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Get Records

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Get Records

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

Request

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

Path Parameters

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job_id: (string) Identifier for the 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 higher 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.

Results

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The API returns the following information:

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

Authorization

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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.

Examples

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

GET _xpack/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,
      "sequence_num": 1,
      "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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