Convergence of Datalog over (Pre-) Semirings

IF 2.3 2区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Journal of the ACM Pub Date : 2024-01-30 DOI:10.1145/3643027
Mahmoud Abo Khamis, Hung Q. Ngo, Reinhard Pichler, Dan Suciu, Yisu Remy Wang
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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 use the semi-naïve evaluation algorithm on any datalog program.

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数据模型在(前)语义上的收敛性
递归查询传统上是在 datalog 框架下研究的,这种语言将递归限制在对集合的单调查询上,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。在本文中,我们研究了在任意语义上解释数据模型时的收敛性。我们考虑一个有序配系,将 datalog 程序的语义定义为该配系中的一个最小定点,并研究达到该定点所需的步骤数(如果有的话)。我们确定了与 datalog 程序的某些收敛特性相对应的语义的代数特性。最后,我们描述了一类有序语义,在这类语义上,我们可以对任何 datalog 程序使用半幼稚求值算法。
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来源期刊
Journal of the ACM
Journal of the ACM 工程技术-计算机:理论方法
CiteScore
7.50
自引率
0.00%
发文量
51
审稿时长
3 months
期刊介绍: The best indicator of the scope of the journal is provided by the areas covered by its Editorial Board. These areas change from time to time, as the field evolves. The following areas are currently covered by a member of the Editorial Board: Algorithms and Combinatorial Optimization; Algorithms and Data Structures; Algorithms, Combinatorial Optimization, and Games; Artificial Intelligence; Complexity Theory; Computational Biology; Computational Geometry; Computer Graphics and Computer Vision; Computer-Aided Verification; Cryptography and Security; Cyber-Physical, Embedded, and Real-Time Systems; Database Systems and Theory; Distributed Computing; Economics and Computation; Information Theory; Logic and Computation; Logic, Algorithms, and Complexity; Machine Learning and Computational Learning Theory; Networking; Parallel Computing and Architecture; Programming Languages; Quantum Computing; Randomized Algorithms and Probabilistic Analysis of Algorithms; Scientific Computing and High Performance Computing; Software Engineering; Web Algorithms and Data Mining
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