Add query planner Phase 2: logical planning and cost estimation #19244
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Introduces LogicalPlanBuilder to convert QueryBuilder to QueryPlanNode tree with multi-dimensional cost tracking (lucene_docs, cpu, memory, io). Adds CostEstimator leveraging Lucene's scorer costs across index leaves with OpenSearch-specific heuristics. Implements volatile cost caching with double-checked locking for thread safety. Supports Boolean, Term, Range, and Match queries with QueryBuilder context preservation. Includes feature flag (opensearch.experimental.feature.query_planner.enabled) for gradual rollout and QueryPlannerIntegration helper for search pipeline integration. Bounded must_not penalty prevents cost explosion on large document sets. Signed-off-by: Atri Sharma <[email protected]>
Signed-off-by: Atri Sharma <[email protected]>
Signed-off-by: Atri Sharma <[email protected]>
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@andrross @rishabhmaurya Please review |
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❌ Gradle check result for 75e057f: FAILURE Please examine the workflow log, locate, and copy-paste the failure(s) below, then iterate to green. Is the failure a flaky test unrelated to your change? |
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❌ Gradle check result for 75e057f: FAILURE Please examine the workflow log, locate, and copy-paste the failure(s) below, then iterate to green. Is the failure a flaky test unrelated to your change? |
This was referenced Sep 8, 2025
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This PR is stalled because it has been open for 30 days with no activity. |
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Following up on Phase 1 (PR #19060), this adds the cost estimation
infrastructure needed for query optimization (RFC #18906).
What this does:
Builds a tree of QueryPlanNode objects from QueryBuilder
Estimates query costs by summing Lucene scorer costs across all segments
Tracks CPU/memory/IO costs alongside document counts
Preserves field names and query metadata (lost when converting to Lucene)
The main insight is using Lucene's existing scorer.cost() aggregated
properly across index leaves, then adding our own heuristics for
things Lucene doesn't track.
Notable implementation details:
BooleanPlanNode caps must_not penalties so costs don't explode
Percentage minimumShouldMatch now works (e.g. "50%")
Feature flagged: -Dopensearch.experimental.feature.query_planner.enabled
No user-visible changes yet - this is just the foundation for Phase 3
where we'll actually optimize queries based on these costs.
Signed-off-by: Atri Sharma [email protected]
By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.
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