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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

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Product type Paperback
Published in Nov 2021
Publisher Packt
ISBN-13 9781800562349
Length 438 pages
Edition 1st Edition
Languages
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Authors (3):
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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
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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

Using Jupyter Notebooks with Athena

Depending on the proficiency level in querying data, some individuals may consider QuickSight to be more of a dashboarding tool that populates results based on pre-set parameters. Individuals looking for a more fluid and interactive experience may feel their needs are better satisfied by a tool designed for authoring and sharing investigations. You're already familiar with the Athena console's basic ability to write queries and display tabular results. Jupyter Notebooks is a powerful companion to analytics engines such as Athena.

In this section, we'll walk through setting up a Jupyter notebook, connecting it to Amazon Athena, and running advanced ad hoc analytics over the NYC Yellow Taxi ride dataset. If you are unfamiliar with SageMaker or Jupyter Notebooks, don't worry. We will walk you through every step of the process so you can add this new tool to your shelf. For the uninitiated, AWS describes SageMaker as the most...

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