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轻量级分布式 RPC 框架

RPC,即 Remote Procedure Call(远程过程调用),说得通俗一点就是: 调用远程计算机上的服务,就像调用本地服务一样

RPC 可基于 HTTP 或 TCP 协议,Web Service 就是基于 HTTP 协议的 RPC ,它具有良好的跨平台性,但其性能却不如基于 TCP 协议的 RPC。会两方面会直接影响 RPC 的性能, 一是传输方式,二是序列化

众所周知, TCP 是传输层协议,HTTP 是应用层协议,而传输层较应用层更加底层,在数据传输方面,越底层越快 ,因此,在一般情况下,TCP 一定比 HTTP 快。就序列化而言, Java 提供了默认的序列化方式,但在高并发的情况下,这种方式将会带来一些性能上的瓶颈 ,于是市面上出现了一系列优秀的序列化框架,比如:Protobuf、Kryo、Hessian、Jackson 等,它们可以取代 Java 默认的序列化,从而提供更高效的性能。

为了支持高并发, 传统的阻塞式 IO 显然不太合适,因此我们需要异步的 IO,即 NIO 。Java 提供了 NIO 的解决方案,Java 7 也提供了更优秀的 NIO.2 支持,用 Java 实现 NIO 并不是遥不可及的事情,只是需要我们熟悉 NIO 的技术细节。

我们需要将服务部署在分布式环境下的不同节点上,通过服务注册的方式,让客户端来自动发现当前可用的服务,并调用这些服务。 这需要一种服务注册表(Service Registry)的组件,让它来注册分布式环境下所有的服务地址(包括:主机名与端口号 )。

应用、服务、服务注册表之间的关系见下图:

轻量级分布式 RPC 框架

每台 Server 上可发布多个 Service,这些 Service 共用一个 host 与 port,在分布式环境下会提供 Server 共同对外提供 Service。此外, 为防止 Service Registry 出现单点故障,因此需要将其搭建为集群环境

本文将为您揭晓开发轻量级分布式 RPC 框架的具体过程, 该框架基于 TCP 协议,提供了 NIO 特性,提供高效的序列化方式,同时也具备服务注册与发现的能力 。根据以上技术需求,我们可使用如下技术选型:

  1. Spring:它是最强大的依赖注入框架,也是业界的权威标准。
  2. Netty :它使 NIO 编程更加容易,屏蔽了 Java 底层的 NIO 细节。
  3. Protostuff:它基于 Protobuf 序列化框架,面向 POJO,无需编写 .proto 文件。
  4. ZooKeeper:提供服务注册与发现功能,开发分布式系统的必备选择,同时它也具备天生的集群能力。

1 第一步:编写服务接口

package com.king.zkrpc;  /**  * 定义服务接口  */ public interface HelloService {      String hello(String name); }

将该接口放在独立的客户端 jar 包中,以供应用使用。

2 第二步:编写服务接口的实现类

package com.king.zkrpc;  /**  * 实现服务接口  */ @RpcService(HelloService.class) // 指定远程接口 public class HelloServiceImpl implements HelloService {      @Override     public String hello(String name) {         return "Hello! " + name;     } }

使用RpcService注解定义在服务接口的实现类上,需要对该实现类指定远程接口,因为实现类可能会实现多个接口,一定要告诉框架哪个才是远程接口。

RpcService代码如下:

package com.king.zkrpc;  import org.springframework.stereotype.Component;  import java.lang.annotation.ElementType; import java.lang.annotation.Retention; import java.lang.annotation.RetentionPolicy; import java.lang.annotation.Target;  /**  * RPC接口注解  */ @Target({ElementType.TYPE}) @Retention(RetentionPolicy.RUNTIME) @Component // 标明可被 Spring 扫描 public @interface RpcService {      Class<?> value(); }

该注解具备 Spring 的Component注解的特性,可被 Spring 扫描。

该实现类放在服务端 jar 包中,该 jar 包还提供了一些服务端的配置文件与启动服务的引导程序。

3 第三步:配置服务端

服务端 Spring 配置文件名为spring-zk-rpc-server.xml,内容如下:

