From 3a23cc67e1c9ad89045242ba18ddc354141d4336 Mon Sep 17 00:00:00 2001 From: Navneet Verma Date: Fri, 22 Sep 2023 14:31:36 -0700 Subject: [PATCH] =?UTF-8?q?Updating=20the=20K-NN=20Filters=20documentation?= =?UTF-8?q?=20due=20to=20recent=20enhancements=20in=E2=80=A6=20(#4987)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * Updating the K-NN Filters documentation due to recent enhancements in Efficient Filters Signed-off-by: Navneet Verma * Fixed the review comments. Signed-off-by: Navneet Verma * Apply suggestions from code review Co-authored-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com> Signed-off-by: Navneet Verma * Apply suggestions from code review Co-authored-by: Nathan Bower Signed-off-by: Navneet Verma * Update settings.md Signed-off-by: Navneet Verma * Update _search-plugins/knn/settings.md Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com> --------- Signed-off-by: Navneet Verma Signed-off-by: Navneet Verma 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 --- _search-plugins/knn/filter-search-knn.md | 23 +++++++++++++---------- _search-plugins/knn/settings.md | 5 +++-- images/faiss-algorithm.jpg | Bin 26341 -> 55486 bytes 3 files changed, 16 insertions(+), 12 deletions(-) diff --git a/_search-plugins/knn/filter-search-knn.md b/_search-plugins/knn/filter-search-knn.md index 7e926a970e..8e349f1b59 100644 --- a/_search-plugins/knn/filter-search-knn.md +++ b/_search-plugins/knn/filter-search-knn.md @@ -13,7 +13,7 @@ To refine k-NN results, you can filter a k-NN search using one of the following - [Efficient k-NN filtering](#efficient-k-nn-filtering): 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 (if there are at least `k` results in total). This approach is supported by the following engines: - Lucene engine with a Hierarchical Navigable Small World (HNSW) algorithm (k-NN plugin versions 2.4 and later) - - Faiss engine with an HNSW algorithm (k-NN plugin versions 2.9 or later) + - Faiss engine with an HNSW algorithm (k-NN plugin versions 2.9 and later) or IVF algorithm (k-NN plugin versions 2.10 and later) - [Post-filtering](#post-filtering): Because it is performed after the k-NN search, this approach may return significantly fewer than `k` results for a restrictive filter. You can use the following two filtering strategies for this approach: - [Boolean post-filter](#boolean-filter-with-ann-search): This approach runs an [approximate nearest neighbor (ANN)]({{site.url}}{{site.baseurl}}/search-plugins/knn/approximate-knn/) search and then applies a filter to the results. The two query parts are executed independently, and then the results are combined based on the query operator (`should`, `must`, and so on) provided in the query. @@ -25,7 +25,7 @@ The following table summarizes the preceding filtering use cases. Filter | When the filter is applied | Type of search | Supported engines and methods | Where to place the `filter` clause :--- | :--- | :--- | :--- -Efficient k-NN filtering | During search (a hybrid of pre- and post-filtering) | Approximate | - `lucene` (`hnsw`)
- `faiss` (`hnsw`) | Inside the k-NN query clause. +Efficient k-NN filtering | During search (a hybrid of pre- and post-filtering) | Approximate | - `lucene` (`hnsw`)
- `faiss` (`hnsw`, `ivf`) | Inside the k-NN query clause. Boolean filter | After search (post-filtering) | Approximate | - `lucene`
- `nmslib`
- `faiss` | Outside the k-NN query clause. Must be a leaf clause. The `post_filter` parameter | After search (post-filtering) | Approximate | - `lucene`
- `nmslib`
