Github user squito commented on a diff in the pull request:
https://github.com/apache/spark/pull/13603#discussion_r69037911
--- Diff:
core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala ---
@@ -576,6 +576,59 @@ private[spark] class TaskSetManager(
}
/**
+ * Check whether the given task set has been blacklisted to the point
that it can't run anywhere.
+ *
+ * It is possible that this taskset has become impossible to schedule
*anywhere* due to the
+ * blacklist. The most common scenario would be if there are fewer
executors than
+ * spark.task.maxFailures. We need to detect this so we can fail the
task set, otherwise the job
+ * will hang.
+ *
+ * There's a tradeoff here: we could make sure all tasks in the task set
are schedulable, but that
+ * would add extra time to each iteration of the scheduling loop. Here,
we take the approach of
+ * making sure at least one of the unscheduled tasks is schedulable.
This means we may not detect
+ * the hang as quickly as we could have, but we'll always detect the
hang eventually, and the
+ * method is faster in the typical case. In the worst case, this method
can take
+ * O(maxTaskFailures + numTasks) time, but it will be faster when there
haven't been any task
+ * failures (this is because the method picks on unscheduled task, and
then iterates through each
+ * executor until it finds one that the task hasn't failed on already).
+ */
+ private[scheduler] def abortIfCompletelyBlacklisted(executors:
Iterable[String]): Unit = {
+
+ def pendingTask: Option[Int] = {
--- End diff --
oh I didn't even know about lastIndexWhere! thanks, simpler, and despite
being a minor point I appreciate learning something new :)
sorry I think I just got on the wrong track in this while thinking about
doing the lazy-removal here as well, and when I decided against it never
stepped back to simplify it.
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