Github user kayousterhout commented on a diff in the pull request:
https://github.com/apache/spark/pull/15505#discussion_r103564111
--- Diff:
core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala ---
@@ -454,33 +452,15 @@ private[spark] class TaskSetManager(
currentLocalityIndex = getLocalityIndex(taskLocality)
lastLaunchTime = curTime
}
- // Serialize and return the task
- val serializedTask: ByteBuffer = try {
- ser.serialize(task)
- } catch {
- // If the task cannot be serialized, then there's no point to
re-attempt the task,
- // as it will always fail. So just abort the whole task-set.
- case NonFatal(e) =>
- val msg = s"Failed to serialize task $taskId, not attempting
to retry it."
- logError(msg, e)
- abort(s"$msg Exception during serialization: $e")
- throw new TaskNotSerializableException(e)
- }
- if (serializedTask.limit > TaskSetManager.TASK_SIZE_TO_WARN_KB *
1024 &&
- !emittedTaskSizeWarning) {
- emittedTaskSizeWarning = true
- logWarning(s"Stage ${task.stageId} contains a task of very large
size " +
- s"(${serializedTask.limit / 1024} KB). The maximum recommended
task size is " +
- s"${TaskSetManager.TASK_SIZE_TO_WARN_KB} KB.")
- }
+
addRunningTask(taskId)
// We used to log the time it takes to serialize the task, but
task size is already
// a good proxy to task serialization time.
// val timeTaken = clock.getTime() - startTime
val taskName = s"task ${info.id} in stage ${taskSet.id}"
logInfo(s"Starting $taskName (TID $taskId, $host, executor
${info.executorId}, " +
- s"partition ${task.partitionId}, $taskLocality,
${serializedTask.limit} bytes)")
--- End diff --
Hmm we probably shouldn't lose this message, because I know some folks rely
on this logging to diagnose issues where their tasks get large. I think the
best thing to do would be to replace the logDebug() in
CoarseGrainedSchedulerBackend (line 273) with this log message at INFO level
(and eliminate the message here), and then `encode()` also needs to return the
size of the serialized task.
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