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International Conference on Intelligent Science and Big Data Engineering

IScIDE 2015: Intelligence Science and Big Data Engineering. Big Data and Machine Learning Techniques pp 443–453Cite as

Research of Massive Data Caching Strategy Based on Key-Value Storage Model

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9243))

Abstract

The development trend of Internet application and software is needed to read-write and access the massive data efficiently and quickly. In order to improve the performance which Web access huge amounts of data and analyze the SQL of data caching strategy, this paper proposes a strategy of the massive data cache based on Key-Value storage model according to the characteristics of massive data access. This strategy can optimize the semantic analysis of SQL for the user’s query, then it extracts data objects which are involved in the query, at last it calculates the cost of cache by Key characteristics. These data will be stored in the cache server in the form of object. Thereby, it can reduce the access to the main database and improve the performance of data access. The experiments show that the caching scheme can effectively reduce the average response time and increase the throughput capacity of system.

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References

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Acknowledgment

This work is supported by project of teaching reform in Jiangxi Province (JXJG-12-8-15) and project of the Education Department of Jiangxi province science and technology projects (No. GJJ12752).

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Authors and Affiliations

  1. Faculty of Information Engineering, East China Institute of Technology, Nanchang, 330013, China

    Lei Wang & Kun Wang

  2. Faculty Water Resource and Environmental Engineering, East China Institute of Technology, Nanchang, 330013, China

    Gongxin Chen

Authors
  1. Lei Wang
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  2. Gongxin Chen
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  3. Kun Wang
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Corresponding author

Correspondence to Lei Wang .

Editor information

Editors and Affiliations

  1. Zhejiang University, Hangzhou, China

    Xiaofei He

  2. Xidian University, Xi'an, China

    Xinbo Gao

  3. Northwestern Polytechnical University, Xi'an, China

    Yanning Zhang

  4. Nanjing University, Nanjing, China

    Zhi-Hua Zhou

  5. Chinese Academy of Sciences, Beijing, China

    Zhi-Yong Liu

  6. Suzhou University of Science and Technology, Suzhou, China

    Baochuan Fu

  7. Suzhou University of Science and Technology, Jiangsu, China

    Fuyuan Hu

  8. Suzhou University of Science and Technology, Jiangsu, China

    Zhancheng Zhang

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© 2015 Springer International Publishing Switzerland

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Cite this paper

Wang, L., Chen, G., Wang, K. (2015). Research of Massive Data Caching Strategy Based on Key-Value Storage Model. In: He, X., et al. Intelligence Science and Big Data Engineering. Big Data and Machine Learning Techniques. IScIDE 2015. Lecture Notes in Computer Science(), vol 9243. Springer, Cham. https://doi.org/10.1007/978-3-319-23862-3_44

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  • DOI: https://doi.org/10.1007/978-3-319-23862-3_44

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23861-6

  • Online ISBN: 978-3-319-23862-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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