Journal of KIISE:Databases (한국정보과학회논문지:데이타베이스)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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Efficient Execution of Range $Top-\kappa$ Queries using a Hierarchical Max R-Tree

계층 최대 R-트리를 이용한 범위 상위-$\kappa$ 질의의 효율적인 수행

  • 홍석진 (서울대학교 전기컴퓨터공학부) ;
  • 이상준 (서울대학교 전기컴퓨터공학) ;
  • 이석호 (서울대학교 전기컴퓨터공학부)
  • Published : 2004.04.01
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Abstract

A range $Top-\kappa$ query returns top k records in order of a measure attribute within a specified region on multi-dimensional data, and it is a powerful tool for analysis in spatial databases and data warehouse environments. In this paper, we propose an algorithm for answering the query via selective traverse of a Hierarchical Max R-Tree(HMR-tree). It is possible to execute the query by accessing only a small part of the leaf nodes in the query region, and the query performance is nearly constant regardless of the size of the query region. The algorithm manages the priority queue efficiently to reduce cost of handling the queue and the proposed HMR-tree can guarantee the same fan-out as the original R-tree.

범위 상위-$\kappa$ 질의는 질의 범위 내의 다차원 데이타 중 값 애트리뷰트를 기준으로 상위 k개의 레코드를 반환하는 질의로 공간 데이타베이스와 데이타 웨어하우스에서 분석을 위해 많이 사용되는 유용한 질의 형태이다. 이 논문에서는 계층 최대 R-트리의 선택적인 탐색을 통해 범위 상위-k 질의를 효과적으로 수행하는 기법을 제시한다. 이 기법은 단말 노드의 일부만을 접근하여 질의를 수행할 수 있으며, 질의 범위의 크기에 관계없이 거의 일정한 성능을 보인다. 또한 이 기법은 우선순위 큐를 효율적으로 관리함으로써 큐의 유지비용을 최소화하며, 기존 R-트리와 같은 팬아웃을 보장할 수 있다.

Keywords

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