Get anomaly detection jobs APIedit

Retrieves configuration information for anomaly detection jobs in the cluster. It accepts a GetJobRequest object and responds with a GetJobResponse object.

Get anomaly detection jobs requestedit

A GetJobRequest object gets can have any number of jobId or groupName entries. However, they all must be non-null. An empty list is the same as requesting for all anomaly detection jobs.

GetJobRequest request = new GetJobRequest("get-machine-learning-job1", "get-machine-learning-job*"); 

Constructing a new request referencing existing jobIds. It can contain wildcards.

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

Optional boolean value for requesting the job in a format that can then be put into another cluster. Certain fields that can only be set when the job is created are removed.

Get anomaly detection jobs responseedit

long numberOfJobs = response.count(); 
List<Job> jobs =; 

getCount() from the GetJobResponse indicates the number of jobs found.

getJobs() is the collection of machine learning Job objects found.

Synchronous executionedit

When executing a GetJobRequest in the following manner, the client waits for the GetJobResponse to be returned before continuing with code execution:

GetJobResponse response = client.machineLearning().getJob(request, RequestOptions.DEFAULT);

Synchronous calls may throw an IOException in case of either failing to parse the REST response in the high-level REST client, the request times out or similar cases where there is no response coming back from the server.

In cases where the server returns a 4xx or 5xx error code, the high-level client tries to parse the response body error details instead and then throws a generic ElasticsearchException and adds the original ResponseException as a suppressed exception to it.

Asynchronous executionedit

Executing a GetJobRequest can also be done in an asynchronous fashion so that the client can return directly. Users need to specify how the response or potential failures will be handled by passing the request and a listener to the asynchronous get-job method:

client.machineLearning().getJobAsync(request, RequestOptions.DEFAULT, listener); 

The GetJobRequest to execute and the ActionListener to use when the execution completes

The asynchronous method does not block and returns immediately. Once it is completed the ActionListener is called back using the onResponse method if the execution successfully completed or using the onFailure method if it failed. Failure scenarios and expected exceptions are the same as in the synchronous execution case.

A typical listener for get-job looks like:

ActionListener<GetJobResponse> listener = new ActionListener<GetJobResponse>() {
    public void onResponse(GetJobResponse response) {

    public void onFailure(Exception e) {

Called when the execution is successfully completed.

Called when the whole GetJobRequest fails.