Implementation of MRPrePost Parallel Algorithm based on Hadoop Platform for Large-Data Mining

Authors

  • Aishwarya Rani M R Bapuji Institute of Engineering and Technology, Davangere
  • Shivanand R D

DOI:

https://doi.org/10.37591/rtpc.v4i2.998

Abstract

Abstract

The volume, velocity and variety of the data have increased several folds in the past few years. The conventional algorithms and techniques used to mine such huge data are found to be less efficient because these algorithms consider only the large threshold value due to which the number of candidates can be reduced, but this will lead mining association rules production to be inaccurate due to low utilization of data. Hence the idea of parallelization is a viable option. This paper focuses on a Hadoop platform based parallel algorithm called MRPrePost; a hybrid of big data mining methods, in order to mine frequent item sets to derive association rules. MRPrePost is based on the idea of parallel design which improves PrePost by way of adding a prefix pattern. It uniformly partitions the search space way instead of the original database, making this algorithm adapt efficiently to mining large data's association rules. The paper intends to conduct experiments implement MRPrePost algorithm on a large data set on Hadoop platform. 

Keywords: Parallelization, hadoop, MRPrePost algorithm, KKD (Knowledge Discovery in Databases), HDFS (Hadoop Distributed File System)

Cite this Article

Aishwarya Rani M R, Shivanand R D. Implementation of MRPrePost Parallel Algorithm based on Hadoop Platform for Large-Data Mining. Recent Trends in Parallel Computing. 2017; 4(2): 10–20p.


Downloads

Published

2017-08-23

Issue

Vol. 4 No. 2 (2017)

Section

Research Articles

License

Declaration and Copyright Transfer Form

(to be completed by authors)

I/ We, the undersigned author(s) of the submitted manuscript, hereby declare, that the above manuscript which is submitted for publication in the STM Journals(s), is not published already in part or whole (except in the form of abstract) in any journal or magazine for private or public circulation, and, is not under consideration of publication elsewhere.

  • I/We will not withdraw the manuscript after 1 week of submission as I have read the Author Guidelines and will adhere to the guidelines.
  • I/We Author(s ) have niether given nor will give this manuscript elsewhere for publishing after submitting in STM Journal(s).
  • I/ We have read the original version of the manuscript and am/ are responsible for the thought contents embodied in it. The work dealt in the manuscript is my/ our own, and my/ our individual contribution to this work is significant enough to qualify for authorship.
  •  I/We also agree to the authorship of the article in the following order:

Author’s name                                    

 

1. ________________

2. ________________

3. ________________

4. ________________

 

We  Author(s) tick this box and would request you to consider it as our signature as we agree to the terms of this Copyright Notice, which will apply to this submission if and when it is published by this journal.