Force buffered data to be processed Generally available; Added in 5.4.0

POST /_ml/anomaly_detectors/{job_id}/_flush
Api key auth Basic auth Bearer auth

The flush jobs API is only applicable when sending data for analysis using the post data API. Depending on the content of the buffer, then it might additionally calculate new results. Both flush and close operations are similar, however the flush is more efficient if you are expecting to send more data for analysis. When flushing, the job remains open and is available to continue analyzing data. A close operation additionally prunes and persists the model state to disk and the job must be opened again before analyzing further data.

Required authorization

  • Cluster privileges: manage_ml

Path parameters

  • job_id string Required

    Identifier for the anomaly detection job.

Query parameters

  • advance_time string | number

    Specifies to advance to a particular time value. Results are generated and the model is updated for data from the specified time interval.

  • calc_interim boolean

    If true, calculates the interim results for the most recent bucket or all buckets within the latency period.

  • end string | number

    When used in conjunction with calc_interim and start, specifies the range of buckets on which to calculate interim results.

  • skip_time string | number

    Specifies to skip to a particular time value. Results are not generated and the model is not updated for data from the specified time interval.

  • start string | number

    When used in conjunction with calc_interim, specifies the range of buckets on which to calculate interim results.

application/json

Body

  • advance_time string | number

    Refer to the description for the advance_time query parameter.

    One of:
    string-1 string UnitMillis number

    Refer to the description for the advance_time query parameter.

    Refer to the description for the advance_time query parameter.

  • calc_interim boolean

    Refer to the description for the calc_interim query parameter.

  • end string | number

    Refer to the description for the end query parameter.

    One of:
    string-1 string UnitMillis number

    Refer to the description for the end query parameter.

    Refer to the description for the end query parameter.

  • skip_time string | number

    Refer to the description for the skip_time query parameter.

    One of:
    string-1 string UnitMillis number

    Refer to the description for the skip_time query parameter.

    Refer to the description for the skip_time query parameter.

  • start string | number

    Refer to the description for the start query parameter.

    One of:
    string-1 string UnitMillis number

    Refer to the description for the start query parameter.

    Refer to the description for the start query parameter.

Responses

  • 200 application/json
    Hide response attributes Show response attributes object
    • flushed boolean Required
    • last_finalized_bucket_end number

      Provides the timestamp (in milliseconds since the epoch) of the end of the last bucket that was processed.
POST /_ml/anomaly_detectors/{job_id}/_flush 
POST _ml/anomaly_detectors/low_request_rate/_flush
{
  "calc_interim": true
}
resp = client.ml.flush_job(
    job_id="low_request_rate",
    calc_interim=True,
)
const response = await client.ml.flushJob({
  job_id: "low_request_rate",
  calc_interim: true,
});
response = client.ml.flush_job(
  job_id: "low_request_rate",
  body: {
    "calc_interim": true
  }
)
$resp = $client->ml()->flushJob([
    "job_id" => "low_request_rate",
    "body" => [
        "calc_interim" => true,
    ],
]);
curl -X POST -H "Authorization: ApiKey $ELASTIC_API_KEY" -H "Content-Type: application/json" -d '{"calc_interim":true}' "$ELASTICSEARCH_URL/_ml/anomaly_detectors/low_request_rate/_flush"
client.ml().flushJob(f -> f
    .calcInterim(true)
    .jobId("low_request_rate")
);
Request example
An example body for a `POST _ml/anomaly_detectors/low_request_rate/_flush` request. 
{
  "calc_interim": true
}