"Evaluating Hybrid Graph Pattern Queries Using Runtime Index Graphs" by Xiaoying Wu, Dimitri Theodoratos et al.
 

Evaluating Hybrid Graph Pattern Queries Using Runtime Index Graphs

Document Type

Conference Proceeding

Publication Date

3-20-2023

Abstract

Graph pattern matching is a fundamental operation for the analysis and exploration of data graphs. In this paper, we present a novel approach for efficiently finding homomorphic matches for hybrid graph patterns, where each pattern edge may be mapped either to an edge or to a path in the input data, thus allowing for higher expressiveness and flexibility in query formulation. A key component of our approach is a lightweight index structure that leverages graph simulation to compactly encode the query answer search space. The index can be built on-the-fly during query execution and does not have to persist on the disk. Using the index, we design a multi-way join algorithm to enumerate query solutions without generating an exploding number of intermediate results. We demonstrate through extensive experiments that our approach can efficiently evaluate a broad spectrum of graph pattern queries and greatly outperforms state-of-the-art approaches. Our source code, datasets and queries are publicly available at https://github.com/wuxyng/RIGMatch.

Identifier

85165077301 (Scopus)

ISBN

[9783893180929]

Publication Title

Advances in Database Technology Edbt

External Full Text Location

https://doi.org/10.48786/edbt.2023.59

e-ISSN

23672005

First Page

710

Last Page

722

Issue

3

Volume

26

Grant

61872276

Fund Ref

National Natural Science Foundation of China

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