Amazon EMR is the industry-leading cloud big data platform for processing vast amounts of data using open source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. In this tech talk, we introduce you to Amazon EMR design patterns and architectural best practices. We show how EMR can help you run Petabyte-scale analysis at less than half of the cost of traditional on-premises solutions and over 3x faster than standard Apache Spark. You'll learn how to spin up and spin down clusters as needed for short jobs and how to create highly available clusters that automatically scale to meet demand. Discover how Apache Hudi simplifies building data pipelines. You will also learn how to run EMR clusters on AWS Outposts for on-premises or hybrid deployments.
Learning Objectives:
*Learn how to design a big data environment using best practices
*Find out the best way to support Apache Spark, Hive, HBase and other open source applications
*See how to choose the right approach for both short- and long-running jobs
***To learn more about the services featured in this talk, please visit: aws.amazon.com/emr Subscribe to AWS Online Tech Talks On AWS:
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