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Energy Efficiency in Main-Memory Databases

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Abstract

As the operating costs of today’s data centres continue to increase and processor manufacturers are forced to meet thermal design power constraints when designing new hardware, the energy efficiency of a main-memory database management system becomes more and more important. Plus, lots of database workloads are more memory-intensive than compute-intensive, which results in computing power being unused and wasted. This can become a problem because wasting computing also means wasting electrical power.

In this paper, we experimentally study the impact of reducing the clock frequency of the processor and the impact of using fewer processor cores on the energy efficiency of common database algorithms such as scans, simple aggregations, simple hash joins, and state-of-the-art join algorithms. We stress the fundamental trade-off between peak performance and energy efficiency, as opposed to the established race-to-idle strategy. Ultimately, we show that reducing unused computing power significantly improves the energy efficiency of memory-bound database algorithms.

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  1. ELV Energy Master Basic 2 Energiekosten-Messgerät

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Acknowledgment

This work was supported by the DFG, Collaborative Research Center SFB 876, A2.

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Authors and Affiliations

  1. Databases and Information Systems Group, TU Dortmund University, Otto-Hahn-Straße 14, 44227, Dortmund, Germany

    Stefan Noll, Henning Funke & Jens Teubner

Authors
  1. Stefan Noll
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  2. Henning Funke
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  3. Jens Teubner
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Correspondence to Stefan Noll.

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Noll, S., Funke, H. & Teubner, J. Energy Efficiency in Main-Memory Databases. Datenbank Spektrum 17, 223–232 (2017). https://doi.org/10.1007/s13222-017-0262-9

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  • DOI: https://doi.org/10.1007/s13222-017-0262-9

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