Get machine learning info API
editGet machine learning info API
editProvides 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 MlInfoResponse
object.
Get machine learning info request
editGet machine learning info response
editSynchronous execution
editWhen executing a MlInfoRequest
in the following manner, the client waits
for the 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 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 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
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 get-ml-info
looks like: