Energy-aware query processing on a parallel database cluster node

Abstract

In the last few years, we have been seeing a significant increase in research about the energy efficiency of hardware and software components in both centralized and parallel platforms. In data centers, DBMSs are one of the major energy consumers, in which, a large amount of data is queried by complex queries running daily. Having green nodes is a pre-condition to design an energy-aware parallel database cluster. Generally, the most existing DBMSs focus on high-performance during query optimization phase, while usually ignoring the energy consumption of the queries. In this paper, we propose a methodology, supported by a tool called EnerQuery, that makes nodes of parallel database clusters saving energy when optimizing queries. To show its effectiveness, we implement our proposal on the top of PostgreSQL DBMS query optimizer. A mathematical cost model based on a machine learning technique is defined and used to estimate the energy consumption of SQL queries.