Put datafeed API
editPut datafeed API
editCreates 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:
datafeedBuilder.setDelayedDataCheckConfig(DelayedDataCheckConfig .enabledDelayedDataCheckConfig(TimeValue.timeValueHours(1)));
Sets the delayed data check configuration.
The window must be larger than the Job’s bucket size, but smaller than 24 hours,
and span less than 10,000 buckets.
Defaults to |
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);
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
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. Failure scenarios and expected exceptions are the same as in the
synchronous execution case.
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: