shimpeko opened a new issue, #15658:
URL: https://github.com/apache/lucene/issues/15658
### Description
I observed a performance regression after upgrading Elasticsearch 8.19.8
(Lucene 9.12.3) to Elasticsearch 9.2.4 (Lucene 10.32). The slowdown appears for
a query shape that uses dis_max + constant_score. I didn’t find any ES‑level
changes that explain the regression, so I suspect Lucene.
__Query shape__
- dis_max (tie=0)
- boost 25 * constant_score( OR of term queries on field1 + field2,
minShouldMatch=1 )
- boost 10 * constant_score( OR of term queries on field3,
minShouldMatch=1 )
__Reproducer__
I created small standalone Lucene benchmark that reproduce performance
regression: https://github.com/shimpeko/lucene-dismax-constantscore-benchmark
__Benchmark result (Java 25.0.2, 5k docs, warmup 200, iters 1000)__
- 9.12.3 -> 0.424 ms/iter
- 10.0.0 -> 0.439 ms/iter
- 10.1.0 -> 1.167 ms/iter
- 10.2.0 -> 1.312 ms/iter
- 10.2.1 -> 1.335 ms/iter
- 10.2.2 -> 1.345 ms/iter
- 10.3.0 -> 1.377 ms/iter
- 10.3.1 -> 1.335 ms/iter
- 10.3.2 -> 1.302 ms/iter
The regression starts at 10.1.0 and persists in later 10.x. There is also
miner regression on 10.2.0
### Version and environment details
__Environment__
- OS: macOS 26.2 (Build 25C56), Darwin 25.2.0
- CPU: Apple M1 Max (10 cores: 8 performance + 2 efficiency)
- RAM: 64 GB
- Java: 25.0.2 (OpenJDK)
- Lucene directory: ByteBuffersDirectory
- Analyzer: WhitespaceAnalyzer
- Index: 5,000 docs, single segment (forceMerge(1))
- Searcher: single‑threaded (no executor)
__Notes__
- In ES tests, similar query without constant_score or without dis_max did
not show notable regress.
Let me know if you’d like additional data or a different reproduction setup.
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