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关于redis:为什么LRU算法原理和代码实现不一样

(1) Redis 里缓存有哪些淘汰策略

内存淘汰策略 解释 备注
noeviction 不进行数据淘汰
allkeys-random 在所有 key 里随机筛选数据
allkeys-lru 在所有 key 里筛选最近最久未应用的数据
allkeys-lfu 在所有 key 里筛选最近起码应用的数据 Redis 4.0 新增
volatile-ttl 在有过期工夫 key 里依据过期工夫的先后筛选
volatile-random 在有过期工夫 key 里随机筛选数据
volatile-lru 在有过期工夫 key 里筛选最近最久未应用的数据
volatile-lfu 在有过期工夫 key 里筛选最近起码应用的数据 Redis 4.0 新增

lru (Least Recently Used) 最近最久未应用
lfu (Least Frequently Used) 最近起码应用

在 redis3.0 之前,默认淘汰策略是volatile-lru;在 redis3.0 及之后(包含 3.0),默认淘汰策略是noeviction

在 3.0 及之后的版本,Redis 在应用的内存空间超过 maxmemory 值时,并不会淘汰数据。

对应到 Redis 缓存,也就是指,一旦缓存被写满了,再有写申请来时,Redis 不再提供服务,而是间接返回谬误。

(1.1) Redis 内存淘汰机制如何启用

Redis 的内存淘汰机制是如何启用近似 LRU 算法的

和 Redis 配置文件 redis.conf 中的两个配置参数无关:

maxmemory,该配置项设定了 Redis server 能够应用的最大内存容量,一旦 server 应用的理论内存量超出该阈值时,server 就会依据 maxmemory-policy 配置项定义的策略,执行内存淘汰操作;

maxmemory-policy,该配置项设定了 Redis server 的内存淘汰策略,次要包含近似 LRU 算法、LFU 算法、按 TTL 值淘汰和随机淘汰等几种算法。

(2) 缓存淘汰算法 / 页面置换算法原理

(2.1) LRU

LRU 算法背地的想法十分奢侈:它认为刚刚被拜访的数据,必定还会被再次拜访。
抉择最近最久未被应用的数据进行淘汰。

长处:
简略、高效
有余:
可能造成缓存净化。

缓存净化:在一些场景下,有些数据被拜访的次数非常少,甚至只会被拜访一次。当这些数据服务完拜访申请后,如果还持续留存在缓存中的话,就只会白白占用缓存空间。

典型场景:全表扫描,对所有数据进行一次读取,每个数据都被读取到了,

(2.2) LFU

记录数据被拜访的频率,抉择在最近应用起码的数据进行淘汰。

(3) Redis 里缓存淘汰算法实现

(3.1) Redis-LRU

LRU 算法在理论实现时,须要用链表治理所有的缓存数据,这会带来额定的空间开销。

而且,当有数据被拜访时,须要在链表上把该数据挪动到 MRU 端,如果有大量数据被拜访,就会带来很多链表挪动操作,会很耗时,进而会升高 Redis 性能。

在 Redis 中,LRU 算法被做了简化,以加重数据淘汰对缓存性能的影响。

Redis 并没有为所有的数据保护一个全局的链表,而是通过随机采样形式,选取肯定数量(例如 100 个)的数据放入候选汇合,后续在候选汇合中依据 lru 字段值的大小进行筛选。

(3.2) Redis-LFU

LFU 缓存策略是在 LRU 策略根底上,为每个数据减少了一个计数器,来统计这个数据的拜访次数。

当应用 LFU 策略筛选淘汰数据时,首先会依据数据的拜访次数进行筛选,把拜访次数最低的数据淘汰出缓存。
如果两个数据的拜访次数雷同,LFU 策略再比拟这两个数据的拜访时效性,把间隔上一次拜访工夫更久的数据淘汰出缓存。

Redis 在实现 LFU 策略的时候,只是把原来 24bit 大小的 lru 字段,又进一步拆分成了两局部。
ldt 值:lru 字段的前 16bit,示意数据的拜访工夫戳;
counter 值:lru 字段的后 8bit,示意数据的拜访次数。

