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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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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

Chapter 4: Metastores, Data Sources, and Data Lakes

One of the best features of Athena is that it allows you to query data where it lives. That data can be sitting on S3, in a relational database, your EC2 environment, or any other source from which business value can be derived. However, the vast majority of Athena's usage is to query data on S3. Before Athena can query this data, it needs to know where the data is and how to read it, as data on S3 can be in many different file formats. Athena needs to translate the databases and tables referenced in SQL statements into physical S3 locations, and then choose the right libraries to interpret the data that's been read from that location. The place where Athena goes to look up these translations is called the metastore.

This chapter will dive into the metastore and the information stored there. We will cover what information is required to register tables in a metastore. The metastore is just one of three key pieces that...

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