99 lines
3.2 KiB
Plaintext
99 lines
3.2 KiB
Plaintext
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[role="xpack"]
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[testenv="platinum"]
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[[update-dfanalytics]]
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=== Update {dfanalytics-jobs} API
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[subs="attributes"]
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++++
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<titleabbrev>Update {dfanalytics-jobs}</titleabbrev>
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++++
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Updates an existing {dfanalytics-job}.
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experimental[]
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[[ml-update-dfanalytics-request]]
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==== {api-request-title}
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`POST _ml/data_frame/analytics/<data_frame_analytics_id>/_update`
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[[ml-update-dfanalytics-prereq]]
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==== {api-prereq-title}
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If the {es} {security-features} are enabled, you must have the following
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built-in roles and privileges:
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* `machine_learning_admin`
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* `kibana_admin` (UI only)
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* source indices: `read`, `view_index_metadata`
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* destination index: `read`, `create_index`, `manage` and `index`
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* cluster: `monitor` (UI only)
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For more information, see <<security-privileges>> and <<built-in-roles>>.
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NOTE: The {dfanalytics-job} remembers which roles the user who created it had at
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the time of creation. When you start the job, it performs the analysis using
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those same roles. If you provide
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<<http-clients-secondary-authorization,secondary authorization headers>>,
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those credentials are used instead.
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[[ml-update-dfanalytics-desc]]
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==== {api-description-title}
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This API updates an existing {dfanalytics-job} that performs an analysis on the source
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indices and stores the outcome in a destination index.
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[[ml-update-dfanalytics-path-params]]
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==== {api-path-parms-title}
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`<data_frame_analytics_id>`::
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(Required, string)
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include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=job-id-data-frame-analytics-define]
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[role="child_attributes"]
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[[ml-update-dfanalytics-request-body]]
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==== {api-request-body-title}
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`allow_lazy_start`::
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(Optional, boolean)
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Specifies whether this job can start when there is insufficient {ml} node
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capacity for it to be immediately assigned to a node. The default is `false`; if
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a {ml} node with capacity to run the job cannot immediately be found, the API
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returns an error. However, this is also subject to the cluster-wide
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`xpack.ml.max_lazy_ml_nodes` setting. See <<advanced-ml-settings>>. If this
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option is set to `true`, the API does not return an error and the job waits in
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the `starting` state until sufficient {ml} node capacity is available.
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`description`::
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(Optional, string)
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include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=description-dfa]
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`model_memory_limit`::
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(Optional, string)
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The approximate maximum amount of memory resources that are permitted for
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analytical processing. The default value for {dfanalytics-jobs} is `1gb`. If
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your `elasticsearch.yml` file contains an `xpack.ml.max_model_memory_limit`
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setting, an error occurs when you try to create {dfanalytics-jobs} that have
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`model_memory_limit` values greater than that setting. For more information, see
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<<ml-settings>>.
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[[ml-update-dfanalytics-example]]
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==== {api-examples-title}
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[[ml-update-dfanalytics-example-preprocess]]
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===== Updating model memory limit example
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The following example shows how to update the model memory limit for the existing {dfanalytics} configuration.
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[source,console]
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--------------------------------------------------
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POST _ml/data_frame/analytics/model-flight-delays/_update
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{
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"model_memory_limit": "200mb"
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}
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--------------------------------------------------
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// TEST[skip:setup kibana sample data]
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