IMPORTANT: No additional bug fixes or documentation updates
will be released for this version. For the latest information, see the
current release documentation.
Delete forecasts API
editDelete forecasts API
editDeletes forecasts from a machine learning job.
Request
editDELETE _ml/anomaly_detectors/<job_id>/_forecast
DELETE _ml/anomaly_detectors/<job_id>/_forecast/<forecast_id>
DELETE _ml/anomaly_detectors/<job_id>/_forecast/_all
Prerequisites
editRequires the manage_ml
cluster privilege. This privilege is included in the
machine_learning_admin
built-in role.
Description
editBy default, forecasts are retained for 14 days. You can specify a different
retention period with the expires_in
parameter in the
forecast jobs API. The delete forecast API enables you to delete
one or more forecasts before they expire.
When you delete a job, its associated forecasts are deleted.
For more information, see Forecasting the future.
Path parameters
edit-
<forecast_id>
-
(Optional, string) A comma-separated list of forecast identifiers. If you do not
specify this optional parameter or if you specify
_all
or*
the API deletes all forecasts from the job. -
<job_id>
- (Required, string) Identifier for the anomaly detection job.
Query parameters
edit-
allow_no_forecasts
-
(Optional, Boolean) Specifies whether an error occurs when there are no
forecasts. In particular, if this parameter is set to
false
and there are no forecasts associated with the job, attempts to delete all forecasts return an error. The default value istrue
. -
timeout
-
(Optional, time units) Specifies the period of time to wait
for the completion of the delete operation. When this period of time elapses,
the API fails and returns an error. The default value is
30s
.
Examples
editresponse = client.ml.delete_forecast( job_id: 'total-requests', forecast_id: '_all' ) puts response
DELETE _ml/anomaly_detectors/total-requests/_forecast/_all
If the request does not encounter errors, you receive the following result:
{ "acknowledged": true }