Get datafeeds API

Get datafeeds API

New API reference

For the most up-to-date API details, refer to Machine learning anomaly detection APIs.

Retrieves configuration information for datafeeds.

Request

GET _ml/datafeeds/<feed_id>

GET _ml/datafeeds/<feed_id>,<feed_id>

GET _ml/datafeeds/

GET _ml/datafeeds/_all

Prerequisites

Requires the monitor_ml cluster privilege. This privilege is included in the machine_learning_user built-in role.

Description

This API returns a maximum of 10,000 datafeeds.

Path parameters

<feed_id>

(Optional, string) Identifier for the datafeed. It can be a datafeed identifier or a wildcard expression.

You can get information for multiple datafeeds in a single API request by using a comma-separated list of datafeeds or a wildcard expression. You can get information for all datafeeds by using _all, by specifying * as the datafeed identifier, or by omitting the identifier.

Query parameters

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.

exclude_generated

(Optional, Boolean) Indicates if certain fields should be removed from the configuration on retrieval. This allows the configuration to be in an acceptable format to be retrieved and then added to another cluster. Default is false.

Response body

The API returns an array of datafeed resources. For the full list of properties, see create datafeeds API.

Response codes

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

resp = client.ml.get_datafeeds(
    datafeed_id="datafeed-high_sum_total_sales",
)
print(resp)

response = client.ml.get_datafeeds(
  datafeed_id: 'datafeed-high_sum_total_sales'
)
puts response

const response = await client.ml.getDatafeeds({
  datafeed_id: "datafeed-high_sum_total_sales",
});
console.log(response);

GET _ml/datafeeds/datafeed-high_sum_total_sales

The API returns the following results:

{
  "count" : 1,
  "datafeeds" : [
    {
      "datafeed_id" : "datafeed-high_sum_total_sales",
      "job_id" : "high_sum_total_sales",
      "authorization" : {
        "roles" : [
          "superuser"
        ]
      },
      "query_delay" : "93169ms",
      "chunking_config" : {
        "mode" : "auto"
      },
      "indices_options" : {
        "expand_wildcards" : [
          "open"
        ],
        "ignore_unavailable" : false,
        "allow_no_indices" : true,
        "ignore_throttled" : true
      },
      "query" : {
        "bool" : {
          "filter" : [
            {
              "term" : {
                "event.dataset" : "sample_ecommerce"
              }
            }
          ]
        }
      },
      "indices" : [
        "kibana_sample_data_ecommerce"
      ],
      "scroll_size" : 1000,
      "delayed_data_check_config" : {
        "enabled" : true
      }
    }
  ]
}