[Vector Upsert 5/5] Add FULL-upsert vector integration coverage - #19301
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[Vector Upsert 5/5] Add FULL-upsert vector integration coverage#19301xiangfu0 wants to merge 5 commits into
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This was referenced Aug 19, 2026
Codecov Report❌ Patch coverage is Additional details and impacted files@@ Coverage Diff @@
## master #19301 +/- ##
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+ Coverage 67.12% 67.19% +0.06%
Complexity 1424 1424
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Files 3462 3463 +1
Lines 220677 220783 +106
Branches 35255 35287 +32
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+ Hits 148136 148355 +219
+ Misses 60708 60586 -122
- Partials 11833 11842 +9
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…r scan Extract a shared computeExactMatches helper that unifies the exact top-K and threshold scan paths and can restrict scoring to an allowed-document bitmap. Introduce VectorCandidateScope, an immutable set of document IDs a vector predicate is allowed to consider as candidates. Vector top-K is not monotonic, so unlike an ordinary predicate -- which is correct to intersect with the result afterwards -- a document set that defines what the query may see has to be applied before candidate generation. The type carries that contract and says nothing about where the restriction came from; callers decide that. ExactVectorScanFilterOperator accepts one via a new constructor overload, and no production caller passes one yet. Also let the operator record its own exact-scan search and fallback metrics, which were previously invisible to VectorSearchMetrics, and report the applied candidate-filter cardinality in explain output. Add filtered-reader coverage for HnswVectorIndexReader.
… param cleanup Only record a vector search metric when a search actually executed, and guarantee backend search parameters are cleared even when configuration fails partway or the explain-context refresh throws. Previously a failure inside configureBackendParams still recorded a search that never ran, and an exception from refreshExplainContext could skip clearBackendParams entirely.
…ata filters FilterPlanNode treated any non-leaf AND sibling as a metadata filter when wiring pre-filter bitmaps for filter-aware ANN. A nested subtree containing a VECTOR_SIMILARITY predicate (e.g. AND(vector, AND(vector2, metadata)) or AND(vector, NOT(vector2))) was eagerly materialized into a bitmap, executing top-K candidate generation out of its boolean context and pushing its results into the sibling vector search as a pre-filter. Track the retained child FilterContexts alongside their operators so wirePreFilterForVectorOperators can pair them, and only treat subtrees with no vector predicate as metadata. Adaptive pre-filter selection for plain metadata siblings is unchanged.
…tor candidate generation FilterPlanNode constructed and executed VECTOR_SIMILARITY before adding SegmentContext.getDocIdsSnapshot() as an outer AND. Obsolete physical versions of upserted rows could therefore occupy per-segment ANN top-K slots and be removed only afterward, producing fewer than K rows or omitting nearer current rows. Pass the snapshot to vector predicates as a required VectorCandidateScope so it constrains candidate generation, while retaining the outer bitmap AND as defense in depth. FilterPlanNode remains the only place that knows the scope comes from the segment's queryable-document snapshot; the operators only see 'documents this predicate may consider'. Choose the execution path at plan time, where both the reader capability and forward index availability are known: - a filter-aware reader receives the scope and does filtered ANN; - a reader that cannot restrict its search is bypassed for ExactVectorScanFilterOperator over the allowed documents, which reports it through fallbackReason; - an empty scope needs no candidate generation and no reader capability at all, so it short-circuits to an empty operator; - when neither path is available the query fails clearly. Because the choice is made once, VectorSimilarityFilterOperator no longer needs a runtime exact-scan branch, and it captures the reader capability once instead of re-reading it per execution, so a plan built on one answer can never execute against another. Required scopes stay separate from optimizer-selected metadata filters and are intersected with them before candidate generation. Non-upsert queries keep the adaptive metadata behavior, and non-vector plans do not copy the snapshot.
Add VectorUpsertTableTest on CustomDataQueryClusterIntegrationTest: six physical records collapse to four current records under FULL upsert, and vector top-K queries must return exactly K current entities with scalar-distance equivalence. Covers a single consuming segment and sealed-plus-consuming segments, both query engines, two replicas, and a skipUpsert=true control proving obsolete rows are physically nearest. The explain assertions also pin the planned execution path per segment type: consuming segments use the exact scan operator because the mutable vector index cannot restrict its search, while sealed segments use filtered ANN.
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Part 5/5 of the split of #19287 (Fix FULL-upsert vector candidate generation).
Stacked on #19300.
Summary
Add
VectorUpsertTableTestonCustomDataQueryClusterIntegrationTest: six physicalrecords collapse to four current records under FULL upsert, and vector top-K queries
must return exactly K current entities with scalar-distance equivalence.
Covers a single consuming segment and sealed-plus-consuming segments, both query
engines, two replicas, and a
skipUpsert=truecontrol proving the obsolete rows arephysically nearest.
The explain assertions also pin the planned execution path per segment type: consuming
segments use the exact scan operator because the mutable vector index cannot restrict
its search, while sealed segments use filtered ANN.
Validation
(0 of K rows returned), confirming it is a genuine regression test.
Stack