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

Working with queries

In Chapter 2, The Databricks Product Suite – A Visual Tour, in Figure 2.9, we briefly introduced the SQL Editor as the intelligent workbench that is at the center of the end user experience for day-to-day work.

In this section, we’ll look into the capabilities that the SQL Editor brings to the table.

In the previous chapters, we used the SQL Editor to either program the security model or explore the data assets visually. Hence, I’m not going to introduce the basic layout of the page and dive straight into the most important features.

Continuing within the spirit of the previous chapters, let’s start by incorporating another dataset from the bundled databricks-datasets into our data catalog for use in this chapter. Here, we will use the NYC Taxi Trip dataset.

Like the previous chapters, execute the following SQL snippet to register this dataset as a database:

--create the database
CREATE DATABASE nyc_taxi;
--Set nyc_taxi...