延时队列实现

考虑使用哪种方式实现延时队列,可能需要考虑下面这些问题:
及时性 消费端能按时收到
同一时间消息的消费权重
可靠性 消息不能出现没有被消费掉的情况
可恢复 假如有其他情况 导致消息系统不可用了 至少能保证数据可以恢复
可撤回 因为是延迟消息 没有到执行时间的消息支持可以取消消费
高可用 多实例 这里指HA/主备模式并不是多实例同时一起工作
消费端如何消费
任务丢失的补偿

一、单机

1. while+sleep组合

定义一个线程,然后 while 循环

public static void main(String[] args) {
    final long timeInterval = 5000;
    new Thread(new Runnable() {
        @Override
        public void run() {
            while (true) {
                System.out.println(Thread.currentThread().getName() + "每隔5秒执行一次");
                try {
                    Thread.sleep(timeInterval);
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
            }
        }
    }).start();
}

这种实现方式下多个定时任务需要开启多个线程,而且线程在做无意义sleep,消耗资源,性能低下。

2. 最小堆实现

2.1 Timer

实现代码,调度两个任务

public static void main(String[] args) {
    Timer timer = new Timer();
    //每隔1秒调用一次
    timer.schedule(new TimerTask() {
        @Override
        public void run() {
            System.out.println("test1");
        }
    }, 1000, 1000);
    //每隔3秒调用一次
    timer.schedule(new TimerTask() {
        @Override
        public void run() {
            System.out.println("test2");
        }
    }, 3000, 3000);

}

schedule实现源码

    public void schedule(TimerTask task, long delay, long period) {
        if (delay < 0)
            throw new IllegalArgumentException("Negative delay.");
        if (period <= 0)
            throw new IllegalArgumentException("Non-positive period.");
        sched(task, System.currentTimeMillis()+delay, -period);
    }

shed里面将任务add到最小堆,然后fixUp进行调整
TimerThread其实就是一个任务调度线程,首先从TaskQueue里面获取排在最前面的任务,然后判断它是否到达任务执行时间点,如果已到达,就会立刻执行任务

class TimerThread extends Thread {

    boolean newTasksMayBeScheduled = true;

    private TaskQueue queue;

    TimerThread(TaskQueue queue) {
        this.queue = queue;
    }

    public void run() {
        try {
            mainLoop();
        } finally {
            // Someone killed this Thread, behave as if Timer cancelled
            synchronized(queue) {
                newTasksMayBeScheduled = false;
                queue.clear();  // Eliminate obsolete references
            }
        }
    }

    /**
     * The main timer loop.  (See class comment.)
     */
    private void mainLoop() {
        while (true) {
            try {
                TimerTask task;
                boolean taskFired;
                synchronized(queue) {
                    // Wait for queue to become non-empty
                    while (queue.isEmpty() && newTasksMayBeScheduled)
                        queue.wait();
                    if (queue.isEmpty())
                        break; // Queue is empty and will forever remain; die

                    // Queue nonempty; look at first evt and do the right thing
                    long currentTime, executionTime;
                    task = queue.getMin();
                    synchronized(task.lock) {
                        if (task.state == TimerTask.CANCELLED) {
                            queue.removeMin();
                            continue;  // No action required, poll queue again
                        }
                        currentTime = System.currentTimeMillis();
                        executionTime = task.nextExecutionTime;
                        if (taskFired = (executionTime<=currentTime)) {
                            if (task.period == 0) { // Non-repeating, remove
                                queue.removeMin();
                                task.state = TimerTask.EXECUTED;
                            } else { // Repeating task, reschedule
                                queue.rescheduleMin(
                                  task.period<0 ? currentTime   - task.period
                                                : executionTime + task.period);
                            }
                        }
                    }
                    if (!taskFired) // Task hasn't yet fired; wait
                        queue.wait(executionTime - currentTime);
                }
                if (taskFired)  // Task fired; run it, holding no locks
                    task.run();
            } catch(InterruptedException e) {
            }
        }
    }
}

总结这个利用最小堆实现的方案,相比 while + sleep 方案,多了一个线程来管理所有的任务,优点就是减少了线程之间的性能开销,提升了执行效率;但是同样也带来的了一些缺点,整体的新加任务写入效率变成了 O(log(n))。

同时,细心的发现,这个方案还有以下几个缺点:

