1.RPC框架介绍
一句话介绍:RPC技术是为了解决远程调用服务的一种技术,使得调用者像调用本地服务一样方便透明。
技术对比:
1.RPC采用二进制字节码传输更加安全。
2.HTTP协议,HTTP 是应用层协议;RPC大多是TCP实现,TCP 是传输层协议。更底层的网络协议,更加高效。
2.轻量分布式RPC框架实现
2.1 服务端实现
编写服务接口
<!-- lang: java -->
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. 编写服务接口的实现类
<!-- lang: java -->
@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:
<!-- lang: java -->
@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。
3. 配置服务端
服务端 Spring 配置文件名为spring.xml,内容如下:
<!-- lang: xml -->
<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:
<!-- 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. 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:
<!-- lang: java -->
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。
5. 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:
<!-- lang: java -->
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:
<!-- lang: java -->
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.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:
<!-- lang: java -->
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:
<!-- lang: java -->
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:
<!-- lang: java -->
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:
<!-- lang: java -->
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);
}
}
<!-- lang: java -->
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:
<!-- lang: java -->
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:
<!-- lang: java -->
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:
<!-- lang: java -->
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。
2.2 客户端实现
1.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:
<!-- lang: java -->
<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:
<!-- lang: java -->
# ZooKeeper 服务器
registry.address=127.0.0.1:2181
2.实现服务发现
同样使用 ZooKeeper 实现服务发现功能,见如下代码:
<!-- lang: java -->
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);
}
}
}
3.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:
<!-- lang: java -->
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:
<!-- lang: java -->
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();
}
}
}
4.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);
}
}
本文通过 Spring + Netty + Protostuff + ZooKeeper (pigeon:Netty + Hessian + MNS)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。
3.依赖框架简介
3.1 zookeeper在RPC框架中作用
简单来说zookeeper=文件系统+监听通知机制。
提供者RPCServer:服务启动后向zookeeper注册他有的services,并将自己的ip地址和端口作为路径,创建对应的URL临时节点调用者RPCClient:调用相应服务时,找到对应的service节点,获得service所有的子节点,并且watch service节点,然后同样注册自己的znode节点调用过程:每个调用端需明确提供者和调用者的数量以及提供者相应的IP地址,之后调用端获得 service/providers的所有子节点 即获得所有的提供者的IP 使用对应负载均衡策略连接其中一个ip地址,进行rpc调度