2014/07/01 by Daniel Schall, Schall, Daniel, Theo Härder +1
Computer Science · #Databases (cs.DB) #Distributed #FOS: Computer and information sciences #Parallel #and Cluster Computing (cs.DC) #cs.DB #cs.DC
paper · pdf · doi:10.48550/arxiv.1407.0386
arXiv admin note: substantial text overlap with arXiv:1407.0120
arxiv created 2014/07/07 · arxiv updated 2014/07/08
Traditional DBMS servers are usually over-provisioned for most of their daily workloads and, because they do not show good energy proportionality, waste a lot of energy while underutilized. A cluster of small (wimpy) servers, where the number of nodes can dynamically adjust to the current workload, might offer better energy characteristics for these workloads. Yet, clusters suffer from "friction losses" and may not be able to quickly adapt to the workload, whereas a single, brawny server delivers performance instantaneously. In this paper, we compare a small cluster of lightweight nodes to a single server in terms of performance and energy efficiency. We run several benchmarks, consisting of OLTP and OLAP queries at variable utilization to test the system's ability to adjust to the workloads. To quantify possible energy saving and its conceivable drawback on query runtime, we evaluate our implementation on a cluster as well as on a single, brawny server and compare the results w.r.t. performance and energy consumption. Our findings confirm that - based on the workload - energy can be saved without sacrificing too much performance.