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Simplify Big Data Analytics with Amazon EMR

You're reading from  Simplify Big Data Analytics with Amazon EMR

Product type Book
Published in Mar 2022
Publisher Packt
ISBN-13 9781801071079
Pages 430 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Sakti Mishra Sakti Mishra
Profile icon Sakti Mishra

Table of Contents (19) Chapters

Preface 1. Section 1: Overview, Architecture, Big Data Applications, and Common Use Cases of Amazon EMR
2. Chapter 1: An Overview of Amazon EMR 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. You have an on-premises persistent Hadoop cluster, where you have a lot of Hive SQL jobs and very few Spark ETL jobs are available. This cluster serves multiple teams and also helps in interactive analytics.

You are assigned the job to plan for AWS cloud migration. Which AWS service is best suited for you?

  1. You have received a JSON file from your source system that you would like to flatten and apply a few standardizations to for your machine learning model prediction. This process needs to be repeated every day so that the machine learning prediction can predict the output for the next day. Which AWS service will you use?
  2. You have a requirement to build a real-time streaming application, where you need to integrate a scalable message bus and Spark Streaming consumer application. You are looking for a managed messaging service that can scale as the number of streaming events increase or decrease. What will you use?
  3. Which AWS services will you choose for the message bus and Spark processing consumer application?
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Simplify Big Data Analytics with Amazon EMR
Published in: Mar 2022 Publisher: Packt ISBN-13: 9781801071079
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