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“单一后进先出执行人/转岗工人”

executor swingworker concurrency swing java

Uhlen · 技术社区 · 15 年前

考虑一个带有JList或JTable的Swing应用程序,当选择更改时,SwingWorker将启动并从数据库加载相关数据并更新UI。这工作得很好,用户界面也很灵敏。

但是,如果用户正在快速更改所选行(按住向上/向下键),我希望确保最后一个所选行是最后加载的行,而且我不想徒劳地查询数据库。所以我想要的是一个单线程执行器,其后进先出队列的大小为1。因此,将任务提交给它将删除以前提交的任何任务,并使它一次最多执行一个任务,并且最多有一个任务等待执行。

我在java.util.concurrent中找不到类似的东西,所以我编写了自己的执行器。我这样做是对的还是我在并发包中遗漏了什么?这个解决方案是可以接受的还是有更好的方法来实现我想要的?

public class SingleLIFOExecutor implements Executor
{
    private final ThreadPoolExecutor executor;
    private Runnable lastCommand;

    public SingleLIFOExecutor()
    {
        executor = new ThreadPoolExecutor(0, 1, 0, TimeUnit.MILLISECONDS, new ArrayBlockingQueue<Runnable>(1));
    }

    @Override
    public void execute(Runnable command)
    {
        executor.remove(lastCommand);
        lastCommand = command;
        executor.execute(command);
    }
}

下面是一个示例,说明如何使用它:

final Executor executor = new SingleLIFOExecutor();
JList jList = createMyList();
jList.addListSelectionListener(new ListSelectionListener()
{
    @Override
    public void valueChanged(ListSelectionEvent e)
    {
        if (!e.getValueIsAdjusting())
        {
            executor.execute(new MyWorker());
        }
    }
});

3 回复 | 直到 15 年前

Daniel Ryan 15 年前

LinkedBlockingDeque似乎仍然使用带有ThreadPoolExecutor的队列。

因此,我使用了一个包装器并将其与ThreadPoolExecutor一起使用:

package util;

import java.util.Collection;
import java.util.Iterator;
import java.util.concurrent.BlockingQueue;
import java.util.concurrent.LinkedBlockingDeque;
import java.util.concurrent.TimeUnit;

/**
 * LIFO BlockingQueue to be used with the ExecutorService.
 * @author Daniel
 * @param <T>
 */
public class LinkedBlockingStack<T> implements BlockingQueue<T>{
    private final LinkedBlockingDeque<T> stack = new LinkedBlockingDeque<T>();

    @Override
    public T remove() {
        return stack.remove();
    }

    @Override
    public T poll() {
        return stack.poll();
    }

    @Override
    public T element() {
        return stack.element();
    }

    @Override
    public T peek() {
        return stack.peek();
    }

    @Override
    public int size() {
        return stack.size();
    }

    @Override
    public boolean isEmpty() {
        return stack.isEmpty();
    }

    @Override
    public Iterator<T> iterator() {
        return stack.iterator();
    }

    @Override
    public Object[] toArray() {
        return stack.toArray();
    }

    @Override
    public <S> S[] toArray(final S[] a) {
        return stack.toArray(a);
    }

    @Override
    public boolean containsAll(final Collection<?> c) {
        return stack.containsAll(c);
    }

    @Override
    public boolean addAll(final Collection<? extends T> c) {
        return stack.addAll(c);
    }

    @Override
    public boolean removeAll(final Collection<?> c) {
        return stack.removeAll(c);
    }

    @Override
    public boolean retainAll(final Collection<?> c) {
        return stack.removeAll(c);
    }

    @Override
    public void clear() {
        stack.clear();
    }

    @Override
    public boolean add(final T e) {
        return stack.offerFirst(e); //Used offerFirst instead of add.
    }

    @Override
    public boolean offer(final T e) {
        return stack.offerFirst(e); //Used offerFirst instead of offer.
    }

    @Override
    public void put(final T e) throws InterruptedException {
        stack.put(e);
    }

    @Override
    public boolean offer(final T e, final long timeout, final TimeUnit unit)
    throws InterruptedException {
        return stack.offerLast(e, timeout, unit);
    }

    @Override
    public T take() throws InterruptedException {
        return stack.take();
    }

    @Override
    public T poll(final long timeout, final TimeUnit unit)
    throws InterruptedException {
        return stack.poll();
    }

    @Override
    public int remainingCapacity() {
        return stack.remainingCapacity();
    }

    @Override
    public boolean remove(final Object o) {
        return stack.remove(o);
    }

    @Override
    public boolean contains(final Object o) {
        return stack.contains(o);
    }

    @Override
    public int drainTo(final Collection<? super T> c) {
        return stack.drainTo(c);
    }

    @Override
    public int drainTo(final Collection<? super T> c, final int maxElements) {
        return stack.drainTo(c, maxElements);
    }
}

akf 15 年前

我相信封锁是你想要的。它支持堆栈。

我的密码里有什么:

private transient final ExecutorService threadPool= 
     new ThreadPoolExecutor(3, 10,10, 
                            TimeUnit.MILLISECONDS, 
                            new LinkedBlockingDeque<Runnable>());

Uhlen 14 年前

这是我实现的解决方案,对我试图解决的问题非常有效:)

/**
 * A "Single Last-In-First-Out Executor".
 * <p>
 * It maintains a queue of <b>one</b> task and only one task may execute simultaneously,
 * submitting a new task to {@link #execute(Runnable)} will discard any previous submitted not yet started tasks.
 */
public class SingleLIFOExecutor implements Executor
{
    private final ThreadPoolExecutor executor;
    private Runnable lastCommand;

    public SingleLIFOExecutor()
    {
        executor = new ThreadPoolExecutor(0, 1, 0, MILLISECONDS, new ArrayBlockingQueue<Runnable>(1));
    }

    /**
     * @see java.util.concurrent.Executor#execute(java.lang.Runnable)
     */
    @Override
    public void execute(Runnable command)
    {
        executor.remove(lastCommand);
        lastCommand = command;
        executor.execute(command);
    }
}