Merge branch 'master' of https://github.com/apache/spark into SPARK-1413

core/src/main/scala/org/apache/spark/SparkContext.scala

@@ -1002,7 +1002,9 @@ class SparkContext(config: SparkConf) extends Logging {
       require(p >= 0 && p < rdd.partitions.size, s"Invalid partition requested: $p")
     }
     val callSite = getCallSite
-    val cleanedFunc = clean(func)
+    // There's no need to check this function for serializability,
+    // since it will be run right away.
+    val cleanedFunc = clean(func, false)
     logInfo("Starting job: " + callSite)
     val start = System.nanoTime
     dagScheduler.runJob(rdd, cleanedFunc, partitions, callSite, allowLocal,
@@ -1135,14 +1137,18 @@ class SparkContext(config: SparkConf) extends Logging {
   def cancelAllJobs() {
     dagScheduler.cancelAllJobs()
   }
-
+  
   /**
    * Clean a closure to make it ready to serialized and send to tasks
    * (removes unreferenced variables in $outer's, updates REPL variables)
+   *
+   * @param f closure to be cleaned and optionally serialized
+   * @param captureNow whether or not to serialize this closure and capture any free 
+   * variables immediately; defaults to true.  If this is set and f is not serializable, 
+   * it will raise an exception.
    */
-  private[spark] def clean[F <: AnyRef](f: F): F = {
-    ClosureCleaner.clean(f)
-    f
+  private[spark] def clean[F <: AnyRef : ClassTag](f: F, captureNow: Boolean = true): F = {
+    ClosureCleaner.clean(f, captureNow)
   }
 
   /**

core/src/main/scala/org/apache/spark/rdd/RDD.scala

@@ -660,14 +660,16 @@ abstract class RDD[T: ClassTag](
    * Applies a function f to all elements of this RDD.
    */
   def foreach(f: T => Unit) {
-    sc.runJob(this, (iter: Iterator[T]) => iter.foreach(f))
+    val cleanF = sc.clean(f)
+    sc.runJob(this, (iter: Iterator[T]) => iter.foreach(cleanF))
   }
 
   /**
    * Applies a function f to each partition of this RDD.
    */
   def foreachPartition(f: Iterator[T] => Unit) {
-    sc.runJob(this, (iter: Iterator[T]) => f(iter))
+    val cleanF = sc.clean(f)
+    sc.runJob(this, (iter: Iterator[T]) => cleanF(iter))
   }
 
   /**

core/src/main/scala/org/apache/spark/util/ClosureCleaner.scala

@@ -22,10 +22,14 @@ import java.io.{ByteArrayInputStream, ByteArrayOutputStream}
 import scala.collection.mutable.Map
 import scala.collection.mutable.Set
 
+import scala.reflect.ClassTag
+
 import com.esotericsoftware.reflectasm.shaded.org.objectweb.asm.{ClassReader, ClassVisitor, MethodVisitor, Type}
 import com.esotericsoftware.reflectasm.shaded.org.objectweb.asm.Opcodes._
 
 import org.apache.spark.Logging
+import org.apache.spark.SparkEnv
+import org.apache.spark.SparkException
 
 private[spark] object ClosureCleaner extends Logging {
   // Get an ASM class reader for a given class from the JAR that loaded it
@@ -101,7 +105,7 @@ private[spark] object ClosureCleaner extends Logging {
     }
   }
 
-  def clean(func: AnyRef) {
+  def clean[F <: AnyRef : ClassTag](func: F, captureNow: Boolean = true): F = {
     // TODO: cache outerClasses / innerClasses / accessedFields
     val outerClasses = getOuterClasses(func)
     val innerClasses = getInnerClasses(func)
@@ -150,6 +154,21 @@ private[spark] object ClosureCleaner extends Logging {
       field.setAccessible(true)
       field.set(func, outer)
     }
+
+    if (captureNow) {
+      cloneViaSerializing(func)
+    } else {
+      func
+    }
+  }
+
+  private def cloneViaSerializing[T: ClassTag](func: T): T = {
+    try {
+      val serializer = SparkEnv.get.closureSerializer.newInstance()
+      serializer.deserialize[T](serializer.serialize[T](func))
+    } catch {
+      case ex: Exception => throw new SparkException("Task not serializable: " + ex.toString)
+    }
   }
 
   private def instantiateClass(cls: Class[_], outer: AnyRef, inInterpreter: Boolean): AnyRef = {

core/src/test/scala/org/apache/spark/FailureSuite.scala

@@ -107,7 +107,7 @@ class FailureSuite extends FunSuite with LocalSparkContext {
     FailureSuiteState.clear()
   }
 
-  test("failure because task closure is not serializable") {
+  test("failure because closure in final-stage task is not serializable") {
     sc = new SparkContext("local[1,1]", "test")
     val a = new NonSerializable
 
@@ -118,13 +118,27 @@ class FailureSuite extends FunSuite with LocalSparkContext {
     assert(thrown.getClass === classOf[SparkException])
     assert(thrown.getMessage.contains("NotSerializableException"))
 
