input: test_edge(),
-                    output: test_edge(),
-                    scan_selection_index: source_root.then_some(0),
-                    bootstrap_read_identity: if source_root {
-                        "shared-bootstrap".into()
-                    } else {
-                        String::new()
-                    },
-                    inputs: node_inputs,
-                    insert_cpu_ops: cpu.insert_cpu_ops.unwrap(),
-                },
-            );
-        }
-        fn resource(
-            physical_id: String,
-            inputs: Vec<EdgeStatistics>,
-            cpu_ops: f64,
-            working_memory_bytes: u64,
-        ) -> SummaryOperatorResourceEvidence {
-            SummaryOperatorResourceEvidence {
-                physical_id,
-                inputs,
-                output: test_edge(),
-                cpu_ops,
-                working_memory_bytes,
-                output_buffer_bytes: 0,
-                executions_per_evaluation: 1,
-                io_bytes_per_execution: Some(0),
-            }
-        }
-        fn bind_ops(
-            model: &mut SummaryMaintenanceCostModel,
-            node: &OperatorNode,
-            seen: &mut HashSet<*const OperatorNode>,
-            inputs: SummaryMaintenanceInputs,
-            cpu: SummaryOperationCpuEvidence,
-        ) {
-            if !seen.insert(node as *const _) {
-                return;
-            }
-            if is_retained(node) {
-                return;
-            }
-            let operation = match &node.operator {
-                Operator::NonASAP(NonASAPOp::BinaryOp { .. }) => {
-                    cpu.evaluation_cpu_ops.map(|cpu_ops| {
-                        SummaryOperatorEvidence::Binary(resource(
-                            format!("binary-{node:p}"),
-                            vec![test_edge(), test_edge()],
-                            cpu_ops,
-                            0,
-                        ))
-                    })
-                }
-                Operator::NonASAP(NonASAPOp::Join { .. }) => None,
-                Operator::NonASAP(_)
-                | Operator::ASAP(
-                    ASAPOp::FinalizeExactAccumulator { .. }
-                    | ASAPOp::MaintainPopulation { .. }
-                    | ASAPOp::EvaluatePopulation { .. },
-                ) => cpu.evaluation_cpu_ops.map(|cpu_ops| {
-                    SummaryOperatorEvidence::ValueOperation(resource(
-                        format!("value-operation-{node:p}"),
-                        vec![test_edge()],
-                        cpu_ops,
-                        0,
-                    ))
-                }),
-                Operator::ASAP(ASAPOp::SummaryMerge { children }) => {
-                    cpu.merge_cpu_ops.map(|cpu_ops| {
-                        SummaryOperatorEvidence::Merge(resource(
-                            format!("merge-{node:p}"),
-                            vec![test_edge(); children.len()],
-                            cpu_ops,
-                            inputs.state_bytes_per_summary,
-                        ))
-                    })
-                }
-                Operator::ASAP(ASAPOp::SummarySubtract { .. }) => {
-                    cpu.subtract_cpu_ops.map(|cpu_ops| {
-                        SummaryOperatorEvidence::Subtract(resource(
-                            format!("subtract-{node:p}"),
-                            vec![test_edge(), test_edge()],
-                            cpu_ops,
-                            inputs.state_bytes_per_summary,
-                        ))
-                    })
-                }
-                Operator::ASAP(ASAPOp::SummaryDelete { .. }) => {
-                    cpu.delete_cpu_ops.and_then(|cpu_ops| {
-                        Some(SummaryOperatorEvidence::Delete {
-                            resource: resource(
-                                format!("delete-{node:p}"),
-                                vec![test_edge()],
-                                cpu_ops,
-                                0,
-                            ),
-                            events_per_second: cpu.delete_events_per_second?,
-                            routing_fanout: cpu.delete_routing_fanout?,
-                        })
-                    })
-                }
-                Operator::ASAP(ASAPOp::SummaryEstimate { .. }) => {
-                    cpu.evaluation_cpu_ops.map(|cpu_ops| {
-                        SummaryOperatorEvidence::Evaluation(resource(
-                            format!("evaluation-{node:p}"),
-                            vec![test_edge()],
-                            cpu_ops,
-                            0,
-                        ))
-                    })
-                }
-                Operator::ASAP(
-                    ASAPOp::SummaryAgg { .. }
-                    | ASAPOp::SummaryJoin { .. }
-                    | ASAPOp::Extension { .. },
-                ) => None,
-            };
-            if let Some(operation) = operation {
-                model
-                    .node_evidence
-                    .operations
-                    .insert(node as *const _, operation);
-                if let Operator::ASAP(ASAPOp::SummaryDelete { summary_input, .. }) = &node.operator
-                {
-                    fn owning_aggs(
-                        node: &OperatorNode,
-                        seen: &mut HashSet<*const OperatorNode>,
-                        owners: &mut Vec<*const OperatorNode>,
-                    ) {
-                        if !seen.insert(node as *const _) {
-                            return;
-                        }
-                        if matches!(node.operator, Operator::ASAP(ASAPOp::SummaryAgg { .. })) {
-                            owners.push(node as *const _);
-                        }
-                        for child in node.children() {
-                            owning_aggs(child, seen, owners);
-                        }
-                    }
-                    let mut owners = Vec::new();
-                    owning_aggs(summary_input, &mut HashSet::new(), &mut owners);
-                    owners.sort_unstable();
-                    owners.dedup();
-                    if let [owner] = owners.as_slice() {
-                        model
-                            .node_evidence
-                            .operation_state_owners
-                            .insert(node as *const _, *owner);
-                    }
-                }
-            }
-            for child in node.children() {
-                bind_ops(model, child, seen, inputs, cpu);
-            }
-        }
-        bind_ops(model, root, &mut HashSet::new(), inputs, cpu);
-    }
-
-    fn streaming_scope() -> ComparisonScope {
-        let workload = streaming_workload();
-        let entry = workload.entries().next().unwrap();
-        ComparisonScope::from_workload(
-            &DataWorkload {
-                arrival: DataArrival::ContinuouslyIngesting,
-                data_ingestion_interval: Evidence {
-                    value: Some(asap_types::workload::DurationMs(1_000)),
-                    ..Default::default()
-                },
-                ingestion_rate: Evidence {
-                    value: Some(Rate(2.0)),
-                    source: EvidenceSource::Declared,
-                    observed_at_ms: None,
-                    valid_for_ms: None,
-                },
-                ..Default::default()
-            },
-            &entry,
-            asap_types::workload::TimestampMs(0),
-            asap_types::workload::DurationMs(5_000),
-            vec![crate::physical_operator_statistics::ScanSelection {
-                source: Source::TimeSeries {
-                    metric: "metrics".into(),
-                },
-                source_snapshot_id: "stream-start".into(),
-                predicates: vec![],
-                info_matchers: vec![],
-            }],
-        )
-        .unwrap()
-    }
-}
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_cost/window.rs b/crates/asap-aware-mapping/src/summary_maintenance_cost/window.rs
deleted file mode 100644
index fb80d5ee0..000000000
--- a/crates/asap-aware-mapping/src/summary_maintenance_cost/window.rs
+++ /dev/null
@@ -1,252 +0,0 @@
-use super::*;
-
-/// One per-state window choice within a complete Planner candidate.
-#[derive(Debug, Clone)]
-pub struct SummaryWindowFrameworkAssignment {
-    pub summary: Rc<OperatorNode>,
-    /// `None` explicitly means that this state is not window-organized.
-    pub framework: Option<SummaryWindowFramework>,
-}
-
-/// Cost evidence for one complete abstract window-framework assignment across
-/// a summary DAG in Planner search.
-///
-/// The provider derives this evidence from a concrete downstream
-/// implementation under the current data workload. The stable identity is
-/// provenance for the chosen implementation, while deployment placement and
-/// runtime configuration remain downstream concerns.
-#[derive(Debug, Clone)]
-pub struct SummaryWindowFrameworkCandidate {
-    /// Stable identity of the complete provider implementation whose evidence
-    /// is bound to this planner-visible framework assignment.
-    pub physical_plan_id: String,
-    /// Exactly one assignment for every summary deployment in the DAG.
-    pub assignments: Vec<SummaryWindowFrameworkAssignment>,
-    /// Registered end-to-end accuracy composition for this complete window
-    /// assignment. EH combinations must use one of the specialized proofs;
-    /// unknown combinations fail closed.
-    pub accuracy: SummaryWindowAccuracyEvidence,
-    pub node_evidence: SummaryNodeEvidence,
-}
-
-pub(super) fn summary_aggregation_identities(root: &OperatorNode) -> HashSet<*const OperatorNode> {
-    fn visit(
-        node: &OperatorNode,
-        seen: &mut HashSet<*const OperatorNode>,
-        out: &mut HashSet<*const OperatorNode>,
-    ) {
-        if !seen.insert(node as *const _) {
-            return;
-        }
-        if matches!(node.operator, Operator::ASAP(ASAPOp::SummaryAgg { .. })) {
-            out.insert(node as *const _);
-        }
-        for child in node.children() {
-            visit(child, seen, out);
-        }
-    }
-
-    let mut out = HashSet::new();
-    visit(root, &mut HashSet::new(), &mut out);
-    out
-}
-
-/// Cardinality normalization used by the PromSketch EH bounds. The paper's
-/// sub-window error is stated relative to the suffix beginning at the query's
-/// left endpoint, so a query-relative bound needs `suffix_rows/query_rows`.
-#[derive(Debug, Clone, Copy, PartialEq)]
-pub enum ExponentialHistogramQueryRange {
-    MostRecentWindow,
-    SubWindow { suffix_rows: u64, query_rows: u64 },
-}
-
-/// Registered accuracy compositions for Exponential Histogram realizations.
-#[derive(Debug, Clone, Copy, PartialEq)]
-pub enum ExponentialHistogramAccuracyEvidence {
-    /// PromSketch EHKLL normalized rank error.
-    KllRank {
-        eh_epsilon: f64,
-        kll_epsilon: f64,
-        failure_probability: f64,
-        range: ExponentialHistogramQueryRange,
-    },
-    /// PromSketch EHUniv/GSum relative error.
-    UniversalGsum {
-        epsilon: f64,
-        failure_probability: f64,
-        range: ExponentialHistogramQueryRange,
-    },
-}
-
-#[derive(Debug, Clone, PartialEq)]
-pub enum SummaryWindowAccuracyEvidence {
-    /// The window implementation preserves exact query-time coverage and adds
-    /// no error. Used for exact tumbling/sliding realizations.
-    Exact,
-    ExponentialHistogram(ExponentialHistogramAccuracyEvidence),
-}
-
-impl ExponentialHistogramQueryRange {
-    fn suffix_to_query_ratio(self) -> Option<f64> {
-        match self {
-            Self::MostRecentWindow => Some(1.0),
-            Self::SubWindow {
-                suffix_rows,
-                query_rows,
-            } if query_rows > 0 && suffix_rows >= query_rows => {
-                Some(suffix_rows as f64 / query_rows as f64)
-            }
-            Self::SubWindow { .. } => None,
-        }
-    }
-}
-
-impl SummaryWindowAccuracyEvidence {
-    pub(super) fn matches_assignments(
-        &self,
-        assignments: &[SummaryWindowFrameworkAssignment],
-    ) -> bool {
-        let eh_summaries: Vec<_> = assignments
-            .iter()
-            .filter(|assignment| {
-                assignment.framework == Some(SummaryWindowFramework::ExponentialHistogram)
-            })
-            .collect();
-        match self {
-            Self::Exact => eh_summaries.is_empty(),
-            Self::ExponentialHistogram(ExponentialHistogramAccuracyEvidence::KllRank {
-                ..
-            }) => {
-                eh_summaries.len() == 1
-                    && eh_summaries.iter().all(|assignment| {
-                        matches!(
-                            &assignment.summary.operator,
-                            Operator::ASAP(ASAPOp::SummaryAgg {
-                                family: FieldDataType::Sketch(kind, _),
-                                ..
-                            }) if kind.algorithm() == &SketchAlgorithm::Kll
-                        )
-                    })
-            }
-            Self::ExponentialHistogram(ExponentialHistogramAccuracyEvidence::UniversalGsum {
-                ..
-            }) => {
-                eh_summaries.len() == 1
-                    && eh_summaries.iter().all(|assignment| {
-                        matches!(
-                            &assignment.summary.operator,
-                            Operator::ASAP(ASAPOp::SummaryAgg {
-                                family: FieldDataType::ExactAggregate(
-                                    ExactKind::Count | ExactKind::Sum,
-                                    _
-                                ),
-                                ..
-                            })
-                        )
-                    })
-            }
-        }
-    }
-
-    /// Compose the two EH combinations proved by PromSketch
-    /// (doi:10.14778/3742728.3742732). Unknown EH combinations deliberately
-    /// have no catch-all arm.
-    pub(super) fn guarantee(&self, uses_exponential_histogram: bool) -> Option<ResultGuarantee> {
-        match self {
-            Self::Exact if !uses_exponential_histogram => {
-                Some(ResultGuarantee::exact("exact window coverage"))
-            }
-            Self::Exact => None,
-            Self::ExponentialHistogram(evidence) if uses_exponential_histogram => {
-                let (metric, bound, failure_probability, rule) = match *evidence {
-                    ExponentialHistogramAccuracyEvidence::KllRank {
-                        eh_epsilon,
-                        kll_epsilon,
-                        failure_probability,
-                        range,
-                    } => {
-                        if !eh_epsilon.is_finite()
-                            || eh_epsilon < 0.0
-                            || !kll_epsilon.is_finite()
-                            || kll_epsilon < 0.0
-                        {
-                            return None;
-                        }
-                        (
-                            ErrorMetric::Rank,
-                            2.0 * eh_epsilon * range.suffix_to_query_ratio()? + kll_epsilon,
-                            failure_probability,
-                            "promsketch_eh_kll_rank",
-                        )
-                    }
-                    ExponentialHistogramAccuracyEvidence::UniversalGsum {
-                        epsilon,
-                        failure_probability,
-                        range,
-                    } => {
-                        if !epsilon.is_finite() || epsilon < 0.0 {
-                            return None;
-                        }
-                        (
-                            ErrorMetric::RelativeValue,
-                            epsilon * range.suffix_to_query_ratio()?,
-                            failure_probability,
-                            "promsketch_eh_universal_gsum",
-                        )
-                    }
-                };
-                if !bound.is_finite()
-                    || bound < 0.0
-                    || !failure_probability.is_finite()
-                    || !(0.0..=1.0).contains(&failure_probability)
-                {
-                    return None;
-                }
-                Some(ResultGuarantee {
-                    metric,
-                    bound: BoundExpr::Constant { value: bound },
-                    failure_probability: ProbabilityExpr::Constant {
-                        value: failure_probability,
-                    },
-                    provenance: vec![GuaranteeSource::RuntimeObservation {
-                        source: rule.into(),
-                        detail: serde_json::json!({
-                            "reference": "doi:10.14778/3742728.3742732"
-                        }),
-                    }],
-                })
-            }
-            Self::ExponentialHistogram(_) => None,
-        }
-    }
-
-    pub(super) fn end_to_end_guarantee(
-        &self,
-        uses_exponential_histogram: bool,
-        summary_guarantee: Option<&ResultGuarantee>,
-    ) -> Option<ResultGuarantee> {
-        let summary = summary_guarantee?;
-        match self {
-            Self::Exact if !uses_exponential_histogram => Some(summary.clone()),
-            Self::ExponentialHistogram(ExponentialHistogramAccuracyEvidence::KllRank {
-                kll_epsilon,
-                failure_probability,
-                ..
-            }) if uses_exponential_histogram => {
-                let summary_bound = summary.bound.evaluate()?;
-                let summary_failure = summary.failure_probability.evaluate()?;
-                if summary.metric != ErrorMetric::Rank
-                    || summary_bound != *kll_epsilon
-                    || summary_failure != *failure_probability
-                {
-                    return None;
-                }
-                self.guarantee(true)
-            }
-            Self::ExponentialHistogram(ExponentialHistogramAccuracyEvidence::UniversalGsum {
-                ..
-            }) if uses_exponential_histogram && summary.is_exact() => self.guarantee(true),
-            _ => None,
-        }
-    }
-}
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_dag_export.rs b/crates/asap-aware-mapping/src/summary_maintenance_dag_export.rs
deleted file mode 100644
index eae562c59..000000000
--- a/crates/asap-aware-mapping/src/summary_maintenance_dag_export.rs
+++ /dev/null
@@ -1,132 +0,0 @@
-//! Serializable DAG export for a materialized summary-maintenance plan.
-//!
-//! `asap-types::dag_export` owns the crate-neutral post-ASAP DAG shape. This
-//! adapter lives in the mapping layer, where summary-maintenance lifecycle
-//! alternatives and their typed rejection reasons are available, and emits
-//! both views together.
-
-use std::collections::HashMap;
-use std::rc::Rc;
-
-use asap_types::ir::OperatorNode;
-use serde::Serialize;
-
-use asap_types::dag_export::{self, SummaryDAG};
-use asap_types::ir::export::PhysicalASAPNodeId;
-use asap_types::post_asap::{
-    ResultGuarantee, SummaryMaintenanceLifecycle, SummaryMaintenanceLifecycleGuarantee,
-    SummaryWindowFramework,
-};
-
-use crate::summary_maintenance_lifecycle::{
-    SummaryMaintenanceLifecyclePlan, SummaryMaintenanceLifecycleRejection,
-};
-
-#[derive(Debug, Clone, Serialize)]
-pub struct SummaryMaintenanceDAGExport {
-    pub dag: SummaryDAG,
-    pub deployments: Vec<SummaryMaintenanceDeploymentExport>,
-    pub horizon_seconds: Option<f64>,
-    pub evaluation_rate_per_second: Option<f64>,
-    pub update_rate_per_second: Option<f64>,
-    pub expected_reads: Option<f64>,
-    pub selected_raw_recompute: bool,
-    #[serde(skip_serializing_if = "Option::is_none")]
-    /// Provider implementation key. The legacy JSON field name is retained
-    /// until the surrounding export receives its own schema-version bump.
-    #[serde(rename = "selected_physical_plan_id")]
-    pub selected_window_implementation_id: Option<String>,
-    pub summary_total_cost: Option<f64>,
-    #[serde(skip_serializing_if = "Option::is_none")]
-    pub window_accuracy_guarantee: Option<ResultGuarantee>,
-    pub raw_recompute_total_cost: Option<f64>,
-}
-
-#[derive(Debug, Clone, Serialize)]
-pub struct SummaryMaintenanceDeploymentExport {
-    pub post_asap_node_id: PhysicalASAPNodeId,
-    #[serde(skip_serializing_if = "Option::is_none")]
-    pub selected_window_framework: Option<SummaryWindowFramework>,
-    #[serde(skip_serializing_if = "Option::is_none")]
-    pub selected: Option<SummaryMaintenanceLifecycleGuaranteeExport>,
-    pub alternatives: Vec<SummaryMaintenanceLifecycleAlternativeExport>,
-}
-
-#[derive(Debug, Clone, Serialize)]
-pub struct SummaryMaintenanceLifecycleAlternativeExport {
-    pub lifecycle: SummaryMaintenanceLifecycle,
-    pub total_cost: Option<f64>,
-    #[serde(skip_serializing_if = "Option::is_none")]
-    pub rejection: Option<SummaryMaintenanceLifecycleRejection>,
-    pub assumptions: Vec<String>,
-}
-
-pub type SummaryMaintenanceLifecycleGuaranteeExport = SummaryMaintenanceLifecycleGuarantee;
-
-pub fn export_summary_maintenance_plan(
-    plan: &SummaryMaintenanceLifecyclePlan,
-) -> SummaryMaintenanceDAGExport {
-    let deployments: Vec<_> = plan
-        .deployments
-        .iter()
-        .map(|deployment| SummaryMaintenanceDeploymentExport {
-            post_asap_node_id: deployment.post_asap_node_id,
-            selected_window_framework: deployment.selected_window_framework.clone(),
-            selected: deployment
-                .summary_maintenance_lifecycle_guarantee
-                .as_ref()
-                .cloned(),
-            alternatives: deployment
-                .alternatives
-                .iter()
-                .map(|alternative| SummaryMaintenanceLifecycleAlternativeExport {
-                    lifecycle: alternative.summary_maintenance_lifecycle.clone(),
-                    total_cost: alternative.total_cost.map(|cost| cost.0),
-                    rejection: alternative.rejection.clone(),
-                    assumptions: alternative.assumptions.clone(),
-                })
-                .collect(),
-        })
-        .collect();
-    let mut dag = dag_export::export_summary(&plan.root);
-    let deployment_by_summary: HashMap<_, _> = plan
-        .deployments
-        .iter()
-        .zip(&deployments)
-        .map(|(deployment, export)| (Rc::as_ptr(&deployment.summary), export))
-        .collect();
-    annotate_lifecycle_deployments(&mut dag, &deployment_by_summary);
-
-    SummaryMaintenanceDAGExport {
-        dag,
-        deployments,
-        horizon_seconds: plan.horizon.map(|horizon| horizon.0),
-        evaluation_rate_per_second: plan.evaluation_rate.map(|rate| rate.0),
-        update_rate_per_second: plan.update_rate.map(|rate| rate.0),
-        expected_reads: plan.expected_reads,
-        selected_raw_recompute: plan.selected_raw_recompute,
-        selected_window_implementation_id: plan.selected_window_implementation_id.clone(),
-        summary_total_cost: plan.summary_total_cost.map(|cost| cost.0),
-        window_accuracy_guarantee: plan.window_accuracy_guarantee.clone(),
-        raw_recompute_total_cost: plan.raw_recompute_total_cost.map(|cost| cost.0),
-    }
-}
-
-/// Attach a deployment directly to the exported node of its `SummaryAgg`,
-/// matched by the `Rc` identity every exported node carries. This makes the
-/// decision visible to dag consumers without asking them to reconstruct
-/// pointer identity from dag position.
-fn annotate_lifecycle_deployments(
-    dag: &mut SummaryDAG,
-    deployments: &HashMap<*const OperatorNode, &SummaryMaintenanceDeploymentExport>,
-) {
-    for dag_node in &mut dag.nodes {
-        let Some(source) = &dag_node.source_node else {
-            continue;
-        };
-        if let Some(deployment) = deployments.get(&Rc::as_ptr(source)) {
-            dag_node.detail["summary_maintenance"] =
-                serde_json::to_value(deployment).expect("lifecycle export is serializable");
-        }
-    }
-}
diff --git a/crates/asap-aware-mapping/src/summary_maintenance_lifecycle.rs b/crates/asap-aware-mapping/src/summary_maintenance_lifecycle.rs
deleted file mode 100644
index 51bb7e29a..000000000
--- a/crates/asap-aware-mapping/src/summary_maintenance_lifecycle.rs
+++ /dev/null
@@ -1,3909 +0,0 @@
-//! Workload-aware summary-maintenance lifecycle planning.
-//!
-//! A **summary-maintenance lifecycle** is the planner policy for when one
-//! materialized summary state is created, retained or shared, updated as data
-//! arrives, and retired. It is deliberately narrower than the end-to-end data
-//! lifecycle and independent of query recurrence. Recurrence says when and how
-//! often queries will read the result. The planner converts that demand into
-//! expected reads and an evaluation rate, then uses those quantities to compare
-//! rebuilding per query with retaining or continuously maintaining state.
-//! Recurrence does not itself prescribe a state-maintenance policy.
-//!
-//! This module enumerates and costs `Ephemeral`, `Prepared`, `Shared`, and
-//! `ContinuouslyMaintained` alternatives for every unique `SummaryAgg` in a
-//! materialized plan, and for every maintained population (`MaintainPopulation`)
-//! that is not an input of a `SummaryAgg`. [`SummaryMaintenanceMode`] is an orthogonal detail of
-//! the selected deployment: state is either built directly or updated
-//! incrementally. Unknown evidence stays unknown and therefore cannot make a
-//! long-lived alternative win.
-
-use asap_types::ir::cse::share_common_sub_dags;
-use std::collections::{HashMap, HashSet};
-use std::rc::Rc;
-
-use asap_types::ir::export::{
-    compile_physical_asap_dag_with_node_ids, compile_physical_asap_workload_with_node_ids,
-    PhysicalASAPDAG, PhysicalASAPDAGValidationError, PhysicalASAPNodeId,
-};
-use asap_types::ir::timing::{apply_lifecycle_timings, LifecycleAssignment, TimingMemo};
-use asap_types::ir::{ASAPOp, Operator, OperatorNode};
-use asap_types::post_asap::{
-    EvaluationSchedule, ExecutionDataStateError, ExecutionTiming, OutputRepresentation,
-    ResultGuarantee, SummaryMaintenanceLifecycle, SummaryMaintenanceLifecycleGuarantee,
-    SummaryMaintenanceMode, SummaryWindowFramework,
-};
-use asap_types::types::AccuracyTarget;
-use asap_types::workload::{
-    DataArrival, DataWorkload, Predictability, QueryRecurrence, QueryWorkload, RepeatedDemand,
-    TimestampMs, WorkloadError,
-};
-
-use crate::analytical_cost::AnalyticalCostError;
-use crate::cost_model::{
-    CompleteSummaryCandidateEstimate, Cost, CostModel, CostedSummaryDeployment,
-};
-use crate::physical_operator_statistics::evaluations_in_horizon;
-use crate::recurrence::{
-    CostRate, EvaluationRate, Horizon, RecurrenceError, RecurrenceProfile, UpdateRate,
-};
-use crate::replacement::{
-    CandidateCostOverrides, CandidateLogicalASAPDAGs, GlobalSelection, RealizationError,
-    Replacement, ReplacementProvenance,
-};
-
-/// Summary-maintenance lifecycle shapes supported by the target runtime.
-///
-/// These independent flags describe the set of lifecycle alternatives the
-/// runtime implements, not simultaneous states of one deployment. Multiple
-/// flags may be `true` (a runtime can support both ephemeral and prepared
-/// state, for example); the planner still selects exactly one mutually
-/// exclusive [`SummaryMaintenanceLifecycle`] for each deployment. A supported
-/// alternative may still be rejected because workload evidence is missing or
-/// its cost is unknown.
-#[derive(Debug, Clone, Copy, PartialEq, Eq)]
-pub struct SummaryMaintenanceLifecycleCapabilities {
-    /// The runtime can build a fresh state for each invocation and retire it
-    /// after that invocation finishes.
-    pub supports_ephemeral: bool,
-    /// The runtime can build state before a predictable execution and retain
-    /// it until that scheduled execution window ends.
-    pub supports_prepared: bool,
-    /// The runtime can retain one state and reuse it across multiple reads.
-    pub supports_shared: bool,
-    /// The runtime can keep state current by applying arriving data updates.
-    pub supports_continuously_maintained: bool,
-}
-
-/// State operations supported by one concrete summary family and
-/// representation.
-///
-/// This differs from [`SummaryMaintenanceLifecycleCapabilities`]: these flags
-/// describe what the summary algorithm itself can do, while lifecycle
-/// capabilities describe what deployment policies the target runtime can
-/// orchestrate.
-#[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
-pub struct SummaryMaintenanceCapabilities {
-    /// Existing state can incorporate arriving input without a full rebuild.
-    pub incremental_update: bool,
-    /// Two independently built states can be combined into one equivalent
-    /// state.
-    pub merge: bool,
-    /// Expired or retracted input can be removed from existing state.
-    pub delete: bool,
-}
-
-impl SummaryMaintenanceLifecycleCapabilities {
-    pub const ALL: Self = Self {
-        supports_ephemeral: true,
-        supports_prepared: true,
-        supports_shared: true,
-        supports_continuously_maintained: true,
-    };
-}
-
-impl Default for SummaryMaintenanceLifecycleCapabilities {
-    fn default() -> Self {
-        Self::ALL
-    }
-}
-
-/// Primitive costs for one concrete summary state. Every field is optional:
-/// missing statistics produce an uncosted alternative, never a zero.
-///
-/// The lifecycle planner combines these state-specific inputs with workload
-/// rates, invocation counts, and the optimization horizon. All `Cost` fields
-/// are one-time costs unless their name explicitly says otherwise.
-#[derive(Debug, Clone, Default, PartialEq)]
-pub struct SummaryMaintenanceLifecycleCostInputs {
-    /// One-time cost to construct the state from its input.
-    pub build_cost: Option<Cost>,
-    /// Cost to incorporate one arriving input update into existing state.
-    pub maintenance_cost_per_update: Option<Cost>,
-    /// Cost of one read or finalization from already-built summary state.
-    pub summary_read_cost: Option<Cost>,
-    /// Cost per second for retaining the state over a lifecycle window.
-    pub retention_cost_rate: Option<CostRate>,
-    /// One-time cost to release or retire the state.
-    pub retirement_cost: Option<Cost>,
-}
-
-#[derive(Debug, Clone, PartialEq, Eq, serde::Serialize)]
-#[serde(rename_all = "snake_case")]
-pub enum SummaryMaintenanceLifecycleRejection {
-    UnsupportedByRuntime,
-    RequiresPredictableOneTimeQuery,
-    RequiresMultipleReads,
-    RequiresHorizon,
-    RequiresContinuousData,
-    MissingOrStaleIngestionRate,
-    SummaryDoesNotSupportIncrementalUpdates,
-    SummaryDoesNotSupportDeletion,
-    MissingCostEvidence,
-}
-
-/// One candidate lifecycle policy for a particular summary deployment.
-///
-/// `total_cost: None` never means zero: it means the planner lacks enough
-/// evidence to cost the candidate. Such a candidate is not selectable and its
-/// `rejection` explains why.
-#[derive(Debug, Clone, PartialEq)]
-pub struct SummaryMaintenanceLifecycleAlternative {
-    /// State creation, retention, sharing, update, and retirement policy.
-    pub summary_maintenance_lifecycle: SummaryMaintenanceLifecycle,
-    /// Complete cost over the requested horizon, when every input is known.
-    pub total_cost: Option<Cost>,
-    /// Why this alternative cannot be selected; `None` means it is legal and
-    /// fully costed.
-    pub rejection: Option<SummaryMaintenanceLifecycleRejection>,
-    /// Human-readable premises used when deriving and costing the alternative.
-    pub assumptions: Vec<String>,
-}
-
-impl SummaryMaintenanceLifecycleAlternative {
-    fn selectable(&self) -> bool {
-        self.rejection.is_none() && self.total_cost.is_some()
-    }
-}
-
-/// One unique retained-state deployment. Shared `Rc` nodes are emitted once.
-#[derive(Debug, Clone)]
-pub struct SummaryMaintenanceDeployment {
-    /// Identity of this summary in the exported post-ASAP semantic DAG.
-    /// It is scoped to one plan version and is not a summary definition or
-    /// summary instance identity.
-    pub post_asap_node_id: PhysicalASAPNodeId,
-    /// The unique materialized `SummaryAgg` represented by this deployment.
-    pub summary: Rc<OperatorNode>,
-    /// Lifecycle, evaluation, and representation commitment selected for this
-    /// state, or `None` when no alternative is selectable.
-    pub summary_maintenance_lifecycle_guarantee: Option<SummaryMaintenanceLifecycleGuarantee>,
-    /// Abstract window primitive selected for this state. Concrete runtime
-    /// implementation, placement, and identity remain downstream decisions.
-    pub selected_window_framework: Option<SummaryWindowFramework>,
-    /// Every lifecycle shape considered, including rejected and uncosted ones.
-    pub alternatives: Vec<SummaryMaintenanceLifecycleAlternative>,
-}
-
-/// Workload-aware lifecycle and window-framework decisions for every unique
-/// summary state reachable from one materialized post-ASAP root.
-#[derive(Debug, Clone)]
-pub struct SummaryMaintenanceLifecyclePlan {
-    /// Root of the materialized post-ASAP DAG being deployed.
-    pub root: Rc<OperatorNode>,
-    /// One entry per unique reachable `SummaryAgg`; shared `Rc` nodes appear
-    /// only once.
-    pub deployments: Vec<SummaryMaintenanceDeployment>,
-    /// Caller-supplied optimization horizon used to turn rates into total
-    /// costs. `None` keeps horizon-dependent alternatives unselectable.
-    pub horizon: Option<Horizon>,
-    /// Aggregate recurring query-evaluation rate derived from the workload.
-    pub evaluation_rate: Option<EvaluationRate>,
-    /// Fresh source-data ingestion rate, when supplied by the workload.
-    pub update_rate: Option<UpdateRate>,
-    /// Total demand inside the horizon, when every recurrence is known.
-    pub expected_reads: Option<f64>,
-    /// Whether global costing preferred rebuilding the raw expression over all
-    /// summary deployments.
-    pub selected_raw_recompute: bool,
-    /// Provider-owned identity of the selected complete physical deployment
-    /// (for example a tumbling, sliding, or exponential-histogram plan).
-    pub selected_window_implementation_id: Option<String>,
-    /// Cost of the selected set of summary deployments, when fully known.
-    pub summary_total_cost: Option<Cost>,
-    /// Composed accuracy guarantee supplied by the selected physical window
-    /// evidence, when the window framework introduces approximation.
-    pub window_accuracy_guarantee: Option<ResultGuarantee>,
-    /// Cost of evaluating the original expression for the same demand, when
-    /// fully known.
-    pub raw_recompute_total_cost: Option<Cost>,
-}
-
-/// Why a lifecycle plan cannot assign execution timing to its DAG.
-#[derive(Debug, thiserror::Error, PartialEq)]
-pub enum SummaryMaintenanceTimingError {
-    #[error(transparent)]
-    InvalidPostAsapDAG(#[from] ExecutionDataStateError),
-    #[error("summary {0:?} has no selected lifecycle")]
-    UnselectedLifecycle(PhysicalASAPNodeId),
-    /// A maintained population outside any `SummaryAgg`'s inputs has no
-    /// deployment, so its timing would be guessed. Enumeration always emits
-    /// one; this arises only for a plan whose root or deployments were edited.
-    #[error("node {0:?} maintains state that has no summary-maintenance lifecycle")]
-    UnplannedMaintainedState(PhysicalASAPNodeId),
-    #[error(transparent)]
-    InvalidPhases(#[from] PhysicalASAPDAGValidationError),
-}
-
-impl SummaryMaintenanceLifecyclePlan {
-    /// The post-ASAP DAG of [`Self::root`] with every node's timing derived
-    /// from the selected lifecycles, so physical compilation places it.
-    ///
-    /// A retained (non-`Ephemeral`) state outlives one query, so it and every
-    /// input it consumes run at ingestion time. Every other node runs at query
-    /// time: evaluations and consumers of retained state, and each `Ephemeral`
-    /// state not consumed by retained state together with its inputs, whose
-    /// raw data the deployment must supply as a query source. This applies to
-    /// maintained populations as to `SummaryAgg` states; a population feeding
-    /// a `SummaryAgg` is one of its inputs. Timings already on the root are
-    /// ignored.
-    pub fn execution_timed_dag(&self) -> Result<PhysicalASAPDAG, SummaryMaintenanceTimingError> {
-        execution_timed_workload_dag(&[self])
-    }
-}
-
-/// One physical ASAP DAG for a workload: a root per plan, in order, with
-/// sub-DAGs shared between plans exported once. Timing follows the selected
-/// lifecycles of every plan's deployments, as in
-/// [`SummaryMaintenanceLifecyclePlan::execution_timed_dag`].
-pub fn execution_timed_workload_dag(
-    plans: &[&SummaryMaintenanceLifecyclePlan],
-) -> Result<PhysicalASAPDAG, SummaryMaintenanceTimingError> {
-    // One memo, so a node shared by several roots is timed and exported once.
-    let mut memo = TimingMemo::new();
-    let assignment = LifecycleAssignment::default_maintained();
-    let timed = plans
-        .iter()
-        .map(|plan| apply_lifecycle_timings(&plan.root, &assignment, &mut memo))
-        .collect::<Result<Vec<_>, _>>()?;
-    let compiled = compile_physical_asap_workload_with_node_ids(&timed)?;
-    let id_of = |node: &Rc<OperatorNode>| {
-        compiled
-            .node_ids
-            .node_id(memo.timed(node).expect("plan node was timed"))
-            .expect("timed plan node belongs to the compiled DAG")
-    };
-    let deployments: Vec<_> = plans
-        .iter()
-        .flat_map(|plan| &plan.deployments)
-        .map(|deployment| (id_of(&deployment.summary), deployment))
-        .collect();
-    for plan in plans {
-        for population in &standalone_populations(&plan.root) {
-            let id = id_of(population);
-            if !deployments.iter().any(|(deployed, _)| *deployed == id) {
-                return Err(SummaryMaintenanceTimingError::UnplannedMaintainedState(id));
-            }
-        }
-    }
-    let dag = compiled.dag;
-    let mut pending = Vec::new();
-    for (id, deployment) in &deployments {
-        let guarantee = deployment
-            .summary_maintenance_lifecycle_guarantee
-            .as_ref()
-            .ok_or(SummaryMaintenanceTimingError::UnselectedLifecycle(*id))?;
-        if guarantee.summary_maintenance_lifecycle != SummaryMaintenanceLifecycle::Ephemeral {
-            pending.push(*id);
-        }
-    }
-    let mut ingestion = HashSet::new();
-    while let Some(id) = pending.pop() {
-        if ingestion.insert(id) {
-            pending.extend(
-                dag.edges
-                    .iter()
-                    .filter(|edge| edge.consumer == id)
-                    .map(|edge| edge.producer),
-            );
-        }
-    }
-    let phases = dag
-        .nodes
-        .iter()
-        .map(|node| {
-            let timing = if ingestion.contains(&node.id) {
-                ExecutionTiming::IngestionTime
-            } else {
-                ExecutionTiming::QueryTime
-            };
-            (node.id, timing)
-        })
-        .collect();
-    Ok(dag.with_execution_phases(&phases)?)
-}
-
-/// Explicit association between a materialized target and the normalized
-/// workload entries whose demand consumes it.
-///
-/// [`QueryWorkload`] remains the source of query demand, while source-data
-/// evidence is supplied independently. Indices avoid copying normalized entry
-/// definitions while ensuring unrelated entries do not influence a target's
-/// lifecycle decision.
-#[derive(Debug, Clone, Copy)]
-pub struct WorkloadDemand<'a> {
-    /// Original normalized query workload.
-    pub workload: &'a QueryWorkload,
-    /// Independent source-data evidence, when the caller has it.
-    pub data_workload: Option<&'a DataWorkload>,
-    /// Indices from [`QueryWorkload::entries`] that consume this target.
-    pub entry_indices: &'a [usize],
-}
-
-impl<'a> WorkloadDemand<'a> {
-    /// Bind query demand without source-data evidence. Callers that have a
-    /// [`DataWorkload`] should use [`Self::new_with_data`] so ingestion facts
-    /// are not silently discarded.
-    pub const fn new_without_data(workload: &'a QueryWorkload, entry_indices: &'a [usize]) -> Self {
-        Self {
-            workload,
-            data_workload: None,
-            entry_indices,
-        }
-    }
-
-    pub const fn new_with_data(
-        workload: &'a QueryWorkload,
-        data_workload: &'a DataWorkload,
-        entry_indices: &'a [usize],
-    ) -> Self {
-        Self {
-            workload,
-            data_workload: Some(data_workload),
-            entry_indices,
-        }
-    }
-}
-
-#[derive(Debug, thiserror::Error)]
-pub enum SummaryMaintenanceLifecyclePlanError {
-    #[error(transparent)]
-    InvalidWorkload(#[from] WorkloadError),
-    #[error("optimization horizon must be finite and strictly positive")]
-    InvalidHorizon,
-    #[error("workload entry index {index} is out of bounds for {entry_count} entries")]
-    InvalidWorkloadEntry { index: usize, entry_count: usize },
-    #[error("a workload-demand binding must contain at least one entry")]
-    EmptyWorkloadDemand,
-    #[error("workload entry index {index} appears more than once in one demand binding")]
-    DuplicateWorkloadEntry { index: usize },
-    #[error(transparent)]
-    InvalidPostAsapDAG(#[from] ExecutionDataStateError),
-}
-
-#[derive(Debug, thiserror::Error)]
-pub enum SummaryMaintenanceLifecycleAssemblyError {
-    #[error(transparent)]
-    AssembleDAG(#[from] RealizationError),
-    #[error(transparent)]
-    SummaryMaintenance(#[from] SummaryMaintenanceLifecyclePlanError),
-}
-
-/// Failure while deriving workload-aware candidate costs before global
-/// selection.
-#[derive(Debug, thiserror::Error)]
-pub enum SummaryMaintenanceLifecycleSelectionError {
-    #[error(transparent)]
-    Recurrence(#[from] RecurrenceError),
-    #[error(transparent)]
-    SummaryMaintenance(#[from] SummaryMaintenanceLifecyclePlanError),
-}
-
-/// Every lifecycle alternative for each unique retained state of one fixed
-/// root, before any lifecycle is chosen.
-///
-/// Planner selection ([`plan_summary_maintenance_lifecycles`]) and a
-/// deployment's explicit choice ([`Self::select`]) both finish from this value,
-/// so they produce the same [`SummaryMaintenanceLifecyclePlan`] shape.
-pub struct SummaryMaintenanceLifecycleCandidates<'a> {
-    /// Unselected plan: deployments carry alternatives but no guarantee or
-    /// window framework.
-    plan: SummaryMaintenanceLifecyclePlan,
-    components: Vec<usize>,
-    arrival: DataArrival,
-    required_accuracy: Vec<AccuracyTarget>,
-    cost_model: &'a dyn CostModel,
-    comparison_target: Option<&'a OperatorNode>,
-}
-
-/// Why an explicit per-state lifecycle choice cannot be bound.
-#[derive(Debug, thiserror::Error, PartialEq)]
-pub enum SummaryMaintenanceLifecycleChoiceError {
-    #[error("summary {0:?} is not a deployment of this root")]
-    UnknownSummary(PhysicalASAPNodeId),
-    #[error("summary {0:?} is chosen more than once")]
-    DuplicateChoice(PhysicalASAPNodeId),
-    #[error("summary {0:?} has no chosen lifecycle")]
-    MissingChoice(PhysicalASAPNodeId),
-    #[error("chosen lifecycle is not an enumerated alternative of summary {0:?}")]
-    NotAnAlternative(PhysicalASAPNodeId),
-    #[error("chosen lifecycle of summary {post_asap_node_id:?} is rejected: {rejection:?}")]
-    Rejected {
-        post_asap_node_id: PhysicalASAPNodeId,
-        rejection: Option<SummaryMaintenanceLifecycleRejection>,
-    },
-    #[error("summary states on one maintenance path have different evaluation schedules")]
-    IncompatibleEvaluationSchedules,
-    #[error("the cost model supplied no complete estimate for the chosen combination")]
-    NoCompleteEstimate,
-}
-
-impl SummaryMaintenanceLifecycleCandidates<'_> {
-    /// One entry per unique retained state (see
-    /// [`SummaryMaintenanceLifecyclePlan::deployments`]), with every
-    /// alternative and its rejection; no lifecycle or window framework is
-    /// selected.
-    pub fn deployments(&self) -> &[SummaryMaintenanceDeployment] {
-        &self.plan.deployments
-    }
-
-    /// Guarantee that binding `lifecycle` would attach under this workload's
-    /// data arrival, so a caller can price an alternative before choosing it.
-    pub fn guarantee(
-        &self,
-        lifecycle: &SummaryMaintenanceLifecycle,
-    ) -> SummaryMaintenanceLifecycleGuarantee {
-        lifecycle_guarantee(lifecycle, self.arrival)
-    }
-
-    fn context(&self) -> CompleteCostContext<'_> {
-        CompleteCostContext {
-            root: &self.plan.root,
-            components: &self.components,
-            cost_model: self.cost_model,
-            comparison_target: self.comparison_target,
-            horizon: self.plan.horizon,
-            expected_reads: self.plan.expected_reads,
-            required_accuracy: &self.required_accuracy,
-        }
-    }
-
-    fn finish(
-        mut self,
-        estimate: Option<CompleteSummaryCandidateEstimate>,
-    ) -> SummaryMaintenanceLifecyclePlan {
-        if let Some(estimate) = estimate {
-            self.plan.summary_total_cost = Some(estimate.cost);
-            self.plan.selected_window_implementation_id = estimate.physical_plan_id;
-            self.plan.window_accuracy_guarantee = estimate.window_accuracy_guarantee;
-        }
-        self.plan
-    }
-
-    /// Planner's choice: the cheapest complete combination of eligible
-    /// alternatives.
-    fn select_cheapest(mut self) -> SummaryMaintenanceLifecyclePlan {
-        let estimate = select_complete_lifecycle_combination(
-            &self.plan.root,
-            &mut self.plan.deployments,
-            &self.components,
-            self.arrival,
-            self.cost_model,
-            self.comparison_target,
-            self.plan.horizon,
-            self.plan.expected_reads,
-            &self.required_accuracy,
-        );
-        self.finish(estimate)
-    }
-
-    /// Bind one caller-chosen lifecycle per summary state. Each choice must be
-    /// an alternative Planner itself could select; the complete estimate is
-    /// then obtained exactly as for Planner selection, so window framework and
-    /// cost are the model's and unknown cost is never replaced by zero.
-    pub fn select(
-        mut self,
-        choices: &[(PhysicalASAPNodeId, SummaryMaintenanceLifecycle)],
-    ) -> Result<SummaryMaintenanceLifecyclePlan, SummaryMaintenanceLifecycleChoiceError> {
-        use SummaryMaintenanceLifecycleChoiceError as E;
-        let deployments = &self.plan.deployments;
-        let mut chosen: Vec<Option<&SummaryMaintenanceLifecycleAlternative>> =
-            vec![None; deployments.len()];
-        let context = self.context();
-        for (id, lifecycle) in choices {
-            let index = deployments
-                .iter()
-                .position(|deployment| deployment.post_asap_node_id == *id)
-                .ok_or(E::UnknownSummary(*id))?;
-            if chosen[index].is_some() {
-                return Err(E::DuplicateChoice(*id));
-            }
-            let alternative = deployments[index]
-                .alternatives
-                .iter()
-                .find(|alternative| alternative.summary_maintenance_lifecycle == *lifecycle)
-                .ok_or(E::NotAnAlternative(*id))?;
-            if !context.eligible(alternative) {
-                return Err(E::Rejected {
-                    post_asap_node_id: *id,
-                    rejection: alternative.rejection.clone(),
-                });
-            }
-            chosen[index] = Some(alternative);
-        }
-        let selected = chosen
-            .into_iter()
-            .enumerate()
-            .map(|(index, alternative)| {
-                let alternative =
-                    alternative.ok_or(E::MissingChoice(deployments[index].post_asap_node_id))?;
-                Ok((
-                    index,
-                    lifecycle_guarantee(&alternative.summary_maintenance_lifecycle, self.arrival),
-                    // Reached only for costed alternatives or when the
-                    // complete hook is authoritative, matching Planner search.
-                    alternative.total_cost.unwrap_or(Cost::ZERO),
-                ))
-            })
-            .collect::<Result<Vec<_>, E>>()?;
-        if selected.is_empty() {
-            return Ok(self.finish(None));
-        }
-        if !context.schedules_compatible(&selected) {
-            return Err(E::IncompatibleEvaluationSchedules);
-        }
-        let estimate = context
-            .estimate(deployments, &selected)
-            .ok_or(E::NoCompleteEstimate)?;
-        let guarantees = selected
-            .into_iter()
-            .map(|(index, guarantee, _)| (index, guarantee))
-            .collect();
-        apply_selection(&mut self.plan.deployments, guarantees, &estimate);
-        Ok(self.finish(Some(estimate)))
-    }
-}
-
-/// Workload-wide evidence derived specifically for summary-maintenance
-/// lifecycle enumeration and costing.
-///
-/// This is not another workload input model. [`QueryWorkload`] and its
-/// normalized entries remain the source of truth. Unlike one
-/// [`asap_types::workload::QueryWorkloadEntry`], these values aggregate all
-/// entries at a particular planning time and optional horizon. It also cannot
-/// reuse [`crate::recurrence::RecurrenceProfile`], which describes recurrence
-/// for one candidate target and counts consumers rather than invocations.
-#[derive(Debug)]
-struct SummaryMaintenanceWorkloadFacts {
-    required_accuracy: Vec<AccuracyTarget>,
-    /// Total one-time and recurring reads inside the horizon. `None` means a
-    /// recurrence or horizon was unknown, not zero reads.
-    reads: Option<f64>,
-    /// Sum of declared invocations across all one-time workload entries.
-    one_time_invocations: u64,
-    /// Sum of usable recurring query rates in evaluations per second.
-    evaluation_rate: Option<EvaluationRate>,
-    /// Fresh workload-level ingestion rate in updates per second.
-    update_rate: Option<UpdateRate>,
-    /// Whether the workload's source data is static, arriving, mixed, or
-    /// unknown.
-    arrival: DataArrival,
-    /// Earliest known activation and latest scheduled execution across
-    /// predictable one-time entries. `None` means no valid preparation window.
-    prepared_window: Option<(TimestampMs, TimestampMs)>,
-    /// Whether every bound consumer is a predictable one-time query suitable
-    /// for prepared state.
-    prepared_eligible: bool,
-    /// Whether maintaining the selected moving time scope requires deleting
-    /// expired input from summary state.
-    requires_deletion: bool,
-}
-
-/// Validate a materialized plan, enumerate lifecycle alternatives for each
-/// unique summary state, and select the cheapest legal alternative whose cost
-/// is fully known.
-pub fn plan_summary_maintenance_lifecycles(
-    root: Rc<OperatorNode>,
-    demand: WorkloadDemand<'_>,
-    now_ms: u64,
-    horizon: Option<Horizon>,
-    capabilities: SummaryMaintenanceLifecycleCapabilities,
-    cost_model: &dyn CostModel,
-) -> Result<SummaryMaintenanceLifecyclePlan, SummaryMaintenanceLifecyclePlanError> {
-    Ok(enumerate_summary_maintenance_lifecycles(
-        root,
-        demand,
-        now_ms,
-        horizon,
-        capabilities,
-        cost_model,
-    )?
-    .select_cheapest())
-}
-
-/// Validate a materialized plan and enumerate lifecycle alternatives for each
-/// unique summary state without choosing one. A deployment that prices the
-/// alternatives itself binds its choice with
-/// [`SummaryMaintenanceLifecycleCandidates::select`].
-pub fn enumerate_summary_maintenance_lifecycles<'a>(
-    root: Rc<OperatorNode>,
-    demand: WorkloadDemand<'_>,
-    now_ms: u64,
-    horizon: Option<Horizon>,
-    capabilities: SummaryMaintenanceLifecycleCapabilities,
-    cost_model: &'a dyn CostModel,
-) -> Result<SummaryMaintenanceLifecycleCandidates<'a>, SummaryMaintenanceLifecyclePlanError> {
-    enumerate_with_profile(
-        root,
-        demand,
-        now_ms,
-        horizon,
-        capabilities,
-        cost_model,
-        None,
-        None,
-    )
-}
-
-/// Internal candidate-costing form. The workload binding supplies temporal
-/// eligibility and data-arrival facts; `profile` supplies effective uses after
-/// DAG path multiplicity has been propagated by `CandidateLogicalASAPDAGs`.
-#[expect(clippy::too_many_arguments, reason = "internal bound planning context")]
-fn enumerate_with_profile<'a>(
-    root: Rc<OperatorNode>,
-    demand: WorkloadDemand<'_>,
-    now_ms: u64,
-    horizon: Option<Horizon>,
-    capabilities: SummaryMaintenanceLifecycleCapabilities,
-    cost_model: &'a dyn CostModel,
-    profile: Option<RecurrenceProfile>,
-    comparison_target: Option<&'a OperatorNode>,
-) -> Result<SummaryMaintenanceLifecycleCandidates<'a>, SummaryMaintenanceLifecyclePlanError> {
-    demand.workload.validate()?;
-    if let Some(data) = demand.data_workload {
-        data.validate()?;
-    }
-    if horizon.is_some_and(|h| !h.0.is_finite() || h.0 <= 0.0) {
-        return Err(SummaryMaintenanceLifecyclePlanError::InvalidHorizon);
-    }
-    let mut facts = workload_facts(
-        demand.workload,
-        demand.data_workload,
-        demand.entry_indices,
-        now_ms,
-        horizon,
-    )?;
-    if let Some(profile) = profile {
-        facts.one_time_invocations = u64::try_from(profile.one_shot_consumers).unwrap_or(u64::MAX);
-        facts.evaluation_rate = profile.evaluation_rate;
-        facts.update_rate = profile.update_rate;
-        facts.reads = match (profile.evaluation_rate, horizon) {
-            (Some(rate), Some(horizon)) => {
-                Some(profile.one_shot_consumers as f64 + rate.0 * horizon.0)
-            }
-            (Some(_), None) => None,
-            (None, _) if profile.one_shot_consumers > 0 => Some(profile.one_shot_consumers as f64),
-            // Preserve unknown recurrence from the normalized workload. An
-            // empty profile does not prove that the target is never read.
-            (None, _) => facts.reads,
-        };
-    }
-    let mut summaries = Vec::new();
-    collect_states(
-        &root,
-        &mut HashSet::new(),
-        &mut summaries,
-        StateKind::SummaryAgg,
-    );
-    summaries.extend(standalone_populations(&root));
-    let mut timing_memo = TimingMemo::new();
-    let timed_root = apply_lifecycle_timings(
-        &root,
-        &LifecycleAssignment::default_maintained(),
-        &mut timing_memo,
-    )?;
-    let node_ids = compile_physical_asap_dag_with_node_ids(&timed_root)?.node_ids;
-    let components = summary_state_components(&summaries);
-    let deployments: Vec<SummaryMaintenanceDeployment> = summaries
-        .into_iter()
-        .map(|summary| {
-            let capabilities = if OperatorNode::reachable(&summary).iter().any(|node| {
-                matches!(
-                    node.non_asap(),
-                    Some(asap_types::ir::NonASAPOp::BinaryOp { .. })
-                ) && asap_types::ir::timing::validate_default(node, ExecutionTiming::IngestionTime)
-                    .is_err()
-            }) {
-                SummaryMaintenanceLifecycleCapabilities {
-                    supports_ephemeral: capabilities.supports_ephemeral,
-                    supports_prepared: false,
-                    supports_shared: false,
-                    supports_continuously_maintained: false,
-                }
-            } else {
-                capabilities
-            };
-            let alternatives = alternatives_for(
-                &facts,
-                horizon,
-                capabilities,
-                cost_model.summary_maintenance_capabilities(&summary),
-                cost_model.summary_maintenance_lifecycle_cost_inputs_for_horizon(&summary, horizon),
-            );
-            SummaryMaintenanceDeployment {
-                post_asap_node_id: timing_memo
-                    .timed(&summary)
-                    .and_then(|timed| node_ids.node_id(timed))
-                    .expect("collected summary belongs to the compiled DAG"),
-                summary,
-                summary_maintenance_lifecycle_guarantee: None,
-                selected_window_framework: None,
-                alternatives,
-            }
-        })
-        .collect();
-    let selected_raw_recompute = !root.contains_asap();
-    Ok(SummaryMaintenanceLifecycleCandidates {
-        plan: SummaryMaintenanceLifecyclePlan {
-            root,
-            deployments,
-            horizon,
-            evaluation_rate: facts.evaluation_rate,
-            update_rate: facts.update_rate,
-            expected_reads: facts.reads,
-            selected_raw_recompute,
-            selected_window_implementation_id: None,
-            summary_total_cost: None,
-            window_accuracy_guarantee: None,
-            raw_recompute_total_cost: None,
-        },
-        components,
-        arrival: facts.arrival,
-        required_accuracy: facts.required_accuracy,
-        cost_model,
-        comparison_target,
-    })
-}
-
-/// Rank semantic summary siblings using the cheapest legal
-/// summary-maintenance lifecycle for each candidate before final global
-/// selection. The candidate space stays compact; only cost overrides are
-/// attached, so shared `Rc` identity and exact-composition commitments remain
-/// the responsibility of `GlobalSelection`.
-///
-/// Summary candidates of different targets whose outermost `SummaryAgg` is
-/// structurally identical (for example p50 and p99 over one KLL) form a class.
-/// When [`shared_state_cost`] can cost that state once against the union of
-/// the targets' entries, each member is offered an equal split of it instead
-/// of its independent cost. If selection then leaves any member of a class on
-/// another choice, that class reverts to independent costs and selection runs
-/// once more.
-pub fn global_selection_with_summary_maintenance_lifecycles<'a, Id>(
-    space: &'a CandidateLogicalASAPDAGs<Id>,
-    demand: WorkloadDemand<'_>,
-    now_ms: u64,
-    horizon: Option<Horizon>,
-    capabilities: SummaryMaintenanceLifecycleCapabilities,
-    cost_model: &dyn CostModel,
-) -> Result<GlobalSelection<'a>, SummaryMaintenanceLifecycleSelectionError> {
-    let WorkloadDemand {
-        workload,
-        data_workload,
-        entry_indices: root_workload_entries,
-    } = demand;
-    let profiles = space.recurrence_profiles_from_workload(
-        workload,
-        data_workload,
-        root_workload_entries,
-        now_ms,
-        horizon,
-    )?;
-    let bindings = space.workload_entries_by_target(workload, root_workload_entries)?;
-    let mut costs = CandidateCostOverrides::default();
-    // Finalized summary candidates, as sharing-class members.
-    let mut members = Vec::new();
-    for group in space.target_subdag_candidates() {
-        let Some(entry_indices) = bindings.get(&Rc::as_ptr(&group.target)) else {
-            continue;
-        };
-        for candidate in &group.candidates {
-            // Only summary realizations carry a maintenance lifecycle; a
-            // logical rewrite or CSE share/recompute candidate does not.
-            let Replacement::SubDAG(summary) = &candidate.replacement else {
-                continue;
-            };
-            if candidate.provenance != ReplacementProvenance::SummaryRealization {
-                continue;
-            }
-            costs.finalize_target(&group.target);
-            let plan = enumerate_with_profile(
-                Rc::clone(summary),
-                WorkloadDemand {
-                    workload,
-                    data_workload,
-                    entry_indices,
-                },
-                now_ms,
-                horizon,
-                capabilities,
-                cost_model,
-                Some(profiles.for_target(&group.target)),
-                Some(&group.target),
-            )?
-            .select_cheapest();
-            let raw = plan
-                .expected_reads
-                .and_then(|reads| cost_model.raw_query_recompute_total_cost(&group.target, reads));
-            // Final comparison is atomic: without the raw side, no summary
-            // override is published even when that summary alone is costed.
-            if let Some(raw) = raw {
-                costs.insert_raw(&group.target, raw);
-                if !plan.deployments.is_empty() {
-                    if let Some(total) = plan.summary_total_cost {
-                        costs.insert(&group.target, candidate, total);
-                    }
-                    members.push((group, candidate, Rc::clone(summary)));
-                }
-            }
-        }
-    }
-
-    // Intern every member once; members whose outermost state (the
-    // `SummaryAgg` every other state of the candidate feeds) interns to the
-    // same node share it. Classes are kept in first-member order.
-    let interned = share_common_sub_dags(
-        members
-            .iter()
-            .enumerate()
-            .map(|(index, (_, _, summary))| (index, Rc::clone(summary)))
-            .collect(),
-    );
-    let mut classes: Vec<(Rc<OperatorNode>, Vec<usize>)> = Vec::new();
-    for (index, root) in interned {
-        let states = summary_states(&root);
-        let Some(state) = states
-            .iter()
-            .find(|state| summary_states(state).len() == states.len())
-        else {
-            continue;
-        };
-        if !standalone_populations(&root).is_empty() {
-            continue;
-        }
-        match classes.iter_mut().find(|(s, _)| Rc::ptr_eq(s, state)) {
-            Some((_, class)) => class.push(index),
-            None => classes.push((Rc::clone(state), vec![index])),
-        }
-    }
-    let mut shared = Vec::new();
-    for (state, class) in classes {
-        let mut targets: Vec<&Rc<OperatorNode>> = Vec::new();
-        for &index in &class {
-            let target = &members[index].0.target;
-            if !targets.iter().any(|t| Rc::ptr_eq(t, target)) {
-                targets.push(target);
-            }
-        }
-        if targets.len() < 2 {
-            continue;
-        }
-        let mut entries: Vec<usize> = targets
-            .iter()
-            .flat_map(|target| bindings[&Rc::as_ptr(target)].iter().copied())
-            .collect();
-        entries.sort_unstable();
-        entries.dedup();
-        let Some(cost) = shared_state_cost(
-            &state,
-            WorkloadDemand {
-                workload,
-                data_workload,
-                entry_indices: &entries,
-            },
-            now_ms,
-            horizon,
-            capabilities,
-            cost_model,
-        )?
-        else {
-            continue;
-        };
-        shared.push((class, Cost(cost.0 / targets.len() as f64)));
-    }
-
-    let with_shared = |kept: &[(Vec<usize>, Cost)]| {
-        let mut costs = costs.clone();
-        for (class, split) in kept {
-            for &index in class {
-                let (group, candidate, _) = &members[index];
-                costs.insert(&group.target, candidate, *split);
-            }
-        }
-        costs
-    };
-    let selection = space.global_selection_with_candidate_costs(
-        cost_model,
-        &profiles,
-        horizon,
-        &with_shared(&shared),
-    )?;
-    let before = shared.len();
-    shared.retain(|(class, _)| {
-        class.iter().all(|&index| {
-            let target = &members[index].0.target;
-            let chosen = selection.for_target(target).and_then(|s| s.chosen);
-            class.iter().any(|&other| {
-                Rc::ptr_eq(&members[other].0.target, target)
-                    && chosen.is_some_and(|chosen| std::ptr::eq(chosen, members[other].1))
-            })
-        })
-    });
-    if shared.len() == before {
-        return Ok(selection);
-    }
-    Ok(space.global_selection_with_candidate_costs(
-        cost_model,
-        &profiles,
-        horizon,
-        &with_shared(&shared),
-    )?)
-}
-
-/// Cost of one `SummaryAgg` state maintained once for every entry in
-/// `demand`, or `None` when no lifecycle alternative is selectable for it.
-/// No comparison target is supplied: the state serves several queries.
-pub(crate) fn shared_state_cost(
-    state: &Rc<OperatorNode>,
-    demand: WorkloadDemand<'_>,
-    now_ms: u64,
-    horizon: Option<Horizon>,
-    capabilities: SummaryMaintenanceLifecycleCapabilities,
-    cost_model: &dyn CostModel,
-) -> Result<Option<Cost>, SummaryMaintenanceLifecyclePlanError> {
-    Ok(enumerate_with_profile(
-        Rc::clone(state),
-        demand,
-        now_ms,
-        horizon,
-        capabilities,
-        cost_model,
-        None,
-        None,
-    )?
-    .select_cheapest()
-    .summary_total_cost)
-}
-
-/// Every unique `SummaryAgg` reachable from `root`.
-pub(crate) fn summary_states(root: &Rc<OperatorNode>) -> Vec<Rc<OperatorNode>> {
-    let mut states = Vec::new();
-    collect_states(
-        root,
-        &mut HashSet::new(),
-        &mut states,
-        StateKind::SummaryAgg,
-    );
-    states
-}
-
-/// Assemble a globally selected phase-valid DAG and attach workload-aware
-/// summary maintenance decisions. This does not create or maintain runtime state.
-pub fn assemble_selected_dag_with_summary_maintenance_lifecycles(
-    selection: &GlobalSelection<'_>,
-    target: &Rc<OperatorNode>,
-    demand: WorkloadDemand<'_>,
-    now_ms: u64,
-    horizon: Option<Horizon>,
-    capabilities: SummaryMaintenanceLifecycleCapabilities,
-    cost_model: &dyn CostModel,
-) -> Result<Option<SummaryMaintenanceLifecyclePlan>, SummaryMaintenanceLifecycleAssemblyError> {
-    selection
-        .assemble_selected_dag(target)?
-        .map(|root| {
-            plan_assembled_dag(
-                root,
-                target,
-                demand,
-                now_ms,
-                horizon,
-                capabilities,
-                cost_model,
-            )
-        })
-        .transpose()
-}
-
-/// The lifecycle half of
-/// [`assemble_selected_dag_with_summary_maintenance_lifecycles`], for a root
-/// the caller already assembled (and possibly interned across queries).
-pub(crate) fn plan_assembled_dag(
-    root: Rc<OperatorNode>,
-    target: &Rc<OperatorNode>,
-    demand: WorkloadDemand<'_>,
-    now_ms: u64,
-    horizon: Option<Horizon>,
-    capabilities: SummaryMaintenanceLifecycleCapabilities,
-    cost_model: &dyn CostModel,
-) -> Result<SummaryMaintenanceLifecyclePlan, SummaryMaintenanceLifecycleAssemblyError> {
-    let mut plan = enumerate_with_profile(
-        root,
-        demand,
-        now_ms,
-        horizon,
-        capabilities,
-        cost_model,
-        None,
-        Some(target),
-    )?
-    .select_cheapest();
-    plan.raw_recompute_total_cost = plan
-        .expected_reads
-        .and_then(|reads| cost_model.raw_query_recompute_total_cost(target, reads));
-    if !plan.selected_raw_recompute
-        && plan.raw_recompute_total_cost.is_none_or(|raw| {
-            plan.summary_total_cost
-                .is_none_or(|summary| raw.0 <= summary.0)
-        })
-    {
-        plan.root = crate::replacement::retain_exact(target)?;
-        plan.deployments.clear();
-        plan.selected_raw_recompute = true;
-        plan.selected_window_implementation_id = None;
-        plan.summary_total_cost = None;
-        plan.window_accuracy_guarantee = None;
-    }
-    Ok(plan)
-}
-
-fn workload_facts(
-    workload: &QueryWorkload,
-    data_workload: Option<&DataWorkload>,
-    workload_entry_indices: &[usize],
-    now_ms: u64,
-    horizon: Option<Horizon>,
-) -> Result<SummaryMaintenanceWorkloadFacts, SummaryMaintenanceLifecyclePlanError> {
-    let mut one_time_invocations = 0u64;
-    let mut recurring_reads = 0.0;
-    let mut recurring_known = true;
-    let mut evaluation_rate = 0.0;
-    let mut has_evaluation_rate = false;
-    let mut prepared_start: Option<TimestampMs> = None;
-    let mut prepared_end: Option<TimestampMs> = None;
-    let mut prepared_eligible = true;
-    let mut requires_deletion = false;
-    let mut required_accuracy = Vec::new();
-
-    let entries: Vec<_> = workload.entries().collect();
-    if workload_entry_indices.is_empty() {
-        return Err(SummaryMaintenanceLifecyclePlanError::EmptyWorkloadDemand);
-    }
-    let mut seen_indices = HashSet::new();
-    for &index in workload_entry_indices {
-        if !seen_indices.insert(index) {
-            return Err(SummaryMaintenanceLifecyclePlanError::DuplicateWorkloadEntry { index });
-        }
-        let entry = entries.get(index).ok_or(
-            SummaryMaintenanceLifecyclePlanError::InvalidWorkloadEntry {
-                index,
-                entry_count: entries.len(),
-            },
-        )?;
-        required_accuracy.push(entry.requirements.accuracy.target());
-        requires_deletion |= entry.time_selection.lookback.is_some()
-            && entry.time_selection.as_of.is_none()
-            && matches!(
-                entry.time_selection.scope,
-                asap_types::workload::QueryTimeScope::RealTime
-                    | asap_types::workload::QueryTimeScope::Mixed
-            );
-        match &entry.recurrence {
-            QueryRecurrence::OneTime {
-                invocations,
-                execute_at,
-            } => {
-                one_time_invocations = one_time_invocations.saturating_add(*invocations);
-                let covered = if let (
-                    Predictability::Predictable {
-                        known_at: Some(known),
-                    },
-                    Some(execute),
-                ) = (&entry.predictability, execute_at)
-                {
-                    if known < execute && now_ms < execute.0 {
-                        let activate = TimestampMs(known.0.max(now_ms));
-                        prepared_start =
-                            Some(prepared_start.map_or(activate, |old| old.min(activate)));
-                        prepared_end = Some(prepared_end.map_or(*execute, |old| old.max(*execute)));
-                        true
-                    } else {
-                        false
-                    }
-                } else {
-                    false
-                };
-                prepared_eligible &= covered;
-            }
-            QueryRecurrence::Repeated(RepeatedDemand::FixedInterval(interval))
-            | QueryRecurrence::Repeated(RepeatedDemand::FixedIntervalAt { interval, .. }) => {
-                prepared_eligible = false;
-                let rate = 1000.0 / f64::from(interval.0);
-                evaluation_rate += rate;
-                has_evaluation_rate = true;
-                if let Some(h) = horizon {
-                    recurring_reads += h.0 * rate;
-                } else {
-                    recurring_known = false;
-                }
-            }
-            QueryRecurrence::Repeated(RepeatedDemand::Scheduled(schedule)) => {
-                prepared_eligible = false;
-                if let Some(h) = horizon {
-                    let end_ms = now_ms.saturating_add((h.0 * 1000.0) as u64);
-                    let reads_in_horizon = schedule
-                        .iter()
-                        .filter(|at| at.0 >= now_ms && at.0 <= end_ms)
-                        .count() as f64;
-                    recurring_reads += reads_in_horizon;
-                    evaluation_rate += reads_in_horizon / h.0;
-                    has_evaluation_rate = true;
-                } else {
-                    recurring_known = false;
-                }
-            }
-            QueryRecurrence::Repeated(RepeatedDemand::EstimatedRate(estimate)) => {
-                prepared_eligible = false;
-                if !estimate.is_fresh_at(now_ms) {
-                    recurring_known = false;
-                    continue;
-                }
-                let rate = estimate.expected_rate.0;
-                evaluation_rate += rate;
-                has_evaluation_rate = true;
-                if let Some(h) = horizon {
-                    recurring_reads += h.0 * rate;
-                } else {
-                    recurring_known = false;
-                }
-            }
-            QueryRecurrence::Unknown => {
-                prepared_eligible = false;
-                recurring_known = false;
-            }
-        }
-    }
-
-    let data = data_workload;
-    let arrival = data.map_or(DataArrival::Unknown, |data| data.arrival);
-    let update_rate = data
-        .and_then(|data| data.ingestion_rate.value_at(now_ms))
-        .map(|rate| UpdateRate(rate.0));
-    let reads = if let Some(horizon) = horizon {
-        let horizon_ms = horizon.0 * 1_000.0;
-        if !horizon_ms.is_finite()
-            || horizon_ms <= 0.0
-            || horizon_ms > u64::MAX as f64
-            || horizon_ms.fract() != 0.0
-        {
-            None
-        } else {
-            workload_entry_indices
-                .iter()
-                .try_fold(0_u64, |total, index| {
-                    let entry = entries.get(*index)?;
-                    match evaluations_in_horizon(&entry.recurrence, now_ms, horizon_ms as u64) {
-                        Ok(count) => total.checked_add(count),
-                        Err(AnalyticalCostError::NoEvaluationsInHorizon) => Some(total),
-                        Err(_) => None,
-                    }
-                })
-                .map(|count| count as f64)
-        }
-    } else {
-        recurring_known.then_some(one_time_invocations as f64 + recurring_reads)
-    };
-    Ok(SummaryMaintenanceWorkloadFacts {
-        required_accuracy,
-        reads,
-        one_time_invocations,
-        evaluation_rate: has_evaluation_rate.then_some(EvaluationRate(evaluation_rate)),
-        update_rate,
-        arrival,
-        prepared_window: prepared_start.zip(prepared_end),
-        prepared_eligible,
-        requires_deletion,
-    })
-}
-
-fn alternatives_for(
-    facts: &SummaryMaintenanceWorkloadFacts,
-    horizon: Option<Horizon>,
-    capabilities: SummaryMaintenanceLifecycleCapabilities,
-    summary_capabilities: SummaryMaintenanceCapabilities,
-    costs: SummaryMaintenanceLifecycleCostInputs,
-) -> Vec<SummaryMaintenanceLifecycleAlternative> {
-    let alternatives = vec![
-        ephemeral(facts, capabilities, &costs),
-        prepared(facts, capabilities, summary_capabilities, &costs),
-        shared(facts, horizon, capabilities, summary_capabilities, &costs),
-        continuous(facts, horizon, capabilities, summary_capabilities, &costs),
-    ];
-    alternatives
-}
-
-fn ephemeral(
-    facts: &SummaryMaintenanceWorkloadFacts,
-    capabilities: SummaryMaintenanceLifecycleCapabilities,
-    costs: &SummaryMaintenanceLifecycleCostInputs,
-) -> SummaryMaintenanceLifecycleAlternative {
-    let lifecycle = SummaryMaintenanceLifecycle::Ephemeral;
-    if !capabilities.supports_ephemeral {
-        return rejected(
-            lifecycle,
-            SummaryMaintenanceLifecycleRejection::UnsupportedByRuntime,
-        );
-    }
-    let total_cost = zip_costs(&[
-        costs.build_cost,
-        costs.summary_read_cost,
-        costs.retirement_cost,
-    ])
-    .zip(facts.reads)
-    .map(|(per_read, reads)| Cost(per_read * reads));
-    costed_or_unknown(
-        lifecycle,
-        total_cost,
-        vec!["state is rebuilt per invocation".into()],
-    )
-}
-
-fn prepared(
-    facts: &SummaryMaintenanceWorkloadFacts,
-    capabilities: SummaryMaintenanceLifecycleCapabilities,
-    summary_capabilities: SummaryMaintenanceCapabilities,
-    costs: &SummaryMaintenanceLifecycleCostInputs,
-) -> SummaryMaintenanceLifecycleAlternative {
-    if !facts.prepared_eligible {
-        return rejected(
-            SummaryMaintenanceLifecycle::Prepared {
-                activate_at: TimestampMs(0),
-                retire_at: TimestampMs(0),
-            },
-            SummaryMaintenanceLifecycleRejection::RequiresPredictableOneTimeQuery,
-        );
-    }
-    let Some((activate_at, retire_at)) = facts.prepared_window else {
-        return rejected(
-            SummaryMaintenanceLifecycle::Prepared {
-                activate_at: TimestampMs(0),
-                retire_at: TimestampMs(0),
-            },
-            SummaryMaintenanceLifecycleRejection::RequiresPredictableOneTimeQuery,
-        );
-    };
-    let lifecycle = SummaryMaintenanceLifecycle::Prepared {
-        activate_at,
-        retire_at,
-    };
-    if !capabilities.supports_prepared {
-        return rejected(
-            lifecycle,
-            SummaryMaintenanceLifecycleRejection::UnsupportedByRuntime,
-        );
-    }
-    if let Some(rejection) = maintenance_capability_rejection(facts, summary_capabilities) {
-        return rejected(lifecycle, rejection);
-    }
-    let seconds = retire_at.0.saturating_sub(activate_at.0) as f64 / 1000.0;
-    let maintenance = maintenance_cost(facts, costs, seconds);
-    let total_cost = match (
-        costs.build_cost,
-        costs.summary_read_cost,
-        costs.retention_cost_rate,
-        costs.retirement_cost,
-        maintenance,
-    ) {
-        (Some(build), Some(read), Some(retention), Some(retire), Some(maintenance)) => Some(Cost(
-            build.0
-                + read.0 * facts.one_time_invocations as f64
-                + retention.0 * seconds
-                + retire.0
-                + maintenance,
-        )),
-        _ => None,
-    };
-    costed_or_unknown(
-        lifecycle,
-        total_cost,
-        vec!["activation and retirement come from the declared schedule".into()],
-    )
-}
-
-fn shared(
-    facts: &SummaryMaintenanceWorkloadFacts,
-    horizon: Option<Horizon>,
-    capabilities: SummaryMaintenanceLifecycleCapabilities,
-    summary_capabilities: SummaryMaintenanceCapabilities,
-    costs: &SummaryMaintenanceLifecycleCostInputs,
-) -> SummaryMaintenanceLifecycleAlternative {
-    let lifecycle = SummaryMaintenanceLifecycle::Shared {
-        retention: asap_types::workload::DurationMs(horizon.map_or(0, |h| (h.0 * 1000.0) as u64)),
-    };
-    if !capabilities.supports_shared {
-        return rejected(
-            lifecycle,
-            SummaryMaintenanceLifecycleRejection::UnsupportedByRuntime,
-        );
-    }
-    if let Some(rejection) = maintenance_capability_rejection(facts, summary_capabilities) {
-        return rejected(lifecycle, rejection);
-    }
-    if facts.reads.is_none_or(|reads| reads <= 1.0) {
-        return rejected(
-            lifecycle,
-            SummaryMaintenanceLifecycleRejection::RequiresMultipleReads,
-        );
-    }
-    let Some(horizon) = horizon else {
-        return rejected(
-            lifecycle,
-            SummaryMaintenanceLifecycleRejection::RequiresHorizon,
-        );
-    };
-    let total_cost = retained_cost(facts, costs, horizon.0);
-    costed_or_unknown(
-        lifecycle,
-        total_cost,
-        vec!["one state is shared across reads".into()],
-    )
-}
-
-fn continuous(
-    facts: &SummaryMaintenanceWorkloadFacts,
-    horizon: Option<Horizon>,
-    capabilities: SummaryMaintenanceLifecycleCapabilities,
-    summary_capabilities: SummaryMaintenanceCapabilities,
-    costs: &SummaryMaintenanceLifecycleCostInputs,
-) -> SummaryMaintenanceLifecycleAlternative {
-    let lifecycle = SummaryMaintenanceLifecycle::ContinuouslyMaintained;
-    if !capabilities.supports_continuously_maintained {
-        return rejected(
-            lifecycle,
-            SummaryMaintenanceLifecycleRejection::UnsupportedByRuntime,
-        );
-    }
-    if !matches!(
-        facts.arrival,
-        DataArrival::ContinuouslyIngesting | DataArrival::Mixed
-    ) {
-        return rejected(
-            lifecycle,
-            SummaryMaintenanceLifecycleRejection::RequiresContinuousData,
-        );
-    }
-    if facts.update_rate.is_none() {
-        return rejected(
-            lifecycle,
-            SummaryMaintenanceLifecycleRejection::MissingOrStaleIngestionRate,
-        );
-    }
-    if let Some(rejection) = maintenance_capability_rejection(facts, summary_capabilities) {
-        return rejected(lifecycle, rejection);
-    }
-    let Some(horizon) = horizon else {
-        return rejected(
-            lifecycle,
-            SummaryMaintenanceLifecycleRejection::RequiresHorizon,
-        );
-    };
-    let total_cost = retained_cost(facts, costs, horizon.0);
-    costed_or_unknown(
-        lifecycle,
-        total_cost,
-        vec!["updates are applied for the optimization horizon".into()],
-    )
-}
-
-fn maintenance_capability_rejection(
-    facts: &SummaryMaintenanceWorkloadFacts,
-    capabilities: SummaryMaintenanceCapabilities,
-) -> Option<SummaryMaintenanceLifecycleRejection> {
-    if matches!(
-        facts.arrival,
-        DataArrival::ContinuouslyIngesting | DataArrival::Mixed
-    ) && !capabilities.incremental_update
-    {
-        Some(SummaryMaintenanceLifecycleRejection::SummaryDoesNotSupportIncrementalUpdates)
-    } else if matches!(
-        facts.arrival,
-        DataArrival::ContinuouslyIngesting | DataArrival::Mixed
-    ) && facts.requires_deletion
-        && !capabilities.delete
-    {
-        Some(SummaryMaintenanceLifecycleRejection::SummaryDoesNotSupportDeletion)
-    } else {
-        None
-    }
-}
-
-fn retained_cost(
-    facts: &SummaryMaintenanceWorkloadFacts,
-    costs: &SummaryMaintenanceLifecycleCostInputs,
-    seconds: f64,
-) -> Option<Cost> {
-    let reads = facts.reads?;
-    let maintenance = maintenance_cost(facts, costs, seconds)?;
-    Some(Cost(
-        costs.build_cost?.0
-            + maintenance
-            + reads * costs.summary_read_cost?.0
-            + seconds * costs.retention_cost_rate?.0
-            + costs.retirement_cost?.0,
-    ))
-}
-
-fn maintenance_cost(
-    facts: &SummaryMaintenanceWorkloadFacts,
-    costs: &SummaryMaintenanceLifecycleCostInputs,
-    seconds: f64,
-) -> Option<f64> {
-    match facts.arrival {
-        DataArrival::AtRest => Some(0.0),
-        DataArrival::ContinuouslyIngesting | DataArrival::Mixed => {
-            Some(seconds * facts.update_rate?.0 * costs.maintenance_cost_per_update?.0)
-        }
-        DataArrival::Unknown => None,
-    }
-}
-
-fn zip_costs(costs: &[Option<Cost>]) -> Option<f64> {
-    costs
-        .iter()
-        .try_fold(0.0, |sum, cost| Some(sum + cost.as_ref()?.0))
-}
-
-fn costed_or_unknown(
-    summary_maintenance_lifecycle: SummaryMaintenanceLifecycle,
-    total_cost: Option<Cost>,
-    assumptions: Vec<String>,
-) -> SummaryMaintenanceLifecycleAlternative {
-    SummaryMaintenanceLifecycleAlternative {
-        summary_maintenance_lifecycle,
-        total_cost,
-        rejection: total_cost
-            .is_none()
-            .then_some(SummaryMaintenanceLifecycleRejection::MissingCostEvidence),
-        assumptions,
-    }
-}
-
-fn rejected(
-    summary_maintenance_lifecycle: SummaryMaintenanceLifecycle,
-    rejection: SummaryMaintenanceLifecycleRejection,
-) -> SummaryMaintenanceLifecycleAlternative {
-    SummaryMaintenanceLifecycleAlternative {
-        summary_maintenance_lifecycle,
-        total_cost: None,
-        rejection: Some(rejection),
-        assumptions: Vec::new(),
-    }
-}
-
-#[derive(Clone, Copy, PartialEq)]
-enum StateKind {
-    SummaryAgg,
-    Population,
-}
-
-/// Collect every unique node of `kind` reachable from `node`.
-fn collect_states(
-    node: &Rc<OperatorNode>,
-    seen: &mut HashSet<*const OperatorNode>,
-    output: &mut Vec<Rc<OperatorNode>>,
-    kind: StateKind,
-) {
-    if !seen.insert(Rc::as_ptr(node)) {
-        return;
-    }
-    if matches!(
-        (&node.operator, kind),
-        (
-            Operator::ASAP(ASAPOp::SummaryAgg { .. }),
-            StateKind::SummaryAgg
-        ) | (
-            Operator::ASAP(ASAPOp::MaintainPopulation { .. }),
-            StateKind::Population
-        )
-    ) {
-        output.push(Rc::clone(node));
-    }
-    for child in node.children() {
-        collect_states(child, seen, output, kind);
-    }
-}
-
-/// Maintained populations that are not an input of any `SummaryAgg`. A
-/// population feeding summary state is on that state's maintenance path, so
-/// that state's lifecycle times it, even when a evaluation also reads it directly.
-fn standalone_populations(root: &Rc<OperatorNode>) -> Vec<Rc<OperatorNode>> {
-    let mut summaries = Vec::new();
-    collect_states(
-        root,
-        &mut HashSet::new(),
-        &mut summaries,
-        StateKind::SummaryAgg,
-    );
-    let mut nested = Vec::new();
-    let mut seen = HashSet::new();
-    for summary in &summaries {
-        collect_states(summary, &mut seen, &mut nested, StateKind::Population);
-    }
-    let nested: HashSet<_> = nested.iter().map(Rc::as_ptr).collect();
-    let mut populations = Vec::new();
-    collect_states(
-        root,
-        &mut HashSet::new(),
-        &mut populations,
-        StateKind::Population,
-    );
-    populations.retain(|population| !nested.contains(&Rc::as_ptr(population)));
-    populations
-}
-
-pub(crate) fn evaluation_schedule(
-    lifecycle: &SummaryMaintenanceLifecycle,
-    arrival: DataArrival,
-) -> EvaluationSchedule {
-    match lifecycle {
-        SummaryMaintenanceLifecycle::Ephemeral => EvaluationSchedule::OneShot,
-        SummaryMaintenanceLifecycle::Prepared { .. }
-        | SummaryMaintenanceLifecycle::Shared { .. }
-            if matches!(
-                arrival,
-                DataArrival::ContinuouslyIngesting | DataArrival::Mixed
-            ) =>
-        {
-            EvaluationSchedule::PerUpdate
-        }
-        SummaryMaintenanceLifecycle::Prepared { .. } => EvaluationSchedule::OneShot,
-        SummaryMaintenanceLifecycle::Shared { .. } => EvaluationSchedule::OnRead,
-        SummaryMaintenanceLifecycle::ContinuouslyMaintained => EvaluationSchedule::PerUpdate,
-    }
-}
-
-/// Summary states composed on one maintenance path must be produced on the
-/// same schedule. Return a component id for each collected state.
-fn summary_state_components(summaries: &[Rc<OperatorNode>]) -> Vec<usize> {
-    let indices: HashMap<_, _> = summaries
-        .iter()
-        .enumerate()
-        .map(|(index, summary)| (Rc::as_ptr(summary), index))
-        .collect();
-    let mut parents: Vec<_> = (0..summaries.len()).collect();
-
-    fn find(parents: &mut [usize], index: usize) -> usize {
-        if parents[index] != index {
-            parents[index] = find(parents, parents[index]);
-        }
-        parents[index]
-    }
-
-    for (parent_index, summary) in summaries.iter().enumerate() {
-        let Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) = &summary.operator else {
-            continue;
-        };
-        if !matches!(
-            child.operator,
-            Operator::ASAP(
-                ASAPOp::SummaryAgg { .. }
-                    | ASAPOp::SummaryJoin { .. }
-                    | ASAPOp::SummarySubtract { .. }
-                    | ASAPOp::SummaryDelete { .. }
-                    | ASAPOp::SummaryMerge { .. }
-            )
-        ) {
-            continue;
-        }
-        let mut descendants = Vec::new();
-        collect_states(
-            child,
-            &mut HashSet::new(),
-            &mut descendants,
-            StateKind::SummaryAgg,
-        );
-        for descendant in descendants {
-            let child_index = indices[&Rc::as_ptr(&descendant)];
-            let parent_root = find(&mut parents, parent_index);
-            let child_root = find(&mut parents, child_index);
-            parents[child_root] = parent_root;
-        }
-    }
-    (0..parents.len())
-        .map(|index| find(&mut parents, index))
-        .collect()
-}
-
-/// Inputs shared by every complete lifecycle-combination evaluation of one
-/// root, whether Planner searches combinations or a caller supplies one.
-struct CompleteCostContext<'a> {
-    root: &'a OperatorNode,
-    components: &'a [usize],
-    cost_model: &'a dyn CostModel,
-    comparison_target: Option<&'a OperatorNode>,
-    horizon: Option<Horizon>,
-    expected_reads: Option<f64>,
-    required_accuracy: &'a [AccuracyTarget],
-}
-
-impl CompleteCostContext<'_> {
-    /// Planner's own admission rule for one alternative. Uncosted alternatives
-    /// are admitted only when the complete-candidate hook is authoritative.
-    fn eligible(&self, alternative: &SummaryMaintenanceLifecycleAlternative) -> bool {
-        alternative.selectable()
-            || (self
-                .cost_model
-                .complete_summary_candidate_estimate_covers_lifecycle_costs()
-                && alternative.rejection
-                    == Some(SummaryMaintenanceLifecycleRejection::MissingCostEvidence))
-    }
-
-    /// `selected` holds one entry per deployment, in deployment order.
-    fn schedules_compatible(
-        &self,
-        selected: &[(usize, SummaryMaintenanceLifecycleGuarantee, Cost)],
-    ) -> bool {
-        !selected.iter().enumerate().any(|(left, (_, a, _))| {
-            selected.iter().enumerate().any(|(right, (_, b, _))| {
-                self.components[left] == self.components[right]
-                    && a.evaluation_schedule != b.evaluation_schedule
-            })
-        })
-    }
-
-    fn estimate(
-        &self,
-        deployments: &[SummaryMaintenanceDeployment],
-        selected: &[(usize, SummaryMaintenanceLifecycleGuarantee, Cost)],
-    ) -> Option<CompleteSummaryCandidateEstimate> {
-        if !self.schedules_compatible(selected) {
-            return None;
-        }
-        let costed: Vec<_> = selected
-            .iter()
-            .map(|(index, guarantee, cost)| CostedSummaryDeployment {
-                summary: &deployments[*index].summary,
-                guarantee,
-                selected_cost: *cost,
-            })
-            .collect();
-        let estimate = self.cost_model.complete_summary_candidate_estimate(
-            self.root,
-            self.comparison_target,
-            &costed,
-            self.horizon,
-            self.expected_reads,
-            self.required_accuracy,
-        )?;
-        (estimate.window_frameworks.len() == deployments.len()).then_some(estimate)
-    }
-}
-
-fn lifecycle_guarantee(
-    lifecycle: &SummaryMaintenanceLifecycle,
-    arrival: DataArrival,
-) -> SummaryMaintenanceLifecycleGuarantee {
-    SummaryMaintenanceLifecycleGuarantee {
-        summary_maintenance_mode: maintenance_mode(lifecycle, arrival),
-        evaluation_schedule: evaluation_schedule(lifecycle, arrival),
-        summary_maintenance_lifecycle: lifecycle.clone(),
-        output_representation: OutputRepresentation::SummaryState,
-    }
-}
-
-fn apply_selection(
-    deployments: &mut [SummaryMaintenanceDeployment],
-    guarantees: Vec<(usize, SummaryMaintenanceLifecycleGuarantee)>,
-    estimate: &CompleteSummaryCandidateEstimate,
-) {
-    for (index, guarantee) in guarantees {
-        deployments[index].summary_maintenance_lifecycle_guarantee = Some(guarantee);
-    }
-    for (deployment, framework) in deployments
-        .iter_mut()
-        .zip(estimate.window_frameworks.iter().cloned())
-    {
-        deployment.selected_window_framework = framework;
-    }
-}
-
-#[expect(clippy::too_many_arguments, reason = "complete combination context")]
-fn select_complete_lifecycle_combination(
-    root: &OperatorNode,
-    deployments: &mut [SummaryMaintenanceDeployment],
-    components: &[usize],
-    arrival: DataArrival,
-    cost_model: &dyn CostModel,
-    comparison_target: Option<&OperatorNode>,
-    horizon: Option<Horizon>,
-    expected_reads: Option<f64>,
-    required_accuracy: &[AccuracyTarget],
-) -> Option<CompleteSummaryCandidateEstimate> {
-    const MAX_COMPLETE_LIFECYCLE_COMBINATIONS: usize = 4_096;
-    if deployments.is_empty() {
-        return None;
-    }
-    let context = CompleteCostContext {
-        root,
-        components,
-        cost_model,
-        comparison_target,
-        horizon,
-        expected_reads,
-        required_accuracy,
-    };
-    // The whole-candidate hook is intentionally arbitrary, so partial costs
-    // cannot soundly prune the search. Bound exhaustive enumeration and fail
-    // closed instead of allowing an adversarial DAG to consume exponential
-    // planner time.
-    let combinations = deployments
-        .iter()
-        .try_fold(1_usize, |product, deployment| {
-            let selectable = deployment
-                .alternatives
-                .iter()
-                .filter(|alternative| context.eligible(alternative))
-                .count();
-            product.checked_mul(selectable)
-        })?;
-    if combinations == 0 || combinations > MAX_COMPLETE_LIFECYCLE_COMBINATIONS {
-        return None;
-    }
-    type Best = Option<(
-        CompleteSummaryCandidateEstimate,
-        Vec<(usize, SummaryMaintenanceLifecycleGuarantee)>,
-    )>;
-    fn visit(
-        index: usize,
-        context: &CompleteCostContext<'_>,
-        deployments: &[SummaryMaintenanceDeployment],
-        arrival: DataArrival,
-        selected: &mut Vec<(usize, SummaryMaintenanceLifecycleGuarantee, Cost)>,
-        best: &mut Best,
-    ) {
-        if index == deployments.len() {
-            let Some(estimate) = context.estimate(deployments, selected) else {
-                return;
-            };
-            if best
-                .as_ref()
-                .is_none_or(|(best_estimate, _)| estimate.cost.0 < best_estimate.cost.0)
-            {
-                *best = Some((
-                    estimate,
-                    selected
-                        .iter()
-                        .map(|(index, guarantee, _)| (*index, guarantee.clone()))
-                        .collect(),
-                ));
-            }
-            return;
-        }
-        for alternative in deployments[index]
-            .alternatives
-            .iter()
-            .filter(|alternative| context.eligible(alternative))
-        {
-            selected.push((
-                index,
-                lifecycle_guarantee(&alternative.summary_maintenance_lifecycle, arrival),
-                alternative.total_cost.unwrap_or(Cost::ZERO),
-            ));
-            visit(index + 1, context, deployments, arrival, selected, best);
-            selected.pop();
-        }
-    }
-
-    let mut best = None;
-    visit(
-        0,
-        &context,
-        deployments,
-        arrival,
-        &mut Vec::new(),
-        &mut best,
-    );
-    let (estimate, guarantees) = best?;
-    apply_selection(deployments, guarantees, &estimate);
-    Some(estimate)
-}
-
-pub(crate) fn maintenance_mode(
-    lifecycle: &SummaryMaintenanceLifecycle,
-    arrival: DataArrival,
-) -> SummaryMaintenanceMode {
-    match lifecycle {
-        SummaryMaintenanceLifecycle::Ephemeral => SummaryMaintenanceMode::DirectBuild,
-        SummaryMaintenanceLifecycle::ContinuouslyMaintained => SummaryMaintenanceMode::Incremental,
-        SummaryMaintenanceLifecycle::Prepared { .. }
-        | SummaryMaintenanceLifecycle::Shared { .. } => match arrival {
-            DataArrival::ContinuouslyIngesting | DataArrival::Mixed => {
-                SummaryMaintenanceMode::Incremental
-            }
-            DataArrival::AtRest | DataArrival::Unknown => SummaryMaintenanceMode::DirectBuild,
-        },
-    }
-}
-
-#[cfg(test)]
-mod tests {
-    // Independent data evidence must be validated at both planning boundaries.
-    #[test]
-    fn rejects_invalid_parallel_data_evidence() {
-        let query = workload(vec![batch(Predictability::AdHoc)], vec![], at_rest());
-        let space = crate::replacement::search_workload(vec![("q", quantile_query())]);
-        for rate in [1.0, -1.0, f64::NAN, f64::INFINITY] {
-            let mut data = at_rest();
-            data.ingestion_rate.value = Some(Rate(rate));
-            assert!(space
-                .recurrence_profiles_from_workload(&query, Some(&data), &[0], 0, None)
-                .is_err());
-            assert!(plan_summary_maintenance_lifecycles(
-                summary(),
-                WorkloadDemand::new_with_data(&query, &data, &[0]),
-                0,
-                None,
-                SummaryMaintenanceLifecycleCapabilities::ALL,
-                &crate::cost_model::DefaultCostModel,
-            )
-            .is_err());
-        }
-    }
-    use super::*;
-    use asap_types::ir::export::{NonASAPOpKind, PhysicalASAPOperatorPayload};
-    use asap_types::ir::{BinaryOperator, NonASAPOp};
-    use asap_types::post_asap::{
-        ExactKind, ExactParams, Field, FieldDataType, GroupingStrategy, ResultGuarantee, Schema,
-        SketchAlgorithm,
-    };
-    use asap_types::pre_asap::AggIntent;
-    use asap_types::pre_asap::{
-        ArithmeticOpKind, BinaryOpKind, ColumnRef, DataType, Reduction, Source,
-    };
-    use asap_types::types::AccuracyTarget;
-    use asap_types::workload::{
-        BatchEntry, DataWorkload, DurationMs, Evidence, EvidenceSource, Predictability, Query,
-        QueryLanguage, QueryRequirements, Rate, RepeatingEntry, RepetitionInterval, TimeSelection,
-    };
-
-    struct UnitCosts;
-
-    impl CostModel for UnitCosts {
-        fn rank_candidates(
-            &self,
-            _intent: &asap_types::pre_asap::AggIntent,
-            candidates: &[asap_types::post_asap::SketchAlgorithm],
-        ) -> Vec<asap_types::post_asap::SketchAlgorithm> {
-            candidates.to_vec()
-        }
-
-        fn summary_maintenance_lifecycle_cost_inputs(
-            &self,
-            _summary: &OperatorNode,
-        ) -> SummaryMaintenanceLifecycleCostInputs {
-            SummaryMaintenanceLifecycleCostInputs {
-                build_cost: Some(Cost(10.0)),
-                maintenance_cost_per_update: Some(Cost(1.0)),
-                summary_read_cost: Some(Cost(1.0)),
-                retention_cost_rate: Some(CostRate(0.1)),
-                retirement_cost: Some(Cost(1.0)),
-            }
-        }
-
-        fn summary_maintenance_capabilities(
-            &self,
-            _summary: &OperatorNode,
-        ) -> SummaryMaintenanceCapabilities {
-            SummaryMaintenanceCapabilities {
-                incremental_update: true,
-                merge: true,
-                delete: true,
-            }
-        }
-    }
-
-    struct RawCheaper;
-
-    impl CostModel for RawCheaper {
-        fn rank_candidates(
-            &self,
-            _intent: &asap_types::pre_asap::AggIntent,
-            candidates: &[asap_types::post_asap::SketchAlgorithm],
-        ) -> Vec<asap_types::post_asap::SketchAlgorithm> {
-            candidates.to_vec()
-        }
-
-        fn summary_maintenance_lifecycle_cost_inputs(
-            &self,
-            summary: &OperatorNode,
-        ) -> SummaryMaintenanceLifecycleCostInputs {
-            UnitCosts.summary_maintenance_lifecycle_cost_inputs(summary)
-        }
-
-        fn summary_maintenance_capabilities(
-            &self,
-            summary: &OperatorNode,
-        ) -> SummaryMaintenanceCapabilities {
-            UnitCosts.summary_maintenance_capabilities(summary)
-        }
-
-        fn raw_query_recompute_cost(&self, _target: &OperatorNode) -> Option<Cost> {
-            Some(Cost(1.0))
-        }
-    }
-
-    struct NoDelete;
-
-    impl CostModel for NoDelete {
-        fn rank_candidates(
-            &self,
-            _intent: &asap_types::pre_asap::AggIntent,
-            candidates: &[asap_types::post_asap::SketchAlgorithm],
-        ) -> Vec<asap_types::post_asap::SketchAlgorithm> {
-            candidates.to_vec()
-        }
-
-        fn summary_maintenance_lifecycle_cost_inputs(
-            &self,
-            summary: &OperatorNode,
-        ) -> SummaryMaintenanceLifecycleCostInputs {
-            UnitCosts.summary_maintenance_lifecycle_cost_inputs(summary)
-        }
-
-        fn summary_maintenance_capabilities(
-            &self,
-            _summary: &OperatorNode,
-        ) -> SummaryMaintenanceCapabilities {
-            SummaryMaintenanceCapabilities {
-                incremental_update: true,
-                merge: true,
-                delete: false,
-            }
-        }
-    }
-
-    struct SummaryMaintenancePrefersDdSketch;
-
-    impl CostModel for SummaryMaintenancePrefersDdSketch {
-        fn raw_query_recompute_total_cost(
-            &self,
-            _target: &OperatorNode,
-            _expected_reads: f64,
-        ) -> Option<Cost> {
-            Some(Cost(1_000.0))
-        }
-
-        fn rank_candidates(
-            &self,
-            _intent: &AggIntent,
-            candidates: &[SketchAlgorithm],
-        ) -> Vec<SketchAlgorithm> {
-            // Preserve semantic mapping's KLL-first order. The lifecycle
-            // total below must be what changes the final choice.
-            candidates.to_vec()
-        }
-
-        fn summary_maintenance_lifecycle_cost_inputs(
-            &self,
-            summary: &OperatorNode,
-        ) -> SummaryMaintenanceLifecycleCostInputs {
-            let build = match sketch_algorithm(summary) {
-                Some(SketchAlgorithm::Kll) => 100.0,
-                Some(SketchAlgorithm::DDSketch) => 1.0,
-                _ => 10.0,
-            };
-            SummaryMaintenanceLifecycleCostInputs {
-                build_cost: Some(Cost(build)),
-                maintenance_cost_per_update: Some(Cost(1.0)),
-                summary_read_cost: Some(Cost(1.0)),
-                retention_cost_rate: Some(CostRate(0.1)),
-                retirement_cost: Some(Cost(1.0)),
-            }
-        }
-    }
-
-    struct IncompatibleNestedCosts;
-
-    struct WholeCandidatePrefersContinuous;
-
-    impl CostModel for WholeCandidatePrefersContinuous {
-        fn rank_candidates(
-            &self,
-            _intent: &AggIntent,
-            candidates: &[SketchAlgorithm],
-        ) -> Vec<SketchAlgorithm> {
-            candidates.to_vec()
-        }
-
-        fn complete_summary_candidate_cost(
-            &self,
-            _root: &OperatorNode,
-            _target: Option<&OperatorNode>,
-            deployments: &[CostedSummaryDeployment<'_>],
-            _horizon: Option<Horizon>,
-            _expected_reads: Option<f64>,
-            _required_accuracy: &[AccuracyTarget],
-        ) -> Option<Cost> {
-            Some(
-                if deployments.iter().all(|deployment| {
-                    matches!(
-                        deployment.guarantee.summary_maintenance_lifecycle,
-                        SummaryMaintenanceLifecycle::ContinuouslyMaintained
-                    )
-                }) {
-                    Cost(1.0)
-                } else {
-                    Cost(100.0)
-                },
-            )
-        }
-    }
-
-    impl CostModel for IncompatibleNestedCosts {
-        fn rank_candidates(
-            &self,
-            _intent: &AggIntent,
-            candidates: &[SketchAlgorithm],
-        ) -> Vec<SketchAlgorithm> {
-            candidates.to_vec()
-        }
-
-        fn summary_maintenance_lifecycle_cost_inputs(
-            &self,
-            summary: &OperatorNode,
-        ) -> SummaryMaintenanceLifecycleCostInputs {
-            // A leaf summary is one built directly over kept pre-ASAP rows
-            // (its child is not an ASAP node); a nested one reads state.
-            let is_leaf = matches!(
-                &summary.operator,
-                Operator::ASAP(ASAPOp::SummaryAgg { child, .. }) if !child.is_asap()
-            );
-            SummaryMaintenanceLifecycleCostInputs {
-                build_cost: Some(Cost(if is_leaf { 1.0 } else { 100.0 })),
-                maintenance_cost_per_update: Some(Cost(if is_leaf { 100.0 } else { 0.0 })),
-                summary_read_cost: Some(Cost::ZERO),
-                retention_cost_rate: Some(CostRate(0.0)),
-                retirement_cost: Some(Cost::ZERO),
-            }
-        }
-
-        fn summary_maintenance_capabilities(
-            &self,
-            _summary: &OperatorNode,
-        ) -> SummaryMaintenanceCapabilities {
-            SummaryMaintenanceCapabilities {
-                incremental_update: true,
-                merge: true,
-                delete: true,
-            }
-        }
-    }
-
-    /// The sketch algorithm of the first `SummaryAgg` reachable from `node`
-    /// (through a evaluation or any relational operator kept above it).
-    fn sketch_algorithm(node: &OperatorNode) -> Option<SketchAlgorithm> {
-        if let Operator::ASAP(ASAPOp::SummaryAgg {
-            family: FieldDataType::Sketch(kind, _),
-            ..
-        }) = &node.operator
-        {
-            return Some(kind.algorithm().clone());
-        }
-        node.children()
-            .into_iter()
-            .find_map(|child| sketch_algorithm(child))
-    }
-
-    fn query_root() -> Rc<OperatorNode> {
-        query_root_for("m")
-    }
-
-    fn query_root_for(metric: &str) -> Rc<OperatorNode> {
-        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Scan {
-            source: Source::TimeSeries {
-                metric: metric.into(),
-            },
-            predicates: vec![],
-            schema: Schema::with_time_index(
-                vec![
-                    Field::plain("ts", DataType::Timestamp, false),
-                    Field::plain("value", DataType::Float64, false),
-                ],
-                0,
-                vec![],
-            ),
-        }))
-        .unwrap()
-    }
-
-    fn sum_query() -> Rc<OperatorNode> {
-        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
-            reduction: Reduction::by(vec![]),
-            measures: vec![AggIntent::Sum { col: None }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: query_root(),
-        }))
-        .unwrap()
-    }
-
-    fn quantile_query() -> Rc<OperatorNode> {
-        OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
-            reduction: Reduction::by(vec![]),
-            measures: vec![AggIntent::Quantile {
-                col: None,
-                q: 0.99,
-                accuracy: AccuracyTarget::Epsilon(0.1),
-            }],
-            output_names: vec![],
-            filters: vec![],
-            having: None,
-            child: query_root(),
-        }))
-        .unwrap()
-    }
-
-    /// An exact sum accumulator over the kept pre-ASAP scan.
-    fn summary() -> Rc<OperatorNode> {
-        let child = Rc::new(
-            query_root()
-                .as_ref()
-                .clone()
-                .with_guarantee(Some(ResultGuarantee::exact("raw"))),
-        );
-        let family = FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum);
-        std::rc::Rc::new(
-            OperatorNode::with_schema(
-                asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
-                    child,
-                    family: family.clone(),
-                    input: asap_types::post_asap::SummaryUpdate::column(ColumnRef::Named(
-                        "value".into(),
-                    )),
-                    reduction: Reduction::by(vec![]),
-                    grouping: GroupingStrategy::default(),
-                    filter: None,
-                }),
-                Schema::lifted(vec![Field::new("state", family, false)], None),
-            )
-            .with_guarantee(Some(ResultGuarantee::exact("sum"))),
-        )
-    }
-
-    fn nested_summary() -> Rc<OperatorNode> {
-        let child = summary();
-        let family = FieldDataType::ExactAggregate(ExactKind::Sum, ExactParams::Sum);
-        std::rc::Rc::new(
-            OperatorNode::with_schema(
-                asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
-                    child,
-                    family: family.clone(),
-                    input: asap_types::post_asap::SummaryUpdate::column(ColumnRef::Named(
-                        "state".into(),
-                    )),
-                    reduction: Reduction::by(vec![]),
-                    grouping: GroupingStrategy::default(),
-                    filter: None,
-                }),
-                Schema::lifted(vec![Field::new("state", family, false)], None),
-            )
-            .with_guarantee(Some(ResultGuarantee::exact("nested sum"))),
-        )
-    }
-
-    fn batch(predictability: Predictability) -> BatchEntry {
-        BatchEntry {
-            query: Query("sum(m)".into()),
-            requirements: QueryRequirements::default(),
-            predictability,
-            invocations: 1,
-            execute_at: None,
-            time_selection: TimeSelection::default(),
-        }
-    }
-
-    fn workload(
-        batches: Vec<BatchEntry>,
-        repeating: Vec<RepeatingEntry>,
-        _data: DataWorkload,
-    ) -> QueryWorkload {
-        QueryWorkload {
-            language: QueryLanguage::PromQL,
-            query_batch: (!batches.is_empty()).then_some(batches),
-            repeating_queries: (!repeating.is_empty()).then_some(repeating),
-        }
-    }
-
-    fn at_rest() -> DataWorkload {
-        DataWorkload {
-            arrival: DataArrival::AtRest,
-            data_ingestion_interval: Evidence {
-                value: Some(DurationMs(1_000)),
-                ..Default::default()
-            },
-            ..Default::default()
-        }
-    }
-
-    fn continuous(observed_at_ms: u64, valid_for_ms: u64) -> DataWorkload {
-        DataWorkload {
-            arrival: DataArrival::ContinuouslyIngesting,
-            data_ingestion_interval: Evidence {
-                value: Some(DurationMs(1_000)),
-                ..Default::default()
-            },
-            ingestion_rate: Evidence {
-                value: Some(Rate(1.0)),
-                source: EvidenceSource::Observed,
-                observed_at_ms: Some(observed_at_ms),
-                valid_for_ms: Some(valid_for_ms),
-            },
-            ..Default::default()
-        }
-    }
-
-    fn repeating() -> RepeatingEntry {
-        RepeatingEntry {
-            query: Query("sum(m)".into()),
-            demand: RepeatedDemand::FixedInterval(RepetitionInterval(1_000)),
-            requirements: QueryRequirements::default(),
-            predictability: Predictability::Predictable { known_at: None },
-            time_selection: TimeSelection::default(),
-        }
-    }
-
-    fn selected_summary_maintenance_lifecycle(
-        deployment: &SummaryMaintenanceDeployment,
-    ) -> Option<&SummaryMaintenanceLifecycle> {
-        deployment
-            .summary_maintenance_lifecycle_guarantee
-            .as_ref()
-            .map(|guarantee| &guarantee.summary_maintenance_lifecycle)
-    }
-
-    #[test]
-    fn fixed_interval_reads_use_the_physical_horizon_multiplicity() {
-        let mut query = repeating();
-        query.demand = RepeatedDemand::FixedInterval(RepetitionInterval(600));
-        let workload = workload(vec![], vec![query], at_rest());
-
-        let facts =
-            workload_facts(&workload, Some(&at_rest()), &[0], 0, Some(Horizon(1.0))).unwrap();
-
-        assert_eq!(facts.reads, Some(1.0));
-    }
-
-    #[test]
-    fn unpredictable_one_time_at_rest_selects_ephemeral() {
-        let plan = plan_summary_maintenance_lifecycles(
-            summary(),
-            WorkloadDemand::new_without_data(
-                &workload(vec![batch(Predictability::AdHoc)], vec![], at_rest()),
-                &[0],
-            ),
-            1_000,
-            None,
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &UnitCosts,
-        )
-        .unwrap();
-        assert_eq!(plan.deployments.len(), 1);
-        assert_eq!(
-            selected_summary_maintenance_lifecycle(&plan.deployments[0]),
-            Some(&SummaryMaintenanceLifecycle::Ephemeral)
-        );
-        let guarantee = plan.deployments[0]
-            .summary_maintenance_lifecycle_guarantee
-            .as_ref()
-            .unwrap();
-        assert_eq!(guarantee.evaluation_schedule, EvaluationSchedule::OneShot);
-        assert_eq!(
-            guarantee.summary_maintenance_mode,
-            SummaryMaintenanceMode::DirectBuild
-        );
-        assert_eq!(
-            guarantee.output_representation,
-            OutputRepresentation::SummaryState
-        );
-        assert_eq!(
-            plan.deployments[0].alternatives[0].total_cost,
-            Some(Cost(12.0))
-        );
-    }
-
-    #[test]
-    fn predictable_scheduled_one_time_offers_prepared_state() {
-        let mut entry = batch(Predictability::Predictable {
-            known_at: Some(TimestampMs(1_000)),
-        });
-        entry.execute_at = Some(TimestampMs(11_000));
-        let plan = plan_summary_maintenance_lifecycles(
-            summary(),
-            WorkloadDemand::new_with_data(
-                &workload(vec![entry], vec![], at_rest()),
-                &at_rest(),
-                &[0],
-            ),
-            1_000,
-            None,
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &UnitCosts,
-        )
-        .unwrap();
-        let prepared = &plan.deployments[0].alternatives[1];
-        assert!(prepared.rejection.is_none());
-        assert_eq!(prepared.total_cost, Some(Cost(13.0)));
-    }
-
-    #[test]
-    fn prepared_state_starts_no_earlier_than_planning_time() {
-        let mut entry = batch(Predictability::Predictable {
-            known_at: Some(TimestampMs(1_000)),
-        });
-        entry.execute_at = Some(TimestampMs(11_000));
-        let plan = plan_summary_maintenance_lifecycles(
-            summary(),
-            WorkloadDemand::new_with_data(
-                &workload(vec![entry], vec![], at_rest()),
-                &at_rest(),
-                &[0],
-            ),
-            6_000,
-            None,
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &UnitCosts,
-        )
-        .unwrap();
-        let prepared = &plan.deployments[0].alternatives[1];
-        assert_eq!(
-            prepared.summary_maintenance_lifecycle,
-            SummaryMaintenanceLifecycle::Prepared {
-                activate_at: TimestampMs(6_000),
-                retire_at: TimestampMs(11_000),
-            }
-        );
-        assert_eq!(prepared.total_cost, Some(Cost(12.5)));
-    }
-
-    #[test]
-    fn expired_one_time_execution_cannot_select_prepared_state() {
-        let mut entry = batch(Predictability::Predictable {
-            known_at: Some(TimestampMs(1_000)),
-        });
-        entry.execute_at = Some(TimestampMs(2_000));
-        let plan = plan_summary_maintenance_lifecycles(
-            summary(),
-            WorkloadDemand::new_without_data(&workload(vec![entry], vec![], at_rest()), &[0]),
-            3_000,
-            None,
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &UnitCosts,
-        )
-        .unwrap();
-        assert_eq!(
-            plan.deployments[0].alternatives[1].rejection,
-            Some(SummaryMaintenanceLifecycleRejection::RequiresPredictableOneTimeQuery)
-        );
-    }
-
-    #[test]
-    fn nested_summary_lifecycles_have_compatible_evaluation_schedules() {
-        let workload = workload(vec![], vec![repeating()], continuous(1_000, 20_000));
-        let plan = plan_summary_maintenance_lifecycles(
-            nested_summary(),
-            WorkloadDemand::new_without_data(&workload, &[0]),
-            1_000,
-            Some(Horizon(10.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &IncompatibleNestedCosts,
-        )
-        .unwrap();
-
-        assert_eq!(plan.deployments.len(), 2);
-        let schedules: HashSet<_> = plan
-            .deployments
-            .iter()
-            .map(|deployment| {
-                deployment
-                    .summary_maintenance_lifecycle_guarantee
-                    .as_ref()
-                    .unwrap()
-                    .evaluation_schedule
-            })
-            .collect();
-        assert_eq!(schedules.len(), 1);
-    }
-
-    #[test]
-    fn repeated_at_rest_selects_shared_without_inventing_updates() {
-        let plan = plan_summary_maintenance_lifecycles(
-            summary(),
-            WorkloadDemand::new_with_data(
-                &workload(vec![], vec![repeating()], at_rest()),
-                &at_rest(),
-                &[0],
-            ),
-            1_000,
-            Some(Horizon(10.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &UnitCosts,
-        )
-        .unwrap();
-        assert_eq!(
-            selected_summary_maintenance_lifecycle(&plan.deployments[0]),
-            Some(&SummaryMaintenanceLifecycle::Shared {
-                retention: DurationMs(10_000)
-            })
-        );
-        assert_eq!(
-            plan.deployments[0]
-                .summary_maintenance_lifecycle_guarantee
-                .as_ref()
-                .unwrap()
-                .summary_maintenance_mode,
-            SummaryMaintenanceMode::DirectBuild
-        );
-        assert_eq!(
-            plan.deployments[0].alternatives[3].rejection,
-            Some(SummaryMaintenanceLifecycleRejection::RequiresContinuousData)
-        );
-        assert_eq!(plan.update_rate, None);
-    }
-
-    #[test]
-    fn repeated_continuous_workload_can_select_continuous_maintenance() {
-        let capabilities = SummaryMaintenanceLifecycleCapabilities {
-            supports_shared: false,
-            ..SummaryMaintenanceLifecycleCapabilities::ALL
-        };
-        let plan = plan_summary_maintenance_lifecycles(
-            summary(),
-            WorkloadDemand::new_with_data(
-                &workload(vec![], vec![repeating()], continuous(1_000, 60_000)),
-                &continuous(1_000, 60_000),
-                &[0],
-            ),
-            1_000,
-            Some(Horizon(10.0)),
-            capabilities,
-            &UnitCosts,
-        )
-        .unwrap();
-        assert_eq!(
-            selected_summary_maintenance_lifecycle(&plan.deployments[0]),
-            Some(&SummaryMaintenanceLifecycle::ContinuouslyMaintained)
-        );
-        assert_eq!(
-            plan.deployments[0]
-                .summary_maintenance_lifecycle_guarantee
-                .as_ref()
-                .unwrap()
-                .summary_maintenance_mode,
-            SummaryMaintenanceMode::Incremental
-        );
-        assert_eq!(plan.evaluation_rate, Some(EvaluationRate(1.0)));
-        assert_eq!(plan.update_rate, Some(UpdateRate(1.0)));
-    }
-
-    #[test]
-    fn stale_ingestion_evidence_cannot_enable_continuous_maintenance() {
-        let plan = plan_summary_maintenance_lifecycles(
-            summary(),
-            WorkloadDemand::new_with_data(
-                &workload(vec![], vec![repeating()], continuous(1_000, 1_000)),
-                &continuous(1_000, 1_000),
-                &[0],
-            ),
-            3_000,
-            Some(Horizon(10.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &UnitCosts,
-        )
-        .unwrap();
-        assert_eq!(
-            plan.deployments[0].alternatives[3].rejection,
-            Some(SummaryMaintenanceLifecycleRejection::MissingOrStaleIngestionRate)
-        );
-        assert_eq!(plan.update_rate, None);
-    }
-
-    #[test]
-    fn unknown_costs_do_not_make_a_long_lived_lifecycle_win() {
-        let plan = plan_summary_maintenance_lifecycles(
-            summary(),
-            WorkloadDemand::new_without_data(
-                &workload(vec![], vec![repeating()], continuous(1_000, 60_000)),
-                &[0],
-            ),
-            1_000,
-            Some(Horizon(10.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &crate::cost_model::DefaultCostModel,
-        )
-        .unwrap();
-        assert_eq!(
-            selected_summary_maintenance_lifecycle(&plan.deployments[0]),
-            None
-        );
-        assert!(plan.deployments[0]
-            .alternatives
-            .iter()
-            .all(|alternative| alternative.rejection.is_some()));
-    }
-
-    #[test]
-    fn unrelated_workload_entries_do_not_create_reuse_for_a_target() {
-        let plan = plan_summary_maintenance_lifecycles(
-            summary(),
-            WorkloadDemand::new_without_data(
-                &workload(
-                    vec![batch(Predictability::AdHoc), batch(Predictability::AdHoc)],
-                    vec![],
-                    at_rest(),
-                ),
-                &[0],
-            ),
-            1_000,
-            Some(Horizon(10.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &UnitCosts,
-        )
-        .unwrap();
-        assert_eq!(
-            selected_summary_maintenance_lifecycle(&plan.deployments[0]),
-            Some(&SummaryMaintenanceLifecycle::Ephemeral)
-        );
-        assert_eq!(
-            plan.deployments[0].alternatives[2].rejection,
-            Some(SummaryMaintenanceLifecycleRejection::RequiresMultipleReads)
-        );
-    }
-
-    #[test]
-    fn scheduled_rate_counts_only_executions_inside_the_horizon() {
-        let mut entry = repeating();
-        entry.demand = RepeatedDemand::Scheduled(vec![
-            TimestampMs(999),
-            TimestampMs(5_000),
-            TimestampMs(20_000),
-        ]);
-        let plan = plan_summary_maintenance_lifecycles(
-            summary(),
-            WorkloadDemand::new_without_data(&workload(vec![], vec![entry], at_rest()), &[0]),
-            1_000,
-            Some(Horizon(10.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &UnitCosts,
-        )
-        .unwrap();
-        assert_eq!(plan.evaluation_rate, Some(EvaluationRate(0.1)));
-    }
-
-    #[test]
-    fn demand_binding_rejects_empty_and_duplicate_entries() {
-        let workload = workload(vec![batch(Predictability::AdHoc)], vec![], at_rest());
-        assert!(matches!(
-            plan_summary_maintenance_lifecycles(
-                summary(),
-                WorkloadDemand::new_without_data(&workload, &[]),
-                1_000,
-                None,
-                SummaryMaintenanceLifecycleCapabilities::ALL,
-                &UnitCosts,
-            ),
-            Err(SummaryMaintenanceLifecyclePlanError::EmptyWorkloadDemand)
-        ));
-        assert!(matches!(
-            plan_summary_maintenance_lifecycles(
-                summary(),
-                WorkloadDemand::new_without_data(&workload, &[0, 0]),
-                1_000,
-                None,
-                SummaryMaintenanceLifecycleCapabilities::ALL,
-                &UnitCosts,
-            ),
-            Err(SummaryMaintenanceLifecyclePlanError::DuplicateWorkloadEntry { index: 0 })
-        ));
-    }
-
-    #[test]
-    fn prepared_requires_every_bound_consumer_to_be_scheduled_and_predictable() {
-        let mut predictable = batch(Predictability::Predictable {
-            known_at: Some(TimestampMs(1_000)),
-        });
-        predictable.execute_at = Some(TimestampMs(2_000));
-        let workload = workload(
-            vec![predictable, batch(Predictability::AdHoc)],
-            vec![],
-            at_rest(),
-        );
-        let plan = plan_summary_maintenance_lifecycles(
-            summary(),
-            WorkloadDemand::new_without_data(&workload, &[0, 1]),
-            1_000,
-            Some(Horizon(10.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &UnitCosts,
-        )
-        .unwrap();
-        assert_eq!(
-            plan.deployments[0].alternatives[1].rejection,
-            Some(SummaryMaintenanceLifecycleRejection::RequiresPredictableOneTimeQuery)
-        );
-    }
-
-    #[test]
-    fn moving_realtime_maintenance_requires_summary_deletion_support() {
-        let mut entry = repeating();
-        entry.time_selection = TimeSelection {
-            scope: asap_types::workload::QueryTimeScope::RealTime,
-            lookback: Some(DurationMs(60_000)),
-            as_of: None,
-        };
-        let plan = plan_summary_maintenance_lifecycles(
-            summary(),
-            WorkloadDemand::new_with_data(
-                &workload(vec![], vec![entry], continuous(1_000, 60_000)),
-                &continuous(1_000, 60_000),
-                &[0],
-            ),
-            1_000,
-            Some(Horizon(10.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &NoDelete,
-        )
-        .unwrap();
-        assert_eq!(
-            plan.deployments[0].alternatives[3].rejection,
-            Some(SummaryMaintenanceLifecycleRejection::SummaryDoesNotSupportDeletion)
-        );
-    }
-
-    #[test]
-    fn lifecycle_cost_can_fall_back_to_raw_recomputation() {
-        let target = sum_query();
-        let space = crate::replacement::search_workload(vec![("q", Rc::clone(&target))]);
-        let selection = space.global_selection(&RawCheaper);
-        let workload = workload(vec![batch(Predictability::AdHoc)], vec![], at_rest());
-        let plan = assemble_selected_dag_with_summary_maintenance_lifecycles(
-            &selection,
-            &space.roots[0].1,
-            WorkloadDemand::new_without_data(&workload, &[0]),
-            1_000,
-            None,
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &RawCheaper,
-        )
-        .unwrap()
-        .unwrap();
-        assert!(plan.selected_raw_recompute);
-        assert_eq!(plan.raw_recompute_total_cost, Some(Cost(1.0)));
-        assert_eq!(plan.summary_total_cost, None);
-        assert!(plan.deployments.is_empty());
-        // The logical query stays exact; deployment assigns execution timing.
-        assert!(!plan.root.contains_asap());
-        assert!(matches!(
-            plan.root.non_asap(),
-            Some(NonASAPOp::Aggregate { .. })
-        ));
-        assert!(plan.root.timing.is_none());
-
-        let exported =
-            crate::summary_maintenance_dag_export::export_summary_maintenance_plan(&plan);
-        assert!(exported.selected_raw_recompute);
-        assert_eq!(exported.raw_recompute_total_cost, Some(1.0));
-        assert_eq!(exported.summary_total_cost, None);
-        assert!(exported.deployments.is_empty());
-    }
-
-    #[test]
-    fn whole_candidate_cost_is_evaluated_before_selecting_a_lifecycle() {
-        let root = summary();
-        let mut deployments = vec![SummaryMaintenanceDeployment {
-            post_asap_node_id: asap_types::ir::export::LogicalASAPNodeId(0),
-            summary: Rc::clone(&root),
-            summary_maintenance_lifecycle_guarantee: None,
-            selected_window_framework: None,
-            alternatives: vec![
-                SummaryMaintenanceLifecycleAlternative {
-                    summary_maintenance_lifecycle: SummaryMaintenanceLifecycle::Ephemeral,
-                    total_cost: Some(Cost(1.0)),
-                    rejection: None,
-                    assumptions: vec![],
-                },
-                SummaryMaintenanceLifecycleAlternative {
-                    summary_maintenance_lifecycle:
-                        SummaryMaintenanceLifecycle::ContinuouslyMaintained,
-                    total_cost: Some(Cost(10.0)),
-                    rejection: None,
-                    assumptions: vec![],
-                },
-            ],
-        }];
-
-        let total = select_complete_lifecycle_combination(
-            &root,
-            &mut deployments,
-            &[0],
-            DataArrival::ContinuouslyIngesting,
-            &WholeCandidatePrefersContinuous,
-            None,
-            Some(Horizon(10.0)),
-            Some(2.0),
-            &[],
-        );
-
-        assert_eq!(total.map(|estimate| estimate.cost), Some(Cost(1.0)));
-        assert!(matches!(
-            deployments[0]
-                .summary_maintenance_lifecycle_guarantee
-                .as_ref()
-                .unwrap()
-                .summary_maintenance_lifecycle,
-            SummaryMaintenanceLifecycle::ContinuouslyMaintained
-        ));
-    }
-
-    #[test]
-    fn complete_lifecycle_enumeration_fails_closed_above_safe_bound() {
-        let root = summary();
-        let alternatives = vec![
-            SummaryMaintenanceLifecycleAlternative {
-                summary_maintenance_lifecycle: SummaryMaintenanceLifecycle::Ephemeral,
-                total_cost: Some(Cost(1.0)),
-                rejection: None,
-                assumptions: vec![],
-            },
-            SummaryMaintenanceLifecycleAlternative {
-                summary_maintenance_lifecycle: SummaryMaintenanceLifecycle::ContinuouslyMaintained,
-                total_cost: Some(Cost(2.0)),
-                rejection: None,
-                assumptions: vec![],
-            },
-        ];
-        let mut deployments: Vec<_> = (0..13)
-            .map(|summary_index| SummaryMaintenanceDeployment {
-                post_asap_node_id: asap_types::ir::export::LogicalASAPNodeId(summary_index as u32),
-                summary: Rc::clone(&root),
-                summary_maintenance_lifecycle_guarantee: None,
-                selected_window_framework: None,
-                alternatives: alternatives.clone(),
-            })
-            .collect();
-        assert_eq!(
-            select_complete_lifecycle_combination(
-                &root,
-                &mut deployments,
-                &(0..13).collect::<Vec<_>>(),
-                DataArrival::ContinuouslyIngesting,
-                &WholeCandidatePrefersContinuous,
-                None,
-                Some(Horizon(10.0)),
-                Some(2.0),
-                &[],
-            ),
-            None
-        );
-        assert!(deployments
-            .iter()
-            .all(|deployment| deployment.summary_maintenance_lifecycle_guarantee.is_none()));
-    }
-
-    #[test]
-    fn materialization_falls_back_to_raw_when_raw_cost_is_unavailable() {
-        let target = quantile_query();
-        let space = crate::replacement::search_workload(vec![("q", target)]);
-        let selection = space.global_selection(&UnitCosts);
-        let workload = workload(vec![batch(Predictability::AdHoc)], vec![], at_rest());
-        let plan = assemble_selected_dag_with_summary_maintenance_lifecycles(
-            &selection,
-            &space.roots[0].1,
-            WorkloadDemand::new_without_data(&workload, &[0]),
-            1_000,
-            None,
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &UnitCosts,
-        )
-        .unwrap()
-        .unwrap();
-        assert!(plan.selected_raw_recompute);
-        assert!(plan.raw_recompute_total_cost.is_none());
-        assert!(!plan.root.contains_asap());
-        assert!(matches!(
-            plan.root.non_asap(),
-            Some(NonASAPOp::Aggregate { .. })
-        ));
-    }
-
-    #[test]
-    fn unmatched_target_is_reported_as_raw_recomputation() {
-        let target = query_root();
-        let space = crate::replacement::search_workload(vec![("q", Rc::clone(&target))]);
-        let selection = space.global_selection(&RawCheaper);
-        let workload = workload(vec![batch(Predictability::AdHoc)], vec![], at_rest());
-        let plan = assemble_selected_dag_with_summary_maintenance_lifecycles(
-            &selection,
-            &space.roots[0].1,
-            WorkloadDemand::new_without_data(&workload, &[0]),
-            1_000,
-            None,
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &RawCheaper,
-        )
-        .unwrap()
-        .unwrap();
-
-        assert!(plan.selected_raw_recompute);
-        assert_eq!(plan.raw_recompute_total_cost, Some(Cost(1.0)));
-        assert_eq!(plan.summary_total_cost, None);
-        assert!(plan.deployments.is_empty());
-        assert!(!plan.root.contains_asap());
-        assert!(matches!(plan.root.non_asap(), Some(NonASAPOp::Scan { .. })));
-    }
-
-    #[test]
-    fn lifecycle_cost_reorders_semantic_summary_candidates_before_materialization() {
-        let target = quantile_query();
-        let space = crate::replacement::search_workload(vec![("q", target)]);
-        let workload = workload(vec![batch(Predictability::AdHoc)], vec![], at_rest());
-
-        let selection = global_selection_with_summary_maintenance_lifecycles(
-            &space,
-            WorkloadDemand::new_with_data(&workload, &at_rest(), &[0]),
-            1_000,
-            None,
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &SummaryMaintenancePrefersDdSketch,
-        )
-        .unwrap();
-        let materialized = selection
-            .assemble_selected_dag(&space.roots[0].1)
-            .unwrap()
-            .unwrap();
-
-        assert_eq!(
-            sketch_algorithm(&materialized),
-            Some(SketchAlgorithm::DDSketch)
-        );
-    }
-
-    #[test]
-    fn lifecycle_cost_counts_one_shared_summary_node_once() {
-        // One shared exact accumulator read twice by the same root: a
-        // query-time `sum + sum` over one finalized state. (`SummaryMerge`
-        // is reserved in the unified IR, so the sharing is expressed through
-        // a relational consumer instead.)
-        let shared = summary();
-        let finalized = Rc::new(
-            OperatorNode::new(Operator::ASAP(ASAPOp::FinalizeExactAccumulator {
-                child: Rc::clone(&shared),
-            }))
-            .unwrap(),
-        );
-        let root =
-            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::BinaryOp {
-                operator: BinaryOperator {
-                    checked_relative_division: false,
-                    checked_finite_division: false,
-                    kind: BinaryOpKind::Arithmetic(ArithmeticOpKind::Add),
-                    vector_match: None,
-                },
-                return_bool: false,
-                lhs: Rc::clone(&finalized),
-                rhs: finalized,
-            }))
-            .unwrap();
-        let workload = workload(
-            vec![batch(Predictability::AdHoc), batch(Predictability::AdHoc)],
-            vec![],
-            at_rest(),
-        );
-        let horizon = Some(Horizon(10.0));
-        let plan = plan_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(&workload, &at_rest(), &[0, 1]),
-            1_000,
-            horizon,
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &UnitCosts,
-        )
-        .unwrap();
-        assert_eq!(plan.deployments.len(), 1);
-        assert!(matches!(
-            selected_summary_maintenance_lifecycle(&plan.deployments[0]),
-            Some(SummaryMaintenanceLifecycle::Shared { .. })
-        ));
-    }
-
-    /// A state costs 10 however often it is read. Recomputing p50 raw costs
-    /// 1 and p99 costs 8.
-    struct P50PrefersRaw;
-
-    impl CostModel for P50PrefersRaw {
-        fn rank_candidates(
-            &self,
-            _intent: &AggIntent,
-            candidates: &[SketchAlgorithm],
-        ) -> Vec<SketchAlgorithm> {
-            candidates.to_vec()
-        }
-
-        fn summary_maintenance_lifecycle_cost_inputs(
-            &self,
-            _summary: &OperatorNode,
-        ) -> SummaryMaintenanceLifecycleCostInputs {
-            SummaryMaintenanceLifecycleCostInputs {
-                build_cost: Some(Cost(10.0)),
-                maintenance_cost_per_update: Some(Cost::ZERO),
-                summary_read_cost: Some(Cost::ZERO),
-                retention_cost_rate: Some(CostRate(0.0)),
-                retirement_cost: Some(Cost::ZERO),
-            }
-        }
-
-        fn summary_maintenance_capabilities(
-            &self,
-            summary: &OperatorNode,
-        ) -> SummaryMaintenanceCapabilities {
-            UnitCosts.summary_maintenance_capabilities(summary)
-        }
-
-        fn raw_query_recompute_total_cost(
-            &self,
-            target: &OperatorNode,
-            _expected_reads: f64,
-        ) -> Option<Cost> {
-            match target.non_asap() {
-                Some(NonASAPOp::Aggregate { measures, .. }) => match measures[..] {
-                    [AggIntent::Quantile { q: 0.5, .. }] => Some(Cost(1.0)),
-                    _ => Some(Cost(8.0)),
-                },
-                _ => None,
-            }
-        }
-    }
-
-    /// p50 and p99 form a sharing class over one state (5 each), but p50's
-    /// raw recompute (1) still wins. The class reverts, so p99 is reselected
-    /// at its independent cost (10) and recomputes raw (8), as it does alone.
-    /// Checked at selection: the assembled plan's own raw comparison would
-    /// recompute p99 raw either way.
-    #[test]
-    fn sharing_class_reverts_when_a_member_selects_elsewhere() {
-        let quantile = |q| {
-            OperatorNode::new_shared(asap_types::ir::Operator::NonASAP(NonASAPOp::Aggregate {
-                reduction: Reduction::by(vec![]),
-                measures: vec![AggIntent::Quantile {
-                    col: None,
-                    q,
-                    accuracy: AccuracyTarget::Epsilon(0.1),
-                }],
-                // A shared output name keeps p50 and p99 on one state.
-                output_names: vec!["value".into()],
-                filters: vec![],
-                having: None,
-                child: query_root(),
-            }))
-            .unwrap()
-        };
-        let workload = workload(vec![], vec![repeating(), repeating()], at_rest());
-        // Whether each root selected a summary rather than raw recompute.
-        let summaries = |space: &CandidateLogicalASAPDAGs<&str>, entries: &[usize]| {
-            let selection = global_selection_with_summary_maintenance_lifecycles(
-                space,
-                WorkloadDemand::new_with_data(&workload, &at_rest(), entries),
-                1_000,
-                Some(Horizon(10.0)),
-                SummaryMaintenanceLifecycleCapabilities::ALL,
-                &P50PrefersRaw,
-            )
-            .unwrap();
-            space
-                .roots
-                .iter()
-                .map(|(_, target)| selection.for_target(target).unwrap().chosen.is_some())
-                .collect::<Vec<_>>()
-        };
-
-        let space = crate::replacement::search_workload(vec![
-            ("p50", quantile(0.5)),
-            ("p99", quantile(0.99)),
-        ]);
-        let alone = crate::replacement::search_workload(vec![("p99", quantile(0.99))]);
-        assert_eq!(summaries(&space, &[0, 1]), vec![false, false]);
-        assert_eq!(summaries(&alone, &[1]), vec![false]);
-    }
-
-    #[test]
-    fn normalized_workload_drives_candidate_logical_asap_dags_recurrence_profiles() {
-        let root = query_root();
-        let space = crate::replacement::search_workload(vec![("dashboard", Rc::clone(&root))]);
-        let workload = workload(vec![], vec![repeating()], continuous(1_000, 60_000));
-        let profiles = space
-            .recurrence_profiles_from_workload(
-                &workload,
-                Some(&continuous(1_000, 60_000)),
-                &[0],
-                1_000,
-                Some(Horizon(10.0)),
-            )
-            .unwrap();
-        // `search_workload` canonicalizes roots through CSE; recurrence
-        // profiles are keyed by that canonical post-CSE node.
-        let profile = profiles.for_target(&space.roots[0].1);
-        assert_eq!(profile.evaluation_rate, Some(EvaluationRate(1.0)));
-        assert_eq!(profile.update_rate, Some(UpdateRate(1.0)));
-        assert_eq!(profile.one_shot_consumers, 0);
-    }
-
-    #[test]
-    fn recurrence_binding_is_explicit_when_root_order_differs_from_workload_order() {
-        let repeating_root = query_root_for("dashboard");
-        let batch_root = query_root_for("batch");
-        let space = crate::replacement::search_workload(vec![
-            ("dashboard", repeating_root),
-            ("batch", batch_root),
-        ]);
-        let workload = workload(
-            vec![batch(Predictability::AdHoc)],
-            vec![repeating()],
-            at_rest(),
-        );
-        let profiles = space
-            .recurrence_profiles_from_workload(&workload, None, &[1, 0], 1_000, Some(Horizon(10.0)))
-            .unwrap();
-        let dashboard = profiles.for_target(&space.roots[0].1);
-        let batch = profiles.for_target(&space.roots[1].1);
-        assert_eq!(dashboard.evaluation_rate, Some(EvaluationRate(1.0)));
-        assert_eq!(dashboard.one_shot_consumers, 0);
-        assert_eq!(batch.evaluation_rate, None);
-        assert_eq!(batch.one_shot_consumers, 1);
-    }
-
-    fn continuous_candidates<'a>(
-        workload: &QueryWorkload,
-        data: &DataWorkload,
-        model: &'a dyn CostModel,
-    ) -> SummaryMaintenanceLifecycleCandidates<'a> {
-        enumerate_summary_maintenance_lifecycles(
-            summary(),
-            WorkloadDemand::new_with_data(workload, data, &[0]),
-            1_000,
-            Some(Horizon(10.0)),
-            SummaryMaintenanceLifecycleCapabilities {
-                supports_shared: false,
-                ..SummaryMaintenanceLifecycleCapabilities::ALL
-            },
-            model,
-        )
-        .unwrap()
-    }
-
-    fn choose(
-        candidates: &SummaryMaintenanceLifecycleCandidates<'_>,
-        lifecycle: SummaryMaintenanceLifecycle,
-    ) -> Vec<(PhysicalASAPNodeId, SummaryMaintenanceLifecycle)> {
-        candidates
-            .deployments()
-            .iter()
-            .map(|deployment| (deployment.post_asap_node_id, lifecycle.clone()))
-            .collect()
-    }
-
-    // Enumeration reports all four lifecycle kinds with their rejections and
-    // selects nothing.
-    #[test]
-    fn enumeration_exposes_every_lifecycle_without_selecting() {
-        let data = continuous(1_000, 60_000);
-        let workload = workload(vec![], vec![repeating()], data.clone());
-        let candidates = continuous_candidates(&workload, &data, &UnitCosts);
-        let [deployment] = candidates.deployments() else {
-            panic!("one summary state");
-        };
-        assert_eq!(deployment.summary_maintenance_lifecycle_guarantee, None);
-        assert_eq!(deployment.selected_window_framework, None);
-        let outcome: Vec<_> = deployment
-            .alternatives
-            .iter()
-            .map(|alternative| {
-                (
-                    &alternative.summary_maintenance_lifecycle,
-                    alternative.rejection.clone(),
-                    alternative.total_cost.is_some(),
-                )
-            })
-            .collect();
-        assert!(matches!(
-            outcome.as_slice(),
-            [
-                (SummaryMaintenanceLifecycle::Ephemeral, None, true),
-                (
-                    SummaryMaintenanceLifecycle::Prepared { .. },
-                    Some(SummaryMaintenanceLifecycleRejection::RequiresPredictableOneTimeQuery),
-                    false
-                ),
-                (
-                    SummaryMaintenanceLifecycle::Shared { .. },
-                    Some(SummaryMaintenanceLifecycleRejection::UnsupportedByRuntime),
-                    false
-                ),
-                (
-                    SummaryMaintenanceLifecycle::ContinuouslyMaintained,
-                    None,
-                    true
-                ),
-            ]
-        ));
-        let guarantee = candidates.guarantee(&SummaryMaintenanceLifecycle::ContinuouslyMaintained);
-        assert_eq!(
-            guarantee.summary_maintenance_mode,
-            SummaryMaintenanceMode::Incremental
-        );
-        assert_eq!(guarantee.evaluation_schedule, EvaluationSchedule::PerUpdate);
-    }
-
-    // Explicitly choosing Planner's own selection reproduces Planner's plan.
-    #[test]
-    fn explicit_choice_of_planner_selection_reproduces_planner_plan() {
-        let data = continuous(1_000, 60_000);
-        let workload = workload(vec![], vec![repeating()], data.clone());
-        let planned = plan_summary_maintenance_lifecycles(
-            summary(),
-            WorkloadDemand::new_with_data(&workload, &data, &[0]),
-            1_000,
-            Some(Horizon(10.0)),
-            SummaryMaintenanceLifecycleCapabilities {
-                supports_shared: false,
-                ..SummaryMaintenanceLifecycleCapabilities::ALL
-            },
-            &UnitCosts,
-        )
-        .unwrap();
-        let candidates = continuous_candidates(&workload, &data, &UnitCosts);
-        let choice = choose(
-            &candidates,
-            SummaryMaintenanceLifecycle::ContinuouslyMaintained,
-        );
-        let chosen = candidates.select(&choice).unwrap();
-        assert_eq!(format!("{chosen:?}"), format!("{planned:?}"));
-    }
-
-    // A deployment may bind a legal alternative Planner's estimate does not
-    // prefer; the plan carries that alternative's guarantee and cost.
-    #[test]
-    fn explicit_choice_may_bind_a_costlier_legal_alternative() {
-        let data = continuous(1_000, 60_000);
-        let workload = workload(vec![], vec![repeating()], data.clone());
-        let candidates = continuous_candidates(&workload, &data, &UnitCosts);
-        let ephemeral_cost = candidates.deployments()[0].alternatives[0].total_cost;
-        let choice = choose(&candidates, SummaryMaintenanceLifecycle::Ephemeral);
-        let plan = candidates.select(&choice).unwrap();
-        assert_eq!(
-            selected_summary_maintenance_lifecycle(&plan.deployments[0]),
-            Some(&SummaryMaintenanceLifecycle::Ephemeral)
-        );
-        assert_eq!(plan.summary_total_cost, ephemeral_cost);
-    }
-
-    // Choices that Planner could not select, or that do not cover exactly the
-    // enumerated states, are refused rather than bound.
-    #[test]
-    fn explicit_choice_rejects_illegal_or_incomplete_choices() {
-        use SummaryMaintenanceLifecycleChoiceError as E;
-        let data = continuous(1_000, 60_000);
-        let workload = workload(vec![], vec![repeating()], data.clone());
-        let select = |model: &dyn CostModel, choice: &dyn Fn(PhysicalASAPNodeId) -> Vec<_>| {
-            let candidates = continuous_candidates(&workload, &data, model);
-            let id = candidates.deployments()[0].post_asap_node_id;
-            (id, candidates.select(&choice(id)).unwrap_err())
-        };
-        let shared = SummaryMaintenanceLifecycle::Shared {
-            retention: DurationMs(10_000),
-        };
-        let (id, error) = select(&UnitCosts, &|id| vec![(id, shared.clone())]);
-        assert_eq!(
-            error,
-            E::Rejected {
-                post_asap_node_id: id,
-                rejection: Some(SummaryMaintenanceLifecycleRejection::UnsupportedByRuntime),
-            }
-        );
-        let continuous = SummaryMaintenanceLifecycle::ContinuouslyMaintained;
-        let (id, error) = select(&crate::cost_model::DefaultCostModel, &|id| {
-            vec![(id, SummaryMaintenanceLifecycle::Ephemeral)]
-        });
-        assert_eq!(
-            error,
-            E::Rejected {
-                post_asap_node_id: id,
-                rejection: Some(SummaryMaintenanceLifecycleRejection::MissingCostEvidence),
-            }
-        );
-        let (id, error) = select(&UnitCosts, &|id| {
-            vec![(
-                id,
-                SummaryMaintenanceLifecycle::Shared {
-                    retention: DurationMs(1),
-                },
-            )]
-        });
-        assert_eq!(error, E::NotAnAlternative(id));
-        let (id, error) = select(&UnitCosts, &|_| vec![]);
-        assert_eq!(error, E::MissingChoice(id));
-        let (id, error) = select(&UnitCosts, &|id| {
-            vec![(id, continuous.clone()), (id, continuous.clone())]
-        });
-        assert_eq!(error, E::DuplicateChoice(id));
-        let (_, error) = select(&UnitCosts, &|_| {
-            vec![(
-                asap_types::ir::export::LogicalASAPNodeId(u32::MAX),
-                continuous.clone(),
-            )]
-        });
-        assert_eq!(
-            error,
-            E::UnknownSummary(asap_types::ir::export::LogicalASAPNodeId(u32::MAX))
-        );
-    }
-
-    // Nested states on one maintenance path must share an evaluation schedule.
-    #[test]
-    fn explicit_choice_rejects_incompatible_nested_schedules() {
-        let workload = workload(vec![], vec![repeating()], continuous(1_000, 20_000));
-        let candidates = enumerate_summary_maintenance_lifecycles(
-            nested_summary(),
-            WorkloadDemand::new_with_data(&workload, &continuous(1_000, 20_000), &[0]),
-            1_000,
-            Some(Horizon(10.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &IncompatibleNestedCosts,
-        )
-        .unwrap();
-        let [outer, inner] = candidates.deployments() else {
-            panic!("two summary states");
-        };
-        let choice = vec![
-            (
-                outer.post_asap_node_id,
-                SummaryMaintenanceLifecycle::Ephemeral,
-            ),
-            (
-                inner.post_asap_node_id,
-                SummaryMaintenanceLifecycle::ContinuouslyMaintained,
-            ),
-        ];
-        assert_eq!(
-            candidates.select(&choice).unwrap_err(),
-            SummaryMaintenanceLifecycleChoiceError::IncompatibleEvaluationSchedules
-        );
-    }
-
-    // A multi-summary root yields one candidate entry per unique state, with
-    // a shared `Rc` state listed once.
-    #[test]
-    fn enumeration_lists_each_unique_summary_state_once() {
-        let shared = summary();
-        let root = test_binary(
-            test_binary(evaluation(&shared), evaluation(&shared)),
-            evaluation(&summary()),
-        );
-        let workload = workload(vec![batch(Predictability::AdHoc)], vec![], at_rest());
-        let candidates = enumerate_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(&workload, &at_rest(), &[0]),
-            1_000,
-            None,
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &UnitCosts,
-        )
-        .unwrap();
-        let ids: HashSet<_> = candidates
-            .deployments()
-            .iter()
-            .map(|deployment| deployment.post_asap_node_id)
-            .collect();
-        assert_eq!(candidates.deployments().len(), 2);
-        assert_eq!(ids.len(), 2);
-        assert!(candidates
-            .deployments()
-            .iter()
-            .any(|deployment| Rc::ptr_eq(&deployment.summary, &shared)));
-    }
-
-    fn evaluation(state: &Rc<OperatorNode>) -> Rc<OperatorNode> {
-        std::rc::Rc::new(
-            OperatorNode::with_schema(
-                asap_types::ir::Operator::ASAP(ASAPOp::FinalizeExactAccumulator {
-                    child: Rc::clone(state),
-                }),
-                Schema::lifted(
-                    vec![Field::new(
-                        "value",
-                        FieldDataType::Plain(DataType::Float64),
-                        false,
-                    )],
-                    None,
-                ),
-            )
-            .with_guarantee(Some(ResultGuarantee::exact("sum"))),
-        )
-    }
-
-    fn test_binary(lhs: Rc<OperatorNode>, rhs: Rc<OperatorNode>) -> Rc<OperatorNode> {
-        let schema = lhs.schema.clone();
-        Rc::new(OperatorNode::with_schema(
-            Operator::NonASAP(NonASAPOp::BinaryOp {
-                lhs,
-                rhs,
-                return_bool: false,
-                operator: BinaryOperator {
-                    kind: BinaryOpKind::Arithmetic(ArithmeticOpKind::Add),
-                    vector_match: None,
-                    checked_relative_division: false,
-                    checked_finite_division: false,
-                },
-            }),
-            schema,
-        ))
-    }
-
-    fn lifecycle_matching(
-        alternatives: &[SummaryMaintenanceLifecycleAlternative],
-        kind: fn(&SummaryMaintenanceLifecycle) -> bool,
-    ) -> SummaryMaintenanceLifecycle {
-        alternatives
-            .iter()
-            .map(|alternative| &alternative.summary_maintenance_lifecycle)
-            .find(|lifecycle| kind(lifecycle))
-            .expect("lifecycle kind is an alternative")
-            .clone()
-    }
-
-    /// Bind the lifecycle `choose` picks for every state of `root`, then
-    /// derive the timed DAG.
-    fn timed_dag(
-        root: Rc<OperatorNode>,
-        workload: &QueryWorkload,
-        data: &DataWorkload,
-        horizon: Option<Horizon>,
-        choose: impl Fn(&SummaryMaintenanceDeployment) -> SummaryMaintenanceLifecycle,
-    ) -> PhysicalASAPDAG {
-        let candidates = enumerate_summary_maintenance_lifecycles(
-            root,
-            WorkloadDemand::new_with_data(workload, data, &[0]),
-            1_000,
-            horizon,
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &UnitCosts,
-        )
-        .unwrap();
-        let choice: Vec<_> = candidates
-            .deployments()
-            .iter()
-            .map(|deployment| (deployment.post_asap_node_id, choose(deployment)))
-            .collect();
-        let dag = candidates
-            .select(&choice)
-            .unwrap()
-            .execution_timed_dag()
-            .unwrap();
-        dag.validate().unwrap();
-        dag
-    }
-
-    /// Operator kinds in node-id order, each paired with its timing.
-    fn timings(dag: &PhysicalASAPDAG) -> Vec<(&'static str, ExecutionTiming)> {
-        dag.nodes
-            .iter()
-            .map(|node| {
-                let kind = match node.payload {
-                    PhysicalASAPOperatorPayload::Relational {
-                        operator: NonASAPOpKind::BinaryOp { .. },
-                    } => "binary",
-                    PhysicalASAPOperatorPayload::Relational { .. } => "raw",
-                    PhysicalASAPOperatorPayload::SummaryAgg { .. } => "state",
-                    PhysicalASAPOperatorPayload::FinalizeExactAccumulator
-                    | PhysicalASAPOperatorPayload::EvaluatePopulation { .. } => "evaluation",
-
-                    _ => "other",
-                };
-                (kind, node.output_state.timing)
-            })
-            .collect()
-    }
-
-    const INGEST: ExecutionTiming = ExecutionTiming::IngestionTime;
-    const QUERY: ExecutionTiming = ExecutionTiming::QueryTime;
-
-    // Every retained lifecycle kind runs its state and inputs at ingestion
-    // time and its evaluation at query time.
-    #[test]
-    fn retained_lifecycles_time_state_and_inputs_at_ingestion() {
-        let mut scheduled = batch(Predictability::Predictable {
-            known_at: Some(TimestampMs(1_000)),
-        });
-        scheduled.execute_at = Some(TimestampMs(11_000));
-        type Case = (
-            QueryWorkload,
-            DataWorkload,
-            Option<Horizon>,
-            fn(&SummaryMaintenanceLifecycle) -> bool,
-        );
-        let cases: [Case; 3] = [
-            (
-                workload(vec![], vec![repeating()], continuous(1_000, 60_000)),
-                continuous(1_000, 60_000),
-                Some(Horizon(10.0)),
-                |lifecycle| {
-                    matches!(
-                        lifecycle,
-                        SummaryMaintenanceLifecycle::ContinuouslyMaintained
-                    )
-                },
-            ),
-            (
-                workload(vec![], vec![repeating()], at_rest()),
-                at_rest(),
-                Some(Horizon(10.0)),
-                |lifecycle| matches!(lifecycle, SummaryMaintenanceLifecycle::Shared { .. }),
-            ),
-            (
-                workload(vec![scheduled], vec![], at_rest()),
-                at_rest(),
-                None,
-                |lifecycle| matches!(lifecycle, SummaryMaintenanceLifecycle::Prepared { .. }),
-            ),
-        ];
-        for (workload, data, horizon, kind) in cases {
-            let dag = timed_dag(
-                evaluation(&summary()),
-                &workload,
-                &data,
-                horizon,
-                |deployment| lifecycle_matching(&deployment.alternatives, kind),
-            );
-            assert_eq!(
-                timings(&dag),
-                [("raw", INGEST), ("state", INGEST), ("evaluation", QUERY)]
-            );
-        }
-    }
-
-    // An Ephemeral state, its raw input, and its evaluation all run at query time.
-    #[test]
-    fn ephemeral_lifecycle_times_state_and_downstream_at_query() {
-        let workload = workload(vec![batch(Predictability::AdHoc)], vec![], at_rest());
-        let dag = timed_dag(evaluation(&summary()), &workload, &at_rest(), None, |_| {
-            SummaryMaintenanceLifecycle::Ephemeral
-        });
-        assert_eq!(
-            timings(&dag),
-            [("raw", QUERY), ("state", QUERY), ("evaluation", QUERY)]
-        );
-    }
-
-    // One state read by two consumers is one deployment; its timing follows
-    // that single choice while both consumers run at query time.
-    #[test]
-    fn shared_state_is_timed_once_for_all_consumers() {
-        let state = summary();
-        let lhs = evaluation(&state);
-        let rhs = Rc::new(lhs.as_ref().clone());
-        let root = test_binary(lhs, rhs);
-        let data = continuous(1_000, 60_000);
-        let workload = workload(vec![], vec![repeating()], data.clone());
-        let dag = timed_dag(root, &workload, &data, Some(Horizon(10.0)), |deployment| {
-            assert!(Rc::ptr_eq(&deployment.summary, &state));
-            SummaryMaintenanceLifecycle::ContinuouslyMaintained
-        });
-        assert_eq!(
-            timings(&dag),
-            [
-                ("raw", INGEST),
-                ("state", INGEST),
-                ("evaluation", QUERY),
-                ("evaluation", QUERY),
-                ("binary", QUERY),
-            ]
-        );
-    }
-
-    // An Ephemeral state consumed by retained state is built on the retained
-    // state's ingestion path; it is not retained, but cannot run at query time.
-    #[test]
-    fn ephemeral_state_feeding_retained_state_runs_at_ingestion() {
-        let mut scheduled = batch(Predictability::Predictable {
-            known_at: Some(TimestampMs(1_000)),
-        });
-        scheduled.execute_at = Some(TimestampMs(11_000));
-        let root = nested_summary();
-        let workload = workload(vec![scheduled], vec![], at_rest());
-        let dag = timed_dag(
-            Rc::clone(&root),
-            &workload,
-            &at_rest(),
-            None,
-            |deployment| {
-                if Rc::ptr_eq(&deployment.summary, &root) {
-                    lifecycle_matching(&deployment.alternatives, |lifecycle| {
-                        matches!(lifecycle, SummaryMaintenanceLifecycle::Prepared { .. })
-                    })
-                } else {
-                    SummaryMaintenanceLifecycle::Ephemeral
-                }
-            },
-        );
-        assert_eq!(
-            timings(&dag),
-            [("raw", INGEST), ("state", INGEST), ("state", INGEST)]
-        );
-    }
-
-    // Timing is not derived for a state without a selected lifecycle, and a
-    // raw-recompute plan runs entirely at query time.
-    #[test]
-    fn timing_requires_a_selected_lifecycle_for_every_state() {
-        let workload = workload(vec![batch(Predictability::AdHoc)], vec![], at_rest());
-        let data = at_rest();
-        let demand = WorkloadDemand::new_with_data(&workload, &data, &[0]);
-        let plan = plan_summary_maintenance_lifecycles(
-            evaluation(&summary()),
-            demand,
-            1_000,
-            None,
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &crate::cost_model::DefaultCostModel,
-        )
-        .unwrap();
-        assert_eq!(
-            plan.execution_timed_dag().unwrap_err(),
-            SummaryMaintenanceTimingError::UnselectedLifecycle(
-                plan.deployments[0].post_asap_node_id
-            )
-        );
-        let raw = plan_summary_maintenance_lifecycles(
-            crate::replacement::retain_exact(&sum_query()).unwrap(),
-            demand,
-            1_000,
-            None,
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &UnitCosts,
-        )
-        .unwrap();
-        assert_eq!(
-            timings(&raw.execution_timed_dag().unwrap()),
-            [("raw", QUERY), ("raw", QUERY)]
-        );
-    }
-
-    /// A strategy-built `sum(a)` over one maintained current-series population.
-    fn population_evaluation() -> Rc<OperatorNode> {
-        let target = crate::test_support::lower_promql("sum(a)", AccuracyTarget::Exact);
-        crate::maintained_population::MaintainedPopulationStrategy::new(std::slice::from_ref(
-            &target,
-        ))
-        .candidate(&target)
-        .unwrap()
-    }
-
-    fn is_population(node: &OperatorNode) -> bool {
-        matches!(
-            node.operator,
-            Operator::ASAP(ASAPOp::MaintainPopulation { .. })
-        )
-    }
-
-    fn population_timings(dag: &PhysicalASAPDAG) -> Vec<(&'static str, ExecutionTiming)> {
-        dag.nodes
-            .iter()
-            .zip(timings(dag))
-            .map(|(node, (kind, timing))| match node.payload {
-                PhysicalASAPOperatorPayload::MaintainPopulation { .. } => ("population", timing),
-                _ => (kind, timing),
-            })
-            .collect()
-    }
-
-    // A maintained population is enumerated as retained state, with costs
-    // from the caller's model for both the maintained and the rebuilt choice.
-    #[test]
-    fn enumeration_includes_maintained_population() {
-        let data = continuous(1_000, 60_000);
-        let workload = workload(vec![], vec![repeating()], data.clone());
-        let candidates = enumerate_summary_maintenance_lifecycles(
-            population_evaluation(),
-            WorkloadDemand::new_with_data(&workload, &data, &[0]),
-            1_000,
-            Some(Horizon(10.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &UnitCosts,
-        )
-        .unwrap();
-        let [deployment] = candidates.deployments() else {
-            panic!("one population state");
-        };
-        assert!(is_population(&deployment.summary));
-        let cost = |lifecycle: SummaryMaintenanceLifecycle| {
-            deployment
-                .alternatives
-                .iter()
-                .find(|alternative| alternative.summary_maintenance_lifecycle == lifecycle)
-                .and_then(|alternative| alternative.total_cost)
-        };
-        // Ephemeral: (build 10 + read 1 + retire 1) x 10 reads. Maintained over
-        // 10 s at 1 update/s: build 10 + updates 10 + reads 10 + retention 1 + retire 1.
-        assert_eq!(
-            cost(SummaryMaintenanceLifecycle::Ephemeral),
-            Some(Cost(120.0))
-        );
-        assert_eq!(
-            cost(SummaryMaintenanceLifecycle::ContinuouslyMaintained),
-            Some(Cost(32.0))
-        );
-    }
-
-    // Without cost evidence a population's alternatives stay unknown: Planner
-    // selects none and timing is refused rather than guessed.
-    #[test]
-    fn population_without_cost_evidence_stays_unselected() {
-        let data = continuous(1_000, 60_000);
-        let workload = workload(vec![], vec![repeating()], data.clone());
-        let plan = plan_summary_maintenance_lifecycles(
-            population_evaluation(),
-            WorkloadDemand::new_with_data(&workload, &data, &[0]),
-            1_000,
-            Some(Horizon(10.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &crate::cost_model::DefaultCostModel,
-        )
-        .unwrap();
-        let [deployment] = plan.deployments.as_slice() else {
-            panic!("one population state");
-        };
-        assert!(deployment
-            .alternatives
-            .iter()
-            .all(|alternative| alternative.total_cost.is_none()));
-        assert!(deployment.summary_maintenance_lifecycle_guarantee.is_none());
-        assert_eq!(
-            plan.execution_timed_dag().unwrap_err(),
-            SummaryMaintenanceTimingError::UnselectedLifecycle(deployment.post_asap_node_id)
-        );
-    }
-
-    // A retained population and its raw input run at ingestion time; an
-    // Ephemeral population is rebuilt from raw input at query time.
-    #[test]
-    fn population_lifecycle_choice_decides_its_timing() {
-        let data = continuous(1_000, 60_000);
-        let workload = workload(vec![], vec![repeating()], data.clone());
-        let timed = |lifecycle: SummaryMaintenanceLifecycle| {
-            population_timings(&timed_dag(
-                population_evaluation(),
-                &workload,
-                &data,
-                Some(Horizon(10.0)),
-                |_| lifecycle.clone(),
-            ))
-        };
-        assert_eq!(
-            timed(SummaryMaintenanceLifecycle::ContinuouslyMaintained),
-            [
-                ("raw", INGEST),
-                ("raw", INGEST),
-                ("population", INGEST),
-                ("evaluation", QUERY)
-            ]
-        );
-        assert_eq!(
-            timed(SummaryMaintenanceLifecycle::Ephemeral),
-            [
-                ("raw", QUERY),
-                ("raw", QUERY),
-                ("population", QUERY),
-                ("evaluation", QUERY)
-            ]
-        );
-    }
-
-    // When retaining is cheaper, Planner's own selection keeps the population
-    // maintained at ingestion time, as realization strategies placed it before
-    // population timing became a lifecycle decision.
-    #[test]
-    fn planner_selection_retains_population_at_ingestion() {
-        let data = continuous(1_000, 60_000);
-        let workload = workload(vec![], vec![repeating()], data.clone());
-        let plan = plan_summary_maintenance_lifecycles(
-            population_evaluation(),
-            WorkloadDemand::new_with_data(&workload, &data, &[0]),
-            1_000,
-            Some(Horizon(10.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &UnitCosts,
-        )
-        .unwrap();
-        // Shared and ContinuouslyMaintained tie at 32; the first wins.
-        assert!(matches!(
-            selected_summary_maintenance_lifecycle(&plan.deployments[0]),
-            Some(SummaryMaintenanceLifecycle::Shared { .. })
-        ));
-        assert_eq!(
-            population_timings(&plan.execution_timed_dag().unwrap()),
-            [
-                ("raw", INGEST),
-                ("raw", INGEST),
-                ("population", INGEST),
-                ("evaluation", QUERY)
-            ]
-        );
-    }
-
-    // A population feeding summary state is that state's input, not a separate
-    // deployment: the state's lifecycle times it.
-    #[test]
-    fn population_feeding_summary_state_follows_that_state() {
-        let Operator::ASAP(ASAPOp::EvaluatePopulation {
-            child: population, ..
-        }) = &population_evaluation().operator
-        else {
-            unreachable!()
-        };
-        let state = summary();
-        let Operator::ASAP(ASAPOp::SummaryAgg {
-            family,
-            input,
-            reduction,
-            grouping,
-            ..
-        }) = &state.operator
-        else {
-            unreachable!()
-        };
-        let state = Rc::new(OperatorNode {
-            operator: Operator::ASAP(ASAPOp::SummaryAgg {
-                child: Rc::clone(population),
-                family: family.clone(),
-                input: input.clone(),
-                reduction: reduction.clone(),
-                grouping: grouping.clone(),
-                filter: None,
-            }),
-            ..state.as_ref().clone()
-        });
-        let data = continuous(1_000, 60_000);
-        let workload = workload(vec![], vec![repeating()], data.clone());
-        let timed = |lifecycle: SummaryMaintenanceLifecycle| {
-            population_timings(&timed_dag(
-                evaluation(&state),
-                &workload,
-                &data,
-                Some(Horizon(10.0)),
-                |deployment| {
-                    assert!(Rc::ptr_eq(&deployment.summary, &state));
-                    lifecycle.clone()
-                },
-            ))
-        };
-        assert_eq!(
-            timed(SummaryMaintenanceLifecycle::ContinuouslyMaintained),
-            [
-                ("raw", INGEST),
-                ("raw", INGEST),
-                ("population", INGEST),
-                ("state", INGEST),
-                ("evaluation", QUERY)
-            ]
-        );
-        assert_eq!(
-            timed(SummaryMaintenanceLifecycle::Ephemeral),
-            [
-                ("raw", QUERY),
-                ("raw", QUERY),
-                ("population", QUERY),
-                ("state", QUERY),
-                ("evaluation", QUERY)
-            ]
-        );
-    }
-
-    // A population both read directly and consumed by summary state is that
-    // state's input in either traversal order: not a separate deployment, and
-    // timed by the state's lifecycle.
-    #[test]
-    fn shared_population_follows_its_summary_consumer() {
-        let direct = population_evaluation();
-        let Operator::ASAP(ASAPOp::EvaluatePopulation {
-            child: population, ..
-        }) = &direct.operator
-        else {
-            unreachable!()
-        };
-        let state = summary();
-        let Operator::ASAP(ASAPOp::SummaryAgg {
-            family,
-            input,
-            reduction,
-            grouping,
-            ..
-        }) = &state.operator
-        else {
-            unreachable!()
-        };
-        let state = Rc::new(OperatorNode {
-            operator: Operator::ASAP(ASAPOp::SummaryAgg {
-                child: Rc::clone(population),
-                family: family.clone(),
-                input: input.clone(),
-                reduction: reduction.clone(),
-                grouping: grouping.clone(),
-                filter: None,
-            }),
-            ..state.as_ref().clone()
-        });
-        let binary = test_binary;
-        let data = continuous(1_000, 60_000);
-        let workload = workload(vec![], vec![repeating()], data.clone());
-        for root in [
-            binary(Rc::clone(&direct), evaluation(&state)),
-            binary(evaluation(&state), Rc::clone(&direct)),
-        ] {
-            for lifecycle in [
-                SummaryMaintenanceLifecycle::ContinuouslyMaintained,
-                SummaryMaintenanceLifecycle::Ephemeral,
-            ] {
-                let dag = timed_dag(
-                    Rc::clone(&root),
-                    &workload,
-                    &data,
-                    Some(Horizon(10.0)),
-                    |deployment| {
-                        assert!(Rc::ptr_eq(&deployment.summary, &state));
-                        lifecycle.clone()
-                    },
-                );
-                let expected = if lifecycle == SummaryMaintenanceLifecycle::Ephemeral {
-                    QUERY
-                } else {
-                    INGEST
-                };
-                for (kind, timing) in population_timings(&dag) {
-                    if matches!(kind, "raw" | "population" | "state") {
-                        assert_eq!(timing, expected, "{kind}");
-                    } else {
-                        assert_eq!(timing, QUERY, "{kind}");
-                    }
-                }
-            }
-        }
-    }
-
-    // A plan whose population deployment was removed after enumeration is
-    // refused rather than timed by a guess.
-    #[test]
-    fn timing_refuses_population_without_deployment() {
-        let data = continuous(1_000, 60_000);
-        let workload = workload(vec![], vec![repeating()], data.clone());
-        let mut plan = plan_summary_maintenance_lifecycles(
-            population_evaluation(),
-            WorkloadDemand::new_with_data(&workload, &data, &[0]),
-            1_000,
-            Some(Horizon(10.0)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &UnitCosts,
-        )
-        .unwrap();
-        let id = plan.deployments.remove(0).post_asap_node_id;
-        assert_eq!(
-            plan.execution_timed_dag(),
-            Err(SummaryMaintenanceTimingError::UnplannedMaintainedState(id))
-        );
-    }
-}
diff --git a/crates/asap-physical-operators/tests/weighted_topk_binding.rs b/crates/asap-physical-operators/tests/weighted_topk_binding.rs
index b4d8c85d3..bca53bb01 100644
--- a/crates/asap-physical-operators/tests/weighted_topk_binding.rs
+++ b/crates/asap-physical-operators/tests/weighted_topk_binding.rs
@@ -760,100 +760,54 @@ fn spatial_topk_exposes_signed_heap_candidate_over_complete_snapshot() {
     }
 }
 
