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.

Query Processing in Database Systems

Modeling the storage structures of a DBMS is a prerequisite to understanding and optimizing database performance. Previously, such modeling was very difficult because the fundamental role of conceptual-to-internal mappings in DBMS implementations went unrecognized.In this paper we present a model of physical databases, called the transformation model, that makes conceptual-to-internal mappings explicit. By exposing such mappings, we show that it is possible to model the storage architectures (i.e., the storage structures and mappings) of many commercial DBMSs in a precise, systematic, and comprehendible way. Models of the INQUIRE, ADABAS, and SYSTEM 2000 storage architectures are presented as examples of the model's utility.We believe the transformation model helps bridge the gap between physical database theory and practice. It also reveals the possibility of a technology to automate the development of physical database software.

Modeling the storage architectures of commercial database systems

A theoretical approach to the optimal design of a large multifile physical database is presented. The design algorithm is based on the theory that, given a set of join methods that satisfy a certain property called separability, the problem of optimal assignment of access structures to the whole database can be reduced to the subproblem of optimizing individual relations independently of one another. Coupling factors are defined to represent all the interactions among the relations. This approach not only reduces the complexity of the problem significantly, but also provides a better understanding of underlying mechanisms.

Separability &#8212;An Approach to Physical Database Design

The Logical Record Access Approach to Database Design

A theoretical approach to the optimal design of a large multifile physical databases is presented. The design algorithm is based on the theory that given a set of join methods that satisfy a certain property called separability, the problem of optimal assignment of access structures to the whole database can be reduced to the subproblem of optimizing individual relations independently of one another. Coupling factors are defined to represent all the interactions among the relations. This approach not only reduces the complexity of the problem significantly, but also provides a better understanding of underlying mechanisms.

Separability - an approach to physical data base design

The task of physical data base design in an DBTG enviornment is examined. Generation of an internal schema which considers questions of storage versus access costs, efficient implementation of data relationships, efficient placement of data within the data base and allocation of primary and secondary storage is shown to be a formidable task.

Current data base design aids are reviewed. One aid, a sophisicated mathematical model of DBTG data bases (Gerritsen 1977) is shown to be a potentially valuable tool. A limitation of this model is that no optimization algorithm other than total enumeration has been found.

This paper proposes an implementation of the Gerritsen model. An interactive design tool, based upon the Gerritsen model, is discussed. A Data Base Design Decision Support System (DBD-DSS) for use by the DBA is developed. The objectives and structure of the DBD-DSS are examined. A comprehensive example illustrating both the user interface and the potential benefits of the interactive tool is presented.

A data base design decision support system

Conceptual and internal schemas in CODASYL

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Rob Gerritsen

Author Tools

Chat about Author

Papers

A data base design decision support system

Conceptual and internal schemas in CODASYL