<?xml version="1.0" encoding="UTF-8"?> <beans xmlns="http://www.springframework.org/schema/beans"        xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"        xmlns:context="http://www.springframework.org/schema/context"        xsi:schemaLocation="http://www.springframework.org/schema/beans  http://www.springframework.org/schema/beans/spring-beans-3.0.xsd   http://www.springframework.org/schema/context   http://www.springframework.org/schema/context/spring-context-3.0.xsd">      <!-- 配置自动扫包 -->     <context:component-scan base-package="com.king.zkrpc"/>      <context:property-placeholder location="classpath:rpc-server-config.properties"/>      <!-- 配置服务注册组件 -->     <bean id="serviceRegistry" class="com.king.zkrpc.ServiceRegistry">         <constructor-arg name="registryAddress" value="${registry.address}"/>     </bean>      <!-- 配置 RPC 服务器 -->     <bean id="rpcServer" class="com.king.zkrpc.RpcServer">         <constructor-arg name="serverAddress" value="${server.address}"/>         <constructor-arg name="serviceRegistry" ref="serviceRegistry"/>     </bean> </beans>

具体的配置参数在rpc-server-config.properties文件中,内容如下:

<!-- lang: java --> # ZooKeeper 服务器 registry.address=127.0.0.1:2181  # RPC 服务器 server.address=127.0.0.1:8000

以上配置表明:连接本地的 ZooKeeper 服务器,并在 8000 端口上发布 RPC 服务。

4 第四步:启动服务器并发布服务

为了加载 Spring 配置文件来发布服务,只需编写一个引导程序即可:

package com.king.zkrpc;  import org.springframework.context.support.ClassPathXmlApplicationContext;  /**  * RPC服务启动入口  */ public class RpcBootstrap {      public static void main(String[] args) {         new ClassPathXmlApplicationContext("spring-zk-rpc-server.xml");     } }

运行RpcBootstrap类的main方法即可启动服务端,但还有两个重要的组件尚未实现,它们分别是: ServiceRegistry与RpcServer ,下文会给出具体实现细节。

5 第五步:实现服务注册

使用 ZooKeeper 客户端可轻松实现服务注册功能,ServiceRegistry代码如下:

package com.king.zkrpc;  import org.apache.zookeeper.*; import org.slf4j.Logger; import org.slf4j.LoggerFactory;  import java.io.IOException; import java.util.concurrent.CountDownLatch;  /**  * 连接ZK注册中心,创建服务注册目录  */ public class ServiceRegistry {      private static final Logger LOGGER = LoggerFactory.getLogger(ServiceRegistry.class);      private CountDownLatch latch = new CountDownLatch(1);      private String registryAddress;      public ServiceRegistry(String registryAddress) {         this.registryAddress = registryAddress;     }      public void register(String data) {         if (data != null) {             ZooKeeper zk = connectServer();             if (zk != null) {                 createNode(zk, data);             }         }     }      private ZooKeeper connectServer() {         ZooKeeper zk = null;         try {             zk = new ZooKeeper(registryAddress, Constant.ZK_SESSION_TIMEOUT, new Watcher() {                 @Override                 public void process(WatchedEvent event) {                     // 判断是否已连接ZK,连接后计数器递减.                     if (event.getState() == Event.KeeperState.SyncConnected) {                         latch.countDown();                     }                 }             });              // 若计数器不为0,则等待.             latch.await();         } catch (IOException | InterruptedException e) {             LOGGER.error("", e);         }         return zk;     }      private void createNode(ZooKeeper zk, String data) {         try {             byte[] bytes = data.getBytes();             String path = zk.create(Constant.ZK_DATA_PATH, bytes, ZooDefs.Ids.OPEN_ACL_UNSAFE, CreateMode.EPHEMERAL_SEQUENTIAL);             LOGGER.debug("create zookeeper node ({} => {})", path, data);         } catch (KeeperException | InterruptedException e) {             LOGGER.error("", e);         }     } }

