期刊名称：Bulletin of the Technical Committee on Data Engineering
出版年度：2011
卷号：34
期号：01
出版社：IEEE Computer Society
摘要：The biggest change in the TPC benchmarks in over two decades is now well underway – namely
the addition of an energy efficiency metric along with traditional performance metrics. This change
is fueled by the growing, real, and urgent demand for energy-efficient database processing. Database
query processing engines must now consider becoming energy-aware, else they risk missing many op-
portunities for significant energy savings. While other recent work has focused on solely optimizing for
energy efficiency, we recognize that such methods are only practical if they also consider performance
requirements specified in SLAs. The focus of this paper is on the design and evaluation of a general
framework for query optimization that considers both performance constraints and energy consumption
as first-class optimization criteria. Our method recognizes and exploits the evolution of modern comput-
ing hardware that allows hardware components to operate in different energy and performance states.
Our optimization framework considers these states and uses an energy consumption model for database
query operations. We have also built a model for an actual commercial DBMS. Using our model the
query optimizer can pick query plans that meet traditional performance goals (e.g., specified by SLAs),
but result in lower energy consumption. Our experimental evaluations show that our system-wide en-
ergy savings can be significant and point toward greater opportunities with upcoming energy-aware
technologies on the horizon
