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RootDemand gained latency_ms in #604; the Example 2 coverage test's demand sets it to None (no latency bound). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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#604 gave RootDemand a latency_ms and a logical candidate several physical candidates. The Hydra count test sets no latency bound and checks the all-query-time physical candidate, which comes first. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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…ummary - Eligibility (S4): a SummaryAgg may run at ingestion time when the data is continuously ingesting or mixed, every root reaching it repeats and is predictable, and it is a tumbling pane or reads one fixed window per evaluation (FixedIntervalAt, window no longer than the interval). The panes of one merge are one unit. - Stage 2 enumerates the down-closed sets of units (all query time first), each built with a workload-wide split_shared_by_phase that copies a node shared by an ingestion-time and a query-time consumer per phase and re-keys the assignment. Above 16 sets it searches greedily by Stage 3's cost and flags the selection as not guaranteed optimal. - Stage 3 takes the cheapest valid physical candidate of each logical one, in the DP and in enumeration. Ingestion-time panes are one pane built as rows arrive: the newest pane pays the build and retains N + 1 panes; the older panes and their inputs cost nothing. - Latency check (S6): a query whose query-time work per evaluation exceeds its latency_ms is rejected with the estimate and the bound (Stage3Calibration::latency_ms_per_cost_unit, 1 CPU-ms per ms). - RootDemand carries latency_ms. Example 1: 112 physical candidates (24 maintain Q2's sum panes), same selection P82 at 4.620; maintained panes cost 47.4 (42.0 memory); 40 candidates over Q2's 100 ms bound. Example 3B: P2 KLL still selected at 2.083; tumbling panes at query time miss the 200 ms bound, maintained ones cost 768.6 (768.0 memory). The executor runs Example 3B's maintained plan per pane and returns the whole-window rows. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
… 2 materialization Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW
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…th its reason A Stage 2 error no longer fails the whole candidate set: stage_pipeline lists that candidate under stage2_physical_asap.pruned and plans the rest. Full materialization enumeration is left to #604. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW
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…th its reason A Stage 2 error no longer fails the whole candidate set: stage_pipeline lists that candidate under stage2_physical_asap.pruned and plans the rest. Full materialization enumeration is left to #604. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW
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…th its reason A Stage 2 error no longer fails the whole candidate set: stage_pipeline lists that candidate under stage2_physical_asap.pruned and plans the rest. Full materialization enumeration is left to #604. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW
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The specs and tests from #590 run the current stages through the shared planner_layering_common pipeline (Pass 1 and composition, optimize_physical_asap, select_plan); tests are named after the stages. Materialization is read from the physical DAG (#667); window forms and retention stay pending adapters. Behavior that works passes (29 tests); every expectation that needs a feature not in this stack is ignored with the PR that delivers it (29 tests): Pass 2 sharing (#588, #595, #596), window composition (#601, #628, #634), materialization enumeration and MatAtQuery (#604, #625), UnivMon sizing and accuracy (#621), SQL recognition and COUNT(*) composition (#598, #603) and plan selection row estimates (#632). Each spec's "Today" column states the current output. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW
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…r candidate logical ASAP DAGs (#576) * feat(planner): #509 Stage 2 physical candidates and Stage 3 plan selection (MVP) Stage 2 implements one logical candidate physically: exact Aggregate{[TopK]} becomes Limit(Sort) per group, summaries stay build -> estimate, every node runs at query time, and the timed roots export as one PhysicalASAPDAG. Stage 3 is the only stage that computes cost. It rejects candidates whose summary misses its query's accuracy target (accuracy model, analytical guarantee) or uses Count-Min over weights not proven non-negative, prices every valid candidate node by node with analytical_cost (illustrative statistics), selects the cheapest and reports the rest as costlier. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * feat(devtools): stage_pipeline emits all four stages for Example 1 Add stage2_physical_asap (no cost) and stage3_selection (costs, selected, every other candidate rejected as invalid or costlier) per the v2 contract. PromQL rows carry the series identity from Stage 0, as runtime state needs. Regenerate tools/dag-viewer/examples/planner-layering-example1.json. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * refactor(planner): read Operator<NodeId> payloads in Stage 2/3 after the export removal Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * fix(planner): Stage 2/3 on #575's composed candidates, query roots and #667 materialization Stage 2 takes query roots, scalar ones included (#542), times every sub-DAG with Materialization::NotMaterialized (#667) and keeps the guarantee Stage 1 composed on every node it implements; a MaintainPopulation is no longer rejected, since it now runs at query time when not materialized. Stage 3 accepts a query's output when its root guarantee meets the target, or when the deployment's accuracy model shows this candidate's output does (AccuracyModel::output_guarantee, none by default). A certified estimate inside the plan is not enough: a difference of two quantile estimates stays listed as invalid, with a reason, under the built-in models. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * test(devtools): regenerate the four-stage Example 1 fixture on the new #575 Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * docs(planner): name Stage 2/3 by the planner-layering stage terms Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * fix(devtools): prune a logical candidate Stage 2 cannot implement, with its reason A Stage 2 error no longer fails the whole candidate set: stage_pipeline lists that candidate under stage2_physical_asap.pruned and plans the rest. Full materialization enumeration is left to #604. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * fix(planner): read empirical output accuracy from deployment evidence in Stage 3 The output-level hook moves from AccuracyModel to AccuracyEvidenceProvider: AccuracyModel stays theoretical, Stage 1 composes root guarantees with the built-in model, and deployment evidence enters only in Stage 3. A scalar root that is exactly scalar(v) inherits v's guarantee; any other scalar expression over an approximate operand has none until #669. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * refactor(planner): name Stage 2/3 code and pipeline keys after the stage names physical_candidates -> physical_asap_optimization (stage2_physical -> optimize_physical_asap, Stage2Error -> PhysicalASAPOptimizationError), stage3_select -> select_plan, and the stage_pipeline keys stage2_physical_asap -> physical_asap_optimization and stage3_selection -> plan_selection. The fixture is regenerated. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * test(planner): plan selection tests after Top-K estimates lost their bound #575 gives Top-K and signed Count-Min estimates guarantee None, so the CountSketch+heap candidate of the top-k fixture no longer carries an analytical guarantee: plan selection rejects it for missing evidence rather than for missing the target. The "misses target" case now uses a quantile summary planned at a looser target, and the per-node cost test admits the CountSketch+heap candidate through deployment evidence. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * fix(planner): exact top-k sorts by the ranked measure in physical optimization Rank a one-measure grouped child by its measure (the SQL heavy-hitter and PromQL `topk(k, sum by ..)` shapes) and per-series rows by the sample value, instead of looking up a `value` column. A node reading the top-k gets a Project restoring the logical [keys.., topk_k] columns over the rows. An Aggregate{[TopK]} with other measures, a filter or HAVING now fails, so its candidate is pruned with the reason. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * fix(devtools): stage_pipeline emits plan_selection when selection fails With no valid candidate the document lists the rejections with a null `selected` (and the Stage 2 pruned list as before); any other selection error is reported under `error`, instead of failing the run. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * docs(planner): plan selection checks Count-Min only under a target; note MVP costing limits Reword the Count-Min test to the decided behavior and test that a query without a target admits the Count-Min candidate. Document that a cost error aborts selection (only from bad declared rates) and that binary, join and concat nodes are priced from their first input only. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * fix(planner): exact top-k ranks by the measure of a composed Stage 1 child After Pass 1 composition a top-k reads its one-measure aggregate as Project(FinalizeExactAccumulator(SummaryAgg)) or Project(SummaryEstimate(..)), not as an Aggregate, so ranking fell back to the sample value: a key named `value` was sorted on, and an integer or multi-column key pruned the candidate. Look through renaming Projects, Filters, finalize and estimate to the SummaryAgg or Aggregate; a grouped one ranks by its last column. The SQL test now composes every Pass 1 choice under exact and approximate targets. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * fix(planner): exact top-k roots output the logical [keys.., topk_k] columns An exact top-k root returned its child's raw rows (Example 1's P1 leaked `ts`, `value` and `$promql_series_identity`), while summary candidates and the frontend give `[keys.., topk_k]`. The restoring Project now sits over the Limit at a root too, so one implementation serves roots and consumers. `topk_k` carries the ranked value's type and nullability, not the frontend's Utf8 placeholder. Regenerate the Example 1 fixture: P1 gains the root Project (node 12). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * fix(planner): charge a NotMaterialized shared node once per consuming query Plan selection prices each node once per computation: a materialized node once, a NotMaterialized node once per query (or materialized node) that reaches it, not counting through a materialized ancestor. Per-node costs carry the multiplier. Also list the per-entity case among the exact top-k shapes Stage 2 cannot rewrite. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * docs(planner): nodes below a materialized node are charged once for it Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW --------- Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
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The specs and tests from #590 run the current stages through the shared planner_layering_common pipeline (Pass 1 and composition, optimize_physical_asap, select_plan); tests are named after the stages. Materialization is read from the physical DAG (#667); window forms and retention stay pending adapters. Behavior that works passes (29 tests); every expectation that needs a feature not in this stack is ignored with the PR that delivers it (29 tests): Pass 2 sharing (#588, #595, #596), window composition (#601, #628, #634), materialization enumeration and MatAtQuery (#604, #625), UnivMon sizing and accuracy (#621), SQL recognition and COUNT(*) composition (#598, #603) and plan selection row estimates (#632). Each spec's "Today" column states the current output. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW
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…stages (#577) * test: acceptance spec and pending tests for planner-layering Example 1 Define MVP acceptance for #509 Example 1 before the Phase C stage APIs exist: 1 -> 6 -> 6 -> 1 candidates (Pass 1 x identical-expression sharing; physical operator implementation only, no materialization). - Spec with per-stage candidate tables, invariants and doc ambiguities. - Integration tests against todo!() stage stubs, ignored until the stages land; workload and Stage 0 frontend-shape tests run now. - Expected-only asap-stage-pipeline/v1 fixture for the DAG viewer. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * test: run the Example 1 acceptance tests against the real stages Replace the todo!() stubs with adapters over Stage 0-3, un-ignore the 11 tests that pass, and give each still-ignored test the precise difference between the implementation and the spec. Add runtime capability checks: the selected plan compiles in the physical planner; compiling every candidate stays ignored with the two runtime gaps it finds. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * test: read Example 1 logical stages as flat DAGs after the export removal Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * test: Example 1 acceptance on the composed stages (1 -> 3 -> 3 -> 1) The tests run Pass 1 and composition, optimize_physical_asap and select_plan through a shared tests/planner_layering_common pipeline, and follow the decided behavior: three Pass 1 candidates (Q2 exact, CMS+heap, CountSketch+heap), every sub-DAG NotMaterialized, P1 selected, CMS+heap invalid (weights not proven non-negative) and CountSketch+heap invalid (a Top-K output has no guarantee and no deployment evidence). Hydra (#605), Pass 2 sharing (#588) and the two runtime gaps (#593, #579) stay ignored with the PR that delivers them. Tests are named after the stages; the compile check no longer uses the PromQL fallback. The spec lists where the doc and the planner differ. The expected-only viewer fixture is removed: the generated four-stage fixture replaces it. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * test: port #590's Example 2-4 acceptance specs and tests The specs and tests from #590 run the current stages through the shared planner_layering_common pipeline (Pass 1 and composition, optimize_physical_asap, select_plan); tests are named after the stages. Materialization is read from the physical DAG (#667); window forms and retention stay pending adapters. Behavior that works passes (29 tests); every expectation that needs a feature not in this stack is ignored with the PR that delivers it (29 tests): Pass 2 sharing (#588, #595, #596), window composition (#601, #628, #634), materialization enumeration and MatAtQuery (#604, #625), UnivMon sizing and accuracy (#621), SQL recognition and COUNT(*) composition (#598, #603) and plan selection row estimates (#632). Each spec's "Today" column states the current output. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * feat(devtools): stage_pipeline examples for #509 Example 3 Ported from #590: --example planner-layering-3a (Pattern A, ad hoc batch of five p99 reports) and planner-layering-3b (Pattern B, repeating 5-min p99), the Example 3 acceptance tests' workloads. Example 1's output is unchanged. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * test: follow #576's per-consumer charging and exact top-k columns Plan selection charges a NotMaterialized node once per consuming query, so the charging helper checks NodeCost.multiplier and the Example 4 A3 ambiguity is recorded as decided. Example 1 checks that exact Q2 sorts by the ranked value and returns [job, topk_10]. The stage viewer guide's tab 1 row now describes the actual all-exact result. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * refactor(devtools): one planning pipeline for stage_pipeline and the acceptance tests run_planning_stages and the #509 example workloads move into the asap-devtools library; stage_pipeline serializes the run and the planner-layering tests adapt it. The shared data workload drops ingestion_rate for data at rest, which validate() requires. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * fix(devtools): select over every candidate; --max-displayed limits only the document stage_pipeline capped enumeration at 64, so Example 3a (243 candidates) selected P41 instead of the cheapest P122 (KLL for all five queries). The pipeline now enumerates, optimizes and prices every candidate; the document shows the first --max-displayed (default 64) plus the selected one, with `combinations` and `capped`. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * docs: Example 2's SQL candidates compose; the SQL test waits only on #598 Running the ignored SQL test composes every candidate and fails only on Q2's options (per-source counts until #598), so #603 is not a blocker. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * test: name stages by number and name; say query-language frontends The frontends' Run field, id and locals become stage0_query_language_frontends, and test names carry stage0..stage3 with the stage name. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * test: charging helper follows plan selection's per-consumer rule With a materialized node the helper accepted any multiplier >= 1. It now computes each node's computations as plan selection does (walks from query roots and materialized nodes' inputs, stopping at materialized nodes), checked on a hand-built candidate with a materialized node. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * test: Example 1 picks Q2 candidates by (option, no shared input) physical_with and the invalid-candidate check no longer assume one candidate per Q2 option, so #588's shared-input variants need no change. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * docs: Example 3 Pattern B charges each node once per consuming query Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * docs(stage-viewer): rows 2, 3a and 3b describe the planner's current output Read from uncapped runs: Example 2's sketch plans are rejected for having no (ε, δ) guarantee, 3a selects P122 (first of 108 tied cheapest plans, nothing shared yet) and 3b selects query-time KLL; panes and the latency check come with the window-summary PRs. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * docs(stage-viewer): row 2 from the SQL run; 3a ties 32 plans, not 108 Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * test: Example 1 counts only unshared candidates; stage3_ charging-helper names The 3-logical and 3-physical counts now hold when #588 adds shared-input variants. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * refactor(devtools): PlanningStagesRun fields carry stage number and name Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * test(devtools): unique temp file per stage_pipeline run cargo test runs the tests as threads of one process, so two runs of the same example shared a file name and one deleted the other's output. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW --------- Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
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…e MajorPass (#674) * feat(planner): run the planning stages as the planner pipeline; retire MajorPass plan_stages runs logical ASAP-aware optimization (Pass 1 and composition of every combination, capped), physical ASAP-aware optimization and plan selection over the frontends' roots, and returns every stage's output. StagePipeline runs it behind OptimizationPass and is the facade default; the stage_pipeline devtool uses it (its fixture is unchanged). The combination count saturates instead of overflowing. summary_sharing: sharing tests are ignored until Pass 2 (#580); the UnivMon legacy-search test is deleted; scalar and combined-quantile tests run on plan_stages. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * test(planner): logical and physical ASAP-aware optimization import no cost model From #582: only plan selection prices plans, so the Pass 1 / composition and physical ASAP-aware optimization modules may not import cost_model, recurrence, analytical_cost, physical_operator_statistics or plan_selection (paths or re-exported names) outside tests. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * fix(planner): compose a per-series avg over rows that carry the series identity The per-series sum keeps the input's labels, so with $promql_series_identity after the sample value its last column is the identity, and composition rejected the only exact option ("non-Float64 per-series avg"). The planner pipeline then had no candidate for avg_over_time. Read the summed value by its role instead. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * test(executor): take plans and candidates from the planner pipeline From #629/#633: executor tests take the plan plan_stages selects (selected_dag) or its composed logical candidates (logical_candidates) instead of the legacy search and global selection. - deployment_computation, precompute_candidates, the candidates.rs fixture: ported. - planspace_series_identity_heap: keeps the selection check; the four tests of the legacy whole-root proposals are deleted. - weighted_topk_binding: ported to Pass 1 heap candidates (Count Sketch only over rates: no sign proof). The tests of legacy-only candidate generation are deleted. Ignored, with reasons: the grouped weighted binding (whole-expression heap, #589) and the two rate-heap executions (top-k output schema, #672). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * test(frontend-promql): take plans and candidates from the planner pipeline From #629/#633, on support helpers over plan_stages (plan_stages, selected_dag, logical_candidates, logical_plan): - count_planning: exact counts select a Count accumulator; count updates are read from the composed Count-Min / Count Sketch candidates. The Hydra test is ported and ignored: Pass 1 offers no Hydra for a grouped count yet (#605). - univmon_candidates: the synthetic accuracy model is gone; UnivMon candidates come from Pass 1 (the shared count at an approximate target), the uncalibrated ones carry no guarantee and plan selection does not select them. - promql_corpus, metrics_observability: totality over Pass 1 and composition (logical_plan) instead of the legacy strategies; the metrics corpus reports composition errors under METRICS_OBSERVABILITY_REPORT. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * test(frontend-sql): take corr's exact plan from the planner pipeline From #633: the plan plan_stages selects replaces retain_exact. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * test(planner): the batch SUM example reads one exact accumulator per query Under the planner pipeline each query's SUM is replaced by its exact accumulator state; sharing identical producers is Pass 2 (#580). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * refactor(planner): stage identifiers carry number and name; enumerate every candidate User decisions (2026-10-13): - stage modules stage2_physical_asap_optimization and stage3_plan_selection; tests stage1_logical_asap_optimization.rs and stage2_physical_asap_optimization_sql.rs; stage_pipeline keys stage0_query_language_frontends, stage1_logical_asap_optimization, stage2_physical_asap_optimization, stage3_plan_selection (fixture regenerated: only the keys change); - enumeration and selection are never capped: plan_stages enumerates every combination; the devtool's --max-displayed (was --max-candidates) caps only the listing; - code docs say "query-language frontends". Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * test(integration): take plans and candidates from the planner pipeline From #629/#633, on asap_integration_tests::planning (plan_stages, selected_dag, logical_candidates): - sql_to_physical, operator_sharing, materialization_e2e, precompute_raw_samples, summary_coverage_e2e, promql_numeric_regressions: ported. - cse.rs: deleted; it pinned the legacy search's memo groups (sharing identical sub-DAGs is Pass 2, #580). - Ignored, with reasons: the UNION ALL summary test (plan selection picks the exact plan until materialization, #604), arithmetic over one selector (#580), the unit-weight heap over raw samples (#589). - precompute_raw_samples no longer requires a Count Sketch heap over raw samples (#589); materialization_e2e takes the quantile's sketch candidate, since plan selection picks the exact plan. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * refactor(devtools): sketch_coverage reports Pass 1's summary candidates From #633: per lowered query, the summary candidates Pass 1 offers, instead of the legacy explain_replacements. The CSE-shareable metric is dropped (sharing is Pass 2). Over every corpus at epsilon 0.01 and a 1 s ingestion interval: 145/2183 lowered queries get a summary candidate, and Pass 1 rejects none. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * test(frontend-promql): the Kubernetes mixin aggregates over topk compose (ignored, #672) Both corpus queries that do not compose aggregate over a topk output, which the frontend declares as [keys.., topk_k] with a Utf8 placeholder and no value column; the outer sum's accumulator has no value to read. They compose once the top-k output carries the ranked value (#672). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW * refactor(devtools): run_planning_stages runs the library's plan_stages One pipeline implementation: the devtool's run_planning_stages (#577) validates the frontends' roots and every composed candidate, and otherwise is plan_stages with the built-in models. Its candidate types are the library's. The Example 1 fixture is unchanged. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W7qG9aFyPij5uWsyAJCxDW --------- Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
This was referenced Oct 13, 2026
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Stack: Wave 2 chain: #599 → #601 → #600 → #604 → #606 → #603 → #605
Rebased on main d4869a7 (DF 54).
