Shadow testing for on-prem Hadoop System & AWS EMR
As enterprises transition from on-prem Hadoop to cloud-native platforms like AWS EMR, ensuring performance parity and operational efficiency is critical.This paper introduces a custom Shadow Testing Framework designed to compare production workloads across both environments.By replaying real queries from on-prem systems in EMR, the framework captures execution metrics, identifies configuration gaps, and supports parallel testing across multiple clusters.Key architectural shifts-such as moving to Tez, S3 storage, and enhanced SQL authorization-are addressed.Our results show that, with tuning, EMR can meet or exceed on-prem performance while delivering scalability, reliability, and cost benefits.This approach enabled a productiongrade EMR deployment supporting thousands of daily queries.
Publication Details
- Journal
- International Research Journal of Modernization in Engineering Technology and Science
- Published
- 2025-05-07
- DOI
- https://doi.org/10.56726/irjmets75169
- Primary Topic
- Anomaly Detection Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00