-/// Deployment-side lifecycle choice: every summary state of `candidate` is
-/// continuously maintained, and the chosen lifecycles set execution timing.
+/// Every summary state of `candidate` maintained at ingestion time, the
+/// materialization a deployment would assign for a continuously served query:
+/// each `SummaryAgg` and every input it consumes run at ingestion time, the
+/// rest at query time. The phases are assigned on the exported DAG because
+/// the candidate pins its finalize boundary to query time.
 fn continuously_maintained_dag(candidate: &Rc<planner_types::ir::OperatorNode>) -> PhysicalASAPDAG {
-    use asap_aware_mapping::{
-        cost_model::{Cost, CostModel},
-        enumerate_summary_maintenance_lifecycles, CostRate, Horizon,
-        SummaryMaintenanceCapabilities, SummaryMaintenanceLifecycleCapabilities,
-        SummaryMaintenanceLifecycleCostInputs, WorkloadDemand,
-    };
-    use planner_types::workload::{
-        DataArrival, Rate, RepeatedDemand, RepeatingEntry, RepetitionInterval,
-    };
-    struct Costed;
-    impl CostModel for Costed {
-        fn rank_candidates(
-            &self,
-            _: &planner_types::pre_asap::agg_intent::AggIntent,
-            candidates: &[SketchAlgorithm],
-        ) -> Vec<SketchAlgorithm> {
-            candidates.to_vec()
-        }
-        fn summary_maintenance_lifecycle_cost_inputs(
-            &self,
-            _: &planner_types::ir::OperatorNode,
-        ) -> SummaryMaintenanceLifecycleCostInputs {
-            SummaryMaintenanceLifecycleCostInputs {
-                build_cost: Some(Cost(10.)),
-                maintenance_cost_per_update: Some(Cost(1.)),
-                summary_read_cost: Some(Cost(1.)),
-                retention_cost_rate: Some(CostRate(0.1)),
-                retirement_cost: Some(Cost(1.)),
-            }
-        }
-        fn summary_maintenance_capabilities(
-            &self,
-            _: &planner_types::ir::OperatorNode,
-        ) -> SummaryMaintenanceCapabilities {
-            SummaryMaintenanceCapabilities {
-                incremental_update: true,
-                merge: true,
-                delete: true,
-            }
-        }
-    }
-    const NOW_MS: u64 = 1_000_000;
-    let queries = QueryWorkload {
-        language: QueryLanguage::PromQL,
-        query_batch: None,
-        repeating_queries: Some(vec![RepeatingEntry {
-            query: Query("topk by(job)(2, rate(m[1m]))".into()),
-            demand: RepeatedDemand::FixedInterval(RepetitionInterval(60_000)),
-            requirements: QueryRequirements::default(),
-            predictability: Predictability::Predictable { known_at: None },
-            time_selection: TimeSelection::default(),
-        }]),
-    };
-    let data = DataWorkload {
-        arrival: DataArrival::ContinuouslyIngesting,
-        ingestion_rate: WorkloadEvidence {
-            value: Some(Rate(1.)),
-            source: planner_types::workload::EvidenceSource::Observed,
-            observed_at_ms: Some(NOW_MS),
-            valid_for_ms: Some(60_000),
-        },
-        ..Default::default()
-    };
-    let lifecycles = enumerate_summary_maintenance_lifecycles(
-        Rc::clone(candidate),
-        WorkloadDemand::new_with_data(&queries, &data, &[0]),
-        NOW_MS,
-        Some(Horizon(100.)),
-        SummaryMaintenanceLifecycleCapabilities::ALL,
-        &Costed,
+    use planner_types::ir::{apply_lifecycle_timings, LifecycleAssignment, TimingMemo};
+    let timed = apply_lifecycle_timings(
+        candidate,
+        &LifecycleAssignment::default_maintained(),
+        &mut TimingMemo::new(),
     )
     .unwrap();
-    let choices = lifecycles
-        .deployments()
+    let dag = planner_types::ir::export::compile_physical_asap_dag(&timed).unwrap();
+    let mut pending: Vec<_> = dag
+        .nodes
         .iter()
-        .map(|deployment| {
-            (
-                deployment.post_asap_node_id,
-                SummaryMaintenanceLifecycle::ContinuouslyMaintained,
-            )
+        .filter(|node| matches!(node.payload, PhysicalASAPOperatorPayload::SummaryAgg { .. }))
+        .map(|node| node.id)
+        .collect();
+    let mut ingestion = std::collections::HashSet::new();
+    while let Some(id) = pending.pop() {
+        if ingestion.insert(id) {
+            pending.extend(
+                dag.edges
+                    .iter()
+                    .filter(|edge| edge.consumer == id)
+                    .map(|edge| edge.producer),
+            );
+        }
+    }
+    let phases = dag
+        .nodes
+        .iter()
+        .map(|node| {
+            let timing = if ingestion.contains(&node.id) {
+                ExecutionTiming::IngestionTime
+            } else {
+                ExecutionTiming::QueryTime
+            };
+            (node.id, timing)
         })
-        .collect::<Vec<_>>();
-    lifecycles
-        .select(&choices)
-        .unwrap()
-        .execution_timed_dag()
-        .unwrap()
+        .collect();
+    dag.with_execution_phases(&phases).unwrap()
 }
 
 // A maintained heap over finalized per-series Rate is the fixed-window
-// placement: lifecycle timing, not a separate candidate, puts it in precompute.
+// placement: materialization timing, not a separate candidate, puts it in precompute.
 #[test]
 fn maintained_rate_heap_lifecycle_compiles_fixed_window_precompute() {
     use asap_physical_operators::physical_planner::{
diff --git a/crates/integration-tests/tests/operator_design_examples.rs b/crates/integration-tests/tests/operator_design_examples.rs
index 4b52026b4..3c4c028d6 100644
--- a/crates/integration-tests/tests/operator_design_examples.rs
+++ b/crates/integration-tests/tests/operator_design_examples.rs
@@ -270,46 +270,15 @@ async fn sql_window_and_filtered_aggregate_types() {
 /// and executes both selected plans. No replacement dag is constructed by the test.
 #[tokio::test]
 async fn batch_planning_replaces_and_shares_summary_operators() {
-    use asap_aware_mapping::cost_model::{Cost, DefaultCostModel};
     use asap_aware_mapping::pass::PlanningModels;
-    use asap_aware_mapping::{
-        CostModel, CostRate, LifecycleInput, SummaryMaintenanceLifecycleCapabilities,
-        SummaryMaintenanceLifecycleCostInputs,
-    };
     use asap_physical_operators::{
         physical_planner::{compile, InputContract},
         runtime::Scope,
         values::{Batch, Value},
     };
     use asap_planner::{e2e_plan, FrontendInput, UserInput};
-    use asap_types::post_asap::SketchAlgorithm;
     use asap_types::workload::*;
     use std::{collections::BTreeMap, sync::Arc};
-    struct Costs;
-    impl CostModel for Costs {
-        fn rank_candidates(
-            &self,
-            intent: &AggIntent,
-            candidates: &[SketchAlgorithm],
-        ) -> Vec<SketchAlgorithm> {
-            DefaultCostModel.rank_candidates(intent, candidates)
-        }
-        fn summary_maintenance_lifecycle_cost_inputs(
-            &self,
-            _: &OperatorNode,
-        ) -> SummaryMaintenanceLifecycleCostInputs {
-            SummaryMaintenanceLifecycleCostInputs {
-                build_cost: Some(Cost(1.0)),
-                maintenance_cost_per_update: Some(Cost::ZERO),
-                summary_read_cost: Some(Cost::ZERO),
-                retention_cost_rate: Some(CostRate(0.0)),
-                retirement_cost: Some(Cost::ZERO),
-            }
-        }
-        fn raw_query_recompute_cost(&self, _: &OperatorNode) -> Option<Cost> {
-            Some(Cost(1000.0))
-        }
-    }
     let queries = [
         "SELECT SUM(bytes) + 1 AS result FROM requests",
         "SELECT SUM(bytes) * 2 AS result FROM requests",
@@ -347,8 +316,7 @@ async fn batch_planning_replaces_and_shares_summary_operators() {
     let output = e2e_plan(UserInput::new(
         &workload,
         FrontendInput::Sql { catalog: &catalog },
-        PlanningModels::builtin().with_cost(&Costs),
-        LifecycleInput::new(0, SummaryMaintenanceLifecycleCapabilities::default()),
+        PlanningModels::builtin(),
     ))
     .await
     .unwrap();
@@ -361,8 +329,7 @@ async fn batch_planning_replaces_and_shares_summary_operators() {
         .collect();
     assert_eq!(states.len(), 1, "the batch owns one shared SUM state");
     for (plan, expected) in output.plans.iter().zip([31.0, 60.0]) {
-        assert!(!plan.plan.selected_raw_recompute);
-        let root = &plan.plan.root;
+        let root = &plan.root;
         root.validate_structure().unwrap();
         assert!(OperatorNode::reachable(root)
             .iter()
diff --git a/crates/integration-tests/tests/summary_maintenance_lifecycle_e2e.rs b/crates/integration-tests/tests/summary_maintenance_lifecycle_e2e.rs
deleted file mode 100644
index 411644d4b..000000000
--- a/crates/integration-tests/tests/summary_maintenance_lifecycle_e2e.rs
+++ /dev/null
@@ -1,1155 +0,0 @@
-//! End-to-end coverage for workload-aware summary-maintenance planning:
-//! source workload -> PromQL lowering -> candidate search ->
-//! summary-maintenance lifecycle selection -> materialized deployment guarantees.
-
-use asap_types::ir::export::PhysicalASAPOperatorPayload;
-use asap_types::ir::ASAPOp;
-use physical_common::compile_physical_asap_dag;
-use std::rc::Rc;
-
-use asap_aware_mapping::cost_model::Cost;
-use asap_aware_mapping::CostRate;
-use asap_aware_mapping::{
-    assemble_selected_dag_with_summary_maintenance_lifecycles, export_summary_maintenance_plan,
-    global_selection_with_summary_maintenance_lifecycles, search_workload_with, CostModel, Horizon,
-    SummaryMaintenanceCapabilities, SummaryMaintenanceLifecycleCapabilities,
-    SummaryMaintenanceLifecycleCostInputs, SummaryMaintenanceLifecycleRejection, WorkloadDemand,
-};
-use asap_frontend_promql::lower_promql_workload;
-use asap_types::ir::OperatorNode;
-use asap_types::post_asap::{
-    EvaluationSchedule, SummaryMaintenanceLifecycle, SummaryMaintenanceMode,
-};
-use asap_types::pre_asap::agg_intent::AggIntent;
-use asap_types::types::AccuracyTarget;
-use asap_types::workload::{
-    AccuracyRequirement, BatchEntry, DataArrival, DataWorkload, DurationMs, Evidence,
-    EvidenceSource, PlanningWorkload, Predictability, Query, QueryLanguage, QueryRequirements,
-    QueryTimeScope, QueryWorkload, Rate, RepeatedDemand, RepeatingEntry, RepetitionInterval,
-    TimeSelection,
-};
-
-const NOW_MS: u64 = 1_000_000;
-
-struct FullyCostedRuntime;
-
-impl CostModel for FullyCostedRuntime {
-    fn raw_query_recompute_total_cost(
-        &self,
-        _target: &OperatorNode,
-        _expected_reads: f64,
-    ) -> Option<Cost> {
-        Some(Cost(1_000.0))
-    }
-
-    fn rank_candidates(
-        &self,
-        _intent: &AggIntent,
-        candidates: &[asap_types::post_asap::SketchAlgorithm],
-    ) -> Vec<asap_types::post_asap::SketchAlgorithm> {
-        candidates.to_vec()
-    }
-
-    fn summary_maintenance_lifecycle_cost_inputs(
-        &self,
-        _summary: &OperatorNode,
-    ) -> SummaryMaintenanceLifecycleCostInputs {
-        SummaryMaintenanceLifecycleCostInputs {
-            build_cost: Some(Cost(10.0)),
-            maintenance_cost_per_update: Some(Cost(1.0)),
-            summary_read_cost: Some(Cost(1.0)),
-            retention_cost_rate: Some(CostRate(0.1)),
-            retirement_cost: Some(Cost(1.0)),
-        }
-    }
-
-    fn summary_maintenance_capabilities(
-        &self,
-        _summary: &OperatorNode,
-    ) -> SummaryMaintenanceCapabilities {
-        SummaryMaintenanceCapabilities {
-            incremental_update: true,
-            merge: true,
-            delete: true,
-        }
-    }
-}
-
-fn dashboard_workload() -> PlanningWorkload {
-    let query = Query("quantile_over_time(0.99, latency[5m])".into());
-    let requirements = QueryRequirements {
-        accuracy: AccuracyRequirement::Explicit(AccuracyTarget::Epsilon(0.01)),
-        ..QueryRequirements::default()
-    };
-    PlanningWorkload {
-        query_workload: QueryWorkload {
-            language: QueryLanguage::PromQL,
-            query_batch: Some(vec![BatchEntry {
-                query: query.clone(),
-                requirements: requirements.clone(),
-                predictability: Predictability::AdHoc,
-                invocations: 1,
-                execute_at: None,
-                time_selection: TimeSelection::default(),
-            }]),
-            repeating_queries: Some(vec![RepeatingEntry {
-                query,
-                demand: RepeatedDemand::FixedInterval(RepetitionInterval(1_000)),
-                requirements,
-                predictability: Predictability::Predictable { known_at: None },
-                time_selection: TimeSelection {
-                    scope: QueryTimeScope::RealTime,
-                    ..TimeSelection::default()
-                },
-            }]),
-        },
-        data_workload: Some(DataWorkload {
-            arrival: DataArrival::ContinuouslyIngesting,
-            ingestion_rate: Evidence {
-                value: Some(Rate(1.0)),
-                source: EvidenceSource::Observed,
-                observed_at_ms: Some(NOW_MS),
-                valid_for_ms: Some(60_000),
-            },
-            data_ingestion_interval: Evidence {
-                value: Some(DurationMs(1_000)),
-                ..Default::default()
-            },
-            ..DataWorkload::default()
-        }),
-    }
-}
-
-#[test]
-fn promql_dashboard_materializes_continuous_summary_with_explained_rejections() {
-    let workload = dashboard_workload();
-    let plan = selected_plan(&workload);
-
-    assert!(!plan.selected_raw_recompute);
-    assert_eq!(plan.expected_reads, Some(100.0));
-    assert_eq!(plan.deployments.len(), 1);
-
-    let deployment = &plan.deployments[0];
-    let guarantee = deployment
-        .summary_maintenance_lifecycle_guarantee
-        .as_ref()
-        .expect("selected lifecycle guarantee");
-    assert_eq!(
-        guarantee.summary_maintenance_lifecycle,
-        SummaryMaintenanceLifecycle::ContinuouslyMaintained
-    );
-    assert_eq!(guarantee.evaluation_schedule, EvaluationSchedule::PerUpdate);
-    assert_eq!(
-        guarantee.summary_maintenance_mode,
-        SummaryMaintenanceMode::Incremental
-    );
-    assert!(deployment.alternatives.iter().any(|alternative| {
-        matches!(
-            alternative.summary_maintenance_lifecycle,
-            SummaryMaintenanceLifecycle::Prepared { .. }
-        ) && alternative.rejection
-            == Some(SummaryMaintenanceLifecycleRejection::RequiresPredictableOneTimeQuery)
-    }));
-    assert!(deployment.alternatives.iter().any(|alternative| {
-        matches!(
-            alternative.summary_maintenance_lifecycle,
-            SummaryMaintenanceLifecycle::Shared { .. }
-        ) && alternative.rejection
-            == Some(SummaryMaintenanceLifecycleRejection::UnsupportedByRuntime)
-    }));
-
-    let exported = serde_json::to_value(export_summary_maintenance_plan(&plan)).unwrap();
-    assert_eq!(
-        exported["deployments"][0]["selected"]["lifecycle"]["kind"],
-        "continuously_maintained"
-    );
-    assert_eq!(
-        exported["deployments"][0]["selected"]["maintenance_mode"],
-        "incremental"
-    );
-    let alternatives = exported["deployments"][0]["alternatives"]
-        .as_array()
-        .expect("exported lifecycle alternatives");
-    assert!(alternatives.iter().any(|alternative| {
-        alternative["lifecycle"]["kind"] == "prepared"
-            && alternative["rejection"] == "requires_predictable_one_time_query"
-    }));
-    assert!(alternatives.iter().any(|alternative| {
-        alternative["lifecycle"]["kind"] == "shared"
-            && alternative["rejection"] == "unsupported_by_runtime"
-    }));
-    assert!(exported["dag"]["nodes"].as_array().is_some());
-    let summary_node = exported["dag"]["nodes"]
-        .as_array()
-        .unwrap()
-        .iter()
-        .find(|node| node["kind"] == "summary_agg")
-        .expect("exported summary_agg node");
-    assert_eq!(
-        summary_node["detail"]["summary_maintenance"]["selected"]["lifecycle"]["kind"],
-        "continuously_maintained"
-    );
-}
-
-fn selected_plan(
-    workload: &PlanningWorkload,
-) -> asap_aware_mapping::SummaryMaintenanceLifecyclePlan {
-    selected_plan_with_model(workload, &FullyCostedRuntime)
-}
-
-fn selected_plan_with_model(
-    workload: &PlanningWorkload,
-    model: &dyn CostModel,
-) -> asap_aware_mapping::SummaryMaintenanceLifecyclePlan {
-    selected_plan_with_horizon(workload, model, Horizon(100.))
-}
-
-fn selected_plan_with_horizon(
-    workload: &PlanningWorkload,
-    model: &dyn CostModel,
-    horizon: Horizon,
-) -> asap_aware_mapping::SummaryMaintenanceLifecyclePlan {
-    workload.validate().unwrap();
-
-    let lowered = lower_promql_workload(workload, 0)
-        .expect("valid PromQL workload")
-        .into_iter()
-        .next()
-        .expect("one normalized workload entry");
-    selected_plan_for_lowered(workload, lowered, model, horizon)
-}
-
-fn selected_plan_for_lowered(
-    workload: &PlanningWorkload,
-    lowered: Rc<asap_types::ir::OperatorNode>,
-    model: &dyn CostModel,
-    horizon: Horizon,
-) -> asap_aware_mapping::SummaryMaintenanceLifecyclePlan {
-    let root = lowered;
-    let strategies = asap_aware_mapping::default_strategies_with(model);
-    let space = search_workload_with(vec![("dashboard", Rc::clone(&root))], &strategies);
-    let target = Rc::clone(&space.roots[0].1);
-    let capabilities = SummaryMaintenanceLifecycleCapabilities {
-        supports_ephemeral: true,
-        supports_prepared: false,
-        supports_shared: false,
-        supports_continuously_maintained: true,
-    };
-
-    let selection = global_selection_with_summary_maintenance_lifecycles(
-        &space,
-        WorkloadDemand {
-            workload: &workload.query_workload,
-            data_workload: workload.data_workload.as_ref(),
-            entry_indices: &[1],
-        },
-        NOW_MS,
-        Some(horizon),
-        capabilities,
-        model,
-    )
-    .unwrap();
-    assemble_selected_dag_with_summary_maintenance_lifecycles(
-        &selection,
-        &target,
-        WorkloadDemand::new_with_data(
-            &workload.query_workload,
-            workload.data_workload.as_ref().unwrap(),
-            &[1],
-        ),
-        NOW_MS,
-        Some(horizon),
-        capabilities,
-        model,
-    )
-    .unwrap()
-    .expect("selected summary plan")
-}
-
-mod physical_common;
-
-/// A selected continuous lifecycle supplies a materialization boundary; its
-/// maintenance and query DAGs execute the selected KLL computation in fresh runs.
-#[test]
-fn continuous_lifecycle_compiles_and_executes_spatial_kll() {
-    use asap_physical_operators::{
-        physical_planner::{compile_candidate, InputContract},
-        runtime::Scope,
-        values::{Batch, Value},
-    };
-    use asap_types::{post_asap::FieldDataType, pre_asap::DataType};
-    use std::{collections::BTreeMap, sync::Arc};
-    let mut workload = dashboard_workload();
-    workload.query_workload.query_batch.as_mut().unwrap()[0].query =
-        Query("quantile(0.99, latency)".into());
-    workload.query_workload.repeating_queries.as_mut().unwrap()[0].query =
-        Query("quantile(0.99, latency)".into());
-    let selected = selected_plan(&workload);
-    assert_eq!(
-        selected.deployments[0]
-            .summary_maintenance_lifecycle_guarantee
-            .as_ref()
-            .unwrap()
-            .summary_maintenance_lifecycle,
-        SummaryMaintenanceLifecycle::ContinuouslyMaintained
-    );
-    let dag = compile_physical_asap_dag(&selected.root).unwrap();
-    let build = dag
-        .nodes
-        .iter()
-        .find(|node| matches!(node.payload, PhysicalASAPOperatorPayload::SummaryAgg { .. }))
-        .unwrap();
-    let input = dag
-        .edges
-        .iter()
-        .find(|edge| edge.consumer == build.id)
-        .unwrap()
-        .producer;
-    let raw = dag.nodes.iter().find(|node| node.id == input).unwrap();
-    let schema = Arc::new(raw.output_schema.clone());
-    let candidate = compile_candidate(
-        &dag,
-        BTreeMap::from([(u64::from(input.0), InputContract::bounded(schema.clone()))]),
-        &[u64::from(dag.roots[0].0)],
-        &[u64::from(build.id.0)],
-    )
-    .unwrap();
-
-    // A continuous input without a finite pane boundary cannot implement this
-    // blocking builder. Retain lifecycle ownership in the candidate payload;
-    // only the legal bounded request candidate reaches workload pricing.
-    let mut unbounded = InputContract::bounded(schema.clone());
-    unbounded.properties.boundedness = asap_physical_operators::plan::Boundedness::Unbounded;
-    let rejected = compile_candidate(
-        &dag,
-        BTreeMap::from([(u64::from(input.0), unbounded)]),
-        &[u64::from(dag.roots[0].0)],
-        &[u64::from(build.id.0)],
-    );
-    assert!(rejected.is_err());
-    let request = compile_candidate(
-        &dag,
-        BTreeMap::from([(u64::from(input.0), InputContract::bounded(schema.clone()))]),
-        &[u64::from(dag.roots[0].0)],
-        &[],
-    )
-    .unwrap();
-    let mut priced = 0;
-    let feedback = asap_physical_operators::physical_planner::select_candidate(
-        vec![
-            rejected.map(|candidate| {
-                (
-                    SummaryMaintenanceLifecycle::ContinuouslyMaintained,
-                    candidate,
-                )
-            }),
-            Ok((SummaryMaintenanceLifecycle::Ephemeral, request)),
-        ],
-        |_| {
-            priced += 1;
-            Ok(Some(
-                asap_physical_operators::physical_planner::CandidateCost {
-                    workload_scope: "dashboard".into(),
-                    horizon_seconds: 100.,
-                    total_cost: 1000.,
-                },
-            ))
-        },
-    )
-    .unwrap();
-    assert_eq!(priced, 1);
-    assert_eq!(feedback.candidate.0, SummaryMaintenanceLifecycle::Ephemeral);
-    for revision in [1, 2] {
-        let rows = (1..=100)
-            .map(|value| {
-                schema
-                    .fields
-                    .iter()
-                    .map(|field| match field.dtype {
-                        FieldDataType::Plain(DataType::Float64) => Value::Float64(f64::from(value)),
-                        FieldDataType::Plain(DataType::Timestamp) => Value::Timestamp(300_000),
-                        _ => panic!("unexpected field {field:?}"),
-                    })
-                    .collect()
-            })
-            .collect();
-        let raw_batch = Batch::try_new(schema.clone(), rows).unwrap();
-        let direct = physical_common::execute(
-            &feedback.candidate.1.query,
-            BTreeMap::from([(u64::from(input.0), raw_batch.clone())]),
-            Scope::Query {
-                evaluation_time_ms: 300_000,
-                revision,
-            },
-        );
-        let state = physical_common::execute(
-            candidate.precompute.as_ref().unwrap(),
-            BTreeMap::from([(u64::from(input.0), raw_batch)]),
-            Scope::Ingestion {
-                window_start_ms: 0,
-                window_end_ms: 300_000,
-                revision,
-            },
-        );
-        let result = physical_common::execute(
-            &candidate.query,
-            BTreeMap::from([(u64::from(build.id.0), state[0][0].clone())]),
-            Scope::Query {
-                evaluation_time_ms: 300_000,
-                revision,
-            },
-        );
-        let values: Vec<_> = result[0]
-            .iter()
-            .flat_map(|batch| batch.rows())
-            .flat_map(|row| row.iter())
-            .filter_map(|value| {
-                if let Value::Float64(value) = value {
-                    Some(*value)
-                } else {
-                    None
-                }
-            })
-            .collect();
-        let direct_values: Vec<_> = direct[0]
-            .iter()
-            .flat_map(|batch| batch.rows())
-            .flat_map(|row| row.iter())
-            .filter_map(|value| {
-                if let Value::Float64(value) = value {
-                    Some(*value)
-                } else {
-                    None
-                }
-            })
-            .collect();
-        assert_eq!(
-            values, direct_values,
-            "maintenance and request candidates preserve the same population"
-        );
-        assert_eq!(values.len(), 1);
-        assert!(
-            (98. ..=100.).contains(&values[0]),
-            "p99 rank must reflect the supplied population"
-        );
-    }
-}
-
-fn quantile_workload(query: &str) -> PlanningWorkload {
-    let mut workload = dashboard_workload();
-    workload.query_workload.query_batch.as_mut().unwrap()[0].query = Query(query.into());
-    workload.query_workload.repeating_queries.as_mut().unwrap()[0].query = Query(query.into());
-    workload
-}
-
-/// Timed DAG for `query` after binding every summary state to `lifecycle`.
-/// Grouped queries carry a physical series identity, as per-entity state needs.
-fn lifecycle_timed_dag(
-    query: &str,
-    lifecycle: &SummaryMaintenanceLifecycle,
-) -> (asap_types::ir::export::PhysicalASAPDAG, Vec<u64>) {
-    use asap_aware_mapping::enumerate_summary_maintenance_lifecycles;
-    let workload = quantile_workload(query);
-    let mut lowered = lower_promql_workload(&workload, 0).unwrap().remove(0);
-    if query.contains(" by(") {
-        lowered =
-            asap_physical_operators::physical_planner::promql_rows::with_series_identity(&lowered)
-                .unwrap();
-    }
-    let root =
-        selected_plan_for_lowered(&workload, lowered, &FullyCostedRuntime, Horizon(100.)).root;
-    let candidates = enumerate_summary_maintenance_lifecycles(
-        root,
-        WorkloadDemand::new_with_data(
-            &workload.query_workload,
-            workload.data_workload.as_ref().unwrap(),
-            &[1],
-        ),
-        NOW_MS,
-        Some(Horizon(100.)),
-        SummaryMaintenanceLifecycleCapabilities::ALL,
-        &FullyCostedRuntime,
-    )
-    .unwrap();
-    let choices: Vec<_> = candidates
-        .deployments()
-        .iter()
-        .map(|deployment| (deployment.post_asap_node_id, lifecycle.clone()))
-        .collect();
-    let mut states: Vec<_> = choices.iter().map(|(id, _)| u64::from(id.0)).collect();
-    states.sort_unstable();
-    let dag = candidates
-        .select(&choices)
-        .unwrap()
-        .execution_timed_dag()
-        .unwrap();
-    (dag, states)
-}
-
-/// Compile inputs for a timed DAG: its raw source, available at either phase.
-fn raw_inputs(
-    dag: &asap_types::ir::export::PhysicalASAPDAG,
-) -> std::collections::BTreeMap<u64, asap_physical_operators::physical_planner::InputContract> {
-    let raw = dag
-        .nodes
-        .iter()
-        .find(|node| {
-            matches!(
-                node.payload,
-                asap_types::ir::export::PhysicalASAPOperatorPayload::Relational {
-                    operator: asap_types::ir::export::NonASAPOpKind::TimeRange { .. }
-                }
-            )
-        })
-        .unwrap();
-    std::collections::BTreeMap::from([(
-        u64::from(raw.id.0),
-        asap_physical_operators::physical_planner::InputContract::bounded(std::sync::Arc::new(
-            raw.output_schema.clone(),
-        )),
-    )])
-}
-
-/// For existing PromQL fixtures, Planner's own retained lifecycle selection
-/// reproduces the timing that realization strategies assign today.
-#[test]
-fn planner_lifecycle_selection_reproduces_strategy_timing() {
-    for query in [
-        "quantile_over_time(0.99, latency[5m])",
-        "quantile(0.99, latency)",
-        "sum by(job)(rate(m[1m]))",
-    ] {
-        let plan = selected_plan(&quantile_workload(query));
-        assert!(!plan.selected_raw_recompute, "{query}");
-        assert!(plan.deployments.iter().all(|deployment| {
-            deployment
-                .summary_maintenance_lifecycle_guarantee
-                .as_ref()
-                .is_some_and(|guarantee| {
-                    guarantee.summary_maintenance_lifecycle
-                        != SummaryMaintenanceLifecycle::Ephemeral
-                })
-        }));
-        let strategy = compile_physical_asap_dag(&plan.root).unwrap();
-        assert_eq!(plan.execution_timed_dag().unwrap(), strategy, "{query}");
-    }
-}
-
-/// An explicitly chosen lifecycle reaches physical compilation through timing:
-/// ContinuouslyMaintained puts the state in precompute, Ephemeral leaves
-/// precompute empty and reads the raw source at query time; both answer alike.
-#[test]
-fn chosen_lifecycle_timing_decides_precompute_contents() {
-    use asap_physical_operators::{
-        physical_planner::{compile_candidate, frontier_from_timing},
-        runtime::Scope,
-        values::{Batch, Value},
-    };
-    use asap_types::{post_asap::FieldDataType, pre_asap::DataType};
-    use std::collections::BTreeMap;
-
-    let mut answers = Vec::new();
-    for lifecycle in [
-        SummaryMaintenanceLifecycle::ContinuouslyMaintained,
-        SummaryMaintenanceLifecycle::Ephemeral,
-    ] {
-        let (dag, states) = lifecycle_timed_dag("quantile(0.99, latency)", &lifecycle);
-        let [state] = states[..] else {
-            panic!("one summary state");
-        };
-        let inputs = raw_inputs(&dag);
-        let (&raw_id, contract) = inputs.iter().next().unwrap();
-        let schema = contract.schema.clone();
-        let frontier = frontier_from_timing(&dag).unwrap();
-        let candidate =
-            compile_candidate(&dag, inputs, &[u64::from(dag.roots[0].0)], &frontier).unwrap();
-        let rows = (1..=100)
-            .map(|value| {
-                schema
-                    .fields
-                    .iter()
-                    .map(|field| match field.dtype {
-                        FieldDataType::Plain(DataType::Float64) => Value::Float64(f64::from(value)),
-                        FieldDataType::Plain(DataType::Timestamp) => Value::Timestamp(300_000),
-                        _ => panic!("unexpected field {field:?}"),
-                    })
-                    .collect()
-            })
-            .collect();
-        let raw_batch = Batch::try_new(schema.clone(), rows).unwrap();
-        let query_scope = Scope::Query {
-            evaluation_time_ms: 300_000,
-            revision: 1,
-        };
-        let result = if lifecycle == SummaryMaintenanceLifecycle::Ephemeral {
-            assert!(frontier.is_empty());
-            assert!(candidate.precompute.is_none());
-            physical_common::execute(
-                &candidate.query,
-                BTreeMap::from([(raw_id, raw_batch)]),
-                query_scope,
-            )
-        } else {
-            assert_eq!(frontier, [state]);
-            assert_eq!(
-                candidate
-                    .materialized_outputs
-                    .keys()
-                    .copied()
-                    .collect::<Vec<_>>(),
-                [state]
-            );
-            let stored = physical_common::execute(
-                candidate.precompute.as_ref().unwrap(),
-                BTreeMap::from([(raw_id, raw_batch)]),
-                Scope::Ingestion {
-                    window_start_ms: 0,
-                    window_end_ms: 300_000,
-                    revision: 1,
-                },
-            );
-            physical_common::execute(
-                &candidate.query,
-                BTreeMap::from([(state, stored[0][0].clone())]),
-                query_scope,
-            )
-        };
-        answers.push(
-            result[0]
-                .iter()
-                .flat_map(|batch| batch.rows())
-                .flat_map(|row| row.iter())
-                .filter_map(|value| match value {
-                    Value::Float64(value) => Some(*value),
-                    _ => None,
-                })
-                .collect::<Vec<_>>(),
-        );
-    }
-    assert_eq!(answers[0], answers[1]);
-    assert_eq!(answers[0].len(), 1);
-}
-
-/// One compilation, cut by each lifecycle assignment's timing, yields exactly
-/// the candidate `compile_candidate` builds for that timed DAG: the retained
-/// state is the frontier under ContinuouslyMaintained, and nothing under
-/// Ephemeral. Covers the KLL quantile fixture and grouped Rate→Sum.
-#[test]
-fn lifecycle_timing_cuts_one_compilation() {
-    use asap_physical_operators::physical_planner::{
-        compile, compile_candidate, cut_candidate, frontier_from_timing,
-    };
-    for query in ["quantile(0.99, latency)", "sum by(job)(rate(m[1m]))"] {
-        let ephemeral = SummaryMaintenanceLifecycle::Ephemeral;
-        let (compiled_dag, _) = lifecycle_timed_dag(query, &ephemeral);
-        let inputs = raw_inputs(&compiled_dag);
-        let roots = [u64::from(compiled_dag.roots[0].0)];
-        let compiled = compile(&compiled_dag, inputs.clone(), &roots).unwrap();
-        for lifecycle in [
-            SummaryMaintenanceLifecycle::ContinuouslyMaintained,
-            ephemeral,
-        ] {
-            let (dag, states) = lifecycle_timed_dag(query, &lifecycle);
-            let frontier = frontier_from_timing(&dag).unwrap();
-            // Retained states read by a query-time consumer, or the root itself.
-            let query_time = |id: u64| {
-                dag.nodes.iter().any(|node| {
-                    u64::from(node.id.0) == id
-                        && node.output_state.timing
-                            == asap_types::post_asap::ExecutionTiming::QueryTime
-                })
-            };
-            let expected_frontier = if lifecycle == SummaryMaintenanceLifecycle::Ephemeral {
-                vec![]
-            } else {
-                states
-                    .iter()
-                    .copied()
-                    .filter(|state| {
-                        *state == u64::from(dag.roots[0].0)
-                            || dag.edges.iter().any(|edge| {
-                                u64::from(edge.producer.0) == *state
-                                    && query_time(u64::from(edge.consumer.0))
-                            })
-                    })
-                    .collect()
-            };
-            assert_eq!(frontier, expected_frontier, "{query} {lifecycle:?}");
-            let cut = cut_candidate(&compiled, &frontier).unwrap();
-            let expected = compile_candidate(&dag, inputs.clone(), &roots, &frontier).unwrap();
-            assert_eq!(
-                serde_json::to_vec(&cut).unwrap(),
-                serde_json::to_vec(&expected).unwrap(),
-                "{query} {lifecycle:?}"
-            );
-        }
-    }
-}
-
-/// A maintained current-series population is placed by its lifecycle choice:
-/// ContinuouslyMaintained stores the population in precompute, Ephemeral
-/// rebuilds it from the raw source at query time; both rank alike.
-#[test]
-fn chosen_population_lifecycle_decides_precompute_contents() {
-    use asap_aware_mapping::{
-        enumerate_summary_maintenance_lifecycles,
-        maintained_population::MaintainedPopulationStrategy,
-    };
-    use asap_physical_operators::{
-        physical_planner::{
-            compile_candidate,
-            promql_rows::{series_row, with_series_identity},
-            InputContract,
-        },
-        runtime::Scope,
-        values::{Batch, Value},
-    };
-    use asap_types::post_asap::maintained_population::PopulationInput;
-    use std::{collections::BTreeMap, sync::Arc};
-
-    let workload = quantile_workload("topk by(job)(1, m)");
-    let root =
-        with_series_identity(&lower_promql_workload(&workload, 0).unwrap().remove(0)).unwrap();
-    let root = MaintainedPopulationStrategy::new(std::slice::from_ref(&root))
-        .candidate(&root)
-        .unwrap();
-    let mut answers = Vec::new();
-    for lifecycle in [
-        SummaryMaintenanceLifecycle::ContinuouslyMaintained,
-        SummaryMaintenanceLifecycle::Ephemeral,
-    ] {
-        let candidates = enumerate_summary_maintenance_lifecycles(
-            Rc::clone(&root),
-            WorkloadDemand::new_with_data(
-                &workload.query_workload,
-                workload.data_workload.as_ref().unwrap(),
-                &[1],
-            ),
-            NOW_MS,
-            Some(Horizon(100.)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &FullyCostedRuntime,
-        )
-        .unwrap();
-        let [deployment] = candidates.deployments() else {
-            panic!("one population state");
-        };
-        let id = deployment.post_asap_node_id;
-        let dag = candidates
-            .select(&[(id, lifecycle.clone())])
-            .unwrap()
-            .execution_timed_dag()
-            .unwrap();
-        let population = dag.nodes.iter().find(|node| node.id == id).unwrap();
-        let PhysicalASAPOperatorPayload::MaintainPopulation { population } = &population.payload
-        else {
-            panic!("the deployment is the maintained population");
-        };
-        let PopulationInput::CurrentSeries(spec) = &population.input else {
-            panic!("current-series population");
-        };
-        let lookback = i64::try_from(spec.lookback_ms).unwrap();
-        let raw = dag
-            .nodes
-            .iter()
-            .find(|node| {
-                matches!(
-                    node.payload,
-                    PhysicalASAPOperatorPayload::Relational {
-                        operator: asap_types::ir::export::NonASAPOpKind::TimeRange { .. }
-                    }
-                )
-            })
-            .unwrap();
-        let (raw_id, schema) = (u64::from(raw.id.0), Arc::new(raw.output_schema.clone()));
-        let frontier =
-            asap_physical_operators::physical_planner::frontier_from_timing(&dag).unwrap();
-        let candidate = compile_candidate(
-            &dag,
-            BTreeMap::from([(raw_id, InputContract::bounded(schema.clone()))]),
-            &[u64::from(dag.roots[0].0)],
-            &frontier,
-        )
-        .unwrap();
-        let end = 60_000;
-        let rows = [("a", end - 1, 100.), ("a", end, 1.), ("b", end, 20.)]
-            .into_iter()
-            .map(|(instance, at, value)| {
-                series_row(
-                    &schema,
-                    &BTreeMap::from([
-                        ("job".into(), "api".into()),
-                        ("instance".into(), instance.into()),
-                    ]),
-                    at,
-                    value,
-                )
-                .unwrap()
-            })
-            .collect();
-        let raw_batch = Batch::try_new(schema.clone(), rows).unwrap();
-        let query_scope = Scope::Query {
-            evaluation_time_ms: end,
-            revision: 1,
-        };
-        let result = if lifecycle == SummaryMaintenanceLifecycle::Ephemeral {
-            assert!(frontier.is_empty());
-            assert!(candidate.precompute.is_none());
-            physical_common::execute(
-                &candidate.query,
-                BTreeMap::from([(raw_id, raw_batch)]),
-                query_scope,
-            )
-        } else {
-            let state = u64::from(id.0);
-            assert_eq!(frontier, [state]);
-            let stored = physical_common::execute(
-                candidate.precompute.as_ref().unwrap(),
-                BTreeMap::from([(raw_id, raw_batch)]),
-                Scope::Ingestion {
-                    window_start_ms: end - lookback,
-                    window_end_ms: end,
-                    revision: 1,
-                },
-            );
-            physical_common::execute(
-                &candidate.query,
-                BTreeMap::from([(state, stored[0][0].clone())]),
-                query_scope,
-            )
-        };
-        answers.push(
-            result[0]
-                .iter()
-                .flat_map(|batch| batch.rows())
-                .flat_map(|row| row.iter())
-                .filter_map(|value| match value {
-                    Value::Float64(value) => Some(*value),
-                    _ => None,
-                })
-                .collect::<Vec<_>>(),
-        );
-    }
-    assert_eq!(answers[0], answers[1]);
-    assert_eq!(answers[0], [20.]);
-}
-
-/// Grouped Rate→Sum is one inventory candidate: retaining the Sum state puts
-/// Rate and Sum in precompute, while an `Ephemeral` Sum over a retained Rate
-/// state leaves Sum in the query DAG.
-#[test]
-fn grouped_rate_sum_placement_is_a_lifecycle_choice() {
-    use asap_aware_mapping::enumerate_summary_maintenance_lifecycles;
-    use asap_physical_operators::physical_planner::{compile_candidate, InputContract};
-    use asap_types::post_asap::{ExactKind, FieldDataType};
-    use std::{collections::BTreeMap, sync::Arc};
-
-    let workload = quantile_workload("sum by(job)(rate(m[1m]))");
-    let root = asap_physical_operators::physical_planner::promql_rows::with_series_identity(
-        &lower_promql_workload(&workload, 0).unwrap().remove(0),
-    )
-    .unwrap();
-    let is_exact = |node: &OperatorNode, kind: ExactKind| {
-        matches!(&node.operator, asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
-            family: FieldDataType::ExactAggregate(k, _), ..
-        }) if *k == kind)
-    };
-    let inventory = asap_aware_mapping::search_workload(vec![("q", root)])
-        .enumerate_candidate_dags(4096)
-        .unwrap();
-    let candidates = inventory
-        .candidates
-        .into_iter()
-        .map(|mut forest| forest.remove(0).1)
-        .filter(|candidate| {
-            matches!(&candidate.operator, asap_types::ir::Operator::ASAP(ASAPOp::FinalizeExactAccumulator { child })
-                if is_exact(child, ExactKind::Sum))
-        })
-        .collect::<Vec<_>>();
-    let [candidate] = candidates.as_slice() else {
-        panic!("one grouped Sum candidate, got {}", candidates.len());
-    };
-    let mut placements = Vec::new();
-    for sum_lifecycle in [
-        SummaryMaintenanceLifecycle::ContinuouslyMaintained,
-        SummaryMaintenanceLifecycle::Ephemeral,
-    ] {
-        let lifecycles = enumerate_summary_maintenance_lifecycles(
-            Rc::clone(candidate),
-            WorkloadDemand::new_with_data(
-                &workload.query_workload,
-                workload.data_workload.as_ref().unwrap(),
-                &[1],
-            ),
-            NOW_MS,
-            Some(Horizon(100.)),
-            SummaryMaintenanceLifecycleCapabilities::ALL,
-            &FullyCostedRuntime,
-        )
-        .unwrap();
-        let choices = lifecycles
-            .deployments()
-            .iter()
-            .map(|deployment| {
-                let lifecycle = if is_exact(&deployment.summary, ExactKind::Sum) {
-                    sum_lifecycle.clone()
-                } else {
-                    SummaryMaintenanceLifecycle::ContinuouslyMaintained
-                };
-                (deployment.post_asap_node_id, lifecycle)
-            })
-            .collect::<Vec<_>>();
-        assert_eq!(choices.len(), 2, "Rate and Sum states");
-        let dag = lifecycles
-            .select(&choices)
-            .unwrap()
-            .execution_timed_dag()
-            .unwrap();
-        let raw = dag
-            .nodes
-            .iter()
-            .find(|node| {
-                matches!(
-                    node.payload,
-                    PhysicalASAPOperatorPayload::Relational {
-                        operator: asap_types::ir::export::NonASAPOpKind::TimeRange { .. }
-                    }
-                )
-            })
-            .unwrap();
-        let frontier =
-            asap_physical_operators::physical_planner::frontier_from_timing(&dag).unwrap();
-        let [boundary] = frontier.as_slice() else {
-            panic!("one precompute output, got {frontier:?}");
-        };
-        let boundary = dag
-            .nodes
-            .iter()
-            .find(|node| u64::from(node.id.0) == *boundary)
-            .unwrap();
-        let physical = compile_candidate(
-            &dag,
-            BTreeMap::from([(
-                u64::from(raw.id.0),
-                InputContract::bounded(Arc::new(raw.output_schema.clone())),
-            )]),
-            &[u64::from(dag.roots[0].0)],
-            &frontier,
-        )
-        .unwrap();
-        let json = |value| String::from_utf8(serde_json::to_vec(value).unwrap()).unwrap();
-        placements.push((
-            boundary.payload.clone(),
-            json(physical.precompute.as_ref().unwrap()),
-            json(&physical.query),
-        ));
-    }
-    let builds = |json: &str, kind: &str| {
-        json.contains(&format!(
-            r#"{{"SummaryBuild":{{"family":{{"ExactAggregate":["{kind}","{kind}"]}}"#
-        ))
-    };
-    let [(retained, retained_pre, retained_query), (ephemeral, ephemeral_pre, ephemeral_query)] =
-        placements.as_slice()
-    else {
-        unreachable!()
-    };
-    let state = |payload: &PhysicalASAPOperatorPayload, kind: ExactKind| {
-        matches!(payload, PhysicalASAPOperatorPayload::SummaryAgg {
-            family: FieldDataType::ExactAggregate(k, _), ..
-        } if *k == kind)
-    };
-    assert!(state(retained, ExactKind::Sum));
-    assert!(builds(retained_pre, "Rate") && builds(retained_pre, "Sum"));
-    assert!(!retained_query.contains("SummaryBuild"));
-    assert!(state(ephemeral, ExactKind::Rate));
-    assert!(builds(ephemeral_pre, "Rate") && !builds(ephemeral_pre, "Sum"));
-    assert!(builds(ephemeral_query, "Sum"));
-}
-
-/// The lifecycle-timed DAG Planner selects for `query` with upfront series
-/// typing, and whether it keeps an ingestion-time Binary.
-fn typed_selection(query: &str) -> (asap_types::ir::export::PhysicalASAPDAG, bool) {
-    use asap_types::post_asap::ExecutionTiming;
-    let workload = quantile_workload(query);
-    let lowered = asap_types::ir::schema_support::with_promql_series_identity(
-        &lower_promql_workload(&workload, 0).unwrap().remove(0),
-    )
-    .unwrap();
-    let dag = selected_plan_for_lowered(&workload, lowered, &FullyCostedRuntime, Horizon(100.))
-        .execution_timed_dag()
-        .unwrap();
-    let ingestion_binary = dag.nodes.iter().any(|node| {
-        matches!(
-            node.payload,
-            PhysicalASAPOperatorPayload::Relational {
-                operator: asap_types::ir::export::NonASAPOpKind::BinaryOp { .. }
-            }
-        ) && node.output_state.timing == ExecutionTiming::IngestionTime
-    });
-    (dag, ingestion_binary)
-}
-
-/// Execute a timed DAG's precompute and query DAGs over `samples`
-/// (`(metric, job, seconds, value)`) at 300s; returns the root's values.
-fn execute_timed(
-    dag: &asap_types::ir::export::PhysicalASAPDAG,
-    samples: &[(&str, &str, i64, f64)],
-) -> Vec<f64> {
-    use asap_physical_operators::{
-        physical_planner::{compile_candidate, frontier_from_timing, promql_rows, InputContract},
-        runtime::Scope,
-        values::{Batch, Value},
-    };
-    use asap_types::{ir::export::PhysicalASAPOperatorPayload, pre_asap::Source};
-    use std::{collections::BTreeMap, sync::Arc};
-    // Raw inputs: a selector Fallback is itself the input; a retained
-    // expression reads each of its selectors through its raw-series slots.
-    let mut raw = BTreeMap::new();
-    for node in &dag.nodes {
-        if !matches!(
-            node.payload,
-            PhysicalASAPOperatorPayload::Relational {
-                operator: asap_types::ir::export::NonASAPOpKind::TimeRange { .. }
-                    | asap_types::ir::export::NonASAPOpKind::Scan { .. }
-            }
-        ) {
-            continue;
-        }
-        let mut id = node.id;
-        loop {
-            let n = dag.nodes.iter().find(|n| n.id == id).unwrap();
-            if let PhysicalASAPOperatorPayload::Relational {
-                operator:
-                    asap_types::ir::export::NonASAPOpKind::Scan {
-                        source: Source::TimeSeries { metric },
-                        ..
-                    },
-            } = &n.payload
-            {
-                raw.insert(
-                    u64::from(node.id.0),
-                    (Arc::new(node.output_schema.clone()), metric.clone()),
-                );
-                break;
-            }
-            id = dag
-                .edges
-                .iter()
-                .find(|e| e.consumer == id)
-                .unwrap()
-                .producer;
-        }
-    }
-    let batch = |schema: &asap_physical_operators::values::SchemaRef, name: &str| {
-        let rows = samples
-            .iter()
-            .filter(|sample| sample.0 == name)
-            .map(|(metric, job, seconds, value)| {
-                let labels = BTreeMap::from([
-                    ("__name__".to_string(), metric.to_string()),
-                    ("job".to_string(), job.to_string()),
-                ]);
-                promql_rows::series_row(schema, &labels, seconds * 1000, *value).unwrap()
-            })
-            .collect();
-        Batch::try_new(schema.clone(), rows).unwrap()
-    };
-    let frontier = frontier_from_timing(dag).unwrap();
-    let candidate = compile_candidate(
-        dag,
-        raw.iter()
-            .map(|(id, (schema, _))| (*id, InputContract::bounded(schema.clone())))
-            .collect(),
-        &[u64::from(dag.roots[0].0)],
-        &frontier,
-    )
-    .unwrap();
-    let raw_sources = |plan: &asap_physical_operators::physical_planner::CompiledPhysicalDAG| {
-        plan.input_contracts()
-            .filter_map(|(id, _)| raw.get(&id).map(|(schema, name)| (id, batch(schema, name))))
-            .collect::<BTreeMap<_, _>>()
-    };
-    let mut query_sources = raw_sources(&candidate.query);
-    if let Some(precompute) = &candidate.precompute {
-        let stored = physical_common::execute(
-            precompute,
-            raw_sources(precompute),
-            Scope::Ingestion {
-                window_start_ms: 240_000,
-                window_end_ms: 300_000,
-                revision: 1,
-            },
-        );
-        for (root, batches) in precompute.roots().iter().zip(stored) {
-            query_sources.insert(*root, batches[0].clone());
-        }
-    }
-    let result = physical_common::execute(
-        &candidate.query,
-        query_sources,
-        Scope::Query {
-            evaluation_time_ms: 300_000,
-            revision: 1,
-        },
-    );
-    result[0]
-        .iter()
-        .flat_map(|batch| batch.rows())
-        .flat_map(|row| row.iter())
-        .filter_map(|value| match value {
-            Value::Float64(value) => Some(*value),
-            _ => None,
-        })
-        .collect()
-}
-
-/// Prometheus drops series without a match: arithmetic over different
-/// selectors keeps only label sets present on both sides (none when disjoint),
-/// and such arithmetic never becomes aligned maintenance.
-#[test]
-fn maintained_arithmetic_over_different_selectors_matches_prometheus() {
-    let query = "sum(sum_over_time(m[1m]) + sum_over_time(n[1m]))";
-    let (dag, ingestion_binary) = typed_selection(query);
-    let disjoint = [
-        ("m", "a", 250, 1.0),
-        ("m", "a", 290, 2.0),
-        ("n", "b", 250, 5.0),
-    ];
-    let values = execute_timed(&dag, &disjoint);
-    assert!(values.is_empty(), "{values:?}");
-    // Only job a is on both sides: m_a + n_a = (1 + 2) + 7; m{job="b"} is dropped.
-    let overlapping = [
-        ("m", "a", 250, 1.0),
-        ("m", "a", 290, 2.0),
-        ("m", "b", 250, 5.0),
-        ("n", "a", 250, 7.0),
-    ];
-    assert_eq!(execute_timed(&dag, &overlapping), [10.0]);
-    assert!(!ingestion_binary);
-    // The quantile's exact fallback runs outside Planner; it must not be maintained either.
-    let (_, ingestion_binary) =
-        typed_selection("quantile(0.9, sum_over_time(m[1m]) + sum_over_time(n[1m]))");
-    assert!(!ingestion_binary);
-}
-
-/// Arithmetic over one selector keeps its maintained layout and adds each
-/// series' two evaluations before the quantile.
-#[test]
-fn maintained_arithmetic_over_one_selector_executes() {
-    let (dag, ingestion_binary) =
-        typed_selection("quantile(0.9, sum_over_time(m[1m]) + sum_over_time(m[1m]))");
-    assert!(ingestion_binary, "one selector shares its key set");
-    let values = execute_timed(
-        &dag,
-        &[
-            ("m", "a", 250, 1.0),
-            ("m", "a", 290, 2.0),
-            ("m", "b", 250, 5.0),
-        ],
-    );
-    // job a: 3 + 3 = 6; job b: 5 + 5 = 10 (mispairing a with b gives 8 and 8).
-    // KLL at epsilon 0.01 returns an input value within 0.01 of rank 0.9; of
-    // two values only the larger is.
-    assert_eq!(values, [10.0]);
-}
diff --git a/crates/planner/src/lib.rs b/crates/planner/src/lib.rs
index 4f527f148..506ed12ea 100644
--- a/crates/planner/src/lib.rs
+++ b/crates/planner/src/lib.rs
@@ -25,8 +25,8 @@ use asap_frontend_sql::{lower_sql_dialect, SqlCatalog, SqlError};
 // configures the same models and reads the same output whether it goes through
 // `e2e_plan` or straight to `optimize`.
 pub use asap_aware_mapping::pass::{
-    optimize, LifecycleInput, MajorPass, OptimizationInput, OptimizationPass, OptimizeError,
-    PassRegistry, PlanOutput, PlanningModels, QueryLifecyclePlan,
+    optimize, MajorPass, OptimizationInput, OptimizationPass, OptimizeError, PassRegistry,
+    PlanOutput, PlanningModels, QueryPlan,
 };
 
 // ── Input ────────────────────────────────────────────────────────────────
@@ -53,9 +53,6 @@ pub struct UserInput<'a> {
     pub workload: &'a PlanningWorkload,
     pub frontend_specific: FrontendInput<'a>,
     pub models: PlanningModels<'a>,
-    /// Planning clock and runtime capabilities for the
-    /// maintenance-versus-recomputation decision every plan carries.
-    pub lifecycle: LifecycleInput,
     /// `None` uses [`MajorPass`]. A black-box caller never sets this.
     pub pass: Option<&'a dyn OptimizationPass>,
 }
@@ -65,13 +62,11 @@ impl<'a> UserInput<'a> {
         workload: &'a PlanningWorkload,
         frontend_specific: FrontendInput<'a>,
         models: PlanningModels<'a>,
-        lifecycle: LifecycleInput,
     ) -> Self {
         Self {
             workload,
             frontend_specific,
             models,
-            lifecycle,
             pass: None,
         }
     }
@@ -101,21 +96,6 @@ impl<'a> UserInput<'a> {
             });
         }
 
-        if let Some(horizon) = self.lifecycle.horizon {
-            if !horizon.0.is_finite() || horizon.0 <= 0.0 {
-                return Err(UserInputError::InvalidHorizon(horizon.0));
-            }
-        }
-        // Two clocks would let the DAG be built for one instant and priced
-        // for another, with neither stage able to notice.
-        if let FrontendInput::Promql { now_ms, .. } = &self.frontend_specific {
-            if *now_ms != self.lifecycle.now_ms {
-                return Err(UserInputError::PlanningTimeMismatch {
-                    frontend: *now_ms,
-                    lifecycle: self.lifecycle.now_ms,
-                });
-            }
-        }
         Ok(())
     }
 }
@@ -142,10 +122,6 @@ pub enum UserInputError {
         language: String,
         frontend: &'static str,
     },
-    #[error("planning horizon must be finite and positive, got {0}")]
-    InvalidHorizon(f64),
-    #[error("frontend planning time {frontend} ms disagrees with lifecycle planning time {lifecycle} ms")]
-    PlanningTimeMismatch { frontend: u64, lifecycle: u64 },
 }
 
 #[derive(Debug, thiserror::Error)]
@@ -194,7 +170,7 @@ pub async fn e2e_plan(input: UserInput<'_>) -> Result<PlanOutput, PlanError> {
     let fallback = MajorPass;
     let pass: &dyn OptimizationPass = input.pass.unwrap_or(&fallback);
 
-    let optimization = OptimizationInput::new(&parsed, input.models, input.lifecycle);
+    let optimization = OptimizationInput::new(&parsed, input.models);
     optimize(pass, optimization).map_err(PlanError::Optimize)
 }
 
@@ -202,8 +178,7 @@ pub async fn e2e_plan(input: UserInput<'_>) -> Result<PlanOutput, PlanError> {
 ///
 /// The SQL and MetricsQL frontends are driven one entry at a time rather than
 /// through `lower_sql_batch`, which walks `query_batch` alone and would drop
-/// every repeating query — exactly the entries whose recurrence the lifecycle
-/// stage needs.
+/// every repeating query, and the output must cover every entry.
 async fn lower(input: &UserInput<'_>) -> Result<Vec<asap_types::ir::QueryRoot>, PlanError> {
     let entries = || input.workload.query_workload.entries();
 
diff --git a/crates/planner/tests/e2e_plan.rs b/crates/planner/tests/e2e_plan.rs
index 3ab55b101..0f929c96d 100644
--- a/crates/planner/tests/e2e_plan.rs
+++ b/crates/planner/tests/e2e_plan.rs
@@ -7,9 +7,7 @@ use asap_aware_mapping::pass::{
     OptimizationInput, OptimizationPass, OptimizeError, PlanOutput, PlanningModels,
 };
 use asap_aware_mapping::replacement::default_strategies_with_evidence;
-use asap_aware_mapping::{
-    search_workload_with_targets, Horizon, LifecycleInput, SummaryMaintenanceLifecycleCapabilities,
-};
+use asap_aware_mapping::search_workload_with_targets;
 use asap_frontend_sql::{lower_sql_dialect, SqlCatalog};
 use asap_planner::{e2e_plan, FrontendInput, PlanError, UserInput, UserInputError};
 use asap_types::pre_asap::schema::{DataType, Field, Schema};
@@ -40,12 +38,6 @@ fn batch(sql: &str) -> BatchEntry {
     }
 }
 
-/// The planning clock and default capabilities, no horizon: the least a
-/// caller can supply.
-fn lifecycle() -> LifecycleInput {
-    LifecycleInput::new(NOW_MS, SummaryMaintenanceLifecycleCapabilities::default())
-}
-
 fn lineitem_catalog() -> SqlCatalog {
     SqlCatalog::new().with_table(
         "lineitem",
@@ -89,7 +81,6 @@ async fn plans_every_query_in_entry_order() {
         &workload,
         FrontendInput::Sql { catalog: &catalog },
         PlanningModels::builtin(),
-        lifecycle(),
     );
 
     let output = e2e_plan(input).await.expect("workload plans");
@@ -97,13 +88,10 @@ async fn plans_every_query_in_entry_order() {
     assert_eq!(output.entry_indices(), vec![0, 1]);
 }
 
-/// With the built-in cost model no lifecycle cost is ever known, and
-/// lifecycle-aware selection then finalizes every summary target as raw
-/// recompute: the cost-only selection picks a sketch for the same workload.
-/// This pins that behavior so the facade's output is not mistaken for a
-/// decision; it is a defect of `DefaultCostModel`, not addressed here.
+/// The facade selects what workload-wide cost selection selects over the
+/// same search space: here a summary for both approximate queries.
 #[tokio::test]
-async fn builtin_cost_model_cannot_price_lifecycles_and_falls_back_to_raw_recompute() {
+async fn facade_plans_match_cost_only_selection() {
     let workload = sql_workload(
         vec![
             batch("SELECT COUNT(DISTINCT l_orderkey) FROM lineitem"),
@@ -118,7 +106,6 @@ async fn builtin_cost_model_cannot_price_lifecycles_and_falls_back_to_raw_recomp
         &workload,
         FrontendInput::Sql { catalog: &catalog },
         models,
-        lifecycle(),
     ))
     .await
     .expect("workload plans");
@@ -153,21 +140,17 @@ async fn builtin_cost_model_cannot_price_lifecycles_and_falls_back_to_raw_recomp
             "entry {}: cost-only selection was expected to pick a summary",
             plan.entry_index
         );
-        assert!(
-            !plan.plan.root.contains_asap()
-                && plan.plan.selected_raw_recompute
-                && plan.plan.deployments.is_empty()
-                && plan.plan.summary_total_cost.is_none()
-                && plan.plan.raw_recompute_total_cost.is_none(),
-            "entry {}: the built-in model priced a lifecycle",
+        assert_eq!(
+            plan.root, cost_only,
+            "entry {}: the facade selected a different DAG",
             plan.entry_index
         );
     }
 }
 
 /// A repeating SQL query reaches the optimizer. `lower_sql_batch` walks
-/// `query_batch` alone, so driving the frontend through it would drop exactly
-/// the entries whose recurrence the lifecycle stage reads.
+/// `query_batch` alone, so driving the frontend through it would drop the
+/// repeating entries.
 #[tokio::test]
 async fn lowers_repeating_sql_entries_too() {
     let workload = sql_workload(
@@ -187,7 +170,6 @@ async fn lowers_repeating_sql_entries_too() {
         &workload,
         FrontendInput::Sql { catalog: &catalog },
         PlanningModels::builtin(),
-        lifecycle(),
     );
 
     let output = e2e_plan(input).await.expect("workload plans");
@@ -229,7 +211,6 @@ async fn runs_a_caller_supplied_pass_instead_of_the_shipped_one() {
         &workload,
         FrontendInput::Sql { catalog: &catalog },
         PlanningModels::builtin(),
-        lifecycle(),
     )
     .with_pass(&pass);
 
@@ -270,7 +251,6 @@ async fn harness_rejects_a_pass_that_mislabels_entry_indices() {
         &workload,
         FrontendInput::Sql { catalog: &catalog },
         PlanningModels::builtin(),
-        lifecycle(),
     )
     .with_pass(&pass);
 
@@ -302,7 +282,6 @@ async fn rejects_a_frontend_that_does_not_match_the_workload_language() {
             histograms: None,
         },
         PlanningModels::builtin(),
-        lifecycle(),
     );
 
     let err = e2e_plan(input).await.unwrap_err();
@@ -312,48 +291,9 @@ async fn rejects_a_frontend_that_does_not_match_the_workload_language() {
     ));
 }
 
-/// Two planning clocks would let the DAG be built for one instant and priced
-/// for another; the input check refuses that before lowering.
-#[test]
-fn rejects_disagreeing_planning_clocks() {
-    let workload = PlanningWorkload {
-        query_workload: QueryWorkload {
-            language: QueryLanguage::PromQL,
-            query_batch: Some(vec![batch("up")]),
-            repeating_queries: None,
-        },
-        data_workload: Some(DataWorkload {
-            arrival: DataArrival::ContinuouslyIngesting,
-            data_ingestion_interval: Evidence {
-                value: Some(DurationMs(15_000)),
-                ..Default::default()
-            },
-            ..Default::default()
-        }),
-    };
-    let input = UserInput::new(
-        &workload,
-        FrontendInput::Promql {
-            now_ms: NOW_MS,
-            histograms: None,
-        },
-        PlanningModels::builtin(),
-        LifecycleInput::new(
-            NOW_MS + 1,
-            SummaryMaintenanceLifecycleCapabilities::default(),
-        ),
-    );
-
-    assert!(matches!(
-        input.validate(),
-        Err(UserInputError::PlanningTimeMismatch { .. })
-    ));
-}
-
-/// The maintenance decisions ride inside each plan, and the DAG is still
-/// there — inside the plan's `root`, not alongside it.
+/// A repeating PromQL query yields one plan carrying its selected DAG root.
 #[tokio::test]
-async fn lifecycle_decisions_ride_inside_each_plan() {
+async fn each_plan_carries_its_selected_root() {
     let workload = PlanningWorkload {
         query_workload: QueryWorkload {
             language: QueryLanguage::PromQL,
@@ -382,61 +322,15 @@ async fn lifecycle_decisions_ride_inside_each_plan() {
             histograms: None,
         },
         PlanningModels::builtin(),
-        lifecycle().with_horizon(Horizon(3_600.0)),
     );
 
     let output = e2e_plan(input).await.expect("workload plans");
     assert_eq!(output.plans.len(), 1);
     assert_eq!(output.plans[0].entry_index, 0);
-    let _: &Rc<_> = &output.plans[0].plan.root;
+    let _: &Rc<_> = &output.plans[0].root;
     assert_eq!(output.operator_roots().len(), 1);
 }
 
-/// Each root's lifecycle is planned against the entries that read it: a
-/// query polled every minute and an unrelated one polled every ten minutes
-/// each see only their own reads over the hour, not the workload's 66.
-#[tokio::test]
-async fn each_plan_counts_only_its_own_entries_reads() {
-    let repeating = |query: &str, interval_ms: u32| RepeatingEntry {
-        query: Query(query.into()),
-        demand: RepeatedDemand::FixedInterval(RepetitionInterval(interval_ms)),
-        requirements: approximate(),
-        predictability: Predictability::Unknown,
-        time_selection: TimeSelection::default(),
-    };
-    let workload = PlanningWorkload {
-        query_workload: QueryWorkload {
-            language: QueryLanguage::PromQL,
-            query_batch: None,
-            repeating_queries: Some(vec![
-                repeating("count_over_time(up[5m])", 60_000),
-                repeating("sum_over_time(latency[5m])", 600_000),
-            ]),
-        },
-        data_workload: Some(DataWorkload {
-            arrival: DataArrival::ContinuouslyIngesting,
-            data_ingestion_interval: Evidence {
-                value: Some(DurationMs(15_000)),
-                ..Default::default()
-            },
-            ..Default::default()
-        }),
-    };
-    let input = UserInput::new(
-        &workload,
-        FrontendInput::Promql {
-            now_ms: NOW_MS,
-            histograms: None,
-        },
-        PlanningModels::builtin(),
-        lifecycle().with_horizon(Horizon(3_600.0)),
-    );
-
-    let output = e2e_plan(input).await.expect("workload plans");
-    let reads: Vec<_> = output.plans.iter().map(|p| p.plan.expected_reads).collect();
-    assert_eq!(reads, vec![Some(60.0), Some(6.0)]);
-}
-
 /// Scalar-only and mixed workloads preserve entry bindings without wrapper nodes.
 #[tokio::test]
 async fn scalar_roots_survive_planning_in_workload_order() {
@@ -465,7 +359,6 @@ async fn scalar_roots_survive_planning_in_workload_order() {
                 histograms: None,
             },
             PlanningModels::builtin(),
-            lifecycle(),
         ))
         .await
         .unwrap();
diff --git a/crates/planner/tests/summary_sharing.rs b/crates/planner/tests/summary_sharing.rs
index 7c198493b..8eb9ed4f8 100644
--- a/crates/planner/tests/summary_sharing.rs
+++ b/crates/planner/tests/summary_sharing.rs
@@ -1,5 +1,5 @@
 //! Structurally identical summary producers chosen by different queries are
-//! shared after Pass 1: one `Rc<OperatorNode>` across their plans, costed once.
+//! shared after Pass 1: one `Rc<OperatorNode>` across their plans.
 
 use asap_types::ir::cse::share_common_sub_dags;
 use asap_types::ir::{ASAPOp, OperatorNode};
@@ -8,16 +8,11 @@ use std::rc::Rc;
 use asap_aware_mapping::accuracy::{
     AccuracyModel, DefaultAccuracyModel, EqualSplitAllocator, PropagationStats,
 };
-use asap_aware_mapping::cost_model::Cost;
-use asap_aware_mapping::pass::{PlanOutput, PlanningModels};
+use asap_aware_mapping::pass::{PlanOutput, PlanningModels, QueryPlan};
 use asap_aware_mapping::replacement::{default_size_params, DEFAULT_DELTA};
 use asap_aware_mapping::{
-    global_selection_with_summary_maintenance_lifecycles, search_workload_with_targets,
-    ASAPStrategies, ReplacementStrategy, WorkloadDemand,
-};
-use asap_aware_mapping::{
-    CostModel, CostRate, DefaultCostModel, Horizon, LifecycleInput, SummaryMaintenanceCapabilities,
-    SummaryMaintenanceLifecycleCapabilities, SummaryMaintenanceLifecycleCostInputs,
+    search_workload_with_targets, ASAPStrategies, CostModel, DefaultCostModel, Replacement,
+    ReplacementStrategy, ReplacementSubDAG, TargetSubDAG,
 };
 use asap_frontend_promql::lower_promql_workload;
 use asap_frontend_sql::SqlCatalog;
@@ -26,7 +21,7 @@ use asap_types::post_asap::{
     AccuracyError, BoundExpr, CompositionOperator, ErrorMetric, ProbabilityExpr, ResultGuarantee,
     SketchStatistic,
 };
-use asap_types::post_asap::{FieldDataType, SketchAlgorithm, SketchParams};
+use asap_types::post_asap::{FieldDataType, SketchAlgorithm, SketchKind, SketchParams};
 use asap_types::pre_asap::agg_intent::default_quantile;
 use asap_types::pre_asap::schema::{DataType, Field, Schema};
 use asap_types::pre_asap::AggIntent;
@@ -38,16 +33,18 @@ use asap_types::workload::{
 };
 
 const NOW_MS: u64 = 1_700_000_000_000;
-const HORIZON_S: f64 = 3_600.0;
 
-/// A state costs `build` once however often it is read; raw recomputation
-/// costs `raw_per_read` per read.
-struct FixedCosts {
-    build: f64,
-    raw_per_read: f64,
-}
+/// Stand-in for the workload-level amortization Stage 2 materialization will
+/// price: a sketch candidate costs `preference(kind)` per sketch state, any
+/// other candidate more than every sketch. Ranking is otherwise built-in.
+struct PreferSketch(fn(&SketchKind) -> f64);
+
+impl CostModel for PreferSketch {
+    // Selection takes the cheapest candidate by `estimate_cost`.
+    fn candidate_cost_covers_complete_plan(&self) -> bool {
+        true
+    }
 
-impl CostModel for FixedCosts {
     fn rank_candidates(
         &self,
         intent: &AggIntent,
@@ -56,41 +53,42 @@ impl CostModel for FixedCosts {
         DefaultCostModel.rank_candidates(intent, candidates)
     }
 
-    fn summary_maintenance_lifecycle_cost_inputs(
-        &self,
-        _summary: &OperatorNode,
-    ) -> SummaryMaintenanceLifecycleCostInputs {
-        SummaryMaintenanceLifecycleCostInputs {
-            build_cost: Some(Cost(self.build)),
-            maintenance_cost_per_update: Some(Cost::ZERO),
-            summary_read_cost: Some(Cost::ZERO),
-            retention_cost_rate: Some(CostRate(0.0)),
-            retirement_cost: Some(Cost::ZERO),
-        }
-    }
-
-    fn summary_maintenance_capabilities(
-        &self,
-        _summary: &OperatorNode,
-    ) -> SummaryMaintenanceCapabilities {
-        SummaryMaintenanceCapabilities {
-            incremental_update: true,
-            merge: true,
-            delete: true,
+    fn estimate_cost(&self, candidate: &ReplacementSubDAG, _: &TargetSubDAG<'_>) -> f64 {
+        let Replacement::SubDAG(root) = &candidate.replacement else {
+            return 1e9;
+        };
+        let kinds: Vec<_> = OperatorNode::reachable(root)
+            .into_iter()
+            .filter_map(|node| match &node.operator {
+                asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
+                    family: FieldDataType::Sketch(kind, _),
+                    ..
+                }) => Some(kind.clone()),
+                _ => None,
+            })
+            .collect();
+        if kinds.is_empty() {
+            1e9
+        } else {
+            kinds.iter().map(self.0).sum()
         }
     }
-
-    fn raw_query_recompute_cost(&self, _target: &OperatorNode) -> Option<Cost> {
-        Some(Cost(self.raw_per_read))
-    }
 }
 
-/// Summaries are far cheaper than raw recomputation, so every query selects
-/// one independently and only sharing is under test.
-const CHEAP_SUMMARY: FixedCosts = FixedCosts {
-    build: 1.0,
-    raw_per_read: 1_000.0,
-};
+/// Prefers the largest KLL, i.e. one sized for the strictest consumer.
+const PREFER_LARGE_KLL: PreferSketch = PreferSketch(|kind| match kind.params() {
+    SketchParams::Kll { k } => 1.0 / f64::from(*k),
+    _ => 1.0,
+});
+
+/// Prefers UnivMon, which can serve every frequency moment from one state.
+const PREFER_UNIVMON: PreferSketch = PreferSketch(|kind| {
+    if kind.algorithm() == &SketchAlgorithm::UnivMon {
+        0.0
+    } else {
+        1.0
+    }
+});
 
 fn requirements(epsilon: f64) -> QueryRequirements {
     QueryRequirements {
@@ -110,11 +108,6 @@ fn repeating(query: &str, epsilon: f64) -> RepeatingEntry {
     }
 }
 
-fn lifecycle() -> LifecycleInput {
-    LifecycleInput::new(NOW_MS, SummaryMaintenanceLifecycleCapabilities::default())
-        .with_horizon(Horizon(HORIZON_S))
-}
-
 fn promql_workload(queries: &[(&str, f64)]) -> PlanningWorkload {
     PlanningWorkload {
         query_workload: QueryWorkload {
@@ -142,7 +135,11 @@ fn promql_workload(queries: &[(&str, f64)]) -> PlanningWorkload {
     }
 }
 
-async fn plan_promql(queries: &[(&str, f64)], costs: &FixedCosts) -> PlanOutput {
+async fn plan_promql(queries: &[(&str, f64)]) -> PlanOutput {
+    plan_promql_with(queries, &DefaultCostModel).await
+}
+
+async fn plan_promql_with(queries: &[(&str, f64)], cost: &dyn CostModel) -> PlanOutput {
     let workload = promql_workload(queries);
     let input = UserInput::new(
         &workload,
@@ -150,13 +147,12 @@ async fn plan_promql(queries: &[(&str, f64)], costs: &FixedCosts) -> PlanOutput
             now_ms: NOW_MS,
             histograms: None,
         },
-        PlanningModels::builtin().with_cost(costs),
-        lifecycle(),
+        PlanningModels::builtin().with_cost(cost),
     );
     e2e_plan(input).await.expect("workload plans")
 }
 
-async fn plan_sql(queries: &[&str], costs: &FixedCosts) -> PlanOutput {
+async fn plan_sql(queries: &[&str]) -> PlanOutput {
     let workload = PlanningWorkload {
         query_workload: QueryWorkload {
             language: QueryLanguage::SQL(SqlDialect::DataFusionSQL),
@@ -178,25 +174,33 @@ async fn plan_sql(queries: &[&str], costs: &FixedCosts) -> PlanOutput {
     let input = UserInput::new(
         &workload,
         FrontendInput::Sql { catalog: &catalog },
-        PlanningModels::builtin().with_cost(costs),
-        lifecycle(),
+        PlanningModels::builtin(),
     );
     e2e_plan(input).await.expect("workload plans")
 }
 
-/// Every summary state each plan deploys.
+/// Every summary state (`SummaryAgg`) each plan reaches, in traversal order.
+fn plan_states(plan: &QueryPlan) -> Vec<Rc<OperatorNode>> {
+    OperatorNode::reachable(&plan.root)
+        .into_iter()
+        .filter(|node| {
+            matches!(
+                node.operator,
+                asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg { .. })
+            )
+        })
+        .collect()
+}
+
+/// Every summary state each plan reaches; each plan selects at least one.
 fn states(output: &PlanOutput) -> Vec<Vec<Rc<OperatorNode>>> {
     output
         .plans
         .iter()
         .map(|plan| {
-            assert!(!plan.plan.selected_raw_recompute, "{:?}", plan.plan.root);
-            assert!(!plan.plan.deployments.is_empty());
-            plan.plan
-                .deployments
-                .iter()
-                .map(|deployment| Rc::clone(&deployment.summary))
-                .collect()
+            let states = plan_states(plan);
+            assert!(!states.is_empty(), "{:?}", plan.root);
+            states
         })
         .collect()
 }
@@ -210,12 +214,12 @@ fn same_states(states: &[Vec<Rc<OperatorNode>>]) -> bool {
             .all(|(left, right)| Rc::ptr_eq(left, right))
 }
 
-/// The deployments a consumer would run, deduplicated by pointer.
+/// The summary states a consumer would run, deduplicated by pointer.
 fn unique_deployments(output: &PlanOutput) -> usize {
     let mut seen: Vec<*const OperatorNode> = Vec::new();
     for plan in &output.plans {
-        for deployment in &plan.plan.deployments {
-            let ptr = Rc::as_ptr(&deployment.summary);
+        for state in plan_states(plan) {
+            let ptr = Rc::as_ptr(&state);
             if !seen.contains(&ptr) {
                 seen.push(ptr);
             }
@@ -225,39 +229,18 @@ fn unique_deployments(output: &PlanOutput) -> usize {
 }
 
 /// p50 and p99 over the same window and accuracy read one KLL: the
-/// equal-params subset of summary capability. Both plans hold the same `Rc`
-/// with the same lifecycle, so a consumer maintains it once.
+/// equal-params subset of summary capability. Both plans hold the same `Rc`,
+/// so a consumer maintains it once.
 #[tokio::test]
 async fn quantiles_with_equal_params_share_one_producer() {
-    let output = plan_promql(
-        &[
-            ("quantile_over_time(0.5, lat[5m])", 0.01),
-            ("quantile_over_time(0.99, lat[5m])", 0.01),
-        ],
-        &CHEAP_SUMMARY,
-    )
+    let output = plan_promql(&[
+        ("quantile_over_time(0.5, lat[5m])", 0.01),
+        ("quantile_over_time(0.99, lat[5m])", 0.01),
+    ])
     .await;
     assert!(same_states(&states(&output)));
-    assert!(!Rc::ptr_eq(
-        &output.plans[0].plan.root,
-        &output.plans[1].plan.root
-    ));
+    assert!(!Rc::ptr_eq(&output.plans[0].root, &output.plans[1].root));
     assert_eq!(unique_deployments(&output), 1);
-    let lifecycles: Vec<_> = output
-        .plans
-        .iter()
-        .map(|plan| {
-            plan.plan.deployments[0]
-                .summary_maintenance_lifecycle_guarantee
-                .clone()
-        })
-        .collect();
-    assert_eq!(lifecycles[0], lifecycles[1]);
-    assert!(lifecycles[0].is_some());
-    // Each plan is planned against both queries' reads.
-    for plan in &output.plans {
-        assert_eq!(plan.plan.expected_reads, Some(12.0));
-    }
 }
 
 /// A different window or label selector is a different producer, even when
@@ -282,27 +265,27 @@ async fn different_producers_are_not_shared() {
             ("quantile_over_time(0.99, lat{job=\"b\"}[5m])", 0.01),
         ],
     ] {
-        let output = plan_promql(&queries, &CHEAP_SUMMARY).await;
+        let output = plan_promql(&queries).await;
         assert!(!same_states(&states(&output)), "{queries:?}");
         assert_eq!(unique_deployments(&output), 2, "{queries:?}");
         for (plan, (_, epsilon)) in output.plans.iter().zip(queries) {
-            assert_eq!(plan.plan.expected_reads, Some(6.0), "{queries:?}");
             assert_eq!(kll_k(plan), kll_k_for(epsilon), "{queries:?}");
         }
     }
 }
 
 /// The KLL `k` of the one state a plan deploys.
-fn kll_k(plan: &asap_aware_mapping::pass::QueryLifecyclePlan) -> u32 {
-    let [deployment] = plan.plan.deployments.as_slice() else {
-        panic!("one state: {:?}", plan.plan.deployments.len());
+fn kll_k(plan: &QueryPlan) -> u32 {
+    let states = plan_states(plan);
+    let [deployment] = states.as_slice() else {
+        panic!("one state: {:?}", states.len());
     };
     let asap_types::ir::Operator::ASAP(ASAPOp::SummaryAgg {
         family: FieldDataType::Sketch(kind, _),
         ..
-    }) = &deployment.summary.operator
+    }) = &deployment.operator
     else {
-        panic!("sketch state: {:?}", deployment.summary.operator);
+        panic!("sketch state: {:?}", deployment.operator);
     };
     let SketchParams::Kll { k } = kind.params() else {
         panic!("KLL state: {kind:?}");
@@ -324,19 +307,20 @@ fn kll_k_for(epsilon: f64) -> u32 {
 }
 
 /// p50 at ε=0.01 and p99 at ε=0.001 over the same input share one KLL sized
-/// for the strictest consumer; each reader's guarantee meets its own target.
+/// for the strictest consumer when the cost model prefers that candidate; each
+/// reader's guarantee meets its own target.
 #[tokio::test]
 async fn quantiles_share_one_producer_sized_for_the_strictest_consumer() {
     let p50 = ("quantile_over_time(0.5, lat[5m])", 0.01);
     let p99 = ("quantile_over_time(0.99, lat[5m])", 0.001);
     assert!(kll_k_for(0.001) > kll_k_for(0.01));
 
-    let output = plan_promql(&[p50, p99], &CHEAP_SUMMARY).await;
+    let output = plan_promql_with(&[p50, p99], &PREFER_LARGE_KLL).await;
     assert!(same_states(&states(&output)));
     assert_eq!(unique_deployments(&output), 1);
     for (plan, (_, epsilon)) in output.plans.iter().zip([p50, p99]) {
         assert_eq!(kll_k(plan), kll_k_for(0.001));
-        let guarantee = plan.plan.root.guarantee.as_ref().expect("certified");
+        let guarantee = plan.root.guarantee.as_ref().expect("certified");
         assert!(
             guarantee.bound.evaluate().unwrap() <= epsilon,
             "{guarantee:?}"
@@ -344,7 +328,7 @@ async fn quantiles_share_one_producer_sized_for_the_strictest_consumer() {
     }
 
     // Alone, the looser query keeps its own, smaller KLL.
-    let alone = plan_promql(&[p50], &CHEAP_SUMMARY).await;
+    let alone = plan_promql_with(&[p50], &PREFER_LARGE_KLL).await;
     assert_eq!(kll_k(&alone.plans[0]), kll_k_for(0.01));
 }
 
@@ -352,11 +336,7 @@ async fn quantiles_share_one_producer_sized_for_the_strictest_consumer() {
 /// quantile, so p50 and p99 over one selector share it.
 #[tokio::test]
 async fn cross_series_p50_and_p99_share_one_producer() {
-    let output = plan_promql(
-        &[("quantile(0.5, lat)", 0.01), ("quantile(0.99, lat)", 0.01)],
-        &CHEAP_SUMMARY,
-    )
-    .await;
+    let output = plan_promql(&[("quantile(0.5, lat)", 0.01), ("quantile(0.99, lat)", 0.01)]).await;
     assert!(same_states(&states(&output)));
     assert_eq!(unique_deployments(&output), 1);
 }
@@ -366,7 +346,7 @@ async fn cross_series_p50_and_p99_share_one_producer() {
 #[tokio::test]
 async fn identical_ungrouped_queries_share_their_producers() {
     let query = ("sum(rate(x[5m]))", 0.01);
-    let output = plan_promql(&[query, query], &CHEAP_SUMMARY).await;
+    let output = plan_promql(&[query, query]).await;
     assert!(same_states(&states(&output)));
     assert_eq!(unique_deployments(&output), 2);
 }
@@ -377,7 +357,7 @@ async fn identical_ungrouped_queries_share_their_producers() {
 async fn identical_sql_percentiles_share_one_producer() {
     let query =
         "SELECT approx_percentile_cont(l_extendedprice, 0.5) FROM lineitem WHERE l_orderkey > 10";
-    let output = plan_sql(&[query, query], &CHEAP_SUMMARY).await;
+    let output = plan_sql(&[query, query]).await;
     assert!(same_states(&states(&output)));
     assert_eq!(unique_deployments(&output), 1);
 }
@@ -391,15 +371,14 @@ async fn sql_p50_and_p99_share_one_producer() {
         "SELECT approx_percentile_cont(l_extendedprice, 0.5) FROM lineitem WHERE l_orderkey > 10";
     let p99 =
         "SELECT approx_percentile_cont(l_extendedprice, 0.99) FROM lineitem WHERE l_orderkey > 10";
-    let output = plan_sql(&[p50, p99], &CHEAP_SUMMARY).await;
+    let output = plan_sql(&[p50, p99]).await;
     assert!(same_states(&states(&output)));
     assert_eq!(unique_deployments(&output), 1);
     let names: Vec<_> = output
         .plans
         .iter()
         .map(|plan| {
-            plan.plan
-                .root
+            plan.root
                 .schema
                 .fields
                 .iter()
@@ -425,32 +404,12 @@ async fn sql_p50_and_p99_share_one_producer() {
             "SELECT approx_percentile_cont(l_orderkey, 0.99) FROM lineitem WHERE l_orderkey > 10",
         ],
     ] {
-        let output = plan_sql(&queries, &CHEAP_SUMMARY).await;
+        let output = plan_sql(&queries).await;
         assert!(!same_states(&states(&output)), "{queries:?}");
         assert_eq!(unique_deployments(&output), 2, "{queries:?}");
     }
 }
 
-/// A state costs 100 and recomputing a query costs 60 over its six reads:
-/// alone, the query recomputes raw. Shared by p50 and p99, the state costs 50
-/// per query, so both keep it.
-#[tokio::test]
-async fn shared_amortization_alone_can_beat_raw_recompute() {
-    let costs = FixedCosts {
-        build: 100.0,
-        raw_per_read: 10.0,
-    };
-    let p50 = ("quantile_over_time(0.5, lat[5m])", 0.01);
-    let p99 = ("quantile_over_time(0.99, lat[5m])", 0.01);
-
-    let alone = plan_promql(&[p50], &costs).await;
-    assert!(alone.plans[0].plan.selected_raw_recompute);
-
-    let output = plan_promql(&[p50, p99], &costs).await;
-    assert!(same_states(&states(&output)));
-    assert_eq!(unique_deployments(&output), 1);
-}
-
 /// Synthetic evidence certifying UnivMon evaluations; it exercises sharing, never
 /// runtime accuracy.
 struct UnivMonEvidence;
@@ -489,7 +448,7 @@ impl AccuracyModel for UnivMonEvidence {
 }
 
 /// Distinct count, entropy and L2 over one input, certified by an accuracy
-/// model, read one UnivMon state: #515 sharing is the summary-capability rule
+/// model and selected by a cost model preferring UnivMon, read one UnivMon state: #515 sharing is the summary-capability rule
 /// when the states are identical. `MajorPass` builds candidates with the
 /// built-in accuracy model, so this runs its pipeline with the test model.
 #[test]
@@ -509,25 +468,12 @@ fn certified_frequency_evaluations_share_one_univmon_state() {
         .collect();
     let strategies: Vec<Box<dyn ReplacementStrategy>> =
         vec![Box::new(ASAPStrategies::new_with_planning_inputs(
-            &CHEAP_SUMMARY,
+            &PREFER_UNIVMON,
             &UnivMonEvidence,
             &EqualSplitAllocator,
         ))];
     let space = search_workload_with_targets(roots, &strategies, &UnivMonEvidence);
-    let entry_indices: Vec<usize> = (0..queries.len()).collect();
-    let selection = global_selection_with_summary_maintenance_lifecycles(
-        &space,
-        WorkloadDemand {
-            workload: &workload.query_workload,
-            data_workload: workload.data_workload.as_ref(),
-            entry_indices: &entry_indices,
-        },
-        NOW_MS,
-        Some(Horizon(HORIZON_S)),
-        SummaryMaintenanceLifecycleCapabilities::default(),
-        &CHEAP_SUMMARY,
-    )
-    .expect("selects");
+    let selection = space.global_selection(&PREFER_UNIVMON);
     let assembled = space
         .roots
         .iter()
diff --git a/crates/types/src/post_asap/mod.rs b/crates/types/src/post_asap/mod.rs
index e282fccad..04e3264c2 100644
--- a/crates/types/src/post_asap/mod.rs
+++ b/crates/types/src/post_asap/mod.rs
@@ -20,7 +20,7 @@
 //! sketch-valued edge types.
 //!
 //! The rest: accuracy guarantees ([`guarantee`]), maintained populations,
-//! summary windows and maintenance lifecycle, and the execution timing /
+//! summary-window panes, and the execution timing /
 //! data-state vocabulary ([`execution_data_state`]).
 
 pub mod execution_data_state;
@@ -28,8 +28,6 @@ pub mod guarantee;
 pub mod maintained_population;
 pub mod query_time;
 pub mod sketch;
-pub mod summary_maintenance;
-pub mod summary_maintenance_lifecycle;
 pub mod summary_window;
 
 pub use crate::pre_asap::schema::{Field, FieldDataType, Schema};
@@ -51,12 +49,6 @@ pub use sketch::{
     SketchCategory, SketchKind, SketchParams, SketchStatistic, StatModelKind, StatModelParams,
     SummaryInputExpr, SummaryUpdate, WaveletKind, WaveletParams, WeightDomain,
 };
-pub use summary_maintenance::SummaryMaintenanceMode;
-pub use summary_maintenance_lifecycle::{
-    EvaluationSchedule, OutputRepresentation, SummaryMaintenanceLifecycle,
-    SummaryMaintenanceLifecycleGuarantee,
-};
 pub use summary_window::{
-    plan_pane_phase, validate_pane_coverage, PaneCoverageError, PaneLayout, SummaryWindowFramework,
-    WindowEdgeCoverage,
+    plan_pane_phase, validate_pane_coverage, PaneCoverageError, PaneLayout, WindowEdgeCoverage,
 };
diff --git a/crates/types/src/post_asap/summary_maintenance.rs b/crates/types/src/post_asap/summary_maintenance.rs
deleted file mode 100644
index 4e7eaf205..000000000
--- a/crates/types/src/post_asap/summary_maintenance.rs
+++ /dev/null
@@ -1,38 +0,0 @@
-//! Planner-level construction mode for a materialized summary.
-//!
-//! An ASAP [`crate::ir::OperatorNode`] is a logical summary expression and deliberately
-//! does not carry this choice: the same candidate may be built directly for
-//! one workload or maintained incrementally for another. Planner search
-//! attaches the selected mode to its lifecycle guarantee; downstream physical
-//! compilation chooses its concrete implementation.
-
-/// How a summary deployment obtains its state, independent of implementation.
-#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash, serde::Serialize, serde::Deserialize)]
-#[serde(rename_all = "snake_case")]
-pub enum SummaryMaintenanceMode {
-    /// Rebuild the summary from its complete input when the deployment needs
-    /// a value. No update stream is required.
-    DirectBuild,
-    /// Create the state once and apply input changes as they arrive.
-    Incremental,
-}
-
-impl SummaryMaintenanceMode {
-    pub const fn as_str(self) -> &'static str {
-        match self {
-            Self::DirectBuild => "direct_build",
-            Self::Incremental => "incremental",
-        }
-    }
-}
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-
-    #[test]
-    fn maintenance_modes_have_stable_export_names() {
-        assert_eq!(SummaryMaintenanceMode::DirectBuild.as_str(), "direct_build");
-        assert_eq!(SummaryMaintenanceMode::Incremental.as_str(), "incremental");
-    }
-}
diff --git a/crates/types/src/post_asap/summary_maintenance_lifecycle.rs b/crates/types/src/post_asap/summary_maintenance_lifecycle.rs
deleted file mode 100644
index 798d861f6..000000000
--- a/crates/types/src/post_asap/summary_maintenance_lifecycle.rs
+++ /dev/null
@@ -1,74 +0,0 @@
-//! Planner-level summary-maintenance lifecycle vocabulary.
-//!
-//! A **summary-maintenance lifecycle** describes when one materialized summary
-//! state is created, retained or shared, updated, and retired. It does not
-//! describe the broader data lifecycle (collection, transport, and storage),
-//! and it is not implied by a logical `SummaryAgg`. Physical planning compares
-//! alternatives using the expected number and timing of reads, the source-data
-//! arrival/update rate, state-operation costs, and runtime capabilities.
-
-use super::SummaryMaintenanceMode;
-use crate::workload::{DurationMs, TimestampMs};
-
-/// When an operator is evaluated. This is independent of whether it owns
-/// state and how long that state is retained.
-#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash, serde::Serialize, serde::Deserialize)]
-#[serde(rename_all = "snake_case")]
-pub enum EvaluationSchedule {
-    OneShot,
-    PerUpdate,
-    OnRead,
-}
-
-/// The form in which this deployment exposes its result to its consumer. The
-/// consumer is the next operator in the execution plan that reads the
-/// summary's output; for example, `Estimate` is the consumer in
-/// `SummaryAgg -> Estimate`. The exposed result is ordinary rows, reusable
-/// summary state, or a finalized value.
-#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash, serde::Serialize, serde::Deserialize)]
-#[serde(rename_all = "snake_case")]
-pub enum OutputRepresentation {
-    PlainRows,
-    SummaryState,
-    FinalizedValue,
-}
-
-/// Abstract policy for when one materialized summary state is created,
-/// retained or shared, updated as data arrives, and retired.
-///
-/// This is not the lifecycle of the source data or query. Query recurrence
-/// provides the expected number and timing of reads; data arrival provides the
-/// expected state-update demand. The planner combines those quantities with
-/// costs and runtime capabilities to compare these policies.
-#[derive(Debug, Clone, PartialEq, Eq, Hash, serde::Serialize, serde::Deserialize)]
-#[serde(tag = "kind", rename_all = "snake_case")]
-pub enum SummaryMaintenanceLifecycle {
-    Ephemeral,
-    Prepared {
-        #[serde(rename = "activate_at_ms")]
-        activate_at: TimestampMs,
-        #[serde(rename = "retire_at_ms")]
-        retire_at: TimestampMs,
-    },
-    Shared {
-        #[serde(rename = "retention_ms")]
-        retention: DurationMs,
-    },
-    ContinuouslyMaintained,
-}
-
-/// The lifecycle commitment emitted for one materialized summary deployment.
-///
-/// This names the summary-maintenance promise explicitly so consumers do not
-/// confuse it with guarantees about the broader data lifecycle. Accuracy is a
-/// separate [`super::ResultGuarantee`].
-#[derive(Debug, Clone, PartialEq, Eq, Hash, serde::Serialize, serde::Deserialize)]
-#[serde(deny_unknown_fields)]
-pub struct SummaryMaintenanceLifecycleGuarantee {
-    #[serde(rename = "lifecycle")]
-    pub summary_maintenance_lifecycle: SummaryMaintenanceLifecycle,
-    #[serde(rename = "maintenance_mode")]
-    pub summary_maintenance_mode: SummaryMaintenanceMode,
-    pub evaluation_schedule: EvaluationSchedule,
-    pub output_representation: OutputRepresentation,
-}
diff --git a/crates/types/src/post_asap/summary_window.rs b/crates/types/src/post_asap/summary_window.rs
index 6d45649b4..724a8d595 100644
--- a/crates/types/src/post_asap/summary_window.rs
+++ b/crates/types/src/post_asap/summary_window.rs
@@ -1,29 +1,13 @@
-//! Planner-level summary-window primitives.
+//! Planner-level summary-window pane primitives.
 //!
-//! These values identify the abstract window framework selected during
-//! candidate search. They do not identify a runtime library, process,
-//! placement, shard layout, storage backend, or deployment instance; those
-//! choices belong to downstream physical compilation.
+//! These values describe pane layout and window-edge coverage. They do not
+//! identify a runtime library, process, placement, shard layout, storage
+//! backend, or deployment instance; those choices belong to downstream
+//! physical compilation.
 
