Github user sun-rui commented on a diff in the pull request:
https://github.com/apache/spark/pull/14775#discussion_r76007335
--- Diff: R/pkg/NAMESPACE ---
@@ -363,4 +363,9 @@ S3method(structField, jobj)
S3method(structType, jobj)
S3method(structType, structField)
+export("newJObject")
+export("callJMethod")
+export("callJStatic")
+export("cleanup.jobj")
--- End diff --
I am a little confused about the discussion at
https://issues.apache.org/jira/browse/SPARK-16611:
````
d) cleanup.jobj:
SystemML uses the MLContext and matrixCharacteristic class that is
instantiated in JVM and whose object ref is kept alive in the sparkR and
later when systemML has done itâs computation. we cleanup the objects. The
way we achieve it using the References classes in R and use itâs finalize
method to register the cleanup.jobj once we have created the jobj via
newJObject(âsysml.classâ)
````
It seems that systemML still uses automatic GC to cleanup jobjs as it is
said that "use itâs finalize method to register the cleanup.jobj ". But a
jobj already has cleanup.jobj registered as its finalizer.
If my understanding is correct, I don't see strong reason for exposing
cleanup.jobj. If active cleanup is demanded, a call to "gc" can be made?
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