Apache Superset

Apache Superset is an open-source data exploration and visualization platform that empowers users to create interactive, shareable dashboards and charts for analyzing and presenting data. It supports a wide range of data sources and provides an intuitive, web-based interface for data exploration, slicing, and dicing, with features like dynamic filtering, pivot tables, and drag-and-drop functionality. Superset also offers a rich set of visualization options and can be extended through custom plugins, making it a versatile tool for data analysts and business users to gain insights from their data and collaborate effectively.

With its exceptional speed and scalability, Firebolt allows users to handle vast amounts of data with minimal query latency, ensuring that Superset dashboards and visualizations load quickly, even when dealing with massive datasets. This integration between Firebolt and Superset creates a powerful combination for data professionals, offering them a streamlined and efficient workflow for extracting maximum value from their data.

Firebolt is also supported in Preset, a fully managed cloud Superset solution.

Prerequisites

Superset can be installed in several ways, including using a pre-built Docker container, building it from source or deploying via Kubernetes Helm chart.

The easiest way to get started is to run Superset via Docker.

You will need:

Docker and Docker Compose.
VirtualBox (Windows only).
Git.

Quickstart

Follow this guide to setup Superset and get your first chart ready.

Setup Superset

Clone Superset’s GitHub repository

git clone https://github.com/apache/superset.git

Change directory to the root of the newly cloned repository and add the Firebolt driver

cd superset
touch ./docker/requirements-local.txt
echo "firebolt-sqlalchemy" >> ./docker/requirements-local.txt

Run Superset via Docker Compose

docker compose -f docker-compose-non-dev.yml up

(Optional) Verify firebolt driver is present in Superset container
```
docker exec -it <container_name> bash
pip freeze | grep firebolt
```
You should see firebolt-sqlalchemy in the output.

Once your Superset is booted up you should be able to access it in http://localhost:8088/

Note: For more installation details, refer to Adding New Database Drivers in Docker in the Superset documentation.

Setup Firebolt connection

After the initial setup in Superset User Inteface head to the Settings -> Database connections in the top right corner.

Database Connections

On the next screen, press the + Database button and select Firebolt from the dropdown. If you don’t see Firebolt in the list, please refer to the Setup Superset section for instructions on how to install the Firebolt driver and verify that the driver is present.

Connect database

The connection expects a SQLAlchemy connection string of the form:

firebolt://{client_id}:{client_secret}@{database}/{engine_name}?account_name={account_name}

To authenticate, use a service account ID and secret. A service account is identified by a client_id and a client_secret. Learn how to generate an ID and secret here.

Account name must be provided, you can learn about accounts in Manage accounts section.

Credentials

Click the Test Connection button to confirm things work end to end. If the connection looks good, save the configuration by clicking the Connect button in the bottom right corner of the modal window. Now you’re ready to start using Superset!

Build your first chart

Note: This section assumes you have followed Firebolt tutorial and loaded a sample data set into your database.

Now that you’ve configured Firebolt as a data source, you can select specific tables (Datasets) that you want to see in Superset.

Go to Data -> Datasets and select + Dataset. There you can select your sample table by specifying Firebolt as your Database, your schema and the table name you chose.

Dataset

Press “Create Dataset and Create Chart”. On the next screen you can select your desired chart type. For this tutorial we will go with a simple Bar Chart.

Chart type

In the next screen you can drag and drop your table columns into Metrics and Dimensions, specify filters or sorting orders. We will plot max play time per level grouping it by level type and sorting the x-axis in ascending order.

Chart

Your first chart is ready! You can now save it, add more data to it or change its type. You can also start building a dashboard with different charts telling a story. Learn more about this functionality and more by following the links below.