Update jobs API
editUpdate jobs API
editUpdates certain properties of a job.
Request
editPOST _xpack/ml/anomaly_detectors/<job_id>/_update
Path parameters
edit-
job_id
(required) - (string) Identifier for the job
Request body
editThe following properties can be updated after the job is created:
Name | Description | Requires Restart |
---|---|---|
|
The approximate maximum amount of
memory resources required for analytical processing. See Analysis Limits. You
can update the |
Yes |
|
Advanced configuration option. The time between each periodic persistence of the model. See Job resources. |
Yes |
|
Contains custom meta data about the job. |
No |
|
A description of the job. See Job resources. |
No |
|
An array of detector update objects. |
No |
|
The identifier of the detector to update (integer). |
No |
|
The new description for the detector. |
No |
|
The new list of rules for the detector. |
No |
|
A list of job groups. See Job resources. |
No |
|
If true, enables calculation and storage of the model bounds for each entity that is being analyzed. See Model Plot Config. |
No |
|
The time in days that model snapshots are retained for the job. See Job resources. |
Yes |
|
Advanced configuration option. The period over which adjustments to the score are applied, as new data is seen. See Job resources. |
Yes |
|
Advanced configuration option. The number of days for which job results are retained. See Job resources. |
Yes |
For those properties that have Requires Restart
set to Yes
in this table,
if the job is open when you make the update, you must stop the data feed, close
the job, then restart the data feed and open the job for the changes to take
effect.
-
If the
memory_status
property in themodel_size_stats
object has a value ofhard_limit
, this means that it was unable to process some data. You might want to re-run this job with an increasedmodel_memory_limit
.
Prerequisites
editYou must have manage_ml
, or manage
cluster privileges to use this API.
For more information, see
Security privileges.
Examples
editThe following example updates the total-requests
job:
POST _xpack/ml/anomaly_detectors/total-requests/_update { "description":"An updated job", "groups": ["group1","group2"], "model_plot_config": { "enabled": true }, "analysis_limits": { "model_memory_limit": "1024mb" }, "renormalization_window_days": 30, "background_persist_interval": "2h", "model_snapshot_retention_days": 7, "results_retention_days": 60, "custom_settings": { "custom_urls" : [{ "url_name" : "Lookup IP", "url_value" : "http://geoiplookup.net/ip/$clientip$" }] } }
When the job is updated, you receive a summary of the job configuration information, including the updated property values. For example:
{ "job_id": "total-requests", "job_type": "anomaly_detector", "job_version": "6.5.0", "groups": [ "group1", "group2" ], "description": "An updated job", "create_time": 1518808660505, "analysis_config": { "bucket_span": "10m", "detectors": [ { "detector_description": "Sum of total", "function": "sum", "field_name": "total", "detector_index": 0 } ], "influencers": [] }, "analysis_limits": { "model_memory_limit": "1024mb", "categorization_examples_limit": 4 }, "data_description": { "time_field": "timestamp", "time_format": "epoch_ms" }, "model_plot_config": { "enabled": true }, "renormalization_window_days": 30, "background_persist_interval": "2h", "model_snapshot_retention_days": 7, "results_retention_days": 60, "custom_settings": { "custom_urls": [ { "url_name": "Lookup IP", "url_value": "http://geoiplookup.net/ip/$clientip$" } ] }, "results_index_name": "shared" }