[SPARK-7237] Clean function in several RDD methods

Author: tedyu <yuzhihong@gmail.com>

Closes #5959 from ted-yu/master and squashes the following commits:

f83d445 [tedyu] Move cleaning outside of mapPartitionsWithIndex
56d7c92 [tedyu] Consolidate import of Random
f6014c0 [tedyu] Remove cleaning in RDD#filterWith
36feb6c [tedyu] Try to get correct syntax
55d01eb [tedyu] Try to get correct syntax
c2786df [tedyu] Correct syntax
d92bfcf [tedyu] Correct syntax in test
164d3e4 [tedyu] Correct variable name
8b50d93 [tedyu] Address Andrew's review comments
0c8d47e [tedyu] Add test for mapWith()
6846e40 [tedyu] Add test for flatMapWith()
6c124a9 [tedyu] Clean function in several RDD methods

2 files changed, 41 insertions, 10 deletions

diff --git a/core/src/main/scala/org/apache/spark/rdd/RDD.scala b/core/src/main/scala/org/apache/spark/rdd/RDD.scala
index b3b60578c9..8baf199f21 100644
--- a/core/src/main/scala/org/apache/spark/rdd/RDD.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/RDD.scala
@@ -717,7 +717,8 @@ abstract class RDD[T: ClassTag](
   def mapPartitionsWithContext[U: ClassTag](
       f: (TaskContext, Iterator[T]) => Iterator[U],
       preservesPartitioning: Boolean = false): RDD[U] = withScope {
-    val func = (context: TaskContext, index: Int, iter: Iterator[T]) => f(context, iter)
+    val cleanF = sc.clean(f)
+    val func = (context: TaskContext, index: Int, iter: Iterator[T]) => cleanF(context, iter)
     new MapPartitionsRDD(this, sc.clean(func), preservesPartitioning)
   }
 
@@ -741,9 +742,11 @@ abstract class RDD[T: ClassTag](
   def mapWith[A, U: ClassTag]
       (constructA: Int => A, preservesPartitioning: Boolean = false)
       (f: (T, A) => U): RDD[U] = withScope {
+    val cleanF = sc.clean(f)
+    val cleanA = sc.clean(constructA)
     mapPartitionsWithIndex((index, iter) => {
-      val a = constructA(index)
-      iter.map(t => f(t, a))
+      val a = cleanA(index)
+      iter.map(t => cleanF(t, a))
     }, preservesPartitioning)
   }
 
@@ -756,9 +759,11 @@ abstract class RDD[T: ClassTag](
   def flatMapWith[A, U: ClassTag]
       (constructA: Int => A, preservesPartitioning: Boolean = false)
       (f: (T, A) => Seq[U]): RDD[U] = withScope {
+    val cleanF = sc.clean(f)
+    val cleanA = sc.clean(constructA)
     mapPartitionsWithIndex((index, iter) => {
-      val a = constructA(index)
-      iter.flatMap(t => f(t, a))
+      val a = cleanA(index)
+      iter.flatMap(t => cleanF(t, a))
     }, preservesPartitioning)
   }
 
@@ -769,9 +774,11 @@ abstract class RDD[T: ClassTag](
    */
   @deprecated("use mapPartitionsWithIndex and foreach", "1.0.0")
   def foreachWith[A](constructA: Int => A)(f: (T, A) => Unit): Unit = withScope {
+    val cleanF = sc.clean(f)
+    val cleanA = sc.clean(constructA)
     mapPartitionsWithIndex { (index, iter) =>
-      val a = constructA(index)
-      iter.map(t => {f(t, a); t})
+      val a = cleanA(index)
+      iter.map(t => {cleanF(t, a); t})
     }
   }
 
@@ -782,9 +789,11 @@ abstract class RDD[T: ClassTag](
    */
   @deprecated("use mapPartitionsWithIndex and filter", "1.0.0")
   def filterWith[A](constructA: Int => A)(p: (T, A) => Boolean): RDD[T] = withScope {
+    val cleanP = sc.clean(p)
+    val cleanA = sc.clean(constructA)
     mapPartitionsWithIndex((index, iter) => {
-      val a = constructA(index)
-      iter.filter(t => p(t, a))
+      val a = cleanA(index)
+      iter.filter(t => cleanP(t, a))
     }, preservesPartitioning = true)
   }
 
@@ -901,7 +910,8 @@ abstract class RDD[T: ClassTag](
    * Return an RDD that contains all matching values by applying `f`.
    */
   def collect[U: ClassTag](f: PartialFunction[T, U]): RDD[U] = withScope {
-    filter(f.isDefinedAt).map(f)
+    val cleanF = sc.clean(f)
+    filter(cleanF.isDefinedAt).map(cleanF)
   }
 
   /**
diff --git a/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite.scala b/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite.scala
index 446c3f24a7..e41f6ee277 100644
--- a/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite.scala
@@ -18,6 +18,7 @@
 package org.apache.spark.util
 
 import java.io.NotSerializableException
+import java.util.Random
 
 import org.scalatest.FunSuite
 
@@ -92,6 +93,11 @@ class ClosureCleanerSuite extends FunSuite {
       expectCorrectException { TestUserClosuresActuallyCleaned.testKeyBy(rdd) }
       expectCorrectException { TestUserClosuresActuallyCleaned.testMapPartitions(rdd) }
       expectCorrectException { TestUserClosuresActuallyCleaned.testMapPartitionsWithIndex(rdd) }
+      expectCorrectException { TestUserClosuresActuallyCleaned.testMapPartitionsWithContext(rdd) }
+      expectCorrectException { TestUserClosuresActuallyCleaned.testFlatMapWith(rdd) }
+      expectCorrectException { TestUserClosuresActuallyCleaned.testFilterWith(rdd) }
+      expectCorrectException { TestUserClosuresActuallyCleaned.testForEachWith(rdd) }
+      expectCorrectException { TestUserClosuresActuallyCleaned.testMapWith(rdd) }
       expectCorrectException { TestUserClosuresActuallyCleaned.testZipPartitions2(rdd) }
       expectCorrectException { TestUserClosuresActuallyCleaned.testZipPartitions3(rdd) }
       expectCorrectException { TestUserClosuresActuallyCleaned.testZipPartitions4(rdd) }
@@ -260,6 +266,21 @@ private object TestUserClosuresActuallyCleaned {
   def testMapPartitionsWithIndex(rdd: RDD[Int]): Unit = {
     rdd.mapPartitionsWithIndex { (_, it) => return; it }.count()
   }
+  def testFlatMapWith(rdd: RDD[Int]): Unit = {
+    rdd.flatMapWith ((index: Int) => new Random(index + 42)){ (_, it) => return; Seq() }.count()
+  }
+  def testMapWith(rdd: RDD[Int]): Unit = {
+    rdd.mapWith ((index: Int) => new Random(index + 42)){ (_, it) => return; 0 }.count()
+  }
+  def testFilterWith(rdd: RDD[Int]): Unit = {
+    rdd.filterWith ((index: Int) => new Random(index + 42)){ (_, it) => return; true }.count()
+  }
+  def testForEachWith(rdd: RDD[Int]): Unit = {
+    rdd.foreachWith ((index: Int) => new Random(index + 42)){ (_, it) => return }
+  }
+  def testMapPartitionsWithContext(rdd: RDD[Int]): Unit = {
+    rdd.mapPartitionsWithContext { (_, it) => return; it }.count()
+  }
   def testZipPartitions2(rdd: RDD[Int]): Unit = {
     rdd.zipPartitions(rdd) { case (it1, it2) => return; it1 }.count()
   }