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.
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You, J., Jia, L., Hu, J., Huang, Q., Xi, J. (2010). Double Table Switch: An Efficient Partitioning Algorithm for Bottom-Up Computation of Data Cubes. In: Cao, L., Zhong, J., Feng, Y. (eds) Advanced Data Mining and Applications. ADMA 2010. Lecture Notes in Computer Science(), vol 6441. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17313-4_19
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DOI: https://doi.org/10.1007/978-3-642-17313-4_19
Publisher Name: Springer, Berlin, Heidelberg
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