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chapter_hashing/hash_algorithm/index.html
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M6 2h12v6l-4 4 4 4v6H6v-6l4-4-4-4V2m10 14.5-4-4-4 4V20h8v-3.5m-4-5 4-4V4H8v3.5l4 4M10 6h4v.75l-2 2-2-2V6Z"/></svg>
<span class="md-ellipsis">
第 2 章 &nbsp; 复杂度
第 2 章 &nbsp; 时空复杂度
</span>
@@ -560,7 +560,7 @@
<nav class="md-nav" data-md-level="1" aria-labelledby="__nav_3_label" aria-expanded="false">
<label class="md-nav__title" for="__nav_3">
<span class="md-nav__icon md-icon"></span>
第 2 章 &nbsp; 复杂度
第 2 章 &nbsp; 时空复杂度
</label>
<ul class="md-nav__list" data-md-scrollfix>
@@ -1157,7 +1157,7 @@
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19.3 17.89c1.32-2.1.7-4.89-1.41-6.21a4.52 4.52 0 0 0-6.21 1.41C10.36 15.2 11 18 13.09 19.3c1.47.92 3.33.92 4.8 0L21 22.39 22.39 21l-3.09-3.11m-2-.62c-.98.98-2.56.97-3.54 0-.97-.98-.97-2.56.01-3.54.97-.97 2.55-.97 3.53 0 .96.99.95 2.57-.03 3.54h.03M19 4H5a2 2 0 0 0-2 2v12a2 2 0 0 0 2 2h5.81a6.3 6.3 0 0 1-1.31-2H5v-4h4.18c.16-.71.43-1.39.82-2H5V8h6v2.81a6.3 6.3 0 0 1 2-1.31V8h6v2a6.499 6.499 0 0 1 2 2V6a2 2 0 0 0-2-2Z"/></svg>
<span class="md-ellipsis">
第 6 章 &nbsp; 散列表
第 6 章 &nbsp; 哈希表
</span>
@@ -1172,7 +1172,7 @@
<nav class="md-nav" data-md-level="1" aria-labelledby="__nav_7_label" aria-expanded="true">
<label class="md-nav__title" for="__nav_7">
<span class="md-nav__icon md-icon"></span>
第 6 章 &nbsp; 散列表
第 6 章 &nbsp; 哈希表
</label>
<ul class="md-nav__list" data-md-scrollfix>
@@ -3903,16 +3903,16 @@
<div class="arithmatex">\[
\begin{aligned}
\text{modulus} &amp; = 9 \newline
\text{key} &amp; = \{ 0, 3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, \cdots \} \newline
\text{hash} &amp; = \{ 0, 3, 6, 0, 3, 6, 0, 3, 6, 0, 3, 6,\cdots \}
\text{key} &amp; = \{ 0, 3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, \dots \} \newline
\text{hash} &amp; = \{ 0, 3, 6, 0, 3, 6, 0, 3, 6, 0, 3, 6,\dots \}
\end{aligned}
\]</div>
<p>如果输入 <code>key</code> 恰好满足这种等差数列的数据分布，那么哈希值就会出现聚堆，从而加重哈希冲突。现在，假设将 <code>modulus</code> 替换为质数 <span class="arithmatex">\(13\)</span> ，由于 <code>key</code> 和 <code>modulus</code> 之间不存在公约数，输出的哈希值的均匀性会明显提升。</p>
<div class="arithmatex">\[
\begin{aligned}
\text{modulus} &amp; = 13 \newline
\text{key} &amp; = \{ 0, 3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, \cdots \} \newline
\text{hash} &amp; = \{ 0, 3, 6, 9, 12, 2, 5, 8, 11, 1, 4, 7, \cdots \}
\text{key} &amp; = \{ 0, 3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, \dots \} \newline
\text{hash} &amp; = \{ 0, 3, 6, 9, 12, 2, 5, 8, 11, 1, 4, 7, \dots \}
\end{aligned}
\]</div>
<p>值得说明的是，如果能够保证 <code>key</code> 是随机均匀分布的，那么选择质数或者合数作为模数都是可以的，它们都能输出均匀分布的哈希值。而当 <code>key</code> 的分布存在某种周期性时，对合数取模更容易出现聚集现象。</p>