Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/1447#discussion_r15042897
--- 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 --
There are all kinds of stuff that's really hard to profile at runtime. For
example, the JVM might decide not to JIT the code because it is longer. It
might decide not to do it because of exceptions. Branch prediction might stop
working because it has too many branches. Etc.
Again, I'm only in favor of this change because it is small, and it might
have impact. If it is a big ugly change, I would be against it without
profiling.
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