一、前言
redis最近经常作为临时缓存使用，能够减少对磁盘IO的操作次数，提高程序的执行效率，但是为了避免但是存储的数据要进行回收，可以通过程序代码删除无用数据，也可以通过设置数据的有效时间，降低了代码开发量，数据的回收交给第三方组件，为了更方便的使用redis的过期功能，我们了解一下redis的数据过期机制。
二、分析
EXPIRE命令可以为指定键设置过期时间，到达过期时间后，这些键会被自动删除，可以通过expireGenericCommand函数为键设置生存时间，该函数会调用setExpire函数，将键、过期时间戳添加到数据库的过期字典redisDb.expires中。
/*-----------------------------------------------------------------------------
* Expires Commands
*----------------------------------------------------------------------------*/
/* This is the generic command implementation for EXPIRE, PEXPIRE, EXPIREAT
* and PEXPIREAT. Because the command second argument may be relative or absolute
* the "basetime" argument is used to signal what the base time is (either 0
* for *AT variants of the command, or the current time for relative expires).
*
* unit is either UNIT_SECONDS or UNIT_MILLISECONDS, and is only used for
* the argv[2] parameter. The basetime is always specified in milliseconds. */
void expireGenericCommand(client *c, long long basetime, int unit) {
robj *key = c->argv[1], *param = c->argv[2];
long long when; /* unix time in milliseconds when the key will expire. */
if (getLongLongFromObjectOrReply(c, param, &when, NULL) != C_OK)
return;
if (unit == UNIT_SECONDS) when *= 1000;
when += basetime;
/* No key, return zero. */
if (lookupKeyWrite(c->db,key) == NULL) {
addReply(c,shared.czero);
return;
}
if (checkAlreadyExpired(when)) {
robj *aux;
int deleted = server.lazyfree_lazy_expire ? dbAsyncDelete(c->db,key) :
dbSyncDelete(c->db,key);
serverAssertWithInfo(c,key,deleted);
server.dirty++;
/* Replicate/AOF this as an explicit DEL or UNLINK. */
aux = server.lazyfree_lazy_expire ? shared.unlink : shared.del;
rewriteClientCommandVector(c,2,aux,key);
signalModifiedKey(c,c->db,key);
notifyKeyspaceEvent(NOTIFY_GENERIC,"del",key,c->db->id);
addReply(c, shared.cone);
return;
} else {
setExpire(c,c->db,key,when);
addReply(c,shared.cone);
signalModifiedKey(c,c->db,key);
notifyKeyspaceEvent(NOTIFY_GENERIC,"expire",key,c->db->id);
server.dirty++;
return;
}
}
setExpire函数
/* Set an expire to the specified key. If the expire is set in the context
* of an user calling a command 'c' is the client, otherwise 'c' is set
* to NULL. The 'when' parameter is the absolute unix time in milliseconds
* after which the key will no longer be considered valid. */
void setExpire(client *c, redisDb *db, robj *key, long long when) {
dictEntry *kde, *de;
/* Reuse the sds from the main dict in the expire dict */
kde = dictFind(db->dict,key->ptr);
serverAssertWithInfo(NULL,key,kde != NULL);
de = dictAddOrFind(db->expires,dictGetKey(kde));
dictSetSignedIntegerVal(de,when);
int writable_slave = server.masterhost && server.repl_slave_ro == 0;
if (c && writable_slave && !(c->flags & CLIENT_MASTER))
rememberSlaveKeyWithExpire(db,key);
}
redis使用两种机制来删除过期键，分别是定时删除和惰性删除。
三、定时删除
serverCron函数会定时触发expire.c/activeExpireCycle函数，该函数会清除数据库中的过期数据直到数据库过期数据比例达到指定比例；
void activeExpireCycle(int type) {
/* Adjust the running parameters according to the configured expire
* effort. The default effort is 1, and the maximum configurable effort
* is 10. */
unsigned long
effort = server.active_expire_effort-1, /* Rescale from 0 to 9. */
config_keys_per_loop = ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP +
ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP/4*effort,
config_cycle_fast_duration = ACTIVE_EXPIRE_CYCLE_FAST_DURATION +
ACTIVE_EXPIRE_CYCLE_FAST_DURATION/4*effort,
config_cycle_slow_time_perc = ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC +
2*effort,
config_cycle_acceptable_stale = ACTIVE_EXPIRE_CYCLE_ACCEPTABLE_STALE-
effort;
/* This function has some global state in order to continue the work
* incrementally across calls. */
static unsigned int current_db = 0; /* Last DB tested. */
static int timelimit_exit = 0; /* Time limit hit in previous call? */
static long long last_fast_cycle = 0; /* When last fast cycle ran. */
int j, iteration = 0;
int dbs_per_call = CRON_DBS_PER_CALL;
long long start = ustime(), timelimit, elapsed;
/* When clients are paused the dataset should be static not just from the
* POV of clients not being able to write, but also from the POV of
* expires and evictions of keys not being performed. */
if (clientsArePaused()) return;
if (type == ACTIVE_EXPIRE_CYCLE_FAST) {
/* Don't start a fast cycle if the previous cycle did not exit
* for time limit, unless the percentage of estimated stale keys is
* too high. Also never repeat a fast cycle for the same period
* as the fast cycle total duration itself. */
if (!timelimit_exit &&
server.stat_expired_stale_perc < config_cycle_acceptable_stale)
return;
if (start < last_fast_cycle + (long long)config_cycle_fast_duration*2)
return;
last_fast_cycle = start;
}
/* We usually should test CRON_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 'config_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. */
timelimit = config_cycle_slow_time_perc*1000000/server.hz/100;
timelimit_exit = 0;
if (timelimit <= 0) timelimit = 1;
if (type == ACTIVE_EXPIRE_CYCLE_FAST)
timelimit = config_cycle_fast_duration; /* in microseconds. */
/* Accumulate some global stats as we expire keys, to have some idea
* about the number of keys that are already logically expired, but still
* existing inside the database. */
long total_sampled = 0;
long total_expired = 0;
for (j = 0; j < dbs_per_call && timelimit_exit == 0; j++) {
/* Expired and checked in a single loop. */
unsigned long expired, sampled;
redisDb *db = server.db+(current_db % server.dbnum);
/* 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 there are still
* a big percentage of keys to expire, compared to the number of keys
* we scanned. The percentage, stored in config_cycle_acceptable_stale
* is not fixed, but depends on the Redis configured "expire effort". */
do {
unsigned long num, slots;
long long now, ttl_sum;
int ttl_samples;
iteration++;
/* 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, sampling the key
* space 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;
sampled = 0;
ttl_sum = 0;
ttl_samples = 0;
if (num > config_keys_per_loop)
num = config_keys_per_loop;
/* Here we access the low level representation of the hash table
* for speed concerns: this makes this code coupled with dict.c,
* but it hardly changed in ten years.
*
* Note that certain places of the hash table may be empty,
* so we want also a stop condition about the number of
* buckets that we scanned. However scanning for free buckets
* is very fast: we are in the cache line scanning a sequential
* array of NULL pointers, so we can scan a lot more buckets
* than keys in the same time. */
long max_buckets = num*20;
long checked_buckets = 0;
while (sampled < num && checked_buckets < max_buckets) {
for (int table = 0; table < 2; table++) {
if (table == 1 && !dictIsRehashing(db->expires)) break;
unsigned long idx = db->expires_cursor;
idx &= db->expires->ht[table].sizemask;
dictEntry *de = db->expires->ht[table].table[idx];
long long ttl;
/* Scan the current bucket of the current table. */
checked_buckets++;
while(de) {
/* Get the next entry now since this entry may get
* deleted. */
dictEntry *e = de;
de = de->next;
ttl = dictGetSignedIntegerVal(e)-now;
if (activeExpireCycleTryExpire(db,e,now)) expired++;
if (ttl > 0) {
/* We want the average TTL of keys yet
* not expired. */
ttl_sum += ttl;
ttl_samples++;
}
sampled++;
}
}
db->expires_cursor++;
}
total_expired += expired;
total_sampled += sampled;
/* Update the average TTL stats for this database. */
if (ttl_samples) {
long long avg_ttl = ttl_sum/ttl_samples;
/* Do a simple running average with a few samples.
