基本概念
所謂完美哈希函數,就是指沒有衝突的哈希函數,即對任意的 key1 != key2 有h(key1) != h(key2)。
設定義域爲X,值域爲Y, n=|X|,m=|Y|,那麼確定有m>=n,若是對於不一樣的key1,key2屬於X,有h(key1)!=h(key2),那麼稱h爲完美哈希函數,當m=n時,h稱爲最小完美哈希函數(這個時候就是一一映射了)。html
在處理大規模字符串數據時,常常要爲每一個字符串分配一個整數ID。這就須要一個字符串的哈希函數。怎麼樣找到一個完美的字符串hash函數呢?
有一些經常使用的字符串hash函數。像BKDRHash,APHash,DJBHash,JSHash,RSHash,SDBMHash,PJWHash,ELFHash等等。都是比較經典的。算法
下面是轉載的對幾個經常使用字符串hash函數的分析:
http://www.cnblogs.com/atlantis13579/archive/2010/02/06/1664792.html編程
經常使用的字符串Hash函數還有ELFHash,APHash等等,都是十分簡單有效的方法。這些函數使用位運算使得每個字符都對最後的函數值產生影響。另外還有以MD5和SHA1爲表明的雜湊函數,這些函數幾乎不可能找到碰撞。函數
經常使用字符串哈希函數有 BKDRHash,APHash,DJBHash,JSHash,RSHash,SDBMHash,PJWHash,ELFHash等等。對於以上幾種哈希函數,我對其進行了一個小小的評測。ui
Hash函數 | 數據1 | 數據2 | 數據3 | 數據4 | 數據1得分 | 數據2得分 | 數據3得分 | 數據4得分 | 平均分 |
BKDRHash | 2 | 0 | 4774 | 481 | 96.55 | 100 | 90.95 | 82.05 | 92.64 |
APHash | 2 | 3 | 4754 | 493 | 96.55 | 88.46 | 100 | 51.28 | 86.28 |
DJBHash | 2 | 2 | 4975 | 474 | 96.55 | 92.31 | 0 | 100 | 83.43 |
JSHash | 1 | 4 | 4761 | 506 | 100 | 84.62 | 96.83 | 17.95 | 81.94 |
RSHash | 1 | 0 | 4861 | 505 | 100 | 100 | 51.58 | 20.51 | 75.96 |
SDBMHash | 3 | 2 | 4849 | 504 | 93.1 | 92.31 | 57.01 | 23.08 | 72.41 |
PJWHash | 30 | 26 | 4878 | 513 | 0 | 0 | 43.89 | 0 | 21.95 |
ELFHash | 30 | 26 | 4878 | 513 | 0 | 0 | 43.89 | 0 | 21.95 |
其中數據1爲100000個字母和數字組成的隨機串哈希衝突個數。數據2爲100000個有意義的英文句子哈希衝突個數。數據3爲數據1的哈希值與 1000003(大素數)求模後存儲到線性表中衝突的個數。數據4爲數據1的哈希值與10000019(更大素數)求模後存儲到線性表中衝突的個數。編碼
通過比較,得出以上平均得分。平均數爲平方平均數。能夠發現,BKDRHash不管是在實際效果仍是編碼實現中,效果都是最突出的。APHash也是較爲優秀的算法。DJBHash,JSHash,RSHash與SDBMHash各有千秋。PJWHash與ELFHash效果最差,但得分類似,其算法本質是類似的。spa
unsigned int SDBMHash(char *str)
{
unsigned int hash = 0;
while (*str)
{
// equivalent to: hash = 65599*hash + (*str++);
hash = (*str++) + (hash << 6) + (hash << 16) - hash;
}
return (hash & 0x7FFFFFFF);
}
// RS Hash Function
unsigned int RSHash(char *str)
{
unsigned int b = 378551;
unsigned int a = 63689;
unsigned int hash = 0;
while (*str)
{
hash = hash * a + (*str++);
a *= b;
}
return (hash & 0x7FFFFFFF);
}
// JS Hash Function
unsigned int JSHash(char *str)
{
unsigned int hash = 1315423911;
while (*str)
{
hash ^= ((hash << 5) + (*str++) + (hash >> 2));
}
return (hash & 0x7FFFFFFF);
}
// P. J. Weinberger Hash Function
unsigned int PJWHash(char *str)
{
unsigned int BitsInUnignedInt = (unsigned int)(sizeof(unsigned int) * 8);
unsigned int ThreeQuarters = (unsigned int)((BitsInUnignedInt * 3) / 4);
unsigned int OneEighth = (unsigned int)(BitsInUnignedInt / 8);
unsigned int HighBits = (unsigned int)(0xFFFFFFFF) << (BitsInUnignedInt - OneEighth);
unsigned int hash = 0;
unsigned int test = 0;
while (*str)
{
hash = (hash << OneEighth) + (*str++);
if ((test = hash & HighBits) != 0)
{
hash = ((hash ^ (test >> ThreeQuarters)) & (~HighBits));
}
}
return (hash & 0x7FFFFFFF);
}
// ELF Hash Function
unsigned int ELFHash(char *str)
{
unsigned int hash = 0;
unsigned int x = 0;
while (*str)
{
hash = (hash << 4) + (*str++);
if ((x = hash & 0xF0000000L) != 0)
{
hash ^= (x >> 24);
hash &= ~x;
}
}
return (hash & 0x7FFFFFFF);
}
// BKDR Hash Function
unsigned int BKDRHash(char *str)
{
unsigned int seed = 131; // 31 131 1313 13131 131313 etc..
unsigned int hash = 0;
while (*str)
{
hash = hash * seed + (*str++);
}
return (hash & 0x7FFFFFFF);
}
// DJB Hash Function
unsigned int DJBHash(char *str)
{
unsigned int hash = 5381;
while (*str)
{
hash += (hash << 5) + (*str++);
}
return (hash & 0x7FFFFFFF);
}
// AP Hash Function
unsigned int APHash(char *str)
{
unsigned int hash = 0;
int i;
for (i=0; *str; i++)
{
if ((i & 1) == 0)
{
hash ^= ((hash << 7) ^ (*str++) ^ (hash >> 3));
}
else
{
hash ^= (~((hash << 11) ^ (*str++) ^ (hash >> 5)));
}
}
return (hash & 0x7FFFFFFF);
}
編程珠璣中的一個hash函數code
//用跟元素個數最接近的質數做爲散列表的大小 #define NHASH 29989 #define MULT 31 unsigned in hash(char *p) { unsigned int h = 0; for (; *p; p++) h = MULT *h + *p; return h % NHASH; }