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<title>10.4. 重识搜索算法 - Hello 算法</title>
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跳转至
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Hello 算法
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10.4. 重识搜索算法
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M20 11v2H8l5.5 5.5-1.42 1.42L4.16 12l7.92-7.92L13.5 5.5 8 11h12Z"/></svg>
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<nav class="md-search__options" aria-label="查找">
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<a href="javascript:void(0)" class="md-search__icon md-icon" title="分享" aria-label="分享" data-clipboard data-clipboard-text="" data-md-component="search-share" tabindex="-1">
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M18 16.08c-.76 0-1.44.3-1.96.77L8.91 12.7c.05-.23.09-.46.09-.7 0-.24-.04-.47-.09-.7l7.05-4.11c.54.5 1.25.81 2.04.81a3 3 0 0 0 3-3 3 3 0 0 0-3-3 3 3 0 0 0-3 3c0 .24.04.47.09.7L8.04 9.81C7.5 9.31 6.79 9 6 9a3 3 0 0 0-3 3 3 3 0 0 0 3 3c.79 0 1.5-.31 2.04-.81l7.12 4.15c-.05.21-.08.43-.08.66 0 1.61 1.31 2.91 2.92 2.91 1.61 0 2.92-1.3 2.92-2.91A2.92 2.92 0 0 0 18 16.08Z"/></svg>
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M19 6.41 17.59 5 12 10.59 6.41 5 5 6.41 10.59 12 5 17.59 6.41 19 12 13.41 17.59 19 19 17.59 13.41 12 19 6.41Z"/></svg>
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<div class="md-search__scrollwrap" data-md-scrollfix>
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<div class="md-search-result" data-md-component="search-result">
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<div class="md-search-result__meta">
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正在初始化搜索引擎
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</div>
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<ol class="md-search-result__list" role="presentation"></ol>
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</div>
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</div>
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</div>
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</div>
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<div class="md-header__source">
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<a href="https://github.com/krahets/hello-algo" title="前往仓库" class="md-source" data-md-component="source">
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><!--! Font Awesome Free 6.4.0 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2023 Fonticons, Inc.--><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg>
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<div class="md-source__repository">
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krahets/hello-algo
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Hello 算法
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<div class="md-nav__source">
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<a href="https://github.com/krahets/hello-algo" title="前往仓库" class="md-source" data-md-component="source">
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2. 复杂度分析
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2.1. 算法效率评估
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2.2. 时间复杂度
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2.3. 空间复杂度
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2.4. 小结
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3. 数据结构简介
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3.1. 数据结构分类
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3.2. 基本数据类型
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3.3. 数字编码 *
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3.4. 字符编码 *
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3.5. 小结
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4. 数组与链表
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4.1. 数组
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4.2. 链表
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<a href="../../chapter_array_and_linkedlist/list/" class="md-nav__link">
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4.3. 列表
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_array_and_linkedlist/summary/" class="md-nav__link">
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4.4. 小结
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</a>
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</li>
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</ul>
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</nav>
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</li>
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<li class="md-nav__item md-nav__item--nested">
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<input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_6" >
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<div class="md-nav__link md-nav__link--index ">
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<a href="../../chapter_stack_and_queue/">5. 栈与队列</a>
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<label for="__nav_6">
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<span class="md-nav__icon md-icon"></span>
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</label>
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</div>
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<nav class="md-nav" data-md-level="1" aria-labelledby="__nav_6_label" aria-expanded="false">
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<label class="md-nav__title" for="__nav_6">
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<span class="md-nav__icon md-icon"></span>
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5. 栈与队列
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</label>
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<ul class="md-nav__list" data-md-scrollfix>
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<li class="md-nav__item">
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<a href="../../chapter_stack_and_queue/stack/" class="md-nav__link">
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5.1. 栈
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_stack_and_queue/queue/" class="md-nav__link">
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5.2. 队列
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_stack_and_queue/deque/" class="md-nav__link">
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5.3. 双向队列
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_stack_and_queue/summary/" class="md-nav__link">
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5.4. 小结
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</a>
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</li>
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</ul>
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</nav>
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</li>
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<li class="md-nav__item md-nav__item--nested">
