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<title data-rh="true">Breaking Hash Table | mf</title><meta data-rh="true" name="viewport" content="width=device-width,initial-scale=1"><meta data-rh="true" name="twitter:card" content="summary_large_image"><meta data-rh="true" property="og:url" content="https://blog.mfocko.xyz/algorithms/hash-tables/breaking/"><meta data-rh="true" property="og:locale" content="en"><meta data-rh="true" name="docusaurus_locale" content="en"><meta data-rh="true" name="docsearch:language" content="en"><meta data-rh="true" name="docusaurus_version" content="current"><meta data-rh="true" name="docusaurus_tag" content="docs-algorithms-current"><meta data-rh="true" name="docsearch:version" content="current"><meta data-rh="true" name="docsearch:docusaurus_tag" content="docs-algorithms-current"><meta data-rh="true" property="og:title" content="Breaking Hash Table | mf"><meta data-rh="true" name="description" content="How to get the linear time complexity in a hash table.
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class="col docItemCol_VOVn"><div class="docItemContainer_Djhp"><article><nav class="theme-doc-breadcrumbs breadcrumbsContainer_Z_bl" aria-label="Breadcrumbs"><ul class="breadcrumbs" itemscope="" itemtype="https://schema.org/BreadcrumbList"><li class="breadcrumbs__item"><a aria-label="Home page" class="breadcrumbs__link" href="/"><svg viewBox="0 0 24 24" class="breadcrumbHomeIcon_YNFT"><path d="M10 19v-5h4v5c0 .55.45 1 1 1h3c.55 0 1-.45 1-1v-7h1.7c.46 0 .68-.57.33-.87L12.67 3.6c-.38-.34-.96-.34-1.34 0l-8.36 7.53c-.34.3-.13.87.33.87H5v7c0 .55.45 1 1 1h3c.55 0 1-.45 1-1z" fill="currentColor"></path></svg></a></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item"><a class="breadcrumbs__link" itemprop="item" href="/algorithms/category/hash-tables/"><span itemprop="name">Hash Tables</span></a><meta itemprop="position" content="1"></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item breadcrumbs__item--active"><span class="breadcrumbs__link" itemprop="name">Breaking Hash Table</span><meta itemprop="position" content="2"></li></ul></nav><div class="tocCollapsible_ETCw theme-doc-toc-mobile tocMobile_ITEo"><button type="button" class="clean-btn tocCollapsibleButton_TO0P">On this page</button></div><div class="theme-doc-markdown markdown"><header><h1>Breaking Hash Table</h1></header><p>We will try to break a hash table and discuss possible ways how to prevent such
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issues to occur.</p>
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<h2 class="anchor anchorWithStickyNavbar_LWe7" id="introduction">Introduction<a href="#introduction" class="hash-link" aria-label="Direct link to Introduction" title="Direct link to Introduction"></a></h2>
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<p>Hash tables are very commonly used to represent sets or dictionaries. Even when
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you look up solution to some problem that requires set or dictionary, it is more
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than likely that you'll find something that references usage of the hash table.
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You might think it's the only possible option<sup><a href="#user-content-fn-1" id="user-content-fnref-1" data-footnote-ref="true" aria-describedby="footnote-label">1</a></sup>, or it's the best one<sup><a href="#user-content-fn-2" id="user-content-fnref-2" data-footnote-ref="true" aria-describedby="footnote-label">2</a></sup>.</p>
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<p>One of the reasons to prefer hash tables over any other representation is the
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fact that they are <strong>supposed</strong> to be faster than the alternatives, but the
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truth lies somewhere in between.</p>
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<p>One of the other possible implementations of the set is a balanced tree. Majorly
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occurring implementations rely on the <em>red-black tree</em>, but you may see also
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others like an <em>AVL tree</em><sup><a href="#user-content-fn-3" id="user-content-fnref-3" data-footnote-ref="true" aria-describedby="footnote-label">3</a></sup> or <em>B-tree</em><sup><a href="#user-content-fn-4" id="user-content-fnref-4" data-footnote-ref="true" aria-describedby="footnote-label">4</a></sup>.</p>
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<h2 class="anchor anchorWithStickyNavbar_LWe7" id="hash-table-v-trees">Hash Table v. Trees<a href="#hash-table-v-trees" class="hash-link" aria-label="Direct link to Hash Table v. Trees" title="Direct link to Hash Table v. Trees"></a></h2>
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<p>The most interesting part are the differences between their implementations. Why
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should you choose hash table, or why should you choose the tree implementation?
