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License: CC BY NC
Data sources: UnpayWall
https://doi.org/10.2991/cse.20...
Article . 2013 . Peer-reviewed
Data sources: Crossref
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Generating Power-Efficient Query Execution Plan

Authors: Hong Gao; Haijie Wang; Jinbao Wang; Xiaowei Liu;

Generating Power-Efficient Query Execution Plan

Abstract

As more and more power is consumed in servers, growing attention has been paid to power management. However, little work has been dated on the power-efficiency of query execution plans generated by the DBMS. Traditional optimal query execution plan does not take power-efficiency into account. This paper tries to generate a power-efficient query execution plan by redesigning the query optimizer of the database. We build a power model to estimate the power consumption of a query execution plan and propose an algorithm to generate the power-efficient query execution plan. Using two experiments based on the TPC-H benchmark, we evaluate the accuracy of our power model and compare the power-efficient query execution plan with the traditional optimal query execution plan. Keywords-query execution plan; power-efficiency; power

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Average
gold