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<input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7" >
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<div class="md-nav__link md-nav__link--index ">
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<a href="../../chapter_hashing/">6. 散列表</a>
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<label for="__nav_7">
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<span class="md-nav__icon md-icon"></span>
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</label>
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</div>
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<nav class="md-nav" data-md-level="1" aria-labelledby="__nav_7_label" aria-expanded="false">
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<label class="md-nav__title" for="__nav_7">
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<span class="md-nav__icon md-icon"></span>
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6. 散列表
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</label>
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<ul class="md-nav__list" data-md-scrollfix>
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<li class="md-nav__item">
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<a href="../../chapter_hashing/hash_map/" class="md-nav__link">
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6.1. 哈希表（New）
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_hashing/hash_collision/" class="md-nav__link">
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6.2. 哈希冲突（New）
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_hashing/hash_algorithm/" class="md-nav__link">
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6.3. 哈希算法（New）
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_hashing/summary/" class="md-nav__link">
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6.4. 小结
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</a>
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</li>
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</ul>
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</nav>
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</li>
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<li class="md-nav__item md-nav__item--nested">
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<input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_8" >
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<div class="md-nav__link md-nav__link--index ">
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<a href="../../chapter_tree/">7. 树</a>
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<label for="__nav_8">
|
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<span class="md-nav__icon md-icon"></span>
|
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</label>
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</div>
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<nav class="md-nav" data-md-level="1" aria-labelledby="__nav_8_label" aria-expanded="false">
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<label class="md-nav__title" for="__nav_8">
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<span class="md-nav__icon md-icon"></span>
|
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7. 树
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</label>
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<ul class="md-nav__list" data-md-scrollfix>
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<li class="md-nav__item">
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<a href="../../chapter_tree/binary_tree/" class="md-nav__link">
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7.1. 二叉树
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_tree/binary_tree_traversal/" class="md-nav__link">
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7.2. 二叉树遍历
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_tree/array_representation_of_tree/" class="md-nav__link">
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7.3. 二叉树数组表示
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_tree/binary_search_tree/" class="md-nav__link">
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7.4. 二叉搜索树
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_tree/avl_tree/" class="md-nav__link">
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7.5. AVL 树 *
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_tree/summary/" class="md-nav__link">
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7.6. 小结
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</a>
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</li>
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</ul>
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</nav>
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</li>
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<li class="md-nav__item md-nav__item--nested">
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<input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_9" >
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<div class="md-nav__link md-nav__link--index ">
|
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<a href="../../chapter_heap/">8. 堆</a>
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<label for="__nav_9">
|
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<span class="md-nav__icon md-icon"></span>
|
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</label>
|
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</div>
|
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<nav class="md-nav" data-md-level="1" aria-labelledby="__nav_9_label" aria-expanded="false">
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<label class="md-nav__title" for="__nav_9">
|
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<span class="md-nav__icon md-icon"></span>
|
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8. 堆
|
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</label>
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<ul class="md-nav__list" data-md-scrollfix>
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<li class="md-nav__item">
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<a href="../../chapter_heap/heap/" class="md-nav__link">
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8.1. 堆
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_heap/build_heap/" class="md-nav__link">
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8.2. 建堆操作
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_heap/top_k/" class="md-nav__link">
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8.3. Top-K 问题（New）
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_heap/summary/" class="md-nav__link">
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8.4. 小结
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</a>
