by Thomas Beyhl, Dominique Blouin, Holger Giese, Leen Lambers
Abstract:
Graph queries have lately gained increased interest due to application areas such as social networks, biological networks, or model queries. For the relational database case the relational algebra and generalized discrimination networks have been studied to find appropriate decompositions into subqueries and ordering of these subqueries for query evaluation or incremental updates of query results. For graph database queries however there is no formal underpinning yet that allows us to find such suitable operationalizations. Consequently, we suggest a simple operational concept for the decomposition of arbitrary complex queries into simpler subqueries and the ordering of these subqueries in form of generalized discrimination networks for graph queries inspired by the relational case. The approach employs graph transformation rules for the nodes of the network and thus we can employ the underlying theory. We further show that the proposed generalized discrimination networks have the same expressive power as nested graph conditions.
Reference:
On the Operationalization of Graph Queries with Generalized Discrimination Networks (Thomas Beyhl, Dominique Blouin, Holger Giese, Leen Lambers), Technical report 106, Hasso Plattner Institute at the University of Potsdam, 2016.
Bibtex Entry:
@TechReport{GieseHildebrandtLambers2010_1_2,
AUTHOR = {Beyhl, Thomas and Blouin, Dominique and Giese, Holger and Lambers, Leen},
TITLE = {{On the Operationalization of Graph Queries with Generalized Discrimination Networks}},
YEAR = {2016},
NUMBER = {106},
INSTITUTION = {Hasso Plattner Institute at the University of Potsdam},
URL = {https://publishup.uni-potsdam.de/opus4-ubp/files/9627/tbhpi106.pdf},
PDF = {uploads/pdf/GieseHildebrandtLambers2010_1_2.pdf},
OPTacc_pdf = {},
ABSTRACT = {Graph queries have lately gained increased interest due to application areas such as social networks, biological networks, or model queries. For the relational database case the relational algebra and generalized discrimination networks have been studied to find appropriate decompositions into subqueries and ordering of these subqueries for query evaluation or incremental updates of query results. For graph database queries however there is no formal underpinning yet that allows us to find such suitable operationalizations. Consequently, we suggest a simple operational concept for the decomposition of arbitrary complex queries into simpler subqueries and the ordering of these subqueries in form of generalized discrimination networks for graph queries inspired by the relational case. The approach employs graph transformation rules for the nodes of the network and thus we can employ the underlying theory. We further show that the proposed generalized discrimination networks have the same expressive power as nested graph conditions. }
}