Query evaluation in probabilistic relational databases

Query Evaluation in Probabilistic Relational Databases

This paper describes a generalization of the relational model in order to capture and manipulate a type of probabilistic information. Probabilistic databases are formalized by means of logic theories based on a probabilistic first-order language proposed by Halpern. A sound a complete method is described for evaluating queries in probabilistic theories. The generalization proposed can be incorp...

Relational Databases Query Optimization using Hybrid Evolutionary Algorithm

Optimizing the database queries is one of hard research problems. Exhaustive search techniques like dynamic programming is suitable for queries with a few relations, but by increasing the number of relations in query, much use of memory and processing is needed, and the use of these methods is not suitable, so we have to use random and evolutionary methods. The use of evolutionary methods, beca...

Query Evaluation on Probabilistic Databases

In this paper we consider the query evaluation problem: how can we evaluate SQL queries on probabilistic databases? Our discussion is restricted to single-block SQL queries using standard syntax, with a modified semantics: each tuple in the answer is associated with a probability representing our confidence in that tuple belonging to the answer. We present here a short summary of the research d...

Scalable Query Evaluation in Relational Databases

The scalability of a query depends on the amount of data that needs to be accessed when computing the answer. This implies three immediate general strategies for improving query performance: decrease the amount of data (including intermediate results) to be accessed by accessing it smarter; decrease the amount by simply reducing the data quantity in the first place; and increase the amount of d...

Query Evaluation for Distributed Heterogeneous Relational Databases