RealGraph: A Graph Engine Leveraging the Power-Law Distribution of Real-World Graphs
- Title
- RealGraph: A Graph Engine Leveraging the Power-Law Distribution of Real-World Graphs
- Author
- 김상욱
- Keywords
- Graph engine; Single machine; Real-world graph; Power-law degree distribution
- Issue Date
- 2019-05
- Publisher
- Association for Computing Machinery
- Citation
- The Web Conference 2019 - Proceedings of the World Wide Web Conference, Page. 807-817
- 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. © 2019 IW3C2 (International World Wide Web Conference Committee), published under Creative Commons CC-BY 4.0 License.
- URI
- https://dl.acm.org/doi/10.1145/3308558.3313434https://repository.hanyang.ac.kr/handle/20.500.11754/151161
- ISBN
- 978-145036674-8
- DOI
- 10.1145/3308558.3313434
- Appears in Collections:
- COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE(컴퓨터소프트웨어학부) > Articles
- Files in This Item:
There are no files associated with this item.
- Export
- RIS (EndNote)
- XLS (Excel)
- XML