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Azure Data Factory Cookbook

Azure Data Factory Cookbook

By : Dmitry Anoshin, Dmitry Foshin, Storchak, Xenia Ireton
4.2 (13)
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Azure Data Factory Cookbook

Azure Data Factory Cookbook

4.2 (13)
By: Dmitry Anoshin, Dmitry Foshin, Storchak, Xenia Ireton

Overview of this book

Azure Data Factory (ADF) is a modern data integration tool available on Microsoft Azure. This Azure Data Factory Cookbook helps you get up and running by showing you how to create and execute your first job in ADF. You’ll learn how to branch and chain activities, create custom activities, and schedule pipelines. This book will help you to discover the benefits of cloud data warehousing, Azure Synapse Analytics, and Azure Data Lake Gen2 Storage, which are frequently used for big data analytics. With practical recipes, you’ll learn how to actively engage with analytical tools from Azure Data Services and leverage your on-premise infrastructure with cloud-native tools to get relevant business insights. As you advance, you’ll be able to integrate the most commonly used Azure Services into ADF and understand how Azure services can be useful in designing ETL pipelines. The book will take you through the common errors that you may encounter while working with ADF and show you how to use the Azure portal to monitor pipelines. You’ll also understand error messages and resolve problems in connectors and data flows with the debugging capabilities of ADF. By the end of this book, you’ll be able to use ADF as the main ETL and orchestration tool for your data warehouse or data platform projects.
Table of Contents (12 chapters)
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Processing big data with Apache Spark

Apache Spark is a well-known big data framework that is often used for big data ETL/ELT jobs and machine learning tasks. ADF allows us to utilize its capabilities in two different ways:

  • Running Spark in an HDInsight cluster
  • Running Databricks notebooks and JAR and Python files

Running Spark in an HDInsight cluster is very similar to the previous recipe. So, we will concentrate on the Databricks service. It also allows running interactive notebooks, which significantly simplifies the development of the ETL/ELT pipelines and machine learning tasks.

Getting ready

Assuming you have a preconfigured resource group and storage account with Azure Data Lake Gen2, log in to your Microsoft Azure account. To run Databricks notebooks, you have to switch to a pay-as-you-go subscription.

How to do it…

  1. Go to the Azure portal and find Databricks.
  2. Click + Add and fill in the project details.
  3. Select your subscription...

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