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</li>
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</ul>
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</nav>
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</li>
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<li class="md-nav__item md-nav__item--nested">
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<input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_10" >
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<div class="md-nav__link md-nav__link--index ">
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<a href="../../chapter_graph/">9. 图</a>
|
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<label for="__nav_10">
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<span class="md-nav__icon md-icon"></span>
|
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</label>
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</div>
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<nav class="md-nav" data-md-level="1" aria-labelledby="__nav_10_label" aria-expanded="false">
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<label class="md-nav__title" for="__nav_10">
|
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<span class="md-nav__icon md-icon"></span>
|
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9. 图
|
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</label>
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<ul class="md-nav__list" data-md-scrollfix>
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<li class="md-nav__item">
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<a href="../../chapter_graph/graph/" class="md-nav__link">
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9.1. 图
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_graph/graph_operations/" class="md-nav__link">
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9.2. 图基础操作
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_graph/graph_traversal/" class="md-nav__link">
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9.3. 图的遍历
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_graph/summary/" class="md-nav__link">
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9.4. 小结
|
|
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</a>
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</li>
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</ul>
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</nav>
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</li>
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<li class="md-nav__item md-nav__item--active md-nav__item--nested">
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<input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_11" checked>
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<div class="md-nav__link md-nav__link--index ">
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<a href="../">10. 搜索</a>
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<label for="__nav_11">
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<span class="md-nav__icon md-icon"></span>
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</label>
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</div>
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<nav class="md-nav" data-md-level="1" aria-labelledby="__nav_11_label" aria-expanded="true">
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<label class="md-nav__title" for="__nav_11">
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<span class="md-nav__icon md-icon"></span>
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10. 搜索
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</label>
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<ul class="md-nav__list" data-md-scrollfix>
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<li class="md-nav__item">
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<a href="../binary_search/" class="md-nav__link">
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10.1. 二分查找
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../binary_search_edge/" class="md-nav__link">
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10.2. 二分查找边界
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../replace_linear_by_hashing/" class="md-nav__link">
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10.3. 哈希优化策略
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</a>
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</li>
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<li class="md-nav__item md-nav__item--active">
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<input class="md-nav__toggle md-toggle" type="checkbox" id="__toc">
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<label class="md-nav__link md-nav__link--active" for="__toc">
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10.4. 重识搜索算法
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<span class="md-nav__icon md-icon"></span>
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</label>
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<a href="./" class="md-nav__link md-nav__link--active">
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10.4. 重识搜索算法
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</a>
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<nav class="md-nav md-nav--secondary" aria-label="目录">
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<label class="md-nav__title" for="__toc">
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<span class="md-nav__icon md-icon"></span>
|
|
|
目录
|
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</label>
|
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|
<ul class="md-nav__list" data-md-component="toc" data-md-scrollfix>
|
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|
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<li class="md-nav__item">
|
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|
<a href="#1041" class="md-nav__link">
|
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10.4.1. 暴力搜索
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</a>
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</li>
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<li class="md-nav__item">
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<a href="#1042" class="md-nav__link">
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10.4.2. 自适应搜索
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</a>
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</li>
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<li class="md-nav__item">
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<a href="#1043" class="md-nav__link">
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|
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10.4.3. 搜索方法选取
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</a>
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</li>
