关于java:请勿过度依赖Redis的过期监听

作者：迪壳
https://juejin.im/post/684490...

Redis 过期监听场景

业务中有相似期待肯定工夫之后执行某种行为的需要 , 比方 30 分钟之后敞开订单 . 网上有很多应用 Redis 过期监听的 Demo , 然而其实这是个大坑 , 因为 Redis 不能确保 key 在指定工夫被删除 , 也就造成了告诉的延期 . 不多说 , 跑个测试

测试状况

先说环境 , redis 运行在 Docker 容器中 , 调配了一个 cpu 以及 512MB 内存, 在 Docker 中执行 redis-benchmark -t set -r 100000 -n 1000000 后果如下:

\====== SET ======  1000000 requests completed in 171.03 seconds  50 parallel clients  3 bytes payload  keep alive: 1  host configuration "save": 3600 1 300 100 60 10000  host configuration "appendonly": no  multi-thread: no

其实这里有些不谨严 benchmark 线程不应该在 Docker 容器外部运行 . 跑分的时候大略 benchmark 和 redis 主线程各自持有 50%CPU

测试代码如下:

@Service@Slf4jpublic class RedisJob {    @Autowired    private StringRedisTemplate stringRedisTemplate;    public DateTimeFormatter dateTimeFormatter = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss");    public LocalDateTime end = LocalDateTime.of(LocalDate.of(2020, 5, 12), LocalTime.of(8, 0));    @Scheduled(cron = "0 56 \* \* \* ?")    public void initKeys() {        LocalDateTime now = LocalDateTime.now();        ValueOperations<String, String> operations = stringRedisTemplate.opsForValue();        log.info("开始设置key");        LocalDateTime begin = now.withMinute(0).withSecond(0).withNano(0);        for (int i = 1; i < 17; i++) {            setExpireKey(begin.plusHours(i), 8, operations);        }        log.info("设置结束: " + Duration.between(now, LocalDateTime.now()));    }    private void setExpireKey(LocalDateTime expireTime, int step, ValueOperations<String, String> operations) {        LocalDateTime localDateTime = LocalDateTime.now().withNano(0);        String nowTime = dateTimeFormatter.format(localDateTime);        while (expireTime.getMinute() < 55) {            operations.set(nowTime + "@" + dateTimeFormatter.format(expireTime), "A", Duration.between(expireTime, LocalDateTime.now()).abs());            expireTime = expireTime.plusSeconds(step);        }    }}

大略意思就是每小时 56 分的时候 , 会减少一批在接下来 16 小时过期的 key , 过期工夫距离 8 秒 , 且过期工夫都在 55 分之前

@Slf4j@Componentpublic class RedisKeyExpirationListener extends KeyExpirationEventMessageListener {    public RedisKeyExpirationListener(RedisMessageListenerContainer listenerContainer) {        super(listenerContainer);    }    public DateTimeFormatter dateTimeFormatter = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss");    @Autowired    private StringRedisTemplate stringRedisTemplate;    @Override    public void onMessage(Message message, byte\[\] pattern) {        String keyName = new String(message.getBody());        LocalDateTime parse = LocalDateTime.parse(keyName.split("@")\[1\], dateTimeFormatter);        long seconds = Duration.between(parse, LocalDateTime.now()).getSeconds();        stringRedisTemplate.execute((RedisCallback<Object>) connection -> {            Long size = connection.dbSize();            log.info("过期key:" + keyName + " ,以后size:" + size + " ,滞后工夫" + seconds);            return null;        });    }}

这里是监测到过期之后打印以后的 dbSize 以及滞后工夫

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@Beanpublic RedisMessageListenerContainer configRedisMessageListenerContainer(RedisConnectionFactory connectionFactory) {    ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();    executor.setCorePoolSize(100);    executor.setMaxPoolSize(100);    executor.setQueueCapacity(100);    executor.setKeepAliveSeconds(3600);    executor.setThreadNamePrefix("redis");    // rejection-policy：当pool曾经达到max size的时候，如何解决新工作    // CALLER\_RUNS：不在新线程中执行工作，而是由调用者所在的线程来执行    executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());    executor.initialize();    RedisMessageListenerContainer container = new RedisMessageListenerContainer();    // 设置Redis的连贯工厂    container.setConnectionFactory(connectionFactory);    // 设置监听应用的线程池    container.setTaskExecutor(executor);    // 设置监听的Topic    return container;}

