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)

Chapter 1: Creating an Azure Databricks Service

Azure Databricks is a high-performance Apache Spark-based platform that has been optimized for the Microsoft Azure cloud.

It offers three environments for building and developing data applications:

  • Databricks Data Science and Engineering: This provides an interactive workspace that enables collaboration between data engineers, data scientists, machine learning engineers, and business analysts and allows you to build big data pipelines.
  • Databricks SQL: This allows you to run ad hoc SQL queries on your data lake and supports multiple visualization types to explore your query results.
  • Databricks Machine Learning: Provides end-to-end machine learning environment for feature development, model training , experiment tracking along with model serving and management.

In this chapter, we will cover how to create an Azure Databricks service using the Azure portal, Azure CLI, and ARM templates. We will learn about different...