模拟并行任务分片

代码部分：

package com.pool;

import com.alibaba.fastjson.JSON;

import java.io.BufferedReader;

import java.io.IOException;

import java.io.InputStreamReader;

import java.io.Reader;

import java.util.ArrayList;

import java.util.List;

import java.util.concurrent.Executors;

import java.util.concurrent.ScheduledThreadPoolExecutor;

import java.util.concurrent.TimeUnit;

import java.util.concurrent.atomic.AtomicInteger;

/**

 * Created on 2016/5/4.

 */

public class ScheduledPoolTest {

    public static void main(String[] args) {

        int len = 3;

        // 定时任务线程池，长度为3

        ScheduledThreadPoolExecutor executor = (ScheduledThreadPoolExecutor) Executors.newScheduledThreadPool(len);

        // 添加3个任务，每5秒执行一次，并行处理

        for (int i = 0; i < 3; i++) {

            executor.scheduleAtFixedRate(new TaskThread(len, i), 0L, 5L, TimeUnit.SECONDS);

        }

        /**

         * 手动关闭pool，没什么太大的用

         */

        try (

                Reader reader = new InputStreamReader(System.in);

                BufferedReader in = new BufferedReader(reader)

        ) {

            while (true) {

                String line = in.readLine();

                if (line.equalsIgnoreCase("no")) {

                    executor.shutdown();

                    break;

                }

            }

        } catch (IOException e) {

            e.printStackTrace();

        }

    }

}

/**

 * 模拟切片任务

 */

class TaskThread implements Runnable {

    private int increase = 0;

    private List<Integer> list;

    // 切片总数

    private int len;

    // 切片余数

    private int mod;

    private int size = 10000;

    public TaskThread(int len, int mod) {

        this.len = len;

        this.mod = mod;

    }

    @Override

    public void run() {

        list = new ArrayList<>();

        for (int i = increase * size; i < (increase + 1) * size; i++) {

            // 根据 mod 分片

            if (i % len == mod) {

                list.add(i);

            }

        }

        increase++;

        System.out.println("**********************************************************");

        System.out.println(Thread.currentThread().getName() + " : " + JSON.toJSONString(list));

        System.out.println("**********************************************************");

    }

}

运行效果：

**********************************************************

**********************************************************

**********************************************************

pool-1-thread-2 : [1,4,7,10,13,16,19,22,25,28,31,34,37,40,43,46,49,52,55,58,61,64,67,70,73,76,79,82,85,88,91,94,97]

**********************************************************

pool-1-thread-3 : [2,5,8,11,14,17,20,23,26,29,32,35,38,41,44,47,50,53,56,59,62,65,68,71,74,77,80,83,86,89,92,95,98]

**********************************************************

pool-1-thread-1 : [0,3,6,9,12,15,18,21,24,27,30,33,36,39,42,45,48,51,54,57,60,63,66,69,72,75,78,81,84,87,90,93,96,99]

**********************************************************

**********************************************************

pool-1-thread-1 : [102,105,108,111,114,117,120,123,126,129,132,135,138,141,144,147,150,153,156,159,162,165,168,171,174,177,180,183,186,189,192,195,198]

**********************************************************

**********************************************************

pool-1-thread-1 : [100,103,106,109,112,115,118,121,124,127,130,133,136,139,142,145,148,151,154,157,160,163,166,169,172,175,178,181,184,187,190,193,196,199]

**********************************************************

**********************************************************

pool-1-thread-1 : [101,104,107,110,113,116,119,122,125,128,131,134,137,140,143,146,149,152,155,158,161,164,167,170,173,176,179,182,185,188,191,194,197]

**********************************************************

no

close the pool

Process finished with exit code 0

只是模拟下在线程池中分片，用的是定时pool

1. 所有属性都是对象的，避免共享

2. 使用分片，确保数据不被多次处理（多个线程处理）

3. 使用多线程处理，提高效率

今天没看其它东东，昨天刚好想到这个，就写了个小demo，只是测试使用，ScheduledThreadPoolExecutor用的不多，一般定时机制都会选择quartz，更灵活与强大！