Start datafeeds API

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Start datafeeds API

Starts a machine learning datafeed in the cluster. It accepts a StartDatafeedRequest object and responds with a StartDatafeedResponse object.

Start datafeeds request

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A StartDatafeedRequest object is created referencing a non-null datafeedId. All other fields are optional for the request.

StartDatafeedRequest request = new StartDatafeedRequest(datafeedId);

Constructing a new request referencing an existing datafeedId.

Optional arguments

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The following arguments are optional.

request.setEnd("2018-08-21T00:00:00Z"); 
request.setStart("2018-08-20T00:00:00Z"); 
request.setTimeout(TimeValue.timeValueMinutes(10));

	Set when the datafeed should end, the value is exclusive. May be an epoch seconds, epoch millis or an ISO 8601 string. "now" is a special value that indicates the current time. If you do not specify an end time, the datafeed runs continuously.
	Set when the datafeed should start, the value is inclusive. May be an epoch seconds, epoch millis or an ISO 8601 string. If you do not specify a start time and the datafeed is associated with a new job, the analysis starts from the earliest time for which data is available.
	Set the timeout for the request

Start datafeeds response

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boolean started = response.isStarted(); 
String node = response.getNode();

	`isStarted()` from the `StartDatafeedResponse` is always `true` if the datafeed was started successfully. (An exception would be thrown instead if the datafeed was not started successfully.)
	`getNode()` returns the node that the datafeed was assigned to. If the datafeed 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 StartDatafeedRequest in the following manner, the client waits for the StartDatafeedResponse to be returned before continuing with code execution:

StartDatafeedResponse response = client.machineLearning().startDatafeed(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 execution

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Executing a StartDatafeedRequest 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 start-datafeed method:

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

The StartDatafeedRequest 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 start-datafeed looks like:

ActionListener<StartDatafeedResponse> listener = new ActionListener<StartDatafeedResponse>() {
    @Override
    public void onResponse(StartDatafeedResponse response) {
        
    }

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

	Called when the execution is successfully completed.
	Called when the whole `StartDatafeedRequest` fails.

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