elasticsearch/docs/reference/ml/df-analytics/apis/estimate-memory-usage-dfanalytics.asciidoc

[role="xpack"]
[testenv="platinum"]
[[estimate-memory-usage-dfanalytics]]
=== Estimate memory usage API

[subs="attributes"]
++++
<titleabbrev>Estimate memory usage for {dfanalytics-jobs}</titleabbrev>
++++

Estimates memory usage for the given {dataframe-analytics-config}.

experimental[]

[[ml-estimate-memory-usage-dfanalytics-request]]
==== {api-request-title}

`POST _ml/data_frame/analytics/_estimate_memory_usage`

[[ml-estimate-memory-usage-dfanalytics-prereq]]
==== {api-prereq-title}

* You must have `monitor_ml` privilege to use this API. For more 
information, see <<security-privileges>> and <<built-in-roles>>.

[[ml-estimate-memory-usage-dfanalytics-desc]]
==== {api-description-title}

This API estimates memory usage for the given {dataframe-analytics-config} before the {dfanalytics-job} is even created.

Serves as an advice on how to set `model_memory_limit` when creating {dfanalytics-job}.

[[ml-estimate-memory-usage-dfanalytics-request-body]]
==== {api-request-body-title}

`data_frame_analytics_config`::
  (Required, object) Intended configuration of {dfanalytics-job}. For more information, see
  <<ml-dfanalytics-resources>>.
  Note that `id` and `dest` don't need to be provided in the context of this API.

[[ml-estimate-memory-usage-dfanalytics-results]]
==== {api-response-body-title}

`expected_memory_without_disk`::
  (string) Estimated memory usage under the assumption that the whole {dfanalytics} should happen in memory
  (i.e. without overflowing to disk).
  
`expected_memory_with_disk`::
  (string) Estimated memory usage under the assumption that overflowing to disk is allowed during {dfanalytics}.
  `expected_memory_with_disk` is usually smaller than `expected_memory_without_disk` as using disk allows to
  limit the main memory needed to perform {dfanalytics}.

[[ml-estimate-memory-usage-dfanalytics-example]]
==== {api-examples-title}

[source,console]
--------------------------------------------------
POST _ml/data_frame/analytics/_estimate_memory_usage
{
  "data_frame_analytics_config": {
    "source": {
      "index": "logdata"
    },
    "analysis": {
      "outlier_detection": {}
    }
  }
}
--------------------------------------------------
// TEST[skip:TBD]

The API returns the following results:

[source,console-result]
----
{
  "expected_memory_without_disk": "128MB",
  "expected_memory_with_disk": "32MB"
}
----