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Efficient processing of label-constraint reachability queries in large graphs
Information Systems
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Recent interests on xml, the Semantic Web, and Web ontology, among other topics, have sparked a renewed interest on graph-structured databases. A fundamental query on graphs is the reachability test of nodes. Recently, 2-hop labeling has been proposed to index a large collection of xml and/or graphs for efficient reachability tests. However, there has been few work on updates of 2-hop labeling. This is compounded by the fact that data may often change over time. In response to these, this paper studies incremental maintenance of 2-hop labeling. We identify the main reason for the inefficiency of updates of existing 2-hop labels. We propose three updatable 2-hop labelings, hybrids of 2-hop labeling, and their incremental maintenance algorithms. The proposed 2--hop labeling is derived from graph connectivity, as opposed to set cover which is used by most previous works. Our experimental evaluation illustrates the space efficiency and update performance of various kinds of 2-hop labelings. Our results show that our incremental maintenance algorithm can be two orders of magnitude faster than previous methods and the size of our 2-hop labeling can be comparable to existing 2-hop labeling. We conclude that there is a natural way to spare some index size for update performance in 2-hop labeling.