Nicksxs's Blog

What hurts more, the pain of hard work or the pain of regret?



这一篇不再是数据结构介绍了,大致的数据结构基本都介绍了,这一篇主要是查漏补缺,或者说讲一些重要且基本的概念,也可能是经常被忽略的,很多讲 redis 的系列文章可能都会忽略,学习 redis 的时候也会,因为觉得源码学习就是讲主要的数据结构和“算法”学习了就好了。
redis 的主要应用就是拿来作为高性能的缓存,那么缓存一般有些啥需要注意的,首先是访问速度,如果取得跟数据库一样快,那就没什么存在的意义,第二个是缓存的字面意思,我只是为了让数据读取快一些,通常大部分的场景这个是需要更新过期的,这里就把我要讲的第一点引出来了(真累,


redis 是如何过期缓存的,可以猜测下,最无脑的就是每个设置了过期时间的 key 都设个定时器,过期了就删除,这种显然消耗太大,清理地最及时,还有的就是 redis 正在采用的懒汉清理策略和定期清理
懒汉策略就是在使用的时候去检查缓存是否过期,比如 get 操作时,先判断下这个 key 是否已经过期了,如果过期了就删掉,并且返回空,如果没过期则正常返回

/* This function is called when we are going to perform some operation
 * in a given key, but such key may be already logically expired even if
 * it still exists in the database. The main way this function is called
 * is via lookupKey*() family of functions.
 * The behavior of the function depends on the replication role of the
 * instance, because slave instances do not expire keys, they wait
 * for DELs from the master for consistency matters. However even
 * slaves will try to have a coherent return value for the function,
 * so that read commands executed in the slave side will be able to
 * behave like if the key is expired even if still present (because the
 * master has yet to propagate the DEL).
 * In masters as a side effect of finding a key which is expired, such
 * key will be evicted from the database. Also this may trigger the
 * propagation of a DEL/UNLINK command in AOF / replication stream.
 * The return value of the function is 0 if the key is still valid,
 * otherwise the function returns 1 if the key is expired. */
int expireIfNeeded(redisDb *db, robj *key) {
    if (!keyIsExpired(db,key)) return 0;

    /* If we are running in the context of a slave, instead of
     * evicting the expired key from the database, we return ASAP:
     * the slave key expiration is controlled by the master that will
     * send us synthesized DEL operations for expired keys.
     * Still we try to return the right information to the caller,
     * that is, 0 if we think the key should be still valid, 1 if
     * we think the key is expired at this time. */
    if (server.masterhost != NULL) return 1;

    /* Delete the key */
    return server.lazyfree_lazy_expire ? dbAsyncDelete(db,key) :

/* Check if the key is expired. */
int keyIsExpired(redisDb *db, robj *key) {
    mstime_t when = getExpire(db,key);
    mstime_t now;

    if (when < 0) return 0; /* No expire for this key */

    /* Don't expire anything while loading. It will be done later. */
    if (server.loading) return 0;

    /* If we are in the context of a Lua script, we pretend that time is
     * blocked to when the Lua script started. This way a key can expire
     * only the first time it is accessed and not in the middle of the
     * script execution, making propagation to slaves / AOF consistent.
     * See issue #1525 on Github for more information. */
    if (server.lua_caller) {
        now = server.lua_time_start;
    /* If we are in the middle of a command execution, we still want to use
     * a reference time that does not change: in that case we just use the
     * cached time, that we update before each call in the call() function.
     * This way we avoid that commands such as RPOPLPUSH or similar, that
     * may re-open the same key multiple times, can invalidate an already
     * open object in a next call, if the next call will see the key expired,
     * while the first did not. */
    else if (server.fixed_time_expire > 0) {
        now = server.mstime;
    /* For the other cases, we want to use the most fresh time we have. */
    else {
        now = mstime();

    /* The key expired if the current (virtual or real) time is greater
     * than the expire time of the key. */
    return now > when;
/* Return the expire time of the specified key, or -1 if no expire
 * is associated with this key (i.e. the key is non volatile) */
long long getExpire(redisDb *db, robj *key) {
    dictEntry *de;

    /* No expire? return ASAP */
    if (dictSize(db->expires) == 0 ||
       (de = dictFind(db->expires,key->ptr)) == NULL) return -1;

    /* The entry was found in the expire dict, this means it should also
     * be present in the main dict (safety check). */
    serverAssertWithInfo(NULL,key,dictFind(db->dict,key->ptr) != NULL);
    return dictGetSignedIntegerVal(de);

这里有几点要注意的,第一是当惰性删除时会根据lazyfree_lazy_expire这个参数去判断是执行同步删除还是异步删除,另外一点是对于 slave,是不需要执行的,因为会在 master 过期时向 slave 发送 del 指令。
光采用这个策略会有什么问题呢,假如一些key 一直未被访问,那这些 key 就不会过期了,导致一直被占用着内存,所以 redis 采取了懒汉式过期加定期过期策略,定期策略是怎么执行的呢

/* This function handles 'background' operations we are required to do
 * incrementally in Redis databases, such as active key expiring, resizing,
 * rehashing. */
void databasesCron(void) {
    /* Expire keys by random sampling. Not required for slaves
     * as master will synthesize DELs for us. */
    if (server.active_expire_enabled) {
        if (server.masterhost == NULL) {
        } else {

