Ted Dunning
Fellow And CTO For Data Fabric
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolTed Dunning is Fellow and CTO for Data Fabric at HPE in Mountain View, bringing 15 years of experience building scalable data platforms and production analytics. He is an active Apache PMC member and ex-board member who bridges open-source stewarding with hands-on engine work. His contributions include implementing core pieces of Apache Drill’s planner and interpreter and authoring the widely used t-digest data structure for accurate streaming quantiles. He also serves on PMC projects such as Zookeeper and Mahout, underscoring deep expertise in distributed systems and machine-learning infrastructure. With a PhD from Sheffield and an MSc from New Mexico State, he specializes in turning research-grade algorithms into robust, tested production code.
15 years of coding experience
PhD, PhD at Sheffield UniversityMSc, MSc at New Mexico State University
German
Stackoverflow
1,897reputation
162kreached
67answers
0questions
parallel-processing
top-5%
hadoop
top-5%
Github Skills (25)
algorithm10
algorithms10
apache-drill10
data-structure10
java10
javas10
query-parser10
antlr10
drilldown10
query-engine10
data-structures10
querying10
hadoop9
big-data9
sql9
Programming languages (18)
Github contributions (5)
tdunning/t-digest
Nov 2013 - Feb 2022
A new data structure for accurate on-line accumulation of rank-based statistics such as quantiles and trimmed means
Role in this project:
Back-end Developer
Back-end DeveloperContributions:7 reviews, 364 commits, 54 PRs in 8 years 4 months
Contributions summary:Ted primarily focused on the development of the `t-digest` data structure, contributing to the core source code. They added source code files and made changes to existing ones, which involved the implementation of the core functionality of this data structure, which accumulates rank-based statistics like quantiles. They also refactored and added tests for verifying the accuracy and functionality of the `t-digest` data structure.
statisticsquantileson-linequantileaccumulation
apache/drill
Sep 2012 - Jan 2018
Apache Drill is a distributed MPP query layer for self describing data
Role in this project:Back-end Developer
Back-end DeveloperContributions:34 commits, 4 PRs, 26 comments in 5 years 5 months
Contributions summary:Ted contributed to the Apache Drill project by implementing and improving the plan parser, which is essential for query execution. Their work involved developing a plan parser using ANTLR, and then improving error messages, debugging, and fixing tests. They also began working on the physical plan interpreter, which indicates a focus on the core query processing engine of Drill.
jdbcdatastreambig-datadatabasehadoop
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