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An overview and an Approach for Graph Data Processing using Hadoop MapReduce

机译:使用Hadoop MapReduce进行图形数据处理的概述和方法

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A very large quantity of data which traditional applications fail to process, leads the world to the era of Big Data. With the increase in opportunity and technology scope, Big Data also leads to many challenges such as data capture, storage, transfer, update, analysis, sharing, search, visualization, privacy of data etc. In order to deal with all these challenges there is a need of proper framework which will not only process the data but also provide a meaningful analysis so as to take proper decision in critical situations either related to industry, healthcare, social network, science, telecom, environment, business etc. The contribution of this paper is to analyze literature related to Big Data & Hadoop framework and provide architecture to process Graph Data. Additionally, it provides online source code in order to understand big data for beginners.
机译:传统应用程序无法处理的大量数据使世界进入了大数据时代。随着机会和技术范围的扩大,大数据还带来了许多挑战,例如数据捕获,存储,传输,更新,分析,共享,搜索,可视化,数据隐私等。需要一个适当的框架,不仅要处理数据,还要提供有意义的分析,以便在与工业,医疗保健,社交网络,科学,电信,环境,商业等相关的紧急情况下做出正确的决策。本文旨在分析与大数据和Hadoop框架相关的文献,并提供用于处理图数据的体系结构。此外,它提供了在线源代码,以便为初学者了解大数据。

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