Github user mateiz commented on a diff in the pull request:
https://github.com/apache/spark/pull/694#discussion_r12765502
--- Diff:
core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala
---
@@ -140,8 +141,29 @@ class CoarseGrainedSchedulerBackend(scheduler:
TaskSchedulerImpl, actorSystem: A
// Launch tasks returned by a set of resource offers
def launchTasks(tasks: Seq[Seq[TaskDescription]]) {
for (task <- tasks.flatten) {
- freeCores(task.executorId) -= scheduler.CPUS_PER_TASK
- executorActor(task.executorId) ! LaunchTask(task)
+ val ser = SparkEnv.get.closureSerializer.newInstance()
+ val serializedTask = ser.serialize(task)
+ if (serializedTask.limit >= akkaFrameSize - 1024) {
+ val taskSetId = scheduler.taskIdToTaskSetId(task.taskId)
+ scheduler.activeTaskSets.get(taskSetId).foreach { taskSet =>
+ try {
+ var msg = "Serialized task %s:%d was %d bytes which " +
+ "exceeds spark.akka.frameSize (%d bytes). " +
+ "Consider using broadcast variables for large values."
+ msg = msg.format(task.taskId, task.index,
serializedTask.limit, akkaFrameSize)
+ taskSet.abort(msg)
+ } catch {
+ case e: Exception => logError("Exception in error callback",
e)
+ }
+ }
+ // scheduler.error(msg)
+ // TODO: Need to throw an exception?
+ // throw new SparkException(msg)
--- End diff --
Do we still need this code in here if we're aborting the TaskSet?
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