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Reseach Article

Examining the Performance of Vertical Fragmentation using FP-MAX Algorithm

by Nidhi Thakur, Balwant Ram
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 116 - Number 23
Year of Publication: 2015
Authors: Nidhi Thakur, Balwant Ram
10.5120/20514-2691

Nidhi Thakur, Balwant Ram . Examining the Performance of Vertical Fragmentation using FP-MAX Algorithm. International Journal of Computer Applications. 116, 23 ( April 2015), 43-48. DOI=10.5120/20514-2691

@article{ 10.5120/20514-2691,
author = { Nidhi Thakur, Balwant Ram },
title = { Examining the Performance of Vertical Fragmentation using FP-MAX Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 116 },
number = { 23 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 43-48 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume116/number23/20514-2691/ },
doi = { 10.5120/20514-2691 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:58:00.660450+05:30
%A Nidhi Thakur
%A Balwant Ram
%T Examining the Performance of Vertical Fragmentation using FP-MAX Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 116
%N 23
%P 43-48
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Today’s business Environment has an increasing need for consistent, scalable, reliable and accessible information which grows steadily.The purpose of this work is to analyse the performance of Vertical Fragmentation on large as well as small database such as educational database, data warehouses, medical databases. Vertical Fragmentation has an important impact in improving the performance of modern applications like document management, multimedia and hypermedia applications. With vertical partitioning, the disk access can be reduced by minimizing the access to irrelevant instance variables when executing the queries. In Present work FP-MAX data mining algorithm is used to extract frequent item set attributes of a large database table. The frequent accessed instance variables are grouped called Vertical fragments. The cost model is applied on Vertical fragments. The results are analyzed for small as well as large datasets in form of Max memory usage, Total time, cost and Frequent itemset count.

References
  1. Adrian Runceanu(2004), “Towards Vertical Fragmentation in distributed databases”.
  2. Amer Ali A. and Abdalla Hassan I. (2012) “An Integrated Design Scheme for Performance Optimization in Distributed Environments “, International Conference on Education and e- Learning Innnovations.
  3. Ankur Bhardwaj et.al,(2012) “Role of Fragmentation in distributed database system” ,International Journal of networking & Parallel Computing Volume 1, Issue 1, September 2012.
  4. Bhuyar P.R. and Gawanda A.D.,(2012) “Distributed Database: Fragmentation and Allocation”, Journal of data Mining and Knowledge Discovery,Volume3.
  5. Bouakkaz M. ,Ouinten Y., Ziani B. (2012) “Vertical Fragmentation of Datawarehouses using FP-MAX Algorithm” ,International Conference on Innovations in Information Technology.
  6. Chaalel,Belbachir,(2013) “An Optimized Vertical Fragmentation Approach”, International Journal of innovative technology and exploring Engineering(IJITEE),Volume-3,Sept 2013.
  7. C.I.Ezeife and Ken Barker(1996), “Vertical fragmentation for advanced object models in a distributed object based system.”
  8. Ezcife.C.I.Zheng Jian “Measuring the performance of database Object Horizontal Fragmentation Schemes ”
  9. Golfarelli Matteo ,Maio Davio and Rizzi Stefano “ Applying Vertical Fragmentation Techniques in Logical Design of Multidimensional Databases”.
  10. Gosta Grahne and Jianfei Zhu(2002), “High performance Mining of maximal frequent itemsets”.
  11. Gupta Surabhi ,Panda Shruti (2012) “Vertical Fragmentation and Re-Fragmentation in Distributed Object Relational Database Systems-(Update Queries Included )” , International Journal of Engineering Research and Development.
  12. Hichame Chaalel and Hafida Belbachir(2013) “ An Optimized vertical fragmentation Approach” ,International Journal of Innovative technology and exploring engineering,Volume 3.
  13. Hui Ma and Markus Kirchberg(2008), “Cost based Fragmentation for distributed complex value databases”.
  14. Jiawei Han et.al,(2000), “Mining frequent patterns without candidate generation.”
  15. Ma Hui ,Scherve Klaus-Dieter and Kirchberg Markus (2006) “ A Heuristic approach to Vertical fragmentation Incorporating Query Information”.
Index Terms

Computer Science
Information Sciences

Keywords

Database Ivertical fragmentation frequent item set data mining.