Earticle

초록

영어

Range-aggregate queries are popular in many applications having business relational data. In order to efficiently evaluate it, several works on data cubes (such as the aggregate cubetree) are proposed. In the aggregate cubetree, each entry in every node stores the aggregate values of its corresponding subtree. Therefore, range-aggregate queries can be processed without visiting the child nodes whose parent nodes are fully included in the query range. However, the aggregate cubetree does not take range queries using partial dimensions and range queries without aggregation operations into account. That is, 1) a great deal of information that is irrelevant to the queries also has to be read from the disk for partially-dimensional range queries and 2) while it improves the performance of range queries with aggregate operations, it degrades the performance of the range queries without aggregate operations. In this paper, we proposed a novel index structure, called Aggregate-Tree (denoted as Ag-Tree), which gets rid of the above-mentioned weaknesses of the aggregate cubetree without any side effects. The experiments and discussions presented in this paper indicate that the new proposal is significant for range queries in data warehouse environments.

목차

Abstract
 1. Introduction
 2. Related Works
 3. Our Proposal
  3.1 General Structure
  3.2 Algorithms
  3.3 Discussion on query performance
 4. Experiments
  4.1 Range queries without aggregate operations
  4.2 Range queries with aggregate operations
 5. Conclusion
 References

키워드

저자

• Yaokai Feng [ Faculty of Information Science and Electrical Engineering, Kyushu University, Japan ]
• Akifumi Makinouchi [ Department of Information Network Engineering, Kurume Institute of Technology, Japan ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605