- X-Pack Reference for 6.0-6.2 and 5.x:
- Introduction
- Installing X-Pack
- Migrating to X-Pack
- Breaking Changes
- Securing Elasticsearch and Kibana
- Monitoring the Elastic Stack
- Alerting on Cluster and Index Events
- Reporting from Kibana
- Graphing Connections in Your Data
- Profiling your Queries and Aggregations
- Machine Learning in the Elastic Stack
- X-Pack Settings
- X-Pack APIs
- Info API
- Security APIs
- Watcher APIs
- Graph APIs
- Machine Learning APIs
- Close Jobs
- Create Datafeeds
- Create Jobs
- Delete Datafeeds
- Delete Jobs
- Delete Model Snapshots
- Flush Jobs
- Get Buckets
- Get Categories
- Get Datafeeds
- Get Datafeed Statistics
- Get Influencers
- Get Jobs
- Get Job Statistics
- Get Model Snapshots
- Get Records
- Open Jobs
- Post Data to Jobs
- Preview Datafeeds
- Revert Model Snapshots
- Start Datafeeds
- Stop Datafeeds
- Update Datafeeds
- Update Jobs
- Update Model Snapshots
- Validate Detectors
- Validate Jobs
- Definitions
- Troubleshooting
- Limitations
- License Management
- Release Notes
WARNING: Version 5.4 of the Elastic Stack has passed its EOL date.
This documentation is no longer being maintained and may be removed. If you are running this version, we strongly advise you to upgrade. For the latest information, see the current release documentation.
Validate Jobs
editValidate Jobs
editThe validate jobs API validates job configuration information.
Request
editPOST _xpack/ml/anomaly_detectors/_validate
Description
editThis API enables you validate the job configuration before you create the job.
This functionality is in technical preview and may be changed or removed in a future release. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features.
Request Body
editFor a list of the properties that you can specify in the body of this API, see Job Resources.
Authorization
editYou must have manage_ml, or manage cluster privileges to use this API.
For more information, see Cluster Privileges.
Examples
editThe following example validates job configuration information:
POST _xpack/ml/anomaly_detectors/_validate { "description" : "Unusual response times by airlines", "analysis_config" : { "bucket_span": "300S", "detectors" :[ { "function": "metric", "field_name": "responsetime", "by_field_name": "airline"}], "influencers": [ "airline" ] }, "data_description" : { "time_field": "time", "time_format": "yyyy-MM-dd'T'HH:mm:ssX" } }
When the validation is complete, you receive the following results:
{ "acknowledged": true }