IMPORTANT: No additional bug fixes or documentation updates
will be released for this version. For the latest information, see the
current release documentation.
Get buckets API
editGet buckets API
editRetrieves job results for one or more buckets.
Request
editGET _ml/anomaly_detectors/<job_id>/results/buckets
GET _ml/anomaly_detectors/<job_id>/results/buckets/<timestamp>
Description
editThe get buckets API presents a chronological view of the records, grouped by bucket.
Path Parameters
edit-
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 Body
edit-
anomaly_score
- (double) Returns buckets with anomaly scores greater or equal than this value.
-
desc
- (boolean) If true, the buckets are sorted in descending order.
-
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.
-
-
sort
-
(string) Specifies the sort field for the requested buckets.
By default, the buckets are sorted by the
timestamp
field. -
start
- (string) Returns buckets with timestamps after this time.
Authorization
editYou 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
editThe following example gets bucket information for the it-ops-kpi
job:
GET _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, "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, "is_interim": false } ], "processing_time_ms": 2, "partition_scores": [], "result_type": "bucket" } ] }