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Block-Centric Computation

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Systems for Big Graph Analytics

Part of the book series: SpringerBriefs in Computer Science ((BRIEFSCOMPUTER))

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Abstract

Vertex-centric computation introduced in Part I has two weaknesses. (1) The model may suffer from poor performance in some real graphs, such as those with a large diameter. This chapter describes a novel block-centric computation model that overcomes the weaknesses of vertex-centric computation, and that significantly speeds up iterative graph computation. We also include a hands-on tutorial on how to get started with Blogel, a state-of-the-art block-centric system, which may be skipped if you are only interested in surveying existing big graph analytics systems. (2) Vertex-centric (and even block-centric) API is not suitable for some important graph mining problems such as mining subgraphs. The next chapter will describe a novel subgraph-centric computation model that makes it easy to write programs for efficient large-scale subgraph mining.

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Notes

  1. 1.

    http://www.cse.cuhk.edu.hk/blogel/.

  2. 2.

    You may also search “Blogel” in Google.

  3. 3.

    http://www.cse.cuhk.edu.hk/blogel/documentation.html.

  4. 4.

    http://www.cse.cuhk.edu.hk/blogel/download.html.

  5. 5.

    http://www.cse.cuhk.edu.hk/blogel/overview.html.

  6. 6.

    http://www.cse.cuhk.edu.hk/blogel/api.html.

  7. 7.

    That is why a user needs to know the structure of BPartVertex and BPartValue.

  8. 8.

    http://www.cse.cuhk.edu.hk/blogel/code/apps/block/sssp/Vor.zip.

  9. 9.

    We copy the line first, since strtok(.) replaces the token splitters with ‘∖0’ and thus changes the line. We use strtok(.) since C++’s stringstream needs to copy the line into its internal buffer for parsing, which incurs additional overhead.

  10. 10.

    http://www.cse.cuhk.edu.hk/blogel/code/apps/block/sssp/STR.zip.

  11. 11.

    http://www.cse.cuhk.edu.hk/blogel/code/apps/block/pagerank/urlPart.zip.

  12. 12.

    http://www.cse.cuhk.edu.hk/blogel/overview.html.

  13. 13.

    http://www.cse.cuhk.edu.hk/blogel/code/apps/block/sssp/block.zip.

References

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  3. Y. Tian, A. Balmin, S. A. Corsten, S. Tatikonda, and J. McPherson. From “think like a vertex” to “think like a graph”. PVLDB, 7(3):193–204, 2013.

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Author information

Authors and Affiliations

  1. Department of Computer and Information Science, University of Alabama at Birmingham, Birmingham, AL, USA

    Da Yan

  2. IBM Almaden Research Center, San Jose, CA, USA

    Yuanyuan Tian

  3. Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong

    James Cheng

Authors
  1. Da Yan
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  2. Yuanyuan Tian
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  3. James Cheng
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Yan, D., Tian, Y., Cheng, J. (2017). Block-Centric Computation. In: Systems for Big Graph Analytics. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-58217-7_5

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  • DOI: https://doi.org/10.1007/978-3-319-58217-7_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-58216-0

  • Online ISBN: 978-3-319-58217-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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