串行阻塞:调度线程只有一个,长任务会阻塞短任务的执行,例如,A任务跑了一分钟,B任务至少需要等1分钟才能跑
容错能力差:没有异常处理能力,一旦一个任务执行故障,后续任务都无法执行

2.2 ScheduledThreadPoolExecutor

鉴于 Timer 的上述缺陷,从 Java 5 开始,推出了基于线程池设计的 ScheduledThreadPoolExecutor 。

image

其设计思想是,每一个被调度的任务都会由线程池来管理执行,因此任务是并发执行的,相互之间不会受到干扰。需要注意的是,只有当任务的执行时间到来时,ScheduledThreadPoolExecutor 才会真正启动一个线程,其余时间 ScheduledThreadPoolExecutor 都是在轮询任务的状态。

简单的使用示例:

        ScheduledThreadPoolExecutor executor = new ScheduledThreadPoolExecutor(3);
        //启动1秒之后,每隔1秒执行一次
        executor.scheduleAtFixedRate(()-> System.out.println("test3"),1,1, TimeUnit.SECONDS);
        //启动1秒之后,每隔3秒执行一次
        executor.scheduleAtFixedRate((() -> System.out.println("test4")),1,3, TimeUnit.SECONDS);

同样的,我们首先打开源码,看看里面到底做了啥

  • 进入scheduleAtFixedRate()方法

首先是校验基本参数,然后将任务作为封装到ScheduledFutureTask线程中,ScheduledFutureTask继承自RunnableScheduledFuture,并作为参数调用delayedExecute()方法进行预处理

public ScheduledFuture<?> scheduleAtFixedRate(Runnable command,
                                              long initialDelay,
                                              long period,
                                              TimeUnit unit) {
    if (command == null || unit == null)
        throw new NullPointerException();
    if (period <= 0)
        throw new IllegalArgumentException();
    ScheduledFutureTask<Void> sft =
        new ScheduledFutureTask<Void>(command,
                                      null,
                                      triggerTime(initialDelay, unit),
                                      unit.toNanos(period));
    RunnableScheduledFuture<Void> t = decorateTask(command, sft);
    sft.outerTask = t;
    delayedExecute(t);
    return t;
}

  • 继续看delayedExecute()方法

可以很清晰的看到,当线程池没有关闭的时候,会通过super.getQueue().add(task)操作,将任务加入到队列,同时调用ensurePrestart()方法做预处理

private void delayedExecute(RunnableScheduledFuture<?> task) {
    if (isShutdown())
        reject(task);
    else {
        super.getQueue().add(task);
        if (isShutdown() &&
            !canRunInCurrentRunState(task.isPeriodic()) &&
            remove(task))
            task.cancel(false);
        else
   //预处理
            ensurePrestart();
    }
}

其中super.getQueue()得到的是一个自定义的new DelayedWorkQueue()阻塞队列,数据存储方面也是一个最小堆结构的队列,这一点在初始化new ScheduledThreadPoolExecutor()的时候,可以看出!

public ScheduledThreadPoolExecutor(int corePoolSize) {
    super(corePoolSize, Integer.MAX_VALUE, 0, NANOSECONDS,
          new DelayedWorkQueue());
}

打开源码可以看到,DelayedWorkQueue其实是ScheduledThreadPoolExecutor中的一个静态内部类,在添加的时候,会将任务加入到RunnableScheduledFuture数组中。然后调用线程池的ensurePrestart方法将任务添加到线程池。调用链:addWorker->t.run->new Worker.run-> runWorker->Runnable r = timed ?
workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :
workQueue.take();->task.run->RunnableScheduledFuture.run

static class DelayedWorkQueue extends AbstractQueue<Runnable>
        implements BlockingQueue<Runnable> {

    private static final int INITIAL_CAPACITY = 16;
    private RunnableScheduledFuture<?>[] queue =
        new RunnableScheduledFuture<?>[INITIAL_CAPACITY];
    private final ReentrantLock lock = new ReentrantLock();
    private int size = 0;   

    //....

