OpenSearch/docs/en/rest-api/ml/forecast.asciidoc

[role="xpack"]
[[ml-forecast]]
=== Forecast Jobs API
++++
<titleabbrev>Forecast Jobs</titleabbrev>
++++

This API uses historical behavior to predict the future behavior of a time
series.

==== Request

`POST _xpack/ml/anomaly_detectors/<job_id>/_forecast`


==== Description

See {xpack-ref}/ml-overview.html#ml-forecasting[Forecasting the Future].

[NOTE]
===============================

* If you use an `over_field_name` property in your job, you cannot create a
forecast. For more information about this property, see <<ml-job-resource>>.
* The job must be open when you create a forecast. Otherwise, an error occurs.
===============================

==== Path Parameters

`job_id`::
  (string) Identifier for the job.


==== Request Parameters

`duration`::
  (time units) A period of time that indicates how far into the future to
  forecast. For example, `30d` corresponds to 30 days. The default value is 1
  day. The forecast starts at the last record that was processed. For more
  information about time units, see <<time-units>>.

`expires_in`::
  (time units) The period of time that forecast results are retained.
  After a forecast expires, the results are deleted. The default value is 14 days.
  If set to a value of `0`, the forecast is never automatically deleted.
  For more information about time units, see <<time-units>>.

==== Authorization

You must have `manage_ml`, or `manage` cluster privileges to use this API.
For more information, see {xpack-ref}/security-privileges.html[Security Privileges].


==== Examples

The following example requests a 10 day forecast for the `total-requests` job:

[source,js]
--------------------------------------------------
POST _xpack/ml/anomaly_detectors/total-requests/_forecast
{
  "duration": "10d"
}
--------------------------------------------------
// CONSOLE
// TEST[skip:todo]

When the forecast is created, you receive the following results:
[source,js]
----
{
  "acknowledged": true,
  "forecast_id": 1507824469268
}
----

You can subsequently see the forecast in the *Single Metric Viewer* in {kib}.
//and in the results that you retrieve by using {ml} APIs such as the
//<<ml-get-bucket,get bucket API>> and <<ml-get-record,get records API>>.