Return-Path: X-Original-To: archive-asf-public-internal@cust-asf2.ponee.io Delivered-To: archive-asf-public-internal@cust-asf2.ponee.io Received: from cust-asf.ponee.io (cust-asf.ponee.io [163.172.22.183]) by cust-asf2.ponee.io (Postfix) with ESMTP id 4728D200D4A for ; Tue, 14 Nov 2017 06:55:43 +0100 (CET) Received: by cust-asf.ponee.io (Postfix) id 458C0160C06; Tue, 14 Nov 2017 05:55:43 +0000 (UTC) Delivered-To: archive-asf-public@cust-asf.ponee.io Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by cust-asf.ponee.io (Postfix) with SMTP id 6492F160BF3 for ; Tue, 14 Nov 2017 06:55:42 +0100 (CET) Received: (qmail 64019 invoked by uid 500); 14 Nov 2017 05:55:41 -0000 Mailing-List: contact reviews-help@spark.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Delivered-To: mailing list reviews@spark.apache.org Received: (qmail 64001 invoked by uid 99); 14 Nov 2017 05:55:41 -0000 Received: from git1-us-west.apache.org (HELO git1-us-west.apache.org) (140.211.11.23) by apache.org (qpsmtpd/0.29) with ESMTP; Tue, 14 Nov 2017 05:55:41 +0000 Received: by git1-us-west.apache.org (ASF Mail Server at git1-us-west.apache.org, from userid 33) id 25032DFBCA; Tue, 14 Nov 2017 05:55:41 +0000 (UTC) From: liyinan926 To: reviews@spark.apache.org Reply-To: reviews@spark.apache.org References: In-Reply-To: Subject: [GitHub] spark pull request #19468: [SPARK-18278] [Scheduler] Spark on Kubernetes - B... Content-Type: text/plain Message-Id: <20171114055541.25032DFBCA@git1-us-west.apache.org> Date: Tue, 14 Nov 2017 05:55:41 +0000 (UTC) archived-at: Tue, 14 Nov 2017 05:55:43 -0000 Github user liyinan926 commented on a diff in the pull request: https://github.com/apache/spark/pull/19468#discussion_r150743119 --- Diff: resource-managers/kubernetes/core/src/main/scala/org/apache/spark/scheduler/cluster/k8s/KubernetesClusterSchedulerBackend.scala --- @@ -0,0 +1,427 @@ +/* + * 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.cluster.k8s + +import java.io.Closeable +import java.net.InetAddress +import java.util.concurrent.{ConcurrentHashMap, ExecutorService, ScheduledExecutorService, TimeUnit} +import java.util.concurrent.atomic.{AtomicInteger, AtomicLong, AtomicReference} +import javax.annotation.concurrent.GuardedBy + +import io.fabric8.kubernetes.api.model._ +import io.fabric8.kubernetes.client.{KubernetesClient, KubernetesClientException, Watcher} +import io.fabric8.kubernetes.client.Watcher.Action +import scala.collection.JavaConverters._ +import scala.collection.mutable +import scala.concurrent.{ExecutionContext, Future} + +import org.apache.spark.SparkException +import org.apache.spark.deploy.k8s.config._ +import org.apache.spark.deploy.k8s.constants._ +import org.apache.spark.rpc.{RpcAddress, RpcEndpointAddress, RpcEnv} +import org.apache.spark.scheduler.{ExecutorExited, SlaveLost, TaskSchedulerImpl} +import org.apache.spark.scheduler.cluster.{CoarseGrainedSchedulerBackend, SchedulerBackendUtils} +import org.apache.spark.util.Utils + +private[spark] class KubernetesClusterSchedulerBackend( + scheduler: TaskSchedulerImpl, + rpcEnv: RpcEnv, + executorPodFactory: ExecutorPodFactory, + kubernetesClient: KubernetesClient, + allocatorExecutor: ScheduledExecutorService, + requestExecutorsService: ExecutorService) + extends CoarseGrainedSchedulerBackend(scheduler, rpcEnv) { + + import KubernetesClusterSchedulerBackend._ + + private val EXECUTOR_ID_COUNTER = new AtomicLong(0L) + private val RUNNING_EXECUTOR_PODS_LOCK = new Object + @GuardedBy("RUNNING_EXECUTOR_PODS_LOCK") + private val runningExecutorsToPods = new mutable.HashMap[String, Pod] + private val executorPodsByIPs = new ConcurrentHashMap[String, Pod]() + private val podsWithKnownExitReasons = new ConcurrentHashMap[String, ExecutorExited]() + private val disconnectedPodsByExecutorIdPendingRemoval = new ConcurrentHashMap[String, Pod]() + + private val kubernetesNamespace = conf.get(KUBERNETES_NAMESPACE) + + private val kubernetesDriverPodName = conf + .get(KUBERNETES_DRIVER_POD_NAME) + .getOrElse(throw new SparkException("Must specify the driver pod name")) + private implicit val requestExecutorContext = ExecutionContext.fromExecutorService( + requestExecutorsService) + + private val driverPod = kubernetesClient.pods() + .inNamespace(kubernetesNamespace) + .withName(kubernetesDriverPodName) + .get() + + override val minRegisteredRatio = + if (conf.getOption("spark.scheduler.minRegisteredResourcesRatio").isEmpty) { + 0.8 + } else { + super.minRegisteredRatio + } + + private val executorWatchResource = new AtomicReference[Closeable] + protected val totalExpectedExecutors = new AtomicInteger(0) + + private val driverUrl = RpcEndpointAddress( + conf.get("spark.driver.host"), + conf.getInt("spark.driver.port", DEFAULT_DRIVER_PORT), + CoarseGrainedSchedulerBackend.ENDPOINT_NAME).toString + + private val initialExecutors = SchedulerBackendUtils.getInitialTargetExecutorNumber(conf) + + private val podAllocationInterval = conf.get(KUBERNETES_ALLOCATION_BATCH_DELAY) + + private val podAllocationSize = conf.get(KUBERNETES_ALLOCATION_BATCH_SIZE) + + private val allocatorRunnable = new Runnable { + + // Maintains a map of executor id to count of checks performed to learn the loss reason + // for an executor. + private val executorReasonCheckAttemptCounts = new mutable.HashMap[String, Int] + + override def run(): Unit = { + handleDisconnectedExecutors() + val executorsToAllocate = mutable.Map[String, Pod]() + val currentTotalRegisteredExecutors = totalRegisteredExecutors.get + val currentTotalExpectedExecutors = totalExpectedExecutors.get + val currentNodeToLocalTaskCount = getNodesWithLocalTaskCounts + if (currentTotalRegisteredExecutors < runningExecutorsToPods.size) { + logDebug("Waiting for pending executors before scaling") + } else if (currentTotalExpectedExecutors <= runningExecutorsToPods.size) { + logDebug("Maximum allowed executor limit reached. Not scaling up further.") + } else { + for (i <- 0 until math.min( + currentTotalExpectedExecutors - runningExecutorsToPods.size, podAllocationSize)) { + val executorId = EXECUTOR_ID_COUNTER.incrementAndGet().toString + val executorPod = executorPodFactory.createExecutorPod( + executorId, + applicationId(), + driverUrl, + conf.getExecutorEnv, + driverPod, + currentNodeToLocalTaskCount) + require(executorPod.getMetadata.getLabels.containsKey(SPARK_EXECUTOR_ID_LABEL), + s"Illegal internal state for pod with name ${executorPod.getMetadata.getName} - all" + + s" executor pods must contain the label $SPARK_EXECUTOR_ID_LABEL.") + val resolvedExecutorIdLabel = executorPod.getMetadata.getLabels.get( + SPARK_EXECUTOR_ID_LABEL) + require(resolvedExecutorIdLabel == executorId, + s"Illegal internal state for pod with name ${executorPod.getMetadata.getName} - all" + + s" executor pods must map the label with key ${SPARK_EXECUTOR_ID_LABEL} to the" + + s" executor's ID. This label mapped instead to: $resolvedExecutorIdLabel.") + executorsToAllocate(executorId) = executorPod + logInfo( + s"Requesting a new executor, total executors is now ${runningExecutorsToPods.size}") + } + } + val allocatedExecutors = executorsToAllocate.mapValues { pod => + Utils.tryLog { + kubernetesClient.pods().create(pod) + } + } + RUNNING_EXECUTOR_PODS_LOCK.synchronized { + allocatedExecutors.map { + case (executorId, attemptedAllocatedExecutor) => + attemptedAllocatedExecutor.map { successfullyAllocatedExecutor => + runningExecutorsToPods.put(executorId, successfullyAllocatedExecutor) + } + } + } + } + + def handleDisconnectedExecutors(): Unit = { + // For each disconnected executor, synchronize with the loss reasons that may have been found + // by the executor pod watcher. If the loss reason was discovered by the watcher, + // inform the parent class with removeExecutor. + disconnectedPodsByExecutorIdPendingRemoval.asScala.foreach { + case (executorId, executorPod) => + val knownExitReason = Option(podsWithKnownExitReasons.remove( + executorPod.getMetadata.getName)) + knownExitReason.fold { + removeExecutorOrIncrementLossReasonCheckCount(executorId) + } { executorExited => + logWarning(s"Removing executor $executorId with loss reason " + executorExited.message) + removeExecutor(executorId, executorExited) + // We keep around executors that have exit conditions caused by the application. This + // allows them to be debugged later on. Otherwise, mark them as to be deleted from the + // the API server. + if (executorExited.exitCausedByApp) { + logInfo(s"Executor $executorId exited because of the application.") + deleteExecutorFromDataStructures(executorId) + } else { + logInfo(s"Executor $executorId failed because of a framework error.") + deleteExecutorFromClusterAndDataStructures(executorId) + } + } + } + } + + def removeExecutorOrIncrementLossReasonCheckCount(executorId: String): Unit = { + val reasonCheckCount = executorReasonCheckAttemptCounts.getOrElse(executorId, 0) + if (reasonCheckCount >= MAX_EXECUTOR_LOST_REASON_CHECKS) { + removeExecutor(executorId, SlaveLost("Executor lost for unknown reasons.")) + deleteExecutorFromClusterAndDataStructures(executorId) + } else { + executorReasonCheckAttemptCounts.put(executorId, reasonCheckCount + 1) + } + } + + def deleteExecutorFromClusterAndDataStructures(executorId: String): Unit = { + deleteExecutorFromDataStructures(executorId) + .foreach(pod => kubernetesClient.pods().delete(pod)) + } + + def deleteExecutorFromDataStructures(executorId: String): Option[Pod] = { + disconnectedPodsByExecutorIdPendingRemoval.remove(executorId) + executorReasonCheckAttemptCounts -= executorId + podsWithKnownExitReasons.remove(executorId) + RUNNING_EXECUTOR_PODS_LOCK.synchronized { + runningExecutorsToPods.remove(executorId).orElse { + logWarning(s"Unable to remove pod for unknown executor $executorId") + None + } + } + } + } + + override def sufficientResourcesRegistered(): Boolean = { + totalRegisteredExecutors.get() >= initialExecutors * minRegisteredRatio + } + + override def start(): Unit = { + super.start() + executorWatchResource.set( + kubernetesClient + .pods() + .withLabel(SPARK_APP_ID_LABEL, applicationId()) + .watch(new ExecutorPodsWatcher())) + + allocatorExecutor.scheduleWithFixedDelay( + allocatorRunnable, 0L, podAllocationInterval, TimeUnit.SECONDS) + + if (!Utils.isDynamicAllocationEnabled(conf)) { + doRequestTotalExecutors(initialExecutors) + } + } + + override def stop(): Unit = { + // stop allocation of new resources and caches. + allocatorExecutor.shutdown() + + // send stop message to executors so they shut down cleanly + super.stop() + + // then delete the executor pods + Utils.tryLogNonFatalError { + val executorPodsToDelete = RUNNING_EXECUTOR_PODS_LOCK.synchronized { + val runningExecutorPodsCopy = Seq(runningExecutorsToPods.values.toSeq: _*) + runningExecutorsToPods.clear() + runningExecutorPodsCopy + } + kubernetesClient.pods().delete(executorPodsToDelete: _*) + executorPodsByIPs.clear() + val resource = executorWatchResource.getAndSet(null) + if (resource != null) { + resource.close() + } + } + Utils.tryLogNonFatalError { + logInfo("Closing kubernetes client") + kubernetesClient.close() + } + } + + /** + * @return A map of K8s cluster nodes to the number of tasks that could benefit from data + * locality if an executor launches on the cluster node. + */ + private def getNodesWithLocalTaskCounts() : Map[String, Int] = { + val nodeToLocalTaskCount = mutable.Map[String, Int]() ++ + synchronized { + hostToLocalTaskCount + } + for (pod <- executorPodsByIPs.values().asScala) { + // Remove cluster nodes that are running our executors already. + // TODO: This prefers spreading out executors across nodes. In case users want + // consolidating executors on fewer nodes, introduce a flag. See the spark.deploy.spreadOut + // flag that Spark standalone has: https://spark.apache.org/docs/latest/spark-standalone.html + nodeToLocalTaskCount.remove(pod.getSpec.getNodeName).nonEmpty || + nodeToLocalTaskCount.remove(pod.getStatus.getHostIP).nonEmpty || + nodeToLocalTaskCount.remove( + InetAddress.getByName(pod.getStatus.getHostIP).getCanonicalHostName).nonEmpty + } + nodeToLocalTaskCount.toMap[String, Int] + } + + override def doRequestTotalExecutors(requestedTotal: Int): Future[Boolean] = Future[Boolean] { + totalExpectedExecutors.set(requestedTotal) + true + } + + override def doKillExecutors(executorIds: Seq[String]): Future[Boolean] = Future[Boolean] { + val podsToDelete = mutable.Buffer[Pod]() + RUNNING_EXECUTOR_PODS_LOCK.synchronized { + for (executor <- executorIds) { + val maybeRemovedExecutor = runningExecutorsToPods.remove(executor) + maybeRemovedExecutor.foreach { executorPod => + disconnectedPodsByExecutorIdPendingRemoval.put(executor, executorPod) + podsToDelete += executorPod + } + if (maybeRemovedExecutor.isEmpty) { + logWarning(s"Unable to remove pod for unknown executor $executor") + } + } + } + kubernetesClient.pods().delete(podsToDelete: _*) + true + } + + private class ExecutorPodsWatcher extends Watcher[Pod] { + + private val DEFAULT_CONTAINER_FAILURE_EXIT_STATUS = -1 + + override def eventReceived(action: Action, pod: Pod): Unit = { + action match { + case Action.MODIFIED if (pod.getStatus.getPhase == "Running" + && pod.getMetadata.getDeletionTimestamp == null) => --- End diff -- Done. --- --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org For additional commands, e-mail: reviews-help@spark.apache.org