在实现 LFU 策略时,Redis 并没有采纳数据每被拜访一次,就给对应的 counter 值加 1 的计数规定,而是采纳了一个更优化的计数规定。

LFU 策略实现的计数规定是:每当数据被拜访一次时,首先,用计数器以后的值乘以配置项 lfu_log_factor 再加 1,再取其倒数,失去一个 p 值;而后,把这个 p 值和一个取值范畴在(0,1)间的随机数 r 值比大小,只有 p 值大于 r 值时,计数器才加 1。

double r = (double)rand()/RAND_MAX;
...
double p = 1.0/(baseval*server.lfu_log_factor+1);
if (r < p) counter++;   

(4) 源码解读

(4.1) 全局 LRU 时钟值的计算

LRU 算法须要晓得数据的最近一次拜访工夫。因而,Redis 设计了 LRU 时钟来记录数据每次拜访的工夫戳。

// file: src/server.h 

/*
 * redis 对象
 */
typedef struct redisObject {
    unsigned type:4;  // 数据类型(string/list/hash/set/zset 等)unsigned encoding:4;  // 编码方式 
    unsigned lru:LRU_BITS;  // LRU 工夫(绝对于全局 lru_clock) 
                            // 或 LFU 数据(低 8 位保留频率 和 高 16 位保留拜访工夫)。// LRU_BITS 为 24 个 bits
    int refcount;  // 援用计数  4 字节
    void *ptr;  // 指针 指向对象的值  8 字节
} robj;
// file: src/server.c

void initServerConfig(void) {

    // 计算全局 LRU 时钟值
    server.lruclock = getLRUClock();}
// file: src/evict.c

/* 
 * 依据时钟分辨率返回 LRU 时钟。* 这是一个缩小位格局的工夫,可用于设置和查看 redisObject 构造的 object->lru 字段。*/
unsigned int getLRUClock(void) {// mstime()是毫秒工夫戳  // mstime()/1000= 秒级工夫戳
    // 与运算 保障值 <= LRU_CLOCK_MAX
    return (mstime()/LRU_CLOCK_RESOLUTION) & LRU_CLOCK_MAX;
}

从代码能够看出,LRU 时钟精度是 1000 毫秒,也就是 1 秒。

#define LRU_BITS 24

// obj->lru 的最大值 // LRU_CLOCK_MAX = 1^24 - 1
#define LRU_CLOCK_MAX ((1<<LRU_BITS)-1) /* Max value of obj->lru */

// LRU 时钟分辨率(毫秒)
#define LRU_CLOCK_RESOLUTION 1000 /* LRU clock resolution in ms */
// file: src/server.c

/* 
 * 返回 UNIX 毫秒工夫戳
 * Return the UNIX time in milliseconds 
 */
mstime_t mstime(void) {return ustime()/1000;
}
// file: src/server.c

/*
 * 返回 UNIX 微秒工夫戳 
 * Return the UNIX time in microseconds 
 */
long long ustime(void) {
    struct timeval tv;
    long long ust;

    gettimeofday(&tv, NULL);
    ust = ((long long)tv.tv_sec)*1000000;
    ust += tv.tv_usec;
    return ust;
}

(4.2) 在运行过程中 LRU 时钟值是如何更新的

和 Redis server 在事件驱动框架中,定期运行的工夫事件所对应的 serverCron 函数无关。

serverCron 函数作为工夫事件的回调函数,自身会依照肯定的频率周期性执行,其频率值是由 Redis 配置文件 redis.conf 中的 hz 配置项决定的。

hz 配置项的默认值是 10,这示意 serverCron 函数会每 100 毫秒 (1 秒 / 10 = 100 毫秒) 运行一次。

// file: src/server.c

/* This is our timer interrupt, called server.hz times per second.
 * Here is where we do a number of things that need to be done asynchronously.
 * For instance:
 *
 * - Active expired keys collection (it is also performed in a lazy way on
 *   lookup).
 * - Software watchdog.
 * - Update some statistic.
 * - Incremental rehashing of the DBs hash tables.
 * - Triggering BGSAVE / AOF rewrite, and handling of terminated children.
 * - Clients timeout of different kinds.
 * - Replication reconnection.
 * - Many more...
 *
 * Everything directly called here will be called server.hz times per second,
 * so in order to throttle execution of things we want to do less frequently
 * a macro is used: run_with_period(milliseconds) {....}
 */

