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org.apache.flink.runtime.minicluster.LocalFlinkMiniCluster.scala Maven / Gradle / Ivy
/*
* 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.flink.runtime.minicluster
import java.net.InetAddress
import java.util.concurrent.{Executor, ScheduledExecutorService}
import akka.actor.{ActorRef, ActorSystem, Props}
import org.apache.flink.api.common.JobID
import org.apache.flink.api.common.io.FileOutputFormat
import org.apache.flink.configuration.{ConfigConstants, Configuration, QueryableStateOptions, TaskManagerOptions}
import org.apache.flink.core.fs.Path
import org.apache.flink.runtime.checkpoint.CheckpointRecoveryFactory
import org.apache.flink.runtime.clusterframework.FlinkResourceManager
import org.apache.flink.runtime.clusterframework.standalone.StandaloneResourceManager
import org.apache.flink.runtime.clusterframework.types.{ResourceID, ResourceIDRetrievable}
import org.apache.flink.runtime.execution.librarycache.BlobLibraryCacheManager
import org.apache.flink.runtime.executiongraph.restart.RestartStrategyFactory
import org.apache.flink.runtime.highavailability.{HighAvailabilityServices, HighAvailabilityServicesUtils}
import org.apache.flink.runtime.instance.InstanceManager
import org.apache.flink.runtime.io.disk.iomanager.IOManager
import org.apache.flink.runtime.io.network.NetworkEnvironment
import org.apache.flink.runtime.io.network.netty.NettyConfig
import org.apache.flink.runtime.jobmanager.scheduler.Scheduler
import org.apache.flink.runtime.jobmanager.{JobManager, MemoryArchivist, SubmittedJobGraphStore}
import org.apache.flink.runtime.jobmaster.JobMaster
import org.apache.flink.runtime.leaderelection.LeaderElectionService
import org.apache.flink.runtime.leaderretrieval.LeaderRetrievalService
import org.apache.flink.runtime.memory.MemoryManager
import org.apache.flink.runtime.messages.JobManagerMessages
import org.apache.flink.runtime.messages.JobManagerMessages.{RunningJobsStatus, StoppingFailure, StoppingResponse}
import org.apache.flink.runtime.metrics.MetricRegistry
import org.apache.flink.runtime.taskexecutor.{TaskExecutor, TaskManagerConfiguration, TaskManagerServices, TaskManagerServicesConfiguration}
import org.apache.flink.runtime.taskmanager.{TaskManager, TaskManagerLocation}
import org.apache.flink.runtime.util.EnvironmentInformation
import scala.concurrent.{Await, ExecutionContext}
import scala.concurrent.duration.FiniteDuration
/**
* Local Flink mini cluster which executes all [[TaskManager]]s and the [[JobManager]] in the same
* JVM. It extends the [[FlinkMiniCluster]] by having convenience functions to setup Flink's
* configuration and implementations to create [[JobManager]] and [[TaskManager]].
