Get anomaly detection job results for buckets

POST also GET /_ml/anomaly_detectors/{job_id}/results/buckets/{timestamp}
POST also GET /_ml/anomaly_detectors/{job_id}/results/buckets

The API presents a chronological view of the records, grouped by bucket.

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

Request body

Response

application/json

buckets object[] required
count number required

Examples

Request Console 1 / 8 languages

An example body for a GET _ml/anomaly_detectors/low_request_rate/results/buckets request.

Console Kibana Dev Tools

POST _ml/anomaly_detectors/low_request_rate/results/buckets
{
  "anomaly_score": 80,
  "start": "1454530200001"
}

JavaScript Elasticsearch JavaScript Client

const response = await client.ml.getBuckets({
  job_id: "low_request_rate",
  anomaly_score: 80,
  start: 1454530200001,
});

Python Elasticsearch Python Client

resp = client.ml.get_buckets(
    job_id="low_request_rate",
    anomaly_score=80,
    start="1454530200001",
)

curl Shell

curl -X POST "$ELASTICSEARCH_URL/_ml/anomaly_detectors/low_request_rate/results/buckets" \
  -H "Authorization: ApiKey $ELASTIC_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "anomaly_score": 80,
    "start": "1454530200001"
  }'

Java Elasticsearch Java Client

client.ml().getBuckets(g -> g
    .anomalyScore(80.0D)
    .jobId("low_request_rate")
    .start(DateTime.of("1454530200001"))
);

C# Elasticsearch .NET Client

var response = await client.MachineLearning
    .GetBucketsAsync(new GetBucketsRequest()
    {
        JobId = "low_request_rate",
        AnomalyScore = 80d,
        Start = DateTimeOffset.Parse("2016-02-03T20:10:00.0010000+00:00", CultureInfo.InvariantCulture, DateTimeStyles.RoundtripKind)
    });

PHP Elasticsearch PHP Client

$resp = $client->ml()->getBuckets([
    "job_id" => "low_request_rate",
    "body" => [
        "anomaly_score" => 80,
        "start" => "1454530200001",
    ],
]);

Ruby Elasticsearch Ruby Client

response = client.ml.get_buckets(
  job_id: "low_request_rate",
  body: {
    "anomaly_score": 80,
    "start": "1454530200001"
  }
)

Response

No example

Required authorization

Authentication

Path parameters

Query parameters

Request body { }

Response

Request body