Typing Regular Path Query Languages for Data Graphs
Dario Colazzo, Carlo Sartiani

TL;DR
This paper introduces a schema language for edge-labelled data graphs and a query type inference method, enhancing optimization and simplifying application development for regular path query languages.
Contribution
It proposes a simple, expressive schema language and a type inference approach that improves query optimization and development in data graph query languages.
Findings
Schema language enhances query optimization
Type inference improves query precision
Facilitates application development
Abstract
Regular path query languages for data graphs are essentially \emph{untyped}. The lack of type information greatly limits the optimization opportunities for query engines and makes application development more complex. In this paper we discuss a simple, yet expressive, schema language for edge-labelled data graphs. This schema language is, then, used to define a query type inference approach with good precision properties.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsGraph Theory and Algorithms · Advanced Database Systems and Queries · Data Management and Algorithms
