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:
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:
- Spring:它是最强大的依赖注入框架,也是业界的权威标准。
- Netty:它使 NIO 编程更加容易,屏蔽了 Java 底层的 NIO 细节。
- Protostuff:它基于 Protobuf 序列化框架,面向 POJO,无需编写 .proto 文件。
- 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。
相关 Maven 依赖请见最后附录。
第一步:编写服务接口
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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。
第二步:编写服务接口的实现类
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@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:
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@Target ({ElementType.TYPE}) @Retention (RetentionPolicy.RUNTIME) @Component // 表明可被 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。
第三步:配置服务端
服务端 Spring 配置文件名为spring.xml,内容如下:
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< beans ...> < context:component-scan base-package = "com.xxx.rpc.sample.server" /> < context:property-placeholder location = "classpath:config.properties" /> <!-- 配置服务注册组件 --> < bean id = "serviceRegistry" class = "com.xxx.rpc.registry.ServiceRegistry" > < constructor-arg name = "registryAddress" value = "${registry.address}" /> </ bean > <!-- 配置 RPC 服务器 --> < bean id = "rpcServer" class = "com.xxx.rpc.server.RpcServer" > < constructor-arg name = "serverAddress" value = "${server.address}" /> < constructor-arg name = "serviceRegistry" ref = "serviceRegistry" /> </ bean > </ beans > |
具体的配置参数在config.properties文件中,内容如下:
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# 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。
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:
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public class RpcBootstrap { public static void main(String[] args) { new ClassPathXmlApplicationContext( "spring.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。
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:
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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) { if (event.getState() == Event.KeeperState.SyncConnected) { latch.countDown(); } } }); 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:
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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。
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:
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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:
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public class RpcRequest { private String requestId; private String className; private String methodName; private Class<?>[] parameterTypes; private Object[] parameters; // getter/setter... } |
使用RpcResponse封装 RPC 响应,代码如下:
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public class RpcResponse { private String requestId; private Throwable error; private Object result; // getter/setter... } |
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:
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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:
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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:
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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:
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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。
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.xml代码如下:
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< beans ...> < context:property-placeholder location = "classpath:config.properties" /> <!-- 配置服务发现组件 --> < bean id = "serviceDiscovery" class = "com.xxx.rpc.registry.ServiceDiscovery" > < constructor-arg name = "registryAddress" value = "${registry.address}" /> </ bean > <!-- 配置 RPC 代理 --> < bean id = "rpcProxy" class = "com.xxx.rpc.client.RpcProxy" > < constructor-arg name = "serviceDiscovery" ref = "serviceDiscovery" /> </ bean > </ beans > |
其中config.properties提供了具体的配置:
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# ZooKeeper 服务器 registry.address=127.0.0.1:2181 |
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:
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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); } } } |
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:
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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.isError()) { 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:
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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(); } } } |
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:
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@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。
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。
附录:Maven 依赖
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<!-- 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 > |