add missing pages (#123774)

docs/reference/elasticsearch/mapping-reference/rank-vectors.md

@@ -0,0 +1,192 @@
+---
+navigation_title: "Rank Vectors"
+mapped_pages:
+  - https://www.elastic.co/guide/en/elasticsearch/reference/master/rank-vectors.html
+---
+
+# Rank Vectors [rank-vectors]
+
+
+::::{warning}
+This functionality is in technical preview and may be changed or removed in a future release. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features.
+::::
+
+
+The `rank_vectors` field type enables late-interaction dense vector scoring in Elasticsearch. The number of vectors per field can vary, but they must all share the same number of dimensions and element type.
+
+The purpose of vectors stored in this field is second order ranking documents with max-sim similarity.
+
+Here is a simple example of using this field with `float` elements.
+
+```console
+PUT my-rank-vectors-float
+{
+  "mappings": {
+    "properties": {
+      "my_vector": {
+        "type": "rank_vectors"
+      }
+    }
+  }
+}
+
+PUT my-rank-vectors-float/_doc/1
+{
+  "my_vector" : [[0.5, 10, 6], [-0.5, 10, 10]]
+}
+```
+
+In addition to the `float` element type, `byte` and `bit` element types are also supported.
+
+Here is an example of using this field with `byte` elements.
+
+```console
+PUT my-rank-vectors-byte
+{
+  "mappings": {
+    "properties": {
+      "my_vector": {
+        "type": "rank_vectors",
+        "element_type": "byte"
+      }
+    }
+  }
+}
+
+PUT my-rank-vectors-byte/_doc/1
+{
+  "my_vector" : [[1, 2, 3], [4, 5, 6]]
+}
+```
+
+Here is an example of using this field with `bit` elements.
+
+```console
+PUT my-rank-vectors-bit
+{
+  "mappings": {
+    "properties": {
+      "my_vector": {
+        "type": "rank_vectors",
+        "element_type": "bit"
+      }
+    }
+  }
+}
+
+POST /my-rank-vectors-bit/_bulk?refresh
+{"index": {"_id" : "1"}}
+{"my_vector": [127, -127, 0, 1, 42]}
+{"index": {"_id" : "2"}}
+{"my_vector": "8100012a7f"}
+```
+
+## Parameters for rank vectors fields [rank-vectors-params]
+
+The `rank_vectors` field type supports the following parameters:
+
+$$$rank-vectors-element-type$$$
+
+`element_type`
+:   (Optional, string) The data type used to encode vectors. The supported data types are `float` (default), `byte`, and bit.
+
+::::{dropdown} Valid values for `element_type`
+`float`
+:   indexes a 4-byte floating-point value per dimension. This is the default value.
+
+`byte`
+:   indexes a 1-byte integer value per dimension.
+
+`bit`
+:   indexes a single bit per dimension. Useful for very high-dimensional vectors or models that specifically support bit vectors. NOTE: when using `bit`, the number of dimensions must be a multiple of 8 and must represent the number of bits.
+
+::::
+
+
+`dims`
+:   (Optional, integer) Number of vector dimensions. Can’t exceed `4096`. If `dims` is not specified, it will be set to the length of the first vector added to the field.
+
+
+## Synthetic `_source` [rank-vectors-synthetic-source]
+
+::::{important}
+Synthetic `_source` is Generally Available only for TSDB indices (indices that have `index.mode` set to `time_series`). For other indices synthetic `_source` is in technical preview. Features in technical preview may be changed or removed in a future release. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features.
+::::
+
+
+`rank_vectors` fields support [synthetic `_source`](mapping-source-field.md#synthetic-source) .
+
+
+## Scoring with rank vectors [rank-vectors-scoring]
+
+Rank vectors can be accessed and used in [`script_score` queries](/reference/query-languages/query-dsl-script-score-query.md).
+
+For example, the following query scores documents based on the maxSim similarity between the query vector and the vectors stored in the `my_vector` field:
+
+```console
+GET my-rank-vectors-float/_search
+{
+  "query": {
+    "script_score": {
+      "query": {
+        "match_all": {}
+      },
+      "script": {
+        "source": "maxSimDotProduct(params.query_vector, 'my_vector')",
+        "params": {
+          "query_vector": [[0.5, 10, 6], [-0.5, 10, 10]]
+        }
+      }
+    }
+  }
+}
+```
+
+Additionally, asymmetric similarity functions can be used to score against `bit` vectors. For example, the following query scores documents based on the maxSimDotProduct similarity between a floating point query vector and bit vectors stored in the `my_vector` field:
+
+```console
+PUT my-rank-vectors-bit
+{
+  "mappings": {
+    "properties": {
+      "my_vector": {
+        "type": "rank_vectors",
+        "element_type": "bit"
+      }
+    }
+  }
+}
+
+POST /my-rank-vectors-bit/_bulk?refresh
+{"index": {"_id" : "1"}}
+{"my_vector": [127, -127, 0, 1, 42]}
+{"index": {"_id" : "2"}}
+{"my_vector": "8100012a7f"}
+
+GET my-rank-vectors-bit/_search
+{
+  "query": {
+    "script_score": {
+      "query": {
+        "match_all": {}
+      },
+      "script": {
+        "source": "maxSimDotProduct(params.query_vector, 'my_vector')",
+        "params": {
+          "query_vector": [
+            [0.35, 0.77, 0.95, 0.15, 0.11, 0.08, 0.58, 0.06, 0.44, 0.52, 0.21,
+       0.62, 0.65, 0.16, 0.64, 0.39, 0.93, 0.06, 0.93, 0.31, 0.92, 0.0,
+       0.66, 0.86, 0.92, 0.03, 0.81, 0.31, 0.2 , 0.92, 0.95, 0.64, 0.19,
+       0.26, 0.77, 0.64, 0.78, 0.32, 0.97, 0.84]
+           ] <1>
+        }
+      }
+    }
+  }
+}
+```
+
+1. Note that the query vector has 40 elements, matching the number of bits in the bit vectors.
+
+
+

