Github user JoshRosen commented on a diff in the pull request:
https://github.com/apache/spark/pull/1598#discussion_r15670058
--- Diff: core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
---
@@ -701,6 +682,53 @@ private[spark] object PythonRDD extends Logging {
}
}
+
+ /**
+ * Convert an RDD of serialized Python dictionaries to Scala Maps (no
recursive conversions).
+ * This function is outdated, PySpark does not use it anymore
+ */
+ def pythonToJavaMap(pyRDD: JavaRDD[Array[Byte]]): JavaRDD[Map[String,
_]] = {
+ pyRDD.rdd.mapPartitions { iter =>
+ val unpickle = new Unpickler
+ iter.flatMap { row =>
+ unpickle.loads(row) match {
+ // in case of objects are pickled in batch mode
+ case objs: JArrayList[JMap[String, _] @unchecked] =>
objs.map(_.toMap)
+ // not in batch mode
+ case obj: JMap[String @unchecked, _] => Seq(obj.toMap)
+ }
+ }
+ }
+ }
+
+ /**
+ * Convert an RDD of serialized Python tuple to Array (no recursive
conversions).
+ * It is only used by pyspark.sql.
+ */
+ def pythonToJava(pyRDD: JavaRDD[Array[Byte]]): JavaRDD[Array[_]] = {
+ pyRDD.rdd.mapPartitions { iter =>
+ val unpickle = new Unpickler
+ iter.flatMap { row =>
+ unpickle.loads(row) match {
+ // in case of objects are pickled in batch mode
+ case objs: JArrayList[_] => Try(objs.map(obj => obj match {
--- End diff --
Does this behave properly in the unbatched case? In general, I don't think
that it's safe to detect batching by checking whether the returned item is a
list, since that might inadvertently flatten a list-of-lists that was
serialized without batching.
(see https://github.com/apache/spark/pull/1338#discussion-diff-15508664)
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