ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2019, Vol. 56 ›› Issue (9): 1821-1831.doi: 10.7544/issn1000-1239.2019.20180670

• 软件技术 • 上一篇    下一篇


邢宝平1, 吕梦圆1, 金培权1,2, 黄国锐3, 岳丽华1,2   

  1. 1(中国科学技术大学计算机科学与技术学院 合肥 230027); 2(中国科学院电磁空间信息重点实验室 合肥 230027); 3(中国人民解放军31002部队 北京 100081) (
  • 出版日期: 2019-09-10
  • 基金资助: 

Energy-Efficiency Query Optimization for Green Datacenters

Xing Baoping1, Lü Mengyuan1, Jin Peiquan1,2, Huang Guorui3, Yue Lihua1,2   

  1. 1(School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027); 2(Key Laboratory of Electromagnetic Space Information, Chinese Academy of Sciences, Hefei 230027); 3(Unit 31002, People’s Liberation Army of China, Beijing 100081)
  • Online: 2019-09-10
  • Supported by: 
    This work was supported by the General Program of the National Natural Science Foundation of China (61672479).

摘要: 降低能耗开销、建设绿色数据中心,已经成为目前大规模数据中心的重要需求.在绿色数据中心,如何使数据库系统在满足性能需求的前提下尽量地节约能耗,即如何提高数据库系统的能耗有效性,是目前研究的重点.数据库系统中的能耗有效性旨在使用更少的电能来提供相同的服务.能耗有效性越高,说明数据库系统可以用更少的能耗就能够响应同样数量的操作,换句话说,可以用更少的能耗达到同样的性能.据此提出了一种面向绿色数据中心的能耗有效查询优化方法.该方法首先利用回归分析建立操作符层的功耗预测模型,从而可以准确地预测给定查询在执行过程中的平均功耗.接着,在PostgreSQL查询优化器中扩充了结合预测能耗成本和时间成本的新的查询执行代价计算模型,并引入性能退化度因子调节性能和能耗的权重.最后构建了数据库系统能耗测试平台,在PostgreSQL上基于TPC-H和TPC-C基准测试进行了实验.结果表明:所提出的功耗预测模型比已有方法准确度更高.同时,提出的性能退化度因子为数据库系统提供了性能和能耗之间的灵活折中方案,并且通过设置适当的性能退化度因子,可以实现比原始PostgreSQL更高的能耗有效性.

关键词: 绿色数据中心, 能耗有效性, 查询优化, 代价模型, 功耗模型

Abstract: Reducing energy consumption and building green datacenters has been one of the major needs of modern large-scale datacenters. In green datacenters, a key research issue is how to lower the energy consumption of database systems while keeping stable performance. This issue is called energy efficiency, and has become a new research frontier recently. Energy efficiency of database systems is defined as using little energy to accomplish as many operations as possible. High energy efficiency means that database systems can use less energy while processing a fixed number of operations. In other words, it uses less energy but achieves the same performance. In this paper, we propose a method for energy-efficient query optimization. First, an operator-level power model is established based on the regression analysis method, which can accurately predict average power consumption during query execution for a given query. Next, a new cost model is proposed for query optimizer, which considers both energy and performance aspects. The new cost model uses a new factor to obtain a better tradeoff between performance and energy costs. A testbed is built for measuring energy consumption of database systems, and the TPC-H and TPC-C benchmarks are used to evaluate the performance of our proposal. The results show that the proposed power model achieves higher precision than existing methods. In addition, the proposed performance-degrade factor can provide flexible trade-offs between performance and energy. Moreover, by setting up an appropriate performance-degrade factor, better energy efficiency can be achieved than the original PostgreSQL.

Key words: green datacenter, energy efficiency, query optimization, cost model, power model