*
* @param userConfiguration Configuration object with the user provided configuration values
* @param singleActorSystem true if all actors (JobManager and TaskManager) shall be run in the same
* [[ActorSystem]], otherwise false
*/
class LocalFlinkMiniCluster(
userConfiguration: Configuration,
highAvailabilityServices: HighAvailabilityServices,
singleActorSystem: Boolean) extends FlinkMiniCluster(
userConfiguration,
highAvailabilityServices,
singleActorSystem) {
def this(userConfiguration: Configuration, useSingleActorSystem: Boolean) = {
this(
userConfiguration,
HighAvailabilityServicesUtils.createAvailableOrEmbeddedServices(
userConfiguration,
ExecutionContext.global),
useSingleActorSystem)
}
def this(userConfiguration: Configuration) = this(userConfiguration, true)
// --------------------------------------------------------------------------
override def generateConfiguration(userConfiguration: Configuration): Configuration = {
val config = getDefaultConfig
setDefaultCiConfig(config)
config.addAll(userConfiguration)
setMemory(config)
initializeIOFormatClasses(config)
// Disable queryable state server if nothing else is configured explicitly
if (!config.containsKey(QueryableStateOptions.SERVER_ENABLE.key())) {
LOG.info("Disabled queryable state server")
config.setBoolean(QueryableStateOptions.SERVER_ENABLE, false)
}
config
}
//------------------------------------------------------------------------------------------------
// Actor classes
//------------------------------------------------------------------------------------------------
val jobManagerClass: Class[_ <: JobManager] = classOf[JobManager]
val taskManagerClass: Class[_ <: TaskManager] = classOf[TaskManager]
val memoryArchivistClass: Class[_ <: MemoryArchivist] = classOf[MemoryArchivist]
val resourceManagerClass: Class[_ <: FlinkResourceManager[_ <: ResourceIDRetrievable]] =
classOf[StandaloneResourceManager]
//------------------------------------------------------------------------------------------------
// Start methods for the distributed components
//------------------------------------------------------------------------------------------------
override def startJobManager(index: Int, system: ActorSystem): ActorRef = {
val config = originalConfiguration.clone()
val jobManagerName = getJobManagerName(index)
val archiveName = getArchiveName(index)
val jobManagerPort = config.getInteger(
ConfigConstants.JOB_MANAGER_IPC_PORT_KEY,
ConfigConstants.DEFAULT_JOB_MANAGER_IPC_PORT)
if(jobManagerPort > 0) {
config.setInteger(ConfigConstants.JOB_MANAGER_IPC_PORT_KEY, jobManagerPort + index)
}
val (instanceManager,
scheduler,
libraryCacheManager,
restartStrategyFactory,
timeout,
archiveCount,
archivePath,
jobRecoveryTimeout,
metricsRegistry) = JobManager.createJobManagerComponents(
config,
futureExecutor,
ioExecutor,
highAvailabilityServices.createBlobStore())
if (config.getBoolean(ConfigConstants.LOCAL_START_WEBSERVER, false)) {
metricsRegistry.get.startQueryService(system, null)
}
val archive = system.actorOf(
getArchiveProps(
memoryArchivistClass,
archiveCount,
archivePath),
archiveName)
system.actorOf(
getJobManagerProps(
jobManagerClass,
config,
futureExecutor,
ioExecutor,
instanceManager,
scheduler,
libraryCacheManager,
archive,
restartStrategyFactory,
timeout,
highAvailabilityServices.getJobManagerLeaderElectionService(
HighAvailabilityServices.DEFAULT_JOB_ID),
highAvailabilityServices.getSubmittedJobGraphStore(),
highAvailabilityServices.getCheckpointRecoveryFactory(),
jobRecoveryTimeout,
metricsRegistry),
jobManagerName)
}
override def startResourceManager(index: Int, system: ActorSystem): ActorRef = {
val config = originalConfiguration.clone()
val resourceManagerName = getResourceManagerName(index)
val resourceManagerPort = config.getInteger(
ConfigConstants.RESOURCE_MANAGER_IPC_PORT_KEY,
ConfigConstants.DEFAULT_RESOURCE_MANAGER_IPC_PORT)
if(resourceManagerPort > 0) {
config.setInteger(ConfigConstants.RESOURCE_MANAGER_IPC_PORT_KEY, resourceManagerPort + index)
}
val resourceManagerProps = getResourceManagerProps(
resourceManagerClass,
config,
highAvailabilityServices.getJobManagerLeaderRetriever(
HighAvailabilityServices.DEFAULT_JOB_ID))
system.actorOf(resourceManagerProps, resourceManagerName)
}
override def startTaskManager(index: Int, system: ActorSystem): ActorRef = {
val config = originalConfiguration.clone()
