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Data Engineering with AWS Cookbook

You're reading from   Data Engineering with AWS Cookbook A recipe-based approach to help you tackle data engineering problems with AWS services

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Product type Paperback
Published in Nov 2024
Publisher Packt
ISBN-13 9781805127284
Length 528 pages
Edition 1st Edition
Languages
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Authors (4):
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Viquar Khan Viquar Khan
Author Profile Icon Viquar Khan
Viquar Khan
Gonzalo Herreros González Gonzalo Herreros González
Author Profile Icon Gonzalo Herreros González
Gonzalo Herreros González
Huda Nofal Huda Nofal
Author Profile Icon Huda Nofal
Huda Nofal
Trâm Ngọc Phạm Trâm Ngọc Phạm
Author Profile Icon Trâm Ngọc Phạm
Trâm Ngọc Phạm
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Toc

Table of Contents (16) Chapters Close

Preface 1. Chapter 1: Managing Data Lake Storage 2. Chapter 2: Sharing Your Data Across Environments and Accounts FREE CHAPTER 3. Chapter 3: Ingesting and Transforming Your Data with AWS Glue 4. Chapter 4: A Deep Dive into AWS Orchestration Frameworks 5. Chapter 5: Running Big Data Workloads with Amazon EMR 6. Chapter 6: Governing Your Platform 7. Chapter 7: Data Quality Management 8. Chapter 8: DevOps – Defining IaC and Building CI/CD Pipelines 9. Chapter 9: Monitoring Data Lake Cloud Infrastructure 10. Chapter 10: Building a Serving Layer with AWS Analytics Services 11. Chapter 11: Migrating to AWS – Steps, Strategies, and Best Practices for Modernizing Your Analytics and Big Data Workloads 12. Chapter 12: Harnessing the Power of AWS for Seamless Data Warehouse Migration 13. Chapter 13: Strategizing Hadoop Migrations – Cost, Data, and Workflow Modernization with AWS 14. Index 15. Other Books You May Enjoy

Using the AWS Glue catalog from another account

Apache Hive is the traditional SQL solution in the Hadoop ecosystem. Since its early versions, it has decoupled the catalog metastore from the query engine to store information about the tables and schemas. This means that multiple tools have added support to integrate with the Hive metastore over the years such as Spark, Presto/Trino, Impala, or the Hive server itself.

When AWS Glue was released, one of the value propositions that it could provide was a Hive-compatible store, which could massively scale and provide fault tolerance out of the box.

When you run EMR on EC2, you can run a Hive metastore or use the Glue catalog as the metastore just by checking the corresponding box in the cluster configuration screen (or setting the equivalent configuration if doing programmatically). When Glue is set as the catalog metastore, all the tools in the cluster that are compatible with Hive will use it to retrieve and store information about...

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