Research Paper | Computer Science & Engineering | India | Volume 3 Issue 11, November 2014
Memory Management in BigData
Yanish Pradhananga, Shridevi C. Karande
The requirement to perform complicated statistic analysis of big data by institutions of engineering, scientific research, health care, commerce, banking and computer research is immense. However, the limitations of the widely used current desktop software like R, excel, minitab and spss gives a researcher limitation to deal with big data and big data analytic tools like IBM BigInsight, HP Vertica, SAP HANA & Pentaho come at an overpriced license. Apache Hadoop is an open source distributed computing framework that uses commodity hardware. With this project, I intend to collaborate Apache Hadoop and R software to develop an analytic platform that stores big data (using open source Apache Hadoop) and perform statistical analysis (using open source R software). Due to the limitations of vertical scaling of computer unit, data storage is handled by several machines and so analysis becomes distributed over all these machines. Apache Hadoop is what comes handy in this environment. To store massive quantities of data as required by researchers, we could use commodity hardware and perform analysis in distributed environment.
Keywords: Minitab, SPSS, Machine learning, IBM BigInsight, HP Vertica, SAP HANA, Pentaho, Apache Hadoop, R, Big Data
Edition: Volume 3 Issue 11, November 2014
Pages: 1183 - 1187
How to Cite this Article?
Yanish Pradhananga, Shridevi C. Karande, "Memory Management in BigData", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=OCT141117, Volume 3 Issue 11, November 2014, 1183 - 1187
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