Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/363#discussion_r11426010
--- Diff: core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
---
@@ -284,6 +286,42 @@ private[spark] object PythonRDD {
file.close()
}
+ def pythonToJava(pyRDD: JavaRDD[Array[Byte]]): JavaRDD[_] = {
+ pyRDD.rdd.mapPartitions { iter =>
+ val unpickle = new Unpickler
+ // TODO: Figure out why flatMap is necessay for pyspark
+ iter.flatMap { row =>
+ unpickle.loads(row) match {
+ case objs: java.util.ArrayList[Any] => objs
+ // Incase the partition doesn't have a collection
+ case obj => Seq(obj)
+ }
+ }
+ }
+ }
+
+ def pythonToJavaMap(pyRDD: JavaRDD[Array[Byte]]): JavaRDD[Map[String,
_]] = {
+ pyRDD.rdd.mapPartitions { iter =>
+ val unpickle = new Unpickler
+ // TODO: Figure out why flatMap is necessay for pyspark
+ iter.flatMap { row =>
+ unpickle.loads(row) match {
+ case objs: java.util.ArrayList[JMap[String, _]] =>
objs.map(_.toMap)
--- End diff --
Probably use `@unchecked` here:
- `java.util.ArrayList[JMap[String, _] @unchecked]`
- `JMap[String @unchecked, _] => Seq(obj.toMap)`
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