Xiaoyu Ma is a seasoned technology leader and CTO for APAC at PingCAP with 10+ years focused on Big Data, distributed systems, and query processing. He led the HTAP product development that produced TiDB’s TiFlash and TiSpark engines, and has hands-on contributions to core open-source projects like TiDB, TiFlash, and TiSpark—implementing merge join logic, JSON codecs, and critical data-locality and pushdown fixes. Based in Shanghai, he blends product GTM and solution engineering responsibilities across APAC while retaining deep backend engineering expertise. Colleagues know him for turning complex query-execution problems into pragmatic, production-ready solutions and for contributing subtle fixes that improve data correctness and performance.
10 years of coding experience
4 years of employment as a software developer
Bachelor Software Engineering, Bachelor Software Engineering at Tongji University
TiSpark is built for running Apache Spark on top of TiDB/TiKV
Role in this project:
Back-end Developer
Contributions:2 releases, 80 commits, 198 PRs in 2 years 10 months
Contributions summary:Xiaoyu primarily contributed to the back-end logic of the TiSpark project. Their commits focused on fixing issues related to range handling, equal translations, date pushdown, and decimal type bounding. They also worked on adding new features, such as batch register tables, and resolving data locality and snapshot timestamp related problems. These changes suggest a strong focus on improving the core functionality and data handling capabilities of TiSpark within the context of Apache Spark.
TiDB - the open-source, cloud-native, distributed SQL database designed for modern applications.
Role in this project:
Back-end Developer / Database Engineer
Contributions:8 reviews, 7 commits, 8 PRs in 3 years 2 months
Contributions summary:Xiaoyu primarily focused on implementing and improving the merge join functionality within the TiDB database system. Their contributions include adding the Merge Join operator with hints, refactoring the code for ordered merge joins to maintain sorting during planning, and fixing the sorting in the explain plan output. These changes involved modifications to the executor, plan, and test files, showcasing their expertise in database query execution and optimization.
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