    public boolean add(Runnable e) {
        return offer(e);
    }

    public boolean offer(Runnable x) {
        if (x == null)
            throw new NullPointerException();
        RunnableScheduledFuture<?> e = (RunnableScheduledFuture<?>)x;
        final ReentrantLock lock = this.lock;
        lock.lock();
        try {
            int i = size;
            if (i >= queue.length)
                grow();
            size = i + 1;
            if (i == 0) {
                queue[0] = e;
                setIndex(e, 0);
            } else {
                siftUp(i, e);
            }
            if (queue[0] == e) {
                leader = null;
                available.signal();
            }
        } finally {
            lock.unlock();
        }
        return true;
    }

    public RunnableScheduledFuture<?> take() throws InterruptedException {
        final ReentrantLock lock = this.lock;
        lock.lockInterruptibly();
        try {
            for (;;) {
                RunnableScheduledFuture<?> first = queue[0];
                if (first == null)
                    available.await();
                else {
                    long delay = first.getDelay(NANOSECONDS);
                    if (delay <= 0)
                        return finishPoll(first);
                    first = null; // don't retain ref while waiting
                    if (leader != null)
                        available.await();
                    else {
                        Thread thisThread = Thread.currentThread();
                        leader = thisThread;
                        try {
                            available.awaitNanos(delay);
                        } finally {
                            if (leader == thisThread)
                                leader = null;
                        }
                    }
                }
            }
        } finally {
            if (leader == null && queue[0] != null)
                available.signal();
            lock.unlock();
        }
    }
}

  • 回到我们最开始说到的ScheduledFutureTask任务线程类,最终执行任务的其实就是它

ScheduledFutureTask任务线程,才是真正执行任务的线程类,只是绕了一圈,做了很多包装,run()方法就是真正执行定时任务的方法。

private class ScheduledFutureTask<V>
            extends FutureTask<V> implements RunnableScheduledFuture<V> {

    /** Sequence number to break ties FIFO */
    private final long sequenceNumber;

    /** The time the task is enabled to execute in nanoTime units */
    private long time;

    /**
     * Period in nanoseconds for repeating tasks.  A positive
     * value indicates fixed-rate execution.  A negative value
     * indicates fixed-delay execution.  A value of 0 indicates a
     * non-repeating task.
     */
    private final long period;

    /** The actual task to be re-enqueued by reExecutePeriodic */
    RunnableScheduledFuture<V> outerTask = this;

    /**
     * Overrides FutureTask version so as to reset/requeue if periodic.
     */
    public void run() {
        boolean periodic = isPeriodic();
        if (!canRunInCurrentRunState(periodic))
            cancel(false);
        else if (!periodic)//非周期性定时任务
            ScheduledFutureTask.super.run();
        else if (ScheduledFutureTask.super.runAndReset()) {//周期性定时任务,需要重置
            setNextRunTime();
            reExecutePeriodic(outerTask);
        }
    }

 //...
}

3.3、小结

ScheduledExecutorService 相比 Timer 定时器,完美的解决上面说到的 Timer 存在的两个缺点!

在单体应用里面,使用 ScheduledExecutorService 可以解决大部分需要使用定时任务的业务需求!

但是这是否意味着它是最佳的解决方案呢?

我们发现线程池中 ScheduledExecutorService 的排序容器跟 Timer 一样,都是采用最小堆的存储结构,新任务加入排序效率是O(log(n)),执行取任务是O(1)。

这里的写入排序效率其实是有空间可提升的,有可能优化到O(1)的时间复杂度,也就是我们下面要介绍的时间轮实现

2.3 DelayQueue

DelayQueue是一个无界延时队列,内部有一个优先队列,可以重写compare接口,按照我们想要的方式进行排序。
实现Demo

    public static void main(String[] args) throws Exception {
        DelayQueue<Order> orders = new DelayQueue<>();
        Order order1 = new Order(1000, "1x");
        Order order2 = new Order(2000, "2x");
        Order order3 = new Order(3000, "3x");
        Order order4 = new Order(4000, "4x");
        orders.add(order1);
        orders.add(order2);
        orders.add(order3);
        orders.add(order4);
        for (; ; ) {
            //没有到期会阻塞
            Order take = orders.take();
            System.out.println(take);
        }
    }
}

class Order implements Delayed {
    @Override
    public String toString() {
        return "DelayedElement{" + "delay=" + delayTime +
                ", expire=" + expire +
                ", data='" + data + '\'' +
                '}';
    }

    Order(long delay, String data) {
        delayTime = delay;
        this.data = data;
        expire = System.currentTimeMillis() + delay;
    }

    private final long delayTime; //延迟时间
    private final long expire;  //到期时间
    private String data;   //数据

    /**
     * 剩余时间=到期时间-当前时间
     */
    @Override
    public long getDelay(TimeUnit unit) {
        return unit.convert(this.expire - System.currentTimeMillis(), TimeUnit.MILLISECONDS);
    }

