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Performance Analysis Using Petri Net Based MapReduce Model in Heterogeneous Clusters

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Advances in Web-Based Learning – ICWL 2013 Workshops (ICWL 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8390))

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Abstract

Currently, big data and large-scale data processing techniques has become an important developing area. MapReduce is an enabling technology of cloud computing. Hadoop is one of the most popular MapReduce implementation, which is the target platform in this paper. When running a MapReduce job, programmers however cannot acquire the information about how to fine-tune the parameters of application. Moreover, programmers need much time on finding the most suitable parameters. This paper evaluates execution processes in MapReduce and form SPN-MR model with Stochastic Petri Net. In order to analyze the performance of SPN-MR, formulas of mean delay time in each time transition are defined. SPN-MR simulates the elapsed time of any MapReduce jobs with known input data sizes and then reduces time cost in performance tuning. SPN-MR carried out several actual test benchmarks. The results showed the average error rate is within 5 percent. Therefore, it can provide effective performance evaluation reports for MapReduce programmers.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan

    Sheng-Tzong Cheng, Hsi-Chuan Wang & Yin-Jun Chen

  2. Department of Information and Communications, Shih Hsin University, Taipei, Taiwan

    Chen-Fei Chen

Authors
  1. Sheng-Tzong Cheng
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  2. Hsi-Chuan Wang
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  3. Yin-Jun Chen
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  4. Chen-Fei Chen
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Corresponding author

Correspondence to Yin-Jun Chen .

Editor information

Editors and Affiliations

  1. Dickson Computer Systems, Kowloon, Hong Kong SAR

    Dickson K. W. Chiu

  2. The University of Hong Kong, Pokfulam, Hong Kong SAR

    Minhong Wang

  3. University of Craiova, Craiova, Romania

    Elvira Popescu

  4. City University of Hong Kong, Hong Kong, Hong Kong SAR

    Qing Li

  5. City University of Hong Kong, Kowloon, Hong Kong SAR

    Rynson Lau

  6. Department of Computer Science and Information Engineering, National Central University, Jhongli City, Taiwan

    Timothy K. Shih

  7. Department of Electrical Engineering, National Cheng Kung University, Taiwan, Taiwan

    Chu-Sing Yang

  8. Digital Systems Centre for Research & Technology Hellas (CERTH), University of Piraeus Dept of Digital Systems, Piraeus, Greece

    Demetrios G. Sampson

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Cheng, ST., Wang, HC., Chen, YJ., Chen, CF. (2015). Performance Analysis Using Petri Net Based MapReduce Model in Heterogeneous Clusters. In: Chiu, D., et al. Advances in Web-Based Learning – ICWL 2013 Workshops. ICWL 2013. Lecture Notes in Computer Science(), vol 8390. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46315-4_18

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  • DOI: https://doi.org/10.1007/978-3-662-46315-4_18

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-46314-7

  • Online ISBN: 978-3-662-46315-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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