Database management systems will continue to manage large data volumes. Thus, efficient algorithms for accessing and manipulating large sets and sequences will be required to provide acceptable performance. The advent of object-oriented and extensible database systems will not solve this problem. On the contrary, modern data models exacerbate it: In order to manipulate large sets of complex objects as efficiently as today’s database systems manipulate simple records, query processing algorithms and software will become more complex, and a solid understanding of algorithm and architectural issues is essential for the designer of database management software. This survey provides a foundation for the design and implementation of query execution facilities in new database management systems. It describes a wide array of practical query evaluation techniques for both relational and post-relational database systems, including iterative execution of complex query evaluation plans, the duality of sort- and hash-based set matching algorithms, types of parallel query execution and their implementation, and special operators for emerging database application domains.

CLASSIC is a data model that encourages the description ofobjects not only in terms of their relations to other known objects, but in terms of a level of intensional structure as well. The CLASSIC language of structured descriptions permits i) partial descriptions of individuals, under an `open world' assumption, ii) answers to queries either as extensional lists of valuesorasdescriptions that necessarily hold of all possible answers, and iii) an easily extensible schema, which can be accessed uniformly with the data. One of the strengths of the approach is that the same language plays multiple roles in the processes of defining and populating the DB, as well as querying and answering. classic (for which we have a prototype main-memory implementation) can actively discover new information about objects from several sources: it can recognize new classes under which an object falls based on a description of the object, it can propagate some deductive consequences of DB upda...

This paper describes a language that is intended to support software engineers in the development of information systems throughout the software lifecycle. This language is not a programming language. Following the example of a number of other software engineering projects, our work is based on the premise that information system development is knowledge-intensive and that the primary responsibility of any language intended to support this task is to be able to formally represent the relevant knowledge.

Knowledge discovery in databases, or data mining, is an important issue in the development of data- and knowledge-base systems. An attribute-oriented induction method has been developed for knowledge discovery in databases. The method integrates a machine learning paradigm, especially learning-from-examples techniques, with set-oriented database operations and extracts generalized data from actual data in databases. An attribute-oriented concept tree ascension technique is applied in generalization, which substantially reduces the computational complexity of database learning processes. Different kinds of knowledge rules, including characteristic rules, discrimination rules, quantitative rules, and data evolution regularities can be discovered efficiently using the attribute-oriented approach. In addition to learning in relational databases, the approach can be applied to knowledge discovery in nested relational and deductive databases. Learning can also be performed with databases containing noisy data and exceptional cases using database statistics. Furthermore, the rules discovered can be used to query database knowledge, answer cooperative queries and facilitate semantic query optimization. Based upon these principles, a prototyped database learning system, DBLEARN, has been constructed for experimentation.

: We present an efficient implementation method for temporal integrity constraints formulated in Past Temporal Logic. Although the constraints can refer to past states of the database, their checking does not require that the entire database history be stored. Instead, every database state is extended with auxiliary relations that contain the historical information necessary for checking constraints. Auxiliary relations can be implemented as materialized relational views. 1 Introduction Integrity constraints form an essential part of every database application. It is customary to distinguish between two kinds of constraints: static and temporal (or dynamic). Static constraints refer to the current state of the database, e.g.,"every manager is also an employee ", while temporal constraints may refer to past and future states in addition to the current state, e.g., "salaries of employees should never decrease" or "once a student drops out of the Ph.D. program, she should not be readmit...

We survey a number of approaches to the problem of finite representation of infinite temporal extensions. Two of them, Datalog 1S and Templog, are syntactical extensions of Datalog; the third is based on repetition and arithmetic constraints. We provide precise characterizations of the expressiveness and the computational complexity of these languages. We also describe query evaluation methods.

A language for databases with sets, tuples, lists, object identity and structural inheritance is proposed. The core language is logic-based with a fixpoint semantics. Methods with overloading and methods evaluated externally providing extensibility of the language are considered. Other important issues such as updates and the introduction of explicit control are discussed. 1 INTRODUCTION The success of the relational database model [19, 38, 27] is certainly due to technological advances such as fast query processing or reliable concurrency control. However, we believe that a major factor in that success has been the existence of simple-to-use languages allowing the definition and manipulation of data. This has to be remembered while considering future generations of database systems. Object-oriented database systems are now being developed, e.g., [15, 12, 22, 39, 36]. An object-oriented approach [24] is used to answer the needs of a much wider variety of applications. Most of th...

One of the most important and difficult problems in logic programming is the problem of finding a suitable declarative or intended semantics for logic programs. The importance of this problem stems from the declarative character of logic programming, whereas its difficulty can be largely attributed to the non-monotonic character of the negation operator used in logic programs. The problem can therefore be viewed as the problem of finding a suitable formalization of the type of non-monotonic reasoning used in logic programming. In this paper we introduce a semantics of logic programs based on the class PERF(P) of all, not necessarily Herbrand, perfect models of a program P and we show that the proposed semantics is not only natural but it also combines many of the desirable features of previous approaches, at the same time eliminating some of their drawbacks. For a positive program P, the class PERF(P) of perfect models coincides with the class MIN(P) of all minimal models of P. The per...

Background material is presented on deductive and normal deductive databases. A historical review is presented of work in disjunctive deductive databases, starting from 1982. The semantics of alternative classes of disjunctive databases is reviewed with their model and fixpoint characterizations. Algorithms are developed to compute answers to queries in the alternative theories using the concept of a model tree. Open problems in this area are discussed.

this paper. In particular, the paper reports on a very significant progress made recently in this area. It also presents some results which have not yet appeared in print. The paper is organized as follows. In the next two sections we define deductive databases and logic programs. Subsequently, in Sections 4 and 5, we discuss model theory and fixed points, which play a crucial role in the definition of semantics. Section 6 is the main section of the paper and is entirely devoted to a systematic exposition and comparison of various proposed semantics. In Section 7 we discuss the relationship between declarative semantics of deductive databases and logic programs and non-monotonic reasoning. Section 8 contains concluding remarks. 2 Deductive Databases