Searching on Your Location with Atlas Search and Geospatial Operators

When thinking about full-text search, text and other string data is probably the first thing to come to mind. In fact, if you’ve been keeping up with my tutorials, you might remember Building an Autocomplete Form Element with Atlas Search and JavaScript or Visually Showing Atlas Search Highlights with JavaScript and HTML, both of which were on text search examples in MongoDB Atlas Search.

Being able to use natural language search on text data is probably one of the most popular use-cases, but there are scenarios where you might need to narrow the results even further.

Let’s say you’re building a restaurant review application like Yelp or a bed and breakfast booking system like Airbnb. Sure, you’ll enter some kind of text criteria for what you’re looking for, but there’s also a location aspect to it. For example, if you want to find a place to get a cheeseburger within walking distance of your current location, you probably don’t want your search results to contain entries from another country. This is an example of a geo search, where you would want to return results based on location coordinates.

In this tutorial, we’re going to see how to use Atlas Search and the compound operator to search based on text entered and within a certain geographical area. For the text entered, we’ll use the autocomplete operator, and for the geospatial component, we’ll use the geoWithin operator.

Zap, Tweet, and Repeat! How to Use Zapier with MongoDB

I’m a huge fan of automation when the scenario allows for it. Maybe you need to keep track of guest information when they RSVP to your event, or maybe you need to monitor and react to feeds of data. These are two of many possible scenarios where you probably wouldn’t want to do things manually.

There are quite a few tools that are designed to automate your life. Some of the popular tools include IFTTT, Zapier, and Automate. The idea behind these services is that given a trigger, you can do a series of events.

In this tutorial, we’re going to see how to collect Twitter data with Zapier, store it in MongoDB using a Realm webhook function, and then run aggregations on it using the MongoDB query language (MQL).

Capturing Hacker News Mentions with Node.js and MongoDB

If you’re in the technology space, you’ve probably stumbled upon Hacker News at some point or another. Maybe you’re interested in knowing what’s popular this week for technology or maybe you have something to share. It’s a platform for information.

The problem is that you’re going to find too much information on Hacker News without a particularly easy way to filter through it to find the topics that you’re interested in. Let’s say, for example, you want to know information about Bitcoin as soon as it is shared. How would you do that on the Hacker News website?

In this tutorial, we’re going to learn how to parse through Hacker News data as it is created, filtering for only the topics that we’re interested in. We’re going to do a sentiment analysis on the potential matches to rank them, and then we’re going to store this information in MongoDB so we can run reports from it. We’re going to do it all with Node.js and some simple pipelines.

Manage Game User Profiles with MongoDB, Phaser, and JavaScript

When it comes to game development, you’re almost always going to need to store information about your player. This information could be around how many health points you currently have in the game or it can extend beyond the game-play experience and into details such as the billing information for the person playing the game. When we talk about this type of data, we’re talking about a user profile store.

The user profile has everything about the user or player and doesn’t end at health points or billing information.

In this tutorial, we’re going to look at creating user profiles in a game that leverages the Phaser game development framework, JavaScript, and MongoDB.

Visually Showing Atlas Search Highlights with JavaScript and HTML

When it comes to finding specific words or phrases within text, you’re probably going to want to use a natural language search option like full-text search (FTS). Sure, you could probably create a complicated and difficult-to-maintain set of regular expressions to search within text, but that is an option that most developers don’t want. Not to mention it won’t cover the full scope of what a natural language processor typically accomplishes.

In a previous tutorial titled Building an Autocomplete Form Element with Atlas Search and JavaScript, I wrote about searching for recipes, as they are being typed, in MongoDB Atlas using the autocomplete operator. While this tutorial accomplished the job quite well, it didn’t elaborate on what exactly was being matched for any given term.

In this tutorial, we’re going to see how to use Atlas Search and work with the highlight data to visually show any matches on the terms in a user facing application. Highlighting is a powerful tool with Search to allow your users to find the exact text that they want in its proper context.

Creating a User Profile Store for a Game With Node.js and MongoDB

When it comes to game development, or at least game development that has an online component to it, you’re going to stumble into the territory of user profile stores. These are essentially records for each of your players and these records contain everything from account information to what they’ve accomplished in the game.

Take the game Plummeting People that some of us at MongoDB (Karen Huaulme, Adrienne Tacke, and Nic Raboy) are building, streaming, and writing about. The idea behind this game, as described in a previous article, is to create a Fall Guys: Ultimate Knockout tribute game with our own spin on it.

Since this game will be an online multiplayer game, each player needs to retain game-play information such as how many times they’ve won, what costumes they’ve unlocked, etc. This information would exist inside a user profile document.

In this tutorial, we’re going to see how to design a user profile store and then build a backend component using Node.js and MongoDB Realm for interacting with it.

Maintaining a Geolocation Specific Game Leaderboard with Phaser and MongoDB

When it comes to game development, an often forgotten component comes in the form of a database for storing gameplay information. The database can contribute to numerous roles, such as storing user profile information, game state, and so much more.

In fact, I created a previous tutorial titled Creating a Multiplayer Drawing Game with Phaser and MongoDB. In this drawing example, every brushstroke made was stored in MongoDB.

In this tutorial, we’re going to look at a different data component for a game. We’re going to explore leaderboards and some of the neat things you can do with them. Like my other tutorial, we’ll be using Phaser and JavaScript.