Bag Query Containment and Information Theory

Author:

Khamis Mahmoud Abo1,Kolaitis Phokion G.2,Ngo Hung Q.1,Suciu Dan3

Affiliation:

1. relationalAI, Berkeley, USA

2. University of California, Santa Cruz, USA

3. University of Washington, WA, USA

Abstract

The query containment problem is a fundamental algorithmic problem in data management. While this problem is well understood under set semantics, it is by far less understood under bag semantics. In particular, it is a long-standing open question whether or not the conjunctive query containment problem under bag semantics is decidable. We unveil tight connections between information theory and the conjunctive query containment under bag semantics. These connections are established using information inequalities, which are considered to be the laws of information theory. Our first main result asserts that deciding the validity of a generalization of information inequalities is many-one equivalent to the restricted case of conjunctive query containment in which the containing query is acyclic; thus, either both these problems are decidable or both are undecidable. Our second main result identifies a new decidable case of the conjunctive query containment problem under bag semantics. Specifically, we give an exponential-time algorithm for conjunctive query containment under bag semantics, provided the containing query is chordal and admits a simple junction tree.

Funder

NSF

Publisher

Association for Computing Machinery (ACM)

Subject

Information Systems

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