Github user mateiz commented on a diff in the pull request:
https://github.com/apache/spark/pull/1447#discussion_r15042905
--- Diff: core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala
---
@@ -571,12 +571,7 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)])
throw new SparkException("Default partitioner cannot partition array
keys.")
}
val cg = new CoGroupedRDD[K](Seq(self, other1, other2, other3),
partitioner)
- cg.mapValues { case Seq(vs, w1s, w2s, w3s) =>
- (vs.asInstanceOf[Seq[V]],
- w1s.asInstanceOf[Seq[W1]],
- w2s.asInstanceOf[Seq[W2]],
- w3s.asInstanceOf[Seq[W3]])
- }
+ cg.mapValues { seq => seq.asInstanceOf[(Seq[V], Seq[W1], Seq[W2],
Seq[W3])] }
--- End diff --
And yeah as Reynold pointed out, this won't actually cast. A Seq is not a
tuple4, you need to make a new one. In this case it might be okay to leave the
code as is, because the non-pattern-matching way will be hairier. Basically
you'd have to do `seq => (seq(0).asInstanceOf[Seq[V]],
seq(1).asInstanceOf[Seq[W1]], etc)`.
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