Book Image

Business Intelligence with Databricks SQL

By : Vihag Gupta
Book Image

Business Intelligence with Databricks SQL

By: Vihag Gupta

Overview of this book

In this new era of data platform system design, data lakes and data warehouses are giving way to the lakehouse – a new type of data platform system that aims to unify all data analytics into a single platform. Databricks, with its Databricks SQL product suite, is the hottest lakehouse platform out there, harnessing the power of Apache Spark™, Delta Lake, and other innovations to enable data warehousing capabilities on the lakehouse with data lake economics. This book is a comprehensive hands-on guide that helps you explore all the advanced features, use cases, and technology components of Databricks SQL. You’ll start with the lakehouse architecture fundamentals and understand how Databricks SQL fits into it. The book then shows you how to use the platform, from exploring data, executing queries, building reports, and using dashboards through to learning the administrative aspects of the lakehouse – data security, governance, and management of the computational power of the lakehouse. You’ll also delve into the core technology enablers of Databricks SQL – Delta Lake and Photon. Finally, you’ll get hands-on with advanced SQL commands for ingesting data and maintaining the lakehouse. By the end of this book, you’ll have mastered Databricks SQL and be able to deploy and deliver fast, scalable business intelligence on the lakehouse.
Table of Contents (21 chapters)
1
Part 1: Databricks SQL on the Lakehouse
9
Part 2: Internals of Databricks SQL
13
Part 3: Databricks SQL Commands
16
Part 4: TPC-DS, Experiments, and Frequently Asked Questions

Playing with the TPC-DS Dataset

In this chapter, we will get acquainted with the TPC-DS dataset. Lakehouse platforms, including Databricks, use TPC-DS benchmarks to prove their capabilities. Hence, it is important to know about it. In this chapter, we will learn about the TPC-DS dataset, the TPC-DS benchmark, and how to use the TPC-DS dataset to validate some of the concepts we learned about in the previous chapters.  

This chapter is only for advanced users who wish to build a larger dataset to test out Databricks SQL features. If you already have access to such a dataset, or you don’t want to test with bigger datasets, there is no need to go through this chapter.

In this chapter, we will cover the following topics:

  • Understanding the TPC-DS dataset
  • Generating TPC-DS data
  • Running automated benchmarks
  • Experimenting with TPC-DS in Databricks SQL