---
type: api
title: Close anomaly detection jobs
description: A job can be opened and closed multiple times throughout its lifecycle. A closed job cannot receive data or perform analysis operations, but you can still explore and navigate results.
url: https://www.elastic.co/elastic/docs-builder/docs/4371/api/doc/elasticsearch/v9/operation/operation-ml-close-job
resource: https://www.elastic.co/elastic/docs-builder/docs/4371/api/doc/elasticsearch/v9/operation/operation-ml-close-job
products:
  - Elasticsearch
---

# Close anomaly detection jobs

Availability: 5.4+

## Paths

- `POST` `/_ml/anomaly_detectors/{job_id}/_close`

- [Api key auth](/elastic/docs-builder/docs/4371/api/doc/elasticsearch/v9/authentication#apikeyauth)
- [Basic auth](/elastic/docs-builder/docs/4371/api/doc/elasticsearch/v9/authentication#basicauth)
- [Bearer auth](/elastic/docs-builder/docs/4371/api/doc/elasticsearch/v9/authentication#bearerauth)

#### Path Parameters

- `job_id` (string Id)
  Identifier for the anomaly detection job. It can be a job identifier, a group name, or a wildcard expression. You can close multiple anomaly detection jobs in a single API request by using a group name, a comma-separated list of jobs, or a wildcard expression. You can close all jobs by using `_all` or by specifying `*` as the job identifier.

## Description

A job can be opened and closed multiple times throughout its lifecycle. A closed job cannot receive data or perform analysis operations, but you can still explore and navigate results.
When you close a job, it runs housekeeping tasks such as pruning the model history, flushing buffers, calculating final results and persisting the model snapshots. Depending upon the size of the job, it could take several minutes to close and the equivalent time to re-open. After it is closed, the job has a minimal overhead on the cluster except for maintaining its meta data. Therefore it is a best practice to close jobs that are no longer required to process data.
If you close an anomaly detection job whose datafeed is running, the request first tries to stop the datafeed. This behavior is equivalent to calling stop datafeed API with the same timeout and force parameters as the close job request.
When a datafeed that has a specified end date stops, it automatically closes its associated job.

## Required authorization

* Cluster privileges: `manage_ml`

## Query String Parameters

- `allow_no_match` (boolean · default: true)
  Specifies what to do when the request: contains wildcard expressions and there are no jobs that match; contains the  `_all` string or no identifiers and there are no matches; or contains wildcard expressions and there are only partial matches. By default, it returns an empty jobs array when there are no matches and the subset of results when there are partial matches.
If `false`, the request returns a 404 status code when there are no matches or only partial matches.
- `force` (boolean · default: false)
  Use to close a failed job, or to forcefully close a job which has not responded to its initial close request; the request returns without performing the associated actions such as flushing buffers and persisting the model snapshots.
If you want the job to be in a consistent state after the close job API returns, do not set to `true`. This parameter should be used only in situations where the job has already failed or where you are not interested in results the job might have recently produced or might produce in the future.
- `timeout` (string Duration · default: 30m)
  Controls the time to wait until a job has closed.

## Request Body

`application/json`

- `allow_no_match` (boolean · default: true) — optional
  Refer to the description for the `allow_no_match` query parameter.
- `force` (boolean · default: false) — optional
  Refer to the descriptiion for the `force` query parameter.
- `timeout` (string Duration · default: 30m) — optional
  Refer to the description for the `timeout` query parameter.

## Response

`application/json`

- `closed` (boolean)
## Code Examples

#### Console

```console
POST _ml/anomaly_detectors/low_request_rate/_close
```

#### JavaScript

```javascript
const response = await client.ml.closeJob({
  job_id: "low_request_rate",
});
```

#### Python

```python
resp = client.ml.close_job(
    job_id="low_request_rate",
)
```

#### curl

```curl
curl -X POST "$ELASTICSEARCH_URL/_ml/anomaly_detectors/low_request_rate/_close" \
  -H "Authorization: ApiKey $ELASTIC_API_KEY"
```

#### Java

```java
client.ml().closeJob(c -> c
    .jobId("low_request_rate")
);
```

#### C#

```c#
var response = await client.MachineLearning.CloseJobAsync(jobId: "low_request_rate");
```

#### PHP

```php
$resp = $client->ml()->closeJob([
    "job_id" => "low_request_rate",
]);
```

#### Ruby

```ruby
response = client.ml.close_job(
  job_id: "low_request_rate"
)
```

## Response Examples

#### Ml close job response example1

A successful response when closing anomaly detection jobs.

```json
{
  "closed": true
}
```