Remove hack workaround for SPARK-668.

Renaming the type paramters solves this problem (see SPARK-694).

I tried this fix earlier, but it didn't work because I didn't run
`sbt/sbt clean` first.

2 files changed, 7 insertions, 26 deletions

diff --git a/core/src/main/scala/spark/api/java/JavaRDDLike.scala b/core/src/main/scala/spark/api/java/JavaRDDLike.scala
index d34d56d169..e18f28d326 100644
--- a/core/src/main/scala/spark/api/java/JavaRDDLike.scala
+++ b/core/src/main/scala/spark/api/java/JavaRDDLike.scala
@@ -12,7 +12,7 @@ import spark.storage.StorageLevel
 import com.google.common.base.Optional
 
 
-trait JavaRDDLike[T, This <: JavaRDDLike[T, This]] extends PairFlatMapWorkaround[T] {
+trait JavaRDDLike[T, This <: JavaRDDLike[T, This]] extends Serializable {
   def wrapRDD(rdd: RDD[T]): This
 
   implicit val classManifest: ClassManifest[T]
@@ -82,12 +82,13 @@ trait JavaRDDLike[T, This <: JavaRDDLike[T, This]] extends PairFlatMapWorkaround
   }
 
   /**
-   * Part of the workaround for SPARK-668; called in PairFlatMapWorkaround.java.
+   *  Return a new RDD by first applying a function to all elements of this
+   *  RDD, and then flattening the results.
    */
-  private[spark] def doFlatMap[K, V](f: PairFlatMapFunction[T, K, V]): JavaPairRDD[K, V] = {
+  def flatMap[K2, V2](f: PairFlatMapFunction[T, K2, V2]): JavaPairRDD[K2, V2] = {
     import scala.collection.JavaConverters._
     def fn = (x: T) => f.apply(x).asScala
-    def cm = implicitly[ClassManifest[AnyRef]].asInstanceOf[ClassManifest[Tuple2[K, V]]]
+    def cm = implicitly[ClassManifest[AnyRef]].asInstanceOf[ClassManifest[Tuple2[K2, V2]]]
     JavaPairRDD.fromRDD(rdd.flatMap(fn)(cm))(f.keyType(), f.valueType())
   }
 
@@ -110,8 +111,8 @@ trait JavaRDDLike[T, This <: JavaRDDLike[T, This]] extends PairFlatMapWorkaround
   /**
    * Return a new RDD by applying a function to each partition of this RDD.
    */
-  def mapPartitions[K, V](f: PairFlatMapFunction[java.util.Iterator[T], K, V]):
-  JavaPairRDD[K, V] = {
+  def mapPartitions[K2, V2](f: PairFlatMapFunction[java.util.Iterator[T], K2, V2]):
+  JavaPairRDD[K2, V2] = {
     def fn = (x: Iterator[T]) => asScalaIterator(f.apply(asJavaIterator(x)).iterator())
     JavaPairRDD.fromRDD(rdd.mapPartitions(fn))(f.keyType(), f.valueType())
   }
diff --git a/core/src/main/scala/spark/api/java/PairFlatMapWorkaround.java b/core/src/main/scala/spark/api/java/PairFlatMapWorkaround.java
deleted file mode 100644
index 68b6fd6622..0000000000
--- a/core/src/main/scala/spark/api/java/PairFlatMapWorkaround.java
+++ /dev/null
@@ -1,20 +0,0 @@
-package spark.api.java;
-
-import spark.api.java.JavaPairRDD;
-import spark.api.java.JavaRDDLike;
-import spark.api.java.function.PairFlatMapFunction;
-
-import java.io.Serializable;
-
-/**
- * Workaround for SPARK-668.
- */
-class PairFlatMapWorkaround<T> implements Serializable {
-    /**
-     *  Return a new RDD by first applying a function to all elements of this
-     *  RDD, and then flattening the results.
-     */
-    public <K, V> JavaPairRDD<K, V> flatMap(PairFlatMapFunction<T, K, V> f) {
-        return ((JavaRDDLike <T, ?>) this).doFlatMap(f);
-    }
-}