agrawaldevesh commented on a change in pull request #29032: URL: https://github.com/apache/spark/pull/29032#discussion_r453796305
########## File path: core/src/main/scala/org/apache/spark/scheduler/DecommissionInfo.scala ########## @@ -0,0 +1,27 @@ +/* + * 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 + +/** + * Provides more detail about a decommissioning event + * @param message human readable reason for why the decommissioning is happening + * @param workerAlsoDecommissioned whether the worker is being decommissioned too. + * Used to know if the shuffle data might be lost too. + */ +private[spark] +case class DecommissionInfo(message: String, workerAlsoDecommissioned: Boolean) Review comment: DecommissionInfo is just an `info` struct. It's not the loss reason itself, so it shouldn't overload ExecutorLossReason. I didn't get the part about TaskScheduler.executorDecommission supporting other cluster managers: TaskScheduler is about task scheduling not coarse grained executor scheduling. I think it should be totally unaware of whether the decommission signal came via Yarn or K8s or whatever other cluster management strategy we have. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
