Tuesday 17 December 2019

Using Gatling to dynamically generate lots of complex JSON

Update (9th July 2021) - I have created a better way of doing this using a separate Java project approach - https://bestofthetest.blogspot.com/2021/07/gatling-and-test-data-generator-pattern.html?m=1

This is a quick post sharing some recent work I’ve done to investigate using Gatling to generate large amounts of load, specifically in the form of complex JSON documents. As the JSON documents are complex, with nesting, relationships and logic, I didn’t want to use the usual method of string replacements with Gatling session variables. I wanted to construct the JSON in code so I could make use of helpful code patterns and practices to make it easier to build and maintain.
At the same time, I wanted to make use of Gatling’s scenario functionality because its a useful way of modelling and shaping data in a realistic manner, as well as also giving a lot of code that generates load for free. I also knew already it was possible to have Gatling call and use Scala code as I had done it before.

The code structure and building JSON

You can find the code here:

The first point of entry for the code is the “TestSimulation.scala” file which defines and executes the Gatling session. I have included a simplistic e-commerce example, where there are two main user stories - your casual shopper who buys 1 or 2 items and big spenders who buy lots of items. In the comments, you can see an example of how I use this to control the load - letting me define a scenario where we have lots of casual shoppers regularly sending data, whereas big spenders are more rare and only occasionally send data.

The key part for this post is the feeders (defined by “.feed”) that pull data defined by a Scala object imported into this test. This is how I bring in JSON objects defined by Scala code into the Gatling session.

If you follow this code, you will see how I’ve written Scala case classes that define the shape of the JSON (under the folder “objects” in my code) and I’ve written Scala objects that define how to generate their respective classes. This gives me a nice separation of maintaining the JSON structure and modifying and maintaining the data set I populate the JSON with.

Relational data in JSON

Sometimes you need to create JSON that has a relationship, such as a variable that sums the numbers of other items or a summed price. If you look at the ItemGenerator code you can see how I’ve been able to dynamically generate a random list of items with random prices but still have a related field “totalPrice” correctly equal the sum of the individual item prices.

Generating random data outside of Gatling’s DSL
In addition to this JSON object generation, I’ve also included some examples of generating random data. Why not use Gatling’s features for this? Well because I want to define the JSON up front, I can’t use Gatling functions without starting a new Gatling session, which you cannot have multiple instances of. So I wrote some of my own code to allow me randomly generate things like loading values from files.
Why did I copy the function “RandomIntBetween” from scala.util.Random? This is because its only available in Scala 2.13 and currently Gatling only works with 2.12.

Debugging Gatling

Also as an aside, I’ve included comments on how to print out Gatling session variables during its run. Gatling can be difficult to debug and sometimes it’s useful to see and tweak its behaviour during the run.


I hope someone finds this useful, I had fun writing this and learned a lot about Gatling and Scala in the process, and I will for sure be referring back to this code in future. I also found myself refactoring this code a whole lot more in the process of uploading and sharing it!

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