Github user rdblue commented on a diff in the pull request:
https://github.com/apache/spark/pull/11242#discussion_r59058645
--- Diff: core/src/main/scala/org/apache/spark/rdd/UnionRDD.scala ---
@@ -62,8 +62,14 @@ class UnionRDD[T: ClassTag](
var rdds: Seq[RDD[T]])
extends RDD[T](sc, Nil) { // Nil since we implement getDependencies
+ // visible for testing
+ private[spark] val isPartitionEvalParallel: Boolean =
+ rdds.length > conf.getInt("spark.rdd.parallelListingThreshold", 10)
--- End diff --
I don't agree that such a source would necessarily break other places in
Spark. There's a big difference between threads may happen to execute some
method concurrently and kicking off a pool of threads at that method.
While there is no known instance, this is based on two real-world cases:
1. Parquet had a caching scheme that assumed no reuse at all, which broken
when that assumption was violated by Hive.
2. Parquet had a proposal to cache splits for Spark, which would require a
static/class-level cache.
InputFormats are one of the most common places to plug in bad code because
they are used for old, custom formats. I'm fine with parallelizing this by
default, but I'm not comfortable with the idea of changing how they are used
and increasing the chances of hitting a bug if one exists without a safety
valve. I also don't see the down-side to having one.
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