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/*
* 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.mesos
import java.io.File
import java.util.{Collections, List => JList}
import java.util.concurrent.locks.ReentrantLock
import scala.collection.JavaConverters._
import scala.collection.mutable
import scala.collection.mutable.{Buffer, HashMap, HashSet}
import org.apache.mesos.Protos.{TaskInfo => MesosTaskInfo, _}
import org.apache.spark.{SecurityManager, SparkContext, SparkException, TaskState}
import org.apache.spark.network.netty.SparkTransportConf
import org.apache.spark.network.shuffle.mesos.MesosExternalShuffleClient
import org.apache.spark.rpc.RpcEndpointAddress
import org.apache.spark.scheduler.{SlaveLost, TaskSchedulerImpl}
import org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
import org.apache.spark.util.Utils
/**
* A SchedulerBackend that runs tasks on Mesos, but uses "coarse-grained" tasks, where it holds
* onto each Mesos node for the duration of the Spark job instead of relinquishing cores whenever
* a task is done. It launches Spark tasks within the coarse-grained Mesos tasks using the
* CoarseGrainedSchedulerBackend mechanism. This class is useful for lower and more predictable
* latency.
*
* Unfortunately this has a bit of duplication from [[MesosFineGrainedSchedulerBackend]],
* but it seems hard to remove this.
*/
private[spark] class MesosCoarseGrainedSchedulerBackend(
scheduler: TaskSchedulerImpl,
sc: SparkContext,
master: String,
securityManager: SecurityManager)
extends CoarseGrainedSchedulerBackend(scheduler, sc.env.rpcEnv)
with org.apache.mesos.Scheduler
with MesosSchedulerUtils {
val MAX_SLAVE_FAILURES = 2 // Blacklist a slave after this many failures
// Maximum number of cores to acquire (TODO: we'll need more flexible controls here)
val maxCores = conf.get("spark.cores.max", Int.MaxValue.toString).toInt
private[this] val shutdownTimeoutMS =
conf.getTimeAsMs("spark.mesos.coarse.shutdownTimeout", "10s")
.ensuring(_ >= 0, "spark.mesos.coarse.shutdownTimeout must be >= 0")
// Synchronization protected by stateLock
private[this] var stopCalled: Boolean = false
// If shuffle service is enabled, the Spark driver will register with the shuffle service.
// This is for cleaning up shuffle files reliably.
private val shuffleServiceEnabled = conf.getBoolean("spark.shuffle.service.enabled", false)
// Cores we have acquired with each Mesos task ID
val coresByTaskId = new HashMap[String, Int]
var totalCoresAcquired = 0
// SlaveID -> Slave
// This map accumulates entries for the duration of the job. Slaves are never deleted, because
// we need to maintain e.g. failure state and connection state.
private val slaves = new HashMap[String, Slave]
/**
* The total number of executors we aim to have. Undefined when not using dynamic allocation.
* Initially set to 0 when using dynamic allocation, the executor allocation manager will send
* the real initial limit later.
*/
private var executorLimitOption: Option[Int] = {
if (Utils.isDynamicAllocationEnabled(conf)) {
Some(0)
} else {
None
}
}
/**
* Return the current executor limit, which may be [[Int.MaxValue]]
* before properly initialized.
