传输层的各种模式——ZeroMQ 库的使用 .

最近在研究 ZeroMQ 库的使用，所以在这里总结一下各种模式，以便日后拿来使用。

关于 ZeroMQ 库，我就不多介绍了，大家可以参考下面一些文章，以及他的官网、使用指南、API 参考、项目仓库等内容。

开源点评：ZeroMQ简介

ZeroMQ的学习和研究

ZeroMQ 的模式

ZeroMQ 的目标是成为 OSI 模型的传输层(Transport Layer)的标准协议，所以他支持各种操作系统，支持多达30种以上的语言，是跨平台、跨语言的传输层库，而且性能是其绝对优势。所以对于进程间通信、节点间通信均可以使用他，可以用他直接替代 socket 的操作。而且用过之后就知道，他用起来非常的简单，学习成本很低，我只用了 1 天时间就把他的 3 种常用模式用 Python 实现了，代码在这里，大家可以参考一下，接下来准备用 C++ 再实现一遍。

ZeroMQ 总结的通信模式如下：

• PUB and SUB
• REQ and REP
• REQ and ROUTER
• DEALER and REP
• DEALER and ROUTER
• DEALER and DEALER
• ROUTER and ROUTER
• PUSH and PULL
• PAIR and PAIR

ZeroMQ 总结的应用模式如下：

• Request-reply, which connects a set of clients to a set of services. This is a remote procedure call and task distribution pattern.
• Publish-subscribe, which connects a set of publishers to a set of subscribers. This is a data distribution pattern.
• Pipeline, which connects nodes in a fan-out / fan-in pattern that can have multiple steps, and loops. This is a parallel task distribution and collection pattern.

当然，实际使用中还得了解一些解决具体问题的模式，所以下面把使用指南中的一些模式整理如下，方便自己日后拿来使用。

最常用的三种模式：

1. Request-Reply

服务器端代码：

package zmq20140508;

import org.zeromq.ZMQ;
/**
 * 
 * @author lijianhua
 *
 */

public class ZMQServer {
	
	public static void main(String[] args) {
		Client client =new Client();
		client.start();
	}
public static class Client extends Thread{
	private String url_worker="inproc://workers";
	private String url_client="tcp://127.0.0.1:6666";
	private ZMQ.Poller poller;
	private ZMQ.Context context;
	private ZMQ.Socket clients;
	private ZMQ.Socket workers;
	@SuppressWarnings("deprecation")
	public void run(){
		context = ZMQ.context(1);
		clients = context.socket(ZMQ.ROUTER);
		clients.bind(url_client);
		
		workers = context.socket(ZMQ.DEALER);
		workers.bind(url_worker);
		
		for(int i=0;i<10;i++){
			new Worker(context,url_worker).start();
		}

		ZMQ.device(ZMQ.QUEUE, clients, workers);//开始因这个犯错，搞了半天
		poller=new ZMQ.Poller(2);//创建一个大小为2的poller
		//分别将上述的pull注册到poller上，注册的事件是读
		ZMQ.PollItem citem = new ZMQ.PollItem(clients, ZMQ.Poller.POLLIN);
		ZMQ.PollItem witem = new ZMQ.PollItem(workers, ZMQ.Poller.POLLIN);
		poller.register(citem);
		poller.register(witem);
		boolean ok =true;
		while(ok){
			poller.poll(); 
				if(poller.getItem(0).isReadable()){
					System.out.println("当前发送：clients");
					byte[] recv = clients.recv();
					workers.send(recv);
				}else{
					System.out.println("当前发送：workers");
					byte[] recv = workers.recv();
					clients.send(recv);
				}
		}
		closeAll();
	}
	public void closeAll(){
		clients.close();
		workers.close();
		context.term();
	}
}
	public static class Worker extends Thread{
		private String url_worker1;
		private ZMQ.Context context1;
		public Worker(ZMQ.Context context,String url_worker) {
			this.url_worker1=url_worker;
			this.context1=context;
		}
		public void run() {
			ZMQ.Socket socket = context1.socket(ZMQ.REP);
			socket.connect(url_worker1);
			ZMQ.Poller poller=new ZMQ.Poller(1);
			ZMQ.PollItem item = new ZMQ.PollItem(socket, ZMQ.Poller.POLLIN);
			poller.register(item);
			while (true){
				if(poller.poll()==ZMQ.Poller.POLLIN){
					byte[] recv = socket.recv();
					System.out.println("fix========"+new String(recv));
					try {
						Thread.sleep(1);
					} catch (InterruptedException e) {
						e.printStackTrace();
					}
					socket.send("world========");
				}
			}
		}
	}
}

