Java并发之:生产者消费者问题

生产者消费者问题是Java并发中的常见问题之一，在实现时，一般可以考虑使用juc包下的BlockingQueue接口，至于具体使用哪个类，则就需要根据具体的使用场景具体分析了。本文主要实现一个生产者消费者的原型，以及实现一个生产者消费者的典型使用场景。

第一个问题：实现一个生产者消费者的原型。

 import java.util.concurrent.*;

 class Consumer implements Runnable {
     BlockingQueue q = null;

     public Consumer(BlockingQueue q) {
         this.q = q;
     }

     @Override
     public void run() {
         while(true) {
             try {
                 q.take();
                 System.out.println("Consumer has taken a product.");
             }catch(InterruptedException e) {

             }
         }
     }
 }

 class Producer implements Runnable {
     BlockingQueue q = null;

     public Producer(BlockingQueue q) {
         this.q = q;
     }

     @Override
     public void run() {
         while(true) {
             try { // note that if there is any chance that block, usually we need a InterruptedException
                 q.put(new Object());
                 System.out.println("Producer has puted a product.");
             }catch(InterruptedException e) {

             }
         }
     }

 }

 public class JC_ProducerConsumerPrototype {
     static int queueCapacity = 1024;
     //static BlockingQueue<Object> q = new ArrayBlockingQueue<Object>(queueCapacity); // Can also compile
     static BlockingQueue q = new ArrayBlockingQueue(queueCapacity); // ABQ must has a capacity
     public static void main(String[] args) {
         Thread t1 = new Thread(new Producer(q));
         Thread t2 = new Thread(new Consumer(q));
         t1.start();
         t2.start();
     }

 }

第二个问题，现在假设生产者是在读取磁盘上的多个log文件，对于每一个文件，依次读取文件中的每一行，也就是一条log记录；消费者需要读取并分析这些记录，假设消费者是计算密集型的。如何在生产者消费者原型的基础上实现这些功能？

这个场景在server端开发中是经常碰到的，因为在Server端，不可避免地会产生大量的日志文件。

 import java.util.concurrent.*;
 import java.io.*;
 import java.nio.*;
 import java.nio.file.*;
 import java.util.*;
 import java.nio.charset.*;

 class Producer implements Runnable {
     BlockingQueue q = null;
     String fileName = null;
     CountDownLatch latch = null;

     public Producer(BlockingQueue q,String fileName,CountDownLatch latch) {
         this.q = q;
         this.fileName = fileName;
         this.latch = latch;
     }

     @Override
     public void run() {
         Path path = Paths.get(".",fileName);
         try{
             List<String> lines = Files.readAllLines(path,StandardCharsets.UTF_8);
             for(int i=lines.size();i>0;i--){
                 try{
                     q.put(lines.get(i));
                 }catch(InterruptedException e) {

                 }
             }
         }catch(IOException e){

         }
         latch.countDown();
     }
 }

 class Consumer implements Runnable {
     BlockingQueue<String> q = null;
     Boolean done = false;

     public Consumer(BlockingQueue q,Boolean done){
         this.q = q;
         this.done = done;
     }

     @Override
     public void run(){
         while(!done||q.size()!=0){
             try{
                 q.take();
             }catch(InterruptedException e){

             }
         }
     }
 }

 public class JC_ProducerConsumerHandlingLog{
     public static int fileCount = 1024;
     public static String[] fileNames = new String[fileCount];
     public static int cpuCount = 8;
     public static CountDownLatch latch = new CountDownLatch(fileCount);
     public static volatile boolean done = false;
     public static BlockingQueue<String> q = new LinkedBlockingQueue<String>(fileCount);//one thread for one file

     public static void main(String[] args){
         for(int i=0;i<fileCount;i++){
             Thread t = new Thread(new Producer(q,fileNames[i],latch));
             t.start();
         }
         for(int i=0;i<cpuCount;i++){//for computing tasks, we don't need too many threads.
             Thread t = new Thread(new Consumer(q,done));
             t.start();
         }
         try{
             latch.await();
             done = true;
         }catch(InterruptedException e){

         }

     }
 }

需要稍微注意一下线程数的选择，对于计算密集型的任务，我认为线程数达到cpu的核数比较合理(在不考虑超线程的情况下，也就是说一个核只有一个线程)。有不同意见欢迎跟我交流！