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Elastic Docs ›Elasticsearch Guide [master] ›REST APIs ›Machine learning anomaly detection APIs

Stop datafeeds API

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Stop datafeeds API

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Stops one or more datafeeds.

Request

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POST _ml/datafeeds/<feed_id>/_stop

POST _ml/datafeeds/<feed_id>,<feed_id>/_stop

POST _ml/datafeeds/_all/_stop

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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A datafeed that is stopped ceases to retrieve data from Elasticsearch. A datafeed can be started and stopped multiple times throughout its lifecycle.

Path parameters

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<feed_id>
(Required, string) Identifier for the datafeed. You can stop multiple datafeeds in a single API request by using a comma-separated list of datafeeds or a wildcard expression. You can close all datafeeds by using _all or by specifying * as the identifier.

Query parameters

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allow_no_match

(Optional, Boolean) Specifies what to do when the request:

  • Contains wildcard expressions and there are no datafeeds that match.
  • Contains the _all string or no identifiers and there are no matches.
  • Contains wildcard expressions and there are only partial matches.

The default value is true, which returns an empty datafeeds array when there are no matches and the subset of results when there are partial matches. If this parameter is false, the request returns a 404 status code when there are no matches or only partial matches.

force
(Optional, Boolean) If true, the datafeed is stopped forcefully.
timeout
(Optional, time) Specifies the amount of time to wait until a datafeed stops. The default value is 20 seconds.

Request body

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You can also specify the query parameters (such as allow_no_match and force) in the request body.

Response codes

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404 (Missing resources)
If allow_no_match is false, this code indicates that there are no resources that match the request or only partial matches for the request.

Examples

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resp = client.ml.stop_datafeed(
    datafeed_id="datafeed-low_request_rate",
    timeout="30s",
)
print(resp)
response = client.ml.stop_datafeed(
  datafeed_id: 'datafeed-low_request_rate',
  body: {
    timeout: '30s'
  }
)
puts response
const response = await client.ml.stopDatafeed({
  datafeed_id: "datafeed-low_request_rate",
  timeout: "30s",
});
console.log(response);
POST _ml/datafeeds/datafeed-low_request_rate/_stop
{
  "timeout": "30s"
}

When the datafeed stops, you receive the following results:

{
  "stopped": true
}
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