OpenSearch/docs/en/rest-api/ml/get-record.asciidoc

[[ml-get-record]]
//lcawley Verified example output 2017-04-11
==== Get Records

The get records API enables you to retrieve anomaly records for a job.


===== Request

`GET _xpack/ml/anomaly_detectors/<job_id>/results/records`

//===== Description

===== Path Parameters

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


===== Request Body

`desc`::
  (boolean) If true, the results are sorted in descending order.

`end`::
  (string) Returns records with timestamps earlier than this time.

`exclude_interim`::
  (boolean) If true, the output excludes interim results.
  By default, interim results are included.

`from`::
  (integer) Skips the specified number of records.

`record_score`::
  (double) Returns records with anomaly scores higher than this value.

`size`::
  (integer) Specifies the maximum number of records to obtain.

`sort`::
  (string) Specifies the sort field for the requested records.
  By default, the records are sorted by the `anomaly_score` value.

`start`::
  (string) Returns records with timestamps after this time.


===== Results

The API returns the following information:

`records`::
  (array) An array of record objects. For more information, see
  <<ml-results-records,Records>>.


===== Authorization

You must have `monitor_ml`, `monitor`, `manage_ml`, or `manage` cluster
privileges to use this API. You also need `read` index privilege on the index
that stores the results. The `machine_learning_admin` and `machine_learning_user`
roles provide these privileges. For more information, see
<<security-privileges>> and <<built-in-roles>>.


===== Examples

The following example gets bucket information for the `it-ops-kpi` job:

[source,js]
--------------------------------------------------
GET _xpack/ml/anomaly_detectors/it-ops-kpi/results/records
{
  "sort": "record_score",
  "desc": true,
  "start": "1454944100000"
}
--------------------------------------------------
// CONSOLE
// TEST[skip:todo]

In this example, the API returns twelve results for the specified
time constraints:
[source,js]
----
{
  "count": 12,
  "records": [
    {
      "job_id": "it-ops-kpi",
      "result_type": "record",
      "probability": 0.00000332668,
      "record_score": 72.9929,
      "initial_record_score": 65.7923,
      "bucket_span": 300,
      "detector_index": 0,
      "sequence_num": 1,
      "is_interim": false,
      "timestamp": 1454944200000,
      "function": "low_sum",
      "function_description": "sum",
      "typical": [
        1806.48
      ],
      "actual": [
        288
      ],
      "field_name": "events_per_min"
    },
  ...
  ]
}
----