redis是一个存储键值对的内存数据库，其存储键值的方式和Java中的HashMap相似。表征redis数据库的结构体是redisDb (在server.h文件中)，redis服务器默认有16个数据库，编号从0到15。
typedef struct redisDb {
dict *dict; /* 键空间 */
dict *expires; /* 过期键空间 */
dict *blocking_keys; /* 客户端在等待的键 (BLPOP) */
dict *ready_keys; /* 接收到 push 的阻塞键 */
dict *watched_keys; /* WATCHED keys for MULTI/EXEC CAS */
struct evictionPoolEntry *eviction_pool; /* Eviction pool of keys */
int id; /* Database ID */
long long avg_ttl; /* Average TTL, just for stats */
} redisDb;
dict 中存储的是 key -> value，而expires存储的 key -> 过期时间
dict是dict.h文件中定义的结构体：
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;
typedef struct dictht {
dictEntry **table;
unsigned long size; //table的大小
unsigned long sizemask;
unsigned long used; //table中键值对的数量
} dictht;
typedef struct dictEntry {
void *key;
union {
void *val;
uint64_t u64;
int64_t s64;
double d;
} v;
struct dictEntry *next;
} dictEntry;
dict可以类比为java中的HashMap，dictEntry对应java.util.HashMap.Entry<K, V>，稍微不同的是，dict对entry的table做了简单的封装（即dictht），而且dict中有两个table用于rehash。
分析dict的dictReplace(dict.c文件中)，类似于HashMap的put：
/* 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 suceed. */
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;
}
dictEntry *dictAddRaw(dict *d, void *key, dictEntry **existing)
{
int 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;
}
主要逻辑在dictAddRaw中，也是先取得table中index，然后使用头插法插入到table的链表中。
如果dict处于rehash状态（即rehashidx ！= -1），则在插入的时候，先调用_dictRehashStep，对于rehash中的dict，使用的table是ht[1]。
static void _dictRehashStep(dict *d) {
if (d->iterators == 0) dictRehash(d,1);
}
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;