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.

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.

This paper presents the design and an initial performance evaluation of the query optimizer generator designed for the EXODUS extensible database system. Algebraic transformation rules are translated into an executable query optimizer, which transforms query trees and selects methods for executing operations according to cost functions associated with the methods. The search strategy avoids exhaustive search and it modifies itself to take advantage of past experience. Computational results show that an optimizer generated for a relational system produces access plans almost as good as those produced by exhaustive search, with the search time cut to a small fraction.

System R is a database management system which provides a high level relational data interface. The system provides a high level of data independence by isolating the end user as much as possible from underlying storage structures. The system permits definition of a variety of relational views on common underlying data. Data control features are provided, including authorization, integrity assertions, triggered transactions, a logging and recovery subsystem, and facilities for maintaining data consistency in a shared-update environment. This paper contains a description of the overall architecture and design of the system. At the present time the system is being implemented and the design evaluated. We emphasize that System R is a vehicle for research in database architecture, and is not planned as a product.

ABSTRACT. The semi-join is a relational algebraic operation that selects a set of tuples in one relation that match one or more tuples of another relation on the joining domains. Semi-joins have been used as a basic ingredient in query processing strategies for a number of hardware and software database systems. However, not all queries can be solved entirely using semi-joins. In this paper the exact class of relational queries that can be solved using semi-joins is shown. It is also shown that queries outside of this class may not even be partially solvable using "short " semi-join programs. In addition, a linear-time membership test for this class is presented.

Strategy for processing multivariable queries in the database management system INGRES is considered. The general procedure is to decompose the query into a sequence of one-variable queries by alternating between (a) reduction: breaking off components of the query which are joined to it by a single variable, and (b) tuple substitution: substituting for one of the variables a tuple at a time. Algorithms for reduction and for choosing the variable to be substituted are given. In most cases the latter decision depends on estimation of costs; heuristic procedures for making such estimates are outlined.

The relational algebra is a procedural query language for relational databases. In this paper we survey extensions of the relational algebra that can query databases recording time-varying data. Such an algebra is a critical part of a temporal DBMS. We identify 26 criteria that provide an objective basis for evaluating temporal algebras, Seven of the criteria are shown to be mutually unsatisfiable, implying there can be no perfect temporal algebra, Choices made as to which of the incompatible criteria are satisfied characterize existing algebras Twelve time-oriented algebras are summarized and then evaluated against the criteria. We demonstrate that the design space has in some sense been explored in that all combinations of basic design decisions have at least one representative algebra. Coverage of the remaining criteria provides one measure of the quality of each algebra We argue that all of the criteria are independent and that the criteria identified as compatible are indeed so, Finally, we list plausible properties proposed by others that are either subsumed by other criteria, are not well defined, or have no objective basis for being evaluated. The algebras realize many different approaches to what appears initially to be a straightforward design task.

We present techniques for optimizing queries in memory-resident database systems. Optimization techniques in memory-resident database systems differ significantly from those in conventional disk-resident database systems. In this paper we address the following aspects of query optimization in such systems and present specific solutions for them: (1) a new approach to developing a CPU-intensive cost model; (2) new optimization strategies for main-memory query processing; (3) new insight into join algorithms and access structures that take advantage of memory residency of data; and (4) the effect of the operating system’s scheduling algorithm on the memory-residency assumption. We present an interesting result that a major cost of processing queries in memory-resident database systems is incurred by evaluation of predicates. We discuss optimization techniques using the Office-by-Example (OBE) that has been under development at IBM Research. We also present the results of performance measurements, which prove to be excellent in the current state of the art. Despite recent work on memory-resident database systems, query optimization aspects in these systems have not been well studied. We believe this paper opens the issues of query optimization in memory-resident database systems and presents practical solutions to them.

The task of increasing the efficiency of database queries has recieved considerable attention. In this paper we describe the improvement of queries expressed as list comprehensions in a lazy functional language. The database literature identifies four algebraic and two implementation-based improvement strategies. For each strategy we show an equivalent improvement for queries expressed as list comprehensions. This means that welldeveloped database algorithms that improve queries using several of these strategies can be emulated to improve comprehension queries. We are also able to improve queries which require greater power than that provided by the relational algebra. Most of the improvements entail transforming a simple, inefficient query into a more complex, but more efficient form. We illustrate each improvement using examples drawn from the database literature. 1 Introduction The functional programming community is often accused of being too inward looking. Functional languages a...

In this thesis we address the problem of providing efficient processing of queries in the extensible environment induced by object-oriented databases. We define a framework for query processing in an object-oriented database and develop designs for major components of this framework. The framework encompasses an object-oriented data model, an algebra to query over that model, transformation rules for the algebra, an internal representation for queries expressed in the algebra, a cost model for analyzing query expressions, and an architecture for an extensible query optimizer. The major contributions of this thesis are an algebra and transformation rules, a representation, and an architecture for extensible query optimization. We show how these components fit into the framework and interact with each other. The EQUAL query algebra presented in this thesis is the first query algebra for object-oriented database systems to be completely consistent with data abstraction, and one of the few...