 use crate::workload::RepeatedDemand;
 use serde::{Deserialize, Serialize};
 
-/// Abstract framework used to organize incrementally maintained summary
-/// state over time.
-///
-/// The built-in variants name semantics that the planner can compare across
-/// implementations with defined planning and accuracy behavior.
-#[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord, Serialize, Deserialize)]
-#[serde(rename_all = "snake_case")]
-pub enum SummaryWindowFramework {
-    /// Disjoint, fixed-width windows.
-    Tumbling,
-    /// Overlapping logical windows, commonly realized from reusable panes.
-    Sliding,
-    /// Hierarchical buckets with exponentially increasing coverage.
-    ExponentialHistogram,
-}
-
 /// Concrete pane phase recorded in a catalog layout or inventory snapshot.
 /// Milliseconds are canonical throughout the shared contract.
 #[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
@@ -122,30 +106,6 @@ pub fn plan_pane_phase(
 mod tests {
     use super::*;
 
-    #[test]
-    fn built_in_frameworks_round_trip() {
-        for framework in [
-            SummaryWindowFramework::Tumbling,
-            SummaryWindowFramework::Sliding,
-            SummaryWindowFramework::ExponentialHistogram,
-        ] {
-            let encoded = serde_json::to_string(&framework).unwrap();
-            assert_eq!(
-                serde_json::from_str::<SummaryWindowFramework>(&encoded).unwrap(),
-                framework
-            );
-        }
-    }
-
-    /// Opaque names cannot enter planning without defined window semantics.
-    #[test]
-    fn unimplemented_window_extensions_are_rejected() {
-        assert!(serde_json::from_value::<SummaryWindowFramework>(
-            serde_json::json!({"extension": "learned_window"})
-        )
-        .is_err());
-    }
-
     #[test]
     fn pane_only_evaluation_rejects_source_and_query_phase_mismatch() {
         let layout = PaneLayout {
diff --git a/docs/design_docs/proposals/asap-aware-mapping/workload-demand-and-summary-lifecycle.md b/docs/design_docs/proposals/asap-aware-mapping/workload-demand-and-summary-lifecycle.md
deleted file mode 100644
index 483e04503..000000000
--- a/docs/design_docs/proposals/asap-aware-mapping/workload-demand-and-summary-lifecycle.md
+++ /dev/null
@@ -1,758 +0,0 @@
-# Design: Query Workloads, Data Workloads, and Summary Lifecycle Maintenance
-
-> Status: partially implemented design. Workload types and
-> [lifecycle planning APIs](../../../../crates/asap-aware-mapping/src/summary_maintenance_lifecycle.rs)
-> implement the bounded planning path described below. The current-support and
-> future-work sections distinguish available behavior from broader search,
-> forecast integration and runtime deployment work.
-
-## Audience and context
-
-This document is for ASAPPlanner designers, architects, researchers, and
-developers working on workload-aware plan selection. It defines how the
-planner should describe query workload, data workload, and the lifecycle of
-summary state. It is a design contract, not a description of the current
-public Rust API.
-
-The terminology follows the ProjectASAP
-[glossary](https://github.com/ProjectASAP/internal-docs/blob/03e1c70f5af3ae9221471898541067eee7f86338/glossary.md).
-That glossary is authoritative for the meanings of data workload, query
-workload, ad-hoc and predictable queries, one-time and repeated queries,
-real-time and longitudinal queries, output cardinality, and lookback window.
-This document maps those concepts into planner responsibilities and records
-where the current model is incomplete.
-
-This design is orthogonal to
-[end-to-end accuracy guarantees](end-to-end-accuracy-guarantees.md). Accuracy
-decides whether a candidate is correct enough. Workload demand and state
-lifecycle decide whether building, maintaining, sharing, or recomputing that
-candidate is worthwhile. Neither decision may override the other.
-
-## Problem and why now
-
-A summary operator does not imply one execution lifecycle. The same exact or
-approximate summary can be:
-
-- built once from data at rest and discarded after one query;
-- prepared before a known future query and retired afterward;
-- shared across a bounded set of requests; or
-- maintained incrementally as data continues to arrive.
-
-Likewise, an exact stateless operator may run once over a batch, once per
-update in an incremental pipeline, or once per readout. Operator statefulness,
-execution schedule, and output representation are separate properties.
-
-The query expression alone cannot determine those properties. The same query
-may arrive unexpectedly during exploration, run once at a scheduled time, or
-repeat every ten seconds on a dashboard. Planning summary state from syntax
-alone either misses reuse or invents reuse that the workload does not justify.
-
-The current `PlanningWorkload` separates query demand from data arrival.
-Query entries include predictability, recurrence or invocation count, accuracy,
-and time selection; `DataWorkload` contains arrival and empirical facts.
-These fields do not themselves select a summary-maintenance lifecycle.
-The [input/output/workflow design](../../architecture/input-output-workflow.md)
-is authoritative for current fields, defaults, and public call sequences.
-
-## Inputs, outputs, and end-to-end behavior
-
-For the broader lifecycle design, four categories of information matter
-(these are not four current top-level Rust fields):
-
-1. logical queries, which define query semantics;
-2. query workload, including per-query accuracy and latency requirements,
-   predictability, recurrence, and queried time scope;
-3. data-workload characteristics, including arrival, volume, cardinality, and
-   distribution;
-4. existing summaries and the lifecycle actions available to the deployment.
-
-Candidate search outputs `CandidateLogicalASAPDAGs`. The implemented lifecycle-aware workflow
-then returns a `SummaryMaintenanceLifecyclePlan` per query root, containing the
-Post-ASAP DAG and maintenance decisions. It can choose exact raw recomputation
-when summary maintenance does not beat raw cost or comparable costs are missing. A
-state deployment states whether a summary is ephemeral, prepared, shared for a
-bounded period, or continuously maintained. It retains costs, assumptions, and
-structured rejection reasons. Exporting full input provenance remains a later
-integration.
-
-```text
-            logical queries ---+
-           query workload -----+
-              data workload ---+--> candidate plans
-        available summaries ---+       -> semantic and accuracy legality
-                                         -> lifecycle alternatives
-                                         -> horizon-normalized cost
-                                         -> selected plan + deployments
-```
-
-For an unpredictable one-time query, the planner may read an existing summary,
-build an ephemeral summary, or recompute from raw data. It must not assume
-future reuse. For a predictable one-time query, it may additionally compare
-preparing state in advance with building or recomputing at execution time. For
-repeated queries, it may amortize build and maintenance cost across reads over
-an explicit horizon.
-
-### End-to-end decision order
-
-```text
-normalize query and data workloads
-    -> derive recurrence, time-scope, and data evidence
-    -> enumerate semantic plan alternatives
-    -> enumerate legal execution contracts and state lifecycles
-    -> validate summary capabilities and phase constraints
-    -> derive and check accuracy guarantees
-    -> normalize one-time and rate costs over an explicit horizon
-    -> rank legal alternatives and compare the selected summary deployment
-       with raw recomputation
-    -> emit plan, deployments, assumptions, and rejected alternatives
-```
-
-## Goals and non-goals
-
-### Goals
-
-- Represent glossary-defined query-workload and data-workload concepts without
-  collapsing independent axes into one enum.
-- Separate an operator's statefulness from its execution schedule and the
-  lifecycle of the state it produces.
-- Make unknown demand explicit and fail closed rather than treating it as zero
-  or infinite reuse.
-- Compare one-time and rate-valued costs only through an explicit horizon.
-- Explain why a selected plan builds, reuses, maintains, or avoids summary
-  state.
-- Preserve a minimal path from the current batch/repeating workload and
-  recurrence profile to the proposed model.
-
-### Non-goals
-
-- Scheduling jobs, assigning machines, admission control, or executing queries.
-- Predicting future query text inside ASAPPlanner.
-- Defining a sketch runtime or state-storage protocol.
-- Choosing a concrete forecasting algorithm for uncertain demand.
-- Changing accuracy targets or guarantee algebra.
-
-## Heilmeier questions
-
-- **What are we trying to do?** Choose whether summary state should be built,
-  maintained, shared, reused, or avoided for different query workloads
-  and data workload.
-- **How is it done today, and what are the limits?** The planner distinguishes
-  one-shot counts, fixed repeating intervals, and an ingest-rate proxy. It
-  cannot distinguish an unexpected exploratory query from a scheduled one-time
-  report, or data at rest from continuous ingestion as an explicit mode.
-- **What is new, and why will it succeed?** Orthogonal workload axes and an
-  explicit state lifecycle let the existing recurrence formulas compare the
-  same summary under different deployment choices without changing query
-  semantics.
-- **Who cares?** Users need predictable latency and cost; operators need to
-  know what state will exist and for how long; planner developers need demand
-  assumptions to be auditable.
-- **What are the risks and costs?** More inputs can make planning harder to
-  configure, forecasts may be stale, and a large lifecycle search space can
-  increase planning cost.
-- **What are the checks for success?** The acceptance cases below must produce
-  different lifecycle alternatives and cost terms for identical query syntax
-  under different workload contracts.
-
-## Proposed design
-
-### Authoritative concepts and ownership
-
-| Concept | Authoritative layer | Reason |
-| --- | --- | --- |
-| Query meaning | Pre-ASAP query IR | Workload metadata must not change semantics |
-| Accuracy requirement | Query workload (per-query) | The required result fidelity may be explicit or supplied by the normalization default |
-| Response-latency requirement | Query workload (per-query) | The optional end-to-end response-time bound belongs to one query execution |
-| Query workload | Workload input | Arrival and recurrence are not inferable from syntax |
-| Data workload | Workload input | Ingestion and distribution describe the data, not query workload |
-| Summary capability | Summary properties | Merge, delete, and update support constrain legal lifecycles |
-| State lifecycle | Physical planning decision | Lifecycle is selected, not declared by `SummaryAgg` |
-| Cost | Cost model and explanation | Cost consumes all inputs but does not define their meaning |
-
-### Query workload
-
-Accuracy and latency are separate per-query requirements within the query
-workload. They constrain different planner decisions and must not be collapsed
-into one SLA value:
-
-```rust
-enum AccuracyRequirement {
-    /// The caller supplied the required result fidelity.
-    Explicit(AccuracyTarget),
-    /// The source omitted accuracy; normalization applies the exact default.
-    ImplicitExact,
-}
-
-enum LatencyRequirement {
-    /// Maximum permitted end-to-end latency for one query execution.
-    ExplicitMax(Duration),
-    /// The caller supplied no latency bound.
-    Unspecified,
-}
-
-struct QueryRequirements {
-    accuracy: AccuracyRequirement,
-    response_latency: LatencyRequirement,
-}
-```
-
-An omitted accuracy field is not an unknown accuracy target and does not permit
-arbitrary approximation: the current normalization policy makes it
-`ImplicitExact`. Keeping that variant distinct from `Explicit(Exact)` preserves
-whether the caller chose exactness or inherited the default. An unspecified
-response-latency requirement imposes no response-time constraint; it is not a
-zero-duration bound or evidence that every latency is acceptable. Accuracy is
-checked as a legality constraint. The normalized model preserves response
-latency, but the current planner does not yet reject plans against that bound.
-
-#### Classification axes
-
-The glossary classifications must be modeled independently.
-
-##### Predictability
-
-```rust
-enum Predictability {
-    /// The query shape is not known before arrival.
-    AdHoc,
-    /// The query or parameterized template is known before execution.
-    Predictable {
-        known_at: Option<Timestamp>,
-    },
-    /// The caller supplied no reliable classification.
-    Unknown,
-}
-```
-
-`AdHoc` does not mean repeated or one-time. It means the query shape was not
-known in advance. The glossary currently places exploratory/ad-hoc queries in
-the one-time category, so the MVP should accept `AdHoc + OneTime` and reserve
-other combinations until a concrete use case establishes their semantics.
-
-##### Recurrence
-
-```rust
-enum QueryRecurrence {
-    OneTime {
-        invocations: u64,
-        execute_at: Option<Timestamp>,
-    },
-    Repeated {
-        demand: RepeatedDemand,
-    },
-    Unknown,
-}
-
-enum RepeatedDemand {
-    FixedInterval(Duration),
-    Scheduled(Vec<Timestamp>),
-    EstimatedRate(DemandEstimate),
-}
-
-struct DemandEstimate {
-    /// Time range over which the demand was measured or forecast.
-    observation_window: ObservationWindow,
-    /// Expected demand, expressed in exactly one form.
-    expected: ExpectedDemand,
-    /// Highest expected invocation rate within the observation window.
-    peak_rate: Option<Rate>,
-    /// Highest expected number of simultaneously executing invocations.
-    max_concurrency: Option<u64>,
-    /// Confidence in this estimate, in the inclusive range [0.0, 1.0].
-    confidence: Confidence,
-    source: EvidenceSource,
-    observed_at: Option<Timestamp>,
-    valid_for: Option<Duration>,
-}
-
-enum ExpectedDemand {
-    /// Expected total invocations over `observation_window`.
-    InvocationCount(u64),
-    /// Expected average invocations per second over `observation_window`.
-    AverageRate(Rate),
-}
-
-struct ObservationWindow {
-    start: Timestamp,
-    end: Timestamp,
-}
-
-struct Confidence(f64);
-```
-
-One-time means no recurrence is expected for that workload entry. Several
-one-time consumers may still share a subplan within a submitted workload.
-Repeated means the same query expression over its selected data is evaluated
-over time, matching the glossary. Parameterized templates require an explicit
-equivalence policy before their executions count as the same query.
-
-Query-workload volume is more than an average rate. Cost and latency can differ
-for the same total request count when requests arrive in bursts or concurrently.
-`ExpectedDemand` makes invocation count and average rate alternative
-representations, preventing conflicting values in one estimate. The observation
-window must be non-empty, rates must be finite and non-negative, and
-`Confidence` must be between zero and one. Fixed intervals and explicit
-schedules are declarations rather than estimates and do not need fabricated
-confidence. The MVP may cost only invocation count and evaluation rate, but it
-must preserve unsupported volume characteristics for explanation rather than
-silently discarding them.
-
-##### Queried time scope
-
-```rust
-enum QueryTimeScope {
-    RealTime,
-    Longitudinal,
-    Mixed,
-    Unknown,
-}
-```
-
-`QueryTimeScope` is not a response-latency requirement. It classifies the event
-time of the data selected by the query; `LatencyRequirement` constrains the
-wall-clock time allowed to produce the result. They are independent: a
-longitudinal query over archived data may require a 100 ms response, while a
-real-time query over the latest data may permit a 30 second response.
-
-This classification is not derived only from a numeric lookback. A five-minute
-lookback over recent data is real-time; the same duration over archived data is
-not. Planning input should therefore carry the classification and the concrete
-time selection separately:
-
-```rust
-struct TimeSelection {
-    scope: QueryTimeScope,
-    lookback: Option<Duration>,
-    as_of: Option<Timestamp>,
-}
-```
-
-For example, the same five-minute lookback has a different scope depending on
-whether it is anchored at the current planning time or at a historical time:
-
-```rust
-// The last five minutes: real-time.
-TimeSelection {
-    scope: QueryTimeScope::RealTime,
-    lookback: Some(Duration::minutes(5)),
-    as_of: None,
-}
-
-// A five-minute interval from archived data: longitudinal.
-TimeSelection {
-    scope: QueryTimeScope::Longitudinal,
-    lookback: Some(Duration::minutes(5)),
-    as_of: Some(timestamp!("2024-01-01T12:05:00Z")),
-}
-```
-
-`lookback` is a query property already represented by temporal query nodes in
-some frontends. The normalized workload should reference or derive it rather
-than introduce a second conflicting value.
-
-### Data workload is separate from query workload
-
-```rust
-enum DataArrival {
-    AtRest,
-    ContinuouslyIngesting,
-    Mixed,
-    Unknown,
-}
-
-/// Statistical distribution of keys in the input data.
-enum DataDistribution {
-    /// A small number of keys account for most observations.
-    Zipf,
-    /// Keys are approximately equally likely.
-    Uniform,
-    /// Observations arrive in bursts with a temporarily concentrated key set.
-    Bursty,
-}
-
-struct DataWorkload {
-    arrival: DataArrival,
-    ingestion_volume: Evidence<u64>,
-    ingestion_rate: Evidence<Rate>,
-    input_cardinality: Evidence<u64>,
-    distribution: Evidence<DataDistribution>,
-}
-```
-
-`DataDistribution` reuses the existing ASAPPlanner classification. It describes
-the key-frequency shape used by summary accuracy and cost models, not whether
-data arrives continuously. An unavailable or unsupported distribution is
-represented by `Evidence.value = None` rather than by assuming the default
-distribution.
-
-The former `DataCharacteristics` was a stale, continuous-ingestion-specific
-case built around series count and samples per second. `DataWorkload` replaces
-it as the normalized input rather than embedding that special case in the
-general model. Data at rest may have row count and scan statistics without a
-nonzero ingestion rate. Unknown arrival must not be interpreted as continuously
-ingesting or at rest.
-
-Every empirical value uses an evidence wrapper conceptually containing:
-
-```rust
-struct Evidence<T> {
-    value: Option<T>,
-    source: EvidenceSource,
-    observed_at: Option<Timestamp>,
-    valid_for: Option<Duration>,
-}
-```
-
-This reuses the provenance and freshness principles from empirical summary
-parameter configuration. Missing, stale, or future-dated evidence remains
-unknown.
-
-### Output cardinality is a derived or evidenced cost input
-
-Output cardinality depends on input cardinality and grouping columns. The
-planner may derive it analytically, accept a catalog estimate, or leave it
-unknown. The source and freshness metadata must be preserved because output
-cardinality affects summary size, read cost, post-processing cost, and network
-cost. It is not a query correctness requirement.
-
-### Separate operator state, schedule, and output
-
-The physical design must not use `SummaryAgg` as shorthand for incremental
-maintenance.
-
-```rust
-enum OperatorState {
-    Stateless,
-    Stateful {
-        mergeable: bool,
-        deletable: bool,
-    },
-}
-
-enum EvaluationSchedule {
-    OneShot,
-    PerUpdate,
-    OnRead,
-}
-
-enum OutputRepresentation {
-    PlainRows,
-    SummaryState,
-    FinalizedValue,
-}
-```
-
-A one-shot sketch builder is stateful while it consumes its input, but it does
-not imply long-lived incremental maintenance. A stateless transform can run
-`PerUpdate` before a downstream maintained summary. These types describe an
-execution contract; they do not replace semantic operators in the post-ASAP IR.
-
-### State lifecycle is a plan alternative
-
-```rust
-enum StateLifecycle {
-    Ephemeral,
-    Prepared {
-        activate_at: Timestamp,
-        retire_at: Timestamp,
-    },
-    Shared {
-        retention: Duration,
-    },
-    ContinuouslyMaintained,
-}
-```
-
-- `Ephemeral` builds state for one submitted workload and discards it afterward.
-- `Prepared` builds or begins maintaining state before a predictable query and
-  retires it after the known need ends.
-- `Shared` retains state for multiple consumers over a bounded lifetime.
-- `ContinuouslyMaintained` applies data updates until an explicit later
-  deployment decision retires the state.
-
-The summary family and its properties constrain which lifecycles are legal.
-For example, an append-only sketch may support continuous inserts but not a
-sliding-window lifecycle requiring deletion. Lifecycle legality is checked
-before cost ranking, like accuracy legality. Deployments provide these
-per-summary properties through `summary_lifecycle_capabilities`; moving
-real-time windows require deletion support as well as incremental updates.
-
-### Existing summaries are planning input
-
-An ad-hoc query cannot justify creating permanent state from unknown future
-demand, but it may use compatible state that already exists. The planning
-problem therefore needs a state catalog describing identity, parameters,
-coverage, freshness, accuracy guarantee, lifecycle, and ownership. Catalog
-integration is a separate implementation increment; this design only requires
-that "reuse existing" and "create new" remain distinguishable alternatives.
-
-### Cost over a horizon
-
-`H` is the optimization horizon: the future wall-clock duration over which the
-planner compares one-time and recurring costs. The existing cost model
-represents it in seconds:
-
-```rust
-/// A finite, strictly positive optimization duration, in seconds.
-struct Horizon(f64);
-```
-
-The horizon is not the query lookback, the queried time scope, or the response
-latency bound. It answers only "over how much future execution time should
-these alternatives be costed?" All alternatives in one decision must use the
-same `H`. `reads(H)` is the number of query evaluations expected or scheduled
-within that horizon; for a fixed evaluation rate it is
-`H * evaluation_rate`, plus any separately modeled one-time invocations.
-Who supplies `H`, and whether a deployment may default it, remains an explicit
-architecture decision below. If no horizon is available, the planner must not
-compare a one-time cost with a rate-valued cost.
-
-For a stateful incremental alternative over horizon `H`:
-
-```text
-total(H) = build_cost
-         + H * update_rate * maintenance_cost_per_update
-         + reads(H) * summary_read_cost
-         + H * retention_cost_rate
-         + retirement_cost
-```
-
-For repeated raw recomputation:
-
-```text
-total(H) = reads(H) * raw_recompute_cost
-```
-
-The current lifecycle-aware materialization sums the selected summary
-deployments and can replace that plan with raw recomputation when the raw cost
-is lower or the summary lifecycle is uncostable. Jointly reconsidering every
-sibling semantic candidate under lifecycle costs remains a later optimizer
-integration; this document does not claim that broader search is implemented.
-
-For an ephemeral summary:
-
-```text
-total = invocations * (build_cost + summary_read_cost + retirement_cost)
-```
-
-`retirement_cost` consistently means the one-time cost of ending a summary
-state lifecycle, including deallocation or other cleanup. For ephemeral state,
-retirement happens immediately after each invocation; for prepared, shared, or
-continuously maintained state, it happens when that deployment is retired.
-
-For prepared state, update and retention terms apply only between activation
-and retirement. Existing state does not pay a new build cost, but its catalog
-provenance must establish that assumption.
-
-The existing `Cost`, `CostRate`, `EvaluationRate`, `UpdateRate`, `Horizon`, and
-`total_cost` types are the minimum viable foundation. The implementation should
-extend their explanations and lifecycle coverage instead of creating a second
-recurrence cost system.
-
-### Unknown and uncertain demand
-
-Unknown demand is not zero demand and is not evidence of future reuse. The MVP
-policy is:
-
-- do not select newly created long-lived state solely on unknown future reuse;
-- allow raw recomputation, ephemeral build, and reuse of already available
-  compatible state;
-- retain an explicit explanation of the missing demand evidence; and
-- require an explicit planning objective before using an estimated demand
-  distribution.
-
-Future uncertain-demand support may add expected-cost, percentile-cost,
-worst-case, or regret objectives. Those policies must consume a typed estimate
-with confidence and provenance; they are not implicit behavior of
-`Predictability::Unknown`.
-
-## Review against the ProjectASAP glossary
-
-The glossary review found the following required coverage and current gaps.
-
-| Glossary concept | Current ASAPPlanner representation | Missing design support |
-| --- | --- | --- |
-| Data at rest vs continuously ingesting | `DataArrival` is explicit | Runtime/catalog-specific arrival discovery remains external |
-| Ingestion volume | `DataWorkload::ingestion_volume` carries evidence | A concrete time basis for volume remains deployment-specific |
-| Ingestion rate | Evidenced independently from query evaluation rate | Preserve richer unit/provenance metadata when integrations require it |
-| Input cardinality | Evidenced workload-level cardinality feeds accuracy | Per-dataset/metric/column scoping remains future work |
-| Data distribution | Evidenced built-in enum | Permit deployment-specific distributions later |
-| Ad-hoc vs predictable | `Predictability` is independent from recurrence | Parameterized-template equivalence remains open |
-| One-time vs repeated | One-time, fixed, scheduled, estimated, and unknown recurrence | Forecast-policy integration remains future work |
-| Query volume and characteristics | Estimates preserve average/count, peak, concurrency, confidence, and freshness | Peak and concurrency are not yet consumed by cost or latency models |
-| Real-time vs longitudinal | `TimeSelection` carries scope, lookback, and `as_of` | Conflict policy with temporal IR remains open |
-| Output cardinality | May be inferred locally; no common evidenced input | Add derived/evidenced value and provenance for costing |
-| Lookback window | Represented in temporal query shapes/frontends | Establish query IR as authority and expose it to workload costing |
-| CTSA pipeline | Not explicitly modeled | Keep as architectural context; planner consumes collect/store/analyze facts but does not model transmission topology in the MVP |
-| CSP(F) | Cost and fidelity partly modeled | Treat scale/performance/fidelity as objectives and constraints; do not collapse fidelity into cost |
-
-Two terminology constraints apply:
-
-1. A repeated query is not inherently a streaming-data workload. It may
-   repeatedly query data at rest.
-2. A one-time query is not inherently stateless. A predictable one-time query
-   may justify prepared state, while an ephemeral summary is stateful during
-   its one execution.
-
-## Minimal complexity
-
-The minimum input model is determined by the downstream applications selected
-for integration, not by a context-free notion of the fewest possible fields.
-Each supported use case must contribute the workload facts that can change
-plan legality, accuracy, lifecycle, or cost:
-
-- Time-series metric queries require queried time scope and lookback.
-- Repeated dashboard queries, including an ASAPQuery integration, require
-  recurrence and evaluation frequency so the planner can cost reuse and
-  maintenance across executions.
-- Batch queries over data at rest require an explicit at-rest arrival mode and
-  must not be assigned a fabricated ingestion rate.
-- Summary techniques whose accuracy depends on the input distribution require
-  evidenced distribution characteristics; omitting them must produce unknown
-  accuracy or a conservative fallback rather than a favorable assumption.
-
-The initial implementation should include the union of fields required by its
-committed integrations. Additional workload dimensions should be added when a
-new downstream use case demonstrates that they affect a planning decision.
-
-The simplest alternative is to extend `BatchEntry` with optional schedule and
-classification fields and extend `RepeatingEntry` with time scope. That is a
-reasonable serialization migration, but it is not a sufficient conceptual
-model: it continues to make predictability and recurrence mutually exclusive
-container choices, and it has no place for data arrival or state lifecycle.
-
-The minimum new conceptual layers are therefore:
-
-1. orthogonal query-demand metadata, required because glossary categories are
-   not one taxonomy;
-2. data-workload metadata, required because ingestion does not describe query
-   recurrence;
-3. state lifecycle as a physical alternative, required because one summary
-   operator can be deployed ephemerally or incrementally.
-
-No separate scheduler, forecasting framework, or replacement cost model is
-introduced. Existing query IR, summary properties, accuracy model, and
-recurrence cost types remain authoritative in their domains.
-
-## Alternatives and decisions
-
-### Encode workload class as one enum
-
-Rejected. Variants such as `AdHoc`, `OneShot`, and `Repeated` overlap:
-predictability and recurrence are different facts, and time scope is a third.
-
-### Infer demand from query syntax or submitted root count
-
-Rejected. Syntax contains no evidence of future arrival, and several roots in
-one request establish only current structural sharing.
-
-### Treat every summary as continuously maintained
-
-Rejected. It excludes ephemeral construction over data at rest and overcharges
-one-time plans. It also hides deployment lifetime from explanations.
-
-### Treat every one-time query as raw recomputation
-
-Rejected. An ephemeral summary may reduce memory or network cost during one
-execution, an existing summary may already answer the query, and a predictable
-future query may justify preparation.
-
-### Fold fidelity into a scalar cost
-
-Rejected. Accuracy and semantic correctness are constraints checked before
-ranking. A cheaper plan cannot purchase permission to violate fidelity.
-
-### Extend the existing recurrence profile only
-
-Partially accepted for implementation reuse, rejected as the whole model.
-`RecurrenceProfile` is an aggregated cost context for a target. It should remain
-the derived input to cost decisions, while normalized workload metadata retains
-predictability, time scope, provenance, and lifecycle information needed before
-and after aggregation.
-
-## Quality attributes and evidence
-
-- **Understandability:** explanations use glossary terms and show each axis
-  separately. Proxy: reviewers can distinguish repeated queries from continuous
-  ingestion in exported plan evidence.
-- **Debuggability:** selected and rejected lifecycle alternatives record costs,
-  horizon-derived decisions, assumptions, and typed rejection reasons. Full
-  demand/data provenance in exported explanations remains future work.
-- **Maintainability:** current recurrence types remain the cost authority;
-  normalized workload types remain the source authority. No duplicate formula
-  system is introduced.
-- **Extensibility:** scheduled and estimated recurrence fit without changing
-  query semantics. Forecasting policies remain pluggable planning objectives.
-- **Performance:** lifecycle enumeration expands the candidate space. The MVP
-  should generate only capability-compatible alternatives and deduplicate
-  equivalent deployments before ranking.
-- **Operability:** every long-lived state has activation, retention or retirement
-  semantics and ownership in output. Concrete runtime APIs are future work.
-- **Security and privacy:** query logs and empirical distributions may be
-  sensitive. Provenance must identify a source without requiring raw query-log
-  contents to be embedded in exported plans.
-
-## Acceptance and test design
-
-Realization acceptance is defined by identical logical queries producing
-different legal lifecycle choices under different workload contracts:
-
-1. **Unpredictable one-time query:** offers raw recomputation, compatible
-   existing state, and ephemeral build; does not justify new continuous state.
-2. **Predictable scheduled one-time query:** may offer prepared state with a
-   bounded activation and retirement period.
-3. **Repeated query over continuously ingesting data:** compares incremental
-   maintenance and repeated recomputation using distinct update and evaluation
-   rates over an explicit horizon.
-4. **Repeated query over data at rest:** uses evaluation rate without inventing
-   maintenance updates.
-5. **Real-time and longitudinal queries with the same expression:** preserve
-   different time selections and may receive different scan, retention, and
-   summary alternatives.
-6. **Unknown demand:** remains unknown in explanation and cannot make a newly
-   created long-lived state win through assumed reuse.
-7. **Mixed one-time and repeated consumers:** requires an explicit horizon and
-   accounts for shared build cost once.
-8. **Accuracy failure:** rejects a lifecycle regardless of favorable workload
-   cost.
-
-Focused unit tests should cover normalization, invalid combinations, evidence
-freshness, lifecycle capability checks, and dimensional cost arithmetic.
-End-to-end tests should cover cases 1–8 through candidate selection and exported
-explanations. A reviewer who did not implement the workload types should design
-or review at least the unknown-demand and mixed-consumer cases; that independent
-review has not occurred for this design document.
-
-## Risks, rollout, and exit criteria
-
-The implementation should roll out additively:
-
-1. add normalized metadata and explanations while preserving current
-   batch/repeating behavior;
-2. derive the existing `RecurrenceProfile` from the richer model;
-3. add ephemeral and existing-state alternatives;
-4. add prepared and continuously maintained lifecycle selection;
-5. integrate empirical demand and state catalogs only when provenance and
-   freshness contracts are available.
-
-Compatibility requires old workloads to normalize without changing their
-current decisions when no new metadata is supplied. Unknown new fields must
-take the documented conservative path rather than acquire optimistic defaults.
-
-Open decisions requiring architecture or product input:
-
-- whether predictable parameterized query templates count as the same repeated
-  query and under which equivalence relation;
-- who supplies the optimization horizon and whether a deployment may define a
-  default for purely repeated workloads;
-- which planning objective governs uncertain demand;
-- how state ownership, quota, and retirement requests cross the planner/runtime
-  boundary;
-- whether real-time versus longitudinal is supplied by the caller, derived by a
-  policy using `as_of` and lookback, or both with conflict diagnostics; and
-- the minimum evidence freshness required before empirical workload data may
-  affect selection.
-
-The design exits draft status when these decisions have owners, the normalized
-input has a compatibility plan, and acceptance cases 1–8 can be expressed in
-fixtures without runtime-specific assumptions.
diff --git a/tools/dag-viewer/README.md b/tools/dag-viewer/README.md
index 8c55aef56..182c0f94c 100644
--- a/tools/dag-viewer/README.md
+++ b/tools/dag-viewer/README.md
@@ -102,15 +102,6 @@ to calibrate against, and `--planner-cost-json` once there is.
 
 Without either flag, `--post-asap` exports the raw DAG only.
 