客服端代码

package zmq20140508;

import org.zeromq.ZMQ;
import org.zeromq.ZMQ.Context;
import org.zeromq.ZMQ.Socket;

public class Request {

	public static void main(String[] args) {
		System.out.println("客户端开始.........");
		Context context = ZMQ.context(1);
		Socket resSocket = context.socket(ZMQ.REQ);//客服端发送消息
//		resSocket.connect("tcp://115.236.73.253:5570");
		resSocket.connect("tcp://127.0.0.1:6666");
		int i=0;
		while(i<5){
			i++;
			try {
				resSocket.send("hello");
				byte[] msg = resSocket.recv();
				String outputStr = new String(msg);
				System.out.println("#### Client Receive:" + outputStr);
			} catch (Exception e) {
				e.printStackTrace();
			}
		}

	}

}

2. Publish-Subscribe

3. Parallel Pipeline

其他模式：

其他模式只是上面三种模式的加强而已，所以也是分为三大类。

A. Request-Reply Patterns

1. The Load-balancing Pattern

代码示例：

package zmq20140505;
import java.util.LinkedList;

import org.zeromq.ZFrame;
import org.zeromq.ZMQ;
import org.zeromq.ZMsg;

public class Balance {
	
	public static class Client {
		public void start() {
			new Thread(new Runnable(){

				public void run() {
					// TODO Auto-generated method stub
					ZMQ.Context context = ZMQ.context(1);
					ZMQ.Socket socket = context.socket(ZMQ.REQ);
					socket.connect("ipc://127.0.0.1:5555");  //连接router，想起发送请求
					
					while (!Thread.currentThread().isInterrupted()) {
						socket.send("hello".getBytes(), 0);  //发送hello请求
						String bb = new String(socket.recv());  //获取返回的数据
						System.out.println("recv Worker : "+bb);	
					}
					socket.close();
					context.term();
				}
				
			}).start();
		}
	}
	
	public static class Worker {
		public void start() {
			new Thread(new Runnable(){

				public void run() {
					// TODO Auto-generated method stub
					ZMQ.Context context = ZMQ.context(1);
					ZMQ.Socket socket = context.socket(ZMQ.REQ);
					
					socket.connect("ipc://127.0.0.1:6666");  //连接，用于获取要处理的请求，并发送回去处理结果
					
					socket.send("ready".getBytes());  //发送ready，表示当前可用
					 
					while (!Thread.currentThread().isInterrupted()) {
						ZMsg msg = ZMsg.recvMsg(socket);  //获取需要处理的请求，其实这里msg最外面的标志frame是router对分配给client的标志frame
						ZFrame request = msg.removeLast();   //最后一个frame其实保存的就是实际的请求数据，这里将其移除，待会用新的frame代替
						
						String now = new String(request.getData());
						System.out.println("recv Client : " + now);
						
						ZFrame frame = new ZFrame("hello fjs".getBytes());  
						msg.addLast(frame);  //将刚刚创建的frame放到msg的最后，worker将会收到
						msg.send(socket);  //将数据发送回去
					}
					socket.close();
					context.term();
				}
				
