Delete expired data API
editDelete expired data API
editDeletes expired and unused machine learning data.
Prerequisites
editRequires the manage_ml cluster privilege. This privilege is included in the
machine_learning_admin built-in role.
Description
editDeletes 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
edit-
<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
edit-
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
editYou can also specify the query parameters (requests_per_second and
timeout) in the request body.
Examples
editresp = 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
}