Abstract
With the prevalence of graph data in a variety of domains, there is an increasing need for a language to query and manipulate graphs with heterogeneous attributes and structures. We present a graph query language (GraphQL) that supports bulk operations on graphs with arbitrary structures and annotated at- tributes. In this language, graphs are the basic unit of information and each query manipulates one or more collections of graphs at a time. The core of GraphQL is a graph algebra extended from the relational algebra in which the selection operator is generalized to graph pattern matching and a composition operator is introduced for rewriting matched graphs. Then, we investigate access methods of the selection operator. Pattern matching over large graphs is challenging due to the NP-completeness of subgraph isomorphism. We address this by a combination of techniques: use of neighborhood subgraphs and pro- files, joint reduction of the search space, and optimization of the search order. Experimental results on real and synthetic large graphs demonstrate that graph specific optimizations outperform an SQL-based implementation by orders of magnitude.
This is a revised and extended version of the article “Graphs-at-a-time: Query Language and Access Methods for Graph Databases”, Huahai He and Ambuj K. Singh, In Proceedings of the 2008 ACMSIGMOD Conference, http://doi.acm.org/10.1145/1376616.1376660. Reprinted with permission of ACM.
Work done while at the University of California, Santa Barbara.
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He, H., Singh, A.K. (2010). Query Language and Access Methods for Graph Databases. In: Aggarwal, C., Wang, H. (eds) Managing and Mining Graph Data. Advances in Database Systems, vol 40. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-6045-0_4
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