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Data Engineering with AWS

You're reading from   Data Engineering with AWS Acquire the skills to design and build AWS-based data transformation pipelines like a pro

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Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781804614426
Length 636 pages
Edition 2nd Edition
Tools
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Author (1):
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Gareth Eagar Gareth Eagar
Author Profile Icon Gareth Eagar
Gareth Eagar
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Toc

Table of Contents (24) Chapters Close

Preface 1. Section 1: AWS Data Engineering Concepts and Trends
2. An Introduction to Data Engineering FREE CHAPTER 3. Data Management Architectures for Analytics 4. The AWS Data Engineer’s Toolkit 5. Data Governance, Security, and Cataloging 6. Section 2: Architecting and Implementing Data Engineering Pipelines and Transformations
7. Architecting Data Engineering Pipelines 8. Ingesting Batch and Streaming Data 9. Transforming Data to Optimize for Analytics 10. Identifying and Enabling Data Consumers 11. A Deeper Dive into Data Marts and Amazon Redshift 12. Orchestrating the Data Pipeline 13. Section 3: The Bigger Picture: Data Analytics, Data Visualization, and Machine Learning
14. Ad Hoc Queries with Amazon Athena 15. Visualizing Data with Amazon QuickSight 16. Enabling Artificial Intelligence and Machine Learning 17. Section 4: Modern Strategies: Open Table Formats, Data Mesh, DataOps, and Preparing for the Real World
18. Building Transactional Data Lakes 19. Implementing a Data Mesh Strategy 20. Building a Modern Data Platform on AWS 21. Wrapping Up the First Part of Your Learning Journey 22. Other Books You May Enjoy
23. Index

Managing groups of users with Amazon Athena workgroups

Athena workgroups are a powerful mechanism for separating different groups and types of user queries (such as SQL based queries, and Spark Notebook queries), for applying cost controls, assigning provisioned capacity, and for implementing strong governance on Athena usage.

All queries within Athena are run in a specific workgroup, and you can apply a number of configuration settings to each workgroup to control costs and governance for the users in that workgroup. The following list shows the configuration items that can be controlled at the workgroup level:

  • The analytic engine that users in this workgroup use (either Athena SQL or Apache Spark)
  • Whether the Athena engine version used for this workgroup is selected and upgraded automatically, or whether you manually specify the engine version to use
  • The S3 location where the results of queries are written to, and whether these files are encrypted or...
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