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Let's compare the differences one by one.</p>
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<h3 class="anchor anchorWithStickyNavbar_LWe7" id="requirements">Requirements<a href="#requirements" class="hash-link" aria-label="Direct link to Requirements" title="Direct link to Requirements"></a></h3>
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<p>We will start with the fundamentals on which the underlying data structures
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rely. We can also consider them as <em>requirements</em> that must be met to be able to
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use the underlying data structure.</p>
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<p>Hash table relies on the <em>hash function</em> that is supposed to distribute the keys
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in such way that they're evenly spread across the slots where the keys (or
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pairs, for dictionary) are stored, but at the same time they're somewhat unique,
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so no clustering occurs.</p>
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<p>Trees depend on the <em>ordering</em> of the elements. They maintain the elements in
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a sorted fashion, so for any pair of the elements that are used as keys, you
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need to be able to decide which one of them is <em>smaller or equal to</em> the other.</p>
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<p>Hash function can be easily created by using the bits that <em>uniquely</em> identify
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a unique element. On the other hand, ordering may not be as easy to define.</p>
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<div class="theme-admonition theme-admonition-tip admonition_xJq3 alert alert--success"><div class="admonitionHeading_Gvgb"><span class="admonitionIcon_Rf37"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>Example</div><div class="admonitionContent_BuS1"><p>If you are familiar with complex numbers, they are a great example of a key that
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does not have ordering (unless you go element-wise for the sake of storing them
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in a tree; though the ordering <strong>is not</strong> defined on them).</p><p>Hashing them is much easier though, you can just “combine” the hashes of the
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real and imaginary parts of the complex number to get a hash of the complex
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number itself.</p></div></div>
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<h3 class="anchor anchorWithStickyNavbar_LWe7" id="underlying-data-structure">Underlying data structure<a href="#underlying-data-structure" class="hash-link" aria-label="Direct link to Underlying data structure" title="Direct link to Underlying data structure"></a></h3>
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<p>The most obvious difference is the <em>core</em> of the idea behind these data
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structures. Hash tables rely on data being stored in one continuous piece of
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memory (the array) where you can “guess” (by using the hash function) the
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location of what you're looking for in a constant time and also access that
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location in the, said, constant time<sup><a href="#user-content-fn-5" id="user-content-fnref-5" data-footnote-ref="true" aria-describedby="footnote-label">5</a></sup>. In case the hash function is
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<em>not good enough</em><sup><a href="#user-content-fn-6" id="user-content-fnref-6" data-footnote-ref="true" aria-describedby="footnote-label">6</a></sup>, you need to go in <em>blind</em>, and if it comes to the worst,
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check everything.</p>
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<div class="theme-admonition theme-admonition-tip admonition_xJq3 alert alert--success"><div class="admonitionHeading_Gvgb"><span class="admonitionIcon_Rf37"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tl;dr</div><div class="admonitionContent_BuS1"><ul>