val rpcPort = config.getInteger(
ConfigConstants.TASK_MANAGER_IPC_PORT_KEY,
ConfigConstants.DEFAULT_TASK_MANAGER_IPC_PORT)
val dataPort = config.getInteger(
ConfigConstants.TASK_MANAGER_DATA_PORT_KEY,
ConfigConstants.DEFAULT_TASK_MANAGER_DATA_PORT)
if (rpcPort > 0) {
config.setInteger(ConfigConstants.TASK_MANAGER_IPC_PORT_KEY, rpcPort + index)
}
if (dataPort > 0) {
config.setInteger(ConfigConstants.TASK_MANAGER_DATA_PORT_KEY, dataPort + index)
}
val localExecution = numTaskManagers == 1
val taskManagerActorName = if (singleActorSystem) {
TaskExecutor.TASK_MANAGER_NAME + "_" + (index + 1)
} else {
TaskExecutor.TASK_MANAGER_NAME
}
val resourceID = ResourceID.generate() // generate random resource id
val taskManagerAddress = InetAddress.getByName(hostname)
val taskManagerConfiguration = TaskManagerConfiguration.fromConfiguration(config)
val taskManagerServicesConfiguration = TaskManagerServicesConfiguration.fromConfiguration(
config,
taskManagerAddress,
localExecution)
val taskManagerServices = TaskManagerServices.fromConfiguration(
taskManagerServicesConfiguration,
resourceID)
val metricRegistry = taskManagerServices.getMetricRegistry()
val props = getTaskManagerProps(
taskManagerClass,
taskManagerConfiguration,
resourceID,
taskManagerServices.getTaskManagerLocation(),
taskManagerServices.getMemoryManager(),
taskManagerServices.getIOManager(),
taskManagerServices.getNetworkEnvironment,
metricRegistry)
if (config.getBoolean(ConfigConstants.LOCAL_START_WEBSERVER, false)) {
metricRegistry.startQueryService(system, resourceID)
}
system.actorOf(props, taskManagerActorName)
}
//------------------------------------------------------------------------------------------------
// Props for the distributed components
//------------------------------------------------------------------------------------------------
def getArchiveProps(
archiveClass: Class[_ <: MemoryArchivist],
archiveCount: Int,
arhivePath: Option[Path]): Props = {
JobManager.getArchiveProps(archiveClass, archiveCount, Option.empty)
}
def getJobManagerProps(
jobManagerClass: Class[_ <: JobManager],
configuration: Configuration,
futureExecutor: ScheduledExecutorService,
ioExecutor: Executor,
instanceManager: InstanceManager,
scheduler: Scheduler,
libraryCacheManager: BlobLibraryCacheManager,
archive: ActorRef,
restartStrategyFactory: RestartStrategyFactory,
timeout: FiniteDuration,
leaderElectionService: LeaderElectionService,
submittedJobGraphStore: SubmittedJobGraphStore,
checkpointRecoveryFactory: CheckpointRecoveryFactory,
jobRecoveryTimeout: FiniteDuration,
metricsRegistry: Option[MetricRegistry])
: Props = {
JobManager.getJobManagerProps(
jobManagerClass,
configuration,
futureExecutor,
ioExecutor,
instanceManager,
scheduler,
libraryCacheManager,
archive,
restartStrategyFactory,
timeout,
leaderElectionService,
submittedJobGraphStore,
checkpointRecoveryFactory,
jobRecoveryTimeout,
metricsRegistry)
}
def getTaskManagerProps(
taskManagerClass: Class[_ <: TaskManager],
taskManagerConfig: TaskManagerConfiguration,
resourceID: ResourceID,
taskManagerLocation: TaskManagerLocation,
memoryManager: MemoryManager,
ioManager: IOManager,
networkEnvironment: NetworkEnvironment,
metricsRegistry: MetricRegistry): Props = {
TaskManager.getTaskManagerProps(
taskManagerClass,
taskManagerConfig,
resourceID,
taskManagerLocation,
memoryManager,
ioManager,
networkEnvironment,
highAvailabilityServices,
metricsRegistry)
}
def getResourceManagerProps(
resourceManagerClass: Class[_ <: FlinkResourceManager[_ <: ResourceIDRetrievable]],
configuration: Configuration,
leaderRetrievalService: LeaderRetrievalService): Props = {
FlinkResourceManager.getResourceManagerProps(
resourceManagerClass,
configuration,
leaderRetrievalService)
}
//------------------------------------------------------------------------------------------------
// Helper methods
//------------------------------------------------------------------------------------------------
def initializeIOFormatClasses(configuration: Configuration): Unit = {
try {
val om = classOf[FileOutputFormat[_]].getDeclaredMethod("initDefaultsFromConfiguration",
classOf[Configuration])
om.setAccessible(true)
om.invoke(null, configuration)
} catch {
case e: Exception =>
LOG.error("Cannot (re) initialize the globally loaded defaults. Some classes might not " +
"follow the specified default behaviour.")
