Li Lu
Software Engineer at The Apache Software Foundation
Palo Alto, California, United States
Summary
👤
Senior🎓
Top SchoolLi Lu is a seasoned software engineer with 15 years of experience building scalable distributed systems and data infrastructure, currently working at Meta and based in Palo Alto. He is a long-time Apache committer and PMC member for Hadoop (since 2016) and a contributor to Apache Ratis, bringing deep expertise in YARN, MapReduce, and reliability improvements to large-scale open-source ecosystems. Previously he led engineering and data initiatives as Director of Engineering at LaiOffer and contributed systems-level performance work at Google and Microsoft Research during his early career. Li holds advanced CS degrees from the University of Rochester and a BEng from Tsinghua, and his open-source contributions include pragmatic bug fixes and reliability enhancements to the widely used Apache Hadoop project. Notably, his work often targets subtle concurrency, exception-handling, and timeline-service issues that materially improve cluster stability and developer ergonomics.
15 years of coding experience
7 years of employment as a software developer
Master of Science (MS), Computer Science, Master of Science (MS), Computer Science at University of RochesterBachelor of Engineering (BEng), Computer Science and Technology, Bachelor of Engineering (BEng), Computer Science and Technology at Tsinghua University
Github Skills (18)
hadoop-mapreduce10
apache-hadoop10
mapreduce10
java10
javas10
yarn310
yarnpkg10
yarn-berry10
yarn210
hbase9
concurrency8
apidoc8
api8
exception-handling8
debug8
Programming languages (2)
Github contributions (5)
apache/hadoop
Oct 2015 - Aug 2017
Apache Hadoop
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:65 commits in 1 year 10 months
Contributions summary:Li primarily focused on improving the Apache Hadoop ecosystem, specifically addressing issues within the YARN framework and MapReduce CLI. Their contributions include bug fixes related to timer tasks, exception handling, and concurrency in the timeline service, as well as enhancing the JobHistoryServer CLI. Furthermore, the user implemented code changes that convert a 404/Not Found into a FileNotFoundException. The user also worked on improving the reliability and efficiency of the Hadoop ecosystem, making various improvements in the timeline service.
apachebig-datasparkhadoopjava
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