int serverCron(struct aeEventLoop *eventLoop, long long id, void *clientData) {

    /* We have just LRU_BITS bits per object for LRU information.
     * So we use an (eventually wrapping) LRU clock.
     *
     * Note that even if the counter wraps it's not a big problem,
     * everything will still work but some object will appear younger
     * to Redis. However for this to happen a given object should never be
     * touched for all the time needed to the counter to wrap, which is
     * not likely.
     *
     * Note that you can change the resolution altering the
     * LRU_CLOCK_RESOLUTION define. */
    // 默认状况下,每 100 毫秒调用 getLRUClock 函数更新一次全局 LRU 时钟值 
    server.lruclock = getLRUClock();}

这样一来,每个键值对就能够从全局 LRU 时钟获取最新的拜访工夫戳了。

(4.3) key-value-LRU 时钟值的初始化与更新

(4.3.1) key-LRU 时钟初始化

对于 key-value 来说,它的 LRU 时钟值最后是在这个键值对被创立的时候,进行初始化设置的,这个初始化操作是在 createObject 函数中调用的。

// file: src/object.c

/*
 * 创立一个 redisObject 对象
 *
 * @param type redisObject 的类型
 * @param *ptr 值的指针
 */
robj *createObject(int type, void *ptr) {
    // 为 redisObject 构造体分配内存空间
    robj *o = zmalloc(sizeof(*o));
  
    // 省略局部代码 

    // 将 lru 字段设置为以后的 lruclock(分钟分辨率),或者 LFU 计数器。// 判断内存过期策略
    if (server.maxmemory_policy & MAXMEMORY_FLAG_LFU) {
        // 对应 lfu 
        // LFU_INIT_VAL=5 对应二进制是 0101 
        // 或运算 
        o->lru = (LFUGetTimeInMinutes()<<8) | LFU_INIT_VAL;
    } else {
        // 对应 lru 
        o->lru = LRU_CLOCK();}
    return o;
}

(4.3.2) key-LRU 时钟更新

只有一个 key 被拜访了,它的 LRU 时钟值就会被更新。而当一个键值对被拜访时,拜访操作最终都会调用 lookupKey 函数。

// file: src/db.c

/* 
 * 低级 key 查找 API
 * 实际上并没有间接从应该依赖 lookupKeyRead()、lookupKeyWrite()和 lookupKeyReadWithFlags()的命令实现中调用。*/
robj *lookupKey(redisDb *db, robj *key, int flags) {dictEntry *de = dictFind(db->dict,key->ptr);
    // 如果节点存在
    if (de) {
        // 从节点里获取 redisObject
        robj *val = dictGetVal(de);

        /* 
         * 更新老化算法的拜访工夫。* 如果咱们有一个正在保留的子过程,请不要这样做,因为这会触发疯狂写入正本。*/
        // 没有沉闷子过程 并且  
        if (!hasActiveChildProcess() && !(flags & LOOKUP_NOTOUCH)){if (server.maxmemory_policy & MAXMEMORY_FLAG_LFU) {
                // 更新 lfu
                updateLFU(val);
            } else {
                // 更新 lru 工夫
                val->lru = LRU_CLOCK();}
        }
        return val;
    } else {return NULL;}
}

(4.4) 近似 LRU 算法的理论执行

Redis 之所以实现近似 LRU 算法的目标,是为了缩小内存资源和操作工夫上的开销。
何时触发算法执行?
算法具体如何执行?

