Eric Hwang
Distinguished Engineer at Starburst Data
San Jose, California, United States
Summary
🤩
Rockstar🎓
Top SchoolEric Hwang is a Distinguished Engineer with 14 years building high-throughput, distributed data systems and a track record of founding and scaling the Presto/Trino query engine. Based in San Jose, he led major engineering organizations at Starburst and Facebook, shipping the world’s first Trino SQL infrastructure-as-a-service and a streaming ingestion platform tested up to 100GBps per table. His work spans storage, serialization, and runtime performance—contributing core improvements to Trino/Presto and open-source projects like Airlift—while also architecting low-latency, production data pipelines that ran across hundreds of thousands of servers. Known for blending deep systems design with hands-on coding, he holds a BS in EECS from UC Berkeley and is comfortable moving between product-level architecture and low-level performance optimizations.
14 years of coding experience
BS Electrical Engineering and Computer Science, BS Electrical Engineering and Computer Science at University of California, Berkeley
Github Skills (27)
data-analysis10
data-engineering10
statistics10
query-optimization10
data-serialization10
statistic10
data-structure10
java10
serialization10
javas10
sql10
data-structures10
concurrency10
guava9
distributed-systems9
Programming languages (1)
Github contributions (5)
prestodb/presto
Jun 2013 - Mar 2017
The official home of the Presto distributed SQL query engine for big data
Role in this project:
Back-end Developer
Back-end DeveloperContributions:294 commits, 207 PRs, 118 pushes in 3 years 9 months
Contributions summary:Eric's commits primarily focus on implementing features for a dictionary-based SerDe (Serialization/Deserialization) for the Presto distributed SQL query engine. The code changes include the creation of `DictionarySerde` and `PackedLongSerde` classes, as well as related classes for managing data serialization. Their work included optimizing the representation of values to use for high-performance, and also included creating a framework that allows for a transactional data output.
distributed-sqlquerybigdataquery-enginesql
airlift/airlift
Aug 2012 - Jan 2023
Airlift framework for building REST services
Role in this project:Back-end Developer
Back-end DeveloperContributions:37 reviews, 189 commits, 24 PRs in 10 years 6 months
Contributions summary:Eric primarily focused on enhancing the `airlift/airlift` project's statistical analysis capabilities. They implemented weighted value support and manual percentile specifications within the `Distribution` class, improving data analysis flexibility. Several commits involved adding and exposing specific percentiles (P01, P05, P10, P25) within the `Distribution` class for easier access to key statistical insights. The user also contributed to the addition of `BoundedExecutor` and `ExecutorServiceAdapter` for managing concurrent tasks.
rest-apipythonrestrest-services
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