    /**
     * 优先队列里面优先级规则
     */
    @Override
    public int compareTo(Delayed o) {
        return (int) (this.getDelay(TimeUnit.MILLISECONDS) - o.getDelay(TimeUnit.MILLISECONDS));
    }

从源码可以看出,DelayQueue的offer和take方法调用的是优先队列的offer和take。并且使用了ReetrtantLock保证线程安全

    public boolean offer(E e) {
        final ReentrantLock lock = this.lock;
        lock.lock();
        try {
            q.offer(e);
            if (q.peek() == e) {
                leader = null;
                available.signal();
            }
            return true;
        } finally {
            lock.unlock();
        }
    }


public E take() throws InterruptedException {
        final ReentrantLock lock = this.lock;
        lock.lockInterruptibly();
        try {
            for (;;) {
                E first = q.peek();
                if (first == null)
                    available.await();
                else {
                    long delay = first.getDelay(NANOSECONDS);
                    if (delay <= 0)
                        return q.poll();
                    first = null; // don't retain ref while waiting
                    if (leader != null)
                        available.await();
                    else {
                        Thread thisThread = Thread.currentThread();
                        leader = thisThread;
                        try {
                            available.awaitNanos(delay);
                        } finally {
                            if (leader == thisThread)
                                leader = null;
                        }
                    }
                }
            }
        } finally {
            if (leader == null && q.peek() != null)
                available.signal();
            lock.unlock();
        }
    }

https://my.oschina.net/u/2474629/blog/1919127

3. 时间轮实现

代码实现:支持秒级别的循环队列,从下标最小的任务集合开始,提交到线程池执行。然后休眠1s,指针移动到下一个下标处。
所谓时间轮(RingBuffer)实现,从数据结构上看,简单的说就是循环队列,从名称上看可能感觉很抽象。
它其实就是一个环形的数组,如图所示,假设我们创建了一个长度为 8 的时间轮。

image

插入、取值流程:

  • 1.当我们需要新建一个 1s 延时任务的时候,则只需要将它放到下标为 1 的那个槽中,2、3、...、7也同样如此。
  • 2.而如果是新建一个 10s 的延时任务,则需要将它放到下标为 2 的槽中,但同时需要记录它所对应的圈数,也就是 1 圈,不然就和 2 秒的延时消息重复了
  • 3.当创建一个 21s 的延时任务时,它所在的位置就在下标为 5 的槽中,同样的需要为他加上圈数为 2,依次类推...

因此,总结起来有两个核心的变量:

  • 数组下标:表示某个任务延迟时间,从数据操作上对执行时间点进行取余
  • 圈数:表示需要循环圈数

通过这张图可以更直观的理解!

image

当我们需要取出延时任务时,只需要每秒往下移动这个指针,然后取出该位置的所有任务即可,取任务的时间消耗为O(1)。

当我们需要插入任务,也只需要计算出对应的下表和圈数,即可将任务插入到对应的数组位置中,插入任务的时间消耗为O(1)。

如果时间轮的槽比较少,会导致某一个槽上的任务非常多,那么效率也比较低,这就和 HashMap 的 hash 冲突是一样的,因此在设计槽的时候不能太大也不能太小。

package com.hui.hui;

import java.util.Collection;
import java.util.HashSet;
import java.util.Map;
import java.util.Set;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.atomic.AtomicBoolean;
import java.util.concurrent.atomic.AtomicInteger;
import java.util.concurrent.locks.Condition;
import java.util.concurrent.locks.Lock;
import java.util.concurrent.locks.ReentrantLock;

public class RingBuffer {

    private static final int STATIC_RING_SIZE = 64;

    private Object[] ringBuffer;

    private int bufferSize;

    /**
     * business thread pool
     */
    private ExecutorService executorService;

    private volatile int size = 0;

    /***
     * task stop sign
     */
    private volatile boolean stop = false;

    /**
     * task start sign
     */
    private volatile AtomicBoolean start = new AtomicBoolean(false);

    /**
     * total tick times
     */
    private AtomicInteger tick = new AtomicInteger();

    private Lock lock = new ReentrantLock();
    private Condition condition = lock.newCondition();

    private AtomicInteger taskId = new AtomicInteger();
    private Map<Integer, Task> taskMap = new ConcurrentHashMap<>(16);

    /**
     * Create a new delay task ring buffer by default size
     *
     * @param executorService the business thread pool
     */
    public RingBuffer(ExecutorService executorService) {
        this.executorService = executorService;
        this.bufferSize = STATIC_RING_SIZE;
        this.ringBuffer = new Object[bufferSize];
    }

