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Parka: A Parallel Implementation of BLAST with MapReduce

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Advances in Intelligent Systems and Interactive Applications (IISA 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 686))

Abstract

Bioinformatics applications have become more data-intensive and compute-intensive, which requires an effective method to implement parallel computing and get a high-throughput. Although there exists some tools to realize parallelization of BLAST, but most of them depend on complex platforms or software. A parallel BLAST is implemented using Spark, which is called Parka. The parallel execution time and speedup of Parka are evaluated in a cluster environment. Then, it is compared with Hadoop-based parallelization method. Results show that it is a scalable and effective parallelization approach for sequence alignment.

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Acknowledgments

This work is partly supported by the National Natural Science Foundation of China (No. 61602169), the Natural Science Foundation of Hunan Province (No. 2015JJ3071), and the Scientific Research Fund of Hunan Provincial Education Department (No. 16C0643).

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Authors and Affiliations

  1. School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, 411201, Hunan, China

    Li Zhang & Bing Tang

Authors
  1. Li Zhang
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  2. Bing Tang
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Corresponding author

Correspondence to Li Zhang .

Editor information

Editors and Affiliations

  1. Technical University of Catalonia, Barcelona, Spain

    Fatos Xhafa

  2. Department of Computer Science and Engineering, Faculty of Engineering and Technology, SOA University, Bhubaneswar, Odisha, India

    Srikanta Patnaik

  3. School of Information Technologies, University of Sydney, Sydney, New South Wales, Australia

    Albert Y. Zomaya

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Zhang, L., Tang, B. (2018). Parka: A Parallel Implementation of BLAST with MapReduce. In: Xhafa, F., Patnaik, S., Zomaya, A. (eds) Advances in Intelligent Systems and Interactive Applications. IISA 2017. Advances in Intelligent Systems and Computing, vol 686. Springer, Cham. https://doi.org/10.1007/978-3-319-69096-4_26

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  • DOI: https://doi.org/10.1007/978-3-319-69096-4_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69095-7

  • Online ISBN: 978-3-319-69096-4

  • eBook Packages: EngineeringEngineering (R0)

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