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]]
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2017-12-14 13:52:49 -05:00
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=== Get Jobs API
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++++
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<titleabbrev>Get Jobs</titleabbrev>
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++++
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2017-04-04 18:26:39 -04:00
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2018-06-13 16:37:35 -04:00
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Retrieves configuration information for jobs.
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2017-04-25 17:08:29 -04:00
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2017-06-06 16:42:47 -04:00
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==== Request
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2017-08-09 11:30:21 -04:00
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`GET _xpack/ml/anomaly_detectors/<job_id>` +
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`GET _xpack/ml/anomaly_detectors/<job_id>,<job_id>` +
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2017-04-04 18:26:39 -04:00
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`GET _xpack/ml/anomaly_detectors/` +
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2017-08-09 11:30:21 -04:00
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`GET _xpack/ml/anomaly_detectors/_all`
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===== Description
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You can get information for multiple jobs in a single API request by using a
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group name, a comma-separated list of jobs, or a wildcard expression. You can
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get information for all jobs by using `_all`, by specifying `*` as the
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`<job_id>`, or by omitting the `<job_id>`.
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2017-04-11 21:52:47 -04:00
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2017-04-18 18:13:21 -04:00
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2017-06-06 16:42:47 -04:00
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==== Path Parameters
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`job_id`::
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(string) Identifier for the job. It can be a job identifier, a group name,
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or a wildcard expression. If you do not specify one of these options, the API
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returns information for all jobs.
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2017-04-25 17:08:29 -04:00
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2017-06-06 16:42:47 -04:00
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==== Results
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2017-04-11 22:26:18 -04:00
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The API returns the following information:
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2017-04-11 21:52:47 -04:00
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`jobs`::
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2017-04-11 22:26:18 -04:00
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(array) An array of job resources.
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2017-04-11 21:52:47 -04:00
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For more information, see <<ml-job-resource,Job Resources>>.
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2017-06-06 16:42:47 -04:00
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==== Authorization
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2017-04-25 17:08:29 -04:00
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You must have `monitor_ml`, `monitor`, `manage_ml`, or `manage` cluster
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2017-06-19 21:23:58 -04:00
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privileges to use this API. For more information, see
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{xpack-ref}/security-privileges.html[Security Privileges].
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2017-04-25 17:08:29 -04:00
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2017-06-06 16:42:47 -04:00
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==== Examples
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2017-04-04 18:26:39 -04:00
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2018-02-09 12:16:24 -05:00
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The following example gets configuration information for the `total-requests` job:
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2017-04-11 21:52:47 -04:00
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[source,js]
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--------------------------------------------------
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2018-02-09 12:16:24 -05:00
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GET _xpack/ml/anomaly_detectors/total-requests
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2017-04-11 21:52:47 -04:00
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--------------------------------------------------
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// CONSOLE
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2018-08-31 19:49:24 -04:00
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// TEST[skip:setup:server_metrics_job]
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2017-04-11 21:52:47 -04:00
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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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"job_id": "total-requests",
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2017-04-11 21:52:47 -04:00
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"job_type": "anomaly_detector",
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2018-02-09 12:16:24 -05:00
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"job_version": "7.0.0-alpha1",
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"description": "Total sum of requests",
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"create_time": 1517011406091,
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2017-04-04 18:26:39 -04:00
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"analysis_config": {
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2018-02-09 12:16:24 -05:00
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"bucket_span": "10m",
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2017-04-04 18:26:39 -04:00
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"detectors": [
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{
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"detector_description": "Sum of total",
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"function": "sum",
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"field_name": "total",
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2017-06-02 05:26:01 -04:00
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"detector_index": 0
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2017-04-04 18:26:39 -04:00
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}
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],
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2018-02-09 12:16:24 -05:00
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"influencers": [ ]
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},
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"analysis_limits": {
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[ML] Set explicit defaults to AnalysisLimits (elastic/x-pack-elasticsearch#4015)
Analysis limits contain settings that affect the resources
used by ML jobs. Those limits always take place. However,
explictly setting them is not required as they have reasonable
defaults. For a long time those defaults lived on the c++ side.
The job could just not have any explicit limits and that meant
defaults would be used at the c++ side. This has the disadvantage
that it is not obvious to the users what these settings are set to.
Additionally, users might not be aware of the settings existence.
On top of that, since 6.1, the default model_memory_limit was lowered
from 4GB to 1GB. For BWC, this meant that jobs where model_memory_limit
is null, the default of 4GB applies. Jobs that were created from 6.1
onwards, contain an explicit setting for model_memory_limit, which is
1GB unless the user sets it differently. This adds additional confusion.
This commit makes analysis limits an always explicit setting on the job.
Regardless of whether the user sets custom limits or not, the job object
(and response) will contain the full analysis limits values.
The possibilities for interpretation of missing values are:
- the entire analysis_limits is null: this may only happen for jobs
created prior to 6.1. Thus we set the model_memory_limit to 4GB.
- analysis_limits are non-null but model_memory_limit is: this also
may only happen for jobs prior to 6.1. Again, we set memory limit to
4GB.
- model_memory_limit is non-null: this either means the user set an
explicit value or the job was created from 6.1 onwards and it has
the explicit default of 1GB. We simply keep the given value.
For categorization_examples_limit the default has always been 4, so
we fill that in when it's missing.
Finally, note that we still need to handle potential null values
for the situation of a mixed cluster.
Original commit: elastic/x-pack-elasticsearch@5b6994ef750298a829dd2995664470cd4cc95e07
2018-02-27 12:49:05 -05:00
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"model_memory_limit": "1024mb",
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"categorization_examples_limit": 4
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2017-04-04 18:26:39 -04:00
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},
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"data_description": {
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2018-02-09 12:16:24 -05:00
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"time_field": "timestamp",
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2017-04-04 18:26:39 -04:00
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"time_format": "epoch_ms"
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},
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"model_snapshot_retention_days": 1,
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"results_index_name": "shared"
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}
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]
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}
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----
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2018-02-09 12:16:24 -05:00
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// TESTRESPONSE[s/"7.0.0-alpha1"/$body.$_path/]
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// TESTRESPONSE[s/1517011406091/$body.$_path/]
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