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<li>I know where should I look</li>
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<li>I can look there instantenously</li>
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<li>If my guesses are very wrong, I might need to check everything</li>
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</ul></div></div>
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<p>On the other hand, tree implementations rely on the self-balancing trees in
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which you don't get as <em>amazing</em> results as with the hash table, but they're
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<strong>consistent</strong>. Given that we have a self-balancing tree, the height of the tree
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is same for <strong>every</strong> input and therefore checking for any element can take the
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same time even in the worst case.</p>
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||
<div class="theme-admonition theme-admonition-tip admonition_xJq3 alert alert--success"><div class="admonitionHeading_Gvgb"><span class="admonitionIcon_Rf37"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tl;dr</div><div class="admonitionContent_BuS1"><ul>
|
||
<li>I don't know where to look</li>
|
||
<li>I know how to get there</li>
|
||
<li>Wherever I look, it takes me about the same time</li>
|
||
</ul></div></div>
|
||
<p>Let's compare side by side:</p>
|
||
<table><thead><tr><th style="text-align:right">time complexity</th><th style="text-align:center">hash table</th><th style="text-align:center">tree</th></tr></thead><tbody><tr><td style="text-align:right">expected</td><td style="text-align:center">constant</td><td style="text-align:center">depends on the height</td></tr><tr><td style="text-align:right">worst-case</td><td style="text-align:center">gotta check everything</td><td style="text-align:center">depends on the height</td></tr></tbody></table>
|
||
<h2 class="anchor anchorWithStickyNavbar_LWe7" id="major-factors-of-hash-tables">Major Factors of Hash Tables<a href="#major-factors-of-hash-tables" class="hash-link" aria-label="Direct link to Major Factors of Hash Tables" title="Direct link to Major Factors of Hash Tables"></a></h2>
|
||
<p>Let's have a look at the major factors that affect the efficiency and
|
||
functioning of a hash table. We have already mentioned the hash function that
|
||
plays a crucial role, but there are also different ways how you can implement
|
||
a hash table, so we will have a look at those too.</p>
|
||
<h3 class="anchor anchorWithStickyNavbar_LWe7" id="hash-functions">Hash functions<a href="#hash-functions" class="hash-link" aria-label="Direct link to Hash functions" title="Direct link to Hash functions"></a></h3>
|
||
<div class="theme-admonition theme-admonition-info admonition_xJq3 alert alert--info"><div class="admonitionHeading_Gvgb"><span class="admonitionIcon_Rf37"><svg viewBox="0 0 14 16"><path fill-rule="evenodd" d="M7 2.3c3.14 0 5.7 2.56 5.7 5.7s-2.56 5.7-5.7 5.7A5.71 5.71 0 0 1 1.3 8c0-3.14 2.56-5.7 5.7-5.7zM7 1C3.14 1 0 4.14 0 8s3.14 7 7 7 7-3.14 7-7-3.14-7-7-7zm1 3H6v5h2V4zm0 6H6v2h2v-2z"></path></svg></span>info</div><div class="admonitionContent_BuS1"><p>We will start with a definition of hash function in a mathematical definition
|
||
and type signature in some known language:</p><span class="katex-display"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML" display="block"><semantics><mrow><mi>h</mi><mo>:</mo><mi>T</mi><mo>→</mo><mi mathvariant="double-struck">N</mi></mrow><annotation encoding="application/x-tex"> h : T \rightarrow \mathbb{N}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.6944em"></span><span class="mord mathnormal">h</span><span class="mspace" style="margin-right:0.2778em"></span><span class="mrel">:</span><span class="mspace" style="margin-right:0.2778em"></span></span><span class="base"><span class="strut" style="height:0.6833em"></span><span class="mord mathnormal" style="margin-right:0.13889em">T</span><span class="mspace" style="margin-right:0.2778em"></span><span class="mrel">→</span><span class="mspace" style="margin-right:0.2778em"></span></span><span class="base"><span class="strut" style="height:0.6889em"></span><span class="mord mathbb">N</span></span></span></span></span><p>For a type signature we will just take the declaration from C++<sup><a