Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/831#discussion_r12824726
--- Diff: core/src/main/scala/org/apache/spark/rdd/RDD.scala ---
@@ -118,8 +118,25 @@ abstract class RDD[T: ClassTag](
// Methods and fields available on all RDDs
//
=======================================================================
+ /** Accessor method which throws a runtime exception if null. This lets
us have
+ a clearer error method when attempting to perform operations on an RDD
inside of
+ a parallel operation as the partitioner is marked as transient */
+ def getPartitioner: Option[Partitioner] = {
+ partitioner match {
+ case null => throw new SparkException("Actions on RDDs inside of
another RDD operation are " +
+ "not supported")
+ case _ => partitioner
+ }
+ }
+
/** The SparkContext that created this RDD. */
- def sparkContext: SparkContext = sc
+ def sparkContext: SparkContext = {
--- End diff --
Without the partitioner check, what error does it through? NPE? In that
case can this be handled by the lookup() function, rather than introducing a
non-intuitive check for partitioner?
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