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

Product typeBook

Published inMar 2022

PublisherPackt

ISBN-139781801071079

Edition1st Edition

Tools

AWS

Concepts

Big Data

Author (1)

Sakti Mishra

Section 3: Implementing Common Use Cases and Best Practices

This part of the book will explain how to implement the most common use cases of Amazon EMR, including batch ETL with Spark, real-time streaming with Spark Streaming, and handling UPSERT operations in S3 data lakes with Apache Hudi. Then it will explain how you can orchestrate your EMR jobs and how you can strategize on-premises Hadoop cluster migration to EMR, and finally, it will cover some of the best practices and cost optimization techniques you can follow while implementing your data analytics pipeline in EMR.

This section comprises the following chapters:

Chapter 9, Implementing Batch ETL Pipeline with Amazon EMR and Apache Spark
Chapter 10, Implementing Real-Time Streaming with Amazon EMR and Spark Streaming
Chapter 11, Implementing UPSERT on S3 Data Lake with Apache Spark and Apache Hudi
Chapter 12, Orchestrating Amazon EMR Jobs with AWS Step Functions and Apache Airflow/MWAA
Chapter 13...

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Author (1)

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.
Read more about Sakti Mishra

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