cloud-fan commented on a change in pull request #31167:
URL: https://github.com/apache/spark/pull/31167#discussion_r559895632
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/AdaptiveSparkPlanExec.scala
##########
@@ -190,7 +191,36 @@ case class AdaptiveSparkPlanExec(
executionId.foreach(onUpdatePlan(_, result.newStages.map(_.plan)))
// Start materialization of all new stages and fail fast if any
stages failed eagerly
- result.newStages.foreach { stage =>
+
+ // SPARK-33933: we should materialize broadcast stages first and
wait the
+ // materialization finish before materialize other stages, to avoid
waiting
+ // for broadcast tasks to be scheduled and leading to broadcast
timeout.
+ val broadcastMaterializationFutures = result.newStages
+ .filter(_.isInstanceOf[BroadcastQueryStageExec])
+ .map { stage =>
+ var future: Future[Any] = null
+ try {
+ future = stage.materialize()
+ future.onComplete { res =>
+ if (res.isSuccess) {
+ events.offer(StageSuccess(stage, res.get))
+ } else {
+ events.offer(StageFailure(stage, res.failed.get))
+ }
+ }(AdaptiveSparkPlanExec.executionContext)
+ } catch {
+ case e: Throwable =>
+ cleanUpAndThrowException(Seq(e), Some(stage.id))
+ }
+ future
+ }
+
+ // Wait for the materialization of all broadcast stages finish
+ broadcastMaterializationFutures.foreach(ThreadUtils.awaitReady(_,
Duration.Inf))
Review comment:
It's great to have a better fix to guarantee the job submission order,
but the current one is not (can cause perf regression if the resource is
sufficient). Guarantee query stage submission is not great but it's better than
doing nothing. If we agree with the compromise, then we should write UT to
verify the behavior, which is the query stage submission order.
If you don't like this compromise, let's slow down and think about how to
fix the problem without perf regression.
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