Efficient big data analysis on a single machine using apache spark and self-organizing map libraries

David Andresic, Petr Šaloun, Ioannis Anagnostopoulos
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引用次数: 1

Abstract

Apache Spark is commonly used as a big data analytical platform on powerful computer clusters, as it primarily employ the main computer memory for the evaluation. Our attempt adds self-organizing map software libraries onto a single big data analytical stack and is efficient and fast enough even on a standard single computer. This innovative approach brings the big data analysis to researchers with limited resources. Our genuine idea was experimentally confirmed and is described here. As a case study for our method we we used the available #Brexit data and the sentiment analysis of corresponding tweets and the correlation with the stock exchange data.
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使用apache spark和自组织地图库在单机上进行高效的大数据分析
Apache Spark通常用作强大的计算机集群上的大数据分析平台,因为它主要使用主计算机内存进行评估。我们尝试将自组织地图软件库添加到单个大数据分析堆栈上,即使在标准的单个计算机上也足够高效和快速。这种创新的方法使资源有限的研究人员能够进行大数据分析。我们的真实想法在实验中得到了证实,并在这里进行了描述。作为我们方法的案例研究,我们使用了可用的#Brexit数据和相应推文的情绪分析以及与证券交易所数据的相关性。
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