基于redis的分布式锁二种应用场景

“分布式锁”是用来解决分布式应用中“并发冲突”的一种常用手段,实现方式一般有基于zookeeper及基于redis二种。具体到业务场景中,我们要考虑二种情况:

一、抢不到锁的请求,允许丢弃(即:忽略)

比如:一些不是很重要的场景,比如“监控数据持续上报”,某一篇文章的“已读/未读”标识位更新,对于同一个id,如果并发的请求同时到达,只要有一个请求处理成功,就算成功。

用活动图表示如下:

基于redis的分布式锁二种应用场景_第1张图片

 

二、并发请求,不论哪一条都必须要处理的场景(即:不允许丢数据)

比如:一个订单,客户正在前台修改地址,管理员在后台同时修改备注。地址和备注字段的修改,都必须正确更新,这二个请求同时到达的话,如果不借助db的事务,很容易造成行锁竞争,但用事务的话,db的性能显然比不上redis轻量。

解决思路:A,B二个请求,谁先抢到分布式锁(假设A先抢到锁),谁先处理,抢不到的那个(即:B),在一旁不停等待重试,重试期间一旦发现获取锁成功,即表示A已经处理完,把锁释放了。这时B就可以继续处理了。

但有二点要注意:

a、需要设置等待重试的最长时间,否则如果A处理过程中有bug,一直卡死,或者未能正确释放锁,B就一直会等待重试,但是又永远拿不到锁。

b、等待最长时间,必须小于锁的过期时间。否则,假设锁2秒过期自动释放,但是A还没处理完(即:A的处理时间大于2秒),这时锁会因为redis key过期“提前”误释放,B重试时拿到锁,造成A,B同时处理。(注:可能有同学会说,不设置锁的过期时间,不就完了么?理论上讲,确实可以这么做,但是如果业务代码有bug,导致处理完后没有unlock,或者根本忘记了unlock,分布式锁就会一直无法释放。所以综合考虑,给分布式锁加一个“保底”的过期时间,让其始终有机会自动释放,更为靠谱)

用活动图表示如下:

基于redis的分布式锁二种应用场景_第2张图片

写了一个简单的工具类:

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package com.cnblogs.yjmyzz.redisdistributionlock;

 

import org.slf4j.Logger;

import org.slf4j.LoggerFactory;

import org.springframework.data.redis.core.StringRedisTemplate;

import org.springframework.util.StringUtils;

 

import java.util.UUID;

import java.util.concurrent.TimeUnit;

 

/**

 * 利用redis获取分布式锁

 *

 * @author 菩提树下的杨过

 * @blog http://yjmyzz.cnblogs.com/

 */

public class RedisLock {

 

    private StringRedisTemplate redisTemplate;

 

    private Logger logger = LoggerFactory.getLogger(this.getClass());

 

    /**

     * simple lock尝试获取锅的次数

     */

    private int retryCount = 3;

 

    /**

     * 每次尝试获取锁的重试间隔毫秒数

     */

    private int waitIntervalInMS = 100;

 

 

    public RedisLock(StringRedisTemplate redisTemplate) {

        this.redisTemplate = redisTemplate;

    }

 

    /**

     * 利用redis获取分布式锁(未获取锁的请求,允许丢弃!)

     *

     * @param redisKey       锁的key值

     * @param expireInSecond 锁的自动释放时间(秒)

     * @return

     * @throws DistributionLockException

     */

    public String simpleLock(final String redisKey, final int expireInSecond) throws DistributionLockException {

        String lockValue = UUID.randomUUID().toString();

        boolean flag = false;

        if (StringUtils.isEmpty(redisKey)) {

            throw new DistributionLockException("key is empty!");

        }

        if (expireInSecond <= 0) {

            throw new DistributionLockException("expireInSecond must be bigger than 0");

        }

        try {

            for (int i = 0; i < retryCount; i++) {

                boolean success = redisTemplate.opsForValue().setIfAbsent(redisKey, lockValue, expireInSecond, TimeUnit.SECONDS);

                if (success) {

                    flag = true;

                    break;

                }

                try {

                    TimeUnit.MILLISECONDS.sleep(waitIntervalInMS);

                catch (Exception ignore) {

                    logger.warn("redis lock fail: " + ignore.getMessage());

 

                }

            }

            if (!flag) {

                throw new DistributionLockException(Thread.currentThread().getName() + " cannot acquire lock now ...");

            }

            return lockValue;

        catch (DistributionLockException be) {

            throw be;

        catch (Exception e) {

            logger.warn("get redis lock error, exception: " + e.getMessage());

            throw e;

        }

    }

 

    /**

     * 利用redis获取分布式锁(未获取锁的请求,将在timeoutSecond时间范围内,一直等待重试)

     *

     * @param redisKey       锁的key值

     * @param expireInSecond 锁的自动释放时间(秒)

     * @param timeoutSecond  未获取到锁的请求,尝试重试的最久等待时间(秒)

     * @return

     * @throws DistributionLockException

     */

    public String lock(final String redisKey, final int expireInSecond, final int timeoutSecond) throws DistributionLockException {

        String lockValue = UUID.randomUUID().toString();

        boolean flag = false;

        if (StringUtils.isEmpty(redisKey)) {

            throw new DistributionLockException("key is empty!");

