Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/2274#discussion_r17140599
--- Diff:
core/src/main/scala/org/apache/spark/rdd/OrderedRDDFunctions.scala ---
@@ -64,4 +64,15 @@ class OrderedRDDFunctions[K : Ordering : ClassTag,
new ShuffledRDD[K, V, V](self, part)
.setKeyOrdering(if (ascending) ordering else ordering.reverse)
}
+
+ /**
+ * Repartition the RDD according to the given partitioner and, within
each resulting partition,
+ * sort records by their keys.
--- End diff --
can u add some documentation explaining this is functionally similar to
doing repartition and then sort within each function, except it is more
optimized because we can push the sorting into the shuffle process?
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