Get data frame analytics job configuration info Generally available

GET /_ml/data_frame/analytics/{id}

All methods and paths for this operation:

GET /_ml/data_frame/analytics

GET /_ml/data_frame/analytics/{id}

You can get information for multiple data frame analytics jobs in a single API request by using a comma-separated list of data frame analytics jobs or a wildcard expression.

Required authorization

  • Cluster privileges: monitor_ml

Path parameters

  • id string Required

    Identifier for the data frame analytics job. If you do not specify this option, the API returns information for the first hundred data frame analytics jobs.

Query parameters

  • allow_no_match boolean

    Specifies what to do when the request:

    1. Contains wildcard expressions and there are no data frame analytics jobs that match.
    2. Contains the _all string or no identifiers and there are no matches.
    3. Contains wildcard expressions and there are only partial matches.

    The default value returns an empty data_frame_analytics 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.

  • from number

    Skips the specified number of data frame analytics jobs.

  • size number

    Specifies the maximum number of data frame analytics jobs to obtain.

  • exclude_generated 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.

Responses

  • 200 application/json
    Hide response attributes Show response attributes object
    • count number Required
    • data_frame_analytics array[object] Required

      An array of data frame analytics job resources, which are sorted by the id value in ascending order.

      Hide data_frame_analytics attributes Show data_frame_analytics attributes object
      • allow_lazy_start boolean
      • analysis object Required
        Hide analysis attribute Show analysis attribute object
        • outlier_detection object

          The configuration information necessary to perform outlier detection. NOTE: Advanced parameters are for fine-tuning classification analysis. They are set automatically by hyperparameter optimization to give the minimum validation error. It is highly recommended to use the default values unless you fully understand the function of these parameters.

      • analyzed_fields object
        Hide analyzed_fields attributes Show analyzed_fields attributes object
        • includes array[string]

          An array of strings that defines the fields that will be excluded from the analysis. You do not need to add fields with unsupported data types to excludes, these fields are excluded from the analysis automatically.

        • excludes array[string]

          An array of strings that defines the fields that will be included in the analysis.

      • authorization object

        The security privileges that the job uses to run its queries. If Elastic Stack security features were disabled at the time of the most recent update to the job, this property is omitted.

        Hide authorization attributes Show authorization attributes object
        • api_key object

          If an API key was used for the most recent update to the job, its name and identifier are listed in the response.

        • roles array[string]

          If a user ID was used for the most recent update to the job, its roles at the time of the update are listed in the response.

        • service_account string

          If a service account was used for the most recent update to the job, the account name is listed in the response.

      • create_time number

        Time unit for milliseconds

      • description string
      • dest object Required
        Hide dest attributes Show dest attributes object
        • index string Required

          Defines the destination index to store the results of the data frame analytics job.

        • results_field string

          Defines the name of the field in which to store the results of the analysis. Defaults to ml.

      • id string Required
      • max_num_threads number
      • model_memory_limit string
      • source object Required
        Hide source attributes Show source attributes object
        • index string | array[string] Required

          Index or indices on which to perform the analysis. It can be a single index or index pattern as well as an array of indices or patterns. NOTE: If your source indices contain documents with the same IDs, only the document that is indexed last appears in the destination index.

        • runtime_mappings object

          Definitions of runtime fields that will become part of the mapping of the destination index.

        • _source object

          Specify includes and/or `excludes patterns to select which fields will be present in the destination. Fields that are excluded cannot be included in the analysis.

        • query object

          The Elasticsearch query domain-specific language (DSL). This value corresponds to the query object in an Elasticsearch search POST body. All the options that are supported by Elasticsearch can be used, as this object is passed verbatim to Elasticsearch. By default, this property has the following value: {"match_all": {}}.

          Query DSL
      • version string
      • _meta object
        Hide _meta attribute Show _meta attribute object
        • * object Additional properties
GET /_ml/data_frame/analytics/{id}
GET _ml/data_frame/analytics/loganalytics
resp = client.ml.get_data_frame_analytics(
    id="loganalytics",
)
const response = await client.ml.getDataFrameAnalytics({
  id: "loganalytics",
});
response = client.ml.get_data_frame_analytics(
  id: "loganalytics"
)
$resp = $client->ml()->getDataFrameAnalytics([
    "id" => "loganalytics",
]);
curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" "$ELASTICSEARCH_URL/_ml/data_frame/analytics/loganalytics"
client.ml().getDataFrameAnalytics(g -> g
    .id("loganalytics")
);