Khamis, M. A., Ngo, H. Q., Pichler, R., Suciu, D., & Wang, Y. R. (2022). Convergence of Datalog over (Pre-) Semirings. In PODS ’22: Proceedings of the 41st ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems (p. 105). Association for Computing Machinery. https://doi.org/10.1145/3517804.3524140
Recursive queries have been traditionally studied in the framework of datalog, a language that restricts recursion to monotone queries over sets, which is guaranteed to converge in polynomial time in the size of the input. But modern big data systems require recursive computations beyond the Boolean space. In this paper we study the convergence of datalog when it is interpreted over an arbitrary semiring. We consider an ordered semiring, define the semantics of a datalog program as a least fixpoint in this semiring, and study the number of steps required to reach that fixpoint, if ever. We identify algebraic properties of the semiring that correspond to certain convergence properties of datalog programs. Finally, we describe a class of ordered semirings on which one can use the semi-naive evaluation algorithm on any datalog program.
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Project title:
HyperTrac: hypergraph Decompositions and Tractability: P30930-N35 (Fonds zur Förderung der wissenschaftlichen Forschung (FWF))
