Lantao Jin
Maintainer at OpenSearch Project
Shanghai, Shanghai, China
Summary
🤩
Rockstar🎓
Top SchoolLantao Jin is a seasoned distributed systems and big-data engineer with 13 years of experience driving Spark internals and cluster-scale performance across leading companies including AWS, ByteDance, eBay, Meituan and Alibaba. At AWS he led EMR Spark performance, Hive, and OpenSearch-related efforts, and now maintains OpenSearch-SQL and OpenSearch-Spark while contributing to Apache Spark core improvements. His work spans TPC-DS optimizations, adaptive query execution, materialized views, Spark upgrades and operational governance—delivering measurable gains in stability and resource efficiency for large production fleets. A pragmatic leader, he combines hands-on kernel-level fixes (Kryo, YARN, executor metrics) with team-building and OKR-driven roadmaps. Active in open source, he has influenced one of the most famous big-data engines (Apache Spark) and maintains critical connectors for OpenSearch, reflecting both deep system expertise and practical product impact.
12 years of coding experience
9 years of employment as a software developer
Master of Science (MS) Computer Science, Master of Science (MS) Computer Science at Nanjing University of Aeronautics and Astronautics
Stackoverflow
11reputation
406reached
0answers
1question
Github Skills (17)
spark10
data-engineering10
big-data10
java10
scala10
javas10
yarnpkg9
yarn39
sql9
performance-optimization9
kryo9
yarn-berry9
yarn29
debug8
debugging8
Programming languages (3)
Github contributions (5)
apache/spark
Apr 2019 - Jan 2021
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Back-end Developer & Data Engineer
Back-end Developer & Data EngineerContributions:31 reviews, 9 commits, 101 PRs in 1 year 9 months
Contributions summary:Lantao primarily contributed to the Apache Spark codebase by enhancing data processing capabilities and improving the stability and efficiency of the system. Their contributions include adding metadata to SparkPlanInfo for better event logging, refactoring code for improved maintainability, and adding garbage collection information to executor metrics for better memory management and performance analysis. Additionally, the user worked on resolving issues related to Kryo serialization and YARN resource management, demonstrating a focus on core system functionalities.
analyticspythondata-processingsqlapache
LantaoJin/calcite
Nov 2018 - Feb 2025
Mirror of Apache Calcite
Contributions:4 pushes, 3 branches in 6 years 3 months
javaapacheapache-calcitecalcite
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