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https://issues.apache.org/jira/browse/SPARK-12834?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-12834:
------------------------------------
Assignee: Apache Spark
> Use type conversion instead of Ser/De of Pickle to transform JavaArray and
> JavaList
> -----------------------------------------------------------------------------------
>
> Key: SPARK-12834
> URL: https://issues.apache.org/jira/browse/SPARK-12834
> Project: Spark
> Issue Type: Improvement
> Reporter: Xusen Yin
> Assignee: Apache Spark
>
> According to the Ser/De code in Python side:
> {code:title=StringIndexerModel|theme=FadeToGrey|linenumbers=true|language=python|firstline=0001|collapse=false}
> def _java2py(sc, r, encoding="bytes"):
> if isinstance(r, JavaObject):
> clsName = r.getClass().getSimpleName()
> # convert RDD into JavaRDD
> if clsName != 'JavaRDD' and clsName.endswith("RDD"):
> r = r.toJavaRDD()
> clsName = 'JavaRDD'
> if clsName == 'JavaRDD':
> jrdd = sc._jvm.SerDe.javaToPython(r)
> return RDD(jrdd, sc)
> if clsName == 'DataFrame':
> return DataFrame(r, SQLContext.getOrCreate(sc))
> if clsName in _picklable_classes:
> r = sc._jvm.SerDe.dumps(r)
> elif isinstance(r, (JavaArray, JavaList)):
> try:
> r = sc._jvm.SerDe.dumps(r)
> except Py4JJavaError:
> pass # not pickable
> if isinstance(r, (bytearray, bytes)):
> r = PickleSerializer().loads(bytes(r), encoding=encoding)
> return r
> {code}
> We use SerDe.dumps to serialize JavaArray and JavaList in PythonMLLibAPI,
> then deserialize them with PickleSerializer in Python side. However, there is
> no need to transform them in such an inefficient way. Instead of it, we can
> use type conversion to convert them, e.g. list(JavaArray) or list(JavaList).
> What's more, there is an issue to Ser/De Scala Array as I said in
> https://issues.apache.org/jira/browse/SPARK-12780
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