Get machine learning info APIedit

Provides defaults and limits used internally by machine learning. These may be useful to a user interface that needs to interpret machine learning configurations where certain fields are missing because the end user was happy with the default value.

It accepts a MlInfoRequest object and responds with a MlInfoResponse object.

Get machine learning info requestedit

MlInfoRequest request = new MlInfoRequest(); 

Constructing a new request.

Get machine learning info responseedit

final Map<String, Object> info = response.getInfo();

info from the MlInfoResponse contains machine learning info details.

Synchronous executionedit

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

MlInfoResponse response = client.machineLearning()
    .getMlInfo(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 MlInfoRequest 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-ml-info method:

    .getMlInfoAsync(request, RequestOptions.DEFAULT, listener); 

The MlInfoRequest 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-ml-info looks like:

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

    public void onFailure(Exception e) {

Called when the execution is successfully completed.

Called when the whole MlInfoRequest fails.