128 lines
3.0 KiB
Plaintext
128 lines
3.0 KiB
Plaintext
//lcawley Verified example output 2017-04-11
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[[ml-get-bucket]]
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==== Get Buckets
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The get bucket API enables you to retrieve information about buckets in the
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results from a job.
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===== Request
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`GET _xpack/ml/anomaly_detectors/<job_id>/results/buckets` +
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`GET _xpack/ml/anomaly_detectors/<job_id>/results/buckets/<timestamp>`
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===== Description
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This API presents a chronological view of the records, grouped by bucket.
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===== Path Parameters
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`job_id`::
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(string) Identifier for the job
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`timestamp`::
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(string) The timestamp of a single bucket result.
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If you do not specify this optional parameter, the API returns information
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about all buckets.
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===== Request Body
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`anomaly_score`::
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(double) Returns buckets with anomaly scores higher than this value.
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`end`::
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(string) Returns buckets with timestamps earlier than this time.
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`exclude_interim`::
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(boolean) If true, the output excludes interim results.
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By default, interim results are included.
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`expand`::
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(boolean) If true, the output includes anomaly records.
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`from`::
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(integer) Skips the specified number of buckets.
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`size`::
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(integer) Specifies the maximum number of buckets to obtain.
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`start`::
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(string) Returns buckets with timestamps after this time.
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===== Results
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The API returns the following information:
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`buckets`::
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(array) An array of bucket objects. For more information, see
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<<ml-results-buckets,Buckets>>.
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===== Authorization
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You must have `monitor_ml`, `monitor`, `manage_ml`, or `manage` cluster
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privileges to use this API. You also need `read` index privilege on the index
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that stores the results. The `machine_learning_admin` and `machine_learning_user`
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roles provide these privileges. For more information, see
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<<security-privileges>> and <<built-in-roles>>.
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===== Examples
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The following example gets bucket information for the `it-ops-kpi` job:
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[source,js]
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--------------------------------------------------
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GET _xpack/ml/anomaly_detectors/it-ops-kpi/results/buckets
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{
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"anomaly_score": 80,
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"start": "1454530200001"
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}
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--------------------------------------------------
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// CONSOLE
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// TEST[skip:todo]
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In this example, the API returns a single result that matches the specified
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score and time constraints:
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[source,js]
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----
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{
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"count": 1,
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"buckets": [
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{
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"job_id": "it-ops-kpi",
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"timestamp": 1454943900000,
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"anomaly_score": 94.1706,
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"bucket_span": 300,
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"initial_anomaly_score": 94.1706,
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"record_count": 1,
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"event_count": 153,
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"is_interim": false,
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"bucket_influencers": [
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{
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"job_id": "it-ops-kpi",
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"result_type": "bucket_influencer",
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"influencer_field_name": "bucket_time",
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"initial_anomaly_score": 94.1706,
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"anomaly_score": 94.1706,
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"raw_anomaly_score": 2.32119,
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"probability": 0.00000575042,
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"timestamp": 1454943900000,
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"bucket_span": 300,
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"sequence_num": 2,
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"is_interim": false
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}
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],
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"processing_time_ms": 2,
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"partition_scores": [],
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"result_type": "bucket"
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}
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]
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}
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----
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