设置 Redis 的过期监听以及线程池信息 ,

最初的测试后果是当 key 数量小于 1 万的时候 , 基本上都能够在 10s 内实现过期告诉 , 然而如果数量到 3 万 , 就有局部 key 会提早 120s . 顺便贴一下我最新的日志

2020-05-13 22:16:48.383  : 过期key:2020-05-13 11:56:02@2020-05-13 22:14:08 ,以后size:57405 ,滞后工夫1602020-05-13 22:16:49.389  : 过期key:2020-05-13 11:56:02@2020-05-13 22:14:32 ,以后size:57404 ,滞后工夫1372020-05-13 22:16:49.591  : 过期key:2020-05-13 10:56:02@2020-05-13 22:13:20 ,以后size:57403 ,滞后工夫2092020-05-13 22:16:50.093  : 过期key:2020-05-13 20:56:00@2020-05-13 22:12:32 ,以后size:57402 ,滞后工夫2582020-05-13 22:16:50.596  : 过期key:2020-05-13 07:56:03@2020-05-13 22:13:28 ,以后size:57401 ,滞后工夫2022020-05-13 22:16:50.697  : 过期key:2020-05-13 20:56:00@2020-05-13 22:14:32 ,以后size:57400 ,滞后工夫1382020-05-13 22:16:50.999  : 过期key:2020-05-13 19:56:00@2020-05-13 22:13:44 ,以后size:57399 ,滞后工夫1862020-05-13 22:16:51.199  : 过期key:2020-05-13 20:56:00@2020-05-13 22:14:40 ,以后size:57398 ,滞后工夫1312020-05-13 22:16:52.205  : 过期key:2020-05-13 15:56:01@2020-05-13 22:16:24 ,以后size:57397 ,滞后工夫282020-05-13 22:16:52.808  : 过期key:2020-05-13 06:56:03@2020-05-13 22:15:04 ,以后size:57396 ,滞后工夫1082020-05-13 22:16:53.009  : 过期key:2020-05-13 06:56:03@2020-05-13 22:16:40 ,以后size:57395 ,滞后工夫132020-05-13 22:16:53.110  : 过期key:2020-05-13 20:56:00@2020-05-13 22:14:56 ,以后size:57394 ,滞后工夫1172020-05-13 22:16:53.211  : 过期key:2020-05-13 06:56:03@2020-05-13 22:13:44 ,以后size:57393 ,滞后工夫1892020-05-13 22:16:53.613  : 过期key:2020-05-13 15:56:01@2020-05-13 22:12:24 ,以后size:57392 ,滞后工夫2692020-05-13 22:16:54.317  : 过期key:2020-05-13 15:56:01@2020-05-13 22:16:00 ,以后size:57391 ,滞后工夫542020-05-13 22:16:54.517  : 过期key:2020-05-13 18:56:00@2020-05-13 22:15:44 ,以后size:57390 ,滞后工夫702020-05-13 22:16:54.618  : 过期key:2020-05-13 21:56:00@2020-05-13 22:14:24 ,以后size:57389 ,滞后工夫1502020-05-13 22:16:54.819  : 过期key:2020-05-13 17:56:00@2020-05-13 22:14:40 ,以后size:57388 ,滞后工夫1342020-05-13 22:16:55.322  : 过期key:2020-05-13 10:56:02@2020-05-13 22:13:52 ,以后size:57387 ,滞后工夫1832020-05-13 22:16:55.423  : 过期key:2020-05-13 07:56:03@2020-05-13 22:14:16 ,以后size:57386 ,滞后工夫159

能够看到 , 当数量达到 5 万的时候 , 大部分都曾经滞后了两分钟 , 对于业务方来说曾经齐全无法忍受了

总结

可能到这里 , 你会说 Redis 给你挖了一个大坑 , 但其实这些都在文档上写的明明白白

How Redis expires keys：https://redis.io/commands/expire#how-redis-expires-keys
Timing of expired events：https://redis.io/topics/notif...#timing-of-expired-events

尤其是在 Timing of expired events 中 , 明确的阐明了 "Basically expired events are generated when the Redis server deletes the key and not when the time to live theoretically reaches the value of zero.", 这两个文章读下来你会感觉 , 卧槽 Redis 的过期策略其实也挺'Low'的

其实公众号看多了 , 你会发现大部分 Demo 都是相互抄来抄去 , 以及翻译官网 Demo . 倡议大家还是审慎一些 , 真要应用的话 , 最好读一下官网文档 , 哪怕用百度翻译也要有一些本人的了解 .

文章比拟干燥 , 感激大家急躁浏览 , 如有倡议恳请留言.

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