Facilitating real-time graph mining

Zhuhua Cai, Dionysios Logothetis, Georgos Siganos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Citations (Scopus)

Abstract

Real-time data processing is increasingly gaining momentum as the preferred method for analytical applications. Many of these applications are built on top of large graphs with hundreds of millions of vertices and edges. A fundamental requirement for real-time processing is the ability to do incremental processing. However, graph algorithms are inherently difficult to compute incrementally due to data dependencies. At the same time, devising incremental graph algorithms is a challenging programming task. This paper introduces GraphInc, a system that builds on top of the Pregel model and provides efficient incremental processing of graphs. Importantly, GraphInc supports incremental computations automatically, hiding the complexity from the programmers. Programmers write graph analytics in the Pregel model without worrying about the continuous nature of the data. GraphInc integrates new data in real-time in a transparent manner, by automatically identifying opportunities for incremental processing. We discuss the basic mechanisms of GraphInc and report on the initial evaluation of our approach.

Original languageEnglish
Title of host publicationCloudDB'12 - Proceedings of the 3rd ACM International Workshop on Cloud Data Management, Co-located with CIKM 2012
Pages1-8
Number of pages8
DOIs
Publication statusPublished - 10 Dec 2012
Event3rd ACM International Workshop on Cloud Data Management, CloudDB 2012 - Co-located with CIKM 2012 - Maui, HI, United States
Duration: 29 Oct 201229 Oct 2012

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Other

Other3rd ACM International Workshop on Cloud Data Management, CloudDB 2012 - Co-located with CIKM 2012
CountryUnited States
CityMaui, HI
Period29/10/1229/10/12

Keywords

  • Graph mining
  • Incremental processing
  • Memoization

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

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  • Cite this

    Cai, Z., Logothetis, D., & Siganos, G. (2012). Facilitating real-time graph mining. In CloudDB'12 - Proceedings of the 3rd ACM International Workshop on Cloud Data Management, Co-located with CIKM 2012 (pp. 1-8). (International Conference on Information and Knowledge Management, Proceedings). https://doi.org/10.1145/2390021.2390023