Write Optimization
Michael A. Bender
Stony Brook University
11am in ITEB 336 on Friday March 4
Abstract:
This talk addresses the problem of ingesting and indexing massive data sets. Traditional storage systems (databases, file systems, document stores) based on B-trees, are I/O-bound on many workloads. This talk explains how write-optimized indexing can substantially reduce the number of I/Os associated with some traditional workloads, enabling some applications to scale by an order of magnitude. The talk explores write-optimization from the perspective of the foundational theory, implementation, and technology transfer.
Speaker Bio:
Michael A. Bender is a professor of computer science at Stony Brook University. He was Founder and Chief Scientist at Tokutek, Inc, an enterprise database company, which was acquired by Percona in 2015. Bender’s research interests span the areas of data structures and algorithms, I/O-efficient computing, scheduling, and parallel computing. He has coauthored over 100 articles on these and other topics. He has won several awards, including an R&D 100 Award, a Test-of-Time award, two Best Paper Awards, and five awards for graduate and undergraduate teaching. Bender received his B.A. in Applied Mathematics from Harvard University in 1992 and obtained a D.E.A. in Computer Science from the Ecole Normale Superieure de Lyon, France in 1993. He completed a Ph.D. on Scheduling Algorithms from Harvard University in 1998. He has held Visiting Scientist positions at both MIT and King’s College London.