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Serverless ETL and Analytics with AWS Glue

You're reading from  Serverless ETL and Analytics with AWS Glue

Product type Book
Published in Aug 2022
Publisher Packt
ISBN-13 9781800564985
Pages 434 pages
Edition 1st Edition
Languages
Authors (6):
Vishal Pathak Vishal Pathak
Profile icon Vishal Pathak
Subramanya Vajiraya Subramanya Vajiraya
Profile icon Subramanya Vajiraya
Noritaka Sekiyama Noritaka Sekiyama
Profile icon Noritaka Sekiyama
Tomohiro Tanaka Tomohiro Tanaka
Profile icon Tomohiro Tanaka
Albert Quiroga Albert Quiroga
Profile icon Albert Quiroga
Ishan Gaur Ishan Gaur
Profile icon Ishan Gaur
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Table of Contents (20) Chapters

Preface 1. Section 1 – Introduction, Concepts, and the Basics of AWS Glue
2. Chapter 1: Data Management – Introduction and Concepts 3. Chapter 2: Introduction to Important AWS Glue Features 4. Chapter 3: Data Ingestion 5. Section 2 – Data Preparation, Management, and Security
6. Chapter 4: Data Preparation 7. Chapter 5: Data Layouts 8. Chapter 6: Data Management 9. Chapter 7: Metadata Management 10. Chapter 8: Data Security 11. Chapter 9: Data Sharing 12. Chapter 10: Data Pipeline Management 13. Section 3 – Tuning, Monitoring, Data Lake Common Scenarios, and Interesting Edge Cases
14. Chapter 11: Monitoring 15. Chapter 12: Tuning, Debugging, and Troubleshooting 16. Chapter 13: Data Analysis 17. Chapter 14: Machine Learning Integration 18. Chapter 15: Architecting Data Lakes for Real-World Scenarios and Edge Cases 19. Other Books You May Enjoy

Summary

In this chapter, we discussed the methods and different optimization features that can be used in AWS Glue ETL to ingest data from file/object stores, JDBC-compatible data stores, and streaming data stores. We also explored serialization and deserialization, which are used by AWS GSR to handle evolving schemas. Then, we introduced Glue Studio Marketplace connectors, using which we can ingest data from SaaS. Finally, we briefly discussed how users can build custom JDBC/Spark/Athena Federated Query connectors to ingest data from data stores that are not directly supported by AWS Glue and when there is no connector readily available in AWS Marketplace.

In the next chapter, we will be discussing data preparation strategies. We'll explore different factors that can be considered while choosing the right service/tool. We will also discuss the different available options: visual data preparation versus source code-/SQL-based data preparation and the different transformation...

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