Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2092#discussion_r16634474
--- Diff: python/pyspark/rdd.py ---
@@ -1715,6 +1715,52 @@ def batch_as(rdd, batchSize):
other._jrdd_deserializer)
return RDD(pairRDD, self.ctx, deserializer)
+ def zipWithIndex(self):
+ """
+ Zips this RDD with its element indices.
+
+ The ordering is first based on the partition index and then the
+ ordering of items within each partition. So the first item in
+ the first partition gets index 0, and the last item in the last
+ partition receives the largest index.
+
+ This method needs to trigger a spark job when this RDD contains
+ more than one partitions.
+
+ >>> sc.parallelize(range(4), 2).zipWithIndex().collect()
+ [(0, 0), (1, 1), (2, 2), (3, 3)]
--- End diff --
I will change it.
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