IMPORTANT: No additional bug fixes or documentation updates
will be released for this version. For the latest information, see the
current release documentation.
Open anomaly detection jobs API
editOpen anomaly detection jobs API
editOpens one or more anomaly detection jobs.
Request
editPOST _ml/anomaly_detectors/{job_id}/_open
Prerequisites
editRequires the manage_ml cluster privilege. This privilege is included in the
machine_learning_admin built-in role.
Description
editAn anomaly detection job must be opened in order for it to be ready to receive and analyze data. It can be opened and closed multiple times throughout its lifecycle.
When you open a new job, it starts with an empty model.
When you open an existing job, the most recent model state is automatically loaded. The job is ready to resume its analysis from where it left off, once new data is received.
Path parameters
edit-
<job_id> - (Required, string) Identifier for the anomaly detection job.
Query parameters
edit-
timeout - (Optional, time) Controls the time to wait until a job has opened. The default value is 30 minutes.
Request body
editYou can also specify the timeout query parameter in the request body.
Response body
edit-
node - (string) The ID of the node that the job was opened on. If the job is allowed to open lazily and has not yet been assigned to a node, this value is an empty string.
-
opened -
(Boolean) For a successful response, this value is always
true. On failure, an exception is returned instead.
Examples
editresp = client.ml.open_job(
job_id="low_request_rate",
timeout="35m",
)
print(resp)
const response = await client.ml.openJob({
job_id: "low_request_rate",
timeout: "35m",
});
console.log(response);
POST _ml/anomaly_detectors/low_request_rate/_open
{
"timeout": "35m"
}
When the job opens, you receive the following results:
{
"opened" : true,
"node" : "node-1"
}