Won Kim

On optimizing an SQL-like nested query

SQL is a high-level nonprocedural data language which has received wide recognition in relational databases. One of the most interesting features of SQL is the nesting of query blocks to an arbitrary depth. An SQL-like query nested to an arbitrary depth is shown to be composed of five basic types of nesting. Four of them have not been well understood and more work needs to be done to improve their execution efficiency. Algorithms are developed that transform queries involving these basic types of nesting into semantically equivalent queries that are amenable to efficient processing by existing query-processing subsystems. These algorithms are then combined into a coherent strategy for processing a general nested query of arbitrary complexity.

A model of authorization for next-generation database systems

The conventional models of authorization have been designed for database systems supporting the hierarchical, network, and relational models of data. However, these models are not adequate for next-generation database systems that support richer data models that include object-oriented concepts and semantic data modeling concepts. Rabitti, Woelk, and Kim [14] presented a preliminary model of authorization for use as the basis of an authorization mechanism in such database systems. In this paper we present a fuller model of authorization that fills a few major gaps that the conventional models of authorization cannot fill for next-generation database systems. We also further formalize the notion of implicit authorization and refine the application of the notion of implicit authorization to object-oriented and semantic modeling concepts. We also describe a user interface for using the model of authorization and consider key issues in implementing the authorization model.

Modeling concepts for VLSI CAD objects

VLSI CAD applications deal with design objects that have an interface description and an implementation description. Versions of design objects have a common interface but differ in their implementations. A molecular object is a modeling construct which enables a database entity to be represented by two sets of heterogeneous records, one set describes the objects interface and the other describes its implementation. Thus a reasonable starting point for modeling design objects is to begin with the concept of molecular objects.nIn this paper, we identify modeling concepts that are fundamental to capturing the semantics of VLSI CAD design objects and versions in terms of molecular objects. A provisional set of user operations on design objects, consistent with these modeling concepts, is also defined. The modeling framework that we present has been found useful for investigating physical storage techniques and change notification problems in version control.

Indexing Techniques for Object-oriented Databases

Object Oriented Database systems (OODBs) need e cient indexing techniques just like other Database systems. However, B+-trees which work very well for Relational Database systems are not good enough for OODBs. Several alternate indexing techniques have been proposed, amongst them H-trees. This report analyses indexing techniques for OODBs, in particular H-trees.

Query Processing in Database Systems

Section I. Introduction to Query Processing.- to Query Processing.- Section II. Query Processing in Distributed Database Management Systems.- Query Processing in R.- Distributed Database Query Processing.- Processing Cyclic Queries.- Section III. Query Processing for Multiple Data Models.- Query Processing in a Multidatabase System.- Querying Relational Views of Networks.- Section IV. Database Updates through Views.- Updating Relational Views.- Section V. Database Access for Special Applications.- Supporting Complex Objects in a Relational System for Engineering Databases.- Database Access Requirements of Knowledge-Based Systems.- A Query Language for Statistical Databases.- Section VI. Techniques for Optimizing the Processing of Multiple Queries.- Common Subexpression Isolation in Multiple Query Optimization.- Global Optimization of Relational Queries: A First Step.- Query Processing Using the Consecutive Retrieval Property.- Section VII. Query Processing in Database Machines.- The Intelligent Database Machine (IDM).- Relational Query Processing on the NON-VON Supercomputer.- Section VIII. Physical Database Design.- Progress Toward Automating the Development of Database System Software.- Physical Database Design: Techniques for Improved Database Performance.- The Property of Separability and Its Application to Physical Database Design.- References.- List of Authors.

Highly available systems for database applications

As users entrust more and more of their applications to computersystems, the need for systems that are continuously operational (24hours per day) has become even greater. This paper presents asurvey and analysis of representative architectures and techniquesthat have been developed for constructing highly available systemsfor database applications. It then proposes a design of adistributed software subsystem that can serve as a unifiedframework for constructing database application systems that meetvarious requirements for high availability.

Supporting Complex Objects in a Relational System for Engineering Databases

Relational databases are of increasing interest for applications outside the traditional business data-processing environment. We have introduced the notion of complex objects as one extension to a relational database system (System R) to better support these non-business applications, in particular, engineering design. In this chapter, we discuss five aspects of complex objects: concepts and semantics, implementation, query optimization, efficient use within application programs, and user interface.

A parallel pipelined relational query processor

This paper presents the design of a relational query processor. The query processor consists of only four processing PIPEs and a number of random-access memory modules. Each PIPE processes tuples of relations in a bit-serial, tuple-parallel manner for each of the primitive database operations which comprise a complex relational query. The design of the query processor meets three major objectives: the query processor must be manufacturable using existing and near-term LSI (VLSI) technology; it must support in a uniform manner both the numeric and nonnumeric processing requirements a high-level user interface like SQL presents; and it must support the query-processing strategy derived in the query optimizer to satisfy certain system-wide performance optimality criteria.

A parallel pipelined relational query processor: An architectural overview

This paper outlines the overall architecture of a query processor for relational queries and describes the design and control of its major processing modules. The query processor consists of only four processing modules and a number of random-access memory modules. Each processing module processes tuples of relations in a bit-serial, tuple-parallel manner for each of the primitive database operations which comprise a complex relational query. The query processor is designed to be manufacturable using existing VLSI technology, and to support in a uniform manner both the numeric and nonnumeric processing requirements a high-level query language like SQL presents.