href="#user-content-fn-7" id="user-content-fnref-7" data-footnote-ref="true" aria-describedby="footnote-label">7</a></sup>:</p><div class="language-cpp codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockContent_biex"><pre tabindex="0" class="prism-code language-cpp codeBlock_bY9V thin-scrollbar" style="color:#393A34;background-color:#f6f8fa"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token plain">std</span><span class="token double-colon punctuation" style="color:#393A34">::</span><span class="token plain">size_t </span><span class="token keyword" style="color:#00009f">operator</span><span class="token punctuation" style="color:#393A34">(</span><span class="token punctuation" style="color:#393A34">)</span><span class="token punctuation" style="color:#393A34">(</span><span class="token keyword" style="color:#00009f">const</span><span class="token plain"> T</span><span class="token operator" style="color:#393A34">&</span><span class="token plain"> key</span><span class="token punctuation" style="color:#393A34">)</span><span class="token plain"> </span><span class="token keyword" style="color:#00009f">const</span><span class="token punctuation" style="color:#393A34">;</span><br></span></code></pre><div class="buttonGroup__atx"><button type="button" aria-label="Copy code to clipboard" title="Copy" class="clean-btn"><span class="copyButtonIcons_eSgA" aria-hidden="true"><svg viewBox="0 0 24 24" class="copyButtonIcon_y97N"><path fill="currentColor" d="M19,21H8V7H19M19,5H8A2,2 0 0,0 6,7V21A2,2 0 0,0 8,23H19A2,2 0 0,0 21,21V7A2,2 0 0,0 19,5M16,1H4A2,2 0 0,0 2,3V17H4V3H16V1Z"></path></svg><svg viewBox="0 0 24 24" class="copyButtonSuccessIcon_LjdS"><path fill="currentColor" d="M21,7L9,19L3.5,13.5L4.91,12.09L9,16.17L19.59,5.59L21,7Z"></path></svg></span></button></div></div></div><p>If you compare with the mathematical definition, it is very similar, except for
|
||
the fact that the memory is not unlimited, so the <em>natural number</em> turned into
|
||
an <em>unsigned integer type</em> (on majority of platforms it will be a 64-bit
|
||
unsigned integer).</p></div></div>
|
||
<p>As we have already touched above, hash function gives “a guess” where to look
|
||
for the key (either when doing a look up, or for insertion to guess a suitable
|
||
spot for the insertion).</p>
|
||
<p>Hash functions are expected to have a so-called <em>avalanche effect</em> which means
|
||
that the smallest change to the key should result in a massive change of hash.
|
||
Avalanche effect technically guarantees that even when your data are clustered
|
||
together, it should lower the amount of conflicts that can occur.</p>
|
||
<div class="theme-admonition theme-admonition-tip admonition_xJq3 alert alert--success"><div class="admonitionHeading_Gvgb"><span class="admonitionIcon_Rf37"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>Exercise for the reader</div><div class="admonitionContent_BuS1"><p>Try to give an example of a hash function that is not good at all.</p></div></div>
|
||
<h3 class="anchor anchorWithStickyNavbar_LWe7" id="implementation-details">Implementation details<a href="#implementation-details" class="hash-link" aria-label="Direct link to Implementation details" title="Direct link to Implementation details"></a></h3>
|
||
<p>There are different variations of the hash tables. You've more than likely seen
|
||
an implementation that keeps linked lists for buckets. However there are also
|
||
other variations that use probing instead.</p>
|
||
<p>With regards to the implementation details, we need to mention the fact that
|
||
even with the bounded hash (as we could've seen above), you're not likely to
|
||
have all the buckets for different hashes available. Most common approach to
|
||
this is having a smaller set of buckets and modifying the hash to fit within.</p>
|
||
<p>One of the most common approaches is to keep lengths of the hash tables in the
|
||
powers of 2 which allows bit-masking to take place.</p>
|
||
<div class="theme-admonition theme-admonition-tip admonition_xJq3 alert alert--success"><div class="admonitionHeading_Gvgb"><span class="admonitionIcon_Rf37"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>Example</div><div class="admonitionContent_BuS1"><p>Let's say we're given <code>h = 0xDEADBEEF</code> and we have <code>l = 65536=2^16</code> spots in our
|
||
hash table. What can we do here?</p><p>Well, we definitely have a bigger hash than spots available, so we need to
|
||
“shrink” it somehow. The most common practice is to take the lower bits of the
|
||
