Xiangpeng Hao is a software engineer and PhD candidate with 10 years of experience specializing in database storage engines, KV stores, and larger-than-memory indexes. He builds reliable systems in Rust with a strong emphasis on performance and correctness. His background blends academic research at the University of Wisconsin–Madison with industry internships at Google, Microsoft, and InfluxData, bringing research rigor to production problems. An active open-source contributor, he implemented BinaryView and Utf8View support and IPC handling in the official Apache Arrow Rust project and optimized Apache DataFusion to avoid unnecessary data copies, demonstrating deep knowledge of data structures, serialization, and query engine internals. Based in Madison, Wisconsin, he moves comfortably between low-level storage design and end-to-end data processing to turn complex research ideas into robust, deployable software.
Contributions:83 reviews, 44 PRs, 196 comments in 2 years
Contributions summary:Xiangpeng contributed to the official Rust implementation of Apache Arrow by adding new data types, specifically `BinaryView` and `Utf8View`, which involved modifying the schema and data structures. They also addressed code review suggestions and updated relevant files. Furthermore, the user worked on IPC format support for the new view types, including changes to the reader and writer. They demonstrated knowledge of data structures, serialization formats, and core Arrow data types.
Contributions:42 reviews, 29 PRs, 103 comments in 2 years
Contributions summary:Xiangpeng contributed primarily to the core data processing logic and query engine functionality. Their work involved implementing support for new data types like `Utf8View` and `BinaryView`, and addressing related issues, including bugs in aggregate functions. They also focused on optimizing performance by avoiding unnecessary data copies when reading arrow files and ensuring correct behavior in various data processing scenarios. Furthermore, the user worked on enhancing the project's functionality, such as fixing issues related to `COUNT(DISTINCT)` on string views and improving the handling of parquet settings.
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