Type to search.

stack es ml estimate-model-memory 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
Shell
elastic stack es ml estimate-model-memory [options]

Estimate job model memory usage.

Behaviour flags:

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

--analysis-config string
For a list of the properties that you can specify in the analysis_config component of the body of this API.
--max-bucket-cardinality string
Estimates of the highest cardinality in a single bucket that is observed for influencer fields over the time period that the job analyzes data. To produce a good answer, values must be provided for all influencer fields. Providing values for fields that are not listed as influencers has no effect on the estimation.
--overall-cardinality string
Estimates of the cardinality that is observed for fields over the whole time period that the job analyzes data. To produce a good answer, values must be provided for fields referenced in the by_field_name, over_field_name and partition_field_name of any detectors. Providing values for other fields has no effect on the estimation. It can be omitted from the request if no detectors have a by_field_name, over_field_name or partition_field_name.
--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