Transforming Property Graphs
Angela Bonifati, Filip Murlak, Yann Ramusat

TL;DR
This paper introduces a declarative framework for property graph transformations using Graph Pattern Calculus, analyzing its complexity, implementing it in openCypher, and demonstrating its practical advantages over ad-hoc methods.
Contribution
It presents a novel declarative approach for property graph transformations based on GPC, including complexity analysis, implementation in openCypher, and empirical evaluation.
Findings
Checking for conflicting property values is PSpace-complete.
The framework is flexible and usable in data integration tasks.
Experimental results show significant practical benefits over ad-hoc scripts.
Abstract
In this paper, we study a declarative framework for specifying transformations of property graphs. In order to express such transformations, we leverage queries formulated in the Graph Pattern Calculus (GPC), which is an abstraction of the common core of recent standard graph query languages, GQL and SQL/PGQ. In contrast to previous frameworks targeting graph topology only, we focus on the impact of data values on the transformations--which is crucial in addressing users needs. In particular, we study the complexity of checking if the transformation rules do not specify conflicting values for properties, and we show this is closely related to the satisfiability problem for GPC. We prove that both problems are PSpace-complete. We have implemented our framework in openCypher. We show the flexibility and usability of our framework by leveraging an existing data integration benchmark,…
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Taxonomy
TopicsAdvanced Graph Theory Research
