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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

Chapter 8: Querying Unstructured and Semi-Structured Data

Many of the world's most valuable datasets are loosely structured. They come from application logs, which don't conform to any standards. They come from event data generated by a system that users interact with, such as a web server, which stores how users navigate an organization's website. They can also come from an analyst generating spreadsheets on a company's financial performance. This data is usually stored and shared in a semi-structured format to make it easier for others to consume. Some query engines have evolved to fully support this semi-structured data.

When talking about structured, semi-structured, and unstructured data, there are many different definitions out there. For this book, structured data is stored in a specialized data format where the schema and the data it represents are one to one. The data is serialized to optimize how the data is read, written, and analyzed. An example...

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