This documentation contains work-in-progress information for future Elastic Stack and Cloud releases. Use the version selector to view supported release docs. It also contains some Elastic Cloud serverless information. Check out our serverless docs for more details.
« Delete filters API Delete anomaly detection jobs API »
Elastic Docs ›Elasticsearch Guide [master] ›REST APIs ›Machine learning anomaly detection APIs

Delete forecasts API

edit

Delete forecasts API

edit

Deletes forecasts from a machine learning job.

Request

edit

DELETE _ml/anomaly_detectors/<job_id>/_forecast

DELETE _ml/anomaly_detectors/<job_id>/_forecast/<forecast_id>

DELETE _ml/anomaly_detectors/<job_id>/_forecast/_all

Prerequisites

edit

Requires the manage_ml cluster privilege. This privilege is included in the machine_learning_admin built-in role.

Description

edit

By 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 is true.
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

edit
resp = client.ml.delete_forecast(
    job_id="total-requests",
    forecast_id="_all",
)
print(resp)
response = client.ml.delete_forecast(
  job_id: 'total-requests',
  forecast_id: '_all'
)
puts response
const response = await client.ml.deleteForecast({
  job_id: "total-requests",
  forecast_id: "_all",
});
console.log(response);
DELETE _ml/anomaly_detectors/total-requests/_forecast/_all

If the request does not encounter errors, you receive the following result:

{
  "acknowledged": true
}
« Delete filters API Delete anomaly detection jobs API »