Huaijin Hao
Software Engineer at OpenObserve
Shenzhen, Guangdong Province, China
Summary
🤩
Rockstar🎓
Top SchoolHuaijin Hao is a software engineer based in Shenzhen with six years of experience specializing in observability, distributed systems, and database systems. Currently at OpenObserve, he works on backend and database engineering for a petabyte-scale observability platform that aims to be a high-performance, cost-effective alternative to Elasticsearch/Splunk/Datadog. His open-source contributions include performance optimizations, query cache FIFO, and Parquet merge improvements in OpenObserve, as well as core planner and feature work in the Apache DataFusion SQL engine. Known for pragmatic refactors and careful correctness fixes (e.g., count(distinct) and explain-plan improvements), he blends deep systems thinking with hands-on performance tuning. He holds education from Harbin Institute of Technology, Shenzhen, and quietly focuses on making large-scale data pipelines faster and more reliable.
7 years of coding experience
哈尔滨工业大学（深圳）
Github Skills (15)
fusion10
apache-arrow10
query-engine10
rust10
sql10
arrows10
arrow-js10
compress9
data-engineering9
performance-optimization9
database-design9
parquet9
compression9
big-data8
query-optimization8
Programming languages (9)
Github contributions (5)
openobserve/openobserve
Jan 2024 - Jul 2026
Open source observability platform for logs, metrics, traces, frontend monitoring, pipelines and LLM observability. A sophisticated, simple and highly performant alternative to Datadog, Splunk, and Elasticsearch with 140x lower storage costs and single binary deployment.
Role in this project:
Back-end Developer & Database Engineer
Back-end Developer & Database EngineerContributions:299 reviews, 291 PRs, 1084 pushes in 2 years 6 months
Contributions summary:Huaijin contributed to the backend functionality of the OpenObserve project. They implemented SQL mode support for alert URLs and refactored the code for count(distinct) to get the correct results. Their work also included optimizing ingester speed, enhancing field search by using hash maps, and improving the performance of merging Parquet files when dealing with a high number of fields. They also worked on the implementation of FIFO for query cache and resolving issues for the metric related features.
datadogelasticsearchfrontendllmmonitoring
apache/datafusion
May 2023 - Jun 2026
Apache DataFusion SQL Query Engine
Role in this project:Back-end Developer
Back-end DeveloperContributions:99 reviews, 43 PRs, 149 comments in 3 years 1 month
Contributions summary:Huaijin contributed to the Apache DataFusion SQL query engine by implementing and modifying core functionalities. Their work involved refactoring code, moving and updating file compression types, and adding new features like `join_on` to the logical plan builder. They also addressed bugs and implemented features to improve the explain plan and support for custom sources.
sql-queryarrowbig-datadataframedatafusion
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