Github user brad-kaiser commented on a diff in the pull request:
https://github.com/apache/spark/pull/19041#discussion_r140841617
--- Diff: core/src/main/scala/org/apache/spark/RecoverCacheShutdown.scala
---
@@ -0,0 +1,234 @@
+/*
+ * 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
+
+import java.util.concurrent.{ScheduledFuture, TimeUnit}
+
+import scala.collection.mutable
+import scala.concurrent.{ExecutionContext, Future}
+import scala.util.Failure
+
+import org.apache.spark.internal.Logging
+import org.apache.spark.rpc.RpcEndpointRef
+import org.apache.spark.storage.{BlockId, BlockManagerId, RDDBlockId}
+import org.apache.spark.storage.BlockManagerMessages.{GetCachedBlocks,
GetMemoryStatus, GetSizeOfBlocks, ReplicateOneBlock}
+import org.apache.spark.util.ThreadUtils
+
+/**
+ * Responsible for asynchronously replicating all of an executors cached
blocks, and then shutting
+ * it down.
+ */
+final private class RecoverCacheShutdown(
+ state: RecoverCacheShutdownState,
+ conf: SparkConf)
+ extends Logging {
+
+ private val threadPool =
ThreadUtils.newDaemonCachedThreadPool("recover-cache-shutdown-pool")
+ private implicit val asyncExecutionContext =
ExecutionContext.fromExecutorService(threadPool)
+
+ /**
+ * Start the recover cache shutdown process for these executors
+ *
+ * @param execIds the executors to start shutting down
+ */
+ def startExecutorKill(execIds: Seq[String]): Unit = {
+ logDebug(s"Recover cached data before shutting down executors
${execIds.mkString(", ")}.")
+ checkForReplicableBlocks(execIds)
+ }
+
+ /**
+ * Stops all thread pools
+ *
+ * @return
+ */
+ def stop(): java.util.List[Runnable] = {
+ threadPool.shutdownNow()
+ state.stop()
+ }
+
+ /**
+ * Get list of cached blocks from BlockManagerMaster. If there are
cached blocks, replicate them,
+ * otherwise kill the executors
+ *
+ * @param execIds the executors to check
+ */
+ private def checkForReplicableBlocks(execIds: Seq[String]) =
state.getBlocks(execIds).foreach {
+ case (executorId, NoMoreBlocks) => state.killExecutor(executorId)
+ case (executorId, NotEnoughMemory) => state.killExecutor(executorId)
+ case (executorId, HasCachedBlocks) => replicateBlocks(executorId)
+ }
+
+ /**
+ * Replicate one cached block on an executor. If there are more, repeat.
If there are none, check
+ * with the block manager master again. If there is an error, go ahead
and kill executor.
+ *
+ * @param execId the executor to save a block one
+ */
+ private def replicateBlocks(execId: String): Unit = {
+ val (response, blockId) = state.replicateFirstBlock(execId)
+ response.onComplete {
+ case scala.util.Success(true) =>
+ logTrace(s"Finished replicating block
${blockId.getOrElse("unknown")} on exec $execId.")
+ replicateBlocks(execId)
+ case scala.util.Success(false) =>
checkForReplicableBlocks(Seq(execId))
+ case Failure(f) =>
+ logWarning(s"Error trying to replicate block
${blockId.getOrElse("unknown")}.", f)
+ state.killExecutor(execId)
+ }
+ }
+}
+
+private object RecoverCacheShutdown {
+ def apply(eam: ExecutorAllocationManager, conf: SparkConf):
RecoverCacheShutdown = {
+ val bmme = SparkEnv.get.blockManager.master.driverEndpoint
+ val state = new RecoverCacheShutdownState(bmme, eam, conf)
+ new RecoverCacheShutdown(state, conf)
+ }
+}
+
+/**
+ * Private class that holds state for all the executors being shutdown.
+ * @param blockManagerMasterEndpoint blockManagerMasterEndpoint
+ * @param executorAllocationManager ExecutorAllocationManager
+ * @param conf spark conf
+ */
+final private class RecoverCacheShutdownState(
+ blockManagerMasterEndpoint: RpcEndpointRef,
+ executorAllocationManager: ExecutorAllocationManager,
+ conf: SparkConf
+ ) extends Logging {
+
+ type ExecMap[T] = mutable.Map[String, T]
+
+ private val forceKillAfterS =
+
conf.getTimeAsSeconds("spark.dynamicAllocation.recoverCachedData.timeout",
"120s")
+ private val scheduler =
+
ThreadUtils.newDaemonSingleThreadScheduledExecutor("recover-cache-shutdown-timers")
+
+ private val blocksToSave: ExecMap[mutable.PriorityQueue[RDDBlockId]] =
new mutable.HashMap
+ private val savedBlocks: ExecMap[mutable.HashSet[RDDBlockId]] = new
mutable.HashMap
+ private val killTimers: ExecMap[ScheduledFuture[_]] = new mutable.HashMap
+
+ /**
+ * Query Block Manager Master for cached blocks.
+ * @param execIds the executors to query
+ * @return a map of executorId to its replication state.
+ */
+ def getBlocks(execIds: Seq[String]): Map[String,
ExecutorReplicationState] = synchronized {
+ logDebug(s"Get all RDD blocks for executors: ${execIds.mkString(",
")}.")
+ execIds.map { id =>
+ if (isThereEnoughMemory(id)) {
--- End diff --
I rewrote this code and simplified it. I don't call GetMemoryStatus for
every executor anymore.
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