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<li>两个不同的 key 经过哈希函数可能得到相同的桶索引，进而发生哈希冲突，导致查询错误。</li> <li>两个不同的 key 经过哈希函数可能得到相同的桶索引，进而发生哈希冲突，导致查询错误。</li>
<li>缓解哈希冲突的途径有两种：哈希表扩容、优化哈希表的表示方式。</li> <li>缓解哈希冲突的途径有两种：哈希表扩容、优化哈希表的表示方式。</li>
<li>负载因子定义为哈希表中元素数量除以桶槽数量，体现哈希冲突的严重程度，常用作哈希表扩容的触发条件。与数组扩容的原理类似，哈希表扩容操作开销也很大。</li> <li>负载因子定义为哈希表中元素数量除以桶槽数量，体现哈希冲突的严重程度，常用作哈希表扩容的触发条件。与数组扩容的原理类似，哈希表扩容操作开销也很大。</li>
<li>链式地址考虑将单个元素转化成一个链表，将所有冲突元素都存储在一个链表中，从而解决哈希冲突。而为了提升查询效率，可以把链表转化为 AVL 树或红黑树，</li> <li>链式地址考虑将单个元素转化成一个链表，将所有冲突元素都存储在一个链表中，从而解决哈希冲突。链表过长会导致查询效率变低，可以通过把链表转化为 AVL 树或红黑树来解决。</li>
<li>开放寻址通过多次探测来解决哈希冲突。线性探测使用固定步长，缺点是不能删除元素且容易产生聚集。多次哈希使用多个哈希函数进行探测，相对线性探测不容易产生聚集，代价是多个哈希函数增加了计算量。</li> <li>开放寻址通过多次探测来解决哈希冲突。线性探测使用固定步长，缺点是不能删除元素且容易产生聚集。多次哈希使用多个哈希函数进行探测，相对线性探测不容易产生聚集，代价是多个哈希函数增加了计算量。</li>
<li>在工业界中，Java 的 HashMap 采用链式地址、Python 的 Dict 采用开放寻址。</li> <li>在工业界中，Java 的 HashMap 采用链式地址、Python 的 Dict 采用开放寻址。</li>
</ul> </ul>

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<label class="md-overlay" for="__drawer"></label> <label class="md-overlay" for="__drawer"></label>
<div data-md-component="skip"> <div data-md-component="skip">
<a href="#_1" class="md-skip">
跳转至
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<label class="md-nav__title" for="__toc">
<span class="md-nav__icon md-icon"></span>
目录
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<ul class="md-nav__list" data-md-component="toc" data-md-scrollfix>
<li class="md-nav__item">
<a href="#_1" class="md-nav__link">
作者简介
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<h1>Home</h1>
<div class="tabbed-set tabbed-alternate" data-tabs="1:1"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1"> </label></div> <div class="tabbed-set tabbed-alternate" data-tabs="1:1"><input checked="checked" id="__tabbed_1_1" name="__tabbed_1" type="radio" /><div class="tabbed-labels"><label for="__tabbed_1_1"> </label></div>
<div class="tabbed-content"> <div class="tabbed-content">
<div class="tabbed-block"> <div class="tabbed-block">
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<p>近两年来，我在力扣上分享了一些题解和算法文章，回复了许多读者的评论问题，遇到最多的一类问题则是“如何入门学习算法”。我逐渐也对这个问题好奇了起来。</p> <p>近两年来，我在力扣上分享了一些题解和算法文章，回复了许多读者的评论问题，遇到最多的一类问题则是“如何入门学习算法”。我逐渐也对这个问题好奇了起来。</p>
<p>两眼一抹黑地刷题应该是最受欢迎的方式。刷题就如同玩“扫雷”游戏一样，基础好的同学可以顺利地将地雷逐个排掉，而基础不足的同学很可能被炸的满头是包，并在受挫中渐渐退缩。通读教材书籍也是常用方法，但对于面向求职的同学来说，毕业季、投递简历、应付笔面试已经占用大部分精力，厚重的书本也因此成为巨大的挑战。</p> <p>两眼一抹黑地刷题应该是最受欢迎的方式。刷题就如同玩“扫雷”游戏一样，基础好的同学可以顺利地将地雷逐个排掉，而基础不足的同学很可能被炸的满头是包，并在受挫中渐渐退缩。通读教材书籍也是常用方法，但对于面向求职的同学来说，毕业季、投递简历、应付笔面试已经占用大部分精力，厚重的书本也因此成为巨大的挑战。</p>
<p>如果你也有上述烦恼，那么很幸运这本书找到了你。本书是我对于该问题给出的答案，虽然不一定正确，但至少代表一次积极的尝试。这本书虽然不足以让你直接拿到 Offer ，但可以带领你探索出算法知识的“地图”，让你了解不同“地雷”的形状大小和分布位置，并使你掌握各种“排雷方法”。</p> <p>如果你也有上述烦恼，那么很幸运这本书找到了你。本书是我对于该问题给出的答案，虽然不一定正确，但至少代表一次积极的尝试。这本书虽然不足以让你直接拿到 Offer ，但会引导你探索数据结构与算法的“知识地图”，带你了解不同“地雷”的形状大小和分布位置，让你掌握各种“排雷方法”。有了这些本领，相信你可以更加得心应手地开展算法学习，逐步搭建起完整的知识体系。</p>
<p>本书提供可一键运行的源代码，已被翻译至 12 种编程语言，托管在 <a href="https://github.com/krahets/hello-algo">github.com/krahets/hello-algo</a> 仓库。发行版 PDF 的更新周期较长，想看最新内容的小伙伴可以前往 <a href="https://www.hello-algo.com/">www.hello-algo.com</a> 网页版。</p> <p>本书提供可一键运行的源代码，已被翻译至十余种编程语言，托管在 <a href="https://github.com/krahets/hello-algo">github.com/krahets/hello-algo</a> 仓库。发行版 PDF 的更新周期较长，想看最新内容的小伙伴可以前往 <a href="https://www.hello-algo.com/">www.hello-algo.com</a> 网页版。</p>
<p>希望这本书能够帮助你把知识的“雪球”滚起来，让你做到心中有数、不慌不忙。加油！</p> <h3 align="left"> 作者简介 </h3>
<h3 id="_1">作者简介<a class="headerlink" href="#_1" title="Permanent link">&para;</a></h3>
<p>靳宇栋 (Krahets)，大厂高级算法工程师，上海交通大学硕士。力扣（LeetCode）全网阅读量最高博主，其 LeetBook《图解算法数据结构》已被订阅 22 万本。</p> <p>靳宇栋 (Krahets)，大厂高级算法工程师，上海交通大学硕士。力扣（LeetCode）全网阅读量最高博主，其 LeetBook《图解算法数据结构》已被订阅 22 万本。</p>
<hr /> <hr />
<h2 align="center"> 致谢 </h2> <h2 align="center"> 致谢 </h2>

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