*/
private[mesos] def executorLimit: Int = executorLimitOption.getOrElse(Int.MaxValue)
// private lock object protecting mutable state above. Using the intrinsic lock
// may lead to deadlocks since the superclass might also try to lock
private val stateLock = new ReentrantLock
val extraCoresPerExecutor = conf.getInt("spark.mesos.extra.cores", 0)
// Offer constraints
private val slaveOfferConstraints =
parseConstraintString(sc.conf.get("spark.mesos.constraints", ""))
// Reject offers with mismatched constraints in seconds
private val rejectOfferDurationForUnmetConstraints =
getRejectOfferDurationForUnmetConstraints(sc)
// Reject offers when we reached the maximum number of cores for this framework
private val rejectOfferDurationForReachedMaxCores =
getRejectOfferDurationForReachedMaxCores(sc)
// A client for talking to the external shuffle service
private val mesosExternalShuffleClient: Option[MesosExternalShuffleClient] = {
if (shuffleServiceEnabled) {
Some(getShuffleClient())
} else {
None
}
}
// This method is factored out for testability
protected def getShuffleClient(): MesosExternalShuffleClient = {
new MesosExternalShuffleClient(
SparkTransportConf.fromSparkConf(conf, "shuffle"),
securityManager,
securityManager.isAuthenticationEnabled(),
securityManager.isSaslEncryptionEnabled())
}
var nextMesosTaskId = 0
@volatile var appId: String = _
def newMesosTaskId(): String = {
val id = nextMesosTaskId
nextMesosTaskId += 1
id.toString
}
override def start() {
super.start()
val driver = createSchedulerDriver(
master,
MesosCoarseGrainedSchedulerBackend.this,
sc.sparkUser,
sc.appName,
sc.conf,
sc.conf.getOption("spark.mesos.driver.webui.url").orElse(sc.ui.map(_.appUIAddress)),
None,
None,
sc.conf.getOption("spark.mesos.driver.frameworkId")
)
unsetFrameworkID(sc)
startScheduler(driver)
}
def createCommand(offer: Offer, numCores: Int, taskId: String): CommandInfo = {
val executorSparkHome = conf.getOption("spark.mesos.executor.home")
.orElse(sc.getSparkHome())
.getOrElse {
throw new SparkException("Executor Spark home `spark.mesos.executor.home` is not set!")
}
val environment = Environment.newBuilder()
val extraClassPath = conf.getOption("spark.executor.extraClassPath")
extraClassPath.foreach { cp =>
environment.addVariables(
Environment.Variable.newBuilder().setName("SPARK_CLASSPATH").setValue(cp).build())
}
val extraJavaOpts = conf.get("spark.executor.extraJavaOptions", "")
// Set the environment variable through a command prefix
// to append to the existing value of the variable
val prefixEnv = conf.getOption("spark.executor.extraLibraryPath").map { p =>
Utils.libraryPathEnvPrefix(Seq(p))
}.getOrElse("")
environment.addVariables(
Environment.Variable.newBuilder()
.setName("SPARK_EXECUTOR_OPTS")
.setValue(extraJavaOpts)
.build())
sc.executorEnvs.foreach { case (key, value) =>
environment.addVariables(Environment.Variable.newBuilder()
.setName(key)
.setValue(value)
.build())
}
val command = CommandInfo.newBuilder()
.setEnvironment(environment)
val uri = conf.getOption("spark.executor.uri")
.orElse(Option(System.getenv("SPARK_EXECUTOR_URI")))
if (uri.isEmpty) {
val runScript = new File(executorSparkHome, "./bin/spark-class").getPath
command.setValue(
"%s \"%s\" org.apache.spark.executor.CoarseGrainedExecutorBackend"
.format(prefixEnv, runScript) +
s" --driver-url $driverURL" +
s" --executor-id $taskId" +
s" --hostname ${offer.getHostname}" +
s" --cores $numCores" +
s" --app-id $appId")
} else {
// Grab everything to the first '.'. We'll use that and '*' to
// glob the directory "correctly".
val basename = uri.get.split('/').last.split('.').head
command.setValue(
s"cd $basename*; $prefixEnv " +
"./bin/spark-class org.apache.spark.executor.CoarseGrainedExecutorBackend" +
s" --driver-url $driverURL" +
s" --executor-id $taskId" +
s" --hostname ${offer.getHostname}" +
s" --cores $numCores" +
s" --app-id $appId")
command.addUris(CommandInfo.URI.newBuilder().setValue(uri.get))
}
conf.getOption("spark.mesos.uris").foreach(setupUris(_, command))
command.build()
}
protected def driverURL: String = {
if (conf.contains("spark.testing")) {
"driverURL"
} else {
RpcEndpointAddress(
conf.get("spark.driver.host"),
conf.get("spark.driver.port").toInt,
CoarseGrainedSchedulerBackend.ENDPOINT_NAME).toString
}
}
override def offerRescinded(d: org.apache.mesos.SchedulerDriver, o: OfferID) {}
override def registered(
d: org.apache.mesos.SchedulerDriver, frameworkId: FrameworkID, masterInfo: MasterInfo) {
appId = frameworkId.getValue
mesosExternalShuffleClient.foreach(_.init(appId))
markRegistered()
}
override def sufficientResourcesRegistered(): Boolean = {
totalCoresAcquired >= maxCores * minRegisteredRatio
}
override def disconnected(d: org.apache.mesos.SchedulerDriver) {}
override def reregistered(d: org.apache.mesos.SchedulerDriver, masterInfo: MasterInfo) {}
/**
* Method called by Mesos to offer resources on slaves. We respond by launching an executor,
* unless we've already launched more than we wanted to.
