Github user jiangxb1987 commented on a diff in the pull request:
https://github.com/apache/spark/pull/21758#discussion_r205102656
--- Diff:
core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala ---
@@ -359,20 +366,55 @@ private[spark] class TaskSchedulerImpl(
// of locality levels so that it gets a chance to launch local tasks
on all of them.
// NOTE: the preferredLocality order: PROCESS_LOCAL, NODE_LOCAL,
NO_PREF, RACK_LOCAL, ANY
for (taskSet <- sortedTaskSets) {
- var launchedAnyTask = false
- var launchedTaskAtCurrentMaxLocality = false
- for (currentMaxLocality <- taskSet.myLocalityLevels) {
- do {
- launchedTaskAtCurrentMaxLocality = resourceOfferSingleTaskSet(
- taskSet, currentMaxLocality, shuffledOffers, availableCpus,
tasks)
- launchedAnyTask |= launchedTaskAtCurrentMaxLocality
- } while (launchedTaskAtCurrentMaxLocality)
- }
- if (!launchedAnyTask) {
- taskSet.abortIfCompletelyBlacklisted(hostToExecutors)
+ // Skip the barrier taskSet if the available slots are less than the
number of pending tasks.
+ if (taskSet.isBarrier && availableSlots < taskSet.numTasks) {
--- End diff --
As listed in the design doc, support running barrier stage with dynamic
resource allocation is Non-Goal of this task. However, we do plan to better
integrate this feature with dynamic resource allocation, hopefully we can get
to work on this before Spark 3.0.
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