/**
 * 多任務(wù)并行+線程池統(tǒng)計(jì)
 * 創(chuàng)建時(shí)間  2018年4月17日
 */
public class StatsDemo {
  final static SimpleDateFormat sdf = new SimpleDateFormat(
      "yyyy-MM-dd HH:mm:ss");
  
  final static String startTime = sdf.format(new Date());
  
  /**
   * IO密集型任務(wù) = 一般為2*CPU核心數(shù)（常出現(xiàn)于線程中：數(shù)據(jù)庫數(shù)據(jù)交互、文件上傳下載、網(wǎng)絡(luò)數(shù)據(jù)傳輸?shù)鹊龋?
   * CPU密集型任務(wù) = 一般為CPU核心數(shù)+1（常出現(xiàn)于線程中：復(fù)雜算法）
   * 混合型任務(wù) = 視機(jī)器配置和復(fù)雜度自測而定
   */
  private static int corePoolSize = Runtime.getRuntime().availableProcessors();
  /**
   * public ThreadPoolExecutor(int corePoolSize,int maximumPoolSize,long keepAliveTime,
   *              TimeUnit unit,BlockingQueue<Runnable> workQueue)
   * corePoolSize用于指定核心線程數(shù)量
   * maximumPoolSize指定最大線程數(shù)
   * keepAliveTime和TimeUnit指定線程空閑后的最大存活時(shí)間
   * workQueue則是線程池的緩沖隊(duì)列,還未執(zhí)行的線程會(huì)在隊(duì)列中等待
   * 監(jiān)控隊(duì)列長度，確保隊(duì)列有界
   * 不當(dāng)?shù)木€程池大小會(huì)使得處理速度變慢，穩(wěn)定性下降，并且導(dǎo)致內(nèi)存泄露。如果配置的線程過少，則隊(duì)列會(huì)持續(xù)變大，消耗過多內(nèi)存。
   * 而過多的線程又會(huì) 由于頻繁的上下文切換導(dǎo)致整個(gè)系統(tǒng)的速度變緩——殊途而同歸。隊(duì)列的長度至關(guān)重要，它必須得是有界的，這樣如果線程池不堪重負(fù)了它可以暫時(shí)拒絕掉新的請(qǐng)求。
   * ExecutorService 默認(rèn)的實(shí)現(xiàn)是一個(gè)無界的 LinkedBlockingQueue。
   */
  private static ThreadPoolExecutor executor = new ThreadPoolExecutor(corePoolSize, corePoolSize+1, 10l, TimeUnit.SECONDS,
      new LinkedBlockingQueue<Runnable>(1000));
  
  public static void main(String[] args) throws InterruptedException {
    CountDownLatch latch = new CountDownLatch(5);
    //使用execute方法
     executor.execute(new Stats("任務(wù)A", 1000, latch));
     executor.execute(new Stats("任務(wù)B", 1000, latch));
     executor.execute(new Stats("任務(wù)C", 1000, latch));
     executor.execute(new Stats("任務(wù)D", 1000, latch));
     executor.execute(new Stats("任務(wù)E", 1000, latch));
    latch.await();// 等待所有人任務(wù)結(jié)束
    System.out.println("所有的統(tǒng)計(jì)任務(wù)執(zhí)行完成:" + sdf.format(new Date()));
  }

  static class Stats implements Runnable {
    String statsName;
    int runTime;
    CountDownLatch latch;

    public Stats(String statsName, int runTime, CountDownLatch latch) {
      this.statsName = statsName;
      this.runTime = runTime;
      this.latch = latch;
    }

    public void run() {
      try {
        System.out.println(statsName+ " do stats begin at "+ startTime);
        //模擬任務(wù)執(zhí)行時(shí)間
        Thread.sleep(runTime);
        System.out.println(statsName + " do stats complete at "+ sdf.format(new Date()));
        latch.countDown();//單次任務(wù)結(jié)束，計(jì)數(shù)器減一
      } catch (InterruptedException e) {
        e.printStackTrace();
      }
    }
  }
}

/**
 * 多任務(wù)并行+線程池統(tǒng)計(jì)
 * 創(chuàng)建時(shí)間  2018年4月17日
 */
public class StatsDemo {
  final static SimpleDateFormat sdf = new SimpleDateFormat(
      "yyyy-MM-dd HH:mm:ss");
  
  final static String startTime = sdf.format(new Date());
  
