[python] Execute hybrid search routes concurrently

[TheR1sing3un]

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.
• Tests verify concurrent execution, stable route order, the single-route fast path, the worker cap, and cleanup before exception propagation.
• Flake8 and git diff --check passed.

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.

Routes	Serial	Concurrent	Speedup
2 x 20 ms	47.238 ms	24.278 ms	1.95x
10 ms + 40 ms	55.602 ms	44.120 ms	1.26x
4 x 20 ms	93.787 ms	24.859 ms	3.77x
5/10/20/40 ms	85.271 ms	44.742 ms	1.91x

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.