[python] Execute hybrid search routes concurrently - #9797
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JingsongLi merged 1 commit intoSep 15, 2026
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Requirement fit: SUPPORTED. Implementation: CLEAN.
Reviewed fadd12d277a9. Independent vector and full-text routes have separate builders and can overlap their local I/O/search work before ranking. The bounded four-worker path preserves route-order conversion and RRF/weighted/MRR ranking, and waits for started work to finish cleanup when a route fails.
Validation: all 10 execution/ranker tests and 3 subtests passed, including ordering, worker limits and exception cleanup. Current head CI is green. The scheduling benchmark uses simulated route latency; actual native-query gains were not reproduced here.
No actionable implementation regression found in this review.
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Purpose
Hybrid search executes independent vector and full-text routes sequentially before ranking their results. Execute multiple routes concurrently with a bounded four-worker pool, then convert results in route order so RRF, weighted-score, and MRR ranking semantics remain unchanged.
Empty and single-route searches keep the direct path. On failure, pending work is cancelled, started routes are allowed to clean up, and the original route exception is propagated.
Tests
python -m pytest -q pypaimon/tests/hybrid_search_execution_test.py pypaimon/tests/hybrid_search_ranker_test.py: 10 passed.git diff --checkpassed.Benchmark
macOS arm64, Python 3.9.6. Each route uses a simulated I/O delay; values are medians of 12 runs. This isolates route scheduling from index implementation and ranking cost.
Results remained in route order in every run. Real query gains depend on route latency distribution and nested native-index parallelism. The temporary benchmark driver is not included in the change.