Chandni Singh
Senior Staff Engineer at The Apache Software Foundation
Cary, North Carolina, United States
Summary
🤩
Rockstar🎓
Top SchoolChandni Singh is a Senior Staff Engineer with 12 years of experience building and scaling large-scale data processing platforms, now at Cloudera and active as a committer across multiple Apache projects. She has deep expertise in shuffle infrastructure, batch and stream processing, and has driven production-grade improvements to Apache Spark’s push-based shuffle and external shuffle service. At LinkedIn she led deployment of a remote shuffle service based on Apache Celeborn and contributed security features like SASL authentication to the project. Her contributions span core stability fixes, network and data-transfer optimizations, and thoughtful API and metrics enhancements across Apex, Spark, Hadoop, and Celeborn. Based in Cary, NC, she combines open-source stewardship with hands-on backend engineering to solve reliability and scalability challenges at internet scale. A less obvious strength is her track record of bridging project-level fixes (e.g., equals/hashCode and checkpointing in Apex) with system-wide operational improvements that reduce data corruption and timeout incidents.
12 years of coding experience
13 years of employment as a software developer
B.Tech., Computer Science and Engineering, B.Tech., Computer Science and Engineering at Dr. A.P.J. Abdul Kalam Technical University (UPTU)MSE, Computer and Information Science, MSE, Computer and Information Science at University of Pennsylvania
Github Skills (18)
spark10
big-data10
data-structure10
java10
scala10
javas10
data-structures10
backend10
netty9
apidoc9
yarnpkg9
yarn39
api9
yarn-berry9
yarn29
Programming languages (4)
Github contributions (5)
apache/apex-core
Mar 2014 - Aug 2016
Mirror of Apache Apex core
Role in this project:
Backend Developer
Backend DeveloperContributions:156 commits, 43 PRs, 224 comments in 2 years 5 months
Contributions summary:Chandni primarily focused on enhancing the core functionalities of the Apache Apex core. They added `equals` and `hashCode` methods to key classes within the logical plan, which indicates improvements in data structure management. The user also addressed a checkpointing issue related to the `DefaultUnifier` and made changes to the aggregator system to support the collection of custom metrics from operators. Additionally, the user contributed to the web interface by adding an API endpoint to retrieve logger information.
apacheapex
apache/spark
Dec 2020 - Jul 2022
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:Back-end Developer
Back-end DeveloperContributions:637 reviews, 9 commits, 28 PRs in 1 year 7 months
Contributions summary:Chandni primarily contributed to the Apache Spark project by implementing and fixing issues related to the external shuffle service. They worked on improving the stability and reliability of the shuffle service, addressing issues like timeouts and data corruption, which involved adding new features and resolving bugs. Their work focused on enhancing the push-based shuffle mechanism within the Spark ecosystem, including supporting executors pushing shuffle blocks, and integrating the shuffle service with the YARN deployment mode. The changes involved significant modifications to the core shuffle logic and network components, optimizing data transfer and handling exceptions.
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