Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Serverless Analytics with Amazon Athena

You're reading from   Serverless Analytics with Amazon Athena Query structured, unstructured, or semi-structured data in seconds without setting up any infrastructure

Arrow left icon
Product type Paperback
Published in Nov 2021
Publisher Packt
ISBN-13 9781800562349
Length 438 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (3):
Arrow left icon
Aaron Wishnick Aaron Wishnick
Author Profile Icon Aaron Wishnick
Aaron Wishnick
Mert Turkay Hocanin Mert Turkay Hocanin
Author Profile Icon Mert Turkay Hocanin
Mert Turkay Hocanin
Anthony Virtuoso Anthony Virtuoso
Author Profile Icon Anthony Virtuoso
Anthony Virtuoso
Arrow right icon
View More author details
Toc

Table of Contents (20) Chapters Close

Preface 1. Section 1: Fundamentals Of Amazon Athena
2. Chapter 1: Your First Query FREE CHAPTER 3. Chapter 2: Introduction to Amazon Athena 4. Chapter 3: Key Features, Query Types, and Functions 5. Section 2: Building and Connecting to Your Data Lake
6. Chapter 4: Metastores, Data Sources, and Data Lakes 7. Chapter 5: Securing Your Data 8. Chapter 6: AWS Glue and AWS Lake Formation 9. Section 3: Using Amazon Athena
10. Chapter 7: Ad Hoc Analytics 11. Chapter 8: Querying Unstructured and Semi-Structured Data 12. Chapter 9: Serverless ETL Pipelines 13. Chapter 10: Building Applications with Amazon Athena 14. Chapter 11: Operational Excellence – Monitoring, Optimization, and Troubleshooting 15. Section 4: Advanced Topics
16. Chapter 12: Athena Query Federation 17. Chapter 13: Athena UDFs and ML 18. Chapter 14: Lake Formation – Advanced Topics 19. Other Books You May Enjoy

Deciding whether to ETL or query in place

The distinction between ETL and querying in place is blurred when using a service such as Athena. In the preceding sections, we reviewed common ETL use cases. In this section, we'll unpack the details that should go into deciding when the downsides of querying in place tilt the scale in favor of ETL. You might be curious why we've deliberately framed the choice as defaulting to querying in place. The reason is simple and comes to us courtesy of John Gail, who in 1975 theorized, "A complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works and cannot be patched up to make it work. You have to start over with a working simple system." In many ways, querying the data in place can be viewed as the most straightforward starting point. Athena's scalability reduces the need to curate your data model to your access patterns highly. In Chapter...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime