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Cloud Scale Analytics with Azure Data Services

You're reading from   Cloud Scale Analytics with Azure Data Services Build modern data warehouses on Microsoft Azure

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Product type Paperback
Published in Jul 2021
Publisher Packt
ISBN-13 9781800562936
Length 520 pages
Edition 1st Edition
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Author (1):
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Patrik Borosch Patrik Borosch
Author Profile Icon Patrik Borosch
Patrik Borosch
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Table of Contents (20) Chapters Close

Preface 1. Section 1: Data Warehousing and Considerations Regarding Cloud Computing
2. Chapter 1: Balancing the Benefits of Data Lakes Over Data Warehouses FREE CHAPTER 3. Chapter 2: Connecting Requirements and Technology 4. Section 2: The Storage Layer
5. Chapter 3: Understanding the Data Lake Storage Layer 6. Chapter 4: Understanding Synapse SQL Pools and SQL Options 7. Section 3: Cloud-Scale Data Integration and Data Transformation
8. Chapter 5: Integrating Data into Your Modern Data Warehouse 9. Chapter 6: Using Synapse Spark Pools 10. Chapter 7: Using Databricks Spark Clusters 11. Chapter 8: Streaming Data into Your MDWH 12. Chapter 9: Integrating Azure Cognitive Services and Machine Learning 13. Chapter 10: Loading the Presentation Layer 14. Section 4: Data Presentation, Dashboarding, and Distribution
15. Chapter 11: Developing and Maintaining the Presentation Layer 16. Chapter 12: Distributing Data 17. Chapter 13: Introducing Industry Data Models 18. Chapter 14: Establishing Data Governance 19. Other Books You May Enjoy

Chapter 7: Using Databricks Spark Clusters

In the last chapter, Chapter 6, Using Synapse Spark Pools, you learned about Spark and the Synapse integrated Spark engine. But what about cases where you only need a Spark cluster to interact with your Data Lake Store? You would, for example, choose Databricks over Synapse Spark pools at this point in time, when you need to work on Spark 3.0 or when you need to implement Structured Streaming. R, as a required programming language, will require Databricks as well as the Databricks-specific features of Delta Lake, such as vacuuming and others. Synapse will offer most of these options, too, in the future. But at the moment, they are available only in Databricks.

With Azure Databricks, Microsoft offers a standalone Spark environment that will give you all the aforementioned options and can still integrate with other data services on Azure if needed. And with Databricks, you have the people at your back that invented Spark. The cluster architecture...

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