A Survey on Distributed Graph Pattern Matching in Massive Graphs

Sarra Bouhenni, Saïd Yahiaoui, Nadia Nouali-Taboudjemat, Hamamache Kheddouci
2021 ACM Computing Surveys  
Besides its NP-completeness, the strict constraints of subgraph isomorphism are making it impractical for graph pattern matching (GPM) in the context of big data. As a result, relaxed GPM models have emerged as they yield interesting results in a polynomial time. However, massive graphs generated by mostly social networks require a distributed storing and processing of the data over multiple machines, thus, requiring GPM to be revised by adopting new paradigms of big graphs processing, e.g.,
more » ... nk-Like-A-Vertex and its derivatives. This article discusses and proposes a classification of distributed GPM approaches with a narrow focus on the relaxed models.
doi:10.1145/3439724 fatcat:vib22wz2zffo3c5alriufetwaa