*/
override def resourceOffers(d: org.apache.mesos.SchedulerDriver, offers: JList[Offer]) {
stateLock.synchronized {
if (stopCalled) {
logDebug("Ignoring offers during shutdown")
// Driver should simply return a stopped status on race
// condition between this.stop() and completing here
offers.asScala.map(_.getId).foreach(d.declineOffer)
return
}
logDebug(s"Received ${offers.size} resource offers.")
val (matchedOffers, unmatchedOffers) = offers.asScala.partition { offer =>
val offerAttributes = toAttributeMap(offer.getAttributesList)
matchesAttributeRequirements(slaveOfferConstraints, offerAttributes)
}
declineUnmatchedOffers(d, unmatchedOffers)
handleMatchedOffers(d, matchedOffers)
}
}
private def declineUnmatchedOffers(
d: org.apache.mesos.SchedulerDriver, offers: Buffer[Offer]): Unit = {
offers.foreach { offer =>
declineOffer(d, offer, Some("unmet constraints"),
Some(rejectOfferDurationForUnmetConstraints))
}
}
private def declineOffer(
d: org.apache.mesos.SchedulerDriver,
offer: Offer,
reason: Option[String] = None,
refuseSeconds: Option[Long] = None): Unit = {
val id = offer.getId.getValue
val offerAttributes = toAttributeMap(offer.getAttributesList)
val mem = getResource(offer.getResourcesList, "mem")
val cpus = getResource(offer.getResourcesList, "cpus")
logDebug(s"Declining offer: $id with attributes: $offerAttributes mem: $mem" +
s" cpu: $cpus for $refuseSeconds seconds" +
reason.map(r => s" (reason: $r)").getOrElse(""))
refuseSeconds match {
case Some(seconds) =>
val filters = Filters.newBuilder().setRefuseSeconds(seconds).build()
d.declineOffer(offer.getId, filters)
case _ => d.declineOffer(offer.getId)
}
}
/**
* Launches executors on accepted offers, and declines unused offers. Executors are launched
* round-robin on offers.
*
* @param d SchedulerDriver
* @param offers Mesos offers that match attribute constraints
*/
private def handleMatchedOffers(
d: org.apache.mesos.SchedulerDriver, offers: Buffer[Offer]): Unit = {
val tasks = buildMesosTasks(offers)
for (offer <- offers) {
val offerAttributes = toAttributeMap(offer.getAttributesList)
val offerMem = getResource(offer.getResourcesList, "mem")
val offerCpus = getResource(offer.getResourcesList, "cpus")
val id = offer.getId.getValue
if (tasks.contains(offer.getId)) { // accept
val offerTasks = tasks(offer.getId)
logDebug(s"Accepting offer: $id with attributes: $offerAttributes " +
s"mem: $offerMem cpu: $offerCpus. Launching ${offerTasks.size} Mesos tasks.")
for (task <- offerTasks) {
val taskId = task.getTaskId
val mem = getResource(task.getResourcesList, "mem")
val cpus = getResource(task.getResourcesList, "cpus")
logDebug(s"Launching Mesos task: ${taskId.getValue} with mem: $mem cpu: $cpus.")
}
d.launchTasks(
Collections.singleton(offer.getId),
offerTasks.asJava)
} else if (totalCoresAcquired >= maxCores) {
// Reject an offer for a configurable amount of time to avoid starving other frameworks
declineOffer(d, offer, Some("reached spark.cores.max"),
Some(rejectOfferDurationForReachedMaxCores))
} else {
declineOffer(d, offer)
}
}
}
/**
* Returns a map from OfferIDs to the tasks to launch on those offers. In order to maximize
* per-task memory and IO, tasks are round-robin assigned to offers.
