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)

Processing streaming and batch data using Structured Streaming

We tend to see scenarios where we need to process batch data in comma-separated values (CSV) or Parquet format stored in ADLS Gen2 and from real-time streaming sources such as Event Hubs together. In this recipe, we will learn how we use Structured Streaming for both batch and real-time streaming sources and process the data together. We will also fetch the data from Azure SQL Database for all metadata information required for our processing.

Getting ready

Before starting, you need to have a valid subscription with contributor access, a Databricks workspace (Premium), and an ADLS Gen2 storage account. Also, ensure that you have been through the previous recipes of this chapter.

We have executed the notebook on Databricks Runtime Version 7.5 having Spark 3.0.1.

You can follow along by running the steps in the following notebook:

https://github.com/PacktPublishing/Azure-Databricks-Cookbook/blob/main/Chapter07...