The ML Get API provides defaults and limits used internally by machine learning. These may be useful to a user interface that needs to interpret machine learning configurations where certain fields are missing because the end user was happy with the default value.
It accepts a
MlInfoRequest object and responds with a
When executing a
MlInfoRequest in the following manner, the client waits
MlInfoResponse to be returned before continuing with code execution:
MlInfoResponse response = client.machineLearning() .getMlInfo(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.
MlInfoRequest 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 get-ml-info 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
get-ml-info looks like: