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  • 标题:A Comparative Study on Big Data Analytics Frameworks, Data Resources and Challenges
  • 本地全文:下载
  • 作者:Flasteen Abuqabita ; Razan Al-Omoush ; Jaber Alwidian
  • 期刊名称:Modern Applied Science
  • 印刷版ISSN:1913-1844
  • 电子版ISSN:1913-1852
  • 出版年度:2019
  • 卷号:13
  • 期号:7
  • 页码:1-14
  • DOI:10.5539/mas.v13n7p1
  • 语种:English
  • 出版社:Canadian Center of Science and Education
  • 摘要:Recently, huge amount of data has been generated in all over the world; these data are very huge, extremely fast and varies in its type. In order to extract the value from this data and make sense of it, a lot of frameworks and tools are needed to be developed for analyzing it. Until now a lot of tools and frameworks were generated to capture, store, analyze and visualize it. In this study we categorized the existing frameworks which is used for processing the big data into three groups, namely as, Batch processing, Stream analytics and Interactive analytics, we discussed each of them in detailed and made comparison on each of them.
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