Book Image

Serverless ETL and Analytics with AWS Glue

By : Vishal Pathak, Subramanya Vajiraya, Noritaka Sekiyama, Tomohiro Tanaka, Albert Quiroga, Ishan Gaur
Book Image

Serverless ETL and Analytics with AWS Glue

By: Vishal Pathak, Subramanya Vajiraya, Noritaka Sekiyama, Tomohiro Tanaka, Albert Quiroga, Ishan Gaur

Overview of this book

Organizations these days have gravitated toward services such as AWS Glue that undertake undifferentiated heavy lifting and provide serverless Spark, enabling you to create and manage data lakes in a serverless fashion. This guide shows you how AWS Glue can be used to solve real-world problems along with helping you learn about data processing, data integration, and building data lakes. Beginning with AWS Glue basics, this book teaches you how to perform various aspects of data analysis such as ad hoc queries, data visualization, and real-time analysis using this service. It also provides a walk-through of CI/CD for AWS Glue and how to shift left on quality using automated regression tests. You’ll find out how data security aspects such as access control, encryption, auditing, and networking are implemented, as well as getting to grips with useful techniques such as picking the right file format, compression, partitioning, and bucketing. As you advance, you’ll discover AWS Glue features such as crawlers, Lake Formation, governed tables, lineage, DataBrew, Glue Studio, and custom connectors. The concluding chapters help you to understand various performance tuning, troubleshooting, and monitoring options. By the end of this AWS book, you’ll be able to create, manage, troubleshoot, and deploy ETL pipelines using AWS Glue.
Table of Contents (20 chapters)
1
Section 1 – Introduction, Concepts, and the Basics of AWS Glue
5
Section 2 – Data Preparation, Management, and Security
13
Section 3 – Tuning, Monitoring, Data Lake Common Scenarios, and Interesting Edge Cases

Sharing data with multiple AWS accounts using AWS Lake Formation permissions

In this section, you will learn how to share data with multiple AWS accounts using AWS Lake Formation permissions.

Lake Formation permission model

As you learned in the previous section, there are challenges in managing S3 bucket policies and Glue Data Catalog resource policies. AWS Lake Formation is the service that is designed to overcome those challenges and simplify data platform management. Lake Formation provides a central layer for defining, classifying, tagging, and managing fine-grained access control to the AWS Glue Data Catalog and Amazon S3 locations. The permission model is designed in an RDBMS-like style so that you can grant permissions on databases, tables, or columns instead of S3 objects. Once you have granted access to tables with Lake Formation permissions, Lake Formation automatically manages both data access and metadata access under the hood, so you don’t need to manually...