<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Justin Jenkins on foojay.io - Friends of OpenJDK</title><link>https://foojayio.github.io/website/today/author/justin-jenkins/</link><description>Articles written by Justin Jenkins on foojay.io - Friends of OpenJDK</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Tue, 07 Oct 2025 14:01:53 +0000</lastBuildDate><atom:link href="https://foojayio.github.io/website/today/author/justin-jenkins/index.xml" rel="self" type="application/rss+xml"/><item><title>Working with Geo Location Data in MongoDB</title><link>https://foojayio.github.io/website/today/working-with-geo-location-data/</link><pubDate>Tue, 07 Oct 2025 14:01:53 +0000</pubDate><guid>https://foojayio.github.io/website/today/working-with-geo-location-data/</guid><description>&lt;p&gt;&lt;a href="https://www.mongodb.com/?utm_campaign=devrel&amp;amp;utm_source=third-party-content&amp;amp;utm_medium=cta&amp;amp;utm_content=geo-mongodb-foojay&amp;amp;utm_term=tony.kim" target="_blank" rel="noopener noreferrer"&gt;MongoDB&lt;/a&gt;
 makes it really easy to work with location data (sometimes called Geo Data) by simplifying how to store this type of data and streamlining how you query for it so you can easily create &amp;ldquo;find nearby&amp;rdquo; queries, or plot your location data with ease!&lt;/p&gt;
&lt;p&gt;Let&amp;rsquo;s start with the basics: modeling your data, indexing it properly, running geo queries, and then displaying results on a map.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Model Your Data with GeoJSON&lt;/strong&gt;&lt;/p&gt;</description></item><item><title>MongoDB Aggregations: Organizing Recipes by Meal Type with $group</title><link>https://foojayio.github.io/website/today/mongodb-aggregations-organizing-recipes-by-meal-type-with-group/</link><pubDate>Thu, 04 Sep 2025 05:31:22 +0000</pubDate><guid>https://foojayio.github.io/website/today/mongodb-aggregations-organizing-recipes-by-meal-type-with-group/</guid><description>&lt;p&gt;In this series, we&amp;rsquo;re exploring different &lt;a href="https://www.mongodb.com/docs/manual/aggregation/?utm_campaign=devrel&amp;amp;utm_source=third-party-content&amp;amp;utm_medium=cta&amp;amp;utm_content=recipe-foojay&amp;amp;utm_term=tony.kim" target="_blank" rel="noopener noreferrer"&gt;MongoDB aggregation operators&lt;/a&gt;
 by applying them to a recipe collection. I hope you&amp;rsquo;ll follow along with each post!&lt;/p&gt;
&lt;p&gt;MongoDB Aggregations Series&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;&lt;a href="https://learnmongo.com/mongodb-aggregations-finding-cooking-times-with-min-and-max/" target="_blank" rel="noopener noreferrer"&gt;MongoDB Aggregations: Finding Cooking Times with $min and $max&lt;/a&gt;
&lt;/li&gt;
&lt;li&gt;MongoDB Aggregations: Organizing Recipes by Meal Type with $group&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;As part of this series, we are imagining you&amp;rsquo;re building a recipe website. For this post, we are adding some new features to our site, including allowing users to browse recipes by meal type&amp;mdash;breakfast, lunch, dinner, etc.&lt;/p&gt;</description></item></channel></rss>