最近在搜索Netty和Zookeeper方面的文章时,看到了这篇文章《轻量级分布式 RPC 框架》,作者用Zookeeper、Netty和Spring写了一个轻量级的分布式RPC框架。花了一些时间看了下他的代码,写的干净简单,写的RPC框架可以算是一个简易版的dubbo。这个RPC框架虽小,但是麻雀虽小,五脏俱全,有兴趣的可以学习一下。
本人在这个简易版的RPC上添加了如下特性:
* 服务异步调用的支持,回调函数callback的支持
* 客户端使用长连接(在多次调用共享连接)
* 服务端异步多线程处理RPC请求
项目地址:https://github.com/luxiaoxun/NettyRpc
2、简介
RPC,即 Remote Procedure Call(远程过程调用),调用远程计算机上的服务,就像调用本地服务一样。RPC可以很好的解耦系统,如WebService就是一种基于Http协议的RPC。
这个RPC整体框架如下:
这个RPC框架使用的一些技术所解决的问题:
服务发布与订阅:服务端使用Zookeeper注册服务地址,客户端从Zookeeper获取可用的服务地址。
通信:使用Netty作为通信框架。
Spring:使用Spring配置服务,加载Bean,扫描注解。
动态代理:客户端使用代理模式透明化服务调用。
消息编解码:使用Protostuff序列化和反序列化消息。
3、服务端发布服务
使用注解标注要发布的服务
服务注解
- @Target({ElementType.TYPE})
- @Retention(RetentionPolicy.RUNTIME)
- @Component
- public @interface RpcService {
- Class<?> value();
- }
一个服务接口:
一个服务实现:使用注解标注
- @RpcService(HelloService.class)
- public class HelloServiceImpl implements HelloService {
- @Override
- public String hello(String name) {
- return "Hello! " + name;
- }
- @Override
- public String hello(Person person) {
- return "Hello! " + person.getFirstName() + " " + person.getLastName();
- }
- }
服务在启动的时候扫描得到所有的服务接口及其实现:
- @Override
- public void setApplicationContext(ApplicationContext ctx) throws BeansException {
- Map<String, Object> serviceBeanMap = ctx.getBeansWithAnnotation(RpcService.class);
- if (MapUtils.isNotEmpty(serviceBeanMap)) {
- for (Object serviceBean : serviceBeanMap.values()) {
- String interfaceName = serviceBean.getClass().getAnnotation(RpcService.class).value().getName();
- handlerMap.put(interfaceName, serviceBean);
- }
- }
- }
在Zookeeper集群上注册服务地址:
- 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) {
- AddRootNode(zk); // Add root node if not exist
- 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 e) {
- LOGGER.error("", e);
- }
- catch (InterruptedException ex){
- LOGGER.error("", ex);
- }
- return zk;
- }
- private void AddRootNode(ZooKeeper zk){
- try {
- Stat s = zk.exists(Constant.ZK_REGISTRY_PATH, false);
- if (s == null) {
- zk.create(Constant.ZK_REGISTRY_PATH, new byte[0], ZooDefs.Ids.OPEN_ACL_UNSAFE, CreateMode.PERSISTENT);
- }
- } catch (KeeperException e) {
- LOGGER.error(e.toString());
- } catch (InterruptedException e) {
- LOGGER.error(e.toString());
- }
- }
- 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 e) {
- LOGGER.error("", e);
- }
- catch (InterruptedException ex){
- LOGGER.error("", ex);
- }
- }
- }
这里在原文的基础上加了AddRootNode()判断服务父节点是否存在,如果不存在则添加一个PERSISTENT的服务父节点,这样虽然启动服务时多了点判断,但是不需要手动命令添加服务父节点了。
关于Zookeeper的使用原理,可以看这里《ZooKeeper基本原理》。
4、客户端调用服务
使用代理模式调用服务:
- 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();
- 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();
- }
- if(serverAddress != null){
- String[] array = serverAddress.split(":");
- String host = array[0];
- int port = Integer.parseInt(array[1]);
- RpcClient client = new RpcClient(host, port);
- RpcResponse response = client.send(request);
- if (response.isError()) {
- throw new RuntimeException("Response error.",new Throwable(response.getError()));
- } else {
- return response.getResult();
- }
- }
- else{
- throw new RuntimeException("No server address found!");
- }
- }
- }
- );
- }
- }
