Speed up tail computation in MemorySegmentES91OSQVectorsScorer #132001
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john-wagster
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szybia
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…-tracking * upstream/main: (26 commits) Add release notes for v9.1.0 release (elastic#131953) Unmute multi_node generative tests (elastic#132021) Avoid re-enqueueing merge tasks (elastic#132020) Fix file entitlements for shared data dir (elastic#131748) ES|QL brute force l2_norm vector function (elastic#132025) Make ES|QL SAMPLE not a pipeline breaker (elastic#132014) Speed up tail computation in MemorySegmentES91OSQVectorsScorer (elastic#132001) Remove deprecated usages in `TransportPutFollowAction` (elastic#132038) Simulate impact of shard movement using shard-level write load (elastic#131406) Remove RemoteClusterService.getConnections() method (elastic#131948) Fix off by one in ValuesBytesRefAggregator (elastic#132032) Use unicode strings in data generation by default (elastic#132028) Adding index.refresh_interval as a data stream setting (elastic#131482) [ES|QL] Add more Min/MaxOverTime CSV tests (elastic#131070) Restrict remote ENRICH after FORK (elastic#131945) Fix decoding of non-ascii field names in ignored source (elastic#132018) [docs] Use centrally maintained version variables (elastic#131939) Configurable Inference timeout during Query time (elastic#131551) ESQL: Allow pruning columns added by InlineJoin (elastic#131204) ESQL: Fail `profile` on text response formats (elastic#128627) ...
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I added more dimensions to be run on OSQScorerBenchmark and I notice that for 782 dimensions the speed was slower than expected:
The reason is that for that number of dimensions, the scalr part is quite big and it is slowing down everything. Add ing the same strategy as in the scalar implementation (ES91OSQVectorsScorer), provides a good speed up for that number of dimensions while the other ones remain practically the same: