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authorSandy Ryza <sandy@cloudera.com>2015-01-28 12:41:23 -0800
committerPatrick Wendell <patrick@databricks.com>2015-01-28 12:41:23 -0800
commit406f6d3070441962222f6a25449ea2c48f52ce88 (patch)
tree13b32a67cdcf1b55423cb1f17ee96ca4a960c7bf /python/pyspark
parentc8e934ef3cd06f02f9a2946e96a1a52293c22490 (diff)
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SPARK-5458. Refer to aggregateByKey instead of combineByKey in docs
Author: Sandy Ryza <sandy@cloudera.com> Closes #4251 from sryza/sandy-spark-5458 and squashes the following commits: 460827a [Sandy Ryza] Python too d2dc160 [Sandy Ryza] SPARK-5458. Refer to aggregateByKey instead of combineByKey in docs
Diffstat (limited to 'python/pyspark')
-rw-r--r--python/pyspark/rdd.py4
1 files changed, 2 insertions, 2 deletions
diff --git a/python/pyspark/rdd.py b/python/pyspark/rdd.py
index f4cfe4845d..efd2f35912 100644
--- a/python/pyspark/rdd.py
+++ b/python/pyspark/rdd.py
@@ -1634,8 +1634,8 @@ class RDD(object):
Hash-partitions the resulting RDD with into numPartitions partitions.
Note: If you are grouping in order to perform an aggregation (such as a
- sum or average) over each key, using reduceByKey will provide much
- better performance.
+ sum or average) over each key, using reduceByKey or aggregateByKey will
+ provide much better performance.
>>> x = sc.parallelize([("a", 1), ("b", 1), ("a", 1)])
>>> map((lambda (x,y): (x, list(y))), sorted(x.groupByKey().collect()))