光看上面的，有点未见全貌 。
/* This is the initial size of every hash table */#define DICT_HT_INITIAL_SIZE4
/* 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;}
看一下真正作为底层被调用的函数，就清楚了 。
所以扩容的步骤是：
1、如果是第一次，那就直接给 4 个。
2、如果不是第一次，那就翻倍给 。
3、把新申请内存的地址存放在ht[1]，并将标识由 -1 转 0，表示需要进行操作 。
4、进行操作 。
/* 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;}
服务繁忙时的渐进式！！！
/* 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);}
当redis中数据量大的时候，整个过程将非常缓慢 。
redis采用了“分而治之”的思想，执行增删查改前，先判断当前字典是否在执行 。如果是，则一个节点 。
服务空闲时的批量！！！
/* Rehash for an amount of time between ms milliseconds and ms+1 milliseconds */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;}