You're reading from Azure Data Engineering Cookbook Get well versed in various data engineering techniques in Azure using this recipe-based guide

Product type Paperback

Published in Sep 2022

Publisher Packt

ISBN-13 9781803246789

Length 608 pages

Edition 2nd Edition

Languages

SQL

Tools

Azure

Concepts

Data Engineering

Authors (3):

Ahmad Osama

Nagaraj Venkatesan

Luca Zanna

View More author details

Table of Contents (16) Chapters

Preface

1. Chapter 1: Creating and Managing Data in Azure Data Lake

2. Chapter 2: Securing and Monitoring Data in Azure Data Lake FREE CHAPTER

3. Chapter 3: Building Data Ingestion Pipelines Using Azure Data Factory

4. Chapter 4: Azure Data Factory Integration Runtime

5. Chapter 5: Configuring and Securing Azure SQL Database

6. Chapter 6: Implementing High Availability and Monitoring in Azure SQL Database

7. Chapter 7: Processing Data Using Azure Databricks

8. Chapter 8: Processing Data Using Azure Synapse Analytics

9. Chapter 9: Transforming Data Using Azure Synapse Dataflows

10. Chapter 10: Building the Serving Layer in Azure Synapse SQL Pool

11. Chapter 11: Monitoring Synapse SQL and Spark Pools

12. Chapter 12: Optimizing and Maintaining Synapse SQL and Spark Pools

13. Chapter 13: Monitoring and Maintaining Azure Data Engineering Pipelines

14. Index

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Processing data using notebooks

Databricks notebooks are the fundamental component in Databricks for performing data processing tasks. In this recipe, we will perform operations such as reading, filtering, cleaning a Comma-Separated Value (CSV) file, and gaining insights from it using a Databricks notebook written in Scala code.

Getting ready

Create a Databricks workspace and a cluster, as explained in the Configuring the Azure Databricks environment recipe.

Download the covid-data.csv file from the path at https://github.com/PacktPublishing/Azure-Data-Engineering-Cookbook-2nd-edition/blob/main/chapter07/covid-data.csv.

How to do it…

Let’s process some data using Scala in a Databricks notebook by following the steps provided here:

Log in to portal.azure.com. Go to All resources and find pactadedatabricks, the Databricks workspace created in the Configuring the Azure Databricks environment recipe. Click Launch Workspace to log in to the Databricks...