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  1. University of Computer Studies, Yangon
  2. Faculty of Computer Science

A Platform for Big Data Analytics on Distributed Scale-out Storage System

http://hdl.handle.net/20.500.12678/0000005017
http://hdl.handle.net/20.500.12678/0000005017
b59bbf1d-413d-4a89-a380-7b4dbd7d1a93
a42d7044-2b75-4e4b-aabe-c2fee8d0132e
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ijbdi2015.pdf ijbdi2015.pdf (762 Kb)
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Article
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Publication
Title
Title A Platform for Big Data Analytics on Distributed Scale-out Storage System
Language en
Publication date 2015
Authors
Aye, Kyar Nyo
Thein, Thandar
Description
Big data analytics is the process of examining large amounts of data of a varietyof types to uncover hidden patterns, unknown correlations and other useful information.Hadoop-based platform emerges to deal with big data. In Hadoop NameNode is used to store metadata in a single system’s memory, which is a performance bottleneck for scale-out. Gluster file system has no performance bottlenecks related to metadata. To achieve massive performance, scalability and fault tolerance for big data analytics, a big data platform is proposed. The proposed big data platform consists of big data storage and big data processing. The Hadoop big data platform and the proposed big data platform are implemented on commodity Linux virtual machines clusters and performance evaluations are conducted. According to the evaluation analysis, the proposed big data platform provides better scalability, fault tolerance, and faster query response time than the Hadoop platform.
Keywords
big data, big data analytics, big data platform, Hadoop MapReduce, Gluster File System, Apache Pig, Apache Hive, Jaql
Identifier 2053-1389
Journal articles
International Journal of Big Data Intelligence (IJBDI)
Conference papers
Books/reports/chapters
Thesis/dissertations
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