Book Image

Apache Superset Quick Start Guide

By : Shashank Shekhar
Book Image

Apache Superset Quick Start Guide

By: Shashank Shekhar

Overview of this book

Apache Superset is a modern, open source, enterprise-ready business intelligence (BI) web application. With the help of this book, you will see how Superset integrates with popular databases like Postgres, Google BigQuery, Snowflake, and MySQL. You will learn to create real time data visualizations and dashboards on modern web browsers for your organization using Superset. First, we look at the fundamentals of Superset, and then get it up and running. You'll go through the requisite installation, configuration, and deployment. Then, we will discuss different columnar data types, analytics, and the visualizations available. You'll also see the security tools available to the administrator to keep your data safe. You will learn how to visualize relationships as graphs instead of coordinates on plain orthogonal axes. This will help you when you upload your own entity relationship dataset and analyze the dataset in new, different ways. You will also see how to analyze geographical regions by working with location data. Finally, we cover a set of tutorials on dashboard designs frequently used by analysts, business intelligence professionals, and developers.
Table of Contents (10 chapters)

Main configuration file

So, we have completed configuring Superset. Let's take a look at the complete Superset configuration file:

# Superset Configuration file
# add file superset_config.py to PYTHONPATH for usage

# Metadata database
SQLALCHEMY_DATABASE_URI = "postgresql+psycopg2://superset:superset@localhost/superset"

# Securing Session data
SECRET_KEY = 'AdLcixY34P' # random string

# Caching Queries
CACHE_CONFIG = {
# Specify the cache type

'CACHE_TYPE': 'redis',
'CACHE_REDIS_URL': 'redis://localhost:6379/0',
# The key prefix for the cache values stored on the server
'CACHE_KEY_PREFIX': 'superset_results'
}

# Set this API key to enable Mapbox visualizations
MAPBOX_API_KEY = os.environ.get('MAPBOX_API_KEY', 'mapbox-api-key')

# Long running query handling using Celery workers
class
...