| Title | PatMat: A Distributed Pattern Matching Engine with Cypher |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Hao, Kongzhang, Yang, Zhengyi, Lai, Longbin, Lai, Zhengmin, Jin, Xin, Lin, Xuemin |
| Conference Name | Proceedings of the 28th ACM International Conference on Information and Knowledge Management |
| Date Published | November 2019 |
| Publisher | Association for Computing Machinery |
| Conference Location | Beijing, China |
| ISBN Number | 978-1-4503-6976-3 |
| Keywords | cyber physical systems, Cypher, distributed processing, graph database, graph pattern matching, join optimization, Lightweight Ciphers, pubcrawl, resilience, Resiliency, Scalability |
| Abstract | Graph pattern matching is one of the most fundamental problems in graph database and is associated with a wide spectrum of applications. Due to its computational intensiveness, researchers have primarily devoted their efforts to improving the performance of the algorithm while constraining the graphs to have singular labels on vertices (edges) or no label. Whereas in practice graphs are typically associated with rich properties, thus the main focus in the industry is instead on powerful query languages that can express a sufficient number of pattern matching scenarios. We demo PatMat in this work to glue together the academic efforts on performance and the industrial efforts on expressiveness. To do so, we leverage the state-of-the-art join-based algorithms in the distributed contexts and Cypher query language - the most widely-adopted declarative language for graph pattern matching. The experiments demonstrate how we are capable of turning complex Cypher semantics into a distributed solution with high performance. |
| URL | https://dl.acm.org/doi/10.1145/3357384.3357840 |
| DOI | 10.1145/3357384.3357840 |
| Citation Key | hao_patmat_2019 |
PatMat: A Distributed Pattern Matching Engine with Cypher