Jonathan Hung
Staff Software Engineer at The Apache Software Foundation
New York City Metropolitan Area United States
Summary
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Rockstar🎓
Top SchoolJonathan Hung is a Staff Software Engineer based in the New York City area with 10 years of experience building and operating large-scale distributed systems, particularly around Hadoop and YARN. At LinkedIn he progressed from Hadoop developer to staff engineer on the Grid team, delivering backend and scheduler improvements that bridge configuration, deployment, and runtime resilience. An active Apache committer and Hadoop PMC member, he has contributed production-grade features like file-based CapacityScheduler configuration and integrations that make big-data workflows more manageable and dynamic. His open-source work on TonY and Azkaban shows a practical focus on making ML and workflow frameworks run reliably on Hadoop clusters, including Azkaban and Azkaban-related tag/config injection and TensorFlow environment fixes. Trained at Stanford (BS EE, MS CS), he combines academic rigor with hands-on DevOps and backend engineering to simplify complex distributed deployments.
10 years of coding experience
6 years of employment as a software developer
Bachelor of Science (BS), Electrical Engineering, Bachelor of Science (BS), Electrical Engineering at Stanford University
Github Skills (22)
hadoop-mapreduce10
cap10
testing10
apache-hadoop10
configuration-management10
workflow-engine10
mapreduce10
hadoop10
java10
scheduler10
javas10
sched10
yarn310
yarnpkg10
yarn-berry10
Programming languages (4)
Github contributions (5)
tony-framework/TonY
Sep 2018 - Oct 2019
TonY is a framework to natively run deep learning frameworks on Apache Hadoop.
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:2 releases, 13 reviews, 31 commits in 1 year 1 month
Contributions summary:Jonathan primarily focused on modifying the TonY framework's core components to improve configuration and deployment on Hadoop. They refactored configuration file handling, introduced configurable retry mechanisms for resource managers, and implemented features for Azkaban integration. Additionally, the user addressed testing and added environment variables to ensure proper TensorFlow configuration within the framework.
horovoddeep-learningmachine-learningapachehadoop-yarn
apache/hadoop
Jan 2017 - Feb 2021
Apache Hadoop
Role in this project:Back-end Developer
Back-end DeveloperContributions:201 commits, 2 PRs, 1 comment in 4 years 1 month
Contributions summary:Jonathan contributed to the Apache Hadoop project by implementing features related to the CapacityScheduler, focusing on the use of a configuration store. The changes included adding a `CSConfigurationProvider` interface and a `FileBasedCSConfigurationProvider` implementation. These modifications allow the CapacityScheduler to load configurations from an external file, improving manageability and potentially enabling dynamic updates to the scheduler's behavior. Furthermore, the commits introduce changes to testing and web service configuration related to configuration management.
apachebig-datasparkhadoopjava
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