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Add missing default ML query descriptions (#2917)
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output/openapi/elasticsearch-openapi.json

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output/openapi/elasticsearch-serverless-openapi.json

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output/schema/schema.json

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specification/_types/query_dsl/abstractions.ts

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@@ -100,6 +100,7 @@ import { TextExpansionQuery } from './TextExpansionQuery'
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import { WeightedTokensQuery } from './WeightedTokensQuery'
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/**
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* An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
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* @variants container
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* @non_exhaustive
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* @ext_doc_id query-dsl

specification/ml/put_data_frame_analytics/MlPutDataFrameAnalyticsRequest.ts

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@@ -31,6 +31,11 @@ import { integer } from '@_types/Numeric'
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* Create a data frame analytics job.
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* This API creates a data frame analytics job that performs an analysis on the
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* source indices and stores the outcome in a destination index.
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* By default, the query used in the source configuration is `{"match_all": {}}`.
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*
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* If the destination index does not exist, it is created automatically when you start the job.
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*
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* If you supply only a subset of the regression or classification parameters, hyperparameter optimization occurs. It determines a value for each of the undefined parameters.
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* @rest_spec_name ml.put_data_frame_analytics
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* @availability stack since=7.3.0 stability=stable
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* @availability serverless stability=stable visibility=public

specification/ml/put_datafeed/MlPutDatafeedRequest.ts

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@@ -39,7 +39,9 @@ import { Duration } from '@_types/Time'
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* Datafeeds retrieve data from Elasticsearch for analysis by an anomaly detection job.
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* You can associate only one datafeed with each anomaly detection job.
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* The datafeed contains a query that runs at a defined interval (`frequency`).
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* If you are concerned about delayed data, you can add a delay (`query_delay`) at each interval.
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* If you are concerned about delayed data, you can add a delay (`query_delay') at each interval.
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* By default, the datafeed uses the following query: `{"match_all": {"boost": 1}}`.
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*
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* When Elasticsearch security features are enabled, your datafeed remembers which roles the user who created it had
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* at the time of creation and runs the query using those same roles. If you provide secondary authorization headers,
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* those credentials are used instead.

specification/ml/put_job/MlPutJobRequest.ts

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@@ -30,6 +30,7 @@ import { Duration } from '@_types/Time'
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/**
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* Create an anomaly detection job.
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* If you include a `datafeed_config`, you must have read index privileges on the source index.
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* If you include a `datafeed_config` but do not provide a query, the datafeed uses `{"match_all": {"boost": 1}}`.
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* @rest_spec_name ml.put_job
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* @availability stack since=5.4.0 stability=stable
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* @availability serverless stability=stable visibility=public

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