[GitHub] [spark] adamkennedy commented on a change in pull request #32766: [SPARK-35627][CORE] Decommission executors in batches to not overload network bandwidth

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adamkennedy commented on a change in pull request #32766:
URL: https://github.com/apache/spark/pull/32766#discussion_r722748621



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File path: core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala
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@@ -478,6 +478,45 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val rpcEnv: Rp
 
   protected def minRegisteredRatio: Double = _minRegisteredRatio
 
+  @GuardedBy("CoarseGrainedSchedulerBackend.this")
+  private val executorsToDecommissionInBatches = new HashSet[String]
+
+  private val executorDecommissionEnabled = conf.get(config.DECOMMISSION_ENABLED)
+  private var periodicBatchExecutorsDecommissionThread: Option[ScheduledExecutorService] = None
+  private var periodicBatchExecutorsDecommissionTask: Option[ScheduledFuture[_]] = None
+
+  if (executorDecommissionEnabled) {
+    /**
+     * Start a thread which runs a task periodically to decommission executors.

Review comment:
       ... and prioritization if possible. If Spark has chosen to decommission but in the mean time the cluster forces several less optimal nodes to die, it may produce more work that no longer requires the Spark-chosen executor to decommission any more.




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