Qi Zhu
Software Engineer at The Apache Software Foundation
Nanjing City, Jiangsu, China
Summary
🤩
Rockstar🎓
Top SchoolQi Zhu is a seasoned software engineer with 11 years of experience specializing in distributed systems, big-data scheduling, and database engines. Based in Nanjing, he is an active Apache committer across DataFusion, Hadoop/YuniKorn, Spark, and contributes performance and correctness fixes to core SQL query and scheduler logic. He has driven production-grade improvements at companies like Cloudera and iQiyi and now works as a Rust database engineer at Massive, bringing systems-level rigor to modern cloud-native stacks. Qi’s notable open-source impact includes optimizing FULL OUTER JOIN and LIMIT behavior in Apache DataFusion and enhancing multi-node allocation and metrics in Hadoop YARN—work that tangibly improves large-cluster efficiency. Comfortable across Rust, Java, and backend systems, he blends deep protocol-level knowledge with pragmatic benchmarking and memory optimizations. Colleagues describe him as a contributor who surfaces subtle correctness issues and turns them into measurable performance gains.
10 years of coding experience
8 years of employment as a software developer
硕士 信息网络, 硕士 信息网络 at Nanjing University of Posts and Telecommunications
Github Skills (20)
cap10
testing10
apache-hadoop10
resource-management10
java10
scheduler10
fusion10
javas10
sched10
performance-optimization10
sql10
yarn310
yarnpkg10
yarn-berry10
query-engine10
Programming languages (11)
Github contributions (5)
apache/datafusion
Jan 2024 - Apr 2025
Apache DataFusion SQL Query Engine
Role in this project:
Back-end Developer
Back-end DeveloperContributions:100 reviews, 33 PRs, 261 comments in 1 year 2 months
Contributions summary:Qi primarily contributed to the Apache DataFusion SQL query engine by fixing bugs and improving the system's performance. Their work involved resolving issues related to the `FULL OUTER JOIN` and `LIMIT` functionality, and correcting incorrect limit pushdown rules. They also added new benchmark tests for improved analysis and data processing capabilities, including supporting `Utf8View` datatype and optimizing code to improve memory usage. Their contributions focused on core query engine functionality, performance optimization, and testing.
querypythonquery-enginedataframerust
apache/hadoop
Dec 2020 - Sep 2021
Apache Hadoop
Role in this project:Back-end Developer
Back-end DeveloperContributions:25 reviews, 12 commits, 25 PRs in 9 months
Contributions summary:The user, Qi Zhu, primarily focused on enhancing the CapacityScheduler within the Hadoop YARN project. Their contributions include implementing multi-node allocation logic, optimizing scheduling, and adding cluster metrics for event queue sizes. These changes involved modifications to core scheduling algorithms, testing infrastructure, and monitoring capabilities, directly improving the resource management and performance of the Hadoop cluster. Additionally, the user addressed issues in the weight mode for queue allocation, ensuring correct assignment of node labels.
apachebig-datasparkhadoopjava
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