An Evolutionary Algorithm for Skyline Query Optimization

  • Marlene Goncalves
  • Ivette Martínez
  • Gabi Escuela
  • Fabiola Di Bartolo
  • Francelice Sardá


Skyline queries have emerged as an answer to the need of solving queries that involve user preferences. Although the evaluation of the Skyline operator is costly, its efficient incorporation into an execution plan may decrease the execution time of SQL queries. This process is known as Skyline Query Optimization. Several solutions for Skyline Query Optimization have already been presented. These solutions are most often based on Dynamic Programming (DP), which means that all alternative plans are exhaustively enumerated. This approach loses effectiveness as the search space size increases. On the other hand, stochastic search algorithms have shown to be successful in solving optimization problems arising from standard queries. Our previous studies have shown that Evolutionary Algorithms (EAs), implemented in the form of eaSky, may outperform DP approaches for Skyline Query Optimization. Such a comparison between EAs and DP is necessary, because DP is used in most database management systems despite its aforementioned scaling problem. In this chapter, we present experimental results of eaSky and show that eaSky can achieve better performance than DP for large queries. An extended version of eaSky has been developed, and experimental results show further improvements in its performance as compared to the original eaSky.


Execution Time Dynamic Program Mutation Operator Database Management System Execution Plan 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Marlene Goncalves
    • 1
  • Ivette Martínez
    • 1
  • Gabi Escuela
    • 1
  • Fabiola Di Bartolo
    • 2
  • Francelice Sardá
    • 2
  1. 1.Departamento de Computación y T.I..Universidad Simón BolívarCaracasVenezuela
  2. 2.Grupo de Inteligencia ArtificialUniversidad Simón BolívarCaracasVenezuela

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