Unions of conjunctive two-way regular path queries (UC2RPQs) are a common abstraction of query languages for graph databases, much like unions of conjunctive queries (UCQs) in the relational case. As in the case of UCQs, their evaluation is NP-complete in combined complexity. Semantic tree-width, i.e. the minimal treewidth of equivalent queries, has been proposed as a candidate criterion to characterize fixed-parameter tractability of UC2RPQs. It was recently shown how to decide the semantic tree-width of a UC2RPQ, by constructing the best under-approximation of a given treewidth, in the form of a UC2RPQ of size doubly exponential in the size of the original query. This leads to an fpt algorithm for evaluating UC2RPQs of semantic TW k which runs in time doubly exponential in the size of the parameter, i.e. in the UC2RPQ. Here we describe a more efficient fpt algorithm for evaluating UC2RPQs of semantic treewidth k which runs in time singly exponential in the size of the parameter. We do this by a careful construction of a witness query which, while still being doubly exponential, can be represented as a Datalog program of bounded width and singly exponential size.
@InProceedings{feier_et_al:LIPIcs.ICDT.2024.22, author = {Feier, Cristina and Gogacz, Tomasz and Murlak, Filip}, title = {{Evaluating Graph Queries Using Semantic Treewidth}}, booktitle = {27th International Conference on Database Theory (ICDT 2024)}, pages = {22:1--22:20}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-312-6}, ISSN = {1868-8969}, year = {2024}, volume = {290}, editor = {Cormode, Graham and Shekelyan, Michael}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2024.22}, URN = {urn:nbn:de:0030-drops-198048}, doi = {10.4230/LIPIcs.ICDT.2024.22}, annote = {Keywords: conjunctive two-way regular path queries, fixed-parameter tractable evaluation, semantic treewidth, Datalog encoding, optimization} }
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