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[Fix] add documentation regarding usage of filter/post_filter in k-NN… (#4494) 

* [Fix] add documentation regarding usage of filter/post_filter in k-NN plugin

Signed-off-by: jiapinw <jiapinw@amazon.com>

* Revise doc update based on comments and offline discussions

Signed-off-by: jiapinw <jiapinw@amazon.com>

* Update doc based on comments

Signed-off-by: jiapinw <jiapinw@amazon.com>

* Update _search-plugins/knn/filter-search-knn.md

Co-authored-by: Nathan Bower <nbower@amazon.com>
Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com>

---------

Signed-off-by: jiapinw <jiapinw@amazon.com>
Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com>
Co-authored-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com>
Co-authored-by: Nathan Bower <nbower@amazon.com>
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@ -17,6 +17,7 @@ To refine k-NN results, you can filter a k-NN search using one of the following
- [Lucene k-NN filter](#using-a-lucene-k-nn-filter): This approach applies filtering _during_ the k-NN search, as opposed to before or after the k-NN search, which ensures that `k` results are returned. You can only use this method with the Hierarchical Navigable Small World (HNSW) algorithm implemented by the Lucene search engine in k-NN plugin versions 2.4 and later. - [Lucene k-NN filter](#using-a-lucene-k-nn-filter): This approach applies filtering _during_ the k-NN search, as opposed to before or after the k-NN search, which ensures that `k` results are returned. You can only use this method with the Hierarchical Navigable Small World (HNSW) algorithm implemented by the Lucene search engine in k-NN plugin versions 2.4 and later.
## Filtered search optimization ## Filtered search optimization
Depending on your dataset and use case, you might be more interested in maximizing recall or minimizing latency. The following table provides guidance on various k-NN search configurations and the filtering methods used to optimize for higher recall or lower latency. The first three columns of the table provide several example k-NN search configurations. A search configuration consists of: Depending on your dataset and use case, you might be more interested in maximizing recall or minimizing latency. The following table provides guidance on various k-NN search configurations and the filtering methods used to optimize for higher recall or lower latency. The first three columns of the table provide several example k-NN search configurations. A search configuration consists of:
@ -197,6 +198,8 @@ The response includes documents containing the matching hotels:
} }
``` ```
The location of the `filter` clause matters when it's used with a k-NN query clause. If the `filter` clause is outside the k-NN query clause, it must be a leaf clause. In this case, the filter is applied after the k-NN search and works exactly like the `post_filter` keyword. If the `filter` clause is within the k-NN query clause, it works as a hybrid of pre- and post-filtering (this option is only supported for the Lucene search engine).
## Lucene k-NN filter implementation ## Lucene k-NN filter implementation
k-NN plugin version 2.2 introduced support for running k-NN searches with the Lucene engine using HNSW graphs. Starting with version 2.4, which is based on Lucene version 9.4, you can use Lucene filters for k-NN searches. k-NN plugin version 2.2 introduced support for running k-NN searches with the Lucene engine using HNSW graphs. Starting with version 2.4, which is based on Lucene version 9.4, you can use Lucene filters for k-NN searches.