漫话Redis源码之六十三

多数人对LRU应该很熟悉吧。这里就是LRU的近似实现算法，其原理跟LRU差不错。

大家在准备笔试面试的时候，肯定遇到过LRU相关的问题。

/* LRU approximation algorithm
 *
 * Redis uses an approximation of the LRU algorithm that runs in constant
 * memory. Every time there is a key to expire, we sample N keys (with
 * N very small, usually in around 5) to populate a pool of best keys to
 * evict of M keys (the pool size is defined by EVPOOL_SIZE).
 *
 * The N keys sampled are added in the pool of good keys to expire (the one
 * with an old access time) if they are better than one of the current keys
 * in the pool.
 *
 * After the pool is populated, the best key we have in the pool is expired.
 * However note that we don't remove keys from the pool when they are deleted
 * so the pool may contain keys that no longer exist.
 *
 * When we try to evict a key, and all the entries in the pool don't exist
 * we populate it again. This time we'll be sure that the pool has at least
 * one key that can be evicted, if there is at least one key that can be
 * evicted in the whole database. */
 
/* Create a new eviction pool. */
void evictionPoolAlloc(void) {
    struct evictionPoolEntry *ep;
    int j;
 
    ep = zmalloc(sizeof(*ep)*EVPOOL_SIZE);
    for (j = 0; j < EVPOOL_SIZE; j++) {
        ep[j].idle = 0;
        ep[j].key = NULL;
        ep[j].cached = sdsnewlen(NULL,EVPOOL_CACHED_SDS_SIZE);
        ep[j].dbid = 0;
    }
    EvictionPoolLRU = ep;
}
 
/* This is an helper function for performEvictions(), 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 bigger 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;
    }
}