The Update Filter API can be used to update an existing machine learning filter
in the cluster. The API accepts a
as a request and returns a
UpdateFilterRequest requires the following argument:
The following arguments are optional:
When executing a
UpdateFilterRequest in the following manner, the client waits
PutFilterResponse to be returned before continuing with code execution:
PutFilterResponse response = client.machineLearning().updateFilter(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
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.
UpdateFilterRequest 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 update-filter 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
update-filter looks like:
PutFilterResponse returns the full representation of
the updated machine learning filter if it has been successfully updated.