Github user brad-kaiser commented on a diff in the pull request:
https://github.com/apache/spark/pull/19041#discussion_r157595863
--- Diff: core/src/main/scala/org/apache/spark/CacheRecoveryManager.scala
---
@@ -0,0 +1,189 @@
+/*
+ * 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.{ConcurrentHashMap, ScheduledFuture, TimeUnit}
+
+import scala.collection.JavaConverters._
+import scala.collection.mutable
+import scala.concurrent.{ExecutionContext, Future}
+import scala.util.{Success => Succ}
+import scala.util.Failure
+
+import org.apache.spark.internal.Logging
+import
org.apache.spark.internal.config.DYN_ALLOCATION_CACHE_RECOVERY_TIMEOUT
+import org.apache.spark.rpc.RpcEndpointRef
+import org.apache.spark.storage.{BlockManagerId, RDDBlockId}
+import org.apache.spark.storage.BlockManagerMessages._
+import org.apache.spark.util.ThreadUtils
+
+/**
+ * Responsible for asynchronously replicating all of an executor's cached
blocks, and then shutting
+ * it down.
+ */
+final private class CacheRecoveryManager(
+ blockManagerMasterEndpoint: RpcEndpointRef,
+ executorAllocationManager: ExecutorAllocationManager,
+ conf: SparkConf)
+ extends Logging {
+
+ private val forceKillAfterS =
conf.get(DYN_ALLOCATION_CACHE_RECOVERY_TIMEOUT)
+ private val threadPool =
ThreadUtils.newDaemonCachedThreadPool("cache-recovery-manager-pool")
+ private implicit val asyncExecutionContext: ExecutionContext =
+ ExecutionContext.fromExecutorService(threadPool)
+ private val scheduler =
+
ThreadUtils.newDaemonSingleThreadScheduledExecutor("cache-recovery-shutdown-timers")
+ private val recoveringExecutors: mutable.Set[String] =
+ ConcurrentHashMap.newKeySet[String]().asScala
+
+ /**
+ * Start the recover cache shutdown process for these executors
+ *
+ * @param execIds the executors to start shutting down
+ */
+ def startCacheRecovery(execIds: Seq[String]): Unit = {
+ logDebug(s"Recover cached data before shutting down executors
${execIds.mkString(", ")}.")
+ val canBeRecovered = checkMem(execIds)
+ recoveringExecutors ++= canBeRecovered
+ val executorsWithKillTimers =
canBeRecovered.zip(canBeRecovered.map(startKillTimer))
+ executorsWithKillTimers.foreach((replicateUntilDone _).tupled)
+ }
+
+ /**
+ * Given a list of executors that will be shut down, check if there is
enough free memory on the
+ * rest of the cluster to hold their data. Return a list of just the
executors for which there
+ * will be enough space. Executors are included smallest first.
+ *
+ * @param execIds executors which will be shut down
+ * @return a Seq of the executors we do have room for
+ */
+ private def checkMem(execIds: Seq[String]): Seq[String] = {
+ val execsToShutDown = execIds.toSet
+ // Memory Status is a map of executor Id to a tuple of Max Memory and
remaining memory on that
+ // executor.
+ val allExecMemStatus: Map[String, (Long, Long)] =
blockManagerMasterEndpoint
+ .askSync[Map[BlockManagerId, (Long, Long)]](GetMemoryStatus)
+ .map { case (blockManagerId, mem) => blockManagerId.executorId ->
mem }
+
+ val (expiringMemStatus, remainingMemStatus) =
allExecMemStatus.partition {
+ case (execId, _) => execsToShutDown.contains(execId)
+ }
+ val freeMemOnRemaining = remainingMemStatus.values.map(_._2).sum
+
+ // The used mem on each executor sorted from least used mem to greatest
+ val executorAndUsedMem: Seq[(String, Long)] =
+ expiringMemStatus.map { case (execId, (maxMem, remainingMem)) =>
+ val usedMem = maxMem - remainingMem
+ execId -> usedMem
+ }.toSeq.sortBy { case (_, usedMem) => usedMem }
+
+ executorAndUsedMem
+ .scan(("start", freeMemOnRemaining)) {
+ case ((_, freeMem), (execId, usedMem)) => (execId, freeMem -
usedMem)
+ }
+ .drop(1)
+ .filter { case (_, freeMem) => freeMem > 0 }
+ .map(_._1)
+ }
+
+ /**
+ * Given an executor id, start a timer that will kill the given executor
after the configured
+ * timeout
+ *
+ * @param execId The id of the executor to be killed
+ * @return a future representing the timer
+ */
+ private def startKillTimer(execId: String): ScheduledFuture[_] = {
+ val killer = new Runnable {
+ def run(): Unit = {
+ logDebug(s"Killing $execId because timeout for recovering cached
data has expired")
+ kill(execId)
+ }
+ }
+ scheduler.schedule(killer, forceKillAfterS, TimeUnit.SECONDS)
+ }
+
+ /**
+ * Recover cached RDD blocks off of an executor until there are no more,
or until
+ * there is an error
+ *
+ * @param execId the id of the executor to be killed
+ * @param killTimer The runnable scheduled to kill this executor. Cancel
it if we finish before
+ * it does.
+ */
+ private def replicateUntilDone(execId: String, killTimer:
ScheduledFuture[_]): Unit = {
+ recoverLatestBlock(execId).onComplete {
+ case Succ(Some(blockId)) =>
+ logTrace(s"Replicated block $blockId on executor $execId")
+ replicateUntilDone(execId, killTimer)
+ case Succ(None) =>
+ killTimer.cancel(false)
+ kill(execId)
+ case Failure(e) =>
+ logWarning("Failure recovering cached data before executor $execId
shutdown", e)
+ killTimer.cancel(false)
+ kill(execId)
+ }
+ }
+
+ /**
+ * Replicate the latest cached rdd block off of this executor on to a
surviving executor, and then
+ * remove the block from this executor
+ *
+ * @param execId the executor to recover a block from
+ * @return A future holding the id of the block that was recovered or
None if there were no blocks
+ * to recover.
+ */
+ private def recoverLatestBlock(execId: String):
Future[Option[RDDBlockId]] = {
+ blockManagerMasterEndpoint
+ .ask[Option[RDDBlockId]](ReplicateLatestRDDBlock(execId,
recoveringExecutors.toSeq))
+ .andThen {
+ case Succ(Some(blockId)) =>
+
blockManagerMasterEndpoint.ask[Boolean](RemoveBlockFromExecutor(execId,
blockId))
+ case _ => // do nothing
+ }
+ }
+
+ /**
+ * Remove the executor from the list of currently recovering executors
and then kill it.
+ *
+ * @param execId the id of the executor to be killed
+ */
+ private def kill(execId: String): Unit = {
+ recoveringExecutors.remove(execId)
+ executorAllocationManager.killExecutors(Seq(execId))
--- End diff --
Not sure what you are recommending here. I take care not to call this
method twice in CacheRecoveryManager. Should I be keep track of the executors i
have killed in the past?
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