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stack es ml preview-datafeed cli command

Serverless Preview

Elastic Cloud Serverless projects are autoscaled environments, fully managed by Elastic and available on Elastic Cloud.

Availability

  • Preview

    This functionality is in technical preview and is ready for evaluation. Use with caution in production; it is not recommended for mission-critical workloads. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features. Specific Support terms apply.

Serverless interfaces and procedures might differ from classic Elastic Stack deployments.

Stack Preview

The Elastic Stack includes Elastic's core products such as Elasticsearch, Kibana, Logstash, and Beats.

Availability

  • Preview

    This functionality is in technical preview and is ready for evaluation. Use with caution in production; it is not recommended for mission-critical workloads. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features. Specific Support terms apply.

Unless stated otherwise on the page, this functionality is available when your Elastic Stack is deployed on Elastic Cloud Hosted, Elastic Cloud Enterprise, Elastic Cloud on Kubernetes, and self-managed environments.

This documentation corresponds to the latest patch available for each minor version. If you're not using the latest patch, check the release notes for changes.

Auth required Idempotent Scope: global
Shell
elastic stack es ml preview-datafeed [options]

Preview a datafeed.

Behaviour flags:

--dry-run — validate all inputs and exit without performing any action

--start string
The start time from where the datafeed preview should begin
--end string
The end time when the datafeed preview should stop
--datafeed-config string
The datafeed definition to preview.
--job-config string
The configuration details for the anomaly detection job that is associated with the datafeed. If the datafeed_config object does not include a job_id that references an existing anomaly detection job, you must supply this job_config object. If you include both a job_id and a job_config, the latter information is used. You cannot specify a job_config object unless you also supply a datafeed_config object.
--datafeed-id string
A numerical character string that uniquely identifies the datafeed. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters. NOTE: If you use this path parameter, you cannot provide datafeed or anomaly detection job configuration details in the request body.
--error-trace
When set to true Elasticsearch will include the full stack trace of errors when they occur.
--filter-path string

Comma-separated list of filters in dot notation which reduce the response returned by Elasticsearch.

Repeatable: pass --filter-path multiple times to supply more than one value

--human
When set to true will return statistics in a format suitable for humans. For example "exists_time": "1h" for humans and "exists_time_in_millis": 3600000 for computers. When disabled the human readable values will be omitted. This makes sense for responses being consumed only by machines.
--pretty
If set to true the returned JSON will be "pretty-formatted". Only use this option for debugging only.
--input-file string
path to a JSON file to use as command input
--dry-run
validate all inputs and exit without performing any action (preview changes without applying them)
--no-validate
skip input validation and send the request as-is
--output-fields string
comma-separated list of fields to include in output (dot-notation supported)
--output-template string
Mustache-like template for custom text output (e.g. "{{id}}: {{name}}")
--json

output as JSON