Exact

Exact Union RegExp

Benjamin Trent caec612fea Make cosine similarity faster by storing magnitude and normalizing vectors (#99445) ... `cosine` is our default similarity and should provide a good experience on speed. `dot_product` is faster than `cosine` as it doesn't require calculating vector magnitudes in the similarity comparison loop. Instead, it can assume vectors have a length of `1` and use an optimized `dot_product` calculation. However, `cosine` as it exists today accepts vectors of any magnitude and cannot take advantage of this. This commit addresses this by: - Normalizing all vectors passed when indexing via `cosine` - Storing the calculated magnitude in an additional field (only if its `!= 1`). - Using the `dot_product` Lucene calculation - Normalizing query vectors when used against these new `cosine` fields - De-normalizing vectors when accessed via scripts - Allowing scripts to access these stored magnitudes.		2023-12-01 13:45:43 -05:00
..
src/test	Make cosine similarity faster by storing magnitude and normalizing vectors (#99445)	2023-12-01 13:45:43 -05:00
build.gradle	Remove unnecessary test logging (#101710)	2023-11-03 10:04:57 +01:00