Hadoop RPC，

Hadoop RPC，

Remote Procedure Call 远程方法调用。不需要了解网络细节，某一程序即可使用该协议请求来自网络内另一台及其程序的服务。它是一个 Client/Server 的结构,提供服务的一方称为Server，消费服务的一方称为Client。

Hadoop 底层的交互都是通过 rpc 进行的。例 如：datanode 和 namenode、tasktracker 和 jobtracker、secondary namenode 和 namenode 之间的通信都是通过 rpc 实现的。

TODO: 此文未写明了。明显需要画 4张图， rpc 原理图，Hadoop rpc 时序图， 客户端 流程图，服端流程图。最好帖几个包图＋ 类图（组件图）。待完善。

要实现远程过程调用，需要有3要素： 1、server 必须发布服务 2、在 client 和 server 两端都需要有模块来处理协议和连接 3、server 发布的服务，需要将接口给到 client

Hadoop RPC

1. 序列化层。 Client 与 Server 端通讯传递的信息采用实现自 Writable 类型
2. 函数调用层。 Hadoop RPC 通过动态代理和 java 反射实现函数调用
3. 网络传输层。Hadoop RPC 采用 TCP/IP socket 机制
4. 服务器框架层。Hadoop RPC 采用 java NIO 事件驱动模型提高 RPC Server 吞吐量

TODO 缺个 RPC 图

Hadoop RPC 源代码主要在org.apache.hadoop.ipc包下。org.apache.hadoop.ipc.RPC 内部包含5个内部类。

• Invocation ：用于封装方法名和参数，作为数据传输层，相当于VO（Value Object）。
• ClientCache ：用于存储client对象，用 socket factory 作为 hash key,存储结构为 hashMap 。
• Invoker ：是动态代理中的调用实现类，继承了 java.lang.reflect.InvocationHandler。
• Server ：是ipc.Server的实现类。
• VersionMismatch : 协议版本。

从客户端开始进行通讯源代码分析

org.apache.hadoop.ipc.Client 有5个内部类

• Call: A call waiting for a value.
• Connection: Thread that reads responses and notifies callers. Each connection owns a socket connected to a remote address. Calls are multiplexed through this socket: responses may be delivered out of order.
• ConnectionId: This class holds the address and the user ticket. The client connections to servers are uniquely identified by
• ParallelCall: Call implementation used for parallel calls.
• ParallelResults: Result collector for parallel calls.

客户端和服务端建立连接的大致执行过程为：

1. 在 Object org.apache.hadoop.ipc.RPC.Invoker.invoke(Object proxy, Method method, Object[] args) 方法中调用
   client.call(new Invocation(method, args), remoteId);

2. 上述的 new Invocation(method, args) 是 org.apache.hadoop.ipc.RPC 的内部类，它包含被调用的方法名称及其参数。此处主要是设置方法和参数。 client 为 org.apache.hadoop.ipc.Client 的实例对象。

3. org.apache.hadoop.ipc.Client.call() 方法的具体源代码。在call()方法中 getConnection()内部获取一个 org.apache.hadoop.ipc.Client.Connection 对象并启动 io 流 setupIOstreams()。

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   Writable org.apache.hadoop.ipc.Client.call(Writable param, ConnectionId remoteId) throwsInterruptedException, IOException { Call call = new Call(param); //A call waiting for a value.   // Get a connection from the pool, or create a new one and add it to the // pool.  Connections to a given ConnectionId are reused. Connection connection = getConnection(remoteId, call);// 主要在 org.apache.hadoop.net 包下。 connection.sendParam(call); //客户端发送数据过程 boolean interrupted = false; synchronized (call) {    while (!call.done) {     try {       call.wait();                           // wait for the result     } catch (InterruptedException ie) {       // save the fact that we were interrupted       interrupted = true;     }   } … … } } // Get a connection from the pool, or create a new one and add it to the // pool.  Connections to a given ConnectionId are reused. private Connection getConnection(ConnectionId remoteId,                                Call call)                                throws IOException, InterruptedException { if (!running.get()) {   // the client is stopped   throw new IOException("The client is stopped"); } Connection connection; // we could avoid this allocation for each RPC by having a  // connectionsId object and with set() method. We need to manage the // refs for keys in HashMap properly. For now its ok. do {   synchronized (connections) {     connection = connections.get(remoteId);     if (connection == null) {       connection = new Connection(remoteId);       connections.put(remoteId, connection);     }   } } while (!connection.addCall(call)); //we don't invoke the method below inside "synchronized (connections)" //block above. The reason for that is if the server happens to be slow, //it will take longer to establish a connection and that will slow the //entire system down. connection.setupIOstreams(); // 向服务段发送一个 header 并等待结果 return connection; }

4. setupIOstreams() 方法。

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   void org.apache.hadoop.ipc.Client.Connection.setupIOstreams() throws InterruptedException { // Connect to the server and set up the I/O streams. It then sends // a header to the server and starts // the connection thread that waits for responses. while (true) {       setupConnection();//  建立连接       InputStream inStream = NetUtils.getInputStream(socket); // 输入       OutputStream outStream = NetUtils.getOutputStream(socket); // 输出       writeRpcHeader(outStream);       } … … // update last activity time   touch(); // start the receiver thread after the socket connection has been set up            start(); }

