Reset anomaly detection jobs APIedit
Resets an existing anomaly detection job.
Requestedit
POST _ml/anomaly_detectors/<job_id>/_reset
Prerequisitesedit
-
Requires the
manage_mlcluster privilege. This privilege is included in themachine_learning_adminbuilt-in role. -
Before you can reset a job, you must close it. You can set
forcetotruewhen closing the job to avoid waiting for the job to complete. See Close jobs.
Descriptionedit
All model state and results are deleted. The job is ready to start over as if it had just been created.
It is not currently possible to reset multiple jobs using wildcards or a comma separated list.
Path parametersedit
-
<job_id> - (Required, string) Identifier for the anomaly detection job.
Query parametersedit
-
wait_for_completion -
(Optional, Boolean) Specifies whether the request should return immediately or
wait until the job reset completes. Defaults to
true. -
delete_user_annotations -
(Optional, Boolean) Specifies whether annotations that have been added by the
user should be deleted along with any auto-generated annotations when the job is
reset. Defaults to
false.
Examplesedit
POST _ml/anomaly_detectors/total-requests/_reset
When the job is reset, you receive the following results:
{
"acknowledged": true
}
In the next example we reset the total-requests job asynchronously:
POST _ml/anomaly_detectors/total-requests/_reset?wait_for_completion=false
When wait_for_completion is set to false, the response contains the id
of the job reset task:
{
"task": "oTUltX4IQMOUUVeiohTt8A:39"
}
If you want to check the status of the reset task, use the Task management by referencing the task ID.