Flume/Dataflow: Easy, Efficient Parallel Data Processing
May 18, 2016 at 3:30pm
CSE 691 (Gates Commons)
In this talk I’ll describe how the line of work starting with Flume and continuing with Dataflow strives to enable parallel data processing pipelines that are both easy to express and efficient to execute, ideally with no user configuring or tuning at all.
Craig Chambers joined Google in 2007. He leads projects aimed at making it easier to develop and evolve complex, efficient software systems, particularly massively parallel systems and web-based applications.
Prior to joining Google, he was a Professor in the Department of Computer Science and Engineering at the University of Washington, Seattle. He joined the faculty there in 1991. His research focused on programming languages, optimizing compilers, and object-oriented systems.
He received his S.B. degree from MIT in 1986, and his Ph.D. degree from Stanford in 1992, both in Computer Science.
He has won a number of awards, including the 2011 Dahl-Nygaard Senior Prize and several “best paper” awards.