源码目录
提交 Application 到 Spark，创建启动 Driver，在 Driver 内开始执行自己的应用程序代码。
1 程序入口
var conf: SparkConf = new SparkConf().setAppName("SparkJob_Demo").setMaster("local[*]")
val sparkContext: SparkContext = new SparkContext(conf)
sparkContext.parallelize(List("aaa", "bbb", "ccc", "ddd"), 2)
.repartition(4)
.collect()
2 进入源码
- 进入
org.apache.spark.SparkContext.scala
class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationClient {
// 省略部分内容
private var _conf: SparkConf = _
private var _eventLogDir: Option[URI] = None
private var _eventLogCodec: Option[String] = None
private var _env: SparkEnv = _
private var _jobProgressListener: JobProgressListener = _
private var _statusTracker: SparkStatusTracker = _
private var _progressBar: Option[ConsoleProgressBar] = None
private var _ui: Option[SparkUI] = None
private var _hadoopConfiguration: Configuration = _
private var _executorMemory: Int = _
private var _schedulerBackend: SchedulerBackend = _
private var _taskScheduler: TaskScheduler = _
private var _heartbeatReceiver: RpcEndpointRef = _
@volatile private var _dagScheduler: DAGScheduler = _
private var _applicationId: String = _
private var _applicationAttemptId: Option[String] = None
private var _eventLogger: Option[EventLoggingListener] = None
private var _executorAllocationManager: Option[ExecutorAllocationManager] = None
private var _cleaner: Option[ContextCleaner] = None
private var _listenerBusStarted: Boolean = false
private var _jars: Seq[String] = _
private var _files: Seq[String] = _
private var _shutdownHookRef: AnyRef = _
try {
_conf = config.clone()
_conf.validateSettings()
// Create the Spark execution environment (cache, map output tracker, etc)
_env = createSparkEnv(_conf, isLocal, listenerBus)
SparkEnv.set(_env)
_statusTracker = new SparkStatusTracker(this)
_progressBar =
if (_conf.getBoolean("spark.ui.showConsoleProgress", true) && !log.isInfoEnabled) {
Some(new ConsoleProgressBar(this))
} else {
None
}
_ui =
if (conf.getBoolean("spark.ui.enabled", true)) {
Some(SparkUI.createLiveUI(this, _conf, listenerBus, _jobProgressListener,
_env.securityManager, appName, startTime = startTime))
} else {
// For tests, do not enable the UI
None
}
// Bind the UI before starting the task scheduler to communicate
// the bound port to the cluster manager properly
_ui.foreach(_.bind())
_hadoopConfiguration = SparkHadoopUtil.get.newConfiguration(_conf)
_executorMemory = _conf.getOption("spark.executor.memory")
.orElse(Option(System.getenv("SPARK_EXECUTOR_MEMORY")))
.orElse(Option(System.getenv("SPARK_MEM"))
.map(warnSparkMem))
.map(Utils.memoryStringToMb)
.getOrElse(1024)
// The Mesos scheduler backend relies on this environment variable to set executor memory.
// TODO: Set this only in the Mesos scheduler.
executorEnvs("SPARK_EXECUTOR_MEMORY") = executorMemory + "m"
executorEnvs ++= _conf.getExecutorEnv
executorEnvs("SPARK_USER") = sparkUser
// We need to register "HeartbeatReceiver" before "createTaskScheduler" because Executor will
// retrieve "HeartbeatReceiver" in the constructor. (SPARK-6640)
_heartbeatReceiver = env.rpcEnv.setupEndpoint(
HeartbeatReceiver.ENDPOINT_NAME, new HeartbeatReceiver(this))
// Create and start the scheduler
val (sched, ts) = SparkContext.createTaskScheduler(this, master, deployMode)
_schedulerBackend = sched
_taskScheduler = ts
_dagScheduler = new DAGScheduler(this)
_heartbeatReceiver.ask[Boolean](TaskSchedulerIsSet)
// start TaskScheduler after taskScheduler sets DAGScheduler reference in DAGScheduler's
// constructor
_taskScheduler.start()
_applicationId = _taskScheduler.applicationId()
_applicationAttemptId = taskScheduler.applicationAttemptId()
_conf.set("spark.app.id", _applicationId)
_ui.foreach(_.setAppId(_applicationId))
_env.blockManager.initialize(_applicationId)
// Optionally scale number of executors dynamically based on workload. Exposed for testing.
val dynamicAllocationEnabled = Utils.isDynamicAllocationEnabled(_conf)
_executorAllocationManager =
if (dynamicAllocationEnabled) {
Some(new ExecutorAllocationManager(this, listenerBus, _conf))
} else {
None
}
_executorAllocationManager.foreach(_.start())
setupAndStartListenerBus()
postEnvironmentUpdate()
postApplicationStart()
// Make sure the context is stopped if the user forgets about it. This avoids leaving
// unfinished event logs around after the JVM exits cleanly. It doesn't help if the JVM
// is killed, though.
_shutdownHookRef = ShutdownHookManager.addShutdownHook(
ShutdownHookManager.SPARK_CONTEXT_SHUTDOWN_PRIORITY) { () =>
logInfo("Invoking stop() from shutdown hook")
stop()
}
} catch {
case NonFatal(e) =>
logError("Error initializing SparkContext.", e)
try {
stop()
} catch {
case NonFatal(inner) =>
logError("Error stopping SparkContext after init error.", inner)
} finally {
throw e
}
}
}
初始化各种参数，设置默认值（只显示了部分内容）。
创建并启动TaskScheduler，创建DAGScheduler等，见后面文章的分析。
这里分析一下创建 Spark execution environment 的过程，即createSparkEnv(_conf, isLocal, listenerBus)
2.1 创建SparkEnv
- 进入
org.apache.spark.SparkContext.scala
private[spark] def createSparkEnv(
conf: SparkConf,
isLocal: Boolean,
listenerBus: LiveListenerBus): SparkEnv = {
SparkEnv.createDriverEnv(conf, isLocal, listenerBus, SparkContext.numDriverCores(master, conf))
}
- 进入
org.apache.spark.SparkEnv.scala
/**
* Create a SparkEnv for the driver.
*/
private[spark] def createDriverEnv(
conf: SparkConf,
isLocal: Boolean,
listenerBus: LiveListenerBus,
numCores: Int,
mockOutputCommitCoordinator: Option[OutputCommitCoordinator] = None): SparkEnv = {
assert(conf.contains(DRIVER_HOST_ADDRESS),
s"${DRIVER_HOST_ADDRESS.key} is not set on the driver!")
assert(conf.contains("spark.driver.port"), "spark.driver.port is not set on the driver!")
val bindAddress = conf.get(DRIVER_BIND_ADDRESS)
val advertiseAddress = conf.get(DRIVER_HOST_ADDRESS)
val port = conf.get("spark.driver.port").toInt
val ioEncryptionKey = if (conf.get(IO_ENCRYPTION_ENABLED)) {
Some(CryptoStreamUtils.createKey(conf))
} else {
None
}
create(
conf,
SparkContext.DRIVER_IDENTIFIER,
bindAddress,
advertiseAddress,
Option(port),
isLocal,
numCores,
ioEncryptionKey,
listenerBus = listenerBus,
mockOutputCommitCoordinator = mockOutputCommitCoordinator
)
}
该方法调用 create 方法创建 Driver 端的 SparkEnv。
- 进入
org.apache.spark.SparkEnv.scala
/**
* Helper method to create a SparkEnv for a driver or an executor.
*/
private def create(
conf: SparkConf,
executorId: String,
bindAddress: String,
advertiseAddress: String,
port: Option[Int],
isLocal: Boolean,
numUsableCores: Int,
ioEncryptionKey: Option[Array[Byte]],
listenerBus: LiveListenerBus = null,
mockOutputCommitCoordinator: Option[OutputCommitCoordinator] = None): SparkEnv = {
val isDriver = executorId == SparkContext.DRIVER_IDENTIFIER
// Listener bus is only used on the driver
if (isDriver) {
assert(listenerBus != null, "Attempted to create driver SparkEnv with null listener bus!")
}
val securityManager = new SecurityManager(conf, ioEncryptionKey)
if (isDriver) {
securityManager.initializeAuth()
}
ioEncryptionKey.foreach { _ =>
if (!securityManager.isEncryptionEnabled()) {
logWarning("I/O encryption enabled without RPC encryption: keys will be visible on the " +
"wire.")
}
}
val systemName = if (isDriver) driverSystemName else executorSystemName
val rpcEnv = RpcEnv.create(systemName, bindAddress, advertiseAddress, port.getOrElse(-1), conf,
securityManager, numUsableCores, !isDriver)
// Figure out which port RpcEnv actually bound to in case the original port is 0 or occupied.
if (isDriver) {
conf.set("spark.driver.port", rpcEnv.address.port.toString)
}
// Create an instance of the class with the given name, possibly initializing it with our conf
def instantiateClass[T](className: String): T = {
val cls = Utils.classForName(className)
// Look for a constructor taking a SparkConf and a boolean isDriver, then one taking just
// SparkConf, then one taking no arguments
try {
cls.getConstructor(classOf[SparkConf], java.lang.Boolean.TYPE)
.newInstance(conf, new java.lang.Boolean(isDriver))
.asInstanceOf[T]
} catch {
case _: NoSuchMethodException =>
try {
cls.getConstructor(classOf[SparkConf]).newInstance(conf).asInstanceOf[T]
} catch {
case _: NoSuchMethodException =>
cls.getConstructor().newInstance().asInstanceOf[T]
}
}
}
// Create an instance of the class named by the given SparkConf property, or defaultClassName
// if the property is not set, possibly initializing it with our conf
def instantiateClassFromConf[T](propertyName: String, defaultClassName: String): T = {
instantiateClass[T](conf.get(propertyName, defaultClassName))
}
val serializer = instantiateClassFromConf[Serializer](
"spark.serializer", "org.apache.spark.serializer.JavaSerializer")
logDebug(s"Using serializer: ${serializer.getClass}")
val serializerManager = new SerializerManager(serializer, conf, ioEncryptionKey)
val closureSerializer = new JavaSerializer(conf)
def registerOrLookupEndpoint(
name: String, endpointCreator: => RpcEndpoint):
RpcEndpointRef = {
if (isDriver) {
logInfo("Registering " + name)
rpcEnv.setupEndpoint(name, endpointCreator)
} else {
RpcUtils.makeDriverRef(name, conf, rpcEnv)
}
}
val broadcastManager = new BroadcastManager(isDriver, conf, securityManager)
val mapOutputTracker = if (isDriver) {
new MapOutputTrackerMaster(conf, broadcastManager, isLocal)
} else {
new MapOutputTrackerWorker(conf)
}
// Have to assign trackerEndpoint after initialization as MapOutputTrackerEndpoint
// requires the MapOutputTracker itself
mapOutputTracker.trackerEndpoint = registerOrLookupEndpoint(MapOutputTracker.ENDPOINT_NAME,
new MapOutputTrackerMasterEndpoint(
rpcEnv, mapOutputTracker.asInstanceOf[MapOutputTrackerMaster], conf))
// Let the user specify short names for shuffle managers
val shortShuffleMgrNames = Map(
"sort" -> classOf[org.apache.spark.shuffle.sort.SortShuffleManager].getName,
"tungsten-sort" -> classOf[org.apache.spark.shuffle.sort.SortShuffleManager].getName)
val shuffleMgrName = conf.get("spark.shuffle.manager", "sort")
val shuffleMgrClass =
shortShuffleMgrNames.getOrElse(shuffleMgrName.toLowerCase(Locale.ROOT), shuffleMgrName)
val shuffleManager = instantiateClass[ShuffleManager](shuffleMgrClass)
val useLegacyMemoryManager = conf.getBoolean("spark.memory.useLegacyMode", false)
val memoryManager: MemoryManager =
if (useLegacyMemoryManager) {
new StaticMemoryManager(conf, numUsableCores)
} else {
UnifiedMemoryManager(conf, numUsableCores)
}
val blockManagerPort = if (isDriver) {
conf.get(DRIVER_BLOCK_MANAGER_PORT)
} else {
conf.get(BLOCK_MANAGER_PORT)
}
val blockTransferService =
new NettyBlockTransferService(conf, securityManager, bindAddress, advertiseAddress,
blockManagerPort, numUsableCores)
val blockManagerMaster = new BlockManagerMaster(registerOrLookupEndpoint(
BlockManagerMaster.DRIVER_ENDPOINT_NAME,
new BlockManagerMasterEndpoint(rpcEnv, isLocal, conf, listenerBus)),
conf, isDriver)
// NB: blockManager is not valid until initialize() is called later.
val blockManager = new BlockManager(executorId, rpcEnv, blockManagerMaster,
serializerManager, conf, memoryManager, mapOutputTracker, shuffleManager,
blockTransferService, securityManager, numUsableCores)
val metricsSystem = if (isDriver) {
// Don't start metrics system right now for Driver.
// We need to wait for the task scheduler to give us an app ID.
// Then we can start the metrics system.
MetricsSystem.createMetricsSystem("driver", conf, securityManager)
} else {
// We need to set the executor ID before the MetricsSystem is created because sources and
// sinks specified in the metrics configuration file will want to incorporate this executor's
// ID into the metrics they report.
conf.set("spark.executor.id", executorId)
val ms = MetricsSystem.createMetricsSystem("executor", conf, securityManager)
ms.start()
ms
}
val outputCommitCoordinator = mockOutputCommitCoordinator.getOrElse {
new OutputCommitCoordinator(conf, isDriver)
}
val outputCommitCoordinatorRef = registerOrLookupEndpoint("OutputCommitCoordinator",
new OutputCommitCoordinatorEndpoint(rpcEnv, outputCommitCoordinator))
outputCommitCoordinator.coordinatorRef = Some(outputCommitCoordinatorRef)
val envInstance = new SparkEnv(
executorId,
rpcEnv,
serializer,
closureSerializer,
serializerManager,
mapOutputTracker,
shuffleManager,
broadcastManager,
blockManager,
securityManager,
metricsSystem,
memoryManager,
outputCommitCoordinator,
conf)
// Add a reference to tmp dir created by driver, we will delete this tmp dir when stop() is
// called, and we only need to do it for driver. Because driver may run as a service, and if we
// don't delete this tmp dir when sc is stopped, then will create too many tmp dirs.
if (isDriver) {
val sparkFilesDir = Utils.createTempDir(Utils.getLocalDir(conf), "userFiles").getAbsolutePath
envInstance.driverTmpDir = Some(sparkFilesDir)
}
envInstance
}
该方法是一个通用方法，用于创建 Driver端 或 Executor端 的SparkEnv。
根据 executorId 区分 Driver端 还是 Executor 端，然后分别构建 RpcEnv、Serializer、ShuffleManager、BroadcastManager 等作为参数创建 SparkEnv。