WatchDog+Redis实现分布式锁

代码说明：
watchDog机制主要是用来对redis中商品key进行锁续命，防止业务处理时间过长导致的误删key值。
lua脚本则用来对redis中指令的原子性操作，注意 lua脚本中不能有复杂逻辑，防止阻塞redis

/**
     * 创建定时任务线程工厂
     */
    private static final ThreadFactory THREAD_FACTORY = new ThreadFactoryBuilder().setNameFormat("watchDog-").get();
	
	/**
	* 创建定时任务线程
	*/
    private static final ScheduledExecutorService SCHEDULED_EXECUTOR_SERVICE = new ScheduledThreadPoolExecutor(10,THREAD_FACTORY);

    /**
     * 存放看门狗返回的线程对象
     */
    private static final ConcurrentHashMap CONCURRENT_HASH_MAP = new ConcurrentHashMap<>(16);


 @GetMapping("/normal")
    public String normalRedisLock() throws InterruptedException {
        //给每一个线程都设置对应的UUID
        String productId = "product_huawei_p30";
        String stock = "stock";
        String clientId = UUID.randomUUID().toString();
        try {
            //如果线程已经被加锁，死循环等待释放锁
            while (true){
                Integer stockNum = Integer.parseInt(stringRedisTemplate.opsForValue().get(stock));
                if(stockNum <= 0){
                    return "商品已经卖完";
                }
                //线程加锁，为10秒钟，设置为对应的客户端ID
                Boolean setIfAbsent = stringRedisTemplate.opsForValue().setIfAbsent(productId, clientId, 10, TimeUnit.SECONDS);
                if(Objects.nonNull(setIfAbsent) && setIfAbsent){
                    break;
                }
            }
            System.out.println("----------------------------------开始扣减库存----------------------------------");
            /**
             * 看门狗机制，目的是在线程业务处理时间过长时，导致锁被提前释放，导致处理完成时错误的释放掉另外线程的锁
             */
            WatchDogThread watchDogThread = new WatchDogThread(productId,clientId,stringRedisTemplate,CONCURRENT_HASH_MAP,SCHEDULED_EXECUTOR_SERVICE);
            ScheduledFuture scheduledFuture = SCHEDULED_EXECUTOR_SERVICE.scheduleAtFixedRate(watchDogThread, 1, 5, TimeUnit.SECONDS);
            /**
             * 采用ConcurrentHaspMap用来存储，watchDog任务，并且停止指定的watchDog任务
             */
            CONCURRENT_HASH_MAP.put(clientId,scheduledFuture);
            //执行业务逻辑
            int stockNum = Integer.parseInt(stringRedisTemplate.opsForValue().get(stock));
            if(stockNum > 0){
                /*System.out.println("模拟业务处理时间过长，看门狗续命机制.....");
                Thread.sleep(20000);*/
                stringRedisTemplate.opsForValue().set(stock,String.valueOf(stockNum-1));
                System.out.println("扣减库存成功库存数量为："+stringRedisTemplate.opsForValue().get(stock));
            }else {
                System.out.println("库存扣减失败。。。。");
            }
        } catch (Exception e) {
            /**
             * 抛出异常时，获取到对应客户端ID的看门狗线程，并且停止看门狗机制
             */
            ScheduledFuture scheduledFuture = CONCURRENT_HASH_MAP.get(clientId);
            if(scheduledFuture != null){
                System.out.println("异常信息，移除看门狗线程。。。");
                scheduledFuture.cancel(true);
                CONCURRENT_HASH_MAP.remove(clientId);
            }
        } finally {
            //释放锁
            stringRedisTemplate.delete(productId);
            System.out.println("----------------------------------业务执行完成----------------------------------");
        }
        return "";

    }

WatchDog实现机制

public class WatchDogThread implements Runnable {

    private String productId;
    private String clientId;
    private StringRedisTemplate stringRedisTemplate;
    private ConcurrentHashMap cacheMap;
    //获取到线程池的引用
    private ScheduledExecutorService scheduledExecutorService;

    /**
     * lua脚本，目的原子操作，获取到商品锁如果等于当前客户端ID，执行锁续命
     */
    private static final String SCRIPT = "if redis.call('get',KEYS[1]) == ARGV[1] then" +
            " local ttl = tonumber(redis.call('ttl',KEYS[1]));" +
            " redis.call('expire',KEYS[1],ttl+ARGV[2]) return redis.call('ttl',KEYS[1]) end";

    public WatchDogThread(String productId,String clientId, StringRedisTemplate stringRedisTemplate, ConcurrentHashMap concurrentHashMap,ScheduledExecutorService scheduledExecutorService) {
        this.clientId = clientId;
        this.productId = productId;
        this.stringRedisTemplate = stringRedisTemplate;
        this.cacheMap = concurrentHashMap;
        this.scheduledExecutorService = scheduledExecutorService;
    }

    @Override
    public void run() {
        String lock = stringRedisTemplate.opsForValue().get(productId);
        try {
            //如果获取到锁为空，或者获取到的锁不等于当前客户端ID，那么就直接停止看门狗
            if (StringUtils.isEmpty(lock) || !clientId.equals(lock)) {
                ScheduledFuture scheduledFuture = cacheMap.get(clientId);
                if (scheduledFuture != null) {
                    System.out.println("库存扣减完成，关闭开门狗。。。");
                    scheduledFuture.cancel(true);
                    cacheMap.remove(clientId);
                }
                return;
            }
            System.out.println("执行续命任务ID:"+lock);
            //执行lua脚本，用来原子性执行锁续命
            stringRedisTemplate.execute(new DefaultRedisScript(SCRIPT, Long.class), Collections.singletonList(productId),clientId,"10");
            Long expire = stringRedisTemplate.getExpire(productId, TimeUnit.SECONDS);
            System.out.println("续命后时间；"+expire);
        } catch (Exception e) {
            System.out.println("watchdog执行失败"+e.getMessage());
            /**
             * 如果watchDog执行续命任务出现异常，直接设置30秒过期时间，防止key值失效，导致误删
             */
            this.stringRedisTemplate.expire(productId,30,TimeUnit.SECONDS);
            /*WatchDogThread watchDogThread = new WatchDogThread(productId,clientId,stringRedisTemplate,this.cacheMap,this.scheduledExecutorService);
            this.scheduledExecutorService.scheduleAtFixedRate(watchDogThread, 1, 5, TimeUnit.SECONDS);*/
        }
    }
}

心得：

如果并发量过高，可以将商品库存进行拆分，如果是redis-cluster架构，可以通过一致性hash，将商品库存分配到不同的redis中进行存储，用来提高并发量。