(4.4.1) 触发机会

近似 LRU 算法的次要逻辑是在 freeMemoryIfNeeded 函数中实现的

processCommand -> freeMemoryIfNeededAndSafe -> freeMemoryIfNeeded

(4.4.2) 近似 LRU 算法执行

次要分 3 大步

  1. 判断以后内存应用状况 -getMaxmemoryState
  2. 更新待淘汰的候选键值对汇合 -evictionPoolPopulate
  3. 抉择被淘汰的键值对并删除 -freeMemoryIfNeeded
// file: src/evict.c

/* This function is periodically called to see if there is memory to free
 * according to the current "maxmemory" settings. In case we are over the
 * memory limit, the function will try to free some memory to return back
 * under the limit.
 *
 * The function returns C_OK if we are under the memory limit or if we
 * were over the limit, but the attempt to free memory was successful.
 * Otherwise if we are over the memory limit, but not enough memory
 * was freed to return back under the limit, the function returns C_ERR. */
int freeMemoryIfNeeded(void) {
    int keys_freed = 0;
    /* By default replicas should ignore maxmemory
     * and just be masters exact copies. */
    if (server.masterhost && server.repl_slave_ignore_maxmemory) return C_OK;

    size_t mem_reported, mem_tofree, mem_freed;
    mstime_t latency, eviction_latency, lazyfree_latency;
    long long delta;
    int slaves = listLength(server.slaves);
    int result = C_ERR;

    /* 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 C_OK;

    // 如果以后内存使用量没有超过 maxmemory,返回
    if (getMaxmemoryState(&mem_reported,NULL,&mem_tofree,NULL) == C_OK)
        return C_OK;

    mem_freed = 0;

    latencyStartMonitor(latency);
    if (server.maxmemory_policy == MAXMEMORY_NO_EVICTION)
        goto cant_free; /* We need to free memory, but policy forbids. */

    while (mem_freed < mem_tofree) {
        int j, k, i;
        static unsigned int next_db = 0;
        sds bestkey = NULL;
        int bestdbid;
        redisDb *db;
        dict *dict;
        dictEntry *de;

        if (server.maxmemory_policy & (MAXMEMORY_FLAG_LRU|MAXMEMORY_FLAG_LFU) ||
            server.maxmemory_policy == MAXMEMORY_VOLATILE_TTL)
        {
            struct evictionPoolEntry *pool = EvictionPoolLRU;

            while(bestkey == NULL) {
                unsigned long total_keys = 0, keys;

                /* We don't want to make local-db choices when expiring keys,
                 * so to start populate the eviction pool sampling keys from
                 * every DB. */
                for (i = 0; i < server.dbnum; i++) {
                    db = server.db+i;
                    dict = (server.maxmemory_policy & MAXMEMORY_FLAG_ALLKEYS) ?
                            db->dict : db->expires;
                    if ((keys = dictSize(dict)) != 0) {evictionPoolPopulate(i, dict, db->dict, pool);
                        total_keys += keys;
                    }
                }
                if (!total_keys) break; /* No keys to evict. */

                /* Go backward from best to worst element to evict. */
                for (k = EVPOOL_SIZE-1; k >= 0; k--) {if (pool[k].key == NULL) continue;
                    bestdbid = pool[k].dbid;

                    if (server.maxmemory_policy & MAXMEMORY_FLAG_ALLKEYS) {de = dictFind(server.db[pool[k].dbid].dict,
                            pool[k].key);
                    } else {de = dictFind(server.db[pool[k].dbid].expires,
                            pool[k].key);
                    }

                    /* Remove the entry from the pool. */
                    if (pool[k].key != pool[k].cached)
                        sdsfree(pool[k].key);
                    pool[k].key = NULL;
                    pool[k].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... Iterate again. */}
                }
            }
        }

        /* volatile-random and allkeys-random policy */
        else if (server.maxmemory_policy == MAXMEMORY_ALLKEYS_RANDOM ||
                 server.maxmemory_policy == MAXMEMORY_VOLATILE_RANDOM)
        {
            /* When evicting a random key, we try to evict a key for
             * each DB, so we use the static 'next_db' variable to
             * incrementally visit all DBs. */
            for (i = 0; i < server.dbnum; i++) {j = (++next_db) % server.dbnum;
                db = server.db+j;
                dict = (server.maxmemory_policy == MAXMEMORY_ALLKEYS_RANDOM) ?
                        db->dict : db->expires;
                if (dictSize(dict) != 0) {de = dictGetRandomKey(dict);
                    bestkey = dictGetKey(de);
                    bestdbid = j;
                    break;
                }
            }
        }

