Shulou(Shulou.com)06/01 Report--

1 Overview

The interfaces in the system usually have limited flow, such as 70 times per second, how to ensure that the calls of our interfaces fail quickly when they exceed the current limit of the third-party interface? At this point, the current limiter is needed. The following is the flow chart of the author using redis to realize the current limiter.

2 code

/ * * obtain current limit permission * @ param key * @ param millisecond milliseconds * @ param limitCount number of current restrictions * @ return * / public static boolean getCurrentLimiting (String key, Long millisecond, Integer limitCount) {try {boolean currentLimitingLock = RedisDistributeLockUtil.lock (key); if (currentLimitingLock) {Long llen = RedisClient.llen (getCurrentLimitingRedisKey (key)); if (llen)

< limitCount){ RedisClient.lpush(getCurrentLimitingRedisKey(key), DateUtil.current(false) + ""); return true; }else{ Long lastTime = Long.parseLong(RedisClient.lindex(getCurrentLimitingRedisKey(key), -1)); if((DateUtil.current(false) - lastTime) >

= millisecond) {RedisClient.lpush (getCurrentLimitingRedisKey (key), DateUtil.current (false) + ""); RedisClient.ltrim (getCurrentLimitingRedisKey (key), 0, limitCount); return true;} finally {RedisDistributeLockUtil.unlock (key);} return false;}

The above article based on Redis current limiter implementation (example explanation) is the editor to share with you all the content, I hope to give you a reference, but also hope that you support more.

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