Group-by skyline query processing in relational engines

Ming Hay Luk, Man Lung Yiu, Eric Lo

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

9 Citations (Scopus)

Abstract

The skyline operator was first proposed in 2001 for retrieving interesting tuples from a dataset. Since then, 100+ skyline-related papers have been published; however, we discovered that one of the most intuitive and practical type of skyline queries, namely, group-by skyline queries remains unaddressed. Group-by skyline queries find the skyline for each group of tuples. In this paper, we present a comprehensive study on processing group-by skyline queries in the context of relational engines. Specifically, we examine the composition of a query plan for a group-by skyline query and develop the missing cost model for the BBS algorithm. Experimental results show that our techniques are able to devise the best query plans for a variety of group-by skyline queries. Our focus is on algorithms that can be directly implemented in today's commercial database systems without the addition of new access methods (which would require addressing the associated challenges of maintenance with updates, concurrency control, etc.).
Original languageEnglish
Title of host publicationACM 18th International Conference on Information and Knowledge Management, CIKM 2009
Pages1433-1436
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2009
EventACM 18th International Conference on Information and Knowledge Management, CIKM 2009 - Hong Kong, Hong Kong
Duration: 2 Nov 20096 Nov 2009

Conference

ConferenceACM 18th International Conference on Information and Knowledge Management, CIKM 2009
Country/TerritoryHong Kong
CityHong Kong
Period2/11/096/11/09

Keywords

  • Group-by
  • Skyline

ASJC Scopus subject areas

  • General Decision Sciences
  • General Business,Management and Accounting

Fingerprint

Dive into the research topics of 'Group-by skyline query processing in relational engines'. Together they form a unique fingerprint.

Cite this