| Title | Fast Parallel Path Concatenation for Graph Extraction (Extended Abstract) |
| Authors | Shao, Yingxia Lei, Kai Chen, Lei Huang, Zi Cui, Bin Liu, Zhongyi Tong, Yunhai Xu, Jin |
| Affiliation | Peking Univ, Sch EECS, Beijing, Peoples R China. Peking Univ, Key Lab High Confidence Software Technol, MOE, Beijing, Peoples R China. Peking Univ, Shenzhen Grad Sch, ECE, Shenzhen, Peoples R China. HKUST, Dept Comp Sci & Engn, Hong Kong, Peoples R China. Univ Queensland, Sch ITEE, Brisbane, Qld 4072, Australia. Alibaba Grp, Beijing, Peoples R China. Peking Univ, Sch EECS, Beijing, Peoples R China. Shao, YX (reprint author), Peking Univ, Key Lab High Confidence Software Technol, MOE, Beijing, Peoples R China. |
| Issue Date | 2018 |
| Publisher | 2018 IEEE 34TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE) |
| Citation | 2018 IEEE 34TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE). 2018, 1753-1754. |
| Abstract | In this paper, we study the problem of extracting a homogeneous graph from a heterogeneous graph. The key challenges of the extraction problem are how to efficiently enumerate paths matched by the provided line pattern and aggregate values for each pair of vertices from the matched paths. To address above two challenges, we propose a parallel graph extraction framework (PGE), where we use vertex-centric model to enumerate paths and compute aggregate functions in parallel. The framework compiles the line pattern into a path concatenation plan and generates the final weighted edges in a divide-and-conquer manner. The new solution outperforms the state-of-the-art ones through the comprehensive experiments. |
| URI | http://hdl.handle.net/20.500.11897/575656 |
| ISSN | 1084-4627 |
| DOI | 10.1109/ICDE.2018.00234 |
| Indexed | CPCI-S(ISTP) |
| Appears in Collections: | 信息科学技术学院 高可信软件技术教育部重点实验室 深圳研究生院待认领 |
