Reids 字典dict
1、字典结构
typedef struct dict {
dictType *type; //不同的key类型的 val的处理方法
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; // 数组
unsigned long size;
unsigned long sizemask; //计算
unsigned long used;
} dictht;
包含两个哈希表dictht ht[2],用于rehash，rehash包含两个：dictExpand扩展和dictResize
dictExpand：扩展，当达到一定的条件，倍数扩展哈希表。（_dictExpandIfNeeded内实现）
dictResize：到一定条件缩小（htNeedsResize内实现）。
底层都是用的rehash过程。rehash过程是一个渐进式过程，分别在get，add，del等操作过程中去分片rehash。分别片大小是1（index）。
后台还会有定时任务去渐进式rehash，分片大小是100。
rehashidx：-1表示未rehash，其他值表示正在rehash的idx值，在渐进式rehash过程中，用来记录rehash进度。
2、哈希算法
也就是hash key的算法。
#define dictHashKey(d, key) (d)->type->hashFunction(key) //计算key的hash值 具体见siphash.c内的代码 比较复杂
hash表的sizemask
始终等于hash表size-1，见代码dictExpand.
if (ht->used > size)
return DICT_ERR;
_dictInit(&n, ht->type, ht->privdata);
n.size = realsize;
n.sizemask = realsize-1; //计算sizemask
n.table = calloc(realsize,sizeof(dictEntry*));
3、rehash
随着哈希表的装载的k v键值对越来越多，hash表的冲突和查找，写入效率都会大大的打折扣，这是我们需要在适宜的时候扩展整个hash表，也就是ht下的table数组大小，减少冲突，提高效率，当然如果有效的使用率过小，也会进行resize反向操作。一般的rehash扩展过程大小是2的倍数扩展的。
扩展过程如下：
rehash_1.png
rehash_2.png
3.1图 rehash前
3.2reset ht size,初始化ht[1],size是ht[0]的倍数
rehash_3.png
3.3rehash过程
rehash_4.png
3.4将ht[0]= ht[1],ht[1] =null；完毕
4、rehash代码
从add入手。
//dict.c
/* Add the key to the DB. It's up to the caller to increment the reference
* counter of the value if needed.
*
* The program is aborted if the key already exists. */
//添加key value调用
void dbAdd(redisDb *db, robj *key, robj *val) {
sds copy = sdsdup(key->ptr); //sds redis字符串
int retval = dictAdd(db->dict, copy, val); //字典添加
serverAssertWithInfo(NULL,key,retval == DICT_OK);
if (val->type == OBJ_LIST) signalListAsReady(db, key);
if (server.cluster_enabled) slotToKeyAdd(key);
}
//dictAdd
/* Add an element to the target hash table */
int dictAdd(dict *d, void *key, void *val)
{
dictEntry *entry = dictAddRaw(d,key,NULL); //添加key
if (!entry) return DICT_ERR;
dictSetVal(d, entry, val);//添加val
return DICT_OK;
}
//dictAddRaw 中的如果判断正在rehash则进行单步dictRehash过程。
static void _dictRehashStep(dict *d) {
if (d->iterators == 0) dictRehash(d,1);
}
//dictRehash，n表示是rehash片大小
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) { //rehash 片知道n减少到0
dictEntry *de, *nextde;
/* 如果 被rehash size小于rehashIdx索引，则不能rehash*/
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 */
//rehash de(idx指定的)
while(de) {
unsigned int 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) { //rehash完毕，ht[0] = ht[1]，设置rehashidx = -1；
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;
}
/* Expand or create the hash table */
/* 这里先申请一个size大小的ht[1]，依据并设置rehashidx =0,表示正在rehash*/
int dictExpand(dict *d, unsigned long size)
{
dictht n; /* the new hash table */
unsigned long realsize = _dictNextPower(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;
/* 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;//修改rehashidx
return DICT_OK;
}
static int dict_can_resize = 1;
static unsigned int dict_force_resize_ratio = 5;
/* Expand the hash table if needed */
/*判断是否需要expand*/
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. */
/**如果是空的，first time则必须扩展 */
if (d->ht[0].size == 0) return dictExpand(d, DICT_HT_INITIAL_SIZE); //初始大小
/* 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. */
//达到条件 used>= size 使用的到到申请的大小size 且可以resize 或者
if (d->ht[0].used >= d->ht[0].size &&
(dict_can_resize ||
d->ht[0].used/d->ht[0].size > dict_force_resize_ratio)) //到达比率
{
return dictExpand(d, d->ht[0].used*2);
}
return DICT_OK;
}
//
* 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 int _dictKeyIndex(dict *d, const void *key, unsigned int hash, dictEntry **existing)
{
unsigned int idx, table;
dictEntry *he;
if (existing) *existing = NULL;
/* Expand the hash table if needed */
if (_dictExpandIfNeeded(d) == DICT_ERR) //错误返回
return -1;
for (table = 0; table <= 1; table++) {
idx = hash & d->ht[table].sizemask; //计算哦
/* 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;
}
//添加key value
dictEntry *dictAddRaw(dict *d, void *key, dictEntry **existing)
{
int index;
dictEntry *entry;
dictht *ht;
if (dictIsRehashing(d)) _dictRehashStep(d);// 渐进式rehash
/* Get the index of the new element, or -1 if
* the element already exists. */
//计算key在table中的索引值 dictHashKey 就是调用宏指令
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. */
//判断是否rehash，添加的话必须在ht[1]添加
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;
}
定时rehash
//dict.c
long long timeInMilliseconds(void) {
struct timeval tv;
gettimeofday(&tv,NULL);
return (((long long)tv.tv_sec)*1000)+(tv.tv_usec/1000);
}
/* Rehash for an amount of time between ms milliseconds and ms+1 milliseconds */
//定时 片大小100
int dictRehashMilliseconds(dict *d, int ms) {
long long start = timeInMilliseconds();
int rehashes = 0;
while(dictRehash(d,100)) { //片大小100
rehashes += 100;
if (timeInMilliseconds()-start > ms) break; //判断是否超过指定时间
}
return rehashes;
}
//server.c
//指定db渐进式rehash
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;
}
/* This function handles 'background' operations we are required to do
* incrementally in Redis databases, such as active key expiring, resizing,
* rehashing. */
void databasesCron(void) {
// 省略......
/* Resize */
for (j = 0; j < dbs_per_call; j++) { //resize
tryResizeHashTables(resize_db % server.dbnum); // resize
resize_db++;
}
/* Rehash */
if (server.activerehashing) { //rehash
for (j = 0; j < dbs_per_call; j++) {
int work_done = incrementallyRehash(rehash_db);//渐进式
if (work_done) {
/* If the function did some work, stop here, we'll do
* more at the next cron loop. */
break;
} else {
/* If this db didn't need rehash, we'll try the next one. */
rehash_db++;
rehash_db %= server.dbnum;
}
}
}
}
}
4、resize
和expand相反，删除扩展的哈希表 减少内存，但最终使用的expand代码
///* Hash table parameters */ service.h
#define HASHTABLE_MIN_FILL 10 /* Minimal hash table fill 10% */
///dict.c
/* Resize the table to the minimal size that contains all the elements,
* but with the invariant of a USED/BUCKETS ratio near to <= 1 */
int dictResize(dict *d)
{
int minimal;
if (!dict_can_resize || dictIsRehashing(d)) return DICT_ERR;
minimal = d->ht[0].used;
if (minimal < DICT_HT_INITIAL_SIZE)
minimal = DICT_HT_INITIAL_SIZE;
return dictExpand(d, minimal);
}
//server.c
int htNeedsResize(dict *dict) {
long long size, used;
size = dictSlots(dict);
used = dictSize(dict);
return (size > DICT_HT_INITIAL_SIZE && //大于初始size
(used*100/size < HASHTABLE_MIN_FILL)); //使用率小于10%
}
/* If the percentage of used slots in the HT reaches HASHTABLE_MIN_FILL
* we resize the hash table to save memory */
void tryResizeHashTables(int dbid) {
if (htNeedsResize(server.db[dbid].dict))
dictResize(server.db[dbid].dict);
if (htNeedsResize(server.db[dbid].expires))
dictResize(server.db[dbid].expires);
}
总结：整个rehash过程是很简单的，
1.在add，update，get等方法中会持续的rehash
2.有定时任务持续rehash
3.在get等方法中，如果字典在rehash过程中，如果ht[0]找不到，就在ht[1]找；
4.add会在新的hash表中插入
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