EVENT DETAILS
Title: Thrifty Data Management
Abstract
The end of Moore's law will push database system designers to be more judicious with computation as the growth in data outpaces the availability of computational resources. Aggressively consuming resources to immediately and quickly complete the task at hand, is one source of wasted resources in modern data systems, especially when the systems expend unnecessary resources on queries or data that might change later. Building database systems that process more data by consuming the same amount of computing resources requires system re-architecture that recognizes, exploits, and integrates users' performance goals and workload characteristics.
In this talk, I will present our thrifty database system that aims to achieve performance goals with minimum resource consumption. I will focus on two specific components. First, I will present Predicate-Constraint, a framework that calculates guaranteed query result ranges based on a lightweight summary of data yet to be processed; thus, it saves additional computations when the data scientists accept a slightly approximated answer. Second, I will introduce Intermittent Query Processing, a new query optimization paradigm that allows database systems to reduce memory consumption when inactive without scarifying the performance. I will conclude by briefly discussing other promising directions.
Biography
Zechao Shang is a postdoctoral scholar working with Michael Franklin and Aaron Elmore at the University of Chicago. His research interest centers on the design and implementation of large-scale data management systems. He received his Ph.D. degree at the Chinese University of Hong Kong. He is the head coach of University of Chicago ICPC team.
TIME Monday February 24, 2020 at 12:00 PM - 1:00 PM
LOCATION Room 3514, Mudd Hall ( formerly Seeley G. Mudd Library) map it
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CONTACT Pam Villalovoz pmv@northwestern.edu
CALENDAR Department of Computer Science