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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

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

View More author details

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 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

Further reading

The following are a few resources you can refer to for further reading:

Considerations and limitations for AWS Glue Data Catalog with Amazon EMR: https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-hive-Metastore-glue.html
Setting up AWS Lake Formation: https://docs.aws.amazon.com/lake-formation/latest/dg/getting-started-setup.html
Detailed steps for Lake Formation integration with Amazon EMR:
Detail steps to configure Apache Ranger in EMR: https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-ranger.html

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Authors (1)

Sakti Mishra

Sakti Mishra

Sakti Mishra is an engineer, architect, author, and technology leader with over 16 years of experience in the IT industry. He is currently working as a senior data lab architect at Amazon Web Services (AWS). He is passionate about technologies and has expertise in big data, analytics, machine learning, artificial intelligence, graph networks, web/mobile applications, and cloud technologies such as AWS and Google Cloud Platform. Sakti has a bachelor's degree in engineering and a master's degree in business administration. He holds several certifications in Hadoop, Spark, AWS, and Google Cloud. He is also an author of multiple technology blogs, workshops, white papers and is a public speaker who represents AWS in various domains and events.

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