Boyang Peng
Apache Spark Contributor at The Apache Software Foundation
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolBoyang Peng is an experienced distributed systems engineer with 11 years building and hardening low-latency stream processing and messaging platforms from startup to enterprise scale. Based in the San Francisco Bay Area, he contributes to Apache Spark and is a committer and PMC member on multiple Apache projects including Pulsar, Storm, and Heron, where he helped create Pulsar Functions, Pulsar IO, and Pulsar SQL. His open-source contributions include enhancing Spark’s Kafka source (adding Trigger.AvailableNow and custom streaming metrics) and expanding Heron’s Windows Bolt, stateful windowing, and testing coverage—work that improves reliability for widely used real-time pipelines. He has held technical leadership roles at Databricks, Splunk, and Streamlio, leading teams and architecting streaming solutions with Flink, Pulsar, and Spark. Known for pragmatic refactoring and test-driven improvements, he blends research-driven scheduling ideas from his Yahoo/UIUC work with production-grade engineering.
11 years of coding experience
9 years of employment as a software developer
Bachelor of Science (BS), Computer Engineering, Bachelor of Science (BS), Computer Engineering at UC Santa BarbaraUniversity of Illinois Urbana-Champaign
English, Chinese
Github Skills (10)
scala10
javas10
big-data10
kafka10
stream-processing10
spark10
sql10
java10
testing10
metric9
Programming languages (8)
Github contributions (5)
apache/incubator-heron
Aug 2017 - Jul 2018
Apache Heron (Incubating) is a realtime, distributed, fault-tolerant stream processing engine from Twitter
Role in this project:
Back-end Developer
Back-end DeveloperContributions:51 commits, 66 PRs, 10 pushes in 10 months
Contributions summary:Boyang primarily focused on enhancing the Apache Heron stream processing engine, specifically by adding support for Windows Bolt. They also improved the windowing functionality, refactoring code to reduce complexity and using timers. They introduced changes related to stateful windowing, implemented additional tests and incorporated various metrics from Apache Storm.
fault-tolerantstream-processingtwitterheronstreaming
apache/spark
Feb 2022 - Jan 2023
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:Back-end Developer
Back-end DeveloperContributions:197 reviews, 2 commits, 21 PRs in 11 months
Contributions summary:Boyang contributed to the Apache Spark project by implementing and fixing features related to the Kafka data source. Their work involved adding support for the `Trigger.AvailableNow` trigger in the Kafka source, enabling processing of all available data in multiple micro-batches. They also addressed a flaky test in the `KafkaMicroBatchSourceSuite`, improving the reliability of the testing infrastructure. Furthermore, the user enhanced the codebase by adding support for reporting custom metrics from streaming sinks.
apache-sparkpythonscalarjava
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