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Journal of Zhejiang University SCIENCE A 2005 Vol.6 No.6 P.519~527

http://doi.org/10.1631/jzus.2005.A0519


Construction and compression of Dwarf


Author(s):  XIANG Long-gang, FENG Yu-cai, GUI Hao

Affiliation(s):  School of Computer Science, Huazhong University of Science and Technology, Wuhan 430074, China

Corresponding email(s):   lg_xiang@hotmail.com, fyc@dm2.com.cn, tigerguihao@sina.com

Key Words:  Data cube, Dwarf, Suffix coalescing, Prefix path, MSV partition, Condensed Dwarf


XIANG Long-gang, FENG Yu-cai, GUI Hao. Construction and compression of Dwarf[J]. Journal of Zhejiang University Science A, 2005, 6(6): 519~527.

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author="XIANG Long-gang, FENG Yu-cai, GUI Hao",
journal="Journal of Zhejiang University Science A",
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T1 - Construction and compression of Dwarf
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DOI - 10.1631/jzus.2005.A0519


Abstract: 
There exists an inherent difficulty in the original algorithm for the construction of dwarf, which prevents it from constructing true dwarfs. We explained when and why it introduces suffix redundancies into the dwarf structure. To solve this problem, we proposed a completely new algorithm called PID. It bottom-up computes partitions of a fact table, and inserts them into the dwarf structure. If a partition is an MSV partition, coalesce its sub-dwarf; otherwise create necessary nodes and cells. Our performance study showed that PID is efficient. For further condensing of dwarf, we proposed Condensed dwarf, a more compressed structure, combining the strength of dwarf and Condensed Cube. By eliminating unnecessary stores of “ALL” cells from the dwarf structure, Condensed dwarf could effectively reduce the size of dwarf, especially for dwarfs of the real world, which was illustrated by our experiments. Its query processing is still simple and, only two minor modifications to PID are required for the construction of Condensed dwarf.

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Reference

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[7] Sismanis, Y., Deligiannakis, A., Roussopoulos, N., Kotidis, Y., 2002. Dwarf: Shrinking the PetaCube. Proceedings of the 2002 ACM SIGMOD International Conference on Management of Data, ACM Press, p.464-475.

[8] Wang, W., Feng, J.L., Lu, H.J., Yu, J.X., 2002. Condensed Cube: An Effective Approach to Reducing Data Cube Size. Proceedings of the 18th International Conference on Data Engineering, IEEE Computer Society Press, p.155-165.

[9] Xin, D., Han, J.W., Li, X.L., Wah, B.W., 2003. Star-cubing: Computing Iceberg Cubes by Top-down and Bottom-up Integration. Proceedings of 29th International Conference on Very Large Data Bases, Morgan Kaufmann Press, p.476-487.

[10] Zhao, Y., Deshpande, P., Naughton, J.F., 1997. An Array-based Algorithm for Simultaneous Multidimensional Aggregates. Proceedings of the 1997 ACM SIGMOD International Conference on Management of Data, ACM Press, p.159-170.

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