| 12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364656667686970717273747576777879808182838485868788899091929394 | [role="xpack"][testenv="platinum"][[ml-forecast]]= Forecast jobs API++++<titleabbrev>Forecast jobs</titleabbrev>++++Predicts the future behavior of a time series by using its historical behavior. [[ml-forecast-request]]== {api-request-title}`POST _ml/anomaly_detectors/<job_id>/_forecast`[[ml-forecast-prereqs]]== {api-prereq-title}Requires the `manage_ml` cluster privilege. This privilege is included in the `machine_learning_admin` built-in role.[[ml-forecast-desc]]== {api-description-title}You can create a forecast job based on an {anomaly-job} to extrapolate future behavior. Refer to{ml-docs}/ml-ad-finding-anomalies.html#ml-ad-forecast[Forecasting the future]and {ml-docs}/ml-limitations.html#ml-forecast-limitations[Forecast limitations] to learn more.You can delete a forecast by using the <<ml-delete-forecast,Delete forecast API>>.[NOTE]===============================* If you use an `over_field_name` property in your job, you cannot create aforecast. For more information about this property, see <<ml-put-job>>.* The job must be open when you create a forecast. Otherwise, an error occurs.===============================[[ml-forecast-path-parms]]== {api-path-parms-title}`<job_id>`::(Required, string)include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=job-id-anomaly-detection][[ml-forecast-request-body]]== {api-request-body-title}`duration`::  (Optional, <<time-units, 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.`expires_in`::  (Optional, <<time-units, 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.`max_model_memory`::  (Optional, <<byte-units,byte value>>) The maximum memory the forecast can use.  If the forecast needs to use more than the provided amount, it will spool to  disk. Default is 20mb, maximum is 500mb and minimum is 1mb. If set to 40% or  more of the job's configured memory limit, it is automatically reduced to  below that amount.[[ml-forecast-example]]== {api-examples-title}[source,console]--------------------------------------------------POST _ml/anomaly_detectors/low_request_rate/_forecast{  "duration": "10d"}--------------------------------------------------// TEST[skip:requires delay]When the forecast is created, you receive the following results:[source,js]----{  "acknowledged": true,  "forecast_id": "wkCWa2IB2lF8nSE_TzZo"}----// NOTCONSOLEYou can subsequently see the forecast in the *Single Metric Viewer* in {kib}.
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