Book Image

Azure Databricks Cookbook

By : Phani Raj, Vinod Jaiswal
Book Image

Azure Databricks Cookbook

By: Phani Raj, Vinod Jaiswal

Overview of this book

Azure Databricks is a unified collaborative platform for performing scalable analytics in an interactive environment. The Azure Databricks Cookbook provides recipes to get hands-on with the analytics process, including ingesting data from various batch and streaming sources and building a modern data warehouse. The book starts by teaching you how to create an Azure Databricks instance within the Azure portal, Azure CLI, and ARM templates. You’ll work through clusters in Databricks and explore recipes for ingesting data from sources, including files, databases, and streaming sources such as Apache Kafka and EventHub. The book will help you explore all the features supported by Azure Databricks for building powerful end-to-end data pipelines. You'll also find out how to build a modern data warehouse by using Delta tables and Azure Synapse Analytics. Later, you’ll learn how to write ad hoc queries and extract meaningful insights from the data lake by creating visualizations and dashboards with Databricks SQL. Finally, you'll deploy and productionize a data pipeline as well as deploy notebooks and Azure Databricks service using continuous integration and continuous delivery (CI/CD). By the end of this Azure book, you'll be able to use Azure Databricks to streamline different processes involved in building data-driven apps.
Table of Contents (12 chapters)

Technical requirements

To follow along with the examples shown in the recipes, you will need to have the following:

  • An Azure subscription and the required permissions on the subscription that was mentioned in the Technical requirements section in Chapter 1, Creating an Azure Databricks Service.
  • An Azure Databricks premium workspace with a Spark 3.x cluster.
  • Databricks SQL is in public preview.

    Important Note

    The UI and some features of Databricks SQL may change in the future when it goes to General Availability (GA) as it is still in public preview.

In the next section, you will learn how to create a user in Databricks SQL.