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AI-assisted Spark UDF rewrites cut one 600-billion-row workload from 274.55 to 12.78 hours

developer.nvidia.com by Elizabeth Goodman 7 min read Editor score 8/10

NVIDIA describes agent-guided UDF rewrites and reports one operator dropping from 274.55 to 12.78 hours across 600 billion rows; a company converted more than 30 production UDFs. The verification and benchmarking workflow offers a concrete path for reducing CPU fallbacks in GPU-accelerated Spark.

What

cuDF skills for Apache Spark guide agents through testing, rewriting, benchmarking and integrating Spark UDFs for GPU acceleration.

How

A customer converted more than 30 production UDFs; one rewrite reduced operator time from 274.55 to 12.78 hours on a 600-billion-row workload.

Why it matters

Replacing opaque UDFs with GPU-executable equivalents can prevent CPU fallback and data-transfer overhead in large Spark workloads.

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