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</ul>
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</nav>
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</li>
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<li class="md-nav__item">
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<a href="../summary/" class="md-nav__link">
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10.5. 小结
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</a>
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</li>
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</ul>
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</nav>
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</li>
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<li class="md-nav__item md-nav__item--nested">
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<input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_12" >
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<div class="md-nav__link md-nav__link--index ">
|
|
|
<a href="../../chapter_sorting/">11. 排序</a>
|
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|
|
<label for="__nav_12">
|
|
|
<span class="md-nav__icon md-icon"></span>
|
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</label>
|
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</div>
|
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<nav class="md-nav" data-md-level="1" aria-labelledby="__nav_12_label" aria-expanded="false">
|
|
|
<label class="md-nav__title" for="__nav_12">
|
|
|
<span class="md-nav__icon md-icon"></span>
|
|
|
11. 排序
|
|
|
</label>
|
|
|
<ul class="md-nav__list" data-md-scrollfix>
|
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<li class="md-nav__item">
|
|
|
<a href="../../chapter_sorting/sorting_algorithm/" class="md-nav__link">
|
|
|
11.1. 排序算法
|
|
|
</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_sorting/selection_sort/" class="md-nav__link">
|
|
|
11.2. 选择排序
|
|
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_sorting/bubble_sort/" class="md-nav__link">
|
|
|
11.3. 冒泡排序
|
|
|
</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_sorting/insertion_sort/" class="md-nav__link">
|
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|
11.4. 插入排序
|
|
|
</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_sorting/quick_sort/" class="md-nav__link">
|
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11.5. 快速排序
|
|
|
</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_sorting/merge_sort/" class="md-nav__link">
|
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|
11.6. 归并排序
|
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_sorting/heap_sort/" class="md-nav__link">
|
|
|
11.7. 堆排序
|
|
|
</a>
|
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</li>
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<li class="md-nav__item">
|
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<a href="../../chapter_sorting/bucket_sort/" class="md-nav__link">
|
|
|
11.8. 桶排序
|
|
|
</a>
|
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</li>
|
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<li class="md-nav__item">
|
|
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<a href="../../chapter_sorting/counting_sort/" class="md-nav__link">
|
|
|
11.9. 计数排序
|
|
|
</a>
|
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</li>
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<li class="md-nav__item">
|
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|
<a href="../../chapter_sorting/radix_sort/" class="md-nav__link">
|
|
|
11.10. 基数排序
|
|
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</a>
|
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</li>
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<li class="md-nav__item">
|
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<a href="../../chapter_sorting/summary/" class="md-nav__link">
|
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11.11. 小结
|
|
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</a>
|
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</li>
|
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</ul>
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</nav>
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</li>
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<li class="md-nav__item md-nav__item--nested">
|
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<input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_13" >
|
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<div class="md-nav__link md-nav__link--index ">
|
|
|
<a href="../../chapter_backtracking/">12. 回溯</a>
|
|
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|
|
<label for="__nav_13">
|
|
|
<span class="md-nav__icon md-icon"></span>
|
|
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</label>
|
|
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|
</div>
|
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|
<nav class="md-nav" data-md-level="1" aria-labelledby="__nav_13_label" aria-expanded="false">
|
|
|
<label class="md-nav__title" for="__nav_13">
|
|
|
<span class="md-nav__icon md-icon"></span>
|
|
|
12. 回溯
|
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</label>
|
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<ul class="md-nav__list" data-md-scrollfix>
|
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<li class="md-nav__item">
|
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|
<a href="../../chapter_backtracking/backtracking_algorithm/" class="md-nav__link">
|
|
|
12.1. 回溯算法
|
|
|
</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_backtracking/permutations_problem/" class="md-nav__link">
|
|
|
12.2. 全排列问题
|
|
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_backtracking/subset_sum_problem/" class="md-nav__link">
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|
12.3. 子集和问题（New）
|
|
|
</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_backtracking/n_queens_problem/" class="md-nav__link">
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|
12.4. N 皇后问题
|
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</a>
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</li>
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<li class="md-nav__item">
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<a href="../../chapter_backtracking/summary/" class="md-nav__link">
|
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12.5. 小结
|
|
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</a>
|
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</li>
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</ul>
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</nav>
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</li>
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<li class="md-nav__item md-nav__item--nested">
