[role="xpack"] [testenv="platinum"] [[ml-get-bucket]] === Get buckets API ++++ Get buckets ++++ Retrieves job results for one or more buckets. ==== Request `GET _ml/anomaly_detectors//results/buckets` + `GET _ml/anomaly_detectors//results/buckets/` ==== Description The get buckets API presents a chronological view of the records, grouped by bucket. ==== Path Parameters `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 `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. ===== Results The API returns the following information: `buckets`:: (array) An array of bucket objects. For more information, see <>. ==== 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 {xpack-ref}/security-privileges.html[Security Privileges] and {xpack-ref}/built-in-roles.html[Built-in Roles]. ==== Examples The following example gets bucket information for the `it-ops-kpi` job: [source,js] -------------------------------------------------- GET _ml/anomaly_detectors/it-ops-kpi/results/buckets { "anomaly_score": 80, "start": "1454530200001" } -------------------------------------------------- // CONSOLE // TEST[skip:todo] In this example, the API returns a single result that matches the specified score and time constraints: [source,js] ---- { "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" } ] } ----