From ac56cf605b61803c26e0004b43c703cca7e02d61 Mon Sep 17 00:00:00 2001
From: Sean Owen <sowen@cloudera.com>
Date: Wed, 6 Jan 2016 17:17:32 -0800
Subject: [SPARK-12604][CORE] Java count(AprroxDistinct)ByKey methods return
 Scala Long not Java

Change Java countByKey, countApproxDistinctByKey return types to use Java Long, not Scala; update similar methods for consistency on java.long.Long.valueOf with no API change

Author: Sean Owen <sowen@cloudera.com>

Closes #10554 from srowen/SPARK-12604.
---
 .../spark/streaming/api/java/JavaDStreamLike.scala     | 18 +++++++++---------
 .../spark/streaming/api/java/JavaPairDStream.scala     |  7 ++++---
 2 files changed, 13 insertions(+), 12 deletions(-)

(limited to 'streaming/src')

diff --git a/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaDStreamLike.scala b/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaDStreamLike.scala
index 84acec7d8e..733147f63e 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaDStreamLike.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaDStreamLike.scala
@@ -17,7 +17,7 @@
 
 package org.apache.spark.streaming.api.java
 
-import java.lang.{Long => JLong}
+import java.{lang => jl}
 import java.util.{List => JList}
 
 import scala.collection.JavaConverters._
@@ -50,8 +50,8 @@ trait JavaDStreamLike[T, This <: JavaDStreamLike[T, This, R], R <: JavaRDDLike[T
 
   def wrapRDD(in: RDD[T]): R
 
-  implicit def scalaIntToJavaLong(in: DStream[Long]): JavaDStream[JLong] = {
-    in.map(new JLong(_))
+  implicit def scalaIntToJavaLong(in: DStream[Long]): JavaDStream[jl.Long] = {
+    in.map(jl.Long.valueOf)
   }
 
   /**
@@ -74,14 +74,14 @@ trait JavaDStreamLike[T, This <: JavaDStreamLike[T, This, R], R <: JavaRDDLike[T
    * Return a new DStream in which each RDD has a single element generated by counting each RDD
    * of this DStream.
    */
-  def count(): JavaDStream[JLong] = dstream.count()
+  def count(): JavaDStream[jl.Long] = dstream.count()
 
   /**
    * Return a new DStream in which each RDD contains the counts of each distinct value in
    * each RDD of this DStream.  Hash partitioning is used to generate the RDDs with
    * Spark's default number of partitions.
    */
-  def countByValue(): JavaPairDStream[T, JLong] = {
+  def countByValue(): JavaPairDStream[T, jl.Long] = {
     JavaPairDStream.scalaToJavaLong(dstream.countByValue())
   }
 
@@ -91,7 +91,7 @@ trait JavaDStreamLike[T, This <: JavaDStreamLike[T, This, R], R <: JavaRDDLike[T
    * partitions.
    * @param numPartitions  number of partitions of each RDD in the new DStream.
    */
-  def countByValue(numPartitions: Int): JavaPairDStream[T, JLong] = {
+  def countByValue(numPartitions: Int): JavaPairDStream[T, jl.Long] = {
     JavaPairDStream.scalaToJavaLong(dstream.countByValue(numPartitions))
   }
 
@@ -101,7 +101,7 @@ trait JavaDStreamLike[T, This <: JavaDStreamLike[T, This, R], R <: JavaRDDLike[T
    * of elements in a window over this DStream. windowDuration and slideDuration are as defined in
    * the window() operation. This is equivalent to window(windowDuration, slideDuration).count()
    */
-  def countByWindow(windowDuration: Duration, slideDuration: Duration) : JavaDStream[JLong] = {
+  def countByWindow(windowDuration: Duration, slideDuration: Duration) : JavaDStream[jl.Long] = {
     dstream.countByWindow(windowDuration, slideDuration)
   }
 
@@ -116,7 +116,7 @@ trait JavaDStreamLike[T, This <: JavaDStreamLike[T, This, R], R <: JavaRDDLike[T
    *                       DStream's batching interval
    */
   def countByValueAndWindow(windowDuration: Duration, slideDuration: Duration)
-    : JavaPairDStream[T, JLong] = {
+    : JavaPairDStream[T, jl.Long] = {
     JavaPairDStream.scalaToJavaLong(
       dstream.countByValueAndWindow(windowDuration, slideDuration))
   }
@@ -133,7 +133,7 @@ trait JavaDStreamLike[T, This <: JavaDStreamLike[T, This, R], R <: JavaRDDLike[T
    * @param numPartitions  number of partitions of each RDD in the new DStream.
    */
   def countByValueAndWindow(windowDuration: Duration, slideDuration: Duration, numPartitions: Int)
-    : JavaPairDStream[T, JLong] = {
+    : JavaPairDStream[T, jl.Long] = {
     JavaPairDStream.scalaToJavaLong(
       dstream.countByValueAndWindow(windowDuration, slideDuration, numPartitions))
   }
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaPairDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaPairDStream.scala
index 2bf3ccec6b..af0d84b332 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaPairDStream.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaPairDStream.scala
@@ -17,7 +17,8 @@
 
 package org.apache.spark.streaming.api.java
 
-import java.lang.{Iterable => JIterable, Long => JLong}
+import java.{lang => jl}
+import java.lang.{Iterable => JIterable}
 import java.util.{List => JList}
 
 import scala.collection.JavaConverters._
@@ -847,7 +848,7 @@ object JavaPairDStream {
   }
 
   def scalaToJavaLong[K: ClassTag](dstream: JavaPairDStream[K, Long])
-  : JavaPairDStream[K, JLong] = {
-    DStream.toPairDStreamFunctions(dstream.dstream).mapValues(new JLong(_))
+  : JavaPairDStream[K, jl.Long] = {
+    DStream.toPairDStreamFunctions(dstream.dstream).mapValues(jl.Long.valueOf)
   }
 }
-- 
cgit v1.2.3