redis代码数据超时实现

redis的超时处理
1） 当再次访问该数据时， 发现该数据已超时过期， 则删掉； 返回给调用者为空。（被动发现）
2） redis server起来之后， 会注册定时器事件(每毫秒触发1次超时)， 在该定时器处理函数中， 轮流各db；大致策略是从该db.expired dict中：
-----a. 尝试取20(ACTIVE_EXPIRE_CYCLE_LOOKUPS_PER_LOOP)次随机key，判断是否有过期的，过期的处理掉。 如果该db中过期的不足5个(ACTIVE_EXPIRE_CYCLE_LOOKUPS_PER_LOOP/4)，则不再处理该db、转而处理下一个db。
-----b. 执行a 16的整数倍次。如果此时发现本次处理时间已太长（>25ms）， 则不再处理。否则继续a  16次。typedef struct redisDb {dict *dict;                 /* The keyspace for this DB */dict *expires;              /* Timeout of keys with a timeout set */如果数据设置了超时，则dict和expires中都会放一份。dict *blocking_keys;        /* Keys with clients waiting for data (BLPOP) */dict *ready_keys;           /* Blocked keys that received a PUSH */dict *watched_keys;         /* WATCHED keys for MULTI/EXEC CAS */int id;long long avg_ttl;          /* Average TTL, just for stats */数据近似平均过期时间
} redisDb;struct redisServer {/* General */char *configfile;           /* Absolute config file path, or NULL */int hz;                     /* serverCron() calls frequency in hertz */redisDb *db;dict *commands;             /* Command table */dict *orig_commands;        /* Command table before command renaming. */aeEventLoop *el; unsigned lruclock:22;       /* Clock incrementing every minute, for LRU */分钟级别的超时设置。unsigned lruclock_padding:10;int shutdown_asap;          /* SHUTDOWN needed ASAP */....
};#define REDIS_LRU_CLOCK_MAX ((1<<21)-1) /* Max value of obj->lru */
#define REDIS_LRU_CLOCK_RESOLUTION 10 /* LRU clock resolution in seconds */
typedef struct redisObject {unsigned type:4;unsigned notused:2;     /* Not used */unsigned encoding:4;unsigned lru:22;        /* lru time (relative to server.lruclock) */ lru = server.lruclockint refcount;void *ptr;
} robj;每次访问该key时，即更新该key对应的value的最近访问时间为server.lruclock。 db.c:lookupKey()。
在读或者写时， 都会调用lookupKey更新。int expireIfNeeded(redisDb *db, robj *key) {mstime_t when = getExpire(db,key);//得到设置的截止超时时间。 绝对时间。未设置超时则为-1。....不符合超时条件，退出； 底下会处理超时。/* Delete the key */server.stat_expiredkeys++;propagateExpire(db,key);//将本次数据超时信息传递给slave、写AOFnotifyKeyspaceEvent(REDIS_NOTIFY_EXPIRED, "expired",key,db->id);//将本次超时信息广播给相关订阅者。？return dbDelete(db,key);//从db.expires和db.dict中删除掉。
}robj *lookupKey(redisDb *db, robj *key) {dictEntry *de = dictFind(db->dict,key->ptr);if (de) {robj *val = dictGetVal(de);/* Update the access time for the ageing algorithm.* Don't do it if we have a saving child, as this will trigger* a copy on write madness. */if (server.rdb_child_pid == -1 && server.aof_child_pid == -1)val->lru = server.lruclock;return val;} else {return NULL;}
}
robj *lookupKeyRead(redisDb *db, robj *key) {robj *val;expireIfNeeded(db,key);  //判断该key是否超时、超时就都淘汰--->底下的读就会失败、因为已经被淘汰了。val = lookupKey(db,key); //if (val == NULL)server.stat_keyspace_misses++;elseserver.stat_keyspace_hits++;return val;
}redis.c:initServer中，增加定时器事件执行serverCron函数：
1)  该函数更新server.lruclock = (server.unixtime/REDIS_LRU_CLOCK_RESOLUTION) & REDIS_LRU_CLOCK_MAX;//server.unixtime =是通过time(NULL)得到的。
即server.lruclock 是当前时间/10 后结果的低21位。
2)  执行databasesCron。该函数负责处理key的超时、rehash、resize。 其中key超时函数activeExpireCyclevoid activeExpireCycle(int type) {/* This function has some global state in order to continue the work* incrementally across calls. */static unsigned int current_db = 0; /* Last DB tested. */从上次访问的db的下一个db接着开始处理static int timelimit_exit = 0;      /* Time limit hit in previous call? */static long long last_fast_cycle = 0; /* When last fast cycle ran. */unsigned int j, iteration = 0;unsigned int dbs_per_call = REDIS_DBCRON_DBS_PER_CALL;long long start = ustime(), timelimit;if (type == ACTIVE_EXPIRE_CYCLE_FAST) {/* Don't start a fast cycle if the previous cycle did not exited* for time limt. Also don't repeat a fast cycle for the same period* as the fast cycle total duration itself. */

