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  • 标题:MESURING THE EFFICENY OF USING HADOOP TO ANALYZE BIG DATA- A CASE STUDY ON TWITTER DATA SET
  • 本地全文:下载
  • 作者:YOUSEF K. SANJALAWE ; MOHAMMED ANBAR
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2017
  • 卷号:95
  • 期号:12
  • 页码:2711
  • 出版社:Journal of Theoretical and Applied
  • 摘要:In last decades, the continuous enhancements of computational power have produced a massive data flow. Big data has been becoming more understandable as well as becoming more available. For instance, the famous online social networks, such as Facebook, and twitter, serve about 560 billion page views everyone�s month. They also store new number of images near 3 billion each one month. This research emphasizes the solution and importance of big data problems using cloud computing (CC). Knowledge implanted in big data can be generated by personal computers PCs, mobile devices, and sensors, but it requires spending millions or billions of dollars in order to solve knowledge and information extraction problems to make suitable and critical decisions. In this research, we use Hadoop tool to analyze the big online data set with 8 GB size. The results show the importance of cloud approach to analyze the huge data with less efforts, cost, and time.
  • 关键词:Big Data; Big Data Analytics; Cloud Service; Hadoop; Analyze Data Of Twitter
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