Added a closureSerializer field in SparkEnv and use it to serialize

tasks.

core/src/main/scala/spark/Executor.scala

@@ -57,16 +57,17 @@ class Executor extends org.apache.mesos.Executor with Logging {
   extends Runnable {
     override def run() = {
       val tid = desc.getTaskId.getValue
+      SparkEnv.set(env)
+      Thread.currentThread.setContextClassLoader(classLoader)
+      val ser = SparkEnv.get.closureSerializer.newInstance()
       logInfo("Running task ID " + tid)
       d.sendStatusUpdate(TaskStatus.newBuilder()
           .setTaskId(desc.getTaskId)
           .setState(TaskState.TASK_RUNNING)
           .build())
       try {
-        SparkEnv.set(env)
-        Thread.currentThread.setContextClassLoader(classLoader)
         Accumulators.clear
-        val task = Utils.deserialize[Task[Any]](desc.getData.toByteArray, classLoader)
+        val task = ser.deserialize[Task[Any]](desc.getData.toByteArray, classLoader)
         for (gen <- task.generation) {// Update generation if any is set
           env.mapOutputTracker.updateGeneration(gen)
         }
@@ -76,7 +77,7 @@ class Executor extends org.apache.mesos.Executor with Logging {
         d.sendStatusUpdate(TaskStatus.newBuilder()
             .setTaskId(desc.getTaskId)
             .setState(TaskState.TASK_FINISHED)
-            .setData(ByteString.copyFrom(Utils.serialize(result)))
+            .setData(ByteString.copyFrom(ser.serialize(result)))
             .build())
         logInfo("Finished task ID " + tid)
       } catch {
@@ -85,7 +86,7 @@ class Executor extends org.apache.mesos.Executor with Logging {
           d.sendStatusUpdate(TaskStatus.newBuilder()
               .setTaskId(desc.getTaskId)
               .setState(TaskState.TASK_FAILED)
-              .setData(ByteString.copyFrom(Utils.serialize(reason)))
+              .setData(ByteString.copyFrom(ser.serialize(reason)))
               .build())
         }
         case t: Throwable => {
@@ -93,7 +94,7 @@ class Executor extends org.apache.mesos.Executor with Logging {
           d.sendStatusUpdate(TaskStatus.newBuilder()
               .setTaskId(desc.getTaskId)
               .setState(TaskState.TASK_FAILED)
-              .setData(ByteString.copyFrom(Utils.serialize(reason)))
+              .setData(ByteString.copyFrom(ser.serialize(reason)))
               .build())
 
           // TODO: Handle errors in tasks less dramatically

core/src/main/scala/spark/LocalScheduler.scala

@@ -38,9 +38,13 @@ private class LocalScheduler(threads: Int, maxFailures: Int) extends DAGSchedule
         // Serialize and deserialize the task so that accumulators are changed to thread-local ones;
         // this adds a bit of unnecessary overhead but matches how the Mesos Executor works.
         Accumulators.clear
-        val bytes = Utils.serialize(task)
-        logInfo("Size of task " + idInJob + " is " + bytes.size + " bytes")
-        val deserializedTask = Utils.deserialize[Task[_]](
+        val ser = SparkEnv.get.closureSerializer.newInstance()
+        val startTime = System.currentTimeMillis
+        val bytes = ser.serialize(task)
+        val timeTaken = System.currentTimeMillis - startTime
+        logInfo("Size of task %d is %d bytes and took %d ms to serialize by %s"
+          .format(idInJob, bytes.size, timeTaken, ser.getClass.getName))
+        val deserializedTask = ser.deserialize[Task[_]](
             bytes, Thread.currentThread.getContextClassLoader)
         val result: Any = deserializedTask.run(attemptId)
         val accumUpdates = Accumulators.values

core/src/main/scala/spark/SimpleJob.scala

@@ -30,6 +30,9 @@ class SimpleJob(
   // Maximum times a task is allowed to fail before failing the job
   val MAX_TASK_FAILURES = 4
 
