tgravescs commented on a change in pull request #27636: 
[SPARK-30873][CORE][YARN]Handling Node Decommissioning for Yarn cluster manger 
in Spark
URL: https://github.com/apache/spark/pull/27636#discussion_r389725623
 
 

 ##########
 File path: 
core/src/main/scala/org/apache/spark/scheduler/DecommissionTracker.scala
 ##########
 @@ -0,0 +1,405 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.scheduler
+
+import java.text.SimpleDateFormat
+import java.util.concurrent.TimeUnit
+import java.util.concurrent.atomic.{AtomicBoolean, AtomicInteger}
+
+import scala.collection.mutable.HashMap
+
+import org.apache.spark.{ExecutorAllocationClient, SparkConf, SparkContext}
+import org.apache.spark.annotation.DeveloperApi
+import org.apache.spark.internal.Logging
+import org.apache.spark.internal.config
+import org.apache.spark.util.{Clock, SystemClock, ThreadUtils, Utils}
+
+/**
+ * DecommissionTracker tracks the list of decommissioned nodes.
+ * This decommission trackers maintains the decommissioned nodes state.
+ * Decommission tracker schedules the executor decommission and shuffle
+ * decommission for that node.
+ */
+private[scheduler] class DecommissionTracker (
+  conf: SparkConf,
+  executorAllocClient: Option[ExecutorAllocationClient],
+  dagScheduler: Option[DAGScheduler],
 
 Review comment:
   why is the DAGScheduler optional here?  SparkContext.dagScheduler doesn't 
return option

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