Tatiana Jin
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Subgraph matching is one of the most important problems in graph analytics. Many algorithms and systems have been proposed for subgraph matching. Most of these works follow Ullmann's backtracking approach as it is memory-efficient in handling an explosive number of intermediate matching results. However, they have largely overlooked an intrinsic problem of backtracking, namely repeated computation, which contributes to a large portion of the heavy computation in subgraph matching. This paper proposes a subgraph matching system, Circinus, which enables effective computation sharing by a new compression-based backtracking method. Our extensive experiments show that Circinus significantly reduces repeated computation, which transfers to up to several orders of magnitude performance improvement.
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Index Terms
- Circinus: Fast Redundancy-Reduced Subgraph Matching
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