+  // Serializer for closures and tasks.
+  val ser = SparkEnv.get.closureSerializer.newInstance()
+
   val callingThread = Thread.currentThread
   val tasks = tasksSeq.toArray
   val numTasks = tasks.length
@@ -170,8 +173,14 @@ class SimpleJob(
             .setType(Resource.Type.SCALAR)
             .setScalar(Resource.Scalar.newBuilder().setValue(CPUS_PER_TASK).build())
             .build()
-          val serializedTask = Utils.serialize(task)
-          logDebug("Serialized size: " + serializedTask.size)
+
+          val startTime = System.currentTimeMillis
+          val serializedTask = ser.serialize(task)
+          val timeTaken = System.currentTimeMillis - startTime
+
+          logInfo("Size of task %d:%d is %d bytes and took %d ms to serialize by %s"
+            .format(jobId, index, serializedTask.size, timeTaken, ser.getClass.getName))
+
           val taskName = "task %d:%d".format(jobId, index)
           return Some(TaskDescription.newBuilder()
               .setTaskId(taskId)
@@ -208,7 +217,8 @@ class SimpleJob(
       tasksFinished += 1
       logInfo("Finished TID %s (progress: %d/%d)".format(tid, tasksFinished, numTasks))
       // Deserialize task result
-      val result = Utils.deserialize[TaskResult[_]](status.getData.toByteArray)
+      val result = ser.deserialize[TaskResult[_]](
+        status.getData.toByteArray)
       sched.taskEnded(tasks(index), Success, result.value, result.accumUpdates)
       // Mark finished and stop if we've finished all the tasks
       finished(index) = true
@@ -230,7 +240,8 @@ class SimpleJob(
       // Check if the problem is a map output fetch failure. In that case, this
       // task will never succeed on any node, so tell the scheduler about it.
       if (status.getData != null && status.getData.size > 0) {
-        val reason = Utils.deserialize[TaskEndReason](status.getData.toByteArray)
+        val reason = ser.deserialize[TaskEndReason](
+          status.getData.toByteArray)
         reason match {
           case fetchFailed: FetchFailed =>
             logInfo("Loss was due to fetch failure from " + fetchFailed.serverUri)

core/src/main/scala/spark/SparkEnv.scala

@@ -3,6 +3,7 @@ package spark
 class SparkEnv (
   val cache: Cache,
   val serializer: Serializer,
+  val closureSerializer: Serializer,
   val cacheTracker: CacheTracker,
   val mapOutputTracker: MapOutputTracker,
   val shuffleFetcher: ShuffleFetcher,
@@ -27,6 +28,11 @@ object SparkEnv {
     val serializerClass = System.getProperty("spark.serializer", "spark.JavaSerializer")
     val serializer = Class.forName(serializerClass).newInstance().asInstanceOf[Serializer]
 
+    val closureSerializerClass =
+      System.getProperty("spark.closure.serializer", "spark.JavaSerializer")
+    val closureSerializer =
+      Class.forName(closureSerializerClass).newInstance().asInstanceOf[Serializer]
+
     val cacheTracker = new CacheTracker(isMaster, cache)
 
     val mapOutputTracker = new MapOutputTracker(isMaster)
@@ -38,6 +44,13 @@ object SparkEnv {
 
     val shuffleMgr = new ShuffleManager()
 
-    new SparkEnv(cache, serializer, cacheTracker, mapOutputTracker, shuffleFetcher, shuffleMgr)
+    new SparkEnv(
+      cache,
+      serializer,
+      closureSerializer,
+      cacheTracker,
+      mapOutputTracker,
+      shuffleFetcher,
+      shuffleMgr)
   }
 }

core/src/main/scala/spark/Utils.scala

@@ -13,16 +13,27 @@ import scala.util.Random
  */
 object Utils {
 
-  // The serializer in this object is used by Spark to serialize closures.
-  val serializerClass = System.getProperty("spark.closure.serializer", "spark.JavaSerializer")
-  val ser = Class.forName(serializerClass).newInstance().asInstanceOf[Serializer]
+  def serialize[T](o: T): Array[Byte] = {
+    val bos = new ByteArrayOutputStream()
+    val oos = new ObjectOutputStream(bos)
+    oos.writeObject(o)
+    oos.close
+    return bos.toByteArray
+  }
 
-  def serialize[T](o: T): Array[Byte] = ser.newInstance().serialize[T](o)
-  
-  def deserialize[T](bytes: Array[Byte]): T = ser.newInstance().deserialize[T](bytes)
+  def deserialize[T](bytes: Array[Byte]): T = {
+    val bis = new ByteArrayInputStream(bytes)
+    val ois = new ObjectInputStream(bis)
+    return ois.readObject.asInstanceOf[T]
+  }
 
   def deserialize[T](bytes: Array[Byte], loader: ClassLoader): T = {
-    ser.newInstance().deserialize[T](bytes, loader)
+    val bis = new ByteArrayInputStream(bytes)
+    val ois = new ObjectInputStream(bis) {
+      override def resolveClass(desc: ObjectStreamClass) =
+        Class.forName(desc.getName, false, loader)
+    }
+    return ois.readObject.asInstanceOf[T]
   }
 
   def isAlpha(c: Char): Boolean = {