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Distributed Graph Analytics pp 1–29Cite as

Introduction to Graph Analytics

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Abstract

This chapter discusses the importance of graph analytics. It describes important concepts in elementary graph theory and different graph representations, programming frameworks for parallelization, and various challenges posed by graph analytics algorithms. Graph partitioning and real-world applications of graphs are also covered. Frameworks and DSLs that can ease programming graph analytics are briefly discussed.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology Palakkad, Palakkad, Kerala, India

    Unnikrishnan Cheramangalath

  2. Department of Computer Science and Engineering, Indian Institute of Technology Madras, Chennai, India

    Rupesh Nasre

  3. Department of Computer Science and Automation, Indian Institute of Science Bangalore, Bangalore, India

    Y. N. Srikant

Authors
  1. Unnikrishnan Cheramangalath
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  2. Rupesh Nasre
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  3. Y. N. Srikant
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Cite this chapter

Cheramangalath, U., Nasre, R., Srikant, Y.N. (2020). Introduction to Graph Analytics. In: Distributed Graph Analytics. Springer, Cham. https://doi.org/10.1007/978-3-030-41886-1_1

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  • DOI: https://doi.org/10.1007/978-3-030-41886-1_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-41885-4

  • Online ISBN: 978-3-030-41886-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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