*
* @param offers Mesos offers that match attribute constraints
* @return A map from OfferID to a list of Mesos tasks to launch on that offer
*/
private def buildMesosTasks(offers: Buffer[Offer]): Map[OfferID, List[MesosTaskInfo]] = {
// offerID -> tasks
val tasks = new HashMap[OfferID, List[MesosTaskInfo]].withDefaultValue(Nil)
// offerID -> resources
val remainingResources = mutable.Map(offers.map(offer =>
(offer.getId.getValue, offer.getResourcesList)): _*)
var launchTasks = true
// TODO(mgummelt): combine offers for a single slave
//
// round-robin create executors on the available offers
while (launchTasks) {
launchTasks = false
for (offer <- offers) {
val slaveId = offer.getSlaveId.getValue
val offerId = offer.getId.getValue
val resources = remainingResources(offerId)
if (canLaunchTask(slaveId, resources)) {
// Create a task
launchTasks = true
val taskId = newMesosTaskId()
val offerCPUs = getResource(resources, "cpus").toInt
val taskCPUs = executorCores(offerCPUs)
val taskMemory = executorMemory(sc)
slaves.getOrElseUpdate(slaveId, new Slave(offer.getHostname)).taskIDs.add(taskId)
val (afterCPUResources, cpuResourcesToUse) =
partitionResources(resources, "cpus", taskCPUs)
val (resourcesLeft, memResourcesToUse) =
partitionResources(afterCPUResources.asJava, "mem", taskMemory)
val taskBuilder = MesosTaskInfo.newBuilder()
.setTaskId(TaskID.newBuilder().setValue(taskId.toString).build())
.setSlaveId(offer.getSlaveId)
.setCommand(createCommand(offer, taskCPUs + extraCoresPerExecutor, taskId))
.setName("Task " + taskId)
.addAllResources(cpuResourcesToUse.asJava)
.addAllResources(memResourcesToUse.asJava)
sc.conf.getOption("spark.mesos.executor.docker.image").foreach { image =>
MesosSchedulerBackendUtil.setupContainerBuilderDockerInfo(
image,
sc.conf,
taskBuilder.getContainerBuilder
)
}
tasks(offer.getId) ::= taskBuilder.build()
remainingResources(offerId) = resourcesLeft.asJava
totalCoresAcquired += taskCPUs
coresByTaskId(taskId) = taskCPUs
}
}
}
tasks.toMap
}
private def canLaunchTask(slaveId: String, resources: JList[Resource]): Boolean = {
val offerMem = getResource(resources, "mem")
val offerCPUs = getResource(resources, "cpus").toInt
val cpus = executorCores(offerCPUs)
val mem = executorMemory(sc)
cpus > 0 &&
cpus <= offerCPUs &&
cpus + totalCoresAcquired <= maxCores &&
mem <= offerMem &&
numExecutors() < executorLimit &&
slaves.get(slaveId).map(_.taskFailures).getOrElse(0) < MAX_SLAVE_FAILURES
}
private def executorCores(offerCPUs: Int): Int = {
sc.conf.getInt("spark.executor.cores",
math.min(offerCPUs, maxCores - totalCoresAcquired))
}
override def statusUpdate(d: org.apache.mesos.SchedulerDriver, status: TaskStatus) {
val taskId = status.getTaskId.getValue
val slaveId = status.getSlaveId.getValue
val state = TaskState.fromMesos(status.getState)
logInfo(s"Mesos task $taskId is now ${status.getState}")
stateLock.synchronized {
val slave = slaves(slaveId)
// If the shuffle service is enabled, have the driver register with each one of the
// shuffle services. This allows the shuffle services to clean up state associated with
// this application when the driver exits. There is currently not a great way to detect
// this through Mesos, since the shuffle services are set up independently.
if (state.equals(TaskState.RUNNING) &&
shuffleServiceEnabled &&
!slave.shuffleRegistered) {
assume(mesosExternalShuffleClient.isDefined,
"External shuffle client was not instantiated even though shuffle service is enabled.")
// TODO: Remove this and allow the MesosExternalShuffleService to detect
// framework termination when new Mesos Framework HTTP API is available.
val externalShufflePort = conf.getInt("spark.shuffle.service.port", 7337)
logDebug(s"Connecting to shuffle service on slave $slaveId, " +
s"host ${slave.hostname}, port $externalShufflePort for app ${conf.getAppId}")
mesosExternalShuffleClient.get
.registerDriverWithShuffleService(
slave.hostname,
externalShufflePort,
sc.conf.getTimeAsMs("spark.storage.blockManagerSlaveTimeoutMs",
s"${sc.conf.getTimeAsMs("spark.network.timeout", "120s")}ms"),
sc.conf.getTimeAsMs("spark.executor.heartbeatInterval", "10s"))
slave.shuffleRegistered = true
}
if (TaskState.isFinished(state)) {
// Remove the cores we have remembered for this task, if it's in the hashmap
for (cores <- coresByTaskId.get(taskId)) {
totalCoresAcquired -= cores
coresByTaskId -= taskId
}
// If it was a failure, mark the slave as failed for blacklisting purposes
if (TaskState.isFailed(state)) {
slave.taskFailures += 1
if (slave.taskFailures >= MAX_SLAVE_FAILURES) {
logInfo(s"Blacklisting Mesos slave $slaveId due to too many failures; " +
"is Spark installed on it?")
