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docs/changelog/137331.yaml

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pr: 137331
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summary: Add ES93BloomFilterStoredFieldsFormat for efficient field existence checks
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area: TSDB
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type: enhancement
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issues: []

docs/reference/elasticsearch/mapping-reference/semantic-text.md

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@@ -25,9 +25,12 @@ type make it simpler to perform semantic search on your data. The
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with [match](/reference/query-languages/query-dsl/query-dsl-match-query.md), [sparse_vector](/reference/query-languages/query-dsl/query-dsl-sparse-vector-query.md)
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or [knn](/reference/query-languages/query-dsl/query-dsl-knn-query.md) queries.
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If you don’t specify an inference endpoint, the `inference_id` field defaults to
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`.elser-2-elasticsearch`, a preconfigured endpoint for the elasticsearch
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service.
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{applies_to}`serverless: ga` If you don’t specify an {{infer}} endpoint, the `inference_id` field defaults to
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`.elser-v2-elastic`, a preconfigured endpoint for the `elasticsearch` service.
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This endpoint uses the [Elastic {{infer-cap}} Service (EIS)](docs-content://explore-analyze/elastic-inference/eis.md#elser-on-eis).
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{applies_to}`stack: ga 9.0` If you don’t specify an {{infer}} endpoint, the `inference_id` field defaults to
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`.elser-2-elasticsearch`, a preconfigured endpoint for the `elasticsearch` service.
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Using `semantic_text`, you won’t need to specify how to generate embeddings for
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your data, or how to index it. The {{infer}} endpoint automatically determines
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are ideal for most use cases or create custom endpoints and reference them in
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the field mappings.
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### Using the default ELSER endpoint
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:::::::{tab-set}
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::::::{tab-item} Using the default ELSER on EIS endpoint on Serverless
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```{applies_to}
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serverless: ga
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```
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If you use the preconfigured `.elser-2-elasticsearch` endpoint, you can set up
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`semantic_text` with the following API request:
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If you use the default `.elser-v2-elastic` endpoint that runs on EIS, you can set up `semantic_text` with the following API request:
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```console
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PUT my-index-000001
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```
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% TEST[skip:Requires inference endpoint]
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::::::
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::::::{tab-item} Using the preconfigured ELSER on EIS endpoint in Cloud
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```{applies_to}
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stack: ga 9.2
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deployment:
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self: unavailable
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```
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If you use the preconfigured `.elser-v2-elastic` endpoint that runs on EIS, you can set up `semantic_text` with the following API request:
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```console
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PUT my-index-000001
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{
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"mappings": {
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"properties": {
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"inference_field": {
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"type": "semantic_text",
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"inference_id": ".elser-v2-elastic"
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}
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}
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}
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}
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```
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::::::
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::::::{tab-item} Using the default ELSER endpoint
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If you use the preconfigured `.elser-2-elasticsearch` endpoint, you can set up `semantic_text` with the following API request:
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```console
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PUT my-index-000001
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{
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"mappings": {
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"properties": {
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"inference_field": {
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"type": "semantic_text"
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}
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}
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}
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}
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```
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::::::
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:::::::
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### Using a custom endpoint
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To use a custom {{infer}} endpoint instead of the default
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`.elser-2-elasticsearch`, you
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To use a custom {{infer}} endpoint instead of the default, you
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must [Create {{infer}} API](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-inference-put)
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and specify its `inference_id` when setting up the `semantic_text` field type.
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% TEST[skip:Requires inference endpoint]
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### Using ELSER on EIS
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```{applies_to}
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stack: preview 9.1
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serverless: preview
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stack: preview 9.1 ga 9.2
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deployment:
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self: unavailable
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serverless: ga
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```
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If you use the preconfigured `.elser-2-elastic` endpoint that utilizes the ELSER model as a service through the Elastic Inference Service ([ELSER on EIS](docs-content://explore-analyze/elastic-inference/eis.md#elser-on-eis)), you can
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set up `semantic_text` with the following API request:
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:::::::{tab-set}
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::::::{tab-item} Using ELSER on EIS on Serverless
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```{applies_to}
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serverless: ga
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```
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```console
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PUT my-index-000001
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{
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"mappings": {
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"properties": {
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"inference_field": {
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"type": "semantic_text"
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}
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}
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}
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}
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```
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::::::
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::::::{tab-item} Using ELSER on EIS in Cloud
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```{applies_to}
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stack: ga 9.2
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deployment:
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self: unavailable
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```
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```console
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PUT my-index-000001
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{
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```
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% TEST[skip:Requires inference endpoint]
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::::{note}
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While we do encourage experimentation, we do not recommend implementing production use cases on top of this feature while it is in Technical Preview.
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::::::
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::::
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:::::::
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## Parameters for `semantic_text` fields [semantic-text-params]
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docs/reference/query-languages/esql/_snippets/commands/layout/fork.md

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The `FORK` processing command creates multiple execution branches to operate
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on the same input data and combines the results in a single output table. A discriminator column (`_fork`) is added to identify which branch each row came from.
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Together with the [`FUSE`](/reference/query-languages/esql/commands/fuse.md) command, `FORK` enables hybrid search to combine and score results from multiple queries. To learn more about using {{esql}} for search, refer to [ES|QL for search](docs-content://solutions/search/esql-for-search.md).
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**Branch identification:**
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- The `_fork` column identifies each branch with values like `fork1`, `fork2`, `fork3`
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- Values correspond to the order branches are defined

muted-tests.yml

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- class: org.elasticsearch.xpack.security.CoreWithSecurityClientYamlTestSuiteIT
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method: test {yaml=indices.validate_query/20_query_string/validate_query with query_string parameters}
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issue: https://github.com/elastic/elasticsearch/issues/137391
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- class: org.elasticsearch.xpack.downsample.ILMDownsampleDisruptionIT
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method: testILMDownsampleRollingRestart
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issue: https://github.com/elastic/elasticsearch/issues/137489
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- class: org.elasticsearch.smoketest.SmokeTestIngestWithAllDepsClientYamlTestSuiteIT
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method: test {yaml=ingest/100_sampling_with_reroute/Test get sample with multiple reroutes}
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issue: https://github.com/elastic/elasticsearch/issues/137457
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- class: org.elasticsearch.xpack.esql.qa.single_node.PushQueriesIT
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method: testEqualityAndOther {SEMANTIC_TEXT_WITH_KEYWORD}
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issue: https://github.com/elastic/elasticsearch/issues/137491
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- class: org.elasticsearch.index.mapper.vectors.DenseVectorFieldMapperTests
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method: testUpdates
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issue: https://github.com/elastic/elasticsearch/issues/137512
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# Examples:
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#

server/src/main/java/org/elasticsearch/cluster/ClusterModule.java

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StreamsMetadata::fromXContent
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)
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);
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entries.add(
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new NamedXContentRegistry.Entry(
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Metadata.ProjectCustom.class,
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new ParseField(RegisteredPolicySnapshots.TYPE),
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RegisteredPolicySnapshots::parse
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)
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);
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return entries;
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}
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