* We just use the current estimate with a weight of 2%
* and the previous estimate with a weight of 98%. */
if (db->avg_ttl == 0) db->avg_ttl = avg_ttl;
db->avg_ttl = (db->avg_ttl/50)*49 + (avg_ttl/50);
}
/* 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. */
if ((iteration & 0xf) == 0) {
/* check once every 16 iterations. */
elapsed = ustime()-start;
if (elapsed > timelimit) {
timelimit_exit = 1;
server.stat_expired_time_cap_reached_count++;
break;
}
}
/* We don't repeat the cycle for the current database if there are
* an acceptable amount of stale keys (logically expired but yet
* not reclaimed). */
} while (sampled == 0 ||
(expired*100/sampled) > config_cycle_acceptable_stale);
}
elapsed = ustime()-start;
server.stat_expire_cycle_time_used += elapsed;
latencyAddSampleIfNeeded("expire-cycle",elapsed/1000);
/* Update our estimate of keys existing but yet to be expired.
* Running average with this sample accounting for 5%. */
double current_perc;
if (total_sampled) {
current_perc = (double)total_expired/total_sampled;
} else
current_perc = 0;
server.stat_expired_stale_perc = (current_perc*0.05)+
(server.stat_expired_stale_perc*0.95);
}
参数说明
type：指定activeExpireCycle函数的执行模式，取值为ACTIVE_EXPIRE_CYCLE_FAST或者ACTIVE_EXPIRE_CYCLE_SLOW。
为了避免该函数阻塞主进程，redis需要控制该函数的执行时间。这里计算几个阈值变量，用于后面控制函数的执行时间。
timelimit:activeExpireCycle函数执行的最长时间，该值的计算与函数的执行模式、server.hz、active-expire-effort相关。
cinfig_keys_per_loop:每次采样删除操作中采集键的最大数量，默认为20.
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config_cycle_acceptable_stable:每次采集后，如果当前已过期键所占比例低于阈值，则不再处理该数据库，默认为10。
active-expire-effort配置控制activeExpireCycle函数的执行时间、占用CPU时间，以及最终的数据库中已过期键的比例。
四、惰性删除
惰性删除很简单，当用户查询键时，检测是否过期，如果该键已过期，则删除该键。该操作由expireIfNeeded函数完成。
不管是定时删除还是惰性删除，删除数据后，还需要生成删除命令并传播到AOF和从节点。
数据淘汰机制
当内存不够时，redis可以主动删除一些数据，以保证redis服务正常运行。该机制即数据淘汰（逐出）机制。
redis支持一下数据淘汰策略：
allkeys-lru/volatile-lru:在数据库字典/过期字典中挑选最近最少使用的数据淘汰。
allkeys-lfu/volatile-lfu：在数据库字典/过期字典中挑选最不经常使用的数据淘汰。
allkey-random/volatile-random：在字典库字典/过期字典中随机挑选数据淘汰。
volatile-ttl：在过期字典中淘汰最快过期的数据。
noeviction：不淘汰任何数据，内存不足时执行写命令会返回错误。默认的内存淘汰算法。
LRU和LFU是常用的缓存淘汰算法。
LRU：醉酒没有访问的数据最先被淘汰；
LFU：最小频率访问的数据最先被淘汰；
redis使用的是LRU近似算法，从数据中获取部分随机数据作为样本数据，并将样本数据中最适合的数据淘汰。
为了实现LRU/LFU近似算法，redis使用redisObject.lru记录键的最新访问时间或键的访问频率。
db.c/lookupKey函数负责从数据库中查找键，每次查找键都会更新redisObject.lru数据：
/* Low level key lookup API, not actually called directly from commands
* implementations that should instead rely on lookupKeyRead(),
* lookupKeyWrite() and lookupKeyReadWithFlags(). */
robj *lookupKey(redisDb *db, robj *key, int flags) {
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 (!hasActiveChildProcess() && !(flags & LOOKUP_NOTOUCH)){
if (server.maxmemory_policy & MAXMEMORY_FLAG_LFU) {
updateLFU(val);
} else {
val->lru = LRU_CLOCK();
}
}
return val;
} else {
return NULL;
}
}
五、总结
分析源码是最有效的理解方式