-The viewer also accepts the JSON produced by
-`export_summary_maintenance_plan`. It renders the materialized summary DAG as
-a single lifecycle-plan lane. Selecting a `SummaryAgg` shows the chosen
-lifecycle and maintenance mode together with every alternative's cost,
-assumptions, and rejection reason. The selected-node panel also shows the
-plan-level summary-versus-raw decision, costs, horizon, expected reads, and
-evaluation/update rates. Raw-recomputation plans retain that decision summary
-even though they have no deployed `SummaryAgg` to annotate.
-
 ## Standalone HTML
 
 ```sh
diff --git a/tools/dag-viewer/lifecycle-summary-maintenance.png b/tools/dag-viewer/lifecycle-summary-maintenance.png
deleted file mode 100644
index e873ffd9fe759a3633010fbbc91eec82cee604b5..0000000000000000000000000000000000000000
GIT binary patch
literal 0
HcmV?d00001

literal 174559
zcmYJbbzB==8?{SIsX!@hu@-HixD|IO?k>ThP~0K76^ayhcY+6Z*WwPr-3cziA)I->
z@4V;aubJ>;PcpLiy{@(H1S`r*V4@SCqoAN*N=b?;qoBO}fr5g%_xd^T&YRD9Fcg&c
zC{m(As;+5=%V-8uO9U_1hL@M)X+#3wk{<tmFCL=6?(xsV%eu|?we!MHQnQ_F?_4u|
z5>s={2`nAYceX@%sHlRT0b~B37d7<T=l^a0W_kMz?|(aS=C3RMx1A*`@*C}cJH`ah
z>HoJ)J@ww;e?$F94n)ED-ya6q%wM9QtdT~I7{yGv7Qr7PN)Czi-l2*r`$Z?jM8*8V
z+4@A`CPkw&_uses%_2oc^-9bY1?46+&v@$})rB(aC+Y-0dPx2^8Ya5V|1)YFMWHX6
zv81$xmV-2{)1I06H_AN!K#9t3>k?VGKGW)N(u2IXnS0AGPBM~`an)=emWPH0&ORWd
zr6n~~n3(!@Q?o$IT?>BhZUU=*FIr<}@Op3EtKInYh05b{b8#<CE<7J!v?|A_@1S{9
zdp-K0wJNLch-=Qz>!Y<!Dk~?zQsW<|^~dQLjLj3;Ia%rMf$_w(2K`o3FGmDL$LXwp
znj|GBUo!j{rz5xinbOWl&N`$pP6zDhRdA9|F@29)rK2;lF^nqb<R_m32BM-fQm^3T
z?-ryETcxA2G%3j}=Vag~2mYUl%2KO>lY#t;2C!{uA=(Om*17Jd$E`x%3adf<5Gwa;
zNelj~hsKR9(h7qiI-*WmYgEtzL>0?({8}orZJ1kW%!RW3^u*kZP?xvjY7B(RV{%$P
zv~#j^u_=#34Sr?CmUGf@vwsU)g_h(R6zW^q0w*ah3pAmqpSrlH7Ke+82sx5_hZ%{7
zp#8jOPVtR0NbJ-@O)U=L<Wm8X6O&Q^(FuH|;bRG0g%+0-Kr~g$n~JN-B209ImHq8(
zJq<-w>Dxhanjq~4kQhjtT;JBp)9{xnz1L=8Dy6)ovaqnSl2F7g8g)&G%%J?(mJ3zE
znWso~d!Vro=E(V*0d=J)*9-R4+j_OCIBDsTN{+ZHSYjPpR2559&T2L6EeV>2h4e@C
z_Ak9Tt5SFNS^6k<GuUsWr1p)Gj0i|#_vXOh;3O8o<3A-PVw@!XqT#aX)plCoHd<o}
zB+yV)S8Nk8g{Ke{tM<l=KEq$j6k;aZ*3_Km3t^#&HI`P8c9;Lf7s)@k>=}<-6LB|D
zk0`Co4gc^oHuJij)ia}$kEt`$^u2<(R@bytSum@hY+RH981@Z!Tbi{y=TjVVuj_YQ
z4G!9|zn{~NttjZ->&Mvic)3|Y7%XmDH7;2n5>`IF+W3Dy&k69*Ajdw&D(4t(yam_7
z&*@Q7o{A3-t!QXyc*yed^J!=YSp^vwlkpS(33eD8@6z+6<mL?yANZ0cZ;bG!e8?Og
zhG)xaqFxr$$rRGX3r|V}gl9!b-ubAh;qI(rXGT%eeEs<=i~Ornitk!xgSyW|@qbU8
z&$H+BH$KvGGFWdyS(st*@$o-V)-n^5lW{*0l|dmzCAl3B{#$I`%XIs$CyCrn3X{dY
z4o<`})i$%MN67mUntPTROf~24+fOV9=90**R{z7+rhSWI2Ztw{z@&r>64FdF!`y-|
z`aCW}RrP#N!Its5xV?c*A?SJU)lgATI@(d6;XMdWtVno#@kl2{`Taq)2mLiVC&y%b
zG_rFsi={d#D#_~3?RGEIeqU%m@F$lP@`I5}u9J&e1!sI-rkR)18_i_WhirLysnC!J
zH4w<?_fNyk4W}BmIPa#2pUMsvVA&<oR`pw`u!=5xH^&0_);9%NXzy>HB**$?C1n$$
z45IX&{r(P|XbjeFQu%U8Q9i-e!NDE5mGm&gevma0rJ#+3gZ#V5zM){*HD*D7Mx_@)
z;$K=f%nG3s=(huwK{ZmsU1U#)+ChEXpV2k+Z~r^7uI~*xpCrsQaBK)){LUHwEO4LI
z8zU`0G%&p30$jTmi!~;<s`YlG=^vU};bB?Igryq!TXVdxKEKb&&+iiGKm<)JK1I|@
zLpS=`c7Op-ZSQz9k*LNx$`0uFqSh}_vc7-(_)%Fo=Io7>MKOhkfu_~RcHzDekhvBu
zx7qbR)wD~Dvqz%$y`1~zpo9GYAH{7<=~%-HZ@RlDhh|VfOk%8z!kDC_th$<#p)?~S
z@<bDQSe*4Js(V?GA>(>Z%z90^sR^bvgLczf4T4MifzQxEipgGq<meU;W9DFTdH6?@
z|5im^88$m@h=LN5Uz$gPiw(+2EuCa>sH#fdVq5ux_4&d*=T41AV@~_{xETQh>zUyB
zT!uXLT9GjMW(p!h$B5|hN)sAx{*g9#M6|18KNZ(X4+-B7D6B|Q^R$v7Xv2Yf1jVO`
z6stm6S@|%X7C2t#JOwMO%1s^&1{0BpxIARdlD=Gchnu$OvR?<jEv`S|`{&u*Sj&&O
zi?o=w<}x@v#Ud4CHlDt~XKHL@udFCiD)8R5X;m-NlbOZ62*2HevpUxZiAdn2jdn{!
zdR!A~)C*x-@)o2x5h6(04iU+YXjEic(1Z~x1)|-(y^c6FbNJ_Z3Yy}Th6^)9E*gT<
z<h-jfl+$X_3%1x7NrPEbWX?9yk)>$UU(*O>)M*^KB;j{6U(IIik*6YKNy(43T`NJe
zZ1s9fCarxsotFVE&mHG(#d!sd4ePdeFTr|b)NT0PuC(kVxh}8`4L8lb@I1P{yX`m-
zSa%`vtZaW6^arzo@EKS6ycc5P4_tKHyg6fARYG^Z(-@z0PC4S8?MCfftW7x9*vu!+
zjqF~q|4uzLx}Mc`CK<ifyhyORLG%RCbT?q~I3iPW>JC>#3d(ibK`<P{&5tWyH(d|!
znK?D#IauieF1TLDob6wnv3zc}wgXFFiMAgM2M|(?>d=5KYHY`)4gOJ5(3t-;`Sw-G
z&*Xg0zlW2Jm$mt(u%{L{p9LX@`VdOF0{P7K6Vi^q)?0<le*)j~Iv>8^{IFX*?T$F~
z+S+5z-(u8jJ6u0&D+C3Fe-fH1@CkU;wA{*Ry7GX>pgmit8?>|4;rnNPetrqc>vEJ`
zKQ3bqhc9)IYHx*=5UnaA+dw%eq3`tgGBh@)2o5GoJ;JqW3E8apT=yyzG6h(lY(1`y
zA!>+++t9TvgME!QPYUveQm4Mr<%x+2S@Zs#?Ks5EXxy*TJMT+kZU;7N<HVHOd#q33
zeZ*(y>m*)V0R|-<9r}x*8mr|x$5|Vg{rU#QU5R$RZ79i8pL#$=&LrJush#8R`2nSc
z_FUkK`;ALA*Vm7Cx3{lY$$YLt@9a&mJ_q1og?N>Zfqd*E&X1W^%2pbJZqfW@zEG&`
z*`J!e^8s%1E^oe$CWlLRL&KPm5C>V=;gLlbe|-WTLqwRSBTdf!RI@}qV|tO%!Bx6S
z!Pv*PD8`K=`rX0!eOQ@Vb)bx)@?`0v3-vn;OiZJ}|0c7PpDD(UtgMmOq#QOY;s-)E
zV81keA75l%UYpy2{I4ya1+TdlCyB_F$CG8BPb4HtD-)gl<EK}|^=Gm9SEOt;qNb(R
zi!}s-&NV7-68R-LL!)qW3c6yglvFD{R@>zeP1JkmndymzmW$K-NWEbN6~(Cf@2toz
z_|VnMmq7yqgPvy(dfu1kw>x`^5x4Dw{rx(%-keTvk5{das*+>-FcYGqSK4;x6!5Nl
zD&64-d-8k7)>jc3v9Yn~+{XXzaI0Tl9-Z%x1T|wVeHJ2<a!bg~-HLj)tj>_ZQK66+
z2diOEy>hrO%_zHy#>TIzeu_zOPaMru9UTm#;g;SLi0k#fUvzc%nTDwrlxGAqp5;$F
z_P7mcM~*SAdhU(qn|CI%vBUPKi`txKKjeS=M)9o*c~3{H75GKv5iiBs^4rXWoUX1B
zqA;3V;_dACc!R_Cepqt#r%E?>cXhkL$2{wW+&6LsPEd8dl@*yphW4kmXDT1#m>INc
zwv0Z^no~2|yZGqUO5@%oMkF0}%*`bYsN^>^E*~t^Uc>}o081?}1vx(6VIJ$w+OA~P
zf1~^+;C}P>woxoU{+2zi-GsI3(^+1gv7{8f&(L~8>7rRU1r<fT?QEOYrG@QE%h7Uu
z`Cs}I&Z)_Xm3mW`NRkJxooy(HkkdM3bn%6tl$I7Pd+9&HO~bP3tgI|OuRDJ4yBfoQ
z5U+bg_SXx1dYyW2R29m{x#IVIqocB3bUQy>#Lsq9mLAqKy=W`{-fq$yPQ-#bvjv@!
zi%V$8g9NV})+W^!sc*EK%}*}1vF0|1Zi+(Tene;ybhAgai15u9<loy##PXCT1V1vW
zq-Y*;;m~Ka-VD)^;ibi1YF`19NY7u+*q)rB958eIv)?{*k@db#cZY6wF32>^*!)p0
zk7Hpd-pKrVQBjf0$=T4cHb)sN3rlW<zyCj)DHDqWGck!iGfT^0Z(h?0zeZd-uF7R%
z9v7dpbKF+r;llN<O+_{i`*TFWSjK?l5S#guqLh^R{pj*kzHH6}9=%?Z<+Z?mmY#SN
zQ8=++qf+<FS69csZj77PwxKgEo|ilV0>Cry6VbnZse3Sa+J^eFdAU`=vCU@FBxTXv
z$x^?;)op+4jgds;uNPP@<r;b7Iyy^_yqqN^^cN!)IXPWt<c&_)Enc2H;A8u~qvHf?
z-oA*@Rug&O<-8%#CD`c|=3zasLOJd-y(4Cc@}i;V^SoTRgfW}WAbcP12m4P$wK_Y$
zw%%jr)cBP}X=@}olE$T_=`?CFXkGDgmM<)vZpH)4n^yfnZc)+g{yb#Dh)S=~+3PYS
zZ@JkiJMkR}kHg*4Et7r=;_|Xst+dJzo>RX1K)_+H1kE2BFnZAXUcECaXm|S8w+)GL
z9RzFkI6>ZGBo1eATi=X#MrQIYH+jwSMqZ<zpGQQz!`K;NVP(&=FR>z~;m@we`ove_
z-P*)kXKg6$hyKjLK~Om%E+K}6lRZaJ^K){lO=KF8^%XG>Bscf;AzmWfBA%z-_L%gO
z!v+F(P|A&)`|_X(R-#AqjoxrM-|O<Aar|<)zds3m`>4s;>MNg|#Jz)li)Si(vB+|!
zfCmU%<#Tr^r>q=ORb>d4C3=i^smT5k`0h57-wUpzB_jh-xV}PUV`aAFZZhkt#zjSa
zg4MHfc3RexxVAj8{6wJGyp}sU4aNXx$LAZF8qF8!I=*?clj<{`?x7&)aaUMW%*DOn
zY&PZJ`}R%voX=KCNmz}apI@BnG5mTu^?G}I`|f(be?}xaCMGXhw^;pGY6rd^D%-YY
z{c*e7H4P=l=rF9%3)-7c8F)=102#{ABG|8?1*#NnHhZU{URyN({2k=O(LgoG_?NLo
zGgm$S@Nct;iAvnT#Yy!n8wR;c=I;AR0fptn@<tjOTEynqS06S<R!HY#v+}buBm^IG
zzj6FM9mbUZzi$h_7*b%^%#RhP{UUu#x%s&Zi<;N*xb!{$V*v;Az6mML)fk{-#jvi^
zO{`13<%MEs(bnRg3n`zY&siW|&_}jGIngvDoF)EGonj7JU+b4hruabgwteBULc?dQ
zAZ3-QL+erk&O&Qz^TAfp?V)F0JX5cNKLv5zo!9d6)L3ifDcf`iQEWmvk0%6v<n2Cd
z<;CS;B^rEzMa(ZjD6cJ3Ep6PVK0<&~JAl62j7}`+aoBvVPfZ=27;Cwdg@;*CAFAQO
z*3D@nC@n3WuPjiyt48R&%Zo{eXq~kcG+S<Yc9aHI|ABw{i0Y>@HTf13VfN*SwI=tP
zRG?tKaPL>&-ym-%k?tJXFvLG%{r9nVfyQd}ALu%AnAZNTcNZGL`ah&MJA3S|3z<(0
z##`DfH?n)|40B)X=r`HP>+5F<<8jtE56}!SGBV2GF~r5khlhpatXii!aM;_QA)G<8
z?njHYc@a%c2Vt4t;b#!4vdjGd3DFXb%KhbL7x?Gocki6B`@*ZM>mjHc8Lb|q{O*XJ
zsiDyslYtyDoM@Qs_}`UgSNJ5zR<B&Ik!)3VrNJ%KIbI9{zs6?qcxOa=x%r|y?svzR
zJ3qwXgwc;DB<w(ArBZz)#rdl4P@Au{g|FS!X1R%*mGz>xR6CrI^J8njmR8O&ypA=&
z^EkbyRF8SWM&}Un4U&^%W*x_L;%fKgU8h7Peb(fBQu%XghrikRaH-a`yEpt5)**D`
z@ZmUJVr<2W+8vTy(5>IeFj=95O_=JCqNO#qlzF)~k=~UOPB=3ql$k$YDlrxnrC7hn
zId4QqPR)mtCM^1Et7P6$uif3+*jlZ-CxDohhsB~JtJBN<vRI?CYpZC=Ofo1U-F!7m
z@&E>BEf`C?y&4%C@5uVueP<*dnP2|r)M}}bVP7X&U0!RTT;y-H`ez|bmO;jPn|aau
z>@{6f@dyHJ+~oG-xoXofm!tU$<l`%BY$L5&%>CH{Utqje&+UEuF(&!#Aq67Am6esz
zYpCs_Gw~}df}7JbBSNUdP$JWM{wV@J1r$UAPA;4r90YuJ2Gu5V$uakpYDy*1?8!*A
zTVCr$FIj2I3)Y6r$3>S+KF@PuO{rk-D>zk?(PBP0K>Xhs8ySoHL<qxSWI@u2Q}fC3
z*#zqs>Td!9l~UacOS$Nem<8nL6S0XId>(SILOB=+CqD$0;o#H1d7Y?XB1<6tVc>SC
zzN-te_o^<f*6mupl!Af+ox#@*{ZT5D$7B0ch@YN8_LEQ#9Y67r`pAKbi?qdl)5!gE
zKVeLSQ<Ia0*z9^kH!1O`y6xPN&cNBkR3bESG)qLblbZ%HesZ+Ad)1L1!aUEX$8JhB
z%QKz)F^9d{{Qj$o(I0qh;Ka{Rbl0Fr{j3A)ny+&o%<kpWzx&^!PCWDLqM^kJCJA5W
zY4?%ujocsm%O8t^(sS2|Lihdq-^p-?nVID#XW%AXJmPgJqAoA*6YR@U{?bE)eD;h=
zAv5{A&09<*HMN06`@gOp*~23v)E%@Mwmug##EIp45c(pKW)4z8uQu-syl%m6rkxfF
zTG}R$@;0H)uSVkG<1m;;yZwd#fQqe7YatXuPSt128Zb$RZ3HPx=T-I-e>O91$vKA-
zx|2K!-JdSTlPy2b7E5KZ=Q9?elF!(AUP1>dSGt1bsRUhFFDm{PI|#z4uvuzIkB{Hh
zX`HP1`llgS@xkT#s@4y?AgxTSn$mPsx4~&K9J9h^Wn*^i1eQ$<;xV;eth5}cidRdc
zW72Or9h^R3W5rRG%ixL-uBks+nF_`Xe?q`nrQ3wNy9#k^e*Q%69Pzpvr7zSjW%3tr
zDX54z-od00lM%WefYP2HmeG^X2*G#UVK7^*b2`#uPyVQ^7zN2ey}&M3WmGViG*M5;
zjoSjXcjR4APP}n+kls%q4!XbG|B<Y!X!l9?l$n(oM`u=U3Z_WNnL}z!9hzX9Jr_C{
zv6M@lndARg8pMVcQb;geF4i-mkRdP)RlT{HPeu0$K|fC{U(U14o}zr4_x)_G@}h4{
zhXhuSA$NOF-yvo63VvWNv6YUi7>$?@bx}q6=-sg~>ea`<AX^kA;n?7PAwb(c1Jyn1
z+FpEl*91+JjZ~1-YB9t>6G_;~S4Bb+_n5v@gS+cc#a}+yzQA25EKEFMq!mHctrKy@
z98Ur!;8ZS?FY&=+It}*7^P@`gJ83DYTW`!g=GySG2uj`O%e7D6yzt1Wr9{R1%JjKY
z4I|KoIMkrZo&6O_VZTi_JEE)Q2&bo~rmMcQX4ekByFNdIZYyiLzATc|%~QTr&~KsX
zh<X3(y)JK^PLn&~w#`yA`W>RjWxd3n&B&7T#OwS}PGpuqwG5cD^Vp)uV5Q9wX{~lf
z2CJi8p$~V<1&c1Ek;D^`Cc)_9_wUm6SZocmUD9xyJjN|@GclUJr81>te>{qg#fLlA
zva|2WuKj}#Rp&<xa|(Uf9M5QU+s($4(``hAe25D(Z_ld<9o!HbdCPfznR*RxZgd;r
z<AKaIJZ42_3vAZ~*i;E$m-(TZk7RN=23&E5puu4Q&R9IRA6l=>0^v*W`Ox|r2{9b5
z69z<Uv=a0BhY71Q#07pPlb$|YHn<6{8se}%!$2?|A>??zfAs1MmHw`jS_!kns&iRQ
z;Ol%VVO&G7rM1vskpcx42Nndj3sBvn|E^(UpDok(Ih+d?!`P9Ll3~(rd)TWqdc429
zc<5@+u(GtgIGo2=4>sGD7mcZ#g%wQ+dOmQ0``<e`)sAS_MWk}UyBb*&8TD6MO-}-y
zEY;N1u!sd(j2G+Jp&+?b7Pp?_X+Rjj=PJEAKR4TNnxt#h%F4;@tsb~NOUMhLkXwHU
z0ED->)4|O2^bCBaHgsIuhMJCU7HofZb-vPMO-Ss%*YVXb`g62Z7)9jD?k>iB%f}_*
zr08g&i!bg(=mKVHoYs^6mN99J35vtJ$H(&c-68IvY;FH{tKh~w=Oe99e1?jOn%sx|
z<5mwGgPwo?Ja0}bwd>2e`uc<mD(t6rs1!0r)0orS!ZGmZ2d}fIp&-lIvZDYDe43+T
zrRrXYgu)J!#@>c<I;F#7?+7uk%fbHMWd4T?O!05#=J4FyZ~6ZJG@)Tx#;CL^m2g~g
zGdi!6<Mi9!H}B9%_?^>YRc@Uu)zi6Myw5iBri<0{B<)uo(BfQeG@4D2eqz{Ea&69+
zRcZ9?X5e!e+!ysFtYp1Q&e!?85d%+JN_qn6d9ybW99y8{Qo+g0{8M_bPhBh<ww=t?
z`FP+ooGj<ZH03W7=JDqEEna~48z!Abey@%1cSm{e_KkhM_i$%~Jn8XVwR%2gFt#Xh
z`+M+u$)O_yr|g<Oi6<(!J6m6zkGyK47Jfxcx+*OFyo&<QeKvx>Z*Pwk(8B)!<HFKK
zfW=d@UcFXW=1ZEe&t#~U5~+Zjib-~MnLBc_bhCg_A(bnR_d&@jE+bkf0D7FRJ&|O|
zaX89J#fBO{atG%jBUURy5rJ;>2ZyS<LSBT^yjit<R#|x#+xzxcXcpqC^RbCVSkN0h
zzq8bns_GxAAi30b|B1qw?H%zeh7m^>^T9O^8(xj+`6Brd+NEZ*k*Q|HCAd&l7zC$g
z%(dV9O+xZPtg<A$)-4qeGr+WaOz>uAxo=>AhK*f|j5hiX?Zs3`4g(ZYI^gx50a9O{
z*_2Y;*7lBpMfW;KnBIDP>lf{GzLHx>_QCbWb;h3pxLVT!n>P#v9l1A15#MaaoXS=x
zSNVmLfVjkbTg8C$=iOvJrlp6w55)I!U)7~-?>zyY6h67i<eqDc5QZf0*LYdkFihcY
zG8UF<pr~vHujxN}U7Zu>6$VQUsB+|gUC<(^nS4jY56#aJ4)Ap@O-<u*2~Wj7?iY^D
z>7Rb=;XS6H?e=i@+Sc#hJli|ZE*`vItvRSC-SG%!yk2R$7S&c+?p?@Hb42P%n92h4
z7=$S@CdM$5vD7@xk5ydTmqS`Z^p~<Bi&v?ia2IvQw4zF0dQ=@wsZ=CZ2Er*z1k1QY
z+Ha^5<+R|YlW2V|I2K{sT=&qeu*ksx4>}La62~QPh_&gd5{nBi(X5}CYe^I14zl6D
zKU}Del-Av7Y5ihLN?PB1UHHc@$&*QmOysFdtL@jr+yrl(O%5xj_}idJl8XzhtS{!1
z{*|bAm!G*k&3^p?0OW(X_BV<fx_@*1r{hR|wzSF5Avpq`52A10VHR}!MIKEyLbx)O
zAupfy-=n$d+>;lKra^qP>&)Z>jHEmF&hMeKwsVPX-kYRiM2GE}Fze;E*ckS!lirbs
zBZ(U8#gq?hzq_vVnug0|Wjd2ixxoGqxsKPxT~1c3HunkP1Ox=H-VtYu2ru(IpzGk=
zPWXAa-M=N7%M|yxJLK-R%^T8{k(rw4^nUDR0QaYH7#p5sEbk7dtkg(BfXbzkAzBK3
zf33!L*14yu2Vhu+(tqCxQ&_<Azfe%1@zhaJ<&A@7!`{x-{5_|{#8jhw!~DQdsL*%F
zNz!<|saiT*J}4o<rA;W4`NUx)BqqgU<96!_3Ant#%E@_2{6)}fhqG7IEuj@ta6e~K
z>XC;LL4&Xl*Rh;rjuA+2f_DrgprOSZeS7|=yD*8}`<Eb(r^8f%;rl#>5rT_@>xoy>
z;38QHL2*0&V(o$i1Y=WKAp|02Jl}BR59qs;>04fIT!LY_@Oc`=m)SYF{mv>vzSi%;
zkaJfw{<A0y=OJP$MZ?m|H8@HWjn|Ez2=`Uo#faZI&p1@EAbr0cp62_xo5oQq(XcWK
zMAOJ$kCsBYL9S<mf0Qc*suNV;A%o~)Yg$md^*?#V#Y9wQN7NFh5}Cr#<Gq1UvU~*!
z;gHwnn$+b|l51mQ0N1Ov<f5aaQ67f1*y~=omz<KddptD?yYcdOqCQJuFOtdrNFfj)
z-%_~zC*Q<6xqTAPnp`WqW?@eyg|m#)({9WUn;uN`rqjm*E5q5LB9EKNLQ3oqT9Rlh
zs9HWK=#(w|J-%*!IGU#7{}qj?zeiVW8~O8}6X6~PVjk+{)PfYVPab#hMfIt#K0enS
z_!}JTv4Ko!(~PI%u`A%g+o62sn;kZ1hB`19w<au;@a0fhJ?i}ho-p1ct$@cBz<u!n
z1z~AsRwbxN9*AjQstuCUeFWqf9v&Vsud~@~om{QObeUfB=qZ%TO*z8A#)gqEy}z(<
zs^GSCN6n=Od9+v$RJ`owFxR>9P8@~_EE7e=@l;ORy~Jekn;SU9Klk6cu?(m6(vO2d
zaXXqW*gyXWE-X?3y+(J;N8JW+@XNr!zzOjF^ro%i-E~hW{^2r$mUfW0-WCF-cR5)h
z<aPk>mMsHvNF>p3jywB+k&Q)ee!7;#+K<=eBt-Am#6gfcWvQ~wWr&opva)#o4S@!N
zNxMGL=&J_w!v`@AO;rwE>;I1h?BQjXikq@y?2bV-t0|2+0ljNub6p6wKUwh#Y)|B%
zaYk3j<jXtF1C5aYQj00+n=+fZnZXa@cM<Q{9)}WdjRWUdP1!7G!0Udu2>2ld+xonL
zXihx2(zzw~Mu}Qr`xO~mZOD8HP#5OL{J6h5vY0Mr&(arMa5GC(R8d*3H@&W*Q87bP
zFI8v%^8Gsphq$m^f~~Es;IGq;b74%J@qOJYyY)LKOX_9Ix!+I3PY>G?3*2{rVjJ(U
z2pa?E`w19jb)_9iQ1I;R5t>YGew6)r5h1c9lz=>Mm45S%g2{?&x=Pb)UB<qLM8RjL
zHEiv>)+uM&hox+Nz43A1+5j5j(CTWpfP@$RGW2mi0f7>e%zo!+>}v5^>}lpJA+)}B
zA$L+tI3ph!Fq~A&)ua7T*LUs4)5dK!4NTQwY2U?&?#!vOF=$nPXaDm(FNw(q`B!~%
zWF=oe2vtp@XKS2u*^`C5tTmA*k@tl`sF-f68E#g6$#>85K>q3&#@0rG*F`#=zFqj@
zcEsr>4zTf+O^K`ar#)`nZ=2%zM%zeo)505xfQ~kPULqdn4E0g?#VmZEM%S@;=TP(m
zR<~f6cQ!k#<N4p8f870pBr5eg9wkO6UqgZ}Gq_CN%Ox=4+s9h3HZe22&PzaSir^E_
zbbjV9!8$VWz{;fAr=bSNhwfy1rBZ^*E+XFnz$KUEjqU-lK*OuWn>V`jxlUqJ$={2g
z`o;use&2as`rO>~L?Lz2dOkLXf{t_Z^Hh$dLb;6}3;_59vR!d>R6cEbeXT4@?<0|;
z6L0eSTzWl$**vlT`lD`&*X2%k3mih@EhjB?_BhDYJtfcHppTz|6CY)sNyBAysII7{
zM8Mm^#6YfFc)Z-Y{BHskuxE>Yi)xDs33(qQCdgl2$HhmxA<v0XQGDV^i+p?9A^Ut!
zqH)sR2-|}M1`g|a?}sh85_w=HIjl(cV43c^;CPHCEBnXRI;1Z$vjM=ex8um=xNMwz
zXLV@Z(?D=qI$f>BZRX-z0F-o--xO$HIX^4~Nu$Qos^zNwrI9yy-!3(3L?us*?XH?x
ze|`NjR~M}Sy+n_{c|^ZqYcd`RAl??Y`-q$zL*6s8RL{@h<tMYIWBQ-=4rXy)XxGq#
zeG!QH3oF`0-K>z#I^t#{BS+gmCo82g)%oE8`lb5ij6Je!XarPzWap`w?XBt7Xa(n8
zo1&uPRi@JH`!IYG5<EP4kRlwi+IDgJIEXb$?cW5x4Qal=;HkA#&Ydo^woGy3naxS;
zRY;NcS@Pg-Z5i5S#~ND!-=gLiZPtdA1(LsOQj~h4#US}n7KeZQuaAlr9aofE%y98T
zf$@6CJ<e+G7CYl;wnh*GYjV;j<>c;_(ZM66%7P5MaA4(JeEZF@O5q<p>9Mud@T`)O
zBu-3Zd=CFBc_~RrT4eoq(Ez0dR@^Pe%)tEI!v0YdWAw<3wj9d>tBRq`?QfKnN;g9z
zwDHincXv1(RE96&4LQn_C5T@|dSQ7sx<OF6b$?u(pFs}1-?rxwsyR2<*~`hxM_B6V
z9^c!&X`1Q53Ciz|*F=3T5|P#dKHa-j67iT2t`uYZsVbnTj#LPb%n#pZ)T#^^ISEM-
zSo})!wG$hsu`sJ;cg-iGV1OgHhk+&h2SsX-LL108TiG>RZ6IU;z?!Vg7vX6!F|?^5
z%|Fh;!lWSmJuYt9(anPLJ#;EUd0er7!xe>z_ln0c^eP6ixJ@p&Jc@eq2_b)u$5u-g
zTN2Cioo!~rq}MmfTm8_zn2rjU27X&}V>B_|9d{>IC)!vPLY1V_8P{3-ez8{it1*Q6
z@8{!&PO>gY#3(!R{c+p)r2!7_oG2n&EQOTv+a41gQ_w+|ic=;gm=S&9y*4SpqOh<q
zXJ?vSZ8DZESl4WsIEqOKE3o_9<a7z1^L^=eNKQ#v=U5P-m$3r)ri+c1K)pB#qlq>D
zdrI%ta?NG8_Qk2je7Z?Dl>=0McCgN<RTYPv`%t#pFuKCAx25Vmv=fflyg+sbv6_x%
zaC_JsHC@srGI?B&k}Iz5PcQMbaM~_eEH*h+hU(yGCD%yLPtyt9X$}t$e@w5Fd~+Nq
zBX_T048`fZ)oVlV=|W#7d;9cn@o&V0l?!0ZEH5wXw|QRf4Pf)@>Pl;bqzmhKw&dlZ
z@rvq}CQWVjn<2+a+5~*c^S>*psE~7%Thp)4zxP#_mmeS<`ZB6Tu}`qi+*3OpAJrjf
zo5pN}_gE?N@bE~dUSfBRd|a%z4f5Z5Iil&t8KJdZO7s(_XQjbD^y)_)XS3*M(+pB=
z+*?T*79&emt&riz53;i85Xiq4jGr$PPko2MO`|hbgGZ0Hfno&*OA64i8a9_ClYd+p
z$YGDq-o#D9-rb+GH}n0!FlFhZHkoOeN&Tj)1Sb4;6%(I!wfW(Hg@qqq7Zhe9glTBE
z+H{rlGM>kQvv(ycRA2P`5#IHu*%%l6^@Ec(l^Aft917i?iXE>XgCnK?Z17Dbh-Zfx
z**%rLeai9s%0NT@`aP3Qn;f@t8^9AhA0so{av-HbK?}JplLWe4zg~PsC&tFcj%_p)
zx3kmm6rMbOq?*^GrBTZLh=XJC(`MK^t;K*U`*-gW?C(*&XrR|jRN{4gSlDo?%Z)Wb
zeqNr>1s06%l*_g$MilK^2v<>RepGxiE-`lB)s6@=;B8l>(%-a}s&*nDwih#7J)!8!
z8RiyN{bih}Ug>M&c0BzmXCBKtUTojVS!2;@g*tz#{{C5@uU%pC&%7g4AntqwaO!yH
z5*;0CvN3$g^qL$VGlGMkHPgC-cSw8M?p`T%4C-;_MaoM_K`c9NO~TR%2sf2A<2K~4
zMlH3tYg*XY@A9oy-2UQ4wNbjNGIo&eN<1&|xF&u1h9#@%vb}(Iwe7am^|n}RdP(2;
zt`({_6@cswBOt-YpRG0350PQiZCj{UV6tBseNA9*8u}Y7>r|vyt58mId(6AJO}qpD
zSQaA9%)TFhp%&w37R=akwYL&a*v~%Na~fH)S};>8v%5_<tJCZqt6aLa7G<N$8>;f%
z_@=bA&Ey4s!ZunxMFyW&!n*#`8`jE-^<HkD^^F#8R`VB*j^4ykeG1Do12G?Aw(d`X
z`lS0Xcr`Yq0v(q<LC}uR^~xjQ(?-0{bxlXtVKlLfjTX7TuBaEUVq=5R{LGE0w_TMQ
z>Q~G+u`$_KZY2l+V-hw@o@%jMe)k({L7aq{$I^lByxW`d^0;RiMs?o?<ow~(HGfE^
z)d1)9bPXq2hXn)cRb1M`BmLhHw3mK=$l^hhldM~4yHq%5h0vm%R4unxgiR=7+Z?o+
zK%k8YFy%0Qv-zWAKhV(8IRt#9-I^$h@cbG4Qr8DEWCkEY_~Pb$U6wKdF=b;6UHS$T
zTBJy`+cDwj)l?6mGe^j2wmH8d=PEI|IGaPKuc2Q^d0_F4g&c)~NaP4+7_Zu7nttOE
z;BlL{>fgNv6e-o%HiyGN!Us*9X6n~!@9A(#^8n*!rc^Ed1KZcJ8K2-#86a6wpsrU+
zro{?o4ljFk4$AUsG-X<8oUvbL(H`8SUM|$#6x`<1D*KN<T#8>=RC7@u?yWXM{(k=(
zLJVH6`tu3X6}Q#{Cqz1JiDGKFgnqUB*<st)Q7-Uhv;CviLET|NO*8}FW5=)}JTs)l
z%0<H!r<8}LNI1os5qv@m{?aYT{GAQ^a13A{6BH`E+H_~LdO`thiTwH-Tp)*B!IaNU
zH*Q=10^rzaiPSG@@sne+h?O7qA7lJbh6WV}Wm-^V^c8I9mA(H6fbT$^MSgY~1Iyv^
zoBabrV^6l@o9pWnSwFqXT=t@b*ey>jm-gWBl;ks?v3VnD)n7L3Ifc~TK@kxVDJcsf
zxH51kax3^gp;UW!M1MT14SE_U5l$rJqjNH%U4M9VlrNt#d{w4de>_vli(|0d?DI4@
zZ3)P5N4tu0jqK--y3O8yT2JjBDcj+B%e?h6QfKYJBBj#^hC6ubq@^@9?TImlfZmTS
zD2C{^Zp6mNj||dMT2xkV>-#u3HqTNr=|fbvFH>hzQc?l~UmjBS<K#ZrpV<R&b(!pe
z;^SS)e?|V;WS)(U3;a2OnE&lnlW;*+S^m!Mu7U^s<6I!l_4p@Z24p=i3rh@#3t-#n
z=y*0daG;rryZ|2ckfe_vO-orGVh2)y#VR{Jw~fx{B<In(D|Z0rW2t6q2%&_EqPf@b
zp3-Q%Beb6IGr{q)&)Qn2NGRU$$y{akaB?-HPSbF>Lc7SVz;<W11a!6p!W>B?Ai15~
zc(KDOxCIb2WbkPcWpk28_vcsq;<~=Ua>ffsrphw4%hq>F+Y9?SkD@oG4~cDwYNwnn
z;}apYZ|vA$s_=sf=Xu%n*1v`k01fLxN9Io1O1_IFeDg+7gOZ(rQz%Q{mbQ3cXb6`F
z8Zi1s<zIH@J8OXF+suZ%W1G-+A+D@r+uWxN9hmI$7p4yJZn(|fG*VTiUkt<#@}@=S
zmsHYBN9Ty6sGPtGomm9TpPexxnZ@hUKGTr7PtkkV2@x6CeQ$qBM|2H-eQXYq*RHCn
z_RqW*MKkySdhW0ETP$znnw0-!#id~QZ!3sxl{|Orm$5knv48bwgSBca=-|T0(C<Hi
zN(M2^X!Wdj-dxGhUF6!WtyetFGd!_l0{5N|)C=jic|VOXnJxYGh5>+_{Ur*LO;FkN
zewf?)DAGiZPyw(x9*q{IjBQc*eAbnTXT_~~!BRuKzbC{@uFRsz%qE2qi`>Aq;P>7_
zc_ij;a5>zICLp-Q$^*lbh;NYH65^-4fV#WZ${Lh@aHZfoA@PqCj@&lUt{5C1{zc9a
zV*5#mKR_5iLH-qQovjRMrRmAD{Uh3y$3G+|f+gBxwpUQEW{$&_bpAdc<XYCV$A-MR
z>e_5J|5nFrxr2n71nM3mM@Bqc3Q<*Rqm$+4P3P;oaBalYQl1L(^VICDkt099F0r!|
z{QD0a9GtMQx8@Wr-uK7I#~>>)TJ(xN2Sl*SL#qCqNofgMEtc7@t5zJ3H#0FGFQy9F
zy6-0}OQob}6f)ayZ+Z$W`x0*T92_dbLn3~Xf;UJ%2`7@m4TjsmyDQk@iptqWrB1%$
zZAaFnWI2Wc-dFY&wI)GxTH1;q##b2Y>mAU70AZyhDbzT8<e@OQxQLU+tW^mP2r7el
zAvZ4ek0flk#GJrlXA5#je)>3-@nID`@x}BR6kRolixL8x(X351w#>Y^m=BvTCqP;f
z>DzgTLjZHihE6qOrEQd1^1D84Y*H~jwxkdfHAP6^pA`;Eiz#URVywxtRI$RX9?NJ0
z0_Z0B;$f0(ptye%+GgR)K8RsOMGC6aK3@AP+UrvZ+8qJ+yATFh&O?P5@c(iFHi~r2
zG;UAPtXBMXP4DWSPCuvowM@6T&6fq$mD0<Z8?$T_spoY)N{r1@Mis8PZjM4c$s1Im
zlA78rYu+NXFy*XX0R!Yp_wHf!7&n=7q~G2oY54Gpg3Ip86d-(Y=|}O{Bg*RV;%$K7
zMz!N=uxB{uz+nHl-nY@=aryIe%yx0qcCWIdSE01zc>fjLr$7QD#EEzQmYE}`i}Q&x
zB4;Lp3n;dAcV$O0E(?i#wqCU7GZ;U^8M7bD%6-t%EP5eGj_6IAdvVs6h==1``ZkxQ
z<D;o3`ZW|(F75+xdIs7-^ZBZP_I95i24B+O67hO(j4amcU>q-TnV9Sxg69w+>wS+2
z)5U7dN6y#1BdGwl;B&l6lWTN{rvquVnpihq5$m_Q%aKaVV?UlxeTI~*5p)mDmbZB#
z$A~qaJ@X|M@GJq<GxFNsLA47;d9knv<jeJ1-K}>@<`?Tuvf9_l#g)T^eQ`#%MhH30
z?JZ_X2HNt}LU+I|n;BPhqhz}m6n{;PsYd_<ADDBhcw1hBrw3<76NH<{B_fqVKH%dw
z8%!A91sqN_bGBN1DO?3V{43fW(<kBs`+I;o8I<h?YYYiFtX%hp0UIM1Z{$LdB7dBw
zp+U94sln<Nou>k*lp$+u#%OXv%dH-QT+|I-9>`9wiy3P++k;u#TqYck27J;|A}ul5
zH^J5F18YL4fC1DOo+$~~Vk8jp$VSILIW;*sE~=ay{L;Jvg<GuH$Bpeq%P|sk@+!1Q
zEyyZ5I#RD~z24z;YhWs8zx0>MIV;9OsF_cjSL*6a=Y1sU=H_Pd$NwOX;x85zAKp!D
zF?_D%vY<~-T>0P$wUCaEsI~XV@TOTC{(eTO3r`AnCNv(+C$Amd?DqA5w)(;t6bVhu
ziQWZ22K;Cs61!)hs`|!XWlw=8K>9=ULx?v*(~99M-l74Y)A+M~<x^Me<5SRK+V=qB
zyCNJmm$R33IJr=W)a<l$&ABGnZE|$RVHb&Q6(c#j`;N3d>ICVP5FCwczJACw<oQR+
z-_stiEo@iKC-x2eO98uyTJn{U7@FIa!v{2to>A2JCF*4(!ps~pywr?Ogz)=Ury#CU
z5$BEGz`JLDGbDS^>$6bK`xOWE9W2s|6VqJCQKd>^faxC&^k!k%a7;K4MYB?yH%2bC
zqMTYu=t#k+F2p$dljY&xw&>^yE27)^p~Uo8A)?`L5oV<Mn4+)j#ZNT`3dU9m2=*qF
zD?Hf6<W+gLcXGcRQ?&nH0}O?IGs`*~`9xm}?@NrWUYeVjqTuMra>3>bRkl1P;Z7R-
zG-mN{O=LqWe$w~TrV6D0Ed>;1zVT5}u8+NPJZh<&rupW2D(M0OZK`V!I;V@>kuoKS
zyP<MSrq7RynIk%$c#yhMo5%GtTx=Ry^W`eBO54Q5SZqgmGqRCX4gu#47(&x=DYN}G
z7FJ~Nt)AobL}vyvZ?3;{B|<-|-6_Z;SUOp|?g$9cEdZ&vL0%qu?aCCBlfi&$F)zi)
zW8Fv+LAR?1Gz<*K#Qo_Ig7ApX%O00T%>e$$5_ZH)+_yS7v2i&G2n^8F(i+a>4dun2
znVHEDa2$oR?gDE|K>@VcW+dbcyFfmf!*OH*b7n@JPwxtF8TQ_jF)`_%egGo$fdm1H
z*T?*lG77e^tTuJu8OGeay!%Udt=mC_l#1za636`JW8XF%==xwWv^A(w9WxQgk2Cv`
zHLvL-9r!&FNgI3|69-e!J|IXtV?9?=nkPnQw{z&$OWB(^mTBUh5|I%2LZyoK6Zq|>
z#ra}FbsCSiWakc6TpZ5b)t=qmL%3t2&BSyn2Lr)A+(OA&BuG{bce{tKe)46p*8D(Q
zhnNhlr*_h36@W1(q#n*KXta1<v?)C<;mM}3m&pWOHHOY$2#DElMd^u+P~jThT_4vN
zo!F;*;fyN#lHO+LwGtCvb1_9RmBJWL(*@O;@HGj(LgOWb0&-Mk$-wZ}c$-r!Dv<bT
zd{PBTgl;fgaqu*eumd13#kYs9u40?JX`Id7b=9x-ny_hRscko@K2l#t*zid&z3z|;
z;4s`6j@Vjd_~olp0ewjgH^=E(6SDbu4Ux*9;(OhltecI-m}za4w_wfMyyD|aa3I$r
zpV8W6#N<<-9b<D@j64788x3{8!e_y)8~6~AGtV-R7uRZXpy&&BJIdXesudY(l;Ob9
z%5MD<;tS;Bs~wKyF)?dPN)F|ZQnm>@Czo;oW(j6acy1>B%tF0<Sg*w65E(MVP%o4W
zEIl~_i6Kb-=9=uSzkb{@7*jxeE)JXqkfL+j+6FrjF7w*@>V>xZIfNTDktvDZ-DIKG
zqUPlE^TICNs#+}8oxNDi&^DE!aBZarr*=rqPNUAfxdv#@$!7!Apux+>YpEiHXImPJ
zCMw5Y1DI@cA66ory;8-_tE{5JT3sdacE7W2Vob0f_V4!xZFlj&q^}q<>VZ-t2K1MC
z8Q$`y(gPjO9zDH06B)G20CH$*x>%;WxP-T4Z6(@nKT?bvipP}B;=~ibZ~!Y}H(Fq8
z`XpfY!w0?n<y!*TTffrMqpCa^*fcvWS5b|{^m%W1Dv%`v*v)3X9h{{dDHBe>-tZL>
zD(CiZ+Hy7!i;(B%Lj#q<@>qtTLO~CB;OF30Fc1RuKt6EGwaX-)M2eT{%qK^X$3dLn
zOTo8aGdf!ct{x_ZgEL5hzOvM)D0+7yo-dQ<5hScO@TzS@-|Gk+AWcBblB6$^tppKg
z8v|<kv(wWgKJ%RBX5Q3XoFy{A=Mk$mnJv==l2&*&b-`+TIO356+ee#@h`F=KOaUNL
zW(0)KZjW~@CIBcb5y@e*AiA1<yxh#7*I=+XnvO$0`N8u%_l*t(3$v0z!57duicDCo
zv{_Lk5l@BZc5(IY=#+GIMMV;alS6&kvVY&i<YWq$H_^6>NFb&Q*v@RG=1nWq<GRe|
z`h-EFq0q1g9f<M~aa#;`1%!^KGdzqdOcaNP4pkaaEgdiEwz?ZD+V%UQzDj+~f37Sm
zSVxO4_E~+|T9%G?=ZcAo0SKg&DK|c($azp7*%xUkiRfP9w<e;afP4003r^O&8x>5l
zgvB~nPlZ>t&7?YZ+T;Jex;${$x(NW>_DM9XyOC@WZenJP{~PrxFq{OGbDZ+TvuJdX
zl{G!>OF(cgIiBL+HWhMBlwv<w(7D_|&Qtfef1>juRB~n^GM2OnfUZ=k66q7A6=kO2
ztWYrJIh?dmRZ<#U-yY|~Uq}MgkCxIbx<4S|Tl{n^J5_!=zIcK_g}|M`5u@biTD`dt
z5@O6*t0i*Rl%LhQ_X<l6*wcFi@q1<@K#zgT<JF(Jxf@2}8w&r3qZHky9p{Tta_Op?
zS~fU__Qb&P(f!!aj8%ciORpE&kr^C36kLRLBw2P9CYRD(mkVY`=H?b9I`x+SqB2nL
zzyh8d&xr%z<MZW-8u-hfg=*cUB`?7>)V&t7P0YOZdK|Wk#}NCoH}9O)t@vwA!Vix4
zT|-){f6jFrt7haXQ{ZCM*0L8FD1?d|GuX(hA{QfGaK=8~gWaDxFD_HDYB<c82wB$d
zPd<9d$)~qcK74$776&Y%3AP+8<9Si>ZLe$IppSaCea3FBQ1#4XbAC*CL<~)}*tfFc
z+l<#*-;))yJ^%6f+YIJ<*VVBgmkTlnfa%174nJI7`xyB%+FcvHM+QgJdHf|rfg16A
zAzYgj&DvXKzD#N}(97dG7do=hvb?mA;jL1p!>3*87rU37t!lQh1;=Stj860sG?0H6
zz`|Of0GQ;|472C)mRH1FqWG!@GeyhIpzELHy)c(jkDCrX@zbnhAW**4{1hb)Nlxao
z*O{h$@PL@5(an~X>s8ix)H8OG!fK2cf%cSY6-F*Xwq3TTE)n|Sk-IB6;G>b6cgoFn
zOGM<ggb5e}Ui}i+*_$_`(-xByS@_3T^Hks6-R>20#Ts#mkt6V}#qkP16}J?}DY6WB
zwM{o=UGkM2;S9K+t`mdl`4h=W>0%@i?*}5HoT8%nYLCP>o4r-0fAAUgNZ6g9JGHo-
zsY(R-(1~uEl(xCLU+zy>1CIG&u31LC%_95^iP{>_)dyFhBK&kJf?Y5;ZDeFby3%a@
z)227hx=Wz~$;t0|9>Zu*HTE6p!si1Q+FmB5Tk9IrXmggB3Uo@N<Hlp}>e^0Stg{kL
zbo+cZ?gUy-&<u%>PR9P&EhDwbz#m;>?B9?m@}uU1_SEjBYC>#08!RR+9*=W-c<0Pd
zglrlXVyoxRIL+sF_iK8;7Kucf%4gP8Gt8$8iQS&x$`q6>_eOkXwc0btKMamkVB>(%
zz**gT^r1dc059%3RA<hJ?g=x3c6%mw#pS>qLE)cQK*P?cGH0!)vk+()csW{Fq=^NL
zoMcc_iw`VgPg=Fyy!wNAFr76V@eGC9NSeqX-Z&0PB;ejsm;?_}nr{*(p7r<lFNi#b
z@9%v-o$4aXajId@mEJ58$@$uG$B9}3Ffny-RbtHDHt(mc3m}}9>O!)^;iC4t@70(L
z=wvvJWrHeHgjP#~9x%mrcMcE=&)^vDWZid~)mV9;su)XEDS170VSUK2)uNk!xi|j5
zm{a@tU2jf9aG|tZ+(7K9-hNYjyQDOkR7~Os@Q<xm8>bc*cL(z@ii;@<X)ZkeQGF|h
z(n5<L`gL!C_Q12?0Ux>U?iyN{YTUn;i6UyMRc1%qkiiP-R;{@>xK{M-XPP2&oX+c$
z>50+a^U}UuY|}FO3|^&S)RD0kd?Y)dJqhcHWhEtZGGFiKm#7FKT}X$3j_)7Im*n9M
zPrSk+-STNXj}JZ2{{F&Bhy+<HEyJL6NVHPro!DwO+9|6j48>1>urUWvRVTKq9+M5;
zrJhU_6a_j>J2OxZ-m@v_Y5ylVC$%%EekCmaTNjH%3eOP#W19VwR{|9KoulCBk*>N$
z;EOy^m_ZK<MQ(mhT2xd_LI$J!CJKMEOJsO3x83RZE|Y#59mvp|tRo~mocOz0MO+-r
z&&_ejz&$=8fsy9xnGqbfyZw(g_gAH*TCLtn=mymko$vrmAy8#QQ8mhTDrY@_uAWK9
z1gINdULBEnKfh!>3GfN8iGu;IWzrM0viqI|1;zNIg+cK7-Q^-+{O!T_0sQQ=al;%F
zLv0;L@YJDbB*KrghLWWSGzkLPKNAY`@1fo5T^nbv3_HDo`gAjnM%iCzNmMhF+#Q2?
zaB*>dQ6Sj7w{}w~Hy+t53aK2Bf6M{^r*KgtnMKg|$~x0l$mdSW7$n9m6RWR9femzu
zAt`;-exv!kUpP}VLHnHpG^3hXn)eSR<j$Y+eb(fT`+4R%y!(52^IC-?v!o1YtpC5i
z7w|6DG|PXF%Kb0`k%5VGB>QV`A>21VE)3_wNLhJ`9AXHYo=);1DV=V(dBIOSlG*;1
znwx@wmgj0r7upCF))o<Zrmp}T{yqMFd&kqOJP_C$j{iOc1sBD?5~LRP7VJacN>(-b
zaiRDDlG<7%Tkjq+O_{sok=gTmZfV6>Ei-8_9|VI!t~UR>3~ti$656bMWV8&eFcQpL
zDrp&+$iHEX@rV#=nn9JW`=GMvB{g3JI&eVg*X$K*Pc%TIIv?4>66}ZcK9zhV%9?F-
za`HAQj){%o7ly~`_BUrV+?Bz6;)=6I6P4d^Z_@%=C-Obcc8H`EM&gpD`Rl{&Fma{W
zdz1?qWVF9hfAf<j@|nj*{KFy5r2aaP6nCYvi~Lu67pnf>FC08z{MWv#>F)lL{OeaL
zIw0OPKKQAlJ?!IA|DJ}3S2}5#NBsZa9_|)<e8tF5PS-ahIXS8^*{c!5^U2`Tm_Y{U
z{fW%`NS<H06a=6IOO5DEgp}lW9*dX|hdj4(7f)daPhqmiL~;rS3i1)qr1;$v4o=U<
zJF5SOv$KwhdTrl5777ZAG>C{a2uOz@B_Kn`&>`L3El78F!_c90cXxMpcjtNBd%J({
zI%~aWopa`oy=0>^^R4H(<GMcgCrU+0Nw<e2rT9jrwQ^dH`FDNL-*^QV=Erj4B;xj`
zRPUrAl01q+%JK*S)Q@f`i;9b-hUs3v4kIg9cXsvfiSKx<lCgl?G-8=(Le|gxp_`eg
zo0LdVo_lF`+;DAPW>S)Zma%<GysL{V_O1&X($#rn!GXwSDNU@U1*wPeT$N^SV`Oh)
z>*-;C;gJk=!Cu~fPf8m1m!F=Zqr0oSQ*ytsj$KN7d~0779elF`OhAVC4P~&`*3O8{
zG1ph9S}5~=14SoxQqFg8S^4R$i^Cm1cj2B69(2$9$2P<qiz-kp4m^>;TC+nz6p0%Z
zD@HA4qb(7CZ(sD2oDF@0mF<84F@LlZ{jBT_w4DGUe}9aVoZJmv2@@Vo%lKqjsDKa$
z2{i#^AUC@pNBJi+69EPPKyFG-zF_U41nr@l3Zs!o>Bhu`E_Y$1XRJ))T(m7t)BdP*
z8o{N#9viKjN^BrWJ#*k^p@Ce{B)(%V3-C+HOxDhEp<{f?4cO)Q!g<>e9ily>F81*`
zf9nw9;<>)T0Ak812I&UuG(+X9$%}kD?n07$yQ%jj%2`om&y1p8pAIE*T|fHkzq~&7
zyv=E-VHdUV_6ihTBe)UK;qNy_Wh7+KW^rF*M1=S3GmeaBJTBuh(UdgLNtP9m7bH+M
zG1b*HN30+3;1Ur0_08mqIV3h&R#s5rvnq`fFhgC|{^gx-J@Xuv6&}dV%zB53^+r^c
zVT+M=MC#QZ<B(Kv|2*!iH;E)0jEqBJ_hN;0H8qA@;&QPIhO91yzdk1vT|M=HVU8Jq
zr-qV}SBQv|GB-V4oC4_)Ix#sTDU(lBuST+*WT?Mq5fRMcx04-?OWy4_(Blq45Bnr4
zEV6U?kf^B0!j|O<;Vb0hkR<S+`^Pg7(ok}{{QcJ_fBYx^qvXr)_xS7ee@P5^EcfRh
zh-VNq{N{rEetoAy`cEjykV@Tyzdr8w@3`cNL&CzEfB*5XS2(o7<JF%Zx)}bi-tfOs
zPGT*6+C;w!i$X*NMY=os`m`73fr=3Jjs_4jvT{;e{(Q`h^=npE)+PU_hzL9k6e@y7
zU4xwNj;}(H)UC04xAtW%ZEe2Rmcc|GMO77*$Um@@i+~oSpFk)Wfrie&D2;s~`^3|o
zp4Hzc<n3?Y`|sBQt`9VXf`B$A1YinomxW)P5)lzyeERe21`{IV?=V<FTLY(<lrs9i
zr|3poopC8KF@%8BD>CSN%ItS*cmQJg>$SlAnzEs*Z%t4zWz_ncE^~5%>;HV6S3-aO
z{J(Kr{_`aIjKYrvv0etoID{Sge=vWnh^MV4m0`g5=M&(P$?AW?M{b<>4&*W*|MRhM
z-=EcgY@nd14Gq!UL)K83@Wt_BbXk0@aco{VUlZWtlM?9s$g8MXHcx@K_T;>`Kk1S&
zwp?Fl`JmXUx#Cg>5>zX-+SaQ;`{(`c{Z(zBt4UZ}Yi}vi244AJN|F#u<&|e;WyP~w
z%PA`dRN1l5jqO%bK=Vv5o3Q`=a(CAC)hOqGd4pmM-ws<RRcxXQ3JdQ{rJegi4Tgt?
zMW~F5i;F>R>YKs0TDxoGhK0pdN@(tMa_3el?!@8p(o$Ps(vIYGspKfmuy#+NukV@d
zy=xmjhw=MQO}&aXSvHqlqa(L>&FzU!@GR1%K%H^f);mo{M|b3O<>43g$$C?5TP_<q
z9VlC%OvB<puiXpF-kqu~<l8>8UZp(8`xyP1cAlkQwdM`88eOj#=-g~G8FqDbrMfbh
zoU|E?n-rP6`D||J$ivgPNh4P>0t})C(??!`Z%{cj2nbRb8i83>G?8g|F57$<!$@~i
z7dp^jjaO}deeu(z#&#2OEjp{~u3&{5_=f&7`+K)PSDY-@S>QX2I%!&>J$`Z|ah`VZ
z_43<>8#rL@L=|``>Gh*_wo}6kc$@6c@vzX)O7w1Hner8WAKhVC=E>FsLKuxo-B7ho
z5VjPlYOQmac`l;p>aL-Y@vOBF@N1&%Rm{R%K3N%xxehioHrLiVVe}--mRaRS<c=Fp
zmhoPo?$6XR>+d{PR!+cEWRAhY6-#1eW@96nSL*EO7^oMUN!pz$v*W6t1Es=3`Fe1Q
zir1+t%y;2?b#f!A#`30Z7Y0yp$Vf>A?)NxtZTs@D@uo^EK}j;P_UTb=NK=Ng!x<~v
z6#h*8`e|G_pftP(>V<{YZdrpdQ*2tpj?8}5s?!~*{G4MT2ml9AY<)|@{|YvU8x|Uh
zK@&e;CL$Dj7hR+D@}D~}`Nh?0`77kSwmidDhMB%EB=kDhw4twi2AO*@+IxaR!ow}I
zRRY+6)6ihllGS+$jaa<d3rSDB{_XAVC({EUE?CpnMk5$4fLZ|aGDC)xT|3YK$H&J5
z&BE`?x;uA^(HlEg<CJL*^9Av~SP}<54hECi%>;GAr=bo;rJUR>vga;KK<;oMG+1wP
zst;uZQUs0E^RWWx4@pvMcc109uV254w<kYv5)t-q4}4o`bzLA3bVRdwQ(26TwzA2K
zbaF~g=y1PCh@?3`QEy_RfT5w$49cRH&bJU=3>xLe?nMcK_Oso+ITtQGAfJVqQ9v!(
z9QNG2u?@!3QIJZ=b!LGRtmNbbTt#eL?9<KJu=eGAmFmT5W={LlmCfQ3Chgv6egpr-
zb@@V|yuf&crK_*r^yeWC=cs3D2#wTi8`Ca9i@7F@jz;4b@Ug>edhxk6JaVFfg?}L9
z6VM6OU0r&39h-Pd$x3N>v9L@O<DtPze6(C{qf*9809gl+2M#toYn-*v*UtgI^Vh5Q
z-g0*WmODc~aF0&6nGGnr6ROXOY6(4&)jml>FHt4L#gkdc+15BqOF-~cZ)-2Pa<X-b
zyOlvuWBB$wC$WI~mXfBwFe@^mv%b_6c*u8zA}D2qU(HBoQAhLg@$nH8^P$kUS?lWS
zACZz}1@H;t6F$4s)Y6)~#?YJGRDJZw$y$?;m$%X0`^&$~EUn=}q@P8$!ePoiwTu2g
z-li2av}Dljp3!H^3+n+Kh1z4rXoWJ}K4b}L>4DcR%!W`B^RpX|@8265A6*;h=`op1
ztz7j^Pfbk?4Gn>NdsU2EG4Ag6ii-JavcfJdCkIg^`1+YL-rY0GNUE}r%sO5`u_!MW
z{q)jqJuU`_VZieU);F+#iTDS&tJ<Gjbk1D*;V|oOTpsQ+bKaBmD$>745S!VZbGjOD
zKc^%%qot)qK=AQ|hv)0XB7{E+2nh+XE@K)&LFo)SI5};xr}^hPHte5wPdE4qYj2t8
zIHqE$AP=9uTE=e=PbCS!)z{T!cf27Y^}@u*2bMq?-&A0`*d8fZ-CV7;zRlQXHWo=@
zJqJsxAzykR-V`w@={~1zmf9oPu43J<X`ZLq%TuLs?V|BhRZi<bAK~OwkLdEnfxGW?
zp^@<Fd^uAruFNpaJ7*wfveIFHnRE}R2>QFa^u_0)7qA{-XNOZn#3Qi7e6qdBs)>(R
z{azmwL_-KaUS+j0k5_%BRO_s9SQLR)8v&Z?n{)YofHeTR(BMwB-sqr>T?Yq%ea~$6
zXTK%;<SanA7p^us+xCK^cjinD5*3@X1)iqxh;XoYRBO+|gBuboi$ez@+v5xdQ?|37
zBFzE;Msp>dbIQ|`hvel$BO}6M{kr2M<;ZBKdy|#D6D_)3C7^w>hxN&R1;~UvI8$Xr
zqEdL_oi8r3#qM2!Yb#$lHv`B>Q|O2Dg)#-DGEL?ytLqGAeNfvF>!mYAclnXFhNqt*
z;i<G%(yi(is@7{wo6*Qrm*qQH?{6L6HM<KA10FzXVPO<i#jW@acDI-Ix9hP0Gcz+~
zhZB{bx_axPcuaZ9KtulbD;)YenrRJOS;hUPq16>0JWJ6=UleU-XcbK(6+QoZ?`k9<
z*bCY(7Woq4Yxf*uf6``QX;P}MFCw~rHfZ<X(2R2jbF2YW8Ir_&xC)0@>H*Z`EiSW(
z!}_7~h_@OnTIJ8?(?E0j9M^1LA>>}xS~!k%eYstX(V*g4`QX3tgVqd9jmN7y$iyE|
z-2(G9UO>g4D+71)@jqjf{~9^|w?OZ|;_OHkH<$bWoESK8X2`QQ|2;k~c@M>Be~#h*
zhmZIF{GG!vbkeClAw$iqb0qR#Gi&ZQhK)sH0E1IpvF`2!$}Oly^{doeZWfn&R#7mE
zieTzs>utsvza$Ns3I@^Y-?e}MydLDq+WT~nszn7-Wq%^|imA5U{mEVHk91m5?(QML
zVeW#BhL)O>llqQke??buuF=zJb9DNp*o^A2x$O%Y0ig3QE%VFHCO{GshSb@vTHAgJ
z&+`}N=l4u;Rhb?WK|^2JgfZgU47Yc5ck5_rt$zI&ur+E<VM56se?8NOrvO@H|Aunn
zXWr=FMoqJCMs67~ze#AX>~7De2~9huK?^npa_k;05@2J;2#Bh92Z>2bNp<$EwYIbk
z;a^K~efyc0muG6vN3C3|p{F;MZA1^2tE`P^;189Hjv*r_2cA5uy`=yN-fNtV?Uj`k
z&~bBauS=sR2}qB!-s8|#Gp2JM;Sv-?xbj}kq}gRPRqr`)-g&H8s;jG`!G}kXf&!>X
z40J=lvWxlle{RKix$;*s1q-jR(NXcj;y7w;S0#ScB)GXb{xSjE{VxXQ+nrUR*}D0g
z(^IRJmDTs}HL}kAq6+g%`RWb<+h9dgldLw?*odmPa=2am3*T(ejOtjSY}gRxR)#FF
z>tHdPzpGtYJ*FaOg^6_YhpP+<0sk@HG-HsrH!>n}H?tNn=i=c3eWU6BgtcVqPvk;F
zL!lH=HZFIOyH0mU%HZPjvs;%%CIWHW@OExQWp=5@Bqk017Hp?;Zj5cdBR`h8!g_nI
zOj)2n$-?2Ti;$2o3{Uh>zOF<_Rv;|&Lst$kB59`Aj}uA-N6|CUJwpoWVAhJ|k(Ty%
zbw&R7(Q`rjWlTV1r4OC0Sr+fsMtb=02P~baS2zGM&|*L3)2&(UFe%db(1_{J;ySB!
z2~p(b)my7?^#!y5k%P~kyQM_HLNqhhMmLX^_dyu5CvjmP9}NfNa_iKg+(E1@V5eW^
z6f{K8ZoZT)K?$0P&3{w^sd^C}&eoPPTgk}SP!Dr_R(5t@BAf4@M-iYTXW)dSc$LKj
zuKl9++r@y9Nt)a;9=J|c3?BKR%phc?rk)%Y%WBJ%d9r!%QGmNE{bP62%oiCMep_M0
zN+7+mv|`Br(7O@zzF1`XrM=_Dl4O2p_OC`v6V<X&>oFZMRY-MDkFfE)LugDyE3^p!
zj$R-l7!4PpOn=H!9p{;@qR?mgvu=bls?YLt<Ve&G4X+p0+q&dSPWq4|DB^Yl=f0d`
z9KBmLN&wR7TTUk}lQ>RJh?v-X-L)y#w`bEr64HPORkiTT6FAHO73}Kvsn{8@*nXi-
zpDK9rQUzmTvEF`m{!CBr=Q&*O6_hkQK1$0lp!Mg27Yg4QBYlueshI^bwKs<Ot1Ft%
z@fLfl#hmZBl?p3kXcY;%=f<u8-M~s;M$0RzxTwPR)H*6K|EN}3MWw){u&*5)sG#8J
zfOu4JFxkGYhDL9F@4&>wH`Dn7(tc$thl}ve#UNJ8Z#GmSNcP#P{ee*hv+~t?<wc>A
z`U<f=ztn;XcB7Y+D%Y&n_fQMUt$}fXg5~3%?<aotH9b9p{?CtaT2KUIg2#V;ytw_Z
zVA20vI3pIw-Sfgv;{An52*aX6dNq%Uu)g0jlXt#h)kDD6<Co#*kwCsC`uklQ<})6P
z5%l!*`G|H1_G`j*ePG4r7lQKeBhvmuJ#Cohoq?kS<q#5|s4&8i#2AY;Gfy$HeFHKY
z5^}Ex7cRrnkw58z)9b0NG_}%+iHOV@B8Vf<gVp}I`)-I^5P!ZVuZ67WK+oCf%9R9@
zW+XbBxVq-PC<q{l=r-P~YO?Q3aYd@yj&(_qYfN`lvULt{iJ&8(YyK&IxOgl*%In#Q
zAHV|aMMxq0jjf_UE-jqa=z+*#L_U#nclXz?D_FXaB^92(59@n9*C8}371cagr7=nU
z8mpA~bIntHI=##Q(S<(??ZG-FNdu&RrF=^C-ncR}@C5Ph*>rnOetmFaj7T+geJ9hO
z<>bz^6<+SfMU1m6dV)LT!3FQYp8XYy%X}*@{XYkJ_ptS`oF4WK;)l8vc1m77_=T5h
zMr6CFp}i}+4gXxf0|D@PT|H|__by1wlX34F+&DecVi;fr!gI)fwosQ6b@l8#!#my?
z^-yz5(C^v9OZHEmjj&cAF?ssW*ZIz=u-PIB7;x2RJKLi+$-Gb2uL9!wW6B4HyW>1v
z4o}Q;lxn|(;efVYqSI5Xe?A=!&UFakCy<yrf+n7p5QgKCt<!Q>D@d^9E!KujKPkqY
zn<Ub^_yLmGU>Jr{jlCDH`ASP``(9y8(%GrvLf2_^%Ntfg!sFBFpw>VP6l@NMLAJGZ
z!zt&DW>T89`>xwo#edJ28VvQ@6L@&miRrl5Xz}v+_?<j#sqsSj&S#?yY?dn%6$oJh
zf!OnviiLZ%SF<h$!A`Q}iB5{;+ao3m10Z+mMblJ?H*p54%Rr;yIt!4u18iI5J}RhT
zxbX?$G8hk5$mjBU1xY?dnkn9Im^ciZL;-Tzi5w$=t*@e@iRIsDt%fZ(MoUT<a9HeT
zT0DdzCnE}L?52?^72CfzaGfawK*q*MX{I+ZR8rFMY)Sd6+~ebW)K@^ea;vj8&!x5z
zv3>sM)LnQ*hz{@c#xcUu_0DFVP$@E$7ZnW*k1{eby?)EhuW+@PMw%)1=2uBca<pD^
zMm|906ett}M2q#^j66^oaoC@mOqGNjD0&9rOc#jc8Ywb4UayU(iad?lf-2|8E~@~z
z%M^$O#|xD@)XY5tun38vny<^%N2j7ECYA+|f!5e^cTi`2&k1<3f+HjEPB#78w{?n&
zitss|*__sHS`IaIR}{<lO7vzWTS9^VzD#fOV53tAnAJmH>8orOXYSW}^@H3F)GL55
zT)A&5-hrIq!_g6Ad3Z_5Nr`_>pD2>D0TB^NLZvAoD{I6M!#X4o{2y~d%&Q^5hys18
z)ckB?4I^$|ARyzS!T;n`DX>1)uL5LJcL29nl<MXfg-iu{>4_Ef)-H!KyvibceB|>z
z*N#XPmZ!*kJY`IgRIwF_^^TOF&B01MDy|weM@dM?VcnGqa1$K0b&#)Lf!0zkO@Vl?
z7BJ~pYz{N(5(D${g#AcPg+*R0qrNWR{~X!7tf!a5tS2`;G}H30Wgd-Y$P(b13TA8Y
zao)y+gkb;XtQsZ*^wz23J16l>>t2ACLB!+yz)nF(PtV9G0)@t49CUOFm57cRPknM8
z`3`tpx^udBdN%+#m6JpEX9YfZNtS>kSH`qzZ9E+x9bKV4>p69bbBfCX3~!j1?I|NI
zLvCzuc6QS=)U%d1i*<IV$}*4*40787aGnJTr$l6CjsqDCnP7@dsqyGi_BH(?%G=NO
zGwEi$tgP~Otd*d2;T>HbSH5q#KPAt{Cod?Nt(v4FmRMEXOevegwTW(3VlaF)5>t%k
zC$4?6Fqk$*rHIBzj+kf5%8Irv4&gIHXO4du`$(Wq5}v_cE-A8iYoEi>Go!86e))_S
zFvOPmPjG?LkywdA^FE|_G(Lg<<u->|Px5t8qL;uI3qnlC&gu63(YTk#89|8**5Z-?
z46Vxo<11VJKsIxDxpjYV=m$jGqB!(FdF=i%L?%@`8ca021tJJZDQGA2{g9+2uv*tv
zl^Tua-35HQftUgpBd9vQ>b)OcH@SHJ)nIx?^Cs)g$-V^W-V`Fg8OwuE2bKRN7JZG_
zDkAc@$?<&k{y+>rl74SId;C$JfS5`~dd4oNdB$%`_}M?c&@tEaa5N9I=BKC0=aPB+
z+pcUq!u~3C&Z;99zYY<a;jJ@Wv$Hpo*qx@!jX^c~qghWw^aM-ST3g_T5Y1?=G8Gf`
zpVIDk7v9a0hWEe0cKBAHKb)sfTd@C~pfHIO<1M#@gzIi_Xy^(;Xb7NWps&tA7!(u~
zewqE6=@9Jfl$VzuD_gB3aI(K&@2ji0uqAGt!Qlt7m+;_g)YsMLTkWS);l+IpQSj4)
zKV7#+u#3sf`~m`U6<XyL6?3x$4|&PC=|;;1t|PXsS!K;Ny}aD{L1eCPa7e0atRMc5
zc_|cvzSFN-cRSf#o>LrVfOm%!p)xm5Mqg#Oj$)Phx9zF-dcchaAOL}(5hN9ZuMqP$
z=DoA9tXBYAMMHgg+-Oc<)-WIT^XFHnvvj-as5MjMIsUrIcVQ`B5i!{~Hul;&5)$I;
z%crzAB9TPo#Ddwctm0y@iqa&e_)^f%`5|!sxV0LkBqizcJqw*(e_Y$ZqQJ9A?wXn$
zkWuV#FKB%OSgjKkwp#<Ei!`x-8kgtq@0v(WSb_Aro5{kGH*g4aokyP~$Z2U~;vOha
zBUz39YpJ3g8UGWREzFCvJs1m!D<{V)`uQ=_m=QYK`g~ov%6xRXT~<X!rKK8V669Ix
z)oE#I#2&_vMuvwYqQb6^4)aSa7cH_1G9p7`o2&)+R>!`D1_v+Xd?wCZ5uI${a+y!W
z8_k7MsZ*0Fh8Rs(t(I;x18wef$!n|ocV128zNvwUH63H-U0r>kDLs?R@DdcJm1v&G
zi3XPKbK1|<?mMqu)nbQvO2pEqyT~r$NUGL9S?d+P17Tf_>WE=SXBXR4)b?mT74u4*
z>MO#~aDdEnSk*KbH7!tq@zkN%@>sRAgtsTuI~v^e{6ai3H{tkPJ?lb2(5O0nAA`**
zAG_<L0Z+#l7937Cc+sTWD~!eQj*en&vfIXhd2e^J6bbX)KV6@O`Fu-bf*L?61eJMu
zdiqJg*({VSFO7h0*g(w+9PgTlw+;>uYk|V^K&Xn14QL}k2*5zt@nelj4mkfa51s*u
zca_yN6$b}c<1Z(Cq;|MOkdW@b!<9|Xa+DuQRF@eAzTxPbtG3xV80?lUK#vczHd0ir
zw7>0}y$1WAR?Bdn;H-CtZc^dhh>^ZwbZ96JN@pP!pG0_0PEqXE`C5!<LN!KG@K@Tg
z2^1$n!Zf|aZuuAh-w9o0=1a2J8CfkUu{2(BqXBXH<;7L;a{OnP+c=lt^mI*Y3>P!Q
zZh6Ox74)RwFSAK?7wk@VGODVi1hnL=#1WphSB|K(_hXUTz{H?tQ9ga1cyal(xLJ?w
z#6;N8QO3FqSj|S6VqJi6`3X1GN5r2Kt|a_d`*SX8kI@GL6RXk-Gs9vd*EW0a#bdp~
zbP8$T`>=j?QF}7oN5fLnmGh?-@b2Pj*Nbf`Hb0J8SFV0dww~+Xpauyh^~hi@KBjn`
zs-(;!HIG|Gv_Q*m4eb0-8S0FH-MU(b-e`_<m1VC;j5QD>EUzB8tIpP__4Z62lP?Yp
z55w5~s!xMP%dEOVTr-+I|CL`MLv>ySNDE=ENH`TLHI7=KyRx~tDT2f72tY?jZ&)3l
zc^Ckr3N0gJ$_K;2o60Ba=?bG1bVYQ~T$Wt#S?Y?CaOwTM-HGXQP;G@j*>t>UdGfpH
zKV2v*ut+N+@<KLmIy*Csk5;^TEC5g(0bEj0Vg$g80o@pgN?YdMc2Hb|rqz~~7tXt_
z#s$2v937RW>hT9HI2u)pX@`T8hPs3}#)9(m1#;&{Dx289*IEB;qi%ixnF7#OMrOv}
zxhUg3z*!!caLyDZrSc<LF`muwd(N*oK6YZ$`UWso!F{;}d|^cl%<{!%VqjK5ds(mb
zE~i=dt{D*Yy~M9SxY(q$dr~>pi!%Vhn#epJ#XT>WcYcM7I}hWfwVG^sqYBn6At{a3
zD&_x?$epysztQgaZu}>7zQH8|$_>7n9sI_Z5mVH{M^pK|HxQx7{PZ5JuJl9UP7b>(
z!@V1iauX#rXP$lMM^8`or?a@7)&LTCYiU#{qq`$qp<DM}faymXb>C`xh;|iBs`pRl
z^iI{6wLB_xMRsveI?~&Jofc*UYME*6BA|NtEXcdUVZTo3G^gjjbJpRdy1F{<n2pv#
z;VYE(Vd=&4^47io$N@460`kJYPz3#=3%)@MUfm+<4$n#CsOn89&vGKY3)`70H&84z
z##_5roA9Ppt*I$9Qb;O<9=Qy7Mij@?Kin-CgTFD2wEp(*eQDY{!-EyqBJ@=)a89V4
zE_ieN3&>GWcPc~PV1<m%LPen=gW_#e?*AkLE@kR{yIQbIbh)aL5M?_y50KB~u_a8w
zsOy{FRX_TtjM0Ff9}OoYA<DzgCcv+tZm3wf7`KG|oz7&#^P&@PHJwOre09I!-*dm{
zi|~_(2n!ENzGZ3^YE~AC<ND%xSD6~_va%s;i=|7vJTPa4b3X5%YGuQG^2M5~W;!;K
zmh%ho!Wv60N<l9*2?vw(nd6QN^nT*U7Y|U(*ry22=Y)UZzJ}(<YZ^VhOGD7jj0n;G
z=QtK<#Dxj>;#)@ICx}!;1HWin_r(Zce@<Zq+%Q@}))x);aT&hurLNMfygq$anlOMg
zCbnP*CkjU&u>SP-do-x>%)t3+YS9lO)RYLrC-;O#sg+0*r^8IQ-~ID9=F=WOz@Vg$
z6YTF0?Ct36=<4j^7lylc8IoiL>K-)Z&Thf3um5J0QRHU-_BY@TKBXl5^EPmB|A(O<
z|Czi0*Fx=(Yopqqv;Dud_`^9s`=3cB<I*!4Ym*-CAgJ-*YYq2*5DomlmwtQyIw#=(
zUd#FdF5C_f_g}y@(0u<};Lrsc%}O+n;Iy!!R0LPlfKUnH?~y2EistU1sF9fg)6vw_
z*3mh(Wu>DV8tI1P!X~7liHnG#A}1#Rc?l^gAq^?eaF7zXKY+Vn{rl@B=Pj7$f(*qS
zkOae}*^p#pB*kT<gF`d!(}6Ax3yv%dBtgYwdVO7eJzbEm!pK4X5)zW)5;EaYQM~?7
z;5c9YEdmHfV1FBwntS5kGg0B*lV@lo!U*Ixf`aUp&ldW*F6lVcBbRM}C3t{2mTseC
zg9RH~4=C{D<*^Ze9t6OD$CqJyfH6h*z5Yc3GRXLEL=E$EcXoDwg2%lD&4|hhNPB?G
zL^B+kO-4DW%A;=n)iylVH#9bfE^M3~;}M)V4=2{QUq0wlBkuK*b!DX3EArr6*1tw4
zv}0GXW}=~E16+Wyp&9Q7-|L^P4xR|89)K@lBw|HQ?psDA(E$HFl)~(LE2D65OhQ6p
zWC&P!6GK3vLrzTW0nfNd^A4OyLfv;VqB8s-R#geSr!k&-3PwBdRh&>Tyod0LpraSU
z-N~>i-~a{WVhF80TdaSw^VmMQ^1Q=I&-66SyN_}T{6J2Y1)}^ebUeL_y5>wyr?Woh
zqZ;hx@CfwDs0=Zj0$4V|O^$cDc>DFsM4LU%z(Aj{Z$y9^wl$KYZDN3qi&<|uI_74<
z=x9pw#O~56?tBGzPcq+p{j3+C-QH|-%E;Q=*S9DzQo9$YFCu>Dxv0+E(kXd%HZYrJ
zOXX6W0#drsOjV(XUmK|4r>U@s)!VL?l^41=^0*a+hWhw$Uyq4Q+M9wp^h_otS;ufF
z+k`xGj%pl}&@UmxgL}y$ILboz5IoeV;Mhn4Dk?tGONcLGEROz>dC`joRRS<aCgF~b
zPBJu9W4Q=@WtCwBn*KP-_peG-ICW#fj~bxN5@Cd*hipQbf&`xGvI%Fxv|jx+LPa$+
zENxqi9fbc?ulPJ9w<35xebVyuMrywam=--b!dR8f^TLk{3#Ay0m$Kw()w`<O-qycO
z>~2P*P_A49;~)mB_;{~M?Ev)~xTAW60|0G(5=FmCS|U7Zxee%K$gN{N>Q?jHGYLtl
z#b0ZhXym7)TrEYk&;201KHUMk`&dUQM!+i^6v2?-2v|%dLVaj9=xG>XZVikNo0U+u
zi}a4P1aD{Dbc?G7MKwDdUfqT)uS-cu8dR}hvI*JjaTLhF+-6+FIxWnj6C8prpTgtf
zZh^Trh|m454hHEzezZKQXgsnz?suxnJRb)#T~7~zv&}*7lhB7Z_&&Jbew7xG)&3<+
z3>=o09UULlhP&gp+(1Xx)L2IS!9!?OGD6;|PXD3hchL^!R!fJ2jh9=H@t&>LSL|yl
z=UW;9hyn!Mp5PSnuW_zU^z?iPjSr0s4i@$@U}V%{MAw49oA;eH?U^s#ZIPc#4d1iB
zh+!qqe%)J{<NG>6mcO+{Vlx(Hq*>h=cF;j~RSrP^t9V9PykcUX*xxJguQ|M0R>)MS
z)0b(bIH4Lhp3Ce6X{(%wh=+ZyY<`7C|6#`l*450Kh_YTsZaF^Sx9S)Tc9fD_M+Of(
zyBg;bi^5BJ_tYT{XOu$1E3LM7OxbI8uNo8Q8#eal)2CjuE*E)v%T-Oy^G+ASo6u7V
z^lD4PPUOn#hTE-xYEZa08Z7zz$^F`L+@5jFaANmxQApVEP1N3PL)U`~7y$S$Q>e7I
zkxICmsArvTJKw=|;UKX+q@-|n7wGJU86f7U)9RuFW!XaJul%z1R#KpF@vX23=6{ap
zlYTENC52AQNRcp<#G_*3$O8fl-w;=1<jH#)bz_z_lS%6(8WRbK0mscve7LmWx{?SK
zRO<Zdu5q?<>aV6gDyD2MjZV8Z5=3HT0E{1oHi@ua+JM(xeAjf*CVI+@&RRH%FgYzf
zV^MkW-9@Jmi}I4Le%7YG-mJ?_o=gBmQ**uT)lfZXX)Jq=6ac4ruY<~GXR6q>`)5_s
z`wE$C`D7;eoS5AD@Z#|3NxWuAs4Xod12kbVzdk=Y2uk6l+r11KG#fNSh}F;0wS5f^
zlJpmG4_J)d)6pm`mQ(qK1VzAcipxqxP^uZA>*rADZEnt~J`(XiL31~Db)8@KVt#Y1
zV_Y2`UXnb3uQZoxy4^S-E-S&U(qnV$%Sujewx%SYI6F@BRf3yaMP(@}GS?`Ns>)jb
zbf>lYX^?8gtP6y9YqVglL_*p4_JeA10`6p4{OZEptZ#yLV>zgMNtA~!1u-n1w=ENb
z291X2DJT<tV2KTV$Vnh9EZm3rZ7_EE&|IM`?|!d&9W)Sgq1hd^;lT|_l+ctZ)1o4}
zk~VTRO~kY;q6_a8G~<q!d2ha}Lh|7Jj81%qD8Y6Ezn}_B`#lr}6E`V2CBqFD0c<4B
z@Y5$yCCAi2nUM2LqRezYzV@wK-D313bMvDrbFfgKpg??=67QS)uRFm~qc=?rbiZsQ
zqWhR7g-r!s-dS>ZB357zP;bAtvXGQq>R~mSsc`>-haI4*Tu`v4<O-HMIw!~5y&0FQ
zg+mJ~#?q?N+@eD3{ULrnR%TmCNwi##BR3NX>4p2a_|T^C_|gcwANGtDD$2_FJOX~0
z=@L&&O8Yt&@8cyk<<qK)uaC!9KlD~cg`+)jm6oI{N6-cGbJ*tgCfXg!;mtRpiqAWL
z9e7T(VxYxz?NYg3g3k#em!cF06%`>PM?xLu$?i9>JS4AFL_&*;?D%Hczb*sGc2@4a
z;U(x#1!Vk4J2R0|zzw|QEyLUGBv1>171i)97JB{sdi8GYo`V$Vt@<{rlVV~L&iuMZ
zjn9+zJ~_s^;ews|>9x6$0z<m1rC=;><IG40Fwfr7(~Y3&#6Fo%1;d-NQ|?-anLksz
z;(4j3f$ED=-I~k}Fad;DWDh1es+A)DaO0_UtkciR#jJ4&9!}>r0-RKbpqWYn>oS>>
z{pR-mN&--mNrO_&XtR?tGVX2`Gmoel>5-@lKDev@GTNZtjRD4G4bmb2Rq6}4kN&Q8
z$PqBm+}wnq7!!de&cy>a9&J%|NKPbwh|$SU=44tJw}=Qa3&U%e{OhDPTX(vBp6Cy6
zmknE_88k;A)%H^4;NcdVux4=Bs;|o?S9nRFCXqVcydM)5`kG^1Ayyylq@%m@u8PNs
zM|~-?e-6NYndoU(Ru9-e+tS^T!0P799PbC8FFxIc<}Gl+Zry0~^s{CAt3MSEl$Ypk
z*#qzg7#hMNYaJdH;jnxNDE^{~xfd7%yv>9K^ELga6yUikZT{?Z=Ia+A1`)NpT;s@3
zMK+4_jSd832x_NBjpv<ukg}Bqe?z+aRcoIId8f)zyl4B}m4h_mtdzd*cLH<5#(-yc
z<3}t*9$|clj~px9J!b1uxnE`oTl!tPrFh?oDGBona^9duC8xmx|9&dq6gz}P1nJ3^
zv|}pV)8BZK=kq(RtgZ|V(=VZhj!L_vd&JiBYBSOAQWW125GoCNAkv0y(F!Skq>~iR
zCYwcSUoon7Z_$KC6jkglEeYA#`GuChB+bsIxOZ7kPyf<i398j{UrI8nwhD7yM@uAX
z{ZD!ZygNXzV`zf5$>UEg0Eiz&{9~DN6gxW;aThm>Wt*0_x3^8P0}g}$Dq86~bVHE>
zY8o6FS_itu%b7Q_n?Dp7a%pb3`4FB5rE?a@0^jNLpPwDBoG}<$jCGU8VNTCAG#(9x
z<*1g!Q)%n#<4g->FZ|@@08+cn!^C?Q9x$mU^Qa7On&EdqaIu+_Lor)jk}a8CbMTlC
zEGYNSeNvr2m@AG6_j`K>(lgV3gX8Kb|NaVuvaIsh(oLXHM21r41ob5fm6Q|-K(u2M
zX9~i6^IBr-rMO?v`n)99Q{%PyV^+6Kt8hD1$%|a5e>7?>HYL>>>1`@fd-$l)`F3PE
z8DGBFJSTY4)StsY_5d`UEDB1A8cFGtscz<mwl0SGSEz*SiZ2$D2)8~qn8dv!<c0Y2
z^6{t-RSK0y7R-GHbC|RYtmEq)KQU4zTq+7D)Y82pE6I{g`s@-Gk<c5?F}$9iF^P<f
zki>4mdO9Rrpj2-FCP&TH-3f0ZAo<0!8?YXy?QuBPIrY<KFep`RS+BJ4t=WLl6T+A?
zzkZ8PxCDQmzZ`-}GDb9QhYkoaJd~O$dV=3|<3Lvwv*+a}T-cHOEn}E_ZC&<~X3A7p
zunaHZ#~U_hwXPlX<0#`)bCOTNYg;=2+xtQkay8d>mdlKfkw3xnsC@Txm*~wUWe{(B
z-#(`~6H_5}8Yp`L1Pb|9af_15I6M+w0tMoI0=pF(3t2Q<B#mn4vpSSd)_VYQLv1a|
zm;aP@orsoJ@9ISUq|#!ocOCvMr*o>*IyIxgcmkb~ed>aQy$ABi`O6JXQ`1}c0MUfc
z&4FPtF_XW9#x>eSKdQg_^#lwQ92%y3oc}E)g$<63KZF^+NXsv;$B>m3JA)-$PD@kM
zA9qqrP{Ot8!`(|KQPFEAk?8uSu2w0&8c4TFWolZ9G&!_}+KAuNJ~v7<GjL+U7O|Kq
zKhbZC2gai!!$eOR=d|@yh8&zmpMk+J<TO6?q@f|Y^mL(mO=2plh}g)K<aar}ne>HW
zHkBSkZC@ao#Go(u{Y@?xg3#b{&2uey!|R#JmdpX!2q5aTvg+;a1^Eb{aQYYAzW)CG
zsZ(5ForQ{%-7VTL8Gah86k^ufSNLTLf#^?x*%`nZ(=8vj&uTg})g@ff0LC5(hRA>p
zjbR>@Xkzu%!De^csljZ;t!ZD0MB$vX<Jpn&ahp|kw9VDcsjCwkJ!fsr))r2!!|8%O
z-p+2RWy$&OWPWD53HH|C<9_r98lXbC(F&&EVwkNFQB#)*ohRnx+-Jl1@N0EDhxh|<
zs;a8?I8C|u`L#Ef_&ku6O6^7L1iXmBXbS!50{hY&ZEfwR$ZsXXWjE$(DGA|G6oXY>
zqveFCJm5O~@<h&Xl1JX3w2YsxT_$^_<8!7Il+UhZL1oBoUc4$<&BQ>t-q>m@<Hr|m
zZJBaWDw|!-?9ANL#V}?k&x{OvFb9TO*&-|?1Z>VJ61TBnSjzDwPH=2&WNc()bNA*%
z*(R8gvS~BSrJ5-)&LlmMB5N}5^ad4`lz?2m*j~$eX?U$5XI1hta(Wr`>`n^6T#{e(
zOb&xpz@Hvv)8W*|^Hr_|aP~obvaop@LH)4AXmX=54AT-0XjZm|QeeO5Q7SdTwry^2
zer!C`(Np8u2bVD#OlH_vbkg<Ns0C4;)A3%Ie~INP1lck^O^5+NspD+kY|YeF)+P3V
z*>0OWBG%SrK-o0^c2`SFOIJ;=kK?m#7idCcTIvo<tBO@;@#&7{eWt2&tEowGH3p5r
zja@X>T~=EPI*PWgrV_Is3afaA0Oy71?0XFe@jI3+R26!<h}%s2iVQk8U<8{T`&%oU
z-HFgSo;X4hrq7g=-Ibvl+iOS@v>u#($nV=ll@;hrUOVJ*+MdK06}|4|M1Q`=X)oH%
z^Gn(5UOSxOC5?*R%CkM~{mD|1I?{`|%JUPyC>jx>4<G0N=}o)2EdI&4eu_aI@VT>#
zP{i)An)=d7O`VU7NNZ|cs2QZ>emzkUsJ?2=wb}Tg`wUOs!NwpHmQ8J+6crXG0ue=L
zr(adAK?M=qg4Zt(VK!k*t1b~Qa|#1mSU^S$NfAcBPgJLYXx$49|FmetY=64r@mKpi
z)1}X<tvFr~J;!AQ^$s9_A50Ul+8RL#QH#)RzI^)FaIUBn_+ghG%e5MR5^X)QmVOK_
zjkJs;13fJwU`@m28s+jc1Vid)bWPYlPlgvKtADgAMnM-*g#>5iWaoemz{{g7xxH@&
zRH-P&hfz@(tm+pZ7YQ1<8y~?V?G5M3w)&!zh$ZmzvRUr1gK;o#IjVf3MJ2Ym<5>af
zQhzu{3)tCl8I8M)R;J7M2I}c`gvZB+kB^S(%$C<upBz8OySO}F=SRZD!p80F>~uOj
zNw+F>=uf=8KJ&H1lWoBWkBsco-c}`Oe)xUKo9#RU9|aMoMeq4QW$N;1+<D==^Tz6J
zfGU9!GzO^{5uAg|UQXSmjR&Z0FHTPG_~nOovI!k5^>`5;I=#QevA@2OxS_SWdDZ2w
zyI_lBaq=C^H@dm`f$bcSsTg>+sx68=m}?M6k6A!Ud~EPgNDwl#Kexts40i0}y<45L
zbJ~w&3>;L=jeW7#x?T0J!$NyS0y0Ff6b3u*Iy(Jk*~(%;lk)bc&ha>rzvBMFPDUGp
zm>aNZ&rh!S!@AB@sE|%$!n|y@XSTqsh>~;w9m|LU{Zrmyc85cLNy(!Y+DDn9SU7J{
ztcG_{s(*r%NJHQRwhEgg?N{-W`^~SOloANQAHBa75Ti*lVK^8#JO&ywxq5Xb4`VOD
z3aLmR5K9UFX>)G<p6Qhb-6MOO)aFOEgA-p}+UJ%5;E0|C37_fb^=`FTjnfUHb7XBk
zI-U@jx%%VNf_ayt92MBZUaWu`{lk(?R4<8%la0-DnOl{*ORm~x_|s@ct;cwqK?zk#
zrqxpB;{{r2dZ=DiW7(pc(FeI61(!VIi60SjKow#G_4;gQ;hO3@p4^D%t6$@_hZi?j
zyP06F#i03M20OS@q~2Vq43s~5ssM~f_zi`dNnujbNTAX8VpH|iw?PKIuJ`;C%NRVH
z(03ZAvM^b7Oz3+lBFEI{oQ&eq(hQ(e_3`7u@i8i`hib_p7Ht`xSJ#B$N_ax=@yi!w
zMGR?sj<QhfM!knLapjJ?fe6D<ds8-U1)h+D`6d%|B6|9;I}r%P42*3mC>!Dv$8n`9
zSeK&cR;;xzwceeQY!Bsoj?0ioW51F*_JhSjU0<Khx(ACXec9S~Vc-=uHa22T*7U>#
z3l$X=9bL|V>x|_@gMR0bmPj1KWSx^v?G+N4x27+l`tzZEIHM0}IS;trc;Lg#&FK%`
zK%gtF&wi2tWk5w@P~m;H#dt=q^6w#)(G#{P%ZiGzzpV5@4T=0)>P^Rlcv2wtPX3_h
zRh8i_=A%c-7W5ijO`4kNK!F<eL;$%fZfk6bGpcc<MO;FHfQ=+DL7SD5{;ZZ^EqDBe
z!IwIJzzV(dA!aBA+a#@<!*&TH<H_Uxx)hsVs3zk%w2BTw^70{WiCG&Hj=8X$VpOYW
zENpQbb4boXE@)GZ7RY;G_>RflvW=2=FKhcBv2P_KNdA1UjzT7tRtfVM9UT=FhWL2<
zBRuy@Hw|uznqrKX{SeP18-{p`26+McJ=li;1R(H*pSeKQ51G@FCA0Lfb=#n^KlKDW
zyFb7heS!fQmWGDw-I1^5E@+ZcQl=FYKv<>09FiGLjyV^Q1h~$cQpHwD#((ijy>~8h
z_X+u28&Z`coBws2iFVUr^(J-9v9XlYe{BW^*r&-@enJ#}Q?K5iRf#3l=1N;@CIt*t
za2tWf;!N`=-zJxt!Y_ODuS{E>fM6WeW+Oa>e(JscH^HwEjO!Z%0P)u!DImNVFM{F@
znxyDKybY%q$pb})PowLF1*ceTvES>LZf|V3dwKa`amOPG0GjynhIGgsY>({}NBrC~
z0GF>GHenPc2C|dAN2J>ToF)BfUfTcVGem5TlKv?zdh+2)%h7-WkuHGm!p+VSCVgkg
zU1D|Y8C5X9J5qp+Znn>1D`WazotlO)%a~*aJ`!L-&O;+3BU2vS+sOlXxS=)?4_H}m
zSUX7x2@`zV4VkZ<garkuEt4xfTHE`Rz=W&Us9|-^w_r|G(wL&YLf5Jv=GiXi!OkT8
zn%7$V?K5mW^1p7!)|(-%V_V>$Zq=4U^I*tY=W%(#iSNVaxU^K)tV0rjEw_@nru;tn
zm1`|>gZ3qRqX~v=Y{)lrRV@K6+#cu4wPuZT+4&ncP$|!1CM|5_(SptBY|G?JE?!c;
z^!*5u#UjRZce9}K<a?*WioPTk7dD{h0HExX+pT_2DYTEPaYjtYX$W6edS7~(zgm=e
zTY1%1R8(moCdm_e8=i{6y>}gb<3pO6-qF#uk{hWwlIcxD#gPz*gqlIK=qU~_y`fVn
zonPX-eb>{ISN=9BS9*<8f{~b5L{ugN@R#eZqwgvRENwqI9A;#m%Wi2iKen0wR4stu
z^@T70(#^o+EY&Io`-V~j45>*EK|cyCg!uXzHbF-yUjG^&)B-5i*_zD*%9lr(ABqw@
zN>s;$L2TPFAK(&5(HMjUj{14;Pjg##3TN-n1m)y99C}TU7YUSNQpgy3<6RCmDOrg-
zeh$&aBoXv^5^A&u?#+YYPuJ($V<r<NW{)BkkzV-P#Vh%gDf9EMwe5o09wK0aks4u<
zo+v9XP2J8IQO?wkNOMzsI#pt5yU@XE-2uckqJd00)HBJs>GJZPG>>K5k5Me_5QwF^
zBb{j+fMtbfl`%@?J%~^b*NO1u<yi~VrR~}7v6Xy%As)!_fQQr6D&+MNpVh4CVwqI5
zCy~S8{_ar(B~%g$EiEgvzh6xA^Ls9J#7cVdDL5uV#DRQ>5{^tJgwx_CoYX5MBosnJ
z-H<w;2KJ%xY<Vce7e9A<Qy;`r=DTeim8hM$X^`Q|OPzTVV%Qs2vtKTSfj}peHm7GH
zgYl*v2JxUA-v^toRJyv6o<iy-KC5$M=b$whF9ei6pU!<wg^>bte9a4ujV67+z4tDD
z_5mUZEI7qQ7I7@MOQ)k<P0~GLDBQ{-9!qgn-8zUSf!-Y(Zb@3k+UW%u03MCW<}UVX
zrX@3rEGhc@ByuCV!ry<t^$h^hV~8jzG8WR@$b+mmWA+D1iSOyeEn}1%F=-|uymNiO
z^bI2?hzHI#_;cN4B<$x7Bj{MlmY>Ri)KDFw;>1>_f`u;grQYLg9lv@AtQ-eH8qZ^-
zkry%95ug7g^G!7sIx!oYn5YoaG0ROV){RZ&rPi{-+s!&?sNcNf&d_B18GpjZArAnb
zl46?Z1lvlP*?(#QW=wB>6_;vV1U+BDtfi36Nlr=WM9Z8oYEJ<a{LnmLKJXBK&!2{h
zvG?{_fp+kZ1jbtlR*O^5*`0(3JFEJ!+SY3QZ!j(Fu$_ld&4Drl_3e?y1DU@Ui1vw&
z=&lmrRRmm8Zf<TM-MG2}X<~ZF`TnfPJ+)$4s(Pz$fz`I;_g2v_@ngAP47soH7LxeZ
zKH7eG4TqL{@P)iQFx35V1jUeF^`er3!qwiRb49mEPpn3<2_ViCe$1##hUx9^tM-^+
zocaFUTIQh%&@Yqif8(7UH{nR0AIp2_g=%F5MN~z8!>S0Aw99Z`LJfO^*CpY}gAiC=
zsG8DFp;qFo>pbBr4K!qL*`52wx+<?1CcB%cN4zVaeZVuKGNKBQHTf)l4od4b_$=fE
z<Psa1Kw9NfZ%?iVrefM3To5<U%k_Zf#}Bt=#M=*dJWw+>mraaTIYSPT*xi@-9OUJx
zoH*^v&6vhTqq#DUr)Q7igeB~47rTu3gB3yXW*Far3kexX2ba#_c8^dbxOS`cwM(zm
z=T_0MDspv)yP+R!K-ExZdsRf}T}j{$Em$~MDt(&I&p&`xE5hoh-Yhd^IwTo7!|Va#
zb~sv7FHtscZ5?#yim0flUNp1<2&PC_#s_tGZX^)*y+du2b-fHRT@(}Gt3RspFaZWe
zG#8iqfdO#~3kwvf3qIUH6pd*!YL!|IZS~*dxq*&*;K@`)#bb&W^OfgcE}GT>NOE^K
zZz7dOxf&)^BQf|(TAG?AWJp0pUjFX(F<_OvL`KBm(EdCA78bU@yJ@X1-_QEQMiE<e
zdvk-sZ2YyhTPAPfr`d8?=AO~i!F~*x<-6|Y<=fWos7&F+FSFVi8DQ$1e~{nt>8-wz
z(WQn(-?Jhra>3vG#)njMd!`162oN2o&c}rC+T*cV-yNM+kL13iQO$>VfB{D0HnXu%
zP}3}R?sf)|(zH1Sb_}O1O^n)$6Dz!(JdDB_9-nA~ge?$k1J&n8XU%$GLdjRUo7n7z
zQbw^f=+9Nm6*!RsX;ults3JqQ4G<j`-_P+yzkEU+zA2nk4SZ+RASg(zwbhu6-L-5;
zLn{=BV&W`*2FN96`?EfwEDGgU_H1B61T2X1MC!A{71}9U6A#kn{O@6<Acq4+2JyF=
zy2-K|I)l-rO7Vq2bycro9I>zkr4WC}sC9<OKX4!)=2_ZIm^vA?(J-H`mVl&qo|~P$
zwsN4rl&^YVkx$hNTnQkB#!m{KDA#$q7zL?XlLr&nW`AmN-Y<GWe8KFLqSCCEnO99<
zW^4WBQ)<v3u$J!X({-UfqtXKrq<Ilb7pSe>z?B8Z#3)~om)FD_^6-F!af4l+dqw%l
zYz~E>kj(5VMkv-YK?wAU{^0&7;un&ZZ#{WRMB{kW9{zJDLGY55l|3PR7W3MeW!(Ps
zbDaz6S_jDV`ns9-$s?=G)(NH+tN9}UFi$k8+;>;&Q)EvZ7#290<(%(9S*EF}DNSZF
zUSOqR4ch79fR8Brmf3sPNUm_L;FdJIVmw><*ewaF@JZiqO$1EiEHN7<sp^@jt<K7P
zg;DypB_<3Q;gGQyqIc`SXy#i$Co?(&%wg@mi83dzxarxo-Z&)e9{d#FVv9ys|KyNs
z;_k=*JPrl1sQII|4GBWb4+=9?%3cp{uSadH&~G>2mnARAsQ-1Ry?M<yda-h7dtwk8
z8jFJ(rK_jiawAdWbPJ?fOd3O`@Xn%O?~HHVUKhqAR#Mz*pK-W|cPm5r;Xvo&VRA=+
zvqb@h`bpp2T{>uhNAnJko!fx}!AB4<H!?g*e<k!TKk@o9q{WmW-P%rygS&O}Ltxk6
zFk=gT%_%y|?9FNP_%gOU`I^qnf30Csbb!WuXUA8}QlDDKM}~RA$4KNk9?ozVem?q-
z{LD?S@It~ud;)|9Ua_<91#!i6uNoNl;*4r7tc#b~U0%(0p}%qdTzl2s(n8$P1py?3
zU%i*VHNxVrEf0Xwz)$FF#>d<Ra!O?!fX4&vPH8EsQdINU*s9p0db?g9^=v|pOKcf_
z6e<R?u8*Yl_lEYZH?g4Lx@gp{sxmsHI+yzF^VjTw(}TF*_30ivAPFF(_bWhrZv6fR
z&tpr`IEWo|aUQybqoH#;9cm|kF#Aav6(6c@tZyjWmt*#W?FH9^)Q2CgB0@sLC1pZ`
z0);@;;D#_Z&-s4vcq6+TG}{v>S?LZ?LH&HpXfCrLgAM@v;oZe~a4?gyU<Ew$$by2>
zwm?!uhFumc=q3Jyb#f(~A)=`uEE^D#h=AB4v%9;KmJ?)A3CI&U6p)_!F2N*0g`S?8
zwmiFrXY-ES9?^$ZG3Zp-F-f9e8g%tyG+q7fh;#(%Yat6ezovqxWhfK(`|;u78?0i2
zA`zg#9eRaFyahsoQCu6DLP-Ey%8^gA4-fq)ekNYFfsgeDH|nF&+!48km)Xnkr{4s<
zZFSujsGB|@wn}Ye5>qwzw0wVXu?_~uQ&4nJ4Bcy{BkbXSC<frJI+vvBNP)Pq{0&LY
zW|Mu+y)z?b>u*lu_H1lZO(utjhe*#}`1%B-%=2jwHpen5MRNipEpuqtrO3Ce++0Sz
z8Sl$`yQ2{f78Z9D_SH1r>oVaO00u`t+gu<aX#+-c`g?egfuyBf8evjUQkLt^h2vdp
z9!CY?b4qxHmq-JHxO;nlUmsY`=|6mkult0?EKR0br^ITo7G!?c1QX^)jbB^S204e?
z9sY)&psH9|we@bSCp?+>p-nyrkylp2-B+Za4>u{+rqkt|k8^P-8?CJmSZ=g1&ff~$
z=Up(g5rzX-_!nY&r2H6PPybkUsVay;Gp$QU88Gt!NYd}7nc6rns}SlSdA~_CkR@36
z)jx3ug?uvdqg=>WL3Hf2yBjKZf)q7?l#6Gv{|T!^c;xbM-sH}JX;+2CAl0>w`cbfe
z^mjg*Ujb-f?I9w9fdZetK@L6K{m+h#34ecKbmAwVmw(3ZG}1s(Tn4yXns&x%`6ept
zTE#hlDqN;Jn}}z-wjzO<qN6~gSZUuqhNo1Rkg&VE9Tmd~$*)3s^zc!3bK~6ITB%>p
zeg6PT+T^emM6k}$wmDo7JziN|{i46qXgXtbOk_L8g%@xdRO;+S@FF8IUd|X7JsLNe
zDzZm%K_Vj~vvoOJ;Ln)R85+UX=~rIx^v7b-9P`ia!EgP=6LI1G7)(CQUan%KjJ|&g
zX)_o#YOuzisLqvWzUtu&s)fWRhG2v4Q%Z({^lfbT$Vo>Q7UC+viNU}SGQfTkd2(3<
zrCQxTI|g0Jv@&ILh=R1`ju^Fxg!%Z7GEX<2L-}QzguhPlGHU1s7?WB$k=w+H{Y}D~
z$>uOtBp37JK_)h<S>Mr<;SvUkm(R_8a@gPN!VB?0Ad(9F3i1+x>UkYmETBP*j*T7{
z6Ox_&j<mO)pUCHA%jD>Ex;%f{x@gw&0jL{D6!?!eJiWLrn62o9$%59d?+xV&-3u<g
zSK%LF8@iBj_l+fSi8OMGj!j(yPk}Emge{>+X$1wggo^jISGUgQ;1-!GladS{9~-)e
zS*3#P*}tNxy@LJKI=0iad~^FyJSNr|$yqPO{xl;2Nc6QAUNV@SB!fqk4$jV3Z_F2|
z3CKs@OupemJe3;0eboHoq*UwP{p=?kL<rQ=b!~y21Py$(lJjG~8Og7OcVB>cVg`R!
zquR>SvSP7aEM7e~ZAiP;^ejC;Kfrq`8_p%h_4dkouc0s|dS7REFztVl_LhH9M_n5)
z1_p?Tf`|yH2-4lD2#9neEg&^?Hz-J#bPnC!9nzh{Fu)MfIpk17o$Y-;_c?#SnODFY
z=JSia*Iw(ozSn!L(_?yKkhYm+4daN8Y%0uB1V^~TiVFKciO-GuxI2Wt(UlwzaRMde
z2581UO)f1zqk2a&%X@Zn*a2=3do3B&XW^zMvGeldefqVmtj+{G%p^TdKioVWgNP{v
zX=+8gTIG5C_d7Z$OBY)94*J-+nC55tn^YavF%A$G!+Ge1TuQ6!HflS!pg^&0tVHHW
zoREaw@Q%fmLe%=cGcU-g8An`9H{KL64ngVp8s@ylN2{OTkvIR*wW9Mj^EUlWMq$M-
zQCD#zd5OA)#Gtj*BQ231sRYlGo}~WHDtb3kI?vE?vv*p>@v!wal$L~)l;{=tvn0)C
zWo_+d#V(vje_DS9wHEja*3q%j25tj%L1rob9eG#V!t<jnpv3}f__L=`!3`0=yE$0L
zGi|^X*vJYfdHZmeJ97BcJsk*ZL~gzt8%jw^j^;Pc2+u;?)L*ap8C=I&yuUtto?SKB
zF*5SyON{;S^3pTlzlAHuoFRUB+0@U#)(fGbDhj3K!fw;c9qVuIxXPcR8p9oT`Hl39
zAV&JV(Rx6J==L}z52a|>-urRk@{X)-9XW9viw*j9j=A&Y4iU<ss&&rmFhkQ{bx;oQ
zDK3^)gRyYG0ypkXu_C(T?U|gnrwK6TZaVq%t*m}uz3Vm6hIL5<W&z{aUZB>RRu?ce
z{lZBkb}}`>#d0pi{H%?c=mlYu<CS=g8@hK<HTHR}WxaN@%`!lh?EHz2UU?XmtKgsh
zvn~3|ay@r<SJzyN9by0p2J~=1!Z2O-1M7var>Ly#us?q4?tCkNhUDa@tCxE#`CyLg
zNK2QNmWUa2`W=zc^xXPWUUXGJr3ftd{wOA63r^cJ`9-x<L9c_(D|OJztBF-5TJLv&
zAfArRntqIkP{1b_#2j|fb21K1ji!kO1Kih=&P1~<ijPsqp|`)6Az3)i^XQ!YXhKjx
zpuM-ZOsVID3KE?-FHuSG<b}kM6$GN#tfAt@k91#_PUU?sNa@3O4}W8QW8*{Dl8=8l
z=KOqMU_h;SYc@-v<Eh8}P1HJ*7H0n-Gde3;hIjih3fV{GG?*dQ2-L^5;mk2WjU1}U
zWd$)gOI>0p{<-{KPRT#0;;{YvviM}{I0^WS-ci2;bAzpgQhe^UBjVE8*<I>))G9^t
zEt-g7F^>%Y9{<nbsiT&Zv{Z(9rMiudGN12XEF3A>0W7u|x21xAa?#FVc5t4-_6f9V
z2TZ1{@XfZ+>dG%oCjL}A6vobe@VfZ{Vq=;;-1G7vMv&PW8B&Yl_EId^>Czaml<T(O
zga?emV0Mlr%8f>NbaNG@;ys-VI*CX=6@N#IE%?<)R3!`s%N<D^aOCIZd;DrN&W)Ce
z6F!8R2UK+s6(kcH3W&kl^J71014ncPO#QR8gO_+olWd2QxD=G=uQ6I*ozH+jVtSXL
z!*5hpjC2>UG&snx#jr7!lf~LnmlniNo=6n3($K_D`s4?eS68caU`l5D^(+?3k+7tj
zIwugy9k|@1*wcK0KbI;fB`cdgopYtMqp#ofzg~cpRPZ^hj7r+nl$KmBF|4xO<}#;W
zRKPrJ*g++lXk#N;^8Q9u2rv)13LjULj>qx&_hh2-ifBe+We=ib*hJ9aU2L#W+X3(5
z1fm1~zwhF7PU(b7%-!-CX0N<j-4F7W;>SU*oNwtgz>_;T)%!uWwh1buXd9GLa#9&*
z#cht{Hr{&SrnwEqAJBSdkC8Q^h1<9P-O(H|O4pbm8ts`{SM-W+X{uMH-!Vwcb;7h)
z<EmL!TftYhirr=sx5zXAlLjLK(dhn>0)@cyo<1XOH99J>^8D$CaSh!<K*qAJ-^*Dg
zY7FEYm(DjKs`Q$H?un}?J~y-YeCi4wt9_q%Fj;=MzbVfpEF>ty3jl3FW&}7wLFr=<
z%4)f=qx5AXM+mY>30Oh|J)RfOibkly`-xof$oDjmUBWax3=A1I9Sx?Yroh=(^4Emh
z=&P`p7&bxac+G72=|)E`b6&Dirfc>tbOvzt#?J7zCY>>t4oFoQW}Rl0>PT2XTeGPV
z^{^Jmlwvhlk^s1Xf7XSVm^>f6vb^7Ar~CPUVzg;us-Ye~=W%9_$XQKDNI;&F9~_<=
zSs2Q?VfhvhtjW>ayMV!vRfFJnth=2-i_;5)CrwaK{fev#c-A{wlaayUVM2~S2_&R)
z9qepuBtL|KXI9#gOK!9~=5Dr1&;&CjRhMv+WV!!W!hjo-=uc2Sk63^Rs%FRj3M3C}
zek_+ttB-0B!^5$7Wf_^7PP_B9PB$NeO6ta988pWLAqqI1)`EY7;->lA*f_V<!bALt
zv9T038+X8p-+T{t1=IlX$SK8H_~)$ok9ROQ2uQkfa8g2k)O+g=t2rCZ7TeI=+_?Sk
zw7iLeb{eGV9O*OwRfBXwfq)r#Nl6@TYru5za6OLacgx`!f}EYX8yZXN$Xa5m`V6||
zR><?kH>5pLTdUgqPIQiZpc9jxyaY%x=YCF`vwDk7ymWL6^tV8CCogM+?v;N9mWCL#
z@iZtbY*D9pQPBgadlO&kS8r?rTUE2#LfQTU%ie-&QebUVpEyfTPfx1d<#Ak67Vkb)
zyl(Frppnbc_C_u(5=89qrN5m4uoy1$nFi10wVfUF6P5m&VJL6<Yi41ClUd;JwSi4n
z8!sGC-mk8{iQ;r_x?wS%7wK<39QrcHSG_)*qQEjo?~vN!TrrT5miFh~SHdv)B1(bb
z&C2ynT^zY-tYF(bP}(O8*@b!hp)lLM?0VJ{PQnfmZON%HF#}mc2Otlk{Z26hqp@_V
z^iP5tyVcct!PJ(l^V<xd!mn3zJKY&}94(lyc3X%=@#`Dh!1!{djv=^fL(kuLXKX;=
zi4NRWa|Gl(R&7h?c1DWBG#GO_Dyo>IY$KVMFg4G~9T%-&cFkIp`CLI)zo8UPF@iee
zX`$hO+E_z&h>9~PCbo~w)D$m=@LVuE=VaWT0p?~(VUzoLtjnc3t$odsx`j|ASN&w+
zz@_PwH<k9Qemz^7j-bHc+#)3zmHNB`)9;wRr<JU)Y51?J@zfk+Yaf-k1eGi;J=?q(
zZp~k;6?pRHi$cWH-x)d<Uu)M=KD~cGq@i!Bw`F3bRBBY6vG!R*9_s;+;;=yWmsFA-
zlL_<Npr4$smohI{o5`0_L#al82FkwnL+`cNAU*plb3#a4EKbuw#Ie$kRf-o{<xL$;
zrpuOff;{$@TE}!TQ~B8U{AJ1cJE#8qJ!$^D%e+u!I==yLJjFEdwQt5;1an8<#oI(c
z`$>16xFKy_8~CE*=9-Su679r5z9uyu=y9rSm@Cz<0!+oPF(0R0epl3*V9=EKqpfO(
zQ@uo^OiZ;{6U5jcJ3G7Hb_@-KThqaaubPR7V)fAOo3k!siB|GxKB~_5vmPr#Aw9t%
zLFtOBh?C2uTMlQQM|*R{J{6H~SCxcxuQozU=Uss?bhbggV}`S!WT7TpJhNE#=;k_e
zeQNP)lOuRZ#GvDC(h4^>drnd4ttU@v$@70b!9W+s`kF$j%(=pEl12KJ?d}fI)6u5E
zUz}yyd}hFSUEhjX$jf?nBmBjapUkBCsx+%4-O|E>h=k;en&*o)z4`X`WIkz`Geal<
zu-x+TYkq!L5giFF#si`mBsU$^D?Zz3@Vu?7S}Hot?gFdvFH{a&!p{~@5&fso(9h!H
zGEi22T3(lpzdzB6xnU^qkbAOZW@P$qGif(QxQR=;X(Ub7_kkkZ$1fyJS7R$SE)D^M
zhX$|XK7LHX3VAgIva57y`iW=kH<tD&{yZp&7!PDc_00>lME8*K*@mn^U>Htmo0X%P
z(d<;WAPvA~dEnRbGFrc^<GpN(EIT#k608UXayK7$0vj?i-e&s~61zU6i%I752<wY@
z;wkdV<7(=0q8+C5Zky5y&+bSHJ}K|oM0tm_O?wArVvYHLm;wX>*@6@hL@3B;RIMIV
z;D)9C{ykN%$$azUL!07&rlz{0e_R~5cK&pegPXMZPQPLBG;6)1ujx|NM??|wwEz?!
zoV7bgTeL|R(LwG9=$Cx@6A4j0brjEV1d&c#-Hx#N?BZe>w|kBH6u@tt<FUT%kFQ+3
zHF&Ah-7Su82FV@92BP|ghF^{bRm(E88&v1~Hocp~fqrwmJy{Z^GcQzCS*+a}7^^=U
zuP~bxmdYb`AzXWhbYpwWQZDNF3gfUp8j-|Rgc>cuL*avkQ-C($*Y1LsL?gEattF0H
z>3U9f6#}?22OZ_&1wzff=|H{pRN$j!EHlqXQd&1=noprgYL7%GaW2m`*^4zDd(v(<
z<Oe>~cFYlzkd(}*&t|Ar8CZKe&qS##xCIV@gxLz`Nz@`of2dvKO0}Y5Bj=lJ7%3GO
zZhe}6SWrJ!3lyPrX%}Z0>i4<M7iVY+9(3DWl2*aM+}WqbB>>m+h0%-eOTi2G{(zw4
z?aeEfk(b8IxP2@8UQglCM9a^jHoQ#~P<priP%sLx`8~cW=*MvhwUxN?!|mv!rS-h^
zQOxiw;Zl6!3v7SC`c`+hRX(Csa=9cHt<H(92~g_koBXqbCT^{Ki-N{DoG!vPnxtp}
zq(x~^)PDeH6$K*Yp|8wAu#qlxL`=l_*1E9ugz|~W3$iFTnG#tUoV0!=f2nFo(2O>N
zSGDnn%aI|gpImqT9^EG{6}*SuZO2Q0+IzXVOhb5db_OD2YVlJ9ZkCQ5K8(CAbdGbX
z%1+4N_%1i5c+_12#MmGW9Q)2#>G)~~z#s7jBPyy->b3(;xKud{j>5Y_Urw|*UbOW1
zGv8`U@0XNRfu74)3)rqNz~n0%DwES3DuEJ|=Fj1IH?uF7g|eKcRHkDnoiVdc?tH1|
zEnp61QlVF<4UKUDRz`)Ry>$vvMCc2wpOJG9hUR1?d>_%KypyBz?|2Zj^q}l-c&wXb
zLdS!iYM0v4rJA-@rB<Ql4J**8cz?InC%>Rzw$TIX<}lO{YVIoLe^f|3GW~F?{jUEn
z4%2zRw=tk(ADzyrCTi8g=DQ#hWU3vGZc3hA_O~S57$xy66}kgrXujQ5aZcni{cdR_
z-Zzm!H85SkXMaz~b>-A{yhQL~D$LaZq8XorD?}gtl*2KtBy1R!q{hL?vGJ-=4;Bli
zPLEpKdovs@Gz#+w)%Em_XYjx`!H&rEKWS7h?S4?;3b(Nk{Ww*BL=5n08kK&yluy-A
z0kUT!x^-3dW0x%+t_pj@b8e>fQ*i*1s1B@)1iDdO1FFDT;F0@pE2!b*0*J(``{%q9
z`RvB;<z8BSk0<6^kuhGl_CZ5u8%(u*Fo44d{n`RyBz@xS?EbCuLt(U3sjK~V1qA!%
zdT4aCjPIC~$d$CKi1%n39fXsHVAf^f=FYSX(g09Yxd;l>I|Fe%ZdR`AJ-)tI0_NXA
z@^BoJhIJ2Wx2PU>inqz><_*y=Q@fFPuGQ(vb(qnx-ulWp?zM$I#?>_>%~mV7L~wc&
z*zm~&tHSY2$OSz`#_om6UBH2T-%`7k0pmCZGCRu*^#Q|BQ<HQpw^+M6`I<}!!hp@X
z^IH?aWK)g(?+}@zMkt}(V(k}tPD5ld8c%^K(x_|!(O1!43f$N#>_#I7>qG7Bmy^{4
zgnr|RMToR7CSQ5*w3@!VASW43H)9#qolh>sW<JrR0Z^w#Dfxnd`mStuKM{Qe88Nf&
z>UiOnN@22~M>4@LKWO7|mNoAi*7DDL*G^Wt%n+-rihjT^oErLAc(vKl7@fxIy|)Y~
zq^6d%<X8K<*$o;IBk9CK%QFoY#-T6a_$Xv?TG|r=0)<M;JB|oGuLB@`rnKl+C*~x;
zP#x?$k2pGQ&$z%3sY3p8t-IpAGzQ3CaWRXz7PFb?!1~m9;!Q<c)cX2DsnwoM=4V$|
z7r-Y?nlm8zs8UTn*T~}ax`vfOT|Aagnd)7n63qR|+rElJdCZ&W&%)a`th{V=!0<+0
zy9>86SB%Y|?{^KtDa*((sOI48S5H8cDs`+EF3eJG&pW%bu`kxfN!IgSB~kJGvU&IJ
z{79O8m^_XOJNOUumYwk<b8LEXHm6(osXS6@UHE$%ryHBNLH>35eQPRTEq65B#`<OC
zQksW*2W^Y5QWe#K^>|ax`2mr@($lB3l$ovMP-Mw;74qsl>Dn7B7#dMjbfc9K^?hA^
zR3=XI-8KJ+ShMT#+8j7XSZOu}7@4A1>KE44nVeGaj*nmM6s5Mh62Bx@s5MeCHNAcd
zyFK2TNxjMyaIkV-*doYhOYh(J-YQ_@?xN<0G%*5;{SM*0&IIlxy@xXlf7LFsg!xJ{
z3o+>9Oks@I<>KDR)xccnG*jEI%oG{<CcJf1Lx<Bph$wmIaCapm<l9o+*rS_RPo0J9
zdX<tea{fNJ%5;mvvuw3Tt=&<xiSU8?eC_7`QV9`eho=Guq2{wqp>b*~IJo$^M~XFW
zqkpc=d%A+->cKd-F|yfI7VLGXHI<scS9~f$E?d$Bl_RB|)o~P92M#-<VKSvJJVS{%
zOIWEB@8`S&5#r^WL?nF9-+Y@Ifo1<(<e`YdUPc!OH#=0o=G7IWI!Cw}t=Hlu?`+&Q
zs?iC1K|-$+>~F}!Pkb?YpYA)MqBS2$%F3Rc9O#K=q<sejQS;iw#FuV%uUJ_|g}rk2
zH6QE=_F8;T2N8*2HuAvI5v2Mo1l;Kg15jIrvyxXj!zoZC8g1`(vN4(Nq3QT~m6GGS
z+o2E$^c(GWdF*>XSYGD!($p+>=2y;Y`y*@3{}vF#^R<Jen3|eAXpFy$z65E**gELi
zn^A%_Vq84j%qLN(6m~PdBpp_7Rpi!W{*YtpP|~6UDVNRZ3&jr|s;il4>-}AJJ0JQF
zhjATkF%|KNYtQ9MAF41<WQqLwUoQZ&wtk9AqCgJSaEfzT3>Tm0WoP&0s6D!QS<#V4
zP;YAWP5$>jUgdd{%f)WOYgKB(mtb9_JPT8{rW<jzLoEdwz#8CH@)PNWg^g}Kr_2){
zBa)U2_iDd9>#ooZ+Ek)02QH}4LBJ5$eZRYly&!f02h+P)hUDDBLZw>S;vrIm4YQ33
z{F=vnI&#=(Gf(QifgzQc3Y9O&tg^ap3;aSmJuLvtsnY1HY^wwAo8MD)cU26<hz!L5
zMQ{OzCh93kR?*TDNoUT^0rIvA$HgE#a*CFwn-#Hh0z3{@HhI-G3SuFzgY<!ifL*~R
z%t*x<T73I(iSwpGOhe;Z%H*VG@*bw)emJyPV>;0Dj+h)O2iZY#q?XL*6|;5@Fo|#U
z7RB#@H~g?lRoLw?Se$v@nMGK5gf`!stBi`gzBS7tHdaT%;A5!Pc9ZkfFzmwY4kB^l
zVn~?gEnCBv4nDvq%xHBiP6ScwUS}(YZzS-o<~#rr@1RrgbRTq?UJ(!+W99(u4N#P?
zL<b*Q2oVhJceJkErx0tqp0yU{%X7x|BI#85^B{=xV_TcK)6mNsmz)Zf`7dt&LK5G@
z9`08X*ROZjlWR6ko<<Bw%LuzP88y}?{ct_ma6RM@cE~uzoZtVd5zp?OlUV1ZQWC8R
zTN#fjoc)m7q+}-kTd&#c$omQv!`L8r_~=#*a<`Spu0XA{!2m%n{^SV@Rk_is?czM>
zDxoRjkyA~jduq9dVZJTF{rSs1VNCWs+8y7`jHo(^6<e}Khd$i6RX#w?R14W&iq7|V
z&>L%iKYs3~yDso!dv`7~$(o8fQ4UCFCEI@W$Vp0ug@zh7((~{>Y*jAT$FAu+VNOZG
z7B;DqH@F0f5$lMh!A+&Q$utPudb-Jw9|=v2MSdOcl3KXaPd9v1FK6AGcB^o*NKR@Q
zk=N>W^AV6w<15~<umo%mBPNvpO_GINrOCom1q|aKR(X;0MY`S34yv#{hN#rD(z-9U
z5Nmanj8Xc@CAVAsQK{oC6LiBbBdh9@mbNWT_4o5DCj;&OU&i0gM%%71XmClt7QAlT
zIT)K<6!{bzEX5gqdfD&sUJhz8p7(~*50DNXE|g5Ac?yE~nP0y|w@yx;$COVN1FSF3
z<MkAl-wI!;K4N?m1kLymQtD-~In-|4lGgKk@YI09W#+o?oj2-f^j|hf63T53K-!4C
z%@-N5z~P~+qr|N5SZUHv1^ii(ZbaJ$i$DfL$RGo+x+#?y?=_y`O)j+|DR&;b#qQzZ
zV=mR_M&~+;^1pMF4VO=v2M`vS>Kt4gFJ@Xl1M$A;S`ufG+uG9c`w`tn<>DQRC&@z>
z`R|%lV17XLMa~1+ir2fkyyK&4IVGe$I$zI%;NuKSZJA1w4b{(`Y;fu51U?IdWoo1S
zCrv3>+hl{?#dCD!bgA+Br=F3=<m^y0KIr+w=uZkyxa@aAhEW=$l7K)M`{^fPexjZ4
z-2JeaN;dB26KP&(H1<_Ut=Y7)l8>(M^vw89e`q7v=U&d1Y8Jm#F~I?&cfi}g3l7Mt
zw^%3$+~d9hGaQ9>z!(}FpmoP{yYO_oxQ30pD3JgzoJ%a-@X4*ed&_%!BiToQNIO^O
zVwRqnotq2Gw{_MbU94bZi|%_6E?@S>n2!jUQGuDLR_O2UbqHRWEVQpUYCK(A6A#a!
z=He(0_zz_dkLE_-E!BK{tbM*hcQ&Y7_v;!btb-Hsccx5T>(Xnc10>%Hg0a&66TU^n
zU=nw1sQj<a>P>kXjRd6AZoT^|L{wB%+FZ+3Cm10@NqER)uzVwMAtz_OP8K|{wl!e|
zSX?v$GikT30L8nlL@zeR;aZWHNaYCoYr9HA4oI-@lD^f~=R2`Y@c83|?__wPyunH|
zuk9SKOLi5r3*ON{U*9S+P5Gbl$M{ZBUY<$LU;r^ByhyvJ#5Zi2-lP<I`{VA|eerJb
zb6GVUPi8&`^V;v{I5TfRR(*+f>sW>hyZDp&@=`8~@c>fxH&%9LCYS5!{%p6UZM?ld
zO@#pxCLsCyh8?Y;G{psC4lT`BXnN_(ZmGJ9WNe(aI3GY@lc?xRFs<l%zk+X#dnHao
zPy6t5xiS`vd(@!Sl_bIIq|*KxIa~0Z>nc)G3e4We_r8KS5fMc;=A?x!x|_`%#YlVA
zK>$(sR1X@BmrpeI8DpcO6jW4KYVD|EF2d7>3U4|r@RYjolIp*8#c~GYw0zgkYK4pq
zy5HFhGHBI-Zib^!Gd~v?@<Xdv#{}z9+QTVqeyF^^-$x$X+m@LwG?4J`@0T2#e-4+m
z*a%<bzEO_5p89E?srD-gKnD1Hk12%Q07sTDrq-ZyG}BHKGr(OIVaA9tXiVZ5ysGoz
zw@u;$T3NB&rpfBM@aI=s^NjTMf#HM#7QabT30|!N344Z_tqkd!&`P=7>0@+HXxeM$
zo-ny=A#Dp(VCMa?3MKvQ^b*NN$zNXfU5Af-F!t;d2r_Puk1iMOq#wRknx1Y^RlfKk
z0APc+ur58`zNPFU3AHeJO|>Vgop>Vw)t5AiR+UcWGwo*Z^ttVJLbfrT39@9yW171C
z#2<|`Ge)%I?w-(p`s71Fvmf}(UB2_Rvt^jFxt7+T*R#A|w~Z%u0<-s@;HcN_y1V>l
zArI&NK9xsWYgyS0fPCV9^?efvtA+RsTH5Pef>*SCA`qR<&d#+Ym6H?J#gGs){}iSD
zLn~{Yk~bnodL%z1<qatoc?lmE<5;##Oza^Mvx8NCAK1F6MEy$rp`OQEnN#^CyBYcw
zdm%MqFW<{IgU7GN8FWpLOEZhLcN$IJ7pZsnS~zTvMi>x&Q`qPe@35b4F+QEm*)`BN
zs3*0;dxVaU93Xaj9wZbeq@BzR4YIv<Ox(a7b|jQG^#zex&VT-<oBOC&acjgURZ<YY
zdX=1_uwu8Hoef^vtgP#TidSkxQj+@;%qh`?+OcsFF^j@%0jatN%=Be(&*iTu(xewH
zM+s&fV-XvVga;$Pr~0A2%oSBNr3~7N9#Xy^P60B4>TF)6?q8q9N8($(Z&xVzTwH!U
z7IEAazMh6Pf;nonR*=g?NMeDczT$WTqZ@548z<Ke47%{@S58C29(U_eoK;={4WN)!
zo54928k;;?6<n*$=am6c=-z95z!Uk={t)4u$ZElcXp&8@Q<~f<GEaGNJV?q7Vfkb&
z*asUx_VjQw2nfhnmq-y`F&rl9M8?DzYD%Z=_C6>duX3-dYC*`U*L>GY)e($OjiSuE
zel74$b3@&eP>Sfd`}c2ore+ADW@w8@YKqGzpuSqr4OcHeD&pMJ&QSCx(bqCPvPF2c
z&D<71v$M8FdV4nk7eta?7hx=pp`r0=sQMr*^FDgJ<C3X;A-FJZSmjAWB`1aH=3Y!X
z&A5Iii}N=xu0Mz972%Y_@zp|evMLQuGwTtA5<w7lrdOV2Vupz2UkP1JUAgj<d#`U3
z^&jCawh$^S5+8J%vKv)y#*~!o9&}t-99sIDPgbCM<Wdv7UbqDf+zXiP@V4!s7vOo2
zRz!zZkT_?#5x(c@IzTL~+iYXJiW5c{5TEoiDG7|ReG&rSsBLcIvw@K<Yfsjht$b<;
z`n`a>+GjKIpBFSFZS413vF~<wQ8jtom>x%}OO(E*_(!Pmtt>B3r)1JB_tmE!qf}}O
zu&8+tV2ZjwjxW2UxaiYy<sUyjsRssG*m*(Rw+b*B4I3;({hOdN6{ktXo;cQkVTj&c
z{GYOtl1mWuXaaITt#rCycSa*|HOP6K1SwBPich53+`D|t4t$O^ojpCc_XV}gL__}a
z28uNwz?1g4zvFEngEhq$fRPBOu~rnE-H;&RK#LpkgeO?_TN^}%h+a9(Vc1e=x6iUQ
zIy19Fv(13X^nO5auo^L4_E>>zzZ=7kh=?~zMkWvDC`sP1si~-{X5bB#tb@j!MtOVn
zyvhAx!ddK`%wj{RlaDbRY>Ow3slr|l!vmae7MF7v>+v#b&5((1l-ZsIbaXq~zZAx9
z^4VWdr2g^L4aoF?78F3z*^LsM&IJVpq4RH>QZIjmW2b2U5kzTz+Mn>v5EWa`vBJ~Z
zw%H^?C6q7udUy%$+Q$`Iby2AXlmPfHQ}$9zyJ4<mL~KrX#W`$tSNMEs)eVM9&&X)c
zWuAW&P4(Dub>js@&r)A)7zd^EG5sGBm{3+nXSj1Jz~Vu&2+d+#3K&?QK>a~GG4un;
zU7}%7iuMcLW}u>4J%Kh_Xw-i1dGrtuHAPiB4;yW}v%ZG?_4~~(S@qU|W?+jeiVyjO
z2$~?5!13|SXQsxq3;G*?V3N&L__(-gKJR&&de{7UA40)ydO0OR{F9o7nK|`c-kZaX
zgQ(=>KrP<GH59++!exkzbWst5`9O?8XN^VAZp;9&-TT;CgX<TbD{9}Pw%R#+>tf|;
zU+utig}IyZPWZjz>+4D47RdN*Al+4cTDP6iXJ2X{;Vg6mihLcG!98**vM)}X;pYHK
z=j-dAl=uR4w1|m_uYZ(4`O0oRr!=W=0&<>NDNwsC?^2o}8;F#Q;u90CSr<S|vPnuk
zbZdXiU=w6E6_-_3r;pLxpr$kFkvML^pH!^4%j#Qo$7yROO2&VED8ZC*LPUK#mQe`z
z<ec~Dc||!Ts=HXT`bo-tN`uV1Z9L#HmIW}f-p24_0OmCRWQ88vTM%G|5P&me7u-Ut
z-W3%ob~L>Rh?{L4XdTH%&{t%@B}>Ap)nFT%^9Q8?m|k_CZ}Ch8H)OK&m-<1iIlI9r
z7sM#84deU7`{Cn1zI|31eUS9`Wy2&S9wASNb!p?daOX8pM)H`mkG}(>>%vD%>wCiA
z_V>l4V)03YAd|D$<{yhc*Oq8)k7aht0=Jd%-O%Gl6s&$p8VDxnulKUXXIopB{S2V@
zjD9ZQEw3p>zwoHa6dt)v{%<63kJ2Q$@XOJpsf%32_GJAtrMrpQAZ4R+F1oIGt}GCh
z!=cySnU5RCK*8reu?63bj|3yVcTj`MIS`)N;EKA3)UH<)(<DvGm^Y+HKk78-kz@1j
zXI9D?di1n_xSL6vR#8!TXRZ<)Kq4Yo^~O1BkXO@oHMc6fw;I>DL?ub6_)|mDXs-g5
za+KKEta}57kd7?bxfV&2T0XNN7JfP9!THK2yQNp5IxM@zOgm=~;CE3I>4Hd)tF_`I
zVmpc~i7(se1iN)cEdlFZ>)p+SsP6FP=hlN~U(7Gm7Z(?gNx6+-^f-8KH>bms^MZEB
z2G{c~PB&ePMy}$R>kEmtYnSksSyknx!CdC2VDztA+-Je9CZ(j*iB~MUI)ErhxQNdM
zk_^R_PRCRpmqf)%zyUlaWx*Wp0?F!sa|Al2R_@&O9V-#zzn4@1N`V>^`1OT*P*b&%
zD%WYta--8;4=#Bdz%wF4rjP0fB5`Mv9}IdSUGM*33joL~L-{+nSZNYU)S+HC*BzPf
z<?`LS3aT4VcXKNz&d!`qW;H*3S_YG;op?#fATWC%5sK7(7Syv`&jraTC`gQs?yMef
zc3#xdOu8h3&eU2o-~81p5ow!ZJxAVVVP~JKG3@9aTQ*Ius;UC*)WW>H(MQ%!v?W?K
zQ&Up`v@?JqY&lzZJRNnz(c!SojS{ww$B8p1MTY#%X@%3rvFm4w7U^T>9z^9ZX*481
z&Fk#kdq1Vc87l&CV78z^meT66Zs{s64rV(*Bm+`X%;(GPPX93~Es+)F-lM(3rW3t-
zResaEKuI#gqZ}O*5f~f}{H2-JzbxXvoW+jB48(%&@BYa_I+2h=_YP4Z!pQi@gu{^(
zMClZNt%;`<+}eVykEEEx!YDpc=VsM$ndcN_M8-g&(Q#TYUTj$Dw8qjJtc^e&P?*qn
zACs;Ox@D4EtyuvMNrk_Hg_~lul^I!FP{8Ii`AD+*#Yc0EdJP$1ZH%84YK3$uVyCZT
zv0TRXR`FF?x$RzxSxV&I4vje889N@HYXoN^y}R808c5#0fxfQy@5-W7lvJ8sH<R}>
zF*q94`d>Pz88`XGtW3v?s$*k~jKrx=UwwF=d-zW-y0kf&4GUB<enqbu5gQv8d~rRO
zwKFv#s(gnYh(JM3ix8!=yK&4`H6bC<v_qZMY1l2FbH?5C^ZUxBDy2XX#$RjkAL`w;
zOWsdxEcth!bw`Heb{Z;NB9wWb$jS;D_U}{IN0Q|U3to&j7zP`Beq6?lH^yVn^sgm7
zx-(y1t(!WJ%`7FG$P#9@21vv8Zir#*^>mrSSR|Jf3p=OYnVi62(2(2Rr0ndju}>GE
z@zEXdj+WMCckrM@o3A`o)+$%*TdsU{&{6)g&yq7(qd=6Yy$w%i@s=w6o|SDXE6TAp
z^g!b}$EGf4msTVLT_9GO1JIZW{Kog(E>u7ghS!G=Mn?CPTpyv2OLckWSaFa^k&z-4
z7KWxatK;gsBwi#Ua_&)4QGzZz@<+g?+Xj`air1PM&(rf!>cRh~KF%(%?ZPpZBeN^f
ziXad*<#5w-h1WWbfSHL+Xj~jw)rf%GVVdXF><k3m{CB(%gw>2M(co0`37dRtbtqJ;
zz=vj$#XAZ+dc-=}r>V@9$ZUJV_QvZe5yeGW%Gr?X9@4SlCI^@w5LT4we&|m(X)cel
zn9W=4I?6ph4tC*7&kyX22{umdKgv{e{8YI~<SP$21Uz0C=QjT<BH!_n`buL!rR(W*
z_YznN(EF4l2W7y7f?lL`i56Hxd15BtkT#F;6{&Hb>I{HdGm+sxu*HA()QcV`o_ekN
zQFc}|Df{N;mhGL;&=xf<$V?W2n|E>A>r^W~d&zpo<3rFFY;ied;^1K5PXbCc`E+*|
zc6OLIg+{GoF{v7}=h^<jRgWBqPXe!@YHTdLfN!9`|2bdO%a>c=&}PoRu}b!;F6qgU
z>0E(WVeHTX=u2(}8*6DL`}z6F@S5=*52^M1ioAUy{*H{yVsViWAB;NO+o#6J_k@4_
z@>8rcGBJ^_*B5&hMd5P&SWLhlf5+n(gLkDM^7%juOkId>-2By&CK*A{S;CEwZ?VoC
zAD}ApdL29!d$9%CvY*kdmNXRq&8k3n1}cV?6+(J?+|M7`^)kgD8SX_CDVKZiM+3KN
z9V3mqX2ye6GBRC3H`|^e#@8%>>@+qrQ=lqC+<y!L-v^DXjf|+<mtix=X1i?=*K`WL
zps%l#gyd+6VtK|h#{7Mg=g-%`3R?@Yg6I$8sXcT3Mj=KwYwc*ftX!&kyi^Yp5^4bo
z(9AhMuELfSo#QQ)P2HR-1qn$~?{h279nJzZgLOt-$S3|38J!E0b4RZJvd4Q1%P7>*
z<`J=mRHR}gb$2(&_`$L0ZIxPoOvYd3alTcZ8^?X~1}iafwLhj%D_=z64FOe%)@fcu
z2O+N8gUqI;*{Lzg`}jLI6IZ;eDbaeHTU&fFPBhLG+r0#zrv0yYajHLjHW{QR9`Ve=
z-bV)o1f<Eaa&s3d=V$me@F_iw?#Ck&_&o{l@DJa-05fisVspWe7cwR@mB4aa^J{!1
z8918~k3bui9rvI;Za_|T=Z?=LV^Za|3*v+kgeT#FdBE|P#`_(fxjSbIw2S^M6|Tn{
zlXZG`#P|QhX2QDGd1`|D4D0XB>b#GC^Tp%ucaO8e$Y<1Y9Z4)y>`&*f%#l-s<<0h9
z?~)N%(G6g;9EP?Apgb3^f4`N@33>SVu}waz-*F^~-41jY0krax?f(N*#?)ut!McR}
zd*=6V2q;onJlhFt8iVXs*^+c_UCOq!=&BWIbvVM}G9Klq0fz<FzSmCxnEYFd^WYJP
z`6~h`#$YBo^#({t*>h#|u&(uh1|8aPBK<|?>hc_y9|%1i_ew1OgUbAY_3y;EFtmJi
ze{mj&tW*kB0qnH4+4ahA8#r}^JeIz;)WHA!lfSxt|M@485fNkXv9N#;HcnQs87eI3
z2o@C=zxd&m1j;i|+lz>JhsxBeGA26gO~QLefBZ9&VfFfm&;I8Jth5jj%3Z8Kk>CIQ
z`9Gij{~s|-Ub&f{!$Xr;@=MGzUsi8FCgWP#kI0lx;C7e^v2_f?0~L+rC-73o?FyQD
z3%VW~dMY2OT9}Y2_5gdBsUoPE^(A`|r`rW^Gkyn@&RD%hk|S9xljh>)DhR+9=`it*
z%9SQIerpBdz}$A50tnUyH9sh2j?kSw^=Jt7I0qVjz^94oP8a6y!I4R<e!*pn1{Khh
z%|B{Qi>Q}_7U@5~^566hPyy@|p6&|A^Ly!4#un47Ic&~Xj^r?E0%*Uem&r%95*<6Q
z6Rpk%vjxw&94|#N0JhZY-odQZAWGq})A=O_O~~(m^Z9>7(!b22ZJkZN!NMLG4%?M7
z-by3D4rTaSwKBHcBTW(;8EJcTLKe3LzvFWo1QQNjR)OJYi^qlK(yxP_uvgzbCl0BC
zxr=m%E`Lqit%DfFp7~)*R6z`*W{rUB<ypI!RQ%JK3WFXHKA8}i8E?Mu(+4$E<w&>J
z`*?FK^8$FCK<u0>z47R8J;Fg7N`zA}zva%x?p#A>cQ=zpMTp~@mlEpmc$;TT+AZTb
z4ux>~SfE(3oUJn4o4=C&0<1F3T1{v`qmh0n^Mad;mezE=WbWJ#QJ`=%`qKk%yOAw>
z#eaSO^uzy9v0iU<DLk{|LB`qX#w3t^JU?0+)MzsKSzgYHXJ4{5p6w>*Sk)yJ7gK5X
zo&GMT<xG=QZ3@zH$2MQ3_RCRhv?HTdQ)hRJ03Q0}Ae+EwF!2+mZnI<am&)gy+Y_1c
zYqP$=M9@M`$oLXq^X%LmNfty{{rQFoAaBM9IXLCMi54GgTw~UlZQR2GQ?fIOEkpVV
zAWoVn&`d3~azG9-^76XuCaa5!iv#J&a;&dyY{{IPO34-*WTy^pHaUhA_PTzn&lCK%
z>8FpsLeGrD_NE;S#?ECiJ(F&S0FR&It7lJM{24+<8V*cDguv)}|M+UA(y8^3h(4U0
zKgGzeJ3+|or0yWf7lA@@?`>!kN|iVJKc-06(IApb5z2mysdGoR4<LglFPD6eNI4-a
z`cuEfaMw;Z=hzo`YONZ_+z?h%oeykl-*ot?<?Cb`Zr6McdzJa77+KTmv?s*x(XS4|
zFXD>7PFIQ1Ys3ad<&G;_!(6V`WRNEScAD&h3p@rUy^EPWZ0ziA#~W>-uxtbWG0M-<
zFN7^u53>R4w()dlSqC_jsGCK-8l5Z=laqX&m!i(1q8~nd1217zcc=*u<86yHb@m)Y
zsji&!wdwKrOrd5g!K&ee8)i^_riV@?f4=zh-a50+=$d1}25=-+>Ma}9aJ{nNpOG_x
z*6vM+)jf|12^nm;y1&g0(LhuaH12>s?0CB|MbJrziAnbCS!$gy3TE{K*?cjZ;<7$G
z=RP3Y$bqL`55ePaBl9NQxw^pTV8i>K3o9{L*Kp9r9eyK|tc{eO{y#`BI6{g58+n#j
ztvRyX5a}3{QBhIZ=&)&SX+*umIL^kVGe6JE+tl~0=i>Z4Jc;FtuCCYoj=I%CGqT3x
zzSmt-Q%qcB^!d>mutAV=TX+JCQx4v?zP<rae#n|CTU+m=6DpUNmTSys;$xtk_EWte
zA%TRJ#1*kBrIy^!FPq3yqMbB3;f8uCyzhE+VgZ~*7mgNFBz5-Z1wKB&rn~Kjr&X%m
zDqD_A`Jmot1bPa9Gugq!T$U3X8wblAAfTckZ*g`Bj8BDK#(}YCu5i650S2^^EjF-N
z+sR3Q`gF!jcx+Xvqo49ytut#urZZfCOm3n1XanZ;_s{hesP4U%*NTIQnTZ-Q=u}Ef
z^z=M?hC;pH`K3k+Dl03S&(uW(1wo1vIYaN#rn49uucxJ@^?`$F!|Bd>uo2*fSWQOX
zc#G~nAbbsSWudm+2g}`Hdw4{`#YW9#+0nqs#Kbh9T7o`0)vYi|kB*LxQab;1|D><K
zcW1WQX|Lr@H3Xi;0B+T3$LEl>-D7?i%;4`f9|i^nATx8>o+J~0g1fb`F)Bc;^#tMS
zU^bceF<;l-Ub-a?jYhj3?|h8%INquT*#FqrwPK_b&2E;dC*~~Sc3poA-9g+35$`Lf
z$(?#o-0;_0!MR6UJ(sDeBtb2>Jz1hEFAvt}^oq!*VtE`!al=p(O?g62+rhfOf77s!
z)_K%QIGpCa!I7;jH7Pn7-8ttmm`5<(R75qP23Q)fKNyE?YHDhLLj6q(K@jaE7!Ri=
z@ftKpg>KDONPUs=x>(CC%5dM=za_(nC&?@9b--Ycvju^)+ewfCVpJ7iKD>*s_?Y<L
z-4g3;TmD<Q%Q6OZ3wDuCKP*b}w3E1$a%IQiV+02!=918R_!&IkI&v7*)e}D5!^<+)
z?^t8JzIAJs2g>hMq*JUhH&YGvkcnD3D`27Et2R?G`bgjt8Tpio!OstqL!INWJ>hb3
z0u2ujFHa|E9sqF=Gs>QVIaO$T6%`^$FU&E@<3>n0(qtip;u}aY6?R2CpN+nmn5$Fh
z0ODgIcXXYe59Zd-pV509kcl+0BO~;9F|u~rJR@)Mm4kyrlI?0<N9R;sQ>G6%R1PJD
zyltQUUoQX%I`N#Wt(^}Jskn_?K7W>sra|&q?^}bGVkjv$2M0&mlTJC4{G-jO^p3>p
z?UYt$g?#-kV7{n<jCsdGpElgNa3p@^a?pMb7WypvkjWRv5Hqu(RDOSb2Jt6+RPQ>&
zNx0|x`)#`_vM1a?rwJ_BCl*LxjX(lN9jFrsv++pT;<<hWRY>B+ZE*~5!i?d{D(l0E
zfH7!lX7-GLBq1fD&2zGspo6q-Qb|pXl;_NAXAax>**eAjeJKMOMh9ZaW{LE=#>U4a
z9ol{!FOKl8%^x{AInh7vn#<PN+KtSS8NXo`>=g+uV^ux(Oc8L|oo{kFo!6epS!g<)
zpZd+64hn;|wl|DYEyKgTy}wg}!&tK2zZAKHuMjAbSDeIEqS1KLA7f@8koP--qkm#!
zqOxroXvs_vH2qmmSL<nb2tKvG6sa6fPVUo{JHmfp&Fmcbm;o9L?vA`Quhnkyu6CoN
z38KZL(GghTcf>(b_4U`P-%DBh`}>^RTul#gb7_Vu6Ypp4D8CqthV=gZXz!l)Wqm|9
z%flEak~3Xi!itVh-sj%q_?tQWXzj^D&D@QO+dn@v`*MH`*q5O)C)2P0{5O8%M^NC~
zr>-ljt6-9{4-%URSxwAvy{=Ys6`!-RaTxJe22}ZKr7$5|#c7^Y5PvV14w2bVe@#fU
z9o%J(?V9r^cs#@mQKH-8s=`@ND@|?uJ{by~erS<iCKbnYae~Sn?L5UCYg9MUpfV2G
zg@meNRLmyFeTrQ$RruInH%<G|L!G_xj8)||M(-u*n7?RfboWK&wxl>x@zz^gQ9d(R
zmHdV6_Ri>3B5#(m#z&>x)p4)k`({OO9FuXDv0`PT{bpzMVEgQ4&)ynLR9bovM1dem
z7680Sd0~LKil={|z2r<MQ<RyPmY1DfiH1X#aSC`xv_IfG9+Z`}^J>^jR~3hH`m%9o
zR~JwUDl<<Lqi@C$@LXf{l#n4N85wCwh^D>$BSB(PGhpc<WGD=Y6%d$JEBz|_tW>92
z$fMi1r({l7F3EF#-J&)hP)$aUwh^A@BNc!%SM53HcA{EL$AJ!QZiYg*-mnHLkVEd|
z{4J}@e-%9c(+@lMgPL48t%UMsLTIfbj6Gg4At?b?DUmm{%dctj?X?j;VPj-fm2!@I
zJJtW?9LV3YK(^Q&B4EHKdG79+>4)cab^e(yBv2(xPPG2ZZsTMAd|K1N+)7X@fZQ4P
zu~OZ%g#jA_@%+|KIA(jPg?z4IWqo}Q>9xN)pavAaMz|wq$#(Wd6?PY@Cm+X<pvb0$
zjd9Bxu^t2lnpXqFlw(HLVdUlEws*(pa0{(kzZumYWYW1Y10!P+x0!AC`cCyW0whm^
zUo;ele*YeIIci;KRCDpojERA#eZ14?pt8$GiXU<BczbWQhEtGodBnS|a!@)(50*#J
zq2jN9R+cVSOHM!n8eTFmwGxct3J4+mx-&T)BJJ=~?+s{Cxn8aW=H}i<iKNHT=zwCE
zr`e@xdm<;mqI-~cXJbv-WpZ$Hch?d)*9zcFnuo?<2iTZUlJBBvjHg{L6ZX7Gg%Brl
zSZ1}@!n}u?T{4T30oW0hOWEiCVBJc4DDL-@)TpQqLVGHM==_8?xvxk1hm@`#j557@
zpUbj(%N2|w{(U}RM}r#uWcD0%8ZpP)V>`u~{Rb1xP0@GWOwUX!+S;S1Y<_;QMs?$@
z!Sp^CXQVBjK=~1tG<(jVDPRDH>(ND1s1$G2=`D*V?#_PU^>%X>Jp<RY<t5u!ILUif
z)`Qt|T+n#ln$F}`0fm3f$h2Lws8;L2iFnZClasF4xG64ma!v+H_Ku!)Es4BC3|qgU
zfR=VbYaw_ATM(A7_-&SgudnK`4XnVZ#P%Rnir;DXOsut~079KZoeS<Wj|&?epSWh0
zjPVLsOaB2QEiDO06tJamaV32*r>M%Czv%#lP;CKoUCdbcS06RGROaR7Mdc2Ik}*~<
z+1_3hWCGiNYc_KOMZLrEjDzq^Lz+_0W8v$|LXi>>ZmbN9)xmfsrBU;H_Ky3#3Jcqa
z%#4gp!EfKvZcyBI%FMvX$gdd*O^9$=nX+-k9ZF*FX`dAUEVa&jrSKGiO<3c5xXZJb
zCo6qQl488rd7YEpMr-JNVrJU=eKSoq9;cStCKOf+EwDo4a3Eh5@VYi%v}%2b%O@_F
z^Jk|Irpl=Kl7s}x<IoM-MGL~;jwUV4@v9@>5q3s{?(N{hpG5|piYl4y$;ML}|6d@%
z?jdO^RM06M98ki^g}=zjA;7JQ_Gr6?=oM?|v@%}me)up7;GG*izi97_f?oE2K6Ggc
zl%F46ZAtmQ^%|MK8c-{WTmxILrx22UtLOZvP}wG4&}kkBgYS8crAiV~>C&Gn+{1hI
z&B|Er=KQASuUG3eIuj65#|`P1mV-%j^WADo6iqFGG-+rs`e3qrId`MpG>W<a2jmlF
zTCaqJ;|ty#!tkl7bChyqh3!tXPIs+7yEErEy?fRZx_sc=As!;MYPS|HhD&RUalAeq
z6do=A<R<B5!aVgT40t>j8a(*v*c6)+r~Z8Fs-Oxb<pSPQ4A`P+r#DAiu37{eK^69*
z+EYQPH3hi2jygtK1G<(#=WmRJgwK7YM9^(cOZz3E=<ld*xioj{@#uU)H<?5p&)zs6
zntD=Bqhx=7Aoe9abN4I{&D!_X7wV^n<DTx$eYOe&yBbHH?#<tp=HqR+QnNk$l&@Jd
zFtWUS3|v)ze6{)T@Zo``db=IeP8b=#Y^jj@rE_~7tJKY<j|-wUIK{%k;y(UMXA}l6
zhzv}`Mb%e;PfI+U%xilRB}>Min3(A7T6elNcD38==5<*gZKTGeE4irAmNdGa#9Mj)
z(Z)#h4txNC)`Is%oI5{XGvb=$%Ipcl^>}sy9!PEN<j~Mi;!8}WXrv%y(AkyP1yRBn
zN1vDDifcMKGLkx+lkscVES2JY>mUb!Fa7&`(EeauR~Y4y{*<3oD(8~lb%)27n9$oE
zHGb|B1I%>5w=y>u-JESSa=x~4@T?_{`KzX8obs^ya~$6cCB&`((<!=dS(@ZzzzWxK
zXV$}dFGb%<^ea;cIrn0BXcD)3DPi+Oxjk8<{XqX<%dT4>?alxD;Qc*Pn77zp8v-ZP
zh6bKO3{#9HxEUT7ULVgVQ2b6{w>vs4=*v;2it)N9mnx*$qHic6u~AoU5MO~Re4~rw
z>n(V3!n&$tvXNA%=5cYneNn!tg6;F)v=h)WIs%RR`TYn3z?EG0y1;XDtHakgLymw4
zM(c8YoFKCs1k|HPgrCRgT$8w8%$=G|TA08yT)>hWUoiw~v_j@q0mr2kFa=MrHJJ{I
z0gKGDm^(jJAa%d~FLbCs56AuC8!UH1^#9c$fWOFw_uoL1e^)o!6bL)h#-rBO`c`ep
zB5DfW@o*@X$P*TSaWF3)QmOp;hM-F)pg5PlqJ~3h=-yp__O3Amth|Ed>Ko@B4{a&C
zXO4+npGg^O5~n_lwC|wG!f<@w(r{EvLHzVR?35@S6HoZgWR%O{A&>9|r5{ai3M4Ra
zFf>d-sKxc48L;w0lj2UP1#+e!Io*EU;`er{loLsxlW3ZA&b+mVgAVsa_<imo(hQxE
zb8C~8dN&@hu~axVmS)f{YizhK+SN&{85+h&rsv4VF7=cwN#2~(OiD>mo6M1qlAWKL
zseB5;rD~+W+Ew~dR}RrH;&YT&YIXpI<&NZd=)nc(uHr~$OF|zK#u(N2sXeGv+}MAZ
zfFBz79v6>!(VjGTGo%uRR(kea;d0Y+Pe9VHLyBh(bVOg7ica{C7}UIb&xYw(XQkIv
z99K_E<-yb&<g!;*WEunuhog_Agu8a^UBy++-4)B>=0$@J4)fRZ5>g`}QW8uxiO_0a
ziFe;~m0)bZJ|9#Jl27s(3Cm#hE)}!00ueR82fCa>v9MD60+n)&29u8lMubmx#+v=&
zxHap}!f!yY6$MIMyY->)prDz04>Q2(1Z}cJ4zoVhsWMA2kztINLsh5VfMyAWu&cR|
z(PX_{4{N6Q!-cC*th_2P@BgqWW{Q24DRtA?zlwutjkqQ@9H5O{vgYYx%8*}KU+q(=
zqzZj2aq!EvI+9RBvky)Pfgf_JCuP*3i%mFjggB=2idG=@8`lNYFq6z|<){I8p=p&u
z;<Z0KPcX4s1{NBNj>I%(MBk#}6bi?whS<tXs!Ad!3S$maE=k`@bbP{?E)d;Z3V0qm
z`HCBVEJ?E{Z*^m10~yETCf*~<3TI-A`E>GkuzrkW8V)?C^vAa=&~QNP3brz8tt>6Q
zI^H#V{i!@YvIy+DB|42^=Y;wO`uJpmGp)M1cI>O%X=sau6<XcgtelgLc}5zV?_K?H
z0dlX)sj){NR{u3>>Bunm*+7BB$*3gQ646Kd<cwaajDvgippL5RD_z*h%em~SvH3Na
z%Cd=~jFgmA6hw<jEeayQBo_rir`Axz@7`{qhW`>tH-g_yRDNb^R>h@FW-(L{D4Czr
z_j057_~A%q>~pnBSn=4*nfuT%rEcX>-t^|=Bw7Gs?`<#oQuUdsqKvNGXSiwM1f&6d
z_V0ZXbR}fWUHG8!YPHy5%3LY9kc#j@R(-t-o4Sr4gCJ$FCnZVXao0W9m-9t9SXf^_
zhmj+jopi0O1Js5RmwQ4@r_zLogj^2or-M{LJLCC-yYK>+VJIhTtXwi38)%ZJ`w8En
z7Am*<RTdDXS5t8&w63&FLSg5k`UcCfrC;F<hEf3cB_+2#UFo0e|9M-L5j0|wxU7!1
z;Pl5Bf(Qb@5qZUBFQKJ%35Ma&<N_v*eWa7{C3@$)GL}(;LE|i`q{LERf7}Z9=5%GV
z5{>3?;yzW#6t9AeCC7qdIy0i&#)7#Nv>XJyFf_chrsw_es;5G!3r*@UT~Ex<TQr6H
zBoDCY;<BQv{&Gir=`)SivEk7G9#617I8MeoPCnm)Z+M;I|7+~0;;2bUT{(rNgoRaS
zlZdUv8sz{HIXY6BT24X|?_qHFRpu=$4yT(oAKnG`!qQy1gvTDYSoA02L6HTHx&Znh
zpT%j>pT&G1zrk*O7XdTw{az8N%I324E0NQTC6%D-YZP@zE;=X&aMnJJ%vYNgs{OS)
zN4xKw^$kP$PB!O`z=`-1$l7H!Hz`dK9D%l4FLi!#b-)Zx8;?Nu#)`MWPP??EpDUY0
zK%V}p*t=)l-|v^7pRdK&*4XP4>G;cIl?5|l_fu5w;-^yz9-vrxcrUF;1fKybPwUrh
zDgRZlLjPA6u)5$z9$vU}KRq`%8V9SNB~0R7mVbFV52GMEBW2~c*IbvAx3NYi7Abo+
zT-HKN;e{@W_XuA-Z6|&JI?N!>lE-Wf{qxTK(ZY{EKZ35l`|%d%k?spY%XWBS%Z`2c
zyvJs}1#;3%t@yjtWRYg8<5jnYj*icLJemgcV+fqj(PVFFr^%zIq`{%d^dm^8^|-)q
zdWi4!?78E`Ff^7?Q~Ju4O^HQ*^HliKesO6vqQjrHf02y+`86guKmUuo_5MIyDIai!
zq=U*x*c}}|^8ax4)p1d7ZPzFVP!LcFLCOLKaOg%tlx~Jjr5kB!5CH)JfuW^)=<Y7*
z?vkz{q#5elob#OLeZP19Q|1Tv+_Ue!uWPM!twjpdb2V&ehK~WilKuMNFtQc%K87$3
zn?A)O(TF=<wmzwj?}`QZH=<*tX|mKAqu(`-92l^2!m-f2^r&A!_BKC4ROU6>dVArN
z>|rtKb?bf^t26VbDk|LpD{#WKMrQY|2|{{bzprjLBTP6RS5y7{{e$w(nnWny#!o|g
zGZlN}>?Xf^O<@>c^h7^#v8c@V`%=tmzb1Yn&9F!MBD#lwAkvAhxTMU$TticR$WHQL
z#+_YRah`<+D#J6M3fcw6-Lc8&5{eQMuM%u<pelWu3jaA;_CU%GHa6KMUWk_bQxB`D
zdte~C>wq8}7|>9UM`hOVo+V(S$-f~WFq9^EjOrL49~XSK-_jl=L&n9)p|B=!|Gu^L
zdoo?-k5)!eiDCV2j+DDrM|n_rOu4Z)0a%*XjUt}%E*zFy@cYXhtW*PeA71C5eXXqA
z4Gs-eC1ULc!kaw=9YH;S7(+<;!=aCUyFP-nGGl_vGa%F!5$!ZKk}&yl2Q8cX;PAiz
zZXnVQa%-|c_MH4rFmW|}h{BBrMUCcJ<3e<y8ujpy=|lyt2oF%5)Osv;kS3L`_v>bB
z=SI1{{h{<)vSD|&{s{#^+RqdG<jv8t$DV&WXkS%TsgenrvhqodpksNq%eqdO50<;i
ziJ})?T~=Bxd<508JVYg5T`Dx8){%`0ST`l=(djO1i-l4E?MHvb4qqE4CZItXl=|lT
z8{S@_0CwNi-P_&QH&<ua0{~Z2aJTu3(2`pML7vEf{K*$$Qyd)35b%+hxk0k$eF?f)
z^{Fm8Q`=a8RDcvXuT$X0b+%5`pjm3Q98<iU>+E8oR@u=v=GzUz#LG8A1;xHU?OFaa
zU1oJWcj=rlyX-Kw#R0c19%*D$6CVIUz-F`Aj}A9S5j#X1r>eGuM5H1E0DOX16;sQ~
zD*L<f#GI2z5i_CAComQ~PT%S1Bs%R(3tsOh`1*<rnc1!PY7~8XL~RAci&nc<^{%Fb
z#dj`gxvQda(UinlYywDQr`Vr!4stM(NP<k8C6Ey)Evex67c=MM_@_anXkOT~&$wsD
zx*FsI5`w7@3%kN3%|APzZqFDu7Yarz?woZ+uo?Gd$mfBM>H*s2#V1hgDG3F1<yg2F
zLO6w7Fwlr%yc-g$b8MNTSKwu%AfgZrO(5)RTN|I#UXEY4Vsw1G6qB!C-AA<FY{Gy|
zB9hT?F|rM`eIQ%hkQk<x1a9o0y~Fzs(e4J-KLK4+Qy{kw%?(T^qwq+1FUJ#RM06!(
zq|%~Q3bi}YnvB1)fbS+XY(;!iU02TkDijZVQ)zWNjH;iw&w+Q^EtAVOEu4b-rX&L3
zmq?vEXxF%avrA58;o^8~YQFt#UzZ$B=|zVh=24#fin*x`3D^R?u(6^a-WBo{zNzb4
zJ->alY{Pqqss!=D&y>VB01r%rbu}S+QwJ7uB+1oNr4<Hla=aw}P-pN4d7ES`u>2nm
z6@#^rv*7~XqGjf?7QY{pzQPV}23qpnx3{0$TPZF+mRdqqLhN??T`9x3>mobwtGg%S
z?_@?IjN5(cUbrIM9oPQ-3(C+Q@Tc{JQ-m}j2J=^XAesj)o8-2xs*aAP?dc6?-m_`}
zGMldA#s?#8B?hcKw=xa+=Ku-xvSs4n_em6)78am-33B})d>`+hxvk9=ih*}{VWWYq
z1nvq}#Zg{i7WgAVceE)eT>5+A%;3jpM0Z^n(1gyT;^S!}x_HP##5Lo=62I$GlL}0;
zX6x$S#QqFzzH<kSghnpvhFR!wG`*B~q@k3}f|=KiSI7^2qhD-XD`R#9f2zpWUV@-V
zuLCHX)YO$E<hQx0`;oN}npYrDgJJ*mWp;M<CpjJX3c>e3d)bl^on*jyI_y+5%E`5~
z9q<E*eu>3OeQ*Y^TX`^rf^}KeAI~DcQk8Rqy98MPH|U*>0O|=E8lm1tqZi4#AzEKA
z(B!A;v3u@^M)z%4x1%+A2A1f%C>h4oSh@JSM-ZK#Q=U-Skm7dSUXzTb<_C-H!mOZc
z&;#x*+LRw05<Nf@T3vg>h#M4fY-R*z7SxBcd~HnfUO!VroWHnTL9;!b&%oE&-VAPJ
z_R4|5Ik@B#tB@n?<kwpxvuBq+($&Hv0}THX#L0JE9zHWwfF<4WDnW=quduG;=GjSa
zZ@#{5^&2kL4sh#j9)~M_S$J<`V062%6x|TLlW5BV=x}Ws%(^N<nVXbWd^Yg@&Dg2?
z0dy}cEkQQ~u3(-vnqd+P1UAx9r+4=TpMji9Wnxh`>^P3R@1XGPF24M-oxxMpP7MCQ
zq;BXr2{x!kb1h6867QWNFd?-Yv~UmEf8XoocV+1R7tr*P{C(lcE&njS@?p;#0HzF<
zi%->m(pJ%gV*MzA$olprzxi6T9?DB|eX47m`vlYXtAcY9C4~luwKxHL?)BEdVHOQ_
z7O*JIA4I5Joul)2(!QeLu@PY9<z#!=Gu_?N+LvRQ+YxwqN#&`z_`#aZ6dA2V%OG`d
zW!-~NDNf=xV(!zav)x`?ep37=;Du#MkX<BiIbtGjS9CSP_*!dj!~yy3&Xy*R`w3zI
zL-#lwp^VIwqfF5e#wk$^vEwGku^Z{Ytuqzl{<)<3%VmeE&ZU(RaWjKIf_rp4I>BbX
zWrD?L9;aPvDhI5ExY#;~dA*Q-77srIRh-V)9ABAb2VIq$_Sl0+34Q;nT9rsiJ7DG@
zCIvj6<6=mvc~woPvkQXD+c)i0-TN;**!0O|fU~%Ewc~oE?!&Q^skpJZO=dGwQ>bn!
zKQE2d5L5S|h{J|F@U910jU-Q>Div4mOyous6o|J*z2ouyw_Q&r5l;DVRK%oIibB;8
zei(XR+Tl=d_Bnf^H*8HYIRe^cI#%bMkbgXPA=j^6lNc7sk*!<FNTEr=yY?<8*iP9W
zW?cBo;K2K;h81ITtQhu$oWjC1N@d%1c^-sGd!8AU6o*y8X>gG<k*QRU8e(EfWnc7(
zY8fds)>gZA1wMnYEuLa;orLKzDfPvA|AEhM5~XQe_cxrkiG!6^;iMG2TOcq%eC=H)
zEgQqdc!F4&IUx~{yNlG5BH~UkY=)x}{B;`e^0u|pG_%G%yq^QhB)oerY@R3Yj~yrl
z9sX<{PM}{njf@j3M#%oGPS4F9Nl&Rn2q#L5lD@Fab&hb64LR|+^PFq%&G&$yBtCa?
zzOytMsQ<yezwrd2_O|su<-XV`y`NxDYV^%*cW}zrD4XpaO_%2}WCSyH^|h78Y|pHj
z2E^oa!JZdq1>z2=Ut@(PQt;;q%9L4-#RO+t&3b%DF645aRlVz7qOpuQ4-({uQG>V@
zx!jY}YMOAxw{oifmhl0_i{PH6>Mcp$FM_PQoU|0yWSJW%A$`P{M$z*$INnh5yPt1#
zN$qKjNor_0xNVIW$evT|C}f@VwPT{T`s5`fWU`JBq8ybUeOyN@ESU!Uj?LOTsJmBK
zkIf{y=-dPr`a8O(yJuU+a$pz4#73E0M2U_2S#^b)>zowR?8+6TnOLEnKnG+cB%d80
zl;(GPAN0Wiz?1oMn3I!z5W1U7i-yL`%3f4n!8~}IQvX|*_(_uZz^;`n;&FEo!nKAO
z<Mb=VV5JoBg6wwSJ3hAOD>rW@oPEK`Lf2j#ND;5|2z=c=M#s3gxG{1oQ&OHT6&3W*
zozz(w`aVmwf!w!qaf@L?_XD~R(Y?Ljw?`2kmq*mqTFoZOiB7mKK!QY<bJz9T<oAHp
zjSn-x0$5nLjNM#IE<B?2!=GtgPhGn$WMtm!`_UIVpWcR%^G{^2A?Q=kWYsAtPER%P
zRxujF(7kM>)1idef1UN*9&u<leii`+!{3u8P4WCoZU3AikHQGnH=1Q95SuJ!CZ5m`
zR)esfmG*+puA%vv-08F|CV$-BzV$;T26)eEub9T!I`5eMLSh2skX~u=T*^~9o^C2-
zC#s~P7C$kttek&N8?w&pzPpuQ8wx^P4o}M6GQ}n;1fg2at0)RleMDH{Xnaam?qOq+
zadASA0oC*>=5gI?Xdh(9<?<+UFW6PJZ~;8JFz{q56P1<0{WUTjv!_~rMcwQ~0cqU-
zJjq-7A8bY$cVSfMK@?}R#eq=%#shpXQmEH6pk2pEh^>4l!ngW>mzzP#ZfqK9ng4F#
z{mR-}aY9jeIBY<tYCO|WUkYbLF)m#IGb+QGg+tj#E&%r^|8<|Fx^l&<PNrwC1O+|2
z^OB~*{X=yxi9WD=2hX<12x=5Tf5O@8e}>^VSeg)Qm}2x$=PeZjAD=m6^fuMQ;R-|j
zipx!$My`)xJ2UJsU66EM(~wx;li+a0%K?Lpc<PjGfv0rqj>;Ilqja<H*ONWGV}{0O
zt0+t8jZRNW-G2o^kzrcTv;Gp}&}?t6koOJmXi|($3^O$_`MtO%9Tq&`tlRAaP$@da
zYL9Ji7o?(6)(Mo;Vy;qeE(Fgqj+%ygq3#gEL!JL_rqWc_NTmW{3BRb~<{{L6rzNa7
zB!w4*C!joxy*KMBoWC<y&+i)heD(e4+K<6+h!DrE;B>QV@050(z+aR?8ePGf_>f?P
z?nLgS)H6d?(snzV4!?X&_L@)U9U=9dTh0@o2`C*lyP??2HTD)62)f8MMx6$Uu%w&S
zCv!PrkHT08_ovh}5rutoV_joYe`Yhb*>{x25~m$^*4+8Xa>3aWdx~#O_n&<TuFo2)
zMc<cpe{2#kNy);xdh6mD0E>L!1In@2fl?~@3psHK{FdMSa1;mM;g2CF2>cW%*`1L;
ze8k-Q6Hg<%Rz>}m=I8hb>l@^>9ps|#r(x|0y186M)sy3889AIjdWVW@*w!XO(Fl)m
zTBdyZ^Q9Vj1mdQY%;g&qe|!Q9_OH{7Q7$zgrN@9TdTLs2zUpef|B80&PL#N&c<l60
z#Cni+))tzgndqWYD5GW29Qh`gaEuOtf)$@um}Pg;a_owq2(V+YBRN<tgm<nY5DG1#
zg+u>h0gK?0t>$e$?PT&3eo&8zcibMWk;(1YBFpFqq2k{dEG~UgFnd(}J2xMi&Yfpn
zDC_Ij$W*^7Pib?Y9G!g^4bCM&X9}Pd-WOrMu`Hl`*b9=A?(XhqVIhu(yNEfWd6m5W
zx9Qm8Eg#P3j$=1YCPGIuoJ_4}fw{z*C=xh5|9d|GTf+Z=lmD%+z`d7#2kPqoybPa$
z%J4t0|3AmPL;v=_lV2<yo=pp5B>4}xf`7{IE~4Xt(u()Rj$5l6<CDg2G_=5v1}06b
z;Mo4BC$Po4IR?8e%`h=G#$B-K{qxI(+I>L>@}JlLx`Ieq7ncs;>4^D&a!Y-rR^pHo
zIJi{XpG(pmYnJaQ6)Lc;z2paGhrd%^K2;Ieu^X=l>^Y&RmC89>TFp)J&>n1naaEd?
zqmHP`^v0&ibKp5@PdUsT_O5-xb@*K_->aw)qetFO7eYD>SgYT^=<DkPpDX!W)z_8e
z!EfpC+fE};t=6M;FDQDrZSUs761njRz)DHX&KepnyoVA{-SV~lq2=BzHvJQ>8s3_$
z5ULZ;bA$76LD@v!db@SXOucINE6FPt2Pqeau3;kesi_A_0wjPU>n<+)-V1seim+cT
zy)m~PuMPJ(XtdzZm?1HVPp(f&^@*_JvNgt77zLgS>Ym55(bK#98D4E@m^i=dkxSfn
zQ~5huxCg}9nVdFUU0-_x$idEdz~pZ*(dF{%<6>I5q#<lT3+=Ba-?8Mg|8t0+9Bq+X
z_1Af$xTG|F&2(E^daT{rT#b8YON*P(O#?y(uzqd;gsiQwHl13kx6(~XvDT<Gd;ahq
zJh!}js@NgI+gm^exLTFFa0~z>WAF&*)#MWXq!{KTL>HdfI?sa9m!qTadkqP-w#U4_
z!d3<*M>};>CytIXah0Sjm$_h|r)SmHdT)BZypGd)4(!+$M_Vi_J#WkCH3oM1FOuH4
zZ|$yex^4UbqDy(8k;}h0-YK_e-^zi}>;UJi>x69$4Y1^aae*faIR$J$l=H7#x2;F>
zhz#xQg=$W>xOTR?%AULk%eJDh<{h<LcYlJSv1m!p8EHryO}9x)s68Qn;|6bC-2Yq$
z=5Ap~k;p==`b_As$03b0gz#v4q}Dn~r`-zj`c2&i%2bR|tB!rImI|h*I8$N8VYb3d
ze{1h;w;2eAfk#}B7M30tt715Ic9;Tu|57zxlAX1VP?tmjyZ%h*jMaS2^3sxYPGE{!
zo;*Y}IN{Ug!I-Y+`A6hN7#Q#ov|ouqeaUj~?~l0(E{zz8Q|^JB#a!&1vc|sV;BXj?
zxgQo5hU0l5LF(Iku{-%E!t=F8)2eN~**JHR)05C1sAD<c^NyA>dLn2;Zg$qGAVCV2
z?c*IarV$-_#cxxL0O@Cm%B#l0r>F))K>+56jLZOFuf)Z#<wHPTbD5)*%)IyvEe{(s
zQR^?_`g^;1Z4RX0V(5JS+}5S<KVG0ytiQe+Gs&F<>s;$gI36j)+2jT=Y;PQ!^~R58
zAn{LRHEls!ufg!z8AZ-z)ruB?9k1!hL1Zp+tv``(Ax(4Qlx*K=d;sheIXR~GXr_;_
z+bb;Qu2JO+1A^{yOhaK=M_b5h9P<h5)a>oEFm$LU`;80gwFd1@$=>mHn%DzA$Imw#
zVXda`lo}^-iE6LQj*isr8s|#wwu5L-H=%#7LK_KxrWvMK&m(8bcSeifvBtVB-dun9
z-RSi{t<`su6QZ;Sx^AA@Mc*Dnz(lwH^hBB%Zs@mfpRbn;!KfUs6H<uigzAmk!OCVs
zy(@zFjqAx>{?Ml^y(6s&;bFzgv|t+Y4Ftk1@O;sKZ|!(%sNSwKB!SnFnTyTA(Gid^
zC=@D~jN{$|Y<kD?39DHk_4)}sa)=avv#!UVBULcnhC(St;;)uZ7p!LMj?cPa9v*kp
zr__Nz=g*U41A>SpCb8e2NS+weignVn?=0>{z3jS0GPCGx7_ytd*oH5Vu7gd1pTC|n
zUqk+Rt?ty+l#*}&el0>2cN@4gb#!!0O{&4%u{X1S3@6>%b3LA@klD`8-uN*%SYfHz
zxZu@T>M>SA$W|OcvXh*U036K&Bc{87l5RHTou=bnM+jxHSzk?4@`q`|EQE5d@?pBL
zi>!o1N{pPQX6=Swwz9~?%~p9*Zcu4ZDH~A;6<^>Efz#qr#$Ll!$FE=CpyYyo%rUQV
z{yj~Shg0PB0Z)CD%-wp53O**|WI`>=F)&DBx$?OjkD5}=j4)dCAy54u$jQJ&1$X!y
zV8H$3E5IX%zow{34+y7tJ<b)5my(fTa4aW$MN0a#m>SFz_4<E%pGp@&Q#8V)(-3z$
zhY#{r7s@<jB#zJB1o)aiawC2HrQdSCis+eFmM3BbBCN>7Rcs9YLiNhU?lE&9VTh8n
zGgVQL7yll-P*H82lt@u~Bo5#(>3s8b*=gaAVVIW*$GICD-zM)fMjvFJ>hyJYPka6z
z?2yq^rna%M*<)%k<Z5HGdWSR&^&L-&N@N@+uAeD;EMs6`6hh9X<32(dn1lD)jq|@Z
z!ZrnMDNC1lu&q$=COIo>A_FESspA(y0(^}%3kyoD6@u3KXhNuZREY1*2hsQT_HH<z
z54T%b(}?nTs6^(f77o1^H-W$&<^gY~u^h88D{a2qC{`{ma9_aq&f=p-z|sdq2PuRN
zWpMFvGVXQ+Ya)|n)4@K?!<OaAZ%HfzBX7m~ong^L`*isdv3JbxdRnMc-J5F^4BS^$
z<qA_Bw0<Vse&HW>!Lw**Bx5Y#N3+f3>swuY;L;R3GKv#Q&UY=x`TmiCtt2*|jKTzv
z<&be^8=IO|+fD)hBo4#hg8x0llWi9d&pod100m<lr(J&uQLcw>-I0HihantY-<fA}
zhRba7H_-G0Q{L+8>TOO7x06d>R7t(7W7awt<Q+N$@`dcXp*`j^ndM+GV`!NcpF*I<
zV5+-aDvFkt!R{dig@U~NexGI~6#6<y+Y)H7H_mIRJXQQ&U*Kg|lvv+1-|_Jm@HkL%
zA1Qe=HEZ42sQ5671%qX_;mY4^LZyQRhz1uIA4$JmNCmzltVzQ5(%*xD$W4GX78y$2
z18_*oVv}+Ke%FG9s#~u$n>4@P&cRPtTc5QU6KZF_=qT~mIPp89q}_z?!k8<rfIZ!)
z{~*eh%xpYQ;*+?z(1(XI)^iQZ@#hOL*2!G4O7MY()%CGOg=UIuaL{isZU^gcUjXyb
z*vFxM23N_ODRMrZK32}<wVJ6*4320>x(Uwm@BGEGyzY6ECJ#X_R92$C01+}J3o=);
za?g#!Z4}UXw;FCUGvQENbJc+Mr5rXRDnXmA3+u*n+kG^|8_Vt$fG-X$(<oXgBh8GZ
z<CnB+iQ9DquS!0Ek<9N0;arB;1f)bVr0N<PHK<IWBdM^SDgx4*85Nrpv7m7Za*Ev7
z*V;U?&cM9z#fvmQJSu*Rl^DP$9SXL)oA5bpfn1!iG^ZOs8IAEj1#`(B^>iafMg|7N
zi1AY6%8iYUf&{+e2~3ZJ<6I!YnX7fQ8qFKqt-si;a%VGM%Vr@kDfHB?$_5VNNDiN;
zR^KE8$IF<xZrm5G0YjJGy6w8t5t2`q^9iVttqKb2FL25EJPw-QiD_0?^f!5WM<j(_
zFrW)LN5aFS;6F28K30z*1@SEV4Is^dJZDrs&pNpfz_D<-JI#v)vM0WhNQ>7T>W=M0
z={)H9BxliG1|{H--kq)hTWP?ZGx4C44(Uz9R0)~y0G?ir2@&U8U{303FJuM$6$$Cn
zPt`#1Pj%|fjfU1Fre12L--<f^q0`)m`#(kP7vaj6e~aO~2A=WoRA)N*_~C990@uJh
zXVCz<{pVZv3N^B@AU~)1ap&wc^EbYK{_|GWaf^zt0`4qYGSaDu=pH~J(dw8OpYv$G
zxGnQZ0!YDIy@1oyE#PTN8e4_4==p*vwB=oO6tNiOVK(-{`}a>=jWvOof{ozin1#t_
z_Etg|;Hx`F)#^0}VdU?M6T{95J=@>4qz2aOmihsKN4p=U3)L*->d-p*rXo%_jEb04
z+k%4)_L83>AzbCf??a2c*8){gOH1#_>M5+;&2MGUUTFcf{9nyX4RLC^6O+I8eQtFk
z4{(nJ)%s%a>aTUhI2fNxKnU+)xCw*~ESs`Cz$CnJ<0hZAcnU6`{@(4{Pkw}*wPNf0
zik6m|<6XfISU^F@uUR;*7&qbe%6fEFGRmCr6_I8H_CjF?ontTtnM<KYu}zHM*yOnT
zr?m54UCT71C^cvjY)Jv4=4x7aT~6GGVEIlnhD|Z%sU?%5US7ElhFzw@$z6(=hEmu#
zI0;R0%FC+A|5Crb*~u)o*RcN)V8)!!>A1M$>Y2HinD}T_^OMg^-qA!$rF$wf(A`Oq
zmyR%F#U4tJvrtMi1BAW|XB_QCZd~e09wQf%>I<mNCkc)HD;grXf{z^4e&!M8iur>)
z^b(2E-~t-QMg3*3sCn%Hfx(^vC5(xGYFDiV8VUeWqu(A3$?S0MHrfpFSK+BC!NlwJ
zMIA~ziX09<PhF?sr)J#(@2QnXhUpEdec@X9!W4{9JpU5<9QMk=8CtPh&f`(8cH@2U
z%RC1FsJI2v{*Y4EEvfyw4PifG^75e;b9Em9KGvIuT+U)_xF57~P*raB+1_H}Cn6)m
z*kaCEE&Sz`QHNUQW60{at4ebL=e3fkC>7Aql0xuqyFN%TSW}D<Ia#VTyf3_knwD+K
z%jR*4*pV`@`CJ8Fm`k~&EjfFhs6(3`df;0kY~PZJm{+u7^oH;~1}FuE<?ScECPf{(
zTn`6_3r8$xF{vDWB4xV_`aQUht9hc}wd%S|dBu^)rf=a`v2vP0X0BvcT3j(%w&UfL
zzvZ+m_>tawI8<#)i>>I^=|aeq5WAzP=^0Q6(~&&VdNs@l*SzEQFdp^D+p92ZFmg@Y
z`HfDZbiuEIb-PFjlMr@QP0gkcO*Uv~XWs#;=&;@YvRXLtWf<N?NoaA{=e5ckO)#SG
zve}-ChV4QVa&Ehc$akzz87lq*W~_tBK3`yb1*f@l6|ckQ<N<sjvMn8M5%3DiUuxt~
z35S=RwHXw9&;Pi?zlp!ltS{jG*1ES(`T;I3>U2xmbJu9#rrw1^Rm0g$STV~Hig4y0
zIeHbeq4zHq0AjjlwaDYy5v`mOG||>`&fN68{iAI~%7=b%eg&z51s9<O^r567O6_S4
z^*AE46Nw}#2?;uLt{qZAv%!+FnWtPwD){n#?o;ss^+R9l^UGg}N#2)=j|v8n&7ZXj
z0C$+8CdmJC#IHDp-BDaiINa|JF$F<)9pq6wi}Nd}?ezgJ0}dNdaAb-3M+iile+K!$
z`MoW8RD7owg{7PF^10coA<7m(jFhBAu3e{&Mn=TZojW7-=#c=DA8Hs}WaZ*W@v-=5
z<#Mug{A2Kws52JXkXM6tS-EfN8k5;@6W^=Xicz%Yqsb>D>xG*>?`u_L>ddNOAH=eJ
zRAS=ejUk*QtVOhugPjwy7!-YwqV0v+!}eS*WwF<<*i+@vm1=V&r22oJ;$q*A=vtW;
zZr)hbwODX}U%uAG=6QX5VY=kx)Y#P%L3FWeTT~ek5|B1NUbsDWG&kcl>%M=~Ur$TW
z>2cnN9~94tkebOLcC=b(sYblha$5=*iMBmF*dQQGu+lW|;UIJJ<T8E%JzoA2Df85&
z(tPd}GdFU!-CP-I839u)-QbUVSzf_@lPYH{%R}{r@D?&BRAKIb3HYaF0L4|efrbV-
zYP;vje)YG4-&D)=7dioxrYI5_eENU@spQZh8d1zDvFCt$<-`j4d2V&`UR!&Jp)t9v
z%pSWaa6DzyYblg&xuM2+eaLWOhLB)Tw_s`kx;0opS`Uwl5^z{z4lMT2D$-k&V*^05
zYTnG-p$EPc9in~<0}1b)n*+=FASbC+fsg&SC>iI=5p(r7M<?~2O2R3a_3Q@na${?<
zN%g{gB>Z`vfRdT_p-mv)aoQ7Paq3V*y*l~*C+NywZe$Icqt<nulco4RJZ5l-@OeNx
zYHP<Boe*VEx&FJWBL68kHgstfriFdsUxrR42$P1&<RKr}RR%HQ5Bt8`u*;lJ<Q0ky
zskrrD=rlSnjLh*o+rY(817gx4#uxPC9o=8<*3#o~iaZ&JT0u^_TAY*(@xHL+#ls3k
z4bEFmIcI}lz%hR9q{atTr~9$BQez;zv@em@PatHNQLDx!zT{P)D+C)kl|NUZEe5%p
zb`)%z{gQS7<^}u;QnPJZHk!+xWB2RS;X$T7#vU<L+(DR8S=`@QYwcv3T-liJyV%@}
z-CF;mk&&Bw=>4*5xrAer`TFGIsi9Z9f(K!0<sg7MGrv<w^1R&1i%6p=UujNTk9Oaa
z_bNaAofFmfbQG}}79Q6C!1slQB-uTQZe=<#HsA~|6nr<&t4W^s$?$Al)meJ1ZfN@H
zq8yGY7=p;9wO@U7O$1P#77&p7B6WGg`lGBBqx-TL^$`)lFvA(wuT@)=Mm*iwUq63_
z_czhDum9O>Box5cRlAEun3m`i9J%cT0$LNlU`~7?&r*ZG7%ELn42jKQN$b@u`+E0n
z$a};|cmd#%hZ!=HYh4^G-s|dev9X!2)+BVw>81;Q0zi{=^OLV|KS-r!7G}nS#}fT%
zv`ln<@;6Wl^2fVtijg!A+EH*H`K1pA5TkbxeATR?{p{g*OJj2p-Frl4g6^p^)q83U
zFB;7|#}O^tm6U_}XFnRKkm`+YeU5?F^9)POlvc9HSC%1)>F+xG{rp6X45c9KDcWfV
zlapVkbrRn;Ti^9rkY78{=}dA85)<thY*w!{9SD!qluf9AOiB7qH(^+yrkXxfDA=q3
zggW41<2pGwruTl6gb1hR7i}jyl+d=%_I^$HQCGWKOrMr=pVun`sWF6^tuvfXotY_W
zj}4)zwcWwn2@5DrL3PuSu9z}UesOK4*<c<Xg7vR6@NHO5)_5X+dAnWDaA8u6eQ{T6
z$bkg85fH2Qwfahenq{N@5fOnHLrPn>AoEumlh6(7xPrA5x6*2E)sOfB^@5uT*$ta|
z{T8wQ`0Qx%Aw!ka=YHo}j2@BhlBS#LN67*E*(9iBKOD@(1<|D3Nix1nLxW*Y3`GCQ
z{=ksf%olU^p+a210=v7||LW~+INhfcAps15B_KMtGW4vuwYpbTeRXP1f2%9nZo&WP
z4%tgvd_nwF9bESFU;<{yheIQ(13G64tf>tjQU<i0Sz}-5{;80V7ASl+1R1s9?18kO
z@QaoCw!B5Z*;;o1A)GF~F>i#Q{br*Yu64Z-uCIytLKvDz5TV$wU3cBe6=BLBT`(UK
zER}p2auTNZ5*?kt+x~>|O-9{P$um#78gAXDtkAd-+EDq(k#%ojF-1`^p%mV`-|0sb
z=v)*fYc%bfpU%7Hn4piU^tcsK!{ua>*njr#0p5ogI>&6&8(p)9iiu`y9AzPZG}$^7
z*slGwzL`%5)YcFUOGi+jpN~G2tkOYYbRQT1E+H^5#Fc<DGCa=eqg4wWG0CRcvAFOU
zV6pF~h4o*uxNo*M(S}32BqXHt(FC3_Mw_QPa<#6E+DnAML4|!5ZD=TULcyD#_A>S6
z+||Jx<U2`t|J8oSLM(Bx=-wI?=;)32#^NKX6&#)_PUP9l#XC_BC%w@mlRCEL)66wy
zx-$9l0wFVl&pkOK|M)FFz4JN!VAoKCNh#f7c+V<z`AW-byh}}u56TI^5_JK$yOZB0
z5lpy{am;F1s*F<70C*}H<M7Y^bZ0!PspTEwQY0l+Z%%nM#vc?q3Cd=WjokVo)l`Fr
zWPEG}P73&tH?ApKW9By>l5i#<7&!MHC_~_31Gy947M;1nAU~t{{v#2dah0{vy528|
zV)kYFI4$qNmNtzxCdqCpu@V0(NYzSRJx(EAE!Ph#KLu`=vRNC{s&s09br3{Zc==^R
zp?4d!uBi5Hp}5Q+a1|3%)3voFaXvDN+&baG_Ui6-1}=X7pRxFKtG!X`8x^2Lv!**Z
z1VT3@UCkjZCi})O175iqhGu#{;g=`%(Ldl8g_rE1vhP5#%rrdqXmxG%s_c`mx3`C5
zg#qByAx}-F@|sIHW)PDzCE8!FD**YiBk)NN)KW+MGV#R0fRI)y4@_{uV1wyXMr#h#
zil$)jm6=x9EfiBd$zx~ZFdJ>s)P#_*Ca;et_<t3?vk7RxA)|N_vf<nyRf|Mkn@NNN
z9}e!4th!%V*ypZpC=xl?Tu)~wA=RT+?m??5{FbEMpzOY>l@3VB7_)b@-I%Y&O}it8
z#b;+1VVGN~kT+fq%LP$pp!ob_Z>Lf1VZ43<&H3W%OJ^vGY>yOCD0{!dV|z(Xab9-x
zUE$pYZ1IVE4RXqJsk@xdjneu<qt%)b5Db{VRxkH;)OtN`J)b_0rD+Hm*KIUp${*})
ztE%y5$WUUK*hx?J?_5^bq$^}p64VnROFn3h8Vs29TsiXT95A&3Eg3JeObo#x7k?O!
zdbS(aPzzrkr1yVC#-DeCz^!da;At?4e0x<(#k*#AwdRfx-O1v5%zx&V`0=e1y;C%z
z_B1J(3lsLp=HSq#hYCC;8|DuIfzp&Ew5e>Q!pSG&X|)-u=iCUp4}Ync!_EQqNf;j?
z8uFLL6u{6DzK6E@--(RcQ$EH>gMWJ9m=gc%m8)vKLnk{Lvq@ZRcKd@~LsaQRhQ1VL
zcc_S~e&!MDP&y45@B*YwL|4Y}o6O%h<e1m7vv1UmqP`|%Zb)is{z7vT6{eOfwk2IP
zq~OV<IVZPoL3J)Y4lkvCOrT#ZVN(fYu3k57K-qDH{*KSdBtWhRjSA!6F7`j97Add!
zB`lz;3!^?N(nlq#c6%{JFPTe6Q3pG;lZ}J*z00x0C+-asd^Gtr`^~{{$_JM?H4avN
zfIGS+h~eDdiT%?elL`lkv009YE@{iKF<SvB`$j+@2`qE8Cf9u?puUEvtH*$ndTV?8
z5$12f7QEUh+KAgc*Q6lflrxu;!nlbf*6k;2cFqS#2P>;Yzeq#dbMKb|5k{AA*e3}A
zp?}6e<`p3a4)3Q)_DHYoko*X+8~q+0(~QGXyTDHXseMDldaq#FF@qvh;JOIUv1g-+
zyT4x^eV3My4GAcI6xsu11!&h8Z=Ww_xiJR4p9apu76DoX+>TqqpkXjFs)*0kKkc{F
zxxh-Q{jB|ZTu!Rz_n|ZTg#(+1ljirI<eSZD0zfZ$R4+w@6%T|aj5@{DAZlyu&Cks-
zC?8&RHTS&hS#SS1JujyK14FG1x^<)158!)@uS$Eu=?sJ*F6X>Iu2*77NIixsr3?&u
zV-Fkr^n6Ck>;bL@{9!2toF7qw0EENDkGdx*0h&&fT|@`u0dOO_?6^0F>$;6eG@OH~
zI|>Vl6u!dEU2M^$UV-<3yc39-G*{QUNW56Ru5rHsdQwuNCrX^iR!iz05Ftdhb`B_R
zu{*Y*fi1XV1?g)}h!#x6VKP3d0NSUG=EYBXddvO~kUS1cMf4{X(eBo{#ErlLSss$!
zy)1_7c5tNp;gedasDt%_t2EQ<Y8NCIp*s-Nv#cn@X*jFe7eCtQcqm|LKHat$T{suj
zwOV#?fu9sidfnbj_fkgsfob0xN~Ra|nX0EJWl(<Y1W;y{TTZE|im_X*JcALWp^NoD
zxG5Q!SoU|^p5+B`w-v0W$cNh66vzCj9c*YsPj06il^i!o)d`9BowdB>vrn%(pLq?)
zNd>j8+OA>@DTAi-S(EW?%XxHg7@NIOMXzjOI^EYE27Pc3yRSRyufP0;?ZHVOzYpQl
zWU#Y?Rq!#dYBg}}<%~Z(ph<N&^pkFu5&wzc1%^wY6<OKH!2xw!>67bnGnakmZqG_k
zzHh3_$#wQBIZs$Hs!Bl~u85}t(jJIOq*Sa@gr~DXDU=mo8ktc&Da7+Mry<b_tR@#9
zU;(67?ctwWst;sHAm4i|9#>xCcD^|q`AU%v#tb5j3O}HAqosHyK@~97!hdR&<GlQx
z_Q%=HGUdw^K6q{fz74E9ZO{J7t*J${F+EF9XCVfRso7wM8%@%{x<a^eqii402l2Zu
zPUOS3g^#DmBC{=nRA+ihtp`F7;XelNWg37gC|P`azBOx`bH{Wc(=_)B@<Fm<Gxb+c
zS^-!o7#9~vRv%oVD{jsNVO5h@-0Q~7cd{0#CReSvektmQSusuwCIxOGvC!dHWadFd
z`zCQGOdGZ$KNHBU7TkMjR6y-3Eu*ZH1N6;Fk<=*xzp~ZLffVHF>`w|^6b38C={3#+
zm*u5AB>vbx^?;;pI-=*X)Y2AGoJUoq!nO}|NA5dRS{5AG?FOu*$}>(IWg#Ki4nd;z
zHRbrYK?Z2_RBkV^07fUS2>`AY+aofR*a4BXKWWPqR?7F^X7yKJpmKh<WcKfc;ViMv
z5#vI6Es^R-mFA?x@jf!jH(R9!t5Hoqz5V~i0xTp#fDkDq<*kKVYNYR!cbYLUDkj8k
z|5k{~A-0~V>1t@ry3wlkZBVqFPjAqEt7m9r*1K#AzS6Vb;}p4*oYoqi%i~vYxgjnt
z@R$S!1Tbmj$NBewGX?W>FA+>?jkFM9Vxp#|!iQQLlA{ChmKr{8UxTbrQ>$IXG2bSG
zjs`8dy!WS119WJR3Bo|PztnEzO+FLyJty8?Zs?IG1`?V~LbpvBDn$hEB=bK0Cpx_M
zoVaMK>i>@T)#4vp>-|S>aEO0~@%3l@C(Et2k59+tWO~l*+Sm5hqzP}qOp^~o^D%Vw
z((E|_e=~FP<8`=N-1l?<7<S3+zKihuV6u(}4Fi5qWVfo^|C~5+O<8}Td8PjMJP8Q9
z<;z3YcQqm@pQ`K*r%>~gpq)AWt<rrBeaS}0BO~^zgqh6<2$aFTnb{$V@uW;I*~jy1
zYx5l-fbhb;3yvNkL)zaA7lm{OL>g5(INg|d{;jJv7<U;lxBk{h5CaU%tGmBL()ry6
zlAI3cEx=2j<`%;BDtW=iR%+=V!fu0VvmuB$-4#idht$~bB!)+!w&euNEoc1B>wrU2
zkwtr;u&<+|<JcSE(uCYpE~Polxhg&z0NjZg&R<XZla>!z+Q@Eyvy!6*SlB{SKavIv
z(v1h-rF`D&W&voQL%btkci1vzE-p8Ty83zy$uh4$A0Lc0`}jAKv%)ERX~9gm`|sb+
zr{4?f4g2CeiR~7niO9$@Zlg^H$<55*SKovXZ9CQ-;0)JYgRNRFslMAyk;_W(=XD=2
zmc5*us(Ull@Gk47(%>pJgA71VO~g9&9!^8yxHvajp1;3^N;4XFC%WP%xfkKNlb#<V
zbz|jLCUb%Wo)nm>@j&_Yr?xEZ(UhsdHUuiROrJWBo?G-?PfCCXoI0!K73ON{;V<2<
zhm*7epANX0#r<S;@SV?o#X{%n@g-&e=N3|dn-UrvZH)0fXZaIfZHGG9?7MUV%7gQR
zbJ*DO_1p}fqXioWhx6r17nqHUky{5*KJbryvHY-S56K0czvQ?<n$rg?W2dITsrdJ8
z9L%@d1{zM*r2am>&=;wC2=2*jNjK|RDH*9GHcMpNkZz)Y69=OJ%bORdr7_KjPEQUe
zRLo@6S8&#`7=8z5vF9cx%+GS#u_@Qj-z-YN$YRQ7KWIK-U7AeaT;F-6tvZ#u*K<ck
zZ6!$6Te{huIZKwj!%dOOwL7pu;XcQ}NMG!E-L0%&$neP{qE3jbAl=dNF(`0hQNSqB
zo!?T_z+eU56@i6I-bBaRdl_HE<>7H%%u;+er6|zHJxw$?a6I7qH@9<?vXW9+h5XF?
ze1T4VjqvKu&OEREnYfD!>f2(gZTc`Uk?8E`2*hnGH+Kc58<F#z6ch=-5e1Aw59oJ>
z0-L|>vtoUb7YgFy-v*`*fxUJfENeHG%~)@F2^0UR!H47lNa&~Qw9e3%FVY?pJpLa1
z9jM3=%7?FOG*BM4LwlZs?`JqInRM#hPIs@eH%Q3LbA`uNY<cpb^sIrY{OIWDOoee^
zNZxk~%t)awF2L0&V7Owr?oF4M17n7uLe0i78qpAP#xR40DjQ&M(fn(0ur|br2n!29
z#L2dwuZM5Ia(cr!QR`S<0VP{s5yz)IPAQaw3?+L`)Y_YnJ|uBj?C$IBMFQ0zm^IvB
zGUbqqe%ZNzN&ejWg^@I=so_Tz`y94)cieVNxaj7_H`MW#fq_Yp#c@RkZvFPex%rBB
zO?fVt=|;Wd2&Hm>=Ld11P(4x?m6OZz%i0F*7-%1G<+v!qIP0g2Jo2*!uHv|IvJi5b
z_x~6CxbK{C<wN!Osm=d_Lw$;i7rzLO%Rc36Yne6JOMwA#R<2#7-IKzgc9f|pshhxU
z1JNP6BrFA*zgJo53h~uiP&*ib<dG~&3;1EDg#SsyB+4fzeC*M^ULu}usc)!|&7b8~
zF!(1$pZhFmmqyf2Oiue(cQ>G{HOoy_c2;BK;u=gl-=ee(k_*?@6w8$lG3`H}Qof0e
zf$N!=JPTU^?d;%$wtq;1jI?wV17W{11qgv9BO$MFy$PUNmr+@GxTCKnJPg9FC)K<E
z+ANJt$UkUR9uajQeyyWg_VxT>w>{7sOAq`?kMbO<>;Zj{i@l}PM}qn?(~GzGTv=wj
z{l3$M8Ycj<zc@jv0hEtPj`N~+A^O@{CnW(WT+MG5*@kDew6%HZLX4TT(jEj2_Y!0=
zf#z{2{>QvH(1LHG0TWjv!;$768k%vQLs_L;`bDUV3KiT?VdzxN_Kz(%(exviEYkx~
z>cT4@aQRP&D8wWf%Dn`{E6vB+YE?Ma7QTY2Ke;5L%Mkfq09Ijj9u*nM;o3iog-`k5
z{Gf*=O^jG3v%+$w0;t8h^^T5lfxp)Verb6*2$hew*s++xRw}t^YR1615hKtm{wONS
zD>FGcZ81|fh0=ayf3QL)=-C(rjl-v8RicR)$|?r2_dqn_I^NstgXvKew!2$^{L5V>
z4K3&(hr@irW2kY#`<?$(?hUUaQiv*GSaGD`YPXg_)xBD)Ad%9YQ92`<*J-P4!xKj-
z<uSvX7cZVM56<@XwzSj%X9y6yIt`|^dPzsdw*SJwkcs8xfBjne*~5*kEfCEk&pQr$
z9QGRH<*1ds1w^G2ICnbwH0=jXI)Ukpt(_eZ18Fr_<iy6(!G2^a@R_#sjjdMt-lV;g
z>HGETS917*$3?mEsnr9edv27vn%R)68!({M{ryX*wb6GON!hD~q;0yUn$O3??mZj^
zALLL?MW6ogcH=?5rF>nTQ73?O^Ej`uLKWNRjZiC(*ca{QCz^x?hMG@Crx<*rQt=-@
zQebKIKO!RA*x~tf&{e7mB$UXJG<3svTbfL$_U9QN;0(nhAPCJs)EmPx4$8txIFd!E
zygFIc21K@Q0DYIyt#uaU=O0;_D-ki2vUNoAbGlBONJ1{}3PWttqz&Y6tY)03QkbbB
z+{hXAW%MueZEYQLPr1H6t_S6n&Pn}T^}C)_ss9TltAiFwPmchCP3K79ADXl?mtPMi
z9zfOq#O$&AM(UYQ2vkPiM7WtsIqlg>Ck6w;wF;b=@=9VXl2%spbxGI24=g0fQ(Rb&
zH9sOePef`0=H;;03_}6`v*G<WvB;&>`1AAc`Q`0{Z|kuwvj=TJ)>!JBumobV4P#>|
zNCTaca1xxGdLfaId86;je_%31ffhs-qbpC;b}VOsoWay_6xLTao@BB22GS`fY}5=j
zrIs3;f!_l`_bnElU;2OWXN}OkgpEGZCrRvw=BxfINyG);Ljtne_IHYvT^AIyRZUhA
zFco{T8b^zaF0x3x&$hOR$PCg92SRHFE25+ygyc{AFMDp!B)GnwJ3pC}UD~N<t8lxJ
zchBXXXO;7|W0ow%T5qEI5nCGw5WfbhpxIfs(*lZ0Yn@u>xk}@K-Ju~CP`YFqPVrV+
zFPtA&V$jfZ07}2nq4l(8FVY*m;alMMt?{%hL<n&-L!@M<ObolnY>cau)m*iMUDuLe
zm4-&pjaGPEII7uk*eMbDS9GpLO7e%MV=&j82!_gAofdYc>PN~xu%kp8Z#>3MHI_SY
zK_-nTl*i4aF)OQ+lqyLi=o(TcOhvUC4aR?aGqZDz2Pmhfr-4BsRB3%(*CQw}5M^~;
z8A>(ZXtUD|>^Y_@EM1Q#|Da>x6%(oC>&R>>LzxN>joqzu8d3Y#bMy7C{O%_f4sT5|
zX1ASkNZZZyMT679T;m}s&`=6az0i-3b1@<4*|h$as&g}~&bxsT6oc(K%B?;E`XCl_
zRUE{iWZs<f&qZn%ZQ^IZl>GrAhS$o%#ik%4P7n64q&J@Y_Mi6jqEk(QFkQ0HL|9jj
ziw)*1QkRe)>D@q?#<I#4<STG3FPwG~@N0BbTvgRSHHl$j_j45wkz`?JFNzw<|Bi!<
zl=K}-UyY1wRNky`faYg|2Sme)gwA>MRpyhw=aI(fprHi6yk)!tOawJ-C=yco`ifN(
z*>fNi`pUuRNQT9iX{krbk@Vfx#B*BYID60imys(%n?%ZKNT0ie8lU<)<^YuuQ}q|`
z8j}u2-b~%;Z2NYZ0(K;Xpscc#k-MLqR_x--2_F__qk8?vQ}FD?bLGf&ioP0l%+u>J
z@%XXe;o3u&@%8SrK>yL`1N;XWkYEj|P;i{KyiDC5%lUJeAqc&=RQAfMEv=B3FT0ZN
z5>SgBzodCx66cQt+wV+JtjH!=r6wdiFQy9Lv=nXriD&@F0zC4`+#}IaF0)VKRl()d
zutA>f^num<T0B~s4EF5p3>|;g!MO{;Kk_7JqIhWCER><Pm{0(X3ALyGQk9Mu@OhjB
z2EVV0H#|ic#BFUSQ${K+rau@PixFUAVm4kK^c)&9`Mmo=CFn7n{1$B30_Oc(gy;#p
zHd=CW=f;zRgP*P|50{p2T|dc52$lL^&KOizV*@=A3crrWemqBZ^VyqF5t7##?bHYY
zORv>+Dk<wNP*8zkO5K6M!Ef4R{Ec9A`=I?WGc(hILNX)-q-q%(*V<go485D1o8_`p
zTS!%o*QX8fJnSPszS5}l;Lpz&=^<ukcpNZYVP&_~Yr0@Qp~-HYi8xtWl>(0!dc(#*
zKNzgJv2HHxfkL&l=5<bD;P90Xd;2?e){`MdNBRdna)LmSs8emb+PT*Vv-X@|)W*Ui
zZ>p%nHJyvY>p$M+A}7ZLBXVew58RnDY9b!2in%o$+!$KDO->8BUSDwCUpeY}ImKAe
z&Ukz(|LI3~_?rB~5n%Ylt5O^xX&15Jo)#7J(=7X>9ZD@TLW>(3AXDXVIs}>sK&KB6
zEfymEjOgYS`wlSN0Qy_8H|bjYI+~0$P+7lqeZ6sls&PXx!(N8IfEC6&R-EA;%kB8B
zLPIXevNmLJx6Ew*N2WVqnH+8G*p|;rX)!T<QS)`4$kFz_b=k-F1l;zFiq!;<=a_fs
za!d)YNS+ciDlCYg=r?k`_l~zxVOswn4_m(DD#XvNTd4S*r_xinV9YBwSTlvZ(@&N9
zv+Tf3vl5O+k!$(ZWK_w4p3{2*0HMF(hogTOLu|e+o(7{zbe?rK7mG2Ay4hRodAd?G
z5iCiBw=j^9dI~C!d38GnuEWw@c<>@9KNcSI3)1+CU4MijlFCy)lMPwY{QSA8X%76(
z=Eg?$1Syx}1OC0);_a)J;;qu)r*t<Rx;6H(ba(!gd4T=oAHM*1uPUG}Kf6z`?!gwi
zl=2P>FI)G%iM4g1WZ|#5+U@~t3O;*zT_3gAyMqnxMn)>q(s_ve{sg|G=mwW#v*|t2
z&8_KjHhw1EVqtf6cmDe1-#;`ft#c(!xYqk)$C8_87KyGaKQ+gW(7xg4AB_ffi=al7
zl#+olA;(JnQOMrSk&W}~R{z@`Y83>tpAF0L*mC+}0DMmCCq>YBSJ+y?T$%B&CLP3U
ziHHpLl_jlJz&8_`ryCnI9O2jk;l|d|88X9DrQ$1V2|%o?s+E+L@!ScV|8zqcq)G+&
zc}Ee8k4T9w<{PTG4@OhD$QXjk%8rV@Fmfs#4lA!_eFMA23hVi80{9M}tORM~`_49F
zLy1Y=@u)SC=+vX`j_IW-oK@Td0FGX0RjKSdl+;bi42tm~$cYPH|G|F%H7(4EgDGE-
zRYp2#_xAP8*zLcf@Gd)g03%qf^kLG)>N<e)d`k#ce*d<Ug_jUHX2xYLnEuKaZ)oG=
z)n?GnD0}cOrMNd?{-w-kxGk;|WeqPMF;t;Yw@mek^5>HlrrczP5il#b$vyb~s)oaq
zmzSnL?Ssi->W*p(Ja`96bU^b3N~fV7)T+?9{EEVH9f8NB!?0i^(UtR9A|xY&G%Z$7
z<$4!RRQob+{}8`mH-}twxhaed*bsoY-tS~Q8#0rwNi#CvaiP63v2wRl^JvL=^6oOH
zOYJ??cE-S-m5R^N4cObMFzRY#gCU<1hK5(P#*^O^L{uL=MqF;khyN5FP|UG!%Vyb9
zPUqn{x<sDi9JfsCaEuwZV|Lp-G&qWtWmI+dbO1IUW*l|c<!x<~pNCR?D=PNpqC|9W
z>U%WO0Fpif#P3Hdo32i;LqZgyfJJ7uRCK>Z*R?y=#`%o%p^^hcvb2a99|uSErp0dh
zC<oM;bCWg%<mBYDb91~78-uALcJmjyZF5yN<|E_Ku7Iv#Ejqp$b*<NY8aJ-GeoskA
zvInO5CP%JCMTnBffHY3YVn>5(%IWMViJ@}iTNyZAtc~?aA3s&d4%s`d1>73#fR>)I
zCVPHimty+H<Yd->_A&mwfZ#Ny7)3_y>f^Cw9cbKW);%Ps<|aAfW1o(^pVJt70#%nw
z@kz*61_|=YLGkhNNI_dv^YZ%9eK3?L=H4fwV8RNH=a-!W3Wk#GqPROraZxraZRhGR
zv7r*&?XhXkGyAI=9Tj3DtdK+r35m45Em60z!VSeT1QW`Bs`REU(%k9n&8pBI9Cpw5
zOFILnTmpBV$tqavi2|;^0v_CaJcLhAVHEj?O^=eI3-7`dM|hn~B&eJ>vJ)HaTh}i+
zRM+V#cl+Zjseba>aA!d6Ny^K8jWWBRKee#TAGe&=H#3u7xHo=s0Ag3^c)z(ynxOz&
zmR{|AKS1IZ_cgNLo6XeS>z{F?7#dz0q)VGi_ambJC@JEsa+rC{Wi=<az-MMty(~s|
zkq`6xd^V}h`xd!gp1PBDrT4@dFnEj0#<~r7?3|BBh=cOqB<reTW1W(7=R75Lm%rKd
z4>{LrbWRH4q%hVA3-P9=t2r=@@XM7|AEG$_O;+w2UGYXBw7%F2gvqtEn{WQgGB!Bg
zn~Ob<2254Y_>X!tv^b#QQ8cB5?bF73H!_s{-loY+epg;Gy>l+m2wac-g5w9<Q03-v
zoR%Q7i^HY2%6K3tl!DFWAU$A<L$}^-%(_X)ou3~ECn$B>#=+ry`Ba3<dj2V!Rh|4Z
z$f#5h_2Yn(ojDl-LhCuuMzxpHZWa3Z`a0}RYm14kpY&}LKG>NoHy=tB1iqAw<ZslJ
z#l*x6Oo0Rc8p306cea|(_9%vTex9$wTA8T-!tweK0d0PM9`-SYJ}#9&oiYAu@+R<t
zt-m-T*gvP>tDgwF_><NNV7cXv;kPmA^ln#M$BSuVa!G$A<WxPT#Qm3o?p$TLUvXS)
z0iWwii#gFnji4wfc`i2z2}Ddtt;F6`QSqS9yunY@?<l9tFZzIB-`CDKf1$Dc;|}jJ
zm@1JY7wo=t+L)PuJMp)Z?^u$Y)&3X#ln5KrL__Ni^7{QrmG(lIn((n{2{JHE!VXh|
zC7HC*>*0x?(}O1CG85}wxDHL+=zCy{0O<q{&k^AxV8kDIwP4ae<l^FT86O+FT4=#Q
z$HJc~vVlPhHTvQ>6qFyDF!+mS>!eL*;*v>f1UNRI3U|<SbcRxZ<+QMBU}(IJ$dGb&
z?*0IW2`QTxnogC9Ijt>kZqxA@$oyn4KB~Q-;BkX%fKe)bkGhyUOisJg{2sI1%3KWi
za-ru(XO21_<OhMZGYE~YH64j^^VLI@nS$L4j8f<oH>dbqd=I`su@_lgVPY3y=c_PA
z6VZi@gc)DM+yn+jC$pcCwoO>v-1GNA2b2;T(O<xM0FW4EzIR>Z4U*gG>^upPJ3E}#
zig<1URxMvunQm$>N_5`7IzmnbDR%gkmC1W>#YaUIbe)CCCDu)#Gw_HwpQki5P^vEP
zPGw|orIQydHD6(6jHZa{RM{&)2xsd&j#m$}d?^zXDFK2GJc#}uUvC{&Ro8|6q9`gT
zC?ZH(bV-+V2}s9AQb4+-rBwt(N?N+Rr9rv`BsYz8cXxdQpEthqo^zdj`Hz<%doR|U
zYmR%|<98=wRB&+1L_gPV7-8+}!@vs(XTFApHuo}RZM0ZHCeO+$nTo1a1WyK0$#*Y_
zsHZmWDy>*c4d43~3W4&+;VlntmR-ChQinHxNV%S?)N_X3#&l^$4UGx)z~}MxyWKt?
z`W@u7_OMfN@8<4%Pjz%A{H2X`UahgVwY52(jmT7OAMM})>%Bu6g4yhBZ3ACEyBE0O
zCp6`>HqvK=gmI&O40em*R9>fpbq&Y$!BU1Ds=ho#c*_jz#6r1j4=JSFm^Vg4vy=-9
zVe$yr_6|-?h4##}Z}(SU9~~V5r;<hrF!DKwxM~XNSjD_I#`@%Ue^yxr7}cfU^)Rn}
zadEOSj9o66tLeJkXS7#$Z6I5z*`p(pO&dNH+?v>zpGS6}*a%r+Hp&Lh>ZBH5-3`*;
z3p-e(y!;shi<UE5Ki{`1J8f=G72z{?#qxw-tSb*-xE^`*M&yn;@;dED)0Nv_oPYKX
z2B7{kob%9uTOOYd%gP?mAYe=qvgS)&lZN<zkLPX1S=-nE66lSf&h)oDPkp@Gd@{Hf
z<-3io3cLng1%)@Th*B3~$9!spdpblM;=<vQG&MF>lvki#yLP_2lNU~3Ma&DJe#_HF
zah!e!oIiHmy}dyMZl{gj@o(nd?89`zh1zaQJN!&_jqji2D*6VUfwT&P2L(vH#WI}i
zLhU3pI4z<4-1tWle{do%tY~WU>ctM$ORMBAtz);oC;t)K&ySfH7^(D{Du{3MU-yVT
zf~$l{duF`_@0`bV`|ZeXM0+@00yfN(MSka5h`QpAhJnFF3b$6XX!FVby0V|d`ubG0
z?M`!#ZVMLCDH(SkS3e^&Gq=r~I7cxGz-%t~=K%PAqQr&UYf6?Fgy0-CcE-5QqP(<U
zJ8vrw*3E{>sNz}_W@)UfcPebwcY#pH*w(Yc4C1blkx|dm+0>}g?c2LRCAMDdo`SIx
zOd^gq$YWciK}Rf;Ef+%EM_I&H^foD*-u9^6cuf?a#rWxw%klo;0B&y<OfHb{SRDd2
z6$6+4bbj<mEP!+(-<(d(dTm+B=H+1a>xNn8UiG=NLYY_&eMNPK{4R0wU_FRW)VHE?
zD|(JJl$C+z%tbdC)y#6}vU7e%)U5m?u(M{C8>w8($B2Q}q(n4c*?%ji4ixq)>G6N9
z!LJ`<8|A4~`^wF;qIqaS)89ln=jX-dW2v;X6v8i|4}cQnGB@pkaLuDyh4?U5CN`@~
zRV9}`YSm2Fv*S{8b*J-F5jaTsCj=(whEiu{t*M}U)c^W*Sh3MhArm`4Kex29!a2kZ
z#?=gJfTGnmk9bzG<k^^;(-&a?7;NKER4tm_V!b=h^V+rR^US^pDyHVf`X&bL)e=s-
z3)6g*K{R^5a_|+>*enKq552^vV>SM>xZQ+te&t+Tyw#Z`j?F;ZNWdqHTH)?IWR)l?
zz7-Ws&F~iYBj{g}y-mVWJ2uA3%GxoopNCb6JC7@dMe4jYtz@oA-}Khz-K$sUC$(Rm
zG!YqH3KN?a$1Y3F)jZtFwngpj!5!!82Pqd(_NTi|MY}LpM0<SPB5V5mQs+Yj-&t#8
zGLDcCs`s;&gvs%;LGy7ww<Ay3h~m07K*FnXTv>mrL3~e4GAq-4tw#ZGG1yx%ax_!q
zsRaXgORruPVo)!K8J@BDSVRs1Nt7K?vdkm2V@Gp(CBlInI5*vP2~N(USq4jvhXNeE
zQw`om{`DOA_`h_5wviv9BbeM2ic9{h&hPO6SfsDeq!PO4$c0>alO^tQ2mpUSnAwb?
zc=OUWPhGkB>tX7ozQyi62}+#j7sMn1gOJ4$q?yv4xtOImlwWrv*B;s5Z#J~qFxa@X
zw8ToMy-HDe)fbKOCXF7Rsi_(KVPQZZ3=gPQv*zZMBwS2rBpq?6vuD;ir1KFvKfuNv
z#b)*!R<)v|DiK{<EV(bqD`W_M)q7%oGHA6cP+%r8AaLn4y3kZ`=sJ!aLx%V#7JhE*
zMIAWVnJmmtFDi}2OvBA3=@mxbsYJ<hY+3ge47!<&qUA5le?@(<FpvUL)D1K*Rtx!n
zt5gzg^JlvT$Y$G-B2ygv2a-!lZ@Qzvx=`Sr5yxS@^kZW!msm~i6*=xo7JKocK?%S(
zIXU~=dQFl0?*EszhoXq{_xf-jRnk6<Yc&8wQqR4mo7b-%FUNvIrDI4%EuB13cY0@M
zXKgLpNLkWnX4bH)T6p5fY}EEMwXC2pW0>*qsk7(RrxGzR0o5U4y`wXYO@xk1LFB1x
zt}nRsKnl6Dr*;6vw2`i!K+pH%9K<QA5EYZ!4=W5Q13k%CzITl3I|r8C>98<wl@=(w
z+KVjpZz1vGsy9t!2YpCx^NU<Y`m`|uq^gAf7ZjP6yEY=~xwvP@CiqKhpT(~%UX5(9
z+CvBBVzcAz#}95x%WIHZzlU&8UvDfBDw166%_X3joQ-Jr$1DM*IoW6;>Y#6B^XMm7
zPF<Yr-tzVWSV0DB4n+k_6N)?Uz{tZYVgy?-5%VbqTD)Mb#?347L^E4uPXcB883`vX
zp0hH_-8t5D=w@#iU>n$-+%CJUep7_w9y2o)8a|no`keXvIft)beq!Pb>`7~;*-y~X
z)MP2QhugR0k-fmaF?^kwT4C|%OdBW!M3^&*{pZbVH+;A0YaN_0V`-`GNJ@4+XO;6e
zIoh`UMk~`ynWw3k`;lBdhB&Tjvz>Y|*!JKYIe1>@tAA?Kapm#9wSZIiEGKFUHRs7+
z5vJnORa~sienh+Ev_V(WDgTmgsf#D@=-yJ39!I-OWn;n0m-Q|-9hltQDuk6rK<KR$
zqjaa~c%^hT<wNT~F153!WDX-(b|WK#g`Y;tIk<)*qM~GP>Alk6E*_~qF=WNUgZ2*d
zf^$mmAE<0N-!(4GWz~lC6?GD;T1hNk9nG~3-U&B9jINnqR&Qz;bJ*E;M?JRPD}QI!
z^)VQ1k|yIt=gm1MdQ1_x;oPo$k5b?8=L)))#qrwr^F4aTM$gDdHP;)eHda|Qx8<<P
zI>R;)hJlyI%FYb@wB?CPW>i_Zcf3PF*eLO|Nfr&WR@YH4`2S@@Fu`b_Ad3*HCfJ8C
zkQ)c<Uxc5ezBsXN?WI#IJ=;99KRemeqh>!Ih~zyeMEdWufsN#nrrTEe?_;tZTUaD*
z<+NdM^heU3u4A}?b|niXTf%OmfCcMv>MNy3BfsZzFrP8v6@BPD<8_`|{10u*eM`*n
zI1KO!XoqG>Yb#?n`*RkSOwBRt-`{(bh=?AhH~#lzUiZE3@&Gi4_m?Q}|2T5T%O9V&
z#Q76(W~QZ${(Nn%prDW-`z<=!83G>xi9cR$Z4Yp0$eexU(6F%cO3GKb?cTc{+eOl;
zcilZCD3ecZR{lf+^y-pX2+oCGWz6tLh+oA;?+gO0$a#3q4!7<@CK+h)rG-um>5*(M
z^8iW@qt&P|UBXWNIrWZ1ojzQL*4O&-{h`qQbKp!V-;Ue?Z^Mqb?aDaKGnU!za~G0W
zlFWK7Jldg3`wJPq)9z9Wi%4RY_rH(^UD70c1f+5K=3|Z*wfxr1g{s9SeuUi3ZQFST
zbkK$Zj%L2a#Cd%DBSN((&pQN|Bpe^e``E=CTGmEOA=>K!4w0#z-WVW5p*KhPa50No
zSX4NcYsPwE-|V9H5wil4fHl)?uRlDOo<921loD)HS%cXk_Xk}VCV*Of;vbWst<5%|
zEJeUh!m9ImXfv-pPf$>h&3wf9WS=+^6tS~(xu>Kr-aohAkG3^YW;YoK$$1+1QabvD
z!~UuR-vtVcupy-K7>*Cj`qBd(-HpOa%}3$+zqh)&T4FZR?TAhcH+x8Ghbk8bM>MDH
zC#t$Crvp8v*EOy#=qZTV7Sd{FCN|^YpXH7TaWxkMIioNv{w+KlQ7G!iaO~ETE{968
zvF7y=Fcbb$-uEfAPL2%p^ptjXA*u$kGv85MJmK$a2j`;=x6`G{qlpsJVI2U_lkhku
ze``1C&*gc$Imu=F6Gr?#Fo}x&Y7P0dCtNm1&yO#{mryYh>FVu&>2o}1b_81L>2`nC
zhTEZ>>7)J4&G$#!a|uFTUD2E~PIEu}{V|h>mR=21%G7kTTR{Hon7T%iZX(oSwuiq0
zv%(p?(ann+C~pYdSFf;f7(d;(eWwYS>G$s43%PUs8k)IEX;{wP`}aqS#jwiN6VlQ)
zmY1>d@a&g&m%vVtr&XD1gd~3@5KdY$pMf-hP%&*&)7klHLCdbNoY7p(Js#K9o1;8_
z^7-aGj&gd&uR^IY#r%mYSDp6S1yGmB*6jTf(69)3mz&!0`dnpXx*)HE29c*(_TF;(
z^R4^M0eUOlj>lL;(Sd>HM%q*B>#j@NbHQmc&~FMmdTA<%hkfjMm80{7oeSHiX`<^w
zxoY-L`3};c6C3@y{(Q*&$cb|60|4b3Db$d#T3u7PJ9X#bbIRwGFV)mW0o&O)bO=#T
zgBE`vL}ujN#c7Cj)1$3!9#WpTY*uM;&@uMuef>`%_Q6>??ngm^J}j0tY-S-%X9<$4
zv>%vg=sCN7%Oc}s|BesFO<9J1{8hRG#oZgyQG99!hCH(qe{XMZpk^+=r{UgPopAfm
zo7IyfCLPNW*ghxUDd^A|l7SqxU3@=wfF3mh#wvQvAF~4;E30$gB3{29t33E=yJF|)
zh(@^e`{LXSoH?rz%$~Q8g8UMn)Ia62U4w466<h5SoIikI$kwbpKYdLKnH|)D64p^H
zCM4Jd%LgM}g^?7YuOis|V%<*G7R)s&dL1dVj*r5%s5W&%8rZ6;f@|S7MOC#tTzCR2
zyw=WKLR@^kuY7c#POaG=U!;<s%m<f2T2eBG(PacYCPOKmu{`W1o$7n;NoiT7j{OpW
zc18yt*@!%nrne!lj4X>>kGGt@_Df`(HpuY#G<ou-$;g&8krcsCp;N0)1R5x-vEsqO
z4k8sHI8~e#KD^gmzSvtu(d6^b(7Iy%93^3m(N0*L+xbVHt1Oj{YZa^zfwHA_yr46G
zKLIr=A|f<4H#DwG<@I+a_>H*vc-&*)6w(a6@_~t(N=TG1jX=5i9bmgQNeQ`ZzC>lw
z5Q@m%?kf%0UatSX_|Q?A5(j`GN%fHG^`i$%$)r180NRR9HXEY1e2mFLt`#gjNb+^H
zS?SLalSA<Hqo^@itgnu7mmVx3)mS^jW2$0OQbYjP3@B-f-+zV+hjzb$&IhpJZeeHn
zCkpR+;%eMb%u=MX238#@;|RFzXh(fdKTSoZ*Nxh*;t+muJ3V*mPjL_xZB|Hqm1<)O
zq*BvXC@J@Lcfo;^JYwGBPpm$s-mfO;1RZeek=LnjZCD0!UPJeK)q3AFSf5U{*qnPd
zOPfYH*KzmIG9l9GV6E%duZP=nZ`i7I&?|E8;4_tp1(=(5(W!BdR#n;)bL1mJKgppU
zA1n!-?CmZo>?yrgQQ2J_(6D_**q0~P1$Lgdyu=<)v?8M@K-7Q9w-uTLCy0zb+Xosh
zL7mXwu-y|E<zWx>4843N#{a+w_?oid>``CKua*9DV{~C)@yypV2*)wC$b+hEmw|^z
z3N$rJAiQ9U@DUE?F%$*uuZ?7NeQiS9jgE+E>g3|&WW1gv0i9MzBUeh0^;EWsi2jl0
zyL(&csZjr?_1uk=m+<t1?nm(aY`2YkB2#lO`}26TbZR)Z_UFu;O-?<v3&YOs>%&3d
z;VF61Dg)qn@n|*!Xj>7q!L7jJ2h|y!*bHG{P&4TITP#zd<zzJi8BVXk>$WvrnASyE
zk=Sy4hcJsvc@3Gike?s~fpomQyXqZC1()G1-InxJqqLzS`bW>d?JLUXw_9#m?h@hS
zXH<t2BAq7Q5<aBFDxN+gx(jMN?W83qpfml|CD+G@?6c7*tuc?t?X$DentFC~k^h{*
zmGF|C=WEL62(>mf{Tq<-`$an3EGc-6Dyr8dw7g@-oe*6ap85s`RG24wr5+2Nafpo~
zC1>5w8`ou2qd%?TW|K<>Np+PBuzBEaWh+ZPctb`(!F(NGwwORu1Q8n;D88g5EPRdF
z+Qr3PFpuENoroHbtJUUX6}>_Uva+9Wad2#omX)-$Cirj}#HA#oxb(jM5El^Gg*U0t
zE3v3T%w_ZT2nN}xT2m~f`@MWp_RbSLnMA~rpW@uK8NbsFwBuXl!?%`X`ld`;UA}2w
z2_Xy7<Q(19F!hLJ`1GGM{Nz*DIf3EEo<p_p8ne~1TQYGxE5q(K*0y%qmFl+Zy>zrM
zqK{q@<<#fQSzZvlm(QA1!m!@qb#Z*45!Nz;>}-=*%x*kt!N1$&OhU508~=Qz6`2NV
z(P*(r*HBNA$df?a1=J+n*qV1!Epcuog@sY9)~XsCTw%&#aGt4JdoyKszLJK)i_fER
zFFY$H#lsp6B{Z@!=9}xi^8$v{^6=`6?*`h9E&1yx7v8VDU(j<hP-)n~o!#Q-NE)ii
z2*0a%^_i`Zi-^`abhI|_qM`souX=th&TEy?odtqhb<!$i;;&xC@3sLbW5V_9b=3=Y
zhVY|@t4bdWEDJo^P*JZcA@%3ycTEi`V>z@1#a9Xn<o2h6-WuRh%ScM<@ygrTu@TGD
z(6lEq^lxux&aAndHTxm*fFm(zXO(%p*pmdjq#)&Dn_(-G0Q=QnkImL<99N!^xy7@C
zEt0={(wN5P2kwi_@E2cNy=8z2+hh4~k}p0hM^FD(@$+e^Rio^^Ev>IlYQdH2c0D}n
zchnE-XUiTI<3F`|(L|V!(a<=t#ew=`{K|&OwLTeG5PFj5Z#VoA73|t==E||L{e2i9
z80zZId=Jomo4#5a8W~9*I-lv8*B16Ncj9M8CRhZX;h@78NWKp6e<|ES&ytUG>o%q~
zuc(!kRUvMU;dFg@;lO~h2+b^xuWpLgJ4-#U{WZ$k?VTNq{vRHh^>Z```;FnzDm8?o
zu(0s*(h^LR&o1`pURGHiwf)m9o88*LfvtzS3|NbD#c$F#K*Z0IFrO%&*&yANqv`4G
zjpR1KO+hH6$sqiG>`qQ4nGEJZ@}xQfkra>sX}ty^4Ou5yc&@Cb9Nf>HAssjgpPQQ-
z17io+CVUq)o~jd-_BE4dj6XrTiVTY_*>v*(;g()qu||6aBIte;7FQXQkx^Jo6bLD4
zPn@5*x{|Vgsw^n5EX~z0)TvKyT@tA%$<eG_2bCWp{&KH3^kNZhdL$(DG)ob>3!Q&$
z#Xa9}vtR#HP+Sa0ZFBQnocH4W>&Nz+laEV+RpqU)p*(}fQ`{vZp0ec`XYVDyu^ox*
z-yP4|9Cqe$=uMFfhivrS?Kun+lPG9^T)*LUo9OwQ!S%7PrvYWlg}Nu0pj}p4&M23X
zR2dI$fA#i*Q?18KwUfze7XnSimja<)UMFBWppZGL&~ESyc?)1Kr`=zHybGNZHEtJC
z77GwHQ;FzWCsoHvc>!p3+u23%Z3O__y(%zp%Y?56>YD_uJHus0g_$D=Elf`9`PJB}
z6B1rW^-^hK<7awiMYeg7td;gF^#l0KcDsIRrEvPQ1m#RdCIEuf4v$XkS9*^cGmz*_
zqwc{$k-bH)C2!pDVos9|=}QLW6({fGEqDuNBlh{FrGpG*(?Nm|CExh{`$GkV;0Kc7
z`K;yY>pv~#f1l}(PcnGDAIvo~G(4PbMJ_HrL@zN6qka|15$G?oKtEP}m{_AuUt_gL
zjqo{X+3@jnW;Gq%j|m~!Ul|PexJ~~524-Bc$BEj*W}l^{f==;}(uvaH_2vpg$jA$T
zZ`Rhik38wAJG;#9Sxot(o-x1DGl0APr`oK$_R7|lB?LA&ZBEJo#LeDxVp+CHb0;)g
zy&#&28r>WB+~Qt}2+qLn#)QTB&+@*PU&CM%PMLCC9?UC!H<j0)sZ{xHs~4iGprnIj
z+IG5!jT*IXqgd_yruha3otC;{3SWz?2Xi6(P;P4VHFJsCShmC;<H5{g8+!h?|JDM`
z*Onnp%d^_Sx_KcwCFS~>E+hdwoU?T!-Ey7ZdJhj=jVfck$`UgUB61Fn?@!7Nx?=J1
z@m+cJw(HJL)`-u!Bs93}RjZvdibIPxidR}>qC;qACps?d_Ol~aA02~se>8Qn(dg-E
zGLSu1Y=RY2)}Mt?+{p&#A(prB50kEHqSl2Iff;bqlZ)C7;O@SeB%OTs{1+4?0O=<B
zb3lO7mIvt%{{q_GJ`g!SnZ6%_YTJ%u1p*?sH1vcl=3ShoXEWe_;Nox=PDLY4roo;T
zYU9I+`yLV+;|>D>vboo<c~x=^<53qB7Q97?4-$a&0w(-FzrT}s>YyegNQ*2kKDH{P
ziHL}1Nc19^A%2?wzT<V>l)vk%w&u#EnfyblFxN;pgU0$;-bI5K)_rX3r%#@wzKS6a
zl@JRcG1Aegzg&zcwKb@JDa?kMPJ`x_jJM#3cy2s&Q)%kUlu(*<M15^q@Ff%cw}hku
zW~ZK>cJt*o@u&Qyk@71LVH*7Y9thz;60cs#Q{p@^3yh7WKh|`yf(A;tgTrM@0Hv1u
zAH6dF%R|RbgKZ$#0?_Is79$%|DuAXhUvU_JrwpV6^WIQUHt76Eu>&VEkf@iMp3S}f
zezW+xDt9MEQ`)bgdVtm}I=~2py#B?DyHA5@4AKrtXRSFUv6|=GLP#T0_X=?~IodIs
zBz8gy6;4#qkD}+ibgivI3l$vIzI;}t324?^pyV@@TGmU*$|*ipQBM`-<St0_h<$0&
zu~p`4I=6aAGLOdf$ChFm`6EP)V6@|pY(V9dqO*jjmE9|Z^;4JiROBu3r8fP5WgUH;
z+EHin$Ba^(+=+z|5#LMuDIW7GadQ7miYUKlF*@8>hNGu7uT3mP=L_jbWX<F>1~rh#
zu2(<d@R*THj`Kv1TY*sFeBDPp@K!kscUg{iPQ;syl;q9#bE~y%<oolVT*8Cvr$Y+0
zikNbBs9wAy<782mC_GaoKonz>Y)fJKD|hajX|KMedtpUK_MF;F--(^ws-TD0iihmE
zJm+XuMqpOVegPrX`MtK`SSi0ht3@(@BwUEe6NcCQ?(h%^Q&^-_Q-5C@`IWEwpl69Y
zgF!H~Foy8qKsxnydDK4bvnYLT*1Ln*nbzyBBf*d6OuZbZRXe#BHqv<LzndWtt80nY
zTiVABA7~@Z)LP>Gv({6@matAk3(bDsS*}>pbd7eMkl`H73=?p{8q1PlTCeU*9>&!?
zzQePZ%hO(V25<3as%w(5BYUjDALoQ<GgYA)aa*3qRP0DIb*a49QZAX|dq!cn$xTK)
zMQo8~lL>=A!p^G(Un63Zk)}NMV*|x^((m+PN2ajJN~U}CNk^vO%5!I&72&a{jlNEE
z;bB}GEC2MGfg;9#uc>Im=9*y`=5^w`Tue63h9wnA>5@VX;TF%*%xMgk%6fX7h-0m%
z_0c;VhfM4(bc9=?{a<wSGNwJ1G5Fkx(E-s<2j==XIAlD|QVwEP287yi^UaTYdfltr
zhBF81UFm$6)RFjUuf-&_FO-{irQ;7!JGfMCq7|`uf9V>t7Uz`QxbIlnUHN5Pl0|ak
zi6cXglkd0@i-}nqX>TVBIj2QSxv<%lmUi*JqKa4+MDE^}&=2cvOD|&-%2Jp!Qv_QJ
z&E3g;2RALl!%?SYKvawfK1SWtYVYWf6qnLXBfjjB-zZb3qoc!wm1F*Y?;|Ya!3z@(
zF~kJH?D2lL=7e`ipWmp#yK;`Pi=;q2e?c!~6oV_))2-lj!Wbw24o?uC(C=U5zI-MO
zF%0l(f_~D`ZN#qyzopdGIYrrepx}RUJ$~O7Cz$HOQ}Cf{)QyaeedFn|;uN+Zd_AQ}
zHxCgE%=rNuzTiqtc{nd1SZ|#vD%;~Mec@o*C(yWa8EwF?*D_}{e9Pl%#+8s;nWay>
z>Plzfh;Sf6F}GF~T@Ry_Z%u0@yOi^VYK$(&l|pobh>WZxRAK1$quYlTh3hKlXz{mY
z?{v4~#b+JzVTXSs!XXF@34(1(QNneqmu*}J4W%u!3}?6jMd~7|Vd3&~{UGCP%~*mV
zh1lFLA8RDlD8EUBvWK?@Uyf|@KkFUnxp(X6&#Cin?Xg%0Y7P8PI-<ufZeU!2PY@at
zu^H%=>KS_P?-b+{vo**qprfM?2;f7PRi0g7-i?LF70UTX(f(b|hlRxPw~_aa`fUf1
z`AqbWuR)I<hWas>6@WO9fTATQ__}Up`r-~W!PCsEyNe8Npqx@rYTK0#?&=U+YAf;2
zCKFB`gxo?8ieun+<A<+nflgnDixWMWk;?rzOmN_NH%u8CS%OH+-GOq72ggl-bn01&
zc*?#p*RSudXE%d)gYw|Duyd{_>sC3`ZR0`hIN-wSRhPQ>jN)u1Z<L$;NTefho_aQN
zTme+KconHk6Rr|Wln|Fo3>S(7uz(=i>-6+AJKNMO0a#rOZzada#Ug+n`tCK&WhRD{
z$zu3!FN_!gL*aFLzD1Wb+W>C+ps7MA7=!yWl&TcGa9^yCs`>of$I`6Q#yg8SUh`T)
zJGMam0UVoDEV;r|f4ls`)ZyZ&{p3_VXJ%bmsfqH7+1A2Afydf{A8R{`jRA^HOl*qk
z-e5=rmA&CuqIORS3~XB)s=S4njT^gbf`#Dwao9X`NZ^|2jC=?Eg2nG;A~nBLhao!T
zDMjc10`kr4Tq?qI#zoaO#>=Hn*rbg1r$g0Rq%~B2P7<0uM&t8f(tbmD|BlIY67(V{
zVVov8V~OQ)aBE>98B05gvnFIPYR3A;uraaJret44`@i%$*Xq4z1XI+Zy?zV$WO^z<
zb0PO57QBz6+v64Y7}cq_D5cy;P##@M_V=t(gAhI9h0~P%dao@>z-WdGhFu*Dm-QfM
z0lf$072rb1=g3M*u5`=A;VXz{T9ENRHX5v+Au;bv^4tfHDTmXRD*v0sya^dy31GfS
zEIlxr-YP_#IoT)n+Zm2#YoDq1{`uplcHmUOT}a5v$figaL=h}UBpUd7hkP%ZXzlE(
zp!vAN!~1xA_QxFi7F0R2rzwO|1pPftH(pRWt#(`wBJ!iZa+xkN_gzIxM(snjV4P>d
zM^{nNu<XgioNQC?l9G}z+-cN9XB>19$L7%lI~eLI;H5u4yaw$oo9A1Fw^2d|I`AUM
zuB+&vx;S=!=6^K#?k%`IhC#ezVrJErRM*IqeTaik+)^!}RV16NG=^klqTa7d!UIM)
zbW#IitDSdeQ|xn$GwVMK+nI?fWexS9XE~I85hgucb%Y@VM{{K2z3T>GST$5r4%6TL
z6*imSq0Fi@cZA{gwF>6qkqPkuN;#1vA!Qm>uIylwf-z(X!<B+9Z!pp6SK3?&p@PM<
zXPlV#FWB9~GqY5zD_5_?eU$lF-KJZUnnd}SjFpv-FYd~ry1W8%$*)D4kP!b;fYYn>
z3BR&yYNprO$?I~i`oCEFNI;R=8Y}U+9%DO65`|@1KY-*26ZVa+qxA#8ZScD8FT10%
z{;57_93QB#_6pm*cVI5?eNRA+vCTP0log?Lt4XtM+rB*N311DgP)pZ&zxoXB+F78)
z-9fX2B&h&k^($)_KMQV!4&68Hx`jY6^-(xEZN>Y)O!mTn&397aaMZnwl+)52sP~Hn
z4lQ-$cUEkS2czlIgvFC{)|S?LFRg-Awg+2U?X%206(v$qk~LOm{+YgA3&1qdnf}h8
z#%A&G0kPBe@05vf^Z1+D$!kDSlaLnQ%T@Ag@6UYQadw1pLA2y`Q94LnX2js~ULo`s
z#&MrXhWUI{+(eNaF|)!<5=9p?${g<H2Kb>y<$J_uk>>mfB8g|5f*<+6T;ZLXptyVU
z_U>LUGn2!M+)Ju=+|BFmyR<mlOSN#FLuIJk%fkJMQCC8>x&aRb%WCKurCQJo-d#bh
z4XKDdX0<g4^Wdo{lB3fzeFnJ<=ffC-fa1s}V=8|^#o5%*;Z35rGbu+pL3jX-U&#^r
z(YfWJ42<13k|caC!|AST@`L~e`9@Xtt$TdnD_ueuvM?qmB@;$rm-=(gDmt7Nk;JI7
zVQ=o*qom{fw`>)0^OJeX7YBKgK3~1lunewVAq_XEH_+92Hh{Z*<m{Yz9wOh%^y3o#
zz(}kKNtN4FdUp?c3v}O<mn+`6?O13su>~W+y+~xa^~Nn1{^hZ%s^ZY=3hy|l_SCQh
z1)pYejbz}i_Ele3+QGW5x1wHYdGX8Jnl6epeSL`<QXd<hEXl-_M~K^GGc`!Oe3dBd
zt08-t71?{*gA9i)IE1CZBdUbB>|*ig1}d#Rf&yXCVjZ4~EK*Q%8aXbGI)E-NM4}+_
zM8%`6m2Qk&`_G45bjk<9%-nUcoB6!Nya5Jg+F?Oq=H|xH6v2fJ6{yZuyPTRq!9sC^
z4(fDQwD3chmlvOJid%A&p+7{SE|y2L9K7b$aGSLEpp<XGblh@t<(AL}pQET-3B<Vk
z8mAZ>Xx?sK^8&h^99F*YNIj-mR7P%}$ynm!vx3TZNAvwF_Rvr!S~Wx4T}nJzcc+=t
z+I^D-3!lYIksVMDupBbAM^@e=YHSze97R(FG7i`h=6(N%AD_LTkpuvF5sQV<JVcs@
zTdpp2F*<HoF1&HRk3v}kVU0mSNXpuJR<R2b^!()VAHQkm-m5@dpWB^Olui2{Cn{!U
zwI_kyVt0>){W}FNVh<aWvsa0LaQ(rG?%$007{3(q_T2x0%p2J}c>LENZ}eW>oJ1@v
zhE5w@w5hkh|DKVFb@`Wq$&GLAa}Ev;_z|x`CD`a<VlMP;JiaLk($B<Z=?%*pADI5e
zk~s4lJ9-*((a=PZIP+?$QBKlKZQL|`#?H>bOhdyUld75CH1+V|;^V4I-K&+a-1ROB
zFV^j8Oem>*Ju<{i1)p5Mo0-+QgZ_?#$hxrReEb<%TKYuIYmb(hh=+uk`andQZSu<!
zdHua0(6RXKzWx`Fo7bG5Hq_92!u_O7dG5-Z!2ib3Fh0^x<|Xxho1?@^<8*0%`qiAA
zL*o&_g1S+xwj$2VW*o6+y~=)X<s?`kh4sAB*rsu@?17pTLM%BgtzDYN!d6j`7053d
zW2H}D&9%O5ZOv#>My5G(S=^Y9R{-?aex31d^Gk8M>c|8YElQl~oK)xbpW&K4a;)sE
z0v5b*?m0MJ6ZkW__dxaETELab!XD?l_Rhwzr(kvWPOGSWA0Ac3Cs?%Z^F&Q~D^WYM
zQ>ISc_~EN8PLs1bo&SdxB<{^!+Y5qt4Va2AEGhc&T<G#-dyyH%z=V%NIZA0bkbeny
zLHQtB#6k2_2vw*+(>#`zhlfV(Ny6gS7NoojUQndy{U)27#BYLPYUz=4mc?J!J~s6`
z=0)Oq(HMMPVs3JBGsDS!Fjy!tWBgN)us>)4uM$IDi4|RsvXO=@e<nkTW|3D^TZ?gz
za>uDgb?fj&Y^EyJ!Kc}si%jKopJ1*!r~aZK)}eGop9Vu&DIWzLR<1{aA3wwl;G*x^
z*xuf?HF~Yid};Yap+%2eDZ9y<;eFW+<-O{aBog>Jf+_{ulWEv#$|rD$pOvYUE9b!a
zu26xicwq2xc7fcM$&A&6T2w(o*%0m0h7vR5`8(FHCa*%mxp0F=u6aO1cMVet><|Nc
zx#s%v&aCM9eS@a@@~1p3{aHPAR0WYE&)>e_g&a{;RWjxK>3M$b$Yg@z!ban()y9zx
z2|TPilRLflmb$UB{a-?|S9%CAUHL`+E0gml6_K1@CyG_AugCEnPHxqK6S#gqi)vJ^
zzo^McazBToF`^;EX$|lF#uRhpx7O`t$3e;r)xctJUL{t4{r)ob92r%=tYP|Ew-3^H
zV#IQSxRHP&F@1=F5x<IjVJJ%K3Ws}2{(Ih^m#bb}UL+Ki$bcMFl#2%)?)sPK>C2bw
z745tBAAZQ}#9szxftJw}0*}qWmwNw-IU_eBVR?GF#9swHm68^}j6;KO5|&UERWx;0
zMdNye!cV4jJj4Y8+;^6lwD@oDlv?5Ft86jUbZRnvKM3a3Jg6i;3D$#A2K_;5aw?z8
zRLdy_Ox+`sBQup?&wKq-$2tMBUL0XGn{9p~@Oy~h2KxNdj+3pf+R5jUWlk4H{w$@*
zhzlO>eG+cF<tIDCU`?6@ug33%zgM#WoG@0#j>>G8vWd=RT?X%IzplWR_O}#}JLtn{
zzPBwm=Xl96dZ1<_Tm=|3(VoW<=m{Zm$NH1?3v%R*2Flj^yc@p%cv~01tR78dI6XVu
zE}v19j7U(4#G3Z6ynFTUwc@{SGvgq-gdY~1<l-ngf7H$nBlVh#DWeCmfF$(knz3~F
zQ_aJrY?&|T258ZSii$)y#Ij~1vH*7y(*CFX;`?QJVzjqB5Zn88ap*9GrnJO#{1N3d
z+Q*N}A&=y|iaP_htINQd{*c%8n3|KUzivF$AiQMXZb0#Tc6i0bOGfe;ClL0`)L1QZ
zjb#$LAbCn>27At`9EMo0xKtP$S(dDG(Xw@8-9%3jN%sJP9`Cz8udan*RW;1T(a?5?
zn#r(mQ|-;Qy$_Fn@B#SVX{xFyO+$O(v_wjR9}^ZPz))a@aT}A{dOcGxAwK64e&gQ4
zkURF1^d7#hk@iTYL&LGHu{^P=lDnfO9{mInYj#al&R&Uz7o59xcWr<g%Ih-4Zr%1W
zgXQ3GN%H*TW5wa2U+*^Y#$bM7g>3^4Ra!r++K29;l0vT2Zn>7fVkR9<iCO>9SaIg^
zr22kUl5uEtHGM$)nDyjrPGtayq?NYj8fnVK033YbeENwg8)_H;lqx{JFi&o$zYWpi
zqf^^`3qI#9YB*FQx6*=#%3RlA%-@Hn(1y!DnnP@jk%{G<vScJo4=>8j&d*WJer>+9
zQe>(ehwgTwYZh#eq~38owFa1BAIw_r0*cmtt?z5+n*;>FRAOIPbJD($2nyCU)9WeL
zrMa&wq!a^I#EEb-b-=~$i2yXQhGA?d!(~U!o)qKo6oPXuu{NdnF~c3)n9YsN$k9{?
z47#)I$k<l-ru|%{#M?hACZ~V$e9SDH?yE~wsErD}X1VRzfD4a?hB0SM<M`MpQn*0u
z5f{1Z==#&EyfV+^$5+1}wJdrm1_ft{OZ_KT0zG}Vz?S2-(2+DC^{6`IDTU8cYUA1A
zI8Ojj*ytr)g8sZJqmwHUr&U|mipx|1j(~gm+`TsoxI7v^t*jfrxmu?M<jk-Cuw6(v
zJ$3%7L74_NL^mGS#Z{vuNXywD;ZrGoFS|)Nv0^WFXYF9&lLbKRhJ0#3HmJmk{?2rs
z#pfEMt7lYl(M?4SGa-2y1wB6_W~lNUwwNZt^QQQ#U*6nhyDU#%hByX>Xj%{Ufeh-x
zqy13iL4tN58GX~7Jf?^TGkE~yX(!$Wtd3{cd@AuMD<TE)xwn+7I16!Lld?<A&TesV
zejko|D#tYrF{7n_oF<b61GVz0a{y-?>Qi%&xh^dp5u4k2U`^rous6Jykq(m>;fX#2
zn~)TNbW{@U>aQ*95kY~jTr*%o0M9Uf)$n2pS#*M93(0CJ-L@Vcsv=IpTN9alZt;qS
z7YWE^);#sfq^zfjF3C@2R-BKxWY3gFv@U98+pa7<D>3Px{pGzw7BdWhAznB9&5qxe
zMVTReHg=X=`5|S+CSxJW(gsJ}jHF-v(xZPQsIva?aS~#5KekO;V0>CFE0d?Fd2(Hj
zL^$eDzqu^3|Ia0@$ob~lRXyvFubpu`+NX;GA%8@Ko8*sjU0N2CvkzxZ{LP|}w<H)I
z(o7Cx)ZEkBO9>X-NLMh(3)y9(+0XB8<#Iiq{yv4OFGWm-_+=EP^Ft>9#Y0EUj>LE*
zz4LdTnC-@&$nDqjqz#YO|L$lgC}eF6?`50&Qbm$@Zb+xs*lbJ{f@jk7Mg;kts+96_
z3-nKq9~>Wy1M&tI)-GUssk958vnMQJu0_gWJ|Mo|rJSW!iN-^?xKduOd`F(}dMf}0
z6Sef!zDM;I0a{8&o=HmfR2Twt=ZjR)$(#KMLcWJ!-w*FjFk_~p^B>}`u@th9;2-Kh
z<miYE-w`1!x|t(Ii6blcR!8T1XsAZ7d<boS`h4@k4$Lr*0AgoFNbE~On5@m*+MGDj
zoZcS-wIz%RDo;9<CiWH4Z#p8A<%lDn<E*e7%SO>9zxd)$cwG(0*4A{?ckOG6>+F&9
zxko!Y6&({RBLTM#Kb2WLarXL>;Qdbj{b6kH<Gt9cym2Mx(@Kw;jKS=Yp@ejI*dSum
zCl}o>QD!j%kFNM#I<?h^l-c$y&q@e^Iss;shTRqnaQ%Me2e4|T*r#}6BNKz?0xTL$
zb<N$~ACBH%{Rq(aJqYoWH=-~8xXmFImiRnm?M+Hvn&g(2s3>mC1pAa6%#<bWs1;U>
z{=wJX+Y1SwR64NHJ!l_peVp{DmwMk!c~v{X{)>B+pI`Cy2X^b-LE{KA;*WhryI_QE
zJ5TTK9LW4yMYj`R#QTN&vb4N>eL#QNP+&V!YP8>;*dIa)-H~4AOpepNxN`rOiZ<O!
zfHAZCwEYE$3+gqtT6@@M!7>*|3IvH2iBgo43i&CS{3hIU))DpLW$*RUNZ9VSc81A5
z*(s@(<;N<i?8rXyQN-XHs;UYK>~gBqZ+rS)z5im5$V2dPYhYLrPE^^Y75j+5FL=><
zir_l_R3KxKe(EC`?e@L#HCJi>5PvLgsarnF-=QLsb>UgAyRT;kChAJ-jjdiKHLIPs
zE>1S-kZ+ibmOk>kM}B`zC#r6_w;=Rovdi2^jNj<KQyJ$S;y+P>=?7sC(8t#{M)hF3
z2i8w&YO}|IWF+Bz!aUx1Zjl$i`S@>5*1Bqd;h5WM`)6RnVU|GEU*x~+p*h1MG2j8?
z4{jlr%q*TsycqVb!Nl=uunVEtH*3bRS6Spq;<DKt=<QdE?S{o9q6^W6gi$$1!<V46
zf3ESOyL(w7CC0<<()P}(7P#7NVT(&k`uh5X$dIA8dU^`evc1zfsAp_+ga^w5(pArS
zAAA2G`HE76QGfL-w&D~fr~Q`WE7ST}OD+7bdtm?Nd$)W0!SeDKN^xzP+19spkEehI
zh$Bk-nnT9LFb#_doAA^x<?G(GQf<d57VODdO?9438TdQ6xH(BVbiW<gO&yLaPsRxz
zF5Wr$Vb6*c9yGA}#$ZkM`6`~7PJ5@&WoqH<OY4xD%a}$IfXS7Ni2)M2x747e7msTH
zw>)}S)QR0~@_wp#1);i$?2M%EGA)2tag=>yGyijA{j6m{nl#JNTjAYOibRhZex|Gy
zb$Gi{pu(@Hn;6VU9TVIWHkz=P4%idsfsx@#?}86>0{G>vGS$WF$PE>deM4W43|L4T
zi6IF1?<M5Fo_sXK1xi><=7?6+`96sQ2t{s?e|VNBjfC-oB;V$e$>mHP*7SwF#n$#B
zo4Jzd>0r1zCpF(B5f+Ts3#8u}mK`rn!qhkL$*CU2UtDDPtEUpZX-77YF;YcToo@E_
zk2+yS_YDr(+S<KE2ujD6zp}*IdF<%O70Dp-IGk2SIbF7PLE)3=eF&WP^h68MluNJk
zkALRoM*BSV&7;%N1Cqkfjd8a&+<`0w<Uuo!-DEzjo9Id#cMZDA_l7F7FycOhFf+@h
ztfDF!(NR<CYc{*F&MRvkh)rpnMs6QWyZ^hFUbb537N(v*&QJj>l?!mE3|ihpEV0>`
zEeDXVQYSu(q*N19WC3jF%PVq*{r>jqQu_^rW`=}qHf;w+ahQ%Q*UeQG(~ou9A_0Y8
z0qX~BxT;UYX}iYY;0}t8{@10C^3fF*woxqF?hF7RSAiPC{>_I9lLql_@BpRu{o;Ge
z=Znrc;~jT>w97$an4X{}4)m9O)cr5L7DUR(3yVKBh=mO|HFM*{RcZN-hH|5s3b)*$
zS66N{$vmxDZt+J~%!a%^M>~^J{TXu&;<;}!e#?XUdA}1yK)iB2bCI$uNj6_2fYa*M
zE%DVSAmOT(I#|FEL*K5iw);u8W{q`AY?9WU<;!T*&=orX>nqt7#l0}U*-yk-G_mf|
zf=4&}#`M{|RrzvKPPpJsim|f&gxl<Inu|$5vSy(3{E2}vSndO_riqS-_h$p{7j&=V
zf+EL3-PruH2unjc>V=@o9XK%z6>kh3)X*mxCY6L6yb~DjNsvN9^uSs5Tlc`g?^k1B
zDEE0=Pm*Z{qk{e!lflUM5mp{Ndd-#@%b98HlY{kF5ibki@l-=Co@c&RvcYRLGvK~B
z^d1CEz_jb|CIh4xNQXcY?!0ig6_dAb7CByi@i~Y#^SSo!WR;h+B?l24>{R(q#)n)c
zg+ZWKWy#U9nJc2sBUtA<Es6G5>Oq$x>`#%knu=Q?!-l8`Ue{UvJ%p{T2mmZ6iZ3|G
z>|uN+bd>stpeq4FP6_8hzvHUW6}$bGP+76Sf|)~H!0+E$00OTik=1Bpxi9y8p{)Z)
zhBbXfPw`!Wwzycl!Jysf0a5v^(<m^sJ3~AN6T?1zn&+Yylrpy3zSx2`(K*fTf-H51
zZXf*-+9B2&&->}|1_KrWQg^idl}?n9E7vE`tRJF$u%h|5;^XOl<KK`!t@!NaaFHwo
z{dsK0t6a^R1=5G|$MLIkV^uf04xKgEK7CxH$t<6^V1z_iHnIb*(<0n8zlh#;;o!)>
zwtU9pUeRaRPe8tbM^_>XsoIV665xsC4wrF*#zP@?yt!qKFc3=>OmgFgd%=J@%v8Md
z4=HY;eU>u}ba*us6g}5%Be~?-{(U|8Hb00}KQWMKbT)QFnpU+!z^B2|GPk$Lk~mdx
z2Nc_kcQ(Q!mo*X`o3<3%KASfp&J^uAPj9neMP7Eapx5<k*M%eL=NVfZukWS!+6BFg
z3nfoIPz1ztN&Aq<jG@8X%Gi(+fOJ1%=*G%;MuGVErxEvO;UuFgoaD`eiuvU~74t}C
zR3s{jA{)EbB;F(b*J(#%g7Aa*Im3WxEiKj6CJGG(+1r>m4wm7ke_)b=vi!fhq$1l5
z%Y!P*JSZhdvvF~-$$JORN9{jBuM;c4cmG(p!LJL7<|(1$3Jy-^{8Zx&*F&=-02jZn
z;AW1KqiSK}dAc(wVxk_M<x4W4rSy>Gp3BMj{fpXfvmq=dG}gvuUThukd!q7r6;=6&
zfgvD<jg2XLeySHvc!KPq^8E?ShB`Wn>+;2tEy|hwK~O=gjl2B>hzu+-*$31(M=*Nt
zaJs7`ArYAy>klExaFWz~U|xIZcG;`^`%>iBdw2H$W_bW)V~qV~tZc6v*>GfWLj`&k
z<DW%bGY@s424~4gJsLkFl$bcq;SLxnHFI2RKKq?*3YuBTyOY=?82syqVvTK?gXHU6
z)f$D`g;EP-QHaQ|<N~2T8d=mh=)f3s@sft|&{&O8+z}!*3RYGgN|w_<9wxglbhlq(
zF05q%;DP8AcF_fwe$?!>%78|SXL8Gkrg6`%1wO}ZozdK<P$A@l<Aj>!uY`E{_Cr;d
z+{<pDRh2uhNdsL!SGI2_SD;Qz(dN%aI~)Cl3$NP8H9MGXQ?0NvX`jCXss}c9kcqPW
z#zf`)Dz1eSzDV|5JOW&Sa_@+YtzUV^MkW}*jI>|li;WHvT|%3~gQ_w4w+=`LMM0n(
z^zY@~!yyWb466n@Xu(r7`Nx%yGu?U@tRy5<{S}v&SBHSAdRY_yr*_YB*`j_##v0Qw
z<;<FI(1Qy%LSr)-1dKi>XB!{yjI?WnV4mOQS$&=W$|<!ND;g51J~I;kZzT^w3$QUB
z-SB*Vz3MBPThEy6>A0nCcw#-YJ3x9rf^wW{F=N?qFiq@6XQd*!SY)O7j%NS3oVcla
zeWyzc*)TSi{X&AfV~>A#0hitK)nXXduH-=Acc*1Ra!he3s2)04wgqCLm_5h^SDQw_
z)I*pA!ZKfJqGEaI2M}_hgzkvs0+sg!MmveeMHC_9gf**D&QSzO-s~CN;*yf|l-lLq
z1L*3@*e~e&t&F+t{xtm1#Kgjqu2xy$m4ytzKy*)~G}Ew0Mn?uk&acfm3?J-A<)=g5
z#4CZx!`-75(wZ|>+u5Zt9Y9IEeOs$&^RSWlpBt3AxVL41(`wooxDaVl1iTO?JNfP1
z*9Tv7M3+3DQM3%bJl#7?C`|LKzStZFNFeosu@Tubav1{d*^}~Ms!C4#C9VhNLls@U
z^`_%c5UO5$__k8Iu8@F>pqZ6w{6wmMdlBgogeg=|2OOQg`(dyU7MH)IN)xf!AFGfA
zoNU{^S;4(S*CEASVloag4fU;Ceh(RwH`tk*!-^Ox_lZpa&G414dSj^MX#I==G%nca
zH6f<`Fx*8#^>cfF+wV5b@<XS*<#inDCb+4i7CMMz9`^*!EJ&z)mi&0{I{S`+%tJoM
zyCN^|$rWTGiZQsJWNeJl)J(?JoE;x%Ey!vLMc{>IPy8H&lUj)&_sO(gt=}jX3um85
zK&E13<;CU_Jbyc)nXLFH=&RY+AB<ISef5Gj0%0UkEZNqT@np1+)eX-{!6O_IeXH_M
zY*H&!E`frF&b(d?A^syX%ZeTyH(FsblCUpJ<UUkB^2Ar5s+QPApYsH;y0d1}hV5s8
zKbIRYyd)YIcGkz;uyOA}dNn{c1{;U+L)vUj2ICD-U3l0BGX?6jEikIGnA>7GqG4!M
z;aXT&tbl-$S4l_ux2qYVcZ{Lw_*HIP-d)!~SIO}EGux}Ye2*48fYFIA;tD)C<NjS)
zw@}={{(g9X&>3yP_5=l4h^MS1JY}M|b+fC-z4BTU`?(M<+^PLL;a6b0Us+m~&Fn8Q
zV^->uS9EoCb+6E55opCs5dk1cifN(|R1M#ZT0q@FBAL@;7%gwvIH$)z5dfmp+10PZ
zvI#;Ot8yI-Fa7D&t0N%nz*y&!ft{)d9BxyUZ}@V0s4iom<Cq>nehyH5laoznN>G_=
z&Pes#piPp(kVwzW9F^%%QTd!SG3luU1BbE=ip7LmZ<&BuWbT5-%rJ%<`ivnLw_0MB
zUFh^|1fNXg)_op;gw_A=&5qA=>I3J@1L7AC?h{V@G&%$ADO@r52TA|UKY~~I)Pi=*
zkIgKI%@Slm0hVfqQFv@4jA20yVqzt!J=4T=AgX!`kARpuTxM3|6@>&6zY>l1(o$#%
zhaRbVO6izFHeCmPM|!hu;%&VhfA?huuvPb?W8AA=NfP!V<I}1Oc@;WrWXbXM)R{||
zg~#OliPH5O+);u)I6Qq#BuZupZ-5$Xzs{psVJvALn{5$*3FQ5BW$XvUr8;YNk=+Bh
z=euizILuY=A8f9AOblpv4WqNKzp$~)tuM(pNmDk}elNVcj!I#_%E@N=dr}_van``b
zTZ;EDNa)5Pq<db7(y*|wIPsRm#E&08YL2uEmQzjwVikJD(m0-M=dGL4;JL|kflys;
zyKoP6<Da@O{kx4Y*KSwnzodN$(nbv}nNqRv5}u0ZmRsT`Z0mNp%WsTzk~JTT9ownL
zg0dE=&p_Ya7WVM#1g2z2%nn-|EY#G`9#D5sQl@Gn!*+dt3nD&;3QPJROO$jSUq0g;
zwIk(p*_QyIx=&84!-W-ViARWk>zq};ozS>2G>*fnUp_`db8M(y)##XM;PF1c^|as$
ztA1;}!}7rlP4Z#_{ZcyD&}*bSIi=CakDYIoQNhM!&<NepmwFR&k{ey+dUB;nP3z8T
zYqdmH%mosgs}E<iY8%7&Pj?huX=&m5a4{Y6g*@)P2dCnCHw+C}aO1ua-NhM6)q9%y
z=;nzPr~npt4#)KyK!n42)1SNK&~zZJBQKG_uB{h;^l1H`LmiCu`lXZymi->nf~GHR
zH}U~Kp*Mz$A0Yc3LYPXVHDgy#w89lMYjJ#8o=xshq9zu7jty4mO}`wlO;y@s(5Py{
zNv5bvnCg_a$opAoyAb$_9znSs$Lj{!;U8V+xQ2!gqYw1ZpX5N123jFqk;av{ylT~f
zzXjNPiTfb|4+#jmsUtqo5a~Jm5M=c+OZa!`#477p3~dK-X-qRp8FCt<K*8nyj3uX;
z*zC!af0cJfYG22=AMo%H!_jm9Wl*pIy~4g?k?P+CeCLjjdXWw4=o>Xcny;CLmCI^)
zgo{1yy?Lk3b4?$hibdpTA;e~3_;<gG!e)M-lym2FZj`NCyT<b5v4>6yZN2jg<K=N7
zij}_H^{M%gkZ1xTY|X4@t?)0(2k-p+Bz=8kk`I4pdA2~?-CeMLINb1{OS4RWFPCo&
zn&LzBrVj$<?J-3DI>^DF78Ztk!cKCzY4VR<T20O@UTt-Q^f3s~v_4!<F=2LSMwEn8
zgtA-6yA7Vtgb+dRU1{GV;d#=et2K_t>G4VAs;T(c2<wY++x-L%{i$hNNG}(BvQKXd
zqrBWUr>j^sIWJ|p-q~9lD?aZFtf0m$QKz?W%hs9)2C}YM9q#_}fceS#Q+9KnFaCa|
z&)H*`)@i7-U&HKsDB`@XpXXxvVM-Pab%}@2jf3%mg+)j$z&Y?GX8hLn-+J!i#7Muu
zCq1c|l+R`9fQ-=Bw~;C0r%V9m?}@}}`zGaw|EUl8*ODUv4@ISzFeIe0o4#H42THf4
zNn{PGrKLBxe^M15^$yTGnrfZg5VyAC={q*KXOU+NNdQJ;iBn~Ps8~dtg|6+IsgIVj
zv<7`56_20z>MMrh%OCb9m|5EipeGm>j~HvwT9&KA5d=Il2R^(Si_c;?-9ibTQk89o
zBxXSx+Ybv#iS>O_Ua7P^L02jf0c&DBzkQ!zt=TFJfY^5<G;ij|`wls6HbN$!VWMkH
zB!o5?09ZelY2l)KEfA&&^Z!2vl9hk+-H-dW3(DQ<cj4vvv%`hW$1WP<d(EHRa+8Jb
zJQ)2?fcw9S_|!jtUWjsz(8pEB>qAXX+R-uqv%y%pf0^m6fdJRl(-(gT?yV<ebWf?-
zc<F?Yl?qUdJpWf$@bZ`&Dp>N2f|Heph7eBd{EQq#zBpIl*!$j@ekULzDgwtzZuAqW
z!Q^qBOxERlh?*B*hOXP+SNey2O$l%-o6^jgCwTl<9((z0b~05DMGyb%GcWq@-h8J2
zegoIQ{iiioDchgPdqk)pD>0_&KmYT8$zI`9y;a0<8ztm5*NAFI)qmnJ6?Hh}hhh2%
z{zVB))#S&KXbP8p>dROB)oDx4d7bq=gGkJKcTnPjH;}$!SMVdT6#v?@QQ~!=9s7`w
z03c$QtlPFx5pHS$>W&5#6%@U8SS<o_*!J8B^FD8GU(RE^@@*8=LH!#>&wtOc;t2#R
zV4&7QXHm2UwUV8!dzvy9P0~T#Kc<{tt8s4f;7P69W4^e+S?c8SBTq+F^O8@I{-*)Q
zA(t)6zb|UquUX()Rq=8-65XbJRA_5f;1}^GOGeN+(^r#ty!H2=Z>4LdI_eT69hfVI
z#@dY&mh_C|uQ^YYZYa>`o_At+_jtDrKVEy4BXv~CKrTW)+q*hhLSCZ(sVY3EekQcg
zedN0=f60c`FlxE?zqJ5)m1rwFev|t*FzP<iv?dhDN3Kn@4fV*s?`G$Grph^*=V7U2
zG6fe@K(1|=x5F>S?6X*I+BMPnZqp5YQTmdR7W3poF-ij`Hdd=bB(Ej&oNbv^iPQb3
zSWasSr3yv?h9xFX8;q5N(>9W;Zz^@#85ydK$<11`uf2ZB)?sJ-DEGC}!fI7fT3y>P
z7>+fi|2m~H<vUCAD00`b|9`F04$-b%msaT#0T=uKSf#^?cM0DwYB+^io}^fnI7pp=
zv()@WSJ{yu=V+0qYw)roixe4)BoZtZc@NZk#91@WV-OM5GNFawuvYy)jJ<VKRqNLU
zjCzGD2uL?rAdPf`g3{fMw8Wu11qDR9yQDdE3Wq~VcXxMp*Y_On@BYU7j_>`(`1W58
zIkERX&tA`3YtA*N^X9P1XH7Oq&2)%7NiKLDBrQe`Eiai(k|EPk0Ha6X{&}#mIc%e%
zm@XTh;gP96#XBWB<;3%lP4Zes^h?N7GKz%4Me41Yfv^w~GX8|DWf9SRhq#sB466nH
zUvu3Ign8ENS4?9<xXCWRbR=brN0%2>O~Dh01~2tdR5Fe~nlNx_xOS*=ZyPe~OgD3}
ziMTH0+l~!NOf+OM!*Mol-<AKNNyB9~W`)WD+1(o=wW0lCpE4oK2@4+k6Z_avTP#x@
z5aeTbr8ddL_JzS8p2IOWZ^ic&60*+Uz$I}Mj5OV`KgZ0$PsnA&A|c!vN$hyXB90uA
z60s1T!X$R)h2Smyn1~ni*0d?c!6!8awFx;!o#V-JeLoy(mTMDpOuEO(Rr`oHtlQ7u
z_D4~xPy}YE^M{Z9PQjm4XzhB{rA`JZ?1a<5R%rd<qYinnzAX?lRCi<KudiHQQ+AVu
z5?%g~+(biAGM?|g|52BESBS|;b!GsbsDAKiO-x(e8vBWTG}&)KM#;66^$aFTKw?Jy
zDB$|(JyGfTLI8sG`Qes_9p#^P(;w^G|9TYhl1L&W(GvXwe&)v6+C|?!{w5?4+HQn+
z!n#-y5o|T?wP-?8L`*!T9ta8Fqbh=OCoU?2q>#ZY(vpNhe`Qte|A=u2*|2{D69|#R
z2nnHoj(72X|31RtJJ|juPJo_H_J6H=L8}J+-xdeLxPTAwZAi2)|7TlOCx!lA@5^gO
z<(M$q?wB=Jq=U)LzqyV5`0Rvr_&I_9kDdTFID`K)@<?uH2tI!ZLN(xUcgwOQx^42R
znI)1Oo_+w{u>vqK#3(=shM%kMlx#Jv_&IqOMH&9+0{l6P0#!Zk#lte9+d^Q7AuI1F
z6`KE4aa?-8#H#G2;C##7tE&J55c2*Uxp6nmS$Z~QI=w-F1tfV@@fIUE`tb(|cHO`J
z-}DeUn$^xDCc(~~S<+3scj_ZKHHVid@wUF%21DS^{C`kJM5q82pN9YMu!`KgelSuz
z`ZMP4kryDN|DQk2j4>Ku&|N6Smp*9oK&FOCJ$1IBVL_)`_6OW-#6g?(O$khvq=KEU
ztNFX^`|^Ld=!iePdmP2kJC0)mE(E&qCdyNWy&y;u%oF}|q)8#Z@IQwU@&Eko-y;9p
zt>OV-0H|zSRtch#lFSSs^5wN|(<;Hh!oU--20-T8?h-j^22}OouD5&r$2mY@<xT$$
zx1iuX$P*ISizJzV_f3P|wm`zgyextpA>kFRJ)KI&;qUj61ES;v3TTVY&2m*>6<0P~
z;b2a846G&D3RJfNyJekGJN5E3m-dX~Wato#ENj&>8+3_@qG*mX(rdyQs9*QMR4TEA
zuZ9X<i}JYLy)<h%V7ea3(}rg<485%QluAy9U>6pp0~b%=E|?XIAQ<e7__m_ePdXip
z0Q)gCvQmI&PIz6gjjA&33}mZU_Z3dU53KEg5Z7BgKhd_Edixe&vFfbs#FR$_FbBY4
z2NFt`Mt4fy@3_bAdR*?!)f!Ylc`_LTXc;d#1mrUrK-Hy?qjH)sI-8rs-?4=boMykn
z%#}y!rz3!}e1=`V4g@5N`EIo#M0dVd4@^9`(@@9`BF5;W*T@AtL(UTB-cV7A6!j^8
zX8ODetV3jgkkuyGri30S-x*A1uSAVd)W-uSV*th<0EYI6v+JwD%Y4wJto<l_=Kit$
z_x;_r#c5$ld-_1S&gnYlQ(T0&5P0<US=ipD`OAIhwSItvyL^!sD4W_qKG8rziGfMZ
zFKDxd?Mnm7`q+Bh*zPPtfY_(hA7rQlo&H5A7!SZ*I&iLQ@7DnmmH|t&qmqxV9kZ;z
zm0_cHJMQvY8k^0OdK|+rQxx1e?7BKYAxBqVO)_$-03d!%_fsCRbh&}46!<}g33_!d
zFifptGgT4=Y(Uzbfhr;+@&6Ljt1Sn=qXLcB&G@4P;L0O6%Er#DP`F;{6{h>{yKB-(
zlQAd?0ibibF(d*PNX!`Q!`K;*jyZ+f?1R~WD0F#0v0@;@ygihjm0t!=W<Nfhc+@AO
zsh&`d(^}*LfInO@&{7;MR5WjB3<Ki%D1X7@1>Kg??q=~Bb)10vFD(Gwl+`|rARLV0
zAKYp^y9FM3z|RU3x3+!&DOHD+-`tNL!E5(lw(1YMwE?%mM_EFMfEpJNJ|SlDJeCfT
zUHa4ytl4hP{{=>FkUj#2<-w&pF9{v!F9SDGnO#j#w|ZLB0IS6>X#+{5d2-a?1`V`L
zz2tkT(W1J~?<~;|(O~0o+PngWxLYYj`LV#IrHtQ?It=xxCk_@7P^UuJ69ZaJJt+4N
zIwi?d$8*xm6<$=0#Vm#o7T*d3Uu8irqO?nVWkBW)43^~s9@hC*xEVe6JsaT+o$02f
z-u13jt)ol$!MPJL07NDe@U#T2I$s^yEFvHeCC4#dC(aKTkIIXn>qU)}z_&+NWugMi
zL86|S+RWW?g9%-lss|Jw9U4dRwCyC!c(PPMM;e`ECehg3&4r^tm5zf^o+?&dGl3JL
zbY8Zf44!FHL62~i380Afewjich0Af}9oWkfvaUdIDSgXI1Lrr+rn+~}q2)tZ%>Ox}
zWy;%5UvqP#;TPYYp0nrl>2!8Q$Zgy=Wl`@f9{$3m_4WH`Xlw-L8O-mtcHLxmAcep~
zPrRmQ)<-HQH@5iE#$?s=>$G3LM<)+~lJGf&!1h!r=vTl#doYG>@2ni0T$;yg-AxJR
zwq0XIQ)w!#tUGNE9F5J2g8oI1Ads*b2WFwb{01x(0@u7KW6)jgZhRN|@VT-$=y&NW
z{4l`d1ws>1PZD&xjZe`>v5Wet7zM&pfQq~_CD7plXyDRuRI<0Ly{T}pR-L;Y@HlI%
z*PcWLaA0jMkA-Wi*=XGh%EYHP27e}N5LX>716t8BF~(7He4bZb=WTH4`2N}UXaM}G
zn7R+PCm5wAM}NBG+W=6zC0an0IyK9xyP~28Ou0&zNLSp*(SkL=lY^3)7CAN@h#LYl
zZQ==Itfc&Rz~^>!d^cYtcyE>ETVooSjs9ak_~r%_iyn+x$N7szVRZSbcD%rC3fu`@
zVF1y6J`YXdE1t5XDWi-KXZ2L*_2f180nQ1$(z_N)4ZwT5JHzjE+`2ul1O!;nsWF|c
zOE<&fnc5-{!ausnYRG>8sMGh?F8IfXN+?P0{CaVLk;0|s#xRdgiO)e*Rbgd<5`-k2
z2P&uQKR>Rpa36;wcxsrAwJOq~puNf}_fI<V<p*%050%GI5xSQJI~kI*u7p`_eM-^S
zWCxHXDJl+o=~QfO9*^UGlCO%0i3v~bFNs$+)9{OliK)NSm5)+I4;2>m_^tmH*})uN
z8zNp@#vdAzTnkz^D_~Q>JueyF36laezNdlTkL0$i0k9=y8d4MgBxj|&iKh1FQ(tUq
zC(bwIvCu{Q(LpL#2lEEYWAgNOjqYOU%q0`vrAlC`<aXik*qn3Ed@iVVj-By(j@$l*
zv>~k<kG*YfjORr9uUk9=UOh_6oD{fqp>%g!41Sk6->7K*(&3$PcDev^%r0yvZzExM
zr+`M`1oLmx=`v=`yA$8}#F7qxqy|*@_P`Fy=^1*I%!`&jk&qJ0lxpLltZrPR`s&Xw
z4(p8agC{<Ai2Rhf1OU&3)EI#M^2L^({}mkzPl$l~|D>xTau1|^AX87kG=I{5Bn>pt
zt{#7z@j6Lb!X`0aHPSuZ8tI7<bKDh_Sp`pKx)Rjb!Rho<t}#0&0P|>h#$YPUEw%*L
z`9k6M8=I2AZBE?4zXTJEfpO&LzsvK7nU4Z=c6EK-YS!W67Pjc|1@N1Gz<bT_7ZUa@
zFLOHa(em~-m$XK`@j<fZ7M_f1<P*h~H<qEtdUdk%44XJ5KEAcj(QMu)WbuasZ%V_{
zG{q9&PP9t>snvt%Rb(gi9Ib{75l*teS$I-}O2tFB#!3I&U*@cn?1~bjwI5&cQ~{1`
zh6yl|b=>1V>tc%QXJY0uAFKcirmqchO;h7`aM21{Nx)qGb#JecZZzFWz8_G)Nzk-M
z-z18U@EL4Rd-jLXPcKWAp?jsFv7rtU-KQAq26qpDrmoaCp{8*hKL99&HDdwqT|LVw
z06}pSM!_wBIntZR&SISgH$XDb)<y)q-1+zrnqMFNz^u;|)u>#7u6=K7y#%wmiV8=e
zD7%~!+5T3Pd1k{s*;ns+o%xhx$9+N1v!zOz-2_%*sQfHH{Y%8dFyb`7WA^K#1DLc|
zXecRq9d%m>Fh6$5(s97q9igkRnmqw_-W3kLiHj?rb!Uf9TcJpfF+&wkGEe}0(e*Y4
zPKx30Qv))kd`l<7D=H!QgXF2ojiFMbbdf!NdkOYgAS?+mC{|)>$6hctGdMoX?Y4LY
zN0Hrx443E>_U&rsqa^qek_4DYlSx0=034ssV@-X=JKw$8^WkKP1p|YL{E(--Hn(Gs
zTywjWRoQ)bWIP1~CXwE`L`Ow{X|(KD*y?datVs8j;6rEJE`q4G#`CyKbe)hF8u0(j
zxf|%ybI|<S=K^oReMY*sWvH9`!Q<PGLIGlu;yH3ZGWGEPg3ABdBL06=Ba<I8z5eY5
zfHy^%{@W}88Ija7!sh`=4vUDGa6p)P1>ty#v`YH_u0g=~SNG`9&=Po*5HI+bU4{Ut
z|5w$6==UNrt*+kQ43qRQz=uX8>0geX{t;S`?C<yy6av6%6Y!e<yDm$Sih0%B+Zzea
zOYSfK$bOK+KLG>%Dg_#>pAO{u6Xv87s^dBA`m(xJCGzI;AvvzW3Ct9mgBfp7Fv$i>
zj!aX_tCY2XsYLIMx#Rw9zYLq%*w)-FO3ym>6;;n*Yvg6@ph`ZMTa?1$#vzWnx;iDi
z*6O~A$v@=NUD5aNVmuxRBS}04XI-P)ab;U~U;RDr9#F!sTx5(&|E&k#WtBVL`ppwC
zWd+RNpHEK=zS^6E3+f#KzXI8rO0Ua&cK=XvlP+WlwJOW$CYkwq&n!=PtyJrhTI-_p
zz_tP{y?X6SI$l_&DvJA{)%Y1hPlMHDY6B3z4WWUaQSgyId)5)fPYC3d{v5Q)jcK1;
zb-<{6l<UBU(fkmb!zY)QUG-3T`N6<g#`9BnAHe~z0K02=+<>d$c<(I?JKsG&$2_qH
zz?GXw3-W2+!Qk?nsPFtPS3xRV&I4bVP|!b5r=v|rwpRU+47(4^{GIs|3Jf0-xJ~8?
zr=95Odr(gHp;Nz?D7#||)jqmNbmQ+kT-O4<in@JIDRFVgbnR$vc+1w<VN9oC#jN?b
z6=1YaPEX(NSEr(*qv!M|n425e-L^?XAQ19UUZbJEWHHZ~m*0H+Ac9WFXFt2Onp}IT
zQNMyY_4!=q77R<rpNYN39-R8@^qIeMn|-Rzv#{EU0r=O4DURmj{(Al9O@HFOfs#EN
zq|`LB?Rc#ZOkU$q$rkGL+BN@TmU@qwt!Uz&3oJTk=j-j9%*+y`V#YJvs+%4)d?Jy(
zOml*ZtoJ9`+vZD@W0DIHa~t1$<>kC^_Z-9-$#hA?YH8rHJ^7`@cz#y2tKDsWJhm&8
zULspeE?iIg0q?UW?0m=T=p+x8IDL>VT<f$AmQjK7bV!t*udhGBY;nzTeFiEHm2~pi
z>1z!joirNDs0-FFWGHh`R<MVFgfMqX7dRL~HT|o8*^Q@s^$#7=Id-n&F3(ncC}tJ+
z5lH^o?fC>(g5G)pvQNIS#*QC=pw@b>_bvhyEsGduYaLVA^hlE{bvzn2CgIb-;p<jc
zKwLsb=Vtw=G3_}IRxmNg#UjiFT)<cV?X^N)pqdvg_FBpNCy%QazFU;z-qiN8-5zj8
zv^hM?5P7Nzcl_EvX{Wb{<xpqdpODTs-s6SxPx}}=ltYI_g;FNj{YmAf-5gi*bFHoM
zccYxRfq1B`xurPNQx~VP6m22oHE#QN!lEI0OwLp5J3*84T)f<c>XkuvyQ$Z^=TWaR
zv$I2pSzoZQ*e+TL(tQ2mGEc_qc@+8)javO6Uwyf8PMeRhdSdkMaD51@V6gD-s#Cqv
ztUpxZX_A<u2K?54bSkZg#Ad!%?dE9dakwJDesN6^jWv<rKyq_)8%j3kwRNHQ$m5p6
z^C}wkk}m})mu!z0&A`kP6QSGLz0+W*VZA3o&&0gk>fBM{*96{?i~EoG+;D-M5QtW_
zYxmf0vF>%W{ckF%l(n55`=g0;IIMcU&H-H2SISYXU!QGK=lJuIr#Y;CdEGyF>|??0
z`yrXvQHjBMZKq~W8-|;xgGHW7Ku-QXQ4{9c8j=h%&|l6Ck4m^b*%smv1$K+&Yds`9
zh6mg0p)}|5x4rINMoQiIFkQj>6ZnyJp~hII%`2We`+>e>ZqMVXthl%dZP<CfRV~nc
zYA#=AEYNNUP-s{d#i+0tyxHC?&m~fFJ{*b$j&S=^_3>jZ?wR_W6~?n7UF9!@9*q@f
z)B_zBGy*2Y%Ak{=tx@R5`X`ykT$atayu6w`voI%1xb^0dw~x7!q@Y%mNH8IP$ei=Y
z#pUsu`|<91Q`3u9@+=_m<7j7>HDYnnv3R~GnARNKeV2Kj2us|ic+8J~FZ}PGkv2rc
zyhC?&o^t1Q@6hy<2^rmV;8!aMmcVgxAuMd2Nr%I7B+afJL#cguco}H)Y@wy_yLqRG
z1{02DD|a)YfT<Kz&#Rrwnqz`x9Be<&Q=?+?+4cTJ$pGb3vy@767X(qx!$U)JBaySU
z=xi!D5%-OB3RjU!c{VOlZWYTypl1}@An^#N2M`!iB`_f{F+t^O3nlxQ{s=FH%jF8n
zgd!gh6Ek+8r<=^>;P()1$}*X!vbVP<SE$mAypx8emHe-Kks8@hOKsCB;BV5`SCpAh
z;lyb<_w%oB*)(h0^Tnay@sN6w%Pbn2oOU}pIH+E=f=NPRJ}L=!b<By)^=0!o8j0VV
zt&OU{Hq+czVfdT_92@}Mx6*Xf2bG_HhNiZwuP<9#&VIC1n3vXKq{I^tfh{bO)~?x&
zhMajsD>S^{$-z{5OG*xe5*b}jsA;zb(hD;T@Dj**T|d~`N_>(#sNCk9sy2rf7mMy@
zDz+hhZ+jq-lQJ94kYnfZ`QGyE`2cUZ`f!^PU~nA*8y6m|ld-JFD4v6<ecdRSvBmoi
zCOP?q8XP&ze&}1niNP;BFv+u!Pq+DNy`W~wqK<h3C2!XRegEx+r46P3We8&FN!m`!
z`Bm^K2?x{FvMe2)B#Ila>*<Io#q_Wh%1WQ7*Tnuvg_5h~d|qPy>({T@1YU&Gh&gVk
z1Gc`L@@KoeJk!=94tDm@j)CvM&yU4WB0468aR|S3nCJ25msC_LqZwTTa!IkVV7e>{
z?*os;3)MjA9B&>qS#tIEif!eJ?Z;AwrKKg)2I@RLlUDt&3T<ebaQ)3HGFbif;<{?_
zEm*xgZfo|Vk_-u)S?k@ZMZ_dTfgfI;4b?>)Tt0O4Y0;xLrHxw{D6e~duTgH<5)B<E
z=l2Air6GEfAEv)_M@k&FIcMQssk>w<Y;Lr!Cm`6KQE*k*46Cda8(_yqMOm1bbob%A
zUCCT0-9no7tBZ7vCFJad0k7EJa6$;h%}rU_;MMB&YgWa}s>6cKLRypJPeu~_TI!RN
zxaIkw%=^ma$j9j!Q3)|s?yXzXPJ8vvmp^C-^@C`dLIv+d_WiR037GGx{_P>l)yQ=n
z4>O^CUK&sJ8W<kl9?Hw8lH;=fO^Et+YgAd}5xCGqE>C(*_2<s}#GK_mcP!npj8$b7
zhLZUzg|<NMDdF!Y=tig!A;F2&Jj#Vrh2|!s3Ttb|twk|qfCT#;_)~WI{d}1rX~pr_
zFkgTLNL#s|{L=gCYP@DlvyVz6dnxGV^k7_Ry#2vV5hqX7v!@?QHJO=99+ALcu<b!n
z3K&ci3kF2b9^ui;(U=l$@7{)9?!71cA%OgK{(RPCe{pBVt{=Y8a<MyOmnRJLi`N?T
z$|s1|jtea)JEyqlV+$E}<vC?$Lr8Zk{rio}9nkzuF>mg-Gp47eg2=gp$gSq<w?~~m
z`J%3()&AN*$n+O#R&u%SyiN{_>4nEpI9&dix1^X?ri)Q{7MYZ^qf*!71Q9SwIFsn_
zUYAu=VsqQ`30h0eGPW|wfvec`bc{r|honY{W!BnSSZG}p=Kq2ft5to!B**;*JRUZ>
zigg<nkAB_Uzft_%G#Aph*!@NH1Sj!QVADdeuX6r8kVMP#IH4V^6J%ugRF%;qvTI+-
z*qj`#WHY(*qU7j&T~Bl8e+Z^w{OamzT-+1tclX1#NJs<Aht6QK&~mokZYAzeGPXFW
z!8*WlGxun<Yo$N7*ets1oPtkGLL#Dj7356LH!G%F5Y1`}nf}`CD)1&@^k1Zw@Y)n0
zN9!L#I_<SEu#`my+H&|f8NDB*q&^hu!0SDiv%kW>Hd#Vdp%VRyIroLqz?@@r-zapy
z9wQkh=zKv9G=%u_8$6HwSRT__O;&j<MVUrX$X``CTr*0<D$$OD1Y&#qxMw5RSI8SU
zIJ0;kg*efuj<&Y8@_Xi!<z!?$qI_;XR%lWoF1-WtW{2^N)xK!D*DL&yEDyHU3a6FA
zx(q9~I5L$&x`0~?PQW*bR)Rs1X^z4^pvJgyAV2GCD@esg-_uEhnWZX`W!torMUNjS
z)LCrRylTC1%_tjRbjr+Dq0&nnrSteNK0%wKikCP!Ss#y$+hvl1ZcYNaaC?Hu1OsH8
zeUDZ*)TqlcTgD4NMk5=!jQCxWgSkm=#~a*8+Z5R8jwG|umMT!~2kf`3hQ!ymCquG*
zoYw`b@~_y~dhYl5sa8qY%yzz=?+Y4^s8Qo~Da!l}QK;8amnhz7|1`V?IST4836%71
z_C;lGAOtnfTYb<$^wm0=TCW1Y(Q~pZ3*Fb))-|L6$r+00bffx+9feY;-C#PJ;P4o&
z)?&6ohTx5KB1@@rsXqJ~J&6TU`|kPY@hXQcbaSQRF{o%Y38$6A_GJ71ltXd0wC!qH
zR{Iq@9Uv`=29Z0hY#f?KzH!`~@g@!><%qi5+2{TAc2xx#M#gVTX!IAZTW=gUOm?3<
z=*)*{*TIlNz)wL0pW?pN$Q75eC-qo%oE)BvhFfoYI(5cCLb&TH1y4>s8aXM@EzDl;
zj`cPW4er<o>yDveSUA>3B^aM2Iizzv-?BN`I1JHtl>#O^j?$R3q);zo8Lun)G#PlC
zGCv<$4Zg)}{$pj=YSYuZmi9gV>$8p7VtwDE5jpB-Jt^ECjcLG$$dN{?0JoJBon%CE
z)&;A&xuPc0j(m1WLNHr=*-u=23BPb!IZr3iQGOCWR1$7rA3JXJt$P(XTx8~pCTk1S
zzw$#TVm8w{R+(cp?oHuwY2GYf&pX<7%d{H)eQ0oXLh=EH*SwFfpQn<WRK~72+rG|T
zh?w16z0`*zSHg>O`J9+vKTe4@%gQEL<J8rDf2h_dkPSVCLH&S!!KIsH*Z(QS>7I6p
zWrMDXv2m5l^3>zN7&%%Vp4Bn`D>{ndjHmX^E2b?XL7S5qiTx??IkH;kN()}I-*Q)`
zq=Gi6$Ll30k+(=lLE##Oof|?PU*>yE<_CGt$rYR6LYpCTy+mK=zqF+Huc<#p`Z9>>
zPPVj`z$7iL^Txl&0(K*JauE{p)R14;KeR}r(l!TUm$2h-?eZJCxlv+#Ox(Y%U8IIi
z5U(i&JZGvLB#{@~K4Cc_>f{|7aeDc@sO;>Q;Rn29E}##5;Xup*2@eY^v7OYPg&c`p
z%gp{>s))U-JhvRKlzfBy91rXypMGOwx7r*A0AZl1E*~(k&lC_z*@^umuouyrM^gVC
zk0UxXa<Mljo5H&GZ!e$^$?)NyMUR@LKpR;;sg_EJ)QE(SCYcP#_wP8o+5f|-08fJC
ze{r${l$~j>65;hdUDJ~8_SnwDoBcVrLzV+Nbn6(~zyICTkktFG&nc=bTCe1S_Uj*c
zd%q`w|0s{L`-J`<jIqPU4}$`tXG%_yda$ScHnuyN-_G@LsWsQLy>Ip!gH*p%O^Mrc
zhx%Ls@BCs9=DaDP=FAn?%j0UD+BDatoL>u^DvwsX6<mIA*c3fR!yw~J(_bZ?g*nvR
zFX&lYBc5ubK!UjVcuGpjU{Y4#To?+X>c<(>ZH~~85cMkkQQyGWRa=+SEoGA%cHi#B
z6B4eKTmMip9w%LxnL02HYW~>mqXSo<jaG&#-I;H_##krWZd6bOLEZIcMO;WofAFPc
zi{DdQM@M2d`wyMittjXlqUamI7?`ipZhB4L;0>_b)^4x~r1ceA>{t{w?n#pN#cmB8
z3~}buIZbeIJKb?S7{H2_P_B2cIWp?Dm@1Qg{;a}u^rv~O3~{jWXu@fZOzIO17u|IC
zn$nC)m@@(CP(I`u?1&r|Q!Ht^`vWBhqjWJ_$RJizgc6SeAE0>89zDH9$(X{w(a|KO
zr1EtNyGqi(dU%|t@;Iy=F2BJF5BG3A6)S%g`|$F9S^eQFAEN(A0E8`D|04CecSBq6
zMU0&UZ;b*UDe35({v^$E%U6`rq8NLH+R(KFc>`b!7~2lp-EXiTya^hD1|3|~fxMrA
zWITn}LyKNUr&^CynNg!`=EG|qhns_~Xi0$Qq?y-rx1YCm$C}8H*La>j^yT7px{OOm
z2%+HRDJ~xd1pR`70_3N}F`UJ$=nmr{4C{<qGqC#w&U4S*t6p<XOF03DlY#o$6bB4)
zfrv$}ni<&np4D{OV&mK_E;(ef_A4rHHH61@=XXZCZ0>{DcJwDMUONYO?9dn>-AYH#
z=hG%=+B`v2zBX`Kv+U(`90Q??VRXG3NR23aj263bB_$<BuU_`s-|0QsluIhN8>7Gr
z?=2vIds8&~dGu#ZQ@F)!eI!Oqo78%$5368<Iap|n3cn#8X%BFnv*riA1SLOx_-}Ve
zMrj<l*ivT-LGg8}Ew6#yu>?OcN5T4%!WY`>^Ibd~9FmhQ_Qc+<WV%?W`Fl_mm=DFJ
zaFd3pmQ&q1?aN;t;Wcm+YAQ5!4V9TLi_{u}Wj3>2KHSp-G>Bs9G=T}hYlk;4_U8pX
zk1D+8=SD)c_h!hZt6`3}ZJbUF*a5kzw<s7u7MjyS&T1m;JyE4$sTv+#RL-Gw%}lee
z7M*Gl7_1eV43qS}iQ?QOb{@-XH7?KdLsqYrVaTV~DaZw}wT}*_TD$L+@##H5eu2W|
zEyVgQUT&!p)p4$TaF;J?O$@F2(ZUOej|i4t@RqXOYFY26p60}AOWm5S9ECg)3<`|~
zo!OCM;+a7&K5%mo=F%XjoEaMFy~p(a(hfr1i<jX6MW6J|gaQJ%xYg<LulHtw>Mp)V
z;`i@=yH){-eb2usSyG+!UIHP_%;ub2YF0&7ZAv4NTA{{c0`qZ5-R}PVp#inWWIEhw
zOC}=X_lZ`Wy^9BWE2pXBNUmuh`D|_GT!|UpdCh%Krr6%T*V>wcqsCh+j*l`@$kbfJ
zc+}9LSR(ukg*=Ck<g)V%b_QnR{j`-li~^pMN6NT-{2uu4*l}$)VU?wK?sHQWW~KX$
z=_#|Y6dt>xk9NgDe$4g<@9gZ38Kxc2_IOKlv}K9QYidBZq<Duq(&R}HvGJz|U$Dw6
ztLRrE#s#X;0qn4OaLE@g*0`#FiHU^NVjqAV5FEU0&6Q0>b>`>@e&wqJMzQ<cP5D=>
z+NJ6i=oy32Ac%W-C@4e}JtH8H9ej#cP+0hSs2`m=d=M{NDsge)lh@^q=~RZLcm4?J
z&hBUDVjY3eP_u^pA~wicUyAx0BYh>aU=nt<x=(wzyyGMsxggzQqcYNu5;=BB!ku6i
zY^gmZdGu8WGF|44EYgoW?aXd|ME`tY4}J|4*Ue{2JVmqz_0IMtJ+`wQ&Tp-TxKs-?
zA}`5|*66+E|GO!04}xgg+}x69y>&848$Da2Wf{2E8<NaLbh(M63^Z;ncP_+fqiI>S
zCnr}uV{K=3wX|lIb7W6X-OkCPx>rX!<IC4)>69}QP*=Ojcx;2j#fv{T)EZL=3!9G?
zyuc24_%J1v%SGcwEbG+i$m6mopWt9=(7-=ApVF*#UtOj1G)0!Hk}{Q;R~Sb;skY3t
z12%ZHN^*Hh3fxXbS}$Jg=cTDYt>$WbZ=R;7>#cT2XTgU{t)}Xvi{vt`42+CEzL@G@
zUIs${z)>?nUKMQK0!g;Epb-kZ(r_gpszT{<DYoQK_cmaC*o5r=oi5{+*Y4+eB@!Ij
zX;^AwW3I3lE_&JVPYz=UF=}14nXa;o?wp=D-5Xur7+k)_BrU71hH4KB3wGy8;5ikm
z%z>H!bRcvoc0JCKF?ZHy(<KXQfx&BUq8mHE*CMuZ2qDKe5uxy4vDZl;Q3CPT>GGn=
zbX2Hu9fr&3xplE<B#AGT!UH!-JnQR|(Za|9jmvpb1-E?;#hiYNxhY;o#*~L?!P_c|
zSx$*6pewaMS6=Kls07t$-Jg<Gqs%u6wX|;o#Rm>KdA;G_4dbj^XeyU)2(@%M*l9w@
zd6_-7GK=lm9eci)F2A|H*mJ`_sQa$D2uU1QG`e+70c}{=mJ?i6_7QKw;ds=&ZA|0$
zl9T(Qf6}Kx-FVCclgk}m*Y!CA+Fz>Fvx6}1M+Z5S0hF}SLnBdl#Ml5(XrnoB_?~E9
z&&KYOOv+Nedn7!#%*$hZvh{s%SqlxHl*bwAxLfHox7_0J;p}g^zg<uBMT_rL8B-Q*
znIn<!*!$mDsL@ULRQ&EoM<Oi!_Q6KW{iodXlB%*#NS?8;ZEQdM&N(@K0ubj)rrd)o
zY3nQGv$L9BDQUtl^B<Gw#bd<OEbtNBpNsNLmdPX+H2<gMUrtax2|ewR8o$#-N#sfO
z85?-$Uljh*>TBC|%TkE<9<Oj(*3<b5o-Uf83h*#p9Din{2CP8efHNc{!Qn(sEB|29
z$ojkeO~vk5y6$(#GD$qMpq?wz25K?W8me{|9i<@s%eHd4>3D$r{L!E8T79V8^IYYO
zqxfUh26MWpZyX5O%;)B6wVwr!lTq>QFN?mdX3tY16J~>5fnx4)R*~ssGw{x8JV#hp
zAtBXkLPEQm_iLyEiHE74{(%l|p8d(l=A}8G&>inG-=ZS^ccI}OA}Kt0#Ul6wZ5RwD
zA_dL<k`A!+_~|30+(UtfpOLNiR6DW}X@&34d3k<Vd!wg!g@<@=qt~~Oh?yKuIq+Qo
z9_4W7ZN6_gp#$-}K>Vdi3^{hH+w(vfxmd?Vh8+V-tKK=gk30}jg;c+vnoPLG%~2nd
zeg$4>tdw8#9WPs^=^x~O>)=xUdgL?7-%~@nCLHBD_~7sqiQB)$IclMQA0pE$QYg#k
zDJnw7$oE_(#?*C;K)&B=SE`KJAoQFAqN09Xioe^jUbf;8moG=osI0=!h8CbSo`^e~
z?RPLLnkCUonq>A7f-xV3{EZro+g7xS<&?V90Lk`kPb0{3FW$$;fAif`JwW+S9iNa0
zaHp`o9e#1mK5?EA?A|TQJ4T_(g)ecmE~LAXp8YGVuy}dnla0b7iuu>KRBlCL$Q<mQ
zv59sU**hcJ@fs~B+W20pc{jz3#&D7Zxz#&!1+zBk&6Q?h$eR)4(Zdyz2S1`8F)aPw
ziWd+kMi)NBZ#66mnaR3k_~34QRP`Zi>sTe{CM!$(7tU0CeW-$B;;+}e2`^%3D~%g}
zTyT~8J?Llxna2OxSPuN%Jt*m=8hiu;`_}_LJS^IieF?5@X!4rH4hyPl5Uy(Ues}1G
z_1rM(WvLpyYhE5K?SrRf|J6%Pw6WfG+gmE(#Kfw6D#FRBsIFom<r8PJ?EIBBa}Du<
zob=qZN9!AfUh76qxs(OUKXl=Qp|!iiVoEtr8_eWAEh4Doe{y@MP6yF$M=v{_;d*>m
z5OmKNfJ9G6uvSLKyJ4lohgBLyt=8({j|Lv|NgUzPQXPDa09WxRC1?yCmTu;;yUTA<
z{j)lscT0$k<&Fetrc!%Is|9JOmatv&jlQaW%**qh@|u*9`Es|C;)z;jUA~;@QtQ-N
zEP3Z?^6T!q<k!*N3e!RD!&Lez*;8fDSFzu9mD}6pY21<JSV_HCBPW5Z`z8x`ZKbK0
zyVYNai5$ihi5&W?hM`=v{7Kwy-VhZcRsvY#>gtSW9IMjZC>k5)77POGDij%lCLad_
zh+o{>9Ym!hM^|}Ja?Yh0Q`HiCuH7|PNp@DPoxHUxxg=Gs;jtZ|;l}ent?32U#?wq<
zZ57PB<7#Zvs&%JH-yU>K{&Ue@5rYzHah{L8v?A27aY&dhw>&_L!Ir+5*5^aO+9vO=
zg9}QLIHpc)!p;5p*&<098s_S@jD$cd)I4UzWJK7LSB8jSFVgA9>j06Wfdc;Un+-^I
z(UG~jv{?Umim8d?tUF^4I``%sn<{l>d4(E1q#P<+5zBmqLi<~R{_A6If<L*5q!?~{
z>l+1;PY|Ofq#N$dKTo;g<0V7!vJcJr<sXC$^N^5CPpvGD_&(Gu<;L|J;Pth{&n(Vs
z>Qq2!wCv?>XqA-dnM@R}i)T>{%-)m}!6N*M#7nA;32c_^b7>4&(v8J+crh1!Ma#<1
zjV$|SFe<;*FifToZjC@{$8ogXsdY<qllnv8xuGBDjSiuqZ&c}nNU((ZT8BP|Ej;{E
z`XeMbG$eo%E1)EV_r@ltUsoEAt<vJkPBIGZM7og=mmgd*%qtAeDy*b@g!C!tp|1b0
znl(wq$nnk>tkaBwxcv1Qua5aKbYi6^BDk_LOsi{OA|rXiT?F)6G$xI+DgVIO7f%%C
zL!SK!gdngn{)w1^@3*2$O8yh``hEYD!k!qj5^A*%5d!TZxeg8w_z96ZT>n`-q*vmI
z-xCob59|<(;J2<=Hd_OqPjj55lhhbu%wF3f-{JcH<l}GPeqpqLiFHJ%h}GTo&B&zH
zrb3Tf&7cw?*79Ws2@q_*$Vbq`<uv_(z29OzUu6=cChE|@eQJnqDU;-fcY%jyBZ;^0
zw=+FhFd%T_Aoi_SIFY$?ZqoH<-#(=4BQ0z{6wH4pD3RM}%={=Z!9KUOoVokGU0DG=
z{l<%D2Y{Xj-hr5gI9epK__r4j6jxZ8Rhi{0k!5U)EK%U79l^-;Tn}l1H;=t1f4LJH
z!um?%hwBK=5to!q<N7fdDMw;(9suzLdz0NlXX&CiE+Q1Nc$`;ufKDZTUkWwuLEf77
zL3=qtvB!@eSg4Ov*r8E$idyM%<XpCE+8rqPfy#xpE}>?4d6PyB)77^WdF;fhvF<=1
zV!_t7&5GvB{x@GxF$A?_RCl!vFNNzoxDl1alq8l4a62F-n0tuS=#<ef4aT5i2BG!W
zvJ=yj+4ZsA;W+DP_#M11JB=~DTf389NoGY_FdTx^x1NUgO&+i$E<5g*EVL^g8$h<r
z4`YWzPpRSHyDYFlH$iHAhS(6^J`BVZchrjNj3!1#x-0MClJ2JrATvj6uf{{{3yQ73
z+lnWDCAR2Iua-fka;xClML7?=JvsOCN6j$&hku&#i~7%;Q#_XYnW+HH#8wYwgaD$|
zGcqzsP4t~%(~Y<W6KN7tQ@x`75=ghm!w2^hoq<;g<k}jE-zyr-kGR)?=w6f;{Hd!V
zxI6fPz`~bCd1m*rdz_`_r_$j|s+TX=p-VbvgOLR6P*r`<p+qcJ^#qNUr@FEBhgkTJ
zQ7+<fX^pQRZ%+Tc`s0BypG+0Jneo3ZCAmhhgU530Pt5-`osDRnP2oeUv)i}1<r#Il
zBu{=@D`=$PM8S8;Z>|4(f!qx<C5gxK?X5rCLM!y*;@g_^mY=WJ&yyb<6hjTrygczO
zjK?&w=-JtU)ojGZ=k>sOLMfw!UOdUdz#z*FxRAbNmZw*xwkTk5U>{S72?!8>ibRN*
zgb7j;`pLy8AW!{FO;i2tq<n-Dt7rMeQDkwJYPL|ef}Z24ev;1_z2tC||C7LAwBIj8
z6`=9ofQh&oPHKS*L3+)d)+$A&OwUEFW<yR_y7}*8w|I>>!~Um||09|E!Zu<iZQarS
z((-YhR{l2<{<%62*~@T7TiUg?TJwG^S|wUtv)0;OOJ6P8D7tt-tCSAe!7K6~xQ?AY
zAxgBTMQ~AeGwE`X6jPm{f%~DGyYzxUUthEbPZ33rh*Y|ggpn-=uUnBFO}MFul~^r)
z*rEi#?{P`(`05y4%c_35>=#_zS&jJ8jrXf8j8cKLT3J78PSk2neU4T|TT~aW_!WcZ
z;wlOn;sc(O+%+}oFV-4>nvj}G--8HmkVLW)z$f0+8cU$Ur>{00d`m-f*#{Q|3_DA?
zYLNha-}wCs$oc!Lib}=ym|7-KFz6dB)1YP8N=YS2de^bU^HFigoSP|0B}Hd(KSJ_b
zV08r<npmOn8bz34l#Y5li<i^VF8M19CGt(Y#_<8cu&dQyyrO99_RG_T2Lw&Q>s<{_
zZ=iNvyHY?=J#dIFhwm&jwLbIcIJQ_e8I~ZJs%WA0kUw`#{aqMTQoyFnu>TH+it1&*
zhO(v$yEDm+cds#2DZgib70iViXJ;o*xon!F63|*7_dN>s6Bm<mJzG+iulBL@)g~8o
z6Ten~vV$OiPoov~07>{QV7@%3oAOYv8kaRb$Z|EBw1X|1J^!-*j-qs&sXb3u=4704
zG604gk#FF%!iX_*7ktPB-hyH}pS@{0pAlO$w`5a828Vxp=sAwTP`xw3^z0zO3EGxT
z^|D5Y*`UuBH~_5}iqDhp0<E5nQ6L5uOgLk(a^W>Zzf|uTXr&OLMipDERsFS!Y$9j)
zQgXbokb$6hqQHCrZnv#5I{Q@zo+#kP?V%3!bKBG6P|8)STB&Q@rY7s&-ccKclY$#w
z!baS~fP!RzM@B+HhGX>-dlFy@W#Q}lqseP;2<z5Ar6PmV{zXq8f^;Cf0qGw@>r#I6
zv<I?c69>s)==x;{<qrPu_O^Q;i-L^wmdCqTct-0uE3b2VB`h8iOYwtzelYyO7kY~n
z*@+UBs(8}?1fE-#B(8~ro~>%2d5p}q29$6w^iKM7O!()b9P3V)Xq0+ZAix0t9A&Tn
zgpckb$)QHMN3mQE`JJY!kG8cR-2BCmZ|yq9dQiLx`DWJbLW9`zkkm23X7i=MXjuJ`
zmtd@u5&B{C4BeO1uXi-3kPbU1)&oqlWz)PRUi@{$M)+kOF)c#KOdd;z3ru)->;!*E
zhT>t_m@<*Cl*D`0qF!iasv-%Z-+uk+rIKX7|8?nif*t0Hl%t-J-r~w96I07J#Fr9s
zgLC}!8z>7TA5Ul^;)Rb!OORG-RK2GViH@Zt;xpnaiOkE=TT7@Qc+m20GE3?Of`GrY
z7>fiDSDAs>>YhWti_7ISIEr@|B-AX2%6`#p?gn~=2~`nyM1CU6EJBDAE_e)1_??Q)
zRsBnk)i@45az^sMF4)!R$G)#2Q|TqUrF{ag0t*u%03W7I`ioIg@zoNmPW0Pb)CB@F
zC2s>-F-?~l!9@D6(XV5E|8A4aWI>!jV+SH3coh>yefNwQizK#@P%t3r$xYl@KII!t
zeE(pOb2dDSZLzfxyDr{obyF^*=Pme3DFZ%%^0j0pqK^9#{y&0FjZi0HgLA2OLk!)o
zrG_D-2CYdS<TY*)%3Px5c73DR)eTUdJ#TMG6#>7P(9hqE^YOmN3x8ht0_D*$>2fRh
z$VRJY_~f38OO&*A9t2uxa?ER-JoYQOYV>z&jrFDgO9X8I=KD#fWbb@(hrNsWENLwO
zA&t7<T6?yHd7|FR-xQQ5BrnLmLi$4gKKt#nPu%Oxr(cm8k|GPey*?{EUSoWK)VOcG
zI~5!lTP)X<_3qB8IEA%g5D>~*J3D)-k<X;brrh>ts^Tx<mRH)g#Y)T$z2lhc?Ke$U
zT@>6<bp!(ud^8wfTEOfypl*yn+{2E&pBV<((y8ij<5>x1K9L}Dg48r^6?S@h_nB{<
z+O_9qgSE3azJXaR@mh?j4c1Ra*{oKjnLL2AY63bjkN)Y@X|3l8tC2`>^1H+Vzmw1N
zdDDRIM$BnGnGf-&88)WIow}Y@DbO-#&9CIYetJ+a|I4YtTU=b+>1Ll%yMF7&SF!@K
z)hU32L6#2DtTLUiR~#1&O_h_j788p{jjpzw7e6h8^Y*2{-W95lkWL3E=0IIX#O+F|
z_b-OycpY{piwt4`0H!3oYa061FX)%&vhkH-xa+4806tvny=ogM0-A*)49fXTDwd<E
z-X|tZ(&e6y`~W;PU02EJ;d0wn2vA<dZexb2of)|3xL>Qje7PBU3f>H~KfYQnWAKiL
zQ8jPt_8QXx{j;+@M*Mw$<B(IzmGw#V`(m9z@r<)s*Rwo%=w6T4+SV32ImWJiXBpn5
zc3^gjQ}%r}A>Tb@%3-S1uDU2oiIzd(C;hH`p3)FBIHBtE(x_SEf}V|y%}Kr*JvocJ
zk`6(&D|#ZMW~oGV`|=xEhn=AewLIGsVcV0505;KdK`1hB=6*Lous;iLrJIM&fz~!N
zH_|`9YZk}Bcv&(fa8A`_to8*<#ugEYCdpR0m~`s-?2bB4p#;<}lQrG`v^41@Wo1(}
zkmK;LZZ3Q&sq>WpI@f{Od^HOppHdw!?`vuiW!VaAU!8+Hc}>TlqnzzwprcKfIiTP<
zT29-qOgz#4yLI`P8fCJ~X18Xzy>)5DfrJC5nm;iE6$gF@_)KxoegEcc(809Ss=hjS
zFke-uiB8Vr<3mdxOF%%-zi2H(CRnGpo8PNh#qV|3yfA^_6KGX&^-fSfH5;y7-6PYi
zveek$_c~v0A80U<%D5V(i&ZIBVZY52V=Z~`)o-<T+x@1)Tbs8k31)2rC}zn0@2<*Y
zuap@>ou=o#Hh*4<V(tZg584@ZdUszB&s&WW2hPtaXIG~rRFnmmxOg5d`%3`^DCfI^
z&YMTdRCWp!eGP6aN7RXS_VyF?M$3zj*tUdgox2wntzBj&CVnl9Gi^w*AlKI*_cZ`e
zA*U~Cn4QaGEy?_SEWo<u%f#PA);o<f_|{zNvKpJBR5^YHBRKaQ)~8)YQDe!xUf~am
zL9@?cf9mow5(V_7i8*ahvow%Hn?L!Vv^cKj&)2fkxjR}iEUi@m-V7BAqMsDzP-=rF
z^hKBHtJmj?aTKJmUUU)`>*9VHR#sMlRNW$r&4q<$`M3e!IIU*0KYtne7T)4NR;;QD
zc%PD>FDfA;V>yvVZiG(c(4k*St3qvMWC~<1&<Jb`wQ3@Ob#7i>9>6PV)mbyuBil}-
zxc@eyAnHxvcD?y9+!maabR;(kgKWPpjXPr6O7a_Nh7u`HO--%zCUR17j4e!TjDpT`
z)@I~TB%-woc(8sI_J<F(*L4N)T>n8*qME6QtNsh5_%(&+2)gCzX6gQ_v0JruU=Rat
zg*T`*_yvkEs%WT^V=>UbAz(0NO8_u~TvO9ricpft1Hr{3xUqEQI-e@zv<5l3eIF|i
zD3qk<>w|cho$oeb;_cAuwG=*wY$H1+T2g+;pPI2U_RV=MDg3o${GJMhDir*Vbw+l(
zRhGVJyXUj3>N)uAX&d?SEmunFl|S4R6cn7Dzcp!-?1Z%`rVDWs3$jzo|0G2B>wNHE
z@F@i6;HI?%%Yat3cvUOy01)#=XjGx-WPBw?XvF}kz^BnM1|UAj#&H>YZcWyJSs!#H
zceujEd}@o%Ljft1POd(UY1rf??dW>qw8HNUy12OS*f==oj@U$(on2iL_gR(E4nke4
z!L^0<k1_nEJ&ZjqpfOA~G;*J|biH7BOsrmuOFc=b@XXh{2}`YjIHS7xK2h|;2jUq?
zu;{bBfp}@ra~YXzC7JOT{M5&&vYU}*f_8SS+9a%Y<rf#uYYpj964cK&y0WvW4xc>H
z<tDv7V2N0}QKVjz&zK5OG@<sab>6fEyt}xlZR*o`0l-oNdZXcD`pZi+kP+pz{#e=b
z@>17b*L@6at-vU1r3zdR@zSWKWa1q;Uc&Is^`;VTQ^u{HqCb7KWt$qI2dVwbK-n!U
zB-+<E@@w+y{XI6=bw~b-uxw)P`yiul<Ulj)GMxJNG&u`l`(BC}g9U1pezYW<W+l!|
zGuKW<0B`eJGTi;BW5J<$d>^$A!^g<U6juEn7|02ZiMFves<V3>v(HTOgM%1nXG9Kh
zo)&)B6_rH%wiAnw>P=)wxgD-%0M|&d!R$b3gL`6n(A4Ghhz6eTwsSsfWX*)!pYq<(
zu?8%^aVN1*8v_v*n%HMsLqtNQWax>g7WkSi?gG;hhEI<9sV4{L6W($#_6;?^Job+y
z0$OPRP8f=}Bgj{V3c28qu2gjw-k*IGZI?SUG&3_Jk`cH6w-*3`0EjXJ>V6Aa<zgKG
zT!DGG=SUIXU#*rmei7B3^lie3Cw=lKxkIy4T<1F*Q^5y0MW*nB2C>%*w%mw+AOFMf
zc^OXqeBm-6G6&C=TN#5);OZdUK&hnUt&_dI95tS1^?s(izj!>UQm)*43ANlLUe%(o
zuyd)df_Q)=nt0~?gAPUICvm&!IN|UUf6=0noy|6l6ls@D87l0kck9=YL_2=@apvin
zv9(2%4Zw__JFw<SsX#4T!p^52toNtNzQ(4-lVJ33Sw6IfaX8bSJSs0O%~OPp0TXHm
zID>Y5L^HwHWpS^wxThmWxmd)+*|6^sew_cXhThU(O|<n+R|sDby56?+c16=N)0mFK
zqM*b88wN%xW+g2n{*lCity6ViyZQO^r`2q|VxGQl4~2}eoTc-9(^ud>UL{uJ8O8>g
z`MiCm%@ThGtFt*CyE^5|E7O_f0W`Ir4?oI-O*zX-?z384q+$w7mgJxl1dyiKWPFA6
z4yd0x#<A*6fnGJ@SmFAIJ43okkGmn2%%^veTMBb`Zx112cDym9nD^*^m_lGfR|h$E
z{h^dClR8;f>7=E_XCzB9UYHGmPgf+cn|Pk5c(4a$YmCx*j$0bq<|ya?a;rR20gKAf
z@%HK@Ghu5q|7?qQ!B#mGF2L&m;WJa(2b@HwcE&Yh<3+4+a}~xc_pVP?yYT5uifJ%#
z2sk`W!~64^n@=A5OtR)+60-I5^hEuPlp&h}PekZoAGw*rXhz@6BrAFf>TTnV)fIzg
z*{7qCO@`?TCr8JhVOapPLT-<|+cB~y2XE!D(&B|&&0BD^kBzleerl?7N!EqCLQGBL
z>0%)**$fepk-QF{RqNf=&1PV#p&6o~`-0XTb8|(2&=lO(7_72^yNQ`&*M4^8dPV=n
zi4jodHQHL+tIa00s<~XLFyFBD^!DcV9}_S#XtU|64mVf<Y`6!ynWsI|)i&ii?7GWV
zG5E?an3%Px=AE7-S|C=7e}(0wPg}Y9c?#e*$t!W*7I(^~@R4xX2KDzrt}+%%CUrO8
zn&=bV%soOPM61-u&{b^Ay+omPr5A@uHO^ALq{@ltG(1tqhqnWkOICc1x;$sKnKD$R
zSSMN_Mc=lrYL^Fy53-q0*<TDaJ-vB~Cz=f>*K0*$?PuX@yRg}~WwJzhfYe6+e*tAI
z>d23Ay78F?r0aa<7j|I_Jg3BPw^JMyAAenw|5k<wrbpN+y+++{r+Lp=>_nbw%h|bF
z579lX8sok=opNJzDimIatsu*Qu~(v@FB^S|C9x#|5g?DoBaQJBV(|qLjs5RJ<{gLa
z-i<HVRMgbe3P1@wH5!PyKYQ5Va659C@d)K4Gyw4U0Q_e7I`Zo-ue03q1*gpsW|pJj
zV*)0kFF}B!1T@h)vHw(;pH>i6e^8uIUR2kL1;^N%K9#ke<YE=*dVjojy*sxydTKu>
zJ3ASV^CxSugTQrfr`vsY$W+{xY^neW(P>^vj!6pNy$;zku>H-top(jkDCR4PUmcy1
z-N$-+>qwIvU;1cPTZw-Bs2QiJRHV?^rs1ZTI9{xa@>gA0rx9Q>LX{5ZFK?V~ZguOP
z?u=!XE71Z%g{!?%ly7vFTdPE^=Hh@PATmj0{d{+KW7Hj^SKe^JMlB%V-S!NNs7T(N
zl$2C5mNxuKhB=f%(B<NSIXE5zSWYBj2e3KqX;BEcBY25kcQ<+0gP++1+|Cl>zH3x{
zE-Jn`q1kG>MKS7*vK;(***7Zyaz7qhYp<(r+E)ETxEp5k%Vt1d?~bNh-dHGcy7%OX
ziRn$$RCBLi440yUc}xqk(MQRMU81f620(ujF98<TBw*T;x|t{L__sDoV1YVNY|9~U
zfzz5MjA9(q_zeQpdybaAA>jlyP-HDXDP~OK<UEZ9p7gF47va!A$t|S7A!yAp{!<E`
z4+NhswHxYPj>kY?>P=$j-551TO{D&neigXhFZYbYrb}tJP-n$<$|{;Rdc06aT-U7n
z2v%j<U9~2iSaoDcfP>SmSDwY9&Zs#pjB<84e@MY=6Cp<(CHA^PxyA1^mR>7u{+fIq
z4j#uCiL8+?^_e~(3kxLZWzsF0x%YPh*#u>uj7!z-#OA(Ne^;05<kDldg&f(G-c(NB
z(?RW;El%^ZB>Y~u0*V?5hh;?P>go2l6P;Ga&=8n}7zb|cV=7~LoI%0CrpvR;d@p@k
z7OfTW-)U4kj{a<w#KDQ=Gany&tOlr2yS(-xfPSj8YExr@Vba-r2^}v$Lv<ZZ^W;ZV
zC*biJUBCvNf({{SS)1YlxbBf<Du3<kZNa7EO3C}4`06yJO@->B>)G>$QJ4v4e!PIe
z*h5rMV5B9`5%dRs_^DZKxxF_a#ia!aVz=u{a&_3At8v-Ao1LDUgJk^7xJD=BGP(*n
zH6Op2ul3yR%9^RMP3E>^WTTg=9&HazFE{Sbn)uwCk2k`=uTrc<PC~%xy7QOs(lI3S
z<4Z`11HhCwa^qae@6{{y#j_;v7(jC=m5+#oAklSYo73Xwx^Ztpc2S-6CU$B+@Bt@!
z3=u{~PfLh=Ba>s9rbMe*VJW()ye>m#b)kLM;9<~{i{){J9wkv(N*0@QyC9LJaJn^|
zIz+e6QMkFWH&?^$J`wgLGDlu1=Ncb?_~1}~I+ytn>D^e_=Q}>&=I(Kg={!<24OiWt
z6{zp=Y80=zPvD|4-O3EWB`;Mg09d$Uud-kRsF<MJo8m^Anu+qS{1g}G;BFwbe9<=x
zJAWfh_~zN?S0#XTGjI%ohH9ajO63pU=)wYe-iq_==1tahdrfVa&8yH1187XI`RK{O
z=tz-rxyb1j78cfn{?wek__KPCZ4sv8?A0zaD-7*IGd$ON_g1FUj`@1Ds_Jg-LJ1=e
z^p6&RHph_Q7N6A<makcj!Ox^t_klA<%3q-hm{3dnZVM(dvb5}5wdHlp)N|d&W}7Ya
z2c#Le$8`*9B$dotX6E$Yg_^N_{4l5BkPzcPH{+k?T3F@5<&EN-Pz+)&&=R=3o=;?V
z`+o>~>!>KZ{$ChHP{~^bR8mmsPHBT2dgyMD?k*J(0Ria-X@>5GA*4aNOX;Cw=$Ny|
z`}dsnocEly-uX+{a*fx_T-V<F`$>6(BeAfhSGCRJ!9vqzKOthFsKD1K!j^!DL9H;p
z`3)j^3%{L)25QIi{<Y}!A=HEXXs9APz|`~<a)B-XOMa%P?X8P`^{K7b2{K6fQD^S%
z&tI&3QIQha#ny9q5upQcH{4WCi`&^!pw)PEa<0jXO+=*FDOdjDmf{IF*jZKH?;d-|
z#{#{u_Mf+obyvg7T^IO>Z?N%AU~1VY4j6kXVDe*EMpwVJb*8n_W**c&Y|XlR_;8H>
zbtFEMX(j!;nE?2n@G18XE06>);_H62wu7Fb=T8Xlxi3^nmLyVAf*9z_g}ym*iW}V*
zGVmhBXJhJ{P?joaf@gvE`5~f@s32SD2+H?6TgM^~3OnWjhQ@-)Vtn@-D5JDm&X{s&
zwRsHV@s|Lc$B^r6Ao&Se>bM4S)8h*lYIXJega!j@;mP8ibi3yyA?<DLPSZ27tf~<8
zcheJ}JdU&~Z7Zy5O1!cM%d}p<#>gC43(ncqfA)`kozAuCw^jyqNGyvwtqa*^0>I0_
zL!FNvp<a`i0(QniGdYr?#7u77@)%5gK!EQ$K4=G=ec<eMUR*qtOjW1)GA_xr0C{>T
zvvYp**#8Sbct{9~dbM@Xl6X;(O<vVv)mC_#ko4$C|IZh4a=0ZqW7{ns-z|5AN=r$3
zAFav3pxHQeH%U%Ki<O$$(AAzO$r|2R%J42w32vmJ5ucgKn<Wz~g_uV6-Apqe^&!fv
z{M>w8s6&G~q7g6^qhUpiXIp3>QsP_JDh`&n2qB80?}py*pisH1x3^xVhBA&#{|55m
zB`7`;T`7T^ONfc}r*SoCR?uGbDku#jFbk10l@?7#$Msu4UU@G5TLz}W>)rkAx}c}0
zCyCc4{kDr~Y0aql;OX{43=S=Wa?j7Dm9dh1<qbGdRzIzbECezy0aKxA>h;}roX(m1
z8rgxqs3-h|K;bOW-!?bKAC9i>!<-gZaYpuzTLI;!(f)YjuU|;!OFyxWKNjXvu<^t(
zn}tT-_ABZKe;$ymt-(f_4sY5o`>p%dkE}dZ{Ejc=q`EIn`_!Ov2M;@rOR%xAEVxPe
zYT9loQ092(2)TV}|3l92C|2{jVV4Lo@qSV{XUNaO+^#FD|FO)xgc~jz*9E{XdRW0Q
zc}Z$^{Y6eWSB?<nDD0B*ysNS=Sx{hVtJxW%sd3%jMR<X2S#|MC*KdvR&w&RwhVJ*Q
zBT%kBTeHVL<5I4&IM-;Cq=ppoS?j+`NX2V8*3vryMU8w4klFC~)5wpgakMXG(<{_4
z7%C9FaYOXYxLAT!4xFWODLWIK){(dd5j3^|i1VR8&tbWy^M3mu{^!QCp9gifCe(F~
z)1EapI~C@3%Q<>Gv(-D}1%W9k6s8=fyNipBrkARsq9E#lAJsp?vpdv!xpA-z+)qGa
z4*7U>{+#A{!|6tpsNc=d5c`@!_tv(z;F#ZX&VbJ)GKZ~1@0g6w0SYGOQ>s_)v#2n)
zSzi6cMxy|nj*!O<E?c10F@e+KQ}azn-|OH?F`5SyiLLlxvpQcvj9%X*RC6tf7F1^i
zTV>0SA3Ro*grrkxdcrOj{fk`YxOco0wvUKEiH8uCRaJq-FICX4H7jVwi<VNv(;4^z
z*GNc$?%xL^;p<=joC$os^<lAXfQRZR4UOjlE@5*;8ViR=0|2@wx($eki)`pinf{cc
zaGzdc`z-4OP9oj;MvnsVf@+!wc53P}U;-RyN>mDcdwy4~Em6b<GPrOZTclCt6c_#$
z26UoR)ux$EP3;Gd=oC@}E|JnLh^VgSg?E9j3!^zGU`95zIM_oLRIL9RbpirKccIi)
zV3D(Hwm#1<P`_Gn<WC!1Y%n*!4AWIF)~m4TA|Ppp!p6xaOAw;=UqxCnK3FebRDol{
zOx^5ycbPFWNfIUQ+5jb&Ee+<hOr%BzltE4ou^0$`*bi*i(eS)mzia+Jqs-Jw<d4(n
ziSCu+sqv0hInf0>0&RI%NN8wCNF37&O~hAd5fJ7oFUo~m>(s1)B?TxSqh3aWrv*qA
zLqkIogtzwE0z?<#gB9`=xk4T~xb+)+5ANL=`+$=Xef-O1dwUyJu9!ZkJzlbvz*bTr
zb1QD_G6VbVM|KxESmaAs`Rk8^k1`L}2mLl$njf?2f06v0lo+p;uQ5CVy^KO^RcuXH
z0I!6ZimO|RSTBSNEHM9INQ=EuNs4Asp85SzThqd+0H9P((0Sf6m7b+afSjhvV&A!a
z^QjKy9UL4S7UbY;|HCj%)M-=mbxUrZ0!?}zG&^{Wp@G&6#YW`7<b8B84jvn2vPThl
zMjeOXOxDw5<QbIqMi#qMDw#RmkCaG>2HX=E7{+MA=6??Yfgh~{yOxRB)R0L78q8|I
zBCwHOQdV7UF`ZF&(`O_eGW7hIR)>|(1(O1hdTiB<YLy!GO}UG`)6+qeFf019{B1o3
zIj-LMjdZ34BKp^ao&N-h)tl{jGBIrdBX3r5iE;z)5zBai`Y16lM;)!Rft`eYKO-u$
zAR3a56F?JJRK(f>YyfO}jaN@dv<63&)1sBGvb8tnfByXZar;xp$lt@y^lcK*K#Os9
zwBmRUo`zJo`*faR6L&>_a|u;Ih8x_sT{5iMdo`H#I~W9+)Qi$@8m>hjXRg#JpgumA
z3~h2)&arjz2ohUraAPCJ#@`-XKSBp501^b73mn%mZc2BBz2NQ#oE!`=_p*%999gp)
z%m~G^QzSg+hQ|ju2>@J%rK_U{_ee@k*6FS?2s~N1;5}Nq;__Wux$*xJA0J;!<b3}=
zfjs2l=t3YKX*c@qF-(O2T2l4{v4s5IAXI^k>-7AB9i<6U1NP<`7uxz{(iO1-z3od>
zEEcx?!YD=Z^f5xl@(~VO7vr%kd7(=_-GRZxjQ!{46E{s>Ptb4qf%*Qwm&}gRo=ixy
z`L&&ZJo8MNt}q+%|98nd{LAo4PVH25Rrt1Zt}@lB7qOCrB<P#1<dwbbi&l`89r2mY
z)*c*LW#shxs@^wIdAhP<vc?x26vUvHUnps#F#k|RA7qV?a$BgiHdz95NR+9N&&f9e
z!{0yB`}cS(`(MrM!MMyhE$!E~`7aO|RAzrSO~)r_nMd~xH|fA(jMa<CmGpOawY9Zw
zMpWxVh#aD%vUPS#ns`=n6_m*MY<#bf7A7Vp&d%R}t{d#@)asL<yUKF{Rs_FXP)Jv#
z-<>;PQ!m~wsTE#~H0={@M3wq%(MsOEd*KL93s#dwlknbEM;7M(9miQ>=8cg;%_x8h
z!w5qOl8ws8ni3KdH8iz=S6r=7qwHOSE7$;X7MEiRd_j<f$La1)Zr*#CN@CvxuiNe%
zF_Y^1y?NenAZJp>YVwSUkJo6{;a{V(P=xD&E@!Z!v8k4uz@RVx-Zb4D{|#-n`}H<c
z3(?R}Q#ZdKrt$GSG4L(Bb$!VRpXzJ*Q9SSU;$@IbEN~qeiF0u&m%ZYr5xQD|jUwY;
z`RYuvro^YMuMNy%ViWQ^Aisx%;2tT1t;+x`k>mMlFvVu?O;3S5@EEes%wjQSWM=5!
z!A1}iIV^wilS_CTp_b@7<55G5b4Nu=7IN|A;-DwW9B^qnb5)lmFlB(8ey?A>!V0Oj
zU3??0b8M*!>}u_6j?17a>2|8!R4HQrPiElB<;>I+yXau)pG-M9aZv{gmfpQsW-Y~B
zy><((n}rIiz-Oy@f0)22#PO9i@1?m!J^Ci}yK}RNiSgXb(ALt-G6M>Gdd3(a`)06h
z`*89mx$cO*Y;!bsvfJ>T@}N|`!;xB=FXmc*l75LTMOPYM!p3%;Q$O2}6p|Vv;_xo*
zCP$A%2IJJ!ss^{6$oek?J9`PJWC0fmR<I~=r&U9)H}}*13yV<rsnL+tLVl-kauEUB
zHZd}?t=`=j=i~JBbl?I8KI6mbIu-x`T%3T^B5<RFb(m7r;_yqAReahDR#uT$FKWS)
z-LKHGew4&*S=(nmIBeY2G>f((g43RP3;NJKt@EfPHZ;*g>Cd0ct`3=)B1ISk8tM9x
zu}s7JWbWLsUD9L1YO2tq0G@-QASZtd3-)c-^SM;M1jhV@20ysdB;~GZLCx0GG-_AZ
z@_B@mT8ZXlX_<PcR_Z9~hK`q40<N0KQ;N)cv}v=F$AOUC7|-Cbc}Pkkv6`dD0-Nq@
zc}9x~g>8qSbbC!D@Tp>HPhnsrlRVz^zl%im{!D(%h6zI*5;JvmbRaA@gn$}9(`#^H
zl~L`)a@cY>GCLwo1fiGF&aB)#0*JdxOsfTmU};?1-Pq*hMmyB4J%SX#TukSpK7fPM
za0_(rYo`R=<`|;Fd4y5@bYr++u*{ea%IAK#!ayN)<L$xaBu+;$Gu(a`NcGut>YZ<v
zI!gFJThM5({8N6%T1a-{%_+0z#JGO5qiT^FpY7N)7f*3|0x~W$v3UU(t*onL6O$Pv
z9D(;Oja^#*Xl)<~Hk!kCY$;BcuAb%#h_i^k)%rMI+Xd)ACP|c|zxYhP%j`+LrvRPZ
zLUVRnJt@!Dkiz_2-BJ5<nvw0V?Q5UE1cZ|dPh?h`gVPr(l}AuSM8w5^I8)+YKwHx#
zA$qTv9zGD{tPxQH3gagjQh!AUyp!3=cjuicB_#vX{qGWNEXF;2)cb&*^a+P09u^HS
zYWGC0_}nGnwVk*c`jdHqKOj4>aeffh1wtb{QGfgc0y;)>2kTF_olY07soN!sb(%W+
z`^A!@E8P~GH+h7Ymmf8Yd;>?T;LmMb>%X>^sZ+YU6-pKx5Au|rN8z#`xa;(O8Oaj&
z+?psR6>>L_m}~`6Ew0;hsxKbuHh2QsC)o1g!-rcu)&hR58JC2VV7XWVK%-nz&BRF|
z3OUV1`|>_1_m8xg7@n90*IhAl1$e$nJMF+tA_o^cJH6jRBUr;yUU^u8qb=t&JTv1B
z^bVKjc5UsMdlf`ZbNoy?s%CF4+s^(t@#L4kkJqUgXJE6HlR4^LK+&wLNsdnqYYJE!
z9+8uKpKN34hQ6jZsbn(m$g$IT=J%1fFOJ)4;zj0yT8VBAs-;yTl(audP+NVuqN_$T
zWCD=&^08lS3JU=^&*j;Fc9J5XEFn>%Mz3Ctj;ScEsmMH<Xr5n(L7CKw(&vIXUkRX=
zOb)<#bZf#6xj)<vPEs6`Rzn+e=eQGUYOU1NUf!p!8)G~!n2-`k9OL=6CdRb}ppO7R
z#D$K$?p_mc*&Zrua=pP7zdv)9uV5GaHkMhNl9)oy<LCS=Ul^r;{lQ!Uz|VjMj#Z~o
z1)gq8eezN!mP(*>ueZYqWYx^XJNirmuEe^q2<*bH25BXz9kTlIE`99gs|)t`xh|XU
zb64h?UFckdLqDfBCGw2>@SE(nJRL=q*Yu?*iINlK)~R!qY3RTmM%USz%SOjcI6W49
zF}X>PC*;VGePs%XoID~Twuhe&PIu?#%508&P}&7*%$XM!egg*39NOc($;sZ{$X=k*
z7@e-Ds!HE3ajKyl9_AQDB|^;Y_EL3`I+GOy*~TKxUdIiY*Z|(F-E~83_bh|F1l>9v
zFC+D0EtYG)ZkN+yQ7jXDvI%p}BG;nC*jP29=e}I5V=#o0f2u;twYM@{0)JE4-R)o`
z8*V<JMo%Q0quaDuV|(2R7~8?r^P1u>8TB5xB!JBYnTcm3=M}l~<mt~@06N$g_l8bB
zIRksOH^yr6R}zkM=SE|d-DFsAIHjmwgRM`q_qnZ3gX7f(^^ARA4!*NUAOTg3ryE&~
z^=zHbR_5i6Bq3E+ERhfNo4AMCCT~ZuWr=KK>ciV@>Mw#`a+DoJ;@#HA_&{zub|D5H
zS26`4KMiByd*!*Yc_-j-@uJBW>e-BxVvXQ(^6p4|WYminyjlNDghuT;#-`*hJ$4C%
zUX;6jAuC?a`~}Pnc}yVMQQ*ZK%*OF7f1)<t?Exb;#>l_pfdKE#`0VL}G@~bH@^Ykn
z3#G2d@k*KW!$af1L)t*%48{cf`}fc1=vQwG+wJk9ZLF*lOzL`GbRw3cC3aL?Tsv3H
z!3F|uyHWv!0E=<TRi>5uedJ+Ld{w{c2C6hCka@+I<qnx&7HqT-Ig+L(S5q83!a^dx
zXH%UGKA~DJGcMagRwr{@=7ZU(7%>Y!(%&sM`tX@gFkjDaz3*2qzKEe$N+x*YMv=yA
zTA*7H8`u>R_mPlFm~$#zh0*6=$rR8CTD+$tMF3wPND>6$CW+)H@Ke1kt_s@$%dO~X
zZ6XjEr58G2rfe;iv_&f9cQf*f_4IV%!N|zSr-y0X3K0nwIzK*~K;K;RMc?l2z+KnY
z)Y?6m*DiA$zrasIlCirluN48(<r+e__h}KIjDKc$*kO7kpe>qT$E360Z^f}gUzx6s
zi2g@G`g5>oVO_fy&X-bW788&Q$qv?YY*;cjs9R2Fc<dzdDC;+90gw>HGK@%Pa#j_B
zhEJT2A3wqx7&W1na*bXn5lsCUX6djX8L3z)aH5i;TUEzD`dwwTMc+4*eQv(nSED~9
zAz$ysU?<9^$<f_5kRa%#FcRw&Nl+zLQJ<t-S^4|J8Plx%OrrZS%v+xD=&-oa<MQWY
zsvfTCKUddFWP`-lq)Gi7mah8(Hx2j(80g`lJ1CgM!8o{9I%@>*5_B(U8DnM$@rfZe
z7(~RxDQx;8K7Hk;y&HYZB-(r|On%Lc7Z6>34hBS$U{!fJt48VXrpr_PCSTR=s(&(d
z*Fga&b$W^$nJ#&(w3=G1l^P4&W9y{#U0@nG>7OwFMvR&__?#%d9<6pM5NYxPk5|sL
zNoV0SpWQ<0D?^>-PW<B-knzbF14%PS#4xF^1*a{l!na`Iy5YaV#b{u<4Q89$Jz_61
zsIzU&jEpR8uI=z7Lv3uVmzI`!ELD3yc8xxDa_nvQrn{w2mSDPO%{3G9TJGr%=?=sP
zKj2MQ7_fDnb%VJpRm2Opd|f=*XN2;^CgoEa8xwO7e}I&RfTCff%vuXRv4-0EIVvsa
z02LhQEwcZ^=4x&xv6xt6x7hJhY<6lYhiZ@l)j$-VqdDPoQV1XAb^>y;<G4D<RijFo
z7*G%9>^hNJzw!R_Bv9usJIh!=&7!+vg|q5<?)yz2V|eU+NfVvjTKt)1=&`eR0gMW3
zG-~k9nF~QS;y^pd`Uy8*t<4~I25>0B94sCe!@j!!uTPI)w)s<EGl9kjKiG*&ztjxL
zKlEE{F<IM{y)M4nt%L>>SHz;<SkG4*Uw;W*{Py+^%!qVHh#9ABYI|%NKkkwO4w<Pr
zN<BC&d>0rNMv>WMX?;*m%pFOhr`PY65djQ(0hB5P;a_Wg)_<kUx?LCR&sH0+1BCTt
z@3^eAbck=E++`Nv$K>SOAVMUfK5D4c-gBYCoK1LSkLJ~jso%xmUXU9+soRM!S+cLB
z+YI5TK<PTB8VP!?;ePIS8_~rzi>PZ1H{#sUJJX*l2c13{=BLHTABRm|ASl+u`#5;9
zT~f5ZHUB?YKzNrzBKcEdz-_qs^i7?eiCo`>HuIYy^TsrjWNAlrKThRYIQd@!5J-l~
z04QU=fB#1YS7uGSzaRdpevs+ds`<UKp=~PXLm)`T*k9C0wDcRD(zfuk>Iy+!`zTK#
zjs%lGn}k9JYLA0P;6x;uytPFV?LxR}(D-Aam7`qAe3i-DzD@07K{IcW=PCZ7{2{kK
zIRE=iKcbTp_C3sM@ah1xLL9SR+kzfh7jk=iy&5%dXPdOP;J28qJIgB*SJdc^;Kb5+
z7-WLF!35hmK){S|FhQzMaLWdDT%UH84eDfP7DStEP889B^b!#Daelal?}7524vvYU
z{iaaiG0kb(8_ST=tPRv*{tcrP-ih{`UN9a@AN2&uu7?y9EJXL93K5sVxwmGrH%1jW
zMhg_vg@ip%H~#pY+Lnl1tCwgd3AA`#ot1&HGAO90O+2JP4W?80K7u=`=IDg?!PD;F
z{rz&I>gCY)@oE0;!_6O+tbEl#hU0f9V6S>yy6z1by0M(Vf(j&~Q2B$Vt-u%;OL%o!
z!J&;?-D<-o9LXm1tXMq^?q*cHb?fjJQ?o|J;TA<=$W+7uk+DU;cp+ih7#>EJKUx_}
zSMR(UoREM3V~BIXD@6CoVp-{Fc>29eOVv|ws1)%zlzmV0BT*?+!h4dO^}=46RUIUv
z%#%vP4$iLvj@BwICjS8X@&Y5od3(wikUM%TT6=S=%Gu=&<|zX8p1DFZmz1&eO5Sr*
z!?HO*3fKQW*C&7r_0g7tAsce8t8Ft^sp)lWRFs&Y$uCo+reA9xgj1C0m-;&g3L}EN
zT-8UAspo5yy{#*E+g*r)WM2dn(>Dn?8~Aza=**r_+{J(Dxp}5EFN2glr#N2BRVOqz
