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ETL with Azure Cookbook

You're reading from   ETL with Azure Cookbook Practical recipes for building modern ETL solutions to load and transform data from any source

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Product type Paperback
Published in Sep 2020
Publisher Packt
ISBN-13 9781800203310
Length 446 pages
Edition 1st Edition
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Authors (3):
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Christian Cote Christian Cote
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Christian Cote
Matija Lah Matija Lah
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Matija Lah
Madina Saitakhmetova Madina Saitakhmetova
Author Profile Icon Madina Saitakhmetova
Madina Saitakhmetova
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Toc

Table of Contents (12) Chapters Close

Preface 1. Chapter 1: Getting Started with Azure and SSIS 2019 2. Chapter 2: Introducing ETL FREE CHAPTER 3. Chapter 3: Creating and Using SQL Server 2019 Big Data Clusters 4. Chapter 4: Azure Data Integration 5. Chapter 5: Extending SSIS with Custom Tasks and Transformations 6. Chapter 6: Azure Data Factory 7. Chapter 7: Azure Databricks 8. Chapter 8: SSIS Migration Strategies 9. Chapter 9: Profiling data in Azure 10. Chapter 10: Manage SSIS and Azure Data Factory with Biml 11. Other Books You May Enjoy

Creating a cluster in our workspace

A cluster is necessary to manipulate and transform data with Databricks. It is composed of a minimum of two machines:

  • A driver node: Receives the commands and dispatches them to a worker.
  • A worker node: Receives and executes the commands. We can use multiple workers that will execute the command in parallel.

There are also two types of clusters:

  • Interactive: A cluster that is started manually. It is used to do interactive queries in a notebook, or another program connected to it, such as Power BI.
  • Automated: A cluster created automatically to run a job and stopped after it. For example, this type of cluster is used when we use a Databricks activity in Azure Data Factory.

Let's create a cluster in our Databricks workspace now.

Getting ready

As with every recipe in this chapter, you will need to upgrade your trial Azure subscription to a Pay-As-You-Go subscription if this is not what you have been using...

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