Exploiting temporal correlation in temporal data warehouses

Ying Feng, Hua Gang Li, Divyakant Agrawal, Amr El Abbadi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Data is typically incorporated in a data warehouse in increasing order of time. Furthermore, the MOLAP data cube tends to be sparse because of the large cardinality of the time dimension. We propose an approach to improve the efficiency of range aggregate queries on MOLAP data cubes in a temporal data warehouse by factoring out the time-related dimensions. These time-related dimensions are handled separately to take advantage of the monotonie trend over time. The proposed technique captures local data trends with respect to time by partitioning data points into blocks, and then uses a perfect binary block tree as an index structure to achieve logarithmic time complexity for both incremental updates and data retrievals. Experimental results establish the scalability and efficiency of the proposed approach on various datasets.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science
EditorsL. Zhou, B.C. Ooi, X. Meng
Pages662-674
Number of pages13
Volume3453
Publication statusPublished - 2005
Externally publishedYes
Event10th International Conference on Database Systems for Advanced Applications, DASFAA 2005 - Beijing, China
Duration: 17 Apr 200520 Apr 2005

Other

Other10th International Conference on Database Systems for Advanced Applications, DASFAA 2005
CountryChina
CityBeijing
Period17/4/0520/4/05

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ASJC Scopus subject areas

  • Computer Science (miscellaneous)

Cite this

Feng, Y., Li, H. G., Agrawal, D., & El Abbadi, A. (2005). Exploiting temporal correlation in temporal data warehouses. In L. Zhou, B. C. Ooi, & X. Meng (Eds.), Lecture Notes in Computer Science (Vol. 3453, pp. 662-674)