Stacked on #600. Part of #580, step 5; #509 Stage 2 "Materialization". Implements decisions S1–S6 and Q44 (pricing #594, panes #601).
Why
Stage 2 ran every summary at query time, so Stage 3 never compared maintaining state at ingestion time with rebuilding it at each evaluation. Example 4's B1 (tumbling KLLs at ingestion time) was not generated. Query latency bounds were not checked.
What
Eligibility (S4). A
SummaryAggmay run at ingestion time when all of these hold:DataWorkload.arrivalisContinuouslyIngestingorMixed.Unknowncounts as not ingesting.Predictable.FixedIntervalAt, with a window no longer than the interval.A summary over a merge of panes reads a sliding window, so it stays at query time. The panes of one merge form one unit.
Down-closed sets. Stage 2 returns one physical candidate per set of units in which everything below an ingestion-time unit is also at ingestion time. The all-query-time candidate comes first. Ids are
P<n>for all query time andP<n>-m<k>otherwise; labels end in "· ingestion time: Kll ×5 panes". Above 16 sets, Stage 2 adds units greedily by Stage 3's cost and flags the selection as not guaranteed optimal.Cross-root phase split.
split_shared_by_phase(&[roots], assignment)copies a node per phase when one consumer reads it at ingestion time and another at query time, across queries. It returns the assignment re-keyed to the copies.Selection. The tree DP's
evaluate, enumeration andfinishtake the cheapest valid physical candidate of each logical candidate. DP-versus-exhaustive tests run with materialization on.Pricing panes. At ingestion time, a pane chain is one pane, built as rows arrive and kept. The newest pane pays the λ-rate build and the memory of
lookback/width + 1panes (S3: in memory only). Older panes, and the shifts and ranges that feed only them, cost 0.Latency check (S6). A candidate is rejected when a query's query-time work for one evaluation is above its
latency_ms. The work counts every query-time node the query reaches, shared nodes included. NewStage3Calibration::latency_ms_per_cost_unit= 1 (one CPU-ms on one core). Example reason:q1: query-time work takes 310.0 ms per evaluation, over the 200 ms latency bound.RootDemandnow carrieslatency_ms.Docs.
stage3-cost-model.mdcovers pane retention, the latency check and the calibration field, and updates Example 1's worked example.Before / After (built-in models, constants untuned)
sum_over_timepanesIngestion time does not win any example under the built-in models. With 1M series, memory for retained per-series state is much larger than the CPU it saves. In a unit test with 10 series at 100k rows/s, maintained panes win, and the DP selects them too.
Tests
timing.rs: a cross-root split keeps the assignment, and a node reached at one timing stays shared.materialization.rs: panes go to ingestion time and the merge stays at query time. Arrival, ad hoc and one-off rules. A whole window needs a phase and must not overlap. Sets are down-closed: an exact sum plus a CMS gives 3 sets, and over panes only the panes count. Greedy above the cap.plan-selection: the newest pane pays the build plus (N+1)× memory, and the older panes pay 0. The latency bound rejects slow candidates with a reason. Maintained panes win with few series, and the DP agrees with exhaustive selection.runtime_b_maintained_panes_match_the_whole_windowcompiles the B1 candidate once. It cuts the candidate atfrontier_from_timingwithcut_candidate, runs the precompute once per pane in that pane'sScope::Ingestionwindow, then runs the query over the 5 kept panes. It returns the whole-window rows (p99 19 and 119). Example 1's selected plan has nothing eligible, so there is no end-to-end case for it.Gate:
cargo fmt --all --check,cargo clippy --workspace --all-targets --all-features -- -D warnings,cargo test --workspace: 1,630 passed / 12 ignored (#600: 1,619 / 12). Viewer: 29 OK (6 skipped).Not in this PR
Links: #509, #580, #594 (Stage 3 cost), #601 (panes), #600.
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