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Adaptive Energy-Control for In-Memory Database Systems

The ever-increasing demand for scalable database systems is limited by their energy consumption, which is one of the major challenges in research today. While existing approaches mainly focused on transaction-oriented disk-based database systems, we are investigating and optimizing the energy consumption and performance of data-oriented scale-up in-memory database systems that make heavy use of the main power consumers, which are processors and main memory. We give an in-depth energy analysis of a current mainstream server system and show that modern processors provide a rich set of energy-control features, but lack the capability of controlling them appropriately, because of missing application-specific knowledge. Thus, we propose the Energy-Control Loop (ECL) as an DBMS-integrated approach for adaptive energy-control on scale-up in-memory database systems that obeys a query latency limit as a soft constraint and actively optimizes energy efficiency and performance of the DBMS. The ECL relies on adaptive workload-dependent energy profiles that are continuously maintained at runtime. In our evaluation, we observed energy savings ranging from 20% to 40% for a real-world load profile.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:79167
Date30 May 2022
CreatorsKissinger, Thomas, Habich, Dirk, Lehner, Wolfgang
PublisherACM
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/acceptedVersion, doc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess
Relation978-1-4503-4703-7, 10.1145/3183713.3183756

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