文章基本信息

标题：An Efficient Multi-Dimensional Data Analysis over Parallel Computing Framework
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作者：Pramod Patil ; Amit Patange
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2015
卷号：6
期号：4
页码：3650-3654
出版社：TechScience Publications
摘要：In the era of big data where data is growing double by it's size over year and year. So it is very difficult to handle and process the massive amount of data. Data storage and data handling should be done in real time and without loss of data. Cloud computing resolves the problem of storage and availability for data analysis task. Big data and parallel computing frameworks comes into picture where data analysis work need to be carried out. In old days data mining and data analysis have been doing by using traditional approach but after introducing various parallel computing framework it is been very easy to process and extract the data with these frameworks and technology. In this paper we details real world difficulties in data extraction, materialization, caching and data mining tasks. Specifically we introduce dremelcube, a dremel technology based framework for efficient cube computation and exploring the interesting cube groups on holistic measures. Here we demonstrate that, unlike existing techniques we can able to analyze the millions of tuples in real time for our datasets. Dremelcube efficiently and successfully computes the data by using holistic measutes over billion tuple datasets.
关键词：Dremelcube; cloud computing; Data mining;Holistic Measures ;Data Analysis