Max Seiden on Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals
In under 15 pages, this paper describes the first principles of OLAP with such clarity and foresight that, over 20 years later, it's direct contributions are still highly relevant to anyone building products and technologies in the analytics space.
Max is a systems engineer with a deep interest in making information accessible to anyone with a question. He's currently at Sigma Computing, where he spends most of his time hacking on query compilation, optimization, and code generation. Before Sigma, he was at Platfora (now Workday) working on data cubes and materialized views using Spark, MapReduce, and the bundle-of-joy that is the Hadoop Ecosystem. Max received a bachelors in computer science from the University of Michigan. When he isn't writing code, you can hear him playing 🎷 in @thefellswoop (instagram)
Aaron Goldman on Chord: A Scalable Peer-to-peer Lookup Service for Internet Applications
This is a foundational paper in the area of Distributed Hash Tables (DHTs).
Chord is a Key/Value store that guarantees queries make a logarithmic number hops and that keys are well balanced.
This DHT paper should be in the mine of anyone building large-scale fault tolerant systems.
Aaron Goldman did his graduate work at the Georgia Institute of Technology where he studied Electrical and Computer Engineering.
He has worked on radar systems for the US Department of Defense,
Anti Abuse at Google, and Runtime Application Self Protection at tCell.
In his spare time he is building a new internet out of immutable data.