Classification and compilation of linear recursive queries in deductive databases (original) (raw)

On semantic query optimization in deductive databases

[1992] Eighth International Conference on Data Engineering, 1992

The focus of this paper is semantic query optimization in the presence of integrity constraints (ICs) such as inclusion dependencies (INDs) and context dependencies (CDs). INDs are well known to arise naturally in many applications. CDs, introduced earlier in a di erent context, can capture natural semantic constraints that cannot be expressed using INDs. Besides, some CDs can also be inferred from given INDs, and further have the advantage of being more directly geared toward semantic query optimization than INDs. We provide an inference mechanism for reasoning with CDs and develop e cient algorithms for semantic query optimization using them. The contributions of this paper are su cient conditions and algorithms for the detection of redundant atoms and rules in a class of linear recursive programs, arising in deductive databases. We take a program transformation approach to semantic query optimization. As a consequence, our approach has the following advantages: (i) our technique is independent of the query processing paradigm used { it may be top-down or bottom-up; (ii) the method is independent of a particular binding pattern of the query or even of the query predicate; and (iii) since optimization is done statically in one shot, our method does not incur run-time overheads such as maintenance of the query subexpressions processed in a loop of the bottom-up evaluation. Our results and techniques apply to conventional relational queries as well as (recursive) queries arising in deductive databases.

Recursive query processing using graph traversal techniques

Proceedings of the fifth international conference on …, 1996

This paper presents STARBASE, n new algorithm for recursive querypmcessittgondeductivedatabasesbaaedon the Chart Parsing algorithm. It is distinct from the other applicationsof parsing to deduction, namely Eartey Deduction and Ftoaenblueth's method, because it removes variabtes fmm literals snd extends the Chart Parsingengine to handte all possible variations in the pattern of arguments in the titerals of deduction rules. Like other tabling methods, STARBASE avoids redundant computation by storing and reusing partial results bu~in contrast with tbetw it does not depend on subsumption and uses syntactic equality checking, instead. Because STARBASE takes a skmgly graph-oriented view of both the database and the deduction tules, the evaluation of a query on a database can be viewed as a process of traversing paths in the graph representing the database.

Experimenting with recursive queries in database and logic programming systems

2008

This paper considers the problem of reasoning on massive amounts of (possibly distributed) data. Presently, existing proposals show some limitations: (i) the quantity of data that can be handled contemporarily is limited, due to the fact that reasoning is generally carried out in main-memory; (ii) the interaction with external (and independent) DBMSs is not trivial and, in several cases, not allowed at all; (iii) the efficiency of present implementations is still not sufficient for their utilization in complex reasoning tasks involving massive amounts of data. This paper provides a contribution in this setting; it presents a new system, called DLV DB , which aims to solve these problems. Moreover, the paper reports the results of a thorough experimental analysis we have carried out for comparing our system with several state-of-the-art systems (both logic and databases) on some classical deductive problems; the other tested systems are: LDL++, XSB, Smodels and three toplevel commercial DBMSs. DLV DB significantly outperforms even the commercial Database Systems on recursive queries.

Towards Bridging the Expressiveness Gap Between Relational and Deductive Databases

2013

SQL technology has evolved during last years, and systems are being more powerful and scalable. However, there exist yet some expressiveness limitations that can be otherwise overcome with inputs from deductive databases. This paper focuses on both practical and theoretical expressiveness issues in current SQL implementations that are overcome in the Datalog Educational System (DES), a deductive system which also includes extended SQL queries with respect to the SQL standard and current DBMS’s. Also, as external database access and interoperability are allowed in DES, results from the deductive field can be tested on current DBMS’s. For instance: Less-limited SQL formulations as non-linear recursive queries, novel features as hypothetical queries, and other query languages as Datalog and Extended Relational Algebra. In addition, some notes on performance are taken.

Evaluation of database recursive logic programs as recurrent function series

ACM SIGMOD Record, 1986

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.

A Framework for an Ecien t Implementation of Deductive Databases

We describe a method for query evaluation in deductive databases which is based on dynamic ltering of data o w. The basic query evaluation strategy is bottom-up and set-oriented. The method imposes no restrictions on the form of Horn axioms, takes advantage of actually stored data, allows compile time preprocessing, and is well suited for parallel and distributed execution.

A Practical Algorithm for Reformulation of Deductive Databases

2018

Database Reformulation is the process of rewriting the data and rules in deductive databases in a functionally equivalent manner, ideally in ways that decrease query processing time while keeping storage costs within acceptable bounds. Early research in this area focussed on materializing existing views, i.e. caching those views as data. Subsequent research investigated the problem of inventing new views to afford different opportunities for materialization. The Bounding Theorem, introduced in this latter effort, is significant in that it gives a finite bound on the number of useful reformulations for conjunctive queries. Unfortunately, the number of possibilities allowed by the Bounding Theorem is doubly exponential in the size of the query (not the database instance). In this paper, we show that we can reduce that double exponential to a single exponential. We first present an improved version of the Bounding Theorem, called the Subgoal Theorem. We then present an additional resul...

Query Evaluation in Deductive Databases

1990

Abstract It is desirable to answer queries posed to deductive databases by computing fixpoints because such computations are directly amenable to set-oriented fact processing. However, the classical fixpoint procedures based on bottom-up processing—the naive and semi-naive methods—are rather primitive and often inefficient.