2010Unpublished venueRequires access

Precise complexity analysis for efficient datalog queries

K. Tuncay Tekle, Yanhong A. Liu

Open publisher page 17 citations

Abstract

Given a set of Datalog rules, facts, and a query, answers to the query can be inferred bottom-up starting with the facts or top-down starting with the query. For efficiently answering the query, top-down evaluation is extended with tabling that stores the results of the subqueries encountered, and bottom-up evaluation is done on rules transformed based on demand from the query.

About this research paper

What this paper is about

Given a set of Datalog rules, facts, and a query, answers to the query can be inferred bottom-up starting with the facts or top-down starting with the query. For efficiently answering the query, top-down evaluation is extended with tabling that stores the results of the subqueries encountered, and bottom-up evaluation is done on rules transformed based on demand from the query.

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OpenAlex reports 17 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

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Method / approach

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Available abstract

Given a set of Datalog rules, facts, and a query, answers to the query can be inferred bottom-up starting with the facts or top-down starting with the query. For efficiently answering the query, top-down evaluation is extended with tabling that stores the results of the subqueries encountered, and bottom-up evaluation is done on rules transformed based on demand from the query.

Key concepts: Datalog, Computer science, Query language, Query optimization, Sargable, Set (abstract data type), Deductive database, Conjunctive query

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