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Big Data Analytics on Large Scale Shared Storage System

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dc.contributor.author Aye, Kyar Nyo
dc.contributor.author Thein, Ni Lar
dc.date.accessioned 2019-07-16T06:43:29Z
dc.date.available 2019-07-16T06:43:29Z
dc.date.issued 2012-02-28
dc.identifier.uri https://onlineresource.ucsy.edu.mm/handle/123456789/917
dc.description.abstract In today’s world, almost every enterprise is seeing an explosion of data. They are getting huge amount of digital data generated daily. Such huge amount of data needs to be stored for various reasons. Now the important question that arises at this point of time is how do we store, manage, process and analyze such huge amount of data most of which is Semi structured or Unstructured in a scalable, fault tolerant and efficient manner. The challenges of big data are most of them is semi structured or unstructured data, need to carry out complex computations over big data and the time required to process big data is as low as possible. In this paper, we propose big data platform based on Hadoop MapReduce framework and Gluster file system over large scale shared storage system to address these challenges. Our big data platform can support large scale data analysis efficiently and effectively. en_US
dc.language.iso en en_US
dc.publisher Tenth International Conference on Computer Applications (ICCA 2012) en_US
dc.subject big data en_US
dc.subject big data analytics en_US
dc.subject big data platform en_US
dc.subject MapReduce framework en_US
dc.subject Gluster File System en_US
dc.subject Scale-out NAS en_US
dc.title Big Data Analytics on Large Scale Shared Storage System en_US
dc.type Article en_US


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