其中,通过Constant配置了所有的常量:

package com.king.zkrpc;  /**  * ZK相关常量  */ public interface Constant {      int ZK_SESSION_TIMEOUT = 5000;      String ZK_REGISTRY_PATH = "/registry";     String ZK_DATA_PATH = ZK_REGISTRY_PATH + "/data"; }

注意:首先需要使用 ZooKeeper 客户端命令行创建/registry永久节点,用于存放所有的服务临时节点。

6 第六步:实现 RPC 服务器

使用 Netty 可实现一个支持 NIO 的 RPC 服务器,需要使用ServiceRegistry注册服务地址,RpcServer代码如下:

package com.king.zkrpc;  import io.netty.bootstrap.ServerBootstrap; import io.netty.channel.ChannelFuture; import io.netty.channel.ChannelInitializer; import io.netty.channel.ChannelOption; import io.netty.channel.EventLoopGroup; import io.netty.channel.nio.NioEventLoopGroup; import io.netty.channel.socket.SocketChannel; import io.netty.channel.socket.nio.NioServerSocketChannel; import org.apache.commons.collections4.MapUtils; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import org.springframework.beans.BeansException; import org.springframework.beans.factory.InitializingBean; import org.springframework.context.ApplicationContext; import org.springframework.context.ApplicationContextAware;  import java.util.HashMap; import java.util.Map;  /**  * 启动并注册服务  */ public class RpcServer implements ApplicationContextAware, InitializingBean {      private static final Logger LOGGER = LoggerFactory.getLogger(RpcServer.class);      private String serverAddress;     private ServiceRegistry serviceRegistry;      private Map<String, Object> handlerMap = new HashMap<>(); // 存放接口名与服务对象之间的映射关系      public RpcServer(String serverAddress) {         this.serverAddress = serverAddress;     }      public RpcServer(String serverAddress, ServiceRegistry serviceRegistry) {         this.serverAddress = serverAddress;         this.serviceRegistry = serviceRegistry;     }      @Override     public void setApplicationContext(ApplicationContext ctx) throws BeansException {         Map<String, Object> serviceBeanMap = ctx.getBeansWithAnnotation(RpcService.class); // 获取所有带有 RpcService 注解的 Spring Bean         if (MapUtils.isNotEmpty(serviceBeanMap)) {             for (Object serviceBean : serviceBeanMap.values()) {                 String interfaceName = serviceBean.getClass().getAnnotation(RpcService.class).value().getName();                 handlerMap.put(interfaceName, serviceBean);             }         }     }      @Override     public void afterPropertiesSet() throws Exception {         EventLoopGroup bossGroup = new NioEventLoopGroup();         EventLoopGroup workerGroup = new NioEventLoopGroup();         try {             ServerBootstrap bootstrap = new ServerBootstrap();             bootstrap.group(bossGroup, workerGroup).channel(NioServerSocketChannel.class)                     .childHandler(new ChannelInitializer<SocketChannel>() {                         @Override                         public void initChannel(SocketChannel channel) throws Exception {                             channel.pipeline()                                     .addLast(new RpcDecoder(RpcRequest.class)) // 将 RPC 请求进行解码(为了处理请求)                                     .addLast(new RpcEncoder(RpcResponse.class)) // 将 RPC 响应进行编码(为了返回响应)                                     .addLast(new RpcHandler(handlerMap)); // 处理 RPC 请求                         }                     })                     .option(ChannelOption.SO_BACKLOG, 128)                     .childOption(ChannelOption.SO_KEEPALIVE, true);              String[] array = serverAddress.split(":");             String host = array[0];             int port = Integer.parseInt(array[1]);              ChannelFuture future = bootstrap.bind(host, port).sync();             LOGGER.debug("server started on port {}", port);              if (serviceRegistry != null) {                 serviceRegistry.register(serverAddress); // 注册服务地址             }              future.channel().closeFuture().sync();         } finally {             workerGroup.shutdownGracefully();             bossGroup.shutdownGracefully();         }     } }

