attilapiros commented on a change in pull request #24245:
[SPARK-13704][CORE][YARN] Reduce rack resolution time
URL: https://github.com/apache/spark/pull/24245#discussion_r271566531
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File path: core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala
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@@ -186,8 +186,23 @@ private[spark] class TaskSetManager(
// Add all our tasks to the pending lists. We do this in reverse order
// of task index so that tasks with low indices get launched first.
- for (i <- (0 until numTasks).reverse) {
- addPendingTask(i)
+ addPendingTasks()
+
+ private def addPendingTasks(): Unit = {
+ val (_, duration) = Utils.timeTakenMs {
+ for (i <- (0 until numTasks).reverse) {
+ addPendingTask(i, resolveRacks = false)
+ }
+ // Resolve the rack for each host. This can be slow, so de-dupe the list
of hosts,
+ // and assign the rack to all relevant task indices.
+ val racks = sched.getRacksForHosts(pendingTasksForHost.keySet.toSeq)
Review comment:
I had the exact same thought when I reached that line.
Even thought about a possible solutions:
- creating a new val with the value `racks.entrySet` and generating the keys
and values from this entry set (as in entry set the key and value is bound
together the ordering will be fixed; even with one iteration the key and the
value can be generated).
- Another possible and more elegant solution is calling
`racks.asScala.unzip`.
Both solutions has some performance cost.
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