[Docs] kNN vector rescoring for quantized vectors#118425
[Docs] kNN vector rescoring for quantized vectors#118425carlosdelest merged 26 commits intoelastic:mainfrom
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…ased DoubleValueSource
…r of results from each shard
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The following example doesn't use rescore_vector, instead it utilizes the top-level rescore.
I am not sure we need to specifically call out ALL the ways that you can rescore. There are 3 ways now (rescore_vector, script score, and "rescore" at the top level). All have their uses, but our docs should be "normal user" prescriptive. Let's focus on rescore_vector as that is the easiest for oversampling and rescoring vectors.
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I think we should keep the existing ways of rescoring until we make rescore_vector GA.
We can group the other ways under a "other ways of doing rescoring" kind of section, but I think it's worth keeping them until rescore_vector is out of tech preview.
WDYT?
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I suppose calling these out is ok, we just need to be perfectly clear what each one means and when to use each one.
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I've set rescore_vector as the way to do it, and an additional section for the other methods, along with when you should use them, in ff7f906.
LMKWYT!
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| [discrete] | ||
| [[dense-vector-knn-search-reranking-script-score]] | ||
| ===== Use a `script_score` query to rescore per shard | ||
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| You can rescore per shard with the <<query-dsl-knn-query, knn query>> and <<query-dsl-script-score-query, script_score query >>. | ||
| Generally, this means that there will be more rescoring per shard, but this can increase overall recall at the cost of compute. |
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let's not bother calling out script_score. I say remove this section and focus on "rescore_vector"
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let's focus on rescore_vector and remove the other sections.
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| include::{es-ref-dir}/rest-api/common-parms.asciidoc[tag=knn-similarity] | ||
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| include::{es-ref-dir}/rest-api/common-parms.asciidoc[tag=knn-rescore-vector] |
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we also need to put it in search-api-knn in search.asciidoc
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Thanks Carlos, nice addition!
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@benwtrent this is ready for review, it includes the latest changes for vector rescoring in #119835 |
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5 participants
Follow up to #116663.
Adds docs for vector rescoring.
Search your data / knn search section:
knn query / knn retriever parameters section: