Exploiting temporal correlation in temporal data warehouses

Authors:
Ying Feng;Hua-Gang Li;Divyakant Agrawal;Amr El Abbadi
Affiliations:
Department of Computer Science, University of California, Santa Barbara;Department of Computer Science, University of California, Santa Barbara;Department of Computer Science, University of California, Santa Barbara;Department of Computer Science, University of California, Santa Barbara
Venue:
DASFAA'05 Proceedings of the 10th international conference on Database Systems for Advanced Applications
Year:
2005

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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 monotonic 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.