+    FailureSuiteState.clear()
+  }
+
+  test("failure because closure in early-stage task is not serializable") {
+    sc = new SparkContext("local[1,1]", "test")
+    val a = new NonSerializable
+
     // Non-serializable closure in an earlier stage
     val thrown1 = intercept[SparkException] {
       sc.parallelize(1 to 10, 2).map(x => (x, a)).partitionBy(new HashPartitioner(3)).count()
     }
     assert(thrown1.getClass === classOf[SparkException])
     assert(thrown1.getMessage.contains("NotSerializableException"))
 
+    FailureSuiteState.clear()
+  }
+
+  test("failure because closure in foreach task is not serializable") {
+    sc = new SparkContext("local[1,1]", "test")
+    val a = new NonSerializable
+
     // Non-serializable closure in foreach function
     val thrown2 = intercept[SparkException] {
       sc.parallelize(1 to 10, 2).foreach(x => println(a))
@@ -135,5 +149,6 @@ class FailureSuite extends FunSuite with LocalSparkContext {
     FailureSuiteState.clear()
   }
 
+
   // TODO: Need to add tests with shuffle fetch failures.
 }

core/src/test/scala/org/apache/spark/serializer/ProactiveClosureSerializationSuite.scala

@@ -0,0 +1,94 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.serializer;
+
+import java.io.NotSerializableException
+
+import org.scalatest.FunSuite
+
+import org.apache.spark.rdd.RDD
+import org.apache.spark.SparkException
+import org.apache.spark.SharedSparkContext
+
+/* A trivial (but unserializable) container for trivial functions */
+class UnserializableClass {
+  def op[T](x: T) = x.toString
+
+  def pred[T](x: T) = x.toString.length % 2 == 0
+}
+
+class ProactiveClosureSerializationSuite extends FunSuite with SharedSparkContext {
+
+  def fixture = (sc.parallelize(0 until 1000).map(_.toString), new UnserializableClass)
+
+  test("throws expected serialization exceptions on actions") {
+    val (data, uc) = fixture
+
+    val ex = intercept[SparkException] {
+      data.map(uc.op(_)).count
+    }
+
+    assert(ex.getMessage.matches(".*Task not serializable.*"))
+  }
+
+  // There is probably a cleaner way to eliminate boilerplate here, but we're
+  // iterating over a map from transformation names to functions that perform that
+  // transformation on a given RDD, creating one test case for each
+
+  for (transformation <- 
+      Map("map" -> map _, "flatMap" -> flatMap _, "filter" -> filter _, "mapWith" -> mapWith _,
+          "mapPartitions" -> mapPartitions _, "mapPartitionsWithIndex" -> mapPartitionsWithIndex _,
+          "mapPartitionsWithContext" -> mapPartitionsWithContext _, "filterWith" -> filterWith _)) {
+    val (name, xf) = transformation
+
+    test(s"$name transformations throw proactive serialization exceptions") {
+      val (data, uc) = fixture
+
+      val ex = intercept[SparkException] {
+        xf(data, uc)
+      }
+
+      assert(ex.getMessage.matches(".*Task not serializable.*"), s"RDD.$name doesn't proactively throw NotSerializableException")
+    }
+  }
+
+  def map(x: RDD[String], uc: UnserializableClass): RDD[String] =
+    x.map(y => uc.op(y))
+
+  def mapWith(x: RDD[String], uc: UnserializableClass): RDD[String] =
+    x.mapWith(x => x.toString)((x,y) => x + uc.op(y))
+
+  def flatMap(x: RDD[String], uc: UnserializableClass): RDD[String] =
+    x.flatMap(y=>Seq(uc.op(y)))
+
+  def filter(x: RDD[String], uc: UnserializableClass): RDD[String] =
+    x.filter(y=>uc.pred(y))
+
+  def filterWith(x: RDD[String], uc: UnserializableClass): RDD[String] =
+    x.filterWith(x => x.toString)((x,y) => uc.pred(y))
+
+  def mapPartitions(x: RDD[String], uc: UnserializableClass): RDD[String] =
+    x.mapPartitions(_.map(y => uc.op(y)))
+
+  def mapPartitionsWithIndex(x: RDD[String], uc: UnserializableClass): RDD[String] =
+    x.mapPartitionsWithIndex((_, it) => it.map(y => uc.op(y)))
+
+  def mapPartitionsWithContext(x: RDD[String], uc: UnserializableClass): RDD[String] =
+    x.mapPartitionsWithContext((_, it) => it.map(y => uc.op(y)))
+
+}

core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite.scala

@@ -50,6 +50,27 @@ class ClosureCleanerSuite extends FunSuite {
     val obj = new TestClassWithNesting(1)
     assert(obj.run() === 96) // 4 * (1+2+3+4) + 4 * (1+2+3+4) + 16 * 1
   }
+
+  test("capturing free variables in closures at RDD definition") {
+    val obj = new TestCaptureVarClass()
+    val (ones, onesPlusZeroes) = obj.run()
+
+    assert(ones === onesPlusZeroes)
+  }
+
+  test("capturing free variable fields in closures at RDD definition") {
+    val obj = new TestCaptureFieldClass()
+    val (ones, onesPlusZeroes) = obj.run()
+
+    assert(ones === onesPlusZeroes)
+  }
+
+  test("capturing arrays in closures at RDD definition") {
+    val obj = new TestCaptureArrayEltClass()
+    val (observed, expected) = obj.run()
+
+    assert(observed === expected)
+  }
 }
 