以上代码中,有两个重要的 POJO 需要描述一下, 它们分别是RpcRequest与RpcResponse

使用RpcRequest封装 RPC 请求,代码如下:

package com.king.zkrpc;  /**  * RPC请求  */ public class RpcRequest {      private String requestId;      private String className;      private String methodName;      private Class<?>[] parameterTypes;      private Object[] parameters;      public String getRequestId() {         return requestId;     }      public void setRequestId(String requestId) {         this.requestId = requestId;     }      public String getClassName() {         return className;     }      public void setClassName(String className) {         this.className = className;     }      public String getMethodName() {         return methodName;     }      public void setMethodName(String methodName) {         this.methodName = methodName;     }      public Class<?>[] getParameterTypes() {         return parameterTypes;     }      public void setParameterTypes(Class<?>[] parameterTypes) {         this.parameterTypes = parameterTypes;     }      public Object[] getParameters() {         return parameters;     }      public void setParameters(Object[] parameters) {         this.parameters = parameters;     } }

使用RpcResponse封装 RPC 响应,代码如下:

package com.king.zkrpc;  /**  * RPC响应  */ public class RpcResponse {      private String requestId;      private Throwable error;      private Object result;      public String getRequestId() {         return requestId;     }      public void setRequestId(String requestId) {         this.requestId = requestId;     }      public Throwable getError() {         return error;     }      public void setError(Throwable error) {         this.error = error;     }      public Object getResult() {         return result;     }      public void setResult(Object result) {         this.result = result;     } }

使用RpcDecoder提供 RPC 解码,只需扩展 Netty 的ByteToMessageDecoder抽象类的decode方法即可 ,代码如下:

package com.king.zkrpc;  import io.netty.buffer.ByteBuf; import io.netty.channel.ChannelHandlerContext; import io.netty.handler.codec.ByteToMessageDecoder;  import java.util.List;  /**  * RPC解码  */ public class RpcDecoder extends ByteToMessageDecoder {      private Class<?> genericClass;      public RpcDecoder(Class<?> genericClass) {         this.genericClass = genericClass;     }      @Override     public void decode(ChannelHandlerContext ctx, ByteBuf in, List<Object> out) throws Exception {         if (in.readableBytes() < 4) {             return;         }         in.markReaderIndex();         int dataLength = in.readInt();         if (dataLength < 0) {             ctx.close();         }         if (in.readableBytes() < dataLength) {             in.resetReaderIndex();             return;         }         byte[] data = new byte[dataLength];         in.readBytes(data);          Object obj = SerializationUtil.deserialize(data, genericClass);         out.add(obj);     } }

使用RpcEncoder提供 RPC 编码,只需扩展 Netty 的MessageToByteEncoder抽象类的encode方法即可 ,代码如下:

package com.king.zkrpc;  import io.netty.buffer.ByteBuf; import io.netty.channel.ChannelHandlerContext; import io.netty.handler.codec.MessageToByteEncoder;  /**  * RPC编码  */ public class RpcEncoder extends MessageToByteEncoder {      private Class<?> genericClass;      public RpcEncoder(Class<?> genericClass) {         this.genericClass = genericClass;     }      @Override     public void encode(ChannelHandlerContext ctx, Object in, ByteBuf out) throws Exception {         if (genericClass.isInstance(in)) {             byte[] data = SerializationUtil.serialize(in);             out.writeInt(data.length);             out.writeBytes(data);         }     } }

