php-perl雜湊演算法實現

 php-perl雜湊實現演算法–DJBX33A(Daniel J. Bernstein, Times 33 with Addition)APR雜湊預設演算法

 代碼如下:APR_DECLARE_NONSTD(unsigned int) apr_hashfunc_default(const char *char_key,                                                      apr_ssize_t *klen){    unsigned int hash = 0;    const unsigned char *key = (const unsigned char *)char_key;    const unsigned char *p;    apr_ssize_t i;     /*     * This is the popular `times 33' hash algorithm which is used by     * perl and also appears in Berkeley DB. This is one of the best     * known hash functions for strings because it is both computed     * very fast and distributes very well.     *     * The originator may be Dan Bernstein but the code in Berkeley DB     * cites Chris Torek as the source. The best citation I have found     * is "Chris Torek, Hash function for text in C, Usenet message     * <27038@mimsy.umd.edu> in comp.lang.c , October, 1990." in Rich     * Salz's USENIX 1992 paper about INN which can be found at     * .     *     * The magic of number 33, i.e. why it works better than many other     * constants, prime or not, has never been adequately explained by     * anyone. So I try an explanation: if one experimentally tests all     * multipliers between 1 and 256 (as I did while writing a low-level     * data structure library some time ago) one detects that even     * numbers are not useable at all. The remaining 128 odd numbers     * (except for the number 1) work more or less all equally well.     * They all distribute in an acceptable way and this way fill a hash     * table with an average percent of approx. 86%.     *     * If one compares the chi^2 values of the variants (see     * Bob Jenkins ``Hashing Frequently Asked Questions'' at     * http://burtleburtle.net/bob/hash/hashfaq.html for a description     * of chi^2), the number 33 not even has the best value. But the     * number 33 and a few other equally good numbers like 17, 31, 63,     * 127 and 129 have nevertheless a great advantage to the remaining     * numbers in the large set of possible multipliers: their multiply     * operation can be replaced by a faster operation based on just one     * shift plus either a single addition or subtraction operation. And     * because a hash function has to both distribute good _and_ has to     * be very fast to compute, those few numbers should be preferred.     *     *                  -- Ralf S. Engelschall      */     if (*klen == APR_HASH_KEY_STRING) {        for (p = key; *p; p++) {            hash = hash * 33 + *p;        }        *klen = p - key;    }    else {        for (p = key, i = *klen; i; i--, p++) {            hash = hash * 33 + *p;        }    }    return hash;}  對函數注釋部分的翻譯: 這是很出名的times33雜湊演算法,此演算法被perl語言採用並在Berkeley DB中出現.它是已知的最好的雜湊演算法之一,在處理以字串為索引值的雜湊時,有著極快的計算效率和很好雜湊分布.最早提出這個演算法的是Dan Bernstein,但是原始碼確實由Clris Torek在Berkeley DB出實作的.我找到的最確切的引文中這樣說”Chris Torek,C語言文本雜湊函數,Usenet訊息<<27038@mimsy.umd.edu> in comp.lang.c ,1990年十月.”在Rich Salz於1992年在USENIX報上發表的討論INN的文章中提到.這篇文章可以在上找到. 33這個奇妙的數字,為什麼它能夠比其他數值效果更好呢?無論重要與否,卻從來沒有人能夠充分說明其中的原因.因此在這裡,我來試著解釋一下.如果某人試著測試1到256之間的每個數字(就像我前段時間寫的一個底層資料結構庫那樣),他會發現,沒有哪一個數位表現是特別突出的.其中的128個奇數(1除外)的表現都差不多,都能夠達到一個能接受的雜湊分布,平均分布率大概是86%. 如果比較這128個奇數中的方差值(gibbon:統計術語,表示隨機變數與它的數學期望之間的平均偏離程度)的話(見Bob Jenkins的<雜湊常見疑問>http://burtleburtle.net/bob/hash/hashfaq.html,中對平方差的描述),數字33並不是表現最好的一個.(gibbon:這裡按照我的理解,照常理,應該是方差越小穩定,但是由於這裡不清楚作者方差的計算公式,以及在雜湊離散表,是不是離散度越大越好,所以不得而知這裡的表現好是指方差值大還是指方差值小),但是數字33以及其他一些同樣好的數字比如 17,31,63,127和129對於其他剩下的數字,在面對大量的雜湊運算時,仍然有一個大大的優勢,就是這些數字能夠將乘法用位元運算配合加減法來替換,這樣的運算速度會提高.畢竟一個好的雜湊演算法要求既有好的分布,也要有高的計算速度,能同時達到這兩點的數字很少.