 // A non-serializable class we create in closures to make sure that we aren't
@@ -143,3 +164,50 @@ class TestClassWithNesting(val y: Int) extends Serializable {
     }
   }
 }
+
+class TestCaptureFieldClass extends Serializable {
+  class ZeroBox extends Serializable {
+    var zero = 0
+  }
+
+  def run(): (Int, Int) = {
+    val zb = new ZeroBox
+
+    withSpark(new SparkContext("local", "test")) {sc =>
+      val ones = sc.parallelize(Array(1, 1, 1, 1, 1))
+      val onesPlusZeroes = ones.map(_ + zb.zero)
+
+      zb.zero = 5
+
+      (ones.reduce(_ + _), onesPlusZeroes.reduce(_ + _))
+    }
+  }
+}
+
+class TestCaptureArrayEltClass extends Serializable {
+  def run(): (Int, Int) = {
+    withSpark(new SparkContext("local", "test")) {sc =>
+      val rdd = sc.parallelize(1 to 10)
+      val data = Array(1, 2, 3)
+      val expected = data(0)
+      val mapped = rdd.map(x => data(0))
+      data(0) = 4
+      (mapped.first, expected)
+    }
+  }
+}
+
+class TestCaptureVarClass extends Serializable {
+  def run(): (Int, Int) = {
+    var zero = 0
+
+    withSpark(new SparkContext("local", "test")) {sc =>
+      val ones = sc.parallelize(Array(1, 1, 1, 1, 1))
+      val onesPlusZeroes = ones.map(_ + zero)
+
+      zero = 5
+
+      (ones.reduce(_ + _), onesPlusZeroes.reduce(_ + _))
+    }
+  }
+}

graphx/src/test/scala/org/apache/spark/graphx/GraphSuite.scala

@@ -62,7 +62,7 @@ class GraphSuite extends FunSuite with LocalSparkContext {
       assert( graph.edges.count() === rawEdges.size )
       // Vertices not explicitly provided but referenced by edges should be created automatically
       assert( graph.vertices.count() === 100)
-      graph.triplets.map { et =>
+      graph.triplets.collect.map { et =>
         assert((et.srcId < 10 && et.srcAttr) || (et.srcId >= 10 && !et.srcAttr))
         assert((et.dstId < 10 && et.dstAttr) || (et.dstId >= 10 && !et.dstAttr))
       }

streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala

@@ -539,15 +539,15 @@ abstract class DStream[T: ClassTag] (
    * on each RDD of 'this' DStream.
    */
   def transform[U: ClassTag](transformFunc: RDD[T] => RDD[U]): DStream[U] = {
-    transform((r: RDD[T], t: Time) => context.sparkContext.clean(transformFunc(r)))
+    transform((r: RDD[T], t: Time) => context.sparkContext.clean(transformFunc(r), false))
   }
 
   /**
    * Return a new DStream in which each RDD is generated by applying a function
    * on each RDD of 'this' DStream.
    */
   def transform[U: ClassTag](transformFunc: (RDD[T], Time) => RDD[U]): DStream[U] = {
-    val cleanedF = context.sparkContext.clean(transformFunc)
+    val cleanedF = context.sparkContext.clean(transformFunc, false)
     val realTransformFunc =  (rdds: Seq[RDD[_]], time: Time) => {
       assert(rdds.length == 1)
       cleanedF(rdds.head.asInstanceOf[RDD[T]], time)
@@ -562,7 +562,7 @@ abstract class DStream[T: ClassTag] (
   def transformWith[U: ClassTag, V: ClassTag](
       other: DStream[U], transformFunc: (RDD[T], RDD[U]) => RDD[V]
     ): DStream[V] = {
-    val cleanedF = ssc.sparkContext.clean(transformFunc)
+    val cleanedF = ssc.sparkContext.clean(transformFunc, false)
     transformWith(other, (rdd1: RDD[T], rdd2: RDD[U], time: Time) => cleanedF(rdd1, rdd2))
   }
 
@@ -573,7 +573,7 @@ abstract class DStream[T: ClassTag] (
   def transformWith[U: ClassTag, V: ClassTag](
       other: DStream[U], transformFunc: (RDD[T], RDD[U], Time) => RDD[V]
     ): DStream[V] = {
-    val cleanedF = ssc.sparkContext.clean(transformFunc)
+    val cleanedF = ssc.sparkContext.clean(transformFunc, false)
     val realTransformFunc = (rdds: Seq[RDD[_]], time: Time) => {
       assert(rdds.length == 2)
       val rdd1 = rdds(0).asInstanceOf[RDD[T]]