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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
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Author (1):
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Sakti Mishra Sakti Mishra
Author Profile Icon Sakti Mishra
Sakti Mishra
LinkedIn
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).rnHe 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.rnSakti 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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Toc

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

Summary

Over the course of this chapter, we have dived deep into Apache Hudi and looked at its features, use cases, and how it is integrated with AWS and Amazon EMR.

We have covered how to create an EMR notebook that points to a long-running EMR cluster and how to use the notebook for interactive development. To showcase interactive development, we explained a small use case using Spark and Hudi, which can enable you to do UPSERT transactions on top of a data lake.

That concludes this chapter! Hopefully, this has helped you get an idea of how to use EMR notebooks for interactive development. In the next chapter, we will explain how to build a workflow to build a data pipeline using Amazon EMR.

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Authors (1)

Profile icon Sakti Mishra
Sakti Mishra
LinkedIn icon
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.
Read more
See other products by Sakti Mishra

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