Redis 源码研究之数据淘汰机制

本文主要介绍Redis的几种数据淘汰机制。

I、上帝视角

由于Redis是内存型数据库,其允许用户设置最大使用内存大小为maxmemory,在内存有限的情况下,为减少内存紧张的情况,当内存数据集大小上升至一定值时,就会实施数据淘汰机制。

Redis提供了以下几种数据淘汰策略:
1、 volatile-lru:从设置过期的数据集中淘汰最少使用的数据;
2、volatile-ttl:从设置过期的数据集中淘汰即将过期的数据(离过期时间最近);
3、volatile-random:从设置过期的数据集中随机选取数据淘汰;
4、allkeys-lru:从所有 数据集中选取使用最少的数据;
5、allkeys-random:从所有数据集中任意选取数据淘汰;
6、no-envicition:不进行淘汰;

II、LRU数据淘汰

1、redisServer中保存了lru计数器server.lrulock,会定时更新,这是根据server.unixtime计算出来的:

// redisServer 保存了lru 计数器
/*src/redis.h/redisServer*/
struct redisServer {
...
unsigned lruclock:22; /* Clock incrementing every minute, for LRU */
...
};  

2、LRU数据淘汰机制使这样的:从数据集中随机挑选几个键值对,取出其中lru最大的键值对淘汰。

III、TTL数据淘汰

1、TTL淘汰机制使从过期时间redisDB.expires表中随机挑选几个键值对,取出其中ttl最大的键值对淘汰。

IV、淘汰发生

1、Redis服务器没执行一个命令,都会检测内存,判断是否需要进行数据淘汰:

// 执行命令
/*src/redis.cprocessCommand*/
int processCommand(redisClient *c) {
        ......
        // 内存超额
        /* Handle the maxmemory directive.
        **
        First we try to free some memory if possible (if there are volatile
        * keys in the dataset). If there are not the only thing we can do
        * is returning an error. */
        if (server.maxmemory) {
                int retval = freeMemoryIfNeeded();
        if ((c->cmd->flags & REDIS_CMD_DENYOOM) && retval == REDIS_ERR) {
                flagTransaction(c);
                addReply(c, shared.oomerr);
                return REDIS_OK;
        }
    }
    ......
}  

2、这其中主要调用了freeMemoryIfNeeded函数,它完成了完整的数据淘汰机制:

int freeMemoryIfNeeded(void) {
    size_t mem_used, mem_tofree, mem_freed;
    int slaves = listLength(server.slaves);

    /* Remove the size of slaves output buffers and AOF buffer from the
     * count of used memory. */
    // 计算出 Redis 目前占用的内存总数,但有两个方面的内存不会计算在内:
    // 1)从服务器的输出缓冲区的内存
    // 2)AOF 缓冲区的内存
    mem_used = zmalloc_used_memory();
    if (slaves) {
        listIter li;
        listNode *ln;

        listRewind(server.slaves,&li);
        while((ln = listNext(&li))) {
            redisClient *slave = listNodeValue(ln);
            unsigned long obuf_bytes = getClientOutputBufferMemoryUsage(slave);
            if (obuf_bytes > mem_used)
                mem_used = 0;
            else
                mem_used -= obuf_bytes;
        }
    }
    if (server.aof_state != REDIS_AOF_OFF) {
        mem_used -= sdslen(server.aof_buf);
        mem_used -= aofRewriteBufferSize();
    }

    /* Check if we are over the memory limit. */
    // 如果目前使用的内存大小比设置的 maxmemory 要小,那么无须执行进一步操作
    if (mem_used <= server.maxmemory) return REDIS_OK;

    // 如果占用内存比 maxmemory 要大,但是 maxmemory 策略为不淘汰,那么直接返回
    if (server.maxmemory_policy == REDIS_MAXMEMORY_NO_EVICTION)
        return REDIS_ERR; /* We need to free memory, but policy forbids. */

    /* Compute how much memory we need to free. */
    // 计算需要释放多少字节的内存
    mem_tofree = mem_used - server.maxmemory;

    // 初始化已释放内存的字节数为 0
    mem_freed = 0;

    // 根据 maxmemory 策略,
    // 遍历字典,释放内存并记录被释放内存的字节数
    while (mem_freed < mem_tofree) {
        int j, k, keys_freed = 0;

        // 遍历所有字典
        for (j = 0; j < server.dbnum; j++) {
            long bestval = 0; /* just to prevent warning */
            sds bestkey = NULL;
            dictEntry *de;
            redisDb *db = server.db+j;
            dict *dict;

            if (server.maxmemory_policy == REDIS_MAXMEMORY_ALLKEYS_LRU ||
                server.maxmemory_policy == REDIS_MAXMEMORY_ALLKEYS_RANDOM)
            {
                // 如果策略是 allkeys-lru 或者 allkeys-random 
                // 那么淘汰的目标为所有数据库键
                dict = server.db[j].dict;
            } else {
                // 如果策略是 volatile-lru 、 volatile-random 或者 volatile-ttl 
                // 那么淘汰的目标为带过期时间的数据库键
                dict = server.db[j].expires;
            }

