Hao Luo - Software Engineer at Roblox

Hao Luo

Software Engineer at Roblox

San Francisco, California, United States

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Summary

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Senior

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Top School

Hao Luo is a software engineer with 11 years of experience building high-performance data and compute platforms, currently working at Roblox in San Francisco. He holds a Ph.D. in Computer Science from the University of Nebraska–Lincoln and has driven backend improvements at top-tier companies including Twitter and Airbnb. Hao is experienced in optimizing storage and query engines—his open-source contributions to Trino/Presto include Parquet reader optimizations, reducing redundant filesystem calls and adding dynamic batching to boost throughput. He has a strong research background and practical systems engineering skills in Python, MATLAB, and large-scale C++/Java services. Colleagues rely on him for tackling tricky I/O and data-processing bottlenecks, a strength honed from work on NVDIMM/transactional key-value stores and concurrent B+Tree implementations.

11 years of coding experience

12 years of employment as a software developer

Doctor of Philosophy (Ph.D.) Computer Science, Doctor of Philosophy (Ph.D.) Computer Science at University of Nebraska-Lincoln

Github Skills (20)

big-data10

query-optimization10

hadoop10

java10

javas10

hive10

sql10

parquet10

query-engine10

presto10

data-set9

data-model9

jdbc9

databases9

user-data9

Programming languages (6)

JavaC++CJavaScriptGoPython

Github contributions (5)

prestodb/presto

Feb 2018 - Sep 2019

The official home of the Presto distributed SQL query engine for big data

Role in this project:

Back-end Developer

Contributions:18 commits, 7 PRs, 25 comments in 1 year 6 months

Contributions summary:Hao primarily focused on optimizing and improving the Presto query engine. They made significant contributions to the `presto-hive` module, refactoring code within the `ParquetPageSourceFactory` to reduce redundant HDFS calls and improve performance. Furthermore, the user added support for extra credentials in the JDBC driver and Presto CLI, as well as made changes to the internal identity and connector identity objects to accomodate the new changes. The user also addressed related issues with improved toString methods and added a system table for credential listing.

distributed-sqlquerybigdataquery-enginesql

trinodb/trino

Jan 2019 - Sep 2022

Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)

Role in this project:

Back-end Developer

Contributions:14 PRs, 58 comments, 2 issues in 3 years 8 months

Contributions summary:Hao primarily focused on optimizing the Parquet reader within the Trino query engine. They addressed performance bottlenecks by removing redundant file system operations and implementing dynamic batch sizing for improved data processing. They also updated and refactored test components related to Parquet file format processing and added a new procedure for syncing table partitions in Hive, showcasing their expertise in data storage and retrieval optimizations.

prestodbdbmsindexingjdbcbigdata

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