        /* Finally remove the selected key. */
        if (bestkey) {
            db = server.db+bestdbid;
            robj *keyobj = createStringObject(bestkey,sdslen(bestkey));
            propagateExpire(db,keyobj,server.lazyfree_lazy_eviction);
            /* We compute the amount of memory freed by db*Delete() 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.
             *
             * Same for CSC invalidation messages generated by signalModifiedKey.
             *
             * AOF and Output buffer memory will be freed eventually so
             * we only care about memory used by the key space. */
            delta = (long long) zmalloc_used_memory();
            latencyStartMonitor(eviction_latency);
            if (server.lazyfree_lazy_eviction)
                dbAsyncDelete(db,keyobj);
            else
                dbSyncDelete(db,keyobj);
            latencyEndMonitor(eviction_latency);
            latencyAddSampleIfNeeded("eviction-del",eviction_latency);
            delta -= (long long) zmalloc_used_memory();
            mem_freed += delta;
            server.stat_evictedkeys++;
            signalModifiedKey(NULL,db,keyobj);
            notifyKeyspaceEvent(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();

            /* Normally our stop condition is the ability to release
             * a fixed, pre-computed amount of memory. However when we
             * are deleting objects in another thread, it's better to
             * check, from time to time, if we already reached our target
             * memory, since the "mem_freed" amount is computed only
             * across the dbAsyncDelete() call, while the thread can
             * release the memory all the time. */
            if (server.lazyfree_lazy_eviction && !(keys_freed % 16)) {if (getMaxmemoryState(NULL,NULL,NULL,NULL) == C_OK) {
                    /* Let's satisfy our stop condition. */
                    mem_freed = mem_tofree;
                }
            }
        } else {goto cant_free; /* nothing to free... */}
    }
    result = C_OK;

cant_free:
    /* We are here if we are not able to reclaim memory. There is only one
     * last thing we can try: check if the lazyfree thread has jobs in queue
     * and wait... */
    if (result != C_OK) {latencyStartMonitor(lazyfree_latency);
        while(bioPendingJobsOfType(BIO_LAZY_FREE)) {if (getMaxmemoryState(NULL,NULL,NULL,NULL) == C_OK) {
                result = C_OK;
                break;
            }
            usleep(1000);
        }
        latencyEndMonitor(lazyfree_latency);
        latencyAddSampleIfNeeded("eviction-lazyfree",lazyfree_latency);
    }
    latencyEndMonitor(latency);
    latencyAddSampleIfNeeded("eviction-cycle",latency);
    return result;
}
(4.4.2.1) 判断以后内存应用状况 -getMaxmemoryState
// file: src/evict.c

/* Get the memory status from the point of view of the maxmemory directive:
 * if the memory used is under the maxmemory setting then C_OK is returned.
 * Otherwise, if we are over the memory limit, the function returns
 * C_ERR.
 *
 * The function may return additional info via reference, only if the
 * pointers to the respective arguments is not NULL. Certain fields are
 * populated only when C_ERR is returned:
 *
 *  'total'     total amount of bytes used.
 *              (Populated both for C_ERR and C_OK)
 *
 *  'logical'   the amount of memory used minus the slaves/AOF buffers.
 *              (Populated when C_ERR is returned)
 *
 *  'tofree'    the amount of memory that should be released
 *              in order to return back into the memory limits.
 *              (Populated when C_ERR is returned)
 *
 *  'level'     this usually ranges from 0 to 1, and reports the amount of
 *              memory currently used. May be > 1 if we are over the memory
 *              limit.
 *              (Populated both for C_ERR and C_OK)
 */
int getMaxmemoryState(size_t *total, size_t *logical, size_t *tofree, float *level) {
    size_t mem_reported, mem_used, mem_tofree;

    /* Check if we are over the memory usage limit. If we are not, no need
     * to subtract the slaves output buffers. We can just return ASAP. */
    mem_reported = zmalloc_used_memory();
    if (total) *total = mem_reported;