}
}
executorTerminated(d, slaveId, taskId, s"Executor finished with state $state")
// In case we'd rejected everything before but have now lost a node
d.reviveOffers()
}
}
}
override def error(d: org.apache.mesos.SchedulerDriver, message: String) {
logError(s"Mesos error: $message")
scheduler.error(message)
}
override def stop() {
// Make sure we're not launching tasks during shutdown
stateLock.synchronized {
if (stopCalled) {
logWarning("Stop called multiple times, ignoring")
return
}
stopCalled = true
super.stop()
}
// Wait for executors to report done, or else mesosDriver.stop() will forcefully kill them.
// See SPARK-12330
val startTime = System.nanoTime()
// slaveIdsWithExecutors has no memory barrier, so this is eventually consistent
while (numExecutors() > 0 &&
System.nanoTime() - startTime < shutdownTimeoutMS * 1000L * 1000L) {
Thread.sleep(100)
}
if (numExecutors() > 0) {
logWarning(s"Timed out waiting for ${numExecutors()} remaining executors "
+ s"to terminate within $shutdownTimeoutMS ms. This may leave temporary files "
+ "on the mesos nodes.")
}
// Close the mesos external shuffle client if used
mesosExternalShuffleClient.foreach(_.close())
if (mesosDriver != null) {
mesosDriver.stop()
}
}
override def frameworkMessage(
d: org.apache.mesos.SchedulerDriver, e: ExecutorID, s: SlaveID, b: Array[Byte]) {}
/**
* Called when a slave is lost or a Mesos task finished. Updates local view on
* what tasks are running. It also notifies the driver that an executor was removed.
*/
private def executorTerminated(
d: org.apache.mesos.SchedulerDriver,
slaveId: String,
taskId: String,
reason: String): Unit = {
stateLock.synchronized {
// Do not call removeExecutor() after this scheduler backend was stopped because
// removeExecutor() internally will send a message to the driver endpoint but
// the driver endpoint is not available now, otherwise an exception will be thrown.
if (!stopCalled) {
removeExecutor(taskId, SlaveLost(reason))
}
slaves(slaveId).taskIDs.remove(taskId)
}
}
override def slaveLost(d: org.apache.mesos.SchedulerDriver, slaveId: SlaveID): Unit = {
logInfo(s"Mesos slave lost: ${slaveId.getValue}")
}
override def executorLost(
d: org.apache.mesos.SchedulerDriver, e: ExecutorID, s: SlaveID, status: Int): Unit = {
logInfo("Mesos executor lost: %s".format(e.getValue))
}
override def applicationId(): String =
Option(appId).getOrElse {
logWarning("Application ID is not initialized yet.")
super.applicationId
}
override def doRequestTotalExecutors(requestedTotal: Int): Boolean = {
// We don't truly know if we can fulfill the full amount of executors
// since at coarse grain it depends on the amount of slaves available.
logInfo("Capping the total amount of executors to " + requestedTotal)
executorLimitOption = Some(requestedTotal)
true
}
override def doKillExecutors(executorIds: Seq[String]): Boolean = {
if (mesosDriver == null) {
logWarning("Asked to kill executors before the Mesos driver was started.")
false
} else {
for (executorId <- executorIds) {
val taskId = TaskID.newBuilder().setValue(executorId).build()
mesosDriver.killTask(taskId)
}
// no need to adjust `executorLimitOption` since the AllocationManager already communicated
// the desired limit through a call to `doRequestTotalExecutors`.
// See [[o.a.s.scheduler.cluster.CoarseGrainedSchedulerBackend.killExecutors]]
true
}
}
private def numExecutors(): Int = {
slaves.values.map(_.taskIDs.size).sum
}
}
private class Slave(val hostname: String) {
val taskIDs = new HashSet[String]()
var taskFailures = 0
var shuffleRegistered = false
}
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