编写一个SerializationUtil工具类,使用Protostuff实现序列化:

package com.king.zkrpc;  import com.dyuproject.protostuff.LinkedBuffer; import com.dyuproject.protostuff.ProtostuffIOUtil; import com.dyuproject.protostuff.Schema; import com.dyuproject.protostuff.runtime.RuntimeSchema; import org.objenesis.Objenesis; import org.objenesis.ObjenesisStd;  import java.util.Map; import java.util.concurrent.ConcurrentHashMap;  /**  * Protostuff序列化与反序列化工具  */ public class SerializationUtil {      private static Map<Class<?>, Schema<?>> cachedSchema = new ConcurrentHashMap<>();      private static Objenesis objenesis = new ObjenesisStd(true);      private SerializationUtil() {     }      @SuppressWarnings("unchecked")     private static <T> Schema<T> getSchema(Class<T> cls) {         Schema<T> schema = (Schema<T>) cachedSchema.get(cls);         if (schema == null) {             schema = RuntimeSchema.createFrom(cls);             if (schema != null) {                 cachedSchema.put(cls, schema);             }         }         return schema;     }      @SuppressWarnings("unchecked")     public static <T> byte[] serialize(T obj) {         Class<T> cls = (Class<T>) obj.getClass();         LinkedBuffer buffer = LinkedBuffer.allocate(LinkedBuffer.DEFAULT_BUFFER_SIZE);         try {             Schema<T> schema = getSchema(cls);             return ProtostuffIOUtil.toByteArray(obj, schema, buffer);         } catch (Exception e) {             throw new IllegalStateException(e.getMessage(), e);         } finally {             buffer.clear();         }     }      public static <T> T deserialize(byte[] data, Class<T> cls) {         try {             T message = (T) objenesis.newInstance(cls);             Schema<T> schema = getSchema(cls);             ProtostuffIOUtil.mergeFrom(data, message, schema);             return message;         } catch (Exception e) {             throw new IllegalStateException(e.getMessage(), e);         }     } }

以上了 使用 Objenesis 来实例化对象,它是比 Java 反射更加强大

注意:如需要替换其它序列化框架,只需修改SerializationUtil即可。当然,更好的实现方式是提供配置项来决定使用哪种序列化方式。

使用RpcHandler中处理 RPC 请求,只需扩展 Netty 的SimpleChannelInboundHandler抽象类即可 ,代码如下:

package com.king.zkrpc;  import io.netty.channel.ChannelFutureListener; import io.netty.channel.ChannelHandlerContext; import io.netty.channel.SimpleChannelInboundHandler; import net.sf.cglib.reflect.FastClass; import net.sf.cglib.reflect.FastMethod; import org.slf4j.Logger; import org.slf4j.LoggerFactory;  import java.util.Map;  /**  * RPC服务端:请求处理过程  */ public class RpcHandler extends SimpleChannelInboundHandler<RpcRequest> {      private static final Logger LOGGER = LoggerFactory.getLogger(RpcHandler.class);      private final Map<String, Object> handlerMap;      public RpcHandler(Map<String, Object> handlerMap) {         this.handlerMap = handlerMap;     }      @Override     public void channelRead0(final ChannelHandlerContext ctx, RpcRequest request) throws Exception {         RpcResponse response = new RpcResponse();         response.setRequestId(request.getRequestId());         try {             Object result = handle(request);             response.setResult(result);         } catch (Throwable t) {             response.setError(t);         }         ctx.writeAndFlush(response).addListener(ChannelFutureListener.CLOSE);     }      private Object handle(RpcRequest request) throws Throwable {         String className = request.getClassName();         Object serviceBean = handlerMap.get(className);          Class<?> serviceClass = serviceBean.getClass();         String methodName = request.getMethodName();         Class<?>[] parameterTypes = request.getParameterTypes();         Object[] parameters = request.getParameters();          // Method method = serviceClass.getMethod(methodName, parameterTypes);         // method.setAccessible(true);         // return method.invoke(serviceBean, parameters);          FastClass serviceFastClass = FastClass.create(serviceClass);         FastMethod serviceFastMethod = serviceFastClass.getMethod(methodName, parameterTypes);         return serviceFastMethod.invoke(serviceBean, parameters);     }      @Override     public void exceptionCaught(ChannelHandlerContext ctx, Throwable cause) {         LOGGER.error("server caught exception", cause);         ctx.close();     } }

