Redis源码剖析之字典

本是古典何须时尚 2022-05-19 13:38 318阅读 0赞

##  ##

以下涉及到的源码均为redis5.0-rc3版本的代码【[点击查看官方源码][Link 1]】

### 文章目录 ###

*   *  
     *  Redis字典
     *  数据结构
     *   *   *  哈希表
             *  字典
     *  关键点
     *   *   *  哈希冲突
             *  空间扩容与释放
     *  操作函数
     *   *   *  创建字典
             *  添加元素
             *  删除元素
             *  rehash操作

## Redis字典 ##

字典是一个key-value形式的数据结构，使用过java中map结构的都应该了解，因为其也是字典；而了解哈希表的也应该不会陌生，因为字典的底层就是哈希表。而redis本身就是一个key-value形式的nosql数据库，足以见得字典结构在redis中的地位。

## 数据结构 ##

字典的定义是在redis源码中的dict.h头文件中，其底层是由哈希表构成。

#### 哈希表 ####

首先来看一下哈希表的结构，在dict.h头文件中是这样定义的：

//哈希表的节点entry
    typedef struct dictEntry {
        void *key;           //键
        union {              //值
            void *val;
            uint64_t u64;
            int64_t s64;
            double d;
        } v;
        struct dictEntry *next;  //next指针
    } dictEntry;
    
    /* This is our hash table structure. Every dictionary has two of this as we
     * implement incremental rehashing, for the old to the new table. */
    typedef struct dictht {    //哈希表
        dictEntry **table;
        unsigned long size; 
        unsigned long sizemask;
        unsigned long used;
    } dictht;

哈希表由如下内容构成：

*  table：哈希表节点数组（指针型）。而节点dictEntry又由key，value及next指针构成；其中value也明确定义了可以是指针、无符号和有符号64位整型、double类型；next指针则是用于解决哈希键的冲突问题。
 *  size：哈希节点数组能容纳的节点个数。
 *  sizemask：值为size-1，是用于计算索引的掩码。
 *  used：节点数组已有节点的个数。

通常，图更能有助于理解，如下所示：  
![这里写图片描述][70]

#### 字典 ####

在dict.h头文件中定义如下：

//特定函数
    typedef struct dictType {
        //计算哈希值
        uint64_t (*hashFunction)(const void *key);
        //复制键
        void *(*keyDup)(void *privdata, const void *key);
        //复制值
        void *(*valDup)(void *privdata, const void *obj);
        //比较键
        int (*keyCompare)(void *privdata, const void *key1, const void *key2);
        //销毁键
        void (*keyDestructor)(void *privdata, void *key);
        //销毁值
        void (*valDestructor)(void *privdata, void *obj);
    } dictType;
    
    typedef struct dict {
        dictType *type;
        void *privdata;
        //哈希表
        dictht ht[2];
        //用于标记是否正在进行rehash操作
        long rehashidx; /* rehashing not in progress if rehashidx == -1 */
        //正在run的迭代器数量
        unsigned long iterators; /* number of iterators currently running */
    } dict;
    
    /* If safe is set to 1 this is a safe iterator, that means, you can call
     * dictAdd, dictFind, and other functions against the dictionary even while
     * iterating. Otherwise it is a non safe iterator, and only dictNext()
     * should be called while iterating. */
    typedef struct dictIterator {
        dict *d;
        long index;
        int table, safe;
        dictEntry *entry, *nextEntry;
        /* unsafe iterator fingerprint for misuse detection. */
        long long fingerprint;
    } dictIterator;

其中，明确标定了需要两个hash表，这是为什么呢？从哈希表结构的定义的代码注释（Every dictionary has two of this as we implement incremental rehashing, for the old to the new table.）可知，一个用于真正存值，另一个则用于在rehash的时候使用。  
字典的示意图如下：  
![这里写图片描述][70 1]

在dict.h头文件中还有这样一行代码，其定义了字典中哈希表hash节点的初始个数为4。

/* This is the initial size of every hash table */
    #define DICT_HT_INITIAL_SIZE     4

从字典结构的源码中还能看见一个dictIterator结构，这便是用于遍历字典的迭代器。

## 关键点 ##

#### 哈希冲突 ####

哈希表插入元素是通过利用key的hash值来计算索引位置，所以会存在冲突情况，而解决冲突则是利用hash节点结构中的next指针。当要插入一个新值的时候，比如entry(key,value)，其插入过程如下图所示：  
![这里写图片描述][70 2]  
哈希冲突的解决过程代码，再后面的**操作函数-添加元素**中可以详见。

#### 空间扩容与释放 ####

空间的扩容和释放过程其实就是rehash过程。在rehash过程正在进行时，会将rehashidx值设置为-1，重新计算key的hash值，然后利用字典中专门为rehash操作而设的一张hash表进行周转迁移数据，具体详见**操作函数-rehash操作**。  
而rehash的过程中，删除、更改和查询元素等操作也是要同时遍历两张hash表的，因为可能你想要的那个元素已被迁移到另一张表中。对于删除元素操作可见**操作函数-删除元素**中的相应代码。

## 操作函数 ##

为了理解一些点，下面将列出部分函数，想知道更多操作的内部细节可浏览源码。此处先给出头文件中宏定义的两个码，后续函数中都会用到。

#define DICT_OK 0
    #define DICT_ERR 1

#### 创建字典 ####

/* Create a new hash table */
    dict *dictCreate(dictType *type,
            void *privDataPtr)
    {
        //创建一个字典指针，分配固定大小内存
        dict *d = zmalloc(sizeof(*d));
        //初始化
        _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;
        //DICT_OK为宏定义的码
        return DICT_OK;
    }

#### 添加元素 ####

字典的添加元素过程是先获取key的hash值，然后再通过掩码计算索引（hash & d->ht\[table\].sizemask），最后锁定索引的位置完成元素的添加。

/* 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)
            计算索引值，如果元素已存在则return
            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));
        //元素的加入总是加在索引处的第一个位置，这一步在解决hash冲突时将新加入的entry->next 指向索引上原有的第一个entry
        entry->next = ht->table[index];
        ht->table[index] = entry;
        ht->used++;
    
        /* Set the hash entry fields. */
        dictSetKey(d, entry, key);
        return entry;
    }
    /* 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++) {
            //用hash值与掩码进行与操作得出索引值
            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;
                    //已存在返回-1
                    return -1;
                }
                he = he->next;
            }
            if (!dictIsRehashing(d)) break;
        }
        //不存在，返回索引位置
        return idx;
    }

#### 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);
    
        //遍历两个hash table并删除给定值，为了避免rehash过程中，用于rehash哈希表存储了要删除的值
        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 */
    }

#### rehash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 */
            //迁移数据
            while(de) {
                uint64_t h;
    
                nextde = de->next;
                /* Get the index in the new hash table */
                //计算新索引
                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) {
            //如果整个rehash操作已完成，则将h[1]和h[0]互换位置
            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;

[Link 1]: https://github.com/antirez/redis/releases
[70]: /images/20220519/d2a6bbbe8304485ebd1a7d5b080c06b7.png
[70 1]: /images/20220519/8bac1e28227a4755a6ee4941649972fa.png
[70 2]: /images/20220519/eeb3c712c63c46428cd102c43b6ad743.png