    /* Defrag keys gradually. */

    /* Perform hash tables rehashing if needed, but only if there are no
     * other processes saving the DB on disk. Otherwise rehashing is bad
     * as will cause a lot of copy-on-write of memory pages. */
    if (!hasActiveChildProcess()) {
        /* We use global counters so if we stop the computation at a given
         * DB we'll be able to start from the successive in the next
         * cron loop iteration. */
        static unsigned int resize_db = 0;
        static unsigned int rehash_db = 0;
        int dbs_per_call = CRON_DBS_PER_CALL;
        int j;

        /* Don't test more DBs than we have. */
        if (dbs_per_call > server.dbnum) dbs_per_call = server.dbnum;

        /* Resize */
        for (j = 0; j < dbs_per_call; j++) {
            tryResizeHashTables(resize_db % server.dbnum);

        /* Rehash */
        if (server.activerehashing) {
            for (j = 0; j < dbs_per_call; j++) {
                int work_done = incrementallyRehash(rehash_db);
                if (work_done) {
                    /* If the function did some work, stop here, we'll do
                     * more at the next cron loop. */
                } else {
                    /* If this db didn't need rehash, we'll try the next one. */
                    rehash_db %= server.dbnum;
/* Try to expire a few timed out keys. The algorithm used is adaptive and
 * will use few CPU cycles if there are few expiring keys, otherwise
 * it will get more aggressive to avoid that too much memory is used by
 * keys that can be removed from the keyspace.
 * Every expire cycle tests multiple databases: the next call will start
 * again from the next db, with the exception of exists for time limit: in that
 * case we restart again from the last database we were processing. Anyway
 * no more than CRON_DBS_PER_CALL databases are tested at every iteration.
 * The function can perform more or less work, depending on the "type"
 * argument. It can execute a "fast cycle" or a "slow cycle". The slow
 * cycle is the main way we collect expired cycles: this happens with
 * the "server.hz" frequency (usually 10 hertz).
 * However the slow cycle can exit for timeout, since it used too much time.
 * For this reason the function is also invoked to perform a fast cycle
 * at every event loop cycle, in the beforeSleep() function. The fast cycle
 * will try to perform less work, but will do it much more often.
 * The following are the details of the two expire cycles and their stop
 * conditions:
 * If type is ACTIVE_EXPIRE_CYCLE_FAST the function will try to run a
 * "fast" expire cycle that takes no longer than EXPIRE_FAST_CYCLE_DURATION
 * microseconds, and is not repeated again before the same amount of time.
 * The cycle will also refuse to run at all if the latest slow cycle did not
 * terminate because of a time limit condition.
 * If type is ACTIVE_EXPIRE_CYCLE_SLOW, that normal expire cycle is
 * executed, where the time limit is a percentage of the REDIS_HZ period
 * as specified by the ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC define. In the
 * fast cycle, the check of every database is interrupted once the number
 * of already expired keys in the database is estimated to be lower than
 * a given percentage, in order to avoid doing too much work to gain too
 * little memory.
 * The configured expire "effort" will modify the baseline parameters in
 * order to do more work in both the fast and slow expire cycles.

#define ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP 20 /* Keys for each DB loop. */
#define ACTIVE_EXPIRE_CYCLE_FAST_DURATION 1000 /* Microseconds. */
#define ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC 25 /* Max % of CPU to use. */
#define ACTIVE_EXPIRE_CYCLE_ACCEPTABLE_STALE 10 /* % of stale keys after which
                                                   we do extra efforts. */
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 +
    config_cycle_fast_duration = ACTIVE_EXPIRE_CYCLE_FAST_DURATION +
    config_cycle_slow_time_perc = ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC +
    config_cycle_acceptable_stale = ACTIVE_EXPIRE_CYCLE_ACCEPTABLE_STALE-

    /* 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)

        if (start < last_fast_cycle + (long long)config_cycle_fast_duration*2)

        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;

        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. */

        /* 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;
            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. */
                    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;
            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;
            /* We don't repeat the cycle for the current database if there are
             * an acceptable amount of stale keys (logically expired but yet
             * not reclained). */
        } while ((expired*100/sampled) > config_cycle_acceptable_stale);

    elapsed = ustime()-start;
    server.stat_expire_cycle_time_used += elapsed;

    /* 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)+

执行定期清除分成两种类型,快和慢,分别由beforeSleepdatabasesCron调用,快版有两个限制,一个是执行时长由ACTIVE_EXPIRE_CYCLE_FAST_DURATION限制,另一个是执行间隔是 2 倍的ACTIVE_EXPIRE_CYCLE_FAST_DURATION,另外这还可以由配置的server.active_expire_effort参数来控制,默认是 1,最大是 10

onfig_cycle_fast_duration = ACTIVE_EXPIRE_CYCLE_FAST_DURATION +

然后会从一定数量的 db 中找出一定数量的带过期时间的 key(保存在 expires中),这里的数量是由

config_keys_per_loop = ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP +
config_cycle_slow_time_perc = ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC +
timelimit = config_cycle_slow_time_perc*1000000/server.hz/100;

这里还有一个额外的退出条件,如果当前数据库的抽样结果已经达到我们所允许的过期 key 百分比,则下次不再处理当前 db,继续处理下个 db