Efficient methods of processing unanticipated queries are a crucial prerequisite for the success of generalized database management systems. A wide variety of approaches to improve the performance of query evaluation algorithms have been proposed: logic-based and semantic transformations, fast implementations of basic operations, and combinatorial or heuristic algorithms for generating alternative access plans and choosing among them. These methods are presented in the framework of a general query evaluation procedure using the relational calculus representation of queries. In addition, nonstandard query optimization issues such as higher level query evaluation, query optimization in distributed databases, and use of database machines are addressed. The focus, however, is on query optimization in centralized database systems.

Some recently proposed extensions to relational database systems, as well as to deductive database systems, require support for multiple-query processing. For example, in a database system enhanced with inference capabilities, a simple query involving a rule with multiple definitions may expand to more than one actual query that has to be run over the database. It is an interesting problem then to come up with algorithms that process these queries together instead of one query at a time. The main motivation for performing such an interquery optimization lies in the fact that queries may share common data. We examine the problem of multiple-query optimization in this paper. The first major contribution of the paper is a systematic look at the problem, along with the presentation and analysis of algorithms that can be used for multiple-query optimization. The second contribution lies in the presentation of experimental results. Our results show that using multiple-query processing algorithms may reduce execution cost considerably.

The purpose of this paper is to show that logic provides a convenient formalism for studying classical database problems. There are two main parts to the paper, devoted respectively to conventional databases and deductive databases. In the first part, we focus on query languages, integrity modeling and maintenance, query optimization, and data

We consider a bottom-up query-evaluation scheme in which facts of relations are allowed to have nonground terms. The Magic Sets query-rewriting technique is generalized to allow arguments of predicates to be treated as bound even though the rules do not provide ground bindings for those arguments. In particular, we regard as "bound" any argument containing a function symbol or a variable that appears more than once in the argument list. Generalized "magic " predicates are thus defined to compute the set of all goals reached in a top-down exploration of the rules, starting from a given query goal; these goals are not facts of constants as in previous versions of the Magic Sets algorithm. The magic predicates are then used to restrict a bottom-up evaluation of the rules so that there are no redundant actions; that is, every step of the bottom-up computation must be performed by any algorithm that uses the same sideways information passing strategy (sips). The price paid, compared to prev...

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. At a workshop held in Toulouse, France in 1977, Gallaire, Minker and Nicolas stated that logic and databases was a field in its own right (see [131]). This was the first time that this designation was made. The impetus for this started approximately twenty years ago in 1976 when I visited Gallaire and Nicolas in Toulouse, France, which culminated in a workshop held in Toulouse, France in 1977. It is appropriate, then to provide an assessment as to what has been achieved in the twenty years since the field started as a distinct discipline. In this retrospective I shall review developments that have taken place in the field, assess the contributions that have been made, consider the status of implementations of deductive databases and discuss the future of work in this area. 1 Introduction As described in [234], the use of logic and deduction in databases started in the late 1960s. Prominent among the developments was the work by Levien and Maron [202, 203, 199, 200, 201] and Kuhns [1...

We define the magic-sets transformation for traditional relational systems (with duplicates, aggregation and grouping), as well as for relational systems extended with recursion. We compare the magic-sets rewriting to traditional optimization techniques for nonrecursive queries, and use performance experiments to argue that the magic-sets transformation is often a better optimization technique. 1 Introduction "Magic-sets" is the name of a query transformation algorithm ([BMSU86]) (and now a class of algorithms Part of this work was done at the IBM Almaden Research Center. Work at Stanford was supported by an NSF grant IRI87 -22886, an Air Force grant AFOSR-88-0266, and a grant of IBM Corporation. y Author's current affiliation: Tandem Computers. z Part of this work was done while the author was visiting IBM Almaden Research Center. Work at Wisconsin was supported by an IBM Faculty Development Award and an NSF grant IRI-8804319. --- Generalized Magic-sets of [BR87], Magic Tem...

An optimizing translation mechanism for the dynamic interaction between a logic-based expert system written in PROLOG and a re-lational database accessible through SQL is presented. The mechanism makes use of an intermediate language that decomposes the optimization problem and makes the proposed approach target-language independent. It can either facilitate expert system-database interaction, e.g., when integrating expert systems into business systems, or augment existing database with (external) deductive capabilities.

How to decrease labor and improve reliability in the development of efficient implementations of nonnumerical algorithms and labor intensive software is an increasingly important problem as the demand for computer technology shifts from easier applications to more complex algorithmic ones; e.g., optimizing compilers for supercomputers, intricate data structures to implement efficient solutions to operations research problems, search and analysis algorithms in genetic engineering, complex software tools for workstations, design automation, etc. It is also a difficult problem that is not solved by current CASE tools and software management disciplines, which are oriented towards data processing and other applications, where the implementation and a prediction of its resource utilization follow more directly from the specification. Recently, Cai and Paige reported experiments suggesting a way to implement nonnumerical algorithms in C at a programming rate (i.e., source lines per second) t...

This paper treats the problem of implementing efficiently recursive Horn Clauses queries, including those with function symbols. In particular, the situation is studied where the initial bindings of the arguments in the recursire query goal can be used in the top-down (as in backward chaining) execution phase to improve the efficiency and, often, to guarantee the termination, of the forward chaining execution phase that implements the fixpoint computation for the recursire query. A general method is given for solving these queries; the method performs an analysis of the binding passing behavior of the query, and then reschedules the overall execution as two fixpoint computations derived as results of this analysis. The first such computation emulates the propagation of bindings in the top-down phase; the second generates the desired answer by proving the goals left unsolved during the previous step. Finally, sufficient conditions for safety are derived, to ensure that the fixpoint computations are completed in a finite number of steps.