![]() More specifically the column is using a JSON alias datatype. Note that the attr column included within the locations table is defined with a JSON data type. In fact, the SQL used to create a new location table should look very familiar. Using JSON within MariaDB is as easy as enabling the ability to store JSON data within a table. So, the locations table will contain both structured and semi-structured data. But, depending on the type, each location could have different details.Įnter JSON that can be used to manage the different information per location type. ![]() We won’t be using any kind of front-end management, but imagine that the locations could be represented on some kind of map like the following.įrom the simplest standpoint, geographic locations, no matter the type, contain foundational information such as the name, type, longitude and latitude. This application will only contain one table, called locations, that will store, yep, you guessed it, locations. To help walk-through the JSON capabilities that are available within MariaDB I’m going to be using a hypothetical application. However, I’ve always found it easiest to consume new technologies by focusing on a simple, (hopefully) relatable use case that you can then use to get your own creative juices flowing. #Json query tutorial softwareThat’s just the world of software development for ya. There are a multitude of use cases where it may make sense to combine structured and semi-structured data. Tip: If you’d like to jump right into a MariaDB database and use the same dataset I’ll be using for the examples in this article be sure to check out this MariaDB JSON Quickstart Guide! Structured Data + Semi-Structured Data Let’s check out some of the JSON functionality that’s available in MariaDB and how you can use it! OK, enough of this “setting the stage” business. The ability to store JSON documents within a relational database allows you to create hybrid data models, containing both structured and semi-structured data, and enjoy all of the benefits of JSON without having to sacrifice the advantages of relational databases (e.g. Keying off of the success that NoSQL solutions have been able to achieve by using semi-structured data in that time, over the past few years JSON integrations have made their way into the relational world. ![]() #Json query tutorial updateAnd that makes sense as one of the problems the NoSQL Revolution set out to solve was flexibility, or having the ability to create, update and remove data and the structures they’re housed in without having to modify things like those pesky relational schemas. OK, but why is that important? Well, in the context of databases, JSON has often been thought of as something you’d use with NoSQL solutions. #Json query tutorial freeOne of those capabilities is its ability to handle JavaScript Object Notation (JSON) formatted data, completely free and out-of-the-box. But, diving deeper into its capabilities, you’ll quickly discover that it’s more than that. I mean, why not? After all, MariaDB is a rock solid relational database solution, and has been for some time now. Heck, you may have even used it to create a database, a couple tables, and even executed a few queries. ![]() To demonstrate the usage of this operator, we need to have a table with a JSON field.You’re likely familiar with MariaDB as your run-of-the-mill relational database. If there are only two arguments for JSON_EXTRACT as used above, we can use the -> operator which is an alias for JSON_EXTRACT. JSON object - A dictionary/hashmap/object (the name is different in different programming languages) with a set of key-value pairs separated by commas and enclosed within curly brackets (', '$.name') | +-+ | "John" | +-+.JSON array - A list of values separated by commas and enclosed within square brackets ().There are two main types of JSON values in MySQL: Let’s first explore the common MySQL functions and operators that can be used to extract data from a JSON field. ![]()
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