Article
Spark in the Age of GPUs: A Practitioner's Perspective on What Comes Next
Apache Spark defined an era of distributed data processing. As the compute landscape shifts toward GPUs and tensor-native workloads, how can Spark evolve?
- Published 2026-03-22
- Author: Yves Ketemwabi Shamavu
- Topics: Apache Spark, GPU Computing, RAPIDS, Data Engineering
Overview
This essay examines the tension between the distributed data stack that powered the last decade and the GPU-first systems defining the next one. It frames Spark not as obsolete infrastructure, but as a platform that needs new execution strategies, better integration with accelerator-native workloads, and a clearer point of view on where orchestration ends and compute specialization begins.
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Key themes
The article focuses on Apache Spark, GPU Computing, RAPIDS, Data Engineering. The complete in-app essay expands on the engineering tradeoffs, implementation details, and practical lessons behind the topic.
- Apache Spark
- GPU Computing
- RAPIDS
- Data Engineering