Redis 源码分析-内部数据结构 dict

在上一篇 Redis 数据库源码分析提到了 Redis 其实用了全局的 hash 表来存储所有的键值对，即下方图示的 dict，dict 中有两个数组，其中 ht[1] 只在 rehash 时候才真正用到，平时都是指向 null，hash 的底层又是使用数组来实现的，那就引出了接下来的几个问题：

redis 启动初始化这个 dict 时数组容量是多少
如果发生了 hash 冲突怎么办
扩容机制（扩容的时机，扩容的实现)

dict 的创建

/* Create a new hash table */
dict *dictCreate(dictType *type, void *privDataPtr)
{
    dict *d = zmalloc(sizeof(*d));
    _dictInit(d,type,privDataPtr);
    return d;
}

/* Initialize the hash table */
int _dictInit(dict *d, dictType *type, void *privDataPtr)
{
    _dictReset(&d->ht[0]);
    _dictReset(&d->ht[1]);
    d->type = type;			
    d->privdata = privDataPtr;
    d->rehashidx = -1;
    d->iterators = 0;
    return DICT_OK;
}

/* Reset a hash table already initialized with ht_init().
 * NOTE: This function should only be called by ht_destroy(). */
static void _dictReset(dictht *ht)
{
    ht->table = NULL;
    ht->size = 0;		// table 的长度, 一定是2的倍数
    ht->sizemask = 0;	// size - 1,具体原因参见上篇
    ht->used = 0;		// 已经存的元素总数
}

代码分析：

2行，创建变量时的 dictType *type，包含很多函数指针，无论是添加或查找 key 时 hash 函数还是删除 dictEntry 时的析构函数
25行，ht->table = NULL，也就是说 dict 在被创建时 table 并没有分配内存空间，意味着第一个数据插入时才会真正分配空间。

dict 的扩容

/* 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;
}

/* Expand or create the hash table */
int dictExpand(dict *d, unsigned long size)
{
    /* the size is invalid if it is smaller than the number of
     * elements already inside the hash table */
    if (dictIsRehashing(d) || d->ht[0].used > size)
        return DICT_ERR;

    dictht n; /* the new hash table */
    unsigned long realsize = _dictNextPower(size);	// _dictNextPower 根据传入的 size 获得最终分配的 size

    /* Rehashing to the same table size is not useful. */
    if (realsize == d->ht[0].size) return DICT_ERR;

    /* Allocate the new hash table and initialize all pointers to NULL */
    n.size = realsize;
    n.sizemask = realsize-1;
    n.table = zcalloc(realsize*sizeof(dictEntry*));
    n.used = 0;

    /* Is this the first initialization? If so it's not really a rehashing
     * we just set the first hash table so that it can accept keys. */
    if (d->ht[0].table == NULL) {
        d->ht[0] = n;
        return DICT_OK;
    }

    /* Prepare a second hash table for incremental rehashing */
    d->ht[1] = n;
    d->rehashidx = 0;
    return DICT_OK;
}

/* Our hash table capability is a power of two */
static unsigned long _dictNextPower(unsigned long size)
{
    unsigned long i = DICT_HT_INITIAL_SIZE;

    if (size >= LONG_MAX) return LONG_MAX + 1LU;
    while(1) {
        if (i >= size)
            return i;
        i *= 2;
    }
}

代码分析：

8行，如果是第一次插入（ht[0].size == 0），用初始化大小（DICT_HT_INITIAL_SIZE）分配，这个值默认是 4
14行，扩容的判断条件，负载因子（d->ht[0].used / d->ht[0].size），即 ht 中元素总数与 bucket 个数的比值
- 负载因子 >= 1，且 dict_can_resize，dict_can_resize 的值受此时 redis 状态的影响，例如 redis 在进行 aof 重写或 rdb生成时，不想造成太多的内存拷贝，就会关闭
- 负载因子 >= 5，即 dict_force_resize_ratio 的默认值，此时 hash 冲突已经很严重了，不管此时处于什么状态，都会进行扩容

dict 的销毁

/* Clear & Release the hash table */
void dictRelease(dict *d)
{
    _dictClear(d,&d->ht[0],NULL);
    _dictClear(d,&d->ht[1],NULL);
    zfree(d);
}

/* Destroy an entire dictionary */
int _dictClear(dict *d, dictht *ht, void(callback)(void *)) {
    unsigned long i;

    /* Free all the elements */
    for (i = 0; i < ht->size && ht->used > 0; i++) {
        dictEntry *he, *nextHe;

        if (callback && (i & 65535) == 0) callback(d->privdata);

        if ((he = ht->table[i]) == NULL) continue;
        while(he) {
            nextHe = he->next;
            dictFreeKey(d, he);
            dictFreeVal(d, he);
            zfree(he);
            ht->used--;
            he = nextHe;
        }
    }
    /* Free the table and the allocated cache structure */
    zfree(ht->table);
    /* Re-initialize the table */
    _dictReset(ht);
    return DICT_OK; /* never fails */
}

#define dictFreeKey(d, entry) \
    if ((d)->type->keyDestructor) \
        (d)->type->keyDestructor((d)->privdata, (entry)->key)
#define dictFreeVal(d, entry) \
    if ((d)->type->valDestructor) \
        (d)->type->valDestructor((d)->privdata, (entry)->v.val)

代码分析：

20-27行：删除每个 dictEntry 时会调用 key 和 value 的析构函数（keyDestructor 和 valDestructor），用于释放键和值所占的内存。

dict 添加元素

主要涉及两个函数，dictAdd 和 dictReplace

dictAdd

该函数向 hash table 中添加数据，如果 key 已经存在会返回失败

/* Add an element to the target hash table */
int dictAdd(dict *d, void *key, void *val)
{
    dictEntry *entry = dictAddRaw(d,key,NULL);
    if (!entry) return DICT_ERR;
    dictSetVal(d, entry, val);
    return DICT_OK;
}

/* Low level add or find:
 * This function adds the entry but instead of setting a value returns the
 * dictEntry structure to the user, that will make sure to fill the value
 * field as he wishes.
 *
 * This function is also directly exposed to the user API to be called
 * mainly in order to store non-pointers inside the hash value, example:
 *
 * entry = dictAddRaw(dict,mykey,NULL);
 * if (entry != NULL) dictSetSignedIntegerVal(entry,1000);
 *
 * Return values:
 *
 * If key already exists NULL is returned, and "*existing" is populated
 * with the existing entry if existing is not NULL.
 *
 * If key was added, the hash entry is returned to be manipulated by the caller.
 */
dictEntry *dictAddRaw(dict *d, void *key, dictEntry **existing)
{
    long index;
    dictEntry *entry;
    dictht *ht;

    if (dictIsRehashing(d)) _dictRehashStep(d);

    /* Get the index of the new element, or -1 if
     * the element already exists. */
    if ((index = _dictKeyIndex(d, key, dictHashKey(d,key), existing)) == -1)
        return NULL;

    /* Allocate the memory and store the new entry.
     * Insert the element in top, with the assumption that in a database
     * system it is more likely that recently added entries are accessed
     * more frequently. */
    ht = dictIsRehashing(d) ? &d->ht[1] : &d->ht[0];
    entry = zmalloc(sizeof(*entry));
    entry->next = ht->table[index];
    ht->table[index] = entry;
    ht->used++;

    /* Set the hash entry fields. */
    dictSetKey(d, entry, key);
    return entry;
}

代码分析：

34行判断此时是否正在 rehash，如果在，则将 rehash 向前推进一步
38行，_dictKeyIndex函数根据传入的 key 寻找插入的位置，如果该 key 已经存在，会返回-1
45行，如果此时正在 rehash，就把数据插入到 ht[1]，否则插入到 ht[0]
47行-49行，使用头插法插入数据

上面有两个关键函数，一个是_dictKeyIndex，另一个是_dictRehashStep

_dictKeyIndex

/* Returns the index of a free slot that can be populated with
 * a hash entry for the given 'key'.
 * If the key already exists, -1 is returned
 * and the optional output parameter may be filled.
 *
 * Note that if we are in the process of rehashing the hash table, the
 * index is always returned in the context of the second (new) hash table. */
static long _dictKeyIndex(dict *d, const void *key, uint64_t hash, dictEntry **existing)
{
    unsigned long idx, table;
    dictEntry *he;
    if (existing) *existing = NULL;

    /* Expand the hash table if needed */
    if (_dictExpandIfNeeded(d) == DICT_ERR)
        return -1;
    for (table = 0; table <= 1; table++) {
        idx = hash & d->ht[table].sizemask;
        /* Search if this slot does not already contain the given key */
        he = d->ht[table].table[idx];
        while(he) {
            if (key==he->key || dictCompareKeys(d, key, he->key)) {
                if (existing) *existing = he;
                return -1;
            }
            he = he->next;
        }
        if (!dictIsRehashing(d)) break;
    }
    return idx;
}

代码分析：

15行，会判断此时是否需要扩容
28行，查找时会先从 ht[0] 查找，如果 ht[0] 中没有数据且此时不在进行 rehash，就直接返回

_dictKeyIndex 如果 key 已经存在会返回 -1，否则返回该 key 需要插入的桶的索引。

_dictRehashStep

/* This function performs just a step of rehashing, and only if there are
 * no safe iterators bound to our hash table. When we have iterators in the
 * middle of a rehashing we can't mess with the two hash tables otherwise
 * some element can be missed or duplicated.
 *
 * This function is called by common lookup or update operations in the
 * dictionary so that the hash table automatically migrates from H1 to H2
 * while it is actively used. */
static void _dictRehashStep(dict *d) {
    if (d->iterators == 0) dictRehash(d,1);
}

/* Performs N steps of incremental rehashing. Returns 1 if there are still
 * keys to move from the old to the new hash table, otherwise 0 is returned.
 *
 * Note that a rehashing step consists in moving a bucket (that may have more
 * than one key as we use chaining) from the old to the new hash table, however
 * since part of the hash table may be composed of empty spaces, it is not
 * guaranteed that this function will rehash even a single bucket, since it
 * will visit at max N*10 empty buckets in total, otherwise the amount of
 * work it does would be unbound and the function may block for a long time. */
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;
}

代码分析：

32-35行，如果 rehashidx 指向的 bucket 里一个 dictEntry 也没有，那么它就没有可迁移的数据。这时它尝试在 ht[0].table 数组中不断向后遍历，直到找到下一个存有数据的 bucket 位置。如果一直找不到，则最多走 n*10 步（empty_visits）。避免在该操作上一直向后遍历，影响响应时间。
43行，原 bucket 里的元素重新 hash 计算后对新的 sizemask 进行余操作，确定在新 table 上的位置。
55-61行，如果 ht[0] 上的数据都迁移到 ht[1] 上了（即d->ht[0].used == 0），那么整个重哈希结束，ht[0] 变成 ht[1] 的内容，而 ht[1] 重置为空。

参考下面这张图：哈希桶即 bucket，entry 即 dictEntry

dictReplace

该函数向 hash table 中添加数据，如果 key 已经存在会替换

/* Add or Overwrite:
 * Add an element, discarding the old value if the key already exists.
 * Return 1 if the key was added from scratch, 0 if there was already an
 * element with such key and dictReplace() just performed a value update
 * operation. */
int dictReplace(dict *d, void *key, void *val)
{
    dictEntry *entry, *existing, auxentry;

    /* Try to add the element. If the key
     * does not exists dictAdd will succeed. */
    entry = dictAddRaw(d,key,&existing);
    if (entry) {
        dictSetVal(d, entry, val);
        return 1;
    }

    /* Set the new value and free the old one. Note that it is important
     * to do that in this order, as the value may just be exactly the same
     * as the previous one. In this context, think to reference counting,
     * you want to increment (set), and then decrement (free), and not the
     * reverse. */
    auxentry = *existing;
    dictSetVal(d, existing, val);
    dictFreeVal(d, &auxentry);
    return 0;
}

代码分析：

12行，如果插入成功（key不存在）entry 就是插入的对象，如果 key 已经存在，则 existing 变量就是对应的 dictEntry
23-26行，注意顺序是先创建并设置新值，再释放旧值。

dict 删除元素

/* Remove an element, returning DICT_OK on success or DICT_ERR if the
 * element was not found. */
int dictDelete(dict *ht, const void *key) {
    return dictGenericDelete(ht,key,0) ? DICT_OK : DICT_ERR;
}

/* Search and remove an element. This is an helper function for
 * dictDelete() and dictUnlink(), please check the top comment
 * of those functions. */
static dictEntry *dictGenericDelete(dict *d, const void *key, int nofree) {
    uint64_t h, idx;
    dictEntry *he, *prevHe;
    int table;

    if (d->ht[0].used == 0 && d->ht[1].used == 0) return NULL;

    if (dictIsRehashing(d)) _dictRehashStep(d);
    h = dictHashKey(d, key);

    for (table = 0; table <= 1; table++) {
        idx = h & d->ht[table].sizemask;
        he = d->ht[table].table[idx];
        prevHe = NULL;
        while(he) {
            if (key==he->key || dictCompareKeys(d, key, he->key)) {
                /* Unlink the element from the list */
                if (prevHe)
                    prevHe->next = he->next;
                else
                    d->ht[table].table[idx] = he->next;
                if (!nofree) {
                    dictFreeKey(d, he);
                    dictFreeVal(d, he);
                    zfree(he);
                }
                d->ht[table].used--;
                return he;
            }
            prevHe = he;
            he = he->next;
        }
        if (!dictIsRehashing(d)) break;
    }
    return NULL; /* not found */
}

代码分析：

17行，如果在 rehash，也推进一步
25-38行，其实就是首先根据 hash 找到对应的 bucket，在链表中删除该元素，找不到则返回 null，根据是否在 rehash 决定只查找 ht[0] 还是 ht[1]
32-33行，删除后会调用 key 和 value 的析构函数（keyDestructor 和 valDestructor）

dict 查找元素

dictEntry *dictFind(dict *d, const void *key)
{
    dictEntry *he;
    uint64_t h, idx, table;

    if (d->ht[0].used + d->ht[1].used == 0) return NULL; /* dict is empty */
    if (dictIsRehashing(d)) _dictRehashStep(d);
    h = dictHashKey(d, key);
    for (table = 0; table <= 1; table++) {
        idx = h & d->ht[table].sizemask;
        he = d->ht[table].table[idx];
        while(he) {
            if (key==he->key || dictCompareKeys(d, key, he->key))
                return he;
            he = he->next;
        }
        if (!dictIsRehashing(d)) return NULL;
    }
    return NULL;
}