  /**
   * IO密集型任務(wù) = 一般為2*CPU核心數(shù)（常出現(xiàn)于線程中：數(shù)據(jù)庫數(shù)據(jù)交互、文件上傳下載、網(wǎng)絡(luò)數(shù)據(jù)傳輸?shù)鹊龋?
   * CPU密集型任務(wù) = 一般為CPU核心數(shù)+1（常出現(xiàn)于線程中：復(fù)雜算法）
   * 混合型任務(wù) = 視機(jī)器配置和復(fù)雜度自測而定
   */
  private static int corePoolSize = Runtime.getRuntime().availableProcessors();
  /**
   * public ThreadPoolExecutor(int corePoolSize,int maximumPoolSize,long keepAliveTime,
   *              TimeUnit unit,BlockingQueue<Runnable> workQueue)
   * corePoolSize用于指定核心線程數(shù)量
   * maximumPoolSize指定最大線程數(shù)
   * keepAliveTime和TimeUnit指定線程空閑后的最大存活時(shí)間
   * workQueue則是線程池的緩沖隊(duì)列,還未執(zhí)行的線程會(huì)在隊(duì)列中等待
   * 監(jiān)控隊(duì)列長度，確保隊(duì)列有界
   * 不當(dāng)?shù)木€程池大小會(huì)使得處理速度變慢，穩(wěn)定性下降，并且導(dǎo)致內(nèi)存泄露。如果配置的線程過少，則隊(duì)列會(huì)持續(xù)變大，消耗過多內(nèi)存。
   * 而過多的線程又會(huì) 由于頻繁的上下文切換導(dǎo)致整個(gè)系統(tǒng)的速度變緩——殊途而同歸。隊(duì)列的長度至關(guān)重要，它必須得是有界的，這樣如果線程池不堪重負(fù)了它可以暫時(shí)拒絕掉新的請(qǐng)求。
   * ExecutorService 默認(rèn)的實(shí)現(xiàn)是一個(gè)無界的 LinkedBlockingQueue。
   */
  private static ThreadPoolExecutor executor = new ThreadPoolExecutor(corePoolSize, corePoolSize+1, 10l, TimeUnit.SECONDS,
      new LinkedBlockingQueue<Runnable>(1000));
  
  public static void main(String[] args) throws InterruptedException {
    List<Future<String>> resultList = new ArrayList<Future<String>>(); 
    //使用submit提交異步任務(wù)，并且獲取返回值為future
    resultList.add(executor.submit(new Stats("任務(wù)A", 1000)));
    resultList.add(executor.submit(new Stats("任務(wù)B", 1000)));
    resultList.add(executor.submit(new Stats("任務(wù)C", 1000)));
    resultList.add(executor.submit(new Stats("任務(wù)D", 1000)));
    resultList.add(executor.submit(new Stats("任務(wù)E", 1000)));
     //遍歷任務(wù)的結(jié)果
    for (Future<String> fs : resultList) { 
      try { 
        System.out.println(fs.get());//打印各個(gè)線任務(wù)執(zhí)行的結(jié)果，調(diào)用future.get() 阻塞主線程，獲取異步任務(wù)的返回結(jié)果
      } catch (InterruptedException e) { 
        e.printStackTrace(); 
      } catch (ExecutionException e) { 
        e.printStackTrace(); 
      } finally { 
        //啟動(dòng)一次順序關(guān)閉，執(zhí)行以前提交的任務(wù)，但不接受新任務(wù)。如果已經(jīng)關(guān)閉，則調(diào)用沒有其他作用。
        executor.shutdown(); 
      } 
    } 
    System.out.println("所有的統(tǒng)計(jì)任務(wù)執(zhí)行完成:" + sdf.format(new Date()));
  }

  static class Stats implements Callable<String> {
    String statsName;
    int runTime;

    public Stats(String statsName, int runTime) {
      this.statsName = statsName;
      this.runTime = runTime;
    }

    public String call() {
      try {
        System.out.println(statsName+ " do stats begin at "+ startTime);
        //模擬任務(wù)執(zhí)行時(shí)間
        Thread.sleep(runTime);
        System.out.println(statsName + " do stats complete at "+ sdf.format(new Date()));
      } catch (InterruptedException e) {
        e.printStackTrace();
      }
      return call();
    }
  }
}