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:

输入图片说明

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

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  1. 啊啊啊 说道:

    把项目弄个git地址更好

    Thumb up 1 Thumb down 0

  2. 左钦菠 说道:

    正在测试楼主的代码,Thrift+ZK 似乎也是不错的方案, Thrift 分装了很多 自动的序列化 通信

    Thumb up 0 Thumb down 0

  3. 小布丁 说道:

    spring.xml没贴出来….,里面是肿么配的

    Thumb up 0 Thumb down 0

  4. Lyn 说道:

    不错,不过轻量级RPC的话,直接上dubbo不就好了?不过这样更能深入理解RPC本质

    Thumb up 0 Thumb down 0

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