Incremental and Iterative Mapreduce for Mining Evolving the Big Data in Banking System

Authors

  • Gayathri S A  Information Technology, Velammal Institute of Technology, Chennai, Tamilnadu, India
  • Preethi. M  Information Technology, Velammal Institute of Technology, Chennai, Tamilnadu, India
  • Shanmugapriya S  Information Technology, Velammal Institute of Technology, Chennai, Tamilnadu, India
  • Sivagami S  Information Technology, Velammal Institute of Technology, Chennai, Tamilnadu, India

Keywords:

Big data, Mining, Map reduce, Hadoop, CBP, MRBGraph

Abstract

Big data is a broad term for datasets so large and complex that the traditional data processing applications are inadequate, so i2mapreduce based framework for incremental and iterative computations are done in big data. State level processing computation easily retrieve the data and also time consuming. Incremental and iterative mapreduce- mapreduce is the most widely used big data processing tool incremental processing is a promising approach to refresh the mining results. Use the same computation logic (update function) to process the data many times. The previous iteration’s output is the next iteration’s input, Stop when the iterated results converges to a fixed point. This concept using the online banking such as create account, withdraw, deposit and to get the details in a effective way. Finally, upload all the data to the cloud using AES algorithm. I2mapreduce is one step algorithm and four iterative algorithm with diverse computation characteristics. It is very secure to all the data are stored in binary format 0 and 1.

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Published

2017-12-31

Issue

Section

Research Articles

How to Cite

[1]
Gayathri S A, Preethi. M, Shanmugapriya S, Sivagami S, " Incremental and Iterative Mapreduce for Mining Evolving the Big Data in Banking System, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 2, pp.496-501, March-April-2016.