    /**
     * Create a new delay task ring buffer by custom buffer size
     *
     * @param executorService the business thread pool
     * @param bufferSize      custom buffer size
     */
    public RingBuffer(ExecutorService executorService, int bufferSize) {
        this(executorService);

        if (!powerOf2(bufferSize)) {
            throw new RuntimeException("bufferSize=[" + bufferSize + "] must be a power of 2");
        }
        this.bufferSize = bufferSize;
        this.ringBuffer = new Object[bufferSize];
    }

    /**
     * Add a task into the ring buffer(thread safe)
     *
     * @param task business task extends {@link Task}
     */
    public int addTask(Task task) {
        int key = task.getKey();
        int id;

        try {
            lock.lock();
            int index = mod(key, bufferSize);
            task.setIndex(index);
            Set<Task> tasks = get(index);

            int cycleNum = cycleNum(key, bufferSize);
            if (tasks != null) {
                task.setCycleNum(cycleNum);
                tasks.add(task);
            } else {
                task.setIndex(index);
                task.setCycleNum(cycleNum);
                Set<Task> sets = new HashSet<>();
                sets.add(task);
                put(key, sets);
            }
            id = taskId.incrementAndGet();
            task.setTaskId(id);
            taskMap.put(id, task);
            size++;
        } finally {
            lock.unlock();
        }

        start();

        return id;
    }

    /**
     * Cancel task by taskId
     *
     * @param id unique id through {@link #addTask(Task)}
     * @return
     */
    public boolean cancel(int id) {

        boolean flag = false;
        Set<Task> tempTask = new HashSet<>();

        try {
            lock.lock();
            Task task = taskMap.get(id);
            if (task == null) {
                return false;
            }

            Set<Task> tasks = get(task.getIndex());
            for (Task tk : tasks) {
                if (tk.getKey() == task.getKey() && tk.getCycleNum() == task.getCycleNum()) {
                    size--;
                    flag = true;
                    taskMap.remove(id);
                } else {
                    tempTask.add(tk);
                }

            }
            //update origin data
            ringBuffer[task.getIndex()] = tempTask;
        } finally {
            lock.unlock();
        }

        return flag;
    }

    /**
     * Thread safe
     *
     * @return the size of ring buffer
     */
    public int taskSize() {
        return size;
    }

    /**
     * Same with method {@link #taskSize}
     *
     * @return
     */
    public int taskMapSize() {
        return taskMap.size();
    }

    /**
     * Start background thread to consumer wheel timer, it will always run until you call method {@link #stop}
     */
    public void start() {
        if (!start.get()) {
            System.out.println("Delay task is starting");
            if (start.compareAndSet(start.get(), true)) {
                Thread job = new Thread(new TriggerJob());
                job.setName("consumer RingBuffer thread");
                job.start();
                start.set(true);
            }

        }
    }

    /**
     * Stop consumer ring buffer thread
     *
     * @param force True will force close consumer thread and discard all pending tasks
     *              otherwise the consumer thread waits for all tasks to completes before closing.
     */
    public void stop(boolean force) {
        if (force) {
            stop = true;
            executorService.shutdownNow();
        } else {
            System.out.println("Delay task is stopping");
            if (taskSize() > 0) {
                try {
                    lock.lock();
                    condition.await();
                    stop = true;
                } catch (InterruptedException e) {
                    System.out.println("InterruptedException" + e);
                } finally {
                    lock.unlock();
                }
            }
            executorService.shutdown();
        }

    }

    private Set<Task> get(int index) {
        return (Set<Task>) ringBuffer[index];
    }

    private void put(int key, Set<Task> tasks) {
        int index = mod(key, bufferSize);
        ringBuffer[index] = tasks;
    }

    /**
     * Remove and get task list.
     *
     * @param key
     * @return task list
     */
    private Set<Task> remove(int key) {
        Set<Task> tempTask = new HashSet<>();
        Set<Task> result = new HashSet<>();

        Set<Task> tasks = (Set<Task>) ringBuffer[key];
        if (tasks == null) {
            return result;
        }

        for (Task task : tasks) {
            if (task.getCycleNum() == 0) {
                result.add(task);

                size2Notify();
            } else {
                // decrement 1 cycle number and update origin data
                task.setCycleNum(task.getCycleNum() - 1);
                tempTask.add(task);
            }
            // remove task, and free the memory.
            taskMap.remove(task.getTaskId());
        }

        //update origin data
        ringBuffer[key] = tempTask;

        return result;
    }

    private void size2Notify() {
        try {
            lock.lock();
            size--;
            if (size == 0) {
                condition.signal();
            }
        } finally {
            lock.unlock();
        }
    }

    private boolean powerOf2(int target) {
        if (target < 0) {
            return false;
        }
        int value = target & (target - 1);
        if (value != 0) {
            return false;
        }

        return true;
    }

    private int mod(int target, int mod) {
        // equals target % mod
        target = target + tick.get();
        return target & (mod - 1);
    }

    private int cycleNum(int target, int mod) {
        //equals target/mod
        return target >> Integer.bitCount(mod - 1);
    }

    /**
     * An abstract class used to implement business.
     */
    public abstract static class Task extends Thread {

        private int index;

        private int cycleNum;

        private int key;

        /**
         * The unique ID of the task
         */
        private int taskId;

        @Override
        public void run() {
        }

        public int getKey() {
            return key;
        }

        /**
         * @param key Delay time(seconds)
         */
        public void setKey(int key) {
            this.key = key;
        }

        public int getCycleNum() {
            return cycleNum;
        }

        private void setCycleNum(int cycleNum) {
            this.cycleNum = cycleNum;
        }

        public int getIndex() {
            return index;
        }

        private void setIndex(int index) {
            this.index = index;
        }

        public int getTaskId() {
            return taskId;
        }

        public void setTaskId(int taskId) {
            this.taskId = taskId;
        }
    }

    private class TriggerJob implements Runnable {

        @Override
        public void run() {
            int index = 0;
            while (!stop) {
                try {
                    Set<Task> tasks = remove(index);
                    for (Task task : tasks) {
                        executorService.submit(task);
                    }

                    if (++index > bufferSize - 1) {
                        index = 0;
                    }

                    //Total tick number of records
                    tick.incrementAndGet();
                    TimeUnit.SECONDS.sleep(1);

                } catch (Exception e) {
                    System.out.println("Exception" + e);
                }

            }

            System.out.println("Delay task has stopped");
        }
    }

    public static void main(String[] args) {
        RingBuffer ringBufferWheel = new RingBuffer(Executors.newFixedThreadPool(2));
        for (int i = 0; i < 3; i++) {
            RingBuffer.Task job = new Job();
            job.setKey(i);
            ringBufferWheel.addTask(job);
        }
    }

    public static class Job extends RingBuffer.Task {
        @Override
        public void run() {

            System.out.println("test5"+getIndex());
        }
    }
}

二、分布式

之前说的单机实现,一旦服务器重启,那么延时任务会丢失,而分布式的方案则不会丢失任务。

Redis ZSet实现

  1. 底层实现:Redis的底层实现是当key大小小于某个阈值,并且键值对个数小于某个阈值(都可配置),使用ZipList实现,否则使用SkipList和Hash实现,SkipList中按照score排序,hash存储成员到分数的映射。
  2. ZSet API
  • 添加,如果值存在添加,将会重新排序。zadd
    127.0.0.1:6379>zadd myZSet 1 zlh ---添加分数为1,值为zlh的zset集合
  • 查看zset集合的成员个数。zcard
    127.0.0.1:6379>zcard myZSet
  • 查看Zset指定范围的成员,withscores为输出结果带分数。zrange
    127.0.0.1:6379>zrange mZySet 0 -1 ----0为开始,-1为结束,输出顺序结果为: zlh tom jim
  • 获取zset成员的下标位置,如果值不存在返回null。zrank
    127.0.0.1:6379>zrank mZySet Jim ---Jim的在zset集合中的下标为2
  • 获取zset集合指定分数之间存在的成员个数。zcount
    127.0.0.1:6379>zcount mySet 1 3 ---输出分数>=1 and 分数 <=3的成员个数为3
  1. 实现思路:
  • 添加任务时,将当前时间+延时时间作为SkipList的分词,job的key作为成员标识加入ZSet
  • 搬运线程开启定时任务,将在当前时间戳之前的任务添加到队列中
  • 开启消费线程,无限循环,超时从队列获取Job,将任务放到线程池中消费
  • 添加任务,消费线程,搬运线程,都需要获取Redis分布式锁

RabbitMQ

参考:https://www.jianshu.com/p/fb83c68feec4

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