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<input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_14" >
|
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<div class="md-nav__link md-nav__link--index ">
|
|
|
<a href="../../chapter_dynamic_programming/">13. 动态规划</a>
|
|
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|
|
<label for="__nav_14">
|
|
|
<span class="md-nav__icon md-icon"></span>
|
|
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</label>
|
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|
</div>
|
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|
<nav class="md-nav" data-md-level="1" aria-labelledby="__nav_14_label" aria-expanded="false">
|
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|
<label class="md-nav__title" for="__nav_14">
|
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|
<span class="md-nav__icon md-icon"></span>
|
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13. 动态规划
|
|
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</label>
|
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<ul class="md-nav__list" data-md-scrollfix>
|
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<li class="md-nav__item">
|
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<a href="../../chapter_dynamic_programming/intro_to_dynamic_programming/" class="md-nav__link">
|
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|
13.1. 初识动态规划
|
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|
</a>
|
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</li>
|
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</ul>
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</nav>
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</li>
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<label class="md-nav__link" for="__nav_15" id="__nav_15_label" tabindex="0">
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14. 附录
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14. 附录
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<li class="md-nav__item">
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<a href="../../chapter_appendix/installation/" class="md-nav__link">
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14.1. 编程环境安装
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</a>
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14.2. 一起参与创作
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</a>
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<a href="#1041" class="md-nav__link">
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10.4.1. 暴力搜索
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</a>
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<a href="#1042" class="md-nav__link">
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10.4.2. 自适应搜索
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</a>
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<a href="#1043" class="md-nav__link">
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10.4.3. 搜索方法选取
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</a>
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<a href="https://github.com/krahets/hello-algo/tree/main/docs/chapter_searching/searching_algorithm_revisited.md" title="编辑此页" class="md-content__button md-icon">
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M10 20H6V4h7v5h5v3.1l2-2V8l-6-6H6c-1.1 0-2 .9-2 2v16c0 1.1.9 2 2 2h4v-2m10.2-7c.1 0 .3.1.4.2l1.3 1.3c.2.2.2.6 0 .8l-1 1-2.1-2.1 1-1c.1-.1.2-.2.4-.2m0 3.9L14.1 23H12v-2.1l6.1-6.1 2.1 2.1Z"/></svg>
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</a>
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<h1 id="104">10.4. 重识搜索算法<a class="headerlink" href="#104" title="Permanent link">¶</a></h1>
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<p>「搜索算法 Searching Algorithm」用于在数据结构（例如数组、链表、树或图）中搜索一个或一组满足特定条件的元素。</p>
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<p>根据实现思路，搜索算法总体可分为两种：</p>
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<ul>
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<li><strong>通过遍历数据结构来定位目标元素</strong>，例如数组、链表、树和图的遍历等。</li>
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<li><strong>利用数据组织结构或数据包含的先验信息，实现高效元素查找</strong>，例如二分查找、哈希查找和二叉搜索树查找等。</li>
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</ul>
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<p>不难发现，这些知识点都已在前面的章节中介绍过，因此搜索算法对于我们来说并不陌生。在本节中，我们将从更加系统的视角切入，重新审视搜索算法。</p>
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<h2 id="1041">10.4.1. 暴力搜索<a class="headerlink" href="#1041" title="Permanent link">¶</a></h2>
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<p>暴力搜索通过遍历数据结构的每个元素来定位目标元素。</p>
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<ul>
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<li>「线性搜索」适用于数组和链表等线性数据结构。它从数据结构的一端开始，逐个访问元素，直到找到目标元素或到达另一端仍没有找到目标元素为止。</li>
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<li>「广度优先搜索」和「深度优先搜索」是图和树的两种遍历策略。广度优先搜索从初始节点开始逐层搜索，由近及远地访问各个节点。深度优先搜索是从初始节点开始，沿着一条路径走到头为止，再回溯并尝试其他路径，直到遍历完整个数据结构。</li>
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</ul>
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<p>暴力搜索的优点是简单且通用性好，<strong>无需对数据做预处理和借助额外的数据结构</strong>。</p>
|
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<p>然而，<strong>此类算法的时间复杂度为 <span class="arithmatex">\(O(n)\)</span></strong> ，其中 <span class="arithmatex">\(n\)</span> 为元素数量，因此在数据量较大的情况下性能较差。</p>
|
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|
<h2 id="1042">10.4.2. 自适应搜索<a class="headerlink" href="#1042" title="Permanent link">¶</a></h2>
|
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<p>自适应搜索利用数据的特有属性（例如有序性）来优化搜索过程，从而更高效地定位目标元素。</p>
|
|
|
<ul>
|
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<li>「二分查找」利用数据的有序性实现高效查找，仅适用于数组。</li>
|
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<li>「哈希查找」利用哈希表将搜索数据和目标数据建立为键值对映射，从而实现查询操作。</li>
|
|
|
<li>「树查找」在特定的树结构（例如二叉搜索树）中，基于比较节点值来快速排除节点，从而定位目标元素。</li>
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|
|
</ul>
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<p>此类算法的优点是效率高，<strong>时间复杂度可达到 <span class="arithmatex">\(O(\log n)\)</span> 甚至 <span class="arithmatex">\(O(1)\)</span></strong> 。</p>
|
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|
<p>然而，<strong>使用这些算法往往需要对数据进行预处理</strong>。例如，二分查找需要预先对数组进行排序，哈希查找和树查找都需要借助额外的数据结构，维护这些数据结构也需要额外的时间和空间开支。</p>
|
|
|
<div class="admonition note">
|
|
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<p class="admonition-title">Note</p>
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<p>自适应搜索算法常被称为查找算法，<strong>主要关注在特定数据结构中快速检索目标元素</strong>。</p>
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</div>
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<h2 id="1043">10.4.3. 搜索方法选取<a class="headerlink" href="#1043" title="Permanent link">¶</a></h2>
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<p>给定大小为 <span class="arithmatex">\(n\)</span> 的一组数据，我们可以使用线性搜索、二分查找、树查找、哈希查找等多种方法在该数据中搜索目标元素。各个方法的工作原理如下图所示。</p>
