Delete expired data API

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Deletes expired and unused machine learning data.

Request

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DELETE _ml/_delete_expired_data

DELETE _ml/_delete_expired_data/<job_id>

Prerequisites

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Requires the manage_ml cluster privilege. This privilege is included in the machine_learning_admin built-in role.

Description

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Deletes all job results, model snapshots and forecast data that have exceeded their retention days period. Machine learning state documents that are not associated with any job are also deleted.

You can limit the request to a single or set of anomaly detection jobs by using a job identifier, a group name, a comma-separated list of jobs, or a wildcard expression. You can delete expired data for all anomaly detection jobs by using _all, by specifying * as the <job_id>, or by omitting the <job_id>.

Path parameters

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<job_id>
(Optional, string) Identifier for an anomaly detection job. It can be a job identifier, a group name, or a wildcard expression.

Query parameters

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requests_per_second
(Optional, float) The desired requests per second for the deletion processes. The default behavior is no throttling.
timeout
(Optional, string) How long can the underlying delete processes run until they are canceled. The default value is 8h (8 hours).

Request body

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You can also specify the query parameters (requests_per_second and timeout) in the request body.

Examples

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resp = client.ml.delete_expired_data(
    timeout="1h",
)
print(resp)
response = client.ml.delete_expired_data(
  timeout: '1h'
)
puts response
const response = await client.ml.deleteExpiredData({
  timeout: "1h",
});
console.log(response);
DELETE _ml/_delete_expired_data?timeout=1h

When the expired data is deleted, you receive the following response:

{
  "deleted": true
}