attilapiros commented on a change in pull request #35881:
URL: https://github.com/apache/spark/pull/35881#discussion_r829167205
##########
File path:
core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala
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@@ -780,15 +805,53 @@ class CoarseGrainedSchedulerBackend(scheduler:
TaskSchedulerImpl, val rpcEnv: Rp
(scheduler.sc.resourceProfileManager.resourceProfileFromId(rpid), num)
}
val response = synchronized {
+ val oldResourceProfileToNumExecutors =
requestedTotalExecutorsPerResourceProfile.map {
+ case (rp, num) =>
+ (rp.id, num)
+ }.toMap
this.requestedTotalExecutorsPerResourceProfile.clear()
this.requestedTotalExecutorsPerResourceProfile ++=
resourceProfileToNumExecutors
this.numLocalityAwareTasksPerResourceProfileId =
numLocalityAwareTasksPerResourceProfileId
this.rpHostToLocalTaskCount = hostToLocalTaskCount
+ updateExecRequestTimes(oldResourceProfileToNumExecutors,
resourceProfileIdToNumExecutors)
doRequestTotalExecutors(requestedTotalExecutorsPerResourceProfile.toMap)
}
defaultAskTimeout.awaitResult(response)
}
+ private def updateExecRequestTimes(oldProfile: Map[Int, Int], newProfile:
Map[Int, Int]): Unit = {
+ newProfile.map {
+ case (k, v) =>
+ val delta = v - oldProfile.getOrElse(k, 0)
+ if (delta != 0) {
+ updateExecRequestTime(k, delta)
+ }
+ }
Review comment:
Should we process those keys (resource profiles) which is in the
`oldProfile` but missing from the `newProfile`?
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