5. 启动org.apache.hadoop.ipc.Client.Connection 客户端获取服务器端放回数据过程

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   void org.apache.hadoop.ipc.Client.Connection.run() while (waitForWork()) {//wait here for work - read or close connection     receiveResponse();   }

ipc.Server源码分析

ipc.Server 有6个内部类：

• Call ：用于存储客户端发来的请求
• Listener ： 监听类，用于监听客户端发来的请求，同时Listener内部还有一个静态类，Listener.Reader，当监听器监听到用户请求，便让Reader读取用户请求。
• ExceptionsHandler: 异常管理
• Responder ：响应RPC请求类，请求处理完毕，由Responder发送给请求客户端。
• Connection ：连接类，真正的客户端请求读取逻辑在这个类中。
• Handler ：请求处理类，会循环阻塞读取callQueue中的call对象，并对其进行操作。

大致过程为：

1. Namenode的初始化时，RPC的server对象是通过ipc.RPC类的getServer()方法获得的。

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   void org.apache.hadoop.hdfs.server.namenode.NameNode.initialize(Configuration conf) throwsIOException // create rpc server InetSocketAddress dnSocketAddr = getServiceRpcServerAddress(conf); if (dnSocketAddr != null) {   int serviceHandlerCount =     conf.getInt(DFSConfigKeys.DFS_NAMENODE_SERVICE_HANDLER_COUNT_KEY,                 DFSConfigKeys.DFS_NAMENODE_SERVICE_HANDLER_COUNT_DEFAULT);   this.serviceRpcServer = RPC.getServer(this, dnSocketAddr.getHostName(),       dnSocketAddr.getPort(), serviceHandlerCount,       false, conf, namesystem.getDelegationTokenSecretManager());   this.serviceRPCAddress = this.serviceRpcServer.getListenerAddress();   setRpcServiceServerAddress(conf); } … … this.server.start();  //start RPC server

2. 启动 server

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   void org.apache.hadoop.ipc.Server.start() // Starts the service.  Must be called before any calls will be handled. public synchronized void start() { responder.start(); listener.start(); handlers = new Handler[handlerCount]; for (int i = 0; i < handlerCount; i++) {   handlers[i] = new Handler(i);   handlers[i].start(); //处理call } }

3. Server处理请求, server 同样使用非阻塞 nio 以提高吞吐量

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   org.apache.hadoop.ipc.Server.Listener.Listener(Server) throws IOException public Listener() throws IOException {   address = new InetSocketAddress(bindAddress, port);   // Create a new server socket and set to non blocking mode   acceptChannel = ServerSocketChannel.open();   acceptChannel.configureBlocking(false); … … }

4. 真正建立连接

   1	void org.apache.hadoop.ipc.Server.Listener.doAccept(SelectionKey key) throws IOException,OutOfMemoryError

   Reader 读数据接收请求

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   void org.apache.hadoop.ipc.Server.Listener.doRead(SelectionKey key) throws InterruptedException try {     count = c.readAndProcess();   } catch (InterruptedException ieo) {     LOG.info(getName() + ": readAndProcess caught InterruptedException", ieo);     throw ieo;   }

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   int org.apache.hadoop.ipc.Server.Connection.readAndProcess() throws IOException,InterruptedException if (!rpcHeaderRead) {       //Every connection is expected to send the header.       if (rpcHeaderBuffer == null) {         rpcHeaderBuffer = ByteBuffer.allocate(2);       }       count = channelRead(channel, rpcHeaderBuffer);       if (count < 0 || rpcHeaderBuffer.remaining() > 0) {         return count;       }       int version = rpcHeaderBuffer.get(0); … … processOneRpc(data.array()); // 数据处理

5. 下面贴出Server.Connection类中的processOneRpc()方法和processData()方法的源码。

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   void org.apache.hadoop.ipc.Server.Connection.processOneRpc(byte[] buf) throws IOException,InterruptedException private void processOneRpc(byte[] buf) throws IOException,     InterruptedException {   if (headerRead) {     processData(buf);   } else {     processHeader(buf);     headerRead = true;     if (!authorizeConnection()) {       throw new AccessControlException("Connection from " + this           + " for protocol " + header.getProtocol()           + " is unauthorized for user " + user);     }   } }

6. 处理call

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   void org.apache.hadoop.ipc.Server.Handler.run() while (running) {     try {       final Call call = callQueue.take(); // pop the queue; maybe blocked here       … …       CurCall.set(call);       try {         // Make the call as the user via Subject.doAs, thus associating         // the call with the Subject         if (call.connection.user == null) {           value = call(call.connection.protocol, call.param,                        call.timestamp);         } else { … …}

7. 返回请求

下面贴出Server.Responder类中的doRespond()方法源码：

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void org.apache.hadoop.ipc.Server.Responder.doRespond(Call call) throws IOException     //     // Enqueue a response from the application.     //     void doRespond(Call call) throws IOException {       synchronized (call.connection.responseQueue) {         call.connection.responseQueue.addLast(call);         if (call.connection.responseQueue.size() == 1) {           processResponse(call.connection.responseQueue, true);         }       }     }

补充： notify()让因wait()进入阻塞队列里的线程（blocked状态）变为runnable，然后发出notify()动作的线程继续执行完，待其完成后，进行调度时，调用wait()的线程可能会被再次调度而进入running状态。