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<title data-rh="true">High Cardinality Relationships | DataHub</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://docs.datahub.com/docs/advanced/high-cardinality"><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-default-current"><meta data-rh="true" name="docsearch:version" content="current"><meta data-rh="true" name="docsearch:docusaurus_tag" content="docs-default-current"><meta data-rh="true" property="og:title" content="High Cardinality Relationships | DataHub"><meta data-rh="true" name="description" content="As explained in What is a Relationship, the raw metadata for forming relationships is captured directly inside of a Metadata Aspect. The most natural way to model this is using an array, e.g. a group membership aspect contains an array of user URNs. However, this poses some challenges when the cardinality of the relationship is expected to be large (say, greater than 10,000). The aspect becomes large in size, which leads to slow update and retrieval. It may even exceed the underlying limit of the document store, which is often in the range of a few MBs. Furthermore, sending large messages (&gt; 1MB) over Kafka requires special tuning and is generally discouraged."><meta data-rh="true" property="og:description" content="As explained in What is a Relationship, the raw metadata for forming relationships is captured directly inside of a Metadata Aspect. The most natural way to model this is using an array, e.g. a group membership aspect contains an array of user URNs. However, this poses some challenges when the cardinality of the relationship is expected to be large (say, greater than 10,000). The aspect becomes large in size, which leads to slow update and retrieval. It may even exceed the underlying limit of the document store, which is often in the range of a few MBs. Furthermore, sending large messages (&gt; 1MB) over Kafka requires special tuning and is generally discouraged."><link data-rh="true" rel="icon" href="/img/favicon.ico"><link data-rh="true" rel="canonical" href="https://docs.datahub.com/docs/advanced/high-cardinality"><link data-rh="true" rel="alternate" href="https://docs.datahub.com/docs/advanced/high-cardinality" hreflang="en"><link data-rh="true" rel="alternate" href="https://docs.datahub.com/docs/advanced/high-cardinality" hreflang="x-default"><link data-rh="true" rel="preconnect" href="https://RK0UG797F3-dsn.algolia.net" crossorigin="anonymous"><link rel="alternate" type="application/rss+xml" href="/learn/rss.xml" title="DataHub RSS Feed">
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</a><div class="searchBox_ZlJk"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20" aria-hidden="true"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div id="__docusaurus_skipToContent_fallback" class="main-wrapper mainWrapper_z2l0 docsWrapper_BCFX"><button aria-label="Scroll back to top" class="clean-btn theme-back-to-top-button backToTopButton_sjWU" type="button"></button><div class="docPage__5DB"><main class="docMainContainer_gTbr docMainContainerEnhanced_Uz_u"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_VOVn"><div class="docItemContainer_Djhp"><article><span class="theme-doc-version-badge badge badge--secondary">Version: Next</span><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"><h1>High Cardinality Relationships</h1><p>As explained in <a href="/docs/what/relationship">What is a Relationship</a>, the raw metadata for forming relationships is captured directly inside of a <a href="/docs/what/aspect">Metadata Aspect</a>. The most natural way to model this is using an array, e.g. a group membership aspect contains an array of user <a href="/docs/what/urn">URNs</a>. However, this poses some challenges when the cardinality of the relationship is expected to be large (say, greater than 10,000). The aspect becomes large in size, which leads to slow update and retrieval. It may even exceed the underlying limit of the document store, which is often in the range of a few MBs. Furthermore, sending large messages (&gt; 1MB) over Kafka requires special tuning and is generally discouraged.</p><p>Depending on the type of relationships, there are different strategies for dealing with high cardinality.</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="1n-relationships">1:N Relationships<a href="#1n-relationships" class="hash-link" aria-label="Direct link to 1:N Relationships" title="Direct link to 1:N Relationships"></a></h3><p>When <code>N</code> is large, simply store the relationship as a reverse pointer on the <code>N</code> side, instead of an <code>N</code>-element array on the <code>1</code> side. In other words, instead of doing this</p><div class="codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#bfc7d5;--prism-background-color:#292d3e"><div class="codeBlockContent_biex"><pre tabindex="0" class="prism-code language-text codeBlock_bY9V thin-scrollbar"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#bfc7d5"><span class="token plain">record MemberList {</span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> members: array[UserUrn]</span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain">}</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></di
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