Regular Path Query Evaluation Sharing a Reduced Transitive Closure Based on Graph Reduction

TL;DR

This paper introduces a novel graph reduction technique and a lightweight transitive closure structure to efficiently evaluate regular path queries with Kleene closures, significantly improving performance.

Contribution

It proposes RPQ-based graph reduction and RTC sharing methods to optimize regular path query evaluation involving Kleene closures.

Findings

Up to 73.86 times faster query response times.

Effective sharing of transitive closure reduces redundant computations.

Formal relational algebra representation enables further optimization.

Abstract

Regular path queries (RPQs) find pairs of vertices of paths satisfying given regular expressions on an edge-labeled, directed multigraph. When evaluating an RPQ, the evaluation of a Kleene closure (i.e., Kleene plus or Kleene star) is very expensive. Furthermore, when multiple RPQs include a Kleene closure as a common sub-query, repeated evaluations of the common sub-query cause serious performance degradation. In this paper, we present a novel concept of RPQ-based graph reduction, which significantly simplifies the original graph through edge-level and vertex-level reductions. Interestingly, RPQ-based graph reduction can replace the evaluation of the Kleene closure on the large original graph to that of the transitive closure to the small reduced graph. We then propose a reduced transitive closure (RTC) as a lightweight structure for efficiently sharing the result of a Kleene closure. We also present an RPQ evaluation algorithm, RTCSharing, which treats each clause in the disjunctive normal form of the given RPQ as a batch unit. If the batch units include a Kleene closure as a common sub-query, we share the lightweight RTC instead of the heavyweight result of the Kleene closure. RPQ-based graph reduction further enables us to formally represent the result of an RPQ including a Kleene closure as a relational algebra expression including the RTC. Through the formal expression, we optimize the evaluation of the batch unit by eliminating useless and redundant operations of the previous method. Experiments show that RTCSharing improves the performance significantly by up to 73.86 times compared with existing methods in terms of query response time.