TY - JOUR AU - Park, Ha-Myung AU - Park, Chiwan AU - Kang, U PY - 2018/04/29 Y2 - 2024/03/19 TI - PegasusN: A Scalable and Versatile Graph Mining System JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 32 IS - 1 SE - Demonstrations DO - 10.1609/aaai.v32i1.11372 UR - https://ojs.aaai.org/index.php/AAAI/article/view/11372 SP - AB - <p> 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. </p> ER -