The design and the implementation of a rule database language (RDL) compiler is presented. In this design, the RDL/C language supports both declarative programming based on a production rule language and C-based procedural programming. The data model is relational. This implies that all rule programs can be solved without having to download data from the database management system (DBMS) into some working memory. The language supports domain variables which can appear in rules. These variables are monitored by the inference engine and included in the semantics of rule firing. A partial ordering among rules is available to the user. The RDL/C compiler translates RDL/C source code into C code with embedded structured query language (SQL) statements. Its implementation is compared to fully integrated deductive databases and to loosely coupled systems. It is shown how the rule-based paradigm for a database can be used as a framework for a general-purpose database application generator.>

Deductive databases provide a formal framework to study rule-based query languages that are extensions of first-order logic. However, deductive database languages and their current implementations do not seem appropriate for improving the development of real applications or even sample of them. Our goal is to make deductive database technology practical. The design and implementation of the RDL1 system, presented in this paper, constitute a step toward this goal. Our approach is based on the integration of a production rule language within a relational database system, the development of a rule-based programming environment and the support of system extensibility using Abstract Data Types. We discuss important practical experience gained during the implementation of the system. Also, comparisons with related work such as LDL, STARBURST and POSTGRES are given.

A method is proposed to store and efficiently retrieve rules in a deductive database. The rules are compiled into an execution model called a PCN (production compilation network). The PCN is stored as a particular relational database which consists of three relations. For a given end-user query the first step of the inference process consists of searching for the relevant rules by traversing the PCN structure. This traversal is computed by a transitive closure of a part of the PCN. The transitive closure is performed by a loop of joins over the relations storing the PCN. In this context, a transitive closure algorithm that is based on a physical clustering of the relations is proposed. This clustering consists of a double hashing technique. It ensures a linear cost for the join operation with weak conditions on the size of the main memory. The approach reduces the number of I/O operations for semi-naive transitive closure operation. This algorithm will be applied to the search for relevant rules and to the transitive computation of linear recursive relations.>

The authors consider the problem of integrating a powerful production rule language, called RDLI, with a relational DBMS. A rule in RDLI is composed of a condition part which is a relational calculus expression and an action part which is a sequence of updates over a database. The semantics of a RDLI rule is presented according to a binary relation over databases states. Then, they introduce a general compilation technique for transforming producing rules in an execution model, the PCN, based on predicate transition networks (PrTN). The features of this model are its descriptive power and its query optimization support.>

The authors introduce a new method to compile queries referencing recursively defined predicates. This method is based on an interpretation of the query and the relations as functions which map one column of a relation to another column. It is shown that a large class of queries with associated recursive rules, including mutually recursive rules, can be computed as the limit of a series of functions. Typical cases of series of functions are given and solved. The solutions lend themselves towards either extended relational algebra or SQL optimized programs to compute the recursive query answers. Examples of applications are given.