为了避免使用 Java 反射带来的性能问题,我们可以使用 CGLib 提供的反射 API,如上面用到的FastClass与FastMethod。

7 第七步:配置客户端

同样使用 Spring 配置文件来配置 RPC 客户端,spring-zk-rpc-client.xml代码如下:

<?xml version="1.0" encoding="UTF-8"?> <beans xmlns="http://www.springframework.org/schema/beans"        xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"        xmlns:context="http://www.springframework.org/schema/context"        xsi:schemaLocation="http://www.springframework.org/schema/beans  http://www.springframework.org/schema/beans/spring-beans-3.0.xsd   http://www.springframework.org/schema/context   http://www.springframework.org/schema/context/spring-context-3.0.xsd">      <context:component-scan base-package="com.king.zkrpc"/>      <context:property-placeholder location="classpath:rpc-client-config.properties"/>      <!-- 配置服务发现组件 -->     <bean id="serviceDiscovery" class="com.king.zkrpc.ServiceDiscovery">         <constructor-arg name="registryAddress" value="${registry.address}"/>     </bean>      <!-- 配置 RPC 代理 -->     <bean id="rpcProxy" class="com.king.zkrpc.RpcProxy">         <constructor-arg name="serviceDiscovery" ref="serviceDiscovery"/>     </bean> </beans>

其中rpc-client-config.properties提供了具体的配置:

<!-- lang: java --> # ZooKeeper 服务器 registry.address=127.0.0.1:2181

8 第八步:实现服务发现

同样使用 ZooKeeper 实现服务发现功能,见如下代码:

package com.king.zkrpc;  import org.apache.zookeeper.KeeperException; import org.apache.zookeeper.WatchedEvent; import org.apache.zookeeper.Watcher; import org.apache.zookeeper.ZooKeeper; import org.slf4j.Logger; import org.slf4j.LoggerFactory;  import java.io.IOException; import java.util.ArrayList; import java.util.List; import java.util.concurrent.CountDownLatch; import java.util.concurrent.ThreadLocalRandom;  /**  * 服务发现:连接ZK,添加watch事件  */ public class ServiceDiscovery {      private static final Logger LOGGER = LoggerFactory.getLogger(ServiceDiscovery.class);      private CountDownLatch latch = new CountDownLatch(1);      private volatile List<String> dataList = new ArrayList<>();      private String registryAddress;      public ServiceDiscovery(String registryAddress) {         this.registryAddress = registryAddress;          ZooKeeper zk = connectServer();         if (zk != null) {             watchNode(zk);         }     }      public String discover() {         String data = null;         int size = dataList.size();         if (size > 0) {             if (size == 1) {                 data = dataList.get(0);                 LOGGER.debug("using only data: {}", data);             } else {                 data = dataList.get(ThreadLocalRandom.current().nextInt(size));                 LOGGER.debug("using random data: {}", data);             }         }         return data;     }      private ZooKeeper connectServer() {         ZooKeeper zk = null;         try {             zk = new ZooKeeper(registryAddress, Constant.ZK_SESSION_TIMEOUT, new Watcher() {                 @Override                 public void process(WatchedEvent event) {                     if (event.getState() == Event.KeeperState.SyncConnected) {                         latch.countDown();                     }                 }             });             latch.await();         } catch (IOException | InterruptedException e) {             LOGGER.error("", e);         }         return zk;     }      private void watchNode(final ZooKeeper zk) {         try {             List<String> nodeList = zk.getChildren(Constant.ZK_REGISTRY_PATH, new Watcher() {                 @Override                 public void process(WatchedEvent event) {                     if (event.getType() == Event.EventType.NodeChildrenChanged) {                         watchNode(zk);                     }                 }             });             List<String> dataList = new ArrayList<>();             for (String node : nodeList) {                 byte[] bytes = zk.getData(Constant.ZK_REGISTRY_PATH + "/" + node, false, null);                 dataList.add(new String(bytes));             }             LOGGER.debug("node data: {}", dataList);             this.dataList = dataList;         } catch (KeeperException | InterruptedException e) {             LOGGER.error("", e);         }     } }