            // 跳过空字典
            if (dictSize(dict) == 0) continue;

            /* volatile-random and allkeys-random policy */
            // 如果使用的是随机策略,那么从目标字典中随机选出键
            if (server.maxmemory_policy == REDIS_MAXMEMORY_ALLKEYS_RANDOM ||
                server.maxmemory_policy == REDIS_MAXMEMORY_VOLATILE_RANDOM)
            {
                de = dictGetRandomKey(dict);
                bestkey = dictGetKey(de);
            }

            /* volatile-lru and allkeys-lru policy */
            // 如果使用的是 LRU 策略,
            // 那么从一集 sample 键中选出 IDLE 时间最长的那个键
            else if (server.maxmemory_policy == REDIS_MAXMEMORY_ALLKEYS_LRU ||
                server.maxmemory_policy == REDIS_MAXMEMORY_VOLATILE_LRU)
            {
                struct evictionPoolEntry *pool = db->eviction_pool;

                while(bestkey == NULL) {
                    //随机取一集键值对
                    evictionPoolPopulate(dict, db->dict, db->eviction_pool);
                    /* Go backward from best to worst element to evict. */
                    for (k = REDIS_EVICTION_POOL_SIZE-1; k >= 0; k--) {
                        if (pool[k].key == NULL) continue;
                        de = dictFind(dict,pool[k].key);

                        /* Remove the entry from the pool. */
                        sdsfree(pool[k].key);
                        /* Shift all elements on its right to left. */
                        memmove(pool+k,pool+k+1,
                            sizeof(pool[0])*(REDIS_EVICTION_POOL_SIZE-k-1));
                        /* Clear the element on the right which is empty
                         * since we shifted one position to the left.  */
                        pool[REDIS_EVICTION_POOL_SIZE-1].key = NULL;
                        pool[REDIS_EVICTION_POOL_SIZE-1].idle = 0;

                        /* If the key exists, is our pick. Otherwise it is
                         * a ghost and we need to try the next element. */
                        if (de) {
                            bestkey = dictGetKey(de);
                            break;
                        } else {
                            /* Ghost... */
                            continue;
                        }
                    }
                }
            }

            /* volatile-ttl */
            // 策略为 volatile-ttl ,从一集 sample 键中选出过期时间距离当前时间最接近的键
            else if (server.maxmemory_policy == REDIS_MAXMEMORY_VOLATILE_TTL) {
                for (k = 0; k < server.maxmemory_samples; k++) {
                    sds thiskey;
                    long thisval;

                    de = dictGetRandomKey(dict);
                    thiskey = dictGetKey(de);
                    thisval = (long) dictGetVal(de);

                    /* Expire sooner (minor expire unix timestamp) is better
                     * candidate for deletion */
                    if (bestkey == NULL || thisval < bestval) {
                        bestkey = thiskey;
                        bestval = thisval;
                    }
                }
            }

            /* Finally remove the selected key. */
            // 删除被选中的键
            if (bestkey) {
                long long delta;

                robj *keyobj = createStringObject(bestkey,sdslen(bestkey));
                propagateExpire(db,keyobj);
                /* We compute the amount of memory freed by dbDelete() alone.
                 * It is possible that actually the memory needed to propagate
                 * the DEL in AOF and replication link is greater than the one
                 * we are freeing removing the key, but we can't account for
                 * that otherwise we would never exit the loop.
                 *
                 * AOF and Output buffer memory will be freed eventually so
                 * we only care about memory used by the key space. */
                // 计算删除键所释放的内存数量
                delta = (long long) zmalloc_used_memory();
                dbDelete(db,keyobj);
                delta -= (long long) zmalloc_used_memory();
                mem_freed += delta;
                
                // 对淘汰键的计数器增一
                server.stat_evictedkeys++;

                notifyKeyspaceEvent(REDIS_NOTIFY_EVICTED, "evicted",
                    keyobj, db->id);
                decrRefCount(keyobj);
                keys_freed++;

                /* When the memory to free starts to be big enough, we may
                 * start spending so much time here that is impossible to
                 * deliver data to the slaves fast enough, so we force the
                 * transmission here inside the loop. */
                if (slaves) flushSlavesOutputBuffers();
            }
        }

        if (!keys_freed) return REDIS_ERR; /* nothing to free... */
    }

    return REDIS_OK;
}

【参考】
[1] 《Redis设计与实现》
[2] 《Redis源码日志》

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