Get anomaly detection job results for categories

POST also GET /_ml/anomaly_detectors/{job_id}/results/categories/{category_id}
POST also GET /_ml/anomaly_detectors/{job_id}/results/categories

Auth

Required authorization

Cluster privileges monitor_ml

Path parameters

job_id string required

Identifier for the anomaly detection job.

category_id number optional

Identifier for the category, which is unique in the job. If you specify neither the category ID nor the partition_field_value, the API returns information about all categories. If you specify only the partition_field_value, it returns information about all categories for the specified partition.

Leave it out to use /_ml/anomaly_detectors/{job_id}/results/categories.

Query parameters

from number · default: 0: Skips the specified number of categories.
partition_field_value string: Only return categories for the specified partition.
size number · default: 100: Specifies the maximum number of categories to obtain.

Request body

page object: Configures pagination. This parameter has the from and size properties.

Response

application/json

categories object[] required
count number required

Examples

Request Console 1 / 8 languages

An example body for a GET _ml/anomaly_detectors/esxi_log/results/categories request.

Console Kibana Dev Tools

POST _ml/anomaly_detectors/esxi_log/results/categories
{
  "page":{
    "size": 1
  }
}

JavaScript Elasticsearch JavaScript Client

const response = await client.ml.getCategories({
  job_id: "esxi_log",
  page: {
    size: 1,
  },
});

Python Elasticsearch Python Client

resp = client.ml.get_categories(
    job_id="esxi_log",
    page={
        "size": 1
    },
)

curl Shell

curl -X POST "$ELASTICSEARCH_URL/_ml/anomaly_detectors/esxi_log/results/categories" \
  -H "Authorization: ApiKey $ELASTIC_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "page": {
      "size": 1
    }
  }'

Java Elasticsearch Java Client

client.ml().getCategories(g -> g
    .jobId("esxi_log")
    .page(p -> p
        .size(1)
    )
);

C# Elasticsearch .NET Client

var response = await client.MachineLearning
    .GetCategoriesAsync(new GetCategoriesRequest()
    {
        JobId = "esxi_log",
        Page = new()
        {
            Size = 1
        }
    });

PHP Elasticsearch PHP Client

$resp = $client->ml()->getCategories([
    "job_id" => "esxi_log",
    "body" => [
        "page" => [
            "size" => 1,
        ],
    ],
]);

Ruby Elasticsearch Ruby Client

response = client.ml.get_categories(
  job_id: "esxi_log",
  body: {
    "page": {
      "size": 1
    }
  }
)

Response

{
  "categories": [
    {
      "category_id": 0,
      "examples": [
        "string"
      ],
      "grok_pattern": "string",
      "job_id": "string",
      "max_matching_length": 0,
      "partition_field_name": "string",
      "partition_field_value": "string",
      "regex": "string",
      "terms": "string",
      "num_matches": 0,
      "preferred_to_categories": [
        "string"
      ],
      "p": "string",
      "result_type": "string",
      "mlcategory": "string"
    }
  ],
  "count": 0
}

Generated from the API spec