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A Comparison of Big Data Analytics Approaches Based on Hadoop MapReduce

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dc.contributor.author Aye, Kyar Nyo
dc.contributor.author Thein, Ni Lar
dc.date.accessioned 2019-07-11T07:30:43Z
dc.date.available 2019-07-11T07:30:43Z
dc.date.issued 2013-02-26
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/755
dc.description.abstract Data continue a massive expansion in scale, diversity, and complexity. Data underpin activities in all sectors of society. Achieving the full transformative potential from the use of data in this increasingly digital world requires not only new data analysis algorithms but also a new generation of systems and distributed computing environments to handle the dramatic growth in the volume of data, the lack of structure for much of it and the increasing computational needs of massive scale analytics. In this paper, we propose big data platform that is built upon open source and built on Hadoop MapReduce , Gluster File System, Apache Pig, Apache Hive and Jaql and compare our platform with other two big data platforms I BM big da ta platform and Splunk . Our big data platform can support large scale data analysis efficiently and effectively. en_US
dc.language.iso en en_US
dc.publisher Eleventh International Conference On Computer Applications (ICCA 2013) en_US
dc.subject big data analytics en_US
dc.subject big data platform en_US
dc.subject Hadoop MapReduce en_US
dc.subject Apache Pig en_US
dc.subject jaql en_US
dc.subject Apache Hive en_US
dc.subject Gluster file system en_US
dc.title A Comparison of Big Data Analytics Approaches Based on Hadoop MapReduce en_US
dc.type Article en_US


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