    /* We may return ASAP if there is no need to compute the level. */
    int return_ok_asap = !server.maxmemory || mem_reported <= server.maxmemory;
    if (return_ok_asap && !level) return C_OK;

    /* Remove the size of slaves output buffers and AOF buffer from the
     * count of used memory. */
    mem_used = mem_reported;
    size_t overhead = freeMemoryGetNotCountedMemory();
    mem_used = (mem_used > overhead) ? mem_used-overhead : 0;

    /* Compute the ratio of memory usage. */
    if (level) {if (!server.maxmemory) {*level = 0;} else {*level = (float)mem_used / (float)server.maxmemory;
        }
    }

    if (return_ok_asap) return C_OK;

    /* Check if we are still over the memory limit. */
    if (mem_used <= server.maxmemory) return C_OK;

    /* Compute how much memory we need to free. */
    mem_tofree = mem_used - server.maxmemory;

    if (logical) *logical = mem_used;
    if (tofree) *tofree = mem_tofree;

    return C_ERR;
}

(4.4.2.2) 更新待淘汰的候选键值对汇合 -evictionPoolPopulate

// file: src/evict.c

/* This is an helper function for freeMemoryIfNeeded(), it is used in order
 * to populate the evictionPool with a few entries every time we want to
 * expire a key. Keys with idle time smaller than one of the current
 * keys are added. Keys are always added if there are free entries.
 *
 * We insert keys on place in ascending order, so keys with the smaller
 * idle time are on the left, and keys with the higher idle time on the
 * right. */

void evictionPoolPopulate(int dbid, dict *sampledict, dict *keydict, struct evictionPoolEntry *pool) {
    int j, k, count;
    dictEntry *samples[server.maxmemory_samples];

    count = dictGetSomeKeys(sampledict,samples,server.maxmemory_samples);
    for (j = 0; j < count; j++) {
        unsigned long long idle;
        sds key;
        robj *o;
        dictEntry *de;

        de = samples[j];
        key = dictGetKey(de);

        /* If the dictionary we are sampling from is not the main
         * dictionary (but the expires one) we need to lookup the key
         * again in the key dictionary to obtain the value object. */
        if (server.maxmemory_policy != MAXMEMORY_VOLATILE_TTL) {if (sampledict != keydict) de = dictFind(keydict, key);
            o = dictGetVal(de);
        }

        /* Calculate the idle time according to the policy. This is called
         * idle just because the code initially handled LRU, but is in fact
         * just a score where an higher score means better candidate. */
        if (server.maxmemory_policy & MAXMEMORY_FLAG_LRU) {idle = estimateObjectIdleTime(o);
        } else if (server.maxmemory_policy & MAXMEMORY_FLAG_LFU) {
            /* When we use an LRU policy, we sort the keys by idle time
             * so that we expire keys starting from greater idle time.
             * However when the policy is an LFU one, we have a frequency
             * estimation, and we want to evict keys with lower frequency
             * first. So inside the pool we put objects using the inverted
             * frequency subtracting the actual frequency to the maximum
             * frequency of 255. */
            idle = 255-LFUDecrAndReturn(o);
        } else if (server.maxmemory_policy == MAXMEMORY_VOLATILE_TTL) {
            /* In this case the sooner the expire the better. */
            idle = ULLONG_MAX - (long)dictGetVal(de);
        } else {serverPanic("Unknown eviction policy in evictionPoolPopulate()");
        }

        /* Insert the element inside the pool.
         * First, find the first empty bucket or the first populated
         * bucket that has an idle time smaller than our idle time. */
        k = 0;
        while (k < EVPOOL_SIZE &&
               pool[k].key &&
               pool[k].idle < idle) k++;
        if (k == 0 && pool[EVPOOL_SIZE-1].key != NULL) {
            /* Can't insert if the element is < the worst element we have
             * and there are no empty buckets. */
            continue;
        } else if (k < EVPOOL_SIZE && pool[k].key == NULL) {/* Inserting into empty position. No setup needed before insert. */} else {
            /* Inserting in the middle. Now k points to the first element
             * greater than the element to insert.  */
            if (pool[EVPOOL_SIZE-1].key == NULL) {
                /* Free space on the right? Insert at k shifting
                 * all the elements from k to end to the right. */

