Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/1447#discussion_r15038340
--- Diff: core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala
---
@@ -216,17 +216,17 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)])
def reducePartition(iter: Iterator[(K, V)]): Iterator[JHashMap[K, V]]
= {
val map = new JHashMap[K, V]
- iter.foreach { case (k, v) =>
- val old = map.get(k)
- map.put(k, if (old == null) v else func(old, v))
+ iter.foreach { pair =>
+ val old = map.get(pair._1)
--- End diff --
It's really hard to tell. I think it is really hard to tell when doing
microbenchmarks because branch prediction takes care of the extra branches. But
I don't know how this impacts real runtime in a real workload without a lot
more instrumentation. My opinion is since it is a small change, it's ok to just
do it this way. If it is a big refactoring, that's a very different story and
deserves more profiling.
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