【Redis】数据结构之dict

dict的基本结构

typedef struct dict {
    dictType *type;
    void *privdata;
    dictht ht[2];
    long rehashidx; /* rehashing not in progress if rehashidx == -1 */
    unsigned long iterators; /* number of iterators currently running */
} dict;
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Redis中dict结构体包含了两个ditcht，这是为了rehash。

typedef struct dictType {
    uint64_t (*hashFunction)(const void *key);
    void *(*keyDup)(void *privdata, const void *key);
    void *(*valDup)(void *privdata, const void *obj);
    int (*keyCompare)(void *privdata, const void *key1, const void *key2);
    void (*keyDestructor)(void *privdata, void *key);
    void (*valDestructor)(void *privdata, void *obj);
} dictType;
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提供了dictType，我认为这是用C语言实现的编译时多态（C语言是不存在多态的，这里准确的说我认为Redis通过dictType这个结构体，复用了dict结构体，很像C++编译时多态的思想） ，在创建dict时需要将dictType传入，不同的dictType可以提供不同的hashFunction、keyDup、keyCompare函数。

typedef struct dictht {
    dictEntry **table;
    unsigned long size;
    unsigned long sizemask;
    unsigned long used;
} dictht;
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dicht的结构中有dictEntry **table这是一个指针数组，可以理解为是哈希表的array部分。

typedef struct dictEntry {
    void *key;
    union {
        void *val;
        uint64_t u64;
        int64_t s64;
        double d;
    } v;
    struct dictEntry *next;
} dictEntry;
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这是dict中每个entry的结构，除了k和不同类型的v以外，还有struct dictEntry *next;体现了这是一个链哈希，即如果发生哈希冲突，就通过链表指针来组织起所有位于同一个哈希槽的entry。

dict的相关操作函数

底层通用的之查找插入key-value对应该放入ht表的哪个槽

/* Returns the index of a free slot that can be populated with
 * an hash entry for the given 'key'.
 * If the key already exists, -1 is returned. */
static int _dictKeyIndex(dict *ht, const void *key) {
    unsigned int h;
    dictEntry *he;

    /* Expand the hashtable if needed */
    if (_dictExpandIfNeeded(ht) == DICT_ERR)
        return -1;
    /* Compute the key hash value */
    h = dictHashKey(ht, key) & ht->sizemask;
    /* Search if this slot does not already contain the given key */
    he = ht->table[h];
    while(he) {
        if (dictCompareHashKeys(ht, key, he->key))
            return -1;
        he = he->next;
    }
    return h;
}
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/* Expand the hash table if needed */
static int _dictExpandIfNeeded(dict *d)
{
    /* Incremental rehashing already in progress. Return. */
    if (dictIsRehashing(d)) return DICT_OK;

    /* If the hash table is empty expand it to the initial size. */
    if (d->ht[0].size == 0) return dictExpand(d, DICT_HT_INITIAL_SIZE);

    /* If we reached the 1:1 ratio, and we are allowed to resize the hash
     * table (global setting) or we should avoid it but the ratio between
     * elements/buckets is over the "safe" threshold, we resize doubling
     * the number of buckets. */
    if (d->ht[0].used >= d->ht[0].size &&
        (dict_can_resize ||
         d->ht[0].used/d->ht[0].size > dict_force_resize_ratio))
    {
        return dictExpand(d, d->ht[0].used*2);
    }
    return DICT_OK;
}
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在dictExpand函数中，有

    _dictInit(&n, ht->type, ht->privdata);
    n.size = realsize;
    n.sizemask = realsize-1;
    n.table = calloc(realsize,sizeof(dictEntry*));
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所以，一个key应该插入到ht的哪个槽呢？就是_dictKeyIndex中的这一句

 h = dictHashKey(ht, key) & ht->sizemask;
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可以保证h的值在[0,size-1]之间，而这些槽已经被初始化了：

n.table = calloc(realsize,sizeof(dictEntry*));
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常规的dictAdd、dictDelete比较简单。

rehash过程

值得一提的是rehash过程。

int dictRehash(dict *d, int n) {
    int empty_visits = n*10; /* Max number of empty buckets to visit. */
    if (!dictIsRehashing(d)) return 0;

    while(n-- && d->ht[0].used != 0) {
        dictEntry *de, *nextde;

        /* Note that rehashidx can't overflow as we are sure there are more
         * elements because ht[0].used != 0 */
        assert(d->ht[0].size > (unsigned long)d->rehashidx);
        while(d->ht[0].table[d->rehashidx] == NULL) {
            d->rehashidx++;
            if (--empty_visits == 0) return 1;
        }
        de = d->ht[0].table[d->rehashidx];
        /* Move all the keys in this bucket from the old to the new hash HT */
        while(de) {
            uint64_t h;

            nextde = de->next;
            /* Get the index in the new hash table */
            h = dictHashKey(d, de->key) & d->ht[1].sizemask;
            de->next = d->ht[1].table[h];
            d->ht[1].table[h] = de;
            d->ht[0].used--;
            d->ht[1].used++;
            de = nextde;
        }
        d->ht[0].table[d->rehashidx] = NULL;
        d->rehashidx++;
    }

    /* Check if we already rehashed the whole table... */
    if (d->ht[0].used == 0) {
        zfree(d->ht[0].table);
        d->ht[0] = d->ht[1];
        _dictReset(&d->ht[1]);
        d->rehashidx = -1;
        return 0;
    }

    /* More to rehash... */
    return 1;
}
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整体来看就是ht[0]的尺寸太小了，为了效率，需要把ht[0]的所有元素都搬运到扩展了尺寸的ht[1]中。
返回值为1说明rehash还没有完成。
返回值为0说明rehash已经完成。并且已经交换了ht[0]和ht[1]，之后的命令写入可以往ht[0]里写了。

int dictRehashMilliseconds(dict *d, int ms) {
    long long start = timeInMilliseconds();
    int rehashes = 0;

    while(dictRehash(d,100)) {
        rehashes += 100;
        if (timeInMilliseconds()-start > ms) break;
    }
    return rehashes;
}
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int incrementallyRehash(int dbid) {
    /* Keys dictionary */
    if (dictIsRehashing(server.db[dbid].dict)) {
        dictRehashMilliseconds(server.db[dbid].dict,1);
        return 1; /* already used our millisecond for this loop... */
    }
    /* Expires */
    if (dictIsRehashing(server.db[dbid].expires)) {
        dictRehashMilliseconds(server.db[dbid].expires,1);
        return 1; /* already used our millisecond for this loop... */
    }
    return 0;
}
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实际上的rehash是在databasesCron函数里做的，incrementallyRehash指定了每次进行rehash的dict和时长(1 ms)。而dicthash()又设置了每次最多进行n个槽和n*10个空槽的遍历。