9 第九步:实现 RPC 代理

这里使用 Java 提供的动态代理技术实现 RPC 代理(当然也可以使用 CGLib 来实现),具体代码如下:

package com.king.zkrpc;  import net.sf.cglib.proxy.InvocationHandler; import net.sf.cglib.proxy.Proxy;  import java.lang.reflect.Method; import java.util.UUID;  /**  * 客户端RPC调用代理  */ public class RpcProxy {      private String serverAddress;     private ServiceDiscovery serviceDiscovery;      public RpcProxy(String serverAddress) {         this.serverAddress = serverAddress;     }      public RpcProxy(ServiceDiscovery serviceDiscovery) {         this.serviceDiscovery = serviceDiscovery;     }      @SuppressWarnings("unchecked")     public <T> T create(Class<?> interfaceClass) {         return (T) Proxy.newProxyInstance(             interfaceClass.getClassLoader(),             new Class<?>[]{interfaceClass},             new InvocationHandler() {                 @Override                 public Object invoke(Object proxy, Method method, Object[] args) throws Throwable {                     RpcRequest request = new RpcRequest(); // 创建并初始化 RPC 请求                     request.setRequestId(UUID.randomUUID().toString());                     request.setClassName(method.getDeclaringClass().getName());                     request.setMethodName(method.getName());                     request.setParameterTypes(method.getParameterTypes());                     request.setParameters(args);                      if (serviceDiscovery != null) {                         serverAddress = serviceDiscovery.discover(); // 发现服务                     }                      String[] array = serverAddress.split(":");                     String host = array[0];                     int port = Integer.parseInt(array[1]);                      RpcClient client = new RpcClient(host, port); // 初始化 RPC 客户端                     RpcResponse response = client.send(request); // 通过 RPC 客户端发送 RPC 请求并获取 RPC 响应                      if (response.getError() != null) {                         throw response.getError();                     } else {                         return response.getResult();                     }                 }             }         );     } }

使用RpcClient类实现 RPC 客户端,只需扩展 Netty 提供的SimpleChannelInboundHandler抽象类即可 ,代码如下:

package com.king.zkrpc;  import io.netty.bootstrap.Bootstrap; import io.netty.channel.*; import io.netty.channel.nio.NioEventLoopGroup; import io.netty.channel.socket.SocketChannel; import io.netty.channel.socket.nio.NioSocketChannel; import org.slf4j.Logger; import org.slf4j.LoggerFactory;  /**  * RPC真正调用客户端  */ public class RpcClient extends SimpleChannelInboundHandler<RpcResponse> {      private static final Logger LOGGER = LoggerFactory.getLogger(RpcClient.class);      private String host;     private int port;      private RpcResponse response;      private final Object obj = new Object();      public RpcClient(String host, int port) {         this.host = host;         this.port = port;     }      @Override     public void channelRead0(ChannelHandlerContext ctx, RpcResponse response) throws Exception {         this.response = response;          synchronized (obj) {             obj.notifyAll(); // 收到响应,唤醒线程         }     }      @Override     public void exceptionCaught(ChannelHandlerContext ctx, Throwable cause) throws Exception {         LOGGER.error("client caught exception", cause);         ctx.close();     }      public RpcResponse send(RpcRequest request) throws Exception {         EventLoopGroup group = new NioEventLoopGroup();         try {             Bootstrap bootstrap = new Bootstrap();             bootstrap.group(group).channel(NioSocketChannel.class)                 .handler(new ChannelInitializer<SocketChannel>() {                     @Override                     public void initChannel(SocketChannel channel) throws Exception {                         channel.pipeline()                             .addLast(new RpcEncoder(RpcRequest.class)) // 将 RPC 请求进行编码(为了发送请求)                             .addLast(new RpcDecoder(RpcResponse.class)) // 将 RPC 响应进行解码(为了处理响应)                             .addLast(RpcClient.this); // 使用 RpcClient 发送 RPC 请求                     }                 })                 .option(ChannelOption.SO_KEEPALIVE, true);              ChannelFuture future = bootstrap.connect(host, port).sync();             future.channel().writeAndFlush(request).sync();              synchronized (obj) {                 obj.wait(); // 未收到响应,使线程等待             }              if (response != null) {                 future.channel().closeFuture().sync();             }             return response;         } finally {             group.shutdownGracefully();         }     } }

