elasticsearch/docs/reference/ml/anomaly-detection/apis/get-ml-info.asciidoc

[role="xpack"]
[testenv="platinum"]
[[get-ml-info]]
= Get machine learning info API

[subs="attributes"]
++++
<titleabbrev>Get {ml} info</titleabbrev>
++++

Returns defaults and limits used by machine learning.

[[get-ml-info-request]]
== {api-request-title}

`GET _ml/info`

[[get-ml-info-prereqs]]
== {api-prereq-title}

Requires the `monitor_ml` cluster privilege. This privilege is included in the 
`machine_learning_user` built-in role.

[[get-ml-info-desc]]
== {api-description-title}

This endpoint is designed to be used by a user interface that needs to fully
understand machine learning configurations where some options are not specified,
meaning that the defaults should be used. This endpoint may be used to find out
what those defaults are. It also provides information about the maximum size
of {ml} jobs that could run in the current cluster configuration.

[[get-ml-info-example]]
== {api-examples-title}

The endpoint takes no arguments:

[source,console]
--------------------------------------------------
GET _ml/info
--------------------------------------------------
// TEST

This is a possible response:

[source,console-result]
----
{
  "defaults" : {
    "anomaly_detectors" : {
      "categorization_analyzer" : {
        "tokenizer" : "ml_classic",
        "filter" : [
          {
            "type" : "stop",
            "stopwords" : [
              "Monday",
              "Tuesday",
              "Wednesday",
              "Thursday",
              "Friday",
              "Saturday",
              "Sunday",
              "Mon",
              "Tue",
              "Wed",
              "Thu",
              "Fri",
              "Sat",
              "Sun",
              "January",
              "February",
              "March",
              "April",
              "May",
              "June",
              "July",
              "August",
              "September",
              "October",
              "November",
              "December",
              "Jan",
              "Feb",
              "Mar",
              "Apr",
              "May",
              "Jun",
              "Jul",
              "Aug",
              "Sep",
              "Oct",
              "Nov",
              "Dec",
              "GMT",
              "UTC"
            ]
          }
        ]
      },
      "model_memory_limit" : "1gb",
      "categorization_examples_limit" : 4,
      "model_snapshot_retention_days" : 10,
      "daily_model_snapshot_retention_after_days" : 1
    },
    "datafeeds" : {
      "scroll_size" : 1000
    }
  },
  "upgrade_mode": false,
  "native_code" : {
    "version": "7.0.0",
    "build_hash": "99a07c016d5a73"
  },
  "limits" : {
    "effective_max_model_memory_limit": "28961mb",
    "total_ml_memory": "86883mb"
  }
}
----
// TESTRESPONSE[s/"upgrade_mode": false/"upgrade_mode": $body.upgrade_mode/]
// TESTRESPONSE[s/"version": "7.0.0",/"version": "$body.native_code.version",/]
// TESTRESPONSE[s/"build_hash": "99a07c016d5a73"/"build_hash": "$body.native_code.build_hash"/]
// TESTRESPONSE[s/"effective_max_model_memory_limit": "28961mb"/"effective_max_model_memory_limit": "$body.limits.effective_max_model_memory_limit"/]
// TESTRESPONSE[s/"total_ml_memory": "86883mb"/"total_ml_memory": "$body.limits.total_ml_memory"/]