Convergence of Datalog over (Pre-) Semirings

Mahmoud Abo Khamis, H. Ngo, R. Pichler, Dan Suciu, Y. Wang
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引用次数: 13

Abstract

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 generalize the semi-na¨ve evaluation algorithm to compute their minimal fixpoints.
数据在(预)半环上的收敛性
递归查询传统上是在datalog的框架下研究的,这种语言将递归限制为对集合的单调查询,保证在输入大小的多项式时间内收敛。但现代大数据系统需要超越布尔空间的递归计算。本文研究了在任意半环上解释数据表时的收敛性。我们考虑一个有序半环,将数据程序的语义定义为该半环中的最小不动点,并研究到达该不动点所需的步骤数(如果有的话)。我们确定了与数据规划的某些收敛性质相对应的半环的代数性质。最后,我们描述了一类有序半环,人们可以在其上推广半朴素求值算法来计算它们的最小不动点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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