zr=uMOkA+KA+l`=fFVskgb)gezUj3?0OgKYK%NG?cld@eIFyV$x`S*BJV}*QjnKeIn
z{Z5P)=`PSqHn-OffL!(jfA6X%%W7i(-peM+C@N9FHEOt;(YRb=s$4@?l}9t>rP_w^
zT0jGI#y#swfA)@<1n4dz1)4GpK<j8tf5~Kart9!2MT6Vr#cu9f&@Tx$w^~c%cPdaj
z)qwkEwyG~HvkpAE@iX<LUB&4Fasy?<j>DHkX>zHYx~wSgdCiXKs#rbm!6Lk%%*^L6
zU)3}>#?d?#wryKs80DM}@^2DOx%&B8jCPd1Tr<vbOjp3|m+a*^?qeT3d=|}eF|hbK
z^WZ0OXDUA?vvQx$d%@9!WsVqSf;L;%355}K1QQ<@DhtxkI0AOH-V;*dj9U=+C4h4=
z6M(`*Els{hv@WaFJA#3DWKYS+`n<!zse+v$?j8D+iwadYZS8isPj_W1$9P|0{6V(e
z5WMU@mMl|PaA2|Y*^{D8J%#Au>M9vrMv^rO_;a#yf!2cZ(nzwsk>}@im*xG=uc|{W
zl+1rg`%N>aWl`c+G8w|y@o|64oNYV=-{v3tS0KI$sPdE}v(vh`O{VV6w@Fy2_1z$P
zW0<rX-OB)D@ippaaWNJP3%rRQYAKh*y|A;~V6jz=L)-_HozWNBXJ=<h#+B;#cx~oh
zU4OwkT&Lo&?v6BN@;pYsoi0i88CEv6>YWji;Z%zUrwa3`;i*mU+S_Vur{lYn1jS|C
zstk;l);rq7Xd-~<a8SQ-Zn>f6-KA@Nudaxfe2T#Qb5lc@EF<(M3;hQ1>X(GN7e_#8
zczqW?qGz?q)42p%H^MhtqEY1;z9+)PHG1x3zQrUHOYZ<i^aq)pMY>IIUtBEV*Y7R(
z0FqK$Tbpd#rY8dnJUPmNs*LKz>XT8!3yO|Qs&Ff(HJ1JPCS_3y<}+RU^<Ck7^&$Z_
z)7<1}9ykpRs>#qOX@Vu3LX_iucWGuI0nVM7BAVx-!-@zz^UAGnjqV4ZQv0G=2f)vE
z#kY!ku*-aDgy=kP8bG9@Mn<B6G1Jtndet$0ei>z>2`3kINdvJW!(V)yFW_+e22bD9
zw+R^2lxWRva-MZUxi28+$T;#1{V%{6uUl*1Q}sh;E0%@+t7aJp=7kz9cZSC6`yVFq
z7HR#uGAD>x?@x`PZMN7PKip|>3nbWPT2h<(y|&sL3xtQ?dX!O{!v%IdkuPyp`npyR
zR3I-YIx0S_1GzO|EsE8Of?I98ocB&P4x&KlN}*nb?NG~&3YWvxlirFicx0NB74qqC
zXULwXin`qlN73!fcx;U@L4lI2HykKO_VlKk-qtztSWRd&Tf^Kg<%t$`8hkS~hBJT=
zT8Z7n%yOnmCTC6J8uhwY$mgPea8JM`el0tSP66)yG>-`s5PbRk`A(Ck9K&GVgZ2hj
zM6~aDk*3qy{j(WdOoR}?ym9bw037MU@SD@_7jy8=jm^m^vbMGsa6emPHm`GsXCy9J
z6O4X-C)~rt^k-&auCZA#u+IZUS?A>)6oPJ-UTdP+keJGv3LxTrKbQ9hkQTEp8!9Dw
z!olrE#zwAt2ia08eh&)^EA0j{GmXt|xU}2ZA9aQ?=ogb;f1?oc&e9DGtFjyiFm+tX
z8HoD`C+AN-mq!X`tdsKO{|)l}cOHG-x$GDKD(wSN(LQ{^ylTaIPUCw5+57|qCm?-n
zbFxOk+Ir4EkdQ%jy4+{I1h-UbXQqn2rMxet!Q^16|I}){T>MX4z+f`}mfzk&(_KO!
zbR)(Q2ZE0L7^WJF`QG+SPYI_)ccFzbhN!FSy^*rX0`<uv`*fff*#krBQEU;&k%^%Y
zHnX#f6SZ6LGrOM8?|`39CUN^V>g1pgI3aOt3~R<vlEE2ZumONzvCc8b{3%y__I{?4
zBU>hnfIv29{BVD&%;|KkNPG0IhC-@Hc3`o!rRC;^fx<^Ekg{aag54kh^h?FBr(;2y
z>Yuj(n;xFk7Nc79S4MSApkkG$KuxdNaTP#&AaBkKxniNC!)ybswND49U)SBSi00?A
z*m;Akn3rrCl_tpegZgu;qxE0Kip_H%1Q@_%Ohh<GuhuLSOLjlpx<*DMgof_)KlQU&
zsGm0<)Wd1)41X&3W(uJ30<Q!V2Rh|u<bxkG)te08hA1WMz2TS!dnp=T^40Z_YG;jO
z34FI`GB<$s<A0-+@fSS9_`soDz>{xX_V$C{kBqL!EbbV$xUccs8=av^J{N@Bb7k!-
z(vRYkgQ4-*p-HqaUZABT@VP0DyNA=uGPmBNe0>55Df+Ko0Ogo2tJ{B+V`!Sq`0<&*
z&jB9&#KcDVgo~l~=jj^<6ckS}y4(JDEERei!|-K-sZ_g9I|8Dw%vgeh|4Cr`Q$91`
z9@eY##K%mKplY<4Zyp^PDPKP=eDxPi?<7DIt5<3uZUzUC{*?~Tua_42)c|)8Ld*n6
zmJ6Vsz~(duVEEo5JndkT2p4zm(?8%dKf8+_d@<nuT19|pbA^=?gBU3gEo0of5`@Rz
zzlOhssMGEG^)Tr3M>~(l<c%JE6DK>3AfBV|H7zK!^}ZJ>B}Mf27MCDkqQd;}Aml$r
z;ccf`_U~0?)7!*-v0!#_;;MKXpyScFU0OfnXKrEPu#4;oPfv#?sJ!S+l}Wu8lMa$5
zn<!$?tyj6w=J@mmC;Kg96jL+={qb75|6Egnk4FnQIF}NYGL5nf)JqTuXuSR@ASA*1
zCkVJpA+ciG`bG+pFn^`g7z{_6)?XHX{@j?$c1#$g((BzfpzVg-LEPb#C@|@H=v@5y
z_AT_$H-ts6jDN$$-b@RURZcgk=UbuK5~AKW2_&zfk3ZVQ7SHrvDOpx|p4DoqymCEU
z3L1?Y<vZ&Q;(T>uXl%~u*9JVdE&=JrH)hY6TG6dN?6kQGX+Aeg;$d1CBAStnKI^Q2
zDt^%Z#r{=tcem8V$VglH2N_>a)#KHbMDS1N{mx2XH(!CpaY$W4LPE&%@G}k=t--;;
z<g{29P2!y8E4}kFEnjW;O{jqR2@*r!cEv9~k2B)mL)w_=PFgsKL${d(Y?9NslXFbb
zIfuakqffda=(G3-j;EaNibl}eM|7VX{ot<iU#2U{f0{cGGsWtcSxavwuB@!gH+wy1
z(}S!6q%Mn~REzsG<1R6yD(n~dk6#DBWU6_!TIP4nYl0kF0I7HSwT@g2(*1uNXSnU8
zjzJyFi6ykA)anK_>WX?%Mt_etv9cL&wo!f*!48b7y3LZntal{9&zryg$Ln{NEGr)m
zF^?UT&u1C5?9Mfzeok~IdQR+|{zUYF9PN}@zQGkKy{7y8zMB~mnGQ@Vj=Lkr*+;Zg
zLY`_b9`Y9JM^&f5P2M$3$boDSgp;}?-tNJ1@vbONt;1F`q$m<%0^;J!YAWQM<i{)r
zY8j3!$L;-&Y2ybB`3kq*)M=P~kz96gtekXl++GpqO`5M%+W980GGH0QYrB}MRsf8f
z!9=VYxn`y_kYdHcg;FLF>fyQmO0V?^WZ_om!|e91L2=(;c?g7cY3(iD^l!H#i`PFE
zLmS5Ed}b#9^&4|<U!5nvZKqjr4DjmU<jGg-mQ~kw-32*kx)lzmEg~sj!p@U83zu_Q
z#l^d5WnO^pjcgeb5Iq$BEf|#DZq1~>OdFIzQ79~$n>G7m9SUY6HroT)EoI*UNz2c=
zkV!K+3Wk67c}UHA7eg3ytE$S394XO?I0M;y^@6r5>cLd3WDzIckUJU{V&dYbWUuJy
zH&pA&O{s*u(IjI_jp9fvdtp%KUEpV%^&to+n~oa^1ULE#g@Cy9_hPxB0=Jt}%B^N_
zAGUQc@d;b0W-Eed{bse;HBfotL3WjHyOU3}rATU2deBp$ZYE1gON4VmDFoZ92=>xk
zjeC>_7m37_lm|Z9JjGV;Q%aH1BD($dyW+<2z`!gnMa0t4MVCcbI%Q2_YG?`}KDJzX
ziWG21{TY2Ed5T)w*Ye__*U4)EU$wHEcqo^UQi;EnTFHuDI=8q?lo@lrQqk=y!tk#d
zKC8b>E6h<rOulZQ*C}%=@Do3dExmlkVa96G#*5MB5j<_inBivHZ@YFDhQ6n*%8QtE
z?+xmI+DoB|iSA!>`SD<BBp`ynJSMr3o?JU(Saqbg&mv&xOce1tPkw4lucO`UD)`b<
zhk$Ottx+>m00C!6I48(K{b5l1c|6c?8r4NmURM3>>zQ*OiW)0~&3|EPwR#`{L5v>c
zFrG!(&eisqsD{Kc`+%J$2Y>5OKycD(DjsmIAMA`cq8|*Q{LcQ7c-l1++5jt@cn@xw
zV>vzSrfVYN3il2(#*nC&MC6|v39Bl(a}~c>lJez=4+3ku*;ssihB>4pkG4;V<v&<J
zXVG^VcM~FFyez_};h&en!qXp|AFZY*0td!T-y79`z17^2IIEDg!6dp&5pXG%X({Aw
z&qYkl+_7+8Da%E)vBCt;dxJ8>I`_Vyt^)^?$#=#r<s8dT^!h>63VqW^YF-;_%{A(p
zn{|I&TOi@%8#@>|#iLW!72}JsAPFNIQ)vWoOh{eb?u?U|dPzg!NZXuja(PI<vnkq=
z?8(c;MSMS?9%g8kL(6R)TtDL7HENgCvuAKYmAWL3qogLj9&AZ}f4*#;9ZQ4AQMCk`
z+5`J{1w%~L%>ub0<w8T|WjVwpe5oTuA%WZQ_isZbB_$|qY;KM@JaaierjLSx{K<}E
z`bhq`mB4CGh2?7bgXfZP)V>mJR6=|_k+Z{escltV-AU*#px-<u;{mEFAZ>CH2G(e(
zX;s?Y3*Ba^wCM4|YY(2lrR?63qd)$a^Ei(MT(^G$N<>#jN1j|58N-2=zfWxQ4|8x-
zS}7|(0(%bD(ONX4DyJ$Yod4)?XJ=<{htbE^2BxOd<>E)Jn0HGxm}#AQV_AhA&)5YU
z=772pC~z=L2m&*kik^lKW^VlaouMv7S)-G%WTVYHG6@d4aY}XwGPviXwyT<mtke?Y
zecDD+iKw1psU#BosL05@IWIA475{pk%`tAFGTqGKERRQ#34gLFBsy#GL|hLuWPHu%
z7fN*CQNE`z_|k#9o?Lz`gJyIOP;{$UjiuF?aqFc1`2mv6d~_2>BX0z6T=c=cy|+0q
zd&=OnSebk{HCp^!w4>4YvRS!dO;$dj;UAz7dSJ}4ot2g4@Q79w2K6|P6yKUGWYn!6
z1L(8UI_ufo>yV((kgZ9-@44nFG3c^_>RPb_BcQ!|Dq`8sxBh2q$lQ}iiI`=HmgrvI
z>+q}dL(T-JgTvK7nGy~jjSNwAw)2gKV_zQtM-Dh;-Me=tG~f%sWNds2TT7Y?^EKoE
z+2lalWq4H;2wL8nDAXP_(YicYh}Hvf5E%Q{;GPBC+NZ@psAfaw=&IkkP6M%{#}zWb
z_U4xjN^(%Y+11hUYfw<g6_Ff|Ih&3b=|A0OWzmc=t)1W=&nuIqHHYS)u3DrvZ17Z@
z{iq~(F07De-g?l;c<H(lefP6mSyyq)*$UL>prGywwQ)5)`~_^k?)Oi?JEyOoQngcT
zJNbFJdu;o^tK?zxZ+_KMlAL$;`KM0x%q5$s*9`=A=FMaJUL#ARP}pVft;lB12LzGh
zfZx#x=Db(+bGlz$9ZxlIdHh6jLCMopbX+Rd9R#gxc3eU+y)iT!kCSV}uWPiXXT@zl
zNq0O?%i(k(GaFKiX#1IrmUy&$J*d@5|8R2|j*4D2V4eU++>6sKLGKL%UGacmVoR?H
zxXY#MCLtkk%V<@-7qRYM=XJ51EY@n8DAESmr=BXs*3)*opG9sQ9UT4~oL34mZftE$
z95pH;xWoG{d#h#QSaTx^b*pIfA#18-Z?O_&dEIV4vCLMp#q-foQxCiCiHM}Z9XmMh
zUJlBn)vM>LRLD2Q6ijg2P4ol(&#f~h*E(y24Qo=$G|U?Vga1)e()L2#aqDyQjTB5%
zCZGD6QTPh9rOpih6kppr2J$kg{pnP0lob6Br1|;Gj%%IGxscxc%s7pRc#43V%jtqK
z$T7&ao2z|Oq`KvXbLTc0nT&24;;{qjLQ1RV{YJ%J{A>E|EhPU03~=PZRe~=bGQ{-_
z9HFvD;nT!ETD0o)X8oGBhK8xh%!t{{rdE8!WM@(h^*XCwCVRGA$d^TOy(E%Q`Q&D?
zJy&{4h;Vzi*o*!RvGLPF`G^Tvh59@WF}+&lP>#*z2J@<u>zvoV$y=ky*DZS^=>g4D
zgNdqOORaM6SThN#lrntG#1w)w&Vk>ncYR-H+T}YF>t4gznEckPzPzd|L!N|nF-!mM
z4$}zA{fTvK0$3M|+n~C=y;(Xp((8e~o$=(~VtNSEK%M|CFth*##qv5;-bUFA2Dw#W
zXu)odUVGS<&tpmV@}*uA$VcqeTI?(UkEh+j+<t?RsVPHDPrlme4+RlIiYfJ<MWxLH
zUx$r<r3#C>9R3WWnDIM$_*PqcCm3%>(B(dkr^_OWB+3G;u2n)?0PQo}S_{4CeNlEc
z($N<H7DSe%leL{$vjOcY%ju=G1TLuERHk|w7`5YAG*v**<o?%tgP!<ua&mUMaEQ_j
zkdD_MZ|eetAhF?}&CdY=U>mG8Y`+M3+^>ML%w`<d)zv-Sp83@h#~2o!1=Hkc>94>G
z=kNu_h?Xg=W&#JNfw&ynlBjoP)w;g)p5Bs@Yk`WNhi3}jyou}oRd<6wW_jFwzanlR
zt?ddJL-siKaj)X`en**q1kn?uyrpDOJN-xZ$tHSvxmY-C!2bJ9n^ik$3_+YeIIy9~
z8i%GNE{w9Fr@=AwEuH{~K4O}0a!V7T@7>x?t{>?i8|y286_fAF3P#OkN>p)^0iRIH
z?LvKFA+YMOcbhLBOij73_ji~`FbdGxg5(VgMlyFb^YZF%Us8Hjr<A>}klA3+Yy!cm
z@n1jphtD+nz{MD4bd?+5rwi~faiIpjurvoPt$Z_!T_s1mL0W1L&Jq%7(cy;|GFDbQ
zHby@m-algM5bGMMkc$2zTW>yy3B@*!%F(O&p=xc-jLw6A>q_pK$xgJJRroC-nY76Y
zTCW9iO9q!lOE^hS2<dgp?+M4J<*V0J>w6pr!U3sYZH|sN!dUsoVmCKaN|Pgc@VW|q
zH-L6#0|JAZjeY1F&9UQzamzKm;MYVkwh)Gd%7CbGa0nz>%Rz5nA2`}U&Rxq_@vcs|
z=cUM!G9KnWOPPayznSObtFY9a9k|9R_i_FAo*q#{N42tynM>}#0CAJCmhtRoKtCy!
zce>J}?CEM>YL0P(833h@=^=)I*eGz0T|saAufzT!LUzo5Wz(yd9Sp#IY*cAwcHcP$
zIt{lX`79|0G;tv68sv0>3K@vh*{R3?)w_1fNgH<SGkQk#qI}&)t-zZT@HXA<SzI5R
z{;_do2rZE*cz5vn`?2p3DY0mktJKieOJvr$%%bKS3>xO@Ks=xf4=?Y8JcCRlm8dJU
zXkuZE^Y?j3P!uh&_&7M3l39@@$etiIKQynI8VrGhhTG0U)UfZgwQGf$+@ps}U2^f{
zPtSuajf{+G<r5!1eF_UHcATCeVN>G<@a}oAYHzd!XSB)r*)Cv_3xHf0NGSix^f3Mk
zioQSE$NB`Ab{@O&9N=qmtOL4^nz!lp9px|A*4AVp{oGES-}HPgZn)fbt5XEC9$HxI
z%>Dj|DW4`B_5J$~c=6C^#Y9YjIxr7eo5y)=t^}pJY~E?c)2T8m3JH+`b`s8+<FAJA
z-hO)bOSks7COjPgs&<Q5$`TWm7MWnEN2n46RybX%Z90v{7J&qK5Zf3Q6a-A~t6HVM
zGtQk5!0+CxmM7MgjXFdkDv(1lZq~Cp>E0fH5r~#}G{S*l94V@=7o(MpD*viY{qfmO
zQP|Pr?vjc3?u~w<Q~^37zT5GRrhT?^jjGT7aelv8Y`3Qu7KU0NYk;gm*5%WX)61aw
z1=Gr^AZ%yW15~3txri9Z`3G?{vbSI}v+sT->~#YDE&k@oxQ2!n5sTJOhH&N1<#7p>
zzF1cDSq*$K4E2oq%~yF3-T|3Prrm3$nTU6HZRhHJ4uAH1|4wMy8*Mw2rIZa|cYJpp
z${lg~e{%Fbi-gkHiW5NsTI0mp@b*65L*FU}%>N!i69m`O#`MAIgu^FE{AfKJHmv((
z3OJEG*`L}w_HvmayT^FA%w-iu(Oz=T4LF*^rj(_1_u$FyQYTd@fF@94>z7wm@z)N<
zoipmErJ$c65WxFylo|TZAl1A5Z{_duBaj8MGR48jZ9DaSaNV!z00=ACZtE+)fhnT(
zO5bCK_K+Vwth)$rq0>Tg^)k_69vBAq04~f9$Q5;ZAT>Bsc)IcmDetzF1^afw*_pVA
zS6Zxhq+RaJkI5gd%c@NfIAB%*?z`^%V%>&={R3m1QXQNXNl&bO;<Exmp!W@^gC)R%
zK>ip8=QE;vlygn(CeMkP)b6<-?l<rvW*Z)ZxHZ7UzZ4KKn+{fe%&HgLw+h(f6o4uL
zizcX2dD*81#8)qAX;n+qOs9rgtx2pvSOVIHAtlAE_0t9<A%lce|1V+mni*$5Ze8c4
z2{&K<UuoUab<%zRmDYXD<MJ@Pt3abp;?!1mSJeFp;FXr32Ec=MYfxWt9TEeji2&i_
zilUfXE$PpJX7s`P1K?Ux&vAx<RP42)Mo9vy%?3AMjLz3czxwQu83QrBC<Dbbo)g<1
zeAlemA{wMg6;V;ZFv3mA8uyNcNwv_xUUCct>dgXZ{xrC?svzcbT!1V$?<K`#u&ULI
zhu}Nf99n3Q>8vrpJ`*qfPfzj6D_{iHZ}j$9TZ!0GXH&EVqIg185bQb%)LSEY&+nc>
zS3tez&dhPrr0v{~L?EmjKQ46I-;ekvu;NgM?#`+<ZU5NRz;OG&!ZU(EyvcjAeUIpO
zHq*5ybBJXlhr@dOB#_l>y*r)-9L!)#9Y1xt3`4bb$nX_w`<#8So1G}aCZu@tfGoT(
zBqU_r{#9-m6_B)yud&RgiuxJaTdU5^tFvk+`&t8CNs)F%oB8?#jjb*C@&?{Z>QL?l
zr|B>13Fnmql@aI%NRI{9yrv7FiL2pDiDiiDR7e)uIo{&KYuO7xkG;PIzjiEvz8Y7=
zM1>;{p{HK8(JGMdqHp&nNrvyRcaNtn%*;C1kNRR*(2B?ykgN|{ETWI|RPz5{5flrh
z)czn(q{B$HP;sGm1XOj9u&!v;Ilg@K=n?2P0m<p$H0x}W$YUWp82!$J$7;#%G_}<?
zj8b$M;GcB4LMkV=vjWo0IaeV9xzttrmYrF1>92s_j-#v$y9=#5(`UV&VpO3wj}zpJ
zk%^|4m^EvBj`le}d>Ncu$xKN`R-i~<taHG$qE!lN5LGm@%e~~nNhj^*OfY=e{yGs8
zh$$$PVUS~RlPvh{KjYwtNS!QN)Tnur37C6!3{3@VowmTCub;&@!1ji?Bjm?n{WBgY
zlKCIgH#!~*R7t#xd3Tr4db-W3uR29MIPNL?dkrHa=s4r96Dq-Dd18l=XOr7zA+h=b
zl6Dcmz`%at76Bp2)Ia=mn^U*-r<mAYQ~c`7|6l<x@&3<jh_|17nRGw48!D$Q^6)+a
zc?&kv<h^ap<(Vp8e}*a`MI>}|%GKg@kkcO@*o0^zZ=E%PCGRhU>vw$O^E3Ae_V4xS
zN>i)JU2L^)88x2u7eK9yhPx4&mq;Pcm3!IH>3liCAh9+K6OR7^Y)29}ZNB*XU#}kJ
ziZ<eo6q$8oiSYt#e-V@g_@I(NrhZ30kIHndl79#8+5+6E3Gi6JD3VFan^Yuyzwusx
zV8Wus|7303+1lEch8Bg&S@+^Gy!8qS4s$K78O&=(8uvB!?{)uTb&KiUb<RNk4Pn55
zKL$%7@O+4Umb}x11JS2KZXP%Mb_3fw=H)5KKgo0}M$XkKOMZO)Jvo{D(Icx;zB(Nd
zXCQyEnt+~Pb%X$GX9DMONoH4g!T5{<I2ld@%~NMsTCLIeX57awuB1pXHVK24In7dg
z4xbsAY>b$qiG(mAg-CEOa8*3z^L@xO1i!fI0Elz7T<YQEBI?R%f5<T4Z7X;VUNipR
zLE6fzKuAhR#V>({i|ZsQdH3Rl!PZF%k&6<3Tpx={-j7{32O#Ns`*uP3qi;HBMiV>|
zoNw5B*2MQiq2pJw@SYxwCNl+CRQgt6v)nc#8)rSrKm(X{2wVy*Ed4-B&o!0QS_bkZ
zKqkY7p3nVzd9jkAz??MC6An$V9-F$qw`hF9e`Q;XOARhCr<RD`erbdH!aK5S8Nn3r
z_6@7Hw&&eKXaSzBcqp4rqZkzkS1PmGy~6S!rvPpz20I{jYpZ04nyub@LO}tHJswLd
z43P316i=00L2Ny~MU=<UW8gvh7Rl))*Z_DrFg30ZB)OfBbO8Ar7sFmW%$#w1-p`<O
zvEsb};F5uP^he@3F3HYRRTAk+uc=JW4CQ#UI4D!ltZQ^eK+y|I))T-Ye^pwh&j!qd
zGM&N`5zB2>sztz-e4`MZ?s8iM^d%D4ZFcRLoWOh&nJ}R31$5BLCzTHKmNOF#as_}u
zblaO&Z-1Y!TD0W0BSGt?l^xum&SX~wF*P@zEKyL%hv^krmNa9ssvl2nRVYt(W=b5h
zrU-btZ5!E|kx)LUGh2oB=Hi`9EHubnl+D*W(Ov7_!|%Nc+j!RiunPI48@{9gV8wD^
z(O|dJGspgYYJ^x9zK!uDWn=1WBi{W{L^sHyH(t5IBo>Z+kqv8X5c}C;$LIB{5!`%>
z^}BHion>Vl<5r%~KVKG!L9~j$4J4+>z}Uvd%(mIHW8~`mi0;J;wCDpUv@Ah8Bf~bY
z(U~Gn9f%4SF&v2oBIAo2)PU8V?=@KS<^dc9&ygp&cL#atxp?F6v^LNe$F``KHh=q;
zC_jIl(W>QGx&5EFHd;0L+q<AdeRCyx9fZcTON6m1HNNUF><A`_ka{8LwgZ;+n5wFA
z*s>%7pB@vTLY{DfGenHpFVwgH<oV;L#4Pf$Gcy`9TG~LO@c+&e=hT!?4Hx(~C*d|m
z%Ks+=_6-puV7Ed#jE?ta=`xYQ(wdz-v|v-o2mn~mjLbu3P__jLsGX_>KQ>~`iRaYP
z3@qTsM*G0*UsYWV8bXMGiXx@*$W}Su1oq>HI^fC?md-3mytZ>iGUgZ2@gsm<<F#Ef
zsnQa*11;8i91M?XkvpRez^n{(wUeCJ=jg*0#_L#gMka=1eO}%MfCM+G096e5rJUmF
zT91%c{L|f8(2|hzutNrqig#tJ!M-;t*WOV5I_{T8Wg0eUhv0P~(<URkhU^21KB&V8
z6oX*h_TA)FWoj5bx@LP^y}zHA&IX2dU?cVNYPii{n1J5#5a$<ia|fj83;6aB9rJ*3
z_TXrZZLZl#9oUY61Mb?)IHKpVy1!%XjHdd;gc^)#nmp{L{>JNcZ`A3g(PI?33>^xP
zmY##E=cHbVBVwSiENs<$FLuO6Y!aaQK8VtAZ9#9nmiRkr$;W{xkCv#w3pRKicC1#>
z?nu#kyJWbh^Ok_)Pj=u(^bWakgxjfY-ht!hm@mYQmV8xwVN!X@8l6+T;(*f4m(Ct3
zeracB87u17jGPyEW#azG7Jcy_3h}_O^`F#1p{rax-?Y!4KZDRTplSnh=lh@w5Cyq+
ztUopNeoyB6KWX1{L}+Pahgq#&_P>8enbu`iflJI-YdlMW?I_fsQ%z2AEp`=|21UR1
z;(fnkbnrGi9}gFg5^M~w#g3XJWY%RHNaM>L&mRr~1%ZB!<7zMRYWw_%`xt0uGS;uK
z4$UipRcPg)Rv`^bDhnFH-k$u|M%_~TxATV`k|rWP{0^qFX~j(%S`0#<a*MwO2j@W6
z%r(j!j{^y*fZ1hVW|RqxI13;VV7}hv($wI4b7WY6<tuXe>v|WinW471xhjJ<39_z7
z6GdakB3|BJ$j$2|(`V@E7Q^84-;v?~M7aTUWqA2GspbL_B$iQtM;I=pi_nBqt3q?4
zdVbN#k=xndDg@e7yT!V`v3>xdop*%9Sx|z|w|)g4``4nq`4@ywkf7A@`}gl4gbgfZ
z>+N0P^9`U7s#Z}#8?dhUTa&=(aPWwhg5Q<-MF;4dF&|8!dV=g6X-ft;2tY61{%r_;
zru^yM+YNpW>edFIE@a8CME*>dK9c^y(R3d{<wv7nopj!v0AC6;9=KsHk-I#WKTAvO
z-rJZq8PBe@zWbt(dKjlwlp__=w<@seFjL{x5EDa;$uDiK^GSuaqMW;io$v4L{q5=B
zA!WGiV3^~8mL|f-mJHkRA;jrdiik88K*ld15mH$Nl{Gaox*kA9#(3|}?KL=XwB#52
z`4<*4b9n|~w=5q)Co8RHbCmoq*4Fg<1GTD*5}@g_y34EMmA?L-fI)VwOYT|*cCLS}
z3qVl>A2`BoaeFZ<HJ(k6(t%W}ymzeOOuvsn9s_-k(X&7$dSYmTPP)op%YejR3jN7T
zaB#G+1O`W1CO<qZ3DF7Fiz1Lxvk{Rq!s@n*oW;SqZHPTQJ4qNixIQ~OjYgk=k>s|>
zH}GiveSKiY|7*Gfe|gq*-<zThWIX;^OAJ3BMF05c*Xyt&<(mxb4~y7w09pU{^*Z(o
zda?QURnGly%mw;y-?I%tRnvb@cNiaT0Wg&x<e3c^q5s7<^8eFdm0%4?H*yD6X}%2E
zy{}*5CV+|)kf!<RZzAa()~*)6@6VUZZFui~ckvFM%qm%Ni1>S9Ce&yEs{BrIdV-oE
z2Z&wvEi2W)l;)rnMPH-|1NwG(CiBlBzRDNi4?R0>TgFpKyjR|iS2$IB2PSJ~YGG?=
z+l#)UCtPT6-*XZQGSueI<yQrcZwD3Z9Q%`pN2lOTe#hZny#Gy=80z8b9-gJhn8jK5
z7KUzE0G|Y;p<|fb$3|&2U*g;%X<>8Y>uzD(byd^&TfzJc7frH%VE));m`}W%4ZC_$
zq(tvPOx?mJhWe=&n0u|RmQ7D+1>R#t_HIev+=ZA8{F$Ne$9OS(7ZH0?5E#Bl2o|N+
zYQxo@GcKho5VK`XolDGpT$_fx=-f-mi3}WovZB|nJLq4=gm_on9l_+L13k$fB;L2@
zdDJqPJN({NkMsKjb^6bIQs9TzSIn~<MXXp25=9(ra$?otdL}(CMG2vJd8L<y1$R5V
zO!?Ipt`^n^Cbqvz9nVDdfZ_tjfE+`tR(CsPWooNIVnii{wDD|Wv1rU(eWJY>(`a_!
z&vnY~j7MYHy6(7_@w3_$fbc!6&H}9gkQg&-ZQu#^CHnhC5y#RpI~mUWfE1fl>ne_<
zP2*u)sUQa}x3Ekjxow(a7-ok_?Y@KG6izJJu};;ye!{uP*$bte1Wo3JeinPGu(*aF
z@=tGy9^>d<A7(CHPiCcT-Mh=plRjrT{lMmBT7l1c^&geP?${ibg8Sxs(ld_oBk8g4
z)!dHU9^_-){rT-AQH;SxDoweV(#Qi*_U+aOs(@1vMy`pKG*I}&B(>T1`l+b~Gf0<A
zV`luQ>C)DMEbwTOop$%TgYg~nYc?rN=jhNsa?tcdzFcqYbg{-Tl<9u`_@jX>(>JSp
zhBNvk^P9o+>zk8PSzf{qe9oEA78jo#_u&GqBS~K$zn8ultI@F)^I<-7o^E0q=T`86
zSI!S!khQMD_A6<O5<G{#<YwKNz|$Xt<3w(wVaQ>zoKJ0K>eYGQCGGH5iyxi3<wZ$k
zPDu@~u`25)H%UNEv`tl;ak<g4h`dmve~SBPVo`S>QRU%=UT>WCrP7zLB~1fioU1uQ
zdzmVi*IC!G3`7hy#i}rrPmS8E!F621N0B^?Jj)Yw5ENA7n*g<DgYfa7iT$JnM)!+G
zakLMT=AmUFH@STEg~Ie%HSP0>kWrN{-bS>0-v{?v&C9+U-nvo;1Jb5E|8)h#&eME!
z+Zpxd@BWuG(CNpAfq_TA*+0$m3(9EzYaxzB=ow`N$8g2B7K1*qAT!{PG1orHKIdJd
zaZPxm1k)cMoE`WdRdVGJ+{CK2ntiyLoG72sVDSEV7Ko^qq{hI;cuxBe2c&}!$coGI
zLgD0as3E4`YkkkcRKM3Bt4c9$o?l2-o|P`OJ$Jc?gEZK0#jK(;*ty&X!?x;P-7GL+
zb;t&!ywa~T4}%n4A5;IX_#~3AM)eriUG{zDg@@G4))3J5(r<cR$ZPxkPDK88fdzel
zX~|wDnGPJRRGh9dg?)XBai;Wl`AOy%?zis8Zw#1m)8#Sp|0XhRjPW~AY9+BO$y7ug
z-y6f$rc-O=u}l=eub+Vm5V{vu^zEc|tklvOn*7~wyZPoudZWi1(l=D|@&`xUN#2=8
z?Q0wd8~0cw9@`b_Zdi6G9Srf@r^-~VA1`kd{tT3}sn|?icJkJ`x>7urJeU}w9|8om
zZ+%b#DlkS>Uhl{DH|a)a^)LL{_@_B>z3$`im)rAGzg`<AOXd5Mcz<@q?l~U(NONko
z(m`A#Y6l%m#P0h4pAU^r0n=1!DsOziB8%6I<VZx+zUCcOe-QIQ;TZ<!O93S=uab;*
zZ%qlr_;0fe>jb@y|5020BxV9jlmW8zt03su`R`dGN@$L#?>|_;4$|hu*RRUwIuTF3
zk2h>U&P}XAxOHn^5*f%NesaR0)wJ?;2}HdQj9Tj}v**FS_k;leR0R-YG3Wv7-=yR3
zE^?N3MvO)_LM#J$t>fmK1%oDLZ)wBv3m{7J)RJm{gsdNX@$!+)OW;2{B4U)Y&!S~l
zxfW1y5>z~<hD5!%?xYpoyf0bZug3QYyeUR^EP4+#(X}Sw%Bbts>DF_6b<Q-fp@3{r
zyvU@8V#a75{7RCsfRCj?jTYoR+iF*(178!!^+Q_FYw!>C&)}gtu+J=*<upSs6OV0P
zm@J$91#3Go{0MGgJozY)?Qu6Zo-hA9{^JDfv+K>cWvW!8;ZmXSzdP^qkLW${n}5nn
zFD0tciE%8aQ(E|abq>HE>umEI&jwq@h&iM8aRU>yFTN#Sg{@QgB(4JiFY0Y@91yET
z-hZYnd#7*&tF|jglQPZrBNALDr}07Xz?%|(u2CpWjIhVaVbZ{Dy+$pdAc<NP_P)|#
zRrhWR)hePCv5jqw)4S8GS#Qa7w1w#6ckW-rTfsxS{tdhj*UWaF7_%y~55A4Il84yc
zp?`wGo&|ZZ+hUdhJ?FozCy(dtp_8ikzsP&*sH(ob{})A3LGddcf`ZZ|-64{j?(UM7
zO*e{wbazQ?y1PTVr8}ggyYtSC=X;)Wp65KjG43CC+&jiye>g-pi@g_X&Nb)f^M1cy
z-&d{n-JT;X)CS^BQH9gYKXiA%`%6AY;038#)u(fzlrQJ!S9v#%!EOmuSdx0ctBj8a
z77wJvDeaJ!U&}vlBc3>jJ1XsXrx>DD3sD+{8Q^(^$&imyJ~JG@!99J&jpFzU;^pFa
z7(plZ<umW+mZ3cdYC>VoO-QGaz|~7`nL$9cY|$yTN)|*w_z;yhvl!8Fb37d~_`%uz
z49D$PcVGHjdY>NS;X0yGI?dwAT+!Jd1?PqHHMd)i(x5?_U#@UjA+dgK1Y~x#F2Sm5
zYOA(TGx>p*(<aeabqf<pleu(@i*~>>s&>Bh%@1Tg&YRu^s=K8{bdE~Pf>&KvB=}Pm
zX7WEt3i(rBvfAE+Rfh*9*I=OIlSxL2q?d4^+HFrWg?2ArK2Hwv^OMOQ#h58GQ`}t`
zEF}&tvbv6|A)G3=I9OXhJp1~V1G!pV$G~{7T(74|$#Nj!w6u&VI9Lj75I|x*m=BYY
z9$d^;<tpX^_^E%!@k;{erj+1$2?;;X*ZkSCTH$CGfU+{~@5*H*>X6b%Pvl^qa$jlf
z#`GJ-w`(JN8y6pIw>xvO7#WXOo&i&Gbz0xBb)OO&pfw*dL&G^bnSpJJigra(Mf&;%
zN?EIe_^0JbDjNZtIRF@*%g38{K9lF|$F)|J_7*gvrsRl{#7X=-MB?At-YzWErmPxc
zyZtkazkt<pK9d~_Dd4ZW<u!2%UlYjBGa)rf;~f-qX`d25Wu+X-<y~#=t9-FbC`Z(2
zzMk3-gBS2Se~>rm;Ec5nB8HI+ZS(ka1a65r4*NH;UZN)A(O3EWn;PuC0ew<=j;s^2
zoq!gV*rA+JVcoME=}J3=?nd%@hKZQ4Xxwn`CthFbA4zRo<Sl9{X3M+jnW;+(0R8T-
zdcYKX$dsZJS~&OMuxcjsgA-*$_aSznDHBqKZs`OlWPfi+%&xN;9m^a*T+fFpJ1mFX
z)2M!l`p}3e-7s+D=NZ|*3Avgs<lf_J?$<JYw<lxqsfW(?GyPs}3LVa`$HSnNU--53
zTMO64L13hH@Y?!!$z<v6gJZ?%G=>#vnz+$4y%g#~$Ke{J;L|@ku2h%6FV#$i&}u*n
zX>qbM7yCT2Q{O?zgPNsOJJr_1YMfwbNP0m?J_nrA0nDx^2keaP(k>M)+jiYO2fwYm
z*Dg`o;m+~9W0{LOL-~c$#qIM~KhV&^$1G+f3_y+7IJBXw=X+&xsxDUHgt&oK36MSl
z_(>KF#tu`GAFg^&<8)GM#hTVWg2^rCB*+X<7(d>mW$`h`;u5R~M4U-~{u0yr)~cA;
zt3dNqtK3a##SdnxXm4cju3C||@*8rQee_j7h@-8Va`CgWgH}PWQ596xRAj-a+Gf=4
zx7ouk<kw)lWEiooPXo!Nn_^AibPb0EaWJwWg=IeKK)rVRVM>Wm_!2-=BpqJ@hOHO!
zs#N0>f1Syd3fK{48V>=%7EppE2BxR$dz!0j91NDm#%7C<ryEX{WQ#&emZ|2o-qFIJ
z;PB%$88EuZjXSy!KBPs$u3y}*TIt3Bn9$G$(zVgr04K5ev(fm!R-HdSmCS?aL{A%b
zS2e#coYSn{aX&jdH%9k%DJDwm%JN}i21ML^na#?@10JLMHFEpA#p#@6xX)?yZs#);
z10nXiyn){WPO=o~(<&%Rn}%$gu9`G)$D;S=lo}ef)jz?WfH%W;f`K2sN5u4nXU7n{
zH9g6oll}cC%@imqCfF@CE^@bFYDCc;Qd-}_N#q;0Zvm2KTv8I1p57`nIW>EA%ga;>
z@%|)rlq`&4f-N|WfH|sbSswjt!(0dvblZGIr*0J+9Zz}ESb*RH#bLiYzeo(=EUJLq
zWKdC*LQOQiWN%NZ#t=LpY_kVDem<V!!~}Z3HeKJHp9gFcD+9j;8VT0kGY{PVVpAF=
zt5-S+fiYaOr$~2F1iOCvR<UXz?cEUu>?`~{fSQ@k@2hK(@+%a~)Brydb&loP5t(F>
zAWrJC0>2OMq(Go6FWk`@|4rbe+8hk@voQYbknUx_-ug!1Y%M0IU;iV#0b5)be%<7q
z?IXHsj86qBEv_wCTHTO|m;FGfD!~7qst^eXp(}gLdw%b4j1^$*Q*4Y>=hgyw=tw`6
zD{!Tn<f}Hyz5Z)r!li+S_L_L7oSX6$8}wrG@HM_^Pry#yudS^ryCqP&HY1;*P|9H2
zu7|)%sK$0eMAAV_(7>&dLS+e)R^_Bm5OHO`M3=6``@(tlso!(XYx-tpb)XbA+NVao
zV88tn+7om=1=Bxw*;Nc2-pUdv{y{aqyERkbcws%1A()1qNe4WR`~~L}ybNrTPRz-r
zOLLxN=xE^|u{Ai#w9DjDV`STAQ&aUMBm{aZakvVOj+U+reYDPRzF6rPyXh0Z2Bkg^
z1e6ktWLM$cnPJ++9nBOQ;a$td#QSHX#A&H*U9xKUV$%UinD-Dm7ymQb>H`q*jNHjm
z>H_wGRGfGPB7r|THeUDG#rk4ql()f<y$uy5%G_)^HPk9m>WurJivNFtsQ2iST|4yj
zmJ%7U!&j66<7I?SyKubJ6a+QBlPI;uF2wBooi0|$P>spw^!GqRxEUR+#nt-?q~ICZ
z6dQ^mguR6_HTo}{Tr5k)Egpst-en=(jY&|K_<NcHyLsb(o&nx{h6kE}%`AFw4?6M)
zFzM}r<&wu>%fGH27I;A!2MGiXegfGp@on(e<FH?iJ^~1yw-}GlfMyHsZ34%C>umoM
zO$uMf-94iqFbFYlXCVXGz>sgC*x6rrp&{h(k(rB(^1SiWJ{sm+0}8El77ii;E<Dd(
zh?<9fUC%+^%!L@<L?e$t&K56_rUY*AyB4<9J|NjuVRYW^j9MchFnHWi5yAU--QoK`
z`O<A5g&ROB0BRvc2OhmXnyY}zV)HJ(O|`~l6tELO0ns1J3ZF$kq_lMSd&(O~6gdyb
ze%vquBo6T3+cOo8pkso1Vh5UlsgM+DHt1OhE~AlL3eY;bOC+`~?Ncfi4A!efgJ=$<
zM~`Z&FqA7C-UCeTNVP01LL?nD`|{)pLup$$KCN}OOQ=0iy#l$BkrWz~Y;V&Ysdhmh
z^kQe04$T+j?(^!*d<29`H#0KH#3W|tIf+KG?B`MKt6R&<_S+nRK0PbaJrGPPoS7HL
z?x4S(B60@!-Ed(1Y=s1siD*Z;?kFB8F3M(el%4JjWg{Z)IqUrYy+;kdL7@r%UuZ@P
zMOIX>I3BJB`UWzyu{f3UpF`I>6ah;BNRhJDQw8X!Se6Lr0Z|<|cDY~%Kxd}x#c#FZ
zr$sdW1xPp3y8+$T)M*5OOGv>l_D*{PKAXo&G9Xz3{1W*B&7Nw$Uy-@vfajJ29RAup
zSej}T+tjjky&msd(9pwk6s?jk2YT@<EtIllGK~+%%0`tg(y7IjzBh?z87c=rU}KmR
zuZJ<gYSh=)8ygxJaHVfx0J|NU>gFIKdfymX(DbV)dtetY-nVo4u)+-0Ku2p*Ca3<>
znhH$OKRldbIu#w}EZu}n_yQ0DHUFM(UU&Sz+#H7A0-aVo-ri$5Dj(jWJ$%3gNX%vY
zv;bh%BK(R68i0(2wHg$JiVV~Jw>~Vx%2)v)P#`~XlzLdM>Uub~-MeeE+u#YUR)@(Z
zvOCY!%L)o{l8L>I?vkrCo=P9w56|RrITKl#bv{v5jlrf^G%RBE)bkGts<ywq7ycx6
zUWO(ZFC|5%#*`4oFqu`1KG%5L1g_LwBNj}ftxE@A?=uJcpE`qyHvor4zctG$LKZaJ
zv%|@rzGAkE4&I%he*=2cTT8XODouwV)3VZB6Hrp_;^vj3RJQ-F1^hn}J-=eOr*&{L
zXFe3X4M-*HyZj%eSMBu;4J#a%ri_Pg4NKX<4G!+#RbVs+pNjgr4pi6D-h_6y>OS#l
zVP*szKliwShBW&f?u;+aUPA=+@r(#62tGi@sPYs%eUM!U7FXlwBqTJ+e0t4lucVL8
zf`Y`OWI%v@NgIj{dLaVee`TsmEdvd-FK~4w7iwXk!+*t~>PZ4mK>f#|0*8SA`TG?#
zRwWu4f#HsT7bBY;)`cMtR&t=~;X=Ve`<^mfMI}xxCjPD|(Ebz@f`KAJO8f$c5Enlg
zxM=t|{wN(}cXCj{3AIQ5F6)E;`rnKAe-BVFMF02aFdTgW3Tp)WRa_~2eM^higy2gY
z?z)tF|EwFL-pC;#XnTM>*MD3ngmm<OP4oO!$OHEKe{Tctlz9uzSAP;P@4|xNKLOrV
z__sH7_aWtgjUo06vI`F=mUz$!y7&Pevza-yc|Oful%1Y8C|PN@E~1C?cni0;lY#dd
zg6a>`fuFAA;lDO4{_WKN+nVFQuM6O(0Y~T1pUbH)#YHOx<ZM;y;4`=deq%dc^z5oR
z_%Av#KuMO`?H0DUb<6=g>tI8LR)`BsVuMldrxd$JU`DGV9$_C}KUmfQMVqh4M?C`_
z6JpRVc}-wSg#t(!f0V3Oc%X)BD&-bre8EaT$<RI271g3|&kQ+O6Ty$b{&PO*es+z$
z(gk$(|9M@1s&%UHh(;6kEQO5#rf!FG{7UI?|K7wV*{tLH15)+Ko-mEBK-M(>YF`iB
za-RJ&f=R#6SpKMfZ<gdEW_x#Zcx;7-KAXx;wdPBW)TCf#?sNk_a^l%^%_qX3jtLx7
zIYo5)=95FTsX>nnQtnNE!g?7eP;^yPVuGceq<IO+>87EN-t>S(7vn;b{qZCU!n`tO
z%#x40Oy0iR64}Y$rAIS{yN+b_>uSW`?|hkCeYkZS__>D8ukl>{SLM(4IluhDcag#Z
zht+we{$@{;9?Y_BMxmQ=($QlV8`>~)+G{loNU4s*mVOTwd|?zM-kirp+OQ{0h?ftw
zUy|DS7&jkey`8Q5BT9e+nIoz<0ar<w)=TAITO1szwq)UrZZ#hdr|B@Mf=PMZa=#A`
zwaKOD&REIRtcybdTKJS?`Q<-X!R-CrdR?`&qPbX016zhS%ZVl9Lu`J|1&_!x%*1qy
zadK?zmk6pUE}iX(nO8F&2smHAb+={7RgMwvLTOWQ#q%RyOSzy)qwc9WkhSk$dRN$@
zki0l@=&ZKqn0J2J`l}e%Z8dIClCfkl>+I^o`HbdjnO3ZN>EaqTdZMZV`p{vq8iP{<
ze)>0bQ&suCPdO152{sFQs`0XKnOr3J3GrFl^yzrAqF%i)y{x9uu$Nt2ZPgeVUzGgr
z(ppo7*wY)U;wE2r8&_scKtv)3pw!U>qAY9yOqrV>B5F><&L-X-mwd*G^xwnY!fp(d
zekhz{xGTC?6f5zDnqtH0c6~s-=!yG-zvn8xpwf9M6JqU~b&GaG`nE$W3i?or7*`PG
z_+gkMUWvTbTt(s2arRX!!DIsAYK?@`7;Cm>!WYW$T&X23ubetclwOI6r)hwj?k}5C
zY~J_P#rq=V>6%1Uw|o-=TUg;P6L+!vn@CelH|Z$5UptBV615`vG7p=zIMD`XqK}Q=
z)|`n*GH;t8#|8|t`8dQ%qn2-dQ_j{!VrEPsH$M;6_w!pDg;-4GK3u<2jxQ!}ce+wE
zE($M9j<v8A#K={k$)Fk7$K*v(G+ec*zsQQ9DtA=hmc1H!=z#Hg(72dhPtIbrAtOuZ
z38AgqRgk>zW2%n36~B14eAikaQp?^s7a0Bx82c2YD#XR*#bxCcpi#IWmb^G>r)Xve
z$yna#Oz|lQOFEqRSg4TtvSZNugR#HBjU&3Vsd;@!;jB=~kW0P0^$Rg<nkSA^Ct6)9
z4GqIb<ZH3joW}b^#r$2$F-12!CS&PCjn;V|GXtrRQRhMgTeInSqp*8=x-2`+FW78L
zvmS6oWlM7+{P^ug_$fizdauT24bL%b*|g*GnDLMYB50-4Xn-sTNv14sUwAi^Ks&{Z
zxw?%${9)W%mZo6%ce{9ZbqRxkFo`yMXu^FkBjOaFwWj}50|a(8TDrwd-~puHH1<W}
zMX+)PJ!VlqcL=Xz?v||5N2Ba#x><AdB$5{xnJkzk;tzVIQhL1gk+<CwnDLN5@{rNt
zZbw{KbAPCo6<=(mmjHnt1y)hA?A9j@X20(3#{~K&88qPN#^doL7ul(Y)S=1+nqDSb
ztk9ba5BZ-$=6w|nP@rmk0gP;p8=Gh(aWb3eiRP2htJ5+569!0v2G9?F*z47~nLkUn
zey8;qG&f+UUmvO3mkLJ4JqcE@E=G0<`h3S_2J`pp4r3WXK8m3cb5W47mANf)R8LvV
zqGz9#Uq5AWN0e_HYUu*KQkKz1yX!=Yp`Xp0C7oxM1BlRmSf47nZOwr|!&wO1{;hQ!
z!<2DS1m{sc7wL&}&V;Q@&TfaZo%%rA{;4JfxhK_D>x;c1%~<8Gz~A~kb1sVfE2|2(
za#tDBCRwKr#TOIileLe{&1`Nyb1~v?42U}<#PyeY3?N@*sk*9DFVF+_^>3ni)E{_?
ze|<aa4g5XTx^Yc5>X){-CSY40VTu+!A9|q~**{AaMYSg*fqJI}f<K|42{QQ-_1s@U
z_83y02x!L5(vSId=ul$+>f1KB0XM^w!Kl(MfGQ>{yPSHOv2!d=P8nCmyx%o#Nyfmk
znzx?VmkyP<U3o(7t<dh3SsQC7#7QtTlg>}H)9*jjXh(Wtl2yNyRB+vEvHGM7&x8xA
z!5=123JnpAGbj={q~wSBS<(F%me{?}X^D%6PKeJNJQ22lU>`FZ72|MB^qOVyG7`PW
znR_M(0P?O;?ZYys79Y_Fb2Y7~&*QnlC?zdpO#6`WX4Xzqwl!8QAE(fR+elqauKOlq
zR~&6$1<W#59}W^cVS}%W9^7G5gT)>bZSGClANALF$bTx7u1T}EMp}^a5Aeex6DtN=
zN}TehaUzR?^P!PtTWDu*MbC4=;N7*(WfAA=bh!$WzFqUVk`1XE1hj?mnBV9ud6DLZ
zs=7ecaCdl^Ey~qhsC<LA4KBObZLKQsWGdkgh@gcJOKN5-CMZ=uw(xo&g!uP5f{(@O
z4IjOo9C30_9<FZJ&FzM=t84+^gLfu>?=TQbe6bWB(tMhHtuOrN-%7{`qscI`9M$XQ
z;X0f&A66!?k`Wi+4~+C~X?6#ig{Q#mu<&WZjKv?mNPGwVql6bB|7-7@a)uN8?v1`y
z)4K~gxcfo{=kGZhLBIQN^7arYf76}Mf&w8htl^IxcK+Tvqdi-i^dILDY<ui=AK1bG
z4o9*NI0q+6miX4g1VJyO6^Jh3`*Iw55V;=OxeR>>uW|^u_&EX%u8kQN_=?vP0^@Q1
z71tb%0a-~xBm@3?HpeYKKmrD??38Zc9>k^&i8fJX$*nZHwaW3m!mvJ@V22dqAe>3U
zAFS{S3Izx0oWR?X0rM7MGKyBFeg@8q`^`5{tJI3sr=_CDV7g4k+__dA6g#giW)yNq
zL2{+wuu~9f_3po0?Ah%$_-$;c&6$g&GC}e|60><a%&WS9l`xvqLSTNTy37)C_}kX$
zW)Tz9$;Mb>S3WyrfIV1%GVQ9Td&mXgtg&h51N^155f+@`8J+OM<E7DI&^1lm7>&xz
zc2{W==PBWMp`2^<?%<QOOF2^8KL&1c<0<F8<q<1S5I%g5P7^rEnLwHV^%Xiysq8%D
zMgy46WbL!W3e#mLK??v}3@HPRI@sX5+EapDrA$08gCp=WeHLE9<uKq_rZy=jWn0#J
zQTaulR^dlqZm|)tXO>68?#R@TLfI7Ab6Kh}b6$rdY6As;N0vR6PA@`<ZV??eS9e+L
zKIY6-%9c)5CejFmz~+j77YXGXk9CIM^SDL$r~b!Cr+BRyqLC&|If_?akf#Hjw<p0X
zEHrqeBqa0IrysZ5XP<41k;~-mDP2T}7*LIGXYH!g0~_T<w|VVz<cD7*34n}pZ(jSK
zbsOpkO?HsUaCJlyncV2&x-l~fA_sJr(Ee1AL0ulOoSaXR-_gHt9Lt&N&TXDvcn%<V
zFj<3<->ch~^?1%1l7;;mbwJ@cm7R!<h;WPh_l?XKG~6IDJlh~lr%~Uw1m$#ce)90D
zfI!t^vRLc&0y-$Zf&wbkOSe5?1?-T!y22W`r>3Wr2Xj%PEkVPmqjUc@U9<IC?_+Dv
zcUFejtsg7+M<i{Uh)(ug?&~$><tvMr@wVnQ_7)O-SqwZxKm_Mi_dH*t6mrhc1~O0{
zL<xCL4<mRK`vnDdX#5{$9P_{TBug0o6{mt4J8AbH;#B@DD?_;dZ|$f+^SedM70eI<
z{M&dBDI??lY#cqdQ0$2w{JDAl`z{WyjSBd0d&xyP@e+YAaPu?*AB)HTGn=P9qpw~*
zT2&6d$iT^kO)ekM1p!rr1;CqB!h6X9m8ZsHZ1<Ive=1e-cP*ew3_u}I6C6DO<cuj#
z7V~*du&=L9gU`*DL=2PduSJ8WE+}vfJ^b+CU79M#2kF=;Uw~I^SCiW)p!*LvI3V;g
z*yyG`fBO7j<$8~{v%P(_mZg`_XxD!6f9_#D?g3eCk78cUr~MLj+Ct6xjey1sWmRQh
z2c=V~AZDVbrl-$#DyMAmMl~!|1`$(ESIeUO{JMk0765q)wX?%xvJvP)YkTx;P563i
zf7TwPq9;zX1mkf6+~>|kpqe}d1~RbsFzBtCQAUt!ZWU&SJ8)^Xbu-u4Z$fXITNW0y
zv7_$;!SQ2<n=c$7mJH3;W^LiK?FRD@2?a<co~$zV=kw<^{!s;jk{<ee1+Ze^*O#8J
zzZ4{vX+vHi3&78pryLI6Zp|JB27%gjdy3;`yq9}H8a%)IwLaO|xt%k-V_~sd3;CR{
z$~69w=@5&W!*(@6E{Q90mTJTKyM*2LiR;;#%pkF#lilvrOzwKslW@R2B4pBkKwu04
zI<RO|+_u{#Ok&3;*OOz1x3{;3lEqW_zVC+Em6`Ni$Yl;Z@Tn^V2}l!zQ!j=lXf<ol
zun7BgOM?h!gvqRdn*z;O048e-lIdY`J|m9|iXM4B!aUkgm_A9oJla@yKi!FEwZv!1
z0-oOouDmuF7mSU1zjr{8b+IxvZ8WFb7WpXzlaYgn17yM%XjBprAISOi&yE+Wh|Xs;
z8urSf2i7=`)0(T6e`gux;sR0Vsk<Yq&rCO*#s<w}F17}v8Day3*4$4CU5$(e;$(o!
zxViZqJ3g3NfJ~Q()f!q<TEPT_VgJ7UPA~20IBn~RHj*T)c00Z=NW*D=F1<3g&6%H<
zM?S+2{X{1y=?3K68jX(I?ay-9oj$&TJqIp}uB;CiO$$5qm(vwyY(@60Fc!6no$o*T
z&Etb!a_+C~qnji01m6#$!5>fJ1ZzD>%}O0cK{UWC8Oc>M+W%60;bt+v4@S*;yKV0C
zS9|8uHKPkDZ^(7i2Hq|%F0#Mu&tCFj1#Wl8o{HZCS~xG&Fzrtxd$5caAAEeY1<V4C
zJoO(F+@+E^jJvfkz9#Z~I3Iv5`8@yGxn8!W3V{v%7qS;4JTRWk3k?J+i>Cn+vASx#
z>gYrNs0P<li-G?9j_12dlnU0XwC@}k<aQHNUvc<hieYoRu1T#=1DZ`%SkKbz$*ES&
zM;@5ce|fLWc?^cm0Lio7?Rqty8;6UWHd@#bmX_9XLWBSO)kN*>LdqtEiW;8Hmg$&z
zx_0P^G6(_wmDVncX0Z2lZO}eMNCbBU7?R1$HpWT^zUg?b<Fi_x<gL5kqT?J<u6(a5
zF1Bhe)LH{V=Zh_w&vyKmFp$WMm7>m^2LGMj^>EZ_h2Nt6*`0y?nDf*B6)@ZY9Sy!8
z_n+)tgl(+<XTmTLJJ+!E#W7_Vb*I$DG4D4z4`}nkU2s!Xq2Y3bl+KmriEpvwZUhsD
zLsT7@(;$FbR_A!w-rA1$62D$G#f2UCRU>KSUc2*9j$~=}^^R<<mwM#7jpL0J8d-o1
zbtz}r=@>IQvKNL1vx#zYw?b|ekmGy#2&eD(FeHJ}W`2G?MHb#f;{b@;MUpbykO0BO
zHM{O<+V8O`m9n>PSlD8a%~+`H3)F#aB^xkB{!yGCVa{5Yc_Xo*4<Cld=gX|4Nmrl^
zYU=2K!*%|fR^4o(D9K;!9_8uoG!-c+3jq0flC^%%1)yMCy9_JYSZEgBXl@d_GtbKR
zi6hTu7lrGZq?%o}asVi#y!#zwM1a*BIQZ@$!&A2SmY0|AS2z%@jS^oFTOSu6Z#h{}
zYCr$^c*BV{hBf{muKKn&o#_|AYl0?nDxd-T8IF({=+xX_k+@)J(Us2`ur?we9{f}6
z_eJ9L4Y-oeura=l26&h!Po4yXhg(o-kodG@@Nk>BbWA)=eJrk(K^^RkK|m1BT6p+d
zLrra6OQYWI8W`brc^zJdcdhp@m3~GG4|6)jkEsz#kxu80#XwxgZ*A+KQ)}=;qt$2<
zpieHCYj0Oo`U}|5pwUi)M_~4a%?S!|r}L5nBNXzpW9)ZvadEA~6cWPJSeHAqz;A)&
zDj^^sAVl`I{#&OAFvVO)V;GQLxzk;Ec7Jp0jj)rMiyqXriN;!0{+EhUgfSy<i_#_Y
zUjNbvv9Ka1HL#H1O`5H=P_>`G%@9gcDK>egz+y3?4d#Z^U3JTe?>DVoQ&f%Q2H%xz
z<6Xu%W<V5T4ZpfNmlr3}^u*Kz(BN!zmqll-eSGA68NeaV%i_s^_epoCkw{hC?CG<v
zp&@?a&<zt^JzlAowJvRzmBG7!B(Bxyf`zk3?s|)gidt)Lmcp3rzURQ@NhW7GdlC5g
zePM<9Bwye<yKC|vvar<b?<)E?jKd!;JX7z(_%HBD+uPezRF%``)9MpJpth&%ZgGb2
zGjQv?26z6*GxGD)SMOGZabG?SFNK$2-(<+=yhV#uFVF__ZX!@&7tS>V2L-}s;Y5(U
zR&Fu|06h2Z4FDTweuya<*0cXa1<vvxq}6PO`_O=m1p3E_#z=u4YB5)nc%Ha3YcEY3
zEf)h_-Ey3bn_)t5>`ox9&yc_);B^GaRl)Le^+ts-FGs-JLULwgW9gRInRO4zFc3mS
zMRtOz+1^|P#xoTGr;<Fm*3Q;BO2n~r4`4HF#Cdspv9qsG$kkwM>jDBVH5P#1d}4nI
z$+q#d9Q|S1LHo+Fo1M#Q;|RF(o+b5;d_aEoj7qD3x{V3U8u2Wa;Z#Enu)-A?&#AS7
z<M3|%w022{+nW!DP9pBo;@t^VAP!ENh?4RGJZmB;6-C^6)R-)ReY~qvDmm-wWV;s3
z;Dh$v3s2}fOYQQ3utR!6c!f+V`COw>k{Op-()Hvi0~-#hQ47h}KPB;0y+sKD;>($N
z`vFxD(dlu=A`1Bog5Lsgn1jAxhKjJ+9()Cp@Xo<L0jFW>#D2J|%PBXCgJx^~UPa#~
zc;<|(Gsah*1o``CGU+eXjF#ow$19eu_U_J=7J3hY5bCzwsX+0aG6<%9q2ioLWOsjm
zfmU*oyc~F<Xu3X9FW4v^H_9vs6b{_b;IKW~nP{8orRE}r_5ph3(;c$ue|4!b;=Nm8
z!-%3$F8g`_^ihT}@$tY$1@X}uZ5eKEcH?WD10e#b3mKwI-nDkS#)CDpAT$Z^2CkO7
zN_F0JoNdjF)v1K%5ZbQxCruVg6}E{fm7VOYMUXvrt>ZHOp}fI$-6hVQ4lq^6>#W~O
z()afENc>mr*XNwCS}8z+`4H<nM#kwntL?IN_tMFiAa!;8%fsX716P<22nR^#1%|7S
zJjv0V(dJ8rG)s$1YUO5<nb!bw!Sp+PvB-C+Lpm7*MynH6nr|u|&9XZ1PnaQwf6mLx
zi=xqd2g38K53w7bK1~f@Sd{hXLU5HjHX6`I^z_t$vP8Mz5rN*4Z&0AH$3qpL|K5Ib
zSJjs<V^c9P)iX9V?*hG-%>P)}(8rBXlx|9icZkFU%TeL?06iQJVh9)B%P1=R!;~L#
z{LkDGt0zQvlQsC`Kguq^zc;GK*=FBVp>Ef&H|x_OJ@1C`xvBHUJp1Rq?|*zNxbeX8
zpA{QXtA_jy9$?e*Auper?O%K%v|#)4rhNq}KnytRdhin<xW#JlG}Qd~Hn^mir+V3U
z@{euAIpK}{ZoLDph!?Qt*Vyc~U1dE9&j5&wfOARSciJBFaC6t)!RHM&97P73b{dZB
zspml7aJEXy`)QhU-u2OaM9-Lr%QYaHh&`|Wl+4q4@#*hNvCIY%y>EVyC|wr-uM$8|
z_Fw<Dq@v0tsCDU2Y+Tsdx;ik>HZ$A$NrZ?$k~?j=5CZ(vc55@P+c^e+<ZVZz9Kw(X
za-dE&Cbz-TjWROF<s7=w69wGL@qDj84(A90U=om#6v!365ab7`nA}zyWp0_nq*7bs
zmE*wR#%ej~wto-_5}3gwG6<g$I(?#%DVgYabtWpHpI#k13A(p7xMQC`2(wsB5&vA2
zihEZezAoF~43=Xq3gl=YH&HwiFdQn)hbj9~y7WsxM)T!-y;3p%IT%m?vu3uZeR{S7
zvQr@diRIs?TH)|Z2?;ok8I8M-!0bCB6}T}<DuL6ZTfFx4>DoLTbq8F^AYT=*DKmgu
zH2Mxm0WXB>BU3I=@}DJwIp#*C2$D9aKe7NSaYrI@qPvHr!31WedTj_-v;bNWMuG-}
zN@}KJ@S=H{)Aj`%Y{atwg3idq<1WSnRC=PQLBar_jjMCG*YMrAj2FzWacX}80G{?>
z0&XyJxN9q5a|u05-e2o@?Ht@cbvg%69h29x+g|N~WdFpPldYL-&xXkwW-1%6%hOjU
z>%3V20xz#w^f5bLEv4hs(%sK5XS_&7V*o_|*z!QP9D*%0;+&ab>Y|lh+nhHj*mSdv
zM$v$-4w$s4gdB^D)pB=11FsZ-&f)6H%l}P>xX3H*M0Wc*qYlL>lkPHHuya(c*UfJB
zgcVp^UcQ>yT-s0#L8~l$>hSYtXoMHYaOR@rX^@L1<Y~C%u>B}(^cs-vi{CtY;Ns@b
zvMrg!F${9@!3Aypd$Rt!f7$rLOB%B$Qnvx!{L2xt8zYt&sEzR<0srh^z8D!$;2D-W
zpRCy(or#vKN*sf*<dh>nWab<tMn-1m3+kqY)uX`(qeRuRe6TqN$UfW6k<@OmvH}|b
zkgUlRn3f6vJ$N-P>-@-(Ydsp%thdYtXy&GtMoQ!g4iR==JEQ=MUZm33etJw)cR#H|
zN|_pj54;EYeql*^dU_z(Hx8Kijz`P|vxh;B0xkh{d|!7W6*f$1-9FK&3AjpSqQ)C7
zEpsYM%FKSxu7U?h4Wo3X9Zd=!pBGx2Ut4P{141Jjd^7K{J65DA;ZzuPelkk51N@nP
zn1UlQEIMEizwUXAf>K#>aWxqh8A;N{2Q1ay#GxYd-eK9TtxtKWR`$<o?$=W+9G+7=
z+@3~Mfc%w_DVt6HbYrZXkwmv94zNm2*Jc|9){*-kB7;GYd0tYlslQBi{TO$<-XI?x
z4J}Js_rUS%OH{J!9obj++Z4)93t#312HIX+XW)Jk5J=~1Vr69=t~W6@ev!-&F!Dyn
zdcvgK@7`JDT{GCFayRj-*SZpTt11!}wKK)V$z;!fp<TKG#3VshTGQRpb7LlOtgWqA
z8)KP`2n~cTVDl8$xBv=oKdmT5c;W7VEuZ329l%mnUOX5qoi->SD9kxA&B*&U&9kr9
z1K?`A^$%KG-(If<ohWZ2-yqy|vw4XR!;9Ws1BL%<6qBi{!LjXH@;Fen0=uPrtpPcu
zR~Sbd@ZtlI;AE)N0_xjWY4VV+mEPy<wijDq9UM)kl2zy%<d<Qw=`^NO3UrPyU2$=M
z;VoN}9HYB&Mr@cg5Tu?Q|7sDY1W)<#p&xZ3FIZQ7^lge_af{N@K7e2Y)3N+a2ADSB
zK;+5cTbeCAZzA3Smw}g`^-0g|&5~tB>k)8+cu;4#&(8tywbF1YPo#NXK5M>KS}q96
zz27E;f<=?E{P83Y7bLj@vN_h?Ijxs}GKX8txuo3f#q^IKb@q+#Yv`ze-pp`hPmv~`
z)nY1)=W(vWaGFxE1sHpP<M`MMf=((`yI~L38r?PRgv>brA3s>DhYdn~_r7&9Q$<6o
zdC$mPgdW9r-MeM9<}laH)Lbgs`!v8&u3Bl*jBsU_S2!c^1mU&+zr_P1G|sYG3U@B7
zdhQ7e3JLm$!{FMNf9)o8kC2%CqnqFo3?4<~^;6a6jED%0ZCuGkI{9Xd!)S1)9>Uf4
z-n@U@A|Mx^;O?G(b$T3GRCIxPr9w)Kj!%Vx9vT8K<h_H!&4d9lu<F<lI&FlTgu+7j
zckUU*#`?h@mWkQ5&%n#pf6m1dKK%!kQ7E8i<(mLV?(RUiV#k&E@dJL<!F5l*Q+_wO
zhYdoMW8Ch<CVQoKRqeCFA*nwv^Wg0lXo7@g;Q+bfnpRf!yV7QiyFD~oHZ>^=k0`Yc
z!cErE-JMqQ<zH9n(DWI_nNDTU4p31L2q3P+BnuCG0WYWkAhF&eT5H$iqJ;r5?k6b2
zg|Gd!;r&BCR71<YK+)Ex)E;?M95SM}l8lo$@CS91REQHAR)!Y%{Q3_uX9c2Pk-kF+
zQP6OUQO^EGes@}M4PVxX{`nLkf}hy)oL2f!H3M~k31`xsBtu4!u_9&K5kF!wRuz2m
zJ==@B*EWF@J`+4ZW_oJ9U?LtL#{#YxZiFT#bP>}IOWzIs&p>*%stNze%z}r=6V!&y
zNkwr6z1Aww?R-bW)LvS=X9&D9VFH*h(!NPbYr4fuWQ9%I!<3$ai{z0Yp07j8t+-W9
z{OmkkG|D&~8pz+4HG)?j_xYAI>hr4~hNWy~-W@t$U4%OIR(kq&l-1T$ygT~0Mxfwb
zBF-c{EO0!t*MjVLi@sTkII8dg*xP>j&VKW@;>uN23*+!}sz=B0NoH9fexQq%NA`gi
zW%yeM#78RMI7oOE$Yb?!U13iGW#*k?^@+8s*{w{XS5M8)Twe`?542`Ak=NZO4vadg
z@IDjtFE79SddgWRNjxn78RP&YSIL{bz%asEI#DN<zwGw@+H;HvjidlK<Go}{Vzj$D
z>7D5qhhEH@k?0j81H)!BejBfI`oKIDF2WK9ZeeVt6!a{^1>zij;I&7%I^8QS_!2cf
zkm?=y=}l+FK$nx&_V;pbAs2(PZ}CHy2G(1m`Y&b+D~}Y$1$_@s#g>u9-@?n*ofPm7
zs&5TUq@8&C8Kn$Jukk1C-cMN?gvs9NdHEzg)=$BrQvI+I-SbW3wUS%(RDw&jilf<t
zqnXN>Vb#Lpn*g?AQYO_}yGtMPzWyG{Q6<Z7>#wrR-jUoazJxD3fEI`o6!O7&wDaD|
z#wt_)`c!3@L5wsclf`6yBkDpBrQ>8^-hNatU~R7_XVbRwy6j7yVD?a5@X*<#Y}P~t
z0W!mhUUuxuJq(mk1l}ej&<OimhxFp`o(E_)|5FzB2npd2Mf6P+b!dAlNz6Ba$3;Wo
zow05`;S7+%-ml`fLR@tAL9vhBPd;D?rsVi@b5BT6K_%xD@_DjFB5*#Q5J6_`s~xtb
z<rs<FVup2#_t;6mN6<%yPZ6*2hd#!zJGY%`;VYLUMncOMij98+l~;)rHj&35tIRQ1
zb!0wq9$CSuOP=#&^^2_yr_X!|zWX&kT-y}#EU|%%_mf6aLsE|+63Z&8Wj~{^&BJzY
z-MnTA$CkP(uAt9K!IwS3Gm7uvmn}pBzGv^WAYK|luk;%pA5Ok@xBqo&(xg`$qWM`S
z_0=q`twU+;{<(J)UrYld1(#wU{M-2Kz5<EU>)Kd%zSMVR2MVV(2}mn!Pd!3&<>DB>
z7k_@>@3wV&B5DYK?Q6~-@TbRQcdf|r<Rubqx`~qKaN~>Md!1M{W53!-j4QMt@go=9
z3U&U{m_@?UC<q9uMs#P1wGQUXA#)%mwOt}M_xu*>YiO9^rGdg^uG}#+#ASQQjBi)(
zh&@#G-h4n+VZEovtx_tXfz5jAV~R(iG^JEh_0fjyCwch*-)vt`jUAz5Q&58%u@rnr
z7;S2loU2b?SyP_7PFj~amn}J;L@<L~onGL0b8rl!VttdAiivD+Qzt1nt8O}$mF~O_
zdRX>5yf;S_aeao<D<%1gFn-|3D(kSF1JpuOLFC$#^}(P9ms@(5^9`C=&PvCt<u=cb
zfuV%2gDn?4ZU+fdnFZ7#1CF0=3viFa-%9d)I+KrcQ)L1VOjSXog#q}gJ0zc)BP35Y
zQ=_NG=HAIStSabVCC@K(2!DP(Wm7)f>%$&@Iy7*T#~l{f(gzF{9yY)SWFcLNg!$tK
zuMA#f4EfG{tzH}p2Bu7ce6_5KTsWNtwBG*K*GKApcLcR!qvSK>_yYCXdW*vyknKLL
ztTvc?|6Ze7=GdZs7s0KtQNLE8l!(c2s!m+u1{)`P#tsYH^3qu1WnW+K#z>xtE^*z4
z{pCdV;VM?f3IsdzXk%fJaijsJgy^OI%f4maXkMnf6B0?CivPRk`}pU=xs0F|E>opk
z<&+5Zf{BVvKAFldgrl?BL+w+trzRlf)XXf;#sH)*@Xj4wW6&*{43{EeqQ2zGm(QN6
zG=>;ls#iR1dIgX8dVMLK6Qf4=Y{u~upbsVcA0d}uUW5{^wr!VFZ}%Y+)+@*cw6za7
zBcq4<dJM3>cmgIUZ5%ndP}+<XBS_j0V&dUSijaZWgY4no1smw(VKHwrP6Uy$w}y&g
z1?|l|tX=~4J3J=xjaaT-I@UJaa(iWlEd^@!JD?lf_u~iGvE;Lwm0Rh2#nZK^G4^0?
zSCwoR<HpUKYIE}}m+LWZM!E2tdd?>gT`o$1Nd!11YMolNu(hq&5{SJtf)eZah~gSp
zA6=>+0hnC286aR8Hl81V)QU1OMg-66pPjazzYiU$A8t}DJvvK-=ega@%w&%^H|c)6
z{noFg6AL#m&eR&E?4sTEyPf*LB2UR%YnNTdJAEXjy~$32NC773qvl!>a&0i$BBf;L
z=?AS)?W%_x)5kvIIgC|VpXw}U;<y?(w30c|Zmi}Mrm*=Ywa9J^lLLPYxBKHjZ3b2}
zkSnd>1Y44+4=WA#6iV~`7C<Tex{$VBSC*fIO!%_1lYBNB*(+6Lsb<8RpJ|o%OywHk
z3hA!T50)uKlV*{~rv#T~yUd8WT7ec`{*P`u<}^G6ivhki$>1}rHbSxKgsc^T9zpPd
z8peCUElG^v*^ZqZT8vtm;##$)*BJNKy}fQV+DnZzupR{8JDV{otT$|QC9_-T++v(}
zLBvGA)|J{K#=jEaDwwh&Dvd5pz|d6#Mx&`iY$83fn?6Z=+zn^vig4+O<oTk8(NTQ+
z;A9@Hw$^XvOVEez^3e0!p!!b9((SMnG3D&A)E^^H-U#HTv%PdHNRQur_p({WVn>O4
z^W4!<me@7Gwv2gm`f6AF=L(@FK@6I52{inZstsT65bdJ{d-!OTwrVBuHFAV91SD|`
zQDqg$V?JzLj@2To%#IaTlx*O7-gpkyE0}g{IT0ge_4hgg0x7AeC?M2n=x;6Z6DqbQ
z2ExyWF0-K|+{Uz^8THc;_1Q#}QsLZBYZ8sbAEiED>(h*`-D$_r2@u6pRj*L0LUmRu
zci;SI;l;sK$cT1ybo?wlFp{GqlcuWh;TmE&FKB3JP?}gID>t0RBY?ul93|#Y`kaur
z)@_ML?tZGCw(ql#3OOra$Iiz21VQ@!TiEYR{cn$yUDY6BDVLb?>PMU0O$t{haqBAQ
zqQ+}66d{R;;h~|CROd512u-hi2!guXODa4Qw<AsM`BB11eN7Y#Au@w$nRFA;7(~pL
zhNr6<XZ`g)T0RZ+R+~4UTgX-%>YT=GC+@ouCQoU3)lF7xE-Yozndfa}<z!=Mnt^~d
z7yi_b{;qHENd&#jo$v4RI2<hOAJTB%x0rPlxpf*=qe&!yLaoOwrjEB9JHs;z$1LY0
z_OV9&`z3MJhufchomPR;Coj2oLJ{0Zj+*X!K&js_Qqj<O_CzYmMi|{VU=#Xj@rraQ
zTne4p6H-<cpw3`+KwEd}9aq@r)99nmmq^~i(v9>#nq-;WSffya!IQ7X?0!P5KYo+u
z_U6KO)?7L((HUjXbVrqgMKL0p(|&&{jf@WDk@x1{)YdR5DP0~Enkp)uc+)t?e(`@0
zKQV5(J*3XIbh#&TLZj%v8b}d~){su}6o0vtcW=1?v11*U^4?&6hmhGchW_E3zSG@p
z$GyGv{94qXVxHYjv)t3;1;#`biGA@*HEx@3s;V4^G>?K4uq3V763$E8-RHq4#Rk1e
z9z+Cb9#=_`i<imiujvYN^P8{suUIn)8V^SaCiSa&+t{JdlC{qdG1bHOao1I}%B#ks
z6MyG+UhV5H@?^q{K#+<DblX<BN>JfVG1doHZX|@8cWjK$!F^HZi`57bf%yGegjk&+
zc4BOp9`B&{4}g^)f;>5Vy-E443S-}LD?;;^kl7wt2rY(o8>!9+@XI53AU~WpgTEj~
zU|%K|#uk7<`|2yNM?l#b-NkQ=r;DiIHPR{HAGu;4vi)5P0I?{7?aefge?6Bzt9)5G
z3vV!GY5%;-T>*bZK<NILP#WosUm)fH{2)Kk_nM!{sB&M^b--T}VGZ8c_m^@Ciecd(
zBf`C?d~?jy)YN`s;`2Rn0a2Nxp2)Btv+zaI_bd1!X(a~mIpcAYgQo){*{!US^>p<>
z%jlfFnlh(*!^Fhf+uMEX+X09e?H!;iXquao3_4Ae*_t}W2aAEv;DLnj-NDiEyo(~6
zy}FuxlKqP7CHMU+q@xuHAw?k}RaFJSb<PGn_<qde6$KBE+ePo>?=SuS<)$Vkd78y}
z03X(yY_z-v=zrC180u{HLQ+!E6rab5Qb3m0rRfYCE-r3`!O+)z6BCo(0sGah>dvg^
zt}d?dXZ`^x4fh)&dKI}33W6%1%$XA(7$7Wwgz*(4gYbmT=gCYX3YeJ7V$7WIt>~E!
z0|Ud9-5SQLWNlqD2HOn*>(ZPd_4S`cMcbTqiQL#Dqq!ZQubsiC>c4U%*Hdk<v69&}
z`IyB>Vtuw3TJMb59)$bmX%UD0M&}h8fYL)mMFl++8h+j*=00>_ILkpoa4#u4I?Bs?
zc}VFELSPha_=ss}q^cup;vmaDIH)b;5u`2r@C&XiWT>dB3gXG~)0J!X2;IVR#|z|~
z4D<}@ZF`VtPkXQpO{qXzttT*^1!yyL&kq35H&6eDi-BS2*eoyhc5CkXQLp8}jz(2R
z1`^^5gkKioB;=jpos&^RiHNW#3=tdnegtU@V?jhP@O^KPm=#PfZp=Up_JPttFeCkT
zGE%C}o;OXDZ+L`+hpnwUGJYKSwf*|!ba`SjQ&n6Mg*9E`d^)G%K9I=nnzObb0f=vF
zGqCvj`dM$VNL&FH9a2!yYo6zQ!)ZNTu}wjd4K8g)25GJmbtYGq)a~aNFJ8pPs(_nE
zvcE4=JfV|zxw*w>j@t>&QU1|u)|}e*#Mf6=R@TYMNer7VD?O9dq;~?4cwiZ@?Ck6*
z<>}r_=ct64X#6r*Mn(`m@2}C#@vbfkc6RpeZiqLM_u*<kJ=0Gkl%2WS@lvH^(BbLq
z?9Nkbq^F^A9Sbl9$&mE9sw->1_=>L=Mp7|dH)<;_J9{D*kv<J3^Yq0XpO#_|thWrY
zboTTBFhy?yPv1-)rMc#ZOH#*&dUg{NEa}`=%fGneD$268N`(T!5_a&&ADfQTcK>L7
zFi{nYPAw`XM&z<V76#c=EM#J0!eP>9+fFz-vcbe$;V3sLRH^5;sdpdH*gKk(`(?z+
zOi#euUuf8eceDe5?N?-v?JV{6_4_!YIHsnWvHOb|`?ZSJdaJF=%E8?Z@q;)yag-YN
zW+~(%AsQh1gb#qaK=Z-D0kG2!o+5uY8!Ajc<e*Lnau8!9#QJk@Pq=`9#nOnBZwAUo
zB|^t0;>IFkC^sT9Ikx8;k(xZ*wl-x0Nl$A2dMU00oHLQfl*e1Y5|g4DtPZ2VoxO#}
z47IaKcbfcyFW2CB=*`lSW-W~Du`>g%n^sdg#jxpU-uutvSu!ovvO}O8#)*xgKc4k|
zoR%<P0g}5lwzIv+<8Jrq<JLr7Y--()(%%D>+Y^&*!<SpxdfnaKTf*AN?U}sLttxnF
zQwOAm$Km0H%Dif=xatbeJervv&y-)sBoX%Xeu{$PJe=~uxu?dK-1)I10rd5rbmKkG
z{v-}sI=V*Zj*8H<4gq(+$p+i-ya2ObBqEq*zkUzwg9_Q!L`r>jaaZEyDdK%phtoad
zsj?@6+G)biq89<ct@Ly#lB)J}>v&_etDnu}Xab-Pr>9v>er@HwCcC9vKJHJf6%HV@
zUjF$W`5Qi~MVbA0&<;<7LQYJ742Rcsb%<zq=0idrGaa3|LMh9sx@r5Jmz-{4U)t(x
zE8}tS;gZxwH7Fz}3aRG%{Rj<JJd-X8;~Yu|355_C@Cdx(o)^cI3Pa8pN3ogq!IA`1
zO8KfV!$3SgKfhl4lq|2L0i=hCKqjN1@o8Tbg)DPbk_O~O3Q|p#7^fA1#%?2^*|j4n
z52-gNSD;{fR$5MeG^eRDDJ(b5#UHoialMd_>zOS!XN><48>_Itv15IGA;Hq*7cAA;
z-^I+rpjmD9gtIQ9)_GH^m>!I?XU>Q12ky6e$QPl5)<3;a03X}N-r7J(f@lg*Aq84q
zmzZBls;I;^xH>VyUZCNfY>b*tJFyIBilearTh{huZSoMww9_%5!oH!R5@`j=mn8If
zdX;-;UEvX|GV~IaX6r5#XR_jETgUjUK?JDs($e4CDKj!6gz{A?lV(?qz?9<rO0(P#
z4qBa9sbb78Whk}VnX}#)S(hZ>{Mn!Rh$dc^(yn-UbTi~lN6=`tobzRrMBNuP@(R=G
z_Ni`@gOPR6Vg?fwnDG$yYFCz*bI7UQAxJCk>l?@pGeVT9;pLR8*LZkwmv*~mAYNTW
zq%%Op+QsE^ik<0jf4kJAZz|-c^lEKP3{ELv5g@cxeK!Sk!#7_ag06h}?}-Vv!Rn2%
z?3N5AYM^R$+F2YFouCU~pkOE5UCNZ&665BcjRy@b4l4mRHjed)0&Z?z+BM0xEA;2E
z^mN$((mdl|TLJ^1^xM_lt*e%r%ERSwCapEkr?NgTCtBvnyr~RvIeNtulP@YJ2K#-~
z+Y7>Qe+3Xsl}|Ssf&PNHuS`O#=0(Tji?psOjDULP{la}SCqbLzqnIy2s$2Chz?igJ
zGTAGB<0F7An`vk6<aV*;C}XP9pbG$2rzZ#c!&F!>jf+UCWDZwSPR@9+XgQl*lcJPT
zjJoGh;@1)0*VRv<L+_-051}bI9R@3RS}7?jI|6;W1TI?+%8e!9wFZc=N|WQMD4K-Z
zB<^tjELobLc_s>j(a6YOl7xSF2>q0OcOQ>8m`*jLP)qa(77(zos{w;(v37Saueuzc
zGSKb-5@;ncF>#oj+?s)Sp0;{dS%mx`o-H%;;G7gGDJiq5y!*|f!HCau1#yY&6}M)#
zP0x$d@UV+h>K6}<B0}lIKAO1r{x-|YH#Qzf;xSzv(LHE=0undDv;wPn9BN=;L0Z=x
z3>MMvzBCmS6bU+z4+Lci9vmK0=+-)3j`?&x@1meM7r(hY{WX%56s0(#3R1V<5BMSb
z$!KZ4&(0_iss$PU_M_C)@D;_pUvjk1bkY3?gClqH+vGPxme}yI%^R1R`US+%I=y>H
zA-a&#BA3y}=1ltyEp|v#UGc1y!l&iMvyX3e>E2>kQeXTPg_h9#L0G-UCH5Ta!<+rj
z+D4MeW7+-yS9%GWjZ$>MFL?_xGIn<6RLg`ue7K%j4{xK3y<g~2U)z2m^|-;txNM%S
zq8P+6n=0o2wY_pAfhNT)Cf0+&*t6C6d+3A_)=cW%A`}pIX5n(@#s~NR(%t$h*&iC)
zpU44dZ>Bpleqnhxu9rA?c<&5)fx?2k-ejs(XCp#1CnpEWMcAf)x-+{um>aB2A`H1A
zr648!l8c9k`tl{St}+y|0f034%x0Y~*n)y>qg2stZLUE#N9&!TX+FV(wT_z=YVjvN
zh=>sp5T=S1`-vh)6qpha1NdY0%gM;-@LsMn8hH`L32Z$!$W@{()HRVk(=a!m$%n5w
z5!~Jez#XByLT+w1{?Ub!0JOKSp`gI5qN0)`3XwE?P@nZ6&{4}CM^Zw<z%3lyK0~Fq
zY`okW8jjU;l?SdTiw2^rk<rnoYa{ezWWSF$L&7s956`dOBVI7vevXPV+*V~Klf-e~
zK4_b(cj0llV$&OYxtdvRb&bRweEKRgH|@>U*5GXbsv?Ft!FvHgUb#1-5a$%~tGCDp
z$ap4{$Oo{7zc3LN241{+#S1-}NNR8efXo2|K3sS>WH-Hn0f{R&fvti8QnyE0Sy{vN
zBk?2_ZU%;&z1qpih`q;1Cu7n|nMRlj&D{A~4Q@25*1!1Q9mX#&BO|pecHKC`G$D}g
zDcdjj1hQ)<eUlx5hv7^6_n#A>qBiJ*HLig{Tg2R~^C^qvBq`p84A)4imv+b*2pIBH
zjM5K>1Px&4$tVe{*_;ap6J+|<UDc(IO;43$a%(lX2$~tg+gq1A1c(NnVX1ZAH92+a
z6twRjBAgAs<hAm<S+JNd87%uQ#*7f5a<@kak6P{SIRuV!9CGl>jJP<vFx1y~aI$~S
z;Z8(E|JhthQW8F?fG2QCNeQRzN3H4-?YFjXJ~WHSe*WyUw8%3oU}!i7bULUH2zA}i
zojEz38mxC|FBw2^OW)LSUp&Xpquh`XOC%vbWMrXsq0IgSxB^$sr@hy{+HGkJq~x#m
zX}z7X1t}06LCMq;bwXzT0Rh@Lg+D`f>tJaD?d?KGF3S_ebW{?MxWiK}72IY%)mLCg
z-?O}enaV4K;@ow-wUeKn{hqf(t#bFVDeB9o30wwK0GbNQULH_lmL0}xK|O@;y)8J(
zV4SoZog9lwiq6&YYM*ru>RMV=t9PvSkx5+nyQ+X_={ROnF87<%SUG<atX0do1_c>K
zl{)R4CZZ2*J5SF{175M797N_W-NxCF@4ZtJx&W&N06LE6bRO#h>fncoryDzr#o8Vx
zx<|*y1gGN<E@F~2xRD$2@$r>PgA8O2S<Ix}58IFHosXZQqRthYVsnEfW3}we^H;n>
zwI?TmLa49W6>oOkZ&92ND>5x#+1i!^A;X00uC`jL)A<pb{mxYwtfx?;mX?Of`f@Ch
zG!UOoqvU74#3c~qo@~t8kNO#aCB>0mjrFM}V`kLB0aWP=-A}Sa7Tbem3PzX9BgUWO
zN-_#5>0rU06X(^IhYQ2c1XRxj*2Tl~t(8Lr>GqUIpjUMzf>EyC_>#-Iz3gOrN<P=H
zAT>2FH+MK+E!tG+ixRCCab0{8cvv*da*_p{Ru-3B>=8|Mb<yuNxiOaJ$kTCoM?{5Y
zL_@W-uHVuX^2tPhM0v<9pOOB3Z-qn&@@|}$?lw_OFqQ#(P>6(tq}yP^*xWoHUy07q
zb`y{A1@1My;oz5Z;1`St4_7NS@$&X|l7*INpM1fjz@V>@+Z@Zsz`(#`HqqACe|r*D
zQi9f}-0R5_JWDwB#Myp3ORG`S$;mr4EY(Li^V-?YQn^;hL7UsOy-enfw~P}BU8c6Q
zN~1Qd;IGUDh}B19KR+#3J9ZUzNVLH7K3F=AUA>terrfX`S<unm33Bi^hs)KzFOKeo
z$_)ZiO3_d%X6EC{-8nJLtx8)E0JXhHL_?#etNVktBir$is`)+QqocGD1|psmyX`5a
zo)phZW@ctwa{Q7~YX*iAsP*|%!0q5)hX<ViwskK8Uu?&D@zO_d%^|plx^OSfA6-DK
zim@@SdO=wju~2}a$ur1brZQoAUvArz&IPe(RZGAm97z?$!D8CpR5)rVwA%4te<{|;
zbR?E{?*C%zEu*SzyLMp|6(uc7N=1;6?p7&jkdjuqJETPkY3UB>?nXdDy1P?Kx*NW^
zyzl3E_q)Hn{y2s*WGy(abIy6xOdmbo_d}P!ke9HLzlD_O<UoXDDl_yZ=a;lb{<A$H
z0YTp`Y6NMnR%Mf~RNTDNhyphNWIqy#Ub-?vJMfYtJU$3NAu={R9#~_A1ilsoGv3?#
zvwk}M8U+(OVQl&hB#L0Q<Xc!<(}U8Ad{<|tq{v8QUJQujsoI&txay>*d^d=BW23@Y
zw8ok7@h9KHKO|1}_V<^ZYs5w5t5=p8wjsS7`y01AdzPzG_XPHr{e0;P!yCq*5rir#
zQ8g$$ysf)i7oOd}Hudd`JT*)Ng_1ZqZ<%UoWl_)alH=3gZ`qy%AXK!?3l#K64Yi=p
z^;DOP;fSHE+27yyJd}u4sRE}DQ(e!++0oj&aq$=iYC1Zw*CSC7!2PZ6<vzcpi=;#H
zcaB<s>;z&imxgpZ60fv?L(DFR!#@wq>FG%q*k&+3X~sba@|+l^7wPksv#l?NeVRNq
zRq1JIrsD+)^70-go!#A-+}5Lw10CJp$6EVbdJ^g=+T5z&KT#<w+vv@7Q(O2zDpd3F
zBx_r>1OyCI!-ZBOw+<z4VG<wy9%GtQ86F-Ec`i9hVm|xYoF3X*Y1R_c#ofaVM}Apf
zy&hOHBklPY@;NR>?Emg4+b}RNXb7)9+U(QX{Bd)t%65l<$>&4@lZd0rrLmdmd0;VJ
zSXkJX9uyHVtEel0P7-?y*sOHBz$T%q0!hrAHk*%*PKpa=8-BenAI@{_iC5~hl#FF(
zv1#svi|KIDK6<%-5wy&(Zba&x)#|QJoyEdHf9;?uY>sXp$|m)~S{o^6o9O@UJb_KE
z=)bea=e+xltmgg{9o)XN>HUL)6?oP@*FG^~@xalT#bR`6NP#pIX$M3zi~G5oyTWm;
z?}BT&CoY~-=jnuv{&6cqr<vtZ_f%-8s}>6^XoPDgG4ba)%FZ2F2rdO>Ki$d4q^+Za
zfLZ(9Yt8wjlf68RJ1!r$Se?&3G1f?UY@LqcYXoVZUoxdC_N#7!!hUO}@?dsz<3S6i
zk%1wtM&;>v>6$S{LJ!H>m7;>~@L_Ju=2WeSSlT0O>>;v_aE&^bFS$WML1RVs$R>@^
zHUxObCl7yPGY`r={JjV*A`}%wMs=uGR=en_1LvQtcJy<nwzf7D%v<nOTAy{RZOwSe
zcBFNw;L<3OJK4c6hRb#XC&p;#56k{tBd6`{dpcxj5ih2yoLg$njwp}s)(TSg!wO{s
zY-VQ=zA0Z0==B)1?YFjeK2+(>WYWvH*sO76zW8HvTLOjfwziKg>?ZOt7#tc3B<7sm
zSj<e%?pU~!*O#4=J~Gs}FdFny0>eLXZ`q*6*cq_cA17$g)jd>uV`{oNpW0zS`U}Tp
zVJTOw`tXHHq0iylH~Nt)DmyznB_^Q(efzNQz1(<0va%;gtA+1ZQ^8HB%W~#>hZ~)K
z*3s`O^hIoKSvOFlr*X{_Bc%kYH&uJ>Pha&qAVc?pg@sGaj%)1}&XlM@GMD-l;@%xD
z&wpM08Md*pk&%@R2@6XN<g@tU3T+?gg?*Gk%EL7<FyLr?l!U+dTfe+5Iy$m5fz4}a
zy!@&I$8@}khK0psJJIdH*!cJ2qJEoPvEGP+fx&8A^_72fMqzNg>HFF54Jv4SvH!L@
zgowzDE8Y1}1MA2_m&PS~G#u};nd+;b0~0O1gPOmxO2t<XR{2&|3Li8?bkmyNB464+
z@4^STlPH>FK)|0<A?hjr-O#(agFUVdpakP|uztWw%;7LORO4(SHZezfu{q<~%BnoZ
z>TtH{ED|n)!d=2J^CCI<x^ih#`O0xirq0^npxj}qw-UxU0o*%6CnqhxoN3b-SXoVf
zM_SnA5|o$@xCIoAHrF=_ZBF6-4DB3TEne|bagxy2$E)u7)jO_IRd$bHUUr_?^XfKe
zYF=`X({zOe2hZ;@Jl>bG+i32Bg{rddulhWG{Ahqq;G!j9tkTg=S@|?lh7_-!ehxpB
zQ%OnraQpCn+z!ks``p^wj}LW(gqAWGwCFS{Uw`+^@@Zc_{%BZIY*g~G-U%D~)!nGL
zxMIgG^#@uZaJwm^l@4YpE%YyDZ#B+Tm)hparkAZWP_CRDGgO&Ourd=7-;*ThEfIMT
z*iGbn`q1$R6;m@!JpR3|uEOzDmVB0Y0<X?WK@gYSmW7>}S^>jYNvE!aK~$W(PNmaj
z?Zp}8#G^H~XcPO>^)YyVt9L~e6oiySI2b6s8|SR`M{Hq0**~M4<iJ_d6%`d_((96W
z`?kBSEiEoHC#S^rKy=&yK)}FwZV^%OB#!}iLMc`{z67;ueyy`S;y5ywShyySHu>nu
zIFw{$f*L<ia3^)@kAADKady^69*uTByS^ekoL-)9PRqKrw|#6#hfhE-k}JEsn5`&&
zkC^+TKu@@W22t4faJHVl{_*cs*+ZS}Ut;^lT6^*s7Zj8@KO8n5Z7}%M;MI4<SE#E`
zEz!NRzSJy$(GX-8iQE$v_C^2+9Bz&`J4LXX=F+_A^q~9F9h+FUMJg1i<HEsN$8OQS
zUs<fjY@zRTaC(sPd&Ybr!ucAC!G`sZXU3Iy)>Lc}b%tG4*S>fWP1aRs2wmL?f#V-|
zV>7)m9ePaqy700x1r{{lko2C4tARNpm;1o=z((W5k2=krN}&|~j~JjKUK`0*oh*gr
z0J#&ezdj{}Jym(oy)A^Y#?r#T;$;4WI)XNq%POm|<^py{h3Bib;h5j(L-XqXK?FHW
z`8x}kx7L%L^qTkE_J^mP&wiEt*;_u223RCVCQdyoGYfJp<pIFTkRKQZI$uCmwlP)E
zH_4DNhGn2{IISqKuTQ)UDk+#5g8Q?<cQjSy;?Mh#$51Zc<?(j!2AAE~BOl|HsPIa|
zp=dCO4Pd5Bv1|AK3=JLJd2oZoKfn<ru6eo15@R?L#$zQi0Z0C{OeM{*cP}k9O)`pk
zZmG1RJWoTd(&>(Kl@7Inr-$?E752sI1D&_Z%F*k$3e;;|BziCinD442mWGiL?O_j5
z`w-=*MN{)Wj_~w6O^=LpzX1ooqX*mNolI!r;?h#B<JDH%L>@8m!;L%n)S%R%2n0CF
z=)I=P`f(dXdG+3yKwg91-x&oxPkkaQOogk=XlTN2izvF>+{SEXD*dRnPirHFy@q<F
z&1K2>ZWoJn)5=IbzmHPK0YQ1Jav4tT{`NYMAC;PaC}DNq;hn&*??qR47SaQ{qN}Pa
z`#F9M=c-1t89h~ai9!PyjLsSU#&mU^x0YCk1BPOrdQ0s@s>)H-FviNLC;TY8H7Z)m
zgaw_qSEuT9)r`ie=Dy3=D%fthAg{d}O5n8$SfSF7u+^VYDDl8VGm^_Md%w9JL8rk3
z(@lnu=!_5siJ_sUYFC5P@9poJDlTB=T<XpPlM%B-3k|IPP1^X55%BeEN;ohR1Gmh^
zi%go=>kN`igt2V%Iy*b>grqCM)M-3r>-w|qVh8tyvS>mmZ>WCrNFjeUL~Su`haiMB
zpUf)k_gF97(zQOjIG+{l+|UsMZF<U^Y`LS@w0D0RJl;RhS|CHi&B)Ar>+7;8x;B!>
zNKZdnP4~ER_VK3;&W8tc{2CfF#MA25)=AmfvgML$sIQ>Ap>jwpaJ{;Qs(K4+y{EP$
zS1~Y{q^^(DSNUuY_cOtUe4bq8v44(S=6xPM=Tkq*sHPMFG&D5SZYKv@Jx4s5(8H1A
z!jin7KlzO@&b|XhTxK%$E<YaQtiL+uIS;tc7-kl?`?R3e>_6C9ANO#fC=rJ#5tk-X
zSSDzuV#ioQ{|yDtn*Q3??#R0dk7;Of0aGY@Y1{L|mG0zYxhS@*119CW#JdSSfs_@f
zjHj|McvLR(X?eUnYVO6b@$l29Ia==4CCI6(2L#j2eV{n!9vkDp$5*nB29xurE6)ZZ
z&db8GvXXM6rZVfJT|Xz>`QM{X1E(y^uy5(5(Do5+YPDjy$_SmkqkX{Po?gDEn3UK|
zl|A&gb7f@*Rra<VF0bize~5|cMf=A4YM3Q^9vDQ?Y24|Cn%>N7f7)4SFB`2OC%v*b
z@P&LOG;#$$E#>z^QSJVLItw!$G_*Y&$pGunp~Zx}HC9%ISGcq}O65;jStUz?Wz8Kd
zR(He9W@=O_ofzUiCz%@_MB9Xt+}xbuA9%G)Cp~t_!$mSvmzt9!K;kn+GZ+~awm39U
z?!e+}6ww_>%pv|U23J`IT+B!7lcGB_an(no%|~-{LHB}e>NZV#f+Hf>7#MH}l3tbc
z4L9qKcaH7X3t~x(k>(kVm~~z{!XD`uXnj`I+Gn#AGA$Q1r3viH>l<&h`1@~c=zlpo
zJ{6BT#+4w%IJX>{JNA|Z<Pj5PQ>DhqdwcgM5Qo-x9e4GiST!FKRSUX`vzbocS3jq)
zz-n~$LV!Dkew{hT?kR&M=(k+bdf7gcB1eR4*r>vqd0kP;+1dKo*w_G~3E$FzAXFlp
zuLmuedMZ-v67|x>p9elcKd-4m!5LL9O@G}(XR1oP?HT#A{^HLKY(m8fa&J?X-9OI<
z_YMrH)#(luHo9>K@yh!6e9qf~Vs<Zguy2@^f%RUkoUEd(f<oF4?-N=uLWBne;WHS2
z)z=!Ll3zWsd84oSiWcW!hm;50xMC&bWGwRR#NiZzI`t@l0VmHaY@o{F)o19bFbWDi
zjo~=k3M9FyHUu==iv3{gy@&o6JZ7&n=j)V)8U%gEb|@M9>mD_Ti->SM334I7gMKc4
zM}$(Qk3obo6DHJiw$RqWEcxPif0jj}U!j%Nm8?d860?%}8>?e#-CP8;ACj{3qzR`7
zzzho_9$iC2LbdsTY4KO61LH%B>y?kw5(gB-^qwmz)!$(P5Rvz$Yn&G*@k>`%j{{r(
zN7AVLQ8GKesn^@PSLmCI*CH^5OO1w9YqjUVdA1(IX|p=av!75xk<d0%ZFV)6+(MbI
zrRe;4yTA;d(?1jaCp7J=lJUGMgUXwemDIn2PCI4-8<J1U4%}<1fXqsndSjGw$5vZD
z?Y%oC01|>UJ^|70Y|^xo?5@-6$}C0*LqdC5UlDe8t+BleqUEM6951qntF4_CAX@x1
zckkY%mM}2Xy;u|s3_H&EoO_Ckim(W|OUy54ggiY<<Qr;0YA{o7M~94jQD!nJc$VAI
z)`q{Lh>6YNulNyho?tRfBoymu^^+1$<9jCRvx|Pt+;{VdN2YhCesVwntE^~Gd|k>i
z4Zv0tS3{qojnAJ9kH98oiTy>tOxf-P4cZNk|6l=iA7|e`cD(j@k^JFBMVVz^Z|{3i
zp|V6rIRypD9UWlZ8|LpPF`MiJ>pYi=>u&FE>sT0wYUdVNC~9l<p@S1ePP)KV-TcG(
zEd21LuR<<aZA?&5W?EMJ<~zV$@>%(ng$jZ^3S=JTf5kG@G@dN3K7t|s5t~hps)*Dp
zbp~$6;Fb`B`C0Rmc5F^3ZB)!DCx?$v75vM5FbC!3ho*lxi@D(v{p{OGIv?r#u3GOC
z91=V<G>Cs}z#jW{Kj;QrYn#xE7!8|NIBxMym~aCh0Wm!mH;II`!Rhl>)gaH>pheZr
zWXQ5Pr_KwDNSr}|t%tT#YGM8N8!S!?R=eqjsN!YQiQUEUdR#g+SYmp-%@BQ^J?%Z=
zm&^gZzAw(@-uw$mILDOa!=s}a=GD>T5sloO^Y=IX_xI677k!i;5)J9&aQ=C~ih5di
zcGkB500^=ddb)LIvobx!GH}|IRSqzm#jN~-S93GIVlJ)fb)vVA2t-C-X90gjF{!1-
z&mXrjN=8k}|0H5X1=Ys~=5Kgz5IT@qf>A<&7vtZ8g6;)8RDT_Hvt|tKx-eOvt%H(C
ze(>i8MXwi({Tde@Nne|C48tG?Kv+nqPbuHG{_{=)3dVX%D4yf(2259J^s=q6_yAg2
zMo6WHI{fkS+{54BU#;<$HF{IXLSKDvY~@~Lf@e2He;;u~2lhlrO0>u9u^&;)3u;+&
z0SdY!dCQc<3{WfaH=TYU!&%3dz{pKf_yg>-%Y}pE5z)u(?Q0R#19`a<pIn^D#iN^V
zSABODVQTRs)=}xPU5=j$B<8s!B-xtp*WCW(=6rgGc27=523sv!uKpKhlm^KO;3lDV
zmk-DT@mN1D?veo?FF~lnm@3?&sL9XFoM9$bh!%%YWp`B%Qh~?>zlO*8rfMLTcw($n
z_VJpaW%9*27RlsusF|s$m8M;&Y$FQd-)V4-`iA-fD0cK!si@jlS6A=Pw70f?Jlf<T
zy5>^cmv?W2CZ?c(&G-{bw;3~0jrGBw)%Rw?Vam$NrG`V?R`YM><iDD5%l9`oH8uay
zkJt~T8OqMiWY}i<rwNg!!ON#QSmXB@92^Wr{}dJzL%lw%o*7IG8zUJr)asp)#j=fX
z1A(;AxQ%(ZyIy6`f#YL_j^QWD>*)VzX!Ylcmi0cc%+b-oXC^wjy8UB<ob%@iIzfu$
zOUteYm4QTjuU6$d!f9~mB3q`dzWt!GWgfl?2!N!t62@XiETR{t71BQac&~(i<>wUw
z9s9##VF`@pzi4TkcK%?ST)~h`tD73o6*ItJ!tj*wt(2mo+QrPpSc-_2!`I=Ilr$i_
zqMe+thxg#_UtieKMle;V&$zg%W#C-Ac;$sMH<wB*5_iwqas-5mqT=EYZDo`A>NidE
zw3-9V#+zPAZW4TX!tHqIv=nQ<x7^Lh$gC}jcmSY|uMK`DihD6xVUQh`nz~Ix95^!7
z5fWgpkf+XNdE5(ZQjThAc=tpmv|mko;F9V1Y(a1E#mdr>^yyO!42)5H6O*;Y-4obr
zW;WIU3XR3fFJ4{IoDWN{!MK1<!yK&38*(+jm@RKK-1i~H{9{goKZJ`Iudd6b8iq0H
zbx+k@NwZT>#kuCn)F_k8#3#3$Zp{=IJFuW}7TT?}_F-;}_wT4~r&3GAFzW`+Fte~|
zczOCbX)B#Z!fg`CX@9+j+j9S7b=jtP-%96v3l>RNS68GNhs*p!Y&%-!lv|-Un*X+<
zz5VxN9Z*j=L+{X4nE8J5^Lw1yzUXRWqWt#leXh%U9kuT}zv9xVGtQ)Hc^zhD8G_)+
zY41=?T--Q6p2t45vNzC@8C7GYz;gPthu~0-GGOpDxw+L`6Gq;$^u`7Xhl(}smR6QU
zg39r{573Wz9ggWgIQ+VOixEr9h0!OWzrSD5&g{dw!Oy^(q#y1K6_<Uu@kQUs200ll
zvuh)!6qJ-c(-q3-g5lQmG~>IQ7iV@`(?gjTW=n#Obd;;v)uzwM$$qu8z`C=Y+S+_g
zUC;M#UPxd_Am+~NJ4XZ?eM1x3US>b*`IiI(R|L{}q8C;-tYD3|sE7Xi`LFk7YGPs`
zNg?CmWq^A$OpH{N8J<8$M+8py%;cy0nDgq9Nl6W!5-OcpBddRgLelhbCXtl~VdFTP
z@#O3JSlK<@Y4!NHY6pU7<r3Sim%=*6*N9j!NH{Zs_^syDZiBpWYNC97yg1*%gnB{<
z)5*nx-?blQWMJrCb&Hsl-U#qy9j&eFW0ewz34M5|Y|SmtD@xbolFNp|O}H-OdH9WQ
zgPZ==GjcMssoIb-b7*(<x^E3-8SxX;*-T)5z#y|*-?;5z_av6f@fOhy<%w~bg_v@)
zD9xz~i;nT}xAXMLnqcIzSw9xJRg3nQ)MgvZC0)s~x_n(Q6DiZsJfK(ms34@f5(EN#
zg2KMGmE$#z`T7`ftZ>17mwgAjX=NYa&l`5WbLCuv1$*@NC-cpW$y(PPt39ErP8Zwp
z#kml2Xi~_E^71(L>L#$;XMv(;dWu^RixI>*D{qX>4&#7*slCac#P}I)=SDoY{p%CV
zn7ZD!Dw+v9=}%<b?nzdG`-Bm9&Gx0Rl7Vom+`Eadq^r9sR55Fwa(o_pAE(^b#D?Lx
z|M*VGaK0K@XZMXt^(_}(-f1<S8!hTWLZ4;x1M6y&HA$;)l_ab_`!o9r*`4bgvO$65
z-bcP4-e>UkG%{4L4cmGFirELOglTwelnRXt&25-;yVI8QuFxSDfM}|J2!cx-j1+UV
zT~YMy{0|8t;^Gz-$K;LAR=2Ax7e&`+l>q8o906CnphlV5h$pco%ew!Dt?5K(t@ai-
zyG_4)QaFd+60^hCvdHMjjI4|jOM`kRG_J2)vJO|-D$m(htmh6<>}n@<TYkR08e5>V
zLtmdPtZCvEX!OEN^V0XNb<rtQ8-%-tczwUY-b!G`aABHr<uyG~dLiA6hiJuz!lq{Y
z0rCO<9E$^=)b$%g;jujSp>e~5gYT*h?dQmPKeTma*C)|fmrx#lp=Zi=AY=a;cepay
z$N&5Avzu2yMY*kx=<H(l2&5Nj&Q>QPSS_b7CN&PFh9eFnmoSNQBxq{FeDGW%%Hecf
zsn24#QZ+Ai@k&!ut0jPdgn;0PfzttYtDj*KW@su4zT?-c;jXp?@^Et~eQWL8w~C6M
zn_oV4bK9JDPS~0GO69*>|CxGrxCQgelFuYVbS#%^tu9f=D}GO0CPx;uy%VeDUcWuu
z7lwW9CIjInSR_0Sr@vS8)Evj{*10tY@$y0k+ZV;C6|<U#W%UK`h>42+X%G}!;qODy
zC@|l-ytwwz@(vxTv9Xy{4}?0LZqEVd^z<fA%^8ON0y&-v4=d|o?)!&(!OibLTvd_>
z5Q32F>3&!B15Pdug{&02i)Md8--!O{G@cXAXC-zs*XHicS#npp@|v-r#_+m2Ga1{k
z9Q2V2_e!;Yj~ZBL2~1AnH6E=nXlQDqYH#m|pv4K7h~rHbu}b&7ip3}^DoIIh^R2HB
zNfS?2dP<t?aIonJaoix@8D%kS9bQ>omCx05xH#=vWzv<Ac=vAf+Xqt9=^sN?Hq?%1
zLP-;M0hfx5lrA?Vf*TA;^zXXmO{cxn`rW+1{GL9o7BQ~Y3o~J1Z<vo(#}_B;2vU&g
zF&kHVHyv*cAl*Xn35m~ex-Y7;741X=FbTOMfg8xkDA1Zv$lv4<Fq_~u%}KDsN?=<4
z{FzoY<q<yqs%%T(ss9-@+2V{*yAV1-!=h-eQgtnVI<4__K@opnG2au{9?CY|(RV5_
zG4dF9FxEB}8l7<4oiT|fw^oO~Fowd<?`y4&wswimz$s|-8gRxNa%0%6clO6i^|q!j
zuI+!PDCTnf<1S`&R8qp+UO*9SG+0n8yexSQ1+&c3h~Gd4cA7Xh0~Rs~R+P4Z^bJmj
z&RB+Aw_FpEvaYUD>_v@%w4Rj3SZ-SZdHK{xP1F(0&6$bD7CYd2KysEu^Svt>L%m4<
z6`J1jG9f|1%2&t}6Xjbz7-Nzgvu8(JcAL`+t5YE+fVXSZ>FVrUOpoL!PuC{5%#jMO
z)|d5CDx9Vyu~ge_>TgURBJkn&Dh@}7L_C_2qe=QPt7Fr76%*eOqT`Mn2O>_RQs)k#
zv?STLZ&5j|K2w^Nl$O$Ju&V@%5}9oHzDmbCR*wxvuSWx#>i-g78)DqAtBVgNd~kkL
zUd<9FZEJg&F2!K5x(fU~OgJ}hdR!?@w72b;s?|~Dw6(T=^*wu`{D7D^C@hYK^_IZf
zx0d_qQu`=x)FlG~<lNbw>7vpuIuhM)|Gli3uP!mKYrXP2C^FLea?+rWAwBZ5*fd1E
zCuU?&5VDovmEdq9hsTGP*-m)^!)miRXtAAm&7mrIi~Eh3q`0WKR8Jxn<TUYTC*JT+
zh@qZ*efqeh1gzpeemI%XNcexA;E>hbU)tbO4k`?Ka+CkV2T*FJW-FW+^7UF~Bu0Bw
z7I<{eItK)%6K45jdM7@9CihCljmSMLxE9uV%d^P$ef4)b#*2#$Z3+udyShiQcb}l?
z4=`^*$rqe9>-1Kqa)mvDd>-yi?y<3|f;Vr{&`8V)2IXXAU{O+1hEd7i@9G1sMRIcT
zYWfRmYJR2omC=pY`;NOi3lWdx<x3kD76;-j49BRRJlSdgwU?wAe2HtKtL-9wmoMJF
zOepSTAvH~B`=rvx2e^O8?frkUzi3E05^Yz3LRc@5C|a0@<cH+tkI%Vpx$vU0*G6Fg
zyXHGo&`9t7T|6aYQ}Cgfw|_O|pOwOee04ADjd8&jHJYdn1eqCfTB4r1dJ9xofszm3
z^L*Sc$k_jrK<3IK7xIo+cr_+30Fy_6fU@MiMB1|@3y&7tRHl#n-`FF7b8YgF%S%zL
zd>iDtyRq>IhNw7p3(J1@x~AqIbW7<!ANswMsR#;xZ+z~be{J9Kty32u#(b^;B%B|6
z14Z)_@nD!%rM;-N`j?K=0tMU4lkJtAg%dPfBmE340`6}ouZ-7*jEv1l4wt%si4D!7
zziIbMm+CG+5s-p1;H6xkFQc?#6&D-JXy}&!?OwU58bUF$s|EbgHI(ZkW~1C@^-t46
zW7Q_n#XDCk%^d{<v=c7Be5O<TAiCPxw_w8MfETU2etsIyfrO2RV2>%*4oSF2+jDaj
z?GpA&N?=1k;mFDbMF@F7zG`LvnAI!HE<&T>!pR~XYS}`#Wk5Pm=-5+hG-66$hn>&^
zS!g1_)HEL$4avzP-U}apZ`1=lNx}~<_~sk;{(}Wj(9m?P%968~4ZB}E*7~da+LFsv
zX0c+jT3QCtzl`)Z$Re1m)QT~8-zE9g+PmG<M;h|{a_Cp%7h+(T#XXn|8jc-USvwT-
zBt=AYToPKO;<=p<*XgbbL5-(38`0X`4G(2|*CI&YwjT)m7i5+)OMpv=@upg(@X3j+
z*cvMlf)I1URUThuTK35=EH~2DIpM=ZnOT{``urFE=xFT}73-L_ObvVJIx4*=ZFzRI
zuI+LsBAjNW{+yXR-k7b&$4QVNqGPJo=D}XI%nf|Jf<QM7iYJt0Jf!>}>z5@`n?^#q
ze9)pRabRu3#CUTQr#<V3!)ck}nC5Dd{gdw>0HqzQFz@T<=DljDlm*stlg+#}Y}N`D
z6;+U?*sDCkCrgx|d|0zlSiQz}YABTq8A;=>>*1Y)kgk(v(dQrB@Vooez)m=6{0M2b
z#oW@EcGz;cTa7YcP~*~tS#73_c;e&cxrcm5g!JH0d+INUOM;EiBRQG;G9CM?s}emM
z6Q%cz0-bOhkY4`X-V669RJ3JTapO6HEtpAfo2lodr9C1b=s^03^_f~1;T}PJg|MP9
z*VCu3b7WLh&IZ!)Y&khkL&C#xxVq-d+Z#4MU2A7SIJdFgLsMM)EK+W`er~8+ddvP3
zFye&H;WBmF1lPk!`)El?$vd^y9^}fLTtw*H;txP{aEwPZm3SE;hGt`J{q$+_{Ra=k
zihc*9&#Q+*(*o0%pU>$}Bsq5WT4bb*$Dxbtnl$z&`!7G=#3o6gyL41Pc13~HM<N!`
zGEw8)k;ikEHBwe&^84rV^4o<-nMNiiCZoZ^-97OBZ&1zM-UP}ej>{&)!~ocm_|RC@
z^Wc2-YTET?`B3ca;r=9GD%f2bw4-lhU}#MM*$Q(N$lk8ClOkk*(yub8t%CdOP9JI9
zeb1nJEAey3oNu{41u0@=OOVv4+eLJsD!_n6(5gQ!{Mg-Tu>W2(@!6LOECR-F#2ynG
zwGKL_y1E8R5!W)z5k{HB&-8=$1G9E_Z(w~wr7M^Il$!7T8+yM>fpW7M829TQ=B0Z1
z+(z^dRJYHfixlG*zm{$9{rzfc#UH63YzXIWQ?ycVYwKYDCH#+>I^&o^u4N>C>i|AB
zEi=zh*DwP-Mo5j!R|&^#wxaoY+zU)d*vi`rld-R_h4Y)>-@+3Tkx}PYlUEP;A4d*+
zJ7ft;GW#71SB1FNUpz72uP1A42?|>_JzCWMC!Xk~;1@ul6X&I6A7T~oHZ8ZL(<5Qa
z8{XPuQ2!w#641zxg7C3?Czp)EF@J1+;n@WdmztNzFmI9Y2{ENI+nl~owwXJ8WRn9;
zY*as&!@7IIl{=*MS?{kjgGH&P&`#r%n>Pnfj>$%|-x>9jC*PSnw1fiiTe`b>_4j-z
zc`g1}!ySiOE}J~+C%D1JP=W>AIMdBDCMIfMw<6dEjr8(Y-<$plK1bSRMkH(*AoKIY
z?z_|w8Fq-yk-OjgkH`r!^5H9)wR>MeiAyuqH#WmPq1E2n+z1Mi0r9M+Xq(yo?dUk?
z5|agZWAJ=Jm@T@T>R(YJTpB)7Z$u?J-Y0(25EeB3?mAK)-{btizi{&VbsxWunU4zG
zKa;L*l3NGqCB6jji=4IiTTz4zoUi^*=~|25S+-)rH5`^JJrkpr+uelPQVAR_Me6)5
zIC&AY8Xr357Zw~(4|C;5baSq5%>8H-KD`OLigfs(UY?$X0}#h!ZZ?t$q#D)nF~ceR
zk1#ODlo`h`oS8-IPxO7EiQzTEtbz9agR(=Fc~mH&y~CMYzRBXk#MYkPD_kAroVYK^
zR~jMXwqRzP;-loKJeCrO8FZbMUg9gDXIq=fMy!b+ivZn@+5Bj*ZEO3`T4d5uj6eyB
zeqf*OfH3>VmD{DimzMg|iRtx6ql#Y{Yve*dX{e`xNyKn^uy)s0-TQ0<;2TLA6|{)0
zxv`7=C@b_(lD|K_e-LL$G2u@K9>LtQ9q(R0&oNo<yMsoRn2Y=DTr);KTw(V6)etTr
zrsq#&q+<pkZF7~9AsRTfMvb)Z5L7mH#xsX=Qv}s^rl}DiU&p{e<GNqry0lLTuwP4a
zv&=#XzLlK39GwPt%filRc#^xj=UbP-iSp&H?1<R7==AjT;;CrRlKxA@pueY1myCXi
zkRl1_kuY1k1C{_JdA@A=p+28$83XszBm-HL@n>p88$?`31^#dpXkrOLHBx20Nm1pV
zfkgs7loqG0>BmmISN&nxfGZ`g?%~qrfd;C6a?I`QsMosp1Wj<GJn0AO9i=*5vLW#}
zUf+gS&{&)ft_|my8?1I74!xC=OJO`D<3ZC4t(bYll9Lb{ySqDNlr~#b5211#tY)GE
zAX2Sy0*yD%cuFOnQ1N<$MA|hZs?ZN6zfWm!w@fVNY3l+kB$u1<aBfotB$rzTPKKK6
zOs*VS0%7tqaOwA`s-`1oTh|Xvhq9G=t$x=3RGVNWAi(cS7STEb+eWqRs?(Bc?+z(!
z_hvb7_M5D7)?+Z@aQe+oldE-R%d9ruu>!5^@!`~&i?g$V14P;C4jJkJ;#dMMylgR0
zo@wdm*k4^DmqnI^PrdKSBThoY=WwFnsjZ~-cKoujFYq9ZyqRDm|GPJ`o0qfWfwA;V
zcv?*jw^Tgu+WPNS9N!JLBJ&+ahk}7udXfbj8{-vwAB)JFg+xVt7#Ip~-8$`beaZE`
zG`j=3m6B~Hy)RHzz`pR7EA{<Do4%&rdSpC`Mnr;z9EB~5wlPi0)(@PmsG{RHc~y)p
ztFFg-BvhYgpI2I8{eEa#p7V670_QU%l^ol^=-@suHZ}(KLbb{9J1P|BZJq6+Vq&0L
z5~hQ8XJ~NHM@bnx@R^x+_S8U{HYg`QYQRA(B_iUzv5}gUBwmjp@y4oBNolN8YG8EQ
zbSuv!iKc`Nwk!!^9qK&rYHlbOI3nmU+yB}y7UfgK$n}JjrfbRKD#$21oJseB$7$ug
zPa!a)9}-pT+3>+LsjK?@W>00?d44`&d$-QgdQYFi+#ri!oj%1(d`(YG4d3(X-o-DB
zs=7afmGD~;1>~-35Op^wB}+?~>0)^@zkh$C4A@<0aI~oReKJ)Dr!-FX%Mqu&5>uQX
z{OlHs_bMlu2p?PiBaQKOd2SksuE<e#-UO+b(9qb}=xEU=GTPb?_s)8!-<9in#295a
zm|0vkhB=Up5eUk&0*qcc-JzJjHRXyZvbWl?{}#)>LFV~@)n^~>uBBM(&i+|X^s2N!
z!NWmmPdz_BM+>w<$!Qn;#!PXtU508S{;lUa($B5meVGeMsU0Ub+XnY=>Bi18JVIpO
z*W>-(kG<;o5Lp;BhhShC=YGE1n5azPapdKG`Z+Cu*O3_K(9>jOaL|e9k@9)g!2z{m
zF+HE{`LpV$=}TR|e~UURUAU4osmU!%5<xUu^tW%&v~wH)X}%=fJKXQ{^=oHm`>C$Z
z+=Wn3cy-KLWZ^;#tHtrsCHQ;$Kt+L1!SweKz2u4RP*Mommf+=zz^|jx>q(vLG}eA6
z-L1X&d#f&bt&Z%uY(wc6akU2qGdPGXB(vqaBwWg`)az?AL)^SiDEO{o3F}F60VqP~
z>4regLQw7=arbb26PtiQ%-<`JkcpL1lK?^+!fE6A^jmK~D1L;Dg0-+ydv1V0zPTDg
zw`twur+N3^NcG@xTR)R<@(W07mZuJ1A1kj@rs?plkHG0nXbe@qgJMDV1hwx+4L6tF
z0V{JUOwdor$;%?=J$xey*>F-?K-A`&SyEWm4|8C)g33qShSlPwUdaleLfVIn4E|!U
zMcXb~sCiGF_K&^A(Das6C@fTJEisUFZapVip1YPfc^dm|pMw|dyy}W7U)=J^(wDg;
z-iY=Dp9gYFc`EfQ4mXSYP<xz}zEW!G>2N(JH)}dI_U^-$nYHNdl<SjjHsG*eut*r_
zXJTQIV;O=W;?wTx|M;3~f;$QBVbieEy)-sfWqKarSf1}(j4}*ZBPD&*(a{Uwyo0Yu
z{1K8`Dst?b-Ki&8{ujYTmd~``DRFepvWzKH`2~hpE27}1ypv{KTx3GYTQcQIcn~6|
zs?<v;FMsp=zF1;f(rYYYEaV9&$4-SdXWguuxnh>iuz&5S++_Oa%P2QuaG};NE-vn!
z*rPvu!uh0bFZQ?l;Jj@RdIUrN+#pj(R@QT!oJNM>p#Hb7aFFVRRV`gU8c&}^o|h-=
zn$~rr1$NPKzpJLWNxTd_nzIDDv-~q!MN!my;A+qVmp9)xr320|s#O#4It(^Nx)ohR
z^m;E}O2s{37txt*|E(A#sQZq?iF{qlWmK5AaU1{BZn7a+rhj9Y&7k?>W9ZC7->h^z
zM-NqDUxEgC)>@8ZLO8pmC`bp1>aHI3n3|USH$;>Y()knfQ4}QU9m+N<oCA5)NsY|l
zTbE;AmQuq0#RY-$MVCJ9yA_O^|5bkXRo+LMt&3*YQU2-n^MHW0N2TEF36bGop^vve
z&4p8EA6P@rpL08$rz8urrR_iKc7Y;4Y{Ci6#ZdZHBAeMX<IOX#8n;<CHbhcl$;-4G
zFrDhV?W<PsfWu0G$Y~W7+4a5?tUvhc{pWo`$wKqR?Y?<oFb4~NX;|rt+CzSh)SSnQ
znxs|^o>@jb`xGyN+*3j`Rw7eE<>2vZuLKC5ii(0>=O<{JoB{gm&F_gLQ2fDNEg&Q)
zv#^do@N~u_BRiXkPx9Z{6zLM-0dFtd_v<`v`dwmu;~g1UqYlo2?2pQKCdR_{97;{^
zq)mJCH!}`V*>E#yH?x~U>hn!SEZ8d)v5<cDG(aw*M3j1Vo_~6|lwy9on^&Cx4R6gE
z7@w1DVlbQKv$61beUurCi$G2}l4B&{f3(G?-QgLykH&ttRg#O@3KIh(+56fTPmD*L
zNh(L`U2$qsv7BACT+YLU$Pe})hBPfT9c{#PqStM_#^IQ=x`M~?FxCW~K@net&EYcJ
zk`G<6D%f=wC5M;DUW}>bHWL9rdzBci<>lo3{yq8wcx6o=P+;lF&P;dLTa3gzH#EbX
zY5Qkhexl#Dd-A4n$0D`j877`;O_@A(xvg+u+<T;F^^YOt$2Ccv=J$`7z4_ohsp+n9
z7hYd-yiY~KVjlc;872hV%<?JP=IO7XKsrMgHZ(BQ)%x(g%HcZN?K>De_UF>?Mpb5N
zk*jQ1pS|F9X4N16?R{Wk;#i`y`X4OdHL7N&hi~}O&IxXJoWt?9MV%Xe-i-uViYhv6
z53XyDcFoV9RaBMd>uG^RiOHt_hQnZn7MVg+LIike!=Xi3rcwRj+|j(gzFyBS9DvXB
z0~o~tz0P~#O79}~K60z6#nHxb`E(OQK3<&TQKT6q_t_WWz|;NR52BA(&ON|+wKZMI
zLQ1N2Oi}k|=!J34&4hWddJ_!i^^c6e9!K;=Yty{k;1Jm=M;n!r_q3^sKmZfPu*tuD
zOJ!Kd^P@&iPJX<il$EuahWzRUf=IuVX6%m@eH6<}v*=j<El{FcN~A}ut+l7~Ly_g~
z2_8L)%Y(d!jUkKMDfna@Lh|0(shvTu^(+8=L5?Mi@hw$FuO0lATwEA*j|U>gpP%CB
z@c2I(PQL?s!;{GqwCr%Y@8{WJV!q%@ovF3TSCaKgQW$KmDFy8-_Qd$8YPCx;v|@tt
z4%UBO_OL31gS9xx8zMYKI^Gl?Ox5r_mx!wm?_({9nHwA8w>|`MWB-?v@P=Y&j5D*c
z7;i49n@rSpq^9nr9T+|9cBEZ--GaH1r4%_(5|fR#sAT*}@Scj6BUiNkOkUTo*^Y<r
zL0VH(yuZC!X0bQ?wG|OMj$JCk%TqIEkAK{VfOn1uEZ9GDVgJcUa)q!3q?aOO&z@yv
zQ4|jtW*H`#t?C>3*7|vS%iL4Q%528r>a5K2LFM|Mlyx8XtTIwG?6W8!B%OYpu4TfD
z38fhfeEyzQ4nTRz(r<==N-4c3o;r(hb5D=8P?ODjBanR5QfF>jI+@*%9MYw0bT>R<
zOnFZBoauASH*F>)kJ%D(cn^rTu`2!WfO1LfA?PkcR#e_j=GW>&%7p9b!@X3-zc_{j
zU`W3&2UdAlXe8dn#s=@|Jf&2U6$_#4I)oy7sYlb-DW#=Q+73$AXSEPNu)B9f6!}_~
ze_=*VfJ9aHOI!fu?OfDH$)%{g$ye@e8{?HTKWr&?)!u|rr3up9y);K0m%lI3mO}et
ztrn@>lXJKvc^xl*M7D=_OQIlS4K(d7(@|(?=Cd&a?QW$=e`5&RAg!xA)*#n>UQ}F6
zd9T`POI_<sNZflUM@CIZc?kwSX6N1gF|%RUqsN=br$;;xpei?rlJ@>FO<y_KA`<vq
zDV@fOJO;q?#Z+7bhZ_h6AhbKnW@_yC7#XS9*p52K5|_H7>2Ip#Jz_CV1TkDS1vmHW
ziW@{kaqv5CYHGS~j9YAb(Hv85$|P;^PmTwClu!Mu!$S*TX;i+-7H+%ep+qPd#MVZ{
zWO%IcARQiE9Yf6`=m%|Y9K}!7c={7A{F$EqURYDuSNA0-CK_+VXa!(!ddDSZH6kLz
zoqZg?$oTkphL0<6;0yrlDc?Up{R0PjXz(rh9qze;u>b1^evmykJ<N9hQh_U!V0SrF
z3^$p0p9&=7rb)#;b294vRLkRhwzRx#rd-$Tu}k&5MKPa${SjM4NC*LQK|*OMnTkSB
zbCqJkB?+&~I_wMYk~c3GaINbjR;%&%^Mj)gYzj85w3t}2RXS!VjfuhO*n(q&(K9mT
zV$()Yp*&*E=y`e5<MJb<Q~WO?0fwp(02EfDT0(-tn;+XDNvqdjqLpVDJ{#7|$X5)u
zCrwKFwR9m;<#0gAs{NRY{=}8xeJ?#O?y}}BQ@Zb<7zB@l;Z=NGCkZJzYnhwcKz9AB
z)6+0~3Pps|34)kES&GZ54RsFQUByQFBv4cYJT7+%M4a;R1N#Q_fx**f%==?|xG-|Q
zcPWRgU0q$&Th>_YA6v)UgHJ+KYiw(*S`OdjQ?aVPzWvWxl;(snhlr=D(5(+>P0%Vv
z&20Q$WdgLgS0HY@G)*G@=eY=Hnc2~dW8N!#FR|O#5}i6aARTxQ(ClySkj)Z2PY=|q
zLM39IO|8nmI6a&VpF0Sk8|kHo+dtAWNfF=kZOSJMQ2+?Oz90M+ma7N9eG9<xvDyDd
zh^X=a0%EVOa4vqq%Udf%M4k5Hdl#sC*9TmsL0Hjg#{nlqYNpmV{Dod(&g;Ld03;2;
z*-lOAEr#!S9TSCA5dNfG`SS-XahjKJikCaNY>$yV-RL_0n@*Ex4J<egt@_ev!_d#B
zAJtN3WfsS8>OLX6t(WjKE%){ofNPG6*=+95biAQZ0I|_b)9Tcjxwk*_|F3@D%>x1|
zu1lqy&Ge7J+IX4s$bUrCYyY4f_t`ALQ2}j&%EWk=MnwgP5FB(-JrfdG^x}(sV{~df
zzj*nJOG<w5of@~z8A;p;P^<PR9ypxfU_ZTL$uvR1QkHyMG+X6GJ5@DOYWgiWSd@T2
z5I}{ZU;n}~;gyyLoMk%8n>BFyA!7OKFpKjNVc8D&kr$e!&J!e%$N3sIjZ0?0vz;j4
z`v-EApH6;)Ggnc*CRd!tg6(vU*Ja90<1_r)@v?u>%(~3saJ>?GoR0!G_Gp}V`N&xn
z;4*Y${GSkSi~j}1lr2K~HOh6YT=mKqyK1c&_Zoeo*m!81*Om^zVKgy5ytXv92ohI8
zmbc-9Q`r-_YY{M<2%nv#r(HT?90O&-mZ!1DyPg`S_C*L|O?DCH$;>#-h=0Hi<-zf_
zv3G%lyuSxmt=z6TVv=x3ieLzufjgXFICr|*$kEt%5;A^9+aCxcuRdYrO68M?;Uv5>
znV+3pqqR(II98{(yl_??8Wy(lWuURGkb~u|U#UY^)lDlslz+v*1;sN}&UUAvA}xW0
zKV0^PVFtLFz(Dq^EMCIAcQtAt{T3nnGxYE39_~3B#bEjZuSri*sE_jN*ZgN#gya7w
zpd`ESSx}6>u|eNaS2AIq?*pR=AD1JR86CEK7}zZQ{jZ410BBo;yL)vNzq7p8^t&GB
zmx=gL1H?o0_m#+QEKcgvIQM&b8A^3@jC^S!t?A1Q(Xf4M8|!~WtU~q!{siSdhKMK(
zz16uX6EI5M3zC7bX)P5`4B~e+(KjU`W1{-3j1(h^mp^AL!YvPF2IxA$+!|m8AtS);
z)glnX?NseMJ9oy%l|g%;J#(=B=LveuGnfm_Z45+6hTGeBFE3C8!-#HkuTNy_eK{>-
zmROx=8_<i3BQ&T|dVqqA>>QmT(=|U;eH5CebP3Aw8)hsvKujD0Fq9@ixS~_dy2%}%
z<6RgO9IPoW{-R6JLS=&0lxU(n+0Njzn#}(TcoN@$o?^AqxtcXeMQ0@AnxL`xoyqDe
zX>hc%eu7ho7?S?JM3-G{*3gNV-*27^lIya-RiYrC`cQGZMny;{n)+ARlBk}p4))N;
zy<roQ8JE&O<9LygpltuZ^|a91+FBrDbv%pAaqRK0ce%=?6uKL#d7*xO=v?|a%n>nB
zQBk1p);gR4(Q9g{AKv2gs_+Im`B2Il&E>9ksv<;O1URBbeNlx2hzW=;yiL+u{o=lb
z2YuiJJwhL39vF;P;LC507t@_3=wwm2W`+iZr}?McK}GTRLl+!*9V1F@X<^ior++kk
z0qTy(t4{EKH4Zq=yIY`#n*2|{kSlDL59b;Znyu)!TOo-)Q&32OynI%ZIXF7JIW+kH
zZa0#^D6ZjbZzes%%F4P4q7v{JnM0-sGxZ0sBOIQebjWw$dezyNTJKy>+aG-+78)MD
z1o`anNmdJ?(@t7at8z*WFVmg9<dIui9P^-zE-SOumJ8MQg}yU)W#>Yr0UN|rktaPM
zu@NAsb7|DQ)z11ixEJwDN!{b+J_iK=^9LZ<Y;0J_1O=m65e>}|u>`m4&RceF*)|<L
zJvPJ9mr6>jCwsVabH6ZnB<}_P7kl{@5~3wa`kZTGuxWI%Qyjci>^B@U!FU0|DMA7Q
zs45U^RbVkN?CyRe?fpAi*6t7rYOZS2xN+DN0YO&~VrR=>WH8fxu|Br9es^6efd>oC
zk^cd494D=ERV-1FkFBM)wj6^P#oXgfkh)2B#q?1@IrtYXgtRnqL)i4;zzMENgt}ZG
znh;Q~Fw!%W7nuxJYN3EgdvLV4S`i??Y{#=km_-Qi!)&82U6OgK92^g}F`(xDc<=Vh
z++=9CZ{ayDO>ER#!<jq`K|au=9TBh#sEGNRXcxz~$?Cyon!cuQbICqR*MI4O+Q{&C
zuj)tK*QlT1dNhdgOvA~Y;(`tghh^*Mr86#_l4N!yyS;MPpCMl*G(lrA+#V8UZFg@a
zf447QJ0H0X_x}Z)W<C9q&(A^l=%e(y4aFiIotlr2uX;4K-t0M^ZNN1oigNh8Cr+_c
z*O0#Xb)@dCRixhsn`nMx15MT=?^3)!Yhl{cUo-Rz?Wu!DM=NwCX^%`bs7<h5P`sd{
z>&Xx;?TwHsU~;WNKrn!j{PS8wM0ZS7lnc%7^7oDr^QcY1D8eA^DS}8PLA<10BIWaC
zGlQpL@014(3@i7ugTlgym=j5m$(XELf0hw(E0<d;mFwO_*13=9cy=)mS=|rG02%1%
zk(UdNh*)5NcH;s3TgK@B7{FtL!y`kVwk%|3XF@l!U0Sm52cGhPhbV|7Yfu2=0oB%C
z7&|%HnX|qgi`Wm2I%nS7M~pP9Xk}~R``_k5+<p&KhU1sPBUr?&jG(Vh3;o~Ci6|u>
z-&MZ1tl@B}=~P<d+BfN2m(TwDq<-oHv&Y=Vuh0)Dn8Xfyhf^L_=|8G$h#1-f-T3Yx
zNO#2RQv%tOCm%u+>PmCtzGr%vXB>c8^E&2@q5;gVSbqM-=~~CF-X9)tur_&X;A;7&
z^VqIAyUuBMVETT>dUp`tgzMu+hcgg@^u7S|;zsXSu@F&qo;nYt#XM1s07wa1b+gIA
zwx3N-fV}{T8cT2g=u81t4wNc~dwY8enxv~t1ROkKhFFL40*|ux?)tu~e325vgz1Zr
z;E>Fqp5=k&LBKDvFVDep{Sj^`5Kb!(8&&-6Gj{s1wVE$}NghF`!Rkke<6H$BHn26U
z04e0H<#nj4nyTS`5E9&bXD#r*OK@jfPB@5Q^8F_-U}bJ2H7TpVIk&WMCt_#eh~zdr
z<(!Ux-W|s%Vjdp;>WqQ7FPpv7qpe1e?Aq+DTf!a~LvRpG!$<)dOdOhH6-miWc(?{5
zgMt`L+M8zg^s*wOCF5CTt)G-{O-@y~be$DM*xF)@ms-GTA!f(5GOJg(#%oI1nVHz7
zhkqM|VLak{eI=QVK|e35ILEncH@}DToLz@e(s`*#27<5h)#}>9<Lb;Uz&3=o)Qve=
z=au%QTO+Y~jvvLt-CZ5M*6H!Kxr2icScJwjf%b<uK2sAD1GAAg)@q9RYFFUyr&Ivf
zvYU$ztYPJKG}YEW=6vSv#&_$M1<=-r*D-^WgTsK;nXQRC4WTE3Qhz{@oti3=DZ#J@
zN;pV>k*&1UL9=4Y0y}$nc$#Nsrp3XZA&5W%oY>DFozKNDt=+}hX-vrz1Anl}1f|ad
zoq)RlB+1c<4npSgiJQ3-b}+Rd==Tu?T5(DPef^56lHca+3JT$XP9=r|*W-A&&C1N2
zi1N$O7++AXw#ESg>JNa17Wyw6Tgwy^^(y^ZvpTo)$;nU7)$SeEpgXWo3)-rU6N0pz
zrJaw<-En5dGjCqKdcwfq4Id97Y5n^;f1y5AHCSA@v%!@JV%s^LFZV?(ZqD@T{KrV4
ztAJCJVgPa?dwY(u$4pEilojgv$-?DXLxw};M#1vZ<SEI?q^JE|Lx>Irupg^sx?W~k
z(JZR=Q1w1{DAZwL5)VT0WxAVdvo$Iixn5QFLs>@1U>G0}XJtjo*b!#%EGjBsrNZ|2
zBS|23Cp_L|c_|D$jNms4eTa?!k2K})8$MP7sVjsh+OIZ@0lp|6b-8HChp!Z+%9{`;
zDIo@RiRw=y^mpW!ESo0_DCK!-_Z=fTF8&y~05J^Wlq$=EX#Y}qh7qjrSV#g9HKgK-
zi`>@{paCTeOtJ#CXdg&mmDdMQ!i_=_`@;Nu03lEJ`E3Y~F`KE?N{7DD4;|yb?<ga3
zP)=_Dz*;UW3`VYF=S{wkk&%%UEekBh@3S+uQ(M0MLyPFop8&L9XpyQ!91<6joR+0)
zqSLm}7Eg_5l7$CphvUl1z7cu)bL*|=x4WWQIV|@D)YaAX^+)|<%Ey`kLNuN%VR`bz
zEe%8uV1^fe0NghkL<bh>Ul#pBOY4c1?L6Me0a?a$s#ObV%MB$wK}&eh8^jnPScgun
zHaLmr78Nam_*slhtIDd%LQR0x2cR*5IaRgZ<~bo;x-JP29dmj}w0&arBRYCK>BP0z
zpQqXpgMg!XsHTQr%TbFo88W+|=zlMa^Ht%xXoo1ttdlMWIJYqEOjnrNFtGH*^CWQS
zL1c;p*t%|tL`OdYlq~4oSZ=oPn>QIoF_@tLR8Y9mB8ZD-6MOS!eRAl`=1oRkKzFRt
zK&C}!#SWM{=_&C#Yh&~xyk*mHOT~wWjKIpI%=l|}{ZCMQP+#l!N@&sx5^!a|MFZlP
zBeKwpn8Py?+1D>%Zf?&6^&O(w5kzDOFHWr$nEPf4Y0`L}l0A~9d`hKkJk2)%DMLp$
z2}fb`gscTb@fB$<j_>J7^(OG#Y7axyOcI)Z9*>v5nwIxK2su&6&z1JN8sd<?y}Afe
zmpA@r6iCzrWx?#86$CXdE`CJxBKDwS8ZAo}E>6QVnN%*OfnO6CR&c1ZH4Vp`YglCC
zyFmZp=JQYL1H}4yi%?o}$5%z80>z;rCf4(&r*-y?1%l5ykIKoVA)WE~T84+W0tOlP
zYZPAa_b)k`m-k?r<{-4jzJ>Jd6VV?zpDzfO1)@wE%XvYAH<~@UXU+smPDFP1ZXQ+q
z{PY;|1cQrxRsIjnnfDS4Jwv+Qk|U^ajV?Ujq7T=aoaOC2ATJ&O#Cdx!0R(U%0mM_0
zTlfEWaMig!dm=Cb>tdh6TJ+$1-gQxbg@p(MMOqa27sPMRU3e}DJTD?23OJK%$9?86
zk&zbhBB+mrU-116?|9bQ)unTJ0zD0qON6_-yNt^vVCT?HLC>K{P+VM`-V>{(l>c1|
zZA2`>cP;yXk~~f7>J`hHvK@H&o<4m$TKi!joIHRg*O)*efyGN5A;*GZ3Q}k$-7AR)
z0FV^uKwF)-3i1^|2VhueV}+1}mlF%?^R`FR&Pys#(GN-3Ln+-xD|+CNqW|o1Lw*E5
zJ?)g6$S2@IIjQiui!^KG<U)LAmR!Qz%niX;HVz-5&CM#YFfuVVZYo>nyBirAYJE6Z
zxXqSNxV|yg42wWLJw1r-O!8TsJ_NJ9me#^ETK`M3^z978Fe*jbTcs9u1l-2YCM53+
z!g?v(?ij1fPVaVyu#D8g8nxfm-=I9pl3xl!^+V2JI30Kn_5N&s_xl($)&PbG`RDV$
zrrc95H0}!)+{;(3CRdH{@UTaFF8nXHZpshYcXpdoTB4tNmSGxsdd>{pPa+|tP3v9>
z^;5opr(EFoL+iSyMU05H$b~2&ej2V`gy>9NsO1AYs2msy3$14jO-$NYZxNys^4a<o
z1_jlqC6oJa(5a$_SCl~Dj+d~&aUc-{W%V^yt7vM@pKY5P@_k%sjqD@+Gci2S+q*I{
zQl8<@;k*><ob0(VUS(upfJwl(0{8ylM~36z;$+g?a>)&4qVaNU9L0Ryx&D47DaDcE
zY_FBqkXm&*+l>KqW({I#@M3!y{-*?F6lUQ0+IF;=fVwHN`p7-`44Oj?NN?EhTxf&6
z8`~-n_7of%yFOv}^6lH*PJ<90PP>$l{C_0^M(F7KWZeX~xVQuada9*W1&a$U`aU(h
zznXfP_Gp;5yk*ld#5>0#)-yFk>#c2UMseV7gI+K4Y8{j@|3n*kzT2YtM1s(IB|3$G
zd+tleB7Eb=ua!jlq%{=9_`?7>n}O-ZU_CMj0uhK9^?!!0GGz)XC@6@D?ZHqMwDo$l
zW&8V=G0pZ!0hAWVFUpe7PAl*u#vm9>w^bvGYi-SFSi4{SSxQAEJ1{@ceEMs7ex?k+
z8YvBpKg}C)aZQ&S)j}A=(>0mj^IR@p(<5(N0i^$FS3*U$tDq<^=`&)pyaoioZTFBO
z{WJrvxUs28;FPWM1G0+XO~JChWZ4!$v538s&(#KeFz7`Jt*)%VfFr|mRs{WsJx3+b
zHb6RjP(!bcjfnXF+Pdy|s`vlTRhmXtwn_)bK0-#4TgV>A$SxcsGc&TThO9(5DYCNn
zI+R^xMRqpH%E~zQ`n^u>`hLH^&tD$Sah&rxpU?aKdcB@Yz6*e>!2%mKFpyONGo0Vc
z_*GO|za}Prz~&h0$5uNoLvJV?7Zc;L@P16OCRK$6LX2adKL^?3J@93Au=fR+JMCuM
zim$72l_vz6F%z!Eq2yI%dOj+mYo`Mq`Z5v|H9vw)N7U5`C5YNskaS%CY;Bu-(ANR>
zdFv{1>E4m?(hr6&qbW&%e4U6(;VS|7pi6r4b#I=yvuL`G5fiu><qW#zW563tALn>?
za^y|3+s|PE!?Q;XK;qM1PC5HyHdnvEWjykSc2-a3UbQDwpDA*uoQuLgK5>~H?|GNy
z4*p#5ZlMpuMn~7S7cZ?kI?nMEr4wy>Nt}J`3#lCY2t@rir+b-HM9r07?|h@v4z1Ha
zy|$((<Zwf)xUXUf%?GL1JUlkLV$!4ub%e%;+=eLOLc&k$9}Em0Hz$aRj;ydt-{8E+
zQG|_wrFxf9Utb^Y<qjoMA1YWp)z94Udb&l!6dxPW4392Tz0h=a+G@(M*3=a1Bq8!M
zNpt1F0_70&QXssGg(dYZ0ghKw(MC#K;z1#0Wfjht^bw7z$xT<jKp(ZPdcwFU4SQjA
zWNPZC`UEs#b<6XBf1_@XU}sk`8HCv`J#d1-oskjhfT)Nh^LRo*n9fDmVU8xIB+7kJ
zXtD+m?$cmUkGzbHe;KJv%{V&)iAd_b;^k$sH*UZflWVh+_D(Q?0|*2vjRtO*LKZ)6
z8*Ym!uW81GgLBQ)w3z4o5jzSgtMS+M)M?6qvX&j1>3}Oj?MHdgm9Pj}(UY7bbYH+8
zjiRBM@W2OLS$F=8U_BkQ#T<`~7vN#f$xZzX#fk^D%T!$qwfw~@kwY?IM>MQP@#1Ik
zV{M`Ci2^U<lkJ#F8{N+XO!(5o6eezb1`>G&MgGLkk3g%b#T?~QBF3z$qvNJ2B<Fn0
zPg>RMcd9*-o77SGVi<L&bAiy!?6&Du_x%sWc$YiLcGm;wa)v&B7-={7z<LX2K-+jW
z7{|I|?T10I*#GIj%qwK>>b>_ulpG(;(P;tGLJd=l23(4xbp<IfLgvxUGgHjpQ;Lq_
zdJz;H+|}7_P88$^Xg4=GKQ=2XM}~SiP{He}Ju3x~FCD8|^ch37oaPr%cVLhGJoisG
zR-l2xpgC2ZdYw(m-tB38;%;v&&Pcyh{oZwk4|hz*$H(X3kLy|gax;)CjDqbr@aa=A
z<}!!16@-U}Kl_B6-H_TF36(WrZ~hs7J1HA5l?#lb`rl6K_8`lD5c(i~5C*JIP>5^C
zmYB&&)M<tuQxb90&|>O~@uz{D$$yquifC6)OPgkL!hG_iDYVpFJAd_0FWJ7qunW}i
zFd?3awWs)LKX=*IlZ`buEz5muED;DKKW1mtLu2%`Jw?IMwWp`jbw~9h>Dre!l0OHU
zA2Y(re@a);<saRCaVd8C&q?P%Q^C8s?aFc-3h^8)c&QjOq17N!KjKwO;un+}ksBQ(
z1XtK*k>fjN2nHk?3#0vOFOZO&-v)XDp-q!Jdi1F13#!SfS*Iymb<mjr+;8<N&d4<7
zEv@$(32(acXmE^{llL{<FM>3<UR<%O^*2LhM^Zlm4F#p3aBpQ*9Ng=7uhcF~5NKgs
zoSc{Wq>Qc`h3<El!56ukTy$o>-a7>j?JOOY0@N6MCa|r7n%=dznvu02)L@R^Sc-A*
zGMGe|=CQr)N9fRvTs-VdcKgDI<;mG*2bxo|bi?l5OSaxR?RRlg^B55=9hN8RWi0d7
z`ByAG^gvo}YWxgf4hIn5k%-5zEuEB+m*>176vU!ksg<c)^c?#_(q)1REy&snpfSW<
z0Cyg^SH0Q8HNDK@p0RO)B5dUKH~yLhh;;OJ>Q}hPp0bq3rKC6et8_xnX37#G%8t;I
z$T)s?I9b7Z)zfhINt7ey26$bja&SP6AV?&8&F?6@xxH3ZwJ)DrS`L<wqDb*jVxshG
zu>2&OUG0*-=X6C+8zT!<3HK4ut|&geYcRn0@+GYC=-{+c3aQSnOQaMm3e;@L$%wYb
zZ;qlcV}-9K=e;P@iUy?%w+E-&-hj}@&dx^u6bNi{@<&RdS^#S^(ib~r5R{2uUm2>r
z?8k@<O2WbvQA24ucceJFcag=^)HL|u1_D@Ta&i)!oB_mKAKcef!HDqeOuX2(KQ@B9
zY*Ns>p{rZ{MO1C;JJ|ADnp#75VxQ}^mue|!Bo@A*gPe$a{||zAG!d}l#ZzMW&Vv@I
zpA+ueU#q^_`dZ}9n40FwL2?I7y10cTsI?Vzl?;^PQh&4<cQ?H3`?9>7^z-CtBK7FW
z>1lv1Lw1(}Rq~33y9wN&8h6NPB#e>z5?RpERyNj^o_nu|xqc%onVa3(Q7Wf-kd3QW
z5-@}_g#s@DD2Poes%H!-TVF(>gxb5*bzu=9Qv9*M7XSp9md2Z<_iS1t5mFEC=iGXi
z`b^uK^cof6KHfhLy&!3nE3z^uR7qV!BQheQ`MNZydME(D!@NxqXO_WgB4j;0xwsp%
zGPz*TM>JYLFd(#Iq{qxNjC<2s)UZMCcY#onNFU!B7Lb;XuR5lvaBp>WRp?TYbbUQ|
z!$Ow??M|^UmY8TWXVc3^m0udz;5?E%?3Z5eS7w@Ke>p>0VW6i*@RugqT>bT0<U4%%
z36c-BKw_b)$}gqa)!Fa<PE(V4TTM|>%^<jC&neE;Nl_p8({(97epq!n_5FAo*$qYw
zff!itt>R3YBhXfrvXOf`J;ErYIQyl!*O(K5O?W9?P1>~EDJFHC7cm%1C9d(C9rBx{
zyeK4(((eolltv4_Emz?oC4EM0OHW59WmQP9TI78m2J2j5NkImlb?4vh?Q<UqSzFtw
zgcp`QGOT(e1cv*3WFp^MUY6b8-Zv>zhT0Epq`kR<p0^CFgk<nHPX?;77}<t8g^Izz
zSY|aN?c(`MlZjN#_pi8yr+DvP+!B?FjL*#QDOZ*;R@Ii>ir3v@ldf0bM?crq-tUwO
zzy;w{Ok)5W3hKlfe4U(JmahM##EaI{Qr}MtapPSu4#a3(kD3?W6aHbzU7-AUmS&>g
zdV4rwlrj(l4)P~gOq!v79;d#D&B)+xX=(B<3h_CDf4Hd`9i>t|LDd4zgdSJ=HKRHX
zJn_;A6GE;cZ|1QEa^~h192_Y(d8sRlZYb)@{cd^zv>m}Ws{bg?d&F}T3JDcuTU*XB
zdtLvBz(DhK+~C-ew_C~&S797{;I_tPsD^=xxTk}^<3yO<pgWjWIxWV=2z%rE0s%){
zTUr!_PNBw6N*SpVE7V$OKm6#?jqNYK^Yl~lVjv=bIAEyv&e;3}h#9~tyTLM4HRS@^
zz=CjrXMLwh{w&bns>6=QOPT2}V`LXD1n%$nJlL9Dt2zJi;X~C+vbz@hT2Ok9g{3AY
zW+t4&hKI{)oROLdPP+Zny>>(Xsyw#|{q2s8b!CMDa`u~UN373Es*DZ>bMwrsuBGs%
z%?RlaV2$bg3oqz$59Rw8#zsVH;Mog8bT)fBoi1WELai7cAJvO!DNDlii$}DWL-1&G
zVG&}&uyAY3Bu6;lB;v@eNC9u{=%_dzWX-tOo<fH5xZ^(FjEXP0@;s`BiYNKTN__mF
zZkeHVK?*8Dos^R|xrbJpgJ<<;Czm%*W=I5ixXJJZtQ^BowNi_Kll98VLG*I4F*3#C
z0wy-8nTGaYuVZ?GMlZGQpftqIRs&N^z0YSBgxuLUi;PD)1uV%%>wM-+K|I~12{L4q
zpYW|Q^|=)?<KW=)#>x}H&X<$UCGWv@6w4e~Z4CEa#Aya$bq$$6GTMPnh07PT^x<pv
zo*}Ryrm*=qT(*8s<W{0ji_gv<P%YN5g^n|AJKdyMM?9D$pH#>5vh!WPM>UxH_M!me
z^`}WSa+|}NdJ2D3In!xyAT(3C=AAXll*MwAvd_)ep0DcHWDXZXG^I(3nPP&dT24lk
z<TX!B-lzJ?rJtIb8Tp!>Gckl`O*<w?6Ye$Mz#Z3^_nC!taMR`9()-qiq-yTgUbz_6
z)Oa&E+FD)Dc>i(>NDvXEw_qtt!sx%s40*)8EY!h&JL&$F4k6VJOyLKi?RRi)IXU$|
z@xhrz-eEwPA-G>43q$<JB6w9a%&iLxI}v(}dnW1=xTZkfP)?%=mJ1Cp_&lu-qB~r|
zm8iFnjkHE`gY1RE#vPc0{h1%=IVX{sQOY1G%#rGzvM$Kt@frlUosQ3#l|J9V$jEy;
zTbxPMKJgPjD+?{{QI>S*EIqf^ovmy)#wU5WZ&kS@W(Fm6!B~PA#%LYw>UkQK?~}$a
zcjf}!VcMTR+oU`KSqY*}LS(D+hCPHk%Y`xPfR;=o*RayQrFY>9t3%@$@yPId&6cHb
zAD38aYNoSPR1y~Wr;rZOLHrI%akulN9R8mtdx`?^iEXiDvt7QF=ytM9==*RrxWtF$
z<#SoOFdRm;&<Q|P2*)5jeSSlG`?(7j3SrnQc{xwr%-lQ@1VG@~emOs<^!~RiDk`B#
z+!So$I3VVNV>Fl_E{s&w*IY9hKL&R72)p&zm@X@cOP5xCMadkDPU)c0Jcj*^i5|lP
zB_<V~lbs*7+P@_iSt#30c8&uP0@w~$ocV9c>h%w|MlHOH2Ju%`E}6<E9`EL4+tya)
zyfFee`AqgS7?Y8QE~KfxQSat|?=?9K=0czmyJKoAeE+sDu3EckV-P&~Al!VU%p=P!
z=T-33mz3e(L&I3588*JYE$b`O$<Y_Arhx6!&zIKa+_=zV{+=^r?}8H3&k0mq$)ulG
zH$-ruH>aC(#?|kBiu7|*h}NdO9raeZ<PiqJWcmIP=5A&)0*My56Qdt!KdSSgyn>ci
z?J3rJH(yAR)%P|727y3+kIoNi;ZtBZDk7a9;uKF6)fAZ?643xlN7*MH1qL<T#j`}3
z!W;o}M~GpFCVTX;@l~mp{<+$nLjokYLQ6S-Hc&f1w~nnZCOHNftHufc!74I)E3l3A
z5D^&?zqEJos@QD$4H)WHke^6NxB33Qhnt%lVsWf{R+KK@xpPM~F(Nlt72C!li>3TU
zxg2FR7%tF51MU~1OpHTZ;%UiB6X5gxQ~G%Hy4w-x03ZruSh5tH+fTDi%HIhJExG;B
z<nf~;^ZjcmiGfO^G*SCp;3&W><D?1ObZ2MGKtHdXmXGoNB8vg|w!bNLTn6wkc%V_{
zx_q&#yFrOp6Tm@oJ6jHeg^B5kFcZ_wGaTqnTm}eUNH$iB15_jKOG~j*X54!>xTcD7
zEcsBCrfUmbHiOTM3JMCcba?ejELe`-YC<A$Yqt9<8xQcC8KY&@0GW&y2a-Gv!87zL
z9hbGNcHLRry2J_6ra{+PPXNR`MSH2-HJqFj-Sg~&={`$ABkC>JFr^X&K?7x@Gj(>*
zC^2=H#vN?T18MLytLRGKHxi&*Jq&m@-%})+Vs!mUC{-KJ^5xaE4^2|AEW+U@q^O}$
z5SB-wqP~7{PtDTzBqN|ks(K%zL+9{oJZCSJA4+S2bODJUt@c&pJNr;TTvB3SP$Uyw
zt`o3s_c$sNq48Pfd}Lp{J~$qGJ5H0X@~J*+wdu)J$WR0>CvFma;5C_%ik4g^Sq=ty
z9z`78H<4<GyibGuyxc?PCki3sQq@q`cT+(D#laDcL;xH%)BmY?WubgSw#N%HrbZUN
ze$_>z%|Q1vEkJszNEB84Amy!C0jeN!7=j#TW@l(hlnKd%M#JD5){gIYo;EUgCn%d`
zaYv)RyBJbfrYy9PXOrm$PO!#FcJ5pEcGor)=%JX@UWwcj6l@2|UKa35j5?yg8mL%U
zvDWjxd)MXmFbFrah%wz+fL<^1{&pCPO8HX@HDzTlHdb)(RT`j(tODjBQ#;JJj03A<
zq-o(kJUq8fQ?MS;7)jmVOy3mJrp4gOqlK|8<f@7pk8&5WH{`0FFjHw;G}Jb>wikQp
z!D>2a1-rijDF+4jOcq7iZGpbQ&#lY-M6os{oF>`af=1lI)-ZMnCk_>7M1-bo_JqNB
zJL_P+TTg$&Dk%EC_GDSY<$=mdrC<Eqe=g{LTU_<Eu6iw}cbfB!X+yqO+3Rl|vP5D)
z9RkYL!eB<>BEJ>s%d6qh;mC0g)!)FTZ+&?|7uG4hOT6=;b&>)n0vAfl%ESgZq15iG
zz$a)0;{;Kt3{8a8dTIJ*G2Zf*{W#$RtG9)$GF93(eW;%13*p5DtK4CnCCJz3T};oo
z5AU6KaV>@+Lmi`ti15|Du3Bz_o;OtvrL-wfiu$%}-oImb%7G&{C4+&QsbM5n0^E{B
zM6?YIluQxUwhpBp9|wxko*^!BEcTb0xV)$%y=nKocYCu54czmh0vz|$woG6&zez?)
z4nvu*+C({}z!!eyAG9N~Aj>PYnf6&7K<HaUai=hm8iTM(C+C%L@=`~>j5itCT4baa
z&aYE#YJ-5U{5sUz)aNymJxi`uNy&$;3G{>jyUVb`Mg08v^X%;3@i9fC*%V@weZFJr
zsd(GJ9G)ysl3JXsx=7Dli8+-9+;1QPX(+Wn4(5xC3)b_;Me6`ufvOA*x?^tc0$XG1
z?YDwBS(9ofa6f?#tCLU_LQ4l`*$UZUm0snx$D#5PTtci8^3FNw%CoR60J$M3x3RnX
z5zZL^alTlV7|rJ9wp@cWHyA2&oqvCCP899=*!_&1SMn1wpq>FZe}<J+BQr%i&*HoQ
zC-_Baq>f26gJ@@UWhEWO!!rkNRNeQN+Ryy^qw|w72%keCJ?7Tqgcp7+To1$JLxBF?
zS=TUQ6<BoZ<?B#p(YNTcd2L3OSucIc15^pxALaj1L!a^#7nc+V@74hk`;q1xql2o-
zoE$zl5uqhfu%_sh41jRdHm`sn1ClTQM+P*OG_}_<>hLj@Z$#=rLj&h=Cf%G{g_fiH
zcT0E$NKNzweN|CW#a{Z>w88o?E;o{rI57wkKKGww38hv_k3w^E3|Rqw?@THaR89J0
zZ-?KwF!pL=T~iliP_~I`n%?9qcSvFdg2=I0g&Q(j>x-u(e8V|(vh@u<Q=R;I;gFeI
z>A6YDe8t>eCyI~fo6mPgvHu>=3i`huY|J&Pgj_K_Jo`?iyTa7X3Q4iUtEa|cLxOiG
zDKq?5aAK9Q!c^$fAiCFQ$1KI%b|<R*NF+<`EFggHFiqg_FNnM-uEtkGLGX-a0JZdD
zFG!Mw5OqK}v;+Y&w;k+A1};93`TC<_sQxg3JUB`lC1Uq|1VYA1f00fI&%KtRXJ8;#
zb?S^AO0b;`WqX`Nni!ZXgoohp6C(TTnKc5mj_2}?8u)E`?QRn#m^+?0fB2jlfys_{
zW?iY|p|2$#xc$h^&21y9Dg9*+M0i3?UTSiVomIjCYMUA&4G3eR!=w5SxQUF7S^w*o
zINbWffG~O@F5<t*TGh3ED0V=@&<&Z8OgZ`wUE^{e&g?4)=zk7Xe1QK+;P(GIHpz^u
z$qQ_{)t@y`+kpV#I}l$Xj)C#-Wp?zOq@=;C7FruaU`+2FqaZxE_!r@Li3!y4_fo32
zby%sHUdP6E=7viC>2dJu)t9pB8yW!qfuZ_SQ2^ZtjAa7&3a|0^ncGZ(g+=e{dzsQ)
zR#=^r7Jy1<Am~6&LiG5bGb144w5je15nHC9vO0X{L`0Z>-la)ve?1=*pMd(+VsiyY
zQ-DD8vain}`dwKGQ~)Q?-){AbZiA0_y1VrkF=1zmlk1v5RX{5q!k5=}azOUf;dVEX
zjTw!L6LWp#lUJoD$5vNUXE^_Tw_$G`O|bL(b#VDUIn9`!o={UG@D@@@J`M(FQ2MvU
ziaC!TNBjJ9UR(cv;*aCq(RU9V0@~g{dFHw{yS%$~3U?n0ez;wM38Ac{c9y>umq=0q
zv@=(?d*DSaUczfw5z=fmkYgwR>gC>s7j9)_?-+s7Eo3bVq{eP4Mn;S2v6+LfZ-H;+
z<+-7zsG3R;)#y1-b#(I1i7;QWHFt74SuXV_mv|uU%dUIH7W4<gX07jgL4ODc2ZqW0
z*XSA1TIIC%zSC#vb9OeMti?4T0UN45c+U4MEG(_$Yo^VmUSEI56UA}Gh+?{5qITb8
zNu~v|fe%YhkEi0TF8A8B-*3nr{y-PFqmsWI69YX+5w66h|NX+g-$UE)K$87OBQNhz
z5c=3%gFRr1gp@2<Zrh_{RyAH+S8EcQl43Ti%3`u(6ep6>hlUKdWxD3Uk*(v16!81f
z_x|mLU7p;aDmY2~_w{O$^SAE?a4>9@JoUGGTjxfrDN0LnzP1*%EK{eYqd+t?5E)oI
z{Y48U5_iRp!$2HN#Q+EZM@iF`&tF<bE6rMJi1()W43!1;<iZjP!R+yk7~@T9>H|jk
zP{?uAnCM8ueu)Z}adL8^aVl8VOzrwl;!#D#74Rk{o74F@Tmtr3_6yr&wv#~JNmGk)
z*=?+ygHoW<Jsx@db%p1)PM*cRh0d)G_JEX>6Q(85)cudV{A3`T*SDk;53hY7p*^8s
z8FCnVj`vTu9|#f8<j%wjy!pO-zgS^@{!lWX%oi{29Rx&D+wvs;-v#1Xm1U$wtoe1z
za^Frwf~$5~nx$ZUVZNZlw+YbGb)`7V-(g>n^L(mJH{xIp%q)n|3?SLaF|K;#_Ptt3
z%;UY;4i4g0`YN4mQ03_k@y4!m-Os=ow8XS&v2rIU!;6-x(5F>Ve*h3$u0|j|rLy6H
zfoiBP(RD<MhL$!X<U_-v@i15}O)N}`4}6gp5h+QhFz)u@IYpo@{5p2;0!LU|TWg@y
z#_X=?XPnl*$x>+a_Zh2NBDKBk&HX%kmb+}C=IVW~FV_onC8Ljd;tC4AAQeGF1Qxy`
zhwgkM19zAX>ra6<Yrh-#MCxLrnaLY~`n>m`cAmz84BR_J!y=HNVE=#-wHd#CJ3;Md
zZ@R^DZo=}fVmhOGcMrr9bA!D$BiScJSpViqLnNc7z0*oOEiK3L!+1&GM3d1GV9fx$
zss71*r%mcEbfi|B`7%Hd@G+A+X-OeQFXl5(Z^q94pj-}yTP9`n%Aqtv_~o_4Kxo9&
zv)OrZHr;-vEZaAf3)20B&gn~fFOBn@`dONtJr7c0NWLo#PfP@eqXQxAYBhuleeLi6
zTRE}pLegD2x=3B<OnV?aRI*K1BkDip^s?knrxvFMvNK5bs$gK2>X5*8hCy2kqp_32
pyD1GP{NP~AIB^|*ASLY6ux4K?na8{&!xO#>1zFV_xxe4`|3CPt6p{b{

diff --git a/tools/dag-viewer/render.py b/tools/dag-viewer/render.py
index fbdaca97a..f5ac3ec76 100755
--- a/tools/dag-viewer/render.py
+++ b/tools/dag-viewer/render.py
@@ -269,23 +269,6 @@ def load_workload(paths: list[Path]) -> dict:
     for path in paths:
         data = json.loads(path.read_text())
         incoming = data.get("queries", [])
-        if not incoming and isinstance(data.get("dag"), dict) and isinstance(data.get("deployments"), list):
-            incoming = [{
-                "name": path.stem or "Summary maintenance plan",
-                "dag": data["dag"],
-                "post_dag": data["dag"],
-                "lifecycle_plan": True,
-                "lifecycle_summary": {
-                    "selected_raw_recompute": data.get("selected_raw_recompute", False),
-                    "summary_total_cost": data.get("summary_total_cost"),
-                    "raw_recompute_total_cost": data.get("raw_recompute_total_cost"),
-                    "horizon_seconds": data.get("horizon_seconds"),
-                    "evaluation_rate_per_second": data.get("evaluation_rate_per_second"),
-                    "update_rate_per_second": data.get("update_rate_per_second"),
-                    "expected_reads": data.get("expected_reads"),
-                    "deployment_count": len(data["deployments"]),
-                },
-            }]
         for q in incoming:
             name = q["name"]
             if name in seen_names:
diff --git a/tools/dag-viewer/test_render.py b/tools/dag-viewer/test_render.py
index 20ccb64cd..e78e978f0 100644
--- a/tools/dag-viewer/test_render.py
+++ b/tools/dag-viewer/test_render.py
@@ -79,43 +79,6 @@ def test_boundary_terms_and_provenance_survive_standalone_export(self):
         self.assertIn(annotation["model_version"], html)
         self.assertIn(annotation["evidence_version"], html)
 
-    def test_loads_summary_maintenance_export_as_a_lifecycle_plan(self):
-        dag = named_dag("unused")["dag"]
-        summary = {
-            "selected_raw_recompute": True,
-            "summary_total_cost": None,
-            "raw_recompute_total_cost": 7.5,
-            "horizon_seconds": 60.0,
-            "evaluation_rate_per_second": 2.0,
-            "update_rate_per_second": 3.0,
-            "expected_reads": 120.0,
-        }
-        with tempfile.TemporaryDirectory() as d:
-            path = Path(d) / "lifecycle.json"
-            path.write_text(json.dumps({"dag": dag, "deployments": [], **summary}))
-            workload = load_workload([path])
-
-        query = workload["queries"][0]
-        self.assertEqual(query["name"], "lifecycle")
-        self.assertTrue(query["lifecycle_plan"])
-        self.assertEqual(query["post_dag"], dag)
-        self.assertEqual(
-            query["lifecycle_summary"],
-            {**summary, "deployment_count": 0},
-        )
-
-    def test_preserves_summary_plan_deployment_count(self):
-        dag = named_dag("unused")["dag"]
-        with tempfile.TemporaryDirectory() as d:
-            path = Path(d) / "lifecycle.json"
-            path.write_text(json.dumps({"dag": dag, "deployments": [{}, {}]}))
-            workload = load_workload([path])
-
-        self.assertEqual(
-            workload["queries"][0]["lifecycle_summary"]["deployment_count"],
-            2,
-        )
-
     def test_merges_queries_across_files_in_order(self):
         with tempfile.TemporaryDirectory() as d:
             f1 = Path(d) / "a.json"
diff --git a/tools/dag-viewer/viewer.js b/tools/dag-viewer/viewer.js
index 6e4dc0c07..c4cbe5b71 100644
--- a/tools/dag-viewer/viewer.js
+++ b/tools/dag-viewer/viewer.js
@@ -122,13 +122,7 @@ function loadFiles(fileList) {
     reader.onload = () => {
       try {
         const parsed = JSON.parse(reader.result);
-        const incoming = parsed.queries || (parsed.dag && parsed.deployments ? [{
-          name: file.name.replace(/\.json$/i, '') || 'Summary maintenance plan',
-          dag: parsed.dag,
-          post_dag: parsed.dag,
-          lifecycle_plan: true,
-          lifecycle_summary: lifecyclePlanSummary(parsed),
-        }] : []);
+        const incoming = parsed.queries || [];
         const existingNames = new Set(queries.map((q) => q.name));
         // One batch id per *file* — every query this one dag_export
         // invocation produced shares its decision.id numbering.
@@ -137,7 +131,7 @@ function loadFiles(fileList) {
           let name = q.name;
           if (existingNames.has(name)) name = `${q.name} (${file.name})`;
           existingNames.add(name);
-          queries.push({ name, dag: q.dag, source: q.source, replacements: q.replacements || [], post_dag: q.post_dag, workload_cost: q.workload_cost, lifecycle_plan: q.lifecycle_plan, lifecycle_summary: q.lifecycle_summary, sourceBatch });
+          queries.push({ name, dag: q.dag, source: q.source, replacements: q.replacements || [], post_dag: q.post_dag, workload_cost: q.workload_cost, sourceBatch });
         });
       } catch (err) {
         alert(`Failed to parse ${file.name}: ${err.message}`);
@@ -154,19 +148,6 @@ function loadFiles(fileList) {
   fileInput.value = '';
 }
 
-function lifecyclePlanSummary(plan) {
-  return {
-    selected_raw_recompute: Boolean(plan.selected_raw_recompute),
-    summary_total_cost: plan.summary_total_cost ?? null,
-    raw_recompute_total_cost: plan.raw_recompute_total_cost ?? null,
-    horizon_seconds: plan.horizon_seconds ?? null,
-    evaluation_rate_per_second: plan.evaluation_rate_per_second ?? null,
-    update_rate_per_second: plan.update_rate_per_second ?? null,
-    expected_reads: plan.expected_reads ?? null,
-    deployment_count: Array.isArray(plan.deployments) ? plan.deployments.length : 0,
-  };
-}
-
 function getParticipants() {
   return Array.from(participants)
     .filter((i) => i >= 0 && i < queries.length)
@@ -481,28 +462,6 @@ function renderPrePostAsap() {
     return;
   }
   hideModeHint();
-  if (selected.length === 1 && selected[0].lifecycle_plan) {
-    viewTitleEl.textContent = `Summary maintenance: ${selected[0].name}`;
-    const elements = laneElements(
-      'summary-maintenance',
-      `${selected[0].name} · lifecycle plan`,
-      selected[0].post_dag,
-      selected[0],
-      'post',
-    );
-    buildCy(elements);
-    finalizeDAGInteractions();
-    applyHighlighting();
-    const initial = cy.nodes().filter((node) => !node.data('isLane') && node.data('root')).first();
-    if (initial && initial.length) {
-      initial.select();
-      showPrePostDetail(initial.data());
-    } else {
-      clearDetail();
-    }
-    fitAndSyncZoom();
-    return;
-  }
   viewTitleEl.textContent = selected.length === 1
     ? `Pre/Post-ASAP: ${selected[0].name}`
     : `Pre/Post-ASAP workload union: ${selected.length} queries`;
@@ -655,7 +614,6 @@ function laneElements(laneId, laneLabel, dag, query, stage, laneCost) {
         laneId,
         stage,
         queryName: query.name,
-        lifecycleSummary: query.lifecycle_summary,
         translations: translationsForNode(query, node, stage),
       },
       classes: node.decision && typeof node.decision.benefit?.value === 'number'
@@ -1009,33 +967,6 @@ function showPrePostDetail(data) {
     : '';
 
   const decisions = data.translations || [];
-  const planSummary = data.lifecycleSummary;
-  let planSummaryHtml = '';
-  if (planSummary) {
-    const value = (item) => item === null || item === undefined ? 'unknown' : String(item);
-    const selected = planSummary.selected_raw_recompute
-      ? 'Raw recomputation'
-      : 'Summary maintenance';
-    planSummaryHtml = `<div class="translationBlock"><h3>Lifecycle plan decision</h3>
-      <div><strong>Selected:</strong> ${escapeHtml(selected)}</div>
-      <div class="translationMeta">summary cost: ${escapeHtml(value(planSummary.summary_total_cost))} · raw recompute cost: ${escapeHtml(value(planSummary.raw_recompute_total_cost))} · deployments: ${escapeHtml(value(planSummary.deployment_count))}</div>
-      <div class="translationMeta">horizon: ${escapeHtml(value(planSummary.horizon_seconds))} s · expected reads: ${escapeHtml(value(planSummary.expected_reads))} · evaluation rate: ${escapeHtml(value(planSummary.evaluation_rate_per_second))}/s · update rate: ${escapeHtml(value(planSummary.update_rate_per_second))}/s</div>
-    </div>`;
-  }
-  const lifecycle = node.detail && node.detail.summary_maintenance;
-  let lifecycleHtml = '';
-  if (lifecycle) {
-    const selected = lifecycle.selected;
-    const selectedText = selected
-      ? `${selected.lifecycle.kind} · ${selected.maintenance_mode} · ${selected.evaluation_schedule} · ${selected.output_representation}`
-      : 'No lifecycle selected';
-    const alternatives = (lifecycle.alternatives || []).map((alternative) => {
-      const status = alternative.rejection ? `rejected: ${alternative.rejection}` : `cost: ${alternative.total_cost}`;
-      const assumptions = (alternative.assumptions || []).join('; ') || 'none';
-      return `<div class="translationCard"><div class="translationStrategy">${escapeHtml(alternative.lifecycle.kind)}</div><div class="translationMeta">${escapeHtml(status)}</div><div class="translationReason">assumptions: ${escapeHtml(assumptions)}</div></div>`;
-    }).join('');
-    lifecycleHtml = `<div class="translationBlock"><h3>Summary maintenance lifecycle</h3><div><strong>Selected:</strong> ${escapeHtml(selectedText)}</div>${alternatives}</div>`;
-  }
   let translationHtml = '';
   if (decisions.length > 0) {
     const cards = decisions.map((entry) => `
@@ -1057,9 +988,7 @@ function showPrePostDetail(data) {
     <span class="chip" style="color:${catColors.border}; background:${catColors.bg}">${escapeHtml(chipLabel)}</span>
     <div style="font-weight:650; margin:0.3rem 0 0.4rem">${escapeHtml(node.label)}</div>
     ${rootHtml}
-    ${planSummaryHtml}
     ${translationHtml}
-    ${lifecycleHtml}
     <h3 class="detailSubhead">IR node content</h3>
     <pre>${escapeHtml(JSON.stringify(node.detail, null, 2))}</pre>
   `;
@@ -1181,7 +1110,7 @@ function loadWorkload(parsed) {
   const incoming = (parsed && parsed.queries) || [];
   // One batch id for this whole document — see `sourceBatch`'s own doc above.
   const sourceBatch = nextSourceBatch++;
-  incoming.forEach((q) => queries.push({ name: q.name, dag: q.dag, source: q.source, replacements: q.replacements || [], post_dag: q.post_dag, workload_cost: q.workload_cost, lifecycle_plan: q.lifecycle_plan, lifecycle_summary: q.lifecycle_summary, sourceBatch }));
+  incoming.forEach((q) => queries.push({ name: q.name, dag: q.dag, source: q.source, replacements: q.replacements || [], post_dag: q.post_dag, workload_cost: q.workload_cost, sourceBatch }));
   if (activeIndex === -1 && queries.length > 0) activeIndex = 0;
   if (participants.size === 0 && activeIndex >= 0) participants.add(activeIndex);
 }

From 68df715fb7ab88a853cada075280138abb913899 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 21:16:24 +0000
Subject: [PATCH 43/48] refactor(ir): default to query-time materialization

Rename LifecycleAssignment to MaterializationAssignment and
apply_lifecycle_timings to apply_materialization_timings. The default
assignment is now all_query_time(): nothing is materialized until Stage 2
materialization (#509) decides per sub-DAG. all_ingestion_time() and set()
assign maintenance explicitly.

- validate_default becomes validate_maintained: candidate legality is still
  checked with every summary maintained, so candidate generation is
  unchanged. planned_data_state and fixed_window_rate_candidates use the
  same maintained assumption, and the maintained precompute compilers in
  promql_rows assign ingestion time explicitly.
- PlanOutput::execution_timed_dag, show_post_asap_ir and the default test
  helpers now emit query-time summaries.
- Tests that exercise maintenance assign it explicitly (new `maintained`
  helpers); a new unit test pins the query-time default.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 .../src/exact_composition.rs                  |  10 +-
 .../src/maintained_population.rs              |  12 +-
 crates/asap-aware-mapping/src/pass/mod.rs     |   8 +-
 crates/asap-aware-mapping/src/replacement.rs  |  37 ++---
 crates/asap-aware-mapping/src/test_support.rs |  28 ++--
 .../src/physical_planner/candidates.rs        |  14 +-
 .../src/physical_planner/promql_rows.rs       |  12 +-
 .../tests/common/mod.rs                       |   8 +-
 .../tests/weighted_topk_binding.rs            |   8 +-
 crates/devtools/src/bin/show_post_asap_ir.rs  |   4 +-
 crates/frontend-promql/tests/support.rs       |  14 +-
 .../tests/maintained_population.rs            |  11 +-
 crates/frontend-sql/tests/pearson_corr.rs     |   8 +-
 crates/integration-tests/src/lib.rs           |  35 +++--
 .../tests/exact_composition.rs                |  14 +-
 .../tests/physical_common/mod.rs              |  27 +++-
 .../tests/precompute_raw_samples.rs           |   6 +-
 .../tests/promql_to_post_asap.rs              |  11 +-
 crates/types/src/ir/mod.rs                    |   6 +-
 crates/types/src/ir/node.rs                   |   2 +-
 crates/types/src/ir/physical_export.rs        |   4 +-
 crates/types/src/ir/timing.rs                 | 130 ++++++++++++------
 .../src/post_asap/execution_data_state.rs     |   6 +-
 crates/types/tests/physical_export.rs         |  18 +--
 24 files changed, 270 insertions(+), 163 deletions(-)

diff --git a/crates/asap-aware-mapping/src/exact_composition.rs b/crates/asap-aware-mapping/src/exact_composition.rs
index f48bc08b5..618265e9b 100644
--- a/crates/asap-aware-mapping/src/exact_composition.rs
+++ b/crates/asap-aware-mapping/src/exact_composition.rs
@@ -67,7 +67,7 @@ use std::rc::Rc;
 
 use asap_types::ir::aggregate_schema::aggregate_output_schema;
 use asap_types::ir::operator_properties::Reduction;
-use asap_types::ir::timing::{planned_data_state, validate_default};
+use asap_types::ir::timing::{planned_data_state, validate_maintained};
 use asap_types::ir::{NonASAPOp, Operator, OperatorNode, Predicate};
 use asap_types::post_asap::execution_data_state::lift_plain;
 use asap_types::post_asap::{
@@ -202,7 +202,7 @@ impl ExactComposition {
 
     /// Build the composed, data_state-validated node over `child`. Every edge of
     /// the result (including everything beneath `child`) is checked by
-    /// `asap_types::ir::timing::validate_default`; an illegal
+    /// `asap_types::ir::timing::validate_maintained`; an illegal
     /// placement is a typed [`RealizationError::ExecutionDataState`], never deferred to a
     /// runtime.
     pub fn compose(&self, child: Rc<OperatorNode>) -> Result<Rc<OperatorNode>, RealizationError> {
@@ -261,7 +261,7 @@ impl ExactComposition {
             OperatorNode::with_schema(Operator::NonASAP(self.op.clone().into_op(child)), schema)
                 .with_guarantee(guarantee),
         );
-        validate_default(&node, self.placement.data_state().timing)?;
+        validate_maintained(&node, self.placement.data_state().timing)?;
         Ok(node)
     }
 
@@ -660,7 +660,7 @@ mod tests {
             Operator::NonASAP(NonASAPOp::Aggregate { .. })
         ));
         // Timing is no longer stored by composition: under the default
-        // lifecycle assignment the composed read-time operation runs at
+        // materialization assignment the composed read-time operation runs at
         // query time.
         assert_eq!(timed(&composed).timing, Some(ExecutionTiming::QueryTime));
         assert!(composed
@@ -701,7 +701,7 @@ mod tests {
             composed.operator,
             Operator::NonASAP(NonASAPOp::Aggregate { .. })
         ));
-        validate_default(&composed, ExecutionTiming::IngestionTime).unwrap();
+        validate_maintained(&composed, ExecutionTiming::IngestionTime).unwrap();
         assert_eq!(
             planned_data_state(&composed, ExecutionTiming::IngestionTime).timing,
             ExecutionTiming::IngestionTime
diff --git a/crates/asap-aware-mapping/src/maintained_population.rs b/crates/asap-aware-mapping/src/maintained_population.rs
index 00fee0306..d37c31c11 100644
--- a/crates/asap-aware-mapping/src/maintained_population.rs
+++ b/crates/asap-aware-mapping/src/maintained_population.rs
@@ -331,15 +331,17 @@ mod tests {
     use crate::test_support::lower_promql;
     use asap_types::ir::cse::share_common_sub_dags;
     use asap_types::ir::export::compile_physical_asap_dag as export_timed;
-    use asap_types::ir::timing::{apply_lifecycle_timings, LifecycleAssignment, TimingMemo};
+    use asap_types::ir::timing::{
+        apply_materialization_timings, MaterializationAssignment, TimingMemo,
+    };
 
-    /// Time `root` under the default lifecycle assignment (which runs the
+    /// Time `root` under the default materialization assignment (which runs the
     /// data-state / population-contract validation) and export it.
     fn compile_physical_asap_dag(root: &Rc<OperatorNode>) -> Result<(), String> {
         root.validate_structure().map_err(|e| e.to_string())?;
-        let timed = apply_lifecycle_timings(
+        let timed = apply_materialization_timings(
             root,
-            &LifecycleAssignment::default_maintained(),
+            &MaterializationAssignment::all_query_time(),
             &mut TimingMemo::new(),
         )
         .map_err(|e| format!("{e:?}"))?;
@@ -465,7 +467,7 @@ mod tests {
         assert_eq!(p.grouping, ["instance"]);
         assert_eq!(p.matchers[0].operation, CurrentSeriesMatch::Regex);
     }
-    // Population timing is a lifecycle choice: a retained or rebuilt
+    // Population timing is a materialization choice: a retained or rebuilt
     // population both validate, while its evaluation must stay at query time.
     #[test]
     fn population_timing_is_not_structural() {
diff --git a/crates/asap-aware-mapping/src/pass/mod.rs b/crates/asap-aware-mapping/src/pass/mod.rs
index 02a01000a..6355b8915 100644
--- a/crates/asap-aware-mapping/src/pass/mod.rs
+++ b/crates/asap-aware-mapping/src/pass/mod.rs
@@ -18,7 +18,9 @@ use std::collections::BTreeMap;
 use std::rc::Rc;
 
 use asap_types::ir::export::compile_physical_asap_workload;
-use asap_types::ir::timing::{apply_lifecycle_timings, LifecycleAssignment, TimingMemo};
+use asap_types::ir::timing::{
+    apply_materialization_timings, MaterializationAssignment, TimingMemo,
+};
 use asap_types::ir::OperatorNode;
 use asap_types::parsed_workload::ParsedWorkload;
 use asap_types::post_asap::ExecutionDataStateError;
@@ -217,11 +219,11 @@ impl PlanOutput {
     ) -> Result<asap_types::ir::export::PhysicalASAPDAG, ExecutionDataStateError> {
         // One memo, so a node shared by several roots is timed and exported once.
         let mut memo = TimingMemo::new();
-        let assignment = LifecycleAssignment::default_maintained();
+        let assignment = MaterializationAssignment::all_query_time();
         let timed = self
             .plans
             .iter()
-            .map(|p| apply_lifecycle_timings(&p.root, &assignment, &mut memo))
+            .map(|p| apply_materialization_timings(&p.root, &assignment, &mut memo))
             .collect::<Result<Vec<_>, _>>()?;
         compile_physical_asap_workload(&timed)
     }
diff --git a/crates/asap-aware-mapping/src/replacement.rs b/crates/asap-aware-mapping/src/replacement.rs
index d7a3d5ada..2020be8a5 100644
--- a/crates/asap-aware-mapping/src/replacement.rs
+++ b/crates/asap-aware-mapping/src/replacement.rs
@@ -351,7 +351,7 @@ use std::collections::{HashMap, HashSet, VecDeque};
 use asap_types::ir::cse::{share_common_sub_dags, structural_hash, HashCache};
 use asap_types::ir::operator_properties::{BinaryOpKind, JoinKind, Reduction};
 use asap_types::ir::summary_coverage::{CoverageRegion, SummaryCoverage};
-use asap_types::ir::timing::validate_default;
+use asap_types::ir::timing::validate_maintained;
 use asap_types::ir::SchemaDerivationError;
 use asap_types::ir::{
     ASAPOp, BinaryOperator, NonASAPOp, Operator, OperatorNode, Predicate, ProjectItem, ScalarExpr,
@@ -1399,10 +1399,11 @@ impl<'a> ASAPStrategies<'a> {
         fn place(node: &Rc<OperatorNode>) -> Option<Rc<OperatorNode>> {
             retime_rate_finalize(node, ExecutionTiming::IngestionTime, true)
         }
+        // Legal only if the candidate stays executable with its states maintained.
         let timed = |node: &Rc<OperatorNode>| {
-            asap_types::ir::timing::apply_lifecycle_timings(
+            asap_types::ir::timing::apply_materialization_timings(
                 node,
-                &asap_types::ir::timing::LifecycleAssignment::default_maintained(),
+                &asap_types::ir::timing::MaterializationAssignment::all_ingestion_time(),
                 &mut asap_types::ir::timing::TimingMemo::new(),
             )
             .ok()
@@ -1764,7 +1765,7 @@ impl ReplacementStrategy for ASAPStrategies<'_> {
     /// the logical root does not expose, so each is a finalized query result
     /// for the identity-carrying root. Placement variants (for example,
     /// fixed-window or query-time Rate aggregation) are not listed here: the
-    /// lifecycle assigns timing and the physical compiler reads it.
+    /// materialization assigns timing and the physical compiler reads it.
     fn propose_for_root(&self, root: &Rc<OperatorNode>, target: &AccuracyTarget) -> Proposals {
         let Ok(typed) = asap_types::ir::schema_support::with_promql_series_identity(root) else {
             return Proposals::default();
@@ -1974,7 +1975,7 @@ fn exact_topk_over_temporal_values(
         )
         .with_guarantee(guarantee),
     );
-    validate_default(&node, ExecutionTiming::QueryTime)?;
+    validate_maintained(&node, ExecutionTiming::QueryTime)?;
     Ok(Some(node))
 }
 
@@ -1993,7 +1994,7 @@ fn realize_temporal_average(
         return Ok(None);
     };
     operator.checked_finite_division = true;
-    validate_default(&node, ExecutionTiming::QueryTime)?;
+    validate_maintained(&node, ExecutionTiming::QueryTime)?;
     Ok(Some(node))
 }
 
@@ -2341,7 +2342,7 @@ pub fn finalize_query_candidate(
 
 /// The read boundary's placement is fixed here, where the candidate's
 /// semantics decide it (a fresh query-time summary over this evaluation's
-/// finalized values vs. finalized values feeding maintenance); the lifecycle
+/// finalized values vs. finalized values feeding maintenance); the materialization
 /// timing pass honors it.
 fn finalize_exact_accumulator(
     node: Rc<OperatorNode>,
@@ -2749,7 +2750,7 @@ fn finish_weighted_topk(
         )
         .with_guarantee(guarantee),
     );
-    validate_default(&result, ExecutionTiming::QueryTime)?;
+    validate_maintained(&result, ExecutionTiming::QueryTime)?;
     Ok(result)
 }
 
@@ -3130,7 +3131,7 @@ fn construct_summary_agg(
     } else if snapshot_weighted {
         // Each evaluation's finalized rates feed a fresh summary; rate snapshots
         // must never accumulate across evaluations. Query time is only the
-        // initial layout; a retained summary's lifecycle moves it to ingestion.
+        // initial layout; a maintained summary's materialization moves it to ingestion.
         finalize_query_candidate(bound_child, &input.child)?
     } else {
         let child =
@@ -4205,7 +4206,7 @@ impl<Id> CandidateLogicalASAPDAGs<Id> {
 }
 
 /// DAG candidates assembled from an unpriced search space.
-/// This is an internal planning stage: callers must still validate lifecycle
+/// This is an internal planning stage: callers must still validate materialization
 /// requirements and compile supported physical operators before deployment.
 /// The caller supplies a finite expansion budget; exceeding it is an error,
 /// never a silently truncated inventory presented as exhaustive.
@@ -5220,7 +5221,7 @@ impl<'a> GlobalSelection<'a> {
             return Ok(Rc::clone(node));
         }
         // A selected summary that realizes its inner aggregate, instead of
-        // hiding it in `KeepPreAsap`, is kept; lifecycle assignment decides
+        // hiding it in `KeepPreAsap`, is kept; materialization assignment decides
         // whether it runs in precompute or at query time.
         let selected_composed_summary = self
             .groups
@@ -5364,7 +5365,7 @@ impl<'a> GlobalSelection<'a> {
         let node = Rc::new(
             OperatorNode::with_schema(operator, target.schema.clone()).with_guarantee(guarantee),
         );
-        validate_default(&node, ExecutionTiming::QueryTime)?;
+        validate_maintained(&node, ExecutionTiming::QueryTime)?;
         Ok(node)
     }
 
@@ -5485,7 +5486,7 @@ fn relink_agg_child(node: &Rc<OperatorNode>, new_child: &Rc<OperatorNode>) -> Rc
                 )
                 .with_guarantee(node.guarantee.clone())
             });
-            match validate_default(&rebuilt, ExecutionTiming::IngestionTime) {
+            match validate_maintained(&rebuilt, ExecutionTiming::IngestionTime) {
                 Ok(_) => rebuilt,
                 Err(_) => Rc::clone(node),
             }
@@ -6898,7 +6899,7 @@ mod tests {
     use super::*;
     use crate::accuracy::PropagationStats;
     use crate::cost_model::Cost;
-    use crate::test_support::{agg, agg_per_entity, lower_promql, metric_scan, timed};
+    use crate::test_support::{agg, agg_per_entity, lower_promql, maintained, metric_scan, timed};
     use asap_types::ir::operator_properties::{Reduction as ReductionTy, Source};
     use asap_types::ir::TimeRangeKind;
     use asap_types::pre_asap::agg_intent::{
@@ -6952,9 +6953,9 @@ mod tests {
     }
 
     // Grouped Sum over Rate evaluations stays a summary state in the inventory,
-    // so lifecycle assignment can place it in precompute or at query time.
+    // so materialization assignment can place it in precompute or at query time.
     #[test]
-    fn grouped_rate_sum_inventory_keeps_sum_state_for_lifecycle_placement() {
+    fn grouped_rate_sum_inventory_keeps_sum_state_for_materialization_placement() {
         let root = lower_promql("sum by(job)(rate(m[1m]))", AccuracyTarget::Exact);
         let inventory = search_workload(vec![(0usize, root)])
             .enumerate_candidate_dags(4096)
@@ -10071,8 +10072,8 @@ mod tests {
         let inner = agg(vec![2], AggIntent::Sum { col: None }, metric_scan(&["job"]));
         let outer = agg(vec![], default_quantile(0.9), inner);
         // Timing is not stored during realization: time the candidate under
-        // the default lifecycle assignment to read the maintenance boundary.
-        let root = timed(&realize(&outer).unwrap());
+        // a maintained materialization assignment to read the maintenance boundary.
+        let root = maintained(&realize(&outer).unwrap());
 
         let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &root.operator else {
             panic!("expected estimate root, got {:?}", root.operator);
diff --git a/crates/asap-aware-mapping/src/test_support.rs b/crates/asap-aware-mapping/src/test_support.rs
index b4d0fd99a..f410f915f 100644
--- a/crates/asap-aware-mapping/src/test_support.rs
+++ b/crates/asap-aware-mapping/src/test_support.rs
@@ -51,7 +51,9 @@ pub(crate) fn lower_promql(query: &str, accuracy: AccuracyTarget) -> Rc<Operator
 use std::time::Duration;
 
 use asap_types::ir::operator_properties::{GroupKeys, Reduction, Source};
-use asap_types::ir::timing::{apply_lifecycle_timings, LifecycleAssignment, TimingMemo};
+use asap_types::ir::timing::{
+    apply_materialization_timings, MaterializationAssignment, TimingMemo,
+};
 use asap_types::ir::{NonASAPOp, Predicate, ScalarExpr, TimeRangeKind};
 use asap_types::pre_asap::agg_intent::AggIntent;
 use asap_types::pre_asap::schema::{ColumnId, DataType, Field, Schema};
@@ -173,18 +175,28 @@ pub(crate) fn time_range(range: Duration, child: Rc<OperatorNode>) -> Rc<Operato
     .unwrap()
 }
 
-/// `root` timed under the default (every summary maintained) lifecycle
+/// `root` timed under the default (every summary at query time)
 /// assignment — the shape export and the post-ASAP validators consume.
 pub(crate) fn timed(root: &Rc<OperatorNode>) -> Rc<OperatorNode> {
-    apply_lifecycle_timings(
+    apply_materialization_timings(
+        root,
+        &MaterializationAssignment::all_query_time(),
+        &mut TimingMemo::new(),
+    )
+    .expect("default materialization timings apply")
+}
+
+/// `root` timed with every summary maintained at ingestion time.
+pub(crate) fn maintained(root: &Rc<OperatorNode>) -> Rc<OperatorNode> {
+    apply_materialization_timings(
         root,
-        &LifecycleAssignment::default_maintained(),
+        &MaterializationAssignment::all_ingestion_time(),
         &mut TimingMemo::new(),
     )
-    .expect("default lifecycle timings apply")
+    .expect("maintained materialization timings apply")
 }
 
-/// Time `root` under the default lifecycle assignment (which runs every
+/// Time `root` under the default materialization assignment (which runs every
 /// data-state / population-contract check) and export it as a physical ASAP DAG.
 pub(crate) fn time_and_export(
     root: &Rc<OperatorNode>,
@@ -192,9 +204,9 @@ pub(crate) fn time_and_export(
     asap_types::ir::export::PhysicalASAPDAG,
     asap_types::post_asap::execution_data_state::ExecutionDataStateError,
 > {
-    let timed = apply_lifecycle_timings(
+    let timed = apply_materialization_timings(
         root,
-        &LifecycleAssignment::default_maintained(),
+        &MaterializationAssignment::all_query_time(),
         &mut TimingMemo::new(),
     )?;
     asap_types::ir::export::compile_physical_asap_dag(&timed)
diff --git a/crates/asap-physical-operators/src/physical_planner/candidates.rs b/crates/asap-physical-operators/src/physical_planner/candidates.rs
index eacd1cfa2..afc674418 100644
--- a/crates/asap-physical-operators/src/physical_planner/candidates.rs
+++ b/crates/asap-physical-operators/src/physical_planner/candidates.rs
@@ -1,7 +1,7 @@
 //! Compile maintenance-selected frontiers without deployment-specific DAG rewrites.
 use super::*;
 
-/// One computation realization; lifecycle/window/revision requirements accompany
+/// One computation realization; materialization/window/revision requirements accompany
 /// it during optimization and deployment. Stored outputs have no storage identity.
 /// Deserialization validates the producer/reader boundary.
 #[derive(Clone, serde::Serialize, serde::Deserialize)]
@@ -86,7 +86,7 @@ pub fn cut_candidate(
     })
 }
 
-/// Materialization frontier implied by lifecycle-assigned timing: ingestion-time
+/// Materialization frontier implied by materialization-assigned timing: ingestion-time
 /// nodes read by a query-time node, plus the root when it is ingestion-timed.
 /// `cut_candidate` of one [`compile`] result with this frontier realizes the
 /// assignment, so different assignments are different cuts of one lowering.
@@ -125,7 +125,7 @@ pub fn frontier_from_timing(dag: &PhysicalASAPDAG) -> Result<Vec<NodeId>, Error>
 
 /// Enumerate bounded, reachable materialization frontiers above explicit inputs.
 /// Each frontier is an antichain: storing an output and its ancestor together
-/// would leave the ancestor unused by query execution. Lifecycle eligibility
+/// would leave the ancestor unused by query execution. Materialization eligibility
 /// and deployment feasibility are evaluated separately before cost selection.
 /// Exceeding the search budget returns an error, never a partial inventory.
 pub fn enumerate_frontiers(
@@ -370,9 +370,9 @@ mod tests {
             .assemble_selected_dag(&space.roots[0].1)
             .unwrap()
             .unwrap();
-        let selected = planner_types::ir::apply_lifecycle_timings(
+        let selected = planner_types::ir::apply_materialization_timings(
             &selected,
-            &Default::default(),
+            &planner_types::ir::MaterializationAssignment::all_ingestion_time(),
             &mut Default::default(),
         )
         .unwrap();
@@ -440,8 +440,8 @@ mod tests {
         )])
     }
 
-    /// Cutting one compilation by a retained-state timing and by the all
-    /// query-time timing (what ContinuouslyMaintained and Ephemeral assign)
+    /// Cutting one compilation by a maintained-state timing and by the all
+    /// query-time timing
     /// lowers each Planner node once and matches `compile_candidate`.
     #[test]
     fn timing_cuts_share_one_lowering() {
diff --git a/crates/asap-physical-operators/src/physical_planner/promql_rows.rs b/crates/asap-physical-operators/src/physical_planner/promql_rows.rs
index 20992dfe7..f85d187d5 100644
--- a/crates/asap-physical-operators/src/physical_planner/promql_rows.rs
+++ b/crates/asap-physical-operators/src/physical_planner/promql_rows.rs
@@ -88,9 +88,10 @@ pub fn compile_current_series_evaluation(
     use planner_types::post_asap::{
         maintained_population::PopulationStatistic, Field as SummaryField,
     };
-    let selected = planner_types::ir::apply_lifecycle_timings(
+    // This compiler emits maintained precompute: every summary at ingestion time.
+    let selected = planner_types::ir::apply_materialization_timings(
         selected,
-        &planner_types::ir::LifecycleAssignment::default_maintained(),
+        &planner_types::ir::MaterializationAssignment::all_ingestion_time(),
         &mut planner_types::ir::TimingMemo::new(),
     )
     .map_err(|e| invalid(e.to_string()))?;
@@ -201,9 +202,10 @@ pub fn compile_rate_ranking(
         }
         node.children().into_iter().find_map(frontier)
     }
-    let selected = planner_types::ir::apply_lifecycle_timings(
+    // This compiler emits maintained precompute: every summary at ingestion time.
+    let selected = planner_types::ir::apply_materialization_timings(
         selected,
-        &planner_types::ir::LifecycleAssignment::default_maintained(),
+        &planner_types::ir::MaterializationAssignment::all_ingestion_time(),
         &mut planner_types::ir::TimingMemo::new(),
     )
     .map_err(|e| invalid(e.to_string()))?;
@@ -239,7 +241,7 @@ pub fn compile_rate_ranking(
     Ok((source, program))
 }
 
-/// Compile a lifecycle-timed DAG whose heap or grouped Sum over per-series
+/// Compile a materialization-timed DAG whose heap or grouped Sum over per-series
 /// Rate evaluations runs at ingestion time: fresh aggregate state per closed
 /// window. The input is the complete collection of per-series counter states.
 pub fn compile_fixed_window_rate_aggregation(
diff --git a/crates/asap-physical-operators/tests/common/mod.rs b/crates/asap-physical-operators/tests/common/mod.rs
index 35ba496b4..b3602adbe 100644
--- a/crates/asap-physical-operators/tests/common/mod.rs
+++ b/crates/asap-physical-operators/tests/common/mod.rs
@@ -1,14 +1,16 @@
 #![allow(dead_code)]
 use planner_types::ir::export::PhysicalASAPDAG;
-use planner_types::ir::{apply_lifecycle_timings, LifecycleAssignment, OperatorNode, TimingMemo};
+use planner_types::ir::{
+    apply_materialization_timings, MaterializationAssignment, OperatorNode, TimingMemo,
+};
 use std::rc::Rc;
 
 pub fn compile_physical_asap_dag(
     root: &Rc<OperatorNode>,
 ) -> Result<PhysicalASAPDAG, Box<dyn std::error::Error>> {
-    let root = apply_lifecycle_timings(
+    let root = apply_materialization_timings(
         root,
-        &LifecycleAssignment::default(),
+        &MaterializationAssignment::default(),
         &mut TimingMemo::default(),
     )?;
     Ok(planner_types::ir::export::compile_physical_asap_dag(&root)?)
diff --git a/crates/asap-physical-operators/tests/weighted_topk_binding.rs b/crates/asap-physical-operators/tests/weighted_topk_binding.rs
index bca53bb01..c14d16979 100644
--- a/crates/asap-physical-operators/tests/weighted_topk_binding.rs
+++ b/crates/asap-physical-operators/tests/weighted_topk_binding.rs
@@ -766,10 +766,10 @@ fn spatial_topk_exposes_signed_heap_candidate_over_complete_snapshot() {
 /// rest at query time. The phases are assigned on the exported DAG because
 /// the candidate pins its finalize boundary to query time.
 fn continuously_maintained_dag(candidate: &Rc<planner_types::ir::OperatorNode>) -> PhysicalASAPDAG {
-    use planner_types::ir::{apply_lifecycle_timings, LifecycleAssignment, TimingMemo};
-    let timed = apply_lifecycle_timings(
+    use planner_types::ir::{apply_materialization_timings, MaterializationAssignment, TimingMemo};
+    let timed = apply_materialization_timings(
         candidate,
-        &LifecycleAssignment::default_maintained(),
+        &MaterializationAssignment::all_query_time(),
         &mut TimingMemo::new(),
     )
     .unwrap();
@@ -809,7 +809,7 @@ fn continuously_maintained_dag(candidate: &Rc<planner_types::ir::OperatorNode>)
 // A maintained heap over finalized per-series Rate is the fixed-window
 // placement: materialization timing, not a separate candidate, puts it in precompute.
 #[test]
-fn maintained_rate_heap_lifecycle_compiles_fixed_window_precompute() {
+fn maintained_rate_heap_compiles_fixed_window_precompute() {
     use asap_physical_operators::physical_planner::{
         compile_candidate, promql_rows::with_series_identity,
     };
diff --git a/crates/devtools/src/bin/show_post_asap_ir.rs b/crates/devtools/src/bin/show_post_asap_ir.rs
index df6c2bfd5..4565657f9 100644
--- a/crates/devtools/src/bin/show_post_asap_ir.rs
+++ b/crates/devtools/src/bin/show_post_asap_ir.rs
@@ -176,9 +176,9 @@ mod tests {
             candidates[0].guarantee.is_none(),
             "missing evidence must not claim a certified ratio bound"
         );
-        let timed = asap_types::ir::timing::apply_lifecycle_timings(
+        let timed = asap_types::ir::timing::apply_materialization_timings(
             &candidates[0],
-            &asap_types::ir::timing::LifecycleAssignment::default_maintained(),
+            &asap_types::ir::timing::MaterializationAssignment::all_query_time(),
             &mut asap_types::ir::timing::TimingMemo::new(),
         )
         .expect("the demo candidate has a legal default timing");
diff --git a/crates/frontend-promql/tests/support.rs b/crates/frontend-promql/tests/support.rs
index bba2656f2..c095eae2d 100644
--- a/crates/frontend-promql/tests/support.rs
+++ b/crates/frontend-promql/tests/support.rs
@@ -69,18 +69,18 @@ pub fn promql_scalar(node: &ScalarExpr) -> Option<f64> {
     }
 }
 
-/// Time `root` under the default (every summary maintained) lifecycle
-/// assignment and export the post-ASAP DAG — the wire-6 export needs every
-/// node timed first.
+/// Time `root` under the default materialization assignment (every summary
+/// at query time) and export the physical DAG — export needs every node
+/// timed first.
 #[allow(dead_code)]
 pub fn post_asap_dag(root: &Rc<OperatorNode>) -> asap_types::ir::export::PhysicalASAPDAG {
-    use asap_types::ir::{apply_lifecycle_timings, LifecycleAssignment, TimingMemo};
-    let timed = apply_lifecycle_timings(
+    use asap_types::ir::{apply_materialization_timings, MaterializationAssignment, TimingMemo};
+    let timed = apply_materialization_timings(
         root,
-        &LifecycleAssignment::default_maintained(),
+        &MaterializationAssignment::all_query_time(),
         &mut TimingMemo::new(),
     )
-    .expect("default lifecycle timings");
+    .expect("default materialization timings");
     asap_types::ir::export::compile_physical_asap_dag(&timed).expect("post-ASAP DAG export")
 }
 
diff --git a/crates/frontend-sql/tests/maintained_population.rs b/crates/frontend-sql/tests/maintained_population.rs
index b01fbbd69..285dfe942 100644
--- a/crates/frontend-sql/tests/maintained_population.rs
+++ b/crates/frontend-sql/tests/maintained_population.rs
@@ -3,8 +3,9 @@ use asap_aware_mapping::maintained_population::MaintainedPopulationStrategy;
 use asap_frontend_sql::{lower_sql, SqlCatalog};
 use asap_types::{
     ir::{
-        apply_lifecycle_timings, cse::share_common_sub_dags, export::compile_physical_asap_dag,
-        ASAPOp, LifecycleAssignment, NonASAPOp, Operator, OperatorNode, TimingMemo,
+        apply_materialization_timings, cse::share_common_sub_dags,
+        export::compile_physical_asap_dag, ASAPOp, MaterializationAssignment, NonASAPOp, Operator,
+        OperatorNode, TimingMemo,
     },
     post_asap::maintained_population::{MaintainedPopulation, PopulationInput},
     pre_asap::{DataType, Field, Schema},
@@ -37,12 +38,12 @@ fn population(mut node: &OperatorNode) -> (&Rc<OperatorNode>, &MaintainedPopulat
     (child, population)
 }
 
-/// Export `plan` the way the planner does: assign the default lifecycle
+/// Export `plan` the way the planner does: assign the default materialization
 /// timings, then compile the timed DAG.
 fn compile(plan: &Rc<OperatorNode>) -> Result<(), String> {
-    let timed = apply_lifecycle_timings(
+    let timed = apply_materialization_timings(
         plan,
-        &LifecycleAssignment::default_maintained(),
+        &MaterializationAssignment::all_query_time(),
         &mut TimingMemo::new(),
     )
     .map_err(|e| e.to_string())?;
diff --git a/crates/frontend-sql/tests/pearson_corr.rs b/crates/frontend-sql/tests/pearson_corr.rs
index 8ef1fb415..560da2b48 100644
--- a/crates/frontend-sql/tests/pearson_corr.rs
+++ b/crates/frontend-sql/tests/pearson_corr.rs
@@ -3,8 +3,8 @@ use std::rc::Rc;
 
 use asap_frontend_sql::{lower_sql, SqlCatalog};
 use asap_types::ir::{
-    apply_lifecycle_timings, export::compile_physical_asap_dag, LifecycleAssignment, NonASAPOp,
-    OperatorNode, ScalarExpr, TimingMemo,
+    apply_materialization_timings, export::compile_physical_asap_dag, MaterializationAssignment,
+    NonASAPOp, OperatorNode, ScalarExpr, TimingMemo,
 };
 use asap_types::pre_asap::{AggIntent, DataType, Field, Schema};
 use asap_types::types::AccuracyTarget;
@@ -152,9 +152,9 @@ async fn corr_survives_exact_plan_compilation() {
     // The exact fallback is the query's own operator DAG, no ASAP node added.
     assert!(!plan.contains_asap(), "expected exact fallback");
     assert_eq!(aggregate(&plan).0, aggregate(&query).0);
-    let timed = apply_lifecycle_timings(
+    let timed = apply_materialization_timings(
         &plan,
-        &LifecycleAssignment::default_maintained(),
+        &MaterializationAssignment::all_query_time(),
         &mut TimingMemo::new(),
     )
     .unwrap();
diff --git a/crates/integration-tests/src/lib.rs b/crates/integration-tests/src/lib.rs
index 7ded8981b..af9598cd3 100644
--- a/crates/integration-tests/src/lib.rs
+++ b/crates/integration-tests/src/lib.rs
@@ -100,22 +100,37 @@ pub mod fixtures {
 /// Timing and export helpers for post-ASAP plans.
 pub mod post_asap {
     use asap_types::ir::export::{compile_physical_asap_dag, PhysicalASAPDAG};
-    use asap_types::ir::{apply_lifecycle_timings, LifecycleAssignment, OperatorNode, TimingMemo};
+    use asap_types::ir::{
+        apply_materialization_timings, MaterializationAssignment, OperatorNode, TimingMemo,
+    };
     use std::rc::Rc;
 
-    /// Time `root` under the default (every summary maintained) lifecycle
-    /// assignment. Returns the timed copy; read `node.timing` on it.
+    /// Time `root` under the default assignment (every summary computed at
+    /// query time). Returns the timed copy; read `node.timing` on it.
     pub fn timed(root: &Rc<OperatorNode>) -> Rc<OperatorNode> {
-        apply_lifecycle_timings(
-            root,
-            &LifecycleAssignment::default_maintained(),
-            &mut TimingMemo::new(),
-        )
-        .expect("default lifecycle timing failed")
+        timed_with(root, &MaterializationAssignment::all_query_time())
+    }
+
+    /// Time `root` with every summary maintained at ingestion time.
+    pub fn maintained(root: &Rc<OperatorNode>) -> Rc<OperatorNode> {
+        timed_with(root, &MaterializationAssignment::all_ingestion_time())
     }
 
-    /// Time `root` (default assignment), then export the wire-6 DAG.
+    fn timed_with(
+        root: &Rc<OperatorNode>,
+        assignment: &MaterializationAssignment,
+    ) -> Rc<OperatorNode> {
+        apply_materialization_timings(root, assignment, &mut TimingMemo::new())
+            .expect("materialization timing failed")
+    }
+
+    /// Time `root` (default assignment), then export the physical DAG.
     pub fn post_asap_dag(root: &Rc<OperatorNode>) -> PhysicalASAPDAG {
         compile_physical_asap_dag(&timed(root)).expect("post-ASAP DAG export failed")
     }
+
+    /// Time `root` with every summary maintained, then export the physical DAG.
+    pub fn maintained_post_asap_dag(root: &Rc<OperatorNode>) -> PhysicalASAPDAG {
+        compile_physical_asap_dag(&maintained(root)).expect("post-ASAP DAG export failed")
+    }
 }
diff --git a/crates/integration-tests/tests/exact_composition.rs b/crates/integration-tests/tests/exact_composition.rs
index f72458377..f8e069a3d 100644
--- a/crates/integration-tests/tests/exact_composition.rs
+++ b/crates/integration-tests/tests/exact_composition.rs
@@ -25,7 +25,7 @@ use asap_aware_mapping::{
     CostModel, DefaultCostModel, EvaluationRate, ExplanationKind, OperationPlacement,
 };
 use asap_integration_tests::fixtures::lower_promql;
-use asap_integration_tests::post_asap::{post_asap_dag, timed};
+use asap_integration_tests::post_asap::{maintained, post_asap_dag, timed};
 use asap_types::dag_export;
 use asap_types::ir::export::{NonASAPOpKind, PhysicalASAPOperatorPayload};
 use asap_types::ir::operator_properties::{Reduction, Source};
@@ -385,9 +385,9 @@ fn every_exact_accumulator_is_finalized_before_an_outer_sketch() {
         let Replacement::SubDAG(root) = &candidates[0].replacement else {
             unreachable!()
         };
-        // Timing is not stored on the plan: time it (default lifecycle,
-        // which also validates every edge) and inspect the timed copy.
-        let root = timed(root);
+        // Timing is not stored on the plan: time it with the outer summary
+        // maintained (which also validates every edge) and inspect the copy.
+        let root = maintained(root);
         let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &root.operator else {
             panic!("expected KLL evaluation, got {:?}", root.operator);
         };
@@ -668,8 +668,8 @@ fn outer_summary_over_an_exact_function_composes_at_ingestion_time() {
     assert!(decision.cost_rate < decision.baseline_rate);
 
     let composed = selection.assemble_selected_dag(&root).unwrap().unwrap();
-    // Walk the timed copy: timing is written by the lifecycle assignment.
-    let composed = timed(&composed);
+    // Walk the timed copy, with the outer summary maintained at ingestion time.
+    let composed = maintained(&composed);
     let Operator::ASAP(ASAPOp::SummaryEstimate { summary_input, .. }) = &composed.operator else {
         panic!("expected evaluation root, got {:?}", composed.operator);
     };
@@ -723,7 +723,7 @@ fn summary_construction_follows_its_value_input_phase() {
     // time, because a evaluation sits below it.
     let state = asap_types::ir::planned_data_state(&illegal, ExecutionTiming::IngestionTime);
     assert_eq!(state.timing, ExecutionTiming::QueryTime);
-    asap_types::ir::validate_default(&illegal, state.timing).unwrap();
+    asap_types::ir::validate_maintained(&illegal, state.timing).unwrap();
 }
 
 #[test]
diff --git a/crates/integration-tests/tests/physical_common/mod.rs b/crates/integration-tests/tests/physical_common/mod.rs
index e23e9721d..fc4c2b655 100644
--- a/crates/integration-tests/tests/physical_common/mod.rs
+++ b/crates/integration-tests/tests/physical_common/mod.rs
@@ -46,10 +46,29 @@ pub fn execute(
 pub fn compile_physical_asap_dag(
     root: &std::rc::Rc<asap_types::ir::OperatorNode>,
 ) -> Result<asap_types::ir::export::PhysicalASAPDAG, Box<dyn std::error::Error>> {
-    let root = asap_types::ir::apply_lifecycle_timings(
+    compile_with(
         root,
-        &Default::default(),
-        &mut Default::default(),
-    )?;
+        &asap_types::ir::MaterializationAssignment::all_query_time(),
+    )
+}
+
+/// As [`compile_physical_asap_dag`], with every summary maintained at
+/// ingestion time, the placement precompute compilation requires.
+#[allow(dead_code)] // Not every test binary sharing this module compiles precompute.
+pub fn compile_maintained_physical_asap_dag(
+    root: &std::rc::Rc<asap_types::ir::OperatorNode>,
+) -> Result<asap_types::ir::export::PhysicalASAPDAG, Box<dyn std::error::Error>> {
+    compile_with(
+        root,
+        &asap_types::ir::MaterializationAssignment::all_ingestion_time(),
+    )
+}
+
+fn compile_with(
+    root: &std::rc::Rc<asap_types::ir::OperatorNode>,
+    assignment: &asap_types::ir::MaterializationAssignment,
+) -> Result<asap_types::ir::export::PhysicalASAPDAG, Box<dyn std::error::Error>> {
+    let root =
+        asap_types::ir::apply_materialization_timings(root, assignment, &mut Default::default())?;
     Ok(asap_types::ir::export::compile_physical_asap_dag(&root)?)
 }
diff --git a/crates/integration-tests/tests/precompute_raw_samples.rs b/crates/integration-tests/tests/precompute_raw_samples.rs
index 4bc8f7ace..f0a270b0d 100644
--- a/crates/integration-tests/tests/precompute_raw_samples.rs
+++ b/crates/integration-tests/tests/precompute_raw_samples.rs
@@ -3,7 +3,7 @@
 mod physical_common;
 use asap_types::ir::export::{PhysicalASAPDAG, PhysicalASAPOperatorPayload};
 use asap_types::ir::OperatorNode;
-use physical_common::compile_physical_asap_dag;
+use physical_common::compile_maintained_physical_asap_dag;
 use std::{collections::BTreeMap, collections::BTreeSet, rc::Rc, sync::Arc};
 
 use asap_aware_mapping::cost_model::DefaultCostModel;
@@ -421,7 +421,7 @@ fn raw_sample_summaries_compile_and_match_their_kernels() {
     let mut checked = BTreeMap::new();
     for (query, accuracy) in queries {
         for candidate in candidates(query, accuracy.clone()) {
-            let dag = compile_physical_asap_dag(&candidate).unwrap();
+            let dag = compile_maintained_physical_asap_dag(&candidate).unwrap();
             for (source, root) in raw_summaries(&dag) {
                 match check(query, &dag, source, root, &rows) {
                     Ok(family) => {
@@ -474,7 +474,7 @@ fn grouped_raw_summary(family: FieldDataType, input: SummaryUpdate) -> (Physical
     )
     .pop()
     .unwrap();
-    let mut dag = compile_physical_asap_dag(&candidate).unwrap();
+    let mut dag = compile_maintained_physical_asap_dag(&candidate).unwrap();
     let (source, root) = raw_summaries(&dag)[0];
     let node = dag
         .nodes
diff --git a/crates/integration-tests/tests/promql_to_post_asap.rs b/crates/integration-tests/tests/promql_to_post_asap.rs
index 9ce1d5d72..24c4209ec 100644
--- a/crates/integration-tests/tests/promql_to_post_asap.rs
+++ b/crates/integration-tests/tests/promql_to_post_asap.rs
@@ -19,7 +19,9 @@ use asap_aware_mapping::{
     ReplacementStrategy, ReplacementSubDAG, TargetSubDAG,
 };
 use asap_integration_tests::fixtures::lower_promql;
-use asap_integration_tests::post_asap::{post_asap_dag, timed};
+use asap_integration_tests::post_asap::{
+    maintained, maintained_post_asap_dag, post_asap_dag, timed,
+};
 use asap_types::ir::export::{NonASAPOpKind, PhysicalASAPOperatorPayload};
 use asap_types::ir::operator_properties::Reduction;
 use asap_types::ir::{ASAPOp, NonASAPOp, Operator, OperatorNode, ScalarExpr};
@@ -1063,8 +1065,9 @@ fn nested_summary_explicitly_finalizes_exact_child_at_ingestion_time() {
         .assemble_selected_dag(&space.roots[0].1)
         .unwrap()
         .unwrap();
-    // Stored timings are gone: time the plan and read the timed copy.
-    let timed_plan = timed(&plan);
+    // Stored timings are gone: time the plan with its outer summary
+    // maintained and read the timed copy.
+    let timed_plan = maintained(&plan);
     let Some(ASAPOp::SummaryEstimate { summary_input, .. }) = timed_plan.asap() else {
         panic!("expected selected quantile summary");
     };
@@ -1123,7 +1126,7 @@ fn physical_node_owns_phase_independently_of_binary_payload() {
             .assemble_selected_dag(&search.roots[0].1)
             .unwrap()
             .unwrap();
-        let dag = post_asap_dag(&plan);
+        let dag = maintained_post_asap_dag(&plan);
         let node = dag
             .nodes
             .iter()
diff --git a/crates/types/src/ir/mod.rs b/crates/types/src/ir/mod.rs
index c4441068b..01d1da021 100644
--- a/crates/types/src/ir/mod.rs
+++ b/crates/types/src/ir/mod.rs
@@ -19,11 +19,11 @@ pub mod cse;
 pub mod export;
 /// Physical ASAP DAG transport: the logical payloads plus execution timing.
 pub mod physical_export;
-/// Execution timing for physical plans: a lifecycle assignment expanded onto every node.
+/// Execution timing for physical plans: a materialization assignment expanded onto every node.
 pub mod timing;
 pub use timing::{
-    apply_lifecycle_timings, data_state, planned_data_state, split_shared_by_phase,
-    validate_default, LifecycleAssignment, TimingMemo,
+    apply_materialization_timings, data_state, planned_data_state, split_shared_by_phase,
+    validate_maintained, MaterializationAssignment, TimingMemo,
 };
 /// Semantic observation coverage, separate from field layout and physical timing.
 pub mod summary_coverage;
diff --git a/crates/types/src/ir/node.rs b/crates/types/src/ir/node.rs
index cc71d32e5..15431962f 100644
--- a/crates/types/src/ir/node.rs
+++ b/crates/types/src/ir/node.rs
@@ -89,7 +89,7 @@ impl Operator {
 /// `schema` and `result_kind` are derived from `operator` and its children
 /// at construction and retained. `guarantee` is `None` until accuracy
 /// assessment establishes one (`None` never means exact). `timing` is `None`
-/// until a lifecycle assignment is applied; export rejects an executable
+/// until a materialization assignment is applied; export rejects an executable
 /// node without one.
 #[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
 pub struct OperatorNode {
diff --git a/crates/types/src/ir/physical_export.rs b/crates/types/src/ir/physical_export.rs
index 2a8c8fd5f..cc38ddf7c 100644
--- a/crates/types/src/ir/physical_export.rs
+++ b/crates/types/src/ir/physical_export.rs
@@ -2,7 +2,7 @@
 //!
 //! Same operator payloads as the logical export, plus the execution timing
 //! (data state) of every node and edge. The input must already be timed
-//! ([`super::timing::apply_lifecycle_timings`]); export reads each node's
+//! ([`super::timing::apply_materialization_timings`]); export reads each node's
 //! timing and does not re-run data-state validation.
 
 use std::collections::{BTreeMap, HashMap, HashSet};
@@ -336,7 +336,7 @@ pub fn compile_physical_asap_dag(
 }
 
 /// Export the timed DAG below `root`. Every reachable node must carry a
-/// timing (see [`super::timing::apply_lifecycle_timings`]); the data-state
+/// timing (see [`super::timing::apply_materialization_timings`]); the data-state
 /// rules were checked by that pass and are not re-run here.
 pub fn compile_physical_asap_dag_with_node_ids(
     root: &Rc<OperatorNode>,
diff --git a/crates/types/src/ir/timing.rs b/crates/types/src/ir/timing.rs
index e19513ba3..eb6f5a9d5 100644
--- a/crates/types/src/ir/timing.rs
+++ b/crates/types/src/ir/timing.rs
@@ -1,16 +1,18 @@
-//! Execution timing: written into every node from a lifecycle assignment,
-//! then validated against each operator's kind and its consuming edges.
+//! Execution timing: written into every node from a materialization
+//! assignment, then validated against each operator's kind and its consuming
+//! edges.
 //!
-//! The logical DAG carries no timing. Summary materialization chooses a
-//! lifecycle per summary state; [`LifecycleAssignment`] records that choice
-//! (ingestion-time maintenance or query-time recomputation per `SummaryAgg`)
-//! and [`apply_lifecycle_timings`] expands it into a timing on every node:
+//! The logical DAG carries no timing. Materialization decides per summary
+//! state whether it is maintained at ingestion time or computed at query
+//! time; [`MaterializationAssignment`] records that choice per `SummaryAgg`
+//! and [`apply_materialization_timings`] expands it into a timing on every node:
 //!
 //! - a node of fixed kind takes its kind's timing (`SummaryEstimate` and
 //!   `EvaluatePopulation` run at query time, `MaintainPopulation` at ingestion
 //!   time);
-//! - a `SummaryAgg` takes the assignment's timing (default: ingestion time),
-//!   unless something below it can only exist at query time;
+//! - a `SummaryAgg` takes the assignment's timing (default: query time, until
+//!   Stage 2 materialization (#509) chooses otherwise), unless something below
+//!   it can only exist at query time;
 //! - every other node runs when its consumer runs: everything that feeds a
 //!   maintained state runs at ingestion time, everything above a evaluation at
 //!   query time.
@@ -43,23 +45,31 @@ use crate::post_asap::execution_data_state::{
 };
 use crate::pre_asap::schema::{DataType, FieldDataType, Schema};
 
-/// The per-state lifecycle choice summary materialization made: for each
-/// `SummaryAgg` node (by identity), whether its state is maintained at
-/// ingestion time or recomputed at query time. A state absent from the map
-/// takes the default, ingestion-time maintenance.
+/// The per-state materialization choice: for each `SummaryAgg` node (by
+/// identity), whether its state is maintained at ingestion time or computed
+/// at query time. A state absent from the map takes the assignment's default.
+/// `Default` is [`Self::all_query_time`]: nothing is materialized until Stage 2
+/// materialization (#509) decides otherwise.
 #[derive(Debug, Clone, Default)]
-pub struct LifecycleAssignment {
+pub struct MaterializationAssignment {
     summary_timings: HashMap<*const OperatorNode, ExecutionTiming>,
+    default_timing: ExecutionTiming,
 }
 
-impl LifecycleAssignment {
-    /// The assignment under which every summary state is maintained at
-    /// ingestion time — the timings every plan carried before lifecycles
-    /// became a planning choice.
-    pub fn default_maintained() -> Self {
+impl MaterializationAssignment {
+    /// Every summary state computed at query time.
+    pub fn all_query_time() -> Self {
         Self::default()
     }
 
+    /// Every summary state maintained at ingestion time.
+    pub fn all_ingestion_time() -> Self {
+        Self {
+            summary_timings: HashMap::new(),
+            default_timing: ExecutionTiming::IngestionTime,
+        }
+    }
+
     pub fn set(&mut self, summary: &Rc<OperatorNode>, timing: ExecutionTiming) {
         self.summary_timings.insert(Rc::as_ptr(summary), timing);
     }
@@ -68,11 +78,11 @@ impl LifecycleAssignment {
         self.summary_timings
             .get(&Rc::as_ptr(summary))
             .copied()
-            .unwrap_or(ExecutionTiming::IngestionTime)
+            .unwrap_or(self.default_timing)
     }
 }
 
-/// Memo of one [`apply_lifecycle_timings`] pass: `input node → timed node`,
+/// Memo of one [`apply_materialization_timings`] pass: `input node → timed node`,
 /// shared by every root of a workload so a node shared by two roots stays
 /// one `Rc`. Re-reaching a node with a different timing is a conflict.
 #[derive(Default)]
@@ -137,9 +147,9 @@ fn forces_query_time(node: &OperatorNode, seen: &mut HashMap<*const OperatorNode
 /// Write the timings of `assignment` into every node reachable from `root`,
 /// top-down, then validate every edge. Returns the timed copy of `root`;
 /// `memo` carries the sharing across the roots of one workload.
-pub fn apply_lifecycle_timings(
+pub fn apply_materialization_timings(
     root: &Rc<OperatorNode>,
-    assignment: &LifecycleAssignment,
+    assignment: &MaterializationAssignment,
     memo: &mut TimingMemo,
 ) -> Result<Rc<OperatorNode>, ExecutionDataStateError> {
     let mut forced = HashMap::new();
@@ -159,24 +169,26 @@ pub fn apply_lifecycle_timings(
     Ok(timed)
 }
 
-/// Validate the sub-DAG below `root` under the default (every summary
-/// maintained) assignment, with `root` consumed at `root_timing`. For
-/// planning-time legality checks of a candidate before it is assembled into
-/// a workload DAG; nothing is kept.
-pub fn validate_default(
+/// Validate the sub-DAG below `root` with every summary maintained at
+/// ingestion time ([`MaterializationAssignment::all_ingestion_time`]) and
+/// `root` consumed at `root_timing`. For planning-time legality checks of a
+/// candidate before it is assembled into a workload DAG: a candidate must stay
+/// executable if materialization later maintains its states. Nothing is kept.
+pub fn validate_maintained(
     root: &Rc<OperatorNode>,
     root_timing: ExecutionTiming,
 ) -> Result<(), ExecutionDataStateError> {
-    let assignment = LifecycleAssignment::default_maintained();
+    let assignment = MaterializationAssignment::all_ingestion_time();
     let mut memo = TimingMemo::new();
     let mut forced = HashMap::new();
     let timed = write(root, root_timing, &assignment, &mut memo, &mut forced)?;
     validate(&timed, &mut HashMap::new())
 }
 
-/// The data state `node` produces under the default assignment when its
-/// consumer runs at `consumer` — the planning-time answer to "what does this
-/// candidate's output look like" before any assignment is applied.
+/// The data state `node` produces with every summary maintained at ingestion
+/// time when its consumer runs at `consumer` — the planning-time answer to
+/// "what does this candidate's output look like", consistent with
+/// [`validate_maintained`].
 pub fn planned_data_state(
     node: &Rc<OperatorNode>,
     consumer: ExecutionTiming,
@@ -185,7 +197,7 @@ pub fn planned_data_state(
     let timing = own_timing(
         node,
         consumer,
-        &LifecycleAssignment::default_maintained(),
+        &MaterializationAssignment::all_ingestion_time(),
         &mut forced,
     );
     ExecutionDataState {
@@ -202,7 +214,7 @@ pub fn planned_data_state(
 fn own_timing(
     node: &Rc<OperatorNode>,
     consumer: ExecutionTiming,
-    assignment: &LifecycleAssignment,
+    assignment: &MaterializationAssignment,
     forced: &mut HashMap<*const OperatorNode, bool>,
 ) -> ExecutionTiming {
     // A placement fixed when the candidate was built (an exact-state read
@@ -229,7 +241,7 @@ fn own_timing(
 fn write(
     node: &Rc<OperatorNode>,
     consumer: ExecutionTiming,
-    assignment: &LifecycleAssignment,
+    assignment: &MaterializationAssignment,
     memo: &mut TimingMemo,
     forced: &mut HashMap<*const OperatorNode, bool>,
 ) -> Result<Rc<OperatorNode>, ExecutionDataStateError> {
@@ -560,7 +572,7 @@ fn validate_non_asap(
 /// one timing stays one `Rc`. Returns the (possibly rewritten) root.
 pub fn split_shared_by_phase(
     root: &Rc<OperatorNode>,
-    assignment: &LifecycleAssignment,
+    assignment: &MaterializationAssignment,
 ) -> Rc<OperatorNode> {
     // First pass: the set of timings each node is reached with.
     let mut reached: HashMap<*const OperatorNode, Vec<ExecutionTiming>> = HashMap::new();
@@ -568,7 +580,7 @@ pub fn split_shared_by_phase(
     fn collect(
         node: &Rc<OperatorNode>,
         consumer: ExecutionTiming,
-        assignment: &LifecycleAssignment,
+        assignment: &MaterializationAssignment,
         reached: &mut HashMap<*const OperatorNode, Vec<ExecutionTiming>>,
         forced: &mut HashMap<*const OperatorNode, bool>,
     ) {
@@ -598,7 +610,7 @@ pub fn split_shared_by_phase(
     fn rebuild(
         node: &Rc<OperatorNode>,
         consumer: ExecutionTiming,
-        assignment: &LifecycleAssignment,
+        assignment: &MaterializationAssignment,
         reached: &HashMap<*const OperatorNode, Vec<ExecutionTiming>>,
         copies: &mut HashMap<(*const OperatorNode, ExecutionTiming), Rc<OperatorNode>>,
         forced: &mut HashMap<*const OperatorNode, bool>,
@@ -764,10 +776,12 @@ mod tests {
         )
     }
 
+    /// Apply with every summary maintained, the placement whose edge rules
+    /// these tests exercise.
     fn apply(root: &Rc<OperatorNode>) -> Result<Rc<OperatorNode>, ExecutionDataStateError> {
-        apply_lifecycle_timings(
+        apply_materialization_timings(
             root,
-            &LifecycleAssignment::default_maintained(),
+            &MaterializationAssignment::all_ingestion_time(),
             &mut TimingMemo::new(),
         )
     }
@@ -776,6 +790,38 @@ mod tests {
         Rc::clone(node.children()[0])
     }
 
+    /// Without a materialization decision, a summary and its input run at
+    /// query time; an explicit per-state choice overrides the default.
+    #[test]
+    fn default_assignment_materializes_nothing() {
+        let summary = agg(scan(), kll());
+        let root = apply_materialization_timings(
+            &summary,
+            &MaterializationAssignment::default(),
+            &mut TimingMemo::new(),
+        )
+        .unwrap();
+        assert_eq!(
+            data_state(&root),
+            Some(ExecutionDataState {
+                timing: ExecutionTiming::QueryTime,
+                primitive: DataPrimitive::SummaryState,
+            })
+        );
+        assert_eq!(
+            data_state(&child(&root)),
+            Some(ExecutionDataState::QUERY_ROWS)
+        );
+        let mut assignment = MaterializationAssignment::all_query_time();
+        assignment.set(&summary, ExecutionTiming::IngestionTime);
+        let root =
+            apply_materialization_timings(&summary, &assignment, &mut TimingMemo::new()).unwrap();
+        assert_eq!(
+            data_state(&root),
+            Some(ExecutionDataState::INGESTION_SUMMARY)
+        );
+    }
+
     #[test]
     fn summary_agg_input_runs_at_ingestion_time() {
         let root = apply(&agg(scan(), kll())).unwrap();
@@ -873,7 +919,7 @@ mod tests {
                 second: ExecutionDataState::QUERY_ROWS,
             })
         );
-        let split = split_shared_by_phase(&root, &LifecycleAssignment::default_maintained());
+        let split = split_shared_by_phase(&root, &MaterializationAssignment::all_ingestion_time());
         assert!(apply(&split).is_ok());
     }
 
@@ -896,10 +942,10 @@ mod tests {
         };
         for operand in [1, 2] {
             assert!(matches!(
-                validate_default(&corr_over(operand), ExecutionTiming::QueryTime),
+                validate_maintained(&corr_over(operand), ExecutionTiming::QueryTime),
                 Err(ExecutionDataStateError::NonPlainOperand { .. })
             ));
         }
-        validate_default(&corr_over(3), ExecutionTiming::QueryTime).unwrap();
+        validate_maintained(&corr_over(3), ExecutionTiming::QueryTime).unwrap();
     }
 }
diff --git a/crates/types/src/post_asap/execution_data_state.rs b/crates/types/src/post_asap/execution_data_state.rs
index de764ea2c..ad6e28781 100644
--- a/crates/types/src/post_asap/execution_data_state.rs
+++ b/crates/types/src/post_asap/execution_data_state.rs
@@ -138,9 +138,11 @@ pub enum ExecutionDataStateError {
     /// `SummaryDelete`, `SummaryJoin`, `Extension`) in an executable plan.
     #[error("{operator} is a reserved operator with no execution contract yet")]
     UnimplementedOperator { operator: &'static str },
-    /// A node reached by export without a timing: the lifecycle timing pass
+    /// A node reached by export without a timing: the materialization timing pass
     /// was not applied to the DAG first.
-    #[error("{operator} node has no execution timing; apply lifecycle timings before export")]
+    #[error(
+        "{operator} node has no execution timing; apply materialization timings before export"
+    )]
     UntimedNode { operator: &'static str },
 }
 
diff --git a/crates/types/tests/physical_export.rs b/crates/types/tests/physical_export.rs
index eaafb7dd2..f69cc5c9b 100644
--- a/crates/types/tests/physical_export.rs
+++ b/crates/types/tests/physical_export.rs
@@ -4,8 +4,8 @@ use asap_types::ir::export::{
 };
 use asap_types::ir::summary_coverage::{CoverageRegion, SummaryCoverage};
 use asap_types::ir::{
-    apply_lifecycle_timings, ASAPOp, LifecycleAssignment, NonASAPOp, Operator, OperatorNode,
-    TimingMemo,
+    apply_materialization_timings, ASAPOp, MaterializationAssignment, NonASAPOp, Operator,
+    OperatorNode, TimingMemo,
 };
 use asap_types::post_asap::{ExactKind, ExactParams, ExecutionTiming, SummaryUpdate};
 use asap_types::pre_asap::{ColumnRef, DataType, Field, FieldDataType, Reduction, Schema, Source};
@@ -48,12 +48,12 @@ fn plan() -> Rc<OperatorNode> {
     .unwrap()
 }
 
-/// Default lifecycle: the summary is maintained at ingestion time and read at query time.
+/// A summary maintained at ingestion time is read at query time.
 #[test]
 fn timed_plan_exports_with_timing_and_coverage() {
-    let timed = apply_lifecycle_timings(
+    let timed = apply_materialization_timings(
         &plan(),
-        &LifecycleAssignment::default_maintained(),
+        &MaterializationAssignment::all_ingestion_time(),
         &mut TimingMemo::new(),
     )
     .unwrap();
@@ -80,9 +80,9 @@ fn timed_plan_exports_with_timing_and_coverage() {
 /// A query-time producer cannot feed an ingestion-time consumer.
 #[test]
 fn query_time_input_to_ingestion_is_rejected() {
-    let timed = apply_lifecycle_timings(
+    let timed = apply_materialization_timings(
         &plan(),
-        &LifecycleAssignment::default_maintained(),
+        &MaterializationAssignment::all_ingestion_time(),
         &mut TimingMemo::new(),
     )
     .unwrap();
@@ -111,11 +111,11 @@ fn batch_shares_the_summary_and_keeps_one_root_per_query() {
         child: state,
     }))
     .unwrap();
-    let assignment = LifecycleAssignment::default_maintained();
+    let assignment = MaterializationAssignment::all_query_time();
     let mut memo = TimingMemo::new();
     let timed: Vec<_> = [first, second]
         .iter()
-        .map(|root| apply_lifecycle_timings(root, &assignment, &mut memo).unwrap())
+        .map(|root| apply_materialization_timings(root, &assignment, &mut memo).unwrap())
         .collect();
     let dag = compile_physical_asap_workload(&timed).unwrap();
     dag.validate().unwrap();

From d83ad48b767da2935e61212beedd60ea3aea01b4 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 21:23:55 +0000
Subject: [PATCH 44/48] docs: drop the summary maintenance lifecycle and
 document the query-time default

Remove the lifecycle APIs, recipes and viewer section from the docs, delete
the workload-demand-and-summary-lifecycle proposal, and point materialization
questions to Stage 2 (#509). Rename LifecycleAssignment/apply_lifecycle_timings/
validate_default to their new names and describe the all-query-time default.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 docs/README.md                                |   3 +-
 docs/design_docs/architecture/README.md       |  34 +--
 .../architecture/asap-aware-mapping.md        |   6 +-
 .../architecture/asap-aware-plan-search.md    |   8 +-
 .../evidence-dependent-candidates.md          |   6 +-
 .../architecture/input-output-workflow.md     | 114 ++-------
 .../architecture/physical-plan-integration.md |  61 +----
 .../architecture/planner-runtime-contract.md  |  47 ++--
 ...d_interface_with_pluggable_optimization.md |  83 +++---
 docs/design_docs/concepts/planner-pipeline.md |   9 +-
 docs/design_docs/concepts/post-asap-ir.md     |  32 +--
 .../physical-planning-and-deployment.md       | 146 +++++------
 .../proposals/asap-aware-mapping/README.md    |   1 -
 .../analytical-resource-cost.md               | 237 ++----------------
 .../maintained-populations.md                 |   5 +-
 .../proposals/asapquery-rule-coverage.md      |   8 +-
 .../asap-aware-mapping-architecture.md        |   4 +-
 docs/develop_docs/library-api.md              | 218 ++--------------
 docs/develop_docs/offline-sketch-evidence.md  |  13 +-
 .../develop_docs/physical-compile-coverage.md |   5 +-
 docs/develop_docs/physical-handoff-costs.md   |   4 +-
 docs/develop_docs/pre-asap-ir.md              |   4 +-
 docs/develop_docs/storage-operation-costs.md  |   3 +-
 .../target-candidate-api-migration.md         |   6 +-
 docs/user_guide_docs/run-a-query.md           |   4 +-
 25 files changed, 250 insertions(+), 811 deletions(-)

diff --git a/docs/README.md b/docs/README.md
index 9f802e094..c9abe1177 100644
--- a/docs/README.md
+++ b/docs/README.md
@@ -19,8 +19,7 @@ Start with [ASAPPlanner input, output, and workflows](design_docs/architecture/i
 for the integration boundary, nested inputs, and choice of planning workflow.
 
 Use [Public library functions and examples](develop_docs/library-api.md) for
-frontend lowering, workload search, ranking, optional selection and lifecycle
-integration.
+frontend lowering, workload search, ranking, selection and DAG assembly.
 
 ## Extend the planner
 
diff --git a/docs/design_docs/architecture/README.md b/docs/design_docs/architecture/README.md
index e5f8ff2e7..d0cc61026 100644
--- a/docs/design_docs/architecture/README.md
+++ b/docs/design_docs/architecture/README.md
@@ -8,7 +8,7 @@ deployment-level decision, and run the selected contract.
 
 For the integration workflow, start with [ASAPPlanner input, output, and
 workflows](input-output-workflow.md). It defines inputs, `CandidateLogicalASAPDAGs`, selection
-and summary-maintenance lifecycle workflows, and future replanning support.
+and assembly workflows, and future replanning support.
 
 ## Planner component flow
 
@@ -23,10 +23,6 @@ flowchart TD
     RANK["Optional cost_sorted: ranked inspection view"]
     SELECT["Optional global_selection + assemble_selected_dag"]
     DAG["Selected logical Post-ASAP DAG"]
-    LINPUT["Optional lifecycle inputs: horizon, rates, capabilities, costs"]
-    LIFE["global_selection_with_summary_maintenance_lifecycles"]
-    LMAT["assemble_selected_dag_with_summary_maintenance_lifecycles"]
-    LPLAN["SummaryMaintenanceLifecyclePlan: DAG root + lifecycle decisions"]
     BACKEND["Downstream: bind physical alternatives, decide deployment, compile and execute"]
     W --> PRE
     F --> PRE
@@ -35,19 +31,15 @@ flowchart TD
     SEARCH --> SPACE
     SPACE --> RANK --> BACKEND
     SPACE --> SELECT --> DAG --> BACKEND
-    SPACE --> LIFE
-    LINPUT --> LIFE --> LMAT --> LPLAN --> BACKEND
 ```
 
