You're reading from Simplify Big Data Analytics with Amazon EMR A beginner's guide to learning and implementing Amazon EMR for building data analytics solutions

Product type Paperback

Published in Mar 2022

Publisher Packt

ISBN-13 9781801071079

Length 430 pages

Edition 1st Edition

Tools

Amazon EMR

Concepts

Big Data

Author (1):

Sakti Mishra

Preface

1. Section 1: Overview, Architecture, Big Data Applications, and Common Use Cases of Amazon EMR

2. Chapter 1: An Overview of Amazon EMR FREE CHAPTER

3. Chapter 2: Exploring the Architecture and Deployment Options

4. Chapter 3: Common Use Cases and Architecture Patterns

5. Chapter 4: Big Data Applications and Notebooks Available in Amazon EMR

6. Section 2: Configuration, Scaling, Data Security, and Governance

7. Chapter 5: Setting Up and Configuring EMR Clusters

8. Chapter 6: Monitoring, Scaling, and High Availability

9. Chapter 7: Understanding Security in Amazon EMR

10. Chapter 8: Understanding Data Governance in Amazon EMR

11. Section 3: Implementing Common Use Cases and Best Practices

12. Chapter 9: Implementing Batch ETL Pipeline with Amazon EMR and Apache Spark

13. Chapter 10: Implementing Real-Time Streaming with Amazon EMR and Spark Streaming

14. Chapter 11: Implementing UPSERT on S3 Data Lake with Apache Spark and Apache Hudi

15. Chapter 12: Orchestrating Amazon EMR Jobs with AWS Step Functions and Apache Airflow/MWAA

16. Chapter 13: Migrating On-Premises Hadoop Workloads to Amazon EMR

17. Chapter 14: Best Practices and Cost-Optimization Techniques

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Test your knowledge

Before finishing this last chapter, test your knowledge with the following questions:

Assume you have recently migrated your on-premise Hadoop cluster to Amazon EMR by following a lift and shift model. You have several batch and streaming workloads running on the same cluster. You have integrated your EMR cluster with AWS CloudWatch and while monitoring the cluster usage, you found not all the EC2 resources are always optimally used. What's the best architecture pattern you can follow to optimize your resource usage and costs?
Assume you have around five different teams who have requested to have their own persistent EMR clusters for different big data workloads. They need SSH access to the cluster master node and would like to access the web interface of Hadoop applications. How should you provide them with access while maintaining security best practices?
Assume you have a multi-tenant persistent EMR cluster that is deployed on EC2. It has...

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