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EnerQuery: Energy-aware query processing
Roukh, Amine; Bellatreche, Ladjel; Ordonez, Carlos
2016In CIKM 2016 - Proceedings of the 2016 ACM Conference on Information and Knowledge Management
Peer reviewed
 

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Keywords :
Database design; Energy efficiency; Query processing; Cost modeling; Energy aware; Energy awareness; In-buildings; Optimizers; Query execution; Trade off; Business, Management and Accounting (all); Decision Sciences (all)
Abstract :
[en] Energy consumption is increasingly more important in large-scale query processing. This problem requires revisiting traditional query processing in actual DBMSs to identify the potential of energy saving, and to study the trade-offs between energy consumption and performance. In this paper, we propose EnerQuery, a tool built on top of a traditional DBMS to capitalize the efforts invested in building energy-aware query optimizers, which have the lion's share in energy consumption. Energy consumption is estimated on all query plan steps and integrated into a mathematical linear cost model used to select the best query plans. To increase end users' energy awareness, EnerQuery features a diagnostic GUI to visualize energy consumption per step and its savings when tuning key parameters during query execution.
Disciplines :
Computer science
Author, co-author :
Roukh, Amine  ;  Université de Mons - UMONS > Faculté Polytechnique > Service Informatique, Logiciel et Intelligence artificielle ; University of Mostaganem, Mostaganem, Algeria
Bellatreche, Ladjel;  LIAS, ISAE-ENSMA, Poitiers, France
Ordonez, Carlos;  University of Houston, Houston, United States
Language :
English
Title :
EnerQuery: Energy-aware query processing
Publication date :
24 October 2016
Event name :
Proceedings of the 25th ACM International on Conference on Information and Knowledge Management
Event place :
Indianapolis, Usa
Event date :
24-10-2016 => 28-10-2016
Main work title :
CIKM 2016 - Proceedings of the 2016 ACM Conference on Information and Knowledge Management
Publisher :
Association for Computing Machinery
ISBN/EAN :
978-1-4503-4073-1
Peer reviewed :
Peer reviewed
Funders :
ACM SIGIR
ACM SIGWEB
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