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708730e27c
This PR adds a new field, `_meta`, to the data frame analytics configuration. The `_meta` field stores an arbitrary key-value map. Keys are strings. Values are arbitrary objects (possibly also maps). The `_meta` field can be updated using the data frame analytics `_update` endpoint.
138 lines
3.8 KiB
Text
138 lines
3.8 KiB
Text
[role="xpack"]
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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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[[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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Requires the following privileges:
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* cluster: `manage_ml` (the `machine_learning_admin` built-in role grants this
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privilege)
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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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NOTE: The {dfanalytics-job} remembers which roles the user who updated it had at
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the time of the update. 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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`max_num_threads`::
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(Optional, integer)
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The maximum number of threads to be used by the analysis.
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The default value is `1`. Using more threads may decrease the time
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necessary to complete the analysis at the cost of using more CPU.
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Note that the process may use additional threads for operational
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functionality other than the analysis itself.
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`_meta`::
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(Optional, object)
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include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=meta]
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`model_memory_limit`::
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(Optional, string)
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include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=model-memory-limit-dfa]
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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/loganalytics/_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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When the job is updated, the response contains its configuration with
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the updated values. For example:
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[source,console-result]
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----
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{
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"id" : "loganalytics",
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"create_time" : 1656364565517,
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"version" : "8.4.0",
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"authorization" : {
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"roles" : [
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"superuser"
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]
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},
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"description" : "Outlier detection on log data",
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"source" : {
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"index" : [
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"logdata"
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],
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"query" : {
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"match_all" : { }
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}
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},
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"dest" : {
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"index" : "logdata_out",
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"results_field" : "ml"
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},
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"analysis" : {
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"outlier_detection" : {
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"compute_feature_influence" : true,
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"outlier_fraction" : 0.05,
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"standardization_enabled" : true
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}
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},
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"model_memory_limit" : "200mb",
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"allow_lazy_start" : false,
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"max_num_threads" : 1
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}
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----
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