2017-06-19 21:23:58 -04:00
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[role="xpack"]
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2018-08-31 19:49:24 -04:00
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[testenv="platinum"]
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2017-04-04 18:26:39 -04:00
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[[ml-get-job-stats]]
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2019-07-30 13:52:23 -04:00
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=== Get {anomaly-job} statistics API
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2017-12-14 13:52:49 -05:00
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++++
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2018-12-20 13:23:28 -05:00
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<titleabbrev>Get job statistics</titleabbrev>
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2017-12-14 13:52:49 -05:00
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++++
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2017-04-04 18:26:39 -04:00
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2019-07-30 13:52:23 -04:00
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Retrieves usage information for {anomaly-jobs}.
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2017-04-04 18:26:39 -04:00
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2019-06-27 12:42:47 -04:00
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[[ml-get-job-stats-request]]
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==== {api-request-title}
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2017-04-04 18:26:39 -04:00
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2018-12-07 15:34:11 -05:00
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`GET _ml/anomaly_detectors/<job_id>/_stats`
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2017-04-04 18:26:39 -04:00
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2018-12-07 15:34:11 -05:00
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`GET _ml/anomaly_detectors/<job_id>,<job_id>/_stats` +
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2017-08-09 11:30:21 -04:00
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2018-12-07 15:34:11 -05:00
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`GET _ml/anomaly_detectors/_stats` +
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2017-08-09 11:30:21 -04:00
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2019-06-27 16:58:42 -04:00
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`GET _ml/anomaly_detectors/_all/_stats`
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[[ml-get-job-stats-prereqs]]
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==== {api-prereq-title}
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* If the {es} {security-features} are enabled, you must have `monitor_ml`,
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`monitor`, `manage_ml`, or `manage` cluster privileges to use this API. See
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2019-10-07 18:23:19 -04:00
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<<security-privileges>>.
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2017-08-09 11:30:21 -04:00
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2019-06-27 12:42:47 -04:00
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[[ml-get-job-stats-desc]]
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==== {api-description-title}
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2017-08-09 11:30:21 -04:00
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2019-07-30 13:52:23 -04:00
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You can get statistics for multiple {anomaly-jobs} in a single API request by
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using a group name, a comma-separated list of jobs, or a wildcard expression.
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You can get statistics for all {anomaly-jobs} by using `_all`, by specifying `*`
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as the `<job_id>`, or by omitting the `<job_id>`.
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2017-08-09 11:30:21 -04:00
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2019-01-17 13:47:15 -05:00
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IMPORTANT: This API returns a maximum of 10,000 jobs.
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2019-06-27 12:42:47 -04:00
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[[ml-get-job-stats-path-parms]]
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==== {api-path-parms-title}
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2017-04-04 18:26:39 -04:00
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2019-07-12 11:26:31 -04:00
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`<job_id>`::
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2019-12-27 16:30:26 -05:00
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(Optional, string)
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include::{docdir}/ml/ml-shared.asciidoc[tag=job-id-anomaly-detection-default]
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2017-04-04 18:26:39 -04:00
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2019-07-30 08:22:14 -04:00
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[[ml-get-job-stats-query-parms]]
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==== {api-query-parms-title}
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`allow_no_jobs`::
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2019-12-27 16:30:26 -05:00
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(Optional, boolean)
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include::{docdir}/ml/ml-shared.asciidoc[tag=allow-no-jobs]
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2019-07-30 08:22:14 -04:00
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2019-06-27 12:42:47 -04:00
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[[ml-get-job-stats-results]]
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==== {api-response-body-title}
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2017-04-04 18:26:39 -04:00
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2017-04-11 21:52:47 -04:00
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The API returns the following information:
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2017-04-04 18:26:39 -04:00
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2017-04-11 21:52:47 -04:00
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`jobs`::
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2019-07-30 13:52:23 -04:00
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(array) An array of {anomaly-job} statistics objects.
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2017-04-04 18:26:39 -04:00
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2019-07-30 08:22:14 -04:00
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[[ml-get-job-stats-response-codes]]
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==== {api-response-codes-title}
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`404` (Missing resources)::
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If `allow_no_jobs` is `false`, this code indicates that there are no
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resources that match the request or only partial matches for the request.
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2019-06-27 12:42:47 -04:00
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[[ml-get-job-stats-example]]
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==== {api-examples-title}
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2017-04-04 18:26:39 -04:00
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2017-04-11 21:52:47 -04:00
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The following example gets usage information for the `farequote` job:
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2019-09-06 11:31:13 -04:00
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[source,console]
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2017-04-11 21:52:47 -04:00
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--------------------------------------------------
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2018-12-07 15:34:11 -05:00
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GET _ml/anomaly_detectors/farequote/_stats
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2017-04-11 21:52:47 -04:00
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--------------------------------------------------
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// TEST[skip:todo]
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2017-05-08 09:53:04 -04:00
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The API returns the following results:
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2017-04-21 11:23:27 -04:00
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[source,js]
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2017-04-04 18:26:39 -04:00
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----
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{
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"count": 1,
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"jobs": [
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{
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2017-04-11 21:52:47 -04:00
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"job_id": "farequote",
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2017-04-04 18:26:39 -04:00
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"data_counts": {
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2017-04-11 21:52:47 -04:00
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"job_id": "farequote",
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"processed_record_count": 86275,
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"processed_field_count": 172550,
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"input_bytes": 6744714,
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"input_field_count": 172550,
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2017-04-04 18:26:39 -04:00
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"invalid_date_count": 0,
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"missing_field_count": 0,
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"out_of_order_timestamp_count": 0,
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"empty_bucket_count": 0,
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2017-04-11 21:52:47 -04:00
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"sparse_bucket_count": 15,
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"bucket_count": 1528,
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"earliest_record_timestamp": 1454803200000,
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"latest_record_timestamp": 1455235196000,
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"last_data_time": 1491948163685,
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"latest_sparse_bucket_timestamp": 1455174900000,
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"input_record_count": 86275
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2017-04-04 18:26:39 -04:00
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},
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"model_size_stats": {
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2017-04-11 21:52:47 -04:00
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"job_id": "farequote",
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2017-04-04 18:26:39 -04:00
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"result_type": "model_size_stats",
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2017-04-11 21:52:47 -04:00
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"model_bytes": 387594,
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"total_by_field_count": 21,
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2017-04-04 18:26:39 -04:00
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"total_over_field_count": 0,
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2017-04-11 21:52:47 -04:00
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"total_partition_field_count": 20,
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2017-04-04 18:26:39 -04:00
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"bucket_allocation_failures_count": 0,
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"memory_status": "ok",
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2017-04-11 21:52:47 -04:00
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"log_time": 1491948163000,
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"timestamp": 1455234600000
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2017-04-04 18:26:39 -04:00
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},
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2019-06-17 02:58:26 -04:00
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"state": "closed",
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"timing_stats": {
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"job_id": "farequote",
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"minimum_bucket_processing_time_ms": 0.0,
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"maximum_bucket_processing_time_ms": 15.0,
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"average_bucket_processing_time_ms": 8.75,
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"exponential_average_bucket_processing_time_ms": 6.1435899
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}
|
2017-04-04 18:26:39 -04:00
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}
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]
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}
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----
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