			}).start();
		}
	}
	
	public static class Middle {
		private LinkedList workers;
		private LinkedList requests;
		private ZMQ.Context context;
		private ZMQ.Poller poller;
		
		public Middle() {
			this.workers = new LinkedList();
			this.requests = new LinkedList();
			this.context = ZMQ.context(1);
			this.poller = new ZMQ.Poller(2);
		}
		
		public void start() {
			ZMQ.Socket fronted = this.context.socket(ZMQ.ROUTER);  //创建一个router，用于接收client发送过来的请求，以及向client发送处理结果
			ZMQ.Socket backend = this.context.socket(ZMQ.ROUTER);  //创建一个router，用于向后面的worker发送数据，然后接收处理的结果
			
			fronted.bind("ipc://127.0.0.1:5555");  //监听，等待client的连接
			backend.bind("ipc://127.0.0.1:6666");  //监听，等待worker连接
			
			//创建pollItem
			ZMQ.PollItem fitem = new ZMQ.PollItem(fronted, ZMQ.Poller.POLLIN);  
			ZMQ.PollItem bitem = new ZMQ.PollItem(backend, ZMQ.Poller.POLLIN);
			
			this.poller.register(fitem);  //注册pollItem
			this.poller.register(bitem);
			
			
			while (!Thread.currentThread().isInterrupted()) {
				this.poller.poll();
				if (fitem.isReadable()) {  //表示前面有请求发过来了
					ZMsg msg = ZMsg.recvMsg(fitem.getSocket());  //获取client发送过来的请求，这里router会在实际请求上面套一个连接的标志frame
					/**
					 * //以下3行查看中间层客服端发过来的值
					 */
					ZFrame request = msg.getLast();
					String now = new String(request.getData());
					System.out.println("fix===="+now);
					
					this.requests.addLast(msg);   //将其挂到请求队列
				}
				if (bitem.isReadable()) {  //这里表示worker发送数据过来了
					ZMsg msg = ZMsg.recvMsg(bitem.getSocket());  //获取msg，这里也会在实际发送的数据前面包装一个连接的标志frame
					//这里需要注意，这里返回的是最外面的那个frame，另外它还会将后面的接着的空的标志frame都去掉
					ZFrame workerID = msg.unwrap();  //把外面那层包装取下来，也就是router对连接的标志frame
					this.workers.addLast(workerID);  //将当前的worker的标志frame放到worker队列里面，表示这个worker可以用了
					ZFrame readyOrAddress = msg.getFirst(); //这里获取标志frame后面的数据，如果worker刚刚启动，那么应该是发送过来的ready，
					if (new String(readyOrAddress.getData()).equals("ready")) {  //表示是worker刚刚启动，发过来的ready
						msg.destroy();
					} else {
						msg.send(fronted);  //表示是worker处理完的返回结果，那么返回给客户端
					}
				}
				while (this.workers.size() > 0 && this.requests.size() > 0) {
					ZMsg request = this.requests.removeFirst();
					ZFrame worker = this.workers.removeFirst();
					
					request.wrap(worker);  //在request前面包装一层，把可以用的worker的标志frame包装上，这样router就会发给相应的worker的连接
					request.send(backend);  //将这个包装过的消息发送出去
				}
			}
			fronted.close();
			backend.close();
			this.context.term();
		}
	}
	
	
	public static void main(String args[]) {
		Worker worker = new Worker();
		worker.start();
		Client client = new Client();
		client.start();
		Middle middle = new Middle();
		middle.start();
		
	}
}

2. The Asynchronous Client-Server Pattern

3. Client-side Reliability (Lazy Pirate Pattern)

4. Basic Reliable Queuing (Simple Pirate Pattern)

5. Robust Reliable Queuing (Paranoid Pirate Pattern)

6. Service-Oriented Reliable Queuing (Majordomo Pattern)

7. Disconnected Reliability (Titanic Pattern)

8. High-availability Pair (Binary Star Pattern)

9. Brokerless Reliability (Freelance Pattern)

B. Publish-Subscribe Patterns

1. Pub-sub Tracing (Espresso Pattern)

2. Slow Subscriber Detection (Suicidal Snail Pattern)

3. High-speed Subscribers (Black Box Pattern)

4. Reliable Publish-Subscribe (Clone Pattern)

C. Parallel Pipeline Patterns