PegasusN: A Scalable and Versatile Graph Mining System
DOI:
https://doi.org/10.1609/aaai.v32i1.11372Keywords:
graph mining, distributed system, hadoop, sparkAbstract
How can we find patterns and anomalies in peta-scale graphs? Even recently proposed graph mining systems fail in processing peta-scale graphs. In this work, we propose PegasusN, a scalable and versatile graph mining system that runs on Hadoop and Spark. To handle enormous graphs, PegasusN provides and seamlessly integrates efficient algorithms for various graph mining operations: graph structure analyses, subgraph enumeration, graph generation, and graph visualization. PegasusN quickly processes extra-large graphs that other systems cannot handle.
Downloads
Published
2018-04-29
How to Cite
Park, H.-M., Park, C., & Kang, U. (2018). PegasusN: A Scalable and Versatile Graph Mining System. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). https://doi.org/10.1609/aaai.v32i1.11372
Issue
Section
Demonstrations