Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/10554#discussion_r48932093
--- Diff: core/src/main/scala/org/apache/spark/api/java/JavaPairRDD.scala
---
@@ -288,17 +288,18 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)])
* immediately to the master as a Map. This will also perform the
merging locally on each mapper
* before sending results to a reducer, similarly to a "combiner" in
MapReduce.
*/
- def reduceByKeyLocally(func: JFunction2[V, V, V]): java.util.Map[K, V] =
+ def reduceByKeyLocally(func: JFunction2[V, V, V]): JMap[K, V] =
mapAsSerializableJavaMap(rdd.reduceByKeyLocally(func))
/** Count the number of elements for each key, and return the result to
the master as a Map. */
- def countByKey(): java.util.Map[K, Long] =
mapAsSerializableJavaMap(rdd.countByKey())
+ def countByKey(): JMap[K, JLong] =
+ mapAsSerializableJavaMap(rdd.countByKey().mapValues(JLong.valueOf))
--- End diff --
what's the reason we still need the mapValues here?
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