A comprehensive technical handbook covering AWS EMR, Amazon's managed big data platform for Apache Spark, Hadoop, Hive, and Presto. This guide covers cluster architecture, EMR Serverless, step execution, instance fleets, Spot integration, security with IAM and Lake Formation, monitoring, cost optimization, and production deployment best practices.
Chapters
EMR Cluster Architecture and Node Roles
20 min read
Provisioning EMR Clusters via CLI and Infrastructure as Code
25 min read
Mastering EMR Instance Fleets and Instance Groups
20 min read
Optimizing Costs with Spot Instances and Auto Scaling
20 min read
Deep Dive into Apache Spark on EMR
25 min read
Hadoop Ecosystem: HDFS, YARN, and MapReduce Configuration
20 min read
Querying Data with Hive and Presto on EMR
15 min read
Implementing EMR Serverless for Transient Workloads
20 min read
Managing EMR Steps and Workflow Orchestration
15 min read
Data Security: IAM Roles for EMR and EC2
20 min read
Fine-Grained Access Control with AWS Lake Formation
25 min read
Data Encryption at Rest and in Transit
15 min read
Monitoring, Logging, and Debugging with CloudWatch and EMR UI
20 min read
Advanced Tuning: Spark Memory Management and Partitioning
25 min read
Integrating EMR with S3 Data Lakes and Glue Data Catalog
20 min read
Production Deployment Best Practices and CI/CD Pipelines
20 min read
Troubleshooting Common EMR Performance Bottlenecks
15 min read
Case Study: Migrating On-Premise Hadoop to EMR
20 min read
Career Roadmap: Certifications and Future Trends in Big Data
10 min read