[GitHub] [spark] attilapiros commented on a diff in pull request #39825: [SPARK-42261][SPARK-42260][K8S] Log Allocation Stalls and Trigger Allocation event without blocking on snapshot

["attilapiros (via GitHub)" <gi...@apache.org>]

attilapiros commented on code in PR #39825:
URL: https://github.com/apache/spark/pull/39825#discussion_r1092616469


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resource-managers/kubernetes/core/src/main/scala/org/apache/spark/scheduler/cluster/k8s/ExecutorPodsAllocator.scala:
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@@ -141,9 +143,26 @@ class ExecutorPodsAllocator(
       totalExpectedExecutorsPerResourceProfileId.put(rp.id, numExecs)
     }
     logDebug(s"Set total expected execs to $totalExpectedExecutorsPerResourceProfileId")
-    if (numOutstandingPods.get() == 0) {
+    if (numOutstandingPods.get() < maxPendingPods) {

Review Comment:
   The [default of KUBERNETES_MAX_PENDING_PODS is Int.MaxValue](https://github.com/apache/spark/blob/master/resource-managers/kubernetes/core/src/main/scala/org/apache/spark/deploy/k8s/Config.scala#L737) (too keep the old behaviour when it was introduced)  and the `numOutstandingPods` main intention was to slow down upscaling at very steep peaks:
   https://github.com/apache/spark/blob/b5b40113a64b4dbbcd4efe86da4409f2be8e9c56/resource-managers/kubernetes/core/src/main/scala/org/apache/spark/scheduler/cluster/k8s/ExecutorPodsAllocator.scala#L397-L399
   
   What about to use the allocation batch size (more a factor of it as good lower limit)?
    
   



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