![]() ![]() Note: The linked tutorials on how to configure your server, install MongoDB, and secure the MongoDB installation refer to Ubuntu 20.04. To learn how to use MongoDB queries, follow our guide on How To Create Queries in MongoDB. Familiarity with querying MongoDB collections and filtering results.To secure MongoDB like this, follow our tutorial on How To Secure MongoDB on Ubuntu 20.04. Your server’s MongoDB instance secured by enabling authentication and creating an administrative user.To set this up, follow our tutorial on How to Install MongoDB on Ubuntu 20.04. This tutorial was validated using a server running Ubuntu 20.04, and you can prepare your server by following this initial server setup tutorial for Ubuntu 20.04. A server with a regular, non-root user with sudo privileges and a firewall configured with UFW.In this tutorial, you’ll learn by example how to create a text index in MongoDB and use it to search the documents in the database against common full-text search queries and filters. However, for scenarios that don’t require the robust search features found in dedicated search engines, some general-purpose database management systems offer their own full-text search capabilities. There are multiple specialized open-source tools for such applications in use, with ElasticSearch being an especially popular choice. This level of flexibility in matching text to a search query is typical for full-text search engines that specialize in searching textual data. ![]() In this case, you may not find exactly what you were looking for since most popular websites with coffee recipes may not contain the exact phrase “coffee recipe.” If you were to enter that phrase into a real search engine, though, you might find pages with titles like “Great Coffee Drinks (with Recipes!)” or “Coffee Shop Drinks and Treats You Can Make at Home.” In these examples, the word “coffee” is present but the titles contain another form of the word “recipe” or exclude it entirely. Imagine you typed “coffee recipe” into a web search engine but it only returned pages that contained that exact phrase. However, these methods fall short when it comes to filtering against fields containing rich textual data. MongoDB queries that filter data by searching for exact matches, using greater-than or less-than comparisons, or by using regular expressions will work well enough in many situations. ![]() The author selected the Open Internet/Free Speech Fund to receive a donation as part of the Write for DOnations program. ![]()
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