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EMR Best Practices

Welcome to the EMR Best Practices Guides. The goal of this project is to offer a set of best practices, templates and guides for operating Amazon EMR. We elected to publish this guidance to GitHub so we could iterate quickly, provide timely and effective recommendations for variety of concerns, and easily incorporate suggestions from the broader community.

We currently have published guides for the following topics:

  • Applications Best practices on frameworks that can be installed on an EMR cluster, such as Hadoop, Spark, HBase, etc.
  • Cost Optimizations Recommended methods for reducing costs in AWS EMR clusters, such as instance type selection, spot instances, autoscaling, and data compression techniques.
  • Observability Techniques for monitoring and understanding performance metrics, logs, and system health indicators within an EMR cluster.
  • Reliability Guidelines for ensuring high availability and fault tolerance in EMR deployments, including multi-region setups, automatic failover mechanisms, and backup strategies.
  • Security Measures for securing EMR clusters against unauthorized access or data breaches
  • Troubleshooting Common issues faced when working with Amazon EMR and steps to resolve them. This may include connectivity problems, application errors, and configuration issues.

Contributing​

We encourage you to contribute to these guides. If you have implemented a practice that has proven to be effective, please share it with us by opening an issue or a pull request. Similarly, if you discover an error or flaw in the guidance we've already published, please submit a PR to correct it.