AbstractThis paper presents several complementary methods for the parallel, bottom-up evaluation of Datalog queries. We introduce the notion of a discriminating predicate, based on hash functions, that partitions the computation between the processors in order to achieve parallelism. A parallelization scheme with the property of nonredundant computation (no duplication of computation by processors) is then studied in detail. The mapping of Datalog programs onto a network of processors, such that the result is a nonredundant computation, is also studied
In the current work, we derive a complete approach to optimization and automatic parallelization of ...
Delivering superior expressive power over RDBMS, while maintaining competitive per-formance, has rep...
AbstractWe consider logic programs without function symbols, called Datalog programs, and study thei...
AbstractThis paper presents several complementary methods for the parallel, bottom-up evaluation of ...
AbstractWe propose a method of parallelizing the evaluation of data-intensive Datalog programs. The ...
We propose a method of parallelizing the evaluation of data-intensive Dalalog programs. The method i...
This paper is concerned with the parallel evaluation of datalog rule programs, mainly by processors ...
Modern data management systems extensively use parallelism to speed up query processing over massive...
An important feature of database technology of the nineties is the use of parallelism for speeding u...
AbstractWe address the problem of parallelizing the evaluation of logic programs in data intensive a...
The increasing available parallelism of computers demands new programming languages that make parall...
There is a tension between the objectives of avoiding irrelevant computation and extracting parallel...
Recently, Ketsman et al. started the investigation of the parallel evaluation of recursive queries i...
Abstract. The increasing available parallelism of computers demands new programming languages that m...
AbstractWe explore an approach to developing Datalog parallelization strategies that aims at good ex...
In the current work, we derive a complete approach to optimization and automatic parallelization of ...
Delivering superior expressive power over RDBMS, while maintaining competitive per-formance, has rep...
AbstractWe consider logic programs without function symbols, called Datalog programs, and study thei...
AbstractThis paper presents several complementary methods for the parallel, bottom-up evaluation of ...
AbstractWe propose a method of parallelizing the evaluation of data-intensive Datalog programs. The ...
We propose a method of parallelizing the evaluation of data-intensive Dalalog programs. The method i...
This paper is concerned with the parallel evaluation of datalog rule programs, mainly by processors ...
Modern data management systems extensively use parallelism to speed up query processing over massive...
An important feature of database technology of the nineties is the use of parallelism for speeding u...
AbstractWe address the problem of parallelizing the evaluation of logic programs in data intensive a...
The increasing available parallelism of computers demands new programming languages that make parall...
There is a tension between the objectives of avoiding irrelevant computation and extracting parallel...
Recently, Ketsman et al. started the investigation of the parallel evaluation of recursive queries i...
Abstract. The increasing available parallelism of computers demands new programming languages that m...
AbstractWe explore an approach to developing Datalog parallelization strategies that aims at good ex...
In the current work, we derive a complete approach to optimization and automatic parallelization of ...
Delivering superior expressive power over RDBMS, while maintaining competitive per-formance, has rep...
AbstractWe consider logic programs without function symbols, called Datalog programs, and study thei...