Open anomaly detection jobs API

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Opens anomaly detection jobs in the cluster. It accepts a OpenJobRequest object and responds with a OpenJobResponse object.

Open anomaly detection jobs request

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An OpenJobRequest object gets created with an existing non-null jobId.

OpenJobRequest openJobRequest = new OpenJobRequest("opening-my-first-machine-learning-job"); 
openJobRequest.setTimeout(TimeValue.timeValueMinutes(10)); 

Constructing a new request referencing an existing jobId

Optionally setting the timeout value for how long the execution should wait for the job to be opened.

Open anomaly detection jobs response

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boolean isOpened = openJobResponse.isOpened(); 
String node = openJobResponse.getNode(); 

isOpened() from the OpenJobResponse is always true if the job was opened successfully. (An exception would be thrown instead if the job was not opened successfully.)

getNode() returns the node that the job was assigned to. If the job is allowed to open lazily and has not yet been assigned to a node then an empty string is returned. If getNode() returns null then the server is an old version that does not return node information.

Synchronous execution

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

OpenJobResponse openJobResponse = client.machineLearning().openJob(openJobRequest, 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 execution

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Executing a OpenJobRequest 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 open-job method:

client.machineLearning().openJobAsync(openJobRequest, RequestOptions.DEFAULT, listener); 

The OpenJobRequest 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 open-job looks like:

ActionListener<OpenJobResponse> listener = new ActionListener<OpenJobResponse>() {
    @Override
    public void onResponse(OpenJobResponse openJobResponse) {
        
    }

    @Override
    public void onFailure(Exception e) {
        
    }
};

Called when the execution is successfully completed.

Called when the whole OpenJobRequest fails.