Merge pull request #608 from pwendell/SPARK-738

SPARK-738: Spark should detect and wrap nonserializable exceptions

5 files changed, 42 insertions, 10 deletions

diff --git a/core/src/main/scala/spark/TaskEndReason.scala b/core/src/main/scala/spark/TaskEndReason.scala
index 420c54bc9a..ca793eb402 100644
--- a/core/src/main/scala/spark/TaskEndReason.scala
+++ b/core/src/main/scala/spark/TaskEndReason.scala
@@ -14,9 +14,17 @@ private[spark] case object Success extends TaskEndReason
 private[spark] 
 case object Resubmitted extends TaskEndReason // Task was finished earlier but we've now lost it
 
-private[spark] 
-case class FetchFailed(bmAddress: BlockManagerId, shuffleId: Int, mapId: Int, reduceId: Int) extends TaskEndReason
+private[spark] case class FetchFailed(
+    bmAddress: BlockManagerId,
+    shuffleId: Int,
+    mapId: Int,
+    reduceId: Int)
+  extends TaskEndReason
 
-private[spark] case class ExceptionFailure(exception: Throwable) extends TaskEndReason
+private[spark] case class ExceptionFailure(
+    className: String,
+    description: String,
+    stackTrace: Array[StackTraceElement])
+  extends TaskEndReason
 
 private[spark] case class OtherFailure(message: String) extends TaskEndReason
diff --git a/core/src/main/scala/spark/executor/Executor.scala b/core/src/main/scala/spark/executor/Executor.scala
index 344face5e6..da20b84544 100644
--- a/core/src/main/scala/spark/executor/Executor.scala
+++ b/core/src/main/scala/spark/executor/Executor.scala
@@ -122,7 +122,7 @@ private[spark] class Executor(executorId: String, slaveHostname: String, propert
         }
 
         case t: Throwable => {
-          val reason = ExceptionFailure(t)
+          val reason = ExceptionFailure(t.getClass.getName, t.toString, t.getStackTrace)
           context.statusUpdate(taskId, TaskState.FAILED, ser.serialize(reason))
 
           // TODO: Should we exit the whole executor here? On the one hand, the failed task may
diff --git a/core/src/main/scala/spark/scheduler/cluster/TaskSetManager.scala b/core/src/main/scala/spark/scheduler/cluster/TaskSetManager.scala
index 27e713e2c4..06de3c755e 100644
--- a/core/src/main/scala/spark/scheduler/cluster/TaskSetManager.scala
+++ b/core/src/main/scala/spark/scheduler/cluster/TaskSetManager.scala
@@ -493,7 +493,7 @@ private[spark] class TaskSetManager(sched: ClusterScheduler, val taskSet: TaskSe
             return
 
           case ef: ExceptionFailure =>
-            val key = ef.exception.toString
+            val key = ef.description
             val now = System.currentTimeMillis
             val (printFull, dupCount) = {
               if (recentExceptions.contains(key)) {
@@ -511,10 +511,11 @@ private[spark] class TaskSetManager(sched: ClusterScheduler, val taskSet: TaskSe
               }
             }
             if (printFull) {
-              val locs = ef.exception.getStackTrace.map(loc => "\tat %s".format(loc.toString))
-              logInfo("Loss was due to %s\n%s".format(ef.exception.toString, locs.mkString("\n")))
+              val locs = ef.stackTrace.map(loc => "\tat %s".format(loc.toString))
+              logInfo("Loss was due to %s\n%s\n%s".format(
+                ef.className, ef.description, locs.mkString("\n")))
             } else {
-              logInfo("Loss was due to %s [duplicate %d]".format(ef.exception.toString, dupCount))
+              logInfo("Loss was due to %s [duplicate %d]".format(ef.description, dupCount))
             }
 
           case _ => {}
diff --git a/core/src/main/scala/spark/scheduler/local/LocalScheduler.scala b/core/src/main/scala/spark/scheduler/local/LocalScheduler.scala
index f060a940a9..ebe42685ad 100644
--- a/core/src/main/scala/spark/scheduler/local/LocalScheduler.scala
+++ b/core/src/main/scala/spark/scheduler/local/LocalScheduler.scala
@@ -101,8 +101,10 @@ private[spark] class LocalScheduler(threads: Int, maxFailures: Int, sc: SparkCon
               submitTask(task, idInJob)
             } else {
               // TODO: Do something nicer here to return all the way to the user
-              if (!Thread.currentThread().isInterrupted)
-                listener.taskEnded(task, new ExceptionFailure(t), null, null, info, null)
+              if (!Thread.currentThread().isInterrupted) {
+                val failure = new ExceptionFailure(t.getClass.getName, t.toString, t.getStackTrace)
+                listener.taskEnded(task, failure, null, null, info, null)
+              }
             }
           }
         }
diff --git a/core/src/test/scala/spark/DistributedSuite.scala b/core/src/test/scala/spark/DistributedSuite.scala
index 4df3bb5b67..33c99471c6 100644
--- a/core/src/test/scala/spark/DistributedSuite.scala
+++ b/core/src/test/scala/spark/DistributedSuite.scala
@@ -18,6 +18,9 @@ import scala.collection.mutable.ArrayBuffer
 import SparkContext._
 import storage.{GetBlock, BlockManagerWorker, StorageLevel}
 
+class NotSerializableClass
+class NotSerializableExn(val notSer: NotSerializableClass) extends Throwable() {}
+
 class DistributedSuite extends FunSuite with ShouldMatchers with BeforeAndAfter with LocalSparkContext {
 
   val clusterUrl = "local-cluster[2,1,512]"
@@ -27,6 +30,24 @@ class DistributedSuite extends FunSuite with ShouldMatchers with BeforeAndAfter
     System.clearProperty("spark.storage.memoryFraction")
   }
 
+  test("task throws not serializable exception") {
+    // Ensures that executors do not crash when an exn is not serializable. If executors crash,
+    // this test will hang. Correct behavior is that executors don't crash but fail tasks
+    // and the scheduler throws a SparkException.
+
+    // numSlaves must be less than numPartitions
+    val numSlaves = 3
+    val numPartitions = 10
+
+    sc = new SparkContext("local-cluster[%s,1,512]".format(numSlaves), "test")
+    val data = sc.parallelize(1 to 100, numPartitions).
+      map(x => throw new NotSerializableExn(new NotSerializableClass))
+    intercept[SparkException] {
+      data.count()
+    }
+    resetSparkContext()
+  }
+
   test("local-cluster format") {
     sc = new SparkContext("local-cluster[2,1,512]", "test")
     assert(sc.parallelize(1 to 2, 2).count() == 2)