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 data definition language commands

In this section, we will learn about data definition commands that are specific to Databricks SQL and Lakehouse. Specifically, we will focus on commands that allow administrators to manage data catalogs, cloud storage locations, and Delta Sharing.

Databricks SQL supports the common data definition commands such as the following:

  • CREATE/ALTER/DROP database/schema
  • CREATE/ALTER/DROP/TRUNCATE table
  • CREATE/ALTER/DROP view

These are standard commands in the database and data warehouse world. They have the same semantics in Databricks SQL and do not require detailed unpacking. However, as we learned in Chapter 3, The Data Catalog, Databricks SQL encapsulates database objects in a new type of object called the catalog. Let’s learn how to create catalog objects and work with them.

DDL for catalogs

Databricks SQL supports a three-level namespace, with the catalog being the highest-level namespace. As a reminder...