Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/11621#discussion_r57661783
--- Diff: python/pyspark/ml/wrapper.py ---
@@ -190,8 +190,30 @@ def _transform(self, dataset):
return DataFrame(self._java_obj.transform(dataset._jdf),
dataset.sql_ctx)
+class JavaCallable(object):
--- End diff --
`JavaWrapper` does define a java object wrapper variable, but also does
more since it is derived from `Params`. Since I need to wrap a Java Summary
object (which is just a plain Java object), it doesn't really make sense to use
it unless we want to change that.
Actually, I think it might make more sense to have `JavaWrapper` inherit
from `JavaCallable` and only define `_java_obj` there. Then rename the classes
a little like this to better reflect what they are for:
`JavaCallable(object)` -> `JavaWrapper(object)`
and
`JavaWrapper(Params)` -> `JavaParamWrapper(JavaWrapper, Params)`
That might be better done in another JIRA though, because of the name change
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