Log Mining Based on Hadoop’s Map and Reduce Technique

Journal Title: International Journal on Computer Science and Engineering - Year 2013, Vol 5, Issue 4

Abstract

In the world of cloud and grid computing Virtual Database Technology (VDB) is one of the effective solutions for integration of data from heterogeneous sources. Hadoop is a large-scale distributed batch processing infrastructure and also designed to efficiently distribute large amounts of work across a set of machines. Hadoop is an implementation of Map Reduce. This paper proposes application for inauguration of new branch of pizza in particular area according to hits from customers. In this paper we will take the log files for the particular website which will be stored on web mining server. These data will be passed on to the cloud server for region wise distribution on the virtual servers. Mapping and reduction will be done on these region wise data. The final output is then sent back to the server and client. This paper utilizes the parallel and distributed processing capability of Hadoop Map Reduce for handling heterogeneous query execution on large datasets. So Virtual Database Engine built on top of this will result in effective high performance distributed data integration

Authors and Affiliations

Anuja Pandit , Amruta Deshpande , Prajakta Karmarkar

Keywords

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  • EP ID EP146249
  • DOI -
  • Views 114
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How To Cite

Anuja Pandit, Amruta Deshpande, Prajakta Karmarkar (2013). Log Mining Based on Hadoop’s Map and Reduce Technique. International Journal on Computer Science and Engineering, 5(4), 270-274. https://europub.co.uk/articles/-A-146249