refactor foldByKey to use combineByKey

core/src/main/scala/spark/PairRDDFunctions.scala

@@ -89,22 +89,28 @@ class PairRDDFunctions[K: ClassManifest, V: ClassManifest](
   }
 
   /**
-   * Merge the values for each key using an associative function and a neutral "zero value".
+   * Merge the values for each key using an associative function and a neutral "zero value" which may
+   * be added to the result an arbitrary number of times, and must not change the result (e.g., Nil for
+   * list concatenation, 0 for addition, or 1 for multiplication.).
    */
   def foldByKey(zeroValue: V, partitioner: Partitioner)(func: (V, V) => V): RDD[(K, V)] = {
-    groupByKey(partitioner).mapValues(seq => seq.fold[V](zeroValue)(func))
+    combineByKey[V]({v: V => func(zeroValue, v)}, func, func, partitioner)
   }
 
 
   /**
-   * Merge the values for each key using an associative function and a neutral "zero value".
+   * Merge the values for each key using an associative function and a neutral "zero value" which may
+   * be added to the result an arbitrary number of times, and must not change the result (e.g., Nil for
+   * list concatenation, 0 for addition, or 1 for multiplication.).
    */
   def foldByKey(zeroValue: V, numPartitions: Int)(func: (V, V) => V): RDD[(K, V)] = {
     foldByKey(zeroValue, new HashPartitioner(numPartitions))(func)
   }
 
   /**
-   * Merge the values for each key using an associative function and a neutral "zero value".
+   * Merge the values for each key using an associative function and a neutral "zero value" which may
+   * be added to the result an arbitrary number of times, and must not change the result (e.g., Nil for
+   * list concatenation, 0 for addition, or 1 for multiplication.).
    */
   def foldByKey(zeroValue: V)(func: (V, V) => V): RDD[(K, V)] = {
     foldByKey(zeroValue, defaultPartitioner(self))(func)

core/src/main/scala/spark/api/java/JavaPairRDD.scala

@@ -161,19 +161,25 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)])(implicit val kManifest: ClassManif
     rdd.countByKeyApprox(timeout, confidence).map(mapAsJavaMap)
 
   /**
-   * Merge the values for each key using an associative function and a neutral "zero value".
+   * Merge the values for each key using an associative function and a neutral "zero value" which may
+   * be added to the result an arbitrary number of times, and must not change the result (e.g., Nil for
+   * list concatenation, 0 for addition, or 1 for multiplication.).
    */
   def foldByKey(zeroValue: V, partitioner: Partitioner, func: JFunction2[V, V, V]): JavaPairRDD[K, V] =
     fromRDD(rdd.foldByKey(zeroValue, partitioner)(func))
 
   /**
-   * Merge the values for each key using an associative function and a neutral "zero value".
+   * Merge the values for each key using an associative function and a neutral "zero value" which may
+   * be added to the result an arbitrary number of times, and must not change the result (e.g., Nil for
+   * list concatenation, 0 for addition, or 1 for multiplication.).
    */
   def foldByKey(zeroValue: V, numPartitions: Int, func: JFunction2[V, V, V]): JavaPairRDD[K, V] =
     fromRDD(rdd.foldByKey(zeroValue, numPartitions)(func))
 
   /**
-   * Merge the values for each key using an associative function and a neutral "zero value".
+   * Merge the values for each key using an associative function and a neutral "zero value" which may
+   * be added to the result an arbitrary number of times, and must not change the result (e.g., Nil for
+   * list concatenation, 0 for addition, or 1 for multiplication.).
    */
   def foldByKey(zeroValue: V, func: JFunction2[V, V, V]): JavaPairRDD[K, V] =
     fromRDD(rdd.foldByKey(zeroValue)(func))