Double table switch: an efficient partitioning algorithm for bottom-up computation of data cubes

Authors:
Jinguo You;Lianying Jia;Jianhua Hu;Qingsong Huang;Jianqing Xi
Affiliations:
School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, Yunnan;School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guangdong;School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, Yunnan;School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, Yunnan;School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guangdong
Venue:
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
Year:
2010

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Abstract

Bottom-up computation of data cubes is an efficient approach which is adopted and developed by many other cubing algorithms such as H-Cubing, Quotient Cube and Closed Cube, etc. The main cost of bottom-up computation is recursively sorting and partitioning the base table in a worse way where large amount of auxiliary spaces are frequently allocated and released. This paper proposed a new partitioning algorithm, called Double Table Switch (DTS). It sets up two table spaces in the memory at the beginning, where the partitioned results in one table are copied into another table alternatively during the bottom-up computation. Thus DTS avoids the costly space management and achieves the constant memory usage. Further, we improve the DTS algorithm by adjusting the dimension order, etc. The experimental results demonstrate the efficiency of DTS.