Mingliang Liu
Apache Ratis Committer And PMC
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolMingliang Liu is a Senior Staff Software Engineer with 13 years of experience building and operating large-scale distributed storage and real-time stream processing systems from AWS and Hortonworks to Salesforce and Netflix. As an Apache committer and PMC for Ratis and Hadoop, he combines deep production expertise in HDFS, HBase, Flink, and Iceberg with active open-source stewardship, contributing bug fixes, performance improvements, and test automation to high-profile projects. At Salesforce he led HA work for Apache Phoenix and cloud-native HBase/Ceph deployments on Kubernetes; at Netflix he focuses on real-time streaming and connector performance. Known for pragmatic refactors (e.g., Iceberg writer and Flink checkpoint fixes) and reliability-first engineering, he routinely surfaces subtle test and robustness issues that prevent production incidents. He holds a PhD in Computer Science from Tsinghua University and is based in San Francisco, blending research rigor with hands-on system design. An “innocent contributor” by GitHub bio, he quietly drives substantial backend improvements across major OSS data platforms.
13 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at Tsinghua UniversityBachelor of Science, Bachelor of Science at China Three Gorges University
Stackoverflow
5,627reputation
244kreached
27answers
0questions
amazon-dynamodb
top-1%
Github Skills (40)
hbase10
checkpoint10
runtimes10
apache-flink10
back-end-development10
testing10
databases10
big-data10
hdfs10
run-time10
flink-sql10
java10
checkpointing10
amazon-dynamodb10
javas10
Programming languages (13)
Github contributions (5)
apache/hadoop
Aug 2016 - Jun 2021
Apache Hadoop
Role in this project:
Back-end Developer
Back-end DeveloperContributions:71 reviews, 339 commits, 42 PRs in 4 years 10 months
Contributions summary:Mingliang's commits primarily focus on enhancing the Hadoop Distributed File System (HDFS). Their work includes implementing improvements to the caller context builder, documenting tools, fixing misleading usage messages, and resolving intermittent test failures. The user also contributed to making the test code more robust by fixing file corruption and increasing timeouts.
apachebig-datasparkhadoopjava
Netflix/mantis
Oct 2021 - Jan 2023
A platform that makes it easy for developers to build realtime, cost-effective, operations-focused applications
Role in this project:Back-end Developer
Back-end DeveloperContributions:36 reviews, 12 commits, 17 PRs in 1 year 3 months
Contributions summary:Mingliang's primary contributions center around enhancements to the Mantis platform, specifically focusing on the `mantis-client` and `mantis-connectors` modules. They've made code cleanups, added parameters to Iceberg writer stage, fixed parameter access, and updated dependencies, with significant code modifications in the `mantis-client` library. Furthermore, the user made changes for integrating ZSTD compression codec and replacing HadoopOutputFile with Iceberg native IO interface. These changes suggest a strong focus on backend development, performance improvements, and connector enhancements within the Mantis ecosystem.
realtimeeffectivefor-developersfocusedcost-effective
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