Github user rdblue commented on a diff in the pull request:
https://github.com/apache/spark/pull/11242#discussion_r56885555
--- Diff: core/src/main/scala/org/apache/spark/rdd/UnionRDD.scala ---
@@ -62,7 +64,23 @@ class UnionRDD[T: ClassTag](
var rdds: Seq[RDD[T]])
extends RDD[T](sc, Nil) { // Nil since we implement getDependencies
+ // Evaluate partitions in parallel. Partitions of each rdd will be
cached by the `partitions`
+ // val in `RDD`.
+ private[spark] lazy val parallelPartitionEval: Boolean = {
--- End diff --
You're right that there are several instances of InputFormat and those
aren't shared across threads. The problem is that Hadoop uses reflection to get
InputFormat instances, which means the way for an InputFormat to cache
intermediate results is to use a static cache available across instances. I
don't think this is a huge risk, but I think it warrants being able to disable
UnionRDD concurrency.
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