Get Bucketsedit

The get bucket API enables you to retrieve job results for one or more buckets.

Requestedit

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

GET _xpack/ml/anomaly_detectors/<job_id>/results/buckets/<timestamp>

Descriptionedit

This API presents a chronological view of the records, grouped by bucket.

Path Parametersedit

job_id
(string) Identifier for the job
timestamp
(string) The timestamp of a single bucket result. If you do not specify this optional parameter, the API returns information about all buckets.

Request Bodyedit

anomaly_score
(double) Returns buckets with anomaly scores higher than this value.
end
(string) Returns buckets with timestamps earlier than this time.
exclude_interim
(boolean) If true, the output excludes interim results. By default, interim results are included.
expand
(boolean) If true, the output includes anomaly records.
page
from
(integer) Skips the specified number of buckets.
size
(integer) Specifies the maximum number of buckets to obtain.
start
(string) Returns buckets with timestamps after this time.

Resultsedit

The API returns the following information:

buckets
(array) An array of bucket objects. For more information, see Buckets.

Authorizationedit

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.

Examplesedit

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

GET _xpack/ml/anomaly_detectors/it-ops-kpi/results/buckets
{
  "anomaly_score": 80,
  "start": "1454530200001"
}

In this example, the API returns a single result that matches the specified score and time constraints:

{
  "count": 1,
  "buckets": [
    {
      "job_id": "it-ops-kpi",
      "timestamp": 1454943900000,
      "anomaly_score": 94.1706,
      "bucket_span": 300,
      "initial_anomaly_score": 94.1706,
      "record_count": 1,
      "event_count": 153,
      "is_interim": false,
      "bucket_influencers": [
        {
          "job_id": "it-ops-kpi",
          "result_type": "bucket_influencer",
          "influencer_field_name": "bucket_time",
          "initial_anomaly_score": 94.1706,
          "anomaly_score": 94.1706,
          "raw_anomaly_score": 2.32119,
          "probability": 0.00000575042,
          "timestamp": 1454943900000,
          "bucket_span": 300,
          "sequence_num": 2,
          "is_interim": false
        }
      ],
      "processing_time_ms": 2,
      "partition_scores": [],
      "result_type": "bucket"
    }
  ]
}