mridulm commented on code in PR #52792:
URL: https://github.com/apache/spark/pull/52792#discussion_r2594690824
##########
core/src/main/scala/org/apache/spark/executor/Executor.scala:
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@@ -381,7 +381,28 @@ private[spark] class Executor(
tr.kill(killMark._1, killMark._2)
killMarks.remove(taskId)
}
- threadPool.execute(tr)
+ try {
+ threadPool.execute(tr)
+ } catch {
+ case t: Throwable =>
+ try {
+ logError(log"Executor launch task ${MDC(TASK_NAME,
taskDescription.name)} failed," +
+ log" reason: ${MDC(REASON, t.getMessage)}")
+ context.statusUpdate(
+ taskDescription.taskId,
+ TaskState.FAILED,
+ env.closureSerializer.newInstance().serialize(new
ExceptionFailure(t, Seq.empty)))
+ } catch {
+ case oom: OutOfMemoryError =>
Review Comment:
I agree with @cloud-fan - special handling, especially of OOM, is not very
robust.
This is one of the reasons why `OnOutOfMemoryError` is set for YARN - better
to fail the executor than get it into unpredictable states.
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