Forecast Job API

The Forecast Job API provides the ability to forecast a machine learning job’s behavior based on historical data. It accepts a ForecastJobRequest object and responds with a ForecastJobResponse object.

Forecast Job Request

A ForecastJobRequest object gets created with an existing non-null jobId. All other fields are optional for the request.

ForecastJobRequest forecastJobRequest = new ForecastJobRequest("forecasting-my-first-machine-learning-job"); 

Constructing a new request referencing an existing jobId

Optional Arguments

The following arguments are optional.

forecastJobRequest.setExpiresIn(TimeValue.timeValueHours(48)); 
forecastJobRequest.setDuration(TimeValue.timeValueHours(24)); 

Set when the forecast for the job should expire

Set how far into the future should the forecast predict

Forecast Job Response

A ForecastJobResponse contains an acknowledgement and the forecast ID

boolean isAcknowledged = forecastJobResponse.isAcknowledged(); 
String forecastId = forecastJobResponse.getForecastId(); 

isAcknowledged() indicates if the forecast was successful

getForecastId() provides the ID of the forecast that was created

Synchronous Execution

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

ForecastJobResponse forecastJobResponse = client.machineLearning().forecastJob(forecastJobRequest, 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

Executing a ForecastJobRequest 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 forecast-job method:

client.machineLearning().forecastJobAsync(forecastJobRequest, RequestOptions.DEFAULT, listener); 

The ForecastJobRequest 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 forecast-job looks like:

ActionListener<ForecastJobResponse> listener = new ActionListener<ForecastJobResponse>() {
    @Override
    public void onResponse(ForecastJobResponse forecastJobResponse) {
        
    }

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

Called when the execution is successfully completed.

Called when the whole ForecastJobRequest fails.