Delete anomaly detection jobs API

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Deletes an existing anomaly detection job.

Request

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DELETE _ml/anomaly_detectors/<job_id>

Prerequisites

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  • Requires the manage_ml cluster privilege. This privilege is included in the machine_learning_admin built-in role.
  • Before you can delete a job, you must delete the datafeeds that are associated with it. See Delete datafeeds.
  • Before you can delete a job, you must close it (unless you specify the force parameter). See Close jobs.

Description

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All job configuration, model state and results are deleted.

Deleting an anomaly detection job must be done via this API only. Do not delete the job directly from the .ml-* indices using the Elasticsearch delete document API. When Elasticsearch security features are enabled, make sure no write privileges are granted to anyone over the .ml-* indices.

It is not currently possible to delete multiple jobs using wildcards or a comma separated list.

Path parameters

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<job_id>
(Required, string) Identifier for the anomaly detection job.

Query parameters

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force
(Optional, Boolean) Use to forcefully delete an opened job; this method is quicker than closing and deleting the job.
wait_for_completion
(Optional, boolean) Specifies whether the request should return immediately or wait until the job deletion completes. Defaults to true.

Examples

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DELETE _ml/anomaly_detectors/total-requests

When the job is deleted, you receive the following results:

{
  "acknowledged": true
}

In the next example we delete the total-requests job asynchronously:

DELETE _ml/anomaly_detectors/total-requests?wait_for_completion=false

When wait_for_completion is set to false, the response contains the id of the job deletion task:

{
  "task": "oTUltX4IQMOUUVeiohTt8A:39"
}