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Azure Data Factory Cookbook

You're reading from  Azure Data Factory Cookbook

Product type Book
Published in Dec 2020
Publisher Packt
ISBN-13 9781800565296
Pages 382 pages
Edition 1st Edition
Languages
Authors (4):
Dmitry Anoshin Dmitry Anoshin
Profile icon Dmitry Anoshin
Dmitry Foshin Dmitry Foshin
Profile icon Dmitry Foshin
Roman Storchak Roman Storchak
Profile icon Roman Storchak
Xenia Ireton Xenia Ireton
Profile icon Xenia Ireton
View More author details
Toc

Table of Contents (12) Chapters close

Preface 1. Chapter 1: Getting Started with ADF 2. Chapter 2: Orchestration and Control Flow 3. Chapter 3: Setting Up a Cloud Data Warehouse 4. Chapter 4: Working with Azure Data Lake 5. Chapter 5: Working with Big Data – HDInsight and Databricks 6. Chapter 6: Integration with MS SSIS 7. Chapter 7: Data Migration – Azure Data Factory and Other Cloud Services 8. Chapter 8: Working with Azure Services Integration 9. Chapter 9: Managing Deployment Processes with Azure DevOps 10. Chapter 10: Monitoring and Troubleshooting Data Pipelines 11. Other Books You May Enjoy

Setting up an HDInsight cluster

HDInsight is a comprehensive solution based on a diverse list of open source platforms. It includes Apache Hadoop, Apache Spark, Apache Kafka, Apache HBase, Apache Hive, Apache Storm, and so on. Solutions based on HDInsight can be integrated with ADF, Azure Data Lake, Cosmos DB, and so on.

In this section, we will set up the HDInsight service, build a basic pipeline, and deploy it to ADF.

Getting ready

Before getting started with the recipe, log in to your Microsoft Azure account.

We assume you have a pre-configured resource group and storage account with Azure Data Lake Gen2.

How to do it…

We will go through the process of creating an HDInsight cluster using the Azure portal and its web interface. Follow these instructions:

  1. Create a user-assigned managed identity. We will need it in the next step, to set up HDInsight cluster access to Data Lake v2. Find Managed Identities in Azure and click +Add.
  2. Fill in the appropriate...
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