Peak Power Plays in Database Engines

Database engines often consume significant power during query processing activities, motivating researchers to investigate the re-design of their internals to minimize these overheads. While the prior literature has dealt exclusively with average power consider-ations, our focus here is on peak power consumption. We begin by profiling the peak power behavior of a representative suite of pop-ular commercial database engines in benchmark query processing environments, and demonstrate that their consumption can often be substantial. Then, we develop a pipeline-based model of query ex-ecution plans that lends itself to accurately estimating peak power consumption, suggesting its gainful employment in server design and capacity planning. More potently, given a space of compet-ing plan choices, it could help identify plans with attractive trade-offs between peak-power and time-efficiency considerations, and we present sample instances of such tradeoffs. Finally, we dis-cuss extensions of our modeling approach to inductive pipelines and multi-query workloads