84 lines
2.3 KiB
Plaintext
84 lines
2.3 KiB
Plaintext
[role="xpack"]
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[testenv="platinum"]
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[[start-dfanalytics]]
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=== Start {dfanalytics-jobs} API
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[subs="attributes"]
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++++
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<titleabbrev>Start {dfanalytics-jobs}</titleabbrev>
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++++
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Starts a {dfanalytics-job}.
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experimental[]
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[[ml-start-dfanalytics-request]]
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==== {api-request-title}
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`POST _ml/data_frame/analytics/<data_frame_analytics_id>/_start`
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[[ml-start-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 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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[[ml-start-dfanalytics-desc]]
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==== {api-description-title}
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A {dfanalytics-job} can be started and stopped multiple times throughout its
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lifecycle.
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If the destination index does not exist, it is created automatically the first
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time you start the {dfanalytics-job}. The `index.number_of_shards` and
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`index.number_of_replicas` settings for the destination index are copied from
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the source index. If there are multiple source indices, the destination index
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copies the highest setting values. The mappings for the destination index are
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also copied from the source indices. If there are any mapping conflicts, the job
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fails to start.
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If the destination index exists, it is used as is. You can therefore set up the
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destination index in advance with custom settings and mappings.
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[[ml-start-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::{docdir}/ml/ml-shared.asciidoc[tag=job-id-data-frame-analytics-define]
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[[ml-start-dfanalytics-query-params]]
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==== {api-query-parms-title}
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`timeout`::
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(Optional, <<time-units,time units>>)
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include::{docdir}/ml/ml-shared.asciidoc[tag=timeout-start]
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[[ml-start-dfanalytics-example]]
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==== {api-examples-title}
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The following example starts the `loganalytics` {dfanalytics-job}:
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[source,console]
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--------------------------------------------------
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POST _ml/data_frame/analytics/loganalytics/_start
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--------------------------------------------------
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// TEST[skip:setup:logdata_job]
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When the {dfanalytics-job} starts, you receive the following results:
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[source,console-result]
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----
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{
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"acknowledged" : true
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}
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----
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