Dichotomies for Queries with Negation in Probabilistic Databases

IF 2.2 2区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Robert Fink, Dan Olteanu
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引用次数: 37

Abstract

This article charts the tractability frontier of two classes of relational algebra queries in tuple-independent probabilistic databases. The first class consists of queries with join, projection, selection, and negation but without repeating relation symbols and union. The second class consists of quantified queries that express the following binary relationships among sets of entities: set division, set inclusion, set equivalence, and set incomparability. Quantified queries are expressible in relational algebra using join, projection, nested negation, and repeating relation symbols. Each query in the two classes has either polynomial-time or #P-hard data complexity and the tractable queries can be recognised efficiently. Our result for the first query class extends a known dichotomy for conjunctive queries without self-joins to such queries with negation. For quantified queries, their tractability is sensitive to their outermost projection operator: They are tractable if no attribute representing set identifiers is projected away and #P-hard otherwise.
概率数据库中带有否定查询的二分类
本文绘制了元独立概率数据库中两类关系代数查询的可跟踪性边界图。第一类由带有连接、投影、选择和否定的查询组成,但不重复关系符号和联合。第二类由量化查询组成,这些查询表示实体集之间的以下二元关系:集分割、集包含、集等价和集不可比较。量化查询可以在关系代数中使用连接、投影、嵌套否定和重复关系符号来表示。这两个类中的每个查询都具有多项式时间或#P-hard数据复杂性,并且可以有效地识别可处理的查询。我们对第一个查询类的结果将已知的不带自连接的联合查询的二分法扩展到带否定的这种查询。对于量化查询,它们的可跟踪性对最外层的投影运算符很敏感:如果没有表示集合标识符的属性被投影掉,它们是可处理的,否则是#P-hard。
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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来源期刊
ACM Transactions on Database Systems
ACM Transactions on Database Systems 工程技术-计算机:软件工程
CiteScore
5.60
自引率
0.00%
发文量
15
审稿时长
>12 weeks
期刊介绍: Heavily used in both academic and corporate R&D settings, ACM Transactions on Database Systems (TODS) is a key publication for computer scientists working in data abstraction, data modeling, and designing data management systems. Topics include storage and retrieval, transaction management, distributed and federated databases, semantics of data, intelligent databases, and operations and algorithms relating to these areas. In this rapidly changing field, TODS provides insights into the thoughts of the best minds in database R&D.
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