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Design of Forum Log System Based on Big Data Analysis

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Green Energy and Networking (GreeNets 2020)

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Abstract

Clicking on the log data saved by the website, using the big data means to analyze and mine the information stored by massive data, many crucial information of website operation can be learned. This paper adopts Hadoop distributed platform, uses HDFS data storage and Hive to analyze log big data, designs a Web log analysis system and expounds the design process of the system.

Foundation item: Philosophy and social science project of heilongjiang province (16EDC04);School-level topics(KJY202002)

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References

  1. Yanhui, M.: Big Data Technology Foundation. Tsinghua University Press, Beijing (2016)

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  2. Wbite, T.: Hadoop: The Definitive Guide. O’Reilly Media, Sebastopol (2015)

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  3. Rutherglen, J.: Hive Programming guide.People Post Press (2013)

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  4. Shenzhi, S.: Research on Web Log Data Analysis System Based on Hadoop. Xidian University

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  5. [Apache Flume] Official document http://flume.apache.org/

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Author information

Authors and Affiliations

  1. Heihe University, Heihe City, Heilongjiang Province, China

    Guanghua Yu, Linan Sun & Yongjuan Wang

Authors
  1. Guanghua Yu
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  2. Linan Sun
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  3. Yongjuan Wang
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Corresponding author

Correspondence to Guanghua Yu .

Editor information

Editors and Affiliations

  1. Heilongjiang University of Science and Technology, Harbin, China

    Xiaolin Jiang

  2. Dalian Polytehnic University, Dalian, China

    Peng Li

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Cite this paper

Yu, G., Sun, L., Wang, Y. (2020). Design of Forum Log System Based on Big Data Analysis. In: Jiang, X., Li, P. (eds) Green Energy and Networking. GreeNets 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 333. Springer, Cham. https://doi.org/10.1007/978-3-030-62483-5_4

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  • DOI: https://doi.org/10.1007/978-3-030-62483-5_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62482-8

  • Online ISBN: 978-3-030-62483-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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