Mridul M
Senior Staff Software Engineer at The Apache Software Foundation
California, United States
Summary
🤩
Rockstar🎓
Top SchoolMridul M is a Senior Staff Software Engineer based in California with over two decades of deep experience building JVM-based backend and runtime systems, and 13 years focused on large-scale data platforms. He has driven production-facing improvements at LinkedIn and Google and played senior engineering roles at Hortonworks, Yahoo and Sun Microsystems, bringing expertise in Java, server-side programming, MapReduce and Hadoop-era architectures. An active Apache committer and PMC member for Spark and Celeborn, he contributes to high-profile projects like Apache Spark and performance tooling such as Honest Profiler, where he optimized JVM sampling and thread visibility. Known for hardening core data processing components—block managers, schedulers and YARN integrations—he blends low-level performance tuning with pragmatic system design. His background suggests a rare combination of long-term runtime proficiency and hands-on open-source stewardship that accelerates both stability and scalability in big data systems.
13 years of coding experience
19 years of employment as a software developer
BTech, BTech at National Institute of Technology Calicut
Github Skills (29)
apache-spark10
spark10
performance-monitor10
c-language10
performance-analytics10
jvm10
code-profiling10
big-data10
hadoop10
java10
scala10
javas10
performance-analysis10
autobuild10
build-automation10
Programming languages (4)
Github contributions (5)
apache/spark
Oct 2017 - Oct 2017
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1899 reviews, 1 commit, 118 PRs in 1 day
Contributions summary:Mridul primarily contributed to the core functionality and stability of the Apache Spark analytics engine. Their work included implementing finer control over block managers and cleaners, addressing review comments, and preventing exceptions in rare cases, which indicates a focus on improving the efficiency and robustness of data processing operations. Additionally, the user modified the scheduler to improve the task management logic, ensuring that tasks are handled more reliably. They also addressed an issue concerning invalid output paths in relation to save operations.
analyticspythondata-processingsqlapache
mesos/spark
Dec 2012 - Sep 2013
Lightning-fast cluster computing in Java, Scala and Python.
Role in this project:Back-end Developer
Back-end DeveloperContributions:112 commits in 8 months
Contributions summary:Mridul's commits primarily focus on enhancing the Apache Spark core for Hadoop 2 YARN support. They have been implementing and modifying code related to building and configuring Spark with Hadoop 2 YARN, including adding Maven profiles and making changes to Hadoop-related utilities. The user's work also includes fixing a bug in atomic updates and addressing issues within the HadoopWriter class. Furthermore, the user has made improvements to checkpointing and other aspects of the Spark core.
pythoncluster-computinglightningsparkscala
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