[GitHub] [spark] dongjoon-hyun commented on a change in pull request #28818: [WIP][SPARK-31198][CORE] Use graceful decommissioning as part of dynamic scaling

[GitBox <gi...@apache.org>]

dongjoon-hyun commented on a change in pull request #28818:
URL: https://github.com/apache/spark/pull/28818#discussion_r441178546



##########
File path: core/src/main/scala/org/apache/spark/scheduler/dynalloc/ExecutorMonitor.scala
##########
@@ -333,11 +335,26 @@ private[spark] class ExecutorMonitor(
   }
 
   override def onBlockUpdated(event: SparkListenerBlockUpdated): Unit = {
-    if (!event.blockUpdatedInfo.blockId.isInstanceOf[RDDBlockId]) {
-      return
-    }
     val exec = ensureExecutorIsTracked(event.blockUpdatedInfo.blockManagerId.executorId,
       UNKNOWN_RESOURCE_PROFILE_ID)
+
+    // Check if it is a shuffle file, or RDD to pick the correct codepath for update
+    if (event.blockUpdatedInfo.blockId.isInstanceOf[ShuffleDataBlockId] && shuffleTrackingEnabled) {
+      /**
+       * The executor monitor keeps track of locations of cache and shuffle blocks and this can be
+       * used to decide which executor(s) Spark should shutdown first. Since we move shuffle blocks
+       * around now this wires it up so that it keeps track of it. We only do this for data blocks
+       * as index and other blocks blocks do not necessarily mean the entire block has been
+       * committed.
+       */
+      event.blockUpdatedInfo.blockId match {
+        case ShuffleDataBlockId(shuffleId, _, _) => exec.addShuffle(shuffleId)

Review comment:
       Since we are touching `ExecutorMonitor`, when do we have a counter operation, `exec.removeShuffle`? In this PR, it seems that `executorsKilled` is used. Is it enough?
   cc @dbtsai 




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