        //该变量为静态变量。上次函数未退出时， timelimit_exit为0； 1则退出。//由于本函数是由定时器事件触发，所以某些情况下可能有多个本函数在执行。

        if (!timelimit_exit) return;
if (start < last_fast_cycle + ACTIVE_EXPIRE_CYCLE_FAST_DURATION*2) return;
last_fast_cycle = start;
}

/* We usually should test REDIS_DBCRON_DBS_PER_CALL per iteration, with
* two exceptions:
*
* 1) Don't test more DBs than we have.
* 2) If last time we hit the time limit, we want to scan all DBs
* in this iteration, as there is work to do in some DB and we don't want
* expired keys to use memory for too much time. */
if (dbs_per_call > server.dbnum || timelimit_exit)
dbs_per_call = server.dbnum;

/* We can use at max ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC percentage of CPU time
* per iteration. Since this function gets called with a frequency of
* server.hz times per second, the following is the max amount of
* microseconds we can spend in this function. */
//ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC 25.
//server.hz default值是 10. 那么timelimit约为25000. （与ustime比， 那么就是25ms）
timelimit = 1000000*ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC/server.hz/100;//

    timelimit_exit = 0;    if (timelimit <= 0) timelimit = 1;    if (type == ACTIVE_EXPIRE_CYCLE_FAST)        timelimit = ACTIVE_EXPIRE_CYCLE_FAST_DURATION; /*1000 in microseconds. */    for (j = 0; j < dbs_per_call; j++) {//dbs_per_call数据库个数。        int expired;        redisDb *db = server.db+(current_db % server.dbnum);//逐个db轮流处理。 每个db只处理        /* Increment the DB now so we are sure if we run out of time         * in the current DB we'll restart from the next. This allows to         * distribute the time evenly across DBs. */        current_db++;        /* Continue to expire if at the end of the cycle more than 25%         * of the keys were expired. */        do {            unsigned long num, slots;            long long now, ttl_sum;            int ttl_samples;            /* If there is nothing to expire try next DB ASAP. */            if ((num = dictSize(db->expires)) == 0) {                db->avg_ttl = 0;                break;            }            slots = dictSlots(db->expires);            now = mstime();            /* When there are less than 1% filled slots getting random             * keys is expensive, so stop here waiting for better times...             * The dictionary will be resized asap. */            if (num && slots > DICT_HT_INITIAL_SIZE &&                (num*100/slots < 1)) break;            /* The main collection cycle. Sample random keys among keys             * with an expire set, checking for expired ones. */            expired = 0;            ttl_sum = 0;            ttl_samples = 0;            if (num > ACTIVE_EXPIRE_CYCLE_LOOKUPS_PER_LOOP)                num = ACTIVE_EXPIRE_CYCLE_LOOKUPS_PER_LOOP;//20。。。。            while (num--) {                dictEntry *de;                long long ttl;                if ((de = dictGetRandomKey(db->expires)) == NULL) break;//取db->expires的随机桶的首元素                ttl = dictGetSignedIntegerVal(de)-now;                if (activeExpireCycleTryExpire(db,de,now)) expired++;//如果已经超时，则从db删掉、增加server.stat_expiredkeys                if (ttl < 0) ttl = 0;                ttl_sum += ttl;                ttl_samples++;            }            /* Update the average TTL stats for this database. */            if (ttl_samples) {                long long avg_ttl = ttl_sum/ttl_samples;                if (db->avg_ttl == 0) db->avg_ttl = avg_ttl;                /* Smooth the value averaging with the previous one. */                db->avg_ttl = (db->avg_ttl+avg_ttl)/2;            }            /* We can't block forever here even if there are many keys to             * expire. So after a given amount of milliseconds return to the             * caller waiting for the other active expire cycle. */            iteration++;            if ((iteration & 0xf) == 0 && /* check once every 16 iterations. */                (ustime()-start) > timelimit)            {                timelimit_exit = 1;            }            if (timelimit_exit) return;            /* We don't repeat the cycle if there are less than 25% of keys             * found expired in the current DB. */        } while (expired > ACTIVE_EXPIRE_CYCLE_LOOKUPS_PER_LOOP/4);    }//end for(int i=.., i < dbnum...)}

