kaivalnp commented on PR #13202: URL: https://github.com/apache/lucene/pull/13202#issuecomment-2024899453
> What was the dimension count & dataset for your performance testing It was the enwiki dataset (https://home.apache.org/~sokolov/enwiki-20120502-lines-1k-100d.vec), unit vectors, 100 dimensions, indexed first 1M vectors, searched next 10K vectors, with `DOT_PRODUCT` similarity function > Looking at the benchmarking, we are adding a 5% overhead to all vector operations when using float32 This overhead is only when a timeout is set but not met, there is no regression when it is not set at all (in the benchmarked case without any filter). IMO this additional check can be useful to time out unexpectedly expensive queries in a production system to keep overall CPU within limits, but looking forward to more opinions here.. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@lucene.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@lucene.apache.org For additional commands, e-mail: issues-h...@lucene.apache.org
