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 the problem: 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 postrelational 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.

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Query evaluation techniques for large databases

In this paper, a terminological framework is provided for describing different transactionoriented recovery schemes for database systems in a conceptual rather than an implementation-dependent way. By introducing the terms materialized database, propagation strategy, and checkpoint, we obtain a means for classifying arbitrary implementations from a unified viewpoint. This is complemented by a classification scheme for logging techniques, which are precisely defined by using the other terms. It is shown that these criteria are related to all relevant questions such as speed and scope of recovery and amount of redundant information required. The primary purpose of this paper, however, is to establish an adequate and precise terminology for a topic in which the confusion of concepts and implementational aspects still imposes a lot of problems.

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Principles of transaction-oriented database recovery

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 dependencies. The second part deals mainly with the representation and manipulation of deduced facts and incomplete information. Categories and Subject Descriptors: H.2.1 [Database Management]: Logical Design— data models; H.2.3 [Database Management]: Languages— query languages; H.2.4 [Database Management]: Systems— query processing General Terms: Deductive Databases, Indefinite Data, Logic and Databases, Null Values, Relational Databases

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Logic and Databases: A Deductive Approach

In this paper we present the data manipulation facility for a structured English query language (SEQUEL) which can be used for accessing data in an integrated relational data base. Without resorting to the concepts of bound variables and quantifiers SEQUEL identifies a set of simple operations on tabular structures, which can be shown to be of equivalent power to the first order predicate calculus. A SEQUEL user is presented with a consistent set of keyword English templates which reflect how people use tables to obtain information. Moreover, the SEQUEL user is able to compose these basic templates in a structured manner in order to form more complex queries. SEQUEL is intended as a data base sublanguage for both the professional programmer and the more infrequent data base user.

SEQUEL: A structured English query language

SEQUEL 2 is a relational data language that provides a consistent, English keyword-oriented set of facilities for query, data definition, data manipulation, and datac ontrol. SEQUEL 2 may be used either as a stand-alone interface for nonspecialists in data processing or as a data sublanguage embedded in a host programming language for use by application programmers and data base administrators. This paper describes SEQUEL 2 and the means by which it is coupled to a host language.

SEQUEL 2: a unified approach to data definition, manipulation, and control

System R, an experimental database system, was constructed to demonstrate that the usability advantages of the relational data model can be realized in a system with the complete function and high performance required for everyday production use. This paper describes the three principal phases of the System R project and discusses some of the lessons learned from System R about the design of relational systems and database systems in general.

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A history and evaluation of System R

This paper presents a data sublanguage called SQUARE, intended for use in ad hoc, interactive problem solving by non-computer specialists. SQUARE is based on the relational model of data, and is shown to be relationally complete; however, it avoids the quantifiers and bound variables required by languages based on the relational calculus. Facilities for query, insertion, deletion, and update on tabular data bases are described. A syntax is given, and suggestions are made for alternative syntaxes, including a syntax based on English key words for users with limited mathematical background.

Specifying queries as relational expressions: the SQUARE data sublanguage

A relational approach makes this experimental data base management system unusually easy to install and use. Some of the decisions made in System R design in order to enhance usability also offer major bonuses in other areas.

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W. Frank King

Papers

A history and evaluation of System R

Specifying queries as relational expressions: the SQUARE data sublanguage

System R: A Relational Data Base Management System