Run Apache Spark and Iceberg 4.5x faster than open source Spark with Amazon EMR
Big Data Blog
This article demonstrates that Amazon EMR 7.12 delivers 4.5x faster Apache Spark and Iceberg performance compared to open source alternatives.
- EMR 7.12 runs TPC-DS 3TB workloads 4.5x faster than open source Spark 3.5.6 with Iceberg 1.10.0
- Performance gains from metadata caching, parallel I/O, adaptive query planning optimizations
- Individual query speedups range from 1.1x to 13.6x, with q23b achieving fastest improvement
- Cost efficiency improved 3.6x compared to open source Spark and Iceberg
- EMR scanned 4.3x less S3 data and 5.3x fewer records than open source version
- Maintains Iceberg features: ACID transactions, time travel, schema evolution
- Benchmark used 9 r5d.4xlarge EC2 instances with 3TB TPC-DS dataset
- Available across EMR on EC2, Serverless, EKS, Outposts, and AWS Glue
Amazon EMR 7.12 provides significant performance and cost improvements for Spark and Iceberg workloads while preserving Iceberg's advanced features, making it viable for production analytics.
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