- `faiss` | Outside the k-NN query clause. Scoring script filter | Before search (pre-filtering) | Exact | N/A | Inside the script score query clause. @@ -42,12 +42,12 @@ Once you've estimated the number of documents in your index, the restrictiveness | Number of documents in an index | Percentage of documents the filter returns | k | Filtering method to use for higher recall | Filtering method to use for lower latency | | :-- | :-- | :-- | :-- | :-- | -| 10M | 2.5 | 100 | Scoring script | Scoring script | -| 10M | 38 | 100 | Efficient k-NN filtering | Boolean filter | -| 10M | 80 | 100 | Scoring script | Efficient k-NN filtering | -| 1M | 2.5 | 100 | Efficient k-NN filtering | Scoring script | -| 1M | 38 | 100 | Efficient k-NN filtering | Efficient k-NN filtering/scoring script | -| 1M | 80 | 100 | Efficient k-NN filtering | Boolean filter | +| 10M | 2.5 | 100 | Efficient k-NN filtering/Scoring script | Scoring script | +| 10M | 38 | 100 | Efficient k-NN filtering | Efficient k-NN filtering | +| 10M | 80 | 100 | Efficient k-NN filtering | Efficient k-NN filtering | +| 1M | 2.5 | 100 | Efficient k-NN filtering/Scoring script | Scoring script | +| 1M | 38 | 100 | Efficient k-NN filtering | Efficient k-NN filtering | +| 1M | 80 | 100 | Efficient k-NN filtering | Efficient k-NN filtering | ## Efficient k-NN filtering @@ -261,13 +261,16 @@ For more ways to construct a filter, see [Constructing a filter](#constructing-a ### Faiss k-NN filter implementation -Starting with k-NN plugin version 2.9, you can use `faiss` filters for k-NN searches. +For k-NN searches, you can use `faiss` filters with an HNSW algorithm (k-NN plugin versions 2.9 and later) or IVF algorithm (k-NN plugin versions 2.10 and later). When you specify a Faiss filter for a k-NN search, the Faiss algorithm decides whether to perform an exact k-NN search with pre-filtering or an approximate search with modified post-filtering. The algorithm uses the following variables: - N: The number of documents in the index. - P: The number of documents in the document subset after the filter is applied (P <= N). - k: The maximum number of vectors to return in the response. +- R: The number of results returned after performing the filtered approximate nearest neighbor search. +- FT (filtered threshold): An index-level threshold defined in the [`knn.advanced.filtered_exact_search_threshold` setting]({{site.url}}{{site.baseurl}}/search-plugins/knn/settings/) that specifies to switch to exact search. +- MDC (max distance computations): The maximum number of distance computations allowed in exact search if `FT` (filtered threshold) is not set. This value cannot be changed. The following flow chart outlines the Faiss algorithm. @@ -699,4 +702,4 @@ POST /hotels-index/_search } } ``` -{% include copy-curl.html %} \ No newline at end of file +{% include copy-curl.html %} diff --git a/_search-plugins/knn/settings.md b/_search-plugins/knn/settings.md index e96780ecf9..79266400c8 100644 --- a/_search-plugins/knn/settings.md +++ b/_search-plugins/knn/settings.md @@ -21,5 +21,6 @@ Setting | Default | Description `knn.memory.circuit_breaker.limit` | 50% | The native memory limit for native library indexes. At the default value, if a machine has 100 GB of memory and the JVM uses 32 GB, the k-NN plugin uses 50% of the remaining 68 GB (34 GB). If memory usage exceeds this value, k-NN removes the least recently used native library indexes. `knn.memory.circuit_breaker.enabled` | true | Whether to enable the k-NN memory circuit breaker. `knn.plugin.enabled`| true | Enables or disables the k-NN plugin. -`knn.model.index.number_of_shards`| 1 | Number of shards to use for the model system index, the OpenSearch index that stores the models used for Approximate k-NN Search. -`knn.model.index.number_of_replicas`| 1 | Number of replica shards to use for the model system index. Generally, in a multi-node cluster, this should be at least 1 to increase stability. +`knn.model.index.number_of_shards`| 1 | The number of shards to use for the model system index, the OpenSearch index that stores the models used for Approximate Nearest Neighbor (ANN) search. +`knn.model.index.number_of_replicas`| 1 | The number of replica shards to use for the model system index. Generally, in a multi-node cluster, this should be at least 1 to increase stability. +`knn.advanced.filtered_exact_search_threshold`| null | The threshold value for the filtered IDs that is used to switch to exact search during filtered ANN search. 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