请勿过度依赖 Redis 的过期监听
来源:juejin.im/post/6844904158227595271
Redis 过期监听场景
业务中有类似等待一定时间之后执行某种行为的需求 , 比如 30 分钟之后关闭订单 . 网上有很多使用 Redis 过期监听的 Demo , 但是其实这是个大坑 , 因为 Redis 不能确保 key 在指定时间被删除 , 也就造成了通知的延期 . 不多说 , 跑个测试
测试情况
先说环境 , redis 运行在 Docker 容器中 , 分配了 一个 cpu 以及 512MB 内存, 在 Docker 中执行 redis-benchmark -t set -r 100000 -n 1000000
结果如下:
\====== 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
其实这里有些不严谨 benchmark
线程不应该在 Docker 容器内部运行 . 跑分的时候大概 benchmark 和 redis 主线程各自持有 50%CPU
测试代码如下:
@Service
@Slf4j
public 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 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("设置完毕: " + Duration.between(now, LocalDateTime.now()));
}
private void setExpireKey(LocalDateTime expireTime, int step, ValueOperations 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);
}
}
}
大概意思就是每小时 56 分的时候 , 会增加一批在接下来 16 小时过期的 key , 过期时间间隔 8 秒 , 且过期时间都在 55 分之前
@Slf4j
@Component
public 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
这里是监测到过期之后打印当前的 dbSize 以及滞后时间
@Bean
public 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已经达到max size的时候,如何处理新任务
// CALLER\_RUNS:不在新线程中执行任务,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的连接工厂
container.setConnectionFactory(connectionFactory);
// 设置监听使用的线程池
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 ,
最后的测试结果是当 key 数量小于 1 万的时候 , 基本上都可以在 10s 内完成过期通知 , 但是如果数量到 3 万 , 就有部分 key 会延迟 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 ,当前size:57405 ,滞后时间160
2020-05-13 22:16:49.389 : 过期key:2020-05-13 11:56:02@2020-05-13 22:14:32 ,当前size:57404 ,滞后时间137
2020-05-13 22:16:49.591 : 过期key:2020-05-13 10:56:02@2020-05-13 22:13:20 ,当前size:57403 ,滞后时间209
2020-05-13 22:16:50.093 : 过期key:2020-05-13 20:56:00@2020-05-13 22:12:32 ,当前size:57402 ,滞后时间258
2020-05-13 22:16:50.596 : 过期key:2020-05-13 07:56:03@2020-05-13 22:13:28 ,当前size:57401 ,滞后时间202
2020-05-13 22:16:50.697 : 过期key:2020-05-13 20:56:00@2020-05-13 22:14:32 ,当前size:57400 ,滞后时间138
2020-05-13 22:16:50.999 : 过期key:2020-05-13 19:56:00@2020-05-13 22:13:44 ,当前size:57399 ,滞后时间186
2020-05-13 22:16:51.199 : 过期key:2020-05-13 20:56:00@2020-05-13 22:14:40 ,当前size:57398 ,滞后时间131
2020-05-13 22:16:52.205 : 过期key:2020-05-13 15:56:01@2020-05-13 22:16:24 ,当前size:57397 ,滞后时间28
2020-05-13 22:16:52.808 : 过期key:2020-05-13 06:56:03@2020-05-13 22:15:04 ,当前size:57396 ,滞后时间108
2020-05-13 22:16:53.009 : 过期key:2020-05-13 06:56:03@2020-05-13 22:16:40 ,当前size:57395 ,滞后时间13
2020-05-13 22:16:53.110 : 过期key:2020-05-13 20:56:00@2020-05-13 22:14:56 ,当前size:57394 ,滞后时间117
2020-05-13 22:16:53.211 : 过期key:2020-05-13 06:56:03@2020-05-13 22:13:44 ,当前size:57393 ,滞后时间189
2020-05-13 22:16:53.613 : 过期key:2020-05-13 15:56:01@2020-05-13 22:12:24 ,当前size:57392 ,滞后时间269
2020-05-13 22:16:54.317 : 过期key:2020-05-13 15:56:01@2020-05-13 22:16:00 ,当前size:57391 ,滞后时间54
2020-05-13 22:16:54.517 : 过期key:2020-05-13 18:56:00@2020-05-13 22:15:44 ,当前size:57390 ,滞后时间70
2020-05-13 22:16:54.618 : 过期key:2020-05-13 21:56:00@2020-05-13 22:14:24 ,当前size:57389 ,滞后时间150
2020-05-13 22:16:54.819 : 过期key:2020-05-13 17:56:00@2020-05-13 22:14:40 ,当前size:57388 ,滞后时间134
2020-05-13 22:16:55.322 : 过期key:2020-05-13 10:56:02@2020-05-13 22:13:52 ,当前size:57387 ,滞后时间183
2020-05-13 22:16:55.423 : 过期key:2020-05-13 07:56:03@2020-05-13 22:14:16 ,当前size:57386 ,滞后时间159
可以看到 , 当数量到达 5 万的时候 , 大部分都已经滞后了两分钟 , 对于业务方来说已经完全无法忍受了
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/notifications#timing-of-expired-events
尤其是在 Timing of expired events 中 , 明确的说明了 "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
获得原创整理:《第2版:互联网大厂面试题》