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Skyline Computation for Big Data

  • R. D. KulkarniEmail author
  • B. F. Momin
Conference paper
  • 852 Downloads
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 16)

Abstract

From a multidimensional dataset, a skyline query extracts the data which satisfy the multiple preferences given by the user. The real challenge in skyline computation is to retrieve such data, in the optimum time. When the datasets are huge, the challenge becomes critical. In this paper, we address exactly this issue focusing on the big data. For this, we aim at utilizing the correlations observed in the user queries. These correlations and the results of historical skyline queries, executed on the same dataset, are very much helpful in optimizing the response time of further skyline computation. For the same purpose, we have earlier proposed a novel structure namely Query Profiler (QP). In this paper, we present a technique namely SkyQP to assert the effectiveness of this concept against the big data. We have also presented the time and space analysis of the proposed technique. The experimental results obtained assert the efficacy of the SkyQP technique.

Keywords

Skyline queries Correlated queries Query profiler 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringWalchand College of EngineeringSangliIndia

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