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<link rel="canonical" href="https://www.hello-algo.com/chapter_array_and_linkedlist/array/">
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6. &nbsp; &nbsp; 散列表
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<a href="../../chapter_searching/">10. &nbsp; &nbsp; 搜索</a>
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12.1. &nbsp; 回溯算法
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12.2. &nbsp; 全排列问题
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12.3. &nbsp; N 皇后问题（New）
12.3. &nbsp; N 皇后问题
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0. &nbsp; &nbsp; 写在前面
<span class="md-nav__icon md-icon"></span>
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<a href="../../chapter_preface/">0. &nbsp; &nbsp; 写在前面</a>
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1. &nbsp; &nbsp; 引言
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<a href="../">4. &nbsp; &nbsp; 数组与链表</a>
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<a href="../../chapter_stack_and_queue/">5. &nbsp; &nbsp; 栈与队列</a>
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6. &nbsp; &nbsp; 散列表
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<a href="../../chapter_hashing/">6. &nbsp; &nbsp; 散列表</a>
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8. &nbsp; &nbsp; 堆
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<a href="../../chapter_searching/">10. &nbsp; &nbsp; 搜索</a>
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</li>
@@ -1697,7 +1853,7 @@
<li class="md-nav__item">
<a href="../../chapter_backtracking/permutations_problem/" class="md-nav__link">
12.2. &nbsp; 全排列问题（New）
12.2. &nbsp; 全排列问题
</a>
</li>
@@ -1711,7 +1867,7 @@
<li class="md-nav__item">
<a href="../../chapter_backtracking/n_queens_problem/" class="md-nav__link">
12.3. &nbsp; N 皇后问题（New）
12.3. &nbsp; N 皇后问题
</a>
</li>
@@ -1904,7 +2060,7 @@
<li>数组支持随机访问、占用内存较少；但插入和删除元素效率低，且初始化后长度不可变。</li>
<li>链表通过更改指针实现高效的节点插入与删除，且可以灵活调整长度；但节点访问效率低、占用内存较多。常见的链表类型包括单向链表、循环链表、双向链表。</li>
<li>动态数组，又称列表，是基于数组实现的一种数据结构。它保留了数组的优势，同时可以灵活调整长度。列表的出现极大地提高了数组的易用性，但可能导致部分内存空间浪费。</li>
<li>下表总结并对比了数组与链表的各项特性。</li>
<li>下表总结并对比了数组与链表的各项特性与操作效率。</li>
</ul>
<div class="center-table">
<table>
@@ -1936,26 +2092,6 @@
<td>随机访问</td>
<td>插入、删除</td>
</tr>
</tbody>
</table>
</div>
<div class="admonition note">
<p class="admonition-title">缓存局部性</p>
<p>在计算机中，数据读写速度排序是“硬盘 &lt; 内存 &lt; CPU 缓存”。当我们访问数组元素时，计算机不仅会加载它，还会缓存其周围的其他数据，从而借助高速缓存来提升后续操作的执行速度。链表则不然，计算机只能挨个地缓存各个节点，这样的多次“搬运”降低了整体效率。</p>
</div>
<ul>
<li>下表对比了数组与链表在各种操作上的效率。</li>
</ul>
<div class="center-table">
<table>
<thead>
<tr>
<th>操作</th>
<th>数组</th>
<th>链表</th>
</tr>
</thead>
<tbody>
<tr>
<td>访问元素</td>
<td><span class="arithmatex">\(O(1)\)</span></td>
@@ -1974,6 +2110,10 @@
</tbody>
</table>
</div>
<div class="admonition note">
<p class="admonition-title">缓存局部性</p>
<p>在计算机中，数据读写速度排序是“硬盘 &lt; 内存 &lt; CPU 缓存”。当我们访问数组元素时，计算机不仅会加载它，还会缓存其周围的其他数据，从而借助高速缓存来提升后续操作的执行速度。链表则不然，计算机只能挨个地缓存各个节点，这样的多次“搬运”降低了整体效率。</p>
</div>
<h2 id="441-q-a">4.4.1. &nbsp; Q &amp; A<a class="headerlink" href="#441-q-a" title="Permanent link">&para;</a></h2>
<div class="admonition question">
<p class="admonition-title">数组存储在栈上和存储在堆上，对时间效率和空间效率是否有影响？</p>
@@ -2110,13 +2250,13 @@
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