RealGraph: A graph engine leveraging the power-law distribution of real-world graphs

Yong Yeon Jo, Sang Wook Kim, Myung Hwan Jang, Sun Ju Park

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

3 Citations (Scopus)

Abstract

As the size of real-world graphs has drastically increased in recent years, a wide variety of graph engines have been developed to deal with such big graphs efficiently. However, the majority of graph engines have been designed without considering the power-law degree distribution of real-world graphs seriously. Two problems have been observed when existing graph engines process real-world graphs: inefficient scanning of the sparse indicator and the delay in iteration progress due to uneven workload distribution. In this paper, we propose RealGraph, a single-machine based graph engine equipped with the hierarchical indicator and the block-based workload allocation. Experimental results on real-world datasets show that RealGraph significantly outperforms existing graph engines in terms of both speed and scalability.

Original languageEnglish
Title of host publicationThe Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019
PublisherAssociation for Computing Machinery, Inc
Pages807-817
Number of pages11
ISBN (Electronic)9781450366748
DOIs
Publication statusPublished - 2019 May 13
Event2019 World Wide Web Conference, WWW 2019 - San Francisco, United States
Duration: 2019 May 132019 May 17

Publication series

NameThe Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019

Conference

Conference2019 World Wide Web Conference, WWW 2019
Country/TerritoryUnited States
CitySan Francisco
Period19/5/1319/5/17

Bibliographical note

Funding Information:
This work was supported by (1) the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (MSIT) (NRF-2017R1A2B3004581) and (2) Next-Generation Information Computing Development Program through NRF funded by MSIT (NRF-2017M3C4A7069440). Also, we appreciate Samsung Electronics' university program [Flash Solutions for Emerging Applications] that significantly helps train our lab. members.

Publisher Copyright:
© 2019 IW3C2 (International World Wide Web Conference Committee), published under Creative Commons CC-BY 4.0 License.

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software

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