Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/15077#discussion_r78549808
--- Diff: core/src/main/scala/org/apache/spark/SparkContext.scala ---
@@ -795,7 +795,7 @@ class SparkContext(config: SparkConf) extends Logging
with ExecutorAllocationCli
def makeRDD[T: ClassTag](seq: Seq[(T, Seq[String])]): RDD[T] = withScope
{
assertNotStopped()
val indexToPrefs = seq.zipWithIndex.map(t => (t._2, t._1._2)).toMap
- new ParallelCollectionRDD[T](this, seq.map(_._1), seq.size,
indexToPrefs)
+ new ParallelCollectionRDD[T](this, seq.map(_._1), math.max(seq.size,
defaultParallelism), indexToPrefs)
--- End diff --
I would say `math.max(seq.size, 1)`. Really this method would normally just
use the provided partition count (called "numSlices" in this old API) but this
one doesn't have that parameter, which is more reason it's an odd man out.
Still I think the most reasonable behavior is to use at least 1 partition.
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