这里每次使用代理远程调用服务,从Zookeeper上获取可用的服务地址,通过RpcClient send一个Request,等待该Request的Response返回。这里原文有个比较严重的bug,在原文给出的简单的Test中是很难测出来的,原文使用了obj的wait和notifyAll来等待Response返回,会出现“假死等待”的情况:一个Request发送出去后,在obj.wait()调用之前可能Response就返回了,这时候在channelRead0里已经拿到了Response并且obj.notifyAll()已经在obj.wait()之前调用了,这时候send后再obj.wait()就出现了假死等待,客户端就一直等待在这里。使用CountDownLatch可以解决这个问题。
注意:这里每次调用的send时候才去和服务端建立连接,使用的是短连接,这种短连接在高并发时会有连接数问题,也会影响性能。
从Zookeeper上获取服务地址:
- 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);
- }
- }
- }
每次服务地址节点发生变化,都需要再次watchNode,获取新的服务地址列表。
5、消息编码
请求消息:
- 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;
- }
- }
- public class RpcResponse {
- private String requestId;
- private String error;
- private Object result;
- public boolean isError() {
- return error != null;
- }
- public String getRequestId() {
- return requestId;
- }
- public void setRequestId(String requestId) {
- this.requestId = requestId;
- }
- public String getError() {
- return error;
- }
- public void setError(String error) {
- this.error = error;
- }
- public Object getResult() {
- return result;
- }
- public void setResult(Object result) {
- this.result = result;
- }
- }
消息序列化和反序列化工具:(基于 Protostuff 实现)
- 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;
- }
- /**
- * 序列化(对象 -> 字节数组)
- */
- @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();
- }
- }
- /**
- * 反序列化(字节数组 -> 对象)
- */
- 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);
- }
- }
- }
由于处理的是TCP消息,本人加了TCP的粘包处理Handler
消息编解码时开始4个字节表示消息的长度,也就是消息编码的时候,先写消息的长度,再写消息。
6、性能改进
1)服务端请求异步处理
Netty本身就是一个高性能的网络框架,从网络IO方面来说并没有太大的问题。
从这个RPC框架本身来说,在原文的基础上把Server端处理请求的过程改成了多线程异步:
- public void channelRead0(final ChannelHandlerContext ctx,final RpcRequest request) throws Exception {
- RpcServer.submit(new Runnable() {
- @Override
- public void run() {
- LOGGER.debug("Receive request " + request.getRequestId());
- RpcResponse response = new RpcResponse();
- response.setRequestId(request.getRequestId());
- try {
- Object result = handle(request);
- response.setResult(result);
- } catch (Throwable t) {
- response.setError(t.toString());
- LOGGER.error("RPC Server handle request error",t);
- }
- ctx.writeAndFlush(response).addListener(ChannelFutureListener.CLOSE).addListener(new ChannelFutureListener() {
- @Override
- public void operationComplete(ChannelFuture channelFuture) throws Exception {
- LOGGER.debug("Send response for request " + request.getRequestId());
- }
- });
- }
- });
- }
Netty 4中的Handler处理在IO线程中,如果Handler处理中有耗时的操作(如数据库相关),会让IO线程等待,影响性能。
2)服务端长连接的管理
客户端保持和服务进行长连接,不需要每次调用服务的时候进行连接,长连接的管理(通过Zookeeper获取有效的地址)。
通过监听Zookeeper服务节点值的变化,动态更新客户端和服务端保持的长连接。这个事情现在放在客户端在做,客户端保持了和所有可用服务的长连接,给客户端和服务端都造成了压力,需要解耦这个实现。
3)客户端请求异步处理
客户端请求异步处理的支持,不需要同步等待:发送一个异步请求,返回Feature,通过Feature的callback机制获取结果。
- IAsyncObjectProxy client = rpcClient.createAsync(HelloService.class);
- RPCFuture helloFuture = client.call("hello", Integer.toString(i));
- String result = (String) helloFuture.get(3000, TimeUnit.MILLISECONDS);
个人觉得该RPC的待改进项:
* 编码序列化的多协议支持。
项目持续更新中。
项目地址:https://github.com/luxiaoxun/NettyRpc
参考:
轻量级分布式 RPC 框架:http://my.oschina.net/huangyong/blog/361751
你应该知道的RPC原理:http://www.cnblogs.com/LBSer/p/4853234.html