redis代码数据超时实现相关推荐

redis lettuce 超时_Spring Cache 操作 Redis 实现数据缓存（上）
点击上方☝SpringForAll社区轻松关注!及时获取有趣有料的技术文章本文来源:http://www.mydlq.club/article/55/ . 一.缓存概念知识 . 1.是什么缓存 . ...
Spring整合Redis做数据缓存（Windows环境）
当我们一个项目的数据量很大的时候,就需要做一些缓存机制来减轻数据库的压力,提升应用程序的性能,对于java项目来说,最常用的缓存组件有Redis.Ehcache和Memcached. Ehcache是 ...
spring boot 缓存_Spring Boot 集成 Redis 实现数据缓存
Spring Boot 集成 Redis 实现数据缓存,只要添加一些注解方法,就可以动态的去操作缓存了,减少代码的操作. 在这个例子中我使用的是 Redis,其实缓存类型还有很多,例如 Ecache. ...
oracle缓存和Redis,说说数据缓存那点事：Redis和memcached对比
[此为"一森咖记"公众号--第86篇文章] 本文预计阅读15分钟 [引言] 当我们为一个并发量较大的应用做数据架构时,会考虑使用缓存,意欲达到三个目标: 1. 加快用户访问速度,提 ...
SpringBoot+Redis完成数据缓存（内容丰富度一定超出你的想象）
SpringBoot+Redis完成数据缓存去年今日此门中人面桃花相映红人面不知何处去桃花依旧笑春风感谢相遇!感谢自己,努力的样子很给力! 为了更多朋友看见,还是和大家说一声抱歉,限制为粉丝 ...
SpringBoot 结合 Spring Cache 操作 Redis 实现数据缓存
点击上方"后端技术精选",选择"置顶公众号" 技术文章第一时间送达! 作者:超级小豆丁 http://www.mydlq.club/article/55/ 系统 ...
Springboot：整合redis对接口数据进行缓存
文章目录 Springboot:整合redis对接口数据进行缓存一.注解及其属性介绍 @Cacheable @CacheEvict @CachePut @CacheConfig 二.代码实现 1.创 ...
spring + redis 实现数据的缓存
1.实现目标通过redis缓存数据.(目的不是加快查询的速度,而是减少数据库的负担) 2.所需jar包注意:jdies和commons-pool两个jar的版本是有对应关系的,注意引入jar包是要 ...
基于 abp vNext 和 .NET Core 开发博客项目 - 使用Redis缓存数据
基于 abp vNext 和 .NET Core 开发博客项目 - 使用Redis缓存数据转载于:https://github.com/Meowv/Blog 在日志记录中使用的静态方法有人指出写法不 ...

redis代码数据超时实现

redis代码数据超时实现相关推荐

最新文章

热门文章

redis代码 数据超时实现

redis代码 数据超时实现相关推荐

最新文章

热门文章

redis代码数据超时实现

redis代码数据超时实现相关推荐