Star Quix Streams

 Install Quix Streams

 Edit on GitHub

Get your data

Danger

This tutorial is out of date. Please check the tutorials overview for our latest tutorials.

Legacy feature

This feature is not available to new users. However, legacy users may still have access to this functionality.

In this part of the tutorial you learn how to obtain some real-time data to work with in the rest of the tutorial. You use a demo data source that generates Formula 1 race car data from a computer game. You use this data as the basis to build a ML model to predict braking patterns.

Create a persisted topic

To make things a little easier, first create a persisted topic to receive the generated data.

1. Log in to Quix.

2. Click Topics on the left-hand menu.

3. Click the Add new, which is located top right.

4. Enter a topic name of f1-data.

5. Leave other values in the Create new topic dialog at their defaults.

6. Click Done. Now wait while the topic is created for you.

7. Once the topic has been created, click the persistence slider button to ensure your data is persisted, as shown in the following screenshot:

   

Generate data from the demo data source

Now generate the actual data for use later in the tutorial by completing the following steps:

1. Click Code Samples on the left-hand sidebar.

2. Find the Demo Data source. This service streams F1 Telemetry data into a topic from a recorded game session.

3. Click the Deploy button in the Demo Data panel.

4. You can leave Name as the default value.

5. Make sure Topic is set to f1-data and then click Deploy.

Once this service is deployed it will run as a job and generate real-time data to the f1-data, and this will be persisted.

This data is retrieved later in this tutorial using Python code that uses the Query API, generated for you by Quix.

Import data into Jupyter Notebook