Github user squito commented on a diff in the pull request:
https://github.com/apache/spark/pull/6750#discussion_r33720045
--- Diff:
core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala ---
@@ -163,6 +163,15 @@ private[spark] class TaskSchedulerImpl(
this.synchronized {
val manager = createTaskSetManager(taskSet, maxTaskFailures)
activeTaskSets(taskSet.id) = manager
+ val stage = taskSet.stageId
+ val conflictingTaskSet = activeTaskSets.exists { case (id, ts) =>
+ // if the id matches, it really should be the same taskSet, but in
some unit tests
+ // we add new taskSets with the same id
+ id != taskSet.id && !ts.isZombie && ts.stageId == stage
+ }
+ if (conflictingTaskSet) {
+ throw new SparkIllegalStateException(s"more than one active
taskSet for stage $stage")
+ }
--- End diff --
restoring the comments from the old diff b/c they are still relevant:
from mark:
> @kayousterhout How much of a concern should the extra overhead be here?
Just wondering whether this (let's hope rare) condition might better be handled
only in a non-production environment and behind an if(debug) kind of flag.
from marcelo:
>Perhaps the code could just look for an existing task set that matches the
stage ID of the task set being added? That should be a little better than the
filter / groupBy.
good point, there isn't any need to do the `groupBy`, so I've made it
simpler.
I'd really rather leave the check in place. In fact I think this fail-fast
behavior is especially important in a *production* environment -- that's much
better than an infinite loop of failures.
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