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The update job API enables you to update certain properties of a job.
The 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. |
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 |
|
An optional description of the job. 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.
-
You can update the
analysis_limitsonly while the job is closed. -
The
model_memory_limitproperty value cannot be decreased. -
If the
memory_statusproperty in themodel_size_statsobject 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.
You must have manage_ml, or manage cluster privileges to use this API.
For more information, see
Security Privileges.
The following example updates the it_ops_new_logs job:
POST _xpack/ml/anomaly_detectors/it_ops_new_logs/_update
{
"description":"An updated job",
"model_plot_config": {
"enabled": true
},
"analysis_limits": {
"model_memory_limit": 1024
},
"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": "it_ops_new_logs",
"job_type": "anomaly_detector",
"description": "An updated job",
"create_time": 1493678314204,
"finished_time": 1493678315850,
"analysis_config": {
"bucket_span": "1800s",
"categorization_field_name": "message",
"detectors": [
{
"detector_description": "Unusual message counts",
"function": "count",
"by_field_name": "mlcategory",
"detector_rules": [],
"detector_index": 0
}
],
"influencers": []
},
"analysis_limits": {
"model_memory_limit": 1024
},
"data_description": {
"time_field": "time",
"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/$clientip$"
}
]
},
"model_snapshot_id": "1493678315",
"results_index_name": "shared"
}