Abstract
Counting the answers to a query is a fundamental problem in databases, with several applications in the evaluation, optimization, and visualization of queries. Unfortunately, counting query answers is a #P-hard problem in most cases, so it is unlikely to be solvable in polynomial time. Recently, new results on approximate counting have been developed, specifically by showing that some problems in automata theory admit fully polynomial-time randomized approximation schemes. These results have several implications for the problem of counting the answers to a query; in particular, for graph and conjunctive queries. In this work, we present the main ideas of these approximation results, by using labeled DAGs instead of automata to simplify the presentation. In addition, we review how to apply these results to count query answers in different areas of databases.
Publisher
Association for Computing Machinery (ACM)
Subject
Information Systems,Software
Reference29 articles.
1. Connecting Knowledge Compilation Classes Width Parameters
2. R. Angles , M. Arenas , P. Barcel´o , A. Hogan , J. Reutter , and D. Vrgoc . Foundations of modern query languages for graph databases. ACM Computing Surveys (CSUR), 50(5):68 , 2017 . R. Angles, M. Arenas, P. Barcel´o, A. Hogan, J. Reutter, and D. Vrgoc. Foundations of modern query languages for graph databases. ACM Computing Surveys (CSUR), 50(5):68, 2017.
3. Counting beyond a Yottabyte, or how SPARQL 1.1 property paths will prevent adoption of the standard
4. #NFA Admits an FPRAS: Efficient Enumeration, Counting, and Uniform Generation for Logspace Classes
5. When is approximate counting for conjunctive queries tractable?