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Simplify Big Data Analytics with Amazon EMR

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

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Product type Paperback
Published in Mar 2022
Publisher Packt
ISBN-13 9781801071079
Length 430 pages
Edition 1st Edition
Concepts
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Author (1):
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Sakti Mishra Sakti Mishra
Author Profile Icon Sakti Mishra
Sakti Mishra
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Table of Contents (19) Chapters Close

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 18. Other Books You May Enjoy

Test your knowledge

Before moving on to the next chapter, test your knowledge with the following questions:

  1. Assume you have a long-running EMR cluster that is being used by multiple teams for ETL jobs and data analysis. Because of its multi-tenant nature, your organization asks that you provide a report of who is accessing the cluster and for which activities. How would you prepare such a report and from where will you collect this information?
  2. Assume you have a long-running EMR cluster that integrates instance fleets into its configurations. Your cluster has one master and three core nodes to start with and you are planning to benefit from EMR scaling capabilities so that when you have more workload, your cluster will scale up, and when the jobs are finished, it will scale down. Out of EMR-managed scaling and autoscaling with custom policies, which one will you choose?
  3. You have a long-running EMR cluster that is being used by multiple teams of your organization. You...
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