                /* Save SDS before overwriting. */
                sds cached = pool[EVPOOL_SIZE-1].cached;
                memmove(pool+k+1,pool+k,
                    sizeof(pool[0])*(EVPOOL_SIZE-k-1));
                pool[k].cached = cached;
            } else {
                /* No free space on right? Insert at k-1 */
                k--;
                /* Shift all elements on the left of k (included) to the
                 * left, so we discard the element with smaller idle time. */
                sds cached = pool[0].cached; /* Save SDS before overwriting. */
                if (pool[0].key != pool[0].cached) sdsfree(pool[0].key);
                memmove(pool,pool+1,sizeof(pool[0])*k);
                pool[k].cached = cached;
            }
        }

        /* Try to reuse the cached SDS string allocated in the pool entry,
         * because allocating and deallocating this object is costly
         * (according to the profiler, not my fantasy. Remember:
         * premature optimization bla bla bla. */
        int klen = sdslen(key);
        if (klen > EVPOOL_CACHED_SDS_SIZE) {pool[k].key = sdsdup(key);
        } else {memcpy(pool[k].cached,key,klen+1);
            sdssetlen(pool[k].cached,klen);
            pool[k].key = pool[k].cached;
        }
        pool[k].idle = idle;
        pool[k].dbid = dbid;
    }
}

(4.4.2.3) 抉择被淘汰的键值对并删除 -freeMemoryIfNeeded

// file: src/evict.c

/* This function is periodically called to see if there is memory to free
 * according to the current "maxmemory" settings. In case we are over the
 * memory limit, the function will try to free some memory to return back
 * under the limit.
 *
 * The function returns C_OK if we are under the memory limit or if we
 * were over the limit, but the attempt to free memory was successful.
 * Otherwise if we are over the memory limit, but not enough memory
 * was freed to return back under the limit, the function returns C_ERR. */
int freeMemoryIfNeeded(void) {
    int keys_freed = 0;
    /* By default replicas should ignore maxmemory
     * and just be masters exact copies. */
    if (server.masterhost && server.repl_slave_ignore_maxmemory) return C_OK;

    size_t mem_reported, mem_tofree, mem_freed;
    mstime_t latency, eviction_latency, lazyfree_latency;
    long long delta;
    int slaves = listLength(server.slaves);
    int result = C_ERR;

    /* 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 C_OK;
    if (getMaxmemoryState(&mem_reported,NULL,&mem_tofree,NULL) == C_OK)
        return C_OK;

    mem_freed = 0;

    latencyStartMonitor(latency);
    if (server.maxmemory_policy == MAXMEMORY_NO_EVICTION)
        goto cant_free; /* We need to free memory, but policy forbids. */

    while (mem_freed < mem_tofree) {
        int j, k, i;
        static unsigned int next_db = 0;
        sds bestkey = NULL;
        int bestdbid;
        redisDb *db;
        dict *dict;
        dictEntry *de;

        if (server.maxmemory_policy & (MAXMEMORY_FLAG_LRU|MAXMEMORY_FLAG_LFU) ||
            server.maxmemory_policy == MAXMEMORY_VOLATILE_TTL)
        {
            struct evictionPoolEntry *pool = EvictionPoolLRU;

            while(bestkey == NULL) {
                unsigned long total_keys = 0, keys;

                /* We don't want to make local-db choices when expiring keys,
                 * so to start populate the eviction pool sampling keys from
                 * every DB. */
                for (i = 0; i < server.dbnum; i++) {
                    db = server.db+i;
                    dict = (server.maxmemory_policy & MAXMEMORY_FLAG_ALLKEYS) ?
                            db->dict : db->expires;
                    if ((keys = dictSize(dict)) != 0) {evictionPoolPopulate(i, dict, db->dict, pool);
                        total_keys += keys;
                    }
                }
                if (!total_keys) break; /* No keys to evict. */

