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cat data frame analytics API

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cat data frame analytics API

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cat APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications. For application consumption, use the get data frame analytics jobs statistics API.

Returns configuration and usage information about data frame analytics jobs.

Request

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GET /_cat/ml/data_frame/analytics/<data_frame_analytics_id>

GET /_cat/ml/data_frame/analytics

Prerequisites

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If the Elasticsearch security features are enabled, you must have the following privileges:

cluster: monitor_ml

For more information, see Security privileges and Machine learning security privileges.

Path parameters

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<data_frame_analytics_id>: (Optional, string) 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

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format

(Optional, string) Short version of the HTTP accept header. Valid values include JSON, YAML, etc.

h

(Optional, string) Comma-separated list of column names to display.

If you do not specify which columns to include, the API returns the default columns. If you explicitly specify one or more columns, it returns only the specified columns.

Valid columns are:

assignment_explanation, ae: Contains messages relating to the selection of a node.
create_time, ct, createTime: (Default) The time when the data frame analytics job was created.
description, d: A description of the job.
dest_index, di, destIndex: Name of the destination index.
failure_reason, fr, failureReason: Contains messages about the reason why a data frame analytics job failed.
id: (Default) Identifier for the data frame analytics job.
model_memory_limit, mml, modelMemoryLimit: The approximate maximum amount of memory resources that are permitted for the data frame analytics job.
node.address, na, nodeAddress: The network address of the node that the data frame analytics job is assigned to.
node.ephemeral_id, ne, nodeEphemeralId: The ephemeral ID of the node that the data frame analytics job is assigned to.
node.id, ni, nodeId: The unique identifier of the node that the data frame analytics job is assigned to.
node.name, nn, nodeName: The name of the node that the data frame analytics job is assigned to.
progress, p: The progress report of the data frame analytics job by phase.
source_index, si, sourceIndex: Name of the source index.
state, s: (Default) Current state of the data frame analytics job.
type, t: (Default) The type of analysis that the data frame analytics job performs.
version, v: The Elasticsearch version number in which the data frame analytics job was created.

help

(Optional, Boolean) If true, the response includes help information. Defaults to false.

s

(Optional, string) Comma-separated list of column names or column aliases used to sort the response.

time

(Optional, time units) Unit used to display time values.

v

(Optional, Boolean) If true, the response includes column headings. Defaults to false.

Examples

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resp = client.cat.ml_data_frame_analytics(
    v=True,
)
print(resp)

response = client.cat.ml_data_frame_analytics(
  v: true
)
puts response

const response = await client.cat.mlDataFrameAnalytics({
  v: "true",
});
console.log(response);

GET _cat/ml/data_frame/analytics?v=true

id               create_time              type             state
classifier_job_1 2020-02-12T11:49:09.594Z classification stopped
classifier_job_2 2020-02-12T11:49:14.479Z classification stopped
classifier_job_3 2020-02-12T11:49:16.928Z classification stopped
classifier_job_4 2020-02-12T11:49:19.127Z classification stopped
classifier_job_5 2020-02-12T11:49:21.349Z classification stopped

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