Robert Evans
Distinguished Distributed System Software Engineer at The Apache Software Foundation
Urbana, Illinois, United States
Summary
🤩
Rockstar🎓
Top SchoolRobert Evans is a Distinguished Distributed System Software Engineer with 14 years of experience building and optimizing large-scale open source data platforms, currently driving GPU-accelerated data processing at NVIDIA. He is a long-standing Apache committer and PMC member for Hadoop and Storm, with deep contributions to core projects like Apache Spark, Hadoop, cuDF, and the NVIDIA Spark-RAPIDS plugin. His work spans backend systems, execution engines, and data serialization—highlighted by columnar processing enhancements in Spark, checksum and shuffle fixes in Hadoop, and GPU-focused optimizations in RAPIDS. Based in Urbana, Illinois, he combines low-level systems expertise (from early Linux-on-ARM work) with modern big-data performance engineering. Colleagues rely on him for pragmatic, production-ready fixes that reduce latency and memory pressure across distributed pipelines. He publishes most of his work as open source, making complex system improvements discoverable and reusable.
14 years of coding experience
17 years of employment as a software developer
The University of Utah
Portuguese
Github Skills (47)
code-optimization10
apache-spark10
debug10
decimals10
filesystem10
c-language10
spark10
apache-storm10
data-engineering10
apache-hadoop10
bigdecimal10
big-data10
decimal-numbers10
data-serialization10
distributed-systems10
Programming languages (8)
Github contributions (5)
NVIDIA/spark-rapids
Jun 2019 - Jan 2023
Spark RAPIDS plugin - accelerate Apache Spark with GPUs
Role in this project:
Back-end Developer
Back-end DeveloperContributions:4315 reviews, 586 commits, 966 PRs in 3 years 8 months
Contributions summary:Robert contributed code to the `nvidia/spark-rapids` repository, specifically focusing on performance optimizations and support for window functions. Their commits modified source code related to arithmetic expressions, decimal data types, and operations, suggesting they were involved in improving the GPU acceleration capabilities. The user also made changes to improve code clarity and address potential memory leaks within the codebase.
gpu-accelerationgpuapachebig-dataspark
rapidsai/cudf
Jun 2019 - Dec 2022
cuDF - GPU DataFrame Library
Role in this project:Back-end Developer & Data Engineer
Back-end Developer & Data EngineerContributions:701 reviews, 421 commits, 246 PRs in 3 years 6 months
Contributions summary:Robert's commits focus on implementing and improving Java APIs and contributing to the Java-based backend infrastructure of the project, specifically within the context of a GPU DataFrame Library (cuDF). They have primarily worked on adding new functionalities like segmented reductions, data partitioning, column-to-row data transformations, and JSON parsing to enhance the data processing capabilities. The user's contributions extend to improving the data processing, adding support for decimal128, and optimizing the performance of existing APIs, indicating involvement in both feature development and optimization efforts for a data engineering workflow.
cudadataframe-librarydata-analysiscppcudf
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