docs/reference/toc.yml

@@ -140,6 +140,7 @@ toc:
           - file: elasticsearch/mapping-reference/range.md
           - file: elasticsearch/mapping-reference/rank-feature.md
           - file: elasticsearch/mapping-reference/rank-features.md
+          - file: elasticsearch/mapping-reference/rank-vectors.md
           - file: elasticsearch/mapping-reference/search-as-you-type.md
           - file: elasticsearch/mapping-reference/semantic-text.md
           - file: elasticsearch/mapping-reference/shape.md

docs/release-notes/index.md

@@ -3,24 +3,26 @@ navigation_title: "Elasticsearch"
 mapped_pages:
   - https://www.elastic.co/guide/en/elasticsearch/reference/current/es-connectors-release-notes.html
   - https://www.elastic.co/guide/en/elasticsearch/reference/current/es-release-notes.html
+  - https://www.elastic.co/guide/en/elasticsearch/reference/master/release-notes-9.0.0.html
+  - https://www.elastic.co/guide/en/elasticsearch/reference/master/migrating-9.0.html
 ---
 
 # Elasticsearch release notes [elasticsearch-release-notes]
 
-Review the changes, fixes, and more in each version of Elasticsearch. 
+Review the changes, fixes, and more in each version of Elasticsearch.
 
 To check for security updates, go to [Security announcements for the Elastic stack](https://discuss.elastic.co/c/announcements/security-announcements/31).
 
-% Release notes include only features, enhancements, and fixes. Add breaking changes, deprecations, and known issues to the applicable release notes sections. 
+% Release notes include only features, enhancements, and fixes. Add breaking changes, deprecations, and known issues to the applicable release notes sections.
 
 % ## version.next [felasticsearch-next-release-notes]
 % **Release date:** Month day, year
 
 % ### Features and enhancements [elasticsearch-next-features-enhancements]
-% * 
+% *
 
 % ### Fixes [elasticsearch-next-fixes]
-% * 
+% *
 
 ## 9.0.0 [elasticsearch-900-release-notes]
 **Release date:** March 25, 2025