 `CandidateLogicalASAPDAGs` is the output of logical candidate search. Each target's candidate set holds
-alternatives and rejection reasons, but no selected maintenance lifecycle.
-Choose among the three branches: inspect candidates (optionally ranked), select
-and assemble logical DAGs, or select and assemble with summary-maintenance
-lifecycle decisions. Use the last branch when Planner owns the maintenance
-decision; otherwise the backend owns it. Its first
-call returns a `GlobalSelection`; the second returns a
-`SummaryMaintenanceLifecyclePlan` with an assembled DAG root and lifecycle
-decisions. No branch by itself deploys or executes a physical plan.
+alternatives and rejection reasons, but no materialization decision.
+Choose between two branches: inspect candidates (optionally ranked), or select
+and assemble logical DAGs. Stage 2 materialization (#509) will decide per
+sub-DAG whether to materialize and whether at ingestion or query time; until
+then every summary runs at query time. No branch by itself deploys or executes
+a physical plan.
 Known-invalid evidence rejects a logical candidate. Missing accuracy evidence
 leaves a constructible candidate visible in `CandidateLogicalASAPDAGs` but uncertified; default
 selection does not commit it without the required guarantee. Cost evidence can
@@ -61,7 +53,7 @@ an unsupported physical alternative into a deployable plan.
 | Shared IR | `asap-types` | The unified operator IR (`ir`: one `OperatorNode` before and after ASAP optimization), schemas, workloads, guarantees, and exported plan data |
 | Front-end common | `frontend-common` | Name-based `UnresolvedOp` tree shared by the front ends, and `resolve_root` into the operator IR |
 | Query frontends | `frontend-sql`, `frontend-promql`, `frontend-metricsql` | Parse source languages and produce canonical Pre-ASAP queries |
-| ASAP-aware mapping | `asap-aware-mapping` | Candidate generation, CSE, legality, accuracy propagation, lifecycle expansion, costing, and ranking |
+| ASAP-aware mapping | `asap-aware-mapping` | Candidate generation, CSE, legality, accuracy propagation, costing, and ranking |
 | Developer inspection | `devtools` | Expose planner DAGs, alternatives, decisions, and explanations for inspection |
 | End-to-end validation | `integration-tests` | Verify behavior across frontends, mapping, and output IR |
 
@@ -77,8 +69,7 @@ The primary output is `CandidateLogicalASAPDAGs`; `cost_sorted` derives an optio
 view with index-aligned costs. Downstream may inspect compatible choices
 across targets rather than assuming the first candidate is a feasible
 physical workload plan. Candidates carry logical summary algorithms,
-parameters, and guarantees; selected maintenance lifecycle decisions appear
-only after a summary-maintenance-lifecycle-aware helper runs. Rejection reasons
+parameters, and guarantees, but no materialization decision. Rejection reasons
 are retained in the candidate space.
 
 ASAPQuery-backend and other downstream applications translate the candidates
@@ -90,10 +81,8 @@ must not silently change Planner-owned semantics.
 
 `CandidateLogicalASAPDAGs::global_selection` optionally coordinates structural choices across
 targets; `GlobalSelection::assemble_selected_dag` constructs a selected semantic DAG.
-Those plain APIs do not establish physical feasibility or a
-maintenance-versus-recompute decision. The lifecycle-aware selection call uses
-additional workload and evidence inputs; its DAG assembly call returns a
-plan with both a root and lifecycle decisions. See the [library guide](../../develop_docs/library-api.md#optional-whole-plan-selection-and-dag-assembly)
+Those APIs do not establish physical feasibility or a
+materialization decision. See the [library guide](../../develop_docs/library-api.md#optional-whole-plan-selection-and-dag-assembly)
 for the distinction. Downstream may consume candidates directly and retains
 responsibility for physical commitment.
 
@@ -104,7 +93,6 @@ responsibility for physical commitment.
 - [Post-ASAP IR](../concepts/post-asap-ir.md)
 - [ASAP-aware mapping](asap-aware-mapping.md)
 - [Accuracy guarantees](../proposals/asap-aware-mapping/end-to-end-accuracy-guarantees.md)
-- [Workload demand and summary lifecycle](../proposals/asap-aware-mapping/workload-demand-and-summary-lifecycle.md)
 - [Physical-plan integration](physical-plan-integration.md)
 - [Analytical resource cost](../proposals/asap-aware-mapping/analytical-resource-cost.md)
 - [Searching over plans](asap-aware-plan-search.md)
diff --git a/docs/design_docs/architecture/asap-aware-mapping.md b/docs/design_docs/architecture/asap-aware-mapping.md
index 78d3e0f9d..c04fa530a 100644
--- a/docs/design_docs/architecture/asap-aware-mapping.md
+++ b/docs/design_docs/architecture/asap-aware-mapping.md
@@ -8,7 +8,7 @@ Given a logical query plan, the mapping layer explores alternative plans that ma
 
 Candidate search takes canonical **Pre-ASAP query roots** and produces
 `CandidateLogicalASAPDAGs`, a compact set of **candidate Post-ASAP DAGs**. Ranking, selection,
-and summary-maintenance lifecycle decisions are subsequent operations over it;
+and DAG assembly are subsequent operations over it;
 see [input, output, and workflows](input-output-workflow.md).
 
 For example, a percentile query might be answered by:
@@ -75,7 +75,6 @@ CandidateLogicalASAPDAGs: compact candidate Post-ASAP DAGs
         |
         +--> inspect / rank
         +--> select and assemble logical DAGs
-        +--> select and assemble with summary-maintenance lifecycle decisions
 ```
 
 ---
@@ -104,9 +103,6 @@ The design is split into focused documents:
 - [ASAPPlanner planner-runtime contract](planner-runtime-contract.md)
   separates planner-owned search and selection from downstream physical
   implementation, deployment, and execution.
-- [Query workloads, data workloads, and summary lifecycle maintenance](../proposals/asap-aware-mapping/workload-demand-and-summary-lifecycle.md) separates
-  query-workload properties from data-workload properties and defines ephemeral, prepared,
-  shared, and continuously maintained summary-state alternatives.
 - [Explainability](../../develop_docs/replacement-explanations.md) describes how the planner reports available replacements
   using the same candidate space it optimizes.
 
diff --git a/docs/design_docs/architecture/asap-aware-plan-search.md b/docs/design_docs/architecture/asap-aware-plan-search.md
index fbc5982bc..e612740b6 100644
--- a/docs/design_docs/architecture/asap-aware-plan-search.md
+++ b/docs/design_docs/architecture/asap-aware-plan-search.md
@@ -84,10 +84,10 @@ sets. This avoids copying every full plan when most structure is shared.
 Cartesian product. `cost_sorted` returns a `RankedTargetSubDAGCandidates` view
 for each target. `global_selection` coordinates supported sharing and
 composition choices; `assemble_selected_dag(root)` assembles one selected DAG
-per query root. This does not prove global physical optimality or select a
-summary-maintenance lifecycle. The
-[workflow design](input-output-workflow.md#workflows) explains when to use the
-ordinary or summary-maintenance-lifecycle-aware path.
+per query root. This does not prove global physical optimality or decide
+which summaries are materialized; Stage 2 materialization (#509) will own that.
+The [workflow design](input-output-workflow.md#workflows) describes the call
+order.
 
 The [code architecture](../../develop_docs/asap-aware-mapping-architecture.md)
 describes current discovery and registry behavior; the
diff --git a/docs/design_docs/architecture/evidence-dependent-candidates.md b/docs/design_docs/architecture/evidence-dependent-candidates.md
index 9dcbba3fd..437cfe4b0 100644
--- a/docs/design_docs/architecture/evidence-dependent-candidates.md
+++ b/docs/design_docs/architecture/evidence-dependent-candidates.md
@@ -58,12 +58,10 @@ not emit a `RejectedCandidate` for that case.
 | HLL confidence | Symbolic failure probability | Reject a fully known unmet root target. |
 | Relative-value composition | Symbolic bound when input sign is unknown | Reject known signed input for this rule. |
 | Exact sum/average/extremum | Symbolic row-count probability term | Reject unsupported metric combinations. |
-| Cost/rate/physical evidence | `None` cost or missing workload rate; candidate remains in `CandidateLogicalASAPDAGs` | Physical/lifecycle evaluation reports unavailable or rejected evidence. |
+| Cost/rate/physical evidence | `None` cost or missing workload rate; candidate remains in `CandidateLogicalASAPDAGs` | Physical evaluation reports unavailable or rejected evidence. |
 | Mixed exact/summary operator | Unknown runtime support; candidate remains in `CandidateLogicalASAPDAGs` | `Some(false)` prevents construction. |
 
-Lifecycle deployment choices are a separate output from `CandidateLogicalASAPDAGs`; their
-capability/cost rejections do not erase the logical summary candidate. The
-backend must still check ordinary summary family, window, and state-operation
+The backend must still check summary family, window, and state-operation
 capabilities before deployment.
 
 - Accuracy/domain: `AccuracyEvidenceProvider` supplies quantile domains and
diff --git a/docs/design_docs/architecture/input-output-workflow.md b/docs/design_docs/architecture/input-output-workflow.md
index 4120811ca..18221035e 100644
--- a/docs/design_docs/architecture/input-output-workflow.md
+++ b/docs/design_docs/architecture/input-output-workflow.md
@@ -18,7 +18,7 @@ Post-ASAP alternatives for the workload.
 | `PlanningWorkload.data_workload` | Data arrival and optional evidence about ingestion, cardinality, and distribution | No implicit default. Set `None` when unavailable for non-PromQL workloads; PromQL requires `Some(DataWorkload)` with a nonzero ingestion interval. |
 | Frontend-specific dependencies (outside `PlanningWorkload`) | `SqlCatalog` for SQL; `now_ms` and, when needed, `HistogramCatalog` for PromQL | `SqlCatalog` is required for SQL lowering; `now_ms` is required for PromQL lowering |
 | Planning models | Candidate cost/ranking and accuracy composition/checking | Used by the relevant APIs; built-in `DefaultCostModel` and `DefaultAccuracyModel` are available |
-| External evidence and capabilities | Domain facts, measured costs, workload statistics, and runtime support | Supply when available and when the chosen optimization or lifecycle decision depends on them; absence is not proof |
+| External evidence and capabilities | Domain facts, measured costs, workload statistics, and runtime support | Supply when available and when the chosen optimization depends on them; absence is not proof |
 
 Frontend lowering and candidate search are stages within this workflow, not
 additional end-to-end inputs. See [Inputs](#inputs) for the nested workload
@@ -30,13 +30,14 @@ fields and [frontend dependencies](#frontend-specific-dependencies).
 |---|---|---|
 | `CandidateLogicalASAPDAGs<Id>` | The legal candidate Post-ASAP DAGs for the workload, represented compactly as canonical roots, one candidate set per target sub-DAG, and cross-target composition information | The ASAPPlanner output |
 
-[Ranking](#ranked-view), [selection and
-DAG assembly](#selection-and-dag-assembly), and
-[summary-maintenance lifecycle](#summary-maintenance-lifecycle-aware-helper) APIs operate on this `CandidateLogicalASAPDAGs`.
+[Ranking](#ranked-view) and [selection and
+DAG assembly](#selection-and-dag-assembly) APIs operate on this `CandidateLogicalASAPDAGs`.
 These are alternative uses of the candidate space, not mandatory sequential
-stages. `CandidateLogicalASAPDAGs` itself has no selected summary-maintenance lifecycle, and
-its candidates do not choose precompute versus query-time placement: a chosen
-lifecycle assignment sets each node's execution timing.
+stages. Its candidates do not choose ingestion-time versus query-time
+placement: a `MaterializationAssignment` sets each node's execution timing.
+Stage 2 materialization (#509) will decide per sub-DAG whether to materialize
+and whether at ingestion or query time; until then every summary runs at query
+time.
 
 The candidate DAGs are logical planning artifacts. ASAPPlanner does **not**
 produce a deployed executable plan; downstream systems bind physical operators,
@@ -58,7 +59,7 @@ PlanningWorkload + frontend dependencies + planning models/evidence
 
 Suppose a dashboard evaluates `count_over_time(up[5m])` once a minute, and
 `up` receives a sample every 15 seconds. This diagram traces the concrete
-inputs and the three possible uses of the same candidate space:
+inputs and the two possible uses of the same candidate space:
 
 ```mermaid
 flowchart TD
@@ -72,10 +73,6 @@ flowchart TD
     I["cost_sorted: inspect choices"]
     G["global_selection + assemble_selected_dag(root)"]
     L["One selected Post-ASAP DAG; the exact pre-ASAP sub-DAG if no optimization is selected"]
-    X["Extra lifecycle inputs: horizon; update rate; capabilities; comparable summary/raw costs"]
-    H["Summary-maintenance-lifecycle-aware selection"]
-    HM["Assemble one selected DAG and decide summary maintenance"]
-    O["SummaryMaintenanceLifecyclePlan: assembled DAG root + maintenance/recompute decision"]
     B["Backend: bind physical operators, deploy, and execute"]
     Q --> F
     D --> F
@@ -83,16 +80,13 @@ flowchart TD
     F --> R --> S --> P
     P --> I
     P --> G --> L --> B
-    P --> H
-    X --> H --> HM --> O --> B
 ```
 
 “Predictable” says the query is known in advance; it is independent of its
 one-minute recurrence. The `CandidateLogicalASAPDAGs` may contain an exact count-summary
-realization, but it is not a deployed query. Without the extra lifecycle
-inputs, the caller can still inspect candidates or obtain a logical DAG; it
-cannot conclude that maintaining a summary is cheaper than recomputing raw
-results.
+realization, but it is not a deployed query. The caller can inspect candidates
+or obtain a logical DAG; deciding whether maintaining a summary is cheaper than
+recomputing raw results belongs to Stage 2 materialization (#509).
 
 For contrast, a one-time SQL query needs a catalog but need not supply data
 arrival evidence merely to inspect logical alternatives:
@@ -110,8 +104,7 @@ flowchart LR
 ```
 
 In this SQL example, `data_workload` can be `None` if the chosen lowering and
-search rules do not consume it. The lifecycle helper is not needed merely to
-inspect the `CandidateLogicalASAPDAGs`.
+search rules do not consume it.
 
 ---
 
@@ -175,9 +168,9 @@ struct BatchEntry {
 |---|---:|---|---|
 | `query` | Yes | Raw query text in `QueryWorkload.language`. | `count(up)` determines the expression to lower and plan. |
 | `requirements` | Yes | Accuracy and response-latency requirements. Defaults mean exact accuracy and unspecified latency. | An explicit ε target permits approximate candidates; the exact default does not. |
-| `predictability` | Yes as a field; `Unknown` is allowed | Whether the query is ad hoc, known in advance, or unknown. `known_at` records when a predictable query became known. | A report known at 10:00 and scheduled for 11:00 may use a `Prepared` summary before execution. `AdHoc` or `Unknown` does not establish that eligibility. |
+| `predictability` | Yes as a field; `Unknown` is allowed | Whether the query is ad hoc, known in advance, or unknown. `known_at` records when a predictable query became known. | A report known at 10:00 and scheduled for 11:00 could have its summary prepared before execution. `AdHoc` or `Unknown` does not establish that eligibility. |
 | `invocations` | Yes, nonzero | Number of executions in this finite batch. | Ten executions can amortize one summary build differently from one execution. |
-| `execute_at` | Optional | Known execution time. | The `Prepared` case above also needs an execution time; without it Planner cannot establish a preparation window. |
+| `execute_at` | Optional | Known execution time. | The prepared case above also needs an execution time; without it no preparation window can be established. |
 | `time_selection` | Yes | Whether the query follows current data or a historical interval, its lookback, and any fixed upper bound. | A moving five-minute window can require deletion/window support that a fixed historical interval does not. |
 
 ##### `repeating_queries: Option<Vec<RepeatingEntry>>`
@@ -197,7 +190,7 @@ struct RepeatingEntry {
 | `query` | Yes | Raw query text in `QueryWorkload.language`. | `rate(up[5m])` determines the expression to lower and plan. |
 | `demand` | Yes | A nonzero fixed interval, fixed interval with evaluation phase, nonempty explicit schedule, or evidence-backed estimated rate. | A query every minute produces more expected reads over a horizon than one every hour. |
 | `requirements` | Yes | Accuracy and response-latency requirements. | An exact dashboard query cannot use an approximate summary solely because it is cheaper. |
-| `predictability` | Yes as a field; `Unknown` is allowed | Records whether future executions are known in advance; independent of recurrence. | Current lifecycle code does not use this field for repeating entries; set `Unknown` if no predictability claim is available. |
+| `predictability` | Yes as a field; `Unknown` is allowed | Records whether future executions are known in advance; independent of recurrence. | Current planner code does not use this field for repeating entries; set `Unknown` if no predictability claim is available. |
 | `time_selection` | Yes | Event-time scope, optional lookback, and optional fixed `as_of` time. | A live five-minute lookback differs from a fixed historical range when checking maintenance capabilities. |
 
 ##### Shared entry fields
@@ -216,7 +209,7 @@ fields expand as follows:
 
 Frontend lowering produces one Pre-ASAP `Rc<OperatorNode>` root for each normalized
 query entry. The caller must retain each root's association with its workload
-entry for later recurrence and lifecycle planning.
+entry for later recurrence and materialization planning.
 
 #### `data_workload: Option<DataWorkload>`
 
@@ -285,8 +278,8 @@ latter cannot be fabricated by one.
 | Accuracy model | Target-aware search takes an `AccuracyModel`; `DefaultAccuracyModel` is available. Default strategies also use it for candidate construction. | Composes candidate guarantees and checks them against requested accuracy. The model does not itself provide missing data-domain facts. |
 | Cost model | Candidate strategies and `cost_sorted`/`global_selection` use a `CostModel`; `DefaultCostModel` is available. | Ranks or selects candidates. The built-in model is not a measured deployment cost for every physical implementation. |
 | Accuracy/domain evidence | `AccuracyEvidenceProvider`; default strategies use `NoAccuracyEvidence` when no provider is supplied. | Input ranges, nonempty populations, Top-K intervals, and similar facts can certify or rule out particular approximations. Missing facts remain unknown. |
-| Measured cost evidence | Supplied through a deployment-specific cost model or physical-evidence provider when cost-based physical/lifecycle comparison is needed. | CPU, memory, and I/O estimates must be comparable before claiming a summary beats raw recomputation. |
-| Runtime/lifecycle capabilities | Passed to lifecycle APIs or checked by deployment-specific providers; `SummaryMaintenanceLifecycleCapabilities::default()` enables all four lifecycle shapes, so it is not proof of actual backend support. | Prevents choosing a maintenance/window operation the intended executor cannot implement. |
+| Measured cost evidence | Supplied through a deployment-specific cost model or physical-evidence provider when cost-based physical comparison is needed. | CPU, memory, and I/O estimates must be comparable before claiming a summary beats raw recomputation. |
+| Runtime capabilities | Checked by deployment-specific providers. | Prevents choosing a maintenance/window operation the intended executor cannot implement. |
 
 For example, the query `quantile_over_time(0.9, data[5m]) /
 quantile_over_time(0.5, data[5m])` does not tell Planner whether the windows
@@ -305,9 +298,6 @@ domain evidence is missing; automatic `global_selection` does not choose it.
 See the [candidate-search reference](../../develop_docs/library-api.md#generate-and-rank-candidates)
 for this backend-selection path.
 
-Additional inputs for a Planner-owned maintenance decision are listed with the
-[summary-maintenance-lifecycle-aware helper](#summary-maintenance-lifecycle-aware-helper).
-
 ---
 
 ## Output
@@ -375,8 +365,7 @@ Then choose the operation matching the caller's responsibility:
 | Purpose | Operation | Result |
 |---|---|---|
 | Inspect candidates or let the backend choose | [Ranked view](#ranked-view), if ranking is useful | Per-target candidate lists and costs |
-| Ask Planner to choose logical computations; backend owns summary maintenance | [Selection and DAG assembly](#selection-and-dag-assembly) | One selected Post-ASAP DAG root per query |
-| Ask Planner to also decide summary maintenance versus raw recomputation | [Summary-maintenance-lifecycle-aware helper](#summary-maintenance-lifecycle-aware-helper) | One plan containing a DAG root and maintenance decisions per query |
+| Ask Planner to choose logical computations | [Selection and DAG assembly](#selection-and-dag-assembly) | One selected Post-ASAP DAG root per query |
 
 ### Ranked view
 
@@ -435,67 +424,8 @@ with some nodes now ASAP operators) and carries no execution timing yet; the
 [API reference](../../develop_docs/library-api.md#api-definition-and-example)
 describes the function signatures and return handling.
 