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<p><img alt="多种搜索策略" src="../searching_algorithm_revisited.assets/searching_algorithms.png" /></p>
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<p align="center"> Fig. 多种搜索策略 </p>
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<p>上述几种方法的操作效率与特性如下表所示。</p>
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<div class="center-table">
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<table>
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<thead>
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<tr>
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<th></th>
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<th>线性搜索</th>
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<th>二分查找</th>
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<th>树查找</th>
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<th>哈希查找</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td>查找元素</td>
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<td><span class="arithmatex">\(O(n)\)</span></td>
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<td><span class="arithmatex">\(O(\log n)\)</span></td>
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<td><span class="arithmatex">\(O(\log n)\)</span></td>
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<td><span class="arithmatex">\(O(1)\)</span></td>
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</tr>
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<tr>
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<td>插入元素</td>
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<td><span class="arithmatex">\(O(1)\)</span></td>
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<td><span class="arithmatex">\(O(n)\)</span></td>
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<td><span class="arithmatex">\(O(\log n)\)</span></td>
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<td><span class="arithmatex">\(O(1)\)</span></td>
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</tr>
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<tr>
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<td>删除元素</td>
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<td><span class="arithmatex">\(O(n)\)</span></td>
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<td><span class="arithmatex">\(O(n)\)</span></td>
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<td><span class="arithmatex">\(O(\log n)\)</span></td>
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|
<td><span class="arithmatex">\(O(1)\)</span></td>
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</tr>
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<tr>
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<td>额外空间</td>
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<td><span class="arithmatex">\(O(1)\)</span></td>
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<td><span class="arithmatex">\(O(1)\)</span></td>
|
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|
<td><span class="arithmatex">\(O(n)\)</span></td>
|
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|
<td><span class="arithmatex">\(O(n)\)</span></td>
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</tr>
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<tr>
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<td>数据预处理</td>
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<td>/</td>
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<td>排序 <span class="arithmatex">\(O(n \log n)\)</span></td>
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<td>建树 <span class="arithmatex">\(O(n \log n)\)</span></td>
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<td>建哈希表 <span class="arithmatex">\(O(n)\)</span></td>
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</tr>
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<tr>
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<td>数据是否有序</td>
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<td>无序</td>
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<td>有序</td>
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<td>有序</td>
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<td>无序</td>
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</tr>
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</tbody>
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</table>
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</div>
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<p>除了以上表格内容，搜索算法的选择还取决于数据体量、搜索性能要求、数据查询与更新频率等。</p>
|
|
|
<p><strong>线性搜索</strong></p>
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|
|
<ul>
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|
|
<li>通用性较好，无需任何数据预处理操作。假如我们仅需查询一次数据，那么其他三种方法的数据预处理的时间比线性搜索的时间还要更长。</li>
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<li>适用于体量较小的数据，此情况下时间复杂度对效率影响较小。</li>
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<li>适用于数据更新频率较高的场景，因为该方法不需要对数据进行任何额外维护。</li>
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</ul>
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<p><strong>二分查找</strong></p>
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<ul>
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<li>适用于大数据量的情况，效率表现稳定，最差时间复杂度为 <span class="arithmatex">\(O(\log n)\)</span> 。</li>
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<li>数据量不能过大，因为存储数组需要连续的内存空间。</li>
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<li>不适用于高频增删数据的场景，因为维护有序数组的开销较大。</li>
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</ul>
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<p><strong>哈希查找</strong></p>
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<ul>
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<li>适合对查询性能要求很高的场景，平均时间复杂度为 <span class="arithmatex">\(O(1)\)</span> 。</li>
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<li>不适合需要有序数据或范围查找的场景，因为哈希表无法维护数据的有序性。</li>
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<li>对哈希函数和哈希冲突处理策略的依赖性较高，具有较大的性能劣化风险。</li>
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<li>不适合数据量过大的情况，因为哈希表需要额外空间来最大程度地减少冲突，从而提供良好的查询性能。</li>
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</ul>
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<p><strong>树查找</strong></p>
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<ul>
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|
<li>适用于海量数据，因为树节点在内存中是离散存储的。</li>
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|
<li>适合需要维护有序数据或范围查找的场景。</li>
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|
<li>在持续增删节点的过程中，二叉搜索树可能产生倾斜，时间复杂度劣化至 <span class="arithmatex">\(O(n)\)</span> 。</li>
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|
<li>若使用 AVL 树或红黑树，则各项操作可在 <span class="arithmatex">\(O(\log n)\)</span> 效率下稳定运行，但维护树平衡的操作会增加额外开销。</li>
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</ul>
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<h2 id="__comments">评论</h2>
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