NettyRpcEnv
源码版本2.4.7
需要关注的是env里面几个关键的属性和方法如图:
1 dispatcher 分发
消息分发程序,负责将RPC消息路由到适当的端点
dispatcher的成员内部类: EndpointData实体
private class EndpointData(
val name: String,
val endpoint: RpcEndpoint,
val ref: NettyRpcEndpointRef) {
val inbox = new Inbox(ref, endpoint)
}
Inbox:收件箱,用于存储[[RpcEndpoint]]的消息并以线程安全的方式向其发布消息
process处理消息,且OnStart消息也是在此产生
// OnStart should be the first message to process
inbox.synchronized {
messages.add(OnStart)
}
/**
* Process stored messages.
*/
def process(dispatcher: Dispatcher): Unit = {
var message: InboxMessage = null
inbox.synchronized {
if (!enableConcurrent && numActiveThreads != 0) {
return
}
message = messages.poll()
if (message != null) {
numActiveThreads += 1
} else {
return
}
}
while (true) {
safelyCall(endpoint) {
message match {
case RpcMessage(_sender, content, context) =>
try {
endpoint.receiveAndReply(context).applyOrElse[Any, Unit](content, { msg =>
throw new SparkException(s"Unsupported message $message from ${_sender}")
})
} catch {
case e: Throwable =>
context.sendFailure(e)
// Throw the exception -- this exception will be caught by the safelyCall function.
// The endpoint's onError function will be called.
throw e
}
case OneWayMessage(_sender, content) =>
endpoint.receive.applyOrElse[Any, Unit](content, { msg =>
throw new SparkException(s"Unsupported message $message from ${_sender}")
})
case OnStart =>
endpoint.onStart()
if (!endpoint.isInstanceOf[ThreadSafeRpcEndpoint]) {
inbox.synchronized {
if (!stopped) {
enableConcurrent = true
}
}
}
case OnStop =>
val activeThreads = inbox.synchronized { inbox.numActiveThreads }
assert(activeThreads == 1,
s"There should be only a single active thread but found $activeThreads threads.")
dispatcher.removeRpcEndpointRef(endpoint)
endpoint.onStop()
assert(isEmpty, "OnStop should be the last message")
case RemoteProcessConnected(remoteAddress) =>
endpoint.onConnected(remoteAddress)
case RemoteProcessDisconnected(remoteAddress) =>
endpoint.onDisconnected(remoteAddress)
case RemoteProcessConnectionError(cause, remoteAddress) =>
endpoint.onNetworkError(cause, remoteAddress)
}
}
inbox.synchronized {
// "enableConcurrent" will be set to false after `onStop` is called, so we should check it
// every time.
if (!enableConcurrent && numActiveThreads != 1) {
// If we are not the only one worker, exit
numActiveThreads -= 1
return
}
message = messages.poll()
if (message == null) {
numActiveThreads -= 1
return
}
}
}
}
def post(message: InboxMessage): Unit = inbox.synchronized {
if (stopped) {
// We already put "OnStop" into "messages", so we should drop further messages
onDrop(message)
} else {
messages.add(message)
false
}
}
端点,RPC引用
private val endpoints: ConcurrentMap[String, EndpointData] =
new ConcurrentHashMap[String, EndpointData]
private val endpointRefs: ConcurrentMap[RpcEndpoint, RpcEndpointRef] =
new ConcurrentHashMap[RpcEndpoint, RpcEndpointRef]
接收消息队列, setUpEndPoint时,会向reveivers发送OnStart消息,异步启动RPC
// Track the receivers whose inboxes may contain messages.
private val receivers = new LinkedBlockingQueue[EndpointData]
注册RpcEndpoint
def registerRpcEndpoint(name: String, endpoint: RpcEndpoint): NettyRpcEndpointRef = {
val addr = RpcEndpointAddress(nettyEnv.address, name)
val endpointRef = new NettyRpcEndpointRef(nettyEnv.conf, addr, nettyEnv)
synchronized {
if (stopped) {
throw new IllegalStateException("RpcEnv has been stopped")
}
if (endpoints.putIfAbsent(name, new EndpointData(name, endpoint, endpointRef)) != null) {
throw new IllegalArgumentException(s"There is already an RpcEndpoint called $name")
}
val data = endpoints.get(name)
endpointRefs.put(data.endpoint, data.ref)
receivers.offer(data) // for the OnStart message
}
endpointRef
}
处理消息的线程池
/** Thread pool used for dispatching messages. */
private val threadpool: ThreadPoolExecutor = {
val availableCores =
if (numUsableCores > 0) numUsableCores else Runtime.getRuntime.availableProcessors()
val numThreads = nettyEnv.conf.getInt("spark.rpc.netty.dispatcher.numThreads",
math.max(2, availableCores))
val pool = ThreadUtils.newDaemonFixedThreadPool(numThreads, "dispatcher-event-loop")
for (i <- 0 until numThreads) {
pool.execute(new MessageLoop)
}
pool
}
死循环监听消息线程实现类
/** Message loop used for dispatching messages. */
private class MessageLoop extends Runnable {
override def run(): Unit = {
try {
while (true) {
try {
val data = receivers.take()
if (data == PoisonPill) {
// Put PoisonPill back so that other MessageLoops can see it.
receivers.offer(PoisonPill)
return
}
data.inbox.process(Dispatcher.this)
} catch {
case NonFatal(e) => logError(e.getMessage, e)
}
}
} catch {
case _: InterruptedException => // exit
case t: Throwable =>
try {
// Re-submit a MessageLoop so that Dispatcher will still work if
// UncaughtExceptionHandler decides to not kill JVM.
threadpool.execute(new MessageLoop)
} finally {
throw t
}
}
}
}
消息处理通过postMessage
/**
* Posts a message to a specific endpoint.
*
* @param endpointName name of the endpoint.
* @param message the message to post
* @param callbackIfStopped callback function if the endpoint is stopped.
*/
private def postMessage(
endpointName: String,
message: InboxMessage,
callbackIfStopped: (Exception) => Unit): Unit = {
val error = synchronized {
val data = endpoints.get(endpointName)
if (stopped) {
Some(new RpcEnvStoppedException())
} else if (data == null) {
Some(new SparkException(s"Could not find $endpointName."))
} else {
data.inbox.post(message)
receivers.offer(data)
None
}
}
// We don't need to call `onStop` in the `synchronized` block
error.foreach(callbackIfStopped)
}
2 startServer
启动TransportServer,并调用dispacher的registerRpcEndpoint方法触发
receivers.offer(data) // for the OnStart message
启动此RpcEnv所对应的角色类
def startServer(bindAddress: String, port: Int): Unit = {
val bootstraps: java.util.List[TransportServerBootstrap] =
if (securityManager.isAuthenticationEnabled()) {
java.util.Arrays.asList(new AuthServerBootstrap(transportConf, securityManager))
} else {
java.util.Collections.emptyList()
}
server = transportContext.createServer(bindAddress, port, bootstraps)
dispatcher.registerRpcEndpoint(
RpcEndpointVerifier.NAME, new RpcEndpointVerifier(this, dispatcher))
}
RpcEnv是Master、Worker的通信基础
调用流程: