Put Datafeed API
editPut Datafeed API
editThe Put Datafeed API can be used to create a new machine learning datafeed
in the cluster. The API accepts a PutDatafeedRequest
object
as a request and returns a PutDatafeedResponse
.
Put Datafeed Request
editA PutDatafeedRequest
requires the following argument:
Datafeed Configuration
editThe DatafeedConfig
object contains all the details about the machine learning datafeed
configuration.
A DatafeedConfig
requires the following arguments:
Optional Arguments
editThe following arguments are optional:
Synchronous Execution
editWhen executing a PutDatafeedRequest
in the following manner, the client waits
for the PutDatafeedResponse
to be returned before continuing with code execution:
PutDatafeedResponse response = client.machineLearning().putDatafeed(request, RequestOptions.DEFAULT);
Asynchronous Execution
editExecuting a PutDatafeedRequest
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 put-datafeed method:
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.
A typical listener for put-datafeed
looks like:
Response
editThe returned PutDatafeedResponse
returns the full representation of
the new machine learning datafeed if it has been successfully created. This will
contain the creation time and other fields initialized using
default values: