Hadoop RPC 的使用实例（hadoop-2.7.0）

Hadoop RPC是Hadoop的一个重要部分，提供分布式环境下的对象调用功能。它主要是通过Java的动态代理（Dynamic Proxy）与反射（Reflect）实现，代理类是由java.lang.reflect.Proxy类在运行期时根据接口，采用Java反射功能动态生成的，并且结合java.lang.reflect.InvocationHandler来处理客户端的请求。下面给出使用Hadoop RPC的过程：

1. 代码：

（1）协议 - MyProtocol.java

import org.apache.hadoop.ipc.VersionedProtocol;
 
public interface MyProtocol extends VersionedProtocol {
	public static final long versionID = 1L;
	
	public String println(String string);
	public int mul(int a, int b);
	public int[] sortGreat(int[] nums, int len);	
}

（2）服务器 - MyServer.java

import java.io.IOException;
import java.net.UnknownHostException;
import java.text.SimpleDateFormat;
import java.util.Date;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.ipc.ProtocolSignature;
import org.apache.hadoop.ipc.RPC;
import org.apache.hadoop.ipc.RPC.Server;

public class MyServer implements MyProtocol {
    private Server server;
    
    public MyServer() {
        try {
        	Configuration conf = new Configuration();
        	
        	/* BindAddress和Port分别表示服务器的host和监听端口号，
        	*  而NnumHandlers表示服务器端处理请求的线程数目;
        	*/
			server = new RPC.Builder(conf)
					.setProtocol(MyServer.class).setInstance(this)
					.setBindAddress("localhost").setPort(9999).setNumHandlers(5)
					.build();
            server.start();
            
            System.out.println("Server is running: " 
            		+ new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date()));
            server.join();
        } catch (UnknownHostException e) {
            e.printStackTrace();
        } catch (IOException e) {
            e.printStackTrace();
        } catch (InterruptedException e) {
            e.printStackTrace();
        }
    }
    
    //重载的方法，用于获取自定义的协议版本号
    @Override
    public long getProtocolVersion(String protocol, long clientVersion) throws IOException {
        return MyProtocol.versionID;
    }
    
    //重载的方法，用于获取协议签名  
    @Override
	public ProtocolSignature getProtocolSignature(String arg0, long arg1,
			int arg2) throws IOException {
		// TODO Auto-generated method stub
    	return new ProtocolSignature(MyProtocol.versionID, null);
	}
    
    @Override
    public String println(String t) {
        System.out.println("receive: " + t);
        return "Hello " + t;
    }
    
    @Override
	public int mul(int a, int b) {
    	System.out.println("receive: " + a + " " + b);
		return a*b;
	}
    
    @Override
    public int[] sortGreat(int[] nums, int len) {
    	System.out.print("receive: ");
    	for(int i=0; i<len; i++) System.out.print(nums[i] + " ");
    	System.out.println();
    	
    	for(int i=0; i<len; i++) {
    		for(int j=i+1; j<len; j++) {
    			if(nums[i] > nums[j]) {
    				int tmp = nums[i];
    				nums[i] = nums[j];
    				nums[j] = tmp;
    			}
    		}
    	}
    	return nums;
    }
    
    public static void main(String[] args) {
        new MyServer();
    }
}

（3）客户端

import java.io.IOException;
import java.net.InetSocketAddress;
import java.util.*;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.ipc.RPC;

public class MyClient {
    
    private MyProtocol proxy;

    public MyClient() {
        InetSocketAddress addr = new InetSocketAddress("localhost", 9999);
        try {
        	//构造客户端代理对象，直接通过代理对象调用远程端的方法
            proxy = (MyProtocol) RPC.waitForProxy(MyProtocol.class, MyProtocol.versionID, addr, new Configuration());
        } catch (IOException e) {
            e.printStackTrace();
        }
    }
    
    public MyProtocol getProxy() {
		return proxy;
	}

	public void close(){
        RPC.stopProxy(proxy);
    }
    
    public static void main(String[] args) {
        MyClient c = new MyClient();
        Scanner cin = new Scanner(System.in);
        
        //字符串
        System.out.println("字符串：");
        System.out.print("send: ");
        String str = cin.next();
        String strAns = c.getProxy().println(str);
        System.out.println("receive: " + strAns);
        System.out.println();
        
        //相乘
        System.out.println("相乘：");
        System.out.print("send: ");
        int a = cin.nextInt();
        int b = cin.nextInt();
        int cAns = c.getProxy().mul(a, b);
        System.out.println("receive: " + cAns);
        System.out.println();
        
        //排序
        System.out.println("排序：");
        int[] nums = new int[1000];
        System.out.print("send(end with #): ");
        int len = 0;
        while(cin.hasNext()) {
        	String tmp = cin.next();
        	if(tmp.equals("#")) break;
        	nums[len++] = Integer.parseInt(tmp);
        }
        int[] numsAns = c.getProxy().sortGreat(nums, len);
        System.out.print("receive: ");
        for(int i=0; i<len; i++) {
        	System.out.print(numsAns[i] + " ");
        }
        System.out.println();
        
        c.close();
        cin.close();
    }
}

2.  jar包

从hadoop-2.7.0.tar.gz中，取出运行所需的jar包，如下：

3. 编译

此处的编译其实使用的就是"javac"指令，但由于需要包含所有的需要的jar包，故还是有些不同。这里jar包的保存目录为：“E:\rpc\extJar”，而java源代码保存的目录为“E:\rpc”，故编译命令写成windows批处理文件为：

compile.bat

javac -cp extJar/commons-collections-3.2.1.jar;extJar/commons-configuration-1.6.jar;extJar/commons-io-2.4.jar;extJar/commons-lang-2.6.jar;extJar/commons-logging-1.1.3.jar;extJar/guava-11.0.2.jar;extJar/hadoop-auth-2.7.0.jar;extJar/hadoop-common-2.7.0.jar;extJar/htrace-core-3.1.0-incubating.jar;extJar/log4j-1.2.17.jar;extJar/protobuf-java-2.5.0.jar;extJar/slf4j-api-1.7.10.jar;extJar/slf4j-log4j12-1.7.10.jar; *.java

4. 运行

同理，服务器和客户端的运行脚本，如下：

server.bat

java -cp extJar/commons-collections-3.2.1.jar;extJar/commons-configuration-1.6.jar;extJar/commons-io-2.4.jar;extJar/commons-lang-2.6.jar;extJar/commons-logging-1.1.3.jar;extJar/guava-11.0.2.jar;extJar/hadoop-auth-2.7.0.jar;extJar/hadoop-common-2.7.0.jar;extJar/htrace-core-3.1.0-incubating.jar;extJar/log4j-1.2.17.jar;extJar/protobuf-java-2.5.0.jar;extJar/slf4j-api-1.7.10.jar;extJar/slf4j-log4j12-1.7.10.jar; MyServer

client.bat

java -cp extJar/commons-collections-3.2.1.jar;extJar/commons-configuration-1.6.jar;extJar/commons-io-2.4.jar;extJar/commons-lang-2.6.jar;extJar/commons-logging-1.1.3.jar;extJar/guava-11.0.2.jar;extJar/hadoop-auth-2.7.0.jar;extJar/hadoop-common-2.7.0.jar;extJar/htrace-core-3.1.0-incubating.jar;extJar/log4j-1.2.17.jar;extJar/protobuf-java-2.5.0.jar;extJar/slf4j-api-1.7.10.jar;extJar/slf4j-log4j12-1.7.10.jar; MyClient

5. 结果：

（1）文件目录

（2）编译结果

上图中最后给出警告，但还未找到解决方法，对运行结果也没有影响。

（3）运行结果

服务器：

客户端：