}
}
def setMemory(config: Configuration): Unit = {
// set this only if no memory was pre-configured
if (config.getLong(TaskManagerOptions.MANAGED_MEMORY_SIZE) ==
TaskManagerOptions.MANAGED_MEMORY_SIZE.defaultValue()) {
val numTaskManager = config.getInteger(
ConfigConstants.LOCAL_NUMBER_TASK_MANAGER,
ConfigConstants.DEFAULT_LOCAL_NUMBER_TASK_MANAGER)
val memoryFraction = config.getFloat(TaskManagerOptions.MANAGED_MEMORY_FRACTION)
// full memory size
var memorySize: Long = EnvironmentInformation.getSizeOfFreeHeapMemoryWithDefrag
// compute the memory size per task manager. we assume equally much memory for
// each TaskManagers and each JobManager
memorySize /= numTaskManager + 1 // the +1 is the job manager
// for each TaskManager, subtract the memory needed for network memory buffers
memorySize -= TaskManagerServices.calculateNetworkBufferMemory(memorySize, config)
memorySize = (memorySize * memoryFraction).toLong
memorySize >>= 20 // bytes to megabytes
config.setLong(TaskManagerOptions.MANAGED_MEMORY_SIZE, memorySize)
}
}
def getDefaultConfig: Configuration = {
val config: Configuration = new Configuration()
config.setString(ConfigConstants.JOB_MANAGER_IPC_ADDRESS_KEY, hostname)
config.setInteger(ConfigConstants.JOB_MANAGER_IPC_PORT_KEY, 0)
config.setInteger(ConfigConstants.LOCAL_NUMBER_TASK_MANAGER,
ConfigConstants.DEFAULT_LOCAL_NUMBER_TASK_MANAGER)
// Reduce number of threads for local execution
config.setInteger(NettyConfig.NUM_THREADS_CLIENT, 1)
config.setInteger(NettyConfig.NUM_THREADS_SERVER, 2)
config
}
protected def getJobManagerName(index: Int): String = {
if(singleActorSystem) {
JobMaster.JOB_MANAGER_NAME + "_" + (index + 1)
} else {
JobMaster.JOB_MANAGER_NAME
}
}
protected def getResourceManagerName(index: Int): String = {
if(singleActorSystem) {
FlinkResourceManager.RESOURCE_MANAGER_NAME + "_" + (index + 1)
} else {
FlinkResourceManager.RESOURCE_MANAGER_NAME
}
}
protected def getArchiveName(index: Int): String = {
if(singleActorSystem) {
JobMaster.ARCHIVE_NAME + "_" + (index + 1)
} else {
JobMaster.ARCHIVE_NAME
}
}
// --------------------------------------------------------------------------
// Actions on running jobs
// --------------------------------------------------------------------------
def currentlyRunningJobs: Iterable[JobID] = {
val leader = getLeaderGateway(timeout)
val future = leader.ask(JobManagerMessages.RequestRunningJobsStatus, timeout)
.mapTo[RunningJobsStatus]
Await.result(future, timeout).runningJobs.map(_.getJobId)
}
def getCurrentlyRunningJobsJava(): java.util.List[JobID] = {
val list = new java.util.ArrayList[JobID]()
currentlyRunningJobs.foreach(list.add)
list
}
def stopJob(id: JobID) : Unit = {
val leader = getLeaderGateway(timeout)
val response = leader.ask(new JobManagerMessages.StopJob(id), timeout)
.mapTo[StoppingResponse]
val rc = Await.result(response, timeout)
rc match {
case failure: StoppingFailure =>
throw new Exception(s"Stopping the job with ID $id failed.", failure.cause)
case _ =>
}
}
}
