Proceedings of the 12th International ACM SIGPLAN Symposium on Principles and Practice of Declarative Programming 2010
DOI: 10.1145/1836089.1836095
|View full text |Cite
|
Sign up to set email alerts
|

Deriving predicate statistics in datalog

Abstract: Database query optimizers rely on data statistics in selecting query execution plans. Similar query optimization techniques are desirable for deductive databases and, to make this happen, we need to be able to collect data statistics for Datalog predicates. The difficulty is, however, that Datalog predicates can be recursive. In this paper, we propose an algorithm, called SDP, that estimates Datalog query sizes efficiently by maintaining the statistical dependency information for derived predicates. Base predi… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2010
2010
2012
2012

Publication Types

Select...
2
1
1

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(1 citation statement)
references
References 19 publications
0
1
0
Order By: Relevance
“…However, comparison of complexity formulas may be difficult in general, in which case estimations of size parameters [20] can be used to help. Future work includes study of powerful methods for automatically simplifying complexity formulas, for estimating values of size parameters, and for using our method for optimizations.…”
Section: Related Work and Conclusionmentioning
confidence: 99%
“…However, comparison of complexity formulas may be difficult in general, in which case estimations of size parameters [20] can be used to help. Future work includes study of powerful methods for automatically simplifying complexity formulas, for estimating values of size parameters, and for using our method for optimizations.…”
Section: Related Work and Conclusionmentioning
confidence: 99%