10 第十步:发送 RPC 请求

使用 JUnit 结合 Spring 编写一个单元测试,代码如下:

<!-- lang: java --> @RunWith(SpringJUnit4ClassRunner.class) @ContextConfiguration(locations = "classpath:spring.xml") public class HelloServiceTest {      @Autowired     private RpcProxy rpcProxy;      @Test     public void helloTest() {         HelloService helloService = rpcProxy.create(HelloService.class);         String result = helloService.hello("World");         Assert.assertEquals("Hello! World", result);     } }

运行以上单元测试,如果不出意外的话,您应该会看到绿条。

11 最后,总结

本文通过 Spring + Netty + Protostuff + ZooKeeper 实现了一个轻量级 RPC 框架,使用 Spring 提供依赖注入与参数配置,使用 Netty 实现 NIO 方式的数据传输,使用 Protostuff 实现对象序列化,使用 ZooKeeper 实现服务注册与发现。使用该框架,可将服务部署到分布式环境中的任意节点上,客户端通过远程接口来调用服务端的具体实现,让服务端与客户端的开发完全分离,为实现大规模分布式应用提供了基础支持。

12 附录:Maven 依赖

<!-- lang: xml --> <!-- JUnit --> <dependency>     <groupId>junit</groupId>     <artifactId>junit</artifactId>     <version>4.11</version>     <scope>test</scope> </dependency>  <!-- SLF4J --> <dependency>     <groupId>org.slf4j</groupId>     <artifactId>slf4j-log4j12</artifactId>     <version>1.7.7</version> </dependency>  <!-- Spring --> <dependency>     <groupId>org.springframework</groupId>     <artifactId>spring-context</artifactId>     <version>3.2.12.RELEASE</version> </dependency> <dependency>     <groupId>org.springframework</groupId>     <artifactId>spring-test</artifactId>     <version>3.2.12.RELEASE</version>     <scope>test</scope> </dependency>  <!-- Netty --> <dependency>     <groupId>io.netty</groupId>     <artifactId>netty-all</artifactId>     <version>4.0.24.Final</version> </dependency>  <!-- Protostuff --> <dependency>     <groupId>com.dyuproject.protostuff</groupId>     <artifactId>protostuff-core</artifactId>     <version>1.0.8</version> </dependency> <dependency>     <groupId>com.dyuproject.protostuff</groupId>     <artifactId>protostuff-runtime</artifactId>     <version>1.0.8</version> </dependency>  <!-- ZooKeeper --> <dependency>     <groupId>org.apache.zookeeper</groupId>     <artifactId>zookeeper</artifactId>     <version>3.4.6</version> </dependency>  <!-- Apache Commons Collections --> <dependency>     <groupId>org.apache.commons</groupId>     <artifactId>commons-collections4</artifactId>     <version>4.0</version> </dependency>  <!-- Objenesis --> <dependency>     <groupId>org.objenesis</groupId>     <artifactId>objenesis</artifactId>     <version>2.1</version> </dependency>  <!-- CGLib --> <dependency>     <groupId>cglib</groupId>     <artifactId>cglib</artifactId>     <version>3.1</version> </dependency>

13 分布式RPC流程图

轻量级分布式 RPC 框架 轻量级分布式 RPC 框架

原文  http://www.importnew.com/20327.html
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