Incremental aggregation on MOLAP cube based on n-dimensional extendible karnaugh arrays

Rabbi, Jakaria, Awal, Md. Abdul and Hasan, K M Azharul Incremental aggregation on MOLAP cube based on n-dimensional extendible karnaugh arrays. International Journal of Computer Science and Network - IJCSN, www.IJCSN.org, 2017, vol. 6, n. 2, pp. 58-64. [Journal article (Paginated)]

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English abstract

Data is increasing so rapidly that new data warehousing approaches are required to process and analyze data. Aggregation of data incrementally is needed to fast access of data and compute aggregation functions. Multidimensional arrays are generally used for this purpose. But some disadvantages such as address space requirement is large and processing time is comparatively slow in case of aggregation. For this purpose we use Extendible Karnaugh Array (EKA). EKA is an efficient scheme which has better performance than other data structures that we have tested in our research. In this research work we use EKA as basic structure for implementing incremental aggregation of data and evaluate its performance over other approaches. We use Multidimensional Online Analytical Processing (MOLAP) which stores data in optimized multi-dimensional array storage, rather than in a relational database. We create 4 and 6 dimensional MOLAP data cube using Traditional Multidimensional Array (TMA) and EKA scheme and compare incremental aggregation with Relational Online Analytical Processing (ROLAP). The effective outcome of EKA structure for incremental aggregation on 4 and 6 dimensional MOLAP structure is shown by some experimental results and efficiency is proved for n higher dimensions.

Item type: Journal article (Paginated)
Keywords: Multidimensional Array, Extendible Array, Karnaugh Map, Dynamic Extension, Data Cube, ROLAP, OLAP, MOLAP, EKA, TMA
Subjects: I. Information treatment for information services > IF. Information transfer: protocols, formats, techniques.
Depositing user: IJCSN Journal
Date deposited: 29 May 2017 07:38
Last modified: 29 May 2017 07:38
URI: http://hdl.handle.net/10760/31136

References

[1] Jin, Chun, and Jaime Carbonell, "Incremental aggregation on

multiple continuous queries," Foundations of Intelligent

Systems, Springer Berlin Heidelberg, pp. 167-177, 2006.

[2] Nesamoney, Diaz, et al, "Method for incremental aggregation of

dynamically increasing database data sets," U.S. Patent No.

5,794,246. 11 Aug. 1998.

[3] K.E. Seamons and M. Winslett (1994),“Physical schemas for

large multidimensional arrays in scientific computing

applications,” Proceedings of SSDBM, pp. 218-227.

[4] S. Sarawagi and M. Stonebraker (1994), “ Efficient organization

of large multidimensional arrays,” Proceedings of ICDE, pp.

328-336.

[5] Y.L. Chun, C.C. Yeh, and S.L. Jen (2002), “Efficient

Representation Scheme for Multidimensional Array Operations,

”IEEE Transactions on Computers, 51(3), pp. 327-345.

[6] Y.L. Chun, C.C. Yeh, and S.L. Jen (2003), “Efficient Data

Parallel Algorithms for Multidimensional Array Operations

Based on the EKMR Scheme for Distributed Memory

Multicomputer,” IEEE Transactions on Parallel and Distributed

Systems, 14(7), pp. 625-639.

[7] KMA Hasan, K Islam, M Islam, T Tsuji, “An extendible data

structure for handling large multidimensional data sets”,

Proceedings of 12th International Conference on Computer and

Information Technology (ICCIT), Dhaka, Bangladesh, pp. 669-

674, 2009.

[8] Ahsan, Sk Md Masudul, and KM Azharul Hasan, "An

implementation scheme for multidimensional extendable array

operations and its evaluation,” Informatics Engineering and

Information Science. Springer Berlin Heidelberg, 2011. 136-

150.

[9] M Ahsan, S Md, KM Hasan, “An Efficient Encoding Scheme to

Handle the Address Space Overflow for Large

Multidimensional Arrays,” Journal of Computers 8 (5), pp.

1136-1144, 2013.

[10] Y. Zhao, P. M. Deshpande and J. F. Naughton, “An array-based

algorithm for simultaneous multidimensional aggregates”, In

Proceedings of the ACM SIGMOD Conference on Management

of Data, pp.159-170, 1997.

[11] S. Sarawagi and M. Stonebraker, “Efficient organization of large

multidimensional arrays”, Proc. of ICDE, pp. 328-336, 1994.

[12] Hasan, KM Azharul, Tatsuo Tsuji, and Ken Higuchi. "An

efficient implementation for MOLAP basic data structure and its

evaluation," Advances in Databases: Concepts, Systems and

Applications. Springer Berlin Heidelberg, 2007. 288-299.


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