The Flush Job API provides the ability to flush a machine learning job’s
datafeed in the cluster.
It accepts a
FlushJobRequest object and responds
FlushJobRequest object gets created with an existing non-null
All other fields are optional for the request.
The following arguments are optional.
Set request to calculate the interim results
Set the advanced time to flush to the particular time value
Set the start time for the range of buckets on which
to calculate the interim results (requires
Set the end time for the range of buckets on which
to calculate interim results (requires
Set the skip time to skip a particular time value
FlushJobResponse contains an acknowledgement and an optional end date for the
last finalized bucket
When executing a
FlushJobRequest in the following manner, the client waits
FlushJobResponse to be returned before continuing with code execution:
FlushJobResponse flushJobResponse = client.machineLearning().flushJob(flushJobRequest, 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
5xx error code, the high-level
client tries to parse the response body error details instead and then throws
ElasticsearchException and adds the original
ResponseException as a
suppressed exception to it.
FlushJobRequest 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 flush-job method:
The asynchronous method does not block and returns immediately. Once it is
ActionListener is called back using the
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
flush-job looks like: