哈希算法将任意长度的二进制值映射为固定长度的较小二进制值，这个小的二进制值称为哈希值。哈希值是一段数据唯一且极其紧凑的数值表示形式。如果散列一段明文而且哪怕只更改该段落的一个字母，随后的哈希都将产生不同的值。要找到散列为同一个值的两个不同的输入，在计算上是不可能的，所以数据的哈希值可以检验数据的完整性。
链表查找的时间效率为O(N)，二分法为log2N，B+ Tree为log2N，但Hash链表查找的时间效率为O(1)。
设计高效算法往往需要使用Hash链表，常数级的查找速度是任何别的算法无法比拟的，Hash链表的构造和冲突的不同实现方法对效率当然有一定的影响，然而Hash函数是Hash链表最核心的部分，下面是几款经典软件中使用到的字符串Hash函数实现，通过阅读这些代码，我们可以在Hash算法的执行效率、离散性、空间利用率等方面有比较深刻的了解。
下面分别介绍几个经典软件中出现的字符串Hash函数。
●PHP中出现的字符串Hash函数
static unsigned long hashpjw(char *arKey, unsigned int nKeyLength)
{
unsigned long h = 0, g;
char *arEnd=arKey+nKeyLength;
while (arKey < arEnd) {
h = (h << 4) + *arKey++;
if ((g = (h & 0xF0000000))) {
h = h ^ (g >> 24);
h = h ^ g;
}
}
return h;
}
●OpenSSL中出现的字符串Hash函数
一。
unsigned long lh_strhash(char *str)
{
int i,l;
unsigned long ret=0;
unsigned short *s;
if (str == NULL) return(0);
l=(strlen(str)+1)/2;
s=(unsigned short *)str;
for (i=0; i
ret^=(s[i]<<(i&0×0f));
return(ret);
}
二。
/* The following hash seems to work very well on normal text strings
* no collisions on /usr/dict/words and it distributes on %2^n quite
* well, not as good as MD5, but still good.
*/
unsigned long lh_strhash(const char *c)
{
unsigned long ret=0;
long n;
unsigned long v;
int r;
if ((c == NULL) || (*c == ‘′))
return(ret);
/*
unsigned char b[16];
MD5(c,strlen(c),b);
return(b[0]|(b[1]<<8)|(b[2]<<16)|(b[3]<<24));
*/
n=0×100;
while (*c)
{
v=n|(*c);
n+=0×100;
r= (int)((v>>2)^v)&0×0f;
ret=(ret(32-r));
ret&=0xFFFFFFFFL;
ret^=v*v;
c++;
}
return((ret>>16)^ret);
}
●MySql中出现的字符串Hash函数
#ifndef NEW_HASH_FUNCTION
/* Calc hashvalue for a key */
static uint calc_hashnr(const byte *key,uint length)
{
register uint nr=1, nr2=4;
while (length–)
{
nr^= (((nr & 63)+nr2)*((uint) (uchar) *key++))+ (nr << 8);
nr2+=3;
}
return((uint) nr);
}
/* Calc hashvalue for a key, case indepenently */
static uint calc_hashnr_caseup(const byte *key,uint length)
{
register uint nr=1, nr2=4;
while (length–)
{
nr^= (((nr & 63)+nr2)*((uint) (uchar) toupper(*key++)))+ (nr << 8);
nr2+=3;
}
return((uint) nr);
}
#else
/*
* Fowler/Noll/Vo hash
*
* The basis of the hash algorithm was taken from an idea sent by email to the
* IEEE Posix P1003.2 mailing list from Phong Vo (kpv@research.att.com) and
* Glenn Fowler (gsf@research.att.com). Landon Curt Noll (chongo@toad.com)
* later improved on their algorithm.
*
* The magic is in the interesting relationship between the special prime
* 16777619 (2^24 + 403) and 2^32 and 2^8.
*
* This hash produces the fewest collisions of any function that we’ve seen so
* far, and works well on both numbers and strings.
*/
uint calc_hashnr(const byte *key, uint len)
{
const byte *end=key+len;
uint hash;
for (hash = 0; key < end; key++)
{
hash *= 16777619;
hash ^= (uint) *(uchar*) key;
}
return (hash);
}
uint calc_hashnr_caseup(const byte *key, uint len)
{
const byte *end=key+len;
uint hash;
for (hash = 0; key < end; key++)
{
hash *= 16777619;
hash ^= (uint) (uchar) toupper(*key);
}
return (hash);
}
#endif
Mysql中对字符串Hash函数还区分了大小写
●另一个经典字符串Hash函数
unsigned int hash(char *str)
{
register unsigned int h;
register unsigned char *p;
for(h=0, p = (unsigned char *)str; *p ; p++)
h = 31 * h + *p;
return h;
}
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