Get data frame analytics jobs

GET /_cat/ml/data_frame/analytics/{id}
GET /_cat/ml/data_frame/analytics

Get configuration and usage information about data frame analytics jobs.

Important

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

Required authorization

Authentication

Api key

Authorization: <value>

Elasticsearch APIs support key-based authentication. You must create an API key and use the encoded value in the request header. For example:

		curl -X GET "${ES_URL}/_cat/indices?v=true" \
  -H "Authorization: ApiKey ${API_KEY}"

To get API keys, use the /_security/api_key APIs.

Basic

Authorization: Basic <credentials>

Bearer

Authorization: Bearer <token>

Elasticsearch APIs support the use of bearer tokens in the Authorization HTTP header to authenticate with the API. For examples, refer to Token-based authentication services

Path parameters

Query parameters

allow_no_match boolean · default: false

Whether to ignore if a wildcard expression matches no configs. (This includes _all string or when no configs have been specified.)

h union · default: create_time,id,state,type

Comma-separated list of column names to display.

Supported values include:

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

s union oneOf

Comma-separated list of column names or column aliases used to sort the response.

Supported values include:

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

One of: string[] or string

Response

application/json

Examples

Request Console 1 / 7 languages

Console Kibana Dev Tools

GET _cat/ml/data_frame/analytics?v=true&format=json

JavaScript Elasticsearch JavaScript Client

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

Python Elasticsearch Python Client

resp = client.cat.ml_data_frame_analytics(
    v=True,
    format="json",
)

curl Shell

curl -X GET "$ELASTICSEARCH_URL/_cat/ml/data_frame/analytics?v=true&format=json" \
  -H "Authorization: ApiKey $ELASTIC_API_KEY"

Java Elasticsearch Java Client

client.cat().mlDataFrameAnalytics();

PHP Elasticsearch PHP Client

$resp = $client->cat()->mlDataFrameAnalytics([
    "v" => "true",
    "format" => "json",
]);

Ruby Elasticsearch Ruby Client

response = client.cat.ml_data_frame_analytics(
  v: "true",
  format: "json"
)

Response

A successful response from GET _cat/ml/data_frame/analytics?v=true&format=json.

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