Analyzing power and energy consumption of large join queries in database systems

Miguel Rodriguez, Daladier Jabba, Eduardo E. Zurek, Augusto Salazar, Pedro Wightmam, Alber Barros, Wilson Nieto

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Performance of large join queries has been widely addressed in the database literature, explicitly the problem of finding a join order that minimizes the execution cost of a given query has been treated. Lately, the elevated electricity consumption of data center facilities have lead to the development of energy-efficient hardware and software. Relational Database Management Systems (RDBMS) have been redesigned to predict power consumption of queries and guide plan selection towards energy reduction goals. In this article, a power consumption comparison between different large join query optimization approaches will be presented. For that purpose, three large join query optimization algorithms will be used, the PostgreSQL genetic algorithms GEQO, a simulated annealing approach SAIO and an automata theory based meta-heuristic DSQO our previous work. The main goal of our research is to analyze the power behavior of different large join query optimizers solving queries derived from the TPC-DS benchmark.

Original languageEnglish
Title of host publicationISIEA 2013 - 2013 IEEE Symposium on Industrial Electronics and Applications
Pages148-153
Number of pages6
DOIs
StatePublished - 2013
Externally publishedYes
Event2013 IEEE Symposium on Industrial Electronics and Applications, ISIEA 2013 - Kuching, Malaysia
Duration: Sep 22 2013Sep 25 2013

Publication series

NameISIEA 2013 - 2013 IEEE Symposium on Industrial Electronics and Applications

Conference

Conference2013 IEEE Symposium on Industrial Electronics and Applications, ISIEA 2013
Country/TerritoryMalaysia
CityKuching
Period09/22/1309/25/13

Keywords

  • energy consumption
  • large join queries
  • query optimization
  • relational database systems

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