Java - 使用 ImageIO 的多线程

Java - Multithreading with ImageIO

我有一个加载缓慢的程序,我猜这是因为我一开始必须加载大量的图像资源。我认为多线程会有所帮助,但现在我不太确定。下面是我的自动多线程方法。

    private static Thread[] t;

    private static int currentThreads;

    public static void loadWithThreads(Object[] array, IntegerRunnable r) {

        final int threads =  Runtime.getRuntime().availableProcessors();
        t = new Thread[threads];

        for (int i = 0; i < threads; i ++) {
            t[i] = new Thread("HMediaConverter") {

                final int id = currentThreads;

                int items = (array.length / threads) * currentThreads;


                @Override
                public void run() {

                    super.run();

                    for (int i = items; i < (items + (array.length / threads)); i ++) {
                        r.run(i);
                    }

                    //Recycle this thread so it can be used for another time.
                    try {
                        t[id].join();
                        lock.notifyAll();
                        currentThreads --;
                    } catch (InterruptedException e) {
                        e.printStackTrace();
                    }

                }


            };
            t[i].setPriority(Thread.MAX_PRIORITY);
            t[i].start();
            currentThreads ++;
        }
    }

这是我的图片加载代码:

public static ImageIcon loadImageIcon(String path) {
    return new ImageIcon(ImageIO.read(Tools.class.getClassLoader().getResource(path));
}

真的有办法加快速度吗?我 运行 这是在一个非常好的 Intel i5 上,它不应该这么慢,所以它一定是我的代码。

隔离哪个部分会减慢速度 - 例如通过 运行 System.currentTimeMillis() 在主要部分之间然后告诉我们最大时间在哪里 - 或者向我们展示所有程序。

所提到的线程处理是有问题的,你不应该使用开箱即用的方法,例如 join 等,除非你在某个地方看到它可以证明有效。

所以 post 次,我们将从那里获取它 - 它可能是图像,也可能是线程

以下是重写,应该可以接近操作员写的内容。重新写入固定大小的线程池可能会更好。

//import java.util.concurrent.atomic.AtomicInteger;

private static Thread[] t;

    private static AtomicInteger completedLoads = new AtomicInteger(0);

    public static void loadWithThreads(Object[] array, IntegerRunnable r) {

        final int threads =  Runtime.getRuntime().availableProcessors();
        t = new Thread[threads];
        completedLoads = new AtomicInteger(0);
        int targetLoads = array.length;
        int itemsPerThread = (array.length / threads);

        for (int i = 0; i < threads; i ++) {
            t[i] = new Thread("HMediaConverter" + i) {

                int startItem = itemsPerThread * i;

                @Override
                public void run() {

                    super.run();

                    for (int i = startItem; i < startItem + itemsPerThread; i ++) {
                        try {
                            r.run(i);
                         }
                         finally {
                                 completedLoads.incrementAndGet();
                         }
                    }
                }
            };
            t[i].setPriority(Thread.MAX_PRIORITY);
            t[i].start();
        }

        // Wait for the images to load    
        while (completedLoads.get() < targetLoads)
        {
                try {
                        Thread.sleep(100);
                }
                catch (InterruptedException ie) {
                        // ignore
                }
        }
    }

正在加载总计 159.14mb 的 113 张图像...

public static void loadWithoutThreads(File[] array) {
    for (File file : array) {
        try {
            ImageIO.read(file);
        } catch (IOException ex) {
            ex.printStackTrace();
        }
    }
}

用了 ~15 秒

有...

public static void loadWithThreads(File[] array) {

    final int threads = Runtime.getRuntime().availableProcessors();
    t = new Thread[threads];

    CountDownLatch latch = new CountDownLatch(threads);

    for (int i = 0; i < threads; i++) {
        t[i] = new Thread("HMediaConverter") {
            final int id = currentThreads;

            int items = (array.length / threads) * currentThreads;

            @Override
            public void run() {
                try {
                    System.out.println("Starting " + id);

                    for (int i = items; i < (items + (array.length / threads)); i++) {
                        try {
                            System.out.println(i + ": " + array[i]);
                            ImageIO.read(array[i]);
                        } catch (IOException ex) {
                            ex.printStackTrace();
                        }
                    }
                } finally {
                    latch.countDown();
                }

            }

        };
        t[i].setPriority(Thread.MAX_PRIORITY);
        System.out.println("Start " + i);
        t[i].start();
        currentThreads++;
    }

    try {
        latch.await();
    } catch (InterruptedException ex) {
        ex.printStackTrace();
    }
}

用了 ~11 秒

与...

public static void loadWithExecutor(File[] images) {
    ExecutorService service = Executors.newFixedThreadPool(2);
    List<ImageLoadingTask> tasks = new ArrayList<>(images.length);
    for (File file : images) {
        tasks.add(new ImageLoadingTask(file));
    }
    try {
        List<Future<BufferedImage>> results = service.invokeAll(tasks);
    } catch (InterruptedException ex) {
        ex.printStackTrace();
    }
    service.shutdown();
}

public static class ImageLoadingTask implements Callable<BufferedImage> {

    private File file;

    public ImageLoadingTask(File file) {
        this.file = file;
    }

    @Override
    public BufferedImage call() throws Exception {
        return ImageIO.read(file);
    }

}

用了 ~7 秒

ExecutorService效率更高,因为当一个线程处理一个较大的文件时,另一个线程可以处理多个小文件。这是通过汇集那些在需要时不做任何工作的线程来实现的,允许一个线程执行大量短时间的工作,而其他线程也很忙。你不需要等那么久

查看 Executors 了解更多详情