VectorDistance - Azure Cosmos DB for NoSQL

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data-bi-name="contributors" title="View all contributors">4 contributors</button> </li></ul> </div> <div id="user-feedback" class="margin-block-xxs display-none-print" data-hide-on-archived> <button id="user-feedback-button" data-test-id="conceptual-feedback-button" class="button button-sm button-clear button-primary" type="button" data-bi-name="user-feedback-button" data-user-feedback-button > <span class="icon" aria-hidden="true"> <span class="docon docon-like"></span> </span> <span>Feedback</span> </button> </div></div><nav id="center-doc-outline" class="doc-outline is-hidden-desktop display-none-print margin-bottom-sm" data-bi-name="intopic toc" aria-label="In this article"> <h2 id="ms--in-this-article" class="title is-6 margin-block-xs">In this article</h2> </nav><p>APPLIES TO: <img src="../../../reusable-content/ce-skilling/azure/media/cosmos-db/yes-icon.svg" role="presentation" data-linktype="relative-path"> NoSQL</p> <p>Returns the similarity score between two specified vectors.</p> <h2 id="syntax">Syntax</h2> <pre><code class="lang-nosql">VectorDistance(<vector_expr_1>, <vector_expr_2>, <bool_expr>, <obj_expr>) </code></pre> <h2 id="arguments">Arguments</h2> <table> <thead> <tr> <th>Parameter</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><strong><code>vector_expr_1</code></strong></td> <td>An array of <code>float32</code> or smaller.</td> </tr> <tr> <td><strong><code>vector_expr_2</code></strong></td> <td>An array of <code>float32</code> or smaller.</td> </tr> <tr> <td><strong><code>bool_expr</code></strong></td> <td>An optional boolean specifying how the computed value is used in an ORDER BY expression. If <code>true</code>, then brute force is used. A value of <code>false</code> uses any index defined on the vector property, if it exists. Default value is <code>false</code>.</td> </tr> <tr> <td><strong><code>obj_expr</code></strong></td> <td>An optional JSON formatted object literal used to specify options for the vector distance calculation. Valid items include <code>distanceFunction</code> and <code>dataType</code>, and <code>searchListSizeMultiplier</code>.</td> </tr> </tbody> </table> <p>Supported parameters for the optional <code>obj_expr</code></p> <table> <thead> <tr> <th>Parameter</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td><strong><code>distanceFunction</code></strong></td> <td>The metric used to compute distance/similarity.</td> </tr> <tr> <td><strong><code>dataType</code></strong></td> <td>The data type of the vectors. <code>float32</code>, <code>int8</code>, <code>uint8</code> values. Default value is <code>float32</code>.</td> </tr> <tr> <td><strong><code>searchListSizeMultiplier</code></strong></td> <td>An integer specifying the size of the search list when conducting a vector search. Increasing this may improve accuracy at the expense of RU cost and latency. Min=1, Default=5, Max=100.</td> </tr> </tbody> </table> <p>Supported metrics for <code>distanceFunction</code> are:</p> <ul> <li><a href="https://en.wikipedia.org/wiki/Cosine_similarity" data-linktype="external"><code>cosine</code></a>, which has values from <code>-1</code> (least similar) to <code>+1</code> (most similar).</li> <li><a href="https://en.wikipedia.org/wiki/Dot_product" data-linktype="external"><code>dotproduct</code></a>, which has values from <code>-∞</code> (<code>-inf</code>) (least similar) to <code>+∞</code> (<code>+inf</code>) (most similar).</li> <li><a href="https://en.wikipedia.org/wiki/Euclidean_distance" data-linktype="external"><code>euclidean</code></a>, which has values from <code>0</code> (most similar) to <code>+∞</code> (<code>+inf</code>) (least similar).</li> </ul> <h2 id="return-types">Return types</h2> <p>Returns a numeric expression that enumerates the similarity score between two expressions.</p> <h2 id="examples">Examples</h2> <p>This first example shows a top 10 vector search query with only the required arguments. One property is projected, along with the score returned by <code>VectorDistance</code>. Then, we user an <code>ORDER BY</code> clause to sort <code>VectorDistance</code> scores in order from most similar to least.</p> <pre><code class="lang-nosql">SELECT TOP 10 s.name, VectorDistance(c.vector1, <query_vector>) FROM c ORDER BY VectorDistance(c.vector1, <query_vector>) </code></pre> <p>This next example also includes optional arguments for <code>VectorDistance</code></p> <pre><code class="lang-nosql">SELECT TOP 10 s.name, VectorDistance(c.vector1, <query_vector>, true, {'distanceFunction':'cosine', 'dataType':'float32'}) FROM c ORDER BY VectorDistance(c.vector1, <query_vector>, true, {'distanceFunction':'cosine', 'dataType':'float32'}) </code></pre> <div class="IMPORTANT"> <p>Important</p> <p>Always use a <code>TOP N</code> clause in the <code>SELECT</code> statement of a query. Otherwise the vector search will try to return many more results and the query will cost more RUs and have higher latency than necessary.</p> </div> <h2 id="remarks">Remarks</h2> <ul> <li>This function requires enabling the <a href="../vector-search#enable-the-vector-indexing-and-search-feature" data-linktype="relative-path">Azure Cosmos DB NoSQL Vector Search feature</a>.</li> <li>This function benefits from a <a href="../../index-policy#vector-indexes" data-linktype="relative-path">vector index</a></li> <li>If <code>false</code> is given as the optional <code>bool_expr</code>, then the vector index defined on the path is used, if one exists. If no index is defined on the vector path, then this function reverts to full scan and incurs higher RU charges and higher latency than if using a vector index.</li> <li>When <code>VectorDistance</code> is used in an <code>ORDER BY</code> clause, no direction needs to be specified for the <code>ORDER BY</code> as the results are always sorted in order of most similar (first) to least similar (last) based on the similarity metric used.</li> <li>The result is expressed as a similarity score.</li> </ul> <h2 id="related-content">Related content</h2> <ul> <li><a href="system-functions" data-linktype="relative-path">System functions</a></li> <li><a href="../vector-search" data-linktype="relative-path">Setup Azure Cosmos DB for NoSQL for vector search</a>.</li> <li><a href="../../index-policy#vector-indexes" data-linktype="relative-path">vector index</a></li> </ul> </div><div id="ms--inline-notifications" class="margin-block-xs" data-bi-name="inline-notification"></div><div 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