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  • Java多线程处理List数据

    实例1:

    解决问题:如何让n个线程顺序遍历含有n个元素的List集合

    import java.util.ArrayList;
    import java.util.List;
    import org.apache.commons.lang3.ArrayUtils;
    
    public class Test_4 {
    /**
    * 多线程处理list
    *
    * @param data 数据list
    * @param threadNum 线程数
    */
    public synchronized void handleList(List<String> data, int threadNum) {
    int length = data.size();
    int tl = length % threadNum == 0 ? length / threadNum : (length
    / threadNum + 1);
    
    for (int i = 0; i < threadNum; i++) {
    int end = (i + 1) * tl;
    HandleThread thread = new HandleThread("线程[" + (i + 1) + "] ", data, i * tl, end > length ? length : end);
    thread.start();
    }
    }
    
    class HandleThread extends Thread {
    private String threadName;
    private List<String> data;
    private int start;
    private int end;
    
    public HandleThread(String threadName, List<String> data, int start, int end) {
    this.threadName = threadName;
    this.data = data;
    this.start = start;
    this.end = end;
    }
    
    public void run() {
    List<String> subList = data.subList(start, end)/*.add("^&*")*/;
    System.out.println(threadName+"处理了"+subList.size()+"条!");
    }
    
    }
    
    public static void main(String[] args) {
    Test_4 test = new Test_4();
    // 准备数据
    List<String> data = new ArrayList<String>();
    for (int i = 0; i < 6666; i++) {
    data.add("item" + i);
    }
    test.handleList(data, 5);
    System.out.println(ArrayUtils.toString(data));
    }
    }

    实例2:

    List多线程并发读取读取现有的list对象

    //测试读取List的线程类,大概34秒
    package com.thread.list;
     
    import java.util.ArrayList;
    import java.util.HashMap;
    import java.util.List;
    import java.util.Map;
     
    public class Main {
        
        public static void main(String[] args) {
            
            List<String> list = new ArrayList<String>();
            Map<Long,Integer> map = new HashMap<Long,Integer>();
    
            for(int i = 0;i<1000;i++){
                list.add(""+i);
            }
            
            int pcount = Runtime.getRuntime().availableProcessors();        
            long start = System.currentTimeMillis();        
            
            for(int i=0;i<pcount;i++){
                
               Thread t = new MyThread1(list,map);
                map.put(t.getId(),Integer.valueOf(i));
                t.start();
                try {
                    t.join();
                } catch (InterruptedException e) {              
                    e.printStackTrace();
                }            
               // System.out.println(list.get(i));
            }        
            System.out.println("----"+(System.currentTimeMillis() - start));
        }    
    }
    
    //线程类
    package com.thread.list;
     
    import java.util.List;
    import java.util.Map;
     
    public class MyThread1 extends Thread {
     
        private List<String> list;
        private Map<Long,Integer> map;
        
        public MyThread1(List<String> list,Map<Long,Integer> map){
            this.list = list;
            this.map = map;
        }
        
        @Override
        public void run() {
            
            int pcount = Runtime.getRuntime().availableProcessors();
            int i = map.get(Thread.currentThread().getId());
            
            for(;i<list.size();i+=pcount){
                System.out.println(list.get(i));
            }              
        }    
    }

    实例3:

    多线程分段处理List集合

    场景:大数据List集合,需要对List集合中的数据同标准库中数据进行对比,生成新增,更新,取消数据 
    解决方案:

      1. List集合分段,
      2. 动态创建线程池newFixedThreadPool
      3. 将对比操作在多线程中实现
        public static void main(String[] args) throws Exception {
        
                // 开始时间
                long start = System.currentTimeMillis();
                List<String> list = new ArrayList<String>();
        
                for (int i = 1; i <= 3000; i++) {
                    list.add(i + "");
                }
                // 每500条数据开启一条线程
                int threadSize = 500;
                // 总数据条数
                int dataSize = list.size();
                // 线程数
                int threadNum = dataSize / threadSize + 1;
                // 定义标记,过滤threadNum为整数
                boolean special = dataSize % threadSize == 0;
        
                // 创建一个线程池
                ExecutorService exec = Executors.newFixedThreadPool(threadNum);
                // 定义一个任务集合
                List<Callable<Integer>> tasks = new ArrayList<Callable<Integer>>();
                Callable<Integer> task = null;
                List<String> cutList = null;
        
                // 确定每条线程的数据
                for (int i = 0; i < threadNum; i++) {
                    if (i == threadNum - 1) {
                        if (special) {
                            break;
                        }
                        cutList = list.subList(threadSize * i, dataSize);
                    } else {
                        cutList = list.subList(threadSize * i, threadSize * (i + 1));
                    }
                    // System.out.println("第" + (i + 1) + "组:" + cutList.toString());
                    final List<String> listStr = cutList;
                    task = new Callable<Integer>() {
        
                        @Override
                        public Integer call() throws Exception {
                            System.out.println(Thread.currentThread().getName() + "线程:" + listStr);
                            return 1;
                        }
                    };
                    // 这里提交的任务容器列表和返回的Future列表存在顺序对应的关系
                    tasks.add(task);
                }
        
                List<Future<Integer>> results = exec.invokeAll(tasks);
        
                for (Future<Integer> future : results) {
                    System.out.println(future.get());
                }
        
                // 关闭线程池
                exec.shutdown();
                System.out.println("线程任务执行结束");
                System.err.println("执行任务消耗了 :" + (System.currentTimeMillis() - start) + "毫秒");
            }
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  • 原文地址:https://www.cnblogs.com/fanleiyang/p/10523788.html
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