-This path selects how to compute the query, not how to maintain summary state.
-
-### Summary-maintenance-lifecycle-aware helper
-
-This workflow performs both candidate selection and DAG assembly, incorporating
-summary-maintenance lifecycle costs. Use it when ASAPPlanner owns the decision
-to maintain summaries versus recompute raw data. It is not needed for candidate
-inspection or when the downstream backend owns that decision.
-
-Starting from an existing `CandidateLogicalASAPDAGs`, call these two public helpers in order;
-there is no need to run the ordinary selection/assembly workflow first:
-
-1. `global_selection_with_summary_maintenance_lifecycles` uses the workload
-   binding, lifecycle capabilities, and comparable costs to choose compatible
-   candidates across target sub-DAGs. It returns `GlobalSelection`, not a DAG or a
-   deployment plan.
-2. For each wanted query root, `assemble_selected_dag_with_summary_maintenance_lifecycles`
-   takes that selection and root, constructs a Post-ASAP DAG, compares the
-   selected summary's maintenance cost with raw recomputation, and returns
-   `Result<Option<SummaryMaintenanceLifecyclePlan>, SummaryMaintenanceLifecycleAssemblyError>`.
-   When a summary does not beat a
-   known raw cost, or a required comparable cost is unavailable, the result
-   retains the exact pre-ASAP root (`retain_exact`) and no summary deployments.
-
-As in ordinary selection, one selection call serves the workload and assembly
-is per root. The second helper calls `assemble_selected_dag` internally; callers
-do not need a separate assembly call. Neither helper creates a materialized view
-or deploys runtime state.
-The output is a selected logical DAG with lifecycle decisions, not an executable
-deployment plan. Any claim of optimization is relative to the supplied cost
-model, evidence, and available candidates.
-See the [library guide's lifecycle and capabilities section](../../develop_docs/library-api.md#lifecycle-and-capabilities)
-for an API example and the capability contract.
-
-Across the two calls, the caller supplies these parameters:
-
-| Helper parameter | Source | Required |
-|---|---|---:|
-| `CandidateLogicalASAPDAGs` | Canonical ASAPPlanner output; passed to selection | Yes |
-| `GlobalSelection` and one root | Selection result and a root in that `CandidateLogicalASAPDAGs`; passed to DAG assembly | Yes for each assembled root |
-| Workload binding | `QueryWorkload` plus the workload-entry indices associated with each root | Yes |
-| Planning time (`now_ms`) | Caller clock in Unix milliseconds | Yes |
-| Planning horizon | Caller policy | Conditional: required for finite totals over recurring demand |
-| Data arrival and update rate | `DataWorkload` evidence | Conditional: required to cost continuous maintenance |
-| Lifecycle capabilities | Deployment/runtime provider | Yes for checking deployable lifecycle alternatives |
-| Summary and raw cost information | Cost model and physical-evidence provider | Yes for a cost-based maintenance-versus-recompute decision |
-
-Recurrence and time selection are already fields of the bound `QueryWorkload`;
-they are not duplicated as separate top-level inputs. Similarly, data arrival
-and update rate are read from the optional `DataWorkload`. Missing required
-facts remain unknown rather than being treated as zero.
-
-The per-query output, `SummaryMaintenanceLifecyclePlan`, **contains** the
-Post-ASAP DAG rather than being a parallel representation. It records:
-
-* the assembled Post-ASAP DAG root (`Rc<OperatorNode>`, with execution timing written);
-* lifecycle choices for summary state;
-* planning horizon and expected reads/updates;
-* selected window implementation and guarantees;
-* comparable summary and raw-recomputation costs; and
-* whether raw recomputation was selected.
+This path selects how to compute the query, not whether summary state is
+materialized.
 
 ---
 
diff --git a/docs/design_docs/architecture/physical-plan-integration.md b/docs/design_docs/architecture/physical-plan-integration.md
index 9bd6ddbc5..2fb056412 100644
--- a/docs/design_docs/architecture/physical-plan-integration.md
+++ b/docs/design_docs/architecture/physical-plan-integration.md
@@ -122,26 +122,10 @@ already exists. Until lowering introduces an explicit physical operator,
 statistics contract, validation rule, and resource formula for an operation,
 a candidate containing it is unavailable.
 
-The streaming integration can consume a complete binding through
-`SummaryNodeEvidence`. That binding is keyed to exact `OperatorNode`
-identities and uses structured evidence for aggregate state, join, merge,
-subtract, delete, evaluation, and retained pre-ASAP work. It is a physical
-evidence boundary, not automatic physical lowering: a deployment must still
-select each concrete implementation and provide all edges, resource facts,
-multiplicities, source ownership, and stable physical identities. The planner
-fails closed when any reachable ASAP node lacks that binding.
-
-The raw/query portion of a streaming comparison remains a `PhysicalDAG` using
-the canonical `PhysicalOperator` and `OperatorStatistics` pairing. Summary
-evidence is kept separate only where lifecycle-driven update, retention, and
-expiration multiplicities require facts beyond the query-DAG
-`Once`/`PerEvaluation` schedule. It must not redefine workload, lifecycle, or
-summary-family semantics.
-
-Lifecycle choice affects the physical DAG but does not replace it. Ephemeral,
-prepared, shared, and continuously maintained alternatives determine when
-build, update, evaluation, merge, subtract, or delete nodes execute. The physical
-operators still determine how each execution consumes CPU, memory, and I/O.
+Materialization choice (Stage 2, #509) affects the physical DAG but does not
+replace it: it determines when build, update, evaluation, merge, subtract, or
+delete nodes execute. The physical operators still determine how each execution
+consumes CPU, memory, and I/O.
 
 ## Statistics contract
 
@@ -470,39 +454,8 @@ a numeric entity key is not a score. Exact accumulator inputs are explicitly
 finalized before row operators consume them. None of these operations proves
 candidate completeness; that evidence belongs to the semi-join's pruning step.
 
-The logical DAG carries no execution layout: `apply_lifecycle_timings` writes
-each node's timing from the lifecycle assignment before export. Uniform phase
+The logical DAG carries no execution layout: `apply_materialization_timings`
+writes each node's timing from a `MaterializationAssignment` before export (all
+query time by default). Uniform phase
 assignment applies to the exported post-ASAP DAG;
 it is not a claim that every deployment has implemented every placement.
-
-
-## Summary cost evidence across data-arrival modes
-
-`SummaryMaintenanceCostModel` binds `SummaryNodeEvidence` and
-`SummaryOperatorEvidence` independently of data-arrival mode. `ComparisonScope`
-and the canonical `DataWorkload` determine arrival semantics; individual operator
-resource records do not define another workload model.
-
-`SummaryMaintenanceInputs::from_workload` requires fresh snapshot cardinality.
-For `AtRest`, it derives zero arrivals without requiring ingestion-rate evidence;
-a fresh nonzero or invalid rate contradicts that declaration and is rejected.
-For `ContinuouslyIngesting`, fresh, finite, nonnegative rate evidence remains
-mandatory. Missing continuous rate evidence is never treated as zero.
-Raw and summary evidence supplied directly by a provider obey the same arrival
-invariant. Their source lineage, horizon, evaluation count, and snapshot dimensions
-must still match. The existing lifecycle planner selects direct builds for a fixed
-snapshot and charges bootstrap work, result evaluation, and retention; it charges
-no arrival updates. This does not add computation-placement policy.
-
-`Mixed` and `Unknown` remain unsupported for analytical comparisons: the current
-workload schema cannot identify separate backlog and arrival populations. The
-adapter fails explicitly rather than guessing a split. The estimator version is
-`summary-maintenance-resource-v2`; evidence type names drop the `Streaming` prefix
-(`SummaryMaintenanceInputs`, `SummaryPhysicalInputEvidence`, `SummaryAggregateEvidence`,
-`RetainedSubDAGEvidence`, `RawInputEvidence`, and the summary window/alternative
-types). Update source imports; no legacy-name aliases are provided.
-
-Regressions cover a fixed snapshot with no rate evidence, contradictory arrival
-rates, scope mismatches, missing continuous-rate/cardinality evidence, and actual
-lifecycle selection of a completely costed at-rest summary against its raw scan.
-The existing continuous-ingestion and mixed-arrival rejection tests remain.
diff --git a/docs/design_docs/architecture/planner-runtime-contract.md b/docs/design_docs/architecture/planner-runtime-contract.md
index 5dfe5f760..0077252ca 100644
--- a/docs/design_docs/architecture/planner-runtime-contract.md
+++ b/docs/design_docs/architecture/planner-runtime-contract.md
@@ -4,33 +4,27 @@
 
 ASAPPlanner produces `CandidateLogicalASAPDAGs`, a compact logical candidate space. Integrators
 may select candidates downstream or ask Planner's helpers to select and assemble
-DAGs. Summary-maintenance lifecycle decisions belong to Planner only when the
-integration uses its lifecycle-aware workflow; physical deployment and execution
-remain downstream. The [input/output/workflow design](input-output-workflow.md)
-defines this boundary.
-
-A downstream provider can report implementation alternatives and their cost and
-accuracy evidence for a Planner-owned comparison. The resulting
-`SummaryMaintenanceLifecyclePlan` contains a Post-ASAP DAG root and maintenance
-decisions; it is not an executable plan. Repeated provider calls do not constitute
-an implemented end-to-end replanning or deployment-transition protocol.
+DAGs. Stage 2 materialization (#509) will decide per sub-DAG whether to
+materialize and whether at ingestion or query time; until then every summary
+runs at query time. Physical deployment and execution remain downstream. The
+[input/output/workflow design](input-output-workflow.md) defines this boundary.
 
 ## Three decision layers
 
 | Layer | Owner | Examples |
 |---|---|---|
 | Logical candidate semantics | ASAPPlanner | Query rewrite; summary family and parameters; grouping; accuracy guarantees when established. |
-| Summary maintenance and realization selection | Planner helpers when delegated to Planner; otherwise downstream | `Ephemeral`, `Prepared`, `Shared`, `ContinuouslyMaintained`; `DirectBuild` or `Incremental`; window implementations compared using provider evidence. |
+| Summary materialization and realization selection | Stage 2 materialization (#509); downstream until then | Ingestion-time maintenance or query-time computation per summary state; direct build or incremental update; window implementations compared using provider evidence. |
 | Concrete implementation and deployment | ASAPQuery-backend and its workload optimizer | Library and data-structure implementation, exact pane layout, placement, sharding, storage, transmission, materialization IDs, executor configuration, and workload-wide assignment. |
 
 ASAPCollector and the ASAPQuery data plane execute the compiled downstream
 plans. They validate capabilities and plan identities, maintain or read the
 specified state, and report runtime observations. They do not silently choose
-a different summary, lifecycle, or realization framework.
+a different summary, materialization, or realization framework.
 
 ## Incremental-maintenance example
 
-When the integration delegates summary-maintenance decisions to Planner,
+Once Stage 2 materialization (#509) owns summary-maintenance decisions,
 ASAPPlanner may decide that a logical summary should be incrementally
 maintained: new data updates existing summary state. It may also select the
 planner-visible window realization—such as tumbling, sliding/panes, or an
@@ -43,7 +37,7 @@ pane representation, runtime operator implementation, placement, sharding,
 watermark behavior, and materialization identifiers. ASAPCollector maintains
 the compiled panes and summary state.
 
-Thus `Incremental` describes the state-update lifecycle, while tumbling,
+Thus incremental update describes how state is maintained, while tumbling,
 sliding, and exponential-histogram describe realization algorithms. They are
 distinct axes, but both can participate in ASAPPlanner's candidate space. The
 backend still owns how the selected algorithms are physically realized.
@@ -64,11 +58,10 @@ selected algorithm's semantics or guarantees.
 ## Iterative planning protocol (future integration)
 
 The sequence below is an intended integration design, not one shipped public
-API or a required path for every caller. Current provider and lifecycle helpers
-support a bounded planning decision; cross-run identity, migration, activation,
-and rollback are not an end-to-end Planner protocol.
+API or a required path for every caller. Cross-run identity, migration,
+activation, and rollback are not an end-to-end Planner protocol.
 
-1. ASAPPlanner enumerates semantically valid logical summaries, lifecycle
+1. ASAPPlanner enumerates semantically valid logical summaries, materialization
    alternatives, and registered realization strategies.
 2. A physical-plan provider maps those candidates to executor-feasible complete
    alternatives. Unsupported candidates are omitted or explicitly rejected.
@@ -76,12 +69,12 @@ and rollback are not an end-to-end Planner protocol.
    scan selection, input/output edges, operation counts, update and bootstrap
    fanout, retained state, CPU, memory, I/O, and accuracy facts.
 4. ASAPPlanner keeps constructible candidates with missing evidence visible
-   in `CandidateLogicalASAPDAGs` but does not certify unknown accuracy. The
-   summary-maintenance-lifecycle-aware workflow compares supported alternatives
-   over the same workload horizon. Missing or incomparable costs do not establish
+   in `CandidateLogicalASAPDAGs` but does not certify unknown accuracy.
+   Materialization compares supported alternatives over the same workload
+   horizon. Missing or incomparable costs do not establish
    that maintaining a summary beats raw recomputation; structural scores and
    optimistic zeroes are not substitutes.
-5. ASAPPlanner outputs the selected Post-ASAP semantics, lifecycle guarantees,
+5. ASAPPlanner outputs the selected Post-ASAP semantics, materialization choices,
    realization contract, and chosen provider identity.
 6. ASAPQuery-backend compiles that result into consistent `CollectorPlan`,
    `BackendPlan`, and `QueryPlan` projections and performs deployment-level and
@@ -106,11 +99,8 @@ such as cache behavior, serialization overhead, compression, spill I/O, or
 data-distribution-dependent sketch error. Provenance and version information
 must accompany those facts so stale observations fail closed.
 
-`SummaryPhysicalPlanAlternative` is the current integration point for a
-complete provider-enumerated implementation. Its identity is returned with the
-winning lifecycle combination. More structured planner-owned realization
-contracts can refine the candidate space without moving executor
-implementation into ASAPPlanner.
+More structured planner-owned realization contracts can refine the candidate
+space without moving executor implementation into ASAPPlanner.
 
 ## Workload-wide optimization
 
@@ -146,7 +136,7 @@ in one cost formula.
   automatically selected.
 - Shared logical nodes remain shared across the planner-runtime contract; physical sharing
   additionally requires compatible filters, grouping, windows, parameters,
-  lifecycle, and guarantees.
+  materialization, and guarantees.
 - Collector, backend, and query plans are projections of one compiled decision
   and cannot be optimized independently into inconsistent semantics.
 
@@ -155,7 +145,6 @@ in one cost formula.
 - [Post-ASAP IR](../concepts/post-asap-ir.md)
 - [Physical plan integration](physical-plan-integration.md)
 - [Analytical resource cost](../proposals/asap-aware-mapping/analytical-resource-cost.md)
-- [Workload demand and summary lifecycle](../proposals/asap-aware-mapping/workload-demand-and-summary-lifecycle.md)
 - [ASAPCollector physical compilation](https://github.com/ProjectASAP/ASAPCollector/blob/87684f4b61514382d8b087724694f93187bfc19c/docs/design_docs/control-plane/post-asap-physical-compilation.md)
 - [ASAPQuery configuration formulation](https://github.com/ProjectASAP/ASAPQuery/blob/main/.design_docs/sketch-config-optimization-formulation.md)
 - [ASAPQuery optimizer MIP formulation](https://github.com/ProjectASAP/ASAPQuery/blob/main/.design_docs/optimizer-mip-formulation.md)
diff --git a/docs/design_docs/architecture/updated_interface_with_pluggable_optimization.md b/docs/design_docs/architecture/updated_interface_with_pluggable_optimization.md
index 4820b6226..682055b0a 100644
--- a/docs/design_docs/architecture/updated_interface_with_pluggable_optimization.md
+++ b/docs/design_docs/architecture/updated_interface_with_pluggable_optimization.md
@@ -9,8 +9,8 @@ What that buys:
 
 * One call in place of six across three stages. `CandidateLogicalASAPDAGs` and
   `GlobalSelection` no longer appear in user code.
-* The root-to-entry bindings a caller used to build by hand are derived, and
-  their ordering contract is checked rather than assumed.
+* The root-to-entry binding a caller used to build by hand is derived, and
+  its ordering contract is checked rather than assumed.
 * A new optimization algorithm can be freely implemented as a trait implementation, rather than a
   rule disguised to fit a two-phase pipeline it does not share.
 
@@ -20,7 +20,6 @@ Unchanged: `CandidateLogicalASAPDAGs`, `cost_sorted`, `global_selection`, and th
 ```text
 PlanningWorkload ──lowering──▶ ParsedWorkload ──OptimizationPass──▶ PlanOutput
     + frontend deps                            + models
-                                               + lifecycle input
 ```
 
 ---
@@ -64,7 +63,6 @@ Details of these types are provided below.
 | `workload` | `&PlanningWorkload` |
 | `frontend_specific` | `Sql { catalog }` / `Promql { now_ms, histograms }` / `Metricsql`; fixed by `query_workload.language` |
 | `models` | Cost model, accuracy model, evidence provider; `PlanningModels::builtin()` for the defaults |
-| `lifecycle` | Planning clock and runtime capabilities for the maintenance-versus-recompute decision every plan carries |
 | `pass` | `None` uses `MajorPass` |
 
 ### `OptimizationInput`
@@ -73,7 +71,6 @@ Details of these types are provided below.
 pub struct OptimizationInput<'a> {
     pub workload: &'a ParsedWorkload,
     pub models: PlanningModels<'a>,          // same type UserInput uses
-    pub lifecycle: LifecycleInput,           // same type UserInput uses
 }
 ```
 
@@ -83,19 +80,18 @@ pub struct OptimizationInput<'a> {
 
 ```rust
 pub struct PlanOutput {
-    pub plans: Vec<QueryLifecyclePlan>,   // one per workload entry, in entries() order
+    pub plans: Vec<QueryPlan>,   // one per workload entry, in entries() order
 }
 
-pub struct QueryLifecyclePlan {
-    pub entry_index: usize,        // index into QueryWorkload::entries()
-    pub plan: SummaryMaintenanceLifecyclePlan,   // its `root` is the DAG
+pub struct QueryPlan {
+    pub entry_index: usize,      // index into QueryWorkload::entries()
+    pub root: Rc<OperatorNode>,  // selected post-ASAP DAG; shared nodes are the same Rc
 }
 ```
 
-Every plan carries the maintenance decisions, so the pass always runs
-lifecycle-aware selection. A cost model that cannot price lifecycles
-(`DefaultCostModel` today) makes that selection fall back to raw recompute for
-every summary target; supply a model with the lifecycle cost hooks.
+Plans carry no materialization decision. `PlanOutput::execution_timed_dag()`
+times every summary at query time until Stage 2 materialization (#509) decides
+per sub-DAG whether to materialize and whether at ingestion or query time.
 
 ---
 
@@ -112,8 +108,9 @@ The `MajorPass` described below will be used by default, which corresponds to th
 |---|---|
 | Build roots | `Id` is the entry's position in `entries()`; the accuracy target comes from its `requirements` |
 | Candidate search | `search_workload_with_targets` with `default_strategies_with_evidence` |
-| Select | `global_selection`, or `global_selection_with_summary_maintenance_lifecycles` with a `WorkloadDemand` derived from the `ParsedWorkload` |
-| Assemble, per root | `assemble_selected_dag`, or its lifecycle-aware counterpart |
+| Select | `CandidateLogicalASAPDAGs::global_selection` |
+| Assemble, per root | `GlobalSelection::assemble_selected_dag` |
+| Share | `asap_types::ir::cse::share_common_sub_dags` across the assembled roots |
 
 Moving it behind the trait changes one thing for existing developers:
 **`ReplacementStrategy` is now a concept of `MajorPass`, not of the optimization
@@ -159,70 +156,60 @@ for name in registry.names() {
 
 `PassRegistry` is caller-owned, not a link-time global, so two tests in one binary cannot see each other's registrations.
 
-### 3.3 The three existing workflows, in this shape
+### 3.3 The existing workflows, in this shape
 
-[Input, output, and workflows](input-output-workflow.md) describes three ways to
-use the candidate space. Only the last is what a pass produces; the other two
-stay on the old interfaces.
+[Input, output, and workflows](input-output-workflow.md) describes two ways to
+use the candidate space. The second is what a pass produces; the first stays
+on the old interfaces.
 
 | Workflow there | Here |
 |---|---|
 | Ranked view (`cost_sorted`) | Not covered by this design, you should handle it with old interfaces |
-| Selection and DAG assembly | Not covered either: `search_workload_with_targets` + `global_selection` + `assemble_selected_dag` |
-| Summary-maintenance-lifecycle-aware helper | `PlanOutput` |
+| Selection and DAG assembly | `PlanOutput` |
 
-The third is no longer a call sequence the caller drives.
+Selection and assembly are no longer a call sequence the caller drives.
 Following is an example of how the old workflow maps to the new interface.
 
 ```rust
-// Before — from a PlanningWorkload and a catalog, with lifecycle decisions.
+// Before — from a PlanningWorkload and a catalog.
 
 // 1. Lower every normalized entry, and record which entry each root came from.
 //    Not lower_sql_batch: it walks query_batch alone and drops repeating entries.
 let mut roots = Vec::new();
-let mut entry_indices = Vec::new();
 for (index, entry) in workload.query_workload.entries().enumerate() {
     let accuracy = entry.requirements.accuracy.target();
     let expr = lower_sql_dialect(&entry.query.0, &catalog, dialect.clone(), accuracy.clone())
         .await?;
     roots.push((index, expr, Some(accuracy)));
-    entry_indices.push(index);
 }
 
 // 2. Search for candidates.
 let strategies = default_strategies_with_evidence(&cost_model, &evidence);
 let space = search_workload_with_targets(roots, &strategies, &accuracy_model);
 
-// 3. Select once for the whole workload, re-binding roots to workload entries.
-let demand = WorkloadDemand {
-    workload: &workload.query_workload,
-    data_workload: workload.data_workload.as_ref(),
-    entry_indices: &entry_indices,
-};
-let selection = global_selection_with_summary_maintenance_lifecycles(
-    &space, demand, now_ms, horizon, capabilities, &cost_model)?;
-
-// 4. Assemble once per root.
-let mut plans = Vec::new();
+// 3. Select once for the whole workload.
+let selection = space.global_selection(&cost_model);
+
+// 4. Assemble once per root, then share common sub-DAGs across roots.
+let mut assembled = Vec::new();
 for (index, root) in &space.roots {
-    let plan = assemble_selected_dag_with_summary_maintenance_lifecycles(
-        &selection, root, demand, now_ms, horizon, capabilities, &cost_model)?;
-    plans.push((*index, plan));
+    if let Some(dag) = selection.assemble_selected_dag(root)? {
+        assembled.push((*index, dag));
+    }
 }
+let plans = share_common_sub_dags(assembled);
 ```
 
 ```rust
 // After.
 let output = e2e_plan(
     UserInput::new(&workload, FrontendInput::Sql { catalog: &catalog },
-                   PlanningModels::builtin(),
-                   LifecycleInput::new(now_ms, capabilities).with_horizon(horizon))
+                   PlanningModels::builtin())
 ).await?;
 ```
 
-Steps 1 and 3 are where the two bindings lived: the `Id` carried through the
-roots tuple, and the `&[usize]` rebuilt for `WorkloadDemand`. Both had to agree
-with `entries()` order, and nothing checked that they did. `MajorPass` still
+Step 1 is where the binding lived: the `Id` carried through the roots tuple had
+to agree with `entries()` order, and nothing checked that it did. `MajorPass` still
 runs all four steps; another pass need not run any of them.
 
 ## 4. Code layout
@@ -230,7 +217,7 @@ runs all four steps; another pass need not run any of them.
 | Crate | What it holds |
 |---|---|
 | `asap-types` | `ParsedWorkload` |
-| `asap-aware-mapping` | `OptimizationPass`, `OptimizationInput`, `PlanOutput`, `PlanningModels`, `LifecycleInput`, `optimize`, `PassRegistry`, `MajorPass` |
+| `asap-aware-mapping` | `OptimizationPass`, `OptimizationInput`, `PlanOutput`, `PlanningModels`, `optimize`, `PassRegistry`, `MajorPass` |
 | `asap-planner` *(new)* | `e2e_plan`, `UserInput`, `FrontendInput`, lowering dispatch |
 
 ```text
@@ -242,9 +229,9 @@ asap-planner ──┬──> asap-frontend-{sql, promql, metricsql}
 
 `asap-planner` is separate because it is the only crate depending on every
 frontend; before it, the sole facade re-exporting more than one was
-`asap-devtools`, a developer-tools crate. `PlanningModels` and `LifecycleInput`
-live in `asap-aware-mapping` because both inputs use them, and `asap-planner`
-re-exports them.
+`asap-devtools`, a developer-tools crate. `PlanningModels` lives in
+`asap-aware-mapping` because both inputs use it, and `asap-planner` re-exports
+it.
 
 ---
 
diff --git a/docs/design_docs/concepts/planner-pipeline.md b/docs/design_docs/concepts/planner-pipeline.md
index 7401ae0da..c07d17775 100644
--- a/docs/design_docs/concepts/planner-pipeline.md
+++ b/docs/design_docs/concepts/planner-pipeline.md
@@ -14,12 +14,11 @@ over that output, not mandatory stages of candidate search.
             |
             +--> inspect candidates, optionally using cost_sorted
             +--> select and assemble logical DAGs
-            +--> select and assemble with summary-maintenance lifecycle decisions
 
-The last two branches are alternatives: use the summary-maintenance-lifecycle-aware
-workflow when Planner owns maintenance-versus-recomputation decisions; otherwise
-the backend owns them. All physical binding, deployment, and execution remain
-downstream responsibilities.
+Stage 2 materialization (#509) will decide per sub-DAG whether to materialize
+and whether at ingestion or query time; until then every summary runs at query
+time. All physical binding, deployment, and execution remain downstream
+responsibilities.
 
 The [input, output, and workflows](../architecture/input-output-workflow.md)
 document defines the public boundary and helper call order.
diff --git a/docs/design_docs/concepts/post-asap-ir.md b/docs/design_docs/concepts/post-asap-ir.md
index 8d2e3c5bb..207ad227e 100644
--- a/docs/design_docs/concepts/post-asap-ir.md
+++ b/docs/design_docs/concepts/post-asap-ir.md
@@ -59,11 +59,9 @@ reject them with `UNIMPLEMENTED_ASAP_OP`):
 
 The earlier draft listed `SummaryCreate` and `SummaryInsert`. These are not
 separate variants. `SummaryAgg` describes the state-producing
-computation and its update input. The
-[summary-maintenance lifecycle](../proposals/asap-aware-mapping/workload-demand-and-summary-lifecycle.md)
-separately describes when state is created, retained, shared, updated and retired.
-Physical binding and runtime execution implement the actual build and update
-operations. Not every summary family supports incremental maintenance.
+computation and its update input. Stage 2 materialization (#509) will decide
+whether and when that state is maintained. Physical binding and runtime
+execution implement the actual build and update operations. Not every summary family supports incremental maintenance.
 
 ## Exact work and composition
 
@@ -76,8 +74,8 @@ Exact work is represented by the ordinary operators, unchanged:
   assessed yet (`is_logical_rewrite`).
 - `BinaryOp` combines independently planned operands. Summary planning may set
   its typed division guards (`checked_finite_division`,
-  `checked_relative_division`); the operator's timing comes from the lifecycle
-  assignment, not from the operator.
+  `checked_relative_division`); the operator's timing comes from the
+  materialization assignment, not from the operator.
 - Aggregate, projection, filter, sort and limit over a evaluation are the ordinary
   `Aggregate`, `Project`, `Filter`, `Sort` and `Limit` operators reading an ASAP
   node. Exact-accumulator state may pass through the projection-like
@@ -105,11 +103,12 @@ not definitions of the operator.
 
 The logical DAG carries no timing: `OperatorNode::timing` is `None` on every
 front-end node and every candidate, and `map_children` clears it. Summary
-materialization chooses a lifecycle per summary state and records it in a
-[`LifecycleAssignment`](../../../crates/types/src/ir/timing.rs) (ingestion-time
-maintenance or query-time recomputation per `SummaryAgg`; a state absent from
-the assignment defaults to ingestion-time maintenance).
-`apply_lifecycle_timings(root, &assignment, &mut TimingMemo)` then writes a
+materialization chooses a timing per summary state and records it in a
+[`MaterializationAssignment`](../../../crates/types/src/ir/timing.rs) (ingestion-time
+maintenance or query-time computation per `SummaryAgg`). The default is
+`all_query_time()`; until Stage 2 materialization (#509) decides otherwise, the
+planner times every `SummaryAgg` at query time.
+`apply_materialization_timings(root, &assignment, &mut TimingMemo)` then writes a
 timing into every node, top-down:
 
 - a node of fixed kind takes its kind's timing — `SummaryEstimate` and
@@ -125,8 +124,9 @@ The pass then validates every edge (rows or exact-accumulator state into a
 a `EvaluatePopulation`, no ingestion work reading a query-time value) and rejects a
 node reached from two consumers that need different timings;
 `split_shared_by_phase` copies such a sub-DAG for one side before the
-assignment is applied. `validate_default` and `planned_data_state` answer the
-same questions for a candidate at planning time without keeping anything.
+assignment is applied. `validate_maintained` and `planned_data_state` answer the
+same questions for a candidate at planning time, assuming every summary is
+maintained at ingestion time, without keeping anything.
 
 ## Exported DAG
 
@@ -154,7 +154,7 @@ included — with children as edges and no embedded sub-DAGs:
   producer's data state and grouping/window compatibility.
 - Each node records `output_state` (timing plus `Raw` or `SummaryState`),
   `output_schema` and `guarantee`. Export reads the timing written by
-  `apply_lifecycle_timings` and rejects an untimed node
+  `apply_materialization_timings` and rejects an untimed node
   (`ExecutionDataStateError::UntimedNode`); it does not re-run data-state
   validation.
 
@@ -193,7 +193,7 @@ membership guarantee's child provenance. An exact request does not accept this
 approximate output path merely because its selected identities are certified.
 
 Deployment chooses ingestion time or query time for these operators. The
-lifecycle assignment writes the placement; `with_execution_phases` can
+materialization assignment writes the placement; `with_execution_phases` can
 reassign it on the exported DAG. Either deployment must give each evaluation a complete
 rate window and an isolated summary state, or maintain an equivalent replacement
 strategy. Appending successive rate snapshots to one cumulative state is invalid.
diff --git a/docs/design_docs/physical-planning-and-deployment.md b/docs/design_docs/physical-planning-and-deployment.md
index 274e4974c..6f6d7f207 100644
--- a/docs/design_docs/physical-planning-and-deployment.md
+++ b/docs/design_docs/physical-planning-and-deployment.md
@@ -7,11 +7,11 @@ A Post-ASAP computation is progressively realized through four layers:
 ```mermaid
 flowchart LR
     L["Logical Post-ASAP DAG<br/><b>What computation?</b>"]
-    M["Summary Maintenance Lifecycle<br/><b>How is state maintained?</b>"]
+    M["Materialization<br/><b>How is state maintained?</b>"]
     P["Physical DAG(s)<br/><b>How is it executed?</b>"]
     D["Deployment Plan / DAG<br/><b>How is it instantiated?</b>"]
 
-    L -->|"Summary Maintenance<br/>Candidate Generation"| M
+    L -->|"Stage 2<br/>Materialization (#509)"| M
     M -->|"Physical Plan<br/>Compiler"| P
     P -->|"Deployment Plan<br/>Compiler"| D
 ```
@@ -19,47 +19,44 @@ flowchart LR
 | Layer | Defines |
 | --- | --- |
 | **Logical Post-ASAP DAG** | Computation semantics |
-| **Summary Maintenance Lifecycle** | Build, retention, reuse, and window strategy |
+| **Materialization** | Build, retention, reuse, and window strategy |
 | **Physical DAG(s)** | Supported physical candidates, executable operators and typed input boundaries |
 | **Deployment Plan / DAG** | Selected candidate, concrete data/state bindings and operational lifecycle |
 
 ASAPPlanner owns the first three layers and the shared physical operator
 implementation library. Deployment systems such as ASAPQuery and asap-fusion
-own deployment compilation and operation. The lifecycle is a planning contract
+own deployment compilation and operation. Materialization is a planning contract
 associated with the logical DAG, not a separate computation IR.
 
-The Logical Post-ASAP DAG is preceded by the Pre-ASAP DAG (`QueryExpr`), the
+> **Status:** Stage 2 materialization (#509) will decide per sub-DAG whether to
+> materialize and whether at ingestion or query time. It is not implemented yet;
+> until then the planner times every summary at query time. Sections 2 and 3
+> describe the intended contract.
+
+The Logical Post-ASAP DAG is preceded by the Pre-ASAP DAG, the
 language-independent query semantics before summary selection. Both are
-logical. Planning builds Post-ASAP `SummaryNode` DAGs; `compile_post_asap_dag`
+logical `OperatorNode` DAGs; `compile_post_asap_dag`
 exports the selected DAG as a `PostAsapDAG`, which is the Physical Plan
 Compiler's input. Its per-node execution phase (ingestion or query time) is
-decided by the selected summary maintenance lifecycle, as the layer contract
-below states.
+decided by a `MaterializationAssignment`, as the layer contract below states.
 
 ### Layer contract
 
 1. **Logical Post-ASAP** (`CandidateLogicalASAPDAGs`) decides what to compute: summary
    families, readouts and sharing. It does not decide placement; timing that a
    realization strategy writes while building a candidate is provisional.
-2. **Summary maintenance lifecycle** (Planner) lists the lifecycle choices for
-   each unique retained state: every summary state (`SummaryAgg`) and every
-   maintained population that does not feed a summary state.
-   A chosen assignment determines every node's
-   `ExecutionTiming`, plus window framework and retention.
-   `SummaryMaintenanceLifecyclePlan::execution_timed_dag` applies it: a retained
-   (non-`Ephemeral`) state and all of its inputs run at ingestion time;
-   readouts, other consumers, and `Ephemeral` states not consumed by retained
-   state run at query time. A population that feeds a summary state is one of
-   that state's inputs and follows its timing.
+2. **Materialization** (Stage 2, #509) chooses ingestion or query time for each
+   summary state (`SummaryAgg`) and records it in a `MaterializationAssignment`.
+   `apply_materialization_timings` writes every node's `ExecutionTiming`: an
+   ingestion-time state and all of its inputs run at ingestion time; readouts,
+   other consumers, and query-time states run at query time.
+   `MaintainPopulation` always runs at ingestion time. The default assignment
+   is all query time, which `PlanOutput::execution_timed_dag` applies.
 3. **Physical compile** (Planner) reads timing: ingestion-time nodes form the
    precompute DAG and the rest form the query DAG, joined by typed outputs. It
    does not see raw ingestion, panes, storage or stored-state readout.
-4. **Backend** chooses the lifecycle assignment with its own `CostModel`:
-   precompute CPU (`maintenance_cost_per_update`), sketch/summary store cost
-   (`retention_cost_rate`), query reads (`summary_read_cost`) and per-query
-   builds (`build_cost`, for `Ephemeral`), counting shared state once.
-   `Ephemeral` requires the deployment to supply the state's raw input as a
-   query-time source.
+4. **Backend** binds and executes the timed DAG. A query-time summary requires
+   the deployment to supply the state's raw input as a query-time source.
 
 ### Candidate generation and deployment selection
 
@@ -69,7 +66,7 @@ because a deployment-independent cost estimate prefers another candidate.
 Logical candidates are an internal search stage, not the deployment handoff.
 
 ```text
-Query semantics + accuracy and lifecycle requirements
+Query semantics + accuracy and freshness requirements
                     ↓ Planner
 Supported Physical DAG candidates + typed inputs/outputs + requirements
                     ↓ backend
@@ -93,9 +90,9 @@ and a feasible candidate that loses on cost. Absence is not a cost comparison.
 
 For `sum by(job)(rate(m[1m]))`, Rate remains per series before grouped Sum.
 `CandidateLogicalASAPDAGs` offers one such candidate, with a per-series Rate state and a grouped
-Sum state. Its lifecycle assignment places it: a retained Sum state finalizes
-Rate and builds Sum within a bounded precompute run; an `Ephemeral` Sum over a
-retained Rate state leaves the Rate readout and Sum in the query DAG. Storing a
+Sum state. Its materialization assignment places it: an ingestion-time Sum state
+finalizes Rate and builds Sum within a bounded precompute run; a query-time Sum
+over an ingestion-time Rate state leaves the Rate readout and Sum in the query DAG. Storing a
 value requires its exact evaluation window, revision, readiness and serving
 cadence to match the query contract.
 
@@ -109,7 +106,7 @@ Planner's candidate space decides what to compute, not placement. For an
 instant-vector PromQL TopK, Planner resolves rows that carry the complete series
 identity and lists the current-series heap realizations per root with the other
 candidates, unranked. Precompute or query-time placement of Rate and grouped Sum
-is not a separate Planner candidate: the summary maintenance lifecycle assigns
+is not a separate Planner candidate: the materialization assignment sets
 each node's timing, and the physical compiler reads it.
 
 This is the target ownership contract. A backend path that still reconstructs
@@ -182,10 +179,10 @@ KLLMerge
   p50     p99
 
           │
-          │ Summary Maintenance Candidate Generation
+          │ Stage 2 Materialization (#509)
           ▼
 
-2. Summary Maintenance Lifecycle
+2. Materialization
 
 KLLBuild(k=200)
   strategy = continuously maintain
@@ -239,7 +236,7 @@ Each stage adds a different class of decision while preserving the preceding
 contracts. Here, continuous maintenance means recurring production of pane state;
 the bounded build DAG does not itself implement an unbounded streaming window.
 
-## 2. Logical Post-ASAP DAG → Summary Maintenance Lifecycle
+## 2. Logical Post-ASAP DAG → Materialization
 
 The **Logical Post-ASAP DAG** defines computation semantics:
 
@@ -257,33 +254,13 @@ Quantile(.5)  Quantile(.99)
 It establishes that KLL with `k=200` is used and that the merge is shared by the
 two readouts. It does not determine when KLL states are built or retained.
 
-**Summary Maintenance Candidate Generation** enumerates legal lifecycle choices
-using workload demand, window/freshness requirements and supported physical
-implementations. Backend selection uses runtime feasibility and cost after
-physical compilation. The following example follows one candidate.
-
-Candidate generation and selection are separate steps. For every unique retained
-state, enumeration reports each lifecycle (ephemeral, prepared, shared,
-continuously maintained) as legal, with a Planner cost or explicitly unknown
-cost, or as rejected with a reason. Planner does not remove a legal alternative
-because its own estimate prefers another. A deployment prices the legal
-alternatives over the whole workload, counting shared state once, and binds one
-lifecycle per state. Binding checks that the choice is legal and that states on
-one maintenance path share an evaluation schedule. An alternative whose cost is
-unknown can be bound only when the deployment's cost model is authoritative for
-complete-candidate cost; unknown cost is never treated as zero. It then yields the same
-lifecycle guarantee and window framework the physical compiler consumes when
-Planner selects. Planner's own cheapest-alternative selection remains available
-for callers without deployment pricing. The window framework is decided for the
-complete combination, not for one alternative in isolation.
-
-A maintained population (for example, the current series of `topk by(job)(1, m)`)
-is retained state like a summary. Retaining it maintains the latest sample per
-series at ingestion and leaves only the readout at query time. Choosing
-`Ephemeral` rebuilds that snapshot from raw samples for each query, so the
-deployment must supply the raw source at query time. The caller's `CostModel`
-prices both through the same lifecycle hooks; a model without population
-evidence leaves them unknown, and they are not selected.
+**Stage 2 Materialization (#509)** will choose when states are built and how
+long they are retained, using workload demand, window/freshness requirements
+and supported physical implementations. Backend selection uses runtime
+feasibility and cost after physical compilation. Retained state includes
+maintained populations (for example, the current series of
+`topk by(job)(1, m)`), which keep the latest sample per series at ingestion and
+leave only the readout at query time.
 
 For the running example, assume it selects:
 
@@ -303,24 +280,24 @@ reuse:
     one merged state serves p50 and p99
 ```
 
-This produces the **Summary Maintenance Lifecycle**.
+This is the running example's **Materialization**.
 
-The lifecycle specifies how the selected logical summary should be maintained,
+It specifies how the selected logical summary should be maintained,
 but not its concrete operator implementation or storage location.
 
 Physical feasibility may feed back into selection. For example, if the required
-pane-based maintenance cannot be implemented, this lifecycle candidate cannot be
+pane-based maintenance cannot be implemented, this materialization cannot be
 selected. One-minute panes alone also cannot cover an arbitrarily phased query
 window; that requires supported boundary handling or a different candidate.
 
-## 3. Summary Maintenance Lifecycle → Physical DAG
+## 3. Materialization → Physical DAG
 
 The **Physical Plan Compiler** consumes both computation semantics and maintenance
 requirements:
 
 ```text
 Logical Post-ASAP DAG (PostAsapDAG)
-+ Summary Maintenance Lifecycle
++ Materialization
 + physical capabilities
         ↓
 Physical Plan Compiler
@@ -328,14 +305,13 @@ Physical Plan Compiler
 Physical DAG(s)
 ```
 
-For the running example, the lifecycle creates two execution boundaries.
+For the running example, materialization creates two execution boundaries.
 
 These two halves are named as `PhysicalASAPDAG` names them, `precompute`
-and `query`. *Maintenance* stays the lifecycle's word (section 2): it covers
+and `query`. *Maintenance* stays materialization's word (section 2): it covers
 how state is built, retained, reused and scheduled. A precompute DAG is the
-physical object that a maintenance lifecycle compiles to, so reusing
-*maintenance* for it collapses two layers that the crates keep apart:
-`asap-aware-mapping::summary_maintenance_*` owns the lifecycle, and
+physical object that maintenance compiles to, so reusing *maintenance* for it
+collapses two layers: Stage 2 materialization (#509) owns maintenance, and
 `asap-physical-operators::physical_planner` owns the DAGs.
 
 ### Precompute Physical DAG
@@ -397,17 +373,17 @@ DAG. If the required behavior cannot be realized, physical compilation fails.
 Materialization frontiers are Planner decisions. A candidate records both the
 precompute Physical DAG and the query Physical DAG, with typed outputs connecting
 them. The deployment compiler binds those outputs; it does not move operators.
-Lifecycle timing gives the frontier: ingestion-time nodes read by query-time
-nodes. For `sum by(job)(rate(m[1m]))`, the two lifecycle choices of the single
+Execution timing gives the frontier: ingestion-time nodes read by query-time
+nodes. For `sum by(job)(rate(m[1m]))`, two materialization choices for the single
 logical candidate give:
 
 ```text
-Candidate A (Rate state retained, Sum Ephemeral):
+Candidate A (Rate state at ingestion time, Sum at query time):
   precompute: counter samples → per-series Rate state
   materialized output: per-series Rate states for window/evaluation/revision
   query: stored Rate states → Rate readout → grouped Sum → result
 
-Candidate B (Rate and Sum states retained):
+Candidate B (Rate and Sum states at ingestion time):
   precompute: counter samples → per-series Rate → grouped Sum state
   materialized output: grouped Sum states for window/evaluation/revision
   query: stored grouped Sum states → Sum readout → result
@@ -430,9 +406,9 @@ feasibility is rejected before pricing. The optimizer supplies candidate
 frontiers and cost evidence, including updates, retention, recurrence and sharing.
 `enumerate_frontiers` constructs bounded, reachable antichain frontiers above explicit input boundaries, including query-only and fully precomputed results. It fails explicitly when the candidate budget is exceeded. Maintenance selection must still reject frontiers that violate window, freshness, or reuse requirements; deployment feasibility is checked before pricing.
 
-The lifecycle layer decides timing; physical compilation reads it. Lowering a
+Materialization decides timing; physical compilation reads it. Lowering a
 node does not depend on the frontier, so each query DAG is lowered once and
-different lifecycle assignments are different cuts of that lowering.
+different materialization assignments are different cuts of that lowering.
 `compile(dag, inputs, roots)` yields the complete `CompiledPhysicalDAG`.
 `frontier_from_timing(&timed_dag)` reads an assignment's timed DAG (from
 `execution_timed_dag`) and returns its frontier: ingestion-time nodes read by
@@ -448,7 +424,7 @@ pane candidates remain a separate lowering.
 
 Physical compilation opens no readers. Bounded precompute outputs become typed
 query inputs. Their source, filters, grouping, build window, evaluation time, readiness and
-revision contracts must accompany the selected lifecycle and be checked during
+revision contracts must accompany the selected materialization and be checked during
 deployment binding. Type compatibility alone does not establish reuse legality.
 
 The Planner integration test executes both candidates through the shared runtime
@@ -463,7 +439,7 @@ The **Deployment Plan Compiler** binds the Physical DAGs to the concrete deploym
 
 ```text
 Physical DAGs
-+ Summary Maintenance Lifecycle
++ Materialization
 + deployment catalog/state
 + sources/materializations
 + operational policy
@@ -507,7 +483,7 @@ InputSlot<KllState>[5 panes]
 ```
 
 The Deployment Plan Compiler establishes bindings and checks that their contracts
-satisfy the physical inputs and selected lifecycle, including KLL parameters,
+satisfy the physical inputs and selected materialization, including KLL parameters,
 source, filters, grouping, window coverage and revision scope. The deployment engine
 resolves request-specific states and checks their actual coverage, revisions and
 readiness at execution time. A compiled plan cannot establish future readiness.
@@ -523,8 +499,8 @@ The complete example makes the ownership boundary explicit:
 | Stage | KLL example decision |
 | --- | --- |
 | **Logical Post-ASAP DAG** | Use `KLL(k=200)` with shared merge for p50/p99 |
-| **Summary Maintenance Candidate Generation** | Maintain 1-minute panes and reuse them for aligned five-minute queries |
-| **Summary Maintenance Lifecycle** | Record pane/window/freshness/reuse requirements and each node's execution timing |
+| **Stage 2 Materialization (#509)** | Maintain 1-minute panes and reuse them for aligned five-minute queries |
+| **Materialization** | Record pane/window/freshness/reuse requirements and each node's execution timing |
 | **Physical Plan Compiler** | Lower to native KLL build, merge, and readout operators |
 | **Physical DAG** | Define precompute and query DAGs with typed input/output boundaries |
 | **Deployment Plan Compiler** | Bind raw input and KLL state slots to concrete sources/materializations |
@@ -534,7 +510,7 @@ The complete example makes the ownership boundary explicit:
 Logical:
     "Use KLL for p50/p99."
 
-Lifecycle:
+Materialization:
     "Maintain reusable 1-minute KLL panes."
 
 Physical:
@@ -564,17 +540,11 @@ snapshots as separate inputs.
 
 ## 6. Executable acceptance coverage
 
-The tests cover optimizer-selected lifecycle execution alongside independent
+The tests cover physical candidate execution alongside independent
 operator/runtime fixtures:
 
 | Test | Contract exercised |
 | --- | --- |
-| `summary_maintenance_lifecycle_e2e::continuous_lifecycle_compiles_and_executes_spatial_kll` | PromQL workload → selected continuous lifecycle → logical DAG → compiled precompute/query candidate → results in independent revisions; an unbounded candidate fails before pricing, and a bounded request candidate summarizes the same input samples |
-| `summary_maintenance_lifecycle_e2e::chosen_lifecycle_timing_decides_precompute_contents` | PromQL workload → enumerated lifecycles → explicit choice → timed DAG → compiled candidate; ContinuouslyMaintained stores the state in precompute, Ephemeral leaves precompute empty and reads the raw source at query time; both return the same p99 |
-| `summary_maintenance_lifecycle_e2e::lifecycle_timing_cuts_one_compilation` | KLL quantile and grouped Rate→Sum: one compilation cut by the ContinuouslyMaintained and Ephemeral timed DAGs equals `compile_candidate` for each; the frontier is the retained state or empty |
-
-| `summary_maintenance_lifecycle_e2e::chosen_population_lifecycle_decides_precompute_contents` | PromQL `topk by(job)` over a maintained population → explicit choice → timed DAG → compiled candidate; ContinuouslyMaintained stores the population in precompute, Ephemeral rebuilds it from raw samples at query time; both rank alike |
-| `summary_maintenance_lifecycle_e2e::planner_lifecycle_selection_reproduces_strategy_timing` | For PromQL summary fixtures, the timed DAG from Planner's retained selection equals the DAG realization strategies produce |
 | `kll_pane_execution::five_panes_roundtrip_and_shared_merge_runs_once` | Explicit one-minute precompute DAGs → real MessagePack state bytes → five required query inputs → shared native merge → p50/p99; counts every sample once, checks adjacent aligned windows and instruments one merge start per run |
 | `kll_pane_execution::restored_panes_reject_corruption_parameters_schema_and_missing_binding` | Corrupt bytes, parameter relabelling, incompatible schemas and absent bindings fail explicitly |
 | `precompute_candidates::grouped_rate_can_be_materialized_before_or_after_grouped_sum` | Cost changes select different legal precompute frontiers; both selected candidates execute with the same reset-sensitive result; uncompilable candidates are not priced |
diff --git a/docs/design_docs/proposals/asap-aware-mapping/README.md b/docs/design_docs/proposals/asap-aware-mapping/README.md
index a58d3b5dd..814d50134 100644
--- a/docs/design_docs/proposals/asap-aware-mapping/README.md
+++ b/docs/design_docs/proposals/asap-aware-mapping/README.md
@@ -9,4 +9,3 @@ extensions. Each status note identifies the implemented scope and remaining work
 - [Shared maintained populations](maintained-populations.md)
 - [Optimization dimensions](optimizations.md)
 - [Summary properties](summary-properties.md)
-- [Workload demand and summary lifecycle](workload-demand-and-summary-lifecycle.md)
diff --git a/docs/design_docs/proposals/asap-aware-mapping/analytical-resource-cost.md b/docs/design_docs/proposals/asap-aware-mapping/analytical-resource-cost.md
index b742a8970..6e270159e 100644
--- a/docs/design_docs/proposals/asap-aware-mapping/analytical-resource-cost.md
+++ b/docs/design_docs/proposals/asap-aware-mapping/analytical-resource-cost.md
@@ -2,7 +2,7 @@
 
 > Status: implemented model with explicit support limits. The
 > [analytical estimator](../../../../crates/asap-aware-mapping/src/analytical_cost.rs)
-> and physical/streaming adapters implement supported evidenced comparisons.
+> and physical-plan adapter implement supported evidenced comparisons.
 > Unsupported operators, arrival modes and missing evidence remain unavailable;
 > proposed extensions are not implied by the implemented formulas.
 
@@ -17,23 +17,19 @@ plans. These are separate concerns:
   evidence to estimate CPU work, peak memory, and source/disk I/O.
 
 The physical-resource estimator itself is independent of the arrival mode.
-Two planner adapters currently lower work into it. `PhysicalPlanCostModel`
-compares complete at-rest plans. `SummaryMaintenanceCostModel` resolves
-`DataArrival::ContinuouslyIngesting` over a finite horizon, including
-bootstrap, arriving updates, retained state, and query readout. Evidence from
-one arrival mode must not be reused for the other. `Mixed` and `Unknown`
-remain unavailable until their distinct data regions are modeled.
-
-Both entry points replace dimensionless plan-node counts with estimates
+One planner adapter currently lowers work into it: `PhysicalPlanCostModel`
+compares complete at-rest plans. Continuously-ingesting, `Mixed` and `Unknown`
+comparisons are unavailable; costing summary maintenance over arriving data
+belongs to Stage 2 materialization (#509). Evidence from one arrival mode must
+not be reused for another.
+
+The adapter replaces dimensionless plan-node counts with estimates
 derived from operator complexity, cardinality, row width, and concrete summary
 parameters. The estimates are predictions; they are not measurements reported
 by a physical executor.
 
 The model does not decide semantic legality. Ordinary summary guarantees are
-composed before costing. A window framework that itself introduces error must,
-however, carry a typed composed guarantee in the same complete evidence bundle;
-the streaming adapter checks that guarantee against every bound workload
-accuracy target before the candidate can be ranked. Missing evidence produces
+composed before costing. Missing evidence produces
 an unavailable estimate, never an assumed zero or a structural-cost fallback.
 
 The implementation keeps five layers distinct:
@@ -64,21 +60,12 @@ physical_operator_statistics.rs ──────┤ physical evidence contract
                                       ▼
 analytical_cost.rs ─────────── operator formulas and CPU/memory/I/O composition
         │
-        ├──────────────► physical_plan_cost_model.rs
-        │                 at-rest raw/rewrite/summary comparison adapter
-        │
-        └──────────────► summary_maintenance_cost/
-                          evidence.rs   authoritative summary evidence
-                          estimator.rs  complete maintenance-DAG resources
-                          window.rs     window assignment and accuracy
-                          model.rs      lifecycle/alternative ranking adapter
+        └──────────────► physical_plan_cost_model.rs
+                          at-rest raw/rewrite/summary comparison adapter
 ```
 
-Raw query plans and incrementally maintained summary plans share
-`EvidenceBackedPhysicalDAG`; there is no streaming-only duplicate of the
-physical DAG or operator-statistics contract. Summary-maintenance modules add
-only the evidence and scheduling semantics that do not exist for an ordinary
-query plan.
+Raw query plans and summary plans share `EvidenceBackedPhysicalDAG`; there is
+no separate physical DAG or operator-statistics contract for summaries.
 
 An estimate has physical dimensions:
 
@@ -236,14 +223,14 @@ normalized workload, lowered query IR, and freshness-aware statistics:
 `DataWorkload` does define whether input is streaming: its `arrival` field is
 `AtRest`, `ContinuouslyIngesting`, `Mixed`, or `Unknown`, and a continuous
 arrival rate comes from fresh `ingestion_rate` evidence. These facts describe
-how source data arrives. They do not choose a lifecycle or a window framework:
+how source data arrives. They do not choose materialization or a window framework:
 `Incremental` describes how a selected summary state is updated, while
 tumbling, sliding, and exponential histogram describe how that state is
 organized over time.
 
 Evidence is read through `Evidence<T>::value_at(planning_time)`. Stale,
 future, or improperly time-bounded evidence remains unknown. Costing follows
-the same freshness rule as accuracy and lifecycle planning.
+the same freshness rule as accuracy checking.
 
 The current workload schema does not yet contain every physical statistic.
 The missing facts have explicit ownership:
@@ -306,7 +293,7 @@ physical operators and matching statistics variants. Until then, a candidate
 containing such an unlowered operation is unavailable rather than partially
 costed.
 
-## Workload horizon and lifecycle
+## Workload horizon
 
 Every alternative must cover the same source data and query horizon. The
 `DataArrival::AtRest` physical-DAG comparison is build-once, read-many:
@@ -327,9 +314,7 @@ incremental updates are a one-time snapshot build.
 
 The at-rest summary alternative scans the selected source snapshot once and
 retains state. Its raw alternative recomputes from that snapshot for every
-query read. The continuously-ingesting entry point separately charges
-bootstrap, updates, summary operations, retained state, and raw evaluations;
-its lifecycle rules are defined below.
+query read.
 
 ### Comparable source and workload scope
 
@@ -733,157 +718,14 @@ input.
 
 ## Summary operator formulas
 
-### Incremental single-summary foundation
-
-For `DataArrival::ContinuouslyIngesting`, the incremental estimator accepts
-one selected lifecycle and one unique logical `SummaryAgg`. This deliberately
-narrow contract prevents one flat evidence record from being reused across
-several summary nodes with different input cardinalities, algorithms, or state
-sizes. Complete multi-node streaming alternatives require per-node physical
-evidence.
-
-The canonical workload supplies fresh bootstrap cardinality, ingestion rate,
-query recurrence, planning time, and a finite horizon. Physical evidence adds
-logical/bootstrap bytes, physical bootstrap scan bytes, active and retained
-window counts, the number of concrete summary-state instances per window, and
-bytes per state instance. Names use `summary`, not `sketch`, because an exact
-aggregate or another non-sketch state is equally valid.
-
-For bootstrap rows `B`, arrivals `U`, simultaneously updated windows `A`,
-query evaluations `Q`, physical summary instances `P`, and state bytes `S`:
-
-```text
-insert invocations = (B + U) × A
-retained memory     = (A + retained_windows) × P × S
-```
-
-Each input row is routed to its matching summary instance; it is not inserted
-into every group. Merge, subtract, and readout work may operate over all `P`
-instances. Delete work follows the same routed window updates rather than
-multiplying every update by every possible group.
-
-An empty bootstrap is valid and has zero logical bytes and zero source reads.
-A non-empty bootstrap requires positive logical and physical source bytes.
-Active window count, summary-instance count, state width, horizon, and query
-evaluation count must be positive; retained-window count may be zero for a new
-stream. Required per-operation CPU evidence must be finite and positive.
-
-Lifecycle retention and the planning horizon are different quantities. A
-short retained window may be maintained throughout a much longer planning
-horizon, so the estimator does not require `retention >= horizon`. Lifecycle
-legality and query time-coverage checks establish whether the retained window
-can answer the query.
-
-### Comparing single-summary lifecycle alternatives
-
-For one logical `SummaryAgg`, the analytical lifecycle adapter converts the
-same physical evidence into the existing lifecycle planner's five cost terms:
-
-| Lifecycle term | Resource basis |
-|---|---|
-| Initial build | Bootstrap rows routed to every bootstrap-active window, plus the bootstrap source read. |
-| Maintenance per update | One arriving row routed to every currently active window. |
-| Summary read | Readout of every physical summary instance needed by one query evaluation. |
-| Retention rate | All active and retained state bytes calibrated over the finite comparison horizon. |
-| Retirement | Zero only for releasing modeled memory; an actual delete, expiration, or rebuild requires explicit operation evidence. |
-
-The existing lifecycle model—not this adapter—enumerates `Ephemeral`,
-`Prepared`, `Shared`, and `ContinuouslyMaintained`, checks workload and runtime
-legality, and multiplies per-update and per-read terms by the normalized
-workload rates. Missing any required term leaves that alternative unavailable.
-
-`Ephemeral` is a direct build, not incremental maintenance. For every query
-evaluation, it rebuilds from the snapshot visible at that evaluation, charges
-that evaluation's complete source read, and releases its state afterward.
-Its state contributes to peak transient memory but not persistent retention.
-
-The raw side is supplied as a complete `ResourceEstimate` for one execution of
-the raw physical DAG. The lifecycle planner applies the same recurrence and
-horizon. This deliberately avoids reconstructing raw work with a special-case
-`input_rows × cpu_per_row` formula that would omit joins, windows, sorts, or
-other operators.
-
-Flat single-summary evidence is bound to the exact `SummaryNode` and raw
-`QueryExpr` identities for which it was produced. It cannot be reused for a
-structurally similar node or for multiple summary states. A complete
-multi-summary `SummaryExpr` DAG requires per-node physical evidence and
-physical-identity deduplication.
-
-### Complete bound streaming summary DAGs
-
-The multi-node streaming path accepts a complete, already-bound
-`SummaryExpr` DAG. It does not guess physical implementations. The provider must
-provide evidence for every reachable node:
-
-| Logical node | Required physical evidence |
-|---|---|
-| `KeepPreAsap` | One retained preprocessing operator with output edge, horizon CPU, workspace, and output buffer. |
-| `SummaryAgg` | Input/output edges, insert CPU, concrete state count and width, bootstrap/update window fanout, and explicit source-read ownership. |
-| `SummaryMerge` | Typed merge evidence with total CPU, workspace, output buffer, I/O, and execution multiplicity. |
-| `SummarySubtract` | Typed subtract evidence with the same resource dimensions. |
-| `SummaryDelete` | Typed delete evidence plus expiration/retraction rate, routing fanout, and the exact state owner. |
-| `SummaryEstimate` | Typed readout evidence with total resource use per execution. |
-| `SummaryJoin` | Ordered input/output edges and total physical join CPU, workspace, output buffer, I/O, and multiplicity. |
-
-The merge/subtract/delete/readout evidence is an enum structured by operation
-kind. Delete-only rate and routing fields therefore cannot be attached to a
-merge or readout. Join CPU is the total build, probe, match-production, and
-output work of the selected algorithm; matched output pairs alone are not a
-valid join cost.
-
-Every parent input edge must equal the corresponding child output edge.
-Provider-owned `physical_id` values deduplicate a shared operator only when
-its complete evidence and physical child identities also agree. The cost model
-holds owning `Rc` references for bound target and summary roots, so pointer
-keys cannot become stale and alias a later allocation.
-
-A `SummaryAgg` that reads storage declares `scan_selection_index = Some(i)`,
-a non-empty bootstrap-read identity, and positive physical source bytes. An
-aggregate over an already-materialized summary edge declares `None`, an empty
-read identity, and zero source bytes. Its logical input rows and bytes remain
-positive when the intermediate is non-empty. This prevents nested aggregates
-from charging the original source scan repeatedly.
-
-For streaming raw recomputation, `planning_time_input_rows`,
-`planning_time_input_bytes`, and `planning_time_source_scan_bytes` describe the
-initial snapshot. Logical bytes per arriving row and physical source bytes per
-arriving row are separate. The recurrence determines every evaluation offset;
-the provider supplies one once-counted physical DAG whose statistics aggregate
-those evolving evaluations over the complete horizon. Marking its nodes
-`PerEvaluation` would multiply the already-aggregated evidence again and is
-rejected. Validation follows only nodes reachable from the physical root. If
-the raw algorithm intentionally reads the same semantic source more than once,
-each reachable scan carries the same evolved source statistics and is charged
-separately; equal scan selection does not deduplicate physical I/O.
-
-This raw-evolution contract currently supports exactly one distinct source
-coverage. A multi-source streaming target is unavailable until per-source
-arrival rates and widths are supplied. Target lineage includes ordinary
-predicates and PromQL info selectors; extra, missing, or mismatched source
-coverage makes both sides incomparable.
-
-Lifecycle enumeration considers only alternatives legal for the canonical
-workload and runtime. A `Prepared` state must cover every scheduled evaluation
-it serves. `Shared.retention` describes data/window coverage, not the planning
-horizon, so a shorter retention value is not rejected merely because the
-optimizer horizon is longer. Missing node evidence, zero required CPU,
-unknown I/O, inconsistent edges, or an unsupported lifecycle combination
-makes the complete candidate unavailable; partial per-state costs are never
-used as a fallback.
+Costing incremental maintenance of continuously-ingested summaries was removed
+with the summary maintenance lifecycle; Stage 2 materialization (#509) will
+define it. The formulas below give per-operation work and state size.
 
 ### Ranking complete physical implementations
 
 A logical summary candidate can be bound to more than one complete physical
-implementation. Each alternative has a non-empty, provider-owned identity and
-a complete `StreamingNodeEvidence` bundle. The planner evaluates every legal
-lifecycle combination against every bound physical implementation over the
-same `ComparisonScope`, excludes alternatives whose evidence is incomplete or
-invalid, and returns both the least calibrated cost and its physical-plan
-identity. Duplicate identities are rejected because they would make the
-selection result ambiguous. If no explicit alternatives are registered, the
-candidate's single canonical evidence bundle is used.
-
-Physical evidence is alternative-specific: window fanout, retained state,
+implementation. Physical evidence is alternative-specific: window fanout, retained state,
 operation costs, and source reads must describe that implementation as a
 whole. The planner does not mix individual nodes from different alternatives.
 
@@ -903,7 +745,7 @@ cpu_ops = bootstrap_rows × bootstrap_window_count × insert_ops(params)
 scan_bytes = source_read_bytes for the build
 ```
 
-Merge, subtract, and delete add their own invocation counts described above;
+Merge, subtract, and delete add their own invocation counts;
 they are never folded into the simple formula implicitly.
 
 Concrete accuracy-sized parameters determine state and work:
@@ -927,7 +769,7 @@ from logical group count alone.
 Summary merge, subtract, delete, and readout are separate physical operators.
 Their CPU and memory use the concrete summary state size and number of input
 states. A plan using one of these operations is unavailable until the
-corresponding formula and required lifecycle evidence are present.
+corresponding formula and required evidence are present.
 
 Summary construction uses physical-input realization rules before it emits a
 `SummaryAgg`. The default rule consumes the logical aggregate's immediate
@@ -988,9 +830,7 @@ mismatches and arithmetic overflow also fail closed.
 ### Downstream physical-planning boundary
 
 This cost model consumes resource evidence for a physical implementation, but
-ASAPPlanner does not own or select that implementation. It does select the
-abstract per-summary `SummaryWindowFramework` assignment by comparing complete
-`StreamingWindowFrameworkCandidate` evidence bundles. Component ownership,
+ASAPPlanner does not own or select that implementation. Component ownership,
 including the distinction between a window primitive and its concrete runtime
 implementation, is defined in
 [ASAPPlanner planner-runtime contract](../../architecture/planner-runtime-contract.md).
@@ -1064,7 +904,7 @@ candidate.
 The intended end-to-end selection pipeline is:
 
 1. enumerates semantically valid alternatives;
-2. checks end-to-end accuracy and lifecycle legality;
+2. checks end-to-end accuracy;
 3. derives fresh workload and operator statistics;
 4. sizes physical summary parameters;
 5. estimates the complete candidate DAG;
@@ -1075,31 +915,8 @@ listed above. `PhysicalPlanCostModel` executes this pipeline for every
 candidate supplied to `CandidateLogicalASAPDAGs::global_selection`. Logical rewrites are
 lowered recursively. Summary candidates participate only after the deployment
 has bound their complete `SummaryExpr` DAG; there is no optimistic generic
-summary fallback. The streaming adapter connects raw recomputation and
-primitive summary lifecycle costs to the existing global lifecycle-selection
-hooks.
-The lifecycle planner enumerates compatible lifecycle combinations for the
-unique `SummaryAgg` deployments and invokes
-`complete_summary_candidate_estimate`
-for each combination before selecting the minimum. The hook receives explicit
-node-to-guarantee bindings plus the horizon and expected reads. Each logical
-occurrence is looked up by exact `Rc` identity, while every
-evidence record also carries a provider-owned physical identity. Equal physical
-identities deduplicate work and retained state only when their logical summary,
-selected window framework, operator facts, edge statistics, lifecycle
-guarantee, and physical child identities agree;
-conflicts make the candidate unavailable. Thus heterogeneous states are costed
-independently and genuinely shared deployments once. Merge, subtract, delete,
-readout, and join participate in automatic
-candidate ranking. Exhaustive whole-root scoring is capped at 4,096 lifecycle
-combinations because an arbitrary whole-candidate hook cannot be soundly
-pruned by primitive costs; a larger space is unavailable rather than consuming
-exponential planner time. If the root needs unavailable operation evidence, the
-hook returns unavailable. Global selection then excludes that summary and
-materialization retains the raw expression. A missing raw estimate also forces
-raw fallback, because no public selection/materialization path may publish an
-uncompared summary. The planner never falls back to the partial `SummaryAgg`
-sum.
+summary fallback. Choosing between a maintained summary and raw recomputation
+belongs to Stage 2 materialization (#509).
 
 Before applying the following arithmetic, callers validate exact equality of
 the raw and selected alternative's `ComparisonScope`, and use the same
diff --git a/docs/design_docs/proposals/asap-aware-mapping/maintained-populations.md b/docs/design_docs/proposals/asap-aware-mapping/maintained-populations.md
index 005670db8..c2b05588e 100644
--- a/docs/design_docs/proposals/asap-aware-mapping/maintained-populations.md
+++ b/docs/design_docs/proposals/asap-aware-mapping/maintained-populations.md
@@ -70,7 +70,7 @@ columns and multi-measure aggregates need additional rules.
 
 ```text
 KeepPreAsap(input)
-  -> MaintainPopulation { input, max_k, quantiles }  [lifecycle-timed]
+  -> MaintainPopulation { input, max_k, quantiles }  [ingestion time]
        -> ReadPopulation { Quantile(q1) }           [read]
        -> ReadPopulation { Quantile(q2) }           [read]
        -> ReadPopulation { TopK(k1) }               [read]
@@ -116,8 +116,7 @@ because their source names or numeric values happen to agree.
 ## Validation, selection and execution responsibilities
 
 Planner validates the declared input, the query-time readout and readout
-compatibility; the population's lifecycle decides whether it is maintained at
-ingestion or rebuilt per query. Its intended guarantee is exact membership and exact readout;
+compatibility; `MaintainPopulation` always runs at ingestion time. Its intended guarantee is exact membership and exact readout;
 a physical implementation still must preserve the language's numeric and empty-input
 semantics. In particular, SQL global COUNT over an empty population returns a row
 with zero, while PromQL COUNT over an empty vector returns an empty vector.
diff --git a/docs/design_docs/proposals/asapquery-rule-coverage.md b/docs/design_docs/proposals/asapquery-rule-coverage.md
index 634878696..9ba999292 100644
--- a/docs/design_docs/proposals/asapquery-rule-coverage.md
+++ b/docs/design_docs/proposals/asapquery-rule-coverage.md
@@ -25,7 +25,7 @@ cost, and selection rules under `optimizer/`. The reviewed source is
 | Subpopulation label placement | Covered more generally | `HydraGroupingStrategy` and `GroupingStrategy` express per-subpopulation and shared multi-subpopulation realizations. |
 | Shared computation | Covered more generally | workload-wide CSE and `SharedSubDAGStrategy` operate on physical DAG identity rather than AQE names. |
 | Average decomposition | Semantic-equivalent rewriting | The same rewrite strategy exposes independently optimizable sum/count accumulators when null semantics and schema permit it. |
-| Merge/delete legality | Covered | Summary-family capabilities and lifecycle validation determine which maintenance operations are legal. |
+| Merge/delete legality | Covered | Summary-family capabilities determine which maintenance operations are legal. |
 | Window-framework selection | Separate physical-planning work | Window selection must compare an extensible set of implementations, including tumbling, sliding, PromSketch-style exponential-histogram windows, and other window frameworks. This audit does not introduce a closed window enum or choose among them. |
 | Retention/cleanup scheduling | Outside planner scope | The audit deliberately does not import ASAPQuery's Arroyo-specific cleanup thresholds, timers, or failure workarounds. The planner may declare a selected summary's required retention horizon and cost it, but the runtime/storage layer owns when and how expired physical state is reclaimed. |
 | Empirical per-sketch atomic costs | Covered through evidence | Analytical statistics and deployment profiles provide cost evidence; benchmark tables should be ingested as calibrated evidence rather than compiled into matching rules. |
@@ -45,7 +45,7 @@ does not create a new strategy category.
 | Whether a finer grouping can answer a coarser grouping | `RollupStrategy` |
 | Whether tighter accuracy can answer a looser request | `AccuracyReconciliationStrategy` |
 | Whether a larger Top-K result can answer a smaller limit | `TopKLimitReuseStrategy` |
-| Which maintenance lifecycle is legal | the summary-maintenance lifecycle planner |
+| Whether and when a summary is materialized | Stage 2 materialization (#509) |
 | Which window framework implements a range | the physical deployment/window-selection planner |
 | How expired physical state is cleaned up | runtime/storage lifecycle management, not a planner strategy |
 
@@ -53,7 +53,7 @@ Accordingly, ASAPQuery's four collapsible temporal/spatial patterns extend the
 existing semantic-rewrite owner. Temporal and spatial function recognition is
 already front-end lowering into `AggIntent`; sketch compatibility remains in
 `ASAPStrategies`; labels remain in `HydraGroupingStrategy`; and
-maintenance lifecycle legality remains in the lifecycle planner. Window
+materialization decisions belong to Stage 2 materialization (#509). Window
 framework selection is separate physical-planning work. None of these become a
 parallel syntax-oriented `PatternStrategy`.
 
@@ -69,7 +69,7 @@ planner.
 Rules match typed operators and declared capabilities, never parser spellings.
 A rule that composes operators states the algebraic law it relies on and
 preserves the original output schema. Unknown pairs, missing statistics, or
-unsupported lifecycle operations produce no candidate; they never silently
+unsupported maintenance operations produce no candidate; they never silently
 fall back to an optimistic estimate.
 
 Window choices should follow the same principle without assuming that every
diff --git a/docs/develop_docs/asap-aware-mapping-architecture.md b/docs/develop_docs/asap-aware-mapping-architecture.md
index 154c131ff..eaf3d879a 100644
--- a/docs/develop_docs/asap-aware-mapping-architecture.md
+++ b/docs/develop_docs/asap-aware-mapping-architecture.md
@@ -257,8 +257,8 @@ contract consistent and preserves the full choice set for other callers.
 
 `CandidateLogicalASAPDAGs::global_selection` optionally coordinates cross-target sharing and
 composition choices. `GlobalSelection::assemble_selected_dag` constructs the selected
-semantic DAG. These plain APIs do not establish lifecycle or physical deployment
-feasibility. Recurrence and lifecycle-aware variants require the corresponding
+semantic DAG. These APIs do not decide materialization or establish physical
+deployment feasibility. Recurrence-aware variants require the corresponding
 workload and evidence inputs; downstream owns physical commitment and execution.
 See the [library workflow](library-api.md#optional-whole-plan-selection-and-dag-assembly).
 
diff --git a/docs/develop_docs/library-api.md b/docs/develop_docs/library-api.md
index fadb6bdc0..7e8b2768d 100644
--- a/docs/develop_docs/library-api.md
+++ b/docs/develop_docs/library-api.md
@@ -15,7 +15,6 @@ do not deploy a plan, and a serializable DAG is not evidence of runtime readines
 | Pre-ASAP IR | Frontend `lower_*` | [Lower a query](#lower-a-query-into-pre-asap-ir) |
 | All ranked candidates | `search_workload_with_targets` -> `cost_sorted` | [Generate and rank](#generate-and-rank-candidates) |
 | Custom optimization set | Construct `Vec<Box<dyn ReplacementStrategy>>`, then search | [Strategies and models](#choose-strategies-and-models) |
-| Summary-maintenance lifecycle comparison | Lifecycle-aware selection -> DAG assembly with maintenance decisions | [Lifecycle recipe](#lifecycle-and-capabilities) |
 | Selected semantic DAG / export | `global_selection` -> `assemble_selected_dag` -> export | [Selection example](#optional-whole-plan-selection-and-dag-assembly) |
 
 Each recipe ends at a different artifact. Use only the stages needed for that
@@ -65,7 +64,7 @@ lower_promql_workload(workload: &PlanningWorkload, now_ms: u64)
 
 `DataWorkload.data_ingestion_interval` must contain a nonzero `Evidence<DurationMs>`.
 Pass the actual planning time as `now_ms` (Unix milliseconds), consistently with
-downstream lifecycle planning. Expired or future cadence evidence is rejected,
+downstream planning. Expired or future cadence evidence is rejected,
 as is expiring evidence without an observation timestamp. The histogram variant
 takes the same timestamp after its histogram catalog argument. The examples use
 `0` only because their explicitly supplied cadence is timeless.
@@ -288,7 +287,8 @@ Callers do not apply `with_series_identity` themselves. Compile each with
 `promql_rows::compile_current_series_evaluation`; other queries keep their previous
 inventory. `global_selection` never commits these candidates; the backend
 compiles and prices them. CandidateLogicalASAPDAGs lists no placement variants: node timing
-comes from the summary maintenance lifecycle.
+comes from a `MaterializationAssignment` (all query time until Stage 2
+materialization, #509, decides otherwise).
 
 ## Choose strategies and models
 
@@ -409,7 +409,7 @@ Module-qualified paths below are relative to `asap_aware_mapping`.
 | Parameter | Available value / constructor | Meaning |
 | --- | --- | --- |
 | `&dyn CostModel` | `DefaultCostModel` | Built-in ordering/sizing and structural estimates; no measured deployment guarantee |
-| `&dyn CostModel` | `empirical_cost::EmpiricalCostModel::new(provider)` | Offline sketch-benchmark model: ranks algorithms using matching offline measurements and supplies partial lifecycle costs |
+| `&dyn CostModel` | `empirical_cost::EmpiricalCostModel::new(provider)` | Offline sketch-benchmark model: ranks algorithms using matching offline measurements |
 | `&dyn CostModel` | `physical_plan_cost_model::PhysicalPlanCostModel::new(&provider, calibration)?` | Deployment-specific physical-plan model: compares complete physical alternatives using provider evidence and resource calibration; evidence may be offline or online |
 | `&dyn AccuracyModel` | `DefaultAccuracyModel` | Built-in guarantee rules and satisfaction checks |
 | `&dyn AccuracyBudgetAllocator` | `EqualSplitAllocator` | Built-in allocation of composition accuracy budgets |
@@ -423,7 +423,7 @@ These models differ in scope, not simply in whether they are offline or online.
 
 | Model | Evidence and comparison | Missing evidence / limits |
 | --- | --- | --- |
-| `EmpiricalCostModel` | Offline sketch benchmarks matched to exact parameters, distribution, environment and validity interval; current algorithm ranking uses measured update CPU nanoseconds | If the measurements required for ranking are incomplete, preserves the incoming algorithm order. Supplies partial build/update lifecycle costs; `estimate_cost()` still uses `DefaultCostModel` structural scores |
+| `EmpiricalCostModel` | Offline sketch benchmarks matched to exact parameters, distribution, environment and validity interval; current algorithm ranking uses measured update CPU nanoseconds | If the measurements required for ranking are incomplete, preserves the incoming algorithm order. `estimate_cost()` still uses `DefaultCostModel` structural scores |
 | `PhysicalPlanCostModel` | A downstream provider supplies a consistent evidence snapshot and complete physical alternatives; calibration converts modeled resource quantities into comparable costs | A candidate with incomplete evidence is unavailable, without structural-cost fallback. Current candidate admission also requires it to cost less than the raw alternative |
 
 `PhysicalPlanCostModel` does not collect online telemetry itself. Its provider
@@ -478,7 +478,7 @@ constructor using default accuracy/allocation and no extra evidence.
 | Extension point | What it controls | What it cannot establish alone |
 | --- | --- | --- |
 | `ReplacementStrategy` | Proposed semantic alternatives | Permission to violate query semantics or downstream support |
-| `CostModel` | Candidate ordering/sizing hooks, recurrence/lifecycle and complete-cost evidence hooks | Correctness, measured costs without evidence, or installed runtime support |
+| `CostModel` | Candidate ordering/sizing hooks and recurrence cost hooks | Correctness, measured costs without evidence, or installed runtime support |
 | `AccuracyModel` | Derivation, propagation and satisfaction of guarantees | A meaningful guarantee without its required assumptions/evidence |
 | `AccuracyBudgetAllocator` | Local accuracy requirements proposed within composition | End-to-end correctness without subsequent validation |
 | `AccuracyEvidenceProvider` | Planning-time statistics used by supported strategies | Authority to change query requirements |
@@ -497,12 +497,9 @@ Keep each provider's evidence scope and freshness valid for the query population
 inputs. `QueryWorkload` contains the language and optional batch/repeating
 entries. Entries carry requirements, predictability, recurrence and time
 selection. These facts are separate: repeated queries can read data at rest.
-`WorkloadDemand` associates a target with the relevant workload entry indices
-and explicitly includes or omits the parallel data evidence.
-Both recurrence and lifecycle planning validate this independent data evidence:
-ingestion rates must be finite and nonnegative, and data at rest cannot have a
-positive ingestion rate. `DataWorkload::validate()` shares these checks with
-`PlanningWorkload::validate()`.
+`DataWorkload::validate()` checks the independent data evidence: ingestion
+rates must be finite and nonnegative, and data at rest cannot have a positive
+ingestion rate. `PlanningWorkload::validate()` shares these checks.
 
 | Type/input | Current behavior | Caller responsibility |
 | --- | --- | --- |
@@ -510,188 +507,11 @@ positive ingestion rate. `DataWorkload::validate()` shares these checks with
 | `DataWorkload::default()` | Unknown arrival, unknown evidence | Supply facts needed for the requested comparisons |
 | `Evidence<T>::default()` | No value, unknown source | Unknown/stale evidence is not zero; provide scoped valid observations |
 | `DefaultCostModel` | Built-in ordering/sizing and structural cost hooks | Supply deployment evidence for calibrated comparisons |
-| `SummaryMaintenanceLifecycleCostInputs::default()` | All primitive costs unknown | Implement the required lifecycle cost hooks; structural defaults are insufficient |
-| `horizon: None` in lifecycle planning | Horizon-dependent alternatives are unselectable | Supply a positive horizon when comparing rates/amortized reuse |
-| Lifecycle capabilities default | All four modes enabled | Override with the actual runtime support |
-| Per-summary maintenance capabilities default | Incremental update, merge, delete all false | Advertise supported operations for the concrete state representation |
 
 `Default` is a Rust constructor contract, not a general serde omission rule.
 Several workload fields require explicit serialized values. A struct field being
 optional also does not guarantee every planning operation can succeed without it.
 
-## Lifecycle and capabilities
-
-Use this workflow when Planner owns summary-maintenance lifecycle decisions;
-otherwise the backend may make them from logical candidates. It includes both
-selection and DAG assembly, so callers do not first run the ordinary workflow.
-The first helper returns one `GlobalSelection`; the second is called per root
-and returns a plan containing `root: Rc<OperatorNode>` (already timed) plus maintenance decisions.
-See the [workflow design](../design_docs/architecture/input-output-workflow.md#summary-maintenance-lifecycle-aware-helper).
-
-Two capabilities are distinct: the runtime can orchestrate a lifecycle, and the
-chosen summary representation supports the required state operations. Both must
-hold. Workload legality and known cost evidence can further restrict alternatives.
-
-### API definition and options
-
-```text
-global_selection_with_summary_maintenance_lifecycles<'a, Id>(
-    space: &'a CandidateLogicalASAPDAGs<Id>, demand: WorkloadDemand<'_>,
-    now_ms: u64, horizon: Option<Horizon>,
-    capabilities: SummaryMaintenanceLifecycleCapabilities, cost_model: &dyn CostModel,
-) -> Result<GlobalSelection<'a>, SummaryMaintenanceLifecycleSelectionError>
-
-assemble_selected_dag_with_summary_maintenance_lifecycles(
-    selection: &GlobalSelection<'_>, target: &Rc<OperatorNode>,
-    demand: WorkloadDemand<'_>, now_ms: u64, horizon: Option<Horizon>,
-    capabilities: SummaryMaintenanceLifecycleCapabilities, cost_model: &dyn CostModel,
-) -> Result<Option<SummaryMaintenanceLifecyclePlan>, SummaryMaintenanceLifecycleAssemblyError>
-```
-
-| Argument | Values / requirements |
-| --- | --- |
-| `space`, `demand` | Actual candidate space plus query demand, optional data evidence, and one normalized workload entry index for each `space.roots` entry |
-| `target` | A root from `space.roots`, after canonical sharing |
-| `demand` | `WorkloadDemand::new_with_data(...)` when data evidence is available; use `new_without_data(...)` only when its absence is intentional |
-| `now_ms` | Actual planning time in Unix milliseconds for evidence freshness |
-| `horizon` | `Some(Horizon(seconds))` with positive finite seconds, or `None` when horizon-dependent comparisons are unavailable |
-| `capabilities` | Explicit Boolean fields below; several may be true |
-| `cost_model` | A model supplying required lifecycle and raw-comparison evidence; default structural estimates are not enough |
-
-| Capability field | `true` permits consideration of… | `false` means… |
-| --- | --- | --- |
-| `supports_ephemeral` | Fresh build per invocation, retired afterward | Exclude that lifecycle |
-| `supports_prepared` | Build before a predictable execution and retain until it | Exclude that lifecycle |
-| `supports_shared` | Retain state for multiple reads | Exclude that lifecycle |
-| `supports_continuously_maintained` | Keep state current as updates arrive | Exclude that lifecycle |
-
-All flags default to true; integrations should pass real support. Enabling a
-flag does not override workload, algorithm-operation or evidence checks.
-
-### Example: lifecycle-aware planning for a batch-only runtime
-
-This helper takes the real workload and cost provider from your application.
-It supports one searched root mapped to one workload entry, and returns a typed
-plan/error rather than making up costs. For a shared root consumed by several
-entries, construct demand using all applicable indices.
-
-```rust
-use asap_aware_mapping::{
-    global_selection_with_summary_maintenance_lifecycles,
-    assemble_selected_dag_with_summary_maintenance_lifecycles, CostModel, Horizon, CandidateLogicalASAPDAGs,
-    SummaryMaintenanceLifecycleCapabilities, SummaryMaintenanceLifecyclePlan,
-    WorkloadDemand,
-};
-use asap_types::workload::PlanningWorkload;
-
-fn plan_batch_root(
-    space: &CandidateLogicalASAPDAGs<&str>,
-    workload: &PlanningWorkload,
-    entry_index: usize,
-    now_ms: u64,
-    horizon: Option<Horizon>,
-    model: &dyn CostModel,
-) -> Result<Option<SummaryMaintenanceLifecyclePlan>, Box<dyn std::error::Error>> {
-    if space.roots.len() != 1 {
-        return Err("this example requires exactly one root".into());
-    }
-    let capabilities = SummaryMaintenanceLifecycleCapabilities {
-        supports_ephemeral: true,
-        supports_prepared: false,
-        supports_shared: false,
-        supports_continuously_maintained: false,
-    };
-    let indices = [entry_index];
-    let demand = WorkloadDemand {
-        workload: &workload.query_workload,
-        data_workload: workload.data_workload.as_ref(),
-        entry_indices: &indices,
-    };
-    let selection = global_selection_with_summary_maintenance_lifecycles(
-        space, demand, now_ms, horizon, capabilities, model,
-    )?;
-    let plan = assemble_selected_dag_with_summary_maintenance_lifecycles(
-        &selection, &space.roots[0].1, demand,
-        now_ms, horizon, capabilities, model,
-    )?;
-    if let Some(plan) = &plan {
-        println!("raw_recompute={}, deployments={:#?}",
-            plan.selected_raw_recompute, plan.deployments);
-    }
-    Ok(plan)
-}
-```
-
-Use this helper with the `space` built by the search example and the corresponding
-workload/provider. No incremental lifecycle is permitted, but unknown evidence
-can still prevent choosing summary state. If only one legal alternative remains,
-recording it is a complete lifecycle decision. Data-at-rest alone does not imply
-that prepared or retained shared state is supported.
-
-| Function | Inputs | Output / promise |
-| --- | --- | --- |
-| `plan_summary_maintenance_lifecycles` | Assembled logical DAG root, `WorkloadDemand`, `now_ms`, optional horizon, runtime capabilities, cost model | `Result<SummaryMaintenanceLifecyclePlan, …>` for that fixed root; does not revisit all semantic candidates |
-| `global_selection_with_summary_maintenance_lifecycles` | `CandidateLogicalASAPDAGs`, workload/root-entry associations, time, horizon, capabilities, cost model | Lifecycle-aware compatible selection/error, using eligible cost evidence |
-| `assemble_selected_dag_with_summary_maintenance_lifecycles` | Selection, target root and lifecycle context | Optional lifecycle plan/error; attaches state deployment decisions |
-| `enumerate_summary_maintenance_lifecycles` | Same inputs as `plan_summary_maintenance_lifecycles` | `SummaryMaintenanceLifecycleCandidates`: per unique retained state, every alternative with its cost or rejection; nothing selected. `guarantee(&lifecycle)` gives the mode/schedule that alternative would carry |
-| `SummaryMaintenanceLifecycleCandidates::select(choices)` | One `(PostAsapNodeId, SummaryMaintenanceLifecycle)` per state, copied from `deployments()` | The same `SummaryMaintenanceLifecyclePlan` Planner selection would produce for that combination, or `SummaryMaintenanceLifecycleChoiceError` when a choice is unknown, missing, duplicated, rejected, schedule-incompatible, or not completely estimable |
-
-Inspect `deployments`, their selected lifecycle/alternatives/rejections,
-`selected_raw_recompute`, and optional summary/raw costs. Success of a function
-call alone is not a certificate that every desired summary was selected or fully
-costed. A raw alternative remains a downstream execution obligation.
-
-Lifecycle feasibility and costs must affect final deployment comparison. Running
-lifecycle analysis after structural selection can evaluate the selected root,
-but does not make the earlier selection lifecycle-optimal. An application may
-consume ranked candidates and perform this comparison downstream instead.
-
-A deployment that prices lifecycles itself calls
-`enumerate_summary_maintenance_lifecycles`, prices the alternatives, and binds
-its choice with `select`. A choice is accepted only if Planner could select it:
-an alternative with `MissingCostEvidence` is accepted only when the cost model's
-complete-candidate hook covers lifecycle costs. Window frameworks and totals come
-from that hook, as in Planner selection.
-
-A lifecycle choice then fixes each physical placement through timing: a
-continuously maintained state and its inputs run at ingestion time, while an
-ephemeral one stays at query time. Compile each query's `PostAsapDAG` once and
-cut every chosen assignment from that result:
-
-```rust
-use asap_physical_operators::physical_planner::{
-    compile, cut_candidate, frontier_from_timing,
-};
-
-let compiled = compile(&dag, inputs, &roots)?; // each node lowered once
-for plan in lifecycle_plans {
-    let frontier = frontier_from_timing(&plan.execution_timed_dag()?)?;
-    // Precompute/query DAGs split at `frontier`; no logical lowering.
-    let candidate = cut_candidate(&compiled, &frontier)?;
-    // Check feasibility and price `candidate`; bind the selected one as is.
-}
-```
-
-The frontier is the set of ingestion-time nodes read by query-time nodes (or an
-ingestion-time root). `frontier_from_timing` rejects a query-time node feeding
-an ingestion-time node. `cut_candidate` returns exactly what
-`compile_candidate(&dag, inputs, &roots, &frontier)` returns and rejects the
-same invalid frontiers. If the DAG has an ingestion-time `Binary`, compile with
-the same timing for that node, because it lowers differently. Temporal pane
-candidates are a different lowering and still use
-`compile_temporal_pane_candidate`.
-
-Retained states are `SummaryAgg` nodes and `MaintainPopulation` nodes that do
-not feed a `SummaryAgg`; a population that does feed one is part of that
-state's input. The lifecycle cost hooks (`summary_maintenance_capabilities`,
-`summary_maintenance_lifecycle_cost_inputs_for_horizon`) and the complete-candidate
-hook therefore also receive `MaintainPopulation` nodes. A model that does not
-recognize one should return unknown costs, which keep its alternatives
-unselected; a model that prices every node uniformly now also prices
-populations, so population candidates can win lifecycle-aware selection. `SummaryMaintenanceLifecyclePlan::execution_timed_dag` times a
-population as it times a summary state: retained at ingestion, `Ephemeral` at
-query time from the raw source.
-
 ## Optional whole-plan selection and DAG assembly
 
 ### What does global selection mean?
@@ -727,14 +547,14 @@ constructs the selected semantic DAG while preserving shared nodes.
 | `cost_sorted()` | How are the alternatives ranked for each subexpression? | Ranked alternatives per target |
 | `global_selection()` | Which compatible choices should be used together, accounting for sharing and dependencies? | A coordinated selection across targets under the supplied model |
 
-Plain `global_selection()` does not automatically perform lifecycle planning or
-establish physical deployment feasibility. Use the corresponding evidence-aware
-workflow for those decisions. Downstream still owns physical commitment.
+Plain `global_selection()` does not decide materialization or establish
+physical deployment feasibility. Stage 2 materialization (#509) will own
+materialization; downstream still owns physical commitment.
 
 | Method on `CandidateLogicalASAPDAGs` / `GlobalSelection` | Behavior |
 | --- | --- |
-| `CandidateLogicalASAPDAGs::global_selection(&model)` | Compatible structural selection across targets; no recurrence or lifecycle planning implied |
-| `CandidateLogicalASAPDAGs::global_selection_with_recurrence(...)` | Compatible selection using supplied recurrence profiles/horizon; no lifecycle commitments implied |
+| `CandidateLogicalASAPDAGs::global_selection(&model)` | Compatible structural selection across targets; no recurrence or materialization planning implied |
+| `CandidateLogicalASAPDAGs::global_selection_with_recurrence(...)` | Compatible selection using supplied recurrence profiles/horizon; no materialization commitments implied |
 | `GlobalSelection::assemble_selected_dag(&target)` | `Result<Option<Rc<OperatorNode>>, RealizationError>`; constructs untimed semantic IR, not stored summary data |
 
 Use a target associated with the searched space; DAG assembly can return `None`
@@ -752,8 +572,8 @@ GlobalSelection::assemble_selected_dag(&self, target: &Rc<OperatorNode>)
 ```
 
 For structural inspection only, this complete example selects a semantic root
-and exports its inspection DAG. It performs no lifecycle or deployment planning.
-Use lifecycle-aware selection above when the comparison needs those decisions.
+and exports its inspection DAG. It performs no materialization or deployment
+planning.
 
 ```rust
 use asap_frontend_promql::lower_promql_workload;
@@ -807,14 +627,13 @@ fn main() -> Result<(), Box<dyn std::error::Error>> {
 | --- | --- |
 | `asap_types::dag_export::export(&query)` | Pre-ASAP inspection dag |
 | `asap_types::dag_export::export_summary(&summary)` | Post-ASAP inspection dag |
-| `asap_types::ir::apply_lifecycle_timings(&root, &assignment, &mut TimingMemo::new())` | Write execution timing into every node from a `LifecycleAssignment` and validate the data-state edges; a lifecycle plan's `root` is already timed |
+| `asap_types::ir::apply_materialization_timings(&root, &assignment, &mut TimingMemo::new())` | Write execution timing into every node from a `MaterializationAssignment` (default: all query time) and validate the data-state edges; `PlanOutput::execution_timed_dag()` applies the default to a planned workload |
 | `asap_types::ir::export::compile_post_asap_dag(&timed_root)` | Export a timed DAG as a `PostAsapDAG` (wire version 7); rejects an untimed node; not a physical plan |
 | `PostAsapDAGDocument::new(dag)` and `.validate()` | Versioned semantic envelope and explicit validation; constructing it alone does not validate |
-| `asap_aware_mapping::export_summary_maintenance_plan(&plan)` | Graph plus lifecycle deployments, alternatives and available cost/guarantee information |
 | `explain_replacements` / `explain_replacements_with` | Findings from default/custom-strategy search; not a complete physical feasibility report |
 
 Choose the export matching your intended handoff: an inspection DAG is not
-interchangeable with a versioned execution contract. Preserve lifecycle and
+interchangeable with a versioned execution contract. Preserve
 cost/guarantee evidence needed downstream instead of exporting only a bare DAG.
 For public symbol details, build local API documentation with:
 
@@ -827,6 +646,5 @@ cargo doc -p asap-aware-mapping -p asap-types --no-deps
 - [Frontend PromQL](../../crates/frontend-promql/src/lib.rs), [SQL](../../crates/frontend-sql/src/lib.rs), [MetricsQL](../../crates/frontend-metricsql/src/lib.rs)
 - [Search, ranking and selection](../../crates/asap-aware-mapping/src/replacement.rs)
 - [Cost models](../../crates/asap-aware-mapping/src/cost_model.rs)
-- [Lifecycle APIs](../../crates/asap-aware-mapping/src/summary_maintenance_lifecycle.rs)
 - [Workload types](../../crates/types/src/workload.rs)
 - [Planner-runtime contract](../design_docs/architecture/planner-runtime-contract.md)
diff --git a/docs/develop_docs/offline-sketch-evidence.md b/docs/develop_docs/offline-sketch-evidence.md
index 56c507de1..4a6d0c2ca 100644
--- a/docs/develop_docs/offline-sketch-evidence.md
+++ b/docs/develop_docs/offline-sketch-evidence.md
@@ -60,8 +60,7 @@ distribution or machine; the provider does not interpolate between datasets.
 Each measured resource is an optional `Measurement` with `value`, optional `stddev`,
 `samples`, and optional `method`. CPU fields are process CPU nanoseconds per
 operation; `build_cpu_ns` measures empty construction. Building an ingested
-snapshot additionally requires `sample_count × update_cpu_ns`; the lifecycle
-helper returns that sum only when both measurements exist. Memory and disk
+snapshot additionally requires `sample_count × update_cpu_ns`. Memory and disk
 fields are bytes; `scan_bytes` records bytes read by scans, not storage occupancy.
 Producer methods must state what
 was measured and how normalization was performed. `retained_bytes` is distinct
@@ -87,12 +86,10 @@ scores as CPU or measured savings.
 
 Deployment cost models can own the provider and call `lookup` with their own
 parameter sizing. This preserves the deployment's other cost and capability
-hooks. The provider's lifecycle helper returns available build/update CPU costs
-for a single independently instantiated state. It deliberately leaves retention,
-retirement and read costs unknown. In particular, a point-frequency benchmark
-read does not price a total-count read, even when both use CMS. A deployment must
-match evaluation semantics and supply the missing lifecycle and raw-query evidence
-before selecting and pricing a complete physical plan. Never combine these
+hooks. A point-frequency benchmark read does not price a total-count read, even
+when both use CMS. A deployment must match evaluation semantics and supply
+retention, retirement, read and raw-query evidence before selecting and pricing
+a complete physical plan. Never combine these
 nanosecond costs with CPU operation counts without explicit calibration.
 
 `error` contains offline observed statistics and a query descriptor. Its metric
diff --git a/docs/develop_docs/physical-compile-coverage.md b/docs/develop_docs/physical-compile-coverage.md
index b8db36c7b..720767696 100644
--- a/docs/develop_docs/physical-compile-coverage.md
+++ b/docs/develop_docs/physical-compile-coverage.md
@@ -5,8 +5,9 @@ Audience: developers moving computation from ASAPQuery-backend into
 
 ## Contract
 
-Logical selection decides what to compute. The maintenance lifecycle sets node
-timing. `physical_planner::compile` turns a timed `PostAsapDAG` into physical
+Logical selection decides what to compute. A `MaterializationAssignment` sets
+node timing (all query time until Stage 2 materialization, #509, decides
+otherwise). `physical_planner::compile` turns a timed `PostAsapDAG` into physical
 operator DAGs. The backend owns ingestion, panes, storage, stored-state
 evaluation, external exact engines, pricing/selection, and execution scheduling.
 
diff --git a/docs/develop_docs/physical-handoff-costs.md b/docs/develop_docs/physical-handoff-costs.md
index 29525f2c5..dcd95e747 100644
--- a/docs/develop_docs/physical-handoff-costs.md
+++ b/docs/develop_docs/physical-handoff-costs.md
@@ -88,8 +88,8 @@ traffic is inferred from logical edges, operator buffers, or scan bytes.
 Unknown endpoints, mismatched payloads, absent node evidence, duplicate IDs,
 stale evidence, invalid coefficients, and integer overflow return typed errors;
 ranking/export report the comparison as unavailable. This extends the physical
-plan adapter; lifecycle-specific summary-maintenance costing and caching are
-separate follow-up integration points.
+plan adapter; summary-maintenance costing for Stage 2 materialization (#509) is
+a separate follow-up integration point.
 
 Verification:
 
diff --git a/docs/develop_docs/pre-asap-ir.md b/docs/develop_docs/pre-asap-ir.md
index 0a5c21ec6..04f71b15a 100644
--- a/docs/develop_docs/pre-asap-ir.md
+++ b/docs/develop_docs/pre-asap-ir.md
@@ -33,7 +33,7 @@ pub struct OperatorNode {
     pub result_kind: OperatorResultKind,      // Relation | InstantVector | RangeVector | State | Scalar
     pub schema: Schema,                       // output schema, derived at construction
     pub guarantee: Option<ResultGuarantee>,   // None until accuracy assessment establishes one
-    pub timing: Option<ExecutionTiming>,      // None until a lifecycle assignment is applied
+    pub timing: Option<ExecutionTiming>,      // None until a materialization assignment is applied
 }
 ```
 
@@ -47,7 +47,7 @@ pub struct OperatorNode {
   retain a more specific schema through `OperatorNode::with_schema`.
 - `guarantee` is `None` until accuracy assessment establishes one; `None` never means exact.
 - `timing` is `None` in every front-end DAG and every candidate. It is written by
-  `ir::timing::apply_lifecycle_timings` (see the Post-ASAP IR document); export rejects an
+  `ir::timing::apply_materialization_timings` (see the Post-ASAP IR document); export rejects an
   untimed node.
 
 `OperatorNode::children()` returns the operator's inputs in field order followed by the
diff --git a/docs/develop_docs/storage-operation-costs.md b/docs/develop_docs/storage-operation-costs.md
index 1a8dacdbd..999b79103 100644
--- a/docs/develop_docs/storage-operation-costs.md
+++ b/docs/develop_docs/storage-operation-costs.md
@@ -71,8 +71,7 @@ estimate and storage request estimate remain independently inspectable.
 Missing entries, expired/future evidence, incompatible node snapshots, zero
 request sizes, invalid calibration, and overflow return typed analytical
 errors. When used by plan ranking/export they make that comparison unavailable.
-This profile extends the physical-plan adapter; the separate summary-maintenance
-lifecycle estimator retains its existing dimensions. Combined physical-plan
+This profile extends the physical-plan adapter. Combined physical-plan
 ranking currently supports storage profiles only with an explicit `NoCache`
 profile. `CacheProfile::Evidence` together with storage evidence makes the
 comparison unavailable: aggregate cache hit ratios cannot identify which
diff --git a/docs/develop_docs/target-candidate-api-migration.md b/docs/develop_docs/target-candidate-api-migration.md
index 1adc6a568..4619be2a8 100644
--- a/docs/develop_docs/target-candidate-api-migration.md
+++ b/docs/develop_docs/target-candidate-api-migration.md
@@ -24,8 +24,8 @@ The earlier #445 renames (`TargetSubDAGCandidates`,
 counterpart) are prerequisites, not additional changes here.
 
 The workflow remains one selection call per workload followed by one assembly
-call per query root. `SummaryMaintenanceLifecyclePlan` contains the assembled
-Post-ASAP DAG root plus maintenance decisions; it is not an executable plan.
+call per query root. The summary-maintenance lifecycle API named above was later
+removed; Stage 2 materialization (#509) will own maintenance decisions.
 
 ## Later: unified operator IR (operator flattening)
 
@@ -41,7 +41,7 @@ or `Operator::ASAP(ASAPOp)`. Old public names are not kept as aliases.
 | `SummaryExpr::ValueOperation { .. }` over a evaluation | An ordinary `NonASAPOp` (`Project`, `Filter`, `Sort`, `Limit`, `Aggregate`) reading an ASAP node; `FinalizeExactAccumulator`, `MaintainPopulation`, `EvaluatePopulation` are `ASAPOp` variants |
 | `Replacement::Summary(..)` / `Replacement::Rewrite(..)` | `Replacement::SubDAG(Rc<OperatorNode>)`; `is_logical_rewrite` tells them apart |
 | `SummaryFamilyType` | `FieldDataType` (its non-`Plain` variants) |
-| Timing stored on post-ASAP nodes | `OperatorNode::timing`, `None` until `ir::timing::apply_lifecycle_timings` writes it from a `LifecycleAssignment` |
+| Timing stored on post-ASAP nodes | `OperatorNode::timing`, `None` until `ir::timing::apply_materialization_timings` writes it from a `MaterializationAssignment` (default: all query time) |
 | `UnresolvedQueryExpr` + `asap_types::pre_asap::resolve_root` | `UnresolvedOp` / `UnresolvedScalar` + `asap_frontend_common::resolve_root` |
 | `pre_asap::canonicalize`, `pre_asap::cse::share_common_sub_dags` | `ir::canonicalize::canonicalize`, `ir::cse::share_common_sub_dags` |
 | `asap_types::post_asap::compile_post_asap_dag` (wire version 5, `Fallback`/`Binary`/`Value` payloads) | `asap_types::ir::export::compile_post_asap_dag` (wire version 7: one node per operator, `Relational` payloads, `ScalarRef` edges); input must be timed |
diff --git a/docs/user_guide_docs/run-a-query.md b/docs/user_guide_docs/run-a-query.md
index 2f7325cc3..c6f52aa61 100644
--- a/docs/user_guide_docs/run-a-query.md
+++ b/docs/user_guide_docs/run-a-query.md
@@ -6,7 +6,7 @@ corpus coverage. These commands do not deploy or execute a physical plan.
 To develop an application using the Rust library, start with
 [Library API: definitions, options, and examples](../develop_docs/library-api.md).
 That guide explains how to choose strategies and models, rank candidates, and
-work with lifecycle capabilities.
+assemble selected DAGs.
 
 ## Choose a command
 
@@ -96,7 +96,7 @@ cargo run -p asap-devtools --bin show_post_asap_ir -- --data-ingestion-interval-
 available binding from the sketch strategy for each query, numbered in cost-model
 order. If no candidate is available, it prints the pre-ASAP fallback as candidate
 1. It does not show the complete ranked workload candidate set or choose a
-deployment lifecycle. Its SQL examples use a fixed demonstration catalog, not
+deployment. Its SQL examples use a fixed demonstration catalog, not
 your database schema. Use the
 [library workflow](../develop_docs/library-api.md) to retain workload alternatives
 and provide your own models.

From 10ef511cc23ed42cad09d3e056a28908a1ecfac0 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 21:25:31 +0000
Subject: [PATCH 45/48] chore(tools): name OperatorNode in viewer comments

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 tools/dag-viewer/render.py | 4 ++--
 tools/dag-viewer/viewer.js | 2 +-
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/tools/dag-viewer/render.py b/tools/dag-viewer/render.py
index f5ac3ec76..7b16796da 100755
--- a/tools/dag-viewer/render.py
+++ b/tools/dag-viewer/render.py
@@ -17,7 +17,7 @@
 This does not add anything index.html doesn't already do — it shares
 viewer.js and node-style.js with it verbatim (see viewer.js's header
 comment) and only differs in packaging: one query's worth of exported
-`QueryExpr` detail *is* its plan (see the side panel on node click), and
+`OperatorNode` detail *is* its plan (see the side panel on node click), and
 shared-hash highlighting *is* what this repo has for CSE today — both a
 hash-based proxy, not real CSE output; see README.md's "Shared-sub-DAG
 highlighting is a proxy" section. Structured cost/benefit annotations
@@ -72,7 +72,7 @@ def _compact(value: object) -> str:
     if not isinstance(value, dict):
         return str(value)
 
-    # Common serde enum/newtype shapes in QueryExpr detail.
+    # Common serde enum/newtype shapes in OperatorNode detail.
     if set(value) == {"Column"}:
         return f"col[{_compact(value['Column'])}]"
     if set(value) == {"Table"} and isinstance(value["Table"], dict):
diff --git a/tools/dag-viewer/viewer.js b/tools/dag-viewer/viewer.js
index c4cbe5b71..d8191dc1a 100644
--- a/tools/dag-viewer/viewer.js
+++ b/tools/dag-viewer/viewer.js
@@ -18,7 +18,7 @@ cytoscape.use(window.cytoscapeDagre);
 // --post-asap whole-query merged post-ASAP DAG (same flattened
 // `{nodes, root}` shape as `dag`, but nodes may be post-ASAP-only kinds
 // like "SummaryAgg" mixed in, and any such node has no `hash` — there's no
-// corresponding QueryExpr to hash) — left `undefined` when absent (omitted
+// corresponding OperatorNode to hash) — left `undefined` when absent (omitted
 // whenever --post-asap wasn't set, or this query had zero replacements),
 // unlike `replacements` which always defaults to an array. `workload_cost`
 // is the optional per-query `NamedDAG.workload_cost` (issue #286), also

From 2c6a4b1995b977776be141c4fe464210ac239d03 Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 14:50:55 +0000
Subject: [PATCH 46/48] feat(planner): enumerate phase-free local logical
 alternatives

---
 crates/asap-aware-mapping/src/lib.rs          |   3 +
 .../src/logical_candidates.rs                 | 147 +++++++++++
 .../tests/logical_candidates.rs               | 243 ++++++++++++++++++
 docs/develop_docs/local-logical-candidates.md |  39 +++
 4 files changed, 432 insertions(+)
 create mode 100644 crates/asap-aware-mapping/src/logical_candidates.rs
 create mode 100644 crates/asap-aware-mapping/tests/logical_candidates.rs
 create mode 100644 docs/develop_docs/local-logical-candidates.md

diff --git a/crates/asap-aware-mapping/src/lib.rs b/crates/asap-aware-mapping/src/lib.rs
index 443fcaca1..88c5aa954 100644
--- a/crates/asap-aware-mapping/src/lib.rs
+++ b/crates/asap-aware-mapping/src/lib.rs
@@ -211,3 +211,6 @@ pub use rewrite::{AvgToSumOverCountStrategy, SemanticEquivalentRewriteStrategy};
 pub use topk_reuse::TopKLimitReuseStrategy;
 
 pub mod maintained_population;
+
+/// Phase-free local candidate generation over the unified IR.
+pub mod logical_candidates;
diff --git a/crates/asap-aware-mapping/src/logical_candidates.rs b/crates/asap-aware-mapping/src/logical_candidates.rs
new file mode 100644
index 000000000..8c8a28913
--- /dev/null
+++ b/crates/asap-aware-mapping/src/logical_candidates.rs
@@ -0,0 +1,147 @@
+//! Pass 1 local alternatives over the unified logical IR.
+//!
+//! Alternatives are nominal realization descriptors attached to their original
+//! target, not ranked plans or accuracy certificates. Workload composition and
+//! physical planning consume this inventory later; empirical models belong to
+//! selection. The legacy search API remains until planner cutover.
+use std::collections::HashSet;
+use std::rc::Rc;
+
+use asap_types::ir::{NonASAPOp, OperatorNode, QueryRoot, SchemaDerivationError};
+use asap_types::post_asap::{ExactKind, ExactParams, SketchKind};
+use asap_types::pre_asap::AggIntent;
+use asap_types::types::AccuracyTarget;
+use thiserror::Error;
+
+use crate::replacement::{
+    accuracy_budget, accuracy_target, default_size_params, summary_candidates, Realization,
+};
+
+/// All local realizations of one single-measure aggregate. The target retains
+/// source, grouping, filters, input expressions and evaluation context.
+#[derive(Debug, Clone)]
+pub struct LocalLogicalTarget {
+    pub target: Rc<OperatorNode>,
+    pub alternatives: Vec<Realization>,
+}
+
+/// Compact Pass 1 inventory; roots and nested producer dependencies are retained.
+#[derive(Debug, Clone)]
+pub struct LocalLogicalCandidates<Id> {
+    pub roots: Vec<(Id, QueryRoot)>,
+    pub targets: Vec<LocalLogicalTarget>,
+}
+
+#[derive(Debug, Error)]
+pub enum LogicalCandidateError {
+    #[error(transparent)]
+    Structure(#[from] SchemaDerivationError),
+    #[error("logical candidate input already has assigned execution timing")]
+    AssignedTiming,
+    #[error("approximate accuracy requires finite positive epsilon and delta in (0, 1)")]
+    InvalidAccuracy,
+}
+
+/// Enumerate exact and summary choices in stable catalog order, without ranking
+/// or empirical assessment. Parameters are candidate dimensions, not a claim
+/// that a deployment meets the request's accuracy requirement.
+pub fn local_realizations_for_intent(
+    intent: &AggIntent,
+) -> Result<Vec<Realization>, LogicalCandidateError> {
+    let mut choices = vec![Realization::PassThrough];
+    let exact = match intent {
+        AggIntent::Count { .. } => Some((ExactKind::Count, ExactParams::Count)),
+        AggIntent::Sum { .. } => Some((ExactKind::Sum, ExactParams::Sum)),
+        AggIntent::Min { .. } => Some((ExactKind::Min, ExactParams::Min)),
+        AggIntent::Max { .. } => Some((ExactKind::Max, ExactParams::Max)),
+        AggIntent::Rate => Some((ExactKind::Rate, ExactParams::Rate)),
+        AggIntent::IRate => Some((ExactKind::IRate, ExactParams::IRate)),
+        AggIntent::Increase => Some((ExactKind::Increase, ExactParams::Increase)),
+        _ => None,
+    };
+    if let Some((kind, params)) = exact {
+        choices.push(Realization::ExactAggregate { kind, params });
+    }
+    if let Some(target) = accuracy_target(intent) {
+        if *target != AccuracyTarget::Exact {
+            let (epsilon, delta) = accuracy_budget(target);
+            if !epsilon.is_finite()
+                || epsilon <= 0.0
+                || !delta.is_finite()
+                || !(0.0..1.0).contains(&delta)
+                || delta == 0.0
+            {
+                return Err(LogicalCandidateError::InvalidAccuracy);
+            }
+            for algorithm in summary_candidates(intent) {
+                choices.push(Realization::Sketch(SketchKind::new(
+                    algorithm.clone(),
+                    default_size_params(algorithm.clone(), intent, epsilon, delta),
+                )));
+            }
+        }
+    }
+    Ok(choices)
+}
+
+/// Discover single-measure targets, including operator plans read by scalar roots.
+/// Multi-measure aggregates remain intact pending a semantics-preserving split.
+pub fn enumerate_local_logical_candidates<Id>(
+    roots: Vec<(Id, QueryRoot)>,
+) -> Result<LocalLogicalCandidates<Id>, LogicalCandidateError> {
+    let mut seen = HashSet::new();
+    let mut targets = Vec::new();
+    for (_, root) in &roots {
+        root.validate_structure()?;
+        let operators = match root {
+            QueryRoot::Operator(node) => vec![node],
+            QueryRoot::Scalar(expr) => expr.operator_refs(),
+        };
+        for root in operators {
+            for node in OperatorNode::reachable(root) {
+                if !seen.insert(Rc::as_ptr(&node)) {
+                    continue;
+                }
+                if node.timing.is_some() {
+                    return Err(LogicalCandidateError::AssignedTiming);
+                }
+                if let Some(NonASAPOp::Aggregate { measures, .. }) = node.non_asap() {
+                    if let [intent] = measures.as_slice() {
+                        targets.push(LocalLogicalTarget {
+                            alternatives: local_realizations_for_intent(intent)?,
+                            target: node,
+                        });
+                    }
+                }
+            }
+        }
+    }
+    Ok(LocalLogicalCandidates { roots, targets })
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    /// Approximate requests must retain the exact execution alternative too.
+    #[test]
+    fn approximate_count_keeps_exact_and_universal_choices() {
+        let choices = local_realizations_for_intent(&AggIntent::Count {
+            accuracy: AccuracyTarget::EpsilonDelta {
+                epsilon: 0.05,
+                delta: 0.01,
+            },
+        })
+        .unwrap();
+        assert!(choices
+            .iter()
+            .any(|choice| matches!(choice, Realization::PassThrough)));
+        assert!(choices.iter().any(|choice| matches!(
+            choice,
+            Realization::ExactAggregate {
+                kind: ExactKind::Count,
+                ..
+            }
+        )));
+        assert!(choices.iter().any(|choice| matches!(choice, Realization::Sketch(kind) if *kind.algorithm() == asap_types::post_asap::SketchAlgorithm::UnivMon)));
+    }
+}
diff --git a/crates/asap-aware-mapping/tests/logical_candidates.rs b/crates/asap-aware-mapping/tests/logical_candidates.rs
new file mode 100644
index 000000000..a08c0739d
--- /dev/null
+++ b/crates/asap-aware-mapping/tests/logical_candidates.rs
@@ -0,0 +1,243 @@
+//! Frontend-to-Pass-1 acceptance: candidate discovery precedes empirical selection.
+use asap_aware_mapping::{
+    logical_candidates::{
+        enumerate_local_logical_candidates, local_realizations_for_intent, LogicalCandidateError,
+    },
+    Realization,
+};
+use asap_types::{
+    ir::operator_properties::{Reduction, Source},
+    ir::{NonASAPOp, Operator, OperatorNode, QueryRoot, ScalarExpr},
+    post_asap::{ExactKind, SketchAlgorithm},
+    pre_asap::{AggIntent, DataType, Field, Schema},
+    types::AccuracyTarget,
+};
+use std::rc::Rc;
+
+fn approximate() -> AccuracyTarget {
+    AccuracyTarget::EpsilonDelta {
+        epsilon: 0.05,
+        delta: 0.01,
+    }
+}
+fn algorithms(choices: &[Realization]) -> Vec<SketchAlgorithm> {
+    choices
+        .iter()
+        .filter_map(|choice| match choice {
+            Realization::Sketch(kind) => Some(kind.algorithm().clone()),
+            _ => None,
+        })
+        .collect()
+}
+fn aggregate(intent: AggIntent) -> Rc<OperatorNode> {
+    let child = OperatorNode::new_shared(Operator::NonASAP(NonASAPOp::Scan {
+        source: Source::Table {
+            table_ref: "flows".into(),
+        },
+        predicates: vec![],
+        schema: Schema::lifted(vec![Field::plain("src_ip", DataType::Utf8, false)], None),
+    }))
+    .unwrap();
+    OperatorNode::new_shared(Operator::NonASAP(NonASAPOp::Aggregate {
+        child,
+        reduction: Reduction::by(vec![]),
+        measures: vec![intent],
+        output_names: vec![],
+        filters: vec![],
+        having: None,
+    }))
+    .unwrap()
+}
+
+/// Example 2 preserves specialized distinct summaries and the universal alternative.
+#[test]
+fn cardinality_keeps_exact_specialized_and_universal_alternatives() {
+    let choices = local_realizations_for_intent(&AggIntent::Cardinality {
+        cols: vec![0],
+        accuracy: approximate(),
+    })
+    .unwrap();
+    assert!(matches!(choices[0], Realization::PassThrough));
+    assert_eq!(
+        algorithms(&choices),
+        vec![
+            SketchAlgorithm::Hll,
+            SketchAlgorithm::Theta,
+            SketchAlgorithm::Kmv,
+            SketchAlgorithm::UnivMon
+        ]
+    );
+    let tuple = local_realizations_for_intent(&AggIntent::Cardinality {
+        cols: vec![0, 1],
+        accuracy: approximate(),
+    })
+    .unwrap();
+    assert!(!algorithms(&tuple).contains(&SketchAlgorithm::UnivMon));
+}
+
+/// Frequency moments retain exact execution and a universal sketch without certification.
+#[test]
+fn frequency_statistics_keep_universal_choices() {
+    for intent in [
+        AggIntent::FrequencyL2 {
+            col: Some(0),
+            accuracy: approximate(),
+        },
+        AggIntent::FrequencyEntropy {
+            col: Some(0),
+            accuracy: approximate(),
+        },
+    ] {
+        let choices = local_realizations_for_intent(&intent).unwrap();
+        assert!(matches!(choices[0], Realization::PassThrough));
+        assert_eq!(algorithms(&choices), vec![SketchAlgorithm::UnivMon]);
+    }
+}
+
+/// An exact request cannot acquire an approximate sketch merely because one is available.
+#[test]
+fn exact_quantile_stays_exact_and_approximate_keeps_both_families() {
+    let choices = local_realizations_for_intent(&AggIntent::Quantile {
+        col: Some(0),
+        q: 0.99,
+        accuracy: approximate(),
+    })
+    .unwrap();
+    assert_eq!(
+        algorithms(&choices),
+        vec![SketchAlgorithm::Kll, SketchAlgorithm::DDSketch]
+    );
+    let exact = local_realizations_for_intent(&AggIntent::Quantile {
+        col: Some(0),
+        q: 0.99,
+        accuracy: AccuracyTarget::Exact,
+    })
+    .unwrap();
+    assert_eq!(exact, vec![Realization::PassThrough]);
+}
+
+/// Scalar roots expose their producer targets; repeated references retain one target identity.
+#[test]
+fn scalar_root_producers_are_discovered_once() {
+    let producer = aggregate(AggIntent::Cardinality {
+        cols: vec![0],
+        accuracy: approximate(),
+    });
+    let roots = vec![
+        (
+            "scalar",
+            QueryRoot::Scalar(ScalarExpr::ScalarSubquery(producer.clone())),
+        ),
+        ("relation", QueryRoot::Operator(producer.clone())),
+    ];
+    let candidates = enumerate_local_logical_candidates(roots).unwrap();
+    assert_eq!(candidates.roots.len(), 2);
+    for (_, root) in &candidates.roots {
+        asap_types::ir::export::compile_logical_asap_query(root)
+            .unwrap()
+            .validate()
+            .unwrap();
+    }
+    assert_eq!(candidates.targets.len(), 1);
+    assert!(Rc::ptr_eq(&candidates.targets[0].target, &producer));
+    assert!(producer.timing.is_none());
+    assert!(producer.guarantee.is_none());
+    asap_types::ir::export::compile_logical_asap_dag(&producer)
+        .unwrap()
+        .validate()
+        .unwrap();
+}
+
+/// Example 1 rate lowering reaches the exact accumulator choice without a cost model.
+#[test]
+fn promql_lowering_reaches_phase_free_local_candidates() {
+    use asap_types::workload::{
+        AccuracyRequirement, BatchEntry, PlanningWorkload, Query, QueryLanguage, QueryRequirements,
+        QueryWorkload,
+    };
+    let workload = PlanningWorkload {
+        query_workload: QueryWorkload {
+            language: QueryLanguage::PromQL,
+            query_batch: Some(vec![BatchEntry {
+                query: Query("sum by (job) (rate(http_requests_total[1m]))".into()),
+                requirements: QueryRequirements {
+                    accuracy: AccuracyRequirement::Explicit(approximate()),
+                    ..Default::default()
+                },
+                predictability: Default::default(),
+                invocations: 1,
+                execute_at: None,
+                time_selection: Default::default(),
+            }]),
+            repeating_queries: None,
+        },
+        data_workload: Some(asap_types::workload::DataWorkload {
+            data_ingestion_interval: asap_types::workload::Evidence {
+                value: Some(asap_types::workload::DurationMs(1000)),
+                ..Default::default()
+            },
+            ..Default::default()
+        }),
+    };
+    let roots = asap_frontend_promql::unified::lower_promql_query_workload(&workload, 0).unwrap();
+    let candidates =
+        enumerate_local_logical_candidates(roots.into_iter().enumerate().collect()).unwrap();
+    assert!(candidates
+        .targets
+        .iter()
+        .any(|target| target.alternatives.iter().any(|choice| matches!(
+            choice,
+            Realization::ExactAggregate {
+                kind: ExactKind::Rate,
+                ..
+            }
+        ))));
+    assert!(candidates
+        .targets
+        .iter()
+        .all(|target| target.target.timing.is_none()));
+}
+
+/// Physical annotations and invalid probability requirements fail at the stage boundary.
+#[test]
+fn assigned_timing_and_invalid_accuracy_are_rejected() {
+    let mut producer = (*aggregate(AggIntent::Count {
+        accuracy: approximate(),
+    }))
+    .clone();
+    producer.timing = Some(asap_types::post_asap::ExecutionTiming::QueryTime);
+    assert!(matches!(
+        enumerate_local_logical_candidates(vec![(0, QueryRoot::Operator(Rc::new(producer)))]),
+        Err(LogicalCandidateError::AssignedTiming)
+    ));
+    for target in [
+        AccuracyTarget::Epsilon(f64::NAN),
+        AccuracyTarget::EpsilonDelta {
+            epsilon: 0.1,
+            delta: 0.0,
+        },
+    ] {
+        assert!(matches!(
+            local_realizations_for_intent(&AggIntent::Count { accuracy: target }),
+            Err(LogicalCandidateError::InvalidAccuracy)
+        ));
+    }
+}
+
+/// Local TopK keeps both declared heap substrates without choosing an implementation.
+#[test]
+fn topk_keeps_both_specialized_heap_choices() {
+    let choices = local_realizations_for_intent(&AggIntent::TopK {
+        k: 10,
+        accuracy: approximate(),
+    })
+    .unwrap();
+    assert!(matches!(choices[0], Realization::PassThrough));
+    assert_eq!(
+        algorithms(&choices),
+        vec![
+            SketchAlgorithm::CmsWithHeap,
+            SketchAlgorithm::CountSketchWithHeap
+        ]
+    );
+}
diff --git a/docs/develop_docs/local-logical-candidates.md b/docs/develop_docs/local-logical-candidates.md
new file mode 100644
index 000000000..b27e9b2d2
--- /dev/null
+++ b/docs/develop_docs/local-logical-candidates.md
@@ -0,0 +1,39 @@
+# Local logical alternatives (Pass 1)
+
+`asap_aware_mapping::logical_candidates` enumerates local realization choices over
+unified `OperatorNode` and `QueryRoot` inputs. It is the first part of logical
+ASAP optimization in [planner layering](../design_docs/proposals/planner-layering.md).
+
+`enumerate_local_logical_candidates(roots)` returns a `LocalLogicalCandidates`
+inventory containing the original named roots and one `LocalLogicalTarget` per
+reachable single-measure aggregate. Discovery includes operator producers read by
+scalar roots and expressions. Pointer identity prevents repeated discovery of one
+shared producer. Inputs with assigned execution timing are rejected.
+
+Each target retains its original operator, including grouping, filter and input
+context, and has an unranked list of existing `Realization` descriptors:
+
+- Exact execution of the original sub-DAG is always retained as `PassThrough`.
+- Mergeable exact intents also offer their exact accumulator kind and parameters.
+- Approximate-capable intents offer all declared specialized/universal sketch
+  algorithms with nominal dimensions from the built-in sizing contracts.
+- Exact accuracy requests do not acquire approximate alternatives. Distinct-tuple
+  counts do not acquire single-value UnivMon alternatives.
+
+For example, an approximate single-column distinct count offers exact execution,
+HLL, Theta, KMV and UnivMon. These are candidate choices, not assessed accuracy
+certificates. Catalog order is stable and has no cost/preference meaning.
+
+The API accepts no empirical cost or accuracy model, runtime capabilities, storage
+policy or materialization assignment. It does not rank, select, construct runtime
+state or claim physical feasibility. Pass 2 must compose and structurally validate
+replacement sub-DAGs and retain independent/shared alternatives before physical
+planning and complete workload selection. The descriptors are not executable
+plans, and callers must not execute the first choice as a selection policy.
+
+Multi-measure aggregates remain intact in the roots until an explicit semantic
+split is supported. Opaque deployment extensions retain exact execution here;
+additional local alternatives require an explicit logical rule rather than a cost
+model making a generation decision. The legacy ranked search remains available
+for the existing pipeline until its later cutover; this module supplies the new
+logical-only entry point without changing production selection prematurely.

From 849e483c9e5466a3d83287c87858b33f94b78ada Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 19:47:09 +0000
Subject: [PATCH 47/48] docs(planner): say local candidates have no execution
 timing assigned

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/asap-aware-mapping/src/lib.rs                  | 3 ++-
 crates/asap-aware-mapping/tests/logical_candidates.rs | 2 +-
 2 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/crates/asap-aware-mapping/src/lib.rs b/crates/asap-aware-mapping/src/lib.rs
index 88c5aa954..f9bf69101 100644
--- a/crates/asap-aware-mapping/src/lib.rs
+++ b/crates/asap-aware-mapping/src/lib.rs
@@ -212,5 +212,6 @@ pub use topk_reuse::TopKLimitReuseStrategy;
 
 pub mod maintained_population;
 
-/// Phase-free local candidate generation over the unified IR.
+/// Local candidate generation over the unified IR. No execution timing is
+/// assigned: that is a Stage 2 materialization decision.
 pub mod logical_candidates;
diff --git a/crates/asap-aware-mapping/tests/logical_candidates.rs b/crates/asap-aware-mapping/tests/logical_candidates.rs
index a08c0739d..d25a4cfdb 100644
--- a/crates/asap-aware-mapping/tests/logical_candidates.rs
+++ b/crates/asap-aware-mapping/tests/logical_candidates.rs
@@ -150,7 +150,7 @@ fn scalar_root_producers_are_discovered_once() {
 
 /// Example 1 rate lowering reaches the exact accumulator choice without a cost model.
 #[test]
-fn promql_lowering_reaches_phase_free_local_candidates() {
+fn promql_lowering_reaches_local_candidates_without_execution_timing() {
     use asap_types::workload::{
         AccuracyRequirement, BatchEntry, PlanningWorkload, Query, QueryLanguage, QueryRequirements,
         QueryWorkload,

From 488c6ebda2d11263c4d99748a5e97925ec3d3c0a Mon Sep 17 00:00:00 2001
From: zzylol <50204836+zzylol@users.noreply.github.com>
Date: Sat, 3 Oct 2026 21:40:48 +0000
Subject: [PATCH 48/48] test(planner): call the promoted PromQL workload
 lowering

The PromQL frontend's unified module was promoted to the crate root later
in the stack; asap_frontend_promql::unified no longer exists.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 crates/asap-aware-mapping/tests/logical_candidates.rs | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/crates/asap-aware-mapping/tests/logical_candidates.rs b/crates/asap-aware-mapping/tests/logical_candidates.rs
index d25a4cfdb..20211ce69 100644
--- a/crates/asap-aware-mapping/tests/logical_candidates.rs
+++ b/crates/asap-aware-mapping/tests/logical_candidates.rs
@@ -179,7 +179,7 @@ fn promql_lowering_reaches_local_candidates_without_execution_timing() {
             ..Default::default()
         }),
     };
-    let roots = asap_frontend_promql::unified::lower_promql_query_workload(&workload, 0).unwrap();
+    let roots = asap_frontend_promql::lower_promql_query_workload(&workload, 0).unwrap();
     let candidates =
         enumerate_local_logical_candidates(roots.into_iter().enumerate().collect()).unwrap();
     assert!(candidates