                /* Go backward from best to worst element to evict. */
                for (k = EVPOOL_SIZE-1; k >= 0; k--) {if (pool[k].key == NULL) continue;
                    bestdbid = pool[k].dbid;

                    if (server.maxmemory_policy & MAXMEMORY_FLAG_ALLKEYS) {de = dictFind(server.db[pool[k].dbid].dict,
                            pool[k].key);
                    } else {de = dictFind(server.db[pool[k].dbid].expires,
                            pool[k].key);
                    }

                    /* Remove the entry from the pool. */
                    if (pool[k].key != pool[k].cached)
                        sdsfree(pool[k].key);
                    pool[k].key = NULL;
                    pool[k].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... Iterate again. */}
                }
            }
        }

        /* volatile-random and allkeys-random policy */
        else if (server.maxmemory_policy == MAXMEMORY_ALLKEYS_RANDOM ||
                 server.maxmemory_policy == MAXMEMORY_VOLATILE_RANDOM)
        {
            /* When evicting a random key, we try to evict a key for
             * each DB, so we use the static 'next_db' variable to
             * incrementally visit all DBs. */
            for (i = 0; i < server.dbnum; i++) {j = (++next_db) % server.dbnum;
                db = server.db+j;
                dict = (server.maxmemory_policy == MAXMEMORY_ALLKEYS_RANDOM) ?
                        db->dict : db->expires;
                if (dictSize(dict) != 0) {de = dictGetRandomKey(dict);
                    bestkey = dictGetKey(de);
                    bestdbid = j;
                    break;
                }
            }
        }

        /* Finally remove the selected key. */
        if (bestkey) {
            db = server.db+bestdbid;
            robj *keyobj = createStringObject(bestkey,sdslen(bestkey));
            propagateExpire(db,keyobj,server.lazyfree_lazy_eviction);
            /* We compute the amount of memory freed by db*Delete() 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.
             *
             * Same for CSC invalidation messages generated by signalModifiedKey.
             *
             * AOF and Output buffer memory will be freed eventually so
             * we only care about memory used by the key space. */
            delta = (long long) zmalloc_used_memory();
            latencyStartMonitor(eviction_latency);
            if (server.lazyfree_lazy_eviction)
                dbAsyncDelete(db,keyobj);
            else
                dbSyncDelete(db,keyobj);
            latencyEndMonitor(eviction_latency);
            latencyAddSampleIfNeeded("eviction-del",eviction_latency);
            delta -= (long long) zmalloc_used_memory();
            mem_freed += delta;
            server.stat_evictedkeys++;
            signalModifiedKey(NULL,db,keyobj);
            notifyKeyspaceEvent(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();

            /* Normally our stop condition is the ability to release
             * a fixed, pre-computed amount of memory. However when we
             * are deleting objects in another thread, it's better to
             * check, from time to time, if we already reached our target
             * memory, since the "mem_freed" amount is computed only
             * across the dbAsyncDelete() call, while the thread can
             * release the memory all the time. */
            if (server.lazyfree_lazy_eviction && !(keys_freed % 16)) {if (getMaxmemoryState(NULL,NULL,NULL,NULL) == C_OK) {
                    /* Let's satisfy our stop condition. */
                    mem_freed = mem_tofree;
                }
            }
        } else {goto cant_free; /* nothing to free... */}
    }
    result = C_OK;

cant_free:
    /* We are here if we are not able to reclaim memory. There is only one
     * last thing we can try: check if the lazyfree thread has jobs in queue
     * and wait... */
    if (result != C_OK) {latencyStartMonitor(lazyfree_latency);
        while(bioPendingJobsOfType(BIO_LAZY_FREE)) {if (getMaxmemoryState(NULL,NULL,NULL,NULL) == C_OK) {
                result = C_OK;
                break;
            }
            usleep(1000);
        }
        latencyEndMonitor(lazyfree_latency);
        latencyAddSampleIfNeeded("eviction-lazyfree",lazyfree_latency);
    }
    latencyEndMonitor(latency);
    latencyAddSampleIfNeeded("eviction-cycle",latency);
    return result;
}

参考资料

https://weikeqin.com/tags/redis/

Redis 源码分析与实战 学习笔记 Day15 15 | 为什么 LRU 算法原理和代码实现不一样?
https://time.geekbang.org/col…

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