hash to represent an index in the table:</p><div class="codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockContent_biex"><pre tabindex="0" class="prism-code language-text codeBlock_bY9V thin-scrollbar" style="color:#393A34;background-color:#f6f8fa"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token plain">h & (l - 1)</span><br></span></code></pre><div class="buttonGroup__atx"><button type="button" aria-label="Copy code to clipboard" title="Copy" class="clean-btn"><span class="copyButtonIcons_eSgA" aria-hidden="true"><svg viewBox="0 0 24 24" class="copyButtonIcon_y97N"><path fill="currentColor" d="M19,21H8V7H19M19,5H8A2,2 0 0,0 6,7V21A2,2 0 0,0 8,23H19A2,2 0 0,0 21,21V7A2,2 0 0,0 19,5M16,1H4A2,2 0 0,0 2,3V17H4V3H16V1Z"></path></svg><svg viewBox="0 0 24 24" class="copyButtonSuccessIcon_LjdS"><path fill="currentColor" d="M21,7L9,19L3.5,13.5L4.91,12.09L9,16.17L19.59,5.59L21,7Z"></path></svg></span></button></div></div></div><p><em>Why does this work?</em> Firstly we subtract 1 from the length (indices run from
|
||
<code>⟨0 ; l - 1⟩</code>, since table is zero-indexed). Therefore if we do <em>binary and</em> on
|
||
any number, we always get a valid index within the table. Let's find the index
|
||
for our hash:</p><div class="codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockContent_biex"><pre tabindex="0" class="prism-code language-text codeBlock_bY9V thin-scrollbar" style="color:#393A34;background-color:#f6f8fa"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token plain">0xDEADBEEF & 0xFFFF = 0xBEEF</span><br></span></code></pre><div class="buttonGroup__atx"><button type="button" aria-label="Copy code to clipboard" title="Copy" class="clean-btn"><span class="copyButtonIcons_eSgA" aria-hidden="true"><svg viewBox="0 0 24 24" class="copyButtonIcon_y97N"><path fill="currentColor" d="M19,21H8V7H19M19,5H8A2,2 0 0,0 6,7V21A2,2 0 0,0 8,23H19A2,2 0 0,0 21,21V7A2,2 0 0,0 19,5M16,1H4A2,2 0 0,0 2,3V17H4V3H16V1Z"></path></svg><svg viewBox="0 0 24 24" class="copyButtonSuccessIcon_LjdS"><path fill="currentColor" d="M21,7L9,19L3.5,13.5L4.91,12.09L9,16.17L19.59,5.59L21,7Z"></path></svg></span></button></div></div></div></div></div>
|
||
<section data-footnotes="true" class="footnotes"><h2 class="anchor anchorWithStickyNavbar_LWe7 sr-only" id="footnote-label">Footnotes<a href="#footnote-label" class="hash-link" aria-label="Direct link to Footnotes" title="Direct link to Footnotes"></a></h2>
|
||
<ol>
|
||
<li id="user-content-fn-1">
|
||
<p>not true <a href="#user-content-fnref-1" data-footnote-backref="" aria-label="Back to reference 1" class="data-footnote-backref">↩</a></p>
|
||
</li>
|
||
<li id="user-content-fn-2">
|
||
<p>also not true <a href="#user-content-fnref-2" data-footnote-backref="" aria-label="Back to reference 2" class="data-footnote-backref">↩</a></p>
|
||
</li>
|
||
<li id="user-content-fn-3">
|
||
<p>actually the first of its kind (the self-balanced trees) <a href="#user-content-fnref-3" data-footnote-backref="" aria-label="Back to reference 3" class="data-footnote-backref">↩</a></p>
|
||
</li>
|
||
<li id="user-content-fn-4">
|
||
<p>Rust chose to implement this instead of the common choice of the red-black
|
||
or AVL tree; main difference lies in the fact that B-trees are not binary
|
||
trees <a href="#user-content-fnref-4" data-footnote-backref="" aria-label="Back to reference 4" class="data-footnote-backref">↩</a></p>
|
||
</li>
|
||
<li id="user-content-fn-5">
|
||
<p>This, of course, does not hold true for the educational implementations of
|
||
the hash tables where conflicts are handled by storing the items in the
|
||
linked lists. In practice linked lists are not that commonly used for
|
||
addressing this issue as it has even worse impact on the efficiency of the
|
||
data structure. <a href="#user-content-fnref-5" data-footnote-backref="" aria-label="Back to reference 5" class="data-footnote-backref">↩</a></p>
|
||
</li>
|
||
<li id="user-content-fn-6">
|
||
<p>My guess is not very good, or it's really bad… <a href="#user-content-fnref-6" data-footnote-backref="" aria-label="Back to reference 6" class="data-footnote-backref">↩</a></p>
|
||
</li>
|
||
<li id="user-content-fn-7">
|
||
<p><a href="https://en.cppreference.com/w/cpp/utility/hash" target="_blank" rel="noopener noreferrer">https://en.cppreference.com/w/cpp/utility/hash</a> <a href="#user-content-fnref-7" data-footnote-backref="" aria-label="Back to reference 7" class="data-footnote-backref">↩</a></p>
|
||
</li>
|
||
</ol>
|
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