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Get records API

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Get records API

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Retrieves anomaly records for an anomaly detection job.

Request

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GET _ml/anomaly_detectors/<job_id>/results/records

Prerequisites

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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.

Path parameters

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<job_id>: (Required, string) Identifier for the anomaly detection job.

Request body

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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.

page

from: (integer) Skips the specified number of records.
size: (integer) Specifies the maximum number of records to obtain.

record_score

(double) Returns records with anomaly scores greater or equal than this value.

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.

Response body

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The API returns the following information:

records: (array) An array of record objects. For more information, see Records.

Examples

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

GET _ml/anomaly_detectors/it-ops-kpi/results/records
{
  "sort": "record_score",
  "desc": true,
  "start": "1454944100000"
}

In this example, the API returns twelve results for the specified time constraints:

{
  "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,
      "is_interim": false,
      "timestamp": 1454944200000,
      "function": "low_sum",
      "function_description": "sum",
      "typical": [
        1806.48
      ],
      "actual": [
        288
      ],
      "field_name": "events_per_min"
    },
  ...
  ]
}

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