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()。

   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。

   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

   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。

   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

   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

   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

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

   Reader 读数据接收请求

   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;
     }

   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。

   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

   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：

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。