        }

        if (expireInSecond <= 0) {

            throw new DistributionLockException("expireInSecond must be greater than 0");

        }

        if (timeoutSecond <= 0) {

            throw new DistributionLockException("timeoutSecond must be greater than 0");

        }

        if (timeoutSecond >= expireInSecond) {

            throw new DistributionLockException("timeoutSecond must be less than expireInSecond");

        }

        try {

            long timeoutAt = System.currentTimeMillis() + timeoutSecond * 1000;

            while (true) {

                boolean success = redisTemplate.opsForValue().setIfAbsent(redisKey, lockValue, expireInSecond, TimeUnit.SECONDS);

                if (success) {

                    flag = true;

                    break;

                }

                if (System.currentTimeMillis() >= timeoutAt) {

                    break;

                }

                try {

                    TimeUnit.MILLISECONDS.sleep(waitIntervalInMS);

                catch (Exception ignore) {

                    logger.warn("redis lock fail: " + ignore.getMessage());

                }

            }

            if (!flag) {

                throw new DistributionLockException(Thread.currentThread().getName() + " cannot acquire lock now ...");

            }

            return lockValue;

        catch (DistributionLockException be) {

            throw be;

        catch (Exception e) {

            logger.warn("get redis lock error, exception: " + e.getMessage());

            throw e;

        }

    }

 

 

    /**

     * 锁释放

     *

     * @param redisKey

     * @param lockValue

     */

    public void unlock(final String redisKey, final String lockValue) {

        if (StringUtils.isEmpty(redisKey)) {

            return;

        }

        if (StringUtils.isEmpty(lockValue)) {

            return;

        }

        try {

            String currLockVal = redisTemplate.opsForValue().get(redisKey);

            if (currLockVal != null && currLockVal.equals(lockValue)) {

                boolean result = redisTemplate.delete(redisKey);

                if (!result) {

                    logger.warn(Thread.currentThread().getName() + " unlock redis lock fail");

                else {

                    logger.info(Thread.currentThread().getName() + " unlock redis lock:" + redisKey + " successfully!");

                }

            }

        catch (Exception je) {

            logger.warn(Thread.currentThread().getName() + " unlock redis lock error:" + je.getMessage());

        }

    }

}

  

然后写个spring-boot来测试一下:

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package com.cnblogs.yjmyzz.redisdistributionlock;

 

import org.slf4j.Logger;

import org.slf4j.LoggerFactory;

import org.springframework.boot.SpringApplication;

import org.springframework.boot.autoconfigure.SpringBootApplication;

import org.springframework.context.ConfigurableApplicationContext;

import org.springframework.data.redis.core.StringRedisTemplate;

 

import java.util.concurrent.CountDownLatch;

import java.util.concurrent.TimeUnit;

 

@SpringBootApplication

public class RedisDistributionLockApplication {

 

    private static Logger logger = LoggerFactory.getLogger(RedisDistributionLockApplication.class);

 

    public static void main(String[] args) throws InterruptedException {

        ConfigurableApplicationContext applicationContext = SpringApplication.run(RedisDistributionLockApplication.class, args);

 

        //初始化

        StringRedisTemplate redisTemplate = applicationContext.getBean(StringRedisTemplate.class);

        RedisLock redisLock = new RedisLock(redisTemplate);

        String lockKey = "lock:test";

 

 

        CountDownLatch start = new CountDownLatch(1);

        CountDownLatch threadsLatch = new CountDownLatch(2);

 

        final int lockExpireSecond = 5;

        final int timeoutSecond = 3;

 

        Runnable lockRunnable = () -> {

            String lockValue = "";

            try {

                //等待发令枪响,防止线程抢跑

                start.await();

 

                //允许丢数据的简单锁示例

                lockValue = redisLock.simpleLock(lockKey, lockExpireSecond);

 

 

                //不允许丢数据的分布式锁示例

                //lockValue = redisLock.lock(lockKey, lockExpireSecond, timeoutSecond);

 

                //停一会儿,故意让后面的线程抢不到锁

                TimeUnit.SECONDS.sleep(2);

                logger.info(String.format("%s get lock successfully, value:%s", Thread.currentThread().getName(), lockValue));

 

            catch (Exception e) {

                e.printStackTrace();

            finally {

                redisLock.unlock(lockKey, lockValue);

                //执行完后,计数减1

                threadsLatch.countDown();

            }

 

        };

 

        Thread t1 = new Thread(lockRunnable, "T1");

        Thread t2 = new Thread(lockRunnable, "T2");

 

        t1.start();

        t2.start();

 

        //预备:开始!

        start.countDown();

 

        //等待所有线程跑完

        threadsLatch.await();

 

        logger.info("======>done!!!");

 

    }

 

}

 用2个线程模拟并发场景,跑起来后,输出如下:

点击查看原图

可以看到T2线程没抢到锁,直接抛出了预期的异常。

把44行的注释打开,即:换成不允许丢数据的模式,再跑一下:

点击查看原图

可以看到,T1先抢到锁,然后经过2秒的处理后,锁释放,这时T2重试拿到了锁,继续处理,最终释放。

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